Miscellaneous hints

Debugging hints

Insert an interactive session within the code: the CIF will run till this point and then provide a prompt to the user. Use the two following lines:

import code
code.interact(local=dict(locals(), **globals()))

You are then in a python command-line environment at this point in the code e.g. all variables known at this point are accessible. To get back to the automatic running, ctrl-D XXXTO CHECKXXX

Inputs of a CTM

In the plugin dedicated to the model, in plugins/models/the_model, ini_mapper lists many dictionnaries used by the_model. Among them are the dictionnaries used for types or groups of inputs. Each dictionnary has a list of keys with the names of the input variables to finally write in the input files (done by the write.py function of the default plugin for each input type for the_model).

Example: for a CTM with emitted species,

emis = {
   ("flux", s): dict_surface
   for s in model.chemistry.emis_species.attributes

so that the dictionnay contains the list of emitted species as retrieved from information obtained previously, here in the chemical scheme’s relevant file.

To add a type of inputs, add the definition of the matching dictionnary and add it to the inputs’ list.

Example: for a CTM with 5 types of inputs,
   {**emis, **inicond, **prescrcond, **prodloss3d, **photj})

It may be required to treat inputs which are not (or should not) be accessible to users e.g. mandatory variables never to be modified.

Example: for LMDz, the chemistry data must include pressure “pmid” and temperature “temp” fields.

In this case, the keys of the matching dictionnary must be explicitely hard-written in ini_mapper.

Example: for a CTM with chemical inputs, some of which depend on the chemical scheme chosen by the user and others are mandatory,
# list of Js from chemical scheme + 2 mandatory variables
list_var = [ j[1][1] for j in model.chemistry.photo_rates.iterrows() ]+ [ 'pmid', 'temp' ]
# make a dictionnary out of it
photj = {
    ("kinetic", l): dict_ini
     for l in list_var

To simply access a dictionnary, declare it in ini_mapper e.g. “model.photj = photj”

Running two versions of the CIF

It can be useful to install a version of the CIF for running simulations while working on developments in another version simultaneously.

From an installation with only one CIF already installed in a git directory:

  • in the directory of the CIF, remove *egg-info

  • in $HOME/.local/lib/python3.7/site-packages/, remove *pyCIF*egg*

  • uninstall the CIF (in its directory, python setup.py develop --user -u)

  • always in the same first CIF directory, install the version chosen for debug/developments (git pull of the chosen version and python setup.py develop --user)

  • get the version for computing in a new directory: git clone git@gitlab.in2p3.fr:satinv/cif.git $HOME/cif-for-prod/ and chose the right branch

  • in this new directory:

    1. in setup.py, line 64, change the name of the CIF (original: pyCIF)

    2. change the name of the directory where the sources are (original: pycif)

    3. run the usual install

Quick check of a datastore file

To make a quick check in interctive mode of a CIF monitor file, launch a python or an ipython session and import the required plugins as in the following example:

from pycif.utils.datastores import dump
ds = dump.read_datastore('monitor.nc')

The datastore file, here monitor.nc, is stored as a dataframe, here ds.