![]() ![]() ![]() ![]() Make sure you are cd’d into this folder in terminal/Anaconda Prompt, and from then on simply call python main.py whenever you would like to run the script. In the editor of your choice (Anaconda comes pre-equipped with GUIs such as Spyder and P圜harm, I also recommend Visual Studio Code or Atom (deprecated)), create a new python file main.py in some code repository. Numpy should be available as well, we’ll need it. With conda list letting us see that psychopy is indeed installed correctly. (base) > conda create -name psychopy python=3.8 Either in terminal (mac) or Anaconda Prompt (windows), creating a conda environment that will allow us to control the packages that are available and their versions. I recommend installing anaconda for this purpose. For this reason, you should always run your code from a virtual environment. PsychoPy, while useful, is not rigorously updated, and so you might encounter some dependency issues if you’re python version is too up to date. Brief Intro To Running Python Files in a Conda Environmentīefore we get started with the actual task design, a quick disclaimer regarding python and package management is necessary. Python always being an excellent choice, we today cover experiment creation in psychopy. While tools such as Qualtrics, which we have covered previously, are quick and easy for building surveys, to build more traditional tasks that collect responses requires a proper programming language. Experimentalists often find themselves needing to present carefully controlled stimuli to participants, control and catalog stimulus conditions, responses, reaction times, and other empirically variables of interest. ![]()
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