diff --git a/main.py b/main.py
index 9c8df18..3fb8002 100644
--- a/main.py
+++ b/main.py
@@ -69,8 +69,8 @@ def do_tint_solve(val):
         dimmer.print_dimmer_state()
     
     def do_tint_table_solve(val):
-        points = 256
-        for i in range(points):
+        points = (256) - 1
+        for i in range(points + 1):
             duty  = i * 100 / points
             tint  = dimmer.solve_tint_for_duty(duty)
             tperc = tint / (dimmer.periode / 2)
diff --git a/rms_vs_tinterrupt.ipynb b/rms_vs_tinterrupt.ipynb
index 63dc00b..1338cc7 100644
--- a/rms_vs_tinterrupt.ipynb
+++ b/rms_vs_tinterrupt.ipynb
@@ -2,7 +2,7 @@
  "cells": [
   {
    "cell_type": "code",
-   "execution_count": 2,
+   "execution_count": 4,
    "source": [
     "from dimmer import Dimmer\r\n",
     "import matplotlib.pyplot as plt\r\n",
@@ -12,20 +12,19 @@
     "\r\n",
     "duty_series = np.arange(0, 100, 1)\r\n",
     "rms_series = [dimmer.solve_tint_for_duty(duty) for duty in duty_series]\r\n",
-    "plt.plot(duty_series, rms_series)\r\n",
-    "plt.ylabel(\"time [s]\")\r\n",
-    "plt.xlabel(\"duty [%]\")\r\n",
+    "plt.plot(rms_series, duty_series)\r\n",
+    "plt.xlabel(\"time [s]\")\r\n",
+    "plt.ylabel(\"duty [%]\")\r\n",
     "plt.grid()"
    ],
    "outputs": [
     {
      "output_type": "display_data",
      "data": {
+      "image/png": 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"
+      ]
      },
      "metadata": {
       "needs_background": "light"
@@ -51,10 +50,10 @@
   },
   "kernelspec": {
    "name": "python3",
-   "display_name": "Python 3.9.1 64-bit ('env': venv)"
+   "display_name": "Python 3.9.1 64-bit"
   },
   "interpreter": {
-   "hash": "a4046a09f199e48e61396275ea0e14da7d6ee49ffd95343aa82a9cc54eb636e7"
+   "hash": "0d008810b9c8467bcb3ca39aa2180e5b81b3a9acb136aab30d47954377cc5120"
   }
  },
  "nbformat": 4,
diff --git a/screenshots/fig_3 - Duty vs timepng.png b/screenshots/fig_3 - Duty vs timepng.png
new file mode 100644
index 0000000..ae0d499
Binary files /dev/null and b/screenshots/fig_3 - Duty vs timepng.png differ
diff --git a/screenshots/fig_3 - Table output.png b/screenshots/fig_3 - Table output.png
index 70ab8da..122ce22 100644
Binary files a/screenshots/fig_3 - Table output.png and b/screenshots/fig_3 - Table output.png differ