Open-source, graph-based Python code generator and analysis toolbox for dynamical systems (pre-implemented and custom models). Most pre-implemented models belong to the family of neural population models.
maxi
and mini
in the equations. Both functions take two input arguments, and return the larger/smaller one, respectivelyadaptive
to the CircuitTemplate.get_run_func
method, which allows to indicate whether the generated equation file is expected to be called with an adaptive step-size solver (adaptive=True
) or notCircuitIR
instantiationCircuitTemplate
that allow to remember the state of all network variables from a previous simulation, even if a new backend is chosen for function generation or more simulationsgrid_search
functionvectorization
of the function grid_search
to vectorize
, to be consistent with the naming of the same argument in CircuitTemplate.run
CircuitTemplate.add_edges_from_matrix
method to allow for edges that connect separate network nodesThis official release is a combination of all the bug fixes and improvements in the pre 1.0 versions up to v0.17.4.
It establishes PyRates as a code-generation tool for dynamical systems modeling with a flexible, intuitive, and well organized language for model definition. At this stage, PyRates comes with support for ordinary and delayed differential equations and can generate vector-field evaluation functions for any ODE/DDE system for each of the following backends:
Minor improvements since 0.17.4:
template_specification.rst
CircuitTemplate.get_run_func
, respectively, now use the frontend variable names instead of the backend variable namesCircuitIR.get_frontend_varname
that returns the frontend variable name given a backend variable name