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import numpy as np

import scipy.ndimage as nd

import logging

import random

# DO NOT IMPORT CPICIMGSIM MODULES HERE

class Logger(object):

    def __init__(self, filename, level='INFO'):

        self.logger = logging.getLogger('cpism_log')

        self.logger.setLevel(logging.DEBUG)

        shinfo = logging.StreamHandler()

        onlyinfo = logging.Filter()

        onlyinfo.filter = lambda record: (record.levelno < logging.WARNING)

        fmtstr = '%(message)s'

        shinfo.setFormatter(logging.Formatter(fmtstr))  # 设置屏幕上显示的格式

        shinfo.setLevel(logging.INFO)

        shinfo.addFilter(onlyinfo)

        sh = logging.StreamHandler()

        fmtstr = '!%(levelname)s!: %(message)s [%(filename)s - %(funcName)s (line: %(lineno)d)]: '

        sh.setFormatter(logging.Formatter(fmtstr))  # 设置屏幕上显示的格式

        sh.setLevel(logging.WARNING)

        th = logging.FileHandler(filename)  # 往文件里写入#指定间隔时间自动生成文件的处理器

        fmtstr = '%(asctime)s %(filename)s [%(funcName)s] - %(levelname)s: %(message)s'

        th.setFormatter(logging.Formatter(fmtstr))  # 设置文件里写入的格式

        th.setLevel(logging.__dict__.get(level.upper()))

        self.logger.addHandler(shinfo)

        self.logger.addHandler(sh)

        self.logger.addHandler(th)

def random_seed_select(seed=-1):

    """

    Select a random seed for numpy.random and return it.

    """

    if seed == -1:

        seed = random.randint(0, 2**32-1)

    np.random.seed(seed)

    return seed

def region_replace(

    background: np.ndarray,

    front: np.ndarray,

    shift: list,

    bmask: float = 1.0,

    fmask: float = 1.0,

    padded_in: bool = False,

    padded_out: bool = False,

    subpix: bool = False

):

    """

    replace a region of the background with the front image.

    Parameters

    ----------

    background: np.ndarray

        The background image.

    front: np.ndarray

        The front image.

    shift: list

        The [x, y] shift of the front image. Unit: pixel.

        Relative to the lower-left corner of the background image.

        [0, 0] means the lower-left corner of the front image is at the lower-left corner of the background image. 

    bmask: float

        The mask of the background image. Default: 1.0

        0.0 means the background image is masked.

        1.0 means the background image is fully added.

    fmask: float

        The mask of the front image. Default: 1.0

        0.0 means the front image is masked (not added).

        1.0 means the front image is fully added.

    padded_in: bool

        Whether the input background image is padded. Default: False

        In the function, the background image is padded by the size of the front image.

        If True, means the background image is padded.

    padded_out: bool

        Whether the output image is padded. Default: False

        In the function, the background image is padded by the size of the front image.

        If True, means the output image is padded.

        padded_in and padded_out are designed for the case that replace_region fuction is called multiple times.

    subpix: bool

        Whether the shift is subpixel. Default: False

        If True, the shift is subpixel, using scipy.ndimage.shift to shift the front image.

        If False, the shift is integer, using numpy slicing to shift the front image.

    Returns

    -------

    np.ndarray

        The output image.

        shape = background.shape if padded_out = False

        shape = background.shape + 2 * front.shape if padded_out = True

    """

    int_shift = np.array(shift).astype(int)

    b_sz = np.array(background.shape)

    f_sz = np.array(front.shape)

    if padded_in:

        padded = background

        b_sz = b_sz - f_sz * 2

    else:

        padded = np.pad(background, ((f_sz[0], f_sz[0]), (f_sz[1], f_sz[1])))

    if np.any((int_shift < -b_sz) | (int_shift > b_sz)):

        if padded_out:

            return padded

        return background

    if subpix:

        subs = np.array(shift) - int_shift

        front = nd.shift(front, (subs[0], subs[1]))

    int_shift += f_sz

    roi_y = int_shift[1]

    roi_x = int_shift[0]

    padded[roi_y: roi_y+f_sz[0], roi_x:roi_x+f_sz[1]] *= bmask

    padded[roi_y: roi_y+f_sz[0], roi_x:roi_x+f_sz[1]] += fmask * front

    if padded_out:

        return padded

    return padded[f_sz[0]:b_sz[0]+f_sz[0], f_sz[1]:b_sz[1]+f_sz[1]]