density,
omega,
tMatrix,
BoltzmannCorrection=BoltzmannCorrection)
shuffleIndices = [0, 3, 4, 5, 6, 7, 10]
tlskde = BS.tlsKDE()
tlskde.fit(tlsdata, shuffleIndices, bandwidth=0.186379686016)
losses = []
newtlsdata = np.copy(tlsdata)
for bi in xrange(0, bSamples):
print "Bootstrapping: working on the {:d} step of {:d}.".format(
bi + 1, bSamples)
newtlsdata[:, shuffleIndices] = tlskde.sample(nPts)
losses.append(
LF.calculateLossFunction(newtlsdata,
density,
omega,
tMatrix,
BoltzmannCorrection=BoltzmannCorrection))
if saveDistros:
BS.SaveDistros(tMatrix, original, losses)
lLoss, uLoss = BS.CalcConfidenceInterval(original, losses)
if plotLoss:
LF.plotLoss(tMatrix, original, lLoss, uLoss)
if saveLoss:
LF.saveLoss(tMatrix, original, lLoss, uLoss, saveLoss)
