model of DCN pyramidal neuron
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# coding: utf-8
# In[1]:
import os
import sys
import pyqtgraph as pg
import numpy as np
# In[7]:
dir_path = os.path.abspath("")
win = pg.GraphicsWindow()
win.setBackground("w")
p1 = win.addPlot(
title="Pauser PSTH",
row=0,
col=0,
labels={"bottom": "T (ms)", "left": "# of spikes"},
)
p2 = win.addPlot(
title="Buildup PSTH",
row=1,
col=0,
labels={"bottom": "T (ms)", "left": "# of spikes"},
)
p3 = win.addPlot(
title="Wide Chopper PSTH",
row=2,
col=0,
labels={"bottom": "T (ms)", "left": "# of spikes"},
)
# In[ ]:
bins = np.arange(0, 80, 0.5)
PB_spike_data = []
with open("Ad081098_065_PauserBuildup_psth.txt", "r+") as df:
for x in df:
x = x.strip("\n").strip()
x = float(x) * 1e-3
if x:
PB_spike_data.append(x)
histogram, binedges = np.histogram(PB_spike_data, bins)
p1.plot(
binedges,
histogram,
stepMode=True,
fillBrush=(0, 0, 0, 255),
brush=pg.mkBrush("k"),
fillLevel=0,
)
B_spike_data = []
with open("Ad041599_062_Buildup_psth.txt", "r+") as df:
for x in df:
x = x.strip("\n").strip()
x = float(x) * 1e-3
if x:
B_spike_data.append(x)
histogram, binedges = np.histogram(B_spike_data, bins)
p2.plot(
binedges,
histogram,
stepMode=True,
fillBrush=(0, 0, 0, 255),
brush=pg.mkBrush("k"),
fillLevel=0,
)
C_spike_data = []
with open("Ad081998_199_WideChopper_psth.txt", "r+") as df:
for x in df:
x = x.strip("\n").strip()
x = float(x) * 1e-3
if x:
C_spike_data.append(x)
histogram, binedges = np.histogram(C_spike_data, bins)
p3.plot(
binedges,
histogram,
stepMode=True,
fillBrush=(0, 0, 0, 255),
brush=pg.mkBrush("k"),
fillLevel=0,
)
# In[ ]:
win.show()
print("finished")
if sys.flags.interactive == 0:
pg.QtGui.QApplication.exec_()