def get_mask_for_station(directions_file = 'data/hydrosheds/directions_for_streamflow9.nc', i_index = -1, j_index = -1): import diagnose_ccc.compare_swe as compare_swe cells = get_connected_cells(directions_file) nx = len(cells) ny = len(cells[0]) the_mask = np.zeros((nx, ny)) theCell = cells[i_index][j_index] the_mask[theCell.coords()] = 1 #of course include the current cell # @type theCell Cell upstream_cells = theCell.get_upstream_cells() for c in upstream_cells: the_mask[c.coords()] = 1 domain_mask = compare_swe.get_domain_mask() the_mask *= domain_mask return the_mask
def main(): fig = plt.figure() ax = fig.add_subplot(1,1,1) for i in xrange(3): members.all_current.pop() domain_mask = compare_swe.get_domain_mask() #plot runoff evol for members for the_id in members.all_current: times, data = get_mean_over_domain(the_id, mask = domain_mask) ax.plot(times, data, "--", label = the_id) print "finished: %s " % the_id times, data = get_mean_over_domain(members.control_id, mask = domain_mask) ax.plot(times, data, label = members.control_id) ax.xaxis.set_major_locator( mpl.dates.MonthLocator(bymonth = range(2,13,2)) ) ax.xaxis.set_major_formatter( mpl.dates.DateFormatter('%b') ) plt.legend(ncol = 3) plt.savefig("runoff_evol.pdf") pass
def main(cls, path_to_spinups_dir = "data/spinup_testing"): data_list = [] domain_mask = compare_swe.get_domain_mask() for fileName in os.listdir(path_to_spinups_dir): spinup = fileName.split("_")[-1].split("yrs")[0] spinup = int(spinup) filePath = os.path.join(path_to_spinups_dir, fileName) data_list += [FirstYearData(path=filePath, spinup_years=spinup)] data_list.sort(key = lambda x: x.spinup_years) plotter = Plotter(first_year_data_list=data_list) plotter.plot_all_on_one(domain_mask=domain_mask)