Skip to content

Improve numerical stability of some tests. #466

New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

Sign up for GitHub

By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.

Already on GitHub? Sign in to your account

Merged
merged 1 commit into from
Oct 6, 2016
Merged

Improve numerical stability of some tests. #466

Show file tree
Hide file tree
Changes from all commits
Commits
Show all changes
1 commit
Select commit
File filter

Filter by extension

Filter by extension
Conversations
Failed to load comments.
Loading
Jump to
Jump to file
Failed to load files.
Loading
Diff view
Diff view
312 changes: 152 additions & 160 deletions testsuite/unittests/test_tsodyks_depressing.sli
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -31,7 +31,9 @@ Script to test Tsodyks short term plasticity depressing synapses according to
Misha Tsodyks, Klaus Pawelzik, Henry Markram
Neural computation 10, 821--853 (1998)

reproduces figure 1 A
Reproduces figure 1 A

Revised by Hans Ekkehard Plesser 2016 using explicit input spike train.

Author: Markus Diesmann, Moritz Helias
FirstVersion: March 2006
Expand All @@ -40,172 +42,162 @@ FirstVersion: March 2006
(unittest) run
/unittest using

% -------
%
% Expected solution
%
% -------

[/tsodyks_synapse /tsodyks_synapse_hom] {
/tsodyks_model Set

ResetKernel % clear all existing network elements
/vm_expected
[
[25 0]
[50 0]
[75 0]
[100 2.401350000000000e+00]
[125 5.302440000000000e+00]
[150 4.108330000000000e+00]
[175 4.322170000000000e+00]
[200 3.053390000000000e+00]
[225 2.871240000000000e+00]
[250 2.028640000000000e+00]
[275 1.908020000000000e+00]
[300 1.396960000000000e+00]
[325 1.375850000000000e+00]
[350 1.057780000000000e+00]
[375 1.103490000000000e+00]
[400 8.865690000000001e-01]
[425 9.693530000000000e-01]
[450 8.028760000000000e-01]
[475 9.046710000000000e-01]
[500 7.626880000000000e-01]
[525 8.738550000000000e-01]
[550 7.435880000000000e-01]
[575 8.592780000000000e-01]
[600 7.345670000000000e-01]
[625 8.524119999999999e-01]
[650 7.303210000000000e-01]
[675 8.491860000000000e-01]
[700 7.283280000000000e-01]
[725 8.476730000000000e-01]
[750 7.273930000000000e-01]
[775 8.469640000000001e-01]
[800 7.269550000000000e-01]
[825 8.466320000000001e-01]
[850 7.267500000000000e-01]
[875 8.464760000000000e-01]
[900 7.266540000000000e-01]
[925 8.464030000000000e-01]
[950 7.266089999999999e-01]
[975 8.463690000000000e-01]
[1000 7.265880000000000e-01]
[1025 8.463530000000000e-01]
[1050 7.265779999999999e-01]
[1075 8.463460000000000e-01]
[1100 4.531260000000000e-01]
[1125 2.425410000000000e-01]
[1150 1.298230000000000e-01]
[1175 6.948920000000000e-02]
]
def

% ---------
% Model parameters
% ---------

/local_num_threads 1 def
/h 0.1 def

/Tau 40.0 def % membrane time constant
/Theta 15.0 def % threshold
/E_L 0.0 def % reset potential of Vm
/R 1.0 def
/C Tau R div def % Tau [ms] / 1.0 GOhm in NEST units
/TauR 2.0 def % refractory time
/Tau_psc 3.0 def % time constant of PSC (=Tau_inact)
/Tau_rec 800.0 def % recovery time
/Tau_fac 0.0 def % facilitation time: 0 == no facilitation
/U 0.5 def % facilitation parameter U
/A 250.0 def % PSC weight in pA

/input_train
[
98.0 % first spike [ms]
1048.0 % last spike [ms]
50.0 % interspike interval [ms]
] Range def

/T_sim 1200. def % simulation time [ms]

userdict begin
% ---------

1 /local_num_threads Set
8 /total_num_virtual_procs Set
0.1 /h Set
[/tsodyks_synapse /tsodyks_synapse_hom]
{
/synapse_model Set

/Tau 40.0 def % membrane time constant
/Theta 15.0 def % threshold
/E_L 0.0 def % reset potential of Vm
/R 1.0 def
/C Tau R div def % Tau [ms] / 1.0 GOhm in NEST units
/TauR 2.0 def % refractory time
/Tau_psc 3.0 def % time constant of PSC (=Tau_inact)
/Tau_rec 800.0 def % recovery time
/Tau_fac 0.0 def % facilitation time
/U 0.5 def % facilitation parameter U
/A 250.0 def % PSC weight in pA
/f 20.0 1000.0 div def % frequency in Hz given converted to 1/ms
ResetKernel % clear all existing network elements

/Tend 1200.0 def % simulation time
/TIstart 50.0 def % start time of current
/TIend 1050.0 def % end time of current


