def test_ConvolveGaussian(self): fileNames = libHrlAnalysis.vector_string() fileNames.append('../../test/data/CA1/spikes_0001.bin') fileNames.append('../../test/data/CA1/spikes_0002.bin') analysis = libHrlAnalysis.HrlNeuralAnalysisHRLSim( 0, 4000, 26200, 28199, fileNames)
def test_ConvolveGaussian(self): fileNames = libHrlAnalysis.vector_string() fileNames.append('../../test/data/CA1/spikes_0001.bin') fileNames.append('../../test/data/CA1/spikes_0002.bin') analysis = libHrlAnalysis.HrlNeuralAnalysisHRLSim(0,4000,26200,28199, fileNames)
def __init__(self, startTime, endTime, spkFile, posFile): libHrlAnalysis.HrlNeuralAnalysis.__init__(self,0,0,0,0,libHrlAnalysis.vector_string()) self.paramsIn().startTime = startTime self.paramsIn().endTime = endTime self.spkFile = spkFile self.posFile = posFile self.x_pos = [] self.y_pos = [] self.t_pos = []
def __init__(self, startTime, endTime, spkFile, posFile): libHrlAnalysis.HrlNeuralAnalysis.__init__( self, 0, 0, 0, 0, libHrlAnalysis.vector_string()) self.paramsIn().startTime = startTime self.paramsIn().endTime = endTime self.spkFile = spkFile self.posFile = posFile self.x_pos = [] self.y_pos = [] self.t_pos = []
def test_getCOV(self): fileNames = libHrlAnalysis.vector_string() fileNames.append('../../test/data/CA1/spikes_0001.bin') fileNames.append('../../test/data/CA1/spikes_0002.bin') analysis = libHrlAnalysis.HrlNeuralAnalysisHRLSim( 0, 4000, 26200, 28199, fileNames) covInfo = analysis.getCOV() data = libHrlAnalysisData.AnalysisData() self.assertTrue(data.fillCOV('../../test/data/CA1/CA1_cov.dat')) self.assertTrue(data.compareCOV(covInfo.cov))
def test_getCOV(self): fileNames = libHrlAnalysis.vector_string() fileNames.append('../../test/data/CA1/spikes_0001.bin') fileNames.append('../../test/data/CA1/spikes_0002.bin') analysis = libHrlAnalysis.HrlNeuralAnalysisHRLSim(0,4000,26200,28199, fileNames) covInfo = analysis.getCOV() data = libHrlAnalysisData.AnalysisData() self.assertTrue(data.fillCOV('../../test/data/CA1/CA1_cov.dat')) self.assertTrue(data.compareCOV(covInfo.cov))
def test_serialize(self): fileNames = libHrlAnalysis.vector_string() fileNames.append('../../test/data/CA1/spikes_0001.bin') fileNames.append('../../test/data/CA1/spikes_0002.bin') analysisIn = libHrlAnalysis.HrlNeuralAnalysisHRLSim( 0, 4000, 26200, 28199, fileNames) analysisIn.buildDataStructures() analysisIn.save("./ser.bin") analysisOut = libHrlAnalysis.HrlNeuralAnalysisHRLSim( 0, 0, 0, 0, libHrlAnalysis.vector_string()) analysisOut.load("./ser.bin") spikes = analysisOut.getSpikeTimes() data = libHrlAnalysisData.AnalysisData() data.fillRasterData('../../test/data/CA1/CA1_raster.dat') self.assertTrue(data.compareRasterDataDim(spikes.time, 1)) self.assertTrue(data.compareRasterDataDim(spikes.spikes, 2))
