Revision: 8211
http://matplotlib.svn.sourceforge.net/matplotlib/?rev=8211&view=rev
Author: leejjoon
Date: 2010-03-23 17:23:50 +0000 (Tue, 23 Mar 2010)
Log Message:
-----------
remove scipy dependency in examples/pylab_examples/demo_agg_filter.py
Modified Paths:
--------------
trunk/matplotlib/examples/pylab_examples/demo_agg_filter.py
Modified: trunk/matplotlib/examples/pylab_examples/demo_agg_filter.py
===================================================================
--- trunk/matplotlib/examples/pylab_examples/demo_agg_filter.py 2010-03-22
16:47:27 UTC (rev 8210)
+++ trunk/matplotlib/examples/pylab_examples/demo_agg_filter.py 2010-03-23
17:23:50 UTC (rev 8211)
@@ -1,11 +1,30 @@
import matplotlib.pyplot as plt
import numpy as np
-import scipy.ndimage as NI
import matplotlib.cm as cm
import matplotlib.mlab as mlab
+def smooth1d(x, window_len):
+ # copied from http://www.scipy.org/Cookbook/SignalSmooth
+ s=np.r_[2*x[0]-x[window_len:1:-1],x,2*x[-1]-x[-1:-window_len:-1]]
+ w = np.hanning(window_len)
+ y=np.convolve(w/w.sum(),s,mode='same')
+ return y[window_len-1:-window_len+1]
+
+def smooth2d(A, sigma=3):
+
+ window_len = max(int(sigma), 3)*2+1
+ A1 = np.array([smooth1d(x, window_len) for x in np.asarray(A)])
+ A2 = np.transpose(A1)
+ A3 = np.array([smooth1d(x, window_len) for x in A2])
+ A4 = np.transpose(A3)
+
+ return A4
+
+
+
+
class BaseFilter(object):
def prepare_image(self, src_image, dpi, pad):
ny, nx, depth = src_image.shape
@@ -58,8 +77,9 @@
def process_image(self, padded_src, dpi):
#offsetx, offsety = int(self.offsets[0]), int(self.offsets[1])
tgt_image = np.zeros_like(padded_src)
- tgt_image[:,:,-1] = NI.gaussian_filter(padded_src[:,:,-1]*self.alpha,
- self.sigma)
+ aa = smooth2d(padded_src[:,:,-1]*self.alpha,
+ self.sigma)
+ tgt_image[:,:,-1] = aa
tgt_image[:,:,:-1] = self.color
return tgt_image
@@ -123,7 +143,7 @@
alpha = new_im[:,:,3]
alpha.fill(0)
alpha[pad:-pad, pad:-pad] = im[:,:,-1]
- alpha2 = NI.grey_dilation(alpha, size=(self.pixels, self.pixels))
+ alpha2 = np.clip(smooth2d(alpha, self.pixels) * 5, 0, 1)
new_im[:,:,-1] = alpha2
new_im[:,:,:-1] = self.color
offsetx, offsety = -pad, -pad
@@ -208,7 +228,7 @@
mec="r", mfc="w", lw=5, mew=3, ms=10, label="Line 1")
- gauss = DropShadowFilter(2)
+ gauss = DropShadowFilter(4)
for l in [l1, l2]:
@@ -257,7 +277,7 @@
rects2 = ax.bar(ind+width+0.1, womenMeans, width, color='y', ec="w", lw=2)
#gauss = GaussianFilter(1.5, offsets=(1,1), )
- gauss = DropShadowFilter(1.5, offsets=(1,1), )
+ gauss = DropShadowFilter(5, offsets=(1,1), )
shadow = FilteredArtistList(rects1+rects2, gauss)
ax.add_artist(shadow)
shadow.set_zorder(rects1[0].get_zorder()-0.1)
@@ -275,21 +295,21 @@
pies = ax.pie(fracs, explode=explode)
ax.patch.set_visible(True)
- light_filter = LightFilter(8)
+ light_filter = LightFilter(9)
for p in pies[0]:
p.set_agg_filter(light_filter)
p.set_rasterized(True) # to support mixed-mode renderers
p.set(ec="none",
lw=2)
- gauss = DropShadowFilter(3, offsets=(3,4), alpha=0.7)
+ gauss = DropShadowFilter(9, offsets=(3,4), alpha=0.7)
shadow = FilteredArtistList(pies[0], gauss)
ax.add_artist(shadow)
shadow.set_zorder(pies[0][0].get_zorder()-0.1)
if 1:
-
+
plt.figure(1, figsize=(6, 6))
plt.subplots_adjust(left=0.05, right=0.95)
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