diff --git a/cron/includes/generation.php b/cron/includes/generation.php
new file mode 100644
index 0000000..623113f
--- /dev/null
+++ b/cron/includes/generation.php
@@ -0,0 +1,124 @@
+<?php
+if (php_sapi_name() != "cli")
+  exit();
+
+// Funció per obtenir el nombre de casos nous al dia originalDay+translation
+// a partir de les dades de la regió (dataRegio).
+function getSumDay($originalDay, $translation, &$dataRegio) {
+  if ($translation >= 0)
+    $day = (clone $originalDay)->add(new DateInterval("P".abs($translation)."D"));
+  else
+    $day = (clone $originalDay)->sub(new DateInterval("P".abs($translation)."D"));
+
+  foreach ($dataRegio as $row) {
+    $rowDay = new DateTime($row["data"]);
+    if ($day == $rowDay) return $row["sum_numcasos"];
+  }
+
+  return 0;
+}
+
+// Funció per fer una consulta a la taula de dades
+function query($soql, $resource = "xuwf-dxjd") {
+  $url = "https://analisi.transparenciacatalunya.cat/resource/".$resource.".json?\$query=".urlencode($soql);
+  $raw = file_get_contents($url);
+  if ($raw === false) return null;
+  return json_decode($raw, true);
+}
+
+// Funció per generar les dades de cada regió
+function generateSummary(&$dataRegio, $habitants){
+  $summary = [];
+
+  // Veiem quin és el primer i l'últim dia de la sèrie
+  $oldestDay = new DateTime("today");
+  $newestDay = new DateTime();
+  $newestDay->setTimestamp(0);
+
+  foreach ($dataRegio as $row) {
+    $date = new DateTime($row["data"]);
+    if ($date < $oldestDay) $oldestDay = $date;
+    if ($date > $newestDay) $newestDay = $date;
+  }
+
+  // Si l'últim dia és avui, posem que sigui ahir, perquè no volem informació
+  // incompleta sobre avui.
+  if ($oldestDay == (new DateTime("today")))
+    $oldestDay = new DateTime("yesterday");
+
+  // Ara calculem les rhos.
+  $rhos = [];
+
+  // Considerem cada dia a partir de 6 dies després del primer dia, i fins al
+  // dia anterior a l'últim dia (extrems inclosos)
+  for ($currentDate = (clone $oldestDay)->add(new DateInterval("P6D"));
+  $currentDate < $newestDay;
+  $currentDate->add(new DateInterval("P1D"))) {
+    // Calculem la rho (velocitat reproductiva efectiva) per aquell dia.
+    // Fórmula: https://biocomsc.upc.edu/en/shared/avaluacio_risc.pdf
+    $num = getSumDay($currentDate, 1, $dataRegio) +
+           getSumDay($currentDate, 0, $dataRegio) +
+           getSumDay($currentDate, -1, $dataRegio);
+
+    $den = getSumDay($currentDate, -4, $dataRegio) +
+           getSumDay($currentDate, -5, $dataRegio) +
+           getSumDay($currentDate, -6, $dataRegio);
+
+    if ($num != 0 && $den == 0) continue;
+
+    $rho = ($num == 0 ? 0 : $num/$den);
+
+    $rhos[] = [
+      "data" => $currentDate->format("c"),
+      "rho" => $rho
+    ];
+  }
+
+  // Considerem cada dia a partir de 13 dies després del primer dia, i fins el
+  // dia anterior a l'últim dia (extrems inclosos)
+  for ($currentDate = (clone $oldestDay)->add(new DateInterval("P13D"));
+    $currentDate < $newestDay;
+    $currentDate->add(new DateInterval("P1D"))) {
+    // Calculem Rho_7 i IA_14
+    // Rho_7(t) := \sum_{i=0}^{7} Rho(t - i)
+    // IA_14(t) := \sum_{i=0}^{14} N(t - i),
+    //   on N(j) és el nombre de casos nous confirmats per PCR el dia j.
+    $sum = 0;
+
+    $p13Date = (clone $currentDate)->sub(new DateInterval("P13D"));
+    $p6Date = (clone $currentDate)->sub(new DateInterval("P6D"));
+
+    foreach ($dataRegio as $row) {
+      $date = new DateTime($row["data"]);
+      if ($date >= $p13Date && $date <= $currentDate) {
+        $sum += $row["sum_numcasos"];
+      }
+    }
+
+    $rhoAverage = 0;
+    $rhoCount = 0;
+
+    foreach ($rhos as $row) {
+      $date = new DateTime($row["data"]);
+      if ($date >= $p6Date && $date <= $currentDate) {
+        ++$rhoCount;
+        $rhoAverage += $row["rho"];
+      }
+    }
+
+    // Si no hem trobat rhos (rhoCount == 0) és perquè el numerador no era 0
+    // però el denominador era sempre 0 al calcular les rhos. Aleshores, tot i
+    // que no poguem calcular la rho_7 a causa de no poder calcular les rho_t
+    // individuals, aquest fet ens indica que el creixement ha sigut altíssim,
+    // i per tant posem una rho_7 de 1000000000, que se surt de la gràfica.
+    $rhoAverage = ($rhoCount == 0 ? 1000000000 : $rhoAverage/$rhoCount);
+
+    $summary[] = [
+      "data" => $currentDate->format("d/m/y"),
+      "ia14" => $sum*(1e5/$habitants),
+      "rho7" => $rhoAverage
+    ];
+  }
+
+  return $summary;
+}
diff --git a/cron/includes/plotAllGraphs.gnu b/cron/includes/plotAllGraphs.gnu
new file mode 100644
index 0000000..ae0914e
--- /dev/null
+++ b/cron/includes/plotAllGraphs.gnu
@@ -0,0 +1,28 @@
+set xlabel "Casos actius per 10^5 habitants"
+set ylabel "Mitjana taxa de creixement darrers 7 dies"
+set title font "Helvetica,20"
+
+set xrange[0:675]
+set yrange[0:5]
+set samples 400
+
+set multiplot layout 3,3
+set key off
+set tics out scale 0.5,0.2
+
+min(a, b) = (a < b ? a : b)
+
+n = 9
+array fileNames[n] = ["TerresDeLEbre.dat", "CampDeTarragona.dat", "AltPirineuAran.dat", "Lleida.dat", "Girona.dat", "CatalunyaCentral.dat", "BarcelonaCiutat.dat", "MetropolitaSud.dat", "MetropolitaNord.dat"]
+array prettyNames[n] = ["Terres de l'Ebre", "Camp de Tarragona", "Alt Pirineu, Aran", "Lleida", "Girona", "Catalunya central", "Barcelona ciutat", "Metropolità sud", "Metropolità nord"]
+
+# The different colored areas correspond to the classification of the EPG values defined on page 8 at https://biocomsc.upc.edu/en/shared/20200506_report_web_51.pdf
+
+do for [i = 1:n] {
+  lastUpdated = system("tail -n 1 ".filesPrefix.fileNames[i]." | awk '{print $1;}'")
+  graphTitle = prettyNames[i]
+  graphDataFile = filesPrefix.fileNames[i]
+  load "includes/plotSingleGraph.gnu"
+}
+
+unset multiplot
diff --git a/cron/includes/plotCustomGraph.gnu b/cron/includes/plotCustomGraph.gnu
new file mode 100644
index 0000000..acf66aa
--- /dev/null
+++ b/cron/includes/plotCustomGraph.gnu
@@ -0,0 +1,19 @@
+set xlabel "Casos actius per 10^5 habitants"
+set ylabel "Mitjana taxa de creixement darrers 7 dies"
+set title font "Helvetica,20"
+
+set yrange[0:5]
+set xrange[0:800]
+set samples 400
+
+set key off
+set tics out scale 0.5,0.2
+
+min(a, b) = (a < b ? a : b)
+
+# The different colored areas correspond to the classification of the EPG values defined on page 8 at https://biocomsc.upc.edu/en/shared/20200506_report_web_51.pdf
+
+lastUpdated = system("tail -n 1 ".fileName." | awk '{print $1;}'")
+graphTitle = name
+graphDataFile = fileName
+load "includes/plotSingleGraph.gnu"
diff --git a/cron/includes/plotSingleGraph.gnu b/cron/includes/plotSingleGraph.gnu
new file mode 100644
index 0000000..152fd11
--- /dev/null
+++ b/cron/includes/plotSingleGraph.gnu
@@ -0,0 +1,2 @@
+set title graphTitle."\n{/*0.4 Última dada (punt negre): ".lastUpdated."}"
+plot 6*x w filledcurve y1=0 lt rgb "#ff9494", 100/x w filledcurve y1=0 lt rgb "#ffe494", 70/x w filledcurve y1=0 lt rgb "#dbff94", 30/x w filledcurve y1=0 lt rgb "#a0ff94", graphDataFile u 2:3 w lp pt 6 lt rgb "black", "< tail -n 1 ".graphDataFile u 2:3 w lp pt 7 lt rgb "black"