from .statistic import StatisticHistogram

import singlecellmultiomics.pyutils as pyutils

import collections

import pandas as pd

import matplotlib.pyplot as plt

import seaborn as sns

class MappingQualityHistogram(StatisticHistogram):

    def __init__(self, args):

        StatisticHistogram.__init__(self, args)

        self.histogram = collections.Counter()

    def processRead(self, R1,R2):

        for read in [R1,R2]:

            if read is None:

                continue

            self.histogram[read.mapping_quality] += 1

    def __repr__(self):

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

    def get_df(self):

        return pd.DataFrame.from_dict({'mq': self.histogram})

    def to_csv(self, path):

        self.get_df().to_csv(path)

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

        df = self.get_df()  # ,'UnmappedReads']]

        df['mq'].plot.bar(figsize=(10, 4))

        ax = plt.gca()

        ax.set_xlabel('Mapping quality')

        ax.set_ylabel('Frequency (reads)')

        if title is not None:

            plt.title(title)

        plt.tight_layout()

        plt.savefig(target_path)

        ax.set_yscale('log')

        sns.despine()

        plt.tight_layout()

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

        plt.close()