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| Original file line number | Diff line number | Diff line change |
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| #!/usr/bin/env python3 | ||
| # -*- coding: utf-8 -*- | ||
| """ | ||
| Created on Thu Apr 2 11:31:54 2020 | ||
| @author: yannick | ||
| """ | ||
|
|
||
| import numpy,os,pandas | ||
| import matplotlib.pyplot as plt | ||
| import mpl_toolkits.mplot3d as plt3d | ||
| import LIBStick_echange_vars | ||
|
|
||
| #rep_travail="/home/yannick/Bureau/LIBS/Scripts_divers_pour_LIBS/Fluorose_LIBS/Spectres_moyen/528-543/" | ||
| #bornes_moyenne_spectres=numpy.linspace(528,543,150) | ||
| limites_zone1=[534.5 , 535.8] | ||
| limites_zone2=[528.0 , 543.0] | ||
| limites_spectre=[528.0, 543.0] | ||
|
|
||
| ############################################################################### | ||
| # 1- fonction qui liste des fichiers *.mean d'un répertoire | ||
| ############################################################################### | ||
| def repertoire_de_travail(rep_script,rep_travail_relatif): | ||
| rep_travail=rep_script+"/"+rep_travail_relatif | ||
| return rep_travail | ||
|
|
||
| def creation_liste_fichiers(rep_travail): | ||
| os.chdir(rep_travail) | ||
| liste=[] | ||
| for fichier in os.listdir(): | ||
| if (os.path.isfile(fichier) and fichier[-4:] == "mean") : | ||
| liste.append(fichier) | ||
| liste.sort() | ||
| return liste | ||
|
|
||
| def lit_spectre(fichier,tableau_abscisses): | ||
| spectre=numpy.loadtxt(fichier,delimiter="\t",usecols=[0],dtype=float,encoding="Latin-1") | ||
| #tableau_abscisses=lit_tableau_abscisses() | ||
| spectre=numpy.vstack((tableau_abscisses,spectre)) | ||
| # spectre=numpy.zeros((0,document.shape[0])) | ||
| # for ligne in document : | ||
| # spectre=numpy.row_stack((spectre,ligne)) | ||
| return spectre | ||
|
|
||
| def lit_tableau_abscisses(): | ||
| global tableau_abscisses | ||
| tableau_abscisses=numpy.loadtxt("tableau_abscisses.txt", delimiter="\t", usecols=[0]) | ||
| return tableau_abscisses | ||
|
|
||
| def creer_tableau(liste): | ||
| i=0 | ||
| for nom_fichier in liste : | ||
| if i==0 : | ||
| fichier_entree=numpy.loadtxt(nom_fichier, delimiter="\t", usecols=[0]) | ||
| #print(fichier_entree) | ||
| tableau_comparatif=numpy.zeros((0,fichier_entree.shape[0])) | ||
| tableau_comparatif=numpy.row_stack((tableau_comparatif,fichier_entree)) | ||
| else : | ||
| fichier_entree=numpy.loadtxt(nom_fichier, delimiter="\t", usecols=[0]) | ||
| tableau_comparatif=numpy.row_stack((tableau_comparatif,fichier_entree)) | ||
| i=i+1 | ||
| #print(tableau_comparatif.shape) | ||
| return tableau_comparatif | ||
|
|
||
| def creer_DataFrame(tableau_comparatif,liste, tableau_abscisses): | ||
| DataFrame_comparatif=pandas.DataFrame(data=tableau_comparatif, index=liste, columns=tableau_abscisses) | ||
| return DataFrame_comparatif | ||
|
|
||
| def creer_DataFrame_resultats(DataFrame_comparatif, limites_zone1,limites_zone2): | ||
| DataFrame_tableau_calculs=pandas.DataFrame() | ||
| Sous_DataFrame = DataFrame_comparatif.loc[ : , limites_zone1[0]:limites_zone1[1]] | ||
| #print(Sous_DataFrame) | ||
| DataFrame_tableau_calculs["Somme zone 1"] = Sous_DataFrame.sum(axis=1) | ||
| Sous_DataFrame = DataFrame_comparatif.loc[ : , limites_zone2[0]:limites_zone2[1]] | ||
| #print(Sous_DataFrame) | ||
| DataFrame_tableau_calculs["Somme zone 2"] = Sous_DataFrame.sum(axis=1) | ||
| DataFrame_tableau_calculs["Rapport"]=DataFrame_tableau_calculs["Somme zone 1"] / DataFrame_tableau_calculs["Somme zone 2"] | ||
| return DataFrame_tableau_calculs | ||
|
|
||
| def Convertir_Dataframe_tableau(DataFrame_comparatif): | ||
| tableau=DataFrame_comparatif.values | ||
