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Plot updates and serendipity code
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+1774
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‎data/results/final_plate_observations/exploitation/Phase 3 Final plate.xlsx

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‎data/results/final_plate_observations/exploitation/serendipity_values.csv

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model,amine,seren,success_fraction,volume_fraction
2+
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CLB0,ZKRCWINLLKOVCL-UHFFFAOYSA-N,0.145026955,1,0.000315138
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CLB1,HJFYRMFYQMIZDG-UHFFFAOYSA-N,0.172728165,0.666666667,0.004097769
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CLB1,JMXLWMIFDJCGBV-UHFFFAOYSA-N,0.071946741,0.8888888890000001,7E-05
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CLB1,NJQKYAASWUGXIT-UHFFFAOYSA-N,0.125784393,0.666666667,5.520000000000001e-05
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F1,JMXLWMIFDJCGBV-UHFFFAOYSA-N,0.489099105,1,7E-05
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KNN0,NJQKYAASWUGXIT-UHFFFAOYSA-N,0.327255,0.111111111,0.127278652
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KNN0,ZKRCWINLLKOVCL-UHFFFAOYSA-N,0.387769,0,0.309135952
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KNN1,HJFYRMFYQMIZDG-UHFFFAOYSA-N,0.318883,0,0.121225653
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KNN1,JMXLWMIFDJCGBV-UHFFFAOYSA-N,0.092155,0.222222222,0.106873082
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KNN1,NJQKYAASWUGXIT-UHFFFAOYSA-N,0.564203,0.333333333,0.187025983
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KNN1,ZKRCWINLLKOVCL-UHFFFAOYSA-N,0.389434,0,0.22041572
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MIT0,HJFYRMFYQMIZDG-UHFFFAOYSA-N,0.46650797200000005,1,0.001731045
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MIT0,JMXLWMIFDJCGBV-UHFFFAOYSA-N,0.740550478,0.111111111,0.004557252
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MIT0,NJQKYAASWUGXIT-UHFFFAOYSA-N,0.503770104,0.666666667,0.022228957999999997
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MIT0,ZKRCWINLLKOVCL-UHFFFAOYSA-N,0.564284083,1,0.003962866
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MIT1,JMXLWMIFDJCGBV-UHFFFAOYSA-N,0.268669877,0.5555555560000001,0.004419124
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MIT1,NJQKYAASWUGXIT-UHFFFAOYSA-N,0.740718167,0.7777777779999999,0.014005118
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PLT0,JMXLWMIFDJCGBV-UHFFFAOYSA-N,0.49168325,0.7777777779999999,0.262321257
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PLT0,NJQKYAASWUGXIT-UHFFFAOYSA-N,0.129446632,0.7777777779999999,0.064729926
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PLT0,ZKRCWINLLKOVCL-UHFFFAOYSA-N,0.76228785,0.5555555560000001,0.075935239
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PLT1,HJFYRMFYQMIZDG-UHFFFAOYSA-N,0.587091539,0.444444444,0.048210072
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PLT1,JMXLWMIFDJCGBV-UHFFFAOYSA-N,0.588206855,0.222222222,0.159116037
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PLT1,NJQKYAASWUGXIT-UHFFFAOYSA-N,0.47013977,0.444444444,0.005551108000000001
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PLT1,ZKRCWINLLKOVCL-UHFFFAOYSA-N,0.568191386,0.7777777779999999,0.07526031799999999

‎data/results/final_plate_observations/serendipity/serendipity_values.csv

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,model,amine,success_fraction,volume_fraction,seren
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‎data/stateset/HJFYRMFYQMIZDG-UHFFFAOYSA-N/vertices.csv

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‎data/stateset/JMXLWMIFDJCGBV-UHFFFAOYSA-N/vertices.csv

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‎data/stateset/NJQKYAASWUGXIT-UHFFFAOYSA-N/vertices.csv

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‎data/stateset/ZKRCWINLLKOVCL-UHFFFAOYSA-N/vertices.csv

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‎notebooks/exploitation_rec_results.ipynb

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‎notebooks/notebook_data/models_used.csv

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Model Code,Model Name
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KNN,K Nearest Neighbors
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DT,Decision Tree
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CLB,Bayesian Additive Regression Trees with Transfer Learning (BART+TL)
5+
PLT,PLATIPUS
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MIT,Bayesian Optimization using Gaussian Processes
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F,Atinary Falcon
8+
G,Falcon GPBO
9+
D,Falcon DNGO
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GR,Gryffin
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TA,Gaussian Processes with Transfer Acquisition Functions
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FH,Falcon with Historical data

‎notebooks/notebook_data/overview_flowchart.png

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‎requirements.txt

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findspark==1.4.2
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future==0.18.2
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greenlet==1.1.2
4+
idna==2.10
5+
imageio==2.6.1
6+
importlib-metadata==2.0.0
7+
ipykernel==5.5.5
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ipython==7.18.1
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ipython-genutils==0.2.0
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ipywidgets==7.6.5
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jedi==0.17.2
12+
joblib==0.14.0
13+
jupyter==1.0.0
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jupyter-client==6.1.7
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jupyter-console==6.2.0
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jupyter-core==4.6.3
17+
jupyterlab==2.3.2
18+
jupyterlab-pygments==0.1.2
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jupyterlab-server==1.2.0
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jupyterlab-widgets==1.0.2
21+
matplotlib==3.1.2
22+
modAL==0.3.6
23+
nbclient==0.5.1
24+
nbconvert==6.0.7
25+
nbformat==5.0.8
26+
nbterm==0.0.11
27+
notebook==6.1.4
28+
numpy==1.19.2
29+
openpyxl==3.0.9
30+
pandas==1.3.5
31+
plotly==5.3.1
32+
pyqtgraph==0.10.0
33+
pyspark==3.2.0
34+
scikit-image==0.16.2
35+
scikit-learn==1.0.2
36+
scipy==1.7.3
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seaborn==0.11.2

‎src/models/classification/BGP/perovskite_doe_bgp.py ‎src/models/regression/BGP/perovskite_doe_bgp.py

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