content
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|---|---|---|---|
# io/z-list.jl
include("caller_name.jl")
include("fld-read.jl")
include("fld-write.jl")
include("ir_dump.jl")
include("prompt.jl")
include("shows.jl")
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export RadialMap, evaluate!, evaluate, SparseRadialMap
import Base: size, show
#### Structure for the lower triangular map M
struct RadialMap
Nx::Int64
p::Int64
L::LinearTransform
C::Array{RadialMapComponent, 1}
# Optimization parameters
γ::Float64
λ::Float64
δ::Float64
κ::Float64
end
function RadialMap(Nx::Int64, p::Int64; γ::Float64=2.0, λ::Float64=0.1, δ::Float64=1e-8, κ::Float64=10.0)
C = RadialMapComponent[]
@inbounds for i=1:Nx
push!(C, RadialMapComponent(i,p))
end
return RadialMap(Nx, p, LinearTransform(Nx), C, γ, λ, δ, κ)
end
function RadialMap(X::Array{Float64,2}, p::Int64; γ::Float64=2.0, λ::Float64=0.1, δ::Float64=1e-8, κ::Float64=10.0)
L = LinearTransform(X; diag = true)
Nx, Ne = size(X)
C = RadialMapComponent[]
@inbounds for i=1:Nx
push!(C, RadialMapComponent(i,p))
end
return RadialMap(Nx, p, LinearTransform(Nx), C, γ, λ, δ, κ)
end
function Base.show(io::IO, M::RadialMap)
println(io,"Radial Map of dimension Nx = $(M.Nx) and order p = $(M.p)
with parameters (γ, λ, δ, κ) = ($(M.γ), $(M.λ), $(M.δ), $(M.κ))")
end
@propagate_inbounds Base.getindex(M::RadialMap, i::Int) = getindex(M.C,i)
@propagate_inbounds Base.setindex!(M::RadialMap, C::RadialMapComponent, i::Int) = setindex!(M.C,C,i)
size(M::RadialMap) = (M.Nx, M.p)
# Evaluate the map RadialMapComponent at z = (z1,...,zNx)
function evaluate!(out, M::RadialMap, z::AbstractVector{Float64}; apply_rescaling::Bool=true, start::Int64=1)
Nx = M.Nx
@assert Nx == size(z,1) "Incorrect length of the input vector"
# We can apply the rescaling to all the components once
if apply_rescaling == true
transform!(M.L, z)
end
@inbounds for i=start:Nx
out[i] = M.C[i](view(z,1:i))
end
if apply_rescaling == true
itransform!(M.L, z)
end
return out
end
evaluate(M::RadialMap, z::AbstractVector{Float64}; apply_rescaling::Bool=true, start::Int64=1) = evaluate!(zeros(M.Nx-start+1), M, z; apply_rescaling = apply_rescaling, start = start)
(M::RadialMap)(z::AbstractVector{Float64}; apply_rescaling::Bool=true, start::Int64=1) = evaluate(M, z; apply_rescaling = apply_rescaling, start = start)
# Evaluate in-place the RadialMap `M`
function evaluate!(out, M::RadialMap, X::AbstractMatrix{Float64}; apply_rescaling::Bool=true, start::Int64=1)
@get M (Nx, p)
NxX, Ne = size(X)
@assert NxX == Nx "Wrong dimension of the ensemble matrix `X`"
if apply_rescaling == true
transform!(M.L, X)
end
@inbounds Threads.@threads for i=1:Ne
col = view(X,:,i)
evaluate!(view(out,:,i), M, col; apply_rescaling = false, start =start)
# out[:,i] .= M(col, start=start)
end
if apply_rescaling == true
itransform!(M.L, X)
end
return out
end
evaluate(M::RadialMap, X::AbstractMatrix{Float64}; apply_rescaling::Bool=true, start::Int64=1) = evaluate!(zero(X), M, X; apply_rescaling = apply_rescaling, start = start)
(M::RadialMap)(X::AbstractMatrix{Float64}; apply_rescaling::Bool=true, start::Int64=1) = evaluate(M, X; apply_rescaling = apply_rescaling, start = start)
#### Sparse Structure for the lower triangular map M
struct SparseRadialMap
Nx::Int64
p::Array{Array{Int64,1}}
L::LinearTransform
C::Array{SparseRadialMapComponent, 1}
# Optimization parameters
γ::Float64
λ::Float64
δ::Float64
κ::Float64
end
function SparseRadialMap(Nx::Int64, p::Array{Array{Int64,1}}; γ::Float64=2.0, λ::Float64=0.1, δ::Float64=1e-8, κ::Float64=10.0)
@assert Nx==size(p,1) "Wrong dimension of the SparseRadialMap"
L = LinearTransform(Nx)
C = SparseRadialMapComponent[]
@inbounds for i=1:Nx
push!(C, SparseRadialMapComponent(i,p[i]))
end
return SparseRadialMap(Nx, p, L, C, γ, λ, δ, κ)
end
function SparseRadialMap(Nx::Int64, p::Array{Int64,1}; γ::Float64=2.0, λ::Float64=0.1, δ::Float64=1e-8, κ::Float64=10.0)
@assert Nx==size(p,1) "Wrong dimension of the SparseRadialMap"
L = LinearTransform(Nx)
C = SparseRadialMapComponent[]
@inbounds for i=1:Nx
push!(C, SparseRadialMapComponent(i,p[i]))
end
return SparseRadialMap(Nx, [fill(p[i],i) for i=1:Nx], L, C, γ, λ, δ, κ)
end
function SparseRadialMap(Nx::Int64, p::Int64; γ::Float64=2.0, λ::Float64=0.1, δ::Float64=1e-8, κ::Float64=10.0)
L = LinearTransform(Nx)
C = SparseRadialMapComponent[]
@inbounds for i=1:Nx
push!(C, SparseRadialMapComponent(i,p))
end
return SparseRadialMap(Nx, [fill(p,i) for i=1:Nx], L, C, γ, λ, δ, κ)
end
# Methods based on an ensemble matrix X
function SparseRadialMap(X::Array{Float64,2}, p::Array{Array{Int64,1}}; γ::Float64=2.0, λ::Float64=0.1, δ::Float64=1e-8, κ::Float64=10.0)
Nx, Ne = size(X)
@assert Nx==size(p,1) "Wrong dimension of the SparseRadialMap"
L = LinearTransform(X)
C = SparseRadialMapComponent[]
@inbounds for i=1:Nx
push!(C, SparseRadialMapComponent(i,p[i]))
end
return SparseRadialMap(Nx, p, L, C, γ, λ, δ, κ)
end
function SparseRadialMap(X::Array{Float64,2}, p::Array{Int64,1}; γ::Float64=2.0, λ::Float64=0.1, δ::Float64=1e-8, κ::Float64=10.0)
Nx, Ne = size(X)
@assert Nx==size(p,1) "Wrong dimension of the SparseRadialMap"
L = LinearTransform(X)
C = SparseRadialMapComponent[]
@inbounds for i=1:Nx
push!(C, SparseRadialMapComponent(i,p[i]))
end
return SparseRadialMap(Nx, [fill(p[i],i) for i=1:Nx], L, C, γ, λ, δ, κ)
end
function SparseRadialMap(X::Array{Float64,2}, p::Int64; γ::Float64=2.0, λ::Float64=0.1, δ::Float64=1e-8, κ::Float64=10.0)
Nx, Ne = size(X)
L = LinearTransform(X)
C = SparseRadialMapComponent[]
@inbounds for i=1:Nx
push!(C, SparseRadialMapComponent(i,p))
end
return SparseRadialMap(Nx, [fill(p,i) for i=1:Nx], L, C, γ, λ, δ, κ)
end
function Base.show(io::IO, M::SparseRadialMap)
println(io,"Sparse Radial Map of dimension Nx = $(M.Nx) and order p = $(M.p)
with parameters (γ, λ, δ, κ) = ($(M.γ), $(M.λ), $(M.δ), $(M.κ))")
end
@propagate_inbounds Base.getindex(M::SparseRadialMap, i::Int) = getindex(M.C,i)
@propagate_inbounds Base.setindex!(M::SparseRadialMap, C::SparseRadialMapComponent, i::Int) = setindex!(M.C,C,i)
size(M::SparseRadialMap) = (M.Nx, M.p)
# Evaluate the map Sparse RadialMap at z = (z1,...,zNx)
function evaluate!(out, M::SparseRadialMap, z::AbstractVector{Float64}; apply_rescaling::Bool=true, start::Int64=1)
Nx = M.Nx
@assert Nx==size(z,1) "Incorrect length of the input vector"
if apply_rescaling == true
transform!(M.L, z)
end
@inbounds for i=start:Nx
if allequal(M.C[i].p,-1)
out[i] = z[i]
else
out[i] = M.C[i](view(z,1:i))
end
end
if apply_rescaling == true
itransform!(M.L, z)
end
return out
end
evaluate(M::SparseRadialMap, z::AbstractVector{Float64}; apply_rescaling::Bool=true, start::Int64=1) = evaluate!(zeros(M.Nx-start+1), M, z; apply_rescaling = apply_rescaling, start = start)
(M::SparseRadialMap)(z::AbstractVector{Float64}; apply_rescaling::Bool=true, start::Int64=1) = evaluate(M, z; apply_rescaling = apply_rescaling, start = start)
# Evaluate the map SparseRadialMapComponent at z = (z1,...,zNx)
function evaluate!(out, M::SparseRadialMap, X::AbstractMatrix{Float64}; apply_rescaling::Bool=true, start::Int64=1)
@get M (Nx, p)
NxX, Ne = size(X)
@assert NxX == Nx "Wrong dimension of the ensemble matrix `X`"
@assert size(out) == (Nx, Ne) "Wrong dimension of the output matrix `out`"
if apply_rescaling == true
transform!(M.L, X)
end
@inbounds for i=1:Ne
col = view(X,:,i)
evaluate!(view(out,:,i), M, col; apply_rescaling = false, start = start)
end
if apply_rescaling == true
itransform!(M.L, X)
end
return out
end
evaluate(M::SparseRadialMap, X::AbstractMatrix{Float64}; apply_rescaling::Bool=true, start::Int64=1) = evaluate!(zero(X), M, X; apply_rescaling = apply_rescaling, start = start)
(M::SparseRadialMap)(X::AbstractMatrix{Float64}; apply_rescaling::Bool=true, start::Int64=1) = evaluate(M, X; apply_rescaling = apply_rescaling, start = start)
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] | 1.991053 | 4,471 |
function qserver(sock::Integer)
fin = open("quotes.txt");
hdr = "Content-type: text/plain\n\n";
qa = readlines(fin);
close(fin);
qn = length(qa);
@async begin
server = listen(sock)
while true
qi = rand(1:qn)
qs = chomp(qa[qi])
sock = accept(server)
println(hdr*qs)
end
end
end
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] | 2.123377 | 154 |
# Unit "hilbert" of the FourierAnalysis Package for julia language
#
# MIT License
# Copyright (c) 2019-2022,
# Marco Congedo, CNRS, Grenobe, France:
# https://sites.google.com/site/marcocongedo/home
# ? CONTENTS :
# This unit implements the Hilbert transform and analytic signal
# estimations for signals of arbitrary length, using FFTW.
"""
```julia
(1)
function analyticsignal( X :: Union{Vector{T}, Matrix{T}},
wl :: Int = size(X, 1);
nonlinear :: Bool = false,
planner :: Planner = getplanner,
⏩ :: Bool = true) where T<:Real
(2)
function analyticsignal( 𝐗 :: Vector{Matrix{T}},
wl :: Int;
nonlinear :: Bool = false,
planner :: Planner = getplanner,
⏩ :: Bool = true) where T<:Real
```
(1)
Compute the analytic signal(AS) of vector `X` or of
all column vectors of matrix `X` via the FFT and iFFT procedure,
as explained in Marple(1999).
If `wl`=size(X, 1) (default), use the standard method passing to the FFT
and iFFT all samples in `X` altogether, whereas if `wl`<size(X, 1) a
sliding-windows method is used (see below).
Return the analytic signal `𝑌`, a complex vector if `X` is a vector
or a complex matrix holding in its columns the analytic signal of the
columns of `X` if `X` is a matrix. `𝑌` has the same number of samples (rows)
as `X`.
Contrarely to what is done in the [DSP](https://github.com/JuliaDSP/DSP.jl)
package, the DC level of the signal is removed, therefore,
if the input signal features a non-zero DC level,
the real part of the AS will be equal to the input signal with the
DC level removed. The imaginary part of `𝑌` is the Hilbert transform
of such no-DC `X`.
The sliding-windows AS allows an efficient estimation of the AS for vectors and
matrices when they are very large; it proceeds
computing the AS on 50% sliding overlapping windows and forming the AS
by retaining the central half of each window. The number of points effectively
used to obtain the final estimation is ``wl``÷2 (integer division).
`wl` must be even for using this estimation. This procedure
produces edge effects, thus the first and last ``wl÷4`` samples of the AS
estimation should be discarded. In practice, one requires the AS of a
larger data segment and trims at least ``wl÷4`` samples at the beginning and
end of the estimation. This is done automatically
by the [`TFanalyticsignal`](@ref) function.
Also, the sliding-windows AS method creates small discontinuities at sample
``wl``÷4 and then every ``wl``÷2 samples,
therefore ``wl`` should be chosen as large as possible.
!!! note "Nota Bene"
In order to avoid FFT computation of very long epochs,
if `wl` > 2^14, then `wl` is set to 2^10. Below this limit, as long as
the computations are feasable, use the standard method. If you absolutely
need to use the sliding-windows method, see [window length in FFTW](@ref)
for setting efficiently argument `wl`.
The input signal should be previously band-pass or high-pass filtered
so as not to contain frequency components below the first discrete
Fourier frequency obtained with windows of `wl` samples, that is,
below sr/wl Hz, where sr is the sampling rate.
**Optional Keyword Arguments**:
`nonlinear`, if true, the analytic signal is normalized so that its amplitude
is ``1.0`` at all points. This allow non-linear univariate and bivariate estimations
(see [timefrequencyuni.jl](@ref) and [timefrequencybi.jl](@ref)).
`planner` is an instance of the [`Planner`](@ref) object, holding the forward
and backward FFTW plans used to compute the FFTs and the iFFTs.
By default the planner is computed, but it can be passed as an
argumet here if it is pre-computed. This is interesting if the
`analyticsignal` function is to be invoked repeatedly.
if `⏩` is true, the method is run in multi-threaded mode across the series
in `X` if the number of series is at least twice the number of threads Julia
is instructed to use. See [Threads](@ref).
(2)
Compute the analytic signal for all ``k``
multivariate data matrices given as a vector of matrices `𝐗`.
Return a vector of matrices hodling the corresponding analytic signals
as in method (1). The FFT and iFFT plans are computed only once.
The ``k`` matrices in `𝐗` may have different number of columns (i.e., different
number of series) and different number of rows (samples).
However, the number of rows must be larger than `wl` for all of them.
If `⏩` is true, this method run in multi-threaded mode across the
matrices in `𝐗` if the number of matrices is at least twice
the number of threads Julia is instructed to use, otherwise it
tries to run each analytic signal estimation in multi-threaded mode
as per method (1). See [Threads](@ref).
This function is called by the following functions operating
on time-frequency reprsentations: [`TFanalyticsignal`](@ref),
[`TFamplitude`](@ref), [`TFphase`](@ref), [`meanAmplitude`](@ref),
[`concentration`](@ref), [`meanDirection`](@ref), [`comodulation`](@ref),
[`coherence`](@ref).
**References**
Marple S.L. (1999)
Computing the Discrete-Time Analytic Signal via FFT.
IEEE Transactions on Signal Processing 47(9), 2600-3.
**Examples**:
```julia
using FourierAnalysis, FFTW, LinearAlgebra, Statistics, Plots, DSP
t=128; lab=["x", "real(y)", "imag(y)"]
# Analytic signal of one vector
x=sinusoidal(10, 2, 128, t, π/2; DC=10) # cosine
y=analyticsignal(x)
# note that real(y) is x without the DC level, i.e., x=real(y)+DC
plot([x, real(y), imag(y)]; labels=lab)
# make a check
s=sinusoidal(10, 2, 128, t, 0) # sine
norm(s-imag(y)) # should be zero
# Analytic Signal by DSP.jl
y2=hilbert(x)
norm(s-imag(y2)) # should be zero
# DSP.jl does not remove the DC level
# thus x=real(y2) in this case
plot([x, real(y2), imag(y2)]; labels=lab)
# Analytic signal of multiple vectors
x=hcat(x, sinusoidal(10, 3, 128, t, π/2; DC=10))
y=analyticsignal(x)
# sliding-windows analytic signal of one vector
# (note edge effects)
x=sinusoidal(10, 2, 128, t*4, π/2; DC=0)
y=analyticsignal(x, t)
plot([x, real(y), imag(y)]; labels=lab)
# sliding-windows analytic signal of multiple vectors
x=hcat(x, sinusoidal(10, 3, 128, t*4, π/2; DC=0))
y=analyticsignal(x, t)
```
"""
function analyticsignal( X :: Union{Vector{T}, Matrix{T}},
wl :: Int = size(X, 1);
nonlinear :: Bool = false,
planner :: Planner = getplanner,
⏩ :: Bool = true) where T<:Real
# get all needed paramters (see below the _paramHT! function)
X_, 𝚙, i𝚙, e, tₐₗₗ, n, wl½, two_wl⁻¹, cT, f, g, ζ = _paramHT!(X, wl, planner)
𝑌=zeros(cT, tₐₗₗ, n) # Preallocate memory for the Analytic Signal of X
# Add to `𝑌` the analytic signal of a vector `X_` or of the column vectors of
# matrix `X_`, computed on the epoch(s) of duration `t` samples starting at
# sample `at`. It does not return anything.
# ARGUMENTS:
# `n` (Int) is the number of columns in `X_`; it must be 1 if `X_` is a vector.
# `wl½` = wl÷2
# `two_wl⁻¹` = 2/wl
# `e` (Int) the number of sliding windows
# `𝚙` is the forward FFTW plan performing the FFT.
# `i𝚙` is the backward FFTW plan performing the iFFT (Hilbert transform).
# `ζ`, =zeros(cT, wl-wl½_), a zero-vector appended to the iFFT vectors, since the second half of the FFT is not computed
# `f`, the lower limit (in samples) of the central half of each Hilbert transform to cumulate with respect to the FFT window
# `g`, the upper limit (in samples) of the central half of each Hilbert transform to cumulate with respect to the FFT window
function _analyticsignal!(at, 𝚗)
#if 𝚗==1 println(at:at+wl-1, " ", f, " ", g, " ", at+f-1:at+g-1) end ###
y = 𝚙*X_[at:at+wl-1, 𝚗] # FFT
@inbounds begin # transform
y[1]=0.
for i=2:wl½ y[i] *= two_wl⁻¹ end
end
# iFFT and cumulate
e==1 ? 𝑌[:, 𝚗]+=i𝚙*vcat(y, ζ) : 𝑌[at+f-1:at+g-1, 𝚗]+=(i𝚙*vcat(y, ζ))[f:g]
end
# add the Analytic Signal
as!(𝚎, 𝚗)=_analyticsignal!((𝚎*wl½)+1, 𝚗)
_thread(⏩, n) ? (for 𝚎=0:e-1 @threads for 𝚗=1:n as!(𝚎, 𝚗) end end) : (for 𝚗=1:n, 𝚎=0:e-1 as!(𝚎, 𝚗) end)
# return a vector if `X` is a vector, a matrix if `X` is a matrix.
# for the sliding-windows version eliminate the first and last
# t½ samples that have been previously padded.
𝑌_ = n==1 ? (e>1 ? 𝑌[:][wl½+1:end-wl½] : 𝑌[:]) : (e>1 ? 𝑌[wl½+1:end-wl½, 1:n] : 𝑌)
if nonlinear @inbounds for i in eachindex(𝑌_) 𝑌_[i]/=abs(𝑌_[i]) end end
return 𝑌_
end
function analyticsignal( 𝐗 :: Vector{Matrix{T}},
wl :: Int;
nonlinear :: Bool = false,
planner :: Planner = getplanner,
⏩ :: Bool = true) where T<:Real
cT, k=typeof(Complex(T(0))), length(𝐗)
planner ≠ getplanner ? plan=planner : plan=Planner(plan_estimate, -1.0, wl, T, true)
𝒀=Vector{Matrix{cT}}(undef, k)
# function to add the analytic signal
as(i, ⏩)=analyticsignal(𝐗[i], wl; nonlinear=nonlinear, planner=plan, ⏩=⏩)
_thread(⏩, k) ? (@threads for i=1:k 𝒀[i]=as(i, false) end) : (for i=1:k 𝒀[i]=as(i, ⏩) end)
return 𝒀
end
# Internal function: prepare all parameters that are needed for
# Analytic Signal and sliding-windows Analytic Signal estimations
#
# ARGUMENTS:
# `X` is the input data vector or matrix (n time-series)
# `wl` (Int) is the epoch length for FFT
# `planner` a pre-computed FFT `Planner` or `getPlanner` to compute it
#
# RETURN
# `X_`: if a standard anaytic signal is requested (t==size(X, 1)) then X_=X
# else X_ is the data in `X` with wl½ zeros prepended and appended.
# `𝚙` the forward FFTW plan. It is computed if argument `planner`=`getplanner`.
# `i𝚙` the backward FFTW plan. It is computed if argument `planner`=`getplanner`.
# `e` (Int) the number of sliding windows, 1 for the standard AS method.
# `tₐₗₗ` (Int) number of samples total. For sliding-windows anaytic signal,
# this is not size(X, 1) as zeros are padded.
# `n` (Int) 1 if `X` is a Vector, the number of columns of `X` otherwise.
# `wl½` `t`÷2 computed by the right aritmetic bit-wise operation `wl`>>1.
# `two_wl⁻¹` = 2/wl.
# `cT` the complex type corresponding to type `T` in function definition
# (e.g., ComplexF64 if T=Float64).
# `f`, the lower limit (in samples) of the central half of each
# Hilbert transform to cumulate with respect to the FFT window.
# `g`, the upper limit (in samples) of the central half of each
# Hilbert transform to cumulate with respect to the FFT window.
# `ζ`, =zeros(cT, wl-wl½_), a zero-vector append to the iFFT vectors,
# since the second half of the FFT is not computed
# NB if wl > 2^14 then t is set to 2^10. This affects the default
# behavior of all AS functions.
function _paramHT!( X :: AbstractArray{T},
wl :: Int,
planner :: Planner) where T<:Real
size(X, 1) < wl && @error 📌*", the number of samples in input matrix is smaller than the desired window length."
wl > 2^14 ? wl = 2^10 : nothing
n, wl½, two_wl⁻¹ = size(X, 2), (wl>>1), T(2/wl)
if size(X, 1)>wl
X_=[zeros(T, wl½, n); X; zeros(T, wl½, n)] else X_=X
isodd(wl) && @error 📌*", for Welch-like Analytic Signal estimation `wl` must be even."
end
tₐₗₗ = size(X_, 1) # for sliding-windows anaytic signal, this is not size(X, 1)
cT = typeof(Complex(T(0)))
if planner ≠ getplanner
𝚙=planner.p
i𝚙=planner.ip
else
𝚙=plan_rfft(zeros(T, wl), flags=plan_estimate, timelimit=-1.0)
i𝚙=plan_bfft(zeros(cT, wl), flags=plan_estimate, timelimit=-1.0)
end
f=wl½÷2+1 # lower limit of central region to copy
g=f+wl½-1 # upper limit of central region to copy
e = (tₐₗₗ-wl)÷wl½+1 # number of 50% overlapping epochs or 1 if tₐₗₗ=wl
ζ=zeros(cT, wl-wl½-1)
return X_, 𝚙, i𝚙, e, tₐₗₗ, n, wl½, two_wl⁻¹, cT, f, g, ζ
end
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114,
198,
437,
198
] | 2.434287 | 4,999 |
"""
$(DocStringExtensions.README)
"""
module DiffEqBayes
using DocStringExtensions
using DiffEqBase, Distributions, Turing, MacroTools
using RecursiveArrayTools, ModelingToolkit
using Parameters, Distributions, Optim, Requires
using Distances, DocStringExtensions, Random, StanSample
STANDARD_PROB_GENERATOR(prob,p) = remake(prob;u0=eltype(p).(prob.u0),p=p)
STANDARD_PROB_GENERATOR(prob::EnsembleProblem,p) = EnsembleProblem(remake(prob.prob;u0=eltype(p).(prob.prob.u0),p=p))
include("turing_inference.jl")
# include("abc_inference.jl")
include("stan_string.jl")
include("stan_inference.jl")
function __init__()
@require DynamicHMC="bbc10e6e-7c05-544b-b16e-64fede858acb" begin
using .DynamicHMC, TransformVariables, LogDensityProblems
include("dynamichmc_inference.jl")
export dynamichmc_inference
end
end
export turing_inference, stan_inference ,abc_inference
end # module
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] | 2.588068 | 352 |
struct OrbitGrid{T}
energy::AbstractVector{T}
pitch::AbstractVector{T}
r::AbstractVector{T}
counts::Vector{Int}
orbit_index::Array{Int,3}
class::Array{Symbol,3}
tau_p::Array{T,3}
tau_t::Array{T,3}
end
function Base.show(io::IO, og::OrbitGrid)
print(io, "OrbitGrid: $(length(og.energy))×$(length(og.pitch))×$(length(og.r)):$(length(og.counts))")
end
function orbit_grid(M::AxisymmetricEquilibrium, eo::AbstractVector, po::AbstractVector, ro::AbstractVector;
q = 1, amu = H2_amu, kwargs...)
nenergy = length(eo)
npitch = length(po)
nr = length(ro)
orbit_index = zeros(Int,nenergy,npitch,nr)
class = fill(:incomplete,(nenergy,npitch,nr))
tau_t = zeros(Float64,nenergy,npitch,nr)
tau_p = zeros(Float64,nenergy,npitch,nr)
norbs = nenergy*npitch*nr
subs = CartesianIndices((nenergy,npitch,nr))
p = Progress(norbs)
channel = RemoteChannel(()->Channel{Bool}(norbs), 1)
orbs = fetch(@sync begin
@async while take!(channel)
ProgressMeter.next!(p)
end
@async begin
orbs = @distributed (vcat) for i=1:norbs
ie,ip,ir = Tuple(subs[i])
c = EPRCoordinate(M,eo[ie],po[ip],ro[ir],q=q,amu=amu)
try
o = get_orbit(M, c; kwargs...)
catch
o = Orbit(EPRCoordinate(;q=q,amu=amu),:incomplete)
end
if o.class in (:incomplete,:invalid,:lost)
o = Orbit(o.coordinate,:incomplete)
end
put!(channel, true)
o
end
put!(channel, false)
orbs
end
end)
for i=1:norbs
class[subs[i]] = orbs[i].class
tau_p[subs[i]] = orbs[i].tau_p
tau_t[subs[i]] = orbs[i].tau_t
end
grid_index = filter(i -> orbs[i].class != :incomplete, 1:norbs)
orbs = filter(x -> x.class != :incomplete, orbs)
norbs = length(orbs)
orbit_index[grid_index] = 1:norbs
return orbs, OrbitGrid(eo,po,ro,fill(1,norbs),orbit_index,class,tau_p,tau_t)
end
function segment_orbit_grid(M::AxisymmetricEquilibrium, orbit_grid::OrbitGrid, orbits::Vector;
norbits=1000, combine=(length(orbits[1].path) != 0),
q = 1, amu = H2_amu, kwargs...)
eo = orbit_grid.energy
po = orbit_grid.pitch
ro = orbit_grid.r
nenergy = length(eo)
npitch = length(po)
nr = length(ro)
norbs = length(orbits)
e_range = extrema(eo)
p_range = extrema(po)
r_range = extrema(ro)
orbs_index = zeros(Int,norbs)
for i = 1:length(orbit_grid.orbit_index)
ii = orbit_grid.orbit_index[i]
ii == 0 && continue
orbs_index[ii] != 0 && continue
orbs_index[ii] = i
end
orbit_index = zeros(Int,nenergy,npitch,nr)
norm = abs.([-(e_range...), -(p_range...), -(r_range...)])
mins = [e_range[1],p_range[1],r_range[1]]
oclasses = [:potato, :stagnation, :trapped, :co_passing, :ctr_passing]
orbit_counts = Dict{Symbol,Int}(o=>count(x -> x.class == o, orbits)
for o in oclasses)
nclusters = 0
orbs = eltype(orbits)[]
orbit_num = 0
for oc in oclasses
nk = max(Int(ceil(norbits*orbit_counts[oc]/norbs)),1)
if (nclusters + nk) > norbits
nk = norbits - nclusters
end
nk == 0 && continue
inds_oc = findall([o.class == oc for o in orbits])
coords = hcat((([o.coordinate.energy, o.coordinate.pitch, o.coordinate.r] .- mins)./norm
for o in orbits if o.class == oc)...)
if nk == 1
if !combine
c = coords .* norm .+ mins
cc = EPRCoordinate(M,mean(c,dims=2)...;q = q, amu=amu)
try
o = get_orbit(M, GCParticle(cc.energy,cc.pitch,cc.r,cc.z,cc.m,cc.q); kwargs...)
push!(orbs,o)
orbit_num = orbit_num + 1
catch
o = Orbit(cc)
push!(orbs,o)
orbit_num = orbit_num + 1
end
else
o = combine_orbits(orbits[inds_oc])
push!(orbs,o)
orbit_num = orbit_num + 1
end
orbit_index[orbs_index[inds_oc]] .= orbit_num
nclusters = nclusters + nk
continue
end
k = kmeans(coords,nk)
if !combine
coords = k.centers.*norm .+ mins
for i=1:size(coords,2)
w = k.assignments .== i
sum(w) == 0 && continue
cc = EPRCoordinate(M,coords[1,i],coords[2,i],coords[3,i], q=q, amu=amu)
try
o = get_orbit(M, GCParticle(cc.energy,cc.pitch,cc.r,cc.z,cc.m,cc.q); kwargs...)
push!(orbs,o)
orbit_num = orbit_num + 1
catch
o = Orbit(cc)
push!(orbs,o)
orbit_num = orbit_num + 1
end
orbit_index[orbs_index[inds_oc[w]]] .= orbit_num
end
else
for i=1:nk
w = k.assignments .== i
sum(w) == 0 && continue
o = combine_orbits(orbits[inds_oc[w]])
push!(orbs,o)
orbit_num = orbit_num + 1
orbit_index[orbs_index[inds_oc[w]]] .= orbit_num
end
end
nclusters = nclusters + nk
end
counts = [count(x -> x == i, orbit_index) for i=1:length(orbs)]
return orbs, OrbitGrid(eo,po,ro,counts,orbit_index,orbit_grid.class,orbit_grid.tau_p,orbit_grid.tau_t)
end
function orbit_matrix(M::AxisymmetricEquilibrium, grid::OrbitGrid, energy, pitch, r, z; kwargs...)
nenergy = length(energy)
npitch = length(pitch)
nr = length(r)
nz = length(z)
norbits = length(grid.counts)
subs = CartesianIndices((nenergy,npitch,nr,nz))
nsubs = length(subs)
p = Progress(nsubs)
channel = RemoteChannel(()->Channel{Bool}(nsubs), 1)
R = fetch(@sync begin
@async while take!(channel)
ProgressMeter.next!(p)
end
@async begin
R = @distributed (hcat) for i=1:nsubs
ie,ip,ir,iz = Tuple(subs[i])
gcp = GCParticle(energy[ie],pitch[ip],r[ir],z[iz])
o = get_orbit(M,gcp;store_path=false,kwargs...)
Rcol = spzeros(norbits)
if !(o.class in (:lost,:incomplete)) && o.coordinate.r > M.axis[1]
oi = orbit_index(grid,o.coordinate)
(oi > 0) && (Rcol[oi] = 1.0)
end
put!(channel,true)
Rcol
end
put!(channel,false)
R
end
end)
return R
end
function write_orbit_grid(grid::OrbitGrid;filename="orbit_grid.h5")
h5open(filename,"w") do file
file["energy"] = collect(grid.energy)
file["pitch"] = collect(grid.pitch)
file["r"] = collect(grid.r)
file["counts"] = grid.counts
file["orbit_index"] = grid.orbit_index
file["class"] = String.(grid.class)
file["tau_p"] = grid.tau_p
file["tau_t"] = grid.tau_p
end
nothing
end
function read_orbit_grid(filename)
isfile(filename) || error("File does not exist")
f = h5open(filename)
energy = read(f["energy"])
pitch = read(f["pitch"])
r = read(f["r"])
counts = read(f["counts"])
orbit_index = read(f["orbit_index"])
class = Symbol.(read(f["class"]))
tau_p = read(f["tau_p"])
tau_t = read(f["tau_t"])
close(f)
return OrbitGrid(energy,pitch,r,counts,orbit_index,class,tau_p,tau_t)
end
function map_orbits(grid::OrbitGrid, f::Vector)
if length(grid.counts) != length(f)
throw(ArgumentError("Incompatible sizes"))
end
dorb = abs((grid.r[2]-grid.r[1])*(grid.energy[2]-grid.energy[1])*(grid.pitch[2]-grid.pitch[1]))
return [i == 0 ? zero(f[1]) : f[i]/(grid.counts[i]*dorb) for i in grid.orbit_index]
end
function orbit_index(grid::OrbitGrid, o::EPRCoordinate; nearest=false)
if !nearest
if (grid.energy[1] <= o.energy <= grid.energy[end]) &&
(grid.pitch[1] <= o.pitch <= grid.pitch[end]) &&
(grid.r[1] <= o.r <= grid.r[end])
i = argmin(abs.(o.energy .- grid.energy))
j = argmin(abs.(o.pitch .- grid.pitch))
k = argmin(abs.(o.r .- grid.r))
ind = grid.orbit_index[i,j,k]
else
ind = 0
end
else
inds = filter(x->grid.orbit_index[x] != 0, CartesianIndices(grid.orbit_index))
data = hcat( ([grid.energy[I[1]], grid.pitch[I[2]], grid.r[I[3]]] for I in inds)...)
tree = KDTree(data)
idxs, dists = knn(tree,[o.energy,o.pitch,o.r],1,false)
ind = grid.orbit_index[inds[idxs[1]]]
end
return ind
end
function bin_orbits(grid::OrbitGrid, orbits; weights::Union{Nothing,Vector},nearest=false)
if weights != nothing
length(weights) == length(orbits) || error("Incompatible weight vector size")
w = weights
else
w = fill(1.0,length(orbits))
end
f = zeros(length(grid.counts))
if !nearest
for (io,o) in enumerate(orbits)
i = argmin(abs.(o.energy .- grid.energy))
j = argmin(abs.(o.pitch .- grid.pitch))
k = argmin(abs.(o.r .- grid.r))
ind = grid.orbit_index[i,j,k]
if ind != 0
f[ind] += w[io]
end
end
else
inds = filter(x->grid.orbit_index[x] != 0, CartesianIndices(grid.orbit_index))
data = hcat( ([grid.energy[I[1]], grid.pitch[I[2]], grid.r[I[3]]] for I in inds)...)
tree = KDTree(data)
for (io, o) in enumerate(orbits)
idxs, dists = knn(tree,[o.energy,o.pitch,o.r],1,false)
f[grid.orbit_index[inds[idxs[1]]]] += w[io]
end
end
return f
end
function combine_orbits(orbits)
norbits = length(orbits)
norbits == 1 && return orbits[1]
o = orbits[1]
r = o.path.r
z = o.path.z
phi = o.path.phi
pitch = o.path.pitch
energy = o.path.energy
dt = o.path.dt
#dl = o.path.dl
c = o.coordinate
isa(c, EPRCoordinate) || error("Wrong orbit coordinate. Expected EPRCoordinate")
ec = c.energy
pc = c.pitch
rc = c.r
zc = c.z
tau_p = o.tau_p
tau_t = o.tau_t
for i=2:norbits
oo = orbits[i]
ec = ec + oo.coordinate.energy
pc = pc + oo.coordinate.pitch
rc = rc + oo.coordinate.r
zc = zc + oo.coordinate.z
tau_t = tau_t + oo.tau_t
tau_p = tau_p + oo.tau_p
append!(r, oo.path.r)
append!(z, oo.path.z)
append!(phi, oo.path.phi)
append!(pitch, oo.path.pitch)
append!(energy, oo.path.energy)
append!(dt, oo.path.dt)
#append!(dl, oo.path.dl)
end
ec = ec/norbits
pc = pc/norbits
rc = rc/norbits
zc = zc/norbits
tau_p = tau_p/norbits
tau_t = tau_p/norbits
cc = EPRCoordinate(ec,pc,rc,zc,zero(zc),c.m,c.q)
path = OrbitPath(o.path.vacuum, o.path.drift, energy,pitch,r,z,phi,dt)#,dl)
if all(x -> x.class == orbits[1].class, orbits)
class = orbits[1].class
else
class = :meta
end
return Orbit(cc, class, tau_p, tau_t, path)
end
function mc2orbit(M::AxisymmetricEquilibrium, d::FIDASIMGuidingCenterParticles, GCP::T; kwargs...) where T <: Function
p = Progress(d.npart)
channel = RemoteChannel(()->Channel{Bool}(d.npart),1)
t = @sync begin
@async while take!(channel)
ProgressMeter.next!(p)
end
@async begin
orbs = @distributed (vcat) for i=1:d.npart
o = get_orbit(M,GCP(d.energy[i],M.sigma*d.pitch[i],d.r[i]/100,d.z[i]/100); kwargs...,store_path=false)
put!(channel,true)
o.coordinate
end
put!(channel,false)
orbs
end
end
return fetch(t)
end
function fbm2orbit(M::AxisymmetricEquilibrium,d::FIDASIMGuidingCenterFunction; GCP=GCDeuteron, n=1_000_000, kwargs...)
dmc = fbm2mc(d,n=n)
return mc2orbit(M, dmc, GCP; kwargs...)
end
struct OrbitSpline{T<:Function}
n::Int
itp::T
end
@inline (os::OrbitSpline)(x) = os.itp(x)
@inline Base.length(os::OrbitSpline) = os.n
function OrbitSpline(p::OrbitPath, t)
length(p) == 0 && return OrbitSpline(0, x -> S4(zeros(4)))
eprz = hcat(p.energy,p.pitch,p.r,p.z)
oi = scale(interpolate(eprz, (BSpline(Cubic(Periodic(OnGrid()))), NoInterp())), t, 1:4)
return OrbitSpline(length(t), x -> S4(oi.(x,1:4)))
end
function OrbitSpline(o::Orbit, t)
return OrbitSpline(o.path, t)
end
function OrbitSpline(o::Orbit)
t = range(0.0, 1.0, length=length(o))
return OrbitSpline(o.path, t)
end
function OrbitSpline(p::OrbitPath)
t = range(0.0, 1.0, length=length(p))
return OrbitSpline(p, t)
end
OrbitSpline(o::OrbitSpline) = o
OrbitSpline(o::OrbitSpline, t) = o
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90,
33,
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92,
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7,
31,
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220,
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220,
220,
220,
2488,
292,
13361,
981,
1011,
0,
7,
17620,
8,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
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44,
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13,
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0,
7,
79,
8,
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220,
220,
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198,
220,
220,
220,
220,
220,
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220,
220,
220,
220,
220,
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220,
220,
220,
220,
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220,
220,
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220,
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220,
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198,
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220,
220,
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8,
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0,
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0,
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11,
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83,
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62,
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8,
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198,
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10618,
62,
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62,
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7,
44,
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31554,
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3020,
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11,
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62,
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26,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
4249,
9895,
28,
12825,
11,
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16193,
13664,
7,
273,
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58,
16,
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6978,
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657,
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220,
220,
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220,
220,
220,
220,
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220,
220,
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220,
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7,
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8,
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7,
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220,
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260,
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7,
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8,
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62,
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796,
1976,
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220,
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21065,
796,
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62,
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13,
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62,
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58,
72,
60,
198,
220,
220,
220,
220,
220,
220,
220,
21065,
6624,
657,
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2555,
198,
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220,
220,
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220,
220,
220,
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62,
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60,
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220,
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62,
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796,
1976,
27498,
7,
5317,
11,
77,
22554,
11,
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2007,
11,
48624,
8,
628,
220,
220,
220,
2593,
796,
2352,
12195,
58,
30420,
68,
62,
9521,
986,
828,
532,
7,
79,
62,
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828,
532,
7,
81,
62,
9521,
23029,
12962,
198,
220,
220,
220,
23550,
796,
685,
68,
62,
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58,
16,
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79,
62,
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58,
16,
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81,
62,
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58,
16,
11907,
198,
220,
220,
220,
267,
37724,
796,
685,
25,
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5549,
11,
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301,
4660,
341,
11,
1058,
9535,
1496,
11,
1058,
1073,
62,
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278,
11,
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24087,
62,
6603,
278,
60,
628,
220,
220,
220,
13066,
62,
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82,
796,
360,
713,
90,
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23650,
11,
5317,
92,
7,
78,
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9127,
7,
87,
4613,
2124,
13,
4871,
6624,
267,
11,
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8,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
329,
267,
287,
267,
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8,
628,
220,
220,
220,
299,
565,
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796,
657,
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220,
220,
220,
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796,
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7,
273,
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8,
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198,
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220,
13066,
62,
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796,
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220,
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299,
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7,
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7,
344,
346,
7,
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62,
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82,
58,
420,
60,
14,
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16,
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220,
220,
220,
220,
220,
220,
611,
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77,
565,
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299,
74,
8,
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220,
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220,
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773,
82,
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78,
13,
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13,
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11,
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13,
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13,
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267,
13,
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13,
81,
60,
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12,
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737,
14,
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198,
220,
220,
220,
220,
220,
220,
220,
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220,
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66,
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500,
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10,
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36624,
796,
412,
4805,
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11,
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7,
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11,
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28,
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26,
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11,
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84,
28,
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84,
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220,
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220,
220,
220,
220,
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220,
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220,
220,
220,
220,
220,
267,
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62,
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7,
44,
11,
20145,
7841,
1548,
7,
535,
13,
22554,
11,
535,
13,
79,
2007,
11,
535,
13,
81,
11,
535,
13,
89,
11,
535,
13,
76,
11,
535,
13,
80,
1776,
479,
86,
22046,
23029,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
4574,
0,
7,
273,
1443,
11,
78,
8,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
13066,
62,
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796,
13066,
62,
22510,
1343,
352,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
4929,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
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25,
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13,
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13,
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0,
7,
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] | 1.867668 | 7,058 |
#module Scaling
export NiceScale, scaled
floorx(x) = x<0 ? ceil(x) : floor(x)
ceilx(x) = x<0 ? floor(x) : ceil(x)
mutable struct NiceScale
minPoint::Float32
maxPoint::Float32
maxTicks::Float32
tickSpacing::Float32
range::Float32
niceMin::Float32
niceMax::Float32
xfact::Float32
xoffset::Float32
function NiceScale(min::Real,max::Real; padding=0.05,steps=10.)
mn = min-padding*(max-min)
mx = max+padding*(max-min)
if mx==mn mn=mn-1; mx=mx+1; end
a=new(mn,mx,steps,0.,0.,0.,0.)
a.range = niceNum(a.maxPoint-a.minPoint)
a.tickSpacing = niceNum( a.range / (a.maxTicks-1),true)
a.niceMin = ceil(a.minPoint / a.tickSpacing ) * a.tickSpacing
a.niceMax = floor(a.maxPoint / a.tickSpacing ) * a.tickSpacing
a.xoffset = (a.minPoint+a.maxPoint)/2
a.xfact = (a.maxPoint-a.minPoint)
return a
end
end # NiceScale
Base.iterate(n::NiceScale,v=1) = v>n.niceMax ? nothing : (v,v+n.tickSpacing)
# Base.start(n::NiceScale) = n.niceMin
# Base.next(n::NiceScale,v) = (v,v+n.tickSpacing)
# Base.done(n::NiceScale,v) = v>n.niceMax
Base.length(n::NiceScale) = Int64((n.niceMax-n.niceMin)/n.tickSpacing)+1
function niceNum(range::Real,round::Bool=false)
exponent = floor(log10(range))
fraction = range / 10^exponent
if round
if fraction <= 1.5 niceFraction = 1
elseif fraction <= 3 niceFraction = 2
elseif fraction <= 7 niceFraction = 5
else niceFraction = 5
end
else
if fraction <= 1 niceFraction = 1
elseif fraction <= 2 niceFraction = 2
elseif fraction <= 5 niceFraction = 5
else niceFraction = 10
end
end
return niceFraction * 10.0^exponent
end
scaled(x::Real,n::NiceScale) = (x-n.xoffset)/n.xfact
#end # Scaling
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] | 2.298292 | 761 |
__precompile__(true)
module NormalisingFlows
using Nabla, Distributions, Roots
import Base: rand, broadcast
import Distributions: AbstractMvNormal, logpdf, dim, params
export InverseNormalisingFlow, INF, logpdf, DiagonalStandardNormal, DiagStdNormal, dim,
invert, DiagAffine, Affine, Planar, Radial, Tanh, params, Invertible, nparams, apply,
logdetJ
export naive_init, naive_init!, identity_init, identity_init!
const RealVec = AbstractVector{<:Real}
const RealMat = AbstractMatrix{<:Real}
# Some initialisation functions. Invertibles and Flows will define concrete versions.
function naive_init end
function naive_init! end
function identity_init end
function identity_init! end
# Misc. definition.
softplus(x) = log1p(exp(x))
include("normal.jl")
include("invertibles.jl")
include("flows.jl")
end # module
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function prob(beta::Real, h::Real)
return 1.0/(1.0+exp(-beta*h)) # beta = 1/T
end
function stochastic_sign{T<:Real}(p::T)
return p > rand() ? one(T) : -one(T)
end
function activatefunc(beta::Float64, h::Float64)
return stochastic_sign(prob(beta,h))
end
function activatefunc(beta::Float64, h::Complex{Float64})
r_val = stochastic_sign(prob(beta,real(h)))
i_val = stochastic_sign(prob(beta,imag(h)))
return complex(r_val, i_val)
end
function activatefunc(beta::Float64, h::Quaternion{Float64})
r_val = stochastic_sign(prob(beta,real(h)))
i_val = stochastic_sign(prob(beta,imagi(h)))
j_val = stochastic_sign(prob(beta,imagj(h)))
k_val = stochastic_sign(prob(beta,imagk(h)))
return quaternion(r_val, i_val, j_val, k_val)
end
function internal_potential(W::AbstractArray{Quaternion{Float64}}, x::AbstractVector{Quaternion{Float64}},cue_pattern::AbstractVector{Float64},pos::Integer,s::Float64,L::Integer)
e1 = dot(W[:,pos],x)
if L==2
val = x[pos]
idx = pos*2
e2 = quaternion(cue_pattern[idx-1] * imagi(val),
cue_pattern[idx-1] * real(val),
cue_pattern[idx ] * imagk(val),
cue_pattern[idx ] * imagj(val))
elseif L==4
val = x[pos]
idx = pos*3
e2 = quaternion(cue_pattern[idx-2] * imagi(val),
cue_pattern[idx-2] * real(val),
cue_pattern[idx-1] * real(val),
cue_pattern[idx ] * real(val))
else
@assert(false,"unimplemented")
end
return (e1 + s*e2)
end
function internal_potential(W::AbstractArray{Complex{Float64}}, x::AbstractVector{Complex{Float64}},cue_pattern::AbstractVector{Float64},pos::Integer,s::Float64,L::Integer)
e1 = dot(W[:,pos],x)
if L==2
e2 = cue_pattern[pos] * complex(imag(x[pos]), real(x[pos]))
else
@assert(false,"unimplemented")
end
return (e1 + s*e2)
end
function internal_potential(W::AbstractArray{Float64}, x::AbstractVector{Float64},cue_pattern::AbstractVector{Float64},pos::Integer,s::Float64,L::Integer)
e1 = dot(W[:,pos],x)
if L==2
n = length(cue_pattern)
pos_cue = (pos -1)%n+1
if pos > n
e2 = cue_pattern[pos_cue] * x[pos_cue]
else
e2 = cue_pattern[pos_cue] * x[pos+n]
end
elseif L==4
n = round(Int,length(x)/L)
pos_cue = (pos -1)%n+1
block = ifloor((pos-1)/n)
@switch block begin
0; e2 = cue_pattern[pos_cue] * x[pos_cue+1*n]
1; e2 = cue_pattern[pos_cue] * x[pos_cue]
2; e2 = cue_pattern[pos_cue+n] * x[pos_cue]
3; e2 = cue_pattern[pos_cue+2*n] * x[pos_cue]
end
else
@assert(false,"unimplemented")
end
return (e1 + s*e2)
end
function update_cue_async!(net::HopfieldNetwork, cue_pattern::AbstractVector,L::Integer, s::Real, beta::Real)
ord = randperm(length(net.state))
for i in ord
h = internal_potential(net.weight,net.state,cue_pattern,i,s,L)
net.state[i] = activatefunc(beta, h)
end
end
function update_cue_sync!(net::HopfieldNetwork, cue_pattern::AbstractVector, L::Integer, s::Real, beta::Real)
state = copy(net.state)
for i = 1:length(net.state)
h = internal_potential(net.weight,state,cue_pattern,i,s,L)
net.state[i] = activatefunc(beta, h)
end
end
function associate!{T1 <: Number, T2 <: Real}(net::HopfieldNetwork, init_pattern::AbstractVector{T1}, cue_pattern::AbstractVector{T2},L::Integer, s::Real, beta::Real, gamma::Real, iterations::Integer = 1_000, sync::Bool = false)
copy!(net.state, init_pattern)
associate!(net,cue_pattern,L,s,beta,gamma, iterations,sync)
end
function associate!{T <: Number}(net::HopfieldNetwork, cue_pattern::AbstractVector{T},L::Integer, s::Real, beta::Real, gamma::Real, iterations::Integer = 1_000, sync::Bool = false)
if sync
update! = update_cue_sync!
else
update! = update_cue_async!
end
beta_step = beta
for i in 1:iterations
update!(net, cue_pattern,L, s, beta_step)
beta_step = beta_timestep(beta_step, gamma)
end
return copy(net.state)
end
function associate_step_async!{T <: Number}(net::HopfieldNetwork, cue_pattern::AbstractVector{T},L::Integer, s::Real, beta::Real, gamma::Real)
update_cue_async!(net, cue_pattern, L, s, beta)
return beta_timestep(beta, gamma)
end
function associate_step_sync!{T <: Number}(net::HopfieldNetwork, cue_pattern::AbstractVector{T},L::Integer, s::Real, beta::Real, gamma::Real)
update_cue_sync!(net, cue_pattern, L, s, beta)
return beta_timestep(beta, gamma)
end
function beta_timestep(beta::Real, gamma::Real)
return gamma * beta;
end
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8,
198,
197,
7783,
34236,
1635,
12159,
26,
198,
437,
628
] | 2.365468 | 1,836 |
using Pixell
using Test
import Pixell: degree, arcminute
using DelimitedFiles
include("test_geometry.jl") # creating geometries and sky ↔ pix
include("test_enmap.jl") # enmap features and manipulation
include("test_transforms.jl")
include("test_distance_transform.jl")
include("test_io.jl")
include("test_plot.jl")
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] | 3.066667 | 105 |
using SpikingNetworks
parseParameters"""
τ = 10
σ=80
Vₜ=0.8
Vᵣ=0
N=100
W=0.1*(ones(N,N)-diagm(ones(N)))"""
parseEquations"""
dv/dt = (Iₑ(t)-v+σ*ξ(t)+W⊙sigmoid(v-0.5))/τ
Iₑ(t)=0.5"""
net=init"""
N=N
v=rand(Vᵣ:0.01:Vₜ,N)"""
spike"v.>Vₜ"
reset"v[i]=Vᵣ"
net.dt=0.1
@time run!(net,100/net.dt)
time,rate=activity(net)
using MatlabPlot
mplot(time,rate)
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] | 1.610092 | 218 |
let
roadway,junction=gen_intersection(roadlength=30.0)
connect_two_seg!(roadway.segments[2],roadway.segments[3],roadway)
connect_two_seg!(roadway.segments[4],roadway.segments[5],roadway)
connect_two_seg!(roadway.segments[6],roadway.segments[7],roadway)
connect_two_seg!(roadway.segments[8],roadway.segments[1],roadway)
doc,r = initialize_XML()
convert_roadway!(r,roadway)
junctions = [junction]
handle_junctions(r,junctions,roadway)
r1 = root(doc)
r1_id = []
for child1 in eachelement(r1)
if haskey(child1, "id")
push!(r1_id,child1["id"])
end
for child2 in eachelement(child1)
if haskey(child2, "id")
push!(r1_id,child2["id"])
end
end
end
doc2 = readxml("test_out.xodr")
r2 = root(doc2)
r2_id = []
for child1 in eachelement(r2)
if haskey(child1, "id")
push!(r2_id,child1["id"])
end
for child2 in eachelement(child1)
if haskey(child2, "id")
push!(r2_id,child2["id"])
end
end
end
@test r1_id == r2_id
end
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374,
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198,
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] | 1.871126 | 613 |
"""
`T` from page `d.jl`.
Links:
- [`ccall`](@ref)
- [`while`](@ref)
- [`@time`](@ref)
- [`T`](@ref)
- [`f`](@ref)
- [`f(x)`](@ref)
- [`f(x, y)`](@ref)
- [`f(::Any, ::Any, ::Any)`](@ref)
"""
type T end
"""
`T` from page `d.jl`.
Links:
- [`ccall`](@ref)
- [`while`](@ref)
- [`@time`](@ref)
- [`T(x)`](@ref)
- [`T(x, y)`](@ref)
- [`T(x, y, z)`](@ref)
- [`f`](@ref)
- [`f(x)`](@ref)
- [`f(x, y)`](@ref)
- [`f(::Any, ::Any, ::Any)`](@ref)
"""
T(x) = T()
"""
`T` from page `d.jl`.
Links:
- [`ccall`](@ref)
- [`while`](@ref)
- [`@time`](@ref)
- [`T()`](@ref)
- [`T(x)`](@ref)
- [`T(x, y)`](@ref)
- [`T(x, y, z)`](@ref)
- [`f`](@ref)
- [`f(x)`](@ref)
- [`f(x, y)`](@ref)
- [`f(::Any, ::Any, ::Any)`](@ref)
"""
T(x, y) = T()
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] | 1.556503 | 469 |
using NSDE
using Test
@testset "NSDE.jl" begin
# Write your tests here.
end
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using Quaternions
using StaticArrays
#using ArrayFire
include("matrix.jl")
include("vector.jl")
"""
TODO
"""
function frustum{T}(left::T, right::T, bottom::T, top::T, znear::T, zfar::T)
(right == left || bottom == top || znear == zfar) && return eye(Mat4x4(T))
T[
2*znear/(right-left) 0 0 0
0 2*znear/(top-bottom) 0 0
(right+left)/(right-left) (top+bottom)/(top-bottom) (-(zfar+znear)/(zfar-znear)) -(2*znear*zfar) / (zfar-znear)
0 0 -1 0
]
end
"""
TODO
"""
function projection_perspective{T}(fovy::T, aspect::T, znear::T, zfar::T)
(znear == zfar) && error("znear ($znear) must be different from tfar ($zfar)")
zfn = 1/(zfar-znear)
t = tan(fovy * 0.5)
h = T(tan(fovy * pi / 360) * znear)
w = T(h * aspect)
left = -w
right = w
bottom = -h
top = h
frustum(-w, w, -h, h, znear, zfar)
end
"""
TODO
"""
function projection_orthographic{T}(left::T,right::T,bottom::T,top::T,znear::T,zfar::T)
(right==left || bottom==top || znear==zfar) && return eye(Mat4x4(T))
T[
2/(right-left) 0 0 0
0 2/(top-bottom) 0 0
0 0 -2/(zfar-znear) 0
-(right+left)/(right-left) -(top+bottom)/(top-bottom) -(zfar+znear)/(zfar-znear) 1
]
end
"""
TODO
"""
function translation{T}(t::Array{T,1})
lt = length(t)
T[
1 0 0 (lt<1?0:t[1])
0 1 0 (lt<2?0:t[2])
0 0 1 (lt<3?0:t[3])
0 0 0 (lt<4?1:t[4])
]
end
"""
TODO
"""
function rotation{T}(r::Array{T,1})
lr = length(r)
T[
1 0 0 0
0 1 0 0
0 0 1 0
(lr<1?0:r[1]) (lr<2?0:r[2]) (lr<3?0:r[3]) (lr<4?1:r[4])
]
end
"""
TODO
"""
function rotation{T}(q::Quaternion{T})
sx, sy, sz = 2q.s*q.v1, 2q.s*q.v2, 2q.s*q.v3
xx, xy, xz = 2q.v1^2, 2q.v1*q.v2, 2q.v1*q.v3
yy, yz, zz = 2q.v2^2, 2q.v2*q.v3, 2q.v3^2
T[
1-(yy+zz) xy+sz xz-sy 0
xy-sz 1-(xx+zz) yz+sx 0
xz+sy yz-sx 1-(xx+yy) 0
0 0 0 1
]
end
"""
TODO
"""
function computeRotation{T}(r::Array{T,1})
lr = length(r)
(lr<3) && error("rotation has less than 3 elements!")
dirBackwards= T[-1,0,0]
dirRight = T[0,0,1]
dirUp = T[0,1,0] #cross(dirRight, dirBackwards)
q = qrotation(dirRight, r[3]) * qrotation(dirUp, r[1]) * qrotation(dirBackwards, r[2])
#q = qrotation(T[1,1,1],0)
#if lr<3 q = qrotation(dirRight, r[3]) end
#if lr<1 q *= qrotation(dirUp, r[1]) end
#if lr<2 q *= qrotation(dirBackwards, r[2]) end
rotation(q)
end
"""
TODO
"""
function scaling{T}(s::Array{T})
ls = length(s)
T[
(ls<1?1:s[1]) 0 0 0
0 (ls<2?1:s[2]) 0 0
0 0 (ls<3?1:s[3]) 0
0 0 0 (ls<4?1:s[4])
]
end
"""
TODO
"""
function transform{T}(t::Array{T,1},r::Array{T,1},s::Array{T,1})
#=
lt = length(t)
lr = length(r)
ls = length(s)
T[
(ls<1?1:s[1]) 0 0 (lt<1?0:t[1])
0 (ls<2?1:s[2]) 0 (lt<2?0:t[2])
0 0 (ls<3?1:s[3]) (lt<3?0:t[3])
(lr<1?0:r[1]) (lr<2?0:r[2]) (lr<3?0:r[3]) (lt<4?1:t[4])*(lr<4?1:r[4])*(ls<4?1:s[4])
]
=#
translation(t)*computeRotation(r)*scaling(s)
end
"""
TODO
"""
function ViewRH{T}(eye::Array{T,1}, yaw::T, pitch::T)
(length(eye) < 3) && error("eye has less than 3 elements!")
# If the pitch and yaw angles are in degrees,
# they need to be converted to radians. Here
# I assume the values are already converted to radians.
cosPitch = cos(pitch)
sinPitch = sin(pitch)
cosYaw = cos(yaw)
sinYaw = sin(yaw)
xaxis = T[ cosYaw, 0, -sinYaw ]
yaxis = T[ sinYaw * sinPitch, cosPitch, cosYaw * sinPitch ]
zaxis = T[ sinYaw * cosPitch, -sinPitch, cosPitch * cosYaw ]
eaxis = T[ -dot(xaxis,eye), -dot(yaxis,eye), -dot(zaxis,eye) ]
# Create a 4x4 view matrix from the right, up, forward and eye position vectors
T[
xaxis[1] yaxis[1] zaxis[1] eaxis[1]*0
xaxis[2] yaxis[2] zaxis[2] eaxis[2]*0
xaxis[3] yaxis[3] zaxis[3] eaxis[3]*0
eaxis[1]*1 eaxis[2]*1 eaxis[3]*1 1
]
end
"""
TODO
"""
function lookat{T}(eye::Array{T,1}, lookAt::Array{T,1}, up::Array{T,1})
(length(eye) < 3) && error("eye has less than 3 elements!")
(length(lookAt) < 3) && error("lookAt has less than 3 elements!")
(length(up) < 3) && error("up has less than 3 elements!")
zaxis = normalize(eye-lookAt)
xaxis = normalize(cross(up,zaxis))
yaxis = normalize(cross(zaxis, xaxis))
eaxis = T[ -dot(xaxis,eye), -dot(yaxis,eye), -dot(zaxis,eye) ]
T[
xaxis[1] yaxis[1] zaxis[1] 0;
xaxis[2] yaxis[2] zaxis[2] 0;
xaxis[3] yaxis[3] zaxis[3] 0;
eaxis[1] eaxis[2] eaxis[3] 1
]
end
"""
TODO
"""
forward{T}(m::Array{T, 2}) = T[m[3,1],m[3,2],m[3,3]]
"""
TODO
"""
right{T}(m::Array{T, 2}) = T[m[1,1],m[1,2],m[1,3]]
"""
TODO
"""
up{T}(m::Array{T, 2}) = T[m[2,1],m[2,2],m[2,3]]
#=
template <typename T, precision P>
GLM_FUNC_QUALIFIER tquat<T, P> angleAxis(T const & angle, tvec3<T, P> const & v)
{
tquat<T, P> Result(uninitialize);
T const a(angle);
T const s = glm::sin(a * static_cast<T>(0.5));
Result.w = glm::cos(a * static_cast<T>(0.5));
Result.x = v.x * s;
Result.y = v.y * s;
Result.z = v.z * s;
return Result;
}
function mat4x4ToMat3x3{T}(q)
qxx = (q.x * q.x)
qyy = (q.y * q.y)
qzz = (q.z * q.z)
qxz = (q.x * q.z)
qxy = (q.x * q.y)
qyz = (q.y * q.z)
qwx = (q.w * q.x)
qwy = (q.w * q.y)
qwz = (q.w * q.z)
Result = Mat3x3(T)
Result[0][0] = T(1) - T(2) * (qyy + qzz);
Result[0][1] = T(2) * (qxy + qwz);
Result[0][2] = T(2) * (qxz - qwy);
Result[1][0] = T(2) * (qxy - qwz);
Result[1][1] = T(1) - T(2) * (qxx + qzz);
Result[1][2] = T(2) * (qyz + qwx);
Result[2][0] = T(2) * (qxz + qwy);
Result[2][1] = T(2) * (qyz - qwx);
Result[2][2] = T(1) - T(2) * (qxx + qyy);
Result
end
=#
# glm::mat4 rotate = glm::transpose(glm::toMat4(m_Rotation));
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function test_sgd_solver(backend)
println("-- Testing simple SGD solver call")
registry_reset(backend)
srand(12345678)
############################################################
# Prepare Random Data
############################################################
N = 5 # works with arbitrary minibatch size as long as
# N == batch_size in MemoryDataLayer so it cycles through
# and gets the same data during forward()
M = 10
P = 4
X = rand(M, N)
W = rand(M, P)
B = rand(P, 1)
Y = (W'*X .+ B)
Y = Y + 0.01*randn(size(Y))
############################################################
# Define network
############################################################
data_layer = MemoryDataLayer(batch_size=N, data=Array[X,Y])
w1 = InnerProductLayer(neuron=Neurons.Sigmoid(), name="ip1",output_dim=20, tops=[:a], bottoms=[:data])
w2 = InnerProductLayer(neuron=Neurons.Identity(), name="ip2",output_dim=4, tops=[:b], bottoms=[:a])
loss_layer = SquareLossLayer(name="loss", bottoms=[:b, :label] )
net = Net("TEST", backend, [w1, w2, loss_layer, data_layer])
# Make a Solver with max iterations 2
method = Adadelta()
params = make_solver_parameters(method,
max_iter=2,
beta1=0.9,
beta2=0.999,
epsilon=1e-8,
load_from="")
solver = Solver(method, params)
solve(solver, net)
# TODO check gradient updates
# TODO check snapshot loading
# TODO check statistic saving
# TODO check other lr policies
# TODO check other mom policies
destroy(net)
end
if test_cpu
test_sgd_solver(backend_cpu)
end
if test_gpu
test_sgd_solver(backend_gpu)
end
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"""
utils.jl
Provides helper functions to `particle_filtering.jl` such as PGFPlots, rmse compute
Also providese helpers used by `scripts/helpers.jl` such as `truncate_vecs`
"""
# function: get frenet s
"""
function get_frenet_s(scene;car_id=-1)
# Examples
```julia
true_next_pos = get_frenet_s(true_next_scene,car_id=1)
```
"""
function get_frenet_s(scene;car_id=-1)
if car_id==-1 print("get_frenet_s says: Give valid car id") end
veh = scene[findfirst(car_id,scene)]
return veh.state.posF.s
end
"""
function get_veh_info(scene;car_id = -1)
- Get position and velocity of specific vehicle from scene
"""
function get_veh_info(scene;car_id = -1)
@assert car_id>0
pos=scene[findfirst(car_id,scene)].state.posF.s
vel = scene[findfirst(car_id,scene)].state.v
return pos,vel
end
# function: get lane id
"""
function get_lane_id(scene,car_id)
# Examples
```julia
get_lane_id(scene,1)
```
"""
function get_lane_id(scene,car_id)
veh = scene[findfirst(car_id,scene)]
return veh.state.posF.roadind.tag.lane
end
# function: get lane change probability
"""
function get_lane_change_prob(start_scene,particle;car_id=-1,num_samplings=10)
- Probability of lane changing start from `start_scene`
- hallucinating using `particle` for `car_id` using `num_samplings` hallucinations
# Examples
```julia
lp = get_lane_change_prob(scene,particle,car_id = 1,roadway=road_ext)
```
"""
function get_lane_change_prob(f::FilteringEnvironment,start_scene,particle;car_id=-1,
num_samplings=10)
if car_id==-1 @show "get_lane_change_prob says: Please give valid car_id" end
start_lane = get_lane_id(start_scene,car_id)
changed_count = 0; unchanged_count = 0
for i in 1:num_samplings
hpos,hlane = hallucinate_a_step(f,start_scene,particle,car_id=car_id)
if hlane == start_lane
unchanged_count += 1
else
changed_count += 1
end
end
return (changed_count+1)/(num_samplings+2)
end
# function: Generate uniform sampling to start the initial particle matrix
"""
function initial_pmat(;limits,num_particles,seed)
- Generate initial particle matrix with `num_particles` particles with every col being a diff particle
- Range of values that parameters can take is specified in `limits`. Should be num_params rows x 2 cols
# Examples
```julia
limits = [10. 40.;0.1 10.;0.5 5.;1. 10.;0. 1.;-1. 1.;-20. 20.;0. 1.]
initial_pmat(limits=limits,num_particles=10,seed=4)
```
"""
function initial_pmat(;limits,num_particles,seed)
Random.seed!(seed)
num_params = size(limits,1)
p_mat = fill(0.,num_params,num_particles)
for i in 1:num_params
p_mat[i,:] = rand(Uniform(limits[i,1],limits[i,2]),1,num_particles)
end
return p_mat
end
# function: pgfplots 2 gif using Reel
"""
function pgfplots2gif(plots;filename="output.gif")
- Make a video using an array of plots. Uses the Reel library.
