Image randomizer1/9/2024 ![]() MyDat = myDat.sample(frac=1).reset_index(drop=True) # Shuffle the dataframe MyDat = pd.read_csv(files) # Get conditions file ![]() This is the code in question: import pandas as pdįileName = ĬonditionFile = pd.DataFrame(columns=) # where 'painting' is the column name for your images However, this meant that the same 16 images after being randomly selected from the 2 files would be shown across all blocks, just in a random order. Therefore, I would like to present 16 images in each block, randomly choose 8 out of the 32 images from the ‘low’ object file, and 8 out of the 32 images from the ‘high’ object file, without using the images again in a later block.Īfter sifting through the forum, the closest solution i could find was how to create a new condition file for each run. I would like to vary the block order so that it is counterbalanced, and also would like to use all 64 images once only in the entire experiment, but randomise the order in which it appears to each participant while still maintaining the structure of 8 ‘low’ images and 8 ‘high’ images per block. I have a list of 32 images for ‘low’ and a list of 32 images for ‘high’, in total. Each block will show a total of 8 ‘low’ images, and 8 ‘high’ images. There will be 16 trials in each block, where each trial is the display of an image. ![]() These images vary based on whether they are low in number of objects or high in number of objects. The design is a within-subjects design, where participants will be shown images across 4 different task instructions (blocks). I’m completely new to PsychoPy (and any sort of coding), and would really appreciate any sort of help! ![]()
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