Mercurial > repos > bgruening > sklearn_pairwise_metrics
changeset 2:4bb3ebf82d6c draft
planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit a349cb4673231f12344e418513a08691925565d9
author | bgruening |
---|---|
date | Fri, 03 Jun 2016 13:57:12 -0400 |
parents | 887b1f85a4b6 |
children | f8cd85c496c9 |
files | main_macros.xml test-data/prp_model01 test-data/prp_model02 test-data/prp_model03 test-data/prp_model04 test-data/prp_model05 test-data/prp_model06 test-data/prp_model07 test-data/prp_model08 test-data/prp_model09 test-data/prp_result01 test-data/prp_result02 test-data/prp_result03 test-data/prp_result04 test-data/prp_result05 test-data/prp_result06 test-data/prp_result07 test-data/prp_result08 test-data/prp_result09 |
diffstat | 19 files changed, 159 insertions(+), 40 deletions(-) [+] |
line wrap: on
line diff
--- a/main_macros.xml Tue May 31 16:52:15 2016 -0400 +++ b/main_macros.xml Fri Jun 03 13:57:12 2016 -0400 @@ -10,7 +10,7 @@ <xml name="macro_stdio"> <stdio> - <exit_code range="1:" level="fatal" description="Error occurred. Please check Tool Standard Error" /> + <exit_code range="1:" level="fatal" description="Error occurred. Please check Tool Standard Error"/> </stdio> </xml> @@ -23,7 +23,7 @@ <option value="load">Load a model and predict</option> </param> <when value="load"> - <param name="infile_model" type="data" format="@MODEL@" label="Models" help="Select a model file." /> + <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"> @@ -37,7 +37,7 @@ </conditional> </when> <when value="train"> - <param name="infile_train" type="data" format="@TRAIN@" label="Training samples (tabular)" /> + <param name="infile_train" type="data" format="@TRAIN@" label="Training samples (tabular)"/> <conditional name="selected_algorithms"> <yield /> </conditional> @@ -52,7 +52,7 @@ <option value="load">Load a model and predict</option> </param> <when value="load"> - <param name="infile_model" type="data" format="@MODEL@" label="Models" help="Select a model file." /> + <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"> @@ -275,6 +275,10 @@ </conditional> </xml> + <xml name="multitype_input" token_format="tabular" token_help="All datasets with tabular format are supporetd."> + <param name="infile_transform" type="data" format="@FORMAT@" label="Select a dataset to transform:" help="@HELP@"/> + </xml> + <!--Advanced options--> <xml name="nn_advanced_options"> @@ -525,58 +529,64 @@ <xml name="sparse_preprocessors"> <param name="selected_pre_processor" type="select" label="Select a preprocessor:"> - <option value="StandardScaler" selected="true">Standardize features by removing the mean and scaling to unit variance</option> - <option value="Binarizer">Binarize data</option> - <option value="Imputer">Complete missing values</option> - <option value="MaxAbsScaler">Scale features by their maximum absolute value</option> - <option value="Normalizer">Normalize samples individually to unit norm</option> + <option value="StandardScaler" selected="true">Standard Scaler (Standardizes features by removing the mean and scaling to unit variance)</option> + <option value="Binarizer">Binarizer (Binarizes data)</option> + <option value="Imputer">Imputer (Completes missing values)</option> + <option value="MaxAbsScaler">Max Abs Scaler (Scales features by their maximum absolute value)</option> + <option value="Normalizer">Normalizer (Normalizes samples individually to unit norm)</option> <yield/> </param> </xml> <xml name="sparse_preprocessor_options"> <when value="Binarizer"> + <expand macro="multitype_input" format="tabular,txt" help="Tabular and sparse datasets are supporetd."/> <section name="options" title="Advanced Options" expanded="False"> - <param argument="copy" type="boolean" optional="true" truevalue="booltrue" falsevalue="boolflase" checked="true" label="Use a copy of data for precomputing binarization" help=" "/> - <param argument="threshold" type="float" optional="true" value="0.0" label="Threshold" help="Feature values below or equal to this are replaced by 0, above it by 1. Threshold may not be less than 0 for operations on sparse matrices. "/> + <param argument="copy" type="boolean" optional="true" truevalue="booltrue" falsevalue="boolflase" checked="true" label="Use a copy of data for precomputing binarization" help=" "/> + <param argument="threshold" type="float" optional="true" value="0.0" label="Threshold" help="Feature values below or equal to this are replaced by 0, above it by 1. Threshold may not be less than 0 for operations on sparse matrices. "/> </section> </when> <when value="Imputer"> - <section name="options" title="Advanced Options" expanded="False"> - <param argument="copy" type="boolean" optional="true" truevalue="booltrue" falsevalue="boolflase" checked="true" label="Use a copy of data for precomputing imputation" help=" "/> - <param argument="strategy" type="select" optional="true" label="Imputation strategy" help=" "> - <option