agmodeling 0.3

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

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
===========
- (2018/11) First version (v 0.3)



Dependencies
=============

Agmodeling is written to be use with python 2.7
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 : 0.238941 : 0.639916 : 0.417968 : 0.575632 : 0.980072 :: 0.648981

Score IPI for PM25_MOD_QUAD
Match : RMSE : Pearson : Kendall : Spearman : LFE :: IPI
0.687539 : 0.102816 : 0.747821 : 0.524258 : 0.695786 : 0.980072 :: 0.756295

Score IPI for PM25_MOD_EARTH
Match : RMSE : Pearson : Kendall : Spearman : LFE :: IPI
0.648910 : 0.092760 : 0.800773 : 0.537126 : 0.713852 : 0.980072 :: 0.765357

Score IPI for PM10_RAW
Match : RMSE : Pearson : Kendall : Spearman : LFE :: IPI
0.486604 : 0.264435 : 0.454199 : 0.269705 : 0.393423 : 0.990418 :: 0.560331

Score IPI for PM10_MOD_QUAD
Match : RMSE : Pearson : Kendall : Spearman : LFE :: IPI
0.742056 : 0.074365 : 0.866073 : 0.612143 : 0.789426 : 0.990418 :: 0.821408

Score IPI for PM10_MOD_EARTH
Match : RMSE : Pearson : Kendall : Spearman : LFE :: IPI
0.763240 : 0.061937 : 0.909195 : 0.657553 : 0.832455 : 0.990418 :: 0.848801

========================================
Results :
RAW MOD_QUAD MOD_EARTH
PM10 0.560331 0.821408 0.848801
PM25 0.648981 0.756295 0.765357

Fin du programme