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
def preparationVecteurs(urbanatlas_input, ucz_output, emprise_file, mask_file,
enter_with_mask, image_file, mnh_file,
built_files_list, hydrography_file, roads_files_list,
rpg_file, indicators_method, ucz_method, dbms_choice,
threshold_ndvi, threshold_ndvi_water, threshold_ndwi2,
threshold_bi_bottom, threshold_bi_top, path_time_log,
temp_directory, format_vector, extension_vector):
print(bold + yellow + "Début de la préparation des données vecteurs." +
endC)
step = " Début de la préparation des données vecteurs : "
timeLine(path_time_log, step)
field_name = 'ID'
field_type = ogr.OFTInteger
emprise_erosion = temp_directory + os.sep + os.path.splitext(
os.path.basename(emprise_file))[0] + "_eroded" + extension_vector
print(bold + cyan +
" Érosion de '%s' pour le découpage des autres vecteurs :" %
(emprise_file) + endC)
bufferVector(
emprise_file, emprise_erosion, -10, "", 1.0, 10, format_vector
) # Création du shape zone d'étude érodée (utile pour la fonction CrossingVectorRaster où shape < raster) - Tampon par défaut : -10
# Traitements sur l'Urban Atlas
print(bold + cyan + " Traitements du fichier Urban Atlas '%s' :" %
(urbanatlas_input) + endC)
basename_grid = os.path.splitext(os.path.basename(urbanatlas_input))[0]
grid_reproject = temp_directory + os.sep + basename_grid + "_reproject" + extension_vector
grid_ready = temp_directory + os.sep + basename_grid + "_cut" + extension_vector
grid_ready_cleaned = temp_directory + os.sep + basename_grid + "_cut_cleaned" + extension_vector
column = "'%s, CODE2012, ITEM2012'" % (field_name)
expression = "CODE2012 NOT IN ('12210', '12220', '12230', '50000')"
updateProjection(urbanatlas_input, grid_reproject, 2154,
format_vector) # MAJ projection
addNewFieldVector(grid_reproject, field_name, field_type, 0, None, None,
format_vector) # Ajout d'un champ ID
updateIndexVector(
grid_reproject,
index_name=field_name) # Mise à jour du champs ID (incrémentation)
cutVector(
emprise_erosion, grid_reproject, grid_ready, format_vector
) # Découpage du fichier Urban Atlas d'entrée à l'emprise de la zone d'étude
ret = filterSelectDataVector(
grid_ready, grid_ready_cleaned, column, expression, format_vector
) # Suppression des polygones eau et routes (uniquement pour le calcul des indicateurs)
if not ret:
raise NameError(
cyan + "preparationVecteurs : " + bold + red +
"Attention problème lors du filtrage des BD vecteurs l'expression SQL %s est incorrecte"
% (expression) + endC)
if indicators_method in ("BD_exogenes", "SI_seuillage", "SI_classif"):
# Traitements sur les fichiers bâti de la BD TOPO
print(bold + cyan + " Traitements des fichiers bâti '%s' :" %
str(built_files_list) + endC)
built_merge = temp_directory + os.sep + "bati_merged" + extension_vector
built_ready = temp_directory + os.sep + "bati" + extension_vector
column = "HAUTEUR"
expression = "HAUTEUR > 0"
built_intersect_list = []
for built_input in built_files_list:
basename = os.path.splitext(os.path.basename(built_input))[0]
built_reproject = temp_directory + os.sep + basename + "_reproject" + extension_vector
built_intersect = temp_directory + os.sep + basename + "_intersect" + extension_vector
updateProjection(built_input, built_reproject, 2154,
format_vector) # MAJ projection
intersectVector(
emprise_file, built_reproject, built_intersect, format_vector
) # Sélection des entités bâti dans l'emprise de l'étude
built_intersect_list.append(built_intersect)
fusionVectors(built_intersect_list, built_merge,
format_vector) # Fusion des couches bâti de la BD TOPO
ret = filterSelectDataVector(
built_merge, built_ready, column, expression
) # Suppression des polygones où la hauteur du bâtiment est à 0
if not ret:
raise NameError(
cyan + "preparationVecteurs : " + bold + red +
"Attention problème lors du filtrage des BD vecteurs l'expression SQL %s est incorrecte"
% (expression) + endC)
addNewFieldVector(built_ready, field_name, field_type, 0, None, None,
format_vector) # Ajout d'un champ ID
updateIndexVector(
built_ready,
index_name=field_name) # Mise à jour du champs ID (incrémentation)
if indicators_method == "BD_exogenes":
# Traitements sur le fichier routes de la BD TOPO
print(bold + cyan +
" Traitements du fichier hydrographie '%s' :" %
(hydrography_file) + endC)
basename_hydrography = os.path.splitext(
os.path.basename(hydrography_file))[0]
hydrography_reproject = temp_directory + os.sep + basename_hydrography + "_reproject" + extension_vector
hydrography_intersect = temp_directory + os.sep + basename_hydrography + "_intersect" + extension_vector
hydrography_ready = temp_directory + os.sep + "eau" + extension_vector
column = "REGIME"
expression = "REGIME LIKE 'Permanent'"
updateProjection(hydrography_file, hydrography_reproject, 2154,
format_vector) # MAJ projection
intersectVector(
emprise_file, hydrography_reproject, hydrography_intersect,
format_vector
) # Sélection des entités routes dans l'emprise de l'étude
ret = filterSelectDataVector(
hydrography_intersect, hydrography_ready, column, expression,
format_vector
) # Sélection des entités suivant le régime hydrographique (permanent)
if not ret:
raise NameError(
cyan + "preparationVecteurs : " + bold + red +
"Attention problème lors du filtrage des BD vecteurs l'expression SQL %s est incorrecte"
% (expression) + endC)
addNewFieldVector(hydrography_ready, field_name, field_type, 0,
None, None, format_vector) # Ajout d'un champ ID
updateIndexVector(hydrography_ready, index_name=field_name
) # Mise à jour du champs ID (incrémentation)
# Traitements sur le fichier RPG
print(bold + cyan + " Traitements du fichier RPG '%s' :" %
(rpg_file) + endC)
basename_RPG = os.path.splitext(os.path.basename(rpg_file))[0]
RPG_reproject = temp_directory + os.sep + basename_RPG + "_reproject" + extension_vector
RPG_ready = temp_directory + os.sep + "RPG" + extension_vector
updateProjection(rpg_file, RPG_reproject, 2154,
format_vector) # MAJ projection
intersectVector(
emprise_file, RPG_reproject, RPG_ready, format_vector
) # Sélection des entités RPG dans l'emprise de l'étude
addNewFieldVector(RPG_ready, field_name, field_type, 0, None, None,
format_vector) # Ajout d'un champ ID
updateIndexVector(RPG_ready, index_name=field_name
) # Mise à jour du champs ID (incrémentation)
########################################################################################################################################################################################################
######################################################################## Partie restant à coder : normalement pas nécessaire puisque cette méthode n'a pas été retenue #################################
########################################################################################################################################################################################################
####
if indicators_method == "SI_seuillage": ####
# Traitements sur les fichiers routes de la BD TOPO ####
print(bold + cyan + " Traitements des fichiers routes '%s' :" %
str(roads_files_list) + endC) ####
####
print(
bold +
"Le script ne peut continuer, le traitements des fichiers routes n'est pas encore entièrement codé"
+ endC) ####
exit(0) ####
####
#~ En entrée : fichier troncon_route + fichier surface_route ####
#~ 1 - reprojection des fichiers en L93 ####
#~ 2 - sélection des entités des fichiers compris dans la zone d'étude (intersect et non découpage) ####
#~ 3 - filtrage des entités de troncon_route suivant la nature ####
#~ ("NATURE IN ('Autoroute', 'Bretelle', 'Quasi-autoroute', 'Route 1 chausse', 'Route 2 chausses', ####
#~ 'Route a 1 chaussee', 'Route a 2 chaussees', 'Route à 1 chaussée', 'Route à 2 chaussées')") ####
#~ 4 - tampon sur les entités de troncon_route correspondant à 'LARGEUR'/2 ####
#~ 5 - fusion des fichiers en un seul shape ####
#~ 6 - ajout d'un nouveau champ ID dans le fichier de fusion ####
#~ 7 - mise à jour de ce champ ID ####
####
########################################################################################################################################################################################################
########################################################################################################################################################################################################
########################################################################################################################################################################################################
step = " Fin de la préparation des données vecteurs : "
timeLine(path_time_log, step)
print(bold + yellow + "Fin de la préparation des données vecteurs." + endC)
print("\n")
return
def detectionOuvrages(input_dico,
output_dir,
method,
im_indice_buffers,
im_indice_sobel,
input_cut_vector,
input_sea_points,
no_data_value,
path_time_log,
channel_order=['Red', 'Green', 'Blue', 'NIR'],
epsg=2154,
format_raster='GTiff',
format_vector="ESRI Shapefile",
extension_raster=".tif",
extension_vector=".shp",
save_results_intermediate=True,
overwrite=True):
# Mise à jour du Log
starting_event = "detectionOuvrages() : Select Detection Ouvrages starting : "
timeLine(path_time_log, starting_event)
# Affichage des paramètres
if debug >= 3:
print(bold + green +
"Variables dans detectionOuvrages - Variables générales" + endC)
print(cyan + "detectionOuvrages() : " + endC + "input_dico : " +
str(input_dico) + endC)
print(cyan + "detectionOuvrages() : " + endC + "output_dir : " +
str(output_dir) + endC)
print(cyan + "detectionOuvrages() : " + endC + "method : " +
str(method) + endC)
print(cyan + "detectionOuvrages() : " + endC + "im_indice_buffers : " +
str(im_indice_buffers) + endC)
print(cyan + "detectionOuvrages() : " + endC + "im_indice_sobel : " +
str(im_indice_sobel) + endC)
print(cyan + "detectionOuvrages() : " + endC + "input_cut_vector : " +
str(input_cut_vector) + endC)
print(cyan + "detectionOuvrages() : " + endC + "input_sea_points : " +
str(input_sea_points) + endC)
print(cyan + "detectionOuvrages() : " + endC + "no_data_value : " +
str(no_data_value) + endC)
print(cyan + "detectionOuvrages() : " + endC + "path_time_log : " +
str(path_time_log) + endC)
print(cyan + "detectionOuvrages() : " + endC + "channel_order: " +
str(channel_order) + endC)
print(cyan + "detectionOuvrages() : " + endC + "epsg : " + str(epsg) +
endC)
print(cyan + "detectionOuvrages() : " + endC + "format_raster : " +
str(format_raster) + endC)
print(cyan + "detectionOuvrages() : " + endC + "format_vector : " +
str(format_vector) + endC)
print(cyan + "detectionOuvrages() : " + endC + "extension_raster : " +
str(extension_raster) + endC)
print(cyan + "detectionOuvrages() : " + endC + "extension_vector : " +
str(extension_vector) + endC)
print(cyan + "detectionOuvrages() : " + endC +
"save_results_intermediate : " + str(save_results_intermediate) +
endC)
print(cyan + "detectionOuvrages() : " + endC + "overwrite : " +
str(overwrite) + endC)
# Initialisation des constantes
PREFIX_OUVRAGES = "Ouvrages_final_"
# Variables
type_extension = os.path.splitext(input_dico[0].split(":")[0])[1]
# Création du répertoire de sortie s'il n'existe pas déjà
if not os.path.exists(output_dir):
os.makedirs(output_dir)
while switch(method):
if case("b"):
if type_extension == extension_raster:
if im_indice_buffers:
if debug >= 2:
print(
cyan + "detectionOuvrages() : " + endC + green +
bold +
"Cas2 : méthode buffers avec imageIndice en entrée et avec calcul TDC, en entrée : -meth b -indb -dico ImageBrute:TailleBuffer+,TailleBuffer-,ImageIndice,SeuilTerreMer -mer -d -outd"
+ endC)
for elt_dico in input_dico:
elt_list = elt_dico.split(":")
tdc = runTDCSeuil(
elt_list[0] + ":" + elt_list[1].split(",")[2] +
"," + elt_list[1].split(",")[3], output_dir,
input_sea_points, input_cut_vector, "", "", "", "",
"", "", "", "", 1.0, False, no_data_value,
path_time_log, channel_order, epsg, format_raster,
format_vector, extension_raster, extension_vector,
save_results_intermediate, overwrite)
buffersOuvrages(tdc, output_dir,
elt_list[1].split(",")[0],
elt_list[1].split(",")[1],
input_cut_vector, path_time_log,
format_vector, extension_vector,
save_results_intermediate, overwrite)
else:
if debug >= 2:
print(
cyan + "detectionOuvrages() : " + endC + green +
bold +
"Cas3 : méthode buffers avec image brute en entrée et avec calcul TDC, en entrée : -meth b -dico ImageBrute:TailleBuffer+,TailleBuffer-,SeuilTerreMer -mer -d -outd"
+ endC)
for elt_dico in input_dico:
elt_list = elt_dico.split(":")
tdc = runTDCSeuil(
elt_list[0] + ":" + elt_list[1].split(",")[2],
output_dir, input_sea_points, input_cut_vector, "",
"", "", "", "", "", "", "", 1.0, True,
no_data_value, path_time_log, channel_order, epsg,
format_raster, format_vector, extension_raster,
extension_vector, save_results_intermediate,
overwrite)
buffersOuvrages(tdc, output_dir,
elt_list[1].split(",")[0],
elt_list[1].split(",")[1],
input_cut_vector, path_time_log,
format_vector, extension_vector,
save_results_intermediate, overwrite)
elif type_extension == extension_vector:
if debug >= 2:
print(
cyan + "detectionOuvrages() : " + endC + green + bold +
"Cas1 : méthode buffers sans calculTDC, en entrée : -meth b -dico TDC:TailleBuffer+,TailleBuffer- -outd"
+ endC)
for elt_dico in input_dico:
elt_list = elt_dico.split(":")
buffersOuvrages(elt_list[0], output_dir,
elt_list[1].split(",")[0],
elt_list[1].split(",")[1],
input_cut_vector, path_time_log,
format_vector, extension_vector,
save_results_intermediate, overwrite)
else:
print(
cyan + "detectionOuvrages() : " + bold + red +
"Format de fichier non valide pour la détection des ouvrages"
+ endC,
file=sys.stderr)
sys.exit(1)
break
if case("s"):
if im_indice_sobel:
if debug >= 2:
print(
cyan + "detectionOuvrages() : " + endC + green + bold +
"Cas4 : méthode Sobel avec image NDWI2 déjà calculée, en entrée : -meth s -inds -dico ImageBrute:ImageNDWI2,SeuilSobel -d -outd"
+ endC)
for elt_dico in input_dico:
elt_list = elt_dico.split(":")
edgeExtractionOuvrages(
elt_list[0] + ":" + elt_list[1].split(",")[0] + "," +
elt_list[1].split(",")[1], output_dir,
input_cut_vector, False, no_data_value, path_time_log,
format_raster, format_vector, extension_raster,
extension_vector, save_results_intermediate, overwrite)
else:
if debug >= 2:
print(
cyan + "detectionOuvrages() : " + endC + green + bold +
"Cas5 : méthode Sobel avec calcul NDWI2, en entrée : -meth s -dico ImageBrute:SeuilSobel -d -outd"
+ endC)
for elt_dico in input_dico:
elt_list = elt_dico.split(":")
edgeExtractionOuvrages(
elt_list[0] + ":" + elt_list[1], output_dir,
input_cut_vector, True, no_data_value, path_time_log,
format_raster, format_vector, extension_raster,
extension_vector, save_results_intermediate, overwrite)
break
if case("bs"):
if im_indice_buffers and im_indice_sobel:
if debug >= 2:
print(
cyan + "detectionOuvrages() : " + endC + green + bold +
"Cas6 : méthode buffers+Sobel avec calcul TDC mais imageIndice et imageNDWI2 déjà calculées, en entrée : -meth bs -indb -inds -dico ImageBrute:TailleBuffer+,TailleBuffer-,ImageIndice,SeuilTerreMer,ImageNDWI2,SeuilSobel -d -outd -mer"
+ endC)
for elt_dico in input_dico:
elt_list = elt_dico.split(":")
tdc = runTDCSeuil(
elt_list[0] + ":" + elt_list[1].split(",")[2] + "," +
elt_list[1].split(",")[3], output_dir,
input_sea_points, input_cut_vector, "", "", "", "", "",
"", "", "", 1.0, False, no_data_value, path_time_log,
channel_order, epsg, format_raster, format_vector,
extension_raster, extension_vector,
save_results_intermediate, overwrite)
buffers_ouvrages_shp = buffersOuvrages(
tdc, output_dir, elt_list[1].split(",")[0],
elt_list[1].split(",")[1], input_cut_vector,
path_time_log, format_vector, extension_vector,
save_results_intermediate, overwrite)
sobel_ouvrages_shp = edgeExtractionOuvrages(
elt_list[0] + ":" + elt_list[1].split(",")[4] + "," +
elt_list[1].split(",")[5], output_dir,
input_cut_vector, False, no_data_value, path_time_log,
format_raster, format_vector, extension_raster,
extension_vector, save_results_intermediate, overwrite)
fusionVectors(
[buffers_ouvrages_shp, sobel_ouvrages_shp[0]],
output_dir + os.sep + PREFIX_OUVRAGES +
os.path.splitext(os.path.basename(elt_list[0]))[0] +
extension_vector, format_vector)
elif im_indice_buffers:
if debug >= 2:
print(
cyan + "detectionOuvrages() : " + endC + green + bold +
"Cas7 : méthode buffers+Sobel avec calcul TDC, imageIndice déjà calculée mais imageNDWI2 à calculer, en entrée : -meth bs -indb -dico ImageBrute:TailleBuffer+,TailleBuffer-,ImageIndice,SeuilTerreMer,SeuilSobel -d -outd -mer"
+ endC)
for elt_dico in input_dico:
elt_list = elt_dico.split(":")
tdc = runTDCSeuil(
elt_list[0] + ":" + elt_list[1].split(",")[2] + "," +
elt_list[1].split(",")[3], output_dir,
input_sea_points, input_cut_vector, "", "", "", "", "",
"", "", "", 1.0, False, no_data_value, path_time_log,
channel_order, epsg, format_raster, format_vector,
extension_raster, extension_vector,
save_results_intermediate, overwrite)
buffers_ouvrages_shp = buffersOuvrages(
tdc, output_dir, elt_list[1].split(",")[0],
elt_list[1].split(",")[1], input_cut_vector,
path_time_log, format_vector, extension_vector,
save_results_intermediate, overwrite)
sobel_ouvrages_shp = edgeExtractionOuvrages(
elt_list[0] + ":" + elt_list[1].split(",")[4],
output_dir, input_cut_vector, True, no_data_value,
path_time_log, format_raster, format_vector,
extension_raster, extension_vector,
save_results_intermediate, overwrite)
fusionVectors(
[buffers_ouvrages_shp, sobel_ouvrages_shp[0]],
output_dir + os.sep + PREFIX_OUVRAGES +
os.path.splitext(os.path.basename(elt_list[0]))[0] +
extension_vector, format_vector)
elif im_indice_sobel:
if debug >= 2:
print(
cyan + "detectionOuvrages() : " + endC + green + bold +
"Cas8 : méthode buffers+Sobel avec TDC et imageNDWI2 déjà calculés, en entrée : -meth bs -inds -dico TDC:TailleBuffer+,TailleBuffer-,ImageBrute,ImageNDWI2,SeuilSobel -d -outd"
+ endC)
for elt_dico in input_dico:
elt_list = elt_dico.split(":")
buffers_ouvrages_shp = buffersOuvrages(
elt_list[1].split(",")[2], output_dir,
elt_list[1].split(",")[0], elt_list[1].split(",")[1],
input_cut_vector, path_time_log, format_vector,
extension_vector, save_results_intermediate, overwrite)
sobel_ouvrages_shp = edgeExtractionOuvrages(
elt_list[0] + ":" + elt_list[1].split(",")[3] + "," +
elt_list[1].split(",")[4], output_dir,
input_cut_vector, False, no_data_value, path_time_log,
format_raster, format_vector, extension_raster,
extension_vector, save_results_intermediate, overwrite)
fusionVectors(
[buffers_ouvrages_shp, sobel_ouvrages_shp[0]],
output_dir + os.sep + PREFIX_OUVRAGES +
os.path.splitext(os.path.basename(elt_list[0]))[0] +
extension_vector, format_vector)
else:
if type_extension == extension_vector:
if debug >= 2:
print(
cyan + "detectionOuvrages() : " + endC + green +
bold +
"Cas9 : méthode buffers+Sobel avec TDC déjà calculé mais imageNDWI2 à calculer, en entrée : -meth bs -dico TDC:TailleBuffer+,TailleBuffer-,ImageBrute,SeuilSobel -d -outd"
+ endC)
for elt_dico in input_dico:
elt_list = elt_dico.split(":")
buffers_ouvrages_shp = buffersOuvrages(
elt_list[0], output_dir, elt_list[1].split(",")[0],
elt_list[1].split(",")[1], input_cut_vector,
path_time_log, format_vector, extension_vector,
save_results_intermediate, overwrite)
sobel_ouvrages_shp = edgeExtractionOuvrages(
elt_list[1].split(",")[2] + ":" +
elt_list[1].split(",")[3], output_dir,
input_cut_vector, True, no_data_value,
path_time_log, format_raster, format_vector,
extension_raster, extension_vector,
save_results_intermediate, overwrite)
fusionVectors(
[buffers_ouvrages_shp, sobel_ouvrages_shp[0]],
output_dir + os.sep + PREFIX_OUVRAGES +
os.path.splitext(
os.path.basename(elt_list[1].split(",")[2]))[0]
+ extension_vector, format_vector)
elif type_extension == extension_raster:
if debug >= 2:
print(
cyan + "detectionOuvrages() : " + endC + green +
bold +
"Cas10 : méthode buffers+Sobel avec calculs TDC, imageNDVI et imageNDWI2 à faire, en entrée : -meth bs -dico ImageBrute:TailleBuffer+,TailleBuffer-,SeuilTerreMer,SeuilSobel -d -outd -mer"
+ endC)
for elt_dico in input_dico:
elt_list = elt_dico.split(":")
tdc = runTDCSeuil(
elt_list[0] + ":" + elt_list[1].split(",")[2],
output_dir, input_sea_points, input_cut_vector, "",
"", "", "", "", "", "", "", 1.0, True,
no_data_value, path_time_log, channel_order, epsg,
format_raster, format_vector, extension_raster,
extension_vector, save_results_intermediate,
overwrite)
buffers_ouvrages_shp = buffersOuvrages(
tdc, output_dir, elt_list[1].split(",")[0],
elt_list[1].split(",")[1], input_cut_vector,
path_time_log, format_vector, extension_vector,
save_results_intermediate, overwrite)
sobel_ouvrages_shp = edgeExtractionOuvrages(
elt_list[0] + ":" + elt_list[1].split(",")[3],
output_dir, input_cut_vector, True, no_data_value,
path_time_log, format_raster, format_vector,
extension_raster, extension_vector,
save_results_intermediate, overwrite)
fusionVectors(
[buffers_ouvrages_shp, sobel_ouvrages_shp[0]],
output_dir + os.sep + PREFIX_OUVRAGES +
os.path.splitext(os.path.basename(elt_list[0]))[0]
+ extension_vector, format_vector)
else:
print(
cyan + "detectionOuvrages() : " + bold + red +
"Format de fichier non valide pour la détection des ouvrages"
+ endC,
file=sys.stderr)
sys.exit(1)
break
else:
print(
cyan + "detectionOuvrages() : " + bold + red +
"Méthode de détection des ouvrages non valide : b pour buffers, s pour méthode de Sobel, bs pour combiner les 2"
+ endC,
file=sys.stderr)
sys.exit(1)
# Mise à jour du Log
ending_event = "detectionOuvrages() : Select Detection Ouvrages ending : "
timeLine(path_time_log, ending_event)
return
def computeMajorityClass(input_grid, temp_directory, nodata_field, built_field,
mineral_field, baresoil_field, water_field,
vegetation_field, high_vegetation_field,
low_vegetation_field, maj_ocs_field, veg_mean_field,
class_label_dico_out, format_vector, extension_vector,
overwrite):
SUFFIX_CLASS = '_class'
FIELD_TYPE = ogr.OFTInteger
FIELD_NAME_MAJORITY = 'majority'
temp_class_list = []
base_name = os.path.splitext(os.path.basename(input_grid))[0]
temp_grid = temp_directory + os.sep + base_name + SUFFIX_CLASS + extension_vector
temp_class0 = temp_directory + os.sep + base_name + SUFFIX_CLASS + "0" + extension_vector
temp_class1 = temp_directory + os.sep + base_name + SUFFIX_CLASS + "1" + extension_vector
temp_class2 = temp_directory + os.sep + base_name + SUFFIX_CLASS + "2" + extension_vector
temp_class3 = temp_directory + os.sep + base_name + SUFFIX_CLASS + "3" + extension_vector
temp_class4 = temp_directory + os.sep + base_name + SUFFIX_CLASS + "4" + extension_vector
### Récupération de la classe majoritaire
if debug >= 3:
print(cyan + "computeMajorityClass() : " + endC + bold +
"Récupération de la classe majoritaire." + endC + '\n')
addNewFieldVector(input_grid,
maj_ocs_field,
FIELD_TYPE,
field_value=None,
field_width=None,
field_precision=None,
format_vector=format_vector)
attr_names_list = getAttributeNameList(input_grid,
format_vector=format_vector)
attr_names_list_str = "'"
for attr_name in attr_names_list:
attr_names_list_str += attr_name + ', '
attr_names_list_str = attr_names_list_str[:-2] + "'"
expression = "%s = '%s' OR %s = '%s' OR %s = '%s' OR %s = '%s'" % (
FIELD_NAME_MAJORITY, nodata_field, FIELD_NAME_MAJORITY, built_field,
FIELD_NAME_MAJORITY, mineral_field, FIELD_NAME_MAJORITY, water_field)
ret = filterSelectDataVector(input_grid,
temp_class0,
attr_names_list_str,
expression,
overwrite=overwrite,
format_vector=format_vector)
updateFieldVector(temp_class0,
field_name=maj_ocs_field,
value=class_label_dico_out["MAJ_OTHERS_CLASS"],
format_vector=format_vector)
temp_class_list.append(temp_class0)
expression = "%s = '%s'" % (FIELD_NAME_MAJORITY, baresoil_field)
ret = filterSelectDataVector(input_grid,
temp_class1,
attr_names_list_str,
expression,
overwrite=overwrite,
format_vector=format_vector)
updateFieldVector(temp_class1,
field_name=maj_ocs_field,
value=class_label_dico_out["MAJ_BARESOIL_CLASS"],
format_vector=format_vector)
temp_class_list.append(temp_class1)
expression = "(%s = '%s' OR %s = '%s' OR %s = '%s') AND (%s < 1)" % (
FIELD_NAME_MAJORITY, vegetation_field, FIELD_NAME_MAJORITY,
low_vegetation_field, FIELD_NAME_MAJORITY, high_vegetation_field,
veg_mean_field)
ret = filterSelectDataVector(input_grid,
temp_class2,
attr_names_list_str,
expression,
overwrite=overwrite,
format_vector=format_vector)
updateFieldVector(temp_class2,
field_name=maj_ocs_field,
value=class_label_dico_out["MAJ_LOW_VEG_CLASS"],
format_vector=format_vector)
temp_class_list.append(temp_class2)
expression = "(%s = '%s' OR %s = '%s' OR %s = '%s') AND (%s >= 1 AND %s < 5)" % (
FIELD_NAME_MAJORITY, vegetation_field, FIELD_NAME_MAJORITY,
low_vegetation_field, FIELD_NAME_MAJORITY, high_vegetation_field,
veg_mean_field, veg_mean_field)
ret = filterSelectDataVector(input_grid,
temp_class3,
attr_names_list_str,
expression,
overwrite=overwrite,
format_vector=format_vector)
updateFieldVector(temp_class3,
field_name=maj_ocs_field,
value=class_label_dico_out["MAJ_MED_VEG_CLASS"],
format_vector=format_vector)
temp_class_list.append(temp_class3)
expression = "(%s = '%s' OR %s = '%s' OR %s = '%s') AND (%s >= 5)" % (
FIELD_NAME_MAJORITY, vegetation_field, FIELD_NAME_MAJORITY,
low_vegetation_field, FIELD_NAME_MAJORITY, high_vegetation_field,
veg_mean_field)
ret = filterSelectDataVector(input_grid,
temp_class4,
attr_names_list_str,
expression,
overwrite=overwrite,
format_vector=format_vector)
updateFieldVector(temp_class4,
field_name=maj_ocs_field,
value=class_label_dico_out["MAJ_HIGH_VEG_CLASS"],
format_vector=format_vector)
temp_class_list.append(temp_class4)
fusionVectors(temp_class_list, temp_grid, format_vector=format_vector)
removeVectorFile(input_grid, format_vector=format_vector)
copyVectorFile(temp_grid, input_grid, format_vector=format_vector)
return 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
def vectorsPreparation(emprise_file, classif_input, grid_input, built_input_list, roads_input_list, grid_output, grid_output_cleaned, built_output, roads_output, col_code_ua, col_item_ua, epsg, path_time_log, format_vector='ESRI Shapefile', extension_vector=".shp", save_results_intermediate=False, overwrite=True):
print(bold + yellow + "Début de la préparation des fichiers vecteurs." + endC + "\n")
timeLine(path_time_log, "Début de la préparation des fichiers vecteurs : ")
if debug >= 3 :
print(bold + green + "vectorsPreparation() : Variables dans la fonction" + endC)
print(cyan + "vectorsPreparation() : " + endC + "emprise_file : " + str(emprise_file) + endC)
print(cyan + "vectorsPreparation() : " + endC + "classif_input : " + str(classif_input) + endC)
print(cyan + "vectorsPreparation() : " + endC + "grid_input : " + str(grid_input) + endC)
print(cyan + "vectorsPreparation() : " + endC + "built_input_list : " + str(built_input_list) + endC)
print(cyan + "vectorsPreparation() : " + endC + "roads_input_list : " + str(roads_input_list) + endC)
print(cyan + "vectorsPreparation() : " + endC + "grid_output : " + str(grid_output) + endC)
print(cyan + "vectorsPreparation() : " + endC + "grid_output_cleaned : " + str(grid_output_cleaned) + endC)
print(cyan + "vectorsPreparation() : " + endC + "built_output : " + str(built_output) + endC)
print(cyan + "vectorsPreparation() : " + endC + "roads_output : " + str(roads_output) + endC)
print(cyan + "vectorsPreparation() : " + endC + "col_code_ua : " + str(col_code_ua) + endC)
print(cyan + "vectorsPreparation() : " + endC + "col_item_ua : " + str(col_item_ua) + endC)
print(cyan + "vectorsPreparation() : " + endC + "epsg : " + str(epsg))
print(cyan + "vectorsPreparation() : " + endC + "path_time_log : " + str(path_time_log) + endC)
print(cyan + "vectorsPreparation() : " + endC + "format_vector : " + str(format_vector) + endC)
print(cyan + "vectorsPreparation() : " + endC + "extension_vector : " + str(extension_vector) + endC)
print(cyan + "vectorsPreparation() : " + endC + "save_results_intermediate : " + str(save_results_intermediate) + endC)
print(cyan + "vectorsPreparation() : " + endC + "overwrite : " + str(overwrite) + endC)
FOLDER_TEMP = 'TEMP'
SUFFIX_VECTOR_REPROJECT = '_reproject'
SUFFIX_VECTOR_INTERSECT = '_intersect'
SUFFIX_VECTOR_MERGE = '_merge'
SUFFIX_VECTOR_SELECT = '_select'
if not os.path.exists(grid_output) or not os.path.exists(built_output) or not os.path.exists(roads_output) or overwrite:
############################################
### Préparation générale des traitements ###
############################################
path_grid_temp = os.path.dirname(grid_output) + os.sep + FOLDER_TEMP
path_built_temp = os.path.dirname(built_output) + os.sep + FOLDER_TEMP
path_roads_temp = os.path.dirname(roads_output) + os.sep + FOLDER_TEMP
if os.path.exists(path_grid_temp):
shutil.rmtree(path_grid_temp)
if os.path.exists(path_built_temp):
shutil.rmtree(path_built_temp)
if os.path.exists(path_roads_temp):
shutil.rmtree(path_roads_temp)
if not os.path.exists(path_grid_temp):
os.mkdir(path_grid_temp)
if not os.path.exists(path_built_temp):
os.mkdir(path_built_temp)
if not os.path.exists(path_roads_temp):
os.mkdir(path_roads_temp)
basename_grid = os.path.splitext(os.path.basename(grid_output))[0]
basename_built = os.path.splitext(os.path.basename(built_output))[0]
basename_roads = os.path.splitext(os.path.basename(roads_output))[0]
# Variables pour ajout colonne ID
field_name = 'ID' # Attention ! Nom fixé en dur dans les scripts indicateurs, pas dans le script final
field_type = ogr.OFTInteger
##############################################
### Traitements sur le vecteur Urban Atlas ###
##############################################
if not os.path.exists(grid_output) or overwrite :
if os.path.exists(grid_output):
removeVectorFile(grid_output)
if os.path.exists(grid_output_cleaned):
removeVectorFile(grid_output_cleaned)
# MAJ projection
grid_reproject = path_grid_temp + os.sep + basename_grid + SUFFIX_VECTOR_REPROJECT + extension_vector
updateProjection(grid_input, grid_reproject, projection=epsg)
# Découpage du fichier Urban Atlas d'entrée à l'emprise de la zone d'étude
grid_output_temp = os.path.splitext(grid_output)[0] + "_temp" + extension_vector
cutVector(emprise_file, grid_reproject, grid_output_temp, overwrite, format_vector)
# Suppression des très petits polygones qui introduisent des valeurs NaN
pixel_size = getPixelSizeImage(classif_input)
min_size_area = pixel_size * 2