def test_serialize(self): fileNames = libHrlAnalysis.vector_string() fileNames.append('../../test/data/CA1/spikes_0001.bin') fileNames.append('../../test/data/CA1/spikes_0002.bin') analysisIn = libHrlAnalysis.HrlNeuralAnalysisHRLSim(0,4000,26200,28199, fileNames) analysisIn.buildDataStructures() analysisIn.save("./ser.bin") analysisOut = libHrlAnalysis.HrlNeuralAnalysisHRLSim( 0,0,0,0, libHrlAnalysis.vector_string()) analysisOut.load("./ser.bin") spikes = analysisOut.getSpikeTimes() data = libHrlAnalysisData.AnalysisData() data.fillRasterData('../../test/data/CA1/CA1_raster.dat') self.assertTrue(data.compareRasterDataDim(spikes.time,1)) self.assertTrue(data.compareRasterDataDim(spikes.spikes,2))
def test_getRasterResult(self): fileNames = libHrlAnalysis.vector_string() fileNames.append('../../test/data/CA1/spikes_0001.bin') fileNames.append('../../test/data/CA1/spikes_0002.bin') analysis = libHrlAnalysis.HrlNeuralAnalysisHRLSim( 0, 4000, 26200, 28199, fileNames) spikes = analysis.getSpikeTimes() data = libHrlAnalysisData.AnalysisData() data.fillRasterData('../../test/data/CA1/CA1_raster.dat') self.assertTrue(data.compareRasterDataDim(spikes.time, 1)) self.assertTrue(data.compareRasterDataDim(spikes.spikes, 2))
def test_GetGaussWindowRates(self): fileNames = libHrlAnalysis.vector_string() fileNames.append('../../test/data/CA1/spikes_0001.bin') fileNames.append('../../test/data/CA1/spikes_0002.bin') analysis = libHrlAnalysis.HrlNeuralAnalysisHRLSim(0,4000,26200,28199, fileNames) rates = analysis.getGaussWindowRate(10,10) data = libHrlAnalysisData.AnalysisData() self.assertTrue(data.fillWindowRates( '../../test/data/CA1/CA1_gauss_window_rates.dat')) self.assertTrue(data.compareWindowRates_double(rates.rates))
def test_getRasterResult(self): fileNames = libHrlAnalysis.vector_string() fileNames.append('../../test/data/CA1/spikes_0001.bin') fileNames.append('../../test/data/CA1/spikes_0002.bin') analysis = libHrlAnalysis.HrlNeuralAnalysisHRLSim(0,4000,26200,28199, fileNames) spikes = analysis.getSpikeTimes() data = libHrlAnalysisData.AnalysisData() data.fillRasterData('../../test/data/CA1/CA1_raster.dat') self.assertTrue(data.compareRasterDataDim(spikes.time,1)) self.assertTrue(data.compareRasterDataDim(spikes.spikes,2))
def test_GetWindowRates(self): fileNames = libHrlAnalysis.vector_string() fileNames.append('../../test/data/CA1/spikes_0001.bin') fileNames.append('../../test/data/CA1/spikes_0002.bin') analysis = libHrlAnalysis.HrlNeuralAnalysisHRLSim( 0, 4000, 26200, 28199, fileNames) rates = analysis.getWindowRate(10, 10) data = libHrlAnalysisData.AnalysisData() self.assertTrue( data.fillWindowRates('../../test/data/CA1/CA1_window_rates.dat')) self.assertTrue(data.compareWindowRates_double(rates.rates))
def test_GetRateBins(self): fileNames = libHrlAnalysis.vector_string() fileNames.append('../../test/data/CA1/spikes_0001.bin') fileNames.append('../../test/data/CA1/spikes_0002.bin') analysis = libHrlAnalysis.HrlNeuralAnalysisHRLSim(0,4000,26200,28199, fileNames) rateBinInfo = analysis.getRateBins(100) data = libHrlAnalysisData.AnalysisData() self.assertTrue(data.fillSpikeBins( '../../test/data/CA1/CA1_spike_bins.dat')) self.assertTrue(data.compareSpikeBinsAt(rateBinInfo.counts,0)) self.assertTrue(data.compareSpikeBinsAt(rateBinInfo.counts,1))
