def dipole(src,
rec,
depth,
res,
freqtime,
aniso=None,
eperm=None,
mperm=None,
verb=2):
r"""Return the electromagnetic field due to a dipole source.
This is a modified version of :func:`empymod.model.dipole`. It returns the
separated contributions of TM--, TM-+, TM+-, TM++, TMdirect, TE--, TE-+,
TE+-, TE++, and TEdirect.
Parameters
----------
src, rec : list of floats or arrays
Source and receiver coordinates (m): [x, y, z].
The x- and y-coordinates can be arrays, z is a single value.
The x- and y-coordinates must have the same dimension.
Sources or receivers placed on a layer interface are considered in the
upper layer.
Sources and receivers must be in the same layer.
depth : list
Absolute layer interfaces z (m); #depth = #res - 1
(excluding +/- infinity).
res : array_like
Horizontal resistivities rho_h (Ohm.m); #res = #depth + 1.
freqtime : float
Frequency f (Hz). (The name `freqtime` is kept for consistency with
:func:`empymod.model.dipole`. Only one frequency at once.
aniso : array_like, optional
Anisotropies lambda = sqrt(rho_v/rho_h) (-); #aniso = #res.
Defaults to ones.
eperm : array_like, optional
Relative electric permittivities epsilon (-);
#eperm = #res. Default is ones.
mperm : array_like, optional
Relative magnetic permeabilities mu (-);
#mperm = #res. Default is ones.
verb : {0, 1, 2, 3, 4}, optional
Level of verbosity, default is 2:
- 0: Print nothing.
- 1: Print warnings.
- 2: Print additional runtime and kernel calls
- 3: Print additional start/stop, condensed parameter information.
- 4: Print additional full parameter information
Returns
-------
TM, TE : list of ndarrays, (nfreq, nrec, nsrc)
Frequency-domain EM field [V/m], separated into
TM = [TM--, TM-+, TM+-, TM++, TMdirect]
and
TE = [TE--, TE-+, TE+-, TE++, TEdirect].
However, source and receiver are normalised. So the source strength is
1 A and its length is 1 m. Therefore the electric field could also be
written as [V/(A.m2)].
The shape of EM is (nfreq, nrec, nsrc). However, single dimensions
are removed.
"""
# === 1. LET'S START ============
t0 = printstartfinish(verb)
# === 2. CHECK INPUT ============
# Check layer parameters
model = check_model(depth, res, aniso, eperm, eperm, mperm, mperm, False,
verb)
depth, res, aniso, epermH, epermV, mpermH, mpermV, _ = model
# Check frequency => get etaH, etaV, zetaH, and zetaV
frequency = check_frequency(freqtime, res, aniso, epermH, epermV, mpermH,
mpermV, verb)
freq, etaH, etaV, zetaH, zetaV = frequency
# Check src and rec
src, nsrc = check_dipole(src, 'src', verb)
rec, nrec = check_dipole(rec, 'rec', verb)
# Get offsets
off, ang = get_off_ang(src, rec, nsrc, nrec, verb)
# Get layer number in which src and rec reside (lsrc/lrec)
lsrc, zsrc = get_layer_nr(src, depth)
lrec, zrec = get_layer_nr(rec, depth)
# Check limitations of this routine compared to the standard `dipole`
if lsrc != lrec: # src and rec in same layer
raise ValueError("src and rec must be in the same layer; "
f"<lsrc>/<lrec> provided: {lsrc}/{lrec}.")
if depth.size < 2: # at least two layers
raise ValueError("model must have more than one layer; "
f"<depth> provided: {_strvar(depth[1:])}.")
if freq.size > 1: # only 1 frequency
raise ValueError("only one frequency permitted; "
f"<freqtime> provided: {_strvar(freqtime)}.")
# === 3. EM-FIELD CALCULATION ============
# This part is a simplification of:
# - model.fem()
# - transform.dlf()
# - kernel.wavenumber()
# DLF filter we use
filt = key_201_2012()
# 3.1. COMPUTE REQUIRED LAMBDAS for given hankel-filter-base
lambd = filt.base / off[:, None]
# 3.2. CALL THE KERNEL
PTM, PTE = greenfct(zsrc, zrec, lsrc, lrec, depth, etaH, etaV, zetaH,
zetaV, lambd)
# 3.3. CARRY OUT THE HANKEL TRANSFORM WITH DLF
ang_fact = angle_factor(ang, 11, False, False)
zm_ang_fact = (ang_fact[:, np.newaxis] - 1) / 2
zp_ang_fact = (ang_fact[:, np.newaxis] + 1) / 2
fact = 4 * np.pi * off
# TE [uu, ud, du, dd, df]
for i, val in enumerate(PTE):
PTE[i] = (ang_fact * np.dot(-val, filt.j1) / off +
np.dot(zm_ang_fact * val * lambd, filt.j0)) / fact
# TM [uu, ud, du, dd, df]
for i, val in enumerate(PTM):
PTM[i] = (ang_fact * np.dot(-val, filt.j1) / off +
np.dot(zp_ang_fact * val * lambd, filt.j0)) / fact
# 3.4. Remove non-physical contributions
# (Note: The T*dd corrections differ slightly from the equations given in
# the accompanying pdf, due to the way the direct field is accounted for
# in the book.)
# General parameters
Gam = np.sqrt((zetaH * etaH)[:, None, :, None]) # Gam for lambd=0
iGam = Gam[:, :, lsrc, 0]
lgam = np.sqrt(zetaH[:, lsrc] * etaH[:, lsrc])
ddepth = np.r_[depth, np.inf]
ds = ddepth[lsrc + 1] - ddepth[lsrc]
def get_rp_rm(z_eta):
r"""Return Rp, Rm."""
