Utilities

Utilities#

Utility functions for spiking neural networks.

Note

This module provides utility functions for loading rate models, generating connectivity parameters, and validating inputs for spiking neural network simulations.

Model Loading#

load_rate_model(model_path)#

Load a trained rate RNN model from MATLAB .mat file.

Parameters:

model_path (str) – Path to the .mat model file

Returns:

Dictionary containing model parameters

Return type:

dict

Raises:

  • FileNotFoundError – If model file doesn’t exist

  • ValueError – If file is not .mat format or corrupted

Network Configuration#

Validation Functions#

Analysis and Formatting#

Example Usage#

Loading Models:

from spiking.utils import load_rate_model

# Load .mat model file
model_data = load_rate_model('models/go-nogo/trained_model.mat')

Creating Network Connectivity:

from spiking.utils import create_connectivity_masks

N = 200  # Number of neurons
P_inh = 0.2  # Proportion of inhibitory neurons

inh, exc, m, som_m = create_connectivity_masks(
    N, P_inh, som_N=10, apply_dale=True, seed=42
)

Generating LIF Parameters:

from spiking.utils import generate_lif_params

# Default parameters
lif_params = generate_lif_params()

# Custom parameters
lif_params = generate_lif_params(dt=0.0001, downsample=2)

Validating Input:

from spiking.utils import validate_stimulus, validate_scaling_factor
import numpy as np

# Validate Go-NoGo stimulus
u = np.zeros((1, 201))  # 1 input, 201 timesteps
validate_stimulus(u, task_type='go-nogo')

# Validate scaling factor
validate_scaling_factor(50.0, valid_range=(20.0, 100.0))

Analyzing Spikes:

from spiking.utils import format_spike_data

# Format spike data for analysis
spike_data = format_spike_data(spikes, dt=0.00005)

print(f"Total spikes: {spike_data['total_spikes']}")
print(f"Mean firing rate: {np.mean(spike_data['firing_rates']):.2f} Hz")

GPU and Random Seed Management:

from spiking.utils import check_gpu_availability, set_random_seed

# Check GPU availability
gpu_available, device_name = check_gpu_availability()
print(f"GPU: {device_name}")

# Set random seed for reproducibility
set_random_seed(42)
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