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You're reading the documentation for a development version. For the latest released version, please have a look at 0.10.1.

# librosa.util.localmin

librosa.util.localmin(x, *, axis=0)[source]

Find local minima in an array

An element `x[i]` is considered a local minimum if the following conditions are met:

• `x[i] < x[i-1]`

• `x[i] <= x[i+1]`

Note that the first condition is strict, and that the first element `x[0]` will never be considered as a local minimum.

Parameters:
xnp.ndarray [shape=(d1,d2,…)]

input vector or array

axisint

axis along which to compute local minimality

Returns:
mnp.ndarray [shape=x.shape, dtype=bool]

indicator array of local minimality along `axis`

Examples

```>>> x = np.array([1, 0, 1, 2, -1, 0, -2, 1])
>>> librosa.util.localmin(x)
array([False,  True, False, False,  True, False,  True, False])
```
```>>> # Two-dimensional example
>>> x = np.array([[1,0,1], [2, -1, 0], [2, 1, 3]])
>>> librosa.util.localmin(x, axis=0)
array([[False, False, False],
[False,  True,  True],
[False, False, False]])
```
```>>> librosa.util.localmin(x, axis=1)
array([[False,  True, False],
[False,  True, False],
[False,  True, False]])
```