added __all__ to all python files

dmipy/core/fitted_modeling_framework.py

@@ -6,6 +6,11 @@
     estimate_spherical_mean_multi_shell)
 
 
+__all__ = [
+    'FittedMultiCompartmentModel'
+]
+
+
 class FittedMultiCompartmentModel:
     """
     The FittedMultiCompartmentModel instance contains information about the

dmipy/core/gradient_conversions.py

@@ -2,6 +2,16 @@
 from .constants import CONSTANTS
 
 
+__all__ = [
+    'q_from_b',
+    'b_from_q',
+    'q_from_g',
+    'g_from_q',
+    'b_from_g',
+    'g_from_b'
+]
+
+
 def q_from_b(
     b, delta, Delta
 ):

dmipy/core/modeling_framework.py

@@ -31,8 +31,17 @@
     'dmipy', 'signal_models'
 )
 
+__all__ = [
+    'ModelProperties',
+    'MultiCompartmentModelProperties',
+    'MultiCompartmentModel',
+    'homogenize_x0_to_data',
+    'ReturnFixedValue'
+]
+
 
 class ModelProperties:
+    "Contains various properties for CompartmentModels."
     @property
     def parameter_ranges(self):
         """Returns the optimization ranges of the model parameters.

dmipy/data/saved_acquisition_schemes.py

@@ -13,7 +13,14 @@
 )
 
 
+__all__ = [
+    'wu_minn_hcp_acquisition_scheme',
+    'duval_cat_spinal_cord_2d_acquisition_scheme'
+]
+
+
 def wu_minn_hcp_acquisition_scheme():
+    "Returns DmipyAcquisitionScheme of Wu-Minn HCP project."
     _bvals = np.loadtxt(
         join(_GRADIENT_TABLES_PATH,
              'bvals_hcp_wu_minn.txt')
@@ -28,7 +35,8 @@ def wu_minn_hcp_acquisition_scheme():
         _bvals, _gradient_directions, _delta, _Delta)
 
 
-def duval_cat_spinal_cord_2d_acquisition_scheme():
+def duval_cat_spinal_cord_2d_acquisition_scheme(bval_shell_distance=1e10):
+    "Returns DmipyAcquisitionScheme of cat spinal cord data."
     scheme_name = 'tanguy_cat_spinal_cord/2D_qspace.scheme'
     scheme = np.loadtxt(DATA_PATH + scheme_name, skiprows=3)
 
@@ -39,7 +47,5 @@ def duval_cat_spinal_cord_2d_acquisition_scheme():
     delta = scheme[:, 5]
     TE = scheme[:, 6]
 
-    bval_shell_distance = 1e10
-
     return acquisition_scheme_from_gradient_strengths(
         G, bvecs, delta, Delta, TE, min_b_shell_distance=bval_shell_distance)

dmipy/data/saved_data.py

@@ -9,8 +9,17 @@
     'dmipy', 'data'
 )
 
+__all__ = [
+    'wu_minn_hcp_coronal_slice',
+    'duval_cat_spinal_cord_2d',
+    'synthetic_camino_data_parallel',
+    'synthetic_camino_data_dispersed',
+    'visualize_correlation_camino_and_estimated_fractions'
+]
+
 
 def wu_minn_hcp_coronal_slice():
+    "Returns example slice of Wu-Minn HCP data subject 100307."
     data_path = join(
         DATA_PATH, 'hcp', 'hcp_example_slice', 'coronal_slice.nii.gz')
     try:
@@ -36,6 +45,7 @@ def wu_minn_hcp_coronal_slice():
 
 
 def duval_cat_spinal_cord_2d():
+    "Returns 2D multi-diffusion time AxCaliber data of cat spinal cord."
     msg = "This data was used by Duval et al. 'Validation of quantitative MRI "
     msg += "metrics using full slice histology with automatic axon "
     msg += "segmentation', ISMRM 2016. Reference at "
@@ -163,6 +173,7 @@ def __init__(self):
 
 def visualize_correlation_camino_and_estimated_fractions(
         estim_fractions_parallel, estim_fractions_dispersed):
+    "Function that visualizes Camino estimated results versus ground truth."
 
     data_parallel = synthetic_camino_data_parallel()
     data_dispersed = synthetic_camino_data_dispersed()

dmipy/distributions/distribute_models.py

@@ -7,6 +7,14 @@
 import copy
 import numpy as np
 
+__all__ = [
+    'DistributedModel',
+    'SD1WatsonDistributed',
+    'SD2BinghamDistributed',
+    'DD1GammaDistributed',
+    'ReturnFixedValue'
+]
+
 
 class DistributedModel:
     "Contains various properties of distributed models."

dmipy/distributions/distributions.py

@@ -45,6 +45,15 @@
 }
 BETA_SCALING = 1e-6
 
+__all__ = [
+    'get_sh_order_from_odi',
+    'SD1Watson',
+    'SD2Bingham',
+    'DD1GammaDistribution',
+    'odi2kappa',
+    'kappa2odi'
+]
+
 
 def get_sh_order_from_odi(odi):
     "Returns minimum sh_order to estimate spherical harmonics for given odi."

dmipy/hcp_interface/downloader_aws.py

@@ -9,6 +9,10 @@
     'dmipy', 'data'
 )
 
+__all__ = [
+    'HCPInterface'
+]
+
 
 class HCPInterface:
     """

dmipy/optimizers/brute2fine.py

@@ -10,6 +10,14 @@
     'dmipy', 'data/spheres'
 )
 
+__all__ = [
+    'GlobalBruteOptimizer',
+    'Brute2FineOptimizer',
+    'nested_to_normalized_fractions',
+    'normalized_to_nested_fractions_array',
+    'find_minimum_argument'
+]
+
 
 class GlobalBruteOptimizer:
     r"""

dmipy/optimizers/mix.py

@@ -1,6 +1,13 @@
 import numpy as np
 from scipy.optimize import differential_evolution, minimize, fmin_cobyla
 
+__all__ = [
+    'MixOptimizer',
+    'nested_to_normalized_fractions',
+    'cobyla_positivity_constraint',
+    'cobyla_unity_constraint'
+]
+
 
 class MixOptimizer:
     """ The stochastic Microstructure In Crossings (MIX) optimizer [1] uses a

dmipy/signal_models/capped_cylinder_models.py

@@ -4,6 +4,10 @@
 from ..core.constants import CONSTANTS
 import numpy as np
 
+__all__ = [
+    'CC3CappedCylinderCallaghanApproximation',
+]
+
 
 class CC3CappedCylinderCallaghanApproximation(ModelProperties):
     r""" The Callaghan model [1]_ - a cylinder with finite radius - for

dmipy/signal_models/cylinder_models.py

@@ -30,6 +30,14 @@
 A_SCALING = 1e-12
 
 
+__all__ = [
+    'C1Stick',
+    'C2CylinderSodermanApproximation',
+    'C3CylinderCallaghanApproximation',
+    'C4CylinderGaussianPhaseApproximation'
+]
+
+
 class C1Stick(ModelProperties):
     r""" The Stick model [1]_ - a cylinder with zero radius - typically used
     for intra-axonal diffusion.

dmipy/signal_models/gaussian_models.py

@@ -32,6 +32,12 @@
 DIFFUSIVITY_SCALING = 1e-9
 A_SCALING = 1e-12
 
+__all__ = [
+    'G1Ball',
+    'G2Zeppelin',
+    'G3RestrictedZeppelin'
+]
+
 
 class G1Ball(ModelProperties):
     r""" The Ball model [1]_ - an isotropic Tensor with one diffusivity.

dmipy/signal_models/plane_models.py

@@ -6,6 +6,11 @@
 DIAMETER_SCALING = 1e-6
 
 
+__all__ = [
+    'P3PlaneCallaghanApproximation'
+]
+
+
 class P3PlaneCallaghanApproximation(ModelProperties):
     r"""
     The Callaghan model [1]_ of diffusion between two parallel infinite plates.

dmipy/signal_models/sphere_models.py

@@ -3,6 +3,11 @@
 
 DIAMETER_SCALING = 1e-6
 
+__all__ = [
+    'S1Dot',
+    'S2SphereSodermanApproximation'
+]
+
 
 class S1Dot(ModelProperties):
     r"""

dmipy/signal_models/spherical_mean_models.py

@@ -10,6 +10,12 @@
 DIFFUSIVITY_SCALING = 1e-9
 A_SCALING = 1e-12
 
+__all__ = [
+    'C1StickSphericalMean',
+    'G2ZeppelinSphericalMean',
+    'G3RestrictedZeppelinSphericalMean'
+]
+
 
 class C1StickSphericalMean(ModelProperties):
     r"""

dmipy/utils/spherical_convolution.py

@@ -4,6 +4,11 @@
 from dipy.utils.optpkg import optional_package
 numba, have_numba, _ = optional_package("numba")
 
+__all__ = [
+    'real_sym_rh_basis',
+    'sh_convolution'
+]
+
 
 def real_sym_rh_basis(sh_order, theta, phi):
     r"""Samples a real symmetric rotational harmonic basis at point on the sphere

dmipy/utils/spherical_mean.py

@@ -2,6 +2,11 @@
 from dipy.reconst.shm import real_sym_sh_mrtrix
 from . import utils
 
+__all__ = [
+    'estimate_spherical_mean_multi_shell',
+    'estimate_spherical_mean_shell'
+]
+
 
 def estimate_spherical_mean_multi_shell(E_attenuation, acquisition_scheme,
                                         sh_order=6):

dmipy/utils/utils.py

@@ -5,6 +5,24 @@
 SPHERE = get_sphere('symmetric362')
 numba, have_numba, _ = optional_package("numba")
 
+__all__ = [
+    'perpendicular_vector',
+    'rotation_matrix_around_100',
+    'rotation_matrix_100_to_theta_phi',
+    'rotation_matrix_100_to_xyz',
+    'rotation_matrix_001_to_xyz',
+    'rotation_matrix_100_to_theta_phi_psi',
+    'T1_tortuosity',
+    'parameter_equality',
+    'define_shell_indices',
+    'cart2sphere',
+    'cart2mu',
+    'R2mu_psi',
+    'sphere2cart',
+    'unitsphere2cart_1d',
+    'unitsphere2cart_Nd'
+]
+
 
 def perpendicular_vector(v):
     """Returns a perpendicular vector to vector "v".