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add test/

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This commit is contained in:
Olivier Debeir
2012-10-04 16:09:56 +02:00
parent 9a7d9cd161
commit 9788400f1f
6 changed files with 104 additions and 105 deletions
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skimage/rank/__init__.py
+1 -1
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@@ -1 +1 @@
from .rank import *
from .crank import *
skimage/rank/core.pxd
-1
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@@ -18,7 +18,6 @@ from libc.stdlib cimport malloc, free
cdef inline int int_max(int a, int b): return a if a >= b else b
cdef inline int int_min(int a, int b): return a if a <= b else b
#---------------------------------------------------------------------------
# 8 bit core kernel
#---------------------------------------------------------------------------
skimage/rank/test/test_16bitbilateral.py
+23
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@@ -0,0 +1,23 @@
import numpy as np
import matplotlib.pyplot as plt
from skimage import data
from skimage.rank import crank_percentiles,crank16_bilateral
if __name__ == '__main__':
a8 = (data.coins()).astype('uint8')
a16 = (data.coins()).astype('uint16')*16
selem = np.ones((20,20),dtype='uint8')
f1 = crank_percentiles.mean(a8,selem = selem,p0=.1,p1=.9)
f2 = crank16_bilateral.mean(a16,selem = selem,bitdepth=12,s0=500,s1=500)
plt.figure()
plt.imshow(np.hstack((a8,f1)))
plt.colorbar()
plt.figure()
plt.imshow(np.hstack((a16,f2)))
plt.colorbar()
plt.show()
skimage/rank/test/test_benchmark.py
+72
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@@ -0,0 +1,72 @@
import numpy as np
import matplotlib.pyplot as plt
from skimage import data
from skimage.morphology import cmorph
from skimage.rank import crank
from tools import log_timing
@log_timing
def cr_max(image,selem):
return crank.maximum(image=image,selem = selem)
@log_timing
def cm_dil(image,selem):
return cmorph.dilate(image=image,selem = selem)
def compare():
"""comparison between
- crank.maximum rankfilter implementation
- cmorph.dilate cython implementation
on increasing structuring element size and increasing image size
"""
# a = (np.random.random((500,500))*256).astype('uint8')
a = data.camera()
rec = []
e_range = range(1,20,1)
for r in e_range:
elem = np.ones((r,r),dtype='uint8')
# elem = (np.random.random((r,r))>.5).astype('uint8')
rc,ms_rc = cr_max(a,elem)
rcm,ms_rcm = cm_dil(a,elem)
rec.append((ms_rc,ms_rcm))
# check if results are identical
assert (rc==rcm).all()
rec = np.asarray(rec)
plt.figure()
plt.title('increasing element size')
plt.plot(e_range,rec)
plt.legend(['crank.maximum','cmorph.dilate'])
plt.figure()
plt.imshow(np.hstack((rc,rcm)))
r = 9
elem = np.ones((r,r),dtype='uint8')
rec = []
s_range = range(100,1000,100)
for s in s_range:
a = (np.random.random((s,s))*256).astype('uint8')
(rc,ms_rc) = cr_max(a,elem)
(rcm,ms_rcm) = cm_dil(a,elem)
rec.append((ms_rc,ms_rcm))
assert (rc==rcm).all()
rec = np.asarray(rec)
plt.figure()
plt.title('increasing image size')
plt.plot(s_range,rec)
plt.legend(['crank.maximum','cmorph.dilate'])
plt.figure()
plt.imshow(np.hstack((rc,rcm)))
plt.show()
if __name__ == '__main__':
compare()
skimage/rank/app.py → skimage/rank/test/test_suite.py
+8 -93
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@@ -1,73 +1,10 @@
import unittest
import numpy as np
from time import time
import matplotlib.pyplot as plt
from skimage import data
from tools import log_timing,init_logger
from skimage.rank import crank,crank16,crank16_bilateral,crank16_percentiles,crank_percentiles
