The diagfi.def Input File

2022-05-11T09:06:26Z

Guillaume.Chaverot:

Example of ''diagfi.def'' file:

<pre>
aire
altitude
ap
aps
ASR
ASRcs
beta
bp
bps
CLF
CLFt
controle
Declin
dt_ekman1
dt_ekman2
dt_diff1
dt_diff2
DYN
evap_surf_flux
fluxsurf_rad
GND
h2o_ice
h2o_ice_col
h2o_ice_surf
h2o_vap
h2o_vap_col
h2o_vap_surf
H2Oice_reffcol
ISR
latentFlux
latitude
longitude
Ls
Lss
mass_evap_col
OLR
OLRcs
p
pctsrf_sic
phisinit
ps
RA
rain
reevap
RH
rnat
sea_ice
sensibFlux
shad
snow
soildepth
tau_col
temp
Time
Tsat
tsea_ice
tslab1
tslab2
tsurf
u
v
w
</pre>

Useful Examples

2022-05-11T09:03:50Z

Guillaume.Chaverot: /* Editing convention */

== Editing convention ==
*Name of the files: ''italic''

== To Edit Sidebar (as admin only!!!) ==
Go to [[MediaWiki:Sidebar]]

== To write some LateX ==
See e.g. [https://lmdz-forge.lmd.jussieu.fr/mediawiki/LMDZPedia/index.php/ExempleMaths LMDZPedia]
And check out this page in "edit" mode!

$$\newcommand{\Re}{\mathrm{Re}\,}
\newcommand{\pFq}[5]{{}_{#1}\mathrm{F}_{#2} \left( \genfrac{}{}{0pt}{}{#3}{#4} \bigg| {#5} \right)}$$

We consider, for various values of $$s$$, the $$n$$-dimensional integral
\begin{align}
\label{def:Wns}
W_n (s)
&:=
\int_{[0, 1]^n}
\left| \sum_{k = 1}^n \mathrm{e}^{2 \pi \mathrm{i} \, x_k} \right|^s \mathrm{d}\boldsymbol{x}
\end{align}
which occurs in the theory of uniform random walk integrals in the plane,
where at each step a unit-step is taken in a random direction. As such,
the integral \eqref{def:Wns} expresses the $$s$$-th moment of the distance
to the origin after $$n$$ steps.

By experimentation and some sketchy arguments we quickly conjectured and
strongly believed that, for $$k$$ a nonnegative integer
\begin{align}
\label{eq:W3k}
W_3(k) &= \Re \, \pFq32{\frac12, -\frac k2, -\frac k2}{1, 1}{4}.
\end{align}

Appropriately defined, \eqref{eq:W3k} also holds for negative odd integers.
The reason for \eqref{eq:W3k} was long a mystery, but it will be explained
at the end of the paper.

== Miscellaneous ==
* HTML like syntax works! e.g. comments with

<pre>

which you see because between "pre" tags
</pre>

* Some special features:
Link to the internal page with all special features: [[Special:Version]]

* Examples of Syntax Highlighting:
Some Fortran Code:
<syntaxhighlight lang="fortran" line>
program truc
implicit none
integer :: i
do i=1,10
write(*,*) "i=",i," for each hello planeto world"
end do
end program
</syntaxhighlight>

Some Python Code:
<syntaxhighlight lang="python" line>
import numpy
import matplotlib as plt
for i in range(0,5,1):
print('hello planeto world")
plt.show()
</syntaxhighlight>

Some bash code:
<syntaxhighlight lang="bash" line>
echo 'hello planeto world'
</syntaxhighlight>

== How to create a new page ==
Option 1: Make a link to that page from a currently existing page, and when you click on that link (will be displayed in red as the system notices that it is a broken link) and the system will ask you if you want to create the page. A reminder on how to add (code-wise) a link to another MediaWiki page (try to follow CamelCase formatting, see option 2 below):
<pre>
[[Link_To_Some_Page|some descriptive text]]
</pre>
which will be rendered as:
[[Link_To_Some_Page|some descriptive text]]

