def get_rgb(): Z, extent = get_demo_image() Z[Z<0] = 0. Z = Z/Z.max() R = Z[:13,:13] G = Z[2:,2:] B = Z[:13,2:] return R, G, B
def demo_images_side_by_sied(ax): from mpl_toolkits.axes_grid import make_axes_locatable divider = make_axes_locatable(ax) Z, extent = get_demo_image() ax2 = divider.new_horizontal(size="100%", pad=0.05) fig1 = ax.get_figure() fig1.add_axes(ax2) ax.imshow(Z, extent=extent, interpolation="nearest") ax2.imshow(Z, extent=extent, interpolation="nearest") for tl in ax2.get_yticklabels(): tl.set_visible(False)
def demo_locatable_axes_easy(ax): from mpl_toolkits.axes_grid import make_axes_locatable divider = make_axes_locatable(ax) ax_cb = divider.new_horizontal(size="5%", pad=0.05) fig1 = ax.get_figure() fig1.add_axes(ax_cb) Z, extent = get_demo_image() im = ax.imshow(Z, extent=extent, interpolation="nearest") plt.colorbar(im, cax=ax_cb) ax_cb.yaxis.tick_right() for tl in ax_cb.get_yticklabels(): tl.set_visible(False) ax_cb.yaxis.tick_right()
def demo_simple_grid(fig): """ A grid of 2x2 images with 0.05 inch pad between images and only the lower-left axes is labeld. """ grid = AxesGrid(fig, 131, # similar to subplot(131) nrows_ncols = (2, 2), axes_pad = 0.05, label_mode = "1", ) Z, extent = get_demo_image() for i in range(4): im = grid[i].imshow(Z, extent=extent, interpolation="nearest") grid.axes_llc.set_xticks([-2, 0, 2]) grid.axes_llc.set_yticks([-2, 0, 2])
def demo_grid_with_single_cbar(fig): """ A grid of 2x2 images with a single colobar """ grid = AxesGrid(fig, 132, # similar to subplot(132) nrows_ncols = (2, 2), axes_pad = 0.0, share_all=True, label_mode = "L", cbar_mode="single", ) Z, extent = get_demo_image() for i in range(4): im = grid[i].imshow(Z, extent=extent, interpolation="nearest") plt.colorbar(im, cax = grid.cbar_axes[0]) grid.cbar_axes[0].colorbar(im) grid.axes_llc.set_xticks([-2, 0, 2]) grid.axes_llc.set_yticks([-2, 0, 2])
def demo_grid_with_each_cbar(fig): """ A grid of 2x2 images. Each image has its own colobar. """ grid = AxesGrid(F, 133, # similar to subplot(122) nrows_ncols = (2, 2), axes_pad = 0.1, label_mode = "1", share_all = True, cbar_location="top", cbar_mode="each", cbar_size="7%", cbar_pad="2%", ) Z, extent = get_demo_image() for i in range(4): im = grid[i].imshow(Z, extent=extent, interpolation="nearest") grid.cbar_axes[i].colorbar(im) grid.axes_llc.set_xticks([-2, 0, 2]) grid.axes_llc.set_yticks([-2, 0, 2])
def demo_locatable_axes_hard(fig1): from mpl_toolkits.axes_grid \ import SubplotDivider, LocatableAxes, Size divider = SubplotDivider(fig1, 2, 2, 2, aspect=True) ax = LocatableAxes(fig1, divider.get_position()) ax_cb = LocatableAxes(fig1, divider.get_position()) h = [Size.AxesX(ax), # main axes Size.Fixed(0.05), # padding, 0.1 inch Size.Fixed(0.2), # colorbar, 0.3 inch ] v = [Size.AxesY(ax)] divider.set_horizontal(h) divider.set_vertical(v) ax.set_axes_locator(divider.new_locator(nx=0, ny=0)) ax_cb.set_axes_locator(divider.new_locator(nx=2, ny=0)) fig1.add_axes(ax) fig1.add_axes(ax_cb) ax_cb.axis["left"].toggle(all=False) ax_cb.axis["right"].toggle(ticks=True) Z, extent = get_demo_image() im = ax.imshow(Z, extent=extent, interpolation="nearest") plt.colorbar(im, cax=ax_cb) plt.setp(ax_cb.get_yticklabels(), visible=False)
import matplotlib.pyplot as plt from mpl_toolkits.axes_grid.inset_locator import zoomed_inset_axes from mpl_toolkits.axes_grid.inset_locator import mark_inset import numpy as np from mpl_toolkits.axes_grid.demo_image import get_demo_image fig = plt.figure(1, [5,4]) ax = fig.add_subplot(111) Z, extent = get_demo_image() Z2 = np.zeros([150, 150], dtype="d") ny, nx = Z.shape Z2[30:30+ny, 30:30+nx] = Z ax.imshow(Z2, extent=extent, interpolation="nearest", origin="lower") axins = zoomed_inset_axes(ax, 6, loc=1) # zoom = 6 axins.imshow(Z2, extent=extent, interpolation="nearest", origin="lower") x1, x2, y1, y2 = -1.5, -0.9, -2.5, -1.9 axins.set_xlim(x1, x2) axins.set_ylim(y1, y2) plt.xticks(visible=False) plt.yticks(visible=False) mark_inset(ax, axins, loc1=2, loc2=4, fc="none", ec="0.5") plt.draw() plt.show()
def demo_simple_image(ax): Z, extent = get_demo_image() im = ax.imshow(Z, extent=extent, interpolation="nearest") cb = plt.colorbar(im) plt.setp(cb.ax.get_yticklabels(), visible=False)