from .DataStream import ENetPosmap as pos_map, day_stamp, span_days, time_border, calc_interval
from .NetchkReader import NetchkReader
from .PainterBase import PainterBase
from matplotlib.figure import Figure
from matplotlib import ticker
from io import BytesIO
import numpy as np
import time as time

import logging
logger = logging.getLogger('ChannelPainter')

_all_net_channels = set()
def _add_net_channel(channel):
    if channel not in _all_net_channels:
        _all_net_channels.add(channel)

def get_net_channels():
    logger.debug(_all_net_channels)
    return list(_all_net_channels)

def net_pathes(reader: NetchkReader, names: set, days: list):
    count = len(days)
    if len(names) > 1:
        _all_data = reader.init_data(count)
    else:
        _all_data = None

    for name in names:
        _add_net_channel(name)
        _ch_data = reader.init_data(count)

        for i, day in enumerate(days):
            data = reader.read(day, name)
            if data is not None:
                column_pos = i * 86400
                view = _ch_data[:, column_pos:column_pos + 86400]
                view += data

        if _all_data is not None:
            _all_data += _ch_data
        yield name, _ch_data

    if _all_data is not None:
        yield 'all', _all_data


class NetcheckPainter(PainterBase):
    def _fig_funs(self):
        def create():
            fig = Figure(figsize=(19, 8))
            ax = fig.subplots()
            ax.set_title('success ratio')
            ax.set(xlabel='time', ylabel='ratio')
            return ax, fig

        def flush(ax, fig, ticks, lables):
            ax.yaxis.set_major_formatter(ticker.PercentFormatter(xmax=1, decimals=4))
            ax.set_xticks(ticks=ticks)
            ax.set_xticklabels(lables)
            fig.autofmt_xdate()
            ax.grid()
            # fig.subplots_adjust(left=0.1, right=0.8, top=0.95, bottom=0.1)
            ax.legend(bbox_to_anchor=(1, 1), loc='upper left')
            fig.tight_layout()

            buf = BytesIO()
            fig.savefig(buf, format="png")
            return buf

        return create, flush

    def _label(self, chname, succ, count):
        lable = f"{chname}"
        if count > 0:
            ratio = round(succ * 100 / count, 5)
        else:
            ratio = 0.00
        lable += f":{succ}/{count}={ratio}%"

        return lable, ratio