# HG changeset patch # User bgruening # Date 1451691474 18000 # Node ID a3fd214e7555628dde407f4d5b0e7d655cf8e238 planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/numeric_clustering commit bafd56379ff227fb81f8cd61d708ebc39814da54 diff -r 000000000000 -r a3fd214e7555 Untitled.ipynb --- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/Untitled.ipynb Fri Jan 01 18:37:54 2016 -0500 @@ -0,0 +1,744 @@ +{ + "cells": [ + { + "cell_type": "code", + "execution_count": 29, + "metadata": { + "collapsed": false + }, + "outputs": [ + { + "data": { + "text/plain": [ + "KMeans(copy_x=True, init='k-means++', max_iter=300, n_clusters=8, n_init=10,\n", + " n_jobs=1, precompute_distances='auto', random_state=None, tol=0.0001,\n", + " verbose=0)" + ] + }, + "execution_count": 29, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "import sys\n", + "import json\n", + "import numpy as np\n", + "import sklearn.cluster\n", + "import pandas\n", + "\n", + "data = pandas.read_csv(\"/home/bag/projects/code/galaxytools/tools/numeric_clustering/test-data/numeric_values.tabular\", sep='\\t', header=0, index_col=None, parse_dates=True, encoding=None )\n", + "my_class = getattr(sklearn.cluster, \"KMeans\")\n", + "cluster_object = my_class()\n", + "\n", + "params = dict()\n", + "cluster_object.set_params(**params)\n" + ] + }, + { + "cell_type": "code", + "execution_count": 32, + "metadata": { + "collapsed": false + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "[0 0 0 0 0 0 0 0 0 0 0 0 3 3 3 3 3 3 3 3 3 3 3 3 3 1 1 1 1 1 1 1 1 1 1 1 1\n", + " 2 2 2 2 2 2 2 2 2 2 2] 48 48\n", + " 0\n", + "0 0\n", + "1 0\n", + "2 0\n", + "3 0\n", + "4 0\n", + "5 0\n", + "6 0\n", + "7 0\n", + "8 0\n", + "9 0\n", + "10 0\n", + "11 0\n", + "12 3\n", + "13 3\n", + "14 3\n", + "15 3\n", + "16 3\n", + "17 3\n", + "18 3\n", + "19 3\n", + "20 3\n", + "21 3\n", + "22 3\n", + "23 3\n", + "24 3\n", + "25 1\n", + "26 1\n", + "27 1\n", + "28 1\n", + "29 1\n", + "30 1\n", + "31 1\n", + "32 1\n", + "33 1\n", + "34 1\n", + "35 1\n", + "36 1\n", + "37 2\n", + "38 2\n", + "39 2\n", + "40 2\n", + "41 2\n", + "42 2\n", + "43 2\n", + "44 2\n", + "45 2\n", + "46 2\n", + "47 2\n" + ] + } + ], + "source": [ + "\n", + "if 4 >= 4:\n", + " data_matrix = data.values[:, 1-1:1]\n", + " #print data_matrix\n", + "else:\n", + " data_matrix = data.values\n", + "\n", + "prediction = cluster_object.fit_predict( data_matrix )\n", + "print prediction, len(prediction), len(data_matrix)\n", + "\n", + "pred = pandas.DataFrame(prediction)\n", + "print pred\n", + "\n", + "#data[len(data.columns)] = prediction\n", + "#data.to_csv(path_or_buf = \"foo.tab\", sep=\"\\t\")\n" + ] + }, + { + "cell_type": "code", + "execution_count": 34, + "metadata": { + "collapsed": false + }, + "outputs": [ + { + "data": { + "text/html": [ + "
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"source": [] + } + ], + "metadata": { + "kernelspec": { + "display_name": "Python 2", + "language": "python", + "name": "python2" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 2 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython2", + "version": "2.7.10" + } + }, + "nbformat": 4, + "nbformat_minor": 0 +} diff -r 000000000000 -r a3fd214e7555 foo.tab --- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/foo.tab Fri Jan 01 18:37:54 2016 -0500 @@ -0,0 +1,49 @@ + 0 58 56 -67 4 5 6 7 +0 0 44 64 -76 7 3 2 0 +1 0 51 48 -73 7 3 2 0 +2 0 58 65 -49 3 3 2 0 +3 0 43 61 -49 3 3 2 0 +4 0 45 43 -79 7 3 2 0 +5 0 42 60 -98 0 3 2 0 +6 0 50 55 -59 3 3 2 0 +7 0 53 53 -56 3 3 2 0 +8 0 45 44 -61 3 3 2 0 +9 0 43 65 -84 0 3 2 0 +10 0 35 52 -75 7 3 2 0 +11 0 56 56 -70 7 3 2 0 +12 1 -61 86 43 6 1 0 2 +13 1 -67 93 15 1 1 0 2 +14 1 -59 94 36 6 1 0 2 +15 1 -50 92 62 2 1 0 2 +16 1 -78 91 70 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+ + + + + + + + + + + + + + + + + + + echo "@VERSION@" + &2 + && + #import json + #set $params = dict() + #for $key, $value in $algorithm_options.items(): + #if not $key.startswith('__') and $key.strip() != 'selected_algorithm' and str($value).strip(): + #if str($value).strip() == 'false': + #set $value = False + #elif str($value).strip() == 'true': + #set $value = True + #else: + #try: + #set $val = float($value) + #try: + #set $value = int($value) + #except: + #set $value = float($value) + #end try + #except: + #set $value = str($value) + #end try + #end if + $params.update({str($key): $value}) + #end if + #end for + #set $json_string = json.dumps( $params ) + + python "$cluster_script" '$json_string' + +]]> + + + += $start_column: + data_matrix = data.values[:, $start_column-1:$end_column] +else: + data_matrix = data.values + +#else: +data_matrix = data.values +#end if +prediction = cluster_object.fit_predict( data_matrix ) +prediction_df = pandas.DataFrame(prediction) +res = pandas.concat([data, prediction_df], axis=1) +res.to_csv(path_or_buf = "$outfile", sep="\t", index=False) +]]> + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + @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} + } + + + diff -r 000000000000 -r a3fd214e7555 test-data/cluster_result01.txt --- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/test-data/cluster_result01.txt Fri Jan 01 18:37:54 2016 -0500 @@ -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 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