# Path: picasso/io.py
# class NoMetadataFileError(FileNotFoundError):
# class TiffMap:
# class TiffMultiMap:
# def _user_settings_filename():
# def load_raw(path, prompt_info=None):
# def save_config(CONFIG):
# def save_raw(path, movie, info):
# def multiple_filenames(path, index):
# def load_tif(path):
# def load_movie(path, prompt_info=None):
# def load_info(path, qt_parent=None):
# def load_user_settings():
# def save_info(path, info, default_flow_style=False):
# def _to_dict_walk(node):
# def save_user_settings(settings):
#     def __init__(self, path, verbose=False):
#     def __enter__(self):
#     def __exit__(self, exc_type, exc_value, traceback):
#     def __getitem__(self, it):
#     def __iter__(self):
#     def __len__(self):
#     def info(self):
#     def get_frame(self, index, array=None):
#     def read(self, type, count=1):
#     def read_numbers(self, type, count=1):
#     def close(self):
#     def tofile(self, file_handle, byte_order=None):
#     def __init__(self, path, memmap_frames=False, verbose=False):
#     def __enter__(self):
#     def __exit__(self, exc_type, exc_value, traceback):
#     def __getitem__(self, it):
#     def __iter__(self):
#     def __len__(self):
#     def close(self):
#     def get_frame(self, index):
#     def info(self):
#     def tofile(self, file_handle, byte_order=None):
# def to_raw_combined(basename, paths):
# def get_movie_groups(paths):
# def to_raw(path, verbose=True):
# def save_datasets(path, info, **kwargs):
# def save_locs(path, locs, info):
# def load_locs(path, qt_parent=None):
# def load_clusters(path, qt_parent=None):
# def load_filter(path, qt_parent=None):
#     TIFF_TYPES = {1: "B", 2: "c", 3: "H", 4: "L", 5: "RATIONAL"}
#     TYPE_SIZES = {
#         "c": 1,
#         "B": 1,
#         "h": 2,
#         "H": 2,
#         "i": 4,
#         "I": 4,
#         "L": 4,
#         "RATIONAL": 8,
#     }


import numba as _numba
import numpy as _np
import collections as _collections
import glob as _glob
import os.path as _ospath
from numpy.lib.recfunctions import append_fields as _append_fields
from numpy.lib.recfunctions import drop_fields as _drop_fields
from picasso import io as _io
from PyQt5 import QtGui, QtCore, QtWidgets
from lmfit import Model as _Model
    else:
        shift_z = _np.insert(_np.cumsum(Dj[:, 2]), 0, 0)
        return shift_y, shift_x, shift_z


def n_futures_done(futures):
    return sum([_.done() for _ in futures])


def remove_from_rec(rec_array, name):
    return _drop_fields(rec_array, name, usemask=False, asrecarray=True)


def locs_glob_map(func, pattern, args=[], kwargs={}, extension=""):
    """
    Maps a function to localization files, specified by a unix style path
    pattern.
    The function must take two arguments: locs and info. It may take additional
    args and kwargs which are supplied to this map function.
    A new locs file will be saved if an extension is provided. In that case the
    mapped function must return new locs and a new info dict.
    """
    paths = _glob.glob(pattern)
    for path in paths:
        locs, info = _io.load_locs(path)
        result = func(locs, info, path, *args, **kwargs)
        if extension:
            base, ext = _ospath.splitext(path)
            out_path = base + "_" + extension + ".hdf5"
            locs, info = result

# Path: picasso/io.py
# class NoMetadataFileError(FileNotFoundError):
# class TiffMap:
# class TiffMultiMap:
# def _user_settings_filename():
# def load_raw(path, prompt_info=None):
# def save_config(CONFIG):
# def save_raw(path, movie, info):
# def multiple_filenames(path, index):
# def load_tif(path):
# def load_movie(path, prompt_info=None):
# def load_info(path, qt_parent=None):
# def load_user_settings():
# def save_info(path, info, default_flow_style=False):
# def _to_dict_walk(node):
# def save_user_settings(settings):
#     def __init__(self, path, verbose=False):
#     def __enter__(self):
#     def __exit__(self, exc_type, exc_value, traceback):
#     def __getitem__(self, it):
#     def __iter__(self):
#     def __len__(self):
#     def info(self):
#     def get_frame(self, index, array=None):
#     def read(self, type, count=1):
#     def read_numbers(self, type, count=1):
#     def close(self):
#     def tofile(self, file_handle, byte_order=None):
#     def __init__(self, path, memmap_frames=False, verbose=False):
#     def __enter__(self):
#     def __exit__(self, exc_type, exc_value, traceback):
#     def __getitem__(self, it):
#     def __iter__(self):
#     def __len__(self):
#     def close(self):
#     def get_frame(self, index):
#     def info(self):
#     def tofile(self, file_handle, byte_order=None):
# def to_raw_combined(basename, paths):
# def get_movie_groups(paths):
# def to_raw(path, verbose=True):
# def save_datasets(path, info, **kwargs):
# def save_locs(path, locs, info):
# def load_locs(path, qt_parent=None):
# def load_clusters(path, qt_parent=None):
# def load_filter(path, qt_parent=None):
#     TIFF_TYPES = {1: "B", 2: "c", 3: "H", 4: "L", 5: "RATIONAL"}
#     TYPE_SIZES = {
#         "c": 1,
#         "B": 1,
#         "h": 2,
#         "H": 2,
#         "i": 4,
#         "I": 4,
#         "L": 4,
#         "RATIONAL": 8,
#     }


# Path: picasso/lib.py
import numba as _numba
import numpy as _np
import collections as _collections
import glob as _glob
import os.path as _ospath
from numpy.lib.recfunctions import append_fields as _append_fields
from numpy.lib.recfunctions import drop_fields as _drop_fields
from picasso import io as _io
from PyQt5 import QtGui, QtCore, QtWidgets
from lmfit import Model as _Model

    else:
        shift_z = _np.insert(_np.cumsum(Dj[:, 2]), 0, 0)
        return shift_y, shift_x, shift_z


def n_futures_done(futures):
    return sum([_.done() for _ in futures])


def remove_from_rec(rec_array, name):
    return _drop_fields(rec_array, name, usemask=False, asrecarray=True)


def locs_glob_map(func, pattern, args=[], kwargs={}, extension=""):
    """
    Maps a function to localization files, specified by a unix style path
    pattern.
    The function must take two arguments: locs and info. It may take additional
    args and kwargs which are supplied to this map function.
    A new locs file will be saved if an extension is provided. In that case the
    mapped function must return new locs and a new info dict.
    """
    paths = _glob.glob(pattern)
    for path in paths:
        locs, info = _io.load_locs(path)
        result = func(locs, info, path, *args, **kwargs)
        if extension:
            base, ext = _ospath.splitext(path)
            out_path = base + "_" + extension + ".hdf5"
            locs, info = result

            _io.save_locs(out_path, locs, info)