[pypy-commit] pypy default: backout the merge of str-dtype-improvement branch. Seems new numpy is not
fijal
noreply at buildbot.pypy.org
Fri Mar 22 18:50:04 CET 2013
Author: Maciej Fijalkowski <fijall at gmail.com>
Branch:
Changeset: r62661:c967eefd1789
Date: 2013-03-21 22:59 -0700
http://bitbucket.org/pypy/pypy/changeset/c967eefd1789/
Log: backout the merge of str-dtype-improvement branch. Seems new numpy
is not doing it any more (also mattip is flying so it would take him
a while to look at it). Feel free to redo if there is some evidence
this is the intended behavior
diff --git a/pypy/module/micronumpy/arrayimpl/concrete.py b/pypy/module/micronumpy/arrayimpl/concrete.py
--- a/pypy/module/micronumpy/arrayimpl/concrete.py
+++ b/pypy/module/micronumpy/arrayimpl/concrete.py
@@ -49,8 +49,8 @@
return
shape = shape_agreement(space, self.get_shape(), arr)
if impl.storage == self.storage:
- impl = impl.copy(space)
- loop.setslice(space, shape, self, impl)
+ impl = impl.copy()
+ loop.setslice(shape, self, impl)
def get_size(self):
return self.size // self.dtype.itemtype.get_element_size()
@@ -245,12 +245,12 @@
return SliceArray(self.start, strides,
backstrides, shape, self, orig_array)
- def copy(self, space):
+ def copy(self):
strides, backstrides = support.calc_strides(self.get_shape(), self.dtype,
self.order)
impl = ConcreteArray(self.get_shape(), self.dtype, self.order, strides,
backstrides)
- return loop.setslice(space, self.get_shape(), impl, self)
+ return loop.setslice(self.get_shape(), impl, self)
def create_axis_iter(self, shape, dim, cum):
return iter.AxisIterator(self, shape, dim, cum)
@@ -281,11 +281,7 @@
def astype(self, space, dtype):
new_arr = W_NDimArray.from_shape(self.get_shape(), dtype)
- if dtype.is_str_or_unicode():
- raise OperationError(space.w_NotImplementedError, space.wrap(
- "astype(%s) not implemented yet" % self.dtype))
- else:
- loop.setslice(space, new_arr.get_shape(), new_arr.implementation, self)
+ loop.copy_from_to(self, new_arr.implementation, dtype)
return new_arr
class ConcreteArrayNotOwning(BaseConcreteArray):
diff --git a/pypy/module/micronumpy/arrayimpl/scalar.py b/pypy/module/micronumpy/arrayimpl/scalar.py
--- a/pypy/module/micronumpy/arrayimpl/scalar.py
+++ b/pypy/module/micronumpy/arrayimpl/scalar.py
@@ -50,7 +50,7 @@
def set_scalar_value(self, w_val):
self.value = w_val.convert_to(self.dtype)
- def copy(self, space):
+ def copy(self):
scalar = Scalar(self.dtype)
scalar.value = self.value
return scalar
diff --git a/pypy/module/micronumpy/interp_arrayops.py b/pypy/module/micronumpy/interp_arrayops.py
--- a/pypy/module/micronumpy/interp_arrayops.py
+++ b/pypy/module/micronumpy/interp_arrayops.py
@@ -116,21 +116,12 @@
"all the input arrays must have same number of dimensions"))
elif i == _axis:
shape[i] += axis_size
- a_dt = arr.get_dtype()
- if dtype.is_record_type() and a_dt.is_record_type():
- #Record types must match
- for f in dtype.fields:
- if f not in a_dt.fields or \
- dtype.fields[f] != a_dt.fields[f]:
- raise OperationError(space.w_TypeError,
- space.wrap("record type mismatch"))
- elif dtype.is_record_type() or a_dt.is_record_type():
- raise OperationError(space.w_TypeError,
- space.wrap("invalid type promotion"))
dtype = interp_ufuncs.find_binop_result_dtype(space, dtype,
arr.get_dtype())
if _axis < 0 or len(arr.get_shape()) <= _axis:
raise operationerrfmt(space.w_IndexError, "axis %d out of bounds [0, %d)", axis, len(shape))
+ if _axis < 0 or len(shape) <= _axis:
+ raise operationerrfmt(space.w_IndexError, "axis %d out of bounds [0, %d)", axis, len(shape))
res = W_NDimArray.from_shape(shape, dtype, 'C')
chunks = [Chunk(0, i, 1, i) for i in shape]
axis_start = 0
diff --git a/pypy/module/micronumpy/interp_boxes.py b/pypy/module/micronumpy/interp_boxes.py
--- a/pypy/module/micronumpy/interp_boxes.py
+++ b/pypy/module/micronumpy/interp_boxes.py
@@ -283,10 +283,6 @@
dtype.itemtype.store(self.arr, self.ofs, ofs,
dtype.coerce(space, w_value))
- def convert_to(self, dtype):
- # if we reach here, the record fields are guarenteed to match.
- return self
-
class W_CharacterBox(W_FlexibleBox):
pass
@@ -300,6 +296,10 @@
arr.storage[i] = arg[i]
return W_StringBox(arr, 0, arr.dtype)
+ def convert_to(self, dtype):
+ from pypy.module.micronumpy import types
+ assert isinstance(dtype.itemtype, types.StringType)
+ return self
class W_UnicodeBox(W_CharacterBox):
def descr__new__unicode_box(space, w_subtype, w_arg):
@@ -313,6 +313,11 @@
# arr.storage[i] = arg[i]
return W_UnicodeBox(arr, 0, arr.dtype)
+ def convert_to(self, dtype):
+ from pypy.module.micronumpy import types
+ assert isinstance(dtype.itemtype, types.UnicodeType)
+ return self
+
class W_ComplexFloatingBox(W_InexactBox):
_attrs_ = ()
diff --git a/pypy/module/micronumpy/interp_dtype.py b/pypy/module/micronumpy/interp_dtype.py
--- a/pypy/module/micronumpy/interp_dtype.py
+++ b/pypy/module/micronumpy/interp_dtype.py
@@ -71,8 +71,6 @@
def box_complex(self, real, imag):
return self.itemtype.box_complex(real, imag)
- def build_and_convert(self, space, box):
- return self.itemtype.build_and_convert(space, self, box)
def coerce(self, space, w_item):
return self.itemtype.coerce(space, self, w_item)
diff --git a/pypy/module/micronumpy/interp_flatiter.py b/pypy/module/micronumpy/interp_flatiter.py
--- a/pypy/module/micronumpy/interp_flatiter.py
+++ b/pypy/module/micronumpy/interp_flatiter.py
@@ -76,7 +76,7 @@
base = self.base
start, stop, step, length = space.decode_index4(w_idx, base.get_size())
arr = convert_to_array(space, w_value)
- loop.flatiter_setitem(space, self.base, arr, start, step, length)
+ loop.flatiter_setitem(self.base, arr, start, step, length)
def descr_iter(self):
return self
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
@@ -258,14 +258,17 @@
return self.implementation.get_scalar_value()
def descr_copy(self, space):
- return W_NDimArray(self.implementation.copy(space))
+ return W_NDimArray(self.implementation.copy())
def descr_get_real(self, space):
return W_NDimArray(self.implementation.get_real(self))
def descr_get_imag(self, space):
ret = self.implementation.get_imag(self)
- return W_NDimArray(ret)
+ if ret:
+ return W_NDimArray(ret)
+ raise OperationError(space.w_NotImplementedError,
+ space.wrap('imag not implemented for this dtype'))
def descr_set_real(self, space, w_value):
# copy (broadcast) values into self
diff --git a/pypy/module/micronumpy/interp_ufuncs.py b/pypy/module/micronumpy/interp_ufuncs.py
--- a/pypy/module/micronumpy/interp_ufuncs.py
+++ b/pypy/module/micronumpy/interp_ufuncs.py
@@ -414,7 +414,7 @@
if promote_to_float:
return find_unaryop_result_dtype(space, dt2, promote_to_float=True)
# If they're the same kind, choose the greater one.
- if dt1.kind == dt2.kind and not dt2.is_flexible_type():
+ if dt1.kind == dt2.kind:
return dt2
# Everything promotes to float, and bool promotes to everything.
@@ -434,23 +434,7 @@
elif dt2.num == 10 or (LONG_BIT == 64 and dt2.num == 8):
# UInt64 + signed = Float64
dtypenum = 12
- elif dt2.is_flexible_type():
- # For those operations that get here (concatenate, stack),
- # flexible types take precedence over numeric type
- if dt2.is_record_type():
- return dt2
- if dt1.is_str_or_unicode():
- if dt2.num == 18:
- if dt2.itemtype.get_element_size() >= \
- dt1.itemtype.get_element_size():
- return dt2
- return dt1
- if dt2.itemtype.get_element_size() >= \
- dt1.itemtype.get_element_size():
- return dt2
- return dt1
- return dt2
- else:
+ else:
# increase to the next signed type
dtypenum = dt2.num + 1
newdtype = interp_dtype.get_dtype_cache(space).dtypes_by_num[dtypenum]
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
@@ -65,19 +65,12 @@
obj_iter.next()
return out
-setslice_driver1 = jit.JitDriver(name='numpy_setslice1',
+setslice_driver = jit.JitDriver(name='numpy_setslice',
greens = ['shapelen', 'dtype'],
- reds = 'auto')
-setslice_driver2 = jit.JitDriver(name='numpy_setslice2',
- greens = ['shapelen', 'dtype'],
- reds = 'auto')
+ reds = ['target', 'source', 'target_iter',
+ 'source_iter'])
-def setslice(space, shape, target, source):
- if target.dtype.is_str_or_unicode():
- return setslice_build_and_convert(space, shape, target, source)
- return setslice_to(space, shape, target, source)
-
-def setslice_to(space, shape, target, source):
+def setslice(shape, target, source):
# note that unlike everything else, target and source here are
# array implementations, not arrays
target_iter = target.create_iter(shape)
@@ -85,26 +78,15 @@
dtype = target.dtype
shapelen = len(shape)
while not target_iter.done():
- setslice_driver1.jit_merge_point(shapelen=shapelen, dtype=dtype)
+ setslice_driver.jit_merge_point(shapelen=shapelen, dtype=dtype,
+ target=target, source=source,
+ target_iter=target_iter,
+ source_iter=source_iter)
target_iter.setitem(source_iter.getitem().convert_to(dtype))
target_iter.next()
source_iter.next()
return target
-def setslice_build_and_convert(space, shape, target, source):
- # note that unlike everything else, target and source here are
- # array implementations, not arrays
- target_iter = target.create_iter(shape)
- source_iter = source.create_iter(shape)
- dtype = target.dtype
- shapelen = len(shape)
- while not target_iter.done():
- setslice_driver2.jit_merge_point(shapelen=shapelen, dtype=dtype)
- target_iter.setitem(dtype.build_and_convert(space, source_iter.getitem()))
- target_iter.next()
- source_iter.next()
- return target
-
reduce_driver = jit.JitDriver(name='numpy_reduce',
greens = ['shapelen', 'func', 'done_func',
'calc_dtype', 'identity'],
@@ -376,27 +358,17 @@
ri.next()
return res
-flatiter_setitem_driver1 = jit.JitDriver(name = 'numpy_flatiter_setitem1',
+flatiter_setitem_driver = jit.JitDriver(name = 'numpy_flatiter_setitem',
greens = ['dtype'],
reds = 'auto')
-flatiter_setitem_driver2 = jit.JitDriver(name = 'numpy_flatiter_setitem2',
- greens = ['dtype'],
- reds = 'auto')
-
-def flatiter_setitem(space, arr, val, start, step, length):
- dtype = arr.get_dtype()
- if dtype.is_str_or_unicode():
- return flatiter_setitem_build_and_convert(space, arr, val, start, step, length)
- return flatiter_setitem_to(space, arr, val, start, step, length)
-
-def flatiter_setitem_to(space, arr, val, start, step, length):
+def flatiter_setitem(arr, val, start, step, length):
dtype = arr.get_dtype()
arr_iter = arr.create_iter()
val_iter = val.create_iter()
arr_iter.next_skip_x(start)
while length > 0:
- flatiter_setitem_driver1.jit_merge_point(dtype=dtype)
+ flatiter_setitem_driver.jit_merge_point(dtype=dtype)
arr_iter.setitem(val_iter.getitem().convert_to(dtype))
# need to repeat i_nput values until all assignments are done
arr_iter.next_skip_x(step)
@@ -405,21 +377,6 @@
# WTF numpy?
val_iter.reset()
-def flatiter_setitem_build_and_convert(space, arr, val, start, step, length):
- dtype = arr.get_dtype()
- arr_iter = arr.create_iter()
- val_iter = val.create_iter()
- arr_iter.next_skip_x(start)
- while length > 0:
- flatiter_setitem_driver2.jit_merge_point(dtype=dtype)
- arr_iter.setitem(dtype.build_and_convert(space, val_iter.getitem()))
- # need to repeat i_nput values until all assignments are done
- arr_iter.next_skip_x(step)
- length -= 1
- val_iter.next()
- # WTF numpy?
