from dataclasses import dataclass
import pandas as pd

from util.constants import NO_DRIFT, DRIFTED, DRIFT_PART
from util.data_prepare import percent_change

DRIFTED_STR = 'DRIFTED'
NO_DRIFT_STR = 'NO_DRIFT'
DRIFT_PART_STR = 'DRIFT_PART'

DRIFT_STR_DICT = {
    NO_DRIFT :   NO_DRIFT_STR,
    DRIFTED :    DRIFTED_STR,
    DRIFT_PART : DRIFT_PART_STR,
}

TREND_DRIFT_TYPE = 'TREND'
LEVEL_DRIFT_TYPE = 'LEVEL'

CONSTANT_INPUT = 'CONSTANT_INPUT'
SHORT_INPUT = 'SHORT_INPUT'
EMPTY_INPUT = 'EMPTY_INPUT'

INPUT_MIN_DATA_POINT = 85
INPUT_MIN_TIME_LENGTH = pd.Timedelta(days=85)

@dataclass
class SegmentInfo:
    idx_start       : int
    idx_end         : int
    val_start       : float
    val_end         : float

    part_or_whole   : int = NO_DRIFT
    idx_threshold   : int = -1

    drift_type      : str           = None
    start_time      : pd.Timestamp  = None
    end_time        : pd.Timestamp  = None
    threshold_time  : pd.Timestamp  = None   

    def length(self):
        return self.idx_end - self.idx_start
    
    def percent_drift(self):
        return percent_change(self.val_start, self.val_end)

    def __str__(self):
        return f'({self.length()}, {self.percent_drift():.1f}%)'
    

def summarize_drift_result(segments):
    drifted_indexes = [i for (i, seg) in enumerate(segments) if seg.part_or_whole == DRIFTED]
    
    if len(drifted_indexes) == 0: # No drifts
        return []
    
    rslt = []
    idx_pre = -1
    for idx in drifted_indexes:
        drift_end = segments[idx].idx_end

        drift_types = []
        for i in range(idx, idx_pre, -1):
            seg = segments[i]
            if seg.part_or_whole == NO_DRIFT:
                break
            drift_types.append(seg.drift_type)
            drift_start = seg.idx_start
       
        rslt.append((list(reversed(drift_types)), drift_end - drift_start))       
        idx_pre = idx

    return rslt