*Last updated: 2023-03-16.*
# tf_quant_finance.math.piecewise.find_interval_index
View source
Function to find the index of the interval where query points lies.
```python
tf_quant_finance.math.piecewise.find_interval_index(
query_xs, interval_lower_xs, last_interval_is_closed=False, dtype=None,
name=None
)
```
Given a list of adjacent half-open intervals [x_0, x_1), [x_1, x_2), ...,
[x_{n-1}, x_n), [x_n, inf), described by a list [x_0, x_1, ..., x_{n-1}, x_n].
Return the index where the input query points lie. If x >= x_n, n is returned,
and if x < x_0, -1 is returned. If `last_interval_is_closed` is set to `True`,
the last interval [x_{n-1}, x_n] is interpreted as closed (including x_n).
#### Example
```python
interval_lower_xs = [0.25, 0.5, 1.0, 2.0, 3.0]
query_xs = [0.25, 3.0, 5.0, 0.0, 0.5, 0.8]
result = find_interval_index(query_xs, interval_lower_xs)
# result == [0, 4, 4, -1, 1, 1]
```
#### Args:
* `query_xs`: Rank 1 real `Tensor` of any size, the list of x coordinates for
which the interval index is to be found. The values must be strictly
increasing.
* `interval_lower_xs`: Rank 1 `Tensor` of the same shape and dtype as
`query_xs`. The values x_0, ..., x_n that define the interval starts.
* `last_interval_is_closed`: If set to `True`, the last interval is interpreted
as closed.
* `dtype`: Optional `tf.Dtype`. If supplied, the dtype for `query_xs` and
`interval_lower_xs`.
Default value: None which maps to the default dtype inferred from
`query_xs`.
* `name`: Optional name of the operation.
#### Returns:
A tensor that matches the shape of `query_xs` with dtype=int32 containing
the indices of the intervals containing query points. `-1` means the query
point lies before all intervals and `n-1` means that the point lies in the
last half-open interval (if `last_interval_is_closed` is `False`) or that
the point lies to the right of all intervals (if `last_interval_is_closed`
is `True`).