def process(self):
self.imfs = self.findIMFs(self.imfsNo)
self.hilbertAlgorithm = Hilbert(self.ecgSignal, self.tWindowSize,
self.samplingFrequency)
self.imfsSum = np.sum(self.imfs, axis=0)
self.rPeaks = self.hilbertAlgorithm.processImfs(self.imfsSum)
return self.rPeaks
def run_Hilbert(self, param):
logging.debug('building Hilbert-R...')
tree = Hilbert(self.data, param)
start = time.clock()
tree.buildIndex()
tree.adjustConsistency()
end = time.clock()
logging.info('[T] Hilbert building time: %.2f' % (end - start))
return self.query(tree)
import os
from Hilbert import Hilbert
refDir = os.path.dirname(os.getcwd())
refNumStr = '102'
refInFileDir = os.path.join(refDir, refNumStr, 'Input.csv')
resOutFileDir = os.path.join(refDir, refNumStr, 'HilbertResultsPython.csv')
refInFile = open(refInFileDir, 'r')
resultFile = open(resOutFileDir, 'w')
refInVector = []
refInVectorStr = refInFile.readline().split(',')
del refInVectorStr[-1]
for item in refInVectorStr:
val = float(item)
refInVector.append(val)
alg = Hilbert(refInVector,
tWindowSize=120.0,
samplingFrequency=360)
resultVector = alg.process()
for val in resultVector or []:
resultFile.write('%d\n' % val)
refInFile.close()
resultFile.close()
def runAlgorithm(self):
self.alg = Hilbert(self.refInVector,
samplingFrequency=self.samplingFreq)
self.resultVector = self.alg.process()
for val in self.resultVector or []:
self.resultFile.write('%d\n' % val)