Menu
I haven't been able to find anything on this, maybe because I don't have the right nomenclature (i.e. I don't know exactly how to ask for it), but anyway, I have a 3D numpy array "a". I would like to identify and plot the 2D surface where a=0. To make clear, the data is double precision floats smoothly varying over 3D space. It is highly likely that the surface a=0 will "thread between" the points of the array, and not exactly lie right on any of them. So I need something that can interpolate to find the a=0 surface and plot it. Does matplotlib have a ready-made routine for doing this?
331
To select a 2D frame, pick a frame for the first axis and select all data from the remaining two: vol [0, :, :] For this exercise, use for loop to plot every 40th slice of vol on a separate subplot. matplotlib.pyplot (as plt) has been imported for you.
These include magnetic resonance imaging (MRI) and serial section transmission electron microscopy (ssTEM), in which a sample is thinly sliced, like a salami, and each of the slices is imaged separately. To view such images in matplotlib, we have to choose a slice, and display only that slice.
The simplest way to plot 3D and 4D images by slicing them into many 2D frames. Plotting many slices sequentially can create a "fly-through" effect that helps you understand the image as a whole.
Using plt.subplots (), initialize a subplots grid with 1 row and 4 columns. Plot every 40th slice of vol in grayscale. To get the appropriate index, multiply ii by 40. Turn off the ticks, labels, and frame for each subplot.
With Plotly you can plot both planar and nonlinear slices in volumetric data: http://nbviewer.jupyter.org/github/empet/Plotly-plots/blob/master/Plotly-Slice-in-volumetric-data.ipynb
53
If you love us? You can donate to us via Paypal or buy me a coffee so we can maintain and grow! Thank you!
Donate Us With
