Hello Nicola, I am not aware of a magical "one function" numpy solution (is there one numpy gurus?).
I don't know if it's optimal, but here's how I usually do similar things. I wrote a simple function that assigns points (any number of dimensions) to a regular multi-dimensional grid. It is here: https://gist.github.com/1509853 It is short, commented and should be straightforward to use. Once you have the assignments, you can: - get the non-empty cell indexes with `np.unique(assignments)` - retrieve the points assigned to a cell with `points[assignments == cell_index]` - iterate over assignments to select the points you want for each cell. Hope this helps, Adrien PS: This is one of the first times I post an answer on this list, so if I did anything wrong, let me know. Numpy is such a wonderful thing and you guys do such an amazing work, that I though it is time to give back at least epsilon of what I got from you :-) 2011/12/22 Nicola Creati <ncre...@inogs.it> > Hello, > > I have a cloud on sparse points that can be described by a Nx3 array (N > is the number of points). Each point is defined by an x, y and z > coordinate: > > x0 y0 z0 > x1 y1 z1 > . . . > . . . > . . . > xn yn zn > > > I need to bin the cloud to a regular 2D array according to a desired bin > size assigning to each cell (bin) the minimum z of all points that fall > in that cell(bin). Moreover I need indexes of points that fall in each > cell(bin). > > Is there any way to accomplish this task in numpy? > > Thanks. > > Nicola Creati > > > > > -- > Nicola Creati > Istituto Nazionale di Oceanografia e di Geofisica Sperimentale - OGS > www.inogs.it Dipartimento di Geofisica della Litosfera Geophysics of > Lithosphere Department CARS (Cartography and Remote Sensing) Research Group > http://www.inogs.it/Cars/ Borgo Grotta Gigante 42/c 34010 Sgonico - > Trieste - ITALY ncre...@ogs.trieste.it > off. +39 040 2140 213 > fax. +39 040 327307 > > _____________________________________________________________________ > This communication, that may contain confidential and/or legally > privileged information, is intended solely for the use of the intended > addressees. Opinions, conclusions and other information contained in this > message, that do not relate to the official business of OGS, shall be > considered as not given or endorsed by it. Every opinion or advice > contained in this communication is subject to the terms and conditions > provided by the agreement governing the engagement with such a client. Any > use, disclosure, copying or distribution of the contents of this > communication by a not-intended recipient or in violation of the purposes > of this communication is strictly prohibited and may be unlawful. For Italy > only: Ai sensi del D.Lgs.196/2003 - "T.U. sulla Privacy" si precisa che le > informazioni contenute in questo messaggio sono riservate ed a uso > esclusivo del destinatario. > _____________________________________________________________________ > > _______________________________________________ > NumPy-Discussion mailing list > NumPy-Discussion@scipy.org > http://mail.scipy.org/mailman/listinfo/numpy-discussion >
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