Delete meris.py

GRSL/MERIS_dataset_generation/meris.py

-# -*- coding: utf-8 -*-
-"""
-Created on Wed Mar 23 10:41:37 2022
-
-@author: Utente
-"""
-import numpy as np
-import os
-os.chdir('C:\\Users\\Utente\\Desktop\\Julich\\Synthetic\\MERIS')
-
-import library as lib
-
-
-
-#mu and sigmas refer to the underlying normal distribution, not the distribution itself
-
-wl_array=[412.5,442.5,490,510,560,620,665,681.25]
-
-n_samples=630
-
-C_mu=-0.86
-X_mu=-1.21
-Y_mu=-1.75
-
-C_sigma=0.3
-X_sigma=0.3
-Y_sigma=0.3
-
-corr_CX=0.8
-corr_CY=0.8
-
-##########################################à
-
-mu=np.array([C_mu,X_mu,Y_mu])
-cov=np.zeros((len(mu),len(mu)))
-
-# for i in range(len(mu)):
-#     cov[i,i]=mu[i]
-
-
-cov[0,0]=C_sigma
-cov[1,1]=X_sigma
-cov[2,2]=Y_sigma
-
-
-
-cov_CX=corr_CX*C_sigma*X_sigma
-cov_CY=corr_CY*C_sigma*Y_sigma
-
-#######################################
-
-cov[0,1]=cov_CX
-cov[1,0]=cov_CX
-
-cov[0,2]=cov_CY
-cov[2,0]=cov_CY
-
-###################################
-
-generator=np.random.default_rng()
-
-samples=generator.multivariate_normal(mean=mu,cov=cov,size=n_samples)
-
-#samples_a=np.random.multivariate_normal(mean=mu,cov=cov,size=n_samples)
-
-oap=np.exp(samples)
-
-#%%
-
-################################
-
-R=np.zeros((oap.shape[0],len(wl_array)))
-
-for i in range(R.shape[0]):
-    C,X,Y=oap[i,:]
-    
-    R[i,:]=lib.get_reflectance_vector(wl_array, C, X, Y)
-    
-
-
-##############################
-#remember to convert to apply the logarithm the dataset!!
-
-
-C_array=oap[:,0]
-
-save_path='C:\\Users\\Utente\\Desktop\\Julich\\Synthetic\\MERIS\dataset\\'
-
-np.save(save_path+'target.npy',C_array)
-np.save(save_path+'input.npy',R)
-np.save(save_path+'oap.npy',oap)