annotate table_compute.xml @ 0:1b0f96ed73f2 draft

"planemo upload for repository https://github.com/galaxyproject/tools-iuc/tree/master/tools/table_compute commit 1ee75135483d5db22c540bc043746cd986f85762"

<tool id="table_compute" name="Table Compute" version="@VERSION@">
    <description>computes operations on table data</description>
    <macros>
        <token name="@VERSION@">0.8</token>
        <token name="@COPEN@"><![CDATA[<code>]]></token>
        <token name="@CCLOSE@"><![CDATA[</code>]]></token>
        <import>allowed_functions.xml</import>
        <!-- text field validators -->
        <macro name="validator_text" >
            <validator type="regex" message="No special characters allowed">^(?:\w+)?$</validator>
            <sanitizer sanitize="false" />
        </macro>
        <macro name="validator_text_required" >
            <validator type="regex" message="No special characters allowed">^(?:\w+)?$</validator>
            <validator type="empty_field" />
        </macro>
        <macro name="validator_index_identifiers" >
            <validator type="regex" message="Specify a comma-separated list of index names without special characters">^(?:\w+(?:, *\w+)*)?$</validator>
            <sanitizer sanitize="false" />
        </macro>
        <macro name="validator_index_ranges">
            <validator type="regex" message="Specify a comma-separated list index numbers or ranges">^(?:\d+(?::\d)*(?:, *\d+(?::\d)*)*)?$</validator>
            <sanitizer sanitize="false" />
        </macro>
        <macro name="validator_functiondef">
            <validator type="regex" message="An expression is required and is allowed to contain only letters, numbers and the characters '_ !-+=/*%.&lt;&gt;()'">^[\w !\-+=/*%,.&lt;&gt;()]+$</validator>
            <sanitizer sanitize="false" />
        </macro>
        <!-- macro for main input tests -->
        <macro name="test_inputs_single" >
            <conditional name="singtabop" >
                <param name="use_type" value="single" />
                <param name="input" value="small.tsv" />
                <conditional name="user" >
                    <yield />
                </conditional>
            </conditional>
        </macro>
        <!-- macro for umi to transcript tests -->
        <macro name="umi2trans" >
            <yield />
            <conditional name="user" >
                <param name="mode" value="element" />
                <param name="element_op" value="gt" />
                <param name="element_value" value="0" />
                <conditional name="element" >
                    <param name="mode" value="custom" />
                    <param name="custom_expr" value="-math.log(1 - elem/4096) * 4096 if elem != 4096 else elem - 0.5" />
                </conditional>
            </conditional>
        </macro>
        <!-- macro for file inputs -->
        <macro name="file_opts">
            <param name="input" type="data" format="tsv,tabular" label="Table" />
            <param name="col_row_names" type="select" display="checkboxes" multiple="true" optional="true"
            label="This input data has">
                <option value="has_col_names" selected="true">Column names on the first row</option>
                <option value="has_row_names" selected="true">Row names on the first column"</option>
            </param>
        </macro>
        <!-- element value macro -->
        <macro name="elem_val_macro" >
            <param name="element_value" type="text" optional="true" label="Filter value" help="This value is converted to numeric if possible, otherwise it is treated as a string" />
        </macro>
    </macros>
    <requirements>
        <requirement type="package" version="0.25">pandas</requirement>
        <requirement type="package" version="1.17">numpy</requirement>
    </requirements>

    <version_command><![CDATA[
        touch '$__tool_directory__/scripts/userconfig.py' && python '$__tool_directory__/scripts/table_compute.py' --version
    ]]></version_command>

    <command detect_errors="exit_code"><![CDATA[
        ## Can only import generated userconfig.py if calling
        ## script is in the same directory. Soft-linking does
        ## not satisfy importing, so we copy everything.
        cp '$userconf' ./userconfig.py &&
        cp '$__tool_directory__/scripts/safety.py' ./safety.py &&
        cp '$__tool_directory__/scripts/table_compute.py' ./table_compute.py &&
        python ./table_compute.py
    ]]></command>
    <configfiles>
        <configfile name="userconf"><![CDATA[

## Range Maker
##  "2:5,11,1:2" specifies "2,3,4,5,11,1,2" which in python is "1,2,3,4,10,0,1"
#def rangemake(tab):
#echo    [(n-1) for r in map(lambda y: range(int(y[0]),int(y[-1])+1), map(lambda x: x.split(':'), tab.split(','))) for n in r]
#end def

## Strip leading and trailing whitespace off custom functions

Default = {
    "reader_skip": 0,
    "precision": $precision,
  #if 'ignore_nas' in str($out_opts):
    "narm": True,
  #else:
    "narm": False,
  #end if
  #if 'output_headers_row' in str($out_opts):
    "out_headers_row": True,
  #else:
    "out_headers_row": False,
  #end if
  #if 'output_headers_col' in str($out_opts):
    "out_headers_col": True,
  #else:
    "out_headers_col": False,
  #end if
  "user_mode": '$singtabop.use_type',
  "outtable": '$table'
}

#if str($singtabop.use_type) == "single":
Data = {
    "tables": [
        {
          "reader_file": '$singtabop.input',
        #if 'has_col_names' in str($singtabop.col_row_names):
          "reader_header": 0,
        #else:
          "reader_header": None,
        #end if
        #if 'has_row_names' in str($singtabop.col_row_names):
          "reader_row_col": 0,
        #else:
          "reader_row_col": False,
        #end if
        }
    ],
    "params": {
      "user_mode_single": '$singtabop.user.mode.value',
    #if $singtabop.user.mode.value == 'precision':
        ## Literally do nothing, the user just sets the precision slider
        ## at the top default level
    }
    #elif $singtabop.user.mode.value == 'select':
        "select_cols_unique": #echo 'select_cols_keepdupe' in str($singtabop.user.select_keepdupe)#,
        "select_rows_unique": #echo 'select_rows_keepdupe' in str($singtabop.user.select_keepdupe)#,
      #if $singtabop.user.select_cols_wanted:
        "select_cols_wanted": $rangemake(str($singtabop.user.select_cols_wanted)),
      #else
        "select_cols_wanted": None,
      #end if
      #if $singtabop.user.select_rows_wanted:
        "select_rows_wanted": $rangemake(str($singtabop.user.select_rows_wanted)),
      #else
        "select_rows_wanted": None,
      #end if
    }
    #elif $singtabop.user.mode.value == 'filtersumval':
        "filtersumval_mode": '$singtabop.user.filtersumval_mode.use.value',
        "filtersumval_axis": $singtabop.user.axis.value,
      #if $singtabop.user.filtersumval_mode.use.value == 'operation':
        "filtersumval_compare": '$singtabop.user.filtersumval_mode.compare_op.value',
        "filtersumval_op": '$singtabop.user.filtersumval_mode.operation.value',
        "filtersumval_against": $singtabop.user.filtersumval_mode.against,
        "filtersumval_minmatch": None,
      #elif $singtabop.user.filtersumval_mode.use.value == 'element':
        "filtersumval_compare": None,
        "filtersumval_op": '$singtabop.user.filtersumval_mode.operation.value',
        ## against could be string or float, so we parse this in the code
        "filtersumval_against": '$singtabop.user.filtersumval_mode.against',
        "filtersumval_minmatch": $singtabop.user.filtersumval_mode.minmatch,
      #end if
    }
    #elif $singtabop.user.mode.value == 'matrixapply':
        "matrixapply_dimension": $singtabop.user.dimension.value,
      #if str($singtabop.user.matrixapply_func.vector_op) == 'custom':
        #set $custom_func = str($singtabop.user.matrixapply_func.custom_func).strip()
        "matrixapply_custom": True,
        "matrixapply_custom_func": '$custom_func',
        "matrixapply_op": None,
      #else
        "matrixapply_custom": False,
        "matrixapply_custom_func": None,
        "matrixapply_op": '$singtabop.user.matrixapply_func.vector_op',
      #end if
    }
    #elif $singtabop.user.mode.value == 'element':
      #if str($singtabop.user.elem_val.element_op) != "None":
        "element_op": '$singtabop.user.elem_val.element_op.value',
        ## Value is string or float, parsed in code later
        "element_value" : '$singtabop.user.elem_val.element_value',
      #else:
        "element_op": None,
      #end if
        "element_mode": '$singtabop.user.element.mode.value',
      #if str($singtabop.user.element.mode) == "replace":
        "element_replace": '$singtabop.user.element.replace_value.value',
      #elif str($singtabop.user.element.mode) == "modify":
        "element_modify_op": '$singtabop.user.element.modify_op.value',
      #elif str($singtabop.user.element.mode) == "scale":
        "element_scale_op": '$singtabop.user.element.scale_op.value',
        "element_scale_value": $singtabop.user.element.scale_value,
      #elif str($singtabop.user.element.mode) == "custom":
        #set $custom_func = str($singtabop.user.element.custom_expr).strip()
        "element_customop": '$custom_func',
      #end if
    }
    #elif $singtabop.user.mode.value == 'fulltable':
        "mode": '$singtabop.user.general.use',
      #if str($singtabop.user.general.use) == 'melt':
        #if str($singtabop.user.general.id_vars).strip():
          #set $melt_ids = [i.strip() for i in str($singtabop.user.general.id_vars).split(',')]
        #else
          #set $melt_ids = 'None'
        #end if
        #if str($singtabop.user.general.value_vars).strip():
          #set $melt_values = [i.strip() for i in str($singtabop.user.general.value_vars).split(',')]
        #else
          #set $melt_values = 'None'
        #end if
        "MELT": {
            "melt_ids": $melt_ids,
            "melt_values": $melt_values,
        },
      #elif str($singtabop.user.general.use) == 'pivot':
        #set $pivot_index = str($singtabop.user.general.index).strip()
        #if $pivot_index:
          #set $pivot_index = "'" + $pivot_index + "'"
        #else:
          #set $pivot_index = 'None'
        #end if
        #set $pivot_column = "'" + str($singtabop.user.general.column).strip() + "'"
        #if str($singtabop.user.general.values).strip():
          #set $pivot_values = [i.strip() for i in str($singtabop.user.general.values).split(',')]
        #else
          #set $pivot_values = 'None'
        #end if
        "PIVOT": {
            "pivot_index": $pivot_index,
            "pivot_column": $pivot_column,
            "pivot_values": $pivot_values,
        },
      #elif str($singtabop.user.general.use) == 'custom':
        #set $custom_func = str($singtabop.user.general.fulltable_custom_expr.value).strip()
        "fulltable_customop": '$custom_func',

      #end if
    },
    #end if
}

#elif str($singtabop.use_type) == "multiple":
#set $custom_func = str($singtabop.fulltable_custom_expr).strip()
Data = {
    "tables": [
    #for $i, $s in enumerate($singtabop.tables)
        {
          "file": '${s.input}',
        #if 'has_col_names' in str($s.col_row_names):
          "header": 0,
        #else:
          "header": None,
        #end if
        #if 'has_row_names' in str($s.col_row_names):
          "row_names": 0,
        #else:
          "row_names": False,
        #end if
        },
    #end for
    ],
    'params': {
        "fulltable_customop" : '$custom_func',
    }
}
#end if

]]>
        </configfile>
    </configfiles>
    <inputs>
        <conditional name="singtabop" >
            <param name="use_type" type="select" label="Input Single or Multiple Tables" help="Operations on single tables are better tailored towards more general use-cases. For multiple tables usage, all tables should ideally be of the same dimensions for simple operations, although complex operations are also supported for unequally sized tables (see Help section)." >
                <option value="single">Single Table</option>
                <option value="multiple">Multiple Tables</option>
            </param>
            <when value="single">
                <expand macro="file_opts" />
                <conditional name="user" >
                    <param name="mode" type="select" label="Type of table operation" >
                        <option value="precision">No operation (just reformat on output)</option>
                        <option value="select">Drop, keep or duplicate rows and columns</option>
                        <option value="filtersumval">Filter rows or columns by their properties</option>
                        <option value="matrixapply">Compute expression across rows or columns</option>
                        <option value="element">Manipulate selected table elements</option>
                        <option value="fulltable">Perform a full table operation</option>
                    </param>
                    <when value="precision" />
                    <when value="select">
                        <param name="select_cols_wanted" type="text" optional="true" label="List of columns to select" help="Comma separated. (e.g. @COPEN@3:5,99,2:4@CCLOSE@ will select columns @COPEN@3,4,5,99,2,3,4@CCLOSE@). Columns can be duplicated by specifying them multiple times. Leave blank to retain all columns. See Example #1 for an example of using this mode." >
                            <expand macro="validator_index_ranges" />
                        </param>
                        <param name="select_rows_wanted" type="text" optional="true" label="List of rows to select" help="The same rules apply as above" >
                            <expand macro="validator_index_ranges" />
                        </param>
                        <param name="select_keepdupe" type="select" display="checkboxes" multiple="true" label="Duplicate Indices" help="Keep duplicates when specifying ranges (e.g. if unset, @COPEN@1:3,2:4@CCLOSE@ will yield @COPEN@1,2,3,4@CCLOSE@ instead of @COPEN@1,2,3,2,3,4@CCLOSE@)" >
                            <option value="select_cols_keepdupe" selected="true" >Keep duplicate columns</option>
                            <option value="select_rows_keepdupe" selected="true" >Keep duplicate rows</option>
                        </param>
                    </when>
                    <when value="filtersumval" >
                        <param name="axis" type="select" display="radio"
                        label="Filter" >
                            <option value="1">Rows</option>
                            <option value="0">Columns</option>
                        </param>
                        <conditional name="filtersumval_mode" >
                            <param name="use" type="select" label="Filter criterion" help="See Example #2 for an example of using this mode." >
                                <option value="operation" >Result of function applied to columns/rows</option>
                                <option value="element" >Number of column/row elements passing filter</option>
                            </param>
                            <when value="operation">
                                <param name="operation" type="select" label="Keep column/row if its observed" >
                                    <expand macro="select_vectorops" />
                                </param>
                                <param name="compare_op" type="select" label="is" >
                                    <expand macro="select_twovaluebooleanops" />
                                </param>
                                <param name="against" type="float" label="this value" value="0" />
                            </when>
                            <when value="element">
                                <param name="minmatch" type="integer" min="1" value="0" label="Keep column/row if at least" />
                                <param name="operation" type="select" label="of its element are" >
                                    <expand macro="select_twovaluebooleanops" >
                                        <option value="str_eq" >~ (Matching)</option>
                                        <option value="str_ne" >!~ (not Matching)</option>
                                    </expand>
                                </param>
                                <param name="against" type="text" label="this value">
                                    <expand macro="validator_functiondef" />
                                </param>
                            </when>
                        </conditional>
                    </when>
                    <when value="matrixapply" >
                        <conditional name="matrixapply_func">
                            <param name="vector_op" type="select" label="Calculate">
                                <option value="custom">Custom Function</option>
                                <expand macro="select_vectorops" >
                                    <option value="rank">Ranks</option>
                                    <option value="cumsum" >Cumulative Sum</option>
                                    <option value="cumprod" >Cumulative Product</option>
                                    <option value="cummin" >Cumulative Minimum</option>
                                    <option value="cummax" >Cumulative Maximum</option>
                                </expand>
                            </param>
                            <when value="custom">
                                <param name="custom_func" type="text"
                                label="Custom function on 'vec'"
                                help="The parameter name is @COPEN@vec@CCLOSE@, referring to a vector of a specific row or column being operated on. Numpy and Pandas DataFrame operators are supported. e.g. @[e-mail](vec) + np.median(vec)@CCLOSE@, and @[e-mail]() + vec.median()@CCLOSE@ are equivalent operations." >
                                    <expand macro="validator_functiondef" />
                                </param>
                            </when>
                            <when value="min" />
                            <when value="max" />
                            <when value="sum" />
                            <when value="count" />
                            <when value="nunique" />
                            <when value="mean" />
                            <when value="median" />
                            <when value="std" />
                            <when value="sem" />
                            <when value="var" />
                            <when value="mad" />
                            <when value="product" />
                            <when value="rank" />
                            <when value="cumsum" />
                            <when value="cumprod" />
                            <when value="cummin" />
                            <when value="cummax" />
                        </conditional>
                        <param name="dimension" type="select" label="For each">
                            <option value="0">Column</option>
                            <option value="1">Row</option>
                        </param>
                    </when>
                    <when value="fulltable">
                        <conditional name="general" >
                            <param name="use" type="select" label="Operation" help="See Examples 5, 7, and 8 for usage" >
                                <option value="melt" >Melt</option>
                                <option value="pivot" >Pivot</option>
                                <option value="custom" >Custom</option>
                            </param>
                            <when value="melt" >
                                <param name="id_vars" type="text" value="" label="Variable IDs"
                                       help="Comma-delimited list of column names to use as identifiers" >
                                    <expand macro="validator_index_identifiers" />
                                </param>
                                <param name="value_vars" type="text" value="" label="Unpivoted IDs"
                                       help="Comma-delimited list of column names to un-pivot. Leave blank to use all." >
                                    <expand macro="validator_index_identifiers" />
                                </param>
                            </when>
                            <when value="pivot" >
                                <param name="index" type="text" value=""
                                label="Index"
                                help="Name of the column to use as new index" >
                                    <expand macro="validator_text" />
                                </param>
                                <param name="column" type="text" value=""
                                label="Column"
                                help="Name of the column to use to generate the columns of the new table from" >
                                    <expand macro="validator_text_required" />
                                </param>
                                <param name="values" type="text" value=""
                                label="Values"
                                help="Names of the columns to use for populating the cells of the new table. Leave blank to use all." >
                                    <expand macro="validator_index_identifiers" />
                                </param>
                            </when>
                            <when value="custom" >
                                <param name="fulltable_custom_expr" type="text"
                                label="Custom expression on 'table', along 'axis' (0 or 1)"
                                help="The parameter name is @COPEN@table@CCLOSE@ and @COPEN@axis@CCLOSE@, referring to the table being acted on and the column (@COPEN@0@CCLOSE@) or row (@COPEN@1@CCLOSE@) to perform the operation on. Numpy, math, Pandas DataFrame operators, and inline @COPEN@if else@CCLOSE@ are supported (e.g. @[e-mail](table) - table.mean(0) / table.std(1)@CCLOSE@). See Example #5 in the Help section. ">