from skimage.morphology import cmorph
import crank
import crank16
import crank_percentiles
import crank16_percentiles
import crank16_bilateral
from cmorph import dilate
@log_timing
def c_max(image,selem):
return crank.maximum(image=image,selem = selem)
@log_timing
def cm_max(image,selem):
return dilate(image=image,selem = selem)
def compare():
"""comparison between
- Cython maximum rankfilter implementation
- weaves maximum rankfilter implementation
- cmorph.dilate cython implementation
on increasing structuring element size and increasing image size
"""
a = (np.random.random((500,500))*256).astype('uint8')
rec = []
for r in range(1,20,1):
elem = np.ones((r,r),dtype='uint8')
# elem = (np.random.random((r,r))>.5).astype('uint8')
(rc,ms_rc) = c_max(a,elem)
(rcm,ms_rcm) = cm_max(a,elem)
rec.append((ms_rc,ms_rw,ms_rcm))
assert (rc==rcm).all()
rec = np.asarray(rec)
plt.plot(rec)
plt.legend(['sliding cython','sliding weaves','cmorph'])
plt.figure()
plt.imshow(np.hstack((rc,rw,rcm)))
r = 9
elem = np.ones((r,r),dtype='uint8')
rec = []
for s in range(100,1000,100):
a = (np.random.random((s,s))*256).astype('uint8')
(rc,ms_rc) = c_max(a,elem)
(rcm,ms_rcm) = cm_max(a,elem)
rec.append((ms_rc,ms_rw,ms_rcm))
assert (rc==rcm).all()
rec = np.asarray(rec)
plt.figure()
plt.plot(rec)
plt.legend(['sliding cython','sliding weaves','cmorph'])
plt.figure()
plt.imshow(np.hstack((rc,rcm)))
plt.show()
class TestSequenceFunctions(unittest.TestCase):
def setUp(self):
@@ -106,7 +43,7 @@ class TestSequenceFunctions(unittest.TestCase):
elem = np.ones((r,r),dtype='uint8')
# elem = (np.random.random((r,r))>.5).astype('uint8')
rc = crank.maximum(image=a,selem = elem)
cm = dilate(image=a,selem = elem)
cm = cmorph.dilate(image=a,selem = elem)
self.assertTrue((rc==cm).all())
def test_bitdepth(self):
@@ -139,11 +76,11 @@ class TestSequenceFunctions(unittest.TestCase):
elem = np.asarray([[1,1,0],[1,1,1],[0,0,1]],dtype='uint8')
f = crank.maximum(image=a,selem = elem,shift_x=1,shift_y=1)
r = np.asarray([[ 0, 0, 0, 0, 0, 0],
[ 0, 0, 0, 0, 0, 0],
[ 0, 0, 255, 0, 0, 0],
[ 0, 0, 255, 255, 255, 0],
[ 0, 0, 0, 255, 255, 0],
[ 0, 0, 0, 0, 0, 0]])
[ 0, 0, 0, 0, 0, 0],
[ 0, 0, 255, 0, 0, 0],
[ 0, 0, 255, 255, 255, 0],
[ 0, 0, 0, 255, 255, 0],
[ 0, 0, 0, 0, 0, 0]])
np.testing.assert_array_equal(r,f)
@@ -156,27 +93,5 @@ class TestSequenceFunctions(unittest.TestCase):
if __name__ == '__main__':
logger = init_logger('app.log')
# unittest.main()
suite = unittest.TestLoader().loadTestsFromTestCase(TestSequenceFunctions)
unittest.TextTestRunner(verbosity=2).run(suite)
# compare()
# a = (data.coins()).astype('uint8')
a8 = (data.coins()).astype('uint8')
a = (data.coins()).astype('uint16')*16
selem = np.ones((20,20),dtype='uint8')
# f1 = filter.soft_gradient(a,struct_elem = selem,bitDepth=8,infSup=[.1,.9])
# f2 = crank16.bottomhat(a,selem = selem,bitdepth=12)
f1 = crank_percentiles.mean(a8,selem = selem,p0=.1,p1=.9)
# f2 = crank16_percentiles.mean(a,selem = selem,bitdepth=12,p0=.1,p1=.9)
f2 = crank16_bilateral.mean(a,selem = selem,bitdepth=12,s0=500,s1=500)
# plt.imshow(f2)
plt.imshow(np.hstack((a,f2)))
plt.colorbar()
plt.show()
skimage/rank/tools.py → skimage/rank/test/tools.py
-10
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@@ -39,14 +39,4 @@ def log_timing(func):
log_timing.level = 0
def tumbnail_it(data):
"""display image with its histogram
"""
h = np.histogram(data[:],100)
hn = 512*h[0]/np.max(h[0])
plt.subplot(1,2,1)
plt.imshow(ima8,interpolation='nearest',cmap=cm.gray)
plt.subplot(1,2,2)
plt.plot(hn)
plt.colorbar()