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