Option 2: Look for it via the search bar! Advice: you should use CamelCase formating (with a "_" between words) as this page name will end up also being the title of the page (with the "_" replaced by spaces), e.g. The_Best_Page_Ever

== Link to the LMD Generic GCM user manual ==

link to the one on the trac which is what is on svn and thus will always be up to date:
https://trac.lmd.jussieu.fr/Planeto/browser/trunk/LMDZ.GENERIC/ManualGCM_GENERIC.pdf

Useful Examples

2022-05-11T09:03:36Z

Guillaume.Chaverot:

== Editing convention ==
Name of the files: ''italic''

== To Edit Sidebar (as admin only!!!) ==
Go to [[MediaWiki:Sidebar]]

== To write some LateX ==
See e.g. [https://lmdz-forge.lmd.jussieu.fr/mediawiki/LMDZPedia/index.php/ExempleMaths LMDZPedia]
And check out this page in "edit" mode!

$$\newcommand{\Re}{\mathrm{Re}\,}
\newcommand{\pFq}[5]{{}_{#1}\mathrm{F}_{#2} \left( \genfrac{}{}{0pt}{}{#3}{#4} \bigg| {#5} \right)}$$

We consider, for various values of $$s$$, the $$n$$-dimensional integral
\begin{align}
\label{def:Wns}
W_n (s)
&:=
\int_{[0, 1]^n}
\left| \sum_{k = 1}^n \mathrm{e}^{2 \pi \mathrm{i} \, x_k} \right|^s \mathrm{d}\boldsymbol{x}
\end{align}
which occurs in the theory of uniform random walk integrals in the plane,
where at each step a unit-step is taken in a random direction. As such,
the integral \eqref{def:Wns} expresses the $$s$$-th moment of the distance
to the origin after $$n$$ steps.

By experimentation and some sketchy arguments we quickly conjectured and
strongly believed that, for $$k$$ a nonnegative integer
\begin{align}
\label{eq:W3k}
W_3(k) &= \Re \, \pFq32{\frac12, -\frac k2, -\frac k2}{1, 1}{4}.
\end{align}

Appropriately defined, \eqref{eq:W3k} also holds for negative odd integers.
The reason for \eqref{eq:W3k} was long a mystery, but it will be explained
at the end of the paper.

== Miscellaneous ==
* HTML like syntax works! e.g. comments with

<pre>

which you see because between "pre" tags
</pre>

* Some special features:
Link to the internal page with all special features: [[Special:Version]]

* Examples of Syntax Highlighting:
Some Fortran Code:
<syntaxhighlight lang="fortran" line>
program truc
implicit none
integer :: i
do i=1,10
write(*,*) "i=",i," for each hello planeto world"
end do
end program
</syntaxhighlight>

Some Python Code:
<syntaxhighlight lang="python" line>
import numpy
import matplotlib as plt
for i in range(0,5,1):
print('hello planeto world")
plt.show()
</syntaxhighlight>

Some bash code:
<syntaxhighlight lang="bash" line>
echo 'hello planeto world'
</syntaxhighlight>

== How to create a new page ==
Option 1: Make a link to that page from a currently existing page, and when you click on that link (will be displayed in red as the system notices that it is a broken link) and the system will ask you if you want to create the page. A reminder on how to add (code-wise) a link to another MediaWiki page (try to follow CamelCase formatting, see option 2 below):
<pre>
[[Link_To_Some_Page|some descriptive text]]
</pre>
which will be rendered as:
[[Link_To_Some_Page|some descriptive text]]

Option 2: Look for it via the search bar! Advice: you should use CamelCase formating (with a "_" between words) as this page name will end up also being the title of the page (with the "_" replaced by spaces), e.g. The_Best_Page_Ever

== Link to the LMD Generic GCM user manual ==

link to the one on the trac which is what is on svn and thus will always be up to date:
https://trac.lmd.jussieu.fr/Planeto/browser/trunk/LMDZ.GENERIC/ManualGCM_GENERIC.pdf

