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