diff --git a/notebooks/AGIPD/AGIPD_Correct_and_Verify.ipynb b/notebooks/AGIPD/AGIPD_Correct_and_Verify.ipynb
index 29f40ffe8023d63df946d4742c020c0bfbd63025..32f9b4aa7eda1fc59080d4a69697bcdec7fed0bf 100644
--- a/notebooks/AGIPD/AGIPD_Correct_and_Verify.ipynb
+++ b/notebooks/AGIPD/AGIPD_Correct_and_Verify.ipynb
@@ -1015,13 +1015,16 @@
    "metadata": {},
    "outputs": [],
    "source": [
+    "raw_float = raw.astype(np.float32)\n",
+    "signal = raw[:, 0, ...]\n",
+    "gain = raw[:, 1, ...]\n",
     "hist, bins_x, bins_y = calgs.histogram2d(\n",
-    "    raw[:,0,...].flatten().astype(np.float32),\n",
-    "    raw[:,1,...].flatten().astype(np.float32),\n",
+    "    signal.flatten().astype(np.float32),\n",
+    "    gain.flatten().astype(np.float32),\n",
     "    bins=(100, 100),\n",
     "    range=[\n",
-    "        np.percentile(raw[:, 0, ...].astype(np.float32), [0.02, 99.8]),\n",
-    "        np.percentile(raw[:, 1, ...].astype(np.float32), [0.02, 99.8]),\n",
+    "        np.percentile(signal, [0.02, 99.8]),\n",
+    "        np.percentile(gain, [0.02, 99.8]),\n",
     "        ],\n",
     "    )\n",
     "do_2d_plot(hist, (bins_x, bins_y), \"Signal (ADU)\", \"Analogue gain (ADU)\")"
@@ -1046,7 +1049,7 @@
     "    corrected.flatten().astype(np.float32),\n",
     "    gains.flatten().astype(np.float32), bins=(100, 3),\n",
     "    range=[\n",
-    "        np.percentile(corrected.flatten().astype(np.float32), [0, 100]),\n",
+    "        np.percentile(corrected, [0, 100]),\n",
     "        [0, 3]\n",
     "        ],\n",
     "    )\n",
@@ -1080,7 +1083,8 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "pulse_range = np.percentile(pulseId.astype(np.float32), [0, 100])\n",
+    "pulse_range = [np.min(pulseId[pulseId>=0]), np.max(pulseId[pulseId>=0])]\n",
+    "\n",
     "# Modify pulse_range, if only one pulse is selected.\n",
     "if pulse_range[0] == pulse_range[1]:\n",
     "    pulse_range = [0, pulse_range[1]+int(acq_rate)]\n",
@@ -1090,12 +1094,15 @@
     "    mean_data.flatten().astype(np.float32),\n",
     "    pulseId.flatten().astype(np.float32),\n",
     "    bins=(100, int(pulse_range[1])),\n",
-    "    range=[\n",
-    "        np.percentile(mean_data.astype(np.float32), [0, 100]),\n",
-    "        pulse_range\n",
-    "    ],\n",
+    "    range=[[-50, 1000], pulse_range],\n",
+    ")\n",
+    "do_2d_plot(hist, (bins_x, bins_y), \"Signal (ADU)\", \"Pulse id\")\n",
+    "hist, bins_x, bins_y = calgs.histogram2d(\n",
+    "    mean_data.flatten().astype(np.float32),\n",
+    "    pulseId.flatten().astype(np.float32),\n",
+    "    bins=(100,  int(pulse_range[1])),\n",
+    "    range=[[-50, 200000], pulse_range]\n",
     ")\n",
-    "\n",
     "do_2d_plot(hist, (bins_x, bins_y), \"Signal (ADU)\", \"Pulse id\")"
    ]
   },
@@ -1131,7 +1138,7 @@
     "fig = plt.figure(figsize=(10, 10))\n",
     "corrected_ave = np.nansum(corrected, axis=(2, 3))\n",
     "plt.scatter(corrected_ave.flatten()/10**6, blshift.flatten(), s=0.9)\n",
-    "plt.xlim(np.percentile(corrected_ave.flatten()/10**6, [2, 98]))\n",
+    "plt.xlim(np.percentile(corrected_ave/10**6, [2, 98]))\n",
     "plt.grid()\n",
     "plt.xlabel('Illuminated corrected [MADU] ')\n",
     "_ = plt.ylabel('Estimated baseline shift [ADU]')"
@@ -1200,7 +1207,7 @@
     "    fig = plt.figure(figsize=(20, 10))\n",
     "    ax = fig.add_subplot(111)\n",
     "    data = np.mean(corrected, axis=0)\n",
-    "    vmin, vmax = np.percentile(data, [5, 99.9])\n",
+    "    vmin, vmax = np.nanpercentile(data, [5, 99.9])\n",
     "    ax = geom.plot_data_fast(data, ax=ax, vmin=vmin, vmax=vmax, cmap=cmap)\n",
     "    pass\n",
     "else:\n",
@@ -1217,7 +1224,7 @@
     "display(Markdown(f'A single shot of the CORRECTED image from cell {cell_id_preview} \\n'))\n",
     "fig = plt.figure(figsize=(20, 10))\n",
     "ax = fig.add_subplot(111)\n",
-    "vmin, vmax = np.percentile(corrected[cell_idx_preview], [5, 99.9])\n",
+    "vmin, vmax = np.nanpercentile(corrected[cell_idx_preview], [5, 99.9])\n",
     "ax = geom.plot_data_fast(\n",
     "    corrected[cell_idx_preview], ax=ax, vmin=vmin, vmax=vmax, cmap=cmap)\n",
     "pass"
@@ -1231,7 +1238,7 @@
    "source": [
     "fig = plt.figure(figsize=(20, 10))\n",
     "ax = fig.add_subplot(111)\n",
-    "vmin, vmax = np.percentile(corrected[cell_idx_preview], [5, 100])\n",
+    "vmin, vmax = np.nanpercentile(corrected[cell_idx_preview], [5, 100])\n",
     "nbins = int((vmax + 50) / 2)\n",
     "h = ax.hist(corrected[cell_idx_preview].flatten(),\n",
     "            bins=nbins, range=(vmin, vmax),\n",