diff --git a/notebooks/AGIPD/Characterize_AGIPD_Gain_Darks_NBC.ipynb b/notebooks/AGIPD/Characterize_AGIPD_Gain_Darks_NBC.ipynb
index 2a719adffb376cb6c3beecd90b6141075781fd1f..f078a19efc75ebb06a33ef645b858ed395b275d8 100644
--- a/notebooks/AGIPD/Characterize_AGIPD_Gain_Darks_NBC.ipynb
+++ b/notebooks/AGIPD/Characterize_AGIPD_Gain_Darks_NBC.ipynb
@@ -331,32 +331,41 @@
     "            first_index = int(first[status != 0][0])\n",
     "        im = np.array(infile[f\"{h5path_f}/data\"][first_index:last_index,...])\n",
     "        cellIds = np.squeeze(infile[f\"{h5path_f}/cellId\"][first_index:last_index,...])\n",
-    "\n",
+    "    \n",
     "    if interlaced:\n",
-    "        ga = im[1::2, 0, ...]\n",
+    "        if not fixed_gain_mode:\n",
+    "            ga = im[1::2, 0, ...]\n",
     "        im = im[0::2, 0, ...].astype(np.float32)\n",
     "        cellIds = cellIds[::2]\n",
     "    else:\n",
-    "        ga = im[:, 1, ...]\n",
+    "        if not fixed_gain_mode:\n",
+    "            ga = im[:, 1, ...]\n",
     "        im = im[:, 0, ...].astype(np.float32)\n",
     "\n",
     "    im = np.rollaxis(im, 2)\n",
     "    im = np.rollaxis(im, 2, 1)\n",
     "\n",
-    "    ga = np.rollaxis(ga, 2)\n",
-    "    ga = np.rollaxis(ga, 2, 1)\n",
-    "\n",
+    "    if not fixed_gain_mode:\n",
+    "        ga = np.rollaxis(ga, 2)\n",
+    "        ga = np.rollaxis(ga, 2, 1)\n",
+    "    \n",
     "    offset = np.zeros((im.shape[0], im.shape[1], num_cells))\n",
-    "    gains = np.zeros((im.shape[0], im.shape[1], num_cells))\n",
     "    noise = np.zeros((im.shape[0], im.shape[1], num_cells))\n",
-    "    gains_std = np.zeros((im.shape[0], im.shape[1], num_cells))\n",
+    "\n",
+    "    if fixed_gain_mode:\n",
+    "        gains = None\n",
+    "        gains_std = None\n",
+    "    else:\n",
+    "        gains = np.zeros((im.shape[0], im.shape[1], num_cells))\n",
+    "        gains_std = np.zeros((im.shape[0], im.shape[1], num_cells))\n",
     "\n",
     "    for cc in np.unique(cellIds[cellIds < num_cells]):\n",
     "        cellidx = cellIds == cc\n",
     "        offset[...,cc] = np.median(im[..., cellidx], axis=2)\n",
     "        noise[...,cc] = np.std(im[..., cellidx], axis=2)\n",
-    "        gains[...,cc] = np.median(ga[..., cellidx], axis=2)\n",
-    "        gains_std[...,cc] = np.std(ga[..., cellidx], axis=2)\n",
+    "        if not fixed_gain_mode:\n",
+    "            gains[...,cc] = np.median(ga[..., cellidx], axis=2)\n",
+    "            gains_std[...,cc] = np.std(ga[..., cellidx], axis=2)\n",
     "\n",
     "    # bad pixels\n",
     "    bp = np.zeros(offset.shape, np.uint32)\n",
@@ -389,10 +398,11 @@
    "source": [
     "offset_g = OrderedDict()\n",
     "noise_g = OrderedDict()\n",
-    "gain_g = OrderedDict()\n",
-    "gainstd_g = OrderedDict()\n",
     "badpix_g = OrderedDict()\n",
-    "\n",
+    "if not fixed_gain_mode:\n",
+    "    gain_g = OrderedDict()\n",
+    "    gainstd_g = OrderedDict()\n",
+    "    \n",
     "start = datetime.now()\n",
     "all_cells = []\n",
     "all_acq_rate = []\n",
@@ -421,15 +431,17 @@
     "        if qm not in offset_g:\n",
     "            offset_g[qm] = np.zeros((offset.shape[0], offset.shape[1], offset.shape[2], 3))\n",
     "            noise_g[qm] = np.zeros_like(offset_g[qm])\n",
-    "            gain_g[qm] = np.zeros_like(offset_g[qm])\n",
-    "            gainstd_g[qm] = np.zeros_like(offset_g[qm])\n",
     "            badpix_g[qm] = np.zeros_like(offset_g[qm], np.uint32)\n",
+    "            if not fixed_gain_mode:\n",
+    "                gain_g[qm] = np.zeros_like(offset_g[qm])\n",
+    "                gainstd_g[qm] = np.zeros_like(offset_g[qm])\n",
     "\n",
     "        offset_g[qm][...,gg] = offset\n",
     "        noise_g[qm][...,gg] = noise\n",
-    "        gain_g[qm][...,gg] = gains\n",
-    "        gainstd_g[qm][..., gg] = gains_std\n",
     "        badpix_g[qm][...,gg] = bp\n",
+    "        if not fixed_gain_mode:\n",
+    "            gain_g[qm][...,gg] = gains\n",
+    "            gainstd_g[qm][..., gg] = gains_std\n",
     "\n",
     "\n",
     "duration = (datetime.now() - start).total_seconds()\n",
@@ -878,7 +890,7 @@
     "if fixed_gain_mode:\n",
     "    constants = ['Offset', 'Noise']\n",
     "else:\n",
-    "    ['Offset', 'Noise', 'ThresholdsDark']\n",
+    "    constants = ['Offset', 'Noise', 'ThresholdsDark']\n",
     "\n",
     "for const in constants:\n",
     "\n",