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Given the following text description, write Python code to implement the functionality described below step by step
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Description:
 Demonstrate using the simulator at the region level, deterministic interation.
Run time
Step1:  Perform the simulation
Step2:  ####Plot pretty pictures of what we just did
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Python Code:
from tvb.simulator.lab import *
import datetime
START_TIME = datetime.datetime.now()
Explanation: Demonstrate using the simulator at the region level, deterministic interation.
Run time: approximately 120 seconds (workstation circa 2013)
Memory requirement: < 1GB
End of explanation
LOG.info("Configuring...")
#Initialise a Model, Coupling, and Connectivity.
oscillator = models.Generic2dOscillator()
white_matter = connectivity.Connectivity(load_default=True)
white_matter.speed = numpy.array([3.0])
white_matter_coupling = coupling.Linear()
#Initialise an Integrator
heunint = integrators.HeunDeterministic()
#Initialise some Monitors with period in physical time
momo = monitors.Raw()
mama = monitors.TemporalAverage()
#Bundle them
what_to_watch = (momo, mama)
#Initialise a Simulator -- Model, Connectivity, Integrator, and Monitors.
sim = simulator.Simulator(model=oscillator, connectivity=white_matter,
                          coupling=white_matter_coupling,
                          integrator=heunint, monitors=what_to_watch)
sim.configure()
LOG.info("Starting simulation...")
#Perform the simulation
raw_data = []
raw_time = []
tavg_data = []
tavg_time = []
for raw, tavg in sim(simulation_length=1000):
    if not raw is None:
        raw_time.append(raw[0])
        raw_data.append(raw[1])
    
    if not tavg is None:
        tavg_time.append(tavg[0])
        tavg_data.append(tavg[1])
LOG.info("Finished simulation.")
print 'It run for %d sec.' % (datetime.datetime.now() - START_TIME).seconds
Explanation: Perform the simulation
End of explanation
#Plot defaults in a few combinations
#Make the lists numpy.arrays for easier use.
RAW = numpy.array(raw_data)
TAVG = numpy.array(tavg_data)
#Plot raw time series
figure(1)
plot(raw_time, RAW[:, 0, :, 0])
title("Raw -- State variable 0")
figure(2)
plot(raw_time, RAW[:, 1, :, 0])
title("Raw -- State variable 1")
#Plot temporally averaged time series
figure(3)
plot(tavg_time, TAVG[:, 0, :, 0])
title("Temporal average")
#Show them
show()
Explanation: ####Plot pretty pictures of what we just did
End of explanation
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