diff --git a/notebooks/LPD/LPDChar_Darks_NBC.ipynb b/notebooks/LPD/LPDChar_Darks_NBC.ipynb
index 5f5749ee5806e102634317df018a08fc30659934..c9508aa5c5d43a540dec87f08045217e229a7ed0 100644
--- a/notebooks/LPD/LPDChar_Darks_NBC.ipynb
+++ b/notebooks/LPD/LPDChar_Darks_NBC.ipynb
@@ -53,6 +53,9 @@
     "thresholds_noise_hard = [1, 35] # bad pixel hard threshold\n",
     "skip_first_ntrains = 10 # Number of first trains to skip\n",
     "\n",
+    "# Parameters for plotting\n",
+    "skip_plots = False  # exit after writing corrected files\n",
+    "\n",
     "instrument = \"FXE\" # instrument name\n",
     "ntrains = 100 # number of trains to use\n",
     "high_res_badpix_3d = False # plot bad-pixel summary in high resolution\n",
@@ -74,6 +77,7 @@
     "from collections import OrderedDict\n",
     "from datetime import datetime\n",
     "from functools import partial\n",
+    "from logging import warning\n",
     "\n",
     "warnings.filterwarnings('ignore')\n",
     "\n",
@@ -228,7 +232,9 @@
     "    im = np.array(infile[\"{}/data\".format(instrument_src, channel)][first_image:last_image, ...])\n",
     "    cellid = np.squeeze(np.array(infile[\"{}/cellId\".format(instrument_src, channel)][first_image:last_image, ...]))\n",
     "    infile.close()\n",
-    "    \n",
+    "    if im.shape[0] == 0:  # No data\n",
+    "        return None, None, channel, gg, cap, None, None, None, None\n",
+    "\n",
     "    cellid_pattern = cellid[:count[0]]\n",
     "\n",
     "    im, g = splitOffGainLPD(im[:, 0, ...])\n",
@@ -323,6 +329,10 @@
     "\n",
     "for ir, r in enumerate(results):\n",
     "    offset, noise, i, gg, cap, bp, data, normal, cellid_pattern = r\n",
+    "    if data is None:\n",
+    "        warning(f\"No data for module {i} of gain {gg}\")\n",
+    "        skip_plots = True\n",
+    "        continue\n",
     "    qm = module_index_to_qm(i)\n",
     "    if qm not in offset_g[cap]:\n",
     "        offset_g[cap][qm] = np.zeros(\n",
@@ -348,6 +358,18 @@
     "          f\"Number of processed trains per cell: {data.shape[0]}.\")"
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "if skip_plots:\n",
+    "    import sys\n",
+    "    print('Skipping plots')\n",
+    "    sys.exit(0)"
+   ]
+  },
   {
    "cell_type": "code",
    "execution_count": null,