neuralib.util.segments

`segment_bool_mask`
`is_sorted`	Check if array is sorted.
`segment_mask`	segmenting an array that the value is long enough.
`segment_epochs`
`has_gap`
`segment_gap`	segmenting an array that cut at the place which the difference of nearby value larger than gap.
`as_segment`
`segment_range`	change [(start, stop)] to [(start, duration)]
`segment_duration`
`segment_at_least_duration`
`segment_expand_duration`
`segment_universe`
`segment_flatten`	sorting and remove overlapped segments.
`segment_invert`
`segment_intersection`
`segment_union`
`segment_diff`
`segment_contains`	whether t in the segments.
`segment_index`	find the index of segs where t located
`segment_overlap`
`segment_overlap_index`
`segment_join`
`segment_join_index`
`segment_map`
`segment_group_map`
`segment_sample`
`segment_bins`	Divide segs into equal-size sub-segments with equal duration and equal interval.
`shuffle_time`	Shuffle t by remapping function method for t in segs.
`shuffle_time_uniform`	Shuffle t for t in segs.
`shuffle_time_normal`	Shuffle t with add a value from a normal distribution for t in segs.
`shift_time`	Shift t with a shift value for t in segs.
`foreach_map`	Map function `f` into vector `v` in given sections.
`grouped_iter`	Groups elements from the input iterable `v` into tuples of length `n`

Data