#!/usr/bin/env python3

# -*- coding: utf-8 -*-

from matplotlib.ticker import MaxNLocator

import matplotlib.pyplot as plt

from .statistic import StatisticHistogram

import singlecellmultiomics.pyutils as pyutils

import collections

import matplotlib

matplotlib.rcParams['figure.dpi'] = 160

matplotlib.use('Agg')

class OversequencingHistogram(StatisticHistogram):

    def __init__(self, args):

        StatisticHistogram.__init__(self, args)

        self.histogram = collections.Counter()

    def processRead(self, R1,R2=None):

        for read in [R1, R2]:

            if read is None:

                continue

            if read.has_tag('RC'):

                overseq = read.get_tag('RC')

                self.histogram[overseq] += 1

                if overseq > 1:

                    self.histogram[overseq - 1] -= 1

                # Compatibility with picard --TAG_DUPLICATE_SET_MEMBERS

                """

                java -jar `which picard.jar` MarkDuplicates I=sorted.bam O=marked_duplicates.bam M=marked_dup_metrics.txt TAG_DUPLICATE_SET_MEMBERS=1

                """

            elif read.has_tag('PG'):

                if read.has_tag('DS') and not read.is_duplicate:

                    self.histogram[read.get_tag('DS')] += 1

                else:

                    self.histogram[1] += 1

            break

    def __repr__(self):

        return f'The average oversequencing is {pyutils.meanOfCounter(self.histogram)}, SD:{pyutils.varianceOfCounter(self.histogram)}'

    def plot(self, target_path, title=None):

        fig, ax = plt.subplots()

        overseqRange = list(range(1, 20))

        ax.scatter(overseqRange, [self.histogram[x] for x in overseqRange])

        if title is not None:

            ax.set_title(title)

        ax.xaxis.set_major_locator(MaxNLocator(integer=True))

        ax.set_xlabel("Amount of fragments associated with molecule")

        ax.set_ylabel("# Molecules")

        plt.tight_layout()

        plt.savefig(target_path)

        ax = plt.gca()

        ax.set_ylim(1, None)

        ax.set_yscale('log')

        plt.savefig(target_path.replace('.png', '.log.png'))

        plt.close()