Miscellaneous hints

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,
mapper["inputs"].update(
   {**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.

This can be done by installing an alternative version of the CIF in a Python virtual environment

  • Get the code for the CIF version you want to install in a new directory, here cif-bis (two options):

    • Copy your CIF directory: cp -r cif/ cif-bis/

    • Clone the CIF repository: git clone git@gitlab.in2p3.fr:satinv/cif.git cif-bis (and checkout the desired branch/commit)

  • Create a Python virtual environment: python -m venv env-cif-bis. Here env-cif-bis is the virtual environment directory (you can choose any directory name or location)

  • Activate the virtual environment: source env-cif-bis/bin/activate. Now the commands python and pip refer to the virtual environment in env-cif-bis (at any point, to deactivate the virtual environment and go back to the usual python installation, use the command deactivate)

  • Install the alternative CIF version in the activated environment: cd cif-bis, pip install -e .

You now have two versions of pycif installed, one supposedly in your main python installation, and a new one in your env-cif-bis virtual environnement.

To use the new pycif version, you need to activate the virtual environment first:

source env-cif-bis/bin/activate
python -m pycif some-config-file.yaml
deactivate # Not strictly necessary

Note

You an check if everything went as intented by checking to which file the new pycif refers:

Activate the virtual environment (if not already activated): source env-cif-bis/bin/activate. Then run python and do:

>>> import pycif
>>> pycif.__file__
'/some/path/pycif/__init__.py'

The printed path should be in your virtual environment directory or in the new CIF directory (cif-bis in the example above) if you installed pycif in editable mode (with pip install -e .)

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.

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