def warn_redirect(message, category, filename, lineno, file=None, line=None):
from mriqc import logging
LOG = logging.getLogger('mriqc.warnings')
if category not in cached_warnings:
LOG.debug('captured warning (%s): %s', category, message)
cached_warnings.append(category)
def individual_html(in_iqms, in_plots=None, exclude_index=0, wf_details=None):
import os.path as op #pylint: disable=W0404
import datetime
from json import load
from mriqc import __version__ as ver
from mriqc.reports.utils import iqms2html, anat_flags, read_report_snippet
from mriqc.data import IndividualTemplate
from mriqc import logging
from io import open #pylint: disable=W0622
report_log = logging.getLogger('mriqc.report')
report_log.setLevel(logging.INFO)
with open(in_iqms) as jsonfile:
iqms_dict = load(jsonfile)
# Now, the in_iqms file should be correctly named
fname = op.splitext(op.basename(in_iqms))[0]
out_file = op.abspath(fname + '.html')
if in_plots is None:
in_plots = []
if wf_details is None:
wf_details = []
# Extract and prune metadata
metadata = iqms_dict.pop('metadata', None)
qctype = metadata.pop('qc_type', None)
file_id = [
metadata.pop(k, None) for k in
['subject_id', 'session_id', 'task_id', 'acq_id', 'rec_id', 'run_id']
]
file_id = [comp for comp in file_id if comp is not None]
# Deal with special IQMs
if qctype.startswith('anat'):
qctype = 'anatomical'
flags = anat_flags(iqms_dict)
if flags:
wf_details.append(flags)
elif qctype.startswith('func'):
qctype = 'functional'
else:
RuntimeError('Unknown QC type "%s"' % qctype)
config = {
'qctype': qctype,
'sub_id': '_'.join(file_id),
'timestamp': datetime.datetime.now().strftime("%Y-%m-%d, %H:%M"),
'version': ver,
'imparams': iqms2html(iqms_dict, 'iqms-table'),
'svg_files': [read_report_snippet(pfile) for pfile in in_plots],
'exclude_index': exclude_index,
'workflow_details': wf_details,
'metadata': iqms2html(metadata, 'metadata-table'),
}
if config['metadata'] is None:
config['workflow_details'].append(
'<span class="warning">File has no metadata</span> '
'<span>(sidecar JSON file missing or empty)</span>')
tpl = IndividualTemplate()
tpl.generate_conf(config, out_file)
report_log.info('Generated individual log (%s)', out_file)
return out_file
def main():
"""Entry point"""
import yaml
from io import open
from argparse import ArgumentParser
from argparse import RawTextHelpFormatter
from pkg_resources import resource_filename as pkgrf
from mriqc.classifier.cv import CVHelper
from mriqc import logging, LOG_FORMAT
warnings.showwarning = warn_redirect
parser = ArgumentParser(
description='MRIQC model selection and held-out evaluation',
formatter_class=RawTextHelpFormatter)
g_clf = parser.add_mutually_exclusive_group()
g_clf.add_argument('--train',
nargs=2,
help='training data tables, X and Y')
g_clf.add_argument('--load-classifier',
nargs="?",
default=pkgrf('mriqc', 'data/rfc-nzs-full-1.0.pklz'),
help='load pickled classifier in')
parser.add_argument('--test-data', help='test data')
parser.add_argument('--test-labels', help='test labels')
parser.add_argument('-X',
'--evaluation-data',
help='classify this CSV table of IQMs')
g_input = parser.add_argument_group('Inputs')
g_input.add_argument('-P',
'--parameters',
action='store',
default=pkgrf('mriqc',
'data/classifier_settings.yml'))
g_input.add_argument('--save-classifier',
action='store',
help='write pickled classifier out')
g_input.add_argument('--log-file',
action='store',
help='write log to this file')
g_input.add_argument(
'--log-level',
action='store',
default='INFO',
choices=['CRITICAL', 'ERROR', 'WARN', 'INFO', 'DEBUG'])
g_input.add_argument('--njobs',
action='store',
default=-1,
type=int,
help='number of jobs')
g_input.add_argument(
'-o',
'--output',
action='store',
default='predicted_qa.csv',
help='file containing the labels assigned by the classifier')
opts = parser.parse_args()
if opts.log_file is not None:
filelogger = logging.getLogger()
fhl = logging.FileHandler(opts.log_file)
fhl.setFormatter(fmt=logging.Formatter(LOG_FORMAT))
filelogger.addHandler(fhl)
filelogger.setLevel(opts.log_level)
parameters = None
if opts.parameters is not None:
with open(opts.parameters) as paramfile:
parameters = yaml.load(paramfile)
train = [False] if opts.train is None else [
val is not None for val in opts.train
]
if all(train):
# Initialize model selection helper
cvhelper = CVHelper(X=opts.train[0],
Y=opts.train[1],
n_jobs=opts.njobs,
param=parameters)
# Perform model selection before setting held-out data, for hygene
cvhelper.fit()
# Pickle if required
if opts.save_classifier:
cvhelper.save(opts.save_classifier)
elif any(train):
raise RuntimeError('Both --train-data and --train-labels must be set')
else:
cvhelper = CVHelper(load_clf=opts.load_classifier,
n_jobs=opts.njobs,
rate_label='rate')
if opts.test_data and opts.test_labels:
# Set held-out data
cvhelper.setXtest(opts.test_data, opts.test_labels)
# Evaluate
print('roc_auc=%f, accuracy=%f' %
(cvhelper.evaluate(scoring='roc_auc'), cvhelper.evaluate()))
if opts.evaluation_data:
cvhelper.predict_dataset(opts.evaluation_data, out_file=opts.output)
def individual_html(in_iqms, in_plots=None):
from os import path as op
import datetime
from json import load
from mriqc import logging, __version__ as ver
from mriqc.utils.misc import BIDS_COMP
from mriqc.reports import REPORT_TITLES
from mriqc.reports.utils import iqms2html, read_report_snippet
from mriqc.data import IndividualTemplate
report_log = logging.getLogger('mriqc.report')
def _get_details(in_iqms, modality):
in_prov = in_iqms.pop('provenance', {})
warn_dict = in_prov.pop('warnings', None)
sett_dict = in_prov.pop('settings', None)
wf_details = []
if modality == 'bold':
bold_exclude_index = in_iqms.get('dumb_trs')
if bold_exclude_index is None:
report_log.warning(
'Building bold report: no exclude index was found')
elif bold_exclude_index > 0:
msg = """\
<span class="problematic">Non-steady state (strong T1 contrast) has been detected in the \
first {} volumes</span>. They were excluded before generating any QC measures and plots."""
wf_details.append(msg.format(bold_exclude_index))
hmc_fsl = sett_dict.pop('hmc_fsl')
if hmc_fsl is not None:
msg = 'Framewise Displacement was computed using '
if hmc_fsl:
msg += 'FSL <code>mcflirt</code>'
else:
msg += 'AFNI <code>3dvolreg</code>'
wf_details.append(msg)
fd_thres = sett_dict.pop('fd_thres')
if fd_thres is not None:
wf_details.append(
'Framewise Displacement threshold was defined at %f mm' %
fd_thres)
elif modality in ('T1w', 'T2w'):
if warn_dict.pop('small_air_mask', False):
wf_details.append(
'<span class="problematic">Detected hat mask was too small</span>'
)
if warn_dict.pop('large_rot_frame', False):
wf_details.append(
'<span class="problematic">Detected a zero-filled frame, has the original '
'image been rotated?</span>')
return in_prov, wf_details
with open(in_iqms) as jsonfile:
iqms_dict = load(jsonfile)
# Now, the in_iqms file should be correctly named
fname = op.splitext(op.basename(in_iqms))[0]
out_file = op.abspath(fname + '.html')
# Extract and prune metadata
metadata = iqms_dict.pop('bids_meta', None)
mod = metadata.pop('modality', None)
prov, wf_details = _get_details(iqms_dict, mod)
file_id = [metadata.pop(k, None) for k in list(BIDS_COMP.keys())]
file_id = [comp for comp in file_id if comp is not None]
if in_plots is None:
in_plots = []
else:
if any(('melodic_reportlet' in k for k in in_plots)):
REPORT_TITLES['bold'].insert(3, 'ICA components')
in_plots = [(REPORT_TITLES[mod][i], read_report_snippet(v))
for i, v in enumerate(in_plots)]
pred_qa = None # metadata.pop('mriqc_pred', None)
config = {
'modality': mod,
'sub_id': '_'.join(file_id),
'timestamp': datetime.datetime.now().strftime("%Y-%m-%d, %H:%M"),
'version': ver,
'imparams': iqms2html(iqms_dict, 'iqms-table'),
'svg_files': in_plots,
'workflow_details': wf_details,
'provenance': iqms2html(prov, 'provenance-table'),
'metadata': iqms2html(metadata, 'metadata-table'),
'pred_qa': pred_qa
}
if config['metadata'] is None:
config['workflow_details'].append(
'<span class="warning">File has no metadata</span> '
'<span>(sidecar JSON file missing or empty)</span>')
tpl = IndividualTemplate()
tpl.generate_conf(config, out_file)
report_log.info('Generated individual log (%s)', out_file)
return out_file
def individual_html(in_iqms, in_plots=None):
import os.path as op #pylint: disable=W0404
import datetime
from json import load
from mriqc import logging, __version__ as ver
from mriqc.utils.misc import BIDS_COMP
from mriqc.reports.utils import iqms2html, read_report_snippet
from mriqc.data import IndividualTemplate
from io import open #pylint: disable=W0622
report_log = logging.getLogger('mriqc.report')
def _get_details(in_iqms, modality):
in_prov = in_iqms.pop('provenance', {})
warn_dict = in_prov.pop('warnings', None)
sett_dict = in_prov.pop('settings', None)
wf_details = []
if modality == 'bold':
bold_exclude_index = in_iqms.get('dumb_trs')
if bold_exclude_index is None:
report_log.warning('Building bold report: no exclude index was found')
elif bold_exclude_index > 0:
msg = """\
<span class="problematic">Non-steady state (strong T1 contrast) has been detected in the \
first {} volumes</span>. They were excluded before generating any QC measures and plots."""
wf_details.append(msg.format(bold_exclude_index))
hmc_fsl = sett_dict.pop('hmc_fsl')
if hmc_fsl is not None:
msg = 'Framewise Displacement was computed using '
if hmc_fsl:
msg += 'FSL <code>mcflirt</code>'
else:
msg += 'AFNI <code>3dvolreg</code>'
wf_details.append(msg)
fd_thres = sett_dict.pop('fd_thres')
if fd_thres is not None:
wf_details.append(
'Framewise Displacement threshold was defined at %f mm' % fd_thres)
elif modality in ('T1w', 'T2w'):
if warn_dict.pop('small_air_mask', False):
wf_details.append(
'<span class="problematic">Detected hat mask was too small</span>')
if warn_dict.pop('large_rot_frame', False):
wf_details.append(
'<span class="problematic">Detected a zero-filled frame, has the original '
'image been rotated?</span>')
return in_prov, wf_details
with open(in_iqms) as jsonfile:
iqms_dict = load(jsonfile)
# Now, the in_iqms file should be correctly named
fname = op.splitext(op.basename(in_iqms))[0]
out_file = op.abspath(fname + '.html')
if in_plots is None:
in_plots = []
# Extract and prune metadata
metadata = iqms_dict.pop('bids_meta', None)
