librosa.util.match_intervals¶

librosa.util.match_intervals(intervals_from, intervals_to, strict=True)[source]¶

Match one set of time intervals to another.

This can be useful for tasks such as mapping beat timings to segments.

Each element [a, b] of intervals_from is matched to the element [c, d] of intervals_to which maximizes the Jaccard similarity between the intervals:

max(0, |min(b, d) - max(a, c)|) / |max(d, b) - min(a, c)|

In strict=True mode, if there is no interval with positive intersection with [a,b], an exception is thrown.

In strict=False mode, any interval [a, b] that has no intersection with any element of intervals_to is instead matched to the interval [c, d] which minimizes:

min(|b - c|, |a - d|)

that is, the disjoint interval [c, d] with a boundary closest to [a, b].

Note

An element of intervals_to may be matched to multiple entries of intervals_from.

Parameters

intervals_fromnp.ndarray [shape=(n, 2)]: The time range for source intervals. The i th interval spans time intervals_from[i, 0] to intervals_from[i, 1]. intervals_from[0, 0] should be 0, intervals_from[-1, 1] should be the track duration.
intervals_tonp.ndarray [shape=(m, 2)]: Analogous to intervals_from.
strictbool: If True, intervals can only match if they intersect. If False, disjoint intervals can match.

Returns

interval_mappingnp.ndarray [shape=(n,)]: For each interval in intervals_from, the corresponding interval in intervals_to.

Raises

ParameterError

If either array of input intervals is not the correct shape

If strict=True and some element of intervals_from is disjoint from every element of intervals_to.

See also

match_events

Examples

>>> ints_from = np.array([[3, 5], [1, 4], [4, 5]])
>>> ints_to = np.array([[0, 2], [1, 3], [4, 5], [6, 7]])
>>> librosa.util.match_intervals(ints_from, ints_to)
array([2, 1, 2], dtype=uint32)
>>> # [3, 5] => [4, 5]  (ints_to[2])
>>> # [1, 4] => [1, 3]  (ints_to[1])
>>> # [4, 5] => [4, 5]  (ints_to[2])

The reverse matching of the above is not possible in strict mode because [6, 7] is disjoint from all intervals in ints_from. With strict=False, we get the following:

>>> librosa.util.match_intervals(ints_to, ints_from, strict=False)
array([1, 1, 2, 2], dtype=uint32)
>>> # [0, 2] => [1, 4]  (ints_from[1])
>>> # [1, 3] => [1, 4]  (ints_from[1])
>>> # [4, 5] => [4, 5]  (ints_from[2])
>>> # [6, 7] => [4, 5]  (ints_from[2])