Hello everybody!

There is a need to build a gradient graph to display the results of calculating the accuracy of geodetic latitude.

My program cyclically calculates the accuracy of calculating the latitude for a given height (in the altitude range from -1 km to 10 km with a step of 1 km for all latitudes about -90 to +90 with a step of 0.16 degrees, the accuracy is magically calculated)

As a result, I get a list that contains 1125 numbers - the accuracy of calculating each i-th latitude at a specific height .

As a result, I have 11 such lists. (at each of the heights)

There is a need to display it on gradient graphics, it can be done with matplotlib, but I do not understand how. I read the documentation and looked at the examples of the script on the website of this library, but I do not understand how it works.

It should be like on the screen, only along the Y axis - heights from -1 km to 10 km, along the X axis - latitudes from -90 to +90, and along the Z axis (the bar to the right) - just accuracy.

enter image description here

Here is a clipping from the script for pcolormesh from their off site:

import numpy as np dx, dy = 0.05, 0.05 y, x = np.mgrid[slice(1, 5 + dy, dy), slice(1, 5 + dx, dx)] z = np.sin(x)**10 + np.cos(10 + y*x) * np.cos(x)

But I just can not understand what is happening with these variables - x, y, z. At the same time, I basically understand what mgrid does, but what is happening inside it in this piece of code is not. (already dealt with this)

Accordingly, without understanding how this example works, I cannot figure out how to solve my problem.

PS If it turned out to be very messy, incomprehensible or something else - do not throw slippers, please) I am still a student and am just learning, and I recently met the python in general, but I have to solve such questions

PS2 Having a little rummaged, (thanks to the first answer under this question) I more or less understood that yes how. Even it turned out to build a graph. enter image description here However, it does not look like a gradient, as if it is turned vertically. The obtained numerical values ​​are generally correct, and I should get a graph like this: enter image description here that is, the problem seems to be in drawing this graph itself, because my numerical values ​​and the standard are very similar (just look at the order of numbers along the Z axis to be sure). But I do not understand why my so goes. Here is the code snippet:

 y, x = np.mgrid[-1000:10000:1000, -0.16:89.84:0.16] z = np.array(lst_b) levels = MaxNLocator(nbins=200).tick_values(z.min(), z.max()) cmap = plt.get_cmap('PiYG') norm = BoundaryNorm(levels, ncolors=cmap.N, clip=True) fig, ax0 = plt.subplots() im = ax0.contourf(x, y, z, cmap=cmap, norm=norm) fig.colorbar(im, ax=ax0) fig.tight_layout() plt.show()

approx. lst_b is a list of 11 lists, each of which contains the numbers I need.

    1 answer 1

    In order to draw a 3D graph, we need an appropriate 3D matrix.

    The np.mgrid [] function allows you to create uniform 2D coordinate lattices for X and Y from slices.

    The easiest way to understand this is with a small example:

     In [49]: x, y = np.mgrid[0.0:1.5:0.5, 0.0:1.5:0.5] In [50]: x Out[50]: array([[0. , 0. , 0. ], [0.5, 0.5, 0.5], [1. , 1. , 1. ]]) In [51]: y Out[51]: array([[0. , 0.5, 1. ], [0. , 0.5, 1. ], [0. , 0.5, 1. ]])

    y - transposed x if you specify the same slices when calling np.mgrid[]

     In [52]: xT == y Out[52]: array([[ True, True, True], [ True, True, True], [ True, True, True]])