# 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.

  1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 from SimPEG import EM, Utils import numpy as np import matplotlib.pyplot as plt def run(plotIt=True): """ Plotting 2D data ================ 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. """ # 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: plt.figure() ax1 = plt.subplot(121) ax2 = plt.subplot(122) # Plot Real Ex (scalar) cont1, ax1 = Utils.plot2Ddata(xyz, Ex.real, dataloc=True, ax=ax1, contourOpts={"cmap": "viridis"}) # 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"}) plt.colorbar(cont1, ax=ax1, orientation="horizontal") plt.colorbar(cont2, ax=ax2, orientation="horizontal") ax1.set_xlabel("x") ax1.set_ylabel("y") ax2.set_xlabel("x") ax2.set_ylabel("y") ax1.set_aspect('equal', adjustable='box') ax2.set_aspect('equal', adjustable='box') if __name__ == '__main__': run() plt.show()