Write an expertimental code in python

Explanation:

Do you write code to run experiments? If so, you’ve probably had the experience of sitting down to code an experiment but getting side-tracked by all the logistics: crossing your independent variables to form conditions, repeating your conditions, randomization, storing intermediate data, etc. It’s frustrating to put all that effort in before even getting to what’s really unique about your experiment. Worse, it encourages bad coding practices like copy-pasting boilerplate from someone else’s experiment code without understanding it.

The purpose of experimentator is to handle all the boring logistics of running experiments and allow you to get straight to what really interests you, whatever that may be. This package was originally intended for behavioral experiments in which human participants are interacting with a graphical interface, but there is nothing domain-specific about it–it should be useful for anyone running experiments with a computer. You might say that experimentator is a library for ‘repeatedly calling a function while systematically varying its inputs and saving the data’ (although that doesn’t do it full justice).

Not handled here

graphics

timing

hardware interfacing

statistics

data processing

The philosophy of experimentator is to do one thing and do it well. It is meant to be used with other libraries that handle the above functionality, and gives you the freedom to choose which you prefer. It is best suited for someone with programming experience and some knowledge of the Python ecosystem, who would rather choose the best tool for each aspect of a project than use an all-in-one package.

Of course, there are alternatives that offer experimental design features along with other capabilities. A selection, as well as recommended complimentary packages, are listed later in the documentation.

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