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)