def computeAreaMicro(repertory_output, table_input_name, data_base_name, micro):
sql_temporary_file = repertory_output + os.sep + "spatialiteTemp.txt"
requete = sqlSurfaceMicro(table_input_name, "ID", micro, data_base_name)
exitCode = os.system("%s > %s"%(requete,sql_temporary_file))
if exitCode != 0:
raise NameError(cyan + "computeAreaMicro() : " + bold + red + "An error occured during fileCreation command. See error message above." + endC)
# Calculer la surface de la microclasse
area_micro = float(readTextFileBySeparator(sql_temporary_file, " ")[0][0])
removeFile(sql_temporary_file)
return area_micro
def readQualityIndicatorsFile(indicators_input_file) :
print(cyan + "readQualityIndicatorsFile() : " + bold + green + "Indicators quality file reading... \n" + endC)
# creer un dictionaire contenant tous les indicateurs de classes et un dictionaire des indicateurs généraux contenu dans le fichier
indicator_macro_dico = []
indicator_general_dico = {}
indicator_general_label = []
indicator_general_value = []
indicators_list = []
composants_list = readTextFileBySeparator(indicators_input_file, ";")
for idx_line in range(len(composants_list)) :
composant = composants_list[idx_line]
# cas des indicateurs pour chaque macro classes
if idx_line < len(composants_list)-2 :
if debug >= 4:
print(composant)
if idx_line == 0 :
line_zero_list = composant
for id_elem in range(1, len(line_zero_list)):
class_elm = cleanSpaceText(line_zero_list[id_elem])
class_dico = {}
class_dico[cleanSpaceText(line_zero_list[0])] = class_elm
indicator_macro_dico.append(class_dico)
else :
line_list = composant
for id_elem in range(1, len(line_list)):
indic_elm = cleanSpaceText(line_list[id_elem])
indicator_macro_dico[id_elem-1][cleanSpaceText(line_list[0])] = indic_elm
# liste (labels) des indicateurs generaux
elif idx_line == len(composants_list)-1 :
if debug >= 4:
print(composant)
for elem in composant :
indicator_general_value.append(cleanSpaceText(elem))
# Valeurs des indicateurs generaux
else :
if debug >= 4:
print(composant)
for elem in composant :
indicator_general_label.append(cleanSpaceText(elem))
# creation dico indicateurs generaux
for indicator_idx in range(len(indicator_general_label)) :
indicator_general_dico[indicator_general_label[indicator_idx]] = indicator_general_value[indicator_idx]
print(cyan + "readQualityIndicatorsFile() : " + bold + green + "Indicators quality file readed \n" + endC)
# retourne les deux dictionaires
return indicator_macro_dico,indicator_general_dico
def readCentroidsFiles(centroids_input_files_list) :
print(cyan + "readCentroidsFile() : " + bold + green + "Centroids file reading...\n" + endC)
microclass_centroides_list = []
for centroids_file in centroids_input_files_list:
if debug >= 4:
print("file centroides : " + centroids_file)
composants_list = readTextFileBySeparator(centroids_file, " ")
microclass_centroides_list.append(composants_list)
for composant in composants_list :
if debug >= 4:
print(composant)
print(cyan + "readCentroidsFile() : " + bold + green + "Centroids file readed \n" + endC)
return microclass_centroides_list
def relaunchFtp(ftp, file_error, local_path):
files_list = readTextFileBySeparator(file_error, '\n')
for files in files_list:
file_ftp = files[0]
repertory = os.path.dirname(file_ftp)
filename = os.path.basename(file_ftp)
local_filename = local_path + os.sep + file_ftp
print(cyan + "relaunchFtp() : " + endC + "Tentative de re-chargement de image file : " + file_ftp + endC)
try:
ftp.cwd(repertory)
ftp.retrbinary("RETR " + filename ,open(local_filename, 'wb').write)
ftp.cwd("/")
except RuntimeError:
print(cyan + "relaunchFtp() : " + bold + red + "Rechargement impossible du fichier : " + file_ftp + endC, file=sys.stderr)
continue
return
def computeAverageAreaMacro(repertory_output, class_labels_list, table_input_name, data_base_name):
average_area_macro_list = []
sql_temporary_file = repertory_output + os.sep + "spatialiteTemp.txt"
for class_label in class_labels_list:
requete = sqlSurfaceAverageMacro(table_input_name, "ID", class_label, data_base_name)
exitCode = os.system("%s > %s"%(requete,sql_temporary_file))
if exitCode != 0:
raise NameError(cyan + "computeAverageAreaMacro() : " + bold + red + "An error occured during file creation. See error message above." + endC)
requete_result = readTextFileBySeparator(sql_temporary_file, " ")
print(requete_result)
if requete_result == []:
average_area_macro_list.append(0)
else:
average_area_macro_list.append(float(requete_result[0][0]))
removeFile(sql_temporary_file)
return average_area_macro_list
def classRasterSubSampling(satellite_image_input, classified_image_input, image_output, table_reallocation, sub_sampling_number, no_data_value, path_time_log, rand_otb=0, ram_otb=0, number_of_actives_pixels_threshold=8000, extension_raster=".tif", save_results_intermediate=False, overwrite=True) :
# Mise à jour du Log
starting_event = "classRasterSubSampling() : Micro class subsampling on classification image starting : "
timeLine(path_time_log,starting_event)
if debug >= 3:
print(cyan + "classRasterSubSampling() : " + endC + "satellite_image_input : " + str(satellite_image_input) + endC)
print(cyan + "classRasterSubSampling() : " + endC + "classified_image_input : " + str(classified_image_input) + endC)
print(cyan + "classRasterSubSampling() : " + endC + "image_output : " + str(image_output) + endC)
print(cyan + "classRasterSubSampling() : " + endC + "table_reallocation : " + str(table_reallocation) + endC)
print(cyan + "classRasterSubSampling() : " + endC + "sub_sampling_number : " + str(sub_sampling_number) + endC)
print(cyan + "classRasterSubSampling() : " + endC + "no_data_value : " + str(no_data_value) + endC)
print(cyan + "classRasterSubSampling() : " + endC + "path_time_log : " + str(path_time_log) + endC)
print(cyan + "classRasterSubSampling() : " + endC + "rand_otb : " + str(rand_otb) + endC)
print(cyan + "classRasterSubSampling() : " + endC + "ram_otb : " + str(ram_otb) + endC)
print(cyan + "classRasterSubSampling() : " + endC + "number_of_actives_pixels_threshold : " + str(number_of_actives_pixels_threshold) + endC)
print(cyan + "classRasterSubSampling() : " + endC + "extension_raster : " + str(extension_raster) + endC)
print(cyan + "classRasterSubSampling() : " + endC + "save_results_intermediate : " + str(save_results_intermediate) + endC)
print(cyan + "classRasterSubSampling() : " + endC + "overwrite : " + str(overwrite) + endC)
# Constantes
CODAGE = "uint16"
CODAGE_8B = "uint8"
TEMP = "TempSubSampling_"
MASK_SUF = "_Mask"
SUB_SAMPLE_SUF = "_SubSampled"
CENTROID_SUF = "_Centroids"
TEMP_OUT = "_temp_out"
EXTENSION_TXT = ".txt"
# Contenu de la nouvelle table
text_new_table = ""
# CREATION DES NOMS DE CHEMINS UTILES
name = os.path.splitext(os.path.basename(image_output))[0]
input_classified_image_path = os.path.dirname(classified_image_input) # Ex : D2_Par_Zone/Paysage_01/Corr_2/Resultats/Temp/
temp_sub_sampling_path = input_classified_image_path + os.sep + TEMP + name + os.sep # Dossier contenant les fichiers temporaires de cette brique. Ex : D2_Par_Zone/Paysage_01/Corr_2/Resultats/Temp/Temp_Sub_Sampling/
input_classified_image_complete_name = os.path.basename(classified_image_input) # Ex : Paysage_01_raw.tif
input_classified_image_name = os.path.splitext(input_classified_image_complete_name)[0] # Ex : Paysage_01_raw
input_classified_image_extend = os.path.splitext(input_classified_image_complete_name)[1] # Ex : .tif
image_output_temp = os.path.splitext(image_output)[0] + TEMP_OUT + extension_raster # Ex : D2_Par_Zone/Paysage_01/Corr_2/Resultats/Temp/Temp_Sub_Sampling/Paysage_01_raw_temp.tif
# Création de temp_sub_sampling_path s'il n'existe pas
if not os.path.isdir(os.path.dirname(temp_sub_sampling_path)) :
os.makedirs(os.path.dirname(temp_sub_sampling_path))
print(cyan + "classRasterSubSampling() : " + bold + green + "START ...\n" + endC)
# Lecture du fichier table de proposition
supp_class_list, reaff_class_list, macro_reaff_class_list, sub_sampling_class_list, sub_sampling_number_list = readReallocationTable(table_reallocation, sub_sampling_number) # Fonction de Lib_text
info_table_list = readTextFileBySeparator(table_reallocation, "\n")
# Recherche de la liste des micro classes contenu dans le fichier de classification d'entrée
class_values_list = identifyPixelValues(classified_image_input)
# Supression dans la table des lignes correspondant aux actions "-2"
for ligne_table in info_table_list:
if not "-2" in ligne_table[0]:
text_new_table += str(ligne_table[0]) + "\n"
if debug >= 3:
print("supp_class_list : " + str(supp_class_list))
print("reaff_class_list : " + str(reaff_class_list))
print("macro_reaff_class_list : " + str(macro_reaff_class_list))
print("sub_sampling_class_list : " + str(sub_sampling_class_list))
print("sub_sampling_number_list : " + str(sub_sampling_number_list))
# Dans cettre brique, on ne s'intéresse qu'à la partie sous echantillonage
# Gestion du cas de suppression
if len(supp_class_list) > 0:
print(cyan + "classRasterSubSampling() : " + bold + yellow + "ATTENTION : Les classes ne sont pas supprimees pour le fichier classification format raster." + '\n' + endC)
# Gestion du cas de réaffectation
if len(reaff_class_list) > 0:
print(cyan + "classRasterSubSampling() : " + bold + yellow + "ATTENTION : la brique SpecificSubSampling ne traite pas les reaffectation. A l'issue de cette brique, verifier la table de reallocation et executer la brique de reallocation." + '\n' + endC)
if len(sub_sampling_class_list) > 0 :
if debug >= 3:
print(cyan + "classRasterSubSampling() : " + bold + green + "DEBUT DU SOUS ECHANTILLONAGE DES CLASSES %s " %(sub_sampling_class_list) + endC)
# Parcours des classes à sous échantilloner
processing_pass_first = False
for idx_class in range(len(sub_sampling_class_list)) :
# INITIALISATION DU TRAITEMENT DE LA CLASSE
# Classe à sous échantilloner. Ex : 21008
class_to_sub_sample = sub_sampling_class_list[idx_class]
if idx_class == 0 or not processing_pass_first :
# Image à reclassifier : classified_image_input au premier tour
image_to_sub_sample = classified_image_input
else :
# Image à reclassifier : la sortie de la boucle précédente ensuite
image_to_sub_sample = image_output
# determiner le label disponible de la classe
base_subclass_label = int(class_to_sub_sample/100)*100
subclass_label = base_subclass_label
for class_value in class_values_list:
if (class_value > subclass_label) and (class_value < base_subclass_label + 100) :
subclass_label = class_value
subclass_label += 1
# subclass_label = int(class_to_sub_sample/100)*100 + 20 + class_to_sub_sample%20 * 5
# Label de départ des sous classes. Formule proposée : 3 premiers chiffres de class_to_sub_sample puis ajout de 20 + 5 * class_to_sub_sample modulo 20. Ex : 21000 -> 21020, 21001-> 21025, 21002-> 21030 etc...
