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Ajout du binning pour l'ACP
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@YLefrais
YLefrais committed Sep 19, 2024
1 parent 7fc0e8d commit c5439bd
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133 changes: 98 additions & 35 deletions LIBStick.py
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Original file line number Diff line number Diff line change
Expand Up @@ -3596,6 +3596,17 @@ def change_flag_traitement_L_ACP():
Change l'état du bouton +ind supp lorsqu'on change une des cases à cocher Spectres normalisés ou Centré réduit
"""
bouton_applique_ind_sup_L_ACP.configure(state="disable")


def change_flag_binning_L_ACP():
"""
Change l'état du spinbox si on change la case à cosser "Binning :"
"""
if flag_binning_L_ACP.get() == True :
entree_binning_L_ACP.configure(state="enable")
else :
entree_binning_L_ACP.configure(state="disable")
change_flag_traitement_L_ACP


def execute_ACP_L_ACP():
Expand All @@ -3617,12 +3628,20 @@ def execute_ACP_L_ACP():
# copie indispensable car la suite modifierait DataFrame_complet_L_ACP !
dataframe = DataFrame_complet_L_ACP.copy(deep=True)
treeview_dataframe = dataframe_treeview_L_ACP()

#test binning
if flag_binning_L_ACP.get() == True :
taille_binning = binning_L_ACP.get()
print("Binning " + str(taille_binning))
dataframe = LIBStick_outils.binning_dataframe(dataframe, taille_binning)

dataframe, treeview_dataframe, dataframe_individus_supp, treeview_dataframe_individus_supp = coupe_dataframe_L_ACP(dataframe,
treeview_dataframe,
tableau_bornes) # suprime les lignes non incluses dans le calcul de l'ACP
if flag_normalise_L_ACP.get() is True:
dataframe = LIBStick_outils.normalise_dataframe_aire(dataframe)



# flag_ACP = True
# if flag_ACP is True : # cas normal, ACP et non pas test de l'ICA. Dancs ce cas penser à indenter le bloc suivant

Expand Down Expand Up @@ -3689,6 +3708,13 @@ def applique_ACP_ind_sup_L_ACP():
# copie indispensable car la suite modifierait DataFrame_complet_L_ACP !
dataframe = DataFrame_complet_L_ACP.copy(deep=True)
treeview_dataframe = dataframe_treeview_L_ACP()

#test binning
if flag_binning_L_ACP.get() == True :
taille_binning = binning_L_ACP.get()
print("Binning " + str(taille_binning))
dataframe = LIBStick_outils.binning_dataframe(dataframe, taille_binning)

dataframe, treeview_dataframe, dataframe_individus_supp, treeview_dataframe_individus_supp = coupe_dataframe_L_ACP(dataframe,
treeview_dataframe,
tableau_bornes) # suprime les lignes non incluses dans le calcul de l'ACP
Expand Down Expand Up @@ -6265,48 +6291,58 @@ def __________IHM_ACP__________():
command=change_flag_traitement_L_ACP)
coche_centre_reduit_L_ACP.grid(row=2, column=1, sticky=tk.W, columnspan=2)

flag_binning_L_ACP = tk.BooleanVar(value=False)
coche_binning_L_ACP = ttk.Checkbutton(frame2_1_L_ACP, text=_("Binning :"),
variable=flag_binning_L_ACP,
command=change_flag_binning_L_ACP)
coche_binning_L_ACP.grid(row=3, column=1, sticky=tk.W, columnspan=2)
binning_L_ACP = tk.IntVar(value=2)
entree_binning_L_ACP = ttk.Spinbox(frame2_1_L_ACP, from_=1, to=20, increment=1, textvariable=binning_L_ACP,
state="disable", width=5)
entree_binning_L_ACP.grid(row=4, column=1, sticky=tk.W)

bouton_execute_L_ACP = ttk.Button(frame2_1_L_ACP, text=_("ACP"),
command=execute_ACP_L_ACP, state="disable", width=6)
bouton_execute_L_ACP.grid(row=3, column=1, sticky=tk.W)
bouton_execute_L_ACP.grid(row=5, column=1, sticky=tk.W)

bouton_applique_ind_sup_L_ACP = ttk.Button(frame2_1_L_ACP, text=_("+ ind. supp."),
command=applique_ACP_ind_sup_L_ACP, state="disable", width=6)
bouton_applique_ind_sup_L_ACP.grid(row=3, column=2, sticky=tk.W)
bouton_applique_ind_sup_L_ACP.grid(row=5, column=2, sticky=tk.W)

bouton_ouvre_L_ACP = ttk.Button(frame2_1_L_ACP, text=_("Ouvre"),
command=ouvre_ACP_L_ACP, state="disable", width=6)
bouton_ouvre_L_ACP.grid(row=4, column=1, sticky=tk.W)
bouton_ouvre_L_ACP.grid(row=6, column=1, sticky=tk.W)

bouton_sauve_L_ACP = ttk.Button(frame2_1_L_ACP, text=_("Sauve"),
command=enregistre_ACP_L_ACP, state="disable", width=6)
bouton_sauve_L_ACP.grid(row=4, column=2, sticky=tk.W)

text_dim_L_ACP = ttk.Label(frame2_1_L_ACP, text=_("Dimensions : "))
text_dim_L_ACP.grid(row=5, column=1, sticky=tk.W, columnspan=2)
dim_1_L_ACP = tk.IntVar(value=1)
entree_dim1_L_ACP = ttk.Spinbox(frame2_1_L_ACP, from_=1, to=10, increment=1, textvariable=dim_1_L_ACP,
width=5, foreground="red", command=affiche_spectres_var_ACP_L_ACP)
dim_2_L_ACP = tk.IntVar(value=2)
entree_dim2_L_ACP = ttk.Spinbox(frame2_1_L_ACP, from_=1, to=10, increment=1, textvariable=dim_2_L_ACP,
width=5, foreground="blue", command=affiche_spectres_var_ACP_L_ACP)
dim_3_L_ACP = tk.IntVar(value=3)
entree_dim3_L_ACP = ttk.Spinbox(frame2_1_L_ACP, from_=1, to=10, increment=1, textvariable=dim_3_L_ACP, state="disable",
width=5, foreground="green", command=affiche_spectres_var_ACP_L_ACP)
entree_dim1_L_ACP.grid(row=6, column=1, sticky=tk.W)
entree_dim2_L_ACP.grid(row=6, column=2, sticky=tk.W)
entree_dim3_L_ACP.grid(row=7, column=1, sticky=tk.W)

flag_3D_L_ACP = tk.BooleanVar(value=False)
coche_3D_L_ACP = ttk.Checkbutton(frame2_1_L_ACP, text="3D", variable=flag_3D_L_ACP, command=change_flag_3D_L_ACP)
coche_3D_L_ACP.grid(row=7, column=2, sticky=tk.W)

flag_echelle_L_ACP = tk.BooleanVar(value=True)
coche_echelle_L_ACP = ttk.Checkbutton(frame2_1_L_ACP, text=_("Même echelle x et y"), variable=flag_echelle_L_ACP)
coche_echelle_L_ACP.grid(row=8, column=1, sticky=tk.W, columnspan=2)

flag_eboulis_L_ACP = tk.BooleanVar(value=True)
coche_eboulis_L_ACP = ttk.Checkbutton(frame2_1_L_ACP, text=_("Diag. éboulis"), variable=flag_eboulis_L_ACP)
coche_eboulis_L_ACP.grid(row=9, column=1, sticky=tk.W, columnspan=2)
bouton_sauve_L_ACP.grid(row=6, column=2, sticky=tk.W)