# Caveat
- Only works with .gif output type. If use .mp4, errors saying process exited ffmpeg
- Relies on the setting Reel.extension
Reel.extension(m::MIME"image/svg+xml") = "svg"
"""
function pgfplots2gif(plots;filename="output.gif")
@assert typeof(filename) == String
frames = Frames(MIME("image/svg+xml"), fps=1)
for (i,plt) in enumerate(plots)
push!(frames, plt)
#PGFPlots.save("test/media/$i.pdf",plt) # Store the pic for debugging
end
write(filename, frames)
print("pgfplots2gif: Making animation called $(filename)")
return nothing
end # End of the reel gif writing function
# function: make pairwise particle variation videos, what pairs to make is the question
"""
- We have a list with corresponding particle matrix at every iteration of filtering
- We shall scatter two columns of said matrix
- We shall make a video with said scatter at every timestep
# Examples
```julia
seed = 2; num_p = 500
Random.seed!(seed)
final_p_mat,iterwise_p_mat = multistep_update(car_id=1,start_frame=2,last_frame=99,num_p=num_p);
plot_pairwise_particles(iterwise_p_mat,filename="test/media/seed2.gif")
```
"""
function plot_pairwise_particles(iterwise_p_mat;filename)
num_params = size(iterwise_p_mat[1],1) # Number of rows tells us the number of parameters
print("num_params = $num_params\n")
pairs = collect(combinations(collect(1:num_params),2))
num_pairs = length(pairs)
print("num_pairs = $num_pairs\n")
groupplots = PGFPlots.GroupPlot[]
# Parameter names. These better match the top of particle_filtering.jl
param_names = Dict(1=>"Desired velocity",2=>"Acceleration output noise",
3=>"Min time headway",4=>"Min separation",5=>"Politeness",6=>"Advantage threshold",
7=>"Headway sensor noise",8=>"Cooperation");
for i in 1:length(iterwise_p_mat)
print("plot_pairwise_particles: iternum = $i\n")
g = PGFPlots.GroupPlot(7,4)
p_mat = iterwise_p_mat[i]
for j in 1:num_pairs
kk = pairs[j]
param_1 = kk[1];param_2 = kk[2]
name_1 = param_names[param_1];name_2=param_names[param_2]
p = PGFPlots.Axis([PGFPlots.Plots.Scatter(p_mat[param_1,:],p_mat[param_2,:])],
xlabel=name_1,ylabel=name_2)
push!(g,p)
end
push!(groupplots,g)
end
pgfplots2gif(groupplots,filename=filename)
return nothing
end
"""
Plot specific pair of parameters eg: v_des vs cooperation
# Examples
```julia
plotspecific(iterwise_p_mat;filename="test/media/vdes_coop.gif")
```
"""
function plotspecific(iterwise_p_mat;filename)
plots=PGFPlots.Axis[]
param_names = Dict(1=>"Desired velocity",2=>"Acceleration output noise",
3=>"Min time headway",4=>"Min separation",5=>"Politeness",6=>"Advantage threshold",
7=>"Headway sensor noise",8=>"Cooperation");
name_1 = param_names[1] # 1 is for desired velocity
name_2 = param_names[8] # 8 is for cooperation
for i in 1:length(iterwise_p_mat)
p_mat = iterwise_p_mat[i]
p = PGFPlots.Axis([PGFPlots.Plots.Scatter(p_mat[1,:],p_mat[8,:])],
xlabel=name_1,ylabel=name_2)
push!(plots,p)
end
pgfplots2gif(plots,filename=filename)
return nothing
end
"""
function avg_dist_particles(p_mat,p_fin)
- Goal is to show that particle filering converges
- `p_mat` is a matrix with particles in every column, say at a certain iteration before convergence
- `p_fin` is the mean of the final particle set i.e. after convergence
- For every particle in `p_mat`, find its norm to `p_fin`. And return the mean of these distances
# Arguments
- `p_mat`: Matrix with particles in every column
- `p_fin`: num_paramx1 vector with the final particle
# Example
```julia
num_iter = length(iterwise_p_mat)
mean_dist_array = fill(0.,num_iter,1)
for i in 1:num_iter
p_mat = iterwise_p_mat[i]
mean_dist_array[i] = avg_dist_particles(p_mat,p_fin)
end
```
"""
function avg_dist_particles(p_mat,p_fin)
val = 0
num_particles = size(p_mat,2)
for i in 1:num_particles # loop over the particles
val+= norm(p_mat[:,i]-p_fin) # add norm distance to final particle
end
return val/num_particles # find mean of the norm distance to final particles
#return sum(sqrt.(sum((p_mat .- p_fin).^2,dims=1)))*1/size(p_mat,2)
end
# function: generate imitation trajectory
"""
function gen_imitation_traj(f::FilteringEnvironment,models;
id_list=[],start_frame=1,duration=10.)
- Use driver models obtained from filtering to generate imitation trajectory
# Example
```julia
veh_id_list = [6]
f = FilteringEnvironment()
new_models,final_particles,mean_dist = obtain_driver_models(f,veh_id_list,500,1,5)
imit_scene_list = gen_imitation_traj(f,new_models,id_list=veh_id_list)
```
"""
function gen_imitation_traj(f::FilteringEnvironment,models;
id_list=[],start_frame=1,duration=10.)
scene_real = f.traj[start_frame]
if !isempty(id_list) keep_vehicle_subset!(scene_real,id_list) end
nticks = Int(ceil(duration/f.timestep))
scene_list = simulate(scene_real,f.roadway,models,nticks,f.timestep)
return scene_list # Note: simulate appends scenes to the start scene
end
"""
- Idea is to have leader vehicles that are replayed from the data
- models has driver model associated to vehicles in id_list
- Not using `simulate` because we want to customize it. Thus use observe, propogate
- And then inserting the replay vehicles within the scene
# Example
```julia
f=FilteringEnvironment()
new_models,final_particles,mean_dist = obtain_driver_models(f,egoids,30,1,30)
imit_scene_list = imitation_with_replay(f,new_models,egoids=[28,29],replay_ids=[6,8,13])
```
"""
function imitation_with_replay(f::FilteringEnvironment,models;
egoids=[],replay_ids=[],start_frame=1,duration=10.)
print("egoids = $egoids\n")
nticks = Int(ceil(duration/f.timestep))
start_scene = deepcopy(f.traj[start_frame])
ego_replay_ids = deepcopy(egoids)
append!(ego_replay_ids,replay_ids)
print("ego_replay_ids = $(ego_replay_ids)\n")
print("start_scene = $start_scene\n")
keep_vehicle_subset!(start_scene,ego_replay_ids)
print("start_scene = $start_scene\n")
# Populate list of ego vehicles from egoids
ego_vehs = Vector{Entity}(undef,length(egoids))
for (i, egoid) in enumerate(egoids)
print("egoid = $egoid\n")
vehidx = findfirst(egoid, start_scene)
print("id = $vehidx\n")
ego_vehs[i] = start_scene[vehidx]
end
scenes = [Scene(Entity{VehicleState,VehicleDef,Int64},
length(start_scene)) for i=1:nticks+1]
copyto!(scenes[1], start_scene)
for tick in 1:nticks
print("tick = $tick")
#empty!(scenes[tick + 1])
traj_scene = deepcopy(f.traj[start_frame+tick])
keep_vehicle_subset!(traj_scene,replay_ids)
copyto!(scenes[tick+1],traj_scene)
for (i, ego_veh) in enumerate(ego_vehs)
print("scenes[tick] = $(scenes[tick])\n")
observe!(models[ego_veh.id], scenes[tick], f.roadway, ego_veh.id)
a = rand(models[ego_veh.id])
veh_state_p = propagate(ego_veh, a, f.roadway, f.timestep)
push!(scenes[tick + 1], Entity(veh_state_p, ego_veh.def, ego_veh.id))
ego_vehs[i] = Entity(ego_veh,veh_state_p)
end
end
return scenes
end
# function: compute rmse of generated trajectory vs true trajectory
"""
function compute_rmse(true_scene_list,halluc_scene_list;id_list)
- Compute rmse position and velocity between `halluc_scene_list` and `true_scene_list`
- `true_scene_list` is the ground truth demonstration trajectory
- `imit_scene_list` is generated by running vehicles using parameters that we want for the driver model
# Returns
- `rmse_pos::Dict{Int64,Vector{Float64}}`: Key is vehid. Value is array. Each elem is timewise rmse pos value for that veh_id
- `rmse_vel::Dict{Int64,Vector{Float64}}`: Key is vehid. Value is array. Each elem is timewise rmse vel value for that veh_id
# Examples
```julia
imit_scene_list = gen_imitation_traj(f,new_models,id_list=veh_id_list)
true_scene_list = f.traj[]
rmse_pos_dict,rmse_vel_dict = compute_rmse(true_scene_list,imit_scene_list,id_list=[1,2,3])
```
"""
function compute_rmse(true_scene_list,imit_scene_list;id_list=[])
@assert length(true_scene_list) == length(imit_scene_list)
rmse_pos = Dict{Int64,Vector{Float64}}()
rmse_vel = Dict{Int64,Vector{Float64}}()
for veh_id in id_list
rmse_pos[veh_id] = []
rmse_vel[veh_id] = []
end
for i in 1:length(true_scene_list)
scene_halluc = imit_scene_list[i]
demo_scene_target = true_scene_list[i]
for veh_id in id_list
demo_veh = demo_scene_target[findfirst(veh_id,demo_scene_target)]
ego_veh = scene_halluc[findfirst(veh_id,scene_halluc)]
push!(rmse_pos[veh_id],norm(demo_veh.state.posG[1:2]-ego_veh.state.posG[1:2]))
push!(rmse_vel[veh_id],norm(demo_veh.state.v - ego_veh.state.v))
end
end
return rmse_pos,rmse_vel
end
# function: Combine carwise rmse into one metric by averaging over cars
"""
function rmse_dict2mean(rmse_dict)
- Take dict of carwise rmse value and return an array with mean of rmse taken over cars
# Returns
- `carmean_rmse`: Vector with length same as num timesteps.
Each element is the rmse value averaged over all cars at that particular timestep
# Examples
```julia
rmse_pos_dict,rmse_vel_dict = compute_rmse(scene_list_1,scene_list_2,id_list=egoids)
rmse_pos = rmse_dict2mean(rmse_pos_dict);rmse_vel = rmse_dict2mean(rmse_vel_dict)
rmse_pos = reshape(rmse_pos,length(rmse_pos),);rmse_vel = reshape(rmse_vel,length(rmse_vel),)
p_pos = PGFPlots.Plots.Linear(collect(1:length(rmse_pos)),rmse_pos,legendentry="rmse pos")
p_vel = PGFPlots.Plots.Linear(collect(1:length(rmse_vel)),rmse_vel,legendentry="rmse vel")
rmse_axis = PGFPlots.Axis([p_pos,p_vel],xlabel="timestep",ylabel="rmse",title="rmse pos and vel")
display(rmse_axis)
```
"""
function rmse_dict2mean(rmse_dict)
num_veh = length(collect(keys(rmse_dict))) # Find length of the vector of keys
num_iter = length(rmse_dict[collect(keys(rmse_dict))[1]]) # Find length of value contained in 1st key
rmse_array = fill(0.,num_iter,num_veh)
i = 0
for (k,v) in rmse_dict
i = i+1
rmse_vals = reshape(v,length(v),1)
rmse_array[:,i] = rmse_vals
end
carmean_rmse = mean(rmse_array,dims=2)
carmean_rmse = reshape(carmean_rmse,length(carmean_rmse),)
return carmean_rmse
end
# Function: Test collisons for list of vehicle ids
"""
- Adapt the get collision to work with vehicle ids and give us collision metrics within notebook
- Source: `AutomotiveDrivingModels/src/Collision-Checkers/Minkowski.jl`
# Example
```julia
f = FilteringEnvironment()
c = collision_check(f.traj[1],[6,8])
c.is_colliding
```
"""
function collision_check(scene, veh_id_list, mem::CPAMemory=CPAMemory())
N = length(veh_id_list)
for (a,A) in enumerate(veh_id_list)
vehA = scene[findfirst(A,scene)]
to_oriented_bounding_box!(mem.vehA, vehA)
for b in a +1 : length(veh_id_list)
B = veh_id_list[b]
vehB = scene[findfirst(B,scene)]
if is_potentially_colliding(vehA, vehB)
to_oriented_bounding_box!(mem.vehB, vehB)
if is_colliding(mem)
return CollisionCheckResult(true, A, B)
end
end
end
end
CollisionCheckResult(false, 0, 0)
end
# function: Find the collisions instances to extract collision metrics
"""
function test_collision
- Assess list of scenes for collision information
# Returns
- Binary array with 0 if no collision at that timestep, and 1 if any collision at that timestep
# Examples
```julia
```
"""
function test_collision(scenes_list,id_list)
collisions_array = fill(0.,length(scenes_list))
for (i,scene) in enumerate(scenes_list)
if collision_check(scene,id_list).is_colliding
collisions_array[i] = 1
end
end
return collisions_array
end
"""
function frac_colliding_timesteps(coll_mat)
- `coll_mat` has different scenarios in different columns
- Each column has 1 in every timestep where there is at least one pair of cars colliding
- We take all the timesteps i.e. N scenarios x H timesteps in each scenario
- Find the fraction of timesteps that have a collision
"""
function frac_colliding_timesteps(coll_mat)
n = size(coll_mat,2) # num columns i.e. scenarios
h = size(coll_mat,1) # num timesteps per scenario
return sum(coll_mat)/(n*h)
end
"""
function pgfplot_vector(vec;leg = "nolegend")
- Plot a vector using PGFPlots
# Example
```julia
plot_rmse_pf = pgfplot_vector(pos_pf,leg="pf")
```
"""
function pgfplot_vector(vec;leg = "nolegend")
vec = reshape(vec,length(vec),)
return PGFPlots.Plots.Linear(collect(1:length(vec)),vec,legendentry=leg)
end
# function to truncate vectors to shortest length one
"""
function truncate_vecs(list_of_vectors)
- Rmse vec lengths will not be same as simulation durations not the same
- Select the shortest length rmse and truncate other scenarios to same length
# Example
```julia
intset = collect(1:10) #integer set to draw random numbers from
l = [rand(intset,4,1),rand(intset,5,1),rand(intset,6,1),rand(intset,10,1),rand(intset,3,1)]
a = truncate_vecs(l)
```
"""
function truncate_vecs(list_of_vectors)
shortest_length = 10000
numvec = length(list_of_vectors)
for i in 1:numvec
curr_len = length(list_of_vectors[i])
if curr_len < shortest_length
shortest_length = curr_len
end
end
#print("longest length = $(longest_length)\n")
new_list = []
for j in 1:numvec
#print("j = $j\n")
# pad with zeros
curr_vec = list_of_vectors[j]
truncated_vec = curr_vec[1:shortest_length]
#print("padded_vec = $(padded_vec)\n")
push!(new_list,truncated_vec)
end
return hcat(new_list...)
end
# Elongate vectors to longest in the list by padding zeros
"""
function pad_zeros(list_of_vectors)
- We need to append zeros to the shorter rmse vectors to make all lengths equal
# Example
```julia
intset = collect(1:10) #integer set to draw random numbers from
l = [rand(intset,4,1),rand(intset,5,1),rand(intset,6,1),rand(intset,10,1),rand(intset,3,1)]
a = pad_zeros(l)
```
"""
function pad_zeros(list_of_vectors)
longest_length = -1
numvec = length(list_of_vectors)
for i in 1:numvec
curr_len = length(list_of_vectors[i])
if curr_len > longest_length
longest_length = curr_len
end
end
#print("longest length = $(longest_length)\n")
new_list = []
for j in 1:numvec
#print("j = $j\n")
# pad with zeros
curr_vec = list_of_vectors[j]
lengthdiff = longest_length-length(curr_vec)
padded_vec = vcat(curr_vec,fill(0.,lengthdiff,1))
#print("padded_vec = $(padded_vec)\n")
push!(new_list,padded_vec)
end
return hcat(new_list...)
end
"""
- Get a list of scenes from replay trajectory
- This will be used to compute metrics of real driving behavior
# Example
```julia
f = FilteringEnvironment()
models,id_list,ts,te = JLD.load(filename,"m","veh_id_list","ts","te")
scene_list = replay_scenelist(f,id_list=id_list,ts=ts,te=te)
```
"""
function replay_scenelist(f::FilteringEnvironment;id_list=[],ts,te)
scene_list = deepcopy(f.traj[ts:te])
for scene in scene_list
if !isempty(id_list) keep_vehicle_subset!(scene,id_list) end
end
return scene_list
end
"""
function reality_metrics(scene_list)
- Compute things about the driving trajectory to assess how `real` the traffic is
# Example
```julia
f = FilteringEnvironment()
filename = "media/upper_4.jld"
models,id_list,ts,te = JLD.load(filename,"m","veh_id_list","ts","te")
scene_list_true = replay_scenelist(f,id_list=id_list,ts=ts,te=te)
stopfrac_true,brakefrac_true = reality_metrics(f,scene_list_true,id_list=id_list)
scene_real = deepcopy(f.traj[ts])
if !isempty(id_list) keep_vehicle_subset!(scene_real,id_list) end
nticks = te-ts+1
scene_list_generated = simulate(start_scene,f.roadway,models,nticks,f.timestep)
stopfrac_gen,brakefrac_gen = reality_metrics(f,scene_list_generated,id_list=id_list)
```
"""
function reality_metrics(f::FilteringEnvironment,scene_list;id_list=[])
# Calculate number of timesteps where more than one car almost stopped
# This is based on visual in May 7 update slides turing test
numscenes = length(scene_list)
stopped_scenes = fill(0.,numscenes,)
for (i,scene) in enumerate(scene_list)
laggards = 0
for veh in scene
if veh.state.v < 2
laggards += 1
end
end
if laggards>1
stopped_scenes[i] = 1
end
end
stopfrac = sum(stopped_scenes)/numscenes
# Calculate hard deceleration instances
numvehs = length(id_list)
acc_mat = fill(0.,numscenes-1,numvehs) #-1 because 1st elem of acc is `missing`
#print("size(acc_mat) = $(size(acc_mat))\n")
for (j,veh_id) in enumerate(id_list)
print("veh_id = $veh_id\n")
acc_trace = acc(f.roadway,scene_list,veh_id)
trace = Float64.(acc_trace[2:end]) # Convert Union missing type to just Float
#popfirst!(trace) # Remove the first element i.e. missing
#print("size(trace) = $(size(trace))\n")
trace = reshape(trace,numscenes-1,)
#print("size(trace) = $(size(trace))\n")
acc_mat[:,j] .= trace
end
num_harddecel = 0
for jj in 1:numscenes-1
if any(x->x<-2,acc_mat[jj,:]) # If any vehicle shows accel less than -2, its hard decel
num_harddecel += 1
end
end
#print("num_harddecel = $(num_harddecel)\n")
harddecelfrac = num_harddecel/(numscenes-1)
return stopfrac,harddecelfrac
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5501,
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318,
4628,
413,
786,
42721,
325,
1426,
1988,
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4600,
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62,
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3712,
35,
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13,
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13,
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7,
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325,
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1930,
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1930,
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26933,
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2625,
16514,
395,
538,
1600,
2645,
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7839,
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7,
26224,
325,
62,
11600,
4008,
58,
16,
11907,
8,
1303,
9938,
4129,
286,
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7763,
287,
352,
301,
1994,
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220,
220,
220,
42721,
325,
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18747,
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3419,
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66,
796,
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] | 2.403041 | 8,746 |
module NamedVectors
using Printf: @printf
using ..Factories: Inference,TypeFactory,FunctionFactory,addargs!,extendbody!
using ..Factories: MixEscaped,Escaped,UnEscaped
using ..TypeTraits: efficientoperations
export NamedVector,@namedvector
export HomoNamedVector,@homonamedvector
"""
NamedVector
Abstract type for all named vectors.
"""
abstract type NamedVector end
"""
getindex(nv::NamedVector,index::Int)
Get the value by the `[]` syntax.
"""
Base.getindex(nv::NamedVector,index::Int)=getfield(nv,index)
"""
setindex!(nv::NamedVector,value,index::Int)
Set the value by the `[]` syntax if mutable.
"""
Base.setindex!(nv::NamedVector,value,index::Int)=setfield!(nv,index,value)
"""
==(nv1::NamedVector,nv2::NamedVector) -> Bool
isequal(nv1::NamedVector,nv2::NamedVector) -> Bool
Overloaded equivalent operator. Two named vector are equal to each other if and only if their keys as well as their values are equal to each other.
!!! note
It is not necessary for two named vectors to be of the same concrete type to be equal to each other.
"""
Base.:(==)(nv1::NamedVector,nv2::NamedVector)=nv1|>keys==nv2|>keys && nv1|>values==nv2|>values
Base.isequal(nv1::NamedVector,nv2::NamedVector)=isequal(nv1|>keys,nv2|>keys) && isequal(nv1|>values,nv2|>values)
"""
<(nv1::NamedVector,nv2::NamedVector) -> Bool
isless(nv1::NamedVector,nv2::NamedVector) -> Bool
Compare two named vectors and judge whether the first is less than the second.
"""
Base.:<(nv1::NamedVector,nv2::NamedVector) = <(efficientoperations,nv1,nv2)
Base.isless(nv1::NamedVector,nv2::NamedVector)=isless(efficientoperations,nv1,nv2)
"""
show(io::IO,nv::NamedVector)
Show a concrete `NamedVector`.
"""
Base.show(io::IO,nv::NamedVector)=@printf io "%s(%s)" nv|>typeof|>nameof join(repr.(nv|>values),',')
"""
hash(nv::NamedVector,h::UInt)
Hash a concrete `NamedVector`.
"""
Base.hash(nv::NamedVector,h::UInt)=hash(nv|>values,h)
"""
convert(::Type{Tuple},nv::NamedVector) -> Tuple
convert(::Type{NV},nv::Tuple) where NV<:NamedVector -> NV
Convert a named vector to tuple and vice versa.
"""
@generated Base.convert(::Type{Tuple},nv::NamedVector)=Expr(:tuple,(:(getfield(nv,$i)) for i=1:(nv|>fieldcount))...)
function Base.convert(::Type{NV},nv::Tuple) where NV<:NamedVector
@assert NV|>fieldcount==nv|>length "convert error: dismatched length between $NV($(NV|>fieldcount)) and input tuple($(nv|>length))."
return NV(nv...)
end
"""
length(::Type{NV}) where NV<:NamedVector -> Int
length(nv::NamedVector) -> Int
Get the length of a concrete `NamedVector`.
"""
Base.length(::Type{NV}) where NV<:NamedVector=NV|>fieldcount
Base.length(nv::NamedVector)=nv|>typeof|>length
"""
zero(::Type{NV}) where NV<:NamedVector -> NV
zero(nv::NamedVector) -> typeof(nv)
Get a concrete `NamedVector` with all values being zero.
"""
@generated Base.zero(::Type{NV}) where NV<:NamedVector=(zeros=(zero(fieldtype(NV,i)) for i=1:(NV|>fieldcount));:(NV($(zeros...))))
Base.zero(nv::NamedVector)=nv|>typeof|>zero
"""
iterate(nv::NamedVector,state=1)
iterate(rv::Iterators.Reverse{<:NamedVector},state=length(rv.itr))
Iterate or reversely iterate over the values of a concrete `NamedVector`.
"""
Base.iterate(nv::NamedVector,state=1)=state>length(nv) ? nothing : (getfield(nv,state),state+1)
Base.iterate(rv::Iterators.Reverse{<:NamedVector},state=length(rv.itr))=state<1 ? nothing : (getfield(rv.itr,state),state-1)
"""
keys(nv::NamedVector) -> NTuple(nv|>fieldcount,Symbol)
values(nv::NamedVector) -> Tuple
pairs(nv::NamedVector) -> Base.Generator
Iterate over the names.
"""
Base.keys(nv::NamedVector)=nv|>typeof|>fieldnames
Base.values(nv::NamedVector)=convert(Tuple,nv)
Base.pairs(nv::NamedVector)=Base.Generator(=>,keys(nv),values(nv))
"""
replace(nv::NamedVector;kwargs...) -> typeof(nv)
Return a copy of a concrete `NamedVector` with some of the field values replaced by the keyword arguments.
"""
Base.replace(nv::NamedVector;kwargs...)=replace(efficientoperations,nv;kwargs...)
"""
map(f,nvs::NV...) where NV<:NamedVector -> NV
Apply function `f` elementwise on the input named vectors.
"""
@generated function Base.map(f,nvs::NV...) where NV<:NamedVector
exprs=Vector{Expr}(undef,NV|>fieldcount)
for i=1:length(exprs)
tmp=[:(nvs[$j][$i]) for j=1:length(nvs)]
exprs[i]=:(f($(tmp...)))
end
return :(($NV)($(exprs...)))
end
"""
@namedvector structdef::Expr
Decorate a "raw" struct to be a subtype of `NamedVector`. Here, "raw" means that the input struct has no explicit supertype and no inner constructors.
"""
macro namedvector(structdef::Expr)
tf=TypeFactory(structdef)
@assert tf.supertype==Inference(:Any) "@namedvector error: no explicit supertype except `Any` is allowed."
@assert length(tf.constructors)==0 "@namedvector error: no inner constructor is allowed."
tf.supertype=Inference(:NamedVector)
paramnames=tuple((param.name for param in tf.params)...)
fieldnames=tuple((field.name for field in tf.fields)...)
fldnm=FunctionFactory(name=:(Base.fieldnames))
addargs!(fldnm,:(::Type{<:$(tf.name)}))
extendbody!(fldnm,Expr(:tuple,QuoteNode.(fieldnames)...))
structdef=tf(MixEscaped(Escaped(tf.name),UnEscaped(paramnames...,:NamedVector)))
fldnmdef=fldnm(MixEscaped(Escaped(:tuple)))
return Expr(:block,:(Base.@__doc__($structdef)),fldnmdef)
end
"""
HomoNamedVector{T}
Abstract type for all homogeneous named vectors.
"""
abstract type HomoNamedVector{T} <: NamedVector end
"""
eltype(::Type{<:HomoNamedVector{T}}) where T
eltype(nv::HomoNamedVector)
Get the type parameter of a concrete `HomoNamedVector`.
"""
Base.eltype(::Type{<:HomoNamedVector{T}}) where T=T
Base.eltype(nv::HomoNamedVector)=nv|>typeof|>eltype
"""
@homonamedvector typename fieldnames dtype::Union{Expr,Symbol}=:nothing mutable::Union{Expr,Bool}=false
Construct a concrete homogeneous named vector with the type name being `typename` and the fieldnames specified by `fieldnames`, and optionally, the type parameters specified by `dtype`.`mutable` can be used as a keyword argument to determine whether the concrete type is mutable.
"""
macro homonamedvector(typename,fieldnames,dtype::Union{Expr,Symbol}=:nothing,mutable::Union{Expr,Bool}=false)
typename=Symbol(typename)
fieldnames=tuple(eval(fieldnames)...)
@assert all(isa(name,Symbol) for name in fieldnames) "homonamedvector error: every field name should be a `Symbol`."
isa(dtype,Expr) && dtype.head==:(<:) && (@assert dtype.args|>length==1 "homonamedvector error: wrong `dtype`.")
dname,dscope=dtype==:nothing ? (:T,:Any) : isa(dtype,Expr) && dtype.head==:(<:) ? (:T,dtype.args[1]) : (dtype,:concrete)
if isa(mutable,Expr)
@assert mutable.head==:(=) && mutable.args[1]==:mutable && isa(mutable.args[2],Bool) "homonamedvector error: wrong `mutable`."
mutable=mutable.args[2]
end
if dscope==:concrete
new=:($(esc(typename)))
super=:(HomoNamedVector{$(esc(dname))})
body=(:($field::$(esc(dname))) for field in fieldnames)
else
new=:($(esc(typename)){$dname<:$(esc(dscope))})
super=:(HomoNamedVector{$dname})
body=(:($field::$dname) for field in fieldnames)
end
structdef=Expr(:struct,mutable,Expr(:<:,new,super),Expr(:block,body...))
functions=:(Base.fieldnames(::Type{<:$(esc(typename))})=$fieldnames)
return Expr(:block,:(Base.@__doc__($structdef)),functions)
end
end #module
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] | 2.606113 | 2,879 |
# Automatically generated using Clang.jl wrap_c, version 0.0.0
using Compat
const Expat_INCLUDED = 1
const Expat_External_INCLUDED = 1
# Skipping MacroDefinition: XMLPARSEAPI ( type ) XMLIMPORT type XMLCALL
# Skipping MacroDefinition: XML_TRUE ( ( XML_Bool ) 1 )
# Skipping MacroDefinition: XML_FALSE ( ( XML_Bool ) 0 )
# begin enum XML_Status
typealias XML_Status UInt32
const XML_STATUS_ERROR = (UInt32)(0)
const XML_STATUS_OK = (UInt32)(1)
const XML_STATUS_SUSPENDED = (UInt32)(2)
# end enum XML_Status
# Skipping MacroDefinition: XML_GetUserData ( parser ) ( * ( void * * ) ( parser ) )
#=
const XML_GetErrorLineNumber = XML_GetCurrentLineNumber
const XML_GetErrorColumnNumber = XML_GetCurrentColumnNumber
const XML_GetErrorByteIndex = XML_GetCurrentByteIndex
=#
const XML_MAJOR_VERSION = 2
const XML_MINOR_VERSION = 1
const XML_MICRO_VERSION = 0
typealias XML_Char UInt8
typealias XML_LChar UInt8
typealias XML_Index Clong
typealias XML_Size Culong
type XML_ParserStruct
end
typealias XML_Parser Ptr{XML_ParserStruct}
typealias XML_Bool Cuchar
# begin enum XML_Error
typealias XML_Error UInt32
const XML_ERROR_NONE = (UInt32)(0)
const XML_ERROR_NO_MEMORY = (UInt32)(1)
const XML_ERROR_SYNTAX = (UInt32)(2)
const XML_ERROR_NO_ELEMENTS = (UInt32)(3)
const XML_ERROR_INVALID_TOKEN = (UInt32)(4)
const XML_ERROR_UNCLOSED_TOKEN = (UInt32)(5)
const XML_ERROR_PARTIAL_CHAR = (UInt32)(6)
const XML_ERROR_TAG_MISMATCH = (UInt32)(7)
const XML_ERROR_DUPLICATE_ATTRIBUTE = (UInt32)(8)
const XML_ERROR_JUNK_AFTER_DOC_ELEMENT = (UInt32)(9)
const XML_ERROR_PARAM_ENTITY_REF = (UInt32)(10)
const XML_ERROR_UNDEFINED_ENTITY = (UInt32)(11)
const XML_ERROR_RECURSIVE_ENTITY_REF = (UInt32)(12)
const XML_ERROR_ASYNC_ENTITY = (UInt32)(13)
const XML_ERROR_BAD_CHAR_REF = (UInt32)(14)
const XML_ERROR_BINARY_ENTITY_REF = (UInt32)(15)
const XML_ERROR_ATTRIBUTE_EXTERNAL_ENTITY_REF = (UInt32)(16)
const XML_ERROR_MISPLACED_XML_PI = (UInt32)(17)
const XML_ERROR_UNKNOWN_ENCODING = (UInt32)(18)
const XML_ERROR_INCORRECT_ENCODING = (UInt32)(19)
const XML_ERROR_UNCLOSED_CDATA_SECTION = (UInt32)(20)
const XML_ERROR_EXTERNAL_ENTITY_HANDLING = (UInt32)(21)
const XML_ERROR_NOT_STANDALONE = (UInt32)(22)
const XML_ERROR_UNEXPECTED_STATE = (UInt32)(23)
const XML_ERROR_ENTITY_DECLARED_IN_PE = (UInt32)(24)
const XML_ERROR_FEATURE_REQUIRES_XML_DTD = (UInt32)(25)
const XML_ERROR_CANT_CHANGE_FEATURE_ONCE_PARSING = (UInt32)(26)
const XML_ERROR_UNBOUND_PREFIX = (UInt32)(27)
const XML_ERROR_UNDECLARING_PREFIX = (UInt32)(28)
const XML_ERROR_INCOMPLETE_PE = (UInt32)(29)
const XML_ERROR_XML_DECL = (UInt32)(30)
const XML_ERROR_TEXT_DECL = (UInt32)(31)
const XML_ERROR_PUBLICID = (UInt32)(32)
const XML_ERROR_SUSPENDED = (UInt32)(33)
const XML_ERROR_NOT_SUSPENDED = (UInt32)(34)
const XML_ERROR_ABORTED = (UInt32)(35)
const XML_ERROR_FINISHED = (UInt32)(36)
const XML_ERROR_SUSPEND_PE = (UInt32)(37)
const XML_ERROR_RESERVED_PREFIX_XML = (UInt32)(38)
const XML_ERROR_RESERVED_PREFIX_XMLNS = (UInt32)(39)
const XML_ERROR_RESERVED_NAMESPACE_URI = (UInt32)(40)
# end enum XML_Error
# begin enum XML_Content_Type
typealias XML_Content_Type UInt32
const XML_CTYPE_EMPTY = (UInt32)(1)
const XML_CTYPE_ANY = (UInt32)(2)
const XML_CTYPE_MIXED = (UInt32)(3)
const XML_CTYPE_NAME = (UInt32)(4)
const XML_CTYPE_CHOICE = (UInt32)(5)
const XML_CTYPE_SEQ = (UInt32)(6)
# end enum XML_Content_Type
# begin enum XML_Content_Quant
typealias XML_Content_Quant UInt32
const XML_CQUANT_NONE = (UInt32)(0)
const XML_CQUANT_OPT = (UInt32)(1)
const XML_CQUANT_REP = (UInt32)(2)
const XML_CQUANT_PLUS = (UInt32)(3)
# end enum XML_Content_Quant
#=
typealias XML_Content XML_cp
=#
type XML_cp
_type::XML_Content_Type
quant::XML_Content_Quant
name::Ptr{XML_Char}
numchildren::UInt32
children::Ptr{XML_cp}
end
typealias XML_ElementDeclHandler Ptr{Void}
typealias XML_AttlistDeclHandler Ptr{Void}
typealias XML_XmlDeclHandler Ptr{Void}
type XML_Memory_Handling_Suite
malloc_fcn::Ptr{Void}
realloc_fcn::Ptr{Void}
free_fcn::Ptr{Void}
end
typealias XML_StartElementHandler Ptr{Void}
typealias XML_EndElementHandler Ptr{Void}
typealias XML_CharacterDataHandler Ptr{Void}
typealias XML_ProcessingInstructionHandler Ptr{Void}
typealias XML_CommentHandler Ptr{Void}
typealias XML_StartCdataSectionHandler Ptr{Void}
typealias XML_EndCdataSectionHandler Ptr{Void}
typealias XML_DefaultHandler Ptr{Void}
typealias XML_StartDoctypeDeclHandler Ptr{Void}
typealias XML_EndDoctypeDeclHandler Ptr{Void}
typealias XML_EntityDeclHandler Ptr{Void}
typealias XML_UnparsedEntityDeclHandler Ptr{Void}
typealias XML_NotationDeclHandler Ptr{Void}
typealias XML_StartNamespaceDeclHandler Ptr{Void}
typealias XML_EndNamespaceDeclHandler Ptr{Void}
typealias XML_NotStandaloneHandler Ptr{Void}
typealias XML_ExternalEntityRefHandler Ptr{Void}
typealias XML_SkippedEntityHandler Ptr{Void}
type XML_Encoding
map::NTuple{256,Cint}
data::Ptr{Void}
convert::Ptr{Void}
release::Ptr{Void}
end
typealias XML_UnknownEncodingHandler Ptr{Void}
# begin enum XML_Parsing
typealias XML_Parsing UInt32
const XML_INITIALIZED = (UInt32)(0)
const XML_PARSING = (UInt32)(1)
const XML_FINISHED = (UInt32)(2)
const XML_SUSPENDED = (UInt32)(3)
# end enum XML_Parsing
type XML_ParsingStatus
parsing::XML_Parsing
finalBuffer::XML_Bool
end
# begin enum XML_ParamEntityParsing
typealias XML_ParamEntityParsing UInt32
const XML_PARAM_ENTITY_PARSING_NEVER = (UInt32)(0)
const XML_PARAM_ENTITY_PARSING_UNLESS_STANDALONE = (UInt32)(1)
const XML_PARAM_ENTITY_PARSING_ALWAYS = (UInt32)(2)
# end enum XML_ParamEntityParsing
type XML_Expat_Version
major::Cint
minor::Cint
micro::Cint
end
# begin enum XML_FeatureEnum
typealias XML_FeatureEnum UInt32
const XML_FEATURE_END = (UInt32)(0)
const XML_FEATURE_UNICODE = (UInt32)(1)
const XML_FEATURE_UNICODE_WCHAR_T = (UInt32)(2)
const XML_FEATURE_DTD = (UInt32)(3)
const XML_FEATURE_CONTEXT_BYTES = (UInt32)(4)
const XML_FEATURE_MIN_SIZE = (UInt32)(5)
const XML_FEATURE_SIZEOF_XML_CHAR = (UInt32)(6)
const XML_FEATURE_SIZEOF_XML_LCHAR = (UInt32)(7)
const XML_FEATURE_NS = (UInt32)(8)
const XML_FEATURE_LARGE_SIZE = (UInt32)(9)
const XML_FEATURE_ATTR_INFO = (UInt32)(10)
# end enum XML_FeatureEnum
type XML_Feature
feature::XML_FeatureEnum
name::Ptr{XML_LChar}
value::Clong
end
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] | 2.427252 | 2,598 |
include(string(pwd(),"/src/gensys.jl"))
theta = 0.36
delta = 0.025
beta = 0.99
A = 1.72
h0 = 0.58
gamma = 0.95
sig = 0.0712
B = A*log(1-h0)/h0
r_bar = 1/beta-(1-delta)
G0 = zeros(7,7)
G1 = zeros(7,7)
Pi = zeros(7,2)
Psi = zeros(7)
G0[1,1] = 1
G0[1,2] = -r_bar*beta
G0[3,5] = 1
G0[7,7] = 1
###G1####
G1[1,1] = 1
G1[2,1] = 1
G1[2,3] = 1
G1[2,4] = -1
G1[3,1] = -(r_bar/theta-delta)
G1[3,4] = r_bar/theta
G1[3,5] = (1-delta)
G1[4,3] = 1-theta
G1[4,4] = -1
G1[4,5] = theta
G1[4,7] = 1
G1[5,2] = -1
G1[5,4] = 1
G1[5,5] = -1
G1[6,3] = -1
G1[6,4] = 1
G1[6,6] = -1
G1[7,7] = gamma
Pi[1,1] = 1
Pi[1,2] = -beta*r_bar
Psi[7] = 1
sol1 = gensys(G0,G1,Psi,Pi)
irf1 = irf(sol1,100,0.01)
using Plots
plot(irf1[:,1], w = 2, label = "C")
plot!(irf1[:,2], w = 2, label = "r")
plot!(irf1[:,3], w = 2, label = "h")
plot!(irf1[:,4], w = 2, label = "y")
plot!(irf1[:,5], w = 2, label = "k")
plot!(irf1[:,6], w = 2, label = "w", line = :dash, color = "red")
hline!([0], color = "black", w = 2, label = "0")
####################
G0 = zeros(7,7)
G1 = zeros(7,7)
Pi = zeros(7,2)
Psi = zeros(7)
h_bar = - (1-theta)/(B*(1-delta*theta*beta/(1-beta*(1-delta))-1))
k_bar = (theta*beta/(1-beta*(1-delta)))^(1/(1-theta))*h_bar
y_bar = r_bar*k_bar/theta
c_bar = y_bar - delta*k_bar
G0[1,1] = 1
G0[1,2] = -r_bar*beta
G0[2,1] = 1
G0[2,3] = 1
G0[2,4] = -1
G0[3,5] = k_bar
G0[4,3] = -(1-theta)
G0[4,4] = 1
G0[4,5] = -theta
G0[4,7] = -1
G0[5,2] = -1
G0[5,4] = 1
G0[5,5] = -1
G0[6,3] = theta
G0[6,5] = -theta
G0[6,6] = 1
G0[6,7] = -1
G0[7,7] = 1
### G1 ####
G1[1,1] = 1
G1[3,1] = -c_bar
G1[3,4] = y_bar
G1[3,5] = (1-delta)*k_bar
G1[7,7] = gamma
Pi[1,1] = 1
Pi[1,2] = -beta*r_bar
Psi[7] = 1
sol2 = gensys(G0,G1,Psi,Pi)
irf1 = irf(sol1,100,0.01)
irf2 = irf(sol2,100,0.01)
plot(irf1[:,1])
plot!(irf2[:,1])
plot(irf1[:,2])
plot!(irf2[:,2])
plot(irf1[:,3])
plot!(irf2[:,3])
plot(irf1[:,4])
plot!(irf2[:,4])
plot(irf1[:,5])
plot!(irf2[:,5])
plot(irf1[:,6])
plot!(irf2[:,6])
G0 = zeros(6,6)
G1 = zeros(6,6)
Pi = zeros(6,2)
Psi = zeros(6)
G0[1,1] = 1
G0[1,2] = -r_bar*beta
G0[3,5] = 1
G0[6,6] = 1
###G1####
G1[1,1] = 1
G1[2,1] = 1
G1[2,3] = 1
G1[2,4] = -1
G1[3,1] = r_bar/theta-delta
G1[3,4] = r_bar/theta
G1[3,5] = (1-delta)
G1[4,3] = 1-theta
G1[4,4] = -1
G1[4,5] = theta
G1[4,6] = 1
G1[5,2] = -1
G1[5,4] = 1
G1[5,5] = -1
G1[6,6] = gamma
Pi[1,1] = 1
Pi[1,2] = -beta*r_bar
Psi[6] = sig
sol3 = gensys(G0,G1,Psi,Pi)
irf3 = irf(sol3,20,0.5)
plot(irf1[:,1])
plot!(irf2[:,1])
plot!(irf3[:,1])
#################
G0 = zeros(7,7)
G1 = zeros(7,7)
Pi = zeros(7,2)
Psi = zeros(7)
G0[1,1] = 1
G0[1,2] = -r_bar*beta
G0[2,1] = -1
G0[2,3] = -1
G0[2,4] = 1
G0[3,5] = 1
G0[4,3] = -(1-theta)
G0[4,4] = 1
G0[4,5] = -theta
G0[4,7] = -1
G0[5,2] = 1
G0[5,4] = -1
G0[5,5] = 1
G0[6,3] = 1
G0[6,4] = -1
G0[6,6] = 1
G0[7,7] = 1
##### G1 #####
G1[1,1] = 1
G1[3,1] = -(r_bar/theta-delta)
G1[3,4] = r_bar/theta
G1[3,5] = 1-delta
G1[7,7] = gamma
Pi[1,1] = 1
Pi[1,2] = -beta*r_bar
Psi[7] = 1
sol4 = gensys(G0,G1,Psi,Pi)
irf4 = irf(sol4,100,0.5)
plot(irf1[:,1])
plot!(irf4[:,1])
plot(irf1[:,2])
plot!(irf4[:,2])
plot(irf1[:,3])
plot!(irf4[:,3])
plot(irf1[:,4])
plot!(irf4[:,4])
plot(irf1[:,5])
plot!(irf4[:,5])
plot(irf1[:,6])
plot!(irf4[:,6])
plot(irf1[:,7])
plot!(irf4[:,7])
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] | 1.480144 | 2,216 |
# see documentation at https://juliadocs.github.io/Documenter.jl/stable/
using Documenter, BrowseTables
makedocs(
modules = [BrowseTables],
format = Documenter.HTML(; prettyurls = get(ENV, "CI", nothing) == "true"),
authors = "Tamas K. Papp",
sitename = "BrowseTables.jl",
pages = Any["index.md"]
# strict = true,
# clean = true,
# checkdocs = :exports,
)
# Some setup is needed for documentation deployment, see “Hosting Documentation” and
# deploydocs() in the Documenter manual for more information.
deploydocs(
repo = "github.com/tpapp/BrowseTables.jl.git",
push_preview = true
)
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] | 2.737991 | 229 |
##############################################################################
##
## Solution method: minimize by sparse least square optimization
##
##############################################################################
##############################################################################
##
## Factor Model (no regressors)
##
##############################################################################
function fit!(t::Union{Type{Val{:levenberg_marquardt}}, Type{Val{:dogleg}}},
fp::FactorModel,
fs::FactorSolution;
maxiter::Integer = 10_000,
tol::Real = 1e-9,
lambda::Number = 0.0)
# initialize
iter = 0
converged = true
fullrank = rank(fp)
fp = FactorModel(deepcopy(fp.y), fp.sqrtw, fp.idrefs, fp.timerefs, 1)
N = size(fs.idpool, 1)
T = size(fs.timepool, 1)
fg = FactorGradient(fp,
FactorSolution(Array(Float64, N), Array(Float64, T)),
FactorSolution(Array(Float64, N), Array(Float64, T))
)
nls = LeastSquaresOptim.LeastSquaresProblem(
view(fs, :, 1),
similar(fp.y),
(x,y) -> f!(fp, x, y),
fg,
g!)
if t == Val{:levenberg_marquardt}
optimizer = LeastSquaresOptim.LevenbergMarquardt()
else
optimizer = LeastSquaresOptim.Dogleg()
end
full = LeastSquaresOptim.LeastSquaresProblemAllocated(nls, optimizer, LeastSquaresOptim.LSMR())
for r in 1:fullrank
fsr = view(fs, :, r)
full.x = fsr
result = LeastSquaresOptim.optimize!(full,
xtol = 1e-32, grtol = 1e-32, ftol = tol, iterations = maxiter)
iter += result.mul_calls
converged = result.converged && converged
if r < fullrank
rescale!(fsr)
subtract_factor!(fp, fsr)
end
end
# rescale factors and loadings so that factors' * factors = Id
return rescale(fs), iter, converged
end
##############################################################################
##
## Interactive FixedEffectModel
##
##############################################################################
function fit!{Rank}(t::Union{Type{Val{:levenberg_marquardt}}, Type{Val{:dogleg}}},
fp::InteractiveFixedEffectsModel{Rank},
fs::InteractiveFixedEffectsSolution{Rank};
maxiter::Integer = 10_000,
tol::Real = 1e-9,
lambda::Number = 0.0)
scaleb = vec(sumabs2(fp.X, 1))
fsT = InteractiveFixedEffectsSolutionT(fs.b, fs.idpool', fs.timepool')
fg = InteractiveFixedEffectsGradientT(fp,
similar(fsT),
InteractiveFixedEffectsSolutionT(scaleb, similar(fsT.idpool), similar(fsT.timepool)))
nls = LeastSquaresOptim.LeastSquaresProblem(fsT, similar(fp.y), (x,y) -> f!(fp, x, y), fg, g!)
if t == Val{:levenberg_marquardt}
optimizer = LeastSquaresOptim.LevenbergMarquardt()
else
optimizer = LeastSquaresOptim.Dogleg()
end
full = LeastSquaresOptim.LeastSquaresProblemAllocated(nls, optimizer, LeastSquaresOptim.LSMR())
temp = similar(fp.y)
result = LeastSquaresOptim.optimize!(full;
xtol = 1e-32, grtol = 1e-32, ftol = tol, iterations = maxiter)
# rescale factors and loadings so that factors' * factors = Id
fs = InteractiveFixedEffectsSolution(fsT.b, fsT.idpool', fsT.timepool')
return rescale(fs), result.mul_calls, result.converged
end
##############################################################################
##
## Methods used in optimize! in LeastSquares
##
##############################################################################
function vecdot{T}(fs1::AbstractArray{T}, fs2::AbstractArray{T})
out = zero(typeof(one(T) * one(T)))
@inbounds @simd for i in eachindex(fs1)
out += fs1[i] * fs2[i]
end
return out
end
function vecdot{T}(x::AbstractArray{T}, y::AbstractArray{T}, w::AbstractArray{T})
out = zero(typeof(one(T) * one(T)))
@inbounds @simd for i in eachindex(x)
out += w[i] * x[i] * y[i]
end
return out
end
for t in (FactorSolution, InteractiveFixedEffectsSolution, InteractiveFixedEffectsSolutionT, HalfInteractiveFixedEffectsSolution)
vars = [:(fill!(x.$field, α)) for field in fieldnames(t)]
expr = Expr(:block, vars...)
@eval begin
function fill!(x::$t, α::Number)
$expr
return x
end
end
vars = [:(scale!(x.$field, α)) for field in fieldnames(t)]
expr = Expr(:block, vars...)
@eval begin
function scale!(x::$t, α::Number)
$expr
return x
end
end
vars = [:(clamp!(x.$field, α, β)) for field in fieldnames(t)]
expr = Expr(:block, vars...)
@eval begin
function clamp!(x::$t, α::Number, β::Number)
$expr
return x
end
end
vars = [:(copy!(x1.$field, x2.$field)) for field in fieldnames(t)]
expr = Expr(:block, vars...)
@eval begin
function copy!(x1::$t, x2::$t)
$expr
return x1
end
end
vars = [:(axpy!(α, x1.$field, x2.$field)) for field in fieldnames(t)]
expr = Expr(:block, vars...)
@eval begin
function axpy!(α::Number, x1::$t, x2::$t)
$expr
return x2
end
end
vars = [:(map!(f, x1.$field, map(x -> x.$field, x2)...)) for field in fieldnames(t)]
expr = Expr(:block, vars...)
@eval begin
function map!(f, x1::$t, x2::$t...)
$expr
return x1
end
end
vars = [:(vecdot(x1.$field, x2.$field)) for field in fieldnames(t)]
expr = Expr(:call, :+, vars...)
@eval begin
function dot(x1::$t, x2::$t)
$expr
end
end
vars = [:(vecdot(x1.$field, x2.$field, w.$field)) for field in fieldnames(t)]
expr = Expr(:call, :+, vars...)
@eval begin
function dot(x1::$t, x2::$t, w::$t)
$expr
end
end
vars = [:(sumabs2(x.$field)) for field in fieldnames(t)]
expr = Expr(:call, :+, vars...)
@eval begin
function sumabs2(x::$t)
$expr
end
end
vars = [:(length(x.$field)) for field in fieldnames(t)]
expr = Expr(:call, :+, vars...)
@eval begin
function length(x::$t)
$expr
end
end
vars = [:(similar(x.$field)) for field in fieldnames(t)]
expr = Expr(:call, t, vars...)
@eval begin
function similar(x::$t)
$expr
end
end
vars = [:(maxabs(x.$field)) for field in fieldnames(t)]
expr = Expr(:call, :max, vars...)
@eval begin
function maxabs(x::$t)
$expr
end
end
end
norm(fs::AbstractFactorSolution) = sqrt(sumabs2(fs))
eltype(fg::AbstractFactorSolution) = Float64
function safe_scale!(x, β)
if β != 1
β == 0 ? fill!(x, zero(eltype(x))) : scale!(x, β)
end
end
##############################################################################
##
## Factor Gradient
##
##############################################################################
abstract AbstractFactorGradient{T}
type FactorGradient{Rank, W, Rid, Rtime, Tid, Ttime, sTid, sTtime} <: AbstractFactorGradient{Rank}
fp::FactorModel{Rank, W, Rid, Rtime}
fs::FactorSolution{Rank, Tid, Ttime}
scalefs::FactorSolution{Rank, sTid, sTtime}
end
function size(fg::FactorGradient, i::Integer)
if i == 1
length(fg.fp.y)
elseif i == 2
length(fg.fs.idpool) + length(fg.fs.timepool)
end
end
type InteractiveFixedEffectsGradientT{Rank, W, Rid, Rtime, Tb, Tid, Ttime, sTb, sTid, sTtime} <: AbstractFactorGradient{Rank}
fp::InteractiveFixedEffectsModel{Rank, W, Rid, Rtime}
fs::InteractiveFixedEffectsSolutionT{Rank, Tb, Tid, Ttime}
scalefs::InteractiveFixedEffectsSolutionT{Rank, sTb, sTid, sTtime}
end
function size(fg::InteractiveFixedEffectsGradientT, i::Integer)
if i == 1
length(fg.fp.y)
elseif i == 2
length(fg.fs.b) + length(fg.fs.idpool) + length(fg.fs.timepool)
end
end
Base.rank{Rank}(f::AbstractFactorGradient{Rank}) = Rank
size(fg::AbstractFactorGradient) = (size(fg, 1), size(fg, 2))
eltype(fg::AbstractFactorGradient) = Float64
LeastSquaresOptim.colsumabs2!(fs::AbstractFactorSolution, fg::AbstractFactorGradient) = copy!(fs, fg.scalefs)
@generated function A_mul_B!{Rank}(α::Number, fg::AbstractFactorGradient{Rank}, fs::AbstractFactorSolution{Rank}, β::Number, y::AbstractVector{Float64})
if Rank == 1
ex = quote
out += (fg.fs.idpool[idi] * fs.timepool[timei]
+ fg.fs.timepool[timei] * fs.idpool[idi])
end
else
ex = quote
@nexprs $Rank r -> begin
out += (fg.fs.idpool[r, idi] * fs.timepool[r, timei]
+ fg.fs.timepool[r, timei] * fs.idpool[r, idi])
end
end
end
quote
mα = convert(Float64, -α)
A_mul_B!_X(mα, fg.fp, fs, β, y)
@fastmath @inbounds @simd for i in 1:length(y)
timei = fg.fp.timerefs[i]
idi = fg.fp.idrefs[i]
out = 0.0
$ex
y[i] += mα * fg.fp.sqrtw[i] * out
end
return y
end
end
function A_mul_B!_X(α::Number, fp::InteractiveFixedEffectsModel, fs::InteractiveFixedEffectsSolutionT, β::Number, y::AbstractVector{Float64})
Base.BLAS.gemm!('N', 'N', α, fp.X, fs.b, convert(Float64, β), y)
end
function A_mul_B!_X(::Number, ::FactorModel, ::FactorSolution, β::Number, y::AbstractVector{Float64})
safe_scale!(y, β)
end
@generated function Ac_mul_B!{Rank}(α::Number, fg::AbstractFactorGradient{Rank}, y::AbstractVector{Float64}, β::Number, fs::AbstractFactorSolution{Rank})
if Rank == 1
ex = quote
fs.idpool[idi] += sqrtwi * fg.fs.timepool[timei]
fs.timepool[timei] += sqrtwi * fg.fs.idpool[idi]
end
else
ex = quote
@nexprs $Rank r -> begin
fs.idpool[r, idi] += sqrtwi * fg.fs.timepool[r, timei]
fs.timepool[r, timei] += sqrtwi * fg.fs.idpool[r, idi]
end
end
end
quote
mα = convert(Float64, -α)
Ac_mul_B!_X(mα, fg.fp, y, β, fs)
@inbounds @simd for i in 1:length(y)
sqrtwi = mα * y[i] * fg.fp.sqrtw[i]
idi = fg.fp.idrefs[i]
timei = fg.fp.timerefs[i]
$ex
end
return fs
end
end
function Ac_mul_B!_X(α::Number, fp::InteractiveFixedEffectsModel, y::AbstractVector{Float64}, β::Number, fs::InteractiveFixedEffectsSolutionT)
safe_scale!(fs, β)
@inbounds @simd for k in 1:length(fs.b)
out = zero(Float64)
for i in 1:length(y)
out += y[i] * fp.X[i, k]
end
fs.b[k] += α * out
end
end
function Ac_mul_B!_X(::Number, ::FactorModel, ::AbstractVector{Float64}, β::Number, fs::FactorSolution) safe_scale!(fs, β)
end
##############################################################################
##
## f! for LeastSquaresOptim
##
##############################################################################
@generated function f!{Rank}(fp::AbstractFactorModel{Rank},
fs::AbstractFactorSolution{Rank}, out::Vector{Float64})
if Rank == 1
ex = quote
out[i] -= sqrtwi * fs.idpool[idi] * fs.timepool[timei]
end
else
ex = quote
@nexprs $Rank r -> begin
out[i] -= sqrtwi * fs.idpool[r, idi] * fs.timepool[r, timei]
end
end
end
quote
copy!(out, fp.y)
A_mul_B!_X(-1.0, fp, fs, 1.0, out)
@fastmath @inbounds @simd for i in 1:length(out)
sqrtwi = fp.sqrtw[i]
idi = fp.idrefs[i]
timei = fp.timerefs[i]
$ex
end
return out
end
end
##############################################################################
##
## g! for LeastSquaresOptim
##
##############################################################################
@generated function g!{Rank}(fs::AbstractFactorSolution{Rank}, fg::AbstractFactorGradient{Rank})
if Rank == 1
ex = quote
fg.scalefs.idpool[idi] += abs2(sqrtwi * fg.fs.timepool[timei])
fg.scalefs.timepool[timei] += abs2(sqrtwi * fg.fs.idpool[idi])
end
else
ex = quote
@nexprs $Rank r -> begin
fg.scalefs.idpool[r, idi] += abs2(sqrtwi * fg.fs.timepool[r, timei])
fg.scalefs.timepool[r, timei] += abs2(sqrtwi * fg.fs.idpool[r, idi])
end
end
end
quote
copy!(fg.fs, fs)
fill!(fg.scalefs.idpool, zero(Float64))
fill!(fg.scalefs.timepool, zero(Float64))
@inbounds @simd for i in 1:length(fg.fp.y)
sqrtwi = fg.fp.sqrtw[i]
idi = fg.fp.idrefs[i]
timei = fg.fp.timerefs[i]
$ex
end
end
end
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198,
29113,
29113,
7804,
4242,
2235,
198,
2235,
198,
2235,
27929,
9104,
357,
3919,
50252,
669,
8,
198,
2235,
198,
29113,
29113,
7804,
4242,
2235,
198,
198,
8818,
4197,
0,
7,
83,
3712,
38176,
90,
6030,
90,
7762,
90,
25,
293,
574,
3900,
62,
3876,
421,
446,
83,
92,
5512,
5994,
90,
7762,
90,
25,
9703,
1455,
11709,
5512,
220,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
277,
79,
3712,
41384,
17633,
11,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
43458,
3712,
41384,
46344,
26,
220,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
3509,
2676,
3712,
46541,
796,
838,
62,
830,
11,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
284,
75,
3712,
15633,
796,
352,
68,
12,
24,
11,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
37456,
3712,
15057,
796,
657,
13,
15,
8,
198,
220,
220,
220,
1303,
41216,
198,
220,
220,
220,
11629,
796,
657,
198,
220,
220,
220,
6718,
2004,
796,
2081,
198,
220,
220,
220,
1336,
43027,
796,
4279,
7,
46428,
8,
198,
220,
220,
220,
277,
79,
796,
27929,
17633,
7,
22089,
30073,
7,
46428,
13,
88,
828,
277,
79,
13,
31166,
81,
4246,
11,
277,
79,
13,
312,
5420,
82,
11,
277,
79,
13,
2435,
5420,
82,
11,
352,
8,
198,
220,
220,
220,
399,
796,
2546,
7,
9501,
13,
312,
7742,
11,
352,
8,
198,
220,
220,
220,
309,
796,
2546,
7,
9501,
13,
2435,
7742,
11,
352,
8,
198,
220,
220,
220,
277,
70,
796,
27929,
42731,
1153,
7,
46428,
11,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
27929,
46344,
7,
19182,
7,
43879,
2414,
11,
399,
828,
15690,
7,
43879,
2414,
11,
309,
36911,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
27929,
46344,
7,
19182,
7,
43879,
2414,
11,
399,
828,
15690,
7,
43879,
2414,
11,
309,
4008,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1267,
198,
220,
220,
220,
299,
7278,
796,
1004,
459,
22266,
3565,
27871,
320,
13,
3123,
459,
22266,
3565,
40781,
7,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1570,
7,
9501,
11,
1058,
11,
352,
828,
220,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
2092,
7,
46428,
13,
88,
828,
220,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
357,
87,
11,
88,
8,
4613,
277,
0,
7,
46428,
11,
2124,
11,
331,
828,
220,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
277,
70,
11,
220,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
308,
8133,
198,
220,
220,
220,
611,
256,
6624,
3254,
90,
25,
293,
574,
3900,
62,
3876,
421,
446,
83,
92,
198,
220,
220,
220,
220,
220,
220,
220,
6436,
7509,
796,
1004,
459,
22266,
3565,
27871,
320,
13,
3123,
574,
3900,
7676,
421,
446,
83,
3419,
198,
220,
220,
220,
2073,
198,
220,
220,
220,
220,
220,
220,
220,
6436,
7509,
796,
1004,
459,
22266,
3565,
27871,
320,
13,
32942,
1455,
3419,
198,
220,
220,
220,
886,
198,
220,
220,
220,
1336,
796,
1004,
459,
22266,
3565,
27871,
320,
13,
3123,
459,
22266,
3565,
40781,
3237,
10533,
7,
77,
7278,
11,
6436,
7509,
11,
1004,
459,
22266,
3565,
27871,
320,
13,
6561,
13599,
28955,
198,
220,
220,
220,
329,
374,
287,
352,
25,
12853,
43027,
198,
220,
220,
220,
220,
220,
220,
220,
277,
27891,
796,
1570,
7,
9501,
11,
1058,
11,
374,
8,
198,
220,
220,
220,
220,
220,
220,
220,
1336,
13,
87,
796,
277,
27891,
198,
220,
220,
220,
220,
220,
220,
220,
1255,
796,
1004,
459,
22266,
3565,
27871,
320,
13,
40085,
1096,
0,
7,
12853,
11,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
742,
349,
796,
352,
68,
12,
2624,
11,
1036,
83,
349,
796,
352,
68,
12,
2624,
11,
10117,
349,
796,
284,
75,
11,
220,
34820,
796,
3509,
2676,
8,
198,
220,
220,
220,
220,
220,
220,
220,
11629,
15853,
1255,
13,
76,
377,
62,
66,
5691,
198,
220,
220,
220,
220,
220,
220,
220,
6718,
2004,
796,
1255,
13,
1102,
332,
2004,
11405,
6718,
2004,
198,
220,
220,
220,
220,
220,
220,
220,
611,
374,
1279,
1336,
43027,
220,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
6811,
1000,
0,
7,
9501,
81,
8,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
34128,
62,
31412,
0,
7,
46428,
11,
277,
27891,
8,
198,
220,
220,
220,
220,
220,
220,
220,
886,
198,
220,
220,
220,
886,
198,
220,
220,
220,
1303,
6811,
1000,
5087,
290,
3440,
654,
523,
326,
5087,
6,
1635,
5087,
796,
5121,
198,
220,
220,
220,
1441,
6811,
1000,
7,
9501,
828,
11629,
11,
6718,
2004,
198,
437,
628,
198,
29113,
29113,
7804,
4242,
2235,
198,
2235,
198,
2235,
21365,
10832,
18610,
17633,
198,
2235,
198,
29113,
29113,
7804,
4242,
2235,
198,
198,
8818,
4197,
0,
90,
27520,
92,
7,
83,
3712,
38176,
90,
6030,
90,
7762,
90,
25,
293,
574,
3900,
62,
3876,
421,
446,
83,
92,
5512,
5994,
90,
7762,
90,
25,
9703,
1455,
11709,
5512,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
277,
79,
3712,
9492,
5275,
13715,
47738,
17633,
90,
27520,
5512,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
43458,
3712,
9492,
5275,
13715,
47738,
46344,
90,
27520,
19629,
220,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
3509,
2676,
3712,
46541,
796,
838,
62,
830,
11,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
284,
75,
3712,
15633,
796,
352,
68,
12,
24,
11,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
37456,
3712,
15057,
796,
657,
13,
15,
8,
198,
220,
220,
220,
5046,
65,
796,
43030,
7,
16345,
8937,
17,
7,
46428,
13,
55,
11,
352,
4008,
198,
220,
220,
220,
43458,
51,
796,
21365,
13715,
47738,
46344,
51,
7,
9501,
13,
65,
11,
43458,
13,
312,
7742,
3256,
43458,
13,
2435,
7742,
11537,
198,
220,
220,
220,
277,
70,
796,
21365,
13715,
47738,
42731,
1153,
51,
7,
46428,
11,
220,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
2092,
7,
9501,
51,
828,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
21365,
13715,
47738,
46344,
51,
7,
9888,
65,
11,
2092,
7,
9501,
51,
13,
312,
7742,
828,
2092,
7,
9501,
51,
13,
2435,
7742,
22305,
198,
220,
220,
220,
299,
7278,
796,
1004,
459,
22266,
3565,
27871,
320,
13,
3123,
459,
22266,
3565,
40781,
7,
9501,
51,
11,
2092,
7,
46428,
13,
88,
828,
357,
87,
11,
88,
8,
4613,
277,
0,
7,
46428,
11,
2124,
11,
331,
828,
277,
70,
11,
308,
8133,
198,
220,
220,
220,
611,
256,
6624,
3254,
90,
25,
293,
574,
3900,
62,
3876,
421,
446,
83,
92,
198,
220,
220,
220,
220,
220,
220,
220,
6436,
7509,
796,
1004,
459,
22266,
3565,
27871,
320,
13,
3123,
574,
3900,
7676,
421,
446,
83,
3419,
198,
220,
220,
220,
2073,
198,
220,
220,
220,
220,
220,
220,
220,
6436,
7509,
796,
1004,
459,
22266,
3565,
27871,
320,
13,
32942,
1455,
3419,
198,
220,
220,
220,
886,
198,
220,
220,
220,
1336,
796,
1004,
459,
22266,
3565,
27871,
320,
13,
3123,
459,
22266,
3565,
40781,
3237,
10533,
7,
77,
7278,
11,
6436,
7509,
11,
1004,
459,
22266,
3565,
27871,
320,
13,
6561,
13599,
28955,
198,
220,
220,
220,
20218,
796,
2092,
7,
46428,
13,
88,
8,
198,
220,
220,
220,
1255,
796,
1004,
459,
22266,
3565,
27871,
320,
13,
40085,
1096,
0,
7,
12853,
26,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
742,
349,
796,
352,
68,
12,
2624,
11,
1036,
83,
349,
796,
352,
68,
12,
2624,
11,
10117,
349,
796,
284,
75,
11,
220,
34820,
796,
3509,
2676,
8,
198,
220,
220,
220,
1303,
6811,
1000,
5087,
290,
3440,
654,
523,
326,
5087,
6,
1635,
5087,
796,
5121,
198,
220,
220,
220,
43458,
796,
21365,
13715,
47738,
46344,
7,
9501,
51,
13,
65,
11,
43458,
51,
13,
312,
7742,
3256,
43458,
51,
13,
2435,
7742,
11537,
198,
220,
220,
220,
1441,
6811,
1000,
7,
9501,
828,
1255,
13,
76,
377,
62,
66,
5691,
11,
1255,
13,
1102,
332,
2004,
198,
437,
628,
198,
29113,
29113,
7804,
4242,
2235,
198,
2235,
198,
2235,
25458,
973,
287,
27183,
0,
287,
1004,
459,
22266,
3565,
198,
2235,
198,
29113,
29113,
7804,
4242,
2235,
198,
198,
8818,
1569,
10210,
313,
90,
51,
92,
7,
9501,
16,
3712,
23839,
19182,
90,
51,
5512,
43458,
17,
3712,
23839,
19182,
90,
51,
30072,
220,
220,
198,
220,
220,
220,
503,
796,
6632,
7,
4906,
1659,
7,
505,
7,
51,
8,
1635,
530,
7,
51,
22305,
198,
220,
220,
220,
2488,
259,
65,
3733,
2488,
14323,
67,
329,
1312,
287,
1123,
9630,
7,
9501,
16,
8,
198,
220,
220,
220,
220,
220,
220,
220,
503,
15853,
43458,
16,
58,
72,
60,
1635,
43458,
17,
58,
72,
60,
198,
220,
220,
220,
886,
198,
220,
220,
220,
1441,
503,
198,
437,
198,
198,
8818,
1569,
10210,
313,
90,
51,
92,
7,
87,
3712,
23839,
19182,
90,
51,
5512,
331,
3712,
23839,
19182,
90,
51,
5512,
266,
3712,
23839,
19182,
90,
51,
30072,
198,
220,
220,
220,
503,
796,
6632,
7,
4906,
1659,
7,
505,
7,
51,
8,
1635,
530,
7,
51,
22305,
198,
220,
220,
220,
2488,
259,
65,
3733,
2488,
14323,
67,
329,
1312,
287,
1123,
9630,
7,
87,
8,
198,
220,
220,
220,
220,
220,
220,
220,
503,
15853,
266,
58,
72,
60,
1635,
2124,
58,
72,
60,
1635,
331,
58,
72,
60,
198,
220,
220,
220,
886,
198,
220,
220,
220,
1441,
503,
198,
437,
628,
198,
1640,
256,
287,
357,
41384,
46344,
11,
21365,
13715,
47738,
46344,
11,
21365,
13715,
47738,
46344,
51,
11,
13139,
9492,
5275,
13715,
47738,
46344,
8,
198,
220,
220,
220,
410,
945,
796,
685,
37498,
20797,
0,
7,
87,
48082,
3245,
11,
26367,
4008,
329,
2214,
287,
2214,
14933,
7,
83,
15437,
198,
220,
220,
220,
44052,
796,
1475,
1050,
7,
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] | 2.118034 | 6,227 |
using CALCEPH
using Test
CALCEPH.disableCustomHandler()
CALCEPH.setCustomHandler(s::String->Nothing )
testpath = joinpath(dirname(pathof(CALCEPH)), "..", "test")
# NAIF ID tests
for (name,id) ∈ naifId.id
@test name ∈ naifId.names[id]
end
for (id,names) ∈ naifId.names
for name ∈ names
@test naifId.id[name] == id
end
end
@test naifId.id[:ssb] == naifId.id[:solar_system_barycenter] == 0
@test naifId.id[:sun] == 10
@test naifId.id[:mercury_barycenter] == 1
@test naifId.id[:mercury] == 199
@test naifId.id[:venus_barycenter] == 2
@test naifId.id[:venus] == 299
@test naifId.id[:emb] == naifId.id[:earth_barycenter] == 3
@test naifId.id[:moon] == 301
@test naifId.id[:earth] == 399
@test naifId.id[:mars_barycenter] == 4
@test naifId.id[:phobos] == 401
@test naifId.id[:deimos] == 402
@test naifId.id[:mars] == 499
@test naifId.id[:jupiter_barycenter] == 5
@test naifId.id[:io] == 501
@test naifId.id[:europa] == 502
@test naifId.id[:ganymede] == 503
@test naifId.id[:callisto] == 504
@test naifId.id[:jupiter] == 599
@test naifId.id[:saturn_barycenter] == 6
@test naifId.id[:titan] == 606
@test naifId.id[:saturn] == 699
@test naifId.id[:uranus_barycenter] == 7
@test naifId.id[:uranus] == 799
@test naifId.id[:neptune_barycenter] == 8
@test naifId.id[:triton] == 801
@test naifId.id[:neptune] == 899
@test naifId.id[:pluto_barycenter] == 9
@test naifId.id[:charon] == 901
@test naifId.id[:pluto] == 999
# test error case: changing name->id mapping
@test_throws CALCEPHException CALCEPH.add!(naifId,:jupiter,1)
# test error case: parsing wrongly formatted body id input file
bid = CALCEPH.BodyId()
@test_throws CALCEPHException CALCEPH.loadData!(bid,joinpath(testpath,"badIds.txt"))
# check memory management
eph1 = Ephem(joinpath(testpath,"example1.dat"))
eph2 = Ephem([joinpath(testpath,"example1.bsp"),
joinpath(testpath,"example1.tpc")])
@test eph1.data != C_NULL
finalize(eph1)
@test eph1.data == C_NULL
@test eph2.data != C_NULL
finalize(eph2)
@test eph2.data == C_NULL
finalize(eph2)
CALCEPH._ephemDestructor(eph2)
# Opening invalid ephemeris
@test_throws CALCEPHException Ephem(String[])
# check constants
eph1 = Ephem(joinpath(testpath,"example1.dat"))
eph2 = Ephem([joinpath(testpath,"example1.bsp"),
joinpath(testpath,"example1.tpc")])
eph3 = Ephem([joinpath(testpath,"checktpc_11627.tpc")])
eph4 = Ephem([joinpath(testpath,"checktpc_str.tpc")])
con1 = constants(eph1)
con2 = constants(eph2)
con3 = constants(eph3)
con4 = constants(eph4)
@test isa(con1,Dict{Symbol,Any})
@test length(con1) == 402
@test con1[:EMRAT] ≈ 81.30056
@test isa(con2,Dict{Symbol,Any})
@test length(con2) == 313
@test con2[:AU] ≈ 1.49597870696268e8
@test isa(con3,Dict{Symbol,Any})
@test length(con3) == 3
@test con3[:BODY000_GMLIST4] == [ 199.0 ; 299.0 ; 301.0 ; 399.0 ]
@test con3[:BODY000_GMLIST2] == [ 499 ; 599 ]
@test con3[:BODY000_GMLIST1] == 699
@test isa(con4,Dict{Symbol,Any})
@test length(con4) == 4
@test con4[:MESSAGE] == "You can't always get what you want."