cleanMiniAreaPolygons(grid_output_temp, grid_output, min_size_area, '', format_vector)
if not save_results_intermediate:
if os.path.exists(grid_output_temp):
removeVectorFile(grid_output_temp, format_vector)
# Ajout d'un champ ID
addNewFieldVector(grid_output, field_name, field_type, 0, None, None, format_vector)
updateIndexVector(grid_output, field_name, format_vector)
# Suppression des polygones eau et routes (uniquement pour le calcul des indicateurs)
column = "'%s, %s, %s'" % (field_name, col_code_ua, col_item_ua)
expression = "%s NOT IN ('12210', '12220', '12230', '50000')" % (col_code_ua)
ret = filterSelectDataVector(grid_output, grid_output_cleaned, column, expression, format_vector)
if not ret :
raise NameError (cyan + "vectorsPreparation : " + bold + red + "Attention problème lors du filtrage des BD vecteurs l'expression SQL %s est incorrecte" %(expression) + endC)
#########################################
### Traitements sur les vecteurs bâti ###
#########################################
if not os.path.exists(built_output) or overwrite :
if os.path.exists(built_output):
removeVectorFile(built_output)
# MAJ projection
built_reproject_list=[]
for built_input in built_input_list:
built_reproject = path_built_temp + os.sep + os.path.splitext(os.path.basename(built_input))[0] + SUFFIX_VECTOR_REPROJECT + extension_vector
updateProjection(built_input, built_reproject, projection=epsg)
built_reproject_list.append(built_reproject)
# Sélection des entités bâti dans l'emprise de l'étude
built_intersect_list = []
for built_reproject in built_reproject_list:
built_intersect = path_built_temp + os.sep + os.path.splitext(os.path.basename(built_reproject))[0] + SUFFIX_VECTOR_INTERSECT + extension_vector
intersectVector(emprise_file, built_reproject, built_intersect, format_vector)
built_intersect_list.append(built_intersect)
# Fusion des couches bâti de la BD TOPO
built_merge = path_built_temp + os.sep + basename_built + SUFFIX_VECTOR_MERGE + extension_vector
built_select = path_built_temp + os.sep + basename_built + SUFFIX_VECTOR_SELECT + extension_vector
fusionVectors(built_intersect_list, built_merge)
# Suppression des polygones où la hauteur du bâtiment est à 0
column = "HAUTEUR"
expression = "HAUTEUR > 0"
ret = filterSelectDataVector(built_merge, built_select, column, expression, format_vector)
if not ret :
raise NameError (cyan + "vectorsPreparation : " + bold + red + "Attention problème lors du filtrage des BD vecteurs l'expression SQL %s est incorrecte" %(expression) + endC)
# Découpage des bati d'entrée à l'emprise de la zone d'étude
cutVector(emprise_file, built_select, built_output, overwrite, format_vector)
# Ajout d'un champ ID
addNewFieldVector(built_output, field_name, field_type, 0, None, None, format_vector)
updateIndexVector(built_output, field_name, format_vector)
###########################################
### Traitements sur les vecteurs routes ###
###########################################
if not os.path.exists(roads_output) or overwrite :
if os.path.exists(roads_output):
removeVectorFile(roads_output)
# MAJ projection
roads_reproject_list=[]
for roads_input in roads_input_list:
roads_reproject = path_roads_temp + os.sep + os.path.splitext(os.path.basename(roads_input))[0] + SUFFIX_VECTOR_REPROJECT + extension_vector
updateProjection(roads_input, roads_reproject, projection=epsg)
roads_reproject_list.append(roads_reproject)
# Sélection des entités routes dans l'emprise de l'étude
roads_intersect_list = []
for roads_reproject in roads_reproject_list:
roads_intersect = path_roads_temp + os.sep + os.path.splitext(os.path.basename(roads_reproject))[0] + SUFFIX_VECTOR_INTERSECT + extension_vector
intersectVector(emprise_file, roads_reproject, roads_intersect, format_vector)
roads_intersect_list.append(roads_intersect)
# Fusion des couches route de la BD TOPO
roads_merge = path_roads_temp + os.sep + basename_roads + SUFFIX_VECTOR_MERGE + extension_vector
roads_select = path_roads_temp + os.sep + basename_roads + SUFFIX_VECTOR_SELECT + extension_vector
fusionVectors(roads_intersect_list, roads_merge)
# Sélection des entités suivant la nature de la route dans la couche routes de la BD TOPO
column = "NATURE"
expression = "NATURE IN ('Autoroute', 'Bretelle', 'Quasi-autoroute', 'Route 1 chausse', 'Route 2 chausses', 'Route a 1 chaussee', 'Route a 2 chaussees', 'Route à 1 chaussée', 'Route à 2 chaussées')"
ret = filterSelectDataVector (roads_merge, roads_select, column, expression, format_vector)
if not ret :
raise NameError (cyan + "vectorsPreparation : " + bold + red + "Attention problème lors du filtrage des BD vecteurs l'expression SQL %s est incorrecte" %(expression) + endC)
# Découpage des routes d'entrée à l'emprise de la zone d'étude
cutVectorAll(emprise_file, roads_select, roads_output, overwrite, format_vector)
# Ajout d'un champ ID
addNewFieldVector(roads_output, field_name, field_type, 0, None, None, format_vector)
updateIndexVector(roads_output, field_name, format_vector)
##########################################
### Nettoyage des fichiers temporaires ###
##########################################
if not save_results_intermediate:
if os.path.exists(path_grid_temp):
shutil.rmtree(path_grid_temp)
if os.path.exists(path_built_temp):
shutil.rmtree(path_built_temp)
if os.path.exists(path_roads_temp):
shutil.rmtree(path_roads_temp)
else:
print(bold + magenta + "La préparation des fichiers vecteurs a déjà eu lieu.\n" + endC)
print(bold + yellow + "Fin de la préparation des fichiers vecteurs.\n" + endC)
timeLine(path_time_log, "Fin de la préparation des fichiers vecteurs : ")
return
def multiBuffersVector(input_file, output_dir, buffer_size, nb_buffers, path_time_log, epsg=2154, format_vector="ESRI Shapefile", project_encoding="UTF-8", overwrite=True):
# Mise à jour du Log
starting_event = "multiBuffersVector() : Select multi buffers vector starting : "
timeLine(path_time_log,starting_event)
# Configuration du format vecteur
driver = ogr.GetDriverByName(format_vector)
# Création de la référence spatiale
srs = osr.SpatialReference()
srs.ImportFromEPSG(epsg)
result_list = []
extension_vector = os.path.splitext(os.path.split(input_file)[1])[1]
nom_input_file = os.path.splitext(os.path.split(input_file)[1])[0]
output_repertory = output_dir + os.sep + "multi_ring_buffers_" + nom_input_file + extension_vector
for i in range(1, nb_buffers+1):
# Création du buffer
output_temp_buffer = output_dir + os.sep + os.path.splitext(os.path.split(input_file)[1])[0] + "_buffer_" + str(i*buffer_size) + extension_vector
bufferVector(input_file, output_temp_buffer, i*buffer_size, "", 1.0, 10, format_vector)
# Ajout d'un champ taille de buffer
data_source_buffer = driver.Open(output_temp_buffer, 1)
buffer_layer = data_source_buffer.GetLayer(0)
buff_size_field = ogr.FieldDefn("size_buff", ogr.OFTReal)
buffer_layer.CreateField(buff_size_field)
for feature in buffer_layer:
feature.SetField("size_buff",i*buffer_size)
buffer_layer.SetFeature(feature)
# Ajout du premier buffer à la liste finale
if i == 1:
result_list.append(output_temp_buffer)
# Transformation des buffers en anneaux
if i>1:
i_preced = i-1
output_temp_buffer_preced = output_dir + os.sep + nom_input_file + "_buffer_" + str(i_preced*buffer_size) + extension_vector
output_temp_ring = output_dir + os.sep + nom_input_file + "_ring_" + str(i*buffer_size) + extension_vector
differenceVector(output_temp_buffer_preced, output_temp_buffer, output_temp_ring, format_vector)
# Remplissage du champ taille du buffer
data_source_ring = driver.Open(output_temp_ring, 1)
ring_layer = data_source_ring.GetLayer(0)
for ring in ring_layer:
ring.SetField("size_buff",i*buffer_size)
ring_layer.SetFeature(ring)
# Ajout de l'anneau à la liste finale
result_list.append(output_temp_ring)
fusionVectors(result_list, output_repertory, format_vector)
# Mise à jour du Log
ending_event = "multiBuffersVector() : multi buffers vector ending : "
timeLine(path_time_log,ending_event)
return output_repertory
def computeQualityIndiceRateQuantity(raster_input,
vector_sample_input,
repertory_output,
base_name,
geom,
size_grid,
pixel_size_x,
pixel_size_y,
field_value_verif,
field_value_other,
no_data_value,
epsg,
format_raster,
format_vector,
extension_raster,
extension_vector,
overwrite=True,
save_results_intermediate=False):
# Définition des constantes
EXT_TXT = '.txt'
SUFFIX_STUDY = '_study'
SUFFIX_CUT = '_cut'
SUFFIX_BUILD = '_build'
SUFFIX_OTHER = '_other'
SUFFIX_LOCAL = '_local'
SUFFIX_MATRIX = '_matrix'
FIELD_NAME_CLASSIF = "classif"
FIELD_TYPE = ogr.OFTInteger
# Les variables locales
vector_local_study = repertory_output + os.sep + base_name + SUFFIX_LOCAL + SUFFIX_STUDY + extension_vector
vector_local_cut_study = repertory_output + os.sep + base_name + SUFFIX_LOCAL + SUFFIX_CUT + SUFFIX_STUDY + extension_vector
vector_local_cut_build = repertory_output + os.sep + base_name + SUFFIX_LOCAL + SUFFIX_CUT + SUFFIX_BUILD + extension_vector
vector_local_cut_other = repertory_output + os.sep + base_name + SUFFIX_LOCAL + SUFFIX_CUT + SUFFIX_OTHER + extension_vector
vector_local_cut = repertory_output + os.sep + base_name + SUFFIX_LOCAL + SUFFIX_CUT + extension_vector
raster_local_cut = repertory_output + os.sep + base_name + SUFFIX_LOCAL + SUFFIX_CUT + extension_raster
matrix_local_file = repertory_output + os.sep + base_name + SUFFIX_LOCAL + SUFFIX_CUT + SUFFIX_MATRIX + EXT_TXT
class_ref_list = None
class_pro_list = None
rate_quantity_list = None
matrix_origine = None
kappa = 0.0
overall_accuracy = 0.0
# Netoyage les fichiers de travail local
if os.path.isfile(vector_local_study):
removeVectorFile(vector_local_study)
if os.path.isfile(vector_local_cut_study):
removeVectorFile(vector_local_cut_study)
if os.path.isfile(vector_local_cut):
removeVectorFile(vector_local_cut)
if os.path.isfile(vector_local_cut_build):
removeVectorFile(vector_local_cut_build)
if os.path.isfile(vector_local_cut_other):
removeVectorFile(vector_local_cut_other)
if os.path.isfile(raster_local_cut):
removeFile(raster_local_cut)
if os.path.isfile(matrix_local_file):
removeFile(matrix_local_file)
# Creation d'un shape file de travail local
polygon_attr_geom_dico = {"1": [geom, {}]}
createPolygonsFromGeometryList({}, polygon_attr_geom_dico,
vector_local_study, epsg, format_vector)
# Découpe sur zone local d'étude du fichier vecteur de référence
cutVector(vector_local_study, vector_sample_input, vector_local_cut_build,
format_vector)
differenceVector(vector_local_cut_build, vector_local_study,
vector_local_cut_other, format_vector)
addNewFieldVector(vector_local_cut_build, FIELD_NAME_CLASSIF, FIELD_TYPE,
field_value_verif, None, None, format_vector)
addNewFieldVector(vector_local_cut_other, FIELD_NAME_CLASSIF, FIELD_TYPE,
field_value_other, None, None, format_vector)
input_shape_list = [vector_local_cut_build, vector_local_cut_other]
fusionVectors(input_shape_list, vector_local_cut)
# Découpe sur zone local d'étude du fichier rasteur de classification
if not cutImageByVector(vector_local_study, raster_input, raster_local_cut,
pixel_size_x, pixel_size_y, no_data_value, 0,
format_raster, format_vector):
return class_ref_list, class_pro_list, rate_quantity_list, kappa, overall_accuracy, matrix_origine
# Calcul de la matrice de confusion
computeConfusionMatrix(raster_local_cut, vector_local_cut, "",
FIELD_NAME_CLASSIF, matrix_local_file, overwrite)
# lecture de la matrice de confusion
matrix, class_ref_list, class_pro_list = readConfusionMatrix(
matrix_local_file)
matrix_origine = copy.deepcopy(matrix)
if matrix == []:
print(
cyan + "computeQualityIndiceRateQuantity() : " + bold + yellow +
"!!! Une erreur c'est produite au cours de la lecture de la matrice de confusion : "
+ matrix_local_file + ". Voir message d'erreur." + endC)
matrix_origine = None
return class_ref_list, class_pro_list, rate_quantity_list, kappa, overall_accuracy, matrix_origine
# Correction de la matrice de confusion
# Dans le cas ou le nombre de microclasses des échantillons de controles
# et le nombre de microclasses de la classification sont différents
class_missing_list = []
if class_ref_list != class_pro_list:
matrix, class_missing_list = correctMatrix(class_ref_list,
class_pro_list, matrix,
no_data_value)
class_count = len(matrix[0]) - len(class_missing_list)
# Calcul des indicateurs de qualité : rate_quantity_list
precision_list, recall_list, fscore_list, performance_list, rate_false_positive_list, rate_false_negative_list, rate_quantity_list, class_list, overall_accuracy, overall_fscore, overall_performance, kappa = computeIndicators(
class_count, matrix, class_ref_list, class_missing_list)
# Chercher si une ligne no data existe si c'est le cas correction de la matrice
if str(no_data_value) in class_pro_list:
pos_col_nodata = class_pro_list.index(str(no_data_value))
for line in matrix_origine:
del line[pos_col_nodata]
class_pro_list.remove(str(no_data_value))
# Suppression des données temporaires locales
if not save_results_intermediate:
if os.path.isfile(vector_local_study):
removeVectorFile(vector_local_study)
if os.path.isfile(vector_local_cut_study):
removeVectorFile(vector_local_cut_study)
if os.path.isfile(vector_local_cut):
removeVectorFile(vector_local_cut)
if os.path.isfile(vector_local_cut_build):
removeVectorFile(vector_local_cut_build)
if os.path.isfile(vector_local_cut_other):
removeVectorFile(vector_local_cut_other)
if os.path.isfile(raster_local_cut):
removeFile(raster_local_cut)
if os.path.isfile(matrix_local_file):
removeFile(matrix_local_file)
return class_ref_list, class_pro_list, rate_quantity_list, kappa, overall_accuracy, matrix_origine
def processTDCfilesSmoothAndFusion(coastline_vectors_input_list, vector_rocky_input, vector_all_output, vector_withrocky_output, generalize_param_method, generalize_param_threshold, name_column_fusion, path_time_log, epsg=2154, format_vector='ESRI Shapefile', extension_vector='.shp', save_results_intermediate=False, overwrite=True):
# Mise à jour du Log
starting_event = "processTDCfilesSmoothAndFusion() : Create final coastline starting : "
timeLine(path_time_log,starting_event)
print(endC)
print(bold + green + "## START : POST TRAITEMENT TDC" + endC)
print(endC)
if debug >= 2:
print(bold + green + "processTDCfilesSmoothAndFusion() : Variables dans la fonction" + endC)
print(cyan + "processTDCfilesSmoothAndFusion() : " + endC + "coastline_vectors_input_list : " + str(coastline_vectors_input_list) + endC)
print(cyan + "processTDCfilesSmoothAndFusion() : " + endC + "vector_rocky_input : " + str(vector_rocky_input) + endC)
print(cyan + "processTDCfilesSmoothAndFusion() : " + endC + "vector_all_output : " + str(vector_all_output) + endC)
print(cyan + "processTDCfilesSmoothAndFusion() : " + endC + "vector_withrocky_output : " + str(vector_withrocky_output) + endC)
print(cyan + "processTDCfilesSmoothAndFusion() : " + endC + "generalize_param_method : " + str(generalize_param_method) + endC)
print(cyan + "processTDCfilesSmoothAndFusion() : " + endC + "generalize_param_threshold : " + str(generalize_param_threshold) + endC)
print(cyan + "processTDCfilesSmoothAndFusion() : " + endC + "name_column_fusion : " + str(name_column_fusion) + endC)
print(cyan + "processTDCfilesSmoothAndFusion() : " + endC + "epsg : " + str(epsg) + endC)
print(cyan + "processTDCfilesSmoothAndFusion() : " + endC + "format_vector : " + str(format_vector) + endC)
print(cyan + "processTDCfilesSmoothAndFusion() : " + endC + "extension_vector : " + str(extension_vector) + endC)
print(cyan + "processTDCfilesSmoothAndFusion() : " + endC + "path_time_log : " + str(path_time_log) + endC)
print(cyan + "processTDCfilesSmoothAndFusion() : " + endC + "save_results_intermediate : " + str(save_results_intermediate) + endC)
print(cyan + "processTDCfilesSmoothAndFusion() : " + endC + "overwrite : " + str(overwrite) + endC)
SUFFIX_SMOOTH = "_smooth"
SUFFIX_TMP = "_tmp"
SUFFIX_SMOOTH = "_smooth"
SUFFIX_FUSION = "_fusion"
repertory_output = os.path.dirname(vector_all_output)
file_name = os.path.splitext(os.path.basename(vector_all_output))[0]
vector_fusion = repertory_output + os.sep + file_name + SUFFIX_FUSION + extension_vector
repertory_temp = repertory_output + os.sep + file_name + SUFFIX_TMP
if not os.path.exists(repertory_temp):
os.makedirs(repertory_temp)
# Vérification de l'existence du vecteur de sortie
check = os.path.isfile(vector_all_output)
# Si oui et si la vérification est activée, passage à l'étape suivante
if check and not overwrite :
print(cyan + "processTDCfilesSmoothAndFusion() : " + bold + green + "Vector general coastline already existe : " + str(vector_all_output) + "." + endC)
# Si non ou si la vérification est désactivée, application des traitements de lissage et de la fusion
else:
# Tentative de suppresion des fichiers
try:
removeVectorFile(vector_all_output)
removeVectorFile(vector_withrocky_output)
except Exception:
# Ignore l'exception levée si le fichier n'existe pas (et ne peut donc pas être supprimé)
pass
# Pour tous les fichiers vecteurs d'entrée appliquer le traitement de lissage par GRASS
param_generalize_dico = {"method":generalize_param_method, "threshold":generalize_param_threshold}
vectors_temp_output_list = []
for input_vector in coastline_vectors_input_list :
vector_name = os.path.splitext(os.path.basename(input_vector))[0]
output_temp_vector = repertory_temp + os.sep + vector_name + SUFFIX_TMP + extension_vector
output_smooth_vector = repertory_temp + os.sep + vector_name + SUFFIX_SMOOTH + extension_vector
vectors_temp_output_list.append(output_temp_vector)
xmin, xmax, ymin, ymax = getEmpriseFile(input_vector, format_vector)
projection = getProjection(input_vector, format_vector)
if projection is None:
projection = epsg
# Init GRASS
if debug >= 3:
print(cyan + "processTDCfilesSmoothAndFusion() : " + bold + green + "Initialisation de GRASS " + endC)
initializeGrass(repertory_temp, xmin, xmax, ymin, ymax, 1, 1, projection)
# Generalize GRASS
if debug >= 3:
print(cyan + "processTDCfilesSmoothAndFusion() : " + bold + green + "Applying smooth GRASS for vector : " + str(input_vector) + endC)
smoothGeomGrass(input_vector, output_smooth_vector, param_generalize_dico, format_vector, overwrite)
geometries2multigeometries(output_smooth_vector, output_temp_vector, name_column_fusion, format_vector)
# Init GRASS
if debug >= 3:
print(cyan + "processTDCfilesSmoothAndFusion() : " + bold + green + "Cloture de GRASS " + endC)
cleanGrass(repertory_temp)
if debug >= 3:
print(cyan + "processTDCfilesSmoothAndFusion() : " + bold + green + "Fusion de tous les vecteurs lissés : " + str(vectors_temp_output_list) + endC)
# Fusion de tous les fichiers vecteurs temp
fusionVectors(vectors_temp_output_list, vector_fusion, format_vector)
# Suppression du champ "cat" introduit par l'application GRASS
deleteFieldsVector(vector_fusion, vector_all_output, ["cat"], format_vector)
# Re-met à jour le champ id avec un increment
updateIndexVector(vector_all_output, "id", format_vector)
# Nettoyage des zones rocheuses sur la ligne de trait de côte
if vector_rocky_input != "" and vector_withrocky_output != "":
if debug >= 3:
print("\n" + cyan + "processTDCfilesSmoothAndFusion() : " + bold + green + "Creation d'un trait de côte generale sans les zones rocheuses : " + str(vector_withrocky_output) + endC)
differenceVector(vector_rocky_input, vector_all_output, vector_withrocky_output, overwrite, format_vector)
# Suppression des fichiers intermédiaires
if not save_results_intermediate :
if debug >= 3:
print(cyan + "processTDCfilesSmoothAndFusion() : " + bold + green + "Suppression des fichiers temporaires " + endC)
if os.path.exists(repertory_temp):
shutil.rmtree(repertory_temp)
removeVectorFile(vector_fusion)
print(endC)
print(bold + green + "## END : POST TRAITEMENT TDC" + endC)
print(endC)
# Mise à jour du Log
ending_event = "processTDCfilesSmoothAndFusion() : Create final coastline ending : "
timeLine(path_time_log,ending_event)
return
def occupationIndicator(classif_input,
mnh_input,
vector_grid_input,
vector_grid_output,
class_label_dico,
epsg,
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 = "occupationIndicator() : Calcul de l'indicateur occupation du sol/hauteur de végétation starting : "
timeLine(path_time_log, starting_event)
print(
bold + green +
"Début du calcul de l'indicateur 'occupation du sol/hauteur de végétation'."
+ endC + "\n")
if debug >= 3:
print(bold + green +
"occupationIndicator() : Variables dans la fonction" + endC)
print(cyan + "occupationIndicator() : " + endC + "classif_input : " +
str(classif_input) + endC)
print(cyan + "occupationIndicator() : " + endC + "mnh_input : " +
str(mnh_input) + endC)
print(cyan + "occupationIndicator() : " + endC +
"vector_grid_input : " + str(vector_grid_input) + endC)
print(cyan + "occupationIndicator() : " + endC +
"vector_grid_output : " + str(vector_grid_output) + endC)
print(cyan + "occupationIndicator() : " + endC +
"class_label_dico : " + str(class_label_dico) + endC)
print(cyan + "occupationIndicator() : " + endC + "epsg : " +
str(epsg) + endC)
print(cyan + "occupationIndicator() : " + endC + "path_time_log : " +
str(path_time_log) + endC)
print(cyan + "occupationIndicator() : " + endC + "format_raster : " +
str(format_raster) + endC)
print(cyan + "occupationIndicator() : " + endC + "format_vector : " +
str(format_vector) + endC)
print(cyan + "occupationIndicator() : " + endC +
"extension_raster : " + str(extension_raster) + endC)
print(cyan + "occupationIndicator() : " + endC +
"extension_vector : " + str(extension_vector) + endC)
print(cyan + "occupationIndicator() : " + endC +
"save_results_intermediate : " + str(save_results_intermediate) +
endC)
print(cyan + "occupationIndicator() : " + endC + "overwrite : " +
str(overwrite) + endC)
# Constante
FIELD_OCS_NAME = 'class_OCS'
FIELD_OCS_TYPE = ogr.OFTInteger
FIELD_MAJORITY_NAME = 'majority'
# Test si le vecteur de sortie existe déjà et si il doit être écrasés
check = os.path.isfile(vector_grid_output)
if check and not overwrite: # Si le fichier de sortie existent deja et que overwrite n'est pas activé
print(
bold + yellow +
"Le calcul de l'indicateur occupation du sol/hauteur de végétation a déjà eu lieu. \n"
+ endC)
print(bold + yellow + "Grid vector output : " + vector_grid_output +
" already exists and will not be created again." + endC)
else:
if check:
try:
removeVectorFile(vector_grid_output)
except Exception:
pass # si le fichier n'existe pas, il ne peut pas être supprimé : cette étape est ignorée
############################################
### Préparation générale des traitements ###
############################################
# Récuperation de la projection de l'image
epsg_proj = getProjectionImage(classif_input)
if epsg_proj == 0:
epsg_proj = epsg
# Liste des classes
key_class_label_list = list(class_label_dico.keys())
# Préparation des fichiers temporaires
temp_path = os.path.dirname(vector_grid_output) + os.sep + "TEMP_OCS"
# Nettoyage du repertoire temporaire si il existe
if os.path.exists(temp_path):
shutil.rmtree(temp_path)
os.makedirs(temp_path)
tempOCS = temp_path + os.sep + "occupation_du_sol" + extension_vector
tempHveg = temp_path + os.sep + "occupation_du_sol_hauteur_de_vegetation" + extension_vector
temp_class0 = temp_path + os.sep + "occupation_du_sol_hauteur_de_vegetation_class0" + extension_vector
temp_class1 = temp_path + os.sep + "occupation_du_sol_hauteur_de_vegetation_class1" + extension_vector
temp_class2 = temp_path + os.sep + "occupation_du_sol_hauteur_de_vegetation_class2" + extension_vector
temp_class3 = temp_path + os.sep + "occupation_du_sol_hauteur_de_vegetation_class3" + extension_vector
temp_class4 = temp_path + os.sep + "occupation_du_sol_hauteur_de_vegetation_class4" + extension_vector
vegetation_height_temp = temp_path + os.sep + "hauteur_vegetation_temp" + extension_raster
vegetation_height = temp_path + os.sep + "hauteur_vegetation" + extension_raster
##############################
### Calcul de l'indicateur ###
##############################
# Récupération de l'occupation du sol de chaque maille
statisticsVectorRaster(classif_input, vector_grid_input, tempOCS, 1,
True, True, False, [], [], class_label_dico,
path_time_log, True, format_vector,
save_results_intermediate, overwrite)
# Récupération de la hauteur moyenne et la hauteur max de la végétation de chaque maille
command = "otbcli_BandMath -il %s %s -out %s float -exp 'im1b1==%s ? im2b1 : 0'" % (
classif_input, mnh_input, vegetation_height_temp,
str(key_class_label_list[4]))
exit_code = os.system(command)
if exit_code != 0:
print(command)
print(
cyan + "occupationIndicator() : " + bold + red +
"!!! Une erreur c'est produite au cours de la commande otbcli_BandMath : "
+ command + ". Voir message d'erreur." + endC,
file=sys.stderr)
raise
command = "gdal_translate -a_srs EPSG:%s -a_nodata 0 -of %s %s %s" % (
str(epsg_proj), format_raster, vegetation_height_temp,
vegetation_height)
exit_code = os.system(command)
if exit_code != 0:
print(command)
print(
cyan + "occupationIndicator() : " + bold + red +
"!!! Une erreur c'est produite au cours de la comande : gdal_translate : "
+ command + ". Voir message d'erreur." + endC,
file=sys.stderr)
raise
statisticsVectorRaster(vegetation_height, tempOCS, tempHveg, 1, False,
False, True, [], [], {}, path_time_log, True,
format_vector, save_results_intermediate,
overwrite)
# Définir le nom des champs
temp_class_list = []
list_class_str = ""
for class_str in key_class_label_list:
list_class_str += "%s, " % (str(class_label_dico[class_str]))
built_str = class_label_dico[key_class_label_list[0]]
road_str = class_label_dico[key_class_label_list[1]]
water_str = class_label_dico[key_class_label_list[2]]
baresoil_str = class_label_dico[key_class_label_list[3]]
vegetation_str = class_label_dico[key_class_label_list[4]]
vegetation_height_medium_str = "H_moy_" + vegetation_str[0:3]
vegetation_height_max_str = "H_max_" + vegetation_str[0:3]
if debug >= 3:
print("built_str = " + built_str)
print("road_str = " + road_str)
print("water_str = " + water_str)
print("baresoil_str = " + baresoil_str)
print("vegetation_str = " + vegetation_str)
print("vegetation_height_medium_str = " +
vegetation_height_medium_str)
print("vegetation_height_max_str = " + vegetation_height_max_str)
column = "'ID, majority, minority, %s%s, %s, %s'" % (
list_class_str, vegetation_height_max_str,
vegetation_height_medium_str, FIELD_OCS_NAME)
# Ajout d'un champ renvoyant la classe d'OCS attribué à chaque polygone et renomer le champ 'mean'
renameFieldsVector(tempHveg, ['max'], [vegetation_height_max_str],
format_vector)
renameFieldsVector(tempHveg, ['mean'], [vegetation_height_medium_str],
format_vector)
addNewFieldVector(tempHveg, FIELD_OCS_NAME, FIELD_OCS_TYPE, 0, None,
None, format_vector)
# Attribution de la classe 0 => classe majoritaire de bâti ou route ou eau
#expression = "(" + built_str + " >= " + baresoil_str + " AND " + built_str + " >= " + vegetation_str + ") OR (" + road_str + " >= " + baresoil_str + " AND " + road_str + " >= " + vegetation_str + ") OR (" + water_str + " >= " + baresoil_str + " AND " + water_str + " >= " + vegetation_str + ")"
expression = "(" + FIELD_MAJORITY_NAME + " = '" + built_str + "') OR (" + FIELD_MAJORITY_NAME + " = '" + road_str + "') OR (" + FIELD_MAJORITY_NAME + " = '" + water_str + "')"
if debug >= 3:
print(expression)
ret = filterSelectDataVector(tempHveg, temp_class0, column, expression,
format_vector)
if not ret:
raise NameError(
cyan + "occupationIndicator() : " + bold + red +
"Attention problème lors du filtrage des BD vecteurs l'expression SQL %s est incorrecte"
% (expression) + endC)
updateFieldVector(temp_class0, FIELD_OCS_NAME, 0, format_vector)
temp_class_list.append(temp_class0)
# Attribution de la classe 1 => classe majoritaire de sol nu
#expression = "(" + baresoil_str + " > " + built_str + " AND " + baresoil_str + " > " + road_str + " AND " + baresoil_str + " > " + water_str + " AND " + baresoil_str + " >= " + vegetation_str + ")"
expression = "(" + FIELD_MAJORITY_NAME + " = '" + baresoil_str + "')"
if debug >= 3:
print(expression)
ret = filterSelectDataVector(tempHveg, temp_class1, column, expression,
format_vector)
if not ret:
raise NameError(
cyan + "occupationIndicator() : " + bold + red +
"Attention problème lors du filtrage des BD vecteurs l'expression SQL %s est incorrecte"
% (expression) + endC)
updateFieldVector(temp_class1, FIELD_OCS_NAME, 1, format_vector)
temp_class_list.append(temp_class1)
# Attribution de la classe 2 => classe majoritaire de végétation avec Hauteur inferieur à 1
#expression = "(" + vegetation_str + " > " + built_str + " AND " + vegetation_str + " > " + road_str + " AND " + vegetation_str + " > " + water_str + " AND " + vegetation_str + " > " + baresoil_str + ") AND (" + vegetation_height_medium_str + " < 1)"
expression = "(" + FIELD_MAJORITY_NAME + " = '" + vegetation_str + "') AND (" + vegetation_height_medium_str + " < 1)"
if debug >= 3:
print(expression)
ret = filterSelectDataVector(tempHveg, temp_class2, column, expression,
format_vector)
if not ret:
raise NameError(
cyan + "occupationIndicator() : " + bold + red +
"Attention problème lors du filtrage des BD vecteurs l'expression SQL %s est incorrecte"
% (expression) + endC)
updateFieldVector(temp_class2, FIELD_OCS_NAME, 2, format_vector)
temp_class_list.append(temp_class2)
# Attribution de la classe 3 => classe majoritaire de végétation avec Hauteur entre 1 et 5
#expression = "(" + vegetation_str + " > " + built_str + " AND " + vegetation_str + " > " + road_str + " AND " + vegetation_str + " > " + water_str + " AND " + vegetation_str + " > " + baresoil_str + ") AND (" + vegetation_height_medium_str + " >= 1 AND " + vegetation_height_medium_str + " < 5)"
expression = "(" + FIELD_MAJORITY_NAME + " = '" + vegetation_str + "') AND (" + vegetation_height_medium_str + " >= 1 AND " + vegetation_height_medium_str + " < 5)"
if debug >= 3:
print(expression)
ret = filterSelectDataVector(tempHveg, temp_class3, column, expression,
format_vector)
if not ret:
raise NameError(
cyan + "occupationIndicator() : " + bold + red +
"Attention problème lors du filtrage des BD vecteurs l'expression SQL %s est incorrecte"
% (expression) + endC)
updateFieldVector(temp_class3, FIELD_OCS_NAME, 3, format_vector)
temp_class_list.append(temp_class3)
# Attribution de la classe 4 => classe majoritaire de végétation avec Hauteur > 5
#expression = "(" + vegetation_str + " > " + built_str + " AND " + vegetation_str + " > " + road_str + " AND " + vegetation_str + " > " + water_str + " AND " + vegetation_str + " > " + baresoil_str + ") AND (" + vegetation_height_medium_str + " >= 5)"
expression = "(" + FIELD_MAJORITY_NAME + " = '" + vegetation_str + "') AND (" + vegetation_height_medium_str + " >= 5)"
if debug >= 3:
print(expression)
ret = filterSelectDataVector(tempHveg, temp_class4, column, expression,
format_vector)
if not ret:
raise NameError(
cyan + "occupationIndicator() : " + bold + red +
"Attention problème lors du filtrage des BD vecteurs l'expression SQL %s est incorrecte"
% (expression) + endC)
updateFieldVector(temp_class4, FIELD_OCS_NAME, 4, format_vector)
temp_class_list.append(temp_class4)
fusionVectors(temp_class_list, vector_grid_output, format_vector)
##########################################
### Nettoyage des fichiers temporaires ###
##########################################
if not save_results_intermediate:
if os.path.exists(temp_path):
shutil.rmtree(temp_path)
# Mise à jour du Log
print(
bold + green +
"Fin du calcul de l'indicateur 'occupation du sol/hauteur de végétation'."
+ endC + "\n")
ending_event = "occupationIndicator() : Calcul de l'indicateur occupation du sol/hauteur de végétation ending : "
timeLine(path_time_log, ending_event)
return
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 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
def selectSamples(image_input_list, sample_image_input, vector_output, table_statistics_output, sampler_strategy, select_ratio_floor, ratio_per_class_dico, name_column, no_data_value, path_time_log, rand_seed=0, ram_otb=0, epsg=2154, format_vector='ESRI Shapefile', extension_vector=".shp", save_results_intermediate=False, overwrite=True) :
# Mise à jour du Log
starting_event = "selectSamples() : Select points in raster mask macro input starting : "
timeLine(path_time_log, starting_event)
if debug >= 3:
print(cyan + "selectSamples() : " + endC + "image_input_list : " + str(image_input_list) + endC)
print(cyan + "selectSamples() : " + endC + "sample_image_input : " + str(sample_image_input) + endC)
print(cyan + "selectSamples() : " + endC + "vector_output : " + str(vector_output) + endC)
print(cyan + "selectSamples() : " + endC + "table_statistics_output : " + str(table_statistics_output) + endC)
print(cyan + "selectSamples() : " + endC + "sampler_strategy : " + str(sampler_strategy) + endC)
print(cyan + "selectSamples() : " + endC + "select_ratio_floor : " + str(select_ratio_floor) + endC)
print(cyan + "selectSamples() : " + endC + "ratio_per_class_dico : " + str(ratio_per_class_dico) + endC)
print(cyan + "selectSamples() : " + endC + "name_column : " + str(name_column) + endC)
print(cyan + "selectSamples() : " + endC + "no_data_value : " + str(no_data_value) + endC)
print(cyan + "selectSamples() : " + endC + "path_time_log : " + str(path_time_log) + endC)
print(cyan + "selectSamples() : " + endC + "rand_seed : " + str(rand_seed) + endC)
print(cyan + "selectSamples() : " + endC + "ram_otb : " + str(ram_otb) + endC)
print(cyan + "selectSamples() : " + endC + "epsg : " + str(epsg) + endC)
print(cyan + "selectSamples() : " + endC + "format_vector : " + str(format_vector) + endC)
print(cyan + "selectSamples() : " + endC + "extension_vector : " + str(extension_vector) + endC)
print(cyan + "selectSamples() : " + endC + "save_results_intermediate : " + str(save_results_intermediate) + endC)
print(cyan + "selectSamples() : " + endC + "overwrite : " + str(overwrite) + endC)
# Constantes
EXT_XML = ".xml"
SUFFIX_SAMPLE = "_sample"
SUFFIX_STATISTICS = "_statistics"
SUFFIX_POINTS = "_points"
SUFFIX_VALUE = "_value"
BAND_NAME = "band_"
COLUMN_CLASS = "class"
COLUMN_ORIGINFID = "originfid"
NB_POINTS = "nb_points"
AVERAGE = "average"
STANDARD_DEVIATION = "st_dev"
print(cyan + "selectSamples() : " + bold + green + "DEBUT DE LA SELECTION DE POINTS" + endC)
# Definition variables et chemins
repertory_output = os.path.dirname(vector_output)
filename = os.path.splitext(os.path.basename(vector_output))[0]
sample_points_output = repertory_output + os.sep + filename + SUFFIX_SAMPLE + extension_vector
file_statistic_points = repertory_output + os.sep + filename + SUFFIX_STATISTICS + SUFFIX_POINTS + EXT_XML
if debug >= 3:
print(cyan + "selectSamples() : " + endC + "file_statistic_points : " + str(file_statistic_points) + endC)
# 0. EXISTENCE DU FICHIER DE SORTIE
#----------------------------------
# Si le fichier vecteur points de sortie existe deja et que overwrite n'est pas activé
check = os.path.isfile(vector_output)
if check and not overwrite:
print(bold + yellow + "Samples points already done for file %s and will not be calculated again." %(vector_output) + endC)
else: # Si non ou si la vérification est désactivée : creation du fichier d'échantillons points
# Suppression de l'éventuel fichier existant
if check:
try:
removeVectorFile(vector_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
if os.path.isfile(table_statistics_output) :
try:
removeFile(table_statistics_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
# 1. STATISTIQUE SUR L'IMAGE DES ECHANTILLONS RASTEUR
#----------------------------------------------------
if debug >= 3:
print(cyan + "selectSamples() : " + bold + green + "Start statistique sur l'image des echantillons rasteur..." + endC)
id_micro_list = identifyPixelValues(sample_image_input)
if 0 in id_micro_list :
id_micro_list.remove(0)
min_micro_class_nb_points = -1
min_micro_class_label = 0
infoStructPointSource_dico = {}
writeTextFile(file_statistic_points, '<?xml version="1.0" ?>\n')
appendTextFileCR(file_statistic_points, '<GeneralStatistics>')
appendTextFileCR(file_statistic_points, ' <Statistic name="pointsPerClassRaw">')
if debug >= 2:
print("Nombre de points par micro classe :" + endC)
for id_micro in id_micro_list :
nb_pixels = countPixelsOfValue(sample_image_input, id_micro)
if debug >= 2:
print("MicroClass : " + str(id_micro) + ", nb_points = " + str(nb_pixels))
appendTextFileCR(file_statistic_points, ' <StatisticPoints class="%d" value="%d" />' %(id_micro, nb_pixels))
if min_micro_class_nb_points == -1 or min_micro_class_nb_points > nb_pixels :
min_micro_class_nb_points = nb_pixels
min_micro_class_label = id_micro
infoStructPointSource_dico[id_micro] = StructInfoMicoClass()
infoStructPointSource_dico[id_micro].label_class = id_micro
infoStructPointSource_dico[id_micro].nb_points = nb_pixels
infoStructPointSource_dico[id_micro].info_points_list = []
del nb_pixels
if debug >= 2:
print("MicroClass min points find : " + str(min_micro_class_label) + ", nb_points = " + str(min_micro_class_nb_points))
appendTextFileCR(file_statistic_points, ' </Statistic>')
pending_event = cyan + "selectSamples() : " + bold + green + "End statistique sur l'image des echantillons rasteur. " + endC
if debug >= 3:
print(pending_event)
timeLine(path_time_log,pending_event)
# 2. CHARGEMENT DE L'IMAGE DES ECHANTILLONS
#------------------------------------------
if debug >= 3:
print(cyan + "selectSamples() : " + bold + green + "Start chargement de l'image des echantillons..." + endC)
# Information image
cols, rows, bands = getGeometryImage(sample_image_input)
xmin, xmax, ymin, ymax = getEmpriseImage(sample_image_input)
pixel_width, pixel_height = getPixelWidthXYImage(sample_image_input)
projection_input = getProjectionImage(sample_image_input)
if projection_input == None or projection_input == 0 :
projection_input = epsg
else :
projection_input = int(projection_input)
pixel_width = abs(pixel_width)
pixel_height = abs(pixel_height)
# Lecture des données
raw_data = getRawDataImage(sample_image_input)
if debug >= 3:
print("projection = " + str(projection_input))
print("cols = " + str(cols))
print("rows = " + str(rows))
# Creation d'une structure dico contenent tous les points différents de zéro
progress = 0
pass_prog = False
for y_row in range(rows) :
for x_col in range(cols) :
value_class = raw_data[y_row][x_col]
if value_class != 0 :
infoStructPointSource_dico[value_class].info_points_list.append(x_col + (y_row * cols))
# Barre de progression
if debug >= 4:
if ((float(y_row) / rows) * 100.0 > progress) and not pass_prog :
progress += 1
pass_prog = True
print("Progression => " + str(progress) + "%")
if ((float(y_row) / rows) * 100.0 > progress + 1) :
pass_prog = False
del raw_data
pending_event = cyan + "selectSamples() : " + bold + green + "End chargement de l'image des echantillons. " + endC
if debug >= 3:
print(pending_event)
timeLine(path_time_log,pending_event)
# 3. SELECTION DES POINTS D'ECHANTILLON
#--------------------------------------
if debug >= 3:
print(cyan + "selectSamples() : " + bold + green + "Start selection des points d'echantillon..." + endC)
appendTextFileCR(file_statistic_points, ' <Statistic name="pointsPerClassSelect">')
# Rendre deterministe la fonction aléatoire de random.sample
if rand_seed > 0:
random.seed( rand_seed )
# Pour toute les micro classes
for id_micro in id_micro_list :
# Selon la stategie de selection
nb_points_ratio = 0
while switch(sampler_strategy.lower()):
if case('all'):
# Le mode de selection 'all' est choisi
nb_points_ratio = infoStructPointSource_dico[id_micro].nb_points
infoStructPointSource_dico[id_micro].sample_points_list = range(nb_points_ratio)
break
if case('percent'):
# Le mode de selection 'percent' est choisi
id_macro_class = int(math.floor(id_micro / 100) * 100)
select_ratio_class = ratio_per_class_dico[id_macro_class]
nb_points_ratio = int(infoStructPointSource_dico[id_micro].nb_points * select_ratio_class / 100)
infoStructPointSource_dico[id_micro].sample_points_list = random.sample(range(infoStructPointSource_dico[id_micro].nb_points), nb_points_ratio)
break
if case('mixte'):
# Le mode de selection 'mixte' est choisi
nb_points_ratio = int(infoStructPointSource_dico[id_micro].nb_points * select_ratio_floor / 100)
if id_micro == min_micro_class_label :
# La plus petite micro classe est concervée intégralement
infoStructPointSource_dico[id_micro].sample_points_list = range(infoStructPointSource_dico[id_micro].nb_points)
nb_points_ratio = min_micro_class_nb_points
elif nb_points_ratio <= min_micro_class_nb_points :
# Les micro classes dont le ratio de selection est inferieur au nombre de points de la plus petite classe sont égement conservées intégralement
infoStructPointSource_dico[id_micro].sample_points_list = random.sample(range(infoStructPointSource_dico[id_micro].nb_points), min_micro_class_nb_points)
nb_points_ratio = min_micro_class_nb_points
else :
# Pour toutes les autres micro classes tirage aleatoire d'un nombre de points correspondant au ratio
infoStructPointSource_dico[id_micro].sample_points_list = random.sample(range(infoStructPointSource_dico[id_micro].nb_points), nb_points_ratio)
break
break
if debug >= 2:
print("MicroClass = " + str(id_micro) + ", nb_points_ratio " + str(nb_points_ratio))
appendTextFileCR(file_statistic_points, ' <StatisticPoints class="%d" value="%d" />' %(id_micro, nb_points_ratio))
appendTextFileCR(file_statistic_points, ' </Statistic>')
appendTextFileCR(file_statistic_points, '</GeneralStatistics>')
pending_event = cyan + "selectSamples() : " + bold + green + "End selection des points d'echantillon. " + endC
if debug >= 3:
print(pending_event)
timeLine(path_time_log,pending_event)
# 4. PREPARATION DES POINTS D'ECHANTILLON
#----------------------------------------
if debug >= 3:
print(cyan + "selectSamples() : " + bold + green + "Start preparation des points d'echantillon..." + endC)
# Création du dico de points
points_random_value_dico = {}
index_dico_point = 0
for micro_class in infoStructPointSource_dico :
micro_class_struct = infoStructPointSource_dico[micro_class]
label_class = micro_class_struct.label_class
point_attr_dico = {name_column:int(label_class), COLUMN_CLASS:int(label_class), COLUMN_ORIGINFID:0}
for id_point in micro_class_struct.sample_points_list:
# Recuperer les valeurs des coordonnees des points
coor_x = float(xmin + (int(micro_class_struct.info_points_list[id_point] % cols) * pixel_width)) + (pixel_width / 2.0)
coor_y = float(ymax - (int(micro_class_struct.info_points_list[id_point] / cols) * pixel_height)) - (pixel_height / 2.0)
points_random_value_dico[index_dico_point] = [[coor_x, coor_y], point_attr_dico]
del coor_x
del coor_y
index_dico_point += 1
del point_attr_dico
del infoStructPointSource_dico
pending_event = cyan + "selectSamples() : " + bold + green + "End preparation des points d'echantillon. " + endC
if debug >=3:
print(pending_event)
timeLine(path_time_log,pending_event)
# 5. CREATION DU FICHIER SHAPE DE POINTS D'ECHANTILLON
#-----------------------------------------------------
if debug >= 3:
print(cyan + "selectSamples() : " + bold + green + "Start creation du fichier shape de points d'echantillon..." + endC)
# Définir les attibuts du fichier résultat
attribute_dico = {name_column:ogr.OFTInteger, COLUMN_CLASS:ogr.OFTInteger, COLUMN_ORIGINFID:ogr.OFTInteger}
# Creation du fichier shape
createPointsFromCoordList(attribute_dico, points_random_value_dico, sample_points_output, projection_input, format_vector)
del attribute_dico
del points_random_value_dico
pending_event = cyan + "selectSamples() : " + bold + green + "End creation du fichier shape de points d'echantillon. " + endC
if debug >=3:
print(pending_event)
timeLine(path_time_log,pending_event)
# 6. EXTRACTION DES POINTS D'ECHANTILLONS
#-----------------------------------------
if debug >= 3:
print(cyan + "selectSamples() : " + bold + green + "Start extraction des points d'echantillon dans l'image..." + endC)
# Cas ou l'on a une seule image
if len(image_input_list) == 1:
# Extract sample
image_input = image_input_list[0]
command = "otbcli_SampleExtraction -in %s -vec %s -outfield prefix -outfield.prefix.name %s -out %s -field %s" %(image_input, sample_points_output, BAND_NAME, vector_output, name_column)
if ram_otb > 0:
command += " -ram %d" %(ram_otb)
if debug >= 3:
print(command)
exitCode = os.system(command)
if exitCode != 0:
raise NameError(cyan + "selectSamples() : " + bold + red + "An error occured during otbcli_SampleExtraction command. See error message above." + endC)
# Cas de plusieurs imagettes
else :
# Le repertoire de sortie
repertory_output = os.path.dirname(vector_output)
# Initialisation de la liste pour le multi-threading et la liste de l'ensemble des echantions locaux
thread_list = []
vector_local_output_list = []
# Obtenir l'emprise des images d'entrées pour redecouper le vecteur d'echantillon d'apprentissage pour chaque image
for image_input in image_input_list :
# Definition des fichiers sur emprise local
file_name = os.path.splitext(os.path.basename(image_input))[0]
emprise_local_sample = repertory_output + os.sep + file_name + SUFFIX_SAMPLE + extension_vector
vector_sample_local_output = repertory_output + os.sep + file_name + SUFFIX_VALUE + extension_vector
vector_local_output_list.append(vector_sample_local_output)
# Gestion sans thread...
#SampleLocalExtraction(image_input, sample_points_output, emprise_local_sample, vector_sample_local_output, name_column, BAND_NAME, ram_otb, format_vector, extension_vector, save_results_intermediate)
# Gestion du multi threading
thread = threading.Thread(target=SampleLocalExtraction, args=(image_input, sample_points_output, emprise_local_sample, vector_sample_local_output, name_column, BAND_NAME, ram_otb, format_vector, extension_vector, save_results_intermediate))
thread.start()
thread_list.append(thread)
# Extraction des echantions points des images
try:
for thread in thread_list:
thread.join()
except:
print(cyan + "selectSamples() : " + bold + red + "Erreur lors de l'éextaction des valeurs d'echantion : impossible de demarrer le thread" + endC, file=sys.stderr)
# Fusion des multi vecteurs de points contenant les valeurs des bandes de l'image
fusionVectors(vector_local_output_list, vector_output, format_vector)
# Clean des vecteurs point sample local file
for vector_sample_local_output in vector_local_output_list :
removeVectorFile(vector_sample_local_output)
if debug >= 3:
print(cyan + "selectSamples() : " + bold + green + "End extraction des points d'echantillon dans l'image." + endC)
# 7. CALCUL DES STATISTIQUES SUR LES VALEURS DES POINTS D'ECHANTILLONS SELECTIONNEES
#-----------------------------------------------------------------------------------
if debug >= 3:
print(cyan + "selectSamples() : " + bold + green + "Start calcul des statistiques sur les valeurs des points d'echantillons selectionnees..." + endC)
# Si le calcul des statistiques est demandé presence du fichier stat
if table_statistics_output != "":
# On récupère la liste de données
pending_event = cyan + "selectSamples() : " + bold + green + "Encours calcul des statistiques part1... " + endC
if debug >=4:
print(pending_event)
timeLine(path_time_log,pending_event)
attribute_name_dico = {}
name_field_value_list = []
names_attribut_list = getAttributeNameList(vector_output, format_vector)
if debug >=4:
print("names_attribut_list = " + str(names_attribut_list))
attribute_name_dico[name_column] = ogr.OFTInteger
for name_attribut in names_attribut_list :
if BAND_NAME in name_attribut :
attribute_name_dico[name_attribut] = ogr.OFTReal
name_field_value_list.append(name_attribut)
name_field_value_list.sort()
res_values_dico = getAttributeValues(vector_output, None, None, attribute_name_dico, format_vector)
del attribute_name_dico
# Trie des données par identifiant micro classes
pending_event = cyan + "selectSamples() : " + bold + green + "Encours calcul des statistiques part2... " + endC
if debug >=4:
print(pending_event)
timeLine(path_time_log,pending_event)
data_value_by_micro_class_dico = {}
stat_by_micro_class_dico = {}
# Initilisation du dico complexe
for id_micro in id_micro_list :
data_value_by_micro_class_dico[id_micro] = {}
stat_by_micro_class_dico[id_micro] = {}
for name_field_value in res_values_dico :
if name_field_value != name_column :
data_value_by_micro_class_dico[id_micro][name_field_value] = []
stat_by_micro_class_dico[id_micro][name_field_value] = {}
stat_by_micro_class_dico[id_micro][name_field_value][AVERAGE] = 0.0
stat_by_micro_class_dico[id_micro][name_field_value][STANDARD_DEVIATION] = 0.0
# Trie des valeurs
pending_event = cyan + "selectSamples() : " + bold + green + "Encours calcul des statistiques part3... " + endC
if debug >=4:
print(pending_event)
timeLine(path_time_log,pending_event)
for index in range(len(res_values_dico[name_column])) :
id_micro = res_values_dico[name_column][index]
for name_field_value in name_field_value_list :
data_value_by_micro_class_dico[id_micro][name_field_value].append(res_values_dico[name_field_value][index])
del res_values_dico
# Calcul des statistiques
pending_event = cyan + "selectSamples() : " + bold + green + "Encours calcul des statistiques part4... " + endC
if debug >=4:
print(pending_event)
timeLine(path_time_log,pending_event)
for id_micro in id_micro_list :
for name_field_value in name_field_value_list :
try :
stat_by_micro_class_dico[id_micro][name_field_value][AVERAGE] = average(data_value_by_micro_class_dico[id_micro][name_field_value])
except:
stat_by_micro_class_dico[id_micro][name_field_value][AVERAGE] = 0
try :
stat_by_micro_class_dico[id_micro][name_field_value][STANDARD_DEVIATION] = standardDeviation(data_value_by_micro_class_dico[id_micro][name_field_value])
except:
stat_by_micro_class_dico[id_micro][name_field_value][STANDARD_DEVIATION] = 0
try :
stat_by_micro_class_dico[id_micro][name_field_value][NB_POINTS] = len(data_value_by_micro_class_dico[id_micro][name_field_value])
except:
stat_by_micro_class_dico[id_micro][name_field_value][NB_POINTS] = 0
del data_value_by_micro_class_dico
# Creation du fichier statistique .csv
pending_event = cyan + "selectSamples() : " + bold + green + "Encours calcul des statistiques part5... " + endC
if debug >= 4:
print(pending_event)
timeLine(path_time_log,pending_event)
text_csv = " Micro classes ; Champs couche image ; Nombre de points ; Moyenne ; Ecart type \n"
writeTextFile(table_statistics_output, text_csv)
for id_micro in id_micro_list :
for name_field_value in name_field_value_list :
# Ecriture du fichier
text_csv = " %d " %(id_micro)
text_csv += " ; %s" %(name_field_value)
text_csv += " ; %d" %(stat_by_micro_class_dico[id_micro][name_field_value][NB_POINTS])
text_csv += " ; %f" %(stat_by_micro_class_dico[id_micro][name_field_value][AVERAGE])
text_csv += " ; %f" %(stat_by_micro_class_dico[id_micro][name_field_value][STANDARD_DEVIATION])
appendTextFileCR(table_statistics_output, text_csv)
del name_field_value_list
else :
if debug >=3:
print(cyan + "selectSamples() : " + bold + green + "Pas de calcul des statistiques sur les valeurs des points demander!!!." + endC)
del id_micro_list
pending_event = cyan + "selectSamples() : " + bold + green + "End calcul des statistiques sur les valeurs des points d'echantillons selectionnees. " + endC
if debug >= 3:
print(pending_event)
timeLine(path_time_log,pending_event)
# 8. SUPRESSION DES FICHIERS INTERMEDIAIRES
#------------------------------------------
if not save_results_intermediate:
if os.path.isfile(sample_points_output) :
removeVectorFile(sample_points_output)
print(cyan + "selectSamples() : " + bold + green + "FIN DE LA SELECTION DE POINTS" + endC)
# Mise à jour du Log
ending_event = "selectSamples() : Select points in raster mask macro input ending : "
timeLine(path_time_log,ending_event)
return
