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planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/numeric_clustering commit bafd56379ff227fb81f8cd61d708ebc39814da54
author bgruening
date Fri, 01 Jan 2016 18:37:54 -0500
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a3fd214e7555 planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/numeric_clustering commit bafd56379ff227fb81f8cd61d708ebc39814da54
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1 <tool id="numeric_clustering" name="Numeric Clustering" version="@VERSION@">
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2 <description></description>
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3 <requirements>
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4 <requirement type="package" version="2.3.0">anaconda</requirement>
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5 </requirements>
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6 <stdio>
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7 <exit_code level="fatal" range="1:"/>
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8 </stdio>
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9 <macros>
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10 <token name="@VERSION@">0.9</token>
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11 <macro name="n_clusters" token_default_value="8">
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12 <param name="n_clusters" type="integer" optional="true" value="@DEFAULT_VALUE@" label="Number of clusters"
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13 help="default value is @DEFAULT_VALUE@ (--n_clusters)"/>
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14 </macro>
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15 <macro name="n_init">
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16 <param name="n_init" type="integer" optional="true" value="" label="Number of runs with different centroid seeds"/>
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17 </macro>
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18 <macro name="max_iter">
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19 <param name="max_iter" type="integer" optional="true" value="" label="Maximum number of iterations per single run"/>
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20 </macro>
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21 <macro name="random_state">
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22 <param name="random_state" type="integer" optional="true" value="" label="Initialize centers"/>
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23 </macro>
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24 <macro name="affinity">
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25 <param name="affinity" type="text" optional="true" value="" label="Affinity"/>
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26 </macro>
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27 <macro name="tol">
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28 <param name="tol" type="float" optional="true" value="" label="Relative tolerance"/>
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29 </macro>
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30 <macro name="init">
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31 <param name="init" type="select" label="Select initialization method">
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32 <option value="k-means++">k-means++</option>
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33 <option value="random">random</option>
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34 </param>
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35 </macro>
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36 </macros>
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37 <version_command>echo "@VERSION@"</version_command>
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38 <command><![CDATA[
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39 cat "$cluster_script" >&2
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40 &&
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41 #import json
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42 #set $params = dict()
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43 #for $key, $value in $algorithm_options.items():
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44 #if not $key.startswith('__') and $key.strip() != 'selected_algorithm' and str($value).strip():
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45 #if str($value).strip() == 'false':
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46 #set $value = False
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47 #elif str($value).strip() == 'true':
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48 #set $value = True
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49 #else:
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50 #try:
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51 #set $val = float($value)
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52 #try:
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53 #set $value = int($value)
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54 #except:
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55 #set $value = float($value)
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56 #end try
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57 #except:
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58 #set $value = str($value)
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59 #end try
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60 #end if
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61 $params.update({str($key): $value})
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62 #end if
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63 #end for
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64 #set $json_string = json.dumps( $params )
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65
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66 python "$cluster_script" '$json_string'
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67
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68 ]]>
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69 </command>
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70 <configfiles>
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71 <configfile name="cluster_script">
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72 <![CDATA[
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73 import sys
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74 import json
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75 import numpy as np
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76 import sklearn.cluster
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77 import pandas
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78
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79 data = pandas.read_csv("$infile", sep='\t', header=0, index_col=None, parse_dates=True, encoding=None, tupleize_cols=False )
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80 my_class = getattr(sklearn.cluster, "$algorithm_options.selected_algorithm")
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81 cluster_object = my_class()
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82
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83 params = json.loads( sys.argv[1] )
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84 cluster_object.set_params(**params)
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85 #if $end_column and $start_column:
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86
