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./run_models.sh runs all models and outputs to txt/model_*.txt NOTE that the formatting in txt/ is special (i.e. it doesn't get printed out that way), and you COULD be overwriting things by running the script. (Don't worry. This is on github.) If you want to run the models yourself, you can run them individually with: python model_<whatever>.py You can also create basic visualizations of the raw data with python vis_basic.py To run tSNE and PCA and get some fancy 3D animated images, run python vis_transform.py ########################### You can find existing images in png/ png/analysis: graphs current error of models vs naive png/basic-vis: outputs from vis_basic png/vis: outputs from vis_transform (including 3d animated spinny graph of the data post-tSNE) png/models: includes ALLL the images from running the HMM baum-welch algorithm (there are a lot) The name format is as such: <location> - <model name> - <data plotted> <num hidden states> . png Note that the x axis is always time, the y axis is always the <data plotted>, and the color always refers to the hidden states. ######################## How to read the output in txt/ step1: pay attention if there's any direct warning messages Here's how to read a sample format of the output: in txt/model_basic.txt: | ##### LGA ##### shape of data --| (25103, 21) | | fitting to HMM, c=2 transition matrix| [[ .91 .09] | [ .17 .83]] data headers-----|---MaxT MeanT MinT MaxD MeanD MinD MaxH MeanH MinH MaxP MeanP MinP MaxV MeanV MinV MaxW MeanW Rain Cloud WindDir WindDir state means-.--|-[[52.23 45.97 39.54 38.43 31.77 25.33 76.99 60.45 44.49 29.79 29.61 29.42 14.6 11.2 7.22 20.22 12.67 . 2.46 3.44 -3.73] \-|--[79.05 72.12 65.15 65.09 60.7 55.67 86.51 70.48 52.35 29.69 29.49 29.32 12.11 8.05 4.17 17.6 9.82 .11 2.81 -1.51 -0.60]] | MaxT MeanT MinT MaxD MeanD MinD MaxH MeanH MinH MaxP MeanP MinP MaxV MeanV MinV MaxW MeanW Rain Cloud WindDir WindDir error metric------|-HMM,----c=2.0: >4.583< average errors--|--[11.26 10.37 9.79 10.2 10.54 11.12 12.5 11.99 12.98 .39 .49 .46 3.72 1.7 3.54 4.85 3.28 .08 2.73 5.67 6.36]
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