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