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87 if $end_column >= $start_column:
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88 data_matrix = data.values[:, $start_column-1:$end_column]
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89 else:
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90 data_matrix = data.values
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91
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92 #else:
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93 data_matrix = data.values
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94 #end if
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95 prediction = cluster_object.fit_predict( data_matrix )
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96 prediction_df = pandas.DataFrame(prediction)
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97 res = pandas.concat([data, prediction_df], axis=1)
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98 res.to_csv(path_or_buf = "$outfile", sep="\t", index=False)
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99 ]]>
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100 </configfile>
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101 </configfiles>
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102 <inputs>
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103 <param name="infile" type="data" format="tabular" label="Data file with numeric values" />
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104 <param name="start_column" type="data_column" data_ref="infile" optional="True" label="Clustering column from" />
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105 <param name="end_column" type="data_column" data_ref="infile" optional="True" label="to" />
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106 <conditional name="algorithm_options">
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107 <param name="selected_algorithm" type="select" label="Clustering Algorithm">
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108 <option value="KMeans">KMeans</option>
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109 <option value="DBSCAN">DBSCAN</option>
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110 <option value="Birch">Birch</option>
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111 <option value="MeanShift">MeanShift</option>
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112 <option value="AffinityPropagation">Affinity Propagation</option>
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113 <option value="AgglomerativeClustering">Agglomerative Clustering</option>
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114 <option value="SpectralClustering">Spectral Clustering</option>
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115 <option value="MiniBatchKMeans">Mini Batch KMeans</option>
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116 </param>
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117 <when value="KMeans">
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118 <expand macro="n_clusters" default_label="8"/>
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119 <expand macro="init"/>
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120 <expand macro="n_init"/>
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121 <expand macro="max_iter"/>
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122 <expand macro="tol"/>
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123 <param name="precompute_distances" type="text" optional="true" value="" label="Precompute distances"/>
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124 <expand macro="random_state"/>
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125 <param name="copy_x" type="boolean" optional="true" truevalue="--copy_x" falsevale="" label="Do not modify original data"/>
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126 </when>
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127 <when value="DBSCAN">
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128 <param name="eps" type="float" optional="true" value="0.5" label="Maximum neghborhood distance"/>
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129 <param name="min_samples" type="integer" optional="true" value="5" label="Core point minimum population"/>
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130 <param name="metric" type="text" optional="true" value="euclidean" label="Metric"/>
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131 <param name="algorithm" type="select" optional="true" value="auto" label="Pointwise distance algorithm">
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132 <option value="auto">auto</option>
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133 <option value="ball_tree">ball_tree</option>
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134 <option value="kd_tree">kd_tree</option>
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135 <option value="brute">brute</option>
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136 </param>
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137 <param name="leaf_size" type="integer" optional="true" value="30" label="Leaf size"/>
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138 </when>
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139 <when value="Birch">
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140 <param name="threshold" type="float" optional="true" value="0.5" label="Subcluster radius threshold"/>
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141 <param name="branching_factor" type="integer" optional="true" value="50" label="Maximum number of subclusters per branch"/>
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142 <expand macro="n_clusters" default_label="3" /> <!-- default to 3-->
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143 <!--param name="compute_labels" type="boolean" optional="true" truevalue="true" falsevale="false" label="Compute labels for each fit"/-->
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144 </when>
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145 <when value="AffinityPropagation">
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146 <param name="damping" type="float" optional="true" value="0.5" label="Damping factor"/>
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147 <expand macro="max_iter"/> <!--default to 200 -->
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148 <param name="convergence_iter" type="integer" optional="true" value="15" label="Number of iterations at each convergence step"/>
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149 <param name="copy" type="boolean" optional="true" truevalue="true" falsevale="false" label="Make a copy of input data"/>
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150 <!--param name="preference" type="text" optional="true" value="None" label="Array like shape (n_samples,)"/-->
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151 <expand macro="affinity"/> <!--default = euclidean-->
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152 </when>
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153 <when value="MeanShift">
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154 <param name="bandwidth" type="float" optional="true" value="" label="RBF kernel bandwidth"/>
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155 <!--param name="seeds" type="list" optional="true" value="None" label=""/-->
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156 <param name="bin_seeding" type="boolean" optional="true" truevalue="true" falsevale="false" label="Discretize initial kernel locations"/>
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157 <param name="min_bin_freq" type="integer" optional="true" value="1" label="Minimum number of seeds per bin"/>
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158 <param name="cluster_all" type="boolean" optional="true" truevalue="true" falsevale="false" label="Cluster all"/>
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159 </when>
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160 <when value="AgglomerativeClustering">
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161 <expand macro="n_clusters" default_label="2" /> <!-- deafault 2-->
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162 <expand macro="affinity"/> <!--default = euclidean-->
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163 <!--param name="memory" type="callable" optional="true" value="Memory(cachedir=None)" label="Caching path"/-->
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164 <!--param name="connectivity" type="list array-like or callable" optional="true" value="None" label="Connectivity matrix"/-->
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165 <param name="n_components" type="integer" optional="true" value="" label="Number of connected components"/>
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166 <!--param name="compute_full_tree" type="text or boolean" optional="true" value="auto" label=""/-->
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167 <param name="linkage" type="select" optional="true" value="ward" label="Linkage">
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168 <option value="ward">ward</option>
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169 <option value="complete">complete</option>
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170 <option value="average">average</option>
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171 </param>
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172 <!--param name="pooling_func" type="callable" optional="np.mean" value="None" label=""/-->
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173 </when>
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174 <when value="SpectralClustering">
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175 <expand macro="n_clusters" default_label="8" />
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176 <param name="eigen_solver" type="select" value="arpack" label="Eigenvalue decomposition strategy">
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177 <option value="arpack">arpack</option>
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178 <option value="lobpcg">lobpcg</option>
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179 <option value="amg">amg</option>
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180 </param>
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181 <expand macro="random_state"/>
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182 <!-- Todo: extend random_state type to int seed, RandomState instance, or None. -->
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183 <expand macro="n_init"/> <!-- default to 10-->
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184 <param name="gamma" type="float" optional="true" value="1.0" label="Kernel scaling factor"/>
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185 <expand macro="affinity"/> <!--default =rbf-->
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186 <param name="n_neighbors" type="integer" optional="true" value="10" label="Number of neighbors"/>
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187 <!--param name="eigen_tol" type="float" optional="true" value="0.0" label="arpack eigendecomposition stopping threshold"/-->
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188 <param name="assign_labels" type="select" optional="true" value="kmeans" label="Assign labels">
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189 <option value="kmeans">kmeans</option>
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190 <option value="discretize">discretize</option>
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191 </param>
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192 <param name="degree" type="integer" optional="true" value="3" label="Degree of the polynomial (polynomial kernel only)"/>
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193 <param name="coef0" type="integer" optional="true" value="1" label="Zero coefficient (polynomial and sigmoid kernels only)"/>
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194 <!--param name="kernel_params" type="dict" optional="true" value="None" label=""/-->
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195 </when>
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196 <when value="MiniBatchKMeans">
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197 <expand macro="n_clusters" default_label="8"/>
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198 <expand macro="init"/>
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199 <expand macro="n_init"/> <!-- default to 3-->
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200 <expand macro="max_iter"/> <!--default to 100-->
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201 <expand macro="tol"/> <!--default = 0.0-->
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202 <expand macro="random_state"/>
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203 <param name="batch_size" type="integer" optional="true" value="100" label="Mini batch size"/>
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204 <!--param name="compute_labels" type="boolean" optional="true" truevalue="true" falsevale="false" label="Compute labels for all data"/-->
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205 <param name="max_no_improvement" type="integer" optional="true" value="10" label="Maximum number of improvement attempts"/>
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206 <param name="init_size" type="integer" optional="true" value="" label="Number of random init samples"/>
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207 <param name="reassignment_ratio" type="float" optional="true" value="0.01" label="Re-assignment ratio"/>
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208 </when>
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209 </conditional>
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210 </inputs>
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211 <outputs>
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212 <data format_source="infile" name="outfile"/>
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213 </outputs>
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214 <tests>
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215 <test>
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216 <param name="infile" value="numeric_values.tabular" ftype="tabular"/>
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217 <param name="selected_algorithm" value="KMeans"/>
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218 <param name="start_column" value="2" />
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219 <param name="end_column" value="4" />
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220 <param name="n_clusters" value="4" />
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221 <param name="init" value="k-means++" />
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222 <param name="random_state" value="100"/>
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223 <output name="outfile" file="cluster_result01.txt"/>
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224 </test>
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225 <test>
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226 <param name="infile" value="numeric_values.tabular" ftype="tabular"/>
