Author: Ronan Lamy <[email protected]>
Branch: indexing
Changeset: r78560:360ba1502914
Date: 2015-07-16 18:47 +0100
http://bitbucket.org/pypy/pypy/changeset/360ba1502914/
Log: Kill Chunks and simply use a new_view() function instead
diff --git a/pypy/module/micronumpy/arrayops.py
b/pypy/module/micronumpy/arrayops.py
--- a/pypy/module/micronumpy/arrayops.py
+++ b/pypy/module/micronumpy/arrayops.py
@@ -5,7 +5,7 @@
from pypy.module.micronumpy.base import convert_to_array, W_NDimArray
from pypy.module.micronumpy.converters import clipmode_converter
from pypy.module.micronumpy.strides import (
- Chunk, Chunks, shape_agreement, shape_agreement_multiple)
+ Chunk, new_view, shape_agreement, shape_agreement_multiple)
from .casting import find_binop_result_dtype, find_result_type
@@ -148,7 +148,8 @@
continue
chunks[axis] = Chunk(axis_start, axis_start + arr.get_shape()[axis], 1,
arr.get_shape()[axis])
- Chunks(chunks).apply(space, res).implementation.setslice(space, arr)
+ view = new_view(space, res, chunks)
+ view.implementation.setslice(space, arr)
axis_start += arr.get_shape()[axis]
return res
@@ -162,9 +163,8 @@
shape = [arr.get_shape()[0] * repeats]
w_res = W_NDimArray.from_shape(space, shape, arr.get_dtype(),
w_instance=arr)
for i in range(repeats):
- chunks = Chunks([Chunk(i, shape[0] - repeats + i, repeats,
- orig_size)])
- view = chunks.apply(space, w_res)
+ chunks = [Chunk(i, shape[0] - repeats + i, repeats, orig_size)]
+ view = new_view(space, w_res, chunks)
view.implementation.setslice(space, arr)
else:
axis = space.int_w(w_axis)
@@ -176,7 +176,7 @@
for i in range(repeats):
chunks[axis] = Chunk(i, shape[axis] - repeats + i, repeats,
orig_size)
- view = Chunks(chunks).apply(space, w_res)
+ view = new_view(space, w_res, chunks)
view.implementation.setslice(space, arr)
return w_res
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
@@ -1,7 +1,7 @@
from pypy.interpreter.error import OperationError, oefmt
from rpython.rlib import jit, rgc
from rpython.rlib.buffer import Buffer
-from rpython.rlib.debug import make_sure_not_resized, debug_print
+from rpython.rlib.debug import make_sure_not_resized
from rpython.rlib.rawstorage import alloc_raw_storage, free_raw_storage, \
raw_storage_getitem, raw_storage_setitem, RAW_STORAGE
from rpython.rtyper.lltypesystem import rffi, lltype, llmemory
@@ -10,13 +10,11 @@
ArrayArgumentException, W_NumpyObject
from pypy.module.micronumpy.iterators import ArrayIter
from pypy.module.micronumpy.strides import (
- Chunk, Chunks, NewAxisChunk, EllipsisChunk,
+ Chunk, new_view, NewAxisChunk, EllipsisChunk,
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
-from rpython.rtyper.annlowlevel import cast_gcref_to_instance
-from pypy.interpreter.baseobjspace import W_Root
class BaseConcreteArray(object):
_immutable_fields_ = ['dtype?', 'storage', 'start', 'size', 'shape[*]',
@@ -225,16 +223,16 @@
space.isinstance_w(w_idx, space.w_slice)):
if len(self.get_shape()) == 0:
raise oefmt(space.w_ValueError, "cannot slice a 0-d array")
- return Chunks([Chunk(*space.decode_index4(w_idx,
self.get_shape()[0]))])
+ return [Chunk(*space.decode_index4(w_idx, self.get_shape()[0]))]
elif isinstance(w_idx, W_NDimArray) and w_idx.is_scalar():
w_idx = w_idx.get_scalar_value().item(space)
if not space.isinstance_w(w_idx, space.w_int) and \
not space.isinstance_w(w_idx, space.w_bool):
raise OperationError(space.w_IndexError, space.wrap(
"arrays used as indices must be of integer (or boolean)
type"))
- return Chunks([Chunk(*space.decode_index4(w_idx,
self.get_shape()[0]))])
+ return [Chunk(*space.decode_index4(w_idx, self.get_shape()[0]))]
elif space.is_w(w_idx, space.w_None):
- return Chunks([NewAxisChunk()])
+ return [NewAxisChunk()]
result = []
i = 0
has_ellipsis = False
@@ -253,7 +251,7 @@
result.append(Chunk(*space.decode_index4(w_item,
self.get_shape()[i])))
