def roi_mask_v2(self, roimask, contrast_data):
filename = tempfile.mktemp(suffix='.png',
dir=self.tmp_image_dir,
prefix='roi_masks-')
mask = cortex.db.get_mask('MNI', 'atlas')
# a = b
roimask = roimask * 1.0
roimask[mask == False] = np.nan
roivol = cortex.Volume(roimask, 'MNI', 'atlas', mask=mask)
# Create flatmap
fig = cortex.quickflat.make_figure(cortex.Volume(contrast_data,
'MNI',
'atlas',
vmin=0,
vmax=1,
cmap='Blues'),
with_colorbar=False,
with_curvature=True,
bgcolor=None)
# Add rois
#if not contrast_data.isPmap:
# add_hash_layer(fig, roivol, [255,255,255], [0,8,12])
add_hash_layer(fig, roivol, [10, 0, 0], [3, 8, 8])
dpi = 100
imsize = fig.get_axes()[0].get_images()[0].get_size()
fig.set_size_inches(np.array(imsize)[::-1] / float(dpi))
fig.savefig(filename, transparent=True, dpi=dpi)
fig.clf()
pltclose(fig)
return filename
def roi_mask_v2(self, roimask, contrast_data):
# Create random filename
prefix = 'group'
if contrast_data.isPmap:
print('This is a Pmap!')
filename = '{0}_{1}_{2}_flatPmap.png'.format(
prefix, contrast_data.contrast.experiment.name,
contrast_data.contrast.contrast_name)
else:
print('This is a not a Pmap!')
filename = '{0}_{1}_{2}_flatmap.png'.format(
prefix, contrast_data.contrast.experiment.name,
contrast_data.contrast.contrast_name)
filename = os.path.join(self.path, filename)
print filename
mask = cortex.db.get_mask('MNI', 'atlas')
# a = b
roimask = roimask * 1.0
roimask[mask == False] = np.nan
roivol = cortex.Volume(roimask, 'MNI', 'atlas', mask=mask)
# print np.sum(np.isnan(roivol.data))
# Create flatmap
#'YlGn'
fig = cortex.quickflat.make_figure(contrast_data,
with_colorbar=False,
with_curvature=True,
bgcolor='black')
# Add rois
if not contrast_data.isPmap:
add_hash_layer(fig, roivol, [255, 255, 255], [0, 8, 12])
add_hash_layer(fig, roivol, [10, 0, 0], [3, 8, 8])
# add_hash_layer(fig, roivol, [10,10,0], [2,6,2])
#add_hash_layer(fig, roivol, [0,50,0], [0,6,4])
#add_hash_layer(fig, roivol, [10,10,0], [2,6,2])
#add_hash_layer(fig, roivol, [255,255,255], [4,6,2])
# Save flatmap
dpi = 100
imsize = fig.get_axes()[0].get_images()[0].get_size()
fig.set_size_inches(np.array(imsize)[::-1] / float(dpi))
# if bgcolor is None:
fig.savefig(filename, transparent=True, dpi=dpi)
# else:
# fig.savefig(filename, facecolor=filename, transparent=False, dpi=dpi)
fig.clf()
pltclose(fig)
# Create HTML pointing to flatmap
html = "<img src='{filename}'/>".format(filename=filename)
return html
def roi_mask_v2(self, roimask, contrast_data):
# Create random filename
prefix = contrast_data.ref_to_subject.pycortex_surface
filename = '{0}_{1}_{2}_flatmap.png'.format(
prefix, contrast_data.contrast.experiment.name,
contrast_data.contrast.contrast_name)
filename = os.path.join(self.path, filename)
print filename
mask = cortex.db.get_mask(
contrast_data.ref_to_subject.pycortex_surface,
contrast_data.ref_to_subject.pycortex_transform)
# a = b
roimask = roimask * 1.0
roimask = cortex.mni.transform_mni_to_subject(
contrast_data.ref_to_subject.pycortex_surface,
contrast_data.ref_to_subject.pycortex_transform,
roimask.T,
contrast_data.ref_to_subject.func_to_mni,
template=default_template).get_data().T
roimask[mask == False] = np.nan
roivol = cortex.Volume(roimask,
contrast_data.ref_to_subject.pycortex_surface,
contrast_data.ref_to_subject.pycortex_transform,
mask=mask)
# print np.sum(np.isnan(roivol.data))
# Create flatmap
contrast_data2 = ContrastDataS(
contrast_data.thresholded_contrast_05.data,
contrast_data.ref_to_subject.pycortex_surface,
contrast_data.ref_to_subject.pycortex_transform,