# text_dim_L_ACP = ttk.Label(frame2_1_L_ACP, text=_("Dimensions : "))
# text_dim_L_ACP.grid(row=5, column=1, sticky=tk.W, columnspan=2)
# dim_1_L_ACP = tk.IntVar(value=1)
# entree_dim1_L_ACP = ttk.Spinbox(frame2_1_L_ACP, from_=1, to=10, increment=1, textvariable=dim_1_L_ACP,
# width=5, foreground="red", command=affiche_spectres_var_ACP_L_ACP)
# dim_2_L_ACP = tk.IntVar(value=2)
# entree_dim2_L_ACP = ttk.Spinbox(frame2_1_L_ACP, from_=1, to=10, increment=1, textvariable=dim_2_L_ACP,
# width=5, foreground="blue", command=affiche_spectres_var_ACP_L_ACP)
# dim_3_L_ACP = tk.IntVar(value=3)
# entree_dim3_L_ACP = ttk.Spinbox(frame2_1_L_ACP, from_=1, to=10, increment=1, textvariable=dim_3_L_ACP, state="disable",
# width=5, foreground="green", command=affiche_spectres_var_ACP_L_ACP)
# entree_dim1_L_ACP.grid(row=6, column=1, sticky=tk.W)
# entree_dim2_L_ACP.grid(row=6, column=2, sticky=tk.W)
# entree_dim3_L_ACP.grid(row=7, column=1, sticky=tk.W)

# flag_3D_L_ACP = tk.BooleanVar(value=False)
# coche_3D_L_ACP = ttk.Checkbutton(frame2_1_L_ACP, text="3D", variable=flag_3D_L_ACP, command=change_flag_3D_L_ACP)
# coche_3D_L_ACP.grid(row=7, column=2, sticky=tk.W)

# flag_echelle_L_ACP = tk.BooleanVar(value=True)
# coche_echelle_L_ACP = ttk.Checkbutton(frame2_1_L_ACP, text=_("Même echelle x et y"), variable=flag_echelle_L_ACP)
# coche_echelle_L_ACP.grid(row=8, column=1, sticky=tk.W, columnspan=2)

# flag_eboulis_L_ACP = tk.BooleanVar(value=True)
# coche_eboulis_L_ACP = ttk.Checkbutton(frame2_1_L_ACP, text=_("Diag. éboulis"), variable=flag_eboulis_L_ACP)
# coche_eboulis_L_ACP.grid(row=9, column=1, sticky=tk.W, columnspan=2)

# flag_calcul_L_ACP=tk.BooleanVar(value=False)
# coche_calcul_L_ACP=ttk.Checkbutton(frame2_1_L_ACP, text="fanalysis ?", variable=flag_calcul_L_ACP)
Expand All @@ -6323,14 +6359,41 @@ def __________IHM_ACP__________():
frame3_1_L_ACP = ttk.Frame(frame3_L_ACP)
frame3_1_L_ACP.grid(row=1, column=7, rowspan=3, sticky=tk.N)

text_dim_L_ACP = ttk.Label(frame3_1_L_ACP, text=_("Dimensions : "))
text_dim_L_ACP.grid(row=1, column=1, sticky=tk.W, columnspan=2)
dim_1_L_ACP = tk.IntVar(value=1)
entree_dim1_L_ACP = ttk.Spinbox(frame3_1_L_ACP, from_=1, to=10, increment=1, textvariable=dim_1_L_ACP,
width=5, foreground="red", command=affiche_spectres_var_ACP_L_ACP)
dim_2_L_ACP = tk.IntVar(value=2)
entree_dim2_L_ACP = ttk.Spinbox(frame3_1_L_ACP, from_=1, to=10, increment=1, textvariable=dim_2_L_ACP,
width=5, foreground="blue", command=affiche_spectres_var_ACP_L_ACP)
dim_3_L_ACP = tk.IntVar(value=3)
entree_dim3_L_ACP = ttk.Spinbox(frame3_1_L_ACP, from_=1, to=10, increment=1, textvariable=dim_3_L_ACP, state="disable",
width=5, foreground="green", command=affiche_spectres_var_ACP_L_ACP)
entree_dim1_L_ACP.grid(row=2, column=1, sticky=tk.W)
entree_dim2_L_ACP.grid(row=2, column=2, sticky=tk.W)
entree_dim3_L_ACP.grid(row=3, column=1, sticky=tk.W)

flag_3D_L_ACP = tk.BooleanVar(value=False)
coche_3D_L_ACP = ttk.Checkbutton(frame3_1_L_ACP, text="3D", variable=flag_3D_L_ACP, command=change_flag_3D_L_ACP)
coche_3D_L_ACP.grid(row=3, column=2, sticky=tk.W)

