API Reference#

Complete API reference for all public functions in pyperfectforesight.

Utilities#

pyperfectforesight.v

Time-indexed symbolic variable

Model processing#

`pyperfectforesight.process_model`	Process model equations and compile to numeric functions
`pyperfectforesight.lead_lag_incidence`	Detect which variables appear at which time lags in the equations
`pyperfectforesight.is_static`	Check if an equation contains only current period variables
`pyperfectforesight.eliminate_static`	Eliminate static variables from dynamic equations
`pyperfectforesight.local_blocks`	Compute symbolic Jacobian blocks for all lags present in equations

Steady state#

`pyperfectforesight.SteadyState`	A steady-state solution with full provenance (params and exogenous values).
`pyperfectforesight.compile_steady_state_funcs`	Compile steady-state residual functions once for repeated use with different parameters.
`pyperfectforesight.solve_steady_state`	Solve for the steady state using pre-compiled functions.
`pyperfectforesight.compute_steady_state_numerical`	Compute steady state numerically by solving the system where all time-indexed variables are set to their steady-state values

High-level solvers#

`pyperfectforesight.solve_perfect_foresight`	Solve the perfect foresight problem using an augmented-path BVP formulation.
`pyperfectforesight.solve_perfect_foresight_homotopy`	Solve a perfect foresight model using homotopy (parameter continuation).
`pyperfectforesight.solve_perfect_foresight_expectation_errors`	Solve a perfect foresight model with multiple surprise (MIT) shocks.

Initial guess#

pyperfectforesight.make_initial_guess

Generate an initial guess path for the perfect foresight solver.

Auxiliary variables#

`pyperfectforesight.solve_auxiliary_nested`	Solve auxiliary equations numerically for a single time period (nested method)
`pyperfectforesight.compute_auxiliary_variables`	Compute auxiliary variables from dynamic variable solution

Low-level solver components#

`pyperfectforesight.residual`	Evaluate residuals of the dynamic equations
`pyperfectforesight.sparse_jacobian`	Build sparse Jacobian matrix using block structure
`pyperfectforesight.append_terminal_conditions`	Append terminal conditions to enforce convergence to steady state