block-by-block IO - part 1 #478
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+ move the commonly shared groups of arguments parsing functions from utils/plot.py into a new sub-module utils/arg_group.py + move the parallel computing related arguments into utils/arg_group.add_parallel_argument() + adjust usages across the whole mintpy package
+ add/modify split2boxes() from ifgram_inversion.py + move key msg and design_matrix into get_design_matrix4defo() for cleaner code + read_geometry(): explicit input arguments + box + add correct_dem_error_patch() from the code of correct_dem_error() + use writefile.layout_hdf() and writefile.wirte_hdf5_block() for block-by-block IO, like ifg_inv.py + add --memory option with support of mintpy.compute.memorySize + run_or_skip(): check file size to detect partially written file
+ utils/writefile.layout_hdf5(): support output file in different size in space from the reference file + subset.py: - add subset_dataset() to get the subseted data from input file - block-by-block IO for HDF5 file with 3D dataset, to significantly reduce the memory usage. Testing on laptop (16GB memory) for ifgramStack.h5 file with 140GB works very smooth.
+ objects/cluster: move split_box2sub_boxes() out of the DaskCluster object for easy import; add print_msg. + diff: add block-by-block IO for time-series files
If the number of valid pixels > 1m, apply a uniform sampling for a faster ramp estimation and for less memory usage
to avoid un-necessary temporal average computation.
+ add -m / --method option to choose among average / nearest + add lks_x/y == 1 check + multilook_data(): ensure in/out matrix in the same data type + multilook_file(): - support nearest downsampling using readfile.read(x/ystep) option - add block-by-block IO for HDF5 files + apply block-by-block IO for multilook.py for efficient memory usage + plot.read_pts2inps(): bug fix when no lookup file is availble + utils1.get_center_lat_lon(): support file in geo coordinates + writefile.write_isce_xml(): add example usage in the comment
…mp_avg/read() and use numpy indexing instead
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Description of proposed changes
The first part of block-by-block IO for the following scripts, in preparation for a memory-efficient smallbaselineApp workflow:
Improved auto-skip for reference_point.py.
objects/ramp.py: downsample the very large dataset for ramp estimation, as suggested in Improve memory efficiency in the steps of calculating ramp, deramp, residual_RMS #436 by @hfattahi.
Reminders