| tableau= numpy.delete(tableau, -1 , axis=1) | ||
| return tableau | ||
|
|
||
| def enregistre_DataFrame_resultats(DataFrame_resultats): | ||
| DataFrame_resultats.to_csv("Resultat_fichiers_classes.csv") | ||
| DataFrame_resultats.to_csv("Resultat_fichiers_classes.tsv", sep='\t') | ||
|
|
||
| ############################################################################### | ||
| # 2- fonction d'affichage graphique du tableau de résultats | ||
| ############################################################################### | ||
| def tableau_256gris(tableau_norm): | ||
| tableau8bits=tableau_norm*255 | ||
| tableau8bits=tableau8bits.astype(int) | ||
| return tableau8bits | ||
|
|
||
| def graphique_creation(tableau8bits,nom_echantillon,limites_spectre): | ||
| #fig=plt.figure() | ||
| fig, ax=plt.subplots() | ||
| #plt.imshow(tableau8bits, cmap="gray", extent=[limites_spectre[0],limites_spectre[1],tableau8bits.shape[0],0], aspect="auto") | ||
| plt.imshow(tableau8bits, cmap="inferno", extent=[limites_spectre[0],limites_spectre[1],tableau8bits.shape[0],0], aspect="auto") | ||
| #print(tableau8bits.shape[0]) | ||
| #print(tableau8bits.shape[1]) | ||
|
|
||
| #imageplot=plt.imshow(tableau8bits, cmap="hot") | ||
| #imageplot=plt.imshow(tableau8bits, cmap="nipy_spectral") | ||
| #plt.colorbar() | ||
| plt.title(nom_echantillon) | ||
| plt.xlabel("Longueur d'onde (nm)") | ||
| plt.ylabel( "Spectres echantillons classés") | ||
| plt.yticks(range(0,tableau8bits.shape[0],5)) | ||
| ax.yaxis.get_ticklocs(minor=True) | ||
| ax.minorticks_on() | ||
| ax.xaxis.set_tick_params(which='minor', bottom=False) | ||
| plt.savefig("figure_plot.png") | ||
| #plt.xlim(limites_spectre[0], limites_spectre[1]) | ||
| #plt.ioff() | ||
| plt.show(block=False) | ||
|
|
||
| def graphique_3D_creation(tableau8bits,nom_echantillon,limites_spectre): | ||
| xx, yy = numpy.mgrid[0:tableau8bits.shape[0], 0:tableau8bits.shape[1]] | ||
| #fig = plt.figure(figsize=(15,15)) | ||
| fig = plt.figure() | ||
| ax = fig.gca(projection='3d') | ||
| ax.plot_surface(xx, yy, tableau8bits ,rstride=1, cstride=1, cmap="inferno",linewidth=0, antialiased=False) | ||
| ax.view_init(80, 30) | ||
|
|
||
| plt.title(nom_echantillon) | ||
| plt.ylabel("Longueur d'onde (nm)") | ||
| plt.xlabel( "Spectres suivant z") | ||
| #ax.set_ylim(limites_spectre[0],limites_spectre[1]) | ||
|
|
||
| plt.xticks(range(0,tableau8bits.shape[0],5)) | ||
| ax.xaxis.get_ticklocs(minor=True) | ||
| ax.minorticks_on() | ||
| ax.yaxis.set_tick_params(which='minor', bottom=False) | ||
|
|
||
| plt.show(block=False) | ||
|
|
||
| def graphique_sauvegarde(tableau8bits) : | ||
| plt.imsave("figure.png",tableau8bits, cmap="inferno") | ||
|
|
||
| ############################################################################### | ||
| # programme principal | ||
| ############################################################################### | ||
| def main(rep_travail, tableau_bornes): | ||
| os.chdir(rep_travail) | ||
| liste=LIBStick_echange_vars.L_comp_liste_fichiers | ||
| tableau_comparatif=creer_tableau(liste) | ||
| #tableau_abscisses=lit_tableau_abscisses() | ||
| DataFrame_comparatif=creer_DataFrame(tableau_comparatif,liste,tableau_abscisses) | ||
| limites_zone1[0]=tableau_bornes[0,0] | ||
| limites_zone1[1]=tableau_bornes[0,1] | ||
| limites_zone2[0]=tableau_bornes[1,0] | ||
| limites_zone2[1]=tableau_bornes[1,1] | ||
| DataFrame_resultats=creer_DataFrame_resultats(DataFrame_comparatif,limites_zone1,limites_zone2) | ||
| DataFrame_comparatif=pandas.concat([DataFrame_comparatif, DataFrame_resultats["Rapport"]], axis=1) | ||
| DataFrame_comparatif=DataFrame_comparatif.sort_values(by=["Rapport"]) | ||
| #print(DataFrame_comparatif) | ||
