def findPointOfHalfM(modelData, fract=0.5):
M = modelData['m'][-1]
Mfract = M * fract
#i = lookupIndexBisect(M / 2.0, modelData['m'])
rho = linInterp(Mfract, modelData['m'], modelData['rho'])
r = linInterp(Mfract, modelData['m'], modelData['r'])
p = linInterp(Mfract, modelData['m'], modelData['p'])
return {'rho': rho, 'r': r, 'p': p}
def predict_conditionalParams(self, idx, t):
# interpolate points off grid
T = t.size()[0]
b_linp = torch.zeros(T, 1, self.nLatent).type(float_type)
A_linp = torch.zeros(T, self.nLatent, self.nLatent).type(float_type)
for i in range(T):
b_linp[i, :, :] = linInterp(t[i], self.b_grid[idx],
self.t_grid[idx])
A_linp[i, :, :] = linInterp(t[i], self.A_grid[idx],
self.t_grid[idx])
return A_linp, b_linp
def predict_marginals(self, idx, t):
# function to evaluate GP at new points for trial idx
# solve for m, S on grid
m, S = self.solveForward_GaussMarkov_grid(self.initialMean[idx],
self.initialCov[idx], idx)
# interpolate points off grid
T = t.size()[0]
m_linp = torch.zeros(T, 1, self.nLatent).type(float_type)
S_linp = torch.zeros(T, self.nLatent, self.nLatent).type(float_type)
for i in range(T):
m_linp[i, :, :] = linInterp(t[i], m, self.t_grid[idx])
S_linp[i, :, :] = linInterp(t[i], S, self.t_grid[idx])
return m_linp, S_linp
def rhobFromEdCached(self, ed):
"""
Does linear interpolation in logspace of self.cachedRhobVsEd
to invert rhob from given ed
"""
answer = linInterp(numpy.log10(ed),
self.cachedRhobVsEd[0],
self.cachedRhobVsEd[1])
return numpy.power(10.0, answer)
def quantityOfSolveVar(x):
#Here we construct the point to interpolate at, but we
# must do it carefully since we don't know apriori what
# solveVar is
point = []
#todo factor this for out of quantityOfSolveVar
for indVar in self.indVars:
if indVar not in pointDict:
#print "NOT", indVar
value = x
else:
value = pointDict[indVar]
if indVar == 'logtemp':
value = pointAsFunctionOfSolveVar(x)
#print indVar, value
point.append(value)
point = tuple(point)
if setBetaEqInSolve:
# tempPointDict = {self.indVars[i]: point[i]
# for i in range(len(self.indVars)) if not self.indVars[i] == 'ye'}
for i in range(len(self.indVars)):
print self.indVars[i]
tempPointDict = []
print "Should not have gotten to this point; debug me!"
sys.exit()
yeForSolve = linInterp(tempPointDict['logrho'],
cachedBetaEqYeVsRhos[0],
cachedBetaEqYeVsRhos[1])
tempPointDict.update({'ye': yeForSolve})
point = self.pointFromDict(tempPointDict)
del tempPointDict
answer = function(x, multidimInterp(point, indVarsTable,
self.h5file[quantity][...],
linInterp, 2)
) - target
return answer
