sangchengfang / hector_mypythom

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All Python scripts call Python 3 as 'python3'. If this does not exist on
your system, create a symbolic link. apply_WF requires the numpy module.



analyse_timeseries.py: workhorse script that calls removeoutliers and
	estimatetrend. Argument is station name + noise model combination.

analyse_and_plot.py: high level script that calls "analyse_timeseries.py" to
	analyse and plot all time series in the ./obs_files directory. It
	assumes these are in the mom format. Argument is noise model 
	combination.

apply_WF.py: computes a varying annual + semi-annual signal for a 
	time series stored in ./obs_files. Argument is station name +
	phi (the coefficient of the AR1 noise describing the random part
	of the seasonal signal). It makes use of analyse_timeseries.py.
	Estimated seasonal signal is stored in ./sea_files while the
	signal-seasonal signal (filtered signal) is stored in ./fil_files.

convert_neu2mom.py: script to convert all *.neu files in the ./ori_files
	directory (format used by SOPAC and JPL) to my mom format, which
	are stored in the raw_files directory.

convert_sol2mom.py: script to convert all *.sol files in the ./ori_files
	directory (format used by GIPSY/OASIS) to my mom format, which
	are stored in the raw_files directory.

convert_tenv32mom.py: script to convert all *.tenv.txt files in the ./ori_files
	directory (format used by Nevada Geodetic Laboratory) to my mom 
	format, which are stored in the raw_files directory.

find_offset.py: script to find offset for a particular time series stored in
	the ./raw_directory. Arguments are station name, noise model 
	combination and, optionally, the label '3D'. The latter assumes that
	the filenames follow the XXXX_[012] convention. That is, _0 contains
	East component, _1 contains North component and _2 the up component.
	XXXX is the station name.

find_all_offsets.py: simply a wrapper to find_offset.py which runs the offset
	detection on all files stored in ./raw_files using the 3D option
	and using the PLWN noise model.

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