Author: mattip <matti.pi...@gmail.com>
Branch: fortran-order
Changeset: r79900:4666c894b561
Date: 2015-09-30 01:38 +0300
http://bitbucket.org/pypy/pypy/changeset/4666c894b561/
Log: convert internal use of order from a char to an enum
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
@@ -140,7 +140,7 @@
dtype = find_result_type(space, args_w, [])
# concatenate does not handle ndarray subtypes, it always returns a ndarray
- res = W_NDimArray.from_shape(space, shape, dtype, 'C')
+ res = W_NDimArray.from_shape(space, shape, dtype, NPY.CORDER)
chunks = [Chunk(0, i, 1, i) for i in shape]
axis_start = 0
for arr in args_w:
diff --git a/pypy/module/micronumpy/base.py b/pypy/module/micronumpy/base.py
--- a/pypy/module/micronumpy/base.py
+++ b/pypy/module/micronumpy/base.py
@@ -38,7 +38,8 @@
self.implementation = implementation
@staticmethod
- def from_shape(space, shape, dtype, order='C', w_instance=None, zero=True):
+ def from_shape(space, shape, dtype, order=NPY.CORDER,
+ w_instance=None, zero=True):
from pypy.module.micronumpy import concrete, descriptor, boxes
from pypy.module.micronumpy.strides import calc_strides
if len(shape) > NPY.MAXDIMS:
@@ -59,8 +60,9 @@
@staticmethod
def from_shape_and_storage(space, shape, storage, dtype, storage_bytes=-1,
- order='C', owning=False, w_subtype=None,
- w_base=None, writable=True, strides=None,
start=0):
+ order=NPY.CORDER, owning=False, w_subtype=None,
+ w_base=None, writable=True, strides=None,
+ start=0):
from pypy.module.micronumpy import concrete
from pypy.module.micronumpy.strides import (calc_strides,
calc_backstrides)
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
@@ -56,6 +56,9 @@
jit.hint(len(backstrides), promote=True)
return backstrides
+ def get_flags(self):
+ return self.flags
+
def getitem(self, index):
return self.dtype.read(self, index, 0)
@@ -360,12 +363,12 @@
# but make the array storage contiguous in memory
shape = self.get_shape()
strides = self.get_strides()
- if order not in ('C', 'F'):
- raise oefmt(space.w_ValueError, "Unknown order %s in astype",
order)
+ if order not in (NPY.KEEPORDER, NPY.FORTRANORDER, NPY.CORDER):
+ raise oefmt(space.w_ValueError, "Unknown order %d in astype",
order)
if len(strides) == 0:
t_strides = []
backstrides = []
- elif order != self.order:
+ elif order in (NPY.FORTRANORDER, NPY.CORDER):
t_strides, backstrides = calc_strides(shape, dtype, order)
else:
indx_array = range(len(strides))
@@ -602,13 +605,13 @@
s = self.get_strides()[0] // dtype.elsize
except IndexError:
s = 1
- if self.order == 'C':
+ if self.order != NPY.FORTRANORDER:
new_shape.reverse()
for sh in new_shape:
strides.append(s * dtype.elsize)
backstrides.append(s * (sh - 1) * dtype.elsize)
s *= max(1, sh)
- if self.order == 'C':
+ if self.order != NPY.FORTRANORDER:
strides.reverse()
backstrides.reverse()
new_shape.reverse()
diff --git a/pypy/module/micronumpy/converters.py
b/pypy/module/micronumpy/converters.py
--- a/pypy/module/micronumpy/converters.py
+++ b/pypy/module/micronumpy/converters.py
@@ -77,9 +77,8 @@
elif order.startswith('K') or order.startswith('k'):
return NPY.KEEPORDER
else:
- raise OperationError(space.w_TypeError, space.wrap(
- "order not understood"))
-
+ raise oefmt(space.w_TypeError, "Unknown order: '%s'", order)
+ return -1
def multi_axis_converter(space, w_axis, ndim):
if space.is_none(w_axis):
diff --git a/pypy/module/micronumpy/ctors.py b/pypy/module/micronumpy/ctors.py
--- a/pypy/module/micronumpy/ctors.py
+++ b/pypy/module/micronumpy/ctors.py
@@ -4,9 +4,10 @@
from rpython.rlib.rstring import strip_spaces
from rpython.rtyper.lltypesystem import lltype, rffi
from pypy.module.micronumpy import descriptor, loop, support
-from pypy.module.micronumpy.base import (
+from pypy.module.micronumpy.base import (wrap_impl,
W_NDimArray, convert_to_array, W_NumpyObject)
-from pypy.module.micronumpy.converters import shape_converter
+from pypy.module.micronumpy.converters import shape_converter, order_converter
+import pypy.module.micronumpy.constants as NPY
def build_scalar(space, w_dtype, w_state):
@@ -99,13 +100,8 @@
dtype = descriptor.decode_w_dtype(space, w_dtype)
if space.is_none(w_order):
- order = 'C'
- else:
- order = space.str_w(w_order)
- if order == 'K':
- order = 'C'
- if order != 'C': # or order != 'F':
- raise oefmt(space.w_ValueError, "Unknown order: %s", order)
+ w_order = space.wrap('C')
+ npy_order = order_converter(space, w_order, NPY.CORDER)
if isinstance(w_object, W_NDimArray):
if (dtype is None or w_object.get_dtype() is dtype):
@@ -124,7 +120,7 @@
copy = True
if copy:
shape = w_object.get_shape()
- w_arr = W_NDimArray.from_shape(space, shape, dtype, order=order)
+ w_arr = W_NDimArray.from_shape(space, shape, dtype,
order=npy_order)
if support.product(shape) == 1:
w_arr.set_scalar_value(dtype.coerce(space,
w_object.implementation.getitem(0)))
@@ -154,7 +150,7 @@
# promote S0 -> S1, U0 -> U1
dtype = descriptor.variable_dtype(space, dtype.char + '1')
- w_arr = W_NDimArray.from_shape(space, shape, dtype, order=order)
+ w_arr = W_NDimArray.from_shape(space, shape, dtype, order=npy_order)
if support.product(shape) == 1: # safe from overflow since from_shape
checks
w_arr.set_scalar_value(dtype.coerce(space, elems_w[0]))
else:
@@ -230,6 +226,7 @@
@unwrap_spec(subok=bool)
def empty_like(space, w_a, w_dtype=None, w_order=None, subok=True):
w_a = convert_to_array(space, w_a)
+ npy_order = order_converter(space, w_order, w_a.get_order())
if space.is_none(w_dtype):
dtype = w_a.get_dtype()
else:
@@ -237,7 +234,16 @@
space.call_function(space.gettypefor(descriptor.W_Dtype), w_dtype))
if dtype.is_str_or_unicode() and dtype.elsize < 1:
dtype = descriptor.variable_dtype(space, dtype.char + '1')
+ if npy_order == NPY.KEEPORDER:
+ # Try to copy the stride pattern
+ impl = w_a.implementation.astype(space, dtype, npy_order)
+ if subok:
+ w_type = space.type(w_a)
+ else:
+ w_type = None
+ return wrap_impl(space, w_type, w_a, impl)
return W_NDimArray.from_shape(space, w_a.get_shape(), dtype=dtype,
+ order=npy_order,
w_instance=w_a if subok else None,
zero=False)
diff --git a/pypy/module/micronumpy/loop.py b/pypy/module/micronumpy/loop.py
--- a/pypy/module/micronumpy/loop.py
+++ b/pypy/module/micronumpy/loop.py
@@ -680,7 +680,8 @@
def tostring(space, arr):
builder = StringBuilder()
iter, state = arr.create_iter()
- w_res_str = W_NDimArray.from_shape(space, [1], arr.get_dtype(), order='C')
+ w_res_str = W_NDimArray.from_shape(space, [1], arr.get_dtype(),
+ order=NPY.CORDER)
itemsize = arr.get_dtype().elsize
with w_res_str.implementation as storage:
res_str_casted = rffi.cast(rffi.CArrayPtr(lltype.Char),
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
@@ -97,7 +97,10 @@
self.fill(space, self.get_dtype().coerce(space, w_value))
def descr_tostring(self, space, w_order=None):
- order = order_converter(space, w_order, NPY.CORDER)
+ try:
+ order = order_converter(space, w_order, NPY.CORDER)
+ except OperationError as e:
+ raise oefmt(space.w_TypeError, "order not understood")
if order == NPY.FORTRANORDER:
raise OperationError(space.w_NotImplementedError, space.wrap(
"unsupported value for order"))
@@ -365,7 +368,12 @@
return self.implementation.getitem(self.implementation.start)
def descr_copy(self, space, w_order=None):
- order = order_converter(space, w_order, NPY.KEEPORDER)
+ if w_order is None:
+ order = NPY.KEEPORDER
+ elif space.isinstance_w(w_order, space.w_int):
+ order = space.int_w(w_order)
+ else:
+ order = order_converter(space, w_order, NPY.KEEPORDER)
if order == NPY.FORTRANORDER:
raise OperationError(space.w_NotImplementedError, space.wrap(
"unsupported value for order"))
@@ -631,7 +639,7 @@
space.newtuple([space.wrap(addr),
space.w_False]))
space.setitem_str(w_d, 'shape', self.descr_get_shape(space))
space.setitem_str(w_d, 'typestr',
self.get_dtype().descr_get_str(space))
- if self.implementation.order == 'C':
+ if self.implementation.order == NPY.CORDER:
# Array is contiguous, no strides in the interface.
strides = space.w_None
else:
@@ -690,8 +698,9 @@
"according to the rule %s",
space.str_w(self.get_dtype().descr_repr(space)),
space.str_w(new_dtype.descr_repr(space)), casting)
- order = support.get_order_as_CF(self.get_order(), order)
- if (not copy and new_dtype == self.get_dtype() and order ==
self.get_order()
+ order = order_converter(space, space.wrap(order), self.get_order())
+ if (not copy and new_dtype == self.get_dtype()
+ and (order in (NPY.KEEPORDER, NPY.ANYORDER) or order ==
self.get_order())
and (subok or type(self) is W_NDimArray)):
return self
impl = self.implementation
@@ -970,7 +979,7 @@
raise OperationError(space.w_ValueError, space.wrap(
"new type not compatible with array."))
# Adapt the smallest dim to the new itemsize
- if self.get_order() == 'F':
+ if self.get_order() == NPY.FORTRANORDER:
minstride = strides[0]
mini = 0
else:
@@ -1134,7 +1143,7 @@
matches = True
if dtype != out.get_dtype():
matches = False
- elif not out.implementation.order == "C":
+ elif not out.implementation.order == NPY.CORDER:
matches = False
elif out.ndims() != len(out_shape):
matches = False
@@ -1403,10 +1412,6 @@
strides=strides)
order = order_converter(space, w_order, NPY.CORDER)
- if order == NPY.CORDER:
- order = 'C'
- else:
- order = 'F'
if space.is_w(w_subtype, space.gettypefor(W_NDimArray)):
return W_NDimArray.from_shape(space, shape, dtype, order)
strides, backstrides = calc_strides(shape, dtype.base, order)
@@ -1443,7 +1448,7 @@
