pycif.plugins.models.satwetch4 — API reference

pycif.plugins.models.satwetch4 — API reference#

Configuration reference: satwetch4 plugin

pycif.plugins.models.satwetch4.ini_mapper.ini_mapper(model, general_mapper={}, backup_comps={}, transforms_order=[], ref_transform='', transform_name='', all_transforms=None, **kwargs)[source]#

Build the data-flow mapper for the SatWetCH4 bottom-up emission model.

Declares:

  • Inputs — soil temperature, inundated fraction, labile carbon, and model parameters (k, Q10) at the model’s configured input resolution.

  • Outputs — CH₄ wetland flux per time step.

Parameters:

  • model – SatWetCH4 plugin instance with all date arrays set.

  • general_mapper (dict) – unused.

  • backup_comps (dict) – unused.

  • transforms_order (list) – unused.

  • ref_transform (str) – unused.

  • transform_name (str) – unused.

  • all_transforms – unused.

  • **kwargs – unused.

Returns:

mapper with inputs, outputs, and outputs2inputs.

Return type:

dict

pycif.plugins.models.satwetch4.ini_periods.ini_periods(self, **kwargs)[source]#

The function ini_periods is optional but very recommended. It is used to define the temporal variables subsimu_dates, input_dates, tstep_dates and tstep_all. The function is automatically called at the initialization of the model class if available. If not available, the temporal variables should be defined manually in the ini_data function (not recommended).

ini_periods is a class method that applies to the model plugin itself. Therefore, the only expected argument is self.

def ini_periods(self, **kwargs):

    self.subsimu_dates = XXXX
    self.tstep_dates = XXXXX
    self.input_dates = XXXXX
    self.tstep_all = XXXXX
pycif.plugins.models.satwetch4.run.run(self, runsubdir, mode, workdir, ddi, nbproc=1, do_simu=True, approx_transf=False, ref_fwd_dir='', overlap=False, datastore=None, **kwargs)[source]#

Run the model in forward, tangent-linear or adjoint mode. This includes:

  • executing the model external executable

  • updating adj_refdir

  • moving files needed for chained simulations to f”{}/../”

Note

For model for which the adjoint is not coded, make sure to return a clear error if the run function is called in adj mode and with do_simu = True

Parameters:

  • self – the model Plugin

  • runsubdir (str) – working directory for the current run

  • mode (str) – forward or backward

  • workdir (str) – pyCIF working directory

  • do_simu (bool) – re-run or not existing simulation

pycif.plugins.models.satwetch4.io.native2inputs.native2inputs(self, datastore, input_type, datei, datef, runsubdir, mode='fwd', onlyinit=False, do_simu=True, check_transforms=False, **kwargs)[source]#

Converts data at the model data resolution stored in datastore to model compatible input files.

Native2inputs will be called for every couple component/tracer as defined in the mapper

Parameters:

  • self – the model Plugin

  • input_type (str) – the component name to be treated; please note that this information is redundant with the keys in datastore

  • datastore – data to convert

  • datei – date interval of the sub-simulation

  • datef – date interval of the sub-simulation

  • mode (str) – running mode: one of ‘fwd’, ‘adj’ and ‘tl’

  • runsubdir (str) – sub-directory for the current simulation

  • workdir (str) – the directory of the whole pyCIF simulation

Note

The format of datastore is a mixture of the model mapper and of the data format as defined here

For each component/tracer, the data itself is stored in the key data, and all the other keys come from the mapper, in case they are useful to dump inputs at the correct format

Note

If the input data was fully consistent with what the model expects, the data itself is not read by pyCIF. Instead, it is possible to directly link files defined by the key input_files (and defined in the fetch function of the corresponding flux plugin).

pycif.plugins.models.satwetch4.io.native2inputs_adj.native2inputs_adj(self, datastore, input_type, datei, datef, runsubdir, mode='fwd', check_transforms=False, **kwargs)[source]#

Read adjoint sensitivity and format them to pyCIF data format.

Warning

This function is used only when the adjoint of the model is available.

Parameters:

  • self – the model Plugin

  • input_type (str) – one of ‘flux’

  • datastore – data to convert if input_type == ‘flux’,

  • datei – date interval of the sub-simulation

  • datef – date interval of the sub-simulation

  • mode (str) – running mode: one of ‘fwd’, ‘adj’ and ‘tl’

  • runsubdir (str) – sub-directory for the current simulation

  • workdir (str) – the directory of the whole pyCIF simulation

pycif.plugins.models.satwetch4.io.outputs2native.outputs2native(self, data2dump, input_type, di, df, runsubdir, mode='fwd', onlyinit=False, check_transforms=False, **kwargs)[source]#

Reads outputs to pyCIF objects.

Parameters:

  • self – the model itself

  • data2dump (dict) – a dictionary with output data structure to be filled with correct data for every component/tracer

  • input_type (str) – the type of model outputs to be processed; this information is redundant with the components of the data2dump dictionary

  • di (datetime.datetime) – starting date of the present sub-simulation

  • df (datetime.datetime) – ending date of the present sub-simulation

  • runsubdir (str) – path to the present sub-simulation work directory

  • mode (str) – running mode; one of “fwd”, “tl” and “adj”

  • onlyinit (bool) – if True, means that the function is called during the initialization process of the observation vector

  • do_simu (bool) – if False, means that the observation vector is retrieving information from a previous existing run; in that case, it may not be necessary to dump files

Returns:

a dictionary with structure the components/tracers to be extracted

Return type:

dict

pycif.plugins.models.satwetch4.io.outputs2native_adj.outputs2native_adj(self, data2dump, input_type, di, df, runsubdir, mode='fwd', onlyinit=False, do_simu=True, check_transforms=False, **kwargs)[source]#

Dumps and/or save information about outputs, so the model knows where to extract information.

In the present template, observations are simply saved for later use by outputs2native. If the model needs information to extract concentration on-the-fly, the information in data2dump should be used. In particular, the columns i and j are the row and columns of each observation in the domain. The column tstep indicates on which time stamp the observation spans, relative to what is indicated in the variable output_intervals in ini_mapper.

The function is called by loadfromoutputs.adjoint.

Parameters:

  • self – the model itself

  • data2dump (dict) – a dictionary with concentration data for each component/tracer

  • input_type (str) – the type of model outputs to be processed; this information is redundant with the components of the data2dump dictionary

  • di (datetime.datetime) – starting date of the present sub-simulation

  • df (datetime.datetime) – ending date of the present sub-simulation

  • runsubdir (str) – path to the present sub-simulation work directory

  • mode (str) – running mode; one of “fwd”, “tl” and “adj”

  • onlyinit (bool) – if True, means that the function is called during the initialization process of the observation vector

  • do_simu (bool) – if False, means that the observation vector is retrieving information from a previous existing run; in that case, it may not be necessary to dump files

pycif.plugins.models.satwetch4.io.inputs.make_auxiliary.make_auxiliary(self, ddi, runsubdir, do_simu=True, mode='fwd', **kwargs)[source]#

Initialize every file or information needed by the model to run, excluding data that are initialized through the function native2inputs.

This includes name lists for Fortran, configuration files, etc.

Every basic files related to the model should be first initialized in self.workdir/model at the initialization step in the function compile.

Hereafter, files are link/copied to runsubdir from the reference ones in self.workdir/model

Note

For configuration files, one should follow the following basic rules:

  • paths expected by the model should always point to the current runsubdir; thus the executable should be linked or copied in runsubdir; in addition, every extra file should be link with a fixed name and the corresponding name should be given in the name-list or configuration file.

  • as many model parameters should be easily modified through the yaml configuration file; however, for some reasons, it may be preferable to limit the possibilities for pyCIF by keeping some parameters fixed; this question is up to the developer implementing one model

Parameters:

  • self – the model plugin

  • ddi (datetime.datetime) – the start data identifying the present simulation period

  • runsubdir (str) – path to the current sub-simulation work directory

  • do_simu (bool) – if False, the simulation does not need to be run, hence, in principle, no auxiliary data needs to be initialized

  • mode (str) – the running mode to compute