mod = metadata.pop('modality', None)
prov, wf_details = _get_details(iqms_dict, mod)
file_id = [metadata.pop(k, None)
for k in list(BIDS_COMP.keys())]
file_id = [comp for comp in file_id if comp is not None]
pred_qa = None #metadata.pop('mriqc_pred', None)
config = {
'modality': mod,
'sub_id': '_'.join(file_id),
'timestamp': datetime.datetime.now().strftime("%Y-%m-%d, %H:%M"),
'version': ver,
'imparams': iqms2html(iqms_dict, 'iqms-table'),
'svg_files': [read_report_snippet(pfile) for pfile in in_plots],
'workflow_details': wf_details,
'provenance': iqms2html(prov, 'provenance-table'),
'metadata': iqms2html(metadata, 'metadata-table'),
'pred_qa': pred_qa
}
if config['metadata'] is None:
config['workflow_details'].append(
'<span class="warning">File has no metadata</span> '
'<span>(sidecar JSON file missing or empty)</span>')
tpl = IndividualTemplate()
tpl.generate_conf(config, out_file)
report_log.info('Generated individual log (%s)', out_file)
return out_file
def individual_html(in_iqms, in_plots=None, api_id=None):
from pathlib import Path
import datetime
from json import load
from mriqc import logging, __version__ as ver
from mriqc.utils.misc import BIDS_COMP
from mriqc.reports import REPORT_TITLES
from mriqc.reports.utils import iqms2html, read_report_snippet
from mriqc.data import IndividualTemplate
report_log = logging.getLogger('mriqc.report')
def _get_details(in_iqms, modality):
in_prov = in_iqms.pop('provenance', {})
warn_dict = in_prov.pop('warnings', None)
sett_dict = in_prov.pop('settings', None)
wf_details = []
if modality == 'bold':
bold_exclude_index = in_iqms.get('dumb_trs')
if bold_exclude_index is None:
report_log.warning('Building bold report: no exclude index was found')
elif bold_exclude_index > 0:
msg = """\
<span class="problematic">Non-steady state (strong T1 contrast) has been detected in the \
first {} volumes</span>. They were excluded before generating any QC measures and plots."""
wf_details.append(msg.format(bold_exclude_index))
hmc_fsl = sett_dict.pop('hmc_fsl')
if hmc_fsl is not None:
msg = 'Framewise Displacement was computed using '
if hmc_fsl:
msg += 'FSL <code>mcflirt</code>'
else:
msg += 'AFNI <code>3dvolreg</code>'
wf_details.append(msg)
fd_thres = sett_dict.pop('fd_thres')
if fd_thres is not None:
wf_details.append(
'Framewise Displacement threshold was defined at %f mm' % fd_thres)
elif modality in ('T1w', 'T2w'):
if warn_dict.pop('small_air_mask', False):
wf_details.append(
'<span class="problematic">Detected hat mask was too small</span>')
if warn_dict.pop('large_rot_frame', False):
wf_details.append(
'<span class="problematic">Detected a zero-filled frame, has the original '
'image been rotated?</span>')
return in_prov, wf_details, sett_dict
in_iqms = Path(in_iqms)
with in_iqms.open() as jsonfile:
iqms_dict = load(jsonfile)
# Now, the in_iqms file should be correctly named
out_file = str(Path(in_iqms.with_suffix(".html").name).resolve())
# Extract and prune metadata
metadata = iqms_dict.pop('bids_meta', None)
mod = metadata.pop('modality', None)
prov, wf_details, _ = _get_details(iqms_dict, mod)
file_id = [metadata.pop(k, None)
for k in list(BIDS_COMP.keys())]
file_id = [comp for comp in file_id if comp is not None]
if in_plots is None:
in_plots = []
else:
if any(('melodic_reportlet' in k for k in in_plots)):
REPORT_TITLES['bold'].insert(3, ('ICA components', 'ica-comps'))
