def button_search(self):
# Utilise la classe Traitement pour faire la recherche
g = Traitement(self.searchd.get(), self.searchf.get(),
self.searchl.get(), self.searchdo.get())
print(g)
g.search()
messagebox.showinfo("Sauvegarde", lecture_txt())
def __init__(self,base,nmois,id,cv_primary,cv_i,taille_maille,classifieur_fr=None,classifieur_fs=None,coef=0,**kwargs):
cm = kwargs.get('cm',plt.cm.RdBu)
cm_bright = kwargs.get('cm_bright', ListedColormap(['#FF0000','#0000FF']))
marker_size = kwargs.get('marker_size',None)
figsize = kwargs.get('figsize',None)
Visualizer.__init__(taille_maille,coef,cm=cm,cm_bright=cm_bright,marker_size=marker_size,figsize=figsize)
std = kwargs.get('std',True)
self.X_fs,self.X_val,self.Y_val,self.X_test,self.Y_test = proc.import_val_test_XY_cv_fs(base,id,cv_primary,cv_i,nmois=nmois,std=std,classifieur_fr=classifieur_fr,classifieur_fs=classifieur_fs)
def generate_CV_sets(dataSet, replace=False):
X = proc.import_X(dataSet.base, dataSet.nmois, std=dataSet.std)
Y = proc.import_Y(dataSet.base, dataSet.nmois)
for id in dataSet.id_list:
df = pd.DataFrame(index=X.index,
columns=np.arange(1,
dataSet.cv_primary.get_n_splits()))
for i, (IndexTrain_iloc,
IndexTest) in enumerate(dataSet.cv_primary.split(X, Y)):
IndexTrain = X.iloc[IndexTrain_iloc].index
Index = [i in IndexTrain for i in X.index]
df[i] = Index
foldername = foldername('CV_primary', dataSet.base)
filename = dataSet.get_filename(id)
df.to_pickle(foldername + filename)
def button_search(self):
print("Boutton Rechercher")
g = Traitement(self.searchd.get(), self.searchf.get(),
self.searchl.get(), self.searchdo.get())
print(g)
def traitement(self,MainWindow):
self.traitementImage = QtWidgets.QMainWindow()
self.ui = traitement.Ui_traitementImage()
self.ui.setupUi(self.traitementImage)
self.traitementImage.show()
MainWindow.close()
def display_base(self,n_dimensions,base,nmois,id,cv_primary,cv_i,classifieur_fr=None,classifieur_fs=None,std=True):
X_fs,X_val,Y_val,X_test,Y_test = proc.import_val_test_XY_cv_fs(base,id,cv_primary,cv_i,nmois=nmois,std=std,classifieur_fr=classifieur_fr,classifieur_fs=classifieur_fs)
self.display_XY(X_fs,X_val,Y_val,X_test,Y_test)
def import_Y(self):
return proc.import_Y(self.base, self.nmois)
def import_X(self):
return proc.import_X(self.base, self.nmois, self.std)