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I doubt there is a standard tool/technique for this kind of task. Nevertheless, there are some approaches. You would need at least one of the following strategies, according to ref. 1 (ch. 8): dimension subsetting: selecting some of the dimensions to display. dimension reduction: transforming the data into a lower-dimensional dataset. dimension embedding: ...


2

In general, one should be very cautious in taking any blanket-statements as an absolute rule. While your professor before might have implied a different logic sequence, mentioned/forgot to mention some details, was wrong or did have only a certain use case in mind – are among possible explanations. axis equal can be good for some cases, and might be a go-to ...


1

Consider the following visualization as an example. It visualizes two binary trees: $T_S$ and $T_V$ for the surface mesh of the sphere and volume mesh of the sphere, respectively. At the 0th level, there is only one node in each tree: $S_1^{(0)}$ and $V_1^{(0)}$. The superscript in the brackets denotes the level in the tree and the subscript denotes the ...


1

You need to look up the VTK file format here: https://vtk.org/wp-content/uploads/2015/04/file-formats.pdf It's not very difficult, you'd just write a single cell for each node of your quad tree. The results will look like the pictures you see here or here or here -- all use VTK file format to visualize meshes.


1

I answered a similar question in StackOverflow. The main "trick" is to transform your grid before plotting. For example, using the following transformation \begin{align} &t' = t\, ,\\ &x' = x e^t\, , \end{align} and then use $(t', x')$ for your plot with contourf() or pcolormesh(). Following is a snippet showing the main idea. import numpy as np ...


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