in_plots = [(REPORT_TITLES[mod][i] + (read_report_snippet(v), ))
for i, v in enumerate(in_plots)]
pred_qa = None # metadata.pop('mriqc_pred', None)
config = {
'modality': mod,
'dataset': metadata.pop('dataset', None),
'bids_name': in_iqms.with_suffix("").name,
'timestamp': datetime.datetime.now().strftime("%Y-%m-%d, %H:%M"),
'version': ver,
'imparams': iqms2html(iqms_dict, 'iqms-table'),
'svg_files': in_plots,
'workflow_details': wf_details,
'webapi_url': prov.pop('webapi_url'),
'webapi_port': prov.pop('webapi_port'),
'provenance': iqms2html(prov, 'provenance-table'),
'md5sum': prov['md5sum'],
'metadata': iqms2html(metadata, 'metadata-table'),
'pred_qa': pred_qa
}
if config['metadata'] is None:
config['workflow_details'].append(
'<span class="warning">File has no metadata</span> '
'<span>(sidecar JSON file missing or empty)</span>')
tpl = IndividualTemplate()
tpl.generate_conf(config, out_file)
report_log.info('Generated individual log (%s)', out_file)
return out_file
# # @Author: oesteban # @Date: 2016-01-05 11:33:39 # @Email: [email protected] # @Last modified by: oesteban """ Encapsulates report generation functions """ from __future__ import print_function, division, absolute_import, unicode_literals from sys import version_info import pandas as pd from builtins import zip, object, str # pylint: disable=W0622 from mriqc import logging from mriqc.utils.misc import BIDS_COMPONENTS MRIQC_REPORT_LOG = logging.getLogger('mriqc.report') MRIQC_REPORT_LOG.setLevel(logging.INFO) def gen_html(csv_file, qctype, csv_failed=None, out_file=None): import os.path as op from os import remove from shutil import copy import datetime from pkg_resources import resource_filename as pkgrf from mriqc import __version__ as ver from mriqc.data import GroupTemplate from mriqc.utils.misc import check_folder if version_info[0] > 2: from io import StringIO as TextIO else:
def main():
"""Entry point"""
import yaml
from io import open
from argparse import ArgumentParser
from argparse import RawTextHelpFormatter
from pkg_resources import resource_filename as pkgrf
from mriqc.classifier.cv import NestedCVHelper
from mriqc import logging, LOG_FORMAT
warnings.showwarning = warn_redirect
parser = ArgumentParser(
description='MRIQC Nested cross-validation evaluation',
formatter_class=RawTextHelpFormatter)
parser.add_argument('training_data', help='input data')
parser.add_argument('training_labels', help='input data')
g_input = parser.add_argument_group('Inputs')
g_input.add_argument('-P',
'--parameters',
action='store',
default=pkgrf('mriqc', 'data/grid_nested_cv.yml'))
g_input.add_argument('--cv-inner',
action='store',
default=10,
help='inner loop of cross-validation')
g_input.add_argument('--cv-outer',
action='store',
default='loso',
help='outer loop of cross-validation')
g_input.add_argument('--log-file',
action='store',
help='write log to this file')
g_input.add_argument(
'--log-level',
action='store',
default='INFO',
choices=['CRITICAL', 'ERROR', 'WARN', 'INFO', 'DEBUG'])
g_input.add_argument('-o',
'--output-file',
action='store',
default='cv_inner_loop.csv',
help='the output table with cross validated scores')
g_input.add_argument('-O',
'--output-outer-cv',
action='store',
default='cv_outer_loop.csv',
help='the output table with cross validated scores')
g_input.add_argument('--njobs',
action='store',
default=-1,
type=int,
help='number of jobs')
g_input.add_argument('--task-id', action='store')
