Author: Ronan Lamy <[email protected]>
Branch: fix-result-types
Changeset: r77672:1ef11fbdb532
Date: 2015-05-29 04:14 +0100
http://bitbucket.org/pypy/pypy/changeset/1ef11fbdb532/
Log: Move find_dtype_for_seq() to ctors.py
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
@@ -64,8 +64,8 @@
#print 'create view from
shape',shape,'dtype',dtype,'descr',w_descr,'data',data_w[0],'rw',rw
raise oefmt(space.w_NotImplementedError,
"creating array from __array_interface__ not supported yet")
- return
-
+ return
+
@unwrap_spec(ndmin=int, copy=bool, subok=bool)
def array(space, w_object, w_dtype=None, copy=True, w_order=None, subok=False,
@@ -114,9 +114,9 @@
elif not copy and (subok or type(w_object) is W_NDimArray):
return w_object
if subok and not type(w_object) is W_NDimArray:
- raise oefmt(space.w_NotImplementedError,
+ raise oefmt(space.w_NotImplementedError,
"array(..., subok=True) only partially implemented")
- # we have a ndarray, but need to copy or change dtype
+ # we have a ndarray, but need to copy or change dtype
if dtype is None:
dtype = w_object.get_dtype()
if dtype != w_object.get_dtype():
@@ -126,7 +126,7 @@
shape = w_object.get_shape()
w_arr = W_NDimArray.from_shape(space, shape, dtype, order=order)
if support.product(shape) == 1:
- w_arr.set_scalar_value(dtype.coerce(space,
+ w_arr.set_scalar_value(dtype.coerce(space,
w_object.implementation.getitem(0)))
else:
loop.setslice(space, shape, w_arr.implementation,
w_object.implementation)
@@ -137,13 +137,13 @@
with imp as storage:
sz = support.product(w_object.get_shape()) * dtype.elsize
return W_NDimArray.from_shape_and_storage(space,
- w_object.get_shape(), storage, dtype, storage_bytes=sz,
+ w_object.get_shape(), storage, dtype, storage_bytes=sz,
w_base=w_base, start=imp.start)
else:
# not an array
shape, elems_w = strides.find_shape_and_elems(space, w_object, dtype)
if dtype is None or (dtype.is_str_or_unicode() and dtype.elsize < 1):
- dtype = strides.find_dtype_for_seq(space, elems_w, dtype)
+ dtype = find_dtype_for_seq(space, elems_w, dtype)
if dtype is None:
dtype = descriptor.get_dtype_cache(space).w_float64dtype
elif dtype.is_str_or_unicode() and dtype.elsize < 1:
@@ -170,7 +170,7 @@
return w_array
shape, elems_w = strides.find_shape_and_elems(space, w_object, None)
- dtype = strides.find_dtype_for_seq(space, elems_w, None)
+ dtype = find_dtype_for_seq(space, elems_w, None)
if dtype is None:
dtype = descriptor.get_dtype_cache(space).w_float64dtype
elif dtype.is_str_or_unicode() and dtype.elsize < 1:
@@ -184,6 +184,21 @@
loop.assign(space, w_arr, elems_w)
return w_arr
+def _dtype_guess(space, dtype, w_elem):
+ from .casting import scalar2dtype, find_binop_result_dtype
+ if isinstance(w_elem, W_NDimArray) and w_elem.is_scalar():
+ w_elem = w_elem.get_scalar_value()
+ elem_dtype = scalar2dtype(space, w_elem)
+ return find_binop_result_dtype(space, elem_dtype, dtype)
+
+def find_dtype_for_seq(space, elems_w, dtype):
+ if len(elems_w) == 1:
+ w_elem = elems_w[0]
+ return _dtype_guess(space, dtype, w_elem)
+ for w_elem in elems_w:
+ dtype = _dtype_guess(space, dtype, w_elem)
+ return dtype
+
def _zeros_or_empty(space, w_shape, w_dtype, w_order, zero):
dtype = space.interp_w(descriptor.W_Dtype,
@@ -359,5 +374,5 @@
return a
else:
writable = not buf.readonly
- return W_NDimArray.from_shape_and_storage(space, [n], storage,
storage_bytes=s,
+ return W_NDimArray.from_shape_and_storage(space, [n], storage,
storage_bytes=s,
dtype=dtype, w_base=w_buffer,
writable=writable)
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
@@ -220,24 +220,6 @@
batch = new_batch
-def _dtype_guess(space, dtype, w_elem):
- from .casting import scalar2dtype, find_binop_result_dtype
- if isinstance(w_elem, W_NDimArray) and w_elem.is_scalar():
- w_elem = w_elem.get_scalar_value()
- elem_dtype = scalar2dtype(space, w_elem)
- return find_binop_result_dtype(space, elem_dtype, dtype)
-
-def find_dtype_for_seq(space, elems_w, dtype):
- if len(elems_w) == 1:
- w_elem = elems_w[0]
- return _dtype_guess(space, dtype, w_elem)
- return _find_dtype_for_seq(space, elems_w, dtype)
-
-def _find_dtype_for_seq(space, elems_w, dtype):
- for w_elem in elems_w:
- dtype = _dtype_guess(space, dtype, w_elem)
- return dtype
-
@jit.unroll_safe
def shape_agreement(space, shape1, w_arr2, broadcast_down=True):
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