raise OperationError(space.w_ValueError, space.wrap(
"subtype must be a subtype of ndarray, not a class instance"))
return W_NDimArray.from_shape_and_storage(space, shape, storage, dtype,
- buf_len, 'C', False,
w_subtype,
+ buf_len, NPY.CORDER, False,
w_subtype,
strides=strides)
else:
return W_NDimArray.from_shape_and_storage(space, shape, storage, dtype,
diff --git a/pypy/module/micronumpy/nditer.py b/pypy/module/micronumpy/nditer.py
--- a/pypy/module/micronumpy/nditer.py
+++ b/pypy/module/micronumpy/nditer.py
@@ -11,6 +11,8 @@
shape_agreement,
shape_agreement_multiple)
from pypy.module.micronumpy.casting import (find_binop_result_dtype,
can_cast_array, can_cast_type)
+import pypy.module.micronumpy.constants as NPY
+from pypy.module.micronumpy.converters import order_converter
def parse_op_arg(space, name, w_op_flags, n, parse_one_arg):
@@ -144,9 +146,9 @@
def is_backward(imp, order):
- if order == 'K' or (order == 'C' and imp.order == 'C'):
+ if order == NPY.KEEPORDER or (order == NPY.CORDER and imp.order ==
NPY.CORDER):
return False
- elif order == 'F' and imp.order == 'C':
+ elif order == NPY.FORTRANORDER and imp.order == NPY.CORDER:
return True
else:
raise NotImplementedError('not implemented yet')
@@ -234,7 +236,7 @@
continue
assert isinstance(op_it, ArrayIter)
indx = len(op_it.strides)
- if it.order == 'F':
+ if it.order == NPY.FORTRANORDER:
indx = len(op_it.array.strides) - indx
assert indx >=0
astrides = op_it.array.strides[indx:]
@@ -250,7 +252,7 @@
it.order)
it.iters[i] = (new_iter, new_iter.reset())
if len(it.shape) > 1:
- if it.order == 'F':
+ if it.order == NPY.FORTRANORDER:
it.shape = it.shape[1:]
else:
it.shape = it.shape[:-1]
@@ -261,10 +263,10 @@
break
# Always coalesce at least one
for i in range(len(it.iters)):
- new_iter = coalesce_iter(it.iters[i][0], it.op_flags[i], it, 'C')
+ new_iter = coalesce_iter(it.iters[i][0], it.op_flags[i], it,
NPY.CORDER)
it.iters[i] = (new_iter, new_iter.reset())
if len(it.shape) > 1:
- if it.order == 'F':
+ if it.order == NPY.FORTRANORDER:
it.shape = it.shape[1:]
else:
it.shape = it.shape[:-1]
@@ -287,7 +289,7 @@
return old_iter
strides = old_iter.strides
backstrides = old_iter.backstrides
- if order == 'F':
+ if order == NPY.FORTRANORDER:
new_shape = shape[1:]
new_strides = strides[1:]
new_backstrides = backstrides[1:]
@@ -346,7 +348,8 @@
class W_NDIter(W_NumpyObject):
_immutable_fields_ = ['ndim', ]
def __init__(self, space, w_seq, w_flags, w_op_flags, w_op_dtypes,
- w_casting, w_op_axes, w_itershape, buffersize=0, order='K'):
+ w_casting, w_op_axes, w_itershape, buffersize=0,
+ order=NPY.KEEPORDER):
self.order = order
self.external_loop = False
self.buffered = False
@@ -439,12 +442,15 @@
str(self.shape))
if self.tracked_index != "":
- if self.order == "K":
- self.order = self.seq[0].implementation.order
+ order = self.order
+ if order == NPY.KEEPORDER:
+ order = self.seq[0].implementation.order
if self.tracked_index == "multi":
backward = False
else:
- backward = self.order != self.tracked_index
+ backward = ((
+ order == NPY.CORDER and self.tracked_index != 'C') or (
+ order == NPY.FORTRANORDER and self.tracked_index != 'F'))
