Author: Brian Kearns <bdkea...@gmail.com>
Branch:
Changeset: r69522:3c6f3f1e357c
Date: 2014-02-27 07:55 -0500
http://bitbucket.org/pypy/pypy/changeset/3c6f3f1e357c/
Log: cleanup
diff --git a/pypy/module/micronumpy/sort.py b/pypy/module/micronumpy/sort.py
--- a/pypy/module/micronumpy/sort.py
+++ b/pypy/module/micronumpy/sort.py
@@ -1,6 +1,3 @@
-""" This is the implementation of various sorting routines in numpy. It's here
-because it only makes sense on a concrete array
-"""
from pypy.interpreter.error import OperationError, oefmt
from rpython.rlib.listsort import make_timsort_class
from rpython.rlib.objectmodel import specialize
@@ -15,6 +12,11 @@
INT_SIZE = rffi.sizeof(lltype.Signed)
+all_types = (types.all_float_types + types.all_complex_types +
+ types.all_int_types)
+all_types = [i for i in all_types if not issubclass(i[0], types.Float16)]
+all_types = unrolling_iterable(all_types)
+
def make_argsort_function(space, itemtype, comp_type, count=1):
TP = itemtype.T
@@ -317,11 +319,6 @@
"sorting of non-numeric types '%s' is not implemented",
arr.dtype.get_name())
-all_types = (types.all_float_types + types.all_complex_types +
- types.all_int_types)
-all_types = [i for i in all_types if not issubclass(i[0], types.Float16)]
-all_types = unrolling_iterable(all_types)
-
class ArgSortCache(object):
built = False
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
@@ -210,7 +210,7 @@
if out:
dtype = out.get_dtype()
temp = W_NDimArray.from_shape(space, temp_shape, dtype,
- w_instance=obj)
+ w_instance=obj)
elif keepdims:
shape = obj_shape[:axis] + [1] + obj_shape[axis + 1:]
else:
@@ -236,25 +236,28 @@
)
dtype = out.get_dtype()
else:
- out = W_NDimArray.from_shape(space, shape, dtype,
w_instance=obj)
+ out = W_NDimArray.from_shape(space, shape, dtype,
+ w_instance=obj)
if obj.get_size() == 0:
if self.identity is not None:
out.fill(space, self.identity.convert_to(space, dtype))
return out
- return loop.do_axis_reduce(space, shape, self.func, obj, dtype,
axis, out,
- self.identity, cumulative, temp)
+ return loop.do_axis_reduce(space, shape, self.func, obj, dtype,
+ axis, out, self.identity, cumulative,
+ temp)
if cumulative:
if out:
if out.get_shape() != [obj.get_size()]:
raise OperationError(space.w_ValueError, space.wrap(
"out of incompatible size"))
else:
- out = W_NDimArray.from_shape(space, [obj.get_size()], dtype,
w_instance=obj)
+ out = W_NDimArray.from_shape(space, [obj.get_size()], dtype,
+ w_instance=obj)
loop.compute_reduce_cumulative(space, obj, out, dtype, self.func,
- self.identity)
+ self.identity)
return out
if out:
- if len(out.get_shape())>0:
+ if len(out.get_shape()) > 0:
raise oefmt(space.w_ValueError,
"output parameter for reduction operation %s has "
"too many dimensions", self.name)
@@ -266,7 +269,8 @@
return out
if keepdims:
shape = [1] * len(obj_shape)
- out = W_NDimArray.from_shape(space, [1] * len(obj_shape), dtype,
w_instance=obj)
+ out = W_NDimArray.from_shape(space, [1] * len(obj_shape), dtype,
+ w_instance=obj)
out.implementation.setitem(0, res)
return out
return res
@@ -278,6 +282,7 @@
raise OperationError(space.w_ValueError, space.wrap(
"outer product only supported for binary functions"))
+
class W_Ufunc1(W_Ufunc):
_immutable_fields_ = ["func", "bool_result"]
argcount = 1
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