8000 ENH: add padding options to diff by mattharrigan · Pull Request #8206 · numpy/numpy · GitHub
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ENH: add padding options to diff #8206

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Merged
merged 1 commit into from
Sep 26, 2018
Merged

ENH: add padding options to diff #8206

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6 changes: 6 additions & 0 deletions doc/release/1.16.0-notes.rst
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Original file line number Diff line number Diff line change
Expand Up @@ -107,6 +107,12 @@ Previously, a ``LinAlgError`` would be raised when an empty matrix/empty
matrices (with zero rows and/or columns) is/are passed in. Now outputs of
appropriate shapes are returned.

``np.diff`` Added kwargs prepend and append
-------------------------------------------
Add kwargs prepend and append, allowing for values to be inserted
on either end of the differences. Similar to options for ediff1d.
Allows for the inverse of cumsum easily via prepend=0

ARM support updated
-------------------
Support for ARM CPUs has been updated to accommodate 32 and 64 bit targets,
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30 changes: 29 additions & 1 deletion numpy/lib/function_base.py
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Expand Up @@ -1090,7 +1090,7 @@ def gradient(f, *varargs, **kwargs):
return outvals


def diff(a, n=1, axis=-1):
def diff(a, n=1, axis=-1, prepend=np._NoValue, append=np._NoValue):
"""
Calculate the n-th discrete difference along the given axis.

Expand All @@ -1108,6 +1108,12 @@ def diff(a, n=1, axis=-1):
axis : int, optional
The axis along which the difference is taken, default is the
last axis.
prepend, append : array_like, optional
Values to prepend or append to "a" along axis prior to
performing the difference. Scalar values are expanded to
arrays with length 1 in the direction of axis and the shape
of the input array in along all other axes. Otherwise the
dimension and shape must match "a" except along axis.
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Can we add a test verifying that ValueError is raised if the shape doesn't match?


Returns
-------
Expand Down Expand Up @@ -1176,6 +1182,28 @@ def diff(a, n=1, axis=-1):
nd = a.ndim
axis = normalize_axis_index(axis, nd)

combined = []
if prepend is not np._NoValue:
prepend = np.asanyarray(prepend)
if prepend.ndim == 0:
shape = list(a.shape)
shape[axis] = 1
prepend = np.broadcast_to(prepend, tuple(shape))
combined.append(prepend)

combined.append(a)

if append is not np._NoValue:
append = np.asanyarray(append)
if append.ndim == 0:
shape = list(a.shape)
shape[axis] = 1
append = np.broadcast_to(append, tuple(shape))
combined.append(append)

if len(combined) > 1:
a = np.concatenate(combined, axis)

slice1 = [slice(None)] * nd
slice2 = [slice(None)] * nd
slice1[axis] = slice(1, None)
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52 changes: 52 additions & 0 deletions numpy/lib/tests/test_function_base.py
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Expand Up @@ -734,6 +734,58 @@ def test_subclass(self):
assert_array_equal(out3.mask, [[], [], [], [], []])
assert_(type(out3) is type(x))

def test_prepend(self):
x = np.arange(5) + 1
assert_array_equal(diff(x, prepend=0), np.ones(5))
assert_array_equal(diff(x, prepend=[0]), np.ones(5))
assert_array_equal(np.cumsum(np.diff(x, prepend=0)), x)
assert_array_equal(diff(x, prepend=[-1, 0]), np.ones(6))

x = np.arange(4).reshape(2, 2)
result = np.diff(x, axis=1, prepend=0)
expected = [[0, 1], [2, 1]]
assert_array_equal(result, expected)
result = np.diff(x, axis=1, prepend=[[0], [0]])
assert_array_equal(result, expected)

result = np.diff(x, axis=0, prepend=0)
expected = [[0, 1], [2, 2]]
assert_array_equal(result, expected)
result = np.diff(x, axis=0, prepend=[[0, 0]])
assert_array_equal(result, expected)

assert_raises(ValueError, np.diff, x, prepend=np.zeros((3,3)))

assert_raises(np.AxisError, diff, x, prepend=0, axis=3)

def test_append(self):
x = np.arange(5)
result = diff(x, append=0)
expected = [1, 1, 1, 1, -4]
assert_array_equal(result, expected)
result = diff(x, append=[0])
assert_array_equal(result, expected)
result = diff(x, append=[0, 2])
expected = expected + [2]
assert_array_equal(result, expected)

x = np.arange(4).reshape(2, 2)
result = np.diff(x, axis=1, append=0)
expected = [[1, -1], [1, -3]]
assert_array_equal(result, expected)
result = np.diff(x, axis=1, append=[[0], [0]])
assert_array_equal(result, expected)

result = np.diff(x, axis=0, append=0)
expected = [[2, 2], [-2, -3]]
assert_array_equal(result, expected)
result = np.diff(x, axis=0, append=[[0, 0]])
assert_array_equal(result, expected)

assert_raises(ValueError, np.diff, x, append=np.zeros((3,3)))

assert_raises(np.AxisError, diff, x, append=0, axis=3)


class TestDelete(object):

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0