Python fetP2P примеры использования

Пример #1

Файл: tutorial_features.py Проект: mxhit-j/SpikeSort

#!/usr/bin/env python
# -*- coding: utf-8 -*-

from spike_sort.io.filters import PyTablesFilter
from spike_sort import extract
from spike_sort import features
from spike_sort import cluster
from spike_sort.ui import plotting
import os

dataset = '/SubjectA/session01/el1'
datapath = '../../../data/tutorial.h5'

io_filter = PyTablesFilter(datapath)
raw = io_filter.read_sp(dataset)
spt = extract.detect_spikes(raw,  contact=3, thresh='auto')

sp_win = [-0.2, 0.8]
spt = extract.align_spikes(raw, spt, sp_win, type="max", resample=10)
sp_waves = extract.extract_spikes(raw, spt, sp_win)
sp_feats = features.combine(
     (
      features.fetP2P(sp_waves),
      features.fetPCA(sp_waves)
     )
)
   
plotting.plot_features(sp_feats)
plotting.show()

Пример #2

Файл: tutorial_clusters.py Проект: nickponvert/SpikeSort

#!/usr/bin/env python
#coding=utf-8

from spike_sort.io.filters import PyTablesFilter
from spike_sort import extract
from spike_sort import features
from spike_sort import cluster
from spike_sort.ui import plotting
import os

dataset = '/SubjectA/session01/el1'
datapath = '../../../data/tutorial.h5'

io_filter = PyTablesFilter(datapath)
raw = io_filter.read_sp(dataset)
spt = extract.detect_spikes(raw, contact=3, thresh='auto')

sp_win = [-0.2, 0.8]
spt = extract.align_spikes(raw, spt, sp_win, type="max", resample=10)
sp_waves = extract.extract_spikes(raw, spt, sp_win)
sp_feats = features.combine(
    (features.fetP2P(sp_waves), features.fetPCs(sp_waves)))

clust_idx = cluster.cluster("gmm", sp_feats, 4)
plotting.plot_features(sp_feats, clust_idx)
plotting.show()
io_filter.close()

Пример #3

Файл: tutorial_features.py Проект: nickponvert/SpikeSort

#!/usr/bin/env python
# coding=utf-8

from spike_sort.io.filters import PyTablesFilter
from spike_sort import extract
from spike_sort import features
from spike_sort import cluster
from spike_sort.ui import plotting
import os

dataset = "/SubjectA/session01/el1"
datapath = "../../../data/tutorial.h5"

io_filter = PyTablesFilter(datapath)
raw = io_filter.read_sp(dataset)
spt = extract.detect_spikes(raw, contact=3, thresh="auto")

sp_win = [-0.2, 0.8]
spt = extract.align_spikes(raw, spt, sp_win, type="max", resample=10)
sp_waves = extract.extract_spikes(raw, spt, sp_win)
sp_feats = features.combine((features.fetP2P(sp_waves), features.fetPCs(sp_waves)))

plotting.plot_features(sp_feats)
plotting.show()