### 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)

ti_fails = ti_fails.filter(TaskFail.task_id.in_([t.task_id for t in dag.tasks]))
        tasks = []
        for ti in tis:
            if not dag.has_task(ti.task_id):
                continue
            
            
            
            try_count = ti.prev_attempted_tries if ti.prev_attempted_tries != 0 else ti.try_number
            task_dict = alchemy_to_dict(ti)
            task_dict["end_date"] = task_dict["end_date"] or timezone.utcnow()
            task_dict["extraLinks"] = dag.get_task(ti.task_id).extra_links
            task_dict["try_number"] = try_count
            task_dict["execution_date"] = dttm.isoformat()
            task_dict["run_id"] = dag_run_id
            tasks.append(task_dict)
        tf_count = 0
        try_count = 1
        prev_task_id = ""
        for failed_task_instance in ti_fails:
            if not dag.has_task(failed_task_instance.task_id):
                continue
            if tf_count != 0 and failed_task_instance.task_id == prev_task_id:
                try_count += 1
            else:
                try_count = 1
            prev_task_id = failed_task_instance.task_id
            tf_count += 1
            task = dag.get_task(failed_task_instance.task_id)
            task_dict = alchemy_to_dict(failed_task_instance)