def label_activity(label):
"""
Create a DataFrame containing the per-session per-subject mean values for an autogenerated ROI based on the given label.
Other parameter customizations are hard-coded below.
"""
import pandas as pd
from samri.plotting import summary
from samri.report import roi
from samri.utilities import bids_substitution_iterator
from samri.fetch.local import roi_from_atlaslabel
from os.path import basename, splitext
mapping='/usr/share/mouse-brain-atlases/dsurqec_mapping.csv'
atlas='/usr/share/mouse-brain-atlases/dsurqec_40micron_labels.nii'
my_roi = roi_from_atlaslabel(atlas,
mapping=mapping,
label_names=[label],
)
workflow_name = 'generic'
substitutions = bids_substitution_iterator(
["ofM","ofMaF","ofMcF1","ofMcF2","ofMpF"],
['5691',"5689","5690","5700","6451","6460","6456","6461","6462"],
["CogB",],
"~/ni_data/ofM.dr/bids/",
workflow_name,
acquisitions=["EPI",],
validate_for_template='{data_dir}/l1/{l1_dir}/sub-{subject}/ses-{session}/sub-{subject}_ses-{session}_acq-{acquisition}_task-{task}_cbv_tstat.nii.gz',
)
df = roi.per_session(substitutions,
filename_template='{data_dir}/l1/{l1_dir}/sub-{subject}/ses-{session}/sub-{subject}_ses-{session}_acq-{acquisition}_task-{task}_cbv_tstat.nii.gz',
roi_mask=my_roi,
feature=[label],
atlas=atlas,
mapping=mapping,
)
df['treatment']='Fluoxetine'
substitutions_ = bids_substitution_iterator(
["ofM","ofMaF","ofMcF1","ofMcF2","ofMpF"],
["6262","6255","5694","5706",'5704','6455','6459'],
["CogB",],
"~/ni_data/ofM.dr/bids/",
workflow_name,
acquisitions=["EPI",],
validate_for_template='{data_dir}/l1/{l1_dir}/sub-{subject}/ses-{session}/sub-{subject}_ses-{session}_acq-{acquisition}_task-{task}_cbv_tstat.nii.gz',
)
df_ = roi.per_session(substitutions_,
filename_template='{data_dir}/l1/{l1_dir}/sub-{subject}/ses-{session}/sub-{subject}_ses-{session}_acq-{acquisition}_task-{task}_cbv_tstat.nii.gz',
roi_mask=my_roi,
feature=[label],
atlas=atlas,
mapping=mapping,
)
df_['treatment']='Vehicle'
df=pd.concat([df_,df])
df=df.rename(columns={'session': 'Session',})
df.to_csv('~/ni_data/ofM.dr/bids/l1/{}/{}.csv'.format(workflow_name, label))
def dr_activity():
import pandas as pd
from behaviopy.plotting import qualitative_times
from samri.plotting import summary
from samri.report import roi
from samri.utilities import bids_substitution_iterator
from samri.fetch.local import roi_from_atlaslabel
workflow_name = 'composite'
substitutions = bids_substitution_iterator(
["ofM", "ofMaF", "ofMcF1", "ofMcF2", "ofMpF"],
['5691', "5689", "5690", "5700"],
[
"CogB",
],
"~/ni_data/ofM.dr/",
workflow_name,
acquisitions=[
"EPI",
],
check_file_format=
'{data_dir}/l1/{l1_dir}/sub-{subject}/ses-{session}/sub-{subject}_ses-{session}_acq-{acquisition}_trial-{trial}_cbv_tstat.nii.gz',
)
fit, anova, subjectdf, voxeldf = roi.per_session(
substitutions,
filename_template=
'{data_dir}/l1/{l1_dir}/sub-{subject}/ses-{session}/sub-{subject}_ses-{session}_acq-{acquisition}_trial-{trial}_cbv_tstat.nii.gz',
roi_mask="~/ni_data/templates/roi/DSURQEc_dr.nii.gz",
)
subjectdf['treatment'] = 'Fluoxetine'
substitutions_ = bids_substitution_iterator(
["ofM", "ofMaF", "ofMcF1", "ofMcF2", "ofMpF"],
["6262", "6255", "5694", "5706", '5704'],
[
"CogB",
],
"~/ni_data/ofM.dr/",
workflow_name,
acquisitions=[
"EPI",
],
check_file_format=
'{data_dir}/l1/{l1_dir}/sub-{subject}/ses-{session}/sub-{subject}_ses-{session}_acq-{acquisition}_trial-{trial}_cbv_tstat.nii.gz',
)
fit_, anova_, subjectdf_, voxeldf_ = roi.per_session(
substitutions_,
filename_template=
'{data_dir}/l1/{l1_dir}/sub-{subject}/ses-{session}/sub-{subject}_ses-{session}_acq-{acquisition}_trial-{trial}_cbv_tstat.nii.gz',
roi_mask="~/ni_data/templates/roi/DSURQEc_dr.nii.gz",
)
subjectdf_['treatment'] = 'Vehicle'
subjectdf = pd.concat([subjectdf_, subjectdf])
subjectdf = subjectdf.rename(columns={
'session': 'Session',
})
subjectdf.to_csv(
'~/ni_data/ofM.dr/l1/{}/dr_summary.csv'.format(workflow_name))
def label_connectivity(workflow_name='DSURQEc_drp', labels=['cortex']):
import pandas as pd
from samri.plotting import summary
from samri.report import roi
from samri.utilities import bids_substitution_iterator
from samri.fetch.local import roi_from_atlaslabel
mapping='/usr/share/mouse-brain-atlases/dsurqec_mapping.csv'
atlas='/usr/share/mouse-brain-atlases/dsurqec_40micron_labels.nii'
my_roi = roi_from_atlaslabel(atlas,
mapping=mapping,
label_names=labels,
)
substitutions = bids_substitution_iterator(
["ofM","ofMaF","ofMcF1","ofMcF2","ofMpF"],
['5691',"5689","5690","5700","6451","6460","6456","6461","6462"],
["CogB",],
"~/ni_data/ofM.dr/bids",
workflow_name,
acquisitions=["EPI",],
validate_for_template='{data_dir}/fc/{preprocessing_dir}/sub-{subject}/ses-{session}/func/sub-{subject}_ses-{session}_acq-{acquisition}_task-{task}_cbv_zstat.nii.gz',
)
df = roi.per_session(substitutions,
filename_template='{data_dir}/fc/{preprocessing_dir}/sub-{subject}/ses-{session}/func/sub-{subject}_ses-{session}_acq-{acquisition}_task-{task}_cbv_zstat.nii.gz',
roi_mask=my_roi,
feature=labels,
atlas=atlas,
mapping=mapping,
)
df['treatment']='Fluoxetine'
substitutions_ = bids_substitution_iterator(
["ofM","ofMaF","ofMcF1","ofMcF2","ofMpF"],
["6262","6255","5694","5706",'5704','6455','6459'],
["CogB",],
"~/ni_data/ofM.dr/bids",
workflow_name,
acquisitions=["EPI",],
validate_for_template='{data_dir}/fc/{preprocessing_dir}/sub-{subject}/ses-{session}/func/sub-{subject}_ses-{session}_acq-{acquisition}_task-{task}_cbv_zstat.nii.gz',
)
df_ = roi.per_session(substitutions_,
filename_template='{data_dir}/fc/{preprocessing_dir}/sub-{subject}/ses-{session}/func/sub-{subject}_ses-{session}_acq-{acquisition}_task-{task}_cbv_zstat.nii.gz',
roi_mask=my_roi,
feature=labels,
atlas=atlas,
mapping=mapping,
)
df_['treatment']='Vehicle'
df = pd.concat([df_,df])
df = df.rename(columns={'session': 'Session','t':'z'})
df.to_csv('~/ni_data/ofM.dr/bids/fc/{}/{}_summary.csv'.format(workflow_name,'-'.join(labels)))
def ctx_pattern_mask_drs_sfc():
import pandas as pd
from samri.plotting import summary
from samri.report import roi
from samri.utilities import bids_substitution_iterator
from samri.fetch.local import roi_from_atlaslabel
workflow_name = 'drs_seed'
my_roi = '~/ni_data/ofM.dr/l2/anova_ctx/anova_fstat.nii.gz'
my_roi = roi.from_img_threshold(my_roi, 2., save_as='~/ni_data/ofM.dr/fc/{}/ctx_pattern_mask.nii.gz'.format(workflow_name))
substitutions = bids_substitution_iterator(
["ofM","ofMaF","ofMcF1","ofMcF2","ofMpF"],
['5691',"5689","5690","5700"],
["CogB",],
"~/ni_data/ofM.dr/",
workflow_name,
acquisitions=["EPI",],
check_file_format='~/ni_data/ofM.dr/fc/{preprocessing_dir}/sub-{subject}/ses-{session}/func/sub-{subject}_ses-{session}_acq-{acquisition}_task-{task}_cbv_zstat.nii.gz',
)
subjectdf, voxeldf = roi.per_session(substitutions,
filename_template='~/ni_data/ofM.dr/fc/{preprocessing_dir}/sub-{subject}/ses-{session}/func/sub-{subject}_ses-{session}_acq-{acquisition}_task-{task}_cbv_zstat.nii.gz',
roi_mask=my_roi,
)
subjectdf['treatment']='Fluoxetine'
substitutions_ = bids_substitution_iterator(
["ofM","ofMaF","ofMcF1","ofMcF2","ofMpF"],
["6262","6255","5694","5706",'5704'],
["CogB",],
"~/ni_data/ofM.dr/",
workflow_name,
acquisitions=["EPI",],
check_file_format='~/ni_data/ofM.dr/fc/{preprocessing_dir}/sub-{subject}/ses-{session}/func/sub-{subject}_ses-{session}_acq-{acquisition}_task-{task}_cbv_zstat.nii.gz',
)
subjectdf_, voxeldf_ = roi.per_session(substitutions_,
filename_template='~/ni_data/ofM.dr/fc/{preprocessing_dir}/sub-{subject}/ses-{session}/func/sub-{subject}_ses-{session}_acq-{acquisition}_task-{task}_cbv_zstat.nii.gz',
roi_mask=my_roi,
)
subjectdf_['treatment']='Vehicle'
subjectdf=pd.concat([subjectdf_,subjectdf])
subjectdf=subjectdf.rename(columns={'session': 'Session','t':'z'})
subjectdf.to_csv('~/ni_data/ofM.dr/fc/{}/ctx_pattern_mask_summary.csv'.format(workflow_name))
def plot_roi_per_session(
l1_dir,
roi_mask,
color,
roi_mask_normalize="",
):
from samri.plotting import summary
from samri.report import roi
substitutions = bids_substitution_iterator(
["ofM", "ofM_aF", "ofM_cF1", "ofM_cF2", "ofM_pF"],
# ["5689","5690","5700"],
["6262", "6255", "5694", "5706", '5704'],
# ["4007","4011","4012","5689","5690","5691"],
# ["4009","4011","4012","5689","5690","5691"],
# ["4008","4009","4011","4012",],
["EPI_CBV_chr_longSOA"],
"~/ni_data/ofM.dr/",
"",
l1_dir=l1_dir,
)
if isinstance(roi, list) and not "/" in roi[0]:
roi = roi_from_atlaslabel(
"~/ni_data/templates/roi/DSURQEc_200micron_labels.nii",
mapping="~/ni_data/templates/roi/DSURQE_mapping.csv",
label_names=roi,
)
fit, anova, subjectdf, voxeldf = roi.per_session(
substitutions,
t_file_template=
"{data_dir}/l1/{l1_dir}/sub-{subject}/ses-{session}/sub-{subject}_ses-{session}_trial-{trial}_tstat.nii.gz",
roi_mask=roi_mask,
roi_mask_normalize=roi_mask_normalize,
)
summary.plot_roi_per_session(subjectdf,
voxeldf,
legend_loc=2,
figure="per-participant",
color=color,
save_as="~/test.png")
print(anova)
def drs_activity(
roi,
atlas='/usr/share/mouse-brain-templates/dsurqec_40micron_labels.nii',
mapping='/usr/share/mouse-brain-templates/dsurqe_labels.csv',
):
"""
TODO : make more generalizable, too many hardcoded values
TODO : Make more elegant, atlas/split could be (partly) relegated to masking function instead of being done here.
Create a DataFrame containing the per-session per-subject mean values for an autogenerated ROI based on the given label.
Other parameter customizations are hard-coded below.
"""
import pandas as pd
from samri.report import roi
from samri.utilities import bids_substitution_iterator
from samri.fetch.local import roi_from_atlaslabel
from os.path import basename, splitext
if mapping and atlas:
mapping = path.abspath(path.expanduser(mapping))
atlas = path.abspath(path.expanduser(atlas))
my_roi = roi_from_atlaslabel(
atlas,
mapping=mapping,
label_names=[roi],
)
roi_name = roi
else:
roi = path.abspath(path.expanduser(roi))
roi_name = splitext(basename(roi))[0]
if roi_name[-4:] == '.nii':
roi_name = roi_name[:-4]
source_workflow = 'generic'
substitutions = bids_substitution_iterator(
["ofM", "ofMaF", "ofMcF1", "ofMcF2", "ofMpF"],
[
'5691', "5689", "5690", "5700", "6451", "6460", "6456", "6461",
"6462"
],
[
"CogB",
],
"~/ni_data/ofM.dr",
source_workflow,
acquisitions=[
"EPI",
],
validate_for_template=
'{data_dir}/l1/{l1_dir}/sub-{subject}/ses-{session}/sub-{subject}_ses-{session}_acq-{acquisition}_task-{task}_cbv_tstat.nii.gz',
)
if mapping and atlas:
df = roi.per_session(
substitutions,
filename_template=
'{data_dir}/l1/{l1_dir}/sub-{subject}/ses-{session}/sub-{subject}_ses-{session}_acq-{acquisition}_task-{task}_cbv_tstat.nii.gz',
roi_mask=my_roi,
feature=[roi],
atlas=atlas,
mapping=mapping,
)
else:
df = roi.per_session(
substitutions,
filename_template=
'{data_dir}/l1/{l1_dir}/sub-{subject}/ses-{session}/sub-{subject}_ses-{session}_task-{task}_acq-{acquisition}_cbv_tstat.nii.gz',
roi_mask=roi,
)
df['treatment'] = 'Fluoxetine'
substitutions_ = bids_substitution_iterator(
["ofM", "ofMaF", "ofMcF1", "ofMcF2", "ofMpF"],
["6262", "6255", "5694", "5706", '5704', '6455', '6459'],
[
"CogB",
],
"~/ni_data/ofM.dr",
source_workflow,
acquisitions=[
"EPI",
],
validate_for_template=
'{data_dir}/l1/{l1_dir}/sub-{subject}/ses-{session}/sub-{subject}_ses-{session}_acq-{acquisition}_task-{task}_cbv_tstat.nii.gz',
)
if mapping and atlas:
df_ = roi.per_session(
substitutions_,
filename_template=
'{data_dir}/l1/{l1_dir}/sub-{subject}/ses-{session}/sub-{subject}_ses-{session}_acq-{acquisition}_task-{task}_cbv_tstat.nii.gz',
roi_mask=my_roi,
feature=[roi],
atlas=atlas,
mapping=mapping,
)
else:
df_ = roi.per_session(
substitutions_,
filename_template=
'{data_dir}/l1/{l1_dir}/sub-{subject}/ses-{session}/sub-{subject}_ses-{session}_task-{task}_acq-{acquisition}_cbv_tstat.nii.gz',
roi_mask=roi,
)
df_['treatment'] = 'Vehicle'
df = pd.concat([df_, df])
df = df.rename(columns={
'session': 'Session',
})
df.to_csv('~/ni_data/ofM.dr/l1/{}/{}.csv'.format(source_workflow,
roi_name))
def roi_activity(roi_mask="~/ni_data/templates/roi/DSURQEc_drp.nii.gz"):
"""
Create a DataFrame containing the per-session per-subject mean values for the specified ROI.
Other parameter customizations are hard-coded below.
"""
import pandas as pd
from samri.plotting import summary
from samri.report import roi
from samri.utilities import bids_substitution_iterator
from samri.fetch.local import roi_from_atlaslabel
from os.path import basename, splitext
workflow_name = 'generic'
substitutions = bids_substitution_iterator(
["ofM", "ofMaF", "ofMcF1", "ofMcF2", "ofMpF"],
#["5689","5690","6456","6461"],
[
'5691', "5689", "5690", "5700", "6451", "6460", "6456", "6461",
"6462"
],
#['5691',"5689","5690","5700",],
[
"CogB",
],
"~/ni_data/ofM.dr/bids/",
workflow_name,
acquisitions=[
"EPI",
],
validate_for_template=
'{data_dir}/l1/{l1_dir}/sub-{subject}/ses-{session}/sub-{subject}_ses-{session}_task-{task}_acq-{acquisition}_cbv_tstat.nii.gz',
)
df = roi.per_session(
substitutions,
filename_template=
'{data_dir}/l1/{l1_dir}/sub-{subject}/ses-{session}/sub-{subject}_ses-{session}_task-{task}_acq-{acquisition}_cbv_tstat.nii.gz',
roi_mask=roi_mask,
)
df['treatment'] = 'Fluoxetine'
substitutions_ = bids_substitution_iterator(
["ofM", "ofMaF", "ofMcF1", "ofMcF2", "ofMpF"],
#["5694","5706",'5704','6455','6459','5794'],
["6262", "6255", "5694", "5706", '5704', '6455', '6459'],
#["6262","6255","5694","5706",'5704',],
[
"CogB",
],
"~/ni_data/ofM.dr/bids/",
workflow_name,
acquisitions=[
"EPI",
],
validate_for_template=
'{data_dir}/l1/{l1_dir}/sub-{subject}/ses-{session}/sub-{subject}_ses-{session}_task-{task}_acq-{acquisition}_cbv_tstat.nii.gz',
)
df_ = roi.per_session(
substitutions_,
filename_template=
'{data_dir}/l1/{l1_dir}/sub-{subject}/ses-{session}/sub-{subject}_ses-{session}_task-{task}_acq-{acquisition}_cbv_tstat.nii.gz',
roi_mask=roi_mask,
)
df_['treatment'] = 'Vehicle'
substitutions__ = bids_substitution_iterator(
["ofM"],
#["5694","5706",'5704','6455','6459','5794'],
[
"6530", "6532", "6542", "6548", '6549', '6552', '6553', '6556',
'6557'
],
#["6262","6255","56","5706",'5704',],
[
"CogB",
],
"~/ni_data/ofM.dr/bids/",
workflow_name,
acquisitions=[
"EPI",
],
validate_for_template=
'{data_dir}/l1/{l1_dir}/sub-{subject}/ses-{session}/sub-{subject}_ses-{session}_task-{task}_acq-{acquisition}_cbv_tstat.nii.gz',
)
df__ = roi.per_session(
substitutions__,
filename_template=
'{data_dir}/l1/{l1_dir}/sub-{subject}/ses-{session}/sub-{subject}_ses-{session}_task-{task}_acq-{acquisition}_cbv_tstat.nii.gz',
roi_mask=roi_mask,
)
df__['treatment'] = 'New'
df = pd.concat([df__, df_, df])
df = df.rename(columns={
'session': 'Session',
})
roi_name = splitext(basename(roi_mask))[0]
if roi_name[-4:] == '.nii':
roi_name = roi_name[:-4]
df.to_csv('~/ni_data/ofM.dr/bids/l1/{}/{}.csv'.format(
workflow_name, roi_name))
def ctx_drs_connectivity():
import pandas as pd
from behaviopy.plotting import qualitative_times
from samri.plotting import summary
from samri.report import roi
from samri.utilities import bids_substitution_iterator
from samri.fetch.local import roi_from_atlaslabel
workflow_name = 'drs_seed'
my_roi = roi_from_atlaslabel(
"~/ni_data/templates/roi/DSURQEc_200micron_labels.nii",
mapping="~/ni_data/templates/roi/DSURQE_mapping.csv",
label_names=["cortex"],
)
substitutions = bids_substitution_iterator(
["ofM", "ofMaF", "ofMcF1", "ofMcF2", "ofMpF"],
['5691', "5689", "5690", "5700"],
[
"CogB",
],
"~/ni_data/ofM.dr/",
workflow_name,
acquisitions=[
"EPI",
],
check_file_format=
'~/ni_data/ofM.dr/fc/{preprocessing_dir}/sub-{subject}/ses-{session}/func/sub-{subject}_ses-{session}_acq-{acquisition}_trial-{trial}_cbv_zstat.nii.gz',
)
fit, anova, subjectdf, voxeldf = roi.per_session(
substitutions,
filename_template=
'~/ni_data/ofM.dr/fc/{preprocessing_dir}/sub-{subject}/ses-{session}/func/sub-{subject}_ses-{session}_acq-{acquisition}_trial-{trial}_cbv_zstat.nii.gz',
roi_mask=my_roi,
)
subjectdf['treatment'] = 'Fluoxetine'
substitutions_ = bids_substitution_iterator(
["ofM", "ofMaF", "ofMcF1", "ofMcF2", "ofMpF"],
["6262", "6255", "5694", "5706", '5704'],
[
"CogB",
],
"~/ni_data/ofM.dr/",
workflow_name,
acquisitions=[
"EPI",
],
check_file_format=
'~/ni_data/ofM.dr/fc/{preprocessing_dir}/sub-{subject}/ses-{session}/func/sub-{subject}_ses-{session}_acq-{acquisition}_trial-{trial}_cbv_zstat.nii.gz',
)
fit_, anova_, subjectdf_, voxeldf_ = roi.per_session(
substitutions_,
filename_template=
'~/ni_data/ofM.dr/fc/{preprocessing_dir}/sub-{subject}/ses-{session}/func/sub-{subject}_ses-{session}_acq-{acquisition}_trial-{trial}_cbv_zstat.nii.gz',
roi_mask=my_roi,
)
subjectdf_['treatment'] = 'Vehicle'
subjectdf = pd.concat([subjectdf_, subjectdf])
subjectdf = subjectdf.rename(columns={'session': 'Session', 't': 'z'})
subjectdf.to_csv(
'~/ni_data/ofM.dr/fc/{}/ctx_summary.csv'.format(workflow_name))
def drs_activity(roi,
atlas='/usr/share/mouse-brain-atlases/dsurqec_40micron_labels.nii',
mapping='/usr/share/mouse-brain-atlases/dsurqe_labels.csv',
):
"""
TODO : make more generalizable, too many hardcoded values
TODO : Make more elegant, atlas/split could be (partly) relegated to masking function instead of being done here.
Create a DataFrame containing the per-session per-subject mean values for an autogenerated ROI based on the given label.
Other parameter customizations are hard-coded below.
"""
import pandas as pd
from samri.plotting import summary
from samri.report import roi
from samri.utilities import bids_substitution_iterator
from samri.fetch.local import roi_from_atlaslabel
from os.path import basename, splitext
if mapping and atlas:
mapping = path.abspath(path.expanduser(mapping))
atlas = path.abspath(path.expanduser(atlas))
my_roi = roi_from_atlaslabel(atlas,
mapping=mapping,
label_names=[roi],
)
roi_name = roi
else:
roi = path.abspath(path.expanduser(roi))
roi_name = splitext(basename(roi))[0]
if roi_name[-4:] == '.nii':
roi_name = roi_name[:-4]
source_workflow = 'generic'
substitutions = bids_substitution_iterator(
["ofM","ofMaF","ofMcF1","ofMcF2","ofMpF"],
['5691',"5689","5690","5700","6451","6460","6456","6461","6462"],
["CogB",],
"~/ni_data/ofM.dr",
source_workflow,
acquisitions=["EPI",],
validate_for_template='{data_dir}/l1/{l1_dir}/sub-{subject}/ses-{session}/sub-{subject}_ses-{session}_acq-{acquisition}_task-{task}_cbv_tstat.nii.gz',
)
if mapping and atlas:
df = roi.per_session(substitutions,
filename_template='{data_dir}/l1/{l1_dir}/sub-{subject}/ses-{session}/sub-{subject}_ses-{session}_acq-{acquisition}_task-{task}_cbv_tstat.nii.gz',
roi_mask=my_roi,
feature=[roi],
atlas=atlas,
mapping=mapping,
)
else:
df = roi.per_session(substitutions,
filename_template='{data_dir}/l1/{l1_dir}/sub-{subject}/ses-{session}/sub-{subject}_ses-{session}_task-{task}_acq-{acquisition}_cbv_tstat.nii.gz',
roi_mask=roi,
)
df['treatment']='Fluoxetine'
substitutions_ = bids_substitution_iterator(
["ofM","ofMaF","ofMcF1","ofMcF2","ofMpF"],
["6262","6255","5694","5706",'5704','6455','6459'],
["CogB",],
"~/ni_data/ofM.dr",
source_workflow,
acquisitions=["EPI",],
validate_for_template='{data_dir}/l1/{l1_dir}/sub-{subject}/ses-{session}/sub-{subject}_ses-{session}_acq-{acquisition}_task-{task}_cbv_tstat.nii.gz',
)
if mapping and atlas:
df_ = roi.per_session(substitutions_,
filename_template='{data_dir}/l1/{l1_dir}/sub-{subject}/ses-{session}/sub-{subject}_ses-{session}_acq-{acquisition}_task-{task}_cbv_tstat.nii.gz',
roi_mask=my_roi,
feature=[roi],
atlas=atlas,
mapping=mapping,
)
else:
df_ = roi.per_session(substitutions_,
filename_template='{data_dir}/l1/{l1_dir}/sub-{subject}/ses-{session}/sub-{subject}_ses-{session}_task-{task}_acq-{acquisition}_cbv_tstat.nii.gz',
roi_mask=roi,
)
df_['treatment']='Vehicle'
df=pd.concat([df_,df])
df=df.rename(columns={'session': 'Session',})
df.to_csv('~/ni_data/ofM.dr/l1/{}/{}.csv'.format(source_workflow, roi_name))
def roi_activity(roi_mask="~/ni_data/templates/roi/DSURQEc_drp.nii.gz"):
"""
Create a DataFrame containing the per-session per-subject mean values for the specified ROI.
Other parameter customizations are hard-coded below.
"""
import pandas as pd
from samri.plotting import summary
from samri.report import roi
from samri.utilities import bids_substitution_iterator
from samri.fetch.local import roi_from_atlaslabel
from os.path import basename, splitext
workflow_name = 'generic'
substitutions = bids_substitution_iterator(
["ofM","ofMaF","ofMcF1","ofMcF2","ofMpF"],
#["5689","5690","6456","6461"],
['5691',"5689","5690","5700","6451","6460","6456","6461","6462"],
#['5691',"5689","5690","5700",],
["CogB",],
"~/ni_data/ofM.dr/bids/",
workflow_name,
acquisitions=["EPI",],
validate_for_template='{data_dir}/l1/{l1_dir}/sub-{subject}/ses-{session}/sub-{subject}_ses-{session}_task-{task}_acq-{acquisition}_cbv_tstat.nii.gz',
)
df = roi.per_session(substitutions,
filename_template='{data_dir}/l1/{l1_dir}/sub-{subject}/ses-{session}/sub-{subject}_ses-{session}_task-{task}_acq-{acquisition}_cbv_tstat.nii.gz',
roi_mask=roi_mask,
)
df['treatment'] = 'Fluoxetine'
substitutions_ = bids_substitution_iterator(
["ofM","ofMaF","ofMcF1","ofMcF2","ofMpF"],
#["5694","5706",'5704','6455','6459','5794'],
["6262","6255","5694","5706",'5704','6455','6459'],
#["6262","6255","5694","5706",'5704',],
["CogB",],
"~/ni_data/ofM.dr/bids/",
workflow_name,
acquisitions=["EPI",],
validate_for_template='{data_dir}/l1/{l1_dir}/sub-{subject}/ses-{session}/sub-{subject}_ses-{session}_task-{task}_acq-{acquisition}_cbv_tstat.nii.gz',
)
df_ = roi.per_session(substitutions_,
filename_template='{data_dir}/l1/{l1_dir}/sub-{subject}/ses-{session}/sub-{subject}_ses-{session}_task-{task}_acq-{acquisition}_cbv_tstat.nii.gz',
roi_mask=roi_mask,
)
df_['treatment'] = 'Vehicle'
substitutions__ = bids_substitution_iterator(
["ofM"],
#["5694","5706",'5704','6455','6459','5794'],
["6530","6532","6542","6548",'6549','6552','6553','6556','6557'],
#["6262","6255","56","5706",'5704',],
["CogB",],
"~/ni_data/ofM.dr/bids/",
workflow_name,
acquisitions=["EPI",],
validate_for_template='{data_dir}/l1/{l1_dir}/sub-{subject}/ses-{session}/sub-{subject}_ses-{session}_task-{task}_acq-{acquisition}_cbv_tstat.nii.gz',
)
df__ = roi.per_session(substitutions__,
filename_template='{data_dir}/l1/{l1_dir}/sub-{subject}/ses-{session}/sub-{subject}_ses-{session}_task-{task}_acq-{acquisition}_cbv_tstat.nii.gz',
roi_mask=roi_mask,
)
df__['treatment'] = 'New'
df = pd.concat([df__,df_,df])
df = df.rename(columns={'session': 'Session',})
roi_name = splitext(basename(roi_mask))[0]
if roi_name[-4:] == '.nii':
roi_name = roi_name[:-4]
df.to_csv('~/ni_data/ofM.dr/bids/l1/{}/{}.csv'.format(workflow_name, roi_name))