def test_GetRateBins(self): fileNames = libHrlAnalysis.vector_string() fileNames.append('../../test/data/CA1/spikes_0001.bin') fileNames.append('../../test/data/CA1/spikes_0002.bin') analysis = libHrlAnalysis.HrlNeuralAnalysisHRLSim( 0, 4000, 26200, 28199, fileNames) rateBinInfo = analysis.getRateBins(100) data = libHrlAnalysisData.AnalysisData() self.assertTrue( data.fillSpikeBins('../../test/data/CA1/CA1_spike_bins.dat')) self.assertTrue(data.compareSpikeBinsAt(rateBinInfo.counts, 0)) self.assertTrue(data.compareSpikeBinsAt(rateBinInfo.counts, 1))
def test_Voltages(self): fileNames = libHrlAnalysis.vector_string() for i in range(20): fileNames.append("../../test/data/VOLT/voltages_%04d.dat"%(i+1)) data = libHrlAnalysisData.AnalysisData() self.assertTrue(data.fillVoltageData( "../../test/data/VOLT/VOLT_TEST.dat")) analysis = libHrlAnalysis.HrlNeuralAnalysisVoltage( 0, 2000, 0, 61, fileNames, 62,False,-49.0) voltageInfo = analysis.voltages() #print "\n\n",len(voltageInfo.voltage),"\n\n" self.assertTrue(data.compareVoltageData(voltageInfo.voltage, 0.0001))
def test_Voltages(self): fileNames = libHrlAnalysis.vector_string() for i in range(20): fileNames.append("../../test/data/VOLT/voltages_%04d.dat" % (i + 1)) data = libHrlAnalysisData.AnalysisData() self.assertTrue( data.fillVoltageData("../../test/data/VOLT/VOLT_TEST.dat")) analysis = libHrlAnalysis.HrlNeuralAnalysisVoltage( 0, 2000, 0, 61, fileNames, 62, False, -49.0) voltageInfo = analysis.voltages() #print "\n\n",len(voltageInfo.voltage),"\n\n" self.assertTrue(data.compareVoltageData(voltageInfo.voltage, 0.0001))
def test_GetSPIKESynchrony(self): fileNames = libHrlAnalysis.vector_string() tester = HrlNeuralAnalysisPythonSynchrony(0,1300,0,1,fileNames) S = tester.getPairSynchrony(0,1) import numpy as np if( os.path.exists("../../test/data/synchrony/synchrony_data.dat") ): values = np.loadtxt("../../test/data/synchrony/synchrony_data.dat") self.assertTrue(len(S.S) == len(values)) for i in range(len(S.S)): self.assertTrue( abs(S.S[i]-values[i]) < 0.00000001) self.assertTrue( abs( tester.calcSPIKEDistance(S)-0.274376) < 0.000001) self.assertTrue( abs( tester.calcSPIKEDistanceAvg(S)-0.211059) < 0.000001) else: self.fail("Could not open file: ../../test/data/synchrony/synchrony_data.dat")
def test_GetSPIKESynchrony(self): fileNames = libHrlAnalysis.vector_string() tester = HrlNeuralAnalysisPythonSynchrony(0, 1300, 0, 1, fileNames) S = tester.getPairSynchrony(0, 1) import numpy as np if (os.path.exists("../../test/data/synchrony/synchrony_data.dat")): values = np.loadtxt("../../test/data/synchrony/synchrony_data.dat") self.assertTrue(len(S.S) == len(values)) for i in range(len(S.S)): self.assertTrue(abs(S.S[i] - values[i]) < 0.00000001) self.assertTrue( abs(tester.calcSPIKEDistance(S) - 0.274376) < 0.000001) self.assertTrue( abs(tester.calcSPIKEDistanceAvg(S) - 0.211059) < 0.000001) else: self.fail( "Could not open file: ../../test/data/synchrony/synchrony_data.dat" )
def __init__(self, neoObj): libHrlAnalysis.HrlNeuralAnalysis.__init__( self, 0, 0, 0, 0, libHrlAnalysis.vector_string()) self.neoObj = neoObj
def __init__(self,neoObj): libHrlAnalysis.HrlNeuralAnalysis.__init__( self,0,0,0,0,libHrlAnalysis.vector_string()) self.neoObj = neoObj