Rewrapped __all__ definition to conform to PEP8.

Standardize NumPy import as "import numpy as np".
Removed unused imports.
Fixed undefined reference to ndarray (should be np.ndarray).
Fixed undefined references to exp (should be math.exp).

1 files changed, 14 insertions, 13 deletions

diff --git a/numpy/oldnumeric/arrayfns.py b/numpy/oldnumeric/arrayfns.py
index 4c31a6827..dbb910770 100644
--- a/numpy/oldnumeric/arrayfns.py
+++ b/numpy/oldnumeric/arrayfns.py
@@ -1,10 +1,11 @@
 """Backward compatible with arrayfns from Numeric
 """
 
-__all__ = ['array_set', 'construct3', 'digitize', 'error', 'find_mask', 'histogram', 'index_sort',
-           'interp', 'nz', 'reverse', 'span', 'to_corners', 'zmin_zmax']
+__all__ = ['array_set', 'construct3', 'digitize', 'error', 'find_mask', 
+           'histogram', 'index_sort', 'interp', 'nz', 'reverse', 'span', 
+           'to_corners', 'zmin_zmax']
 
-import numpy as nx
+import numpy as np
 from numpy import asarray
 
 class error(Exception):
@@ -14,7 +15,7 @@ def array_set(vals1, indices, vals2):
     indices = asarray(indices)
     if indices.ndim != 1:
         raise ValueError, "index array must be 1-d"
-    if not isinstance(vals1, ndarray):
+    if not isinstance(vals1, np.ndarray):
         raise TypeError, "vals1 must be an ndarray"
     vals1 = asarray(vals1)
     vals2 = asarray(vals2)
@@ -31,7 +32,7 @@ def index_sort(arr):
 def interp(y, x, z, typ=None):
     """y(z) interpolated by treating y(x) as piecewise function
     """
-    res = numpy.interp(z, x, y)
+    res = np.interp(z, x, y)
     if typ is None or typ == 'd':
         return res
     if typ == 'f':
@@ -40,17 +41,17 @@ def interp(y, x, z, typ=None):
     raise error, "incompatible typecode"
 
 def nz(x):
-    x = asarray(x,dtype=nx.ubyte)
+    x = asarray(x,dtype=np.ubyte)
     if x.ndim != 1:
         raise TypeError, "intput must have 1 dimension."
-    indxs = nx.flatnonzero(x != 0)
+    indxs = np.flatnonzero(x != 0)
     return indxs[-1].item()+1
 
 def reverse(x, n):
     x = asarray(x,dtype='d')
     if x.ndim != 2:
         raise ValueError, "input must be 2-d"
-    y = nx.empty_like(x)
+    y = np.empty_like(x)
     if n == 0:
         y[...] = x[::-1,:]
     elif n == 1:
@@ -58,11 +59,11 @@ def reverse(x, n):
     return y
 
 def span(lo, hi, num, d2=0):
-    x = linspace(lo, hi, num)
+    x = np.linspace(lo, hi, num)
     if d2 <= 0:
         return x
     else:
-        ret = empty((d2,num),x.dtype)
+        ret = np.empty((d2,num),x.dtype)
         ret[...] = x
         return ret
 
@@ -71,15 +72,15 @@ def zmin_zmax(z, ireg):
     ireg = asarray(ireg, dtype=int)
     if z.shape != ireg.shape or z.ndim != 2:
         raise ValueError, "z and ireg must be the same shape and 2-d"
-    ix, iy = nx.nonzero(ireg)
+    ix, iy = np.nonzero(ireg)
     # Now, add more indices
     x1m = ix - 1
     y1m = iy-1
     i1 = x1m>=0
     i2 = y1m>=0
     i3 = i1 & i2
-    nix = nx.r_[ix, x1m[i1], x1m[i1], ix[i2] ]
-    niy = nx.r_[iy, iy[i1],  y1m[i3], y1m[i2]]
+    nix = np.r_[ix, x1m[i1], x1m[i1], ix[i2] ]
+    niy = np.r_[iy, iy[i1],  y1m[i3], y1m[i2]]
     # remove any negative indices
     zres = z[nix,niy]
     return zres.min().item(), zres.max().item()