Python for Experimental Psychologists

About this book II About Python 3 About the authors 3 1. Python 1 1.1 Installation 3 1.1.1 Versions 3 1.1.2 Dependencies 4 1.1.3 Anaconda 5 1.1.4 WinPython 6 1.1.5 Installing packages with pip 6 1.2 Terminal and interpreter 8 1.3 Editor 11 2. Variable Types 13 2.1 Numbers 13 2.1.1 Integers 14 2.1.2 Floats 16 2.2 Assigning Variables 19 2.3 Booleans 22 2.4 Letters 26 2.4.1 Strings 26 2.4.2 String Functions 27 2.4.3 String formatting 29 2.5 Sets 32 2.5.1 Lists 33 2.5.2 Tuples 40 2.5.3 Arrays 41 2.5.4 NumPy Arrays 43 2.5.5 Dictionaries 45 2.6 Classes 48 2.7 Functions 49 2.7.1 Arguments 53 2.7.2 Keyword arguments 54 2.7.3 Local and Global Variables 56 2.7.4 Create Your First Function 57 2.7.5 Create Your Second Function 58 2.7.6 Create Your Third Function 59 Make Some Noise 62 Random Numbers 62 Noise 63 Matplotlib 65 3. Creating and Presenting Stimuli 67 3.1 Scripts 68 3.2 The PsychoPy Coder View 69 3.3 The Window 70 3.3.1 Units and Colours in PsychoPy Windows 72 3.4 Comments 75 3.5 Make some text 76 3.4.1 Understanding win.flip() 77 3.5 Throwing Shapes 80 3.6 Presenting Images 81 3.6.1 Adding masks to images using Numpy arrays 82 3.6.2 Blurring images using Python Imaging Library 84 3.6 Making many stimuli 85 3.6.1 Creating stimuli in random locations 86 3.6.2 For Loops 87 3.6.3 Indentation 89 3.6.4 While Loops 92 3.6.5 Using Loops to generate many stimuli 95 3.6.5 Element Array Stim 96 3.7 Timing visual stimuli by frames 98 3.8 Making dynamic stimuli 100 3.9 Comments (again) 102 4. Processing Responses 103 4.1 Are Peripherals Accurate Enough? 104 4.2 Keyboard input 106 4.2.1 Waiting for Keyboard input 107 4.2.3 Understanding the “zero point” of keyboard response times 110 4.2.2 Fetching Keyboard input without waiting 112 4.3 If Statements 114 4.4 Typed responses 116 4.5 Mouse Responses 118 4.5.1 Fetching the current mouse position 119 4.5.2 Check the status of the mouse buttons 120 4.5.4 Check for mouse scroll behaviour 122 4.6 Using while loops with the mouse 123 Make Some Noise 125 What Is Sound? 125 Sinusoid and Noise 125 Numbers To Sound 131 5. Scripting An Experiment 137 5.1 Make a single trial 138 5.1.1 Presenting stimuli in our experiment 139 5.1.2 Using functions in experiments 142 5.1.3 Gathering responses in our experiment 144 5.2 Presenting several trials 145 5.2.1 using variable timing trial-by-trial 147 5.3 Importing spreadsheets and saving data 148 5.3.1 Importing a spreadsheet of trials 149 5.3.2 The TrialHandler 151 5.3.3 The Experiment Handler 152 5.4 Gathering participant information 153 5.4.1 Constants 153 5.4.2 Presenting a dialogue box 154 5.5 Storing keyboard accuracy 156 5.6 Block designs and counterbalancing 158 5.6.1 Randomised block designs 158 5.6.2 Counterbalanced block designs 160 5.7 Understanding the data 161 Make Some Noise 163 Do You Have A Joystick? 163 Using a Joystick 165 Using a Keyboard 168 Playing Sounds On Button Presses 171 Unexpected Instrument 175 6. Analysing Behavioural Data 178 6.1 Analysis Plan 178 6.2 Extracting Data 180 6.3 Selecting Data 187 6.4 Averaging Data 190 6.5 Plotting Data 195 6.6 Combining Datasets 201 6.7 Statistical Testing 216 7. Analysing Traces 219 7.0.1 Pupil Size 219 7.0.2 PyGaze Analyser 220 7.1 Read Eye-Tracker Data 220 7.2 Plot Your First Trace 223 7.3 Averaging Traces 227 8. Eye Tracking 237 8.0.1 The Basics 238 8.1 Creating An Eye-Tracking Experiment 240 8.1.1 Materials 240 8.1.2 constants.py 241 8.1.3 Screens 244 8.1.4 The EyeTracker Class 246 8.1.5 Single Trial 249 8.1.6 Whole Experiment 254 8.2 Processing Gaze Data 256 8.2.1 Extracting Gaze Data 258 8.2.2 Processing Gaze Data 263 8.2.3 Analysing Fixations 265 9. Common Statistical Tests 273 9.1 UGH BORING 273 9.1.1 Variance and Error 273 9.1.2 When is something surprising? 276 9.2 T-tests 278 9.2.1 What is a p-value? 279 9.2.2 One-sample t-test 280 9.2.3 Related-samples t-test 282 9.2.4 Independent-samples t-test 284 9.3 Correlation 285 9.3.1 Covariance 286 9.3.2 Pearson's R coefficient 287 9.3.3 Spearman's ρ coefficient 288 9.3.4 Side-note: Who are these tests named after? 289 9.4 Linear regression 289 9.4.1 Univariable linear regression 291 4.9.2 Multivariable linear regression 292 Getting Help 298 Stack Overflow 298 Documentation Websites 298 PyGaze Forum 298 Acknowledgements 300 References 302