How to analyse InSight pressure data to get the local and non local turbulence
Part 1: basic case (to do first, called version "" or "1")
(without removing vortex signature and with no limit on the higher frequency)
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STEP 1: DOWNLOAD DATA FROM PDS:
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pressure
https://atmos.nmsu.edu/PDS/data/PDS4/InSight/ps_bundle/data_calibrated/
Put them in a folder "pressure_data/" with internal folders with the blocks of sols downloaded (ie. "pressure_data/0000-0122/" for sols between 0 and 122).

wind + temperature
https://atmos.nmsu.edu/PDS/data/PDS4/InSight/twins_bundle/data_derived/
Put them in a folder "twins_data/" with internal folders with the blocks of sols downloaded (ie. "twins_data/0000-0122/" for sols between 0 and 122).


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STEP 2: WITH USUAL INSIGHT DATA FILES: 
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for files with no stop or frequency change during the acquisition
They have a frequency either 10 or 2 Hz (corresponding to files of 88 622 Ko or 17 704 Ko)
pfreq = 10 or 2  

1) run read_pressure_autom.py
   independent analysis on each day
   but it creates parasitic effects on boundaries between two days
   it saves pythons variables in a new folder for each sol: "pressure_stdev/Sol"+sol"/":
		lmst, ltst, pressure, pfreq, pmoy for 100s, pmoy for 1000s, pdev for 100s and pdev for 1000s
   it plots pressure over each sol (useful to check if the acquisition is complete or not)
   it computes (and can plot) the moving mean of the pressure over 100s and 1000s (pmoy)
   it computes (and can plot) the moving standard deviation of the pmoy variables
   called programs: mod_movingmean, mod_turbu, mod_dev, mod_simpleplot_data (for plot) and mod_superplot_data (for plot)
   
At this stage, organize the sol folders in folders by months: eg. "pressure_stdev/0614-0668/Sol0668/"
The months used for this study are:
# 0000-0055    0056-0111    0112-0167    0168-0222    0223-0278
# 0279-0334    0335-0390    0391-0445    0446-0501    0502-0557
# 0558-0613    0614-0668    0669-0724    0725-0780    0781-0836
   
2) run corr_interday.py
   it combines sols 2 by 2 to correct the boundary parasitic effects
   it puts NaNs if there is no data on next/previous sol
   called programs: mod_movingmean, mod_turbu, mod_dev
   it updates and saves the variables pmoy and pdev
   
3) results can be plotted using plot_p_dev_all.py
   /!\ in this case of version "", these are not the exact local and non local turbulence presented in the paper. The other corrections have to be taken into account (see readme part 2 and readme part 3).
   it plots color surface with p_dev as a function of sol and hour
   it is possible to plot 1 month or 3 months (for that change the figure size in mod_colorplot.py)
   called programs: mod_loopconcat_v2.py and mod_colorplot.py
   there is also the version plot_p_dev_all_year.py for plots over one year
   there is also the version plot_p_dev_all_all.py for plots over 837 sols
   

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STEP 3: WITH INSIGHT DATA FILES WITH STOPS DURING THE ACQUISITION 
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1) run read_pressure_autom.py 

[OLD MANUAL VERSION]
	2) run print_pfreq.py
	   to check the pressure acquisition frequency (usually 10 or 2)

	3) pb_data_missing.py
	   choose the right blocks to run (possible to run several blocks if necessary):
	   if there are "holes": it adds NaNs in p_moy and p_dev on the hole sides
	   if there is no beginning or end: it adds NaNs to avoid pbs in corr_interday
	   
	4) add the "Sol####" folder into the corresponding monthly folder

	5) run corr_interday.py
	6) run plot_p_dev_all.py
	
[NEW AUTOMATIC VERSION: BEST]
	2) run make_nocompletesol.py
		it creates a variable (nocompletesol.npy) to indicate how the sol is problematic
	
	3) run pb_data_missing_autom.py
		it works month by month
		/!\ for version 1, to run only once!!! (it adds supplementary NaNs)
		
	4) run corr_interday.py, or corr_interday_v2.py for no vortex cases
	5) run plot_p_dev_all.py


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STEP 4: WITH INSIGHT DATA FILES WITH PFREQ CHANGE 
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before corr_interday.py:

For version 1:
Use cut_variable.py
with read_pressure_for_cut_variable.py

For the other versions:
Use cut_variable_v2.py
with read_pressure2_no_for_cut_variable.py