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