def temporal_qc_al_in_one():
import matplotlib.pyplot as plt
import matplotlib.ticker as plticker
import numpy as np
from samri.report.snr import iter_base_metrics
from samri.plotting.timeseries import multi
from samri.utilities import bids_substitution_iterator
substitutions = bids_substitution_iterator(
['testSTIM'],
['COILphantom'],
['CcsI'],
'/home/chymera/ni_data/phantoms/',
'bids',
acquisitions=[
'EPIalladj', 'EPIcopyadjNODUM', 'EPIcopyadj', 'EPImoveGOP'
],
)
timecourses = iter_base_metrics(
'{data_dir}/{preprocessing_dir}/sub-{subject}/ses-{session}/func/sub-{subject}_ses-{session}_acq-{acquisition}_task-{task}.nii',
substitutions)
multi(
timecourses,
designs=[],
events_dfs=[],
subplot_titles='acquisition',
quantitative=False,
save_as="temp_qc.pdf",
samri_style=True,
ax_size=[16, 6],
unit_ticking=True,
)
def p_clusters(mask):
from samri.plotting import summary, timeseries
substitutions = bids_substitution_iterator(
["ofM", "ofM_aF", "ofM_cF1", "ofM_cF2", "ofM_pF"],
["4011", "4012", "5689", "5690", "5691"],
# ["4007","4008","4011","4012","5689","5690","5691"],
["EPI_CBV_jb_long", "EPI_CBV_chr_longSOA"],
"~/ni_data/ofM.dr/",
"composite",
l1_dir="dr",
)
timecourses, designs, stat_maps, events_dfs, subplot_titles = summary.p_filtered_ts(
substitutions,
ts_file_template=
"{data_dir}/preprocessing/{preprocessing_dir}/sub-{subject}/ses-{session}/func/sub-{subject}_ses-{session}_task-{scan}.nii.gz",
beta_file_template=
"{data_dir}/l1/{l1_dir}/sub-{subject}/ses-{session}/sub-{subject}_ses-{session}_task-{scan}_cope.nii.gz",
# p_file_template="{data_dir}/l1/{l1_dir}/sub-{subject}/ses-{session}/sub-{subject}_ses-{session}_task-{scan}_pstat.nii.gz",
p_file_template=
"{data_dir}/l1/{l1_dir}/sub-{subject}/ses-{session}/sub-{subject}_ses-{session}_task-{scan}_pfstat.nii.gz",
design_file_template=
"{data_dir}/l1/{l1_workdir}/_subject_session_scan_{subject}.{session}.{scan}/modelgen/run0.mat",
event_file_template=
"{data_dir}/preprocessing/{preprocessing_dir}/sub-{subject}/ses-{session}/func/sub-{subject}_ses-{session}_task-{scan}_events.tsv",
brain_mask=mask,
p_level=0.05,
)
timeseries.multi(timecourses,
designs,
stat_maps,
events_dfs,
subplot_titles,
figure="timecourses")
plt.show()
def temporal_qc_al_in_one():
import matplotlib.pyplot as plt
import matplotlib.ticker as plticker
import numpy as np
from samri.report.snr import iter_base_metrics
from samri.plotting.timeseries import multi
from samri.utilities import bids_substitution_iterator
substitutions = bids_substitution_iterator(
['testSTIM'],
['COILphantom'],
['CcsI'],
'/home/chymera/ni_data/phantoms/',
'bids',
acquisitions=['EPIalladj','EPIcopyadjNODUM','EPIcopyadj','EPImoveGOP'],
)
timecourses = iter_base_metrics('{data_dir}/{preprocessing_dir}/sub-{subject}/ses-{session}/func/sub-{subject}_ses-{session}_acq-{acquisition}_task-{task}.nii', substitutions)
multi(timecourses,
designs=[],
events_dfs=[],
subplot_titles='acquisition',
quantitative=False,
save_as="temp_qc.pdf",
samri_style=True,
ax_size=[16,6],
unit_ticking=True,
)
def temporal_qc_separate():
import matplotlib.pyplot as plt
