import sys
import warnings
from pathlib import Path
from typing import Union, Tuple, List, Dict, Optional, Any
if sys.version_info.minor >= 11:
from typing import Self
else:
Self = Any
import pandas as pd
from iode.common import EqTest, PrintEquationsAs, PrintEquationsLecAs
from iode.time.period import Period
from iode.util import join_lines, table2str, JUSTIFY
from iode.iode_database.abstract_database import IodeDatabase, PositionalIndexer
from iode.objects.equation import Equation
from iode.util import suppress_msgs, enable_msgs
from iode.iode_cython import Equations as CythonEquations
EquationInput = Union[str, Dict[str, Any], Equation]
[docs]
class Equations(IodeDatabase):
r"""
IODE Equations database.
Attributes
----------
filename: str
description: str
Parameters
----------
filepath: str, optional
file containing the IODE equations to load.
Returns
-------
Equations
Examples
--------
>>> from iode import equations, SAMPLE_DATA_DIR
>>> equations.load(f"{SAMPLE_DATA_DIR}/fun.eqs") # doctest: +ELLIPSIS, +NORMALIZE_WHITESPACE
Loading .../fun.eqs
274 objects loaded
>>> len(equations)
274
>>> equations # doctest: +ELLIPSIS, +NORMALIZE_WHITESPACE
Workspace: Equations
nb equations: 274
filename: ...\tests\data\fun.eqs
<BLANKLINE>
name lec method sample block fstat r2adj dw loglik date
ACAF (ACAF/VAF[-1]) :=acaf1+acaf2*GOSF[-1]+ acaf4*(TIME=1995) LSQ 1980Y1:1996Y1 ACAF 32.2732 0.7963 2.3293 83.8075 12-06-1998
ACAG ACAG := ACAG[-1]+r VBBP[-1]+(0.006*VBBP[-1]*(TIME=2001)-0.008*(TIME=2008)) LSQ None ACAG 0.0000 0.0000 0.0000 0.0000
AOUC AOUC:=((WCRH/QL)/(WCRH/QL)[1990Y1])*(VAFF/(VM+VAFF))[-1]+PM*(VM/(VAFF+VM))[-1] LSQ None AOUC 0.0000 0.0000 0.0000 0.0000
BENEF d BENEF :=d(VBNP-(IT+ITCEE)+SUB-DPUU-(WCF+SSFFIC+WDOM+WBG+ YN)-(GOSH-DPUH+IDH)-DTF-RIDGG+YIDG) LSQ None BENEF 0.0000 0.0000 0.0000 0.0000
BQY BQY:=(YK+YN)/PBBP LSQ None BQY 0.0000 0.0000 0.0000 0.0000
... ... ... ... ... ... ... ... ... ...
YSSF dln YSSF:=dln WBF_ LSQ None YSSF 0.0000 0.0000 0.0000 0.0000
YSSG YSSG := SSF+SSH-(YSSF+COTRES) LSQ None YSSG 0.0000 0.0000 0.0000 0.0000
ZF grt ZF :=grt PC+ZX-0.05*grt PME LSQ None ZF 0.0000 0.0000 0.0000 0.0000
ZJ grt ZJ :=grt PC +ZX-0.05*grt PME LSQ None ZJ 0.0000 0.0000 0.0000 0.0000
ZZF_ ZZF_ := ZZF_[-1] LSQ None ZZF_ 0.0000 0.0000 0.0000 0.0000
<BLANKLINE>
"""
[docs]
def __init__(self, filepath: str=None):
raise TypeError("This class cannot be instantiated directly.")
@classmethod
def get_instance(cls) -> Self:
instance = cls.__new__(cls)
instance._cython_instance = CythonEquations()
return instance
def _load(self, filepath: str):
self._cython_instance._load(filepath)
def _subset(self, pattern: str, copy: bool) -> Self:
instance = Equations.get_instance()
instance._cython_instance = self._cython_instance.initialize_subset(instance._cython_instance, pattern, copy)
return instance
def get_lec(self, key: Union[str, int]) -> str:
r"""
Get the LEC of an equation in the database.
Parameters
----------
key : str or int
Name or index of the equation in the database.
Returns
-------
str
Examples
--------
>>> from iode import equations, SAMPLE_DATA_DIR
>>> equations.load(f"{SAMPLE_DATA_DIR}/fun.eqs") # doctest: +ELLIPSIS, +NORMALIZE_WHITESPACE
Loading .../fun.eqs
274 objects loaded
>>> equations.get_lec("ACAF") # doctest: +NORMALIZE_WHITESPACE
'(ACAF/VAF[-1]) :=acaf1+acaf2*GOSF[-1]+\nacaf4*(TIME=1995)'
>>> equations.get_lec(0) # doctest: +NORMALIZE_WHITESPACE
'(ACAF/VAF[-1]) :=acaf1+acaf2*GOSF[-1]+\nacaf4*(TIME=1995)'
"""
name = self._single_object_key_to_name(key)
if not name in self:
raise KeyError(f"Name '{name}' not found in the {type(self).__name__} workspace")
return self._cython_instance.get_lec(name)
@property
def i(self) -> PositionalIndexer:
r"""
Allow to select the ith equation in the database.
Examples
--------
>>> from iode import equations, SAMPLE_DATA_DIR
>>> equations.load(f"{SAMPLE_DATA_DIR}/fun.eqs") # doctest: +ELLIPSIS, +NORMALIZE_WHITESPACE
Loading .../fun.eqs
274 objects loaded
>>> # get the first equation
>>> equations.i[0] # doctest: +NORMALIZE_WHITESPACE
Equation(endogenous = 'ACAF',
lec = '(ACAF/VAF[-1]) :=acaf1+acaf2*GOSF[-1]+\nacaf4*(TIME=1995)',
method = 'LSQ',
from_period = '1980Y1',
to_period = '1996Y1',
block = 'ACAF',
tests = {corr = 1,
dw = 2.32935,
fstat = 32.2732,
loglik = 83.8075,
meany = 0.00818467,
r2 = 0.821761,
r2adj = 0.796299,
ssres = 5.19945e-05,
stderr = 0.00192715,
stderrp = 23.5458,
stdev = 0.0042699},
date = '12-06-1998')
>>> # get the last equation
>>> equations.i[-1] # doctest: +NORMALIZE_WHITESPACE
Equation(endogenous = 'ZZF_',
lec = 'ZZF_ := ZZF_[-1]',
method = 'LSQ',
comment = ' ',
block = 'ZZF_')
>>> # update first equation
>>> equations.i[0] = "(ACAF/VAF[-1]) := acaf1 + acaf2 * GOSF[-1] + acaf4*(TIME=1995)"
>>> equations.i[0] # doctest: +NORMALIZE_WHITESPACE
Equation(endogenous = 'ACAF',
lec = '(ACAF/VAF[-1]) := acaf1 + acaf2 * GOSF[-1] + acaf4*(TIME=1995)',
method = 'LSQ',
from_period = '1980Y1',
to_period = '1996Y1',
block = 'ACAF')
>>> # update last equation
>>> equations.i[-1] = "ZZF_ := ZZF_[-1] + 1"
>>> equations.i[-1] # doctest: +NORMALIZE_WHITESPACE
Equation(endogenous = 'ZZF_',
lec = 'ZZF_ := ZZF_[-1] + 1',
method = 'LSQ',
comment = ' ',
block = 'ZZF_')
"""
return PositionalIndexer(self)
def _get_object(self, key: Union[str, int]) -> Equation:
name = self._single_object_key_to_name(key)
if not name in self:
raise KeyError(f"Name '{name}' not found in the {type(self).__name__} workspace")
eq = Equation.get_instance()
eq._cython_instance = self._cython_instance._get_object(name, eq._cython_instance)
return eq
def _set_object(self, key: Union[str, int], value):
name = self._single_object_key_to_name(key)
if isinstance(value, pd.Series):
value = value.to_dict()
# update existing equation
if name in self:
if isinstance(value, str):
equation = self._get_object(name)
equation.lec = value
elif isinstance(value, Equation):
equation = value
elif isinstance(value, dict):
equation = self._get_object(name)
if 'lec' in value:
equation.lec = value.pop('lec')
if 'method' in value:
equation.method = value.pop('method')
if 'sample' in value:
equation.sample = value.pop('sample')
if 'comment' in value:
equation.comment = value.pop('comment')
if 'instruments' in value:
equation.instruments = value.pop('instruments')
if 'block' in value:
equation.block = value.pop('block')
if 'tests' in value:
warnings.warn(f"Cannot update equation '{name}': 'tests' cannot be updated manually. Skipped new values.")
del value['tests']
if 'date' in value:
warnings.warn(f"Cannot update equation '{name}': 'date' cannot be updated manually. Skipped new value.")
del value['date']
if len(value):
raise ValueError(f"Cannot update equation '{name}': only 'lec', 'method', 'sample', 'comment', "
f"'instruments' and 'block' keys are accepted. "
f"Got unknown key(s): {';'.join(value.keys())}")
else:
raise TypeError(f"Cannot update equation '{name}': Expected input to be of type str or dict or Equation. "
f"Got value of type {type(value).__name__}")
# add a new equation
else:
if isinstance(value, str):
equation = Equation(endogenous=name, lec=value.strip())
elif isinstance(value, Equation):
equation = value
elif isinstance(value, (tuple, list)):
value = [name] + list(value)
equation = Equation(*value)
elif isinstance(value, dict):
value['endogenous'] = name
equation = Equation(**value)
else:
raise TypeError(f"Cannot add equation '{name}': Expected input to be of type str or tuple or list or "
f"dict or Equation. Got value of type {type(value).__name__}")
self._cython_instance._set_object(name, equation._cython_instance)
[docs]
def __getitem__(self, key: Union[str, List[str]]) -> Union[Equation, Self]:
r"""
Return the (subset of) equation(s) referenced by `key`.
The `key` can represent a single object name (e.g. "ACAF") or a list of object names ("ACAF;ACAG;AOUC")
or a pattern (e.g. "A*") or a list of sub-patterns (e.g. "A*;*_").
If the `key` represents a list of object names or of sub-patterns, each name or sub-pattern is separated
by a `separator` character which is either a whitespace ` `, or a comma `,`, or a semi-colon `;`, or a
tabulation `\t`, or a newline `\n`.
A (sub-)`pattern` is a list of characters representing a group of object names.
It includes some special characters which have a special meaning:
- `*` : any character sequence, even empty
- `?` : any character (one and only one)
- `@` : any alphanumerical char [A-Za-z0-9]
- `&` : any non alphanumerical char
- `|` : any alphanumeric character or none at the beginning and end of a string
- `!` : any non-alphanumeric character or none at the beginning and end of a string
- `\` : escape the next character
Note that the `key` can contain references to IODE lists which are prefixed with the symbol `$`.
Parameters
----------
key: str or list(str)
(the list of) name(s) of the equation(s) to get.
The list of equations to get can be specified by a pattern or by a list of sub-patterns (e.g. "A*;*_").
Returns
-------
Single equation or a subset of the database.
Examples
--------
>>> from iode import SAMPLE_DATA_DIR
>>> from iode import equations
>>> equations.load(f"{SAMPLE_DATA_DIR}/fun.eqs") # doctest: +ELLIPSIS, +NORMALIZE_WHITESPACE
Loading .../fun.eqs
274 objects loaded
>>> # a) get one equation
>>> equations["ACAF"] # doctest: +NORMALIZE_WHITESPACE
Equation(endogenous = 'ACAF',
lec = '(ACAF/VAF[-1]) :=acaf1+acaf2*GOSF[-1]+\nacaf4*(TIME=1995)',
method = 'LSQ',
from_period = '1980Y1',
to_period = '1996Y1',
block = 'ACAF',
tests = {corr = 1,
dw = 2.32935,
fstat = 32.2732,
loglik = 83.8075,
meany = 0.00818467,
r2 = 0.821761,
r2adj = 0.796299,
ssres = 5.19945e-05,
stderr = 0.00192715,
stderrp = 23.5458,
stdev = 0.0042699},
date = '12-06-1998')
>>> # b) get a subset of the Equations database using a pattern
>>> equations_subset = equations["A*"]
>>> equations_subset.names
['ACAF', 'ACAG', 'AOUC']
>>> # c) get a subset of the Equations database using a list of names
>>> equations_subset = equations[["ACAF", "AOUC", "BQY", "BVY"]]
>>> equations_subset.names
['ACAF', 'AOUC', 'BQY', 'BVY']
"""
return super().__getitem__(key)
[docs]
def __setitem__(self, key: Union[str, List[str]], value: Union[str, Equation, Dict[str, Any], List[Union[str, Equation, Dict[str, Any]]]]):
r"""
Update/add a (subset of) equation(s) referenced by `key` from/to the Equations database.
The `key` can represent a single object name (e.g. "ACAF") or a list of object names ("ACAF;ACAG;AOUC")
or a pattern (e.g. "A*") or a list of sub-patterns (e.g. "A*;*_").
If the `key` represents a list of object names or of sub-patterns, each name or sub-pattern is separated
by a `separator` character which is either a whitespace ` `, or a comma `,`, or a semi-colon `;`, or a
tabulation `\t`, or a newline `\n`.
A (sub-)`pattern` is a list of characters representing a group of object names.
It includes some special characters which have a special meaning:
- `*` : any character sequence, even empty
- `?` : any character (one and only one)
- `@` : any alphanumerical char [A-Za-z0-9]
- `&` : any non alphanumerical char
- `|` : any alphanumeric character or none at the beginning and end of a string
- `!` : any non-alphanumeric character or none at the beginning and end of a string
- `\` : escape the next character
Note that the `key` can contain references to IODE lists which are prefixed with the symbol `$`.
Parameters
----------
key: str or list(str)
(the list of) name(s) of the equation(s) to update/add.
The list of equations to update/add can be specified by a pattern or by a list of sub-patterns
(e.g. "A*;*_").
value: str or Equation or dict(str, ...) or pandas.DataFrame or Equations
If str, then it is interpreted as the LEC of the equation.
The key 'endogenous' is added automatically and does not need to be specified.
If pandas DataFrame, then only the columns 'endogenous', 'lec', 'method', 'sample', 'block',
'instruments' and 'comment' are used. The columns 'endogenous' and 'lec' are mandatory.
The tests values as well the (estimation) date of equations are set/updated when performing the estimation.
See Also
--------
iode.Equation
Examples
--------
>>> import pandas as pd
>>> from iode import SAMPLE_DATA_DIR
>>> from iode import equations, variables, Equation, EqMethod
>>> equations.load(f"{SAMPLE_DATA_DIR}/fun.eqs") # doctest: +ELLIPSIS, +NORMALIZE_WHITESPACE
Loading .../fun.eqs
274 objects loaded
>>> variables.load(f"{SAMPLE_DATA_DIR}/fun.var") # doctest: +ELLIPSIS, +NORMALIZE_WHITESPACE
Loading .../fun.var
394 objects loaded
>>> # a) add one equation
>>> equations["BDY"] = "BDY := YN - YK"
>>> equations["BDY"] # doctest: +NORMALIZE_WHITESPACE
Equation(endogenous = 'BDY',
lec = 'BDY := YN - YK',
method = 'LSQ',
from_period = '1960Y1',
to_period = '2015Y1')
>>> # b) update one equation
>>> equations["ACAF"] # doctest: +NORMALIZE_WHITESPACE
Equation(endogenous = 'ACAF',
lec = '(ACAF/VAF[-1]) :=acaf1+acaf2*GOSF[-1]+\nacaf4*(TIME=1995)',
method = 'LSQ',
from_period = '1980Y1',
to_period = '1996Y1',
block = 'ACAF',
tests = {corr = 1,
dw = 2.32935,
fstat = 32.2732,
loglik = 83.8075,
meany = 0.00818467,
r2 = 0.821761,
r2adj = 0.796299,
ssres = 5.19945e-05,
stderr = 0.00192715,
stderrp = 23.5458,
stdev = 0.0042699},
date = '12-06-1998')
>>> # update only the LEC
>>> equations["ACAF"] = "(ACAF/VAF[-1]) := acaf1 + acaf2 * GOSF[-1] + acaf4 * (TIME=1995)"
>>> equations["ACAF"] # doctest: +NORMALIZE_WHITESPACE
Equation(endogenous = 'ACAF',
lec = '(ACAF/VAF[-1]) := acaf1 + acaf2 * GOSF[-1] + acaf4 * (TIME=1995)',
method = 'LSQ',
from_period = '1980Y1',
to_period = '1996Y1',
block = 'ACAF')
>>> # update block and sample of a block of equations to estimation (dictionary)
>>> estim_sample = "2000Y1:2010Y1"
>>> block = "ACAF; ACAG; AOUC"
>>> for eq_name in block.split(';'):
... equations[eq_name] = {"sample": estim_sample, "block": block}
>>> (equations["ACAF"].sample, equations["ACAG"].sample, equations["AOUC"].sample)
(Sample("2000Y1:2010Y1"), Sample("2000Y1:2010Y1"), Sample("2000Y1:2010Y1"))
>>> (equations["ACAF"].block, equations["ACAG"].block, equations["AOUC"].block)
('ACAF; ACAG; AOUC', 'ACAF; ACAG; AOUC', 'ACAF; ACAG; AOUC')
>>> # update lec, method, sample and block
>>> equations["ACAF"].lec = "(ACAF/VAF[-1]) := acaf2 * GOSF[-1] + acaf4 * (TIME=1995)"
>>> equations["ACAF"].method = EqMethod.MAX_LIKELIHOOD
>>> # new equation sample is from 1990Y1 to 2015Y1
>>> equations["ACAF"].sample = "1990Y1:2015Y1"
>>> equations["ACAF"].block = "ACAF"
>>> equations["ACAF"] # doctest: +NORMALIZE_WHITESPACE
Equation(endogenous = 'ACAF',
lec = '(ACAF/VAF[-1]) := acaf2 * GOSF[-1] + acaf4 * (TIME=1995)',
method = 'MAX_LIKELIHOOD',
from_period = '1990Y1',
to_period = '2015Y1',
block = 'ACAF')
>>> # c) add/update several equations at once
>>> # 1) using a dict of values
>>> eq_ACAF = Equation("ACAF", "(ACAF/VAF[-1]) :=acaf1+acaf2*GOSF[-1]+ acaf4*(TIME=1995)",
... method=EqMethod.ZELLNER, from_period='1980Y1', to_period='1996Y1')
>>> eq_ACAG = Equation("ACAG", "ACAG := ACAG[-1]+r VBBP[-1]+(0.006*VBBP[-1]*(TIME=2001)-0.008*(TIME=2008))",
... method=EqMethod.ZELLNER, from_period='1980Y1', to_period='1996Y1')
>>> eq_AOUC = Equation("AOUC", "AOUC:=((WCRH/QL)/(WCRH/QL)[1990Y1])*(VAFF/(VM+VAFF))[-1]+PM*(VM/(VAFF+VM))[-1]",
... method=EqMethod.ZELLNER, from_period='1980Y1', to_period='1996Y1')
>>> values = {"ACAF": eq_ACAF, "ACAG": eq_ACAG, "AOUC": eq_AOUC}
>>> equations["ACAF, ACAG, AOUC"] = values
>>> equations["ACAF, ACAG, AOUC"] # doctest: +ELLIPSIS, +NORMALIZE_WHITESPACE
Workspace: Equations
nb equations: 3
filename: ...fun.eqs
<BLANKLINE>
name lec method sample ...
ACAF (ACAF/VAF[-1]) :=acaf1+acaf2*GOSF[-1]+ acaf4*(TIME=1995) ZELLNER 1980Y1:1996Y1 ...
ACAG ACAG := ACAG[-1]+r VBBP[-1]+(0.006*VBBP[-1]*(TIME=2001)-0.008*(TIME=2008)) ZELLNER 1980Y1:1996Y1 ...
AOUC AOUC:=((WCRH/QL)/(WCRH/QL)[1990Y1])*(VAFF/(VM+VAFF))[-1]+PM*(VM/(VAFF+VM))[-1] ZELLNER 1980Y1:1996Y1 ...
<BLANKLINE>
>>> # 2) using a pandas DataFrame
>>> data = []
>>> data.append(["ACAF", "(ACAF/VAF[-1]) :=acaf1+acaf2*GOSF[-1]+ acaf4*(TIME=1995)", "GLS", '1980Y1:1996Y1'])
>>> data.append(["ACAG", "ACAG := ACAG[-1]+r VBBP[-1]+(0.006*VBBP[-1]*(TIME=2001)-0.008*(TIME=2008))", "GLS", '1980Y1:1996Y1'])
>>> data.append(["AOUC", "AOUC:=((WCRH/QL)/(WCRH/QL)[1990Y1])*(VAFF/(VM+VAFF))[-1]+PM*(VM/(VAFF+VM))[-1]", "GLS", '1980Y1:1996Y1'])
>>> df = pd.DataFrame(data, index=["ACAF", "ACAG", "AOUC"], columns=["endogenous", "lec", "method", "sample"])
>>> equations["ACAF, ACAG, AOUC"] = df
>>> equations["ACAF, ACAG, AOUC"] # doctest: +ELLIPSIS, +NORMALIZE_WHITESPACE
Workspace: Equations
nb equations: 3
filename: ...fun.eqs
<BLANKLINE>
name lec method sample ...
ACAF (ACAF/VAF[-1]) :=acaf1+acaf2*GOSF[-1]+ acaf4*(TIME=1995) GLS 1980Y1:1996Y1 ...
ACAG ACAG := ACAG[-1]+r VBBP[-1]+(0.006*VBBP[-1]*(TIME=2001)-0.008*(TIME=2008)) GLS 1980Y1:1996Y1 ...
AOUC AOUC:=((WCRH/QL)/(WCRH/QL)[1990Y1])*(VAFF/(VM+VAFF))[-1]+PM*(VM/(VAFF+VM))[-1] GLS 1980Y1:1996Y1 ...
<BLANKLINE>
>>> # 3) using another Equations database (subset)
>>> equations_subset = equations["ACAF, ACAG, AOUC"].copy()
>>> equations_subset["ACAF"].method = EqMethod.MAX_LIKELIHOOD
>>> equations_subset["ACAG"].method = EqMethod.MAX_LIKELIHOOD
>>> equations_subset["AOUC"].method = EqMethod.MAX_LIKELIHOOD
>>> equations["ACAF, ACAG, AOUC"] = equations_subset
>>> equations["ACAF, ACAG, AOUC"] # doctest: +ELLIPSIS, +NORMALIZE_WHITESPACE
Workspace: Equations
nb equations: 3
filename: ...fun.eqs
<BLANKLINE>
name lec method sample ...
ACAF (ACAF/VAF[-1]) :=acaf1+acaf2*GOSF[-1]+ acaf4*(TIME=1995) MAX_LIKELIHOOD 1980Y1:1996Y1 ...
ACAG ACAG := ACAG[-1]+r VBBP[-1]+(0.006*VBBP[-1]*(TIME=2001)-0.008*(TIME=2008)) MAX_LIKELIHOOD 1980Y1:1996Y1 ...
AOUC AOUC:=((WCRH/QL)/(WCRH/QL)[1990Y1])*(VAFF/(VM+VAFF))[-1]+PM*(VM/(VAFF+VM))[-1] MAX_LIKELIHOOD 1980Y1:1996Y1 ...
<BLANKLINE>
>>> # d) working on a subset
>>> # 1) get subset
>>> equations_subset = equations["A*"]
>>> equations_subset.names
['ACAF', 'ACAG', 'AOUC']
>>> # 2) add a equation to the subset
>>> equations_subset["AOUC_"] = "AOUC_ := ((WCRH/QL)/(WCRH/QL)[1990Y1]) * (VAFF/(VM+VAFF))[-1] + PM * (VM/(VAFF+VM))[-1]"
>>> equations_subset["AOUC_"] # doctest: +NORMALIZE_WHITESPACE
Equation(endogenous = 'AOUC_',
lec = 'AOUC_ := ((WCRH/QL)/(WCRH/QL)[1990Y1]) * (VAFF/(VM+VAFF))[-1] + PM * (VM/(VAFF+VM))[-1]',
method = 'LSQ',
from_period = '1960Y1',
to_period = '2015Y1')
>>> # --> new equation also appears in the global workspace
>>> "AOUC_" in equations
True
>>> equations["AOUC_"] # doctest: +NORMALIZE_WHITESPACE
Equation(endogenous = 'AOUC_',
lec = 'AOUC_ := ((WCRH/QL)/(WCRH/QL)[1990Y1]) * (VAFF/(VM+VAFF))[-1] + PM * (VM/(VAFF+VM))[-1]',
method = 'LSQ',
from_period = '1960Y1',
to_period = '2015Y1')
>>> # 3) update a equation in the subset
>>> equations_subset["AOUC_"] = "AOUC_ := ((WCRH/QL)/(WCRH/QL)[1990Y1]) * (VAFF/(VM+VAFF))[-1]"
>>> equations_subset["AOUC_"] # doctest: +NORMALIZE_WHITESPACE
Equation(endogenous = 'AOUC_',
lec = 'AOUC_ := ((WCRH/QL)/(WCRH/QL)[1990Y1]) * (VAFF/(VM+VAFF))[-1]',
method = 'LSQ',
from_period = '1960Y1',
to_period = '2015Y1')
>>> # --> equation is also updated in the global workspace
>>> equations["AOUC_"] # doctest: +NORMALIZE_WHITESPACE
Equation(endogenous = 'AOUC_',
lec = 'AOUC_ := ((WCRH/QL)/(WCRH/QL)[1990Y1]) * (VAFF/(VM+VAFF))[-1]',
method = 'LSQ',
from_period = '1960Y1',
to_period = '2015Y1')
"""
super().__setitem__(key, value)
[docs]
def __delitem__(self, key):
r"""
Remove the (subset of) equation(s) referenced by `key` from the Equations database.
Parameters
----------
key: str or list(str)
(list of) name(s) of the equation(s) to be removed.
The list of names can be given as a string pattern (e.g. "A*;*_").
Examples
--------
>>> from iode import SAMPLE_DATA_DIR
>>> from iode import equations
>>> equations.load(f"{SAMPLE_DATA_DIR}/fun.eqs") # doctest: +ELLIPSIS, +NORMALIZE_WHITESPACE
Loading .../fun.eqs
274 objects loaded
>>> # a) delete one equation
>>> equations.get_names("A*")
['ACAF', 'ACAG', 'AOUC']
>>> del equations["ACAF"]
>>> equations.get_names("A*")
['ACAG', 'AOUC']
>>> # b) delete several equations at once using a pattern
>>> del equations["A*"]
>>> equations.get_names("A*")
[]
>>> # c) delete several equations at once using a list of names
>>> equations.get_names("B*")
['BENEF', 'BQY', 'BRUGP', 'BVY']
>>> del equations[["BENEF", "BQY"]]
>>> equations.get_names("B*")
['BRUGP', 'BVY']
>>> # delete one equation from a subset of the global database
>>> equations_subset = equations["D*"]
>>> equations_subset.names
['DEBT', 'DPU', 'DPUF', 'DPUG', 'DPUGO', 'DPUH', 'DPUU', 'DTF', 'DTH', 'DTH1', 'DTH1C']
>>> del equations_subset["DPUGO"]
>>> equations_subset.names
['DEBT', 'DPU', 'DPUF', 'DPUG', 'DPUH', 'DPUU', 'DTF', 'DTH', 'DTH1', 'DTH1C']
>>> # NOTE: the equation has also been deleted from the global database
>>> "DPUGO" in equations
False
>>> equations.get_names("D*")
['DEBT', 'DPU', 'DPUF', 'DPUG', 'DPUH', 'DPUU', 'DTF', 'DTH', 'DTH1', 'DTH1C']
"""
super().__delitem__(key)
@property
def coefficients(self) -> List[str]:
r"""
Return the list of coefficients (scalars) used in the equations of
(the subset of) the database.
Examples
--------
>>> from iode import SAMPLE_DATA_DIR
>>> from iode import equations
>>> equations.load(f"{SAMPLE_DATA_DIR}/fun.eqs") # doctest: +ELLIPSIS, +NORMALIZE_WHITESPACE
Loading .../fun.eqs
274 objects loaded
>>> equations["A*"].coefficients
['acaf1', 'acaf2', 'acaf4']
"""
return super()._coefficients()
@property
def variables(self) -> List[str]:
r"""
Return the list of variables used in the equations of (the subset of) the database.
