8000 MAINT: Spellcheck some files. by charris · Pull Request #4844 · numpy/numpy · GitHub
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MAINT: Spellcheck some files. #4844

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Merged
merged 1 commit into from
Jul 6, 2014
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MAINT: Spellcheck some files. #4844

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18 changes: 9 additions & 9 deletions numpy/core/src/multiarray/mapping.c
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Original file line number Diff line number Diff line change
Expand Up @@ -1224,7 +1224,7 @@ array_assign_boolean_subscript(PyArrayObject *self,

if (needs_api) {
/*
* FIXME?: most assignment operations stop after the first occurance
* FIXME?: most assignment operations stop after the first occurrence
* of an error. Boolean does not currently, but should at least
* report the error. (This is only relevant for things like str->int
* casts which call into python)
Expand Down Expand Up @@ -1439,7 +1439,7 @@ array_subscript(PyArrayObject *self, PyObject *op)
/*
* TODO: Should this be a view or not? The only reason not would be
* optimization (i.e. of array[...] += 1) I think.
* Before, it was just self for a single Ellipis.
* Before, it was just self for a single ellipsis.
*/
result = PyArray_View(self, NULL, NULL);
/* A single ellipsis, so no need to decref */
Expand Down Expand Up @@ -1664,7 +1664,7 @@ array_assign_item(PyArrayObject *self, Py_ssize_t i, PyObject *op)
/*
* This fallback takes the old route of `arr.flat[index] = values`
* for one dimensional `arr`. The route can sometimes fail slightly
* different (ValueError instead of IndexError), in which case we
* differently (ValueError instead of IndexError), in which case we
* warn users about the change. But since it does not actually care *at all*
* about shapes, it should only fail for out of bound indexes or
* casting errors.
Expand Down Expand Up @@ -2448,7 +2448,7 @@ PyArray_MapIterCheckIndices(PyArrayMapIterObject *mit)
NPY_BEGIN_THREADS_DEF;

if (mit->size == 0) {
/* All indices got broadcasted away, do *not* check as it always was */
/* All indices got broadcast away, do *not* check as it always was */
return 0;
}

Expand Down Expand Up @@ -2671,7 +2671,7 @@ PyArray_MapIterNew(npy_index_info *indices , int index_num, int index_type,
* 1. No subspace iteration is necessary, so the extra_op can
* be included into the index iterator (it will be buffered)
* 2. Subspace iteration is necessary, so the extra op is iterated
* independendly, and the iteration order is fixed at C (could
* independently, and the iteration order is fixed at C (could
* also use Fortran order if the array is Fortran order).
* In this case the subspace iterator is not buffered.
*
Expand Down Expand Up @@ -2864,7 +2864,7 @@ PyArray_MapIterNew(npy_index_info *indices , int index_num, int index_type,
NPY_ITER_GROWINNER;

/*
* For a single 1-d operand, guarantee itertion order
* For a single 1-d operand, guarantee iteration order
* (scipy used this). Note that subspace may be used.
*/
if ((mit->numiter == 1) && (PyArray_NDIM(index_arrays[0]) == 1)) {
Expand Down Expand Up @@ -3076,7 +3076,7 @@ PyArray_MapIterNew(npy_index_info *indices , int index_num, int index_type,

fail:
/*
* Check whether the operand was not broadcastable and replace the error
* Check whether the operand could not be broadcast and replace the error
* in that case. This should however normally be found early with a
* direct goto to broadcast_error
*/
Expand All @@ -3091,7 +3091,7 @@ PyArray_MapIterNew(npy_index_info *indices , int index_num, int index_type,
/* (j < 0 is currently impossible, extra_op is reshaped) */
j >= 0 &&
PyArray_DIM(extra_op, i) != mit->dimensions[j]) {
/* extra_op cannot be broadcasted to the indexing result */
/* extra_op cannot be broadcast to the indexing result */
goto broadcast_error;
}
}
Expand Down Expand Up @@ -3151,7 +3151,7 @@ PyArray_MapIterNew(npy_index_info *indices , int index_num, int index_type,
* that most of this public API is currently not guaranteed
* to stay the same between versions. If you plan on using
* it, please consider adding more utility functions here
* to accomodate new features.
* to accommodate new features.
*/
NPY_NO_EXPORT PyObject *
PyArray_MapIterArray(PyArrayObject * a, PyObject * index)
Expand Down
28 changes: 14 additions & 14 deletions numpy/core/tests/test_indexing.py
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Expand Up @@ -147,7 +147,7 @@ def test_boolean_indexing_onedim(self):

def test_boolean_assignment_value_mismatch(self):
# A boolean assignment should fail when the shape of the values
# cannot be broadcasted to the subscription. (see also gh-3458)
# cannot be broadcast to the subscription. (see also gh-3458)
a = np.arange(4)
def f(a, v):
a[a > -1] = v
Expand Down Expand Up @@ -188,12 +188,12 @@ def test_reverse_strides_and_subspace_bufferinit(self):
# If the strides are not reversed, the 0 in the arange comes last.
assert_equal(a[0], 0)

# This also tests that the subspace buffer is initiliazed:
# This also tests that the subspace buffer is initialized:
a = np.ones((5, 2))
c = np.arange(10).reshape(5, 2)[::-1]
a[b, :] = c
assert_equal(a[0], [0, 1])

def test_reversed_strides_result_allocation(self):
# Test a bug when calculating the output strides for a result array
# when the subspace size was 1 (and test other cases as well)
Expand Down Expand Up @@ -346,7 +346,7 @@ def test_small_regressions(self):
# Reference count of intp for index checks
a = np.array([0])
refcount = sys.getrefcount(np.dtype(np.intp))
# item setting always checks indices in seperate function:
# item setting always checks indices in separate function:
a[np.array([0], dtype=np.intp)] = 1
a[np.array([0], dtype=np.uint8)] = 1
assert_raises(IndexError, a.__setitem__,
Expand Down Expand Up @@ -537,11 +537,11 @@ class TestMultiIndexingAutomated(TestCase):
These test use code to mimic the C-Code indexing for selection.

NOTE: * This still lacks tests for complex item setting.
* If you change behavoir of indexing, you might want to modify
* If you change behavior of indexing, you might want to modify
these tests to try more combinations.
* Behavior was written to match numpy version 1.8. (though a
first version matched 1.7.)
* Only tuple indicies are supported by the mimicing code.
* Only tuple indices are supported by the mimicking code.
(and tested as of writing this)
* Error types should match most of the time as long as there
is only one error. For multiple errors, what gets raised
Expand All @@ -564,7 +564,7 @@ def setUp(self):
slice(4, -1, -2),
slice(None, None, -3),
# Some Fancy indexes:
np.empty((0, 1, 1), dtype=np.intp), # empty broadcastable
np.empty((0, 1, 1), dtype=np.intp), # empty and can be broadcast
np.array([0, 1, -2]),
np.array([[2], [0], [1]]),
np.array([[0, -1], [0, 1]], dtype=np.dtype('intp').newbyteorder()),
Expand Down Expand Up @@ -611,7 +611,7 @@ def _get_multi_index(self, arr, indices):
fancy_dim = 0
# NOTE: This is a funny twist (and probably OK to change).
# The boolean array has illegal indexes, but this is
# allowed if the broadcasted fancy-indices are 0-sized.
# allowed if the broadcast fancy-indices are 0-sized.
# This variable is to catch that case.
error_unless_broadcast_to_empty = False

Expand Down Expand Up @@ -656,7 +656,7 @@ def _get_multi_index(self, arr, indices):
if arr.ndim - ndim < 0:
# we can't take more dimensions then we have, not even for 0-d arrays.
# since a[()] makes sense, but not a[(),]. We will raise an error
# lateron, unless a broadcasting error occurs first.
# later on, unless a broadcasting error occurs first.
raise IndexError

if ndim == 0 and not None in in_indices:
Expand All @@ -668,7 +668,7 @@ def _get_multi_index(self, arr, indices):

for ax, indx in enumerate(in_indices):
if isinstance(indx, slice):
# convert to an index array anways:
# convert to an index array
indx = np.arange(*indx.indices(arr.shape[ax]))
indices.append(['s', indx])
continue
Expand Down Expand Up @@ -701,7 +701,7 @@ def _get_multi_index(self, arr, indices):
indx = flat_indx
else:
# This could be changed, a 0-d boolean index can
# make sense (even outide the 0-d indexed array case)
# make sense (even outside the 0-d indexed array case)
# Note that originally this is could be interpreted as
# integer in the full integer special case.
raise IndexError
Expand Down Expand Up @@ -753,7 +753,7 @@ def _get_multi_index(self, arr, indices):
arr = arr.transpose(*(fancy_axes + axes))

# We only have one 'f' index now and arr is transposed accordingly.
# Now handle newaxes by reshaping...
# Now handle newaxis by reshaping...
ax = 0
for indx in indices:
if indx[0] == 'f':
Expand All @@ -771,7 +771,7 @@ def _get_multi_index(self, arr, indices):
res = np.broadcast(*indx[1:]) # raises ValueError...
else:
res = indx[1]
# unfortunatly the indices might be out of bounds. So check
# unfortunately the indices might be out of bounds. So check
# that first, and use mode='wrap' then. However only if
# there are any indices...
if res.size != 0:
Expand Down Expand Up @@ -909,7 +909,7 @@ def test_multidim(self):
# spot and the simple ones in one other spot.
with warnings.catch_warnings():
# This is so that np.array(True) is not accepted in a full integer
# index, when running the file seperatly.
# index, when running the file separately.
warnings.filterwarnings('error', '', DeprecationWarning)
for simple_pos in [0, 2, 3]:
tocheck = [self.fill_indices, self.complex_indices,
Expand Down
24 changes: 12 additions & 12 deletions numpy/core/tests/test_regression.py
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Expand Up @@ -181,7 +181,7 @@ def test_endian_bool_indexing(self,level=rlevel):
assert_(np.all(b[yb] > 0.5))

