#!/usr/bin/env python
# coding: utf-8

# In[1]:


get_ipython().run_line_magic('matplotlib', 'widget')
import os
import numpy
import matplotlib.pyplot as plt
from tvb.simulator.lab import *


# # Exploring longer time series
# 
# 
# The scripting interface has two interactive tools for looking at the 
# TimeSeries generated in simulations. This tutorial shows an example of
# their use, using a demo dataset for region time-series.
# 
# These are mainly of use for longer simulations, of at least a few seconds.
# 
# ## Example data
# 
# As a simple set of example data, we will use a linear stochastic model with the default connectivity:

# In[2]:


connectivity=connectivity.Connectivity.from_file()
connectivity.speed=numpy.array([1.0])

sim = simulator.Simulator(
    connectivity=connectivity,
    coupling=coupling.Linear(a=numpy.array([2e-4])),
    integrator=integrators.EulerStochastic(dt=10.0),
    model=models.Linear(gamma=numpy.array([-1e-2])),
    monitors=(monitors.Raw(),),
    simulation_length=60e3
).configure()

(time, data), = sim.run()

plt.figure()
plt.plot(time/1e3, data[:, 0, :, 0], 'k', alpha=0.1);
plt.xlabel('Time (s)')


# 
# ## Create a TimeSeriesRegion Datatype
# 
# 
# Because we just stored our simulation as a simple array, we need to turn it into one of 
# TVB's TimeSeries datatypes, which is what the two plotting tools operate on, in this case 
# we'll use TimeSeriesRegion.

# In[3]:


tsr = time_series.TimeSeriesRegion(
    data=data,
    connectivity=sim.connectivity,
    sample_period=sim.monitors[0].period / 1e3,
    sample_period_unit='s')
tsr.configure()
tsr


# Create And Launch A TimeSeriesInteractive
# ------------------------------------------
# 
# Our typical approach throughout these tutorials has been to to simply plot our time-series 
# using PyLab's plot() function. This is fine as a quick way to look at the small amounts of 
# data we'd been producing, but is insufficient for longer, more meaningful, time-series, 
# such as we get when trying to runs simulations aimed at generating time-series comparable 
# to experimental data. 
# 
# TimeSeriesInteractive is a tool for looking at these longer time-series. It's still 
# relatively simple, but it adds a number of useful features. The time-series are plotted
# in the main central panel with a constant vertical offset, the label for each channel or
# region displayed down the left hand side. Along the bottom are three basic controls:
# on the left there is a slider that allows the length of the window to be changed (in 
# physical units); in the middle a set of buttons exist to step forward and backward 
# through the time-series at different speeds (at the top of the window there is an 
# indicator showing where you are in the time-series); and on the right the vertical 
# spacing, or offset between time series can be set, this has the effect of scaling the 
# time-series' amplitudes.

# In[4]:


#Create and launch the interactive visualiser
import tvb.simulator.plot.timeseries_interactive as ts_int
tsi = ts_int.TimeSeriesInteractive(time_series=tsr)
tsi.configure()
tsi.show()