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Addressing some PR comments
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@yjzhenglamarmota
yjzhenglamarmota committed May 24, 2022
1 parent 7407c8a commit 29334d3
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62 changes: 31 additions & 31 deletions mintpy/closure_phase_bias.py
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Original file line number Diff line number Diff line change
Expand Up @@ -24,9 +24,9 @@
"""
EXAMPLE = """example:
closure_phase_bias.py -i inputs/ifgramStack.h5 --nl 20 --action create_mask
closure_phase_bias.py -i inputs/ifgramStack.h5 --nl 20 --numsigma 2.5 --action create_mask
closure_phase_bias.py -i inputs/ifgramStack.h5 --nl 20 --bw 10 -a quick_biasEstimate
closure_phase_bias.py -i inputs/ifgramStack.h5 --nl 20 --bw 10 -a biasEstimate
closure_phase_bias.py -i inputs/ifgramStack.h5 --nl 20 --num_sigma 2.5 --action create_mask
closure_phase_bias.py -i inputs/ifgramStack.h5 --nl 20 --bw 10 -a quick_bias_estimate
closure_phase_bias.py -i inputs/ifgramStack.h5 --nl 20 --bw 10 -a bias_estimate --noupdate_CP -c local
"""

def create_parser():
Expand All @@ -36,18 +36,18 @@ def create_parser():
parser.add_argument('-i','--ifgramstack',type = str, dest = 'ifgram_stack',help = 'interferogram stack file that contains the unwrapped phases')
parser.add_argument('--nl', dest = 'nl', type = int, default = 20, help = 'connection level that we are correcting to (or consider as no bias)')
parser.add_argument('--bw', dest = 'bw', type = int, default = 10, help = 'bandwidth of time-series analysis that you want to correct')
parser.add_argument('--numsigma',dest = 'numsigma', type = float, default = 3, help = 'Threashold for phase (number of sigmas,0-infty), default to be 3 sigma of a Gaussian distribution (assumed distribution for the cumulative closure phase) with sigma = pi/sqrt(3*num_cp)')
parser.add_argument('--num_sigma',dest = 'num_sigma', type = float, default = 3, help = 'Threashold for phase (number of sigmas,0-infty), default to be 3 sigma of a Gaussian distribution (assumed distribution for the cumulative closure phase) with sigma = pi/sqrt(3*num_cp)')
parser.add_argument('--epi',dest = 'episilon', type = float, default = 0.3, help = 'Threashold for amplitude (0-1), default 0.3')
parser.add_argument('--maxMemory', dest = 'max_memory', type = float, default = 8, help = 'max memory to use in GB')
parser.add_argument('--noupdate_CP',dest = 'update_CP', action = 'store_false', help = 'Use when no need to compute closure phases')
parser.add_argument('-o', dest = 'outdir', type = str, default = '.', help = 'output file directory')
parser.add_argument('-a','--action', dest='action', type=str, default='create_mask',
choices={'create_mask', 'quick_biasEstimate', 'biasEstimate'},
choices={'create_mask', 'quick_bias_estimate', 'bias_estimate'},
help='action to take (default: %(default)s):\n'+
'create_mask - create a mask of areas susceptible to closure phase errors\n'+
'quick_biasEstimate - estimate how bias decays with time, will output sequential closure phase files, and gives a quick and appximate bias estimation\n'
'biasEstimate - estimate how bias decays with time, processed for each pixel on a pixel by pixel basis')
'quick_bias_estimate - estimate how bias decays with time, will output sequential closure phase files, and gives a quick and appximate bias estimation\n'
'bias_estimate - estimate how bias decays with time, processed for each pixel on a pixel by pixel basis')
parser = arg_group.add_parallel_argument(parser)
parser = arg_group.add_memory_argument(parser)
return parser

def cmd_line_parse(iargs=None):
Expand Down Expand Up @@ -378,7 +378,7 @@ def estimatetsbias_approx(nl, bw, tbase, date_ordinal, wvl, box, outdir):
biasts[np.isnan(biasts)]=biasts2[np.isnan(biasts1)]
return biasts

def quickbiascorrection(ifgram_stack, nl, bw, max_memory, outdir):
def quickbiascorrection(ifgram_stack, nl, bw, maxMemory, outdir):
'''
Output Wr (eq.20 in Zheng et al., 2022) and a quick approximate solution to bias time-series
Input parameters:
Expand Down Expand Up @@ -421,7 +421,7 @@ def quickbiascorrection(ifgram_stack, nl, bw, max_memory, outdir):
writefile.layout_hdf5(Wr_filedir, ds_name_dict, meta)

# split igram_file into blocks to save memory
box_list, num_box = ifginv.split2boxes(ifgram_stack, max_memory)
box_list, num_box = ifginv.split2boxes(ifgram_stack, maxMemory)

#process block-by-block
for i, box in enumerate(box_list):
Expand Down Expand Up @@ -543,13 +543,13 @@ def estimate_bias(ifgram_stack, nl, bw, wvl, box, outdir):

return biasts_bwn,box

def biascorrection(ifgram_stack, nl, bw, max_memory, outdir, parallel):
def biascorrection(ifgram_stack, nl, bw, maxMemory, outdir, parallel):
'''
input: ifgram_stack -- the ifgramstack file that you did time-series analysis with
input: nl -- the connection level that we assume bias-free
input: bw -- the bandwidth of the time-series analysis, should be consistent with the network stored in ifgram_stack
input: wvl -- wavelength of the SAR satellite
input: max_memory -- maximum memory of each patch
input: maxMemory -- maximum memory of each patch
input: outdir -- directory for output files
'''
stack_obj = ifgramStack(ifgram_stack)
Expand All @@ -560,7 +560,7 @@ def biascorrection(ifgram_stack, nl, bw, max_memory, outdir, parallel):
date2s = [i.split('_')[1] for i in date12_list]
SLC_list = sorted(list(set(date1s + date2s)))
# split igram_file into blocks to save memory
box_list, num_box = ifginv.split2boxes(ifgram_stack, max_memory)
box_list, num_box = ifginv.split2boxes(ifgram_stack, maxMemory)

# estimate for bias time-series
biasfile = os.path.join(outdir, 'bias_timeseries.h5')
Expand Down Expand Up @@ -621,12 +621,12 @@ def biascorrection(ifgram_stack, nl, bw, max_memory, outdir, parallel):
return


def creat_cp_mask(ifgram_stack, nl, max_memory, numsigma, threshold_amp, outdir):
def creat_cp_mask(ifgram_stack, nl, maxMemory, num_sigma, threshold_amp, outdir):
"""
Input parameters:
ifgram_stack: stack file
nl : maximum connection level that assumed to be bias free
max_memory : maxum memory for each bounding box
maxMemory : maxum memory for each bounding box
threshold_pha, threshold_amp: threshold of phase and ampliutde of the cumulative sequential closure phase
"""
stack_obj = ifgramStack(ifgram_stack)
Expand All @@ -653,7 +653,7 @@ def creat_cp_mask(ifgram_stack, nl, max_memory, numsigma, threshold_amp, outdir)
print('last SLC: ', SLC_list[-1])

# split igram_file into blocks to save memory
box_list, num_box = ifginv.split2boxes(ifgram_stack,max_memory)
box_list, num_box = ifginv.split2boxes(ifgram_stack,maxMemory)
closurephase = np.zeros([length,width],np.complex64)
#process block-by-block
for i, box in enumerate(box_list):
Expand All @@ -672,7 +672,7 @@ def creat_cp_mask(ifgram_stack, nl, max_memory, numsigma, threshold_amp, outdir)
# The standard deviation of phase in cumulative wrapped closure phase is pi/sqrt(3)/sqrt(numcp) -- again another simplification assuming no correlation.
# We use 3\delta as threshold -- 99.7% confidence

threshold_pha = np.pi/np.sqrt(3)/np.sqrt(numcp)*numsigma
threshold_pha = np.pi/np.sqrt(3)/np.sqrt(numcp)*num_sigma

mask = np.ones([length,width],np.float32)
mask[np.abs(np.angle(closurephase))>threshold_pha] = 0 # this masks areas with potential bias
Expand All @@ -692,7 +692,7 @@ def creat_cp_mask(ifgram_stack, nl, max_memory, numsigma, threshold_amp, outdir)
return

# ouput wrapped, and unwrapped sequential closure phases, and cumulative closure phase time-series of connection-conn
def compute_unwrap_closurephase(ifgram_stack, conn, max_memory, outdir):
def compute_unwrap_closurephase(ifgram_stack, conn, maxMemory, outdir):
stack_obj = ifgramStack(ifgram_stack)
stack_obj.open()
length, width = stack_obj.length, stack_obj.width
Expand All @@ -719,7 +719,7 @@ def compute_unwrap_closurephase(ifgram_stack, conn, max_memory, outdir):
print('last SLC: ', SLC_list[-1])

