from neuroanalysis.fitting import Psp
from neuroanalysis.ui.fitting import FitExplorer
pg.mkQApp()
pg.dbg()
# Load PSP data from the test_data repository
if len(sys.argv) == 1:
data_file = 'test_data/test_psp_fit/1485904693.10_8_2NOTstacked.json'
else:
data_file = sys.argv[1]
data = json.load(open(data_file))
y = np.array(data['input']['data'])
x = np.arange(len(y)) * data['input']['dt']
psp = Psp()
params = OrderedDict([
('xoffset', (10e-3, 10e-3, 15e-3)),
('yoffset', 0),
('amp', 0.1e-3),
('rise_time', (2e-3, 500e-6, 10e-3)),
('decay_tau', (4e-3, 1e-3, 50e-3)),
('rise_power', (2.0, 'fixed')),
])
fit = psp.fit(y, x=x, xtol=1e-3, maxfev=100, params=params)
x = FitExplorer(fit=fit)
x.show()
import numpy as np
import pyqtgraph as pg
from collections import OrderedDict
from neuroanalysis.fitting import Psp
from neuroanalysis.ui.fitting import FitExplorer
pg.mkQApp()
data = np.loadtxt('psp.csv', delimiter=',', skiprows=1, usecols=[0, 1])
x = data[:, 0]
y = data[:, 1]
psp = Psp()
params = OrderedDict([
('xoffset', (2e-3, 5e-4, 5e-3)),
('yoffset', 0),
('amp', 10e-12),
('rise_time', (2e-3, 50e-6, 10e-3)),
('decay_tau', (4e-3, 500e-6, 50e-3)),
('rise_power', (2.0, 'fixed')),
])
fit = psp.fit(y * 1e12, x=x, xtol=1e-3, maxfev=100, **params)
x = FitExplorer(fit=fit)
x.show()