I\'m looking for a clear comparison of meshgrid-like functions. Unfortunately I don\'t find it!
Numpy http://docs.scipy.org/doc/numpy/reference/ provides
numpy.meshgrid
is modelled after Matlab's meshgrid
command. It is used to vectorise functions of two variables, so that you can write
x = numpy.array([1, 2, 3])
y = numpy.array([10, 20, 30])
XX, YY = numpy.meshgrid(x, y)
ZZ = XX + YY
ZZ => array([[11, 12, 13],
[21, 22, 23],
[31, 32, 33]])
So ZZ
contains all the combinations of x
and y
put into the function. When you think about it, meshgrid
is a bit superfluous for numpy arrays, as they broadcast. This means you can do
XX, YY = numpy.atleast_2d(x, y)
YY = YY.T # transpose to allow broadcasting
ZZ = XX + YY
and get the same result.
mgrid
and ogrid
are helper classes which use index notation so that you can create XX
and YY
in the previous examples directly, without having to use something like linspace
. The order in which the output are generated is reversed.
YY, XX = numpy.mgrid[10:40:10, 1:4]
ZZ = XX + YY # These are equivalent to the output of meshgrid
YY, XX = numpy.ogrid[10:40:10, 1:4]
ZZ = XX + YY # These are equivalent to the atleast_2d example
I am not familiar with the scitools stuff, but ndgrid
seems equivalent to meshgrid
, while BoxGrid
is actually a whole class to help with this kind of generation.