8000 DOC, MAINT: Enforce np.ndarray arg for np.put and np.place by gfyoung · Pull Request #7000 · numpy/numpy · GitHub
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DOC, MAINT: Enforce np.ndarray arg for np.put and np.place #7000

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Merged
merged 1 commit into from
Jan 15, 2016
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DOC, MAINT: Enforce np.ndarray arg for np.put and np.place #7000

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8 changes: 7 additions & 1 deletion numpy/core/fromnumeric.py
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Original file line number Diff line number Diff line change
Expand Up @@ -445,7 +445,13 @@ def put(a, ind, v, mode='raise'):
array([ 0, 1, 2, 3, -5])

"""
return a.put(ind, v, mode)
try:
put = a.put
except AttributeError:
raise TypeError("argument 1 must be numpy.ndarray, "
"not {name}".format(name=type(a).__name__))

return put(ind, v, mode)


def swapaxes(a, axis1, axis2):
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17 changes: 17 additions & 0 deletions numpy/core/tests/test_fromnumeric.py
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@@ -0,0 +1,17 @@
from __future__ import division, absolute_import, print_function

from numpy import put
from numpy.testing import TestCase, assert_raises


class TestPut(TestCase):

def test_bad_array(self):
# We want to raise a TypeError in the
# case that a non-ndarray object is passed
# in since `np.put` modifies in place and
# hence would do nothing to a non-ndarray
v = 5
indx = [0, 2]
bad_array = [1, 2, 3]
assert_raises(TypeError, put, bad_array, indx, v)
6 changes: 5 additions & 1 deletion numpy/lib/function_base.py
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Expand Up @@ -1779,7 +1779,7 @@ def place(arr, mask, vals):

Parameters
----------
arr : array_like
arr : ndarray
Array to put data into.
mask : array_like
Boolean mask array. Must have the same size as `a`.
Expand All @@ -1801,6 +1801,10 @@ def place(arr, mask, vals):
[44, 55, 44]])

"""
if not isinstance(arr, np.ndarray):
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Could we use the same duck-typing solution as above, with the try/except clause?

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It feels little more awkward in this case because _insert is not an ndarray method. I suppose you could do something like the following:

try:
   put = arr.put
except AttributeError:
   raise TypeError(...)
return _insert(arr, mask, vals)

However, it seems like more contrived compared to the others since we're relying on a method that has nothing to do with what is being called.

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What error message do you get when place is not valid? What sort of duck typing does it currently support, if any?

It might be worth updating _insert instead.

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@shoyer : See #7003, which does a complete revamp of arr_insert (that is tied to _insert) and does the type checking. In the case of np.place, this PR should serve as a stopgap measure until #7003 can be merged.

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@shoyer : Sorry, I didn't answer the remainder of your question; I only had seen the "It might be worth" part on my phone when I was reading it. place doesn't actually do any duck-typing if you pass in a non-ndarray to it. Rather, it does nothing, which is why I added that isinstance check to the code. However, #7003 will embed that check into the C code, which is preferable. However, I wouldn't mind merging the isinstance check into the codebase FTTB.

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OK, agreed!

raise TypeError("argument 1 must be numpy.ndarray, "
"not {name}".format(name=type(arr).__name__))

return _insert(arr, mask, vals)


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4 changes: 4 additions & 0 deletions numpy/lib/tests/test_function_base.py
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Expand Up @@ -674,6 +674,10 @@ def test_basic(self):
assert_array_equal(b, [3, 2, 2, 3, 3])

def test_place(self):
# Make sure that non-np.ndarray objects
# raise an error instead of doing nothing
assert_raises(TypeError, place, [1, 2, 3], [True, False], [0, 1])

a = np.array([1, 4, 3, 2, 5, 8, 7])
place(a, [0, 1, 0, 1, 0, 1, 0], [2, 4, 6])
assert_array_equal(a, [1, 2, 3, 4, 5, 6, 7])
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4 changes: 0 additions & 4 deletions numpy/lib/tests/test_regression.py
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Expand Up @@ -85,10 +85,6 @@ def test_poly_eq(self, level=rlevel):
assert_(x != y)
assert_(x == x)

def test_mem_insert(self, level=rlevel):
# Ticket #572
np.lib.place(1, 1, 1)

def test_polyfit_build(self):
# Ticket #628
ref = [-1.06123820e-06, 5.70886914e-04, -1.13822012e-01,
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