* Removed old/unnecessary models
* Added a `simulation.{iter_}from_py` method to load simulations from python
files
* Changed tests of examples to run programmatic simulations
* Fixed programmatic examples
Treating time and conditions as the same entity was getting confusing, and it
added a lot of unnecessary abstraction in a critical part (the scheduler).
The scheduling queue now has the time as a floating number (faster), the agent
id (for ties) and the condition, as well as the agent. The first three
elements (time, id, condition) can be considered as the "key" for the event.
To allow for agent execution to be "randomized" within every step, a new
parameter has been added to the scheduler, which makes it add a random number to
the key in order to change the ordering.
`EventedAgent.received` now checks the messages before returning control to the
user by default.
* Removed references to `set_state`
* Split some functionality from `agents` into separate files (`fsm` and
`network_agents`)
* Rename `neighboring_agents` to `neighbors`
* Delete some spurious functions
Documentation needs some improvement
The API has been simplified to only allow for ONE topology per
NetworkEnvironment.
This covers the main use case, and simplifies the code.
All tests pass but some features are still missing/unclear:
- Mesa agents do not have a `state`, so their "metrics" don't get stored. I will
probably refactor this to remove some magic in this regard. This should get rid
of the `_state` dictionary and the setitem/getitem magic.
- Simulation is still different from a runner. So far only Agent and
Environment/Model have been updated.
See CHANGELOG.md for a full list of changes
* Removed nxsim
* Refactored `agents.NetworkAgent` and `agents.BaseAgent`
* Refactored exporters
* Added stats to history
