def main():
fig, ax = plt.subplots(3, 2, figsize=(7, 10))
fig.tight_layout()
if 1:
# Same terrain and data.
data = make_test_data('circles', noise_factor=0.05) * 2 - 7
terrain = data
else:
# Different terrain and data. Matplotlib hill shading can only show the data.
data = make_test_data('hills') * -1
terrain = make_test_data('circles', noise_factor=0.05) * 2
assert terrain.shape == data.shape, "{} != {}".format(terrain.shape, data.shape)
print("data range: {} {}".format(np.min(data), np.max(data)))
if len(sys.argv) > 1:
cmap_name = sys.argv[1]
else:
#cmap_name = 'copper' # from http://matplotlib.org/examples/pylab_examples/shading_example.html?highlight=codex%20shade
#cmap_name = 'gist_earth' # works reasonably fine with all of them
cmap_name = 'bwr' # shows that mpl & pegtop don't work when there is no increasing intensity
#cmap_name = 'cubehelix' # shows that HSV blending does not work were color is black
#cmap_name = 'rainbow' # shows that mpl & pegtop don't work when there is no increasing intensity
#cmap_name = 'Paired_r' # is nice to inspect when the data is different from the terrain
print ("Using colormap: {!r}".format(cmap_name))
cmap = plt.cm.get_cmap(cmap_name)
cmap.set_bad('cyan')
cmap.set_over('cyan')
cmap.set_under('cyan')
abs_max = np.max(np.abs(data)) # force color bar to be symmetrical.
norm = mpl.colors.Normalize(vmin=-abs_max, vmax=abs_max)
#norm = mpl.colors.Normalize(vmin=-2, vmax=3)
draw(ax[0, 0], cmap=cmap, norm=norm, title='No shading',
image_data = data)
draw(ax[0, 1], cmap=plt.cm.gray, title='Matplotlib intensity',
image_data = mpl_surface_intensity(terrain))
ls = LightSource(azdeg=DEF_AZIMUTH, altdeg=DEF_ELEVATION)
draw(ax[1, 0], cmap=cmap, norm=norm, title='Matplotlib hill shading',
image_data = ls.shade(data, cmap=cmap, norm=norm))
draw(ax[1, 1], cmap=cmap, norm=norm, title='Pegtop blending',
image_data = mpl_hill_shade(data, terrain=terrain,
cmap=cmap, norm=norm, blend_function=pegtop_blending))
draw(ax[2, 0], cmap=cmap, norm=norm, title='RGB blending',
image_data = mpl_hill_shade(data, terrain=terrain,
cmap=cmap, norm=norm, blend_function=rgb_blending))
draw(ax[2, 1], cmap=cmap, norm=norm, title='HSV blending',
image_data = mpl_hill_shade(data, terrain=terrain,
cmap=cmap, norm=norm, blend_function=hsv_blending))
plt.show()
def main():
fig, ax = plt.subplots(2, 2, figsize=(10, 10))
fig.tight_layout()
data = make_test_data('circles')
terrain = 10 * make_test_data('hills', noise_factor=0.05)
assert terrain.shape == data.shape, "{} != {}".format(terrain.shape, data.shape)
print("min data: {}".format(np.min(data)))
print("max data: {}".format(np.max(data)))
# Some color maps to try.
#cmap = plt.cm.get_cmap('bwr')
#cmap = plt.cm.get_cmap('CMRmap')
#cmap = plt.cm.get_cmap('rainbow')
#cmap = plt.cm.get_cmap('cool_r')
cmap = plt.cm.get_cmap('Set1')
# Optionally set the over and under flow colors.
#cmap.set_bad('yellow')
#cmap.set_over('cyan')
#cmap.set_under('magenta')
if ['--autoscale'] in sys.argv:
print ("Auto scale legend")
dnorm = mpl.colors.Normalize()
else:
dmin = 0
dmax = 10
print ("clip legend at ({}, {})".format(dmin, dmax))
dnorm = mpl.colors.Normalize(vmin=dmin, vmax=dmax)
# Don't auto scale the intensities, it gives the wrong impression
inorm = mpl.colors.Normalize(vmin=0.0, vmax=1.0)
azimuth = DEF_AZIMUTH
elevation = DEF_ELEVATION
draw(ax[0, 0], cmap=plt.cm.gist_earth, title='Terrain height',
image_data = terrain)
draw(ax[0, 1], cmap=INTENSITY_CMAP, norm=inorm,
title='Shaded terrain (azim = {}, elev = {})'.format(azimuth, elevation),
image_data = hill_shade(terrain, blend_function=no_blending,
azimuth=azimuth, elevation=elevation))
draw(ax[1, 0], cmap=cmap, norm=dnorm, title='Surface properties',
image_data = data)
draw(ax[1, 1], cmap=cmap, norm=dnorm, title='Shaded terrain with surface properties',
image_data = hill_shade(data, terrain=terrain,
azimuth=azimuth, elevation=elevation,
cmap=cmap, norm=dnorm))
plt.show()
def main():
fig, ax = plt.subplots(2, 2, figsize=(10, 10))
fig.tight_layout()
data = -25 * make_test_data('hills',
noise_factor=0.025) # secretly swapped :-)
#data = -25 * make_test_data('circles', noise_factor=0.025) # secretly swapped :-)
terrain = data
assert terrain.shape == data.shape, "{} != {}".format(
terrain.shape, data.shape)
if '--bw' in sys.argv:
# Only intensities
blend_function = no_blending
cmap = INTENSITY_CMAP
# Don't auto scale the intensities, it gives the wrong impression
norm = mpl.colors.Normalize(vmin=0.0, vmax=1.0)
else:
blend_function = rgb_blending
cmap = plt.cm.get_cmap('gist_earth')
norm = mpl.colors.Normalize()
azimuths = [45, 135, 270] # North-East, North-West and South.
elevations = [60] * len(azimuths)
# Draw shading by separate light sources
for idx, (azim, elev) in enumerate(zip(azimuths, elevations)):
row = idx // 2
col = idx % 2
draw(ax[row, col],
cmap=cmap,
norm=norm,
title='azim = {}, elev = {}'.format(azim, elev),
image_data=hill_shade(data,
terrain,
blend_function=blend_function,
ambient_weight=1,
lamp_weight=5,
cmap=cmap,
norm=norm,
azimuth=azim,
elevation=elev))
# Draw shading by all light sources combined
draw(ax[1, 1],
cmap=cmap,
norm=norm,
title='combined'.format(azim, elev),
image_data=hill_shade(data,
terrain,
blend_function=blend_function,
ambient_weight=1,
lamp_weight=[5, 5, 5],
cmap=cmap,
norm=norm,
azimuth=azimuths,
elevation=elevations))
plt.show()
def main():
fig, axes = plt.subplots(1, 1)
# Generate terrain of 200 by 200 km, height between -2.25 and 5.7 km
data = make_test_data('hills', noise_factor=0.05) / 2 + 2
print("data range: {} {}".format(np.min(data), np.max(data)))
cmap = plt.cm.get_cmap('gist_earth')
vmin, vmax = -5, 5 # scale clip color map between -5, 5
rgb = hill_shade(
data,
terrain=data * 5, # scale terrain height to make relief visible
#azimuth=90, elevation=60, # un-comment to use non-default values
#ambient_weight=0, lamp_weight=5, # un-comment to use non-default values
cmap=cmap,
vmin=vmin,
vmax=vmax)
axes.imshow(rgb, norm=None, origin='lower')
add_colorbar(axes,
label='Terrain height [km]',
cmap=cmap,
vmin=vmin,
vmax=vmax)
axes.set_xlabel('[km]')
axes.set_ylabel('[km]')
fig.tight_layout()
plt.show()
def main():
fig, ax = plt.subplots(3, 4, figsize=(15, 10))
fig.tight_layout()
#terrain = make_test_data('circles', noise_factor=0.0)
terrain = make_test_data('hills', noise_factor=0.1)
