iode.Identities

class iode.Identities

IODE Identities database.

Parameters:

filepath: str, optional: file containing the IODE identities to load.

Returns:

Identities

Examples

>>> from iode import identities, SAMPLE_DATA_DIR
>>> identities.load(f"{SAMPLE_DATA_DIR}/fun.idt")
>>> len(identities)
48
>>> identities              
Workspace: Identities
nb identities: 48
filename: ...\tests\data\fun.idt

 name                                                   identities
AOUC        ((WCRH/QL)/(WCRH/QL)[1990Y1])*(VAFF/(VM+VAFF))[-1]+PM*(VM/(VM+VAFF))[-1]
AOUC_       exp(ln(((WCF/NFYH)/QL)+PKF/(QAFF/KNFFY))*(QAFF/(QX+QAFF)+.05)[-1]+ln PM*(QM/ (QAFF+QM)-0.05)[-1])
FLGR        FLG/VBBP
GAP2        100*(QAFF_/(Q_F+Q_I))
GAP_        100*((QAF_/Q_F)-1)
...         ...
XTFP        grt TFPFHP_
XW          0
Y           QBBP_P
YSEFPR      YSEFP/WBGP
YSFICR      YSFIC/(TWGP*ZJ)

Attributes:

filename: str
description: str

Methods

`clear`(self)	Delete all objects from the current database.
`copy`(self)	Create a copy of an IODE database.
`copy_from`(self, input_files[, objects_names])	Copy (a subset of) objects from the input file(s) 'input_files' into the current database.
`execute`(self[, identities, from_period, ...])	Execute the specified identity(ies).
`from_series`(self, s)	Copy the pandas Series s into the IODE Identities database.
`get_names`(self[, pattern])	Returns the list of objects names given a pattern.
`is_copy_subset`(self)	Whether or not the present object represents of a subset of a global IODE database and if the IODE objects of the subset represent deep copies of the IODE objects from the global IODE database.
`is_subset`(self)	Whether or not the present object represents a subset of a global IODE database.
`load`(self, filepath)	Load objects stored in file 'filepath' into the current database.
`merge`(self, other[, overwrite])
`merge_from`(self, input_file)	Merge all objects stored in the input file 'input_file' into the current database.
`remove`(self, names)	Delete the object(s) named 'names' from the current database.
`rename`(self, old_name, new_name)	Rename an object of the database.
`save`(self, filepath)	Save objects of the current database into the file 'filepath'.
`search`(self, pattern[, word, ...])	Return a list of all objects from the current database having a specific pattern in their names or LEC expression, comment...
`to_series`(self)	Create a pandas Series from the current Identities database.

__init__(*args, **kwargs)

Methods

`__init__`(args, *kwargs)
`clear`(self)	Delete all objects from the current database.
`copy`(self)	Create a copy of an IODE database.
`copy_from`(self, input_files[, objects_names])	Copy (a subset of) objects from the input file(s) 'input_files' into the current database.
`execute`(self[, identities, from_period, ...])	Execute the specified identity(ies).
`from_series`(self, s)	Copy the pandas Series s into the IODE Identities database.
`get_names`(self[, pattern])	Returns the list of objects names given a pattern.
`is_copy_subset`(self)	Whether or not the present object represents of a subset of a global IODE database and if the IODE objects of the subset represent deep copies of the IODE objects from the global IODE database.
`is_subset`(self)	Whether or not the present object represents a subset of a global IODE database.
`load`(self, filepath)	Load objects stored in file 'filepath' into the current database.
`merge`(self, other[, overwrite])
`merge_from`(self, input_file)	Merge all objects stored in the input file 'input_file' into the current database.
`remove`(self, names)	Delete the object(s) named 'names' from the current database.
`rename`(self, old_name, new_name)	Rename an object of the database.
`save`(self, filepath)	Save objects of the current database into the file 'filepath'.
`search`(self, pattern[, word, ...])	Return a list of all objects from the current database having a specific pattern in their names or LEC expression, comment...
`to_series`(self)	Create a pandas Series from the current Identities database.

Attributes

`description`	description: str
`filename`	filename: str
`names`	names: List[str]
`series`	series: Series