def serialization_complex_example (num=5, dist=1, dim=10, C=2.0, width=10): import os from numpy import concatenate, zeros, ones from numpy.random import randn, seed from modshogun import RealFeatures, MulticlassLabels from modshogun import GMNPSVM from modshogun import GaussianKernel try: from modshogun import SerializableHdf5File,SerializableAsciiFile, \ SerializableJsonFile,SerializableXmlFile,MSG_DEBUG except ImportError: return from modshogun import NormOne, LogPlusOne seed(17) data=concatenate((randn(dim, num), randn(dim, num) + dist, randn(dim, num) + 2*dist, randn(dim, num) + 3*dist), axis=1) lab=concatenate((zeros(num), ones(num), 2*ones(num), 3*ones(num))) feats=RealFeatures(data) #feats.io.set_loglevel(MSG_DEBUG) #feats.io.enable_file_and_line() kernel=GaussianKernel(feats, feats, width) labels=MulticlassLabels(lab) svm = GMNPSVM(C, kernel, labels) feats.add_preprocessor(NormOne()) feats.add_preprocessor(LogPlusOne()) feats.set_preprocessed(1) svm.train(feats) bias_ref = svm.get_svm(0).get_bias() #svm.print_serializable() fstream = SerializableHdf5File("blaah.h5", "w") status = svm.save_serializable(fstream) check_status(status,'h5') fstream = SerializableAsciiFile("blaah.asc", "w") status = svm.save_serializable(fstream) check_status(status,'asc') fstream = SerializableJsonFile("blaah.json", "w") status = svm.save_serializable(fstream) check_status(status,'json') fstream = SerializableXmlFile("blaah.xml", "w") status = svm.save_serializable(fstream) check_status(status,'xml') fstream = SerializableHdf5File("blaah.h5", "r") new_svm=GMNPSVM() status = new_svm.load_serializable(fstream) check_status(status,'h5') new_svm.train() bias_h5 = new_svm.get_svm(0).get_bias() fstream = SerializableAsciiFile("blaah.asc", "r") new_svm=GMNPSVM() status = new_svm.load_serializable(fstream) check_status(status,'asc') new_svm.train() bias_asc = new_svm.get_svm(0).get_bias() fstream = SerializableJsonFile("blaah.json", "r") new_svm=GMNPSVM() status = new_svm.load_serializable(fstream) check_status(status,'json') new_svm.train() bias_json = new_svm.get_svm(0).get_bias() fstream = SerializableXmlFile("blaah.xml", "r") new_svm=GMNPSVM() status = new_svm.load_serializable(fstream) check_status(status,'xml') new_svm.train() bias_xml = new_svm.get_svm(0).get_bias() os.unlink("blaah.h5") os.unlink("blaah.asc") os.unlink("blaah.json") os.unlink("blaah.xml") return svm,new_svm, bias_ref, bias_h5, bias_asc, bias_json, bias_xml