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)
