Remove end keyword from NESTML models

.github/workflows/nestml-build.yml

@@ -124,7 +124,6 @@ jobs:
 
  - name: Generate Lexer and Parser using Antlr4
  run: |
- find pynestml/generated -not -name __init__.py -a -not -name generated -delete
  cd pynestml/grammars
  ./generate_lexer_parser
 

doc/models_library/aeif_cond_alpha.rst

@@ -45,9 +45,6 @@ iaf_cond_alpha, aeif_cond_exp
 
 Parameters
 ++++++++++
-
-
-
 .. csv-table::
  :header: "Name", "Physical unit", "Default value", "Description"
  :widths: auto
@@ -72,7 +69,6 @@ Parameters
 
 
 
-
 State variables
 +++++++++++++++
 
@@ -92,105 +88,18 @@ Equations
 
 
 
-
 .. math::
  \frac{ dV_{m} } { dt }= \frac 1 { C_{m} } \left( { (-g_{L} \cdot (V_{bounded} - E_{L}) + I_{spike} - I_{syn,exc} - I_{syn,inh} - w + I_{e} + I_{stim}) } \right) 
 
-
 .. math::
  \frac{ dw } { dt }= \frac 1 { \tau_{w} } \left( { (a \cdot (V_{bounded} - E_{L}) - w) } \right) 
 
 
 
-
-
 Source code
 +++++++++++
 
-.. code-block:: nestml
-
- neuron aeif_cond_alpha:
- state:
- V_m mV = E_L # Membrane potential
- w pA = 0pA # Spike-adaptation current
- end
- equations:
- inline V_bounded mV = min(V_m,V_peak) # prevent exponential divergence
- kernel g_inh = (e / tau_syn_inh) * t * exp(-t / tau_syn_inh)
- kernel g_exc = (e / tau_syn_exc) * t * exp(-t / tau_syn_exc)
- # Add inlines to simplify the equation definition of V_m
- inline exp_arg real = (V_bounded - V_th) / Delta_T
- inline I_spike pA = g_L * Delta_T * exp(exp_arg)
- inline I_syn_exc pA = convolve(g_exc,exc_spikes) * (V_bounded - E_exc)
- inline I_syn_inh pA = convolve(g_inh,inh_spikes) * (V_bounded - E_inh)
- V_m'=(-g_L * (V_bounded - E_L) + I_spike - I_syn_exc - I_syn_inh - w + I_e + I_stim) / C_m
- w'=(a * (V_bounded - E_L) - w) / tau_w
- end
-
- parameters:
- # membrane parameters
- C_m pF = 281.0pF # Membrane Capacitance
- t_ref ms = 0.0ms # Refractory period
- V_reset mV = -60.0mV # Reset Potential
- g_L nS = 30.0nS # Leak Conductance
- E_L mV = -70.6mV # Leak reversal Potential (aka resting potential)
- # spike adaptation parameters
-
- # spike adaptation parameters
- a nS = 4nS # Subthreshold adaptation
- b pA = 80.5pA # Spike-triggered adaptation
- Delta_T mV = 2.0mV # Slope factor
- tau_w ms = 144.0ms # Adaptation time constant
- V_th mV = -50.4mV # Threshold Potential
- V_peak mV = 0mV # Spike detection threshold
- # synaptic parameters
-
- # synaptic parameters
- E_exc mV = 0mV # Excitatory reversal Potential
- tau_syn_exc ms = 0.2ms # Synaptic Time Constant Excitatory Synapse
- E_inh mV = -85.0mV # Inhibitory reversal Potential
- tau_syn_inh ms = 2.0ms # Synaptic Time Constant for Inhibitory Synapse
- # constant external input current
-
- # constant external input current
- I_e pA = 0pA
- end
- internals:
- # Impulse to add to DG_EXC on spike arrival to evoke unit-amplitude conductance excursion
- PSConInit_E nS/ms = nS * e / tau_syn_exc
- # Impulse to add to DG_INH on spike arrival to evoke unit-amplitude conductance excursion
- PSConInit_I nS/ms = nS * e / tau_syn_inh
- # refractory time in steps
- RefractoryCounts integer = steps(t_ref)
- # counts number of tick during the refractory period
-
- # counts number of tick during the refractory period
- r integer 
- end
- input:
- inh_spikes nS <-inhibitory spike
- exc_spikes nS <-excitatory spike
- I_stim pA <-current
- end
-
- output: spike
-
- update:
- integrate_odes()
- if r > 0: # refractory
- r -= 1 # decrement refractory ticks count
- V_m = V_reset # clamp potential
- elif V_m >= V_peak:
- r = RefractoryCounts
- V_m = V_reset # clamp potential
- w += b
- emit_spike()
- end
- end
-
- end
-
-
+The model source code can be found in the NESTML models repository here: `aeif_cond_alpha <https://github.com/nest/nestml/tree/master/models/neurons/aeif_cond_alpha.nestml>`_.
 
