diff --git a/notebooks/Jungfrau/Jungfrau_darks_Summary_NBC.ipynb b/notebooks/Jungfrau/Jungfrau_darks_Summary_NBC.ipynb
index 0e3818a737f7d68561313812b7b659bab6c6443c..5568147b70b47d2fcce2b1634f7a754fbd818c4e 100644
--- a/notebooks/Jungfrau/Jungfrau_darks_Summary_NBC.ipynb
+++ b/notebooks/Jungfrau/Jungfrau_darks_Summary_NBC.ipynb
@@ -111,21 +111,32 @@
"metadata": {},
"outputs": [],
"source": [
+ "fixed_gain = False # constant is adaptive by default.\n",
"# Get the constant shape from one of the local constants.\n",
"# This is one way to realize the number of memory cells.\n",
"with h5py.File(list(out_folder.glob(\"const_Offset_*\"))[0], 'r') as f:\n",
" const_shape = f[\"data\"][()].shape\n",
+ " # Get fixed gain value to decide offset vmin, vmax\n",
+ " # for later constant map plots.\n",
+ " gain_mode = \"condition/Gain mode/value\"\n",
+ " if gain_mode in f:\n",
+ " fixed_gain = f[gain_mode][()]\n",
+ " \n",
"\n",
- "initial_stacked_constants = np.zeros(((nmods,)+const_shape))\n",
+ "initial_stacked_constants = np.full(((nmods,)+const_shape), np.nan)\n",
"curr_constants = { c: initial_stacked_constants.copy() for c in dark_constants}\n",
"prev_constants = { c: initial_stacked_constants.copy() for c in dark_constants}\n",
"\n",
+ "execulded_constants = [] # constants excluded from comparison plots.\n",
+ "\n",
"# Loop over modules\n",
- "for i, mod in enumerate(sorted(expected_modules)):\n",
- " # Loop over expected dark constants in out_folder.\n",
- " # Some constants can be missing in out_folder.\n",
- " pdu = mod_mapping[mod]\n",
- " for cname in dark_constants:\n",
+ "for cname in dark_constants:\n",
+ " excluded_modules = [] # modules with no previous constants.\n",
+ " for i, mod in enumerate(sorted(expected_modules)):\n",
+ " # Loop over expected dark constants in out_folder.\n",
+ " # Some constants can be missing in out_folder.\n",
+ " pdu = mod_mapping[mod]\n",
+ " \n",
" # first load new constant\n",
" fpath = out_folder / f\"const_{cname}_{pdu}.h5\"\n",
" with h5py.File(fpath, 'r') as f:\n",
@@ -134,16 +145,23 @@
" # Load previous constants.\n",
" old_mod_mdata = prev_const_metadata[mod]\n",
"\n",
- " if cname not in old_mod_mdata:\n",
- " continue\n",
- "\n",
- " filepath = old_mod_mdata[cname][\"filepath\"]\n",
- " h5path = old_mod_mdata[cname][\"h5path\"]\n",
- "\n",
- " if not filepath or not h5path:\n",
- " continue\n",
- " with h5py.File(filepath, \"r\") as fd:\n",
- " prev_constants[cname][i, ...] = fd[f\"{h5path}/data\"][()]"
+ " if cname in old_mod_mdata: # a module can be missing from detector dark processing.\n",
+ " filepath = old_mod_mdata[cname][\"filepath\"]\n",
+ " h5path = old_mod_mdata[cname][\"h5path\"]\n",
+ " if not filepath or not h5path:\n",
+ " excluded_modules.append(mod)\n",
+ " prev_constants[cname][i, ...].fill(np.nan)\n",
+ " else:\n",
+ " with h5py.File(filepath, \"r\") as fd:\n",
+ " prev_constants[cname][i, ...] = fd[f\"{h5path}/data\"][()]\n",
+ "\n",
+ " if excluded_modules:\n",
+ " print(f\"Previous {cname} constants for {excluded_modules} are not available.\\n.\")\n",
+ " # Exclude constants from comparison plots, if the corresponding\n",