# Part du principe qu'il y a moins de 20 micro classes et que chacune est sous échantillonnée au maximum en 5 sous parties. Si ce n'est pas le cas : A ADAPTER
number_of_sub_samples = sub_sampling_number_list[idx_class] # Nombre de sous classes demandées pour le sous échantillonage de class_to_sub_sample. Ex : 4
class_mask_raster = temp_sub_sampling_path + input_classified_image_name + "_" + str(class_to_sub_sample) + MASK_SUF + input_classified_image_extend # Ex : D2_Par_Zone/Paysage_01/Corr_2/Resultats/Temp/Temp_Sub_Sampling/Paysage_01_raw_21008_Mask.tif
class_subsampled_raster = temp_sub_sampling_path + input_classified_image_name + "_" + str(class_to_sub_sample) + SUB_SAMPLE_SUF + input_classified_image_extend # Ex : D2_Par_Zone/Paysage_01/Corr_2/Resultats/Temp/Temp_Sub_Sampling/Paysage_01_raw_21008_SubSampled.tif
centroid_file = temp_sub_sampling_path + input_classified_image_name + "_" + str(class_to_sub_sample) + CENTROID_SUF + EXTENSION_TXT # Ex : D2_Par_Zone/Paysage_01/Corr_2/Resultats/Temp/Temp_Sub_Sampling/Paysage_01_raw_21008_Centroid.txt
if debug >= 5:
print(cyan + "classRasterSubSampling() : " + endC + "class_to_sub_sample :" , class_to_sub_sample)
print(cyan + "classRasterSubSampling() : " + endC + "subclass_label :" , subclass_label)
print(cyan + "classRasterSubSampling() : " + endC + "number_of_sub_samples :" , number_of_sub_samples)
print(cyan + "classRasterSubSampling() : " + endC + "class_mask_raster :" , class_mask_raster)
print(cyan + "classRasterSubSampling() : " + endC + "class_subsampled_raster :" , class_subsampled_raster)
print(cyan + "classRasterSubSampling() : " + endC + "centroid_file :" , centroid_file)
if debug >= 3:
print(cyan + "classRasterSubSampling() : " + bold + green + "CLASSE %s/%s : SOUS ECHANTILLONAGE DE %s EN %s CLASSES " %(idx_class+1, len(sub_sampling_class_list), class_to_sub_sample, number_of_sub_samples) + endC)
# ETAPE 1/5 : EXTRACTION DU MASQUE BINAIRE DES PIXELS CORRESPONDANT A LA CLASSE
expression_masque = "\"im1b1 == %s? 1 : 0\"" %(class_to_sub_sample)
command = "otbcli_BandMath -il %s -out %s %s -exp %s" %(classified_image_input, class_mask_raster, CODAGE_8B, expression_masque)
if debug >=2:
print("\n" + cyan + "classRasterSubSampling() : " + bold + green + "CLASSE %s/%s - ETAPE 1/5 : Debut de l extraction du masque binaire de la classe %s" %(idx_class+1, len(sub_sampling_class_list),class_to_sub_sample) + endC)
print(command)
os.system(command)
if debug >=2:
print(cyan + "classRasterSubSampling() : " + bold + green + "CLASSE %s/%s - ETAPE 1/5 : Fin de l extraction du masque binaire de la classe %s, disponible ici : %s" %(idx_class+1, len(sub_sampling_class_list),class_to_sub_sample, class_mask_raster) + endC)
# TEST POUR SAVOIR SI ON EST EN CAPACITE D'EFFECTUER LE KMEANS
number_of_actives_pixels = countPixelsOfValue(class_mask_raster, 1) # Comptage du nombre de pixels disponibles pour effectuer le kmeans
if number_of_actives_pixels > (number_of_sub_samples * number_of_actives_pixels_threshold) : # Cas où il y a plus de pixels disponibles pour effectuer le kmeans que le seuil
# ETAPE 2/5 : CLASSIFICATION NON SUPERVISEE DES PIXELS CORRESPONDANT A LA CLASSE
if debug >= 3:
print("\n" + cyan + "classRasterSubSampling() : " + bold + green + "CLASSE %s/%s - ETAPE 2/5 : Il y a assez de pixels pour faire le sous echantillonage : %s sur %s requis au minimum " %(idx_class+1, len(sub_sampling_class_list), number_of_actives_pixels, int(number_of_sub_samples) * number_of_actives_pixels_threshold) + endC)
if debug >=2:
print("\n" + cyan + "classRasterSubSampling() : " + bold + green + "CLASSE %s/%s - ETAPE 2/5 : Debut du sous echantillonage par classification non supervisee en %s classes " %(idx_class+1, len(sub_sampling_class_list), number_of_sub_samples) + endC)
# appel du kmeans
input_mask_list = []
input_mask_list.append(class_mask_raster)
output_masked_image_list = []
output_masked_image_list.append(class_subsampled_raster)
output_centroids_files_list = []
output_centroids_files_list.append(centroid_file)
macroclass_sampling_list = []
macroclass_sampling_list.append(number_of_sub_samples)
macroclass_labels_list = []
macroclass_labels_list.append(subclass_label)
applyKmeansMasks(satellite_image_input, input_mask_list, "", "", output_masked_image_list, output_centroids_files_list, macroclass_sampling_list, macroclass_labels_list, no_data_value, path_time_log, 200, 1, -1, 0.0, rand_otb, ram_otb, number_of_actives_pixels_threshold, extension_raster, save_results_intermediate, overwrite)
if debug >=2:
print(cyan + "classRasterSubSampling() : " + bold + green + "CLASSE %s/%s - ETAPE 2/5 : Fin du sous echantillonage par classification non supervisee en %s classes, disponible ici %s : " %(idx_class+1, len(sub_sampling_class_list), number_of_sub_samples, class_subsampled_raster) + endC)
# ETAPE 3/5 : INTEGRATION DES NOUVELLES SOUS CLASSES DANS LA TABLE DE REALLOCATION
# Ouveture du fichier table de proposition pour re-ecriture
for i in range(number_of_sub_samples):
class_values_list.append(subclass_label + i)
text_new_table += str(subclass_label + i) + ";" + str(subclass_label + i) + "; METTRE A JOUR MANUELLEMENT (origine : " + str(class_to_sub_sample) + ")" + "\n"
# ETAPE 4/5 : APPLICATION DU SOUS ECHANTILLONAGE AU RESULTAT DE CLASSIFICATION
expression_application_sous_echantillonage = "\"im1b1 == %s? im2b1 : im1b1\"" %(class_to_sub_sample)
command = "otbcli_BandMath -il %s %s -out %s %s -exp %s" %(image_to_sub_sample, class_subsampled_raster, image_output_temp, CODAGE, expression_application_sous_echantillonage)
if debug >=2:
print("\n" + cyan + "classRasterSubSampling() : " + bold + green + "CLASSE %s/%s - ETAPE 4/5 : Debut de l application du sous echantillonage present dans %s sur %s" %(idx_class+1, len(sub_sampling_class_list), class_subsampled_raster, classified_image_input) + endC)
print(command)
os.system(command)
if debug >=2:
print(cyan + "classRasterSubSampling() : " + bold + green + "CLASSE %s/%s - ETAPE 4/5 : Fin de l application du sous echantillonage present dans %s sur %s, sortie disponible ici : %s" %(idx_class+1, len(sub_sampling_class_list), class_subsampled_raster, classified_image_input, image_output_temp) + endC)
# ETAPE 5/5 : GESTION DES RENOMMAGES ET SUPPRESSIONS
if debug >=2:
print("\n" + cyan + "classRasterSubSampling() : " + bold + green + "CLASSE %s/%s - ETAPE 5/5 : Debut du renommage et suppression des dossiers intermediaires" %(idx_class+1, len(sub_sampling_class_list)) + endC)
if debug >=3 :
print("\n" + green + "classified image input: %s" %(classified_image_input) + endC)
print("\n" + green + "image to sub sample: %s" %(image_to_sub_sample) + endC)
print("\n" + green + "image temp : %s" %(image_output_temp) + endC)
print("\n" + green + "image output : %s" %(image_output) + endC)
# Si l'image d'entrée et l'image de sorte sont le même fichier on efface le fichier d'entrée pour le re-creer avec le fichier re-travaillé
if image_output == classified_image_input and os.path.isfile(classified_image_input) :
removeFile(classified_image_input)
os.rename(image_output_temp,image_output)
processing_pass_first = True
# SUPPRESSION DES FICHIERS TEMPORAIRES
if not save_results_intermediate :
if os.path.isfile(class_mask_raster) :
removeFile(class_mask_raster)
if os.path.isfile(class_subsampled_raster) :
removeFile(class_subsampled_raster)
if os.path.isfile(centroid_file) :
removeFile(centroid_file)
if debug >=2:
print(cyan + "classRasterSubSampling() : " + bold + green + "CLASSE %s/%s - ETAPE 5/5 : Fin du renommage et suppression des dossiers intermediaires" %(idx_class+1, len(sub_sampling_class_list)) + endC)
else: # Cas où il n'y a pas assez de pixels pour effectuer le kmeans
if debug >=2:
print("\n" + cyan + "classRasterSubSampling() : " + bold + yellow + "CLASSE %s/%s - ETAPE 2/5 : Nombre insuffisant de pixels disponibles pour appliquer le kmeans : %s sur %s requis au minimum " %(idx_class+1, len(sub_sampling_class_list), number_of_actives_pixels, int(number_of_sub_samples) * number_of_actives_pixels_threshold) + endC)
print(cyan + "classRasterSubSampling() : " + bold + yellow + "CLASSE %s/%s - ETAPE 2/5 : SOUS ECHANTILLONAGE NON APPLIQUE A LA CLASSE %s" %(idx_class+1, len(sub_sampling_class_list), class_to_sub_sample) + endC + "\n")
# MISE A JOUR DU FICHIER image_to_sub_sample
if idx_class == 0:
processing_pass_first = False
# MISE A JOUR DE LA TABLE DE REALLOCATION
text_new_table += str(class_to_sub_sample) + ";" + str(class_to_sub_sample) + ";CLASSE TROP PETITE POUR SOUS ECHANTILLONAGE" + "\n"
# SUPPRESSION DU MASQUE
if not save_results_intermediate and os.path.isfile(class_mask_raster) :
removeFile(class_mask_raster)
else:
shutil.copy2(classified_image_input, image_output) # Copie du raster d'entree si pas de sous-echantillonnage
# Ecriture de la nouvelle table dans le fichier
writeTextFile(table_reallocation, text_new_table)
# SUPPRESSION DU DOSSIER ET DES FICHIERS TEMPORAIRES
if not save_results_intermediate and os.path.isdir(os.path.dirname(temp_sub_sampling_path)) :
shutil.rmtree(os.path.dirname(temp_sub_sampling_path))
print(cyan + "classRasterSubSampling() : " + bold + green + "END\n" + endC)
# Mise à jour du Log
ending_event = "classRasterSubSampling() : Micro class subsampling on classification image ending : "
timeLine(path_time_log,ending_event)
return
def vectorsListToOcs(input_text,
output_raster,
footprint_vector,
reference_raster,
codage_raster='uint8',
epsg=2154,
no_data_value=0,
format_raster='GTiff',
format_vector='ESRI Shapefile',
extension_raster='.tif',
extension_vector='.shp',
path_time_log='',
save_results_intermediate=False,
overwrite=True):
if debug >= 3:
print(
'\n' + bold + green +
"OCS raster à partir d'une liste de vecteurs - Variables dans la fonction :"
+ endC)
print(cyan + " vectorsListToOcs() : " + endC + "input_text : " +
str(input_text) + endC)
print(cyan + " vectorsListToOcs() : " + endC + "output_raster : " +
str(output_raster) + endC)
