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buffer_size=1000
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Martin Luessi committed Aug 2, 2013
1 parent 658b6ff commit 18c5029
Showing 1 changed file with 4 additions and 4 deletions.
8 changes: 4 additions & 4 deletions mne/stats/cluster_level.py
Original file line number Diff line number Diff line change
Expand Up @@ -871,7 +871,7 @@ def permutation_cluster_test(X, threshold=None, n_permutations=1024,
connectivity=None, verbose=None, n_jobs=1,
seed=None, max_step=1, exclude=None,
step_down_p=0, t_power=1, out_type='mask',
check_disjoint=False, buffer_size=500):
check_disjoint=False, buffer_size=1000):
"""Cluster-level statistical permutation test
For a list of 2d-arrays of data, e.g. power values, calculate some
Expand Down Expand Up @@ -995,7 +995,7 @@ def permutation_cluster_1samp_test(X, threshold=None, n_permutations=1024,
connectivity=None, verbose=None, n_jobs=1,
seed=None, max_step=1, exclude=None,
step_down_p=0, t_power=1, out_type='mask',
check_disjoint=False, buffer_size=500):
check_disjoint=False, buffer_size=1000):
"""Non-parametric cluster-level 1 sample T-test
From a array of observations, e.g. signal amplitudes or power spectrum
Expand Down Expand Up @@ -1125,7 +1125,7 @@ def spatio_temporal_cluster_1samp_test(X, threshold=None,
n_permutations=1024, tail=0, stat_fun=ttest_1samp_no_p,
connectivity=None, verbose=None, n_jobs=1, seed=None, max_step=1,
spatial_exclude=None, step_down_p=0, t_power=1, out_type='indices',
check_disjoint=False, buffer_size=500):
check_disjoint=False, buffer_size=1000):
"""Non-parametric cluster-level 1 sample T-test for spatio-temporal data
This function provides a convenient wrapper for data organized in the form
Expand Down Expand Up @@ -1254,7 +1254,7 @@ def spatio_temporal_cluster_test(X, threshold=1.67,
n_permutations=1024, tail=0, stat_fun=f_oneway,
connectivity=None, verbose=None, n_jobs=1, seed=None, max_step=1,
spatial_exclude=None, step_down_p=0, t_power=1, out_type='indices',
check_disjoint=False, buffer_size=500):
check_disjoint=False, buffer_size=1000):
"""Non-parametric cluster-level test for spatio-temporal data
This function provides a convenient wrapper for data organized in the form
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