--- title: Visualize fixed-window plots order: 225 --- As of Rerun 0.16, the [TimeSeriesView](../../reference/types/views/time_series_view.md) now supports direct manipulation of the visible time range. This allows you to create a plot that only shows a fixed window of data. ## VisibleTimeRange To specify the visible time range, you must pass one or more `VisibleTimeRange` objects to the `time_ranges` parameter of the `TimeSeriesView` blueprint type. If your app only uses a single timeline, you can directly pass a single `VisibleTimeRange` object instead of wrapping it in a list. The `VisibleTimeRange` object takes three parameters: - `timeline`: The timeline that the range will apply to. This must match the timeline used to log your data, or if you are only using the rerun-provided timestamps, you can use the strings `"log_time"`, or `"log_tick"`. - `start`: The start of the visible time range. - `end`: The end of the visible time range. The `start` and `end` parameters are set using a `TimeRangeBoundary`: - To specify an absolute time, you can use the `TimeRangeBoundary.absolute()` method. - To specify a cursor-relative time, you can use the `TimeRangeBoundary.cursor_relative()` method. - You can also specify `TimeRangeBoundary.infinite()` to indicate that the start or end of the time range should be unbounded. In order to account for the different types of timeline (temporal or sequence-based), both the `TimeRangeBoundary.absolute()` and `TimeRangeBoundary.cursor_relative()` methods can be specified using one of the keyword args: - `seconds`/`nanos`: Use these if you called `rr.set_time()` to update the timeline. - `seq`: Use this if you called `rr.set_time_sequence()` to update the timeline. ## Example syntax To create a trailing 5 second window plot, you can specify your `TimeSeriesView` like this: ```python rrb.TimeSeriesView( origin="plot_path", time_ranges=rrb.VisibleTimeRange( timeline="time", start=rrb.TimeRangeBoundary.cursor_relative(seconds=-5.0), end=rrb.TimeRangeBoundary.cursor_relative(), ), ) ``` ## Full example For a complete working example, you can run the following code: snippet: tutorials/fixed_window_plot This should create a plot that only shows the last 5 seconds of data. If you select the view, you should see that the time range is configured as expected. Alternatively, you can check out a more full-featured example with multiple plot windows [here](https://github.com/rerun-io/rerun/tree/latest/examples/python/live_scrolling_plot). ## Additional notes - Any time you log data, it has two timepoints associated with it: "log_time", and "log_tick".