---
title: "How does graphing work?"
slug: how-does-graphing-work
url: https://invertbio.com/docs/faq/how-does-graphing-work
---

# How does graphing work?

## Time-series Charts

### Time normalization

-   All time based charts are normalized to the **Run Start** time which calculates the **Elapsed Run Time (ERT).**
-   If there is data recorded prior the Run Start time, click _View -> Show Pre-run start data_ to reveal the data prior to t=0.

### Zoom

-   For Y-axis zooming, click on the two axis numbers to set the zoom bounds.
-   For X-axis zooming, click and drag within the graph.

### Downsampling and Interpolation

-   In order to maintain a snappy interface, we downsample the vast amount of available raw data for the line charts.
-   Data is interpolated between time points to enable the calculations in formulas and grouped time-series statistics for runs that do not have identical data frequencies.
-   Higher resolution raw data will render as you increase the zoom and is also available through the data export.

### Chart Splits

-   In the View options you can select to split the data:
    -   All-in-one
        -   This will show all metrics and runs on a singular graph.
        -   Each metric has a unique texture and each run has a unique color.
    -   Split metrics
        -   This creates a separate chart for each metric.
        -   Each run has a unique color which is consistent across each chart.
    -   Split Runs
        -   This creates a separate chart for each run or run group.
        -   Each metric has a unique color which is consistent across each chart.
    -   Separate
        -   Each metric and run is separated onto their own chart.

### Grouping

-   Use the 'Group by' option to categorize runs by metadata and access Invert's inter-run statistical comparison tools.
-   Line chart groups aggregate the run's interpolated data and display a solid line for the 50th percentile (median) values with a shaded range of the 16th to 84th percentiles. This ensures a distribution-agnostic analysis. Unlike mean and standard deviation, these percentiles provide a summary of both central tendency and variability within data. If the data is normally distributed these percentiles will represent 1 standard deviation.

## Scatterplot Charts

-   Toggle to scatter charts under the View dropdown menu.

    ![](/docs/faq/how-does-graphing-work/image-1.png)

-   The x-axis is set to the run name by default. However, you can select any categorical or time-series aggregated metric available to the selected runs by clicking on the tile next to the **X**.
-   The y-axis metrics can be any numeric values. This includes time-series aggregations, single-point values (numeric metadata), and calculated metrics.
    -   Time-series aggregation options include mean, minimum, maximum, standard deviation, first, last, and count.