Esempio n. 1
0
import nonlinearity as nlt
import genlinmod as glm

from omb import OMB
from stimulus import Stimulus

#exp, stim_nr  = '20180710', 8
#exp, stim_nr  = 'Kuehn', 13

fff_stimnr = asc.stimulisorter(exp)['fff'][0]

st = OMB(exp, stim_nr)
fff = Stimulus(exp, fff_stimnr)

# Get rid of list of numpy arrays
fff_stas = np.array(fff.read_datafile()['stas'])

glmlabel = 'GLM_contrast'

savepath = os.path.join(st.stim_dir, glmlabel)
os.makedirs(savepath, exist_ok=True)

texture_data = st.read_texture_analysis()

all_spikes = st.allspikes()

start = dt.datetime.now()

kall = np.zeros((st.nclusters, st.filter_length))
muall = np.zeros(st.nclusters)
Esempio n. 2
0
    phasic_index = np.abs(posarea + negarea) / (np.abs(negarea) + np.abs(posarea)) # Ravi et al., 2019 J.Neurosci
    biphasic_index = 1 - phasic_index
    return biphasic_index

def biphasic_index3(sta):
    return np.abs(sta.max() + sta.min()) / (np.abs(sta.max()) + np.abs(sta.min()))

def biphasic_index3_stas(stas):
    maxs = stas.max(axis=1)
    mins = stas.min(axis=1)
    return 1 - (np.abs(maxs + mins) / (np.abs(maxs) + np.abs(mins)))

ff = Stimulus('20180710', 1)
ff = Stimulus('Kuehn', 2)

data = ff.read_datafile()
stas = np.array(data['stas'])

bps = np.empty(ff.nclusters)
bps2 = np.empty(ff.nclusters)
bps3 = biphasic_index3_stas(stas)

#%%
for i in range(ff.nclusters):

    pospeaks = find_peaks(stas[i, :], prominence=.2)[0]
    negpeaks = find_peaks(-stas[i, :], prominence=.2)[0]
    peaks = np.sort(np.hstack((pospeaks, negpeaks)))
    plt.plot(stas[i, :])
    plt.plot(peaks, stas[i, peaks], 'ro')
    if peaks.shape[0] == 2: