Author: Brian Kearns <bdkea...@gmail.com>
Branch: numpy-refactor
Changeset: r69495:9fa7ed888869
Date: 2014-02-27 01:01 -0500
http://bitbucket.org/pypy/pypy/changeset/9fa7ed888869/
Log: consolidate array creation funcs in ctors.py
diff --git a/pypy/module/cpyext/ndarrayobject.py
b/pypy/module/cpyext/ndarrayobject.py
--- a/pypy/module/cpyext/ndarrayobject.py
+++ b/pypy/module/cpyext/ndarrayobject.py
@@ -7,7 +7,8 @@
from rpython.rtyper.lltypesystem import rffi, lltype
from pypy.module.cpyext.api import cpython_api, Py_ssize_t, CANNOT_FAIL
from pypy.module.cpyext.api import PyObject
-from pypy.module.micronumpy.ndarray import W_NDimArray, array
+from pypy.module.micronumpy.ndarray import W_NDimArray
+from pypy.module.micronumpy.ctors import array
from pypy.module.micronumpy.descriptor import get_dtype_cache, W_Dtype
from pypy.module.micronumpy.concrete import ConcreteArray
from rpython.rlib.rawstorage import RAW_STORAGE_PTR
diff --git a/pypy/module/micronumpy/__init__.py
b/pypy/module/micronumpy/__init__.py
--- a/pypy/module/micronumpy/__init__.py
+++ b/pypy/module/micronumpy/__init__.py
@@ -7,14 +7,14 @@
'ndarray': 'ndarray.W_NDimArray',
'dtype': 'descriptor.W_Dtype',
- 'array': 'ndarray.array',
- 'zeros': 'ndarray.zeros',
- 'empty': 'ndarray.zeros',
- 'empty_like': 'ndarray.empty_like',
+ 'array': 'ctors.array',
+ 'zeros': 'ctors.zeros',
+ 'empty': 'ctors.zeros',
+ 'empty_like': 'ctors.empty_like',
'_reconstruct' : 'ndarray._reconstruct',
- 'scalar' : 'ndarray.build_scalar',
+ 'scalar' : 'ctors.build_scalar',
'dot': 'arrayops.dot',
- 'fromstring': 'interp_support.fromstring',
+ 'fromstring': 'ctors.fromstring',
'flatiter': 'flatiter.W_FlatIterator',
'concatenate': 'arrayops.concatenate',
'where': 'arrayops.where',
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
@@ -86,7 +86,7 @@
def convert_to_array(space, w_obj):
- from pypy.module.micronumpy.ndarray import array
+ from pypy.module.micronumpy.ctors import array
if isinstance(w_obj, W_NDimArray):
return w_obj
return array(space, w_obj)
diff --git a/pypy/module/micronumpy/boxes.py b/pypy/module/micronumpy/boxes.py
--- a/pypy/module/micronumpy/boxes.py
+++ b/pypy/module/micronumpy/boxes.py
@@ -40,7 +40,7 @@
return get_dtype_cache(space).dtypes_by_num[num]
def descr__new__(space, w_subtype, w_value=None):
- from pypy.module.micronumpy.ndarray import array
+ from pypy.module.micronumpy.ctors import array
dtype = _get_dtype(space)
if not space.is_none(w_value):
w_arr = array(space, w_value, dtype, copy=False)
diff --git a/pypy/module/micronumpy/compile.py
b/pypy/module/micronumpy/compile.py
--- a/pypy/module/micronumpy/compile.py
+++ b/pypy/module/micronumpy/compile.py
@@ -10,7 +10,7 @@
from pypy.module.micronumpy import boxes
from pypy.module.micronumpy.descriptor import get_dtype_cache
from pypy.module.micronumpy.base import W_NDimArray
-from pypy.module.micronumpy.ndarray import array
+from pypy.module.micronumpy.ctors import array
from pypy.module.micronumpy.arrayops import where
from pypy.module.micronumpy import ufuncs
from rpython.rlib.objectmodel import specialize, instantiate
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
@@ -84,3 +84,15 @@
"duplicate value in 'axis'"))
out[axis] = True
return out
+
+
+def shape_converter(space, w_size, dtype):
+ if space.is_none(w_size):
+ return []
+ if space.isinstance_w(w_size, space.w_int):
+ return [space.int_w(w_size)]
+ shape = []
+ for w_item in space.fixedview(w_size):
+ shape.append(space.int_w(w_item))
+ shape += dtype.shape
+ return shape[:]
diff --git a/pypy/module/micronumpy/interp_support.py
b/pypy/module/micronumpy/ctors.py
rename from pypy/module/micronumpy/interp_support.py
