MAINT: Clean up core/_methods.py and core/fromnumeric.py

Use issubclass instead of issubdtype.
Add some blank lines.
Remove trailing whitespace.
Remove uneeded float casts since true_divide is default.
Clean up documentation a bit.

2 files changed, 15 insertions, 17 deletions

diff --git a/numpy/core/_methods.py b/numpy/core/_methods.py
index 51731b9c2..6312d35cf 100644
--- a/numpy/core/_methods.py
+++ b/numpy/core/_methods.py
@@ -7,7 +7,7 @@ from __future__ import division, absolute_import, print_function
 
 from numpy.core import multiarray as mu
 from numpy.core import umath as um
-from numpy.core.numeric import asanyarray, isnan, issubdtype
+from numpy.core.numeric import asanyarray
 from numpy.core import numerictypes as nt
 
 def _amax(a, axis=None, out=None, keepdims=False):
@@ -48,19 +48,20 @@ def _mean(a, axis=None, dtype=None, out=None, keepdims=False):
     arr = asanyarray(a)
 
     # Cast bool, unsigned int, and int to float64
-    if dtype is None and (issubdtype(arr.dtype, nt.integer) or
-                          issubdtype(arr.dtype, nt.bool_)):
+    if dtype is None and issubclass(arr.dtype.type, (nt.integer, nt.bool_)):
         ret = um.add.reduce(arr, axis=axis, dtype='f8',
                             out=out, keepdims=keepdims)
     else:
         ret = um.add.reduce(arr, axis=axis, dtype=dtype,
                             out=out, keepdims=keepdims)
+
     rcount = _count_reduce_items(arr, axis)
     if isinstance(ret, mu.ndarray):
         ret = um.true_divide(ret, rcount,
                         out=ret, casting='unsafe', subok=False)
     else:
-        ret = ret / float(rcount)
+        ret = ret / rcount
+
     return ret
 
 def _var(a, axis=None, dtype=None, out=None, ddof=0,
@@ -68,23 +69,23 @@ def _var(a, axis=None, dtype=None, out=None, ddof=0,
     arr = asanyarray(a)
 
     # First compute the mean, saving 'rcount' for reuse later
-    if dtype is None and (issubdtype(arr.dtype, nt.integer) or
-                          issubdtype(arr.dtype, nt.bool_)):
+    if dtype is None and issubclass(arr.dtype.type, (nt.integer, nt.bool_)):
         arrmean = um.add.reduce(arr, axis=axis, dtype='f8', keepdims=True)
     else:
         arrmean = um.add.reduce(arr, axis=axis, dtype=dtype, keepdims=True)
+
     rcount = _count_reduce_items(arr, axis)
     if isinstance(arrmean, mu.ndarray):
         arrmean = um.true_divide(arrmean, rcount,
                             out=arrmean, casting='unsafe', subok=False)
     else:
-        arrmean = arrmean / float(rcount)
+        arrmean = arrmean / rcount
 
     # arr - arrmean
     x = arr - arrmean
 
     # (arr - arrmean) ** 2
-    if issubdtype(arr.dtype, nt.complex_):
+    if issubclass(arr.dtype.type, nt.complexfloating):
         x = um.multiply(x, um.conjugate(x), out=x).real
     else:
         x = um.multiply(x, x, out=x)
@@ -100,7 +101,7 @@ def _var(a, axis=None, dtype=None, out=None, ddof=0,
         ret = um.true_divide(ret, rcount,
                         out=ret, casting='unsafe', subok=False)
     else:
-        ret = ret / float(rcount)
+        ret = ret / rcount
 
     return ret
 
diff --git a/numpy/core/fromnumeric.py b/numpy/core/fromnumeric.py
index 35d36d960..e325c5fd1 100644
--- a/numpy/core/fromnumeric.py
+++ b/numpy/core/fromnumeric.py
@@ -62,9 +62,9 @@ def take(a, indices, axis=None, out=None, mode='raise'):
         The source array.
     indices : array_like
         The indices of the values to extract.
-        
+
         .. versionadded:: 1.8.0
-        
+
         Also allow scalars for indices.
     axis : int, optional
         The axis over which to select values. By default, the flattened
@@ -2664,8 +2664,7 @@ def mean(a, axis=None, dtype=None, out=None, keepdims=False):
     See Also
     --------
     average : Weighted average
-    nanmean : Arithmetic mean while ignoring NaNs
-    var, nanvar
+    std, var, nanmean, nanstd, nanvar
 
     Notes
     -----
@@ -2752,8 +2751,7 @@ def std(a, axis=None, dtype=None, out=None, ddof=0, keepdims=False):
 
     See Also
     --------
-    var, mean
-    nanmean, nanstd
+    var, mean, nanmean, nanstd, nanvar
     numpy.doc.ufuncs : Section "Output arguments"
 
     Notes
@@ -2856,8 +2854,7 @@ def var(a, axis=None, dtype=None, out=None, ddof=0,
 
     See Also
     --------
-    std : Standard deviation
-    mean : Average
+    std , mean, nanmean, nanstd, nanvar
     numpy.doc.ufuncs : Section "Output arguments"
 
     Notes