opts = parser.parse_args()
logger = logging.getLogger()
if opts.log_file is not None:
fhl = logging.FileHandler(opts.log_file)
fhl.setFormatter(fmt=logging.Formatter(LOG_FORMAT))
logger.addHandler(fhl)
logger.setLevel(opts.log_level)
parameters = None
if opts.parameters is not None:
with open(opts.parameters) as paramfile:
parameters = yaml.load(paramfile)
cvhelper = NestedCVHelper(opts.training_data,
opts.training_labels,
n_jobs=opts.njobs,
param=parameters,
task_id=opts.task_id)
cvhelper.cv_inner = read_cv(opts.cv_inner)
cvhelper.cv_outer = read_cv(opts.cv_outer)
# Run inner loop before setting held-out data, for hygene
cvhelper.fit()
with open(opts.output_file, 'a' if PY3 else 'ab') as outfile:
flock(outfile, LOCK_EX)
save_headers = op.getsize(opts.output_file) == 0
cvhelper.get_inner_cv_scores().to_csv(outfile,
index=False,
header=save_headers)
flock(outfile, LOCK_UN)
with open(opts.output_outer_cv, 'a' if PY3 else 'ab') as outfile:
flock(outfile, LOCK_EX)
save_headers = op.getsize(opts.output_outer_cv) == 0
cvhelper.get_outer_cv_scores().to_csv(outfile,
index=False,
header=save_headers)
flock(outfile, LOCK_UN)
import numpy as np
import pandas as pd
from mriqc import __version__, logging
from .data import read_iqms, read_dataset, zscore_dataset
from .sklearn_extension import ModelAndGridSearchCV, RobustGridSearchCV, nested_fit_and_score
from sklearn.base import is_classifier, clone
from sklearn.metrics.scorer import check_scoring
from sklearn.model_selection import LeavePGroupsOut, StratifiedKFold
from sklearn.model_selection._split import check_cv
from builtins import object, str
LOG = logging.getLogger('mriqc.classifier')
DEFAULT_TEST_PARAMETERS = {
'svc_linear': [{
'C': [0.1, 1]
}],
}
EXCLUDE_COLUMNS = [
'size_x', 'size_y', 'size_z', 'spacing_x', 'spacing_y', 'spacing_z'
]
class CVHelperBase(object):
def __init__(self,
X,
import pandas as pd
import matplotlib
import subprocess
matplotlib.use('Agg')
import matplotlib.pyplot as plt
from matplotlib.backends.backend_pdf import PdfPages
import jinja2
from mriqc.utils.misc import generate_csv
from mriqc.interfaces.viz_utils import (
plot_mosaic, plot_measures, plot_all, DINA4_LANDSCAPE, DEFAULT_DPI)
from mriqc import logging
MRIQC_REPORT_LOG = logging.getLogger('mriqc.report')
MRIQC_REPORT_LOG.setLevel(logging.INFO)
STRUCTURAL_QCGROUPS = [[
['cjv'],
['cnr'],
['efc'],
['fber'],
['wm2max'],
['snr', 'snr_csf', 'snr_gm', 'snr_wm'],
['fwhm_avg', 'fwhm_x', 'fwhm_y', 'fwhm_z'],
['qi1', 'qi2']
], [
['inu_range', 'inu_med'],
['icvs_csf', 'icvs_gm', 'icvs_wm'],
['rpve_csf', 'rpve_gm', 'rpve_wm'],
def upload_qc_metrics(in_iqms, email='', no_sub=False):
"""Upload qc metrics to remote repository.
Arguments:
in_iqms -- Path to the qc metric json file as a string
Keyword arguments:
email -- email address to be included with the metric submission, defaults to empty string
no_sub -- Flag from settings indicating whether or not metrics should be submitted. If False, metrics will be submitted. If True, metrics will not be submitted. Defaults to False.
Returns:
either returns response object if a response was successfully sent
or it returns the string "No Response"
"""
from json import load, dumps
import requests
from mriqc import logging
report_log = logging.getLogger('mriqc.report')
report_log.setLevel(logging.INFO)
if no_sub is True:
report_log.info(
'QC metrics were not uploaded because --no_sub or --testing options were set.'