# Scale terrain.
terrain *= 5
# Don't auto scale the intensities, it gives the wrong impression
inorm = mpl.colors.Normalize(vmin=0.0, vmax=1.0)
# Draw the terrain as color map
draw(ax[0, 0], cmap=plt.cm.gist_earth, title='No shading', ticks=True,
image_data = terrain)
# Draw empty space
ax[1, 0].set_axis_off()
ax[2, 0].set_axis_off()
cmap = INTENSITY_CMAP
azim0_is_east = True # If true, azimuth 0 will correspond to east just as in our implementation
azimuths = [45, 90, 135]
#elev = 50
# At low elevation you will see still noise bumps in places that are completely in the shadows.
# This may seem nice but it is incorrect.
elev = 15
for idx, azim in enumerate(azimuths):
col = idx + 1
draw(ax[0, col], cmap=cmap, norm=inorm,
title="MPL normalized (azim = {}, elev = {})".format(azim, elev),
image_data = mpl_surface_intensity(terrain, azimuth=azim, elevation=elev,
azim0_is_east=azim0_is_east, normalize=True))
draw(ax[1, col], cmap=cmap, norm=inorm,
title="MPL (azim = {}, elev = {})".format(azim, elev),
image_data = mpl_surface_intensity(terrain, azimuth=azim, elevation=elev,
azim0_is_east=azim0_is_east, normalize=False))
draw(ax[2, col], cmap=cmap, norm=inorm,
title="Diffuse (azim = {}, elev = {})".format(azim, elev),
image_data = relative_surface_intensity(terrain, azimuth=azim, elevation=elev))
plt.show()
def main():
fig, ax = plt.subplots(2, 2, figsize=(10, 10))
fig.tight_layout()
data = -25 * make_test_data('hills', noise_factor=0.025) # secretly swapped :-)
#data = -25 * make_test_data('circles', noise_factor=0.025) # secretly swapped :-)
terrain = data
assert terrain.shape == data.shape, "{} != {}".format(terrain.shape, data.shape)
if '--bw' in sys.argv:
# Only intensities
blend_function = no_blending
cmap=INTENSITY_CMAP
# Don't auto scale the intensities, it gives the wrong impression
norm = mpl.colors.Normalize(vmin=0.0, vmax=1.0)
else:
blend_function = rgb_blending
cmap = plt.cm.get_cmap('gist_earth')
norm = mpl.colors.Normalize()
azimuths = [45, 135, 270] # North-East, North-West and South.
elevations = [60] * len(azimuths)
# Draw shading by separate light sources
for idx, (azim, elev) in enumerate(zip(azimuths, elevations)):
row = idx // 2
col = idx % 2
draw(ax[row, col], cmap=cmap, norm=norm,
title='azim = {}, elev = {}'.format(azim, elev),
image_data = hill_shade(data, terrain, blend_function=blend_function,
ambient_weight = 1, lamp_weight = 5,
cmap=cmap, norm=norm,
azimuth=azim, elevation=elev))
# Draw shading by all light sources combined
draw(ax[1, 1], cmap=cmap, norm=norm,
title='combined'.format(azim, elev),
image_data = hill_shade(data, terrain, blend_function=blend_function,
ambient_weight = 1, lamp_weight = [5, 5, 5],
cmap=cmap, norm=norm,
azimuth=azimuths, elevation=elevations))
plt.show()
def main():
fig, axes = plt.subplots(1, 1)
# Generate terrain of 200 by 200 km, height between -2.25 and 5.7 km
data = make_test_data('hills', noise_factor=0.05) / 2 + 2
print("data range: {} {}".format(np.min(data), np.max(data)))
cmap=plt.cm.get_cmap('gist_earth')
vmin, vmax = -5, 5 # scale clip color map between -5, 5
rgb = hill_shade(data, terrain=data * 5, # scale terrain height to make relief visible
#azimuth=90, elevation=60, # un-comment to use non-default values
#ambient_weight=0, lamp_weight=5, # un-comment to use non-default values
cmap=cmap, vmin=vmin, vmax=vmax)
axes.imshow(rgb, norm=None, origin='lower')
add_colorbar(axes, label='Terrain height [km]', cmap=cmap, vmin=vmin, vmax=vmax)
axes.set_xlabel('[km]')
axes.set_ylabel('[km]')
fig.tight_layout()
plt.show()
def main():
fig, ax = plt.subplots(3, 2, figsize=(7, 10))
fig.tight_layout()
if 1:
# Same terrain and data.
data = make_test_data('circles', noise_factor=0.05) * 2 - 7
terrain = data
else:
# Different terrain and data. Matplotlib hill shading can only show the data.
data = make_test_data('hills') * -1
terrain = make_test_data('circles', noise_factor=0.05) * 2
assert terrain.shape == data.shape, "{} != {}".format(
terrain.shape, data.shape)
print("data range: {} {}".format(np.min(data), np.max(data)))
if len(sys.argv) > 1:
cmap_name = sys.argv[1]
else:
#cmap_name = 'copper' # from http://matplotlib.org/examples/pylab_examples/shading_example.html?highlight=codex%20shade
#cmap_name = 'gist_earth' # works reasonably fine with all of them
cmap_name = 'bwr' # shows that mpl & pegtop don't work when there is no increasing intensity
#cmap_name = 'cubehelix' # shows that HSV blending does not work were color is black
#cmap_name = 'rainbow' # shows that mpl & pegtop don't work when there is no increasing intensity
#cmap_name = 'Paired_r' # is nice to inspect when the data is different from the terrain
print("Using colormap: {!r}".format(cmap_name))
cmap = plt.cm.get_cmap(cmap_name)
cmap.set_bad('cyan')
cmap.set_over('cyan')
cmap.set_under('cyan')
abs_max = np.max(np.abs(data)) # force color bar to be symmetrical.
norm = mpl.colors.Normalize(vmin=-abs_max, vmax=abs_max)
#norm = mpl.colors.Normalize(vmin=-2, vmax=3)
draw(ax[0, 0], cmap=cmap, norm=norm, title='No shading', image_data=data)
draw(ax[0, 1],
cmap=plt.cm.gray,
title='Matplotlib intensity',
image_data=mpl_surface_intensity(terrain))
ls = LightSource(azdeg=DEF_AZIMUTH, altdeg=DEF_ELEVATION)
draw(ax[1, 0],
cmap=cmap,
norm=norm,
title='Matplotlib hill shading',
image_data=ls.shade(data, cmap=cmap, norm=norm))
draw(ax[1, 1],
cmap=cmap,
norm=norm,
title='Pegtop blending',
image_data=mpl_hill_shade(data,
terrain=terrain,
cmap=cmap,
norm=norm,
blend_function=pegtop_blending))
draw(ax[2, 0],
cmap=cmap,
norm=norm,
title='RGB blending',
image_data=mpl_hill_shade(data,
terrain=terrain,
cmap=cmap,
norm=norm,
blend_function=rgb_blending))
draw(ax[2, 1],
cmap=cmap,
norm=norm,
title='HSV blending',
image_data=mpl_hill_shade(data,
terrain=terrain,
cmap=cmap,
norm=norm,
blend_function=hsv_blending))
plt.show()
def main():
fig, ax = plt.subplots(3, 4, figsize=(15, 10))
fig.tight_layout()
#terrain = make_test_data('circles', noise_factor=0.0)
terrain = make_test_data('hills', noise_factor=0.1)
