def read_baseline_info(baseline_file, reference_file):
"""Read date, bperp and/or DOP info
Parameters: baseline_file : str, path of bl_list.txt file
reference_file : str, path of ifgramStack.h5 file
Returns: date_list : list of str in YYMMDD format
tbase_list : list of int in days
pbase_list : list of float in meter
dop_list : None, list of 1D array in size of (3,)
"""
dop_list = None
if baseline_file:
date_list, pbase_list, dop_list = pnet.read_baseline_file(
baseline_file)[0:3]
date_list = ptime.yymmdd(date_list)
tbase_list = ptime.date_list2tbase(date_list)[0]
elif reference_file:
obj = ifgramStack(reference_file)
date12_list_all = obj.get_date12_list(dropIfgram=False)
date12_list_all = ptime.yymmdd_date12(date12_list_all)
m_dates = [i.split('-')[0] for i in date12_list_all]
s_dates = [i.split('-')[1] for i in date12_list_all]
date_list = sorted(list(set(m_dates + s_dates)))
tbase_list = ptime.date_list2tbase(date_list)[0]
pbase_list = obj.get_perp_baseline_timeseries(
dropIfgram=False).tolist()
return date_list, tbase_list, pbase_list, dop_list
def threshold_coherence_based_mst(date12_list, coh_list):
"""Return a minimum spanning tree of network based on the coherence inverse.
Inputs:
date12_list - list of string in YYMMDD-YYMMDD format
coh_list - list of float, average coherence for each interferogram
Output:
mst_date12_list - list of string in YYMMDD-YYMMDD format, for MST network of interferograms
"""
# coh_list --> coh_mat --> weight_mat
coh_mat = coherence_matrix(date12_list, coh_list)
mask = ~np.isnan(coh_mat)
wei_mat = np.zeros(coh_mat.shape)
wei_mat[:] = np.inf
wei_mat[mask] = 1/coh_mat[mask]
# MST path based on weight matrix
wei_mat_csr = sparse.csr_matrix(wei_mat)
mst_mat_csr = sparse.csgraph.minimum_spanning_tree(wei_mat_csr)
# Get date6_list
date12_list = ptime.yymmdd_date12(date12_list)
m_dates = [date12.split('-')[0] for date12 in date12_list]
s_dates = [date12.split('-')[1] for date12 in date12_list]
date6_list = ptime.yymmdd(sorted(ptime.yyyymmdd(list(set(m_dates + s_dates)))))
# Convert MST index matrix into date12 list
[s_idx_list, m_idx_list] = [date_idx_array.tolist()
for date_idx_array in sparse.find(mst_mat_csr)[0:2]]
mst_date12_list = []
for i in range(len(m_idx_list)):
idx = sorted([m_idx_list[i], s_idx_list[i]])
date12 = date6_list[idx[0]]+'-'+date6_list[idx[1]]
mst_date12_list.append(date12)
return mst_date12_list
def threshold_coherence_based_mst(date12_list, coh_list):
"""Return a minimum spanning tree of network based on the coherence inverse.
Inputs:
date12_list - list of string in YYMMDD-YYMMDD format
coh_list - list of float, average coherence for each interferogram
Output:
mst_date12_list - list of string in YYMMDD-YYMMDD format, for MST network of interferograms
"""
# coh_list --> coh_mat --> weight_mat
coh_mat = coherence_matrix(date12_list, coh_list)
mask = ~np.isnan(coh_mat)
wei_mat = np.zeros(coh_mat.shape)
wei_mat[:] = np.inf
wei_mat[mask] = 1/coh_mat[mask]
# MST path based on weight matrix
wei_mat_csr = sparse.csr_matrix(wei_mat)
mst_mat_csr = sparse.csgraph.minimum_spanning_tree(wei_mat_csr)
# Get date6_list
date12_list = ptime.yymmdd_date12(date12_list)
m_dates = [date12.split('-')[0] for date12 in date12_list]
s_dates = [date12.split('-')[1] for date12 in date12_list]
date6_list = ptime.yymmdd(sorted(ptime.yyyymmdd(list(set(m_dates + s_dates)))))
# Convert MST index matrix into date12 list
[s_idx_list, m_idx_list] = [date_idx_array.tolist()
for date_idx_array in sparse.find(mst_mat_csr)[0:2]]
mst_date12_list = []
for i in range(len(m_idx_list)):
idx = sorted([m_idx_list[i], s_idx_list[i]])
date12 = date6_list[idx[0]]+'-'+date6_list[idx[1]]
mst_date12_list.append(date12)
return mst_date12_list
def coherence_matrix(date12_list,
coh_list,
diag_value=np.nan,
fill_triangle='both',
date_list=None):
"""Return coherence matrix based on input date12 list and its coherence
Inputs:
date12_list - list of string in YYMMDD-YYMMDD format
coh_list - list of float, average coherence for each interferograms
diag_value - number, value to be filled in the diagonal
fill_triangle - str, 'both', 'upper', 'lower'
Output:
coh_matrix - 2D np.array with dimension length = date num
np.nan value for interferograms non-existed.
