def _linrate_calc(ifg_paths, params, vcmt, tiles, preread_ifgs):
"""
MPI wrapper for linrate calculation
"""
process_tiles = mpiops.array_split(tiles)
log.info('Calculating linear rate map')
output_dir = params[cf.TMPDIR]
for t in process_tiles:
log.info('Calculating linear rate of tile {}'.format(t.index))
ifg_parts = [shared.IfgPart(p, t, preread_ifgs) for p in ifg_paths]
mst_grid_n = np.load(os.path.join(output_dir,
'mst_mat_{}.npy'.format(t.index)))
rate, error, samples = linrate.linear_rate(ifg_parts, params,
vcmt, mst_grid_n)
# declare file names
np.save(file=os.path.join(output_dir,
'linrate_{}.npy'.format(t.index)),
arr=rate)
np.save(file=os.path.join(output_dir,
'linerror_{}.npy'.format(t.index)),
arr=error)
np.save(file=os.path.join(output_dir,
'linsamples_{}.npy'.format(t.index)),
arr=samples)
mpiops.comm.barrier()
def linrate_calc(ifg_paths, params, vcmt, tiles, preread_ifgs):
"""
MPI capable linrate calculation.
:param ifg_paths: List of interferogram paths
:param params: Parameters dictionary corresponding to config file
:param vcmt: vcmt array
:param tiles: List of all tiles used during MPI processes
:param preread_ifgs: Dictionary containing interferogram characteristics for efficient computing
:return xxxx
"""
process_tiles = mpiops.array_split(tiles)
log.info('Calculating linear rate')
output_dir = params[cf.TMPDIR]
for t in process_tiles:
log.info('calculating lin rate of tile {}'.format(t.index))
ifg_parts = [shared.IfgPart(p, t, preread_ifgs) for p in ifg_paths]
mst_grid_n = np.load(
os.path.join(output_dir, 'mst_mat_{}.npy'.format(t.index)))
rate, error, samples = linrate.linear_rate(ifg_parts, params, vcmt,
mst_grid_n)
# declare file names
np.save(file=os.path.join(output_dir,
'linrate_{}.npy'.format(t.index)),
arr=rate)
np.save(file=os.path.join(output_dir,
'linerror_{}.npy'.format(t.index)),
arr=error)
np.save(file=os.path.join(output_dir,
'linsamples_{}.npy'.format(t.index)),
arr=samples)
mpiops.comm.barrier()
def calculate_linear_rate(ifgs, params, vcmt, mst_mat=None):
# log.info('Calculating linear rate')
res = linrate.linear_rate(ifgs, params, vcmt, mst_mat)
for r in res:
if r is None:
raise ValueError('TODO: bad value')
rate, error, samples = res
write_linrate_tifs(ifgs, params, res)
# log.info('Linear rate calculated')
return rate, error, samples
def test_linear_rate(self):
# Simple test with one pixel and equal weighting
exprate = array([[5.0]])
experr = array([[0.836242010007091]]) # from Matlab Pirate
expsamp = array([[5]])
vcmt = eye(6, 6)
mst = ones((6, 1, 1))
mst[4] = 0
params = default_params()
rate, error, samples = linear_rate(self.ifgs, params, vcmt, mst)
assert_array_almost_equal(rate, exprate)
assert_array_almost_equal(error, experr)
assert_array_almost_equal(samples, expsamp)