In this pull request, my first version of the Adaptive Rush-Larsen is implemented for the Trovato and ToRORd-fkatp cellular models. Basically, to use the Adaptive Rush-Larsen functions in CPU/GPU you need to implement an additional RHS function to calculate the coefficients 'a' and 'b', which are model-specific. In addition, you need to define a boolean mapping array, in order to tell if an equation is Hodkin-Huxley style or not. Please check the files from both models for more details on the implementation.
Furthermore, a new version of the 'trace_plot' script is also present in this commit. Using this new version the user can now plot the state-vector traces from a simulation which uses the 'save_as_text_or_binary' [save_result] function. This also works with multiple cells, you just need to provide a file with the cell coordinates to plot. For now, no Purkinje related function was tested.
Hello Sachetto,
In this pull request, my first version of the Adaptive Rush-Larsen is implemented for the Trovato and ToRORd-fkatp cellular models. Basically, to use the Adaptive Rush-Larsen functions in CPU/GPU you need to implement an additional RHS function to calculate the coefficients 'a' and 'b', which are model-specific. In addition, you need to define a boolean mapping array, in order to tell if an equation is Hodkin-Huxley style or not. Please check the files from both models for more details on the implementation.
Furthermore, a new version of the 'trace_plot' script is also present in this commit. Using this new version the user can now plot the state-vector traces from a simulation which uses the 'save_as_text_or_binary' [save_result] function. This also works with multiple cells, you just need to provide a file with the cell coordinates to plot. For now, no Purkinje related function was tested.
Best regards, Lucas