Rename package to pysr

README.md

@@ -1,4 +1,4 @@
-# Eureqa.jl
+# PySR.jl
 
 **Symbolic regression built on Julia, and interfaced by Python.
 Uses regularized evolution and simulated annealing.**
@@ -33,14 +33,14 @@ For python, you need to have Python 3, numpy, and pandas installed.
 
 ```python
 import numpy as np
-from eureqa import eureqa
+from pysr import pysr
 
 # Dataset
 X = 2*np.random.randn(100, 5)
 y = 2*np.cos(X[:, 3]) + X[:, 0]**2 - 2
 
 # Learn equations
-equations = eureqa(X, y, niterations=5)
+equations = pysr(X, y, niterations=5)
 
 ...
 
@@ -75,10 +75,10 @@ You can add more operators in `operators.jl`, or use default
 Julia ones. Make sure all operators are defined for scalar `Float32`.
 Then just specify the operator names in your call, as above.
 You can also change the dataset learned on by passing in `X` and `y` as
-numpy arrays to `eureqa(...)`.
+numpy arrays to `pysr(...)`.
 
 ```python
-eureqa(X=None, y=None, threads=4, niterations=20,
+pysr(X=None, y=None, threads=4, niterations=20,
    ncyclesperiteration=int(default_ncyclesperiteration),
    binary_operators=["plus", "mult"], unary_operators=["cos", "exp", "sin"],
    alpha=default_alpha, annealing=True, fractionReplaced=default_fractionReplaced,
@@ -147,6 +147,8 @@ pd.DataFrame, Results dataframe, giving complexity, MSE, and equations
 
 # TODO
 
+- [ ] Rename package to avoid trademark issues
+    - PySR?
 - [ ] Calculate feature importances of future mutations, by looking at correlation between residual of model, and the features.
     - Store feature importances of future, and periodically update it.
 - [ ] Implement more parts of the original Eureqa algorithms: https://www.creativemachineslab.com/eureqa.html

hyperparamopt.py

@@ -4,7 +4,7 @@ import numpy as np
 import pickle as pkl
 import hyperopt
 from hyperopt import hp, fmin, tpe, Trials
-import eureqa
+import pysr
 import time
 
 import contextlib
@@ -77,7 +77,7 @@ def run_trial(args):
             print(f"Starting test {i}")
             for j in range(ntrials):
                 print(f"Starting trial {j}")
-                trial = eureqa.eureqa(
+                trial = pysr.pysr(
                     test=f"simple{i}",
                     threads=4,
                     binary_operators=["plus", "mult", "pow", "div"],

eureqa.py → src/sr.py

@@ -23,7 +23,7 @@ default_topn =                    10
 default_parsimony =              1e-4
 default_perturbationFactor =     1.0
 
-def eureqa(X=None, y=None, threads=4,
+def pysr(X=None, y=None, threads=4,
             niterations=100,
             ncyclesperiteration=300,
             binary_operators=["plus", "mult"],
@@ -178,7 +178,7 @@ const y = convert(Array{Float32, 1}, """f"{y_str})""""
         'julia -O3',
         '--threads auto',
         '-e',
-        f'\'include(".hyperparams_{rand_string}.jl"); include(".dataset_{rand_string}.jl"); include("eureqa.jl"); fullRun({niterations:d}, npop={npop:d}, ncyclesperiteration={ncyclesperiteration:d}, fractionReplaced={fractionReplaced:f}f0, verbosity=round(Int32, {verbosity:f}), topn={topn:d})\'',
+        f'\'include(".hyperparams_{rand_string}.jl"); include(".dataset_{rand_string}.jl"); include("sr.jl"); fullRun({niterations:d}, npop={npop:d}, ncyclesperiteration={ncyclesperiteration:d}, fractionReplaced={fractionReplaced:f}f0, verbosity=round(Int32, {verbosity:f}), topn={topn:d})\'',
         ]
     if timeout is not None:
         command = [f'timeout {timeout}'] + command
@@ -232,4 +232,4 @@ if __name__ == "__main__":
             help="Unary operators. Make sure they are defined in operators.jl")
     args = vars(parser.parse_args()) #dict
 
-    eureqa(**args)
+    pysr(**args)