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updated reference documentation
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Soeren Sonnenburg
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/** \page staticcmdline Static Command Line Interface Function Reference | ||
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\section Features_sec Features | ||
\arg \b pr_loqo \verbatim [results]=sg('pr_loqo', 'Var1', Var1, 'Var2', Var2) \endverbatim | ||
\arg \b load_features \verbatim sg('load_features', filename, feature_class, type, target[, size[, comp_features]]) \endverbatim | ||
\arg \b save_features \verbatim sg('save_features', filename, type, target) \endverbatim | ||
\arg \b clean_features \verbatim sg('clean_features', 'TRAIN|TEST') \endverbatim | ||
\arg \b get_features \verbatim [features]=sg('get_features', 'TRAIN|TEST') \endverbatim | ||
\arg \b add_features \verbatim sg('add_features', 'TRAIN|TEST', features[, DNABINFILE|<ALPHABET>]) \endverbatim | ||
\arg \b add_multiple_features \verbatim sg('add_multiple_features', 'TRAIN|TEST', repetitions, features[, DNABINFILE|<ALPHABET>]) \endverbatim | ||
\arg \b add_dotfeatures \verbatim sg('add_dotfeatures', 'TRAIN|TEST', features[, DNABINFILE|<ALPHABET>]) \endverbatim | ||
\arg \b set_features \verbatim sg('set_features', 'TRAIN|TEST', features[, DNABINFILE|<ALPHABET>][, [from_position_list|slide_window], window size, [position_list|shift], skip) \endverbatim | ||
\arg \b set_ref_features \verbatim sg('set_ref_features', 'TRAIN|TEST') \endverbatim | ||
\arg \b del_last_features \verbatim sg('del_last_features', 'TRAIN|TEST') \endverbatim | ||
\arg \b convert \verbatim sg('convert', 'TRAIN|TEST', from_class, from_type, to_class, to_type[, order, start, gap, reversed]) \endverbatim | ||
\arg \b reshape \verbatim sg('reshape', 'TRAIN|TEST, num_feat, num_vec) \endverbatim | ||
\arg \b load_labels \verbatim sg('load_labels', filename, 'TRAIN|TARGET') \endverbatim | ||
\arg \b set_labels \verbatim sg('set_labels', 'TRAIN|TEST', labels) \endverbatim | ||
\arg \b get_labels \verbatim [labels]=sg('get_labels', 'TRAIN|TEST') \endverbatim | ||
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\section Kernel_sec Kernel | ||
\arg \b set_kernel_normalization \verbatim sg('set_kernel_normalization', IDENTITY|AVGDIAG|SQRTDIAG|FIRSTELEMENT|VARIANCE|ZEROMEANCENTER, size[, kernel-specific parameters]) \endverbatim | ||
\arg \b set_kernel \verbatim sg('set_kernel', type, size[, kernel-specific parameters]) \endverbatim | ||
\arg \b add_kernel \verbatim sg('add_kernel', weight, kernel-specific parameters) \endverbatim | ||
\arg \b del_last_kernel \verbatim sg('del_last_kernel') \endverbatim | ||
\arg \b init_kernel \verbatim sg('init_kernel', 'TRAIN|TEST') \endverbatim | ||
\arg \b clean_kernel \verbatim sg('clean_kernel') \endverbatim | ||
\arg \b save_kernel \verbatim sg('save_kernel', filename, 'TRAIN|TEST') \endverbatim | ||
\arg \b get_kernel_matrix \verbatim [K]]=sg('get_kernel_matrix', ['TRAIN|TEST') \endverbatim | ||
\arg \b set_WD_position_weights \verbatim sg('set_WD_position_weights', W[, 'TRAIN|TEST']) \endverbatim | ||
\arg \b get_subkernel_weights \verbatim [W]=sg('get_subkernel_weights') \endverbatim | ||
\arg \b set_subkernel_weights \verbatim sg('set_subkernel_weights', W) \endverbatim | ||
\arg \b set_subkernel_weights_combined \verbatim sg('set_subkernel_weights_combined', W, idx) \endverbatim | ||
\arg \b get_dotfeature_weights_combined \verbatim [W]=sg('get_dotfeature_weights_combined', 'TRAIN|TEST') \endverbatim | ||
\arg \b set_dotfeature_weights_combined \verbatim sg('set_dotfeature_weights_combined', W, idx) \endverbatim | ||
\arg \b set_last_subkernel_weights \verbatim sg('set_last_subkernel_weights', W) \endverbatim | ||
\arg \b get_WD_position_weights \verbatim [W]=sg('get_WD_position_weights') \endverbatim | ||
\arg \b get_last_subkernel_weights \verbatim [W]=sg('get_last_subkernel_weights') \endverbatim | ||
\arg \b compute_by_subkernels \verbatim [W]=sg('compute_by_subkernels') \endverbatim | ||
\arg \b init_kernel_optimization \verbatim sg('init_kernel_optimization') \endverbatim | ||
\arg \b get_kernel_optimization \verbatim [W]=sg('get_kernel_optimization') \endverbatim | ||
\arg \b delete_kernel_optimization \verbatim sg('delete_kernel_optimization') \endverbatim | ||
\arg \b use_diagonal_speedup \verbatim sg('use_diagonal_speedup', '0|1') \endverbatim | ||
\arg \b set_kernel_optimization_type \verbatim sg('set_kernel_optimization_type', 'FASTBUTMEMHUNGRY|SLOWBUTMEMEFFICIENT') \endverbatim | ||
\arg \b set_solver \verbatim sg('set_solver', 'AUTO|CPLEX|GLPK|INTERNAL') \endverbatim | ||
\arg \b set_constraint_generator \verbatim sg('set_constraint_generator', 'LIBSVM_ONECLASS|LIBSVM_MULTICLASS|LIBSVM|SVMLIGHT|LIGHT|SVMLIGHT_ONECLASS|GPBTSVM|MPDSVM|GNPPSVM|GMNPSVM') \endverbatim | ||
\arg \b set_prior_probs \verbatim sg('set_prior_probs', 'pos probs, neg_probs') \endverbatim | ||
\arg \b set_prior_probs_from_labels \verbatim sg('set_prior_probs_from_labels', 'labels') \endverbatim | ||
\arg \b resize_kernel_cache \verbatim sg('resize_kernel_cache', size) \endverbatim | ||
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\section Distance_sec Distance | ||
\arg \b set_distance \verbatim sg('set_distance', type, data type[, distance-specific parameters]) \endverbatim | ||
\arg \b init_distance \verbatim sg('init_distance', 'TRAIN|TEST') \endverbatim | ||
\arg \b get_distance_matrix \verbatim [D]=sg('get_distance_matrix') \endverbatim | ||
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\section Classifier_sec Classifier | ||
\arg \b classify \verbatim [result]=sg('classify') \endverbatim | ||
\arg \b svm_classify \verbatim [result]=sg('svm_classify') \endverbatim | ||
\arg \b classify_example \verbatim [result]=sg('classify_example', feature_vector_index) \endverbatim | ||
\arg \b svm_classify_example \verbatim [result]=sg('svm_classify_example', feature_vector_index) \endverbatim | ||
\arg \b get_classifier \verbatim [bias, weights]=sg('get_classifier', [index in case of MultiClassSVM]) \endverbatim | ||
\arg \b get_clustering \verbatim [radi, centers|merge_distances, pairs]=sg('get_clustering') \endverbatim | ||
\arg \b new_svm \verbatim sg('new_svm', 'LIBSVM_ONECLASS|LIBSVM_MULTICLASS|LIBSVM|SVMLIGHT|LIGHT|LIGHT_ONECLASS|SVMLIN|GPBTSVM|MPDSVM|GNPPSVM|GMNPSVM|SUBGRADIENTSVM|WDSVMOCAS|SVMOCAS|SVMSGD|SVMBMRM|SVMPERF|KERNELPERCEPTRON|PERCEPTRON|LIBLINEAR_LR|LIBLINEAR_L2|LDA|LPM|LPBOOST|SUBGRADIENTLPM|KNN') \endverbatim | ||
