def test3(self):
import sys
data1 = np.array([[ 0, 0, 0, 0, 0, 0, 0],
[ 0, 0, 0, 0, 0, 0, 0],
[ 0, 1, 1, 1, 1, 1, 0],
[ 0, 0, 0, 0, 0, 0, 0]])
bl1 = np.zeros(data1.shape,np.intc)
np1 = connectedpixels.connectedpixels(data1,bl1,0.1)
data2 = np.array([[ 0, 0, 0, 0, 0, 0, 0],
[ 0, 2, 0, 0, 0, 2, 0],
[ 0, 2, 0, 0, 0, 2, 0],
[ 0, 2, 0, 0, 0, 2, 0]])
bl2 = np.zeros(data2.shape,np.intc)
np2 = connectedpixels.connectedpixels(data2,bl2,0.1)
r1 = connectedpixels.blobproperties(data1, bl1, np1)
r2 = connectedpixels.blobproperties(data2, bl2, np2)
connectedpixels.bloboverlaps(bl1,np1,r1,
bl2,np2,r2, verbose=0)
# check which peaks are zeroed
self.assertAlmostEqual(np.sum(r1[0]),0.,6)
# Results pile up all in r2[0]
self.assertAlmostEqual(np.sum(r2[1]),0.,6)
from ImageD11.connectedpixels import s_1, s_I, s_I2, \
s_fI, s_ffI, s_sI, s_ssI, s_sfI, \
bb_mn_f, bb_mn_s, bb_mx_f, bb_mx_s,\
mx_I, mx_I_f, mx_I_s
self.assertAlmostEqual(r2[0,s_1],11, 6)
self.assertAlmostEqual(r2[0,s_I],17, 6)
def test_2_shapes(self):
for t in [np.uint8, np.int8, np.uint16, np.int16,
np.int32, np.uint32, np.float32, np.float]:
data = np.array( [[ 1, 0, 1, 0, 2, 0, 2],
[ 1, 0, 1, 0, 2, 0, 2],
[ 1, 0, 1, 0, 0, 2, 0],
[ 1, 1, 1, 0, 2, 0, 2]],t)
bl = np.zeros(data.shape,np.int32)
connectedpixels.connectedpixels(
data,
bl,
0.1) # threshold
err = np.sum(np.ravel(data-bl))
self.assertEqual(err, 0)
def skip_test_2_transpose(self):
for t in [np.uint8, np.int8, np.uint16, np.int16,
np.int32, np.uint32, np.float32, np.float]:
data = np.array( [[ 1, 0, 1, 0, 2, 0, 2],
[ 1, 0, 1, 0, 2, 0, 2],
[ 1, 0, 1, 0, 0, 2, 0],
[ 1, 1, 1, 0, 2, 0, 2]],t)
bl = np.zeros(data.shape,np.int32)
self.assertRaises(ValueError,
connectedpixels.connectedpixels,
*(np.transpose(data),bl,0.1))
connectedpixels.connectedpixels(
np.transpose(data),np.transpose(bl),0.1)
err = np.sum(np.ravel(data-bl))
self.assertEqual(err, 0)
def test_find_max(self):
for t in [np.uint8, np.int8, np.uint16, np.int16,
np.int32, np.uint32, np.float32, np.float]:
data = np.array( [[ 1, 0, 1],
[ 1, 0, 1],
[ 1, 8, 1],
[ 1, 1, 1]],t)
bl = np.zeros(data.shape,np.int32)
npx = connectedpixels.connectedpixels(
data,bl,0.1)
self.assertEqual(npx,1)
err = np.sum(np.ravel(data-bl))
self.assertEqual(err, 7) # 8-1
res = connectedpixels.blobproperties(data,
bl,
npx,
omega=22.)
from ImageD11.connectedpixels import s_1, s_I, s_I2, \
s_fI, s_ffI, s_sI, s_ssI, s_sfI, \
bb_mn_f, bb_mn_s, bb_mx_f, bb_mx_s,\
bb_mn_o, bb_mx_o, \
mx_I, mx_I_f, mx_I_s, mx_I_o
# print res,res.shape
self.assertAlmostEqual(res[0][s_1],10)
self.assertAlmostEqual(res[0][mx_I],8)
self.assertAlmostEqual(res[0][mx_I_f],1)
self.assertAlmostEqual(res[0][mx_I_s],2)
self.assertAlmostEqual(res[0][mx_I_o],22)
def test1(self):
import sys
data1 = np.array([[ 1, 0, 1, 0, 0, 0, 0],
[ 1, 0, 1, 0, 0, 0, 0],
[ 1, 0, 1, 1, 0, 0, 0],
[ 1, 1, 1, 0, 0, 0, 0]])
bl1 = np.zeros(data1.shape, np.intc)
np1 = connectedpixels.connectedpixels(data1,bl1,0.1)
data2 = np.array([[ 0, 0, 0, 0, 2, 0, 2],
[ 0, 0, 0, 0, 2, 0, 2],
[ 0, 0, 0, 2, 0, 2, 0],
[ 0, 0, 0, 0, 2, 0, 2]])
bl2 = np.zeros(data2.shape,np.intc)
np2 = connectedpixels.connectedpixels(data2,bl2,0.1)
r1 = connectedpixels.blobproperties(data1, bl1, np1, omega=-10.0)
r2 = connectedpixels.blobproperties(data2, bl2, np2, omega=10.0)
connectedpixels.bloboverlaps(bl1,np1,r1,
bl2,np2,r2, verbose=0)
# check r1 is zeroed
err = np.sum(np.ravel(r1))
self.assertAlmostEqual(err,0.,6)
from ImageD11.connectedpixels import s_1, s_I, s_I2, \
s_fI, s_ffI, s_sI, s_ssI, s_sfI, \
bb_mn_f, bb_mn_s, bb_mx_f, bb_mx_s,\