1.0 for diagonal elements
"""
# Get date list
date12_list = ptime.yymmdd_date12(date12_list)
if not date_list:
m_dates = [date12.split('-')[0] for date12 in date12_list]
s_dates = [date12.split('-')[1] for date12 in date12_list]
date_list = sorted(list(set(m_dates + s_dates)))
date_list = ptime.yymmdd(date_list)
date_num = len(date_list)
coh_mat = np.zeros([date_num, date_num])
coh_mat[:] = np.nan
for date12 in date12_list:
date1, date2 = date12.split('-')
idx1 = date_list.index(date1)
idx2 = date_list.index(date2)
coh = coh_list[date12_list.index(date12)]
if fill_triangle in ['upper', 'both']:
coh_mat[idx1, idx2] = coh # symmetric
if fill_triangle in ['lower', 'both']:
coh_mat[idx2, idx1] = coh
if diag_value is not np.nan:
for i in range(date_num): # diagonal value
coh_mat[i, i] = diag_value
return coh_mat
def select_pairs_sequential(date_list, num_conn=2, date_format=None):
"""Select Pairs in a Sequential way:
For each acquisition, find its num_connection nearest acquisitions in the past time.
Reference:
Fattahi, H., and F. Amelung (2013), DEM Error Correction in InSAR Time Series, IEEE TGRS, 51(7), 4249-4259.
Parameters: date_list - list of str for date
num_conn - int, number of sequential connections
date_format - str / None, output date format
Returns: date12_list - list of str for date12
"""
date_list = sorted(date_list)
date_inds = list(range(len(date_list)))
# Get pairs index list
date12_inds = []
for date_ind in date_inds:
for i in range(num_conn):
if date_ind - i - 1 >= 0:
date12_inds.append([date_ind - i - 1, date_ind])
date12_inds = [sorted(i) for i in sorted(date12_inds)]
# Convert index into date12
date12_list = [
'{}_{}'.format(date_list[ind12[0]], date_list[ind12[1]])
for ind12 in date12_inds
]
# adjust output date format
if date_format is not None:
if date_format == 'YYYYMMDD':
date12_list = ptime.yyyymmdd_date12(date12_list)
elif date_format == 'YYMMDD':
date12_list = ptime.yymmdd_date12(date12_list)
else:
raise ValueError(
'un-supported date format: {}!'.format(date_format))
return date12_list
def select_network_candidate(inps):
date_list, tbase_list, pbase_list, dop_list = read_baseline_info(
baseline_file=inps.baseline_file, reference_file=inps.referenceFile)
# Pair selection from reference
if inps.referenceFile:
log('select initial network from reference file: {}'.format(
inps.referenceFile))
stack_obj = ifgramStack(inps.referenceFile)
date12_list = stack_obj.get_date12_list(dropIfgram=True)
date12_list = ptime.yymmdd_date12(date12_list)
# Pais selection from method
elif inps.baseline_file:
log('select initial network with method: {}'.format(inps.method))
if inps.method == 'all':
date12_list = pnet.select_pairs_all(date_list)
elif inps.method == 'delaunay':
date12_list = pnet.select_pairs_delaunay(date_list, pbase_list,
inps.norm)
elif inps.method == 'star':
date12_list = pnet.select_pairs_star(date_list)
elif inps.method == 'sequential':
date12_list = pnet.select_pairs_sequential(date_list, inps.connNum)
elif inps.method == 'hierarchical':
date12_list = pnet.select_pairs_hierarchical(
date_list, pbase_list, inps.tempPerpList)
elif inps.method == 'mst':
date12_list = pnet.select_pairs_mst(date_list, pbase_list)
else:
raise Exception('Unrecoganized select method: ' + inps.method)
log('initial number of interferograms: {}'.format(len(date12_list)))
inps.date12_list = date12_list
inps.date_list = date_list
inps.tbase_list = tbase_list
inps.pbase_list = pbase_list
inps.dop_list = dop_list
return inps
def coherence_matrix(date12_list, coh_list, diag_value=np.nan, fill_triangle='both', date_list=None):
"""Return coherence matrix based on input date12 list and its coherence
Inputs:
date12_list - list of string in YYMMDD-YYMMDD format
coh_list - list of float, average coherence for each interferograms
diag_value - number, value to be filled in the diagonal
fill_triangle - str, 'both', 'upper', 'lower'
Output:
coh_matrix - 2D np.array with dimension length = date num
np.nan value for interferograms non-existed.
1.0 for diagonal elements
"""
# Get date list
date12_list = ptime.yymmdd_date12(date12_list)
if not date_list:
m_dates = [date12.split('-')[0] for date12 in date12_list]
s_dates = [date12.split('-')[1] for date12 in date12_list]
date_list = sorted(list(set(m_dates + s_dates)))
date_list = ptime.yymmdd(date_list)
date_num = len(date_list)
coh_mat = np.zeros([date_num, date_num])
coh_mat[:] = np.nan
for date12 in date12_list:
date1, date2 = date12.split('-')
idx1 = date_list.index(date1)
idx2 = date_list.index(date2)
coh = coh_list[date12_list.index(date12)]
if fill_triangle in ['upper', 'both']:
coh_mat[idx1, idx2] = coh # symmetric
if fill_triangle in ['lower', 'both']:
coh_mat[idx2, idx1] = coh
if diag_value is not np.nan:
for i in range(date_num): # diagonal value
coh_mat[i, i] = diag_value
return coh_mat
