diff options
Diffstat (limited to 'numpy/oldnumeric/functions.py')
| -rw-r--r-- | numpy/oldnumeric/functions.py | 42 |
1 files changed, 21 insertions, 21 deletions
diff --git a/numpy/oldnumeric/functions.py b/numpy/oldnumeric/functions.py index 1f09d8f84..5b2b1a8bf 100644 --- a/numpy/oldnumeric/functions.py +++ b/numpy/oldnumeric/functions.py @@ -1,6 +1,6 @@ # Functions that should behave the same as Numeric and need changing -import numpy as N +import numpy as np import numpy.core.multiarray as mu import numpy.core.numeric as nn from typeconv import convtypecode, convtypecode2 @@ -13,40 +13,40 @@ __all__ = ['take', 'repeat', 'sum', 'product', 'sometrue', 'alltrue', 'average'] def take(a, indicies, axis=0): - return N.take(a, indicies, axis) + return np.take(a, indicies, axis) def repeat(a, repeats, axis=0): - return N.repeat(a, repeats, axis) + return np.repeat(a, repeats, axis) def sum(x, axis=0): - return N.sum(x, axis) + return np.sum(x, axis) def product(x, axis=0): - return N.product(x, axis) + return np.product(x, axis) def sometrue(x, axis=0): - return N.sometrue(x, axis) + return np.sometrue(x, axis) def alltrue(x, axis=0): - return N.alltrue(x, axis) + return np.alltrue(x, axis) def cumsum(x, axis=0): - return N.cumsum(x, axis) + return np.cumsum(x, axis) def cumproduct(x, axis=0): - return N.cumproduct(x, axis) + return np.cumproduct(x, axis) def argmax(x, axis=-1): - return N.argmax(x, axis) + return np.argmax(x, axis) def argmin(x, axis=-1): - return N.argmin(x, axis) + return np.argmin(x, axis) def compress(condition, m, axis=-1): - return N.compress(condition, m, axis) + return np.compress(condition, m, axis) def fromfunction(args, dimensions): - return N.fromfunction(args, dimensions, dtype=int) + return np.fromfunction(args, dimensions, dtype=int) def ones(shape, typecode='l', savespace=0, dtype=None): """ones(shape, dtype=int) returns an array of the given @@ -87,14 +87,14 @@ def asarray(a, typecode=None, dtype=None): return mu.array(a, dtype, copy=0) def nonzero(a): - res = N.nonzero(a) + res = np.nonzero(a) if len(res) == 1: return res[0] else: raise ValueError, "Input argument must be 1d" def reshape(a, shape): - return N.reshape(a, shape) + return np.reshape(a, shape) def arange(start, stop=None, step=1, typecode=None, dtype=None): dtype = convtypecode2(typecode, dtype) @@ -105,20 +105,20 @@ def fromstring(string, typecode='l', count=-1, dtype=None): return mu.fromstring(string, dtype, count=count) def ravel(m): - return N.ravel(m) + return np.ravel(m) def trace(a, offset=0, axis1=0, axis2=1): - return N.trace(a, offset=0, axis1=0, axis2=1) + return np.trace(a, offset=0, axis1=0, axis2=1) def indices(dimensions, typecode=None, dtype=None): dtype = convtypecode(typecode, dtype) - return N.indices(dimensions, dtype) + return np.indices(dimensions, dtype) def where(condition, x, y): - return N.where(condition, x, y) + return np.where(condition, x, y) def cross_product(a, b, axis1=-1, axis2=-1): - return N.cross(a, b, axis1, axis2) + return np.cross(a, b, axis1, axis2) def average(a, axis=0, weights=None, returned=False): - return N.average(a, axis, weights, returned) + return np.average(a, axis, weights, returned) |