1 files changed, 124 insertions, 0 deletions
diff --git a/numpy/oldnumeric/functions.py b/numpy/oldnumeric/functions.py
new file mode 100644
index 000000000..1f09d8f84
--- /dev/null
+++ b/numpy/oldnumeric/functions.py
@@ -0,0 +1,124 @@
+# Functions that should behave the same as Numeric and need changing
+
+import numpy as N
+import numpy.core.multiarray as mu
+import numpy.core.numeric as nn
+from typeconv import convtypecode, convtypecode2
+
+__all__ = ['take', 'repeat', 'sum', 'product', 'sometrue', 'alltrue',
+           'cumsum', 'cumproduct', 'compress', 'fromfunction',
+           'ones', 'empty', 'identity', 'zeros', 'array', 'asarray',
+           'nonzero', 'reshape', 'arange', 'fromstring', 'ravel', 'trace',
+           'indices', 'where','sarray','cross_product', 'argmax', 'argmin',
+           'average']
+
+def take(a, indicies, axis=0):
+    return N.take(a, indicies, axis)
+
+def repeat(a, repeats, axis=0):
+    return N.repeat(a, repeats, axis)
+
+def sum(x, axis=0):
+    return N.sum(x, axis)
+
+def product(x, axis=0):
+    return N.product(x, axis)
+
+def sometrue(x, axis=0):
+    return N.sometrue(x, axis)
+
+def alltrue(x, axis=0):
+    return N.alltrue(x, axis)
+
+def cumsum(x, axis=0):
+    return N.cumsum(x, axis)
+
+def cumproduct(x, axis=0):
+    return N.cumproduct(x, axis)
+
+def argmax(x, axis=-1):
+    return N.argmax(x, axis)
+
+def argmin(x, axis=-1):
+    return N.argmin(x, axis)
+
+def compress(condition, m, axis=-1):
+    return N.compress(condition, m, axis)
+
+def fromfunction(args, dimensions):
+    return N.fromfunction(args, dimensions, dtype=int)
+
+def ones(shape, typecode='l', savespace=0, dtype=None):
+    """ones(shape, dtype=int) returns an array of the given
+    dimensions which is initialized to all ones.
+    """
+    dtype = convtypecode(typecode,dtype)
+    a = mu.empty(shape, dtype)
+    a.fill(1)
+    return a
+
+def zeros(shape, typecode='l', savespace=0, dtype=None):
+    """zeros(shape, dtype=int) returns an array of the given
+    dimensions which is initialized to all zeros
+    """
+    dtype = convtypecode(typecode,dtype)
+    return mu.zeros(shape, dtype)
+
+def identity(n,typecode='l', dtype=None):
+    """identity(n) returns the identity 2-d array of shape n x n.
+    """
+    dtype = convtypecode(typecode, dtype)
+    return nn.identity(n, dtype)
+
+def empty(shape, typecode='l', dtype=None):
+    dtype = convtypecode(typecode, dtype)
+    return mu.empty(shape, dtype)
+
+def array(sequence, typecode=None, copy=1, savespace=0, dtype=None):
+    dtype = convtypecode2(typecode, dtype)
+    return mu.array(sequence, dtype, copy=copy)
+
+def sarray(a, typecode=None, copy=False, dtype=None):
+    dtype = convtypecode2(typecode, dtype)
+    return mu.array(a, dtype, copy)
+
+def asarray(a, typecode=None, dtype=None):
+    dtype = convtypecode2(typecode, dtype)
+    return mu.array(a, dtype, copy=0)
+
+def nonzero(a):
+    res = N.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)
+
+def arange(start, stop=None, step=1, typecode=None, dtype=None):
+    dtype = convtypecode2(typecode, dtype)
+    return mu.arange(start, stop, step, dtype)
+
+def fromstring(string, typecode='l', count=-1, dtype=None):
+    dtype = convtypecode(typecode, dtype)
+    return mu.fromstring(string, dtype, count=count)
+
+def ravel(m):
+    return N.ravel(m)
+
+def trace(a, offset=0, axis1=0, axis2=1):
+    return N.trace(a, offset=0, axis1=0, axis2=1)
+
+def indices(dimensions, typecode=None, dtype=None):
+    dtype = convtypecode(typecode, dtype)
+    return N.indices(dimensions, dtype)
+
+def where(condition, x, y):
+    return N.where(condition, x, y)
+
+def cross_product(a, b, axis1=-1, axis2=-1):
+    return N.cross(a, b, axis1, axis2)
+
+def average(a, axis=0, weights=None, returned=False):
+    return N.average(a, axis, weights, returned)