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103 lines
3.0 KiB
103 lines
3.0 KiB
2 years ago
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"""
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Test the embedded auditory nerve model with a set of tone pips.
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(Zilany et al. 2014; requires MATLAB)
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This demonstrates the lowest-level access to the auditory nerve model that is
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available in the cnmodel API. For higher-level tools, see test_sound_stim.py
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(which uses an_model.get_spiketrain) and test_sgc_input.py (which uses
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cells.DummySGC).
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Usage:
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python test_an_model.py
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(no arguments)
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(Adapted from makeANF_CF_RI.m)
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"""
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import time
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import numpy as np
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import pyqtgraph as pg
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from cnmodel import an_model
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from cnmodel.util import sound
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def test_an_model():
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# model fiber parameters
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CF = 1.5e3 # CF in Hz
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cohc = 1.0 # normal ohc function
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cihc = 1.0 # normal ihc function
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species = (
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1
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) # 1 for cat (2 for human with Shera et al. tuning 3 for human with Glasberg & Moore tuning)
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noiseType = 1 # 1 for variable fGn (0 for fixed fGn)
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fiberType = (
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3
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) # spontaneous rate (in spikes/s) of the fiber BEFORE refractory effects "1" = Low "2" = Medium "3" = High
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implnt = (
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0
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) # "0" for approximate or "1" for actual implementation of the power-law functions in the Synapse
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# stimulus parameters
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F0 = CF # stimulus frequency in Hz
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Fs = 100e3 # sampling rate in Hz (must be 100, 200 or 500 kHz)
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T = 150e-3 # stimulus duration in seconds
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pdur = 0.02 # pip duration
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pstart = [0.01, 0.035] # pip start times
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rt = 2.5e-3 # rise/fall time in seconds
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stimdb = 65 # stimulus intensity in dB SPL
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# PSTH parameters
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nrep = 50 # number of stimulus repetitions (e.g., 50)
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psthbinwidth = 0.5e-3 # binwidth in seconds
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stim = sound.TonePip(
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rate=Fs,
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duration=T,
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f0=F0,
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dbspl=stimdb,
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pip_duration=pdur,
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pip_start=pstart,
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ramp_duration=rt,
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)
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t = stim.time
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pin = stim.sound
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db = stim.measure_dbspl(rt, T - rt)
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an_model.seed_rng(34978)
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start = time.time()
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vihc = an_model.model_ihc(
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pin, CF, nrep, 1 / Fs, T + 1e-3, cohc, cihc, species
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) # , _transfer=False)
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print("IHC time:", time.time() - start)
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start = time.time()
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m, v, psth = an_model.model_synapse(
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vihc, CF, nrep, 1 / Fs, fiberType, noiseType, implnt
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)
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print("Syn time:", time.time() - start)
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win = pg.GraphicsWindow()
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p1 = win.addPlot(title="Input Stimulus (%0.1f dBSPL)" % db)
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p1.plot(t, pin)
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p2 = win.addPlot(col=0, row=1, title="IHC voltage")
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p2.setXLink(p1)
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# vihc = vihc.get()[0]
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vihc = vihc[: len(vihc) // nrep]
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t = np.arange(len(vihc)) * 1e-5
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p2.plot(t, vihc)
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p3 = win.addPlot(col=0, row=2, title="ANF PSTH")
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p3.setXLink(p2)
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ds = 100
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size = psth.size // ds
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psth = psth[: size * ds].reshape(size, ds).sum(axis=1)
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t = np.arange(len(psth)) * 1e-5 * ds
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p3.plot(t, psth[:-1], stepMode=True, fillLevel=0, fillBrush="w")
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if sys.flags.interactive == 0:
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pg.QtGui.QApplication.exec_()
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if __name__ == "__main__":
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import sys
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test_an_model()
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