def fit_test():
print "Testing GLS"
model = LMMBasicAnimal(ylist = ['length'],plist=['size'])
dataFile = "data/test.data"
treeFile = "data/test.newick"
# loadFromFile(self,dataFile,treeFile,taxa_column='taxa',sep='TAB'):
model.loadFromFile(dataFile,treeFile,sep='SPACE')
model.fitGLS()
# model.fitLMMBasic()
print "--------------------"
def simulate_one_tree():
#treeFile = 'data/test.newick'
treeFile = "data/bz.trees.newick"
tree = PhyloTree(treeFile, schema='newick')
tree.normalize()
G = tree.getV()
Gs = [G]
#(y,X,beta,Z,b,G,cholL,sigma2_b,R,sigma2_e) = lmmsample(tree)
beta = [15,2.5]
(y,X,Z,Ls,u,e) =lmm_sample(beta,Gs=Gs,sigma2=[5,1])
(n,xx) = np.shape(y)
# saveModelData('data/bodybraindata.txt','Body',['Brain'],y,X,tree)
model = LMMBasicAnimal(ylist = ['Body'],plist=['Brain'])
#return
#model = LMMBasicAnimal(ylist = ['length'],plist=['size'])
R = np.asmatrix(np.eye(n))
model.loadFromMatrices(y,X,Z,G,R)
model.fitLMMBasic()
#model.fitGLSLambda()
#return 0
invG = np.linalg.inv(model.G)
#cholG = np.asmatrix(scipy.linalg.cholesky(G,lower=True))
print ("*** initializing LmmMcmc object")
# gibbs = GibbsAnimal(y,X,Z,invG,cholG)
gibbs = MC2Lmm(y,X,Z,Ginvs=[invG])
gibbs.set_init_params(init_beta=[10,1.5],init_sigma2_u=0.5,init_sigma2_e=0.5)
# Time this
t1 = time.time()
ret = gibbs.simulate(num_samples=100,burnin=2000,thin=20)
t2 = time.time()
print 'time='+str(t2-t1)
print "**** Finished sampling ****"
print "NUM SAMPLES = " + str(gibbs.num_samples)
if (ret != 0):
print "Horror!"
if (gibbs.num_samples < 1):
return -1
gibbs.plot()
else:
print 'Finished successfully'
gibbs.plot()
#gibbs.save_to_file('samples2.log',filetype='xls')
#print samples
#print np.shape(samples)
#(num_params,num_samples) = np.shape(samples)
return 0
def fit_mammals():
model = LMMBasicAnimal(ylist = ['Body'],plist=['Brain'])
dataFile = "data/bzdata.txt"
treeFile = "data/bz.trees.newick"
# loadFromFile(self,dataFile,treeFile,taxa_column='taxa',sep='TAB'):
model.loadFromFile(dataFile,treeFile,taxa_column='Name',sep='SPACE')
model.fitGLS()
# model.fitLMMBasic()
print "--------------------"
model.fitGLSLambda()
def fit_simulate2():
treeFile = 'data/test.newick'
dataFile = "data/test.data"
#treeFile = "data/bz.trees.newick"
tree = PhyloTree(treeFile, schema='newick')
tree.normalize()
#(y,X,beta,Z,b,G,cholL,sigma2_b,R,sigma2_e) = lmmsample(tree)
#saveModelData2('data/bodybraindata.txt','Body',['Brain'],y,X,tree)
#model = LMMBasicAnimal(ylist = ['Body'],plist=['Brain'])
#return
model = LMMBasicAnimal(ylist = ['length'],plist=['size'])
model.loadFromFile(dataFile,treeFile,sep='SPACE')
invG = np.linalg.inv(model.G)
cholG = np.asmatrix(scipy.linalg.cholesky(model.G,lower=True))
print ("*** initializing LmmMcmc object")
gibbs = GibbsAnimal(model.y,model.X,model.Z,invG,cholG)
#gibbs = MC2Lmm(y,X,Z,Ginvs=[invG])
#gibbs.set_init_params(init_beta=[10,1.5],init_sigma2_u=0.5,init_sigma2_e=0.5)
# Time this
t1 = time.time()
ret = gibbs.simulate(num_samples=100,burnin=2000,thin=20)
t2 = time.time()
print 'time='+str(t2-t1)
print "**** Finished sampling ****"
print "NUM SAMPLES = " + str(gibbs.num_samples)
if (ret != 0):
print "Horror!"
if (gibbs.num_samples < 1):
return -1
gibbs.plot()
else:
print 'Finished successfully'
gibbs.plot()
#gibbs.save_to_file('samples2.log',filetype='xls')
#print samples
#print np.shape(samples)
#(num_params,num_samples) = np.shape(samples)
return 0