# Get Rp/Rm for lambd=0
Rp, Rm = reflections(depth, z_eta, Gam, lrec, lsrc)
# Depending on model Rp/Rm have 3 or 4 dimensions. Last two are
# wavenumbers and layers btw src and rec, which both are 1.
if Rp.ndim == 4:
Rp = np.squeeze(Rp, axis=3)
if Rm.ndim == 4:
Rm = np.squeeze(Rm, axis=3)
Rp = np.squeeze(Rp, axis=2)
Rm = np.squeeze(Rm, axis=2)
# Calculate reverberation M and general factor npfct
Ms = 1 - Rp * Rm * np.exp(-2 * iGam * ds)
npfct = ang_fact * zetaH[:, lsrc] / (fact * off * lgam * Ms)
return Rp, Rm, npfct
# TE modes TE[uu, ud, du, dd]
Rp, Rm, npfct = get_rp_rm(zetaH)
PTE[0] += npfct * Rp * Rm * np.exp(-lgam * (2 * ds - zrec + zsrc))
PTE[1] += npfct * Rp * np.exp(-lgam * (2 * ddepth[lrec + 1] - zrec - zsrc))
PTE[2] += npfct * Rm * np.exp(-lgam * (zrec + zsrc))
PTE[3] += npfct * Rp * Rm * np.exp(-lgam * (2 * ds + zrec - zsrc))
# TM modes TM[uu, ud, du, dd]
Rp, Rm, npfct = get_rp_rm(etaH)
PTM[0] -= npfct * Rp * Rm * np.exp(-lgam * (2 * ds - zrec + zsrc))
PTM[1] += npfct * Rp * np.exp(-lgam * (2 * ddepth[lrec + 1] - zrec - zsrc))
PTM[2] += npfct * Rm * np.exp(-lgam * (zrec + zsrc))
PTM[3] -= npfct * Rp * Rm * np.exp(-lgam * (2 * ds + zrec - zsrc))
# 3.5 Reshape for number of sources
for i, val in enumerate(PTE):
PTE[i] = np.squeeze(val.reshape((-1, nrec, nsrc), order='F'))
for i, val in enumerate(PTM):
PTM[i] = np.squeeze(val.reshape((-1, nrec, nsrc), order='F'))
# === 4. FINISHED ============
printstartfinish(verb, t0)
# return [TMuu, TMud, TMdu, TMdd, TMdf], [TEuu, TEud, TEdu, TEdd, TEdf]
return PTM, PTE
def test_angle_factor(): # 5. angle_factor
dat = DATAKERNEL['angres'][()]
for ddat in dat:
res = kernel.angle_factor(**ddat['inp'])
assert_allclose(res, ddat['res'])
b_zero = np.pi * np.arange(1.25, maxint + 1)
for i in range(10):
b_x0 = special.j1(b_zero)
b_x1 = special.jv(2, b_zero)
b_h = -b_x0 / (b_x0 / b_zero - b_x1)
b_zero += b_h
if all(np.abs(b_h) < 8 * np.finfo(float).eps * b_zero):
break
xint = np.concatenate((np.array([1e-20]), b_zero))
dx = np.repeat(np.diff(xint) / 2, nquad)
Bx = dx * (np.tile(g_x, maxint) + 1) + np.repeat(xint[:-1], nquad)
BJ0 = special.j0(Bx) * np.tile(g_w, maxint)
BJ1 = special.j1(Bx) * np.tile(g_w, maxint)
intervals = xint / off[:, None]
lambd = Bx / off[:, None]
factAng = kernel.angle_factor(angle, ab, msrc, mrec)
# 1 Spline version
start = np.log(lambd.min())
stop = np.log(lambd.max())
ilambd = np.logspace(start, stop, (stop - start) * pts_per_dec + 1, 10)
PJ0, PJ1, PJ0b = kernel.wavenumber(zsrc, zrec, lsrc, lrec, depth,
etaH[None, :], etaV[None, :],
zetaH[None, :], zetaV[None, :],
np.atleast_2d(ilambd), ab, False, msrc,
mrec, False)
si_PJ0r = iuSpline(np.log(ilambd), PJ0.real)
si_PJ0i = iuSpline(np.log(ilambd), PJ0.imag)
si_PJ1r = iuSpline(np.log(ilambd), PJ1.real)
si_PJ1i = iuSpline(np.log(ilambd), PJ1.imag)
si_PJ0br = iuSpline(np.log(ilambd), PJ0b.real)
si_PJ0bi = iuSpline(np.log(ilambd), PJ0b.imag)
def test_hankel(htype): # 1. DLF / 2. QWE / 3. QUAD
# Compare wavenumber-domain calculation / DLF with analytical
# frequency-domain fullspace solution
calc = getattr(transform, 'hankel_' + htype)
model = utils.check_model([], 10, 2, 2, 5, 1, 10, True, 0)
depth, res, aniso, epermH, epermV, mpermH, mpermV, _ = model
frequency = utils.check_frequency(1, res, aniso, epermH, epermV, mpermH,
mpermV, 0)
_, etaH, etaV, zetaH, zetaV = frequency
src = [0, 0, 0]
src, nsrc = utils.check_dipole(src, 'src', 0)
for ab_inp in [11, 12, 13, 33]:
ab, msrc, mrec = utils.check_ab(ab_inp, 0)
_, htarg = utils.check_hankel(htype, {}, 0)
xdirect = False # Important, as we want to compare wavenr-frequency!
rec = [np.arange(1, 11) * 500, np.zeros(10), 300]
rec, nrec = utils.check_dipole(rec, 'rec', 0)
off, angle = utils.get_off_ang(src, rec, nsrc, nrec, 0)
ang_fact = kernel.angle_factor(angle, ab, msrc, mrec)
lsrc, zsrc = utils.get_layer_nr(src, depth)
lrec, zrec = utils.get_layer_nr(rec, depth)
# # # 0. No Spline # # #
if htype != 'quad': # quad is always using spline
# Wavenumber solution plus transform
# Adjust htarg for dlf
if htype == 'dlf':
lambd, int_pts = transform.get_dlf_points(
htarg['dlf'], off, htarg['pts_per_dec'])
htarg['lambd'] = lambd
htarg['int_pts'] = int_pts
wvnr0, _, conv = calc(zsrc, zrec, lsrc, lrec, off, ang_fact, depth,
ab, etaH, etaV, zetaH, zetaV, xdirect, htarg,
msrc, mrec)
# Analytical frequency-domain solution
freq0 = kernel.fullspace(off, angle, zsrc, zrec, etaH, etaV, zetaH,
zetaV, ab, msrc, mrec)
# Compare
assert_allclose(conv, True)
assert_allclose(np.squeeze(wvnr0), np.squeeze(freq0))
# # # 1. Spline; One angle # # #
_, htarg = utils.check_hankel(htype, {'pts_per_dec': 80}, 0)
if htype == 'quad': # Lower atol to ensure convergence
_, htarg = utils.check_hankel('quad', {'rtol': 1e-8}, 0)