\arg \b new_classifier \verbatim sg('new_classifier', 'LIBSVM_ONECLASS|LIBSVM_MULTICLASS|LIBSVM|SVMLIGHT|LIGHT|LIGHT_ONECLASS|SVMLIN|GPBTSVM|MPDSVM|GNPPSVM|GMNPSVM|SUBGRADIENTSVM|WDSVMOCAS|SVMOCAS|SVMSGD|SVMBMRM|SVMPERF|KERNELPERCEPTRON|PERCEPTRON|LIBLINEAR_LR|LIBLINEAR_L2|LDA|LPM|LPBOOST|SUBGRADIENTLPM|KNN') \endverbatim | ||
\arg \b new_regression \verbatim sg('new_regression', 'SVRLIGHT|LIBSVR|KRR') \endverbatim | ||
\arg \b new_clustering \verbatim sg('new_clustering', 'KMEANS|HIERARCHICAL') \endverbatim | ||
\arg \b load_classifier \verbatim [filename, type]=sg('load_classifier') \endverbatim | ||
\arg \b save_classifier \verbatim sg('save_classifier', filename) \endverbatim | ||
\arg \b get_num_svms \verbatim [number of SVMs in MultiClassSVM]=sg('get_num_svms') \endverbatim | ||
\arg \b get_svm \verbatim [bias, alphas]=sg('get_svm', [index in case of MultiClassSVM]) \endverbatim | ||
\arg \b set_svm \verbatim sg('set_svm', bias, alphas) \endverbatim | ||
\arg \b set_linear_classifier \verbatim sg('set_linear_classifier', bias, w) \endverbatim | ||
\arg \b get_svm_objective \verbatim [objective]=sg('get_svm_objective') \endverbatim | ||
\arg \b compute_svm_primal_objective \verbatim [objective]=sg('compute_svm_primal_objective') \endverbatim | ||
\arg \b compute_svm_dual_objective \verbatim [objective]=sg('compute_svm_dual_objective') \endverbatim | ||
\arg \b compute_mkl_primal_objective \verbatim [objective]=sg('compute_mkl_primal_objective') \endverbatim | ||
\arg \b compute_mkl_dual_objective \verbatim [objective]=sg('compute_mkl_dual_objective') \endverbatim | ||
\arg \b compute_relative_mkl_duality_gap \verbatim [gap]=sg('compute_relative_mkl_duality_gap') \endverbatim | ||
\arg \b compute_absolute_mkl_duality_gap \verbatim [gap]=sg('compute_absolute_mkl_duality_gap') \endverbatim | ||
\arg \b do_auc_maximization \verbatim sg('do_auc_maximization', 'auc') \endverbatim | ||
\arg \b set_perceptron_parameters \verbatim sg('set_perceptron_parameters', learnrate, maxiter) \endverbatim | ||
\arg \b train_classifier \verbatim sg('train_classifier', [classifier-specific parameters]) \endverbatim | ||
\arg \b train_regression \verbatim sg('train_regression') \endverbatim | ||
\arg \b train_clustering \verbatim sg('train_clustering') \endverbatim | ||
\arg \b svm_train \verbatim sg('svm_train', [classifier-specific parameters]) \endverbatim | ||
\arg \b svm_qpsize \verbatim sg('svm_qpsize', size) \endverbatim | ||
\arg \b svm_max_qpsize \verbatim sg('svm_max_qpsize', size) \endverbatim | ||
\arg \b svm_bufsize \verbatim sg('svm_bufsize', size) \endverbatim | ||
\arg \b c \verbatim sg('c', C1[, C2]) \endverbatim | ||
\arg \b svm_epsilon \verbatim sg('svm_epsilon', epsilon) \endverbatim | ||
\arg \b svr_tube_epsilon \verbatim sg('svr_tube_epsilon', tube_epsilon) \endverbatim | ||
\arg \b svm_nu \verbatim sg('svm_nu', nu) \endverbatim | ||
\arg \b mkl_parameters \verbatim sg('mkl_parameters', weight_epsilon, C_MKL [, mkl_norm ]) \endverbatim | ||
\arg \b elasticnet_lambda \verbatim sg('elasticnet_lambda', ent_lambda) \endverbatim | ||
\arg \b mkl_block_norm \verbatim sg('mkl_block_norm', mkl_block_norm) \endverbatim | ||
\arg \b svm_max_train_time \verbatim sg('svm_max_train_time', max_train_time) \endverbatim | ||
\arg \b use_shrinking \verbatim sg('use_shrinking', enable_shrinking) \endverbatim | ||
\arg \b use_batch_computation \verbatim sg('use_batch_computation', enable_batch_computation) \endverbatim | ||
\arg \b use_linadd \verbatim sg('use_linadd', enable_linadd) \endverbatim | ||
\arg \b svm_use_bias \verbatim sg('svm_use_bias', enable_bias) \endverbatim | ||
\arg \b mkl_use_interleaved_optimization \verbatim sg('mkl_use_interleaved_optimization', enable_interleaved_optimization) \endverbatim | ||
\arg \b krr_tau \verbatim sg('krr_tau', tau) \endverbatim | ||
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\section Preprocessors_sec Preprocessors | ||
\arg \b add_preproc \verbatim sg('add_preproc', preproc[, preproc-specific parameters]) \endverbatim | ||
\arg \b del_preproc \verbatim sg('del_preproc') \endverbatim | ||
\arg \b attach_preproc \verbatim sg('attach_preproc', 'TRAIN|TEST', force) \endverbatim | ||
\arg \b clean_preproc \verbatim sg('clean_preproc') \endverbatim | ||
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\section HMM_sec HMM | ||
\arg \b new_hmm \verbatim sg('new_hmm', N, M) \endverbatim | ||
\arg \b load_hmm \verbatim sg('load_hmm', filename) \endverbatim | ||
\arg \b save_hmm \verbatim sg('save_hmm', filename[, save_binary]) \endverbatim | ||
\arg \b get_hmm \verbatim [p, q, a, b]=sg('get_hmm') \endverbatim | ||
\arg \b append_hmm \verbatim sg('append_hmm', p, q, a, b) \endverbatim | ||
\arg \b append_model \verbatim sg('append_model', 'filename'[, base1, base2]) \endverbatim | ||
\arg \b set_hmm \verbatim sg('set_hmm', p, q, a, b) \endverbatim | ||
\arg \b set_hmm_as \verbatim sg('set_hmm_as', POS|NEG|TEST) \endverbatim | ||
\arg \b chop \verbatim sg('chop', chop) \endverbatim | ||
\arg \b pseudo \verbatim sg('pseudo', pseudo) \endverbatim | ||
\arg \b load_defs \verbatim sg('load_defs', filename, init) \endverbatim | ||
\arg \b hmm_classify \verbatim [result]=sg('hmm_classify') \endverbatim | ||
\arg \b one_class_linear_hmm_classify \verbatim [result]=sg('one_class_linear_hmm_classify') \endverbatim | ||
\arg \b one_class_hmm_classify \verbatim [result]=sg('one_class_hmm_classify') \endverbatim | ||
\arg \b one_class_hmm_classify_example \verbatim [result]=sg('one_class_hmm_classify_example', feature_vector_index) \endverbatim | ||
\arg \b hmm_classify_example \verbatim [result]=sg('hmm_classify_example', feature_vector_index) \endverbatim | ||
\arg \b output_hmm \verbatim sg('output_hmm') \endverbatim | ||
\arg \b output_hmm_defined \verbatim sg('output_hmm_defined') \endverbatim | ||
\arg \b hmm_likelihood \verbatim [likelihood]=sg('hmm_likelihood') \endverbatim | ||
\arg \b likelihood \verbatim sg('likelihood') \endverbatim | ||
\arg \b save_hmm_likelihood \verbatim sg('save_hmm_likelihood', filename[, save_binary]) \endverbatim | ||
\arg \b get_viterbi_path \verbatim [path, likelihood]=sg('get_viterbi_path', dim) \endverbatim | ||
\arg \b vit_def \verbatim sg('vit_def') \endverbatim | ||
\arg \b vit \verbatim sg('vit') \endverbatim | ||
\arg \b bw \verbatim sg('bw') \endverbatim | ||
\arg \b bw_def \verbatim sg('bw_def') \endverbatim | ||
\arg \b bw_trans \verbatim sg('bw_trans') \endverbatim | ||
\arg \b linear_train \verbatim sg('linear_train') \endverbatim | ||
\arg \b save_hmm_path \verbatim sg('save_hmm_path', filename[, save_binary]) \endverbatim | ||
\arg \b convergence_criteria \verbatim sg('convergence_criteria', num_iterations, epsilon) \endverbatim | ||
\arg \b normalize_hmm \verbatim sg('normalize_hmm', [keep_dead_states]) \endverbatim | ||
