diff --git a/notebooks/pnCCD/Correct_pnCCD_NBC.ipynb b/notebooks/pnCCD/Correct_pnCCD_NBC.ipynb
index 8723b6ef5aff7bcf3775c29a95bd1af3944fc64f..ab838561f5787a39709cc91bc5bc426ed5dc19ab 100644
--- a/notebooks/pnCCD/Correct_pnCCD_NBC.ipynb
+++ b/notebooks/pnCCD/Correct_pnCCD_NBC.ipynb
@@ -105,7 +105,6 @@
"import copy\n",
"import os\n",
"import glob\n",
- "import gc\n",
"import datetime\n",
"from datetime import timedelta\n",
"from prettytable import PrettyTable\n",
@@ -739,14 +738,8 @@
" ddsetp[...] = np.moveaxis(patterns, 2, 0)\n",
"\n",
" histCalPcorr.fill(data) # filling histogram with split events corrected data\n",
- " \n",
- " singles_events = np.zeros(data.shape, data.dtype)\n",
- " for s in range(100, 102): # events' patterns indices are: 100 (singles), 101 (first singles)\n",
- " singles_events = copy.copy(data[...])\n",
- " singles_events[patterns != s] = np.nan # Throwing out doubles, triples, quadruple, clusters\n",
- " histCalPcorrS.fill(singles_events) # filling histogram with singles events data\n",
- " del singles_events # This line and the next delet this variable from the memory so we do not \n",
- " gc.collect() # fill the memory up with copies of data per sequence\n",
+ " data[patterns != 100] = np.nan # Discard doubles, triples, quadruple, clusters, first singles\n",
+ " histCalPcorrS.fill(data) # filling histogram with singles events data\n",
" \n",
" # mean_im_cc = averaged over all pattern classified corrected images \n",
" # (in the first sequence only)\n",
@@ -815,7 +808,7 @@
"# good.\n",
"\n",
"if gain == 1:\n",
- " x_range = (3000, 16000)\n",
+ " x_range = (0, 30000)\n",
"elif gain == 64:\n",
" x_range = (0, 1000)"
]
@@ -885,7 +878,7 @@
" 'label': 'Singles Events'\n",
" }])\n",
"fig = xana.simplePlot(figure, aspect=1, x_label='ADU', y_label='Number of Occurrences', figsize='2col',\n",
- " y_log=True, x_range=xrange, title = '1 ADU per bin is used.',\n",
+ " y_log=True, x_range=x_range, title = '1 ADU per bin is used.',\n",
" legend='top-right-frame-1col')"
]
},
@@ -1063,35 +1056,6 @@
" a = ax.axis('equal')"
]
},
- {
- "cell_type": "code",
- "execution_count": null,
- "metadata": {
- "ExecuteTime": {
- "end_time": "2018-12-06T16:10:56.212586Z",
- "start_time": "2018-12-06T16:10:56.204731Z"
- }
- },
- "outputs": [],
- "source": [
- "# Again, we are setting a few parameters so that the plots always look good regardless of what the gain is:\n",
- "\n",
- "if gain == 1:\n",
- " vmin = -50 \n",
- " vmax = 40000\n",
- " panel_top_low_lim = -3000\n",
- " panel_top_high_lim = 65000\n",
- " panel_side_low_lim = -3000 \n",
- " panel_side_high_lim = 65000\n",
- "elif gain == 64:\n",
- " vmin = 0\n",
- " vmax = 20000\n",
- " panel_top_low_lim = 0\n",
- " panel_top_high_lim = 20000\n",
- " panel_side_low_lim = 0\n",
- " panel_side_high_lim = 20000"
- ]
- },
{
"cell_type": "markdown",
"metadata": {},
@@ -1112,61 +1076,29 @@
"outputs": [],
"source": [
"fig = xana.heatmapPlot(uncor_mean_im, x_label='Columns', y_label='Rows', lut_label='Signal (ADU)', aspect=1, \n",
- " x_range=(0, pixels_y), y_range=(0, pixels_x), vmin=vmin, vmax=vmax, \n",
- " panel_x_label='Row Stat (ADU)', panel_y_label='Column Stat (ADU)', \n",
- " panel_top_low_lim = panel_top_low_lim, panel_top_high_lim = panel_top_high_lim,\n",
- " panel_side_low_lim = panel_side_low_lim, panel_side_high_lim = panel_side_high_lim, \n",