The diagfi.def Input File

2022-05-11T09:00:25Z

Guillaume.Chaverot: Created blank page

The z2sig.def Input File

2022-05-11T08:59:40Z

Guillaume.Chaverot: Created blank page

The callphys.def Input File

2022-05-11T08:58:49Z

Guillaume.Chaverot: Created blank page

Tool Box

2022-05-11T08:30:03Z

Guillaume.Chaverot: /* Panoply */

== Pre-processing Tools ==
=== newstart ===
=== start2archive ===
=== visualization tools ===
=== other third party scripts and tools ===

TO BE COMPLETED

== Post-processing tools ==
=== zrecast ===

TO BE COMPLETED

=== mass stream function ===

The mass stream function (and the total angular momentum) can be computed from a diagfi.nc or a stats.nc, using the '''streamfunction.F90''' script. The script is located at

<syntaxhighlight lang="bash">
trunk/LMDZ.GENERIC/utilities
</syntaxhighlight>

To compile the script, open the ''compile'' file in the same directory and do the following:
* Replace "pgf90" with your favorite fortran compiler
* replace "/distrib/local/netcdf/pgi_7.1-6_32/lib" with the lib address and directory that contains your NetCDF library (file ''libnetcdf.a'').
* Replace "/distrib/local/netcdf/pgi_7.1-6_32/include" with the address of the directory that contains the NetCDF include file (''netcdf.inc'').
* You can mess with the compiling options but it is not mandatory.

Once the script is compiled, copy it in the same directory as your '''.nc''' file and run

<syntaxhighlight lang="bash">
./streamfunction.e
</syntaxhighlight>
The script will ask you for the name of your '''.nc''' file, and will run and produce a new '''nameofyourfile_stream.nc''' file.

'''Be careful''' : In this new file, all fields are temporally and zonally averaged.

If you want to use '''python''' instead of '''fortran''', you can take a look at this [https://github.com/aymeric-spiga/dynanalysis repo]. It hosts a tool to perform dynamical analysis of GCM simulations (and therefore, it computes the mass stream function and a lot of other stuff), but it is tailored for Dynamico only.

== Continuing Simulations ==

At the end of a simulation, the model generates restart files (files 'restart.nc' and 'restartfi.nc') which contain the final state of the model. The 'restart.nc' and 'restartfi.nc' files have the same format as the 'start.nc' and 'startfi.nc' files, respectively.

These files can in fact be used as initial states to continue the simulation, using the following renaming command lines:

<syntaxhighlight lang="bash">
mv restart.nc start.nc
mv restartfi.nc startfi.nc
</syntaxhighlight>

Running a simulation with these start files will in fact resume the simulation from where the previous run ended.

=== bash scripts ===

We have set up very simple bash scripts to automatize the launching of chain simulations. Here is an example of bash script that does the job:

<syntaxhighlight lang="bash">
#!/bin/bash
###########################################################################
# Script to perform several chained LMD Mars GCM simulations
# SET HERE the maximum total number of simulations

nummax=100

###########################################################################

echo "---------------------------------------------------------"
echo "STARTING LOOP RUN"
echo "---------------------------------------------------------"

dir=`pwd`
machine=`hostname`
address=`whoami`

# Look for file "num_run" which should contain
# the value of the previously computed season
# (defaults to 0 if file "num_run" does not exist)
if [[ -r num_run ]] ; then
echo "found file num_run"
numold=`cat num_run`
else
numold=0
fi
echo "numold is set to" ${numold}

# Set value of current season
(( numnew = ${numold} + 1 ))
echo "numnew is set to" ${numnew}

# Look for initialization data files (exit if none found)
if [[ ( -r start${numold}.nc && -r startfi${numold}.nc ) ]] ; then
\cp -f start${numold}.nc start.nc
\cp -f startfi${numold}.nc startfi.nc
else
if (( ${numold} == 99999 )) ; then
echo "No run because previous run crashed ! (99999 in num_run)"
exit
else
echo "Where is file start"${numold}".nc??"
exit
fi
fi

# Run GCM -- THIS LINE NEEDS TO BE MODIFIED WITH THE CORRECT GCM EXECUTION COMMAND
mpirun -np 8 gcm_64x48x26_phystd_para.e < diagfi.def > lrun${numnew}

# Check if run ended normaly and copy datafiles
if [[ ( -r restartfi.nc && -r restart.nc ) ]] ; then
echo "Run seems to have ended normaly"

\mv -f restart.nc start${numnew}.nc
\mv -f restartfi.nc startfi${numnew}.nc

else
if [[ -r num_run ]] ; then
\mv -f num_run num_run.crash
else
echo "No file num_run to build num_run.crash from !!"
# Impose a default value of 0 for num_run
echo 0 > num_run.crash
fi
echo 99999 > num_run
exit
fi

# Copy other datafiles that may have been generated
if [[ -r diagfi.nc ]] ; then
\mv -f diagfi.nc diagfi${numnew}.nc
fi
if [[ -r diagsoil.nc ]] ; then
\mv -f diagsoil.nc diagsoil${numnew}.nc
fi
if [[ -r stats.nc ]] ; then
\mv -f stats.nc stats${numnew}.nc
fi
if [[ -f profiles.dat ]] ; then
\mv -f profiles.dat profiles${numnew}.dat
\mv -f profiles.hdr profiles${numnew}.hdr
fi

# Prepare things for upcoming runs by writing
# value of computed season in file num_run
echo ${numnew} > num_run

# If we are over nummax : stop
if (( $numnew + 1 > $nummax )) ; then
exit
else
\cp -f run_gnome exe_mars
./exe_mars
fi

</syntaxhighlight>

Summary of what this bash script does,

* Bulleted list item

== Visualization software ==
=== Panoply ===
Panoply is a user-friendly tool for viewing raw NetCDF data, available here: https://www.giss.nasa.gov/tools/panoply/

[[File:Example panoply.png|thumb|Screenshot of panoply showing here LMD Generic results for the exoplanet TRAPPIST-1e]]

=== ncview ===
=== paraview ===
=== planetoplot ===
=== python scripts ===

TO BE COMPLETED

Profiling Method

2022-05-11T08:12:43Z

Guillaume.Chaverot:

If you want to do some profiling of the GCM (like knowing the time passed in each subroutine when running a simulation), here is a simple methodology to follow:

<ol>
<li> add the option -pg in the lines %BASE_FFLAGS and %BASE_LD of your arch.fcm file
<li> compile the GCM
<li> run your simulation ; after it is completed, you should have a binary file named gmon.out
<li> use the unix command gprof on your gcm executable, and write the output in a text file, for example:

<syntaxhighlight lang="bash">
gprof gcm.e > profiling.txt
</syntaxhighlight>

gprof will read the gmon.out file, and output profiling information. For more information on how to use gprof, type man gprof

You now have in your text file a lot of information on time used by the subroutines of the GCM code and their proportion to the whole run's duration. Especially, you have first the "Flat profile", which sorts the subroutines by their own time consumption ("self"):

<syntaxhighlight>
Flat profile:
Each sample counts as 0.01 seconds.
% cumulative self self total
time seconds seconds calls s/call s/call name
10.32 0.16 0.16 360 0.00 0.00 aerave_
7.74 0.28 0.12 60 0.00 0.00 lwxd_
...
</syntaxhighlight>

and second, the "Call graph", which displays the parents-children links between the subroutines, and sorts them by their "total" time (self+children).

<syntaxhighlight>
Call graph (explanation follows)
granularity: each sample hit covers 2 byte(s) for 0.65% of 1.55 seconds
index % time self children called name
0.00 1.55 1/1 main [2]
[1] 100.0 0.00 1.55 1 MAIN__ [1]
0.00 1.49 1/1 leapfrog_p_ [3]
0.00 0.04 1/1 filtreg_mod_mp_inifilr_ [30]
0.00 0.01 1/1 inidissip_ [75]
0.00 0.01 1/1 iniphysiq_mod_mp_iniphysiq_ [77]
0.00 0.00 1/1 conf_gcm_ [272]
0.00 0.00 1/1 parallel_lmdz_mp_init_parallel_ [355]
0.00 0.00 1/1 mod_const_mpi_mp_init_const_mpi_ [317]
0.00 0.00 1/1 bands_mp_read_distrib_ [250]
0.00 0.00 1/1 parallel_lmdz_mp_barrier_ [353]
0.00 0.00 1/1 bands_mp_set_bands_ [251]
0.00 0.00 1/1 bands_mp_writebands_ [252]
0.00 0.00 1/1 mod_hallo_mp_init_mod_hallo_ [321]
0.00 0.00 1/30 parallel_lmdz_mp_setdistrib_ [172]
0.00 0.00 1/1 cpdet_mod_mp_ini_cpdet_ [275]
0.00 0.00 1/1 infotrac_mp_infotrac_init_ [299]
0.00 0.00 1/1 dynetat0_ [287]
0.00 0.00 1/1 dynredem0_p_ [290]
0.00 0.00 1/1 iniconst_ [301]
0.00 0.00 1/1 inigeom_ [302]
-----------------------------------------------
...
</syntaxhighlight>

