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Updating to Scipy 1.14 #2406

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a47ec44
Updating to scipy 1.12
joshua-cogliati-inl Jan 24, 2024
8eb0b5e
Scikitlearn 1.0 is incompatible with scipy 1.12, so updating to 1.1
joshua-cogliati-inl Jan 25, 2024
2ade198
Sometimes only a 1d array is returned.
joshua-cogliati-inl Jan 25, 2024
d2c5317
Merge remote-tracking branch 'origin/devel' into scipy_1_12
joshua-cogliati-inl Dec 5, 2024
eb93d44
Removing testing kulsinski metric.
joshua-cogliati-inl Dec 5, 2024
2d9c229
simps is deprecated so switching to simpson
joshua-cogliati-inl Dec 5, 2024
2640624
Handle change from https://github.com/scikit-learn/scikit-learn/pull/…
joshua-cogliati-inl Dec 6, 2024
9a695a2
Improving test to classify better.
joshua-cogliati-inl Dec 6, 2024
0a8bf49
Updating to Scipy 1.14
joshua-cogliati-inl Dec 6, 2024
177cbac
Merge remote-tracking branch 'origin/devel' into scipy_1_14
joshua-cogliati-inl Jul 21, 2025
0197e5c
Scikit-learn needs to be updated to 1.3 to work with scipy 1.14
joshua-cogliati-inl Jul 21, 2025
aaf9842
Normalize is removed from LinearRegression
joshua-cogliati-inl Jul 21, 2025
a567a3b
Checking if normalize around.
joshua-cogliati-inl Jul 21, 2025
c42eded
LinearRegression no-longer has a normalized parameter.
joshua-cogliati-inl Jul 21, 2025
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4 changes: 2 additions & 2 deletions dependencies.xml
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Expand Up @@ -39,8 +39,8 @@ Note all install methods after "main" take
<main>
<h5py/>
<numpy>1.26</numpy>
<scipy>1.12</scipy>
<scikit-learn>1.1</scikit-learn>
<scipy>1.14</scipy>
<scikit-learn>1.3</scikit-learn>
<pandas/>
<!-- Note most versions of xarray work, but some (such as 0.20) don't -->
<xarray/>
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4 changes: 2 additions & 2 deletions ravenframework/SupervisedLearning/ARMA.py
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Expand Up @@ -1192,7 +1192,7 @@ def _trainFourier(self, pivotValues, periods, values, masks=None,target=None):
# 1: cos(2pi*t/period[0]),
# 2: sin(2pi*t/period[1]),
# 3: cos(2pi*t/period[1]), ...
fourierEngine = sklearn.linear_model.LinearRegression(normalize=False)
fourierEngine = sklearn.linear_model.LinearRegression()
fourierSignals = fourierSignalsFull[masks, :]
values = values[masks]
# check collinearity
Expand All @@ -1209,7 +1209,7 @@ def _trainFourier(self, pivotValues, periods, values, masks=None,target=None):
coeffs = np.zeros(F2)
for fn in range(F2):
fSignal = fourierSignals[:,fn]
eng = sklearn.linear_model.LinearRegression(normalize=False)
eng = sklearn.linear_model.LinearRegression()
eng.fit(fSignal.reshape(H,1), signalToFit)
thisIntercept = eng.intercept_
thisCoeff = eng.coef_[0]
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12 changes: 7 additions & 5 deletions ravenframework/SupervisedLearning/ScikitLearn/LinearModel/LinearRegression.py
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Expand Up @@ -33,7 +33,7 @@ class LinearRegression(ScikitLearnBase):
"""
Ordinary least squares Linear Regression.
"""
info = {'problemtype':'regression', 'normalize':False}
info = {'problemtype':'regression'}

def __init__(self):
"""
Expand Down Expand Up @@ -70,9 +70,7 @@ class cls.
descr=r"""Whether the intercept should be estimated or not. If False,
the data is assumed to be already centered.""", default=True))
specs.addSub(InputData.parameterInputFactory("normalize", contentType=InputTypes.BoolType,
descr=r"""This parameter is ignored when fit_intercept is set to False. If True,
the regressors X will be normalized before regression by subtracting the mean and
dividing by the l2-norm.""", default=False))
descr=r"""This parameter is deprecated and ignored."""))
