def test_catch_areas(): fig, ax = plt.subplots() gdir = init_hef() graphics.plot_catchment_areas(gdir, ax=ax) fig.tight_layout() return fig
list_talks = [ tasks.compute_centerlines, #Compute the centerlines following Kienholz et al., (2014). tasks.initialize_flowlines, #Computes more physical Inversion Flowlines from geometrical Centerlines tasks.compute_downstream_line, #Computes the Flowline along the unglaciated downstream topography tasks.catchment_area, #Compute the catchment areas of each tributary line. tasks.catchment_width_geom, #Compute geometrical catchment widths for each point of the flowlines tasks.catchment_width_correction, #Corrects for NaNs and inconsistencies in the geometrical widths. tasks.compute_downstream_bedshape #The bedshape obtained by fitting a parabola to the line's normals and downstream altitude ] for task in list_talks: workflow.execute_entity_task(task, gdirs) for agdir in gdirs: graphics.plot_centerlines(agdir, figsize=(8, 7), use_flowlines=True, add_downstream=True) graphics.plot_catchment_areas(agdir, figsize=(8, 7)) graphics.plot_catchment_width(agdir, corrected=True, figsize=(8, 7)) # Location of Monthly Climate Data for the Glacier #fpath = gdir.get_filepath('climate_monthly') #print(fpath) #ds = xr.open_dataset(fpath) #print(ds) # Data is in hydrological years # -> let's just ignore the first and last calendar years #ds.temp.resample(time='AS').mean()[1:-1].plot() plt.show() #workflow.execute_entity_task(tasks.local_t_star, gdirs);
h2 = h2 / np.sum(h2) f, axs = plt.subplots(2, 2, figsize=(9, 8)) axs = np.asarray(axs).flatten() llkw = {'interval': 0} letkm = dict(color='black', ha='right', va='top', fontsize=18, bbox=dict(facecolor='white', edgecolor='black')) xt, yt = 109.3, 1.5 im = graphics.plot_catchment_areas(gdir, ax=axs[0], title='', lonlat_contours_kwargs=llkw, add_scalebar=True) axs[0].text(xt, yt, 'a', **letkm) graphics.plot_catchment_width(gdir, ax=axs[1], title='', add_colorbar=False, lonlat_contours_kwargs=llkw, add_scalebar=False) axs[1].text(xt, yt, 'b', **letkm) graphics.plot_catchment_width(gdir, ax=axs[2],
f, axs = plt.subplots(2, 2, figsize=(8.5, 7)) axs = np.asarray(axs).flatten() llkw = {'interval': 0} letkm = dict(color='black', ha='right', va='top', fontsize=12, bbox=dict(facecolor='white', edgecolor='black')) xt, yt = 109, 2. im = graphics.plot_catchment_areas(gdir, ax=axs[0], title='', lonlat_contours_kwargs=llkw, add_scalebar=True, lines_cmap=LCMAP, mask_cmap=MCMAP) axs[0].text(xt, yt, 'a', **letkm) graphics.plot_catchment_width(gdir, ax=axs[1], title='', add_colorbar=False, lonlat_contours_kwargs=llkw, add_scalebar=False, lines_cmap=LCMAP) axs[1].text(xt, yt, 'b', **letkm)