Mass Inference Project

A project exploring how people make inferences about the masses of objects.

Choosing stimuli

First, pick stimuli by executing code in the notebook lib/mass/analysis/choose-stimuli.ipynb. This will create new directories in resources/sso for the desired stimuli.

Running simulations

You can run most everything with the script bin/simulate.py, though if you need finer-grained control over individual steps of the simulations, you can use the scripts in bin/simulate. For each step, both options are listed, or you can run all steps at once using bin/simulate.py --all.

Note, however, that the client will still need to be run separately: if you run bin/simulate.py --all, when it gets to the server, it will run the server and wait for a client to connect. Once all simulations are run and the server exits, it will move on to processing the simulations.

1. First you need to generate sim scripts:

   bin/simulate.py -e mass_inference -t G-b-truth --generate bin/simulate/generate_script.py -e mass_inference -t G-b-truth.

2. Then, launch the server with the appropriate parameters for the simulation, e.g.:

   bin/simulate.py -e mass_inference -t G-b-truth --run-server bin/simulate/run_simulations.py server -e mass_inference -t G-b-truth -k hello -f

3. Then run the client, e.g.:

   bin/simulate.py -e mass_inference -t G-b-truth --run-client bin/simulate/run_sims.py client -k hello -s -n 2

4. Finally, process the simulations and save them as datapackages:

   bin/simulate.py -e mass_inference -t G-b-truth --process bin/simulate/process_simulations.py -e mass_inference -t G-b-truth

Computing model queries

TODO: more details on computing model queries

1. Run bin/process_model_fall.py
2. Run bin/save_stability.py

Rendering stimuli

You can run most everything with the script bin/render.py, though if you need finer-grained control over individual steps of the render, you can use the scripts in bin/render. For each step, both options are listed, or you can run all steps at once using bin/render.py --all.

1. First create the rendering scripts:

   bin/render.py -e mass_inference-G --generate bin/render/generate_script.py -e mass_inference-G

2. Then run the renderer with the appropriate parameters, e.g.:

   bin/render.py -e mass_inference-G --render bin/render/render_stimuli.py -e mass_inference-G

3. Now convert the videos that were rendered to various webformats:

   bin/render.py -e mass_inference-G --convert bin/render/convert_videos.py -e mass_inference-G

Deploying the experiment

TODO: more details on deploying the experiment

1. Run bin/experiment/link_stimuli.py
2. Run bin/experiment/generate_configs.py
3. Run bin/experiment/deploy_experiment.py