diff --git a/jupyter_notebooks/smlm_challenge_2013_dao3d_2dfixed.ipynb b/jupyter_notebooks/smlm_challenge_2013_dao3d_2dfixed.ipynb
index b4bf09bd..8cea5a63 100644
--- a/jupyter_notebooks/smlm_challenge_2013_dao3d_2dfixed.ipynb
+++ b/jupyter_notebooks/smlm_challenge_2013_dao3d_2dfixed.ipynb
@@ -82,32 +82,35 @@
     "params = parameters.ParametersDAO()\n",
     "\n",
     "# Analyze the whole movie.\n",
-    "params.setAttr(\"max_frame\", \"int\", -1)    \n",
-    "params.setAttr(\"start_frame\", \"int\", -1)\n",
+    "params.changeAttr(\"max_frame\", -1)    \n",
+    "params.changeAttr(\"start_frame\", -1)\n",
     "\n",
-    "params.setAttr(\"background_sigma\", \"float\", 8.0)\n",
+    "params.changeAttr(\"background_sigma\", 8.0)\n",
     "\n",
     "# These were specified on the website for this dataset.\n",
-    "params.setAttr(\"camera_gain\", \"float\", 1.0)\n",
-    "params.setAttr(\"camera_offset\", \"float\", 100.0)\n",
+    "params.changeAttr(\"camera_gain\", 1.0)\n",
+    "params.changeAttr(\"camera_offset\", 100.0)\n",
     "\n",
-    "params.setAttr(\"find_max_radius\", \"int\", 5)\n",
-    "params.setAttr(\"foreground_sigma\", \"float\", 1.0)\n",
-    "params.setAttr(\"iterations\", \"int\", 20)\n",
-    "params.setAttr(\"model\", \"string\", \"2dfixed\")\n",
-    "params.setAttr(\"pixel_size\", \"float\", 100.0)\n",
-    "params.setAttr(\"roi_size\", \"int\", 9)\n",
+    "# Since this parameter can be either a float or an int we need\n",
+    "# to specify which type we want it to be.\n",
+    "params.changeAttr(\"find_max_radius\", 5, node_type = \"float\")\n",
+    "\n",
+    "params.changeAttr(\"foreground_sigma\", 1.0)\n",
+    "params.changeAttr(\"iterations\", 20)\n",
+    "params.changeAttr(\"model\", \"2dfixed\")\n",
+    "params.changeAttr(\"pixel_size\", 100.0)\n",
+    "params.changeAttr(\"roi_size\", 9)\n",
     "\n",
     "# Convert from FWHM in nanometers to sigma in pixels.\n",
-    "params.setAttr(\"sigma\", \"float\", 258.21/(100.0 * 2.355))\n",
-    "params.setAttr(\"threshold\", \"float\", 6)\n",
+    "params.changeAttr(\"sigma\", 258.21/(100.0 * 2.355))\n",
+    "params.changeAttr(\"threshold\", 6)\n",
     "\n",
     "# Don't do tracking.\n",
-    "params.setAttr(\"radius\", \"float\", \"0\")\n",
-    "params.setAttr(\"descriptor\", \"string\", \"1\")\n",
+    "params.changeAttr(\"radius\", \"0.0\")\n",
+    "params.changeAttr(\"descriptor\", \"1\")\n",
     "\n",
     "# Don't do drift-correction.\n",
-    "params.setAttr(\"drift_correction\", \"int\", 0)\n",
+    "params.changeAttr(\"drift_correction\", 0)\n",
     "\n",
     "params.toXMLFile(\"analysis.xml\", pretty = True)"
    ]
@@ -141,28 +144,30 @@
     "Reference results:\n",
     "\n",
     "```\n",
-    "Added 46444\n",
-    "   4708 peak finding iterations.\n",
+    "Added 46437\n",
+    "   4705 peak finding iterations.\n",
     "\n",
     "   0 fits reset due to Cholesky failure.\n",
     "   14 fits reset due to image margin.\n",
     "   677 fits reset due to negative value in fit function.\n",
-    "   115 fits reset due to negative height.\n",
-    "   534072 fits reset due to non-decreasing error (LM).\n",
+    "   110 fits reset due to negative height.\n",
+    "   533925 fits reset due to non-decreasing error (LM).\n",
     "   0 fits did not converge.\n",
     "   17 fits were lost.\n",
     "   415 peaks lost to proximity filter.\n",
     "   244 peaks lost to low significance.\n",
-    "   6711697 fitting iterations.\n",
+    "   6706925 fitting iterations.\n",
     "\n",
     "Tracking.\n",
     "\n",
     "Checking z values.\n",
     "\n",
     "Analysis complete\n",
-    "CPU times: user 55 s, sys: 171 ms, total: 55.1 s\n",
-    "Wall time: 55 s\n",
-    "```"
+    "CPU times: user 55.5 s, sys: 486 ms, total: 56 s\n",
+    "Wall time: 55.4 s\n",
+    "```\n",
+    "\n",
+    "Results may vary slightly. In particular the FFTW library is not completely deterministic when run with `FFTW_MEASURE`."
    ]
   },
   {