# torch_geometric.nn.aggr.QuantileAggregation

class QuantileAggregation(q: Union[float, List[float]], interpolation: str = 'linear', fill_value: float = 0.0)[source]

Bases: Aggregation

An aggregation operator that returns the feature-wise $$q$$-th quantile of a set $$\mathcal{X}$$. That is, for every feature $$d$$, it computes

$\begin{split}{\mathrm{Q}_q(\mathcal{X})}_d = \begin{cases} x_{\pi_i,d} & i = q \cdot n, \\ f(x_{\pi_i,d}, x_{\pi_{i+1},d}) & i < q \cdot n < i + 1,\\ \end{cases}\end{split}$

where $$x_{\pi_1,d} \le \dots \le x_{\pi_i,d} \le \dots \le x_{\pi_n,d}$$ and $$f(a, b)$$ is an interpolation function defined by interpolation.

Parameters
• q (float or list) – The quantile value(s) $$q$$. Can be a scalar or a list of scalars in the range $$[0, 1]$$. If more than a quantile is passed, the results are concatenated.

• interpolation (str) –

Interpolation method applied if the quantile point $$q\cdot n$$ lies between two values $$a \le b$$. Can be one of the following:

• "lower": Returns the one with lowest value.

• "higher": Returns the one with highest value.

• "midpoint": Returns the average of the two values.

• "nearest": Returns the one whose index is nearest to the quantile point.

• "linear": Returns a linear combination of the two elements, defined as $$f(a, b) = a + (b - a)\cdot(q\cdot n - i)$$.

(default: "linear")

• fill_value (float, optional) – The default value in the case no entry is found for a given index (default: 0.0).

forward(x: Tensor, index: = None, ptr: = None, dim_size: = None, dim: int = -2) [source]
Parameters
• x (torch.Tensor) – The source tensor.

• index (torch.Tensor, optional) – The indices of elements for applying the aggregation. One of index or ptr must be defined. (default: None)

• ptr (torch.Tensor, optional) – If given, computes the aggregation based on sorted inputs in CSR representation. One of index or ptr must be defined. (default: None)

• dim_size (int, optional) – The size of the output tensor at dimension dim after aggregation. (default: None)

• dim (int, optional) – The dimension in which to aggregate. (default: -2)