import matplotlib.ticker as plticker
import numpy as np
import pandas as pd
from samri.report.snr import base_metrics
from samri.plotting.timeseries import multi
from samri.utilities import bids_substitution_iterator
substitutions = bids_substitution_iterator(
['testSTIM'],
['COILphantom'],
['CcsI'],
'/home/chymera/ni_data/phantoms/',
'bids',
acquisitions=['EPIalladj','EPIcopyadjNODUM','EPIcopyadj','EPImoveGOP'],
)
for i in substitutions:
timecourses = base_metrics('{data_dir}/{preprocessing_dir}/sub-{subject}/ses-{session}/func/sub-{subject}_ses-{session}_acq-{acquisition}_trial-{trial}.nii', i)
events_df = pd.read_csv('{data_dir}/{preprocessing_dir}/sub-{subject}/ses-{session}/func/sub-{subject}_ses-{session}_acq-{acquisition}_trial-{trial}_events.tsv'.format(**i), sep='\t')
multi(timecourses,
designs=[],
events_dfs=[events_df],
subplot_titles='acquisition',
quantitative=False,
save_as='temp_{acquisition}.pdf'.format(**i),
samri_style=True,
ax_size=[16,6],
unit_ticking=True,
)
def temporal_qc_separate():
import matplotlib.pyplot as plt
import matplotlib.ticker as plticker
import numpy as np
import pandas as pd
from samri.report.snr import base_metrics
from samri.plotting.timeseries import multi
from samri.utilities import bids_substitution_iterator
substitutions = bids_substitution_iterator(
['testSTIM'],
['COILphantom'],
['CcsI'],
'/home/chymera/ni_data/phantoms/',
'bids',
acquisitions=['EPIalladj','EPIcopyadjNODUM','EPIcopyadj','EPImoveGOP'],
)
for i in substitutions:
timecourses = base_metrics('{data_dir}/{preprocessing_dir}/sub-{subject}/ses-{session}/func/sub-{subject}_ses-{session}_acq-{acquisition}_task-{task}.nii', i)
events_df = pd.read_csv('{data_dir}/{preprocessing_dir}/sub-{subject}/ses-{session}/func/sub-{subject}_ses-{session}_acq-{acquisition}_task-{task}_events.tsv'.format(**i), sep='\t')
multi(timecourses,
designs=[],
events_dfs=[events_df],
subplot_titles='acquisition',
quantitative=False,
save_as='temp_{acquisition}.pdf'.format(**i),
samri_style=True,
ax_size=[16,6],
unit_ticking=True,
)
def roi(roi_path="~/ni_data/templates/roi/f_dr_chr.nii.gz"): from samri.plotting import summary, timeseries substitutions = bids_substitution_iterator( ["ofM","ofM_aF","ofM_cF1","ofM_cF2","ofM_pF"], [4007,4008,4009,4011,4012], ["EPI_CBV_jb_long"], "~/ni_data/ofM.dr/", "composite", ) timecourses, designs, stat_maps, subplot_titles = summary.roi_ts(substitutions, roi_path=roi_path,) timeseries.multi(timecourses, designs, stat_maps, subplot_titles, figure="timecourses") plt.show()
def test_multi_roi_timeseries():
import matplotlib.pyplot as plt
from os import path
from samri.plotting import summary, timeseries
from samri.utilities import bids_substitution_iterator
from samri.fetch.local import roi_from_atlaslabel
substitutions = bids_substitution_iterator(
sessions=[
'ofM',
'ofMaF',
],
subjects=[
'4007',
],
runs=[
'0',
'1',
],
modalities=[
'bold',
'cbv',
],
data_dir='/usr/share/samri_bidsdata',
# BOLD scans are not recognized, since the current (=sci-biology/samri_bidsdata-0.2) filt file suffix also contains `_maths_` for CBV, but not for BOLD.
validate_for_template="{data_dir}/l1/sub-{subject}/ses-{session}/sub-{subject}_ses-{session}_task-JogB_acq-EPIlowcov_run-{run}_{modality}.nii.gz",
)
mapping='/usr/share/mouse-brain-atlases/dsurqe_labels.csv'
atlas='/usr/share/mouse-brain-atlases/dsurqec_40micron_labels.nii'
my_roi = roi_from_atlaslabel(atlas,
mapping=mapping,
label_names=['cortex'],
)
timecourses, designs, _, events_dfs, subplot_titles = summary.ts_overviews(substitutions, my_roi,
ts_file_template="{data_dir}/l1/sub-{subject}/ses-{session}/sub-{subject}_ses-{session}_task-JogB_acq-EPIlowcov_run-{run}_{modality}.nii.gz",
betas_file_template="{data_dir}/l1/sub-{subject}/ses-{session}/sub-{subject}_ses-{session}_task-JogB_acq-EPIlowcov_run-{run}_{modality}_betas.nii.gz",
design_file_template="{data_dir}/l1/sub-{subject}/ses-{session}/sub-{subject}_ses-{session}_task-JogB_acq-EPIlowcov_run-{run}_{modality}_design.mat",
event_file_template='{data_dir}/preprocessing/sub-{subject}/ses-{session}/func/sub-{subject}_ses-{session}_task-JogB_acq-EPIlowcov_run-{run}_events.tsv',
n_jobs_percentage=0.5,
)
style_file = path.join(path.dirname(path.realpath(__file__)),'../samri_multiple-ts.conf')
plt.style.use(style_file)
timeseries.multi(timecourses, designs, events_dfs, subplot_titles,
quantitative=False,
save_as='_multi_roi_timeseries.pdf',
)
def qc_regressor(sessions, subjects, scans, workflow_name, mask,
data_dir="~/ni_data/ofM.dr",
save_as="",
):
from samri.plotting import summary, timeseries
plt.style.use('samri_multiple-ts.conf')
substitutions = bids_substitution_iterator(sessions,subjects,scans,data_dir,workflow_name)
timecourses, designs, stat_maps, events_dfs, subplot_titles = summary.ts_overviews(substitutions, mask,
ts_file_template="{data_dir}/preprocessing/{preprocessing_dir}/sub-{subject}/ses-{session}/func/sub-{subject}_ses-{session}_trial-{scan}.nii.gz",
beta_file_template="{data_dir}/l1/{l1_dir}/sub-{subject}/ses-{session}/sub-{subject}_ses-{session}_trial-{scan}_cope.nii.gz",
design_file_template="{data_dir}/l1/{l1_workdir}/_subject_session_scan_{subject}.{session}.{scan}/modelgen/run0.mat",
event_file_template="{data_dir}/preprocessing/{preprocessing_dir}/sub-{subject}/ses-{session}/func/sub-{subject}_ses-{session}_trial-{scan}_events.tsv",
)
timeseries.multi(timecourses, designs, stat_maps, events_dfs, subplot_titles,
figure="timecourses",
quantitative=False,
save_as=save_as,
)
def qc_regressor(sessions, subjects, scans, workflow_name, mask,
data_dir="~/ni_data/ofM.dr",
save_as="",
):
from samri.plotting import summary, timeseries
plt.style.use('samri_multiple-ts.conf')
substitutions = bids_substitution_iterator(sessions,subjects,scans,data_dir,workflow_name)
timecourses, designs, stat_maps, events_dfs, subplot_titles = summary.ts_overviews(substitutions, mask,
ts_file_template="{data_dir}/preprocessing/{preprocessing_dir}/sub-{subject}/ses-{session}/func/sub-{subject}_ses-{session}_task-{scan}.nii.gz",
beta_file_template="{data_dir}/l1/{l1_dir}/sub-{subject}/ses-{session}/sub-{subject}_ses-{session}_task-{scan}_cope.nii.gz",
design_file_template="{data_dir}/l1/{l1_workdir}/_subject_session_scan_{subject}.{session}.{scan}/modelgen/run0.mat",
event_file_template="{data_dir}/preprocessing/{preprocessing_dir}/sub-{subject}/ses-{session}/func/sub-{subject}_ses-{session}_task-{scan}_events.tsv",
)
timeseries.multi(timecourses, designs, stat_maps, events_dfs, subplot_titles,
