def kernel_locality_improved_string_modular(fm_train_dna=traindat,fm_test_dna=testdat,length=5,inner_degree=5,outer_degree=7): from shogun.Features import StringCharFeatures, DNA from shogun.Kernel import LocalityImprovedStringKernel feats_train=StringCharFeatures(fm_train_dna, DNA) feats_test=StringCharFeatures(fm_test_dna, DNA) kernel=LocalityImprovedStringKernel( feats_train, feats_train, length, inner_degree, outer_degree) km_train=kernel.get_kernel_matrix() kernel.init(feats_train, feats_test) km_test=kernel.get_kernel_matrix() return km_train,km_test,kernel
def create_kernel(kname, kparam, feats_train): """Call the corresponding constructor for the kernel""" if kname == 'gauss': kernel = GaussianKernel(feats_train, feats_train, kparam['width']) elif kname == 'linear': kernel = LinearKernel(feats_train, feats_train) kernel.set_normalizer(AvgDiagKernelNormalizer(kparam['scale'])) elif kname == 'poly': kernel = PolyKernel(feats_train, feats_train, kparam['degree'], kparam['inhomogene'], kparam['normal']) elif kname == 'wd': kernel = WeightedDegreePositionStringKernel(feats_train, feats_train, kparam['degree']) kernel.set_normalizer( AvgDiagKernelNormalizer(float(kparam['seqlength']))) kernel.set_shifts(kparam['shift'] * numpy.ones(kparam['seqlength'], dtype=numpy.int32)) #kernel=WeightedDegreeStringKernel(feats_train, feats_train, kparam['degree']) elif kname == 'spec': kernel = CommUlongStringKernel(feats_train, feats_train) elif kname == 'cumspec': kernel = WeightedCommWordStringKernel(feats_train, feats_train) kernel.set_weights(numpy.ones(kparam['degree'])) elif kname == 'spec2': kernel = CombinedKernel() k0 = CommWordStringKernel(feats_train['f0'], feats_train['f0']) k0.io.disable_progress() kernel.append_kernel(k0) k1 = CommWordStringKernel(feats_train['f1'], feats_train['f1']) k1.io.disable_progress() kernel.append_kernel(k1) elif kname == 'cumspec2': kernel = CombinedKernel() k0 = WeightedCommWordStringKernel(feats_train['f0'], feats_train['f0']) k0.set_weights(numpy.ones(kparam['degree'])) k0.io.disable_progress() kernel.append_kernel(k0) k1 = WeightedCommWordStringKernel(feats_train['f1'], feats_train['f1']) k1.set_weights(numpy.ones(kparam['degree'])) k1.io.disable_progress() kernel.append_kernel(k1) elif kname == 'localalign': kernel = LocalAlignmentStringKernel(feats_train, feats_train) elif kname == 'localimprove': kernel = LocalityImprovedStringKernel(feats_train, feats_train, kparam['length'],\ kparam['indeg'], kparam['outdeg']) else: print 'Unknown kernel %s' % kname kernel.set_cache_size(32) return kernel