### Description

Currently Airflow has a `Filter Upstream` View/option inside the graph view. (As documented [here](https://docs.astronomer.io/learn/airflow-ui#graph-view) under `Filter Upstream`)

<img width="682" alt="image" src="https://user-images.githubusercontent.com/9246654/211711759-670a1180-7f90-4ecd-84b0-2f3b290ff477.png">

It would be great if there were also the options
1. `Filter Downstream` &
2. `Filter Downstream & Upstream`

### Use case/motivation

Sometimes it is useful to view downstream tasks & down & upstream tasks when reviewing dags. This feature would make it as easy to view those as it is to view upstream today.

### Related issues

I found nothing with a quick search

### Are you willing to submit a PR?

- [ ] Yes I am willing to submit a PR!

### Code of Conduct

- [X] I agree to follow this project's [Code of Conduct](https://github.com/apache/airflow/blob/main/CODE_OF_CONDUCT.md)

else:
            base_date = dag.get_latest_execution_date() or timezone.utcnow()
        root = request.args.get("root")
        if root:
            dag = dag.partial_subset(task_ids_or_regex=root, include_upstream=True, include_downstream=False)
        chart_height = wwwutils.get_chart_height(dag)
        chart = nvd3.lineChart(
            name="lineChart",
            x_custom_format=True,
            x_axis_date=True,
            x_axis_format=LINECHART_X_AXIS_TICKFORMAT,
            height=chart_height,
            chart_attr=self.line_chart_attr,
        )
        cum_chart = nvd3.lineChart(
            name="cumLineChart",
            x_custom_format=True,
            x_axis_date=True,
            x_axis_format=LINECHART_X_AXIS_TICKFORMAT,
            height=chart_height,
            chart_attr=self.line_chart_attr,
        )
        y_points = defaultdict(list)
        x_points = defaultdict(list)
        task_instances = dag.get_task_instances_before(base_date, num_runs, session=session)
        if task_instances:
            min_date = task_instances[0].execution_date
        else:
            min_date = timezone.utc_epoch()
        ti_fails = (