# split igram_file into blocks to save memory
box_list, num_box = ifginv.split2boxes(ifgram_stack,max_memory)
box_list, num_box = ifginv.split2boxes(ifgram_stack,maxMemory)

closurephase = np.zeros([len(SLC_list)-conn, length,width],np.float32)
#process block-by-block
Expand Down Expand Up @@ -785,34 +785,34 @@ def compute_unwrap_closurephase(ifgram_stack, conn, max_memory, outdir):

def main(iargs = None):
inps = cmd_line_parse(iargs)
if inps.numsigma:
numsigma = inps.numsigma
if inps.num_sigma:
num_sigma = inps.num_sigma
else:
numsigma = 3
num_sigma = 3
if inps.action == 'create_mask':
creat_cp_mask(inps.ifgram_stack, inps.nl, inps.max_memory, numsigma, inps.episilon, inps.outdir)
creat_cp_mask(inps.ifgram_stack, inps.nl, inps.maxMemory, num_sigma, inps.episilon, inps.outdir)

if inps.action == 'quick_biasEstimate':
if inps.action == 'quick_bias_estimate':
maxconn = np.maximum(2,inps.bw) # to make sure we have con-2 closure phase processed
if inps.update_CP:
for conn in np.arange(2,maxconn+1):
compute_unwrap_closurephase(inps.ifgram_stack, conn, inps.max_memory, inps.outdir)
compute_unwrap_closurephase(inps.ifgram_stack, inps.nl, inps.max_memory, inps.outdir)
compute_unwrap_closurephase(inps.ifgram_stack, conn, inps.maxMemory, inps.outdir)
compute_unwrap_closurephase(inps.ifgram_stack, inps.nl, inps.maxMemory, inps.outdir)
# a quick solution to bias-correction and output diagonal component of Wr (how fast the bias-inducing signal decays with temporal baseline)
quickbiascorrection(inps.ifgram_stack, inps.nl, inps.bw, inps.max_memory, inps.outdir)
quickbiascorrection(inps.ifgram_stack, inps.nl, inps.bw, inps.maxMemory, inps.outdir)

if inps.action == 'biasEstimate':
if inps.action == 'bias_estimate':
if inps.update_CP:
for conn in np.arange(2,inps.bw+2): # to make sure we have con-2 closure phase processed
compute_unwrap_closurephase(inps.ifgram_stack, conn, inps.max_memory, inps.outdir)
compute_unwrap_closurephase(inps.ifgram_stack, inps.nl, inps.max_memory, inps.outdir)
compute_unwrap_closurephase(inps.ifgram_stack, conn, inps.maxMemory, inps.outdir)
compute_unwrap_closurephase(inps.ifgram_stack, inps.nl, inps.maxMemory, inps.outdir)
# bias correction
parallel={
"clustertype" : inps.cluster,
"numWorker" : inps.numWorker,
"config_name" : inps.config,
}
biascorrection(inps.ifgram_stack, inps.nl, inps.bw, inps.max_memory, inps.outdir, parallel)
biascorrection(inps.ifgram_stack, inps.nl, inps.bw, inps.maxMemory, inps.outdir, parallel)

if __name__ == '__main__':
main(sys.argv[1:])
5 changes: 2 additions & 3 deletions mintpy/utils/isce_utils.py
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Original file line number Diff line number Diff line change
Expand Up @@ -23,7 +23,7 @@
import numpy as np
from mintpy.objects import sensor
from mintpy.utils import ptime, readfile, writefile, utils1 as ut

from scipy import ndimage
# suppress matplotlib DEBUG message
import logging
mpl_logger = logging.getLogger('matplotlib')
Expand Down Expand Up @@ -949,7 +949,6 @@ def convolve(data, kernel):
inputs: data - complex array
kernel - convolution kernel
'''
from scipy import ndimage
R = ndimage.convolve(data.real, kernel, mode='constant',cval=0.0)
Im =ndimage.convolve(data.imag, kernel, mode='constant',cval=0.0)

Expand Down Expand Up @@ -1006,7 +1005,7 @@ def unwrap_snaphu(intfile,corfile,unwfile, meta ,cost='SMOOTH'):

width = int(meta['width'])
wavelength = float(meta['WAVELENGTH'])
altitude = float(meta['altitude'])
altitude = float(meta['HEIGHT'])
rglooks = int(meta['RLOOKS'])
azlooks = int(meta['ALOOKS'])
earthRadius = float(meta['earthRadius'])
Expand Down

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