+ " x_range=(0, pixels_y), y_range=(0, pixels_x), \n",
+ " panel_x_label='Row Stat (ADU)', panel_y_label='Column Stat (ADU)',\n",
" title = 'Uncorrected Image Averaged over the First Sequence')\n",
"\n",
- "# At lower gain, we need to change the vmin and vmax for the following plots:\n",
- "if gain == 64:\n",
- " vmin = 0\n",
- " vmax = 8000\n",
- " \n",
- "\n",
"fig = xana.heatmapPlot(offset_mean_im, x_label='Columns', y_label='Rows', lut_label='Signal (ADU)', aspect=1, \n",
- " x_range=(0, pixels_y), y_range=(0, pixels_x), vmin=vmin, vmax=vmax, \n",
- " panel_x_label='Row Stat (ADU)', panel_y_label='Column Stat (ADU)', \n",
- " panel_top_low_lim = panel_top_low_lim, panel_top_high_lim = panel_top_high_lim,\n",
- " panel_side_low_lim = panel_side_low_lim, panel_side_high_lim = panel_side_high_lim, \n",
+ " x_range=(0, pixels_y), y_range=(0, pixels_x), \n",
+ " panel_x_label='Row Stat (ADU)', panel_y_label='Column Stat (ADU)', \n",
" title = 'Offset Corrected Image Averaged over the First Sequence')\n",
"if corr_bools.get('relgain'):\n",
" fig = xana.heatmapPlot(gain_mean_im, x_label='Columns', y_label='Rows', \n",
" lut_label='Gain Corrected Signal (ADU)', aspect=1, \n",
- " x_range=(0, pixels_y), y_range=(0, pixels_x), vmin=vmin, vmax=vmax, \n",
- " panel_x_label='Row Stat (ADU)', panel_y_label='Column Stat (ADU)', \n",
- " panel_top_low_lim = panel_top_low_lim, panel_top_high_lim = panel_top_high_lim,\n",
- " panel_side_low_lim = panel_side_low_lim, panel_side_high_lim = panel_side_high_lim, \n",
+ " x_range=(0, pixels_y), y_range=(0, pixels_x), \n",
+ " panel_x_label='Row Stat (ADU)', panel_y_label='Column Stat (ADU)', \n",
" title = 'Mean Gain Corrected Image of the First Sequence')\n",
"\n",
"if corr_bools.get('pattern_class') and corr_bools.get('common_mode'):\n",
" fig = xana.heatmapPlot(cm_mean_im, x_label='Columns', y_label='Rows', lut_label='Signal (ADU)', aspect=1, \n",
- " x_range=(0, pixels_y), y_range=(0, pixels_x), vmin=vmin, vmax=vmax,\n",
+ " x_range=(0, pixels_y), y_range=(0, pixels_x), \n",
" panel_x_label='Row Stat (ADU)', panel_y_label='Column Stat (ADU)', \n",
- " panel_top_low_lim = panel_top_low_lim, panel_top_high_lim = panel_top_high_lim,\n",
- " panel_side_low_lim = panel_side_low_lim, panel_side_high_lim = panel_side_high_lim, \n",
" title = 'Common Mode Corrected Image Averaged over the First Sequence')\n",
" \n",
- "# Again, we need to change the vmin and vmax and other settings for this last plot:\n",
- " if gain == 1:\n",
- " vmin = 0\n",
- " vmax = 600\n",
- " panel_top_low_lim = 0\n",
- " panel_top_high_lim = 500\n",
- " panel_side_low_lim = 0\n",
- " panel_side_high_lim = 2000\n",
- " elif gain == 64:\n",
- " vmin = 0\n",
- " vmax = 600\n",
- " panel_top_low_lim = 0\n",
- " panel_top_high_lim = 2000\n",
- " panel_side_low_lim = 0\n",
- " panel_side_high_lim = 2000\n",
- " \n",
" fig = xana.heatmapPlot(mean_im_cc, x_label='Columns', y_label='Rows', lut_label='Signal (ADU)', aspect=1,\n",
- " x_range=(0, pixels_y), y_range=(0, pixels_x), vmin=vmin, vmax=vmax,\n",
- " panel_top_low_lim = panel_top_low_lim, panel_top_high_lim = panel_top_high_lim,\n",
- " panel_side_low_lim = panel_side_low_lim, panel_side_high_lim = panel_side_high_lim, \n",
+ " x_range=(0, pixels_y), y_range=(0, pixels_x),\n",
" title = 'Image after All Corrections Averaged over the First Sequence')"
]
},
