Source code for tvb.rateML.run.regular_run

from tvb.simulator.lab import *

import numpy as np
import math

import matplotlib.pyplot as plt

from tvb.rateML.XML2model import RateML

[docs] class regularRun: def __init__(self, sim_length, g, s, dt, period, omega = 60, filename='connectivity_zerlaut_68.zip'): # def __init__(self, sim_length, g, s, dt, period, omega = 60, filename='paupau.zip'): self.sim_length = sim_length self.g = np.array([g]) self.s = np.array([s]) self.dt = dt self.period = period self.omega = omega * 2.0 * math.pi / 1e3 (self.connectivity, self.coupling) = self.tvb_connectivity(filename) self.SC = self.connectivity.weights
[docs] def tvb_connectivity(self, filename): white_matter = connectivity.Connectivity.from_file(source_file=filename) white_matter.configure() white_matter.speed = np.array([self.s]) # white_matter_coupling = coupling.Linear(a=self.g) # white_matter_coupling = coupling.Scaling(a=self.g) white_matter_coupling = coupling.Coupling() return white_matter, white_matter_coupling
[docs] def tvb_python_model(self, modelExec): # populations = models.Generic2dOscillator() # original # populations = models.KuramotoT() # generated # populations = models.OscillatorT() # generated # populations = models.MontbrioT() # generated # populations = models.RwongwangT() # generated # populations = models.EpileptorT() # generated model = 'models.' + modelExec + '()' populations = eval(model) populations.configure() populations.omega = np.array([self.omega]) return populations
[docs] def simulate_python(self, modelExec): # Initialize Model model = self.tvb_python_model(modelExec) # zerlaut setup noises = noise.Additive(nsig=np.array([0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 1.0]), ntau=0.0) integrator = integrators.HeunStochastic(dt=.1, noise=noises) # Initialize integrator # Initialize Monitors monitorsen = (monitors.TemporalAverage(period=self.period)) # Initialize Simulator sim = simulator.Simulator(model=model, connectivity=self.connectivity, coupling=coupling.Linear(a=np.array(self.g), b=np.array(0.0)), integrator=integrator, monitors=[monitorsen]) sim.configure() # sim.history.buffer[:] = 0.0 # sim.current_state[:] = 0.0 # print('shb', sim.history.buffer.shape) # ('n_time', 'n_cvar', 'n_node', 'n_mode') (time, data) = sim.run(simulation_length=self.sim_length)[0] # pad some zeros to make it equivalent to GPU for comparison # CPU is now +1 timestep longer # data = np.insert(data, 0, 0, axis=0) # data = data[:-1] # print('ds',data.shape) plt.plot((data[:, 0, :, 0]), 'k', alpha=.2) plt.show() return (time, data)
if __name__ == '__main__': # model_filename = 'Oscillator' # language='python' # # RateML(model_filename, language) simtime = 2000 g = .4 # g = 0.0042 s = 4.0 dt = .1 period = 10 model = 'Zerlaut_adaptation_second_order' (time, data) = regularRun(simtime, g, s, dt, period).simulate_python(model)