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I was trying to use PySR and I ran into a problem: I ran it once and the model was able to identify the equation correctly. However, after trying to run my code on other data, nothing happens but the code stops at the following error (see below)
I am not sure if I am causing this problem or what the problem could be. I am running the code in Python 3.11.0 and Julia 1.8.5. If there is already an issue that would help, then sorry for posting the same question twice. I hope that you can help me in resolving this problem.
Best wishes,
Bartosz
Version
0.16.3
Operating System
Windows
Package Manager
pip
Interface
Jupyter Notebook
Relevant log output
UserWarning Traceback (most recent call last)
Cell In[45], line 19
1 from pysr import PySRRegressor
3 model = PySRRegressor(
4 niterations=40, # < Increase me for better results
5 binary_operators=["+", "*", "-"],
(...)
17 progress=False
18 )
---> 19 model.fit(x_train_ic,x_dot)
File ~\Anaconda3\envs\tristan\Lib\site-packages\pysr\sr.py:1904, in PySRRegressor.fit(self, X, y, Xresampled, weights, variable_names, X_units, y_units)
1900 seed = random_state.get_state()[1][0] # For julia random
1902 self._setup_equation_file()
-> 1904 mutated_params = self._validate_and_set_init_params()
1906 (
1907 X,
1908 y,
(...)
1915 X, y, Xresampled, weights, variable_names, X_units, y_units
1916 )
1918 if X.shape[0] > 10000 and not self.batching:
File ~\Anaconda3\envs\tristan\Lib\site-packages\pysr\sr.py:1346, in PySRRegressor._validate_and_set_init_params(self)
1344 parameter_value = 1
1345 elif parameter == "progress" and not buffer_available:
-> 1346 warnings.warn(
1347 "Note: it looks like you are running in Jupyter. "
1348 "The progress bar will be turned off."
1349 )
1350 parameter_value = False
1351 packed_modified_params[parameter] = parameter_value
UserWarning: Note: it looks like you are running in Jupyter. The progress bar will be turned off.
Extra Info
This the minimal example, the x_train_ic is just a time series and x_dot the derivatives of it.
from pysr import PySRRegressor
model = PySRRegressor(
niterations=40, # < Increase me for better results
binary_operators=["+", "*", "-"],
#unary_operators=[
# "cos",
# "exp",
# "sin",
# "inv(x) = 1/x",
# ^ Custom operator (julia syntax)
#],
#extra_sympy_mappings={"inv": lambda x: 1 / x},
# ^ Define operator for SymPy as well
loss="loss(prediction, target) = (prediction - target)^2",
# ^ Custom loss function (julia syntax)
progress=False
)
model.fit(x_train_ic,x_dot)
The text was updated successfully, but these errors were encountered:
When you say run it a second time what do you mean? Could you paste the entire example both runs?
Also it doesn’t look like there’s an error here. Is the code maybe still running but just running very slowly? You could see if it is still using the CPU in the task manager for example, or if it actually exited.
What happened?
Hello,
I was trying to use PySR and I ran into a problem: I ran it once and the model was able to identify the equation correctly. However, after trying to run my code on other data, nothing happens but the code stops at the following error (see below)
I am not sure if I am causing this problem or what the problem could be. I am running the code in Python 3.11.0 and Julia 1.8.5. If there is already an issue that would help, then sorry for posting the same question twice. I hope that you can help me in resolving this problem.
Best wishes,
Bartosz
Version
0.16.3
Operating System
Windows
Package Manager
pip
Interface
Jupyter Notebook
Relevant log output
Extra Info
This the minimal example, the x_train_ic is just a time series and x_dot the derivatives of it.
The text was updated successfully, but these errors were encountered: