From d862aab80ed7b94e8a0a1d32ea90bdc833973f13 Mon Sep 17 00:00:00 2001
From: karnem <mikhail.karnevskiy@desy.de>
Date: Sun, 29 Dec 2019 16:40:51 +0100
Subject: [PATCH] comparison with constants in summary
---
notebooks/LPD/LPDChar_Darks_NBC.ipynb | 46 +++++++--------------------
1 file changed, 12 insertions(+), 34 deletions(-)
diff --git a/notebooks/LPD/LPDChar_Darks_NBC.ipynb b/notebooks/LPD/LPDChar_Darks_NBC.ipynb
index 09826cea8..0e878db3a 100644
--- a/notebooks/LPD/LPDChar_Darks_NBC.ipynb
+++ b/notebooks/LPD/LPDChar_Darks_NBC.ipynb
@@ -68,7 +68,7 @@
"\n",
"mem_cells = 512 # number of memory cells used\n",
"local_output = True # output constants locally\n",
- "db_output = True # output constants to database\n",
+ "db_output = False # output constants to database\n",
"bias_voltage = 250 # detector bias voltage\n",
"cal_db_interface = \"tcp://max-exfl016:8015#8025\" # the database interface to use\n",
"cal_db_timeout = 300000 # timeout on caldb requests\"\n",
@@ -192,8 +192,7 @@
"outputs": [],
"source": [
"# set everything up filewise\n",
- "if not os.path.exists(out_folder):\n",
- " os.makedirs(out_folder)\n",
+ "os.makedirs(out_folder, exist_ok=True)\n",
"\n",
"gmf = gain_map_files(in_folder, gain_runs, sequences, DET_FILE_INSET, QUADRANTS, MODULES_PER_QUAD)\n",
"gain_mapped_files, total_sequences, total_file_size = gmf"
@@ -359,30 +358,6 @@
"logger.send()"
]
},
- {
- "cell_type": "code",
- "execution_count": null,
- "metadata": {},
- "outputs": [],
- "source": [
- "# save everything to file.\n",
- "if local_output:\n",
- " for cap in capacitor_settings:\n",
- " runs = [v for k, v in gain_runs.items() if cap in k]\n",
- " ofile = \"{}/lpd_offset_store_{}_{}_{}.h5\".format(out_folder, \n",
- " \"_\".join(runs), \n",
- " cap, \n",
- " \"_\".join([str(m) for m in modules]))\n",
- " store_file = h5py.File(ofile, \"w\")\n",
- " for qm in offset_g[cap].keys():\n",
- " store_file[\"{}/Offset/0/data\".format(qm)] = offset_g[cap][qm]\n",
- " store_file[\"{}/Noise/0/data\".format(qm)] = noise_g[cap][qm]\n",
- " store_file[\"{}/BadPixelsDark/0/data\".format(qm)\n",
- " ] = badpix_g[cap][qm]\n",
- " store_file.close()\n",
- " print('Constants are stored to {}'.format(ofile))"
- ]
- },
{
"cell_type": "code",
"execution_count": null,
@@ -414,6 +389,8 @@
" if mdata is not None and data is not None:\n",
" time = mdata.calibration_constant_version.begin_at\n",
" old_mdata[const] = time.isoformat()\n",
+ " os.makedirs('{}/old/'.format(out_folder), exist_ok=True)\n",
+ " save_const_to_h5(mdata, '{}/old/'.format(out_folder))\n",
" else:\n",
" old_mdata[const] = \"Not found\""
]
@@ -455,6 +432,10 @@
"# Save constants in the calibration DB\n",
"for cap in capacitor_settings:\n",
" for qm in res[cap]:\n",
+ " # Do not store empty constants\n",
+ " # In case of 0 trains data_g is initiated with nans and never refilled.\n",
+ " if np.count_nonzero(~np.isnan(data_g[cap][qm]))==0:\n",
+ " continue\n",
" for const in res[cap][qm]:\n",
"\n",
" metadata = ConstantMetaData()\n",
@@ -577,7 +558,7 @@
"for cap in capacitor_settings:\n",
" for i in modules:\n",
" qm = \"Q{}M{}\".format(i//4+1, i % 4+1)\n",
- " if data_g[cap][qm].shape[0] == 0:\n",
+ " if np.count_nonzero(~np.isnan(data_g[cap][qm])) == 0:\n",
" break\n",
" for gain in range(3):\n",
" data = data_g[cap][qm][:, gain]\n",
@@ -743,11 +724,11 @@
" display(\n",
" Markdown('### Cell-12 overview - {} gain'.format(gain_names[gain])))\n",
"\n",
- " fig = plt.figure(figsize=(15, 12) , tight_layout={'pad': 0.1, 'w_pad': 0.1})\n",
+ " fig = plt.figure(figsize=(18, 22) , tight_layout={'pad': 0.1, 'w_pad': 0.1})\n",
" for qm in res[cap]:\n",
" for iconst, const in enumerate(['Offset', 'Noise', 'BadPixelsDark']):\n",
"\n",
- " ax = fig.add_subplot(221+iconst)\n",
+ " ax = fig.add_subplot(321+iconst)\n",
"\n",
" data = res[cap][qm][const][:, :, 12, gain]\n",
" vmax = 1.5 * np.nanmedian(res[cap][qm][const][:, :, 12, gain])\n",
@@ -779,9 +760,6 @@
" use_axis=ax,\n",
" title='{}'.format(title))\n",
"\n",
- " #show_overview(res[cap], cell, gain, out_folder=out_folder, infix=\"_\".join(gain_runs.values()))\n",
- "\n",
- " fig = plt.figure(figsize=(10, 5))\n",
" for qm in res[cap]:\n",
" for iconst, const in enumerate(['Offset', 'Noise']):\n",
" data = res[cap][qm][const]\n",
@@ -805,7 +783,7 @@
" },\n",
" ]\n",
"\n",
- " ax = fig.add_subplot(121+iconst)\n",
+ " ax = fig.add_subplot(325+iconst)\n",
" _ = simplePlot(d, figsize=(5, 7), aspect=1,\n",
" x_label=\"{} value [ADU]\".format(const),\n",
" y_label=\"# of occurance\",\n",
--
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