flag_echelle_L_ACP = tk.BooleanVar(value=True)
coche_echelle_L_ACP = ttk.Checkbutton(frame3_1_L_ACP, text=_("Même echelle\n x et y"), variable=flag_echelle_L_ACP)
coche_echelle_L_ACP.grid(row=4, column=1, sticky=tk.W, columnspan=2)

flag_eboulis_L_ACP = tk.BooleanVar(value=True)
coche_eboulis_L_ACP = ttk.Checkbutton(frame3_1_L_ACP, text=_("Diag. éboulis"), variable=flag_eboulis_L_ACP)
coche_eboulis_L_ACP.grid(row=5, column=1, sticky=tk.W, columnspan=2)

flag_plotly_L_ACP = tk.BooleanVar(value=True)
coche_plotly_L_ACP = ttk.Checkbutton(frame3_1_L_ACP, text=_("\n Diag. plotly\n"), variable=flag_plotly_L_ACP)
coche_plotly_L_ACP.grid(row=1, column=1)
coche_plotly_L_ACP = ttk.Checkbutton(frame3_1_L_ACP, text=_("Diag. plotly"), variable=flag_plotly_L_ACP)
coche_plotly_L_ACP.grid(row=6, column=1, sticky=tk.W, columnspan=2)

bouton_enregistre_L_ACP = ttk.Button(frame3_1_L_ACP, text=_("Enregistrer \nfacteurs \nde l'ACP"),
command=enregistre_facteurs_ACP_L_ACP,
state="disable", width=10)
bouton_enregistre_L_ACP.grid(row=2, column=1)
bouton_enregistre_L_ACP.grid(row=7, column=1, sticky=tk.W, columnspan=2)

ligne_position_1_L_ACP = canevas0_L_ACP.create_line(0, 0, 0, hauteur_canevas_spectres, fill="white")

Expand Down
60 changes: 60 additions & 0 deletions LIBStick_outils.py
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Original file line number Diff line number Diff line change
Expand Up @@ -293,3 +293,63 @@ def normalise_dataframe_aire(dataframe): # données lignes
tableau[ligne, :] = (tableau[ligne, :] / aire)
dataframe = pd.DataFrame(tableau, index=dataframe.index, columns=dataframe.columns)
return dataframe


###################################################################################################
# Binning des spectres d'un tableau, données en colonnes, abscisses dans la première colonne
###################################################################################################
def binning_spectre (spectre, taille_bin=2):
"""
Effectue un binning par moyenne sur un spectre.
Args:
spectre: Le spectre d'entrée sous forme de tableau NumPy.
taille_bin: La taille de chaque bin.
Returns:
Le spectre binné.
"""
# Vérification de la taille du spectre par rapport à la taille du bin
# et supprime les derniers pixels du spectres
if len(spectre) % taille_bin != 0:
supprime = (len(spectre) % taille_bin)
spectre = spectre[: -supprime]
# Reshape le spectre en une matrice où chaque ligne correspond à un bin
spectre_reshape = spectre.reshape(-1, taille_bin)
# Calcul de la moyenne de chaque ligne (chaque bin)
spectre_binne = np.mean(spectre_reshape, axis=1)
# print("-----------------------")
# print(spectre.shape)
# print(spectre_reshape)
# print(spectre_reshape.shape)
# print(spectre_binne.shape)
return spectre_binne


def binning_dataframe(dataframe, taille_bin=2):
"""
Effectue un binning par moyenne sur tous les spectres d'un Dataframe (un spectre par ligne)
Parameters
----------
dataframe : TYPE
DESCRIPTION.
taille_bin : TYPE, optional
DESCRIPTION. The default is 2.
Returns
-------
None.
"""
tableau = dataframe.values
tableau_binne = np.zeros((tableau.shape[0], tableau.shape[1]//taille_bin))
for ligne in range(tableau.shape[0]):
spectre = tableau[ligne, :]
spectre_binne = binning_spectre(spectre, taille_bin)
tableau_binne[ligne, :] = spectre_binne

colonnes = dataframe.columns.values
colonnes_binne = binning_spectre(colonnes, taille_bin)
dataframe_binne = pd.DataFrame(tableau_binne, index=dataframe.index)
dataframe_binne.columns = colonnes_binne
# print(dataframe)
# print("------------------------")
# print(dataframe_binne)
return dataframe_binne

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