def test_taper_functions(load_magnetic_anomaly):
d = load_magnetic_anomaly["mag_data"]
xc = load_magnetic_anomaly["xc"]
yc = load_magnetic_anomaly["yc"]
xmin, xmax, ymin, ymax = load_magnetic_anomaly["extent"]
grid = pycurious.CurieGrid(d, xmin, xmax, ymin, ymax)
# Take Fourier transform using different taper functions
k, Phi1, sigma_Phi1 = grid.radial_spectrum(grid.data, taper=None)
k, Phi2, sigma_Phi2 = grid.radial_spectrum(grid.data, taper=np.hanning)
k, Phi3, sigma_Phi3 = grid.radial_spectrum(grid.data, taper=np.hamming)
grad_Phi1 = np.gradient(Phi1, k)
grad_Phi2 = np.gradient(Phi2, k)
grad_Phi3 = np.gradient(Phi3, k)
assert (
Phi1.mean() > Phi2.mean()
), "FAILED! 'taper=np.hanning' not significantly different from 'taper=None'"
assert (
Phi1.mean() > Phi3.mean()
), "FAILED! 'taper=np.hamming' not significantly different from 'taper=None'"
assert (
grad_Phi1.mean() > grad_Phi2.mean()
), "FAILED! 'taper=np.hanning' has steeper gradient from 'taper=None'"
assert (
grad_Phi1.mean() > grad_Phi3.mean()
), "FAILED! 'taper=np.hamming' has steeper gradient from 'taper=None'"
def test_FFT(load_magnetic_anomaly):
d = load_magnetic_anomaly["mag_data"]
xc = load_magnetic_anomaly["xc"]
yc = load_magnetic_anomaly["yc"]
xmin, xmax, ymin, ymax = load_magnetic_anomaly["extent"]
grid = pycurious.CurieGrid(d, xmin, xmax, ymin, ymax)
# Take Fourier transform
k, Phi, sigma_Phi = grid.radial_spectrum(grid.data, taper=None)
# radial power spectrum should decrease with wavenumber
# divide Phi into three sections
i3 = len(k) // 3
Phi1 = Phi[:i3]
Phi2 = Phi[i3:2 * i3]
Phi3 = Phi[2 * i3:]
# also sigma_Phi should decrease with wavenumber
sigma_Phi1 = sigma_Phi[:i3]
sigma_Phi2 = sigma_Phi[i3:2 * i3]
sigma_Phi3 = sigma_Phi[2 * i3:]
error_msg = "FAILED! Fast Fourier Transform did not produce a valid power spectrum"
assert Phi1.mean() > Phi2.mean() > Phi3.mean(), error_msg
assert sigma_Phi1.mean() > sigma_Phi2.mean() > sigma_Phi3.mean(), error_msg
def test_subgrid(load_magnetic_anomaly):
d = load_magnetic_anomaly["mag_data"]
xc = load_magnetic_anomaly["xc"]
yc = load_magnetic_anomaly["yc"]
xmin, xmax, ymin, ymax = load_magnetic_anomaly["extent"]
grid = pycurious.CurieGrid(d, xmin, xmax, ymin, ymax)
window_size = 100e3
subgrid = grid.subgrid(window_size, xc, yc)
error_msg = "FAILED! Subgrid is of shape {} and domain is of shape {}".format(
subgrid.shape, grid.data.shape)
assert subgrid.shape[0] < grid.data.shape[0], error_msg
assert subgrid.shape[1] < grid.data.shape[1], error_msg
def test_CurieGrid_routines(load_magnetic_anomaly):
d = load_magnetic_anomaly["mag_data"]
xc = load_magnetic_anomaly["xc"]
yc = load_magnetic_anomaly["yc"]
xmin, xmax, ymin, ymax = load_magnetic_anomaly["extent"]
max_window = load_magnetic_anomaly["max_window"]
cpd = pycurious.CurieGrid(d, xmin, xmax, ymin, ymax)
assert time_routine(cpd.__init__, d, xmin, xmax, ymin, ymax)
assert time_routine(cpd.subgrid, max_window, xc, yc)
assert time_routine(cpd.create_centroid_list, 0.1 * max_window)
assert time_routine(cpd.remove_trend_linear, cpd.data)
assert time_routine(cpd.radial_spectrum, cpd.data)
assert time_routine(cpd.azimuthal_spectrum, cpd.data)
assert time_routine(cpd.reduce_to_pole, cpd.data, 30.0, 30.0)
assert time_routine(cpd.upward_continuation, cpd.data, 10e3)
def test_Tanaka(load_magnetic_anomaly):
d = load_magnetic_anomaly["mag_data"]
xc = load_magnetic_anomaly["xc"]
yc = load_magnetic_anomaly["yc"]
xmin, xmax, ymin, ymax = load_magnetic_anomaly["extent"]
grid = pycurious.CurieGrid(d, xmin, xmax, ymin, ymax)
# wavenumber bands for Z0 and Zt, respectively
kwin_Z0 = (0.005, 0.03)
kwin_Zt = (0.03, 0.7)
k, Phi, sigma_Phi = grid.radial_spectrum(grid.data,
taper=np.hanning,
power=0.5)
(Ztr, btr, dZtr), (Zor, bor,
dZor) = pycurious.tanaka1999(k, Phi, sigma_Phi, kwin_Z0,
kwin_Zt)
Zb, eZb = pycurious.ComputeTanaka(Ztr, dZtr, Zor, dZor)
error_msg = "FAILED! Tanaka CPD is {:.4f} different from expected, uncertainty is {:.4f}".format(
Zb - 10.0, eZb)
assert np.abs(Zb - 10.0) < 2.0 and eZb < Zb, error_msg
# save grid
np.savez_compressed('mag_grid2.npz',
data=mag_grid,
xm=xmin,
xM=xmax,
ym=ymin,
yM=ymax)
#print(mag_grid.shape,xmin,xmax,ymin,ymax)
#plt.imshow(mag_grid, extent=(xmin, xmax, ymin, ymax), origin='lower')
#plt.show()
#exit()
## plt.imshow(mag_grid, extent=(xmin, xmax, ymin, ymax), origin='lower')
## initialise CurieGrid object
grid = pycurious.CurieGrid(mag_grid, xmin, xmax, ymin, ymax)
## Let's not!'
## let's pick a point in the centre of the study area
#xpt = xmin + (xmax-xmin)/2
#ypt = ymin + (ymax-ymin)/2
#print(xpt,ypt)
## get a subsection of the grid
#subgrid = grid.subgrid(xpt, ypt, 50000.)
#print(subgrid.shape)
## compute radial spectrum
#S, k, sigma2 = grid.radial_spectrum(subgrid, taper=None)
## fig, (ax1, ax2) = plt.subplots(1,2,figsize=(12,4))
## ax1.plot(k, abs(S))
##ax2.plot(sf, abs(S))
#Zb,eZb = grid.Tanaka(S, k, sigma2,kmin=0.05, kmax=0.2)