### 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)

"""Get DAG runs as calendar"""
        def _convert_to_date(session, column):
            """Convert column to date."""
            if session.bind.dialect.name == "mssql":
                return column.cast(Date)
            else:
                return func.date(column)
        dag = get_airflow_app().dag_bag.get_dag(dag_id, session=session)
        dag_model = DagModel.get_dagmodel(dag_id, session=session)
        if not dag:
            flash(f'DAG "{dag_id}" seems to be missing from DagBag.', "error")
            return redirect(url_for("Airflow.index"))
        wwwutils.check_import_errors(dag.fileloc, session)
        wwwutils.check_dag_warnings(dag.dag_id, session)
        root = request.args.get("root")
        if root:
            dag = dag.partial_subset(task_ids_or_regex=root, include_downstream=False, include_upstream=True)
        dag_states = (
            session.query(
                (_convert_to_date(session, DagRun.execution_date)).label("date"),
                DagRun.state,
                func.max(DagRun.data_interval_start).label("data_interval_start"),
                func.max(DagRun.data_interval_end).label("data_interval_end"),
                func.count("*").label("count"),
            )