brainiak · mihaic · Jan 14, 2019 · Jan 10, 2019 · Jan 10, 2019 · Jan 13, 2019
diff --git a/brainiak/fcma/preprocessing.py b/brainiak/fcma/preprocessing.py
@@ -30,11 +30,11 @@
 logger = logging.getLogger(__name__)
 
 __all__ = [
-    "RandomType",
-    "prepare_fcma_data",
     "generate_epochs_info",
+    "prepare_fcma_data",
     "prepare_mvpa_data",
     "prepare_searchlight_mvpa_data",
+    "RandomType",
 ]
 
 

diff --git a/brainiak/fcma/util.py b/brainiak/fcma/util.py
@@ -24,6 +24,10 @@
 from scipy.stats.mstats import zscore
 import math
 
+__all__ = [
+    "compute_correlation",
+]
+
 
 def _normalize_for_correlation(data, axis):
     """normalize the data before computing correlation

diff --git a/brainiak/funcalign/srm.py b/brainiak/funcalign/srm.py
@@ -43,7 +43,8 @@
 import sys
 
 __all__ = [
-    "SRM", "DetSRM"
+    "DetSRM",
+    "SRM",
 ]
 
 logger = logging.getLogger(__name__)

diff --git a/brainiak/funcalign/sssrm.py b/brainiak/funcalign/sssrm.py
@@ -46,7 +46,7 @@
 from brainiak.funcalign import srm
 
 __all__ = [
-    "SSSRM"
+    "SSSRM",
 ]
 
 logger = logging.getLogger(__name__)

diff --git a/brainiak/hyperparamopt/hpo.py b/brainiak/hyperparamopt/hpo.py
@@ -38,6 +38,10 @@
 
 logger = logging.getLogger(__name__)
 
+__all__ = [
+    "fmin",
+]
+
 
 def get_sigma(x, min_limit=-np.inf, max_limit=np.inf):
     """Compute the standard deviations around the points for a 1D GMM.

diff --git a/brainiak/image.py b/brainiak/image.py
@@ -15,10 +15,11 @@
 
 __all__ = [
     "ConditionSpec",
-    "SingleConditionSpec",
-    "mask_image",
     "MaskedMultiSubjectData",
+    "mask_image",
+    "mask_images",
     "multimask_images",
+    "SingleConditionSpec",
 ]
 
 import itertools

diff --git a/brainiak/io.py b/brainiak/io.py
@@ -15,6 +15,7 @@
 
 __all__ = [
     "load_boolean_mask",
+    "load_images",
     "load_images_from_dir",
     "load_labels",
     "save_as_nifti_file",

diff --git a/brainiak/isc.py b/brainiak/isc.py
@@ -58,6 +58,17 @@
 
 logger = logging.getLogger(__name__)
 
+__all__ = [
+    "bootstrap_isc",
+    "compute_summary_statistic",
+    "isfc",
+    "isc",
+    "permutation_isc",
+    "phaseshift_isc",
+    "timeshift_isc",
+]
+
+
 MAX_RANDOM_SEED = 2**32 - 1
 
 
@@ -105,7 +116,7 @@ def isc(data, pairwise=False, summary_statistic=None):
     """
 
     # Check response time series input format
-    data, n_TRs, n_voxels, n_subjects = check_timeseries_input(data)
+    data, n_TRs, n_voxels, n_subjects = _check_timeseries_input(data)
 
     # No summary statistic if only two subjects
     if n_subjects == 2:
@@ -184,7 +195,7 @@ def isfc(data, pairwise=False, summary_statistic=None):
     """
 
     # Check response time series input format
-    data, n_TRs, n_voxels, n_subjects = check_timeseries_input(data)
+    data, n_TRs, n_voxels, n_subjects = _check_timeseries_input(data)
 
     # Handle just two subjects properly
     if n_subjects == 2:
@@ -236,7 +247,7 @@ def isfc(data, pairwise=False, summary_statistic=None):
     return isfcs
 
 
-def check_timeseries_input(data):
+def _check_timeseries_input(data):
 
     """Checks response time series input data for ISC analysis
 
@@ -299,7 +310,7 @@ def check_timeseries_input(data):
     return data, n_TRs, n_voxels, n_subjects
 
 
-def check_isc_input(iscs, pairwise=False):
+def _check_isc_input(iscs, pairwise=False):
 
     """Checks ISC inputs for statistical tests
 
@@ -466,7 +477,7 @@ def bootstrap_isc(iscs, pairwise=False, summary_statistic='median',
     """
 
     # Standardize structure of input data
-    iscs, n_subjects, n_voxels = check_isc_input(iscs, pairwise=pairwise)
+    iscs, n_subjects, n_voxels = _check_isc_input(iscs, pairwise=pairwise)
 
     # Check for valid summary statistic
     if summary_statistic not in ('mean', 'median'):
@@ -558,7 +569,7 @@ def bootstrap_isc(iscs, pairwise=False, summary_statistic='median',
     return observed, ci, p, distribution
 
 
-def check_group_assignment(group_assignment, n_subjects):
+def _check_group_assignment(group_assignment, n_subjects):
     if type(group_assignment) == list:
         pass
     elif type(group_assignment) == np.ndarray:
@@ -574,7 +585,7 @@ def check_group_assignment(group_assignment, n_subjects):
     return group_assignment
 
 
-def get_group_parameters(group_assignment, n_subjects, pairwise=False):
+def _get_group_parameters(group_assignment, n_subjects, pairwise=False):
 
     # Set up dictionary to contain group info
     group_parameters = {'group_assignment': group_assignment,
@@ -652,9 +663,9 @@ def get_group_parameters(group_assignment, n_subjects, pairwise=False):
     return group_parameters
 
 
-def permute_one_sample_iscs(iscs, group_parameters, i, pairwise=False,
-                            summary_statistic='median', group_matrix=None,
-                            exact_permutations=None, prng=None):
+def _permute_one_sample_iscs(iscs, group_parameters, i, pairwise=False,
+                             summary_statistic='median', group_matrix=None,
+                             exact_permutations=None, prng=None):
 
     """Applies one-sample permutations to ISC data
 
@@ -720,9 +731,9 @@ def permute_one_sample_iscs(iscs, group_parameters, i, pairwise=False,
     return isc_sample
 
 
-def permute_two_sample_iscs(iscs, group_parameters, i, pairwise=False,
-                            summary_statistic='median',
-                            exact_permutations=None, prng=None):
+def _permute_two_sample_iscs(iscs, group_parameters, i, pairwise=False,
+                             summary_statistic='median',
+                             exact_permutations=None, prng=None):
 
     """Applies two-sample permutations to ISC data
 
@@ -875,19 +886,19 @@ def permutation_isc(iscs, group_assignment=None, pairwise=False,  # noqa: C901
     """
 
     # Standardize structure of input data
-    iscs, n_subjects, n_voxels = check_isc_input(iscs, pairwise=pairwise)
+    iscs, n_subjects, n_voxels = _check_isc_input(iscs, pairwise=pairwise)
 
     # Check for valid summary statistic
     if summary_statistic not in ('mean', 'median'):
         raise ValueError("Summary statistic must be 'mean' or 'median'")
 
     # Check match between group labels and ISCs
-    group_assignment = check_group_assignment(group_assignment,
-                                              n_subjects)
+    group_assignment = _check_group_assignment(group_assignment,
+                                               n_subjects)
 
     # Get group parameters
-    group_parameters = get_group_parameters(group_assignment, n_subjects,
-                                            pairwise=pairwise)
+    group_parameters = _get_group_parameters(group_assignment, n_subjects,
+                                             pairwise=pairwise)
 
     # Set up permutation type (exact or Monte Carlo)
     if group_parameters['n_groups'] == 1:
@@ -956,7 +967,7 @@ def permutation_isc(iscs, group_assignment=None, pairwise=False,  # noqa: C901
 
