diff --git a/notebooks/LPD/LPDChar_Darks_NBC.ipynb b/notebooks/LPD/LPDChar_Darks_NBC.ipynb index a364b2fe252600908d8038aa81310c944fe7b016..360eebee416b3b38573f531053aa69ffca0742eb 100644 --- a/notebooks/LPD/LPDChar_Darks_NBC.ipynb +++ b/notebooks/LPD/LPDChar_Darks_NBC.ipynb @@ -750,7 +750,7 @@ "for cap in capacitor_settings:\n", " for gain in range(3):\n", " display(\n", - " Markdown('### Cell-12 overview - {} gain.'.format(gain_names[gain])))\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", " for qm in res[cap]:\n", @@ -859,7 +859,7 @@ "rebin = 8 if not high_res_badpix_3d else 2\n", "\n", "for gain in range(3):\n", - " display(Markdown('### Bad pixel behaviour - {} gain. ###'.format(gain_names[gain])))\n", + " display(Markdown('### Bad pixel behaviour - {} gain ###'.format(gain_names[gain])))\n", " for cap in capacitor_settings:\n", " for mod, data in badpix_g[cap].items():\n", " plot_badpix_3d(data[...,gain], cols, title='', rebin_fac=rebin)\n", @@ -915,7 +915,7 @@ "for cap in res:\n", " for qm in res[cap]:\n", " for gain in range(3):\n", - " display(Markdown('### Summary across tiles - {} gain.'.format(gain_names[gain])))\n", + " display(Markdown('### Summary across tiles - {} gain'.format(gain_names[gain])))\n", "\n", " for const in res[cap][qm]:\n", " data = np.copy(res[cap][qm][const][:, :, :, gain])\n", @@ -1014,7 +1014,7 @@ "for cap in res:\n", " for qm in res[cap]:\n", " for gain in range(3):\n", - " display(Markdown('### Variation of offset and noise across ASICs - {} gain.'.format(gain_names[gain])))\n", + " display(Markdown('### Variation of offset and noise across ASICs - {} gain'.format(gain_names[gain])))\n", "\n", " fig = plt.figure(figsize=(15, 6))\n", " for iconst, const in enumerate(['Offset', 'Noise']):\n", @@ -1049,7 +1049,7 @@ "for cap in res:\n", " for qm in res[cap]:\n", " for gain in range(3):\n", - " display(Markdown('### Variation of offset and noise across tiles - {} gain.'.format(gain_names[gain])))\n", + " display(Markdown('### Variation of offset and noise across tiles - {} gain'.format(gain_names[gain])))\n", "\n", " fig = plt.figure(figsize=(15, 6))\n", " for iconst, const in enumerate(['Offset', 'Noise']):\n", @@ -1105,7 +1105,7 @@ "for cap in res:\n", " for qm in res[cap]:\n", " for gain in range(3):\n", - " display(Markdown('### Mean over pixels - {} gain.'.format(gain_names[gain])))\n", + " display(Markdown('### Mean over pixels - {} gain'.format(gain_names[gain])))\n", " \n", " fig = plt.figure(figsize=(9,11))\n", "\n", @@ -1285,7 +1285,7 @@ "\n", " table.append(line)\n", "\n", - " display(Markdown('### {} [ADU]. Good pixels only. ###'.format(const)))\n", + " display(Markdown('### {} [ADU], good pixels only ###'.format(const)))\n", " md = display(Latex(tabulate.tabulate(table, tablefmt='latex', headers=header))) " ] } diff --git a/notebooks/LPD/LPDChar_Darks_Summary_NBC.ipynb b/notebooks/LPD/LPDChar_Darks_Summary_NBC.ipynb index a0ea28996740c460fa6e082c34c34c6ce0ea4001..975eeff63b6112e4089da3300cedf9ca4c15148c 100644 --- a/notebooks/LPD/LPDChar_Darks_Summary_NBC.ipynb +++ b/notebooks/LPD/LPDChar_Darks_Summary_NBC.ipynb @@ -233,12 +233,12 @@ "# Loop over capacitor settings, modules, constants\n", "for const_name, const in constants.items():\n", "\n", - " display(Markdown('### Summary across Modules - {}.'.format(const_name)))\n", + " display(Markdown('### Summary across Modules - {}'.format(const_name)))\n", " for gain in range(3):\n", " data = np.copy(const[:, :, :, :, gain])\n", "\n", " if const_name != 'BadPixelsDark':\n", - " label = '{} value [ADU]. Good pixels only.'.format(const_name)\n", + " label = '{} value [ADU], good pixels only'.format(const_name)\n", " data[constants['BadPixelsDark'][:, :, :, :, gain] > 0] = np.nan\n", " datamean = np.nanmean(data, axis=(1, 2))\n", "\n", @@ -300,7 +300,7 @@ "\n", " if const_name != 'BadPixelsDark':\n", " ax = fig.add_subplot(122)\n", - " label = '$\\sigma$ {} [ADU]. Good pixels only.'.format(const_name)\n", + " label = '$\\sigma$ {} [ADU], good pixels only'.format(const_name)\n", " d = []\n", " for im, mod in enumerate(np.nanstd(data, axis=(1, 2))):\n", " d.append({'x': np.arange(mod.shape[0]),\n", @@ -376,7 +376,7 @@ " t_line.append('{:6.0f} ({:6.3f}) '.format(\n", " datasum, datamean))\n", " \n", - " label = '## Number (fraction) of bad pixels.'\n", + " label = '## Number (fraction) of bad pixels'\n", " else:\n", "\n", " data[constants['BadPixelsDark']\n", @@ -385,7 +385,7 @@ " t_line.append('{:6.1f} $\\\\pm$ {:6.1f}'.format(\n", " np.nanmean(data), np.nanstd(data)))\n", " \n", - " label = '## Average {} [ADU]. Good pixels only. ##'.format(const_name)\n", + " label = '## Average {} [ADU], good pixels only ##'.format(const_name)\n", " \n", " \n", " table.append(t_line)\n",