profile_dict['image2_snowIndex'] = ndsi2mean # add mean snow index profile for image 1
profiles.append(profile_dict) # add to list
# Translate timeslices across space (profiles) to timeseries across time at a point (pts)
pts = wgt.convertProfilesListToPointTimeseries(profiles)
# Collect all transect data to write out
timeNow = dt.datetime.now()
profile_data={ 'sample_pts_lon_lat':sample_pts_lon_lat, 'sample_pts_PS':sample_pts_PS, 'sample_pts_frontdist':sample_pts_frontdist.tolist(),\
'sampled_on_date_iso':timeNow.isoformat(), 'profile_shapefile':profile_shapefile, 'profile_shapefile_dir':profile_shapefile_dir,\
'profile_shapefile_projection_Proj':originalSrsProj, 'profiles':profiles, 'pts':pts, 'transect_name':transName }
# Write transect velocity data to json file
jsonFnOut = transName + '_swathVelocitySampling_' + timeNow.strftime("%Y-%m-%d") + '.json'
wgt.writeJsonFile(profile_data,jsonFnOut)
## ANALYSIS AND PLOTTING
for featNum in range(0,lyr.GetFeatureCount()): # iterate over all transects
# just hacking these for testing - will change to loop
#feat = lyr.GetFeature(59) # kaskWB if using the epsg102006 transects
#feat = lyr.GetFeature(19) # kaskWB if using the st elias utm7n transects
#feat = lyr.GetFeature(8) # nabeEB if using the wrangells utm7n transects
#featNum = 17 # nabeEB if using new WStE transects
feat = lyr.GetFeature(featNum) # get feature
lineGeom = feat.geometry() # get geometry of profile line
transName = feat.GetField(1) # transect name
# Get json fn (assumes only one in this directory for each transect)
summerTiming = {'doys':suDoys,'midDates':suMidDates,'startDates':suStarts,'endDates':suEnds,'dDays':suDts}
winterTiming = {'doys':wiDoys,'midDates':wiMidDates,'startDates':wiStarts,'endDates':wiEnds,'dDays':wiDts}
# Save to dict for writing out
velocityChangeDict[transName] = speedupDictNow
velocityChangeDict2[transName] = speedupDictNow2
allSeasonalVelocities[transName]=seasonalVelocityDictToJson
allGlacierTiming[transName]={'summer':summerTiming,'winter':winterTiming}
# Plot seasonal velocity data
#wgt.plotSeasonalVelocity(seasonalVelocityDict2,speedupDictNow2,termDist,1,1)
#wgt.plotSeasonalSpeedup(speedupDictNow2,termDist,1,1)
# Write timing out
jsonFnOut0 = 'timingDict_fullyAutomated_27jan2017.json'
wgt.writeJsonFile(allGlacierTiming,jsonFnOut0)
# Write speedup plots out
jsonFnOut1 = 'speedupDict_fullyAutomated_28nov2016.json'
jsonFnOut2 = 'speedupDict_2iterTempFilter_fullyAutomated_28nov2016.json'
wgt.writeJsonFile(velocityChangeDict,jsonFnOut1)
wgt.writeJsonFile(velocityChangeDict2,jsonFnOut2)
# Write seasonal velocity out
jsonFnOut3 = 'seasonalVelocityProfiles_2iterTempFilter_fullyAutomated_24jan2017.json'
wgt.writeJsonFile(allSeasonalVelocities,jsonFnOut3)
# Define speedup distance
from scipy.stats import ranksums
profiles.append(profile_dict) # add to list
# Translate timeslices across space (profiles) to timeseries across time at a point (pts)
pts = wgt.convertProfilesListToPointTimeseries(profiles)
# Collect all transect data to write out
timeNow = dt.datetime.now()
profile_data={ 'sample_pts_lon_lat':sample_pts_lon_lat, 'sample_pts_PS':sample_pts_PS, 'sample_pts_frontdist':sample_pts_frontdist.tolist(),\
'sampled_on_date_iso':timeNow.isoformat(), 'profile_shapefile':profile_shapefile, 'profile_shapefile_dir':profile_shapefile_dir,\
'profile_shapefile_projection_Proj':originalSrsProj, 'profiles':profiles, 'pts':pts, 'transect_name':transName }
# Write transect velocity data to json file
jsonFnOut = transName + '_swathVelocitySampling_' + timeNow.strftime(
"%Y-%m-%d") + '.json'
wgt.writeJsonFile(profile_data, jsonFnOut)
## ANALYSIS AND PLOTTING
for featNum in range(0, lyr.GetFeatureCount()): # iterate over all transects
# just hacking these for testing - will change to loop
#feat = lyr.GetFeature(59) # kaskWB if using the epsg102006 transects
#feat = lyr.GetFeature(19) # kaskWB if using the st elias utm7n transects
#feat = lyr.GetFeature(8) # nabeEB if using the wrangells utm7n transects
#featNum = 17 # nabeEB if using new WStE transects
