Knowledge Base

Multiple Selections in a Data Profile

You can create different data selections in the same Data profile. Each sequence of boxes must end in a separate Result box. When you analyze the data using that Data profile, the results (statistics, track plots, or heatmaps) are displayed for each selection separately.

Tip: With large data sets, you may have a large number of possible data selections. Create multiple Data profiles, each specifying one of those selection criteria, and then run batch calculations for each combination between Data profiles and Analysis profiles.

Example: Tracks have been recorded for a number of animals at Day after treatment 1 and 2. Day after treatment is an independent variable. You want to calculate statistics for the two groups separately, but also with all tracks pooled together.

Connect each Filter sequence to a separate Result box. To add a Result box, click the button next to Result in the Components pane.

The first Result box receives the data after filtering with the independent variable Day after treatment = 1. The second Result box receives the data after filtering with Day after treatment = 2. The third Result box receives all data. The statistics are calculated separately for each criterion.

Tip: Click the Settings button in a Result box to change its name. Enter a name associated with the selection (for example, "Day 1"). You will see this name in the results table.

In the analysis results, you can see which output is produced by which Result box. Look up the Result header.

See Also

• Analyze Groups of Tracks

Visualize Data

Main Topics and Tasks

• Introduction to Data Visualization
• Plot Tracks
• Plot Heatmaps
• Plot Integrated Data
• Customize Tracks and Plots

Introduction to Data Visualization

Learn About

• Important Terms in Data Visualization
• Useful Things to Know in Data Visualization

Important Terms in Data Visualization

Track Plot

Visualization of one or multiple trials, where the subject's position is displayed over a static (background) image. Use track plots to visually inspect trials and compare the effect of experimental treatments.

• See Plot Tracks

Heatmap

Visualization of one or multiple trials, where the density of sample points is represented as a color. It is useful to find hotspots.

• See Plot Heatmaps

Integrated Data

Combines visualization of tracks with video (when present), and dependent variables and external data (when present) plotted against time.

• See Plot Integrated Data

Useful Things to Know in Data Visualization

To Visualize the Data

Do one of the following:

• Choose Analysis > Results > one of the options Plot Tracks, Plot Heatmaps, or Plot Integrated Data.
• In the Experiment Explorer, under Results, click Track Visualization, Heatmap Visualization, or Integrated Visualization.

To Visualize a Specific Data Set

On the toolbar, choose the Track Smoothing profile, Data Profile and Analysis Profile, and a trial (for Integrated visualization).

To Customize Track Colors, Data Points, Etc.

Choose the options on the right-hand pane.

• See Customize Tracks and Plots

To Customize the Elements on Your Screen

Click the Show/Hide button at the top-right corner and choose the options you require.

• See Customize Tracks and Plots

To Move and Resize Windows

• To move a window, click its title bar and drag it to the desired position. You can either dock a window or let it float on the screen.
• To resize a window, point with your mouse to the window's left or top margin so the mouse pointer turns to a double arrow. Drag the margin to the desired position.

Plot Tracks

What Do You Want to Do?

• Plot Tracks
• Sort Track Plots
• View and Play Back Tracks
• Export Track Plots

Plot Tracks

Aim

Choose Track Visualization to visualize a set of tracks. This function is particularly useful when you want to have an overview of your data acquired so far. If you want to visualize data from one specific trial together with video or external data, see Plot Integrated Data.

Procedure

1. Choose Analysis > Results > Plot Tracks, or in the Experiment Explorer, under Results, click Track Visualization.
2. On the toolbar, choose the Track Smoothing profile and the Data profile that you want to use. The two profiles define the samples to plot.
3. See Customize Tracks and Plots.

Notes

• If you want to plot tracks in colors depending on the value of a dependent variable, like velocity, make sure that that variable is defined in one of the Analysis profiles. Then, repeat the steps above and choose the correct Analysis profile.
• If your data selection contains nesting criteria, all samples are plotted, however the samples excluded by nesting are displayed in a different color.
• You may sometimes get the following message: You have recorded data with more than one Arena Settings, and the layout of the plot matrix is such that tracks obtained with different Arena Settings are expected to be plotted in the same plot. Add the independent variable Arena Settings to the layout (see Sort the Track Plots by a New Variable). Alternatively, in your Data profile filter data from one of the Arena Settings.
• Sometimes a variable number of cells in the plot matrix are empty. This is caused by the fact that there are no tracks corresponding to the values of the independent variable specified in the plot headers. To create a more compact matrix, choose a different set of independent variables to sort track plots (see Sort Track Plots).