geoana.em.fdem.MagneticDipoleHalfSpace.magnetic_field#

MagneticDipoleHalfSpace.magnetic_field(xy, field='secondary')#

Magnetic field due to a magnetic dipole over a half space

The analytic expression is only valid for a source and receiver at the surface of the earth. For arbitrary source and receiver locations above the earth, use the layered solution.

Parameters
xy(…, 2) numpy.ndarray

receiver locations of shape

field(“secondary”, “total”)

Flag for the type of field to return.

Returns
(n_freq, …, 3) numpy.array of complex

Magnetic field at all frequencies for the gridded locations provided. Output array is squeezed when n_freq and/or n_loc = 1.

Examples

Here, we define an z-oriented magnetic dipole at (0, 0, 0) and plot the secondary magnetic field at multiple frequencies at (5, 0, 0).

>>> from geoana.em.fdem import MagneticDipoleHalfSpace
>>> from geoana.utils import ndgrid
>>> from geoana.plotting_utils import plot2Ddata
>>> import numpy as np
>>> import matplotlib.pyplot as plt

Let us begin by defining the electric current dipole.

>>> frequency = np.logspace(2, 6, 41)
>>> location = np.r_[0., 0., 0.]
>>> orientation = np.r_[0., 0., 1.]
>>> moment = 1.
>>> sigma = 1.0
>>> simulation = MagneticDipoleHalfSpace(
>>>     frequency, location=location, orientation=orientation,
>>>     moment=moment, sigma=sigma
>>> )

Now we define the receiver location and plot the secondary field.

>>> xyz = np.c_[5, 0, 0]
>>> H = simulation.magnetic_field(xyz, field='secondary')

Finally, we plot the real and imaginary components of the magnetic field.

>>> fig = plt.figure(figsize=(6, 4))
>>> ax1 = fig.add_axes([0.15, 0.15, 0.8, 0.8])
>>> ax1.semilogx(frequency, np.real(H[:, 2]), 'r', lw=2)
>>> ax1.semilogx(frequency, np.imag(H[:, 2]), 'r--', lw=2)
>>> ax1.set_xlabel('Frequency (Hz)')
>>> ax1.set_ylabel('Secondary field (H/m)')
>>> ax1.grid()
>>> ax1.autoscale(tight=True)
>>> ax1.legend(['real', 'imaginary'])

(Source code, png, pdf)

../../_images/geoana-em-fdem-MagneticDipoleHalfSpace-magnetic_field-1.png