def test_endian_where(self,level=rlevel):
"""GitHuB issue #369"""
"""GitHub issue #369"""
net = np.zeros(3, dtype='>f4')
net[1] = 0.00458849
net[2] = 0.605202
Expand Down Expand Up @@ -290,7 +290,7 @@ def test_unicode_string_comparison(self,level=rlevel):

def test_tobytes_FORTRANORDER_discontiguous(self,level=rlevel):
"""Fix in r2836"""
# Create discontiguous Fortran-ordered array
# Create non-contiguous Fortran ordered array
x = np.array(np.random.rand(3, 3), order='F')[:, :2]
assert_array_almost_equal(x.ravel(), np.fromstring(x.tobytes()))

Expand All @@ -311,7 +311,7 @@ def bfb(): x[:] = np.arange(3, dtype=float)
self.assertRaises(ValueError, bfb)

def test_nonarray_assignment(self):
# See also Issue gh-2870, test for nonarray assignment
# See also Issue gh-2870, test for non-array assignment
# and equivalent unsafe casted array assignment
a = np.arange(10)
b = np.ones(10, dtype=bool)
Expand Down Expand Up @@ -560,15 +560,15 @@ def test_reshape_zero_strides(self, level=rlevel):
assert_(a.reshape(5, 1).strides[0] == 0)

def test_reshape_zero_size(self, level=rlevel):
"""Github Issue #2700, setting shape failed for 0-sized arrays"""
"""GitHub Issue #2700, setting shape failed for 0-sized arrays"""
a = np.ones((0, 2))
a.shape = (-1, 2)

# Cannot test if NPY_RELAXED_STRIDES_CHECKING changes the strides.
# With NPY_RELAXED_STRIDES_CHECKING the test becomes superfluous.
@dec.skipif(np.ones(1).strides[0] == np.iinfo(np.intp).max)
def test_reshape_trailing_ones_strides(self):
# Github issue gh-2949, bad strides for trailing ones of new shape
# GitHub issue gh-2949, bad strides for trailing ones of new shape
a = np.zeros(12, dtype=np.int32)[::2] # not contiguous
strides_c = (16, 8, 8, 8)
strides_f = (8, 24, 48, 48)
Expand Down Expand Up @@ -756,9 +756,9 @@ def test_bool_indexing_invalid_nr_elements(self, level=rlevel):
s = np.ones(10, dtype=float)
x = np.array((15,), dtype=float)
def ia(x, s, v): x[(s>0)]=v
# After removing deprecation, the following is are ValueErrors.
# After removing deprecation, the following are ValueErrors.
# This might seem odd as compared to the value error below. This
# is due to the fact that the new code always use "nonzero" logic
# is due to the fact that the new code always uses "nonzero" logic
# and the boolean special case is not taken.
self.assertRaises(IndexError, ia, x, s, np.zeros(9, dtype=float))
self.assertRaises(IndexError, ia, x, s, np.zeros(11, dtype=float))
Expand Down Expand Up @@ -848,7 +848,7 @@ def test_object_array_refcounting(self, level=rlevel):
cnt0_b = cnt(b)
cnt0_c = cnt(c)

# -- 0d -> 1d broadcasted slice assignment
# -- 0d -> 1-d broadcast slice assignment

arr = np.zeros(5, dtype=np.object_)

Expand All @@ -865,7 +865,7 @@ def test_object_array_refcounting(self, level=rlevel):

del arr

# -- 1d -> 2d broadcasted slice assignment
# -- 1-d -> 2-d broadcast slice assignment

arr = np.zeros((5, 2), dtype=np.object_)
arr0 = np.zeros(2, dtype=np.object_)
Expand All @@ -884,7 +884,7 @@ def test_object_array_refcounting(self, level=rlevel):

del arr, arr0

# -- 2d copying + flattening
# -- 2-d copying + flattening

arr = np.zeros((5, 2), dtype=np.object_)

Expand Down Expand Up @@ -1029,8 +1029,8 @@ def test_compress_small_type(self, level=rlevel):
b = np.zeros((2, 1), dtype = np.single)
try:
a.compress([True, False], axis = 1, out = b)
raise AssertionError("compress with an out which cannot be " \
"safely casted should not return "\
raise AssertionError("compress with an out which cannot be "
"safely casted should not return "
"successfully")
except TypeError:
pass
Expand Down
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