elif htype == 'dlf': # Adjust htarg for dlf
lambd, int_pts = transform.get_dlf_points(htarg['dlf'], off,
htarg['pts_per_dec'])
htarg['lambd'] = lambd
htarg['int_pts'] = int_pts
# Wavenumber solution plus transform
wvnr1, _, conv = calc(zsrc, zrec, lsrc, lrec, off, ang_fact, depth, ab,
etaH, etaV, zetaH, zetaV, xdirect, htarg, msrc,
mrec)
# Analytical frequency-domain solution
freq1 = kernel.fullspace(off, angle, zsrc, zrec, etaH, etaV, zetaH,
zetaV, ab, msrc, mrec)
# Compare
if htype == 'qwe' and ab in [13, 33]:
assert_allclose(conv, False)
else:
assert_allclose(conv, True)
assert_allclose(np.squeeze(wvnr1), np.squeeze(freq1), rtol=1e-4)
# # # 2. Spline; Multi angle # # #
rec = [np.arange(1, 11) * 500, np.arange(-5, 5) * 200, 300]
rec, nrec = utils.check_dipole(rec, 'rec', 0)
off, angle = utils.get_off_ang(src, rec, nsrc, nrec, 0)
ang_fact = kernel.angle_factor(angle, ab, msrc, mrec)
if htype == 'qwe': # Put a very low diff_quad, to test it.; lower err
_, htarg = utils.check_hankel(
'qwe', {
'rtol': 1e-8,
'maxint': 200,
'pts_per_dec': 80,
'diff_quad': .1,
'a': 1e-6,
'b': .1,
'limit': 1000
}, 0)
elif htype == 'dlf': # Adjust htarg for dlf
lambd, int_pts = transform.get_dlf_points(htarg['dlf'], off,
htarg['pts_per_dec'])
htarg['lambd'] = lambd
htarg['int_pts'] = int_pts
# Analytical frequency-domain solution
wvnr2, _, conv = calc(zsrc, zrec, lsrc, lrec, off, ang_fact, depth, ab,
etaH, etaV, zetaH, zetaV, xdirect, htarg, msrc,
mrec)
# Analytical frequency-domain solution
freq2 = kernel.fullspace(off, angle, zsrc, zrec, etaH, etaV, zetaH,
zetaV, ab, msrc, mrec)
# Compare
assert_allclose(conv, True)
assert_allclose(np.squeeze(wvnr2), np.squeeze(freq2), rtol=1e-4)
# # # 3. Spline; pts_per_dec # # #
if htype == 'dlf':
_, htarg = utils.check_hankel('dlf', {
'dlf': 'key_201_2012',
'pts_per_dec': 20
}, 0)
lambd, int_pts = transform.get_dlf_points(htarg['dlf'], off,
htarg['pts_per_dec'])
htarg['lambd'] = lambd
htarg['int_pts'] = int_pts
elif htype == 'qwe':
_, htarg = utils.check_hankel('qwe', {
'maxint': 80,
'pts_per_dec': 100
}, 0)
if htype != 'quad': # quad is always pts_per_dec
# Analytical frequency-domain solution
wvnr3, _, conv = calc(zsrc, zrec, lsrc, lrec, off, ang_fact, depth,
ab, etaH, etaV, zetaH, zetaV, xdirect, htarg,
msrc, mrec)
# Analytical frequency-domain solution
freq3 = kernel.fullspace(off, angle, zsrc, zrec, etaH, etaV, zetaH,
zetaV, ab, msrc, mrec)
# Compare
assert_allclose(conv, True)
assert_allclose(np.squeeze(wvnr3), np.squeeze(freq3), rtol=1e-4)
# # # 4. Spline; Only one offset # # #
rec = [5000, 0, 300]
rec, nrec = utils.check_dipole(rec, 'rec', 0)
off, angle = utils.get_off_ang(src, rec, nsrc, nrec, 0)
ang_fact = kernel.angle_factor(angle, ab, msrc, mrec)
if htype == 'qwe':
_, htarg = utils.check_hankel('qwe', {
'maxint': 200,
'pts_per_dec': 80
}, 0)
elif htype == 'quad':
_, htarg = utils.check_hankel('quad', {}, 0)
elif htype == 'dlf':
lambd, int_pts = transform.get_dlf_points(htarg['dlf'], off,
htarg['pts_per_dec'])
htarg['lambd'] = lambd
htarg['int_pts'] = int_pts
# Analytical frequency-domain solution
wvnr4, _, conv = calc(zsrc, zrec, lsrc, lrec, off, ang_fact, depth, ab,
etaH, etaV, zetaH, zetaV, xdirect, htarg, msrc,
mrec)
# Analytical frequency-domain solution
freq4 = kernel.fullspace(off, angle, zsrc, zrec, etaH, etaV, zetaH,
zetaV, ab, msrc, mrec)
# Compare
assert_allclose(conv, True)
assert_allclose(np.squeeze(wvnr4), np.squeeze(freq4), rtol=1e-4)
def test_dlf(): # 10. dlf
# DLF is integral of hankel_dlf and fourier_dlf, and therefore tested a lot
# through those. Here we just ensure status quo. And if a problem arises in
# hankel_dlf or fourier_dlf, it would make it obvious if the problem arises
# from dlf or not.
# Check DLF for Fourier
t = DATA['t'][()]
for i in [0, 1, 2]:
dat = DATA['fourier_dlf' + str(i)][()]
tres = DATA['tEM' + str(i)][()]
finp = dat['fEM']
ftarg = dat['ftarg']
if i > 0:
finp /= 2j * np.pi * dat['f']
if i > 1:
finp *= -1
if ftarg['pts_per_dec'] == 0:
finp = finp.reshape(t.size, -1)
tEM = transform.dlf(finp,
2 * np.pi * dat['f'],
t,
ftarg['dlf'],
ftarg['pts_per_dec'],
kind=ftarg['kind'])
assert_allclose(tEM * 2 / np.pi, tres, rtol=1e-3)
# Check DLF for Hankel
for ab in [12, 22, 13, 33]:
model = utils.check_model([], 10, 2, 2, 5, 1, 10, True, 0)
depth, res, aniso, epermH, epermV, mpermH, mpermV, _ = model
frequency = utils.check_frequency(1, res, aniso, epermH, epermV,
mpermH, mpermV, 0)
_, etaH, etaV, zetaH, zetaV = frequency
src = [0, 0, 0]
src, nsrc = utils.check_dipole(src, 'src', 0)
ab, msrc, mrec = utils.check_ab(ab, 0)
ht, htarg = utils.check_hankel('dlf', {}, 0)
xdirect = False # Important, as we want to comp. wavenumber-frequency!
rec = [np.arange(1, 11) * 500, np.zeros(10), 300]
rec, nrec = utils.check_dipole(rec, 'rec', 0)
off, angle = utils.get_off_ang(src, rec, nsrc, nrec, 0)
lsrc, zsrc = utils.get_layer_nr(src, depth)
lrec, zrec = utils.get_layer_nr(rec, depth)
dlf = htarg['dlf']
pts_per_dec = htarg['pts_per_dec']
# # # 0. No Spline # # #
# dlf calculation
lambd = dlf.base / off[:, None]
PJ = kernel.wavenumber(zsrc, zrec, lsrc, lrec, depth, etaH, etaV,
zetaH, zetaV, lambd, ab, xdirect, msrc, mrec)
# Angle factor, one example with None instead of 1's.
if ab != 13:
ang_fact = kernel.angle_factor(angle, ab, msrc, mrec)
else:
ang_fact = None
# dlf calculation
fEM0 = transform.dlf(PJ, lambd, off, dlf, 0, ang_fact=ang_fact, ab=ab)
# Analytical frequency-domain solution
freq1 = kernel.fullspace(off, angle, zsrc, zrec, etaH, etaV, zetaH,
zetaV, ab, msrc, mrec)
# Compare
assert_allclose(np.squeeze(fEM0), np.squeeze(freq1))
# # # 1. Spline; One angle # # #
# dlf calculation
lambd, _ = transform.get_dlf_points(dlf, off, pts_per_dec)
PJ1 = kernel.wavenumber(zsrc, zrec, lsrc, lrec, depth, etaH, etaV,
zetaH, zetaV, lambd, ab, xdirect, msrc, mrec)
# dlf calculation
fEM1 = transform.dlf(PJ1,
lambd,
off,
dlf,
pts_per_dec,
ang_fact=ang_fact,
ab=ab)
# Compare
assert_allclose(np.squeeze(fEM1), np.squeeze(freq1), rtol=1e-4)
# # # 2.a Lagged; One angle # # #
rec = [np.arange(1, 11) * 500, np.arange(-5, 5) * 0, 300]
rec, nrec = utils.check_dipole(rec, 'rec', 0)
off, angle = utils.get_off_ang(src, rec, nsrc, nrec, 0)
# dlf calculation
lambd, _ = transform.get_dlf_points(dlf, off, -1)
PJ2 = kernel.wavenumber(zsrc, zrec, lsrc, lrec, depth, etaH, etaV,
zetaH, zetaV, lambd, ab, xdirect, msrc, mrec)
ang_fact = kernel.angle_factor(angle, ab, msrc, mrec)
# dlf calculation
fEM2 = transform.dlf(PJ2,
lambd,
off,
dlf,
-1,
ang_fact=ang_fact,
ab=ab)
# Analytical frequency-domain solution
freq2 = kernel.fullspace(off, angle, zsrc, zrec, etaH, etaV, zetaH,
zetaV, ab, msrc, mrec)
# Compare
assert_allclose(np.squeeze(fEM2), np.squeeze(freq2), rtol=1e-4)
# # # 2.b Lagged; Multi angle # # #
rec = [np.arange(1, 11) * 500, np.arange(-5, 5) * 200, 300]
rec, nrec = utils.check_dipole(rec, 'rec', 0)
off, angle = utils.get_off_ang(src, rec, nsrc, nrec, 0)
# dlf calculation
lambd, _ = transform.get_dlf_points(dlf, off, -1)
PJ2 = kernel.wavenumber(zsrc, zrec, lsrc, lrec, depth, etaH, etaV,
zetaH, zetaV, lambd, ab, xdirect, msrc, mrec)
ang_fact = kernel.angle_factor(angle, ab, msrc, mrec)
# dlf calculation
fEM2 = transform.dlf(PJ2,
lambd,
off,
dlf,
-1,
ang_fact=ang_fact,
ab=ab)
# Analytical frequency-domain solution
freq2 = kernel.fullspace(off, angle, zsrc, zrec, etaH, etaV, zetaH,
zetaV, ab, msrc, mrec)
# Compare
assert_allclose(np.squeeze(fEM2), np.squeeze(freq2), rtol=1e-4)
# # # 3. Spline; Multi angle # # #
lambd, _ = transform.get_dlf_points(dlf, off, 30)
# dlf calculation
PJ3 = kernel.wavenumber(zsrc, zrec, lsrc, lrec, depth, etaH, etaV,
zetaH, zetaV, lambd, ab, xdirect, msrc, mrec)
# dlf calculation
fEM3 = transform.dlf(PJ3,
lambd,
off,
dlf,
30,
ang_fact=ang_fact,
ab=ab)
# Compare
assert_allclose(np.squeeze(fEM3), np.squeeze(freq2), rtol=1e-3)
def test_hankel(htype): # 1. fht / 2. hqwe / 3. hquad
# Compare wavenumber-domain calculation / FHT with analytical
# frequency-domain fullspace solution
calc = getattr(transform, htype)
model = utils.check_model([], 10, 2, 2, 5, 1, 10, True, 0)
depth, res, aniso, epermH, epermV, mpermH, mpermV, _ = model
frequency = utils.check_frequency(1, res, aniso, epermH, epermV, mpermH,
mpermV, 0)
_, etaH, etaV, zetaH, zetaV = frequency
src = [0, 0, 0]
src, nsrc = utils.check_dipole(src, 'src', 0)
for ab_inp in [11, 12, 13, 33]:
ab, msrc, mrec = utils.check_ab(ab_inp, 0)
_, htarg = utils.check_hankel(htype, None, 0)
xdirect = False # Important, as we want to compare wavenr-frequency!
