API Reference (Python)

WORKSPACE

Comments

Comments([filepath])	IODE Comments database.
Comments.names	List of names of all objects in the current database.
Comments.iode_type	Return the object type of the current database.
Comments.filename	Return the filepath associated with the current database.
Comments.description	Description of the current database.
Comments.load(filepath)	Load objects stored in file 'filepath' into the current database.
Comments.save(filepath[, compress])	Save objects of the current database into the file 'filepath'.
Comments.clear()	Delete all objects from the current database.
Comments.copy([pattern])	Create a new database instance in which each object is a copy of the original object from the global IODE database.
Comments.new_detached()	Create a new empty detached database.
Comments.subset(pattern, copy)	Create a subset of the database filtered by a name pattern.
Comments.print_to_file(filepath[, names, format])	Print the list comments defined by names to the file filepath using the format format.
Comments.get_names([pattern, filepath])	Returns the list of objects names given a pattern.
Comments.get_names_from_pattern(list_name, ...)	Generate an IODE list containing the names of objects that match a given pattern.
Comments.rename(old_name, new_name[, overwrite])	Rename an object of the database.
Comments.search(pattern[, word, ...])	Return a list of all objects from the current database having a specific pattern in their names or LEC expression, comment...
Comments.index(name)	Return the position of the IODE object with name name in the database.
Comments.__len__()	Return the number of IODE objects in the current database.
Comments.__contains__(item)	Test if the IODE object named item is present in the current database.
Comments.__iter__()	Iterate over object names.
Comments.__getitem__(key)	Return the (subset of) comment(s) referenced by key.
Comments.__setitem__(key, value)	Update/add a (subset of) comment(s) referenced by key from/to the Comments database.
Comments.__delitem__(key)	Remove the (subset of) comment(s) referenced by key from the Comments database.
Comments.i	Allow to select the ith comment in the database.
Comments.copy_from(input_files[, names])	Copy (a subset of) comments from the input file(s) 'input_files' into the current database.
Comments.merge(other[, overwrite])	Merge the content of the 'other' database into the current database.
Comments.merge_from(input_file)	Merge all objects stored in the input file 'input_file' into the current database.
Comments.compare(filepath[, ...])	The objects of the current database are compared with those stored in the file filepath.
Comments.is_detached	Whether or not any change made on the present database or subset will modify the global IODE workspace.
Comments.is_global_workspace	Whether or not the present database represents the global IODE workspace.

Properties and methods specific to Comments

Comments.series	Create a pandas Series from the current Comments database.
Comments.from_series(s)	Copy the pandas Series s into the IODE Comments database.
Comments.to_series()	Create a pandas Series from the current Comments database.
Comments.convert_file(input_file, ...[, ...])	Convert an external file representing IODE comments to an IODE comments file (.cmt).

Equations

Equations([filepath])	IODE Equations database.
Equations.names	List of names of all objects in the current database.
Equations.iode_type	Return the object type of the current database.
Equations.filename	Return the filepath associated with the current database.
Equations.description	Description of the current database.
Equations.load(filepath)	Load objects stored in file 'filepath' into the current database.
Equations.save(filepath[, compress])	Save objects of the current database into the file 'filepath'.
Equations.clear()	Delete all objects from the current database.
Equations.copy([pattern])	Create a new database instance in which each object is a copy of the original object from the global IODE database.
Equations.subset(pattern, copy)	Create a subset of the database filtered by a name pattern.
Equations.new_detached()	Create a new empty detached database.
Equations.print_to_file(filepath[, names, ...])	Print the list equations defined by names to the file filepath using the format format.
Equations.search(pattern[, word, ...])	Return a list of all objects from the current database having a specific pattern in their names or LEC expression, comment...
Equations.index(name)	Return the position of the IODE object with name name in the database.
Equations.get_names([pattern, filepath])	Returns the list of objects names given a pattern.
Equations.get_names_from_pattern(list_name, ...)	Generate an IODE list containing the names of objects that match a given pattern.
Equations.rename(old_name, new_name[, overwrite])	Rename an object of the database.
Equations.coefficients	Return the list of coefficients (scalars) used in the equations of (the subset of) the database.
Equations.variables	Return the list of variables used in the equations of (the subset of) the database.
Equations.__len__()	Return the number of IODE objects in the current database.
Equations.__contains__(item)	Test if the IODE object named item is present in the current database.
Equations.__iter__()	Iterate over object names.
Equations.__getitem__(key)	Return the (subset of) equation(s) referenced by key.
Equations.__setitem__(key, value)	Update/add a (subset of) equation(s) referenced by key from/to the Equations database.
Equations.__delitem__(key)	Remove the (subset of) equation(s) referenced by key from the Equations database.
Equations.i	Allow to select the ith equation in the database.
Equations.copy_from(input_files[, names])	Copy (a subset of) equations from the input file(s) 'input_files' into the current database.
Equations.merge(other[, overwrite])	Merge the content of the 'other' database into the current database.
Equations.merge_from(input_file)	Merge all objects stored in the input file 'input_file' into the current database.
Equations.compare(filepath[, ...])	The objects of the current database are compared with those stored in the file filepath.
Equations.is_detached	Whether or not any change made on the present database or subset will modify the global IODE workspace.
Equations.is_global_workspace	Whether or not the present database represents the global IODE workspace.