+ " # previous constants are not available for all modules.\n",
+ " if len(excluded_modules) == nmods:\n",
+ " execulded_constants.append(cname)\n",
+ " print(f\"No comparison plots for {cname}.\\n\")"
]
},
{
@@ -178,6 +196,9 @@
" \"Noise\": [(0., 50.), (0., 50.), (0., 50.)],\n",
" \"BadPixelsDark\": [(0., 5.), (0., 5.), (0., 5.)],\n",
"}\n",
+ "# vmin and vmax are different for Offset for fixed gain constants. \n",
+ "if fixed_gain:\n",
+ " const_range[\"Offset\"] = [(0, 8000), (0, 8000), (0, 8000)]\n",
"\n",
"diff_const_range = {\n",
" \"Offset\": [(0, 500), (0, 500), (0, 500)],\n",
@@ -190,27 +211,27 @@
"axis = OrderedDict({\n",
" \"ax0\": {\n",
" \"gs\": gs[0, 1:3],\n",
- " \"shrink\": 0.9,\n",
+ " \"shrink\": 0.7,\n",
" \"pad\": 0.05,\n",
" \"label\": \"ADCu\",\n",
- " \"title\": '{}',\n",
- " 'location': 'right',\n",
+ " \"title\": \"{}\",\n",
+ " \"location\": \"right\",\n",
" },\n",
" \"ax1\": {\n",
" \"gs\": gs[1, :2],\n",
- " \"shrink\": 0.6,\n",
- " \"pad\": 0.05,\n",
+ " \"shrink\": 0.7,\n",
+ " \"pad\": 0.02,\n",
" \"label\": \"ADCu\",\n",
- " 'location': 'left',\n",
- " \"title\": 'Difference with previous {}',\n",
+ " \"location\": \"left\",\n",
+ " \"title\": \"Difference with previous {}\",\n",
" },\n",
" \"ax2\": {\n",
" \"gs\": gs[1, 2:],\n",
- " \"shrink\": 0.6,\n",
- " \"pad\": 0.05,\n",
+ " \"shrink\": 0.7,\n",
+ " \"pad\": 0.02,\n",
" \"label\": \"%\",\n",
- " 'location': 'right',\n",
- " \"title\": 'Difference with previous {} %'},\n",
+ " \"location\": \"right\",\n",
+ " \"title\": \"Difference with previous {} %\"},\n",
" })"
]
},
@@ -239,7 +260,7 @@
" mean_frac = np.abs(mean_diff / mean_const) * 100\n",
" \n",
" for gain in range(gainstages):\n",
- " plot_data = {\n",
+ " data_to_plot = {\n",
" f'ax0': mean_const[..., gain],\n",
" f'ax1': mean_diff[..., gain],\n",
" f'ax2': mean_frac[..., gain],\n",
@@ -248,9 +269,10 @@
" # Plotting constant overall modules.\n",
" display(Markdown(f'### {cname} - {gain_names[gain]}'))\n",
" if nmods > 1:\n",
- " fig = plt.figure(figsize=(30, 30))\n",
+ " fig = plt.figure(figsize=(20, 20))\n",
" else:\n",
- " fig = plt.figure(figsize=(31, 18))\n",
+ " fig = plt.figure(figsize=(20, 10))\n",
+ " \n",
" for axname, axv in axis.items():\n",
" # Add the min and max plot values for each axis.\n",
" if axname == \"ax0\":\n",
@@ -259,16 +281,21 @@
" vmin, vmax = 0, 100\n",
" else:\n",
" vmin, vmax = diff_const_range[cname][gain]\n",
+ " # Avoid difference plots if previous constants\n",
+ " # are missing for the detector.\n",
+ " if cname in execulded_constants and axname != \"ax0\":\n",
+ " break\n",
" ax = fig.add_subplot(axv[\"gs\"])\n",
"\n",
- " geom.plot_data_fast(\n",
- " plot_data[axname],\n",
+ " geom.plot_data(\n",
+ " data_to_plot[axname],\n",
" vmin=vmin, vmax=vmax, ax=ax, \n",
" colorbar={\n",
" \"shrink\": axv[\"shrink\"],\n",
" \"pad\": axv[\"pad\"],\n",
- " \"location\": axv[\"location\"]},\n",
- " )\n",
+ " \"location\": axv[\"location\"],\n",
+ " }\n",
+ " )\n",
"\n",
" colorbar = ax.images[0].colorbar\n",
" colorbar.set_label(axv[\"label\"], fontsize=15)\n",