reprojecting a Gaussian Grid to a regular grid

Hello, I have a set of data on a Gaussian grid. I have a latitude
array, a longitude array, and a data array:
In [121]: vlats.shape
Out[121]: (880, 1760)
In [122]: vlons.shape
Out[122]: (880, 1760)
In [123]: vtypes.shape
Out[123]: (880, 1760)

The longitude seems to go from -360 to 0.6, the latitude is more regular:
In [124]: vlons.min(); vlons.max()
Out[124]: -360.0
Out[124]: 0.59499999999880615

In [125]: vlats.min(); vlats.max()
Out[125]: -89.843513517868473
Out[125]: 89.843513517868473

I thought (and it was also suggested) I could use 'interp' from the
mpl_toolkits.basemap package, but I'm not sure how to do this. Does
anyone have experience with this? An alternative suggestion was to use
the scipy interp capabilities; again, I'm not certain I know how to go
about this.