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.buildinfo

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+# Sphinx build info version 1
+# This file hashes the configuration used when building these files. When it is not found, a full rebuild will be done.
+config: 16d3360a29ba6d075d2077b5939d3251
+tags: 645f666f9bcd5a90fca523b33c5a78b7

CNAME

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+geoana.simpeg.xyz

_downloads/049ebf5f8db05b09e65ed55207cc4cf0/geoana-em-static-MagnetostaticSphere-magnetic_field-1.py

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+# Here, we define a sphere with permeability mu_sphere in a uniform magnetostatic field with permeability
+# mu_background and plot the total and secondary magnetic fields.
+#
+import numpy as np
+import matplotlib.pyplot as plt
+from matplotlib import patches
+from mpl_toolkits.axes_grid1 import make_axes_locatable
+from geoana.em.static import MagnetostaticSphere
+#
+# Define the sphere.
+#
+mu_sphere = 10. ** -1
+mu_background = 10. ** -3
+radius = 1.0
+simulation = MagnetostaticSphere(
+    location=None, mu_sphere=mu_sphere, mu_background=mu_background, radius=radius, primary_field=None
+)
+#
+# Now we create a set of gridded locations and compute the magnetic fields.
+#
+X, Y = np.meshgrid(np.linspace(-2*radius, 2*radius, 20), np.linspace(-2*radius, 2*radius, 20))
+Z = np.zeros_like(X) + 0.25
+xyz = np.stack((X, Y, Z), axis=-1)
+ht = simulation.magnetic_field(xyz, field='total')
+hs = simulation.magnetic_field(xyz, field='secondary')
+#
+# Finally, we plot the total and secondary magnetic fields.
+#
+fig, axs = plt.subplots(1, 2, figsize=(18,12))
+titles = ['Total Magnetic Field', 'Secondary Magnetic Field']
+for ax, H, title in zip(axs.flatten(), [ht, hs], titles):
+    H_amp = np.linalg.norm(H, axis=-1)
+    im = ax.pcolor(X, Y, H_amp, shading='auto')
+    divider = make_axes_locatable(ax)
+    cax = divider.append_axes("right", size="5%", pad=0.05)
+    cb = plt.colorbar(im, cax=cax)
+    cb.set_label(label= 'Amplitude ($A/m$)')
+    ax.streamplot(X, Y, H[..., 0], H[..., 1], density=0.75)
+    ax.add_patch(patches.Circle((0, 0), radius, fill=False, linestyle='--'))
+    ax.set_ylabel('Y coordinate ($m$)')
+    ax.set_xlabel('X coordinate ($m$)')
+    ax.set_aspect('equal')
+    ax.set_title(title)
+plt.tight_layout()
+plt.show()

_downloads/05ff2fa7d9719112280af013b3598c83/geoana-em-tdem-TransientPlaneWave-electric_field-1.py

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+# Here, we define a transient planewave in the x-direction in a wholespace.
+#
+from geoana.em.tdem import TransientPlaneWave
+import numpy as np
+from geoana.utils import ndgrid
+from mpl_toolkits.axes_grid1 import make_axes_locatable
+import matplotlib.pyplot as plt
+#
+# Let us begin by defining the transient planewave in the x-direction.
+#
+time = 1.0
+orientation = 'X'
+sigma = 1.0
+simulation = TransientPlaneWave(
+    time=time, orientation=orientation, sigma=sigma
+)
+#
+# Now we create a set of gridded locations and compute the electric field.
+#
+x = np.linspace(-1, 1, 20)
+z = np.linspace(-1000, 0, 20)
+xyz = ndgrid(x, np.array([0]), z)
+e_vec = simulation.electric_field(xyz)
+ex = e_vec[..., 0]
+#
+# Finally, we plot the x-oriented electric field.
+#
+plt.pcolor(x, z, ex.reshape(20, 20), shading='auto')
+cb = plt.colorbar()
+cb.set_label(label= 'Electric Field ($V/m$)')
+plt.ylabel('Z coordinate ($m$)')
+plt.xlabel('X coordinate ($m$)')
+plt.title('Electric Field of a Transient Planewave in the x-direction in a Wholespace')
+plt.show()

_downloads/0c25dfedb7c71cf82b20ef17513a0696/geoana-em-static-LineCurrentFreeSpace-magnetic_field-1.py

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+# Here, we define a horizontal square loop and plot the magnetic field
+# on the xz-plane that intercepts at y=0.
+#
+from geoana.em.static import LineCurrentFreeSpace
+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 loop. Note that to create an inductive
+# source, we closed the loop.
+#
+x_nodes = np.array([-0.5, 0.5, 0.5, -0.5, -0.5])
+y_nodes = np.array([-0.5, -0.5, 0.5, 0.5, -0.5])
+z_nodes = np.zeros_like(x_nodes)
+nodes = np.c_[x_nodes, y_nodes, z_nodes]
+simulation = LineCurrentFreeSpace(nodes)
+#
+# Now we create a set of gridded locations and compute the magnetic field.
+#
+xyz = ndgrid(np.linspace(-1, 1, 50), np.array([0]), np.linspace(-1, 1, 50))
+H = simulation.magnetic_field(xyz)
+#
+# Finally, we plot the magnetic field.
+#
+fig = plt.figure(figsize=(4, 4))
+ax = fig.add_axes([0.15, 0.15, 0.75, 0.75])
+plot2Ddata(xyz[:, [0, 2]], H[:, [0, 2]], ax=ax, vec=True, scale='log', ncontour=25)
+ax.set_xlabel('X')
+ax.set_ylabel('Z')
+ax.set_title('Magnetic field')

