aragog.utilities

def combine_properties(weight: Any, property1: Any, property2: Any) -> Any:
    """Linear weighting of two quantities.

    Args:
        weight: The weight to apply to property1
        property1: The value of the first property
        property2: The value of the second property

    Returns:
        The combined (weighted) property
    """
    out = weight * property1 + (1.0 - weight) * property2

    return out

def is_file(value: Any) -> bool:
    """Checks if value is a file.

    Args:
        value: Object to be checked

    Returns:
        True if the value is a file, otherwise False
    """
    if isinstance(value, (str, Path)):
        return Path(value).is_file()

    return False

def is_monotonic_increasing(some_array: npt.NDArray) -> bool:
    """Returns True if an array is monotonically increasing, otherwise returns False."""
    return np.all(np.diff(some_array) > 0)

def is_number(value: Any) -> bool:
    """Checks if value is a number.

    Args:
        value: Object to be checked

    Returns:
        True if the value is a number, otherwise False
    """
    try:
        float(value)
        return True

    except (TypeError, ValueError):
        return False

def profile_decorator(func):
    """Decorator to profile a function"""

    @wraps(func)
    def wrapper(*args, **kwargs):
        with Profile() as profile:
            result = func(*args, **kwargs)
        stats = Stats(profile).strip_dirs().sort_stats(SortKey.TIME)
        stats.print_stats()
        return result

    return wrapper

def tanh_weight(value: FloatOrArray, threshold: float, width: float) -> npt.NDArray:
    """Computes the tanh weight for viscosity profile and smoothing.

    Args:
        value: Value
        threshold: Threshold value
        width: Width of smoothing

    Returns:
        weight
    """
    arg: FloatOrArray = (value - threshold) / width
    weight: npt.NDArray = 0.5 * (1.0 + np.tanh(arg))

    return weight