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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
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])