rec = [np.arange(1, 11)*500, np.zeros(10), 300]
rec, nrec = utils.check_dipole(rec, 'rec', 0)
off, angle = utils.get_off_ang(src, rec, nsrc, nrec, 0)
factAng = kernel.angle_factor(angle, ab, msrc, mrec)
lsrc, zsrc = utils.get_layer_nr(src, depth)
lrec, zrec = utils.get_layer_nr(rec, depth)
# # # 0. No Spline # # #
if htype != 'hquad': # hquad is always using spline
# Wavenumber solution plus transform
# Adjust htarg for fht
if htype == 'fht':
lambd, int_pts = transform.get_spline_values(htarg[0], off,
htarg[1])
htarg = (htarg[0], htarg[1], lambd, int_pts)
wvnr0, _, conv = calc(zsrc, zrec, lsrc, lrec, off, factAng, depth,
ab, etaH, etaV, zetaH, zetaV, xdirect, htarg,
False, msrc, mrec)
# Analytical frequency-domain solution
freq0 = kernel.fullspace(off, angle, zsrc, zrec, etaH, etaV, zetaH,
zetaV, ab, msrc, mrec)
# Compare
assert_allclose(conv, True)
assert_allclose(np.squeeze(wvnr0), np.squeeze(freq0))
# # # 1. Spline; One angle # # #
htarg, _ = utils.spline_backwards_hankel(htype, None, 'spline')
_, htarg = utils.check_hankel(htype, htarg, 0)
if htype == 'hquad': # Lower atol to ensure convergence
_, htarg = utils.check_hankel('quad', [1e-8], 0)
elif htype == 'fht': # Adjust htarg for fht
lambd, int_pts = transform.get_spline_values(htarg[0], off,
htarg[1])
htarg = (htarg[0], htarg[1], lambd, int_pts)
# Wavenumber solution plus transform
wvnr1, _, conv = calc(zsrc, zrec, lsrc, lrec, off, factAng, depth, ab,
etaH, etaV, zetaH, zetaV, xdirect, htarg, False,
msrc, mrec)
# Analytical frequency-domain solution
freq1 = kernel.fullspace(off, angle, zsrc, zrec, etaH, etaV, zetaH,
zetaV, ab, msrc, mrec)
# Compare
if htype == 'hqwe' and ab in [13, 33]:
assert_allclose(conv, False)
else:
assert_allclose(conv, True)
assert_allclose(np.squeeze(wvnr1), np.squeeze(freq1), rtol=1e-4)
# # # 2. Spline; Multi angle # # #
rec = [np.arange(1, 11)*500, np.arange(-5, 5)*200, 300]
rec, nrec = utils.check_dipole(rec, 'rec', 0)
off, angle = utils.get_off_ang(src, rec, nsrc, nrec, 0)
factAng = kernel.angle_factor(angle, ab, msrc, mrec)
if htype == 'hqwe': # Put a very low diff_quad, to test it.; lower err
_, htarg = utils.check_hankel('qwe', [1e-8, '', '', 200, 80, .1,
1e-6, .1, 1000], 0)
elif htype == 'fht': # Adjust htarg for fht
lambd, int_pts = transform.get_spline_values(htarg[0], off,
htarg[1])
htarg = (htarg[0], htarg[1], lambd, int_pts)
# Analytical frequency-domain solution
wvnr2, _, conv = calc(zsrc, zrec, lsrc, lrec, off, factAng, depth, ab,
etaH, etaV, zetaH, zetaV, xdirect, htarg, False,
msrc, mrec)
# Analytical frequency-domain solution
freq2 = kernel.fullspace(off, angle, zsrc, zrec, etaH, etaV, zetaH,
zetaV, ab, msrc, mrec)
# Compare
assert_allclose(conv, True)
assert_allclose(np.squeeze(wvnr2), np.squeeze(freq2), rtol=1e-4)
# # # 3. Spline; pts_per_dec # # #
if htype == 'fht':
_, htarg = utils.check_hankel('fht', ['key_201_2012', 20], 0)
lambd, int_pts = transform.get_spline_values(htarg[0], off,
htarg[1])
htarg = (htarg[0], htarg[1], lambd, int_pts)
elif htype == 'hqwe':
_, htarg = utils.check_hankel('qwe', ['', '', '', 80, 100], 0)
if htype != 'hquad': # hquad is always pts_per_dec
# Analytical frequency-domain solution
wvnr3, _, conv = calc(zsrc, zrec, lsrc, lrec, off, factAng, depth,
ab, etaH, etaV, zetaH, zetaV, xdirect, htarg,
False, msrc, mrec)
# Analytical frequency-domain solution
freq3 = kernel.fullspace(off, angle, zsrc, zrec, etaH, etaV, zetaH,
zetaV, ab, msrc, mrec)
# Compare
assert_allclose(conv, True)
assert_allclose(np.squeeze(wvnr3), np.squeeze(freq3), rtol=1e-4)
# # # 4. Spline; Only one offset # # #
rec = [5000, 0, 300]
rec, nrec = utils.check_dipole(rec, 'rec', 0)
off, angle = utils.get_off_ang(src, rec, nsrc, nrec, 0)
factAng = kernel.angle_factor(angle, ab, msrc, mrec)
if htype == 'hqwe':
_, htarg = utils.check_hankel('qwe', ['', '', '', 200, 80], 0)
elif htype == 'hquad':
_, htarg = utils.check_hankel('quad', None, 0)
elif htype == 'fht':
lambd, int_pts = transform.get_spline_values(htarg[0], off,
htarg[1])
htarg = (htarg[0], htarg[1], lambd, int_pts)
# Analytical frequency-domain solution
wvnr4, _, conv = calc(zsrc, zrec, lsrc, lrec, off, factAng, depth, ab,
etaH, etaV, zetaH, zetaV, xdirect, htarg, False,
msrc, mrec)
# Analytical frequency-domain solution
freq4 = kernel.fullspace(off, angle, zsrc, zrec, etaH, etaV, zetaH,
zetaV, ab, msrc, mrec)
# Compare
assert_allclose(conv, True)
assert_allclose(np.squeeze(wvnr4), np.squeeze(freq4), rtol=1e-4)
def test_dlf(): # 10. dlf
# DLF is integral of fht and ffht, and therefore tested a lot through
# those. Here we just ensure status quo. And if a problem arises in fht or
# ffht, it would make it obvious if the problem arises from dlf or not.
# Check DLF for Fourier
t = DATA['t'][()]
for i in [0, 1, 2]:
dat = DATA['ffht' + str(i)][()]
tres = DATA['tEM' + str(i)][()]
finp = dat['fEM']
ftarg = dat['ftarg']
if i > 0:
finp /= 2j * np.pi * dat['f']
if i > 1:
finp *= -1
if ftarg[1] == 0:
finp = finp.reshape(t.size, -1)
tEM = transform.dlf(finp,
2 * np.pi * dat['f'],
t,
ftarg[0],
ftarg[1],
kind=ftarg[2])
assert_allclose(tEM * 2 / np.pi, tres, rtol=1e-3)
# Check DLF for Hankel
for ab in [12, 22, 13, 33]:
model = utils.check_model([], 10, 2, 2, 5, 1, 10, True, 0)
depth, res, aniso, epermH, epermV, mpermH, mpermV, isfullspace = model
frequency = utils.check_frequency(1, res, aniso, epermH, epermV,
mpermH, mpermV, 0)
freq, etaH, etaV, zetaH, zetaV = frequency
src = [0, 0, 0]
src, nsrc = utils.check_dipole(src, 'src', 0)
ab, msrc, mrec = utils.check_ab(ab, 0)
ht, htarg = utils.check_hankel('fht', None, 0)
options = utils.check_opt(None, None, ht, htarg, 0)
use_ne_eval, loop_freq, loop_off = options
xdirect = False # Important, as we want to comp. wavenumber-frequency!
