apply_PLSR_coeffs_cmd.py

# -*- coding: utf-8 -*-
"""
Created on Mon Nov 26 14:29:10 2018

Based on Zhihui's apply_PLSR_coeffs script.

Applying ASD fresh spectra models and predict traits
"""
import argparse
import numpy as np, os,pandas as pd,glob

def main():    
    #-----------------parse inout and output
    parser = argparse.ArgumentParser(description = "Apply ASD fresh spectra models for trait prediction")
    parser.add_argument("-outDir", help="Output directory",required=True, type = str)
    parser.add_argument("-plsrDir", help="Directory for PLS coefficients", required=True, type = str)
    parser.add_argument("--specCSV", help="Spectra csv file name with full directory ", required=True, type = str)
    args = parser.parse_args()
    
    
    plsrCSVs = glob.glob("%s/*.csv" % args.plsrDir)
#    plsrCSVs = glob.glob(plsrDir+'*.csv')
    plsrCSVs = sorted(plsrCSVs)
    
    df_spec = pd.read_csv(args.specCSV, sep=',')
    spec = df_spec.iloc[:,0:2151].values
    
    #---------------vector normalization
    spec_len = np.tile(np.linalg.norm(spec, axis=1), (spec.shape[1], 1))
    spec = spec/spec_len.T
    
    #---------------5nm resampling
    wl_step = 5
    wl = np.arange(350,2501)
    spec = spec[:,0::wl_step]
    wl = wl[0::wl_step]
    
    #----------------appyling PLSR coefficients
    df_all=pd.DataFrame()
    df_all=df_spec.iloc[:,2151:]
    
    for plsrCSV in plsrCSVs:
        trait_model = pd.read_csv(plsrCSV, sep=',', index_col=0).values
        intercept = trait_model[:, 0]
        coefficients = np.array(trait_model[:, list(np.arange(1, trait_model.shape[1]))])
        
        traitPred = np.einsum('jl,ml->jm',spec,coefficients, optimize='optimal')
        traitPred = traitPred + intercept
        traitPred_mean = traitPred.mean(axis=1)
        traitPred_std = traitPred.std(axis=1,ddof=1)
    
        trait = os.path.basename(plsrCSV)[14:-4]
        df_all.loc[:,trait+'_mean'] = traitPred_mean
        df_all.loc[:,trait+'_std'] = traitPred_std
    
    #----------------write predicted traits to csv
    outfile = os.path.join(args.outDir,os.path.basename(args.specCSV)[:-4]+'_traits.csv')
    df_all.to_csv(outfile)

		
if __name__== "__main__":
    main()


#python apply_PLSR_coeffs_cmd.py -outDir ./output/ -plsrDir ./coefficients --specCSV test_spectra.csv