On Thu, Sep 1, 2016 at 3:49 PM, Florian Lindner <mailinglists@xgm.de> wrote:
>
> Hello,
>
> thanks for your reply which was really helpful!
>
> My problem is that I discovered that the data I got is rather unordered.
>
> The documentation for reshape says: Read the elements of a using this index order, and place the elements into the
> reshaped array using this index order. ‘C’ means to read / write the elements using C-like index order, with the last
> axis index changing fastest, back to the first axis index changing slowest. ‘F’ means to read / write the elements using
> Fortran-like index order, with the first index changing fastest, and the last index changing slowest.
>
> With my data both dimensions change, so there is no specific ordering of the points, just a bunch of arbitrarily mixed
> "x y z value" data.
>
> My idea is:
>
> out = np.loadtxt(...)
> x = np.unique(out[:,0])
> y = np.unique[out]:,1])
> xx, yy = np.meshgrid(x, y)
>
> values = lookup(xx, yy, out)
>
> lookup is ufunc (I hope that term is correct here) that looks up the value of every x and y in out, like
> x_filtered = out[ out[:,0] == x, :]
> y_filtered  = out[ out[:,1] == y, :]
> return y_filtered[2]
>
> (untested, just a sketch)
>
> Would this work? Any better way?

If the (x, y) values are actually drawn from a rectilinear grid, then you can use np.lexsort() to sort the rows before reshaping.