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227 <param name="selected_algorithm" value="KMeans"/>
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228 <param name="start_column" value="2" />
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229 <param name="end_column" value="4" />
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230 <param name="n_clusters" value="4" />
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231 <param name="init" value="random" />
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232 <param name="random_state" value="100"/>
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233 <output name="outfile" file="cluster_result02.txt"/>
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234 </test>
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235 <test>
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236 <param name="infile" value="numeric_values.tabular" ftype="tabular"/>
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237 <param name="selected_algorithm" value="DBSCAN"/>
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238 <param name="start_column" value="2" />
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239 <param name="end_column" value="4" />
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240 <param name="algorithm" value="kd_tree"/>
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241 <param name="leaf_size" value="10"/>
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242 <param name="eps" value="1.0"/>
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243 <output name="outfile" file="cluster_result03.txt"/>
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244 </test>
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245 <test>
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246 <param name="infile" value="numeric_values.tabular" ftype="tabular"/>
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247 <param name="selected_algorithm" value="Birch"/>
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248 <param name="start_column" value="2" />
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249 <param name="end_column" value="4" />
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250 <param name="n_clusters" value="4"/>
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251 <param name="threshold" value="0.008"/>
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252 <output name="outfile" file="cluster_result04.txt"/>
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253 </test>
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254 <test>
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255 <param name="infile" value="numeric_values.tabular" ftype="tabular"/>
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256 <param name="selected_algorithm" value="Birch"/>
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257 <param name="start_column" value="2" />
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258 <param name="end_column" value="4" />
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259 <param name="branching_factor" value="20"/>
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260 <output name="outfile" file="cluster_result05.txt"/>
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261 </test>
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262 <test>
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263 <param name="infile" value="numeric_values.tabular" ftype="tabular"/>
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264 <param name="selected_algorithm" value="AffinityPropagation"/>
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265 <param name="start_column" value="2" />
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266 <param name="end_column" value="4" />
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267 <param name="affinity" value="euclidean"/>
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268 <param name="copy" value="false"/>
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269 <output name="outfile" file="cluster_result06.txt"/>
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270 </test>
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271 <test>
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272 <param name="infile" value="numeric_values.tabular" ftype="tabular"/>
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273 <param name="selected_algorithm" value="AffinityPropagation"/>
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274 <param name="start_column" value="2" />
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275 <param name="end_column" value="4" />
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276 <param name="damping" value="0.8"/>
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277 <output name="outfile" file="cluster_result07.txt"/>
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278 </test>
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279 <test>
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280 <param name="infile" value="numeric_values.tabular" ftype="tabular"/>
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281 <param name="selected_algorithm" value="MeanShift"/>
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282 <param name="start_column" value="2" />
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283 <param name="end_column" value="4" />
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284 <param name="min_bin_freq" value="3"/>
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285 <output name="outfile" file="cluster_result08.txt"/>
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286 </test>
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287 <test>
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288 <param name="infile" value="numeric_values.tabular" ftype="tabular"/>
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289 <param name="selected_algorithm" value="MeanShift"/>
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290 <param name="start_column" value="2" />
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291 <param name="end_column" value="4" />
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292 <param name="cluster_all" value="False"/>
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293 <output name="outfile" file="cluster_result09.txt"/>
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294 </test>
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295 <test>
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296 <param name="infile" value="numeric_values.tabular" ftype="tabular"/>
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297 <param name="selected_algorithm" value="AgglomerativeClustering"/>
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298 <param name="start_column" value="2" />
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299 <param name="end_column" value="4" />
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300 <param name="affinity" value="euclidean"/>
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301 <param name="linkage" value="average"/>
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302 <param name="n_clusters" value="4"/>
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303 <output name="outfile" file="cluster_result10.txt"/>
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304 </test>
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305 <test>
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306 <param name="infile" value="numeric_values.tabular" ftype="tabular"/>
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307 <param name="selected_algorithm" value="AgglomerativeClustering"/>