rename to pypy/module/micronumpy/ctors.py
--- a/pypy/module/micronumpy/interp_support.py
+++ b/pypy/module/micronumpy/ctors.py
@@ -3,9 +3,117 @@
from rpython.rtyper.lltypesystem import lltype, rffi
from pypy.module.micronumpy import descriptor, loop
from rpython.rlib.rstring import strip_spaces
-from pypy.module.micronumpy.base import W_NDimArray
+from pypy.module.micronumpy import ufuncs
+from pypy.module.micronumpy.base import W_NDimArray, convert_to_array
+from pypy.module.micronumpy.converters import shape_converter
+from pypy.module.micronumpy.strides import find_shape_and_elems
-FLOAT_SIZE = rffi.sizeof(lltype.Float)
+
+def build_scalar(space, w_dtype, w_state):
+ from rpython.rtyper.lltypesystem import rffi, lltype
+ if not isinstance(w_dtype, descriptor.W_Dtype):
+ raise oefmt(space.w_TypeError,
+ "argument 1 must be numpy.dtype, not %T", w_dtype)
+ if w_dtype.elsize == 0:
+ raise oefmt(space.w_ValueError, "itemsize cannot be zero")
+ if not space.isinstance_w(w_state, space.w_str):
+ raise oefmt(space.w_TypeError, "initializing object must be a string")
+ if space.len_w(w_state) != w_dtype.elsize:
+ raise oefmt(space.w_ValueError, "initialization string is too small")
+ state = rffi.str2charp(space.str_w(w_state))
+ box = w_dtype.itemtype.box_raw_data(state)
+ lltype.free(state, flavor="raw")
+ return box
+
+
+@unwrap_spec(ndmin=int, copy=bool, subok=bool)
+def array(space, w_object, w_dtype=None, copy=True, w_order=None, subok=False,
+ ndmin=0):
+ # for anything that isn't already an array, try __array__ method first
+ if not isinstance(w_object, W_NDimArray):
+ w___array__ = space.lookup(w_object, "__array__")
+ if w___array__ is not None:
+ if space.is_none(w_dtype):
+ w_dtype = space.w_None
+ w_array = space.get_and_call_function(w___array__, w_object,
w_dtype)
+ if isinstance(w_array, W_NDimArray):
+ # feed w_array back into array() for other properties
+ return array(space, w_array, w_dtype, False, w_order, subok,
ndmin)
+ else:
+ raise oefmt(space.w_ValueError,
+ "object __array__ method not producing an array")
+
+ 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 != 'C': # or order != 'F':
+ raise oefmt(space.w_ValueError, "Unknown order: %s", order)
+
+ # arrays with correct dtype
+ if isinstance(w_object, W_NDimArray) and \
+ (space.is_none(w_dtype) or w_object.get_dtype() is dtype):
+ shape = w_object.get_shape()
+ if copy:
+ w_ret = w_object.descr_copy(space)
+ else:
+ if ndmin <= len(shape):
+ return w_object
+ new_impl = w_object.implementation.set_shape(space, w_object,
shape)
+ w_ret = W_NDimArray(new_impl)
+ if ndmin > len(shape):
+ shape = [1] * (ndmin - len(shape)) + shape
+ w_ret.implementation = w_ret.implementation.set_shape(space,
+ w_ret, shape)
+ return w_ret
+
+ # not an array or incorrect dtype
+ shape, elems_w = find_shape_and_elems(space, w_object, dtype)
+ if dtype is None or (dtype.is_str_or_unicode() and dtype.elsize < 1):
+ for w_elem in elems_w:
+ if isinstance(w_elem, W_NDimArray) and w_elem.is_scalar():
+ w_elem = w_elem.get_scalar_value()
+ dtype = ufuncs.find_dtype_for_scalar(space, w_elem, dtype)
+ if dtype is None:
+ dtype = descriptor.get_dtype_cache(space).w_float64dtype
+ elif dtype.is_str_or_unicode() and dtype.elsize < 1:
+ # promote S0 -> S1, U0 -> U1
+ dtype = descriptor.variable_dtype(space, dtype.char + '1')
+
+ if ndmin > len(shape):
+ shape = [1] * (ndmin - len(shape)) + shape
+ w_arr = W_NDimArray.from_shape(space, shape, dtype, order=order)
+ arr_iter = w_arr.create_iter()
+ for w_elem in elems_w:
+ arr_iter.setitem(dtype.coerce(space, w_elem))
+ arr_iter.next()
+ return w_arr
+
+
+def zeros(space, w_shape, w_dtype=None, w_order=None):
