comparison main_macros.xml @ 10:badf6af0a182 draft

planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 97c4f22cdcfa6cddeeffc7b102c418a7ff12a888

9:049c8e817869

<macros>
  <token name="@VERSION@">0.9</token>

  <token name="@COLUMNS_FUNCTION@">
def read_columns(f, c, return_df=False, **args):
  data = pandas.read_csv(f, **args)
  cols = c.split (',')
  cols = map(int, cols)
  cols = list(map(lambda x: x - 1, cols))
  data = data.iloc[:,cols]
  y = data.values
  if return_df:
    return y, data
  else:
    return y
  return y
  </token>

## generate an instance for one of sklearn.feature_selection classes
## must call "@COLUMNS_FUNCTION@"
  <token name="@FEATURE_SELECTOR_FUNCTION@">
def feature_selector(inputs):
  selector = inputs["selected_algorithm"]
  selector = getattr(sklearn.feature_selection, selector)
  options = inputs["options"]

    <param name="infile2" type="data" format="@FORMAT2@" label="@LABEL2@" help="@HELP2@"/>
    <param name="col2" multiple="@MULTIPLE2@" type="data_column" data_ref="infile2" label="Select target column(s):"/>
    <yield/>
  </xml>

  <xml name="samples_tabular" token_multiple1="False" token_multiple2="False">
    <param name="infile1" type="data" format="tabular" label="Training samples dataset:"/>
    <param name="header1" type="boolean" optional="True" truevalue="booltrue" falsevalue="boolfalse" checked="False" label="Does the dataset contain header:" />
    <param name="col1" multiple="@MULTIPLE1@" type="data_column" data_ref="infile1" label="Select target column(s):"/>
    <param name="infile2" type="data" format="tabular" label="Dataset containing class labels:"/>
    <param name="header2" type="boolean" optional="True" truevalue="booltrue" falsevalue="boolfalse" checked="False" label="Does the dataset contain header:" />
    <param name="col2" multiple="@MULTIPLE2@" type="data_column" data_ref="infile2" label="Select target column(s):"/>
    <yield/>
  </xml>

  <xml name="clf_inputs_extended" token_label1=" " token_label2=" " token_multiple="False">
    <conditional name="true_columns">
      <param name="selected_input1" type="select" label="Select the input type of true labels dataset:">

  </xml>

  <xml name="clf_inputs" token_label1="Dataset containing true labels (tabular):" token_label2="Dataset containing predicted values (tabular):" token_multiple1="False" token_multiple="False">
    <param name="infile1" type="data" format="tabular" label="@LABEL1@"/>
    <param name="header1" type="boolean" optional="True" truevalue="booltrue" falsevalue="boolfalse" checked="False" label="Does the dataset contain header:" />
    <param name="col1" multiple="@MULTIPLE1@" type="data_column" data_ref="infile1" label="Select the target column:"/>
    <param name="infile2" type="data" format="tabular" label="@LABEL2@"/>
    <param name="header2" type="boolean" optional="True" truevalue="booltrue" falsevalue="boolfalse" checked="False" label="Does the dataset contain header:" />
    <param name="col2" multiple="@MULTIPLE@" type="data_column" data_ref="infile2" label="Select target column(s):"/>
  </xml>

  <xml name="multiple_input" token_name="input_files" token_max_num="10" token_format="txt" token_label="Sparse matrix file (.mtx, .txt)" token_help_text="Specify a sparse matrix file in .txt format.">
    <repeat name="@NAME@" min="1" max="@MAX_NUM@" title="Select input file(s):">
        <param name="input" type="data" format="@FORMAT@" label="@LABEL@" help="@HELP_TEXT@"/>

10:badf6af0a182

<macros>
  <token name="@VERSION@">0.9</token>

  <token name="@COLUMNS_FUNCTION@">
def read_columns(f, c=None, c_option='by_index_number', return_df=False, **args):
  data = pandas.read_csv(f, **args)
  if c_option == 'by_index_number':
    cols = list(map(lambda x: x - 1, c))
    data = data.iloc[:,cols]
  y = data.values
  if return_df:
    return y, data
  else:
    return y
  return y
  </token>

