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)
def test_catch_areas():
fig, ax = plt.subplots()
gdir = init_hef()
graphics.plot_catchment_areas(gdir, ax=ax)
fig.tight_layout()
return fig