% set resolution and limits on delays
% limits must be set BEFORE connecting any elements
0
<<
/resolution h
/local_num_threads local_num_threads
% /total_num_virtual_procs total_num_virtual_procs
>> SetStatus

cout 15 setprecision

tsodyks_model
<< /tau_psc Tau_psc
/tau_rec Tau_rec
/tau_fac Tau_fac
/U U
/delay 0.1
/weight A
/u 0.0
/x 1.0
>> SetDefaults

/iaf_tum_2000 Create /neuron1 Set

neuron1 << /tau_m Tau
/t_ref_tot TauR
/t_ref_abs TauR
/tau_syn_ex Tau_psc
/tau_syn_in Tau_psc
/C_m C
/V_reset E_L
/E_L E_L
/V_th Theta
/V_m E_L
>> SetStatus
% neuron1 GetStatus info

/iaf_tum_2000 Create /neuron2 Set

neuron2 << /tau_m Tau
/t_ref_tot TauR
/t_ref_abs TauR
/tau_syn_ex Tau_psc
/tau_syn_in Tau_psc
/C_m C
/V_reset E_L
/E_L E_L
/V_th Theta
/V_m E_L
>> SetStatus
% neuron2 GetStatus info

/I0 Theta C mul Tau div 1.0 1.0 f div TauR sub Tau div neg exp sub div def

/dc_generator Create /dc_gen Set
dc_gen << /amplitude I0 /start TIstart /stop TIend >> SetStatus

/voltmeter Create /vm Set
vm << /withtime true
/to_memory true
/interval 25.0
>> SetStatus

dc_gen neuron1 Connect

vm neuron2 Connect

neuron1 neuron2 tsodyks_model Connect

Tend Simulate

% compare results to expected voltage trace
vm [/events [/times /V_m]] get cva
6 ToUnitTestPrecision
Transpose /vm_sim Set % array of recorded data

% to print to screen
%vm_sim {
% ==
%} forall


[
[25 0]
[50 0]
[75 0]
[100 2.401350000000000e+00]
[125 5.302440000000000e+00]
[150 4.108330000000000e+00]
[175 4.322170000000000e+00]
[200 3.053390000000000e+00]
[225 2.871240000000000e+00]
[250 2.028640000000000e+00]
[275 1.908020000000000e+00]
[300 1.396960000000000e+00]
[325 1.375850000000000e+00]
[350 1.057780000000000e+00]
[375 1.103490000000000e+00]
[400 8.865690000000001e-01]
[425 9.693530000000000e-01]
[450 8.028760000000000e-01]
[475 9.046710000000000e-01]
[500 7.626880000000000e-01]
[525 8.738550000000000e-01]
[550 7.435880000000000e-01]
[575 8.592780000000000e-01]
[600 7.345670000000000e-01]
[625 8.524119999999999e-01]
[650 7.303210000000000e-01]
[675 8.491860000000000e-01]
[700 7.283280000000000e-01]
[725 8.476730000000000e-01]
[750 7.273930000000000e-01]
[775 8.469640000000001e-01]
[800 7.269550000000000e-01]
[825 8.466320000000001e-01]
[850 7.267500000000000e-01]
[875 8.464760000000000e-01]
[900 7.266540000000000e-01]
[925 8.464030000000000e-01]
[950 7.266089999999999e-01]
[975 8.463690000000000e-01]
[1000 7.265880000000000e-01]
[1025 8.463530000000000e-01]
[1050 7.265779999999999e-01]
[1075 8.463460000000000e-01]
[1100 4.531260000000000e-01]
[1125 2.425410000000000e-01]
[1150 1.298230000000000e-01]
[1175 6.948920000000000e-02]
] /vm_expected Set

vm_sim vm_expected eq assert_or_die

end
% set resolution and limits on delays
% limits must be set BEFORE connecting any elements
0
<<
/resolution h
/local_num_threads local_num_threads
>> SetStatus

/sg /spike_generator << /spike_times input_train >> Create def
/pn /parrot_neuron Create def

/neuron
/iaf_tum_2000
<< /tau_m Tau
/t_ref_tot TauR
/t_ref_abs TauR
/tau_syn_ex Tau_psc
/tau_syn_in Tau_psc
/C_m C
/V_reset E_L
/E_L E_L
/V_th Theta
/V_m E_L >>
Create def

/vm
/voltmeter
<< /withtime true
/to_memory true
/interval 25.0
>>
Create def

synapse_model
<< /tau_psc Tau_psc
/tau_rec Tau_rec
/tau_fac Tau_fac
/U U
/delay 0.1
/weight A
/u 0.0
/x 1.0
>> SetDefaults

sg pn Connect % pn required, devices cannot project to plastic synapses
pn neuron synapse_model Connect
vm neuron Connect

T_sim Simulate

% compare results to expected voltage trace
vm [/events [/times /V_m]] get cva
6 ToUnitTestPrecision
Transpose /vm_sim Set % array of recorded data

% to print to screen
vm_sim {
==
} forall

vm_sim vm_expected eq assert_or_die

} forall % tsodyks models

Expand Down
Loading