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Nathancoisne authoredNathancoisne authored
5_Synthetic measures from agents' travels.gaml 21.71 KiB
/**
* Name: Deplacementdevelos
* Based on the internal empty template.
* Author: nathancoisne
* Tags:
*/
model Deplacementdevelos
/*
* This model generates pollution measures from the trips generated by 'travel agents'. Pollution data are extracted from a hourly pollution model from AtmoSud (date: 27/05/2021)
*
*/
global {
file bound <- shape_file("../includes/Marseille/boundary_Marseille.shp");
bool workers <- false; // une seule population en 'true' à la fois pour le stockage des mesures par type d'agent
bool students <- false;
bool leisures <- true;
bool measure_NO2 <- true;
bool measure_O3 <- true;
bool measure_PM10 <- true;
bool measure_PM25 <- true;
geometry shape <- envelope(bound);
// coordonees des rasters de pollution
float min_x <- 889462.50000;
float min_y <- 6236287.50000;
float max_x <- 905062.50000;
float max_y <- 6254412.50000;
int compteur_ID <- 0;
init{
// mise en mémoire du cube de pollution NO2, O3, PM10, PM25 (24 rasters horaires)
list<matrix<float>> NO2_rasters;
list<matrix<float>> O3_rasters;
list<matrix<float>> PM10_rasters;
list<matrix<float>> PM25_rasters;
if measure_NO2 {
// raster heure 0 manquant pour la journée du 27
matrix<float> pollution_raster_float <- 0.0 as_matrix({624, 725});
NO2_rasters << pollution_raster_float;
loop i from: 1 to: 23{
string path_grid;
if (i < 10){
path_grid <- '../includes/Marseille/pollution_model/raster_dep13_NO2_202105270' + i + '_202105270' + i + '.tif';
}
else{
path_grid <- '../includes/Marseille/pollution_model/raster_dep13_NO2_20210527' + i + '_20210527' + i + '.tif';
}
matrix my_data <- grid_file(path_grid) as_matrix({624, 725});
matrix<float> pollution_raster_float <- 0.0 as_matrix({624, 725});
loop j from: 0 to: 623{
loop k from: 0 to: 724{
pollution_raster_float[j, k] <- float (my_data[j, k] get("grid_value"));
}
}
write ('raster NO2 ' + i + ' chargé');
write('max: ' + max(pollution_raster_float));
NO2_rasters << pollution_raster_float;
}
}
if measure_O3 {
matrix<float> pollution_raster_float <- 0.0 as_matrix({624, 725});
O3_rasters << pollution_raster_float;
loop i from: 1 to: 23{
string path_grid;
if (i < 10){
path_grid <- '../includes/Marseille/pollution_model/raster_dep13_O3_202105270' + i + '_202105270' + i + '.tif';
}
else{
path_grid <- '../includes/Marseille/pollution_model/raster_dep13_O3_20210527' + i + '_20210527' + i + '.tif';
}
matrix my_data <- grid_file(path_grid) as_matrix({624, 725});
matrix<float> pollution_raster_float <- 0.0 as_matrix({624, 725});
loop j from: 0 to: 623{
loop k from: 0 to: 724{
pollution_raster_float[j, k] <- float (my_data[j, k] get("grid_value"));
}
}
write ('raster O3 ' + i + ' chargé');
write('max: ' + max(pollution_raster_float));
O3_rasters << pollution_raster_float;
}
}
if measure_PM10 {
matrix<float> pollution_raster_float <- 0.0 as_matrix({624, 725});
PM10_rasters << pollution_raster_float;
loop i from: 1 to: 23{
string path_grid;
if (i < 10){
path_grid <- '../includes/Marseille/pollution_model/raster_dep13_PM10_202105270' + i + '_202105270' + i + '.tif';
}
else{
path_grid <- '../includes/Marseille/pollution_model/raster_dep13_PM10_20210527' + i + '_20210527' + i + '.tif';
}
matrix my_data <- grid_file(path_grid) as_matrix({624, 725});
matrix<float> pollution_raster_float <- 0.0 as_matrix({624, 725});
loop j from: 0 to: 623{
loop k from: 0 to: 724{
pollution_raster_float[j, k] <- float (my_data[j, k] get("grid_value"));
}
}
write ('raster PM10 ' + i + ' chargé');
write('max: ' + max(pollution_raster_float));
PM10_rasters << pollution_raster_float;
}
}
if measure_PM25 {
matrix<float> pollution_raster_float <- 0.0 as_matrix({624, 725});
PM25_rasters << pollution_raster_float;
loop i from: 1 to: 23{
string path_grid;
if (i < 10){
path_grid <- '../includes/Marseille/pollution_model/raster_dep13_PM25_202105270' + i + '_202105270' + i + '.tif';
}
else{
path_grid <- '../includes/Marseille/pollution_model/raster_dep13_PM25_20210527' + i + '_20210527' + i + '.tif';
}
matrix my_data <- grid_file(path_grid) as_matrix({624, 725});
matrix<float> pollution_raster_float <- 0.0 as_matrix({624, 725});
loop j from: 0 to: 623{
loop k from: 0 to: 724{
pollution_raster_float[j, k] <- float (my_data[j, k] get("grid_value"));
}
}
write ('raster PM25 ' + i + ' chargé');
write('max: ' + max(pollution_raster_float));
PM25_rasters << pollution_raster_float;
}
}
// generation des donnees de pollution pour chaque type d'agent
if workers{
write("generating workers measures");
create measure from: shape_file("../results/Marseille/worker/aller_worker/positions_aller_worker.shp") with: [time_of_measure::(read("time")), name_of_agent::(read('agent'))]{
int worker_number <- int((((name_of_agent split_with '[')[1]) split_with ']')[0]);
write(worker_number);
if (worker_number > 3000){do die;} // on calcule les mesures faites pour une majorité d'agent. le reste servira de test aux prédictions faites à partir de ces mesures
ID <- compteur_ID;
compteur_ID <- compteur_ID + 1;
geometry CRS_2154 <- location CRS_transform("EPSG:2154");
list<string> coord <- string(CRS_2154) split_with ",";
latitude <- float(coord[1]);
longitude <- float((coord[0] split_with "{")[0]);
int cell_x <- int((longitude - min_x) / 25);
int cell_y <- int((max_y - latitude) / 25);
// obtention de la concentration de polluant : interpolation linéaire entre les deux rasters horaires qui 'encadrent' l'heure de mesure
int hour_before_measure <- time_of_measure.hour;
int hour_after_measure <- hour_before_measure + 1;
int min_measure <- time_of_measure.minute; int sec_measure <- time_of_measure.second;
if measure_NO2 {
NO2_concentration <- NO2_rasters[hour_before_measure][cell_x,cell_y] +
(NO2_rasters[hour_after_measure][cell_x,cell_y] - NO2_rasters[hour_before_measure][cell_x,cell_y]) * (min_measure * 60 + sec_measure) / 3600;
}
if measure_O3 {
O3_concentration <- O3_rasters[hour_before_measure][cell_x,cell_y] +
(O3_rasters[hour_after_measure][cell_x,cell_y] - O3_rasters[hour_before_measure][cell_x,cell_y]) * (min_measure * 60 + sec_measure) / 3600;
}
if measure_PM10 {
PM10_concentration <- PM10_rasters[hour_before_measure][cell_x,cell_y] +
(PM10_rasters[hour_after_measure][cell_x,cell_y] - PM10_rasters[hour_before_measure][cell_x,cell_y]) * (min_measure * 60 + sec_measure) / 3600;
}
if measure_PM25 {
PM25_concentration <- PM25_rasters[hour_before_measure][cell_x,cell_y] +
(PM25_rasters[hour_after_measure][cell_x,cell_y] - PM25_rasters[hour_before_measure][cell_x,cell_y]) * (min_measure * 60 + sec_measure) / 3600;
}
save [ID, name_of_agent, longitude, latitude, time_of_measure, NO2_concentration, O3_concentration, PM10_concentration, PM25_concentration]
to: "../results/Marseille/worker/workers_measures.csv" type:"csv" rewrite: false;
}
ask measure{do die;}
create measure from: shape_file("../results/Marseille/worker/retour_worker/positions_retour_worker.shp") with: [time_of_measure::(read("time")), name_of_agent::(read('agent'))]{
int worker_number <- int((((name_of_agent split_with '[')[1]) split_with ']')[0]);
write(worker_number);
if (worker_number > 3000){do die;} // on calcule les mesures faites pour une majorité d'agent. le reste servira de test aux prédictions faites à partir de ces mesures
ID <- compteur_ID;
compteur_ID <- compteur_ID + 1;
geometry CRS_2154 <- location CRS_transform("EPSG:2154");
list<string> coord <- string(CRS_2154) split_with ",";
latitude <- float(coord[1]);
longitude <- float((coord[0] split_with "{")[0]);
int cell_x <- int((longitude - min_x) / 25);
int cell_y <- int((max_y - latitude) / 25);
// obtention de la concentration de polluant : interpolation linéaire entre les deux rasters horaires qui 'encadrent' l'heure de mesure
int hour_before_measure <- time_of_measure.hour;
int hour_after_measure <- hour_before_measure + 1;
int min_measure <- time_of_measure.minute;
int sec_measure <- time_of_measure.second;
if measure_NO2 {
NO2_concentration <- NO2_rasters[hour_before_measure][cell_x,cell_y] +
(NO2_rasters[hour_after_measure][cell_x,cell_y] - NO2_rasters[hour_before_measure][cell_x,cell_y]) * (min_measure * 60 + sec_measure) / 3600;
}
if measure_O3 {
O3_concentration <- O3_rasters[hour_before_measure][cell_x,cell_y] +
(O3_rasters[hour_after_measure][cell_x,cell_y] - O3_rasters[hour_before_measure][cell_x,cell_y]) * (min_measure * 60 + sec_measure) / 3600;
}
if measure_PM10 {
PM10_concentration <- PM10_rasters[hour_before_measure][cell_x,cell_y] +
(PM10_rasters[hour_after_measure][cell_x,cell_y] - PM10_rasters[hour_before_measure][cell_x,cell_y]) * (min_measure * 60 + sec_measure) / 3600;
}
if measure_PM25 {
PM25_concentration <- PM25_rasters[hour_before_measure][cell_x,cell_y] +
(PM25_rasters[hour_after_measure][cell_x,cell_y] - PM25_rasters[hour_before_measure][cell_x,cell_y]) * (min_measure * 60 + sec_measure) / 3600;
}
save [ID, name_of_agent, longitude, latitude, time_of_measure, NO2_concentration, O3_concentration, PM10_concentration, PM25_concentration]
to: "../results/Marseille/worker/workers_measures.csv" type:"csv" rewrite: false;
}
ask measure{do die;}
}
if students{
write("generating students measures");
create measure from: shape_file("../results/Marseille/student/aller_student/positions_aller_student.shp") with: [time_of_measure::(read("time")), name_of_agent::(read('agent'))]{
int student_number <- int((((name_of_agent split_with '[')[1]) split_with ']')[0]);
write(student_number);
if (student_number > 1800){do die;} // on calcule les mesures faites pour une majorité d'agent. le reste servira de test aux prédictions faites à partir de ces mesures
ID <- compteur_ID;
compteur_ID <- compteur_ID + 1;
geometry CRS_2154 <- location CRS_transform("EPSG:2154");
list<string> coord <- string(CRS_2154) split_with ",";
latitude <- float(coord[1]);
longitude <- float((coord[0] split_with "{")[0]);
int cell_x <- int((longitude - min_x) / 25);
int cell_y <- int((max_y - latitude) / 25);
// obtention de la concentration de polluant : interpolation linéaire entre les deux rasters horaires qui 'encadrent' l'heure de mesure
int hour_before_measure <- time_of_measure.hour;
int hour_after_measure <- hour_before_measure + 1;
int min_measure <- time_of_measure.minute;
int sec_measure <- time_of_measure.second;
if measure_NO2 {
NO2_concentration <- NO2_rasters[hour_before_measure][cell_x,cell_y] +
(NO2_rasters[hour_after_measure][cell_x,cell_y] - NO2_rasters[hour_before_measure][cell_x,cell_y]) * (min_measure * 60 + sec_measure) / 3600;
}
if measure_O3 {
O3_concentration <- O3_rasters[hour_before_measure][cell_x,cell_y] +
(O3_rasters[hour_after_measure][cell_x,cell_y] - O3_rasters[hour_before_measure][cell_x,cell_y]) * (min_measure * 60 + sec_measure) / 3600;
}
if measure_PM10 {
PM10_concentration <- PM10_rasters[hour_before_measure][cell_x,cell_y] +
(PM10_rasters[hour_after_measure][cell_x,cell_y] - PM10_rasters[hour_before_measure][cell_x,cell_y]) * (min_measure * 60 + sec_measure) / 3600;
}
if measure_PM25 {
PM25_concentration <- PM25_rasters[hour_before_measure][cell_x,cell_y] +
(PM25_rasters[hour_after_measure][cell_x,cell_y] - PM25_rasters[hour_before_measure][cell_x,cell_y]) * (min_measure * 60 + sec_measure) / 3600;
}
save [ID, name_of_agent, longitude, latitude, time_of_measure, NO2_concentration, O3_concentration, PM10_concentration, PM25_concentration]
to: "../results/Marseille/student/students_measures.csv" type:"csv" rewrite: false;
}
ask measure{do die;}
create measure from: shape_file("../results/Marseille/student/retour_student/positions_retour_student.shp") with: [time_of_measure::(read("time")), name_of_agent::(read('agent'))]{
int student_number <- int((((name_of_agent split_with '[')[1]) split_with ']')[0]);
write(student_number);
if (student_number > 1800){do die;} // on calcule les mesures faites pour une majorité d'agent. le reste servira de test aux prédictions faites à partir de ces mesures
ID <- compteur_ID;
compteur_ID <- compteur_ID + 1;
geometry CRS_2154 <- location CRS_transform("EPSG:2154");
list<string> coord <- string(CRS_2154) split_with ",";
latitude <- float(coord[1]);
longitude <- float((coord[0] split_with "{")[0]);
int cell_x <- int((longitude - min_x) / 25);
int cell_y <- int((max_y - latitude) / 25);
// obtention de la concentration de polluant : interpolation linéaire entre les deux rasters horaires qui 'encadrent' l'heure de mesure
int hour_before_measure <- time_of_measure.hour;
int hour_after_measure <- hour_before_measure + 1;
int min_measure <- time_of_measure.minute;
int sec_measure <- time_of_measure.second;
if measure_NO2 {
NO2_concentration <- NO2_rasters[hour_before_measure][cell_x,cell_y] +
(NO2_rasters[hour_after_measure][cell_x,cell_y] - NO2_rasters[hour_before_measure][cell_x,cell_y]) * (min_measure * 60 + sec_measure) / 3600;
}
if measure_O3 {
O3_concentration <- O3_rasters[hour_before_measure][cell_x,cell_y] +
(O3_rasters[hour_after_measure][cell_x,cell_y] - O3_rasters[hour_before_measure][cell_x,cell_y]) * (min_measure * 60 + sec_measure) / 3600;
}
if measure_PM10 {
PM10_concentration <- PM10_rasters[hour_before_measure][cell_x,cell_y] +
(PM10_rasters[hour_after_measure][cell_x,cell_y] - PM10_rasters[hour_before_measure][cell_x,cell_y]) * (min_measure * 60 + sec_measure) / 3600;
}
if measure_PM25 {
PM25_concentration <- PM25_rasters[hour_before_measure][cell_x,cell_y] +
(PM25_rasters[hour_after_measure][cell_x,cell_y] - PM25_rasters[hour_before_measure][cell_x,cell_y]) * (min_measure * 60 + sec_measure) / 3600;
}
save [ID, name_of_agent, longitude, latitude, time_of_measure, NO2_concentration, O3_concentration, PM10_concentration, PM25_concentration]
to: "../results/Marseille/student/students_measures.csv" type:"csv" rewrite: false;
}
ask measure{do die;}
}
if leisures{
write("generating leisures measures");
create measure from: shape_file("../results/Marseille/leisure/aller_leisure/positions_aller_leisure.shp") with: [time_of_measure::(read("time")), name_of_agent::(read('agent'))]{
int leisure_number <- int((((name_of_agent split_with '[')[1]) split_with ']')[0]);
write(leisure_number);
if (leisure_number > 6200){do die;} // on calcule les mesures faites pour une majorité d'agent. le reste servira de test aux prédictions faites à partir de ces mesures
ID <- compteur_ID;
compteur_ID <- compteur_ID + 1;
geometry CRS_2154 <- location CRS_transform("EPSG:2154");
list<string> coord <- string(CRS_2154) split_with ",";
latitude <- float(coord[1]);
longitude <- float((coord[0] split_with "{")[0]);
int cell_x <- int((longitude - min_x) / 25);
int cell_y <- int((max_y - latitude) / 25);
// obtention de la concentration de polluant : interpolation linéaire entre les deux rasters horaires qui 'encadrent' l'heure de mesure
int hour_before_measure <- time_of_measure.hour;
int hour_after_measure <- hour_before_measure + 1;
int min_measure <- time_of_measure.minute;
int sec_measure <- time_of_measure.second;
if measure_NO2 {
NO2_concentration <- NO2_rasters[hour_before_measure][cell_x,cell_y] +
(NO2_rasters[hour_after_measure][cell_x,cell_y] - NO2_rasters[hour_before_measure][cell_x,cell_y]) * (min_measure * 60 + sec_measure) / 3600;
}
if measure_O3 {
O3_concentration <- O3_rasters[hour_before_measure][cell_x,cell_y] +
(O3_rasters[hour_after_measure][cell_x,cell_y] - O3_rasters[hour_before_measure][cell_x,cell_y]) * (min_measure * 60 + sec_measure) / 3600;
}
if measure_PM10 {
PM10_concentration <- PM10_rasters[hour_before_measure][cell_x,cell_y] +
(PM10_rasters[hour_after_measure][cell_x,cell_y] - PM10_rasters[hour_before_measure][cell_x,cell_y]) * (min_measure * 60 + sec_measure) / 3600;
}
if measure_PM25 {
PM25_concentration <- PM25_rasters[hour_before_measure][cell_x,cell_y] +
(PM25_rasters[hour_after_measure][cell_x,cell_y] - PM25_rasters[hour_before_measure][cell_x,cell_y]) * (min_measure * 60 + sec_measure) / 3600;
}
save [ID, name_of_agent, longitude, latitude, time_of_measure, NO2_concentration, O3_concentration, PM10_concentration, PM25_concentration]
to: "../results/Marseille/leisure/leisures_measures.csv" type:"csv" rewrite: false;
}
ask measure{do die;}
create measure from: shape_file("../results/Marseille/leisure/retour_leisure/positions_retour_leisure.shp") with: [time_of_measure::(read("time")), name_of_agent::(read('agent'))]{
int leisure_number <- int((((name_of_agent split_with '[')[1]) split_with ']')[0]);
write(leisure_number);
if (leisure_number > 6200){do die;} // on calcule les mesures faites pour une majorité d'agent. le reste servira de test aux prédictions faites à partir de ces mesures
ID <- compteur_ID;
compteur_ID <- compteur_ID + 1;
geometry CRS_2154 <- location CRS_transform("EPSG:2154");
list<string> coord <- string(CRS_2154) split_with ",";
latitude <- float(coord[1]);
longitude <- float((coord[0] split_with "{")[0]);
int cell_x <- int((longitude - min_x) / 25);
int cell_y <- int((max_y - latitude) / 25);
// obtention de la concentration de polluant : interpolation linéaire entre les deux rasters horaires qui 'encadrent' l'heure de mesure
int hour_before_measure <- time_of_measure.hour;
int hour_after_measure <- hour_before_measure + 1;
int min_measure <- time_of_measure.minute;
int sec_measure <- time_of_measure.second;
if measure_NO2 {
NO2_concentration <- NO2_rasters[hour_before_measure][cell_x,cell_y] +
(NO2_rasters[hour_after_measure][cell_x,cell_y] - NO2_rasters[hour_before_measure][cell_x,cell_y]) * (min_measure * 60 + sec_measure) / 3600;
}
if measure_O3 {
O3_concentration <- O3_rasters[hour_before_measure][cell_x,cell_y] +
(O3_rasters[hour_after_measure][cell_x,cell_y] - O3_rasters[hour_before_measure][cell_x,cell_y]) * (min_measure * 60 + sec_measure) / 3600;
}
if measure_PM10 {
PM10_concentration <- PM10_rasters[hour_before_measure][cell_x,cell_y] +
(PM10_rasters[hour_after_measure][cell_x,cell_y] - PM10_rasters[hour_before_measure][cell_x,cell_y]) * (min_measure * 60 + sec_measure) / 3600;
}
if measure_PM25 {
PM25_concentration <- PM25_rasters[hour_before_measure][cell_x,cell_y] +
(PM25_rasters[hour_after_measure][cell_x,cell_y] - PM25_rasters[hour_before_measure][cell_x,cell_y]) * (min_measure * 60 + sec_measure) / 3600;
}
save [ID, name_of_agent, longitude, latitude, time_of_measure, NO2_concentration, O3_concentration, PM10_concentration, PM25_concentration]
to: "../results/Marseille/leisure/leisures_measures.csv" type:"csv" rewrite: false;
}
ask measure{do die;}
}
}
}
species measure {
int ID;
string name_of_agent;
float longitude min: min_x max: max_x - 0.1;
float latitude min: min_y max: max_y - 0.1;
date time_of_measure;
float NO2_concentration;
float O3_concentration;
float PM10_concentration;
float PM25_concentration;
}
grid pollution_cell file: grid_file('../includes/Marseille/pollution_model/raster_dep13_NO2_2021052701_2021052701.tif'){
}
experiment bike_traffic type: gui {
}