                                    <expand macro="validator_functiondef" />
                                </param>
                            </when>
                        </conditional>
                    </when>
                    <when value="element">
                        <conditional name="element" >
                            <param name="mode" type="select"
                            label="Operation to perform" >
                                <option value="replace">Replace values</option>
                                <option value="modify">Transform</option>
                                <option value="scale">Arithmetic operation</option>
                                <option value="custom">Custom</option>
                            </param>
                            <when value="replace" >
                                <param name="replace_value" type="text" label="Replacement value" help="This value is converted to numeric if possible, otherwise it is treated as a string" />
                            </when>
                            <when value="modify" >
                                <param name="modify_op" type="select" label="Transformation function" help="Example: to transform values to their square root, select @COPEN@Square Root@CCLOSE@ here.">
                                    <expand macro="select_onevalueoperator" />
                                </param>
                            </when>
                            <when value="scale">
                                <param name="scale_op" type="select" label="Operation" help="The selected operation will be applied to the table elements as the first operand. The value of the second operand can be provided in the next box. Example: to raise all values to the power of 5, select @COPEN@Power@CCLOSE@ here and type @COPEN@5@CCLOSE@ in the box below." >
                                    <expand macro="select_twovaluenumericoperator" />
                                </param>
                                <param name="scale_value" type="float" value="0" label="Second operand value" />
                            </when>
                            <when value="custom">
                                <param name="custom_expr" type="text"
                                label="Custom expression on 'elem'"
                                help="The parameter name is @COPEN@elem@CCLOSE@, referring to the element being acted on. Most operators and @COPEN@if@CCLOSE@ @COPEN@else@CCLOSE@ statements are supported. See Examples #3 and #4 in the Help section.">
                                    <expand macro="validator_functiondef" />
                                </param>
                            </when>
                        </conditional>
                        <conditional name="elem_val" >
                            <param name="element_op" type="select" label="Operate on elements"
                                help="Only selected elements will be manipulated. Other elements will retain their original value." >
                                <expand macro="select_twovaluebooleanops" >
                                    <option value="None" selected="true">All</option>
                                </expand>
                            </param>
                            <when value="None" />
                            <when value="lt">
                                <expand macro="elem_val_macro" />
                            </when>
                            <when value="le">
                                <expand macro="elem_val_macro" />
                            </when>
                            <when value="gt">
                                <expand macro="elem_val_macro" />
                            </when>
                            <when value="ge">
                                <expand macro="elem_val_macro" />
                            </when>
                            <when value="eq">
                                <expand macro="elem_val_macro" />
                            </when>
                            <when value="ne">
                                <expand macro="elem_val_macro" />
                            </when>
                        </conditional>
                    </when>
                </conditional>
            </when>
            <when value="multiple">
                <repeat name="tables" title="Tables" min="1" default="1">
                    <expand macro="file_opts" />
                </repeat>
                <param name="fulltable_custom_expr" type="text"
                label="Custom expression on 'tableN'"
                help="The parameter name is @COPEN@tableN@CCLOSE@, where @COPEN@N@CCLOSE@ refers to a specific table. e.g. @COPEN@table1 + table3 - table2@CCLOSE@, will add the first and third input tables and then subtract the second. Most operators and @COPEN@if@CCLOSE@ @COPEN@else@CCLOSE@ statements are supported. See Example #6 in the Help section for further examples.">
                    <expand macro="validator_functiondef" />
                </param>
            </when>
        </conditional>
        <param name="out_opts" type="select" display="checkboxes" multiple="true" optional="true"
               label="Output formatting options">
            <option value="ignore_nas" selected="true">Ignore NA values</option>
            <option value="output_headers_col" selected="true">Output column headers</option>
            <option value="output_headers_row" selected="true">Output row headers</option>
        </param>
        <param name="precision" type="integer" min="0" max="20" value="6" label="Output decimal precision" />
    </inputs>
    <outputs>
        <data name="table" format="tabular" label="${tool.name} on ${on_string}" />
    </outputs>
    <tests>
        <test expect_num_outputs="1">
            <!-- Test 1: Select -->
            <expand macro="test_inputs_single" >
                <param name="mode" value="select" />
                <param name="select_cols_wanted" value="2:4,2,2" />
                <param name="select_rows_wanted" value="2:5,3,3" />
                <param name="select_keepdupe" value="select_cols_keepdupe" />
            </expand>
            <param name="precision" value="2" />
            <output name="table" value="small.select.tsv" />
        </test>
        <test expect_num_outputs="1">
            <!-- Test 2: Select, cols only -->
            <expand macro="test_inputs_single" >
                <param name="mode" value="select" />
                <param name="select_cols_wanted" value="2:4,2,2" />
                <param name="select_keepdupe" value="select_cols_keepdupe,select_rows_keepdupe" />
            </expand>
            <param name="precision" value="2" />
            <output name="table" value="small.select.colsonly.tsv" />
        </test>
        <test expect_num_outputs="1">
            <!-- Test 3: Select, rows only -->
            <expand macro="test_inputs_single" >
                <param name="mode" value="select" />
                <param name="select_rows_wanted" value="2:5,3,3" />
                <param name="select_keepdupe" value="select_cols_keepdupe" />
            </expand>
            <param name="precision" value="2" />
            <output name="table" value="small.select.rowsonly.tsv" />
        </test>
        <test expect_num_outputs="1">
            <!-- Test 4: Filtersumval, row -->
            <expand macro="test_inputs_single" >
                <param name="mode" value="filtersumval" />
                <param name="axis" value="1" />
                <conditional name="filtersumval_mode" >
                    <param name="use" value="operation" />
                    <param name="operation" value="sum" />
                    <param name="compare_op" value="gt" />
                    <param name="against" value="50" />
                </conditional>
            </expand>
            <param name="precision" value="2" />
            <output name="table" value="small.fs.rowsum.gt.50.tsv" />
        </test>
        <test expect_num_outputs="1">
            <!-- Test 5: Filtersumval, col neq 0 -->
            <expand macro="test_inputs_single" >
                <param name="mode" value="filtersumval" />
                <param name="axis" value="0" />
                 <conditional name="filtersumval_mode" >
                    <param name="use" value="operation" />
                    <param name="operation" value="sum" />
                    <param name="compare_op" value="ne" />
                    <param name="against" value="0" />
                </conditional>
            </expand>
            <param name="precision" value="2" />
            <output name="table" value="small.fs.colsum.neq0.tsv" />
        </test>
        <test expect_num_outputs="1">
            <!-- Test 6: Filtersumval, col val gt 10 -->
            <expand macro="test_inputs_single" >
                <param name="mode" value="filtersumval" />
                <param name="axis" value="0" />
                <conditional name="filtersumval_mode" >
                    <param name="use" value="operation" />
                    <param name="operation" value="sum" />
                    <param name="compare_op" value="gt" />
                    <param name="against" value="10" />
                </conditional>
            </expand>
            <param name="precision" value="2" />
            <output name="table" value="small.fs.colsum.gt10.tsv" />
        </test>
        <test expect_num_outputs="1">
            <!-- Test 7: Filtersumval, median val col >= 2 -->
            <expand macro="test_inputs_single" >
                <param name="mode" value="filtersumval" />
                <param name="axis" value="0" />
                <conditional name="filtersumval_mode" >
                    <param name="use" value="operation" />
                    <param name="operation" value="median" />
                    <param name="compare_op" value="ge" />
                    <param name="against" value="2" />
                </conditional>
            </expand>
            <param name="precision" value="5" />
            <output name="table" value="small.fs.medvalcol.ge2.tsv" />
        </test>
        <test expect_num_outputs="1">
            <!-- Test 8: Filtersumval, keep rows with at least
                 two values > 2 -->
            <expand macro="test_inputs_single" >
                <param name="mode" value="filtersumval" />
                <param name="axis" value="1" />
                <conditional name="filtersumval_mode" >
                    <param name="use" value="element" />
                    <param name="operation" value="gt" />
                    <param name="against" value="2" />
                    <param name="minmatch" value="2" />
                </conditional>
            </expand>
            <param name="precision" value="5" />
            <output name="table" value="small.fs.elemgt2.mm2.tsv" />
        </test>
        <test expect_num_outputs="1">
            <!-- Test 9: Filtersumval, keep cols with at least
                 4 string values matching "0" -->
            <expand macro="test_inputs_single" >
                <param name="mode" value="filtersumval" />
                <param name="axis" value="0" />
                <conditional name="filtersumval_mode" >
                    <param name="use" value="element" />
                    <param name="operation" value="str_ne" />
                    <param name="against" value="0" />
                    <param name="minmatch" value="4" />
                </conditional>
            </expand>
            <param name="precision" value="3" />
            <output name="table" value="small.fs.elemnmatch0.mm4.tsv" />
        </test>
        <test expect_num_outputs="1">
            <!-- Test 10: Matrix Apply, row max  -->
            <expand macro="test_inputs_single" >
                <param name="mode" value="matrixapply" />
                <param name="dimension" value="1" />
                <conditional name="matrixapply_func" >
                    <param name="vector_op" value="max" />
                </conditional>
            </expand>
            <param name="precision" value="0" />
            <param name="out_opts" value="ignore_nas,output_headers_row" />
            <output name="table" value="small.matapp.rowmax.tsv" />
        </test>
        <test expect_num_outputs="1">
            <!-- Test 11: Element, all, scale, remainder 5  -->
            <expand macro="test_inputs_single" >
                <param name="mode" value="element" />
                <conditional name="elem_val">
                    <param name="element_op" value="None" />
                </conditional>
                <conditional name="element" >
                    <param name="mode" value="scale" />
                    <param name="scale_op" value="mod" />
                    <param name="scale_value" value="5" />
                </conditional>
            </expand>
            <param name="precision" value="2" />
            <output name="table" value="small.element.scalerem5.tsv" />
        </test>
        <test expect_num_outputs="1">
            <!-- Test 12: Matrix Apply, column custom  -->
            <expand macro="test_inputs_single" >
                <param name="mode" value="matrixapply" />
                <param name="dimension" value="0" />
                <conditional name="matrixapply_func" >
                    <param name="vector_op" value="custom" />
                    <param name="custom_func" value="vec.sum()+vec.median()" />
                </conditional>
            </expand>
            <param name="precision" value="2" />
            <param name="out_opts" value="ignore_nas,output_headers_row" />
            <output name="table" value="small.matapp.colcust.tsv" />
        </test>
        <test expect_num_outputs="1">
            <!-- Test 13: Element, non-zero, custom -->
            <expand macro="test_inputs_single" >
                <param name="mode" value="element" />
                <conditional name="elem_val">
                    <param name="element_op" value="gt" />
                    <param name="element_value" value="0" />
                </conditional>
                <conditional name="element" >
                    <param name="mode" value="custom" />
                    <!-- valid complex expression for non-zero vals -->
                    <param name="custom_expr" value="(math.log10(elem)+elem)/elem if (elem &lt; math.inf) else 1.0" />
                </conditional>
            </expand>
            <output name="table" value="small.element.custom.tsv" />
        </test>
        <test expect_num_outputs="1">
            <!-- Test 14: umi2transcript test1 -->
            <expand macro="umi2trans" >
                <param name="input" value="mat1.umi.tsv" />
                <output name="table" value="mat1.trans.tsv" />
            </expand>
        </test>
        <test expect_num_outputs="1">
            <!-- Test 15: umi2transcript test2 -->
            <expand macro="umi2trans" >
                <param name="input" value="mat2.umi.tsv" />
                <output name="table" value="mat2.trans.tsv" />
            </expand>
        </test>
        <test expect_num_outputs="1">
            <!-- Test 16: B-test - mean and sd in custom func -->
            <expand macro="test_inputs_single" >
                <param name="mode" value="fulltable" />
                <conditional name="general" >
                    <param name="use" value="custom" />
                    <param name="fulltable_custom_expr"
                           value="table - table.mean(0) / table.std(0)" />
                </conditional>
            </expand>
            <output name="table" value="small.fulltable.tsv" />
        </test>
        <test expect_num_outputs="1">
            <!-- Test 17: Multiple table test -->
            <conditional name="singtabop" >
                <param name="use_type" value="multiple" />
                <repeat name="tables">
                    <param name="input" value="small.tsv" />
                </repeat>
                <repeat name="tables">
                    <param name="input" value="small.tsv" />
                </repeat>
                <repeat name="tables">
                    <param name="input" value="small.tsv" />
                </repeat>
                <param name="fulltable_custom_expr" value="(3 * table1) + np.log(table3 + 20) - table2" />            </conditional>
            <output name="table" value="small.multiple.tsv" />
        </test>
        <!-- User tests that failed previously -->
        <test expect_num_outputs="1">
            <!-- Test 18 -->
            <expand macro="test_inputs_single" >
                <param name="mode" value="fulltable" />
                <conditional name="general" >
                    <param name="use" value="custom" />
                    <param name="fulltable_custom_expr" value="table * 2" />
                </conditional>
            </expand>
            <output name="table" >
                <assert_contents>
                    <has_n_columns n="10" />
                    <has_line_matching expression="^gene1\s20\.000000\s0\s12\s-20\.200000\s20\s2\.200000\s0\.000000\s0\s0\.000000$" />
                    <has_line_matching expression="gene5\s2\.000000\s0\s0\s-20\.000000\s880\s12\.000000\s0\.000000\s0\s3\.800000" />
                </assert_contents>
            </output>
        </test>
        <test expect_num_outputs="1">
            <!-- Test 19 -->
            <expand macro="test_inputs_single" >
                <param name="mode" value="fulltable" />
                <conditional name="general" >
                    <param name="use" value="custom" />
                    <param name="fulltable_custom_expr" value="table == 5" />
                </conditional>
            </expand>
            <output name="table" >
                <assert_contents>
                    <has_n_columns n="10" />
                    <has_line_matching expression="^gene1(\sFalse)+$" />
                    <has_line_matching expression="gene5(\sFalse)+$" />
                </assert_contents>
            </output>
        </test>
        <test expect_num_outputs="1" expect_failure="true">
            <!-- Test 20 -->
            <expand macro="test_inputs_single" >
                <param name="mode" value="fulltable" />
                <conditional name="general" >
                    <param name="use" value="custom" />
                    <param name="fulltable_custom_expr" value="for n in table: n = n + 1" />
                </conditional>
            </expand>
        </test>
        <test expect_num_outputs="1" expect_failure="true">
            <!-- Test 21 -->
            <expand macro="test_inputs_single" >
                <param name="mode" value="fulltable" />
                <conditional name="general" >
                    <param name="use" value="custom" />
                    <param name="fulltable_custom_expr" value="table + table[0,0]" />
                </conditional>
            </expand>
        </test>
        <test expect_num_outputs="1">
            <!-- Test 22: Melt -->
            <expand macro="test_inputs_single" >
                <param name="mode" value="fulltable" />
                <conditional name="general" >
                    <param name="use" value="melt" />
                    <param name="id_vars" value="cell1,cell3" />
                    <param name="value_vars" value="cell5,cell6" />
                </conditional>
            </expand>
            <param name="out_opts" value="ignore_nas,output_headers_col" />
            <output name="table" >
                <assert_contents>
                    <has_n_columns n="4" />
                    <has_line_matching expression="^cell1\scell3\svariable\svalue$" />
                    <has_line_matching expression="^1\.0+\s0+\scell6\s6\.0+$" />
                </assert_contents>
            </output>
        </test>
        <test expect_num_outputs="1">
            <!-- Test 23: Pivot -->
            <expand macro="test_inputs_single" >
                <param name="mode" value="fulltable" />
                <conditional name="general" >
                    <param name="use" value="pivot" />
                    <param name="index" value="cell1" />
                    <param name="column" value="cell2" />
                    <param name="values" value="cell3,cell7,cell9" />
                </conditional>
            </expand>
            <output name="table" >
                <assert_contents>
                    <has_n_columns n="4" />
                    <has_line_matching expression="^\scell3\scell7\scell9$" />
                    <has_line_matching expression="^1\.0+\s0\.0+\s0\.0+\s1\.90+$" />
                    <has_line_matching expression="^10\.0+\s6\.0+\s0\.0+\s0\.0+$" />
                </assert_contents>
            </output>
        </test>
        <!-- Add Example Text Tests -->
        <test expect_num_outputs="1" >
            <!-- Test 24: Ex 1 -->
            <conditional name="singtabop" >
                <param name="use_type" value="single" />
                <param name="input" value="examples.1.tsv" />
                <param name="col_row_names" value="has_col_names,has_row_names" />
                <conditional name="user" >
                    <param name="mode" value="select" />
                    <param name="select_cols_wanted" value="1,1,3" />
                    <param name="select_rows_wanted" value="1:3,2" />
                    <param name="select_keepdupe" value="select_cols_keepdupe,select_rows_keepdupe" />
                </conditional>
            </conditional>
            <output name="table" >
                <assert_contents>
                    <has_n_columns n="4" />
                    <has_line_matching expression="^\s+c1\s+c1\s+c3$" />
                    <has_line_matching expression="^g2\s+3\s+3\s+9$" />
                </assert_contents>
            </output>
        </test>
        <test expect_num_outputs="1" >
            <!-- Test 25: Ex 2 -->
            <conditional name="singtabop" >
                <param name="use_type" value="single" />
                <param name="input" value="examples.2.tsv" />
                <param name="col_row_names" value="has_col_names,has_row_names" />
                <conditional name="user" >
                    <param name="mode" value="filtersumval" />
                    <param name="axis" value="1" />
                    <conditional name="filtersumval_mode" >
                        <param name="use" value="operation" />
                        <param name="operation" value="sum" />
                        <param name="compare_op" value="lt" />
                        <param name="against" value="50" />
                    </conditional>
                </conditional>
            </conditional>
            <output name="table" >
                <assert_contents>
                    <has_n_columns n="4" />
                    <has_line_matching expression="^\s+c1\s+c2\s+c3$" />
                    <has_line_matching expression="^g3\s+4\s+8\s+12$" />
                </assert_contents>
            </output>
        </test>
        <test expect_num_outputs="1" >
            <!-- Test 26: Ex 3_P1 -->
            <conditional name="singtabop" >
                <param name="use_type" value="single" />
                <param name="input" value="examples.3p1.tsv" />
                <param name="col_row_names" value="has_col_names,has_row_names" />
                <conditional name="user" >
                    <param name="mode" value="element" />
                    <conditional name="element" >
                        <param name="mode" value="custom" />
                        <param name="custom_expr" value="elem &#60; 10" />
                    </conditional>
                    <conditional name="elem_val" >
                        <param name="element_op" value="None" />
                    </conditional>
                </conditional>
            </conditional>
            <output name="table" >
                <assert_contents>
                    <has_n_columns n="4" />
                    <has_line_matching expression="^g1\s+False\s+False\s+False$" />
                    <has_line_matching expression="^g4\s+False\s+True\s+True$" />
                </assert_contents>
            </output>
        </test>
        <test expect_num_outputs="1" >
            <!-- Test 27: Ex 3_P2 -->
            <conditional name="singtabop" >
                <param name="use_type" value="single" />
                <param name="input" value="examples.3p2.tsv" />
                <param name="col_row_names" value="has_col_names,has_row_names" />
                <conditional name="user" >
                    <param name="mode" value="matrixapply" />
                    <param name="dimension" value="1" />
                    <conditional name="matrixapply_func" >
                        <param name="vector_op" value="sum" />
                    </conditional>
                </conditional>
            </conditional>
            <output name="table" >
                <assert_contents>
                    <has_n_columns n="2" />
                    <has_line_matching expression="^g1\s+0$" />
                    <has_line_matching expression="^g4\s+2$" />
                </assert_contents>
            </output>
	        </test>
        <test expect_num_outputs="1" >
            <!-- Test 28: Ex 4 -->
            <conditional name="singtabop" >
                <param name="use_type" value="single" />
                <param name="input" value="examples.4.tsv" />
                <param name="col_row_names" value="has_col_names,has_row_names" />
                <conditional name="user" >
                    <param name="mode" value="element" />
                    <conditional name="element" >
                        <param name="mode" value="custom" />
                        <param name="custom_expr" value="(math.log(elem) / elem) if (elem > 5) else 1" />
                    </conditional>
                    <conditional name="elem_val" >
                        <param name="element_op" value="All" />
                    </conditional>
                </conditional>
            </conditional>
            <output name="table" >
                <assert_contents>
                    <has_n_columns n="4" />
                    <has_line_matching expression="^g1\s+1\.00\d+\s+0\.149\d+\s+0\.113\d+$" />
                    <has_line_matching expression="^g4\s+0\.05\d+\s+1\.000\d+\s+1\.000\d+$" />
                </assert_contents>
            </output>
        </test>
        <test expect_num_outputs="1" >
            <!-- Test 29: Ex 5 -->
            <conditional name="singtabop" >
                <param name="use_type" value="single" />
                <param name="input" value="examples.5.tsv" />
                <param name="col_row_names" value="has_col_names,has_row_names" />
                <conditional name="user" >
                    <param name="mode" value="fulltable" />
                    <conditional name="general" >
                        <param name="use" value="custom" />
                        <param name="fulltable_custom_expr" value="table - table.mean(0)/table.std(0)" />
                    </conditional>
                </conditional>
            </conditional>
            <output name="table" >
                <assert_contents>
                    <has_n_columns n="4" />
                    <has_line_matching expression="^g1\s+9\.\d+\s+17\.\d+\s+28\.\d+$" />
                    <has_line_matching expression="^g4\s+80\.\d+\s+7\.\d+\s+8\.\d+$" />
                </assert_contents>
            </output>
        </test>
        <test expect_num_outputs="1" >
            <!-- Test 30: Ex 6 -->
            <conditional name="singtabop" >
                <param name="use_type" value="multiple" />
                <repeat name="tables" >
                    <param name="input" value="examples.6p1.tsv" />
                    <param name="col_row_names" value="has_col_names,has_row_names" />
                </repeat>
                <repeat name="tables" >
                    <param name="input" value="examples.6p2.tsv" />
                    <param name="col_row_names" value="has_col_names,has_row_names" />
                </repeat>
                <repeat name="tables" >
                    <param name="input" value="examples.6p3.tsv" />
                    <param name="col_row_names" value="has_col_names,has_row_names" />
                </repeat>
                <param name="fulltable_custom_expr" value="table1 / min(np.max(np.max(table2)), np.max(np.max(table3)))" />
            </conditional>
            <output name="table" >
                <assert_contents>
                    <has_n_columns n="4" />
                    <has_line_matching expression="^g1\s+3\.3\d+\s+6\.6\d+\s+10\.0\d+$" />
                    <has_line_matching expression="^g3\s+1\.3\d+\s+2\.6\d+\s+3\.3\d+$" />
                </assert_contents>
            </output>
        </test>
        <test expect_num_outputs="1" >
            <!-- Test 31: Ex 7 -->
            <conditional name="singtabop" >
                <param name="use_type" value="single" />
                <param name="input" value="examples.7.tsv" />
                <param name="col_row_names" value="has_col_names,has_row_names" />
                <conditional name="user">
                    <param name="mode" value="fulltable" />
                    <conditional name="general" >
                        <param name="use" value="melt" />
                        <param name="id_vars" value="A" />
                        <param name="value_vars" value="B,C" />
                    </conditional>
                </conditional>
            </conditional>
            <output name="table" >
                <assert_contents>
                    <has_n_columns n="4" />
                    <has_line_matching expression="^0\s+a\s+B\s+B\s*$" />
                    <has_line_matching expression="^5\s+c\s+C\s+5\s*$" />
                </assert_contents>
            </output>
        </test>
        <test expect_num_outputs="1" >
            <!-- Test 32: Ex 8 -->
            <conditional name="singtabop" >
                <param name="use_type" value="single" />
                <param name="input" value="examples.8.tsv" />
                <param name="col_row_names" value="has_col_names,has_row_names" />
                <conditional name="user" >
                    <param name="mode" value="fulltable" />
                    <conditional name="general" >
                        <param name="use" value="pivot" />
                        <param name="index" value="foo" />
                        <param name="column" value="bar" />
                        <param name="values" value="baz" />
                    </conditional>
                </conditional>
            </conditional>
            <output name="table" >
                <assert_contents>
                    <has_n_columns n="4" />
                    <has_line_matching expression="^one\s+1\s+2\s+3$" />
                    <has_line_matching expression="^two\s+4\s+5\s+6$" />
                </assert_contents>
            </output>
        </test>
    </tests>
    <help><![CDATA[
This tool computes table expressions on the element, row, and column basis. It can sub-select,
duplicate, as well as perform general and custom expressions on rows, columns or elements.

Only a single operation can be performed on the data. Multiple operations can be performed by
chaining successive runs of this tool. This is to provide a more transparent workflow for complex operations.



Examples
========

Example 1: Sub-selecting from a table
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

We have the following table:

 === === === ===
  .  c1  c2  c3
 === === === ===
 g1  10  20  30
 g2   3   6   9
 g3   4   8  12
 g4  81   6   3
 === === === ===

and we want to duplicate c1 and remove c2. Also select g1 to g3 and add g2 at the end as well. This would result in the output table:

 === === === ===
  .  c1  c1  c3
 === === === ===
 g1  10  10  30
 g2   3   3   9
 g3   4   4  12
 g2   3   3   9
 === === === ===

In Galaxy we would select the following:

 * *Input Single or Multiple Tables* → **Single Table**
 * *Column names on first row?* → **Yes**
 * *Row names on first column?* → **Yes**
 * *Type of table operation* →    **Drop, keep or duplicate rows and columns**

   * *List of columns to select* → **1,1,3**
   * *List of rows to select* → **1:3,2**
   * *Keep duplicate columns* → **Yes**
   * *Keep duplicate rows* → **Yes**

Example 2: Filter for rows with row sums less than 50
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

We have the following table:

 === === === ===
  .  c1  c2  c3
 === === === ===
 g1  10  20  30
 g2   3   6   9
 g3   4   8  12
 g4  81   6   3
 === === === ===

and we want:

 === === === ===
  .  c1  c2  c3
 === === === ===
 g2   3   6   9
 g3   4   8  12
 === === === ===

In Galaxy we would select the following:

 * *Input Single or Multiple Tables* → **Single Table**
 * *Column names on first row?* → **Yes**
 * *Row names on first column?* → **Yes**
 * *Type of table operation* →    **Filter rows or columns by their properties**

   * *Filter* → **Rows**
   * *Filter Criterion* → **Result of function applied to columns/rows**

     * *Keep column/row if its observed* → **Sum**
     * *is* → **< (Less Than)**
     * *this value* → **50**


Example 3: Count the number of values per row smaller than a specified value
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

We have the following table:

 === === === ===
  .  c1  c2  c3
 === === === ===
 g1  10  20  30
 g2   3   6   9
 g3   4   8  12
 g4  81   6   3
 === === === ===

and we want to count how many elements in each row are smaller than 10, i.e.,
we want to obtain the following results table:

 === ===
  .  vec
 === ===
 g1   0
 g2   3
 g3   2
 g4   2
 === ===

In Galaxy we would select the following:

 * *Input Single or Multiple Tables* → **Single Table**
 * *Column names on first row?* → **Yes**
 * *Row names on first column?* → **Yes**
 * *Type of table operation* →    **Manipulate selected table elements**

   * *Operation to perform* → **Custom**

     * *Custom Expression on 'elem'* → **elem < 10**

   * *Operate on elements* → **All**

**Note:** *There are actually simpler ways to achieve our purpose, but here we are demonstrating the use of a custom expression.*

After executing, we would then be presented with a table like so:

 === ===== ===== =====
  .     c1    c2    c3
 === ===== ===== =====
 g1  False False False
 g2  True  True  True
 g3  True  True  False
 g4  False True  True
 === ===== ===== =====

To get to our desired table, we would then process this table with the tool again:

 * *Input Single or Multiple Tables* → **Single Table**
 * *Column names on first row?* → **Yes**
 * *Row names on first column?* → **Yes**
 * *Type of table operation* →    **Compute Expression across Rows or Columns**

   * *Calculate* → **Sum**
   * *For each* → **Row**

Executing this will sum all the 'True' values in each row. Note that the values must have no extra whitespace in them for this to work (e.g. 'True ' or ' True' will not be parsed correctly).


Example 4: Perform a scaled log-transformation conditionally
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

We want to perform a scaled log transformation on all values greater than 5, and set all other values to 1.

We have the following table:

 === === === ===
  .  c1  c2  c3
 === === === ===
 g1   0  20  30
 g2   3   0   9
 g3   4   8   0
 g4  81   0   0
 === === === ===

and we want:

 === ========== ========= =========
  .          c1        c2        c3
 === ========== ========= =========
 g1  1.00000000 0.1497866 0.1133732
 g2  1.00000000 1.0000000 0.2441361
 g3  1.00000000 0.2599302 1.0000000
 g4  0.05425246 1.0000000 1.0000000
 === ========== ========= =========

In Galaxy we would select the following:

 * *Input Single or Multiple Tables* → **Single Table**
 * *Column names on first row?* → **Yes**
 * *Row names on first column?* → **Yes**
 * *Type of table operation* →  **Manipulate selected table elements**

   * *Operation to perform* → **Custom**

     * *Custom Expression* → ::

         (math.log(elem) / elem) if (elem > 5) else 1

     * *Operate on elements* → **All**


Example 5: Perform a Full table operation
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

We have the following table:

 === === === ===
  .  c1  c2  c3
 === === === ===
 g1  10  20  30
 g2   3  10   9
 g3   4   8  10
 g4  81  10  10
 === === === ===

and we want to subtract from each column the mean of that column divided by the standard deviation of it to yield:


 === ========= ========= =========
  .         c1        c2        c3
 === ========= ========= =========
 g1   9.351737 17.784353 28.550737
 g2   2.351737  7.784353  7.550737
 g3   3.351737  5.784353  8.550737
 g4  80.351737  7.784353  8.550737
 === ========= ========= =========

In Galaxy we would select the following:

 * *Input Single or Multiple Tables* → **Single Table**
 * *Column names on first row?* → **Yes**
 * *Row names on first column?* → **Yes**
 * *Type of table operation* →  **Perform a Full Table Operation**

   * *Operation* → **Custom**

   * *Custom Expression on 'table' along axis (0 or 1)* → ::

      table - table.mean(0)/table.std(0)


Example 6: Perform operations on multiple tables
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

We have the following three input tables:

Table 1

 === === === ===
  .  c1  c2  c3
 === === === ===
 g1  10  20  30
 g2   3  10   9
 g3   4   8  10
 === === === ===

Table 2

 === === ===
  .  c1  c2
 === === ===
 g1   1   2
 g2   3   4
 g3   6   5
 === === ===

Table 3

 === === === ===
  .  c1  c2  c3
 === === === ===
 g1   1   2   3
 g2   1   2   3
 === === === ===


*Note that the dimensions of these tables do not match.*

Dimensions:
 * Table1 [3,3]
 * Table2 [3,2]
 * Table3 [2,3]

In order to perform simple operations between Tables, they must be of the same dimensions.

To add Table2 to Table3 we would have to transpose one of the tables using the in-built `T` method::

    table2 + table3.T

or::

    table2.T + table3

We can also perform more general operations using all 3 tables, such as taking the minimum value of
the maximum values of Table2 and Table3, and dividing the Table1 values by it::

    table1 / min(table2.values.max(), table3.values.max())


To perform these types of operations in Galaxy we would select the following:

 * *Input Single or Multiple Tables* → **Multiple Tables**
 * *(For each inserted table)*
    * *Column names on first row?* → **Yes**
    * *Row names on first column?* → **Yes**
 * *Custom Expression* → ::

    <insert your desired function>

Please note that the last example shown above was chosen to illustrate the
limitations of the tool. Nested attributes like `table2.values.max` are
disallowed in expressions in the tool so the above would have to be replaced
with the harder to read workaround::

    table1 / min(np.max(np.max(table2)), np.max(np.max(table3)))

Also note that, currently `min()`, `max()` and `sum()` are the only built-in
Python functions that can be used inside expressions. If you want to use
additional functions, these have to be qualified functions from the `math`,
`np` or `pd` libraries.


Example 7: Melt
~~~~~~~~~~~~~~~

We have the following table

 === === === ===
  .   A   B   C
 === === === ===
  0   a   B   1
  1   b   B   3
  2   c   B   5
 === === === ===

and we want:

 === === ======== =====
  .   A  variable value
 === === ======== =====
  0   a     B       B
  1   b     B       B
  2   c     B       B
  3   a     C       1
  4   b     C       3
  5   c     C       5
 === === ======== =====


In Galaxy we would select the following:

 * *Input Single or Multiple Tables* → **Single Table**
 * *Column names on first row?* → **Yes**
 * *Row names on first column?* → **Yes**
 * *Type of table operation* →  **Perform a Full Table Operation**

   * *Operation* → **Melt**
   * *Variable IDs* → "A"
   * *Unpivoted IDs* → "B,C"

This converts the "B" and "C" columns into variables.


Example 8: Pivot
~~~~~~~~~~~~~~~~

We have the following table

 === === === === ===
  .  foo bar baz zoo
 === === === === ===
  0  one  A   1   x
  1  one  B   2   y
  2  one  C   3   z
  3  two  A   4   q
  4  two  B   5   w
  5  two  C   6   t
 === === === === ===

and we want:

 === === === ===
  .   A   B   C
 === === === ===
 one  1   2   3
 two  4   5   6
 === === === ===

In Galaxy we would select the following:

 * *Input Single or Multiple Tables* → **Single Table**
 * *Column names on first row?* → **Yes**
 * *Row names on first column?* → **Yes**
 * *Type of table operation* →  **Perform a Full Table Operation**

   * *Operation* → **Pivot**
   * *Index* → "foo"
   * *Column* → "bar"
   * *Values* → "baz"

This splits the matrix using "foo" and "bar" using only the values from "baz". Header values may contain extra information.

]]></help>
    <citations></citations>
</tool>