v0.5.0

Minor fixes, primarily the Duplex connection now works properly.

v0.4.9

This release adds the capability to solve for the time independent Steady State

• adds special SteadyState subclass of ImplicitSolver, utilizing the existing optimizers
• bidirectional connnections called Duplex that couple two IO pairs as a subclass of Connection, useful for RF systems with ports

v0.4.8

This release mostly handles a better integration of the AD framework into the solver suite.

• reworked event handling system to act on blocks directly for monitoring and resoution, makes it more versatile
• simulation initialization now utilizes the add_xx methods and is therefore more streamlined
• introduced optim module that houses the AD framework and the solvers for the implicit update equation s for implicit solvers
• the AD framework now has functions for jacobian evaluation and a decorator to compute jacobians automatically
• extended the implicit update equation solver suite by newton-type methods that leverage the AD framework to get the jacobians (experimental and not used currently)
• implicit integrators now support the Value class from the AD framework, this makes stiff systems fully differentiable

v0.4.7

• Event handling system with zero-crossing detection and handling of scheduled events with error control, compatible with all integrators
• 25% faster AD by using integer indexing for gradient references in Value class
• blocks, connections and events are the three major system components that are managed by the Simulation class now
• blocks, connections and events have on and off methods that enable activating and deactivating them (dynamically, based on events or for debugging purposes) in the simulation

v0.4.6

• reworked error controllers for the adaptive timestep integrators
• added GEAR type integrators to the solver library (multistep methods with adaptive timestep and adaptive order selection)

v0.4.5

• fixed path length estimation for nested subsystems and added tests and an example
• renamed utils.funcs to utils.utils, which makes more sense

v0.4.4

• minor fixes
• fixed RKDP54 butcher table
• test coverage for Value and Parameter classes for AD framework

v0.4.3

• refactoring of numerical integrators (solvers), separate parent classes for diagonally implicit and explicit runge kutta methods simplifies the specific methods significantly
• performance of runge kutta methods improved >10% by using explicit loops with indexing to construct slope instead of sum comprehension

Enhanced AD and Fixes

• created interface for automatic differentiation framework to numpy ufuncs
• updated testsuite
• general bugfixing regarding implicit solvers (jacobian computation)

AD

Lots of refactors, improvements and new features since the last release including:

• Added rudimentary automatic differentiation (AD) framework in pathsim.diff to make the simulations differentiable w.r.t. predefined parameters
• Refactoring of numerical integrators to be compatible with AD framework for transient simulation
• Added lots of test, initial coverage was above 85%, more coming in the future
• Overall cleanup