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Brian Kearns  committed 5369e4d

update app-level code for _numpypy submodules

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  • Parent commits b8c9382
  • Branches cleanup-numpypy-namespace

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Files changed (10)

File lib_pypy/numpypy/core/__init__.py

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-import _numpypy
-from _numpypy import *
 import numeric
 from numeric import *
 import fromnumeric
 from shape_base import *
 from fromnumeric import amax as max, amin as min
-from _numpypy import absolute as abs
+from numeric import absolute as abs
 __all__ = []
-__all__ += _numpypy.__all__
 __all__ += numeric.__all__
 __all__ += fromnumeric.__all__
 __all__ += shape_base.__all__

File lib_pypy/numpypy/core/_methods.py

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 # Array methods which are called by the both the C-code for the method
 # and the Python code for the NumPy-namespace function
-#from numpy.core import multiarray as mu
-#from numpy.core import umath as um
-import _numpypy as mu
-um = mu
-from numpy.core.numeric import asanyarray
+import multiarray as mu
+import umath as um
+from numeric import asanyarray
 def _amax(a, axis=None, out=None, keepdims=False):
     return um.maximum.reduce(a, axis=axis,

File lib_pypy/numpypy/core/arrayprint.py

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 # and by Travis Oliphant  2005-8-22 for numpy
 import sys
-import _numpypy as _nt
-from _numpypy import maximum, minimum, absolute, not_equal, isnan, isinf
-#from _numpypy import format_longfloat, datetime_as_string, datetime_data
+import numerictypes as _nt
+from umath import maximum, minimum, absolute, not_equal, isnan, isinf
+#from multiarray import format_longfloat, datetime_as_string, datetime_data
 from fromnumeric import ravel

File lib_pypy/numpypy/core/multiarray.py

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-from _numpypy import set_string_function, typeinfo
+from _numpypy.multiarray import *

File lib_pypy/numpypy/core/numeric.py

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 __all__ = [
-           'ufunc',
-           'asanyarray', 'base_repr',
+           'newaxis', 'ufunc',
+           'asarray', 'asanyarray', 'base_repr',
            'array_repr', 'array_str', 'set_string_function',
-           'array_equal', 'asarray', 'outer', 'identity', 'little_endian',
+           'array_equal', 'outer', 'identity', 'little_endian',
            'Inf', 'inf', 'infty', 'Infinity', 'nan', 'NaN', 'False_', 'True_',
-from _numpypy import array, ndarray, int_, float_, bool_, flexible #, complex_# , longlong
-from _numpypy import concatenate, sin
-from .fromnumeric import any
 import sys
 import multiarray
+from multiarray import *
+del set_string_function
+del typeinfo
 import umath
 from umath import *
-from numpypy.core.arrayprint import array2string
-ufunc = type(sin)
+import numerictypes
+from numerictypes import *
 def extend_all(module):
     adict = {}
         if a not in adict:
 newaxis = None
+ufunc = type(sin)
 # XXX this file to be reviewed
 def seterr(**args):
     return ''.join(reversed(res or '0'))
+#Use numarray's printing function
+from arrayprint import array2string
 _typelessdata = [int_, float_]#, complex_]
 # XXX
 #if issubclass(intc, int):
         return multiarray.set_string_function(f, repr)
+set_string_function(array_str, 0)
+set_string_function(array_repr, 1)
+little_endian = (sys.byteorder == 'little')
 def array_equal(a1, a2):
     True if two arrays have the same shape and elements, False otherwise.
     return array(a, dtype, copy=False, order=order)
-set_string_function(array_str, 0)
-set_string_function(array_repr, 1)
-little_endian = (sys.byteorder == 'little')
-Inf = inf = infty = Infinity = PINF
-nan = NaN = NAN
-False_ = bool_(False)
-True_ = bool_(True)
 def outer(a,b):
     Compute the outer product of two vectors.
     from numpy import eye
     return eye(n, dtype=dtype)
+Inf = inf = infty = Infinity = PINF
+nan = NaN = NAN
+False_ = bool_(False)
+True_ = bool_(True)
+import fromnumeric
+from fromnumeric import *

File lib_pypy/numpypy/core/shape_base.py

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 __all__ = ['atleast_1d', 'atleast_2d', 'atleast_3d', 'vstack', 'hstack']
-import _numpypy
+import numeric as _nx
 from numeric import array, asanyarray, newaxis
 def atleast_1d(*arys):
-    return _numpypy.concatenate(map(atleast_2d,tup),0)
+    return _nx.concatenate(map(atleast_2d,tup),0)
 def hstack(tup):
     arrs = map(atleast_1d,tup)
     # As a special case, dimension 0 of 1-dimensional arrays is "horizontal"
     if arrs[0].ndim == 1:
-        return _numpypy.concatenate(arrs, 0)
+        return _nx.concatenate(arrs, 0)
-        return _numpypy.concatenate(arrs, 1)
+        return _nx.concatenate(arrs, 1)

File lib_pypy/numpypy/core/umath.py

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+from _numpypy.umath import *
 import math
 e = math.e
 pi = math.pi

File lib_pypy/numpypy/lib/function_base.py

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 __all__ = ['average']
-from _numpypy import array
+from ..core.numeric import array
 def average(a):
     # This implements a weighted average, for now we don't implement the

File lib_pypy/numpypy/lib/shape_base.py

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 __all__ = ['dstack']
-import numpypy.core.numeric as _nx
-from numpypy.core import atleast_3d
+from ..core import numeric as _nx
+from ..core import atleast_3d
 def dstack(tup):

File lib_pypy/numpypy/lib/twodim_base.py

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 __all__ = ['eye']
-from _numpypy import zeros
+from ..core.numeric import zeros
 def eye(N, M=None, k=0, dtype=float):