### 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)

ignore_ti_state=ignore_ti_state,
        )
        failed_deps = list(ti.get_failed_dep_statuses(dep_context=dep_context))
        if failed_deps:
            failed_deps_str = ", ".join(f"{dep.dep_name}: {dep.reason}" for dep in failed_deps)
            msg = f"Could not queue task instance for execution, dependencies not met: {failed_deps_str}"
            return redirect_or_json(origin, msg, "error", 400)
        executor.job_id = None
        executor.start()
        executor.queue_task_instance(
            ti,
            ignore_all_deps=ignore_all_deps,
            ignore_task_deps=ignore_task_deps,
            ignore_ti_state=ignore_ti_state,
        )
        executor.heartbeat()
        ti.queued_dttm = timezone.utcnow()
        session.merge(ti)
        msg = f"Sent {ti} to the message queue, it should start any moment now."
        return redirect_or_json(origin, msg)
    @expose("/delete", methods=["POST"])
    @auth.has_access(
        [
            (permissions.ACTION_CAN_DELETE, permissions.RESOURCE_DAG),
        ]
    )
    @action_logging
    def delete(self):
        """Deletes DAG."""
        from airflow.api.common import delete_dag