Author: Brian Kearns <[email protected]>
Branch:
Changeset: r68462:1d2fb89d5c6f
Date: 2013-12-18 01:54 -0500
http://bitbucket.org/pypy/pypy/changeset/1d2fb89d5c6f/
Log: cleanup
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
@@ -1405,38 +1405,34 @@
# arrays with correct dtype
dtype = interp_dtype.decode_w_dtype(space, w_dtype)
if isinstance(w_object, W_NDimArray) and \
- (space.is_none(w_dtype) or w_object.get_dtype() is dtype):
+ (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):
+ 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)
+ 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.get_size() < 1):
+ if dtype is None or (dtype.is_str_or_unicode() and dtype.get_size() < 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 = interp_ufuncs.find_dtype_for_scalar(space, w_elem,
- dtype)
- #if dtype is interp_dtype.get_dtype_cache(space).w_float64dtype:
- # break
-
+ dtype = interp_ufuncs.find_dtype_for_scalar(space, w_elem, dtype)
if dtype is None:
dtype = interp_dtype.get_dtype_cache(space).w_float64dtype
- if dtype.is_str_or_unicode() and dtype.get_size() < 1:
- # promote S0 -> S1, U0 -> U1
- dtype = interp_dtype.variable_dtype(space, dtype.char + '1')
+ elif dtype.is_str_or_unicode() and dtype.get_size() < 1:
+ # promote S0 -> S1, U0 -> U1
+ dtype = interp_dtype.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)
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