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unwrap: Refactor wrap_around argument.

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This commit is contained in:
Jostein Bø Fløystad
2013-07-08 11:59:22 +02:00
parent 933e2c77f3
commit b29dd83eea
1 changed files with 16 additions and 8 deletions
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skimage/exposure/unwrap.py
+16 -8
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@@ -4,10 +4,7 @@ import _unwrap_2d
import _unwrap_3d
def unwrap(wrapped_array,
wrap_around_axis_0=False,
wrap_around_axis_1=False,
wrap_around_axis_2=False):
def unwrap(wrapped_array, wrap_around=False):
'''From ``image``, wrapped to lie in the interval [-pi, pi), recover the
original, unwrapped image.
@@ -21,8 +18,19 @@ def unwrap(wrapped_array,
image_unwrapped : array_like
'''
wrapped_array = np.require(wrapped_array, np.float32, ['C'])
if wrapped_array.ndim not in [2,3]:
raise ValueError('input array needs to have 2 or 3 dimensions')
if wrapped_array.ndim not in (2, 3):
raise ValueError('image must be 2 or 3 dimensional')
if isinstance(wrap_around, bool):
wrap_around = [wrap_around] * wrapped_array.ndim
elif (hasattr(wrap_around, '__getitem__')
and not isinstance(wrap_around, basestring)):
if not len(wrap_around) == wrapped_array.ndim:
raise ValueError('Length of wrap_around must equal the '
'dimensionality of image')
wrap_around = [bool(wa) for wa in wrap_around]
else:
raise ValueError('wrap_around must be a bool or a sequence with '
'length equal to the dimensionality of image')
wrapped_array_masked = np.ma.asarray(wrapped_array)
unwrapped_array = np.empty_like(wrapped_array_masked.data)
@@ -30,12 +38,12 @@ def unwrap(wrapped_array,
_unwrap_2d._unwrap2D(wrapped_array_masked.data,
np.ma.getmaskarray(wrapped_array_masked).astype(np.uint8),
unwrapped_array,
bool(wrap_around_axis_0), bool(wrap_around_axis_1))
wrap_around[0], wrap_around[1])
elif wrapped_array.ndim == 3:
_unwrap_3d._unwrap3D(wrapped_array_masked.data,
np.ma.getmaskarray(wrapped_array_masked).astype(np.uint8),
unwrapped_array,
bool(wrap_around_axis_0), bool(wrap_around_axis_1), bool(wrap_around_axis_2))
wrap_around[0], wrap_around[1], wrap_around[2])
if np.ma.isMaskedArray(wrapped_array):
return np.ma.array(unwrapped_array, mask = wrapped_array_masked.mask)