bb_mn_o, bb_mx_o,\
mx_I, mx_I_f, mx_I_s
# check total pixels
self.assertAlmostEqual(r2[0,s_1], 18.0, 6)
self.assertAlmostEqual(r2[0,s_I], 26.0, 6)
self.assertAlmostEqual(r2[0,bb_mn_f], 0.0, 6)
self.assertAlmostEqual(r2[0,bb_mx_f], 6.0, 6)
self.assertAlmostEqual(r2[0,bb_mn_s], 0.0, 6)
self.assertAlmostEqual(r2[0,bb_mx_s], 3.0, 6)
self.assertAlmostEqual(r2[0,bb_mn_o], -10.0, 6)
self.assertAlmostEqual(r2[0,bb_mx_o], 10.0, 6)
assert np.allclose(drlnew, drlold), (drlold, drlnew, drlv2new)
assert nnew == nold, (nnew, nold)
print nnew, nold
print "Seems that score is OK"
print "Seems that score_and_refine is OK"
print "Seems that score_and_assign is OK"
print "Seems that refine_assigned is OK"
print connectedpixels.s_1
BTYPE = np.intc
a = np.arange(3 * 4).reshape(3, 4).astype(np.float32)
r = np.zeros(a.shape, BTYPE)
npk = connectedpixels.connectedpixels(a, r, 1.01, 1)
print a
print "Pks", npk
print r
# npk = connectedpixels.connectedpixels( a.astype(float), r, 1, 1)
npk = connectedpixels.connectedpixels(a, r, 1.01, 1, 0)
print "Pks", npk
print r
a = np.array([[0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0],
[0, 1, 0, 1, 0, 0, 1, 1, 1, 1, 0, 0, 0, 0, 0],
[0, 0, 1, 0, 0, 0, 1, 0, 0, 0, 1, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 1, 0, 1, 0, 1, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 1, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 1, 1, 1, 1, 0, 0, 0, 0, 1],
[0, 0, 1, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0],
def skip_test_2_transpose(self):
for t in [np.uint8, np.int8, np.uint16, np.int16,
np.int32, np.uint32, np.float32, np.float]:
data = np.array( [[ 1, 0, 1, 0, 2, 0, 2],
[ 1, 0, 1, 0, 2, 0, 2],
[ 1, 0, 1, 0, 0, 2, 0],
[ 1, 1, 1, 0, 2, 0, 2]],t)
bl = np.zeros(data.shape,np.int32)
self.assertRaises(ValueError,
connectedpixels.connectedpixels,
*(np.transpose(data),bl,0.1))
npx = connectedpixels.connectedpixels(
np.transpose(data),np.transpose(bl),0.1)
self.assertEqual(npx,2)
err = np.sum(np.ravel(data-bl))
self.assertEqual(err, 0)
res = connectedpixels.blobproperties(data, bl, npx)
from ImageD11.connectedpixels import s_1, s_I, s_I2, \
s_fI, s_ffI, s_sI, s_ssI, s_sfI, \
bb_mn_f, bb_mn_s, bb_mx_f, bb_mx_s,\
bb_mn_o, bb_mx_o, \
mx_I, mx_I_f, mx_I_s
# print res,res.shape
self.assertAlmostEqual(res[0][s_1],9)
self.assertAlmostEqual(res[1][s_1],7)
self.assertAlmostEqual(res[0][s_I],9)
self.assertAlmostEqual(res[1][s_I],14)
self.assertAlmostEqual(res[0][s_I2],9)
self.assertAlmostEqual(res[1][s_I2],28)
# [[ 1, 0, 1, 0, 2, 0, 2], --> Fast
# [ 1, 0, 1, 0, 2, 0, 2], |
# [ 1, 0, 1, 0, 0, 2, 0], |
# [ 1, 1, 1, 0, 2, 0, 2]],t) V Slow
# f*I:
# f= 0, 1, 2, 3, 4, 5, 6
# [[ 0, 0, 2, 0, 8, 0, 12], --> Fast
# [ 0, 0, 2, 0, 8, 0, 12], |
# [ 0, 0, 2, 0, 0,10, 0 ], |
# [ 0, 1, 2, 0, 8, 0, 12]],t) V Slow
# =9 =70
self.assertAlmostEqual(res[0][s_fI],9)
self.assertAlmostEqual(res[1][s_fI],70)
# s*I:
# s=
# 0[[ 0, 0, 0, 0, 0, 0, 0], --> Fast
# 1 [ 1, 0, 1, 0, 2, 0, 2], |
# 2 [ 2, 0, 2, 0, 0, 4, 0], |
# 3 [ 3, 3, 3, 0, 6, 0, 6]],t) V Slow
# =15 =20
self.assertAlmostEqual(res[0][s_sI],15)
self.assertAlmostEqual(res[1][s_sI],20)
# Bounding box
self.assertAlmostEqual(res[0][bb_mn_f],0)
self.assertAlmostEqual(res[1][bb_mn_f],4)
self.assertAlmostEqual(res[0][bb_mx_f],2)
self.assertAlmostEqual(res[1][bb_mx_f],6)
self.assertAlmostEqual(res[0][bb_mn_s],0)
self.assertAlmostEqual(res[1][bb_mn_s],0)
self.assertAlmostEqual(res[0][bb_mx_s],3)
self.assertAlmostEqual(res[1][bb_mx_s],3)
self.assertAlmostEqual(res[1][bb_mn_o],0)
self.assertAlmostEqual(res[0][bb_mx_o],0)