Examples
--------
>>> from iode import SAMPLE_DATA_DIR
>>> from iode import equations
>>> equations.load(f"{SAMPLE_DATA_DIR}/fun.eqs") # doctest: +ELLIPSIS, +NORMALIZE_WHITESPACE
Loading .../fun.eqs
274 objects loaded
>>> equations["A*"].variables
['ACAF', 'ACAG', 'AOUC', 'GOSF', 'PM', 'QL', 'TIME', 'VAF', 'VAFF', 'VBBP', 'VM', 'WCRH']
"""
return super()._variables()
[docs]
def estimate(self, from_period: Union[str, Period]=None, to_period: Union[str, Period]=None,
list_eqs: Union[str, List[str]]=None, quiet: bool=False) -> bool:
r"""
Estimate an equation or a block of equations.
At the end of the estimation process, certain variables and scalars are automatically created
if the process has converged. These variables and scalars can be used for computational purposes and,
as they are part of the global workspace, can be saved for future use.
The tests resulting from the last estimation are saved as scalars. The same applies to residuals,
left-hand and right-hand members of equations.
Saved tests (as scalars) have the following names (`e<ith>_*` for the <ith> equation of the block):
- `e<ith>_n` : number of sample periods
- `e<ith>_k` : number of estimated coefficients
- `e<ith>_stdev` : std dev of residuals
- `e<ith>_meany` : mean of Y
- `e<ith>_ssres` : sum of squares of residuals
- `e<ith>_stderr` : std error
- `e<ith>_stderrp` : std error percent (in %)
- `e<ith>_fstat` : F-Stat
- `e<ith>_r2` : R square
- `e<ith>_r2adj` : adjusted R-squared
- `e<ith>_dw` : Durbin-Watson
- `e<ith>_loglik` : Log Likelihood
Calculated series are saved in special variables:
- `_YCALC<i>` : right-hand side of the <ith> equation in the block
- `_YOBS<i>` : left-hand side of the <ith> equation in the block
- `_YRES<i>` : residuals of the <ith> equation of the block
Outside the estimation sample, the series values are :math:`NA`.
Parameters
----------
from_period : str or Period, optional
The starting period of the execution range.
Defaults to the starting period of the current Variables sample.
to_period : str or Period, optional
The ending period of the execution range.
Defaults to the ending period of the current Variables sample.
list_eqs: str or list(str), optional
List of equations to be estimated.
If not provided, all equations of the present Equations database will be estimated.
Default to None (all equations).
quiet : bool, optional
If True, suppresses the log messages during the estimation process
Default to False.
Returns
-------
bool
True if the estimation process has converged, False otherwise.
Warnings
--------
If some equations to be estimated belongs to a same block, the *block* (:meth:`Equation.block`),
*method* (:meth:`Equation.method`), and *instruments* (':meth:`Equation.instruments`) of each of
them must have been updated before.
Examples
--------
>>> from iode import SAMPLE_DATA_DIR, equations, scalars, variables
>>> equations.load(f"{SAMPLE_DATA_DIR}/fun.eqs") # doctest: +ELLIPSIS, +NORMALIZE_WHITESPACE
Loading .../fun.eqs
274 objects loaded
>>> variables.load(f"{SAMPLE_DATA_DIR}/fun.var") # doctest: +ELLIPSIS, +NORMALIZE_WHITESPACE
Loading .../fun.var
394 objects loaded
>>> equations["ACAF"].lec
'(ACAF/VAF[-1]) :=acaf1+acaf2*GOSF[-1]+\nacaf4*(TIME=1995)'
>>> equations["DPUH"].lec
'dln (DPUH/DPUHO):=dpuh_1+dpuh_2*dln(IHU/PI5)+dln PC'
>>> # create scalars
>>> scalars["acaf1"] = 0., 1.
>>> scalars["acaf2"] = 0., 1.
>>> scalars["acaf4"] = 0., 1.
>>> scalars["dpuh_1"] = 0., 1.
>>> scalars["dpuh_2"] = 0., 1.
>>> # estimate an equation
>>> success = equations.estimate("1980Y1", "1996Y1", "ACAF") # doctest: +NORMALIZE_WHITESPACE
Estimating : iteration 1 (||eps|| = 0.173205)
<BLANKLINE>
Estimating : iteration 2 (||eps|| = 5.16075e-09)
<BLANKLINE>
Solution reached after 2 iteration(s). Creating results file ...
<BLANKLINE>
>>> success
True
>>> # or equivalenty
>>> success = equations["ACAF"].estimate("1980Y1", "1996Y1") # doctest: +NORMALIZE_WHITESPACE
Estimating : iteration 1 (||eps|| = 7.05003e-13)
<BLANKLINE>
Solution reached after 1 iteration(s). Creating results file ...
<BLANKLINE>
>>> scalars["acaf1"]
Scalar(0.0157705, 1, 0.00136949)
>>> scalars["acaf2"]
Scalar(-7.96505e-06, 1, 1.48247e-06)
>>> scalars["acaf4"]
Scalar(-0.0085027, 1, 0.00208257)
>>> scalars["dpuh_1"]
Scalar(0, 1, na)
>>> scalars["dpuh_2"]
Scalar(0, 1, na)
>>> equations["ACAF"] # doctest: +ELLIPSIS, +NORMALIZE_WHITESPACE
Equation(endogenous = 'ACAF',
lec = '(ACAF/VAF[-1]) :=acaf1+acaf2*GOSF[-1]+\nacaf4*(TIME=1995)',
method = 'LSQ',
from_period = '1980Y1',
to_period = '1996Y1',
block = 'ACAF',
tests = {corr = 1,
dw = 2.33007,
fstat = 32.2851,
loglik = 83.8101,
meany = 0.00818467,
r2 = 0.821815,
r2adj = 0.79636,
ssres = 5.19787e-05,
stderr = 0.00192685,
stderrp = 23.5422,
stdev = 0.0042699},
date = '...')
>>> # observed values (left hand side of the equation)
>>> variables["_YOBS0", "1980Y1:1996Y1"] # doctest: +ELLIPSIS, +NORMALIZE_WHITESPACE
Workspace: Variables
nb variables: 1
filename: ...fun.var
description: Modèle fun - Simulation 1
sample: 1980Y1:1996Y1
mode: LEVEL
<BLANKLINE>
name 1980Y1 1981Y1 1982Y1 ... 1994Y1 1995Y1 1996Y1
_YOBS0 0.01 0.02 0.01 ... 0.00 -0.00 0.01
<BLANKLINE>
>>> # fitted values (right hand side of the equation)
>>> variables["_YCALC0", "1980Y1:1996Y1"] # doctest: +ELLIPSIS, +NORMALIZE_WHITESPACE
Workspace: Variables
nb variables: 1
filename: ...fun.var
description: Modèle fun - Simulation 1
sample: 1980Y1:1996Y1
mode: LEVEL
<BLANKLINE>
name 1980Y1 1981Y1 1982Y1 ... 1994Y1 1995Y1 1996Y1
_YCALC0 0.01 0.01 0.01 ... 0.01 -0.00 0.00
<BLANKLINE>
>>> # residuals values
>>> variables["_YRES0", "1980Y1:1996Y1"] # doctest: +ELLIPSIS, +NORMALIZE_WHITESPACE
Workspace: Variables
nb variables: 1
filename: ...fun.var
description: Modèle fun - Simulation 1
sample: 1980Y1:1996Y1
mode: LEVEL
<BLANKLINE>
name 1980Y1 1981Y1 1982Y1 ... 1994Y1 1995Y1 1996Y1
_YRES0 -0.00 0.00 -0.00 ... -0.00 0.00 0.00
<BLANKLINE>
>>> # estimate a block
>>> # prepare equations (same block and method)
>>> block = "ACAF;DPUH"
>>> for name in block.split(";"):
... equations[name] = {"block": block, "method": "LSQ"}
>>> success = equations.estimate("1980Y1", "1996Y1", block) # doctest: +ELLIPSIS, +NORMALIZE_WHITESPACE
Estimating : iteration 1 (||eps|| = 0.141421)
<BLANKLINE>
Estimating : iteration 2 (||eps|| = 1.522e-12)
<BLANKLINE>
Solution reached after 2 iteration(s). Creating results file ...
<BLANKLINE>
Estimating : iteration 1 (||eps|| = 4.34603e-12)
<BLANKLINE>
Solution reached after 1 iteration(s). Creating results file ...
<BLANKLINE>
>>> success
True
>>> scalars["acaf1"]
Scalar(0.0157705, 1, 0.00136079)
>>> scalars["acaf2"]
Scalar(-7.96505e-06, 1, 1.47188e-06)
>>> scalars["acaf4"]
Scalar(-0.0085027, 1, 0.00206603)
>>> scalars["dpuh_1"]
Scalar(0.0109855, 1, 0.00481857)
>>> scalars["dpuh_2"]
Scalar(0.0574893, 1, 0.0368951)
>>> equations["ACAF"] # doctest: +ELLIPSIS, +NORMALIZE_WHITESPACE
Equation(endogenous = 'ACAF',
lec = '(ACAF/VAF[-1]) :=acaf1+acaf2*GOSF[-1]+\nacaf4*(TIME=1995)',
method = 'LSQ',
from_period = '1980Y1',
to_period = '1996Y1',
block = 'ACAF;DPUH',
tests = {corr = 1,
dw = 2.33007,
fstat = 32.2851,
loglik = 83.8101,
meany = 0.00818467,
r2 = 0.821815,
r2adj = 0.79636,
ssres = 5.19787e-05,
stderr = 0.00192685,
stderrp = 23.5422,
stdev = 0.0042699},
date = '...')