+ dtype = space.interp_w(descriptor.W_Dtype,
+ 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')
+ shape = shape_converter(space, w_shape, dtype)
+ return W_NDimArray.from_shape(space, shape, dtype=dtype)
+
+
+@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)
+ if w_dtype is None:
+ dtype = w_a.get_dtype()
+ else:
+ dtype = space.interp_w(descriptor.W_Dtype,
+ 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')
+ return W_NDimArray.from_shape(space, w_a.get_shape(), dtype=dtype,
+ w_instance=w_a if subok else None)
+
def _fromstring_text(space, s, count, sep, length, dtype):
sep_stripped = strip_spaces(sep)
@@ -57,6 +165,7 @@
return space.wrap(a)
+
def _fromstring_bin(space, s, count, length, dtype):
itemsize = dtype.elsize
assert itemsize >= 0
@@ -74,11 +183,11 @@
loop.fromstring_loop(space, a, dtype, itemsize, s)
return space.wrap(a)
+
@unwrap_spec(s=str, count=int, sep=str, w_dtype=WrappedDefault(None))
def fromstring(space, s, w_dtype=None, count=-1, sep=''):
dtype = space.interp_w(descriptor.W_Dtype,
- space.call_function(space.gettypefor(descriptor.W_Dtype), w_dtype)
- )
+ space.call_function(space.gettypefor(descriptor.W_Dtype), w_dtype))
length = len(s)
if sep == '':
return _fromstring_bin(space, s, count, length, dtype)
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
@@ -7,9 +7,8 @@
from pypy.module.micronumpy.base import W_NDimArray, convert_to_array,\
ArrayArgumentException, wrap_impl
from pypy.module.micronumpy import descriptor, ufuncs, boxes, arrayops
-from pypy.module.micronumpy.strides import find_shape_and_elems,\
- get_shape_from_iterable, to_coords, shape_agreement, \
- shape_agreement_multiple
+from pypy.module.micronumpy.strides import get_shape_from_iterable, to_coords,
\
+ shape_agreement, shape_agreement_multiple
from pypy.module.micronumpy.flagsobj import W_FlagsObject
from pypy.module.micronumpy.flatiter import W_FlatIterator
from pypy.module.micronumpy.appbridge import get_appbridge_cache
@@ -19,20 +18,11 @@
from rpython.rlib import jit
from rpython.rlib.rstring import StringBuilder
from pypy.module.micronumpy.concrete import BaseConcreteArray
-from pypy.module.micronumpy.converters import order_converter,
multi_axis_converter
+from pypy.module.micronumpy.converters import order_converter,
shape_converter, \
+ multi_axis_converter
from pypy.module.micronumpy import support
from pypy.module.micronumpy import constants as NPY
-def _find_shape(space, w_size, dtype):
- if space.is_none(w_size):
- return []
- if space.isinstance_w(w_size, space.w_int):
- return [space.int_w(w_size)]
- shape = []
- for w_item in space.fixedview(w_size):
- shape.append(space.int_w(w_item))
- shape += dtype.shape
- return shape[:]
def _match_dot_shapes(space, left, right):
left_shape = left.get_shape()
@@ -1141,7 +1131,7 @@
from pypy.module.micronumpy.support import calc_strides
dtype = space.interp_w(descriptor.W_Dtype,
space.call_function(space.gettypefor(descriptor.W_Dtype), w_dtype))
- shape = _find_shape(space, w_shape, dtype)
+ shape = shape_converter(space, w_shape, dtype)
if not space.is_none(w_buffer):
if (not space.is_none(w_strides)):
@@ -1194,7 +1184,7 @@
dtype = space.interp_w(descriptor.W_Dtype,
space.call_function(space.gettypefor(descriptor.W_Dtype),
w_dtype))
- shape = _find_shape(space, w_shape, dtype)
+ shape = shape_converter(space, w_shape, dtype)
if w_subtype:
if not space.isinstance_w(w_subtype, space.w_type):
raise OperationError(space.w_ValueError, space.wrap(
@@ -1395,107 +1385,6 @@
__array__ = interp2app(W_NDimArray.descr___array__),
)
-@unwrap_spec(ndmin=int, copy=bool, subok=bool)
-def array(space, w_object, w_dtype=None, copy=True, w_order=None, subok=False,
- ndmin=0):
- # for anything that isn't already an array, try __array__ method first
- if not isinstance(w_object, W_NDimArray):
- w___array__ = space.lookup(w_object, "__array__")
- if w___array__ is not None:
- if space.is_none(w_dtype):
- w_dtype = space.w_None
- w_array = space.get_and_call_function(w___array__, w_object,
w_dtype)
- if isinstance(w_array, W_NDimArray):
- # feed w_array back into array() for other properties
- return array(space, w_array, w_dtype, False, w_order, subok,
ndmin)
- else:
- raise oefmt(space.w_ValueError,
- "object __array__ method not producing an array")
-
- 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 != 'C': # or order != 'F':
- raise oefmt(space.w_ValueError, "Unknown order: %s", order)
-
- # arrays with correct dtype
- if isinstance(w_object, W_NDimArray) and \
- (space.is_none(w_dtype) or w_object.get_dtype() is dtype):
- shape = w_object.get_shape()
- if copy:
- w_ret = w_object.descr_copy(space)
- else:
- if ndmin <= len(shape):
- return w_object
- new_impl = w_object.implementation.set_shape(space, w_object,
shape)
- w_ret = W_NDimArray(new_impl)
- if ndmin > len(shape):
- shape = [1] * (ndmin - len(shape)) + shape
- w_ret.implementation = w_ret.implementation.set_shape(space,
- w_ret, shape)
- return w_ret
-
- # not an array or incorrect dtype
- shape, elems_w = find_shape_and_elems(space, w_object, dtype)
- if dtype is None or (dtype.is_str_or_unicode() and dtype.elsize < 1):
- for w_elem in elems_w:
- if isinstance(w_elem, W_NDimArray) and w_elem.is_scalar():
- w_elem = w_elem.get_scalar_value()
- dtype = ufuncs.find_dtype_for_scalar(space, w_elem, dtype)
- if dtype is None:
- dtype = descriptor.get_dtype_cache(space).w_float64dtype
- elif dtype.is_str_or_unicode() and dtype.elsize < 1:
- # promote S0 -> S1, U0 -> U1
- dtype = descriptor.variable_dtype(space, dtype.char + '1')
-
- if ndmin > len(shape):
- shape = [1] * (ndmin - len(shape)) + shape
- w_arr = W_NDimArray.from_shape(space, shape, dtype, order=order)
- arr_iter = w_arr.create_iter()
- for w_elem in elems_w:
- arr_iter.setitem(dtype.coerce(space, w_elem))
- arr_iter.next()
- return w_arr
-
-def zeros(space, w_shape, w_dtype=None, w_order=None):
- dtype = space.interp_w(descriptor.W_Dtype,
- 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')
- shape = _find_shape(space, w_shape, dtype)
- return W_NDimArray.from_shape(space, shape, dtype=dtype)
-
-@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)
- if w_dtype is None:
- dtype = w_a.get_dtype()
- else:
- dtype = space.interp_w(descriptor.W_Dtype,
- 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')
- return W_NDimArray.from_shape(space, w_a.get_shape(), dtype=dtype,
- w_instance=w_a if subok else None)
-
-def build_scalar(space, w_dtype, w_state):
- from rpython.rtyper.lltypesystem import rffi, lltype
- if not isinstance(w_dtype, descriptor.W_Dtype):
- raise oefmt(space.w_TypeError,
- "argument 1 must be numpy.dtype, not %T", w_dtype)
- if w_dtype.elsize == 0:
- raise oefmt(space.w_ValueError, "itemsize cannot be zero")
- if not space.isinstance_w(w_state, space.w_str):
- raise oefmt(space.w_TypeError, "initializing object must be a string")
- if space.len_w(w_state) != w_dtype.elsize:
- raise oefmt(space.w_ValueError, "initialization string is too small")
- state = rffi.str2charp(space.str_w(w_state))
- box = w_dtype.itemtype.box_raw_data(state)
- lltype.free(state, flavor="raw")
- return box
def _reconstruct(space, w_subtype, w_shape, w_dtype):
return descr_new_array(space, w_subtype, w_shape, w_dtype)
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