Epochs

An epoch is a structural container, or division within Timelines, that serves to group and organize sets of components, actions, or data in a meaningful and coherent manner.

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The Timeline is a way to organize a sequence of components, in a certain order. In is divided into Epochs. Epochs are useful because they give you a visual summary of a group of components. Each epoch has a thumbnail that shows the regions and patterns created within the epoch. The thumbnail is scaled to fit the thumbnail window.

It's up to the user to decide how many epochs to include in their timeline. Epochs are helpful because they visualize and summarize a subset of components. To this end, the epoch headers include a thumbnail that renders the regions and patterns created within the epoch, scaled to fit the thumbnail window. By default, Timelines consist of only one epoch. Clicking on the + buttons on either side of the timeline adds a new epoch in this location. If you have more than one epoch, you can move them around by clicking and holding the epoch and dragging it to a new location in the experiment design.

Within an epoch, allComponents components are executed from top to bottom, sequentially. It is similar to following the instructions of a cookbook or executing a programming script.

LabMaestro draws visual Regions that are higher up in an epoch before drawing the ones that are lower. Like other programming software, this means that regions drawn later will appear on top of previous visual regions, as if on so many layers.

By default, all visual regions are hidden when we exit an epoch. However, we can also hide them within an epoch using the Show/Hide Region Commands. We can also alter the behaviour of epochs to continue showing the visual stimuli in the following epoch.

LabMaestro provides several options for previewing experiment designs. However, it is important to note that the previews only have access to locally available information: Previews may not always be complete. For instance, you may have incorporated variable delays or method-driven values that may only come into full effect during runtime when clicking on ‘Launch Experiment'. Therefore, as part of the experiment design process, you should always examine the outputs of a deployed experiment file to ensure you have a comprehensive understanding of the experiment’s behaviour at runtime.