Change PySR defaults; fixes #99

README.md

@@ -94,7 +94,6 @@ PySR's main interface is in the style of scikit-learn:
 from pysr import PySRRegressor
 model = PySRRegressor(
     niterations=5,
-    populations=8,
     binary_operators=["+", "*"],
     unary_operators=[
         "cos",

docs/examples.md

@@ -7,13 +7,6 @@ import numpy as np
 from pysr import *
 ```
 
-We'll also set up some default options that will
-make these simple searches go faster (but are less optimal
-for more complex searches).
-
-```python
-kwargs = dict(populations=5, niterations=5, annealing=True)
-```
 
 ## 1. Simple search
 
@@ -23,7 +16,7 @@ find the expression `2 cos(x3) + x0^2 - 2`.
 ```python
 X = 2 * np.random.randn(100, 5)
 y = 2 * np.cos(X[:, 3]) + X[:, 0] ** 2 - 2
-model = PySRRegressor(binary_operators=["+", "-", "*", "/"], **kwargs)
+model = PySRRegressor(binary_operators=["+", "-", "*", "/"])
 model.fit(X, y)
 print(model)
 ```
@@ -38,7 +31,6 @@ y = 1 / X[:, 0]
 model = PySRRegressor(
     binary_operators=["plus", "mult"],
     unary_operators=["inv(x) = 1/x"],
-    **kwargs
 )
 model.fit(X, y)
 print(model)
@@ -54,7 +46,6 @@ y = 1 / X[:, [0, 1, 2]]
 model = PySRRegressor(
     binary_operators=["plus", "mult"],
     unary_operators=["inv(x) = 1/x"],
-    **kwargs
 )
 model.fit(X, y)
 ```
@@ -124,7 +115,6 @@ model = PySRRegressor(
     binary_operators=["+", "-", "*", "/"],
     unary_operators=["exp"],
     select_k_features=5,
-    **kwargs
 )
 ```
 Now let's fit this:
@@ -174,7 +164,6 @@ model = PySRRegressor(
     binary_operators=["+", "-", "*", "/"],
     unary_operators=["exp"],
     denoise=True,
-    **kwargs
 )
 model.fit(X, y)
 print(model)

docs/options.md

@@ -25,7 +25,7 @@ and complexity.
 
 It will also dump to a csv
 at the end of every iteration,
-which is `hall_of_fame_{date_time}.csv` by default.
+which is `.hall_of_fame_{date_time}.csv` by default.
 It also prints the equations to stdout.
 
 ## Model selection
@@ -91,7 +91,7 @@ you want `pysr` to use.
 
 ## Populations
 
-By default, `populations=20`, but you can set a different
+By default, `populations=100`, but you can set a different
 number of populations with this option.
 More populations may increase
 the diversity of equations discovered, though will take longer to train.

example.py

@@ -7,7 +7,6 @@ from pysr import PySRRegressor
 
 model = PySRRegressor(
     niterations=5,
-    populations=8,
     binary_operators=["+", "*"],
     unary_operators=[
         "cos",

pysr/sr.py

@@ -365,14 +365,14 @@ class PySRRegressor(BaseEstimator, RegressorMixin):
         unary_operators=None,
         procs=cpu_count(),
         loss="L2DistLoss()",
-        populations=20,
-        niterations=100,
-        ncyclesperiteration=300,
+        populations=100,
+        niterations=4,
+        ncyclesperiteration=100,
         alpha=0.1,
         annealing=False,
-        fractionReplaced=0.10,
-        fractionReplacedHof=0.10,
-        npop=1000,
+        fractionReplaced=0.01,
+        fractionReplacedHof=0.005,
+        npop=100,
         parsimony=1e-4,
         migration=True,
         hofMigration=True,