def output_json(regions, options):
"""Write a GeoJSON collection of `regions` with their discrepancy."""
discrepancies = [v[0] for v in regions]
colormap = mpl.cm.ScalarMappable(sps.mcolor.Normalize(min(discrepancies),
max(discrepancies)),
'YlOrBr')
schema = {'geometry': 'Polygon', 'properties': [('discrepancy', 'float'),
('color', 'str'),
('photos', 'float'),
('checkins', 'float')]}
get_color = lambda v: sps.mcolor.rgb2hex(colormap.to_rgba(v))
city = options['city']
photos_as_background = options['photos_background']
prefix = '_only' if options['only'] else ''
ratio = options.pop('ratio', 0)
if photos_as_background:
photos_idx, checkins_idx = 2, 3
name = city+prefix+'_checkins_d.json'
options['photos_ratio'] = ratio
else:
photos_idx, checkins_idx = 3, 2
name = city+prefix+'_photos_d.json'
options['checkins_ratio'] = ratio
polys = [{'geometry': sps.mapping(r[1]), 'properties':
{'discrepancy': r[0], 'color': get_color(r[0]),
'photos': r[photos_idx], 'checkins': r[checkins_idx]}}
for r in regions]
name = os.path.join('maps', name)
write_collection(polys, name, schema)
options['city'] = '"{}"'.format(options['city'])
with open(os.path.join('maps', city+'.js'), 'a') as f:
f.write('\n'.join(['var {} = {};'.format(var, str(val).lower())
for var, val in options.iteritems()]))
options['city'] = city
def full_disc_json(lratio, nz, city='paris'):
it = np.nditer(lratio, flags=['f_index'])
colormap = mpl.cm.ScalarMappable(sps.mcolor.Normalize(nz.min(), nz.max()),
'coolwarm')
schema = {
'geometry': 'Polygon',
'properties': [('ratio', 'float'), ('color', 'str')]
}
get_color = lambda v: sps.mcolor.rgb2hex(colormap.to_rgba(v))
polys = []
box = lambda i: sps.shape(sps.bbox_to_polygon(sps.index_to_rect(i), False))
while not it.finished:
idx, val = it.index, it[0]
if not np.isinf(val):
val = float(val)
polys.append({
'geometry': sps.mapping(box(idx)),
'properties': {
'ratio': val,
'color': get_color(val)
}
})
it.iternext()
print(polys[0])
name = 'maps/' + city + '_full_d.json'
write_collection(polys, name, schema)
def full_disc_json(lratio, nz, city='paris'):
it = np.nditer(lratio, flags=['f_index'])
colormap = mpl.cm.ScalarMappable(sps.mcolor.Normalize(nz.min(), nz.max()),
'coolwarm')
schema = {'geometry': 'Polygon', 'properties': [('ratio', 'float'),
('color', 'str')]}
get_color = lambda v: sps.mcolor.rgb2hex(colormap.to_rgba(v))
polys = []
box = lambda i: sps.shape(sps.bbox_to_polygon(sps.index_to_rect(i), False))
while not it.finished:
idx, val = it.index, it[0]
if not np.isinf(val):
val = float(val)
polys.append({'geometry': sps.mapping(box(idx)), 'properties':
{'ratio': val, 'color': get_color(val)}})
it.iternext()
print(polys[0])
name = 'maps/'+city+'_full_d.json'
write_collection(polys, name, schema)
def output_json(regions, options):
"""Write a GeoJSON collection of `regions` with their discrepancy."""
discrepancies = [v[0] for v in regions]
colormap = mpl.cm.ScalarMappable(
sps.mcolor.Normalize(min(discrepancies), max(discrepancies)), 'YlOrBr')
schema = {
'geometry':
'Polygon',
'properties': [('discrepancy', 'float'), ('color', 'str'),
('photos', 'float'), ('checkins', 'float')]
}
get_color = lambda v: sps.mcolor.rgb2hex(colormap.to_rgba(v))
city = options['city']
photos_as_background = options['photos_background']
prefix = '_only' if options['only'] else ''
ratio = options.pop('ratio', 0)
if photos_as_background:
photos_idx, checkins_idx = 2, 3
name = city + prefix + '_checkins_d.json'
options['photos_ratio'] = ratio
else:
photos_idx, checkins_idx = 3, 2
name = city + prefix + '_photos_d.json'
options['checkins_ratio'] = ratio
polys = [{
'geometry': sps.mapping(r[1]),
'properties': {
'discrepancy': r[0],
'color': get_color(r[0]),
'photos': r[photos_idx],
'checkins': r[checkins_idx]
}
} for r in regions]
name = os.path.join('maps', name)
write_collection(polys, name, schema)
options['city'] = '"{}"'.format(options['city'])
with open(os.path.join('maps', city + '.js'), 'a') as f:
f.write('\n'.join([
'var {} = {};'.format(var,
str(val).lower())
for var, val in options.iteritems()
]))
options['city'] = city
