Mercurial > repos > bgruening > sklearn_sample_generator
changeset 0:f58c35905608 draft
planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit a6e80305ed0892c8163d690a2d376d6b454824de-dirty
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--- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/main_macros.xml Mon May 02 16:14:36 2016 -0400 @@ -0,0 +1,341 @@ +<macros> + <token name="@VERSION@">0.9</token> + + <xml name="python_requirements"> + <requirements> + <requirement type="package" version="0.2.1b">eden</requirement> + <yield /> + </requirements> + </xml> + + <xml name="macro_stdio"> + <stdio> + <exit_code range="1:" level="fatal" description="Error occurred. Please check Tool Standard Error" /> + </stdio> + </xml> + + <xml name="train_loadConditional" token_train="tabular" token_data="tabular" token_model="txt"> + <conditional name="selected_tasks"> + <param name="selected_task" type="select" label="Select a Classification Task"> + <option value="load">Load a model and predict</option> + <option value="train" selected="true">Train a model</option> + </param> + <when value="load"> + <param name="infile_model" type="data" format="@MODEL@" label="Models" help="Select a model file." /> + <param name="infile_data" type="data" format="@DATA@" label="Data (tabular)" help="Select the dataset you want to classify."/> + <conditional name="prediction_options"> + <param name="prediction_option" type="select" label="Select the type of prediction"> + <option value="predict">Predict class labels</option> + <option value="advanced">Include advanced options</option> + </param> + <when value="predict"> + </when> + <when value="advanced"> + </when> + </conditional> + </when> + <when value="train"> + <param name="infile_train" type="data" format="@TRAIN@" label="Training samples (tabular)" /> + <conditional name="selected_algorithms"> + <yield /> + </conditional> + </when> + </conditional> + </xml> + + <xml name="advanced_section"> + <section name="options" title="Advanced Options" expanded="False"> + <yield /> + </section> + </xml> + + <xml name="tabular_input"> + <param name="infile" type="data" format="tabular" label="Data file with numeric values"/> + <param name="start_column" type="data_column" data_ref="infile" optional="True" label="Select a subset of data. Start column:" /> + <param name="end_column" type="data_column" data_ref="infile" optional="True" label="End column:" /> + </xml> + + <xml name="tol" token_default_value="0.0" token_help_text="Early stopping heuristics based on the relative center changes. Set to default (0.0) to disable this convergence detection."> + <param argument="tol" type="float" optional="true" value="@DEFAULT_VALUE@" label="Tolerance" help="@HELP_TEXT@"/> + </xml> + + <xml name="n_clusters" token_default_value="8"> + <param argument="n_clusters" type="integer" optional="true" value="@DEFAULT_VALUE@" label="Number of clusters" help=" "/> + </xml> + + <xml name="fit_intercept" token_checked="true"> + <param argument="fit_intercept" type="boolean" optional="true" truevalue="booltrue" falsevalue="boolflase" checked="@CHECKED@" label="Estimate the intercept" help="If false, the data is assumed to be already centered."/> + </xml> + + <xml name="n_iter" token_default_value="5" token_help_text="The number of passes over the training data (aka epochs). "> + <param argument="n_iter" type="integer" optional="true" value="@DEFAULT_VALUE@" label="Number of iterations" help="@HELP_TEXT@"/> + </xml> + + <xml name="shuffle" token_checked="true" token_help_text=" " token_label="Shuffle data after each iteration"> + <param argument="shuffle" type="boolean" optional="true" truevalue="booltrue" falsevalue="boolflase" checked="@CHECKED@" label="@LABEL@" help="@HELP_TEXT@"/> + </xml> + + <xml name="random_state" token_default_value="" token_help_text="Integer number. The seed of the pseudo random number generator to use when shuffling the data. A fixed seed allows reproducible results."> + <param argument="random_state" type="integer" optional="true" value="@DEFAULT_VALUE@" label="Random seed number" help="@HELP_TEXT@"/> + </xml> + + <xml name="warm_start" token_checked="true" token_help_text="When set to True, reuse the solution of the previous call to fit as initialization,otherwise, just erase the previous solution."> + <param argument="warm_start" type="boolean" optional="true" truevalue="booltrue" falsevalue="boolflase" checked="@CHECKED@" label="Perform warm start" help="@HELP_TEXT@"/> + </xml> + + <xml name="C" token_default_value="1.0" token_help_text="Penalty parameter C of the error term."> + <param argument="C" type="float" optional="true" value="@DEFAULT_VALUE@" label="Penalty parameter" help="@HELP_TEXT@"/> + </xml> + + <!--xml name="class_weight" token_default_value="" token_help_text=""> + <param argument="class_weight" type="" optional="true" value="@DEFAULT_VALUE@" label="" help="@HELP_TEXT@"/> + </xml--> + + <xml name="alpha" token_default_value="0.0001" token_help_text="Constant that multiplies the regularization term if regularization is used. "> + <param argument="alpha" type="float" optional="true" value="@DEFAULT_VALUE@" label="Regularization coefficient" help="@HELP_TEXT@"/> + </xml> + + <xml name="n_samples" token_default_value="100" token_help_text="The total number of points equally divided among clusters."> + <param argument="n_samples" type="integer" optional="true" value="@DEFAULT_VALUE@" label="Number of samples" help="@HELP_TEXT@"/> + </xml> + + <xml name="n_features" token_default_value="2" token_help_text="Number of different numerical properties produced for each sample."> + <param argument="n_features" type="integer" optional="true" value="@DEFAULT_VALUE@" label="Number of features" help="@HELP_TEXT@"/> + </xml> + + <xml name="noise" token_default_value="0.0" token_help_text="Floating point number. "> + <param argument="noise" type="float" optional="true" value="@DEFAULT_VALUE@" label="Standard deviation of the Gaussian noise added to the data" help="@HELP_TEXT@"/> + </xml> + + <xml name="C" token_default_value="1.0" token_help_text="Penalty parameter C of the error term. "> + <param argument="C" type="float" optional="true" value="@DEFAULT_VALUE@" label="Penalty parameter" help="@HELP_TEXT@"/> + </xml> + + <xml name="max_iter" token_default_value="300" token_label="Maximum number of iterations per single run" token_help_text=" "> + <param argument="max_iter" type="integer" optional="true" value="@DEFAULT_VALUE@" label="@LABEL@" help="@HELP_TEXT@"/> + </xml> + + <xml name="n_init" token_default_value="10" > + <param argument="n_init" type="integer" optional="true" value="@DEFAULT_VALUE@" label="Number of runs with different centroid seeds" help=" "/> + </xml> + + <xml name="init"> + <param argument="init" type="select" label="Centroid initialization method" help="''k-means++'' selects initial cluster centers that speed up convergence. ''random'' chooses k observations (rows) at random from data as initial centroids."> + <option value="k-means++">k-means++</option> + <option value="random">random</option> + </param> + </xml> + + <xml name="multiple_sparse"> + <repeat name="sparse_inputs" min="1" max="10" title="Inputs"> + <param name="input" type="data" format="txt" label="Sparse matrix file (.mtx, .txt)" help="Specify a sparse matrix file in .txt format."/> + </repeat> + </xml> + + <xml name="eden_citation"> + <citations> + <citation type="bibtex"> + @misc{fabrizio_costa_2015_15094, + author = {Fabrizio Costa and + Björn Grüning and + gigolo}, + title = {EDeN: EDeN - Graph Vectorizer}, + month = feb, + year = 2015, + doi = {10.5281/zenodo.15094}, + url = {http://dx.doi.org/10.5281/zenodo.15094} + } + } + </citation> + </citations> + </xml> + + <xml name="sklearn_citation"> + <citations> + <citation type="bibtex"> + @article{scikit-learn, + title={Scikit-learn: Machine Learning in {P}ython}, + author={Pedregosa, F. and Varoquaux, G. and Gramfort, A. and Michel, V. + and Thirion, B. and Grisel, O. and Blondel, M. and Prettenhofer, P. + and Weiss, R. and Dubourg, V. and Vanderplas, J. and Passos, A. and + Cournapeau, D. and Brucher, M. and Perrot, M. and Duchesnay, E.}, + journal={Journal of Machine Learning Research}, + volume={12}, + pages={2825--2830}, + year={2011} + url = {https://github.com/scikit-learn/scikit-learn} + } + </citation> + </citations> + </xml> + + <xml name="scipy_citation"> + <citations> + <citation type="bibtex"> + @Misc{, + author = {Eric Jones and Travis Oliphant and Pearu Peterson and others}, + title = {{SciPy}: Open source scientific tools for {Python}}, + year = {2001--}, + url = "http://www.scipy.org/", + note = {[Online; accessed 2016-04-09]} + } + </citation> + </citations> + </xml> + + + <xml name="nn_advanced_options"> + <section name="options" title="Advanced Options" expanded="False"> + <yield/> + <param argument="weights" type="select" label="Weight function" help="Used in prediction."> + <option value="uniform" selected="true" help="Uniform weights. All points in each neighborhood are weighted equally.">Uniform</option> + <option value="distance" help="Weight points by the inverse of their distance.">Distance</option> + </param> + <param argument="algorithm" type="select" label="Neighbor selection algorithm" help=" "> + <option value="auto" selected="true">Auto</option> + <option value="ball_tree">BallTree</option> + <option value="kd_tree">KDTree</option> + <option value="brute">Brute-force</option> + </param> + <param argument="leaf_size" type="integer" value="30" label="Leaf size" help="Used with BallTree and KDTree. Affects the time and memory usage of the constructed tree."/> + <!--param name="metric"--> + <!--param name="p"--> + <!--param name="metric_params"--> + </section> + </xml> + + <xml name="svc_advanced_options"> + <section name="options" title="Advanced Options" expanded="False"> + <yield/> + <param argument="kernel" type="select" optional="true" label="Kernel type" help="Kernel type to be used in the algorithm. If none is given, ‘rbf’ will be used."> + <option value="rbf" selected="true">rbf</option> + <option value="linear">linear</option> + <option value="poly">poly</option> + <option value="sigmoid">sigmoid</option> + <option value="precomputed">precomputed</option> + </param> + <param argument="degree" type="integer" optional="true" value="3" label="Degree of the polynomial (polynomial kernel only)" help="Ignored by other kernels. dafault : 3 "/> + <!--TODO: param argument="gamma" float, optional (default=’auto’) --> + <param argument="coef0" type="float" optional="true" value="0.0" label="Zero coefficient (polynomial and sigmoid kernels only)" help="Independent term in kernel function. dafault: 0.0 "/> + <param argument="shrinking" type="boolean" optional="true" truevalue="booltrue" falsevalue="boolflase" checked="true" label="Use the shrinking heuristic" help=" "/> + <param argument="probability" type="boolean" optional="true" truevalue="booltrue" falsevalue="boolflase" checked="false" label="Enable probability estimates. " help="This must be enabled prior to calling fit, and will slow down that method."