Datasets:

anton-l

/

python_sample_10k

like 0

SyuziH/HTI-3-Group-2-Syuzi-Harutyunyan

a39282edd778a2bd2cb2d7576bae217257f9b47f

8a55474e5a4297ef2e43e887eb1fa601855bd06c

/Homework 3/is_prime.py

4a2a7bf99860b74b3b56e9c207beb59f35245677

no_license

https://github.com/SyuziH/HTI-3-Group-2-Syuzi-Harutyunyan

ae91410f61b5c177e6b9f6f1842060cf6e0853b8

dad4b9dafc77d41e0fba14ed3e87f17b5fc549d4

refs/heads/master

def is_prime(num): if num > 1: for i in range(2, num): if (num % i == 0): print('No') break else: print('Yes') else: print('Is not a prime number') number = int(input('Enter the number ')) is_prime(number)

UTF-8

Python

py

is_prime.py

masary2989/EC_site_webapp

f9c23434d0ebd66f4d69c1ba289027480d2faa55

23541da0aae0f5040cb47b1a55c604c05d4418cd

/eth_ec_server/ec_site/migrations/0001_initial.py

1b879e3b5920e4d88e52bb669dc94a4d667dffca

no_license

https://github.com/masary2989/EC_site_webapp

17f30aafcb9d7747af60d324f4c7e61f5e251ba7

a9f1c7bb36eb6855bcfdec78d484c368d89e9c2a

refs/heads/master

Visual Basic

# Generated by Django 2.1.4 on 2018-12-18 05:27 from django.db import migrations, models import django.db.models.deletion class Migration(migrations.Migration): initial = True dependencies = [ ] operations = [ migrations.CreateModel( name='Address', fields=[ ('id', models.AutoField(auto_created=True, primary_key=True, serialize=False, verbose_name='ID')), ('address', models.CharField(max_length=100)), ('message', models.CharField(max_length=300)), ('created_at', models.DateTimeField(auto_now_add=True)), ('updated_at', models.DateTimeField(auto_now_add=True)), ], ), migrations.CreateModel( name='order', fields=[ ('id', models.AutoField(auto_created=True, primary_key=True, serialize=False, verbose_name='ID')), ('contract_tx', models.BigIntegerField()), ('message', models.CharField(max_length=300)), ('payment', models.PositiveSmallIntegerField()), ('created_at', models.DateTimeField(auto_now_add=True)), ('updated_at', models.DateTimeField(auto_now_add=True)), ], ), migrations.CreateModel( name='Product', fields=[ ('id', models.AutoField(auto_created=True, primary_key=True, serialize=False, verbose_name='ID')), ('name', models.CharField(max_length=100)), ('message', models.CharField(max_length=300)), ('image', models.ImageField(upload_to='ec_site/uploads/%Y/%m/%d/')), ('price', models.PositiveSmallIntegerField()), ('created_at', models.DateTimeField(auto_now_add=True)), ('updated_at', models.DateTimeField(auto_now_add=True)), ], ), migrations.CreateModel( name='User', fields=[ ('id', models.AutoField(auto_created=True, primary_key=True, serialize=False, verbose_name='ID')), ('name', models.CharField(max_length=100)), ('email', models.EmailField(max_length=254)), ('message', models.CharField(max_length=300)), ('created_at', models.DateTimeField(auto_now_add=True)), ('updated_at', models.DateTimeField(auto_now_add=True)), ], ), migrations.AddField( model_name='order', name='pid', field=models.ManyToManyField(to='ec_site.Product'), ), migrations.AddField( model_name='order', name='uid', field=models.ForeignKey(on_delete=django.db.models.deletion.CASCADE, to='ec_site.User'), ), migrations.AddField( model_name='address', name='uid', field=models.ForeignKey(on_delete=django.db.models.deletion.CASCADE, to='ec_site.User'), ), ]

UTF-8

Python

py

0001_initial.py

Jazminnava/Mundo-de-productos

ec39a993722a60393fbc6c3739eddbb0abfbb643

c62e1758762440c94098271d77c03482895a25d1

/migrations/versions/ef581bcb9460_inital_mirtaions.py

82ca82bb36af2a4da0af20e66f3ec5708694a2fc

no_license

https://github.com/Jazminnava/Mundo-de-productos

548e61d9a21e67388f9bbe1509c2b0ca94ef9ee4

8748587d62a4cbafd01e20f4e7a1a63b95fb2e9e

refs/heads/master

"""inital mirtaions Revision ID: ef581bcb9460 Revises: Create Date: 2020-08-05 01:02:02.400739 """ from alembic import op import sqlalchemy as sa # revision identifiers, used by Alembic. revision = 'ef581bcb9460' down_revision = None branch_labels = None depends_on = None def upgrade(): # ### commands auto generated by Alembic - please adjust! ### op.create_table('administrador', sa.Column('id', sa.Integer(), nullable=False), sa.Column('name', sa.String(length=80), nullable=False), sa.Column('apellidop', sa.String(length=80), nullable=False), sa.Column('apellidom', sa.String(length=80), nullable=False), sa.Column('edad', sa.String(length=80), nullable=False), sa.Column('telefono', sa.String(length=80), nullable=False), sa.Column('calle', sa.String(length=80), nullable=False), sa.Column('colonia', sa.String(length=80), nullable=False), sa.Column('numdire', sa.String(length=70), nullable=False), sa.Column('image_1', sa.String(length=150), nullable=False), sa.PrimaryKeyConstraint('id') ) op.create_table('brand', sa.Column('id', sa.Integer(), nullable=False), sa.Column('name', sa.String(length=40), nullable=False), sa.PrimaryKeyConstraint('id'), sa.UniqueConstraint('name') ) op.create_table('category', sa.Column('id', sa.Integer(), nullable=False), sa.Column('name', sa.String(length=40), nullable=False), sa.PrimaryKeyConstraint('id'), sa.UniqueConstraint('name') ) op.create_table('cliente', sa.Column('id', sa.Integer(), nullable=False), sa.Column('name', sa.String(length=80), nullable=False), sa.Column('apellidop', sa.String(length=80), nullable=False), sa.Column('apellidom', sa.String(length=80), nullable=False), sa.Column('edad', sa.String(length=80), nullable=False), sa.Column('telefono', sa.String(length=80), nullable=False), sa.Column('calle', sa.String(length=80), nullable=False), sa.Column('colonia', sa.String(length=80), nullable=False), sa.Column('numdire', sa.String(length=70), nullable=False), sa.Column('image_1', sa.String(length=150), nullable=False), sa.PrimaryKeyConstraint('id') ) op.create_table('dueño', sa.Column('id', sa.Integer(), nullable=False), sa.Column('name', sa.String(length=80), nullable=False), sa.Column('apellidop', sa.String(length=80), nullable=False), sa.Column('apellidom', sa.String(length=80), nullable=False), sa.Column('edad', sa.String(length=80), nullable=False), sa.Column('telefono', sa.String(length=80), nullable=False), sa.Column('calle', sa.String(length=80), nullable=False), sa.Column('colonia', sa.String(length=80), nullable=False), sa.Column('numdire', sa.String(length=70), nullable=False), sa.Column('image_1', sa.String(length=150), nullable=False), sa.PrimaryKeyConstraint('id') ) op.create_table('register', sa.Column('id', sa.Integer(), nullable=False), sa.Column('name', sa.String(length=50), nullable=True), sa.Column('f_name', sa.String(length=50), nullable=True), sa.Column('username', sa.String(length=50), nullable=True), sa.Column('email', sa.String(length=50), nullable=True), sa.Column('password', sa.String(length=200), nullable=True), sa.Column('state', sa.String(length=50), nullable=True), sa.Column('city', sa.String(length=50), nullable=True), sa.Column('contact', sa.String(length=50), nullable=True), sa.Column('address', sa.String(length=50), nullable=True), sa.Column('zipcode', sa.String(length=50), nullable=True), sa.Column('profile', sa.String(length=200), nullable=True), sa.Column('date_created', sa.DateTime(), nullable=False), sa.PrimaryKeyConstraint('id'), sa.UniqueConstraint('email'), sa.UniqueConstraint('username') ) op.create_table('user', sa.Column('id', sa.Integer(), nullable=False), sa.Column('name', sa.String(length=30), nullable=False), sa.Column('username', sa.String(length=80), nullable=False), sa.Column('email', sa.String(length=120), nullable=False), sa.Column('password', sa.String(length=180), nullable=False), sa.Column('profile', sa.String(length=180), nullable=False), sa.PrimaryKeyConstraint('id'), sa.UniqueConstraint('email'), sa.UniqueConstraint('username') ) op.create_table('vendedor', sa.Column('id', sa.Integer(), nullable=False), sa.Column('name', sa.String(length=80), nullable=False), sa.Column('apellidop', sa.String(length=80), nullable=False), sa.Column('apellidom', sa.String(length=80), nullable=False), sa.Column('edad', sa.String(length=80), nullable=False), sa.Column('telefono', sa.String(length=80), nullable=False), sa.Column('calle', sa.String(length=80), nullable=False), sa.Column('colonia', sa.String(length=80), nullable=False), sa.Column('numdire', sa.String(length=70), nullable=False), sa.Column('image_1', sa.String(length=150), nullable=False), sa.PrimaryKeyConstraint('id') ) op.create_table('addproduct', sa.Column('id', sa.Integer(), nullable=False), sa.Column('name', sa.String(length=80), nullable=False), sa.Column('price', sa.Numeric(precision=10, scale=2), nullable=False), sa.Column('discount', sa.Integer(), nullable=False), sa.Column('stock', sa.Integer(), nullable=False), sa.Column('colors', sa.Text(), nullable=False), sa.Column('desc', sa.Text(), nullable=False), sa.Column('pub_date', sa.DateTime(), nullable=False), sa.Column('brand_id', sa.Integer(), nullable=False), sa.Column('category_id', sa.Integer(), nullable=False), sa.Column('image_1', sa.String(length=150), nullable=False), sa.Column('image_2', sa.String(length=150), nullable=False), sa.Column('image_3', sa.String(length=150), nullable=False), sa.ForeignKeyConstraint(['brand_id'], ['brand.id'], ), sa.ForeignKeyConstraint(['category_id'], ['category.id'], ), sa.PrimaryKeyConstraint('id') ) op.create_table('venta', sa.Column('id', sa.Integer(), nullable=False), sa.Column('name', sa.String(length=80), nullable=False), sa.Column('precio', sa.String(length=80), nullable=False), sa.Column('total', sa.String(length=80), nullable=False), sa.Column('cliente_id', sa.Integer(), nullable=False), sa.Column('vendedor_id', sa.Integer(), nullable=False), sa.Column('addproduct_id', sa.Integer(), nullable=False), sa.ForeignKeyConstraint(['addproduct_id'], ['addproduct.id'], ), sa.ForeignKeyConstraint(['cliente_id'], ['cliente.id'], ), sa.ForeignKeyConstraint(['vendedor_id'], ['vendedor.id'], ), sa.PrimaryKeyConstraint('id') ) # ### end Alembic commands ### def downgrade(): # ### commands auto generated by Alembic - please adjust! ### op.drop_table('venta') op.drop_table('addproduct') op.drop_table('vendedor') op.drop_table('user') op.drop_table('register') op.drop_table('dueño') op.drop_table('cliente') op.drop_table('category') op.drop_table('brand') op.drop_table('administrador') # ### end Alembic commands ###

UTF-8

Python

py

ef581bcb9460_inital_mirtaions.py

amkalsi/cmssw

5d9bb25a263db52197a1f1b04574bc5af57da158

006ff11fd8cfd5406c6f4318f1bafa1542095f2a

/SLHCUpgradeSimulations/Geometry/python/fakeConditions_Phase1_cff.py

105dcbf9971250dc22709c419f43bebd6ea7d0f6

permissive

https://github.com/amkalsi/cmssw

8ac5f481c7d7263741b5015381473811c59ac3b1

ad0f69098dfbe449ca0570fbcf6fcebd6acc1154

refs/heads/CMSSW_7_4_X

Apache-2.0

import FWCore.ParameterSet.Config as cms siPixelFakeGainOfflineESSource = cms.ESSource("SiPixelFakeGainOfflineESSource", file = cms.FileInPath('SLHCUpgradeSimulations/Geometry/data/PhaseI/EmptyPixelSkimmedGeometry_phase1.txt') ) es_prefer_fake_gain = cms.ESPrefer("SiPixelFakeGainOfflineESSource","siPixelFakeGainOfflineESSource") from CalibTracker.SiStripESProducers.fake.SiStripNoisesFakeESSource_cfi import * SiStripNoisesGenerator.NoiseStripLengthSlope=cms.vdouble(51.) #dec mode SiStripNoisesGenerator.NoiseStripLengthQuote=cms.vdouble(630.) siStripNoisesFakeESSource = cms.ESSource("SiStripNoisesFakeESSource") es_prefer_fake_strip_noise = cms.ESPrefer("SiStripNoisesFakeESSource", "siStripNoisesFakeESSource") from CalibTracker.SiStripESProducers.fake.SiStripQualityFakeESSource_cfi import * siStripQualityFakeESSource = cms.ESSource("SiStripQualityFakeESSource") es_prefer_fake_strip_quality = cms.ESPrefer("SiStripQualityFakeESSource", "siStripQualityFakeESSource") from CalibTracker.SiStripESProducers.fake.SiStripPedestalsFakeESSource_cfi import * siStripPedestalsFakeESSource = cms.ESSource("SiStripPedestalsFakeESSource") es_prefer_fake_strip_pedestal = cms.ESPrefer("SiStripPedestalsFakeESSource", "siStripPedestalsFakeESSource") from CalibTracker.SiStripESProducers.fake.SiStripLorentzAngleFakeESSource_cfi import * siStripLorentzAngleFakeESSource = cms.ESSource("SiStripLorentzAngleFakeESSource") es_prefer_fake_strip_LA = cms.ESPrefer("SiStripLorentzAngleFakeESSource", "siStripLorentzAngleFakeESSource") siStripLorentzAngleSimFakeESSource = cms.ESSource("SiStripLorentzAngleSimFakeESSource") es_prefer_fake_strip_LA_sim = cms.ESPrefer("SiStripLorentzAngleSimFakeESSource", "siStripLorentzAngleSimFakeESSource") from CalibTracker.SiStripESProducers.fake.SiStripApvGainFakeESSource_cfi import * SiStripApvGainGenerator.MeanGain=cms.double(1.0) SiStripApvGainGenerator.SigmaGain=cms.double(0.0) SiStripApvGainGenerator.genMode = cms.string("default") myStripApvGainFakeESSource = cms.ESSource("SiStripApvGainFakeESSource") es_prefer_myStripApvGainFakeESSource = cms.ESPrefer("SiStripApvGainFakeESSource", "myStripApvGainFakeESSource") myStripApvGainSimFakeESSource = cms.ESSource("SiStripApvGainSimFakeESSource") es_prefer_myStripApvGainSimFakeESSource = cms.ESPrefer("SiStripApvGainSimFakeESSource", "myStripApvGainSimFakeESSource") from CalibTracker.SiStripESProducers.fake.SiStripThresholdFakeESSource_cfi import * siStripThresholdFakeESSource = cms.ESSource("SiStripThresholdFakeESSource") es_prefer_fake_strip_threshold = cms.ESPrefer("SiStripThresholdFakeESSource", "siStripThresholdFakeESSource") # from Geometry.TrackerGeometryBuilder.trackerGeometry_cfi import * Double check this later # TrackerDigiGeometryESModule.applyAlignment = False from RecoTracker.MeasurementDet.MeasurementTrackerESProducer_cfi import * MeasurementTracker.inactiveStripDetectorLabels = cms.VInputTag() MeasurementTracker.UseStripModuleQualityDB = cms.bool(False) MeasurementTracker.UseStripAPVFiberQualityDB = cms.bool(False) from RecoVertex.BeamSpotProducer.BeamSpotFakeParameters_cfi import * BeamSpotFakeConditions.X0 = cms.double(0.0) BeamSpotFakeConditions.Y0 = cms.double(0.0) BeamSpotFakeConditions.Z0 = cms.double(0.0) BeamSpotFakeConditions.dxdz = cms.double(0.0) BeamSpotFakeConditions.dydz = cms.double(0.0) BeamSpotFakeConditions.sigmaZ = cms.double(5.3) BeamSpotFakeConditions.widthX = cms.double(0.0015) BeamSpotFakeConditions.widthY = cms.double(0.0015) BeamSpotFakeConditions.emittanceX = cms.double(0.) BeamSpotFakeConditions.emittanceY = cms.double(0.) BeamSpotFakeConditions.betaStar = cms.double(0.) BeamSpotFakeConditions.errorX0 = cms.double(0.00002) BeamSpotFakeConditions.errorY0 = cms.double(0.00002) BeamSpotFakeConditions.errorZ0 = cms.double(0.04000) BeamSpotFakeConditions.errordxdz = cms.double(0.0) BeamSpotFakeConditions.errordydz = cms.double(0.0) BeamSpotFakeConditions.errorSigmaZ = cms.double(0.03000) BeamSpotFakeConditions.errorWidth = cms.double(0.00003) es_prefer_beamspot = cms.ESPrefer("BeamSpotFakeConditions","") from SimGeneral.TrackingAnalysis.trackingParticles_cfi import * mergedtruth.volumeRadius = cms.double(100.0) mergedtruth.volumeZ = cms.double(900.0) mergedtruth.discardOutVolume = cms.bool(True) #from Geometry.TrackerNumberingBuilder.pixelSLHCGeometryConstants_cfi import * from Geometry.TrackerGeometryBuilder.idealForDigiTrackerSLHCGeometry_cff import *

UTF-8

Python

py

fakeConditions_Phase1_cff.py

dkeefe3773/pong-rl

e3844b275290147c174b2ea4bc88e34c90d23451

541222c60bd307affe8bf54a1427f148f2e8d3a1

/apps/game_render_test.py

9e053c6b237b8414099c39ceb80546bde09da625

permissive

https://github.com/dkeefe3773/pong-rl

e9b06bc1412b489ecb42d0ed2e3e5d612348f8cd

e0d548267d7e0ca1b8690224cfd827af8ff571ab

refs/heads/master

MIT

Python

import time from gamerender.pongrenders import DefaultPongRenderer from injections import providers from proto_gen.gamemaster_pb2 import PlayerIdentifier, PaddleType def test_game_render(): player_left_identifier = PlayerIdentifier(player_name="LEFT_PLAYER", paddle_strategy_name="LEFT_STRATEGY", paddle_type=PaddleType.LEFT) player_right_identifier = PlayerIdentifier(player_name="RIGHT_PLAYER", paddle_strategy_name="RIGHT_STRATEGY", paddle_type=PaddleType.RIGHT) pong_renderer: DefaultPongRenderer = providers.GameRendererProviders.pong_renderer() pong_renderer.register_player(player_left_identifier) time.sleep(1) pong_renderer.register_player(player_right_identifier) time.sleep(1) pong_renderer.start_game() if __name__ == "__main__": test_game_render()

UTF-8

Python

py

game_render_test.py

asmirnov69/pybx

0f190925d30a1873d02f85c299e96f2797ac76d9

732a541fd311256d1468e2ad50d8d11e27fe0a15

/src/libpybx-py/codegen_cpp.py

4cd01e20232ee5e6c3cb0e02aff98cfa7c5b502f

no_license

https://github.com/asmirnov69/pybx

1ff929824f059a95dbd7ca4a2fe3a59fd8eeed39

e98db07297b26f0d477ef4f28894573f08c967a6

refs/heads/master

import ipdb import os.path def generate_prolog(source_pybx_fn, out_fd): macro_lock_s = os.path.basename(source_pybx_fn).split(".")[0].upper() prolog_code = f"""// -*- c++ -*- // generated code: source - {source_pybx_fn} #ifndef __{macro_lock_s}_STUBS_HH__ #define __{macro_lock_s}_STUBS_HH__ #define TOKENPASTE(x, y) x ## y #define TOKENPASTE2(x, y) TOKENPASTE(x, y) #define UNIQUE static int TOKENPASTE2(Unique_, __LINE__) #include <memory> #include <string> #include <stdexcept> using namespace std; #include <kvan/json-io.h> #include <libpybx-cpp/communicator.h> #include <libpybx-cpp/proto.h> #include <libpybx-cpp/remote-methods.h> """ print(prolog_code, file = out_fd) def generate_epilog(out_fd): print("#endif", file = out_fd) def get_cpp_namespace(identifier): return "pybx::" + identifier def generate_struct_def(struct_def, out_fd): # struct def #ipdb.set_trace() cpp_namespace = get_cpp_namespace(struct_def.def_type.__module__) print(f"namespace {cpp_namespace} {{", file = out_fd) print(f"struct {struct_def.name} {{", file = out_fd) for m_def in struct_def.fields: #ipdb.set_trace() m_cpp_name = m_def.get_member_name() m_cpp_type = m_def.get_member_type().get_cpp_code_name() print(f" {m_cpp_type} {m_cpp_name};", file = out_fd); print("};\n}", file = out_fd) #get_struct_descriptor print(f"template <> inline StructDescriptor get_struct_descriptor<{cpp_namespace}::{struct_def.name}>()", file = out_fd) print("{", file = out_fd) print(" static const StructDescriptor sd = {", file = out_fd) for m_def in struct_def.fields: m_cpp_name = m_def.get_member_name() print(f" make_member_descriptor(\"{m_cpp_name}\", &{cpp_namespace}::{struct_def.name}::{m_cpp_name}),", file = out_fd) print(" };", file = out_fd) print(" return sd;", file = out_fd) print("}", file = out_fd) def generate_enum_def(enum_def, out_fd): #enum def #ipdb.set_trace() cpp_namespace = get_cpp_namespace(enum_def.def_type.__module__) print(f"namespace {cpp_namespace} {{", file = out_fd) print(f"enum class {enum_def.name} {{", file = out_fd); for m_name, m_value in zip(enum_def.members, enum_def.member_values): print(f"{m_name} = {m_value},", file = out_fd) print("};", file = out_fd) print(f"}}", file = out_fd) # get_enum_value_string print(f"template <> inline std::string get_enum_value_string<{cpp_namespace}::{enum_def.name}>({cpp_namespace}::{enum_def.name} v) {{", file = out_fd) print(" std::string ret;", file = out_fd) print(" switch (v) {", file = out_fd) for m_name, m_value in zip(enum_def.members, enum_def.member_values): print(f" case {cpp_namespace}::{enum_def.name}::{m_name}: ret = \"{m_name}\"; break;", file = out_fd) print(" }", file = out_fd) print(" return ret;", file = out_fd) print("}", file = out_fd) # set_enum_value print(f"template <> inline void set_enum_value<{cpp_namespace}::{enum_def.name}>({cpp_namespace}::{enum_def.name}* v, const std::string& new_v)", file = out_fd) print("{", file = out_fd) m_name = enum_def.members[0] print(f" if (new_v == \"{m_name}\") *v = {cpp_namespace}::{enum_def.name}::{m_name};", file = out_fd) for m_name in enum_def.members[1:]: print(f" else if (new_v == \"{m_name}\") *v = {cpp_namespace}::{enum_def.name}::{m_name};", file = out_fd) print(" else {", file = out_fd) print(" std::ostringstream m;", file = out_fd) print(f" m << \"set_enum_value for {enum_def.name}: unknown string \" << new_v;", file = out_fd) print(" throw runtime_error(m.str());", file = out_fd) print(" }", file = out_fd) print("}", file = out_fd) def generate_interface_client_forward_declarations(module_def, out_fd): cpp_namespace = get_cpp_namespace(module_def.name) print(f"namespace {cpp_namespace} {{", file = out_fd) for interface_def in module_def.interfaces: print(f"class {interface_def.name}_rop;", file = out_fd) print("}", file = out_fd) def generate_interface_client_declarations(interface_def, out_fd): cpp_namespace = get_cpp_namespace(interface_def.def_type.__module__) class_name = interface_def.name + "_rop" print(f"namespace {cpp_namespace} {{", file = out_fd) print(f"class {class_name} {{", file = out_fd) print("private:", file = out_fd) print(" ::pybx::Communicator* comm{nullptr};", file = out_fd) print(" std::shared_ptr<ix::WebSocket> ws;", file = out_fd) print("public:", file = out_fd) print(" bool oneway{false};", file = out_fd) print(" std::string object_id;", file = out_fd) print(f" std::string __interface_type{{\"{cpp_namespace}.{interface_def.name}\"}};", file = out_fd) print(f" {class_name}();", file = out_fd) print(f" {class_name}(::pybx::Communicator* comm, std::shared_ptr<ix::WebSocket> ws, const std::string& ws_url, const std::string& object_id);", file = out_fd) print(f" {class_name}(::pybx::Communicator* comm, const std::string& object_id);", file = out_fd) print(f" void activate(::pybx::Communicator* comm, std::shared_ptr<ix::WebSocket> ws);", file = out_fd) for m_def in interface_def.methods: m_cpp_ret_type = m_def.get_method_return_type().get_cpp_code_name() m_args_l = [] for t, n in zip(m_def.get_method_arg_types(), m_def.get_method_args()): m_args_l.append(t.get_cpp_code_name() + " " + n) m_args = ", ".join(m_args_l) print(f" {m_cpp_ret_type} {m_def.name}({m_args});", file = out_fd) print(f"}};", file = out_fd) print(f"}}", file = out_fd) # get_struct_descriptor for rop class print(f"template <> inline StructDescriptor get_struct_descriptor<{cpp_namespace}::{class_name}>()", file = out_fd) print("{", file = out_fd) print(" static const StructDescriptor sd = {", file = out_fd) print(f" make_member_descriptor(\"object_id\", &{cpp_namespace}::{class_name}::object_id),", file = out_fd) print(f" make_member_descriptor(\"__interface_type\", &{cpp_namespace}::{class_name}::__interface_type),", file = out_fd) print(" };", file = out_fd) print(" return sd;", file = out_fd) print("}", file = out_fd) def generate_interface_server_declarations(interface_def, out_fd): cpp_namespace = get_cpp_namespace(interface_def.def_type.__module__) print(f"namespace {cpp_namespace} {{", file = out_fd) print(f"class {interface_def.name} : public ::pybx::Object {{", file = out_fd) print("public:", file = out_fd) print(f" typedef {interface_def.name}_rop rop_t;", file = out_fd) #ipdb.set_trace() for m_def in interface_def.methods: m_cpp_ret_type = m_def.get_method_return_type().get_cpp_code_name() m_args_l = [] for t, n in zip(m_def.get_method_arg_types(), m_def.get_method_args()): m_args_l.append(t.get_cpp_code_name() + " " + n) m_args = ", ".join(m_args_l) print(f" virtual {m_cpp_ret_type} {m_def.name}({m_args}) = 0;", file = out_fd) print(f"}};", file = out_fd) print(f"}}", file = out_fd) # method implementations for m_def in interface_def.methods: method_impl_class_name = f"{interface_def.name}__{m_def.name}" # method impl class print(f"namespace {cpp_namespace} {{", file = out_fd) print(f"struct {method_impl_class_name} : public ::pybx::method_impl", file = out_fd) print("{", file = out_fd) print(" struct args_t {", file = out_fd) m_args_l = [] for t, n in zip(m_def.get_method_arg_types(), m_def.get_method_args()): tt = t.get_cpp_code_name() m_args_l.append(f"{tt} {n};") m_args = "\n".join(m_args_l) print(f" {m_args}", file = out_fd) print(" };", file = out_fd) print(" struct return_t {", file = out_fd) m_cpp_ret_type = m_def.get_method_return_type().get_cpp_code_name() m_cpp_ret_type = m_cpp_ret_type if m_cpp_ret_type != "void" else "json_null_t" print(f" {m_cpp_ret_type} retval;", file = out_fd) print(" };", file = out_fd) print(" void do_call(const std::string& req_s, std::string* res_s, std::shared_ptr<ix::WebSocket>) override;", file = out_fd) print("};", file = out_fd) print(f"}}", file = out_fd) # get_struct_descriptor for args_t, return_t, Request<args_t>, Response<return_t> print(f"template <> inline StructDescriptor get_struct_descriptor<{cpp_namespace}::{method_impl_class_name}::args_t>()", file = out_fd) print("{", file = out_fd) print(" static const StructDescriptor sd = {", file = out_fd) for m_arg in m_def.get_method_args(): print(f" make_member_descriptor(\"{m_arg}\", &{cpp_namespace}::{method_impl_class_name}::args_t::{m_arg}),", file = out_fd) print(" };", file = out_fd) print(" return sd;", file = out_fd) print("}", file = out_fd) print(f"template <> inline StructDescriptor get_struct_descriptor<::pybx::Request<{cpp_namespace}::{method_impl_class_name}::args_t>>()", file = out_fd) print("{", file = out_fd) print(f" return get_StructDescriptor_T<{cpp_namespace}::{method_impl_class_name}::args_t, ::pybx::Request>::get_struct_descriptor();", file = out_fd) print("}", file = out_fd) print(f"template <> inline StructDescriptor get_struct_descriptor<{cpp_namespace}::{method_impl_class_name}::return_t>()", file = out_fd) print("{", file = out_fd) print(" static const StructDescriptor sd = {", file = out_fd) print(f" make_member_descriptor(\"retval\", &{cpp_namespace}::{method_impl_class_name}::return_t::retval),", file = out_fd) print(" };", file = out_fd) print(" return sd;", file = out_fd) print("}", file = out_fd) print(f"template <> inline StructDescriptor get_struct_descriptor<::pybx::Response<{cpp_namespace}::{method_impl_class_name}::return_t>>()", file = out_fd) print("{", file = out_fd) print(f" return get_StructDescriptor_T<{cpp_namespace}::{method_impl_class_name}::return_t, ::pybx::Response>::get_struct_descriptor();", file = out_fd) print("}", file = out_fd) def generate_interface_client_definitions(interface_def, out_fd): cpp_namespace = get_cpp_namespace(interface_def.def_type.__module__) class_name = f"{interface_def.name}_rop" print(f"namespace {cpp_namespace} {{", file = out_fd) print(f"inline {class_name}::{class_name}()", file = out_fd) print("{", file = out_fd) print("}", file = out_fd) print(f"inline {class_name}::{class_name}(::pybx::Communicator* comm,", file = out_fd) print("std::shared_ptr<ix::WebSocket> ws,", file = out_fd) print("const std::string& ws_url, const std::string& object_id)", file = out_fd) print("{", file = out_fd) print(" this->comm = comm;", file = out_fd) print(" this->ws = ws;", file = out_fd) print(" this->object_id = object_id;", file = out_fd) print("}", file = out_fd) print(f"inline {class_name}::{class_name}(::pybx::Communicator* comm, const std::string& object_id)", file = out_fd) print("{", file = out_fd) print(" this->comm = comm;", file = out_fd) print(" this->object_id = object_id;", file = out_fd) print("}", file = out_fd) print(f"inline void {class_name}::activate(::pybx::Communicator* c, std::shared_ptr<ix::WebSocket> ws)", file = out_fd) method_activate_code = f""" {{ this->comm = c; if (this->ws == nullptr) {{ this->ws = ws; }} else {{ throw runtime_error("{class_name}::activate: not implemented for universal rop"); }} }} """ print(method_activate_code, file = out_fd) for m_def in interface_def.methods: generate_interface_client_method_definition(class_name, interface_def.name, m_def, out_fd) print(f"}} // end of namespace", file = out_fd) def generate_interface_client_method_definition(rop_class_name, interface_class_name, m_def, out_fd): # rop methods method_impl_class_name = f"{interface_class_name}__{m_def.name}" m_args_l = [] for t, n in zip(m_def.get_method_arg_types(), m_def.get_method_args()): tt = t.get_cpp_code_name() m_args_l.append(f"{tt} {n}") m_args = ",".join(m_args_l) m_ret_type = m_def.get_method_return_type().get_cpp_code_name() disable_void_return = "//" if m_ret_type == "void" else "" req_args_assignments = ";\n".join(["req.args." + x + "=" + x for x in m_def.get_method_args()]) print(f"inline {m_ret_type} {rop_class_name}::{m_def.name}({m_args})", file = out_fd) print("{", file = out_fd) rop_method_template = f""" ::pybx::Request<{method_impl_class_name}::args_t> req{{ .message_type = this->oneway ? ::pybx::message_type_t::METHOD_ONEWAY_CALL : ::pybx::message_type_t::METHOD_CALL, .message_id = ::pybx::create_new_message_id(), .method_signature = "{method_impl_class_name}", .object_id = object_id, .args = {method_impl_class_name}::args_t() }}; {req_args_assignments}; {disable_void_return} {m_ret_type} ret; ostringstream json_os; to_json(json_os, req); if (this->oneway) {{ comm->send_oneway(ws, json_os.str(), req.message_id); }} else {{ auto res_s = comm->send_and_wait_for_response(ws, json_os.str(), req.message_id); comm->check_response(res_s.first, res_s.second); ::pybx::Response<{method_impl_class_name}::return_t> res; from_json(&res, res_s.second); {disable_void_return} ret = res.retval.retval; }} {disable_void_return} return ret; """ print(rop_method_template, file = out_fd) print("}", file = out_fd) def generate_interface_server_method_impls(module_def, interface_def, out_fd): cpp_namespace = get_cpp_namespace(interface_def.def_type.__module__) print(f"namespace {cpp_namespace} {{", file = out_fd) for m_def in interface_def.methods: generate_interface_server_method_impl_definition(module_def, interface_def, m_def, out_fd) print(f"}}", file = out_fd) def generate_interface_server_method_impl_definition(module_def, interface_def, m_def, out_fd): #ipdb.set_trace() # activations code below is temp setup capabale to handle # use-case of server callbacks only. More reigirous type support required # to support all possible combinations like vector of rops, returns of rop # etc activations = [] if 1: args_with_activation = [] for arg, arg_type in zip(m_def.get_method_args(), m_def.get_method_arg_types()): if arg_type.is_rop_type(): activations.append(f"req.args.{arg}.activate(comm, ws);") activations_code = "\n".join(activations) m_args = ", ".join(["req.args." + x for x in m_def.get_method_args()]) m_ret_type = m_def.get_method_return_type().get_cpp_code_name() disable_void_return = "//" if m_ret_type == "void" else "" method_impl_do_call_tmpl = f""" ostringstream res_os; try {{ ::pybx::Request<args_t> req; from_json(&req, req_s); {activations_code} auto o = comm->find_object(req.object_id); auto self = dynamic_pointer_cast<{interface_def.name}>(o); if (self == nullptr) {{ throw runtime_error("dyn type mismatch"); }} ::pybx::Response<return_t> res; res.message_id = ::pybx::create_new_message_id(); res.orig_message_id = req.message_id; {disable_void_return} res.retval.retval = self->{m_def.name}({m_args}); to_json(res_os, res); }} catch (exception& e) {{ ::pybx::ExceptionResponse eres; eres.message_id = ::pybx::create_new_message_id(); eres.orig_message_id = ::pybx::get_message_id(req_s); eres.remote_exception_text = e.what(); to_json(res_os, eres); }} *res_s = res_os.str(); """ class_name = f"{interface_def.name}__{m_def.name}" print(f"inline void {class_name}::do_call(const string& req_s, string* res_s, shared_ptr<ix::WebSocket> ws)", file = out_fd) print("{", file = out_fd) print(method_impl_do_call_tmpl, file = out_fd) print("}", file = out_fd) print(f"UNIQUE = ::pybx::RemoteMethods::register_method(\"{class_name}\", std::make_shared<{class_name}>());", file = out_fd) def generate_cpp_file(module_def, out_fd, source_pybx_fn): generate_prolog(source_pybx_fn, out_fd) for enum_def in module_def.enums: generate_enum_def(enum_def, out_fd) for struct_name in module_def.struct_order: struct_def = module_def.structs[struct_name] generate_struct_def(struct_def, out_fd) generate_interface_client_forward_declarations(module_def, out_fd) for interface_def in module_def.interfaces: generate_interface_client_declarations(interface_def, out_fd) #ipdb.set_trace() for interface_def in module_def.interfaces: generate_interface_server_declarations(interface_def, out_fd) for interface_def in module_def.interfaces: generate_interface_client_definitions(interface_def, out_fd) for interface_def in module_def.interfaces: generate_interface_server_method_impls(module_def, interface_def, out_fd) generate_epilog(out_fd)

UTF-8

Python

py

codegen_cpp.py

Hansen-chen/python_demo_program

f78ed3d01a66ba28f40e64c5ced3fe2672c54a69

bf6e9f82f990057de2e8c621d5818584688400e4

/venv/main.py

f4f6046d81c1420ce3873a7850289a210ba98559

no_license

https://github.com/Hansen-chen/python_demo_program

4475843b1019a96ca1703331c61766797766fd34

d0cf12a2cbaea0fbb3860e8e915d2d0bf273fad1

refs/heads/master

#!/usr/bin/env python # -*- coding: utf-8 -*- import numpy as np import pandas as pd import datetime as dt import matplotlib.pyplot as plt data_datetime = [] data_candlestick = [] try: f = open('HKEX.HSI.txt', 'r') #data = f.read() #print(data) separator=" " for line in f: columns = line.split(separator) if len(columns) >= 1: #print(columns[0]+" "+columns[1]) try: data_datetime.append(dt.datetime.strptime(columns[0]+" "+columns[1], '%d/%m/%Y %H:%M:%S')) data_candlestick.append(columns[9].rstrip()) except ValueError: print("first line") finally: data_candlestick = np.array(data_candlestick) data_candlestick = data_candlestick.astype(np.int) #check hourly aggregate data data_dictionary = dict(zip(data_datetime, data_candlestick)) df = pd.DataFrame({'time':data_datetime, 'type':data_candlestick}) df = df.set_index('time').groupby([pd.Grouper(freq='H')]).sum() print(df.groupby(df.index.map(lambda t: t.hour)).describe()) #print(test) if f: f.close()

UTF-8

Python

py

main.py

Pranjal290/Web-Cam-Motion-Detector

748aa3f1a2207881b36606aac03ce9a423f55fc9

b1ac6f26f7a235703eed1eaf15ad72b619cff451

/video_capture.py

08257898566ad4f792cd6136bf695d3ee9b30c84

no_license

https://github.com/Pranjal290/Web-Cam-Motion-Detector

801dde1398e166f8af1b4e8c17004df9dab2aa40

b22e331b82864c7d17ea614d77189ec2101c5909

refs/heads/master

import cv2,time,pandas from datetime import datetime first_frame=None video=cv2.VideoCapture(0) status_list=[None,None] time=[] df=pandas.DataFrame(columns=['Start','End']) #using panda dataframe to store date and time of motion. while True: check,frame=video.read() status=0 grey=cv2.cvtColor(frame,cv2.COLOR_BGR2GRAY) #converting frame image to grey scaled version. grey=cv2.GaussianBlur(grey,(21,21),0) if first_frame is None: first_frame=grey #storing the first frame. continue delta_frame=cv2.absdiff(first_frame,grey) #calculating the absolute difference between the initial frame and changed image. tresh_delta=cv2.threshold(delta_frame,30,255,cv2.THRESH_BINARY)[1] tresh_delta=cv2.dilate(tresh_delta,None,iterations=2) (cnts,_)=cv2.findContours(tresh_delta.copy(),cv2.RETR_EXTERNAL,cv2.CHAIN_APPROX_SIMPLE) for contour in cnts: if cv2.contourArea(contour)<10000: #comparing different contours. continue status=1 (x,y,w,h)=cv2.boundingRect(contour) #indicating changes withe a green rectangle. cv2.rectangle(frame,(x,y),(x+w,y+w),(0,255,0),3) status_list.append(status) if status_list[-1]==1 and status_list[-2]==0: #storing the time of motion in a list. time.append(datetime.now()) if status_list[-1]==0 and status_list[-2]==1: time.append(datetime.now()) cv2.imshow("Delta Frame",delta_frame) #displaying the frames. cv2.imshow("Threshhold Frame",tresh_delta) cv2.imshow("Colour Frame",frame) key =cv2.waitKey(1) if key==ord('q'): #defining letter to close the window. if status==1: time.append(datetime.now()) break for i in range(0,len(time),2): df=df.append({"Start":time[i],"End":time[i+1]},ignore_index=True) #inserting values to data frame. df.to_csv("Times.csv") #creating .csv executable file. video.release() cv2.destroyAllWindows # PRESS 'q' ON KEYBOARD TO STOP THE PROGRAM

UTF-8

Python

py

video_capture.py

abandonsea/msba_reid

1459e19999eced757abe35aca1118546c8e59556

68f76af689d79d3e4a94354a4e644a878d8cfd40

/engine/deprecated/v2/inference_save_res.py

cd2f824e553a79fdf65d5a684cb77b4b77ab87d6

no_license

https://github.com/abandonsea/msba_reid

b9d00660141f8e657ac090d1426d00a36d19fed9

831158247ed116e82a9ed285e25974abdfbf755b

refs/heads/master

# encoding: utf-8 """ @author: liaoxingyu @contact: sherlockliao01@gmail.com """ import logging import torch import numpy as np import torch.nn.functional as F from data.datasets.eval_reid import evaluate from data.prefetcher import data_prefetcher from utils.re_ranking import re_ranking from utils.distance import low_memory_local_dist, local_dist def inference( cfg, model, test_dataloader, num_query, thetas ): logger = logging.getLogger("reid_baseline.inference") logger.info("Start inferencing") model.eval() feats, pids, camids = [], [], [] local_feats = [] test_prefetcher = data_prefetcher(test_dataloader) batch = test_prefetcher.next() while batch[0] is not None: img, pid, camid = batch with torch.no_grad(): feat = model(img) if isinstance(feat, tuple): feats.append(feat[0]) local_feats.append(feat[1]) else: feats.append(feat) pids.extend(pid.cpu().numpy()) camids.extend(np.asarray(camid)) batch = test_prefetcher.next() feats = torch.cat(feats, dim=0) if len(local_feats) > 0: local_feats = torch.cat(local_feats, dim=0) if cfg.TEST.NORM: feats = F.normalize(feats, p=2, dim=1) if len(local_feats) > 0: local_feats = F.normalize(local_feats, p=2, dim=1) # query qf = feats[:num_query] if len(local_feats) > 0: lqf = local_feats[:num_query] # gallery gf = feats[num_query:] if len(local_feats) > 0: lgf = local_feats[num_query:] if len(local_feats) > 0: # calculate the local distance lqf = lqf.permute(0, 2, 1) lgf = lgf.permute(0, 2, 1) #logger.info('Computing local_qg_distmat ...') local_qg_distmat = low_memory_local_dist(lqf.cpu().numpy(), lgf.cpu().numpy(), aligned=True) #logger.info('Computing local_qq_distmat ...') local_qq_distmat = low_memory_local_dist(lqf.cpu().numpy(), lqf.cpu().numpy(), aligned=True) #logger.info('Computing local_gg_distmat ...') local_gg_distmat = low_memory_local_dist(lgf.cpu().numpy(), lgf.cpu().numpy(), aligned=True) local_distmat = np.concatenate( [np.concatenate([local_qq_distmat, local_qg_distmat], axis=1), np.concatenate([local_qg_distmat.T, local_gg_distmat], axis=1)], axis=0) else: local_distmat = None use_rerank = True if use_rerank: #thetas = [0.4, 0.5, 0.9, 0.95, 1.0] scores, indices, dist_mats = [], [], [] logger.info("use reranking") for theta in thetas: distmat = re_ranking(qf, gf, k1=6, k2=2, lambda_value=0.3, local_distmat=local_distmat, theta_value=theta) score = distmat index = np.argsort(score, axis=1) # from small to large scores.append(score) indices.append(index) dist_mats.append(distmat) return scores, indices, dist_mats else: logger.info("No reranking") distmat = -torch.mm(qf, gf.t()).cpu().numpy() score = distmat index = np.argsort(score, axis=1) # from small to large return score, index def inference_flipped( cfg, model, test_dataloader, num_query, thetas, use_local_feature=True # 是否使用local特征 ): logger = logging.getLogger("reid_baseline.inference") logger.info("Start inferencing") model.eval() g_feats, l_feats, gf_feats, lf_feats, pids, camids = [], [], [], [], [], [] val_prefetcher = data_prefetcher(test_dataloader) batch = val_prefetcher.next() while batch[0] is not None: img, pid, camid = batch with torch.no_grad(): g_feat, l_feat = model(img) gf_feat, lf_feat = model(torch.flip(img, [3])) g_feats.append(g_feat.data.cpu()) l_feats.append(l_feat.data.cpu()) gf_feats.append(gf_feat.data.cpu()) lf_feats.append(lf_feat.data.cpu()) pids.extend(pid.cpu().numpy()) camids.extend(np.asarray(camid)) batch = val_prefetcher.next() g_feats = torch.cat(g_feats, dim=0) l_feats = torch.cat(l_feats, dim=0) gf_feats = torch.cat(gf_feats, dim=0) lf_feats = torch.cat(lf_feats, dim=0) if cfg.TEST.NORM: g_feats = F.normalize(g_feats, p=2, dim=1) gf_feats = F.normalize(gf_feats, p=2, dim=1) # query qf = g_feats[:num_query] lqf = l_feats[:num_query] qff = gf_feats[:num_query] lqff = lf_feats[:num_query] q_pids = np.asarray(pids[:num_query]) q_camids = np.asarray(camids[:num_query]) # gallery gf = g_feats[num_query:] lgf = l_feats[num_query:] gff = gf_feats[num_query:] lgff = lf_feats[num_query:] g_pids = np.asarray(pids[num_query:]) g_camids = np.asarray(camids[num_query:]) # calculate the global distance scores, indices, dist_mats = [], [], [] #use_local_feature = True if use_local_feature: logger.info("--------computing local features ...--------") lqf = lqf.permute(0, 2, 1) lgf = lgf.permute(0, 2, 1) local_distmat = low_memory_local_dist(lqf.numpy(), lgf.numpy(), aligned=True) local_qq_distmat = low_memory_local_dist(lqf.numpy(), lqf.numpy(), aligned=True) local_gg_distmat = low_memory_local_dist(lgf.numpy(), lgf.numpy(), aligned=True) local_dist = np.concatenate( [np.concatenate([local_qq_distmat, local_distmat], axis=1), np.concatenate([local_distmat.T, local_gg_distmat], axis=1)], axis=0) logger.info("--------computing flipped local features ...--------") lqff = lqff.permute(0, 2, 1) lgff = lgff.permute(0, 2, 1) local_distmat = low_memory_local_dist(lqff.numpy(), lgff.numpy(), aligned=True) local_qq_distmat = low_memory_local_dist(lqff.numpy(), lqff.numpy(), aligned=True) local_gg_distmat = low_memory_local_dist(lgff.numpy(), lgff.numpy(), aligned=True) local_dist_flip = np.concatenate( [np.concatenate([local_qq_distmat, local_distmat], axis=1), np.concatenate([local_distmat.T, local_gg_distmat], axis=1)], axis=0) else: local_dist = None local_dist_flip = None logger.info("use reranking") for theta in thetas: distmat = re_ranking(qf, gf, k1=6, k2=2, lambda_value=0.3, local_distmat=local_dist, theta_value=theta, only_local=False) distmat_flip = re_ranking(qff, gff, k1=6, k2=2, lambda_value=0.3, local_distmat=local_dist_flip, theta_value=theta, only_local=False) # 合并距离 distmat = (distmat + distmat_flip) / 2 score = distmat index = np.argsort(score, axis=1) # from small to large scores.append(score) indices.append(index) dist_mats.append(distmat) return scores, indices, dist_mats

UTF-8

Python

py

inference_save_res.py

0AdityaD/competitive

a0de5dbc78d4888f9483265ed57136360ba28a7d

7e2b5fa590b34bb589f97242b1e139219ab6c97b

/kattis/perfect_powers.py

aa2166e84902b4b0b927c4e09ef11a64d2eb43cb

no_license

https://github.com/0AdityaD/competitive

a7195c8096fc443d2aa506910da472b8b0a21226

497345e0cdad058d57bb84dc96dfc1856eae5cbe

refs/heads/master

from collections import defaultdict from random import randint def gcd2(a, b): a, b = max(a, b), min(a, b) if b == 0: return a return gcd2(b, a % b) def gcd(ls): if len(ls) == 0: return 1 ans = ls[0] for elt in ls[1:]: ans = gcd2(elt, ans) return ans def is_prime(n, primes): for prime in primes: if n % prime == 0: return False elif prime * prime > n: return True return True def gen_primes(): primes = [2, 3] for i in range(5, 100001, 2): if is_prime(i, primes): primes.append(i) return primes def factor(x, primes): factorization = defaultdict(int) for prime in primes: if prime * prime > x: break while x % prime == 0: x //= prime factorization[prime] += 1 if x > 1: factorization[x] += 1 return factorization def solve(x, primes): f = factor(abs(x), primes) result = gcd(list(f.values())) if x < 0: while result % 2 == 0: result //= 2 print(result) def main(): primes = gen_primes() x = int(input()) while x != 0: solve(x, primes) x = int(input()) if __name__ == '__main__': main()

UTF-8

Python

py

perfect_powers.py

yuyasugano/dynamodb-ohlcv-crypto

6a7100eaa504f3af78074814e23425941039c281

f3ac44c5c376a3f7e1b6d384c26916d4e9c43dde

/dynamodb-sam/resizer.py

f41f00cc69fc9ea3c2f369b10fa4d9419ea392a6

permissive

https://github.com/yuyasugano/dynamodb-ohlcv-crypto

ddbfef21b220a65a923a3ea766c54ab0a4d07c7f

c7bef03bccb43baaf306c9d1f2a32c6fbccc57fa

refs/heads/master

import os import boto3 import datetime region = os.environ.get('AWS_DEFAULT_REGION', 'ap-northeast-1') dynamodb = boto3.client('dynamodb', region_name=region) class DailyResize(object): FIRST_DAY_RCU, FIRST_DAY_WCU = 3, 3 OLD_DAY_RCU, OLD_DAY_WCU = 1, 1 def __init__(self, table_prefix): self.table_prefix = table_prefix def create_new(self): # create new table today = datetime.date.today() tomorrow = datetime.date.today() + datetime.timedelta(1) new_table_name = "{}_{}".format(self.table_prefix, self._format_date(tomorrow)) dynamodb.create_table( TableName = new_table_name, KeySchema = [ { 'AttributeName': 'name', 'KeyType': 'HASH' # Partition Key }, { 'AttributeName': 'datetime', 'KeyType': 'RANGE' # Sort Key } ], AttributeDefinitions = [ { 'AttributeName': 'name', 'AttributeType': 'S', }, { 'AttributeName': 'datetime', 'AttributeType': 'S' } ], ProvisionedThroughput = { 'ReadCapacityUnits': self.FIRST_DAY_RCU, 'WriteCapacityUnits': self.FIRST_DAY_WCU }, ) print("Table created with name {}".format(new_table_name)) return new_table_name def resize_old(self): # update older table yesterday = datetime.date.today() - datetime.timedelta(1) old_table_name = "{}_{}".format(self.table_prefix, self._format_date(yesterday)) self._update_table(old_table_name, self.OLD_DAY_RCU, self.OLD_DAY_WCU) return 'OK' def delete_old(self): # delete older table weekago = datetime.date.today() - datetime.timedelta(7) old_table_name = "{}_{}".format(self.table_prefix, self._format_date(weekago)) self._delete_table(old_table_name) return 'OK' def _update_table(self, table_name, RCU, WCU): """ Update RCU/WCU of the given table (if exists) """ print("Updating table with name {}".format(table_name)) try: dynamodb.update_table( TableName = table_name, ProvidionedThroughput = { 'ReadCapacityUnits': RCU, 'WriteCapacityUnits': WCU, }, ) except dynamodb.exceptions.ResourceNotFoundException as e: print("DynamoDB Table {} not found".format(table_name)) def _delete_table(self, table_name): """ Delete the given table (if exists) """ print("Deleting table with name {}".format(table_name)) try: dynamodb.delete_table(TableName = table_name) except dynamodb.exceptions.ResourceInUseException as e: print("DynamoDB Table {} in use".format(table_name)) except dynamodb.exceptions.ResourceNotFoundException as e: print("DynamoDB Table {} not found".format(table_name)) @staticmethod def _format_date(d): return d.strftime("%Y-%m-%d")

UTF-8

Python

py

resizer.py

piohhmy/euler

99b98d97fbd91616fb282d1e3d0891bb245f7c95

7af1b10e4389a4be5f2f22f3178fff2503280929

/p022.py

0861e4c3a41fafc703117affd664275c7bc87c1d

permissive

https://github.com/piohhmy/euler

559f15fa9f7f5c644b65b43674646e0f520fd46e

f1b548a28a503fb8a0878fda75c32e1dcfb33243

refs/heads/master

""" Using names.txt (right click and 'Save Link/Target As...'), a 46K text file containing over five-thousand first names, begin by sorting it into alphabetical order. Then working out the alphabetical value for each name, multiply this value by its alphabetical position in the list to obtain a name score. For example, when the list is sorted into alphabetical order, COLIN, which is worth 3 + 15 + 12 + 9 + 14 = 53, is the 938th name in the list. So, COLIN would obtain a score of 938 x 53 = 49714. What is the total of all the name scores in the file? """ def alphabetical_value(name): return sum([ord(letter) - 64 for letter in name]) def solve_p22(): with open('p022_names.txt', 'r') as namefile: names = namefile.readline() namelist = sorted([name.strip('"') for name in names.split(",")]) total = 0 for i, name in enumerate(namelist): total += (i+1) * alphabetical_value(name) return total if __name__ == '__main__': print(solve_p22())

UTF-8

Python

py

p022.py

POFK/LensFinder

d1bfaaf055bf0bacc7960555267588a2eb2764d0

bcb13b92bf0a1ec85f40c99e9ffa49654bd3a3a5

/lens/eval.py

9c9d1732120322d6eee74b0463f21bd45eeec20b

permissive

https://github.com/POFK/LensFinder

81fc2c67366396240f6f6d4c2c3ba02fb74a8539

56a8cb3f99a68b5922e0a8c76e1cee27ef75a09e

refs/heads/master

MIT

Jupyter Notebook

#!/usr/bin/env python # coding=utf-8 import os import numpy as np import torch import h5py import tqdm import glob from torch.utils.data import Dataset, DataLoader, ConcatDataset from torchvision import transforms from main import * random_crop = args.crop_range #name = 'area1_hdf5_2' name = 'area2_hdf5' model_path = '/data/dell5/userdir/maotx/Lens/model/lens_049_40.cpt' BaseDir = '/data/inspur_disk03/userdir/wangcx/BASS_stack/area2/'+name OutDir = '/data/dell5/userdir/maotx/Lens/result/{}_{}'.format( name, model_path.split('/')[-1][:-4]) check_dir(OutDir) fps = glob.glob(BaseDir + '/*.hdf5') fps = [i.replace(BaseDir + '/', '') for i in fps] class HdfDataset(Dataset): """My dataset.""" def __init__(self, root, path, transform=None): """ Args: transform (callable, optional): Optional transform to be applied on a sample. """ self.root = root self.path = path self.transform = transform with h5py.File(os.path.join(root, path), 'r') as fp: self.keys = list(fp.keys()) def _init_fn(self, num): self.fp = h5py.File(os.path.join(self.root, self.path), 'r') def __len__(self): return len(self.keys) def __getitem__(self, idx): image = self.fp[self.keys[idx]] g = self._center(image['g'][...].reshape(-1)) r = self._center(image['r'][...].reshape(-1)) z = self._center(image['z'][...].reshape(-1)) image = np.c_[g, r, z].reshape(101, 101, 3) key = self.keys[idx] if self.transform: image = self.transform(image) return {'image': image, 'key': key, 'path': self.path} def _center(self, x): mean = x.mean() std = x.std() return (x - mean) / std class HdfConcatDataset(ConcatDataset): def _init_fn(self, num): for ds in self.datasets: ds._init_fn(num) class ToTensor(object): def __call__(self, image): image = image.transpose((2, 0, 1)) image = np.clip(image, -100, 100) image = torch.from_numpy(image) return image class Crop(object): """Crop randomly the image in a sample. Args: output_size (tuple or int): Desired output size. If int, square crop is made. """ def __init__(self, output_size): assert isinstance(output_size, (int, tuple)) if isinstance(output_size, int): self.output_size = (output_size, output_size) else: assert len(output_size) == 2 self.output_size = output_size def __call__(self, image): h, w = image.shape[:2] new_h, new_w = self.output_size top = (h - new_h)//2 left = (w - new_w)//2 image = image[top:top + new_h, left:left + new_w] return image def eval(BaseDir, fps=[], OutDir=OutDir, model_path=model_path): preprocess = transforms.Compose([Crop(random_crop), ToTensor()]) model, _ = get_model() model = torch.nn.DataParallel(model) _ = torch.load(model_path, map_location='cpu') model, epoch = load(model_path, model) print('loading {}'.format(model_path), epoch) model.eval() for fp in tqdm.tqdm(fps): BASS_ds = HdfDataset(root=BaseDir, path=fp, transform=preprocess) BASS_dl = DataLoader(BASS_ds, batch_size=args.batch_size, num_workers=4, worker_init_fn=BASS_ds._init_fn) PROB = [] with torch.no_grad(): for data_step in BASS_dl: key = data_step['key'] prob = torch.sigmoid(model(data_step['image'])).numpy() PROB.append(zip(key, prob)) wpath = os.path.join(OutDir, fp.replace('.hdf5','.txt')) with open(wpath, 'w') as FP: for result in PROB: for key, P_value in result: temp = "{}\t{}\t{}\n".format(key, P_value[0], P_value[1]) FP.writelines(temp) if __name__ == "__main__": eval(BaseDir, fps=fps, OutDir=OutDir, model_path=model_path)

UTF-8

Python

py

eval.py

psyvirgin/markpress

8d46bd036473cae172d283e8f67f5de1d439217c

141beebb8650263669d03f1cca1ca1e1c3d4bd64

/lib/wordpress.py

57e257324aafc06e34fa9afd363cfe2b34dde63b

permissive

https://github.com/psyvirgin/markpress

c3eddb8370e7e326e7d01d85f05aff84bcabdc07

e5f12795b1e82e2223f33953cc9694690c96a959

refs/heads/master

#! /usr/bin/python #---------------------------------------------------------------------- # # wordpress.py - wordpress # # NOTE: # for more information, please see the readme file # #---------------------------------------------------------------------- import sys, time, os import markdown3 import blogpost #---------------------------------------------------------------------- # global definition #---------------------------------------------------------------------- def die (message): sys.stderr.write('%s\n'%message) sys.stderr.flush() sys.exit(1) #---------------------------------------------------------------------- # configure #---------------------------------------------------------------------- class configure (object): def __init__ (self, home = '.'): self._dirhome = os.path.abspath(home) self._ininame = self.path('wordpress.ini') self._inipath = '' self._config = {} self._posts = [] self._names = [] self._wordpress = {} self._update_site() self._update_posts() def path (self, name): return os.path.abspath(os.path.join(self._dirhome, name)) def die (self, message): sys.stderr.write('%s\n'%message) sys.stderr.flush() sys.exit(1) return 0 def _read_content (self, name): content = open(name, 'rb').read() if content[:3] == '\xef\xbb\xbf': content = content[3:] return content def _update_site (self): if not os.path.exists(self._ininame): self.die('missing %s\n'%self._ininame) import StringIO import ConfigParser sio = StringIO.StringIO(self._read_content(self._ininame)) cp = ConfigParser.ConfigParser() cp.readfp(sio) for sect in cp.sections(): self._config[sect] = {} for key, val in cp.items(sect): self._config[sect][key] = val.strip('\r\n\t ') class Object (object): pass self._wordpress = Object() self._wordpress.url = self.config('default', 'url') self._wordpress.username = self.config('default', 'username') self._wordpress.password = self.config('default', 'password') if not self._wordpress.url: self.die('can not find url in %s\n'%self._ininame) if not self._wordpress.username: self.die('can not find username in %s\n'%self._ininame) return 0 def config (self, sect, key, default = None): if not sect in self._config: return default val = self._config[sect].get(key, default) return val def _update_posts (self): self._posts = [] self._names = {} for fn in os.listdir(self.path('doc')): ext = os.path.splitext(fn)[-1].lower() if ext != '.md': continue class Object (object): pass main = os.path.splitext(fn)[0] post = Object() post.name = fn post.filename = {} post.filename['md'] = self.path('doc/' + fn) post.filename['html'] = self.path('data/' + main + '.html') post.filename['meta'] = self.path('data/' + main + '.blogpost') self._update_info(post) self._posts.append(post) self._names[fn] = post return 0 def _update_info (self, post): time_md = os.stat(post.filename['md']).st_ctime time_html = -1 time_meta = -1 post.modified = False if os.path.exists(post.filename['html']): time_html = os.stat(post.filename['html']).st_ctime if time_html < time_md: post.modified = True else: post.modified = True if os.path.exists(post.filename['meta']): time_meta = os.stat(post.filename['meta']).st_ctime if time_meta < time_md: post.modified = True else: post.modified = True post.title = '' post.categories = [] post.tags = [] return 0 def __getitem__ (self, index): if type(index) in (type(''), type(u'')): return self._names.get(index) return self._posts[index] def __contains__ (self, index): if type(index) in (type(''), type(u'')): return (index in self._names) return (index >= 0) and (index < len(self._posts)) def __len__ (self): return len(self._posts) def __repr__ (self): return repr([ p.name for p in self._posts ]) def markdown (self, post): content = open(post.filename['md'], 'rb').read() if content[:3] == '\xef\xbb\xbf': content = content[3:] content = content.decode('utf-8') extras = ['metadata', 'fenced-code-blocks'] extras.append('cuddled-lists') extras.append('tables') extras.append('footnotes') post.html = markdown3.markdown(content, extras = extras) #print post.html.metadata post.metadata = post.html.metadata and post.html.metadata or {} post.title = post.metadata.get('title', '').strip('\r\n\t ') categories = post.metadata.get('categories', '').split(',') tags = post.metadata.get('tags', '').split(',') post.categories = [] post.tags = [] for n in [ n.strip() for n in categories ]: if n: post.categories.append(n) for n in [ n.strip() for n in tags ]: if n: post.tags.append(n) post.id = post.metadata.get('id', None) post.status = post.metadata.get('status', 'published').strip() return post def wordpress (self, options): class Object (object): pass opt = Object() opt.attributes = [] opt.asciidoc_opts = [] opt.categories = '' opt.doctype = None opt.conf_file = None opt.force = False opt.force_media = False opt.mandatory_parameters = '' opt.media_dir = None opt.media = True opt.dry_run = False opt.pages = False opt.id = None opt.proxy = None opt.title = None opt.status = None opt.verbose = 0 opt.command = None opt.filename = None opt.status = 'published' import xmlrpclib for n in options: opt.__dict__[n] = options[n] try: blogpost.OPTIONS = opt blog = blogpost.Blogpost( \ self._wordpress.url, \ self._wordpress.username, \ self._wordpress.password, \ opt) blog.set_blog_file(opt.filename) blog.load_cache() blog.get_parameters() blog.check_mandatory_parameters() blog.title = blog.parameters.get('title', blog.title) if opt.title: blog.title = opt.title if opt.id is not None: blog.id = opt.id blog.post_type = blog.parameters.get('posttype', blog.post_type) if blog.post_type is None: blog.post_type = 'post' blog.status = blog.parameters.get('status', blog.status) if opt.status: blog.status = opt.status if blog.status is None: blog.status = 'published' blog.status = 'published' blog.doctype = blog.parameters.get('doctype', blog.doctype) if opt.doctype is not None: blog.doctype = options.doctype if blog.doctype is None: blog.doctype = 'article' # default opt.categories = blog.parameters.get('categories', opt.categories) command = opt.command if command == 'info': blog.info() elif command == 'categories': if opt.categories: blog.set_categories() else: blog.list_categories() elif command == 'list': blog.list() elif command == 'delete': if blog.id is None: die('missing cache file: specify id please') blog.delete() elif command == 'dump': blog.dump() elif command in ('post', 'create', 'update'): if blog.id is not None and command == 'create': die('document has been previously posted, use update command') if blog.id is None and command == 'update': die('missing cache file: specify id instead') if command == 'update' or \ command == 'post' and blog.id is not None: blog.update() if command == 'create' or \ command == 'post' and blog.id is None: blog.create() if opt.categories: blog.set_categories() else: die('unknow command') except xmlrpclib.ProtocolError, e: die(e) return 0 #---------------------------------------------------------------------- # wordpress #---------------------------------------------------------------------- class wordpress (object): def __init__ (self, home = '.'): self.config = configure(home) self.verbose = False def info (self, message): if self.verbose: print message return 0 def warn (self, message): sys.stderr.write('%s\n'%message) sys.stderr.flush() def synchronize (self, name, force = False, verbose = False): self.verbose = verbose if os.path.splitext(name)[-1] != '.md': self.warn('can not synchronize non markdown file') return -1 if not name in self.config: self.warn('missing doc/%s in %s'%(name, self.config._dirhome)) return -2 post = self.config[name] if post.modified == False and force == False: self.info('[skip: %s]'%name) return 0 self.info('[synchronizing: %s]'%name) self.config.markdown(post) if not post.title: self.warn('missing title in %s'%(name)) return -3 opt = {} opt['title'] = post.title.encode('utf-8') if post.id: opt['title'] = post.id if post.categories: opt['categories'] = (','.join(post.categories)).encode('utf-8') if post.tags: opt['tags'] = (','.join(post.tags)).encode('utf-8') opt['command'] = 'post' self.info('writing: %s'%post.filename['html']) fp = open(post.filename['html'], 'wb') fp.write(post.html.encode('utf-8')) fp.close() opt['filename'] = post.filename['html'] opt['status'] = 'published' opt['force'] = force self.config.wordpress(opt) self.info('') return 0 #---------------------------------------------------------------------- # main #---------------------------------------------------------------------- def main(args = None): if args == None: args = sys.argv args = [ n for n in args ] import optparse description = 'A Wordpress command-line weblog client for markdown' parser = optparse.OptionParser( \ usage='usage: %prog [OPTIONS] BLOG_FILE', version='1.0.0', description = description) parser.add_option('--force', action='store_true', dest='force', default = False, help = 'force blog file to upload') OPTIONS, ARGS = parser.parse_args(args) if len(ARGS) < 2: print 'missing blog_file' return -1 filename = ARGS[1] print ARGS wp = wordpress() wp.synchronize(filename, OPTIONS.force, True) return 0 #---------------------------------------------------------------------- # testing case #---------------------------------------------------------------------- if __name__ == '__main__': def test1(): config = configure('.') print config.path('.') print config print config._wordpress.url print config._wordpress.username return 0 def test2(): wp = wordpress() wp.synchronize('post.3.md', True, True) return 0 #test2() main()

UTF-8

Python

py

wordpress.py

Frixoe/canadian-name-generator

58e96b09f928ae70ab27c91ab52f0f78cee0c1ee

6fb34a4996dd10d63abb92ca01a56126ecd73b61

/main.py

b7b42e5519e30e443ef42966be76793dbc906c95

permissive

https://github.com/Frixoe/canadian-name-generator

d2e70206fb2ebce4e359eaae1420fb7feff7ae03

ee041639d4ea1209275a625b1f6ce6caf96bfa0f

refs/heads/master

import pandas as pd import numpy as np import os os.environ['KERAS_BACKEND'] = 'theano' # Using 'theano' backend for keras import tensorflow as tf import keras from keras.models import Sequential, load_model from keras.layers import Dense, LSTM, TimeDistributed, Activation # Loading the data into a DataFrame df = pd.read_csv("names.csv") # Converting df column to list names = list(df["name"][:]) names = [item.lower() for item in names] #Creating vocab for Index to Char itc = {key: value for key, value in enumerate(sorted(list(set("".join(names)))))} itc[26] = "\n" # Creating vocab for Char to Index cti = {itc[key]: key for key in itc.keys()} # Setting the maximum length of a name(CAN BE CHANGED) max_len = 30 # Create a zeros array with necessary shape data = np.zeros((len(names), max_len, len(itc.keys()))) # Fill the data array with correct encodings of the names for i in range(data.shape[0]): error = False for j in range(data.shape[1]): try: data[i, j, cti[names[i][j]]] = 1 except IndexError: data[i, j, cti["\n"]] = 1; error = True; break if not error: data[i, data.shape[1] - 1, cti["\n"]] = 1 # Reassigning the data to training samples X and targets Y X, Y = np.zeros(data.shape), np.zeros(data.shape) X[:, :, :], Y[:, :Y.shape[1] - 1, :] = data[:, :, :], data[:, 1:, :] # Splitting the Data into training and evaluation sets split_to_and_from = 374000 X_train, Y_train, X_test, Y_test = (X[:split_to_and_from, :, :], Y[:split_to_and_from, :], X[split_to_and_from:, :, :], Y[split_to_and_from:, :]) ##### CREATING THE MODEL # Hyper - params time_steps = max_len b_size = 2000 n_cells = 30 l_r = 0.01 print("Creating model...") global model model = Sequential([ LSTM(n_cells, input_shape=(None, X.shape[2]), return_sequences=True), TimeDistributed(Dense(len(cti), activation="softmax")) ]) print("Model created!") # Compiling the model model.compile("rmsprop", loss="categorical_crossentropy", metrics=["accuracy"]) def pred(length): ''' Generate a name with the model. ''' X_pred = np.zeros((1, length, len(cti))) pred = [np.random.randint(len(cti) - 1)] gen = [itc[pred[-1]]] for i in range(length): X_pred[0, i, :][pred[-1]] = 1 pred_arr = model.predict(X_pred[:, :, :], batch_size=1, verbose=0) pred_arr = pred_arr[0, i, :] p = np.argmax(pred_arr) pred.append(p) gen.append(itc[pred[-1]]) return "".join(gen) def train_model(num_epochs): print("Training the model now for {} epochs...".format(num_epochs)) current_e = 1 while current_e < num_epochs: # Fitting the model model.fit(x=X_train, y=Y_train, batch_size=b_size, epochs=1, verbose=1) # Generate a name of max_len print(pred(max_len).strip("\n")) print("Training complete!") def save_my_model(): # Saves weights and architecture model.save("my_keras_model.h5") # Training the model train_model(10) # Save model save_my_model() # Evaluating the model metrics = model.evaluate(x=X_test, y=Y_test, batch_size=100) print("Model metrics: ") for m_name, m in zip(model.metrics_names, metrics): print("{}: {}".format(m_name, m))

UTF-8

Python

py

main.py

MuggleWei/useful_scripts

53737d148a06aba8152ed65e262075762deb6c7a

dd6ee0d198b200606247a9f98a6036a0556758cf

/essential_sources/essential_sources.py

9967818ddf96e30e860ce2c30d403684fcd3970d

no_license

https://github.com/MuggleWei/useful_scripts

03407709900c3a5f40bc87b44430a07cfc6484f8

8a9ffa8318254b04ac1e0fc57bf3646f229d094c

refs/heads/master

Vim Script

""" 下载必备代码库 """ import os import subprocess def run_subprocess(args): """ 运行子进程并实时输出 :param args: 执行的命令 """ with subprocess.Popen(args, stdout=subprocess.PIPE) as p: try: for line in p.stdout: if not line: break print("{}".format(line.decode("utf-8"))) except Exception as e: print("{} failed: {}".format(args, e)) if __name__ == "__main__": # 需要备份的代码库 source_list = [ # 自己的代码库 "https://github.com/MuggleWei/mugglec.git", "https://github.com/MuggleWei/Hakuna_Matata.git", "https://github.com/MuggleWei/useful_scripts.git", "https://github.com/MuggleWei/mugglewei.github.io.git", "https://github.com/MuggleWei/learning_compass.git", "https://github.com/MuggleWei/babeltrader.git", "https://github.com/MuggleWei/mugglecpp.git", "https://github.com/MuggleWei/latency-benchmark.git", "https://github.com/MuggleWei/callback_benchmark.git", "https://github.com/MuggleWei/srclient.git", "https://github.com/MuggleWei/webtoy.git", "https://github.com/MuggleWei/goev.git", "https://github.com/MuggleWei/hpb.git", "https://github.com/MuggleWei/hpkg.git", # 代码 "https://github.com/python/cpython.git", "https://github.com/vim/vim.git", "https://github.com/neovim/neovim.git", "https://github.com/Kitware/CMake.git", "https://github.com/wolfSSL/wolfssl.git", "https://github.com/openssl/openssl.git", "https://github.com/Mbed-TLS/mbedtls.git", "https://github.com/gpg/gnupg.git", "https://github.com/gpg/libgcrypt.git", "https://github.com/gpg/libgpg-error.git", "https://github.com/madler/zlib.git", "https://github.com/facebook/zstd.git", "https://github.com/mcmilk/7-Zip-zstd.git", "https://github.com/the-tcpdump-group/libpcap.git", "https://github.com/libevent/libevent.git", "https://github.com/sqlite/sqlite.git", "https://github.com/google/googletest.git", "https://github.com/gperftools/gperftools.git" "https://github.com/protocolbuffers/protobuf.git", "https://github.com/gflags/gflags.git", "https://github.com/danmar/cppcheck.git", "https://github.com/leethomason/tinyxml2.git", "https://github.com/Tencent/rapidjson.git", "https://github.com/bkaradzic/bgfx.git", "https://github.com/ocornut/imgui.git", "https://github.com/ArthurSonzogni/FTXUI.git", "https://github.com/tcltk/tcl.git", # 编译某些项目时需要此库 "https://github.com/openai/gpt-2.git", # 学习/博客/例子 # "https://github.com/jiji262/wooyun_articles.git", # 2.5G 太占硬盘了 :( "https://github.com/wolfSSL/wolfssl-examples.git", # 日常生活 "https://github.com/shadowsocks/shadowsocks-libev.git", "https://github.com/adityatelange/hugo-PaperMod.git", "https://github.com/KaTeX/KaTeX.git", "https://github.com/mdaines/viz.js.git", ] # 当前工作目录下的目录 cur_dirs = os.listdir(".") # 遍历清单, 获取状态 cur_dir = os.getcwd() for src in source_list: name = src.split("/")[-1][:-4] if name in cur_dirs: print("----------------------------------------------") print("{}: already exists, git pull".format(name)) # 进入文件夹 os.chdir(name) # 运行git pull args = ["git", "pull"] run_subprocess(args=args) # 返回原目录 os.chdir(cur_dir) else: print("----------------------------------------------") print("{}: clone".format(name)) # 运行git pull args = ["git", "clone", src] run_subprocess(args=args)

UTF-8

Python

py

essential_sources.py

ybdesire/pylearn

3799b6d8c702a86451e2db0148370e6b36f7ebb3

90a1aa497ec53fa87bc31cd5101ad55adb22cddb

/exception/ex_print_error_line.py

8dfedad23a2fd5208efc49bf1ee5ca929dd1a387

no_license

https://github.com/ybdesire/pylearn

39821e3e5cb61c021afc7af2052e0de7077961e2

400e525c0529bea6da74aab9bc86fe5e26549d32

refs/heads/master

import sys try: x = 1+1 y = x/0 z = 2+2 except Exception as e: s = sys.exc_info() print('exception error msg : {0}'.format(s[1])) print('exception on line: {0} '.format(s[2].tb_lineno))

UTF-8

Python

py

ex_print_error_line.py

COLAB2/tagsim

7ae49a43e3d16721de29163afe38e6daa68b5cd9

468f88552212e17cec428437d119b824e5660943

/fieldComparisonMidca.py

15fcdd3427847381884a2ef77eca5f01e3e5dff3

no_license

https://github.com/COLAB2/tagsim

c3efb6b4715163b53cfe3328880fd77ffc466722

9d4c040a7c842cb14c0075b423345db209e51958

refs/heads/master

import numpy as np import time import matplotlib.pyplot as plt from gridworld import Grid import gridworld from AcousticTag import AcousticTag from Agent import Agent from AcousticReciever import AcousticReciever import socket import threading import traceback import sys wp_list = None allDetectionData = None allMeasurementData = [] t = 0 endSim = False def find_max_5_values_avg(time): a = {} for each in time: if each in a: a[each] += 1 else: a[each] = 1 values = a.values() #print ("best 5 values: ") if values: values.sort(reverse=True) #print (values[:5]) #print (sum(values[:5])) return float(sum(values[:7])) / 7 else: return 0 def find_max_7_values_avg_measurement(time, data): a = {} for index, each in enumerate(time): if each in a: a[each] += data[index] else: a[each] = data[index] values = a.values() #print ("best 5 values: ") if values: values.sort(reverse=True) #print (values[:5]) #print (sum(values[:5])) return float(sum(values[:5])) / 5 else: return 0 def MidcaComLink(): global running, searchComplete, wp_list, agent, E, det_count, agentList run = True # create an INET, STREAMing socket sock = socket.socket(socket.AF_INET, socket.SOCK_STREAM) # bind the socket to a public host, and a well-known port sock.bind(('127.0.0.1', 5700)) sock.listen(5) # accept connections from outside (clientsocket, address) = sock.accept() # now do something with the clientsocket print("starting") while run: try: clientsocket, address = sock.accept() data = clientsocket.recv(1024) data = data.decode('utf-8') cmd = data.split(',') #print(cmd) if cmd[0] == 'quit': running = False run = False endSim = True if cmd[0] == 'start': running = True if cmd[0] == 'moveTo': x = int(cmd[1]) - 1 y = int(cmd[2]) - 1 center = np.array([x * x_range/5.0, y * y_range/5.0]) + np.array([.5*x_range/5.0, .5*y_range/5.0]) wp_list[0] = [center] if cmd[0] == 'moveToPhysicalPosition': x=int(cmd[1])-1 y=int(cmd[2])-1 center=np.array([x,y]) wp_list[0]=[center] if cmd[0] == 'inCell': agent = agentList[0] pos = agent.getPos() bin = E.getAbstractPos(pos[0], pos[1]) x = int(cmd[1]) y = int(cmd[2]) myx, myy = E.getCellXY(pos[0], pos[1]) bin2 = 5 * (y - 1) + (x - 1) clientsocket.send(str.encode(str(x == myx and y == myy))) #print(bin, bin2) if cmd[0] == 'time': clientsocket.send(str.encode(str(t))) if cmd[0] == 'getCell': agent = agentList[0] pos = agent.getPos() bin = E.getAbstractPos(pos[0], pos[1]) myx, myy = E.getCellXY(pos[0], pos[1]) clientsocket.send(str.encode(str(myx) + "," + str(myy))) if cmd[0] == 'search': x = int(cmd[1]) - 1 y = int(cmd[2]) - 1 center = np.array([x * x_range/5.0, y * y_range/5.0]) + np.array([.5*x_range/5.0, .5*y_range/5.0]) wp_list[0] = search(wp_list[0], center) searchComplete = False if cmd[0] == 'searchComplete': clientsocket.send(str.encode(str(searchComplete))) if cmd[0] == 'get_tags': agent = agentList[0] bin = 5 * (int(cmd[2]) - 1) + (int(cmd[1])) #print (bin) count = 0 unique = [] for data in allDetectionData: if (data[3] == bin) and (not data[0] in unique): count = count + 1 unique.append(data[0]) clientsocket.send(str.encode(str(count))) if cmd[0] == 'get_measurement': #allMeasurementData.append([latestMeas, [pos[0], pos[1]], bin]) # latestMeas, [pos0, pos1], bin bin = 5 * (int(cmd[2]) - 1) + (int(cmd[1])) - 1 print (bin) sum = 0 unique = [] for data in allMeasurementData: if (data[3] == bin) and (not data[2] in unique): sum += data[0] unique.append(data[2]) clientsocket.send(str.encode(str(sum))) if cmd[0] == "get_adjacent_measurement": agent = agentList[0] factor = 2 xll = (int(cmd[1]) - 1) * factor * 2 yll = (int(cmd[2]) - 1) * factor * 2 pos = agent.getPos() bin = E.getAbstractPos(pos[0], pos[1]) - 1 unique = [] count = [0, 0, 0, 0] time = [[], [], [], []] measured_data = [[], [], [], []] total_count = 0 for data in allMeasurementData: # tag ID,time,agent pos,bin if (data[3] == bin) and (not data[2] in unique): #print (data) total_count += 1 unique.append(data[2]) # north if data[2][1] > (yll + (factor * 1.50)): count[0] += data[0] measured_data[0].append(data[0]) time[0].append(data[1]) # print ("north") # south if data[2][1] < (yll + (factor *.50)): count[1] += data[0] measured_data[1].append(data[0]) time[1].append(data[1]) # print ("south") # east if data[2][0] > (xll + (factor *1.50)): count[2] += data[0] measured_data[2].append(data[0]) time[2].append(data[1]) # print ("east") # west if data[2][0] < (xll + (factor *.50)): count[3] += data[0] measured_data[3].append(data[0]) time[3].append(data[1]) # print ("west") #print ("time: ") #print (time) #print ("Measured_data : ") #print (measured_data) result = [] # north avg_rate = find_max_7_values_avg_measurement(time[0], measured_data[0]) #print ("Average value") #print (avg_rate) result.append(avg_rate) # south avg_rate = find_max_7_values_avg_measurement(time[1], measured_data[1]) #print ("Average value") #print (avg_rate) result.append(avg_rate) # east avg_rate = find_max_7_values_avg_measurement(time[2], measured_data[2]) #print ("Average value") #print (avg_rate) result.append(avg_rate) # west avg_rate = find_max_7_values_avg_measurement(time[3], measured_data[3]) #print ("Average value") #print (avg_rate) result.append(avg_rate) data_to_be_sent = ",".join(str(i) for i in result) clientsocket.send(str.encode(data_to_be_sent)) if cmd[0] == 'get_tags_adjacent': agent = agentList[0] factor = 2 xll = (int(cmd[1]) - 1) * factor * 2 yll = (int(cmd[2]) - 1) * factor * 2 pos = agent.getPos() bin = E.getAbstractPos(pos[0], pos[1]) probability = [] unique = [] count = [0, 0, 0, 0] time = [[], [], [], []] total_count = 0 for data in allDetectionData:#tag ID,time,agent pos,bin if (data[3] == bin) and (not data[0] in unique): total_count += 1 unique.append(data[0]) # north if data[2][1] > (yll + (factor * 1.50)): count[0] += 1 time[0].append(data[1]) # print ("north") # south if data[2][1] < (yll + (factor * .50)): count[1] += 1 time[1].append(data[1]) # print ("south") # east if data[2][0] > (xll + (factor * 1.50)): count[2] += 1 time[2].append(data[1]) # print ("east") # west if data[2][0] < (xll + (factor * .50)): count[3] += 1 time[3].append(data[1]) # print ("west") print (time) print (count) result = [] # north avg_rate = find_max_5_values_avg(time[0]) #print ("Average value") #print (avg_rate) result.append(avg_rate) # south avg_rate = find_max_5_values_avg(time[1]) #print ("Average value") #print (avg_rate) result.append(avg_rate) # east avg_rate = find_max_5_values_avg(time[2]) #print ("Average value") #print (avg_rate) result.append(avg_rate) # west avg_rate = find_max_5_values_avg(time[3]) #print ("Average value") #print (avg_rate) result.append(avg_rate) data_to_be_sent = ",".join(str(i) for i in result) #print ("The data is : ") #print (data_to_be_sent) clientsocket.send(str.encode(data_to_be_sent)) """ #south avg_rate = find_max_5_values_avg(time[1]) result.append(poisson_rate(avg_rate, 0.8)) #east avg_rate = find_max_5_values_avg(time[2]) result.append(poisson_rate(avg_rate, 0.8)) #west avg_rate = find_max_5_values_avg(time[3]) result.append(poisson_rate(avg_rate, 0.8)) data_to_be_sent = ",".join(str(result)) clientsocket.send(str.encode(data_to_be_sent)) # calculate time for i,each in enumerate(time): each.sort() counted_times = sum([times-each[0] for times in each]) time[i] = counted_times print (time) print (count) result = [] # calculate poison for north if time[0] and count[0]: rate = count[0]/time[0] p = math.exp(-rate) for i in xrange(total_count): p *= rate p /= i + 1 result.append(p) else: result.append(0.0) # calculate poison for south if time[1] and count[1]: rate = count[1]/time[1] p = math.exp(-rate) for i in xrange(total_count): p *= rate p /= i + 1 result.append(p) else: result.append(0.0) # calculate poison for east if time[2] and count[2]: rate = count[2]/time[2] p = math.exp(-rate) for i in xrange(total_count): p *= rate p /= i + 1 result.append(p) else: result.append(0.0) # calculate poison for west if time[3] and count[3]: rate = count[3]/time[3] p = math.exp(-rate) for i in xrange(total_count): p *= rate p /= i + 1 result.append(p) else: result.append(0.0) print (result) data_to_be_sent = ",".join(str(result)) clientsocket.send(str.encode(data_to_be_sent)) """ if cmd[0] == 'get_tags_adjacent_new': agent = agentList[0] factor = 2 xll = (int(cmd[1]) - 1) * factor * 2 yll = (int(cmd[2]) - 1) * factor * 2 pos = agent.getPos() bin = E.getAbstractPos(pos[0], pos[1]) probability = [] unique = [] count = [0, 0, 0, 0] time = [[], [], [], []] total_count = 0 for data in allDetectionData: # tag ID,time,agent pos,bin if (data[3] == bin) and (not data[0] in unique): total_count += 1 unique.append(data[0]) # north if data[2][1] > (yll + (factor * 1.50)): count[0] += 1 time[0].append(data[1]) # print ("north") # south if data[2][1] < (yll + (factor * .50)): count[1] += 1 time[1].append(data[1]) # print ("south") # east if data[2][0] > (xll + (factor * 1.50)): count[2] += 1 time[2].append(data[1]) # print ("east") # west if data[2][0] < (xll + (factor * .50)): count[3] += 1 time[3].append(data[1]) # print ("west") print (count) data_to_be_sent = ",".join(str(i) for i in count) # print ("The data is : ") # print (data_to_be_sent) clientsocket.send(str.encode(data_to_be_sent)) if cmd[0] == 'cell_lambda': agent = agentList[0] if len(cmd) < 2: pos = agent.getPos() bin = E.getAbstractPos(pos[0], pos[1]) - 1 clientsocket.send(str.encode(str(agent.belief_map[bin]))) else: #bin = E.getAbstractPos(int(cmd[1]), int(cmd[2])) - 1 bin = 5 * (int(cmd[1]) - 1) + (int(cmd[2])) - 1 clientsocket.send(str.encode(str(agent.belief_map[bin]))) det_count[0] = 0 clientsocket.close()#syncVar=True except Exception as e: traceback.print_exc() print(e) print("ending") clientsocket.close() def ErgodicComLink(): global u, run, updateGP,t run=True sock.send(str.encode(str(x_range))) while run: agent=agentList[0] st=agent.state bin=E.getAbstractPos(st[0],st[1])-1 try: if not updateGP: sock.send(str.encode(str(round(st[0],1)/x_range)+" "+str(round(st[1],1)/x_range)+" "+str(st[2])+" "+str(st[3])+" "+str(t)+" "+"None ")) else: updateGP=False sock.send(str.encode(str(round(st[0],1)/x_range)+" "+str(round(st[1],1)/x_range)+" "+str(st[2])+" "+str(st[3])+" "+str(t)+" "+str(latestMeas))) except: run=False t=simtime data = sock.recv(1024) data = data.decode('utf-8') cmd=data.split(',') if len(cmd)>1: u=(float(cmd[0]),float(cmd[1])) if st[0]>x_range or st[0]<0 or st[1]<0 or st[1]>y_range: _,utemp=wp_track(agent.getPos(),np.array([x_range/2,y_range/2])) u=np.clip(np.array([np.cos(utemp), np.sin(utemp)]),-0.1,0.1) #print(st,u) print(t,round(st[0],1),round(st[1],1),round(st[2],3),round(st[3],3),u) syncVar=True def ErgodicComLink2(): global u, run, updateGP,t run=True sock.send(str.encode(str(x_range))) while run: syncVar=False agent=agentList[0] st=agent.state bin=E.getAbstractPos(st[0],st[1])-1 try: if not updateGP: sock.send(str.encode(str(round(st[0],1)/x_range)+" "+str(round(st[1],1)/x_range)+" "+str(t)+" "+"None ")) else: updateGP=False sock.send(str.encode(str(round(st[0],1)/x_range)+" "+str(round(st[1],1)/x_range)+" "+str(t)+" "+str(latestMeas))) except: run=False t=simtime data = sock.recv(1024) data = data.decode('utf-8') cmd=data.split(',') if len(cmd)>1: u=(float(cmd[0]),float(cmd[1])) if st[0]>x_range or st[0]<0 or st[1]<0 or st[1]>y_range: _,utemp=wp_track(agent.getPos(),np.array([x_range/2,y_range/2])) u=np.clip(np.array([np.cos(utemp), np.sin(utemp)]),-0.1,0.1) #print(st,u) print(t,round(st[0],1),round(st[1],1),u) def doubleIntegratorErgodicControl(agent,update): global run,t st=agent.state try: if not update: sock.send(str.encode(str(round(st[0],1)/x_range)+" "+str(round(st[1],1)/x_range)+" "+str(st[2])+" "+str(st[3])+" "+str(t)+" "+"None ")) else: sock.send(str.encode(str(round(st[0],1)/x_range)+" "+str(round(st[1],1)/x_range)+" "+str(st[2])+" "+str(st[3])+" "+str(t)+" "+str(latestMeas))) except: run=False t=simtime return data = sock.recv(1024) data = data.decode('utf-8') cmd=data.split(',') if len(cmd)>1: u=(float(cmd[0]),float(cmd[1])) if st[0]>x_range or st[0]<0 or st[1]<0 or st[1]>y_range: _,utemp=wp_track(agent.getPos(),np.array([x_range/2,y_range/2])) u=np.clip(np.array([np.cos(utemp), np.sin(utemp)]),-0.1,0.1) return u def singleIntegratorErgodicControl(agent,update): global run,t st=agent.state try: if not update: sock.send(str.encode(str(round(st[0],1)/x_range)+" "+str(round(st[1],1)/x_range)+" "+str(t)+" "+"None ")) else: sock.send(str.encode(str(round(st[0],1)/x_range)+" "+str(round(st[1],1)/x_range)+" "+str(t)+" "+str(latestMeas))) except: run=False t=simtime return data = sock.recv(1024) data = data.decode('utf-8') cmd=data.split(',') if len(cmd)>1: u=(float(cmd[0]),float(cmd[1])) if st[0]>x_range or st[0]<0 or st[1]<0 or st[1]>y_range: _,utemp=wp_track(agent.getPos(),np.array([x_range/2,y_range/2])) u=np.clip(np.array([np.cos(utemp), np.sin(utemp)]),-0.1,0.1) return u def MidcaIntegrator(agent,update): global running, searchComplete, wp_list, E, det_count, agentList, run, t run = True st= agent.state try: if not update: #sock.send(str.encode(str(round(st[0],1)/x_range)+" "+str(round(st[1],1)/x_range)+" "+str(t)+" "+"None ")) pass else: pass #sock.send(str.encode(str(round(st[0],1)/x_range)+" "+str(round(st[1],1)/x_range)+" "+str(t)+" "+str(latestMeas))) except: run=False t=simtime return # accept connections from outside (clientsocket, address) = sock.accept() data = clientsocket.recv(1024) data = data.decode('utf-8') cmd=data.split(',') #print(cmd) if cmd[0] == 'quit': running = False run = False endSim = True elif cmd[0] == 'start': running = True elif cmd[0] == 'moveTo': x = int(cmd[1]) - 1 y = int(cmd[2]) - 1 center = np.array([x * x_range / 5.0, y * y_range / 5.0]) + np.array( [.5 * x_range / 5.0, .5 * y_range / 5.0]) wp_list[0] = [center] elif cmd[0] == 'moveToPhysicalPosition': x = int(cmd[1]) - 1 y = int(cmd[2]) - 1 center = np.array([x, y]) wp_list[0] = [center] elif cmd[0] == 'inCell': agent = agentList[0] pos = agent.getPos() bin = E.getAbstractPos(pos[0], pos[1]) x = int(cmd[1]) y = int(cmd[2]) myx, myy = E.getCellXY(pos[0], pos[1]) bin2 = 5 * (y - 1) + (x - 1) clientsocket.send(str.encode(str(x == myx and y == myy))) # print(bin, bin2) elif cmd[0] == 'time': clientsocket.send(str.encode(str(t))) elif cmd[0] == 'getCell': agent = agentList[0] pos = agent.getPos() bin = E.getAbstractPos(pos[0], pos[1]) myx, myy = E.getCellXY(pos[0], pos[1]) clientsocket.send(str.encode(str(myx) + "," + str(myy))) elif cmd[0] == 'search': x = int(cmd[1]) - 1 y = int(cmd[2]) - 1 center = np.array([x * x_range / 5.0, y * y_range / 5.0]) + np.array( [.5 * x_range / 5.0, .5 * y_range / 5.0]) wp_list[0] = search(wp_list[0], center) searchComplete = False elif cmd[0] == 'searchComplete': clientsocket.send(str.encode(str(searchComplete))) elif cmd[0] == 'get_tags': agent = agentList[0] bin = 5 * (int(cmd[2]) - 1) + (int(cmd[1])) # print (bin) count = 0 unique = [] for data in allDetectionData: if (data[3] == bin) and (not data[0] in unique): count = count + 1 unique.append(data[0]) clientsocket.send(str.encode(str(count))) elif cmd[0] == 'get_measurement': # allMeasurementData.append([latestMeas, [pos[0], pos[1]], bin]) # latestMeas, [pos0, pos1], bin bin = 5 * (int(cmd[2]) - 1) + (int(cmd[1])) - 1 print (bin) sum = 0 unique = [] for data in allMeasurementData: if (data[3] == bin) and (not data[2] in unique): sum += data[0] unique.append(data[2]) clientsocket.send(str.encode(str(sum))) elif cmd[0] == "get_adjacent_measurement": agent = agentList[0] factor = 2 xll = (int(cmd[1]) - 1) * factor * 2 yll = (int(cmd[2]) - 1) * factor * 2 pos = agent.getPos() bin = E.getAbstractPos(pos[0], pos[1]) - 1 unique = [] count = [0, 0, 0, 0] time = [[], [], [], []] measured_data = [[], [], [], []] total_count = 0 for data in allMeasurementData: # tag ID,time,agent pos,bin if (data[3] == bin) and (not data[2] in unique): # print (data) total_count += 1 unique.append(data[2]) # north if data[2][1] > (yll + (factor * 1.50)): count[0] += data[0] measured_data[0].append(data[0]) time[0].append(data[1]) # print ("north") # south if data[2][1] < (yll + (factor * .50)): count[1] += data[0] measured_data[1].append(data[0]) time[1].append(data[1]) # print ("south") # east if data[2][0] > (xll + (factor * 1.50)): count[2] += data[0] measured_data[2].append(data[0]) time[2].append(data[1]) # print ("east") # west if data[2][0] < (xll + (factor * .50)): count[3] += data[0] measured_data[3].append(data[0]) time[3].append(data[1]) # print ("west") # print ("time: ") # print (time) # print ("Measured_data : ") # print (measured_data) result = [] # north avg_rate = find_max_7_values_avg_measurement(time[0], measured_data[0]) # print ("Average value") # print (avg_rate) result.append(avg_rate) # south avg_rate = find_max_7_values_avg_measurement(time[1], measured_data[1]) # print ("Average value") # print (avg_rate) result.append(avg_rate) # east avg_rate = find_max_7_values_avg_measurement(time[2], measured_data[2]) # print ("Average value") # print (avg_rate) result.append(avg_rate) # west avg_rate = find_max_7_values_avg_measurement(time[3], measured_data[3]) # print ("Average value") # print (avg_rate) result.append(avg_rate) data_to_be_sent = ",".join(str(i) for i in result) clientsocket.send(str.encode(data_to_be_sent)) elif cmd[0] == 'get_tags_adjacent': agent = agentList[0] factor = 2 xll = (int(cmd[1]) - 1) * factor * 2 yll = (int(cmd[2]) - 1) * factor * 2 pos = agent.getPos() bin = E.getAbstractPos(pos[0], pos[1]) probability = [] unique = [] count = [0, 0, 0, 0] time = [[], [], [], []] total_count = 0 for data in allDetectionData: # tag ID,time,agent pos,bin if (data[3] == bin) and (not data[0] in unique): total_count += 1 unique.append(data[0]) # north if data[2][1] > (yll + (factor * 1.50)): count[0] += 1 time[0].append(data[1]) # print ("north") # south if data[2][1] < (yll + (factor * .50)): count[1] += 1 time[1].append(data[1]) # print ("south") # east if data[2][0] > (xll + (factor * 1.50)): count[2] += 1 time[2].append(data[1]) # print ("east") # west if data[2][0] < (xll + (factor * .50)): count[3] += 1 time[3].append(data[1]) # print ("west") print (time) print (count) result = [] # north avg_rate = find_max_5_values_avg(time[0]) # print ("Average value") # print (avg_rate) result.append(avg_rate) # south avg_rate = find_max_5_values_avg(time[1]) # print ("Average value") # print (avg_rate) result.append(avg_rate) # east avg_rate = find_max_5_values_avg(time[2]) # print ("Average value") # print (avg_rate) result.append(avg_rate) # west avg_rate = find_max_5_values_avg(time[3]) # print ("Average value") # print (avg_rate) result.append(avg_rate) data_to_be_sent = ",".join(str(i) for i in result) # print ("The data is : ") # print (data_to_be_sent) clientsocket.send(str.encode(data_to_be_sent)) elif cmd[0] == 'get_tags_adjacent_new': agent = agentList[0] factor = 2 xll = (int(cmd[1]) - 1) * factor * 2 yll = (int(cmd[2]) - 1) * factor * 2 pos = agent.getPos() bin = E.getAbstractPos(pos[0], pos[1]) probability = [] unique = [] count = [0, 0, 0, 0] time = [[], [], [], []] total_count = 0 for data in allDetectionData: # tag ID,time,agent pos,bin if (data[3] == bin) and (not data[0] in unique): total_count += 1 unique.append(data[0]) # north if data[2][1] > (yll + (factor * 1.50)): count[0] += 1 time[0].append(data[1]) # print ("north") # south if data[2][1] < (yll + (factor * .50)): count[1] += 1 time[1].append(data[1]) # print ("south") # east if data[2][0] > (xll + (factor * 1.50)): count[2] += 1 time[2].append(data[1]) # print ("east") # west if data[2][0] < (xll + (factor * .50)): count[3] += 1 time[3].append(data[1]) # print ("west") print (count) data_to_be_sent = ",".join(str(i) for i in count) # print ("The data is : ") # print (data_to_be_sent) clientsocket.send(str.encode(data_to_be_sent)) elif cmd[0] == 'cell_lambda': agent = agentList[0] if len(cmd) < 2: pos = agent.getPos() bin = E.getAbstractPos(pos[0], pos[1]) - 1 clientsocket.send(str.encode(str(agent.belief_map[bin]))) else: # bin = E.getAbstractPos(int(cmd[1]), int(cmd[2])) - 1 bin = 5 * (int(cmd[1]) - 1) + (int(cmd[2])) - 1 clientsocket.send(str.encode(str(agent.belief_map[bin]))) det_count[0] = 0 clientsocket.close() if len(cmd)>=1: return ''' psuedo code create grid world generate tag positons based on probability map and total number of fish N create agents simulation: 1. detect tags 2. update tag.lastPing 3. updte agent dynamics ''' def draw(x): plt.figure(1) plt.axis('scaled') plt.grid(True) plt.plot(x[0], x[1], 'r.') plt.xlim([0, E.x_range]) plt.ylim([0, E.y_range]) plt.xticks(np.arange(0,E.x_range,E.x_range/5.0)) plt.yticks(np.arange(0,E.y_range,E.y_range/5.0)) plt.draw() def drawAgent(x,r=None): plt.figure(1) plt.axis('scaled') plt.grid(True) plt.plot(x[0], x[1], 'bo') if r==None: pass else: circ=plt.Circle((x[0], x[1]), r, color='b', fill=False) plt.gcf().gca().add_artist(circ) plt.xlim([0, E.x_range]) plt.ylim([0, E.y_range]) plt.xticks(np.arange(0,E.x_range,E.x_range/5.0)) plt.yticks(np.arange(0,E.y_range,E.y_range/5.0)) plt.draw() def iterative_average(x,n,ave): return ave+(x-ave)/(n+1) def simulate_dynamics(agent,u,tspan,dt): inc = agent.state for i in np.linspace(tspan[0],tspan[1],int((tspan[1]-tspan[0])/dt)): inc+=agent.dynamics(inc,u)*dt#+world.flow(agent.getPos())*dt return inc def f1_plan(x0, x, N): u = np.zeros(N) xsim = x0.copy() for n in range(N): e = x-xsim angle = np.arctan2(e[1], e[0]) u[n] = angle xsim += 0.005*np.array([np.cos(u[n]), np.sin(u[n])]) return u def search(wp_list,X): #X is the center position of one of the 25 cells offset=.375*x_range/5 wp_list.append(np.array(X)) wp_list.append(np.array(X)+np.array([-offset,offset])) wp_list.append(np.array(X)+np.array([offset,offset])) wp_list.append(np.array(X)+np.array([offset,-offset])) wp_list.append(np.array(X)+np.array([-offset,-offset])) wp_list.append(np.array(X) + np.array([-offset, offset])) wp_list.append(np.array(X)) return wp_list def wp_track(x,wp_list): global searchComplete e = np.array(wp_list[0])-x if np.linalg.norm(e) < x_range/50.0 and len(wp_list) > 1: #print(wp_list) del wp_list[0] if len(wp_list) == 1: searchComplete=True return wp_list, 1*np.arctan2(e[1],e[0]) ######################## motion models ################################### def m1_step(x,u): return 1*np.array([np.cos(u), np.sin(u)]) def m2_step(x,u): # |0 0 1 0|x |0 0| # |0 0 0 1|y + |0 0|u1 # |0 0 -a 0|vx |1 0|u2 # |0 0 0 -b|vy |0 1| a=.25 return np.matmul(1*np.array([[0, 0, 1, 0],[0,0,0,1],[0,0,-a,0],[0,0,0,-a]]),x)+np.matmul(1*np.array([[0,0],[0,0],[1,0],[0,1]]),u) def m3_step(x,u): return np.array([max(min(u[0],1),-1),max(min(u[1],1),-1)]) ############################# test functions ############################################### def rastrigin(x,y): return 20+x**2+y**2-10*(np.cos(2*np.pi*x)+np.cos(2*np.pi*y)) def rosenbrock(x,y): a,b=(10,.001) return b*(y-x**2)**2+(a-x)**2 def gaussianSum(x,y): r1 = np.array([.75*x_range,.45*y_range]) r2 = np.array([.3*x_range,.7*y_range]) loc = np.array([x,y]) return 10*np.exp(-0.05*np.linalg.norm(loc-r1)**2)+15*np.exp(-0.1*np.linalg.norm(loc-r2)**2) def tagField(tagData,pos,t,time_step,sensorRange): #last_ping=tagData[:,0],posx=tagData[:,1],posy=tagData[:,2],posz=tagData[:,3],delay=tagData[:,4],ID=tagData[:,5],bin=tagData[:,6]=tagData #diff=tagData[:,1:3]-np.array([pos[0],pos[1]]) distance=np.linalg.norm(tagData[:,1:3]-np.array([pos[0],pos[1]]),axis=1) eps=time_step/100.0 c1=(np.fmod(t,tagData[:,4]+eps)-(tagData[:,0]+tagData[:,4]))<time_step c2=(np.fmod(t,tagData[:,4]+eps)>(tagData[:,0]+tagData[:,4])) pinging = np.logical_and(c1,c2) dtSet= np.logical_and(distance<sensorRange,pinging) return tagData[np.where(pinging)[0],:],tagData[np.where(dtSet)[0],5],np.sum(dtSet)#pinging,detection set,detectionNum density_map = np.array([0.1, 0.1, 0.4, 0.3, 0.2, 0.1, 0.3, 0.3, 0.1, 0.3, 0.2, 0.3, 0.3, 0.2, 0.1, 0.3, 0.9, 0.3, 0.2, 0.1, 0.2, 0.3, 0.2, 0.1, 0.1]) #################################### simulation settings ################################### N = 1000 #how many tags present simtime=1000 #max simulation time numAgents=1 #number of agents exploring sensorRange=2 x_range=20.0 #grid size y_range=20.0 spacing=(1,1)#(.5,.5) #spacing between points for visualizing fields searchMethods = ["MIDCA","SUSD","ERGODIC_DI","DEMO","ERGODIC_SI"] method = searchMethods[0] fields= ["tag","gassian sum","rosenbrock","rastrigin"] #fieldMax = [(5.5,14,1.5),(.3*x_range,.7*y_range,14)]#tag field absolute max 9.5 # for tag_100 #fieldMax = [(5.5,14,2),(.3*x_range,.7*y_range,14)]#tag field absolute max 9.5 # for tag_200 #fieldMax = [(5.5,14,4.1),(.3*x_range,.7*y_range,14)]#tag field absolute max 9.5 # for tag_500 fieldMax = [(5.5,14,6),(.3*x_range,.7*y_range,14)]#tag field absolute max 9.5 # for tag_1000 field = fields[0] measurement_time = 2.0 time_step=.5 #start_pos=(.05*x_range,.1*y_range) """ start_pos = [(4.361675414742551382e+00, 1.458277069766090328e+01), (1.545820006278236569e+01, 6.457247090829543623e+00), (6.295868290928718913e-01, 7.231587833833630796e+00), (1.125840547944832792e+01, 4.275635236417141272e-01), (1.547922926485634232e+00, 4.900255414078060312e+00), (1.510704267728113237e+01, 1.783478215173388648e+01), (2.204755346558018303e-01, 6.173268062869025741e+00), (4.958469349586305697e+00, 4.716507947006558510e+00), (1.479491107030286301e+01, 1.459564048874953457e+01), (3.171471926407209985e+00, 1.005076470181938575e+01), (1.234584097168078287e+01, 6.461087057506860631e+00), (1.067132595610898349e+01, 1.024013704378120160e+01), (2.627585809888457469e+00, 1.260149797724160514e+01), (4.046709532503120599e+00, 1.067246776102524386e+01), (1.408113055270808722e+01, 1.423915807887335561e+01), (1.414334725656964054e+01, 1.920331742981397838e+01), (8.702805949851414979e+00, 1.927219991502269991e+01), (1.902459420257870448e+01, 1.459444585671132621e+01), (1.071787563199973192e+01, 6.014617171762742132e+00), (7.813659480510352751e+00, 3.109500212981364253e+00) ] """ start_pos = (1.545820006278236569e+01, 6.457247090829543623e+00) show_only_when_pinging=False stopOnMax = True visualize = True syncronize = True logData=True ############################################################################################### t=0 last_meas=t run=False running=False searchComplete=False updateGP=False latestMeas=0 u=0 taglist=[] agentList=[] tagx=np.zeros(N) tagy=np.zeros(N) """ for i in range(N): #taglist.append(AcousticTag(i,last_ping=-np.random.rand()),ping_delay=max(2,30*np.random.randn())) # most realistic taglist.append(AcousticTag(i,last_ping=-17*np.random.rand())) # more realistic (pings are not aligned in time) # taglist.append(AcousticTag(i)) #better for understanding because pings are aligned in time and all have same ping interval x,y,_ = taglist[i].pos tagx[i]=x tagy[i]=y """ E = Grid(taglist,x_range=x_range, y_range=y_range) if field == fields[0]: taglist= E.loadTagList("testField1_1000") #E.setMap(density_map) tagData=np.genfromtxt("testField1_1000.csv",delimiter=",") #E.saveTagList("tags") for i in range(numAgents): s= AcousticReciever(np.array([0,0,0]),sensorRange) if method == searchMethods[2]: #agentList.append(Agent(np.array([np.random.rand()*x_range,np.random.rand()*y_range,0,0]),s,E,dim=2)) agentList.append(Agent(np.array([start_pos[0],start_pos[1],0,0]),s,E,dim=2)) agentList[i].dynamics=m2_step u=[0,0] elif method == searchMethods[4]: #agentList.append(Agent(np.array([np.random.rand()*x_range,np.random.rand()*y_range,0,0]),s,E,dim=2)) agentList.append(Agent(np.array([start_pos[0],start_pos[1]]),s,E,dim=2)) agentList[i].dynamics=m3_step u=[0,0] else: #agentList.append(Agent(np.array([np.random.rand()*x_range,np.random.rand()*y_range]),s,E,dim=2)) agentList.append(Agent(np.array([start_pos[0],start_pos[1]]),s,E,dim=2)) agentList[i].dynamics=m1_step for i in range(len(taglist)): x,y,_ = taglist[i].pos tagx[i]=x tagy[i]=y if field == fields[1]: nx_bins = int(x_range/spacing[0]) ny_bins = int(y_range/spacing[1]) x_bins=np.array(range(nx_bins))*x_range/nx_bins y_bins=np.array(range(ny_bins))*y_range/ny_bins plottingPoints = [(idx+spacing[0]/2.0,idy+spacing[1]/2.0,gaussianSum(idx+spacing[0]/2.0,idy+spacing[1]/2.0)) for idx in x_bins for idy in y_bins] plottingPoints = np.array(plottingPoints) plottingPoints.shape=(nx_bins,ny_bins,3) if field == fields[2]: nx_bins = int(x_range/spacing[0]) ny_bins = int(y_range/spacing[1]) x_bins=np.array(range(nx_bins))*x_range/nx_bins y_bins=np.array(range(ny_bins))*y_range/ny_bins plottingPoints = [(idx+spacing[0]/2.0,idy+spacing[1]/2.0,rosenbrock(idx+spacing[0]/2.0,idy+spacing[1]/2.0)) for idx in x_bins for idy in y_bins] plottingPoints = np.array(plottingPoints) plottingPoints.shape=(nx_bins,ny_bins,3) if field == fields[3]: nx_bins = int(x_range/spacing[0]) ny_bins = int(y_range/spacing[1]) x_bins=np.array(range(nx_bins))*x_range/nx_bins y_bins=np.array(range(ny_bins))*y_range/ny_bins plottingPoints = [(idx+spacing[0]/2.0,idy+spacing[1]/2.0,rastrigin(idx+spacing[0]/2.0,idy+spacing[1]/2.0)) for idx in x_bins for idy in y_bins] plottingPoints = np.array(plottingPoints) plottingPoints.shape=(nx_bins,ny_bins,3) #draw((tagx,tagy)) ''' for t in range(N): draw(taglist[t].pos) #plt.pause(.1) ''' # simulation #input('Enter to begin simulation') ######################### socket threads ############################################### # create an INET, STREAMing socket sock = socket.socket(socket.AF_INET, socket.SOCK_STREAM) if method == searchMethods[2] or method == searchMethods[4]: # connect to ergodic controller sock.connect(('localhost', 8080)) if method == searchMethods[2] or method == searchMethods[4] and syncronize: sock.send(str.encode(str(x_range))) if method == searchMethods[2] and not syncronize: xthread = threading.Thread(target=ErgodicComLink) xthread.start() if method == searchMethods[4] and not syncronize: xthread = threading.Thread(target=ErgodicComLink2) xthread.start() if method == searchMethods[0] and syncronize: # now do something with the clientsocket # in this case, we'll pretend this is a threaded server sock.bind(('127.0.0.1', 5700)) sock.listen(5) else: # now do something with the clientsocket # in this case, we'll pretend this is a threaded server xthread = threading.Thread(target=MidcaComLink) xthread.start() while not running: pass ########################################################################## if method==searchMethods[3] or method==searchMethods[0]: wp_list = [[],[],[]] #wp_list[0] = search(wp_list[0], [.3*x_range, .3*y_range]) #wp_list[0] = search(wp_list[0], [.3*x_range, .7*y_range]) #wp_list[0] = search(wp_list[0], [5.5, 14]) if method==searchMethods[3] or method==searchMethods[0]: wp_list = [[],[],[]] for i in range(len(agentList)): agent=agentList[i] pos=agent.getPos() wp_list[i] = [[pos[0], pos[1]]] det_count=[0,0,0] ################################################ simulation loop #################################### endSim=False maxMeas=0 while t<=simtime:#or running: #change to better simulation stopping criteria posx=np.zeros(numAgents) posy=np.zeros(numAgents) pinging_x =np.zeros(1) pinging_y =np.zeros(1) #print(t) for i in range(len(agentList)): agent=agentList[i] pos=agent.getPos() #state = agent.getPos()# #srange=agent.sensor.range if method==searchMethods[3] or method==searchMethods[0]: wp_list[i], u = wp_track(np.array(pos), wp_list[i]) MidcaIntegrator(agent, updateGP) #print(t, pos, u, latestMeas) if updateGP: updateGP = False #print(t,pos,u,latestMeas) if method == searchMethods[2] and syncronize: u=doubleIntegratorErgodicControl(agent,updateGP) #print(t,pos,u,latestMeas) if updateGP: updateGP=False if method == searchMethods[4] and syncronize: u = singleIntegratorErgodicControl(agent, updateGP) print(t, pos, u, latestMeas) if updateGP: updateGP = False state=simulate_dynamics(agent,u, [0,time_step],.1) dets=agent.updateAgent(state,t) pos=agent.getPos() if field == fields[0]: pinging,detSet,dets2=tagField(tagData,pos,t,time_step,sensorRange) #print(t,pinging.shape,dets,dets,detSet,agent.sensor.detectionSet) allDetectionData = agent.sensor.detectionList # history of every tag detection. includes (tag ID,time,agent pos,bin) det_count[i]+=dets if field == fields[3]: latestMeas=rastrigin(pos[0],pos[1]) if last_meas+measurement_time<=t: updateGP = True elif field == fields[2]: latestMeas=rosenbrock(pos[0],pos[1]) if last_meas+measurement_time<=t: updateGP = True elif field == fields[1]: latestMeas=gaussianSum(pos[0],pos[1]) bin = E.getAbstractPos(pos[0], pos[1]) - 1 allMeasurementData.append([latestMeas, t, [pos[0], pos[1]], bin]) if latestMeas >= fieldMax[1][2]: endSim=True if last_meas+measurement_time<=t: updateGP = True elif field == fields[0]: if last_meas+measurement_time<=t: updateGP = True bin=E.getAbstractPos(pos[0],pos[1])-1 dtSet=agent.sensor.detectionSet rate_meas = len(dtSet)*1.0/measurement_time latestMeas=rate_meas if latestMeas >= fieldMax[0][2]: endSim=True agent.belief_count[bin]+=1 agent.belief_map[bin]= iterative_average(rate_meas,agent.belief_count[bin],round(agent.belief_map[bin],3)) #iteratively average rate measurement if len(agent.sensor.detectionSet)>0: #print("agent ",i,", rate = ",rate_meas,",average rate = ",agent.belief_map[bin], " in bin ", bin) #print(last_meas,t,dtSet) agent.sensor.detectionSet=set() posx[i]=pos[0] posy[i]=pos[1] plt.clf() if last_meas+measurement_time<=t: last_meas=t if field == fields[0]: for tag in taglist: if show_only_when_pinging: if tag.pinging(t): x,y,_ = tag.pos pinging_x=np.append(pinging_x,x) pinging_y=np.append(pinging_y,y) tag.updatePing(t) if show_only_when_pinging and visualize: draw((pinging_x,pinging_y)) elif visualize: draw((tagx,tagy)) if (field == fields[1] or field == fields[2] or field == fields[3]) and visualize: updateGP = True sensorRange=None plt.contourf(plottingPoints[:,:,0], plottingPoints[:,:,1],plottingPoints[:,:,2], 20, cmap='coolwarm')# cmap='inferno'), cmap='RdGy') if maxMeas<latestMeas: maxMeas=latestMeas if endSim and stopOnMax: break t+=time_step if visualize: drawAgent((posx,posy),r=sensorRange) plt.pause(0.00001) #plt.pause(time_step) ################################################ end simulation loop #################################### ################################################ final plots ###################################### run=False if method==searchMethods[2] or method==searchMethods[4]: sock.send("end ".encode('utf-8')) #input('done') if field == fields[0]: draw((tagx,tagy)) drawAgent((posx,posy),r=sensorRange) for i in range(len(agentList)): agent=agentList[i] print("agent ",i," rate estimates") agent.belief_map.shape=(5,5) print(np.flip(agent.belief_map,0)) print("and measurements taken per cell") agent.belief_count.shape=(5,5) print(np.flip(agent.belief_count,0)) print("True probability density map") E.p.shape=(5,5) print(np.flip(E.p,0)) #spacing=(50,50) """ print("Rate field approximation for sensor with range",sensorRange," spaced at intervals of",spacing) approx,pnts=E.approximateField(measurement_time,spacing=spacing,sensorRange=sensorRange,get_points=True) #print(np.round(approx,decimals=2)) plt.figure(2) plt.axis('scaled') plt.grid(True) #print('\n',pnts[:,:,0],'\n',pnts[:,:,1]) #plt.plot(pnts[:,:,0].flatten(), pnts[:,:,1].flatten(), 'r.',cmap='coolwarm') plt.contourf(pnts[:,:,0], pnts[:,:,1], np.flip(np.round(approx,decimals=2),(0,1)).transpose(), 20, cmap='coolwarm')# cmap='inferno'), cmap='RdGy') cbar = plt.colorbar() cbar.set_label('Detection rate') """ if field == fields[1] or field == fields[2] or field == fields[3]: plt.contourf(plottingPoints[:,:,0], plottingPoints[:,:,1],plottingPoints[:,:,2], 20, cmap='coolwarm')# cmap='inferno'), cmap='RdGy') drawAgent((posx,posy)) plt.figure(2) plt.axis('scaled') plt.grid(True) plt.contourf(plottingPoints[:,:,0], plottingPoints[:,:,1],plottingPoints[:,:,2], 20, cmap='coolwarm')# cmap='inferno'), cmap='RdGy') cbar = plt.colorbar() cbar.set_label('heat map') plt.xlim([0, x_range]) plt.ylim([0, y_range]) plt.xticks(np.arange(0,x_range,spacing[0])) plt.yticks(np.arange(0,y_range,spacing[1])) plt.draw() plt.pause(0.00001) if logData: f=open("log.txt",'a') f.write(field+","+str(t)+","+str(agent.getPos())+","+str(latestMeas)+"\n") f.close() print(str(t)+","+str(agent.getPos())+","+str(latestMeas),", max val: ",maxMeas) sock.close() print('done')

UTF-8

Python

py

fieldComparisonMidca.py

wtbarnes/tutorial-notebooks

045fb49f2bdd37ee06fe9784377955c594e92578

6a58661ebe27bf45540c7f1d8d4554cb298e5a47

/2021_HinodeIRIS/fit-eis-data.py

6ba5cadb45d4ba65fe24ff5e7cc50b9ab0e4a7e3

permissive

https://github.com/wtbarnes/tutorial-notebooks

44da1cf9e4631fd5a579a670832c7ee2f6e86ad1

74e8a5305d7ccfe2cfb99c13efbff0391e910a62

refs/heads/master

MIT

""" Download level 1 EIS HDF5 files for 2021-04-24 and then fit the Fe XII 195.119 profile to produce level 3 FITS files """ import eispac import eispac.net # This registers the EIS NRL client from sunpy.net import Fido, attrs as a if __name__ == '__main__': # Download the level 1 data q = Fido.search( a.Time('2021-04-24 04:00:00','2021-04-24 05:00:00'), a.Instrument('EIS'), a.Physobs.intensity, a.Source('Hinode'), a.Provider('NRL'), a.Level('1'), ) files = Fido.fetch(q) files = sorted(files) # Read in the fitting templates template_names = [ 'fe_12_195_119.1c.template.h5', ] templates = [eispac.read_template(eispac.data.get_fit_template_filepath(t)) for t in template_names] # Fit level 1 data using each template and save out the intensity for t in templates: cube = eispac.read_cube(files[0], window=t.central_wave) fit_res = eispac.fit_spectra(cube, t, ncpu='max') m = fit_res.get_map(measurement='intensity') m.save(f"data/eis_{'_'.join(m.measurement.lower().split())}.fits", overwrite=True)

UTF-8

Python

py

fit-eis-data.py

KoyamaLab/composition

d372ba0d003c92d4e4f0243be3eb99afb0a62c8b

85eeb016eb23707af6efc5bb93c92c2f4f547af4

/composition.py

a18614bfccc93a4e70c8660bd91e67e4e4f70059

no_license

https://github.com/KoyamaLab/composition

1d502ebf217d54a6c3fe5dcd3f35c35ab4b074a5

c836b453b784c613aa1d89518accb823917ec28a

refs/heads/master

#!/usr/bin/env python3 # -*- coding: utf-8 -*- # Calculate composition of alloy # # arguments: # argv[0] : dictionary, { 'element_name': element_composition, ... } # argv[1] : float, alloy_weight [g] import sys from elements import ELEMENTS def debug(arg): print(arg) mass = arg[1] t = int(arg[2]) elms = {} for i in range(t): elms.update({arg[3+i]:float(arg[3+i+t])}) print(elms) def composition(arg): mol_mass = 0 mass = float(arg[1]) # 最終生成質量 t = int(arg[2]) # t元系 elms = {} for i in range(t): elms.update({arg[3+i]:float(arg[3+i+t])}) for name, val in elms.items(): elem = ELEMENTS[name] mol_mass += elem.mass * val for name, val in elms.items(): elem = ELEMENTS[name] print(elem.name, mass / mol_mass * val * elem.mass) if __name__ == "__main__": #debug(sys.argv) composition(sys.argv)

UTF-8

Python

py

composition.py

sguttikon/openai-rosbot-env

c252fac22c38a2f1b3c69f9b58327ef06010c0fc

2a6f9db66bea745ec6ad33ee59e1d557b07e27bf

/gazebo_models/indoor_layouts/src/layout_to_occpmap.py

1865c4c7b85eaf0622320dc39db3b4a76d432478

permissive

https://github.com/sguttikon/openai-rosbot-env

bd958b6614e5a4ffa3f69caba18b2b4d97d3b662

e34a5843c8218ae733ee4e0d3ccecdf13ccafd87

refs/heads/master

#!/usr/bin/env python3 import argparse import numpy as np import cv2 as cv def get_occupany_map(img: np.ndarray, output_path: str, output_size: tuple): """ Convert the HouseExpo indoor layout to occupancy map Parameters ---------- img: numpy.ndarray input image output_path: str full path (*.pgm) indicating where to store the file output_size: tuple the output image shape as (rows, cols) """ (rows, cols) = img.shape # the houseexpo layout has black-background so perform inverse transform _, thresh_img = cv.threshold(img, 1, 255, cv.THRESH_BINARY_INV) # find and draw contours i.e, borders # reference: https://docs.opencv.org/3.4/d4/d73/tutorial_py_contours_begin.html contours, hierarchy = cv.findContours(thresh_img, cv.RETR_TREE, cv.CHAIN_APPROX_SIMPLE) cv.drawContours(thresh_img, contours, contourIdx=1, color=100, thickness=3) # switch colors => 205: unknown, 255: free, 0: occupied thresh_img = np.where(thresh_img==255, np.uint8(205), thresh_img) # unknown thresh_img = np.where(thresh_img==0, np.uint8(255), thresh_img) # free thresh_img = np.where(thresh_img==100, np.uint8(0), thresh_img) # obstacle # add padding to borders to make the output have equal width and height padding = max(rows, cols) + 50 thresh_img = cv.copyMakeBorder(thresh_img, (padding-rows)//2, (padding-rows)//2, \ (padding-cols)//2, (padding-cols)//2, cv.BORDER_CONSTANT, value=205) thresh_img = cv.resize(thresh_img, output_size) # store the image cv.imwrite(output_path, thresh_img) if __name__ == '__main__': parser = argparse.ArgumentParser(description='Convert HouseExpo indoor layout images to occupany map') parser.add_argument('--file_path', dest='file_path', \ required=True, help='full path to layout image') parser.add_argument('--output_path', dest='output_path', \ required=True, help='full path to output image (*.pgm)') parser.add_argument('--o_shape', dest='o_shape', type=int, \ default=768, help='output occupancy map shape') args = parser.parse_args() img = cv.imread(args.file_path, cv.IMREAD_UNCHANGED) get_occupany_map(img, args.output_path, (args.o_shape, args.o_shape))

UTF-8

Python

py

layout_to_occpmap.py

bdnaeem3/pyBlog

67564593f5c8a173243e41096114273d8aa3cdb5

c7b7667f3ac846de17a27ce85cd99bc085bec74b

/blog/serializer.py

ea6eec9edbe13d81a7f7f29ba9ebe8c008253d49

no_license

https://github.com/bdnaeem3/pyBlog

d603de30ea6a828ff4a8ba137b44bd6e63e06715

a15fb3b04d45faebaa3b040966851e34ff1a513b

refs/heads/master

Python

from rest_framework import serializers from . import models class PostSerializer(serializers.ModelSerializer): class Meta: model = models.Post fields = ('id', 'title', 'content', 'date_created', 'author') extra_kwargs = { 'author': { 'read_only': True } }

