Attribute harmonization. supported_dimensions and supported_priors

Author: IvanARashid

src/standardized/ETP_SRI_LinearFitting.py

@@ -25,13 +25,14 @@ class ETP_SRI_LinearFitting(OsipiBase):
     required_bounds_optional = True # Bounds may not be required but are optional
     required_initial_guess = False
     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
     supported_initial_guess = False
     supported_thresholds = True
+    supported_dimensions = 1
+    supported_priors = False
 
     def __init__(self, bvalues=None, thresholds=None, bounds=None, initial_guess=None, weighting=None, stats=False):
         """

src/standardized/IAR_LU_biexp.py

@@ -26,12 +26,13 @@ class IAR_LU_biexp(OsipiBase):
     required_bounds_optional = True # Bounds may not be required but are optional
     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
+    supported_dimensions = 1
+    supported_priors = False
 
     def __init__(self, bvalues=None, thresholds=None, bounds=None, initial_guess=None, weighting=None, stats=False):
         """

src/standardized/IAR_LU_modified_mix.py

@@ -26,12 +26,13 @@ class IAR_LU_modified_mix(OsipiBase):
     required_bounds_optional = True # Bounds may not be required but are optional
     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 = False
     supported_thresholds = False
+    supported_dimensions = 1
+    supported_priors = False
 
     def __init__(self, bvalues=None, thresholds=None, bounds=None, initial_guess=None, weighting=None, stats=False):
         """

src/standardized/IAR_LU_modified_topopro.py

@@ -26,12 +26,13 @@ class IAR_LU_modified_topopro(OsipiBase):
     required_bounds_optional = True # Bounds may not be required but are optional
     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 = False
     supported_thresholds = False
+    supported_dimensions = 1
+    supported_priors = False
 
     def __init__(self, bvalues=None, thresholds=None, bounds=None, initial_guess=None, weighting=None, stats=False):
         """

src/standardized/IAR_LU_segmented_2step.py

@@ -26,12 +26,13 @@ class IAR_LU_segmented_2step(OsipiBase):
     required_bounds_optional = True # Bounds may not be required but are optional
     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 = True
+    supported_dimensions = 1
+    supported_priors = False
 
     def __init__(self, bvalues=None, thresholds=None, bounds=None, initial_guess=None):
         """

src/standardized/IAR_LU_segmented_3step.py

@@ -26,12 +26,13 @@ class IAR_LU_segmented_3step(OsipiBase):
     required_bounds_optional = True # Bounds may not be required but are optional
     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
+    supported_dimensions = 1
+    supported_priors = False
 
     def __init__(self, bvalues=None, thresholds=None, bounds=None, initial_guess=None, weighting=None, stats=False):
         """

src/standardized/IAR_LU_subtracted.py

@@ -26,12 +26,13 @@ class IAR_LU_subtracted(OsipiBase):
     required_bounds_optional = True # Bounds may not be required but are optional
     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
+    supported_dimensions = 1
+    supported_priors = False
 
     def __init__(self, bvalues=None, thresholds=None, bounds=None, initial_guess=None):
         """

src/standardized/OGC_AmsterdamUMC_Bayesian_biexp.py

@@ -25,13 +25,13 @@ class OGC_AmsterdamUMC_Bayesian_biexp(OsipiBase):
     required_bounds_optional = True  # Bounds may not be required but are optional
     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 = True
+    supported_dimensions = 1
     supported_priors = True
 
     def __init__(self, bvalues=None, thresholds=None, bounds=None, initial_guess=None, fitS0=True, prior_in=None):

src/standardized/OGC_AmsterdamUMC_biexp.py

@@ -25,13 +25,14 @@ class OGC_AmsterdamUMC_biexp(OsipiBase):
     required_bounds_optional = True  # Bounds may not be required but are optional
     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
+    supported_dimensions = 1
+    supported_priors = False
 
     def __init__(self, bvalues=None, thresholds=None, bounds=None, initial_guess=None, fitS0=True):
         """

src/standardized/OGC_AmsterdamUMC_biexp_segmented.py

@@ -25,13 +25,14 @@ class OGC_AmsterdamUMC_biexp_segmented(OsipiBase):
     required_bounds_optional = True  # Bounds may not be required but are optional
     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 = True
+    supported_dimensions = 1
+    supported_priors = False
 
     def __init__(self, bvalues=None, thresholds=150, bounds=None, initial_guess=None):
         """