Author: mattip <matti.pi...@gmail.com>
Branch:
Changeset: r82336:d77888929462
Date: 2016-02-19 16:29 +0200
http://bitbucket.org/pypy/pypy/changeset/d77888929462/
Log: test, fix indexing ndarray with scalar, single boolean array
diff --git a/pypy/module/micronumpy/concrete.py
b/pypy/module/micronumpy/concrete.py
--- a/pypy/module/micronumpy/concrete.py
+++ b/pypy/module/micronumpy/concrete.py
@@ -12,8 +12,8 @@
ArrayArgumentException, W_NumpyObject
from pypy.module.micronumpy.iterators import ArrayIter
from pypy.module.micronumpy.strides import (
- IntegerChunk, SliceChunk, NewAxisChunk, EllipsisChunk, new_view,
- calc_strides, calc_new_strides, shape_agreement,
+ IntegerChunk, SliceChunk, NewAxisChunk, EllipsisChunk, BooleanChunk,
+ new_view, calc_strides, calc_new_strides, shape_agreement,
calculate_broadcast_strides, calc_backstrides, calc_start, is_c_contiguous,
is_f_contiguous)
from rpython.rlib.objectmodel import keepalive_until_here
@@ -236,6 +236,8 @@
@jit.unroll_safe
def _prepare_slice_args(self, space, w_idx):
+ print '_prepare_slice_args', w_idx
+ from pypy.module.micronumpy import boxes
if space.isinstance_w(w_idx, space.w_str):
raise oefmt(space.w_IndexError, "only integers, slices (`:`), "
"ellipsis (`...`), numpy.newaxis (`None`) and integer or "
@@ -258,6 +260,7 @@
result = []
i = 0
has_ellipsis = False
+ has_filter = False
for w_item in space.fixedview(w_idx):
if space.is_w(w_item, space.w_Ellipsis):
if has_ellipsis:
@@ -272,6 +275,16 @@
elif space.isinstance_w(w_item, space.w_slice):
result.append(SliceChunk(w_item))
i += 1
+ elif isinstance(w_item, W_NDimArray) and
w_item.get_dtype().is_bool():
+ if has_filter:
+ # in CNumPy, the support for this is incomplete
+ raise oefmt(space.w_ValueError,
+ "an index can only have a single boolean mask; "
+ "use np.take or create a sinlge mask array")
+ has_filter = True
+ result.append(BooleanChunk(w_item))
+ elif isinstance(w_item, boxes.W_GenericBox):
+ result.append(IntegerChunk(w_item.descr_int(space)))
else:
result.append(IntegerChunk(w_item))
i += 1
@@ -280,11 +293,14 @@
return result
def descr_getitem(self, space, orig_arr, w_index):
+ print 'concrete descr_gettiem %s' % str(w_index)[:35]
try:
item = self._single_item_index(space, w_index)
+ print 'concrete descr_gettiem _single_item_index succeeded'
return self.getitem(item)
except IndexError:
# not a single result
+ print 'concrete descr_gettiem _single_item_index failed'
chunks = self._prepare_slice_args(space, w_index)
return new_view(space, orig_arr, chunks)
diff --git a/pypy/module/micronumpy/ndarray.py
b/pypy/module/micronumpy/ndarray.py
--- a/pypy/module/micronumpy/ndarray.py
+++ b/pypy/module/micronumpy/ndarray.py
@@ -107,8 +107,9 @@
arr = W_NDimArray(self.implementation.transpose(self, None))
return space.wrap(loop.tostring(space, arr))
- def getitem_filter(self, space, arr):
- if arr.ndims() > 1 and arr.get_shape() != self.get_shape():
+ def getitem_filter(self, space, arr, axis=0):
+ shape = self.get_shape()
+ if arr.ndims() > 1 and arr.get_shape() != shape:
raise OperationError(space.w_IndexError, space.wrap(
"boolean index array should have 1 dimension"))
if arr.get_size() > self.get_size():
@@ -116,14 +117,14 @@
"index out of range for array"))
size = loop.count_all_true(arr)
if arr.ndims() == 1:
- if self.ndims() > 1 and arr.get_shape()[0] != self.get_shape()[0]:
+ if self.ndims() > 1 and arr.get_shape()[0] != shape[axis]:
msg = ("boolean index did not match indexed array along"
- " dimension 0; dimension is %d but corresponding"
- " boolean dimension is %d" % (self.get_shape()[0],
+ " dimension %d; dimension is %d but corresponding"
+ " boolean dimension is %d" % (axis, shape[axis],
arr.get_shape()[0]))
#warning =
space.gettypefor(support.W_VisibleDeprecationWarning)
space.warn(space.wrap(msg), space.w_VisibleDeprecationWarning)
- res_shape = [size] + self.get_shape()[1:]
+ res_shape = shape[:axis] + [size] + shape[axis+1:]
else:
res_shape = [size]
w_res = W_NDimArray.from_shape(space, res_shape, self.get_dtype(),
@@ -149,6 +150,8 @@
def _prepare_array_index(self, space, w_index):
if isinstance(w_index, W_NDimArray):
return [], w_index.get_shape(), w_index.get_shape(), [w_index]
+ if isinstance(w_index, boxes.W_GenericBox):
+ return [], [1], [1], [w_index]
w_lst = space.listview(w_index)
for w_item in w_lst:
if not (space.isinstance_w(w_item, space.w_int) or
space.isinstance_w(w_item, space.w_float)):
@@ -162,7 +165,14 @@
arr_index_in_shape = False
prefix = []
for i, w_item in enumerate(w_lst):
- if (isinstance(w_item, W_NDimArray) or
+ if isinstance(w_item, W_NDimArray) and
w_item.get_dtype().is_bool():
+ if w_item.ndims() > 0:
+ indexes_w[i] = w_item
+ else:
+ raise oefmt(space.w_IndexError,
+ "in the future, 0-d boolean arrays will be "
+ "interpreted as a valid boolean index")
+ elif (isinstance(w_item, W_NDimArray) or
space.isinstance_w(w_item, space.w_list)):
w_item = convert_to_array(space, w_item)
if shape is None:
@@ -232,6 +242,8 @@
raise oefmt(space.w_IndexError,
"in the future, 0-d boolean arrays will be "
"interpreted as a valid boolean index")
+ elif isinstance(w_idx, boxes.W_GenericBox):
+ w_ret = self.getitem_array_int(space, w_idx)
else:
try:
w_ret = self.implementation.descr_getitem(space, self, w_idx)
diff --git a/pypy/module/micronumpy/strides.py
b/pypy/module/micronumpy/strides.py
--- a/pypy/module/micronumpy/strides.py
+++ b/pypy/module/micronumpy/strides.py
@@ -77,14 +77,40 @@
backstride = base_stride * max(0, base_length - 1)
return 0, base_length, base_stride, backstride
+class BooleanChunk(BaseChunk):
+ input_dim = 1
+ out_dim = 1
+ def __init__(self, w_idx):
+ self.w_idx = w_idx
+
+ def compute(self, space, base_length, base_stride):
+ raise oefmt(space.w_NotImplementedError, 'cannot reach')
def new_view(space, w_arr, chunks):
arr = w_arr.implementation
- r = calculate_slice_strides(space, arr.shape, arr.start, arr.get_strides(),
- arr.get_backstrides(), chunks)
+ dim = -1
+ for i, c in enumerate(chunks):
+ if isinstance(c, BooleanChunk):
+ dim = i
+ break
+ if dim >= 0:
+ # filter by axis r
+ filtr = chunks.pop(dim)
+ assert isinstance(filtr, BooleanChunk)
+ w_arr = w_arr.getitem_filter(space, filtr.w_idx, axis=dim)
+ arr = w_arr.implementation
+ r = calculate_slice_strides(space, arr.shape, arr.start,
+ arr.get_strides(), arr.get_backstrides(), chunks)
+ else:
+ r = calculate_slice_strides(space, arr.shape, arr.start,
+ arr.get_strides(), arr.get_backstrides(), chunks)
shape, start, strides, backstrides = r
- return W_NDimArray.new_slice(space, start, strides[:], backstrides[:],
+ w_ret = W_NDimArray.new_slice(space, start, strides[:], backstrides[:],
shape[:], arr, w_arr)
+ if dim == 0:
+ # Do not return a view
+ return w_ret.descr_copy(space, space.wrap(w_ret.get_order()))
+ return w_ret
@jit.unroll_safe
def _extend_shape(old_shape, chunks):
@@ -127,7 +153,7 @@
jit.isconstant(len(chunks)))
def calculate_slice_strides(space, shape, start, strides, backstrides, chunks):
"""
- Note: `chunks` must contain exactly one EllipsisChunk object.
+ Note: `chunks` can contain at most one EllipsisChunk object.
"""
size = 0
used_dims = 0
diff --git a/pypy/module/micronumpy/test/test_deprecations.py
b/pypy/module/micronumpy/test/test_deprecations.py
--- a/pypy/module/micronumpy/test/test_deprecations.py
+++ b/pypy/module/micronumpy/test/test_deprecations.py
@@ -24,7 +24,7 @@
# boolean indexing matches the dims in index
# to the first index.ndims in arr, not implemented in pypy yet
raises(IndexError, arr.__getitem__, index)
- raises(TypeError, arr.__getitem__, (slice(None), index))
+ raises(IndexError, arr.__getitem__, (slice(None), index))
else:
raises(np.VisibleDeprecationWarning, arr.__getitem__, index)
raises(np.VisibleDeprecationWarning, arr.__getitem__,
(slice(None), index))
diff --git a/pypy/module/micronumpy/test/test_ndarray.py
b/pypy/module/micronumpy/test/test_ndarray.py
--- a/pypy/module/micronumpy/test/test_ndarray.py
+++ b/pypy/module/micronumpy/test/test_ndarray.py
@@ -2541,6 +2541,23 @@
a[b] = np.array([[4.]])
assert (a == [[4., 4., 4.]]).all()
+ def test_indexing_by_boolean(self):
+ import numpy as np
+ a = np.arange(6).reshape(2,3)
+ assert (a[[True, False], :] == [[3, 4, 5], [0, 1, 2]]).all()
+ b = a[np.array([True, False]), :]
+ assert (b == [[0, 1, 2]]).all()
+ assert b.base is None
+ b = a[:, np.array([True, False, True])]
+ assert b.base is not None
+
+ def test_scalar_indexing(self):
+ import numpy as np
+ a = np.arange(6).reshape(2,3)
+ i = np.dtype('int32').type(0)
+ assert (a[0] == a[i]).all()
+
+
def test_ellipsis_indexing(self):
import numpy as np
import sys
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