@test con4[:DISTANCE_UNITS] == "KILOMETERS"
@test con4[:MISSION_UNITS] == [ "KILOMETERS" ; "SECONDS" ; "KILOMETERS/SECOND" ]
@test con4[:CONTINUED_STRINGS] == ["This //", "is //", "just //", "one long //", "string.", "Here's a second //", "continued //", "string."]
# Retrieving constants from closed ephemeris
finalize(eph2)
@test_throws CALCEPHException constants(eph2)
# test compute*
# test data and thresholds from CALCEPH C library tests
inpop_files = [joinpath(testpath,"example1.dat")]
spk_files = [joinpath(testpath,"example1.bsp"),
joinpath(testpath,"example1.tpc"),
joinpath(testpath,"example1.tf"),
joinpath(testpath,"example1.bpc"),
joinpath(testpath,"example1spk_time.bsp")]
testfile = joinpath(testpath,"example1_tests.dat")
test_data = [
(inpop_files,false),
(spk_files,false),
(inpop_files,true),
(spk_files,true)
]
include("testfunction1.jl")
for (ephFiles,prefetch) in test_data
testFunction1(testfile,ephFiles,prefetch)
end
testfile2 = joinpath(testpath,"example1_tests_naifid.dat")
include("testfunction2.jl")
for (ephFiles,prefetch) in test_data
testFunction2(testfile,testfile2,ephFiles,prefetch)
end
# test error case wrong order
eph1 = Ephem(joinpath(testpath,"example1.bsp"))
@test_throws CALCEPHException compute(eph1,0.0,0.0,1,0,0,4)
@test_throws CALCEPHException compute(eph1,0.0,0.0,1,0,0,-1)
# test error case:
@test_throws CALCEPHException compute(eph1,0.0,0.0,-144,0,0)
# Five-Point Stencil
f(x)=x^8
@test_throws ErrorException CALCEPH.fivePointStencil(f,1.5,5,0.001)
@test_throws ErrorException CALCEPH.fivePointStencil(f,1.5,-1,0.001)
@test_throws ErrorException CALCEPH.fivePointStencil(f,1.5,4,0.0)
val = CALCEPH.fivePointStencil(f,1.5,4,0.001)
ref = [25.62890625,136.6875,637.875,2551.5,8505.0]
@test ref[1] ≈ val[1] atol=1e-10
@test ref[2] ≈ val[2] atol=1e-8
@test ref[3] ≈ val[3] atol=1e-5
@test ref[4] ≈ val[4] atol=1e-2
@test ref[5] ≈ val[5] atol=1e-2
# introspection
eph = Ephem(inpop_files)
@test timeScale(eph) == 1
records = positionRecords(eph)
@test length(records) == 12
records = orientationRecords(eph)
@test length(records) == 1
@test timespan(eph) == (2.442457e6, 2.451545e6, 1)
# rotangmom
eph = Ephem(joinpath(testpath,"example2_rotangmom.dat"))
a = rotAngMom(eph,2.4515e6,0.0,399,useNaifId+unitSec)
b = rotAngMom(eph,2.4515e6,0.0,399,useNaifId+unitSec,1)
@test a == b
@test length(a) == 6
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] | 2.238855 | 2,445 |
struct QuasiArray{T,N,AXES<:NTuple{N,AbstractVector}} <: AbstractQuasiArray{T,N}
parent::Array{T,N}
axes::AXES
function QuasiArray{T,N,AXES}(par::AbstractArray{T,N}, axes::AXES) where {T,N,AXES<:NTuple{N,AbstractVector}}
size(par) == length.(axes) || throw(ArgumentError("Axes must be compatible with parent dimensions"))
new{T,N,AXES}(convert(Array{T,N},par),axes)
end
end
QuasiArray{T,N,AXES}(par::AbstractArray{<:Any,N}, axes::AXES) where {T,N,AXES<:NTuple{N,AbstractVector}} =
QuasiArray{T,N,AXES}(convert(AbstractArray{T,N}, par)::AbstractArray{T,N}, axes)
const QuasiMatrix{T,AXES<:NTuple{2,AbstractVector}} = QuasiArray{T,2,AXES}
const QuasiVector{T,AXES<:Tuple{AbstractVector}} = QuasiArray{T,1,AXES}
QuasiArray{T,N}(::UndefInitializer, axes::NTuple{N,AbstractVector}) where {T,N} =
QuasiArray(Array{T}(undef, map(length,axes)), axes)
QuasiArray{T,N}(::UndefInitializer, axes::Vararg{AbstractVector,N}) where {T,N} =
QuasiArray{T,N}(undef, axes)
QuasiVector(::UndefInitializer, axes::AbstractVector) where T =
QuasiArray(Vector(undef,length(axes)), (axes,))
QuasiMatrix(::UndefInitializer, ax1::AbstractVector, ax2::AbstractVector) where T =
QuasiArray(Matrix(undef,length(ax1),length(ax2)), (ax1,ax2))
QuasiArray(par::AbstractArray{T,N}, axes::NTuple{N,AbstractVector}) where {T,N} =
QuasiArray{T,N,typeof(axes)}(par, axes)
QuasiMatrix(par::AbstractMatrix{T}, axes::NTuple{2,AbstractVector}) where T =
QuasiArray{T,2,typeof(axes)}(par, axes)
QuasiVector(par::AbstractVector{T}, axes::Tuple{AbstractVector}) where T =
QuasiArray{T,1,typeof(axes)}(par, axes)
QuasiArray{T}(par::AbstractArray{<:Any,N}, axes::NTuple{N,AbstractVector}) where {T,N} =
QuasiArray{T,N,typeof(axes)}(par, axes)
QuasiArray{T}(par::AbstractArray{T,N}, axes::NTuple{N,AbstractVector}) where {T,N} =
QuasiArray{T,N,typeof(axes)}(par, axes)
QuasiMatrix{T}(par::AbstractMatrix, axes::NTuple{2,AbstractVector}) where T =
QuasiMatrix{T,typeof(axes)}(par, axes)
QuasiVector{T}(par::AbstractVector, axes::Tuple{AbstractVector}) where T =
QuasiVector{T,typeof(axes)}(par, axes)
QuasiArray(par::AbstractArray{T,N}, axes::Vararg{AbstractVector,N}) where {T,N} =
QuasiArray(par, axes)
QuasiMatrix(par::AbstractMatrix{T}, axes::Vararg{AbstractVector,2}) where T =
QuasiMatrix(par, axes)
QuasiVector(par::AbstractVector{T}, axes::AbstractVector) where T =
QuasiVector(par, (axes,))
QuasiArray{T}(par::AbstractArray{<:Any,N}, axes::Vararg{AbstractVector,N}) where {T,N} =
QuasiArray{T}(par, axes)
QuasiMatrix{T}(par::AbstractMatrix, axes::Vararg{AbstractVector,2}) where T =
QuasiMatrix{T}(par, axes)
QuasiVector{T}(par::AbstractVector, axes::AbstractVector) where T =
QuasiVector{T}(par, (axes,))
QuasiMatrix(λ::UniformScaling, ax::NTuple{2,AbstractVector}) = QuasiMatrix(Matrix(λ,map(length,ax)...), ax)
QuasiMatrix{T}(λ::UniformScaling, ax::NTuple{2,AbstractVector}) where T = QuasiMatrix{T}(Matrix(λ,map(length,ax)...), ax)
QuasiMatrix(λ::UniformScaling, ax1::AbstractVector, ax2::AbstractVector) = QuasiMatrix(λ, (ax1, ax2))
QuasiMatrix{T}(λ::UniformScaling, ax1::AbstractVector, ax2::AbstractVector) where T = QuasiMatrix{T}(λ, (ax1, ax2))
QuasiArray(par::AbstractArray) = QuasiArray(par, axes(par))
QuasiMatrix(par::AbstractArray) = QuasiMatrix(par, axes(par))
QuasiVector(par::AbstractArray) = QuasiVector(par, axes(par))
QuasiArray{T,N,AXES}(par::AbstractArray{T,N}, axes::NTuple{N,AbstractQuasiOrVector}) where {T,N,AXES} =
QuasiArray{T,N,AXES}(par, map(domain,axes))
QuasiArray{T,N}(par::AbstractArray{T,N}, axes::NTuple{N,AbstractQuasiOrVector}) where {T,N} =
QuasiArray{T,N}(par, map(domain,axes))
QuasiArray{T}(par::AbstractArray{T,N}, axes::NTuple{N,AbstractQuasiOrVector}) where {T,N} =
QuasiArray{T}(par, map(domain,axes))
QuasiArray(par::AbstractArray{T,N}, axes::NTuple{N,AbstractQuasiOrVector}) where {T,N} =
QuasiArray(par, map(domain,axes))
QuasiMatrix(par::AbstractMatrix{T}, axes::NTuple{2,AbstractQuasiOrVector}) where T =
QuasiMatrix(par, map(domain,axes))
QuasiVector(par::AbstractVector{T}, axes::Tuple{AbstractQuasiOrVector}) where T =
QuasiVector(par, map(domain,axes))
QuasiVector(par::AbstractVector{T}, axes::AbstractArray) where {T} =
QuasiVector(par, (axes,))
QuasiArray(a::AbstractQuasiArray{T}) where T = QuasiArray{T}(a[map(collect,axes(a))...], axes(a))
QuasiArray{T}(a::AbstractQuasiArray) where T = QuasiArray(convert(AbstractArray{T},a[map(collect,axes(a))...]), axes(a))
QuasiArray{T,N}(a::AbstractQuasiArray{<:Any,N}) where {T,N} = QuasiArray(convert(AbstractArray{T,N},a[map(collect,axes(a))...]), axes(a))
QuasiArray{T,N,AXES}(a::AbstractQuasiArray{<:Any,N}) where {T,N,AXES} = QuasiArray{T,N,AXES}(Array{T}(a), axes(a))
QuasiMatrix(a::AbstractQuasiMatrix) = QuasiArray(a)
QuasiVector(a::AbstractQuasiVector) = QuasiArray(a)
convert(::Type{T}, a::AbstractQuasiArray) where {T<:QuasiArray} = a isa T ? a : T(a)
convert(::Type{QuasiArray{T,N}}, a::AbstractQuasiArray) where {T,N} = a isa QuasiArray{T,N} ? a : QuasiArray{T,N}(a)
convert(::Type{QuasiArray{T}}, a::AbstractQuasiArray) where T = a isa QuasiArray{T} ? a : QuasiArray{T}(a)
convert(::Type{AbstractQuasiArray{T,N}}, a::QuasiArray) where {T,N} = convert(QuasiArray{T,N}, a)
convert(::Type{AbstractQuasiArray{T}}, a::QuasiArray) where T = convert(QuasiArray{T}, a)
convert(::Type{AbstractQuasiArray{T,N}}, a::QuasiArray{T,N}) where {T,N} = a
convert(::Type{AbstractQuasiArray{T}}, a::QuasiArray{T}) where T = a
AbstractQuasiArray{T,N}(a::QuasiArray) where {T,N} = QuasiArray{T,N}(a)
AbstractQuasiArray{T}(a::QuasiArray) where T = QuasiArray{T}(a)
_inclusion(d::Slice) = d
_inclusion(d::OneTo) = d
_inclusion(d::IdentityUnitRange{<:Integer}) = d
_inclusion(d::AbstractUnitRange{<:Integer}) = IdentityUnitRange(d)
_inclusion(d) = Inclusion(d)
axes(A::QuasiArray) = map(_inclusion,A.axes)
parent(A::QuasiArray) = A.parent
@propagate_inbounds @inline function _getindex(::Type{IND}, A::QuasiArray, I::IND) where IND
@boundscheck checkbounds(A, I...)
A.parent[findfirst.(isequal.(I), A.axes)...]
end
@propagate_inbounds @inline function _setindex!(::Type{IND}, A::QuasiArray, v, I::IND) where IND
@boundscheck checkbounds(A, I...)
@inbounds A.parent[findfirst.(isequal.(I), A.axes)...] = v
A
end
function _quasimatrix_pow(A, p)
axes(A,1) == axes(A,2) || throw(DimensionMismatch("axes must match"))
QuasiArray(A.parent^p, A.axes)
end
^(A::QuasiMatrix, p::Number) = _quasimatrix_pow(A, p)
^(A::QuasiMatrix, p::Integer) = _quasimatrix_pow(A, p)
==(A::QuasiArray{T,N,NTuple{N,OneTo{Int}}}, B::AbstractArray{V,N}) where {T,V,N} =
axes(A) == axes(B) && A.parent == B
==(B::AbstractArray{V,N}, A::QuasiArray{T,N,NTuple{N,OneTo{Int}}}) where {T,V,N} =
A == B
function reshape(A::QuasiVector, ax::Tuple{Any,OneTo{Int}})
@assert ax == (axes(A,1),Base.OneTo(1))
QuasiMatrix(reshape(A.parent,size(A.parent,1),1), (A.axes[1], Base.OneTo(1)))
end
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] | 2.380759 | 2,952 |
const SPEED_OF_LIGHT = 1.0
const SPEED_OF_LIGHT² = SPEED_OF_LIGHT * SPEED_OF_LIGHT
const VACUUM_PERMITTIVITY = 1.0
const VACUUM_PERMITTIVITY⁻¹ = 1 / VACUUM_PERMITTIVITY
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function murmur64(h::UInt64)
h ⊻= h >> 33
h *= 0xff51afd7ed558ccd
h ⊻= h >> 33
h *= 0xc4ceb9fe1a85ec53
h ⊻= h >> 33
return h
end
# returns random number, modifies the seed
function splitmix64(seed::UInt64)
seed += 0x9e3779b97f4a7c15
z = (seed ⊻ (seed >> 30)) * 0xbf58476d1ce4E5b9
z = (z ⊻ (z >> 27)) * 0x94d049bb133111eb
return seed, z ⊻ (z >> 31)
end
function mixsplit(key::UInt64, seed::UInt64)
return murmur64(key + seed)
end
function rotl64(n::UInt64, c::Int)
return (n << UInt64(c & 63)) | (n >> UInt64((-c) & 63))
end
function reduce(hash, n::UInt32)
# http://lemire.me/blog/2016/06/27/a-fast-alternative-to-the-modulo-reduction/
return UInt32((UInt64(hash) * UInt64(n)) >> 32)
end
# xor fold
@inline function fingerprint(::Type{UInt8}, hash::UInt64)
hash = (hash >> 32) ⊻ ((hash << 32) >> 32) # fold to 32 bits
hash = (hash >> 16) ⊻ ((hash << 48) >> 48) # fold to 16 bits
hash = (hash >> 8) ⊻ ((hash << 56) >> 56) # fold to 8 bits
return UInt8(hash)
end
@inline function fingerprint(::Type{UInt16}, hash::UInt64)
hash = (hash >> 32) ⊻ ((hash << 32) >> 32) # fold to 32 bits
hash = (hash >> 16) ⊻ ((hash << 48) >> 48) # fold to 16 bits
return UInt16(hash)
end
@inline function fingerprint(::Type{UInt32}, hash::UInt64)
hash = (hash >> 32) ⊻ ((hash << 32) >> 32) # fold to 32 bits
return UInt32(hash)
end
function mod3(x)
if (x > 2)
x -= 3
end
return x
end
function binary_fuse_mulhi(a::UInt64, b::UInt64)
return UInt64((UInt128(a) * UInt128(b)) >> 64)
end
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471,
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7,
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9609,
5598,
8,
198,
437,
628
] | 2.247407 | 675 |
using ReservoirComputing
#model parameters
res_size = 30
radius = 1.2
activation = tanh
degree = 6
sparsity = 0.5
sigma = 0.1
beta = 0.0
alpha = 1.0
nla_type = NLADefault()
in_size = 3
extended_states = false
h_steps = 2
#Let gamma be any number between 0 and 1
γ = rand()
model_in_size = 1
W = init_reservoir_givendeg(res_size, radius, degree)
train_len = 50
predict_len = 12
data = ones(Float64, in_size, 100)
train = data[:, 1:1+train_len-1]
test = data[:, train_len:train_len+predict_len-1]
#test input layers functions
input_layer = [init_input_layer, init_dense_input_layer, init_sparse_input_layer, min_complex_input, irrational_sign_input, physics_informed_input]
for t in input_layer
if t == init_sparse_input_layer
W_in = t(res_size, in_size, sigma, sparsity)
elseif t == physics_informed_input
W_in = t(res_size, in_size, sigma, γ, model_in_size)
else
W_in = t(res_size, in_size, sigma)
end
esn = ESN(W,
train,
W_in,
activation = activation,
alpha = alpha,
nla_type = nla_type,
extended_states = extended_states)
@test size(W_in, 1) == res_size
@test size(W_in, 2) == in_size
end
#test physics informed input layer function
W_in = physics_informed_input(res_size, in_size, sigma, γ, model_in_size)
#Test num weights have been alotted correctly for raw states according to the gamma chosen
@test sum(x->x!=0, W_in[:, 1:2]) == floor(Int, res_size*γ)
#Test num weights have been alotted correctly for model input according to the gamma chosen
@test sum(x->x!=0, W_in[:, 3]) == floor(Int, res_size*(1-γ))
#Test every reservoir node is connected exclusively to one state
@test length(findall(x->x>1, [sum(x->x!=0, W_in[i, :]) for i in 1:res_size])) == 0
#Test in_size to always be greater than model output size
bad_model_out_size = 10
@test_throws DimensionMismatch physics_informed_input(res_size, in_size, sigma, γ, bad_model_out_size)
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] | 2.517375 | 777 |
module GenericRegex
module IR
include("ir/graph.jl")
include("ir/opcode.jl")
include("ir/graph2opcode.jl")
end
module Parse
include("parse/unicode.jl")
end
end
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] | 2.619048 | 63 |
# # Turtle Programming
# ## Introduction
# In this tutorial we will have a look at _Turtle Programming_. In 1967 a general purpose programming language called LOGO was created. The main highlight of this language was turtle graphics. In turtle graphics we have a robot with a pen which draws on a canvas. We can control this turtle using a few commands. The main commands are :
#
# * `forward` : move the turtle forward
# * `turn` : turn the turtle
# * `penUp/penDown` : activate/deactivate the turtle's pen
#
# To get a brief understanding of how _this_ works head over [here](https://rawgit.com/wrschneider99/js-turtle/master/turtle.html).
#
# While Turtle programming generally refers to a 2-D turtle we have a 3-D version available. In the 3-D version we have three types of `turn` available for each of the dimensions of the turtle.
#
# * `pitch`
# * `yaw`
# * `roll`
#
# Let's first start with only operating on a 2-D plane and later we will discuss 3-D.
#
# You need to clear up space for experimentation. Use `setBlocks()` with PiCraft.AIR to clear up space. If you are on the Java edition then it is suggested that you use
# `New World -> Creative -> World Type: Superflat -> Customize -> Presets -> The Void -> Create New World`
# Then we can setup a canvas for drawing as follows:
using PiCraft
p = getPos()
setBlocks(p .+ (-50, 0, -50), p .+ (50, 0, 50), Block(35, 15))
# 
#
# To initialize the turtle:
t = turtle(pos = p)
# Since we are only concerned with the 2 dimensions of the plane we only need a single turn function which will be `yaw`
turn = yaw
move(t, 10)
turn(t, 45) # Note that the angle is in degrees, use `deg2rad(θ)` to convert from radians.
move(t, 10)
t.penBlock = PiCraft.IRON_BLOCK # Change penBlock
move(t, 10)
turn(t, 45)
move(t, 10)
t.penDown = false
turn(t, 90)
move(t, 10)
t.penDown = true
move(t, 10)
# 
# To reset the canvas and the turtle it can be convenient to define a function
function clrscr(t, p)
setBlocks(p .+ (-50, 0, -50), p .+ (50, 0, 50), Block(35, 15))
t.pos = p
end
clrscr(t, p)
# Draw a square
move(t, 10)
yaw(t, 90)
move(t, 10)
yaw(t, 90)
move(t, 10)
yaw(t, 90)
move(t, 10)
# 
# We can also use a 'for loop' for the same
clrscr(t, p)
for i in 1:4
move(t, 10)
yaw(t, 90)
end
# Similarly, we can draw a triangle
# Draw a triangle
clrscr(t, p)
for i in 1:3
move(t, 10)
turn(t, 120)
end
# Challenge: Figure out how to draw a general polygon using a loop
#
# Solution:
function drawPolygon(t::turtle, n::Integer, l::Real)
θ = 180 - 360/n
for i in 1:n
move(t, l)
yaw(t, θ)
end
end
clrscr(t, p)
# Star
for i in 1:5
move(t, 50)
turn(t, 144)
end
# 
# We can also make spirals.
#
# Spiral
clrscr(t, p)
for i in 1:10
move(t, 5*i)
turn(t, 90)
end
# 
clrscr(t, p)
for i in 1:10
move(t, 5 + 5*i)
turn(t, 120)
end
# 
# ---
# ## 3-D turtle
# As mentioned earlier instedad of a single `turn` command we have 3 commands, namely `yaw`, `pitch` and `roll`.
#
# 
# In essence we have 3 mutually perpendicular axis on the turtle.
#
# * Longitudinal(turtle.direction, points forward) : Roll Axis
# * Lateral : Pitch Axis
# * Vertical(turtle.normal, points downwards) : Yaw Axis
#
# To get the positive rotation direction use the [corkscrew rule](https://en.wikipedia.org/wiki/Right-hand_rule).
# 
#
# Curl your right hand's fingers with the thumb pointing outwards like in a thumbs up position. When your thumb points in the axis vector then the curl direction is the positive rotation direction.
#
# We dont need a canvas to experiment with the 3-D turtle. Reset the world as required.
move(t, 10)
pitch(t, 45)
move(t, 10)
pitch(t, -45)
yaw(t, 90)
move(t, 10)
roll(t, 90)
pitch(t, 90)
move(t, 10)
# 
#
# We can use the same concepts of the 2-D turtle to draw in 3-D.
#
# Square inclined at 45 degrees
t = turtle(pos = getPos())
pitch(t, 45)
for i in 1:4
move(t, 10)
yaw(t, 90)
end
# 
#
# Spring
t = turtle(pos = getPos())
R = 20
C = 2*pi*R
for i in 1:720
move(t, C/90)
yaw(t, 7)
pitch(t, 5)
end
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] | 2.638188 | 1,744 |
using DataInterpolations, Test
@testset "Interface" begin include("interface.jl") end
@testset "Interpolation Tests" begin include("interpolation_tests.jl") end
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31,
9288,
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366,
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341,
30307,
1,
2221,
2291,
7203,
3849,
16104,
341,
62,
41989,
13,
20362,
4943,
886,
198
] | 3.521739 | 46 |
function createSonumList(::Type{T},nbit::Int) where {T<:AbstractFloat}
return zeros(T,2^(nbit-1)+1)
end
function createSonumTable(::Type{T},nbit::Int) where {T<:AbstractFloat}
n = 2^(nbit-1)+1
A = Array{T,2}(undef,n,n)
return Symmetric(A),A
end
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# Autogenerated wrapper script for fpzip_jll for x86_64-apple-darwin
export libfpzip
JLLWrappers.@generate_wrapper_header("fpzip")
JLLWrappers.@declare_library_product(libfpzip, "@rpath/libfpzip.1.dylib")
function __init__()
JLLWrappers.@generate_init_header()
JLLWrappers.@init_library_product(
libfpzip,
"lib/libfpzip.1.3.0.dylib",
RTLD_LAZY | RTLD_DEEPBIND,
)
JLLWrappers.@generate_init_footer()
end # __init__()
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export localSympFromQuad, getDecoupleSequence, getInterferenceBasedSequence, getSequence
# From (source quadrautre, target quadratre) to Local Symplectic Matrix transforming source to Ω target
↑(m, i) = 2*m - (i % 2)
↓(m, i) = 2*m -1 + (i % 2)
getPattern(v::Vector)=(n->n>tolerance).( (diag∘sqrt∘Diagonal∘(x->x'*x)∘(v->reshape(v, 2, :)))(v) )
function Lkmij(u, v, m, i, j)
if norm(v[2*m-1:2*m])<tolerance
return i==j ? 1 : 0
else
return (-1)^(j+1)*v[↑(m, i)]*u[↓(m, j)]/( v[2*m]^2 + v[2*m-1]^2 ) + (-1)^i*v[↓(m, i)]*u[↑(m, j)]/( u[2*m]^2 + u[2*m-1]^2 )
end
end
function localSympFromQuad(u::Vector, v::Vector; lambda::Real = 1)::Symp
if length(u) % 2 !=0 || length(u) != length(v) || getPattern(u) != getPattern(v)
return error("input not valid")
end
n = length(u) ÷ 2
if n == 1
return Symp([ Lkmij(lambda * u, v, 1, i, j) for i in 1:2, j in 1:2 ])
else
return ⊕([ Symp([ Lkmij(lambda * u, v, m, i, j) for i in 1:2, j in 1:2 ]) for m in 1:n ]...)
end
end
# Get Local Operations L3 L2 L1 for the Decoupling Sequence S4 L3 S3 L2 S2 L1 S1
function getDecoupleSequence(S4::Symp, S3::Symp, S2::Symp, S1::Symp, m::Int=1)::Vector{Symp}
# if !(all(x->isGeneric(x), [S1, S2, S3, S4]) ) return error("not generic") end
L1 = localSympFromQuad(S1.S[:,2*m-1], S2.S[2*m-1,:])
L3 = localSympFromQuad(S3.S[:,2*m-1], S4.S[2*m-1,:])
T1 = S2 * L1 * S1
T2 = S4 * L3 * S3
u = T1.S[:,2*m]
v = T2.S[2*m,:] + sum( (k->T1.S[k,2*m-1]*T1.S[k,2*m]-T2.S[2*m-1,k]*T2.S[2*m,k]).(1:length(u)) ) * T2.S[2*m-1, :]
L2 = localSympFromQuad(u, v; lambda = lambda)
return [S4, L3, S3, L2, S2, L1, S1]
end
# Get local Operations L16, L15, ..., L1 for the interfernce-basded sequence LR S L15 S ... S L1 S, with a given 4×4 target Symplectic Matrix S⊙
function getSequence(Ss::Vector{Symp{T}}, modeToDecouple::Int)::Vector{Symp} where T
if length(Ss) == 4
return getDecoupleSequence(Ss..., modeToDecouple)
else
step = length(Ss) ÷ 4
Rs = [ getSequence(Ss[i:i+step-1], modeToDecouple-1 ) for i in 1:step:length(Ss) ]
Ls = getDecoupleSequence([ *(RLst...) for RLst in Rs]..., modeToDecouple)
return vcat([ (i%2==0) ? [ Ls[i] ] : Rs[(i+1) ÷ 2] for i in 1:7 ]...)
end
end
function getInterferenceBasedSequence(S::Symp, ST::Symp)::Vector{Symp}
if !(isGeneric(S)) return error("not generic") end
Ss = [S for i in 1:4^nModes(ST)]
Ss[end] = Ss[end] * (ST ⊕ Id(nModes(S) - nModes(ST)))^-1
Ss = getSequence(Ss, nModes(ST))
LR = Symp( ( *(Ss...).S[1:2*nModes(ST), 1:2*nModes(ST)]) )^-1 ⊕ Id(nModes(S) - nModes(ST))
Ss[end] = Ss[end] * (ST ⊕ Id(nModes(S) - nModes(ST)))
return vcat([ LR ] , Ss)
end
# Interference-Based Sequence with Automatic Local Randomization
function getSequenceWithRandomization(Ss::Vector{Symp{T}}, modeToDecouple::Int)::Vector{Symp} where T
if length(Ss) == 4
return getDecoupleSequence(Ss..., modeToDecouple)
else
step = length(Ss) ÷ 4
Rs = [ getSequence(Ss[i:i+step-1], modeToDecouple-1 ) for i in 1:step:length(Ss) ]
Ls = getDecoupleSequence([ *(RLst...) for RLst in Rs]..., modeToDecouple)
return vcat([ (i%2==0) ? [ Ls[i] ] : Rs[(i+1) ÷ 2] for i in 1:7 ]...)
end
end
function getIQSWithRandomization(S::Symp, ST::Symp)::Vector{Symp}
if !(isGeneric(S)) return error("not generic") end
Ss = [S for i in 1:4^nModes(ST)]
Ss[end] = Ss[end] * (ST ⊕ Id(nModes(S) - nModes(ST)))^-1
Ss = getSequenceWithRandomization(Ss, nModes(ST))
LR = Symp( ( *(Ss...).S[1:2*nModes(ST), 1:2*nModes(ST)]) )^-1 ⊕ Id(nModes(S) - nModes(ST))
Ss[end] = Ss[end] * (ST ⊕ Id(nModes(S) - nModes(ST)))
return vcat([ LR ] , Ss)
end | [
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] | 1.965571 | 1,917 |
function yaml_node_from_string(fn::AbstractString)
# Didn't find how to access the top node more easily.
#
yml_types = Dict{String,Function}()
yml_types["!Cartesian"] = ((c,n)->n)
yml_types["!Smolyak"] = ((c,n)->n)
yml_types["!Normal"] = ((c,n)->n)
yml_types["!MarkovChain"] = ((c,n)->n)
yml_types["!Product"] = ((c,n)->n)
yml_types["!PoissonProcess"] = ((c,n)->n)
yml_types["!DeathProcess"] = ((c,n)->n)
yml_types["!AgingProcess"] = ((c,n)->n)
yml_types["!VAR1"] = ((c,n)->n)
yml_types["tag:yaml.org,2002:null"] = ((c,n)->n)
yml_types["tag:yaml.org,2002:bool"] = ((c,n)->n)
yml_types["tag:yaml.org,2002:int"] = ((c,n)->n)
yml_types["tag:yaml.org,2002:float"] = ((c,n)->n)
yml_types["tag:yaml.org,2002:binary"] = ((c,n)->n)
yml_types["tag:yaml.org,2002:timestamp"] = ((c,n)->n)
yml_types["tag:yaml.org,2002:omap"] = ((c,n)->n)
yml_types["tag:yaml.org,2002:pairs"] = ((c,n)->n)
yml_types["tag:yaml.org,2002:set"] = ((c,n)->n)
yml_types["tag:yaml.org,2002:str"] = ((c,n)->n)
yml_types["tag:yaml.org,2002:seq"] = ((c,n)->n)
yml_types["tag:yaml.org,2002:map"] = ((c,n)->n)
return YAML.load(fn, yml_types)
end
function yaml_node_from_file(fn::AbstractString)
txt = open(f->read(f,String), fn)
txt = replace(txt, "\r"=>"")
return yaml_node_from_string(txt)
end
mutable struct Location
start_mark::YAML.Mark
end_mark::YAML.Mark
end
mutable struct MissingElement <: Exception
path::Vector{AbstractString}
k::Integer # index of first missing element
loc::Location
end
function Base.getindex(d::YAML.MappingNode, l::AbstractString...)
el = d
for k=1:length(l)
# if !(typeof(el)<:YAML.MappingNode)
# println("This is not going to fly")
if !(l[k] in keys(el))
loc = Location(el.start_mark, el.end_mark)
throw(MissingElement(collect(l), k, loc))
else
el = el[l[k]]
end
end
return el
end
function Base.getindex(d::YAML.MappingNode, l::Symbol...)
return Base.getindex(d, [string(e) for e in l]...)
end
mutable struct LinterException <: Exception
msg::AbstractString
loc::Location
src::AbstractString
end
mutable struct LinterWarning <: Exception
errvalue::AbstractString
errtype::AbstractString
msg::AbstractString
loc::Location
src::AbstractString
end
#LinterException(msg::AbstractString, loc::Location) = LinterException(msg, loc, "<string>")
LinterWarning(msg::AbstractString, loc::Location) = LinterWarning(msg, loc, "<string>", errtype)
function get_loc(d)
Location(d.start_mark, d.end_mark)
end
function check_name(d)
if !("name" in keys(d)) || typeof(d["name"].value ) != String || d["name"].value == ""
return false
end
end
function check_symbol_validity(sym)
# Not sure if it is necesarry to check if that's a string: yaml structure saves by default as string(??)
if typeof(sym) != String || match(r"^[a-zA-Z0-9_]*$",sym) == nothing || string(sym)[1:1] == "_"
return false
end
end
#function check_equations(d::YAML.MappingNode, filename="<string>")
#Known_equation_types -> ["transition", "arbitrage", "value", "felicity", "expectation"]
#end
function check_model_sections(d::YAML.MappingNode, filename="<string>")
errors = LinterWarning[]
warnings = LinterWarning[]
# Can add other reauired models sections: symbols, equations ...
if check_name(d) == false
if !("name" in keys(d))
msg = ""
errvalue = "name"
errtype = "Missing model part"
loc = get_loc(d)
elseif typeof(d["name"].value ) != String || d["name"].value == ""
errvalue = string(d["name"].value)
errtype = "Invalid model name"
loc = get_loc(d["name"])
msg = "Model name should be non-empty string"
# push!(errors/warnings, LinterWarning(errvalue, errtype, msg, loc, src)
end
push!(errors, LinterWarning(errvalue, errtype, msg, loc, filename))
end
return [errors, warnings]
end
function check_calibration(d::YAML.MappingNode, filename="<string>")
errors = LinterWarning[]
warnings = LinterWarning[]
model_symbol_types = keys(d[:symbols])
model_symbols = []
model_symbols_vec = []
for key in keys(d[:symbols])
n = length(d[:symbols][key].value)
for i=1:n
# would be cooler to do directly for sym in syms[vg]
sym = d[:symbols][key].value[i]
push!(model_symbols_vec, (key, sym.value, sym))
push!(model_symbols, sym.value)
end
end
model_symbols = cat(model_symbols, keys(d[:definitions]); dims=1)
for (i, key) in enumerate(keys(d["calibration"]))
if !(key in model_symbols)
errvalue = key
errtype = "Calibration not in symbols"
loc = get_loc(d["calibration"].value[i][1])
msg = string(key, " is not declared in the symbols section ")
push!(warnings, LinterWarning(errvalue, errtype, msg, loc, filename))
elseif count(c -> c == key, collect( keys(d["calibration"]))) > 1
floc = something(findfirst(isequal(key), keys(d["calibration"])), 0)
loc_first = get_loc(d["calibration"].value[floc][1])
if i > floc
errvalue = key
errtype = "Invalid calibration"
loc = get_loc(d["calibration"].value[i][1])
msg = string(key, " already declared in calibration section at line ",loc_first.start_mark.line, ", column ",loc_first.start_mark.column)
push!(errors, LinterWarning(errvalue, errtype, msg, loc, filename))
end
end
end
return [errors, warnings]
end
function check_equations(d::YAML.MappingNode, filename="<string>")
errors = LinterWarning[]
warnings = LinterWarning[]
# check symbol names:
required_equation_types = ["transition"]
optional_equation_types = ["arbitrage", "value", "felicity", "expectation", "direct_response"]
known_equation_types = cat(required_equation_types, optional_equation_types; dims=1)
model_equation_types = keys(d[:equations])
node_transition = YAML.ScalarNode[]
node_arbitrage = YAML.ScalarNode[]
for eq in d[:equations].value
if eq[1].value == "transition"
node_transition = eq[1]
elseif eq[1].value == "arbitrage"
node_arbitrage = eq[1]
end
end
for s in required_equation_types
if !(s in model_equation_types)
errvalue = string(s)
errtype = "Missing equation type"
msg = ""
loc = get_loc(d[:equations])
# push!(errors/warnings, LinterWarning(errvalue, errtype, msg, loc, src)
push!(errors, LinterWarning(errvalue, errtype, msg, loc, filename))
end
end
for (i,sg) in enumerate(keys(d["equations"]))
if !(sg in cat(known_equation_types; dims=1))
errvalue = string(sg)
errtype = "Unknown equation type"
msg = ""
# get precise location
loc = get_loc(d["equations"].value[i][1])
push!(warnings, LinterWarning(errvalue, errtype, msg, loc, filename))
end
end
if ("transition" in model_equation_types) && ("states" in keys(d[:symbols]))
n_transition = length(d[:equations]["transition"].value)
n_states = length(d[:symbols]["states"].value)
if n_transition != n_states
errvalue = string(node_transition.value)
errtype = "Invalid number of equations"
msg = "Number of transition equations should be equal to number of states"
# get precise location
loc = get_loc(node_transition)
push!(errors, LinterWarning(errvalue, errtype, msg, loc, filename))
end
end
if ("arbitrage" in model_equation_types) && ("controls" in keys(d[:symbols]))
n_arbitrage = length(d[:equations]["arbitrage"].value)
n_controls = length(d[:symbols]["controls"].value)
if n_arbitrage != n_controls
errvalue = string(node_arbitrage.value)
errtype = "Invalid number of equations"
msg = "Number of arbitrage equations should be equal to number of controls"
# get precise location
loc = get_loc(node_arbitrage.value)
push!(warnings, LinterWarning(errvalue, errtype, msg, loc, filename))
end
end
return [errors, warnings]
end
function check_symbols(d::YAML.MappingNode, filename="<string>")
### so far, this is just an example
errors = LinterWarning[]
warnings = LinterWarning[]
# check symbol names:
required_symbol_types = ["states", "controls", "exogenous", "parameters"]
optional_symbol_types = [ "values", "rewards", "expectations"]
known_symbol_types = cat(required_symbol_types, optional_symbol_types; dims=1)
model_symbol_types = keys(d[:symbols])
model_symbols = []
model_symbols_vec = []
for key in keys(d[:symbols])
n = length(d[:symbols][key].value)
for i=1:n
# would be cooler to do directly for sym in syms[vg]
sym = d[:symbols][key].value[i]
push!(model_symbols_vec, (key, sym.value, sym))
push!(model_symbols, sym.value)
end
end
for s in required_symbol_types
if !(s in model_symbol_types)
errvalue = string(s)
errtype = "Missing symbol type"
msg = ""
loc = get_loc(d[:symbols])
# push!(errors/warnings, LinterWarning(errvalue, errtype, msg, loc, src)
push!(errors, LinterWarning(errvalue, errtype, msg, loc, filename))
end
end
for (i,sg) in enumerate(keys(d["symbols"]))
if !(sg in cat(known_symbol_types; dims=1))
errvalue = string(sg)
errtype = "Unknown symbol type"
msg = ""
# get precise location
loc = get_loc(d["symbols"].value[i][1])
push!(warnings, LinterWarning(errvalue, errtype, msg, loc, filename))
end
end
for (i,m) in enumerate(values(d["symbols"]))
for (j, n) in enumerate(values(d["symbols"])[i])
sym =n.value
if check_symbol_validity(sym) == false
errvalue = string(sym)
errtype = "Invalid symbol"
loc = get_loc(n)
# get precise location
if typeof(sym) != String
msg = "symbol should be a string"
elseif match(r"^[a-zA-Z0-9_]*$",sym) == nothing
msg = "symbol should be an 'alphanumeric' string"
elseif string(sym)[1:1] == "_"
msg = "symbol should not start with a number or an underscore"
end
push!(errors, LinterWarning(errvalue, errtype, msg, loc, filename))
end
end
end
for (i,symnode) in enumerate(model_symbols_vec)
if count(c -> c == symnode[2], collect(model_symbols)) > 1
floc = something(findfirst(isequal(symnode[2]), model_symbols), 0)
loc_first = get_loc(model_symbols_vec[floc][3])
if i > floc
errvalue = symnode[2]
errtype = "Invalid symbol"
loc = get_loc(symnode[3])
msg = string(symnode[2], " already declared as '", symnode[1] , " at line ",loc_first.start_mark.line, ", column ",loc_first.start_mark.column)
push!(errors, LinterWarning(errvalue, errtype, msg, loc, filename))
end
end
end
for (i, sym) in enumerate(keys(d["definitions"]))
if check_symbol_validity(sym) == false
errvalue = string(sym)
errtype = "Invalid definition"
loc = get_loc(d["definitions"].value[i][1])
# get precise location
if typeof(sym) != String
msg = "symbol should be a string"
elseif match(r"^[a-zA-Z0-9_]*$",sym) == nothing
msg = "symbol should be an 'alphanumeric' string"
elseif string(sym)[1:1] == "_"
msg = "symbol should not start with a number or an underscore"
end
push!(errors, LinterWarning(errvalue, errtype, msg, loc, filename))
end
end
for (i, key) in enumerate(keys(d["definitions"]))
if (key in model_symbols)
floc = something(findfirst(isequal(key), model_symbols), 0)
loc_first = get_loc(model_symbols_vec[floc][3])
declared_sym_type = model_symbols_vec[floc][1]
errvalue = key
errtype = "Invalid definition"
loc = get_loc(d["definitions"].value[i][1])
msg = string(key, " already declared in symbols section as '", declared_sym_type , "' at line",loc_first.start_mark.line, ", column ",loc_first.start_mark.column)
push!(errors, LinterWarning(errvalue, errtype, msg, loc, filename))
elseif count(c -> c == key, collect( keys(d["definitions"]))) > 1
floc = something(findfirst(isequal(key), keys(d["definitions"])), 0)
loc_first = get_loc(d["definitions"].value[floc][1])
if i > floc
errvalue = key
errtype = "Invalid definition"
loc = get_loc(d["definitions"].value[i][1])
msg = string(key, " already declared in definitions section at line ",loc_first.start_mark.line, ", column ",loc_first.start_mark.column)
push!(errors, LinterWarning(errvalue, errtype, msg, loc, filename))
end
end
end
for (i,symnode) in enumerate(model_symbols_vec)
if !(symnode[2] in keys(d["calibration"]))
errvalue = symnode[2]
errtype = "Symbol not calibrated"
loc = get_loc(symnode[3])
msg = string(symnode[2], " not found in calibration section")
push!(warnings, LinterWarning(errvalue, errtype, msg, loc, filename))
end
end
return [errors, warnings]
end
function check_equations(fn::AbstractString)
d = yaml_node_from_file(fn)
errs, wars = check_equations(d, fn)
end
function check_calibration(fn::AbstractString)
d = yaml_node_from_file(fn)
errs, wars = check_calibration(d, fn)
end
function check_symbols(fn::AbstractString)
d = yaml_node_from_file(fn)
errs, wars = check_symbols(d, fn)
end
function check_model_sections(fn::AbstractString)
d = yaml_node_from_file(fn)
errs, wars = check_model_sections(d, fn)
end
function check_model(fn::AbstractString)
d = yaml_node_from_file(fn)
errs, wars = check_model(d, fn)
end
function print_error(err::LinterWarning)
printstyled("error "; color=:light_red)
print("at line ",err.loc.start_mark.line, ", column ",err.loc.start_mark.column, " : ")
print(err.errtype)
if err.msg != ""
printstyled(" '",err.errvalue,"' "; color=:light_green)
println(">> ", err.msg)
else
printstyled(" '",err.errvalue,"' "; color=:light_green)
println()
end
end
function print_warning(err::LinterWarning)
printstyled("warning "; color=:light_blue)
print("at line ",err.loc.start_mark.line, ", colummn ",err.loc.start_mark.column, " : ")
print(err.errtype)
if err.msg != ""
printstyled(" '",err.errvalue,"' "; color=:light_green)
println(">> ", err.msg)
else
printstyled(" '",err.errvalue,"' "; color=:light_green)
println()
end
end
function format_human(errors::Vector{LinterWarning}, warnings::Vector{LinterWarning})
for err in cat(errors; dims=1)
print_error(err)
end
for err in cat(warnings; dims=1)
print_warning(err)
end
end
function lint(filename::AbstractString; format=:human)
funnames = [check_model_sections, check_symbols, check_equations, check_calibration]
errors = LinterWarning[]
warnings = LinterWarning[]
for fun in funnames
errors2, warnings2 = fun(filename)
errors = cat(errors, errors2; dims=1)
warnings = cat(warnings, warnings2; dims=1)
end
if format == :human
format_human(errors,warnings)
else
println("Format '", format, "' not implemented (yet).")
end
return cat(errors, warnings; dims=1)
end
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437,
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] | 2.335772 | 6,698 |
//test 2 in julia
function a()
x = 1
while < x 4 do
x + = x 1
end
print(x)
end | [
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function logit(theta, y, x)
p = 1.0./(1.0 .+ exp.(-x*theta))
obj = y.*log.(p) .+ (log.(1.0 .- p)).*(1.0 .- y)
end
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#
# Just returns a fine mesh for the fit
#
function finexy(X,fine,model,fit)
Xmin = minimum(X)
Xmax = maximum(X)
x = collect(Xmin:(Xmax-Xmin)/fine:Xmax)
y = model(x,fit.param)
ypred = model(X,fit.param)
return x, y, ypred
end
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"""
mosaic(f::TF, layers::Vector{T}) where {TF <: Function, T <: SimpleSDMLayer}
Joins a series of _possibly_ overlapping `layers` by applying the function `f`
to the values that occupy the same cells. Note that the function `f` should
return a single value and accept an vector as input. Functions like
`Statistics.mean`, etc, work well.
Using `mosaic` with `maximum` is equivalent to `raster::merge` from the *R*
package `raster`.
"""
function mosaic(f::TF, layers::Vector{T}) where {TF <: Function, T <: SimpleSDMLayer}
# Check the dimensions
for i in 1:(length(layers)-1)
for j in 1:length(layers)
if !(all(stride(layers[i]) .≈ stride(layers[j])))
throw(DimensionMismatch("Layers $i and $j have different strides"))
end
end
end
# Check the types
itypes = eltype.(layers)
if length(unique(itypes)) > 1
@warn """
The numeric types of the layers are not unique, this can cause performance issues.
The returned layer will have $(first(itypes)).
"""
end
# Get the new bounding boxes
n_left = minimum([layer.left for layer in layers])
n_right = maximum([layer.right for layer in layers])
n_bottom = minimum([layer.bottom for layer in layers])
n_top = maximum([layer.top for layer in layers])
# Get the gridsize
nr = round(Int64, (n_top - n_bottom)/2stride(layers[1],1))
nc = round(Int64, (n_right - n_left)/2stride(layers[1],2))
# Prepare the grid
grid = fill(nothing, nc, nr)
grid = convert(Matrix{Union{Nothing,itypes[1]}}, grid)
L = SimpleSDMResponse(grid, n_left, n_right, n_bottom, n_top)
# Fill in the information
for lat in latitudes(L)
for lon in longitudes(L)
V = [layer[lon, lat] for layer in layers]
filter!(!isnothing, V)
filter!(!isnan, V)
length(V) == 0 && continue
L[lon, lat] = convert(itypes[1], f(V))
end
end
# Return
return T <: SimpleSDMResponse ? L : convert(SimpleSDMPredictor, L)
end | [
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] | 2.437718 | 859 |
using Rubin
using Tests
using Elliptic
using HypergeometricFunctions
using Polylogarithms
using SpecialFunctions
@test integrate((im+cot(x))^-1*cos(x)^4, x) == :(1//32*(im+-1*cot(x))^-2+5//32*(im+cot(x))^-2+im*(-8*cot(x)+8im)^-1+3*im*(16im+16*cot(x))^-1+-1//16*im*x+-1//24*im*(im+cot(x))^-3)
@test integrate((im+cot(x))^-1*cos(x)^3, x) == :(-1//5*cos(x)^5+-1//3*im*sin(x)^3+1//5*im*sin(x)^5)
@test integrate((im+cot(x))^-1*cos(x)^2, x) == :(1//8*(im+cot(x))^-2+im*(-8*cot(x)+8im)^-1+im*(4im+4*cot(x))^-1+-1//8*im*x)
@test integrate((im+cot(x))^-1*cos(x), x) == :(-1//3*cos(x)^3+-1//3*im*sin(x)^3)
@test integrate((im+cot(x))^-1*sec(x), x) == :(-1*cos(x)+im*sin(x)+-1*im*arctanh(sin(x)))
@test integrate((im+cot(x))^-1*sec(x)^2, x) == :(-1*log(sin(x))+im*x+-1*im*tan(x)+log(tan(x)))
@test integrate((im+cot(x))^-1*sec(x)^3, x) == :((1/2)*im*arctanh(sin(x))+-1//2*im*sec(x)*tan(x)+sec(x))
@test integrate((im+cot(x))^-1*sec(x)^4, x) == :((1/2)*tan(x)^2+-1//3*im*tan(x)^3)
@test integrate((im+cot(x))^-1*sec(x)^5, x) == :(1//3*sec(x)^3+1//8*im*arctanh(sin(x))+-1//4*im*sec(x)^3*tan(x)+1//8*im*sec(x)*tan(x))
@test integrate((im+cot(x))^-1*sec(x)^6, x) == :((1/2)*tan(x)^2+1//4*tan(x)^4+-1//3*im*tan(x)^3+-1//5*im*tan(x)^5)
@test integrate((a+b*cot(x))^-1*cos(x)^4, x) == :(-1*(4*a^2+4*b^2)^-1*sin(x)^4*(b+a*cot(x))+1//8*(a^2+b^2)^-2*sin(x)^2*(4*b*(b^2+2*a^2)+a*(b^2+5*a^2)*cot(x))+-1*b*a^4*(a^2+b^2)^-3*log(a*sin(x)+b*cos(x))+1//8*a*x*(a^2+b^2)^-3*(-1*b^4+3*a^4+-6*a^2*b^2))
@test integrate((a+b*cot(x))^-1*cos(x)^3, x) == :(a*(a^2+b^2)^-1*sin(x)+-1*a*(3*a^2+3*b^2)^-1*sin(x)^3+-1*b*(3*a^2+3*b^2)^-1*cos(x)^3+b*a^3*(a^2+b^2)^-5//2*arctanh((a^2+b^2)^-1//2*(a*cos(x)+-1*b*sin(x)))+-1*a*b^2*(a^2+b^2)^-2*sin(x)+-1*b*a^2*(a^2+b^2)^-2*cos(x))
@test integrate((a+b*cot(x))^-1*cos(x)^2, x) == :((2*a^2+2*b^2)^-1*sin(x)^2*(b+a*cot(x))+(1/2)*a*x*(a^2+b^2)^-2*(a^2+-1*b^2)+-1*b*a^2*(a^2+b^2)^-2*log(a*sin(x)+b*cos(x)))
@test integrate((a+b*cot(x))^-1*cos(x), x) == :(a*(a^2+b^2)^-1*sin(x)+-1*b*(a^2+b^2)^-1*cos(x)+a*b*(a^2+b^2)^-3//2*arctanh((a^2+b^2)^-1//2*(a*cos(x)+-1*b*sin(x))))
@test integrate((a+b*cot(x))^-1*sec(x), x) == :(a^-1*arctanh(sin(x))+b*a^-1*(a^2+b^2)^-1//2*arctanh((a^2+b^2)^-1//2*(a*cos(x)+-1*b*sin(x))))
@test integrate((a+b*cot(x))^-1*sec(x)^2, x) == :(a^-1*tan(x)+-1*b*a^-2*log(a+b*cot(x))+-1*b*a^-2*log(tan(x)))
@test integrate((a+b*cot(x))^-1*sec(x)^3, x) == :((1/2)*a^-1*arctanh(sin(x))+a^-3*b^2*arctanh(sin(x))+(1/2)*a^-1*sec(x)*tan(x)+-1*b*a^-2*sec(x)+b*a^-3*(a^2+b^2)^(1/2)*arctanh((a^2+b^2)^-1//2*(a*cos(x)+-1*b*sin(x))))
@test integrate((a+b*cot(x))^-1*sec(x)^4, x) == :(1//3*a^-1*tan(x)^3+a^-3*(a^2+b^2)*tan(x)+-1//2*b*a^-2*tan(x)^2+-1*b*a^-4*(a^2+b^2)*log(a+b*cot(x))+-1*b*a^-4*(a^2+b^2)*log(tan(x)))
@test integrate((1+2*cot(x))^-1*sec(x), x) == :(2//5*5^(1/2)*arctanh(1//5*5^(1/2)*(-2*sin(x)+cos(x)))+arctanh(sin(x)))
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] | 1.469219 | 1,933 |
function evaluate()
periodic_boundary()
reorder()
Threads.@threads for i = 1:Npart
kernel_summation(i)
end
if gradient == "IntegralApproach"
Threads.@threads for i = 1:Npart
sph[i].c11 = 0
# neighbour loop
s = index_list[i]
for t = (s - Nngb) : (s + Nngb)
t = order_periodic(t)
k = index_order[t]
sph[i].c11 += correction_matrix(i, k)
end
end
end
Threads.@threads for i = 1:Npart
# refresh
sph[i].F1 = 0
sph[i].dU = 0
sph[i].dalpha = 0
divv = 0
# neighbour loop
s = index_list[i]
for t = (s - Nngb) : (s + Nngb)
t = order_periodic(t)
k = index_order[t]
sph[i].F1 += force(i, k)
sph[i].dU += dU(i, k)
if time_dependent_viscosity
divv += divergence_v(i, k)
end
end
if time_dependent_viscosity
sph[i].dalpha = dalpha_visc(i, divv)
end
end
end
function periodic_boundary()
for i = 1:Npart
if sph[i].x < x_min
sph[i].x += lbox
elseif sph[i].x > x_max
sph[i].x -= lbox
end
end
end
function reorder()
x_array = []
for i = 1:Npart
push!(x_array, sph[i].x)
end
global index_order = sortperm(x_array)
global index_list = zeros(Int, Npart)
for i = 1:Npart
j = index_order[i]
index_list[j] = i
end
end
function order_periodic(j)
if j < 1
j += Npart
elseif j > Npart
j -= Npart
end
return j
end
function kernel_summation(i)
# search neighbour, adjust smoothing length and estimate density
evaluate_hsml(i)
density(i, volume_element)
# EoS
eos(i, volume_element)
end
function evaluate_hsml(i)
h0 = eta_hsml * (sph[i].m / sph[i].rho)
CHA = 1
iter = 0
while CHA > TOL
sph[i].hsml = h0
density(i, "mass")
h1 = h0 - g(i) / dgdh(i)
CHA = abs(h0 - h1) / 2 / (h0 + h1)
h0 = h1
iter += 1
if iter > 1e4
sph[i].hsml = h0
println("iteration loop of hsml evaluation exceeds 1e4.")