value="mean" selected="true">Replace missing values using the mean along the axis</option> - <option value="median">Replace missing values using the median along the axis</option> - <option value="most_frequent">Replace missing using the most frequent value along the axis</option> - </param> - <param argument="missing_values" type="text" optional="true" value="NaN" label="Placeholder for missing values" help="For missing values encoded as numpy.nan, use the string value “NaN”"/> - <param argument="axis" type="select" optional="true" label="The axis along which to impute" help=" "> - <option value="0" selected="true">Impute along columns</option> - <option value="1">Impute along rows</option> - </param> - </section> + <expand macro="multitype_input" format="tabular,txt" help="Tabular and sparse datasets are supporetd."/> + <section name="options" title="Advanced Options" expanded="False"> + <param argument="copy" type="boolean" optional="true" truevalue="booltrue" falsevalue="boolflase" checked="true" label="Use a copy of data for precomputing imputation" help=" "/> + <param argument="strategy" type="select" optional="true" label="Imputation strategy" help=" "> + <option value="mean" selected="true">Replace missing values using the mean along the axis</option> + <option value="median">Replace missing values using the median along the axis</option> + <option value="most_frequent">Replace missing using the most frequent value along the axis</option> + </param> + <param argument="missing_values" type="text" optional="true" value="NaN" label="Placeholder for missing values" help="For missing values encoded as numpy.nan, use the string value “NaN”"/> + <param argument="axis" type="boolean" optional="true" truevalue="1" falsevalue="0" label="Impute along axis = 1" help="If fasle, axis = 0 is selected for imputation. "/> + <!--param argument="axis" type="select" optional="true" label="The axis along which to impute" help=" "> + <option value="0" selected="true">Impute along columns</option> + <option value="1">Impute along rows</option> + </param--> + </section> </when> <when value="StandardScaler"> - <section name="options" title="Advanced Options" expanded="False"> - <param argument="copy" type="boolean" optional="true" truevalue="booltrue" falsevalue="boolflase" checked="true" label="Use a copy of data for performing inplace scaling" help=" "/> - <param argument="with_mean" type="boolean" optional="true" truevalue="booltrue" falsevalue="boolflase" checked="true" label="Center the data before scaling" help=" "/> - <param argument="with_std" type="boolean" optional="true" truevalue="booltrue" falsevalue="boolflase" checked="true" label="Scale the data to unit variance (or unit standard deviation)" help=" "/> - </section> + <expand macro="multitype_input"/> + <section name="options" title="Advanced Options" expanded="False"> + <param argument="copy" type="boolean" optional="true" truevalue="booltrue" falsevalue="boolflase" checked="true" label="Use a copy of data for performing inplace scaling" help=" "/> + <param argument="with_mean" type="boolean" optional="true" truevalue="booltrue" falsevalue="boolflase" checked="true" label="Center the data before scaling" help=" "/> + <param argument="with_std" type="boolean" optional="true" truevalue="booltrue" falsevalue="boolflase" checked="true" label="Scale the data to unit variance (or unit standard deviation)" help=" "/> + </section> </when> <when value="MaxAbsScaler"> - <section name="options" title="Advanced Options" expanded="False"> - <param argument="copy" type="boolean" optional="true" truevalue="booltrue" falsevalue="boolflase" checked="true" label="Use a copy of data for precomputing scaling" help=" "/> - </section> + <expand macro="multitype_input" format="tabular,txt" help="Tabular and sparse datasets are supporetd."/> + <section name="options" title="Advanced Options" expanded="False"> + <param argument="copy" type="boolean" optional="true" truevalue="booltrue" falsevalue="boolflase" checked="true" label="Use a copy of data for precomputing scaling" help=" "/> + </section> </when> <when value="Normalizer"> - <section name="options" title="Advanced Options" expanded="False"> - <param argument="norm" type="select" optional="true" label="The norm to use to normalize non zero samples" help=" "> - <option value="l1" selected="true">l1</option> - <option value="l2">l2</option> - <option value="max">max</option> - <param argument="copy" type="boolean" optional="true" truevalue="booltrue" falsevalue="boolflase" checked="true" label="Use a copy of data for precomputing row normalization" help=" "/> - </param> - </section> + <expand macro="multitype_input" format="tabular,txt" help="Tabular and sparse datasets are supporetd."/> + <section name="options" title="Advanced Options" expanded="False"> + <param argument="norm" type="select" optional="true" label="The norm to use to normalize non zero samples" help=" "> + <option value="l1" selected="true">l1</option> + <option value="l2">l2</option> + <option value="max">max</option> + <param argument="copy" type="boolean" optional="true" truevalue="booltrue" falsevalue="boolflase" checked="true" label="Use a copy of data for precomputing row normalization" help=" "/> + </param> + </section> </when> <yield/> </xml>
--- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/test-data/prp_result01 Fri Jun 03 13:57:12 2016 -0400 @@ -0,0 +1,15 @@ +0.340792241503 -0.392122793309 0.249050728091 -0.769815625858 -0.170138220973 +-0.862075755531 -0.190485884192 0.24710543975 0.742293134619 -0.679070605191 +-0.448575437572 0.199203123002 -0.812112096739 0.278559309077 0.0406914316875 +1.33428163284 1.66416082626 -3.00011335793 -0.670112383949 -0.0704503877547 +0.761526726038 0.917627410889 -1.95449332713 -0.567530116888 0.100635636548 +0.351707781935 0.635120251133 -1.51891502937 -0.309716974447 0.0995703002013 +-1.15469955812 -0.528932346979 0.727954822594 0.826185585523 -0.612742173567 +-0.176836714677 -1.58302563298 1.83524452493 -1.05539551285 0.237779665023 +-0.0458904476457 0.408969436205 -1.15586321892 -0.0244669672622 0.0750175270781 +-2.32259976346 -1.54646621316 2.23314889088 1.4052188635 -0.511535448293 +0.33596216675 -0.162180718453 -0.0355684060349 -0.595834626266 -0.284612086542 +0.0981742501127 -0.298032722308 0.182304008722 -0.42567750847 -0.299001698602 +0.693972528706 -0.0466258179106 -0.253067281294 -0.917227391557 -0.219285708489 +-1.85600914205 -0.890335299747 0.832008450126 1.07651729919 0.0955850219353 +0.723568479543 -0.413574630084 0.19661484069 -1.219698096 -0.0291442646963
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--- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/test-data/prp_result04 Fri Jun 03 13:57:12 2016 -0400 @@ -0,0 +1,15 @@ +0.0 -0.253855596808 0.134420613871 -0.560212076994 0.0 +-0.580706111253 0.269877398274 0.534957856136 0.571982134735 0.0 +-0.000165133108783 0.763654517468 -0.0804627978317 0.469187120466 1.0 +1.5847898825 1.9253361878 -1.72125318508 0.0 1.0 +0.962321505733 1.24899458116 -1.03034124258 -0.0383760408013 1.0 +0.620264240423 1.04155475721 -0.685377754397 0.106648574849 1.0 +-0.881088095119 -0.028466436412 0.862443663986 0.581821558844 0.0 +-0.774525327099 -1.43228418232 1.06529910722 -0.948711918516 0.0 +0.308088625944 0.89296467989 -0.379156802711 0.280201159646 1.0 +-1.94311479736 -0.853046623285 1.97164195151 0.849501639775 0.0 +0.0917532091045 0.0 0.0 -0.398618667806 0.0 +-0.0951931852238 -0.0895252058342 0.183494989243 -0.295234953979 0.0 +0.336679935704 0.0370214907519 -0.223441677167 -0.615260064152 0.0 +-1.22388442495 -0.079861817192 1.17508115529 0.885454357124 1.0 +0.202330657224 -0.373588074037 -0.0183956151589 -0.891223086637 0.0
--- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/test-data/prp_result05 Fri Jun 03 13:57:12 2016 -0400 @@ -0,0 +1,7 @@ +%%MatrixMarket matrix coordinate real general +% +3 3 4 +1 1 1 +2 3 1 +3 1 1 +3 3 1
--- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/test-data/prp_result06 Fri Jun 03 13:57:12 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/prp_result07 Fri Jun 03 13:57:12 2016 -0400 @@ -0,0 +1,15 @@ +0.108665139011 -0.5565683482 0.0169733875077 -0.958962367167 -0.816496580928 +-0.571099536518 0.0792679658547 0.465423608048 0.979765457216 -0.816496580928 +0.108471837009 0.678736447658 -0.223614760609 0.803743046655 1.22474487139 +1.96379316226 2.0890722453 -2.06067941621 0.000324237526991 1.22474487139 +1.23514229057 1.26796195008 -1.28711935665 -0.065389486603 1.22474487139 +0.834735886268 1.01612031648 -0.900890721629 0.182945343826 1.22474487139 +-0.922721566735 -0.282935381937 0.832083851483 0.99661412602 -0.816496580928 +-0.797981006883 -1.98723568294 1.05920522412 -1.6242152405 -0.816496580928 +0.469308433082 0.835725023547 -0.558039074324 0.480130421839 1.22474487139 +-2.16591192182 -1.28401423621 2.07396641364 1.45497967458 -0.816496580928 +0.216069881629 -0.248375798767 -0.133526859597 -0.682255742645 -0.816496580928 +-0.00276638101632 -0.357063579425 0.0719181270631 -0.505225264563 -0.816496580928 +0.50277693294 -0.203429980112 -0.383697028135 -1.05322452049 -0.816496580928 +-1.32399310738 -0.345331774338 1.1821195963 1.51654378855 1.22474487139 +0.345509957574 -0.701929166993 -0.154122991003 -1.52577347424 -0.816496580928
--- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/test-data/prp_result08 Fri Jun 03 13:57:12 2016 -0400 @@ -0,0 +1,9 @@ +%%MatrixMarket matrix coordinate real general +% +3 3 6 +1 1 1 +1 3 -0.01818181818181818 +2 3 1 +3 1 0.04 +3 2 -1 +3 3 0.2363636363636364
--- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/test-data/prp_result09 Fri Jun 03 13:57:12 2016 -0400 @@ -0,0 +1,9 @@ +%%MatrixMarket matrix coordinate real general +% +3 3 6 +1 1 0.8333333333333334 +1 3 -0.1666666666666667 +2 3 1 +3 1 0.005235602094240837 +3 2 -0.6544502617801047 +3 3 0.3403141361256544