comparison paracords_plot.py @ 2:9958188c6195 draft default tip

"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/plotly_parallel_coordinates_plot commit b26c6ec671ec63cce1f86c70e928673ed2c82f82"

1:7b21a9b5922f

import sys
import argparse
import plotly
import plotly.graph_objs as go
import pandas as pd

def main(infile, col_dimensions, categorized, col_color):
    """
    Produce an interactive paracords plotting html
    Args:
        infile: str, tabular file
        col_dimensions: str, comma separated index numbers. For example: "3,4,5"
        col_color: str, index number
    """
    df = pd.read_csv(infile, sep='\t', parse_dates=True)

    dimensions = []
    col_dimensions = [int(x)-1 for x in col_dimensions.split(',')]
    for col in col_dimensions:
        values = df[df.columns[col]]
        if categorized == 'boolfalse' and all(type(e) is int for e in values ):
            dimensions.append(
                dict(   values = values,
                        tickformat = ",.2r",
                        label = df.columns[col])
            )
        elif categorized == 'boolfalse' and all(type(e) is float for e in values ):
            dimensions.append(
                dict(   values = values,
                        tickformat = "g",
                        label = df.columns[col])
            )
        else:
            unique_values = list(set(values))
            unique_values.sort()
            dimensions.append(
                dict(   range = [0, len(unique_values)-1],
                        tickvals = list(range(len(unique_values))),
                        ticktext = [str(e) for e in unique_values],
                        values = list(map(lambda e: unique_values.index(e), values )),
                        label = df.columns[col])
            )

    col_color = int(col_color) - 1
    colors = df[df.columns[col_color]]
    if all(type(e) is int for e in colors ):

    aparser = argparse.ArgumentParser()
    aparser.add_argument( "-i", "--input", dest="infile", required=True)
    aparser.add_argument( "-d", "--col_dimensions", dest="col_dimensions")
    aparser.add_argument( "-t", "--categorized_datatype", dest="categorized")
    aparser.add_argument( "-c", "--col_color", dest="col_color")
    args = aparser.parse_args()

    main(args.infile, args.col_dimensions, args.categorized, args.col_color)

2:9958188c6195

import sys
import argparse
import plotly
import plotly.graph_objs as go
import pandas as pd
import re


def main(infile, col_dimensions, categorized, col_color,
         dimension_mode='by_index'):
    """
    Produce an interactive paracords plotting html
    Args:
        infile: str, tabular file
        col_dimensions: str, comma separated index numbers. For example: "3,4,5"
        col_color: str, index number
        dimension_mode: str, one ['by_index', 'by_name']
    """
    df = pd.read_csv(infile, sep='\t', parse_dates=True)

    dimensions = []

    if dimension_mode not in ['by_index', 'by_name']:
        raise ValueError("Select dimensions `{}` is not supported!"\
                         .format(dimension_mode))
    if dimension_mode == 'by_index':
        col_dimensions = [int(x)-1 for x in col_dimensions.split(',')]
        col_dimensions = df.columns[col_dimensions]
    else:
        if '*' not in col_dimensions:
            col_dimensions = [header.strip() for header in col_dimensions.split(',')]
        else:
            pattern = col_dimensions.strip()
            col_dimensions = [header for header in df.columns
                              if re.search(pattern, header)]

    for col_name in col_dimensions:
        values = df[col_name]
        if categorized == 'boolfalse' and all(type(e) is int for e in values ):
            dimensions.append(
                dict(   values = values,
                        tickformat = ",.2r",
                        label = col_name)
            )
        elif categorized == 'boolfalse' and all(type(e) is float for e in values ):
            dimensions.append(
                dict(   values = values,
                        tickformat = "g",
                        label = col_name)
            )
        else:
            unique_values = list(set(values))
            unique_values.sort()
            # cast to str, fix object indexing
            unique_values = [repr(e) for e in unique_values]
            dimensions.append(
                dict(   range = [0, len(unique_values)-1],
                        tickvals = list(range(len(unique_values))),
                        ticktext = unique_values,
                        values = list(map(lambda e: unique_values.index(repr(e)), values )),
                        label = col_name)
            )

    col_color = int(col_color) - 1
    colors = df[df.columns[col_color]]
    if all(type(e) is int for e in colors ):

    aparser = argparse.ArgumentParser()
    aparser.add_argument( "-i", "--input", dest="infile", required=True)
    aparser.add_argument( "-d", "--col_dimensions", dest="col_dimensions")
    aparser.add_argument( "-t", "--categorized_datatype", dest="categorized")
    aparser.add_argument( "-c", "--col_color", dest="col_color")
    aparser.add_argument( "-m", "--dimension_mode", dest="dimension_mode")
    args = aparser.parse_args()

    main(args.infile, args.col_dimensions, args.categorized, args.col_color,
         args.dimension_mode)