LinearRegression unknown keyword normalize

[huangtu577]

I just installed the PySINDy library, and it throws an TypeError: LinearRegression.__init__() got an unexpected keyword argument 'normalize' out of the box.
The version that conda installed for scikit-learn without any specification is 1.4.2.
According to the Changelog from scikit-learn , the normalize keyword has been deprecated since version 1.0 and removed since 1.2. However there is a proposed fix in the above linked changelog.

Reproducing code example:

import pysindy
differentiation_method = ps.FiniteDifference(order=2)
feature_library = ps.PolynomialLibrary(degree=3)
optimizer = ps.STLSQ(threshold=0.2)

Error message:

---

TypeError                                 Traceback (most recent call last)
Cell In[15], [line 3](vscode-notebook-cell:?execution_count=15&line=3)
      [1](vscode-notebook-cell:?execution_count=15&line=1) differentiation_method = ps.FiniteDifference(order=2)
      [2](vscode-notebook-cell:?execution_count=15&line=2) feature_library = ps.PolynomialLibrary(degree=3)
----> [3](vscode-notebook-cell:?execution_count=15&line=3) optimizer = ps.STLSQ(threshold=0.2)

File ~/anaconda3/envs/rebound/lib/python3.10/site-packages/pysindy/optimizers/stlsq.py:105, in STLSQ.__init__(self, threshold, alpha, max_iter, ridge_kw, normalize, fit_intercept, copy_X, initial_guess)
     [94](https://file+.vscode-resource.vscode-cdn.net/home/fabian/Documents/Studium/rebound/~/anaconda3/envs/rebound/lib/python3.10/site-packages/pysindy/optimizers/stlsq.py:94) def __init__(
     [95](https://file+.vscode-resource.vscode-cdn.net/home/fabian/Documents/Studium/rebound/~/anaconda3/envs/rebound/lib/python3.10/site-packages/pysindy/optimizers/stlsq.py:95)     self,
     [96](https://file+.vscode-resource.vscode-cdn.net/home/fabian/Documents/Studium/rebound/~/anaconda3/envs/rebound/lib/python3.10/site-packages/pysindy/optimizers/stlsq.py:96)     threshold=0.1,
   (...)
    [103](https://file+.vscode-resource.vscode-cdn.net/home/fabian/Documents/Studium/rebound/~/anaconda3/envs/rebound/lib/python3.10/site-packages/pysindy/optimizers/stlsq.py:103)     initial_guess=None,
    [104](https://file+.vscode-resource.vscode-cdn.net/home/fabian/Documents/Studium/rebound/~/anaconda3/envs/rebound/lib/python3.10/site-packages/pysindy/optimizers/stlsq.py:104) ):
--> [105](https://file+.vscode-resource.vscode-cdn.net/home/fabian/Documents/Studium/rebound/~/anaconda3/envs/rebound/lib/python3.10/site-packages/pysindy/optimizers/stlsq.py:105)     super(STLSQ, self).__init__(
    [106](https://file+.vscode-resource.vscode-cdn.net/home/fabian/Documents/Studium/rebound/~/anaconda3/envs/rebound/lib/python3.10/site-packages/pysindy/optimizers/stlsq.py:106)         max_iter=max_iter,
    [107](https://file+.vscode-resource.vscode-cdn.net/home/fabian/Documents/Studium/rebound/~/anaconda3/envs/rebound/lib/python3.10/site-packages/pysindy/optimizers/stlsq.py:107)         normalize=normalize,
    [108](https://file+.vscode-resource.vscode-cdn.net/home/fabian/Documents/Studium/rebound/~/anaconda3/envs/rebound/lib/python3.10/site-packages/pysindy/optimizers/stlsq.py:108)         fit_intercept=fit_intercept,
    [109](https://file+.vscode-resource.vscode-cdn.net/home/fabian/Documents/Studium/rebound/~/anaconda3/envs/rebound/lib/python3.10/site-packages/pysindy/optimizers/stlsq.py:109)         copy_X=copy_X,
    [110](https://file+.vscode-resource.vscode-cdn.net/home/fabian/Documents/Studium/rebound/~/anaconda3/envs/rebound/lib/python3.10/site-packages/pysindy/optimizers/stlsq.py:110)     )
    [112](https://file+.vscode-resource.vscode-cdn.net/home/fabian/Documents/Studium/rebound/~/anaconda3/envs/rebound/lib/python3.10/site-packages/pysindy/optimizers/stlsq.py:112)     if threshold < 0:
    [113](https://file+.vscode-resource.vscode-cdn.net/home/fabian/Documents/Studium/rebound/~/anaconda3/envs/rebound/lib/python3.10/site-packages/pysindy/optimizers/stlsq.py:113)         raise ValueError("threshold cannot be negative")

File ~/anaconda3/envs/rebound/lib/python3.10/site-packages/pysindy/optimizers/base.py:81, in BaseOptimizer.__init__(self, max_iter, normalize, fit_intercept, initial_guess, copy_X)
     [73](https://file+.vscode-resource.vscode-cdn.net/home/fabian/Documents/Studium/rebound/~/anaconda3/envs/rebound/lib/python3.10/site-packages/pysindy/optimizers/base.py:73) def __init__(
     [74](https://file+.vscode-resource.vscode-cdn.net/home/fabian/Documents/Studium/rebound/~/anaconda3/envs/rebound/lib/python3.10/site-packages/pysindy/optimizers/base.py:74)     self,
     [75](https://file+.vscode-resource.vscode-cdn.net/home/fabian/Documents/Studium/rebound/~/anaconda3/envs/rebound/lib/python3.10/site-packages/pysindy/optimizers/base.py:75)     max_iter=20,
   (...)
     [79](https://file+.vscode-resource.vscode-cdn.net/home/fabian/Documents/Studium/rebound/~/anaconda3/envs/rebound/lib/python3.10/site-packages/pysindy/optimizers/base.py:79)     copy_X=True,
     [80](https://file+.vscode-resource.vscode-cdn.net/home/fabian/Documents/Studium/rebound/~/anaconda3/envs/rebound/lib/python3.10/site-packages/pysindy/optimizers/base.py:80) ):
---> [81](https://file+.vscode-resource.vscode-cdn.net/home/fabian/Documents/Studium/rebound/~/anaconda3/envs/rebound/lib/python3.10/site-packages/pysindy/optimizers/base.py:81)     super(BaseOptimizer, self).__init__(
     [82](https://file+.vscode-resource.vscode-cdn.net/home/fabian/Documents/Studium/rebound/~/anaconda3/envs/rebound/lib/python3.10/site-packages/pysindy/optimizers/base.py:82)         fit_intercept=fit_intercept, normalize=normalize, copy_X=copy_X
     [83](https://file+.vscode-resource.vscode-cdn.net/home/fabian/Documents/Studium/rebound/~/anaconda3/envs/rebound/lib/python3.10/site-packages/pysindy/optimizers/base.py:83)     )
     [85](https://file+.vscode-resource.vscode-cdn.net/home/fabian/Documents/Studium/rebound/~/anaconda3/envs/rebound/lib/python3.10/site-packages/pysindy/optimizers/base.py:85)     if max_iter <= 0:
     [86](https://file+.vscode-resource.vscode-cdn.net/home/fabian/Documents/Studium/rebound/~/anaconda3/envs/rebound/lib/python3.10/site-packages/pysindy/optimizers/base.py:86)         raise ValueError("max_iter must be positive")

TypeError: LinearRegression.__init__() got an unexpected keyword argument 'normalize'

PySINDy/Python version information:

1.3.0 3.10.14 (main, May 6 2024, 19:42:50) [GCC 11.2.0]

[Jacob-Stevens-Haas]

Thank you!! This is a great find. I'll get on it soon. Since SINDy.model is a Pipeline, this should be a reasonably easy fix

[ggmirandac]

Hi,

I just wanted to mention that the version that you have on Conda-forge is not up to date, and results on the same issues.

Just that.

[ddeboerfluid]

Hi,

Is there any (quick) fix to this available?

[Jacob-Stevens-Haas]

@ddeboerfluid The quick fix is to install an updated version, either from pypi or here. Actually, it looks like this bug was fixed at least two years ago, which is where the blame of the most recent normalization code points (b9fc48c).

We'll be releasing a new version shortly, but you can always get the current version with

pip install git+https://github.com/dynamicslab/pysindy

@ggmirandac, it was only put on conda-forge a few years ago manually by a previous maintainer. I don't personally use conda, but I would be happy for a PR into .github/workflows/release.yml to automate that release.

[Dipa-chiniyaa]

from sklearn.linear_model import LinearRegression

lr = LinearRegression()

can also works