print(cyan + " vectorsListToOcs() : " + endC +
"footprint_vector : " + str(footprint_vector) + endC)
print(cyan + " vectorsListToOcs() : " + endC +
"reference_raster : " + str(reference_raster) + endC)
print(cyan + " vectorsListToOcs() : " + endC + "codage_raster : " +
str(codage_raster) + endC)
print(cyan + " vectorsListToOcs() : " + endC + "epsg : " +
str(epsg) + endC)
print(cyan + " vectorsListToOcs() : " + endC + "no_data_value : " +
str(no_data_value) + endC)
print(cyan + " vectorsListToOcs() : " + endC + "format_raster : " +
str(format_raster) + endC)
print(cyan + " vectorsListToOcs() : " + endC + "format_vector : " +
str(format_vector) + endC)
print(cyan + " vectorsListToOcs() : " + endC +
"extension_raster : " + str(extension_raster) + endC)
print(cyan + " vectorsListToOcs() : " + endC +
"extension_vector : " + str(extension_vector) + endC)
print(cyan + " vectorsListToOcs() : " + endC + "path_time_log : " +
str(path_time_log) + endC)
print(cyan + " vectorsListToOcs() : " + endC +
"save_results_intermediate : " + str(save_results_intermediate) +
endC)
print(cyan + " vectorsListToOcs() : " + endC + "overwrite : " +
str(overwrite) + endC + '\n')
# Définition des constantes
SUFFIX_TEMP = '_temp'
SUFFIX_CUT = '_cut'
SUFFIX_FILTER = '_filter'
SUFFIX_BUFFER = '_buffer'
TEXT_SEPARATOR = ':'
# Mise à jour du log
starting_event = "vectorsListToOcs() : Début du traitement : "
timeLine(path_time_log, starting_event)
print(cyan + "vectorsListToOcs() : " + bold + green +
"DEBUT DES TRAITEMENTS" + endC + '\n')
# Définition des variables 'basename'
output_raster_basename = os.path.basename(
os.path.splitext(output_raster)[0])
output_raster_dirname = os.path.dirname(output_raster)
# Définition des variables temp
temp_directory = output_raster_dirname + os.sep + output_raster_basename + SUFFIX_TEMP
temp_raster = temp_directory + os.sep + output_raster_basename + SUFFIX_TEMP + extension_raster
# Nettoyage des traitements précédents
if overwrite:
if debug >= 3:
print(cyan + "vectorsListToOcs() : " + endC +
"Nettoyage des traitements précédents." + '\n')
removeFile(output_raster)
cleanTempData(temp_directory)
else:
if os.path.exists(output_raster):
print(cyan + "vectorsListToOcs() : " + bold + yellow +
"Le fichier de sortie existe déjà et ne sera pas regénéré." +
endC)
raise
if not os.path.exixts(temp_directory):
os.makedirs(temp_directory)
pass
# Test de l'emprise des fichiers vecteur d'emprise et raster de référence (le raster doit être de même taille ou plus grand que le vecteur)
xmin_fpt, xmax_fpt, ymin_fpt, ymax_fpt = getEmpriseFile(
footprint_vector, format_vector=format_vector)
xmin_ref, xmax_ref, ymin_ref, ymax_ref = getEmpriseImage(reference_raster)
if round(xmin_fpt, 4) < round(xmin_ref, 4) or round(xmax_fpt, 4) > round(
xmax_ref, 4) or round(ymin_fpt, 4) < round(ymin_ref, 4) or round(
ymax_fpt, 4) > round(ymax_ref, 4):
print(cyan + "vectorsListToOcs() : " + bold + red +
"xmin_fpt, xmax_fpt, ymin_fpt, ymax_fpt" + endC,
xmin_fpt,
xmax_fpt,
ymin_fpt,
ymax_fpt,
file=sys.stderr)
print(cyan + "vectorsListToOcs() : " + bold + red +
"xmin_ref, xmax_ref, ymin_ref, ymax_ref" + endC,
xmin_ref,
xmax_ref,
ymin_ref,
ymax_ref,
file=sys.stderr)
raise NameError(
cyan + "vectorsListToOcs() : " + bold + red +
"The extend of the footprint vector (%s) is greater than the reference raster (%s)."
