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progress bar #2

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progress bar #2

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c2f5b78
include counter
robbertmijn Sep 20, 2023
046acb6
optional progbar
robbertmijn Sep 20, 2023
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21 changes: 17 additions & 4 deletions time_series_test.py
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Original file line number Diff line number Diff line change
Expand Up @@ -16,6 +16,7 @@
import random
from collections import namedtuple


__version__ = '0.11.2'
DEFAULT_HUE_COLORMAP = 'Dark2'
DEFAULT_ANNOTATION_COLORMAP = 'brg'
Expand Down Expand Up @@ -116,7 +117,7 @@ def lmer_crossvalidation_test(dm, formula, groups, re_formula=None, winlen=1,
samples_re=samples_re, **kwargs)


def lmer_series(dm, formula, winlen=1, fit_kwargs={}, **kwargs):
def lmer_series(dm, formula, winlen=1, progbar=False, fit_kwargs={}, **kwargs):
"""Performs a sample-by-sample linear-mixed-effects analysis. See
`lmer_crossvalidation()` for an explanation of the arguments.

Expand Down Expand Up @@ -161,7 +162,14 @@ def lmer_series(dm, formula, winlen=1, fit_kwargs={}, **kwargs):
model = smf.ols
else:
model = smf.mixedlm
for i in range(0, depth, winlen):

if progbar:
from tqdm import tqdm
iterator = tqdm(range(0, depth, winlen), 'lmer_series')
else:
iterator = range(0, depth, winlen)

for i in iterator:
logger.debug('sample {}'.format(i))
with warnings.catch_warnings():
warnings.simplefilter('ignore')
Expand Down Expand Up @@ -192,7 +200,7 @@ def lmer_series(dm, formula, winlen=1, fit_kwargs={}, **kwargs):
def lmer_permutation_test(dm, formula, groups, re_formula=None, winlen=1,
suppress_convergence_warnings=False, fit_kwargs={},
iterations=1000, cluster_p_threshold=.05,
test_intercept=False, **kwargs):
test_intercept=False, progbar=False, **kwargs):
"""Performs a cluster-based permutation test based on sample-by-sample
linear-mixed-effects analyses. The permutation test identifies clusters
based on p-value threshold and uses the absolute of the summed z-values of
Expand Down Expand Up @@ -254,7 +262,12 @@ def lmer_permutation_test(dm, formula, groups, re_formula=None, winlen=1,
for effect, clusters in cluster_obs.items()}
logger.info(f'observed clusters: {cluster_obs}')
# Now run through all iterations
for i in range(iterations):
if progbar:
from tqdm import tqdm
iterator = tqdm(iterations, 'lmer_permutation_test')
else:
iterator = iterations
for i in iterator:
# If there are no significant clusters, we'll skip the test altogether
# to save time. The Intercept doesn't count here, because the intercept
# generally does have significant clusters but we're not interested in
Expand Down