STDP synapse and IAF neuron generation for the compartmental feature [WIP] #1103
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…plates_fix Maint/updated jinja templates fix
…dated-jinja-templates
…wert_cm_stdp # Conflicts: # pynestml/codegeneration/nest_compartmental_code_generator.py # pynestml/codegeneration/printers/cpp_function_call_printer.py # tests/nest_compartmental_tests/resources/continuous_test.nestml # tests/nest_tests/stdp_triplet_synapse_test.py
…ation # Conflicts: # pynestml/codegeneration/nest_compartmental_code_generator.py
ToDO: - convolve calls for synapses - printing for all control-structures in update and function blocks - syntax for self_spike - rigorous testing - merge of redundant ast_collectors - template file divide for mechanisms
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I believe the executing package should be added to the dependencies. |
LeanderEwert
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…wert_cm_stdp # Conflicts: # pynestml/codegeneration/nest_compartmental_code_generator.py # pynestml/codegeneration/resources_nest/point_neuron/common/SynapseHeader.h.jinja2 # pynestml/codegeneration/resources_nest_compartmental/cm_neuron/cm_neuroncurrents_@[email protected] # pynestml/transformers/synapse_post_neuron_transformer.py # pynestml/utils/ast_vector_parameter_setter_and_printer.py
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Making the creation of NESTML synapses compatible with the compartmental feature requires adjustments, as the compartmental neuron generation pipeline constructs neurons in a fundamentally different way. Since NESTML synapses are paired with their post-synaptic neuron during generation, the STDP feature must be specifically implemented for the compartmental pipeline.
The lack of cross-compartment or global variable access has made it impossible, or at least very difficult and unintuitive, to write IAF neurons.
The solutions to both problems have significant overlap, which is why both will be addressed in this pull request.