Tools and scripts for working with the SolarJets zooniverse project.
In this README file we go through the workflow of this package, specifically the order in which the aggregation in run. The ipynb notebooks contained in this directory are listed with their primary function and when they can be usefull to open.
To install the required python modules, run the following in main repo folder:
python3 -m pip install -r requirements.txt# Start in the JetOrNot directory
cd JetOrNotFollow the steps in the README JetOrNot to do the aggregation steps of the data.
Look at the jet subject and non-jet subjects distribution over time.
jet_time_distribution.ipynb
Look at the resulting agreements and check the number of votes per subject.
jetornot.ipynb
Plot the agreement of the subjects in Jet Or Not workflow over time. Sorted by SOL/ HEK event
Plotting_agreement_T0.ipynb
cd ..
cd BoxTheJets/Follow the steps in the README BoxTheJets to do the aggregation steps of the data.
Look at the first results of the jet aggregation. Check the resulting box and point clusters and the aggregation code in multiple jet subjects.
simple_analysis.ipynb
Calculate the confidence of the jets found in the subjects. Are the jets of high quality or should a cut be made based on their confidence scores.
jet_confidence.ipynb
Plot the agreement of the Jet Or Not question asked during the BoxThe Jets workflow, sorted by SOL/HEK event. Note that gaps will be present in the graphs due to the presence of only the pushed subjects.
Plotting_agreement_T3.ipynb
From here you can also go on and export the Jet clusters from Find_export_jet_clusters.ipynb using the SOL_T3_stats.csv and subjects_T3.csv made files. However, since the question of the JetOrNot workflow and first question of the BoxTheJets workflow we can also combine the answers to get a better count on the agreement scores.
cd ..python3 make_Tc_csvfiles.pyThis combines the binary resulting of the first workflow and second workflow questions to make the combined answers. This creates the SOL_Tc_stats.csv and subjects_Tc.csv in the main directory.
Plot the agreement of the combined result of subjects over time. Sorted by SOL/ HEK event
Plotting_agreement_Tc.ipynb
Look at the results of the two workflow questions. Are the agreements scores changing during the second workflow? Do many subjects go from 'yes' to 'no' jet during the second worflow? Are the right subjects being send through?
Analysis_combined_question_results.ipynb
Go back to the BoxTheJet/ folder
cd BoxTheJets/Open Find_export_jetclusters.ipynb and run the code until the end. Note that at the moment this part of the code can only be done on the foxsiadmins computer becaus access to the database is required.
The export will be done in a json and a csv format. The csv format will be easier to quickly work with for the statistics, but for full access to the aggregated zooniverse data and the functions written for the JetCluster object the json file has a wider functionality.
Look at the jet size evolution per SOL/HEK event
Plotting_box_size.ipynb
Go back to main directory for the two last jupyter notebooks.
cd ..Look at the extracted properties of the jet clusters. Get histograms of the length, width, duration, velocity, base position and uncertainty. Possibly filter data on a maximal uncertainty. Plot the jet location on the solar map.
Jet_statistics.ipynb
Visualise the final Jet clusters, get the plots made during the aggregation per SOL/ HEK event and export the json or gif from one jet cluster.
Looking_jets_plots.ipynb