# [Numpy-discussion] A correction to numpy trapz function

Ryan May rmay31@gmail....
Sat Jul 12 10:31:11 CDT 2008

```Nadav Horesh wrote:
> The function trapz accepts x axis vector only for axis=-1. Here is my modification (correction?) to let it accept a vector x for integration along any axis:
>
> def trapz(y, x=None, dx=1.0, axis=-1):
>     """
>     Integrate y(x) using samples along the given axis and the composite
>     trapezoidal rule.  If x is None, spacing given by dx is assumed. If x
>     is an array, it must have either the dimensions of y, or a vector of
>     length matching the dimension of y along the integration axis.
>     """
>     y = asarray(y)
>     nd = y.ndim
>     slice1 = [slice(None)]*nd
>     slice2 = [slice(None)]*nd
>     slice1[axis] = slice(1,None)
>     slice2[axis] = slice(None,-1)
>     if x is None:
>         d = dx
>     else:
>         x = asarray(x)
>         if x.ndim == 1:
>             if len(x) != y.shape[axis]:
>                 raise ValueError('x length (%d) does not match y axis %d length (%d)' % (len(x), axis, y.shape[axis]))
>             d = diff(x)
>             return tensordot(d, (y[slice1]+y[slice2])/2.0,(0, axis))
>         d = diff(x, axis=axis)
>     return add.reduce(d * (y[slice1]+y[slice2])/2.0,axis)
>

What version were you working with originally? With 1.1, this is what I
have:

def trapz(y, x=None, dx=1.0, axis=-1):
"""Integrate y(x) using samples along the given axis and the composite
trapezoidal rule.  If x is None, spacing given by dx is assumed.
"""
y = asarray(y)
if x is None:
d = dx
else:
d = diff(x,axis=axis)
nd = len(y.shape)
slice1 = [slice(None)]*nd
slice2 = [slice(None)]*nd
slice1[axis] = slice(1,None)
slice2[axis] = slice(None,-1)
return add.reduce(d * (y[slice1]+y[slice2])/2.0,axis)

For me, this works fine with supplying x for axis != -1.

Ryan

--
Ryan May