def test_circle_se():
from mahotas.morph import circle_se
for r in (4, 5):
c = circle_se(r)
assert len(c) == (2 * r + 1)
assert len(c) == len(c.T)
assert not c.all()
assert c.any()
with pytest.raises(ValueError):
circle_se(-1)
def bernsen(f, radius, contrast_threshold, gthresh=None):
'''
thresholded = bernsen(f, radius, contrast_threshold, gthresh={128})
Bernsen local thresholding
Parameters
----------
f : ndarray
input image
radius : integer
radius of circle (to consider "local")
contrast_threshold : integer
contrast threshold
gthresh : numeric, optional
global threshold to fall back in low contrast regions
Returns
-------
thresholded : binary ndarray
See Also
--------
gbernsen : function
Generalised Bernsen thresholding
'''
from mahotas.morph import circle_se
if gthresh is None:
gthresh = 128
return gbernsen(f, circle_se(radius), contrast_threshold, gthresh)
def bernsen(f, radius, contrast_threshold, gthresh=None):
'''
thresholded = bernsen(f, radius, contrast_threshold, gthresh={128})
Bernsen local thresholding
Parameters
----------
f : ndarray
input image
radius : integer
radius of circle (to consider "local")
contrast_threshold : integer
contrast threshold
gthresh : numeric, optional
global threshold to fall back in low contrast regions
Returns
-------
thresholded : binary ndarray
See Also
--------
gbernsen : function
Generalised Bernsen thresholding
'''
from mahotas.morph import circle_se
if gthresh is None:
gthresh = 128
return gbernsen(f, circle_se(radius), contrast_threshold, gthresh)
def test_circle_se():
from mahotas.morph import circle_se
for r in (4,5):
c = circle_se(r)
assert len(c) == (2*r + 1)
assert len(c) == len(c.T)
assert not c.all()
assert c.any()
@raises(ValueError)
def circle_1():
circle_se(-1)
circle_1()
def circle_1():
circle_se(-1)
def circle_1():
circle_se(-1)