@printf("i = %d, h0 = %.7f, CHA = %.7f, g(i) = %.7f, rho = %.7f\n", i, h0, CHA, g(i), density(i, "mass"))
break
end
end
end
function g(i)
return sph[i].hsml - eta_hsml * sph[i].m / sph[i].rho
end
function dgdh(i)
drhodh = 0
sph[i].dydh = 0
s = index_list[i]
for t = (s - Nngb) : (s + Nngb)
t = order_periodic(t)
k = index_order[t]
drhodh += sph[k].m * dWdh(i, k)
sph[i].dydh += Z(k) * dWdh(i, k)
end
dgdh = 1 + eta_hsml * sph[i].m / sph[i].rho^2 * drhodh
return dgdh
end
function density(i::Int, Z_input)
y = 0
# particle "i" is sth particle from left
s = index_list[i]
# take kernel summation for 2Nngb particles around particle "i"
for t = (s - Nngb) : (s + Nngb)
# consider tth particle from left
t = order_periodic(t)
# k is the index number of tth particle from left
k = index_order[t]
if Z_input == "mass"
y += sph[k].m * W(i, k)
elseif Z_input == "U"
y += sph[k].U * (gamma - 1) * W(i, k)
else
@assert 0
end
end
if Z_input == "mass"
sph[i].rho = y
elseif Z_input == "U"
sph[i].P = y
else
@assert 0
end
end
function eos(i::Int, Z_input)
if sph[i].U < 0
@show i, sph[i].x, sph[i].p / sph[i].m
end
@assert sph[i].U > 0
if Z_input == "mass"
sph[i].P = (gamma - 1) * sph[i].rho / sph[i].m * sph[i].U
elseif Z_input == "U"
sph[i].rho = sph[i].P / (gamma - 1) * sph[i].m / sph[i].U
else
@assert 0
end
end
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] | 1.968018 | 1,751 |
# Maybe a fancy trick shot isn't the best idea; after all, you only have one
# probe, so you had better not miss.
#
# To get the best idea of what your options are for launching the probe, you
# need to find every initial velocity that causes the probe to eventually be
# within the target area after any step.
#
# In the above example, there are 112 different initial velocity values that
# meet these criteria:
#
# 23,-10 25,-9 27,-5 29,-6 22,-6 21,-7 9,0 27,-7 24,-5
# 25,-7 26,-6 25,-5 6,8 11,-2 20,-5 29,-10 6,3 28,-7
# 8,0 30,-6 29,-8 20,-10 6,7 6,4 6,1 14,-4 21,-6
# 26,-10 7,-1 7,7 8,-1 21,-9 6,2 20,-7 30,-10 14,-3
# 20,-8 13,-2 7,3 28,-8 29,-9 15,-3 22,-5 26,-8 25,-8
# 25,-6 15,-4 9,-2 15,-2 12,-2 28,-9 12,-3 24,-6 23,-7
# 25,-10 7,8 11,-3 26,-7 7,1 23,-9 6,0 22,-10 27,-6
# 8,1 22,-8 13,-4 7,6 28,-6 11,-4 12,-4 26,-9 7,4
# 24,-10 23,-8 30,-8 7,0 9,-1 10,-1 26,-5 22,-9 6,5
# 7,5 23,-6 28,-10 10,-2 11,-1 20,-9 14,-2 29,-7 13,-3
# 23,-5 24,-8 27,-9 30,-7 28,-5 21,-10 7,9 6,6 21,-5
# 27,-10 7,2 30,-9 21,-8 22,-7 24,-9 20,-6 6,9 29,-5
# 8,-2 27,-8 30,-5 24,-7
#
# How many distinct initial velocity values cause the probe to be within the
# target area after any step?
# read input
(targetx1, targetx2, targety1, targety2) = parse.(
Int,
match(
r"x=(-?\d+)..(-?\d+), y=(-?\d+)..(-?\d+)",
readline("input.txt")
)
)
# The sum of consecutive integers from 0 to n is n(n+1)/2. Using this, we can
# find the minimum possible starting x velocity by solving n(n+1)/2=targetx1-1.
# Anything equal to or less than that result will fall to a velocity of zero
# before reaching the target zone.
# n(n+1)/2=targetx1-1
# n^2 + n - 2*(targetx1-1) = 0
# n = (-b +- sqrt(b^2 - 4ac)) / 2a
minimum_xvel = floor(Int, sqrt(1 + 8 * (targetx1-1)) / 2)
# Our minimum starting y velocity is equal to the minimum target y because
# anything less than that will overshoot our target y on the very first step.
# See part 1 for an explanation of how to find the maximum starting y velocity.
#
# From a giving y velocity, we can determine how many steps it'll take to reach
# the target y. From that, we can find what x velocities will get us in the
# target x range. Then we increment our starting y velocity and do it again.
cnt = 0
for yvel in targety1:(abs(targety1)-1)
inityvel = yvel
# I feel like there's some mathematical way to calculate how many steps it'll
# take to reach the target y zone with an initial y velocity, but I can't
# brain it at the moment, so...
steps = 0
if yvel > 0
# I did brain this little optimization: when our initial y velocity is
# positive, it'll take 2*yvel+1 steps to get to a y position of 0, at which
# point our velocity will be -yvel-1
steps = 2 * yvel + 1
yvel = -yvel - 1
end
# find the minimum number of steps required to reach the target y range
# yvel is guaranteed non-positive at this point
ypos = 0
while ypos > targety2
ypos += yvel
yvel -= 1
steps += 1
end
# a given initial y velocity may hit the target y range more than once - we
# need to keep track of the x velocities we've already matched so we don't
# count them again
matched_x = Int[]
while ypos >= targety1
# Maximum x velocity is the point where steps(max+(max-steps+1))/2=targetx2
# steps*max + steps*max - steps^2 + steps = 2*targetx2
# 2*steps*max = 2*targetx2 + steps^2 - steps
# max = targetx2/steps + steps/2 - 1/2
# This isn't quite right, but my brain is done.
for xvel in minimum_xvel:floor(Int, targetx2 / steps + steps / 2 - 0.5)
initxvel = xvel
xpos = 0
for _ in 1:steps
xpos += xvel
xvel -= 1
xvel == 0 && break
end
if targetx1 <= xpos <= targetx2 && !in(initxvel, matched_x)
global cnt += 1
println(initxvel, ",", inityvel, ": ", steps, " - ", xpos, ",", ypos)
push!(matched_x, initxvel)
end
end
ypos += yvel
yvel -= 1
steps += 1
end
end
println("Result: ", cnt)
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] | 2.396483 | 1,763 |
function initlearning(N,T,J,Choice,y,x)
bigN = zeros(Int64,J)
bstart = zeros(size(x,2),J)
resid = Array{Float64}[]
abilsub = Array{Float64}[]
Resid = zeros(size(y))
Csum = zeros(N*S,J)
tresid = zeros(N*S,J)
for j=1:J
bigN[j] = sum(Choice.==j) # later sum needs to be weighted by PTypesl
flag = y[:,j].!=999
bstart[:,j] = x[flag,:,j]\y[flag,j]
push!(resid ,y[flag,j].-x[flag,:,j]*bstart[:,j])
push!(abilsub,y[flag,j].-x[flag,:,j]*bstart[:,j])
Resid[vec(Choice.==j),j] = resid[j]
Csum[:,j] = (sum(reshape(Choice.==j,(T,N*S));dims=1))'
tresid[:,j] = (sum(reshape(Resid[:,j],(T,N*S));dims=1))'
end
abil = tresid./(Csum.+eps())
abil = kron(abil,ones(T,1))
Psi1 = deepcopy(Csum)
for j=1:J
resid[j] .+= abil[vec(Choice.==j),j]
Resid[vec(Choice.==j),j] = resid[j]
end
sig2=zeros(500,J)
cov2=zeros(500,convert(Int64,(J+1)*J/2))
sigtemp = zeros(J,1)
covtemp = zeros(J)
return bigN,bstart,resid,abilsub,Resid,Csum,tresid,Psi1,sig2,cov2,sigtemp,covtemp
end
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abstract type RatesCacheTrait end
struct HasRates <: RatesCacheTrait end
# populate the rates vector with each jump's propensity
@inline function update_jump_rates!(::HasRates, rates, total_rate, state, model)
total_rate = zero(total_rate)
for j in eachindex(rates)
rate_j = rate(model, state, j)
@inbounds rates[j] = rate_j
@fastmath total_rate += rate_j
end
return total_rate
end
# populate the rates vector with each reaction channel's propensity evaluated at x,
# given that reaction R_k occured
@inline function update_jump_rates!(::HasRates, rates, total_rate, state, model, k)
for j in dependents(model.dep_graph, k)
rate_j = rate(model, state, j)
@inbounds @fastmath total_rate += rate_j - rates[j]
@inbounds rates[j] = rate_j
end
return total_rate
end
@inline function update_jump_rates!(::HasRates, rates, total_rate, state, model::InteractingParticleSystem, unused)
xdiff = state.xdiff
reactions = model.reactions
for s in eachindex(xdiff)
if xdiff[s]
for j in eachindex(rates)
rxn = reactions[j]
if s == rxn.class
rate_j = rate(model, state, j)
@inbounds @fastmath total_rate += rate_j - rates[j]
@inbounds rates[j] = rate_j
end
end
end
end
return total_rate
end
# linear search
@inline function search_jump_rates(::HasRates, rates, total_rate)
u = rand() * total_rate
c = zero(total_rate)
j = 0
for rate in rates
c += rate
j += 1
c >= u && break
end
return j
end
struct HasSums <: RatesCacheTrait end
# populate the rates vector with partial sums of the reaction channels' propensities evaluated at x
@inline function update_jump_rates!(::HasSums, rates, total_rate, state, model)
rates[1] = rate(model, state, 1)
for j in 2:length(rates)
@fastmath rates[j] = rates[j - 1] + rate(model, state, j)
end
return rates[end]
end
# binary search on jump rates
@inline function search_jump_rates(::HasSums, rates, total_rate)
return searchsortedfirst(rates, rand() * total_rate)
end
# search on jump times
@inline function search_jump_times(::HasRates, rates)
n = length(rates)
j = 1
@inbounds s = randexp() / rates[1]
for k in 2:n
@inbounds w = randexp() / rates[k]
if w < s
j = k
s = w
end
end
return (j, s)
end | [
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] | 2.473469 | 980 |
function part1(input)
start = map_cave(input)
n = Ref(0)
find_paths(start, n, false)
return n[]
end
function part2(input)
start = map_cave(input)
n = Ref(0)
find_paths(start, n, true)
return n[]
end
mutable struct Cave
name::Symbol
small::Bool
visited::Bool
neighbors::Vector{Cave}
end
Cave(name) = Cave(Symbol(name), all(islowercase, collect(name)), false, Cave[])
function map_cave(input)
caves = Dict{String, Cave}()
for line in eachline(input)
cave1, cave2 = get_cave.(Ref(caves), split(line, "-"))
push!(cave1.neighbors, cave2)
push!(cave2.neighbors, cave1)
end
return caves["start"]
end
get_cave(caves, name) = get!(() -> Cave(name), caves, name)
function find_paths(cave, n, allow_second_visit)
if cave.name == :end
n[] += 1
return
end
second_visit = false
if cave.small && cave.visited
if !allow_second_visit || cave.name == :start
return
end
second_visit = true
allow_second_visit = false
end
cave.visited = true
for neighbor in cave.neighbors
find_paths(neighbor, n, allow_second_visit)
end
if !second_visit
cave.visited = false
end
end
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] | 2.170984 | 579 |
"""
Sampling parameters to use with a texture.
"""
Base.@kwdef struct Sampling
magnification::Vk.Filter = Vk.FILTER_CUBIC_IMG
minification::Vk.Filter = Vk.FILTER_CUBIC_IMG
mipmap_mode::Vk.SamplerMipmapMode = Vk.SAMPLER_MIPMAP_MODE_LINEAR
address_modes::NTuple{3,Vk.SamplerAddressMode} = ntuple(Returns(Vk.SAMPLER_ADDRESS_MODE_CLAMP_TO_BORDER), 3)
mip_lod_bias::Float32 = 0.
anistropy_enable::Bool = true
max_anisotropy::Float32 = 16.
compare_enable::Bool = false
compare_op::Vk.CompareOp = Vk.COMPARE_OP_GREATER_OR_EQUAL
lod_bounds::NTuple{2,Float32} = (0., 1000.)
border_color::Vk.BorderColor = Vk.BORDER_COLOR_INT_OPAQUE_BLACK
unnormalized_coordinates::Bool = false
end
function Vk.Sampler(device, sampling::Sampling)
create_info = Vk.SamplerCreateInfo(
sampling.magnification,
sampling.minification,
sampling.mipmap_mode,
sampling.address_modes...,
sampling.mip_lod_bias,
sampling.anistropy_enable,
sampling.max_anisotropy,
sampling.compare_enable,
sampling.compare_op,
sampling.lod_bounds...,
sampling.border_color,
sampling.unnormalized_coordinates,
)
unwrap(Vk.create_sampler(device, create_info))
end
const DEFAULT_SAMPLING = Sampling()
"""
Texture identified by name with sampling parameters.
This texture is to be transformed into a texture index (to index into an array of sampled images or combined image-samplers depending on whether sampling parameters are provided) to be included as a material parameter in push constant data.
"""
struct Texture
name::Symbol
sampling::Union{Nothing,Sampling}
end
Texture(name::Symbol) = Texture(name, nothing)
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] | 2.51895 | 686 |
"""
MicrophysicsParameters
Module containing 1-moment bulk microphysics parameters.
"""
module MicrophysicsParameters
using CLIMA.ParametersType
@exportparameter MP_n_0 8e6 * 2 "Marshall-Palmer distribution n_0 coeff [1/m4]"
@exportparameter C_drag 0.55 "drag coefficient for rain drops [-]"
@exportparameter τ_cond_evap 10 "condensation/evaporation timescale [s]"
@exportparameter q_liq_threshold 5e-4 "autoconversion threshold [-] ∈(0.5, 1) * 1e-3 "
@exportparameter τ_acnv 1e3 "autoconversion timescale [s] ∈(1e3, 1e4) "
@exportparameter E_col 0.8 "collision efficiency [-]"
@exportparameter a_vent 1.5 "ventilation factor coefficient [-]"
@exportparameter b_vent 0.53 "ventilation factor coefficient [-]"
@exportparameter K_therm 2.4e-2 "thermal conductivity of air [J/m/s/K] "
@exportparameter D_vapor 2.26e-5 "diffusivity of water vapor [m2/s]"
@exportparameter ν_air 1.6e-5 "kinematic viscosity of air [m2/s]"
@exportparameter N_Sc ν_air/D_vapor "Schmidt number [-]"
end
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] | 2.083045 | 578 |
abstract type Gate end
struct QulacsGate <: Gate
pyobj::PyObject
end
function RX(target::Int, angle::Float64)
QulacsGate(qulacs.gate.RX(target, angle))
end
function RY(target::Int, angle::Float64)
QulacsGate(qulacs.gate.RY(target, angle))
end
function RZ(target::Int, angle::Float64)
QulacsGate(qulacs.gate.RZ(target, angle))
end
function get_matrix(gate::QulacsGate)
gate.pyobj.get_matrix()
end | [
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] | 2.44186 | 172 |
using NLSolvers
NLE_PROBS = Dict()
# Rosenbrock
# Source: MINPACK
NLE_PROBS["rosenbrock"] = Dict()
NLE_PROBS["rosenbrock"]["array"] = Dict()
function F_rosenbrock!(Fx, x)
Fx[1] = 1 - x[1]
Fx[2] = 10(x[2] - x[1]^2)
return Fx
end
function J_rosenbrock!(Jx, x)
Jx[1, 1] = -1
Jx[1, 2] = 0
Jx[2, 1] = -20 * x[1]
Jx[2, 2] = 10
return Jx
end
function FJ_rosenbrock!(Fx, Jx, x)
F_rosenbrock!(Fx, x)
J_rosenbrock!(Jx, x)
Fx, Jx
end
function Jvop_rosenbrock!(x)
function JacV(Fv, v)
Fv[1] = -1 * v[1]
Fv[2,] = -20 * x[1] * v[1] + 10 * v[2]
end
LinearMap(JacV, length(x))
end
NLE_PROBS["rosenbrock"]["array"]["x0"] = [-1.2, 1.0]
NLE_PROBS["rosenbrock"]["array"]["mutating"] = NLSolvers.VectorObjective(
F_rosenbrock!,
J_rosenbrock!,
FJ_rosenbrock!,
Jvop_rosenbrock!,
)
function F_powell_singular!(x::Vector, Fx::Vector, Jx::Union{Nothing,Matrix} = nothing)
if !(Fx isa Nothing)
Fx[1] = x[1] + 10x[2]
Fx[2] = sqrt(5) * (x[3] - x[4])
Fx[3] = (x[2] - 2x[3])^2
Fx[4] = sqrt(10) * (x[1] - x[4])^2
end
if !(Jx isa Nothing)
fill!(Jx, 0)
Jx[1, 1] = 1
Jx[1, 2] = 10
Jx[2, 3] = sqrt(5)
Jx[2, 4] = -Jx[2, 3]
Jx[3, 2] = 2(x[2] - 2x[3])
Jx[3, 3] = -2Jx[3, 2]
Jx[4, 1] = 2sqrt(10) * (x[1] - x[4])
Jx[4, 4] = -Jx[4, 1]
end
objective_return(Fx, Jx)
end
function Jvop_powell_singular(x)
function JacV(Fv, v)
Fv[1] = v[1] + 10 * v[2]
Fv[2] = (v[3] - v[4]) * sqrt(5)
xx23 = 2 * x[2] - 4 * x[3]
Fv[3] = v[2] * xx23 - v[3] * xx23 * 2
xx41 = 2 * sqrt(10) * (x[1] - x[4])
Fv[4] = v[1] * xx41 - v[4] * xx41
end
LinearMap(JacV, length(x))
end
#=
NLE_PROBS["quantile"] = Dict()
NLE_PROBS["quantile"]["number"] = Dict()
@inline quantile_f(Fx, x) = log(max(x, 0.000001))
@inline quantile_j(Jx, x) = 1.0/x
@inline function quantile_fj(Fx, Jx, x)
Fx = quantile_f(Fx, x)
Jx = quantile_j(Jx, x)
Fx, Jx
end
NLE_PROBS["quantile"]["number"]["x0"] = 0.5
NLE_PROBS["quantile"]["number"]["mutating"] = quantobj
function f()
quantile_f(Fx, x) = log(max(x, 0.000001))
quantile_j(Jx, x) = 1.0/x
function quantile_fj(Fx, Jx, x)
Fx = quantile_f(Fx, x)
Jx = quantile_j(Jx, x)
Fx, Jx
end
quantobj = NLSolvers.VectorObjective(quantile_f, quantile_j, quantile_fj, nothing)
quantproblem = NEqProblem(quantobj, nothing, NLSolvers.Euclidean(0), NLSolvers.OutOfPlace())
method = LineSearch(Newton())
options = NEqOptions()
state = NLSolvers.init(quantproblem, method, 3.0)
@time res = solve(quantproblem, 0.4, method, options, state)
@time res = solve(quantproblem, 0.4, method, options, state)
end
quantile_f(Fx, x) = log(max(x, 0.000001))
quantile_j(Jx, x) = 1.0/x
function quantile_fj(Fx, Jx, x)
Fx = quantile_f(Fx, x)
Jx = quantile_j(Jx, x)
Fx, Jx
end
const quantobj = NLSolvers.VectorObjective(quantile_f, quantile_j, quantile_fj, nothing)
const quantproblem = NEqProblem(quantobj, nothing, NLSolvers.Euclidean(0), NLSolvers.OutOfPlace())
method = LineSearch(Newton())
options = NEqOptions()
state = NLSolvers.init(quantproblem, method, 3.0)
@time res = solve(quantproblem, 0.4, method, options, state)
@time res = solve(quantproblem, 0.4, method, options, state)
=#
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46249,
198
] | 1.843511 | 1,834 |
module symbolic_repr
export filler, output, maxHarm, concatFiller,build_candidates
mutable struct filler
sym::String
voiced::Bool
aspirated::Bool
act::Float64
end
Base.show(io::IO, x::filler) = print(io, "$(x.sym) : $(x.act)")
mutable struct output
root_initial::filler
root_final::filler
suffix::filler
repr::String
harmony::Float64
end
Base.show(io::IO, x::output) = print(io, "$(x.repr) : harmony: $(x.harmony) ($(x.root_initial.sym) : $(x.root_initial.act), $(x.root_final.sym) : $(x.root_final.act), $(x.suffix.sym) : $(x.suffix.act))")
"""Join representations of two or three fillers into a string"""
function concatFiller(x::filler, y::filler, z::filler=nothing)
if z == nothing
repr = x.sym * y.sym
else
repr = x.sym * y.sym * z.sym
end
return repr
end
"""Build all possible combinations
Each candidate will be a Vector with the following elements
initial, final, suffix, string_repr, placeholder for harmony
"""
function build_candidates(initial::Vector{filler}, medial::Vector{filler}, suffix::Vector{filler})
candidates = []
for c_i ∈ initial
for c_f ∈ medial
for c_s ∈ suffix
cand = output(c_i, c_f, c_s, concatFiller(c_i, c_f, c_s),-Inf)
push!(candidates, cand)
end
end
end
return candidates
end
"""Find the candidate with the highest harmony
Return a tuple winner, maxh where
__winner__ : the winner
__maxh__ : harmony of the winner
"""
function maxHarm(candidates::Vector{Any})
max_h = -Inf
winner = []
for el in candidates
if el.harmony > max_h
max_h = el.harmony
winner = el.repr
end
end
return (winner, max_h)
end
"""Decrease gradient activations for wrong winners"""
function decrease_activations(x::output)
(x.root_initial.act > 0.05 && x.root_initial.act < 1 ) ? x.root_initial.act -= 0.02 : nothing
(x.root_final.act > 0.05 && x.root_final.act < 1) ? x.root_final.act -= 0.02 : nothing
(x.suffix.act > 0.05 && x.suffix.act < 1) ? x.suffix.act -= 0.02 : nothing
end
"""Increase activations for the winner"""
function increase_activations(x::output)
x.root_initial.act < 1 ? x.root_initial.act += 0.02 : nothing
x.root_final.act < 1 ? x.root_final.act += 0.02 : nothing
x.suffix.act < 1 ? x.suffix.act += 0.02 : nothing
end
end # module
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437,
628,
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] | 2.450761 | 985 |
"""
Node
Abstract type for nodes in the AST tree.
"""
abstract type Node end | [
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] | 2.866667 | 30 |
@testset "Map" begin
include("Map/FqPolyRing.jl")
end
| [
31,
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push!(LOAD_PATH, "./")
using CAS_QMDP
using ArgParse
# Default:
# penalty_action=0.02,
# penalty_closeness=10.0,
# penalty_nmac=1000.0,
# penalty_conflict=1.0
function parse_commandline()
s = ArgParseSettings()
@add_arg_table s begin
"--filename"
help = "Filename of the alpha matrix"
arg_type = String
default = "default_filename"
"--sample"
help = "If using random sampled noise"
arg_type = Bool
default = false
"--discount"
help = "Discount factor"
arg_type = Float64
default = 0.95
"--penalty_action"
help = "Reward function parameter: penalty on action"
arg_type = Float64
default = 5.0
"--penalty_closeness"
help = "Reward function parameter: penalty on closeness between agents"
arg_type = Float64
default = 1.0
"--penalty_nmac"
help = "Reward function parameter: penalty on near mid-air collisions"
arg_type = Float64
default = 1000.0
"--penalty_conflict"
help = "Reward function parameter: penalty on conflict"
arg_type = Float64
default = 50.0
end
return parse_args(s)
end
function main()
parsed_args = parse_commandline()
filename = parsed_args["filename"]
if_sample = parsed_args["sample"]
discount = parsed_args["discount"]
penalty_action = parsed_args["penalty_action"]
penalty_closeness = parsed_args["penalty_closeness"]
penalty_nmac = parsed_args["penalty_nmac"]
penalty_conflict = parsed_args["penalty_conflict"]
if filename == "default_filename"
filename = disc * "_maxdist_2km_nmac_150m" *
"_Discount_" * string(discount) *
"_ActWeight_" * string(actual_weight)[1 : min(length(string(actual_weight)), 4)] *
"_IfSample_" * string(if_sample) *
"_PenAction_" * string(penalty_action) *
"_PenConflict_" * string(penalty_conflict) *
"_PenCloseness_" * string(penalty_closeness) *
"_PenNmac_" * string(penalty_nmac) *
sigma_str
end
# filename = "test_mid2_2"
open("./VICAS_parameter_sweep_logs.csv", "a") do io
@printf(io, "\n")
@printf(io, "%s,%s,%f,%f,%f,%f,%f,%f,%f",
string(Dates.now()), disc, penalty_action, penalty_closeness, penalty_nmac, penalty_conflict,
sigma_v, sigma_alert_deg, sigma_coc_deg)
end
policy = qmdp(filename,
discount=discount,
if_sample=if_sample,
penalty_action=penalty_action,
penalty_conflict=penalty_conflict,
penalty_closeness=penalty_closeness,
penalty_nmac=penalty_nmac)
write_alphas(policy, filename)
end
main() | [
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] | 2.379942 | 1,037 |
@testset "test function create_impedance_perturbation" begin
file = "../test/data/matpower/case5.m"
# Set up dummy scenario
data = PMs.parse_file(file)
α = 0.01
ϵ = 1
λ = 50
# Apply the perturbation to this scenario
perturbed_data = PMPP.create_impedance_perturbation(data, α, ϵ, λ)
# Check that the new parameters have been returned
@test haskey(perturbed_data, "g_lb")
@test haskey(perturbed_data, "g_ub")
@test haskey(perturbed_data, "b_lb")
@test haskey(perturbed_data, "b_ub")
# Check that all other required parameters have been returned
for (key, value) in data
@test haskey(perturbed_data, key)
end
end
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] | 2.481884 | 276 |
"""
module DielectricFunctions
for defining dielectric and pump functions either as piecewise constant
or with user-supplied functions
"""
module DielectricFunctions
export DielectricFunction,
PumpFunction,
piecewise_constant_ε,
piecewise_constant_F
"""
struct DielectricFunction
---
DielectricFunction(n1=1,n2=0) -> dielectric
DielectricFunction(n::Complex) -> dielectric
piecewise constant dielectric function with index given by `n1+1im*n2`
---
DielectricFunction(ε::Function, parameters::Dict) -> dielectric
ε is any function with the signature ε(x,y,parameters::Dict{Symbol,Float64})
which evaluates to the dielectric at position `x,y`. For example:
ε(x,y,params) = 2+sin(2πx/params[:period])
---
(::DielectricFunction)(x,y) -> ε
"""
struct DielectricFunction
ε::Function
parameters::Dict{Symbol,Float64}
DielectricFunction(ε::Function=piecewise_constant_ε,
parameters::Dict{Symbol,T}=Dict(:n₁=>1,:n₂=>0)
) where T<:Number = new(ε,parameters)
DielectricFunction(n::Complex) = DielectricFunction(real(n),imag(n))
function DielectricFunction(n1::Real,n2::Real=0.0)
parameters = Dict(:n₁=>n1,:n₂=>n2)
return DielectricFunction(piecewise_constant_ε,parameters)
end
(df::DielectricFunction)(x::Number,y::Number) = df.ε(x,y,df.parameters)
function Base.show(io::IO,d::DielectricFunction)
print(io, "DielectricFunction: ")
if d.ε==piecewise_constant_ε
print(io, "piecewise_constant_ε: ",d.parameters[:n₁]+1im*d.parameters[:n₂])
else
print(io, d.ε,": ", d.parameters)
end
end
end
"""
struct PumpFunction
---
PumpFunction(F=0) -> pump
piecewise constant pump function with pump parameter given by `F`
---
PumpFunction(F::Function, parameters::Dict) -> pump
F is any real function with the signature F(x,y,parameters::Dict{Symbol,Float64})
which evaluates to the pump profile at position `x,y`. For example:
F(x,y,params) = sin(2πx/params[:period])
---
(::PumpFunction)(x,y) -> F
"""
struct PumpFunction
F::Function
parameters::Dict{Symbol,Float64}
PumpFunction(F::Function=piecewise_constant_F,
parameters::Dict{Symbol,T}=Dict(:F=>0)
) where T<:Number = new(F,parameters)
function PumpFunction(F::Real)
parameters = Dict(:F=>F)
return PumpFunction(piecewise_constant_F,parameters)
end
(pf::PumpFunction)(x::Number,y::Number) = pf.F(x,y,pf.parameters)
function Base.show(io::IO,d::PumpFunction)
print(io, "PumpFunction: ")
if d.F==piecewise_constant_F
print(io, "piecewise_constant_F: ",d.parameters[:F])
else
print(io, d.F,": ", d.parameters)
end
end
end
"""
piecewise_constant_ε(x,y,parameters) -> ε
"""
function piecewise_constant_ε(x::Number,y::Number,parameters::Dict)
n1 = get!(parameters,:n₁,nothing)
n2 = get!(parameters,:n₂,nothing)
return complex(n1,n2)^2
end
"""
piecewise_constant_F(x,y,parameters) -> F
"""
piecewise_constant_F(x::Number,y::Number,parameters::Dict) = get!(parameters,:F,nothing)
end # module
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] | 2.338257 | 1,354 |
function macWithCarry(a::ArbDigit, b::ArbDigit, c::ArbDigit, carry::DoubleArbDigit)
@assert carry < (one(DoubleArbDigit) << BITS)
carry += DoubleArbDigit(a) + DoubleArbDigit(b) * DoubleArbDigit(c)
return carry % ArbDigit, carry >> BITS
end
function mulWithCarry(a::ArbDigit, b::ArbDigit, cin::DoubleArbDigit)
cout = DoubleArbDigit(a) * DoubleArbDigit(b) + cin
return cout % ArbDigit, cout >> BITS
end
function macDigit!(acc::AbstractVector{ArbDigit}, b::AbstractVector{ArbDigit}, c::ArbDigit)
iszero(c) && return
# we need to make sure that we have enough space
# meaning length(b) +1 for carry
@assert length(acc) > length(b) "accumulator needs extra space for carry!"
carry = zero(DoubleArbDigit)
a_lo = @view acc[begin:length(b)]
a_hi = @view acc[length(b)+1:end]
# we want to add `b*c+carry` into `acc`,
# so we add elementwise into the lower
# length(b) digits of `acc`.
# whatever is left over is our true carry.
for (a,(i,b)) in zip(a_lo, enumerate(b))
a_lo[i], carry = macWithCarry(a, b, c, carry)
end
carry_hi, carry_lo = fromDoubleArbDigit(carry)
# if we have carry from multiplying, we add it here
final_carry = if iszero(carry_hi)
_add2!(a_hi, carry_lo)
else
_add2!(a_hi, [carry_hi, carry_lo])
end
# there should never be anything left over
# i.e. if this assert fires, the one above
# should also have fired already
@assert iszero(final_carry) "carry overflow during multiplication!"
end
function long_mul!(acc::AbstractVector{ArbDigit}, b::AbstractVector{ArbDigit}, c::AbstractVector{ArbDigit})
# naive long multiplication
# multiply each digit of `c` with `b` and
# write to `acc`
for (i,ci) in enumerate(c)
macDigit!(@view(acc[i:end]), b, ci)
end
end
function karatsuba!(acc::AbstractVector{ArbDigit}, a::AbstractVector{ArbDigit}, b::AbstractVector{ArbDigit})
#= karatsuba multiplication
exponents are just for numbering, not power function
power is denoted by ^
write x*y in two parts:
a = a¹ * sh + a²
b = b¹ * sh + b²
now this becomes
a*b = (a¹ * sh + a²) * (b¹ * sh + b²)
= a¹ * b¹ * sh^2
+ (a² * b¹ + a¹ * b²) * sh
+ a² * b²
now set p¹ = a¹ * b¹ and p³ = a² * b²:
a*b = p¹ * sh^2
+ (a² * b¹ + a¹ * b²) * sh
+ p³
here comes karatsuba's trick:
a¹ * b² + a² * b¹
= a¹ * b² + a² * b¹ - p¹ + p¹ - p³ + p³
= a¹ * b² + a² * b¹ - a¹ * b¹ - a² * b² + p¹ + p³
= -(a¹ * b¹ - a¹ * b² - a² * b¹ + a² * b²) + p¹ + p³
= -((a² - a¹) * (b² - b¹)) + p¹ + p³
so we now have p² = (a² - a¹) * (b² - b¹) and thus
a*b = p¹ * sh^2
+ (p¹ + p³ - p²) * sh
+ p³
so our intermediate products are
p¹ = a¹ * b¹
p² = (a² - a¹) * (b² - b¹)
p³ = a² * b²
which we can use to rearrange the above like so
a*b = p¹ * sh^2
+ p¹ * sh
+ p³ * sh
- p² * sh
+ p³
= p³
+ p³ * sh
+ p¹ * sh
+ p¹ * sh^2
- p² * sh
with evaluation order from top to bottom. This means,
by offsetting our index instead of really multiplying
by `sh`, we can only calculate p¹, p² and p³ once each
and reuse the result when adding. Subtracting p²*sh at
the end is done to ensure we don't go negative. An
informal argument for that is that we're multiplying
positive integers - that can't ever give a negative
result and since all transformations above are valid,
the result has to be positive as well. However, to ensure
we don't go negative during an intermediate step, we
make sure to subtract as the last step.
=#
short, long = length(a) < length(b) ? (a,b) : (b,a)
@assert length(short) <= length(long)
@assert length(acc) >= length(short)+length(long)
short_half_len = div(length(short), 2)
short² = @view short[begin:short_half_len]
short¹ = @view short[short_half_len+1:end]
long² = @view long[begin:short_half_len]
long¹ = @view long[short_half_len+1:end]
# uppers are longer, so we need at most that space
p_len = length(short¹) + length(long¹)
p = Vector{ArbDigit}(undef, p_len)
p_num = ArbUInt(p)
resize!(p, p_len)
fill!(p, zero(ArbDigit))
# p³ = a² * b²
mac3!(p, short², long²)
normalize!(p_num) # remove excess zeros
# acc += p³
add2!(acc, p)
# acc += p³*sh
add2!(@view(acc[short_half_len+1:end]), p)
# zero buffer
resize!(p, p_len)
fill!(p, zero(ArbDigit))
# p¹ = a¹ * b¹
mac3!(p, short¹, long¹)
normalize!(p_num) # remove excess zeros
# acc += p¹*sh
add2!(@view(acc[short_half_len+1:end]), p)
# acc += p¹*sh^2
add2!(@view(acc[2*short_half_len+1:end]), p)
# now for p²
# p² = (a² - a¹) * (b² - b¹)
# tmp¹ = a² - a¹
# tmp² = b² - b¹
# this could be negative, so we have to take care
sign¹, tmp¹ = sub_sign(short², short¹)
sign², tmp² = sub_sign(long², long¹)
if sign¹ * sign² > 0
# both subtractions are positive, so we
# have to _subtract_ from acc
resize!(p, p_len)
fill!(p, zero(ArbDigit))
mac3!(p, tmp¹, tmp²)
normalize!(p_num) # remove excess zeros
# acc -= p²*sh
sub2!(@view(acc[short_half_len+1:end]), p)
elseif sign¹ * sign² < 0
# one subtraction is negative, so we
# have to _add_ to acc
mac3!(@view(acc[short_half_len+1:end]), tmp¹, tmp²)
else
# one of the subtractions results in 0
# we don't have to do anything!
end
# we're a mutating function - so return nothing
return nothing
end
function mac3!(acc::AbstractVector{ArbDigit}, b::AbstractVector{ArbDigit}, c::AbstractVector{ArbDigit})
if !iszero(length(b)) && iszero(first(b))
nz = findfirst(!iszero, b)
nz === nothing && return # only zeros!
b = @view b[nz:end]
acc = @view acc[nz:end]
end
if !iszero(length(c)) && iszero(first(c))
nz = findfirst(!iszero, c)
nz === nothing && return # only zeros!
c = @view c[nz:end]
acc = @view acc[nz:end]
end
short, long = length(b) < length(c) ? (b,c) : (c,b)
if length(short) <= 32
long_mul!(acc, long, short)
else #if length(short) <= 256
karatsuba!(acc, long, short)
#else
# TODO: implement Toom-3 multiplication for numbers larger than 256 digits
#throw(ArgumentError("Multiplication for numbers with more than 256 digits has not been implemented yet."))
end
end
function sub_sign(a::AbstractVector{ArbDigit}, b::AbstractVector{ArbDigit})
if !isempty(a) && iszero(last(a))
idx = something(findlast(!iszero, a), 0)
a = @view a[begin:idx]
end
if !isempty(b) && iszero(last(b))
idx = something(findlast(!iszero, b), 0)
b = @view b[begin:idx]
end
ret = if a == b
(0, ArbDigit[])
elseif _less(<, a, b)
retArr = copy(b)
sub2!(retArr, a)
(-1, retArr)
else
retArr = copy(a)
sub2!(retArr, b)
(1, retArr)
end
return ret
end
function mul3(x::AbstractVector{ArbDigit}, y::AbstractVector{ArbDigit})
len = length(x) + length(y)
prod = zeros(ArbDigit, len)
mac3!(prod, x, y)
ArbUInt(prod)
end
function scalar_mul!(a::ArbUInt, b::ArbDigit)
if iszero(b)
set_zero!(a)
elseif isone(b)
return
else
if ispow2(b)
# this will break with too large numbers
shl!(a, trailing_zeros(b))
else
carry = zero(DoubleArbDigit)
for i in eachindex(a.data)
a[i], carry = mulWithCarry(a[i], b, carry)
end
!iszero(carry) && push!(a.data, carry % ArbDigit)
end
end
end
Base.:(*)(a::ArbUInt, b::ArbUInt) = mul3(a.data, b.data)
Base.:(*)(a::ArbUInt, b::Unsigned) = scalar_mul!(deepcopy(a), ArbDigit(b))
Base.:(*)(b::Unsigned, a::ArbUInt) = scalar_mul!(deepcopy(a), ArbDigit(b))
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] | 2.036162 | 4,065 |
# Copyright (c) 2021
#
# Permission is hereby granted, free of charge, to any person obtaining a copy
# of this software and associated documentation files (the "Software"), to deal
# in the Software without restriction, including without limitation the rights
# to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
# copies of the Software, and to permit persons to whom the Software is
# furnished to do so, subject to the following conditions:
#
# The above copyright notice and this permission notice shall be included in all
# copies or substantial portions of the Software.
#
# THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
# IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
# FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
# AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
# LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
# OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
# SOFTWARE.
using LinearAlgebra;
"""
SL0(A::Matrix{Float64}, b::Vector{Float64}; maxiter=100, epsilon=0.01, sigma_decrease_factor=0.85)
Find the solution to Ax=b using Iterative Recursive Least Squares.
### Input
- `A` -- Matrix: Ax=b
- `b` -- Vector: Ax=b
- `sigma_decrease_factor` -- (optional) number of optmization iterations
- `epsilon` -- (optional) threshold to stop optimizing
- `maxiter` -- (optional) max number of iterations
### Output
Solution to Ax=b (Vector{Float64})
### Algorithm
Smoothed L0 (http://ee.sharif.edu/~SLzero/)
"""
function SL0(A::Matrix{Float64},
b::Vector{Float64};
sigma_decrease_factor=.85,
maxiter=150,
epsilon=.001)
# set up the locals
local mu_0, L, A_pinv, s, x;
# assign constants
mu_0 = 2; # The value of mu_0 scales the sequence of mu
L = 3; # number of iterations of the internal (steepest ascent) loop
A_pinv = pinv(A); # pseudo-inverse of matrix A defined by A_pinv=A'*inv(A*A')
# initialize the solution
s = A_pinv*b;
sigma = 2*maximum(abs.(s));
for j = 1:maxiter
for i = 1:L
delta = s.*exp.(-abs.(s).^2/sigma^2);
s -= mu_0*delta;
s -= A_pinv*(A*s - b);
end
sigma *= sigma_decrease_factor;
end
x = s;
i = abs.(x) .< epsilon;
x[i] = zeros(sum(i));
return x
end
# A = randn(10, 50); b = randn(10);
# x = SL0(A, b);
# println(x)
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] | 2.557312 | 1,012 |
@testset "Testing MatMul" begin
# First, test normal matmul.
a = rand(Float32, 10, 20)
b = rand(Float32, 20, 10)
A = OneDNN.Memory(a)
B = OneDNN.Memory(b)
Z = OneDNN.materialize(OneDNN.matmul(A, B))
z = a * b
@test size(Z) == (size(a, 1), size(b, 2))
@test isapprox(Z, z)
@inferred *(a, b)
Z = OneDNN.materialize(
OneDNN.matmul(OneDNN.Memory(transpose(b)), OneDNN.Memory(transpose(a)))
)
@test isapprox(transpose(Z), z)
# Do pullbacks work?
# Note: `rrule` definition lives in ChainRuies.jl under `Base/arraymath.jl`.
x = randn(Float32, 100, 100)
y = randn(Float32, 100, 100)
X = OneDNN.Memory(x)
Y = OneDNN.Memory(y)
Z, back_dnnl = Zygote._pullback(*, X, Y)
z, back_jl = Zygote._pullback(*, x, y)
@test isapprox(OneDNN.materialize(Z), z)
dz = Float32(0.125) * randn(Float32, size(z))
DZ = OneDNN.Memory(dz)
grads_jl = back_jl(dz)
grads_dnnl = back_dnnl(DZ)
@test length(grads_jl) == length(grads_dnnl) == 3
@test grads_jl[1] === grads_dnnl[1] === nothing
@test isapprox(grads_jl[2], OneDNN.materialize(grads_dnnl[2]))
@test isapprox(grads_jl[3], OneDNN.materialize(grads_dnnl[3]))
end
# # Test applying some post ops
# x = rand(Float32, 2, 2)
# y = rand(Float32, 2, 2)
# z = rand(Float32, 2, 2)
# # expected result
# expected = (x * y) + (transpose(z) * x)
# out = OneDNN.matmul(y, x)
# postops = OneDNN.PostOps()
# OneDNN.appendsum!(postops)
# attr = OneDNN.Attributes()
# OneDNN.add!(attr, postops)
# OneDNN.matmul!(out, x, transpose(z); attributes = attr)
# result = OneDNN.materialize(out)
# @test isapprox(result, expected)
# # Test scaling
# x = randn(Float32, 5, 5)
# y = randn(Float32, 5, 5)
# attr = OneDNN.Attributes()
# OneDNN.setscale!(attr, 2)
# z = OneDNN.matmul(y, x; attributes = attr)
# @test isapprox(OneDNN.materialize(z), 2 * x * y)
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] | 2.10901 | 899 |
using Markdown
"""
struct Element
atomic_number::Int
symbol_name::String
chinese_name::String
english_name::String
latin_name::String
pinyin_name::String
end # struct Element
元素结构体，包含元素的原子序数，元素符号，中文名，英文名，拉丁文名，拼音名。
构造函数：
```julia
Element(Z, sym, chinese, english, latin, pinyin)
Element(ele::Element) # identity
Element(Z::Integer) # 从原子序数构造
Element(name::Union{AbstractString, Symbol}) # 从任何名称构造，比如 "Fe", "铝", "Oxygen"
```
"""
struct Element
atomic_number::Int
symbol_name::String
chinese_name::String
english_name::String
latin_name::String
pinyin_name::String
Element(Z, sym, chinese, english, latin, pinyin) = new(Z, sym, chinese, english, latin, pinyin)
end # struct Element
"不存在的元素"
const NoneElement = Element(-1, "", "", "", "", "")
"判断是否为不存在的元素"
is_none(ele::Element)::Bool = !(1 <= ele.atomic_number <= 118)
"元素周期表"
const element_table = [
Element(1, "H", "氢", "Hydrogen", "Hydrogenium", "qīng"),
Element(2, "He", "氦", "Helium", "Helium", "hài"),
Element(3, "Li", "锂", "Lithium", "Lithium", "lǐ"),
Element(4, "Be", "铍", "Beryllium", "Beryllium", "pí"),
Element(5, "B", "硼", "Boron", "Borum", "péng"),
Element(6, "C", "碳", "Carbon", "Сarbonium (Carboneum)", "tàn"),
Element(7, "N", "氮", "Nitrogen", "Nitrogenium", "dàn"),
Element(8, "O", "氧", "Oxygen", "Oxygenium", "yǎng"),
Element(9, "F", "氟", "Fluorine", "Fluorum", "fú"),
Element(10, "Ne", "氖", "Neon", "Neon", "nǎi"),
Element(11, "Na", "钠", "Sodium", "Natrium", "nà"),
Element(12, "Mg", "镁", "Magnesium", "Magnesium", "měi"),
Element(13, "Al", "铝", "Aluminum", "Aluminium", "lǚ"),
Element(14, "Si", "硅", "Silicon", "Silicium", "guī"),
Element(15, "P", "磷", "Phosphorus", "Phosphorus", "lín"),
Element(16, "S", "硫", "Sulfur", "Sulphuris", "liú"),
Element(17, "Cl", "氯", "Chlorine", "Сhlorum", "lǜ"),
Element(18, "Ar", "氩", "Argon", "Argon", "yà"),
Element(19, "K", "钾", "Potassium", "Kalium", "jiǎ"),
Element(20, "Ca", "钙", "Calcium", "Сalcium", "gài"),
Element(21, "Sc", "钪", "Scandium", "Scandium", "kàng"),
Element(22, "Ti", "钛", "Titanium", "Titanium", "tài"),
Element(23, "V", "钒", "Vanadium", "Vanadium", "fán"),
Element(24, "Cr", "铬", "Chromium", "Chromium", "gè"),
Element(25, "Mn", "锰", "Manganese", "Manganum", "měng"),
Element(26, "Fe", "铁", "Iron", "Ferrum", "tiě"),
Element(27, "Co", "钴", "Cobalt", "Cobaltum", "gǔ"),
Element(28, "Ni", "镍", "Nickel", "Niccolum", "niè"),
Element(29, "Cu", "铜", "Copper", "Cuprum", "tóng"),
Element(30, "Zn", "锌", "Zinc", "Zincum", "xīn"),
Element(31, "Ga", "镓", "Gallium", "Gallium", "jiā"),
Element(32, "Ge", "锗", "Germanium", "Germanium", "zhě"),
Element(33, "As", "砷", "Arsenic", "Arsenicum", "shēn"),
Element(34, "Se", "硒", "Selenium", "Selenium", "xī"),
Element(35, "Br", "溴", "Bromine", "Bromum", "xiù"),
Element(36, "Kr", "氪", "Krypton", "Krypton", "kè"),
Element(37, "Rb", "铷", "Rubidium", "Rubidium", "rú"),
Element(38, "Sr", "锶", "Strontium", "Strontium", "sī"),
Element(39, "Y", "钇", "Yttrium", "Yttrium", "yǐ"),
Element(40, "Zr", "锆", "Zirconium", "Zirconium", "gào"),
Element(41, "Nb", "铌", "Niobium", "Niobium", "ní"),
Element(42, "Mo", "钼", "Molybdenum", "Molybdaenum", "mù"),
Element(43, "Tc", "锝", "Technetium", "Technetium", "dé"),
Element(44, "Ru", "钌", "Ruthenium", "Ruthenium", "liǎo"),
Element(45, "Rh", "铑", "Rhodium", "Rhodium", "lǎo"),
Element(46, "Pd", "钯", "Palladium", "Palladium", "bǎ"),
Element(47, "Ag", "银", "Silver", "Argentum", "yín"),
Element(48, "Cd", "镉", "Cadmium", "Cadmium", "gé"),
Element(49, "In", "铟", "Indium", "Indium", "yīn"),
Element(50, "Sn", "锡", "Tin", "Stannum", "xī"),
Element(51, "Sb", "锑", "Antimony", "Stibium", "tī"),
Element(52, "Te", "碲", "Tellurium", "Tellurium", "dì"),
Element(53, "I", "碘", "Iodine", "Iodium", "diǎn"),
Element(54, "Xe", "氙", "Xenon", "Xenon", "xiān"),
Element(55, "Cs", "铯", "Caesium", "Caesium", "sè"),
Element(56, "Ba", "钡", "Barium", "Barium", "bèi"),
Element(57, "La", "镧", "Lanthanum", "Lanthanum", "lán"),
Element(58, "Ce", "铈", "Cerium", "Cerium", "shì"),
Element(59, "Pr", "镨", "Praseodymium", "Praseodymium", "pǔ"),
Element(60, "Nd", "钕", "Neodymium", "Neodymium", "nǚ"),
Element(61, "Pm", "钷", "Promethium", "Promethium", "pǒ"),
Element(62, "Sm", "钐", "Samarium", "Samarium", "shān"),
Element(63, "Eu", "铕", "Europium", "Europium", "yǒu"),
Element(64, "Gd", "钆", "Gadolinium", "Gadolinium", "gá"),
Element(65, "Tb", "铽", "Terbium", "Terbium", "tè"),
Element(66, "Dy", "镝", "Dysprosium", "Dysprosium", "dī"),
Element(67, "Ho", "钬", "Holmium", "Holmium", "huǒ"),
Element(68, "Er", "铒", "Erbium", "Erbium", "ěr"),
Element(69, "Tm", "铥", "Thulium", "Thulium", "diū"),
Element(70, "Yb", "镱", "Ytterbium", "Ytterbium", "yì"),
Element(71, "Lu", "镥", "Lutetium", "Lutetium", "lǔ"),
Element(72, "Hf", "铪", "Hafnium", "Hafnium", "hā"),
Element(73, "Ta", "钽", "Tantalum", "Tantalum", "tǎn"),
Element(74, "W", "钨", "Tungsten", "Wolframium", "wū"),
Element(75, "Re", "铼", "Rhenium", "Rhenium", "lái"),
Element(76, "Os", "锇", "Osmium", "Osmium", "é"),
Element(77, "Ir", "铱", "Iridium", "Iridium", "yī"),
Element(78, "Pt", "铂", "Platinum", "Platinum", "bó"),
Element(79, "Au", "金", "Gold", "Aurum", "jīn"),
Element(80, "Hg", "汞", "Mercury", "Hydrargyrum", "gǒng"),
Element(81, "Tl", "铊", "Thallium", "Thallium", "tā"),
Element(82, "Pb", "铅", "Lead", "Plumbum", "qiān"),
Element(83, "Bi", "铋", "Bismuth", "Bisemutum (Bismuthum, Bismutum)", "bì"),
Element(84, "Po", "钋", "Polonium", "Polonium", "pō"),
Element(85, "At", "砹", "Astatine", "Astatum", "ài"),
Element(86, "Rn", "氡", "Radon", "Radon", "dōng"),
Element(87, "Fr", "钫", "Francium", "Francium", "fāng"),
Element(88, "Ra", "镭", "Radium", "Radium", "léi"),
Element(89, "Ac", "锕", "Actinium", "Actinium", "ā"),
Element(90, "Th", "钍", "Thorium", "Thorium", "tǔ"),
Element(91, "Pa", "镤", "Protactinium", "Protactinium", "pú"),
Element(92, "U", "铀", "Uranium", "Uranium", "yóu"),
Element(93, "Np", "镎", "Neptunium", "Neptunium", "ná"),
Element(94, "Pu", "钚", "Plutonium", "Plutonium", "bù"),
Element(95, "Am", "镅", "Americium", "Americium", "méi"),
Element(96, "Cm", "锔", "Curium", "Curium", "jú"),
Element(97, "Bk", "锫", "Berkelium", "Berkelium", "péi"),
Element(98, "Cf", "锎", "Californium", "Californium", "kāi"),
Element(99, "Es", "锿", "Einsteinium", "Einsteinium", "āi"),
Element(100, "Fm", "镄", "Fermium", "Fermium", "fèi"),
Element(101, "Md", "钔", "Mendelevium", "Mendelevium", "mén"),
Element(102, "No", "锘", "Nobelium", "Nobelium", "nuò"),
Element(103, "Lr", "铹", "Lawrencium", "Lawrencium", "láo"),
Element(104, "Rf", "𬬻", "Rutherfordium", "Rutherfordium", "lú"),
Element(105, "Db", "𬭊", "Dubnium", "Dubnium", "dù"),
Element(106, "Sg", "𬭳", "Seaborgium", "Seaborgium", "xǐ"),
Element(107, "Bh", "𬭛", "Bohrium", "Bohrium", "bō"),
Element(108, "Hs", "𬭶", "Hassium", "Hassium", "hēi"),
Element(109, "Mt", "鿏", "Meitnerium", "Meitnerium", "mài"),
Element(110, "Ds", "𫟼", "Darmstadtium", "Darmstadtium", "dá"),
Element(111, "Rg", "𬬭", "Roentgenium", "Roentgenium", "lún"),
Element(112, "Cn", "鎶", "Copernicium", "Copernecium", "gē"),
Element(113, "Nh", "鉨", "Nihonium", "Nihonium", "nǐ"),
Element(114, "Fl", "𫓧", "Flerovium", "Flerovium", "fū"),
Element(115, "Mc", "镆", "Moscovium", "Moscovium", "mò"),
Element(116, "Lv", "鉝", "Livermorium", "Livermorium", "lì"),
Element(117, "Ts", "石田", "Tennessine", "Tennessine", "tián"),
Element(118, "Og", "气奥", "Oganesson", "Oganneson", "ào")
]
"通过原子序数查找元素"
find_element_with_Z(Z::Integer) = (1 <= Z <= 118) ? element_table[Z] : NoneElement
"通过元素符号查找元素"
function find_element_with_symbol(sym::AbstractString)
pos = findfirst(ele -> ele.symbol_name == sym, element_table)
pos === nothing ? NoneElement : element_table[pos]
end
"通过元素中文名查找元素"
function find_element_with_chinese(chinese::AbstractString)
pos = findfirst(ele -> ele.chinese_name == chinese, element_table)
pos === nothing ? NoneElement : element_table[pos]
end
"通过元素英文名查找元素"
function find_element_with_english(english::AbstractString)
pos = findfirst(ele -> ele.english_name == english, element_table)
pos === nothing ? NoneElement : element_table[pos]
end
"通过元素拉丁文名查找元素"
function find_element_with_latin(latin::AbstractString)
pos = findfirst(ele -> match(Regex("\\b" * latin * "\\b"), ele.latin_name) !== nothing, element_table)
pos === nothing ? NoneElement : element_table[pos]
end
"通过元素拼音查找元素"
function find_element_with_pinyin(pinyin::AbstractString)
pos = findfirst(ele -> ele.pinyin_name == pinyin, element_table)
pos === nothing ? NoneElement : element_table[pos]
end
"""
find_element(name::Union{Integer, AbstractString})
通过任何名称查找元素，包括使用原子序数
"""
function find_element(name::Union{Integer, AbstractString})
name isa Integer && return find_element_with_Z(name)
ele = find_element_with_symbol(name)
is_none(ele) && (ele = find_element_with_chinese(name))
is_none(ele) && (ele = find_element_with_english(name))
is_none(ele) && (ele = find_element_with_latin(name))
is_none(ele) && (ele = find_element_with_pinyin(name))
return ele
end
Element(ele::Element) = ele
Element(Z::Integer) = find_element_with_Z(Z)
Element(name::Union{AbstractString, Symbol}) = find_element(string(name))
const ElementConstructType = Union{Element, Integer, AbstractString, Symbol}
"获取原子序数"
getZ(ele::ElementConstructType) = Element(ele).atomic_number
"获取原子序数"
atomic_number(ele::ElementConstructType) = Element(ele).atomic_number
"获取元素符号"
symbol(ele::ElementConstructType) = Element(ele).symbol_name
"获取元素中文名"
chinese(ele::ElementConstructType) = Element(ele).chinese_name
"获取元素英文名"
english(ele::ElementConstructType) = Element(ele).english_name
"获取元素拉丁文名"
latin(ele::ElementConstructType) = Element(ele).latin_name
"获取元素中文名拼音"
pinyin(ele::ElementConstructType) = Element(ele).pinyin_name
"""
show_element_table(type::AbstractString="symbol")
打印元素周期表，`type`可以是`"symbol", "chinese"`两种
"""
function show_element_table(type::AbstractString="symbol")
choose_field = nothing
use_space = ""
if type == "symbol"
choose_field = symbol
use_space = " "
elseif type == "chinese"
choose_field = chinese
use_space = "\u3000"
else
throw(ArgumentError("invalid element table type: $type"))
end
# 第一行
str = @sprintf("%-2s%s %-2s\n", choose_field(Element(1)), repeat(" " * use_space, 16), choose_field(Element(2)))
# 第二、三行
for line = 2:3
start = (line - 2) * 8 + 3
for z = start:start+1
str = str * @sprintf("%-2s ", choose_field(Element(z)))
end
str = str * repeat(use_space * " ", 10)
for z = start+2:start+6
str = str * @sprintf("%-2s ", choose_field(Element(z)))
end
str = str * @sprintf("%-2s\n", choose_field(Element(start+7)))
end
# 第四、五行
for line = 4:5
start = (line - 4) * 18 + 19
for z = start:start+16
str = str * @sprintf("%-2s ", choose_field(Element(z)))
end
str = str * @sprintf("%-2s\n", choose_field(Element(start + 17)))
end
# 第六、七行
for line = 6:7
start = (line - 6) * 32 + 55
for z = start:start+2
str = str * @sprintf("%-2s ", choose_field(Element(z)))
end
for z = start+17:start+30
str = str * @sprintf("%-2s ", choose_field(Element(z)))
end
str = str * @sprintf("%-2s\n", choose_field(Element(start + 31)))
end
str = str * repeat(use_space * " ", 17) * use_space * "\n"
# 附加行
for line = 6:7
str = str * repeat(use_space * " ", 2)
start = (line - 6) * 32 + 57
for z = start:start+14
str = str * @sprintf("%-2s ", choose_field(Element(z)))
end
str = str * repeat(use_space * " ", 7)
str = str * use_space * "\n"
end
print(str)
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] | 1.938865 | 6,363 |
@testset "composite: RGB" begin
@testset "clear: $T" for T in Ts
@test CompositeClear(RGBA{T}(1, 0.75, 0, 0.6), RGBA{T}(0, 0.5, 1, 0.6)) ≈ RGBA{T}(0, 0, 0, 0)
end
@testset "copy: $T" for T in Ts
@test CompositeCopy(RGBA{T}(1, 0.75, 0, 0.6), RGBA{T}(0, 0.5, 1, 0.6)) ≈ RGBA{T}(0, 0.5, 1, 0.6)
end
@testset "destination: $T" for T in Ts
@test CompositeDestination(RGBA{T}(1, 0.75, 0, 0.6), RGBA{T}(0, 0.5, 1, 0.6)) ≈ RGBA{T}(1, 0.75, 0, 0.6)
end
@testset "source-over: $T" for T in Ts
@test CompositeSourceOver(RGBA{T}(1, 0.75, 0, 0.6), RGBA{T}(0, 0.5, 1, 0.6)) ≈ RGBA{T}(2/7, 4/7, 5/7, 0.84)
@test CompositeSourceOver(RGBA{T}(1, 0.75, 0, 0), RGBA{T}(0, 0.5, 1, 0.6)) ≈ RGBA{T}(0, 0.5, 1, 0.6)
@test CompositeSourceOver(RGBA{T}(1, 0.75, 0, 1), RGBA{T}(0, 0.5, 1, 0.6)) ≈ RGBA{T}(0.4, 0.6, 0.6, 1)
end
@testset "destination-over: $T" for T in Ts
@test CompositeDestinationOver(RGBA{T}(1, 0.75, 0, 0.6), RGBA{T}(0, 0.5, 1, 0.6)) ≈ RGBA{T}(5/7, 19/28, 2/7, 0.84)
@test CompositeDestinationOver(RGBA{T}(1, 0.75, 0, 0), RGBA{T}(0, 0.5, 1, 0.6)) ≈ RGBA{T}(0, 0.5, 1, 0.6)
@test CompositeDestinationOver(RGBA{T}(1, 0.75, 0, 1), RGBA{T}(0, 0.5, 1, 0.6)) ≈ RGBA{T}(1, 0.75, 0, 1)
end
@testset "source-in: $T" for T in Ts
@test CompositeSourceIn(RGBA{T}(1, 0.75, 0, 0.6), RGBA{T}(0, 0.5, 1, 0.6)) ≈ RGBA{T}(0, 0.5, 1, 0.36)
@test CompositeSourceIn(RGBA{T}(1, 0.75, 0, 0), RGBA{T}(0, 0.5, 1, 0.6)) ≈ RGBA{T}(0, 0, 0, 0)
@test CompositeSourceIn(RGBA{T}(1, 0.75, 0, 1), RGBA{T}(0, 0.5, 1, 0.6)) ≈ RGBA{T}(0, 0.5, 1, 0.6)
end
@testset "destination-in: $T" for T in Ts
@test CompositeDestinationIn(RGBA{T}(1, 0.75, 0, 0.6), RGBA{T}(0, 0.5, 1, 0.6)) ≈ RGBA{T}(1, 0.75, 0, 0.36)
@test CompositeDestinationIn(RGBA{T}(1, 0.75, 0, 0), RGBA{T}(0, 0.5, 1, 0.6)) ≈ RGBA{T}(0, 0, 0, 0)
@test CompositeDestinationIn(RGBA{T}(1, 0.75, 0, 1), RGBA{T}(0, 0.5, 1, 0.6)) ≈ RGBA{T}(1, 0.75, 0, 0.6)
end
@testset "source-out: $T" for T in Ts
@test CompositeSourceOut(RGBA{T}(1, 0.75, 0, 0.6), RGBA{T}(0, 0.5, 1, 0.6)) ≈ RGBA{T}(0, 0.5, 1, 0.24)
@test CompositeSourceOut(RGBA{T}(1, 0.75, 0, 0), RGBA{T}(0, 0.5, 1, 0.6)) ≈ RGBA{T}(0, 0.5, 1, 0.6)
@test CompositeSourceOut(RGBA{T}(1, 0.75, 0, 1), RGBA{T}(0, 0.5, 1, 0.6)) ≈ RGBA{T}(0, 0, 0, 0)
end
@testset "destination-out: $T" for T in Ts
@test CompositeDestinationOut(RGBA{T}(1, 0.75, 0, 0.6), RGBA{T}(0, 0.5, 1, 0.6)) ≈ RGBA{T}(1, 0.75, 0, 0.24)
@test CompositeDestinationOut(RGBA{T}(1, 0.75, 0, 0), RGBA{T}(0, 0.5, 1, 0.6)) ≈ RGBA{T}(0, 0, 0, 0)
@test CompositeDestinationOut(RGBA{T}(1, 0.75, 0, 1), RGBA{T}(0, 0.5, 1, 0.6)) ≈ RGBA{T}(1, 0.75, 0, 0.4)
end
@testset "source-atop: $T" for T in Ts
@test CompositeSourceAtop(RGBA{T}(1, 0.75, 0, 0.6), RGBA{T}(0, 0.5, 1, 0.6)) ≈ RGBA{T}(0.4, 0.6, 0.6, 0.6)
@test CompositeSourceAtop(RGBA{T}(1, 0.75, 0, 0), RGBA{T}(0, 0.5, 1, 0.6)) ≈ RGBA{T}(0, 0, 0, 0)
@test CompositeSourceAtop(RGBA{T}(1, 0.75, 0, 1), RGBA{T}(0, 0.5, 1, 0.6)) ≈ RGBA{T}(0.4, 0.6, 0.6, 1)
end
@testset "destination-atop: $T" for T in Ts
@test CompositeDestinationAtop(RGBA{T}(1, 0.75, 0, 0.6), RGBA{T}(0, 0.5, 1, 0.6)) ≈ RGBA{T}(0.6, 0.65, 0.4, 0.6)
@test CompositeDestinationAtop(RGBA{T}(1, 0.75, 0, 0), RGBA{T}(0, 0.5, 1, 0.6)) ≈ RGBA{T}(0, 0.5, 1, 0.6)
@test CompositeDestinationAtop(RGBA{T}(1, 0.75, 0, 1), RGBA{T}(0, 0.5, 1, 0.6)) ≈ RGBA{T}(1, 0.75, 0, 0.6)
end
@testset "xor: $T" for T in Ts
@test CompositeXor(RGBA{T}(1, 0.75, 0, 0.6), RGBA{T}(0, 0.5, 1, 0.6)) ≈ RGBA{T}(0.5, 0.625, 0.5, 0.48)
@test CompositeXor(RGBA{T}(1, 0.75, 0, 0), RGBA{T}(0, 0.5, 1, 0.6)) ≈ RGBA{T}(0, 0.5, 1, 0.6)
@test CompositeXor(RGBA{T}(1, 0.75, 0, 1), RGBA{T}(0, 0.5, 1, 0.6)) ≈ RGBA{T}(1, 0.75, 0, 0.4)
end
@testset "lighter: $T" for T in Ts
@test CompositeLighter(RGBA{T}(1, 0.75, 0, 0.6), RGBA{T}(0, 0.5, 1, 0.6)) ≈ RGBA{T}(0.6, 0.75, 0.6, 1)
@test CompositeLighter(RGBA{T}(1, 0.75, 0, 0), RGBA{T}(0, 0.5, 1, 0.6)) ≈ RGBA{T}(0, 0.5, 1, 0.6)
@test CompositeLighter(RGBA{T}(1, 0.75, 0, 1), RGBA{T}(0, 0.5, 1, 0.6)) ≈ RGBA{T}(1, 1, 0.6, 1)
end
end
@testset "composite: opaque RGBs" begin
c1, c2 = RGB{Float32}(1, 0.75, 0), RGB{Float64}(0, 0.5, 1)
t1, t2 = ARGB(c1), ARGB(c2)
m = BlendLuminosity
@testset "$(keyword(op))" for op in (CompositeCopy,
CompositeDestination,
CompositeSourceOver,
CompositeDestinationOver,
CompositeSourceIn,
CompositeDestinationIn,
CompositeSourceAtop,
CompositeDestinationAtop,
CompositeLighter)
@test ARGB(op(c1, c2, mode=m)) === op(t1, t2, mode=m)
end
@testset "$(keyword(op))" for op in (CompositeClear,
CompositeSourceOut,
CompositeDestinationOut,
CompositeXor)
@test_throws MethodError op(c1, c2, mode=m)
end
end
@testset "composite: RGB over opaque RGB" begin
c1, c2 = RGB{Float32}(1, 0.75, 0), RGB{Float64}(0, 0.5, 1)
t1, t2 = ARGB(c1), ARGB(c2, 0.25)
m = BlendLuminosity
@testset "$(keyword(op))" for op in (CompositeDestination,
CompositeSourceOver,
CompositeDestinationOver,
CompositeSourceAtop,
CompositeLighter)
c = op(c1, c2, opacity=0.25, mode=m)
@test ARGB(c) === ARGB(op(c1, t2, mode=m)) === op(t1, t2, mode=m)
end
@testset "$(keyword(op))" for op in (CompositeClear,
CompositeCopy,
CompositeSourceIn,
CompositeDestinationIn,
CompositeSourceOut,
CompositeDestinationOut,
CompositeDestinationAtop,
CompositeXor)
@test_throws MethodError op(c1, c2, opacity=0.25, mode=m)
@test_throws MethodError op(c1, t2, mode=m)
end
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] | 1.622471 | 4,103 |
#
# Compute Polar Decomposition via SVD
#
struct SVDAlg <: PolarAlg end
function solve!(alg::SVDAlg,
X::Matrix{T}, U::Matrix{T}, H::Matrix{T}) where {T}
F = svd(X, full = false)
PQt = Array{T}(undef, size(U))
mul!(PQt, F.U, transpose(F.V))
copyto!(U, PQt)
copyto!(H, F.V * Diagonal(F.S) * F.Vt)
H = (1/T(2)) * (H + H')
return SVDResult(U, H)
end
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] | 1.83871 | 217 |
using Cxx
using OpenNI2
using CVCore
using CVHighGUI
const ni2 = OpenNI2
isesc(key) = key == 27
genfilename(ext=".png") =
joinpath(dirname(@__FILE__), string(now(), "_", time_ns(), ext))
# Turn this on if you prefer to use Kinect v2
# assumed that libfreenect2-openni2 driver is installed
use_libfreenect2_openni2_driver = false
always_save = false
show_ir = true
show_depth = true
if use_libfreenect2_openni2_driver
w, h = 512, 424
else
w, h = 640>>1, 480>>1
end
function setVideoMode(stream, si, w, h, pxfmt)
modes = ni2.getSupportedVideoModes(si)
found = false
for mode in modes
if Int(ni2.getResolutionX(mode)) == w &&
Int(ni2.getResolutionY(mode)) == h &&
ni2.getPixelFormat(mode) == pxfmt
println("$w x $h : video mode found")
ni2.setVideoMode(stream, mode)
found = true
break
end
end
!found && error("video mode not found")
end
ni2.initialize()
device = ni2.DevicePtr()
ni2.open(device)
ni2.setDepthColorSyncEnabled(device, false)
di = ni2.getDeviceInfo(device)
@show ni2.getName(di)
@show ni2.getVendor(di)
depth = ni2.VideoStreamPtr()
ni2.create(depth, device, ni2.SENSOR_DEPTH)
!use_libfreenect2_openni2_driver && ni2.setMirroringEnabled(depth, true)
setVideoMode(depth, ni2.getSensorInfo(device, ni2.SENSOR_DEPTH), w, h,
ni2.PIXEL_FORMAT_DEPTH_1_MM)
ir = ni2.VideoStreamPtr()
ni2.create(ir, device, ni2.SENSOR_IR)
!use_libfreenect2_openni2_driver && ni2.setMirroringEnabled(ir, true)
setVideoMode(ir, ni2.getSensorInfo(device, ni2.SENSOR_IR), w, h,
ni2.PIXEL_FORMAT_GRAY16)
ni2.setImageRegistrationMode(device, ni2.IMAGE_REGISTRATION_OFF)
foreach(ni2.start, [depth, ir])
frame = ni2.VideoFrameRef()
while true
readyIndex = ni2.waitForAnyStream([depth, ir])
if readyIndex == 0
ni2.readFrame(depth, frame)
arr = convert(Array{ni2.DepthPixel,2}, frame)
scaledarr = arr * 1/maximum(arr)
show_depth && imshow("depth", scaledarr)
elseif readyIndex == 1
ni2.readFrame(ir, frame)
arr = convert(Array{ni2.Grayscale16Pixel,2}, frame)
scaledarr = arr * 1/maximum(arr)
show_ir && imshow("ir", scaledarr)
end
key = waitKey(delay=1)
isesc(key) && break
if key == 's' || always_save
scale!(scaledarr, 255.)
ext = readyIndex == 0 ? "_depth.png" : "_ir.png"
fname = genfilename(ext)
@show fname
imwrite(fname, Mat(scaledarr))
end
rand() > 0.95 && gc(false)
end
destroyAllWindows()
foreach(ni2.stop, [depth, ir])
foreach(ni2.destroy, [depth, ir])
ni2.close(device)
ni2.shutdown()
# Force deallocate
depth=0;ir=0;device=0;gc()
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] | 2.243802 | 1,210 |
using Documenter, BeurlingLasso
makedocs(
modules = [BeurlingLasso],
format = Documenter.HTML(; prettyurls = get(ENV, "CI", nothing) == "true"),
authors = "Romain Petit",
sitename = "BeurlingLasso",
pages = [
"Introduction" => "index.md",
"Examples" => "examples.md"
]
# strict = true,
# clean = true,
# checkdocs = :exports,
)
deploydocs(
repo = "github.com/rpetit/BeurlingLasso.jl.git",
)
| [
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] | 2.267677 | 198 |
### A Pluto.jl notebook ###
# v0.17.0
using Markdown
using InteractiveUtils
# ╔═╡ d65d8190-7aa2-11eb-0e64-837b0676b7ca
begin
using Pkg
Pkg.activate(".")
using Plots, LaTeXStrings, PrettyTables
include("tools.jl")
end;
# ╔═╡ 81a9741a-798f-11eb-22fc-7fd2f87480dc
md"""
# MATH 522 Numerical Analysis
Christoph Ortner, ortner@math.ubc.ca, University of British Columbia
A course on approximation theory and with focus on computational aspects and applications.
