def get_studies(val=None):
x, y, z, radius = get_params(val)
points = Peak.closestPeaks(radius, x, y, z)
# Track number of peaks and study details for each found study,
# keeping only peaks that haven't been previously seen for current
# study/x/y/z combination.
seen = {}
study_counts = defaultdict(list)
for p in points:
key = hash((p.pmid, round(p.x, 2), round(p.y, 2), round(p.z, 2)))
if key in seen:
next
study_counts[p.pmid].append(p)
seen[key] = 1
if 'dt' in request.args:
data = []
for pmid, peaks in study_counts.items():
s = peaks[0].study
link = '<a href={0}>{1}</a>'.format(url_for('studies.show',
val=pmid), s.title)
data.append([link, s.authors, s.journal, len(peaks)])
else:
data = [{'pmid': pmid, 'peaks': len(peaks)}
for pmid, peaks in study_counts.items()]
return jsonify(data=data)
def location_api(val):
args = [int(i) for i in val.split('_')]
if len(args) == 3: args.append(10)
x, y, z, radius = args
### PEAKS ###
# Limit search to 20 mm to keep things fast
if radius > 20: radius = 20
points = Peak.closestPeaks(radius,x,y,z)
points = points.group_by(Peak.pmid) #prevents duplicate studies
points = points.add_columns(sqlalchemy.func.count(Peak.id)) #counts duplicate peaks
### IMAGES ###
location = Location.query.filter_by(x=x, y=y, z=z).first()
images = [] if location is None else location.images
images = [{'label': i.label, 'id': i.id} for i in images if i.display]
if 'draw' in request.args:
data = []
for p in points:
s = p[0].study
link = '<a href={0}>{1}</a>'.format(url_for('studies.show',val=s.pmid),s.title)
data.append([link, s.authors, s.journal,p[1]])
data = jsonify(data=data)
else:
data = {
'studies': [{'pmid':p[0].study.pmid,'peaks':p[1] } for p in points],
'images': images
}
data = jsonify(data=data)
return data
def get_location():
"""
Retrieve location data
---
tags:
- locations
responses:
200:
description: Location data
default:
description: No locations found
parameters:
- in: query
name: x
description: x-coordinate
required: true
type: integer
- in: query
name: y
description: y-coordinate
required: true
type: integer
- in: query
name: z
description: z-coordinate
required: true
type: integer
- in: query
name: r
description: Radius of sphere within which to search for study activations, in mm (default = 6, max = 20).
required: false
type: integer
"""
x = int(request.args['x'])
y = int(request.args['y'])
z = int(request.args['z'])
# Radius: 6 mm by default, max 2 cm
r = min(int(request.args.get('r', 6)), 20)
# Check validity of coordinates and redirect if necessary
check_xyz(x, y, z)
loc = Location.query.filter_by(x=x, y=y, z=z).first()
if loc is None:
from nsweb.controllers.locations import make_location
loc = make_location(x, y, z)
peaks = Peak.closestPeaks(r, x, y, z)
peaks = peaks.group_by(Peak.pmid)
peaks = peaks.add_columns(func.count(Peak.id))
loc.studies = [p[0].study for p in peaks]
schema = LocationSchema()
return jsonify(data=schema.dump(loc).data)
def get_studies(val=None):
x, y, z, radius = get_params(val)
points = Peak.closestPeaks(radius, x, y, z)
# prevents duplicate studies
points = points.group_by(Peak.pmid)
# counts duplicate peaks
points = points.add_columns(sqlalchemy.func.count(Peak.id))
if 'dt' in request.args:
data = []
for p in points:
s = p[0].study
link = '<a href={0}>{1}</a>'.format(url_for('studies.show',
val=s.pmid), s.title)
data.append([link, s.authors, s.journal, p[1]])
data = jsonify(data=data)
else:
data = [{'pmid': p[0].study.pmid, 'peaks':p[1]} for p in points]
data = jsonify(data=data)
return data