/> + <!-- param argument="cache_size"--> + <!--expand macro="class_weight"/--> + <expand macro="tol" default_value="0.001" help_text="Tolerance for stopping criterion. "/> + <expand macro="max_iter" default_value="-1" label="Solver maximum number of iterations" help_text="Hard limit on iterations within solver, or -1 for no limit."/> + <!--param argument="decision_function_shape"--> + <expand macro="random_state" help_text="Integer number. The seed of the pseudo random number generator to use when shuffling the data for probability estimation. A fixed seed allows reproducible results."/> + </section> + </xml> + + <xml name="spectral_clustering_advanced_options"> + <section name="options" title="Advanced Options" expanded="False"> + <expand macro="n_clusters"/> + <param argument="eigen_solver" type="select" value="" label="Eigen solver" help="The eigenvalue decomposition strategy to use."> + <option value="arpack" selected="true">arpack</option> + <option value="lobpcg">lobpcg</option> + <option value="amg">amg</option> + <!--None--> + </param> + <expand macro="random_state"/> + <expand macro="n_init"/> + <param argument="gamma" type="float" optional="true" value="1.0" label="Kernel scaling factor" help="Scaling factor of RBF, polynomial, exponential chi^2 and sigmoid affinity kernel. Ignored for affinity=''nearest_neighbors''."/> + <param argument="affinity" type="select" label="Affinity" help="Affinity kernel to use. "> + <option value="rbf" selected="true">RBF</option> + <option value="precomputed">precomputed</option> + <option value="nearest_neighbors">Nearset neighbors</option> + </param> + <param argument="n_neighbors" type="integer" optional="true" value="10" label="Number of neighbors" help="Number of neighbors to use when constructing the affinity matrix using the nearest neighbors method. Ignored for affinity=''rbf''"/> + <!--param argument="eigen_tol"--> + <param argument="assign_labels" type="select" label="Assign labels" help="The strategy to use to assign labels in the embedding space."> + <option value="kmeans" selected="true">kmeans</option> + <option value="discretize">discretize</option> + </param> + <param argument="degree" type="integer" optional="true" value="3" label="Degree of the polynomial (polynomial kernel only)" help="Ignored by other kernels. dafault : 3 "/> + <param argument="coef0" type="integer" optional="true" value="1" label="Zero coefficient (polynomial and sigmoid kernels only)" help="Ignored by other kernels. dafault : 1 "/> + <!--param argument="kernel_params"--> + </section> + </xml> + + <xml name="minibatch_kmeans_advanced_options"> + <section name="options" title="Advanced Options" expanded="False"> + <expand macro="n_clusters"/> + <expand macro="init"/> + <expand macro="n_init" default_value="3"/> + <expand macro="max_iter" default_value="100"/> + <expand macro="tol" help_text="Early stopping heuristics based on normalized center change. To disable set to 0.0 ."/> + <expand macro="random_state"/> + <param argument="batch_size" type="integer" optional="true" value="100" label="Batch size" help="Size of the mini batches."/> + <!--param argument="compute_labels"--> + <param argument="max_no_improvement" type="integer" optional="true" value="10" label="Maximum number of improvement attempts" help=" + Convergence detection based on inertia (the consecutive number of mini batches that doe not yield an improvement on the smoothed inertia). + To disable, set max_no_improvement to None. "/> + <param argument="init_size" type="integer" optional="true" value="" label="Number of random initialization samples" help="Number of samples to randomly sample for speeding up the initialization . ( default: 3 * batch_size )"/> + <param argument="reassignment_ratio" type="float" optional="true" value="0.01" label="Re-assignment ratio" help="Controls the fraction of the maximum number of counts for a center to be reassigned. Higher values yield better clustering results."/> + </section> + </xml> + + <xml name="kmeans_advanced_options"> + <section name="options" title="Advanced Options" expanded="False"> + <expand macro="n_clusters"/> + <expand macro="init"/> + <expand macro="n_init"/> + <expand macro="max_iter"/> + <expand macro="tol" default_value="0.0001" help_text="Relative tolerance with regards to inertia to declare convergence."/> + <!--param argument="precompute_distances"/--> + <expand macro="random_state"/> + <param argument="copy_x" type="boolean" optional="true" truevalue="booltrue" falsevalue="boolflase" checked="true" label="Use a copy of data for precomputing distances" help="Mofifying the original data introduces small numerical differences caused by subtracting and then adding the data mean."/> + </section> + </xml> + + <xml name="birch_advanced_options"> + <section name="options" title="Advanced Options" expanded="False"> + <param argument="threshold" type="float" optional="true" value="0.5" label="Subcluster radius threshold" help="The radius of the subcluster obtained by merging a new sample; the closest subcluster should be less than the threshold to avoid a new subcluster."/> + <param argument="branching_factor" type="integer" optional="true" value="50" label="Maximum number of subclusters per branch" help="Maximum number of CF subclusters in each node."/> + <expand macro="n_clusters" default_value="3"/> + <!--param argument="compute_labels"/--> + </section> + </xml> + + <xml name="dbscan_advanced_options"> + <section name="options" title="Advanced Options" expanded="False"> + <param argument="eps" type="float" optional="true" value="0.5" label="Maximum neighborhood distance" help="The maximum distance between two samples for them to be considered as in the same neighborhood."/> + <param argument="min_samples" type="integer" optional="true" value="5" label="Minimal core point density" help="The number of samples (or total weight) in a neighborhood for a point (including the point itself) to be considered as a core point."/> + <param argument="metric" type="text" optional="true" value="euclidean" label="Metric" help="The metric to use when calculating distance between instances in a feature array."/> + <param argument="algorithm" type="select" label="Pointwise distance computation algorithm" help="The algorithm to be used by the NearestNeighbors module to compute pointwise distances and find nearest neighbors."> + <option value="auto" selected="true">auto</option> + <option value="ball_tree">ball_tree</option> + <option value="kd_tree">kd_tree</option> + <option value="brute">brute</option> + </param> + <param argument="leaf_size" type="integer" optional="true" value="30" label="Leaf size" help="Leaf size passed to BallTree or cKDTree. Memory and time efficieny factor in tree constrution and querying."/> + </section> + </xml> + + <xml name="clustering_algorithms_options"> + <conditional name="algorithm_options"> + <param name="selected_algorithm" type="select" label="Clustering Algorithm"> + <option value="KMeans" selected="true">KMeans</option> + <option value="SpectralClustering">Spectral Clustering</option> + <option value="MiniBatchKMeans">Mini Batch KMeans</option> + <option value="DBSCAN">DBSCAN</option> + <option value="Birch">Birch</option> + </param> + <when value="KMeans"> + <expand macro="kmeans_advanced_options"/> + </when> + <when value="DBSCAN"> + <expand macro="dbscan_advanced_options"/> + </when> + <when value="Birch"> + <expand macro="birch_advanced_options"/> + </when> + <when value="SpectralClustering"> + <expand macro="spectral_clustering_advanced_options"/> + </when> + <when value="MiniBatchKMeans"> + <expand macro="minibatch_kmeans_advanced_options"/> + </when> + </conditional> + </xml> +</macros>
--- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/sample_generator.xml Mon May 02 16:14:36 2016 -0400 @@ -0,0 +1,377 @@ +<tool id="sklearn_sample_generator" name="Generate" version="@VERSION@"> + <description>random samples with controlled size and complexity</description> + <macros> + <import>main_macros.xml</import> + </macros> + <expand macro="python_requirements"/> + <expand macro="macro_stdio"/> + <version_command>echo "@VERSION@"</version_command> + <command> + <![CDATA[ + python "$sample_generator_script" '$inputs' + ]]> + </command> + <configfiles> + <inputs name="inputs" /> + <configfile name="sample_generator_script"> + <![CDATA[ +import sys +import json +import pandas +import numpy as np +from sklearn import datasets + +input_json_path = sys.argv[1] +params = json.load(open(input_json_path, "r")) + +my_function = getattr(datasets, params["sample_generators"]["selected_generator"]) +options = params["sample_generators"]["options"] +my_points, my_targets = my_function(**options) + +points_df = pandas.DataFrame(my_points) +targets_df = pandas.DataFrame(my_targets) +res = pandas.concat([points_df, targets_df], axis=1) +res.to_csv(path_or_buf = "$outfile", sep="\t", index=False) + + ]]> + </configfile> + </configfiles> + <inputs> + <conditional name="sample_generators"> + <param name="selected_generator" type="select" label="Sample type:"> + <option value="make_blobs" selected="true">Isotropic Gaussian blobs for clustering</option> + <option value="make_classification">Random n-class classification problem</option> + <option value="make_gaussian_quantiles">Isotropic Gaussian and label samples by quantile</option> + <option value="make_hastie_10_2">Data for binary classification (used in Hastie et al)</option> + <option value="make_circles">Large circle containing a smaller circle in 2d (circles)</option> + <option value="make_moons">Two interleaving half circles (moons)</option> + <option value="make_regression">Random regression problem</option> + <option value="make_sparse_uncorrelated">Random regression problem with sparse uncorrelated design</option> + <option value="make_friedman1">“Friedman #1” regression problem</option> + <option value="make_friedman2">“Friedman #2” regression problem</option> + <option value="make_friedman3">“Friedman #3” regression problem</option> + <!--option value="make_low_rank_matrix">Mostly low rank matrix with bell-shaped singular values</option--> + <!--option value="make_multilabel_classification">Random multilabel classification problem</option--> + <option value="make_s_curve">S curve dataset</option> + <option value="make_swiss_roll">Swiss roll dataset</option> + <!--option value="make_sparse_coded_signal">Sparse combination of dictionary elements</option--> + <!--option value="make_sparse_spd_matrix">Sparse symmetric definite positive matrix</option--> + <!--option value="make_spd_matrix">Random symmetric, positive-definite matrix</option--> + <!--option value="make_biclusters">Array with constant block diagonal structure for biclustering</option> + <option value="make_checkerboard">Array with block checkerboard structure for biclustering</option--> + </param> + <when value="make_blobs"> + <section name="options" title="Advanced Options" expanded="False"> + <expand macro="n_samples"/> + <expand macro="n_features"/> + <param argument="centers" type="integer" optional="true" value="3" label="Number of centers to generate" help=" "/> + <!--todo: expand centers type : int or array of shape [n_centers, n_features]--> + <param argument="cluster_std" type="float" optional="true" value="1.0" label="Standard deviation of the clusters" help=" "/> + <!--todo: expand cluster_std type : float or sequence of floats--> + <!--param argument=center_box--> + <expand macro="shuffle" label="Shuffle the samples"/> + <expand macro="random_state"/> + </section> + </when> + <when value="make_classification"> + <section name="options" title="Advanced Options" expanded="False"> + <expand macro="n_samples"/> + <expand macro="n_features" default_value="20"/> + <param argument="n_informative" type="integer" optional="true" value="2" label="Number of informative features" help="Each class is composed of a number of gaussian clusters each located around the vertices of a hypercube in a subspace of dimension n_informative. For each cluster, informative features are drawn independently from N(0, 1) and then randomly linearly combined within each cluster in order to add covariance. The clusters are then placed on the vertices of the hypercube. "/> + <param argument="n_redundant" type="integer" optional="true" value="2" label="Number of redundant features" help="These features are generated as random linear combinations of the informative features. "/> + <param argument="n_repeated" type="integer" optional="true" value="0" label="Number of duplicated features" help="These are drawn randomly from the informative and the redundant features. "/> + <param argument="n_classes" type="integer" optional="true" value="2" label="Number of classes" help="The number of classes (or labels) of the classification problem. "/> + <param argument="n_clusters_per_class" type="integer" optional="true" value="2" label="Number of clusters per class" help=" "/> + <!--param argument = weights--> + <param argument="flip_y" type="float" optional="true" value="0.01" label="Fraction of samples with randomly exchanged class labels" help=" "/> + <!--param argument = class_sep--> + <!--param argument = hypercube--> + <!--param argument = shift--> + <!--param argument = scale--> + <expand macro="shuffle" label="Shuffle the samples"/> + <expand macro="random_state"/> + </section> + </when> + <when value="make_gaussian_quantiles"> + <section name="options" title="Advanced Options" expanded="False"> + <!--param argument = mean--> + <expand macro="n_samples"/> + <expand macro="n_features"/> + <param argument="cov" type="float" optional="true" value="1" label="Unit matrix coefficient" help="The covariance matrix will be this value times the unit matrix. This dataset only produces symmetric normal distributions. "/> + <param argument="n_classes" type="integer" optional="true" value="2" label="Number of classes" help="The number of classes (or labels) of the classification problem. "/> + <expand macro="shuffle" label="Shuffle the samples"/> + <expand macro="random_state"/> + </section> + </when> + <when value="make_hastie_10_2"> + <section name="options" title="Advanced Options" expanded="False"> + <expand macro="n_samples" default_value="12000"/> + <expand macro="random_state"/> + </section> + </when> + <when value="make_circles"> + <section name="options" title="Advanced Options" expanded="False"> + <expand macro="n_samples"/> + <expand macro="shuffle" label="Shuffle the samples"/> + <expand macro="noise" default_value=""/> + <param argument="factor" type="float" optional="true" value="0.8" label="Scale factor between inner and outer circle" help=" Floating point number less than 1. "/> + <expand macro="random_state"/> + </section> + </when> + <when value="make_moons"> + <section name="options" title="Advanced Options" expanded="False"> + <expand macro="n_samples"/> + <expand macro="shuffle" label="Shuffle the samples"/> + <expand macro="noise" default_value=""/> + <expand macro="random_state"/> + </section> + </when> + <when value="make_regression"> + <section name="options" title="Advanced Options" expanded="False"> + <expand macro="n_samples"/> + <expand macro="n_features" default_value="100"/> + <param argument="n_informative" type="integer" optional="true" value="10" label="Number of informative features" help="the number of features used to build the linear model used to generate the output "/> + <param argument="n_targets" type="integer" optional="true" value="1" label="Number of regression targets" help="The dimension of the y output vector associated with a sample. By default, the output is a scalar."/> + <param argument="bias" type="float" optional="true" value="0.0" label="Bias of the true function" help="The bias term in the underlying linear model. "/> + <!--param argument = effective_rank--> + <!--param argument = tail_strength--> + <!--param argument = coef--> + <expand macro="noise"/> + <expand macro="random_state"/> + </section> + </when> + <when value="make_sparse_uncorrelated"> + <section name="options" title="Advanced Options" expanded="False"> + <expand macro="n_samples"/> + <expand macro="n_features" default_value="10"/> + <expand macro="random_state"/> + </section> + </when> + <when value="make_friedman1"> + <section name="options" title="Advanced Options" expanded="False"> + <expand macro="n_samples"/> + <expand macro="n_features" default_value="10"/> + <expand macro="noise"/> + <expand macro="random_state"/> + </section> + </when> + <when value="make_friedman2"> + <section name="options" title="Advanced Options" expanded="False"> + <expand macro="n_samples"/> + <expand macro="noise"/> + <expand macro="random_state"/> + </section> + </when> + <when value="make_friedman3"> + <section name="options" title="Advanced Options" expanded="False"> + <expand macro="n_samples"/> + <expand macro="noise"/> + <expand macro="random_state"/> + </section> + </when> + <!--when value="make_low_rank_matrix"> + <section name="options" title="Advanced Options" expanded="False"> + <expand macro="n_samples"/> + <expand macro="n_features" default_value="100"/> + <expand macro="random_state"/> + </section> + </when--> + <!--when value="make_multilabel_classification"> + <section name="options" title="Advanced Options" expanded="False"> + <expand macro="n_samples"/> + <expand macro="n_features" default_value="20"/> + <expand macro="random_state"/> + </section> + </when--> + <when value="make_s_curve"> + <section name="options" title="Advanced Options" expanded="False"> + <expand macro="n_samples"/> + <expand macro="noise"/> + <expand macro="random_state"/> + </section> + </when> + <when value="make_swiss_roll"> + <section name="options" title="Advanced Options" expanded="False"> + <expand macro="n_samples"/> + <expand macro="noise"/> + <expand macro="random_state"/> + </section> + </when> + <!--when value="make_sparse_coded_signal"> + <section name="options" title="Advanced Options" expanded="False"> + <expand macro="n_samples" default_value=""/> + <expand macro="n_features" default_value=""/> + <expand macro="random_state"/> + </section> + </when--> + <!--when value="make_spd_matrix"> + <section name="options" title="Advanced Options" expanded="False"> + <expand macro="random_state"/> + </section> + </when--> + <!--when value="make_sparse_spd_matrix"> + <section name="options" title="Advanced Options" expanded="False"> + <expand macro="random_state"/> + </section> + </when--> + <!--when value="make_biclusters"> + <section name="options" title="Advanced Options" expanded="False"> + <expand macro="shuffle" label="Shuffle the samples"/> + <expand macro="noise"/> + <expand macro="random_state"/> + </section> + </when> + <when value="make_checkerboard"> + <section name="options" title="Advanced Options" expanded="False"> + <expand macro="shuffle" label="Shuffle the samples"/> + <expand macro="noise"/> + <expand macro="random_state"/> + </section> + </when--> + </conditional> + </inputs> + <outputs> + <data format="tabular" name="outfile"/> + </outputs> + <tests> + <test> + <param name="selected_generator" value="make_blobs"/> + <param name="random_state" value="100"/> + <output name="outfile" file="blobs.txt"/> + </test> + <test> + <param name="selected_generator" value="make_classification"/> + <param name="random_state" value="100"/> + <output name="outfile" file="class.txt"/> + </test> + <test> + <param name="selected_generator" value="make_circles"/> + <param name="random_state" value="100"/> + <output name="outfile" file="circles.txt"/> + </test> + <test> + <param name="selected_generator" value="make_friedman1"/> + <param name="random_state" value="100"/> + <output name="outfile" file="friedman1.txt"/> + </test> + <test> + <param name="selected_generator" value="make_friedman2"/> + <param name="random_state" value="100"/> + <output name="outfile" file="friedman2.txt"/> + </test> + <test> + <param name="selected_generator" value="make_friedman3"/> + <param name="random_state" value="100"/> + <output name="outfile" file="friedman3.txt"/> + </test> + <test> + <param name="selected_generator" value="make_gaussian_quantiles"/> + <param name="random_state" value="100"/> + <output name="outfile" file="gaus.txt"/> + </test> + <test> + <param name="selected_generator" value="make_hastie_10_2"/> + <param name="random_state" value="100"/> + <output name="outfile" file="hastie.txt" compare="contains"/> + </test> + <test> + <param name="selected_generator" value="make_moons"/> + <param name="random_state" value="100"/> + <output name="outfile" file="moons.txt"/> + </test> + <test> + <param name="selected_generator" value="make_regression"/> + <param name="random_state" value="100"/> + <output name="outfile" file="regression.txt"/> + </test> + <test> + <param name="selected_generator" value="make_s_curve"/> + <param name="random_state" value="100"/> + <output name="outfile" file="scurve.txt"/> + </test> + <test> + <param name="selected_generator" value="make_sparse_uncorrelated"/> + <param name="random_state" value="100"/> + <output name="outfile" file="sparse_u.txt"/> + </test> + <test> + <param name="selected_generator" value="make_swiss_roll"/> + <param name="random_state" value="100"/> + <output name="outfile" file="swiss_r.txt"/> + </test> + </tests> + <help> + <![CDATA[ +**What it does** + +This tool generates artificial data samples with specified size and controlled complexity. +It provides sample generators for the following machine learning problems: + + + +**1 - Single_label classification and clustering** + + These generators produce a file containing the data samples. It is a tabular representation with samples in rows having features in columns. + (In machine learning, each numerical property of a sample is called a feature.) + The corresponding discrete targets are generated in a separate column. This column is added as the last coulmn of the data. + + + **Example** + Sample data with 4 features and a single target (n_samples=8 , n_features=4) : + + + features columns + :: + + 4.01163365529 -6.10797684314 8.29829894763 -9.10139563721 + 10.0788438916 1.59539821454 10.0684278289 4.16975127881 + -5.17607775503 -0.878286135332 6.92941850665 -5.27083063186 + 4.00975406235 -7.11847496542 9.3802423585 -9.36732159584 + 4.61204065139 -5.71217537352 9.12509610964 -9.2260804162 + 8.26530668997 2.96705005011 8.88881190248 2.75339082289 + 2.96366327113 -3.76295851562 11.7113372463 -9.79136150321 + 8.13319631944 -0.223645298585 10.5820605308 4.47715318678 + + target column + :: + + 1 + 0 + 2 + 1 + 1 + 0 + 1 + 0 + + The following generators are included in this section: + + + * **Isotropic Gaussian blobs for clustering** creates multiclass datasets by allocating each class one or more normally-distributed clusters of points (isotropic = equally distributed in all directions). It provides control regarding the centers and standard deviations of each cluster, and is used to demonstrate clustering. + + * **Random n-class classification problem** does the same specialising in introducing noise by way of: correlated, redundant and uninformative features; multiple Gaussian clusters per class; and linear transformations of the feature space. + + * **Isotropic Gaussian and label samples by quantile** divides a single Gaussian cluster into near-equal-size classes separated by concentric hyperspheres. + + * **Data for binary classification (Hastie)** generates a binary problem similar to the above with 10 features. + + * **Circles** and **moons** generate 2-dimensional binary classification datasets that are challenging to certain algorithms (e.g. centroid-based clustering or linear classification), including optional Gaussian noise. They are useful for visualisation. + +**2 - Generators for regression** + + These generators produce output with same same format as in section 1, thoguh aimed for regression problems. The following generators are included in this section: + + * **Random regression problem** produces regression targets as an optionally-sparse random linear combination of random features, with noise. Its informative features may be uncorrelated, or low rank (few features account for most of the variance). It can produce multiple targets for each point. + + * **Random regression problem with sparse uncorrelated design** produces a target as a linear combination of four features with fixed coefficients. + + * **Nonlinear generators** encode explicitly non-linear relations: **“Friedman #1”** is related by polynomial and sine transforms; **“Friedman #2”** includes feature multiplication and reciprocation; and **“Friedman #3”** is similar with an arctan transformation on the target. + +**3 - Generators for manifold learning** + + Generators belonging to this group produce datasets suitable for non-linear dimensionality reduction problems. The idea behind this type of problem is that the dimensionality of many data sets is only artificially high. **S curve dataset** and **Swiss roll dataset** produce the same points-targets output format, sample points are 3-dimensional and the target column indicates the univariate position of the sample according to the main dimension of the points in the manifold. + + ]]> + </help> + <expand macro="sklearn_citation"/> +</tool>
--- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/test-data/RF01704.fasta Mon May 02 16:14:36 2016 -0400 @@ -0,0 +1,4 @@ +>CP000097.1/1411351-1411410 +CAACGUUCACCUCACAUUUGUGAGGCGCAGACAACCCAGGCCAAGGAACGGGGACCUGGA +>ACNY01000002.1/278641-278580 +GAUCGUUCACUUCGCAUCGCGCGAAGCGCAGUUCGCCUCAGGCCAUGGAACGGGGACCUGAG
--- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/test-data/blobs.txt Mon May 02 16:14:36 2016 -0400 @@ -0,0 +1,101 @@ +0 1 0 +0.336818458967 -3.40287961299 0 +-9.48324265576 -8.66266051537 2 +-1.93336328496 5.70953908147 1 +-10.0318240599 -5.57834393458 2 +0.541860776617 -4.37693628327 0 +-8.12962929067 -7.0555432055 2 +-0.730825785694 7.32375551699 1 +-1.84142532007 6.20630466831 1 +0.410071850317 -3.99744881 0 +-8.73509589323 -5.49090535209 2 +1.84941962277 -3.91839345673 0 +-9.15256068849 -9.17805648051 2 +-3.21429939078 5.75926163957 1 +0.284503785497 -3.61576522644 0 +-0.929074849223 5.79099955374 1 +0.366925241945 6.51861929623 1 +1.59909917965 -3.07105617298 0 +-9.71270568436 -7.91707651499 2 +-10.0804044306 -6.55135324109 2 +1.10594345774 -4.4190637495 0 +2.48708049649 -2.89100712361 0 +0.00587148930883 -3.1831425554 0 +1.61854359735 -4.88855922559 0 +-9.15856722108 -7.13894114848 2 +-3.0763357146 7.80049676786 1 +0.111746530225 -3.6161582871 0 +-9.43932350782 -7.29863034571 2 +-1.69466229591 4.40837111118 1 +1.05261752638 -3.49553009702 0 +-10.505605921 -5.99245086002 2 +1.54081964153 -4.53702344151 0 +0.322287896808 6.89854008043 1 +0.616219696606 -5.27504803638 0 +-10.2254539233 -8.71635918421 2 +-10.6100410759 -8.15999270542 2 +-0.745479667003 -2.96189843151 0 +0.788487589902 -5.32234377939 0 +-10.4200527675 -7.78467770434 2 +-2.90664752997 5.79835066176 1 +-10.321439212 -8.9271205211 2 +-0.213385598618 7.84779827248 1 +-0.0719473257255 -5.26054466249 0 +-7.60696893547 -7.73382713698 2 +-1.37722038387 6.91773657444 1 +-3.21560019076 7.26468660351 1 +-10.3615448954 -6.91944465708 2 +-9.60457341239 -9.25351754602 2 +-2.72690231566 6.73825747902 1 +-2.80603999217 6.99066208996 1 +-0.819526714793 7.58241271254 1 +-2.08847400981 5.6960714472 1 +-0.319918761498 -4.98235849166 0 +-11.320665797 -8.20937750735 2 +-7.96236061275 -9.01605369666 2 +2.16784691057 -6.16570792178 0 +1.89502027522 -5.86480290918 0 +-8.66871499099 -7.79890226276 2 +2.05772110385 -6.12322912451 0 +-9.31359960682 -8.00568199999 2 +-0.767430563562 -5.47682217583 0 +-3.46772941923 6.76072133441 1 +1.09049844437 -5.87582929335 0 +-0.11521126331 -4.07510454496 0 +1.08927850504 -5.50265562869 0 +-0.615050479257 7.65521576625 1 +0.429963213115 -5.55093054438 0 +-0.75919485469 5.58853030732 1 +-9.12599657252 -8.00673850069 2 +-9.77537442083 -6.61925671968 2 +-3.01723334528 7.0034067772 1 +-0.973089464367 -4.06651907196 0 +-0.488300213042 -5.66504681204 0 +-11.9208115933 -7.64815817127 2 +-9.38262507166 -7.5849629871 2 +0.0765227534059 7.58891330491 1 +0.976962303653 -3.92480270763 0 +-7.83082970823 -7.91191526652 2 +-3.0073685661 5.70163666961 1 +-1.87511017769 5.62449960555 1 +-9.68323206674 -8.25353931958 2 +-9.30119933759 -8.47564800182 2 +0.323659674147 -5.10078403494 0 +-1.74836105433 5.46645574795 1 +-0.560643408512 6.87612506044 1 +0.678603004996 -4.17761085385 0 +-8.20199888806 -8.29076835439 2 +-3.05026420957 8.94223661488 1 +-8.81193622652 -7.79813533758 2 +-9.16862770716 -7.13275033182 2 +-4.48296365907 6.92883992454 1 +-10.5222522479 -6.80543393828 2 +-1.58567165074 6.89948024039 1 +-1.75853685208 6.44534621139 1 +-9.91452153947 -8.11181559274 2 +-1.40077619512 6.92380628122 1 +-1.19228020908 6.14310846867 1 +0.875413399048 -5.0455510336 0 +1.48113771751 -3.6964070848 0 +0.524959376488 6.34480823448 1 +-0.0136995536637 -4.41397334864 0
--- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/test-data/circles.txt Mon May 02 16:14:36 2016 -0400 @@ -0,0 +1,101 @@ +0 1 0 +-0.0627905195293 -0.998026728428 0 +0.0502324156235 0.798421382743 1 +-0.992114701314 -0.125333233564 0 +0.425779291565 -0.904827052466 0 +-0.309016994375 -0.951056516295 0 +-1.0 -3.21624529935e-16 0 +-0.187381314586 -0.982287250729 0 +-0.535826794979 -0.844327925502 0 +-0.774866528903 -0.198951909732 1 +-0.876306680044 0.481753674102 0 +-0.2472135955 -0.760845213036 1 +0.8 0.0 1 +0.428661435983 -0.675462340402 1 +-0.583174901937 0.547637684743 1 +0.701045344035 -0.385402939281 1 +-0.743821188711 -0.294499642148 1 +-0.743821188711 0.294499642148 1 +0.809016994375 0.587785252292 0 +0.309016994375 -0.951056516295 0 +0.187381314586 0.982287250729 0 +-0.876306680044 -0.481753674102 0 +-0.428661435983 -0.675462340402 1 +-0.509939191799 -0.616410594221 1 +0.637423989749 -0.770513242776 0 +-0.929776485888 -0.368124552685 0 +-0.929776485888 0.368124552685 0 +-0.968583161129 0.248689887165 0 +0.2472135955 -0.760845213036 1 +-0.149905051669 -0.785829800583 1 +-0.809016994375 0.587785252292 0 +-0.637423989749 -0.770513242776 0 +0.728968627421 0.684547105929 0 +0.929776485888 0.368124552685 0 +0.0627905195293 0.998026728428 0 +0.793691761052 0.100266586851 1 +-0.340623433252 -0.723861641973 1 +-0.774866528903 0.198951909732 1 +-0.149905051669 0.785829800583 1 +0.701045344035 0.385402939281 1 +-0.509939191799 0.616410594221 1 +-0.8 -2.57299623948e-16 1 +-0.793691761052 0.100266586851 1 +0.509939191799 0.616410594221 1 +0.535826794979 -0.844327925502 0 +-0.793691761052 -0.100266586851 1 +0.793691761052 -0.100266586851 1 +-0.535826794979 0.844327925502 0 +0.509939191799 -0.616410594221 1 +-0.0502324156235 0.798421382743 1 +1.0 0.0 0 +-0.637423989749 0.770513242776 0 +0.728968627421 -0.684547105929 0 +0.0627905195293 -0.998026728428 0 +0.809016994375 -0.587785252292 0 +0.187381314586 -0.982287250729 0 +-0.6472135955 0.470228201834 1 +0.583174901937 -0.547637684743 1 +-0.809016994375 -0.587785252292 0 +-0.701045344035 0.385402939281 1 +0.876306680044 -0.481753674102 0 +0.583174901937 0.547637684743 1 +-0.6472135955 -0.470228201834 1 +0.340623433252 -0.723861641973 1 +0.0502324156235 -0.798421382743 1 +-0.728968627421 0.684547105929 0 +-0.583174901937 -0.547637684743 1 +0.6472135955 0.470228201834 1 +0.149905051669 -0.785829800583 1 +0.149905051669 0.785829800583 1 +-0.2472135955 0.760845213036 1 +0.929776485888 -0.368124552685 0 +0.992114701314 -0.125333233564 0 +0.637423989749 0.770513242776 0 +0.743821188711 -0.294499642148 1 +0.340623433252 0.723861641973 1 +0.6472135955 -0.470228201834 1 +-0.0627905195293 0.998026728428 0 +0.992114701314 0.125333233564 0 +-0.728968627421 -0.684547105929 0 +0.876306680044 0.481753674102 0 +-0.968583161129 -0.248689887165 0 +0.968583161129 0.248689887165 0 +0.425779291565 0.904827052466 0 +-0.425779291565 0.904827052466 0 +0.428661435983 0.675462340402 1 +0.2472135955 0.760845213036 1 +-0.309016994375 0.951056516295 0 +0.774866528903 -0.198951909732 1 +-0.425779291565 -0.904827052466 0 +-0.187381314586 0.982287250729 0 +-0.340623433252 0.723861641973 1 +0.743821188711 0.294499642148 1 +0.774866528903 0.198951909732 1 +0.309016994375 0.951056516295 0 +0.968583161129 -0.248689887165 0 +-0.701045344035 -0.385402939281 1 +-0.0502324156235 -0.798421382743 1 +-0.428661435983 0.675462340402 1 +-0.992114701314 0.125333233564 0 +0.535826794979 0.844327925502 0
--- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/test-data/class.txt Mon May 02 16:14:36 2016 -0400 @@ -0,0 +1,101 @@ +0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 0 +1.10393109848 1.11373246944 2.92966089343 0.826367847487 -0.502443930163 -0.977831171644 -0.670224226198 -0.37834187454 -1.91009113413 0.410808918987 1.63591387535 -0.354440178774 -0.777688394588 -0.711126068648 -1.16329587635 2.88152332359 -0.33316100166 1.02496354466 -1.20472252968 0.968602715198 1 +-0.527003420199 -2.43702669941 -0.463981262016 0.672496442533 0.321286938919 -1.45610559753 0.97337371093 1.26354483633 -0.965519031461 -0.304402845929 0.292832563572 -0.64248112675 -0.177782925174 -0.235750969868 0.770818433376 1.00249346092 0.444029462098 0.386733640203 -1.09097595301 0.43741724168 1 +0.634379093789 -0.704455703099 -1.54799256341 -1.13754239866 0.757499524423 -0.258689590472 1.21131850738 0.825559181467 1.04885507906 -0.0135579180305 -0.368245564128 -1.84223417403 0.979141336046 -0.23658235286 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--- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/test-data/cluster_result01.txt Mon May 02 16:14:36 2016 -0400 @@ -0,0 +1,48 @@ +0 44 64 -76 0 +0 51 48 -73 0 +0 58 65 -49 0 +0 43 61 -49 0 +0 45 43 -79 0 +0 42 60 -98 0 +0 50 55 -59 0 +0 53 53 -56 0 +0 45 44 -61 0 +0 43 65 -84 0 +0 35 52 -75 0 +0 56 56 -70 0 +1 -61 86 43 2 +1 -67 93 15 2 +1 -59 94 36 2 +1 -50 92 62 2 +1 -78 91 70 2 +1 -35 87 47 2 +1 -56 91 52 2 +1 -61 81 46 2 +1 -83 78 34 2 +1 -50 87 45 2 +1 -67 73 50 2 +1 -50 97 45 2 +1 -61 111 45 2 +2 -109 23 -92 1 +2 -94 20 -96 1 +2 -85 26 -88 1 +2 -90 33 -114 1 +2 -63 9 -106 1 +2 -79 9 -93 1 +2 -99 26 -108 1 +2 -81 19 -110 1 +2 -108 21 -108 1 +2 -92 27 -106 1 +2 -88 2 -106 1 +2 -88 15 -103 1 +3 54 -74 4 3 +3 42 -92 31 3 +3 39 -99 -7 3 +3 48 -115 -5 3 +3 39 -96 2 3 +3 31 -109 9 3 +3 33 -96 -8 3 +3 23 -102 4 3 +3 38 -90 21 3 +3 34 -107 1 3 +3 35 -78 18 3
--- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/test-data/cluster_result02.txt Mon May 02 16:14:36 2016 -0400 @@ -0,0 +1,48 @@ +0 44 64 -76 3 +0 51 48 -73 3 +0 58 65 -49 3 +0 43 61 -49 3 +0 45 43 -79 3 +0 42 60 -98 3 +0 50 55 -59 3 +0 53 53 -56 3 +0 45 44 -61 3 +0 43 65 -84 3 +0 35 52 -75 3 +0 56 56 -70 3 +1 -61 86 43 2 +1 -67 93 15 2 +1 -59 94 36 2 +1 -50 92 62 2 +1 -78 91 70 2 +1 -35 87 47 2 +1 -56 91 52 2 +1 -61 81 46 2 +1 -83 78 34 2 +1 -50 87 45 2 +1 -67 73 50 2 +1 -50 97 45 2 +1 -61 111 45 2 +2 -109 23 -92 0 +2 -94 20 -96 0 +2 -85 26 -88 0 +2 -90 33 -114 0 +2 -63 9 -106 0 +2 -79 9 -93 0 +2 -99 26 -108 0 +2 -81 19 -110 0 +2 -108 21 -108 0 +2 -92 27 -106 0 +2 -88 2 -106 0 +2 -88 15 -103 0 +3 54 -74 4 1 +3 42 -92 31 1 +3 39 -99 -7 1 +3 48 -115 -5 1 +3 39 -96 2 1 +3 31 -109 9 1 +3 33 -96 -8 1 +3 23 -102 4 1 +3 38 -90 21 1 +3 34 -107 1 1 +3 35 -78 18 1
--- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/test-data/cluster_result03.txt Mon May 02 16:14:36 2016 -0400 @@ -0,0 +1,48 @@ +0 44 64 -76 -1 +0 51 48 -73 -1 +0 58 65 -49 -1 +0 43 61 -49 -1 +0 45 43 -79 -1 +0 42 60 -98 -1 +0 50 55 -59 -1 +0 53 53 -56 -1 +0 45 44 -61 -1 +0 43 65 -84 -1 +0 35 52 -75 -1 +0 56 56 -70 -1 +1 -61 86 43 -1 +1 -67 93 15 -1 +1 -59 94 36 -1 +1 -50 92 62 -1 +1 -78 91 70 -1 +1 -35 87 47 -1 +1 -56 91 52 -1 +1 -61 81 46 -1 +1 -83 78 34 -1 +1 -50 87 45 -1 +1 -67 73 50 -1 +1 -50 97 45 -1 +1 -61 111 45 -1 +2 -109 23 -92 -1 +2 -94 20 -96 -1 +2 -85 26 -88 -1 +2 -90 33 -114 -1 +2 -63 9 -106 -1 +2 -79 9 -93 -1 +2 -99 26 -108 -1 +2 -81 19 -110 -1 +2 -108 21 -108 -1 +2 -92 27 -106 -1 +2 -88 2 -106 -1 +2 -88 15 -103 -1 +3 54 -74 4 -1 +3 42 -92 31 -1 +3 39 -99 -7 -1 +3 48 -115 -5 -1 +3 39 -96 2 -1 +3 31 -109 9 -1 +3 33 -96 -8 -1 +3 23 -102 4 -1 +3 38 -90 21 -1 +3 34 -107 1 -1 +3 35 -78 18 -1
--- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/test-data/cluster_result04.txt Mon May 02 16:14:36 2016 -0400 @@ -0,0 +1,48 @@ +0 44 64 -76 1 +0 51 48 -73 1 +0 58 65 -49 1 +0 43 61 -49 1 +0 45 43 -79 1 +0 42 60 -98 1 +0 50 55 -59 1 +0 53 53 -56 1 +0 45 44 -61 1 +0 43 65 -84 1 +0 35 52 -75 1 +0 56 56 -70 1 +1 -61 86 43 2 +1 -67 93 15 2 +1 -59 94 36 2 +1 -50 92 62 2 +1 -78 91 70 2 +1 -35 87 47 2 +1 -56 91 52 2 +1 -61 81 46 2 +1 -83 78 34 2 +1 -50 87 45 2 +1 -67 73 50 2 +1 -50 97 45 2 +1 -61 111 45 2 +2 -109 23 -92 3 +2 -94 20 -96 3 +2 -85 26 -88 3 +2 -90 33 -114 3 +2 -63 9 -106 3 +2 -79 9 -93 3 +2 -99 26 -108 3 +2 -81 19 -110 3 +2 -108 21 -108 3 +2 -92 27 -106 3 +2 -88 2 -106 3 +2 -88 15 -103 3 +3 54 -74 4 0 +3 42 -92 31 0 +3 39 -99 -7 0 +3 48 -115 -5 0 +3 39 -96 2 0 +3 31 -109 9 0 +3 33 -96 -8 0 +3 23 -102 4 0 +3 38 -90 21 0 +3 34 -107 1 0 +3 35 -78 18 0
--- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/test-data/cluster_result05.txt Mon May 02 16:14:36 2016 -0400 @@ -0,0 +1,48 @@ +0 44 64 -76 0 +0 51 48 -73 0 +0 58 65 -49 0 +0 43 61 -49 0 +0 45 43 -79 0 +0 42 60 -98 0 +0 50 55 -59 0 +0 53 53 -56 0 +0 45 44 -61 0 +0 43 65 -84 0 +0 35 52 -75 0 +0 56 56 -70 0 +1 -61 86 43 2 +1 -67 93 15 2 +1 -59 94 36 2 +1 -50 92 62 2 +1 -78 91 70 2 +1 -35 87 47 2 +1 -56 91 52 2 +1 -61 81 46 2 +1 -83 78 34 2 +1 -50 87 45 2 +1 -67 73 50 2 +1 -50 97 45 2 +1 -61 111 45 2 +2 -109 23 -92 0 +2 -94 20 -96 0 +2 -85 26 -88 0 +2 -90 33 -114 0 +2 -63 9 -106 0 +2 -79 9 -93 0 +2 -99 26 -108 0 +2 -81 19 -110 0 +2 -108 21 -108 0 +2 -92 27 -106 0 +2 -88 2 -106 0 +2 -88 15 -103 0 +3 54 -74 4 1 +3 42 -92 31 1 +3 39 -99 -7 1 +3 48 -115 -5 1 +3 39 -96 2 1 +3 31 -109 9 1 +3 33 -96 -8 1 +3 23 -102 4 1 +3 38 -90 21 1 +3 34 -107 1 1 +3 35 -78 18 1
--- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/test-data/cluster_result06.txt Mon May 02 16:14:36 2016 -0400 @@ -0,0 +1,48 @@ +0 44 64 -76 0 +0 51 48 -73 0 +0 58 65 -49 0 +0 43 61 -49 0 +0 45 43 -79 0 +0 42 60 -98 0 +0 50 55 -59 0 +0 53 53 -56 0 +0 45 44 -61 0 +0 43 65 -84 0 +0 35 52 -75 0 +0 56 56 -70 0 +1 -61 86 43 1 +1 -67 93 15 1 +1 -59 94 36 1 +1 -50 92 62 1 +1 -78 91 70 1 +1 -35 87 47 1 +1 -56 91 52 1 +1 -61 81 46 1 +1 -83 78 34 1 +1 -50 87 45 1 +1 -67 73 50 1 +1 -50 97 45 1 +1 -61 111 45 1 +2 -109 23 -92 2 +2 -94 20 -96 2 +2 -85 26 -88 2 +2 -90 33 -114 2 +2 -63 9 -106 2 +2 -79 9 -93 2 +2 -99 26 -108 2 +2 -81 19 -110 2 +2 -108 21 -108 2 +2 -92 27 -106 2 +2 -88 2 -106 2 +2 -88 15 -103 2 +3 54 -74 4 3 +3 42 -92 31 3 +3 39 -99 -7 3 +3 48 -115 -5 3 +3 39 -96 2 3 +3 31 -109 9 3 +3 33 -96 -8 3 +3 23 -102 4 3 +3 38 -90 21 3 +3 34 -107 1 3 +3 35 -78 18 3
--- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/test-data/cluster_result07.txt Mon May 02 16:14:36 2016 -0400 @@ -0,0 +1,48 @@ +0 44 64 -76 0 +0 51 48 -73 0 +0 58 65 -49 0 +0 43 61 -49 0 +0 45 43 -79 0 +0 42 60 -98 0 +0 50 55 -59 0 +0 53 53 -56 0 +0 45 44 -61 0 +0 43 65 -84 0 +0 35 52 -75 0 +0 56 56 -70 0 +1 -61 86 43 1 +1 -67 93 15 1 +1 -59 94 36 1 +1 -50 92 62 1 +1 -78 91 70 1 +1 -35 87 47 1 +1 -56 91 52 1 +1 -61 81 46 1 +1 -83 78 34 1 +1 -50 87 45 1 +1 -67 73 50 1 +1 -50 97 45 1 +1 -61 111 45 1 +2 -109 23 -92 2 +2 -94 20 -96 2 +2 -85 26 -88 2 +2 -90 33 -114 2 +2 -63 9 -106 2 +2 -79 9 -93 2 +2 -99 26 -108 2 +2 -81 19 -110 2 +2 -108 21 -108 2 +2 -92 27 -106 2 +2 -88 2 -106 2 +2 -88 15 -103 2 +3 54 -74 4 3 +3 42 -92 31 3 +3 39 -99 -7 3 +3 48 -115 -5 3 +3 39 -96 2 3 +3 31 -109 9 3 +3 33 -96 -8 3 +3 23 -102 4 3 +3 38 -90 21 3 +3 34 -107 1 3 +3 35 -78 18 3
--- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/test-data/cluster_result08.txt Mon May 02 16:14:36 2016 -0400 @@ -0,0 +1,48 @@ +0 44 64 -76 0 +0 51 48 -73 0 +0 58 65 -49 0 +0 43 61 -49 0 +0 45 43 -79 0 +0 42 60 -98 0 +0 50 55 -59 0 +0 53 53 -56 0 +0 45 44 -61 0 +0 43 65 -84 0 +0 35 52 -75 0 +0 56 56 -70 0 +1 -61 86 43 0 +1 -67 93 15 0 +1 -59 94 36 0 +1 -50 92 62 0 +1 -78 91 70 0 +1 -35 87 47 0 +1 -56 91 52 0 +1 -61 81 46 0 +1 -83 78 34 0 +1 -50 87 45 0 +1 -67 73 50 0 +1 -50 97 45 0 +1 -61 111 45 0 +2 -109 23 -92 0 +2 -94 20 -96 0 +2 -85 26 -88 0 +2 -90 33 -114 0 +2 -63 9 -106 0 +2 -79 9 -93 0 +2 -99 26 -108 0 +2 -81 19 -110 0 +2 -108 21 -108 0 +2 -92 27 -106 0 +2 -88 2 -106 0 +2 -88 15 -103 0 +3 54 -74 4 1 +3 42 -92 31 1 +3 39 -99 -7 1 +3 48 -115 -5 1 +3 39 -96 2 1 +3 31 -109 9 1 +3 33 -96 -8 1 +3 23 -102 4 1 +3 38 -90 21 1 +3 34 -107 1 1 +3 35 -78 18 1
--- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/test-data/cluster_result09.txt Mon May 02 16:14:36 2016 -0400 @@ -0,0 +1,48 @@ +0 44 64 -76 0 +0 51 48 -73 0 +0 58 65 -49 0 +0 43 61 -49 0 +0 45 43 -79 0 +0 42 60 -98 0 +0 50 55 -59 0 +0 53 53 -56 0 +0 45 44 -61 0 +0 43 65 -84 0 +0 35 52 -75 0 +0 56 56 -70 0 +1 -61 86 43 0 +1 -67 93 15 0 +1 -59 94 36 0 +1 -50 92 62 0 +1 -78 91 70 0 +1 -35 87 47 0 +1 -56 91 52 0 +1 -61 81 46 0 +1 -83 78 34 0 +1 -50 87 45 0 +1 -67 73 50 0 +1 -50 97 45 0 +1 -61 111 45 0 +2 -109 23 -92 0 +2 -94 20 -96 0 +2 -85 26 -88 0 +2 -90 33 -114 0 +2 -63 9 -106 0 +2 -79 9 -93 0 +2 -99 26 -108 0 +2 -81 19 -110 0 +2 -108 21 -108 0 +2 -92 27 -106 0 +2 -88 2 -106 0 +2 -88 15 -103 0 +3 54 -74 4 1 +3 42 -92 31 1 +3 39 -99 -7 1 +3 48 -115 -5 1 +3 39 -96 2 1 +3 31 -109 9 1 +3 33 -96 -8 1 +3 23 -102 4 1 +3 38 -90 21 1 +3 34 -107 1 1 +3 35 -78 18 1
--- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/test-data/cluster_result10.txt Mon May 02 16:14:36 2016 -0400 @@ -0,0 +1,48 @@ +0 44 64 -76 3 +0 51 48 -73 3 +0 58 65 -49 3 +0 43 61 -49 3 +0 45 43 -79 3 +0 42 60 -98 3 +0 50 55 -59 3 +0 53 53 -56 3 +0 45 44 -61 3 +0 43 65 -84 3 +0 35 52 -75 3 +0 56 56 -70 3 +1 -61 86 43 0 +1 -67 93 15 0 +1 -59 94 36 0 +1 -50 92 62 0 +1 -78 91 70 0 +1 -35 87 47 0 +1 -56 91 52 0 +1 -61 81 46 0 +1 -83 78 34 0 +1 -50 87 45 0 +1 -67 73 50 0 +1 -50 97 45 0 +1 -61 111 45 0 +2 -109 23 -92 2 +2 -94 20 -96 2 +2 -85 26 -88 2 +2 -90 33 -114 2 +2 -63 9 -106 2 +2 -79 9 -93 2 +2 -99 26 -108 2 +2 -81 19 -110 2 +2 -108 21 -108 2 +2 -92 27 -106 2 +2 -88 2 -106 2 +2 -88 15 -103 2 +3 54 -74 4 1 +3 42 -92 31 1 +3 39 -99 -7 1 +3 48 -115 -5 1 +3 39 -96 2 1 +3 31 -109 9 1 +3 33 -96 -8 1 +3 23 -102 4 1 +3 38 -90 21 1 +3 34 -107 1 1 +3 35 -78 18 1
--- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/test-data/cluster_result11.txt Mon May 02 16:14:36 2016 -0400 @@ -0,0 +1,48 @@ +0 44 64 -76 2 +0 51 48 -73 2 +0 58 65 -49 2 +0 43 61 -49 2 +0 45 43 -79 2 +0 42 60 -98 2 +0 50 55 -59 2 +0 53 53 -56 2 +0 45 44 -61 2 +0 43 65 -84 2 +0 35 52 -75 2 +0 56 56 -70 2 +1 -61 86 43 0 +1 -67 93 15 0 +1 -59 94 36 0 +1 -50 92 62 0 +1 -78 91 70 0 +1 -35 87 47 0 +1 -56 91 52 0 +1 -61 81 46 0 +1 -83 78 34 0 +1 -50 87 45 0 +1 -67 73 50 0 +1 -50 97 45 0 +1 -61 111 45 0 +2 -109 23 -92 1 +2 -94 20 -96 1 +2 -85 26 -88 1 +2 -90 33 -114 1 +2 -63 9 -106 1 +2 -79 9 -93 1 +2 -99 26 -108 1 +2 -81 19 -110 1 +2 -108 21 -108 1 +2 -92 27 -106 1 +2 -88 2 -106 1 +2 -88 15 -103 1 +3 54 -74 4 3 +3 42 -92 31 3 +3 39 -99 -7 3 +3 48 -115 -5 3 +3 39 -96 2 3 +3 31 -109 9 3 +3 33 -96 -8 3 +3 23 -102 4 3 +3 38 -90 21 3 +3 34 -107 1 3 +3 35 -78 18 3
--- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/test-data/cluster_result12.txt Mon May 02 16:14:36 2016 -0400 @@ -0,0 +1,48 @@ +0 44 64 -76 1 +0 51 48 -73 1 +0 58 65 -49 1 +0 43 61 -49 0 +0 45 43 -79 1 +0 42 60 -98 1 +0 50 55 -59 1 +0 53 53 -56 1 +0 45 44 -61 0 +0 43 65 -84 1 +0 35 52 -75 1 +0 56 56 -70 1 +1 -61 86 43 2 +1 -67 93 15 1 +1 -59 94 36 1 +1 -50 92 62 0 +1 -78 91 70 1 +1 -35 87 47 1 +1 -56 91 52 0 +1 -61 81 46 2 +1 -83 78 34 1 +1 -50 87 45 0 +1 -67 73 50 1 +1 -50 97 45 0 +1 -61 111 45 1 +2 -109 23 -92 0 +2 -94 20 -96 3 +2 -85 26 -88 3 +2 -90 33 -114 3 +2 -63 9 -106 0 +2 -79 9 -93 1 +2 -99 26 -108 3 +2 -81 19 -110 3 +2 -108 21 -108 3 +2 -92 27 -106 3 +2 -88 2 -106 0 +2 -88 15 -103 3 +3 54 -74 4 1 +3 42 -92 31 3 +3 39 -99 -7 3 +3 48 -115 -5 1 +3 39 -96 2 3 +3 31 -109 9 3 +3 33 -96 -8 3 +3 23 -102 4 3 +3 38 -90 21 3 +3 34 -107 1 3 +3 35 -78 18 3
--- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/test-data/cluster_result13.txt Mon May 02 16:14:36 2016 -0400 @@ -0,0 +1,48 @@ +0 44 64 -76 5 +0 51 48 -73 2 +0 58 65 -49 0 +0 43 61 -49 5 +0 45 43 -79 2 +0 42 60 -98 0 +0 50 55 -59 7 +0 53 53 -56 7 +0 45 44 -61 0 +0 43 65 -84 5 +0 35 52 -75 4 +0 56 56 -70 2 +1 -61 86 43 7 +1 -67 93 15 4 +1 -59 94 36 4 +1 -50 92 62 1 +1 -78 91 70 2 +1 -35 87 47 4 +1 -56 91 52 1 +1 -61 81 46 7 +1 -83 78 34 0 +1 -50 87 45 1 +1 -67 73 50 0 +1 -50 97 45 1 +1 -61 111 45 4 +2 -109 23 -92 4 +2 -94 20 -96 4 +2 -85 26 -88 4 +2 -90 33 -114 3 +2 -63 9 -106 0 +2 -79 9 -93 5 +2 -99 26 -108 3 +2 -81 19 -110 4 +2 -108 21 -108 3 +2 -92 27 -106 3 +2 -88 2 -106 4 +2 -88 15 -103 4 +3 54 -74 4 5 +3 42 -92 31 1 +3 39 -99 -7 4 +3 48 -115 -5 0 +3 39 -96 2 4 +3 31 -109 9 2 +3 33 -96 -8 4 +3 23 -102 4 2 +3 38 -90 21 1 +3 34 -107 1 2 +3 35 -78 18 1
--- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/test-data/cluster_result14.txt Mon May 02 16:14:36 2016 -0400 @@ -0,0 +1,48 @@ +0 44 64 -76 2 +0 51 48 -73 2 +0 58 65 -49 5 +0 43 61 -49 5 +0 45 43 -79 2 +0 42 60 -98 2 +0 50 55 -59 5 +0 53 53 -56 5 +0 45 44 -61 2 +0 43 65 -84 2 +0 35 52 -75 2 +0 56 56 -70 2 +1 -61 86 43 1 +1 -67 93 15 1 +1 -59 94 36 1 +1 -50 92 62 1 +1 -78 91 70 7 +1 -35 87 47 1 +1 -56 91 52 1 +1 -61 81 46 7 +1 -83 78 34 7 +1 -50 87 45 1 +1 -67 73 50 7 +1 -50 97 45 1 +1 -61 111 45 1 +2 -109 23 -92 6 +2 -94 20 -96 6 +2 -85 26 -88 6 +2 -90 33 -114 6 +2 -63 9 -106 3 +2 -79 9 -93 3 +2 -99 26 -108 6 +2 -81 19 -110 6 +2 -108 21 -108 6 +2 -92 27 -106 6 +2 -88 2 -106 3 +2 -88 15 -103 6 +3 54 -74 4 4 +3 42 -92 31 4 +3 39 -99 -7 0 +3 48 -115 -5 0 +3 39 -96 2 0 +3 31 -109 9 0 +3 33 -96 -8 0 +3 23 -102 4 0 +3 38 -90 21 4 +3 34 -107 1 0 +3 35 -78 18 4
--- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/test-data/cluster_result15.txt Mon May 02 16:14:36 2016 -0400 @@ -0,0 +1,48 @@ +0 44 64 -76 1 +0 51 48 -73 1 +0 58 65 -49 1 +0 43 61 -49 1 +0 45 43 -79 1 +0 42 60 -98 1 +0 50 55 -59 1 +0 53 53 -56 1 +0 45 44 -61 1 +0 43 65 -84 1 +0 35 52 -75 1 +0 56 56 -70 1 +1 -61 86 43 2 +1 -67 93 15 2 +1 -59 94 36 2 +1 -50 92 62 2 +1 -78 91 70 2 +1 -35 87 47 2 +1 -56 91 52 2 +1 -61 81 46 2 +1 -83 78 34 2 +1 -50 87 45 2 +1 -67 73 50 2 +1 -50 97 45 2 +1 -61 111 45 2 +2 -109 23 -92 3 +2 -94 20 -96 3 +2 -85 26 -88 3 +2 -90 33 -114 3 +2 -63 9 -106 3 +2 -79 9 -93 3 +2 -99 26 -108 3 +2 -81 19 -110 3 +2 -108 21 -108 3 +2 -92 27 -106 3 +2 -88 2 -106 3 +2 -88 15 -103 3 +3 54 -74 4 0 +3 42 -92 31 0 +3 39 -99 -7 0 +3 48 -115 -5 0 +3 39 -96 2 0 +3 31 -109 9 0 +3 33 -96 -8 0 +3 23 -102 4 0 +3 38 -90 21 0 +3 34 -107 1 0 +3 35 -78 18 0
--- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/test-data/cluster_result16.txt Mon May 02 16:14:36 2016 -0400 @@ -0,0 +1,48 @@ +0 44 64 -76 0 +0 51 48 -73 0 +0 58 65 -49 0 +0 43 61 -49 0 +0 45 43 -79 0 +0 42 60 -98 0 +0 50 55 -59 0 +0 53 53 -56 0 +0 45 44 -61 0 +0 43 65 -84 0 +0 35 52 -75 0 +0 56 56 -70 0 +1 -61 86 43 2 +1 -67 93 15 2 +1 -59 94 36 2 +1 -50 92 62 2 +1 -78 91 70 2 +1 -35 87 47 2 +1 -56 91 52 2 +1 -61 81 46 2 +1 -83 78 34 2 +1 -50 87 45 2 +1 -67 73 50 2 +1 -50 97 45 2 +1 -61 111 45 2 +2 -109 23 -92 3 +2 -94 20 -96 3 +2 -85 26 -88 3 +2 -90 33 -114 3 +2 -63 9 -106 3 +2 -79 9 -93 3 +2 -99 26 -108 3 +2 -81 19 -110 3 +2 -108 21 -108 3 +2 -92 27 -106 3 +2 -88 2 -106 3 +2 -88 15 -103 3 +3 54 -74 4 1 +3 42 -92 31 1 +3 39 -99 -7 1 +3 48 -115 -5 1 +3 39 -96 2 1 +3 31 -109 9 1 +3 33 -96 -8 1 +3 23 -102 4 1 +3 38 -90 21 1 +3 34 -107 1 1 +3 35 -78 18 1
--- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/test-data/cluster_result17.txt Mon May 02 16:14:36 2016 -0400 @@ -0,0 +1,4 @@ +0 +1 +0 +0
--- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/test-data/cluster_result18.txt Mon May 02 16:14:36 2016 -0400 @@ -0,0 +1,4 @@ +-1 +-1 +-1 +-1
--- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/test-data/cluster_result19.txt Mon May 02 16:14:36 2016 -0400 @@ -0,0 +1,4 @@ +0 +1 +0 +0
--- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/test-data/cluster_result20.txt Mon May 02 16:14:36 2016 -0400 @@ -0,0 +1,4 @@ +0 +1 +0 +0
--- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/test-data/cluster_result21.txt Mon May 02 16:14:36 2016 -0400 @@ -0,0 +1,4 @@ +0 +1 +0 +0
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--- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/test-data/csc_sparse1.mtx Mon May 02 16:14:36 2016 -0400 @@ -0,0 +1,9 @@ +%%MatrixMarket matrix coordinate integer general +% +3 3 6 +1 1 1 +3 1 2 +3 2 3 +1 3 4 +2 3 5 +3 3 6
--- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/test-data/csc_sparse2.mtx Mon May 02 16:14:36 2016 -0400 @@ -0,0 +1,9 @@ +%%MatrixMarket matrix coordinate real general +% +3 3 6 +1 1 1.5 +3 1 -2 +3 2 0.3 +1 3 41 +2 3 0.1235 +3 3 6
--- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/test-data/csc_stack_result01.mtx Mon May 02 16:14:36 2016 -0400 @@ -0,0 +1,15 @@ +%%MatrixMarket matrix coordinate real general +% +3 6 12 +1 1 1 +3 1 2 +3 2 3 +1 3 4 +2 3 5 +3 3 6 +1 4 1.5 +3 4 -2 +3 5 0.3 +1 6 41 +2 6 0.1235 +3 6 6
--- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/test-data/csr_sparse1.mtx Mon May 02 16:14:36 2016 -0400 @@ -0,0 +1,9 @@ +%%MatrixMarket matrix coordinate integer general +% +3 3 6 +1 1 1 +1 3 2 +2 3 3 +3 1 4 +3 2 5 +3 3 6
--- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/test-data/csr_sparse2.mtx Mon May 02 16:14:36 2016 -0400 @@ -0,0 +1,9 @@ +%%MatrixMarket matrix coordinate real general +% +3 3 6 +1 1 1 +1 3 -0.2 +2 3 11 +3 1 0.04 +3 2 -5 +3 3 2.6
--- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/test-data/csr_stack_result01.mtx Mon May 02 16:14:36 2016 -0400 @@ -0,0 +1,15 @@ +%%MatrixMarket matrix coordinate real general +% +6 3 12 +1 1 1 +1 3 2 +2 3 3 +3 1 4 +3 2 5 +3 3 6 +4 1 1 +4 3 -0.2 +5 3 11 +6 1 0.04 +6 2 -5 +6 3 2.6
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--- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/test-data/hastie.txt Mon May 02 16:14:36 2016 -0400 @@ -0,0 +1,20 @@ +0 1 2 3 4 5 6 7 8 9 0 +-1.74976547305 0.342680403328 1.15303580256 -0.252436036521 0.981320786951 0.514218841394 0.221179669221 -1.07004333057 -0.189495830823 0.255001444273 -1.0 +-0.458026985503 0.435163488123 -0.583595050323 0.816847071686 0.67272080571 -0.104411143391 -0.531280376852 1.02973268513 -0.438135622704 -1.11831824626 -1.0 +1.61898166068 1.54160517451 -0.251879139213 -0.842435738251 0.184518690564 0.937082201109 0.731000343835 1.36155612515 -0.326238059202 0.0556760148548 -1.0 +0.222399608555 -1.44321699523 -0.756352305594 0.816454011019 0.750444761534 -0.455946927468 1.18962226803 -1.69061682638 -1.35639904886 -1.23243451391 1.0 +-0.544439161672 -0.668171736813 0.0073145632289 -0.612938735478 1.29974807476 -1.73309562365 -0.98331009913 0.357507753167 -1.61357850282 1.47071386661 1.0 +-1.18801759732 -0.549746193535 -0.940046161545 -0.827932364366 0.108863467834 0.507809590492 -0.86222734651 1.24946974273 -0.0796112459174 -0.889731481265 -1.0 +-0.881798389483 0.0186389494881 0.237844621924 0.0135485486286 -1.63552939938 -1.04420987771 0.613038881688 0.736205213324 1.0269214394 -1.43219061106 -1.0 +-1.84118830019 0.366093226167 -0.331777135053 -0.68921797809 2.0346075615 -0.550714411915 0.750453330327 -1.30699233908 0.580573335794 -1.10452309266 1.0 +0.690121470225 0.686890066138 -1.56668752958 0.904974121467 0.778822399323 0.428232870597 0.108871989898 0.0282836348231 -0.578825824791 -1.19945119919 -1.0 +-1.70595200574 0.369163957107 1.87657342696 -0.376903350169 1.83193608183 0.00301743403121 -0.0760234657246 0.0039575939876 -0.185014110897 -2.48715153522 1.0 +-1.70465120576 -1.13626100683 -2.97331547405 0.0333172781389 -0.248888667058 -0.450176435012 0.132427801149 0.0222139280394 0.317367975941 -0.752414177725 1.0 +-1.29639180715 0.0951394435655 -0.423715099943 -1.18598356493 -0.365461992677 -1.27102304085 1.58617093842 0.693390658517 -1.95808123421 -0.13480131199 1.0 +-1.54061602455 2.04671396848 -1.39699934495 -1.09717198464 -0.238712869315 -1.42906689845 0.949004776505 -0.0193975859625 0.89459770576 0.75969311985 1.0 +-1.49772038108 -1.19388597679 1.2962625864 0.952275626082 -1.21725413064 -0.157265167375 -1.50758516026 0.107884130807 0.747055655099 0.429676435863 1.0 +-1.41504292085 -0.640759923011 0.779626303664 -0.438120916349 2.07479316795 -0.343297682182 -0.616629371683 0.76318364606 0.192917191823 -0.348458930652 -1.0 +2.29865394071 -0.165209552641 0.466299368357 0.269987238631 -0.319831047118 -1.14774159988 1.70362398812 -0.722150770056 1.09368664966 -0.22951775324 1.0 +-0.00889866329211 -0.543198008407 0.753062187692 -1.60943889617 1.94326226343 -1.44743611232 0.130248455353 0.949360864661 -2.01518871712 -0.0795405869341 1.0 +0.301049463788 -1.68489996169 0.222390809445 -0.684921735247 -0.126201183714 1.99027364975 0.522997804521 -0.0163454027575 -0.415816335841 -1.35850293676 1.0 +-0.514429891369 -0.216060120003 0.422380220422 -1.09404293103 1.23690788519 -0.230284678427 -0.704418199735 -0.591375121085 0.736995169018 0.435867252515 -1.0
--- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/test-data/lda_prediction_result01.tabular Mon May 02 16:14:36 2016 -0400 @@ -0,0 +1,5 @@ +3.68258022948 2.82110345641 -3.990140724 -1.9523364774 0 +0.015942057224 -0.711958594347 0.125502976978 -0.972218263337 0 +2.08690768825 0.929399321468 -2.12924084484 -1.99714022188 0 +1.41321052084 0.523750660422 -1.4210539291 -1.49298569451 0 +0.76831404394 1.38267855169 -0.989045048734 0.649504257894 1
--- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/test-data/lda_prediction_result02.tabular Mon May 02 16:14:36 2016 -0400 @@ -0,0 +1,5 @@ +3.68258022948 2.82110345641 -3.990140724 -1.9523364774 0 +0.015942057224 -0.711958594347 0.125502976978 -0.972218263337 0 +2.08690768825 0.929399321468 -2.12924084484 -1.99714022188 0 +1.41321052084 0.523750660422 -1.4210539291 -1.49298569451 0 +0.76831404394 1.38267855169 -0.989045048734 0.649504257894 1
--- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/test-data/moons.txt Mon May 02 16:14:36 2016 -0400 @@ -0,0 +1,101 @@ +0 1 0 +-0.718349350098 0.695682550603 0 +0.281650649902 -0.195682550603 1 +-0.0960230259077 0.995379112949 0 +-0.871318704123 0.490717552004 0 +-0.623489801859 0.781831482468 0 +-0.0320515775717 0.999486216201 0 +-0.672300890261 0.740277997075 0 +-0.518392568311 0.855142763005 0 +1.15959989503 -0.487181783414 1 +0.222520933956 0.974927912182 0 +1.62348980186 -0.281831482468 1 +0.0 0.5 1 +1.9009688679 0.0661162608824 1 +0.654634945579 -0.43846842205 1 +1.98155915699 0.308841371299 1 +1.22252093396 -0.474927912182 1 +0.840400104967 -0.487181783414 1 +0.949055747011 0.315108218024 0 +-0.838088104892 0.545534901211 0 +0.761445958369 0.648228395308 0 +-0.284527586631 0.958667853037 0 +1.51839256831 -0.355142763005 1 +1.46253829024 -0.386599306373 1 +-0.926916757346 0.375267004879 0 +-0.222520933956 0.974927912182 0 +0.159599895033 0.987181783414 0 +0.0960230259077 0.995379112949 0 +1.83808810489 -0.0455349012105 1 +1.67230089026 -0.240277997075 1 +0.284527586631 0.958667853037 0 +-0.462538290241 0.886599306373 0 +0.926916757346 0.375267004879 0 +0.981559156991 0.191158628701 0 +0.718349350098 0.695682550603 0 +0.00205460724966 0.435929780019 1 +1.57211666012 -0.320172254597 1 +0.903976974092 -0.495379112949 1 +0.376510198141 -0.281831482468 1 +0.032705136961 0.24634541609 1 +0.595216656878 -0.414412623016 1 +1.03205157757 -0.499486216201 1 +0.967948422428 -0.499486216201 1 +0.0990311320976 0.0661162608824 1 +-0.900968867902 0.433883739118 0 +1.09602302591 -0.495379112949 1 +2.0 0.5 1 +0.462538290241 0.886599306373 0 +1.92691675735 0.124732995121 1 +0.327699109739 -0.240277997075 1 +1.0 0.0 0 +0.404783343122 0.914412623016 0 +-0.949055747011 0.315108218024 0 +-0.761445958369 0.648228395308 0 +-0.967294863039 0.25365458391 0 +-0.801413621868 0.598110530491 0 +0.715472413369 -0.458667853037 1 +1.94905574701 0.184891781976 1 +-0.345365054421 0.93846842205 0 +0.777479066044 -0.474927912182 1 +-0.981559156991 0.191158628701 0 +0.073083242654 0.124732995121 1 +1.34536505442 -0.43846842205 1 +1.87131870412 0.00928244799606 1 +1.76144595837 -0.148228395308 1 +0.345365054421 0.93846842205 0 +1.40478334312 -0.414412623016 1 +0.0509442529893 0.184891781976 1 +1.80141362187 -0.0981105304912 1 +0.238554041631 -0.148228395308 1 +0.427883339878 -0.320172254597 1 +-0.991790013823 0.127877161685 0 +-1.0 1.22464679915e-16 0 +0.900968867902 0.433883739118 0 +1.99179001382 0.372122838315 1 +0.161911895108 -0.0455349012105 1 +1.96729486304 0.24634541609 1 +0.672300890261 0.740277997075 0 +0.99794539275 0.0640702199807 0 +-0.404783343122 0.914412623016 0 +0.967294863039 0.25365458391 0 +-0.159599895033 0.987181783414 0 +0.991790013823 0.127877161685 0 +0.838088104892 0.545534901211 0 +0.518392568311 0.855142763005 0 +0.128681295877 0.00928244799606 1 +0.198586378132 -0.0981105304912 1 +0.572116660122 0.820172254597 0 +1.99794539275 0.435929780019 1 +-0.572116660122 0.820172254597 0 +0.623489801859 0.781831482468 0 +0.481607431689 -0.355142763005 1 +0.0184408430089 0.308841371299 1 +0.00820998617675 0.372122838315 1 +0.801413621868 0.598110530491 0 +-0.99794539275 0.0640702199807 0 +1.28452758663 -0.458667853037 1 +1.7183493501 -0.195682550603 1 +0.537461709759 -0.386599306373 1 +0.0320515775717 0.999486216201 0 +0.871318704123 0.490717552004 0
--- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/test-data/nn_model01.txt Mon May 02 16:14:36 2016 -0400 @@ -0,0 +1,128 @@ +ccopy_reg +_reconstructor +p0 +(csklearn.neighbors.classification +KNeighborsClassifier +p1 +c__builtin__ +object +p2 +Ntp3 +Rp4 +(dp5 +S'n_neighbors' +p6 +I5 +sS'n_jobs' +p7 +I1 +sS'_y' +p8 +cnumpy.core.multiarray +_reconstruct +p9 +(cnumpy +ndarray +p10 +(I0 +tp11 +S'b' +p12 +tp13 +Rp14 +(I1 +(I48 +tp15 +cnumpy +dtype +p16 +(S'i8' +p17 +I0 +I1 +tp18 +Rp19 +(I3 +S'<' +p20 +NNNI-1 +I-1 +I0 +tp21 +bI00 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+p53 +tp54 +bsb. \ No newline at end of file
--- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/test-data/nn_model02.txt Mon May 02 16:14:36 2016 -0400 @@ -0,0 +1,302 @@ +ccopy_reg +_reconstructor +p0 +(csklearn.neighbors.classification +RadiusNeighborsClassifier +p1 +c__builtin__ +object +p2 +Ntp3 +Rp4 +(dp5 +S'n_neighbors' +p6 +NsS'n_jobs' +p7 +I1 +sS'_y' +p8 +cnumpy.core.multiarray +_reconstruct +p9 +(cnumpy +ndarray +p10 +(I0 +tp11 +S'b' +p12 +tp13 +Rp14 +(I1 +(I48 +tp15 +cnumpy +dtype +p16 +(S'i8' +p17 +I0 +I1 +tp18 +Rp19 +(I3 +S'<' +p20 +NNNI-1 +I-1 +I0 +tp21 +bI00 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0/\x00\x00\x00\x00\x00\x00\x004\x00\x00\x00\x00\x00\x00\x00.\x00\x00\x00\x00\x00\x00\x00"\x00\x00\x00\x00\x00\x00\x00-\x00\x00\x00\x00\x00\x00\x002\x00\x00\x00\x00\x00\x00\x00-\x00\x00\x00\x00\x00\x00\x00-\x00\x00\x00\x00\x00\x00\x00\xa4\xff\xff\xff\xff\xff\xff\xff\xa0\xff\xff\xff\xff\xff\xff\xff\xa8\xff\xff\xff\xff\xff\xff\xff\x8e\xff\xff\xff\xff\xff\xff\xff\x96\xff\xff\xff\xff\xff\xff\xff\xa3\xff\xff\xff\xff\xff\xff\xff\x94\xff\xff\xff\xff\xff\xff\xff\x92\xff\xff\xff\xff\xff\xff\xff\x94\xff\xff\xff\xff\xff\xff\xff\x96\xff\xff\xff\xff\xff\xff\xff\x96\xff\xff\xff\xff\xff\xff\xff\x99\xff\xff\xff\xff\xff\xff\xff\x04\x00\x00\x00\x00\x00\x00\x00\x1f\x00\x00\x00\x00\x00\x00\x00\xf9\xff\xff\xff\xff\xff\xff\xff\xfb\xff\xff\xff\xff\xff\xff\xff\x02\x00\x00\x00\x00\x00\x00\x00\t\x00\x00\x00\x00\x00\x00\x00\xf8\xff\xff\xff\xff\xff\xff\xff\x04\x00\x00\x00\x00\x00\x00\x00\x15\x00\x00\x00\x00\x00\x00\x00\x01\x00\x00\x00\x00\x00\x00\x00\x12\x00\x00\x00\x00\x00\x00\x00' +p120 +tp121 +bsb. \ No newline at end of file
--- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/test-data/nn_model03.txt Mon May 02 16:14:36 2016 -0400 @@ -0,0 +1,87 @@ +ccopy_reg +_reconstructor +p0 +(csklearn.neighbors.nearest_centroid +NearestCentroid +p1 +c__builtin__ +object +p2 +Ntp3 +Rp4 +(dp5 +S'centroids_' +p6 +cnumpy.core.multiarray +_reconstruct +p7 +(cnumpy +ndarray +p8 +(I0 +tp9 +S'b' +p10 +tp11 +Rp12 +(I1 +(I4 +I4 +tp13 +cnumpy +dtype +p14 +(S'f8' +p15 +I0 +I1 +tp16 +Rp17 +(I3 +S'<' +p18 +NNNI-1 +I-1 +I0 +tp19 +bI00 +S'\x00\x00\x00\x00\x00\x00\x00\x00\xab\xaa\xaa\xaa\xaa\x8aG@\x00\x00\x00\x00\x00\xc0K@UUUUUEQ\xc0\x00\x00\x00\x00\x00\x00\x00@\xab\xaa\xaa\xaa\xaajV\xc0\xab\xaa\xaa\xaa\xaa*3@\x00\x00\x00\x00\x00\xa0Y\xc0\x00\x00\x00\x00\x00\x00\xf0?\xc5N\xec\xc4N\xecM\xc0;\xb1\x13;\xb1SV@\x14;\xb1\x13;\xb1F@\x00\x00\x00\x00\x00\x00\x08@\xe9\xa2\x8b.\xba\xe8B@\x8c.\xba\xe8\xa2\x0bX\xc0t\xd1E\x17]t\x19@' +p20 +tp21 +bsS'metric' +p22 +Veuclidean +p23 +sS'classes_' +p24 +g7 +(g8 +(I0 +tp25 +g10 +tp26 +Rp27 +(I1 +(I4 +tp28 +g14 +(S'i8' +p29 +I0 +I1 +tp30 +Rp31 +(I3 +S'<' +p32 +NNNI-1 +I-1 +I0 +tp33 +bI00 +S'\x00\x00\x00\x00\x00\x00\x00\x00\x01\x00\x00\x00\x00\x00\x00\x00\x02\x00\x00\x00\x00\x00\x00\x00\x03\x00\x00\x00\x00\x00\x00\x00' +p34 +tp35 +bsS'shrink_threshold' +p36 +Nsb. \ No newline at end of file
--- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/test-data/nn_prediction_result01.tabular Mon May 02 16:14:36 2016 -0400 @@ -0,0 +1,49 @@ +0 58 56 -67 0 +0 44 64 -76 0 +0 51 48 -73 0 +0 58 65 -49 0 +0 43 61 -49 0 +0 45 43 -79 0 +0 42 60 -98 0 +0 50 55 -59 0 +0 53 53 -56 0 +0 45 44 -61 0 +0 43 65 -84 0 +0 35 52 -75 0 +0 56 56 -70 0 +1 -61 86 43 2 +1 -67 93 15 2 +1 -59 94 36 2 +1 -50 92 62 2 +1 -78 91 70 2 +1 -35 87 47 2 +1 -56 91 52 2 +1 -61 81 46 2 +1 -83 78 34 2 +1 -50 87 45 2 +1 -67 73 50 2 +1 -50 97 45 2 +1 -61 111 45 2 +2 -109 23 -92 1 +2 -94 20 -96 1 +2 -85 26 -88 1 +2 -90 33 -114 1 +2 -63 9 -106 1 +2 -79 9 -93 1 +2 -99 26 -108 1 +2 -81 19 -110 1 +2 -108 21 -108 1 +2 -92 27 -106 1 +2 -88 2 -106 1 +2 -88 15 -103 1 +3 54 -74 4 3 +3 42 -92 31 3 +3 39 -99 -7 3 +3 48 -115 -5 3 +3 39 -96 2 3 +3 31 -109 9 3 +3 33 -96 -8 3 +3 23 -102 4 3 +3 38 -90 21 3 +3 34 -107 1 3 +3 35 -78 18 3
--- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/test-data/nn_prediction_result02.tabular Mon May 02 16:14:36 2016 -0400 @@ -0,0 +1,49 @@ +0 58 56 -67 0 +0 44 64 -76 0 +0 51 48 -73 0 +0 58 65 -49 0 +0 43 61 -49 0 +0 45 43 -79 0 +0 42 60 -98 0 +0 50 55 -59 0 +0 53 53 -56 0 +0 45 44 -61 0 +0 43 65 -84 0 +0 35 52 -75 0 +0 56 56 -70 0 +1 -61 86 43 2 +1 -67 93 15 2 +1 -59 94 36 2 +1 -50 92 62 2 +1 -78 91 70 2 +1 -35 87 47 2 +1 -56 91 52 2 +1 -61 81 46 2 +1 -83 78 34 2 +1 -50 87 45 2 +1 -67 73 50 2 +1 -50 97 45 2 +1 -61 111 45 2 +2 -109 23 -92 1 +2 -94 20 -96 1 +2 -85 26 -88 1 +2 -90 33 -114 1 +2 -63 9 -106 1 +2 -79 9 -93 1 +2 -99 26 -108 1 +2 -81 19 -110 1 +2 -108 21 -108 1 +2 -92 27 -106 1 +2 -88 2 -106 1 +2 -88 15 -103 1 +3 54 -74 4 3 +3 42 -92 31 3 +3 39 -99 -7 3 +3 48 -115 -5 3 +3 39 -96 2 3 +3 31 -109 9 3 +3 33 -96 -8 3 +3 23 -102 4 3 +3 38 -90 21 3 +3 34 -107 1 3 +3 35 -78 18 3
--- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/test-data/nn_prediction_result03.tabular Mon May 02 16:14:36 2016 -0400 @@ -0,0 +1,49 @@ +0 58 56 -67 0 +0 44 64 -76 0 +0 51 48 -73 0 +0 58 65 -49 0 +0 43 61 -49 0 +0 45 43 -79 0 +0 42 60 -98 0 +0 50 55 -59 0 +0 53 53 -56 0 +0 45 44 -61 0 +0 43 65 -84 0 +0 35 52 -75 0 +0 56 56 -70 0 +1 -61 86 43 2 +1 -67 93 15 2 +1 -59 94 36 2 +1 -50 92 62 2 +1 -78 91 70 2 +1 -35 87 47 2 +1 -56 91 52 2 +1 -61 81 46 2 +1 -83 78 34 2 +1 -50 87 45 2 +1 -67 73 50 2 +1 -50 97 45 2 +1 -61 111 45 2 +2 -109 23 -92 1 +2 -94 20 -96 1 +2 -85 26 -88 1 +2 -90 33 -114 1 +2 -63 9 -106 1 +2 -79 9 -93 1 +2 -99 26 -108 1 +2 -81 19 -110 1 +2 -108 21 -108 1 +2 -92 27 -106 1 +2 -88 2 -106 1 +2 -88 15 -103 1 +3 54 -74 4 3 +3 42 -92 31 3 +3 39 -99 -7 3 +3 48 -115 -5 3 +3 39 -96 2 3 +3 31 -109 9 3 +3 33 -96 -8 3 +3 23 -102 4 3 +3 38 -90 21 3 +3 34 -107 1 3 +3 35 -78 18 3
--- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/test-data/numeric_values.tabular Mon May 02 16:14:36 2016 -0400 @@ -0,0 +1,49 @@ +0 58 56 -67 +0 44 64 -76 +0 51 48 -73 +0 58 65 -49 +0 43 61 -49 +0 45 43 -79 +0 42 60 -98 +0 50 55 -59 +0 53 53 -56 +0 45 44 -61 +0 43 65 -84 +0 35 52 -75 +0 56 56 -70 +1 -61 86 43 +1 -67 93 15 +1 -59 94 36 +1 -50 92 62 +1 -78 91 70 +1 -35 87 47 +1 -56 91 52 +1 -61 81 46 +1 -83 78 34 +1 -50 87 45 +1 -67 73 50 +1 -50 97 45 +1 -61 111 45 +2 -109 23 -92 +2 -94 20 -96 +2 -85 26 -88 +2 -90 33 -114 +2 -63 9 -106 +2 -79 9 -93 +2 -99 26 -108 +2 -81 19 -110 +2 -108 21 -108 +2 -92 27 -106 +2 -88 2 -106 +2 -88 15 -103 +3 54 -74 4 +3 42 -92 31 +3 39 -99 -7 +3 48 -115 -5 +3 39 -96 2 +3 31 -109 9 +3 33 -96 -8 +3 23 -102 4 +3 38 -90 21 +3 34 -107 1 +3 35 -78 18
--- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/test-data/qda_prediction_result01.tabular Mon May 02 16:14:36 2016 -0400 @@ -0,0 +1,5 @@ +3.68258022948 2.82110345641 -3.990140724 -1.9523364774 0 +0.015942057224 -0.711958594347 0.125502976978 -0.972218263337 0 +2.08690768825 0.929399321468 -2.12924084484 -1.99714022188 0 +1.41321052084 0.523750660422 -1.4210539291 -1.49298569451 0 +0.76831404394 1.38267855169 -0.989045048734 0.649504257894 1