# Scale terrain.
terrain *= 5
# Don't auto scale the intensities, it gives the wrong impression
inorm = mpl.colors.Normalize(vmin=0.0, vmax=1.0)
# Draw the terrain as color map
draw(ax[0, 0],
cmap=plt.cm.gist_earth,
title='No shading',
ticks=True,
image_data=terrain)
# Draw empty space
ax[1, 0].set_axis_off()
ax[2, 0].set_axis_off()
cmap = INTENSITY_CMAP
azim0_is_east = True # If true, azimuth 0 will correspond to east just as in our implementation
azimuths = [45, 90, 135]
#elev = 50
# At low elevation you will see still noise bumps in places that are completely in the shadows.
# This may seem nice but it is incorrect.
elev = 15
for idx, azim in enumerate(azimuths):
col = idx + 1
draw(ax[0, col],
cmap=cmap,
norm=inorm,
title="MPL normalized (azim = {}, elev = {})".format(azim, elev),
image_data=mpl_surface_intensity(terrain,
azimuth=azim,
elevation=elev,
azim0_is_east=azim0_is_east,
normalize=True))
draw(ax[1, col],
cmap=cmap,
norm=inorm,
title="MPL (azim = {}, elev = {})".format(azim, elev),
image_data=mpl_surface_intensity(terrain,
azimuth=azim,
elevation=elev,
azim0_is_east=azim0_is_east,
normalize=False))
draw(ax[2, col],
cmap=cmap,
norm=inorm,
title="Diffuse (azim = {}, elev = {})".format(azim, elev),
image_data=relative_surface_intensity(terrain,
azimuth=azim,
elevation=elev))
plt.show()
def main():
fig, ax = plt.subplots(2, 2, figsize=(10, 10))
fig.tight_layout()
data = make_test_data('circles')
terrain = 10 * make_test_data('hills', noise_factor=0.05)
assert terrain.shape == data.shape, "{} != {}".format(
terrain.shape, data.shape)
print("min data: {}".format(np.min(data)))
print("max data: {}".format(np.max(data)))
# Some color maps to try.
#cmap = plt.cm.get_cmap('bwr')
#cmap = plt.cm.get_cmap('CMRmap')
#cmap = plt.cm.get_cmap('rainbow')
#cmap = plt.cm.get_cmap('cool_r')
cmap = plt.cm.get_cmap('Set1')
# Optionally set the over and under flow colors.
#cmap.set_bad('yellow')
#cmap.set_over('cyan')
#cmap.set_under('magenta')
if ['--autoscale'] in sys.argv:
print("Auto scale legend")
dnorm = mpl.colors.Normalize()
else:
dmin = 0
dmax = 10
print("clip legend at ({}, {})".format(dmin, dmax))
dnorm = mpl.colors.Normalize(vmin=dmin, vmax=dmax)
# Don't auto scale the intensities, it gives the wrong impression
inorm = mpl.colors.Normalize(vmin=0.0, vmax=1.0)
azimuth = DEF_AZIMUTH
elevation = DEF_ELEVATION
draw(ax[0, 0],
cmap=plt.cm.gist_earth,
title='Terrain height',
image_data=terrain)
draw(ax[0, 1],
cmap=INTENSITY_CMAP,
norm=inorm,
title='Shaded terrain (azim = {}, elev = {})'.format(
azimuth, elevation),
image_data=hill_shade(terrain,
blend_function=no_blending,
azimuth=azimuth,
elevation=elevation))
draw(ax[1, 0],
cmap=cmap,
norm=dnorm,
title='Surface properties',
image_data=data)
draw(ax[1, 1],
cmap=cmap,
norm=dnorm,
title='Shaded terrain with surface properties',
image_data=hill_shade(data,
terrain=terrain,
azimuth=azimuth,
elevation=elevation,
cmap=cmap,
norm=dnorm))
plt.show()