i += 1
- return Chunks(result)
+ return result
def descr_getitem(self, space, orig_arr, w_index):
try:
@@ -262,7 +260,7 @@
except IndexError:
# not a single result
chunks = self._prepare_slice_args(space, w_index)
- return chunks.apply(space, orig_arr)
+ return new_view(space, orig_arr, chunks)
def descr_setitem(self, space, orig_arr, w_index, w_value):
try:
@@ -271,7 +269,7 @@
except IndexError:
w_value = convert_to_array(space, w_value)
chunks = self._prepare_slice_args(space, w_index)
- view = chunks.apply(space, orig_arr)
+ view = new_view(space, orig_arr, chunks)
view.implementation.setslice(space, w_value)
def transpose(self, orig_array, axes=None):
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
@@ -20,7 +20,7 @@
from pypy.module.micronumpy.flagsobj import W_FlagsObject
from pypy.module.micronumpy.strides import (
get_shape_from_iterable, shape_agreement, shape_agreement_multiple,
- is_c_contiguous, is_f_contiguous, calc_strides)
+ is_c_contiguous, is_f_contiguous, calc_strides, new_view)
from pypy.module.micronumpy.casting import can_cast_array
@@ -179,7 +179,7 @@
if iter_shape is None:
# w_index is a list of slices, return a view
chunks = self.implementation._prepare_slice_args(space, w_index)
- return chunks.apply(space, self)
+ return new_view(space, self, chunks)
shape = res_shape + self.get_shape()[len(indexes):]
w_res = W_NDimArray.from_shape(space, shape, self.get_dtype(),
self.get_order(), w_instance=self)
@@ -195,7 +195,7 @@
if iter_shape is None:
# w_index is a list of slices
chunks = self.implementation._prepare_slice_args(space, w_index)
- view = chunks.apply(space, self)
+ view = new_view(space, self, chunks)
view.implementation.setslice(space, val_arr)
return
if support.product(iter_shape) == 0:
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
@@ -10,31 +10,6 @@
pass
-class Chunks(BaseChunk):
- def __init__(self, l):
- self.l = l
-
- @jit.unroll_safe
- def extend_shape(self, old_shape):
- shape = []
- i = -1
- for i, c in enumerate_chunks(self.l):
- if c.step != 0:
- shape.append(c.lgt)
- s = i + 1
- assert s >= 0
- return shape[:] + old_shape[s:]
-
- def apply(self, space, orig_arr):
- arr = orig_arr.implementation
- shape = self.extend_shape(arr.shape)
- r = calculate_slice_strides(arr.shape, arr.start, arr.get_strides(),
- arr.get_backstrides(), self.l)
- _, start, strides, backstrides = r
- return W_NDimArray.new_slice(space, start, strides[:], backstrides[:],
- shape[:], arr, orig_arr)
-
-
class Chunk(BaseChunk):
axis_step = 1
@@ -64,6 +39,27 @@
pass
+def new_view(space, w_arr, chunks):
+ arr = w_arr.implementation
+ shape = _extend_shape(arr.shape, chunks)
+ r = calculate_slice_strides(arr.shape, arr.start, arr.get_strides(),
+ arr.get_backstrides(), chunks)
+ _, start, strides, backstrides = r
+ return W_NDimArray.new_slice(space, start, strides[:], backstrides[:],
+ shape[:], arr, w_arr)
+
[email protected]_safe
+def _extend_shape(old_shape, chunks):
+ shape = []
+ i = -1
+ for i, c in enumerate_chunks(chunks):
+ if c.step != 0:
+ shape.append(c.lgt)
+ s = i + 1
+ assert s >= 0
+ return shape[:] + old_shape[s:]
+
+
class BaseTransform(object):
pass
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
@@ -4,7 +4,7 @@
from pypy.conftest import option
from pypy.module.micronumpy.appbridge import get_appbridge_cache
-from pypy.module.micronumpy.strides import Chunk, Chunks
+from pypy.module.micronumpy.strides import Chunk, new_view
from pypy.module.micronumpy.ndarray import W_NDimArray
from pypy.module.micronumpy.test.test_base import BaseNumpyAppTest
@@ -22,7 +22,7 @@
def create_slice(space, a, chunks):
- return Chunks(chunks).apply(space, W_NDimArray(a)).implementation
+ return new_view(space, W_NDimArray(a), chunks).implementation
def create_array(*args, **kwargs):
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