nest.tests.test_sp package¶
Submodules¶
nest.tests.test_sp.mpitest_issue_578_sp module¶
nest.tests.test_sp.test_conn_builder module¶
nest.tests.test_sp.test_disconnect module¶
nest.tests.test_sp.test_disconnect_multiple module¶
nest.tests.test_sp.test_enable_multithread module¶
nest.tests.test_sp.test_get_sp_status module¶
Structural Plasticity GetStatus Test¶
This tests the functionality of the GetStructuralPlasticityStatus function
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class
nest.tests.test_sp.test_get_sp_status.
TestGetStructuralPlasticityStatus
(methodName='runTest')[source]¶ Bases:
unittest.case.TestCase
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all
= {'structural_plasticity_synapses': {'syn1': {'model': 'synapse_ex', 'post_synaptic_element': 'Den_ex', 'pre_synaptic_element': 'Axon_ex'}}, 'structural_plasticity_update_interval': 1000}¶
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growth_curve
= {'continuous': False, 'eps': 0.05, 'eta': 0.0, 'growth_curve': 'gaussian', 'growth_rate': 0.0001}¶ Now we assign the growth curves to the corresponding synaptic elements
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neuron_model
= 'iaf_psc_alpha'¶
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nodes
= (1, 2)¶
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sp_interval
= 1000¶
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sp_synapses
= {'syn1': {'model': 'synapse_ex', 'post_synaptic_element': 'Den_ex', 'pre_synaptic_element': 'Axon_ex'}}¶
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syn
= {'model': 'synapse_ex', 'post_synaptic_element': 'Den_ex', 'pre_synaptic_element': 'Axon_ex'}¶
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synaptic_elements
= {'Axon_ex': {'growth_curve': 'gaussian', 'growth_rate': 0.0001, 'continuous': False, 'eta': 0.0, 'eps': 0.05}, 'Den_ex': {'growth_curve': 'gaussian', 'growth_rate': 0.0001, 'continuous': False, 'eta': 0.0, 'eps': 0.05}, 'Den_in': {'growth_curve': 'gaussian', 'growth_rate': 0.0001, 'continuous': False, 'eta': 0.0, 'eps': 0.05}}¶
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nest.tests.test_sp.test_growth_curves module¶
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class
nest.tests.test_sp.test_growth_curves.
GaussianNumericSEI
(eta=0.1, eps=0.7, growth_rate=1.0, *args, **kwargs)[source]¶ Bases:
nest.tests.test_sp.test_growth_curves.SynapticElementIntegrator
Compute the number of synaptic element corresponding to a linear growth curve dse/dCa = nu * (2 * exp( ((Ca - xi)/zeta)^2 ) - 1) with:
xi = (eta + eps) / 2.0 zeta = (eta - eps) / (2.0 * sqrt(ln(2.0)))Use numerical integration (see scipy.integrate.quad)
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class
nest.tests.test_sp.test_growth_curves.
LinearExactSEI
(eps=0.7, growth_rate=1.0, *args, **kwargs)[source]¶ Bases:
nest.tests.test_sp.test_growth_curves.SynapticElementIntegrator
Compute the number of synaptic element corresponding to a linear growth curve dse/dCa = nu * (1 - Ca/eps) Use the exact solution
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class
nest.tests.test_sp.test_growth_curves.
LinearNumericSEI
(eps=0.7, growth_rate=1.0, *args, **kwargs)[source]¶ Bases:
nest.tests.test_sp.test_growth_curves.SynapticElementIntegrator
Compute the number of synaptic element corresponding to a linear growth curve dse/dCa = nu * (1 - Ca/eps) Use numerical integration (see scipy.integrate.quad)
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class
nest.tests.test_sp.test_growth_curves.
SigmoidNumericSEI
(eps=0.7, growth_rate=1.0, psi=0.1, *args, **kwargs)[source]¶ Bases:
nest.tests.test_sp.test_growth_curves.SynapticElementIntegrator
Compute the number of synaptic element corresponding to a sigmoid growth curve dse/dCa = nu * ((2.0 / exp( (Ca - eps)/psi)) - 1.0)
Use numerical integration (see scipy.integrate.quad)
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class
nest.tests.test_sp.test_growth_curves.
SynapticElementIntegrator
(tau_ca=10000.0, beta_ca=0.001)[source]¶ Bases:
object
Generic class which describes how to compute the number of Synaptic Element based on Ca value Each derived class should overwrite the get_se(self, t) method
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get_se
(t)[source]¶ Parameters: (float) (t) – current time Returns: Number of synaptic element Should be overwritten
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