def test_eqlayer_polereduce():
"EQLTotalField can reduce data to the pole"
# Use remanent magnetization
sinc, sdec = -70, 30
model = [Prism(-100, 100, -500, 500, 0, 100,
{'magnetization': utils.ang2vec(5, sinc, sdec)})]
inc, dec = -60, -15
shape = (50, 50)
area = [-2000, 2000, -2000, 2000]
x, y, z = gridder.regular(area, shape, z=-100)
data = prism.tf(x, y, z, model, inc, dec)
true = prism.tf(x, y, z, model, -90, 0, pmag=utils.ang2vec(5, -90, 0))
layer = PointGrid(area, 200, shape)
eql = (EQLTotalField(x, y, z, data, inc, dec, layer, sinc, sdec)
+ 1e-24*Damping(layer.size))
eql.fit()
assert_allclose(eql[0].predicted(), data, rtol=0.01)
layer.addprop('magnetization',
utils.ang2vec(eql.estimate_, inc=-90, dec=0))
calc = sphere.tf(x, y, z, layer, inc=-90, dec=0)
assert_allclose(calc, true, atol=10, rtol=0.05)
def test_pel_polereduce():
"PELTotalField can reduce data to the pole"
# Use remanent magnetization
sinc, sdec = -70, 30
model = [Prism(-100, 100, -500, 500, 0, 100,
{'magnetization': utils.ang2vec(5, sinc, sdec)})]
inc, dec = -60, -15
shape = (40, 40)
area = [-2000, 2000, -2000, 2000]
x, y, z = gridder.regular(area, shape, z=-100)
data = prism.tf(x, y, z, model, inc, dec)
true = prism.tf(x, y, z, model, -90, 0, pmag=utils.ang2vec(5, -90, 0))
layer = PointGrid(area, 100, shape)
windows = (20, 20)
degree = 3
pel = PELTotalField(x, y, z, data, inc, dec, layer, windows, degree,
sinc, sdec)
eql = pel + 1e-25*PELSmoothness(layer, windows, degree)
eql.fit()
assert_array_almost_equal(eql[0].predicted(), data, decimal=1)
layer.addprop('magnetization',
utils.ang2vec(eql.estimate_, inc=-90, dec=0))
calc = sphere.tf(x, y, z, layer, inc=-90, dec=0)
assert_allclose(calc, true, atol=10, rtol=0.05)
def test_eql_grav_jacobian():
"EQLGravity produces the right Jacobian matrix for single source"
model = PointGrid([-10, 10, -10, 10], 500, (2, 2))[0]
model.addprop('density', 1)
n = 1000
x, y, z = gridder.scatter([-10, 10, -10, 10], n, z=-100, seed=42)
data = sphere.gz(x, y, z, [model])
eql = EQLGravity(x, y, z, data, [model])
A = eql.jacobian(None)
assert A.shape == (n, 1)
assert_allclose(A[:, 0], data, rtol=0.01)
def test_eql_mag_jacobian():
"EQLTotalField produces the right Jacobian matrix for single source"
inc, dec = -30, 20
model = PointGrid([-10, 10, -10, 10], 500, (2, 2))[0]
model.addprop('magnetization', utils.ang2vec(1, inc, dec))
n = 1000
x, y, z = gridder.scatter([-10, 10, -10, 10], n, z=-100, seed=42)
data = sphere.tf(x, y, z, [model], inc, dec)
eql = EQLTotalField(x, y, z, data, inc, dec, [model])
A = eql.jacobian(None)
assert A.shape == (n, 1)
assert_allclose(A[:, 0], data, rtol=0.01)
def test_eqlgrav_prism_interp():
"EQLGravity can interpolate data from a prism"
model = [Prism(-300, 300, -500, 500, 100, 600, {'density': 400})]
shape = (30, 30)
n = shape[0]*shape[1]
area = [-2000, 2000, -2000, 2000]
x, y, z = gridder.scatter(area, n, z=-100, seed=42)
data = prism.gz(x, y, z, model)
layer = PointGrid(area, 200, shape)
eql = EQLGravity(x, y, z, data, layer) + 1e-23*Damping(layer.size)
eql.fit()
layer.addprop('density', eql.estimate_)
assert_allclose(eql[0].predicted(), data, rtol=0.01)
xp, yp, zp = gridder.regular(area, shape, z=-100)
true = prism.gz(xp, yp, zp, model)
calc = sphere.gz(xp, yp, zp, layer)
assert_allclose(calc, true, rtol=0.05)
def test_pelgrav_prism_interp():
"PELGravity can interpolate data from a prism"
model = [Prism(-300, 300, -500, 500, 100, 600, {'density': 400})]
shape = (40, 40)
n = shape[0]*shape[1]
area = [-2000, 2000, -2000, 2000]
x, y, z = gridder.scatter(area, n, z=-100, seed=42)
data = prism.gz(x, y, z, model)
layer = PointGrid(area, 100, shape)
windows = (20, 20)
degree = 1
eql = (PELGravity(x, y, z, data, layer, windows, degree)
+ 5e-22*PELSmoothness(layer, windows, degree))
eql.fit()
layer.addprop('density', eql.estimate_)
assert_allclose(eql[0].predicted(), data, rtol=0.01)
xp, yp, zp = gridder.regular(area, shape, z=-100)
true = prism.gz(xp, yp, zp, model)
calc = sphere.gz(xp, yp, zp, layer)
assert_allclose(calc, true, atol=0.001, rtol=0.05)