## generate an instance for one of sklearn.feature_selection classes
  <token name="@FEATURE_SELECTOR_FUNCTION@">
def feature_selector(inputs):
  selector = inputs["selected_algorithm"]
  selector = getattr(sklearn.feature_selection, selector)
  options = inputs["options"]

    <param name="infile2" type="data" format="@FORMAT2@" label="@LABEL2@" help="@HELP2@"/>
    <param name="col2" multiple="@MULTIPLE2@" type="data_column" data_ref="infile2" label="Select target column(s):"/>
    <yield/>
  </xml>

  <xml name="samples_tabular" token_multiple1="false" token_multiple2="false">
    <param name="infile1" type="data" format="tabular" label="Training samples dataset:"/>
    <param name="header1" type="boolean" optional="true" truevalue="booltrue" falsevalue="boolfalse" checked="False" label="Does the dataset contain header:" />
    <conditional name="column_selector_options_1">
      <expand macro="samples_column_selector_options" multiple="@MULTIPLE1@"/>
    </conditional>
    <param name="infile2" type="data" format="tabular" label="Dataset containing class labels:"/>
    <param name="header2" type="boolean" optional="true" truevalue="booltrue" falsevalue="boolfalse" checked="False" label="Does the dataset contain header:" />
    <conditional name="column_selector_options_2">
      <expand macro="samples_column_selector_options" column_option="selected_column_selector_option2" col_name="col2" multiple="@MULTIPLE2@" infile="infile2"/>
    </conditional>
    <yield/>
  </xml>

  <xml name="samples_column_selector_options" token_column_option="selected_column_selector_option" token_col_name="col1" token_multiple="False" token_infile="infile1">
    <param name="@COLUMN_OPTION@" type="select" label="Choose how to select data by column:">
      <option value="by_index_number" selected="true">Select columns by column index number(s)</option>
      <!--
      <option value="by_header_name">Select columns by column header name(s)</option>
      <option value="all_but_by_index_number">All columns but by column index number(s)</option>
      <option value="all_but_by_header_name">All columns but by column header name(s)</option> 
      -->
      <option value="all_columns">All columns</option>
    </param>
    <when value="by_index_number">
      <param name="@COL_NAME@" multiple="@MULTIPLE@" type="data_column" data_ref="@INFILE@" label="Select target column(s):"/>
    </when>
    <when value="all_columns">
    </when>
  </xml>

  <xml name="clf_inputs_extended" token_label1=" " token_label2=" " token_multiple="False">
    <conditional name="true_columns">
      <param name="selected_input1" type="select" label="Select the input type of true labels dataset:">

  </xml>

  <xml name="clf_inputs" token_label1="Dataset containing true labels (tabular):" token_label2="Dataset containing predicted values (tabular):" token_multiple1="False" token_multiple="False">
    <param name="infile1" type="data" format="tabular" label="@LABEL1@"/>
    <param name="header1" type="boolean" optional="True" truevalue="booltrue" falsevalue="boolfalse" checked="False" label="Does the dataset contain header:" />
    <conditional name="column_selector_options_1">
      <expand macro="samples_column_selector_options" multiple="@MULTIPLE1@"/>
    </conditional>
    <param name="infile2" type="data" format="tabular" label="@LABEL2@"/>
    <param name="header2" type="boolean" optional="True" truevalue="booltrue" falsevalue="boolfalse" checked="False" label="Does the dataset contain header:" />
    <conditional name="column_selector_options_2">
      <expand macro="samples_column_selector_options" column_option="selected_column_selector_option2" col_name="col2" multiple="@MULTIPLE@" infile="infile2"/>
    </conditional>
  </xml>

  <xml name="multiple_input" token_name="input_files" token_max_num="10" token_format="txt" token_label="Sparse matrix file (.mtx, .txt)" token_help_text="Specify a sparse matrix file in .txt format.">
    <repeat name="@NAME@" min="1" max="@MAX_NUM@" title="Select input file(s):">
        <param name="input" type="data" format="@FORMAT@" label="@LABEL@" help="@HELP_TEXT@"/>