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| MINTPY-TIMESERIES_RMS(1) | User Commands | MINTPY-TIMESERIES_RMS(1) |
NAME¶
mintpy-timeseries_rms - Calculate Root Mean Square (RMS) of deramped residual phase time-series.
DESCRIPTION¶
usage: timeseries_rms.py [-h] [-t TEMPLATE_FILE] [-m MASKFILE] [-r DERAMP]
- [--cutoff CUTOFF] [--figsize WID LEN]
- [--tick-year-num TICK_YEAR_NUM] timeseries_file
Calculate Root Mean Square (RMS) of deramped residual phase time-series.
positional arguments:¶
- timeseries_file
- Timeseries file
options:¶
- -h, --help
- show this help message and exit
- -t TEMPLATE_FILE, --template TEMPLATE_FILE
- template file with options
- -m MASKFILE, --mask MASKFILE
- mask file for estimation
- -r DERAMP, --ramp DERAMP, --deramp DERAMP
- ramp type to be remove for RMS calculation. Default - quadratic; no - do not remove ramp
- --cutoff CUTOFF
- M-score used for outlier detection based on standardised residuals Recommend range: [3, 4], default is 3.
- --figsize WID LEN
- figure size in inches - width and length
- --tick-year-num TICK_YEAR_NUM
- Year number per major tick
template options:¶
- ## Calculate the Root Mean Square (RMS) of residual phase time-series for each acquisition ## reference: Yunjun et al. (2019, section 4.9 and 5.4) ## To get rid of long wavelength component in space, a ramp is removed for each acquisition ## Set optimal reference date to date with min RMS ## Set exclude dates (outliers) to dates with RMS > cutoff * median RMS (Median Absolute Deviation) mintpy.residualRMS.maskFile = auto #[file name / no], auto for maskTempCoh.h5, mask for ramp estimation mintpy.residualRMS.deramp = auto #[quadratic / linear / no], auto for quadratic mintpy.residualRMS.cutoff = auto #[0.0-inf], auto for 3
example:¶
- timeseries_rms.py
- timeseriesResidual.h5
- timeseries_rms.py
- timeseriesResidual.h5 --template smallbaselineApp.cfg
- timeseries_rms.py
- timeseriesResidual.h5 -m maskTempCoh.h5 --cutoff 3
| May 2022 | mintpy-timeseries_rms v1.3.3 |