from openpyxl import load_workbook
from os import scandir
from os.path import exists
from sys import argv
from pandas import read_csv
from re import match
from threading import Thread
from time import sleep

class GetThreadResult(Thread):
    def __init__(self, func, args=()):
        super(GetThreadResult, self).__init__()
        self.func = func
        self.args = args
        self.result = 0

    def run(self):
        sleep(1)
        self.result = self.func(*self.args)

    def get_result(self):
        Thread.join(self)  # 等待线程执行完毕
        try:
            return self.result
        except Exception as Err:
            return None


def w2t_local(msg, wait, w2t):
    while True:
        global stop
        if stop == 0 and wait != 0:
            sleep(1)
            w2t(msg, wait)
        else:
            break


def traversal_files(path, w2t):
    # 功能：以列表的形式分别返回指定路径下的文件和文件夹，不包含子目录
    # 参数：路径
    # 返回值：路径下的文件夹列表 路径下的文件列表
    if not exists(path):
        msg = f'数据文件夹{path}不存在，请确认后重试......'
        w2t(msg, 0, 1)
    else:
        dirs = []
        files = []
        for item in scandir(path):
            if item.is_dir():
                dirs.append(item.path)
            elif item.is_file():
                files.append(item.path)

        return dirs, files


def initialization(path, sub, w2t):
    _, data_files = traversal_files(path, w2t)
    count = 0

    for data_file in data_files:
        filename = data_file.split('\\')[-1]
        if sub != 'cycle':
            if not (match('j[1-7].*\\.data', filename) or match('j[1-7].*\\.csv', filename)):
                msg = f"所有文件必须以 jx_ 开头，以 .data/csv 结尾（x取值1-7），请检查后重新运行。"
                w2t(msg, 0, 2)
        else:
            if filename.endswith('.xlsx'):
                count += 1
            elif not (match('j[1-7].*\\.data', filename) or match('j[1-7].*\\.csv', filename)):
                msg = f"所有文件必须以 jx_ 开头，以 .data/csv 结尾（x取值1-7），请检查后重新运行。"
                w2t(msg, 0, 3)

    if sub == 'cycle' and count != 1:
        w2t("未找到电机电流数据处理excel表格，确认后重新运行！", 0, 4)

    return data_files


def current_max(data_files, rcs, trqh, w2t):
    current = {1: 0, 2: 0, 3: 0, 4: 0, 5: 0, 6: 0, 7: 0}
    for data_file in data_files:
        if data_file.endswith('.data'):
            df = read_csv(data_file, sep='\t')
        elif data_file.endswith('.csv'):
            df = read_csv(data_file, sep=',', encoding='gbk', header=8)

        axis = int(data_file.split('\\')[-1].split('_')[0].removeprefix('j'))
        rca = rcs[axis-1]

        col = df.columns.values[trqh-1]
        c_max = df[col].max()

        scale = 1 if data_file.endswith('.csv') else 1000
        _ = abs(c_max/scale*rca)
        current[axis] = _
        w2t(f"{data_file}: {_:.4f}")

    w2t("【MAX】数据处理完毕......")
    return current


def current_avg(data_files, rcs, trqh, w2t):
    current = {1: 0, 2: 0, 3: 0, 4: 0, 5: 0, 6: 0, 7: 0}
    for data_file in data_files:
        if data_file.endswith('.data'):
            df = read_csv(data_file, sep='\t')
        elif data_file.endswith('.csv'):
            df = read_csv(data_file, sep=',', encoding='gbk', header=8)

        axis = int(data_file.split('\\')[-1].split('_')[0].removeprefix('j'))
        rca = rcs[axis-1]

        col = df.columns.values[trqh - 1]
        c_std = df[col].std()
        c_avg = df[col].mean()

        scale = 1 if data_file.endswith('.csv') else 1000
        _ = (abs(c_avg)+c_std)/scale*rca
        current[axis] = _
        w2t(f"{data_file}: {_:.4f}")

    w2t("【AVG】数据处理完毕......")
    return current


def current_cycle(dur, data_files, rcs, vel, trq, trqh, w2t):
    result = None
    hold = []
    single = []
    for data_file in data_files:
        filename = data_file.split('\\')[-1]
        if data_file.endswith('.xlsx'):
            result = data_file
        elif match('j[1-7]_hold_.*\\.data', filename) or match('j[1-7]_hold_.*\\.csv', filename):
            hold.append(data_file)
        else:
            single.append(data_file)

    w2t(f"正在打开文件 {result}，需要 10s 左右", 1)

    global stop
    stop = 0
    t_excel = GetThreadResult(load_workbook, args=(result, ))
    t_wait = Thread(target=w2t_local, args=('.', 1, w2t))
    t_excel.start()
    t_wait.start()
    t_excel.join()
    wb = t_excel.get_result()
    stop = 1
    sleep(1.1)
    w2t('')

    if hold != []:
        avg = current_avg(hold, rcs, trqh, w2t)
        for axis, cur_value in avg.items():
            try:
                shtname = f"J{axis}"
                wb[shtname]["J4"].value = float(cur_value)
            except:
                pass

    if dur == 0:
        p_single(wb, single, vel, trq, w2t)
    else:
        p_scenario()

    w2t(f"正在保存文件 {result}，需要 10s 左右", 1)
    stop = 0
    t_excel = Thread(target=wb.save, args=(result, ))
    t_wait = Thread(target=w2t_local, args=('.', 1, w2t))
    t_excel.start()
    t_wait.start()
    t_excel.join()
    stop = 1
    sleep(1.1)
    w2t('\n')
    w2t("----------------------------------------------------------")
    w2t("全部处理完毕")


def p_single(wb, single, vel, trq, w2t):
    # 1. 先找到第一个速度为零的点，数据从后往前找，一开始就是零的情况不予考虑
    # 2. 记录第一个点的位置，继续向前查找第二个速度为零的点，同理，一开始为零的点不予考虑
    # 3. 记录第二个点的位置，并将其中的数据拷贝至对应位置
    for data_file in single:
        axis = int(data_file.split('\\')[-1].split('_')[0].removeprefix('j'))
        shtname = f"J{axis}"
        ws = wb[shtname]

        if data_file.endswith('.data'):
            df = read_csv(data_file, sep='\t')
        elif data_file.endswith('.csv'):
            df = read_csv(data_file, sep=',', encoding='gbk', header=8)

        # 过滤尾部无效数据
        _row_e = df.index[-1]
        _row_s = _row_e - 200
        while _row_e > 200:
            speed_avg = df.iloc[_row_s:_row_e, vel-1].abs().mean()
            if speed_avg > 2:
                _row_e -= 50
                _row_s -= 50
                continue
            else:
                break
        else:
            w2t("数据有误，需要检查，无法找到第一个有效起始点...", 0, 1)

        # 找到第一个起始点 row_end，继续找到有数据的部分
        row_end = _row_e - 100
        _row_e -= 200
        _row_s -= 200
        while _row_e > 200:
            speed_avg = df.iloc[_row_s:_row_e, vel-1].abs().mean()
            if speed_avg < 2:
                _row_e -= 50
                _row_s -= 50
                continue
            else:
                break
        else:
            w2t("数据有误，需要检查，无法找到第二个有效起始点...", 0, 2)

        # 目前已经有一点的速度值了，继续往前搜寻下一个速度为零的点
        _row_e -= 200
        _row_s -= 200
        while _row_e > 200:
            speed_avg = df.iloc[_row_s:_row_e, vel-1].abs().mean()
            if speed_avg > 2:
                _row_e -= 50
                _row_s -= 50
                continue
            else:
                break
        else:
            w2t("数据有误，需要检查，无法找到第三个有效起始点...", 0, 3)

        row_start = _row_s + 180
        data = []
        for row in range(row_start, row_end):
            data.append(df.iloc[row, vel-1])
            data.append(df.iloc[row, trq-1])

        i = 0
        for row in ws.iter_rows(min_row=2, min_col=2, max_row=15000, max_col=3):
            for cell in row:
                try:
                    cell.value = data[i]
                    i += 1
                except:
                    cell.value = None


def p_scenario():
    pass


# =======================================


def main(path, sub, rcs, vel, trq, trqh, dur, w2t):
    data_files = initialization(path, sub, w2t)
    if sub == 'max':
        current_max(data_files, rcs, trqh, w2t)
    elif sub == 'avg':
        current_avg(data_files, rcs, trqh, w2t)
    elif sub == 'cycle':
        current_cycle(dur, data_files, rcs, vel, trq, trqh, w2t)
    else:
        pass


if __name__ == '__main__':
    stop = 0
    main(*argv[1:])