Develop Reference

3D plot from CSV matrix

I have a matrix in .csv format with the first row being temperatures and the first column wavelengths. The z-values in the matrix are intensities. I am trying to import the matrix into python and plotting the 3D surface. I tried doing it in excel but there is a limit to the y-values it can plot. Can someone please assist me with this. I tried multiple sources but my difficulty lies in importing the matrix as it is into python, especially the z-values. Matrix.csv

Plotly Express 3D vectors

In python I am busy calculating the closest point of approach between two aircraft for which I have radar point coordinates AND the speed vectors.
To test the algorithm, I am setting up some standard positions and speed vectors and calculate the closest point of approach.
To study the result, I want to create in Plotly Express:
the two starting points
the two speed vectors of the aircraft, each represented by an arrow from their starting point.
a line between the two paths at the location of the closest point of approach. The two points could each be (probably) on the extended line of the initial speed vectors.
Why Plotly Express? Because you can move and swivel around them to investigate.
I had it working in Matplotlib, but then I cannot move around them to study the interaction in 3D.

Python Streamplot from large 1D arrays

I need to plot streamtraces from CFD analysis with Python, over a 2D contour plot. My problem is that I'm dealing with 4 large 1D arrays (x,y coordinates and u,v velocity components), say over 100k points, arising from an external CFD simulation (so I cannot manipulate them). Creating 2D arrays from them (e.g. with scipy.interpolate.griddata as I found) causes my computer to crash due to excessive memory usage.
I've also tried with quiver but I can't get a size for the arrows that scales with the dimensions of the plot: they are either too big or too small and anyway too many.
Since I've looked at all the solutions I've found but none worked.

try to vectorize your loops that may help greatly with large scale datas.

Plotting a 3d triangular mesh from point cloud

I have this object/point cloud,rendered with pyopengl and pygame.
My object is a numpy array of the co-ordinates of the point. I wish to generate a 3d triangular mesh of this object, also it would be nice if you could decrease the number of triangles.
I have tried scipy.spatial.Delaunay and it doesnt generate triangles for 3d objects.

Dual Contouring would probably work well here, it's an algorithm that takes voxelized data and turns it into a mesh. I don't understand it trivially enough to outline it here, but basically you'd take your array of points and place them into a 3D grid array where if that grid cell contains a point it's set to equal 1 (full), and if it doesn't it is set to 0 (empty), you would then run the DC algorithm on this grid and it would output a mesh. The nice thing about this algorithm is it supports internal cavities and concave shapes.
Here's some links I found that may help you if you decide to use DC:
Basic Dual Contouring Theory
http://ngildea.blogspot.com/2014/11/implementing-dual-contouring.html
This is the github repo to the source I used when I implemented this algorithm in Unity3D:
https://github.com/nickgildea/DualContouringSample

Plot Arbitray Slice of 3d points in Python

So I am a bit new to python and having a little trouble.
I am attempting to plot (project) a 3d data set onto an arbitrary plane. I can of course plot xy etc. but since my data has a particular orientation (all the points fall into an arbitrary orientated cylinder) I want project all the points onto a plane that slices that cylinder orthogonally and that plane would have a arbitrary orientation.
I am working with microseismic data if anyone is familiar with that and all the points are located around a wellbore with follows an arbitrary but fairly straight azimuth.
The data is in Cartesian coordinates.