Python itertools.filterfalse方法代碼示例

# 需要導入模塊: import itertools [as 別名]
# 或者: from itertools import filterfalse [as 別名]
def mean(l, ignore_nan=False, empty=0):
    """
    nanmean compatible with generators.
    """
    l = iter(l)
    if ignore_nan:
        l = ifilterfalse(isnan, l)
    try:
        n = 1
        acc = next(l)
    except StopIteration:
        if empty == 'raise':
            raise ValueError('Empty mean')
        return empty
    for n, v in enumerate(l, 2):
        acc += v
    if n == 1:
        return acc
    return acc / n 

# 需要導入模塊: import itertools [as 別名]
# 或者: from itertools import filterfalse [as 別名]
def unique_everseen(iterable, key=None):
    "List unique elements, preserving order. Remember all elements ever seen."
    # unique_everseen('AAAABBBCCDAABBB') --> A B C D
    # unique_everseen('ABBCcAD', str.lower) --> A B C D
    # straight from the docs, https://docs.python.org/3/library/itertools.html#itertools-recipes
    seen = set()
    seen_add = seen.add
    if key is None:
        for element in itertools.filterfalse(seen.__contains__, iterable):
            seen_add(element)
            yield element
    else:
        for element in iterable:
            k = key(element)
            if k not in seen:
                seen_add(k)
                yield element 

# 需要導入模塊: import itertools [as 別名]
# 或者: from itertools import filterfalse [as 別名]
def _need_update(curr_list, desired_list):
    """
    Checks to see if there are any difference in curr_list or desired_list. If they are different this returns True.

    Args:
        curr_list (list): list of dictionaries
        desired_list (list): list of dictionaries

    Returns:
         bool
    """
    #Checks if items need to be added or removed.
    add = list(itertools.filterfalse(lambda x: x in curr_list, desired_list))
    remove = list(itertools.filterfalse(lambda x: x in desired_list, curr_list))
    if add or remove:
        return True
    return False 

# 需要導入模塊: import itertools [as 別名]
# 或者: from itertools import filterfalse [as 別名]
def _need_update(self, curr_list, desired_list):
        """
        Checks to see if there are any difference in curr_list or desired_list. If they are different this returns True.

        Args:
            curr_list (list): list of dictionaries
            desired_list (list): list of dictionaries

        Returns:
            bool
        """
        #Checks if items need to be added or removed.
        add = list(itertools.filterfalse(lambda x: x in curr_list, desired_list))
        remove = list(itertools.filterfalse(lambda x: x in desired_list, curr_list))
        if add or remove:
            return True
        return False 

# 需要導入模塊: import itertools [as 別名]
# 或者: from itertools import filterfalse [as 別名]
def _need_update(self, curr_list, desired_list):
        """
        Checks to see if there are any differences in curr_list or desired_list. If they are different True is returned.

        Args:
            curr_list (list): list of dictionaries
            desired_list (list): list of dictionaries

        Returns:
             bool
        """
        # Checks if items need to be added or removed.
        add = list(itertools.filterfalse(lambda x: x in curr_list, desired_list))
        remove = list(itertools.filterfalse(lambda x: x in desired_list, curr_list))
        if add or remove:
            return True
        return False 

# 需要導入模塊: import itertools [as 別名]
# 或者: from itertools import filterfalse [as 別名]
def filter_control(
        cls, segments: Iterable["Segment"], is_control=False
    ) -> Iterable["Segment"]:
        """Filter segments by ``is_control`` attribute.

        Args:
            segments (Iterable[Segment]): An iterable of Segment instances.
            is_control (bool, optional): is_control flag to match in search.

        Returns:
            Iterable[Segment]: And iterable of Segment instances.
        
        """
        if is_control:
            return filter(attrgetter("is_control"), segments)
        else:
            return filterfalse(attrgetter("is_control"), segments) 

# 需要導入模塊: import itertools [as 別名]
# 或者: from itertools import filterfalse [as 別名]
def mean(l, ignore_nan=False, empty=0):
    """
    nanmean compatible with generators.
    """
    l = iter(l)
    if ignore_nan:
        l = filterfalse(np.isnan, l)
    try:
        n = 1
        acc = next(l)
    except StopIteration:
        if empty == 'raise':
            raise ValueError('Empty mean')
        return empty
    for n, v in enumerate(l, 2):
        acc += v
    if n == 1:
        return acc
    return acc / n 

# 需要導入模塊: import itertools [as 別名]
# 或者: from itertools import filterfalse [as 別名]
def unique_everseen(iterable, key=None):
    """List unique elements, preserving order. Remember all elements ever seen.

    >>> ''.join(unique_everseen('AAAABBBCCDAABBB'))
    'ABCD'
    >>> ''.join(unique_everseen('ABBCcAD', str.lower))
    'ABCD'

    """
    seen = set()
    seen_add = seen.add
    if key is None:
        for element in filterfalse(seen.__contains__, iterable):
            seen_add(element)
            yield element
    else:
        for element in iterable:
            k = key(element)
            if k not in seen:
                seen_add(k)
                yield element 

# 需要導入模塊: import itertools [as 別名]
# 或者: from itertools import filterfalse [as 別名]
def unique_everseen(iterable, key=None):
    """List unique elements, preserving order. Remember all elements ever seen.

    >>> list(unique_everseen('AAAABBBCCDAABBB'))
    ['A', 'B', 'C', 'D']
    >>> list(unique_everseen('ABBCcAD', str.lower))
    ['A', 'B', 'C', 'D']
    """
    seen = set()
    seen_add = seen.add
    if key is None:
        for element in filterfalse(seen.__contains__, iterable):
            seen_add(element)
            yield element
    else:
        for element in iterable:
            k = key(element)
            if k not in seen:
                seen_add(k)
                yield element 

# 需要導入模塊: import itertools [as 別名]
# 或者: from itertools import filterfalse [as 別名]
def mean(l, ignore_nan=False, empty=0):
    """
    nanmean compatible with generators.
    """
    l = iter(l)
    if ignore_nan:
        l = filterfalse(isnan, l)
    try:
        n = 1
        acc = next(l)
    except StopIteration:
        if empty == "raise":
            raise ValueError("Empty mean")
        return empty
    for n, v in enumerate(l, 2):
        acc += v
    if n == 1:
        return acc
    return acc / n


# --------------------------- Convinient classes --------------------------- 

# 需要導入模塊: import itertools [as 別名]
# 或者: from itertools import filterfalse [as 別名]
def _op_descendants(self, op, only):
        """Descendants of the given operator in the quantum circuit.

        Args:
            op (Operator): operator in the quantum circuit
            only (str, None): the type of descendants to return.

                - ``'G'``: only return non-observables (default)
                - ``'O'``: only return observables
                - ``None``: return all descendants

        Returns:
            list[Operator]: descendants in a topological order
        """
        succ = self.circuit.descendants_in_order((op,))
        if only == "O":
            return list(filter(_is_observable, succ))
        if only == "G":
            return list(itertools.filterfalse(_is_observable, succ))
        return succ 

# 需要導入模塊: import itertools [as 別名]
# 或者: from itertools import filterfalse [as 別名]
def unique_everseen(iterable, key=None):
    """List unique elements, preserving order.

    Remember all elements ever seen

    >>> list(unique_everseen('AAAABBBCCDAABBB'))
    ['A', 'B', 'C', 'D']
    >>> list(unique_everseen('ABBCcAD', str.lower))
    ['A', 'B', 'C', 'D']

    """
    seen = set()
    seen_add = seen.add
    if key is None:
        for element in itertools.filterfalse(seen.__contains__, iterable):
            seen_add(element)
            yield element
    else:
        for element in iterable:
            k = key(element)
            if k not in seen:
                seen_add(k)
                yield element 

# 需要導入模塊: import itertools [as 別名]
# 或者: from itertools import filterfalse [as 別名]
def mean(l, ignore_nan=True, empty=0):
    """
    nanmean compatible with generators.
    """
    l = iter(l)
    if ignore_nan:
        l = filterfalse(isnan, l)
    try:
        n = 1
        acc = next(l)
    except StopIteration:
        if empty == 'raise':
            raise ValueError('Empty mean')
        return empty
    for n, v in enumerate(l, 2):
        acc += v
    if n == 1:
        return acc
    return acc / n 

# 需要導入模塊: import itertools [as 別名]
# 或者: from itertools import filterfalse [as 別名]
def mean(values, ignore_nan=False, empty=0):
    """
    Nanmean compatible with generators.
    """
    values = iter(values)
    if ignore_nan:
        values = ifilterfalse(isnan, values)
    try:
        n = 1
        acc = next(values)
    except StopIteration:
        if empty == "raise":
            raise ValueError("Empty mean")
        return empty
    for n, v in enumerate(values, 2):  # noqa: B007
        acc += v
    if n == 1:
        return acc
    return acc / n 

# 需要導入模塊: import itertools [as 別名]
# 或者: from itertools import filterfalse [as 別名]
def get_parsed_py_files(self, whitelist=None):
        parsed_py_files = self._parsed_py_files
        if whitelist:
            parsed_py_files = filterfalse(
                lambda parsed_file: parsed_file.is_in_whitelist(whitelist),
                parsed_py_files
            )
        return parsed_py_files