"""
# ╔═╡ d28341ea-798f-11eb-3819-a3bc46d12e77
md"""
# § 0. Introduction and Motivation
## § 0.1 Composite Trapezoidal Rule
Consider two functions defined on $[-\pi, \pi]$,
```math
f_1(x) = \frac{1}{1 + x^2}, \qquad
f_2(x) = \frac{1}{1 + \sin^2(x)}
```
"""
# ╔═╡ 4127884c-7991-11eb-17f4-c76f7a96a556
begin
f1(x) = 1 / (1 + x^2)
f2(x) = 1 / (1 + sin(x)^2)
plot(f1, -π, π, lw=3, label = L"f_1(x) = 1/(1+x^2)")
plot!(f2, -π, π, lw = 3, label = L"f_2(x) = 1/(1+\sin^2(x))",
size = (550, 250), legend = :outertopright )
end
# ╔═╡ 779c0428-7990-11eb-0437-0d930f606312
md"""
We approximate the integral $I[f_j] := \int_{-\pi}^\pi f_j(x) \,dx$ with a quadrature rule, the [composite trapezoidal rule](https://en.wikipedia.org/wiki/Trapezoidal_rule)
```math
\begin{aligned}
I[f] \approx I_N[f] := \sum_{n = -N+1}^N \frac{2\pi}{2N}
\cdot \frac{f(x_{n-1})) + f(x_n)}{2}
\end{aligned}
```
where $x_n = 2\pi n / (2N) = \pi n/N, n = -N, \dots, N$ are the quadrature nodes.
If $f \in C^1$ then it is not too difficult to show that on each sub-interval $(x_{n-1}, x_n)$ of length ``h \approx 1/N`` approximating ``f`` with a piecewise affine function yields an ``O(h^2)`` error and therefore the total error is expected to also scale like ``h^2 \approx N^{-2}``, i.e., we expect that
```math
|I[f] - I_N[f]| \lesssim N^{-2}
```
"""
# ╔═╡ 8de1aef6-7abf-11eb-186a-f98c6e94f5d1
md"""
To test this numerically we implement the quadrature rule rewritten as follows:
```math
I_N[f] = \frac{\pi}{2N} \big(f(-\pi) + f(\pi)\big)
+ \frac{\pi}{N} \sum_{n = -N+1}^{N-1} f(\pi n/N)
```
"""
# ╔═╡ 07ad43fe-7993-11eb-28d0-a3a4b0efcf12
@doc raw"""
`trapezoidal_rule(f, N)` : composite trapezoidal rule on [-π, π],
```math
I_N[f] = \frac{\pi}{2N} \big(f(-\pi) + f(\pi)\big)
+ \frac{\pi}{N} \sum_{n = -N+1}^{N-1} f(\pi n/N)
```
* `f` : function defining the integrand
* `N` : number of integration nodes is ``2N+1``
* Output: value for composite trapezoidal rule
"""
trapezoidal_rule(f, N) = (
0.5*π/N * (f(-π) + f(π))
+ π/N * sum( f(n*π/N) for n = -N+1:N-1 ) );
# ╔═╡ dc5cad34-7992-11eb-3fc4-a54869ad9b9f
begin
NN = 3:3:30 # number of quadrature points N means 2N+1 points
I1 = 2 * atan(π) # exact value of ∫ f₁
I2 = √2 * π # exact value of ∫ f₂
I1N = trapezoidal_rule.(f1, NN) # trapezoidal rule approximations
I2N = trapezoidal_rule.(f2, NN)
E1N = abs.(I1N .- I1) # errors
E2N = abs.(I2N .- I2)
end;
# ╔═╡ 21134062-7ab5-11eb-1cdc-856a378f3c7d
md"""##### Convergence Trapezoidal rule
$(
ata_table( (NN, "``N``", "%d"),
(I1N, "``I_N[f_1]``", "%1.5f"),
(E1N, "``E_N[f_1]``", "%1.1e"),
(I2N, "``I_N[f_2]``", "%1.5f"),
(E2N, "``E_N[f_2]``", "%1.1e"),
))
* ``I_N[f]`` : trapezoidal rule approximation with ``2N+1`` quadrature points
* ``E_N[f] := |I_N[f] - \int_{-\pi}^\pi f(x) \,dx |`` : error
"""
# ╔═╡ edf219ca-7abf-11eb-3d52-83c82513ab0d
md"""Plotting the error will give us a more qualitative view ..."""
# ╔═╡ fc2e003a-7abf-11eb-38c3-2f5db67014e3
begin
Px = plot(NN, E1N, lw=2, m=:o, ms=4, label = L"E_N[f_1]", yaxis = :log10)
plot!(NN, E2N.+1e-16, lw=2, m=:o, ms=4, label = L"E_N[f_2]",
xlabel = L"N")
P1 = plot!(deepcopy(Px), NN[3:end], 0.04*NN[3:end].^(-2), lw=2, ls=:dash,
c=:black, label = L"N^{-2}", ylims = [1e-6, 1e-1], xaxis = :log10)
P2 = plot!(Px, NN[2:6], 0.1*exp.(- 2 * log(1 + sqrt(2)) * NN[2:6]), lw=2,
c=:black, ls = :dash, label = L"e^{- 2 \alpha N}",
legend = :right, ylims = [1e-16, 1e-1])
# alpha = log(sqrt(2)+1)
plot(P1, P2, size = (500, 300))
end
# ╔═╡ 1f961e64-7abf-11eb-0429-5d79965db4ca
md"""
An unexpected outcome? By the end of the first part of this course we should
be able to explain this result.
"""
# ╔═╡ b1d433f0-7ac2-11eb-06ca-5ffe4fbf5bff
md"""
## §0.2 What is Approximation Theory
[Wikipedia:](https://en.wikipedia.org/wiki/Approximation_theory) In mathematics, approximation theory is concerned with how functions can best be approximated with simpler functions, and with quantitatively characterizing the errors introduced thereby. Note that what is meant by best and simpler will depend on the application.
For the purpose of computational mathematics we should start by asking what operations are available to us on a computer: +, -, *, /. Everything else must be built from those. This means that the only functions we can implement immediately are polynomials and rational functions:
```math
p_N(x) = a_0 + a_1 x + \dots + a_N x^N, \qquad r_{NM}(x) = \frac{p_N(x)}{q_M(x)}
```
We could (maybe should?) build this entire course based on polynomials. Instead, I decided to use trigonometric polynomials; more on this in the next notebook.
In any programming language, including Julia which we are using in this course, when you call mathematical functions such as
```julia
exp, cos, sin, acos, log, ...
```
you are in fact evaluating a rational approximant that approximates this function to within machine precision (typically ``\epsilon \approx 10^{-16}`` for 64bit floating point accuracy).
"""
# ╔═╡ e5952ed8-88bc-11eb-08fe-27778602caba
md"""
Beyond implementing special functions, why should we approximate a general function ``f`` by a polynomial? There are many reasons:
* ``f`` might be expensive to evaluate, hence replacing it with a cheap but accurate "surrogate" ``p_N`` would give us computationally efficient access to ``f``
* ``f`` might be unknown, but we know it solves some equation, e.g. a PDE, ``L[f] = 0``. We may be able to construct an approximate equation for a polynomial ``L_N[p_N] = 0`` and prove that solving this implies ``p_N \approx f``.
* ``f`` might be unknown but we have some observations (data) about it. We might then "fit" a polynomial ``p_N`` to this data in order to infer further information about ``f``.
What implicit or explicit assumptions are we making in these tasks? How should we optimize our approximation parameters (the polynomial degree ``N`` in this case). What can we say about the accuracy of approximation, i.e. how close is ``p_N`` to ``f``? How can we optimally sample ``f`` to obtain good approximations? These are the kind of questions that approximation theory and numerical analysis are concerned with.
"""
# ╔═╡ 2caa010c-7aa8-11eb-1554-9b8864597364
md"""
## §0.4 Resources
### Julia
* https://julialang.org
* https://juliaacademy.com
* https://juliadocs.github.io/Julia-Cheat-Sheet/
Although you won't need it for this course, I recommend VS Code for serious work with Julia (unless you are already committed to another very good editor such as Emacs, Vim, Sublime etc. Atom is still a good choice but most development has now moved to VS Code.
### Pluto.jl
* https://github.com/fonsp/Pluto.jl
* https://www.wias-berlin.de/people/fuhrmann/SciComp-WS2021/assets/nb01-first-contact-pluto.html
* https://computationalthinking.mit.edu/Spring21/
### Course Material
* https://github.com/cortner/ApxThyApp.git
This contains Pluto notebooks, older Jupyter notebooks (I may choose to switch back to Jupyter if I decide I don't like Pluto), and my lecture notes which are still under development but at least the basic theory part is now maturing nicely. The lecture notes also contain further references and exercise.
"""
# ╔═╡ Cell order:
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] | 2.29415 | 3,641 |
using .Nodes
using ..Partitioners
# TODO: Allow the instantiation without the specification of width (Could be
# determined from the training data)
struct Discriminator{P <: AbstractPartitioner,T <: AbstractNode} <: AbstractModel
partitioner::P
nodes::Vector{T}
end
function Discriminator{P,T}(partitioner::P; kargs...) where {P <: AbstractPartitioner,T <: AbstractNode}
nodes = [T(;kargs...) for _ in 1:length(partitioner)]
Discriminator{P,T}(partitioner, nodes)
end
function Discriminator{RandomPartitioner,T}(width::Int, n::Int; seed::Union{Nothing,Int}=nothing, kargs...) where {T <: AbstractNode}
partitioner = RandomPartitioner(width, n; seed)
Discriminator{RandomPartitioner,T}(partitioner; kargs...)
end
function Discriminator{P,T}(X::U, partitioner::P; kargs...) where {P <: AbstractPartitioner,T <: AbstractNode,U <: AbstractVecOrMat{Bool}}
d = Discriminator{P,T}(partitioner; kargs...)
train!(d, X)
return d
end
function Discriminator{RandomPartitioner,T}(X::U, n::Int; seed::Union{Nothing,Int}=nothing, kargs...) where {T <: AbstractNode,U <: AbstractVecOrMat{Bool}}
d = Discriminator{RandomPartitioner,T}(size(X)[end], n; seed, kargs...)
train!(d, X)
return d
end
## Aliases and convenience constructors
# Default node is DictNode with random partitioning
Discriminator(args...; kargs...) = Discriminator{RandomPartitioner,DictNode}(args...; kargs...)
const BitDiscriminator = Discriminator{RandomPartitioner,DictNode{BitVector}}
const BleachingDiscriminator = Discriminator{RandomPartitioner,AccNode} # This should be the default classification discriminator
RegressionDiscriminator = Discriminator{RandomPartitioner,RegressionNode}
GeneralizedRegressionDiscriminator = Discriminator{RandomPartitioner,GeneralizedRegressionNode}
# Generic functions
function train!(d::Discriminator{<:AbstractPartitioner,<:AbstractClassificationNode}, X::T) where {T <: AbstractVecOrMat{Bool}}
for (node, x) in Iterators.zip(d.nodes, partition(d.partitioner, X))
Nodes.train!(node, x)
end
return nothing
end
function train!(d::Discriminator{<:AbstractPartitioner,<:AbstractRegressionNode}, X, y)
for (node, x) in Iterators.zip(d.nodes, partition(d.partitioner, X))
Nodes.train!(node, x, y)
end
return nothing
end
initial_response(::AbstractVector{Bool}) = zero(Int)
initial_response(X::AbstractMatrix{Bool}) = zeros(Int, size(X, 1))
# TODO: Output response in relative terms? (i.e. divide by the number of nodes)
function predict(d::Discriminator{<:AbstractPartitioner,<:AbstractClassificationNode}, X::AbstractVecOrMat{Bool}; b::Int=0)
response = initial_response(X)
for (node, x) in Iterators.zip(d.nodes, partition(d.partitioner, X))
response += predict(node, x; b)
end
return response
end
function predict(d::Discriminator{<:AbstractPartitioner,<:AbstractRegressionNode}, X::AbstractMatrix{Bool})
[predict(d, x) for x in eachrow(X)]
end
# TODO: In the context of discriminators, predict and predict_response are the same thing.
# Implement predict_response as an alias to predict
################################################################################
# Specialized training and prediction methods for the regresion variant
function predict(d::Discriminator{P,RegressionNode}, X::AbstractVector{Bool}) where {P <: AbstractPartitioner}
partial_count = zero(Int)
estimate = zero(Float64)
for (node, x) in Iterators.zip(d.nodes, partition(d.partitioner, X))
count, sum = predict(node, x)
if node.γ != 1.0
count = (1 - node.γ^count) / (1 - node.γ)
end
partial_count += count
estimate += sum
end
return partial_count == 0 ? estimate : estimate / partial_count
end
################################################################################
# Specialized training and prediction methods for the generalized regresion discriminator
# This expects that α is a constant
function predict(d::Discriminator{P,GeneralizedRegressionNode}, X::AbstractVector{Bool}) where {P <: AbstractPartitioner}
running_numerator = zero(Float64)
running_denominator = zero(Float64)
for (node, x) in Iterators.zip(d.nodes, partition(d.partitioner, X))
count, estimate = predict(node, x)
α = node.α
if count != 0
running_numerator += estimate / α
running_denominator += 1 / α
end
end
return running_denominator == 0 ? zero(Float64) : running_numerator / running_denominator
end
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] | 2.878845 | 1,593 |
#=
Code to process the binaries from the harp board.
=#
using ArgParse
using Glob
include("harp_binary_functions.jl")
function parse_commandline()
s = ArgParseSettings()
@add_arg_table s begin
"--new_fold", "-n"
help = "Set to write .csv into a new folder for each file"
action = :store_true
"dir"
help = "Positional - Directory or file to parse. If string ends with .bin then the program will execute the single binary"
required = true
end
return parse_args(s)
end
function main()
parsed_args = parse_commandline()
spec_flag = 0
## Now turn string arguments into what they actually should be
dir = parsed_args["dir"]
# Now start parsing the data
to_analyse = Vector{String}()
if occursin(".bin",dir)
push!(to_analyse,dir)
elseif isdir(dir)
dir_files = readdir(dir)
for cur_file in dir_files
if occursin(".bin",cur_file)
push!(to_analyse,joinpath(dir,cur_file))
end
end
else
ArgumentError("Invalid path provided")
end
for cur_path in to_analyse
if check_exist(cur_path,parsed_args["new_fold"])
println("Processing $cur_path")
else
println("Output files for $cur_path already exist - moving on")
continue
end
Message, Timestamp, Addresses,Payloads, Types = read_harp_bin(cur_path)
events,writes = track_state(Message, Timestamp, Addresses,Payloads, Types)
if parsed_args["new_fold"]
sink_folder(events,writes,cur_path)
else
sink_data(events,writes,cur_path)
end
end
end
function check_exist(dir,new_fold)
base_title = replace(dir,".bin"=>"")
if new_fold
file_names = glob(joinpath(base_title,"*.csv"))
else
file_names = glob(string(base_title,"*.csv"))
end
return isempty(file_names)
end
main()
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] | 2.273249 | 871 |
# *****************************************************************************
# Written by Ritchie Lee, ritchie.lee@sv.cmu.edu
# *****************************************************************************
# Copyright ã 2015, United States Government, as represented by the
# Administrator of the National Aeronautics and Space Administration. All
# rights reserved. The Reinforcement Learning Encounter Simulator (RLES)
# platform is licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License. You
# may obtain a copy of the License at
# http://www.apache.org/licenses/LICENSE-2.0. Unless required by applicable
# law or agreed to in writing, software distributed under the License is
# distributed on an "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
# KIND, either express or implied. See the License for the specific language
# governing permissions and limitations under the License.
# _____________________________________________________________________________
# Reinforcement Learning Encounter Simulator (RLES) includes the following
# third party software. The SISLES.jl package is licensed under the MIT Expat
# License: Copyright (c) 2014: Youngjun Kim.
# Permission is hereby granted, free of charge, to any person obtaining a copy
# of this software and associated documentation files (the "Software"), to
# deal in the Software without restriction, including without limitation the
# rights to use, copy, modify, merge, publish, distribute, sublicense, and/or
# sell copies of the Software, and to permit persons to whom the Software is
# furnished to do so, subject to the following conditions:
# The above copyright notice and this permission notice shall be included in
# all copies or substantial portions of the Software. THE SOFTWARE IS PROVIDED
# "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED, INCLUDING BUT
# NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR
# PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT
# HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN
# ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN
# CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE.
# *****************************************************************************
export script_base, script_dasc, script_libcas098small, script_libcas0100star, script_libcas0100llcem
export process_jsons
using FilterNMACInfo
const DATADIR = joinpath(dirname(@__FILE__), "..", "..", "..", "data")
const DASC_JSON = joinpath(DATADIR, "dasc/json")
const DASC_CSV = joinpath(DATADIR, "dasc/csv")
const DASC_OUT = Pkg.dir("Datasets/data/dasc") #requires Datasets to be installed
const LIBCAS098SMALL_JSON = joinpath(DATADIR, "libcas098small/json")
const LIBCAS098SMALL_CSV = joinpath(DATADIR, "libcas098small/csv")
const LIBCAS098SMALL_OUT = Pkg.dir("Datasets/data/libcas098small")
const LIBCAS0100STAR_JSON = joinpath(DATADIR, "libcas0100star/json")
const LIBCAS0100STAR_CSV = joinpath(DATADIR, "libcas0100star/csv")
const LIBCAS0100STAR_OUT = Pkg.dir("Datasets/data/libcas0100star")
const LIBCAS0100LLCEM_JSON = joinpath(DATADIR, "libcas0100llcem/json")
const LIBCAS0100LLCEM_CSV = joinpath(DATADIR, "libcas0100llcem/csv")
const LIBCAS0100LLCEM_OUT = Pkg.dir("Datasets/data/libcas0100llcem")
#####################
#Add an entry here
#dasc set
function script_dasc(fromjson::Bool=true)
script_base(DASC_JSON, DASC_CSV, DASC_OUT;
fromjson=fromjson, correct_coc=true)
end
#from APL 20151230, libcas0.9.8, MCTS iterations=500, testbatch
function script_libcas098small(fromjson::Bool=true)
script_base(LIBCAS098SMALL_JSON, LIBCAS098SMALL_CSV, LIBCAS098SMALL_OUT;
fromjson=fromjson, correct_coc=true)
end
#Generated 20160413, libcas0.10.0, MCTS iterations=3000, 2ac, stardbn
function script_libcas0100star(fromjson::Bool=true)
script_base(LIBCAS0100STAR_JSON, LIBCAS0100STAR_CSV, LIBCAS0100STAR_OUT;
fromjson=fromjson, correct_coc=false)
end
#Generated 20160422, libcas0.10.0, MCTS iterations=3000, 2ac, llcemdbn
function script_libcas0100llcem(fromjson::Bool=true)
script_base(LIBCAS0100LLCEM_JSON, LIBCAS0100LLCEM_CSV, LIBCAS0100LLCEM_OUT;
fromjson=fromjson, correct_coc=false)
end
#####################
function script_base(jsondir::AbstractString, csvdir::AbstractString,
outdir::AbstractString;
fromjson::Bool=true, correct_coc::Bool=true,
verbose::Bool=true)
if fromjson
verbose && println("converting to csv...")
mkpath(csvdir)
convert2csvs(jsondir, csvdir)
end
tmpdir = mktempdir()
verbose && println("tmp=$tmpdir")
verbose && println("converting to dataframes...")
csvs2dataframes(csvdir, tmpdir)
if correct_coc
verbose && println("correcting cocs...")
correct_coc_stays!(tmpdir)
end
add_encounter_info!(tmpdir)
mkpath(outdir)
verbose && println("saving dataset...")
make_dataset(tmpdir, jsondir, outdir)
end
"""
Convenience function to process a new dataset from directory of json files
dataname is the name of the dataset (no spaces)
jsonpath is the directory of input json files
adds 2 new datasets to Datasets/data (original and filtered NMAC)
"""
function process_jsons(dataname::AbstractString, jsonpath::AbstractString)
csvpath = joinpath(jsonpath, "csv")
outpath = Pkg.dir("Datasets", "data", dataname)
script_base(jsonpath, csvpath, outpath; fromjson=true, correct_coc=false)
filtname = dataname * "filt"
filtpath = Pkg.dir("Datasets", "data", filtname)
filter_nmac_info(FilterNMACInfo.isnmac, dataname, filtpath)
end
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] | 2.99532 | 1,923 |
# Copyright © 2021 Alexander L. Hayes
# Apache 2.0 License
"""Request copies of relational datasets.
"""
using HTTP
using ZipFile
include("base.jl")
include("types.jl")
"""
Available datasets from the
[`srlearn/datasets`](https://github.com/srlearn/datasets) repository.
"""
DATASETS = [
"toy_cancer",
"toy_father",
"citeseer",
"cora",
"uwcse",
"webkb",
"financial_nlp_small",
"nell_sports",
"icml",
"boston_housing",
"drug_interactions",
"toy_machines",
]
"""Default download version.
If a "version" parameter is not passed to `load`, a dataset of this version
is downloaded by default.
"""
LATEST_VERSION = "v0.0.5"
"""
load(name::String, version::Union{String, Nothing} = nothing; fold::Int64 = 1)
Load the training and test folds for a dataset.
"""
function load(name::String, version::Union{String, Nothing} = nothing; fold::Int64 = 1)
data_location = fetch(name, version)
return deserialize_zipfile(data_location, name, fold=fold)
end
function deserialize_zipfile(data_location::String, name::String; fold::Int64 = 1)
reader = ZipFile.Reader(data_location)
folds = _n_folds(reader)
train_pos, train_neg, train_facts = nothing, nothing, nothing
test_pos, test_neg, test_facts = nothing, nothing, nothing
# TODO(hayesall): The ZipFile.jl doesn't make it quite as easy to seek a file by name.
# There's a package for building iterators out of tar archives, but it appears that
# the only way to do a "file name lookup" is by building an intermediate dictionary
# and jumping to the index of the name you want.
file_num = Dict{String, Int64}()
for (i, fname) in enumerate(reader.files)
file_num[fname.name] = i
end
if folds == 0
train_pos = readlines(reader.files[file_num["$(name)/train/train_pos.txt"]])
train_neg = readlines(reader.files[file_num["$(name)/train/train_neg.txt"]])
train_facts = readlines(reader.files[file_num["$(name)/train/train_facts.txt"]])
test_pos = readlines(reader.files[file_num["$(name)/test/test_pos.txt"]])
test_neg = readlines(reader.files[file_num["$(name)/test/test_neg.txt"]])
test_facts = readlines(reader.files[file_num["$(name)/test/test_facts.txt"]])
elseif fold > folds
throw(error("Fold ($(fold)) does not exist in $(data_location)"))
else
train_pos = readlines(reader.files[file_num["$(name)/fold$(fold)/train/train_pos.txt"]])
train_neg = readlines(reader.files[file_num["$(name)/fold$(fold)/train/train_neg.txt"]])
train_facts = readlines(reader.files[file_num["$(name)/fold$(fold)/train/train_facts.txt"]])
test_pos = readlines(reader.files[file_num["$(name)/fold$(fold)/test/test_pos.txt"]])
test_neg = readlines(reader.files[file_num["$(name)/fold$(fold)/test/test_neg.txt"]])
test_facts = readlines(reader.files[file_num["$(name)/fold$(fold)/test/test_facts.txt"]])
end
close(reader)
return RelationalDataset((
train_pos,
train_neg,
train_facts,
)), RelationalDataset((
test_pos,
test_neg,
test_facts,
))
end
"""
fetch(name::String, version::Union{String, Nothing} = nothing)
Download a dataset with `name` and `version`, write the zipfile to the cache
directory, and return a string representing the path to the file on disk.
"""
function fetch(name::String, version::Union{String, Nothing} = nothing)::String
data_file = _make_file_path(name, version)
if Base.Filesystem.isfile(data_file)
return data_file
end
download_url = _make_data_url(name, version)
request = HTTP.request("GET", download_url)
io = open(data_file, "w")
write(io, request.body)
close(io)
return data_file
end
function _make_file_path(name::String, version::Union{String, Nothing} = nothing)::String
@assert name in DATASETS
if version == nothing
return Base.Filesystem.joinpath(
get_data_home(),
"$(name)_$(LATEST_VERSION).zip",
)
end
return Base.Filesystem.joinpath(
get_data_home(),
"$(name)_$(version).zip",
)
end
function _make_data_url(name::String, version::Union{String, Nothing} = nothing)::String
@assert name in DATASETS
if version == nothing
version = LATEST_VERSION
end
# TODO(hayesall): Enforce no v0.0.2 or v0.0.3
return "https://github.com/srlearn/datasets/releases/download/$(version)/$(name)_$(version).zip"
end
"""Does this zipfile contain CV folds?"""
function _has_folds(zip::ZipFile.Reader)::Bool
return any([occursin("fold", file.name) for file in zip.files])
end
"""How many folds does this contain?"""
function _n_folds(zip::ZipFile.Reader)::Int64
if !_has_folds(zip)
return 0
end
numbers = Int64[]
for path in zip.files
if occursin("fold", path.name)
append!(numbers, parse(Int64, split(split(path.name, "fold")[2], "/")[1]))
end
end
return maximum(numbers)
end
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function onlineplot!(fig, axis_dict, stats::AbstractVector, iter, data, variable, i)
for (j, stat) in enumerate(stats)
axis_dict[(variable, stat)] = fig[i, j] = Axis(fig, title="$(name(stat))")
limits!(axis_dict[(variable, stat)], 0.0, 10.0, -1.0, 1.0)
onlineplot!(axis_dict[(variable, stat)], stat, iter, data[variable], data[:iter], i, j)
tight_ticklabel_spacing!(axis_dict[(variable, stat)])
end
end
function onlineplot!(axis, stat::Symbol, args...)
onlineplot!(axis, Val(stat), args...)
end
onlineplot!(axis, ::Val{:mean}, args...) = onlineplot!(axis, Mean(), args...)
onlineplot!(axis, ::Val{:var}, args...) = onlineplot!(axis, Variance(), args...)
onlineplot!(axis, ::Val{:autocov}, args...) = onlineplot!(axis, AutoCov(20), args...)
onlineplot!(axis, ::Val{:hist}, args...) = onlineplot!(axis, KHist(50, Float32), args...)
# Generic fallback for OnlineStat objects
function onlineplot!(axis, stat::T, iter, data, iterations, i, j) where {T<:OnlineStat}
window = data.b
@eval TStat = $(nameof(T))
stat = Observable(TStat(Float32))
on(iter) do _
stat[] = fit!(stat[], last(value(data)))
end
statvals = Observable(MovingWindow(window, Float32))
on(stat) do s
statvals[] = fit!(statvals[], Float32(value(s)))
end
statpoints = map!(Observable(Point2f0.([0], [0])), statvals) do v
Point2f0.(value(iterations), value(v))
end
lines!(axis, statpoints, color = std_colors[i], linewidth = 3.0)
end
function onlineplot!(axis, ::Val{:trace}, iter, data, iterations, i, j)
trace = map!(Observable([Point2f0(0, 0)]), iter) do _
Point2f0.(value(iterations), value(data))
end
lines!(axis, trace, color = std_colors[i]; linewidth = 3.0)
end
function onlineplot!(axis, stat::KHist, iter, data, iterations, i, j)
nbins = stat.k
stat = Observable(KHist(nbins, Float32))
on(iter) do _
stat[] = fit!(stat[], last(value(data)))
end
hist_vals = Node(Point2f0.(collect(range(0f0, 1f0, length=nbins)), zeros(Float32, nbins)))
on(stat) do h
edges, weights = OnlineStats.xy(h)
weights = nobs(h) > 1 ? weights / OnlineStats.area(h) : weights
hist_vals[] = Point2f0.(edges, weights)
end
barplot!(axis, hist_vals; color=std_colors[i])
# barplot!(axis, rand(4), rand(4))
end
function expand_extrema(xs)
xmin, xmax = xs
diffx = xmax - xmin
xmin = xmin - 0.1 * abs(diffx)
xmax = xmax + 0.1 * abs(diffx)
return (xmin, xmax)
end
function onlineplot!(axis, ::Val{:kde}, iter, data, iterations, i, j)
interpkde = Observable(InterpKDE(kde([1f0])))
on(iter) do _
interpkde[] = InterpKDE(kde(value(data)))
end
xs = Observable(range(0, 2, length=10))
on(iter) do _
xs[] = range(expand_extrema(extrema(value(data)))..., length = 200)
end
kde_pdf = lift(xs) do xs
pdf.(Ref(interpkde[]), xs)
end
lines!(axis, xs, kde_pdf, color = std_colors[i], linewidth = 3.0)
end
name(s::Val{:histkde}) = "Hist. + KDE"
function onlineplot!(axis, ::Val{:histkde}, iter, data, iterations, i, j)
onlineplot!(axis, KHist(50), iter, data, iterations, i, j)
onlineplot!(axis, Val(:kde), iter, data, iterations, i, j)
end
function onlineplot!(axis, stat::AutoCov, iter, data, iterations, i, j)
b = length(stat.cross)
stat = Observable(AutoCov(b, Float32))
on(iter) do _
stat[] = fit!(stat[], last(value(data)))
end
statvals = map!(Observable(zeros(Float32, b + 1)), stat) do s
value(s)
end
scatter!(axis, Point2f0.([0.0, b], [-0.1, 1.0]), markersize = 0.0, color = RGBA(0.0, 0.0, 0.0, 0.0)) # Invisible points to keep limits fixed
lines!(axis, 0:b, statvals, color = std_colors[i], linewidth = 3.0)
end
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] | 2.302368 | 1,647 |
macro callhook4(hook, r, req, id)
quote
for f! in $r.hooks[$hook]
result = f!($r, $(esc(req)), $id)
if isa(result, Dict{Symbol, Any})
$(esc(req)) = result
elseif isa(result, Response)
return result
end
end
end
end
macro callhook5(hook, r, req, id, res)
quote
for f! in $r.hooks[$hook]
result = f!($r, $req, $id, $(esc(res)))
if isa(result, Response)
$(esc(res)) = result
end
end
$(esc(res))
end
end
(r::Resource)(req::Request) = req |> parserequest |> r
function (r::Resource)(req::Dict{Symbol, Any}, id::AbstractString="/")
@callhook4(:onroute, r, req, id)
res = if isempty(req[:path]) # leaf node
@callhook4(:onhandle, r, req, id)
raw = callmethod(r, req, id)
@callhook5(:onresponse, r, req, id, raw)
else
req[Symbol(r.name * "id")] = id
route(r.subresources, req, shift!(req[:path]))
end
@callhook5(:onreturn, r, req, id, res)
end
function route(candidates::Vector{Resource}, req, id)
ismatch(p::AbstractString) = p == "*" || p == id
ismatch(p::Function) = p(id)
ismatch(p::Regex) = Base.ismatch(p, id)
i = findfirst(x->ismatch(x.route), candidates)
if i == 0
Response(404)
else
candidates[i](req, id)
end
end
function parserequest(req::Request)
uri = URI(req.resource)
Dict{Symbol, Any}(
:method => req.method |> Symbol,
:headers => req.headers,
:body => req.data,
:path => uri.path |> splitpath,
:query => uri.query |> parsequerystring # this should be moved out of Rest.jl. Maybe add a mixin system?
)
end
splitpath(p::AbstractString) = split(p, '/', keep=false)
function callmethod(r::Resource, req::Dict{Symbol, Any}, id::AbstractString)
let m = r.methods, v = req[:method],
h = [r.hooks[v]; (cb, r, req, id) -> haskey(m, v) ? m[v](req, id) : Response(405)]
callone(i) = (req::Dict{Symbol, Any}, id::AbstractString) ->
h[i](callone(i+1), r, req, id)
callone(1)(req, id)
end
end
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] | 2.03525 | 1,078 |
struct ShaderCompilationError <: Exception
msg
end
Base.showerror(io::IO, err::ShaderCompilationError) = print(io, "ShaderCompilationError:\n\n$(err.msg)")
"""
compile(shader)
Compile a shader file in text format to SPIR-V.
"""
function compile(source::ShaderSource; extra_flags=[], validate_spirv=true)::ShaderSource
flags = ["-V"; "--stdin"; extra_flags]
source.language == SPIR_V && error("Shader $source already compiled")
source.language == HLSL && push!(flags, "-D")
if validate_spirv && "--spirv-val" ∉ flags
push!(flags, "--spirv-val")
end
if isempty(source.entry_points)
entry_point = :main
elseif length(source.entry_points) == 1
entry_point = first(source.entry_points)
else
error("Multiple entry points not supported in uncompiled source")
end
dst = string(tempname(), ".spv")
input = IOBuffer()
write(input, source.code)
seekstart(input)
err = IOBuffer()
append!(flags, [
"-e",
string(entry_point),
"-S",
string(file_ext(source.language, source.stage)),
"-o",
dst,
])
try
run(pipeline(`$glslangValidator $flags`, stdin=input, stdout=err))
catch e
if e isa ProcessFailedException
err_str = String(take!(err))
throw(ShaderCompilationError(err_str))
else
rethrow(e)
end
end
code = read(dst)
rm(dst)
ShaderSource(code, SPIR_V, source.stage, [entry_point])
end
function Vk.ShaderModule(device, source::ShaderSource)
length(source.code) % 4 == 0 || pad_shader_code!(source.code)
Vk.ShaderModule(device, length(source.code), reinterpret(UInt32, source.code))
end
function Vk.PipelineShaderStageCreateInfo(shader::Shader)
specialization_info = isempty(shader.specialization_constants) ? C_NULL : shader.specialization_constants
Vk.PipelineShaderStageCreateInfo(shader.source.stage, shader.shader_module, string(shader.entry_point); specialization_info)
end
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] | 2.435252 | 834 |
###### problem parameters ####
k= # number of defence faciity
I= # number of customer
J= # number of facility services
###### initialize paramaters
m= # number of memplex
n= # number of frog in each memplex
q= # number of submemlex members
###### generate initial population
###### partition population into memplexs
###### memetic evolution withing each memplex
##### shuffling all frogs
#### check termination consdition
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] | 3.46875 | 128 |
#
# Denoise an SPD Example with Cyclic Proximal Point applied to the
#
# L2-TV functional with anisotropic TV
#
# where the example is the same data as for the corresponding CP algorithm
#
using Manopt
using Images, CSV, DataFrames, LinearAlgebra, JLD2
#
# Settings
ExportResult = true
ExportOrig = true
ExportResultVideo = false
ExportTable = true
resultsFolder = "src/examples/Total_Variation/S2_TV/"
experimentName = "WhirlCPPA"
if !isdir(resultsFolder)
mkdir(resultsFolder)
end
#
# Manifold & Data
f = artificialS2WhirlImage(64)
pixelM = Sphere(2);
if ExportOrig
renderAsymptote(resultsFolder*experimentName*"-orig.asy", asyExportS2Data; data=f) # (5)
end
#
# Parameters
α = 1.5
maxIterations = 4000
#
# Build Problem for L2-TV
M = Power(pixelM,size(f))
d = length(size(f))
iRep = [Integer.(ones(d))...,d]
fidelity(x) = 1/2*distance(M,x,f)^2
Λ(x) = forwardLogs(M,x) # on T_xN
prior(x) = norm(norm.(Ref(pixelM),getValue(repeat(x,iRep...)), getValue(Λ(x)) ), 1)
#
# Setup and Optimize
cost(x) = fidelity(x) + α*prior(x)
proximalMaps = [(λ,x) -> proxDistance(M,λ,f,x,2), (λ,x) -> proxTV(M,α*λ,x,1)]
x0 = f
@time y, yRec = cyclicProximalPoint(M,cost,proximalMaps,x0;
debug = [:Iteration," | ", DebugProximalParameter()," | ", :Change, " | ", :Cost, "\n",100,:Stop],
record = [:Iteration, :Iterate, :Cost],
stoppingCriterion = stopAfterIteration(maxIterations),
λ = i -> π/(2*i)
)
#
# Results
if ExportResult
renderAsymptote(resultsFolder*experimentName*"-result-$(maxIterations)-α$(replace(string(α), "." => "-")).asy", asyExportS2Data; data=y, render=4) #(6)
end
if ExportTable
A = cat( [ y[1] for y in yRec], [y[3] for y in yRec]; dims=2 )
CSV.write(string(resultsFolder*experimentName*"-Result.csv"),
DataFrame(A), writeheader=false);
save(resultsFolder*experimentName*"-CostValue.jld2",
Dict("compareCostFunctionValue" => last(yRec)[3])
)
end | [
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38381,
18,
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198,
220,
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220,
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198,
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] | 2.496073 | 764 |
using SparseArrays
function numerical_fluxes(flux, mesh, w, scheme, dt=0.0)
map(i_face -> numerical_flux(flux, mesh, w, scheme, i_face, dt), collect(inner_faces(mesh)))
end
"""Sparse matrix to sum the flux on both side of a face and get the change in a cell.
In 1D: sparse matrix.
For 2D cartesian mesh, it should be a higher order mesh, but since there is no higher dimensional sparse array, the field needs to be reshaped to a vector...
"""
function inner_faces_to_cells_matrix(mesh::AbstractCartesianMesh)
D = spzeros(FiniteVolumes.nb_cells(mesh), FiniteVolumes.nb_inner_faces(mesh))
li = LinearIndices(cell_centers(mesh))
for (i, face) in enumerate(FiniteVolumes.inner_faces(mesh))
i_cell_1, i_cell_2 = cells_next_to_inner_face(mesh, face)
D[li[i_cell_1], i] -= face_area(mesh, face) / cell_volume(mesh, i_cell_1)
D[li[i_cell_2], i] += face_area(mesh, face) / cell_volume(mesh, i_cell_1)
end
D
end
function update!(w, Φ, mesh, dt=0.0)
for (i, face) in enumerate(inner_faces(mesh))
i_cell_1, i_cell_2 = cells_next_to_inner_face(mesh, face)
w[i_cell_1] -= dt*Φ[i] * face_area(mesh, face) / cell_volume(mesh, i_cell_1)
w[i_cell_2] += dt*Φ[i] * face_area(mesh, face) / cell_volume(mesh, i_cell_2)
end
end
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] | 2.293594 | 562 |
using DataStructures: Deque
#=------------------------------------------------------------------------------
This section contains the `Tile` data structure, `TileCircle` data structure,
and functions that operate on these data structures. The `TileCircle` provides
and interface to an underlying double-ended queue and represents the circle
of tiles placed during a game. Tiles are placed in skip-wise fashion, that is,
each tile is placed between the tiles 1 and 2 spaces clockwise from the last
placed tile.
------------------------------------------------------------------------------=#
"""
A `Tile` is a data structure containing the value of the tile and
the ID of the player who played it.
"""
struct Tile
number::Int
played_by::Int
end
"""
TileCircle only contains a double-ended queue, a data structure with efficent
push/pop operations on both ends. I'm wrapping the deque in a data structure
so I can specialize functions for it.
"""
struct TileCircle
inner::Deque{Tile}
end
TileCircle() = TileCircle(Deque{Tile}()) # Default empty constructor
"""
rotate!(circle::TileCircle)
Rotate the entire circle counter-clockwise by one 'tick', which has the effect
of moving the insertion point for new values forward by one.
"""
function rotate!(circle::TileCircle)
isempty(circle.inner) && return
push!(circle.inner, popfirst!(circle.inner))
end
"""
push!(circle::TileCircle, tile::Tile)
Specialization of the base `push!()` function for a `TileCircle`, always inserts
new values after skipping the next clockwise value.
"""
function Base.push!(circle::TileCircle, tile::Tile)
rotate!(circle)
push!(circle.inner, tile)
end
"Dispatches for methods on the inner double-ended queue."
Base.isempty((; inner)::TileCircle) = isempty(inner)
Base.length((; inner)::TileCircle) = length(inner)
"""
next_tile(circle::TileCircle)
Returns the next tile in sequence from the current position.
"""
function next_tile(circle::TileCircle)
isempty(circle) && error("This `TileCircle` is empty!")
return first(circle.inner)
end
"""
rotate_to!(circle::TileCircle)
Rotate the circle until the next tile is the tile whose value matches `n`.
"""
function rotate_to!(circle::TileCircle, n::Int=0)
0 <= n < length(circle) || error("There's no `$n` tile in this `TileCircle`!")
while next_tile(circle).number != n
rotate!(circle)
end
end
"""
collect(circle::TileCircle)
Collect the contents of the circle into a Vector, with tiles ordered by
position (i.e., tile `0` in the first position, tile `1` in the second
position, etc.).
"""
function Base.collect(circle::TileCircle)
new_copy = deepcopy(circle)
isempty(circle) || rotate_to!(new_copy)
return collect(new_copy.inner)
end
#=------------------------------------------------------------------------------
This section contains the `TileGame` data structure and functions that operate
on that data structure. The `TileGame` models and provides an interface for
an ongoing game, tracking the circle of tiles laid, the number of players,
and the number of tiles played and remaining. Functions are provided for
playing one or all rounds of the game and calculating the scores given the
current state of the game.
------------------------------------------------------------------------------=#
"""
A `TileGame` represents the current state of an ongoing game, including
the circle of tiles, the number of players, the number of tiles played,
and the number of tiles left to be played.
"""
mutable struct TileGame
circle::TileCircle
players::Int
played::Int
remaining::Int
end
"""
TileGame(players::Int, tiles::Int)
Constructor that takes a number of players and number of tiles, creating
a `TileGame`.
"""
function TileGame(players::Int, tiles::Int)
circle = TileCircle()
return TileGame(circle, players, 0, tiles)
end
"""
play_round!(game::TileGame)
Given a `TileGame`, play a single round, laying the next tile into the
circle and updating the number of tiles played and the number of tiles
remaining.
"""
function play_round!(game::TileGame)
game.remaining <= 0 && return
tile = Tile(game.played, game.played % game.players)
push!(game.circle, tile)
game.played += 1
game.remaining -= 1
end
"""
play_all!(game::TileGame)
Given a `TileGame`, play all the remaining rounds, updating the game to
its final state with all tiles in the circle and none remaining to be played.
"""
function play_all!(game::TileGame)
while game.remaining > 0
play_round!(game)
end
end
"""
scores((; circle, players)::TileGame)
Calculate and return the list of scores for each player given the current
state of a `TileGame`. Returns a list of scores, in order by player ID.
"""
function scores((; circle, players)::TileGame)
score_list = Dict()
for (idx, tile) in enumerate(collect(circle))
(; number, played_by) = tile
position = idx - 1
current_score = get!(score_list, played_by, 0)
score_list[played_by] = current_score + (number * position)
end
return score_list
end
#=------------------------------------------------------------------------------
This section contains the function to complete the puzzle, demonstrating
the ergonomics of the previously implemented data structures.
------------------------------------------------------------------------------=#
"""
game_winning_score(players::Int, tiles::Int)
Given the number of players and tiles, return the highest score at the
end of the game.
"""
function game_winning_score(players::Int, tiles::Int)
game = TileGame(players, tiles)
play_all!(game) # 1, Lay all the tiles
scorecard = scores(game) # 2. Determine player scores
return reduce(max, values(scorecard), init = 0) # 3. Return maximum score
end
#=------------------------------------------------------------------------------
This section contains the tests to verify the operation of the main function,
proving puzzle completion.
------------------------------------------------------------------------------=#
using Test
@testset "Should return zero when there are no tiles." begin
@test game_winning_score(5, 0) == 0
end
@testset "Should return high score for a one-player game" begin
@test game_winning_score(1, 10) == 211
end
@testset "Should return high score for a two-player game" begin
@test game_winning_score(2, 15) == 424
end
@testset "Should return high score for a many-player game" begin
@test game_winning_score(100, 5000) == 314997735
end | [
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] | 3.41491 | 1,945 |
function master_formulation(rd::RoutingData, type::FlowFormulation)
m = _create_model(rd)
rm = basic_routing_model_unitary(m, rd, type) # Includes flow-conservation constraints.
@variable(m, mu >= 0)
@objective(m, Min, mu)
@variable(m, dual_alpha[e in edges(rd), d in demands(rd), v in vertices(rd)])
@variable(m, dual_beta[e in edges(rd), e2 in edges(rd)] >= 0)
# Robust uncertainty sets (one per edge).
if rd.model_robust_reformulation_traffic_matrices
dual_constraints = Dict{Edge{Int}, Dict{Edge{Int}, ConstraintRef}}(
e => Dict{Edge{Int}, ConstraintRef}() for e in edges(rd)
) # Edge -> demand -> constraint reference.
end
for e in edges(rd)
for d in demands(rd)
# Dual constraint from the flow variables.
for e2 in edges(rd)
@constraint(m, dual_beta[e, e2] + dual_alpha[e, d, dst(e2)] - dual_alpha[e, d, src(e2)] >= 0)
end
# Dual constraint from the demand variables.
c = @constraint(m, dual_alpha[e, d, src(d)] - dual_alpha[e, d, dst(d)] >= rm.routing[d, e])
if rd.model_robust_reformulation_traffic_matrices
dual_constraints[e][d] = c
end
end
# Relate the main decision variables to the uncertainty sets.
lhs = sum(dual_beta[e, e2] * capacity(rd, e2) for e2 in edges(rd))
@constraint(m, lhs / capacity(rd, e) <= mu)
end
return RoutingModel(rd, m, UnitaryFlows, rm.routing, mu=mu, dual_alpha=dual_alpha, dual_beta=dual_beta)
end
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] | 2.204482 | 714 |
@testset "minimal_intersection_test" begin
@test intersect(interval(1.0,3.0), interval(2.1,4.0)) == interval(2.1,3.0)
@test intersect(interval(1.0,3.0), interval(3.0,4.0)) == interval(3.0,3.0)
@test intersect(interval(1.0,3.0), emptyinterval()) == emptyinterval()
@test intersect(entireinterval(), emptyinterval()) == emptyinterval()
@test intersect(interval(1.0,3.0), entireinterval()) == interval(1.0,3.0)
end
@testset "minimal_convex_hull_test" begin
@test hull(interval(1.0,3.0), interval(2.1,4.0)) == interval(1.0,4.0)
@test hull(interval(1.0,1.0), interval(2.1,4.0)) == interval(1.0,4.0)
@test hull(interval(1.0,3.0), emptyinterval()) == interval(1.0,3.0)
@test hull(emptyinterval(), emptyinterval()) == emptyinterval()
@test hull(interval(1.0,3.0), entireinterval()) == entireinterval()
end
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3849,
2100,
28955,
6624,
2104,
3849,
2100,
3419,
198,
437,
628
] | 2.307692 | 364 |
macro goma_str(anything)
println("キュー")
end
@show goma"ゴマちゃんの鳴き声は"
@show goma"9="
@show goma"3x3="
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# 3D groundwater
using Plots
using CUDA
using TimerOutputs
using Athesis
function groundwater3d(useGPU=false, myFloat=Float64)
to = TimerOutput()
@timeit to "total run time" begin
# Initialize the model
println("Running 3D groundwater model:")
defaultInput = getDefaultInput(myFloat)
simulation = initSimulation(defaultInput, useGPU, myFloat, to)
runSimulation!(simulation, to)
plotSimulation(simulation, to)
end
print_timer(to)
end
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] | 2.350877 | 228 |
# List of vector to vector conversion functions
# should accept a function call like: f(x) where x is a input vector
const vec2vec = [
:mcep,
:gcep,
:mgcep,
:uels,
:fftcep,
:lpc,
:mfcc,
:lpc2c,
:lpc2lsp,
:lpc2par,
:par2lpc,
:lsp2sp,
:mc2b,
:b2mc,
:b2c,
:c2acr,
:c2ir,
:ic2ir,
:c2ndps,
:ndps2c,
:gc2gc,
:gnorm,
:ignorm,
:freqt,
:frqtr,
:mgc2mgc,
:mgc2sp,
:mgclsp2sp
]
# extend vector to vector conversion for matrix input (col-wise)
# should accept a function call like: f(x) where x is a input matrix
for f in vec2vec
@eval begin
function $f(x::StridedMatrix{Cdouble}, args...; kargs...)
outbuf = $f(view(x, :, 1), args...; kargs...)
ret = Array{eltype(outbuf)}(length(outbuf), size(x, 2))
copy!(ret, 1, outbuf, 1, length(outbuf))
for i = 2:size(x, 2)
@inbounds ret[:, i] = $f(view(x, :, i), args...; kargs...)
end
ret
end
end
end
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] | 1.504702 | 957 |
@inline function getVelocityDelta(joint::Rotational0, body1::AbstractBody, body2::Body{T}, ω::SVector{3,T}) where T
Δω = ω # in body1 frame
return Δω
end
@inline function getPositionDelta(joint::Rotational0, body1::AbstractBody, body2::Body{T}, θ::Quaternion{T}) where T
Δq = θ # in body1 frame
return Δq
end
@inline function setForce!(joint::Rotational0, body1::Body, body2::Body{T}, τ::SVector{3,T}, No) where T
τ1 = vrotate(-τ, body1.q[No] * joint.qoff)
τ2 = -τ1
body1.τ[No] = τ1
body2.τ[No] = τ2
return
end
@inline function setForce!(joint::Rotational0, body1::Origin, body2::Body{T}, τ::SVector{3,T}, No) where T
body2.τ[No] = vrotate(τ, joint.qoff)
return
end
@inline function minimalCoordinates(joint::Rotational0, body1::AbstractBody, body2::AbstractBody, No)
body2.q[No]
end
@inline g(joint::Rotational0, body1::AbstractBody, body2::AbstractBody, Δt, No) = g(joint)
@inline ∂g∂posa(joint::Rotational0, body1::AbstractBody, body2::AbstractBody, No) = ∂g∂posa(joint)
@inline ∂g∂posb(joint::Rotational0, body1::AbstractBody, body2::AbstractBody, No) = ∂g∂posb(joint)
@inline ∂g∂vela(joint::Rotational0, body1::AbstractBody, body2::AbstractBody, Δt, No) = ∂g∂vela(joint)
@inline ∂g∂velb(joint::Rotational0, body1::AbstractBody, body2::AbstractBody, Δt, No) = ∂g∂velb(joint)
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64,
7,
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8,
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31,
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17,
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8,
796,
18872,
224,
70,
24861,
224,
626,
65,
7,
73,
1563,
8,
198
] | 2.333333 | 573 |
# This file was generated, do not modify it. # hide
figure(figsize=(12, 6))
stem(res)
xlim(0, length(res))
savefig(joinpath(@OUTPUT, "residuals.png")) # hide | [
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# # Constants
const c_0 = 2.99792458e8
const N_SEAWATER = 1.3800851282
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println("hey")
| [
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198
] | 2.666667 | 6 |
"""
vectormesh(x::AbstractRange, y::AbstractRange)
Returns a square/rectangular grid of points generated from a x and y ranges.
"""
function vectormesh(x::AbstractRange, y::AbstractRange)
[collect(i) for i in collect(Iterators.product(x, y))]
end
"""
transform_steps(transform_matrix::Matrix; n_steps::Int64 = 240)
Breaks a 2x2 transformation matrix into incremental n_steps. Useful for interactive/animated transforms.
"""
function transform_steps(transform_matrix::Matrix; n_steps::Int64 = 240)
basis = [1 0; 0 1]
transforms = []
for j in 1:n_steps+1
push!(transforms, basis .+ (j/n_steps).*(transform_matrix .- basis))
end
transforms
end | [
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10,
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7,
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4008,
198,
197,
437,
198,
197,
198,
197,
7645,
23914,
198,
437
] | 2.894737 | 228 |
using VCFTools
using MendelImpute
using Random
"""
filter_and_mask(data::String, samples::Int)
Creates reference haplotypes and (unphased) target genotype files from `data`.
# Inputs
`data`: The full (phased) data simulated by msprime.
`samples`: Number of samples (genotypes) desired in target file. Remaining haplotypes will become the reference panel
"""
function filter_and_mask(data::String, samples::String)
missingprop = 0.1
n = nsamples(data)
p = nrecords(data)
samples = convert
samples > n && error("requested samples exceed total number of genotypes in $data.")