\arg \b add_states \verbatim sg('add_states', states, value) \endverbatim | ||
\arg \b permutation_entropy \verbatim sg('permutation_entropy', width, seqnum) \endverbatim | ||
\arg \b relative_entropy \verbatim [result]=sg('relative_entropy') \endverbatim | ||
\arg \b entropy \verbatim [result]=sg('entropy') \endverbatim | ||
\arg \b set_feature_matrix \verbatim sg('set_feature_matrix', features) \endverbatim | ||
\arg \b set_feature_matrix_sparse \verbatim sg('set_feature_matrix_sparse', sp1, sp2) \endverbatim | ||
\arg \b new_plugin_estimator \verbatim sg('new_plugin_estimator', pos_pseudo, neg_pseudo) \endverbatim | ||
\arg \b train_estimator \verbatim sg('train_estimator') \endverbatim | ||
\arg \b plugin_estimate_classify_example \verbatim [result]=sg('plugin_estimate_classify_example', feature_vector_index) \endverbatim | ||
\arg \b plugin_estimate_classify \verbatim [result]=sg('plugin_estimate_classify') \endverbatim | ||
\arg \b set_plugin_estimate \verbatim sg('set_plugin_estimate', emission_probs, model_sizes) \endverbatim | ||
\arg \b get_plugin_estimate \verbatim [emission_probs, model_sizes]=sg('get_plugin_estimate') \endverbatim | ||
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\section Signals_sec Signals | ||
\arg \b signals_set_model \verbatim sg('signals_set_model', arg1) \endverbatim | ||
\arg \b signals_set_positions \verbatim sg('signals_set_positions', positions) \endverbatim | ||
\arg \b signals_set_labels \verbatim sg('signals_set_labels', labels) \endverbatim | ||
\arg \b signals_set_split \verbatim sg('signals_set_split', split) \endverbatim | ||
\arg \b signals_set_train_mask \verbatim sg('signals_set_train_mask', ) \endverbatim | ||
\arg \b signals_add_feature \verbatim sg('signals_add_feature', feature) \endverbatim | ||
\arg \b signals_add_kernel \verbatim sg('signals_add_kernel', kernelparam) \endverbatim | ||
\arg \b signals_run \verbatim sg('signals_run', arg1) \endverbatim | ||
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\section Structure_sec Structure | ||
\arg \b best_path \verbatim sg('best_path', from, to) \endverbatim | ||
\arg \b best_path_2struct \verbatim [prob, path, pos]=sg('best_path_2struct', p, q, cmd_trans, seq, pos, genestr, penalties, penalty_info, nbest, content_weights, segment_sum_weights) \endverbatim | ||
\arg \b set_plif_struct \verbatim sg('set_plif_struct', id, name, limits, penalties, transform, min_value, max_value, use_cache, use_svm) \endverbatim | ||
\arg \b get_plif_struct \verbatim [id, name, limits, penalties, transform, min_value, max_value, use_cache, use_svm]=sg('get_plif_struct') \endverbatim | ||
\arg \b precompute_subkernels \verbatim sg('precompute_subkernels') \endverbatim | ||
\arg \b precompute_content_svms \verbatim sg('precompute_content_svms', sequence, position_list, weights) \endverbatim | ||
\arg \b get_lin_feat \verbatim [lin_feat]=sg('get_lin_feat') \endverbatim | ||
\arg \b set_lin_feat \verbatim sg('set_lin_feat', lin_feat) \endverbatim | ||
\arg \b init_dyn_prog \verbatim sg('init_dyn_prog', num_svms) \endverbatim | ||
\arg \b clean_up_dyn_prog \verbatim sg('clean_up_dyn_prog') \endverbatim | ||
\arg \b init_intron_list \verbatim sg('init_intron_list', start_positions, end_positions, quality) \endverbatim | ||
