# Path: sktracker/utils/progress.py
# def print_progress(progress, message=None, out=None):
#     """Display a progress bar filled with a variable value. print_progress
#     also works under IPython notebook.
# 
#     Set `progress` to -1 to remove the progress bar.
# 
#     Parameters
#     ----------
#     progress: int
#         Variable value use to fill the progress bar. Should be between 0
#         and 100.
#     out: OutStream
#         Where to stream progress bar. None will redirect output to `sys.stdout`.
# 
#     Returns
#     -------
#     None. Display the progress bar.
# 
#     Examples
#     --------
#     >>> import time
#     >>> from sktracker.utils import print_progress
# 
#     >>> n = 5
#     >>> for i in range(n):
#     >>>     time.sleep(1)
# 
#     >>>     print_progress((i + 1) * 100 / n)
#     100% [=================================================>]
#     >>> print_progress(-1)
# 
#     """
# 
#     if out is None:
#         out = sys.stdout
# 
#     # If process is finished
#     if progress == -1:
#         out.write("\r" + " " * 80 + "\r\r")
#         out.flush()
#         return
# 
#     # Size of the progress bar
#     size = 50
# 
#     # Compute current progress
#     progress_bar = (progress) * size / 100
# 
#     # Build progress bar
#     bar = "["
#     for i in range(int(progress_bar - 1)):
#         bar += "="
#     bar += ">"
#     for i in range(int(size - progress_bar)):
#         bar += " "
#     bar += "]"
# 
#     if message:
#         bar = " ".join([bar, message])
# 
#     # Write progress bar
#     bar_str = "\r%d%% " % (progress) + bar
#     out.write(bar_str)
#     out.flush()


import logging
import pandas as pd
import numpy as np
from scipy import integrate
from skimage.filters import threshold_otsu
from skimage.measure import regionprops
from skimage.segmentation import clear_border
from skimage.morphology import binary_closing
from skimage.morphology import square
from skimage.morphology import medial_axis
from skimage.morphology import label
from ..utils.progress import print_progress
    parameters : dict
        object_height : float
            Typical size of the object in um.
        minimal_area : float
            Typical area of the object in um^2.

    Returns
    ------()
    shapes : :class:`pd.DataFrame`
        Contains cell boundary properties for each time_stamp
    """

    _parameters = DEFAULT_PARAMETERS.copy()
    _parameters.update(parameters)
    parameters = _parameters

    # Load parameters
    sigma = parameters['object_height'] / metadata['PhysicalSizeZ']
    minimal_area = parameters['minimal_area'] / metadata['PhysicalSizeX']

    sizeX = metadata['SizeX']
    sizeY = metadata['SizeY']

    # calculate the correlation image from the z-stack
    cellprop = []
    t_tot = metadata['SizeT']
    for t, imt in enumerate(data_iterator):

        if show_progress:
            p = int(float(t + 1) / t_tot * 100.)

# Path: sktracker/utils/progress.py
# def print_progress(progress, message=None, out=None):
#     """Display a progress bar filled with a variable value. print_progress
#     also works under IPython notebook.
# 
#     Set `progress` to -1 to remove the progress bar.
# 
#     Parameters
#     ----------
#     progress: int
#         Variable value use to fill the progress bar. Should be between 0
#         and 100.
#     out: OutStream
#         Where to stream progress bar. None will redirect output to `sys.stdout`.
# 
#     Returns
#     -------
#     None. Display the progress bar.
# 
#     Examples
#     --------
#     >>> import time
#     >>> from sktracker.utils import print_progress
# 
#     >>> n = 5
#     >>> for i in range(n):
#     >>>     time.sleep(1)
# 
#     >>>     print_progress((i + 1) * 100 / n)
#     100% [=================================================>]
#     >>> print_progress(-1)
# 
#     """
# 
#     if out is None:
#         out = sys.stdout
# 
#     # If process is finished
#     if progress == -1:
#         out.write("\r" + " " * 80 + "\r\r")
#         out.flush()
#         return
# 
#     # Size of the progress bar
#     size = 50
# 
#     # Compute current progress
#     progress_bar = (progress) * size / 100
# 
#     # Build progress bar
#     bar = "["
#     for i in range(int(progress_bar - 1)):
#         bar += "="
#     bar += ">"
#     for i in range(int(size - progress_bar)):
#         bar += " "
#     bar += "]"
# 
#     if message:
#         bar = " ".join([bar, message])
# 
#     # Write progress bar
#     bar_str = "\r%d%% " % (progress) + bar
#     out.write(bar_str)
#     out.flush()


# Path: sktracker/detection/cell_boundaries_detector.py
import logging
import pandas as pd
import numpy as np
from scipy import integrate
from skimage.filters import threshold_otsu
from skimage.measure import regionprops
from skimage.segmentation import clear_border
from skimage.morphology import binary_closing
from skimage.morphology import square
from skimage.morphology import medial_axis
from skimage.morphology import label
from ..utils.progress import print_progress

    parameters : dict
        object_height : float
            Typical size of the object in um.
        minimal_area : float
            Typical area of the object in um^2.

    Returns
    ------()
    shapes : :class:`pd.DataFrame`
        Contains cell boundary properties for each time_stamp
    """

    _parameters = DEFAULT_PARAMETERS.copy()
    _parameters.update(parameters)
    parameters = _parameters

    # Load parameters
    sigma = parameters['object_height'] / metadata['PhysicalSizeZ']
    minimal_area = parameters['minimal_area'] / metadata['PhysicalSizeX']

    sizeX = metadata['SizeX']
    sizeY = metadata['SizeY']

    # calculate the correlation image from the z-stack
    cellprop = []
    t_tot = metadata['SizeT']
    for t, imt in enumerate(data_iterator):

        if show_progress:
            p = int(float(t + 1) / t_tot * 100.)

            print_progress(p)