Aug 27, 2016 · Jul 18, 2016 · Jul 18, 2016 · Jul 18, 2016 · Jul 20, 2016 · Aug 16, 2016
diff --git a/examples/api/demo_affine_image.py b/examples/api/demo_affine_image.py
 """
 For the backends thatsupports draw_image with optional affine
 For the backends thatsupport draw_image with optional affine
 transform (e.g., agg, ps backend), the image of the output should
 have its boundarymatches thered rectangles.
 have its boundarymatch thedashed yellow rectangle.
 """

 import numpy as np
 import matplotlib.cm as cm
 import matplotlib.mlab as mlab
 import matplotlib.pyplot as plt
 import matplotlib.transforms as mtransforms
    return Z


 if 1:
 def do_plot(ax, Z, transform):
    im = ax.imshow(Z, interpolation='none',
                   origin='lower',
                   extent=[-2, 4, -3, 2], clip_on=True)

    # image rotation
    trans_data = transform + ax.transData
    im.set_transform(trans_data)

    fig, ax1 = plt.subplots(1, 1)
    Z = get_image()
    im1 = ax1.imshow(Z, interpolation='none',
                     origin='lower',
                     extent=[-2, 4, -3, 2], clip_on=True)
    # 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--",
            transform=trans_data)
    ax.set_xlim(-5, 5)
    ax.set_ylim(-4, 4)

    trans_data2 = mtransforms.Affine2D().rotate_deg(30) + ax1.transData
    im1.set_transform(trans_data2)

    # display intended extent of the image
    x1, x2, y1, y2 = im1.get_extent()
    x3, y3 = x2, y1
 # 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))

    ax1.plot([x1, x2, x2, x1, x1], [y1, y1, y2, y2, y1], "--",
             transform=trans_data2)
 # everything and a translation
 do_plot(ax4, Z, mtransforms.Affine2D().
        rotate_deg(30).skew_deg(30, 15).scale(-1, .5).translate(.5, -1))

    ax1.set_xlim(-3, 5)
    ax1.set_ylim(-4, 4)
 plt.show()
Original file line number	Diff line number	Diff line change
		@@ -1,11 +1,10 @@
		"""
		For the backends thatsupports draw_image with optional affine
		For the backends thatsupport draw_image with optional affine
		transform (e.g., agg, ps backend), the image of the output should
		have its boundarymatches thered rectangles.
		have its boundarymatch thedashed yellow rectangle.
		"""

		import numpy as np
		import matplotlib.cm as cm
		import matplotlib.mlab as mlab
		import matplotlib.pyplot as plt
		import matplotlib.transforms as mtransforms
Expand All		@@ -21,25 +20,37 @@ def get_image():
		return Z


		if 1:
		def do_plot(ax, Z, transform):
		im = ax.imshow(Z, interpolation='none',
		origin='lower',
		extent=[-2, 4, -3, 2], clip_on=True)

		# image rotation
		trans_data = transform + ax.transData
		im.set_transform(trans_data)

		fig, ax1 = plt.subplots(1, 1)
		Z = get_image()
		im1 = ax1.imshow(Z, interpolation='none',
		origin='lower',
		extent=[-2, 4, -3, 2], clip_on=True)
		# 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--",
		transform=trans_data)
		ax.set_xlim(-5, 5)
		ax.set_ylim(-4, 4)

		trans_data2 = mtransforms.Affine2D().rotate_deg(30) + ax1.transData
		im1.set_transform(trans_data2)

		# display intended extent of the image
		x1, x2, y1, y2 = im1.get_extent()
		x3, y3 = x2, y1
		# 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))

		ax1.plot([x1, x2, x2, x1, x1], [y1, y1, y2, y2, y1], "--",
		transform=trans_data2)
		# everything and a translation
		do_plot(ax4, Z, mtransforms.Affine2D().
		rotate_deg(30).skew_deg(30, 15).scale(-1, .5).translate(.5, -1))

		ax1.set_xlim(-3, 5)
		ax1.set_ylim(-4, 4)
		plt.show()