Properties and methods specific to Equations

Equations.df	Create a pandas DataFrame from the current Equations database.
Equations.from_frame(df)	Copy the pandas DataFrame df into the IODE Equations database.
Equations.to_frame()	Create a pandas DataFrame from the current Equations database.
Equations.estimate([from_period, to_period, ...])	Estimate an equation or a block of equations.
Equations.estimate_step_wise(eq_names[, ...])	Estimates (an) equation(s) and searches for the best possible test values for all possible combinations of coefficients.
Equations.print_nb_decimals	Number of decimals to print.
Equations.print_equations_as	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.
Equations.print_equations_lec_as	Whether to print the LEC formula of each equation:

Identities

Identities([filepath])	IODE Identities database.
Identities.names	List of names of all objects in the current database.
Identities.iode_type	Return the object type of the current database.
Identities.filename	Return the filepath associated with the current database.
Identities.description	Description of the current database.
Identities.load(filepath)	Load objects stored in file 'filepath' into the current database.
Identities.save(filepath[, compress])	Save objects of the current database into the file 'filepath'.
Identities.clear()	Delete all objects from the current database.
Identities.copy([pattern])	Create a new database instance in which each object is a copy of the original object from the global IODE database.
Identities.subset(pattern, copy)	Create a subset of the database filtered by a name pattern.
Identities.new_detached()	Create a new empty detached database.
Identities.print_to_file(filepath[, names, ...])	Print the list identities defined by names to the file filepath using the format format.
Identities.search(pattern[, word, ...])	Return a list of all objects from the current database having a specific pattern in their names or LEC expression, comment...
Identities.index(name)	Return the position of the IODE object with name name in the database.
Identities.get_names([pattern, filepath])	Returns the list of objects names given a pattern.
Identities.get_names_from_pattern(list_name, ...)	Generate an IODE list containing the names of objects that match a given pattern.
Identities.rename(old_name, new_name[, ...])	Rename an object of the database.
Identities.coefficients	Return the list of coefficients (scalars) used in the identities of (the subset of) the database.
Identities.variables	Return the list of variables used in the identities of (the subset of) the database.
Identities.__len__()	Return the number of IODE objects in the current database.
Identities.__contains__(item)	Test if the IODE object named item is present in the current database.
Identities.__iter__()	Iterate over object names.
Identities.__getitem__(key)	Return the (subset of) identity(ies) referenced by key.
Identities.__setitem__(key, value)	Update/add a (subset of) identity(ies) referenced by key from/to the Identities database.
Identities.__delitem__(key)	Remove the (subset of) identity(ies) referenced by key from the Identities database.
Identities.i	Allow to select the ith identity in the database.
Identities.copy_from(input_files[, names])	Copy (a subset of) identities from the input file(s) 'input_files' into the current database.
Identities.merge(other[, overwrite])	Merge the content of the 'other' database into the current database.
Identities.merge_from(input_file)	Merge all objects stored in the input file 'input_file' into the current database.
Identities.compare(filepath[, ...])	The objects of the current database are compared with those stored in the file filepath.
Identities.is_detached	Whether or not any change made on the present database or subset will modify the global IODE workspace.
Identities.is_global_workspace	Whether or not the present database represents the global IODE workspace.

Properties and methods specific to Identities

Identities.series	Create a pandas Series from the current Identities database.
Identities.from_series(s)	Copy the pandas Series s into the IODE Identities database.
Identities.to_series()	Create a pandas Series from the current Identities database.
Identities.execute([identities, ...])	Execute the specified identity(ies).

Lists

Lists([filepath])	IODE Lists database.
Lists.names	List of names of all objects in the current database.
Lists.iode_type	Return the object type of the current database.
Lists.filename	Return the filepath associated with the current database.
Lists.description	Description of the current database.
Lists.load(filepath)	Load objects stored in file 'filepath' into the current database.
Lists.save(filepath[, compress])	Save objects of the current database into the file 'filepath'.
Lists.clear()	Delete all objects from the current database.
Lists.copy([pattern])	Create a new database instance in which each object is a copy of the original object from the global IODE database.
Lists.subset(pattern, copy)	Create a subset of the database filtered by a name pattern.
Lists.new_detached()	Create a new empty detached database.
Lists.print_to_file(filepath[, names, format])	Print the list IODE lists defined by names to the file filepath using the format format.
Lists.search(pattern[, word, ...])	Return a list of all objects from the current database having a specific pattern in their names or LEC expression, comment...
Lists.index(name)	Return the position of the IODE object with name name in the database.
Lists.get_names([pattern, filepath])	Returns the list of objects names given a pattern.
Lists.get_names_from_pattern(list_name, ...)	Generate an IODE list containing the names of objects that match a given pattern.
Lists.rename(old_name, new_name[, overwrite])	Rename an object of the database.
Lists.__len__()	Return the number of IODE objects in the current database.
Lists.__contains__(item)	Test if the IODE object named item is present in the current database.
Lists.__iter__()	Iterate over object names.
Lists.__getitem__(key)	Return the (subset of) IODE list(s) referenced by key.
Lists.__setitem__(key, value)	Update/add a (subset of) IODE list(s) referenced by key from/to the Lists database.
Lists.__delitem__(key)	Remove the (subset of) IODE list(s) referenced by key from the Lists database.
Lists.i	Allow to select the ith list in the database.
Lists.copy_from(input_files[, names])	Copy (a subset of) lists from the input file(s) 'input_files' into the current database.
Lists.merge(other[, overwrite])	Merge the content of the 'other' database into the current database.
Lists.merge_from(input_file)	Merge all objects stored in the input file 'input_file' into the current database.
Lists.compare(filepath[, ...])	The objects of the current database are compared with those stored in the file filepath.
Lists.is_detached	Whether or not any change made on the present database or subset will modify the global IODE workspace.
Lists.is_global_workspace	Whether or not the present database represents the global IODE workspace.

Properties and methods specific to Lists

Lists.series	Create a pandas Series from the current Lists database.
Lists.from_series(s)	Copy the pandas Series s into the IODE Lists database.
Lists.to_series()	Create a pandas Series from the current Lists database.

Scalars

Scalars([filepath])	IODE Scalars database.
Scalars.names	List of names of all objects in the current database.
Scalars.iode_type	Return the object type of the current database.
Scalars.filename	Return the filepath associated with the current database.
Scalars.description	Description of the current database.
Scalars.load(filepath)	Load objects stored in file 'filepath' into the current database.
Scalars.save(filepath[, compress])	Save objects of the current database into the file 'filepath'.
Scalars.clear()	Delete all objects from the current database.
Scalars.copy([pattern])	Create a new database instance in which each object is a copy of the original object from the global IODE database.
Scalars.subset(pattern, copy)	Create a subset of the database filtered by a name pattern.
Scalars.new_detached()	Create a new empty detached database.
Scalars.print_to_file(filepath[, names, format])	Print the list scalars defined by names to the file filepath using the format format.
Scalars.search(pattern[, word, ...])	Return a list of all objects from the current database having a specific pattern in their names or LEC expression, comment...
Scalars.index(name)	Return the position of the IODE object with name name in the database.
Scalars.get_names([pattern, filepath])	Returns the list of objects names given a pattern.
Scalars.get_names_from_pattern(list_name, ...)	Generate an IODE list containing the names of objects that match a given pattern.
Scalars.rename(old_name, new_name[, overwrite])	Rename an object of the database.
Scalars.__len__()	Return the number of IODE objects in the current database.
Scalars.__contains__(item)	Test if the IODE object named item is present in the current database.
Scalars.__iter__()	Iterate over object names.
Scalars.__getitem__(key)	Return the (subset of) scalar(s) referenced by key.
Scalars.__setitem__(key, value)	Update/add a (subset of) scalar(s) referenced by key from/to the Scalars database.
Scalars.__delitem__(key)	Remove the (subset of) scalar(s) referenced by key from the Scalars database.
Scalars.i	Allow to select the ith scalar in the database.
Scalars.copy_from(input_files[, names])	Copy (a subset of) scalars from the input file(s) 'input_files' into the current database.
Scalars.merge(other[, overwrite])	Merge the content of the 'other' database into the current database.
Scalars.merge_from(input_file)	Merge all objects stored in the input file 'input_file' into the current database.
Scalars.compare(filepath[, ...])	The objects of the current database are compared with those stored in the file filepath.
Scalars.is_detached	Whether or not any change made on the present database or subset will modify the global IODE workspace.
Scalars.is_global_workspace	Whether or not the present database represents the global IODE workspace.

Properties and methods specific to Scalars

Scalars.df	Create a pandas DataFrame from the current Scalars database.
Scalars.from_series(s)	Copy the pandas Series s into the IODE Scalars database.
Scalars.from_frame(df)	Copy the pandas DataFrame df into the IODE Scalars database.
Scalars.to_frame()	Create a pandas DataFrame from the current Scalars database.
Scalars.print_nb_decimals	Number of decimals to print.

Tables

Tables([filepath])	IODE Tables database.
Tables.names	List of names of all objects in the current database.
Tables.iode_type	Return the object type of the current database.
Tables.filename	Return the filepath associated with the current database.
Tables.description	Description of the current database.
Tables.load(filepath)	Load objects stored in file 'filepath' into the current database.
Tables.save(filepath[, compress])	Save objects of the current database into the file 'filepath'.
Tables.clear()	Delete all objects from the current database.
Tables.copy([pattern])	Create a new database instance in which each object is a copy of the original object from the global IODE database.
Tables.subset(pattern, copy)	Create a subset of the database filtered by a name pattern.
Tables.new_detached()	Create a new empty detached database.
Tables.print_to_file(filepath[, names, ...])	Print the list tables defined by names to the file filepath using the format format.
Tables.search(pattern[, word, ...])	Return a list of all objects from the current database having a specific pattern in their names or LEC expression, comment...
Tables.index(name)	Return the position of the IODE object with name name in the database.
Tables.get_names([pattern, filepath])	Returns the list of objects names given a pattern.
Tables.get_names_from_pattern(list_name, ...)	Generate an IODE list containing the names of objects that match a given pattern.
Tables.rename(old_name, new_name[, overwrite])	Rename an object of the database.
Tables.coefficients	Return the list of coefficients (scalars) used in the tables of (the subset of) the database.
Tables.variables	Return the list of variables used in the tables of (the subset of) the database.
Tables.__len__()	Return the number of IODE objects in the current database.
Tables.__contains__(item)	Test if the IODE object named item is present in the current database.
Tables.__iter__()	Iterate over object names.
Tables.__getitem__(key)	Return the (subset of) table(s) referenced by key.
Tables.__setitem__(key, value)	Update/add a (subset of) table(s) referenced by key from/to the Tables database.
Tables.__delitem__(key)	Remove the (subset of) table(s) referenced by key from the Tables database.
Tables.i	Allow to select the ith table in the database.
Tables.copy_from(input_files[, names])	Copy (a subset of) tables from the input file(s) 'input_files' into the current database.
Tables.merge(other[, overwrite])	Merge the content of the 'other' database into the current database.
Tables.merge_from(input_file)	Merge all objects stored in the input file 'input_file' into the current database.
Tables.compare(filepath[, ...])	The objects of the current database are compared with those stored in the file filepath.
Tables.is_detached	Whether or not any change made on the present database or subset will modify the global IODE workspace.
Tables.is_global_workspace	Whether or not the present database represents the global IODE workspace.

Properties and methods specific to Tables

Tables.print_nb_decimals	Number of decimals to print.
Tables.print_tables_as	Whether to print the full definitions, only the titles or the computed values of the IODE tables in the current database.

Variables

Variables([filepath])	IODE Variables database.
Variables.names	List of names of all objects in the current database.
Variables.iode_type	Return the object type of the current database.
Variables.filename	Return the filepath associated with the current database.
Variables.description	Description of the current database.
Variables.load(filepath)	Load objects stored in file 'filepath' into the current database.
Variables.save(filepath[, compress])	Save objects of the current database into the file 'filepath'.
Variables.clear()	Delete all objects from the current database.
Variables.copy([pattern])	Create a new Variables database in which each variable is a copy of the original variable from the global Variables workspace.
Variables.subset(pattern, copy[, ...])	Create a subset of the database filtered by a name pattern.
Variables.new_detached()	Create a new empty detached database.
Variables.print_to_file(filepath[, names, ...])	Print the list variables defined by names to the file filepath using the format format.
Variables.search(pattern[, word, ...])	Return a list of all objects from the current database having a specific pattern in their names or LEC expression, comment...
Variables.index(name)	Return the position of the IODE object with name name in the database.
Variables.get_names([pattern, filepath])	Returns the list of objects names given a pattern.
Variables.get_names_from_pattern(list_name, ...)	Generate an IODE list containing the names of objects that match a given pattern.
Variables.rename(old_name, new_name[, overwrite])	Rename an object of the database.
Variables.__len__()	Return the number of IODE objects in the current database.
Variables.__contains__(item)	Test if the IODE object named item is present in the current database.
Variables.__iter__()	Iterate over object names.
Variables.__getitem__(key)	Return the (subset of) variable(s) referenced by key.
Variables.__setitem__(key, value)	Update/add a (subset of) variable(s) referenced by key from/to the Variables database.
Variables.__delitem__(key)	Remove the (subset of) variable(s) referenced by key from the Variables database.
Variables.i	Allow to select the ith variable in the database.
Variables.copy_from(input_files[, ...])	Copy (a subset of) variables from the input file(s) 'input_files' into the current database.
Variables.merge(other[, overwrite])	Merge the content of the 'other' database into the current database.
Variables.merge_from(input_file)	Merge all objects stored in the input file 'input_file' into the current database.
Variables.compare(filepath[, ...])	The objects of the current database are compared with those stored in the file filepath.
Variables.is_detached	Whether or not any change made on the present database or subset will modify the global IODE workspace.
Variables.is_global_workspace	Whether or not the present database represents the global IODE workspace.

Properties and methods specific to Variables

Variables.mode	Current display mode for the IODE Variables values.
Variables.sample	Current (or new) sample of the IODE Variables database.
Variables.nb_periods	Return the number of periods from the current Variables sample.
Variables.periods	Return the list of periods from the current Variables sample.
Variables.periods_as_str	Return the list of periods as string from the current Variables sample.
Variables.periods_as_float	Return the list of periods as float from the current Variables sample.
Variables.threshold	Threshold under which the difference between 2 variables are considered equal.
Variables.__add__(other)	Add other to the current (subset of) Variables object.
Variables.__radd__(other)	Add other to the current (subset of) Variables object.
Variables.__iadd__(other)	Add other to the current (subset of) Variables object.
Variables.__sub__(other)	Subtract other from the current (subset of) Variables object.
Variables.__rsub__(other)	subtract self from other.
Variables.__isub__(other)	subtract other from the current (subset of) Variables object.
Variables.__mul__(other)	multiply the current (subset of) Variables object by other.
Variables.__rmul__(other)	multiply other by the current (subset of) Variables object.
Variables.__imul__(other)	multiply the current (subset of) Variables object by other.
Variables.__truediv__(other)	divide the current (subset of) Variables object by other.
Variables.__rtruediv__(other)	divide other by the current (subset of) Variables object.
Variables.__itruediv__(other)	divide the current (subset of) Variables object by other.
Variables.__pow__(other)	Compute the expression \(self^{other}\) ( self ** other ).
Variables.periods_subset([from_period, ...])	Return a subset of the periods from the current Variables sample.
Variables.low_to_high(type_of_series, ...)	Build series with higher periodicity for stock data (Unemployment, Debt, ...) or flow data (GNP, Deficit, ...).
Variables.high_to_low(type_of_series, ...)	Build series of lower periodicity by (summing the / taking the average of the / taking the last observation of) sub-periods.
Variables.extrapolate(method[, from_period, ...])	Extrapolate variables using one the method described below, based on previous periods.
Variables.seasonal_adjustment(input_file[, ...])	Eliminate seasonal variations in monthly series (= variables).
Variables.trend_correction(input_file, lambda_)	Implementation of the Hodrick-Prescott method for trend series (= variables) construction.
Variables.execute_RAS(pattern, xdim, ydim, ...)	Execute the RAS algorithm (also called IPF for 'Iterative Proportional Fitting').
Variables.from_numpy(data[, vars_names, ...])	Copy the numpy ndarray array into the IODE Variables database.
Variables.to_numpy()	Create a Numpy ndarray from the current Variables database.
Variables.df	Create a pandas DataFrame from the current Variables database.
Variables.from_frame(df)	Copy the pandas DataFrame df into the IODE Variables database.
Variables.to_frame(vars_axis_name, ...)	Create a pandas DataFrame from the current Variables database.
Variables.from_array(array[, ...])	Copies the Array array into the IODE Variables database.
Variables.to_array(vars_axis_name, ...)	Creates an Array from the current IODE Variables database.
Variables.plot([names, periods, plot_type, ...])	Plot the variables defined by names for the periods defined by periods.
Variables.convert_file(input_file, ...[, ...])	Convert an external file representing IODE variables to an IODE variables file (.var).
Variables.export_as_file(variables_file, ...)	Convert an IODE Variables file to a format used by some other programs.

Miscellaneous

load_extra_files(extra_files[, quiet])	Load extra file(s) referenced in generalized samples.
reset_extra_files()	reset extra files referenced in generalized samples.

IODE OBJECTS

EQUATION

Equation(endogenous, lec[, method, ...])	An equation represents an equality mixing variables and scalars (coefficients) and is part of a model.
Equation.endogenous	Endogenous variable of the current equation.
Equation.lec	LEC expression of the current equation.
Equation.sample	Estimation sample of the current equation.
Equation.method	Estimation method.
Equation.comment	Equation comment.
Equation.block	Estimation block of equations to which the equation belongs.
Equation.instruments	Instrument(s) used for the estimation.
Equation.tests	Estimation tests.
Equation.coefficients	Return the list of coefficients present in the current equation.
Equation.variables	Return the list of variables present in the equation.
Equation.copy()	Return a copy of the current Equation.
Equation.get_formated_date([format])	Return the date of last estimation in a given format.
Equation.split_equation()	Split an equation into its left-hand side and its right-hand side.
Equation.estimate([from_period, to_period, ...])	Estimate the present equation.
Equation.estimate_step_wise([from_period, ...])	Estimates an equation and searches for the best possible test values for all possible combinations of coefficients.

IDENTITY

Identity(lec)	An identity is an expression written in the LEC language that allows the construction of a new statistical series based on already defined series.
Identity.lec	Return the LEC formula of the identity.
Identity.coefficients	Return the list of coefficients present in the current identity.
Identity.variables	Return the list of variables present in the identity.
Identity.copy()	Return a copy of the current Identity.

LIST

split_list(list_txt)

Split an IODE list written as a string and return a Python list.

SCALAR

Scalar([value, relax])	Scalars are essentially estimated coefficients of econometric equations.
Scalar.value
Scalar.relax
Scalar.std
Scalar.copy()	Return a copy of the current Scalar.

TABLE

Table([nb_columns, table_title, ...])	One of the most frequently performed operations during a simulation exercise is the display of tables of results and charts.
Table.nb_lines
Table.nb_columns
Table.title	Title of the table.
Table.language	Language.
Table.ymin	Minimum values on the Y axis.
Table.ymax	Maximum values on the Y axis.
Table.gridx	The gridx value of the table offers a choice of three X-grid options:
Table.gridy	The gridy value of the table offers a choice of three Y-grid options:
Table.graph_axis	Graph axis of the table allows you to select the type of axis:
Table.graph_alignment	Graph alignment of the table.
Table.box	Whether the graph should be boxed.
Table.shadow	Whether or not to place a shadow behind the chart.
Table.divider	Returns the divider line of the table.
Table.coefficients	Get the list of coefficients (scalars) associated with all cells of type 'LEC' of the table.
Table.variables	Get the list of variables associated with all cells of the type 'LEC' of the table.
Table.compute(generalized_sample[, ...])	Compute the values corresponding to LEC expressions in cells.
Table.copy()	Return a copy of the current Table.
Table.index(key)	Return the index of the line containing the string key.
Table.insert(index, value)	Insert a new line in the table.
Table.__len__()	Number of lines of the table.
Table.__getitem__(index)	Get a line of the table.
Table.__setitem__(index, value)	Update a line of the table.
Table.__delitem__(index)	Delete the line at the given index
Table.__iadd__(value)	Append a new line to the table.
Table.plot([title, plot_type, grid, y_log, ...])	Plot the table using the sample of the variables workspace.

TableLine()	IODE Table line.
TableLine.line_type	Type of the table line.
TableLine.axis_left	Whether or not the values of the present line correspond to the Y axis displayed on the left of the graph.
TableLine.graph_type	Graph type associated with the table line.
TableLine.__len__()
TableLine.__getitem__(index)	Get the cell of a line.
TableLine.__setitem__(index, value)	Update the content of a cell of the line.
TableLine.__delitem__(index)

TableCell()	IODE Table cell.
TableCell.cell_type	Type of the content of the cell.
TableCell.align	Alignment of the text in the cell.
TableCell.bold	Whether or not the cell text is bold.
TableCell.italic	Whether or not the cell text is italic.
TableCell.underline	Whether or not the cell text is underline.
TableCell.coefficients	Get the list of coefficients (scalars) associated with the LEC expression of a cell of type 'LEC'.
TableCell.variables	Get the list of variables associated with the LEC expression of a cell of type 'LEC'.

COMPUTED TABLE

ComputedTable()	Object returned by the method compute().
ComputedTable.nb_decimals	The number of decimals used for rounding the values when displayed.
ComputedTable.nb_lines	The number of lines of the computed table.
ComputedTable.lines	List of line names of the computed table.
ComputedTable.nb_columns	The number of columns of the computed table.
ComputedTable.columns	List of column names of the computed table.
ComputedTable.nb_files	The number of files used to compute the table.
ComputedTable.files	The list of files associated with the computed table.
ComputedTable.nb_operations_between_files	The number of operations between files.
ComputedTable.sample	The sample associated with the computed table.
ComputedTable.nb_periods	The number of periods associated with the computed table.
ComputedTable.title	The title of the computed table.
ComputedTable.ymin	Minimum values on the Y axis.
ComputedTable.ymax	Maximum values on the Y axis.
ComputedTable.gridx	The gridx value of the table offers a choice of three X-grid options:
ComputedTable.gridy	The gridy value of the table offers a choice of three Y-grid options:
ComputedTable.graph_axis	Graph axis of the table allows you to select the type of axis:
ComputedTable.graph_alignment	Graph alignment of the table.
ComputedTable.is_editable(row, column)	Check if a cell in the computed table is editable.
ComputedTable.to_array()	Convert the computed table to a larray Array.
ComputedTable.to_frame()	Convert the computed table to a pandas DataFrame.
ComputedTable.__getitem__(key)	Get the value of a cell of the computed table.
ComputedTable.__setitem__(key, value)	Assign a new value to a cell.
ComputedTable.print_to_file(destination_file)	Print the present computed table to a file.
ComputedTable.plot([title, plot_type, grid, ...])	Plot the computed table.
ComputedTable.plot_data	Returns a dictionary containing the data to be plotted.

TIME

Period(period_or_year[, periodicity, step])
Period.year	Corresponding year of the period
Period.periodicity	Possible values are:
Period.step	Position of the period in the year
Period.difference(other)	Number of sub periods between two periods.
Period.nb_periods_per_year	Number of periods in a year according to the periodicity.
Period.shift(nb_periods)	Shift the current period by a number of sub periods.
Period.__float__()	Returns a float representation of the period.
Sample(start_period[, end_period])	A sample represents the series of sub periods attached to the IODE variables or to the estimation process.
Sample.start
Sample.end
Sample.nb_periods
Sample.index(period)	Position of the 'period' in the sample.
Sample.get_period_list(astype)	List of all periods of the sample.
Sample.intersection(other_sample)	Compute the intersection between two samples.

ESTIMATION

Equation.estimate([from_period, to_period, ...])	Estimate the present equation.
Equations.estimate([from_period, to_period, ...])	Estimate an equation or a block of equations.
dynamic_adjustment(method, eqs[, c1, c2])	Transform a LEC equation to add a dynamic adjustment.
dickey_fuller_test(lec, drift, trend, order)	Dickey-Fuller tests.

SIMULATION

Simulation([convergence_threshold, relax, ...])	Class for simulate models.
Simulation.convergence_threshold	Indicates the convergence threshold below which the simulation ends positively for the current period.
Simulation.relax	Relaxation parameter.
Simulation.sort_algorithm	Sorting algorithm used to reorganized the list of equations before the simulation is performed.
Simulation.sort_algorithm_long	Sorting algorithm used to reorganized the list of equations before the simulation is performed.
Simulation.initialization_method	At the start of each period to be simulated, a starting value must be chosen for each endogenous variable. This value can be : - \(Y := Y[-1], if Y null or NA\) (TM1) : each null or NA endogen at the start takes the value of the previous period, - \(Y := Y[-1], always\) (TM1_A) : each endogen takes the value of the previous period at the start, - \(Y := extrapolation, if Y null or NA\) (EXTRA) : each null or NA endogen takes as value a linear extrapolation of the two previous periods, - \(Y := extrapolation, always\) (EXTRA_A) : each endogen takes as its value a linear extrapolation of the two preceding periods, whether or not it is zero at the start, - \(Y unchanged\) (ASIS): endogenous values are not initialized. They retain their value whether or not they are zero, - \(Y := Y[-1], if Y = NA\) (TM1_NA): each NA value takes the value of the previous period, - \(Y := extrapolation, if Y = NA\) (EXTRA_NA): each NA value takes the value of a linear extrapolation of the two previous periods.
Simulation.initialization_method_long	At the start of each period to be simulated, a starting value must be chosen for each endogenous variable.
Simulation.max_nb_iterations	Maximum number of iterations to reach a solution.
Simulation.max_nb_iterations_newton	Maximum number of iterations when the Newton-Raphson algorithm is used.
Simulation.nb_passes	Number of passes to make when the pseudo-triangulation sorting algorithm is used.
Simulation.debug	Option to automatically generates IODE lists containing pre-recursive, interdependent and post-recursive equations: _PRE, _INTER and _POST.
Simulation.debug_newton	Save a trace of the sub-iterations when the Newton-Raphson alogrithm is used.
Simulation.nb_iterations(period)	Number of iterations to converge in the last simulation for the period period.
Simulation.save_nb_iterations(var_name)	Save the number of iterations needed to complete each simulated period in a new variable named var_name.
Simulation.norm(period)	Get the norm value of the last simulation for the period period.
Simulation.save_norms(var_name)	Save the lowest norm value reached to complete each simulated period in a new variable named var_name.
Simulation.model_exchange([list_exo])	Set a list of endogenous-exogenous pairs for goal seeking.
Simulation.model_compile([list_eqs, quiet])	Recompiles a list of equations, or all equations if no list is specified.
Simulation.model_simulate(from_period, to_period)	Run the simulation of a model for a given sample.
Simulation.model_calculate_SCC(nb_iterations)	Decompose the model into Strongly Connex Components (SCC) and reorder it.
Simulation.model_simulate_SCC(from_period, ...)	Simulates a model previously decomposed into Strongly Connex Components (SCC) and reordered.

LEC

execute_lec(lec[, period])

Compute a LEC formula using the current Variables and Scalars databases.

REPORTS

execute_report(filepath[, parameters])	Execute an IODE report.
execute_command(command)	Execute one or several IODE commands.
set_t(time)	Set the value of t in {report expressions}.
increment_t(increment)	Increment the value of t in {report expressions} by a given number of periods.

GRAPHICAL USER INTERFACE

view_workspace([directory_path, depth])

Open the Graphical User Interface to view and edit the IODE databases.

PRINT

write_destination(filename[, file_type])	Initialize a new output session
write_flush()	Flush the output session buffer
write_close()	End an output session
write([text])	Send a string into the current opened buffer
write_title(title[, level])	Print a title of the given level
write_enum(text[, level])	Print a bulleted paragraph of the given level
write_paragraph(text[, level])	Print a paragraph of the given level
write_code_block(text[, level])	Start a code block of the given level or end the block if level < 0
write_page_header(text)	Define the page header as from the current page
write_page_footer(text)	Define the page footer as from the current page

MISCELLANEOUS

is_NA(value)	Check whether a float value represents a valid IODE number or an IODE Not Available \(NA\) value.
suppress_msgs()	Suppress the output during an IODE session
enable_msgs()	Reset the normal output mechanism during an IODE session

DEPRECATED