)
r = "No Response"
else:
with open(in_iqms, 'r') as h:
in_data = load(h)
# metadata whitelist
whitelist = [
"ContrastBolusIngredient", "RepetitionTime", "TaskName",
"Manufacturer", "ManufacturersModelName", "MagneticFieldStrength",
"DeviceSerialNumber", "SoftwareVersions",
"HardcopyDeviceSoftwareVersion", "ReceiveCoilName",
"GradientSetType", "MRTransmitCoilSequence", "MatrixCoilMode",
"CoilCombinationMethod", "PulseSequenceType",
"PulseSequenceDetails", "NumberShots",
"ParallelReductionFactorInPlane", "ParallelAcquisitionTechnique",
"PartialFourier", "PartialFourierDirection",
"PhaseEncodingDirection", "EffectiveEchoSpacing",
"TotalReadoutTime", "EchoTime", "InversionTime", "SliceTiming",
"SliceEncodingDirection", "NumberOfVolumesDiscardedByScanner",
"NumberOfVolumesDiscardedByUser", "DelayTime", "FlipAngle",
"MultibandAccelerationFactor", "Instructions", "TaskDescription",
"CogAtlasID", "CogPOID", "InstitutionName", "InstitutionAddress",
"ConversionSoftware", "ConversionSoftwareVersion", "md5sum",
"modality", "mriqc_pred", "software", "subject_id", "version"
]
# flatten data
data = {k: v for k, v in list(in_data.items()) if k != 'metadata'}
# Filter Metadata values that aren't in whitelist
try:
data.update({
k: v
for k, v in list(in_data['metadata'].items()) if k in whitelist
})
except KeyError:
pass
# Preemptively adding code to handle settings
try:
data.update({
k: v
for k, v in list(in_data['settings'].items()) if k in whitelist
})
except KeyError:
pass
if email != '':
data['email'] = email
secret_key = 'ZUsBaabr6PEbav5DKAHIODEnwpwC58oQTJF7KWvDBPUmBIVFFtwOd7lQBdz9r9ulJTR1BtxBDqDuY0owxK6LbLB1u1b64ZkIMd46'
headers = {'token': secret_key, "Content-Type": "application/json"}
try:
r = requests.put("http://34.201.213.252:5000/measurements/upload",
headers=headers,
data=dumps(data))
if r.status_code == 201:
report_log.info('QC metrics successfully uploaded.')
else:
report_log.warn('QC metrics failed to upload. Status %d: %s' %
(r.status_code, r.text))
except requests.ConnectionError as e:
report_log.warn(
'QC metrics failed to upload due to connection error shown below:\n%s'
% e)
r = "No Response"
return r
def individual_html(in_iqms, in_plots=None, exclude_index=0, wf_details=None):
import os.path as op #pylint: disable=W0404
import datetime
from json import load
from mriqc import __version__ as ver
from mriqc.utils.misc import BIDS_COMP
from mriqc.reports.utils import iqms2html, anat_flags, read_report_snippet
from mriqc.data import IndividualTemplate
from mriqc import logging
from io import open #pylint: disable=W0622
report_log = logging.getLogger('mriqc.report')
report_log.setLevel(logging.INFO)
with open(in_iqms) as jsonfile:
iqms_dict = load(jsonfile)
# Now, the in_iqms file should be correctly named
fname = op.splitext(op.basename(in_iqms))[0]
out_file = op.abspath(fname + '.html')
if in_plots is None:
in_plots = []
if wf_details is None:
wf_details = []
# Extract and prune metadata
metadata = iqms_dict.pop('metadata', None)
mod = metadata.pop('modality', None)
file_id = [metadata.pop(k, None) for k in list(BIDS_COMP.keys())]
file_id = [comp for comp in file_id if comp is not None]
pred_qa = None #metadata.pop('mriqc_pred', None)
# Deal with special IQMs
if mod in ('T1w', 'T2w'):
flags = anat_flags(iqms_dict)
if flags:
wf_details.append(flags)
elif mod == 'bold':
pass
else:
RuntimeError('Unknown modality "%s"' % mod)
config = {
'modality': mod,
'sub_id': '_'.join(file_id),
'timestamp': datetime.datetime.now().strftime("%Y-%m-%d, %H:%M"),
'version': ver,
'imparams': iqms2html(iqms_dict, 'iqms-table'),
'svg_files': [read_report_snippet(pfile) for pfile in in_plots],
'exclude_index': exclude_index,
'workflow_details': wf_details,
'metadata': iqms2html(metadata, 'metadata-table'),
'pred_qa': pred_qa
}
if config['metadata'] is None:
config['workflow_details'].append(
'<span class="warning">File has no metadata</span> '
'<span>(sidecar JSON file missing or empty)</span>')
tpl = IndividualTemplate()
tpl.generate_conf(config, out_file)
report_log.info('Generated individual log (%s)', out_file)
return out_file