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308 <param name="start_column" value="2" />
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309 <param name="end_column" value="4" />
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310 <param name="linkage" value="complete"/>
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311 <param name="n_clusters" value="4"/>
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312 <output name="outfile" file="cluster_result11.txt"/>
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313 </test>
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314 <test>
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315 <param name="infile" value="numeric_values.tabular" ftype="tabular"/>
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316 <param name="selected_algorithm" value="SpectralClustering"/>
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317 <param name="start_column" value="2" />
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318 <param name="end_column" value="4" />
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319 <param name="eigen_solver" value="arpack"/>
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320 <param name="n_neighbors" value="12"/>
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321 <param name="n_clusters" value="4"/>
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322 <param name="assign_labels" value="discretize"/>
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323 <param name="random_state" value="100"/>
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324 <output name="outfile" file="cluster_result12.txt"/>
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325 </test>
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326 <test>
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327 <param name="infile" value="numeric_values.tabular" ftype="tabular"/>
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328 <param name="selected_algorithm" value="SpectralClustering"/>
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329 <param name="start_column" value="2" />
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330 <param name="end_column" value="4" />
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331 <param name="assign_labels" value="discretize"/>
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332 <param name="random_state" value="100"/>
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333 <param name="degree" value="2"/>
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334 <output name="outfile" file="cluster_result13.txt"/>
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335 </test>
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336 <test>
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337 <param name="infile" value="numeric_values.tabular" ftype="tabular"/>
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338 <param name="selected_algorithm" value="MiniBatchKMeans"/>
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339 <param name="start_column" value="2" />
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340 <param name="end_column" value="4" />
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341 <param name="tol" value="0.5"/>
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342 <param name="random_state" value="100"/>
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343 <output name="outfile" file="cluster_result14.txt"/>
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344 </test>
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345 <test>
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346 <param name="infile" value="numeric_values.tabular" ftype="tabular"/>
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347 <param name="selected_algorithm" value="MiniBatchKMeans"/>
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348 <param name="n_init" value="5"/>
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349 <param name="start_column" value="2" />
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350 <param name="end_column" value="4" />
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351 <param name="batch_size" value="10"/>
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352 <param name="n_clusters" value="4"/>
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353 <param name="random_state" value="100"/>
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354 <param name="reassignment_ratio" value="1.0"/>
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355 <output name="outfile" file="cluster_result15.txt"/>
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356 </test>
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357 <test>
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358 <param name="infile" value="numeric_values.tabular" ftype="tabular"/>
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359 <param name="selected_algorithm" value="KMeans"/>
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360 <param name="start_column" value="1" />
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361 <param name="end_column" value="1" />
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362 <param name="n_clusters" value="4" />
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363 <param name="random_state" value="100"/>
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364 <output name="outfile" file="cluster_result16.txt"/>
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365 </test>
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366 </tests>
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367 <help><![CDATA[
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368 **What it does**
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369
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370 This clustering tool offers different clustering algorithms which are provided by
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371 scikit-learn to find similarities among samples and cluster the samples based on these similarities.
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372
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373 ]]></help>
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374 <citations>
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375 <citation type="bibtex">
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376 @article{scikit-learn,
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377 title={Scikit-learn: Machine Learning in {P}ython},
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378 author={Pedregosa, F. and Varoquaux, G. and Gramfort, A. and Michel, V.
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379 and Thirion, B. and Grisel, O. and Blondel, M. and Prettenhofer, P.
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380 and Weiss, R. and Dubourg, V. and Vanderplas, J. and Passos, A. and
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381 Cournapeau, D. and Brucher, M. and Perrot, M. and Duchesnay, E.},
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382 journal={Journal of Machine Learning Research},
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383 volume={12},
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384 pages={2825--2830},
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385 year={2011}
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386 url = {https://github.com/scikit-learn/scikit-learn}
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387 }
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388 </citation>
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389 </citations>
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390 </tool>