source: src/Readme @ 1

                - content -

htune_case_setup.R     htune_EmulatingSCM.R  htune_ncdf2Rdata.R  param2R.sh
htune_convertDesign.R  htune_metric.R        htune_plot.R        Readme
serie_LMDZ.sh


               - Description -

Main programs :
===============

Step 0 :
   param2R.sh : define list of parameters and there range
             create the R script  ModelParam.R
   Usage : ./param2R.sh LHCSIZE NLHC PARAM_FILE
   Ex : ./param2R.sh 30 3 LMDZ/param_cld
   NLHC should be >= 3


Step 1 : htune_convertDesign.R, Automatically run by param2R.sh from version 9
   creates design for the emulator using ModelParam.R
   outputs : Par1D_Wave1.asc containing the parameter values
                for SCM simulations
             Wave1.RData containing normalized parameter values for
                the SCM
   TBD : create a function that could be called from anywhere to
         transformed normalized to non normalized

Step 2 : serie_LMDZ.sh
   The only model depedant script
   Use : ./serie_LMDZ.sh case1 [case2]
   Run a series of the LMDZ SCM reading the parameters from Par1D_Wave1.asc
   netcdf ouptut files should be put in
   ./WAVE1/[cas] 
   with names SCM_1-101.nc given in Par1D_Wave1.asc
   Also put the available LES 1D output files in WAVE1

   TBD : a version for MUSC
         Treat LES independently depending on the case consider ?
         Normalize the case names ?

Step 3 : htune_ncdf2Rdata.R
   i/ Reads results from WAVE1/*nc
   ii/ Plots profiles for all the simulations with function "tout_tracer" from
   htune_plot
   iii/ computes metrics with function get_metric from htune_metric.R
   output files
   Wave1_LES.Rdata : metrics computed on LES
   Wave1_SCM.Rdata : metrics computed on SCM
   Assume that all the files are at an hourly time frequency
   Metrics already available :
     targetvar="theta500" theta 500hPa 
     targetvar="zhneb"    average height of cloudiness (int z f dz / int f dz)
   TBD : control case_name from outside
   TBD : extend the "tout_tracer" to "tout"

Step 4 : htune_EmulatingSCM.R
    Emulator building reading Wave1_LES.Rdata and Wave1_SCM.Rdata
    Definition and plots of ROY spaces





Functions :
===========
htune_case_setup.R : some cases caracteristics for plots
htune_metric.R : metrics computation
htune_plot.R :  plots


Imput from Exeter :
===================
StanEmulateCodeR.R which requires :
AutoLMcode.R
CustomPredict.R
impLayoutplot.R
JamesDevelopment.R
DannyDevelopment.R
MultiWaveHM.R
MySpeed1const.stan
PredictSpeed1const.stan
PredictSpeed2DWconst.stan
MySpeed1.stan
PredictSpeed1.stan
PredictSpeed2DW.stan
kLHC.R : LHS clever sampling


Discussion / conventions :
==========================

I propose to use hourly averaged outputs.
Should work for all the available cases.



Installation rstudio :
======================

Here is how to install RStudio on Ubuntu 16.04

sudo apt-get install r-base
wget https://download1.rstudio.org/rstudio-xenial-1.0.153-amd64.deb
sudo apt-get install gdebi
sudo gdebi rstudio-xenial-1.0.153-amd64.deb

then, you should be able to open RStudio by simply using the command:
rstudio

when you install the supplementary libraries for RStudio on Ubuntu, you will need to install netcdf-bin et libnetcdf-dev, otherwise
the ncdf4 library won't install correctly

here is the complete list written on the white board for copy pasting:

installed.packages(c("ncdf4","rstan","tensor","Hmisc","lhs","fields","rgl","shape","mco","far","dicekriging","GenSA","mvtnorm"))

Evetuellement
r-cran-rgl
libx11-dev
libglu1-mesa-dev