Seminar Series Description: The ability to program is increasingly important to the field of vision science. Programming experiments in Matlab or Python allows the researcher incredible flexibility to create the exact stimulus and analysis protocol desired. In this series, we will provide a solid foundation and entry-point for researchers to start using programming to enhance their research.
Over the course of 5 sessions, we will create a complete vision science experiment together in python and then analyze the results in Matlab. Future sessions build upon previous sessions, so attendees are encouraged to save their work and continue with the same files throughout the series. Files will be available for anybody who cannot access the previous week's script or were unable to attend the previous session.
To get the most out of this series, all attendees are encouraged to not miss sessions 2-5 if possible, and to actively practice the programming techniques even after the series ends.
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Session 1: Basic introduction to programming. This session is highly recommended for anybody who does not have any experience with programming. People who already have a basic understanding of the fundamental parts of a script (variables, arrays, flow control) may not want to attend this session.
June 25th
1-3 PM
Anticipated topics covered:
- Variables and manipulating variables
- lists/arrays, indexing
- flow control (if statements, while loops, for loops)
- Exploring differences in the above between Matlab and Python
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Session 2: Creating experimental stimuli with Python (PsychoPy), part 1.
July 2nd
1-3 PM
Anticipated topics covered:
- Structuring a stimulus script
- Displaying images
- Animating movement
- debugging techniques for PsychoPy Coder
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Session 3: Creating experimental stimuli in Python (PsychoPy), part 2.
July 9th
1-3 PM
Anticipated topics covered:
- Randomly interleaving different conditions (method of constant stimuli)
- registering participant responses
- saving/outputting data
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Session 4: Handling data in Matlab, part 1
July 16th
1-3 PM
Anticipated topics covered:
- Parsing/consolidating data files
- Effectively using arrays to avoid complicated and error-prone loop-based code
- Simple statistical tests
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Session 5: Handling data in Matlab, part 2
July 23rd
1-3 PM
Anticipated topics covered:
- Plotting/visualizing data
- Simple curve fitting (such as for psychometric functions)