Author: mattip
Branch: matrixmath-reshape
Changeset: r49934:b87bb33414be
Date: 2011-11-28 23:06 +0200
http://bitbucket.org/pypy/pypy/changeset/b87bb33414be/
Log: fix shape,reshape. Ready for review
diff --git a/pypy/module/micronumpy/interp_numarray.py
b/pypy/module/micronumpy/interp_numarray.py
--- a/pypy/module/micronumpy/interp_numarray.py
+++ b/pypy/module/micronumpy/interp_numarray.py
@@ -98,6 +98,66 @@
endshape[i] = remainder[i]
return endshape
+#Recalculating strides. Find the steps that the iteration does for each
+#dimension, given the stride and shape. Then try to create a new stride that
+#fits the new shape, using those steps. If there is a shape/step mismatch
+#(meaning that the realignment of elements crosses from one step into another)
+#return None so that the caller can raise an exception.
+def calc_new_strides(new_shape, old_shape, old_strides):
+ #Return the proper strides for new_shape, or None
+ # if the mapping crosses stepping boundaries
+
+ #Assumes that nelems have been matched, len(shape) > 1 for old_shape and
+ # len(new_shape) > 0
+ steps = []
+ last_step = 1
+ oldI = 0
+ new_strides = []
+ if old_strides[0] < old_strides[-1]:
+ for i in range(len(old_shape)):
+ steps.append(old_strides[i] / last_step)
+ last_step = old_shape[i] * old_strides[i]
+ cur_step = steps[0]
+ n_new_elems_used = 1
+ n_old_elems_to_use = old_shape[0]
+ for s in new_shape:
+ new_strides.append(cur_step * n_new_elems_used)
+ n_new_elems_used *= s
+ while n_new_elems_used > n_old_elems_to_use:
+ oldI += 1
+ if steps[oldI] != steps[oldI - 1]:
+ return None
+ n_old_elems_to_use *= old_shape[oldI]
+ if n_new_elems_used == n_old_elems_to_use:
+ oldI += 1
+ if oldI >= len(old_shape):
+ break
+ cur_step = steps[oldI]
+ n_old_elems_to_use *= old_shape[oldI]
+ else:
+ for i in range(len(old_shape) - 1, -1, -1):
+ steps.insert(0, old_strides[i] / last_step)
+ last_step = old_shape[i] * old_strides[i]
+ cur_step = steps[-1]
+ n_new_elems_used = 1
+ oldI = -1
+ n_old_elems_to_use = old_shape[-1]
+ for s in new_shape[::-1]:
+ new_strides.insert(0, cur_step * n_new_elems_used)
+ n_new_elems_used *= s
+ while n_new_elems_used > n_old_elems_to_use:
+ oldI -= 1
+ if steps[oldI] != steps[oldI + 1]:
+ return None
+ n_old_elems_to_use *= old_shape[oldI]
+ if n_new_elems_used == n_old_elems_to_use:
+ oldI -= 1
+ if oldI < -len(old_shape):
+ break
+ cur_step = steps[oldI]
+ n_old_elems_to_use *= old_shape[oldI]
+ return new_strides
+
def descr_new_array(space, w_subtype, w_item_or_iterable, w_dtype=None,
w_order=NoneNotWrapped):
# find scalar
@@ -497,7 +557,7 @@
def descr_get_shape(self, space):
return space.newtuple([space.wrap(i) for i in self.shape])
-
+
def descr_set_shape(self, space, w_iterable):
concrete = self.get_concrete()
new_size = 0
@@ -533,7 +593,7 @@
raise OperationError(space.w_ValueError,
space.wrap("total size of new array must be unchanged"))
concrete.setshape(space, new_shape)
-
+
def descr_get_size(self, space):
return space.wrap(self.find_size())
@@ -784,15 +844,17 @@
shape[:])
def descr_reshape(self, space, w_iterable):
+ '''Return a reshaped view into the original array's data
+ '''
new_sig = signature.Signature.find_sig([
NDimSlice.signature, self.signature,
])
concrete = self.get_concrete()
#concrete = self
- ndims = len(self.shape)
- strides = [0]*ndims
- backstrides = [0]*ndims
- shape = []*ndims
+ ndims = len(concrete.shape)
+ strides = [0] * ndims
+ backstrides = [0] * ndims
+ shape = [0] * ndims
for i in range(len(concrete.shape)):
strides[i] = concrete.strides[i]
backstrides[i] = concrete.backstrides[i]
@@ -890,7 +952,7 @@
builder.append(self.dtype.str_format(self.value))
def setshape(self, space, new_shape):
- pass
+ pass
class VirtualArray(BaseArray):
"""
@@ -1066,11 +1128,9 @@
return
elif len(self.shape) < 2:
#REVIEWER: this code could be refactored into calc_strides
- #but then calc_strides would have to accept a factor of the
- #current stride
+ #but then calc_strides would have to accept a stepping factor
strides = []
backstrides = []
- self.shape = new_shape[:]
s = self.strides[0]
if self.order == 'C':
new_shape.reverse()
@@ -1081,62 +1141,22 @@
if self.order == 'C':
strides.reverse()
backstrides.reverse()
+ new_shape.reverse()
self.strides = strides[:]
self.backstrides = backstrides[:]
+ self.shape = new_shape[:]
return
- #REVIEWER: wordy comment to explain what the intention was. Please
- #edit or remove.
