from __future__ import division import sys import svm import windowfile import pickle import numpy as np import matplotlib.pyplot as plt import scipy.signal as sg print('load model') model = svm.libsvm.svm_load_model('/ssd/15o04000_15o04001_h.svmmodel') print('load A') A = windowfile.readwins(open('/ssd/15o03000_h.features')) print('load sig') sig = windowfile.readwinsEx(open('/ssd/15o03000_h.spikes')) print('load randomForest') clf = pickle.load( open("RandomForestOverlapModel.pickle", 'rb')) state = 'single' probs = (svm.c_double*2)(0,0) pA = 1. pB = 1. maxamp = 0. sigs_now = [] #H = np.zeros(256) print('-') counter = 0 tam = A.shape[0] for i in xrange(tam):
import matplotlib.pyplot as plt import numpy as np import scipy.signal as sg import windowfile import sys A = windowfile.readwinsEx(open(sys.argv[1])) H = np.zeros(256) vec_raw = np.zeros(1000000) j = 0 i = 0 while (True): try: i += 1 off, ch, sig_now = A.next() H += np.abs(sg.hilbert(sig_now)) if i % 11 == 0: idx, = np.where(H > 0.2 * H.max()) t = idx.size vec_raw[j] = t j += 1 H.fill(0.) if j % 1000 == 0: sys.stdout.write('\r%d' % j) sys.stdout.flush() except:
from __future__ import division import sys import svm import windowfile import pickle import numpy as np import matplotlib.pyplot as plt import scipy.signal as sg print('load model') model = svm.libsvm.svm_load_model('/ssd/15o04000_15o04001_h.svmmodel') print('load A') A = windowfile.readwins(open('/ssd/15o03000_h.features')) print('load sig') sig = windowfile.readwinsEx(open('/ssd/15o03000_h.spikes')) print('load randomForest') clf = pickle.load(open("RandomForestOverlapModel.pickle", 'rb')) state = 'single' probs = (svm.c_double * 2)(0, 0) pA = 1. pB = 1. maxamp = 0. sigs_now = [] #H = np.zeros(256) print('-') counter = 0 tam = A.shape[0] for i in xrange(tam): if i % 10000 == 0:
import matplotlib.pyplot as plt import numpy as np import scipy.signal as sg import windowfile import sys A = windowfile.readwinsEx(open(sys.argv[1])) H = np.zeros(256) vec_raw = np.zeros(1000000) j = 0 i = 0 while True: try: i += 1 off, ch, sig_now = A.next() H += np.abs(sg.hilbert(sig_now)) if i % 11 == 0: idx, = np.where(H > 0.2 * H.max()) t = idx.size vec_raw[j] = t j += 1 H.fill(0.0) if j % 1000 == 0: sys.stdout.write("\r%d" % j) sys.stdout.flush() except: