diff --git a/doc/BOZ analysis part I.a Correction determination.ipynb b/doc/BOZ analysis part I.a Correction determination.ipynb
index 28fb78d89edda631c98e1fb41518a846b9ef9af1..ae50811741325895f8d86564f63a559e8c1d4273 100644
--- a/doc/BOZ analysis part I.a Correction determination.ipynb	
+++ b/doc/BOZ analysis part I.a Correction determination.ipynb	
@@ -65,6 +65,21 @@
     "rois_th = 4"
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "proposal = int(proposal)\n",
+    "darkrun = int(darkrun)\n",
+    "run = int(run)\n",
+    "module = int(module)\n",
+    "gain = int(gain)\n",
+    "sat_level = int(sat_level)\n",
+    "rois_th = int(rois_th)"
+   ]
+  },
   {
    "cell_type": "code",
    "execution_count": 3,
diff --git a/scripts/boz_parameters_job.sh b/scripts/boz_parameters_job.sh
index f66bac4ef45b603cd2aef003d05af77cbb7c4ede..f8c199a10f4883798c5e415c8195a5110123b64f 100644
--- a/scripts/boz_parameters_job.sh
+++ b/scripts/boz_parameters_job.sh
@@ -5,7 +5,7 @@
 #SBATCH --mail-type=END,FAIL
 #SBATCH --output=logs/%j-%x.out
 
-PROPOSAL=2619
+PROPOSAL=2784
 DARK=$1
 RUN=$2
 GAIN=$3
@@ -19,10 +19,25 @@ module load exfel_anaconda3/1.1
 
 echo processing run $RUN
 PDIR=$(find-proposal $PROPOSAL)
+PPROPOSAL="p$(printf '%06d' $PROPOSAL)"
 RDIR="$PDIR/usr/processed_runs/r$(printf '%04d' $RUN)"
 mkdir $RDIR
 
-papermill 'BOZ analysis part I.a Correction determination.ipynb' \
-	$RDIR/output.ipynb \
- -p proposal $PROPOSAL -p darkrun $DARK -p run $RUN -p module $MODULE \
- -p gain $GAIN -p rois_th $ROISTH -p sat_level $SATLEVEL -k xfel
+NB='BOZ analysis part I.a Correction determination.ipynb'
+KERNEL="SCS Toolbox ($PPROPOSAL)"
+
+#activate the proposal environment
+ACTIVATE="$PDIR/usr/Software/envs/toolbox_$PPROPOSAL/bin/activate"
+source $ACITVATE
+
+python -c "import papermill as pm; pm.execute_notebook(\
+  '$NB', \
+	'$RDIR/output.ipynb', \
+  parameters=dict(proposal='$PROPOSAL', \
+                  darkrun='$DARK', \
+                  run='$RUN', \
+                  module='$MODULE', \
+                  gain='$GAIN', \
+                  rois_th='$ROISTH', \
+                  sat_level='$SATLEVEL', \
+                  kernel='$KERNEL'))"
diff --git a/src/toolbox_scs/routines/boz.py b/src/toolbox_scs/routines/boz.py
index b37726f5854078caa78444962a6929c52164f57b..0b11c5b8600bca7e6ca1322f0719bb93900ef365 100644
--- a/src/toolbox_scs/routines/boz.py
+++ b/src/toolbox_scs/routines/boz.py
@@ -536,15 +536,16 @@ def inspect_histogram(arr, arr_dark=None, mask=None, extra_lines=False):
     from matplotlib.ticker import MultipleLocator
 
     f = plt.figure(figsize=(6, 3))
+    ax = plt.gca()
     h = histogram_module(arr, mask=mask)
     Sum_h = np.sum(h)
-    plt.plot(np.arange(2**9), h/Sum_h, marker='o',
+    ax.plot(np.arange(2**9), h/Sum_h, marker='o',
             ms=3, markerfacecolor='none', lw=1)
 
     if arr_dark is not None:
         hd = histogram_module(arr_dark, mask=mask)
         Sum_hd = np.sum(hd)
-        plt.plot(np.arange(2**9), hd/Sum_hd, marker='o',
+        ax.plot(np.arange(2**9), hd/Sum_hd, marker='o',
                 ms=3, markerfacecolor='none', lw=1, c='k', alpha=.5)
     else:
         hd = None
@@ -552,19 +553,19 @@ def inspect_histogram(arr, arr_dark=None, mask=None, extra_lines=False):
     if extra_lines:
         for k in range(50, 271):
             if not (k - 2) % 8:
-                plt.axvline(k, c='k', alpha=0.5, ls='--')
+                ax.axvline(k, c='k', alpha=0.5, ls='--')
             if not (k - 3) % 16:
-                plt.axvline(k, c='g', alpha=0.3, ls='--')
+                ax.axvline(k, c='g', alpha=0.3, ls='--')
             if not (k - 7) % 32:
-                plt.axvline(k, c='r', alpha=0.3, ls='--')
+                ax.axvline(k, c='r', alpha=0.3, ls='--')
 
-    plt.axvline(271, c='C1', alpha=0.5, ls='--')
+    ax.axvline(271, c='C1', alpha=0.5, ls='--')
 
-    plt.xlim([0, 2**9-1])
-    plt.yscale('log')
-    plt.axes().xaxis.set_minor_locator(MultipleLocator(10))
-    plt.xlabel('DSSC pixel value')
-    plt.ylabel('count frequency')
+    ax.set_xlim([0, 2**9-1])
+    ax.set_yscale('log')
+    ax.xaxis.set_minor_locator(MultipleLocator(10))
+    ax.set_xlabel('DSSC pixel value')
+    ax.set_ylabel('count frequency')
 
     return (h, hd), f
 
@@ -1337,7 +1338,7 @@ def inspect_correction(params, gain=None):
                 good_d[n].values.flatten()/good_d[r].values.flatten(),
                 [photon_scale, np.linspace(0.95, 1.05, 150)*m],
                 cmap='Blues',
-                norm=LogNorm(vmax=200),
+                norm=LogNorm(vmin=0.2, vmax=200),
                 # alpha=0.5 # make  the plot looks ugly with lots of white lines
                 )
             h, xedges, yedges, img2 = axs[l, k].hist2d(
@@ -1345,7 +1346,7 @@ def inspect_correction(params, gain=None):
                 sat_d[n].values.flatten()/sat_d[r].values.flatten(),
                 [photon_scale, np.linspace(0.95, 1.05, 150)*m],
                 cmap='Reds',
-                norm=LogNorm(vmax=200),
+                norm=LogNorm(vmin=0.2, vmax=200),
                 # alpha=0.5 # make  the plot looks ugly with lots of white lines
                 )