# output filenames (tgt_data1.vcf.gz, ref_data1.vcf.gz, and tgt_masked_data1.vcf.gz)
tgt = "./tgt_" * data
ref = "./ref_" * data
tgt_mask = "./tgt_masked_" * data
tgt_mask_unphase = "./tgt_masked_unphased_" * data
# compute target and reference index
tgt_index = falses(n)
tgt_index[1:samples] .= true
ref_index = .!tgt_index
record_index = 1:p # save all records (SNPs)
# generate masking matrix with `missingprop`% of trues (true = convert to missing)
Random.seed!(2020)
masks = falses(p, samples)
for j in 1:samples, i in 1:p
rand() < missingprop && (masks[i, j] = true)
end
# create outputs
VCFTools.filter(data, record_index, tgt_index, des = tgt)
VCFTools.filter(data, record_index, ref_index, des = ref)
mask_gt(tgt, masks, des=tgt_mask)
# finally, unphase the target data
unphase(tgt_mask, outfile=tgt_mask_unphase)
end
data = ARGS[1]
samples = parse(Int, ARGS[2])
filter_and_mask(data, samples)
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62,
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62,
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7,
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11,
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8,
198
] | 2.559809 | 627 |
# Automatically generated using Clang.jl
# Skipping MacroDefinition: cpAssertSoft ( __condition__ , ... ) if ( ! ( __condition__ ) ) { cpMessage ( # __condition__ , __FILE__ , __LINE__ , 1 , 0 , __VA_ARGS__ ) ; abort ( ) ; }
# Skipping MacroDefinition: cpAssertWarn ( __condition__ , ... ) if ( ! ( __condition__ ) ) cpMessage ( # __condition__ , __FILE__ , __LINE__ , 0 , 0 , __VA_ARGS__ )
# Skipping MacroDefinition: cpAssertHard ( __condition__ , ... ) if ( ! ( __condition__ ) ) { cpMessage ( # __condition__ , __FILE__ , __LINE__ , 1 , 1 , __VA_ARGS__ ) ; abort ( ) ; }
const CP_USE_DOUBLES = 1
# Skipping MacroDefinition: INFINITY ( __builtin_inf ( ) )
# Skipping MacroDefinition: CP_PI ( ( cpFloat ) 3.14159265358979323846264338327950288 )
const cpTrue = 1
const cpFalse = 0
# Skipping MacroDefinition: CP_NO_GROUP ( ( cpGroup ) 0 )
# Skipping MacroDefinition: CP_ALL_CATEGORIES ( ~ ( cpBitmask ) 0 )
# Skipping MacroDefinition: CP_WILDCARD_COLLISION_TYPE ( ~ ( cpCollisionType ) 0 )
const CP_BUFFER_BYTES = 32 * 1024
const CP_MAX_CONTACTS_PER_ARBITER = 2
# Skipping MacroDefinition: CP_ARBITER_GET_SHAPES ( __arb__ , __a__ , __b__ ) cpShape * __a__ , * __b__ ; cpArbiterGetShapes ( __arb__ , & __a__ , & __b__ ) ;
# Skipping MacroDefinition: CP_ARBITER_GET_BODIES ( __arb__ , __a__ , __b__ ) cpBody * __a__ , * __b__ ; cpArbiterGetBodies ( __arb__ , & __a__ , & __b__ ) ;
const CP_VERSION_MAJOR = 7
const CP_VERSION_MINOR = 0
const CP_VERSION_RELEASE = 3
# Skipping MacroDefinition: CP_CONVEX_HULL ( __count__ , __verts__ , __count_var__ , __verts_var__ ) cpVect * __verts_var__ = ( cpVect * ) alloca ( __count__ * sizeof ( cpVect ) ) ; int __count_var__ = cpConvexHull ( __count__ , __verts__ , __verts_var__ , NULL , 0.0 ) ;
const cpFloat = Cdouble
const cpHashValue = Csize_t
const cpCollisionID = UInt32
const cpBool = Cuchar
const cpDataPointer = Ptr{Cvoid}
const cpCollisionType = Csize_t
const cpGroup = Csize_t
const cpBitmask = UInt32
const cpTimestamp = UInt32
struct cpArbiterFwd end
struct cpArrayFwd end
struct cpBodyFwd end
struct cpCollisionHandlerFwd end
struct cpConstraintClassFwd end
struct cpConstraintFwd end
struct cpContactFwd end
struct cpContactBufferHeaderFwd end
struct cpHashSetFwd end
struct cpShapeClassFwd end
struct cpShapeFwd end
struct cpSpaceFwd end
struct cpSpatialIndexClassFwd end
struct cpSpatialIndexFwd end
struct cpSplittingPlaneFwd end
struct cpVect
x::cpFloat
y::cpFloat
end
struct cpTransform
a::cpFloat
b::cpFloat
c::cpFloat
d::cpFloat
tx::cpFloat
ty::cpFloat
end
struct cpMat2x2
a::cpFloat
b::cpFloat
c::cpFloat
d::cpFloat
end
struct cpArray
num::Cint
max::Cint
arr::Ptr{Ptr{Cvoid}}
end
const cpHashSet = Cvoid
const cpBodyVelocityFunc = Ptr{Cvoid}
const cpBodyPositionFunc = Ptr{Cvoid}
const cpSpatialIndexDestroyImpl = Ptr{Cvoid}
const cpSpatialIndexCountImpl = Ptr{Cvoid}
const cpSpatialIndexEachImpl = Ptr{Cvoid}
const cpSpatialIndexContainsImpl = Ptr{Cvoid}
const cpSpatialIndexInsertImpl = Ptr{Cvoid}
const cpSpatialIndexRemoveImpl = Ptr{Cvoid}
const cpSpatialIndexReindexImpl = Ptr{Cvoid}
const cpSpatialIndexReindexObjectImpl = Ptr{Cvoid}
const cpSpatialIndexReindexQueryImpl = Ptr{Cvoid}
const cpSpatialIndexQueryImpl = Ptr{Cvoid}
const cpSpatialIndexSegmentQueryImpl = Ptr{Cvoid}
struct cpSpatialIndexClass
destroy::cpSpatialIndexDestroyImpl
count::cpSpatialIndexCountImpl
each::cpSpatialIndexEachImpl
contains::cpSpatialIndexContainsImpl
insert::cpSpatialIndexInsertImpl
remove::cpSpatialIndexRemoveImpl
reindex::cpSpatialIndexReindexImpl
reindexObject::cpSpatialIndexReindexObjectImpl
reindexQuery::cpSpatialIndexReindexQueryImpl
query::cpSpatialIndexQueryImpl
segmentQuery::cpSpatialIndexSegmentQueryImpl
end
const cpSpatialIndexBBFunc = Ptr{Cvoid}
struct cpSpatialIndex
klass::Ptr{cpSpatialIndexClassFwd}
bbfunc::cpSpatialIndexBBFunc
staticIndex::Ptr{cpSpatialIndexFwd}
dynamicIndex::Ptr{cpSpatialIndexFwd}
end
const cpContactBufferHeader = Cvoid
const cpCollisionBeginFunc = Ptr{Cvoid}
const cpCollisionPreSolveFunc = Ptr{Cvoid}
const cpCollisionPostSolveFunc = Ptr{Cvoid}
const cpCollisionSeparateFunc = Ptr{Cvoid}
struct cpCollisionHandler
typeA::cpCollisionType
typeB::cpCollisionType
beginFunc::cpCollisionBeginFunc
preSolveFunc::cpCollisionPreSolveFunc
postSolveFunc::cpCollisionPostSolveFunc
separateFunc::cpCollisionSeparateFunc
userData::cpDataPointer
end
struct cpSpace
iterations::Cint
gravity::cpVect
damping::cpFloat
idleSpeedThreshold::cpFloat
sleepTimeThreshold::cpFloat
collisionSlop::cpFloat
collisionBias::cpFloat
collisionPersistence::cpTimestamp
userData::cpDataPointer
stamp::cpTimestamp
curr_dt::cpFloat
dynamicBodies::Ptr{cpArrayFwd}
staticBodies::Ptr{cpArrayFwd}
rousedBodies::Ptr{cpArrayFwd}
sleepingComponents::Ptr{cpArrayFwd}
shapeIDCounter::cpHashValue
staticShapes::Ptr{cpSpatialIndexFwd}
dynamicShapes::Ptr{cpSpatialIndexFwd}
constraints::Ptr{cpArrayFwd}
arbiters::Ptr{cpArrayFwd}
contactBuffersHead::Ptr{cpContactBufferHeaderFwd}
cachedArbiters::Ptr{cpHashSetFwd}
pooledArbiters::Ptr{cpArrayFwd}
allocatedBuffers::Ptr{cpArrayFwd}
locked::UInt32
usesWildcards::cpBool
collisionHandlers::Ptr{cpHashSetFwd}
defaultHandler::cpCollisionHandler
skipPostStep::cpBool
postStepCallbacks::Ptr{cpArrayFwd}
staticBody::Ptr{cpBodyFwd}
end
struct cpBodySleeping
root::Ptr{cpBodyFwd}
next::Ptr{cpBodyFwd}
idleTime::cpFloat
end
struct cpBody
velocity_func::cpBodyVelocityFunc
position_func::cpBodyPositionFunc
m::cpFloat
m_inv::cpFloat
i::cpFloat
i_inv::cpFloat
cog::cpVect
p::cpVect
v::cpVect
f::cpVect
a::cpFloat
w::cpFloat
t::cpFloat
transform::cpTransform
userData::cpDataPointer
v_bias::cpVect
w_bias::cpFloat
space::Ptr{cpSpaceFwd}
shapeList::Ptr{cpShapeFwd}
arbiterList::Ptr{cpArbiterFwd}
constraintList::Ptr{cpConstraintFwd}
sleeping::cpBodySleeping
end
@cenum cpShapeType::UInt32 begin
CP_CIRCLE_SHAPE = 0
CP_SEGMENT_SHAPE = 1
CP_POLY_SHAPE = 2
CP_NUM_SHAPES = 3
end
const cpShapeCacheDataImpl = Ptr{Cvoid}
const cpShapeDestroyImpl = Ptr{Cvoid}
const cpShapePointQueryImpl = Ptr{Cvoid}
const cpShapeSegmentQueryImpl = Ptr{Cvoid}
struct cpShapeClass
type::cpShapeType
cacheData::cpShapeCacheDataImpl
destroy::cpShapeDestroyImpl
pointQuery::cpShapePointQueryImpl
segmentQuery::cpShapeSegmentQueryImpl
end
struct cpShapeMassInfo
m::cpFloat
i::cpFloat
cog::cpVect
area::cpFloat
end
struct cpBB
l::cpFloat
b::cpFloat
r::cpFloat
t::cpFloat
end
struct cpShapeFilter
group::cpGroup
categories::cpBitmask
mask::cpBitmask
end
struct cpShape
klass::Ptr{cpShapeClassFwd}
space::Ptr{cpSpaceFwd}
body::Ptr{cpBodyFwd}
massInfo::cpShapeMassInfo
bb::cpBB
sensor::cpBool
e::cpFloat
u::cpFloat
surfaceV::cpVect
userData::cpDataPointer
type::cpCollisionType
filter::cpShapeFilter
next::Ptr{cpShapeFwd}
prev::Ptr{cpShapeFwd}
hashid::cpHashValue
end
struct cpArbiterThread
next::Ptr{cpArbiterFwd}
prev::Ptr{cpArbiterFwd}
end
struct cpContact
r1::cpVect
r2::cpVect
nMass::cpFloat
tMass::cpFloat
bounce::cpFloat
jnAcc::cpFloat
jtAcc::cpFloat
jBias::cpFloat
bias::cpFloat
hash::cpHashValue
end
@cenum cpArbiterState::UInt32 begin
CP_ARBITER_STATE_FIRST_COLLISION = 0
CP_ARBITER_STATE_NORMAL = 1
CP_ARBITER_STATE_IGNORE = 2
CP_ARBITER_STATE_CACHED = 3
CP_ARBITER_STATE_INVALIDATED = 4
end
struct cpArbiter
e::cpFloat
u::cpFloat
surface_vr::cpVect
data::cpDataPointer
a::Ptr{cpShapeFwd}
b::Ptr{cpShapeFwd}
body_a::Ptr{cpBodyFwd}
body_b::Ptr{cpBodyFwd}
thread_a::cpArbiterThread
thread_b::cpArbiterThread
count::Cint
contacts::Ptr{cpContactFwd}
n::cpVect
handler::Ptr{cpCollisionHandlerFwd}
handlerA::Ptr{cpCollisionHandlerFwd}
handlerB::Ptr{cpCollisionHandlerFwd}
swapped::cpBool
stamp::cpTimestamp
state::cpArbiterState
end
const cpConstraintPreStepImpl = Ptr{Cvoid}
const cpConstraintApplyCachedImpulseImpl = Ptr{Cvoid}
const cpConstraintApplyImpulseImpl = Ptr{Cvoid}
const cpConstraintGetImpulseImpl = Ptr{Cvoid}
struct cpConstraintClass
preStep::cpConstraintPreStepImpl
applyCachedImpulse::cpConstraintApplyCachedImpulseImpl
applyImpulse::cpConstraintApplyImpulseImpl
getImpulse::cpConstraintGetImpulseImpl
end
const cpConstraintPreSolveFunc = Ptr{Cvoid}
const cpConstraintPostSolveFunc = Ptr{Cvoid}
struct cpConstraint
klass::Ptr{cpConstraintClassFwd}
space::Ptr{cpSpaceFwd}
a::Ptr{cpBodyFwd}
b::Ptr{cpBodyFwd}
next_a::Ptr{cpConstraintFwd}
next_b::Ptr{cpConstraintFwd}
maxForce::cpFloat
errorBias::cpFloat
maxBias::cpFloat
collideBodies::cpBool
preSolve::cpConstraintPreSolveFunc
postSolve::cpConstraintPostSolveFunc
userData::cpDataPointer
end
struct cpCircleShape
shape::cpShape
c::cpVect
tc::cpVect
r::cpFloat
end
struct cpSegmentShape
shape::cpShape
a::cpVect
b::cpVect
n::cpVect
ta::cpVect
tb::cpVect
tn::cpVect
r::cpFloat
a_tangent::cpVect
b_tangent::cpVect
end
struct cpSplittingPlane
v0::cpVect
n::cpVect
end
struct cpPolyShape
shape::cpShape
r::cpFloat
count::Cint
planes::Ptr{cpSplittingPlaneFwd}
_planes::NTuple{12, cpSplittingPlane}
end
struct cpPinJoint
constraint::cpConstraint
anchorA::cpVect
anchorB::cpVect
dist::cpFloat
r1::cpVect
r2::cpVect
n::cpVect
nMass::cpFloat
jnAcc::cpFloat
bias::cpFloat
end
struct cpSlideJoint
constraint::cpConstraint
anchorA::cpVect
anchorB::cpVect
min::cpFloat
max::cpFloat
r1::cpVect
r2::cpVect
n::cpVect
nMass::cpFloat
jnAcc::cpFloat
bias::cpFloat
end
struct cpPivotJoint
constraint::cpConstraint
anchorA::cpVect
anchorB::cpVect
r1::cpVect
r2::cpVect
k::cpMat2x2
jAcc::cpVect
bias::cpVect
end
struct cpGrooveJoint
constraint::cpConstraint
grv_n::cpVect
grv_a::cpVect
grv_b::cpVect
anchorB::cpVect
grv_tn::cpVect
clamp::cpFloat
r1::cpVect
r2::cpVect
k::cpMat2x2
jAcc::cpVect
bias::cpVect
end
const cpDampedSpringForceFunc = Ptr{Cvoid}
struct cpDampedSpring
constraint::cpConstraint
anchorA::cpVect
anchorB::cpVect
restLength::cpFloat
stiffness::cpFloat
damping::cpFloat
springForceFunc::cpDampedSpringForceFunc
target_vrn::cpFloat
v_coef::cpFloat
r1::cpVect
r2::cpVect
nMass::cpFloat
n::cpVect
jAcc::cpFloat
end
const cpDampedRotarySpringTorqueFunc = Ptr{Cvoid}
struct cpDampedRotarySpring
constraint::cpConstraint
restAngle::cpFloat
stiffness::cpFloat
damping::cpFloat
springTorqueFunc::cpDampedRotarySpringTorqueFunc
target_wrn::cpFloat
w_coef::cpFloat
iSum::cpFloat
jAcc::cpFloat
end
struct cpRotaryLimitJoint
constraint::cpConstraint
min::cpFloat
max::cpFloat
iSum::cpFloat
bias::cpFloat
jAcc::cpFloat
end
struct cpRatchetJoint
constraint::cpConstraint
angle::cpFloat
phase::cpFloat
ratchet::cpFloat
iSum::cpFloat
bias::cpFloat
jAcc::cpFloat
end
struct cpGearJoint
constraint::cpConstraint
phase::cpFloat
ratio::cpFloat
ratio_inv::cpFloat
iSum::cpFloat
bias::cpFloat
jAcc::cpFloat
end
const cpSimpleMotorJoint = Cvoid
struct cpContactPointSetPoints
pointA::cpVect
pointB::cpVect
distance::cpFloat
end
struct cpContactPointSet
count::Cint
normal::cpVect
points::cpContactPointSetPoints
end
const cpSpatialIndexIteratorFunc = Ptr{Cvoid}
const cpSpatialIndexQueryFunc = Ptr{Cvoid}
const cpSpatialIndexSegmentQueryFunc = Ptr{Cvoid}
const cpSpaceHash = Cvoid
const cpBBTree = Cvoid
const cpBBTreeVelocityFunc = Ptr{Cvoid}
const cpSweep1D = Cvoid
@cenum cpBodyType::UInt32 begin
CP_BODY_TYPE_DYNAMIC = 0
CP_BODY_TYPE_KINEMATIC = 1
CP_BODY_TYPE_STATIC = 2
end
const cpBodyShapeIteratorFunc = Ptr{Cvoid}
const cpBodyConstraintIteratorFunc = Ptr{Cvoid}
const cpBodyArbiterIteratorFunc = Ptr{Cvoid}
struct cpPointQueryInfo
shape::Ptr{cpShapeFwd}
point::cpVect
distance::cpFloat
gradient::cpVect
end
struct cpSegmentQueryInfo
shape::Ptr{cpShapeFwd}
point::cpVect
normal::cpVect
alpha::cpFloat
end
struct cpSimpleMotor
constraint::cpConstraint
rate::cpFloat
iSum::cpFloat
jAcc::cpFloat
end
const cpPostStepFunc = Ptr{Cvoid}
const cpSpacePointQueryFunc = Ptr{Cvoid}
const cpSpaceSegmentQueryFunc = Ptr{Cvoid}
const cpSpaceBBQueryFunc = Ptr{Cvoid}
const cpSpaceShapeQueryFunc = Ptr{Cvoid}
const cpSpaceBodyIteratorFunc = Ptr{Cvoid}
const cpSpaceShapeIteratorFunc = Ptr{Cvoid}
const cpSpaceConstraintIteratorFunc = Ptr{Cvoid}
struct cpSpaceDebugColor
r::Cfloat
g::Cfloat
b::Cfloat
a::Cfloat
end
const cpSpaceDebugDrawCircleImpl = Ptr{Cvoid}
const cpSpaceDebugDrawSegmentImpl = Ptr{Cvoid}
const cpSpaceDebugDrawFatSegmentImpl = Ptr{Cvoid}
const cpSpaceDebugDrawPolygonImpl = Ptr{Cvoid}
const cpSpaceDebugDrawDotImpl = Ptr{Cvoid}
const cpSpaceDebugDrawColorForShapeImpl = Ptr{Cvoid}
@cenum cpSpaceDebugDrawFlags::UInt32 begin
CP_SPACE_DEBUG_DRAW_SHAPES = 1
CP_SPACE_DEBUG_DRAW_CONSTRAINTS = 2
CP_SPACE_DEBUG_DRAW_COLLISION_POINTS = 4
end
struct cpSpaceDebugDrawOptions
drawCircle::cpSpaceDebugDrawCircleImpl
drawSegment::cpSpaceDebugDrawSegmentImpl
drawFatSegment::cpSpaceDebugDrawFatSegmentImpl
drawPolygon::cpSpaceDebugDrawPolygonImpl
drawDot::cpSpaceDebugDrawDotImpl
flags::cpSpaceDebugDrawFlags
shapeOutlineColor::cpSpaceDebugColor
colorForShape::cpSpaceDebugDrawColorForShapeImpl
constraintColor::cpSpaceDebugColor
collisionPointColor::cpSpaceDebugColor
data::cpDataPointer
end
const cpSpacePointQueryBlock = Cvoid
const cpSpaceSegmentQueryBlock = Cvoid
const cpSpaceBBQueryBlock = Cvoid
const cpSpaceShapeQueryBlock = Cvoid
const CP_POLY_SHAPE_INLINE_ALLOC = 6
struct cpCollisionInfo
a::Ptr{cpShapeFwd}
b::Ptr{cpShapeFwd}
id::cpCollisionID
n::cpVect
count::Cint
arr::Ptr{cpContactFwd}
end
const cpSpaceArbiterApplyImpulseFunc = Ptr{Cvoid}
struct cpPostStepCallback
func::cpPostStepFunc
key::Ptr{Cvoid}
data::Ptr{Cvoid}
end
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] | 2.448178 | 5,982 |
### A Pluto.jl notebook ###
# v0.15.1
using Markdown
using InteractiveUtils
# This Pluto notebook uses @bind for interactivity. When running this notebook outside of Pluto, the following 'mock version' of @bind gives bound variables a default value (instead of an error).
macro bind(def, element)
quote
local el = $(esc(element))
global $(esc(def)) = Core.applicable(Base.get, el) ? Base.get(el) : missing
el
end
end
# ╔═╡ 6df3beed-24a7-4b26-a315-0520f4863190
develop=false
# ╔═╡ 9701cbe0-d048-11eb-151b-67dda7b72b71
begin
using Pkg
Pkg.activate(mktempdir())
Pkg.add("Revise")
using Revise
Pkg.add(["PyPlot","ExtendableGrids","PlutoUI","Plots"])
if develop
Pkg.develop(["PlutoVista","GridVisualize"])
else
Pkg.add(["PlutoVista","GridVisualize"])
end
using PyPlot,PlutoVista,GridVisualize,ExtendableGrids,PlutoUI,Plots
end
# ╔═╡ 68e2c958-b417-4ba1-9577-697304fe140a
TableOfContents()
# ╔═╡ b35d982d-1fa9-413d-b008-892b4f241097
md"""
# Test notebook for PlutoVista backend of GridVisualize
"""
# ╔═╡ 00b04f6b-34a6-4e30-9864-d273305281d4
md"""
## 1D scalar plot
"""
# ╔═╡ a20d74c9-16da-408a-b247-0c17321888f9
function testplot1(Plotter)
grid=simplexgrid(0:0.01:10)
scalarplot(grid,map(sin,grid),Plotter=Plotter,resolution=(600,200),markershape=:star5,markevery=20, xlabel="x",ylabel="z",legend=:rt,label="sin")
end
# ╔═╡ cc17187f-404c-4c31-8625-fa067eea7273
testplot1(PyPlot)
# ╔═╡ ad1c4dd6-7c6b-4433-a1ac-b2f817ba5d81
testplot1(Plots)
# ╔═╡ 33482af8-3542-4723-ae43-770a789b69b3
testplot1(PlutoVista)
# ╔═╡ c4eeb06f-932e-4acc-8e5b-f2a7f9242a42
function testplot2(Plotter;t=0)
p=GridVisualizer(Plotter=Plotter, resolution=(500,200),legend=:rt,xlabel="x")
grid=simplexgrid(0:0.01:10)
scalarplot!(p,grid,map(x->sin(x-t),grid),Plotter=Plotter,color=:red,label="sin(x-$(t))",linestyle=:dash)
scalarplot!(p,grid,map(cos,grid),Plotter=Plotter,color=:green,clear=false,label="cos",linestyle=:dashdot,linewidth=3)
reveal(p)
end
# ╔═╡ 29ca4775-6ba5-474c-bd2c-8f770b09addd
testplot2(PyPlot)
# ╔═╡ c0ab77e8-01ea-436d-85f2-34e253944f11
testplot2(Plots)
# ╔═╡ 84192945-d4b6-4949-8f06-d94e04a7a56d
testplot2(PlutoVista)
# ╔═╡ 63fe3259-7d79-40ec-98be-e0592e40ee6b
@bind t2 PlutoUI.Slider(0:0.1:5,show_value=true)
# ╔═╡ 4de6b5c9-4d2d-4bcb-bc88-c6f50a23f9b6
testplot2(PlutoVista,t=t2)
# ╔═╡ 2061e7fd-c740-4d4b-af5b-7a3a9444aafd
md"""
### Changeable data (experimental)
This just updates the data. In the 1D case the difference seems to be not critical.
"""
# ╔═╡ f84beb4f-4136-4e5a-ba43-279b703fc75f
begin
X2=0:0.001:10
grid2=simplexgrid(collect(X2))
f2(t)=map( (x)->sin(x^2-t),grid2)
end
# ╔═╡ c1278fb2-3e75-445f-893a-b8b8a7e931d3
p=PlutoVista.PlutoVistaPlot(resolution=(600,200))
# ╔═╡ 29fa4467-65ee-4dad-a660-5197864ddbdc
md"""
t4: $(@bind t4 PlutoUI.Slider(-10:0.1:10, default=0, show_value=true))
"""
# ╔═╡ 661531f7-f740-4dd4-9a59-89ddff06ba5c
PlutoVista.plot!(p,X2,f2(t4))
# ╔═╡ 9bb243cc-c69a-405b-bb35-6cddfde8fd30
begin
myplot(t)=scalarplot!(vis2,grid2,f2(t),show=true)
vis2=GridVisualizer(resolution=(600,200),Plotter=PlutoVista,datadim=1)
end
# ╔═╡ f4c78c61-19b1-4889-aa20-c6a3b157d435
md"""
t3: $(@bind t3 PlutoUI.Slider(-10:0.1:10, default=0, show_value=true))
"""
# ╔═╡ be369a01-a0c2-4a6b-831b-f716cc807240
myplot(t3)
# ╔═╡ ed9b80e5-9678-4ba6-bb36-c2e0674ed9ba
md"""
## 1D grid plot
"""
# ╔═╡ 9ce4f63d-cd96-48d7-a637-07cb84fa88ab
function testgridplot(Plotter)
grid=simplexgrid(0:1:10)
cellmask!(grid,[0.0],[5],2)
bfacemask!(grid,[5],[5],3)
gridplot(grid, Plotter=Plotter,resolution=(600,200),legend=:rt)
end
# ╔═╡ 77eeefc7-e416-426b-8f87-1bc8439dae6d
testgridplot(PyPlot)
# ╔═╡ d503ee1e-1e1f-4235-b286-dc3137a2c96a
testgridplot(PlutoVista)
# ╔═╡ ae1fe1ab-4a0e-4c80-bd6f-912201fb4bb4
md"""
## 2D Scalar plot
"""
# ╔═╡ d5258595-60e4-406f-a71e-69111cdad8b9
function testplot3(Plotter)
X=0:0.1:10
grid=simplexgrid(X,X)
f=map( (x,y)->sin(x)*atan(y),grid)
scalarplot(grid,f,Plotter=Plotter,resolution=(300,300),flimits=(-π/2,π/2),backend=:vtk)
end
# ╔═╡ c98a90bf-1a3e-4681-a3b0-663c6844df6b
testplot3(PyPlot)
# ╔═╡ a0c3067b-3aa5-493e-b132-89746483b5ce
testplot3(Plots)
# ╔═╡ 0998a9a7-d57a-476e-aacd-bee9396e9b8f
testplot3(PlutoVista)
# ╔═╡ cefb38c1-159e-42db-8088-294573fcece2
md"""
### Changeable data (experimental)
Here we observe a more profound advantage, and vtk.js also has a rather understandable way how data can be updated.
Generally, with plutovista we need two cells - one with the graph shown, and a second one which triggers the modification.
"""
# ╔═╡ a9f4f98f-ec2f-42d6-88da-4a8a6f727e93
begin
X=0:0.1:10
grid=simplexgrid(X,X)
f(t)=map( (x,y)->sin(x-t)*atan(y)*cos((y-t)),grid)
end
# ╔═╡ 412c905f-050c-4b78-a66f-0d03978e7edf
begin
vis=GridVisualizer(resolution=(300,300),Plotter=PlutoVista)
myplot2(t)=scalarplot!(vis,grid,f(t),show=true,clear=true,flimits=(-π/2,π/2))
end
# ╔═╡ 6f1707ed-79ab-42dc-8ad8-d66a9e1a65b3
md"""
t= $(@bind t PlutoUI.Slider(-10:0.1:10, default=0, show_value=true))
"""
# ╔═╡ 461481ef-f88b-4e4e-b57d-ce003abbfdf1
myplot2(t)
# ╔═╡ Cell order:
# ╠═6df3beed-24a7-4b26-a315-0520f4863190
# ╠═9701cbe0-d048-11eb-151b-67dda7b72b71
# ╠═68e2c958-b417-4ba1-9577-697304fe140a
# ╟─b35d982d-1fa9-413d-b008-892b4f241097
# ╟─00b04f6b-34a6-4e30-9864-d273305281d4
# ╠═a20d74c9-16da-408a-b247-0c17321888f9
# ╠═cc17187f-404c-4c31-8625-fa067eea7273
# ╠═ad1c4dd6-7c6b-4433-a1ac-b2f817ba5d81
# ╠═33482af8-3542-4723-ae43-770a789b69b3
# ╠═c4eeb06f-932e-4acc-8e5b-f2a7f9242a42
# ╠═29ca4775-6ba5-474c-bd2c-8f770b09addd
# ╠═c0ab77e8-01ea-436d-85f2-34e253944f11
# ╠═84192945-d4b6-4949-8f06-d94e04a7a56d
# ╠═63fe3259-7d79-40ec-98be-e0592e40ee6b
# ╠═4de6b5c9-4d2d-4bcb-bc88-c6f50a23f9b6
# ╟─2061e7fd-c740-4d4b-af5b-7a3a9444aafd
# ╠═f84beb4f-4136-4e5a-ba43-279b703fc75f
# ╠═c1278fb2-3e75-445f-893a-b8b8a7e931d3
# ╠═661531f7-f740-4dd4-9a59-89ddff06ba5c
# ╟─29fa4467-65ee-4dad-a660-5197864ddbdc
# ╠═9bb243cc-c69a-405b-bb35-6cddfde8fd30
# ╠═be369a01-a0c2-4a6b-831b-f716cc807240
# ╟─f4c78c61-19b1-4889-aa20-c6a3b157d435
# ╠═ed9b80e5-9678-4ba6-bb36-c2e0674ed9ba
# ╠═9ce4f63d-cd96-48d7-a637-07cb84fa88ab
# ╠═77eeefc7-e416-426b-8f87-1bc8439dae6d
# ╠═d503ee1e-1e1f-4235-b286-dc3137a2c96a
# ╟─ae1fe1ab-4a0e-4c80-bd6f-912201fb4bb4
# ╠═d5258595-60e4-406f-a71e-69111cdad8b9
# ╠═c98a90bf-1a3e-4681-a3b0-663c6844df6b
# ╠═a0c3067b-3aa5-493e-b132-89746483b5ce
# ╠═0998a9a7-d57a-476e-aacd-bee9396e9b8f
# ╟─cefb38c1-159e-42db-8088-294573fcece2
# ╠═a9f4f98f-ec2f-42d6-88da-4a8a6f727e93
# ╠═412c905f-050c-4b78-a66f-0d03978e7edf
# ╠═461481ef-f88b-4e4e-b57d-ce003abbfdf1
# ╟─6f1707ed-79ab-42dc-8ad8-d66a9e1a65b3
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] | 1.726395 | 3,834 |
# %% Import NaMaster for the power spectrum analysis on a partial sky
# Reference: Alonso et al., MNRAS, 484, 4127 (2019), https://github.com/LSSTDESC/NaMaster
nmt = pyimport("pymaster")
# Read in and apodize mask (C^2 apodization, 10 degrees)
m = readMapFromFITS(maskfile, 1, Float64)
mask = nmt.mask_apodization(m.pixels, 10.0, apotype = "C2")
# Create binning scheme. We will use Δℓ multipoles per bandpower.
b = nmt.NmtBin.from_nside_linear(nside, Δℓ, is_Dell = true)
# Array with effective multipole per bandpower
ell_eff = b.get_effective_ells()
nbands = b.get_n_bands()
# The function defined below will compute the power spectrum between two
# NmtFields f_a and f_b, using the coupling matrix stored in the
# NmtWorkspace wsp and subtracting the deprojection bias clb.
# Note that the most expensive operations in the MASTER algorithm are
# the computation of the coupling matrix and the deprojection bias. Since
# these two objects are precomputed, this function should be pretty fast!
function compute_master(f_a, f_b, wsp)
# Compute the power spectrum (a la anafast) of the masked fields
# Note that we only use n_iter=0 here to speed up the computation,
# but the default value of 3 is recommended in general.
cl_coupled = nmt.compute_coupled_cell(f_a, f_b)
# Decouple power spectrum into bandpowers inverting the coupling matrix
cl_decoupled = wsp.decouple_cell(cl_coupled)
return cl_decoupled
end
| [
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] | 3.050847 | 472 |
#===
ファイルの読み込み
===#
# include(".jl")
# export save
#===
共通型，関数
・全ての構造体はOptimizerの子型になる
===#
export SGD,Momentum,Adam,update!
#===SGD==============#
mutable struct SGD <: Optimizer
learning_rate
function SGD(;learning_rate=0.001)
new(learning_rate)
end
end
function fit!(this::SGD,model::Models)
model.common.optimizer = this
end
function update!(this::SGD,model::Models)
cnt = 1
@inbounds for i in 1:length(model.common.layers)
grads = model.common.layers[i].grads
if grads === nothing
continue
end
for j in 1:length(grads)
grad = grads[j]
model.common.layers[i].params[j] .-= this.learning_rate*grad
cnt+=1
end
end
nothing
end
function convert_to_cu!(this::SGD,model::Models)
return nothing
end
function convert_to_array!(this::SGD,model::Models)
return nothing
end
#===Momentum=========#
mutable struct Momentum <: Optimizer
learning_rate
vs #速度
momentum
function Momentum(;learning_rate=0.001,momentum=0.8)
new(learning_rate,[],momentum)
end
end
function fit!(this::Momentum,model::Models)
@inbounds for i in 1:length(model.common.layers)
params = model.common.layers[i].params
if params === nothing
continue
end
for j in 1:length(params)
param = params[j]
s = copy(param) * 0
append!(this.vs,[s])
end
end
model.common.optimizer = this
nothing
end
function update!(this::Momentum,model::Models)
cnt = 1
@inbounds for i in 1:length(model.common.layers)
grads = model.common.layers[i].grads
if grads === nothing
continue
end
for j in 1:length(grads)
grad = grads[j]
this.vs[cnt] = this.momentum * this.vs[cnt] - this.learning_rate * grad
model.common.layers[i].params[j] .+= this.vs[cnt]
cnt+=1
end
end
nothing
end
function convert_to_cu!(this::Momentum,model::Models)
this.vs = cu.(this.vs)
return nothing
end
function convert_to_array!(this::Momentum,model::Models)
this.vs = Array.(this.vs)
return nothing
end
#====Adam============#
mutable struct Adam <: Optimizer
learning_rate
p1
p2
e
vs #momentam
ss #RMSProp
function Adam(;learning_rate=0.001,p1=0.95,p2=0.99,e=10^(-12))
new(learning_rate,p1,p2,e,[],[])
end
end
function fit!(this::Adam,model::Models)
@inbounds for i in 1:length(model.common.layers)
params = model.common.layers[i].params
if params === nothing
continue
end
for j in 1:length(params)
param = params[j]
s = copy(param) * 0
append!(this.vs,[s])
append!(this.ss,[s])
end
end
model.common.optimizer = this
nothing
end
function update!(this::Adam,model::Models)
cnt = 1
@inbounds for i in 1:length(model.common.layers)
grads = model.common.layers[i].grads
if grads === nothing
continue
end
for j in 1:length(grads)
grad = grads[j]
v = this.p1 .* this.vs[cnt] .+ (1-this.p1).*grad
s = this.p2 .* this.ss[cnt] .+ (1-this.p2).*(grad .^2)
model.common.layers[i].params[j] .-= this.learning_rate*(v./sqrt.(this.e .+s))
this.vs[cnt] = v
this.ss[cnt] = s
cnt+=1
end
end
nothing
end
function convert_to_cu!(this::Adam,model::Models)
this.vs = cu.(this.vs)
this.ss = cu.(this.ss)
return nothing
end
function convert_to_array!(this::Adam,model::Models)
this.vs = Array.(this.vs)
this.ss = Array.(this.ss)
return nothing
end | [
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] | 1.931102 | 2,032 |
__precompile__()
"""
# SeisRequests
Basic implementation of seismic web requests, returning only the raw results
of a request.
Currently implemented schemes are the FDSN Web Services specification, and IRIS's
web services specification for data (timeseries). Further specifications will
be added in the future.
To request data, create a one of the [FDSNRequest](@ref) types and use the
[get_request](@ref) method on it. This method returns a `HTTP.Message.Response`
containing the raw response in the field `body`.
### Specifications
FDSN Web Services request specification:
http://www.fdsn.org/webservices/FDSN-WS-Specifications-1.1.pdf
Details on IRISWS timeseries can be found at:
https://service.iris.edu/irisws/timeseries/1/
"""
module SeisRequests
export
FDSNDataSelect,
FDSNEvent,
FDSNStation,
IRISTimeSeries,
add_server!,
get_request,
request_uri,
server_list
using Compat
using Compat.Dates
import Compat: @info
@static if VERSION < v"0.7-"
using Missings
end
using HTTP
using Parameters
import DataStructures: OrderedDict
"URIs of servers to which requests can be sent by key"
const SERVERS = Dict{String,String}(
"IRIS" => "http://service.iris.edu",
"INGV" => "http://webservices.ingv.it",
"Orfeus" => "http://www.orfeus-eu.org",
"NCEDC" => "http://service.ncedc.org")
const DEFAULT_SERVER = "IRIS"
"Dict describing the common HTTP status codes returned by FDSN services"
const STATUS_CODES = Dict{Int,String}(
200 => "Successful request, results follow",
204 => "Request was properly formatted and submitted but no data matches the selection",
400 => "Bad request due to improper specification, unrecognized parameter, parameter value out of range, etc.",
401 => "Unauthorized, authentication required",
403 => "Authentication failed or access blocked to restricted data",
404 => "Alternate to 204 (set via the ‘nodata’ parameter), normally used for results returned to a web browser.",
413 => "Request would result in too much data being returned or the request itself is too large, returned error message should include the service limitations in the detailed description. Service limits should also be documented in the service WADL.",
414 => "Request URI too large",
500 => "Internal server error",
503 => "Service temporarily unavailable, used in maintenance and error conditions")
const CODE_SUCCESS = 200
const CODES_FAILURE = (400, 401, 403, 404, 413, 414, 500, 503)
# Types which accept missing values
const MBool = Union{Missing,Bool}
const MDateTime = Union{Missing,DateTime}
const MFloat = Union{Missing,Float64}
const MInt = Union{Missing,Int}
const MString = Union{Missing,String}
"""
SeisRequest
An abstract type representing any kind of web request for seismic data.
Current subtypes of `SeisRequest`:
- `FDSNRequest`
- `IRISRequest`
"""
abstract type SeisRequest end
include("fdsnws.jl")
include("irisws.jl")
"""Default version string for all requests."""
version_string(::SeisRequest) = "1"
"""
request_uri(r::SeisRequest; server=$(DEFAULT_SERVER)) -> uri
Return a URI for the request `r`, which can then be obtained via HTTP GET.
`server` can either be a URI or one of the available servers. (See [server_list](@ref).)
"""
function request_uri(r::SeisRequest; server=DEFAULT_SERVER)
server = server in keys(SERVERS) ? SERVERS[server] : server
protocol = protocol_string(r)
service = service_string(r)
version = version_string(r)
uri = join((server, protocol, service, version, "query?"), "/")
firstfield = true
if server == "http://service.ncedc.org"
for f in fieldnames(typeof(r))
v = getfield(r, f)
if !ismissing(v)
if f == :starttime
firstfield ? (uri *= "$(f)"[1:5]*"=$(v)"; firstfield=false) : uri = join((uri, "$(f)"[1:5]*"=$(v)"), "&")
elseif (f == :format) || (f == :nodata) #not print in uri
else
firstfield ? (uri *= "$(f)"[1:3]*"=$(v)"; firstfield=false) : uri = join((uri, "$(f)"[1:3]*"=$(v)"), "&")
end
end
end
else
for f in fieldnames(typeof(r))
v = getfield(r, f)
if !ismissing(v)
if firstfield
uri *= "$(f)=$(v)"
firstfield = false
else
uri = join((uri, "$(f)=$(v)"), "&")
end
end
end
end
uri
end
"""
add_server!(label, uri)
Add a server with key `label` to the global list of servers.
See also [server_list](@ref).
"""
function add_server!(label, uri)
label ∈ keys(SERVERS) && throw(ArgumentError("A server with label `$label` already exists"))
SERVERS[label] = uri
end
"""
server_list() -> servers
Return a list of available servers for use with a `SeisRequest`.
See also [add_server!](@ref).
"""
server_list() = collect(keys(SERVERS))
"""
get_request(r::SeisRequest; server=$(DEFAULT_SERVER)) -> response::HTTP.Message.Response
Return `response`, the result of requesting `r` via the HTTP GET command. Optionally specify
the server either by URI or one of the available servers. (See [server_list](@ref).)
"""
function get_request(r::SeisRequest; server=DEFAULT_SERVER, verbose=true)
uri = request_uri(r; server=server)
#Specify request headers
#Wrong request headers cause server internal error (500)
if server == "NCEDC"
headers = ["Host" => "service.ncedc.org", "User-Agent" => "curl/7.60.0", "Accept" => "*/*"]
elseif server == "IRIS"
headers = ["Host" => "service.iris.edu", "User-Agent" => "curl/7.60.0", "Accept" => "*/*"]
else
headers = []
end
response = HTTP.request("GET", uri; headers=headers)
status_text = STATUS_CODES[response.status]
if verbose
@info("Request status: " * status_text)
else
response.status in CODES_FAILURE && warn("Request status: " * status_text)
end
response
end
end # module
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] | 2.641836 | 2,309 |
words = ["Enjoy", "Rosetta", "Code"]
function sleepprint(s)
sleep(rand())
println(s)
end
@sync for word in words
@async sleepprint(word)
end
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if Sys.iswindows()
@info "No tests enabled for for your platform by default."
else
include("gen.jl")
ENV["TEST_SRVR_ASYNC"] = "true"
include("srvr.jl")
include("clnt.jl")
include("memtransport_tests.jl")
include("filetransport_tests.jl")
include("utils_tests.jl")
end
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] | 2.495868 | 121 |
###############################################################################
##### Theta functions
###############################################################################
struct Theta
nome ::ComplexF64
nome_powers ::Array{ComplexF64, 2}
powers_num ::Int64
ϵ ::Float64
end
function Theta(ω1::ComplexF64,
ω3::ComplexF64,
ϵ ::Float64)
q = nome(ω1, ω3)
nome_powers = precompute_nome_powers(q, ϵ, ω1+ω3)
powers_num = size(nome_powers, 2)
Theta(q, nome_powers, powers_num, ϵ)
end
"""
nome(ω1::ComplexF64, ω3::ComplexF64)
Return the nome for the giving pair of lattice generators.
"""
function nome(
ω1::ComplexF64,
ω3::ComplexF64
)
#####
τ = ω3 / ω1
q = exp(1im * π * τ)
end
"""
precompute_nome_powers(; q::ComplexF64, ϵ::Float64, z0::ComplexF64, max_n_terms ::Integer = 10)
Create array of precomputed nome powers for evaluating theta functions with given tolerance.
# RETURN:
- Array{ComplexF64, 2}(2, n)
"""
function precompute_nome_powers(
# nome
q ::ComplexF64,
# tolerance
ϵ ::Float64,
# point for tolerance checking
z0 ::ComplexF64,
# maximum number of terms
max_n_terms ::Integer = 10
)
#####
n = 0
while true
# theta_1(z,q) = 2 sum_{n=0}^infty (-1)^n q^{(n+0.5)^2} sin((2n+1)z)
dt1 = 2*(2n+1)*cos((2n+1)*z0)*q^((n+0.5)^2)
# theta_2(z,q) = 2 sum_{n=0}^infty q^{(n+0.5)^2} cos((2n+1)z)
dt2 = 2*(2n+1)*sin((2n+1)*z0)*q^((n+0.5)^2)
if (abs(dt1) < ϵ) && (abs(dt1) < ϵ)
break
end
n += 1
if n > max_n_terms
error("Series don't converge")
end
end
nome_powers = Array{ComplexF64, 2}(undef, 2, n+1)
for k in 0 : n
nome_powers[1, k+1] = q^((k+0.5)^2)
nome_powers[2, k+1] = nome_powers[1, k+1] * (2k+1)
end
return nome_powers
end
@doc """
theta(th::Theta, z::ComplexF64)
Compute θ_1(z), θ_2(z), θ_1'(z), θ_2'(z) with given precomputed array of nome powers.
"""
function theta(
th ::Theta,
z ::ComplexF64
)
#####
t1 :: ComplexF64 = 0
t2 :: ComplexF64 = 0
dt1 :: ComplexF64 = 0
dt2 :: ComplexF64 = 0
sign = 1.0
N = th.powers_num-1
for n in 0 : N
z_n = (2n+1)*z
sin_z = sin(z_n)
cos_z = cos(z_n)
# theta_1(z,q) = 2 sum_{n=0}^N (-1)^n q^{(n+0.5)^2} sin((2n+1)z)
t1 += 2 * sign * th.nome_powers[1, n+1] * sin_z
# theta_2(z,q) = 2 sum_{n=0}^N q^{(n+0.5)^2} cos((2n+1)z)
t2 += 2 * th.nome_powers[1, n+1] * cos_z
# theta_1'(z,q) = 2 sum_{n=0}^N (-1)^n (2n+1) q^{(n+0.5)^2} cos((2n+1)z))
dt1 += 2 * sign * th.nome_powers[2, n+1] * cos_z
# theta_2'(z,q) = -2 sum_{n=0}^N (2n+1) q^{(n+0.5)^2} sin((2n+1)z)
dt2 += -2 * th.nome_powers[2, n+1] * sin_z
sign = -sign
end
return t1, t2, dt1, dt2
end
""""
theta(θ::Theta; th_k::Integer, d_n::Integer,z::ComplexF64)
Compute ``\\frac{d^n}{dz^n} \\theta_k(z, q)`` with tolerance `ϵ`.
"""
function theta(
# Theta data struct
th ::Theta;
# theta-function number
th_k ::Integer,
# derivative number
d_n ::Integer,
# point for computation
z ::ComplexF64,
)
#####
q = th.nome
ϵ = th.ϵ
if (th_k < 1) || (th_k > 4)
error("Invalid theta function number")
end
rem_d = d_n % 4
d_sin_sign = (rem_d == 0) || (rem_d == 1) ? 1 : -1
d_cos_sign = (rem_d == 0) || (rem_d == 3) ? 1 : -1
res :: ComplexF64 = 0
if (th_k == 1) || (th_k == 2)
res = 0
n = 0
else
n = 1
if d_n == 0
res = 1
else
res = 0
end
end
sign = (-1)^n
while true
# theta_1(z,q) = 2 sum_{n=0}^infty (-1)^n q^{(n+0.5)^2} sin((2n+1)z)
if th_k == 1
term = 2 * sign * (2n+1)^d_n * q^((n+0.5)^2) * d_sin_sign
if d_n % 2 == 0
term *= sin((2n+1)*z)
else
term *= cos((2n+1)*z)
end
end
# theta_2(z,q) = 2 sum_{n=0}^infty q^{(n+0.5)^2} cos((2n+1)z)
if th_k == 2
term = 2 * (2n+1)^d_n * q^((n+0.5)^2) * d_cos_sign
if d_n % 2 == 0
term *= cos((2n+1)*z)
else
term *= sin((2n+1)*z)
end
end
# theta_3(z,q) = 1 + 2 sum_{n=1}^infty q^{n^2} cos(2nz)
if th_k == 3
term = 2 * (2n)^d_n * q^(n^2) * d_cos_sign
if d_n % 2 == 0
term *= cos(2n*z)
else
term *= sin(2n*z)
end
end
# theta_4(z,q) = 1 + 2 sum_{n=1}^infty (-1)^n q^{n^2} cos(2nz)
if th_k == 4
term = 2 * sign * (2n)^d_n * q^(n^2) * d_cos_sign
if d_n % 2 == 0
term *= cos(2n*z)
else
term *= sin(2n*z)
end
end
res += term
n += 1
sign = -sign
if abs(term) < ϵ
break
end
end
return res
end
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# This file was generated by the Julia Swagger Code Generator
# Do not modify this file directly. Modify the swagger specification instead.
struct AppsV1beta1Api <: SwaggerApi
client::Swagger.Client
end
function _swaggerinternal_createAppsV1beta1NamespacedControllerRevision(_api::AppsV1beta1Api, namespace::String, body; pretty=nothing, dryRun=nothing, fieldManager=nothing, _mediaType=nothing)
_ctx = Swagger.Ctx(_api.client, "POST", IoK8sApiAppsV1beta1ControllerRevision, "/apis/apps/v1beta1/namespaces/{namespace}/controllerrevisions", ["BearerToken"], body)
Swagger.set_param(_ctx.path, "namespace", namespace) # type String
Swagger.set_param(_ctx.query, "pretty", pretty) # type String
Swagger.set_param(_ctx.query, "dryRun", dryRun) # type String
Swagger.set_param(_ctx.query, "fieldManager", fieldManager) # type String
Swagger.set_header_accept(_ctx, ["application/json", "application/yaml", "application/vnd.kubernetes.protobuf"])
Swagger.set_header_content_type(_ctx, (_mediaType === nothing) ? ["*/*"] : [_mediaType])
return _ctx
end
"""
create a ControllerRevision
Param: namespace::String (required)
Param: body::IoK8sApiAppsV1beta1ControllerRevision (required)
Param: pretty::String
Param: dryRun::String
Param: fieldManager::String
Return: IoK8sApiAppsV1beta1ControllerRevision
"""
function createAppsV1beta1NamespacedControllerRevision(_api::AppsV1beta1Api, namespace::String, body; pretty=nothing, dryRun=nothing, fieldManager=nothing, _mediaType=nothing)
_ctx = _swaggerinternal_createAppsV1beta1NamespacedControllerRevision(_api, namespace, body; pretty=pretty, dryRun=dryRun, fieldManager=fieldManager, _mediaType=_mediaType)
Swagger.exec(_ctx)
end
function createAppsV1beta1NamespacedControllerRevision(_api::AppsV1beta1Api, response_stream::Channel, namespace::String, body; pretty=nothing, dryRun=nothing, fieldManager=nothing, _mediaType=nothing)
_ctx = _swaggerinternal_createAppsV1beta1NamespacedControllerRevision(_api, namespace, body; pretty=pretty, dryRun=dryRun, fieldManager=fieldManager, _mediaType=_mediaType)
Swagger.exec(_ctx, response_stream)
end
function _swaggerinternal_createAppsV1beta1NamespacedDeployment(_api::AppsV1beta1Api, namespace::String, body; pretty=nothing, dryRun=nothing, fieldManager=nothing, _mediaType=nothing)
_ctx = Swagger.Ctx(_api.client, "POST", IoK8sApiAppsV1beta1Deployment, "/apis/apps/v1beta1/namespaces/{namespace}/deployments", ["BearerToken"], body)
Swagger.set_param(_ctx.path, "namespace", namespace) # type String
Swagger.set_param(_ctx.query, "pretty", pretty) # type String
Swagger.set_param(_ctx.query, "dryRun", dryRun) # type String
Swagger.set_param(_ctx.query, "fieldManager", fieldManager) # type String
Swagger.set_header_accept(_ctx, ["application/json", "application/yaml", "application/vnd.kubernetes.protobuf"])
Swagger.set_header_content_type(_ctx, (_mediaType === nothing) ? ["*/*"] : [_mediaType])
return _ctx
end
"""
create a Deployment
Param: namespace::String (required)
Param: body::IoK8sApiAppsV1beta1Deployment (required)
Param: pretty::String
Param: dryRun::String
Param: fieldManager::String
Return: IoK8sApiAppsV1beta1Deployment
"""
function createAppsV1beta1NamespacedDeployment(_api::AppsV1beta1Api, namespace::String, body; pretty=nothing, dryRun=nothing, fieldManager=nothing, _mediaType=nothing)
_ctx = _swaggerinternal_createAppsV1beta1NamespacedDeployment(_api, namespace, body; pretty=pretty, dryRun=dryRun, fieldManager=fieldManager, _mediaType=_mediaType)
Swagger.exec(_ctx)
end
function createAppsV1beta1NamespacedDeployment(_api::AppsV1beta1Api, response_stream::Channel, namespace::String, body; pretty=nothing, dryRun=nothing, fieldManager=nothing, _mediaType=nothing)
_ctx = _swaggerinternal_createAppsV1beta1NamespacedDeployment(_api, namespace, body; pretty=pretty, dryRun=dryRun, fieldManager=fieldManager, _mediaType=_mediaType)
Swagger.exec(_ctx, response_stream)
end
function _swaggerinternal_createAppsV1beta1NamespacedDeploymentRollback(_api::AppsV1beta1Api, name::String, namespace::String, body; dryRun=nothing, fieldManager=nothing, pretty=nothing, _mediaType=nothing)
_ctx = Swagger.Ctx(_api.client, "POST", IoK8sApimachineryPkgApisMetaV1Status, "/apis/apps/v1beta1/namespaces/{namespace}/deployments/{name}/rollback", ["BearerToken"], body)
Swagger.set_param(_ctx.path, "name", name) # type String
Swagger.set_param(_ctx.path, "namespace", namespace) # type String
Swagger.set_param(_ctx.query, "dryRun", dryRun) # type String
Swagger.set_param(_ctx.query, "fieldManager", fieldManager) # type String
Swagger.set_param(_ctx.query, "pretty", pretty) # type String
Swagger.set_header_accept(_ctx, ["application/json", "application/yaml", "application/vnd.kubernetes.protobuf"])
Swagger.set_header_content_type(_ctx, (_mediaType === nothing) ? ["*/*"] : [_mediaType])
return _ctx
end
"""
create rollback of a Deployment
Param: name::String (required)
Param: namespace::String (required)
Param: body::IoK8sApiAppsV1beta1DeploymentRollback (required)
Param: dryRun::String
Param: fieldManager::String
Param: pretty::String
Return: IoK8sApimachineryPkgApisMetaV1Status
"""
function createAppsV1beta1NamespacedDeploymentRollback(_api::AppsV1beta1Api, name::String, namespace::String, body; dryRun=nothing, fieldManager=nothing, pretty=nothing, _mediaType=nothing)
_ctx = _swaggerinternal_createAppsV1beta1NamespacedDeploymentRollback(_api, name, namespace, body; dryRun=dryRun, fieldManager=fieldManager, pretty=pretty, _mediaType=_mediaType)
Swagger.exec(_ctx)
end
function createAppsV1beta1NamespacedDeploymentRollback(_api::AppsV1beta1Api, response_stream::Channel, name::String, namespace::String, body; dryRun=nothing, fieldManager=nothing, pretty=nothing, _mediaType=nothing)
_ctx = _swaggerinternal_createAppsV1beta1NamespacedDeploymentRollback(_api, name, namespace, body; dryRun=dryRun, fieldManager=fieldManager, pretty=pretty, _mediaType=_mediaType)
Swagger.exec(_ctx, response_stream)
end
function _swaggerinternal_createAppsV1beta1NamespacedStatefulSet(_api::AppsV1beta1Api, namespace::String, body; pretty=nothing, dryRun=nothing, fieldManager=nothing, _mediaType=nothing)
_ctx = Swagger.Ctx(_api.client, "POST", IoK8sApiAppsV1beta1StatefulSet, "/apis/apps/v1beta1/namespaces/{namespace}/statefulsets", ["BearerToken"], body)
Swagger.set_param(_ctx.path, "namespace", namespace) # type String
Swagger.set_param(_ctx.query, "pretty", pretty) # type String
Swagger.set_param(_ctx.query, "dryRun", dryRun) # type String
Swagger.set_param(_ctx.query, "fieldManager", fieldManager) # type String
Swagger.set_header_accept(_ctx, ["application/json", "application/yaml", "application/vnd.kubernetes.protobuf"])
Swagger.set_header_content_type(_ctx, (_mediaType === nothing) ? ["*/*"] : [_mediaType])
return _ctx
end
"""
create a StatefulSet
Param: namespace::String (required)
Param: body::IoK8sApiAppsV1beta1StatefulSet (required)
Param: pretty::String
Param: dryRun::String
Param: fieldManager::String
Return: IoK8sApiAppsV1beta1StatefulSet
"""
function createAppsV1beta1NamespacedStatefulSet(_api::AppsV1beta1Api, namespace::String, body; pretty=nothing, dryRun=nothing, fieldManager=nothing, _mediaType=nothing)
_ctx = _swaggerinternal_createAppsV1beta1NamespacedStatefulSet(_api, namespace, body; pretty=pretty, dryRun=dryRun, fieldManager=fieldManager, _mediaType=_mediaType)
Swagger.exec(_ctx)
end
function createAppsV1beta1NamespacedStatefulSet(_api::AppsV1beta1Api, response_stream::Channel, namespace::String, body; pretty=nothing, dryRun=nothing, fieldManager=nothing, _mediaType=nothing)
_ctx = _swaggerinternal_createAppsV1beta1NamespacedStatefulSet(_api, namespace, body; pretty=pretty, dryRun=dryRun, fieldManager=fieldManager, _mediaType=_mediaType)
Swagger.exec(_ctx, response_stream)
end
function _swaggerinternal_deleteAppsV1beta1CollectionNamespacedControllerRevision(_api::AppsV1beta1Api, namespace::String; pretty=nothing, allowWatchBookmarks=nothing, body=nothing, __continue__=nothing, dryRun=nothing, fieldSelector=nothing, gracePeriodSeconds=nothing, labelSelector=nothing, limit=nothing, orphanDependents=nothing, propagationPolicy=nothing, resourceVersion=nothing, timeoutSeconds=nothing, watch=nothing, _mediaType=nothing)
_ctx = Swagger.Ctx(_api.client, "DELETE", IoK8sApimachineryPkgApisMetaV1Status, "/apis/apps/v1beta1/namespaces/{namespace}/controllerrevisions", ["BearerToken"], body)
Swagger.set_param(_ctx.path, "namespace", namespace) # type String
Swagger.set_param(_ctx.query, "pretty", pretty) # type String
Swagger.set_param(_ctx.query, "allowWatchBookmarks", allowWatchBookmarks) # type Bool
Swagger.set_param(_ctx.query, "continue", __continue__) # type String
Swagger.set_param(_ctx.query, "dryRun", dryRun) # type String
Swagger.set_param(_ctx.query, "fieldSelector", fieldSelector) # type String
Swagger.set_param(_ctx.query, "gracePeriodSeconds", gracePeriodSeconds) # type Int32
Swagger.set_param(_ctx.query, "labelSelector", labelSelector) # type String
Swagger.set_param(_ctx.query, "limit", limit) # type Int32
Swagger.set_param(_ctx.query, "orphanDependents", orphanDependents) # type Bool
Swagger.set_param(_ctx.query, "propagationPolicy", propagationPolicy) # type String
Swagger.set_param(_ctx.query, "resourceVersion", resourceVersion) # type String
Swagger.set_param(_ctx.query, "timeoutSeconds", timeoutSeconds) # type Int32
Swagger.set_param(_ctx.query, "watch", watch) # type Bool
Swagger.set_header_accept(_ctx, ["application/json", "application/yaml", "application/vnd.kubernetes.protobuf"])
Swagger.set_header_content_type(_ctx, (_mediaType === nothing) ? ["*/*"] : [_mediaType])
return _ctx
end
"""
delete collection of ControllerRevision
Param: namespace::String (required)
Param: pretty::String
Param: allowWatchBookmarks::Bool
Param: body::IoK8sApimachineryPkgApisMetaV1DeleteOptions
Param: __continue__::String
Param: dryRun::String
Param: fieldSelector::String
Param: gracePeriodSeconds::Int32
Param: labelSelector::String
Param: limit::Int32
Param: orphanDependents::Bool
Param: propagationPolicy::String
Param: resourceVersion::String
Param: timeoutSeconds::Int32
Param: watch::Bool
Return: IoK8sApimachineryPkgApisMetaV1Status
"""
function deleteAppsV1beta1CollectionNamespacedControllerRevision(_api::AppsV1beta1Api, namespace::String; pretty=nothing, allowWatchBookmarks=nothing, body=nothing, __continue__=nothing, dryRun=nothing, fieldSelector=nothing, gracePeriodSeconds=nothing, labelSelector=nothing, limit=nothing, orphanDependents=nothing, propagationPolicy=nothing, resourceVersion=nothing, timeoutSeconds=nothing, watch=nothing, _mediaType=nothing)
_ctx = _swaggerinternal_deleteAppsV1beta1CollectionNamespacedControllerRevision(_api, namespace; pretty=pretty, allowWatchBookmarks=allowWatchBookmarks, body=body, __continue__=__continue__, dryRun=dryRun, fieldSelector=fieldSelector, gracePeriodSeconds=gracePeriodSeconds, labelSelector=labelSelector, limit=limit, orphanDependents=orphanDependents, propagationPolicy=propagationPolicy, resourceVersion=resourceVersion, timeoutSeconds=timeoutSeconds, watch=watch, _mediaType=_mediaType)
Swagger.exec(_ctx)
end
function deleteAppsV1beta1CollectionNamespacedControllerRevision(_api::AppsV1beta1Api, response_stream::Channel, namespace::String; pretty=nothing, allowWatchBookmarks=nothing, body=nothing, __continue__=nothing, dryRun=nothing, fieldSelector=nothing, gracePeriodSeconds=nothing, labelSelector=nothing, limit=nothing, orphanDependents=nothing, propagationPolicy=nothing, resourceVersion=nothing, timeoutSeconds=nothing, watch=nothing, _mediaType=nothing)
_ctx = _swaggerinternal_deleteAppsV1beta1CollectionNamespacedControllerRevision(_api, namespace; pretty=pretty, allowWatchBookmarks=allowWatchBookmarks, body=body, __continue__=__continue__, dryRun=dryRun, fieldSelector=fieldSelector, gracePeriodSeconds=gracePeriodSeconds, labelSelector=labelSelector, limit=limit, orphanDependents=orphanDependents, propagationPolicy=propagationPolicy, resourceVersion=resourceVersion, timeoutSeconds=timeoutSeconds, watch=watch, _mediaType=_mediaType)
Swagger.exec(_ctx, response_stream)
end
function _swaggerinternal_deleteAppsV1beta1CollectionNamespacedDeployment(_api::AppsV1beta1Api, namespace::String; pretty=nothing, allowWatchBookmarks=nothing, body=nothing, __continue__=nothing, dryRun=nothing, fieldSelector=nothing, gracePeriodSeconds=nothing, labelSelector=nothing, limit=nothing, orphanDependents=nothing, propagationPolicy=nothing, resourceVersion=nothing, timeoutSeconds=nothing, watch=nothing, _mediaType=nothing)
_ctx = Swagger.Ctx(_api.client, "DELETE", IoK8sApimachineryPkgApisMetaV1Status, "/apis/apps/v1beta1/namespaces/{namespace}/deployments", ["BearerToken"], body)
Swagger.set_param(_ctx.path, "namespace", namespace) # type String
Swagger.set_param(_ctx.query, "pretty", pretty) # type String
Swagger.set_param(_ctx.query, "allowWatchBookmarks", allowWatchBookmarks) # type Bool
Swagger.set_param(_ctx.query, "continue", __continue__) # type String
Swagger.set_param(_ctx.query, "dryRun", dryRun) # type String
Swagger.set_param(_ctx.query, "fieldSelector", fieldSelector) # type String
Swagger.set_param(_ctx.query, "gracePeriodSeconds", gracePeriodSeconds) # type Int32
Swagger.set_param(_ctx.query, "labelSelector", labelSelector) # type String
Swagger.set_param(_ctx.query, "limit", limit) # type Int32
Swagger.set_param(_ctx.query, "orphanDependents", orphanDependents) # type Bool
Swagger.set_param(_ctx.query, "propagationPolicy", propagationPolicy) # type String
Swagger.set_param(_ctx.query, "resourceVersion", resourceVersion) # type String
Swagger.set_param(_ctx.query, "timeoutSeconds", timeoutSeconds) # type Int32
Swagger.set_param(_ctx.query, "watch", watch) # type Bool
Swagger.set_header_accept(_ctx, ["application/json", "application/yaml", "application/vnd.kubernetes.protobuf"])
Swagger.set_header_content_type(_ctx, (_mediaType === nothing) ? ["*/*"] : [_mediaType])
return _ctx
end
"""
delete collection of Deployment
Param: namespace::String (required)
Param: pretty::String
Param: allowWatchBookmarks::Bool
Param: body::IoK8sApimachineryPkgApisMetaV1DeleteOptions
Param: __continue__::String
Param: dryRun::String
Param: fieldSelector::String
Param: gracePeriodSeconds::Int32
Param: labelSelector::String
Param: limit::Int32
Param: orphanDependents::Bool
Param: propagationPolicy::String
Param: resourceVersion::String
Param: timeoutSeconds::Int32
Param: watch::Bool
Return: IoK8sApimachineryPkgApisMetaV1Status
"""
function deleteAppsV1beta1CollectionNamespacedDeployment(_api::AppsV1beta1Api, namespace::String; pretty=nothing, allowWatchBookmarks=nothing, body=nothing, __continue__=nothing, dryRun=nothing, fieldSelector=nothing, gracePeriodSeconds=nothing, labelSelector=nothing, limit=nothing, orphanDependents=nothing, propagationPolicy=nothing, resourceVersion=nothing, timeoutSeconds=nothing, watch=nothing, _mediaType=nothing)
_ctx = _swaggerinternal_deleteAppsV1beta1CollectionNamespacedDeployment(_api, namespace; pretty=pretty, allowWatchBookmarks=allowWatchBookmarks, body=body, __continue__=__continue__, dryRun=dryRun, fieldSelector=fieldSelector, gracePeriodSeconds=gracePeriodSeconds, labelSelector=labelSelector, limit=limit, orphanDependents=orphanDependents, propagationPolicy=propagationPolicy, resourceVersion=resourceVersion, timeoutSeconds=timeoutSeconds, watch=watch, _mediaType=_mediaType)
Swagger.exec(_ctx)
end
function deleteAppsV1beta1CollectionNamespacedDeployment(_api::AppsV1beta1Api, response_stream::Channel, namespace::String; pretty=nothing, allowWatchBookmarks=nothing, body=nothing, __continue__=nothing, dryRun=nothing, fieldSelector=nothing, gracePeriodSeconds=nothing, labelSelector=nothing, limit=nothing, orphanDependents=nothing, propagationPolicy=nothing, resourceVersion=nothing, timeoutSeconds=nothing, watch=nothing, _mediaType=nothing)
_ctx = _swaggerinternal_deleteAppsV1beta1CollectionNamespacedDeployment(_api, namespace; pretty=pretty, allowWatchBookmarks=allowWatchBookmarks, body=body, __continue__=__continue__, dryRun=dryRun, fieldSelector=fieldSelector, gracePeriodSeconds=gracePeriodSeconds, labelSelector=labelSelector, limit=limit, orphanDependents=orphanDependents, propagationPolicy=propagationPolicy, resourceVersion=resourceVersion, timeoutSeconds=timeoutSeconds, watch=watch, _mediaType=_mediaType)
Swagger.exec(_ctx, response_stream)
end
function _swaggerinternal_deleteAppsV1beta1CollectionNamespacedStatefulSet(_api::AppsV1beta1Api, namespace::String; pretty=nothing, allowWatchBookmarks=nothing, body=nothing, __continue__=nothing, dryRun=nothing, fieldSelector=nothing, gracePeriodSeconds=nothing, labelSelector=nothing, limit=nothing, orphanDependents=nothing, propagationPolicy=nothing, resourceVersion=nothing, timeoutSeconds=nothing, watch=nothing, _mediaType=nothing)
_ctx = Swagger.Ctx(_api.client, "DELETE", IoK8sApimachineryPkgApisMetaV1Status, "/apis/apps/v1beta1/namespaces/{namespace}/statefulsets", ["BearerToken"], body)
Swagger.set_param(_ctx.path, "namespace", namespace) # type String
Swagger.set_param(_ctx.query, "pretty", pretty) # type String
Swagger.set_param(_ctx.query, "allowWatchBookmarks", allowWatchBookmarks) # type Bool
Swagger.set_param(_ctx.query, "continue", __continue__) # type String
Swagger.set_param(_ctx.query, "dryRun", dryRun) # type String
Swagger.set_param(_ctx.query, "fieldSelector", fieldSelector) # type String
Swagger.set_param(_ctx.query, "gracePeriodSeconds", gracePeriodSeconds) # type Int32
Swagger.set_param(_ctx.query, "labelSelector", labelSelector) # type String
Swagger.set_param(_ctx.query, "limit", limit) # type Int32
Swagger.set_param(_ctx.query, "orphanDependents", orphanDependents) # type Bool
Swagger.set_param(_ctx.query, "propagationPolicy", propagationPolicy) # type String
Swagger.set_param(_ctx.query, "resourceVersion", resourceVersion) # type String
Swagger.set_param(_ctx.query, "timeoutSeconds", timeoutSeconds) # type Int32
Swagger.set_param(_ctx.query, "watch", watch) # type Bool
Swagger.set_header_accept(_ctx, ["application/json", "application/yaml", "application/vnd.kubernetes.protobuf"])
Swagger.set_header_content_type(_ctx, (_mediaType === nothing) ? ["*/*"] : [_mediaType])
return _ctx
end
"""
delete collection of StatefulSet
Param: namespace::String (required)
Param: pretty::String
Param: allowWatchBookmarks::Bool
Param: body::IoK8sApimachineryPkgApisMetaV1DeleteOptions
Param: __continue__::String
Param: dryRun::String
Param: fieldSelector::String
Param: gracePeriodSeconds::Int32
Param: labelSelector::String
Param: limit::Int32
Param: orphanDependents::Bool
Param: propagationPolicy::String
Param: resourceVersion::String
Param: timeoutSeconds::Int32
Param: watch::Bool
Return: IoK8sApimachineryPkgApisMetaV1Status
"""
