arrays: Generic arrays utilities#

Module containing array utilities.

daxs.utils.arrays.intersect(a: ndarray[Any, dtype[float64]], b: ndarray[Any, dtype[float64]], sort: bool = False) → ndarray[Any, dtype[float64]][source]#

Compute the intersection of two arrays.

The function sorts the input arrays if required, determines the indices of the intersecting region, and returns the intersection. If there is no intersection, an empty array is returned.

Parameters:

  • a – The first input array.

  • b – The second input array.

  • sort – If True, the input arrays are sorted; default is False.

Returns:

The intersection of the input arrays. If there is no intersection, an empty array is returned.

Return type:

intersection

daxs.utils.arrays.union(a: ndarray[Any, dtype[float64]], b: ndarray[Any, dtype[float64]], sort: bool = False) → ndarray[Any, dtype[float64]][source]#
daxs.utils.arrays.merge(a: ndarray[Any, dtype[Any]], b: ndarray[Any, dtype[Any]], mode: str = 'intersection', sort: bool = False) → ndarray[Any, dtype[Any]][source]#

Merge two array using the specified mode.

daxs.utils.arrays.discretize_intervals(intervals: list[list[float]]) → ndarray[Any, dtype[float64]][source]#
daxs.utils.arrays.trapezoid(y: npt.NDArray[np.float64], x: npt.NDArray[np.float64] | None = None) → float[source]#

Integrate y using the composite trapezoidal rule while ignoring NaN values.

Parameters:

  • y – The values of the function to integrate. NaN values are ignored.

  • x – The sample points corresponding to y values. If None, points are assumed to be spaced at a unit distance.

Returns:

The estimated integral of y using the trapezoidal rule.

Return type:

float