_downloads/0d82c9a80d4704774fd8867de05810eb/geoana-em-static-MagneticDipoleWholeSpace-vector_potential-1.py

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+# Here, we define a z-oriented magnetic dipole and plot the vector
+# potential on the xy-plane that intercepts at z=0.
+#
+from geoana.em.static import MagneticDipoleWholeSpace
+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 magnetic dipole.
+#
+location = np.r_[0., 0., 0.]
+orientation = np.r_[0., 0., 1.]
+moment = 1.
+dipole_object = MagneticDipoleWholeSpace(
+    location=location, orientation=orientation, moment=moment
+)
+#
+# Now we create a set of gridded locations and compute the vector potential.
+#
+xyz = ndgrid(np.linspace(-1, 1, 20), np.linspace(-1, 1, 20), np.array([0]))
+a = dipole_object.vector_potential(xyz)
+#
+# Finally, we plot the vector potential on the plane. Given the symmetry,
+# there are only horizontal components.
+#
+fig = plt.figure(figsize=(4, 4))
+ax = fig.add_axes([0.15, 0.15, 0.8, 0.8])
+plot2Ddata(xyz[:, 0:2], a[:, 0:2], ax=ax, vec=True, scale='log')
+ax.set_xlabel('X')
+ax.set_ylabel('Z')
+ax.set_title('Vector potential at z=0')

_downloads/0e40bdc2af091bc0a56939f6b81a4617/geoana-em-static-MagneticDipoleWholeSpace-magnetic_flux_density-1.py

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+# Here, we define a z-oriented magnetic dipole and plot the magnetic
+# flux density on the xy-plane that intercepts y=0.
+#
+from geoana.em.static import MagneticDipoleWholeSpace
+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 magnetic dipole.
+#
+location = np.r_[0., 0., 0.]
+orientation = np.r_[0., 0., 1.]
+moment = 1.
+dipole_object = MagneticDipoleWholeSpace(
+    location=location, orientation=orientation, moment=moment
+)
+#
+# Now we create a set of gridded locations and compute the vector potential.
+#
+xyz = ndgrid(np.linspace(-1, 1, 20), np.array([0]), np.linspace(-1, 1, 20))
+B = dipole_object.magnetic_flux_density(xyz)
+#
+# Finally, we plot the vector potential on the plane. Given the symmetry,
+# there are only horizontal components.
+#
+fig = plt.figure(figsize=(4, 4))
+ax = fig.add_axes([0.15, 0.15, 0.8, 0.8])
+plot2Ddata(xyz[:, 0::2], B[:, 0::2], ax=ax, vec=True, scale='log')
+ax.set_xlabel('X')
+ax.set_ylabel('Z')
+ax.set_title('Magnetic flux density at y=0')

_downloads/1431bc967a3504f266f06fe58b074465/geoana-gravity-PointMass-gravitational_field-1.py

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+# Here, we define a point mass with mass=1kg and plot the gravitational
+# field lines in the xy-plane.
+#
+import numpy as np
+import matplotlib.pyplot as plt
+from geoana.gravity import PointMass
+#
+# Define the point mass.
+#
+location = np.r_[0., 0., 0.]
+mass = 1.0
+simulation = PointMass(
+    mass=mass, location=location
+)
+#
+# Now we create a set of gridded locations and compute the gravitational field.
+#
+X, Y = np.meshgrid(np.linspace(-1, 1, 20), np.linspace(-1, 1, 20))
+Z = np.zeros_like(X) + 0.25
+xyz = np.stack((X, Y, Z), axis=-1)
+g = simulation.gravitational_field(xyz)
+#
+# Finally, we plot the gravitational field lines.
+#
+plt.quiver(X, Y, g[:,:,0], g[:,:,1])
+plt.xlabel('x')
+plt.ylabel('y')
+plt.title('Gravitational Field Lines for a Point Mass')
+plt.show()

_downloads/15111a326c15e71fe9acfe5b5142fd70/geoana-em-fdem-ElectricDipoleWholeSpace-current_density-1.py

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+# Here, we define an x-oriented electric dipole and plot the current
+# density on the xz-plane that intercepts y=0.
+#
+from geoana.em.fdem import ElectricDipoleWholeSpace
+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(1, 3, 3)
+location = np.r_[0., 0., 0.]
+orientation = np.r_[1., 0., 0.]
+current = 1.
+sigma = 1.0
+simulation = ElectricDipoleWholeSpace(
+    frequency, location=location, orientation=orientation,
+    current=current, sigma=sigma
+)
+#
+# Now we create a set of gridded locations and compute the current density.
+#
+xyz = ndgrid(np.linspace(-1, 1, 20), np.array([0]), np.linspace(-1, 1, 20))
+J = simulation.current_density(xyz)
+#
+# Finally, we plot the real and imaginary components of the current density.
+#
+f_ind = 1
+fig = plt.figure(figsize=(6, 3))
+ax1 = fig.add_axes([0.15, 0.15, 0.40, 0.75])
+plot2Ddata(
+    xyz[:, 0::2], np.real(J[f_ind, :, 0::2]), vec=True, ax=ax1, scale='log', ncontour=25
+)
+ax1.set_xlabel('X')
+ax1.set_ylabel('Z')
+ax1.autoscale(tight=True)
+ax1.set_title('Real component {} Hz'.format(frequency[f_ind]))
+ax2 = fig.add_axes([0.6, 0.15, 0.40, 0.75])
+plot2Ddata(
+    xyz[:, 0::2], np.imag(J[f_ind, :, 0::2]), vec=True, ax=ax2, scale='log', ncontour=25
+)
+ax2.set_xlabel('X')
+ax2.set_yticks([])
+ax2.autoscale(tight=True)
+ax2.set_title('Imag component {} Hz'.format(frequency[f_ind]))

_downloads/18a8b5df8125bbc9d88b2ab30515c4db/geoana-em-tdem-ElectricDipoleWholeSpace-magnetic_field_time_deriv-1.py

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+# Here, we define a z-oriented electric dipole and plot the time-derivative
+# of the magnetic field on the xy-plane that intercepts z=0.
+#
+from geoana.em.tdem import ElectricDipoleWholeSpace
+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.
+#
+time = np.logspace(-6, -2, 3)
+location = np.r_[0., 0., 0.]
+orientation = np.r_[0., 0., 1.]
+current = 1.
+sigma = 1.0
+simulation = ElectricDipoleWholeSpace(
+    time, location=location, orientation=orientation,
+    current=current, sigma=sigma
+)
+#
+# Now we create a set of gridded locations and compute the dh/dt.
+#
+xyz = ndgrid(np.linspace(-10, 10, 20), np.linspace(-10, 10, 20), np.array([0]))
+dHdt = simulation.magnetic_field_time_deriv(xyz)
+#
+# Finally, we plot dH/dt at the desired locations/times.
+#
+t_ind = 0
+fig = plt.figure(figsize=(4, 4))
+ax = fig.add_axes([0.15, 0.15, 0.8, 0.8])
+plot2Ddata(xyz[:, 0:2], dHdt[t_ind, :, 0:2], ax=ax, vec=True, scale='log')
+ax.set_xlabel('X')
+ax.set_ylabel('Y')
+ax.set_title('dH/dt at {} s'.format(time[t_ind]))

_downloads/1bbc3da5fb9f2c64c55ad12f3e49236d/geoana-em-fdem-ElectricDipoleWholeSpace-magnetic_field-1.py

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+# Here, we define an z-oriented electric dipole and plot the magnetic field
+# on the xy-plane that intercepts z=0.
+#
+from geoana.em.fdem import ElectricDipoleWholeSpace
+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(1, 3, 3)
+location = np.r_[0., 0., 0.]
+orientation = np.r_[0., 0., 1.]
+current = 1.
+sigma = 1.0
+simulation = ElectricDipoleWholeSpace(
+    frequency, location=location, orientation=orientation,
+    current=current, sigma=sigma
+)
+#
+# Now we create a set of gridded locations and compute the magnetic field.
+#
+xyz = ndgrid(np.linspace(-1, 1, 20), np.linspace(-1, 1, 20), np.array([0]))
+H = simulation.magnetic_field(xyz)
+#
+# Finally, we plot the real and imaginary components of the magnetic field.
+#
+f_ind = 1
+fig = plt.figure(figsize=(6, 3))
+ax1 = fig.add_axes([0.15, 0.15, 0.40, 0.75])
+plot2Ddata(
+    xyz[:, 0:2], np.real(H[f_ind, :, 0:2]), vec=True, ax=ax1, scale='log', ncontour=25
+)
+ax1.set_xlabel('X')
+ax1.set_ylabel('Y')
+ax1.autoscale(tight=True)
+ax1.set_title('Real component {} Hz'.format(frequency[f_ind]))
+ax2 = fig.add_axes([0.6, 0.15, 0.40, 0.75])
+plot2Ddata(
+    xyz[:, 0:2], np.imag(H[f_ind, :, 0:2]), vec=True, ax=ax2, scale='log', ncontour=25
+)
+ax2.set_xlabel('X')
+ax2.set_yticks([])
+ax2.autoscale(tight=True)
+ax2.set_title('Imag component {} Hz'.format(frequency[f_ind]))