UTF-8

Python

py

serializer.py

patrickxrivera/python-flask-rest-api

757a63de5c831b7b9c26d740c68c1d14ea05ff8b

9951b6539b96a9505f47294f46d17be2b74cf313

/section3/src/app.py

d99adcd0472342f3e909f773006e4158611b8303

no_license

https://github.com/patrickxrivera/python-flask-rest-api

7421c354ab3a49443de62254cc4261ac7ba3bdf0

0d9fef6fe402502f699f0a3b834e7b0f758067c9

refs/heads/master

from flask import Flask, jsonify, request app = Flask(__name__) stores = [ { 'name': 'Complete Life Optimization', 'items': [ { 'name': 'Bulletproof Coffe', 'price': 20.99 } ] } ] @app.route('/store', methods=['POST']) def create_store(): request_data = request.get_json() new_store = { 'name': request_data['name'], 'items': [] } stores.append(new_store) return jsonify(new_store) def find_target_store(target_store_name): def find(store): return store['name'] == target_store_name return find @app.route('/store/<string:name>') def get_store(name): target_store = list(filter(find_target_store(name), stores)) return jsonify({'store': target_store}) if target_store else jsonify({'message': 'No store found with that name.'}) @app.route('/stores') def get_stores(): return jsonify({'stores': stores}) @app.route('/store/<string:name>/item') def create_item_in_store(name): request_data = request.get_json() for store in stores: if store['name'] == name: new_item = { 'name': request_data['name'], 'price': request_data['price'] } store['items'].append(new_item) jsonify({'new_item': new_item}) return jsonify({'message': 'store not found'}) @app.route('/store/<string:name>/item') def get_items_in_store(name): for store in stores: if name == store['name']: return jsonify({'store': store['items']}) return jsonify({ message: 'No store found with that name.' }) app.run(port=5000)

UTF-8

Python

py

app.py

Dawitworku/Python-stack

5df4894875d219eb9593c280bf246e627fc8f99f

f0520714c2a49bd89c131446d947677fe5a5df5f

/_python/OOP/MathDojo/Math_Dojo.py

cb0d82595b3e6c60f02aa0ae34df048d034c3ab4

no_license

https://github.com/Dawitworku/Python-stack

38c12f70279c3c913f5eefd47b9954939de2690b

198645fa4eef948895be238828b2ce998a37ed03

refs/heads/master

class MathDojo: def __init__(self): self.result = 0 def add(self, num, *nums): splat = 0 for i in nums: splat += i self.result += num + splat return self def subtract(self, num, *nums): splatvar = 0 for i in nums: splatvar -= i self.result -= (num - splatvar) return self # create an instance: md = MathDojo() # x = md.add(2).add(2,5,1).subtract(3,2).result x = md.add(2).result print(x) y = md.add(150).add(100,55,45).subtract(30,200).result print(y) z = md.add(5).add(5,5,5).subtract(5,5).result print(z) # x = md.add(2) # y = md.add(2,5,1) # z = md.subtract(3,2,5)

UTF-8

Python

py

Math_Dojo.py

jaw566/RosConnect

b1bbab597b30ad31fbd8e1fa64e4cfda7e37aabc

6d9a30a1eb771057aa95b882fffe40a6aadf0264

/App/init_desktop_file.py

6f48dedde331857a9cbaee86fea8a379afe81b6b

no_license

https://github.com/jaw566/RosConnect

28c1fa76c6aa97ca585bbd2e0da3d0bdb747a332

50a5a803c4c3db2435b5a7926066dfb25228a9ff

refs/heads/master

#!/usr/bin/env python3 import os def main(): HOME = os.environ['HOME'] with open(HOME+'/Desktop/RosConnect.desktop','r') as file: data = file.readlines() data[4] = "Icon="+HOME+"/logo.png\n" with open(HOME+'/Desktop/RosConnect.desktop','w') as file: file.writelines(data) if __name__ == "__main__": main()

UTF-8

Python

py

init_desktop_file.py

DarkLii/Hogwarts-16

59a31af389448e0849fd529dc3d0a3f4a2e60408

b9f6d0c29da869e844ae88132aecd9d10072241b

/pytest_allure/data_base/redis/redis_op.py

81c96b9dfaf081710b2300621787f8b6dadc73e7

no_license

https://github.com/DarkLii/Hogwarts-16

63b10ff3ace397b7b95731d2882bfb97f6e537c9

d0de06281afad023b1bc94221c8117bf111c9479

refs/heads/master

# -*- coding:utf-8 -*- # @Author: DarkLi # @Time : 2020/8/28 # @Desc : redis 操作封装 import json from redis import StrictRedis, ConnectionPool from pytest_allure.utiles.decorator import log_wrapper class RedisOp: def __init__(self, obj, data_base_config): # if hasattr(obj, "Log") and obj.Log.get("output_console", True): # self.log = Logger(level="info") # else: # self.log = None self.log = obj.log if hasattr(obj, "log") else None self.host = data_base_config["host"] self.port = data_base_config["port"] self.user = data_base_config["user"] self.password = data_base_config["password"] self.db = data_base_config["database"] self.charset = data_base_config.get("charset", "UTF-8") self.decode_responses = data_base_config.get("decode_responses", True) self.pool = ConnectionPool(host=self.host, port=self.port, password=self.password, db=self.db, decode_responses=self.decode_responses) # 获取连接 self.connection = StrictRedis(connection_pool=self.pool) def close(self): # 关闭连接池所有连接，PS：慎用 self.connection.connection_pool.disconnect() """ string 类型 redis 操作：{"key": "value"} """ @log_wrapper def set(self, key, value, time=None): """ 单条插入 key_value :param key: :param value: :param time: 单位为秒 :return: """ if isinstance(value, dict): value = json.dumps(value, ensure_ascii=False) if time: ret = self.connection.setex(key, time, value) else: ret = self.connection.set(key, value) return ret @log_wrapper def setnx(self, key, value): """ key 不存在时 插入数据 :param key: :param value: :return: """ return self.connection.setnx(key, value) @log_wrapper def psetex(self, name, time_ms, value): """ 插入含过期时间的 key_value :param name: :param time_ms: 单位为毫秒 :param value: :return: """ return self.connection.psetex(name, time_ms, value) @log_wrapper def mset(self, key_value_dict): """ 批量插入 key_value :param key_value_dict: :return: """ for key, value in key_value_dict.items(): if isinstance(value, dict): key_value_dict[key] = json.dumps(value, ensure_ascii=False) return self.connection.mset(key_value_dict) @log_wrapper def msetnx(self, key_value_dict): """ key 均不存在时才插入 :param key_value_dict: :return: """ return self.connection.msetnx(key_value_dict) @log_wrapper def get(self, key): """ 获取 key 的 value :param key: :return: """ return self.connection.get(key) @log_wrapper def mget(self, key_list): """ 回多个 key 对应的 value :param key_list: 格式为 列表 :return: """ return self.connection.mget(key_list) @log_wrapper def getset(self, key): """ 给数据库中 key 赋予值 value 并返回上次的 value :param key: :return: """ return self.connection.getset(key) @log_wrapper def keys(self, key): """ 获取所有符合规则的 key :param key: eg: "n*" :return: """ return self.connection.keys(key) """ redis key 操作 """ @log_wrapper def exists(self, key): """ 判断 key 是否存在 :param key: :return: """ return self.connection.exists(key) @log_wrapper def expire(self, key, time): """ 设定key的过期时间，单位秒 :param key: :param time: 单位秒 :return: """ return self.connection.expire(key, time) @log_wrapper def delete(self, key): """ 删除一个 key :param key: :return: """ return self.connection.delete(key) @log_wrapper def mdelete(self, key_list): """ 删除多个指定的 key :param key_list: :return: """ for key in key_list: self.connection.delete(key) """ hash 类型 redis 操作：{"name":{"key": "value"}} """ # TODO hash 类型 redis 操作 """ list 类型 redis 操作：{"key": []} """ # TODO list 类型 redis 操作 if __name__ == '__main__': data_base_config = { "host": "172.16.11.127", "port": 6379, "database": 13, "user": "root", "password": "standalone_passwd_test", } data_base = RedisOp(data_base_config) test_key = "test_key" test_value = "test_value" data_base.set(test_key, test_value) data_base.get(test_key) key_value_dict = { "mset_key_1": {"mset_key_111": "mset_value_111"}, "mset_key_2": {"mset_key_222": "mset_value_222"}, } data_base.mset(key_value_dict) key_list = [test_key, "mset_key_1", "mset_key_2"] data_base.mdelete(key_list)

UTF-8

Python

py

redis_op.py

wyu0hop/check_APPPacker

2e697d3db308ab8049ea2f4157a6a94acae88db5

1d917be085435f66658b86cf9b9b285ecb0a1e56

/check_APPPacker.py

2b27a5ab4991963a9e9c404f71a98a86ab0648e9

no_license

https://github.com/wyu0hop/check_APPPacker

0c37dfcf02ad36f6a394de351f9b35e00b8096bd

16d25c0d49d600f16d4e7ddb32a4d02095d51c92

refs/heads/master

import zipfile import sys #@Time :2019.12.3 #@Author :zengxin packer_dict={ "libchaosvmp.so":"使用了娜迦进行加固", "libddog.so":"使用了娜迦进行加固", "libfdog.so":"使用了娜迦进行加固", "libedog.so":"使用了娜迦企业版进行加固", "libexec.so":"使用了爱加密加固（可能性大）或腾讯进行加固", "libexecmain.so":"使用了爱加密进行加固", "ijiami.dat":"使用了爱加密进行加固", "ijiami.ajm":"使用了爱加密企业版进行加固", "af.bin":"使用了爱加密进行加固", "signed.bin":"使用了爱加密进行加固", "libsecexe.so":"使用了梆梆免费版进行加固", "libsecmain.so":"使用了梆梆免费版进行加固", "libSecShell.so":"使用了梆梆免费版进行加固", "secData0.jar":"使用了梆梆免费版进行加固", "libSecShell-x86.so":"使用了梆梆免费版进行加固", "libDexHelper.so":"使用了梆梆企业版进行加固", "libDexHelper-x86.so":"使用了梆梆企业版进行加固", "classes.jar":"使用了梆梆定制版进行加固", "DexHelper.so":"使用了梆梆定制版进行加固", "libprotectClass.so":"使用了360进行加固", # ".appkey":"使用了360进行加固", "libjiagu.so":"使用了360进行加固", "libjiagu_art.so":"使用了360进行加固", "libjiagu_x86.so":"使用了360进行加固", "libcmvmp.so":"使用了中国移动安全进行加固", "libmogosec_dex.so":"使用了中国移动安全进行加固", "libmogosec_sodecrypt.so":"使用了中国移动安全进行加固", "libmogosecurity.so":"使用了中国移动安全进行加固", "mogosec_classes":"使用了中国移动安全进行加固", "mogosec_data":"使用了中国移动安全进行加固", "mogosec_dexinfo":"使用了中国移动安全进行加固", "mogosec_march":"使用了中国移动安全进行加固", "libegis.so":"使用了通付盾进行加固", "libNSaferOnly.so":"使用了通付盾进行加固", "libreincp.so":"使用了珊瑚灵御进行加固", "libreincp_x86.so":"使用了珊瑚灵御进行加固", "libnqshield.so":"使用了网秦进行加固", "libbaiduprotect.so":"使用了百度进行加固", "baiduprotect1.jar":"使用了百度进行加固", "baiduprotect.jar":"使用了百度进行加固", "libuusafe.jar.so":"使用了UU安全进行加固", "libuusafe.so":"使用了UU安全进行加固", "libuusafeempty.so":"使用了UU安全进行加固", "dp.arm-v7.so.dat":"使用了DexProtect进行加固", "dp.arm.so.dat":"使用了DexProtect进行加固", "aliprotect.dat":"使用了阿里聚安全进行加固", "libsgmain.so":"使用了阿里聚安全进行加固", "libsgsecuritybody.so":"使用了阿里聚安全进行加固", "libmobisec.so":"使用了阿里聚安全进行加固", "libfakejni.so":"使用了阿里聚安全进行加固", "libzuma.so":"使用了阿里聚安全进行加固", "libzumadata.so":"使用了阿里聚安全进行加固", "libpreverify1.so":"使用了阿里聚安全进行加固", "classes.dex.dat":"使用了dexprotect进行加固", "dp.arm-v7.so.dat":"使用了dexprotect进行加固", "dp.arm.so.dat":"使用了dexprotect进行加固", "libtup.so":"使用了腾讯进行加固", "libshell.so":"使用了腾讯进行加固", "tencent_stub":"使用了腾讯进行加固", "mix.dex":"使用了腾讯进行加固", "libshella":"使用了腾讯进行加固", "libshellx":"使用了腾讯进行加固", "libshella-xxxx.so":"使用了腾讯进行加固", "libshellx-xxxx.so":"使用了腾讯进行加固", "mix.dex":"使用了腾讯进行加固", "mixz.dex":"使用了腾讯进行加固", "libtosprotection.armeabi.so":"使用了腾讯御安全进行加固", "libtosprotection.armeabi-v7a.so":"使用了腾讯御安全进行加固", "libtosprotection.x86.so":"使用了腾讯御安全进行加固", "libtest.so":"使用了腾讯御安全进行加固", "tosversion":"使用了腾讯御安全进行加固", "libTmsdk":"使用了腾讯御安全进行加固", "libTmsdk-xxx-mfr.so":"使用了腾讯御安全进行加固", "libnesec.so":"使用了网易易盾进行加固", "libAPKProtect.so":"使用了APKProtect进行加固", "libkwscmm.so":"使用了几维安全进行加固", "libkwscr.so":"使用了几维安全进行加固", "libkwslinker.so":"使用了几维安全进行加固", "kdpdata.so":"使用了几维安全进行加固", "dex.dat":"使用了几维安全进行加固", "libkdp.so":"使用了几维安全进行加固", "libx3g.so":"使用了顶像科技进行加固", "libapssec.so":"使用了盛大进行加固", "librsprotect.so":"使用了瑞星进行加固", "libitsec.so":"使用了海云安进行加固", "itse":"使用了海云安进行加固", "libapktoolplus_jiagu.so":"使用了apktoolplus进行加固", "jiagu_data.bin":"使用了apktoolplus进行加固", "sign.bin":"使用了apktoolplus进行加固" } def packerDetector(apkpath): packertype="未进行加固或未匹配到该特征库" packersign="" zipfiles=zipfile.ZipFile(apkpath) nameList=zipfiles.namelist() for fileName in nameList: for packer in packer_dict.keys(): if packer in fileName: packertype=packer_dict[packer] packersign=packer print("经检测，该apk"+packertype) def main(): if len(sys.argv)==2: packerDetector(sys.argv[1]) else: print("请输入正确的apk包名") print("eg:python3 check_APPPacker.py whm_2019.apk") if __name__ == '__main__': main()

UTF-8

Python

py

check_APPPacker.py

retresco/pcrf

ef1f88edce6806df32090cc4dae6ea35b065eb27

185380ede44d0227563d2a5d8aff26228ec0b5ff

/python-wrapper/pcrf-apply-demo.py

30920937a0f592de90ca6ec5bce53f8c4da8bfa6

permissive

https://github.com/retresco/pcrf

b4086b66aba88c704530e82e9a49a202514875a5

329982ade6a5a785d5fc7b76933557aed81d2206

refs/heads/master

C++

import pcrf_python import json # Load config file config = pcrf_python.CRFConfiguration("../demo/chunk.cfg") config.set_running_text_input(True) # Load model model = pcrf_python.SimpleLinearCRFFirstOrderModel("../demo/chunker.model") # Construct applier on the basis of the CRF model and the configuration crf_applier = pcrf_python.FirstOrderLCRFApplier(model,config) # Set the output mode to "tab-separated" (the other possibility is "json", # but this currently works only for NER tasks) crf_applier.set_output_mode("tsv") # Apply to input string utf8_string = "Merkel and Obama met at the G7 summit at Schloss Elmau near Garmisch-Partenkirchen." out_string = crf_applier.apply_to(utf8_string) print('\nResults') print out_string # Apply to file out_string = crf_applier.apply_to_text_file("cl-final.txt") print('\nResults') print out_string

UTF-8

Python

py

pcrf-apply-demo.py

temirxan011/balton

45b6415a443fd2292b54d1a05579d951725ec25d

6222dc42f191f2417eb89dbe4fb3470928aba875

/Iearn_dict.py

3ac1d90fa5c3ee04d02c875cbdfda68c551569ac

no_license

https://github.com/temirxan011/balton

1a9c3133af1ec0f069d49d825fa2dc813539b0b3

97a5e18f11f9c2e8555b6e15e34752252abdf44a

refs/heads/main

import os def learn_dict(): os.system('CLS') statistics_right = statistics_wrong = 0 # переменные для введения статистики # вывод всех словарей dict_list = os.listdir(path='./dict') print('\nСПИСОК ДОСТУПНЫХ СЛОВАРЕЙ') for i in dict_list: print('| ' + i, end=' ') # запись данных из файла в список name_dict = input('\nВведите название словаря: ') with open('./dict/' + name_dict + '.txt', 'r') as f: dict = f.read().split("|") # процесс обучения и проверки правильности перевода print('\n----------|' + name_dict + '|-----------') for i in range(0, (len(dict)//2) + 2, 2): print(dict[i]) str_translite = input('Перевод: ') if str_translite == dict[i + 1]: print('ПРАВИЛЬНО' + '\n-----------------------------') statistics_right += 1 else: print('ОШИБКА,' + ' ПРАВИЛЬНЫЙ ОТВЕТ: ' + dict[i+1] + '\n-----------------------------') statistics_wrong += 1 print('--------|' + 'СТАТИСТИКА' + '|---------' + '\nПРАВИЛЬНО: ', statistics_right, ' | НЕПРАВИЛЬНО: ', statistics_wrong)

UTF-8

Python

py

Iearn_dict.py

frolkin28/alg_lab2

ebb601483af7334391597cea372f39559d431e6e

502edb2d07a4c8ab43623819518a47e0b8c9d352

/alg2.py

d4a10a22ab6fc08e40f267d3597f2b691ecaf7a0

no_license

https://github.com/frolkin28/alg_lab2

cc9d470d22c3449063499937eaa67bc41110333a

1f9faa210826045f04090acf3dd520641002a9ab

refs/heads/master

def selection_sort(array): i, size = 0, len(array) comps, swaps = 0, 0 while i < size: min_i, j = i, i + 1 while j < size: comps += 1 if array[j] < array[min_i]: min_i = j j += 1 swaps += 1 array[i], array[min_i] = array[min_i], array[i] i += 1 return array, comps, swaps def merge(array, l, m, r): comps, swaps = 0, 0 l_copy = array[l:m + 1] r_copy = array[m + 1:r + 1] l_copy_index = 0 r_copy_index = 0 sorted_index = l while l_copy_index < len(l_copy) and r_copy_index < len(r_copy): comps += 1 if l_copy[l_copy_index] <= r_copy[r_copy_index]: array[sorted_index] = l_copy[l_copy_index] l_copy_index += 1 swaps += 1 else: array[sorted_index] = r_copy[r_copy_index] r_copy_index += 1 swaps += 1 sorted_index += 1 while l_copy_index < len(l_copy): swaps += 1 array[sorted_index] = l_copy[l_copy_index] l_copy_index = l_copy_index + 1 sorted_index += 1 while r_copy_index < len(r_copy): swaps += 1 array[sorted_index] = r_copy[r_copy_index] r_copy_index += 1 sorted_index += 1 return comps, swaps comps, swaps = 0, 0 def merge_sort(array, left, right): global comps, swaps if left < right: m = (left + right) // 2 merge_sort(array, left, m) merge_sort(array, m + 1, right) temp_comps, temp_swaps = merge(array, left, m, right) print(array) comps += temp_comps swaps += temp_swaps return array, comps, swaps

UTF-8

Python

py

alg2.py

uservipin/python

b35ddf463357dbae37de88ee00b8184fe6bf71de

8370a2408372fd7b828a58cac149e690bd409308

/Classe_modules_practise/Create_Time_class.py

2c89816f311b900506aa04343789a5b3d0d7c8e1

no_license

https://github.com/uservipin/python

a0f7176817cfabbc75d7f4999efd6d4667455c19

6f7e99038e262558c395ccbdbbb26175bf55e8b7

refs/heads/main

# Create a Time class and initialize it with hours and minutes. # 1. Make a method addTime which should take two time object and add them. # E.g.- # (2 hour and 50 min)+(1 hr and 20 min) is (4 hr and 10 min) # 2. Make a method displayTime which should print the time. # 3. Make a method DisplayMinute which should display the total minutes in the Time. # E.g.- (1 hr 2 min) should display 62 minute. class Time: def __init__(self,hours,minutes): self.hours= hours self.minutes= minutes self.total_minute =0 self.minutes_and_hour=0 # print(self.hours) # print(self.minutes) def addTime(time_1,time_2): #print('Both times are: ',time_1,time_2) # print('Minutes are :',time_1.minutes) # print('Minutes_if hours are :', time_1.hours*60) # print('Minutes are :', time_2.minutes) # print('Minutes_if hours are :', time_2.hours * 60) total_minute = time_1.minutes +time_1.hours*60 +time_2.minutes+time_2.hours * 60 #print('total Minutes are : ',total_minutes) minutes_and_hour = [total_minute//60,total_minute%60] # return minutes_and_hour[0], minutes_and_hour[1] def total_minutes(self): return self.total_minute def minutes_and_hours(self): return self.minutes_and_hour t1 = Time(3,40) t2 = Time(4,50) t3 =Time.addTime(t1,t2)

UTF-8

Python

py

Create_Time_class.py

ywcmaike/pcdnet

747f50b319131a8463585fd26de4efac48e97337

7c9b4c05573c197b2b28748ecdde76d27cf62c03

/model/point_model.py

d726a1ad9eff515ac85262ad58aeb6b314855abe

no_license

https://github.com/ywcmaike/pcdnet

c196f45bbd0a79385c6743bf06411743d2d9a9d7

04330bec176cf2ea594542bb6005559bc8f77a7d

refs/heads/master

import torch import torch.nn as nn import torch.nn.functional as F from .layer.project import GraphProject, GraphProjectU def maxpool(x, dim=-1, keepdim=False): out, _ = x.max(dim=dim, keepdim=keepdim) return out class ResnetBlockFC(nn.Module): def __init__(self, size_in, size_out=None, size_h=None): super().__init__() # Attributes if size_out is None: size_out = size_in if size_h is None: size_h = min(size_in, size_out) self.size_in = size_in self.size_h = size_h self.size_out = size_out # Submodules self.fc_0 = nn.Linear(size_in, size_h) self.fc_1 = nn.Linear(size_h, size_out) self.actvn = nn.ReLU() if size_in == size_out: self.shortcut = None else: self.shortcut = nn.Linear(size_in, size_out, bias=False) # Initialization nn.init.zeros_(self.fc_1.weight) def forward(self, x): net = self.fc_0(self.actvn(x)) dx = self.fc_1(self.actvn(net)) if self.shortcut is not None: x_s = self.shortcut(x) else: x_s = x return x_s + dx class ResnetPointnet(nn.Module): def __init__(self, input_dim=128, output_dim=3, hidden_dim=128): super().__init__() self.fc_pos = nn.Linear(input_dim, 2*hidden_dim) self.block_0 = ResnetBlockFC(2*hidden_dim, hidden_dim) self.block_1 = ResnetBlockFC(2*hidden_dim, hidden_dim) self.block_2 = ResnetBlockFC(2*hidden_dim, hidden_dim) self.block_3 = ResnetBlockFC(2*hidden_dim, hidden_dim) self.block_4 = ResnetBlockFC(2*hidden_dim, hidden_dim) self.fc_c = nn.Linear(hidden_dim, output_dim) self.actvn = nn.ReLU() self.pool = maxpool def forward(self, p): batch_size, T, D = p.size() # output size: B x T X F net = self.fc_pos(p) net = self.block_0(net) pooled = self.pool(net, dim=1, keepdim=True).expand(net.size()) net = torch.cat([net, pooled], dim=2) net = self.block_1(net) pooled = self.pool(net, dim=1, keepdim=True).expand(net.size()) net = torch.cat([net, pooled], dim=2) net = self.block_2(net) pooled = self.pool(net, dim=1, keepdim=True).expand(net.size()) net = torch.cat([net, pooled], dim=2) net = self.block_3(net) pooled = self.pool(net, dim=1, keepdim=True).expand(net.size()) net = torch.cat([net, pooled], dim=2) net = self.block_4(net) c = self.fc_c(self.actvn(net)) return c class ResPointNet(nn.Module): def __init__(self, input_channel, param, output_channel=3): super(ResPointNet, self).__init__() self.param = param self.project = GraphProjectU(param.use_z_weight) self.respoint = ResnetPointnet(input_channel) def forward(self, img_feats, points, proj_mat): B = img_feats.shape[0] x = self.project(points, img_feats, proj_mat) output_points = self.respoint(x) return output_points + points

UTF-8

Python

py

point_model.py

sohaibullah4d/Practice-Problems

56609fe16f6286f077669192ef501f1bdc96c4ed

68601a11f81f414bada398cc38fac197326babc6

/3.2(a).py

5b29f42805c266180beb94e13cbd0b19e0753e4a

no_license

https://github.com/sohaibullah4d/Practice-Problems

cffec945e08d4baa93a454a0aab90aee13144f72

7ba4dd30b1381bbbd2969efe3205bd48bfc55d56

refs/heads/master

print("MUHAMMAD SOHAIB - 18B-054-CS - section A") print("\t\t\t PRACTICE PROBLEM 3.2(a)") age = int(input("Enter ypur age:")) if age > 62: print("You can get your pension benefits") else: print("Sorry")

UTF-8

Python

py

3.2(a).py

acarter881/exercismExercises

528cc46052df112413b0774f8a7a721d45d72d11

df2c7670a30d24cb53a0e3e4177f3cdfd381a5a0

/acronym/acronym.py

19bae512e68a6d518f4a0d925be055d315920aaa

no_license

https://github.com/acarter881/exercismExercises

d25a40de570db47edb95334c4c324f0707bedf50

3fe82d93ed89316630fe1819f60b075fc77f327e

refs/heads/main

import re acroRegEx = re.compile("([A-Za-z])[A-Za-z']*") def abbreviate(words): return ''.join(re.findall(acroRegEx, words)).upper() print(abbreviate('Complementary metal-oxide semiconductor'))

UTF-8

Python

py

acronym.py

zhangpeng0v0/Python_learning_notes

1ea9de413d6b05732fd981de8c56f58003aa8c2b

05ad79e3698bb484a7c0272a15610d3da955a5f3

/Python_learning_notes/code/函数/函数和过程.py

c8dea7185ae0f5391559a20b193c2610106e33b3

no_license

https://github.com/zhangpeng0v0/Python_learning_notes

5bcd3292f5d770c8cc2e895433698a7aa372ef42

8f2dc18bb13a07ec92c489d28afd66da1186bea9

refs/heads/master

# def fun(): # return None # # fun() # # def fun(): # print('hello world') # # # print('hello world')

UTF-8

Python

py

函数和过程.py

guru-aot/ccpractice

2e29d40ab39f0f4dec0980ef5d7e45b33c03c3f7

371a10da1ed0c978cb285fbe303ae493d79da1a7

/backend/tests/test_api.py

9880f34d9036890de11405c4af73008a41b4a503

no_license

https://github.com/guru-aot/ccpractice

634940a8abf2455fe18fb4a0d151bcf614210046

cdcc98ce6550d80767f392dfbe83f946e1effa4d

refs/heads/main

import uuid TEST_JWT_HEADER = { "alg": "RS256", "typ": "JWT", "kid": "foiclientapp" } TEST_JWT_CLAIMS = { "iss": "https://iam.aot-technologies.com/auth/realms/foirealm", "sub": "3559e79c-7115-41c1-bb26-1a3dc54bbf5e", "aud": ["foiclientapp"], "firstname": "Test", "lastname": "User", "realm_access": { "roles": [ "approver" ] }, "preferred_username": "user" } def factory_auth_header(jwt, claims): """Produce JWT tokens for use in tests.""" return {'Authorization': 'Bearer ' + jwt.create_jwt(claims=claims, header=TEST_JWT_HEADER)} REQUEST_OBJECT = { 'name': 'unit test1', 'description': 'Unit test the post request status', 'status': 'submitted', 'createdby': 'unittest user', 'updated': False, 'transactionid': str(uuid.uuid4()) } def test_ping(app, client): response = client.get('/') assert response.status_code == 200 def test_secure(app, client, jwt): headers = factory_auth_header(jwt=jwt, claims=TEST_JWT_CLAIMS) response = client.get('requests/test', headers=headers) assert response.status_code == 200 # def test_ping_text(app, client, jwt): # headers = factory_auth_header(jwt=jwt, claims=TEST_JWT_CLAIMS) # response = client.get('/ping', headers=headers) # assert b'pong' in response.data def test_get_requests(app, client, jwt): headers = factory_auth_header(jwt=jwt, claims=TEST_JWT_CLAIMS) response = client.get('/requests/all', headers=headers) assert response.status_code == 200 def test_get_requests_text(app, client, jwt): headers = factory_auth_header(jwt=jwt, claims=TEST_JWT_CLAIMS) response = client.get('/requests/all', headers=headers) assert b'test' in response.data def test_post_requests(app, client, jwt): headers = factory_auth_header(jwt=jwt, claims=TEST_JWT_CLAIMS) response = client.post('/requests/add', json=REQUEST_OBJECT, headers=headers) assert response.status_code == 200 def test_post_requests_text(app, client, jwt): headers = factory_auth_header(jwt=jwt, claims=TEST_JWT_CLAIMS) data = {'name': 'unit test2', 'description': 'Unit test the POST request text', 'status': 'submitted', 'createdby': 'unittest user', 'updated': False, 'transactionid': str(uuid.uuid4())} response = client.post('/requests/add', json=data, headers=headers) assert b'true' in response.data def test_update_requests(app, client, jwt): headers = factory_auth_header(jwt=jwt, claims=TEST_JWT_CLAIMS) data = {'name': 'unit test3', 'description': 'Unit test the PUT request text', 'status': 'submitted', 'createdby': 'unittest user', 'updated': False, 'transactionid': str(uuid.uuid4())} response = client.put('/requests/10', json=data, headers=headers) assert response.status_code == 200 # def test_delete_requests(app, client, jwt): # headers = factory_auth_header(jwt=jwt, claims=TEST_JWT_CLAIMS) # response = client.delete('/requests/12', headers=headers) # assert response.status_code == 200

UTF-8

Python

py

test_api.py

sbtries/class_pandaaaa

f5c3fd97d7f95c0e0d0d87fcee6ea08044227568

aef69557d8960205a780e61b7c2dfbb1d7733449

/Code/Theo/django/todo/todo_app/migrations/0002_alter_todoitem_completed_date.py

bf109484aae1281150831d0a101170f157275702

no_license

https://github.com/sbtries/class_pandaaaa

579d6be89a511bdc36b0ce8c95545b9b704a734a

bbf9c419a00879118a55c2c19e5b46b08af806bc

refs/heads/master

# Generated by Django 3.2.5 on 2021-07-29 21:18 from django.db import migrations, models class Migration(migrations.Migration): dependencies = [ ('todo_app', '0001_initial'), ] operations = [ migrations.AlterField( model_name='todoitem', name='completed_date', field=models.DateTimeField(null=True), ), ]

UTF-8

Python

py

0002_alter_todoitem_completed_date.py

tori46/DeDiv

676fe7f9ffb4f8e85e9d381e6817e26f45c9c8f9

e75324ac6a13d5176feb62dcb6310035bae16f4b

/filter_top_scores.py

f1c0823386d01aa15cb578a8257fadf1d3990d86

no_license

https://github.com/tori46/DeDiv

f393d6fea1aca446b51d9a2ff34d9c484953c164

27c9cc4c06e512594ab9ac6c1b6853762a137729

refs/heads/master

"""Filter the candidate outputs to the ones with highest likelihood score.""" import glob import json import csv import editdistance import nltk from bert_serving.client import BertClient from mosestokenizer import MosesDetokenizer from sklearn.cluster import KMeans import collections import configargparse import numpy as np import os def filter_candidates(candidates, scores, num_candidates): """Returns the num_candidates canadidates with the lowest scores.""" new_candidates, new_scores = [], [] sorted_by_score = sorted(zip(candidates, scores), key=lambda x: x[1], reverse=True) for cand, score in sorted_by_score: if cand not in new_candidates and len(cand) > 0 and len(new_candidates) < num_candidates: new_candidates.append(cand) new_scores.append(score) assert len(new_candidates) == num_candidates return new_candidates, new_scores def main(opt): if not os.path.exists(opt.output_dir): os.makedirs(opt.output_dir) all_results = {} for json_file in glob.glob(os.path.join(opt.input_dir, '*.json')): out_json_file = os.path.join(opt.output_dir, os.path.basename(json_file)) ## Check to make sure file doesn't already exist if not os.path.isfile(out_json_file): with open(json_file, 'r') as f: try: experiment = json.load(f) print('Processing ' + json_file) except: print('Error processing ' + json_file) print('Skipping it.') continue for ex_num, example in enumerate(experiment['results']): candidates = example['pred'] scores = example['scores'] candidates, scores = filter_candidates(candidates, scores, opt.num_cands) if ex_num < 3: print(candidates) print(scores) example['pred'] = candidates example['scores'] = scores out_json_file = os.path.join(opt.output_dir, os.path.basename(json_file)) with open(out_json_file, 'w') as f: json.dump(experiment, f) else: print("SKIPPING: " + json_file) if __name__ == '__main__': parser = configargparse.ArgumentParser( description='analyze_diversity.py', config_file_parser_class=configargparse.YAMLConfigFileParser, formatter_class=configargparse.ArgumentDefaultsHelpFormatter) group = parser.add_argument_group('Arguments') group.add('--input_dir', type=str, required=True, help='Directory containing json files.') group.add('--output_dir', type=str, required=True, help='Directory to write out files.') group.add('--num_cands', type=int, default=10, help='The target number of candidates.') opt = parser.parse_args() main(opt)

UTF-8

Python

py

filter_top_scores.py

vgmoose/Splite

e8cfd4b8b9c262c688e42350b69ccc20a5cada21

3c2fc3e906b1836a4c28458cf97aca2882b5f40e

/splite.py

29573e4c53bb78ec9c8dc3716285b09e63cae5e9

no_license

https://github.com/vgmoose/Splite

0c1eaa225674c519efa731261faf722637009038

78596bd3def2081fe934b3bb7f6a17bb57226c6b

refs/heads/master

import json import sys import os print ".--=============--=============--." print "| Welcome to Splite! |" print ".--=============--=============--." yeswords = ["yes", "y", "ya", "ok", "okay"] try: from PIL import Image except: ans = raw_input("The Python Image Library is required to continue. Install it now? ") if ans.lower() in yeswords: try: os.system("sudo easy_install pip") os.system("sudo pip install Pillow") except: print("Install failed. Make sure you have a working gcc compiler") exit() prev = [] try: f = open(".prev", "r") for line in f: prev.append(line) f.close() except: pass cur = open(".prev", "w") cur_line = 0 def to_rgb(argb): return "".join(map(chr, argb)).encode('hex') def sp_input(msg, default=""): global cur_line out = "| " + msg old = "" try: old += prev[cur_line].rstrip("\n") except: old = default if old != "": out += " [" + old + "]" out += ": " resp = raw_input(out) if resp == "": resp = old cur_line += 1 cur.write(resp+"\n") return resp try: sheet = sys.argv[1] print("| Using " + sheet) except: sheet = raw_input("| Path to sprite sheet: ") tile_width = int(sp_input(" Width of tile")) tile_height = int(sp_input("Height of tile")) frames = int(sp_input(" Number of frames")) names = sp_input("List of row names").replace(", ",",") dirs = names.split(",") #print ".--------------------------------" #print("| Opening your sprite sheet...") im = Image.open(sheet) pix = im.convert('RGBA') offsetx = 0 offsety = 0 autobg = to_rgb(pix.getpixel((offsety, offsetx))) truebg = sp_input("Background color", autobg) print ".--------------------------------" print "| I'm going to take " + sheet print "| make " + str(len(dirs)) + " folders: " + str(dirs) print "| representing iOS / OS X image sets" print "| with " + str(frames) + " frames each" print "| where every frame is " + str(tile_width) + "x" + str(tile_height) print "| and remove the background color #" + truebg print ".--------------------------------" ans = raw_input("| Is this correct? ") if not ans.lower() in yeswords: print("| I'm sorry to hear that :(") print ".--------------------------------" exit() atlas_name = sp_input("Enter image atlas name") print ".--------------------------------" aname = atlas_name + ".spriteatlas" print "| Making " + aname + " directory" os.mkdir(aname) #print "| Making " + aname + "/Contents.json" main_content = {"info": { "version": 1, "author": "Splite" } } outjson = open(aname + "/Contents.json", "w") outjson.write(json.dumps(main_content, indent=4, separators=(',', ': '))) outjson.close() dcount = 0 for d in dirs: print "| Processing " + d + ".imageset" for x in range(1, frames+1): bname = aname + "/" + atlas_name + "_" + d + "_" + str(x) + ".imageset" # print "| Creating " + bname + " directory" os.mkdir(bname) sub_content = { "images" : [ { "idiom" : "universal", "filename" : "tiles-0.png", "scale" : "1x" }, { "idiom" : "universal", "scale" : "2x" }, { "idiom" : "universal", "scale" : "3x" } ], "info" : { "version" : 1, "author" : "Splite" } } # print "| Creating " + bname + "/Contents.json" outjson = open(bname + "/Contents.json", "w") outjson.write(json.dumps(sub_content, indent=4, separators=(',', ': '))) outjson.close() # print "| Processing " + d + ".imageset: " + str(tile_width) + "x" + str(tile_height) + " frame #" + str(x) top = dcount*tile_height left = x*tile_width bottom = top + tile_height right = left + tile_width nim = im.crop((left, top, right, bottom)) npix = nim.load() for zy in range(0, tile_height): for zx in range(0, tile_width): if to_rgb(npix[zy, zx]) == truebg: # make transparent npix[zy, zx] = (255, 255, 255, 0) nim.save(bname + "/tiles-0.png") dcount += 1 print ".--=============--=============--." print "| All Done!! |" print ".--=============--=============--."

UTF-8

Python

py

splite.py

Vivenkko/Python

f70d26240212a2abf8b5c12f543496c6aa280ce9

f613067c07773785551f1daecb1ae4727cda83a3

/Ejercicios/Ticket de Compra/ticket.py

b12c2210716a5ca282b1daa579e605f7746a51ec

no_license

https://github.com/Vivenkko/Python

e37510ea66d07fcfbfdd9ced63dc351aad40e535

0a908ab389875480b23b30e68ff353fbe6a377c7

refs/heads/master

# -*- coding: utf-8 -*- import producto import alimentacion import electronica import ropa listaProductos = [ alimentacion('ES-SE-22314','cebolla',0.14,'11/11/2017'), alimentacion('ES-JA-23623','botella de vino',11.55,'01/01/2038'), alimentacion('ES-CO-12352','chuleta de cerdo',0.90,'10/11/2017'), alimentacion('SU-SC-23145','tableta de chocolate',1.15,'10/02/2018'), alimentacion('ES-VI-54324','queso curado de cabra',13.30,'20/0/2018'), ropa('CH-YG-92114','vaqueros negros',19.95,'38'), ropa('CH-BE-54628','camiseta joker',9.95,'M'), ropa('CH-HK-13597','deportes Fila',29.95,'43'), ropa('CH-YZ-95371','colgante Mjölnir',2.50,'12'), ropa('CH-GH-53928','tirantes negros',11.25,'M'), electronica('US-CA-52417','iPhone X',1350.00,'1 año'), electronica('US-CO-74125','portátil Mountain',2150.00,'2 años'), electronica('US-MI-95682','lcd samsung s8',250.00,'6 meses'), electronica('US-CH-12456','microSD 1 TB',100.00,'1 año'), electronica('US-TX-65236','usb cafetera',50.00,'8 meses') ] print listaProductos

UTF-8

Python

py

ticket.py

KaioAntonio/CPTBot

f1c5be6fe2d29fc0932da2f0c2bb368834a1968d

65296a1e4dbcb71011268ea6d0a926046073cf4e

/main.py

cf8c24accd77865dd65a9e1a62738174e4aaa42c

no_license

https://github.com/KaioAntonio/CPTBot

d37c0b74e926ed0d92246dd46baa928395d4b53d

76515429ea4d52184e2408d2af94b80dd83d4b86

refs/heads/master

import discord client = discord.Client() @client.event async def on_ready(): print("O BOT ESTÁ ONLINE") @client.event async def on_message(message): content = message.content.lower() channel = message.channel author = message.author.name mention = message.author.mention if(author == "CPTbot"): return if(content == "!play" and channel.name == "⭐𝐂𝐇𝐀𝐓"): await channel.send("ENVIE SOMENTE NO CHAT DE MUSICA " + mention) if (content == "bom dia" and channel.name == "⭐𝐂𝐇𝐀𝐓"): await channel.send("bom dia " + mention) if (content == "boa tarde" and channel.name == "⭐𝐂𝐇𝐀𝐓"): await channel.send("boa tarde " + mention) if (content == "boa noite" and channel.name == "⭐𝐂𝐇𝐀𝐓"): await channel.send("boa noite " + mention) client.run("ODk1MDYyNjM0OTk3NjE2NjYx.YVzGCQ.Yfi18iHdIKAHwV7A68lyN2we188")

UTF-8

Python