rec = [np.arange(1, 11) * 500, np.zeros(10), 300]
rec, nrec = utils.check_dipole(rec, 'rec', 0)
off, angle = utils.get_off_ang(src, rec, nsrc, nrec, 0)
lsrc, zsrc = utils.get_layer_nr(src, depth)
lrec, zrec = utils.get_layer_nr(rec, depth)
fhtfilt = htarg[0]
pts_per_dec = htarg[1]
# # # 0. No Spline # # #
# fht calculation
lambd = fhtfilt.base / off[:, None]
PJ = kernel.wavenumber(zsrc, zrec, lsrc, lrec, depth, etaH, etaV,
zetaH, zetaV, lambd, ab, xdirect, msrc, mrec,
use_ne_eval)
factAng = kernel.angle_factor(angle, ab, msrc, mrec)
# dlf calculation
fEM0 = transform.dlf(PJ,
lambd,
off,
fhtfilt,
0,
factAng=factAng,
ab=ab)
# Analytical frequency-domain solution
freq1 = kernel.fullspace(off, angle, zsrc, zrec, etaH, etaV, zetaH,
zetaV, ab, msrc, mrec)
# Compare
assert_allclose(np.squeeze(fEM0), np.squeeze(freq1))
# # # 1. Spline; One angle # # #
options = utils.check_opt('spline', None, ht, htarg, 0)
use_ne_eval, loop_freq, loop_off = options
# fht calculation
lambd, _ = transform.get_spline_values(fhtfilt, off, pts_per_dec)
PJ1 = kernel.wavenumber(zsrc, zrec, lsrc, lrec, depth, etaH, etaV,
zetaH, zetaV, lambd, ab, xdirect, msrc, mrec,
use_ne_eval)
# dlf calculation
fEM1 = transform.dlf(PJ1,
lambd,
off,
fhtfilt,
pts_per_dec,
factAng=factAng,
ab=ab)
# Compare
assert_allclose(np.squeeze(fEM1), np.squeeze(freq1), rtol=1e-4)
# # # 2.a Lagged; One angle # # #
rec = [np.arange(1, 11) * 500, np.arange(-5, 5) * 0, 300]
rec, nrec = utils.check_dipole(rec, 'rec', 0)
off, angle = utils.get_off_ang(src, rec, nsrc, nrec, 0)
# fht calculation
lambd, _ = transform.get_spline_values(fhtfilt, off, -1)
PJ2 = kernel.wavenumber(zsrc, zrec, lsrc, lrec, depth, etaH, etaV,
zetaH, zetaV, lambd, ab, xdirect, msrc, mrec,
use_ne_eval)
factAng = kernel.angle_factor(angle, ab, msrc, mrec)
# dlf calculation
fEM2 = transform.dlf(PJ2,
lambd,
off,
fhtfilt,
-1,
factAng=factAng,
ab=ab)
# Analytical frequency-domain solution
freq2 = kernel.fullspace(off, angle, zsrc, zrec, etaH, etaV, zetaH,
zetaV, ab, msrc, mrec)
# Compare
assert_allclose(np.squeeze(fEM2), np.squeeze(freq2), rtol=1e-4)
# # # 2.b Lagged; Multi angle # # #
rec = [np.arange(1, 11) * 500, np.arange(-5, 5) * 200, 300]
rec, nrec = utils.check_dipole(rec, 'rec', 0)
off, angle = utils.get_off_ang(src, rec, nsrc, nrec, 0)
# fht calculation
lambd, _ = transform.get_spline_values(fhtfilt, off, -1)
PJ2 = kernel.wavenumber(zsrc, zrec, lsrc, lrec, depth, etaH, etaV,
zetaH, zetaV, lambd, ab, xdirect, msrc, mrec,
use_ne_eval)
factAng = kernel.angle_factor(angle, ab, msrc, mrec)
# dlf calculation
fEM2 = transform.dlf(PJ2,
lambd,
off,
fhtfilt,
-1,
factAng=factAng,
ab=ab)
# Analytical frequency-domain solution
freq2 = kernel.fullspace(off, angle, zsrc, zrec, etaH, etaV, zetaH,
zetaV, ab, msrc, mrec)
# Compare
assert_allclose(np.squeeze(fEM2), np.squeeze(freq2), rtol=1e-4)
# # # 3. Spline; Multi angle # # #
lambd, _ = transform.get_spline_values(fhtfilt, off, 10)
# fht calculation
PJ3 = kernel.wavenumber(zsrc, zrec, lsrc, lrec, depth, etaH, etaV,
zetaH, zetaV, lambd, ab, xdirect, msrc, mrec,
use_ne_eval)
# dlf calculation
fEM3 = transform.dlf(PJ3,
lambd,
off,
fhtfilt,
10,
factAng=factAng,
ab=ab)
# Compare
assert_allclose(np.squeeze(fEM3), np.squeeze(freq2), rtol=1e-3)
if ab % 10 > 3:
msrc = True
else:
msrc = False
if mrec:
msrc = not msrc
iab[i] = (msrc, mrec, ab)
i += 1
# # A -- ANGLE # #
angres = []
angle = np.array([1., 2., 4., 5.])
for key, val in iab.items():
inp = {'angle': angle, 'ab': val[2], 'msrc': val[0], 'mrec': val[1]}
res = kernel.angle_factor(angle, val[2], val[0], val[1])
angres.append({'inp': inp, 'res': res})
# # B -- WAVENUMBER # #
# Example: 6-layer model; source in second layer, receiver in last
freq = np.array([0.003, 2.5, 1e6])
res = np.array([3, .3, 10, 4, 3, 1])
aniso = np.array([1, .5, 3, 1, 2, 1])
epermH = np.array([80, 100, 3, 8, 1, 1])
epermV = np.array([100, 30, 1, 10, 68, 9])
mpermH = np.array([.5, 100, 30, 1, 30, 1])
mpermV = np.array([2, 1, 30, 9, 50, 1])
etaH = 1/res + np.outer(2j*np.pi*freq, epermH*epsilon_0)
etaV = 1/(res*aniso*aniso) + np.outer(2j*np.pi*freq, epermV*epsilon_0)
zetaH = np.outer(2j*np.pi*freq, mpermH*mu_0)
b_zero = np.pi * np.arange(1.25, maxint + 1)
for i in range(10):
b_x0 = special.j1(b_zero)
b_x1 = special.jv(2, b_zero)
b_h = -b_x0 / (b_x0 / b_zero - b_x1)
b_zero += b_h
if all(np.abs(b_h) < 8 * np.finfo(float).eps * b_zero):
break
xint = np.concatenate((np.array([1e-20]), b_zero))
dx = np.repeat(np.diff(xint) / 2, nquad)
Bx = dx * (np.tile(g_x, maxint) + 1) + np.repeat(xint[:-1], nquad)
BJ0 = special.j0(Bx) * np.tile(g_w, maxint)
BJ1 = special.j1(Bx) * np.tile(g_w, maxint)
intervals = xint / off[:, None]
lambd = Bx / off[:, None]
ang_fact = kernel.angle_factor(angle, ab, msrc, mrec)
# 1 Spline version
start = np.log(lambd.min())
stop = np.log(lambd.max())
ilambd = np.logspace(start,
stop,
int((stop - start) * pts_per_dec + 1),
base=10.0)
PJ0, PJ1, PJ0b = kernel.wavenumber(zsrc, zrec, lsrc, lrec, depth,
etaH[None, :], etaV[None, :],
zetaH[None, :], zetaV[None, :],
np.atleast_2d(ilambd), ab, False, msrc,
mrec)
si_PJ0r = iuSpline(np.log(ilambd), PJ0.real)
si_PJ0i = iuSpline(np.log(ilambd), PJ0.imag)
si_PJ1r = iuSpline(np.log(ilambd), PJ1.real)
continue
if ab % 10 > 3:
msrc = True
else:
msrc = False
if mrec:
msrc = not msrc
iab[ab] = (msrc, mrec)
# # A -- ANGLE # #
angres = []
angle = np.array([1., 2., 4., 5.])
for key, val in iab.items():
inp = {'angle': angle, 'ab': key, 'msrc': val[0], 'mrec': val[1]}
res = kernel.angle_factor(angle, key, val[0], val[1])
angres.append({'inp': inp, 'res': res})
# # B -- WAVENUMBER # #
# Example: 6-layer model; source in second layer, receiver in last
freq = np.array([0.003, 2.5, 1e6])
res = np.array([3, .3, 10, 4, 3, 1])
aniso = np.array([1, .5, 3, 1, 2, 1])
epermH = np.array([80, 100, 3, 8, 1, 1])
epermV = np.array([100, 30, 1, 10, 68, 9])
mpermH = np.array([.5, 100, 30, 1, 30, 1])
mpermV = np.array([2, 1, 30, 9, 50, 1])
etaH = 1 / res + np.outer(2j * np.pi * freq, epermH * epsilon_0)
etaV = 1 / (res * aniso * aniso) + np.outer(2j * np.pi * freq,
epermV * epsilon_0)
def setup(self, size):
# One big, one small model
if size == 'Small': # Total size: 5*1*1*1 = 5
off = np.array([500., 1000.])
else: # Total size: 5*100*1*201 = 100'500
off = np.arange(1, 101)*200.
# Define survey
freq = np.array([1])
lsrc = 1
lrec = 1
angle = np.zeros(off.shape)
ab = 11
msrc = False
mrec = False
if VERSION2:
zsrc = 250.
zrec = 300.
else:
zsrc = np.array([250.]) # Not sure if this distinction
zrec = np.array([300.]) # is actually needed
use_ne_eval = False
# Define model
depth = np.array([-np.infty, 0, 300, 2000, 2100])
res = np.array([2e14, .3, 1, 50, 1])
aniso = np.ones(res.shape)
epermH = np.ones(res.shape)
epermV = np.ones(res.shape)
mpermH = np.ones(res.shape)
mpermV = np.ones(res.shape)
# Other parameters
xdirect = False
verb = 0
# Compute eta, zeta
etaH = 1/res + np.outer(2j*np.pi*freq, epermH*epsilon_0)
etaV = 1/(res*aniso*aniso) + np.outer(2j*np.pi*freq, epermV*epsilon_0)
zetaH = np.outer(2j*np.pi*freq, mpermH*mu_0)
zetaV = np.outer(2j*np.pi*freq, mpermV*mu_0)
# Collect input
self.hankel = {'zsrc': zsrc, 'zrec': zrec, 'lsrc': lsrc, 'lrec': lrec,
'off': off, 'depth': depth, 'ab': ab, 'etaH': etaH,
'etaV': etaV, 'zetaH': zetaH, 'zetaV': zetaV, 'xdirect':
xdirect, 'msrc': msrc, 'mrec': mrec}
if not VERSION2:
self.hankel['use_ne_eval'] = use_ne_eval
# Before c73d6647; you had to give `ab` to `check_hankel`;
# check_opt didn't exist then.
if VERSION2:
charg = (verb, )
new_version = True
else:
try:
opt = utils.check_opt(None, None, 'fht', ['', 0], verb)
charg = (verb, )
if np.size(opt) == 4:
new_version = False
else:
new_version = True
except VariableCatch:
new_version = False
charg = (ab, verb)
# From 9bed72b0 onwards, there is no `use_spline`; `htarg` input
# changed (29/04/2018; before v1.4.1).
if new_version:
if VERSION2:
htarg = {'dlf': 'key_201_2009', 'pts_per_dec': -1}
else:
htarg = ['key_201_2009', -1]
else:
htarg = ['key_201_2009', None]
# HT arguments
if VERSION2:
dlfargname = 'htarg'
qweargname = 'htarg'
quadargname = 'htarg'
htarg1 = {'dlf': 'key_201_2009', 'pts_per_dec': 0}
htarg2 = {'dlf': 'key_201_2009', 'pts_per_dec': 10}
name = 'dlf'
else:
dlfargname = 'fhtarg'
qweargname = 'qweargs'
quadargname = 'quadargs'
htarg1 = ['key_201_2009', 0]
htarg2 = ['key_201_2009', 10]
name = 'fht'
_, fhtarg_st = utils.check_hankel(name, htarg1, *charg)
self.fhtarg_st = {dlfargname: fhtarg_st}
_, fhtarg_sp = utils.check_hankel(name, htarg2, *charg)
self.fhtarg_sp = {dlfargname: fhtarg_sp}
_, fhtarg_la = utils.check_hankel(name, htarg, *charg)
self.fhtarg_la = {dlfargname: fhtarg_la}
# QWE: We lower the requirements here, otherwise it takes too long
# ['rtol', 'atol', 'nquad', 'maxint', 'pts_per_dec', 'diff_quad', 'a',
# 'b', 'limit']
# Args depend if QUAD included into QWE or not
try:
if VERSION2:
args_sp = {'atol': 1e-6, 'rtol': 1e-10, 'nquad': 51,
'maxint': 100, 'pts_per_dec': 10,
'diff_quad': np.inf}
args_st = {'atol': 1e-6, 'rtol': 1e-10, 'nquad': 51,
'maxint': 100, 'pts_per_dec': 0,
'diff_quad': np.inf}
else:
args_sp = [1e-6, 1e-10, 51, 100, 10, np.inf]
args_st = [1e-6, 1e-10, 51, 100, 0, np.inf]
_, qwearg_sp = utils.check_hankel('qwe', args_sp, *charg)
_, qwearg_st = utils.check_hankel('qwe', args_st, *charg)
except VariableCatch:
args_sp = [1e-6, 1e-10, 51, 100, 10]
args_st = [1e-6, 1e-10, 51, 100, 0]
_, qwearg_sp = utils.check_hankel('qwe', args_sp, *charg)
_, qwearg_st = utils.check_hankel('qwe', args_st, *charg)
self.qwearg_st = {qweargname: qwearg_st}
self.qwearg_sp = {qweargname: qwearg_sp}
# QUAD: We lower the requirements here, otherwise it takes too long
# ['rtol', 'atol', 'limit', 'a', 'b', 'pts_per_dec']
if VERSION2:
args = {'atol': 1e-6, 'rtol': 1e-10, 'limit': 100, 'a': 1e-6,
'b': 0.1, 'pts_per_dec': 10}
else:
args = [1e-6, 1e-10, 100, 1e-6, 0.1, 10]
try: # QUAD only included since 6104614e (before v1.3.0)
_, quadargs = utils.check_hankel('quad', args, *charg)
self.quadargs = {quadargname: quadargs}
except VariableCatch:
self.quadargs = {}
if not new_version and not VERSION2:
self.fhtarg_la.update({'use_spline': True})
self.fhtarg_sp.update({'use_spline': True})
self.fhtarg_st.update({'use_spline': False})
self.qwearg_sp.update({'use_spline': True})
self.qwearg_st.update({'use_spline': False})
self.quadargs.update({'use_spline': True})
if VERSION2:
self.hankel['ang_fact'] = kernel.angle_factor(
angle, ab, msrc, mrec)
else:
# From bb6447a onwards ht-transforms take `factAng`, not `angle`,
# to avoid re-calculation in loops.
try:
transform.fht(angle=angle, **self.fhtarg_la, **self.hankel)
self.hankel['angle'] = angle
except VariableCatch:
self.hankel['factAng'] = kernel.angle_factor(
angle, ab, msrc, mrec)
if not VERSION2:
# From b6f6872 onwards fht-transforms calculates lambd/int_pts in
# model.fem, not in transform.fht, to avoid re-calculation in
# loops.
try:
transform.fht(**self.fhtarg_la, **self.hankel)
except VariableCatch:
lambd, int_pts = transform.get_spline_values(
fhtarg_st[0], off, fhtarg_st[1])
self.fhtarg_st.update({'fhtarg': (
fhtarg_st[0], fhtarg_st[1], lambd, int_pts)})
lambd, int_pts = transform.get_spline_values(
fhtarg_la[0], off, fhtarg_la[1])
self.fhtarg_la.update(
{'fhtarg':
(fhtarg_la[0], fhtarg_la[1], lambd, int_pts)})
lambd, int_pts = transform.get_spline_values(
fhtarg_sp[0], off, fhtarg_sp[1])
self.fhtarg_sp.update(
{'fhtarg':
(fhtarg_sp[0], fhtarg_sp[1], lambd, int_pts)})
def setup_cache(self):
"""setup_cache is not parametrized, so we do it manually. """
data = {}
for size in self.params[0]: # size
data[size] = {}
# One big, one small model
if size == 'Small': # Small; Total size: 5*1*1*1 = 5
x = np.array([500., 1000.])
else: # Big; Total size: 5*100*100*201 = 10'050'000
x = np.arange(1, 101)*200.
# Define model parameters
freq = np.array([1])
src = [0, 0, 250]
rec = [x, np.zeros(x.shape), 300]
depth = np.array([-np.infty, 0, 300, 2000, 2100])
res = np.array([2e14, .3, 1, 50, 1])
ab = 11
xdirect = False
verb = 0
if not VERSION2:
use_ne_eval = False
# Checks (since DLF exists the `utils`-checks haven't changed, so
# we just use them here.
model = utils.check_model(depth, res, None, None, None, None, None,
xdirect, verb)
depth, res, aniso, epermH, epermV, mpermH, mpermV, _ = model
frequency = utils.check_frequency(freq, res, aniso, epermH, epermV,
mpermH, mpermV, verb)
freq, etaH, etaV, zetaH, zetaV = frequency
ab, msrc, mrec = utils.check_ab(ab, verb)
src, nsrc = utils.check_dipole(src, 'src', verb)
rec, nrec = utils.check_dipole(rec, 'rec', verb)
off, angle = utils.get_off_ang(src, rec, nsrc, nrec, verb)
lsrc, zsrc = utils.get_layer_nr(src, depth)
lrec, zrec = utils.get_layer_nr(rec, depth)
for htype in self.params[1]: # htype
# pts_per_dec depending on htype
if htype == 'Standard':
pts_per_dec = 0
elif htype == 'Lagged':
pts_per_dec = -1
else:
pts_per_dec = 10
# Compute kernels for dlf
if VERSION2:
# HT arguments
_, fhtarg = utils.check_hankel(
'dlf',
{'dlf': 'key_201_2009',
'pts_per_dec': pts_per_dec},
0)
inp = (fhtarg['dlf'], off, fhtarg['pts_per_dec'])
lambd, _ = transform.get_dlf_points(*inp)
else:
# HT arguments
_, fhtarg = utils.check_hankel(
'fht', ['key_201_2009', pts_per_dec], 0)
inp = (fhtarg[0], off, fhtarg[1])
lambd, _ = transform.get_spline_values(*inp)
if VERSION2:
inp = (zsrc, zrec, lsrc, lrec, depth, etaH, etaV, zetaH,
zetaV, lambd, ab, xdirect, msrc, mrec)
else:
inp = (zsrc, zrec, lsrc, lrec, depth, etaH,
etaV, zetaH, zetaV, lambd, ab, xdirect,
msrc, mrec, use_ne_eval)
PJ = kernel.wavenumber(*inp)
factAng = kernel.angle_factor(angle, ab, msrc, mrec)
# Signature changed at commit a15af07 (20/05/2018; before
# v1.6.2)
try:
dlf = {'signal': PJ, 'points': lambd, 'out_pts': off,
'ab': ab}
if VERSION2:
dlf['ang_fact'] = factAng
dlf['filt'] = fhtarg['dlf']
dlf['pts_per_dec'] = fhtarg['pts_per_dec']
else:
dlf['factAng'] = factAng
dlf['filt'] = fhtarg[0]
dlf['pts_per_dec'] = fhtarg[1]
transform.dlf(**dlf)
except VariableCatch:
dlf = {'signal': PJ, 'points': lambd, 'out_pts': off,
'targ': fhtarg, 'factAng': factAng}
data[size][htype] = dlf
return data
