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SF.net SVN: matplotlib:[8472] trunk/matplotlib/lib/matplotlib/image.py
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From: <lee...@us...> - 2010-06-27 02:07:23
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Revision: 8472
http://matplotlib.svn.sourceforge.net/matplotlib/?rev=8472&view=rev
Author: leejjoon
Date: 2010-06-27 02:07:17 +0000 (Sun, 27 Jun 2010)
Log Message:
-----------
_get_unsampled_image now returns a sliced image if possible
Modified Paths:
--------------
trunk/matplotlib/lib/matplotlib/image.py
Modified: trunk/matplotlib/lib/matplotlib/image.py
===================================================================
--- trunk/matplotlib/lib/matplotlib/image.py 2010-06-26 19:29:48 UTC (rev 8471)
+++ trunk/matplotlib/lib/matplotlib/image.py 2010-06-27 02:07:17 UTC (rev 8472)
@@ -24,7 +24,7 @@
# the image namespace:
from matplotlib._image import *
-from matplotlib.transforms import BboxBase
+from matplotlib.transforms import BboxBase, Bbox
import matplotlib.transforms as mtransforms
class _AxesImageBase(martist.Artist, cm.ScalarMappable):
@@ -135,7 +135,7 @@
raise RuntimeError('The make_image method must be overridden.')
- def _get_unsampled_image(self, A, image_extents, viewlim, noslice=False):
+ def _get_unsampled_image(self, A, image_extents, viewlim):
"""
convert numpy array A with given extents ([x1, x2, y1, y2] in
data coordinate) into the Image, given the vielim (should be a
@@ -150,7 +150,7 @@
sx = dxintv/viewlim.width
sy = dyintv/viewlim.height
numrows, numcols = A.shape[:2]
- if noslice is False and sx > 2:
+ if sx > 2:
x0 = (viewlim.x0-xmin)/dxintv * numcols
ix0 = max(0, int(x0 - self._filterrad))
x1 = (viewlim.x1-xmin)/dxintv * numcols
@@ -164,7 +164,7 @@
else:
xslice = slice(0, numcols)
- if noslice is False and sy > 2:
+ if sy > 2:
y0 = (viewlim.y0-ymin)/dyintv * numrows
iy0 = max(0, int(y0 - self._filterrad))
y1 = (viewlim.y1-ymin)/dyintv * numrows
@@ -248,9 +248,57 @@
"""
+ trans = self.get_transform() #axes.transData
+
+ # convert the coordinates to the intermediate coordinate (ic).
+ # The transformation from the ic to the canvas is a pure
+ # affine transfor.
+
+ # A straight-forward way is to use the non-affine part of the
+ # original transform for conversion to the ic.
+
+ # firs, convert the image extent to the ic
+ x_llc, x_trc, y_llc, y_trc = self.get_extent()
+
+ xy = trans.transform_non_affine(np.array([(x_llc, y_llc),
+ (x_trc, y_trc)]))
+
+ _xx1, _yy1 = xy[0]
+ _xx2, _yy2 = xy[1]
+
+ extent_in_ic = _xx1, _xx2, _yy1, _yy2
+
+ # define trans_ic_to_canvas : unless _image_skew_coordinate is
+ # set, it is simply a affine part of the original transform.
+ if self._image_skew_coordinate:
+ # skew the image when required.
+ x_lrc, y_lrc = self._image_skew_coordinate
+ xy2 = trans.transform_non_affine(np.array([(x_lrc, y_lrc)]))
+ _xx3, _yy3 = xy2[0]
+
+ tr_rotate_skew = self._get_rotate_and_skew_transform(_xx1, _yy1,
+ _xx2, _yy2,
+ _xx3, _yy3)
+ trans_ic_to_canvas = tr_rotate_skew+trans.get_affine()
+ else:
+ trans_ic_to_canvas = trans.get_affine()
+
+ # Now, viewLim in the ic. It can be roated and can be
+ # skewed. Make it big enough.
+ x1, y1, x2, y2 = self.axes.bbox.extents
+ trans_canvas_to_ic = trans_ic_to_canvas.inverted()
+ xy_ = trans_canvas_to_ic.transform(np.array([(x1, y1),
+ (x2, y1),
+ (x2, y2),
+ (x1, y2)]))
+ x1_, x2_ = min(xy_[:,0]), max(xy_[:,0])
+ y1_, y2_ = min(xy_[:,1]), max(xy_[:,1])
+ viewLim_in_ic = Bbox.from_extents(x1_, y1_, x2_, y2_)
+
+
+ # get the image, sliced if necessary. This is done in the ic.
im, xmin, ymin, dxintv, dyintv, sx, sy = \
- self._get_unsampled_image(self._A, self.get_extent(),
- self.axes.viewLim, noslice=True)
+ self._get_unsampled_image(self._A, extent_in_ic, viewLim_in_ic)
if im is None: return # I'm not if this check is required. -JJL
@@ -262,35 +310,16 @@
im.reset_matrix()
numrows, numcols = im.get_size()
- im.resize(numcols, numrows) # just to create im.bufOut that is required by backends. There may be better solution -JJL
+ im.resize(numcols, numrows) # just to create im.bufOut that
+ # is required by backends. There
+ # may be better solution -JJL
im._url = self.get_url()
- trans = self.get_transform() #axes.transData
- xy = trans.transform_non_affine(np.array([(xmin, ymin),
- (xmin+dxintv, ymin+dyintv)]))
- xx1, yy1 = xy[0]
- xx2, yy2 = xy[1]
+ renderer.draw_image(gc, xmin, ymin, im, dxintv, dyintv,
+ trans_ic_to_canvas)
- if self._image_skew_coordinate:
- # skew the image when required.
- x_llc, x_trc, y_llc, y_trc = self.get_extent()
- x_lrc, y_lrc = self._image_skew_coordinate
- xy = trans.transform_non_affine(np.array([(x_llc, y_llc),
- (x_trc, y_trc),
- (x_lrc, y_lrc)]))
- _xx1, _yy1 = xy[0]
- _xx2, _yy2 = xy[1]
- _xx3, _yy3 = xy[2]
- 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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