@@ -1189,58 +1121,26 @@
},
"outputs": [],
"source": [
- "if gain == 1:\n",
- " vmin = -50\n",
- " vmax = 10000\n",
- " panel_top_low_lim = 0\n",
- " panel_top_high_lim = 20000\n",
- " panel_side_low_lim = 0\n",
- " panel_side_high_lim = 20000\n",
- " \n",
- "elif gain == 64:\n",
- " vmin = 0\n",
- " vmax = 2000\n",
- " panel_top_low_lim = 0\n",
- " panel_top_high_lim = 20000\n",
- " panel_side_low_lim = 0\n",
- " panel_side_high_lim = 20000\n",
- "\n",
"fig = xana.heatmapPlot(uncor_single_im, x_label='Columns', y_label='Rows', lut_label='Signal (ADU)', aspect=1, \n",
- " x_range=(0, pixels_y), y_range=(0, pixels_x), vmin=vmin, vmax=vmax,\n",
- " panel_x_label='Row Stat (ADU)', panel_y_label='Column Stat (ADU)', \n",
- " panel_top_low_lim = panel_top_low_lim, panel_top_high_lim = panel_top_high_lim,\n",
- " panel_side_low_lim = panel_side_low_lim, panel_side_high_lim = panel_side_high_lim, \n",
+ " x_range=(0, pixels_y), y_range=(0, pixels_x), \n",
+ " panel_x_label='Row Stat (ADU)', panel_y_label='Column Stat (ADU)', \n",
" title = 'Uncorrected Image (First Frame of First Sequence)')\n",
"\n",
"fig = xana.heatmapPlot(offset_single_im, x_label='Columns', y_label='Rows', lut_label='Signal (ADU)', aspect=1, \n",
- " x_range=(0, pixels_y), y_range=(0, pixels_x), vmin=vmin, vmax=vmax,\n",
- " panel_x_label='Row Stat (ADU)', panel_y_label='Column Stat (ADU)', \n",
- " panel_top_low_lim = panel_top_low_lim, panel_top_high_lim = panel_top_high_lim,\n",
- " panel_side_low_lim = panel_side_low_lim, panel_side_high_lim = panel_side_high_lim, \n",
+ " x_range=(0, pixels_y), y_range=(0, pixels_x),\n",
+ " panel_x_label='Row Stat (ADU)', panel_y_label='Column Stat (ADU)', \n",
" title = 'Offset Corrected Image (First Frame of First Sequence)')\n",
"\n",
"if corr_bools.get('pattern_class'):\n",
- " # At lower gain, we need to change the vmin and vmax for the following plots:\n",
- " if gain == 64:\n",
- " vmin = 0\n",
- " vmax = 600\n",
- " panel_top_low_lim = 0\n",
- " panel_top_high_lim = 800\n",
- " panel_side_low_lim = 0\n",
- " panel_side_high_lim = 800\n",
" if corr_bools.get('common_mode'):\n",
" fig = xana.heatmapPlot(cm_single_im, x_label='Columns', y_label='Rows', lut_label='Signal (ADU)', aspect=1, \n",
- " x_range=(0, pixels_y), y_range=(0, pixels_x), vmin=vmin, vmax=vmax,\n",
+ " x_range=(0, pixels_y), y_range=(0, pixels_x), \n",
" panel_x_label='Row Stat (ADU)', panel_y_label='Column Stat (ADU)', \n",
- " panel_top_low_lim = panel_top_low_lim, panel_top_high_lim = panel_top_high_lim,\n",
- " panel_side_low_lim = panel_side_low_lim, panel_side_high_lim = panel_side_high_lim, \n",
" title = 'Common Mode Corrected Image (First Frame of First Sequence)')\n",
" \n",
" fig = xana.heatmapPlot(single_im_cc, x_label='Columns', y_label='Rows', lut_label='Signal (ADU)', aspect=1,\n",
- " x_range=(0, pixels_y), y_range=(0, pixels_x), vmin=vmin, vmax=vmax,\n",
- " panel_x_label='Row Stat (ADU)', panel_y_label='Column Stat (ADU)', \n",
- " panel_top_low_lim = panel_top_low_lim, panel_top_high_lim = panel_top_high_lim,\n",
- " panel_side_low_lim = panel_side_low_lim, panel_side_high_lim = panel_side_high_lim, \n",
+ " x_range=(0, pixels_y), y_range=(0, pixels_x), \n",
+ " panel_x_label='Row Stat (ADU)', panel_y_label='Column Stat (ADU)', \n",
" title = 'Image after All Corrections (First Frame of First Sequence)')"
]
},