[Matplotlib-users] Script two planes
Glenn Nelson
kitecamguy at gmail.com
Fri May 11 10:54:11 EDT 2018
It's been a long time since I had to do surface fitting to data (let alone
display of such), so I did a quick search and found an answer for you that
not only finds best-fit plane, but also displays the input points with a
wireframe to represent the plane, and all of that in a rotating 3D display.
The solution uses matplotlib.pytplot.plot_wireframe() and Axes3D (it
imports it, but I don't see it get used).
Here's the answer, from stackexchange, of course:
https://math.stackexchange.com/questions/99299/best-fitting-plane-given-a-set-of-points
----
Glenn Nelson in Santa Cruz
social: http://google.com/+GlennNelson
see my Kite Aerial Photos at http://www.glenn-nelson.us/kap
On Tue, May 8, 2018 at 2:16 PM alberto <voodoo.bender at gmail.com> wrote:
> Hi Paul,
> I would visualize the atoms of two planes to see how much they are tilted.
> I'm a beginner of python, but I think that matplotlib is necessary.
>
> Alberto
>
> Il mar 8 mag 2018 09:18 PM Paul Hobson <pmhobson at gmail.com> ha scritto:
>
>> Alberto,
>>
>> It should be possible to do that with python, but I don't see a path
>> forward where matplotlib is required. Linear algebra and interpolation
>> available in numpy and scipy should suffice.
>> -Paul
>>
>> On Tue, May 8, 2018 at 12:13 PM, alberto <voodoo.bender at gmail.com> wrote:
>>
>>> Hi
>>> I have a set of cartesian coordinates that define two plane of different
>>> atoms.
>>> Is it possible calculate distance and orthogonal projection?
>>> regards
>>>
>>> Alberto
>>>
>>> This is my data
>>>
>>> 24
>>> test plane
>>>
>>> Pb -9.9300426676 4.1025666804 8.7420388123
>>> Pb -4.0641923655 4.0198687706 1.6849745870
>>> Pb -9.9866302880 4.1933336180 -1.3285956262
>>> Pb -4.1207799859 4.1106357083 -8.3856598515
>>> Pb -1.2684114297 4.1285931245 6.3124736259
>>> Pb 4.5974388723 4.0458952147 -0.7445905994
>>> Pb -1.3249990502 4.2193600622 -3.7581608126
>>> Pb 4.5408512519 4.1366621524 -10.8152250379
>>> Pb 7.3932198081 4.1546195686 3.8829084395
>>> Pb 13.2590701101 4.0719216589 -3.1741557858
>>> Pb 7.3366321877 4.2453865063 -6.1877259990
>>> Pb 13.2024824897 4.1626885965 -13.2447902243
>>> Mg -11.5004149207 -4.2961447648 13.2944782095
>>> Mg -5.6345646187 -4.3788426745 6.2374139842
>>> Mg -11.5570025411 -4.2053778271 3.2238437711
>>> Mg -5.6911522391 -4.2880757369 -3.8332204543
>>> Mg -2.8387836829 -4.2701183206 10.8649130231
>>> Mg 3.0270666192 -4.3528162304 3.8078487978
>>> Mg -2.8953713033 -4.1793513830 0.7942785847
>>> Mg 2.9704789987 -4.2620492927 -6.2627856407
>>> Mg 5.8228475550 -4.2440918765 8.4353478367
>>> Mg 11.6886978570 -4.3267897862 1.3782836114
>>> Mg 5.7662599345 -4.1533249388 -1.6352866017
>>> Mg 11.6321102366 -4.2360228486 -8.6923508271
>>>
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