- val_iter.reset()
-
fromstring_driver = jit.JitDriver(name = 'numpy_fromstring',
greens = ['itemsize', 'dtype'],
reds = 'auto')
@@ -504,6 +461,18 @@
val_arr.descr_getitem(space, w_idx))
iter.next()
+copy_from_to_driver = jit.JitDriver(greens = ['dtype'],
+ reds = 'auto')
+
+def copy_from_to(from_, to, dtype):
+ from_iter = from_.create_iter()
+ to_iter = to.create_iter()
+ while not from_iter.done():
+ copy_from_to_driver.jit_merge_point(dtype=dtype)
+ to_iter.setitem(from_iter.getitem().convert_to(dtype))
+ to_iter.next()
+ from_iter.next()
+
byteswap_driver = jit.JitDriver(greens = ['dtype'],
reds = 'auto')
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
@@ -1480,32 +1480,6 @@
a = (a + a)[::2]
b = concatenate((a[:3], a[-3:]))
assert (b == [2, 6, 10, 2, 6, 10]).all()
- a = concatenate((array([1]), array(['abc'])))
- assert str(a.dtype) == '|S3'
- a = concatenate((array([]), array(['abc'])))
- assert a[0] == 'abc'
- a = concatenate((['abcdef'], ['abc']))
- assert a[0] == 'abcdef'
- assert str(a.dtype) == '|S6'
-
- def test_record_concatenate(self):
- # only an exact match can succeed
- from numpypy import zeros, concatenate
- a = concatenate((zeros((2,),dtype=[('x', int), ('y', float)]),
- zeros((2,),dtype=[('x', int), ('y', float)])))
- assert a.shape == (4,)
- exc = raises(TypeError, concatenate,
- (zeros((2,), dtype=[('x', int), ('y', float)]),
- (zeros((2,), dtype=[('x', float), ('y', float)]))))
- assert str(exc.value).startswith('record type mismatch')
- exc = raises(TypeError, concatenate, ([1], zeros((2,),
- dtype=[('x', int), ('y', float)])))
- assert str(exc.value).startswith('invalid type promotion')
- exc = raises(TypeError, concatenate, (['abc'], zeros((2,),
- dtype=[('x', int), ('y', float)])))
- assert str(exc.value).startswith('invalid type promotion')
-
-
def test_std(self):
from numpypy import array
@@ -1676,12 +1650,6 @@
a = array('x').astype('S3').dtype
assert a.itemsize == 3
- # scalar vs. array
- try:
- a = array([1, 2, 3.14156]).astype('S3').dtype
- assert a.itemsize == 3
- except NotImplementedError:
- skip('astype("S3") not implemented for numeric arrays')
def test_base(self):
from numpypy import array
@@ -1987,7 +1955,7 @@
assert (a.transpose() == b).all()
def test_flatiter(self):
- from numpypy import array, flatiter, arange, zeros
+ from numpypy import array, flatiter, arange
a = array([[10, 30], [40, 60]])
f_iter = a.flat
assert f_iter.next() == 10
@@ -2003,9 +1971,6 @@
a = arange(10).reshape(5, 2)
raises(IndexError, 'a.flat[(1, 2)]')
assert a.flat.base is a
- m = zeros((2,2), dtype='S3')
- m.flat[1] = 1
- assert m[0,1] == '1'
def test_flatiter_array_conv(self):
from numpypy import array, dot
diff --git a/pypy/module/micronumpy/types.py b/pypy/module/micronumpy/types.py
--- a/pypy/module/micronumpy/types.py
+++ b/pypy/module/micronumpy/types.py
@@ -1635,7 +1635,6 @@
def get_size(self):
return self.size
-
class StringType(BaseType, BaseStringType):
T = lltype.Char
@@ -1643,7 +1642,7 @@
def coerce(self, space, dtype, w_item):
from pypy.module.micronumpy.interp_dtype import new_string_dtype
arg = space.str_w(space.str(w_item))
- arr = VoidBoxStorage(len(arg), new_string_dtype(space, len(arg)))
+ arr = interp_boxes.VoidBoxStorage(len(arg), new_string_dtype(space, len(arg)))
for i in range(len(arg)):
arr.storage[i] = arg[i]
return interp_boxes.W_StringBox(arr, 0, arr.dtype)
@@ -1684,20 +1683,6 @@
def to_builtin_type(self, space, box):
return space.wrap(self.to_str(box))
- def build_and_convert(self, space, mydtype, box):
- if box.get_dtype(space).is_str_or_unicode():
- arg = box.get_dtype(space).itemtype.to_str(box)
- else:
- w_arg = box.descr_str(space)
- arg = space.str_w(space.str(w_arg))
- arr = VoidBoxStorage(self.size, mydtype)
- i = 0
- for i in range(min(len(arg), self.size)):
- arr.storage[i] = arg[i]
- for j in range(i + 1, self.size):
- arr.storage[j] = '\x00'
- return interp_boxes.W_StringBox(arr, 0, arr.dtype)
-
class VoidType(BaseType, BaseStringType):
T = lltype.Char
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