- #We know that the product of new_shape is correct.
- #Now we must check that the new shape does not create stepping
conflicts
- # for the strides It works like this:
- # - Determine the right-to-lef tor left-to-right fastest iterating
- # dimension. Note it is not enough just to check self.order, since a
- # transpose reverses everything.
- # - Start recalculating the strides, by each dimension. Keep a running
- # cumprod of the old shape up to this dimension vs. the new shape up
- # to this dimension. Every time the products match, update the stride
- # currently in use.
- # - The strides for each of the matching pieces must also match,
- # - The stride will always be based on the old stride of the lowest
- # dimension in the chunk, since
- new_dims = range(len(new_shape))
- old_dims = range(len(self.shape))
- if self.strides[0]> self.strides[-1]:
- #This is the normal thing to do
- new_dims.reverse()
- old_dims.reverse()
- nd = 0
- od = 0
- prod_old = 1
- prod_new = self.strides[old_dims[od]]
- cur_old_stride = self.strides[old_dims[od]]
- new_strides = [0]*len(new_shape)
- while nd < len(new_dims):
- new_strides[new_dims[nd]] = cur_old_stride
- prod_new *= new_shape[nd]
- while prod_new >= prod_old:
- if prod_new == prod_old:
- #Finished an old dim on a match. All is good
- od += 1
- prod_old *= self.shape[old_dims[od]]
- cur_old_stride = self.strides[old_dims[od]]
- elif prod_new > prod_old:
- #Crossed over onto a different old_dim.
- #Strides must be "equal" as per steps
- od += 1
- if self.strides[old_dims[od]] / self.shape[old_dims[od -
1]] \
- <> self.strides[old_dims[od-1]]:
- raise OperationError(space.w_AttributeError,
space.wrap(
+ new_strides = calc_new_strides(new_shape, self.shape, self.strides)
+ if new_strides is None:
+ raise OperationError(space.w_AttributeError, space.wrap(
"incompatible shape for a non-contiguous array"))
- prod_old *= self.shape[old_dims[od]]
- nd += 1
- new_backstrides = [0]*len(new_shape)
+ new_backstrides = [0] * len(new_shape)
for nd in range(len(new_shape)):
new_backstrides[nd] = (new_shape[nd] - 1) * new_strides[nd]
- self.strides = new_strides
- self.backstrides = new_backstrides
- self.shape = new_shape
-
+ self.strides = new_strides[:]
+ self.backstrides = new_backstrides[:]
+ self.shape = new_shape[:]
+
class VirtualView(VirtualArray):
pass
diff --git a/pypy/module/micronumpy/test/test_numarray.py
b/pypy/module/micronumpy/test/test_numarray.py
--- a/pypy/module/micronumpy/test/test_numarray.py
+++ b/pypy/module/micronumpy/test/test_numarray.py
@@ -158,6 +158,13 @@
assert shape_agreement(self.space,
[5, 2], [4, 3, 5, 2]) == [4, 3, 5, 2]
+ def test_calc_new_strides(self):
+ from pypy.module.micronumpy.interp_numarray import calc_new_strides
+ assert calc_new_strides([2, 4, 3], [8, 3], [1, 16]) == [1, 2, 16]
+ assert calc_new_strides([2, 3, 4], [8, 3], [1, 16]) is None
+ assert calc_new_strides([8, 3], [2, 4, 3], [48, 6, 1]) == [6, 1]
+ assert calc_new_strides([24], [2, 4, 3], [48, 6, 1]) is None
+ assert calc_new_strides([24], [2, 4, 3], [48, 6, 2]) is None
class AppTestNumArray(BaseNumpyAppTest):
def test_type(self):
@@ -336,27 +343,29 @@
assert a.shape == (12, )
exc = raises(ValueError, "a.shape = 10")
assert str(exc.value) == "total size of new array must be unchanged"
+
def test_reshape(self):
from numpypy import array, zeros
a = array(range(12))
exc = raises(ValueError, "b = a.reshape((3, 10))")
assert str(exc.value) == "total size of new array must be unchanged"
b = a.reshape((3, 4))
+ assert b.shape == (3, 4)
assert (b == [range(4), range(4, 8), range(8, 12)]).all()
b[:, 0] = 1000
assert (a == [1000, 1, 2, 3, 1000, 5, 6, 7, 1000, 9, 10, 11]).all()
a = zeros((4, 2, 3))
a.shape = (12, 2)
+
def test_slice_reshape(self):
from numpypy import array, zeros
- a = array(range(12))
+ a = zeros((4, 2, 3))
b = a[::2, :, :]
- b.shape = (2,6)
+ b.shape = (2, 6)
exc = raises(AttributeError, "b.shape = 12")
assert str(exc.value) == \
"incompatible shape for a non-contiguous array"
- b.shape = (2, 6)
- a = array(range(12))
+ b = a[::2, :, :].reshape((2, 6))
def test_add(self):
from numpypy import array
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