function deleteAppsV1beta1CollectionNamespacedStatefulSet(_api::AppsV1beta1Api, namespace::String; pretty=nothing, allowWatchBookmarks=nothing, body=nothing, __continue__=nothing, dryRun=nothing, fieldSelector=nothing, gracePeriodSeconds=nothing, labelSelector=nothing, limit=nothing, orphanDependents=nothing, propagationPolicy=nothing, resourceVersion=nothing, timeoutSeconds=nothing, watch=nothing, _mediaType=nothing)
_ctx = _swaggerinternal_deleteAppsV1beta1CollectionNamespacedStatefulSet(_api, namespace; pretty=pretty, allowWatchBookmarks=allowWatchBookmarks, body=body, __continue__=__continue__, dryRun=dryRun, fieldSelector=fieldSelector, gracePeriodSeconds=gracePeriodSeconds, labelSelector=labelSelector, limit=limit, orphanDependents=orphanDependents, propagationPolicy=propagationPolicy, resourceVersion=resourceVersion, timeoutSeconds=timeoutSeconds, watch=watch, _mediaType=_mediaType)
Swagger.exec(_ctx)
end
function deleteAppsV1beta1CollectionNamespacedStatefulSet(_api::AppsV1beta1Api, response_stream::Channel, namespace::String; pretty=nothing, allowWatchBookmarks=nothing, body=nothing, __continue__=nothing, dryRun=nothing, fieldSelector=nothing, gracePeriodSeconds=nothing, labelSelector=nothing, limit=nothing, orphanDependents=nothing, propagationPolicy=nothing, resourceVersion=nothing, timeoutSeconds=nothing, watch=nothing, _mediaType=nothing)
_ctx = _swaggerinternal_deleteAppsV1beta1CollectionNamespacedStatefulSet(_api, namespace; pretty=pretty, allowWatchBookmarks=allowWatchBookmarks, body=body, __continue__=__continue__, dryRun=dryRun, fieldSelector=fieldSelector, gracePeriodSeconds=gracePeriodSeconds, labelSelector=labelSelector, limit=limit, orphanDependents=orphanDependents, propagationPolicy=propagationPolicy, resourceVersion=resourceVersion, timeoutSeconds=timeoutSeconds, watch=watch, _mediaType=_mediaType)
Swagger.exec(_ctx, response_stream)
end
function _swaggerinternal_deleteAppsV1beta1NamespacedControllerRevision(_api::AppsV1beta1Api, name::String, namespace::String; pretty=nothing, body=nothing, dryRun=nothing, gracePeriodSeconds=nothing, orphanDependents=nothing, propagationPolicy=nothing, _mediaType=nothing)
_ctx = Swagger.Ctx(_api.client, "DELETE", IoK8sApimachineryPkgApisMetaV1Status, "/apis/apps/v1beta1/namespaces/{namespace}/controllerrevisions/{name}", ["BearerToken"], body)
Swagger.set_param(_ctx.path, "name", name) # type String
Swagger.set_param(_ctx.path, "namespace", namespace) # type String
Swagger.set_param(_ctx.query, "pretty", pretty) # type String
Swagger.set_param(_ctx.query, "dryRun", dryRun) # type String
Swagger.set_param(_ctx.query, "gracePeriodSeconds", gracePeriodSeconds) # type Int32
Swagger.set_param(_ctx.query, "orphanDependents", orphanDependents) # type Bool
Swagger.set_param(_ctx.query, "propagationPolicy", propagationPolicy) # type String
Swagger.set_header_accept(_ctx, ["application/json", "application/yaml", "application/vnd.kubernetes.protobuf"])
Swagger.set_header_content_type(_ctx, (_mediaType === nothing) ? ["*/*"] : [_mediaType])
return _ctx
end
"""
delete a ControllerRevision
Param: name::String (required)
Param: namespace::String (required)
Param: pretty::String
Param: body::IoK8sApimachineryPkgApisMetaV1DeleteOptions
Param: dryRun::String
Param: gracePeriodSeconds::Int32
Param: orphanDependents::Bool
Param: propagationPolicy::String
Return: IoK8sApimachineryPkgApisMetaV1Status
"""
function deleteAppsV1beta1NamespacedControllerRevision(_api::AppsV1beta1Api, name::String, namespace::String; pretty=nothing, body=nothing, dryRun=nothing, gracePeriodSeconds=nothing, orphanDependents=nothing, propagationPolicy=nothing, _mediaType=nothing)
_ctx = _swaggerinternal_deleteAppsV1beta1NamespacedControllerRevision(_api, name, namespace; pretty=pretty, body=body, dryRun=dryRun, gracePeriodSeconds=gracePeriodSeconds, orphanDependents=orphanDependents, propagationPolicy=propagationPolicy, _mediaType=_mediaType)
Swagger.exec(_ctx)
end
function deleteAppsV1beta1NamespacedControllerRevision(_api::AppsV1beta1Api, response_stream::Channel, name::String, namespace::String; pretty=nothing, body=nothing, dryRun=nothing, gracePeriodSeconds=nothing, orphanDependents=nothing, propagationPolicy=nothing, _mediaType=nothing)
_ctx = _swaggerinternal_deleteAppsV1beta1NamespacedControllerRevision(_api, name, namespace; pretty=pretty, body=body, dryRun=dryRun, gracePeriodSeconds=gracePeriodSeconds, orphanDependents=orphanDependents, propagationPolicy=propagationPolicy, _mediaType=_mediaType)
Swagger.exec(_ctx, response_stream)
end
function _swaggerinternal_deleteAppsV1beta1NamespacedDeployment(_api::AppsV1beta1Api, name::String, namespace::String; pretty=nothing, body=nothing, dryRun=nothing, gracePeriodSeconds=nothing, orphanDependents=nothing, propagationPolicy=nothing, _mediaType=nothing)
_ctx = Swagger.Ctx(_api.client, "DELETE", IoK8sApimachineryPkgApisMetaV1Status, "/apis/apps/v1beta1/namespaces/{namespace}/deployments/{name}", ["BearerToken"], body)
Swagger.set_param(_ctx.path, "name", name) # type String
Swagger.set_param(_ctx.path, "namespace", namespace) # type String
Swagger.set_param(_ctx.query, "pretty", pretty) # type String
Swagger.set_param(_ctx.query, "dryRun", dryRun) # type String
Swagger.set_param(_ctx.query, "gracePeriodSeconds", gracePeriodSeconds) # type Int32
Swagger.set_param(_ctx.query, "orphanDependents", orphanDependents) # type Bool
Swagger.set_param(_ctx.query, "propagationPolicy", propagationPolicy) # type String
Swagger.set_header_accept(_ctx, ["application/json", "application/yaml", "application/vnd.kubernetes.protobuf"])
Swagger.set_header_content_type(_ctx, (_mediaType === nothing) ? ["*/*"] : [_mediaType])
return _ctx
end
"""
delete a Deployment
Param: name::String (required)
Param: namespace::String (required)
Param: pretty::String
Param: body::IoK8sApimachineryPkgApisMetaV1DeleteOptions
Param: dryRun::String
Param: gracePeriodSeconds::Int32
Param: orphanDependents::Bool
Param: propagationPolicy::String
Return: IoK8sApimachineryPkgApisMetaV1Status
"""
function deleteAppsV1beta1NamespacedDeployment(_api::AppsV1beta1Api, name::String, namespace::String; pretty=nothing, body=nothing, dryRun=nothing, gracePeriodSeconds=nothing, orphanDependents=nothing, propagationPolicy=nothing, _mediaType=nothing)
_ctx = _swaggerinternal_deleteAppsV1beta1NamespacedDeployment(_api, name, namespace; pretty=pretty, body=body, dryRun=dryRun, gracePeriodSeconds=gracePeriodSeconds, orphanDependents=orphanDependents, propagationPolicy=propagationPolicy, _mediaType=_mediaType)
Swagger.exec(_ctx)
end
function deleteAppsV1beta1NamespacedDeployment(_api::AppsV1beta1Api, response_stream::Channel, name::String, namespace::String; pretty=nothing, body=nothing, dryRun=nothing, gracePeriodSeconds=nothing, orphanDependents=nothing, propagationPolicy=nothing, _mediaType=nothing)
_ctx = _swaggerinternal_deleteAppsV1beta1NamespacedDeployment(_api, name, namespace; pretty=pretty, body=body, dryRun=dryRun, gracePeriodSeconds=gracePeriodSeconds, orphanDependents=orphanDependents, propagationPolicy=propagationPolicy, _mediaType=_mediaType)
Swagger.exec(_ctx, response_stream)
end
function _swaggerinternal_deleteAppsV1beta1NamespacedStatefulSet(_api::AppsV1beta1Api, name::String, namespace::String; pretty=nothing, body=nothing, dryRun=nothing, gracePeriodSeconds=nothing, orphanDependents=nothing, propagationPolicy=nothing, _mediaType=nothing)
_ctx = Swagger.Ctx(_api.client, "DELETE", IoK8sApimachineryPkgApisMetaV1Status, "/apis/apps/v1beta1/namespaces/{namespace}/statefulsets/{name}", ["BearerToken"], body)
Swagger.set_param(_ctx.path, "name", name) # type String
Swagger.set_param(_ctx.path, "namespace", namespace) # type String
Swagger.set_param(_ctx.query, "pretty", pretty) # type String
Swagger.set_param(_ctx.query, "dryRun", dryRun) # type String
Swagger.set_param(_ctx.query, "gracePeriodSeconds", gracePeriodSeconds) # type Int32
Swagger.set_param(_ctx.query, "orphanDependents", orphanDependents) # type Bool
Swagger.set_param(_ctx.query, "propagationPolicy", propagationPolicy) # type String
Swagger.set_header_accept(_ctx, ["application/json", "application/yaml", "application/vnd.kubernetes.protobuf"])
Swagger.set_header_content_type(_ctx, (_mediaType === nothing) ? ["*/*"] : [_mediaType])
return _ctx
end
"""
delete a StatefulSet
Param: name::String (required)
Param: namespace::String (required)
Param: pretty::String
Param: body::IoK8sApimachineryPkgApisMetaV1DeleteOptions
Param: dryRun::String
Param: gracePeriodSeconds::Int32
Param: orphanDependents::Bool
Param: propagationPolicy::String
Return: IoK8sApimachineryPkgApisMetaV1Status
"""
function deleteAppsV1beta1NamespacedStatefulSet(_api::AppsV1beta1Api, name::String, namespace::String; pretty=nothing, body=nothing, dryRun=nothing, gracePeriodSeconds=nothing, orphanDependents=nothing, propagationPolicy=nothing, _mediaType=nothing)
_ctx = _swaggerinternal_deleteAppsV1beta1NamespacedStatefulSet(_api, name, namespace; pretty=pretty, body=body, dryRun=dryRun, gracePeriodSeconds=gracePeriodSeconds, orphanDependents=orphanDependents, propagationPolicy=propagationPolicy, _mediaType=_mediaType)
Swagger.exec(_ctx)
end
function deleteAppsV1beta1NamespacedStatefulSet(_api::AppsV1beta1Api, response_stream::Channel, name::String, namespace::String; pretty=nothing, body=nothing, dryRun=nothing, gracePeriodSeconds=nothing, orphanDependents=nothing, propagationPolicy=nothing, _mediaType=nothing)
_ctx = _swaggerinternal_deleteAppsV1beta1NamespacedStatefulSet(_api, name, namespace; pretty=pretty, body=body, dryRun=dryRun, gracePeriodSeconds=gracePeriodSeconds, orphanDependents=orphanDependents, propagationPolicy=propagationPolicy, _mediaType=_mediaType)
Swagger.exec(_ctx, response_stream)
end
function _swaggerinternal_getAppsV1beta1APIResources(_api::AppsV1beta1Api; _mediaType=nothing)
_ctx = Swagger.Ctx(_api.client, "GET", IoK8sApimachineryPkgApisMetaV1APIResourceList, "/apis/apps/v1beta1/", ["BearerToken"])
Swagger.set_header_accept(_ctx, ["application/json", "application/yaml", "application/vnd.kubernetes.protobuf"])
Swagger.set_header_content_type(_ctx, (_mediaType === nothing) ? ["application/json", "application/yaml", "application/vnd.kubernetes.protobuf"] : [_mediaType])
return _ctx
end
"""
get available resources
Return: IoK8sApimachineryPkgApisMetaV1APIResourceList
"""
function getAppsV1beta1APIResources(_api::AppsV1beta1Api; _mediaType=nothing)
_ctx = _swaggerinternal_getAppsV1beta1APIResources(_api; _mediaType=_mediaType)
Swagger.exec(_ctx)
end
function getAppsV1beta1APIResources(_api::AppsV1beta1Api, response_stream::Channel; _mediaType=nothing)
_ctx = _swaggerinternal_getAppsV1beta1APIResources(_api; _mediaType=_mediaType)
Swagger.exec(_ctx, response_stream)
end
function _swaggerinternal_listAppsV1beta1ControllerRevisionForAllNamespaces(_api::AppsV1beta1Api; allowWatchBookmarks=nothing, __continue__=nothing, fieldSelector=nothing, labelSelector=nothing, limit=nothing, pretty=nothing, resourceVersion=nothing, timeoutSeconds=nothing, watch=nothing, _mediaType=nothing)
_ctx = Swagger.Ctx(_api.client, "GET", IoK8sApiAppsV1beta1ControllerRevisionList, "/apis/apps/v1beta1/controllerrevisions", ["BearerToken"])
Swagger.set_param(_ctx.query, "allowWatchBookmarks", allowWatchBookmarks) # type Bool
Swagger.set_param(_ctx.query, "continue", __continue__) # type String
Swagger.set_param(_ctx.query, "fieldSelector", fieldSelector) # type String
Swagger.set_param(_ctx.query, "labelSelector", labelSelector) # type String
Swagger.set_param(_ctx.query, "limit", limit) # type Int32
Swagger.set_param(_ctx.query, "pretty", pretty) # type String
Swagger.set_param(_ctx.query, "resourceVersion", resourceVersion) # type String
Swagger.set_param(_ctx.query, "timeoutSeconds", timeoutSeconds) # type Int32
Swagger.set_param(_ctx.query, "watch", watch) # type Bool
Swagger.set_header_accept(_ctx, ["application/json", "application/yaml", "application/vnd.kubernetes.protobuf", "application/json;stream=watch", "application/vnd.kubernetes.protobuf;stream=watch"])
Swagger.set_header_content_type(_ctx, (_mediaType === nothing) ? ["*/*"] : [_mediaType])
return _ctx
end
"""
list or watch objects of kind ControllerRevision
Param: allowWatchBookmarks::Bool
Param: __continue__::String
Param: fieldSelector::String
Param: labelSelector::String
Param: limit::Int32
Param: pretty::String
Param: resourceVersion::String
Param: timeoutSeconds::Int32
Param: watch::Bool
Return: IoK8sApiAppsV1beta1ControllerRevisionList
"""
function listAppsV1beta1ControllerRevisionForAllNamespaces(_api::AppsV1beta1Api; allowWatchBookmarks=nothing, __continue__=nothing, fieldSelector=nothing, labelSelector=nothing, limit=nothing, pretty=nothing, resourceVersion=nothing, timeoutSeconds=nothing, watch=nothing, _mediaType=nothing)
_ctx = _swaggerinternal_listAppsV1beta1ControllerRevisionForAllNamespaces(_api; allowWatchBookmarks=allowWatchBookmarks, __continue__=__continue__, fieldSelector=fieldSelector, labelSelector=labelSelector, limit=limit, pretty=pretty, resourceVersion=resourceVersion, timeoutSeconds=timeoutSeconds, watch=watch, _mediaType=_mediaType)
Swagger.exec(_ctx)
end
function listAppsV1beta1ControllerRevisionForAllNamespaces(_api::AppsV1beta1Api, response_stream::Channel; allowWatchBookmarks=nothing, __continue__=nothing, fieldSelector=nothing, labelSelector=nothing, limit=nothing, pretty=nothing, resourceVersion=nothing, timeoutSeconds=nothing, watch=nothing, _mediaType=nothing)
_ctx = _swaggerinternal_listAppsV1beta1ControllerRevisionForAllNamespaces(_api; allowWatchBookmarks=allowWatchBookmarks, __continue__=__continue__, fieldSelector=fieldSelector, labelSelector=labelSelector, limit=limit, pretty=pretty, resourceVersion=resourceVersion, timeoutSeconds=timeoutSeconds, watch=watch, _mediaType=_mediaType)
Swagger.exec(_ctx, response_stream)
end
function _swaggerinternal_listAppsV1beta1DeploymentForAllNamespaces(_api::AppsV1beta1Api; allowWatchBookmarks=nothing, __continue__=nothing, fieldSelector=nothing, labelSelector=nothing, limit=nothing, pretty=nothing, resourceVersion=nothing, timeoutSeconds=nothing, watch=nothing, _mediaType=nothing)
_ctx = Swagger.Ctx(_api.client, "GET", IoK8sApiAppsV1beta1DeploymentList, "/apis/apps/v1beta1/deployments", ["BearerToken"])
Swagger.set_param(_ctx.query, "allowWatchBookmarks", allowWatchBookmarks) # type Bool
Swagger.set_param(_ctx.query, "continue", __continue__) # type String
Swagger.set_param(_ctx.query, "fieldSelector", fieldSelector) # type String
Swagger.set_param(_ctx.query, "labelSelector", labelSelector) # type String
Swagger.set_param(_ctx.query, "limit", limit) # type Int32
Swagger.set_param(_ctx.query, "pretty", pretty) # type String
Swagger.set_param(_ctx.query, "resourceVersion", resourceVersion) # type String
Swagger.set_param(_ctx.query, "timeoutSeconds", timeoutSeconds) # type Int32
Swagger.set_param(_ctx.query, "watch", watch) # type Bool
Swagger.set_header_accept(_ctx, ["application/json", "application/yaml", "application/vnd.kubernetes.protobuf", "application/json;stream=watch", "application/vnd.kubernetes.protobuf;stream=watch"])
Swagger.set_header_content_type(_ctx, (_mediaType === nothing) ? ["*/*"] : [_mediaType])
return _ctx
end
"""
list or watch objects of kind Deployment
Param: allowWatchBookmarks::Bool
Param: __continue__::String
Param: fieldSelector::String
Param: labelSelector::String
Param: limit::Int32
Param: pretty::String
Param: resourceVersion::String
Param: timeoutSeconds::Int32
Param: watch::Bool
Return: IoK8sApiAppsV1beta1DeploymentList
"""
function listAppsV1beta1DeploymentForAllNamespaces(_api::AppsV1beta1Api; allowWatchBookmarks=nothing, __continue__=nothing, fieldSelector=nothing, labelSelector=nothing, limit=nothing, pretty=nothing, resourceVersion=nothing, timeoutSeconds=nothing, watch=nothing, _mediaType=nothing)
_ctx = _swaggerinternal_listAppsV1beta1DeploymentForAllNamespaces(_api; allowWatchBookmarks=allowWatchBookmarks, __continue__=__continue__, fieldSelector=fieldSelector, labelSelector=labelSelector, limit=limit, pretty=pretty, resourceVersion=resourceVersion, timeoutSeconds=timeoutSeconds, watch=watch, _mediaType=_mediaType)
Swagger.exec(_ctx)
end
function listAppsV1beta1DeploymentForAllNamespaces(_api::AppsV1beta1Api, response_stream::Channel; allowWatchBookmarks=nothing, __continue__=nothing, fieldSelector=nothing, labelSelector=nothing, limit=nothing, pretty=nothing, resourceVersion=nothing, timeoutSeconds=nothing, watch=nothing, _mediaType=nothing)
_ctx = _swaggerinternal_listAppsV1beta1DeploymentForAllNamespaces(_api; allowWatchBookmarks=allowWatchBookmarks, __continue__=__continue__, fieldSelector=fieldSelector, labelSelector=labelSelector, limit=limit, pretty=pretty, resourceVersion=resourceVersion, timeoutSeconds=timeoutSeconds, watch=watch, _mediaType=_mediaType)
Swagger.exec(_ctx, response_stream)
end
function _swaggerinternal_listAppsV1beta1NamespacedControllerRevision(_api::AppsV1beta1Api, namespace::String; pretty=nothing, allowWatchBookmarks=nothing, __continue__=nothing, fieldSelector=nothing, labelSelector=nothing, limit=nothing, resourceVersion=nothing, timeoutSeconds=nothing, watch=nothing, _mediaType=nothing)
_ctx = Swagger.Ctx(_api.client, "GET", IoK8sApiAppsV1beta1ControllerRevisionList, "/apis/apps/v1beta1/namespaces/{namespace}/controllerrevisions", ["BearerToken"])
Swagger.set_param(_ctx.path, "namespace", namespace) # type String
Swagger.set_param(_ctx.query, "pretty", pretty) # type String
Swagger.set_param(_ctx.query, "allowWatchBookmarks", allowWatchBookmarks) # type Bool
Swagger.set_param(_ctx.query, "continue", __continue__) # type String
Swagger.set_param(_ctx.query, "fieldSelector", fieldSelector) # type String
Swagger.set_param(_ctx.query, "labelSelector", labelSelector) # type String
Swagger.set_param(_ctx.query, "limit", limit) # type Int32
Swagger.set_param(_ctx.query, "resourceVersion", resourceVersion) # type String
Swagger.set_param(_ctx.query, "timeoutSeconds", timeoutSeconds) # type Int32
Swagger.set_param(_ctx.query, "watch", watch) # type Bool
Swagger.set_header_accept(_ctx, ["application/json", "application/yaml", "application/vnd.kubernetes.protobuf", "application/json;stream=watch", "application/vnd.kubernetes.protobuf;stream=watch"])
Swagger.set_header_content_type(_ctx, (_mediaType === nothing) ? ["*/*"] : [_mediaType])
return _ctx
end
"""
list or watch objects of kind ControllerRevision
Param: namespace::String (required)
Param: pretty::String
Param: allowWatchBookmarks::Bool
Param: __continue__::String
Param: fieldSelector::String
Param: labelSelector::String
Param: limit::Int32
Param: resourceVersion::String
Param: timeoutSeconds::Int32
Param: watch::Bool
Return: IoK8sApiAppsV1beta1ControllerRevisionList
"""
function listAppsV1beta1NamespacedControllerRevision(_api::AppsV1beta1Api, namespace::String; pretty=nothing, allowWatchBookmarks=nothing, __continue__=nothing, fieldSelector=nothing, labelSelector=nothing, limit=nothing, resourceVersion=nothing, timeoutSeconds=nothing, watch=nothing, _mediaType=nothing)
_ctx = _swaggerinternal_listAppsV1beta1NamespacedControllerRevision(_api, namespace; pretty=pretty, allowWatchBookmarks=allowWatchBookmarks, __continue__=__continue__, fieldSelector=fieldSelector, labelSelector=labelSelector, limit=limit, resourceVersion=resourceVersion, timeoutSeconds=timeoutSeconds, watch=watch, _mediaType=_mediaType)
Swagger.exec(_ctx)
end
function listAppsV1beta1NamespacedControllerRevision(_api::AppsV1beta1Api, response_stream::Channel, namespace::String; pretty=nothing, allowWatchBookmarks=nothing, __continue__=nothing, fieldSelector=nothing, labelSelector=nothing, limit=nothing, resourceVersion=nothing, timeoutSeconds=nothing, watch=nothing, _mediaType=nothing)
_ctx = _swaggerinternal_listAppsV1beta1NamespacedControllerRevision(_api, namespace; pretty=pretty, allowWatchBookmarks=allowWatchBookmarks, __continue__=__continue__, fieldSelector=fieldSelector, labelSelector=labelSelector, limit=limit, resourceVersion=resourceVersion, timeoutSeconds=timeoutSeconds, watch=watch, _mediaType=_mediaType)
Swagger.exec(_ctx, response_stream)
end
function _swaggerinternal_listAppsV1beta1NamespacedDeployment(_api::AppsV1beta1Api, namespace::String; pretty=nothing, allowWatchBookmarks=nothing, __continue__=nothing, fieldSelector=nothing, labelSelector=nothing, limit=nothing, resourceVersion=nothing, timeoutSeconds=nothing, watch=nothing, _mediaType=nothing)
_ctx = Swagger.Ctx(_api.client, "GET", IoK8sApiAppsV1beta1DeploymentList, "/apis/apps/v1beta1/namespaces/{namespace}/deployments", ["BearerToken"])
Swagger.set_param(_ctx.path, "namespace", namespace) # type String
Swagger.set_param(_ctx.query, "pretty", pretty) # type String
Swagger.set_param(_ctx.query, "allowWatchBookmarks", allowWatchBookmarks) # type Bool
Swagger.set_param(_ctx.query, "continue", __continue__) # type String
Swagger.set_param(_ctx.query, "fieldSelector", fieldSelector) # type String
Swagger.set_param(_ctx.query, "labelSelector", labelSelector) # type String
Swagger.set_param(_ctx.query, "limit", limit) # type Int32
Swagger.set_param(_ctx.query, "resourceVersion", resourceVersion) # type String
Swagger.set_param(_ctx.query, "timeoutSeconds", timeoutSeconds) # type Int32
Swagger.set_param(_ctx.query, "watch", watch) # type Bool
Swagger.set_header_accept(_ctx, ["application/json", "application/yaml", "application/vnd.kubernetes.protobuf", "application/json;stream=watch", "application/vnd.kubernetes.protobuf;stream=watch"])
Swagger.set_header_content_type(_ctx, (_mediaType === nothing) ? ["*/*"] : [_mediaType])
return _ctx
end
"""
list or watch objects of kind Deployment
Param: namespace::String (required)
Param: pretty::String
Param: allowWatchBookmarks::Bool
Param: __continue__::String
Param: fieldSelector::String
Param: labelSelector::String
Param: limit::Int32
Param: resourceVersion::String
Param: timeoutSeconds::Int32
Param: watch::Bool
Return: IoK8sApiAppsV1beta1DeploymentList
"""
function listAppsV1beta1NamespacedDeployment(_api::AppsV1beta1Api, namespace::String; pretty=nothing, allowWatchBookmarks=nothing, __continue__=nothing, fieldSelector=nothing, labelSelector=nothing, limit=nothing, resourceVersion=nothing, timeoutSeconds=nothing, watch=nothing, _mediaType=nothing)
_ctx = _swaggerinternal_listAppsV1beta1NamespacedDeployment(_api, namespace; pretty=pretty, allowWatchBookmarks=allowWatchBookmarks, __continue__=__continue__, fieldSelector=fieldSelector, labelSelector=labelSelector, limit=limit, resourceVersion=resourceVersion, timeoutSeconds=timeoutSeconds, watch=watch, _mediaType=_mediaType)
Swagger.exec(_ctx)
end
function listAppsV1beta1NamespacedDeployment(_api::AppsV1beta1Api, response_stream::Channel, namespace::String; pretty=nothing, allowWatchBookmarks=nothing, __continue__=nothing, fieldSelector=nothing, labelSelector=nothing, limit=nothing, resourceVersion=nothing, timeoutSeconds=nothing, watch=nothing, _mediaType=nothing)
_ctx = _swaggerinternal_listAppsV1beta1NamespacedDeployment(_api, namespace; pretty=pretty, allowWatchBookmarks=allowWatchBookmarks, __continue__=__continue__, fieldSelector=fieldSelector, labelSelector=labelSelector, limit=limit, resourceVersion=resourceVersion, timeoutSeconds=timeoutSeconds, watch=watch, _mediaType=_mediaType)
Swagger.exec(_ctx, response_stream)
end
function _swaggerinternal_listAppsV1beta1NamespacedStatefulSet(_api::AppsV1beta1Api, namespace::String; pretty=nothing, allowWatchBookmarks=nothing, __continue__=nothing, fieldSelector=nothing, labelSelector=nothing, limit=nothing, resourceVersion=nothing, timeoutSeconds=nothing, watch=nothing, _mediaType=nothing)
_ctx = Swagger.Ctx(_api.client, "GET", IoK8sApiAppsV1beta1StatefulSetList, "/apis/apps/v1beta1/namespaces/{namespace}/statefulsets", ["BearerToken"])
Swagger.set_param(_ctx.path, "namespace", namespace) # type String
Swagger.set_param(_ctx.query, "pretty", pretty) # type String
Swagger.set_param(_ctx.query, "allowWatchBookmarks", allowWatchBookmarks) # type Bool
Swagger.set_param(_ctx.query, "continue", __continue__) # type String
Swagger.set_param(_ctx.query, "fieldSelector", fieldSelector) # type String
Swagger.set_param(_ctx.query, "labelSelector", labelSelector) # type String
Swagger.set_param(_ctx.query, "limit", limit) # type Int32
Swagger.set_param(_ctx.query, "resourceVersion", resourceVersion) # type String
Swagger.set_param(_ctx.query, "timeoutSeconds", timeoutSeconds) # type Int32
Swagger.set_param(_ctx.query, "watch", watch) # type Bool
Swagger.set_header_accept(_ctx, ["application/json", "application/yaml", "application/vnd.kubernetes.protobuf", "application/json;stream=watch", "application/vnd.kubernetes.protobuf;stream=watch"])
Swagger.set_header_content_type(_ctx, (_mediaType === nothing) ? ["*/*"] : [_mediaType])
return _ctx
end
"""
list or watch objects of kind StatefulSet
Param: namespace::String (required)
Param: pretty::String
Param: allowWatchBookmarks::Bool
Param: __continue__::String
Param: fieldSelector::String
Param: labelSelector::String
Param: limit::Int32
Param: resourceVersion::String
Param: timeoutSeconds::Int32
Param: watch::Bool
Return: IoK8sApiAppsV1beta1StatefulSetList
"""
function listAppsV1beta1NamespacedStatefulSet(_api::AppsV1beta1Api, namespace::String; pretty=nothing, allowWatchBookmarks=nothing, __continue__=nothing, fieldSelector=nothing, labelSelector=nothing, limit=nothing, resourceVersion=nothing, timeoutSeconds=nothing, watch=nothing, _mediaType=nothing)
_ctx = _swaggerinternal_listAppsV1beta1NamespacedStatefulSet(_api, namespace; pretty=pretty, allowWatchBookmarks=allowWatchBookmarks, __continue__=__continue__, fieldSelector=fieldSelector, labelSelector=labelSelector, limit=limit, resourceVersion=resourceVersion, timeoutSeconds=timeoutSeconds, watch=watch, _mediaType=_mediaType)
Swagger.exec(_ctx)
end
function listAppsV1beta1NamespacedStatefulSet(_api::AppsV1beta1Api, response_stream::Channel, namespace::String; pretty=nothing, allowWatchBookmarks=nothing, __continue__=nothing, fieldSelector=nothing, labelSelector=nothing, limit=nothing, resourceVersion=nothing, timeoutSeconds=nothing, watch=nothing, _mediaType=nothing)
_ctx = _swaggerinternal_listAppsV1beta1NamespacedStatefulSet(_api, namespace; pretty=pretty, allowWatchBookmarks=allowWatchBookmarks, __continue__=__continue__, fieldSelector=fieldSelector, labelSelector=labelSelector, limit=limit, resourceVersion=resourceVersion, timeoutSeconds=timeoutSeconds, watch=watch, _mediaType=_mediaType)
Swagger.exec(_ctx, response_stream)
end
function _swaggerinternal_listAppsV1beta1StatefulSetForAllNamespaces(_api::AppsV1beta1Api; allowWatchBookmarks=nothing, __continue__=nothing, fieldSelector=nothing, labelSelector=nothing, limit=nothing, pretty=nothing, resourceVersion=nothing, timeoutSeconds=nothing, watch=nothing, _mediaType=nothing)
_ctx = Swagger.Ctx(_api.client, "GET", IoK8sApiAppsV1beta1StatefulSetList, "/apis/apps/v1beta1/statefulsets", ["BearerToken"])
Swagger.set_param(_ctx.query, "allowWatchBookmarks", allowWatchBookmarks) # type Bool
Swagger.set_param(_ctx.query, "continue", __continue__) # type String
Swagger.set_param(_ctx.query, "fieldSelector", fieldSelector) # type String
Swagger.set_param(_ctx.query, "labelSelector", labelSelector) # type String
Swagger.set_param(_ctx.query, "limit", limit) # type Int32
Swagger.set_param(_ctx.query, "pretty", pretty) # type String
Swagger.set_param(_ctx.query, "resourceVersion", resourceVersion) # type String
Swagger.set_param(_ctx.query, "timeoutSeconds", timeoutSeconds) # type Int32
Swagger.set_param(_ctx.query, "watch", watch) # type Bool
Swagger.set_header_accept(_ctx, ["application/json", "application/yaml", "application/vnd.kubernetes.protobuf", "application/json;stream=watch", "application/vnd.kubernetes.protobuf;stream=watch"])
Swagger.set_header_content_type(_ctx, (_mediaType === nothing) ? ["*/*"] : [_mediaType])
return _ctx
end
"""
list or watch objects of kind StatefulSet
Param: allowWatchBookmarks::Bool
Param: __continue__::String
Param: fieldSelector::String
Param: labelSelector::String
Param: limit::Int32
Param: pretty::String
Param: resourceVersion::String
Param: timeoutSeconds::Int32
Param: watch::Bool
Return: IoK8sApiAppsV1beta1StatefulSetList
"""
function listAppsV1beta1StatefulSetForAllNamespaces(_api::AppsV1beta1Api; allowWatchBookmarks=nothing, __continue__=nothing, fieldSelector=nothing, labelSelector=nothing, limit=nothing, pretty=nothing, resourceVersion=nothing, timeoutSeconds=nothing, watch=nothing, _mediaType=nothing)
_ctx = _swaggerinternal_listAppsV1beta1StatefulSetForAllNamespaces(_api; allowWatchBookmarks=allowWatchBookmarks, __continue__=__continue__, fieldSelector=fieldSelector, labelSelector=labelSelector, limit=limit, pretty=pretty, resourceVersion=resourceVersion, timeoutSeconds=timeoutSeconds, watch=watch, _mediaType=_mediaType)
Swagger.exec(_ctx)
end
function listAppsV1beta1StatefulSetForAllNamespaces(_api::AppsV1beta1Api, response_stream::Channel; allowWatchBookmarks=nothing, __continue__=nothing, fieldSelector=nothing, labelSelector=nothing, limit=nothing, pretty=nothing, resourceVersion=nothing, timeoutSeconds=nothing, watch=nothing, _mediaType=nothing)
_ctx = _swaggerinternal_listAppsV1beta1StatefulSetForAllNamespaces(_api; allowWatchBookmarks=allowWatchBookmarks, __continue__=__continue__, fieldSelector=fieldSelector, labelSelector=labelSelector, limit=limit, pretty=pretty, resourceVersion=resourceVersion, timeoutSeconds=timeoutSeconds, watch=watch, _mediaType=_mediaType)
Swagger.exec(_ctx, response_stream)
end
function _swaggerinternal_patchAppsV1beta1NamespacedControllerRevision(_api::AppsV1beta1Api, name::String, namespace::String, body; pretty=nothing, dryRun=nothing, fieldManager=nothing, force=nothing, _mediaType=nothing)
_ctx = Swagger.Ctx(_api.client, "PATCH", IoK8sApiAppsV1beta1ControllerRevision, "/apis/apps/v1beta1/namespaces/{namespace}/controllerrevisions/{name}", ["BearerToken"], body)
Swagger.set_param(_ctx.path, "name", name) # type String
Swagger.set_param(_ctx.path, "namespace", namespace) # type String
Swagger.set_param(_ctx.query, "pretty", pretty) # type String
Swagger.set_param(_ctx.query, "dryRun", dryRun) # type String
Swagger.set_param(_ctx.query, "fieldManager", fieldManager) # type String
Swagger.set_param(_ctx.query, "force", force) # type Bool
Swagger.set_header_accept(_ctx, ["application/json", "application/yaml", "application/vnd.kubernetes.protobuf"])
Swagger.set_header_content_type(_ctx, (_mediaType === nothing) ? ["application/json-patch+json", "application/merge-patch+json", "application/strategic-merge-patch+json", "application/apply-patch+yaml"] : [_mediaType])
return _ctx
end
"""
partially update the specified ControllerRevision
Param: name::String (required)
Param: namespace::String (required)
Param: body::IoK8sApimachineryPkgApisMetaV1Patch (required)
Param: pretty::String
Param: dryRun::String
Param: fieldManager::String
Param: force::Bool
Return: IoK8sApiAppsV1beta1ControllerRevision
"""
function patchAppsV1beta1NamespacedControllerRevision(_api::AppsV1beta1Api, name::String, namespace::String, body; pretty=nothing, dryRun=nothing, fieldManager=nothing, force=nothing, _mediaType=nothing)
_ctx = _swaggerinternal_patchAppsV1beta1NamespacedControllerRevision(_api, name, namespace, body; pretty=pretty, dryRun=dryRun, fieldManager=fieldManager, force=force, _mediaType=_mediaType)
Swagger.exec(_ctx)
end
function patchAppsV1beta1NamespacedControllerRevision(_api::AppsV1beta1Api, response_stream::Channel, name::String, namespace::String, body; pretty=nothing, dryRun=nothing, fieldManager=nothing, force=nothing, _mediaType=nothing)
_ctx = _swaggerinternal_patchAppsV1beta1NamespacedControllerRevision(_api, name, namespace, body; pretty=pretty, dryRun=dryRun, fieldManager=fieldManager, force=force, _mediaType=_mediaType)
Swagger.exec(_ctx, response_stream)
end
function _swaggerinternal_patchAppsV1beta1NamespacedDeployment(_api::AppsV1beta1Api, name::String, namespace::String, body; pretty=nothing, dryRun=nothing, fieldManager=nothing, force=nothing, _mediaType=nothing)
_ctx = Swagger.Ctx(_api.client, "PATCH", IoK8sApiAppsV1beta1Deployment, "/apis/apps/v1beta1/namespaces/{namespace}/deployments/{name}", ["BearerToken"], body)
Swagger.set_param(_ctx.path, "name", name) # type String
Swagger.set_param(_ctx.path, "namespace", namespace) # type String
Swagger.set_param(_ctx.query, "pretty", pretty) # type String
Swagger.set_param(_ctx.query, "dryRun", dryRun) # type String
Swagger.set_param(_ctx.query, "fieldManager", fieldManager) # type String
Swagger.set_param(_ctx.query, "force", force) # type Bool
Swagger.set_header_accept(_ctx, ["application/json", "application/yaml", "application/vnd.kubernetes.protobuf"])
Swagger.set_header_content_type(_ctx, (_mediaType === nothing) ? ["application/json-patch+json", "application/merge-patch+json", "application/strategic-merge-patch+json", "application/apply-patch+yaml"] : [_mediaType])
return _ctx
end
"""
partially update the specified Deployment
Param: name::String (required)
Param: namespace::String (required)
Param: body::IoK8sApimachineryPkgApisMetaV1Patch (required)
Param: pretty::String
Param: dryRun::String
Param: fieldManager::String
Param: force::Bool
Return: IoK8sApiAppsV1beta1Deployment
"""
function patchAppsV1beta1NamespacedDeployment(_api::AppsV1beta1Api, name::String, namespace::String, body; pretty=nothing, dryRun=nothing, fieldManager=nothing, force=nothing, _mediaType=nothing)
_ctx = _swaggerinternal_patchAppsV1beta1NamespacedDeployment(_api, name, namespace, body; pretty=pretty, dryRun=dryRun, fieldManager=fieldManager, force=force, _mediaType=_mediaType)
Swagger.exec(_ctx)
end
function patchAppsV1beta1NamespacedDeployment(_api::AppsV1beta1Api, response_stream::Channel, name::String, namespace::String, body; pretty=nothing, dryRun=nothing, fieldManager=nothing, force=nothing, _mediaType=nothing)
_ctx = _swaggerinternal_patchAppsV1beta1NamespacedDeployment(_api, name, namespace, body; pretty=pretty, dryRun=dryRun, fieldManager=fieldManager, force=force, _mediaType=_mediaType)
Swagger.exec(_ctx, response_stream)
end
function _swaggerinternal_patchAppsV1beta1NamespacedDeploymentScale(_api::AppsV1beta1Api, name::String, namespace::String, body; pretty=nothing, dryRun=nothing, fieldManager=nothing, force=nothing, _mediaType=nothing)
_ctx = Swagger.Ctx(_api.client, "PATCH", IoK8sApiAppsV1beta1Scale, "/apis/apps/v1beta1/namespaces/{namespace}/deployments/{name}/scale", ["BearerToken"], body)
Swagger.set_param(_ctx.path, "name", name) # type String
Swagger.set_param(_ctx.path, "namespace", namespace) # type String
Swagger.set_param(_ctx.query, "pretty", pretty) # type String
Swagger.set_param(_ctx.query, "dryRun", dryRun) # type String
Swagger.set_param(_ctx.query, "fieldManager", fieldManager) # type String
Swagger.set_param(_ctx.query, "force", force) # type Bool
Swagger.set_header_accept(_ctx, ["application/json", "application/yaml", "application/vnd.kubernetes.protobuf"])
Swagger.set_header_content_type(_ctx, (_mediaType === nothing) ? ["application/json-patch+json", "application/merge-patch+json", "application/strategic-merge-patch+json", "application/apply-patch+yaml"] : [_mediaType])
return _ctx
end
"""
partially update scale of the specified Deployment
Param: name::String (required)
Param: namespace::String (required)
Param: body::IoK8sApimachineryPkgApisMetaV1Patch (required)
Param: pretty::String
Param: dryRun::String
Param: fieldManager::String
Param: force::Bool
Return: IoK8sApiAppsV1beta1Scale
"""
function patchAppsV1beta1NamespacedDeploymentScale(_api::AppsV1beta1Api, name::String, namespace::String, body; pretty=nothing, dryRun=nothing, fieldManager=nothing, force=nothing, _mediaType=nothing)
_ctx = _swaggerinternal_patchAppsV1beta1NamespacedDeploymentScale(_api, name, namespace, body; pretty=pretty, dryRun=dryRun, fieldManager=fieldManager, force=force, _mediaType=_mediaType)
Swagger.exec(_ctx)
end
function patchAppsV1beta1NamespacedDeploymentScale(_api::AppsV1beta1Api, response_stream::Channel, name::String, namespace::String, body; pretty=nothing, dryRun=nothing, fieldManager=nothing, force=nothing, _mediaType=nothing)
_ctx = _swaggerinternal_patchAppsV1beta1NamespacedDeploymentScale(_api, name, namespace, body; pretty=pretty, dryRun=dryRun, fieldManager=fieldManager, force=force, _mediaType=_mediaType)
Swagger.exec(_ctx, response_stream)
end
function _swaggerinternal_patchAppsV1beta1NamespacedDeploymentStatus(_api::AppsV1beta1Api, name::String, namespace::String, body; pretty=nothing, dryRun=nothing, fieldManager=nothing, force=nothing, _mediaType=nothing)
_ctx = Swagger.Ctx(_api.client, "PATCH", IoK8sApiAppsV1beta1Deployment, "/apis/apps/v1beta1/namespaces/{namespace}/deployments/{name}/status", ["BearerToken"], body)
Swagger.set_param(_ctx.path, "name", name) # type String
Swagger.set_param(_ctx.path, "namespace", namespace) # type String
Swagger.set_param(_ctx.query, "pretty", pretty) # type String
Swagger.set_param(_ctx.query, "dryRun", dryRun) # type String
Swagger.set_param(_ctx.query, "fieldManager", fieldManager) # type String
Swagger.set_param(_ctx.query, "force", force) # type Bool
Swagger.set_header_accept(_ctx, ["application/json", "application/yaml", "application/vnd.kubernetes.protobuf"])
Swagger.set_header_content_type(_ctx, (_mediaType === nothing) ? ["application/json-patch+json", "application/merge-patch+json", "application/strategic-merge-patch+json", "application/apply-patch+yaml"] : [_mediaType])
return _ctx
end
"""
partially update status of the specified Deployment
Param: name::String (required)
Param: namespace::String (required)
Param: body::IoK8sApimachineryPkgApisMetaV1Patch (required)
Param: pretty::String
Param: dryRun::String
Param: fieldManager::String
Param: force::Bool
Return: IoK8sApiAppsV1beta1Deployment
"""
function patchAppsV1beta1NamespacedDeploymentStatus(_api::AppsV1beta1Api, name::String, namespace::String, body; pretty=nothing, dryRun=nothing, fieldManager=nothing, force=nothing, _mediaType=nothing)
_ctx = _swaggerinternal_patchAppsV1beta1NamespacedDeploymentStatus(_api, name, namespace, body; pretty=pretty, dryRun=dryRun, fieldManager=fieldManager, force=force, _mediaType=_mediaType)
Swagger.exec(_ctx)
end
function patchAppsV1beta1NamespacedDeploymentStatus(_api::AppsV1beta1Api, response_stream::Channel, name::String, namespace::String, body; pretty=nothing, dryRun=nothing, fieldManager=nothing, force=nothing, _mediaType=nothing)
_ctx = _swaggerinternal_patchAppsV1beta1NamespacedDeploymentStatus(_api, name, namespace, body; pretty=pretty, dryRun=dryRun, fieldManager=fieldManager, force=force, _mediaType=_mediaType)
Swagger.exec(_ctx, response_stream)
end
function _swaggerinternal_patchAppsV1beta1NamespacedStatefulSet(_api::AppsV1beta1Api, name::String, namespace::String, body; pretty=nothing, dryRun=nothing, fieldManager=nothing, force=nothing, _mediaType=nothing)
_ctx = Swagger.Ctx(_api.client, "PATCH", IoK8sApiAppsV1beta1StatefulSet, "/apis/apps/v1beta1/namespaces/{namespace}/statefulsets/{name}", ["BearerToken"], body)
Swagger.set_param(_ctx.path, "name", name) # type String
Swagger.set_param(_ctx.path, "namespace", namespace) # type String
Swagger.set_param(_ctx.query, "pretty", pretty) # type String
Swagger.set_param(_ctx.query, "dryRun", dryRun) # type String
Swagger.set_param(_ctx.query, "fieldManager", fieldManager) # type String
Swagger.set_param(_ctx.query, "force", force) # type Bool
Swagger.set_header_accept(_ctx, ["application/json", "application/yaml", "application/vnd.kubernetes.protobuf"])
Swagger.set_header_content_type(_ctx, (_mediaType === nothing) ? ["application/json-patch+json", "application/merge-patch+json", "application/strategic-merge-patch+json", "application/apply-patch+yaml"] : [_mediaType])
return _ctx
end
"""
partially update the specified StatefulSet
Param: name::String (required)
Param: namespace::String (required)
Param: body::IoK8sApimachineryPkgApisMetaV1Patch (required)
Param: pretty::String
Param: dryRun::String
Param: fieldManager::String
Param: force::Bool
Return: IoK8sApiAppsV1beta1StatefulSet
"""
function patchAppsV1beta1NamespacedStatefulSet(_api::AppsV1beta1Api, name::String, namespace::String, body; pretty=nothing, dryRun=nothing, fieldManager=nothing, force=nothing, _mediaType=nothing)
_ctx = _swaggerinternal_patchAppsV1beta1NamespacedStatefulSet(_api, name, namespace, body; pretty=pretty, dryRun=dryRun, fieldManager=fieldManager, force=force, _mediaType=_mediaType)
Swagger.exec(_ctx)
end
function patchAppsV1beta1NamespacedStatefulSet(_api::AppsV1beta1Api, response_stream::Channel, name::String, namespace::String, body; pretty=nothing, dryRun=nothing, fieldManager=nothing, force=nothing, _mediaType=nothing)
_ctx = _swaggerinternal_patchAppsV1beta1NamespacedStatefulSet(_api, name, namespace, body; pretty=pretty, dryRun=dryRun, fieldManager=fieldManager, force=force, _mediaType=_mediaType)
Swagger.exec(_ctx, response_stream)
end
function _swaggerinternal_patchAppsV1beta1NamespacedStatefulSetScale(_api::AppsV1beta1Api, name::String, namespace::String, body; pretty=nothing, dryRun=nothing, fieldManager=nothing, force=nothing, _mediaType=nothing)
_ctx = Swagger.Ctx(_api.client, "PATCH", IoK8sApiAppsV1beta1Scale, "/apis/apps/v1beta1/namespaces/{namespace}/statefulsets/{name}/scale", ["BearerToken"], body)
Swagger.set_param(_ctx.path, "name", name) # type String
Swagger.set_param(_ctx.path, "namespace", namespace) # type String
Swagger.set_param(_ctx.query, "pretty", pretty) # type String
Swagger.set_param(_ctx.query, "dryRun", dryRun) # type String
Swagger.set_param(_ctx.query, "fieldManager", fieldManager) # type String
Swagger.set_param(_ctx.query, "force", force) # type Bool
Swagger.set_header_accept(_ctx, ["application/json", "application/yaml", "application/vnd.kubernetes.protobuf"])
Swagger.set_header_content_type(_ctx, (_mediaType === nothing) ? ["application/json-patch+json", "application/merge-patch+json", "application/strategic-merge-patch+json", "application/apply-patch+yaml"] : [_mediaType])
return _ctx
end
"""
partially update scale of the specified StatefulSet
Param: name::String (required)
Param: namespace::String (required)
Param: body::IoK8sApimachineryPkgApisMetaV1Patch (required)
Param: pretty::String
Param: dryRun::String
Param: fieldManager::String
Param: force::Bool
Return: IoK8sApiAppsV1beta1Scale
"""
function patchAppsV1beta1NamespacedStatefulSetScale(_api::AppsV1beta1Api, name::String, namespace::String, body; pretty=nothing, dryRun=nothing, fieldManager=nothing, force=nothing, _mediaType=nothing)
_ctx = _swaggerinternal_patchAppsV1beta1NamespacedStatefulSetScale(_api, name, namespace, body; pretty=pretty, dryRun=dryRun, fieldManager=fieldManager, force=force, _mediaType=_mediaType)
Swagger.exec(_ctx)
end
function patchAppsV1beta1NamespacedStatefulSetScale(_api::AppsV1beta1Api, response_stream::Channel, name::String, namespace::String, body; pretty=nothing, dryRun=nothing, fieldManager=nothing, force=nothing, _mediaType=nothing)
_ctx = _swaggerinternal_patchAppsV1beta1NamespacedStatefulSetScale(_api, name, namespace, body; pretty=pretty, dryRun=dryRun, fieldManager=fieldManager, force=force, _mediaType=_mediaType)
Swagger.exec(_ctx, response_stream)
end
function _swaggerinternal_patchAppsV1beta1NamespacedStatefulSetStatus(_api::AppsV1beta1Api, name::String, namespace::String, body; pretty=nothing, dryRun=nothing, fieldManager=nothing, force=nothing, _mediaType=nothing)
_ctx = Swagger.Ctx(_api.client, "PATCH", IoK8sApiAppsV1beta1StatefulSet, "/apis/apps/v1beta1/namespaces/{namespace}/statefulsets/{name}/status", ["BearerToken"], body)
Swagger.set_param(_ctx.path, "name", name) # type String
Swagger.set_param(_ctx.path, "namespace", namespace) # type String
Swagger.set_param(_ctx.query, "pretty", pretty) # type String
Swagger.set_param(_ctx.query, "dryRun", dryRun) # type String
Swagger.set_param(_ctx.query, "fieldManager", fieldManager) # type String
Swagger.set_param(_ctx.query, "force", force) # type Bool
Swagger.set_header_accept(_ctx, ["application/json", "application/yaml", "application/vnd.kubernetes.protobuf"])
Swagger.set_header_content_type(_ctx, (_mediaType === nothing) ? ["application/json-patch+json", "application/merge-patch+json", "application/strategic-merge-patch+json", "application/apply-patch+yaml"] : [_mediaType])
return _ctx
end
"""
partially update status of the specified StatefulSet
Param: name::String (required)
Param: namespace::String (required)
Param: body::IoK8sApimachineryPkgApisMetaV1Patch (required)
Param: pretty::String
Param: dryRun::String
Param: fieldManager::String
Param: force::Bool
Return: IoK8sApiAppsV1beta1StatefulSet
"""
function patchAppsV1beta1NamespacedStatefulSetStatus(_api::AppsV1beta1Api, name::String, namespace::String, body; pretty=nothing, dryRun=nothing, fieldManager=nothing, force=nothing, _mediaType=nothing)
_ctx = _swaggerinternal_patchAppsV1beta1NamespacedStatefulSetStatus(_api, name, namespace, body; pretty=pretty, dryRun=dryRun, fieldManager=fieldManager, force=force, _mediaType=_mediaType)
Swagger.exec(_ctx)
end
function patchAppsV1beta1NamespacedStatefulSetStatus(_api::AppsV1beta1Api, response_stream::Channel, name::String, namespace::String, body; pretty=nothing, dryRun=nothing, fieldManager=nothing, force=nothing, _mediaType=nothing)
_ctx = _swaggerinternal_patchAppsV1beta1NamespacedStatefulSetStatus(_api, name, namespace, body; pretty=pretty, dryRun=dryRun, fieldManager=fieldManager, force=force, _mediaType=_mediaType)
Swagger.exec(_ctx, response_stream)
end
function _swaggerinternal_readAppsV1beta1NamespacedControllerRevision(_api::AppsV1beta1Api, name::String, namespace::String; pretty=nothing, exact=nothing, __export__=nothing, _mediaType=nothing)
_ctx = Swagger.Ctx(_api.client, "GET", IoK8sApiAppsV1beta1ControllerRevision, "/apis/apps/v1beta1/namespaces/{namespace}/controllerrevisions/{name}", ["BearerToken"])
Swagger.set_param(_ctx.path, "name", name) # type String
Swagger.set_param(_ctx.path, "namespace", namespace) # type String
Swagger.set_param(_ctx.query, "pretty", pretty) # type String
Swagger.set_param(_ctx.query, "exact", exact) # type Bool
Swagger.set_param(_ctx.query, "export", __export__) # type Bool
Swagger.set_header_accept(_ctx, ["application/json", "application/yaml", "application/vnd.kubernetes.protobuf"])
Swagger.set_header_content_type(_ctx, (_mediaType === nothing) ? ["*/*"] : [_mediaType])
return _ctx
end
"""
read the specified ControllerRevision
Param: name::String (required)
Param: namespace::String (required)
Param: pretty::String
Param: exact::Bool
Param: __export__::Bool
Return: IoK8sApiAppsV1beta1ControllerRevision
"""
function readAppsV1beta1NamespacedControllerRevision(_api::AppsV1beta1Api, name::String, namespace::String; pretty=nothing, exact=nothing, __export__=nothing, _mediaType=nothing)
_ctx = _swaggerinternal_readAppsV1beta1NamespacedControllerRevision(_api, name, namespace; pretty=pretty, exact=exact, __export__=__export__, _mediaType=_mediaType)
Swagger.exec(_ctx)
end
function readAppsV1beta1NamespacedControllerRevision(_api::AppsV1beta1Api, response_stream::Channel, name::String, namespace::String; pretty=nothing, exact=nothing, __export__=nothing, _mediaType=nothing)
_ctx = _swaggerinternal_readAppsV1beta1NamespacedControllerRevision(_api, name, namespace; pretty=pretty, exact=exact, __export__=__export__, _mediaType=_mediaType)
Swagger.exec(_ctx, response_stream)
end
function _swaggerinternal_readAppsV1beta1NamespacedDeployment(_api::AppsV1beta1Api, name::String, namespace::String; pretty=nothing, exact=nothing, __export__=nothing, _mediaType=nothing)
_ctx = Swagger.Ctx(_api.client, "GET", IoK8sApiAppsV1beta1Deployment, "/apis/apps/v1beta1/namespaces/{namespace}/deployments/{name}", ["BearerToken"])
Swagger.set_param(_ctx.path, "name", name) # type String
Swagger.set_param(_ctx.path, "namespace", namespace) # type String
Swagger.set_param(_ctx.query, "pretty", pretty) # type String
Swagger.set_param(_ctx.query, "exact", exact) # type Bool
Swagger.set_param(_ctx.query, "export", __export__) # type Bool
Swagger.set_header_accept(_ctx, ["application/json", "application/yaml", "application/vnd.kubernetes.protobuf"])
Swagger.set_header_content_type(_ctx, (_mediaType === nothing) ? ["*/*"] : [_mediaType])
return _ctx
end
"""
read the specified Deployment
Param: name::String (required)
Param: namespace::String (required)
Param: pretty::String
Param: exact::Bool
Param: __export__::Bool
Return: IoK8sApiAppsV1beta1Deployment
"""
function readAppsV1beta1NamespacedDeployment(_api::AppsV1beta1Api, name::String, namespace::String; pretty=nothing, exact=nothing, __export__=nothing, _mediaType=nothing)
_ctx = _swaggerinternal_readAppsV1beta1NamespacedDeployment(_api, name, namespace; pretty=pretty, exact=exact, __export__=__export__, _mediaType=_mediaType)
Swagger.exec(_ctx)
end
function readAppsV1beta1NamespacedDeployment(_api::AppsV1beta1Api, response_stream::Channel, name::String, namespace::String; pretty=nothing, exact=nothing, __export__=nothing, _mediaType=nothing)
_ctx = _swaggerinternal_readAppsV1beta1NamespacedDeployment(_api, name, namespace; pretty=pretty, exact=exact, __export__=__export__, _mediaType=_mediaType)
Swagger.exec(_ctx, response_stream)
end
function _swaggerinternal_readAppsV1beta1NamespacedDeploymentScale(_api::AppsV1beta1Api, name::String, namespace::String; pretty=nothing, _mediaType=nothing)
_ctx = Swagger.Ctx(_api.client, "GET", IoK8sApiAppsV1beta1Scale, "/apis/apps/v1beta1/namespaces/{namespace}/deployments/{name}/scale", ["BearerToken"])
Swagger.set_param(_ctx.path, "name", name) # type String
Swagger.set_param(_ctx.path, "namespace", namespace) # type String
Swagger.set_param(_ctx.query, "pretty", pretty) # type String
Swagger.set_header_accept(_ctx, ["application/json", "application/yaml", "application/vnd.kubernetes.protobuf"])
Swagger.set_header_content_type(_ctx, (_mediaType === nothing) ? ["*/*"] : [_mediaType])
return _ctx
end
"""
read scale of the specified Deployment
Param: name::String (required)
Param: namespace::String (required)
Param: pretty::String
Return: IoK8sApiAppsV1beta1Scale
"""
function readAppsV1beta1NamespacedDeploymentScale(_api::AppsV1beta1Api, name::String, namespace::String; pretty=nothing, _mediaType=nothing)
_ctx = _swaggerinternal_readAppsV1beta1NamespacedDeploymentScale(_api, name, namespace; pretty=pretty, _mediaType=_mediaType)
Swagger.exec(_ctx)
end
function readAppsV1beta1NamespacedDeploymentScale(_api::AppsV1beta1Api, response_stream::Channel, name::String, namespace::String; pretty=nothing, _mediaType=nothing)
_ctx = _swaggerinternal_readAppsV1beta1NamespacedDeploymentScale(_api, name, namespace; pretty=pretty, _mediaType=_mediaType)
Swagger.exec(_ctx, response_stream)
end
function _swaggerinternal_readAppsV1beta1NamespacedDeploymentStatus(_api::AppsV1beta1Api, name::String, namespace::String; pretty=nothing, _mediaType=nothing)
_ctx = Swagger.Ctx(_api.client, "GET", IoK8sApiAppsV1beta1Deployment, "/apis/apps/v1beta1/namespaces/{namespace}/deployments/{name}/status", ["BearerToken"])
Swagger.set_param(_ctx.path, "name", name) # type String
Swagger.set_param(_ctx.path, "namespace", namespace) # type String
Swagger.set_param(_ctx.query, "pretty", pretty) # type String
Swagger.set_header_accept(_ctx, ["application/json", "application/yaml", "application/vnd.kubernetes.protobuf"])
Swagger.set_header_content_type(_ctx, (_mediaType === nothing) ? ["*/*"] : [_mediaType])
return _ctx
end
"""
read status of the specified Deployment
Param: name::String (required)
Param: namespace::String (required)
Param: pretty::String
Return: IoK8sApiAppsV1beta1Deployment
"""
function readAppsV1beta1NamespacedDeploymentStatus(_api::AppsV1beta1Api, name::String, namespace::String; pretty=nothing, _mediaType=nothing)
_ctx = _swaggerinternal_readAppsV1beta1NamespacedDeploymentStatus(_api, name, namespace; pretty=pretty, _mediaType=_mediaType)
Swagger.exec(_ctx)
end
function readAppsV1beta1NamespacedDeploymentStatus(_api::AppsV1beta1Api, response_stream::Channel, name::String, namespace::String; pretty=nothing, _mediaType=nothing)
_ctx = _swaggerinternal_readAppsV1beta1NamespacedDeploymentStatus(_api, name, namespace; pretty=pretty, _mediaType=_mediaType)
Swagger.exec(_ctx, response_stream)
end
function _swaggerinternal_readAppsV1beta1NamespacedStatefulSet(_api::AppsV1beta1Api, name::String, namespace::String; pretty=nothing, exact=nothing, __export__=nothing, _mediaType=nothing)
_ctx = Swagger.Ctx(_api.client, "GET", IoK8sApiAppsV1beta1StatefulSet, "/apis/apps/v1beta1/namespaces/{namespace}/statefulsets/{name}", ["BearerToken"])
Swagger.set_param(_ctx.path, "name", name) # type String
Swagger.set_param(_ctx.path, "namespace", namespace) # type String
Swagger.set_param(_ctx.query, "pretty", pretty) # type String
Swagger.set_param(_ctx.query, "exact", exact) # type Bool
Swagger.set_param(_ctx.query, "export", __export__) # type Bool
Swagger.set_header_accept(_ctx, ["application/json", "application/yaml", "application/vnd.kubernetes.protobuf"])
Swagger.set_header_content_type(_ctx, (_mediaType === nothing) ? ["*/*"] : [_mediaType])
return _ctx
end
"""
read the specified StatefulSet
Param: name::String (required)
Param: namespace::String (required)
Param: pretty::String
Param: exact::Bool
Param: __export__::Bool
Return: IoK8sApiAppsV1beta1StatefulSet
"""
function readAppsV1beta1NamespacedStatefulSet(_api::AppsV1beta1Api, name::String, namespace::String; pretty=nothing, exact=nothing, __export__=nothing, _mediaType=nothing)
_ctx = _swaggerinternal_readAppsV1beta1NamespacedStatefulSet(_api, name, namespace; pretty=pretty, exact=exact, __export__=__export__, _mediaType=_mediaType)
Swagger.exec(_ctx)
end
function readAppsV1beta1NamespacedStatefulSet(_api::AppsV1beta1Api, response_stream::Channel, name::String, namespace::String; pretty=nothing, exact=nothing, __export__=nothing, _mediaType=nothing)
_ctx = _swaggerinternal_readAppsV1beta1NamespacedStatefulSet(_api, name, namespace; pretty=pretty, exact=exact, __export__=__export__, _mediaType=_mediaType)
Swagger.exec(_ctx, response_stream)
end
function _swaggerinternal_readAppsV1beta1NamespacedStatefulSetScale(_api::AppsV1beta1Api, name::String, namespace::String; pretty=nothing, _mediaType=nothing)
_ctx = Swagger.Ctx(_api.client, "GET", IoK8sApiAppsV1beta1Scale, "/apis/apps/v1beta1/namespaces/{namespace}/statefulsets/{name}/scale", ["BearerToken"])
Swagger.set_param(_ctx.path, "name", name) # type String
Swagger.set_param(_ctx.path, "namespace", namespace) # type String
Swagger.set_param(_ctx.query, "pretty", pretty) # type String
Swagger.set_header_accept(_ctx, ["application/json", "application/yaml", "application/vnd.kubernetes.protobuf"])
Swagger.set_header_content_type(_ctx, (_mediaType === nothing) ? ["*/*"] : [_mediaType])
return _ctx
end
"""
read scale of the specified StatefulSet
Param: name::String (required)