self.index_iter = IndexIterator(self.shape, backward=backward)
# handle w_op_dtypes part 2: copy where needed if possible
@@ -456,7 +462,6 @@
self.dtypes[i] = seq_d
elif self_d != seq_d:
impl = self.seq[i].implementation
- order = support.get_order_as_CF(impl.order, self.order)
if self.buffered or 'r' in self.op_flags[i].tmp_copy:
if not can_cast_array(
space, self.seq[i], self_d, self.casting):
@@ -466,7 +471,7 @@
space.str_w(seq_d.descr_repr(space)),
space.str_w(self_d.descr_repr(space)),
self.casting)
-
+ order = support.get_order_as_CF(impl.order,
self.order)
new_impl = impl.astype(space, self_d,
order).copy(space)
self.seq[i] = W_NDimArray(new_impl)
else:
@@ -704,13 +709,15 @@
@unwrap_spec(w_flags=WrappedDefault(None), w_op_flags=WrappedDefault(None),
- w_op_dtypes=WrappedDefault(None), order=str,
+ w_op_dtypes=WrappedDefault(None), w_order=WrappedDefault(None),
w_casting=WrappedDefault(None), w_op_axes=WrappedDefault(None),
- w_itershape=WrappedDefault(None), buffersize=int)
+ w_itershape=WrappedDefault(None), w_buffersize=WrappedDefault(0))
def descr_new_nditer(space, w_subtype, w_seq, w_flags, w_op_flags, w_op_dtypes,
- w_casting, w_op_axes, w_itershape, buffersize=0, order='K'):
+ w_casting, w_op_axes, w_itershape, w_buffersize, w_order):
+ npy_order = order_converter(space, w_order, NPY.KEEPORDER)
+ buffersize = space.int_w(w_buffersize)
return W_NDIter(space, w_seq, w_flags, w_op_flags, w_op_dtypes, w_casting,
w_op_axes,
- w_itershape, buffersize, order)
+ w_itershape, buffersize, npy_order)
W_NDIter.typedef = TypeDef('numpy.nditer',
__new__ = interp2app(descr_new_nditer),
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
@@ -371,14 +371,14 @@
backstrides = []
s = 1
shape_rev = shape[:]
- if order == 'C':
+ if order in [NPY.CORDER, NPY.ANYORDER]:
shape_rev.reverse()
for sh in shape_rev:
slimit = max(sh, 1)
strides.append(s * dtype.elsize)
backstrides.append(s * (slimit - 1) * dtype.elsize)
s *= slimit
- if order == 'C':
+ if order in [NPY.CORDER, NPY.ANYORDER]:
strides.reverse()
backstrides.reverse()
return strides, backstrides
@@ -406,7 +406,7 @@
last_step = 1
oldI = 0
new_strides = []
- if order == 'F':
+ if order == NPY.FORTRANORDER:
for i in range(len(old_shape)):
steps.append(old_strides[i] / last_step)
last_step *= old_shape[i]
@@ -426,7 +426,7 @@
if oldI < len(old_shape):
cur_step = steps[oldI]
n_old_elems_to_use *= old_shape[oldI]
- elif order == 'C':
+ else:
for i in range(len(old_shape) - 1, -1, -1):
steps.insert(0, old_strides[i] / last_step)
last_step *= old_shape[i]
diff --git a/pypy/module/micronumpy/support.py
b/pypy/module/micronumpy/support.py
--- a/pypy/module/micronumpy/support.py
+++ b/pypy/module/micronumpy/support.py
@@ -7,6 +7,7 @@
from pypy.interpreter.typedef import GetSetProperty
from pypy.objspace.std.typeobject import W_TypeObject
from pypy.objspace.std.objspace import StdObjSpace
+from pypy.module.micronumpy import constants as NPY
def issequence_w(space, w_obj):
from pypy.module.micronumpy.base import W_NDimArray
@@ -173,15 +174,11 @@
return space.is_true(space.gt(w_priority_r, w_priority_l))