| LIBStick_echange_vars.L_comp_DataFrame_resultats = DataFrame_resultats = DataFrame_resultats.sort_values(by=["Rapport"]) | ||
| print(DataFrame_resultats.shape) | ||
| enregistre_DataFrame_resultats(DataFrame_resultats) | ||
|
|
||
| tableau_comparatif=Convertir_Dataframe_tableau(DataFrame_comparatif) | ||
| #print (tableau_comparatif) | ||
| #print (tableau_comparatif.shape) | ||
|
|
||
| tableau8bits=tableau_256gris(tableau_comparatif) | ||
| if LIBStick_echange_vars.L_comp_flag_2D : | ||
| graphique_creation(tableau8bits, "Echantillons classés", limites_spectre) | ||
| if LIBStick_echange_vars.L_comp_flag_3D : | ||
| graphique_3D_creation(tableau8bits, "Echantillons classés", limites_spectre) | ||
| graphique_sauvegarde(tableau8bits) | ||
|
|
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| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -0,0 +1,61 @@ | ||
| #!/usr/bin/env python3 | ||
| # -*- coding: utf-8 -*- | ||
| """ | ||
| Created on Mon Mar 23 14:42:42 2020 | ||
| @author: yannick | ||
| """ | ||
|
|
||
| import numpy,os | ||
| import LIBStick_echange_vars | ||
|
|
||
| ############################################################################### | ||
| # 1- fonctions | ||
| ############################################################################### | ||
| def extraction_spectres(tableau_norm): | ||
| #tableau_extrait=LIBStick_creation_tableau_norm.tableau_norm.copy() | ||
| tableau_extrait=tableau_norm.copy() | ||
| print ("format tableau initial : ") | ||
| print(tableau_extrait.shape) | ||
| indice_premier=(LIBStick_echange_vars.L_ext_bornes_moyenne_spectres[0]-1) | ||
| indice_dernier=(LIBStick_echange_vars.L_ext_bornes_moyenne_spectres[1]-1) | ||
| cols_supprime_debut=list() | ||
| cols_supprime_fin=list() | ||
| if indice_premier > 0 : | ||
| for i in range(0,indice_premier) : | ||
| cols_supprime_debut.append(i) | ||
| if indice_dernier < LIBStick_echange_vars.L_ext_nombre_fichiers : | ||
| for i in range(indice_dernier+1, LIBStick_echange_vars.L_ext_nombre_fichiers): | ||
| cols_supprime_fin.append(i) | ||
| cols_supprime=cols_supprime_debut+cols_supprime_fin | ||
| print ("colonnes à supprimer : ") | ||
| print(cols_supprime) | ||
| tableau_extrait=numpy.delete(tableau_extrait, cols_supprime, axis=1) | ||
| print ("format tableau extrait : ") | ||
| print(tableau_extrait.shape) | ||
| return tableau_extrait | ||
|
|
||
| def creation_spectre_moyen(tableau_extrait): | ||
| spectre_moyen=tableau_extrait.sum(axis=1) | ||
| spectre_moyen=spectre_moyen/tableau_extrait.shape[1] | ||
| print("format spectre moyen : ") | ||
| print(spectre_moyen.shape) | ||
| return spectre_moyen | ||
|
|
||
| def enregistre_fichier(spectre_moyen, nom_echantillon, bornes): | ||
| nom_fichier=nom_echantillon+"_spectre_moyen_"+ str(bornes[0])+"_"+str(bornes[1])+".mean" | ||
| nom_fichier=str(numpy.char.replace(nom_fichier, " ", "_")) | ||
| numpy.savetxt(nom_fichier,spectre_moyen,delimiter="\t", newline="\n") | ||
| print (nom_fichier) | ||
|
|
||
| ############################################################################### | ||
| # programme principal | ||
| ############################################################################### | ||
| def main (rep_travail,nom_echantillon, bornes) : | ||
| print("===========================================") | ||
| os.chdir(rep_travail) | ||
| tableau_norm=numpy.loadtxt("tableau_normalisé.txt",delimiter="\t",dtype=float,encoding="Latin-1") | ||
| tableau_extrait=extraction_spectres(tableau_norm) | ||
| spectre_moyen=creation_spectre_moyen(tableau_extrait) | ||
| enregistre_fichier(spectre_moyen, nom_echantillon, bornes) | ||
| return spectre_moyen |
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