0, #contrast_data.thresholded_contrast_05.vmin,
1.25, #contrast_data.thresholded_contrast_05.vmax,
contrast_data.contrast,
contrast_data.func_to_mni,
contrast_data.ref_to_subject,
cmap="Blues") #YlGn RdPu
# print ContrastDataS.data.shape
contrast_data2.data[contrast_data2.ref_to_subject._voxels_predicted ==
False] = np.nan
fig = cortex.quickflat.make_figure(contrast_data2,
with_colorbar=False,
with_curvature=True,
shadow=0,
**self.quickflat_args)
# bgcolor='black')
# Add rois
#add_hash_layer(fig, roivol, [0,10,255], [0,50000,50001], alpha = 0.5)
#add_hash_layer(fig, roivol, [255,255,255], [0,8,12])
add_hash_layer(fig, roivol, [10, 0, 0], [0, 8, 8])
#add_hash_layer(fig, roivol, [10,0,0], [3,8,4])
#add_hash_layer(fig, roivol, [0,50,0], [4,8,2])
# add_hash_layer(fig, roivol, [10,10,0], [2,5,2])
# add_hash_layer(fig, roivol, [0,50,0], [0,5,2])
# add_hash_layer(fig, roivol, [10,10,0], [2,5,2])
# add_hash_layer(fig, roivol, [255,255,255], [4,5,2])
# Save flatmap
dpi = 100
imsize = fig.get_axes()[0].get_images()[0].get_size()
fig.set_size_inches(np.array(imsize)[::-1] / float(dpi))
# if bgcolor is None:
fig.savefig(filename, transparent=True, dpi=dpi)
# else:
# fig.savefig(filename, facecolor=filename, transparent=False, dpi=dpi)
fig.clf()
pltclose(fig)
# Create HTML pointing to flatmap
html = "<img src='{filename}'/>".format(filename=filename)
return html
def plotMeteogramFile(latitude=None,
longitude=None,
location=None,
days=3,
plotType="enhanced-hres"):
print(latitude, longitude)
print(plotType)
if location:
latitude, longitude, altitude, _ = getCoordinates([("--location",
location)])
elif latitude is not None and longitude is not None:
latitude = float(latitude)
longitude = float(longitude)
from altitude import ElevationService
e = ElevationService('.cache/')
altitude = e.get_elevation(latitude, longitude)
if altitude is None:
altitude = -999
else:
latitude = 52.2646577
longitude = 10.5236066
altitude = 79
if days <= 10:
allMeteogramData = getData(float(longitude),
float(latitude),
altitude,
writeToFile=False)
else:
allMeteogramData = getData(float(longitude),
float(latitude),
altitude,
writeToFile=False,
meteogram="15days")
tzName = tz.tzNameAt(latitude, longitude)
today = datetime.utcnow()
fromIndex, toIndex = getTimeFrame(allMeteogramData, today,
today + timedelta(days))
fig = plotMeteogram(allMeteogramData, fromIndex, toIndex, tzName, plotType)
filename = str(today) + str(latitude) + str(longitude) + "forecast.png"
tmpSize = prop.get_size()
prop.set_size(16)
print(tmpSize)
fig.suptitle(location + " " + str(np.round(latitude, decimals = 2)) +\
"°/" + str(np.round(longitude, decimals = 2)) +\
"°/" + str(altitude) + "m", fontproperties=prop)
prop.set_size(tmpSize)
if '2t' in allMeteogramData:
#fig.text(0.1,0.03,allMeteogramData['2t']['date']+"-"+allMeteogramData['2t']['time'],fontproperties=prop)
fig.text(0.2,
0.06,
"Forecast from the European Weather Centre from " +
allMeteogramData['2t']['date'] + " at " +
allMeteogramData['2t']['time'][0:2] + ":" +
allMeteogramData['2t']['time'][0:2] + " UTC",
fontproperties=prop)
if 'tp24' in allMeteogramData:
fig.text(0.2,
0.06,
"Forecast from the European Weather Centre from " +
allMeteogramData['tp24']['date'] + " at " +
allMeteogramData['tp24']['time'][0:2] + ":" +
allMeteogramData['tp24']['time'][0:2] + " UTC",
fontproperties=prop)
#fig.text(0.1,0.03,allMeteogramData['tp24']['date']+"-"+allMeteogramData['tp24']['time'],fontproperties=prop)
fig.savefig("/tmp/" + filename, dpi=300, bbox_inches='tight')
pltclose(fig)
return filename