Kernel attributes (nest.NestModule)¶
The NEST kernel can be controlled from the PyNEST interface by getting or
setting attributes on the nest module:
# set a single kernel attribute
nest.resolution = 0.1
# set multiple attributes at once
nest.set(min_delay=0.1, max_delay=2.0)
# if you have the attributes in a dictionary
params = {'min_delay': 0.1, 'max_delay': 2.0}
nest.set(**params)
Here is a list of attributes that can be get and/or set on the nest module:
- class nest.NestModule(name)¶
A module class for the
nestroot module to control the dynamic generation of module level attributes such as the KernelAttributes, lazy loading some submodules and importing the public APIs of the lib submodules.- adaptive_target_buffers¶
Whether MPI buffers for communication of connections resize on the fly, defaults to
True.- Type:
- buffer_size_spike_data¶
Total size of MPI buffer for communication of spikes, defaults to
2.- Type:
- buffer_size_target_data¶
Total size of MPI buffer for communication of connections, defaults to
2.- Type:
- dict_miss_is_error¶
Whether missed dictionary entries are treated as errors, defaults to
True.- Type:
- eprop_learning_window¶
Task-specific learning window of the e-prop plasticity mechanism [ms]., defaults to
1000.0.- Type:
- eprop_reset_neurons_on_update¶
If True, reset dynamic variables of e-prop neurons upon e-prop update., defaults to
True.- Type:
- eprop_update_interval¶
Task-specific update interval of the e-prop plasticity mechanism [ms]., defaults to
1000.0.- Type:
- get(*args)¶
Forward kernel attribute getting to GetKernelStatus().
- growth_curves¶
The list of the available structural plasticity growth curves.
read only
- growth_factor_buffer_target_data¶
If MPI buffers for communication of connections resize on the fly, grow them by this factor each round, defaults to
1.5.- Type:
- keep_source_table¶
Whether to keep source table after connection setup is complete, defaults to
True.- Type:
- local_spike_counter¶
Number of spikes fired by neurons on a given MPI rank during the most recent call to
Simulate(). Only spikes from “normal” neurons are counted, not spikes generated by devices such aspoisson_generator. Resets on each call toSimulateorRun..read only
- Type:
- max_buffer_size_target_data¶
Maximal size of MPI buffers for communication of connections, defaults to
16777216.- Type:
- max_update_time¶
Longest wall-clock time measured so far for a full update step [seconds].
read only
- Type:
- min_update_time¶
Shortest wall-clock time measured so far for a full update step [seconds].
read only
- Type:
- ms_per_tic¶
The number of milliseconds per tic. Calculated by ms_per_tic = 1 / tics_per_ms.
read only
- Type:
- node_models¶
The list of the available node (i.e., neuron or device) models.
read only
- off_grid_spiking¶
Whether to transmit precise spike times in MPI communication.
read only
- Type:
- print_time¶
Whether to print progress information during the simulation, defaults to
False.- Type:
- raster_plot = <module 'nest.raster_plot' from '/home/docs/checkouts/readthedocs.org/user_builds/nest-simulator/checkouts/latest/pynest/nest/raster_plot.py'>¶
- recv_buffer_size_secondary_events¶
Size of MPI recv buffers for communicating secondary events (in bytes, per MPI rank, for developers).
read only
- Type:
- rng_seed¶
Seed value used as base for seeding NEST random number generators (\(1 \leq s\leq 2^{32}-1\)), defaults to
143202461.- Type:
- send_buffer_size_secondary_events¶
Size of MPI send buffers for communicating secondary events (in bytes, per MPI rank, for developers).
read only
- Type:
- property server¶
Wrap lazy loaded property.
- set(**kwargs)¶
Forward kernel attribute setting to SetKernelStatus().
- spike_buffer_grow_extra¶
When spike exchange buffer is expanded, resize it to (1 + spike_buffer_grow_extra) * required_buffer_size, defaults to
0.5.- Type:
- spike_buffer_resize_log¶
Log of spike buffer resizing as a dictionary. It contains the times of the resizings (simulation clock in steps, always multiple of
min_delay),global_max_spikes_sent, that is, the observed spike number that triggered the resize, and thenew_buffer_size. Sizes for the buffer section sent from one rank to another rank.read only
- Type:
- spike_buffer_shrink_limit¶
If the largest number of spikes sent from any rank to any rank is less than spike_buffer_shrink_limit * buffer_size, then reduce buffer size. spike_buffer_shrink_limit == 0 means that buffers never shrink. See
spike_buffer_shrink_sparefor how the new buffer size is determined, defaults to0.2.- Type:
- spike_buffer_shrink_spare¶
When the buffer shrinks, set the new size to (1 + spike_buffer_shrink_spare) * required_buffer_size. See spike_buffer_shrink_limit for when buffers shrink, defaults to
0.1.- Type:
- structural_plasticity_synapses¶
Defines all synapses which are plastic for the structural plasticity algorithm. Each entry in the dictionary is composed of a synapse model, the presynaptic element and the postsynaptic element.
- Type:
- structural_plasticity_update_interval¶
Defines the time interval in ms at which the structural plasticity manager will make changes in the structure of the network ( creation and deletion of plastic synapses), defaults to
10000.- Type:
- tics_per_ms¶
The number of tics per millisecond. Change of tics_per_ms requires simultaneous specification of resolution, defaults to
1000.0.- Type:
- tics_per_step¶
The number of tics per simulation time step. Calculated as tics_per_step = resolution * tics_per_ms.
read only
- Type:
- update_time_limit¶
Maximum wall-clock time for one full update step [seconds]. This can be used to terminate simulations that slow down significantly. Simulations may still get stuck if the slowdown occurs within a single update step, defaults to
inf.- Type:
- use_compressed_spikes¶
Whether to use spike compression; if a neuron has targets on multiple threads of a process, this switch makes sure that only a single packet is sent to the process instead of one packet per target thread; it implies that connections are sorted by source., defaults to
True.- Type:
- userdict = {}¶
The variable userdict allows users to store custom data with the NEST kernel.
Example: nest.userdict[“nodes”] = [1,2,3,4]
- visualization = <module 'nest.visualization' from '/home/docs/checkouts/readthedocs.org/user_builds/nest-simulator/checkouts/latest/pynest/nest/visualization.py'>¶
- voltage_trace = <module 'nest.voltage_trace' from '/home/docs/checkouts/readthedocs.org/user_builds/nest-simulator/checkouts/latest/pynest/nest/voltage_trace.py'>¶
- wfr_interpolation_order¶
Interpolation order of polynomial used in wfr iterations, defaults to
3.- Type:
- wfr_max_iterations¶
Maximal number of iterations used for waveform relaxation, defaults to
15.- Type: