Пример #1
0
def addDataBaseExo(image_input,
                   image_classif_add_output,
                   class_file_dico,
                   class_buffer_dico,
                   class_sql_dico,
                   path_time_log,
                   format_vector='ESRI Shapefile',
                   extension_raster=".tif",
                   extension_vector=".shp",
                   save_results_intermediate=False,
                   overwrite=True,
                   simplifie_param=10.0):

    # Mise à jour du Log
    starting_event = "addDataBaseExo() : Add data base exogene to classification starting : "
    timeLine(path_time_log, starting_event)

    # Print
    if debug >= 3:
        print(bold + green + "Variables dans la fonction" + endC)
        print(cyan + "addDataBaseExo() : " + endC + "image_input : " +
              str(image_input) + endC)
        print(cyan + "addDataBaseExo() : " + endC +
              "image_classif_add_output : " + str(image_classif_add_output) +
              endC)
        print(cyan + "addDataBaseExo() : " + endC + "class_file_dico : " +
              str(class_file_dico) + endC)
        print(cyan + "addDataBaseExo() : " + endC + "class_buffer_dico : " +
              str(class_buffer_dico) + endC)
        print(cyan + "addDataBaseExo() : " + endC + "class_sql_dico : " +
              str(class_sql_dico) + endC)
        print(cyan + "addDataBaseExo() : " + endC + "path_time_log : " +
              str(path_time_log) + endC)
        print(cyan + "addDataBaseExo() : " + endC + "format_vector : " +
              str(format_vector) + endC)
        print(cyan + "addDataBaseExo() : " + endC + "extension_raster : " +
              str(extension_raster) + endC)
        print(cyan + "addDataBaseExo() : " + endC + "extension_vector : " +
              str(extension_vector) + endC)
        print(cyan + "addDataBaseExo() : " + endC +
              "save_results_intermediate : " + str(save_results_intermediate) +
              endC)
        print(cyan + "addDataBaseExo() : " + endC + "overwrite : " +
              str(overwrite) + endC)

    # Constantes
    FOLDER_MASK_TEMP = 'Mask_'
    FOLDER_FILTERING_TEMP = 'Filt_'
    FOLDER_CUTTING_TEMP = 'Cut_'
    FOLDER_BUFF_TEMP = 'Buff_'

    SUFFIX_MASK_CRUDE = '_mcrude'
    SUFFIX_MASK = '_mask'
    SUFFIX_FUSION = '_info'
    SUFFIX_VECTOR_FILTER = "_filt"
    SUFFIX_VECTOR_CUT = '_decoup'
    SUFFIX_VECTOR_BUFF = '_buff'

    CODAGE = "uint16"

    # ETAPE 1 : NETTOYER LES DONNEES EXISTANTES
    if debug >= 2:
        print(cyan + "addDataBaseExo() : " + bold + green +
              "NETTOYAGE ESPACE DE TRAVAIL..." + endC)

    # Nom de base de l'image
    image_name = os.path.splitext(os.path.basename(image_input))[0]

    # Nettoyage d'anciennes données résultat

    # Si le fichier résultat existent deja et que overwrite n'est pas activé
    check = os.path.isfile(image_classif_add_output)
    if check and not overwrite:
        print(bold + yellow + "addDataBaseExo() : " + endC +
              image_classif_add_output +
              " has already added bd exo and will not be added again." + endC)
    else:
        if check:
            try:
                removeFile(image_classif_add_output
                           )  # Tentative de suppression du fichier
            except Exception:
                pass  # Si le fichier ne peut pas être supprimé, on suppose qu'il n'existe pas et on passe à la suite

        # Définition des répertoires temporaires
        repertory_output = os.path.dirname(image_classif_add_output)
        repertory_mask_temp = repertory_output + os.sep + FOLDER_MASK_TEMP + image_name
        repertory_samples_filtering_temp = repertory_output + os.sep + FOLDER_FILTERING_TEMP + image_name
        repertory_samples_cutting_temp = repertory_output + os.sep + FOLDER_CUTTING_TEMP + image_name
        repertory_samples_buff_temp = repertory_output + os.sep + FOLDER_BUFF_TEMP + image_name

        if debug >= 4:
            print(repertory_mask_temp)
            print(repertory_samples_filtering_temp)
            print(repertory_samples_cutting_temp)
            print(repertory_samples_buff_temp)

        # Creer les répertoires temporaire si ils n'existent pas
        if not os.path.isdir(repertory_output):
            os.makedirs(repertory_output)
        if not os.path.isdir(repertory_mask_temp):
            os.makedirs(repertory_mask_temp)
        if not os.path.isdir(repertory_samples_filtering_temp):
            os.makedirs(repertory_samples_filtering_temp)
        if not os.path.isdir(repertory_samples_cutting_temp):
            os.makedirs(repertory_samples_cutting_temp)
        if not os.path.isdir(repertory_samples_buff_temp):
            os.makedirs(repertory_samples_buff_temp)

        # Nettoyer les répertoires temporaire si ils ne sont pas vide
        cleanTempData(repertory_mask_temp)
        cleanTempData(repertory_samples_filtering_temp)
        cleanTempData(repertory_samples_cutting_temp)
        cleanTempData(repertory_samples_buff_temp)

        if debug >= 2:
            print(cyan + "addDataBaseExo() : " + bold + green +
                  "... FIN NETTOYAGE" + endC)

        # ETAPE 2 : CREER UN SHAPE DE DECOUPE

        if debug >= 2:
            print(cyan + "addDataBaseExo() : " + bold + green +
                  "SHAPE DE DECOUPE..." + endC)

        # 2.1 : Création des masques délimitant l'emprise de la zone par image

        vector_mask = repertory_mask_temp + os.sep + image_name + SUFFIX_MASK_CRUDE + extension_vector
        createVectorMask(image_input, vector_mask)

        # 2.2 : Simplification du masque global

        vector_simple_mask_cut = repertory_mask_temp + os.sep + image_name + SUFFIX_MASK + extension_vector
        simplifyVector(vector_mask, vector_simple_mask_cut, simplifie_param,
                       format_vector)

        if debug >= 2:
            print(cyan + "addDataBaseExo() : " + bold + green +
                  "...FIN SHAPE DE DECOUPEE" + endC)

        # ETAPE 3 : DECOUPER BUFFERISER LES VECTEURS ET FUSIONNER

        if debug >= 2:
            print(cyan + "addDataBaseExo() : " + bold + green +
                  "MISE EN PLACE DES TAMPONS..." + endC)

        image_combined_list = []
        # Parcours du dictionnaire associant les macroclasses aux noms de fichiers
        for macroclass_label in class_file_dico:
            vector_fusion_list = []
            for index_info in range(len(class_file_dico[macroclass_label])):
                input_vector = class_file_dico[macroclass_label][index_info]
                vector_name = os.path.splitext(
                    os.path.basename(input_vector))[0]
                output_vector_filtered = repertory_samples_filtering_temp + os.sep + vector_name + SUFFIX_VECTOR_FILTER + extension_vector
                output_vector_cut = repertory_samples_cutting_temp + os.sep + vector_name + SUFFIX_VECTOR_CUT + extension_vector
                output_vector_buff = repertory_samples_buff_temp + os.sep + vector_name + SUFFIX_VECTOR_BUFF + extension_vector
                sql_expression = class_sql_dico[macroclass_label][index_info]
                buffer_str = class_buffer_dico[macroclass_label][index_info]
                buff = 0.0
                col_name_buf = ""
                try:
                    buff = float(buffer_str)
                except:
                    col_name_buf = buffer_str
                    print(
                        cyan + "addDataBaseExo() : " + bold + green +
                        "Pas de valeur buffer mais un nom de colonne pour les valeur à bufferiser : "
                        + endC + col_name_buf)

                if os.path.isfile(input_vector):
                    if debug >= 3:
                        print(cyan + "addDataBaseExo() : " + endC +
                              "input_vector : " + str(input_vector) + endC)
                        print(cyan + "addDataBaseExo() : " + endC +
                              "output_vector_filtered : " +
                              str(output_vector_filtered) + endC)
                        print(cyan + "addDataBaseExo() : " + endC +
                              "output_vector_cut : " + str(output_vector_cut) +
                              endC)
                        print(cyan + "addDataBaseExo() : " + endC +
                              "output_vector_buff : " +
                              str(output_vector_buff) + endC)
                        print(cyan + "addDataBaseExo() : " + endC + "buff : " +
                              str(buff) + endC)
                        print(cyan + "addDataBaseExo() : " + endC + "sql : " +
                              str(sql_expression) + endC)

                    # 3.0 : Recuperer les vecteurs d'entrée et filtree selon la requete sql par ogr2ogr
                    if sql_expression != "":
                        names_attribut_list = getAttributeNameList(
                            input_vector, format_vector)
                        column = "'"
                        for name_attribut in names_attribut_list:
                            column += name_attribut + ", "
                        column = column[0:len(column) - 2]
                        column += "'"
                        ret = filterSelectDataVector(input_vector,
                                                     output_vector_filtered,
                                                     column, sql_expression,
                                                     format_vector)
                        if not ret:
                            print(
                                cyan + "addDataBaseExo() : " + bold + yellow +
                                "Attention problème lors du filtrage des BD vecteurs l'expression SQL %s est incorrecte"
                                % (sql_expression) + endC)
                            output_vector_filtered = input_vector
                    else:
                        print(cyan + "addDataBaseExo() : " + bold + green +
                              "Pas de filtrage sur le fichier du nom : " +
                              endC + output_vector_filtered)
                        output_vector_filtered = input_vector

                    # 3.1 : Découper le vecteur selon l'empise de l'image d'entrée
                    cutoutVectors(vector_simple_mask_cut,
                                  [output_vector_filtered],
                                  [output_vector_cut], format_vector)

                    # 3.2 : Bufferiser lesvecteurs découpé avec la valeur défini dans le dico ou trouver dans la base du vecteur lui même si le nom de la colonne est passée dans le dico
                    if os.path.isfile(output_vector_cut) and (
                        (buff != 0) or (col_name_buf != "")):
                        bufferVector(output_vector_cut, output_vector_buff,
                                     buff, col_name_buf, 1.0, 10,
                                     format_vector)
                    else:
                        print(cyan + "addDataBaseExo() : " + bold + green +
                              "Pas de buffer sur le fichier du nom : " + endC +
                              output_vector_cut)
                        output_vector_buff = output_vector_cut

                    # 3.3 : Si un shape résulat existe l'ajouté à la liste de fusion
                    if os.path.isfile(output_vector_buff):
                        vector_fusion_list.append(output_vector_buff)
                        if debug >= 3:
                            print("file for fusion : " + output_vector_buff)
                    else:
                        print(bold + yellow +
                              "pas de fichiers avec ce nom : " + endC +
                              output_vector_buff)

                else:
                    print(cyan + "addDataBaseExo() : " + bold + yellow +
                          "Pas de fichier du nom : " + endC + input_vector)

            # 3.4 : Fusionner les shapes transformés d'une même classe, rasterization et labelisations des vecteurs
            # Si une liste de fichier shape existe
            if not vector_fusion_list:
                print(bold + yellow + "Pas de fusion sans donnee a fusionnee" +
                      endC)
            else:
                # Rasterization et BandMath des fichiers shapes
                raster_list = []
                for vector in vector_fusion_list:
                    if debug >= 3:
                        print(cyan + "addDataBaseExo() : " + endC +
                              "Rasterization : " + vector + " label : " +
                              macroclass_label)
                    raster_output = os.path.splitext(
                        vector)[0] + extension_raster

                    # Rasterisation
                    rasterizeBinaryVector(vector, image_input, raster_output,
                                          macroclass_label, CODAGE)
                    raster_list.append(raster_output)

                if debug >= 3:
                    print(cyan + "addDataBaseExo() : " + endC +
                          "nombre d'images a combiner : " +
                          str(len(raster_list)))

                # Liste les images raster combined and sample
                image_combined = repertory_output + os.sep + image_name + '_' + str(
                    macroclass_label) + SUFFIX_FUSION + extension_raster
                image_combined_list.append(image_combined)

                # Fusion des images raster en une seule
                mergeListRaster(raster_list, image_combined, CODAGE)

        if debug >= 2:
            print(cyan + "addDataBaseExo() : " + bold + green +
                  "FIN DE L AFFECTATION DES TAMPONS" + endC)

        # ETAPE 4 : ASSEMBLAGE DE L'IMAGE CLASSEE ET DES BD EXOS
        if debug >= 2:
            print(cyan + "addDataBaseExo() : " + bold + green +
                  "ASSEMBLAGE..." + endC)

        # Ajout de l'image de classification a la liste des image bd conbinées
        image_combined_list.append(image_input)
        # Fusion les images avec la classification
        mergeListRaster(image_combined_list, image_classif_add_output, CODAGE)
        if debug >= 2:
            print(cyan + "addDataBaseExo() : " + bold + green + "FIN" + endC)

    # ETAPE 5 : SUPPRESIONS FICHIERS INTERMEDIAIRES INUTILES

    # Suppression des données intermédiaires
    if not save_results_intermediate:

        image_combined_list.remove(image_input)
        for to_delete in image_combined_list:
            removeFile(to_delete)

        # Suppression des repertoires temporaires
        deleteDir(repertory_mask_temp)
        deleteDir(repertory_samples_filtering_temp)
        deleteDir(repertory_samples_cutting_temp)
        deleteDir(repertory_samples_buff_temp)

    # Mise à jour du Log
    ending_event = "addDataBaseExo() : Add data base exogene to classification ending : "
    timeLine(path_time_log, ending_event)

    return
def estimateQualityMns(image_input,
                       vector_cut_input,
                       vector_sample_input_list,
                       vector_sample_points_input,
                       raster_input_dico,
                       vector_output,
                       no_data_value,
                       path_time_log,
                       format_raster='GTiff',
                       epsg=2154,
                       format_vector='ESRI Shapefile',
                       extension_raster=".tif",
                       extension_vector=".shp",
                       save_results_intermediate=False,
                       overwrite=True):

    # Mise à jour du Log
    starting_event = "estimateQualityMns() : Masks creation starting : "
    timeLine(path_time_log, starting_event)

    print(endC)
    print(bold + green + "## START : CREATE HEIGHT POINTS FILE FROM MNS" +
          endC)
    print(endC)

    if debug >= 2:
        print(bold + green +
              "estimateQualityMns() : Variables dans la fonction" + endC)
        print(cyan + "estimateQualityMns() : " + endC + "image_input : " +
              str(image_input) + endC)
        print(cyan + "estimateQualityMns() : " + endC + "vector_cut_input : " +
              str(vector_cut_input) + endC)
        print(cyan + "estimateQualityMns() : " + endC +
              "vector_sample_input_list : " + str(vector_sample_input_list) +
              endC)
        print(cyan + "estimateQualityMns() : " + endC +
              "vector_sample_points_input : " +
              str(vector_sample_points_input) + endC)
        print(cyan + "estimateQualityMns() : " + endC +
              "raster_input_dico : " + str(raster_input_dico) + endC)
        print(cyan + "estimateQualityMns() : " + endC + "vector_output : " +
              str(vector_output) + endC)
        print(cyan + "estimateQualityMns() : " + endC + "no_data_value : " +
              str(no_data_value))
        print(cyan + "estimateQualityMns() : " + endC + "path_time_log : " +
              str(path_time_log) + endC)
        print(cyan + "estimateQualityMns() : " + endC + "epsg  : " +
              str(epsg) + endC)
        print(cyan + "estimateQualityMns() : " + endC + "format_raster : " +
              str(format_raster) + endC)
        print(cyan + "estimateQualityMns() : " + endC + "format_vector : " +
              str(format_vector) + endC)
        print(cyan + "estimateQualityMns() : " + endC + "extension_raster : " +
              str(extension_raster) + endC)
        print(cyan + "estimateQualityMns() : " + endC + "extension_vector : " +
              str(extension_vector) + endC)
        print(cyan + "estimateQualityMns() : " + endC +
              "save_results_intermediate : " + str(save_results_intermediate) +
              endC)
        print(cyan + "estimateQualityMns() : " + endC + "overwrite : " +
              str(overwrite) + endC)

    # Définion des constantes
    EXT_DBF = '.dbf'
    EXT_CSV = '.csv'

    CODAGE = "uint16"

    SUFFIX_STUDY = '_study'
    SUFFIX_CUT = '_cut'
    SUFFIX_TEMP = '_temp'
    SUFFIX_CLEAN = '_clean'
    SUFFIX_SAMPLE = '_sample'

    ATTRIBUTE_ID = "ID"
    ATTRIBUTE_Z_INI = "Z_INI"
    ATTRIBUTE_Z_FIN = "Z_FIN"
    ATTRIBUTE_PREC_ALTI = "PREC_ALTI"
    ATTRIBUTE_Z_REF = "Z_Ref"
    ATTRIBUTE_Z_MNS = "Z_Mns"
    ATTRIBUTE_Z_DELTA = "Z_Delta"

    ERODE_EDGE_POINTS = -1.0

    ERROR_VALUE = -99.0
    ERROR_MIN_VALUE = -9999
    ERROR_MAX_VALUE = 9999

    # ETAPE 0 : PREPARATION DES FICHIERS INTERMEDIAIRES

    # Si le fichier de sortie existe on ecrase
    check = os.path.isfile(vector_output)
    if check and not overwrite:  # Si un fichier de sortie avec le même nom existe déjà, et si l'option ecrasement est à false, alors FIN
        print(cyan + "estimateQualityMns() : " + bold + yellow +
              "Create  file %s already exist : no actualisation" %
              (vector_output) + endC)
        return

    if os.path.isfile(os.path.splitext(vector_output)[0] + EXT_CSV):
        removeFile(os.path.splitext(vector_output)[0] + EXT_CSV)

    repertory_output = os.path.dirname(vector_output)
    base_name = os.path.splitext(os.path.basename(vector_output))[0]

    vector_output_temp = repertory_output + os.sep + base_name + SUFFIX_TEMP + extension_vector
    raster_study = repertory_output + os.sep + base_name + SUFFIX_STUDY + extension_raster
    vector_study = repertory_output + os.sep + base_name + SUFFIX_STUDY + extension_vector
    vector_study_clean = repertory_output + os.sep + base_name + SUFFIX_STUDY + SUFFIX_CLEAN + extension_vector
    image_cut = repertory_output + os.sep + base_name + SUFFIX_CUT + extension_raster
    vector_sample_temp = repertory_output + os.sep + base_name + SUFFIX_SAMPLE + SUFFIX_TEMP + extension_vector
    vector_sample_temp_clean = repertory_output + os.sep + base_name + SUFFIX_SAMPLE + SUFFIX_TEMP + SUFFIX_CLEAN + extension_vector

    # Utilisation des données raster externes
    raster_cut_dico = {}
    for raster_input in raster_input_dico:
        base_name_raster = os.path.splitext(os.path.basename(raster_input))[0]
        raster_cut = repertory_output + os.sep + base_name_raster + SUFFIX_CUT + extension_raster
        raster_cut_dico[raster_input] = raster_cut
        if os.path.exists(raster_cut):
            removeFile(raster_cut)

    # ETAPE 1 : DEFINIR UN SHAPE ZONE D'ETUDE

    if (not vector_cut_input is None) and (vector_cut_input != "") and (
            os.path.isfile(vector_cut_input)):
        cutting_action = True
        vector_study = vector_cut_input

    else:
        cutting_action = False
        createVectorMask(image_input, vector_study)

    # ETAPE 2 : DECOUPAGE DU RASTEUR PAR LE VECTEUR D'ETUDE SI BESOIN ET REECHANTILLONAGE SI BESOIN

    if cutting_action:
        # Identification de la tailles de pixels en x et en y du fichier MNS de reference
        pixel_size_x, pixel_size_y = getPixelWidthXYImage(image_input)

        # Si le fichier de sortie existe deja le supprimer
        if os.path.exists(image_cut):
            removeFile(image_cut)

        # Commande de découpe
        if not cutImageByVector(vector_study, image_input, image_cut,
                                pixel_size_x, pixel_size_y, no_data_value, 0,
                                format_raster, format_vector):
            print(
                cyan + "estimateQualityMns() : " + bold + red +
                "Une erreur c'est produite au cours du decoupage de l'image : "
                + image_input + endC,
                file=sys.stderr)
            raise

        if debug >= 2:
            print(cyan + "estimateQualityMns() : " + bold + green +
                  "DECOUPAGE DU RASTER %s AVEC LE VECTEUR %s" %
                  (image_input, vector_study) + endC)
    else:
        image_cut = image_input

    # Definir l'emprise du fichier MNS de reference

    # Decoupage de chaque raster de la liste des rasters
    for raster_input in raster_input_dico:
        raster_cut = raster_cut_dico[raster_input]
        if not cutImageByVector(vector_study, raster_input, raster_cut,
                                pixel_size_x, pixel_size_y, no_data_value, 0,
                                format_raster, format_vector):
            raise NameError(
                cyan + "estimateQualityMns() : " + bold + red +
                "Une erreur c'est produite au cours du decoupage du raster : "
                + raster_input + endC)

    # Gémotrie de l'image
    pixel_size_x, pixel_size_y = getPixelWidthXYImage(image_cut)
    cols, rows, bands = getGeometryImage(image_cut)
    xmin, xmax, ymin, ymax = getEmpriseImage(image_cut)

    if debug >= 3:
        print("Geometrie Image : ")
        print("  cols = " + str(cols))
        print("  rows = " + str(rows))
        print("  xmin = " + str(xmin))
        print("  xmax = " + str(xmax))
        print("  ymin = " + str(ymin))
        print("  ymax = " + str(ymax))
        print("  pixel_size_x = " + str(pixel_size_x))
        print("  pixel_size_y = " + str(pixel_size_y))
        print("\n")

    # Création du dico coordonnées des points en systeme cartographique
    points_random_value_dico = {}
    # liste coordonnées des points au format matrice image brute
    points_coordonnees_image_list = []

    # Selon que l'on utilise le fichier de points d'echantillons ou que l'on recréé a partir des sommets des vecteurs lignes
    if (vector_sample_points_input is None) or (vector_sample_points_input
                                                == ""):

        # ETAPE 3 : DECOUPAGES DES VECTEURS DE REFERENCE D'ENTREE PAR LE VECTEUR D'ETUDE ET LEUR FUSION ET
        #           LECTURE D'UN VECTEUR DE LIGNES ET SAUVEGARDE DES COORDONNEES POINTS DES EXTREMITEES ET LEUR HAUTEUR

        # Découpage des vecteurs de bd réference avec le vecteur zone d'étude
        vector_sample_input_cut_list = []
        for vector_sample in vector_sample_input_list:
            vector_name = os.path.splitext(os.path.basename(vector_sample))[0]
            vector_sample_cut = repertory_output + os.sep + vector_name + SUFFIX_CUT + extension_vector
            vector_sample_input_cut_list.append(vector_sample_cut)
        cutoutVectors(vector_study, vector_sample_input_list,
                      vector_sample_input_cut_list, format_vector)

        # Fusion des vecteurs de bd réference découpés
        fusionVectors(vector_sample_input_cut_list, vector_sample_temp,
                      format_vector)

        # Preparation des colonnes
        names_column_start_point_list = [
            ATTRIBUTE_ID, ATTRIBUTE_Z_INI, ATTRIBUTE_PREC_ALTI
        ]
        names_column_end_point_list = [
            ATTRIBUTE_ID, ATTRIBUTE_Z_FIN, ATTRIBUTE_PREC_ALTI
        ]
        fields_list = [
            ATTRIBUTE_ID, ATTRIBUTE_PREC_ALTI, ATTRIBUTE_Z_INI, ATTRIBUTE_Z_FIN
        ]

        multigeometries2geometries(vector_sample_temp,
                                   vector_sample_temp_clean, fields_list,
                                   "MULTILINESTRING", format_vector)
        points_coordinates_dico = readVectorFileLinesExtractTeminalsPoints(
            vector_sample_temp_clean, names_column_start_point_list,
            names_column_end_point_list, format_vector)

    else:
        # ETAPE 3_BIS : DECOUPAGE DE VECTEURS D'ECHANTILLONS POINTS PAR LE VECTEUR D'EMPRISE ET
        #               LECTURE DES COORDONNES D'ECHANTILLONS DURECTEMENT DANS LE FICHIER VECTEUR POINTS

        # Liste coordonnées des points au format matrice image brute
        cutVectorAll(vector_study, vector_sample_points_input,
                     vector_sample_temp, format_vector)
        points_coordinates_dico = readVectorFilePoints(vector_sample_temp,
                                                       format_vector)

    # ETAPE 4 : PREPARATION DU VECTEUR DE POINTS

    for index_key in points_coordinates_dico:
        # Recuperer les valeurs des coordonnees
        coord_info_list = points_coordinates_dico[index_key]
        coor_x = coord_info_list[0]
        coor_y = coord_info_list[1]
        attribut_dico = coord_info_list[2]

        # Coordonnées des points au format matrice image
        pos_x = int(round((coor_x - xmin) / abs(pixel_size_x)) - 1)
        pos_y = int(round((ymax - coor_y) / abs(pixel_size_y)) - 1)

        if pos_x < 0:
            pos_x = 0
        if pos_x >= cols:
            pos_x = cols - 1
        if pos_y < 0:
            pos_y = 0
        if pos_y >= rows:
            pos_y = rows - 1

        coordonnees_list = [pos_x, pos_y]
        points_coordonnees_image_list.append(coordonnees_list)

        value_ref = 0.0
        if ATTRIBUTE_Z_INI in attribut_dico.keys():
            value_ref = float(attribut_dico[ATTRIBUTE_Z_INI])
        if ATTRIBUTE_Z_FIN in attribut_dico.keys():
            value_ref = float(attribut_dico[ATTRIBUTE_Z_FIN])

        precision_alti = 0.0
        if ATTRIBUTE_PREC_ALTI in attribut_dico.keys():
            precision_alti = float(attribut_dico[ATTRIBUTE_PREC_ALTI])

        point_attr_dico = {
            ATTRIBUTE_ID: index_key,
            ATTRIBUTE_Z_REF: value_ref,
            ATTRIBUTE_PREC_ALTI: precision_alti,
            ATTRIBUTE_Z_MNS: 0.0,
            ATTRIBUTE_Z_DELTA: 0.0
        }

        for raster_input in raster_input_dico:
            field_name = raster_input_dico[raster_input][0][0]
            point_attr_dico[field_name] = 0.0

        points_random_value_dico[index_key] = [[coor_x, coor_y],
                                               point_attr_dico]

    # ETAPE 5 : LECTURE DES DONNEES DE HAUTEURS ISSU DU MNS et autre raster

    # Lecture dans le fichier raster des valeurs
    values_height_list = getPixelsValueListImage(
        image_cut, points_coordonnees_image_list)
    values_others_dico = {}
    for raster_input in raster_input_dico:
        raster_cut = raster_cut_dico[raster_input]
        values_list = getPixelsValueListImage(raster_cut,
                                              points_coordonnees_image_list)
        values_others_dico[raster_input] = values_list

    for i in range(len(points_random_value_dico)):
        value_mns = values_height_list[i]
        value_ref = points_random_value_dico[i][1][ATTRIBUTE_Z_REF]

        points_random_value_dico[i][1][ATTRIBUTE_Z_MNS] = float(value_mns)
        precision_alti = points_random_value_dico[i][1][ATTRIBUTE_PREC_ALTI]
        points_random_value_dico[i][1][ATTRIBUTE_PREC_ALTI] = float(
            precision_alti)
        value_diff = value_ref - value_mns
        points_random_value_dico[i][1][ATTRIBUTE_Z_DELTA] = float(value_diff)

        for raster_input in raster_input_dico:
            field_name = raster_input_dico[raster_input][0][0]
            value_other = values_others_dico[raster_input][i]
            points_random_value_dico[i][1][field_name] = float(value_other)

    # ETAPE 6 : CREATION D'UN VECTEUR DE POINTS AVEC DONNEE COORDONNES POINT ET HAUTEUR REFERENCE ET MNS

    # Suppression des points contenant des valeurs en erreur et en dehors du filtrage
    points_random_value_dico_clean = {}
    for i in range(len(points_random_value_dico)):
        value_ref = points_random_value_dico[i][1][ATTRIBUTE_Z_REF]
        if value_ref != ERROR_VALUE and value_ref > ERROR_MIN_VALUE and value_ref < ERROR_MAX_VALUE:

            points_is_valid = True
            for raster_input in raster_input_dico:
                if len(raster_input_dico[raster_input]) > 1 and len(
                        raster_input_dico[raster_input][1]) > 1:
                    threshold_min = float(
                        raster_input_dico[raster_input][1][0])
                    threshold_max = float(
                        raster_input_dico[raster_input][1][1])
                    field_name = raster_input_dico[raster_input][0][0]
                    value_raster = float(
                        points_random_value_dico[i][1][field_name])
                    if value_raster < threshold_min or value_raster > threshold_max:
                        points_is_valid = False

            if points_is_valid:
                points_random_value_dico_clean[i] = points_random_value_dico[i]

    # Définir les attibuts du fichier résultat
    attribute_dico = {
        ATTRIBUTE_ID: ogr.OFTInteger,
        ATTRIBUTE_PREC_ALTI: ogr.OFTReal,
        ATTRIBUTE_Z_REF: ogr.OFTReal,
        ATTRIBUTE_Z_MNS: ogr.OFTReal,
        ATTRIBUTE_Z_DELTA: ogr.OFTReal
    }

    for raster_input in raster_input_dico:
        field_name = raster_input_dico[raster_input][0][0]
        attribute_dico[field_name] = ogr.OFTReal

    createPointsFromCoordList(attribute_dico, points_random_value_dico_clean,
                              vector_output_temp, epsg, format_vector)

    # Suppression des points en bord de zone d'étude
    bufferVector(vector_study, vector_study_clean, ERODE_EDGE_POINTS, "", 1.0,
                 10, format_vector)
    cutVectorAll(vector_study_clean, vector_output_temp, vector_output, True,
                 format_vector)

    # ETAPE 7 : TRANSFORMATION DU FICHIER .DBF EN .CSV
    dbf_file = repertory_output + os.sep + base_name + EXT_DBF
    csv_file = repertory_output + os.sep + base_name + EXT_CSV

    if debug >= 2:
        print(cyan + "estimateQualityMns() : " + bold + green +
              "Conversion du fichier DBF %s en fichier CSV %s" %
              (dbf_file, csv_file) + endC)

    convertDbf2Csv(dbf_file, csv_file)

    # ETAPE 8 : SUPPRESIONS FICHIERS INTERMEDIAIRES INUTILES

    # Suppression des données intermédiaires
    if not save_results_intermediate:
        if cutting_action:
            if os.path.isfile(image_cut):
                removeFile(image_cut)
        else:
            if os.path.isfile(vector_study):
                removeVectorFile(vector_study)

        for raster_input in raster_input_dico:
            raster_cut = raster_cut_dico[raster_input]
            if os.path.isfile(raster_cut):
                removeFile(raster_cut)

        if os.path.isfile(vector_output_temp):
            removeVectorFile(vector_output_temp)

        if os.path.isfile(vector_study_clean):
            removeVectorFile(vector_study_clean)

        if os.path.isfile(vector_sample_temp):
            removeVectorFile(vector_sample_temp)

        if os.path.isfile(vector_sample_temp_clean):
            removeVectorFile(vector_sample_temp_clean)

        for vector_file in vector_sample_input_cut_list:
            if os.path.isfile(vector_file):
                removeVectorFile(vector_file)

    print(bold + green + "## END : CREATE HEIGHT POINTS FILE FROM MNSE" + endC)

    # Mise à jour du Log
    ending_event = "estimateQualityMns() : Masks creation ending : "
    timeLine(path_time_log, ending_event)

    return
Пример #3
0
def createMnh(image_mns_input, image_mnt_input, image_threshold_input, vector_emprise_input, image_mnh_output, automatic, bd_road_vector_input_list, bd_road_buff_list, sql_road_expression_list, bd_build_vector_input_list, height_bias, threshold_bd_value, threshold_delta_h, mode_interpolation, method_interpolation, interpolation_bco_radius, simplify_vector_param, epsg, no_data_value, ram_otb, path_time_log, format_raster='GTiff', format_vector='ESRI Shapefile', extension_raster=".tif", extension_vector=".shp", save_results_intermediate=False, overwrite=True):

    # Mise à jour du Log
    starting_event = "createMnh() : MNH creation starting : "
    timeLine(path_time_log,starting_event)

    print(endC)
    print(bold + green + "## START : MNH CREATION" + endC)
    print(endC)

    if debug >= 2:
        print(bold + green + "createMnh() : Variables dans la fonction" + endC)
        print(cyan + "createMnh() : " + endC + "image_mns_input : " + str(image_mns_input) + endC)
        print(cyan + "createMnh() : " + endC + "image_mnt_input : " + str(image_mnt_input) + endC)
        print(cyan + "createMnh() : " + endC + "image_threshold_input : " + str(image_threshold_input) + endC)
        print(cyan + "createMnh() : " + endC + "vector_emprise_input : " + str(vector_emprise_input) + endC)
        print(cyan + "createMnh() : " + endC + "image_mnh_output : " + str(image_mnh_output) + endC)
        print(cyan + "createMnh() : " + endC + "automatic : " + str(automatic) + endC)
        print(cyan + "createMnh() : " + endC + "bd_road_vector_input_list : " + str(bd_road_vector_input_list) + endC)
        print(cyan + "createMnh() : " + endC + "bd_road_buff_list : " + str(bd_road_buff_list) + endC)
        print(cyan + "createMnh() : " + endC + "sql_road_expression_list : " + str(sql_road_expression_list) + endC)
        print(cyan + "createMnh() : " + endC + "bd_build_vector_input_list : " + str(bd_build_vector_input_list) + endC)
        print(cyan + "createMnh() : " + endC + "height_bias : " + str(height_bias) + endC)
        print(cyan + "createMnh() : " + endC + "threshold_bd_value : " + str(threshold_bd_value) + endC)
        print(cyan + "createMnh() : " + endC + "threshold_delta_h : " + str(threshold_delta_h) + endC)
        print(cyan + "createMnh() : " + endC + "mode_interpolation : " + str(mode_interpolation) + endC)
        print(cyan + "createMnh() : " + endC + "method_interpolation : " + str(method_interpolation) + endC)
        print(cyan + "createMnh() : " + endC + "interpolation_bco_radius : " + str(interpolation_bco_radius) + endC)
        print(cyan + "createMnh() : " + endC + "simplify_vector_param : " + str(simplify_vector_param) + endC)
        print(cyan + "createMnh() : " + endC + "epsg : " + str(epsg) + endC)
        print(cyan + "createMnh() : " + endC + "no_data_value : " + str(no_data_value) + endC)
        print(cyan + "createMnh() : " + endC + "ram_otb : " + str(ram_otb) + endC)
        print(cyan + "createMnh() : " + endC + "path_time_log : " + str(path_time_log) + endC)
        print(cyan + "createMnh() : " + endC + "format_raster : " + str(format_raster) + endC)
        print(cyan + "createMnh() : " + endC + "format_vector : " + str(format_vector) + endC)
        print(cyan + "createMnh() : " + endC + "extension_raster : " + str(extension_raster) + endC)
        print(cyan + "createMnh() : " + endC + "extension_vector : " + str(extension_vector) + endC)
        print(cyan + "createMnh() : " + endC + "save_results_intermediate : " + str(save_results_intermediate) + endC)
        print(cyan + "createMnh() : " + endC + "overwrite : " + str(overwrite) + endC)

    # LES CONSTANTES
    PRECISION = 0.0000001

    CODAGE_8B = "uint8"
    CODAGE_F = "float"

    SUFFIX_CUT = "_cut"
    SUFFIX_CLEAN = "_clean"
    SUFFIX_SAMPLE = "_sample"
    SUFFIX_MASK = "_mask"
    SUFFIX_TMP = "_tmp"
    SUFFIX_MNS = "_mns"
    SUFFIX_MNT = "_mnt"
    SUFFIX_ROAD = "_road"
    SUFFIX_BUILD = "_build"
    SUFFIX_RASTER = "_raster"
    SUFFIX_VECTOR = "_vector"

    # DEFINIR LES REPERTOIRES ET FICHIERS TEMPORAIRES
    repertory_output = os.path.dirname(image_mnh_output)
    basename_mnh = os.path.splitext(os.path.basename(image_mnh_output))[0]

    sub_repertory_raster_temp = repertory_output + os.sep + basename_mnh + SUFFIX_RASTER + SUFFIX_TMP
    sub_repertory_vector_temp = repertory_output + os.sep + basename_mnh + SUFFIX_VECTOR + SUFFIX_TMP
    cleanTempData(sub_repertory_raster_temp)
    cleanTempData(sub_repertory_vector_temp)

    basename_vector_emprise = os.path.splitext(os.path.basename(vector_emprise_input))[0]
    basename_mns_input = os.path.splitext(os.path.basename(image_mns_input))[0]
    basename_mnt_input = os.path.splitext(os.path.basename(image_mnt_input))[0]

    image_mnh_tmp = sub_repertory_raster_temp + os.sep + basename_mnh + SUFFIX_TMP + extension_raster
    image_mnh_road = sub_repertory_raster_temp + os.sep + basename_mnh + SUFFIX_ROAD + extension_raster

    vector_bd_bati_temp = sub_repertory_vector_temp + os.sep + basename_mnh + SUFFIX_BUILD + SUFFIX_TMP + extension_vector
    vector_bd_bati = repertory_output + os.sep + basename_mnh + SUFFIX_BUILD + extension_vector
    raster_bd_bati = sub_repertory_vector_temp + os.sep + basename_mnh + SUFFIX_BUILD + extension_raster
    removeVectorFile(vector_bd_bati)

    image_emprise_mnt_mask = sub_repertory_raster_temp + os.sep + basename_vector_emprise + SUFFIX_MNT + extension_raster
    image_mnt_cut = sub_repertory_raster_temp + os.sep + basename_mnt_input + SUFFIX_CUT + extension_raster
    image_mnt_clean = sub_repertory_raster_temp + os.sep + basename_mnt_input + SUFFIX_CLEAN + extension_raster
    image_mnt_clean_sample = sub_repertory_raster_temp + os.sep + basename_mnt_input + SUFFIX_CLEAN + SUFFIX_SAMPLE + extension_raster
    image_emprise_mns_mask = sub_repertory_raster_temp + os.sep + basename_vector_emprise + SUFFIX_MNS + extension_raster
    image_mns_cut = sub_repertory_raster_temp + os.sep + basename_mns_input + SUFFIX_CUT + extension_raster
    image_mns_clean = sub_repertory_raster_temp + os.sep + basename_mns_input + SUFFIX_CLEAN + extension_raster

    vector_bd_road_temp = sub_repertory_vector_temp + os.sep + basename_mnh + SUFFIX_ROAD + SUFFIX_TMP + extension_vector
    raster_bd_road_mask = sub_repertory_raster_temp + os.sep + basename_mnh + SUFFIX_ROAD + SUFFIX_MASK + extension_raster

    if image_threshold_input != "" :
        basename_threshold_input = os.path.splitext(os.path.basename(image_threshold_input))[0]
        image_threshold_cut = sub_repertory_raster_temp + os.sep + basename_threshold_input + SUFFIX_CUT + extension_raster
        image_threshold_mask = sub_repertory_raster_temp + os.sep + basename_threshold_input + SUFFIX_MASK + extension_raster

    # VERIFICATION SI LE FICHIER DE SORTIE EXISTE DEJA
    # Si un fichier de sortie avec le même nom existe déjà, et si l'option ecrasement est à false, alors on ne fait rien
    check = os.path.isfile(image_mnh_output)
    if check and not overwrite:
        print(bold + yellow +  "createMnh() : " + endC + "Create mnh %s from %s and %s already done : no actualisation" % (image_mnh_output, image_mns_input, image_mnt_input) + endC)
    # Si non, ou si la fonction ecrasement est désative, alors on le calcule
    else:
        if check:
            try: # Suppression de l'éventuel fichier existant
                removeFile(image_mnh_output)
            except Exception:
                pass # Si le fichier ne peut pas être supprimé, on suppose qu'il n'existe pas et on passe à la suite

        # DECOUPAGE DES FICHIERS MS ET MNT D'ENTREE PAR LE FICHIER D'EMPRISE
        if debug >= 3:
            print(bold + green +  "createMnh() : " + endC + "Decoupage selon l'emprise des fichiers %s et %s " %(image_mns_input, image_mnt_input) + endC)

        # Fonction de découpe du mns
        if not cutImageByVector(vector_emprise_input, image_mns_input, image_mns_cut, None, None, no_data_value, epsg, format_raster, format_vector) :
            raise NameError (cyan + "createMnh() : " + bold + red + "!!! Une erreur c'est produite au cours du decoupage de l'image : " + image_mns_input + ". Voir message d'erreur." + endC)

        # Fonction de découpe du mnt
        if not cutImageByVector(vector_emprise_input, image_mnt_input, image_mnt_cut, None, None, no_data_value, epsg, format_raster, format_vector) :
            raise NameError (cyan + "createMnh() : " + bold + red + "!!! Une erreur c'est produite au cours du decoupage de l'image : " + image_mnt_input + ". Voir message d'erreur." + endC)

        if debug >= 3:
            print(bold + green +  "createMnh() : " + endC + "Decoupage des fichiers %s et %s complet" %(image_mns_cut, image_mnt_cut) + endC)


        # REBOUCHAGE DES TROUS DANS LE MNT D'ENTREE SI NECESSAIRE

        nodata_mnt = getNodataValueImage(image_mnt_cut)
        pixelNodataCount = countPixelsOfValue(image_mnt_cut, nodata_mnt)

        if pixelNodataCount > 0 :

            if debug >= 3:
                print(bold + green +  "createMnh() : " + endC + "Fill the holes MNT for  %s" %(image_mnt_cut) + endC)

            # Rasterisation du vecteur d'emprise pour creer un masque pour boucher les trous du MNT
            rasterizeBinaryVector(vector_emprise_input, image_mnt_cut, image_emprise_mnt_mask, 1, CODAGE_8B)

            # Utilisation de SAGA pour boucher les trous
            fillNodata(image_mnt_cut, image_emprise_mnt_mask, image_mnt_clean, save_results_intermediate)

            if debug >= 3:
                print(bold + green +  "createMnh() : " + endC + "Fill the holes MNT to %s completed" %(image_mnt_clean) + endC)

        else :
            image_mnt_clean = image_mnt_cut
            if debug >= 3:
                print(bold + green +  "\ncreateMnh() : " + endC + "Fill the holes not necessary MNT for %s" %(image_mnt_cut) + endC)


        # REBOUCHAGE DES TROUS DANS LE MNS D'ENTREE SI NECESSAIRE

        nodata_mns = getNodataValueImage(image_mns_cut)
        pixelNodataCount = countPixelsOfValue(image_mns_cut, nodata_mns)

        if pixelNodataCount > 0 :

            if debug >= 3:
                print(bold + green +  "createMnh() : " + endC + "Fill the holes MNS for  %s" %(image_mns_cut) + endC)

            # Rasterisation du vecteur d'emprise pour creer un masque pour boucher les trous du MNS
            rasterizeBinaryVector(vector_emprise_input, image_mns_cut, image_emprise_mns_mask, 1, CODAGE_8B)

            # Utilisation de SAGA pour boucher les trous
            fillNodata(image_mns_cut, image_emprise_mns_mask, image_mns_clean, save_results_intermediate)

            if debug >= 3:
                print(bold + green +  "\ncreateMnh() : " + endC + "Fill the holes MNS to %s completed" %(image_mns_clean) + endC)

        else :
            image_mns_clean = image_mns_cut
            if debug >= 3:
                print(bold + green +  "createMnh() : " + endC + "Fill the holes not necessary MNS for %s" %(image_mns_cut) + endC)

        # CALLER LE FICHIER MNT AU FORMAT DU FICHIER MNS

        # Commande de mise en place de la geométrie re-echantionage
        command = "otbcli_Superimpose -inr " + image_mns_clean + " -inm " + image_mnt_clean + " -mode " + mode_interpolation + " -interpolator " + method_interpolation + " -out " + image_mnt_clean_sample

        if method_interpolation.lower() == 'bco' :
            command += " -interpolator.bco.radius " + str(interpolation_bco_radius)
        if ram_otb > 0:
            command += " -ram %d" %(ram_otb)

        if debug >= 3:
            print(cyan + "createMnh() : " + bold + green + "Réechantillonage du fichier %s par rapport à la reference %s" %(image_mnt_clean, image_mns_clean) + endC)
            print(command)

        exit_code = os.system(command)
        if exit_code != 0:
            print(command)
            raise NameError (cyan + "createMnh() : " + bold + red + "!!! Une erreur c'est produite au cours du superimpose de l'image : " + image_mnt_input + ". Voir message d'erreur." + endC)

        # INCRUSTATION DANS LE MNH DES DONNEES VECTEURS ROUTES

        if debug >= 3:
            print(bold + green +  "createMnh() : " + endC + "Use BD road to clean MNH"  + endC)

        # Creation d'un masque de filtrage des donnes routes (exemple : le NDVI)
        if image_threshold_input != "" :
            if not cutImageByVector(vector_emprise_input, image_threshold_input, image_threshold_cut, None, None, no_data_value, epsg, format_raster, format_vector) :
                raise NameError (cyan + "createMnh() : " + bold + red + "!!! Une erreur c'est produite au cours du decoupage de l'image : " + image_threshold_input + ". Voir message d'erreur." + endC)
            createBinaryMask(image_threshold_cut, image_threshold_mask, threshold_bd_value, False, CODAGE_8B)

        # Execution de la fonction createMacroSamples pour une image correspondant au données routes
        if bd_road_vector_input_list != [] :
            createMacroSamples(image_mns_clean, vector_emprise_input, vector_bd_road_temp, raster_bd_road_mask, bd_road_vector_input_list, bd_road_buff_list, sql_road_expression_list, path_time_log, basename_mnh, simplify_vector_param, format_vector, extension_vector, save_results_intermediate, overwrite)

        if debug >= 3:
            print(bold + green +  "\ncreateMnh() : " + endC + "File raster from BD road is create %s" %(raster_bd_road_mask) + endC)

        # CALCUL DU MNH

        # Calcul par bandMath du MNH definir l'expression qui soustrait le MNT au MNS en introduisant le biais et en mettant les valeurs à 0 à une valeur approcher de 0.0000001
        delta = ""
        if height_bias > 0 :
            delta = "+%s" %(str(height_bias))
        elif height_bias < 0 :
            delta = "-%s" %(str(abs(height_bias)))
        else :
            delta = ""

        # Definition de l'expression
        if bd_road_vector_input_list != [] :
            if image_threshold_input != "" :
                expression = "\"im3b1 > 0 and im4b1 > 0?%s:(im1b1-im2b1%s) > 0.0?im1b1-im2b1%s:%s\"" %(str(PRECISION), delta, delta, str(PRECISION))
                command = "otbcli_BandMath -il %s %s %s %s -out %s %s -exp %s" %(image_mns_clean, image_mnt_clean_sample, raster_bd_road_mask, image_threshold_mask, image_mnh_tmp, CODAGE_F, expression)
            else :
                expression = "\"im3b1 > 0?%s:(im1b1-im2b1%s) > 0.0?im1b1-im2b1%s:%s\"" %(str(PRECISION), delta, delta, str(PRECISION))
                command = "otbcli_BandMath -il %s %s %s -out %s %s -exp %s" %(image_mns_clean, image_mnt_clean_sample, raster_bd_road_mask, image_mnh_tmp, CODAGE_F, expression)
        else :
            expression = "\"(im1b1-im2b1%s) > 0.0?im1b1-im2b1%s:%s\"" %(delta, delta, str(PRECISION))
            command = "otbcli_BandMath -il %s %s -out %s %s -exp %s" %(image_mns_clean, image_mnt_clean_sample, image_mnh_tmp, CODAGE_F, expression)

        if ram_otb > 0:
            command += " -ram %d" %(ram_otb)

        if debug >= 3:
            print(cyan + "createMnh() : " + bold + green + "Calcul du MNH  %s difference du MNS : %s par le MNT :%s" %(image_mnh_tmp, image_mns_clean, image_mnt_clean_sample) + endC)
            print(command)

        exitCode = os.system(command)
        if exitCode != 0:
            print(command)
            raise NameError(cyan + "createMnh() : " + bold + red + "An error occured during otbcli_BandMath command to compute MNH " + image_mnh_tmp + ". See error message above." + endC)

        # DECOUPAGE DU MNH

        if bd_build_vector_input_list == []:
            image_mnh_road = image_mnh_output

        if debug >= 3:
            print(bold + green +  "createMnh() : " + endC + "Decoupage selon l'emprise du fichier mnh %s " %(image_mnh_tmp) + endC)

        # Fonction de découpe du mnh
        if not cutImageByVector(vector_emprise_input, image_mnh_tmp, image_mnh_road, None, None, no_data_value, epsg, format_raster, format_vector) :
            raise NameError (cyan + "createMnh() : " + bold + red + "!!! Une erreur c'est produite au cours du decoupage de l'image : " + image_mns_input + ". Voir message d'erreur." + endC)

        if debug >= 3:
            print(bold + green +  "createMnh() : " + endC + "Decoupage du fichier mnh %s complet" %(image_mnh_road) + endC)

        # INCRUSTATION DANS LE MNH DES DONNEES VECTEURS BATIS

        # Si demander => liste de fichier vecteur bati passé en donnée d'entrée
        if bd_build_vector_input_list != []:

            # Découpage des vecteurs de bd bati exogenes avec l'emprise
            vectors_build_cut_list = []
            for vector_build_input in bd_build_vector_input_list :
                vector_name = os.path.splitext(os.path.basename(vector_build_input))[0]
                vector_build_cut = sub_repertory_vector_temp + os.sep + vector_name + SUFFIX_CUT + extension_vector
                vectors_build_cut_list.append(vector_build_cut)
            cutoutVectors(vector_emprise_input, bd_build_vector_input_list, vectors_build_cut_list, format_vector)

            # Fusion des vecteurs batis découpés
            fusionVectors (vectors_build_cut_list, vector_bd_bati_temp)

            # Croisement vecteur rasteur entre le vecteur fusion des batis et le MNH créé precedement
            statisticsVectorRaster(image_mnh_road, vector_bd_bati_temp, "", 1, False, False, True, ['PREC_PLANI','PREC_ALTI','ORIGIN_BAT','median','sum','std','unique','range'], [], {}, path_time_log, True, format_vector, save_results_intermediate, overwrite)

            # Calcul de la colonne delta_H entre les hauteurs des batis et la hauteur moyenne du MNH sous le bati
            COLUMN_ID = "ID"
            COLUMN_H_BUILD = "HAUTEUR"
            COLUMN_H_BUILD_MIN = "Z_MIN"
            COLUMN_H_BUILD_MAX = "Z_MAX"
            COLUMN_H_MNH = "mean"
            COLUMN_H_MNH_MIN = "min"
            COLUMN_H_MNH_MAX = "max"
            COLUMN_H_DIFF = "H_diff"

            field_type = ogr.OFTReal
            field_value = 0.0
            field_width = 20
            field_precision = 2
            attribute_name_dico = {}
            attribute_name_dico[COLUMN_ID] = ogr.OFTString
            attribute_name_dico[COLUMN_H_BUILD] = ogr.OFTReal
            attribute_name_dico[COLUMN_H_MNH] = ogr.OFTReal

            # Ajouter la nouvelle colonne H_diff
            addNewFieldVector(vector_bd_bati_temp, COLUMN_H_DIFF, field_type, field_value, field_width, field_precision, format_vector)

            # Recuperer les valeur de hauteur du bati et du mnt dans le vecteur
            data_z_dico = getAttributeValues(vector_bd_bati_temp, None, None, attribute_name_dico, format_vector)

            # Calculer la difference des Hauteur bati et mnt
            field_new_values_dico = {}
            for index in range(len(data_z_dico[COLUMN_ID])) :
                index_polygon = data_z_dico[COLUMN_ID][index]
                delta_h = abs(data_z_dico[COLUMN_H_BUILD][index] - data_z_dico[COLUMN_H_MNH][index])
                field_new_values_dico[index_polygon] = {COLUMN_H_DIFF:delta_h}

            # Mettre à jour la colonne H_diff dans le vecteur
            setAttributeIndexValuesList(vector_bd_bati_temp, COLUMN_ID, field_new_values_dico, format_vector)

            # Suppression de tous les polygones bati dons la valeur du delat H est inferieur à threshold_delta_h
            column = "'%s, %s, %s, %s, %s, %s, %s, %s'"% (COLUMN_ID, COLUMN_H_BUILD, COLUMN_H_BUILD_MIN, COLUMN_H_BUILD_MAX, COLUMN_H_MNH, COLUMN_H_MNH_MIN, COLUMN_H_MNH_MAX, COLUMN_H_DIFF)
            expression = "%s > %s" % (COLUMN_H_DIFF, threshold_delta_h)
            filterSelectDataVector(vector_bd_bati_temp, vector_bd_bati, column, expression, overwrite, format_vector)

            # Attention!!!! PAUSE pour trie et verification des polygones bati nom deja present dans le MNH ou non
            if not automatic :
                print(bold + blue +  "Application MnhCreation => " + endC + "Vérification manuelle du vecteur bati %s pour ne concerver que les batis non présent dans le MNH courant %s" %(vector_bd_bati_temp, image_mnh_road) + endC)
                input(bold + red + "Appuyez sur entree pour continuer le programme..." + endC)

            # Creation du masque bati avec pour H la hauteur des batiments
            rasterizeVector(vector_bd_bati, raster_bd_bati, image_mnh_road, COLUMN_H_BUILD)

            # Fusion du mask des batis et du MNH temporaire
            expression = "\"im1b1 > 0.0?im1b1:im2b1\""
            command = "otbcli_BandMath -il %s %s -out %s %s -exp %s" %(raster_bd_bati, image_mnh_road, image_mnh_output, CODAGE_F, expression)

            if ram_otb > 0:
                command += " -ram %d" %(ram_otb)

            if debug >= 3:
                print(cyan + "createMnh() : " + bold + green + "Amelioration du MNH  %s ajout des hauteurs des batis %s" %(image_mnh_road, raster_bd_bati) + endC)
                print(command)

            exitCode = os.system(command)
            if exitCode != 0:
                print(command)
                raise NameError(cyan + "createMnh() : " + bold + red + "An error occured during otbcli_BandMath command to compute MNH Final" + image_mnh_output + ". See error message above." + endC)

    # SUPPRESIONS FICHIERS INTERMEDIAIRES INUTILES

    # Suppression des fichiers intermédiaires
    if not save_results_intermediate :
        if bd_build_vector_input_list != []:
            removeFile(image_mnh_road)
        removeFile(image_threshold_cut)
        removeFile(image_threshold_mask)
        removeFile(raster_bd_bati)
        removeVectorFile(vector_bd_road_temp)
        removeVectorFile(vector_bd_bati_temp)
        removeVectorFile(vector_bd_bati) # A confirmer!!!
        removeFile(raster_bd_road_mask)
        removeFile(image_mnh_tmp)
        deleteDir(sub_repertory_raster_temp)
        deleteDir(sub_repertory_vector_temp)

    print(endC)
    print(bold + green + "## END : MNH CREATION" + endC)
    print(endC)

    # Mise à jour du Log
    ending_event = "createMnh() : MNH creation ending : "
    timeLine(path_time_log,ending_event)

    return
Пример #4
0
def createDifference(image_ortho_input,
                     image_mns_input,
                     image_mnt_input,
                     bd_vector_input_list,
                     zone_buffer_dico,
                     departments_list,
                     image_difference_output,
                     vector_difference_output,
                     fileld_bd_raster,
                     simplifie_param,
                     threshold_ndvi,
                     threshold_difference,
                     filter_difference_0,
                     filter_difference_1,
                     path_time_log,
                     format_vector='ESRI Shapefile',
                     extension_raster=".tif",
                     extension_vector=".shp",
                     save_results_intermediate=False,
                     channel_order=['Red', 'Green', 'Blue', 'NIR'],
                     overwrite=True):

    # Mise à jour du Log
    starting_event = "createDifference() : create macro samples starting : "
    timeLine(path_time_log, starting_event)

    # constantes
    CODAGE = "float"

    FOLDER_MASK_TEMP = 'Mask_'
    FOLDER_CUTTING_TEMP = 'Cut_'
    FOLDER_BUFF_TEMP = 'Buff_'
    FOLDER_RESULT_TEMP = 'Tmp_'

    SUFFIX_MASK_CRUDE = '_mcrude'
    SUFFIX_MASK = '_mask'
    SUFFIX_FILTERED = '_filtered'
    SUFFIX_VECTOR_CUT = '_decoup'
    SUFFIX_VECTOR_BUFF = '_buff'
    SUFFIX_NEW_MNS = '_new_mns'
    SUFFIX_DIFF_MNS = '_diff_mns'
    SUFFIX_NDVI = '_ndvi'

    # print
    if debug >= 3:
        print(bold + green + "Variables dans la fonction" + endC)
        print(cyan + "createDifference() : " + endC + "image_ortho_input : " +
              str(image_ortho_input) + endC)
        print(cyan + "createDifference() : " + endC + "image_mns_input : " +
              str(image_mns_input) + endC)
        print(cyan + "createDifference() : " + endC + "image_mnt_input : " +
              str(image_mnt_input) + endC)
        print(cyan + "createDifference() : " + endC +
              "bd_vector_input_list : " + str(bd_vector_input_list) + endC)
        print(cyan + "createDifference() : " + endC + "zone_buffer_dico : " +
              str(zone_buffer_dico) + endC)
        print(cyan + "createDifference() : " + endC + "departments_list : " +
              str(departments_list) + endC)
        print(cyan + "createDifference() : " + endC +
              "image_difference_output : " + str(image_difference_output) +
              endC)
        print(cyan + "createDifference() : " + endC +
              "vector_difference_output : " + str(vector_difference_output) +
              endC)
        print(cyan + "createDifference() : " + endC + "fileld_bd_raster : " +
              str(fileld_bd_raster) + endC)
        print(cyan + "createDifference() : " + endC + "simplifie_param : " +
              str(simplifie_param) + endC)
        print(cyan + "createDifference() : " + endC + "threshold_ndvi : " +
              str(threshold_ndvi) + endC)
        print(cyan + "createDifference() : " + endC +
              "threshold_difference : " + str(threshold_difference) + endC)
        print(cyan + "createDifference() : " + endC +
              "filter_difference_0 : " + str(filter_difference_0) + endC)
        print(cyan + "createDifference() : " + endC +
              "filter_difference_1 : " + str(filter_difference_1) + endC)
        print(cyan + "createDifference() : " + endC + "path_time_log : " +
              str(path_time_log) + endC)
        print(cyan + "createDifference() : " + endC + "channel_order : " +
              str(channel_order) + endC)
        print(cyan + "createDifference() : " + endC + "format_vector : " +
              str(format_vector) + endC)
        print(cyan + "createDifference() : " + endC + "extension_raster : " +
              str(extension_raster) + endC)
        print(cyan + "createDifference() : " + endC + "extension_vector : " +
              str(extension_vector) + endC)
        print(cyan + "createDifference() : " + endC +
              "save_results_intermediate : " + str(save_results_intermediate) +
              endC)
        print(cyan + "createDifference() : " + endC + "overwrite : " +
              str(overwrite) + endC)

    # ETAPE 1 : NETTOYER LES DONNEES EXISTANTES

    print(cyan + "createDifference() : " + bold + green +
          "NETTOYAGE ESPACE DE TRAVAIL..." + endC)

    # Nom de base de l'image
    image_name = os.path.splitext(os.path.basename(image_ortho_input))[0]

    # Test si le fichier résultat différence existe déjà et si il doit être écrasés
    check = os.path.isfile(vector_difference_output)

    if check and not overwrite:  # Si le fichier difference existe deja et que overwrite n'est pas activé
        print(cyan + "createDifference() : " + bold + yellow +
              "File difference  " + vector_difference_output +
              " already exists and will not be created again." + endC)
    else:
        if check:
            try:
                removeFile(vector_difference_output)
            except Exception:
                pass  # si le fichier n'existe pas, il ne peut pas être supprimé : cette étape est ignorée

        # Définition des répertoires temporaires
        repertory_output = os.path.dirname(vector_difference_output)
        repertory_output_temp = repertory_output + os.sep + FOLDER_RESULT_TEMP + image_name
        repertory_mask_temp = repertory_output + os.sep + FOLDER_MASK_TEMP + image_name
        repertory_samples_cutting_temp = repertory_output + os.sep + FOLDER_CUTTING_TEMP + image_name
        repertory_samples_buff_temp = repertory_output + os.sep + FOLDER_BUFF_TEMP + image_name

        print(repertory_output_temp)
        print(repertory_mask_temp)
        print(repertory_samples_cutting_temp)
        print(repertory_samples_buff_temp)

        # Création des répertoires temporaire qui n'existent pas
        if not os.path.isdir(repertory_output_temp):
            os.makedirs(repertory_output_temp)
        if not os.path.isdir(repertory_mask_temp):
            os.makedirs(repertory_mask_temp)
        if not os.path.isdir(repertory_samples_cutting_temp):
            os.makedirs(repertory_samples_cutting_temp)
        if not os.path.isdir(repertory_samples_buff_temp):
            os.makedirs(repertory_samples_buff_temp)

        # Nettoyage des répertoires temporaire qui ne sont pas vide
        cleanTempData(repertory_mask_temp)
        cleanTempData(repertory_samples_cutting_temp)
        cleanTempData(repertory_samples_buff_temp)
        cleanTempData(repertory_output_temp)

        BD_topo_layers_list = []
        #zone = zone_buffer_dico.keys()[0]
        zone = list(zone_buffer_dico)[0]
        # Creation liste des couches des bd exogenes utilisées
        for layers_buffer in zone_buffer_dico[zone]:
            BD_topo_layers_list.append(layers_buffer[0])

        print(cyan + "createDifference() : " + bold + green +
              "... FIN NETTOYAGE" + endC)

        # ETAPE 2 : DECOUPER LES VECTEURS

        print(cyan + "createDifference() : " + bold + green +
              "DECOUPAGE ECHANTILLONS..." + endC)

        # 2.1 : Création du masque délimitant l'emprise de la zone par image
        vector_mask = repertory_mask_temp + os.sep + image_name + SUFFIX_MASK_CRUDE + extension_vector
        createVectorMask(image_ortho_input, vector_mask)

        # 2.2 : Simplification du masque
        vector_simple_mask = repertory_mask_temp + os.sep + image_name + SUFFIX_MASK + extension_vector
        simplifyVector(vector_mask, vector_simple_mask, simplifie_param,
                       format_vector)

        # 2.3 : Découpage des vecteurs copiés en local avec le masque
        vector_output_list = []
        for vector_input in bd_vector_input_list:
            vector_name = os.path.splitext(os.path.basename(vector_input))[0]
            extension = os.path.splitext(os.path.basename(vector_input))[1]
            vector_output = repertory_samples_cutting_temp + os.sep + vector_name + SUFFIX_VECTOR_CUT + extension
            vector_output_list.append(vector_output)
        cutoutVectors(vector_simple_mask, bd_vector_input_list,
                      vector_output_list, format_vector)

        print(cyan + "createDifference() : " + bold + green +
              "...FIN DECOUPAGE" + endC)

        # ETAPE 3 : BUFFERISER LES VECTEURS

        print(cyan + "createDifference() : " + bold + green +
              "MISE EN PLACE DES TAMPONS..." + endC)

        # Parcours du dictionnaire associant la zone aux noms de fichiers et aux tampons associés
        for elem_buff in zone_buffer_dico[zone]:
            # Parcours des départements
            for dpt in departments_list:

                input_shape = repertory_samples_cutting_temp + os.sep + elem_buff[
                    0] + "_" + dpt + SUFFIX_VECTOR_CUT + extension_vector
                output_shape = repertory_samples_buff_temp + os.sep + elem_buff[
                    0] + "_" + dpt + SUFFIX_VECTOR_BUFF + extension_vector
                buff = elem_buff[1]
                if os.path.isfile(input_shape):
                    if debug >= 3:
                        print(cyan + "createDifference() : " + endC +
                              "input_shape : " + str(input_shape) + endC)
                        print(cyan + "createDifference() : " + endC +
                              "output_shape : " + str(output_shape) + endC)
                        print(cyan + "createDifference() : " + endC +
                              "buff : " + str(buff) + endC)
                    bufferVector(input_shape, output_shape, buff, "", 1.0, 10,
                                 format_vector)
                else:
                    print(cyan + "createDifference() : " + bold + yellow +
                          "Pas de fichier du nom : " + endC + input_shape)

        print(cyan + "createDifference() : " + bold + green +
              "FIN DE L AFFECTATION DES TAMPONS" + endC)

        # ETAPE 4 : FUSION DES SHAPES DE LA BD TOPO

        print(cyan + "createDifference() : " + bold + green +
              "FUSION DATA BD..." + endC)

        shape_buff_list = []
        # Parcours du dictionnaire associant la zone au nom du fichier
        for elem_buff in zone_buffer_dico[zone]:
            # Parcours des départements
            for dpt in departments_list:
                shape_file = repertory_samples_buff_temp + os.sep + elem_buff[
                    0] + "_" + dpt + SUFFIX_VECTOR_BUFF + extension_vector

                if os.path.isfile(shape_file):
                    shape_buff_list.append(shape_file)
                    print("file for fusion : " + shape_file)
                else:
                    print(bold + yellow + "pas de fichiers avec ce nom : " +
                          endC + shape_file)

            # si une liste de fichier shape existe
            if not shape_buff_list:
                print(bold + yellow + "Pas de fusion sans donnee a fusionnee" +
                      endC)
            else:
                # Fusion des fichiers shape
                image_zone_shape = repertory_output_temp + os.sep + image_name + '_' + zone + extension_vector
                fusionVectors(shape_buff_list, image_zone_shape)

        print("File BD : " + image_zone_shape)
        print(cyan + "createDifference() : " + bold + green +
              "FIN DE LA FUSION" + endC)

    # ETAPE 5 : RASTERISER LE FICHIER SHAPE DE ZONE BD
    print(cyan + "createDifference() : " + bold + green +
          "RASTERIZATION DE LA FUSION..." + endC)
    image_zone_raster = repertory_output_temp + os.sep + image_name + '_' + zone + extension_raster
    rasterizeVector(image_zone_shape,
                    image_zone_raster,
                    image_ortho_input,
                    fileld_bd_raster,
                    codage=CODAGE)
    print(cyan + "createDifference() : " + bold + green +
          "FIN DE LA RASTERIZATION" + endC)

    # ETAPE 6 : CREER UN NOUVEAU MMS ISSU DU MNT + DATA BD_TOPO
    print(cyan + "createDifference() : " + bold + green +
          "CREATION NOUVEAU MNS..." + endC)
    image_new_mns_output = repertory_output_temp + os.sep + image_name + SUFFIX_NEW_MNS + extension_raster
    createMNS(image_ortho_input, image_mnt_input, image_zone_raster,
              image_new_mns_output)
    print(cyan + "createDifference() : " + bold + green +
          "FIN DE LA CREATION MNS" + endC)

    # ETAPE 7 : CREER D'UN MASQUE SUR LES ZONES VEGETALES
    print(cyan + "createDifference() : " + bold + green +
          "CREATION DU NDVI..." + endC)
    image_ndvi_output = repertory_output_temp + os.sep + image_name + SUFFIX_NDVI + extension_raster
    createNDVI(image_ortho_input, image_ndvi_output, channel_order)
    print(cyan + "createDifference() : " + bold + green +
          "FIN DE LA CREATION DU NDVI" + endC)

    print(cyan + "createDifference() : " + bold + green +
          "CREATION DU MASQUE NDVI..." + endC)
    image_ndvi_mask_output = repertory_output_temp + os.sep + image_name + SUFFIX_NDVI + SUFFIX_MASK + extension_raster
    createBinaryMask(image_ndvi_output, image_ndvi_mask_output, threshold_ndvi,
                     False)
    print(cyan + "createDifference() : " + bold + green +
          "FIN DE LA CREATION DU MASQUE NDVI" + endC)

    # ETAPE 8 : CREER UN FICHIER DE DIFFERENCE DES MNS AVEC MASQUAGE DES ZONES VEGETALES
    print(cyan + "createDifference() : " + bold + green +
          "CREATION DIFFERENCE MNS..." + endC)
    #image_diff_mns_output = repertory_output + os.sep + image_name + SUFFIX_DIFF_MNS + extension_raster
    image_diff_mns_output = image_difference_output
    createDifferenceFile(image_mns_input, image_new_mns_output,
                         image_ndvi_mask_output, image_diff_mns_output)
    print(cyan + "createDifference() : " + bold + green +
          "FIN DE LA CREATION DE LA DIFFERENCE MNS" + endC)

    print(cyan + "createDifference() : " + bold + green +
          "CREATION DU MASQUE DE DIFFERENCE..." + endC)
    image_diff_mns_mask_output = repertory_output_temp + os.sep + image_name + SUFFIX_DIFF_MNS + SUFFIX_MASK + extension_raster
    createBinaryMask(image_diff_mns_output, image_diff_mns_mask_output,
                     threshold_difference, True)
    print(cyan + "createDifference() : " + bold + green +
          "FIN DE LA CREATION DU MASQUE DE DIFFERENCE" + endC)

    print(cyan + "createDifference() : " + bold + green +
          "FILTRAGE DU MASQUE DE DIFFERENCE..." + endC)
    image_diff_mns_filtered_output = repertory_output_temp + os.sep + image_name + SUFFIX_DIFF_MNS + SUFFIX_FILTERED + extension_raster
    filterBinaryRaster(image_diff_mns_mask_output,
                       image_diff_mns_filtered_output, filter_difference_0,
                       filter_difference_1)
    print(cyan + "createDifference() : " + bold + green +
          "FIN DU FILTRAGE DU MASQUE DE DIFFERENCE" + endC)

    # ETAPE 9 : RASTERISER LE FICHIER DE DIFFERENCE DES MNS
    print(cyan + "createDifference() : " + bold + green +
          "VECTORISATION DU RASTER DE DIFFERENCE..." + endC)
    vector_diff_mns_filtered_output = repertory_output_temp + os.sep + image_name + SUFFIX_DIFF_MNS + SUFFIX_FILTERED + extension_vector
    polygonizeRaster(image_diff_mns_filtered_output,
                     vector_diff_mns_filtered_output,
                     image_name,
                     field_name="DN")
    print(cyan + "createDifference() : " + bold + green +
          "FIN DE VECTORISATION DU RASTER DE DIFFERENCE" + endC)

    print(cyan + "createDifference() : " + bold + green +
          "SIMPLIFICATION VECTEUR DE DIFFERENCE..." + endC)
    simplifyVector(vector_diff_mns_filtered_output, vector_difference_output,
                   simplifie_param, format_vector)
    print(cyan + "createDifference() : " + bold + green +
          "FIN DE SIMPLIFICATION DI VECTEUR DE DIFFERENCE" + endC)

    # ETAPE 10 : SUPPRESIONS FICHIERS INTERMEDIAIRES INUTILES
    if not save_results_intermediate:

        # Supression des .geom dans le dossier
        for to_delete in glob.glob(repertory_mask_temp + os.sep + "*.geom"):
            removeFile(to_delete)

        # Suppression des repertoires temporaires
        deleteDir(repertory_mask_temp)
        deleteDir(repertory_samples_cutting_temp)
        deleteDir(repertory_samples_buff_temp)
        deleteDir(repertory_output_temp)

    # Mise à jour du Log
    ending_event = "createDifference() : create macro samples ending : "
    timeLine(path_time_log, ending_event)

    return
def main(gui=False):

    # Définition des différents paramètres du parser
    parser = argparse.ArgumentParser(
        formatter_class=argparse.RawTextHelpFormatter,
        prog="VectorRasterCutting",
        description="\
    Info : Cutting list of raster and vector file by vector file. \n\
    Objectif : Découper des fichiers raster et vecteurs. \n\
    Example : python VectorRasterCutting.py -il /mnt/Data/gilles.fouvet/RA/Haute-Savoie_SansTunnel/haute_savoie_usage_sans_tunnels.tif \n\
                                                /mnt/Data/gilles.fouvet/RA/Haute-Savoie_500m/Global/Resultats/Raster/Haute_Savoie_Couverture_Apres_PT_Directs_et_Indirects.tif \n\
                                                /mnt/Data/gilles.fouvet/RA/Haute-Savoie_200m/Global/Resultats/Raster/Haute_Savoie_Couverture_Apres_PT_Directs_et_Indirects_200m2.tif \n\
                                                /mnt/Data/gilles.fouvet/RA/Haute-Savoie_500m/Global/Resultats/Raster/Haute-Savoie_Couverture_Apres_PT_Directs_et_Indirects_500m2.tif  \n\
                                            -vl /mnt/Data/gilles.fouvet/RA/Haute-Savoie_500m/Global/Resultats/Vecteur/Sauvegarde_500m2/Haute-Savoie_Couverture_Apres_PT_Directs_et_Indirects_clnd_500m2.shp \n\
                                                /mnt/Data/gilles.fouvet/RA/Haute-Savoie_200m/Global/Resultats/Vecteur/Sauvegarde_200m2/Haute-Savoie_Couverture_Apres_PT_Directs_et_Indirects_clnd_200m2.shp \n\
                                            -c  /mnt/Data/gilles.fouvet/RA/Haute-Savoie/Global/Preparation/Study_Boundaries/DEP74.SHP \n\
                                            -iol /mnt/Data/gilles.fouvet/RA/Haute-Savoie_SansTunnel/haute_savoie_usage_sans_tunnels.tif \n\
                                                /mnt/Data/gilles.fouvet/RA/Haute-Savoie_500m/Global/Resultats/Raster/Haute_Savoie_Couverture_Apres_PT_Directs_et_Indirects_cut.tif \n\
                                                /mnt/Data/gilles.fouvet/RA/Haute-Savoie_200m/Global/Resultats/Raster/Haute_Savoie_Couverture_Apres_PT_Directs_et_Indirects_200m2_cut.tif \n\
                                                /mnt/Data/gilles.fouvet/RA/Haute-Savoie_500m/Global/Resultats/Raster/Haute-Savoie_Couverture_Apres_PT_Directs_et_Indirects_500m2_cut.tif  \n\
                                            -vol /mnt/Data/gilles.fouvet/RA/Haute-Savoie_500m/Global/Resultats/Vecteur/Sauvegarde_500m2/Haute-Savoie_Couverture_Apres_PT_Directs_et_Indirects_clnd_500m2_cut.shp \n\
                                                /mnt/Data/gilles.fouvet/RA/Haute-Savoie_200m/Global/Resultats/Vecteur/Sauvegarde_200m2/Haute-Savoie_Couverture_Apres_PT_Directs_et_Indirects_clnd_200m2_cut.shp \n\
                                            -b 10.0 \n\
                                            -r 5.0 \n\
                                            -epsg 2154 \n\
                                            -ndv 65535 \n\
                                            -z \n\
                                            -log /mnt/Data/gilles.fouvet/RA/Haute-Savoie_SansTunnel/FichierHaute-Savoie.log"
    )

    parser.add_argument('-il',
                        '--images_input_list',
                        default="",
                        nargs="+",
                        help="List input images to cut",
                        type=str,
                        required=False)
    parser.add_argument('-vl',
                        '--vectors_input_list',
                        default="",
                        nargs="+",
                        help="List input vectors to cut.",
                        type=str,
                        required=False)
    parser.add_argument(
        '-c',
        '--vector_cut',
        default="",
        help="Vector input contain the vector to cut images and vectors input.",
        type=str,
        required=True)
    parser.add_argument('-iol',
                        '--images_output_list',
                        default="",
                        nargs="+",
                        help="List output images cut",
                        type=str,
                        required=False)
    parser.add_argument('-vol',
                        '--vectors_output_list',
                        default="",
                        nargs="+",
                        help="List output vectors to cut.",
                        type=str,
                        required=False)
    parser.add_argument(
        '-b',
        '--buffer_size',
        default=0,
        help="Option : Value of positive buffer in metrer , default : 0 ",
        type=float,
        required=False)
    parser.add_argument(
        '-r',
        '--round_pixel_size',
        default=0,
        help=
        "Option : Value of around to dunnage if at 0 the value is read size pixel image (in metre), default : 0 ",
        type=float,
        required=False)
    parser.add_argument(
        "-epsg",
        '--epsg',
        default=0,
        help=
        "Option : Projection parameter of data if 0 used projection of raster file",
        type=int,
        required=False)
    parser.add_argument(
        "-ndv",
        '--no_data_value',
        default=0,
        help="Option pixel value for raster file to no data, default : 0 ",
        type=int,
        required=False)
    parser.add_argument(
        '-rm',
        '--resampling_methode',
        default="",
        help=
        "Option : Define the algo methode uses to resampling. By default : if empty (by default) not used.",
        type=str,
        required=False)
    parser.add_argument(
        '-z',
        '--z_compress',
        action='store_true',
        default=False,
        help=
        "Option : The rasters images cutting and compress are produced, default : False",
        required=False)
    parser.add_argument(
        '-raf',
        '--format_raster',
        default="GTiff",
        help="Option : Format output image, by default : GTiff (GTiff, HFA...)",
        type=str,
        required=False)
    parser.add_argument('-vef',
                        '--format_vector',
                        default="ESRI Shapefile",
                        help="Format of the output file.",
                        type=str,
                        required=False)
    parser.add_argument(
        '-rae',
        '--extension_raster',
        default=".tif",
        help="Option : Extension file for image raster. By default : '.tif'",
        type=str,
        required=False)
    parser.add_argument(
        '-vee',
        '--extension_vector',
        default=".shp",
        help="Option : Extension file for vector. By default : '.shp'",
        type=str,
        required=False)
    parser.add_argument('-log',
                        '--path_time_log',
                        default="",
                        help="Name of log",
                        type=str,
                        required=False)
    parser.add_argument(
        '-sav',
        '--save_results_inter',
        action='store_true',
        default=False,
        help=
        "Save or delete intermediate result after the process. By default, False",
        required=False)
    parser.add_argument(
        '-now',
        '--overwrite',
        action='store_false',
        default=True,
        help="Overwrite files with same names. By default, True",
        required=False)
    parser.add_argument(
        '-debug',
        '--debug',
        default=3,
        help="Option : Value of level debug trace, default : 3 ",
        type=int,
        required=False)
    args = displayIHM(gui, parser)

    # RECUPERATION DES ARGUMENTS

    # Récupération des l'images d'entrées
    if args.images_input_list != None:
        images_input_list = args.images_input_list
        for image_input in images_input_list:
            if image_input != "" and not os.path.isfile(image_input):
                raise NameError(cyan + "VectorRasterCutting : " + bold + red +
                                "File %s not existe!" % (image_input) + endC)

    # Récupération des vecteurs d'entrées
    if args.vectors_input_list != None:
        vectors_input_list = args.vectors_input_list
        for vector_input in vectors_input_list:
            if vector_input != "" and not os.path.isfile(vector_input):
                raise NameError(cyan + "VectorRasterCutting : " + bold + red +
                                "File %s not existe!" % (vector_input) + endC)

    # Récupération du vecteur de découpe
    if args.vector_cut != None:
        vector_cut = args.vector_cut
        if not os.path.isfile(vector_cut):
            raise NameError(cyan + "VectorRasterCutting : " + bold + red +
                            "File %s not existe!" % (vector_cut) + endC)

    # Récupération des l'images de sorties
    if args.images_output_list != None:
        images_output_list = args.images_output_list

    # Récupération des vecteurs de sorties
    if args.vectors_output_list != None:
        vectors_output_list = args.vectors_output_list

    # Parametre du buffer
    if args.buffer_size != None:
        buffer_size = args.buffer_size

    # Parametre de l'arrondi
    if args.round_pixel_size != None:
        round_pixel_size = args.round_pixel_size

    # Paramettre de projection
    if args.epsg != None:
        epsg = args.epsg

    # Paramettre des no data
    if args.no_data_value != None:
        no_data_value = args.no_data_value

    # Paramètres definition de la metode de resampling
    if args.resampling_methode != None:
        resampling_methode = args.resampling_methode

    # option de compression
    if args.z_compress != None:
        z_compress = args.z_compress

    # Paramètre format des images de sortie
    if args.format_raster != None:
        format_raster = args.format_raster

    # Récupération du format du fichier de sortie
    if args.format_vector != None:
        format_vector = args.format_vector

    # Paramètre de l'extension des images rasters
    if args.extension_raster != None:
        extension_raster = args.extension_raster

    # Récupération de l'extension des fichiers vecteurs
    if args.extension_vector != None:
        extension_vector = args.extension_vector

    # Récupération du nom du fichier log
    if args.path_time_log != None:
        path_time_log = args.path_time_log

    # Récupération de l'option de sauvegarde des fichiers temporaires
    if args.save_results_inter != None:
        save_results_intermediate = args.save_results_inter

    # Récupération de l'option écrasement
    if args.overwrite != None:
        overwrite = args.overwrite

    # Récupération de l'option niveau de debug
    if args.debug != None:
        global debug
        debug = args.debug

    if debug >= 3:
        print(bold + green + "VectorRasterCutting : Variables dans le parser" +
              endC)
        print(cyan + "VectorRasterCutting : " + endC + "images_input_list : " +
              str(images_input_list) + endC)
        print(cyan + "VectorRasterCutting : " + endC +
              "vectors_input_list : " + str(vectors_input_list) + endC)
        print(cyan + "VectorRasterCutting : " + endC + "vector_cut : " +
              str(vector_cut) + endC)
        print(cyan + "VectorRasterCutting : " + endC +
              "images_output_list : " + str(images_output_list) + endC)
        print(cyan + "VectorRasterCutting : " + endC +
              "vectors_output_list : " + str(vectors_output_list) + endC)
        print(cyan + "VectorRasterCutting : " + endC + "round_pixel_size : " +
              str(round_pixel_size) + endC)
        print(cyan + "VectorRasterCutting : " + endC + "buffer_size : " +
              str(buffer_size) + endC)
        print(cyan + "VectorRasterCutting : " + endC + "epsg : " + str(epsg) +
              endC)
        print(cyan + "VectorRasterCutting : " + endC + "no_data_value : " +
              str(no_data_value) + endC)
        print(cyan + "VectorRasterCutting : " + endC +
              "resampling_methode : " + str(resampling_methode) + endC)
        print(cyan + "VectorRasterCutting : " + endC + "z_compress : " +
              str(z_compress) + endC)
        print(cyan + "VectorRasterCutting : " + endC + "format_raster : " +
              str(format_raster) + endC)
        print(cyan + "VectorRasterCutting : " + endC + "format_vector : " +
              str(format_vector) + endC)
        print(cyan + "VectorRasterCutting : " + endC + "extension_raster : " +
              str(extension_raster) + endC)
        print(cyan + "VectorRasterCutting : " + endC + "extension_vector : " +
              str(extension_vector) + endC)
        print(cyan + "VectorRasterCutting : " + endC + "path_time_log : " +
              str(path_time_log) + endC)
        print(cyan + "VectorRasterCutting : " + endC +
              "save_results_inter : " + str(save_results_intermediate) + endC)
        print(cyan + "VectorRasterCutting : " + endC + "overwrite : " +
              str(overwrite) + endC)
        print(cyan + "VectorRasterCutting : " + endC + "debug : " +
              str(debug) + endC)

    # EXECUTION DE LA FONCTION
    # Si les dossiers de sorties n'existent pas, on les crées
    for image_output in images_output_list:
        if not os.path.isdir(os.path.dirname(image_output)):
            os.makedirs(os.path.dirname(image_output))

    for vector_output in vectors_output_list:
        if not os.path.isdir(os.path.dirname(vector_output)):
            os.makedirs(os.path.dirname(vector_output))

    # Execution de la fonction de decoupe pour une liste d'image raster
    if len(images_input_list) > 0:
        cutRasterImages(images_input_list, vector_cut, images_output_list,
                        buffer_size, round_pixel_size, epsg, no_data_value,
                        resampling_methode, z_compress, path_time_log,
                        format_raster, format_vector, extension_raster,
                        extension_vector, save_results_intermediate, overwrite)

    # Execution de la fonction de decoupe pour une liste de vecteur
    if len(vectors_input_list) > 0:
        # Pour tous les fichiers vecteurs à découpper
        cutoutVectors(vector_cut, vectors_input_list, vectors_output_list,
                      overwrite, format_vector)
def createMacroSamples(image_input, vector_to_cut_input, vector_sample_output, raster_sample_output, bd_vector_input_list, bd_buff_list, sql_expression_list, path_time_log, macro_sample_name="", simplify_vector_param=10.0, format_vector='ESRI Shapefile', extension_vector=".shp", save_results_intermediate=False, overwrite=True) :

    # Mise à jour du Log
    starting_event = "createMacroSamples() : create macro samples starting : "
    timeLine(path_time_log,starting_event)

    if debug >= 3:
        print(bold + green + "createMacroSamples() : Variables dans la fonction" + endC)
        print(cyan + "createMacroSamples() : " + endC + "image_input : " + str(image_input) + endC)
        print(cyan + "createMacroSamples() : " + endC + "vector_to_cut_input : " + str(vector_to_cut_input) + endC)
        print(cyan + "createMacroSamples() : " + endC + "vector_sample_output : " + str(vector_sample_output) + endC)
        print(cyan + "createMacroSamples() : " + endC + "raster_sample_output : " + str(raster_sample_output) + endC)
        print(cyan + "createMacroSamples() : " + endC + "bd_vector_input_list : " + str(bd_vector_input_list) + endC)
        print(cyan + "createMacroSamples() : " + endC + "bd_buff_list : " + str(bd_buff_list) + endC)
        print(cyan + "createMacroSamples() : " + endC + "sql_expression_list : " + str(sql_expression_list) + endC)
        print(cyan + "createMacroSamples() : " + endC + "path_time_log : " + str(path_time_log) + endC)
        print(cyan + "createMacroSamples() : " + endC + "macro_sample_name : " + str(macro_sample_name) + endC)
        print(cyan + "createMacroSamples() : " + endC + "simplify_vector_param : " + str(simplify_vector_param) + endC)
        print(cyan + "createMacroSamples() : " + endC + "format_vector : " + str(format_vector))
        print(cyan + "createMacroSamples() : " + endC + "extension_vector : " + str(extension_vector) + endC)
        print(cyan + "createMacroSamples() : " + endC + "save_results_intermediate : " + str(save_results_intermediate) + endC)
        print(cyan + "createMacroSamples() : " + endC + "overwrite : " + str(overwrite) + endC)

    # Constantes
    FOLDER_MASK_TEMP = "Mask_"
    FOLDER_CUTTING_TEMP = "Cut_"
    FOLDER_FILTERING_TEMP = "Filter_"
    FOLDER_BUFF_TEMP = "Buff_"

    SUFFIX_MASK_CRUDE = "_crude"
    SUFFIX_MASK = "_mask"
    SUFFIX_VECTOR_CUT = "_cut"
    SUFFIX_VECTOR_FILTER = "_filt"
    SUFFIX_VECTOR_BUFF = "_buff"

    CODAGE = "uint8"

    # ETAPE 1 : NETTOYER LES DONNEES EXISTANTES

    print(cyan + "createMacroSamples() : " + bold + green + "Nettoyage de l'espace de travail..." + endC)

    # Nom du repertoire de calcul
    repertory_macrosamples_output = os.path.dirname(vector_sample_output)

    # Test si le vecteur echantillon existe déjà et si il doit être écrasés
    check = os.path.isfile(vector_sample_output) or os.path.isfile(raster_sample_output)

    if check and not overwrite: # Si les fichiers echantillons existent deja et que overwrite n'est pas activé
        print(bold + yellow + "File sample : " + vector_sample_output + " already exists and will not be created again." + endC)
    else :
        if check:
            try:
                removeVectorFile(vector_sample_output)
                removeFile(raster_sample_output)
            except Exception:
                pass # si le fichier n'existe pas, il ne peut pas être supprimé : cette étape est ignorée

        # Définition des répertoires temporaires
        repertory_mask_temp = repertory_macrosamples_output + os.sep + FOLDER_MASK_TEMP + macro_sample_name
        repertory_samples_cutting_temp = repertory_macrosamples_output + os.sep + FOLDER_CUTTING_TEMP + macro_sample_name
        repertory_samples_filtering_temp = repertory_macrosamples_output + os.sep + FOLDER_FILTERING_TEMP + macro_sample_name
        repertory_samples_buff_temp = repertory_macrosamples_output + os.sep + FOLDER_BUFF_TEMP + macro_sample_name

        if debug >= 4:
            print(cyan + "createMacroSamples() : " + endC + "Création du répertoire : " + str(repertory_mask_temp))
            print(cyan + "createMacroSamples() : " + endC + "Création du répertoire : " + str(repertory_samples_cutting_temp))
            print(cyan + "createMacroSamples() : " + endC + "Création du répertoire : " + str(repertory_samples_buff_temp))

        # Création des répertoires temporaire qui n'existent pas
        if not os.path.isdir(repertory_macrosamples_output):
            os.makedirs(repertory_macrosamples_output)
        if not os.path.isdir(repertory_mask_temp):
            os.makedirs(repertory_mask_temp)
        if not os.path.isdir(repertory_samples_cutting_temp):
            os.makedirs(repertory_samples_cutting_temp)
        if not os.path.isdir(repertory_samples_filtering_temp):
            os.makedirs(repertory_samples_filtering_temp)
        if not os.path.isdir(repertory_samples_buff_temp):
            os.makedirs(repertory_samples_buff_temp)

        # Nettoyage des répertoires temporaire qui ne sont pas vide
        cleanTempData(repertory_mask_temp)
        cleanTempData(repertory_samples_cutting_temp)
        cleanTempData(repertory_samples_filtering_temp)
        cleanTempData(repertory_samples_buff_temp)

        print(cyan + "createMacroSamples() : " + bold + green + "... fin du nettoyage" + endC)

        # ETAPE 2 : DECOUPAGE DES VECTEURS

        print(cyan + "createMacroSamples() : " + bold + green + "Decoupage des echantillons ..." + endC)

        if vector_to_cut_input == None :
            # 2.1 : Création du masque délimitant l'emprise de la zone par image
            image_name = os.path.splitext(os.path.basename(image_input))[0]
            vector_mask = repertory_mask_temp + os.sep + image_name + SUFFIX_MASK_CRUDE + extension_vector
            createVectorMask(image_input, vector_mask)

            # 2.2 : Simplification du masque
            vector_simple_mask = repertory_mask_temp + os.sep + image_name + SUFFIX_MASK + extension_vector
            simplifyVector(vector_mask, vector_simple_mask, simplify_vector_param, format_vector)
        else :
            vector_simple_mask = vector_to_cut_input

        # 2.3 : Découpage des vecteurs de bd exogenes avec le masque
        vectors_cut_list = []
        for vector_input in bd_vector_input_list :
            vector_name = os.path.splitext(os.path.basename(vector_input))[0]
            vector_cut = repertory_samples_cutting_temp + os.sep + vector_name + SUFFIX_VECTOR_CUT + extension_vector
            vectors_cut_list.append(vector_cut)
        cutoutVectors(vector_simple_mask, bd_vector_input_list, vectors_cut_list, format_vector)

        print(cyan + "createMacroSamples() : " + bold + green + "... fin du decoupage" + endC)

        # ETAPE 3 : FILTRAGE DES VECTEURS

        print(cyan + "createMacroSamples() : " + bold + green + "Filtrage des echantillons ..." + endC)

        vectors_filtered_list = []
        if sql_expression_list != [] :
            for idx_vector in range (len(bd_vector_input_list)):
                vector_name = os.path.splitext(os.path.basename(bd_vector_input_list[idx_vector]))[0]
                vector_cut = vectors_cut_list[idx_vector]
                if idx_vector < len(sql_expression_list) :
                    sql_expression = sql_expression_list[idx_vector]
                else :
                    sql_expression = ""
                vector_filtered = repertory_samples_filtering_temp + os.sep + vector_name + SUFFIX_VECTOR_FILTER + extension_vector
                vectors_filtered_list.append(vector_filtered)

                # Filtrage par ogr2ogr
                if sql_expression != "":
                    names_attribut_list = getAttributeNameList(vector_cut, format_vector)
                    column = "'"
                    for name_attribut in names_attribut_list :
                        column += name_attribut + ", "
                    column = column[0:len(column)-2]
                    column += "'"
                    ret = filterSelectDataVector(vector_cut, vector_filtered, column, sql_expression, format_vector)
                    if not ret :
                        print(cyan + "createMacroSamples() : " + bold + yellow + "Attention problème lors du filtrage des BD vecteurs l'expression SQL %s est incorrecte" %(sql_expression) + endC)
                        copyVectorFile(vector_cut, vector_filtered)
                else :
                    print(cyan + "createMacroSamples() : " + bold + yellow + "Pas de filtrage sur le fichier du nom : " + endC + vector_filtered)
                    copyVectorFile(vector_cut, vector_filtered)

        else :
            print(cyan + "createMacroSamples() : " + bold + yellow + "Pas de filtrage demandé" + endC)
            for idx_vector in range (len(bd_vector_input_list)):
                vector_cut = vectors_cut_list[idx_vector]
                vectors_filtered_list.append(vector_cut)

        print(cyan + "createMacroSamples() : " + bold + green + "... fin du filtrage" + endC)

        # ETAPE 4 : BUFFERISATION DES VECTEURS

        print(cyan + "createMacroSamples() : " + bold + green + "Mise en place des tampons..." + endC)

        vectors_buffered_list = []
        if bd_buff_list != [] :
            # Parcours des vecteurs d'entrée
            for idx_vector in range (len(bd_vector_input_list)):
                vector_name = os.path.splitext(os.path.basename(bd_vector_input_list[idx_vector]))[0]
                buff = bd_buff_list[idx_vector]
                vector_filtered = vectors_filtered_list[idx_vector]
                vector_buffered = repertory_samples_buff_temp + os.sep + vector_name + SUFFIX_VECTOR_BUFF + extension_vector

                if buff != 0:
                    if os.path.isfile(vector_filtered):
                        if debug >= 3:
                            print(cyan + "createMacroSamples() : " + endC + "vector_filtered : " + str(vector_filtered) + endC)
                            print(cyan + "createMacroSamples() : " + endC + "vector_buffered : " + str(vector_buffered) + endC)
                            print(cyan + "createMacroSamples() : " + endC + "buff : " + str(buff) + endC)
                        bufferVector(vector_filtered, vector_buffered, buff, "", 1.0, 10, format_vector)
                    else :
                        print(cyan + "createMacroSamples() : " + bold + yellow + "Pas de fichier du nom : " + endC + vector_filtered)

                else :
                    print(cyan + "createMacroSamples() : " + bold + yellow + "Pas de tampon sur le fichier du nom : " + endC + vector_filtered)
                    copyVectorFile(vector_filtered, vector_buffered)

                vectors_buffered_list.append(vector_buffered)

        else :
            print(cyan + "createMacroSamples() : " + bold + yellow + "Pas de tampon demandé" + endC)
            for idx_vector in range (len(bd_vector_input_list)):
                vector_filtered = vectors_filtered_list[idx_vector]
                vectors_buffered_list.append(vector_filtered)

        print(cyan + "createMacroSamples() : " + bold + green + "... fin de la mise en place des tampons" + endC)

        # ETAPE 5 : FUSION DES SHAPES

        print(cyan + "createMacroSamples() : " + bold + green + "Fusion par macroclasse ..." + endC)

        # si une liste de fichier shape à fusionner existe
        if not vectors_buffered_list:
            print(cyan + "createMacroSamples() : " + bold + yellow + "Pas de fusion sans donnee à fusionner" + endC)
        # s'il n'y a qu'un fichier shape en entrée
        elif len(vectors_buffered_list) == 1:
            print(cyan + "createMacroSamples() : " + bold + yellow + "Pas de fusion pour une seule donnee à fusionner" + endC)
            copyVectorFile(vectors_buffered_list[0], vector_sample_output)
        else :
            # Fusion des fichiers shape
            vectors_buffered_controled_list = []
            for vector_buffered in vectors_buffered_list :
                if os.path.isfile(vector_buffered) and (getGeometryType(vector_buffered, format_vector) in ('POLYGON', 'MULTIPOLYGON')) and (getNumberFeature(vector_buffered, format_vector) > 0):
                    vectors_buffered_controled_list.append(vector_buffered)
                else :
                    print(cyan + "createMacroSamples() : " + bold + red + "Attention fichier bufferisé est vide il ne sera pas fusionné : " + endC + vector_buffered, file=sys.stderr)

            fusionVectors(vectors_buffered_controled_list, vector_sample_output, format_vector)

        print(cyan + "createMacroSamples() : " + bold + green + "... fin de la fusion" + endC)

    # ETAPE 6 : CREATION DU FICHIER RASTER RESULTAT SI DEMANDE

    # Creation d'un masque binaire
    if raster_sample_output != "" and image_input != "" :
        repertory_output = os.path.dirname(raster_sample_output)
        if not os.path.isdir(repertory_output):
            os.makedirs(repertory_output)
        rasterizeBinaryVector(vector_sample_output, image_input, raster_sample_output, 1, CODAGE)

    # ETAPE 7 : SUPPRESIONS FICHIERS INTERMEDIAIRES INUTILES

    # Suppression des données intermédiaires
    if not save_results_intermediate:

        # Supression du fichier de decoupe si celui ci a été créer
        if vector_simple_mask != vector_to_cut_input :
            if os.path.isfile(vector_simple_mask) :
                removeVectorFile(vector_simple_mask)

        # Suppression des repertoires temporaires
        deleteDir(repertory_mask_temp)
        deleteDir(repertory_samples_cutting_temp)
        deleteDir(repertory_samples_filtering_temp)
        deleteDir(repertory_samples_buff_temp)

    # Mise à jour du Log
    ending_event = "createMacroSamples() : create macro samples ending : "
    timeLine(path_time_log,ending_event)

    return