>>> # observed values for ACAF
>>> variables["_YOBS0", "1980Y1:1996Y1"] # doctest: +ELLIPSIS, +NORMALIZE_WHITESPACE
Workspace: Variables
nb variables: 1
filename: ...fun.var
description: Modèle fun - Simulation 1
sample: 1980Y1:1996Y1
mode: LEVEL
<BLANKLINE>
name 1980Y1 1981Y1 1982Y1 ... 1994Y1 1995Y1 1996Y1
_YOBS0 0.01 0.02 0.01 ... 0.00 -0.00 0.01
<BLANKLINE>
>>> # fitted values for ACAF
>>> variables["_YCALC0", "1980Y1:1996Y1"] # doctest: +ELLIPSIS, +NORMALIZE_WHITESPACE
Workspace: Variables
nb variables: 1
filename: ...fun.var
description: Modèle fun - Simulation 1
sample: 1980Y1:1996Y1
mode: LEVEL
<BLANKLINE>
name 1980Y1 1981Y1 1982Y1 ... 1994Y1 1995Y1 1996Y1
_YCALC0 0.01 0.01 0.01 ... 0.01 -0.00 0.00
<BLANKLINE>
>>> # residuals values for ACAF
>>> variables["_YRES0", "1980Y1:1996Y1"] # doctest: +ELLIPSIS, +NORMALIZE_WHITESPACE
Workspace: Variables
nb variables: 1
filename: ...fun.var
description: Modèle fun - Simulation 1
sample: 1980Y1:1996Y1
mode: LEVEL
<BLANKLINE>
name 1980Y1 1981Y1 1982Y1 ... 1994Y1 1995Y1 1996Y1
_YRES0 -0.00 0.00 -0.00 ... -0.00 -0.00 0.00
<BLANKLINE>
>>> equations["DPUH"] # doctest: +ELLIPSIS, +NORMALIZE_WHITESPACE
Equation(endogenous = 'DPUH',
lec = 'dln (DPUH/DPUHO):=dpuh_1+dpuh_2*dln(IHU/PI5)+dln PC',
method = 'LSQ',
from_period = '1980Y1',
to_period = '1996Y1',
block = 'ACAF;DPUH',
tests = {corr = 0.126096,
dw = 3.15593,
fstat = 3.51611,
loglik = 43.5743,
meany = 0.0505132,
r2 = 0.189895,
r2adj = 0.135888,
ssres = 0.00591031,
stderr = 0.01985,
stderrp = 39.2966,
stdev = 0.0213538},
date = '...')
>>> # observed values for DPUH
>>> variables["_YOBS1", "1980Y1:1996Y1"] # doctest: +ELLIPSIS, +NORMALIZE_WHITESPACE
Workspace: Variables
nb variables: 1
filename: ...fun.var
description: Modèle fun - Simulation 1
sample: 1980Y1:1996Y1
mode: LEVEL
<BLANKLINE>
name 1980Y1 1981Y1 1982Y1 ... 1994Y1 1995Y1 1996Y1
_YOBS1 0.06 0.09 0.07 ... 0.04 0.04 0.01
<BLANKLINE>
>>> # fitted values for DPUH
>>> variables["_YCALC1", "1980Y1:1996Y1"] # doctest: +ELLIPSIS, +NORMALIZE_WHITESPACE
Workspace: Variables
nb variables: 1
filename: ...fun.var
description: Modèle fun - Simulation 1
sample: 1980Y1:1996Y1
mode: LEVEL
<BLANKLINE>
name 1980Y1 1981Y1 1982Y1 ... 1994Y1 1995Y1 1996Y1
_YCALC1 0.07 0.06 0.08 ... 0.04 0.03 0.03
<BLANKLINE>
>>> # residuals values for DPUH
>>> variables["_YRES1", "1980Y1:1996Y1"] # doctest: +ELLIPSIS, +NORMALIZE_WHITESPACE
Workspace: Variables
nb variables: 1
filename: ...fun.var
description: Modèle fun - Simulation 1
sample: 1980Y1:1996Y1
mode: LEVEL
<BLANKLINE>
name 1980Y1 1981Y1 1982Y1 ... 1994Y1 1995Y1 1996Y1
_YRES1 -0.01 0.02 -0.02 ... -0.00 0.01 -0.03
<BLANKLINE>
"""
try:
if quiet:
suppress_msgs()
success = self._cython_instance.estimate(from_period, to_period, list_eqs)
if quiet:
enable_msgs()
return success
except Exception as e:
if quiet:
enable_msgs()
raise e
[docs]
def copy_from(self, input_files: Union[str, List[str]], names: Union[str, List[str]]='*'):
r"""
Copy (a subset of) equations from the input file(s) 'input_files' into the current database.
Parameters
----------
input_file: str or list(str)
file(s) from which the copied equations are read.
names: str or list(str)
list of equations to copy from the input file(s).
Defaults to load all equations from the input file(s).
"""
input_files, names = self._copy_from(input_files, names)
self._cython_instance.copy_from(input_files, names)
def from_series(self, s: pd.Series):
r"""
Copy the pandas Series `s` into the IODE Equations database.
The equation names to copy are deduced from the index of the Series.
Parameters
----------
s: Series
pandas Series containing the equations as LEC expressions to copy into the Equations database.
All other Equation attributes (method, sample, comment, block, ...) will be set to their default
values (see :class:`Equation`).
Notes
-----
The index of the passed Series is sorted in alphabetical order before
copying to IODE Equations database.
See Also
--------
Equations.from_frame
Equations.to_frame
Examples
--------
>>> from iode import equations, variables
>>> import pandas as pd
>>> variables.clear()
>>> variables.sample = "1960Y1:2015Y1"
>>> equations.clear()
>>> len(equations)
0
>>> # create the pandas Series
>>> data = {"A": "A := t",
... "B": "B := grt A",
... "C": "C := exp t",
... "D": "ln D := t",
... "E": "1/E := B",
... "F": "d(F) := t + 1"}
>>> s = pd.Series(data)
>>> # display the pandas series
>>> s # doctest: +NORMALIZE_WHITESPACE
A A := t
B B := grt A
C C := exp t
D ln D := t
E 1/E := B
F d(F) := t + 1
dtype: object
>>> # load into the IODE Equations database
>>> equations.from_series(s)
>>> len(equations)
6
>>> equations.names
['A', 'B', 'C', 'D', 'E', 'F']
>>> equations["A"] # doctest: +NORMALIZE_WHITESPACE
Equation(endogenous = 'A',
lec = 'A := t',
method = 'LSQ',
from_period = '1960Y1',
to_period = '2015Y1')
>>> equations["F"] # doctest: +NORMALIZE_WHITESPACE
Equation(endogenous = 'F',
lec = 'd(F) := t + 1',
method = 'LSQ',
from_period = '1960Y1',
to_period = '2015Y1')
"""
if not (self.is_global_workspace or self.is_detached):
# check that all names in the pandas object are present in the current subset
self._check_same_names(self.names, s.index.tolist())
for index, value in s.items():
self._set_object(index, value)
[docs]
def from_frame(self, df: pd.DataFrame):
r"""
Copy the pandas DataFrame `df` into the IODE Equations database.
The equation names to copy are deduced from the index of the DataFrame.
Parameters
----------
df: DataFrame
pandas DataFrame containing the equations to copy into the Equations database.
The passed DataFrame must at least contains:
- an index containing the names of the equations
- a column labeled 'lec' containing the LEC expressions of the equations.
Other possible columns are 'method', 'sample', 'comment', 'instruments' and 'block'
(see :class:`Equation`).
Notes
-----
The index of the passed DataFrame is sorted in alphabetical order before
copying to IODE Equations database.
See Also
--------
Equations.from_series
Equations.to_frame
Examples
--------
>>> from iode import equations, variables
>>> import pandas as pd
>>> import numpy as np
>>> variables.clear()
>>> variables.sample = "1960Y1:2015Y1"
>>> equations.clear()
>>> len(equations)
0
>>> # create the pandas DataFrame
>>> columns=["lec", "method", "sample", "corr", "fstat", "r2", "date"]
>>> data = {"A": ["A := t", "LSQ", "1980Y1:2010Y1", 1.0, 0.79, 0.05, "12-06-1998"],
... "B": ["B := grt A", "LSQ", "1980Y1:2010Y1", 1.0, 0.896, 0.15, "12-06-1998"],
... "C": ["C := exp t", "ZELLNER", "1990Y1:", 1.0, 0.1258, 0.0225, ""],
... "D": ["ln D := t", "MAX_LIKELIHOOD", "", 1.0, 0.358, 0.0698, "12-06-1998"],
... "E": ["1/E := B", "LSQ", ":2010Y1", 1.0, 0.689, 2.23e-03, ""],
... "F": ["d(F) := t + 1", "GLS", "", 1.0, 0.05, 4.568e-04, ""]}
>>> df = pd.DataFrame.from_dict(data, orient='index', columns=columns)
>>> # display the pandas series
>>> df # doctest: +NORMALIZE_WHITESPACE
lec method sample ... fstat r2 date
A A := t LSQ 1980Y1:2010Y1 ... 0.7900 0.050000 12-06-1998
B B := grt A LSQ 1980Y1:2010Y1 ... 0.8960 0.150000 12-06-1998
C C := exp t ZELLNER 1990Y1: ... 0.1258 0.022500
D ln D := t MAX_LIKELIHOOD ... 0.3580 0.069800 12-06-1998
E 1/E := B LSQ :2010Y1 ... 0.6890 0.002230
F d(F) := t + 1 GLS ... 0.0500 0.000457
<BLANKLINE>
[6 rows x 7 columns]
>>> # load into the IODE Equations database
>>> equations.from_frame(df)
>>> len(equations)
6
>>> equations.names
['A', 'B', 'C', 'D', 'E', 'F']
>>> df.loc["A"] # doctest: +NORMALIZE_WHITESPACE
lec A := t
method LSQ
sample 1980Y1:2010Y1
corr 1.0
fstat 0.79
r2 0.05
date 12-06-1998
Name: A, dtype: object
>>> equations["A"] # doctest: +NORMALIZE_WHITESPACE
Equation(endogenous = 'A',
lec = 'A := t',
method = 'LSQ',
from_period = '1980Y1',
to_period = '2010Y1',
tests = {corr = 1,
dw = 0,
fstat = 0.79,
loglik = 0,
meany = 0,
r2 = 0.05,
r2adj = 0,
ssres = 0,
stderr = 0,
stderrp = 0,
stdev = 0},
date = '12-06-1998')
>>> df.loc["F"] # doctest: +NORMALIZE_WHITESPACE
lec d(F) := t + 1
method GLS
sample
corr 1.0
fstat 0.05
r2 0.000457
date
Name: F, dtype: object
>>> equations["F"] # doctest: +NORMALIZE_WHITESPACE
Equation(endogenous = 'F',
lec = 'd(F) := t + 1',
method = 'GLS',
from_period = '1960Y1',
to_period = '2015Y1',
tests = {corr = 1,
dw = 0,
fstat = 0.05,
loglik = 0,
meany = 0,
r2 = 0.0004568,
r2adj = 0,
ssres = 0,
stderr = 0,
stderrp = 0,
stdev = 0})
"""
if not (self.is_global_workspace or self.is_detached):
# check that all names in the pandas object are present in the current subset
self._check_same_names(self.names, df.index.to_list())
if 'lec' not in df.columns:
raise ValueError("Expected at least one column with name 'lec'. "
f"Got dataframe with column names {df.columns.to_list()}")
if len(df.columns) == 1:
self.from_series(df['lec'])
else:
test_names = [member.name.lower() for member in EqTest]
for row in df.itertuples(name='Equation'):
args = row._asdict()
# note: equation name = endogenous variable
endogenous = args.pop('Index')
if 'endogenous' in args:
if args['endogenous'] != endogenous:
raise ValueError(f"Mismatch between equation name '{endogenous}' and "
f"its endogenous variable name '{args['endogenous']}'")
del args['endogenous']
sample = args.pop('sample', '')
if ':' not in sample:
from_period, to_period = '', ''
else:
from_period, to_period = sample.split(":")
args["from_period"] = from_period
args["to_period"] = to_period
# date and tests cannot be set by the users
date = args.pop('date', '')
test_values = [args.pop(test_name, 0.0) for test_name in test_names]
equation = Equation(endogenous, **args)
equation._set_tests_from_list(test_values)
equation._set_date(date)
self._set_object(endogenous, equation)
[docs]
def to_frame(self) -> pd.DataFrame:
r"""
Create a pandas DataFrame from the current Equations database.
The index of the returned DataFrame is build from the Equations names.
See Also
--------
Equations.from_series
Equations.from_frame
Examples
--------
>>> from iode import SAMPLE_DATA_DIR, equations
>>> import pandas as pd
>>> equations.load(f"{SAMPLE_DATA_DIR}/fun.eqs") # doctest: +ELLIPSIS, +NORMALIZE_WHITESPACE
Loading .../fun.eqs
274 objects loaded
>>> len(equations)
274
>>> # Export the IODE Equations database as a pandas DataFrame
>>> df = equations.to_frame()
>>> len(df)
274
>>> df.index.to_list() # doctest: +ELLIPSIS
['ACAF', 'ACAG', 'AOUC', ..., 'YSSG', 'ZF', 'ZJ', 'ZZF_']
>>> equations["ACAF"] # doctest: +NORMALIZE_WHITESPACE
Equation(endogenous = 'ACAF',
lec = '(ACAF/VAF[-1]) :=acaf1+acaf2*GOSF[-1]+\nacaf4*(TIME=1995)',
method = 'LSQ',
from_period = '1980Y1',
to_period = '1996Y1',
block = 'ACAF',
tests = {corr = 1,
dw = 2.32935,
fstat = 32.2732,
loglik = 83.8075,
meany = 0.00818467,
r2 = 0.821761,
r2adj = 0.796299,
ssres = 5.19945e-05,
stderr = 0.00192715,
stderrp = 23.5458,
stdev = 0.0042699},
date = '12-06-1998')
>>> df.loc["ACAF"] # doctest: +NORMALIZE_WHITESPACE
lec (ACAF/VAF[-1]) :=acaf1+acaf2*GOSF[-1]+\nacaf4*...
method LSQ
sample 1980Y1:1996Y1
comment
instruments
block ACAF
corr 1.0
stdev 0.00427
meany 0.008185
ssres 0.000052
stderr 0.001927
stderrp 23.545813
fstat 32.273193
r2 0.821761
r2adj 0.796299
dw 2.329346
loglik 83.807526
date 12-06-1998
Name: ACAF, dtype: object
>>> equations["YDH_"] # doctest: +NORMALIZE_WHITESPACE
Equation(endogenous = 'YDH_',
lec = 'grt YDH_ :=grt((WBU_+YN+GOSH_+IDH)-(SSF+SSH+DTH)+(SBH+OCUH))',
method = 'LSQ',
comment = ' ',
block = 'YDH_')
>>> df.loc["YDH_"] # doctest: +NORMALIZE_WHITESPACE
lec grt YDH_ :=grt((WBU_+YN+GOSH_+IDH)-(SSF+SSH+DT...
method LSQ
sample None
comment
instruments
block YDH_
corr 0.0
stdev 0.0
meany 0.0
ssres 0.0
stderr 0.0
stderrp 0.0
fstat 0.0
r2 0.0
r2adj 0.0
dw 0.0
loglik 0.0
date
Name: YDH_, dtype: object
>>> # Export a subset of the IODE Equations database as a pandas DataFrame
>>> df = equations["A*;*_"].to_frame()
>>> len(df)
29
>>> df.index.to_list() # doctest: +ELLIPSIS
['ACAF', 'ACAG', 'AOUC', ..., 'WNF_', 'YDH_', 'ZZF_']
>>> equations["ACAF"] # doctest: +NORMALIZE_WHITESPACE
Equation(endogenous = 'ACAF',
lec = '(ACAF/VAF[-1]) :=acaf1+acaf2*GOSF[-1]+\nacaf4*(TIME=1995)',
method = 'LSQ',
from_period = '1980Y1',
to_period = '1996Y1',
block = 'ACAF',
tests = {corr = 1,
dw = 2.32935,
fstat = 32.2732,
loglik = 83.8075,
meany = 0.00818467,
r2 = 0.821761,
r2adj = 0.796299,
ssres = 5.19945e-05,
stderr = 0.00192715,
stderrp = 23.5458,
stdev = 0.0042699},
date = '12-06-1998')
>>> df.loc["ACAF"] # doctest: +NORMALIZE_WHITESPACE
lec (ACAF/VAF[-1]) :=acaf1+acaf2*GOSF[-1]+\nacaf4*...
method LSQ
sample 1980Y1:1996Y1
comment
instruments
block ACAF
corr 1.0
stdev 0.00427
meany 0.008185
ssres 0.000052
stderr 0.001927
stderrp 23.545813
fstat 32.273193
r2 0.821761
r2adj 0.796299
dw 2.329346
loglik 83.807526
date 12-06-1998
Name: ACAF, dtype: object
>>> equations["YDH_"] # doctest: +NORMALIZE_WHITESPACE
Equation(endogenous = 'YDH_',
lec = 'grt YDH_ :=grt((WBU_+YN+GOSH_+IDH)-(SSF+SSH+DTH)+(SBH+OCUH))',
method = 'LSQ',
comment = ' ',
block = 'YDH_')
>>> df.loc["YDH_"] # doctest: +NORMALIZE_WHITESPACE
lec grt YDH_ :=grt((WBU_+YN+GOSH_+IDH)-(SSF+SSH+DT...
method LSQ
sample None
comment
instruments
block YDH_
corr 0.0
stdev 0.0
meany 0.0
ssres 0.0
stderr 0.0
stderrp 0.0
fstat 0.0
r2 0.0
r2adj 0.0
dw 0.0
loglik 0.0
date
Name: YDH_, dtype: object
"""
test_names = [member.name.lower() for member in EqTest]
dtype = {"lec": str, "method": str, "sample": str, "comment": str, "instruments": str, "block": str}
dtype.update({test_name: float for test_name in test_names})
dtype.update({"date": str})
# note: [:1] to skip endogenous value which is the same as name
data = {name: self._get_object(name)._as_tuple()[1:] for name in self.names}
return pd.DataFrame.from_dict(data, orient='index', columns=list(dtype.keys())).astype(dtype)
@property
def df(self) -> pd.DataFrame:
r"""
Create a pandas DataFrame from the current Equations database.
The index of the returned DataFrame is build from the Equations names.
See Also
--------
Equations.to_frame
Examples
--------
>>> from iode import SAMPLE_DATA_DIR, equations
>>> import pandas as pd
>>> equations.load(f"{SAMPLE_DATA_DIR}/fun.eqs") # doctest: +ELLIPSIS, +NORMALIZE_WHITESPACE
Loading .../fun.eqs
274 objects loaded
>>> len(equations)
274
>>> # Export the IODE Equations database as a pandas DataFrame
>>> df = equations.df
>>> len(df)
274
>>> df.index.to_list() # doctest: +ELLIPSIS
['ACAF', 'ACAG', 'AOUC', ..., 'YSSG', 'ZF', 'ZJ', 'ZZF_']
>>> equations["ACAF"] # doctest: +NORMALIZE_WHITESPACE
Equation(endogenous = 'ACAF',
lec = '(ACAF/VAF[-1]) :=acaf1+acaf2*GOSF[-1]+\nacaf4*(TIME=1995)',
method = 'LSQ',
from_period = '1980Y1',
to_period = '1996Y1',
block = 'ACAF',
tests = {corr = 1,
dw = 2.32935,
fstat = 32.2732,
loglik = 83.8075,
meany = 0.00818467,
r2 = 0.821761,
r2adj = 0.796299,
ssres = 5.19945e-05,
stderr = 0.00192715,
stderrp = 23.5458,
stdev = 0.0042699},
date = '12-06-1998')
>>> df.loc["ACAF"] # doctest: +NORMALIZE_WHITESPACE
lec (ACAF/VAF[-1]) :=acaf1+acaf2*GOSF[-1]+\nacaf4*...
method LSQ
sample 1980Y1:1996Y1
comment
instruments
block ACAF
corr 1.0
stdev 0.00427
meany 0.008185
ssres 0.000052
stderr 0.001927
stderrp 23.545813
fstat 32.273193
r2 0.821761
r2adj 0.796299
dw 2.329346
loglik 83.807526
date 12-06-1998
Name: ACAF, dtype: object
>>> equations["YDH_"] # doctest: +NORMALIZE_WHITESPACE
Equation(endogenous = 'YDH_',
lec = 'grt YDH_ :=grt((WBU_+YN+GOSH_+IDH)-(SSF+SSH+DTH)+(SBH+OCUH))',
method = 'LSQ',
comment = ' ',
block = 'YDH_')
>>> df.loc["YDH_"] # doctest: +NORMALIZE_WHITESPACE
lec grt YDH_ :=grt((WBU_+YN+GOSH_+IDH)-(SSF+SSH+DT...
method LSQ
sample None
comment
instruments
block YDH_
corr 0.0
stdev 0.0
meany 0.0
ssres 0.0
stderr 0.0
stderrp 0.0
fstat 0.0
r2 0.0
r2adj 0.0
dw 0.0
loglik 0.0
date
Name: YDH_, dtype: object
>>> # Export a subset of the IODE Equations database as a pandas DataFrame
>>> df = equations["A*;*_"].df
>>> len(df)
29
>>> df.index.to_list() # doctest: +ELLIPSIS
['ACAF', 'ACAG', 'AOUC', ..., 'WNF_', 'YDH_', 'ZZF_']
>>> equations["ACAF"] # doctest: +NORMALIZE_WHITESPACE
Equation(endogenous = 'ACAF',
lec = '(ACAF/VAF[-1]) :=acaf1+acaf2*GOSF[-1]+\nacaf4*(TIME=1995)',
method = 'LSQ',
from_period = '1980Y1',
to_period = '1996Y1',
block = 'ACAF',
tests = {corr = 1,
dw = 2.32935,
fstat = 32.2732,
loglik = 83.8075,
meany = 0.00818467,
r2 = 0.821761,
r2adj = 0.796299,
ssres = 5.19945e-05,
stderr = 0.00192715,
stderrp = 23.5458,
stdev = 0.0042699},
date = '12-06-1998')
>>> df.loc["ACAF"] # doctest: +NORMALIZE_WHITESPACE
lec (ACAF/VAF[-1]) :=acaf1+acaf2*GOSF[-1]+\nacaf4*...
method LSQ
sample 1980Y1:1996Y1
comment
instruments
block ACAF
corr 1.0
stdev 0.00427
meany 0.008185
ssres 0.000052
stderr 0.001927
stderrp 23.545813
fstat 32.273193
r2 0.821761
r2adj 0.796299
dw 2.329346
loglik 83.807526
date 12-06-1998
Name: ACAF, dtype: object
>>> equations["YDH_"] # doctest: +NORMALIZE_WHITESPACE
Equation(endogenous = 'YDH_',
lec = 'grt YDH_ :=grt((WBU_+YN+GOSH_+IDH)-(SSF+SSH+DTH)+(SBH+OCUH))',
method = 'LSQ',
comment = ' ',
block = 'YDH_')
>>> df.loc["YDH_"] # doctest: +NORMALIZE_WHITESPACE
lec grt YDH_ :=grt((WBU_+YN+GOSH_+IDH)-(SSF+SSH+DT...
method LSQ
sample None
comment
instruments
block YDH_
corr 0.0
stdev 0.0
meany 0.0
ssres 0.0
stderr 0.0
stderrp 0.0
fstat 0.0
r2 0.0
r2adj 0.0
dw 0.0
loglik 0.0
date
Name: YDH_, dtype: object
"""
return self.to_frame()
def _str_table(self, names: List[str]) -> str:
data = []
for name in names:
eq = self._get_object(name)
tests = eq.tests
data += [[join_lines(eq.lec), eq.method, str(eq.sample), eq.block, tests["fstat"],
tests["r2adj"], tests["dw"], tests["loglik"], eq.date]]
# transpose data
data = [list(row) for row in zip(*data)]
columns = {"name": names, "lec": data[0], "method": data[1], "sample": data[2], "block": data[3],
"fstat": data[4], "r2adj": data[5], "dw": data[6], "loglik": data[7], "date": data[8]}
return table2str(columns, max_lines=10, justify_funcs={"name": JUSTIFY.LEFT, "lec": JUSTIFY.LEFT})
@property
def print_nb_decimals(self) -> int:
r"""
Number of decimals to print.
Parameters
----------
value: int
number of decimals to print (equations coeffs, scalars and computed tables values).
Examples
--------
>>> from iode import equations
>>> equations.print_nb_decimals = 4
>>> equations.print_nb_decimals
4
"""
return self._cython_instance._get_print_nb_decimals()
@print_nb_decimals.setter
def print_nb_decimals(self, value: int):
self._cython_instance._set_print_nb_decimals(value)
@property
def print_equations_as(self) -> PrintEquationsAs:
r"""
Whether to print only the LEC formula, or the LEC formula and the comment,
or the LEC formula, the comment and the estimation results of the IODE equations
in the current database.
Parameters
----------
value: PrintEquationsAs
Possible values are: PrintEquationsAs.EQ_ONLY, PrintEquationsAs.EQ_COMMENTS,
PrintEquationsAs.EQ_COMMENTS_ESTIMATION
Examples
--------
>>> from iode import equations, PrintEquationsAs
>>> equations.print_equations_as
<PrintEquationsAs.EQ_ONLY: 0>
>>> equations.print_equations_as = PrintEquationsAs.EQ_COMMENTS
>>> equations.print_equations_as
<PrintEquationsAs.EQ_COMMENTS: 1>
>>> equations.print_equations_as = "EQ_COMMENTS_ESTIMATION"
>>> equations.print_equations_as
<PrintEquationsAs.EQ_COMMENTS_ESTIMATION: 2>
"""
i_value = self._cython_instance.get_print_equations_as()
return PrintEquationsAs(i_value)
@print_equations_as.setter
def print_equations_as(self, value: Union[PrintEquationsAs, str, int]):
if not isinstance(value, (PrintEquationsAs, str, int)):
raise TypeError(f"Expected value of type PrintEquationsAs, str or int. "
f"Got {type(value).__name__} instead.")
if isinstance(value, int) and not (0 <= value <= 2):
raise ValueError(f"Invalid value {value}. Expected value between 0 and 2.")
if isinstance(value, str):
upper_str = value.upper()
if upper_str not in PrintEquationsAs.__members__:
raise ValueError(f"Invalid value '{value}'. "
f"Expected one of {', '.join(PrintEquationsAs.__members__.keys())}. ")
value = PrintEquationsAs[upper_str]
value = str(int(value))
self._cython_instance.set_print_equations_as(value)
@property
def print_equations_lec_as(self) -> PrintEquationsLecAs:
r"""
Whether to print the LEC formula of each equation:
- as is,
- with coefficients replaced by their values,
- with coefficients replaced by their values + t-tests.
Parameters
----------
value: PrintEquationsLecAs
Possible values are: PrintEquationsLecAs.AS_IS,
PrintEquationsLecAs.COEFFS_TO_VALUES,
PrintEquationsLecAs.COEFFS_TO_VALUES_TTEST
Examples
--------
>>> from iode import equations, PrintEquationsLecAs
>>> equations.print_equations_lec_as
<PrintEquationsLecAs.AS_IS: 0>
>>> equations.print_equations_lec_as = PrintEquationsLecAs.COEFFS_TO_VALUES
>>> equations.print_equations_lec_as
<PrintEquationsLecAs.COEFFS_TO_VALUES: 1>
>>> equations.print_equations_lec_as = "COEFFS_TO_VALUES_TTEST"
>>> equations.print_equations_lec_as
<PrintEquationsLecAs.COEFFS_TO_VALUES_TTEST: 2>
"""
i_value = self._cython_instance.get_print_equations_lec_as()
return PrintEquationsLecAs(i_value)
@print_equations_lec_as.setter
def print_equations_lec_as(self, value: Union[PrintEquationsLecAs, str, int]):
if not isinstance(value, (PrintEquationsLecAs, str, int)):
raise TypeError(f"Expected value of type PrintEquationsLecAs, str or int. "
f"Got {type(value).__name__} instead.")
if isinstance(value, int) and not (0 <= value <= 2):
raise ValueError(f"Invalid value {value}. Expected value between 0 and 2.")
if isinstance(value, str):
upper_str = value.upper()
if upper_str not in PrintEquationsLecAs.__members__:
raise ValueError(f"Invalid value '{value}'. "
f"Expected one of {', '.join(PrintEquationsLecAs.__members__.keys())}. ")
value = PrintEquationsLecAs[upper_str]
value = str(int(value))
self._cython_instance.set_print_equations_lec_as(value)
[docs]
def print_to_file(self, filepath: Union[str, Path], names: Union[str, List[str]]=None, format: str=None):
r"""
Print the list equations defined by `names` to the file `filepath` using the format `format`.
Argument `format` must be in the list:
- 'H' (HTML file)
- 'M' (MIF file)
- 'R' (RTF file)
- 'C' (CSV file)
If argument `format` is null (default), the *A2M* format will be used to print the output.
If the filename does not contain an extension, it is automatically added based on
the value of `format`.
If `names` is a string, it is considered as a *pattern* and the function will print
all equations matching the pattern. The following characters in *pattern* have a
special meaning:
- `*` : any character sequence, even empty
- `?` : any character (one and only one)
- `@` : any alphanumerical char [A-Za-z0-9]
- `&` : any non alphanumerical char
- `|` : any alphanumeric character or none at the beginning and end of a string
- `!` : any non-alphanumeric character or none at the beginning and end of a string
- `\` : escape the next character
If `names` is None, print all equations of the (subset of the) current database.
Parameters
----------
filepath: str or Path
path to the file to print.
If the filename does not contain an extension, it is automatically
added based on the value of the format argument.
names: str or list of str, optional
pattern or list of names of the equations to print.
If None, print all equations of the (subset of the) current database.
Defaults to None.
format: str, optional
format of the output file. Possible values are: 'H' (HTML file),
'M' (MIF file), 'R' (RTF file) or 'C' (CSV file).
Defaults to None meaning that the equations will be dumped in the *A2M* format.
Examples
--------
>>> from iode import equations, scalars, SAMPLE_DATA_DIR
>>> from iode import PrintEquationsAs, PrintEquationsLecAs
>>> output_dir = getfixture('tmp_path')
>>> equations.load(f"{SAMPLE_DATA_DIR}/fun.eqs") # doctest: +ELLIPSIS, +NORMALIZE_WHITESPACE
Loading .../fun.eqs
274 objects loaded
>>> scalars.load(f"{SAMPLE_DATA_DIR}/fun.scl") # doctest: +ELLIPSIS, +NORMALIZE_WHITESPACE
Loading .../fun.scl
161 objects loaded
>>> equations.print_nb_decimals = 4
>>> equations.print_equations_as = PrintEquationsAs.EQ_ONLY
>>> equations.print_equations_lec_as = PrintEquationsLecAs.AS_IS
>>> equations.print_to_file(output_dir / "equations_lec_only.csv", ["ACAF", "ACAG"]) # doctest: +ELLIPSIS
Printing IODE objects definition to file '...equations_lec_only.csv'...
Printing ACAF ...
Printing ACAG ...
Print done
>>> with open(output_dir / "equations_lec_only.csv") as f: # doctest: +NORMALIZE_WHITESPACE
... print(f.read())
...
" - (ACAF/VAF[-1 ]) := acaf1 + acaf2*GOSF[-1 ] + acaf4*(TIME= 1995)"
" - ACAG := ACAG[-1 ] + r VBBP[-1 ] + (0.006*VBBP[-1 ]*(TIME= 2001) -0.008*(TIME= 2008) )"
>>> equations.print_equations_as = PrintEquationsAs.EQ_ONLY
>>> equations.print_equations_lec_as = PrintEquationsLecAs.COEFFS_TO_VALUES
>>> equations.print_to_file(output_dir / "equations_coeffs_as_values.csv", ["ACAF", "ACAG"]) # doctest: +ELLIPSIS
Printing IODE objects definition to file '...equations_coeffs_as_values.csv'...
Printing ACAF ...
Printing ACAG ...
Print done
>>> with open(output_dir / "equations_coeffs_as_values.csv") as f: # doctest: +NORMALIZE_WHITESPACE
... print(f.read())
...
" - (ACAF/VAF[-1 ]) := 0.0158 + -0.0000*GOSF[-1 ] + -0.0085*(TIME= 1995)"
" - ACAG := ACAG[-1 ] + r VBBP[-1 ] + (0.006*VBBP[-1 ]*(TIME= 2001) -0.008*(TIME= 2008) )"
<BLANKLINE>
>>> equations.print_equations_as = PrintEquationsAs.EQ_ONLY
>>> equations.print_equations_lec_as = PrintEquationsLecAs.COEFFS_TO_VALUES_TTEST
>>> equations.print_to_file(output_dir / "equations_coeffs_ttest.csv", ["ACAF", "ACAG"]) # doctest: +ELLIPSIS
Printing IODE objects definition to file '...equations_coeffs_ttest.csv'...
Printing ACAF ...
Printing ACAG ...
Print done
>>> with open(output_dir / "equations_coeffs_ttest.csv") as f: # doctest: +NORMALIZE_WHITESPACE
... print(f.read())
...
" - (ACAF/VAF[-1 ]) := 0.0158(11.5206) + -0.0000(-5.3691) *GOSF[-1 ] + -0.0085(-4.0825) *(TIME= 1995)"
" - ACAG := ACAG[-1 ] + r VBBP[-1 ] + (0.006*VBBP[-1 ]*(TIME= 2001) -0.008*(TIME= 2008) )"
<BLANKLINE>
>>> equations.print_equations_as = PrintEquationsAs.EQ_COMMENTS
>>> equations.print_equations_lec_as = PrintEquationsLecAs.AS_IS
>>> equations.print_to_file(output_dir / "equations_lec_cmt.csv", ["ACAF", "ACAG"]) # doctest: +ELLIPSIS
Printing IODE objects definition to file '...equations_lec_cmt.csv'...
Printing ACAF ...
Printing ACAG ...
Print done
>>> with open(output_dir / "equations_lec_cmt.csv") as f: # doctest: +NORMALIZE_WHITESPACE
... print(f.read())
...
" - (ACAF/VAF[-1 ]) := acaf1 + acaf2*GOSF[-1 ] + acaf4*(TIME= 1995)"
" - ACAG := ACAG[-1 ] + r VBBP[-1 ] + (0.006*VBBP[-1 ]*(TIME= 2001) -0.008*(TIME= 2008) )"
>>> equations.print_equations_as = PrintEquationsAs.EQ_COMMENTS_ESTIMATION
>>> equations.print_equations_lec_as = PrintEquationsLecAs.AS_IS
>>> equations.print_to_file(output_dir / "equations_lec_cmt_estim.csv", ["ACAF", "ACAG"]) # doctest: +ELLIPSIS
Printing IODE objects definition to file '...equations_lec_cmt_estim.csv'...
Printing ACAF ...
Printing ACAG ...
Print done
>>> with open(output_dir / "equations_lec_cmt_estim.csv") as f: # doctest: +NORMALIZE_WHITESPACE
... print(f.read())
...
" - (ACAF/VAF[-1 ]) := acaf1 + acaf2*GOSF[-1 ] + acaf4*(TIME= 1995)"
" - Estimation : L on 1980Y1-1996Y1"
" - Block : ACAF"
" - Tests :"
" - St dev of residuals : 0.004270"
" - Mean of YOBS : 0.008185"
" - Sum of Squares of Residuals : 0.000052"
" - Standard error (%) : 0.001927 (23.545813)"
" - F-stat : 32.273193"
" - R2 (R2 adjusted) : 0.821761 (0.796299)"
" - Durbin-Watson : 2.329346"
" - Log Likelihood : 83.807526"
" - Coefficient values (relax, stderr, t-stat) :"
" - acaf1 : 0.0158 (1, 0.0014, 11.5206)"
" - acaf2 : -0.0000 (1, 0.0000, -5.3691)"
" - acaf4 : -0.0085 (1, 0.0021, -4.0825)"
" - ACAG := ACAG[-1 ] + r VBBP[-1 ] + (0.006*VBBP[-1 ]*(TIME= 2001) -0.008*(TIME= 2008) )"
<BLANKLINE>
"""
super().print_to_file(filepath, names, format)
def __hash__(self) -> int:
r"""
Return a hash value for the current Equations database.
Examples
--------
>>> from iode import SAMPLE_DATA_DIR, equations
>>> equations.load(f"{SAMPLE_DATA_DIR}/fun.eqs") # doctest: +ELLIPSIS, +NORMALIZE_WHITESPACE
Loading .../fun.eqs
274 objects loaded
>>> len(equations)
274
>>> original_hash = hash(equations)
>>> # modify one equation
>>> eq = equations["ACAF"]
>>> original_lec = eq.lec
>>> eq.lec = "ACAF := 1"
>>> equations["ACAF"] = eq
>>> original_hash == hash(equations)
False
>>> eq.lec = original_lec # revert the change
>>> equations["ACAF"] = eq
>>> original_hash == hash(equations)
True
>>> # delete a equation
>>> original_eq = equations["ACAF"]
>>> del equations["ACAF"]
>>> original_hash == hash(equations)
False
>>> equations["ACAF"] = original_eq
>>> original_hash == hash(equations)
True
>>> # add a equation
>>> equations["NEW"] = "NEW := 0"
>>> original_hash == hash(equations)
False
>>> del equations["NEW"]
>>> original_hash == hash(equations)
True
"""
return super().__hash__()
equations: Equations = Equations.get_instance()