def plot_eigenvectors(eigenvectors, num_components, sz, filename=None, start_component=0, rows=None, cols=None, title="Subplot", color=True): if (rows is None) or (cols is None): rows = cols = int(math.ceil(np.sqrt(num_components))) num_components = np.min(num_components, eigenvectors.shape[1]) fig = plt.figure() for i in range(start_component, num_components): vi = eigenvectors[0:, i].copy() vi = minmax(np.asarray(vi), 0, 255, dtype=np.uint8) vi = vi.reshape(sz) ax0 = fig.add_subplot(rows, cols, (i - start_component) + 1) plt.setp(ax0.get_xticklabels(), visible=False) plt.setp(ax0.get_yticklabels(), visible=False) plt.title("%s #%d" % (title, i), create_font('Tahoma', 10)) if color: implot = plt.imshow(np.asarray(vi)) else: implot = plt.imshow(np.asarray(vi), cmap=cm.grey) if filename is None: fig.show() else: fig.savefig(filename, format="png", transparent=False)
def plot_gray(X, sz=None, filename=None): if not sz is None: X = X.reshape(sz) X = minmax(I, 0, 255) fig = plt.figure() implot = plt.imshow(np.asarray(Ig), cmap=cm.gray) if filename is None: plt.show() else: fig.savefig(filename, format="png", transparent=False)