def _render_background(self, fullpath_to_raster):
"""
Renders the background image that
will form the drape plot, e.g. a hillshade
"""
if self._backgroundtype == "Hillshade":
self.Hillshade = LSDP.Hillshade(self.fullpath_to_raster)
self.colourmap = "gray"
elif self._backgroundtype == "Terrain":
self.Hillshade = LSDP.ReadRasterArrayBlocks(
self.fullpath_to_raster)
self.colourmap = LSDP.colours.UsefulColourmaps.niceterrain
#self.colourmap = LSDP.colours.UsefulColourmaps.darkearth
#self.colourmap = "terrain"
else:
print ("That background style is not yet supported. Currently only " \
" 'Hillshade' and 'Terrain' are supported.")
def MultiDrapeMaps(DataDir, ElevationRaster, DrapeRasterWild, cmap, drape_min_threshold=None, drape_max=None):
"""
Plots flood extents from water depth rasters
draped over the catchment elevation raster
in a series of subplots
Takes a wildcard for the drapes
Expexts a fixed elevation raster, but this could be
modified in future.
Thought: consider, if plotting multiple datasets, how you
are going to deal with min a max values in the colur range.
imshow will automatically set vmin and vmax and stretch the colour bar
over this - which can be visually misleading. Ideally, you
want to have the same colour map used for *all* subplots, and
this is not default behaviour.
"""
f, ax_arr = plt.subplots(2, 2, figsize=(10, 5), sharex=True, sharey=True)
ax_arr = ax_arr.ravel()
FPFiles = sorted(glob.glob(DataDirectory+DrapeRasterWild), key=str)
n_files = len(FPFiles)
print("Number of files = ", n_files)
elev_raster_file = DataDir + ElevationRaster
hillshade = LSDP.Hillshade(elev_raster_file)
#hillshade_array = LSDP.ReadRasterArrayBlocks(elev_raster_file)
# now get the extent
extent_raster = LSDP.GetRasterExtent(elev_raster_file)
x_min = extent_raster[0]
x_max = extent_raster[1]
y_min = extent_raster[2]
y_max = extent_raster[3]
# now get the tick marks
n_target_tics = 5
xlocs,ylocs,new_x_labels,new_y_labels = LSDP.GetTicksForUTM(elev_raster_file,x_max,x_min,y_max,y_min,n_target_tics)
print("xmax: " + str(x_max))
print("xmin: " + str(x_min))
print("ymax: " + str(y_max))
print("ymin: " + str(y_min))
"""
Find the maximum water depth in all rasters.
You need this to normalize the colourscale accross
all plots when teh imshow is done later.
"""
try:
print("Calculating max drape raster value by scanning rasters...")
max_water_depth = findmaxval_multirasters(FPFiles)
drape_max = max_water_depth
except:
print("Something went wrong trying to obtain the max value in \
your drape raster file list.")
finally:
print("The drape(s) max value is set to: ", drape_max)
for i in range(n_files):
print("The floodplain file name is: ", FPFiles[i])
FP_raster = LSDP.ReadRasterArrayBlocks(FPFiles[i])
#FP_raster = np.ma.masked_where(FP_raster <= 0, FP_raster)
filename = os.path.basename(FPFiles[i])
title = mplext.labels.make_line_label(filename)
print(title)
low_values_index = FP_raster < drape_min_threshold
FP_raster[low_values_index] = np.nan
im = ax_arr[i].imshow(hillshade, "gray", extent=extent_raster, interpolation="nearest")
"""
Now we can set vmax to be the maximum water depth we calcualted earlier, making our separate
subplots all have the same colourscale
"""
im = ax_arr[i].imshow(FP_raster, cmap, extent=extent_raster,
alpha=1.0, interpolation="none",
vmin=drape_min_threshold,
vmax=drape_max)
ax_arr[i].set_title(title)
f.subplots_adjust(right=0.8)
cax = f.add_axes([0.9, 0.1, 0.03, 0.8])
cbar = f.colorbar(im, cax=cax)
cbar.set_label("Water depth (m)")
#cbar.set_ticks(np.linspace(0, 8, 8))
#cbar = mplext.colours.colorbar_index(f, cax, 8, cmap,
# drape_min_threshold, drape_max)
cbar.set_label("Water depth (m)")
#tick_locator = ticker.MaxNLocator(nbins=8)
#cbar.locator = tick_locator
#cbar.update_ticks()
f.text(0.5, 0.04, 'Easting (m)', ha='center')
f.text(0.04, 0.5, 'Northing (m)', va='center', rotation='vertical')
