def main():
model = LatLonHolder()
station_manager = StationManager()
station_manager.read_stations_from_files_rivdis()
selected_stations = []
ij_list = []
composite_index = 0
for longitude, latitude in zip( model.longitudes, model.latitudes ):
the_station = station_manager.get_station_closest_to(longitude, latitude)
if the_station != None:
selected_stations.append(the_station)
ix = model.get_ix(composite_index)
iy = model.get_iy(composite_index)
ij_list.append([ix, iy])
composite_index += 1
for station in selected_stations:
print station.longitude, station.latitude, station.id
print ij_list
def plot_monthly_means_with_measurements(model_points):
years = mdates.YearLocator(5, month=1, day=1) # every year
months = mdates.MonthLocator() # every month
yearsFmt = mdates.DateFormatter("%Y")
plt.cla()
##holder of longitudes and latitudes of the model grid points
holder = LatLonHolder()
# Manager of the measurement data
station_manager = StationManager()
station_manager.read_stations_from_files_rivdis()
station_manager.read_data_from_files_hydat()
print station_manager.get_station_by_id("02NG005")
measure_stations = []
selected_model_points = []
for model_point in model_points:
lon, lat = holder.get_lon_lat(model_point.ix, model_point.iy)
the_station = station_manager.get_station_closest_to(lon, lat)
if the_station != None:
measure_stations.append(the_station)
model_point.set_longitude(lon)
model_point.set_latitude(lat)
selected_model_points.append(model_point)
fig = plt.figure(figsize=(18, 18))
num_cols = 2
num_rows = len(selected_model_points) / num_cols
if len(selected_model_points) % num_cols > 0:
num_rows += 1
inches_per_pt = 1.0 / 72.27 # Convert pt to inch
golden_mean = (sqrt(5) - 1.0) / 2.0 # Aesthetic ratio
fig_width = 100.0 * inches_per_pt # width in inches
fig_height = fig_width * golden_mean # height in inches
fig_size = [fig_width, 10 * fig_height]
params = {
"axes.labelsize": 14,
"text.fontsize": 14,
"font.size": 14,
"legend.fontsize": 14,
"xtick.labelsize": 14,
"ytick.labelsize": 14,
}
print "fig_size = ", fig_size
pylab.rcParams.update(params)
assert len(selected_model_points) > 0
model_dates = selected_model_points[0].get_monthly_dates_sorted()
for i, model_point in enumerate(selected_model_points):
ax = plt.subplot(num_rows, num_cols, i + 1)
# plot model data
values = model_point.get_monthly_means_sorted_by_date()
ax.plot(model_dates, values, label="model")
# plot measurement data
values = measure_stations[i].get_values_for_dates(model_dates)
ax.plot(model_dates, values, "-", label="measurements", lw=3)
plt.title(model_point.__str__() + "\n" + measure_stations[i].__str__())
# format the ticks
ax.xaxis.set_major_locator(years)
ax.xaxis.set_major_formatter(yearsFmt)
ax.legend()
# ax.xaxis.set_minor_locator(months)
fig.subplots_adjust(wspace=0.4)
# fig.autofmt_xdate()
fig.savefig("comparison.png")
pass