def plot_radiance_image_strip(
image,
count=5,
ev_steps=-2,
cctf_encoding=COLOUR_STYLE_CONSTANTS.colour.colourspace.cctf_encoding,
**kwargs):
"""
Plots given HDRI / radiance image as strip of images of varying exposure.
Parameters
----------
image : array_like
HDRI / radiance image to plot.
count : int, optional
Strip images count.
ev_steps : numeric, optional
Exposure variation for each image of the strip.
cctf_encoding : callable, optional
Encoding colour component transfer function / opto-electronic
transfer function used for plotting.
Other Parameters
----------------
\\**kwargs : dict, optional
{:func:`colour.plotting.display`},
Please refer to the documentation of the previously listed definition.
Returns
-------
tuple
Current figure and axes.
"""
image = as_float_array(image)
grid = matplotlib.gridspec.GridSpec(1, count)
grid.update(wspace=0, hspace=0)
height, width, _channel = image.shape
for i in range(count):
ev = i * ev_steps
axis = plt.subplot(grid[i])
axis.imshow(np.clip(cctf_encoding(adjust_exposure(image, ev)), 0, 1))
axis.text(width * 0.05,
height - height * 0.05,
'EV {0}'.format(ev),
color=(1, 1, 1))
axis.set_xticks([])
axis.set_yticks([])
axis.set_aspect('equal')
return render(**kwargs)
def radiance_image_strip_plot(image,
count=5,
ev_steps=-2,
encoding_cctf=DEFAULT_PLOTTING_ENCODING_CCTF,
**kwargs):
"""
Plots given HDRI / radiance image as strip of images of varying exposure.
Parameters
----------
image : array_like
HDRI / radiance image to plot.
count : int, optional
Strip images count.
ev_steps : numeric, optional
Exposure variation for each image of the strip.
encoding_cctf : callable, optional
Encoding colour component transfer function / opto-electronic
transfer function used for plotting.
Other Parameters
----------------
\**kwargs : dict, optional
{:func:`colour.plotting.display`},
Please refer to the documentation of the previously listed definition.
Returns
-------
Figure
Current figure or None.
"""
image = np.asarray(image)
grid = matplotlib.gridspec.GridSpec(1, count)
grid.update(wspace=0, hspace=0)
height, width, _channel = image.shape
for i in range(count):
ev = i * ev_steps
axis = matplotlib.pyplot.subplot(grid[i])
axis.imshow(np.clip(encoding_cctf(adjust_exposure(image, ev)), 0, 1))
axis.text(width * 0.05,
height - height * 0.05,
'EV {0}'.format(ev),
color=(1, 1, 1))
axis.set_xticks([])
axis.set_yticks([])
axis.set_aspect('equal')
return display(**kwargs)
def radiance_image_strip_plot(image,
count=5,
ev_steps=-2,
encoding_cctf=DEFAULT_PLOTTING_ENCODING_CCTF,
**kwargs):
"""
Plots given HDRI / radiance image as strip of images of varying exposure.
Parameters
----------
image : array_like
HDRI / radiance image to plot.
count : int, optional
Strip images count.
ev_steps : numeric, optional
Exposure variation for each image of the strip.
encoding_cctf : callable, optional
Encoding colour component transfer function / opto-electronic
transfer function used for plotting.
\**kwargs : dict, optional
Keywords arguments.
Returns
-------
Figure
Current figure or None.
"""
image = np.asarray(image)
grid = matplotlib.gridspec.GridSpec(1, count)
grid.update(wspace=0, hspace=0)
height, width, _channel = image.shape
for i in range(count):
ev = i * ev_steps
axis = matplotlib.pyplot.subplot(grid[i])
axis.imshow(
np.clip(encoding_cctf(adjust_exposure(image, ev)), 0, 1))
axis.text(width * 0.05,
height - height * 0.05,
'EV {0}'.format(ev),
color=(1, 1, 1))
axis.set_xticks([])
axis.set_yticks([])
axis.set_aspect('equal')
return display(**kwargs)
def radiance_image_strip_plot(image,
count=5,
ev_steps=-2,
OECF=DEFAULT_PLOTTING_OECF):
"""
Plots given HDRI / radiance image as strip of images of varying exposure.
Parameters
----------
image : array_like
HDRI / radiance image to plot.
count : int, optional
Strip images count.
ev_steps : numeric, optional
Exposure variation for each image of the strip.
OECF : callable, optional
OECF / opto-electronic conversion function used for plotting.
Returns
-------
bool
Definition success.
"""
image = np.asarray(image)
grid = matplotlib.gridspec.GridSpec(1, count)
grid.update(wspace=0, hspace=0)
height, width, _channel = image.shape
for i in range(count):
ev = i * ev_steps
axis = matplotlib.pyplot.subplot(grid[i])
axis.imshow(
np.clip(OECF(adjust_exposure(image, ev)), 0, 1))
axis.text(width * 0.05,
height - height * 0.05,
'EV {0}'.format(ev),
color=(1, 1, 1))
axis.set_xticks([])
axis.set_yticks([])
axis.set_aspect('equal')
matplotlib.pyplot.show()
return True
