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Supplemental Materials
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dataset
modified on 2018-07-23, 16:48 Stimuli, data, and model predictions for the paper titled "Modeling human intuitions about liquid flow with particle-based simulation" (Bates, Yildirim, Battaglia, Tenenbaum) forthcoming in PLOS Computational Biology.
Content Description
Stimuli:
Exp1_images: Images for all stimuli in Experiment 1Exp2_images: Images for all stimuli in Experiment 2
Exp1_movies: Videos used for practice trials in Experiment 1
Exp2_movies: Videos used for practice trials in Experiment 2
Data:
responses.zip: Subject responses, indexed by stimulus name, in Pickle format. These can be loaded in Python using:
import pickle
with open([file name], 'rb') as fid:
data = pickle.load(fid)
The resulting format will be a Python dictionary.
Model Predictions:
(Note: load using Python NumPy, e.g.
import numpy as np
data = np.load('path_to_file')
All files are simple, numpy arrays containing model predictions for each set of parameter values. See notes below for description of each dimension. Parameter values along a dimension always go from low to high.)
SPH ground truth:
exp1_grnd_water_200.npy
exp1_grnd_stickyhoney_100.npy
exp2_grnd_water_200.npy
exp2_grnd_stickyhoney_100.npy
Dimensions: (scenes)
SPH Intuitive Fluids Engine:
exp1_damping_alpha_0.01_0.2_2.0_sticky_N_1_5_10_15_25_50_75_100.npy
exp2_damping_alpha_0.01_0.2_2.0_sticky_N_1_5_10_15_25_50_75_100.npy
Dimensions: (scenes, alpha, zeta, # particles)
SPH Intuitive Fluids Engine (Position Noise, from Bates et al. 2015, referenced in text):
exp1_position_noise_alpha_0.01_0.2_2.0_sticky_noiselevels_5_N_1_5_10_15_25_50_75_100_samples_16.npy
exp2_position_noise_alpha_0.01_0.2_2.0_sticky_N_noiselevels_5_1_5_10_15_25_50_75_100_samples_16.npy
Dimensions: (scenes, alpha, noise magnitudes, # particles, noisy samples)
SimpleSim and Gravity Heuristic:
exp1_heuristic.npy
exp2_heuristic.npy
Dimensions: (scenes, g, m)
Convolutional Neural Networks:
convnet_exp1_water.npy
convnet_exp1_honey.npy
convnet_exp2_water.npy
convnet_exp2_honey.npy
Dimensions: (scenes)