def get_order_as_CF(proto_order, req_order):
- if req_order == 'C':
- return 'C'
- elif req_order == 'F':
- return 'F'
- elif req_order == 'K':
- return proto_order
- elif req_order == 'A':
- return proto_order
-
+ if req_order == NPY.CORDER:
+ return NPY.CORDER
+ elif req_order == NPY.FORTRANORDER:
+ return NPY.FORTRANORDER
+ return proto_order
def descr_set_docstring(space, w_obj, w_docstring):
if not isinstance(space, StdObjSpace):
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
@@ -6,6 +6,7 @@
from pypy.module.micronumpy.appbridge import get_appbridge_cache
from pypy.module.micronumpy.strides import Chunk, new_view, EllipsisChunk
from pypy.module.micronumpy.ndarray import W_NDimArray
+import pypy.module.micronumpy.constants as NPY
from pypy.module.micronumpy.test.test_base import BaseNumpyAppTest
@@ -45,20 +46,20 @@
return self.space.newtuple(args_w)
def test_strides_f(self):
- a = create_array(self.space, [10, 5, 3], MockDtype(), order='F')
+ a = create_array(self.space, [10, 5, 3], MockDtype(),
order=NPY.FORTRANORDER)
assert a.strides == [1, 10, 50]
assert a.backstrides == [9, 40, 100]
def test_strides_c(self):
- a = create_array(self.space, [10, 5, 3], MockDtype(), order='C')
+ a = create_array(self.space, [10, 5, 3], MockDtype(), order=NPY.CORDER)
assert a.strides == [15, 3, 1]
assert a.backstrides == [135, 12, 2]
- a = create_array(self.space, [1, 0, 7], MockDtype(), order='C')
+ a = create_array(self.space, [1, 0, 7], MockDtype(), order=NPY.CORDER)
assert a.strides == [7, 7, 1]
assert a.backstrides == [0, 0, 6]
def test_create_slice_f(self):
- a = create_array(self.space, [10, 5, 3], MockDtype(), order='F')
+ a = create_array(self.space, [10, 5, 3], MockDtype(),
order=NPY.FORTRANORDER)
s = create_slice(self.space, a, [Chunk(3, 0, 0, 1)])
assert s.start == 3
assert s.strides == [10, 50]
@@ -77,7 +78,7 @@
assert s.shape == [10, 3]
def test_create_slice_c(self):
- a = create_array(self.space, [10, 5, 3], MockDtype(), order='C')
+ a = create_array(self.space, [10, 5, 3], MockDtype(), order=NPY.CORDER)
s = create_slice(self.space, a, [Chunk(3, 0, 0, 1)])
assert s.start == 45
assert s.strides == [3, 1]
@@ -97,7 +98,7 @@
assert s.shape == [10, 3]
def test_slice_of_slice_f(self):
- a = create_array(self.space, [10, 5, 3], MockDtype(), order='F')
+ a = create_array(self.space, [10, 5, 3], MockDtype(),
order=NPY.FORTRANORDER)
s = create_slice(self.space, a, [Chunk(5, 0, 0, 1)])
assert s.start == 5
s2 = create_slice(self.space, s, [Chunk(3, 0, 0, 1)])
@@ -114,7 +115,7 @@
assert s2.start == 1 * 15 + 2 * 3
def test_slice_of_slice_c(self):
- a = create_array(self.space, [10, 5, 3], MockDtype(), order='C')
+ a = create_array(self.space, [10, 5, 3], MockDtype(), order=NPY.CORDER)
s = create_slice(self.space, a, [Chunk(5, 0, 0, 1)])
assert s.start == 15 * 5
s2 = create_slice(self.space, s, [Chunk(3, 0, 0, 1)])
@@ -131,14 +132,14 @@
assert s2.start == 1 * 15 + 2 * 3
def test_negative_step_f(self):
- a = create_array(self.space, [10, 5, 3], MockDtype(), order='F')
+ a = create_array(self.space, [10, 5, 3], MockDtype(),
order=NPY.FORTRANORDER)
s = create_slice(self.space, a, [Chunk(9, -1, -2, 5)])
