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fix: use keyword bvecs= in gradient_table() calls to suppress dipy deprecation warning #157

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Merged
IvanARashid merged 1 commit into from
May 4, 2026
Merged

fix: use keyword bvecs= in gradient_table() calls to suppress dipy deprecation warning #157

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2 changes: 1 addition & 1 deletion src/standardized/IAR_LU_biexp.py
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Original file line number Diff line number Diff line change
Expand Up @@ -59,7 +59,7 @@ def __init__(self, bvalues=None, thresholds=None, bounds=None, initial_guess=Non
if self.bvalues is not None:
bvec = np.zeros((self.bvalues.size, 3))
bvec[:,2] = 1
gtab = gradient_table(self.bvalues, bvec, b0_threshold=0)
gtab = gradient_table(self.bvalues, bvecs=bvec, b0_threshold=0)

self.IAR_algorithm = IvimModelBiExp(gtab, bounds=self.bounds, initial_guess=self.initial_guess)
else:
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4 changes: 2 additions & 2 deletions src/standardized/IAR_LU_modified_mix.py
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Original file line number Diff line number Diff line change
Expand Up @@ -58,7 +58,7 @@ def __init__(self, bvalues=None, thresholds=None, bounds=None, initial_guess=Non
if self.bvalues is not None:
bvec = np.zeros((self.bvalues.size, 3))
bvec[:,2] = 1
gtab = gradient_table(self.bvalues, bvec, b0_threshold=0)
gtab = gradient_table(self.bvalues, bvecs=bvec, b0_threshold=0)

bounds = [[self.bounds["f"][0], self.bounds["Dp"][0]*1000, self.bounds["D"][0]*1000],
[self.bounds["f"][1], self.bounds["Dp"][1]*1000, self.bounds["D"][1]*1000]]
Expand Down Expand Up @@ -90,7 +90,7 @@ def ivim_fit(self, signals, bvalues, **kwargs):

bvec = np.zeros((bvalues.size, 3))
bvec[:,2] = 1
gtab = gradient_table(bvalues, bvec, b0_threshold=0)
gtab = gradient_table(bvalues, bvecs=bvec, b0_threshold=0)

self.IAR_algorithm = IvimModelVP(gtab, bounds=bounds, rescale_results_to_mm2_s=True)

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4 changes: 2 additions & 2 deletions src/standardized/IAR_LU_modified_topopro.py
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Expand Up @@ -61,7 +61,7 @@ def __init__(self, bvalues=None, thresholds=None, bounds=None, initial_guess=Non
if self.bvalues is not None:
bvec = np.zeros((self.bvalues.size, 3))
bvec[:,2] = 1
gtab = gradient_table(self.bvalues, bvec, b0_threshold=0)
gtab = gradient_table(self.bvalues, bvecs=bvec, b0_threshold=0)

bounds = [[self.bounds["f"][0], self.bounds["Dp"][0]*1000, self.bounds["D"][0]*1000],
[self.bounds["f"][1], self.bounds["Dp"][1]*1000, self.bounds["D"][1]*1000]]
Expand Down Expand Up @@ -92,7 +92,7 @@ def ivim_fit(self, signals, bvalues, **kwargs):

bvec = np.zeros((bvalues.size, 3))
bvec[:,2] = 1
gtab = gradient_table(bvalues, bvec, b0_threshold=0)
gtab = gradient_table(bvalues, bvecs=bvec, b0_threshold=0)

self.IAR_algorithm = IvimModelTopoPro(gtab, bounds=bounds, rescale_results_to_mm2_s=True)

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4 changes: 2 additions & 2 deletions src/standardized/IAR_LU_segmented_2step.py
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Original file line number Diff line number Diff line change
Expand Up @@ -60,7 +60,7 @@ def __init__(self, bvalues=None, thresholds=None, bounds=None, initial_guess=Non
if self.bvalues is not None:
bvec = np.zeros((self.bvalues.size, 3))
bvec[:,2] = 1
gtab = gradient_table(self.bvalues, bvec, b0_threshold=0)
gtab = gradient_table(self.bvalues, bvecs=bvec, b0_threshold=0)
bounds = [[self.bounds["S0"][0], self.bounds["f"][0], self.bounds["Dp"][0], self.bounds["D"][0]], \
[self.bounds["S0"][1], self.bounds["f"][1], self.bounds["Dp"][1], self.bounds["D"][1]]]

Expand Down Expand Up @@ -97,7 +97,7 @@ def ivim_fit(self, signals, bvalues, thresholds=None, **kwargs):

bvec = np.zeros((bvalues.size, 3))
bvec[:,2] = 1
gtab = gradient_table(bvalues, bvec, b0_threshold=0)
gtab = gradient_table(bvalues, bvecs=bvec, b0_threshold=0)

if self.thresholds is None:
self.thresholds = 200
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4 changes: 2 additions & 2 deletions src/standardized/IAR_LU_segmented_3step.py
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Original file line number Diff line number Diff line change
Expand Up @@ -60,7 +60,7 @@ def __init__(self, bvalues=None, thresholds=None, bounds=None, initial_guess=Non
if self.bvalues is not None:
bvec = np.zeros((self.bvalues.size, 3))
bvec[:,2] = 1
gtab = gradient_table(self.bvalues, bvec, b0_threshold=0)
gtab = gradient_table(self.bvalues, bvecs=bvec, b0_threshold=0)

# Adapt the bounds to the format needed for the algorithm
bounds = [[self.bounds["S0"][0], self.bounds["f"][0], self.bounds["Dp"][0], self.bounds["D"][0]], \
Expand Down Expand Up @@ -99,7 +99,7 @@ def ivim_fit(self, signals, bvalues, **kwargs):

bvec = np.zeros((bvalues.size, 3))
bvec[:,2] = 1
gtab = gradient_table(bvalues, bvec, b0_threshold=0)
gtab = gradient_table(bvalues, bvecs=bvec, b0_threshold=0)

self.IAR_algorithm = IvimModelSegmented3Step(gtab, bounds=bounds, initial_guess=initial_guess)

Expand Down
4 changes: 2 additions & 2 deletions src/standardized/IAR_LU_subtracted.py
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Original file line number Diff line number Diff line change
Expand Up @@ -58,7 +58,7 @@ def __init__(self, bvalues=None, thresholds=None, bounds=None, initial_guess=Non
if self.bvalues is not None:
bvec = np.zeros((self.bvalues.size, 3))
bvec[:,2] = 1
gtab = gradient_table(self.bvalues, bvec, b0_threshold=0)
gtab = gradient_table(self.bvalues, bvecs=bvec, b0_threshold=0)

# Adapt the bounds to the format needed for the algorithm
bounds = [[self.bounds["S0"][0], self.bounds["f"][0], self.bounds["Dp"][0], self.bounds["D"][0]], \
Expand Down Expand Up @@ -97,7 +97,7 @@ def ivim_fit(self, signals, bvalues, **kwargs):

bvec = np.zeros((bvalues.size, 3))
bvec[:,2] = 1
gtab = gradient_table(bvalues, bvec, b0_threshold=0)
gtab = gradient_table(bvalues, bvecs=bvec, b0_threshold=0)

self.IAR_algorithm = IvimModelSubtracted(gtab, bounds=bounds, initial_guess=initial_guess)

Expand Down
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