pycontrails.Model

class pycontrails.Model(met=None, params=None, **params_kwargs)

Bases: ABC

Base class for physical models.

Implementing classes must implement the eval() method

__init__(met=None, params=None, **params_kwargs)

Methods

__init__([met, params])

downselect_met()

Downselect met domain to the max/min bounds of source.

eval([source])

Abstract method to handle evaluation.

get_source_param(key[, default, set_attr])

Get source data with default set by parameter key.

require_met()

Ensure that met is a MetDataset.

require_source_type(type_)

Ensure that source is type_.

set_source([source])

Attach original or copy of input source to source.

set_source_met([optional, variable])

Ensure or interpolate each required met_variables on source .

transfer_met_source_attrs([source])

Transfer met source metadata from met to source.

update_params([params])

Update model parameters on params.

Attributes

params

Instantiated model parameters, in dictionary form

met

Meteorology data

source

Data evaluated in model

hash

Generate a unique hash for model instance.

interp_kwargs

Shortcut to create interpolation arguments from params.

long_name

Get long name descriptor, annotated on xr.DataArray outputs.

met_required

Require meteorology is not None on __init__()

name

class`Flight`.

met_variables

Required meteorology pressure level variables.

processed_met_variables

Set of required parameters if processing already complete on met input.

optional_met_variables

Optional meteorology variables
default_params

alias of ModelParams

downselect_met()

Downselect met domain to the max/min bounds of source.

Override this method if special handling is needed in met down-selection.

  • source must be defined before calling downselect_met().

  • This method copies and re-assigns met using met.copy() to avoid side-effects.

Raises:
abstract eval(source=None, **params)

Abstract method to handle evaluation.

Implementing classes should override call signature to overload source inputs and model outputs.

Parameters:

  • source (ModelInput, optional) – Dataset defining coordinates to evaluate model. Defined by implementing class, but must be a subset of ModelInput. If None, met is assumed to be evaluation points.

  • **params (Any) – Overwrite model parameters before evaluation.

Returns:

ModelOutput – Return type depends on implementing model

get_source_param(key, default=<object object>, *, set_attr=True)

Get source data with default set by parameter key.

Retrieves data with the following hierarchy:

  1. source.data[key]. Returns np.ndarray | xr.DataArray.

  2. source.attrs[key]

  3. params[key]

  4. default

In case 3., the value of params[key] is attached to source.attrs[key].

Parameters:

  • key (str) – Key to retrieve

  • default (Any, optional) – Default value if key is not found.

  • set_attr (bool, optional) – If True (default), set source.attrs[key] to params[key] if found. This allows for better post model evaluation tracking.

Returns:

Any – Value(s) found for key in source data, source attrs, or model params

Raises:

KeyError – Raises KeyError if key is not found in any location and default is not provided.

See also

-

property hash

Generate a unique hash for model instance.

Returns:

str – Unique hash for model instance (sha1)

property interp_kwargs

Shortcut to create interpolation arguments from params.

The output of this is useful for passing to interpolate_met().

Returns:

dict[str, Any] – Dictionary with keys

  • ”method”

  • ”bounds_error”

  • ”fill_value”

  • ”localize”

  • ”use_indices”

  • ”q_method”

as determined by params.

abstract property long_name

Get long name descriptor, annotated on xr.DataArray outputs.

met

Meteorology data

met_required = False

Require meteorology is not None on __init__()

met_variables

Required meteorology pressure level variables. Each element in the list is a MetVariable or a tuple[MetVariable]. If element is a tuple[MetVariable], the variable depends on the data source. Only one variable in the tuple is required.

abstract property name

class`Flight`.

Type:

Get model name for use as a data key in xr.DataArray or

optional_met_variables

Optional meteorology variables

params

Instantiated model parameters, in dictionary form

processed_met_variables

Set of required parameters if processing already complete on met input.

require_met()

Ensure that met is a MetDataset.

Returns:

MetDataset – Returns reference to met. This is helpful for type narrowing met when meteorology is required.

Raises:

ValueError – Raises when met is None.

require_source_type(type_)

Ensure that source is type_.

Returns:

_Source – Returns reference to source. This is helpful for type narrowing source to specific type(s).

Raises:

ValueError – Raises when source is not _type_.

set_source(source=None)

Attach original or copy of input source to source.

Parameters:

source (MetDataset | GeoVectorDataset | Flight | Iterable[Flight] | None) – Parameter source passed in eval(). If None, an empty MetDataset with coordinates like met is set to source.

See also

-

meth:eval

set_source_met(optional=False, variable=None)

Ensure or interpolate each required met_variables on source .

For each variable in met_variables, check source for data variable with the same name.

For GeoVectorDataset sources, try to interpolate met if variable does not exist.

For MetDataset sources, try to get data from met if variable does not exist.

Parameters:
Raises:
source

Data evaluated in model

transfer_met_source_attrs(source=None)

Transfer met source metadata from met to source.

update_params(params=None, **params_kwargs)

Update model parameters on params.

Parameters:

  • params (dict[str, Any], optional) – Model parameters to update, as dictionary. Defaults to {}

  • **params_kwargs (Any) – Override keys in params with keyword arguments.