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Statistical modeling tools, to unify model creation and scoring based on python

Project description

Agmodeling

Statistical modeling tools, to unify model creation and scoring based on python

package agmodeling.setscoring implements a part of the SET method for comparing sensor output as described by :

An Evaluation Tool Kit of Air Quality 1 Micro-Sensing Units (Barak Fishbain1,Uri Lerner, Nuria Castell-Balaguer)

What’s New

  • (2019/08) python 3 support (v 0.4)
  • (2018/11) First version (v 0.3)

Dependencies

Agmodeling is written to be use with python 2.7 and python 3.6 It requires Pandas, numpy and scipy It requires Pandas:

pip install pandas
pip install numpy
pip install scipy

Installations

pip install agmodeling

Uses cases

from agmodeling.scoring.set_method import get_IPI_score import pandas as pd

file = u’sample_data.xlsx’ print (u’Read excel data file : %s’%file) df = pd.read_excel(file) ipi = get_IPI_score(df[u”PM10_REF”], df[u”PM10_MOD_EARTH”])

print ipi

Match : RMSE : Pearson : Kendall : Spearman : LFE :: IPI

0.763240 : 0.061937 : 0.909195 : 0.657553 : 0.832455 : 0.990418 :: 0.848801

0.848801

You can run the whole demo inside the package

cd demo python .demo_SET_scoring.py Read excel data file : sample_data.xlsx containing 2568 data

Score IPI for PM25_RAW
Match : RMSE : Pearson : Kendall : Spearman : LFE :: IPI 0.492835 : 0.869434 : 0.639916 : 0.417968 : 0.575632 : 0.980010 :: 0.539488
Score IPI for PM25_MOD_QUAD
Match : RMSE : Pearson : Kendall : Spearman : LFE :: IPI 0.687539 : 0.374117 : 0.747821 : 0.524258 : 0.695786 : 0.980010 :: 0.710216
Score IPI for PM25_MOD_EARTH
Match : RMSE : Pearson : Kendall : Spearman : LFE :: IPI 0.648910 : 0.337527 : 0.800773 : 0.537126 : 0.713852 : 0.980010 :: 0.723857
Score IPI for PM10_RAW
Match : RMSE : Pearson : Kendall : Spearman : LFE :: IPI 0.486604 : 0.786641 : 0.454199 : 0.269705 : 0.393423 : 0.990388 :: 0.467946
Score IPI for PM10_MOD_QUAD
Match : RMSE : Pearson : Kendall : Spearman : LFE :: IPI 0.742056 : 0.221220 : 0.866073 : 0.612143 : 0.789426 : 0.990388 :: 0.796478
Score IPI for PM10_MOD_EARTH
Match : RMSE : Pearson : Kendall : Spearman : LFE :: IPI 0.763240 : 0.184250 : 0.909195 : 0.657553 : 0.832455 : 0.990388 :: 0.828097

Results : ” RAW MOD_QUAD MOD_EARTH PM10 0.467946 0.796478 0.828097 PM25 0.539488 0.710216 0.723857”

Fin du programme

Project details


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