import os
from EMD import EMD
refDir = os.path.dirname(os.getcwd())
refNumStr = '101'
refInFileDir = os.path.join(refDir, refNumStr, 'Input.csv')
resOutFileDir = os.path.join(refDir, refNumStr, 'EMDResultsPython.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 = EMD(refInVector, tWindowSize=120.0, samplingFrequency=360, imfsNo=3)
resultVector = alg.process()
for val in resultVector or []:
resultFile.write('%d\n' % val)
refInFile.close()
resultFile.close()
class EMDTest(unittest.TestCase):
def setUp(self):
refDir = os.path.dirname(os.getcwd())
refNumStr = '103'
refInFileDir = os.path.join(refDir, refNumStr, 'Input.csv')
refOutFileDir = os.path.join(refDir, refNumStr, 'EMDOutput.csv')
resOutFileDir = os.path.join(refDir, refNumStr, 'EMDResultsPython.csv')
self.imfOutFileDir = os.path.join(refDir, refNumStr, 'Imf.csv')
envOutFileDir = os.path.join(refDir, refNumStr, 'Envelope.csv')
self.samplingFreq = 360.0
self.imfsNo = 3
self.tWindowSize = 120.0
self.refInFile = open(refInFileDir, 'r')
self.refOutFile = open(refOutFileDir, 'r')
self.resultFile = open(resOutFileDir, 'w')
# self.imfOutFileFile = open(imfOutFileDir, 'w')
self.envOutFileFile = open(envOutFileDir, 'w')
self.refInVector = []
self.refOutVector = []
self.resultVector = []
self.refIntSignalVector = []
self.refMarksVector = []
def tearDown(self):
self.refInFile.close()
self.refOutFile.close()
self.resultFile.close()
# self.imfOutFileFile.close()
self.envOutFileFile.close()
def loadReferenceData(self):
refInVectorStr = self.refInFile.readline().split(',')
del refInVectorStr[-1]
for item in refInVectorStr:
val = float(item)
self.refInVector.append(val)
refOutVectorStr = self.refOutFile.readline().split(',')
del refOutVectorStr[-1]
for item in refOutVectorStr:
val = int(float(item))
self.refOutVector.append(val)
def runAlgorithm(self):
self.alg = EMD(self.refInVector,
tWindowSize=self.tWindowSize,
samplingFrequency=self.samplingFreq,
imfsNo=self.imfsNo)
self.resultVector = self.alg.process()
self.env = self.alg.hilbertAlgorithm.envelope
self.imfs = self.alg.imfs
# self.spline_upper = self.alg.spline_upper
for val in self.resultVector or []:
self.resultFile.write('%d\n' % val)
# for val in self.imf:
# self.imfOutFileFile.write('%f\n' % val)
np.savetxt(self.imfOutFileDir, self.imfs, delimiter=',')
for val in self.env:
self.envOutFileFile.write('%f\n' % val)
def isResultIdentical(self):
result = True
# self.assertTrue(len(self.resultVector) > 0)
print 'Output size: {}'.format(len(self.resultVector))
for ref, res in zip(self.refOutVector, self.resultVector):
# print '{} {}'.format(ref, res)
if ref != res:
print 'reference ({}) and result ({}) are not equal'.format(ref, res)
result = False
return result
def testAlgorithm(self):
self.loadReferenceData()
self.runAlgorithm()
self.assertTrue(self.isResultIdentical(), 'Reference vector and result vector are not identical')
import os
from EMD import EMD
refDir = os.path.dirname(os.getcwd())
refNumStr = '101'
refInFileDir = os.path.join(refDir, refNumStr, 'Input.csv')
resOutFileDir = os.path.join(refDir, refNumStr, 'EMDResultsPython.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 = EMD(refInVector,
tWindowSize=120.0,
samplingFrequency=360,
imfsNo=3)
resultVector = alg.process()
for val in resultVector or []:
resultFile.write('%d\n' % val)
refInFile.close()
resultFile.close()
