2018-04-19 00:22:11 -0600 | commented answer | How does list_plot3d interpret nxn matrices? As a side note, the behavior of |
2018-04-19 00:22:00 -0600 | commented answer | How does list_plot3d interpret nxn matrices? That makes sense. And it also serves as a natural 3D extension to the output obtained from calling |
2018-04-18 23:50:30 -0600 | received badge | ● Scholar (source) |
2018-04-18 13:34:16 -0600 | asked a question | How does list_plot3d interpret nxn matrices? From the documentation of
Intuitively I would guess that the function would only accept $3 \times n$ matrices and/or their transposes, but the first example on the document page is a plot of a five by five matrix Question: How does One might suspect that |
2018-04-16 17:22:52 -0600 | received badge | ● Supporter (source) |
2018-04-16 10:49:14 -0600 | commented question | Correct input for list_plot3d(..., interpolation='spline') Here's an example (if I understand correctly) of some points having 'nice' x and y coordinates: pts=[(0,0,1),(1,0,2),(0,1,2),(1,1,5)]. Using pts instead of the six points given in the post yields the same TypeError. Can you get a smooth surface from any point set? A single functioning example would be of great help. But I guess I'm off to read the source code: /scipy/interpolate//_fitpack_impl.pyc |
2018-04-16 07:46:14 -0600 | received badge | ● Student (source) |
2018-04-16 07:19:24 -0600 | received badge | ● Editor (source) |
2018-04-16 07:05:11 -0600 | commented answer | Correct input for list_plot3d(..., interpolation='spline') Thanks for the answer, but I don't get it yet. Shouldn't the spline approximation through six points in a plane be the plane itself? Also, the same |
2018-04-15 13:06:03 -0600 | asked a question | Correct input for list_plot3d(..., interpolation='spline') I'm trying to construct smooth surfaces from lists of points in 3-space using
returns the error
The following returns the expected piecewise linear surface suggesting that there is a special restriction on the input when using the
Question: What is the correct input to obtain a best fit polynomial surface going through the six points in $\mathbb{R}^3$? Edit: As pointed out by @slelievre, since these six points lie in a common plane, the corresponding surface should be the plane containing the points. So why does |