Affine transform of an image

Prepending an affine transformation (Affine2D) to the data transform of an image allows to manipulate the image's shape and orientation. This is an example of the concept of transform chaining.

The image of the output should have its boundary match the dashed yellow rectangle.

import numpy as np
import matplotlib.pyplot as plt
import matplotlib.transforms as mtransforms

def get_image():
    delta = 0.25
    x = y = np.arange(-3.0, 3.0, delta)
    X, Y = np.meshgrid(x, y)
    Z1 = np.exp(-X**2 - Y**2)
    Z2 = np.exp(-(X - 1)**2 - (Y - 1)**2)
    Z = (Z1 - Z2)
    return Z

def do_plot(ax, Z, transform):
    im = ax.imshow(Z, interpolation='none',
                   extent=[-2, 4, -3, 2], clip_on=True)

    trans_data = transform + ax.transData

    # display intended extent of the image
    x1, x2, y1, y2 = im.get_extent()
    ax.plot([x1, x2, x2, x1, x1], [y1, y1, y2, y2, y1], "y--",
    ax.set_xlim(-5, 5)
    ax.set_ylim(-4, 4)

# prepare image and figure
fig, ((ax1, ax2), (ax3, ax4)) = plt.subplots(2, 2)
Z = get_image()

# image rotation
do_plot(ax1, Z, mtransforms.Affine2D().rotate_deg(30))

# image skew
do_plot(ax2, Z, mtransforms.Affine2D().skew_deg(30, 15))

# scale and reflection
do_plot(ax3, Z, mtransforms.Affine2D().scale(-1, .5))

# everything and a translation
do_plot(ax4, Z, mtransforms.Affine2D().
        rotate_deg(30).skew_deg(30, 15).scale(-1, .5).translate(.5, -1))
affine image


The use of the following functions, methods and classes is shown in this example:

Keywords: matplotlib code example, codex, python plot, pyplot Gallery generated by Sphinx-Gallery