comparison plotly_tabular_tool/plotlytabular.xml @ 1:449c918bc4cd draft

Uploaded

0:7c166107a2e2

<tool name="plotlytabular" id="plotlytabular" version="3.0">
  <!--Source in git at: https://github.com/fubar2/galaxy_tf_overlay-->
  <!--Created by [e-mail] at 27/07/2023 18:47:26 using the Galaxy Tool Factory.-->
  <description>Plotly plot generator</description>
  <requirements>
    <requirement version="1.5.3" type="package">pandas</requirement>
    <requirement version="5.9.0" type="package">plotly</requirement>
  </requirements>

a('--ycol',default='')
a('--colourcol',default='')
a('--hovercol',default='')
a('--title',default='Default plot title')
args = parser.parse_args()
df = pd.read_csv(args.input_tab, sep='\t')
MAXLEN=35
NCOLS = df.columns.size
defaultcols = ['col%d' % (x+1) for x in range(NCOLS)]
if len(args.header.strip()) > 0:
    newcols = args.header.split(',')
    if len(newcols) == NCOLS:
        df.columns = newcols
    else:
        sys.stderr.write('#### Supplied header %s has %d comma delimited header names - does not match the input tabular file %d columns - using col1,...coln' % (args.header, len(newcols), NCOLS))
        df.columns = defaultcols
else:
    df.columns = defaultcols
#df['col11'] = [-math.log(x) for x in df['col11']] # convert so large values reflect statistical surprise
isColour = False
isHover = False
if len(args.colourcol.strip()) > 0:
    isColour = True
if len(args.hovercol.strip()) > 0:
    isHover = True
if isHover and isColour:
    fig = px.scatter(df, x=args.xcol, y=args.ycol, color=args.colourcol, hover_name=args.hovercol)
elif isHover:
    fig = px.scatter(df, x=args.xcol, y=args.ycol, hover_name=args.hovercol)
elif isColour:

#end raw]]></configfile>
  </configfiles>
  <inputs>
    <param name="input_tab" type="data" optional="false" label="Tabular input file to plot" help="" format="tabular" multiple="false"/>
    <param name="xcol" type="text" value="col1" label="x axis for plat" help=""/>
    <param name="ycol" type="text" value="col12" label="y axis for plot" help=""/>
    <param name="colourcol" type="text" value="col2" label="column containing a groupable variable for colour. Default none." help="Adds a legend so choose wisely "/>
    <param name="hovercol" type="text" value="col21" label="columname for hover string" help=""/>
    <param name="title" type="text" value="default title" label="Title for the plot" help="Special characters will probably be escaped so do not use them"/>
    <param name="header" type="text" value="" label="Use this comma delimited list of column header names for this tabular file. Default is None when col1...coln will be used" help="Default for Galaxy blast outputs with 25 columns. The column names supplied for xcol, ycol, hover and colour MUST match either the supplied list, or if none, col1...coln."/>
  </inputs>
  <outputs>
    <data name="htmlout" format="html" label="htmlout" hidden="false"/>
  </outputs>
  <tests>
    <test>
      <output name="htmlout" value="htmlout_sample" compare="sim_size" delta="5000"/>
      <param name="input_tab" value="input_tab_sample"/>
      <param name="xcol" value="col1"/>
      <param name="ycol" value="col12"/>
      <param name="colourcol" value="col2"/>
      <param name="hovercol" value="col21"/>
      <param name="title" value="default title"/>
      <param name="header" value=""/>
    </test>
  </tests>
  <help><![CDATA[

    a('--ycol',default='')
    a('--colourcol',default='')
    a('--hovercol',default='')
    a('--title',default='Default plot title')
    args = parser.parse_args()
    df = pd.read_csv(args.input_tab, sep='\t')
    MAXLEN=35
    NCOLS = df.columns.size
    defaultcols = ['col%d' % (x+1) for x in range(NCOLS)]
    if len(args.header.strip()) > 0:
        newcols = args.header.split(',')
        if len(newcols) == NCOLS:
            df.columns = newcols
        else:
            sys.stderr.write('#### Supplied header %s has %d comma delimited header names - does not match the input tabular file %d columns - using col1,...coln' % (args.header, len(newcols), NCOLS))
            df.columns = defaultcols
    else:
        df.columns = defaultcols
    #df['col11'] = [-math.log(x) for x in df['col11']] # convert so large values reflect statistical surprise
    isColour = False
    isHover = False
    if len(args.colourcol.strip()) > 0:
        isColour = True
    if len(args.hovercol.strip()) > 0:
        isHover = True
    if isHover and isColour:
        fig = px.scatter(df, x=args.xcol, y=args.ycol, color=args.colourcol, hover_name=args.hovercol)
    elif isHover:
        fig = px.scatter(df, x=args.xcol, y=args.ycol, hover_name=args.hovercol)
    elif isColour:

1:449c918bc4cd

<tool name="plotlytabular" id="plotlytabular" version="3.0">
  <!--Source in git at: https://github.com/fubar2/galaxy_tf_overlay-->
  <!--Created by [e-mail] at 28/07/2023 13:36:22 using the Galaxy Tool Factory.-->
  <description>Plotly plot generator</description>
  <requirements>
    <requirement version="1.5.3" type="package">pandas</requirement>
    <requirement version="5.9.0" type="package">plotly</requirement>
  </requirements>

a('--ycol',default='')
a('--colourcol',default='')
a('--hovercol',default='')
a('--title',default='Default plot title')
args = parser.parse_args()
isColour = False
isHover = False
if len(args.colourcol.strip()) > 0:
    isColour = True
if len(args.hovercol.strip()) > 0:
    isHover = True
df = pd.read_csv(args.input_tab, sep='\t')
MAXLEN=35
NCOLS = df.columns.size
defaultcols = ['col%d' % (x+1) for x in range(NCOLS)]
testcols = df.columns
if len(args.header.strip()) > 0:
    newcols = args.header.split(',')
    if len(newcols) == NCOLS:
        df.columns = newcols
    else:
        sys.stderr.write('#### Supplied header %s has %d comma delimited header names - does not match the input tabular file %d columns - using col1,...coln' % (args.header, len(newcols), NCOLS))
        df.columns = defaultcols
else: # no header supplied - check for a real one that matches the x and y axis column names
    colsok = (args.xcol in testcols) and (args.ycol in testcols) # if they match, probably ok...should use more code and logic..
    if not colsok:
        sys.stderr.write('replacing supplied header %s over existing %s' % (testcols, defaultcols))
        df.columns = defaultcols
#df['col11'] = [-math.log(x) for x in df['col11']] # convert so large values reflect statistical surprise
if isHover and isColour:
    fig = px.scatter(df, x=args.xcol, y=args.ycol, color=args.colourcol, hover_name=args.hovercol)
elif isHover:
    fig = px.scatter(df, x=args.xcol, y=args.ycol, hover_name=args.hovercol)
elif isColour:

#end raw]]></configfile>
  </configfiles>
  <inputs>
    <param name="input_tab" type="data" optional="false" label="Tabular input file to plot" help="" format="tabular" multiple="false"/>
    <param name="xcol" type="text" value="sepal_length" label="x axis for plot" help=""/>
    <param name="ycol" type="text" value="sepal_width" label="y axis for plot" help=""/>
    <param name="colourcol" type="text" value="petal_width" label="column containing a groupable variable for colour. Default none." help="Adds a legend so choose wisely "/>
    <param name="hovercol" type="text" value="species_id" label="columname for hover string" help=""/>
    <param name="title" type="text" value="Iris data sepal length by sepal width coloured by petal width with species_id as the hover column" label="Title for the plot" help="Special characters will probably be escaped so do not use them"/>
    <param name="header" type="text" value="" label="Use this comma delimited list of column header names for this tabular file. Default is None when col1...coln will be used" help="Default for Galaxy blast outputs with 25 columns. The column names supplied for xcol, ycol, hover and colour MUST match either the supplied list, or if none, col1...coln."/>
  </inputs>
  <outputs>
    <data name="htmlout" format="html" label="htmlout" hidden="false"/>
  </outputs>
  <tests>
    <test>
      <output name="htmlout" value="htmlout_sample" compare="sim_size" delta="5000"/>
      <param name="input_tab" value="input_tab_sample"/>
      <param name="xcol" value="sepal_length"/>
      <param name="ycol" value="sepal_width"/>
      <param name="colourcol" value="petal_width"/>
      <param name="hovercol" value="species_id"/>
      <param name="title" value="Iris data sepal length by sepal width coloured by petal width with species_id as the hover column"/>
      <param name="header" value=""/>
    </test>
  </tests>
  <help><![CDATA[

    a('--ycol',default='')
    a('--colourcol',default='')
    a('--hovercol',default='')
    a('--title',default='Default plot title')
    args = parser.parse_args()
    isColour = False
    isHover = False
    if len(args.colourcol.strip()) > 0:
        isColour = True
    if len(args.hovercol.strip()) > 0:
        isHover = True
    df = pd.read_csv(args.input_tab, sep='\t')
    MAXLEN=35
    NCOLS = df.columns.size
    defaultcols = ['col%d' % (x+1) for x in range(NCOLS)]
    testcols = df.columns
    if len(args.header.strip()) > 0:
        newcols = args.header.split(',')
        if len(newcols) == NCOLS:
            df.columns = newcols
        else:
            sys.stderr.write('#### Supplied header %s has %d comma delimited header names - does not match the input tabular file %d columns - using col1,...coln' % (args.header, len(newcols), NCOLS))
            df.columns = defaultcols
    else: # no header supplied - check for a real one that matches the x and y axis column names
        colsok = (args.xcol in testcols) and (args.ycol in testcols) # if they match, probably ok...should use more code and logic..
        if not colsok:
            sys.stderr.write('replacing supplied header %s over existing %s' % (testcols, defaultcols))
            df.columns = defaultcols
    #df['col11'] = [-math.log(x) for x in df['col11']] # convert so large values reflect statistical surprise
    if isHover and isColour:
        fig = px.scatter(df, x=args.xcol, y=args.ycol, color=args.colourcol, hover_name=args.hovercol)
    elif isHover:
        fig = px.scatter(df, x=args.xcol, y=args.ycol, hover_name=args.hovercol)
    elif isColour: