`tsdat.config.variable_definition`¶

Module Contents¶

Classes¶

`VarKeys`	Class that provides a handle for keys in the variables section of the
`VarInputKeys`	Class that provides a handle for keys in the variable input section of
`ConverterKeys`	Class that provides a handle for keys in the converter section of
`VarInput`	Class to explicitly encode fields set by the variable’s input source
`VariableDefinition`	Class to encode variable definitions from the config file. Also provides

class tsdat.config.variable_definition.VarKeys¶

Class that provides a handle for keys in the variables section of the pipeline config file.

INPUT = input¶

DIMS = dims¶

TYPE = type¶

ATTRS = attrs¶

class tsdat.config.variable_definition.VarInputKeys¶

Class that provides a handle for keys in the variable input section of the pipeline config file.

NAME = name¶

CONVERTER = converter¶

UNITS = units¶

REQUIRED = required¶

class tsdat.config.variable_definition.ConverterKeys¶

Class that provides a handle for keys in the converter section of the pipeline config file.

CLASSNAME = classname¶

PARAMETERS = parameters¶

class tsdat.config.variable_definition.VarInput(dictionary: Dict, defaults: Union[Dict, None] = None)¶

Class to explicitly encode fields set by the variable’s input source defined by the yaml file.

Parameters

dictionary (Dict) – The dictionary entry corresponding with a variable’s input section from the config file.
defaults (Dict, optional) – The default input parameters, defaults to {}

is_required(self) → bool¶

class tsdat.config.variable_definition.VariableDefinition(name: str, dictionary: Dict, available_dimensions: Dict[str, tsdat.config.dimension_definition.DimensionDefinition], defaults: Union[Dict, None] = None)¶

Class to encode variable definitions from the config file. Also provides a few utility methods.

Parameters

name (str) – The name of the variable in the output file.
dictionary (Dict) – The dictionary entry corresponding with this variable in the config file.

:param: available_dimensions: A mapping of dimension name to DimensionDefinition objects.

Parameters: defaults (Dict, optional) – The defaults to use when instantiating this VariableDefinition object, defaults to {}.

_parse_input(self, dictionary: Dict, defaults: Union[Dict, None] = None) → VarInput ¶

Parses the variable’s input property, if it has one, from the variable dictionary.

Parameters

dictionary (Dict) – The dictionary entry corresponding with this variable in the config file.
defaults (Dict, optional) – The defaults to use when instantiating the VariableDefinition object, defaults to {}.

Returns

A VarInput object for this VariableDefinition, or None.

Return type

VarInput

_parse_attributes(self, dictionary: Dict, defaults: Union[Dict, None] = None) → Dict[str, Any]¶

Parses the variable’s attributes from the variable dictionary.

Parameters

dictionary (Dict) – The dictionary entry corresponding with this variable in the config file.
defaults (Dict, optional) – The defaults to use when instantiating the VariableDefinition object, defaults to {}.

Returns

A mapping of attribute name to attribute value.

Return type

Dict[str, Any]

_parse_dimensions(self, dictionary: Dict, available_dimensions: Dict[str, tsdat.config.dimension_definition.DimensionDefinition], defaults: Union[Dict, None] = None) → Dict[str, tsdat.config.dimension_definition.DimensionDefinition]¶

Parses the variable’s dimensions from the variable dictionary.

Parameters

dictionary (Dict) – The dictionary entry corresponding with this variable in the config file.
available_dimensions – A mapping of dimension name to DimensionDefinition.
defaults (Dict, optional) – The defaults to use when instantiating the VariableDefinition object, defaults to {}.

Returns

A mapping of dimension name to DimensionDefinition objects.

Return type

Dict[str, DimensionDefinition]

_parse_data_type(self, dictionary: Dict, defaults: Union[Dict, None] = None) → object¶

Parses the data_type string and returns the appropriate numpy data type (i.e. “float” -> np.float).

Parameters

dictionary (Dict) – The dictionary entry corresponding with this variable in the config file.
defaults (Dict, optional) – The defaults to use when instantiating the VariableDefinition object, defaults to {}.

Raises

KeyError – Raises KeyError if the data type in the dictionary does not match a valid data type.

Returns

The numpy data type corresponding with the type provided in the yaml file, or data_type if the provided data_type is not in the ME Data Standards list of data types.

Return type

object

add_fillvalue_if_none(self, attributes: Dict[str, Any]) → Dict[str, Any]¶

Adds the _FillValue attribute to the provided attributes dictionary if the _FillValue attribute has not already been defined and returns the modified attributes dictionary.

Parameters: attributes (Dict[str, Any]) – The dictionary containing user-defined variable attributes.
Returns: The dictionary containing user-defined variable attributes. Is guaranteed to have a _FillValue attribute.
Return type: Dict[str, Any]

is_constant(self) → bool¶

Returns True if the variable is a constant. A variable is constant if it does not have any dimensions.

Returns: True if the variable is constant, False otherwise.
Return type: bool

is_predefined(self) → bool¶

Returns True if the variable’s data was predefined in the config yaml file.

Returns: True if the variable is predefined, False otherwise.
Return type: bool

is_coordinate(self) → bool¶

Returns True if the variable is a coordinate variable. A variable is defined as a coordinate variable if it is dimensioned by itself.

Returns: True if the variable is a coordinate variable, False otherwise.
Return type: bool

is_derived(self) → bool¶

Return True if the variable is derived. A variable is derived if it does not have an input and it is not predefined.

Returns: True if the Variable is derived, False otherwise.
Return type: bool

has_converter(self) → bool¶

Returns True if the variable has an input converter defined, False otherwise.

Returns: True if the Variable has a converter defined, False otherwise.
Return type: bool

is_required(self) → bool¶

Returns True if the variable has the ‘required’ property defined and the ‘required’ property evaluates to True. A required variable is a variable which much be retrieved in the input dataset. If a required variable is not in the input dataset, the process should crash.

Returns: True if the variable is required, False otherwise.
Return type: bool

has_input(self) → bool¶

Return True if the variable is copied from an input dataset, regardless of whether or not unit and/or naming conversions should be applied.

Returns: True if the Variable has an input defined, False otherwise.
Return type: bool

get_input_name(self) → str¶

Returns the name of the variable in the input if defined, otherwise returns None.

Returns: The name of the variable in the input, or None.
Return type: str

get_input_units(self) → str¶

If the variable has input, returns the units of the input variable or the output units if no input units are defined.

Returns: The units of the input variable data.
Return type: str

get_output_units(self) → str¶

Returns the units of the output data or None if no units attribute has been defined.

Returns: The units of the output variable data.
Return type: str

get_coordinate_names(self) → List[str]¶

Returns the names of the coordinate VariableDefinition(s) that this VariableDefinition is dimensioned by.

Returns: A list of dimension/coordinate variable names.
Return type: List[str]

get_shape(self) → Tuple[int]¶

Returns the shape of the data attribute on the VariableDefinition.

Raises: KeyError – Raises a KeyError if the data attribute has not been set yet.
Returns: The shape of the VariableDefinition’s data, or None.
Return type: Tuple[int]

get_data_type(self) → numpy.dtype¶

Retrieves the variable’s data type.

Returns: Returns the data type of the variable’s data as a numpy dtype.
Return type: np.dtype

get_FillValue(self) → int¶

Retrieves the variable’s _FillValue attribute, using -9999 as a default if it has not been defined.

Returns: Returns the variable’s _FillValue.
Return type: int

run_converter(self, data: numpy.ndarray) → numpy.ndarray¶

If the variable has an input converter, runs the input converter for the input/output units on the provided data.

Parameters: data (np.ndarray) – The data to be converted.
Returns: Returns the data after it has been run through the variable’s converter.
Return type: np.ndarray

to_dict(self) → Dict¶

Returns the Variable as a dictionary to be used to intialize an empty xarray Dataset or DataArray.

Returns a dictionary like (Example is for temperature):

{
    "dims": ["time"],
    "data": [],
    "attrs": {"units": "degC"}
}

Returns: A dictionary representation of the variable.
Return type: Dict

tsdat.config.variable_definition¶

Module Contents¶

Classes¶

`tsdat.config.variable_definition`¶