Commit 1b98ae46 authored by Philipp Frank's avatar Philipp Frank
Browse files

small fixes

parent 7a7617ba
Pipeline #91901 passed with stages
in 14 minutes and 29 seconds
......@@ -25,9 +25,9 @@ from time import time
import nifty6 as ift
import src as vlbi
from config import comm, nranks, rank, master
from config import doms, dt, eps, min_timestamps_per_bin, npixt, nthreads
from config import doms, eps, min_timestamps_per_bin, nthreads
from config import sky_movie_mf as sky
from config import startt, dt, npix
from config import startt, dt, npixt
def stat_plotting(pos, KL):
if master:
......@@ -79,8 +79,7 @@ def optimization_heuristic(ii, likelihoods):
lh = lh_full_ph
return minimizer, N_samples, N_iterations, lh
def build_likelihood(rawdd, startt, npix, dt, mode):
def build_likelihood(rawdd, startt, npixt, dt, mode):
lh = []
active_inds = []
for freq in
......@@ -103,13 +102,13 @@ def build_likelihood(rawdd, startt, npix, dt, mode):
vis2closph, evalsph, _ = vlbi.Visibilities2ClosurePhases(dd)
llh.append(ift.GaussianEnergy(mean=vis2closph(vis)) @ vis2closph)
llh_op = reduce(add, llh) @ nfft.ducktape(ind)
ift.extra.check_jacobian_consistency(llh_op, ift.from_random(llh_op.domain),
tol=1e-5, ntries=10)
if mode == 'full' and freq ==[0]:
ift.extra.check_jacobian_consistency(llh_op, ift.from_random(llh_op.domain),
tol=1e-5, ntries=10)
conv = vlbi.DomainTuple2MultiField(, active_inds)
lh= reduce(add, lh) @ conv
return lh
return reduce(add, lh) @ conv
def setup():
if len(sys.argv) != 3:
......@@ -124,13 +123,13 @@ def setup():
pre_output = pre_data
lh_full = build_likelihood(rawd, startt, npix, dt,'full')
lh_full_ph = build_likelihood(rawd, startt, npix, dt,'ph')
lh_full_amp = build_likelihood(rawd, startt, npix, dt,'amp')
lh_full = build_likelihood(rawd, startt, npixt, dt, 'full')
lh_full_ph = build_likelihood(rawd, startt, npixt, dt, 'ph')
lh_full_amp = build_likelihood(rawd, startt, npixt, dt, 'amp')
lh_cut = build_likelihood(rawd, startt, npix//2, dt,'full')
lh_cut_ph = build_likelihood(rawd, startt, npix//2, dt,'ph')
lh_cut_amp = build_likelihood(rawd, startt, npix//2, dt,'amp')
lh_cut = build_likelihood(rawd, startt, npixt//2, dt, 'full')
lh_cut_ph = build_likelihood(rawd, startt, npixt//2, dt, 'ph')
lh_cut_amp = build_likelihood(rawd, startt, npixt//2, dt, 'amp')
pos = vlbi.load_hdf5(fname_input, sky.domain) if master else None
if nranks > 1:
......@@ -151,7 +150,7 @@ def main():
with open("time_averaging.txt", 'w') as f:
# delete the file such that new lines can be appended
f.write("min max avg med\n")
pos, sky, ic, pre_output, likelihoods= setup()
pos, sky, ic, pre_output, likelihoods = setup()
for ii in range(60):
......@@ -159,7 +158,7 @@ def main():
if master:
print(f'Iter: {ii}, N_samples: {N_samples}, N_iter: {N_iterations}')
ll = lh @ sky
H = ift.StandardHamiltonian(ll, ic)
KL = ift.MetricGaussianKL(pos, H, N_samples, comm=comm, mirror_samples=True)
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