         # If one group, apply sign-flipping procedure
         if group_parameters['n_groups'] == 1:
-            isc_sample = permute_one_sample_iscs(
+            isc_sample = _permute_one_sample_iscs(
                             iscs, group_parameters, i,
                             pairwise=pairwise,
                             summary_statistic=summary_statistic,
@@ -965,7 +976,7 @@ def permutation_isc(iscs, group_assignment=None, pairwise=False,  # noqa: C901
 
         # If two groups, set up group matrix get the observed difference
         else:
-            isc_sample = permute_two_sample_iscs(
+            isc_sample = _permute_two_sample_iscs(
                             iscs, group_parameters, i,
                             pairwise=pairwise,
                             summary_statistic=summary_statistic,
@@ -1057,7 +1068,7 @@ def timeshift_isc(data, pairwise=False, summary_statistic='median',
     """
 
     # Check response time series input format
-    data, n_TRs, n_voxels, n_subjects = check_timeseries_input(data)
+    data, n_TRs, n_voxels, n_subjects = _check_timeseries_input(data)
 
     # Get actual observed ISC
     observed = isc(data, pairwise=pairwise,
@@ -1191,7 +1202,7 @@ def phaseshift_isc(data, pairwise=False, summary_statistic='median',
     """
 
     # Check response time series input format
-    data, n_TRs, n_voxels, n_subjects = check_timeseries_input(data)
+    data, n_TRs, n_voxels, n_subjects = _check_timeseries_input(data)
 
     # Get actual observed ISC
     observed = isc(data, pairwise=pairwise,

diff --git a/brainiak/reprsimil/brsa.py b/brainiak/reprsimil/brsa.py
@@ -62,8 +62,11 @@
 logger = logging.getLogger(__name__)
 
 __all__ = [
-    "BRSA", "GBRSA", "prior_GP_var_inv_gamma", "prior_GP_var_half_cauchy",
-    "Ncomp_SVHT_MG_DLD_approx"
+    "BRSA",
+    "GBRSA",
+    "Ncomp_SVHT_MG_DLD_approx",
+    "prior_GP_var_inv_gamma",
+    "prior_GP_var_half_cauchy",
 ]
 
 

diff --git a/brainiak/searchlight/searchlight.py b/brainiak/searchlight/searchlight.py
@@ -23,7 +23,11 @@
 """
 
 __all__ = [
-        "Searchlight", "Shape", "Cube", "Diamond", "Ball"
+    "Ball",
+    "Cube",
+    "Diamond",
+    "Searchlight",
+    "Shape",
 ]
 
 

diff --git a/brainiak/utils/fmrisim.py b/brainiak/utils/fmrisim.py
@@ -92,16 +92,16 @@
 import copy
 
 __all__ = [
-    "generate_signal",
-    "generate_stimfunction",
-    "export_3_column",
-    "export_epoch_file",
-    "convolve_hrf",
     "apply_signal",
     "calc_noise",
+    "compute_signal_change",
+    "convolve_hrf",
+    "export_3_column",
+    "export_epoch_file",
+    "generate_signal",
+    "generate_stimfunction",
     "generate_noise",
     "mask_brain",
-    "compute_signal_change",
 ]
 
 logger = logging.getLogger(__name__)

diff --git a/brainiak/utils/utils.py b/brainiak/utils/utils.py
@@ -30,18 +30,19 @@
 """
 
 __all__ = [
-    "from_tri_2_sym",
-    "from_sym_2_tri",
-    "sumexp_stable",
+    "center_mass_exp",
+    "compute_p_from_null_distribution",
     "concatenate_not_none",
     "cov2corr",
-    "ReadDesign",
+    "ecdf",
+    "from_tri_2_sym",
+    "from_sym_2_tri",
     "gen_design",
-    "usable_cpu_count",
-    "center_mass_exp",
     "phase_randomize",
-    "ecdf",
-    "p_from_null"
+    "p_from_null",
+    "ReadDesign",
+    "sumexp_stable",
+    "usable_cpu_count",
 ]