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Support for bounds, initial guess, and threhold inputs #90

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Support for bounds, initial guess, and threhold inputs #90

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becea1a
Fixed bug
IvanARashid Jan 3, 2025
9dfe0af
Bugfixes for bounds and initial guesses
IvanARashid Jan 8, 2025
c7c4376
Added support for initial guesses, bounds, and thresholds where appli…
IvanARashid Feb 7, 2025
f56880c
Merge branch 'main' into wrapper_dev
IvanARashid Feb 7, 2025
3f36ddc
Delete, not relevant
IvanARashid Feb 7, 2025
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6 changes: 3 additions & 3 deletions src/original/IAR_LundUniversity/ivim_fit_method_biexp.py
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Original file line number Diff line number Diff line change
Expand Up @@ -61,13 +61,13 @@ def ivim_model(self, b, S0, f, D_star, D):

def set_bounds(self, bounds):
# Use this function for fits that uses curve_fit
if bounds == None:
if bounds is None:
self.bounds = np.array([(0, 0, 0.005, 0), (np.inf, 1, 0.1, 0.004)])
else:
self.bounds = np.array([(0, *bounds[0]), (np.inf, *bounds[1])])
self.bounds = np.array([bounds[0], bounds[1]])

def set_initial_guess(self, initial_guess):
if initial_guess == None:
if initial_guess is None:
self.initial_guess = (1, 0.2, 0.03, 0.001)
else:
self.initial_guess = initial_guess
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6 changes: 3 additions & 3 deletions src/original/IAR_LundUniversity/ivim_fit_method_linear.py
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Original file line number Diff line number Diff line change
Expand Up @@ -83,13 +83,13 @@ def sivim_model(self, b, S0, f, D):

def set_bounds(self, bounds):
# Use this function for fits that uses curve_fit
if bounds == None:
if bounds is None:
self.bounds = np.array([(0, 0, 0), (np.inf, 1, 0.004)])
else:
self.bounds = np.array([(0, *bounds[0]), (np.inf, *bounds[1])])
self.bounds = np.array([bounds[0], bounds[1]])

def set_initial_guess(self, initial_guess):
if initial_guess == None:
if initial_guess is None:
self.initial_guess = (1, 0.2, 0.001)
else:
self.initial_guess = initial_guess
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2 changes: 1 addition & 1 deletion src/original/IAR_LundUniversity/ivim_fit_method_modified_mix.py
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Original file line number Diff line number Diff line change
Expand Up @@ -78,7 +78,7 @@ def __init__(self, gtab, bounds=None, maxiter=10, xtol=1e-8, rescale_units=False
if gtab.bvals[-1] >= 10:
self.bvals = gtab.bvals/1000

if bounds == None:
if bounds is None:
# Bounds expressed as (lower bound, upper bound) for [f, D*, D].
self.bounds = np.array([(0, 1), (5, 100), (0, 4)])
elif (bounds[0][1] <= 1) or rescale_units: # Realistically, if mm2/s units are used, D* bound is <= 1
Expand Down
2 changes: 1 addition & 1 deletion src/original/IAR_LundUniversity/ivim_fit_method_modified_topopro.py
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Original file line number Diff line number Diff line change
Expand Up @@ -76,7 +76,7 @@ def __init__(self, gtab, bounds=[[0, 0.005, 1e-5], [1, 0.1, 0.004]], \
# and are thus not changed.
if gtab.bvals[-1] >= 10:
self.bvals = gtab.bvals/1000
if bounds == None:
if bounds is None:
# Bounds expressed as (lower bound, upper bound) for [f, D*, D].
self.bounds = np.array([(0, 1), (5, 100), (0, 4)])
elif (bounds[0][1] <= 1) or rescale_units: # Realistically, if mm2/s units are used, D* bound is <= 1
Expand Down
6 changes: 3 additions & 3 deletions src/original/IAR_LundUniversity/ivim_fit_method_segmented_2step.py
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Original file line number Diff line number Diff line change
Expand Up @@ -86,13 +86,13 @@ def ivim_signal(self, b, S0, f, D_star, D):

def set_bounds(self, bounds):
# Use this function for fits that uses curve_fit
if bounds == None:
if bounds is None:
self.bounds = np.array([(0, 0, 0.005, 0), (np.inf, 1, 0.1, 0.004)])
else:
self.bounds = np.array([(0, *bounds[0]), (np.inf, *bounds[1])])
self.bounds = np.array([bounds[0], bounds[1]])

def set_initial_guess(self, initial_guess):
if initial_guess == None:
if initial_guess is None:
self.initial_guess = (1, 0.2, 0.03, 0.001)
else:
self.initial_guess = initial_guess
Expand Down
6 changes: 3 additions & 3 deletions src/original/IAR_LundUniversity/ivim_fit_method_segmented_3step.py
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Original file line number Diff line number Diff line change
Expand Up @@ -105,13 +105,13 @@ def ivim_signal(self, b, S0, f, D_star, D):

def set_bounds(self, bounds):
# Use this function for fits that uses curve_fit
if bounds == None:
if bounds is None:
self.bounds = np.array([(0, 0, 0.005, 0), (np.inf, 1, 0.1, 0.004)])
else:
self.bounds = np.array([(0, *bounds[0]), (np.inf, *bounds[1])])
self.bounds = np.array([bounds[0], bounds[1]])

def set_initial_guess(self, initial_guess):
if initial_guess == None:
if initial_guess is None:
self.initial_guess = (1, 0.2, 0.03, 0.001)
else:
self.initial_guess = initial_guess
Expand Down
6 changes: 3 additions & 3 deletions src/original/IAR_LundUniversity/ivim_fit_method_sivim.py
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Original file line number Diff line number Diff line change
Expand Up @@ -77,13 +77,13 @@ def sivim_model(self, b, S0, f, D):

def set_bounds(self, bounds):
# Use this function for fits that uses curve_fit
if bounds == None:
if bounds is None:
self.bounds = np.array([(0, 0, 0), (np.inf, 1, 0.004)])
else:
self.bounds = np.array([(0, *bounds[0]), (np.inf, *bounds[1])])
self.bounds = np.array([bounds[0], bounds[1]])

def set_initial_guess(self, initial_guess):
if initial_guess == None:
if initial_guess is None:
self.initial_guess = (1, 0.2, 0.001)
else:
self.initial_guess = initial_guess
Expand Down
6 changes: 3 additions & 3 deletions src/original/IAR_LundUniversity/ivim_fit_method_subtracted.py
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Original file line number Diff line number Diff line change
Expand Up @@ -93,13 +93,13 @@ def perfusion_signal(self, b, S0, D_star):

def set_bounds(self, bounds):
# Use this function for fits that uses curve_fit
if bounds == None:
if bounds is None:
self.bounds = np.array([(0, 0, 0.005, 0), (np.inf, 1, 0.1, 0.004)])
else:
self.bounds = np.array([(0, *bounds[0]), (np.inf, *bounds[1])])
self.bounds = np.array([bounds[0], bounds[1]])

def set_initial_guess(self, initial_guess):
if initial_guess == None:
if initial_guess is None:
self.initial_guess = (1, 0.2, 0.03, 0.001)
else:
self.initial_guess = initial_guess
Expand Down
130 changes: 0 additions & 130 deletions src/original/IAR_LundUniversity/simple_test_of_fits.py
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This file was deleted.

9 changes: 7 additions & 2 deletions src/standardized/ETP_SRI_LinearFitting.py
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Original file line number Diff line number Diff line change
Expand Up @@ -27,6 +27,11 @@ class ETP_SRI_LinearFitting(OsipiBase):
required_initial_guess_optional = False
accepted_dimensions = 1
# Not sure how to define this for the number of accepted dimensions. Perhaps like the thresholds, at least and at most?

# Supported inputs in the standardized class
supported_bounds = False
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I don't understand how these are used.
Are these now properties of the class that I can ask using self.supported_bounds? That would help with testing :)

supported_initial_guess = False
supported_thresholds = True

def __init__(self, bvalues=None, thresholds=None, bounds=None, initial_guess=None, weighting=None, stats=False):
"""
Expand All @@ -36,7 +41,7 @@ def __init__(self, bvalues=None, thresholds=None, bounds=None, initial_guess=Non
Our OsipiBase object could contain functions that compare the inputs with
the requirements.
"""
super(ETP_SRI_LinearFitting, self).__init__(bvalues, thresholds, bounds, initial_guess)
super(ETP_SRI_LinearFitting, self).__init__(bvalues=bvalues, thresholds=thresholds, bounds=bounds, initial_guess=initial_guess)

# Could be a good idea to have all the submission-specfic variable be
# defined with initials?
Expand Down Expand Up @@ -67,7 +72,7 @@ def ivim_fit(self, signals, bvalues=None, linear_fit_option=False, **kwargs):

results = {}
if linear_fit_option:
f, Dstar = ETP_object.linear_fit(bvalues, signals)
f, Dstar = ETP_object.linear_fit(bvalues, signals, self.ETP_weighting, self.ETP_stats)

results["f"] = f
results["D*"] = Dstar
Expand Down
11 changes: 8 additions & 3 deletions src/standardized/IAR_LU_biexp.py
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Expand Up @@ -27,6 +27,11 @@ class IAR_LU_biexp(OsipiBase):
required_initial_guess = False
required_initial_guess_optional = True
accepted_dimensions = 1 # Not sure how to define this for the number of accepted dimensions. Perhaps like the thresholds, at least and at most?

# Supported inputs in the standardized class
supported_bounds = True
supported_initial_guess = True
supported_thresholds = False

def __init__(self, bvalues=None, thresholds=None, bounds=None, initial_guess=None, weighting=None, stats=False):
"""
Expand All @@ -46,7 +51,7 @@ def __init__(self, bvalues=None, thresholds=None, bounds=None, initial_guess=Non
bvec[:,2] = 1
gtab = gradient_table(self.bvalues, bvec, b0_threshold=0)

self.IAR_algorithm = IvimModelBiExp(gtab)
self.IAR_algorithm = IvimModelBiExp(gtab, bounds=self.bounds, initial_guess=self.initial_guess)
else:
self.IAR_algorithm = None

Expand All @@ -72,7 +77,7 @@ def ivim_fit(self, signals, bvalues, **kwargs):
bvec[:,2] = 1
gtab = gradient_table(bvalues, bvec, b0_threshold=0)

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

fit_results = self.IAR_algorithm.fit(signals)

Expand Down Expand Up @@ -104,7 +109,7 @@ def ivim_fit_full_volume(self, signals, bvalues, **kwargs):
bvec[:,2] = 1
gtab = gradient_table(bvalues, bvec, b0_threshold=0)

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

fit_results = self.IAR_algorithm.fit(signals)

Expand Down
9 changes: 7 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 @@ -28,6 +28,11 @@ class IAR_LU_modified_mix(OsipiBase):
required_initial_guess_optional = True
accepted_dimensions = 1 # Not sure how to define this for the number of accepted dimensions. Perhaps like the thresholds, at least and at most?

# Supported inputs in the standardized class
supported_bounds = True
supported_initial_guess = False
supported_thresholds = False

def __init__(self, bvalues=None, thresholds=None, bounds=None, initial_guess=None, weighting=None, stats=False):
"""
Everything this algorithm requires should be implemented here.
Expand All @@ -46,7 +51,7 @@ def __init__(self, bvalues=None, thresholds=None, bounds=None, initial_guess=Non
bvec[:,2] = 1
gtab = gradient_table(self.bvalues, bvec, b0_threshold=0)

self.IAR_algorithm = IvimModelVP(gtab)
self.IAR_algorithm = IvimModelVP(gtab, bounds=self.bounds, rescale_results_to_mm2_s=True)
else:
self.IAR_algorithm = None

Expand All @@ -72,7 +77,7 @@ def ivim_fit(self, signals, bvalues, **kwargs):
bvec[:,2] = 1
gtab = gradient_table(bvalues, bvec, b0_threshold=0)

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

fit_results = self.IAR_algorithm.fit(signals)

Expand Down
9 changes: 7 additions & 2 deletions src/standardized/IAR_LU_modified_topopro.py
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Original file line number Diff line number Diff line change
Expand Up @@ -28,6 +28,11 @@ class IAR_LU_modified_topopro(OsipiBase):
required_initial_guess_optional = True
accepted_dimensions = 1 # Not sure how to define this for the number of accepted dimensions. Perhaps like the thresholds, at least and at most?

# Supported inputs in the standardized class
supported_bounds = True
supported_initial_guess = False
supported_thresholds = False

def __init__(self, bvalues=None, thresholds=None, bounds=None, initial_guess=None, weighting=None, stats=False):
"""
Everything this algorithm requires should be implemented here.
Expand All @@ -46,7 +51,7 @@ def __init__(self, bvalues=None, thresholds=None, bounds=None, initial_guess=Non
bvec[:,2] = 1
gtab = gradient_table(self.bvalues, bvec, b0_threshold=0)

self.IAR_algorithm = IvimModelTopoPro(gtab)
self.IAR_algorithm = IvimModelTopoPro(gtab, bounds=self.bounds, rescale_results_to_mm2_s=True)
else:
self.IAR_algorithm = None

Expand All @@ -72,7 +77,7 @@ def ivim_fit(self, signals, bvalues, **kwargs):
bvec[:,2] = 1
gtab = gradient_table(bvalues, bvec, b0_threshold=0)

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

fit_results = self.IAR_algorithm.fit(signals)

Expand Down
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