feat = lyr.GetFeature(featNum) # get feature
lineGeom = feat.geometry() # get geometry of profile line
transName = feat.GetField(1) # transect name
# Get json fn (assumes only one in this directory for each transect)
try:
alpha = np.append(alpha, dz / dx)
elevDict[transName] = {
'dist': dist.tolist(),
'slope': alpha.tolist(),
'elevMean': zStats['means'],
'elevMin': zStats['mins'],
'elevMax': zStats['maxs'],
'elevStd': zStats['stds'],
'elevCount': zStats['counts']
}
# Write transect velocity data to json file
jsonFnOut = os.path.split(
albersCenterlinesFn)[1][:-4] + '_elevationProfiles.json'
wgt.writeJsonFile(elevDict, jsonFnOut)
## PLOTTING ELEVATION PROFILES
color_idx = np.linspace(0, 1, len(elevDict))
cols = plt.cm.GnBu(color_idx)
transIter = elevDict.iterkeys()
meanMins = []
meanMeans = []
meanMaxs = []
meanDists = []
for i in range(0, len(elevDict)):
transName = transIter.next()
elevNow = elevDict[transName]
randInd = np.random.randint(0, len(elevDict))
plt.plot(np.array(elevNow['dist']) / 1e3,
# plt.text(-.19,-.13,'UG rmse: ' + "{0:.3f}".format(rmseUp))
# plt.text(-.19,-.09,'DG r2: ' + "{0:.3f}".format(r2down))
# plt.text(-.19,-0.03,'DG rmse: ' + "{0:.3f}".format(rmseDown))
plt.xlim((-.2,.2))
plt.ylim((-.2,.2))
plt.xlabel('Observed speedup [m/d]',fontsize=16)
plt.ylabel('Best linear \n fit speedup [m/d]',fontsize=16)
plt.savefig(transNow + '_quantifySpeedupPlot_relToSnowline.pdf')
#plt.show()
plt.close()
except KeyError:
print "Key error on " + transNow
ranksumExists = 0
wgt.writeJsonFile(quantifySpeedupDict,'quantifySpeedupDict_withSnowline_handTreated_07feb2017.json')
# Look at all glaciers together
#data = wgt.readJsonFile('/Users/wiar9509/Google Drive/wrangells/json/quantifySpeedupDict_07feb2017.json')
qSpeed = wgt.readJsonFile('/Users/wiar9509/Google Drive/wrangells/json/quantifySpeedupDict_withSnowline_handTreated_07feb2017.json')
# initialize
transNameList = []
speedMagListUp = []
speedMagListDown = []
speedSlopeListUp = []
speedSlopeListDown = []
color_idx = np.linspace(0, 1, len(qSpeed))
cols = plt.cm.Paired(color_idx)
interpProfileCoords = wgt.readVertexCoordsFromPolyline(transName+'_swathSamplePoints.shp') # read vertex coordinates from interpolated line
stats = wgt.zonal_stats(outDirectory + transName+'_samplePolygons.shp', albersDemFn) # swath profile along transect
zStats = wgt.readZonalStatsOutput(stats) # read swath profile output
dz = np.diff(zStats['means'])
dx = np.diff(dist)
alpha = np.nan
alpha = np.append(alpha,dz/dx)
elevDict[transName] = {'dist':dist.tolist(),'slope':alpha.tolist(),'elevMean':zStats['means'],'elevMin':zStats['mins'],'elevMax':zStats['maxs'],'elevStd':zStats['stds'],'elevCount':zStats['counts']}
# Write transect velocity data to json file
jsonFnOut = os.path.split(albersCenterlinesFn)[1][:-4] + '_elevationProfiles.json'
wgt.writeJsonFile(elevDict,jsonFnOut)
## PLOTTING ELEVATION PROFILES
color_idx = np.linspace(0, 1, len(elevDict))
cols = plt.cm.GnBu(color_idx)
transIter = elevDict.iterkeys()
meanMins = []
meanMeans = []
meanMaxs = []
meanDists = []
for i in range(0,len(elevDict)):
transName = transIter.next()
elevNow = elevDict[transName]
# plt.text(-.19,-.09,'DG r2: ' + "{0:.3f}".format(r2down))
# plt.text(-.19,-0.03,'DG rmse: ' + "{0:.3f}".format(rmseDown))
plt.xlim((-.2, .2))
plt.ylim((-.2, .2))
plt.xlabel('Observed speedup [m/d]', fontsize=16)
plt.ylabel('Best linear \n fit speedup [m/d]', fontsize=16)
plt.savefig(transNow + '_quantifySpeedupPlot_relToSnowline.pdf')
#plt.show()
plt.close()
except KeyError:
print "Key error on " + transNow
ranksumExists = 0
wgt.writeJsonFile(
quantifySpeedupDict,
'quantifySpeedupDict_withSnowline_handTreated_07feb2017.json')
# Look at all glaciers together
#data = wgt.readJsonFile('/Users/wiar9509/Google Drive/wrangells/json/quantifySpeedupDict_07feb2017.json')
qSpeed = wgt.readJsonFile(
'/Users/wiar9509/Google Drive/wrangells/json/quantifySpeedupDict_withSnowline_handTreated_07feb2017.json'
)
# initialize
transNameList = []
speedMagListUp = []
speedMagListDown = []
speedSlopeListUp = []
speedSlopeListDown = []