Python 2d grid : Assigning values to coordinates in the grid

Question

I'm just a beginner Python user so bear with me,

I've created a 2d XY grid using np.meshgrid, and would like to know how to assign values to some of the points in the grid. The application is to set a mass to certain points in the grid to model point masses. My code as of now is as follows:

import numpy as np
x = np.arange(11)
y = np.arange(11)

X, Y = np.meshgrid(x,y)

Thanks a lot!

what do you mean by "assign values to some of the points in the grid." like have a Z array of values for each X,Y coordinate? — Tadhg McDonald-Jensen
– Tadhg McDonald-Jensen, Commented Jun 4, 2016 at 16:30
well yes something like that, but I couldn't think of how to relate the Z as a function of X and Y coordinates and then say, plot it as a contour to visualise it — ThunderFlash
– ThunderFlash, Commented Jun 4, 2016 at 16:44
@karasinski gave you an answer for what you seem to be asking. You can give any value directly by attribution, ´Z[5,5] = 5´. What is your grid supposed to represent? Are you working in estimation? — armatita
– armatita, Commented Jun 4, 2016 at 20:18
Could you show me an example code for the entire process? i really am missing out on something basic here my bad. The grid merely represents coordinates and I want to include point masses at some points. I have to use it to model a gravitational lensing system. — ThunderFlash
– ThunderFlash, Commented Jun 4, 2016 at 20:23

John Karasinski · Accepted Answer · 2016-06-04 21:44:50Z

1

Since you're a beginner Python user, I highly recommend you take the time to check out the documentation for the packages you are using. Does this example from matplotlib's documentation answer your question?

from mpl_toolkits.mplot3d import Axes3D
from matplotlib import cm
from matplotlib.ticker import LinearLocator, FormatStrFormatter
import matplotlib.pyplot as plt
import numpy as np

fig = plt.figure()
ax = fig.gca(projection='3d')
X = np.arange(-5, 5, 0.25)
Y = np.arange(-5, 5, 0.25)
X, Y = np.meshgrid(X, Y)
R = np.sqrt(X**2 + Y**2)
Z = np.sin(R)
surf = ax.plot_surface(X, Y, Z, rstride=1, cstride=1, cmap=cm.coolwarm,
                       linewidth=0, antialiased=False)
ax.set_zlim(-1.01, 1.01)

ax.zaxis.set_major_locator(LinearLocator(10))
ax.zaxis.set_major_formatter(FormatStrFormatter('%.02f'))

fig.colorbar(surf, shrink=0.5, aspect=5)

plt.show()

Alternatively, you could also view the numpy documentation for the meshgrid function, which gives a similar example:

x = np.arange(-5, 5, 0.1)
y = np.arange(-5, 5, 0.1)
xx, yy = meshgrid(x, y, sparse=True)
z = np.sin(xx**2 + yy**2) / (xx**2 + yy**2)
h = plt.contourf(x,y,z)

EDIT

If you want to manually set the values of Z, you can do something along the lines of

fig = plt.figure()
ax = fig.gca(projection='3d')
x = np.arange(11)
y = np.arange(11)
X, Y = np.meshgrid(x,y)
Z = np.zeros_like(X)
Z[5][5] = 5
surf = ax.plot_surface(X, Y, Z, rstride=1, cstride=1)
plt.show()

edited Jun 4, 2016 at 21:44

answered Jun 4, 2016 at 19:22

John Karasinski

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1 Comment

ThunderFlash Over a year ago

Thanks for your suggestion! but I did come across these examples before, and I'm comfortable with defining a function z over the entire x y coordinate plane. What I seem to be stuck at is say, letting (x,y) = (5,5) have a z value of 5. A particular value for a particular coordinate. I'm not sure how to go about doing that? An example would be, say I have a grid of 10 x 10. I want the (5,5) coordinate to have a magnitude of 5. How would I define this?

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