def filter_diff(d, error_filter, error_filter_length):
'''Filter the hap difference array d using the filter of type error_filter.'''
# d is a binary image. Filter genotype errors, manifested as spikes in d
if error_filter == 'median':
return ndimage.median_filter(d, error_filter_length)
# filtered_diff = ndimage.median_filter(d_snps, error_filter_length, mode='constant', cval=0)
elif error_filter == 'fast_max':
center_value = 2 * error_filter_length + 1
window = [1] * center_value
window[error_filter_length] = center_value
f = ndimage.convolve(d, np.array(window, dtype=int))
return ((f > 1) & (f < center_value)).astype('int')
elif error_filter == 'max_except_center':
return util.max_except_center_filter(d, error_filter_length)
else:
raise ValueError('Unsupported error filter ''%s''' % (error_filter,))
def filter_diff(d, error_filter, error_filter_length):
'''Filter the hap difference array d using the filter of type error_filter.'''
# d is a binary image. Filter genotype errors, manifested as spikes in d
if error_filter == 'median':
return ndimage.median_filter(d, error_filter_length)
# filtered_diff = ndimage.median_filter(d_snps, error_filter_length, mode='constant', cval=0)
elif error_filter == 'fast_max':
center_value = 2 * error_filter_length + 1
window = [1] * center_value
window[error_filter_length] = center_value
f = ndimage.convolve(d, np.array(window, dtype=int))
return ((f > 1) & (f < center_value)).astype('int')
elif error_filter == 'max_except_center':
return util.max_except_center_filter(d, error_filter_length)
else:
raise ValueError('Unsupported error filter '
'%s'
'' % (error_filter, ))
def test_filter_max_except_center(self):
'''Custom digitla filter.'''
assert_equal(max_except_center_filter(np.array([0, 0, 1, 0, 0, 1]), 3), [0, 0, 0, 0, 0, 0], 'Wrong custom filter result')
assert_equal(max_except_center_filter(np.array([0, 0, 1, 1, 0, 1]), 5), [0, 0, 1, 1, 0, 1], 'Wrong custom filter result')
def test_filter_max_except_center(self):
'''Custom digitla filter.'''
assert_equal(max_except_center_filter(np.array([0, 0, 1, 0, 0, 1]), 3),
[0, 0, 0, 0, 0, 0], 'Wrong custom filter result')
assert_equal(max_except_center_filter(np.array([0, 0, 1, 1, 0, 1]), 5),
[0, 0, 1, 1, 0, 1], 'Wrong custom filter result')
