#!/usr/bin/env python

""" MultiQC module to parse output from Kallisto """

from __future__ import print_function
from collections import OrderedDict
import os
import logging
import re

from multiqc import config
from multiqc.plots import bargraph
from multiqc.modules.base_module import BaseMultiqcModule

# Initialise the logger
log = logging.getLogger(__name__)

class MultiqcModule(BaseMultiqcModule):
    """ Kallisto module """

    def __init__(self):

        # Initialise the parent object
        super(MultiqcModule, self).__init__(name='Kallisto', anchor='kallisto',
        href="http://pachterlab.github.io/kallisto/",
        info="is a program for quantifying abundances of transcripts from RNA-Seq data.")

        # Find and load any Kallisto reports
        self.kallisto_data = dict()
        for f in self.find_log_files('kallisto', filehandles=True):
            self.parse_kallisto_log(f)

        # Filter to strip out ignored sample names
        self.kallisto_data = self.ignore_samples(self.kallisto_data)

        if len(self.kallisto_data) == 0:
            raise UserWarning

        log.info("Found {} reports".format(len(self.kallisto_data)))

        # Write parsed report data to a file
        self.write_data_file(self.kallisto_data, 'multiqc_kallisto')

        # Basic Stats Table
        self.kallisto_general_stats_table()

        # Alignment Rate Plot
        self.add_section( plot = self.kallisto_alignment_plot() )


    def parse_kallisto_log(self, f):
        s_name = total_reads = paligned_reads = fraglength = None
        for l in f['f']:

            # Get input filename
            match = re.search(r'\[quant\] will process (pair|file) 1: (\S+)', l)
            if match:
                s_name = self.clean_s_name(os.path.basename(match.group(2)), f['root'])

            if s_name is not None:
                # Alignment rates
                aligned = re.search(r'\[quant\] processed ([\d,]+) reads, ([\d,]+) reads pseudoaligned', l)
                if aligned:
                    total_reads = float(aligned.group(1).replace(',',''))
                    paligned_reads = float(aligned.group(2).replace(',',''))

                # Paired end fragment lengths
                flength = re.search(r'\[quant\] estimated average fragment length: ([\d\.]+)', l)
                if flength:
                    fraglength = float(flength.group(1).replace(',',''))

                if 'quantifying the abundances' in l:
                    if s_name in self.kallisto_data:
                        log.debug("Duplicate sample name found! Overwriting: {}".format(s_name))
                    self.add_data_source(f, s_name)
                    self.kallisto_data[s_name] = {
                        'total_reads': total_reads,
                        'pseudoaligned_reads': paligned_reads,
                        'not_pseudoaligned_reads': total_reads - paligned_reads,
                        'percent_aligned': (paligned_reads / total_reads) * 100
                    }
                    if fraglength is not None:
                        self.kallisto_data[s_name]['fragment_length'] = fraglength
                    s_name = total_reads = paligned_reads = fraglength = None

    def kallisto_general_stats_table(self):
        """ Take the parsed stats from the Kallisto report and add it to the
        basic stats table at the top of the report """

        headers = OrderedDict()
        headers['fragment_length'] = {
            'title': 'Frag Length',
            'description': 'Estimated average fragment length',
            'min': 0,
            'suffix': 'bp',
            'scale': 'RdYlGn'
        }
        headers['percent_aligned'] = {
            'title': '% Aligned',
            'description': '% processed reads that were pseudoaligned',
            'max': 100,
            'min': 0,
            'suffix': '%',
            'scale': 'YlGn'
        }
        headers['pseudoaligned_reads'] = {
            'title': '{} Aligned'.format(config.read_count_prefix),
            'description': 'Pseudoaligned reads ({})'.format(config.read_count_desc),
            'min': 0,
            'scale': 'PuRd',
            'modify': lambda x: x * config.read_count_multiplier,
            'shared_key': 'read_count'
        }
        self.general_stats_addcols(self.kallisto_data, headers)

    def kallisto_alignment_plot (self):
        """ Make the HighCharts HTML to plot the alignment rates """

        # Specify the order of the different possible categories
        keys = OrderedDict()
        keys['pseudoaligned_reads'] = { 'color': '#437bb1', 'name': 'Pseudoaligned' }
        keys['not_pseudoaligned_reads'] =   { 'color': '#b1084c', 'name': 'Not aligned' }

        # Config for the plot
        config = {
            'id': 'kallisto_alignment',
            'title': 'Kallisto: Alignment Scores',
            'ylab': '# Reads',
            'cpswitch_counts_label': 'Number of Reads'
        }

        return bargraph.plot(self.kallisto_data, keys, config)