 Characterisation
 ++++++++++++++++
@@ -200,4 +109,4 @@ Characterisation
 
 .. footer::
 
- Generated at 2022-03-28 19:04:29.432312
+ Generated at 2023-03-22 17:48:48.943078

doc/models_library/aeif_cond_exp.rst

@@ -46,9 +46,6 @@ iaf_cond_exp, aeif_cond_alpha
 
 Parameters
 ++++++++++
-
-
-
 .. csv-table::
  :header: "Name", "Physical unit", "Default value", "Description"
  :widths: auto
@@ -73,7 +70,6 @@ Parameters
 
 
 
-
 State variables
 +++++++++++++++
 
@@ -93,101 +89,18 @@ Equations
 
 
 
-
 .. math::
  \frac{ dV_{m} } { dt }= \frac 1 { C_{m} } \left( { (-g_{L} \cdot (V_{bounded} - E_{L}) + I_{spike} - I_{syn,exc} - I_{syn,inh} - w + I_{e} + I_{stim}) } \right) 
 
-
 .. math::
  \frac{ dw } { dt }= \frac 1 { \tau_{w} } \left( { (a \cdot (V_{bounded} - E_{L}) - w) } \right) 
 
 
 
-
-
 Source code
 +++++++++++
 
-.. code-block:: nestml
-
- neuron aeif_cond_exp:
- state:
- V_m mV = E_L # Membrane potential
- w pA = 0pA # Spike-adaptation current
- end
- equations:
- inline V_bounded mV = min(V_m,V_peak) # prevent exponential divergence
- kernel g_inh = exp(-t / tau_syn_inh)
- kernel g_exc = exp(-t / tau_syn_exc)
- # Add inlines to simplify the equation definition of V_m
- inline exp_arg real = (V_bounded - V_th) / Delta_T
- inline I_spike pA = g_L * Delta_T * exp(exp_arg)
- inline I_syn_exc pA = convolve(g_exc,exc_spikes) * (V_bounded - E_exc)
- inline I_syn_inh pA = convolve(g_inh,inh_spikes) * (V_bounded - E_inh)
- V_m'=(-g_L * (V_bounded - E_L) + I_spike - I_syn_exc - I_syn_inh - w + I_e + I_stim) / C_m
- w'=(a * (V_bounded - E_L) - w) / tau_w
- end
-
- parameters:
- # membrane parameters
- C_m pF = 281.0pF # Membrane Capacitance
- t_ref ms = 0.0ms # Refractory period
- V_reset mV = -60.0mV # Reset Potential
- g_L nS = 30.0nS # Leak Conductance
- E_L mV = -70.6mV # Leak reversal Potential (aka resting potential)
- # spike adaptation parameters
-
- # spike adaptation parameters
- a nS = 4nS # Subthreshold adaptation
- b pA = 80.5pA # Spike-triggered adaptation
- Delta_T mV = 2.0mV # Slope factor
- tau_w ms = 144.0ms # Adaptation time constant
- V_th mV = -50.4mV # Threshold Potential
- V_peak mV = 0mV # Spike detection threshold
- # synaptic parameters
-
- # synaptic parameters
- E_exc mV = 0mV # Excitatory reversal Potential
- tau_syn_exc ms = 0.2ms # Synaptic Time Constant Excitatory Synapse
- E_inh mV = -85.0mV # Inhibitory reversal Potential
- tau_syn_inh ms = 2.0ms # Synaptic Time Constant for Inhibitory Synapse
- # constant external input current
-
- # constant external input current
- I_e pA = 0pA
- end
- internals:
- # refractory time in steps
- RefractoryCounts integer = steps(t_ref)
- # counts number of tick during the refractory period
-
- # counts number of tick during the refractory period
- r integer 
- end
- input:
- inh_spikes nS <-inhibitory spike
- exc_spikes nS <-excitatory spike
- I_stim pA <-current
- end
-
- output: spike
-
- update:
- integrate_odes()
- if r > 0: # refractory
- r -= 1 # decrement refractory ticks count
- V_m = V_reset # clamp potential
- elif V_m >= V_peak:
- r = RefractoryCounts + 1
- V_m = V_reset # clamp potential
- w += b
- emit_spike()
- end
- end
-
- end
-
-
+The model source code can be found in the NESTML models repository here: `aeif_cond_exp <https://github.com/nest/nestml/tree/master/models/neurons/aeif_cond_exp.nestml>`_.
 
 Characterisation
 ++++++++++++++++
@@ -197,4 +110,4 @@ Characterisation
 
 .. footer::
 
- Generated at 2022-03-28 19:04:29.501988
+ Generated at 2023-03-22 17:48:48.899673