Plotting 2D dataΒΆ

Often measured data is in 2D, but locations are not gridded. Data can be vectoral, hence we want to plot direction and amplitude of the vector. Following example use SimPEG’s analytic function (electric dipole) to generate data at 2D plane.

from SimPEG import EM, Utils
import numpy as np
import matplotlib.pyplot as plt

def run(plotIt=True):
    # Make un-gridded xyz points

    x = np.linspace(-50, 50, 30)
    x += np.random.randn(x.size)*0.1*x
    y = np.linspace(-50, 50, 30)
    y += np.random.randn(x.size)*0.1*y
    z = np.r_[50.]
    xyz = Utils.ndgrid(x, y, z)
    sig = 1.
    f = np.r_[1.]
    srcLoc = np.r_[0., 0., 0.]

    # Use analytic fuction to compute Ex, Ey, Ez
    Ex, Ey, Ez = EM.Analytics.E_from_ElectricDipoleWholeSpace(
        xyz, srcLoc, sig, f

    if plotIt:
        ax1 = plt.subplot(121)
        ax2 = plt.subplot(122)
        # Plot Real Ex (scalar)
        cont1, ax1, cont1l = Utils.plot2Ddata(
            xyz, Ex.real, dataloc=True,
            ax=ax1, contourOpts={"cmap": "viridis"},
            ncontour=5, level=True,
            levelOpts={'colors': 'k', 'linestyles': 'dashed', 'linewidths': 1}
        # Make it as (ndata,2) matrix
        E = np.c_[Ex, Ey]
        # Plot Real E (vector)
        cont2, ax2 = Utils.plot2Ddata(
            xyz, E.real, vec=True,
            ax=ax2, contourOpts={"cmap": "viridis"},
        cb1 = plt.colorbar(
            cont1, ax=ax1, orientation="horizontal",
        ), rotation=45)
        cb2 = plt.colorbar(
            cont2, ax=ax2, orientation="horizontal",
        ), rotation=45)

        ax1.set_aspect('equal', adjustable='box')
        ax2.set_aspect('equal', adjustable='box')

if __name__ == '__main__':

Total running time of the script: ( 0 minutes 0.415 seconds)

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