From ed217404af459dc6ffee9e1966826802ebb5ff31 Mon Sep 17 00:00:00 2001
From: Thomas Kluyver <thomas.kluyver@xfel.eu>
Date: Mon, 17 Feb 2025 16:31:30 +0100
Subject: [PATCH] Improve LPD darks per-memory-cell plots
---
notebooks/LPD/LPDChar_Darks_NBC.ipynb | 93 ++++++++++++++++-----------
1 file changed, 56 insertions(+), 37 deletions(-)
diff --git a/notebooks/LPD/LPDChar_Darks_NBC.ipynb b/notebooks/LPD/LPDChar_Darks_NBC.ipynb
index 11f1dd73a..3689c6035 100644
--- a/notebooks/LPD/LPDChar_Darks_NBC.ipynb
+++ b/notebooks/LPD/LPDChar_Darks_NBC.ipynb
@@ -1195,18 +1195,17 @@
" for gain in range(3):\n",
" display(Markdown('### Mean over pixels - {} gain'.format(gain_names[gain])))\n",
"\n",
- " fig = plt.figure(figsize=(9,11))\n",
+ " fig, axs = plt.subplots(nrows=3, figsize=(9,11))\n",
"\n",
- " for iconst, const in enumerate(res[qm]):\n",
- "\n",
- " ax = fig.add_subplot(311+iconst)\n",
+ " # Offset, Noise\n",
+ " non_mask_consts = [c for c in res[qm] if c != 'BadPixelsDark']\n",
"\n",
+ " for iconst, const in enumerate(non_mask_consts):\n",
" data = res[qm][const][:,:,:510,gain]\n",
- " if const == 'BadPixelsDark':\n",
- " data[data>0] = 1.0\n",
"\n",
+ " # Mask out bad pixels\n",
" dataBP = np.copy(data)\n",
- " dataBP[badpix_g[qm][:,:,:510,gain]>0] = -10\n",
+ " dataBP[badpix_g[qm][:,:,:510,gain]>0] = np.nan\n",
"\n",
" data = np.nanmean(data, axis=(0,1))\n",
" dataBP = np.nanmean(dataBP, axis=(0,1))\n",
@@ -1214,43 +1213,63 @@
" d = [{'y': data,\n",
" 'x': np.arange(data.shape[0]),\n",
" 'drawstyle': 'steps-mid',\n",
- " 'label' : 'All data'\n",
- " }\n",
- " ]\n",
- "\n",
- " if const != 'BadPixelsDark':\n",
- " d.append({'y': dataBP,\n",
+ " 'linestyle': 'dotted',\n",
+ " 'label' : 'All data',\n",
+ " },\n",
+ " {'y': dataBP,\n",
" 'x': np.arange(data.shape[0]),\n",
" 'drawstyle': 'steps-mid',\n",
- " 'label' : 'good pixels only'\n",
- " })\n",
- " y_title = \"{} value [ADU]\".format(const)\n",
- " title = \"{} value, {} gain\".format(const, gain_names[gain])\n",
- " else:\n",
- " y_title = \"Fraction of Bad Pixels\"\n",
- " title = \"Fraction of Bad Pixels, {} gain\".format(gain_names[gain])\n",
+ " 'label' : 'Good pixels only',\n",
+ " },\n",
+ " ]\n",
+ " data_min = np.nanmin([data, dataBP])\n",
+ " data_max = np.nanmax([data[20:], dataBP[20:]])\n",
"\n",
- " data_min = np.min([data, dataBP])if const != 'BadPixelsDark' else np.min([data])\n",
- " data_max = np.max([data[20:], dataBP[20:]])\n",
" data_dif = data_max - data_min\n",
"\n",
- " local_max = np.max([data[200:300], dataBP[200:300]])\n",
+ " # Ensure the line in the main plot isn't covered by the inset\n",
+ " local_max = np.nanmax([data[90:310], dataBP[90:310]])\n",
" frac = 0.35\n",
" new_max = (local_max - data_min*(1-frac))/frac\n",
- " new_max = np.max([data_max, new_max])\n",
- "\n",
- " _ = simplePlot(d, figsize=(10,10), aspect=2, xrange=(-12, 510),\n",
- " x_label = 'Memory Cell ID', \n",
- " y_label=y_title, use_axis=ax,\n",
- " title=title,\n",
- " title_position=[0.5, 1.15], \n",
- " inset='xy-coord-right', inset_x_range=(0,20), inset_indicated=True,\n",
- " inset_labeled=True, inset_coord=[0.2,0.5,0.6,0.95],\n",
- " inset_lw = 1.0, y_range = [data_min-data_dif*0.05, new_max+data_dif*0.05],\n",
- " y_log=False, legend='outside-top-ncol2-frame', legend_size='18%',\n",
- " legend_pad=0.00)\n",
- "\n",
- " plt.tight_layout(pad=1.08, h_pad=0.35)\n",
+ " new_max = np.nanmax([data_max, new_max])\n",
+ "\n",
+ " simplePlot(d, use_axis=axs[iconst], aspect=2,\n",
+ " x_range=(-12, 510),\n",
+ " y_range=(data_min-data_dif*0.05, new_max+data_dif*0.05),\n",
+ " x_label=\"Memory Cell ID\",\n",
+ " y_label=f\"{const} value [ADU]\",\n",
+ " title=f\"{const} value, {gain_names[gain]} gain\",\n",
+ " title_position=[0.5, 1.15],\n",
+ " inset='xy-coord-right', inset_x_range=(0,20), inset_indicated=True,\n",
+ " inset_labeled=True, inset_coord=[0.2, 0.5, 0.6, 0.95], inset_lw=1.0,\n",
+ " legend='top-right', legend_size='18%', legend_pad=0.00)\n",
+ "\n",
+ " # BadPixelsDark\n",
+ " data = res[qm]['BadPixelsDark'][:,:,:510,gain].copy()\n",
+ " data[data > 0] = 1.0\n",
+ " data = np.mean(data, axis=(0,1))\n",
+ "\n",
+ " d = [{'y': data, 'x': np.arange(data.shape[0]), 'drawstyle': 'steps-mid'}]\n",
+ " data_min, data_max = 0., 1.\n",
+ "\n",
+ " # Ensure the line in the main plot isn't covered by the inset\n",
+ " local_max = np.max(data[90:310])\n",
+ " frac = 0.35\n",
+ " new_max = (local_max - data_min*(1-frac))/frac\n",
+ " new_max = np.max([data_max, new_max])\n",
+ "\n",
+ " simplePlot(d, use_axis=axs[2], aspect=2,\n",
+ " x_label='Memory Cell ID',\n",
+ " y_label=\"Fraction of Bad Pixels\",\n",
+ " x_range=(-12, 510),\n",
+ " y_range=(data_min-0.05, new_max+0.05),\n",
+ " title=f\"Fraction of Bad Pixels, {gain_names[gain]} gain\",\n",
+ " title_position=[0.5, 1.15],\n",
+ " inset='xy-coord-right', inset_x_range=(0,20), inset_indicated=True,\n",
+ " inset_labeled=True, inset_coord=[0.2,0.5,0.6,0.95], inset_lw=1.0,\n",
+ " )\n",
+ "\n",
+ " fig.tight_layout(pad=1.08, h_pad=0.35)\n",
"\n",
" plt.show()"
]
--
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