diff --git a/notebooks/Jungfrau/Jungfrau_dark_analysis_all_gains_burst_mode_NBC.ipynb b/notebooks/Jungfrau/Jungfrau_dark_analysis_all_gains_burst_mode_NBC.ipynb
index 3401a39b86ab21ce34ab066d60202ba0cb5051bc..8a1212ac54115779e07716a49fa8ca22e0756dd7 100644
--- a/notebooks/Jungfrau/Jungfrau_dark_analysis_all_gains_burst_mode_NBC.ipynb
+++ b/notebooks/Jungfrau/Jungfrau_dark_analysis_all_gains_burst_mode_NBC.ipynb
@@ -18,23 +18,23 @@
    "outputs": [],
    "source": [
     "cluster_profile = 'noDB'  # the ipcluster profile name\n",
-    "in_folder = '/gpfs/exfel/exp/FXE/201931/p900089/raw/'  # folder under which runs are located, required\n",
-    "out_folder = '/gpfs/exfel/data/scratch/karnem/test_dark/' # path to place reports at, required\n",
+    "in_folder = '/gpfs/exfel/exp/FXE/202030/p900121/raw/'  # folder under which runs are located, required\n",
+    "out_folder = '/gpfs/exfel/exp/HSLAB/201831/p900053/proc/proc_data/FXE/p900121/test_dark/' # path to place reports at, required\n",
     "sequences = 1  # number of sequence files in that run\n",
-    "run_high = 86 # run number for G0 dark run, required\n",
-    "run_med = 87 # run number for G1 dark run, required\n",
-    "run_low = 88 # run number for G2 dark run, required\n",
+    "run_high = 130 # run number for G0 dark run, required\n",
+    "run_med = 131 # run number for G1 dark run, required\n",
+    "run_low = 132 # run number for G2 dark run, required\n",
     "\n",
-    "karabo_da = ['JNGFR01'] # list of data aggregators, which corresponds to different JF modules\n",
-    "karabo_id = \"FXE_XAD_JF1M\"  # bla karabo prefix of Jungfrau devices\n",
+    "karabo_da = ['JNGFR03'] # list of data aggregators, which corresponds to different JF modules\n",
+    "karabo_id = \"FXE_XAD_JF500K\"  # bla karabo prefix of Jungfrau devices\n",
     "karabo_id_control = \"\"  # if control is on a different ID, set to empty string if it is the same a karabo-id\n",
-    "receiver_id = 'RECEIVER-{}' # inset for receiver devices\n",
+    "receiver_id = 'JNGFR{:02d}' # inset for receiver devices\n",
     "receiver_control_id = \"CONTROL\" # inset for control devices\n",
     "path_template = 'RAW-R{:04d}-{}-S{{:05d}}.h5'  # template to use for file name, double escape sequence number\n",
     "h5path = '/INSTRUMENT/{}/DET/{}:daqOutput/data'  # path in H5 file under which images are located\n",
     "h5path_run = '/RUN/{}/DET/{}' # path to run data\n",
     "h5path_cntrl = '/CONTROL/{}/DET/{}' # path to control data\n",
-    "karabo_da_control = \"JNGFR01\" # file inset for control data\n",
+    "karabo_da_control = \"JNGFRCTRL00\" # file inset for control data\n",
     "\n",
     "use_dir_creation_date = True # use dir creation date\n",
     "cal_db_interface = 'tcp://max-exfl016:8016'  # calibrate db interface to connect to\n",
@@ -44,7 +44,7 @@
     "\n",
     "integration_time = 1000 # integration time in us, will be overwritten by value in file\n",
     "bias_voltage = 90  # sensor bias voltage in V, will be overwritten by value in file\n",
-    "badpixel_threshold_sigma = 20.  # bad pixels defined by values outside n times this std from median\n",
+    "badpixel_threshold_sigma = 5.  # bad pixels defined by values outside n times this std from median\n",
     "offset_abs_threshold_low = [1000, 10000, 10000]  # absolute bad pixel threshold in terms of offset, lower values\n",
     "offset_abs_threshold_high = [8000, 15000, 15000]  # absolute bad pixel threshold in terms of offset, upper values\n",
     "chunkSize = 10  # iteration chunk size, needs to match or be less than number of images in a sequence file\n",
@@ -83,7 +83,7 @@
     "from XFELDetAna.detectors.jungfrau import readerPSI as jfreaderPSI\n",
     "from XFELDetAna.detectors.jungfrau import reader as jfreader\n",
     "from XFELDetAna.detectors.jungfrau.jf_chunk_reader import JFChunkReader\n",
-    "from XFELDetAna.detectors.jungfrau.util import non_empty_trains, count_n_files, rollout_data, sanitize_data_cellid\n",
+    "from XFELDetAna.detectors.jungfrau.util import count_n_files, rollout_data, sanitize_data_cellid\n",
     "import glob\n",
     "import matplotlib.pyplot as plt\n",
     "%matplotlib inline\n",
@@ -236,7 +236,7 @@
     "           \n",
     "              \n",
     "            \n",
-    "            idxs = non_empty_trains(trainId)\n",
+    "            idxs = np.nonzero(trainId)[0]\n",
     "            images = images[..., idxs]\n",
     "            gainmaps = gainmaps[..., idxs]\n",
     "            fr_num = fr_num[..., idxs]\n",
@@ -409,8 +409,8 @@
     "bad_pixels_map = np.zeros(noise_map.shape, np.uint32)\n",
     "def eval_bpidx(d):\n",
     "\n",
-    "    mdn = np.nanmedian(d, axis=(0, 1, 2))[None, None, None, :]\n",
-    "    std = np.nanstd(d, axis=(0, 1, 2))[None, None, None, :]    \n",
+    "    mdn = np.nanmedian(d, axis=(0, 1))[None, None, :, :]\n",
+    "    std = np.nanstd(d, axis=(0, 1))[None, None, :, :]    \n",
     "    idx = (d > badpixel_threshold_sigma*std+mdn) | (d < (-badpixel_threshold_sigma)*std+mdn)\n",
     "        \n",
     "    return idx\n",
@@ -516,7 +516,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.7.6"
+   "version": "3.6.7"
   }
  },
  "nbformat": 4,