assert s.start == 9
assert s.strides == [-2, 10, 50]
assert s.backstrides == [-8, 40, 100]
def test_negative_step_c(self):
- a = create_array(self.space, [10, 5, 3], MockDtype(), order='C')
+ a = create_array(self.space, [10, 5, 3], MockDtype(), order=NPY.CORDER)
s = create_slice(self.space, a, [Chunk(9, -1, -2, 5)])
assert s.start == 135
assert s.strides == [-30, 3, 1]
@@ -155,17 +156,17 @@
def test_calc_new_strides(self):
from pypy.module.micronumpy.strides import calc_new_strides
- assert calc_new_strides([2, 4], [4, 2], [4, 2], "C") == [8, 2]
- assert calc_new_strides([2, 4, 3], [8, 3], [1, 16], 'F') == [1, 2, 16]
- assert calc_new_strides([2, 3, 4], [8, 3], [1, 16], 'F') is None
- assert calc_new_strides([24], [2, 4, 3], [48, 6, 1], 'C') is None
- assert calc_new_strides([24], [2, 4, 3], [24, 6, 2], 'C') == [2]
- assert calc_new_strides([105, 1], [3, 5, 7], [35, 7, 1],'C') == [1, 1]
- assert calc_new_strides([1, 105], [3, 5, 7], [35, 7, 1],'C') == [105,
1]
- assert calc_new_strides([1, 105], [3, 5, 7], [35, 7, 1],'F') is None
- assert calc_new_strides([1, 1, 1, 105, 1], [15, 7], [7, 1],'C') == \
+ assert calc_new_strides([2, 4], [4, 2], [4, 2], NPY.CORDER) == [8, 2]
+ assert calc_new_strides([2, 4, 3], [8, 3], [1, 16], NPY.FORTRANORDER)
== [1, 2, 16]
+ assert calc_new_strides([2, 3, 4], [8, 3], [1, 16], NPY.FORTRANORDER)
is None
+ assert calc_new_strides([24], [2, 4, 3], [48, 6, 1], NPY.CORDER) is
None
+ assert calc_new_strides([24], [2, 4, 3], [24, 6, 2], NPY.CORDER) == [2]
+ assert calc_new_strides([105, 1], [3, 5, 7], [35, 7, 1],NPY.CORDER) ==
[1, 1]
+ assert calc_new_strides([1, 105], [3, 5, 7], [35, 7, 1],NPY.CORDER) ==
[105, 1]
+ assert calc_new_strides([1, 105], [3, 5, 7], [35, 7,
1],NPY.FORTRANORDER) is None
+ assert calc_new_strides([1, 1, 1, 105, 1], [15, 7], [7, 1],NPY.CORDER)
== \
[105, 105, 105, 1, 1]
- assert calc_new_strides([1, 1, 105, 1, 1], [7, 15], [1, 7],'F') == \
+ assert calc_new_strides([1, 1, 105, 1, 1], [7, 15], [1,
7],NPY.FORTRANORDER) == \
[1, 1, 1, 105, 105]
def test_find_shape(self):
diff --git a/pypy/module/micronumpy/test/test_nditer.py
b/pypy/module/micronumpy/test/test_nditer.py
--- a/pypy/module/micronumpy/test/test_nditer.py
+++ b/pypy/module/micronumpy/test/test_nditer.py
@@ -120,8 +120,8 @@
skip('Fortran order not implemented')
it = nditer([a, b])
-
- assert list(it) == zip(range(1, 5), range(1, 5))
+ r = list(it)
+ assert r == zip(range(1, 5), range(1, 5))
def test_interface(self):
from numpy import arange, nditer, zeros
diff --git a/pypy/module/micronumpy/ufuncs.py b/pypy/module/micronumpy/ufuncs.py
--- a/pypy/module/micronumpy/ufuncs.py
+++ b/pypy/module/micronumpy/ufuncs.py
@@ -667,9 +667,9 @@
for dt_in, dt_out in self.dtypes:
if can_cast_to(dtype, dt_in) and dt_out == dt_in:
return dt_in
- raise ValueError(
+ raise oefmt(space.w_ValueError,
"could not find a matching type for %s.accumulate, "
- "requested type has type code '%s'" % (self.name, dtype.char))
+ "requested type has type code '%s'", self.name, dtype.char)
def _calc_dtype(self, space, l_dtype, r_dtype, out, casting,
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