def check(path = 'data/hydrosheds/directions_for_streamflow9.nc'):
cells = pe.get_connected_cells(directions_path = path)
def compare_swe_2d():
"""
Compare seasonal mean
"""
start = datetime(1980,01,01,00)
end = datetime(1996, 12, 31,00)
months = [12,1,2]
#calculate mean for ccc data accounting for the mask
domain_mask = get_domain_mask()
cccData = getTemporalMeanCCCDataForMask(domain_mask,
startDate = start,
endDate = end, months = months)
lon_selected = polar_stereographic.lons[domain_mask == 1]
lat_selected = polar_stereographic.lats[domain_mask == 1]
geopointList = []
for lon, lat in zip(lon_selected, lat_selected):
geopointList.append(GeoPoint(longitude = lon, latitude = lat))
print 'Selecting obs data'
sweObs = SweHolder()
obsData = sweObs.getTemporalMeanDataFromNetCDFforPoints(geopointList, startDate = start,
endDate = end, months = months)
to_plot = np.ma.masked_all(polar_stereographic.lons.shape)
condition = domain_mask == 1
to_plot[condition] = (cccData - obsData) / obsData * 100
xs = polar_stereographic.xs
ys = polar_stereographic.ys
basemap = polar_stereographic.basemap
plot_utils.apply_plot_params()
basemap.pcolormesh(xs, ys, to_plot, cmap = mpl.cm.get_cmap('jet', 9), vmin = -60, vmax = 120)
basemap.drawcoastlines()
plt.colorbar(ticks = LinearLocator(numticks = 10), format = '%.1f')
plt.title('Snow Water Equivalent (%) \n $(S_{\\rm CRCM4} - S_{\\rm obs.})/S_{\\rm obs.}\\cdot100\%$\n')
#zoom to domain
selected_x = xs[~to_plot.mask]
selected_y = ys[~to_plot.mask]
marginx = abs(np.min(selected_x) * 5.0e-2)
marginy = abs(np.min(selected_y) * 5.0e-2)
plt.xlim(np.min(selected_x) - marginx, np.max(selected_x) + marginx)
plt.ylim(np.min(selected_y) - marginy, np.max(selected_y) + marginy)
bb.plot_basin_boundaries_from_shape(basemap, plotter = plt, linewidth = 2, edge_color = 'k')
##overlay flow directions
cells = cpe.get_connected_cells('data/hydrosheds/directions_for_streamflow9.nc')
read_infocell.plot_directions(cells, basemap = basemap, domain_mask = get_domain_mask())
selected_stations = [
104001, 103715, 93806, 93801,
92715, 81006, 61502, 80718,
40830, 42607
]
selected_ids = map(lambda x: "%06d" % x, selected_stations)
print selected_ids
cpe.plot_station_positions(id_list=selected_ids, use_warpimage=False,
save_to_file=False, the_basemap=basemap)
plt.savefig('swe_djf_validation.pdf', bbox_inches = 'tight')
pass