# New in sklearn version 0.24
# specs.addSub(InputData.parameterInputFactory("positive", contentType=InputTypes.BoolType,
# descr=r"""When set to True, forces the coefficients to be positive.""", default=False))
Expand All @@ -85,7 +83,11 @@ def _handleInput(self, paramInput):
@ Out, None
"""
super()._handleInput(paramInput)
settings, notFound = paramInput.findNodesAndExtractValues(['fit_intercept','normalize'])
settings, notFound = paramInput.findNodesAndExtractValues(['fit_intercept'])
# notFound must be empty
assert(not notFound)
oldSettings, oldNotFound = paramInput.findNodesAndExtractValues(['normalize'])
if not oldNotFound:
self.raiseAWarning("Deprecated setting found: "+str(oldSettings))
self.raiseAnError(IOError,"Deprecated setting found: "+str(oldSettings))
self.initializeModel(settings)
2 changes: 1 addition & 1 deletion ravenframework/SupervisedLearning/ScikitLearn/ScikitLearnBase.py
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Expand Up @@ -261,7 +261,7 @@ def _localNormalizeData(self,values,names,feat):
@ In, feat, string, feature to (not) normalize
@ Out, None
"""
if not self.info['normalize']:
if 'normalize' in self.info and not self.info['normalize']:
self.muAndSigmaFeatures[feat] = (0.0,1.0)
else:
super()._localNormalizeData(values,names,feat)
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1 change: 0 additions & 1 deletion tests/framework/PostProcessors/CrossValidations/test_LabelKFold.xml
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Expand Up @@ -27,7 +27,6 @@
<Features>x1,x2</Features>
<Target>ans</Target>
<fit_intercept>True</fit_intercept>
<normalize>True</normalize>
</ROM>
<PostProcessor name="pp1" subType="CrossValidation">
<SciKitLearn>
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1 change: 0 additions & 1 deletion tests/framework/PostProcessors/CrossValidations/test_cross_validation.xml
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Expand Up @@ -27,7 +27,6 @@
<Features>x1,x2</Features>
<Target>ans</Target>
<fit_intercept>True</fit_intercept>
<normalize>True</normalize>
</ROM>
<PostProcessor name="pp1" subType="CrossValidation">
<SciKitLearn>
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1 change: 0 additions & 1 deletion tests/framework/PostProcessors/CrossValidations/test_labelShuffleSplit.xml
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Expand Up @@ -27,7 +27,6 @@
<Features>x1,x2</Features>
<Target>ans</Target>
<fit_intercept>True</fit_intercept>
<normalize>True</normalize>
</ROM>
<PostProcessor name="pp1" subType="CrossValidation">
<SciKitLearn>
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1 change: 0 additions & 1 deletion tests/framework/PostProcessors/CrossValidations/test_leaveOneLabelOut.xml
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Expand Up @@ -27,7 +27,6 @@
<Features>x1,x2</Features>
<Target>ans</Target>
<fit_intercept>True</fit_intercept>
<normalize>True</normalize>
</ROM>
<PostProcessor name="pp1" subType="CrossValidation">
<SciKitLearn>
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1 change: 0 additions & 1 deletion tests/framework/PostProcessors/CrossValidations/test_leaveOneOut.xml
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Expand Up @@ -27,7 +27,6 @@
<Features>x1,x2</Features>
<Target>ans</Target>
<fit_intercept>True</fit_intercept>
<normalize>True</normalize>
</ROM>
<PostProcessor name="pp1" subType="CrossValidation">
<SciKitLearn>
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1 change: 0 additions & 1 deletion tests/framework/PostProcessors/CrossValidations/test_leavePLabelOut.xml
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Expand Up @@ -27,7 +27,6 @@
<Features>x1,x2</Features>
<Target>ans</Target>
<fit_intercept>True</fit_intercept>
<normalize>True</normalize>
</ROM>
<PostProcessor name="pp1" subType="CrossValidation">
<SciKitLearn>
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1 change: 0 additions & 1 deletion tests/framework/PostProcessors/CrossValidations/test_leavePOut.xml
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Expand Up @@ -27,7 +27,6 @@
<Features>x1,x2</Features>
<Target>ans</Target>
<fit_intercept>True</fit_intercept>
<normalize>True</normalize>
</ROM>
<PostProcessor name="pp1" subType="CrossValidation">
<SciKitLearn>
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1 change: 0 additions & 1 deletion tests/framework/PostProcessors/CrossValidations/test_shuffleSplit.xml
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Expand Up @@ -27,7 +27,6 @@
<Features>x1,x2</Features>
<Target>ans</Target>
<fit_intercept>True</fit_intercept>
<normalize>True</normalize>
</ROM>
<PostProcessor name="pp1" subType="CrossValidation">
<SciKitLearn>
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1 change: 0 additions & 1 deletion tests/framework/PostProcessors/CrossValidations/test_stratifiedKFold.xml
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Expand Up @@ -27,7 +27,6 @@
<Features>x1,x2</Features>
<Target>ans</Target>
<fit_intercept>True</fit_intercept>
<normalize>True</normalize>
</ROM>
<PostProcessor name="pp1" subType="CrossValidation">
<SciKitLearn>
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1 change: 0 additions & 1 deletion tests/framework/PostProcessors/CrossValidations/test_stratifiedShuffleSplit.xml
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Expand Up @@ -27,7 +27,6 @@
<Features>x1,x2</Features>
<Target>ans</Target>
<fit_intercept>True</fit_intercept>
<normalize>True</normalize>
</ROM>
<PostProcessor name="pp1" subType="CrossValidation">
<SciKitLearn>
Expand Down