Hi all,

I have just merged PR #764 [1], which has some implications for the interactive problem description files (especially for time-dependent problems), because the imperative API has been revisited. The PR #764 addresses the long standing issue #378 [2] which caused a number of subtle bugs. The main changed are listed below, for more see the PR page.

I recommend looking at [3], [4], [5] - do not hesitate to ask in case of problems.

[1] https://github.com/sfepy/sfepy/pull/764 [2] https://github.com/sfepy/sfepy/issues/378 [3] https://sfepy.org/doc-devel/examples/diffusion-time_poisson_interactive.html [4] https://sfepy.org/doc-devel/examples/linear_elasticity-its2D_interactive.htm... [5] https://sfepy.org/doc-devel/primer.html#running-sfepy-in-interactive-mode

Description of the changes:

Old (replaced) API:

• State instance holds a global DOF vector that contains as contiguous sub-vectors (slices) the data of the unknown (state) variables from the Variables container.
• Possible to set DOF vector to a variable without changing the DOF vector in the State instance that contains the variable. -> Prone to hard-to-debug bugs (#378)
• Inconsistent naming of functions (historical code evolution).

New API:

• No State, only Variables.
• Once Variables.init_state() is called, the state variables are locked - cannot use variable.set_data() directly.
• Problem.solve() and other functions that worked/returned State instance return now the Variables instance instead.
• Declarative problem description API not affected.
• Imperative problem description API changed in a not backward-compatible way due to:
  • Renamed or removed functions (mostly Variables and related Equations methods and former State methods).
  • Locking of the state variables.
  • No need to create State instances (no State class).
  • Problem.create_state() is now an alias to Problem.get_initial_state(), which sets up initial conditions - those have to be set using Problem.set_ics() before Problem.create_state()/.get_initial_state() are called.
  • Stationary examples likely affected only in post-processing of results, after calling Problem.solve().
  • Time dependent examples need to be adjusted already when dealing with the initial state: calling Problem.get_initial_state() should do the job (provided the conditions are set, see above).

Best regards, r.