%matplotlib inline

from __future__ import division, print_function, absolute_import

import numpy as np
import scipy.signal as dsp
import pandas as pd
import matplotlib.pyplot as plt

import cochlea
import cochlea.stats
import thorns as th
import thorns.waves as wv

fs = 100e3
cf = 1000
tone = wv.ramped_tone(
    fs=fs,
    freq=1000,
    duration=0.1,
    dbspl=50
)

wv.plot_signal(tone, fs)

anf_trains = cochlea.run_zilany2014(
    tone,
    fs,
    anf_num=(200,0,0),
    cf=cf,
    seed=0,
    species='cat'
)

th.plot_raster(anf_trains)

t = np.arange(0, 0.05, 1/fs)
chirp = dsp.chirp(t, 80, t[-1], 8000)
chirp = cochlea.set_dbspl(chirp, 50)

wv.plot_signal(chirp, fs)

anf_trains = cochlea.run_zilany2014(
    chirp,
    fs,
    anf_num=(0,0,50),
    cf=(125, 10e3, 100),
    seed=0,
    species='human'
)

th.plot_raster(th.accumulate(anf_trains))

rates = cochlea.stats.calc_rate_level(
        model=cochlea.run_zilany2014,
        cf=1000,
        model_pars={'fs': 100e3, 'species': 'human'}
)

rates.plot()