Finally, for nice profiling visualizations like call trees, you can use the python script from https://github.com/jrfonseca/gprof2dot

''From https://trac.lmd.jussieu.fr/Planeto/wiki/ProfilingMethod''

Profiling Method

2022-05-11T08:02:11Z

Guillaume.Chaverot:

If you want to do some profiling of the GCM (like knowing the time passed in each subroutine when running a simulation), here is a simple methodology to follow:

1) add the option -pg in the lines %BASE_FFLAGS and %BASE_LD of your arch.fcm file

2) compile the GCM

3) run your simulation ; after it is completed, you should have a binary file named gmon.out

4) use the unix command gprof on your gcm executable, and write the output in a text file, for example:

<syntaxhighlight lang="bash" line>
gprof gcm.e > profiling.txt
</syntaxhighlight>

gprof will read the gmon.out file, and output profiling information. For more information on how to use gprof, type man gprof

You now have in your text file a lot of information on time used by the subroutines of the GCM code and their proportion to the whole run's duration. Especially, you have first the "Flat profile", which sorts the subroutines by their own time consumption ("self"):

Flat profile:
Each sample counts as 0.01 seconds.
% cumulative self self total
time seconds seconds calls s/call s/call name
10.32 0.16 0.16 360 0.00 0.00 aerave_
7.74 0.28 0.12 60 0.00 0.00 lwxd_
...

and second, the "Call graph", which displays the parents-children links between the subroutines, and sorts them by their "total" time (self+children).

Call graph (explanation follows)
granularity: each sample hit covers 2 byte(s) for 0.65% of 1.55 seconds
index % time self children called name
0.00 1.55 1/1 main [2]
[1] 100.0 0.00 1.55 1 MAIN__ [1]
0.00 1.49 1/1 leapfrog_p_ [3]
0.00 0.04 1/1 filtreg_mod_mp_inifilr_ [30]
0.00 0.01 1/1 inidissip_ [75]
0.00 0.01 1/1 iniphysiq_mod_mp_iniphysiq_ [77]
0.00 0.00 1/1 conf_gcm_ [272]
0.00 0.00 1/1 parallel_lmdz_mp_init_parallel_ [355]
0.00 0.00 1/1 mod_const_mpi_mp_init_const_mpi_ [317]
0.00 0.00 1/1 bands_mp_read_distrib_ [250]
0.00 0.00 1/1 parallel_lmdz_mp_barrier_ [353]
0.00 0.00 1/1 bands_mp_set_bands_ [251]
0.00 0.00 1/1 bands_mp_writebands_ [252]
0.00 0.00 1/1 mod_hallo_mp_init_mod_hallo_ [321]
0.00 0.00 1/30 parallel_lmdz_mp_setdistrib_ [172]
0.00 0.00 1/1 cpdet_mod_mp_ini_cpdet_ [275]
0.00 0.00 1/1 infotrac_mp_infotrac_init_ [299]
0.00 0.00 1/1 dynetat0_ [287]
0.00 0.00 1/1 dynredem0_p_ [290]
0.00 0.00 1/1 iniconst_ [301]
0.00 0.00 1/1 inigeom_ [302]
-----------------------------------------------
...

5) for nice profiling visualizations, like call trees, you can use the python script from https://github.com/jrfonseca/gprof2dot

Profiling Method

2022-05-11T07:59:36Z

Guillaume.Chaverot: Created blank page