def make_location(x, y, z):
location = Location(x, y, z)
# Add Neurosynth coactivation image if it exists
filename = 'metaanalytic_coactivation_%d_%d_%d_pFgA_z_FDR_0.01.nii.gz' % (
x, y, z)
filename = join(settings.IMAGE_DIR, 'coactivation', filename)
if not exists(filename):
tasks.make_coactivation_map.delay(x, y, z).wait()
if exists(filename):
ma_image = LocationImage(
name='Meta-analytic coactivation for seed (%d, %d, %d)' % (
x, y, z),
image_file=filename,
label='Meta-analytic coactivation',
stat='z-score',
display=1,
download=1,
description='This image displays regions coactivated with the seed'
' region across all studies in the Neurosynth database. It '
'represents meta-analytic coactivation rather than time '
'series-based connectivity.'
)
location.images.append(ma_image)
# Add Yeo FC image if it exists
filename = join(settings.IMAGE_DIR, 'fcmri',
'functional_connectivity_%d_%d_%d.nii.gz' % (x, y, z))
if exists(filename):
fc_image = LocationImage(
name='YeoBucknerFCMRI for seed (%d, %d, %d)' % (x, y, z),
image_file=filename,
label='Functional connectivity',
stat='corr. (r)',
description='This image displays resting-state functional '
'connectivity for the seed region in a sample of 1,000 subjects. '
'To reduce blurring of signals across cerebro-cerebellar and '
'cerebro-striatal boundaries, fMRI signals from adjacent cerebral '
'cortex were regressed from the cerebellum and striatum. For '
'details, see '
'<a href="http://jn.physiology.org/content/106/3/1125.long">Yeo et'
'al (2011)</a>, <a href="http://jn.physiology.org/cgi/pmidlookup?'
'view=long&pmid=21795627">Buckner et al (2011)</a>, and '
'<a href="http://jn.physiology.org/cgi/pmidlookup?view=long&'
'pmid=22832566">Choi et al (2012)</a>.',
display=1,
download=1
)
location.images.append(fc_image)
db.session.add(location)
db.session.commit()
# Decode both images
for img in location.images:
decode_analysis_image(img.id)
return location
def get_decoding():
"""
Retrieve decoding data for a single image
---
tags:
- decode
responses:
200:
description: Decoding data
default:
description: Decoding not found
parameters:
- in: query
name: uuid
description: UUID of the decoding
required: false
type: string
- in: query
name: image
description: ID of image to decode
type: integer
required: false
- in: query
name: neurovault
description: NeuroVault ID of image to decode
type: integer
required: false
- in: query
name: url
description: URL of Nifti image to decode
type: string
required: false
"""
dec = Decoding.query.filter_by(display=1)
if 'uuid' in request.args:
dec = dec.filter_by(uuid=request.args['uuid']).first()
elif 'image' in request.args:
dec = decode.decode_analysis_image(request.args['image'])
elif 'neurovault' in request.args:
dec_id = decode.decode_neurovault(request.args['neurovault'],
render=False)
dec = dec.filter_by(uuid=dec_id).first()
elif 'url' in request.args:
dec_id = decode.decode_url(request.args['url'], render=False)
dec = dec.filter_by(uuid=dec_id).first()
schema = DecodingSchema()
return jsonify(data=schema.dump(dec).data)
def get_decoding():
"""
Retrieve decoding data for a single image
---
tags:
- decode
responses:
200:
description: Decoding data
default:
description: Decoding not found
parameters:
- in: query
name: uuid
description: UUID of the decoding
required: false
type: string
- in: query
name: image
description: ID of image to decode
type: integer
required: false
- in: query
name: neurovault
description: NeuroVault ID of image to decode
type: integer
required: false
- in: query
name: url
description: URL of Nifti image to decode
type: string
required: false
"""
dec = Decoding.query.filter_by(display=1)
if 'uuid' in request.args:
dec = dec.filter_by(uuid=request.args['uuid']).first()
elif 'image' in request.args:
dec = decode.decode_analysis_image(request.args['image'])
elif 'neurovault' in request.args:
dec_id = decode.decode_neurovault(request.args['neurovault'],
render=False)
dec = dec.filter_by(uuid=dec_id).first()
elif 'url' in request.args:
dec_id = decode.decode_url(request.args['url'], render=False)
dec = dec.filter_by(uuid=dec_id).first()
schema = DecodingSchema()
return jsonify(data=schema.dump(dec).data)
def get_decoding_data(image, get_json=True):
if Image.query.get(image) is None:
return error_page("Invalid image requested for decoding. Please check"
" to make sure there is a valid image with id=%d." %
image)
dec = decode_analysis_image(image)
df = os.path.join(settings.DECODING_RESULTS_DIR, dec.uuid + '.txt')
if not os.path.exists(df):
return error_page("An unspecified error occurred during decoding.")
data = open(df).read().splitlines()
data = [x.split('\t') for x in data]
data = [[f, round(float(v or '0'), 3)] for (f, v) in data]
return jsonify(data=data) if get_json else data
def get_decoding_data(image, get_json=True):
if Image.query.get(image) is None:
return error_page("Invalid image requested for decoding. Please check"
" to make sure there is a valid image with id=%d." %
image)
dec = decode_analysis_image(image)
df = os.path.join(settings.DECODING_RESULTS_DIR, dec.uuid + '.txt')
if not os.path.exists(df):
return error_page("An unspecified error occurred during decoding.")
data = open(df).read().splitlines()
data = [x.split('\t') for x in data]
data = [[f, round(float(v or '0'), 3)] for (f, v) in data]
return jsonify(data=data) if get_json else data
def show(symbol):
gene = Gene.query.filter_by(symbol=symbol).first()
if gene is None:
return error_page("We have no data for the gene '%s'" % symbol)
image = gene.images[0]
# Run decoder if it hasn't been run before
dec = decode_analysis_image(image.id)
url = '/images/%s' % image.id
images = [{
'id': image.id,
'name': symbol,
'url': url,
'colorPalette': 'intense red-blue',
'download': url,
'sign': 'both'
}]
return render_template('genes/show.html.slim', gene=gene,
images=json.dumps(images), image_id=dec.uuid)
def show(symbol):
gene = Gene.query.filter_by(symbol=symbol).first()
if gene is None:
return error_page("We have no data for the gene '%s'" % symbol)
image = gene.images[0]
# Run decoder if it hasn't been run before
dec = decode_analysis_image(image.id)
url = '/images/%s' % image.id
images = [{
'id': image.id,
'name': symbol,
'url': url,
'colorPalette': 'intense red-blue',
'download': url,
'sign': 'both'
}]
return render_template('genes/show.html.slim',
gene=gene,
images=json.dumps(images),
image_id=dec.uuid)