Param: namespace::String (required)
Param: pretty::String
Return: IoK8sApiAppsV1beta1Scale
"""
function readAppsV1beta1NamespacedStatefulSetScale(_api::AppsV1beta1Api, name::String, namespace::String; pretty=nothing, _mediaType=nothing)
_ctx = _swaggerinternal_readAppsV1beta1NamespacedStatefulSetScale(_api, name, namespace; pretty=pretty, _mediaType=_mediaType)
Swagger.exec(_ctx)
end
function readAppsV1beta1NamespacedStatefulSetScale(_api::AppsV1beta1Api, response_stream::Channel, name::String, namespace::String; pretty=nothing, _mediaType=nothing)
_ctx = _swaggerinternal_readAppsV1beta1NamespacedStatefulSetScale(_api, name, namespace; pretty=pretty, _mediaType=_mediaType)
Swagger.exec(_ctx, response_stream)
end
function _swaggerinternal_readAppsV1beta1NamespacedStatefulSetStatus(_api::AppsV1beta1Api, name::String, namespace::String; pretty=nothing, _mediaType=nothing)
_ctx = Swagger.Ctx(_api.client, "GET", IoK8sApiAppsV1beta1StatefulSet, "/apis/apps/v1beta1/namespaces/{namespace}/statefulsets/{name}/status", ["BearerToken"])
Swagger.set_param(_ctx.path, "name", name) # type String
Swagger.set_param(_ctx.path, "namespace", namespace) # type String
Swagger.set_param(_ctx.query, "pretty", pretty) # type String
Swagger.set_header_accept(_ctx, ["application/json", "application/yaml", "application/vnd.kubernetes.protobuf"])
Swagger.set_header_content_type(_ctx, (_mediaType === nothing) ? ["*/*"] : [_mediaType])
return _ctx
end
"""
read status of the specified StatefulSet
Param: name::String (required)
Param: namespace::String (required)
Param: pretty::String
Return: IoK8sApiAppsV1beta1StatefulSet
"""
function readAppsV1beta1NamespacedStatefulSetStatus(_api::AppsV1beta1Api, name::String, namespace::String; pretty=nothing, _mediaType=nothing)
_ctx = _swaggerinternal_readAppsV1beta1NamespacedStatefulSetStatus(_api, name, namespace; pretty=pretty, _mediaType=_mediaType)
Swagger.exec(_ctx)
end
function readAppsV1beta1NamespacedStatefulSetStatus(_api::AppsV1beta1Api, response_stream::Channel, name::String, namespace::String; pretty=nothing, _mediaType=nothing)
_ctx = _swaggerinternal_readAppsV1beta1NamespacedStatefulSetStatus(_api, name, namespace; pretty=pretty, _mediaType=_mediaType)
Swagger.exec(_ctx, response_stream)
end
function _swaggerinternal_replaceAppsV1beta1NamespacedControllerRevision(_api::AppsV1beta1Api, name::String, namespace::String, body; pretty=nothing, dryRun=nothing, fieldManager=nothing, _mediaType=nothing)
_ctx = Swagger.Ctx(_api.client, "PUT", IoK8sApiAppsV1beta1ControllerRevision, "/apis/apps/v1beta1/namespaces/{namespace}/controllerrevisions/{name}", ["BearerToken"], body)
Swagger.set_param(_ctx.path, "name", name) # type String
Swagger.set_param(_ctx.path, "namespace", namespace) # type String
Swagger.set_param(_ctx.query, "pretty", pretty) # type String
Swagger.set_param(_ctx.query, "dryRun", dryRun) # type String
Swagger.set_param(_ctx.query, "fieldManager", fieldManager) # type String
Swagger.set_header_accept(_ctx, ["application/json", "application/yaml", "application/vnd.kubernetes.protobuf"])
Swagger.set_header_content_type(_ctx, (_mediaType === nothing) ? ["*/*"] : [_mediaType])
return _ctx
end
"""
replace the specified ControllerRevision
Param: name::String (required)
Param: namespace::String (required)
Param: body::IoK8sApiAppsV1beta1ControllerRevision (required)
Param: pretty::String
Param: dryRun::String
Param: fieldManager::String
Return: IoK8sApiAppsV1beta1ControllerRevision
"""
function replaceAppsV1beta1NamespacedControllerRevision(_api::AppsV1beta1Api, name::String, namespace::String, body; pretty=nothing, dryRun=nothing, fieldManager=nothing, _mediaType=nothing)
_ctx = _swaggerinternal_replaceAppsV1beta1NamespacedControllerRevision(_api, name, namespace, body; pretty=pretty, dryRun=dryRun, fieldManager=fieldManager, _mediaType=_mediaType)
Swagger.exec(_ctx)
end
function replaceAppsV1beta1NamespacedControllerRevision(_api::AppsV1beta1Api, response_stream::Channel, name::String, namespace::String, body; pretty=nothing, dryRun=nothing, fieldManager=nothing, _mediaType=nothing)
_ctx = _swaggerinternal_replaceAppsV1beta1NamespacedControllerRevision(_api, name, namespace, body; pretty=pretty, dryRun=dryRun, fieldManager=fieldManager, _mediaType=_mediaType)
Swagger.exec(_ctx, response_stream)
end
function _swaggerinternal_replaceAppsV1beta1NamespacedDeployment(_api::AppsV1beta1Api, name::String, namespace::String, body; pretty=nothing, dryRun=nothing, fieldManager=nothing, _mediaType=nothing)
_ctx = Swagger.Ctx(_api.client, "PUT", IoK8sApiAppsV1beta1Deployment, "/apis/apps/v1beta1/namespaces/{namespace}/deployments/{name}", ["BearerToken"], body)
Swagger.set_param(_ctx.path, "name", name) # type String
Swagger.set_param(_ctx.path, "namespace", namespace) # type String
Swagger.set_param(_ctx.query, "pretty", pretty) # type String
Swagger.set_param(_ctx.query, "dryRun", dryRun) # type String
Swagger.set_param(_ctx.query, "fieldManager", fieldManager) # type String
Swagger.set_header_accept(_ctx, ["application/json", "application/yaml", "application/vnd.kubernetes.protobuf"])
Swagger.set_header_content_type(_ctx, (_mediaType === nothing) ? ["*/*"] : [_mediaType])
return _ctx
end
"""
replace the specified Deployment
Param: name::String (required)
Param: namespace::String (required)
Param: body::IoK8sApiAppsV1beta1Deployment (required)
Param: pretty::String
Param: dryRun::String
Param: fieldManager::String
Return: IoK8sApiAppsV1beta1Deployment
"""
function replaceAppsV1beta1NamespacedDeployment(_api::AppsV1beta1Api, name::String, namespace::String, body; pretty=nothing, dryRun=nothing, fieldManager=nothing, _mediaType=nothing)
_ctx = _swaggerinternal_replaceAppsV1beta1NamespacedDeployment(_api, name, namespace, body; pretty=pretty, dryRun=dryRun, fieldManager=fieldManager, _mediaType=_mediaType)
Swagger.exec(_ctx)
end
function replaceAppsV1beta1NamespacedDeployment(_api::AppsV1beta1Api, response_stream::Channel, name::String, namespace::String, body; pretty=nothing, dryRun=nothing, fieldManager=nothing, _mediaType=nothing)
_ctx = _swaggerinternal_replaceAppsV1beta1NamespacedDeployment(_api, name, namespace, body; pretty=pretty, dryRun=dryRun, fieldManager=fieldManager, _mediaType=_mediaType)
Swagger.exec(_ctx, response_stream)
end
function _swaggerinternal_replaceAppsV1beta1NamespacedDeploymentScale(_api::AppsV1beta1Api, name::String, namespace::String, body; pretty=nothing, dryRun=nothing, fieldManager=nothing, _mediaType=nothing)
_ctx = Swagger.Ctx(_api.client, "PUT", IoK8sApiAppsV1beta1Scale, "/apis/apps/v1beta1/namespaces/{namespace}/deployments/{name}/scale", ["BearerToken"], body)
Swagger.set_param(_ctx.path, "name", name) # type String
Swagger.set_param(_ctx.path, "namespace", namespace) # type String
Swagger.set_param(_ctx.query, "pretty", pretty) # type String
Swagger.set_param(_ctx.query, "dryRun", dryRun) # type String
Swagger.set_param(_ctx.query, "fieldManager", fieldManager) # type String
Swagger.set_header_accept(_ctx, ["application/json", "application/yaml", "application/vnd.kubernetes.protobuf"])
Swagger.set_header_content_type(_ctx, (_mediaType === nothing) ? ["*/*"] : [_mediaType])
return _ctx
end
"""
replace scale of the specified Deployment
Param: name::String (required)
Param: namespace::String (required)
Param: body::IoK8sApiAppsV1beta1Scale (required)
Param: pretty::String
Param: dryRun::String
Param: fieldManager::String
Return: IoK8sApiAppsV1beta1Scale
"""
function replaceAppsV1beta1NamespacedDeploymentScale(_api::AppsV1beta1Api, name::String, namespace::String, body; pretty=nothing, dryRun=nothing, fieldManager=nothing, _mediaType=nothing)
_ctx = _swaggerinternal_replaceAppsV1beta1NamespacedDeploymentScale(_api, name, namespace, body; pretty=pretty, dryRun=dryRun, fieldManager=fieldManager, _mediaType=_mediaType)
Swagger.exec(_ctx)
end
function replaceAppsV1beta1NamespacedDeploymentScale(_api::AppsV1beta1Api, response_stream::Channel, name::String, namespace::String, body; pretty=nothing, dryRun=nothing, fieldManager=nothing, _mediaType=nothing)
_ctx = _swaggerinternal_replaceAppsV1beta1NamespacedDeploymentScale(_api, name, namespace, body; pretty=pretty, dryRun=dryRun, fieldManager=fieldManager, _mediaType=_mediaType)
Swagger.exec(_ctx, response_stream)
end
function _swaggerinternal_replaceAppsV1beta1NamespacedDeploymentStatus(_api::AppsV1beta1Api, name::String, namespace::String, body; pretty=nothing, dryRun=nothing, fieldManager=nothing, _mediaType=nothing)
_ctx = Swagger.Ctx(_api.client, "PUT", IoK8sApiAppsV1beta1Deployment, "/apis/apps/v1beta1/namespaces/{namespace}/deployments/{name}/status", ["BearerToken"], body)
Swagger.set_param(_ctx.path, "name", name) # type String
Swagger.set_param(_ctx.path, "namespace", namespace) # type String
Swagger.set_param(_ctx.query, "pretty", pretty) # type String
Swagger.set_param(_ctx.query, "dryRun", dryRun) # type String
Swagger.set_param(_ctx.query, "fieldManager", fieldManager) # type String
Swagger.set_header_accept(_ctx, ["application/json", "application/yaml", "application/vnd.kubernetes.protobuf"])
Swagger.set_header_content_type(_ctx, (_mediaType === nothing) ? ["*/*"] : [_mediaType])
return _ctx
end
"""
replace status of the specified Deployment
Param: name::String (required)
Param: namespace::String (required)
Param: body::IoK8sApiAppsV1beta1Deployment (required)
Param: pretty::String
Param: dryRun::String
Param: fieldManager::String
Return: IoK8sApiAppsV1beta1Deployment
"""
function replaceAppsV1beta1NamespacedDeploymentStatus(_api::AppsV1beta1Api, name::String, namespace::String, body; pretty=nothing, dryRun=nothing, fieldManager=nothing, _mediaType=nothing)
_ctx = _swaggerinternal_replaceAppsV1beta1NamespacedDeploymentStatus(_api, name, namespace, body; pretty=pretty, dryRun=dryRun, fieldManager=fieldManager, _mediaType=_mediaType)
Swagger.exec(_ctx)
end
function replaceAppsV1beta1NamespacedDeploymentStatus(_api::AppsV1beta1Api, response_stream::Channel, name::String, namespace::String, body; pretty=nothing, dryRun=nothing, fieldManager=nothing, _mediaType=nothing)
_ctx = _swaggerinternal_replaceAppsV1beta1NamespacedDeploymentStatus(_api, name, namespace, body; pretty=pretty, dryRun=dryRun, fieldManager=fieldManager, _mediaType=_mediaType)
Swagger.exec(_ctx, response_stream)
end
function _swaggerinternal_replaceAppsV1beta1NamespacedStatefulSet(_api::AppsV1beta1Api, name::String, namespace::String, body; pretty=nothing, dryRun=nothing, fieldManager=nothing, _mediaType=nothing)
_ctx = Swagger.Ctx(_api.client, "PUT", IoK8sApiAppsV1beta1StatefulSet, "/apis/apps/v1beta1/namespaces/{namespace}/statefulsets/{name}", ["BearerToken"], body)
Swagger.set_param(_ctx.path, "name", name) # type String
Swagger.set_param(_ctx.path, "namespace", namespace) # type String
Swagger.set_param(_ctx.query, "pretty", pretty) # type String
Swagger.set_param(_ctx.query, "dryRun", dryRun) # type String
Swagger.set_param(_ctx.query, "fieldManager", fieldManager) # type String
Swagger.set_header_accept(_ctx, ["application/json", "application/yaml", "application/vnd.kubernetes.protobuf"])
Swagger.set_header_content_type(_ctx, (_mediaType === nothing) ? ["*/*"] : [_mediaType])
return _ctx
end
"""
replace the specified StatefulSet
Param: name::String (required)
Param: namespace::String (required)
Param: body::IoK8sApiAppsV1beta1StatefulSet (required)
Param: pretty::String
Param: dryRun::String
Param: fieldManager::String
Return: IoK8sApiAppsV1beta1StatefulSet
"""
function replaceAppsV1beta1NamespacedStatefulSet(_api::AppsV1beta1Api, name::String, namespace::String, body; pretty=nothing, dryRun=nothing, fieldManager=nothing, _mediaType=nothing)
_ctx = _swaggerinternal_replaceAppsV1beta1NamespacedStatefulSet(_api, name, namespace, body; pretty=pretty, dryRun=dryRun, fieldManager=fieldManager, _mediaType=_mediaType)
Swagger.exec(_ctx)
end
function replaceAppsV1beta1NamespacedStatefulSet(_api::AppsV1beta1Api, response_stream::Channel, name::String, namespace::String, body; pretty=nothing, dryRun=nothing, fieldManager=nothing, _mediaType=nothing)
_ctx = _swaggerinternal_replaceAppsV1beta1NamespacedStatefulSet(_api, name, namespace, body; pretty=pretty, dryRun=dryRun, fieldManager=fieldManager, _mediaType=_mediaType)
Swagger.exec(_ctx, response_stream)
end
function _swaggerinternal_replaceAppsV1beta1NamespacedStatefulSetScale(_api::AppsV1beta1Api, name::String, namespace::String, body; pretty=nothing, dryRun=nothing, fieldManager=nothing, _mediaType=nothing)
_ctx = Swagger.Ctx(_api.client, "PUT", IoK8sApiAppsV1beta1Scale, "/apis/apps/v1beta1/namespaces/{namespace}/statefulsets/{name}/scale", ["BearerToken"], body)
Swagger.set_param(_ctx.path, "name", name) # type String
Swagger.set_param(_ctx.path, "namespace", namespace) # type String
Swagger.set_param(_ctx.query, "pretty", pretty) # type String
Swagger.set_param(_ctx.query, "dryRun", dryRun) # type String
Swagger.set_param(_ctx.query, "fieldManager", fieldManager) # type String
Swagger.set_header_accept(_ctx, ["application/json", "application/yaml", "application/vnd.kubernetes.protobuf"])
Swagger.set_header_content_type(_ctx, (_mediaType === nothing) ? ["*/*"] : [_mediaType])
return _ctx
end
"""
replace scale of the specified StatefulSet
Param: name::String (required)
Param: namespace::String (required)
Param: body::IoK8sApiAppsV1beta1Scale (required)
Param: pretty::String
Param: dryRun::String
Param: fieldManager::String
Return: IoK8sApiAppsV1beta1Scale
"""
function replaceAppsV1beta1NamespacedStatefulSetScale(_api::AppsV1beta1Api, name::String, namespace::String, body; pretty=nothing, dryRun=nothing, fieldManager=nothing, _mediaType=nothing)
_ctx = _swaggerinternal_replaceAppsV1beta1NamespacedStatefulSetScale(_api, name, namespace, body; pretty=pretty, dryRun=dryRun, fieldManager=fieldManager, _mediaType=_mediaType)
Swagger.exec(_ctx)
end
function replaceAppsV1beta1NamespacedStatefulSetScale(_api::AppsV1beta1Api, response_stream::Channel, name::String, namespace::String, body; pretty=nothing, dryRun=nothing, fieldManager=nothing, _mediaType=nothing)
_ctx = _swaggerinternal_replaceAppsV1beta1NamespacedStatefulSetScale(_api, name, namespace, body; pretty=pretty, dryRun=dryRun, fieldManager=fieldManager, _mediaType=_mediaType)
Swagger.exec(_ctx, response_stream)
end
function _swaggerinternal_replaceAppsV1beta1NamespacedStatefulSetStatus(_api::AppsV1beta1Api, name::String, namespace::String, body; pretty=nothing, dryRun=nothing, fieldManager=nothing, _mediaType=nothing)
_ctx = Swagger.Ctx(_api.client, "PUT", IoK8sApiAppsV1beta1StatefulSet, "/apis/apps/v1beta1/namespaces/{namespace}/statefulsets/{name}/status", ["BearerToken"], body)
Swagger.set_param(_ctx.path, "name", name) # type String
Swagger.set_param(_ctx.path, "namespace", namespace) # type String
Swagger.set_param(_ctx.query, "pretty", pretty) # type String
Swagger.set_param(_ctx.query, "dryRun", dryRun) # type String
Swagger.set_param(_ctx.query, "fieldManager", fieldManager) # type String
Swagger.set_header_accept(_ctx, ["application/json", "application/yaml", "application/vnd.kubernetes.protobuf"])
Swagger.set_header_content_type(_ctx, (_mediaType === nothing) ? ["*/*"] : [_mediaType])
return _ctx
end
"""
replace status of the specified StatefulSet
Param: name::String (required)
Param: namespace::String (required)
Param: body::IoK8sApiAppsV1beta1StatefulSet (required)
Param: pretty::String
Param: dryRun::String
Param: fieldManager::String
Return: IoK8sApiAppsV1beta1StatefulSet
"""
function replaceAppsV1beta1NamespacedStatefulSetStatus(_api::AppsV1beta1Api, name::String, namespace::String, body; pretty=nothing, dryRun=nothing, fieldManager=nothing, _mediaType=nothing)
_ctx = _swaggerinternal_replaceAppsV1beta1NamespacedStatefulSetStatus(_api, name, namespace, body; pretty=pretty, dryRun=dryRun, fieldManager=fieldManager, _mediaType=_mediaType)
Swagger.exec(_ctx)
end
function replaceAppsV1beta1NamespacedStatefulSetStatus(_api::AppsV1beta1Api, response_stream::Channel, name::String, namespace::String, body; pretty=nothing, dryRun=nothing, fieldManager=nothing, _mediaType=nothing)
_ctx = _swaggerinternal_replaceAppsV1beta1NamespacedStatefulSetStatus(_api, name, namespace, body; pretty=pretty, dryRun=dryRun, fieldManager=fieldManager, _mediaType=_mediaType)
Swagger.exec(_ctx, response_stream)
end
function _swaggerinternal_watchAppsV1beta1ControllerRevisionListForAllNamespaces(_api::AppsV1beta1Api; allowWatchBookmarks=nothing, __continue__=nothing, fieldSelector=nothing, labelSelector=nothing, limit=nothing, pretty=nothing, resourceVersion=nothing, timeoutSeconds=nothing, watch=nothing, _mediaType=nothing)
_ctx = Swagger.Ctx(_api.client, "GET", IoK8sApimachineryPkgApisMetaV1WatchEvent, "/apis/apps/v1beta1/watch/controllerrevisions", ["BearerToken"])
Swagger.set_param(_ctx.query, "allowWatchBookmarks", allowWatchBookmarks) # type Bool
Swagger.set_param(_ctx.query, "continue", __continue__) # type String
Swagger.set_param(_ctx.query, "fieldSelector", fieldSelector) # type String
Swagger.set_param(_ctx.query, "labelSelector", labelSelector) # type String
Swagger.set_param(_ctx.query, "limit", limit) # type Int32
Swagger.set_param(_ctx.query, "pretty", pretty) # type String
Swagger.set_param(_ctx.query, "resourceVersion", resourceVersion) # type String
Swagger.set_param(_ctx.query, "timeoutSeconds", timeoutSeconds) # type Int32
Swagger.set_param(_ctx.query, "watch", watch) # type Bool
Swagger.set_header_accept(_ctx, ["application/json", "application/yaml", "application/vnd.kubernetes.protobuf", "application/json;stream=watch", "application/vnd.kubernetes.protobuf;stream=watch"])
Swagger.set_header_content_type(_ctx, (_mediaType === nothing) ? ["*/*"] : [_mediaType])
return _ctx
end
"""
watch individual changes to a list of ControllerRevision. deprecated: use the 'watch' parameter with a list operation instead.
Param: allowWatchBookmarks::Bool
Param: __continue__::String
Param: fieldSelector::String
Param: labelSelector::String
Param: limit::Int32
Param: pretty::String
Param: resourceVersion::String
Param: timeoutSeconds::Int32
Param: watch::Bool
Return: IoK8sApimachineryPkgApisMetaV1WatchEvent
"""
function watchAppsV1beta1ControllerRevisionListForAllNamespaces(_api::AppsV1beta1Api; allowWatchBookmarks=nothing, __continue__=nothing, fieldSelector=nothing, labelSelector=nothing, limit=nothing, pretty=nothing, resourceVersion=nothing, timeoutSeconds=nothing, watch=nothing, _mediaType=nothing)
_ctx = _swaggerinternal_watchAppsV1beta1ControllerRevisionListForAllNamespaces(_api; allowWatchBookmarks=allowWatchBookmarks, __continue__=__continue__, fieldSelector=fieldSelector, labelSelector=labelSelector, limit=limit, pretty=pretty, resourceVersion=resourceVersion, timeoutSeconds=timeoutSeconds, watch=watch, _mediaType=_mediaType)
Swagger.exec(_ctx)
end
function watchAppsV1beta1ControllerRevisionListForAllNamespaces(_api::AppsV1beta1Api, response_stream::Channel; allowWatchBookmarks=nothing, __continue__=nothing, fieldSelector=nothing, labelSelector=nothing, limit=nothing, pretty=nothing, resourceVersion=nothing, timeoutSeconds=nothing, watch=nothing, _mediaType=nothing)
_ctx = _swaggerinternal_watchAppsV1beta1ControllerRevisionListForAllNamespaces(_api; allowWatchBookmarks=allowWatchBookmarks, __continue__=__continue__, fieldSelector=fieldSelector, labelSelector=labelSelector, limit=limit, pretty=pretty, resourceVersion=resourceVersion, timeoutSeconds=timeoutSeconds, watch=watch, _mediaType=_mediaType)
Swagger.exec(_ctx, response_stream)
end
function _swaggerinternal_watchAppsV1beta1DeploymentListForAllNamespaces(_api::AppsV1beta1Api; allowWatchBookmarks=nothing, __continue__=nothing, fieldSelector=nothing, labelSelector=nothing, limit=nothing, pretty=nothing, resourceVersion=nothing, timeoutSeconds=nothing, watch=nothing, _mediaType=nothing)
_ctx = Swagger.Ctx(_api.client, "GET", IoK8sApimachineryPkgApisMetaV1WatchEvent, "/apis/apps/v1beta1/watch/deployments", ["BearerToken"])
Swagger.set_param(_ctx.query, "allowWatchBookmarks", allowWatchBookmarks) # type Bool
Swagger.set_param(_ctx.query, "continue", __continue__) # type String
Swagger.set_param(_ctx.query, "fieldSelector", fieldSelector) # type String
Swagger.set_param(_ctx.query, "labelSelector", labelSelector) # type String
Swagger.set_param(_ctx.query, "limit", limit) # type Int32
Swagger.set_param(_ctx.query, "pretty", pretty) # type String
Swagger.set_param(_ctx.query, "resourceVersion", resourceVersion) # type String
Swagger.set_param(_ctx.query, "timeoutSeconds", timeoutSeconds) # type Int32
Swagger.set_param(_ctx.query, "watch", watch) # type Bool
Swagger.set_header_accept(_ctx, ["application/json", "application/yaml", "application/vnd.kubernetes.protobuf", "application/json;stream=watch", "application/vnd.kubernetes.protobuf;stream=watch"])
Swagger.set_header_content_type(_ctx, (_mediaType === nothing) ? ["*/*"] : [_mediaType])
return _ctx
end
"""
watch individual changes to a list of Deployment. deprecated: use the 'watch' parameter with a list operation instead.
Param: allowWatchBookmarks::Bool
Param: __continue__::String
Param: fieldSelector::String
Param: labelSelector::String
Param: limit::Int32
Param: pretty::String
Param: resourceVersion::String
Param: timeoutSeconds::Int32
Param: watch::Bool
Return: IoK8sApimachineryPkgApisMetaV1WatchEvent
"""
function watchAppsV1beta1DeploymentListForAllNamespaces(_api::AppsV1beta1Api; allowWatchBookmarks=nothing, __continue__=nothing, fieldSelector=nothing, labelSelector=nothing, limit=nothing, pretty=nothing, resourceVersion=nothing, timeoutSeconds=nothing, watch=nothing, _mediaType=nothing)
_ctx = _swaggerinternal_watchAppsV1beta1DeploymentListForAllNamespaces(_api; allowWatchBookmarks=allowWatchBookmarks, __continue__=__continue__, fieldSelector=fieldSelector, labelSelector=labelSelector, limit=limit, pretty=pretty, resourceVersion=resourceVersion, timeoutSeconds=timeoutSeconds, watch=watch, _mediaType=_mediaType)
Swagger.exec(_ctx)
end
function watchAppsV1beta1DeploymentListForAllNamespaces(_api::AppsV1beta1Api, response_stream::Channel; allowWatchBookmarks=nothing, __continue__=nothing, fieldSelector=nothing, labelSelector=nothing, limit=nothing, pretty=nothing, resourceVersion=nothing, timeoutSeconds=nothing, watch=nothing, _mediaType=nothing)
_ctx = _swaggerinternal_watchAppsV1beta1DeploymentListForAllNamespaces(_api; allowWatchBookmarks=allowWatchBookmarks, __continue__=__continue__, fieldSelector=fieldSelector, labelSelector=labelSelector, limit=limit, pretty=pretty, resourceVersion=resourceVersion, timeoutSeconds=timeoutSeconds, watch=watch, _mediaType=_mediaType)
Swagger.exec(_ctx, response_stream)
end
function _swaggerinternal_watchAppsV1beta1NamespacedControllerRevision(_api::AppsV1beta1Api, name::String, namespace::String; allowWatchBookmarks=nothing, __continue__=nothing, fieldSelector=nothing, labelSelector=nothing, limit=nothing, pretty=nothing, resourceVersion=nothing, timeoutSeconds=nothing, watch=nothing, _mediaType=nothing)
_ctx = Swagger.Ctx(_api.client, "GET", IoK8sApimachineryPkgApisMetaV1WatchEvent, "/apis/apps/v1beta1/watch/namespaces/{namespace}/controllerrevisions/{name}", ["BearerToken"])
Swagger.set_param(_ctx.path, "name", name) # type String
Swagger.set_param(_ctx.path, "namespace", namespace) # type String
Swagger.set_param(_ctx.query, "allowWatchBookmarks", allowWatchBookmarks) # type Bool
Swagger.set_param(_ctx.query, "continue", __continue__) # type String
Swagger.set_param(_ctx.query, "fieldSelector", fieldSelector) # type String
Swagger.set_param(_ctx.query, "labelSelector", labelSelector) # type String
Swagger.set_param(_ctx.query, "limit", limit) # type Int32
Swagger.set_param(_ctx.query, "pretty", pretty) # type String
Swagger.set_param(_ctx.query, "resourceVersion", resourceVersion) # type String
Swagger.set_param(_ctx.query, "timeoutSeconds", timeoutSeconds) # type Int32
Swagger.set_param(_ctx.query, "watch", watch) # type Bool
Swagger.set_header_accept(_ctx, ["application/json", "application/yaml", "application/vnd.kubernetes.protobuf", "application/json;stream=watch", "application/vnd.kubernetes.protobuf;stream=watch"])
Swagger.set_header_content_type(_ctx, (_mediaType === nothing) ? ["*/*"] : [_mediaType])
return _ctx
end
"""
watch changes to an object of kind ControllerRevision. deprecated: use the 'watch' parameter with a list operation instead, filtered to a single item with the 'fieldSelector' parameter.
Param: name::String (required)
Param: namespace::String (required)
Param: allowWatchBookmarks::Bool
Param: __continue__::String
Param: fieldSelector::String
Param: labelSelector::String
Param: limit::Int32
Param: pretty::String
Param: resourceVersion::String
Param: timeoutSeconds::Int32
Param: watch::Bool
Return: IoK8sApimachineryPkgApisMetaV1WatchEvent
"""
function watchAppsV1beta1NamespacedControllerRevision(_api::AppsV1beta1Api, name::String, namespace::String; allowWatchBookmarks=nothing, __continue__=nothing, fieldSelector=nothing, labelSelector=nothing, limit=nothing, pretty=nothing, resourceVersion=nothing, timeoutSeconds=nothing, watch=nothing, _mediaType=nothing)
_ctx = _swaggerinternal_watchAppsV1beta1NamespacedControllerRevision(_api, name, namespace; allowWatchBookmarks=allowWatchBookmarks, __continue__=__continue__, fieldSelector=fieldSelector, labelSelector=labelSelector, limit=limit, pretty=pretty, resourceVersion=resourceVersion, timeoutSeconds=timeoutSeconds, watch=watch, _mediaType=_mediaType)
Swagger.exec(_ctx)
end
function watchAppsV1beta1NamespacedControllerRevision(_api::AppsV1beta1Api, response_stream::Channel, name::String, namespace::String; allowWatchBookmarks=nothing, __continue__=nothing, fieldSelector=nothing, labelSelector=nothing, limit=nothing, pretty=nothing, resourceVersion=nothing, timeoutSeconds=nothing, watch=nothing, _mediaType=nothing)
_ctx = _swaggerinternal_watchAppsV1beta1NamespacedControllerRevision(_api, name, namespace; allowWatchBookmarks=allowWatchBookmarks, __continue__=__continue__, fieldSelector=fieldSelector, labelSelector=labelSelector, limit=limit, pretty=pretty, resourceVersion=resourceVersion, timeoutSeconds=timeoutSeconds, watch=watch, _mediaType=_mediaType)
Swagger.exec(_ctx, response_stream)
end
function _swaggerinternal_watchAppsV1beta1NamespacedControllerRevisionList(_api::AppsV1beta1Api, namespace::String; allowWatchBookmarks=nothing, __continue__=nothing, fieldSelector=nothing, labelSelector=nothing, limit=nothing, pretty=nothing, resourceVersion=nothing, timeoutSeconds=nothing, watch=nothing, _mediaType=nothing)
_ctx = Swagger.Ctx(_api.client, "GET", IoK8sApimachineryPkgApisMetaV1WatchEvent, "/apis/apps/v1beta1/watch/namespaces/{namespace}/controllerrevisions", ["BearerToken"])
Swagger.set_param(_ctx.path, "namespace", namespace) # type String
Swagger.set_param(_ctx.query, "allowWatchBookmarks", allowWatchBookmarks) # type Bool
Swagger.set_param(_ctx.query, "continue", __continue__) # type String
Swagger.set_param(_ctx.query, "fieldSelector", fieldSelector) # type String
Swagger.set_param(_ctx.query, "labelSelector", labelSelector) # type String
Swagger.set_param(_ctx.query, "limit", limit) # type Int32
Swagger.set_param(_ctx.query, "pretty", pretty) # type String
Swagger.set_param(_ctx.query, "resourceVersion", resourceVersion) # type String
Swagger.set_param(_ctx.query, "timeoutSeconds", timeoutSeconds) # type Int32
Swagger.set_param(_ctx.query, "watch", watch) # type Bool
Swagger.set_header_accept(_ctx, ["application/json", "application/yaml", "application/vnd.kubernetes.protobuf", "application/json;stream=watch", "application/vnd.kubernetes.protobuf;stream=watch"])
Swagger.set_header_content_type(_ctx, (_mediaType === nothing) ? ["*/*"] : [_mediaType])
return _ctx
end
"""
watch individual changes to a list of ControllerRevision. deprecated: use the 'watch' parameter with a list operation instead.
Param: namespace::String (required)
Param: allowWatchBookmarks::Bool
Param: __continue__::String
Param: fieldSelector::String
Param: labelSelector::String
Param: limit::Int32
Param: pretty::String
Param: resourceVersion::String
Param: timeoutSeconds::Int32
Param: watch::Bool
Return: IoK8sApimachineryPkgApisMetaV1WatchEvent
"""
function watchAppsV1beta1NamespacedControllerRevisionList(_api::AppsV1beta1Api, namespace::String; allowWatchBookmarks=nothing, __continue__=nothing, fieldSelector=nothing, labelSelector=nothing, limit=nothing, pretty=nothing, resourceVersion=nothing, timeoutSeconds=nothing, watch=nothing, _mediaType=nothing)
_ctx = _swaggerinternal_watchAppsV1beta1NamespacedControllerRevisionList(_api, namespace; allowWatchBookmarks=allowWatchBookmarks, __continue__=__continue__, fieldSelector=fieldSelector, labelSelector=labelSelector, limit=limit, pretty=pretty, resourceVersion=resourceVersion, timeoutSeconds=timeoutSeconds, watch=watch, _mediaType=_mediaType)
Swagger.exec(_ctx)
end
function watchAppsV1beta1NamespacedControllerRevisionList(_api::AppsV1beta1Api, response_stream::Channel, namespace::String; allowWatchBookmarks=nothing, __continue__=nothing, fieldSelector=nothing, labelSelector=nothing, limit=nothing, pretty=nothing, resourceVersion=nothing, timeoutSeconds=nothing, watch=nothing, _mediaType=nothing)
_ctx = _swaggerinternal_watchAppsV1beta1NamespacedControllerRevisionList(_api, namespace; allowWatchBookmarks=allowWatchBookmarks, __continue__=__continue__, fieldSelector=fieldSelector, labelSelector=labelSelector, limit=limit, pretty=pretty, resourceVersion=resourceVersion, timeoutSeconds=timeoutSeconds, watch=watch, _mediaType=_mediaType)
Swagger.exec(_ctx, response_stream)
end
function _swaggerinternal_watchAppsV1beta1NamespacedDeployment(_api::AppsV1beta1Api, name::String, namespace::String; allowWatchBookmarks=nothing, __continue__=nothing, fieldSelector=nothing, labelSelector=nothing, limit=nothing, pretty=nothing, resourceVersion=nothing, timeoutSeconds=nothing, watch=nothing, _mediaType=nothing)
_ctx = Swagger.Ctx(_api.client, "GET", IoK8sApimachineryPkgApisMetaV1WatchEvent, "/apis/apps/v1beta1/watch/namespaces/{namespace}/deployments/{name}", ["BearerToken"])
Swagger.set_param(_ctx.path, "name", name) # type String
Swagger.set_param(_ctx.path, "namespace", namespace) # type String
Swagger.set_param(_ctx.query, "allowWatchBookmarks", allowWatchBookmarks) # type Bool
Swagger.set_param(_ctx.query, "continue", __continue__) # type String
Swagger.set_param(_ctx.query, "fieldSelector", fieldSelector) # type String
Swagger.set_param(_ctx.query, "labelSelector", labelSelector) # type String
Swagger.set_param(_ctx.query, "limit", limit) # type Int32
Swagger.set_param(_ctx.query, "pretty", pretty) # type String
Swagger.set_param(_ctx.query, "resourceVersion", resourceVersion) # type String
Swagger.set_param(_ctx.query, "timeoutSeconds", timeoutSeconds) # type Int32
Swagger.set_param(_ctx.query, "watch", watch) # type Bool
Swagger.set_header_accept(_ctx, ["application/json", "application/yaml", "application/vnd.kubernetes.protobuf", "application/json;stream=watch", "application/vnd.kubernetes.protobuf;stream=watch"])
Swagger.set_header_content_type(_ctx, (_mediaType === nothing) ? ["*/*"] : [_mediaType])
return _ctx
end
"""
watch changes to an object of kind Deployment. deprecated: use the 'watch' parameter with a list operation instead, filtered to a single item with the 'fieldSelector' parameter.
Param: name::String (required)
Param: namespace::String (required)
Param: allowWatchBookmarks::Bool
Param: __continue__::String
Param: fieldSelector::String
Param: labelSelector::String
Param: limit::Int32
Param: pretty::String
Param: resourceVersion::String
Param: timeoutSeconds::Int32
Param: watch::Bool
Return: IoK8sApimachineryPkgApisMetaV1WatchEvent
"""
function watchAppsV1beta1NamespacedDeployment(_api::AppsV1beta1Api, name::String, namespace::String; allowWatchBookmarks=nothing, __continue__=nothing, fieldSelector=nothing, labelSelector=nothing, limit=nothing, pretty=nothing, resourceVersion=nothing, timeoutSeconds=nothing, watch=nothing, _mediaType=nothing)
_ctx = _swaggerinternal_watchAppsV1beta1NamespacedDeployment(_api, name, namespace; allowWatchBookmarks=allowWatchBookmarks, __continue__=__continue__, fieldSelector=fieldSelector, labelSelector=labelSelector, limit=limit, pretty=pretty, resourceVersion=resourceVersion, timeoutSeconds=timeoutSeconds, watch=watch, _mediaType=_mediaType)
Swagger.exec(_ctx)
end
function watchAppsV1beta1NamespacedDeployment(_api::AppsV1beta1Api, response_stream::Channel, name::String, namespace::String; allowWatchBookmarks=nothing, __continue__=nothing, fieldSelector=nothing, labelSelector=nothing, limit=nothing, pretty=nothing, resourceVersion=nothing, timeoutSeconds=nothing, watch=nothing, _mediaType=nothing)
_ctx = _swaggerinternal_watchAppsV1beta1NamespacedDeployment(_api, name, namespace; allowWatchBookmarks=allowWatchBookmarks, __continue__=__continue__, fieldSelector=fieldSelector, labelSelector=labelSelector, limit=limit, pretty=pretty, resourceVersion=resourceVersion, timeoutSeconds=timeoutSeconds, watch=watch, _mediaType=_mediaType)
Swagger.exec(_ctx, response_stream)
end
function _swaggerinternal_watchAppsV1beta1NamespacedDeploymentList(_api::AppsV1beta1Api, namespace::String; allowWatchBookmarks=nothing, __continue__=nothing, fieldSelector=nothing, labelSelector=nothing, limit=nothing, pretty=nothing, resourceVersion=nothing, timeoutSeconds=nothing, watch=nothing, _mediaType=nothing)
_ctx = Swagger.Ctx(_api.client, "GET", IoK8sApimachineryPkgApisMetaV1WatchEvent, "/apis/apps/v1beta1/watch/namespaces/{namespace}/deployments", ["BearerToken"])
Swagger.set_param(_ctx.path, "namespace", namespace) # type String
Swagger.set_param(_ctx.query, "allowWatchBookmarks", allowWatchBookmarks) # type Bool
Swagger.set_param(_ctx.query, "continue", __continue__) # type String
Swagger.set_param(_ctx.query, "fieldSelector", fieldSelector) # type String
Swagger.set_param(_ctx.query, "labelSelector", labelSelector) # type String
Swagger.set_param(_ctx.query, "limit", limit) # type Int32
Swagger.set_param(_ctx.query, "pretty", pretty) # type String
Swagger.set_param(_ctx.query, "resourceVersion", resourceVersion) # type String
Swagger.set_param(_ctx.query, "timeoutSeconds", timeoutSeconds) # type Int32
Swagger.set_param(_ctx.query, "watch", watch) # type Bool
Swagger.set_header_accept(_ctx, ["application/json", "application/yaml", "application/vnd.kubernetes.protobuf", "application/json;stream=watch", "application/vnd.kubernetes.protobuf;stream=watch"])
Swagger.set_header_content_type(_ctx, (_mediaType === nothing) ? ["*/*"] : [_mediaType])
return _ctx
end
"""
watch individual changes to a list of Deployment. deprecated: use the 'watch' parameter with a list operation instead.
Param: namespace::String (required)
Param: allowWatchBookmarks::Bool
Param: __continue__::String
Param: fieldSelector::String
Param: labelSelector::String
Param: limit::Int32
Param: pretty::String
Param: resourceVersion::String
Param: timeoutSeconds::Int32
Param: watch::Bool
Return: IoK8sApimachineryPkgApisMetaV1WatchEvent
"""
function watchAppsV1beta1NamespacedDeploymentList(_api::AppsV1beta1Api, namespace::String; allowWatchBookmarks=nothing, __continue__=nothing, fieldSelector=nothing, labelSelector=nothing, limit=nothing, pretty=nothing, resourceVersion=nothing, timeoutSeconds=nothing, watch=nothing, _mediaType=nothing)
_ctx = _swaggerinternal_watchAppsV1beta1NamespacedDeploymentList(_api, namespace; allowWatchBookmarks=allowWatchBookmarks, __continue__=__continue__, fieldSelector=fieldSelector, labelSelector=labelSelector, limit=limit, pretty=pretty, resourceVersion=resourceVersion, timeoutSeconds=timeoutSeconds, watch=watch, _mediaType=_mediaType)
Swagger.exec(_ctx)
end
function watchAppsV1beta1NamespacedDeploymentList(_api::AppsV1beta1Api, response_stream::Channel, namespace::String; allowWatchBookmarks=nothing, __continue__=nothing, fieldSelector=nothing, labelSelector=nothing, limit=nothing, pretty=nothing, resourceVersion=nothing, timeoutSeconds=nothing, watch=nothing, _mediaType=nothing)
_ctx = _swaggerinternal_watchAppsV1beta1NamespacedDeploymentList(_api, namespace; allowWatchBookmarks=allowWatchBookmarks, __continue__=__continue__, fieldSelector=fieldSelector, labelSelector=labelSelector, limit=limit, pretty=pretty, resourceVersion=resourceVersion, timeoutSeconds=timeoutSeconds, watch=watch, _mediaType=_mediaType)
Swagger.exec(_ctx, response_stream)
end
function _swaggerinternal_watchAppsV1beta1NamespacedStatefulSet(_api::AppsV1beta1Api, name::String, namespace::String; allowWatchBookmarks=nothing, __continue__=nothing, fieldSelector=nothing, labelSelector=nothing, limit=nothing, pretty=nothing, resourceVersion=nothing, timeoutSeconds=nothing, watch=nothing, _mediaType=nothing)
_ctx = Swagger.Ctx(_api.client, "GET", IoK8sApimachineryPkgApisMetaV1WatchEvent, "/apis/apps/v1beta1/watch/namespaces/{namespace}/statefulsets/{name}", ["BearerToken"])
Swagger.set_param(_ctx.path, "name", name) # type String
Swagger.set_param(_ctx.path, "namespace", namespace) # type String
Swagger.set_param(_ctx.query, "allowWatchBookmarks", allowWatchBookmarks) # type Bool
Swagger.set_param(_ctx.query, "continue", __continue__) # type String
Swagger.set_param(_ctx.query, "fieldSelector", fieldSelector) # type String
Swagger.set_param(_ctx.query, "labelSelector", labelSelector) # type String
Swagger.set_param(_ctx.query, "limit", limit) # type Int32
Swagger.set_param(_ctx.query, "pretty", pretty) # type String
Swagger.set_param(_ctx.query, "resourceVersion", resourceVersion) # type String
Swagger.set_param(_ctx.query, "timeoutSeconds", timeoutSeconds) # type Int32
Swagger.set_param(_ctx.query, "watch", watch) # type Bool
Swagger.set_header_accept(_ctx, ["application/json", "application/yaml", "application/vnd.kubernetes.protobuf", "application/json;stream=watch", "application/vnd.kubernetes.protobuf;stream=watch"])
Swagger.set_header_content_type(_ctx, (_mediaType === nothing) ? ["*/*"] : [_mediaType])
return _ctx
end
"""
watch changes to an object of kind StatefulSet. deprecated: use the 'watch' parameter with a list operation instead, filtered to a single item with the 'fieldSelector' parameter.
Param: name::String (required)
Param: namespace::String (required)
Param: allowWatchBookmarks::Bool
Param: __continue__::String
Param: fieldSelector::String
Param: labelSelector::String
Param: limit::Int32
Param: pretty::String
Param: resourceVersion::String
Param: timeoutSeconds::Int32
Param: watch::Bool
Return: IoK8sApimachineryPkgApisMetaV1WatchEvent
"""
function watchAppsV1beta1NamespacedStatefulSet(_api::AppsV1beta1Api, name::String, namespace::String; allowWatchBookmarks=nothing, __continue__=nothing, fieldSelector=nothing, labelSelector=nothing, limit=nothing, pretty=nothing, resourceVersion=nothing, timeoutSeconds=nothing, watch=nothing, _mediaType=nothing)
_ctx = _swaggerinternal_watchAppsV1beta1NamespacedStatefulSet(_api, name, namespace; allowWatchBookmarks=allowWatchBookmarks, __continue__=__continue__, fieldSelector=fieldSelector, labelSelector=labelSelector, limit=limit, pretty=pretty, resourceVersion=resourceVersion, timeoutSeconds=timeoutSeconds, watch=watch, _mediaType=_mediaType)
Swagger.exec(_ctx)
end
function watchAppsV1beta1NamespacedStatefulSet(_api::AppsV1beta1Api, response_stream::Channel, name::String, namespace::String; allowWatchBookmarks=nothing, __continue__=nothing, fieldSelector=nothing, labelSelector=nothing, limit=nothing, pretty=nothing, resourceVersion=nothing, timeoutSeconds=nothing, watch=nothing, _mediaType=nothing)
_ctx = _swaggerinternal_watchAppsV1beta1NamespacedStatefulSet(_api, name, namespace; allowWatchBookmarks=allowWatchBookmarks, __continue__=__continue__, fieldSelector=fieldSelector, labelSelector=labelSelector, limit=limit, pretty=pretty, resourceVersion=resourceVersion, timeoutSeconds=timeoutSeconds, watch=watch, _mediaType=_mediaType)
Swagger.exec(_ctx, response_stream)
end
function _swaggerinternal_watchAppsV1beta1NamespacedStatefulSetList(_api::AppsV1beta1Api, namespace::String; allowWatchBookmarks=nothing, __continue__=nothing, fieldSelector=nothing, labelSelector=nothing, limit=nothing, pretty=nothing, resourceVersion=nothing, timeoutSeconds=nothing, watch=nothing, _mediaType=nothing)
_ctx = Swagger.Ctx(_api.client, "GET", IoK8sApimachineryPkgApisMetaV1WatchEvent, "/apis/apps/v1beta1/watch/namespaces/{namespace}/statefulsets", ["BearerToken"])
Swagger.set_param(_ctx.path, "namespace", namespace) # type String
Swagger.set_param(_ctx.query, "allowWatchBookmarks", allowWatchBookmarks) # type Bool
Swagger.set_param(_ctx.query, "continue", __continue__) # type String
Swagger.set_param(_ctx.query, "fieldSelector", fieldSelector) # type String
Swagger.set_param(_ctx.query, "labelSelector", labelSelector) # type String
Swagger.set_param(_ctx.query, "limit", limit) # type Int32
Swagger.set_param(_ctx.query, "pretty", pretty) # type String
Swagger.set_param(_ctx.query, "resourceVersion", resourceVersion) # type String
Swagger.set_param(_ctx.query, "timeoutSeconds", timeoutSeconds) # type Int32
Swagger.set_param(_ctx.query, "watch", watch) # type Bool
Swagger.set_header_accept(_ctx, ["application/json", "application/yaml", "application/vnd.kubernetes.protobuf", "application/json;stream=watch", "application/vnd.kubernetes.protobuf;stream=watch"])
Swagger.set_header_content_type(_ctx, (_mediaType === nothing) ? ["*/*"] : [_mediaType])
return _ctx
end
"""
watch individual changes to a list of StatefulSet. deprecated: use the 'watch' parameter with a list operation instead.
Param: namespace::String (required)
Param: allowWatchBookmarks::Bool
Param: __continue__::String
Param: fieldSelector::String
Param: labelSelector::String
Param: limit::Int32
Param: pretty::String
Param: resourceVersion::String
Param: timeoutSeconds::Int32
Param: watch::Bool
Return: IoK8sApimachineryPkgApisMetaV1WatchEvent
"""
function watchAppsV1beta1NamespacedStatefulSetList(_api::AppsV1beta1Api, namespace::String; allowWatchBookmarks=nothing, __continue__=nothing, fieldSelector=nothing, labelSelector=nothing, limit=nothing, pretty=nothing, resourceVersion=nothing, timeoutSeconds=nothing, watch=nothing, _mediaType=nothing)
_ctx = _swaggerinternal_watchAppsV1beta1NamespacedStatefulSetList(_api, namespace; allowWatchBookmarks=allowWatchBookmarks, __continue__=__continue__, fieldSelector=fieldSelector, labelSelector=labelSelector, limit=limit, pretty=pretty, resourceVersion=resourceVersion, timeoutSeconds=timeoutSeconds, watch=watch, _mediaType=_mediaType)
Swagger.exec(_ctx)
end
function watchAppsV1beta1NamespacedStatefulSetList(_api::AppsV1beta1Api, response_stream::Channel, namespace::String; allowWatchBookmarks=nothing, __continue__=nothing, fieldSelector=nothing, labelSelector=nothing, limit=nothing, pretty=nothing, resourceVersion=nothing, timeoutSeconds=nothing, watch=nothing, _mediaType=nothing)
_ctx = _swaggerinternal_watchAppsV1beta1NamespacedStatefulSetList(_api, namespace; allowWatchBookmarks=allowWatchBookmarks, __continue__=__continue__, fieldSelector=fieldSelector, labelSelector=labelSelector, limit=limit, pretty=pretty, resourceVersion=resourceVersion, timeoutSeconds=timeoutSeconds, watch=watch, _mediaType=_mediaType)
Swagger.exec(_ctx, response_stream)
end
function _swaggerinternal_watchAppsV1beta1StatefulSetListForAllNamespaces(_api::AppsV1beta1Api; allowWatchBookmarks=nothing, __continue__=nothing, fieldSelector=nothing, labelSelector=nothing, limit=nothing, pretty=nothing, resourceVersion=nothing, timeoutSeconds=nothing, watch=nothing, _mediaType=nothing)
_ctx = Swagger.Ctx(_api.client, "GET", IoK8sApimachineryPkgApisMetaV1WatchEvent, "/apis/apps/v1beta1/watch/statefulsets", ["BearerToken"])
Swagger.set_param(_ctx.query, "allowWatchBookmarks", allowWatchBookmarks) # type Bool
Swagger.set_param(_ctx.query, "continue", __continue__) # type String
Swagger.set_param(_ctx.query, "fieldSelector", fieldSelector) # type String
Swagger.set_param(_ctx.query, "labelSelector", labelSelector) # type String
Swagger.set_param(_ctx.query, "limit", limit) # type Int32
Swagger.set_param(_ctx.query, "pretty", pretty) # type String
Swagger.set_param(_ctx.query, "resourceVersion", resourceVersion) # type String
Swagger.set_param(_ctx.query, "timeoutSeconds", timeoutSeconds) # type Int32
Swagger.set_param(_ctx.query, "watch", watch) # type Bool
Swagger.set_header_accept(_ctx, ["application/json", "application/yaml", "application/vnd.kubernetes.protobuf", "application/json;stream=watch", "application/vnd.kubernetes.protobuf;stream=watch"])
Swagger.set_header_content_type(_ctx, (_mediaType === nothing) ? ["*/*"] : [_mediaType])
return _ctx
end
"""
watch individual changes to a list of StatefulSet. deprecated: use the 'watch' parameter with a list operation instead.
Param: allowWatchBookmarks::Bool
Param: __continue__::String
Param: fieldSelector::String
Param: labelSelector::String
Param: limit::Int32
Param: pretty::String
Param: resourceVersion::String
Param: timeoutSeconds::Int32
Param: watch::Bool
Return: IoK8sApimachineryPkgApisMetaV1WatchEvent
"""
function watchAppsV1beta1StatefulSetListForAllNamespaces(_api::AppsV1beta1Api; allowWatchBookmarks=nothing, __continue__=nothing, fieldSelector=nothing, labelSelector=nothing, limit=nothing, pretty=nothing, resourceVersion=nothing, timeoutSeconds=nothing, watch=nothing, _mediaType=nothing)
_ctx = _swaggerinternal_watchAppsV1beta1StatefulSetListForAllNamespaces(_api; allowWatchBookmarks=allowWatchBookmarks, __continue__=__continue__, fieldSelector=fieldSelector, labelSelector=labelSelector, limit=limit, pretty=pretty, resourceVersion=resourceVersion, timeoutSeconds=timeoutSeconds, watch=watch, _mediaType=_mediaType)
Swagger.exec(_ctx)
end
function watchAppsV1beta1StatefulSetListForAllNamespaces(_api::AppsV1beta1Api, response_stream::Channel; allowWatchBookmarks=nothing, __continue__=nothing, fieldSelector=nothing, labelSelector=nothing, limit=nothing, pretty=nothing, resourceVersion=nothing, timeoutSeconds=nothing, watch=nothing, _mediaType=nothing)
_ctx = _swaggerinternal_watchAppsV1beta1StatefulSetListForAllNamespaces(_api; allowWatchBookmarks=allowWatchBookmarks, __continue__=__continue__, fieldSelector=fieldSelector, labelSelector=labelSelector, limit=limit, pretty=pretty, resourceVersion=resourceVersion, timeoutSeconds=timeoutSeconds, watch=watch, _mediaType=_mediaType)
Swagger.exec(_ctx, response_stream)
end
export createAppsV1beta1NamespacedControllerRevision, createAppsV1beta1NamespacedDeployment, createAppsV1beta1NamespacedDeploymentRollback, createAppsV1beta1NamespacedStatefulSet, deleteAppsV1beta1CollectionNamespacedControllerRevision, deleteAppsV1beta1CollectionNamespacedDeployment, deleteAppsV1beta1CollectionNamespacedStatefulSet, deleteAppsV1beta1NamespacedControllerRevision, deleteAppsV1beta1NamespacedDeployment, deleteAppsV1beta1NamespacedStatefulSet, getAppsV1beta1APIResources, listAppsV1beta1ControllerRevisionForAllNamespaces, listAppsV1beta1DeploymentForAllNamespaces, listAppsV1beta1NamespacedControllerRevision, listAppsV1beta1NamespacedDeployment, listAppsV1beta1NamespacedStatefulSet, listAppsV1beta1StatefulSetForAllNamespaces, patchAppsV1beta1NamespacedControllerRevision, patchAppsV1beta1NamespacedDeployment, patchAppsV1beta1NamespacedDeploymentScale, patchAppsV1beta1NamespacedDeploymentStatus, patchAppsV1beta1NamespacedStatefulSet, patchAppsV1beta1NamespacedStatefulSetScale, patchAppsV1beta1NamespacedStatefulSetStatus, readAppsV1beta1NamespacedControllerRevision, readAppsV1beta1NamespacedDeployment, readAppsV1beta1NamespacedDeploymentScale, readAppsV1beta1NamespacedDeploymentStatus, readAppsV1beta1NamespacedStatefulSet, readAppsV1beta1NamespacedStatefulSetScale, readAppsV1beta1NamespacedStatefulSetStatus, replaceAppsV1beta1NamespacedControllerRevision, replaceAppsV1beta1NamespacedDeployment, replaceAppsV1beta1NamespacedDeploymentScale, replaceAppsV1beta1NamespacedDeploymentStatus, replaceAppsV1beta1NamespacedStatefulSet, replaceAppsV1beta1NamespacedStatefulSetScale, replaceAppsV1beta1NamespacedStatefulSetStatus, watchAppsV1beta1ControllerRevisionListForAllNamespaces, watchAppsV1beta1DeploymentListForAllNamespaces, watchAppsV1beta1NamespacedControllerRevision, watchAppsV1beta1NamespacedControllerRevisionList, watchAppsV1beta1NamespacedDeployment, watchAppsV1beta1NamespacedDeploymentList, watchAppsV1beta1NamespacedStatefulSet, watchAppsV1beta1NamespacedStatefulSetList, watchAppsV1beta1StatefulSetListForAllNamespaces
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] | 3.097005 | 40,472 |
""" Solve the classical GP Regression (especially valid for augmented likelihoods) """
mutable struct Analytic{T<:Real} <: Inference{T}
ϵ::T #Convergence criteria
nIter::Integer #Number of steps performed
Stochastic::Bool #Use of mini-batches
nSamples::Int64
nSamplesUsed::Int64 #Size of mini-batches
MBIndices::Vector{Int64} #Indices of the minibatch
ρ::T #Stochastic Coefficient
HyperParametersUpdated::Bool #To know if the inverse kernel matrix must updated
xview::SubArray{T,2,Matrix{T}}
yview::SubArray
function Analytic{T}(ϵ::T,nIter::Integer,Stochastic::Bool,nSamples::Integer,MBIndices::AbstractVector,ρ::T,flag::Bool) where T
return new{T}(ϵ,nIter,Stochastic,nSamples,nSamples,MBIndices,ρ,flag)
end
end
"""`Analytic(;ϵ::T=1e-5)`
Analytic inference structure for the classical GP regression
**Keyword arguments**
- `ϵ::T` : convergence criteria, which can be user defined
"""
function Analytic(;ϵ::T=1e-5) where {T<:Real}
Analytic{T}(ϵ,0,false,1,collect(1:1),1.0,true)
end
function Base.show(io::IO,inference::Analytic{T}) where T
print(io,"Analytic Inference")
end
function init_inference(inference::Analytic{T},nLatent::Integer,nFeatures::Integer,nSamples::Integer,nSamplesUsed::Integer) where {T<:Real}
inference.nSamples = nSamples
inference.nSamplesUsed = nSamples
inference.MBIndices = 1:nSamples
inference.ρ = one(T)
return inference
end
function analytic_updates!(model::GP{T}) where {T}
if !isnothing(model.likelihood.opt_noise)
model.likelihood.σ² = mean(abs2,model.y.-first(model.f).μ)
end
model.f[1].μ = first(model.f).K\(model.y - first(model.f).μ₀(model.X))
end
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] | 2.535022 | 671 |
module ComputeManager
using Cairn.Client
using Excavator: Job
function run(job::t)
# TODO keep track of ComputeNodes
# start
# run the job
end
immutable MapJob
dfs::Vector{Cairn.Client.t}
executable::Job.Key
files::Cairn.RPC.KeySpan
results_dir::Job.Key
done::Job.Key # Special 0-replication file!
end
immutable ReduceJob
dfs::Vector{Cairn.Client.t}
executable::Job.Key
files::Cairn.RPC.KeySpan
results_dir::Job.Key
end
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] | 2.322115 | 208 |
# https://adventofcode.com/2021/day/15
using AdventOfCode
using Graphs
using SimpleWeightedGraphs
input = split.(readlines("2021/data/day_15.txt"),"") |> Base.Fix1(reduce,hcat) .|> parse
function makegraph(mat)
g=SimpleWeightedGraph(Graphs.SimpleGraphs.grid(size(mat)), 1)
for edge in edges(g)
w=mat[src(edge)]+mat[dst(edge)]
add_edge!(g,src(edge),dst(edge),w)
end
g
end
function part_1(input)
g=makegraph(input)
ds=dijkstra_shortest_paths(g,1)
(ds.dists[end]-input[begin]+input[end])÷2
end
function part_2(input)
fullmap=(repeat(input,5,5).+
repeat((0:4).+(0:4)',inner=size(input)).-1) .%9 .+1
g=makegraph(fullmap)
ds=dijkstra_shortest_paths(g,1)
(ds.dists[end]-input[begin]+input[end])÷2
end
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] | 2.11326 | 362 |
## dew pressure solver
function x0_dew_pressure(model::EoSModel,T,y)
#TODO
#on sufficiently large temps,
#the joule-thompson inversion occurs
#making the virial coeff positive
#on those cases, use an strategy that supposes pure gas on that side
#Pbi = inf
#xi = 0
#check each T with T_scale, if treshold is over, replace Pi with inf
pure = split_model(model)
crit = crit_pure.(pure)
T_c = [tup[1] for tup in crit]
V_c = [tup[3] for tup in crit]
_0 = zero(T+first(y))
nan = _0/_0
sat_nan = (nan,nan,nan)
replaceP = ifelse.(T_c .< T,true,false)
eachx = eachcol(Diagonal(ones(eltype(y),length(y))))
# Bi = second_virial_coefficient.(model,T,eachx)
#using P_B(2B) as a sat aproximation
#z = 1 + B/v
#P_B = RT/v(1+B/v)
#P_B(2B) = -RT/2B(1-B/2B)
#P_B(2B) = -0.25*RT/B
sat = [if !replaceP[i] saturation_pressure(pure[i],T) else sat_nan end for i in 1:length(pure)]
P_sat = [tup[1] for tup in sat]
V_l_sat = [tup[2] for tup in sat]
V_v_sat = [tup[3] for tup in sat]
# P_Bi = @. -0.25*R̄*T/Bi
#=xP0 = yP
#dot(x,P0) = P
P = dot(x,P0)
=#
P⁻¹ = zero(T)
V0_l = zero(T)
V0_v = zero(T)
Pi = zero(y)
for i in 1:length(y)
if !replaceP[i]
Pi[i] = P_sat[i][1]
P⁻¹+=y[i]/Pi[i]
V0_v += y[i]*V_v_sat[i]
else
Pi[i] = pressure(pure[i],V_c[i],T)
P⁻¹+=y[i]/Pi[i]
V0_v += y[i]*V_c[i]*1.2
end
end
#@show P_Bi
#P = dot(x,P_Bi)
P = 1/P⁻¹
x = @. y*P/Pi
xsum = 1/∑(x)
x = x.*xsum
for i in 1:length(y)
if !replaceP[i]
V0_l += x[i]*V_l_sat[i]
else
V0_l += x[i]*V_c[i]
end
end
prepend!(x,log10.([V0_l,V0_v]))
return x
end
function dew_pressure(model::EoSModel, T, y; v0 =nothing)
TYPE = promote_type(eltype(T),eltype(y))
# lb_v = lb_volume(model,x)
ts = T_scales(model,y)
pmix = p_scale(model,y)
if v0 === nothing
v0 = x0_dew_pressure(model,T,y)
end
len = length(v0[1:end-1])
#xcache = zeros(eltype(x0),len)
Fcache = zeros(eltype(v0[1:end-1]),len)
f!(F,z) = Obj_dew_pressure(model, F, T, exp10(z[1]), exp10(z[2]), z[3:end],y,ts,pmix)
r =Solvers.nlsolve(f!,v0[1:end-1],LineSearch(Newton()))
sol = Solvers.x_sol(r)
v_l = exp10(sol[1])
v_v = exp10(sol[2])
x = FractionVector(sol[3:end])
P_sat = pressure(model,v_v,T,y)
return (P_sat, v_l, v_v, x)
end
function Obj_dew_pressure(model::EoSModel, F, T, v_l, v_v, x, y,ts,ps)
x = FractionVector(x) #julia magic, check misc.jl
μ_l = VT_chemical_potential(model,v_l,T,x)
μ_v = VT_chemical_potential(model,v_v,T,y)
p_l = pressure(model,v_l,T,x)
p_v = pressure(model,v_v,T,y)
for i in 1:length(x)
F[i] = (μ_l[i]-μ_v[i])/(R̄*ts[i])
end
F[end] = (p_l-p_v)/ps
return F
end
function dew_temperature(model,p,y)
f(z) = Obj_dew_temperature(model,z,p,y)
pure = split_model(model)
sat = saturation_temperature.(pure,p)
Ti = zero(y)
for i ∈ 1:length(y)
if isnan(sat[i][1])
Tc,pc,vc = crit_pure(pure[i])
g(x) = p-pressure(pure[i],vc,x,[1.])
Ti[i] = Roots.find_zero(g,(Tc))
else
Ti[i] = sat[i][1]
end
end
T = Roots.find_zero(f,sum(Ti)/length(y))
p,v_l,v_v,x = dew_pressure(model,T,y)
return T,v_l,v_v,x
end
function Obj_dew_temperature(model,T,p,y)
p̃,v_l,v_v,y = dew_pressure(model,T,y)
return p̃-p
end
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] | 1.742154 | 2,071 |
@static if VERSION < v"0.7.0-"
using Base.Test
else
using Test
import Pkg
end
using InteractiveCodeSearch
macro test_nothrow(ex)
quote
@test begin
$(esc(ex))
true
end
end
end
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