\arg \b precompute_tiling_features \verbatim sg('precompute_tiling_features', intensities, probe_pos, tiling_plif_ids) \endverbatim | ||
\arg \b long_transition_settings \verbatim sg('long_transition_settings', use_long_transitions, threshold, max_len) \endverbatim | ||
\arg \b set_model \verbatim sg('set_model', content_weights, transition_pointers, use_orf, mod_words) \endverbatim | ||
\arg \b best_path_trans \verbatim [prob, path, pos]=sg('best_path_trans', p, q, nbest, seq_path, a_trans, segment_loss) \endverbatim | ||
\arg \b best_path_trans_deriv \verbatim [p_deriv, q_deriv, cmd_deriv, penalties_deriv, my_scores, my_loss]=sg('best_path_trans_deriv', , my_path, my_pos, p, q, cmd_trans, seq, pos, genestr, penalties, state_signals, penalty_info, dict_weights, mod_words [, segment_loss, segmend_ids_mask]) \endverbatim | ||
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\section POIM_sec POIM | ||
\arg \b compute_poim_wd \verbatim [W]=sg('compute_poim_wd', max_order, distribution) \endverbatim | ||
\arg \b get_SPEC_consensus \verbatim [W]=sg('get_SPEC_consensus') \endverbatim | ||
\arg \b get_SPEC_scoring \verbatim [W]=sg('get_SPEC_scoring', max_order) \endverbatim | ||
\arg \b get_WD_consensus \verbatim [W]=sg('get_WD_consensus') \endverbatim | ||
\arg \b get_WD_scoring \verbatim [W]=sg('get_WD_scoring', max_order) \endverbatim | ||
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\section Utility_sec Utility | ||
\arg \b crc \verbatim [crc32]=sg('crc', string) \endverbatim | ||
\arg \b ! \verbatim sg('!', system_command) \endverbatim | ||
\arg \b exit \verbatim sg('exit') \endverbatim | ||
\arg \b quit \verbatim sg('quit') \endverbatim | ||
\arg \b exec \verbatim sg('exec', filename) \endverbatim | ||
\arg \b set_output \verbatim sg('set_output', 'STDERR|STDOUT|filename') \endverbatim | ||
\arg \b set_threshold \verbatim sg('set_threshold', threshold) \endverbatim | ||
\arg \b init_random \verbatim sg('init_random', value_to_initialize_RNG_with) \endverbatim | ||
\arg \b threads \verbatim sg('threads', num_threads) \endverbatim | ||
\arg \b translate_string \verbatim [translation]=sg('translate_string', string, order, start) \endverbatim | ||
\arg \b clear \verbatim sg('clear') \endverbatim | ||
\arg \b tic \verbatim sg('tic') \endverbatim | ||
\arg \b toc \verbatim sg('toc') \endverbatim | ||
\arg \b print \verbatim sg('print', msg) \endverbatim | ||
\arg \b echo \verbatim sg('echo', level) \endverbatim | ||
\arg \b loglevel \verbatim sg('loglevel', 'ALL|DEBUG|INFO|NOTICE|WARN|ERROR|CRITICAL|ALERT|EMERGENCY') \endverbatim | ||
\arg \b syntax_highlight \verbatim sg('syntax_highlight', 'ON|OFF') \endverbatim | ||
\arg \b progress \verbatim sg('progress', 'ON|OFF') \endverbatim | ||
\arg \b get_version \verbatim [version]=sg('get_version') \endverbatim | ||
\arg \b help \verbatim sg('help') \endverbatim | ||
\arg \b whos \verbatim sg('whos') \endverbatim | ||
\arg \b run_python \verbatim [results]=sg('run_python', 'Var1', Var1, 'Var2', Var2,..., python_function) \endverbatim | ||
\arg \b run_octave \verbatim [results]=sg('run_octave', 'Var1', Var1, 'Var2', Var2,..., octave_function) \endverbatim | ||
\arg \b run_r \verbatim [results]=sg('run_r', 'Var1', Var1, 'Var2', Var2,..., r_function) \endverbatim | ||
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*/ |
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