% (footprint_vector, reference_raster) + endC)
# Récupération des traitements à faire dans le fichier texte d'entrée
text_list = readTextFileBySeparator(input_text, TEXT_SEPARATOR)
####################################################################
print(cyan + "vectorsListToOcs() : " + bold + green +
"Début de la génération de l'OCS raster à partir de vecteurs." +
endC + '\n')
# Boucle sur les traitements à réaliser
for text in text_list:
idx = text_list.index(text) + 1
class_label = int(text[0])
vector_file = text[1]
if debug >= 3:
print(cyan + "vectorsListToOcs() : " + endC + bold +
"Génération %s/%s : " % (idx, len(text_list)) + endC +
"traitement du fichier %s (label %s)." %
(vector_file, str(class_label)) + '\n')
# Gestion des noms des fichiers temporaires
vector_file_basename = os.path.basename(
os.path.splitext(vector_file)[0])
vector_file_cut = temp_directory + os.sep + vector_file_basename + SUFFIX_CUT + extension_vector
vector_file_filter = temp_directory + os.sep + vector_file_basename + SUFFIX_FILTER + extension_vector
vector_file_buffer = temp_directory + os.sep + vector_file_basename + SUFFIX_BUFFER + extension_vector
vector_file_raster = temp_directory + os.sep + vector_file_basename + extension_raster
# Gestion des variables de traitement (tampon et filtrage SQL)
try:
buffer_len = float(text[2])
except ValueError:
buffer_len = text[2]
except Exception:
buffer_len = ''
try:
sql_filter = text[3]
except Exception:
sql_filter = ''
# Découpage à l'emprise de la zone d'étude
if debug >= 3:
print(cyan + "vectorsListToOcs() : " + endC +
"Découpage à l'emprise de la zone d'étude." + '\n')
cutVectorAll(footprint_vector,
vector_file,
vector_file_cut,
overwrite=overwrite,
format_vector=format_vector)
# Filtrage SQL (facultatif)
if sql_filter != '':
if debug >= 3:
print(cyan + "vectorsListToOcs() : " + endC +
"Application du filtrage SQL : %s." % sql_filter + '\n')
attr_names_list = getAttributeNameList(vector_file_cut,
format_vector=format_vector)
column = "'"
for attr_name in attr_names_list:
column += attr_name + ", "
column = column[:-2]
column += "'"
filterSelectDataVector(vector_file_cut,
vector_file_filter,
column,
sql_filter,
overwrite=overwrite,
format_vector=format_vector)
else:
vector_file_filter = vector_file_cut
# Application d'un tampon (facultatif)
if buffer_len != '' and buffer_len != 0:
if debug >= 3:
print(cyan + "vectorsListToOcs() : " + endC +
"Application d'un buffer : %s." % buffer_len + '\n')
if type(buffer_len) is float:
bufferVector(vector_file_filter,
vector_file_buffer,
buffer_len,
col_name_buf='',
fact_buf=1.0,
quadsecs=10,
format_vector=format_vector)
else:
bufferVector(vector_file_filter,
vector_file_buffer,
0,
col_name_buf=buffer_len,
fact_buf=1.0,
quadsecs=10,
format_vector=format_vector)
else:
vector_file_buffer = vector_file_filter
# Rastérisation du vecteur préparé
if debug >= 3:
print(cyan + "vectorsListToOcs() : " + endC +
"Rastérisation du vecteur préparé." + '\n')
rasterizeBinaryVector(vector_file_buffer,
reference_raster,
vector_file_raster,
label=class_label,
codage=codage_raster)
# Ajout de l'information dans le raster de sortie
if debug >= 3:
print(cyan + "vectorsListToOcs() : " + endC +
"Ajout de l'information dans le raster de sortie." + '\n')
if idx == 1:
shutil.copy(vector_file_raster, output_raster)
else:
removeFile(temp_raster)
shutil.copy(output_raster, temp_raster)
removeFile(output_raster)
expression = "im1b1!=%s ? im1b1 : im2b1" % no_data_value
rasterCalculator([temp_raster, vector_file_raster],
output_raster,
expression,
codage=codage_raster)
print(cyan + "vectorsListToOcs() : " + bold + green +
"Fin de la génération de l'OCS raster à partir de vecteurs." + endC +
'\n')
####################################################################
# Suppression des fichiers temporaires
if not save_results_intermediate:
if debug >= 3:
print(cyan + "vectorsListToOcs() : " + endC +
"Suppression des fichiers temporaires." + '\n')
deleteDir(temp_directory)
print(cyan + "vectorsListToOcs() : " + bold + green +
"FIN DES TRAITEMENTS" + endC + '\n')
# Mise à jour du log
ending_event = "vectorsListToOcs() : Fin du traitement : "
timeLine(path_time_log, ending_event)
return 0