Revision: 8099
http://matplotlib.svn.sourceforge.net/matplotlib/?rev=8099&view=rev
Author: leejjoon
Date: 2010-01-28 20:37:46 +0000 (Thu, 28 Jan 2010)
Log Message:
-----------
experimental support of Image._image_skew_coordinate
Modified Paths:
--------------
trunk/matplotlib/lib/matplotlib/image.py
Added Paths:
-----------
trunk/matplotlib/examples/api/demo_affine_image.py
Added: trunk/matplotlib/examples/api/demo_affine_image.py
===================================================================
--- trunk/matplotlib/examples/api/demo_affine_image.py
(rev 0)
+++ trunk/matplotlib/examples/api/demo_affine_image.py 2010-01-28 20:37:46 UTC
(rev 8099)
@@ -0,0 +1,51 @@
+#!/usr/bin/env python
+
+
+"""
+For the backends that supports draw_image with optional affine
+transform (e.g., ps backend), the image of the output should
+have its boundary matches the red rectangles.
+"""
+
+import numpy as np
+import matplotlib.cm as cm
+import matplotlib.mlab as mlab
+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 = mlab.bivariate_normal(X, Y, 1.0, 1.0, 0.0, 0.0)
+ Z2 = mlab.bivariate_normal(X, Y, 1.5, 0.5, 1, 1)
+ Z = Z2-Z1 # difference of Gaussians
+ return Z
+
+def imshow_affine(ax, z, *kl, **kwargs):
+ im = ax.imshow(z, *kl, **kwargs)
+ x1, x2, y1, y2 = im.get_extent()
+ im._image_skew_coordinate = (x2, y1)
+ return im
+
+
+if 1:
+ ax = plt.subplot(111)
+ Z = get_image()
+ im = imshow_affine(ax, Z, interpolation='nearest', cmap=cm.jet,
+ origin='lower', extent=[-2, 4, -3, 2])
+
+ trans_data2 = mtransforms.Affine2D().rotate_deg(30) + ax.transData
+ im.set_transform(trans_data2)
+
+ # display intended extent of the image
+ x1, x2, y1, y2 = im.get_extent()
+ x3, y3 = x2, y1
+
+ ax.plot([x1, x2, x2, x1, x1], [y1, y1, y2, y2, y1], "r--", lw=3,
+ transform=trans_data2)
+
+ ax.set_xlim(-3, 5)
+ ax.set_ylim(-4, 4)
+
+ plt.savefig("demo_affine_image")
Modified: trunk/matplotlib/lib/matplotlib/image.py
===================================================================
--- trunk/matplotlib/lib/matplotlib/image.py 2010-01-28 19:09:20 UTC (rev
8098)
+++ trunk/matplotlib/lib/matplotlib/image.py 2010-01-28 20:37:46 UTC (rev
8099)
@@ -25,6 +25,7 @@
from matplotlib._image import *
from matplotlib.transforms import BboxBase
+import matplotlib.transforms as mtransforms
class _AxesImageBase(martist.Artist, cm.ScalarMappable):
zorder = 0
@@ -96,6 +97,12 @@
self._imcache = None
+ # this is an expetimental attribute, if True, unsampled image
+ # will be drawn using the affine transform that are
+ # appropriately skewed so that the given postition
+ # corresponds to the actual position in the coordinate. -JJL
+ self._image_skew_coordinate = None
+
self.update(kwargs)
def get_size(self):
@@ -204,6 +211,36 @@
return im, xmin, ymin, dxintv, dyintv, sx, sy
+ @staticmethod
+ def _get_rotate_and_skew_transform(x1, y1, x2, y2, x3, y3):
+ """
+ Retuen a transform that does
+ (x1, y1) -> (x1, y1)
+ (x2, y2) -> (x2, y2)
+ (x2, y1) -> (x3, y3)
+
+ It was intended to derive a skew transform that preserve the
+ lower-left corner (x1, y1) and top-right corner(x2,y2), but
+ change the the lower-right-corner(x2, y1) to a new position
+ (x3, y3).
+ """
+ tr1 = mtransforms.Affine2D()
+ tr1.translate(-x1, -y1)
+ x2a, y2a = tr1.transform_point((x2, y2))
+ x3a, y3a = tr1.transform_point((x3, y3))
+
+ inv_mat = 1./(x2a*y3a-y2a*x3a) * np.mat([[y3a, -y2a],[-x3a, x2a]])
+
+ a, b = (inv_mat * np.mat([[x2a], [x2a]])).flat
+ c, d = (inv_mat * np.mat([[y2a], [0]])).flat
+
+ tr2 = mtransforms.Affine2D.from_values(a, c, b, d, 0, 0)
+
+ tr = (tr1 + tr2 + mtransforms.Affine2D().translate(x1,
y1)).inverted().get_affine()
+
+ return tr
+
+
def _draw_unsampled_image(self, renderer, gc):
"""
draw unsampled image. The renderer should support a draw_image method
@@ -227,13 +264,25 @@
im._url = self.get_url()
trans = self.get_transform() #axes.transData
- xx1, yy1 = trans.transform_non_affine((xmin, ymin))
- xx2, yy2 = trans.transform_non_affine((xmin+dxintv, ymin+dyintv))
+ xy = trans.transform_non_affine([(xmin, ymin),
+ (xmin+dxintv, ymin+dyintv)])
+ xx1, yy1 = xy[0]
+ xx2, yy2 = xy[1]
- renderer.draw_image(gc, xx1, yy1, im, xx2-xx1, yy2-yy1,
- trans.get_affine())
+ if self._image_skew_coordinate:
+ # skew the image when required.
+ x_lrc, y_lrc = self._image_skew_coordinate
+ xy = trans.transform_non_affine([(x_lrc, y_lrc)])
+ xx3, yy3 = xy[0]
+ tr_rotate_skew = self._get_rotate_and_skew_transform(xx1, yy1,
xx2, yy2, xx3, yy3)
+ tr = tr_rotate_skew+trans.get_affine()
+ else:
+ tr = trans.get_affine()
+ renderer.draw_image(gc, xx1, yy1, im, xx2-xx1, yy2-yy1, tr)
+
+
def _check_unsampled_image(self, renderer):
"""
return True if the image is better to be drawn unsampled.
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