a : array_like
Input data.
bins : int or sequence of scalars, optional
If bins is an int, it defines the number of equalwidth
bins in the given range (10, by default). If bins is a sequence,
it defines the bin edges, including the rightmost edge, allowing
for nonuniform bin widths.
range : (float, float), optional
The lower and upper range of the bins. If not provided, range
is simply (a.min(), a.max()). Values outside the range are
ignored. Note that with new set to False, values below
the range are ignored, while those above the range are tallied
in the rightmost bin.
normed : bool, optional
If False, the result will contain the number of samples
in each bin. If True, the result is the value of the
probability density function at the bin, normalized such that
the integral over the range is 1. Note that the sum of the
histogram values will often not be equal to 1; it is not a
probability mass function.
weights : array_like, optional
An array of weights, of the same shape as a. Each value in a
only contributes its associated weight towards the bin count
(instead of 1). If normed is True, the weights are normalized,
so that the integral of the density over the range remains 1.
The weights keyword is only available with new set to True.
new : {None, True, False}, optional
 Whether to use the new semantics for histogram:
 None : the new behaviour is used, no warning is printed.
 True : the new behaviour is used and a warning is raised about
the future removal of the new keyword.
 False : the old behaviour is used and a DeprecationWarning
is raised.
As of NumPy 1.3, this keyword should not be used explicitly since it
will disappear in NumPy 1.4.
