Revision 0635a16e55a5604d5c3831271775e3031861f096 authored by alexggmatthews on 25 August 2016, 11:49 UTC, committed by alexggmatthews on 25 August 2016, 11:49 UTC
1 parent 1d8073e
simple_regression.py
``````import GPflow
import tensorflow as tf
import os
import numpy as np

def getData():
rng = np.random.RandomState( 1 )
N = 30
X = rng.rand(N,1)
Y = np.sin(12*X) + 0.66*np.cos(25*X) + rng.randn(N,1)*0.1 + 3
return X,Y

def getRegressionModel(X,Y):
#build the GPR object
k = GPflow.kernels.Matern52(1)
meanf = GPflow.mean_functions.Linear(1,0)
m = GPflow.gpr.GPR(X, Y, k, meanf)
m.likelihood.variance = 0.01
print "Here are the parameters before optimization"
m
return m

def optimizeModel(m):
m.optimize()
print "Here are the parameters after optimization"
m

def setModelPriors( m ):
#we'll choose rather arbitrary priors.
m.kern.lengthscales.prior = GPflow.priors.Gamma(1., 1.)
m.kern.variance.prior = GPflow.priors.Gamma(1., 1.)
m.likelihood.variance.prior = GPflow.priors.Gamma(1., 1.)
m.mean_function.A.prior = GPflow.priors.Gaussian(0., 10.)
m.mean_function.b.prior = GPflow.priors.Gaussian(0., 10.)
print "model with priors ", m

def getSamples( m ):
samples = m.sample(100, epsilon = 0.1)
return samples

def runExperiments(plotting=True,outputGraphs=False):
X,Y = getData()
m = getRegressionModel(X,Y)
optimizeModel(m)
setModelPriors( m )
samples = getSamples( m )

if __name__ == '__main__':
runExperiments()
#cProfile.run( 'runExperiments( plotting=False )' )
``````

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