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--- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/test-data/svc_model01.txt Mon May 02 16:14:36 2016 -0400 @@ -0,0 +1,299 @@ +ccopy_reg +_reconstructor +p0 +(csklearn.svm.classes +SVC +p1 +c__builtin__ +object +p2 +Ntp3 +Rp4 +(dp5 +S'_impl' +p6 +S'c_svc' +p7 +sS'kernel' +p8 +S'rbf' +p9 +sS'verbose' +p10 +I00 +sS'probability' +p11 +I00 +sS'classes_' +p12 +cnumpy.core.multiarray +_reconstruct +p13 +(cnumpy +ndarray +p14 +(I0 +tp15 +S'b' +p16 +tp17 +Rp18 +(I1 +(I4 +tp19 +cnumpy +dtype +p20 +(S'i8' +p21 +I0 +I1 +tp22 +Rp23 +(I3 +S'<' +p24 +NNNI-1 +I-1 +I0 +tp25 +bI00 +S'\x00\x00\x00\x00\x00\x00\x00\x00\x01\x00\x00\x00\x00\x00\x00\x00\x02\x00\x00\x00\x00\x00\x00\x00\x03\x00\x00\x00\x00\x00\x00\x00' +p26 +tp27 +bsS'support_' +p28 +g13 +(g14 +(I0 +tp29 +g16 +tp30 +Rp31 +(I1 +(I48 +tp32 +g20 +(S'i4' +p33 +I0 +I1 +tp34 +Rp35 +(I3 +S'<' +p36 +NNNI-1 +I-1 +I0 +tp37 +bI00 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+S"\x05\xb6\x01\xbd\xd9\x10C\xbf'\xba\x1bxV\xaf\xb3\xbfl\x01\xfa7\x8f,\xb5?\xa6\xe7p\x80V\xaf\xb3\xbf\xc7\xd1\xe5\xd1QU\xb5?<2-\x0b]\xb0\xc3?" +p109 +tp110 +bsS'probB_' +p111 +g13 +(g14 +(I0 +tp112 +g16 +tp113 +Rp114 +(I1 +(I0 +tp115 +g47 +I00 +g60 +tp116 +bsS'cache_size' +p117 +I200 +sS'gamma' +p118 +S'auto' +p119 +sb. \ No newline at end of file
--- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/test-data/svc_model02.txt Mon May 02 16:14:36 2016 -0400 @@ -0,0 +1,299 @@ +ccopy_reg +_reconstructor +p0 +(csklearn.svm.classes +NuSVC +p1 +c__builtin__ +object +p2 +Ntp3 +Rp4 +(dp5 +S'_impl' +p6 +S'nu_svc' +p7 +sS'kernel' +p8 +S'rbf' +p9 +sS'verbose' +p10 +I00 +sS'probability' +p11 +I00 +sS'classes_' +p12 +cnumpy.core.multiarray +_reconstruct +p13 +(cnumpy +ndarray +p14 +(I0 +tp15 +S'b' +p16 +tp17 +Rp18 +(I1 +(I4 +tp19 +cnumpy +dtype +p20 +(S'i8' +p21 +I0 +I1 +tp22 +Rp23 +(I3 +S'<' +p24 +NNNI-1 +I-1 +I0 +tp25 +bI00 +S'\x00\x00\x00\x00\x00\x00\x00\x00\x01\x00\x00\x00\x00\x00\x00\x00\x02\x00\x00\x00\x00\x00\x00\x00\x03\x00\x00\x00\x00\x00\x00\x00' +p26 +tp27 +bsS'support_' +p28 +g13 +(g14 +(I0 +tp29 +g16 +tp30 +Rp31 +(I1 +(I48 +tp32 +g20 +(S'i4' +p33 +I0 +I1 +tp34 +Rp35 +(I3 +S'<' +p36 +NNNI-1 +I-1 +I0 +tp37 +bI00 +S'\x00\x00\x00\x00\x01\x00\x00\x00\x02\x00\x00\x00\x03\x00\x00\x00\x04\x00\x00\x00\x05\x00\x00\x00\x06\x00\x00\x00\x07\x00\x00\x00\x08\x00\x00\x00\t\x00\x00\x00\n\x00\x00\x00\x0b\x00\x00\x00\x19\x00\x00\x00\x1a\x00\x00\x00\x1b\x00\x00\x00\x1c\x00\x00\x00\x1d\x00\x00\x00\x1e\x00\x00\x00\x1f\x00\x00\x00 \x00\x00\x00!\x00\x00\x00"\x00\x00\x00#\x00\x00\x00$\x00\x00\x00\x0c\x00\x00\x00\r\x00\x00\x00\x0e\x00\x00\x00\x0f\x00\x00\x00\x10\x00\x00\x00\x11\x00\x00\x00\x12\x00\x00\x00\x13\x00\x00\x00\x14\x00\x00\x00\x15\x00\x00\x00\x16\x00\x00\x00\x17\x00\x00\x00\x18\x00\x00\x00%\x00\x00\x00&\x00\x00\x00\'\x00\x00\x00(\x00\x00\x00)\x00\x00\x00*\x00\x00\x00+\x00\x00\x00,\x00\x00\x00-\x00\x00\x00.\x00\x00\x00/\x00\x00\x00' +p38 +tp39 +bsS'dual_coef_' +p40 +g13 +(g14 +(I0 +tp41 +g16 +tp42 +Rp43 +(I1 +(I3 +I48 +tp44 +g20 +(S'f8' +p45 +I0 +I1 +tp46 +Rp47 +(I3 +S'<' +p48 +NNNI-1 +I-1 +I0 +tp49 +bI00 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--- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/test-data/svc_model03.txt Mon May 02 16:14:36 2016 -0400 @@ -0,0 +1,159 @@ +ccopy_reg +_reconstructor +p0 +(csklearn.svm.classes +LinearSVC +p1 +c__builtin__ +object +p2 +Ntp3 +Rp4 +(dp5 +S'loss' +p6 +Vsquared_hinge +p7 +sS'C' +p8 +F1.0 +sS'classes_' +p9 +cnumpy.core.multiarray +_reconstruct +p10 +(cnumpy +ndarray +p11 +(I0 +tp12 +S'b' +p13 +tp14 +Rp15 +(I1 +(I4 +tp16 +cnumpy +dtype +p17 +(S'i8' +p18 +I0 +I1 +tp19 +Rp20 +(I3 +S'<' +p21 +NNNI-1 +I-1 +I0 +tp22 +bI00 +S'\x00\x00\x00\x00\x00\x00\x00\x00\x01\x00\x00\x00\x00\x00\x00\x00\x02\x00\x00\x00\x00\x00\x00\x00\x03\x00\x00\x00\x00\x00\x00\x00' +p23 +tp24 +bsS'verbose' +p25 +I0 +sS'intercept_scaling' +p26 +F1.0 +sS'dual' +p27 +I01 +sS'fit_intercept' +p28 +I01 +sS'max_iter' +p29 +I1000 +sS'n_iter_' +p30 +cnumpy.core.multiarray +scalar +p31 +(g17 +(S'i4' +p32 +I0 +I1 +tp33 +Rp34 +(I3 +S'<' +p35 +NNNI-1 +I-1 +I0 +tp36 +bS'\xe8\x03\x00\x00' +p37 +tp38 +Rp39 +sS'penalty' +p40 +Vl2 +p41 +sS'multi_class' +p42 +Vovr +p43 +sS'random_state' +p44 +I5 +sS'tol' +p45 +F0.001 +sS'coef_' +p46 +g10 +(g11 +(I0 +tp47 +g13 +tp48 +Rp49 +(I1 +(I4 +I4 +tp50 +g17 +(S'f8' +p51 +I0 +I1 +tp52 +Rp53 +(I3 +S'<' +p54 +NNNI-1 +I-1 +I0 +tp55 +bI01 +S'@@\xae\xfaP\xc8\xd4\xbf\xe8\x9b\x9e\x13"\xd6\xdb\xbf\xba\xc8\xd0f\xd1\xb9`\xbf\xca\xa9\x1a\xa8\x93\xda&\xbfv\xa2{\x1d\n\x8e\x95?\x1a\xb3\xc3\x80`\x9fn\xbf\xa5E?\x1dKV\x88\xbf\xb4]v\x97t8f?~R\x8dH\xd4\x9c\x89?+\xe8\xb4\x8b\xe7N\x7f\xbf\xdef\x84\xc2\xaa\xbc\x8e?\xc7\x193\xe1OO\x90\xbf\xc6UW_\x17\xdd\x87\xbf\xed\xa5\x82\x11Xbh?\x9b5w\xe8\x7fR\x9d?\xff\x9fao\xeaB|?' +p56 +tp57 +bsS'intercept_' +p58 +g10 +(g11 +(I0 +tp59 +g13 +tp60 +Rp61 +(I1 +(I4 +tp62 +g53 +I00 +S'\x9e\x05)W2\xcf\xc3\xbf\x98\xa4\x94\x94\x06\xf1\xd1\xbf\x1b<a=\xfb\x89S\xbf[\x9e>\x89\xb1<4\xbf' +p63 +tp64 +bsS'class_weight' +p65 +Nsb. \ No newline at end of file
--- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/test-data/svc_prediction_result01.tabular Mon May 02 16:14:36 2016 -0400 @@ -0,0 +1,49 @@ +0 58 56 -67 0 +0 44 64 -76 0 +0 51 48 -73 0 +0 58 65 -49 0 +0 43 61 -49 0 +0 45 43 -79 0 +0 42 60 -98 0 +0 50 55 -59 0 +0 53 53 -56 0 +0 45 44 -61 0 +0 43 65 -84 0 +0 35 52 -75 0 +0 56 56 -70 0 +1 -61 86 43 2 +1 -67 93 15 2 +1 -59 94 36 2 +1 -50 92 62 2 +1 -78 91 70 2 +1 -35 87 47 2 +1 -56 91 52 2 +1 -61 81 46 2 +1 -83 78 34 2 +1 -50 87 45 2 +1 -67 73 50 2 +1 -50 97 45 2 +1 -61 111 45 2 +2 -109 23 -92 1 +2 -94 20 -96 1 +2 -85 26 -88 1 +2 -90 33 -114 1 +2 -63 9 -106 1 +2 -79 9 -93 1 +2 -99 26 -108 1 +2 -81 19 -110 1 +2 -108 21 -108 1 +2 -92 27 -106 1 +2 -88 2 -106 1 +2 -88 15 -103 1 +3 54 -74 4 3 +3 42 -92 31 3 +3 39 -99 -7 3 +3 48 -115 -5 3 +3 39 -96 2 3 +3 31 -109 9 3 +3 33 -96 -8 3 +3 23 -102 4 3 +3 38 -90 21 3 +3 34 -107 1 3 +3 35 -78 18 3
--- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/test-data/svc_prediction_result02.tabular Mon May 02 16:14:36 2016 -0400 @@ -0,0 +1,49 @@ +0 58 56 -67 0 +0 44 64 -76 0 +0 51 48 -73 0 +0 58 65 -49 0 +0 43 61 -49 0 +0 45 43 -79 0 +0 42 60 -98 0 +0 50 55 -59 0 +0 53 53 -56 0 +0 45 44 -61 0 +0 43 65 -84 0 +0 35 52 -75 0 +0 56 56 -70 0 +1 -61 86 43 2 +1 -67 93 15 2 +1 -59 94 36 2 +1 -50 92 62 2 +1 -78 91 70 2 +1 -35 87 47 2 +1 -56 91 52 2 +1 -61 81 46 2 +1 -83 78 34 2 +1 -50 87 45 2 +1 -67 73 50 2 +1 -50 97 45 2 +1 -61 111 45 2 +2 -109 23 -92 1 +2 -94 20 -96 1 +2 -85 26 -88 1 +2 -90 33 -114 1 +2 -63 9 -106 1 +2 -79 9 -93 1 +2 -99 26 -108 1 +2 -81 19 -110 1 +2 -108 21 -108 1 +2 -92 27 -106 1 +2 -88 2 -106 1 +2 -88 15 -103 1 +3 54 -74 4 3 +3 42 -92 31 3 +3 39 -99 -7 3 +3 48 -115 -5 3 +3 39 -96 2 3 +3 31 -109 9 3 +3 33 -96 -8 3 +3 23 -102 4 3 +3 38 -90 21 3 +3 34 -107 1 3 +3 35 -78 18 3
--- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/test-data/svc_prediction_result03.tabular Mon May 02 16:14:36 2016 -0400 @@ -0,0 +1,49 @@ +0 58 56 -67 0 +0 44 64 -76 0 +0 51 48 -73 0 +0 58 65 -49 0 +0 43 61 -49 0 +0 45 43 -79 0 +0 42 60 -98 0 +0 50 55 -59 0 +0 53 53 -56 0 +0 45 44 -61 0 +0 43 65 -84 0 +0 35 52 -75 0 +0 56 56 -70 0 +1 -61 86 43 2 +1 -67 93 15 2 +1 -59 94 36 2 +1 -50 92 62 2 +1 -78 91 70 2 +1 -35 87 47 2 +1 -56 91 52 2 +1 -61 81 46 2 +1 -83 78 34 2 +1 -50 87 45 2 +1 -67 73 50 2 +1 -50 97 45 2 +1 -61 111 45 2 +2 -109 23 -92 2 +2 -94 20 -96 3 +2 -85 26 -88 2 +2 -90 33 -114 0 +2 -63 9 -106 0 +2 -79 9 -93 3 +2 -99 26 -108 1 +2 -81 19 -110 0 +2 -108 21 -108 1 +2 -92 27 -106 0 +2 -88 2 -106 3 +2 -88 15 -103 3 +3 54 -74 4 3 +3 42 -92 31 3 +3 39 -99 -7 3 +3 48 -115 -5 3 +3 39 -96 2 3 +3 31 -109 9 3 +3 33 -96 -8 3 +3 23 -102 4 3 +3 38 -90 21 3 +3 34 -107 1 3 +3 35 -78 18 3
--- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/test-data/swiss_r.txt Mon May 02 16:14:36 2016 -0400 @@ -0,0 +1,101 @@ +0 1 2 0 +-9.02243256039 16.3440735244 -3.91158679019 9.83385989955 +3.63249892241 16.3715663708 6.37347946891 7.33595862597 +-6.59990374868 12.8168912174 5.68894891724 8.71337301364 +12.6005826994 6.48900731901 1.36421345798 12.6742164541 +0.211487814316 14.6524330578 -4.75215950419 4.75686315221 +5.33691943034 18.0519842103 -2.41562073899 5.85815095065 +0.424440090632 13.1317989129 -11.0258838101 11.0340501713 +12.4648244371 20.6305644218 -0.880263861039 12.4958678255 +5.76317738541 20.5065026673 -1.67200654934 6.00081823394 +-7.69903426446 3.50057675518 -6.58731737524 10.132515917 +11.2027859032 0.486740866046 6.81511168671 13.1129004913 +6.15412671259 3.37563551865 2.60836155376 6.68407253026 +6.35942079066 19.3934333304 1.1301790428 6.45906629951 +4.89011222064 20.0245468475 -2.99390399146 5.73381710909 +5.95327096921 4.43054679309 3.25076997787 6.78298906691 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--- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/test-data/test.tabular Mon May 02 16:14:36 2016 -0400 @@ -0,0 +1,5 @@ +3.68258022948 2.82110345641 -3.990140724 -1.9523364774 +0.015942057224 -0.711958594347 0.125502976978 -0.972218263337 +2.08690768825 0.929399321468 -2.12924084484 -1.99714022188 +1.41321052084 0.523750660422 -1.4210539291 -1.49298569451 +0.76831404394 1.38267855169 -0.989045048734 0.649504257894
--- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/test-data/test_set.tabular Mon May 02 16:14:36 2016 -0400 @@ -0,0 +1,49 @@ +0 58 56 -67 +0 44 64 -76 +0 51 48 -73 +0 58 65 -49 +0 43 61 -49 +0 45 43 -79 +0 42 60 -98 +0 50 55 -59 +0 53 53 -56 +0 45 44 -61 +0 43 65 -84 +0 35 52 -75 +0 56 56 -70 +1 -61 86 43 +1 -67 93 15 +1 -59 94 36 +1 -50 92 62 +1 -78 91 70 +1 -35 87 47 +1 -56 91 52 +1 -61 81 46 +1 -83 78 34 +1 -50 87 45 +1 -67 73 50 +1 -50 97 45 +1 -61 111 45 +2 -109 23 -92 +2 -94 20 -96 +2 -85 26 -88 +2 -90 33 -114 +2 -63 9 -106 +2 -79 9 -93 +2 -99 26 -108 +2 -81 19 -110 +2 -108 21 -108 +2 -92 27 -106 +2 -88 2 -106 +2 -88 15 -103 +3 54 -74 4 +3 42 -92 31 +3 39 -99 -7 +3 48 -115 -5 +3 39 -96 2 +3 31 -109 9 +3 33 -96 -8 +3 23 -102 4 +3 38 -90 21 +3 34 -107 1 +3 35 -78 18
--- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/test-data/train.tabular Mon May 02 16:14:36 2016 -0400 @@ -0,0 +1,15 @@ +-0.409899987374 -0.649450145317 0.510268556953 -0.229110484125 0 +-1.10383560019 0.0611191480175 1.01725565283 1.79193066057 0 +-0.41009731911 0.731046118333 0.238276079462 1.60843479815 1 +1.48390157074 2.30714564103 -1.83858336229 0.770904924566 1 +0.74006063964 1.38952620136 -0.96404935579 0.702401167325 1 +0.331307031883 1.10808437795 -0.527405721679 0.961279646112 1 +-1.4627878344 -0.343655746393 1.43177660405 1.80949467985 0 +-1.33544682955 -2.24827087098 1.6885444678 -0.922608257112 0 +-0.0417384245742 0.906486336146 -0.13980113811 1.27108242642 1 +-2.73189476502 -1.46239633785 2.83576394706 2.28732123255 0 +-0.300256196558 -0.305034204892 0.340123288396 0.0593443810367 0 +-0.523654501136 -0.426496596688 0.572385315213 0.243891110892 0 +-0.00757221265553 -0.254805682403 0.0572980350837 -0.327374762308 0 +-1.87242461384 -0.413385894664 1.82750303608 2.35149919802 1 +-0.168117705611 -0.811895938369 0.316838713275 -0.819986910541 0
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