MilesCranmer commited on
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7ab053d
1 Parent(s): 32c64f7

Update docs to mention state saving

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  1. README.md +3 -1
  2. docs/start.md +3 -1
README.md CHANGED
@@ -74,7 +74,7 @@ Most common issues at this stage are solved
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  by [tweaking the Julia package server](https://github.com/MilesCranmer/PySR/issues/27).
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  to use up-to-date packages.
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- # Quickstart
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  Let's create a PySR example. First, let's import
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  numpy to generate some test data:
@@ -144,6 +144,8 @@ This arrow in the `pick` column indicates which equation is currently selected b
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  SymPy format (`sympy_format`), and even JAX and PyTorch format
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  (both of which are differentiable).
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  There are several other useful features such as denoising (e.g., `denoising=True`),
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  feature selection (e.g., `select_k_features=3`).
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  For a summary of features and options, see [this docs page](https://pysr.readthedocs.io/en/latest/docs/options/).
 
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  by [tweaking the Julia package server](https://github.com/MilesCranmer/PySR/issues/27).
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  to use up-to-date packages.
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+ # Introduction
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  Let's create a PySR example. First, let's import
80
  numpy to generate some test data:
 
144
  SymPy format (`sympy_format`), and even JAX and PyTorch format
145
  (both of which are differentiable).
146
 
147
+ Note that `PySRRegressor` stores the state of the last search, and will restart from where you left off the next time you call `.fit()`. This will cause problems if significant changes are made to the search parameters (like changing the operators). You can run `model.reset()` to reset the state.
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+
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  There are several other useful features such as denoising (e.g., `denoising=True`),
150
  feature selection (e.g., `select_k_features=3`).
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  For a summary of features and options, see [this docs page](https://pysr.readthedocs.io/en/latest/docs/options/).
docs/start.md CHANGED
@@ -19,7 +19,7 @@ Most common issues at this stage are solved
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  by [tweaking the Julia package server](https://github.com/MilesCranmer/PySR/issues/27).
20
  to use up-to-date packages.
21
 
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- # Quickstart
23
 
24
  Let's create a PySR example. First, let's import
25
  numpy to generate some test data:
@@ -89,6 +89,8 @@ This arrow in the `pick` column indicates which equation is currently selected b
89
  SymPy format (`sympy_format`), and even JAX and PyTorch format
90
  (both of which are differentiable).
91
 
 
 
92
  There are several other useful features such as denoising (e.g., `denoising=True`),
93
  feature selection (e.g., `select_k_features=3`).
94
  For a summary of features and options, see [this docs page](https://pysr.readthedocs.io/en/latest/docs/options/).
 
19
  by [tweaking the Julia package server](https://github.com/MilesCranmer/PySR/issues/27).
20
  to use up-to-date packages.
21
 
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+ # Introduction
23
 
24
  Let's create a PySR example. First, let's import
25
  numpy to generate some test data:
 
89
  SymPy format (`sympy_format`), and even JAX and PyTorch format
90
  (both of which are differentiable).
91
 
92
+ Note that `PySRRegressor` stores the state of the last search, and will restart from where you left off the next time you call `.fit()`. This will cause problems if significant changes are made to the search parameters (like changing the operators). You can run `model.reset()` to reset the state.
93
+
94
  There are several other useful features such as denoising (e.g., `denoising=True`),
95
  feature selection (e.g., `select_k_features=3`).
96
  For a summary of features and options, see [this docs page](https://pysr.readthedocs.io/en/latest/docs/options/).