figure="timecourses",
quantitative=False,
save_as=save_as,
)
def p_clusters(mask):
from samri.plotting import summary, timeseries
substitutions = bids_substitution_iterator(
["ofM","ofM_aF","ofM_cF1","ofM_cF2","ofM_pF"],
["4011","4012","5689","5690","5691"],
# ["4007","4008","4011","4012","5689","5690","5691"],
["EPI_CBV_jb_long","EPI_CBV_chr_longSOA"],
"~/ni_data/ofM.dr/",
"composite",
l1_dir="dr",
)
timecourses, designs, stat_maps, events_dfs, subplot_titles = summary.p_filtered_ts(substitutions,
ts_file_template="{data_dir}/preprocessing/{preprocessing_dir}/sub-{subject}/ses-{session}/func/sub-{subject}_ses-{session}_task-{scan}.nii.gz",
beta_file_template="{data_dir}/l1/{l1_dir}/sub-{subject}/ses-{session}/sub-{subject}_ses-{session}_task-{scan}_cope.nii.gz",
# p_file_template="{data_dir}/l1/{l1_dir}/sub-{subject}/ses-{session}/sub-{subject}_ses-{session}_task-{scan}_pstat.nii.gz",
p_file_template="{data_dir}/l1/{l1_dir}/sub-{subject}/ses-{session}/sub-{subject}_ses-{session}_task-{scan}_pfstat.nii.gz",
design_file_template="{data_dir}/l1/{l1_workdir}/_subject_session_scan_{subject}.{session}.{scan}/modelgen/run0.mat",
event_file_template="{data_dir}/preprocessing/{preprocessing_dir}/sub-{subject}/ses-{session}/func/sub-{subject}_ses-{session}_task-{scan}_events.tsv",
brain_mask=mask,
p_level=0.05,
)
timeseries.multi(timecourses, designs, stat_maps, events_dfs, subplot_titles, figure="timecourses")
plt.show()
def test_multi_roi_timeseries():
import matplotlib.pyplot as plt
from os import path
from samri.plotting import summary, timeseries
from samri.utilities import bids_substitution_iterator
from samri.fetch.local import roi_from_atlaslabel
substitutions = bids_substitution_iterator(
sessions=[
'ofM',
'ofMaF',
],
subjects=[
'4007',
],
runs=[
'0',
'1',
],
modalities=[
'bold',
'cbv',
],
data_dir='/usr/share/samri_bidsdata',
# BOLD scans are not recognized, since the current (=sci-biology/samri_bidsdata-0.2) filt file suffix also contains `_maths_` for CBV, but not for BOLD.
validate_for_template=
"{data_dir}/l1/sub-{subject}/ses-{session}/sub-{subject}_ses-{session}_task-JogB_acq-EPIlowcov_run-{run}_{modality}.nii.gz",
)
mapping = '/usr/share/mouse-brain-atlases/dsurqe_labels.csv'
atlas = '/usr/share/mouse-brain-atlases/dsurqec_40micron_labels.nii'
my_roi = roi_from_atlaslabel(
atlas,
mapping=mapping,
label_names=['cortex'],
)
timecourses, designs, _, events_dfs, subplot_titles = summary.ts_overviews(
substitutions,
my_roi,
ts_file_template=
"{data_dir}/l1/sub-{subject}/ses-{session}/sub-{subject}_ses-{session}_task-JogB_acq-EPIlowcov_run-{run}_{modality}.nii.gz",
betas_file_template=
"{data_dir}/l1/sub-{subject}/ses-{session}/sub-{subject}_ses-{session}_task-JogB_acq-EPIlowcov_run-{run}_{modality}_betas.nii.gz",
design_file_template=
"{data_dir}/l1/sub-{subject}/ses-{session}/sub-{subject}_ses-{session}_task-JogB_acq-EPIlowcov_run-{run}_{modality}_design.mat",
event_file_template=
'{data_dir}/preprocessing/sub-{subject}/ses-{session}/func/sub-{subject}_ses-{session}_task-JogB_acq-EPIlowcov_run-{run}_events.tsv',
n_jobs_percentage=0.5,
)
style_file = path.join(path.dirname(path.realpath(__file__)),
'../samri_multiple-ts.conf')
plt.style.use(style_file)
timeseries.multi(
timecourses,
designs,
events_dfs,
subplot_titles,
quantitative=False,
save_as='_multi_roi_timeseries.pdf',
)
