Processing the readings#

In the previous section, you parsed the readings of your measurements of Lu-177 from the Hidex 300 SL automatic liquid scintillator counter CSV files. You extracted, for each cycle and repetition, the measurements provided by the Hidex 300 SL automatic liquid scintillator counter of count rate, counts, real time, dead time and end time, both for the radionuclide sample and the background.

But you may need some extra information about the background and sample measurements. Also, you may need the net measurements derived from the sample and background measurements. Let’s see how you can do this using the Hidex300 class.

Process background measurements#

Take the processor from the previous section. Let’s get some other quantities of interest from the background readings. Process the background measurements using the processor.process_readings() method and specifying the type of measurement you want to process:

processor.process_readings(kind='background')

Then inspect the processed background readings to understand its structure and contents. The processor store the background measurements as a table using a pandas DataFrame. Access the background measurements by calling the processor.background attribute:

>>> print(processor.background)
   Cycle  Sample  Repetition  Count rate (cpm)  Counts (reading)  Dead time Real time (s)            End time  Live time (s)     Elapsed time Elapsed time (s)      Counts  Counts uncertainty  Counts uncertainty (%)
0      1       1           1             83.97               140        1.0           100 2023-11-30 08:44:20          100.0  0 days 00:00:00              0.0  139.950000           11.830046                8.453052
1      1       1           2             87.57               146        1.0           100 2023-11-30 08:51:04          100.0  0 days 00:06:44            404.0  145.950000           12.080977                8.277476
2      2       1           1             92.36               154        1.0           100 2023-12-06 10:23:19          100.0  6 days 01:38:59         524339.0  153.933333           12.406987                8.059974
3      2       1           2             87.56               146        1.0           100 2023-12-06 10:30:03          100.0  6 days 01:45:43         524743.0  145.933333           12.080287                8.277949
4      3       1           1             82.16               137        1.0           100 2023-12-12 08:41:22          100.0 11 days 23:57:02        1036622.0  136.933333           11.701852                8.545656
5      3       1           2             82.77               138        1.0           100 2023-12-12 08:48:04          100.0 12 days 00:03:44        1037024.0  137.950000           11.745212                8.514108
6      4       1           1             98.36               164        1.0           100 2023-12-22 08:47:48          100.0 22 days 00:03:28        1901008.0  163.933333           12.803645                7.810276
7      4       1           2             76.17               127        1.0           100 2023-12-22 08:54:28          100.0 22 days 00:10:08        1901408.0  126.950000           11.267209                8.875312

This table compiles all the quantities of interest for the background measurements for each cycle and repetition. In addition to the quantities parsed directly from the Hidex 300 SL automatic liquid scintillator counter CSV files (count rate, counts, real time, dead time and end time), it compiles the live time, elapsed time, and counts value and uncertainty. See more details about these quantities in the Topic guide.

Note

To process the background, sample or net measurements using the processor.process_readings() method, you need to parse the readings first using the processor.parse_readings() method. Otherwise, you will get an error.

Process sample measurements#

Next, you can process the radionuclide sample measurements in the same way you just did for the background measurements. Just use the processor.process_readings() method specifying the type sample instead of background:

>>> processor.process_readings(kind='sample')

Then inspect the processed sample readings by calling the processor.sample attribute:

>>> print(processor.sample)
   Cycle  Sample  Repetition  Count rate (cpm)  Counts (reading)  Dead time Real time (s)            End time  Live time (s)     Elapsed time Elapsed time (s)         Counts  Counts uncertainty  Counts uncertainty (%)
0      1       2           1         252623.23            374237      1.125           100 2023-11-30 08:47:44      88.888889  0 days 00:00:00              0.0  374256.637037          611.765181                0.163461
1      1       2           2         251953.09            373593      1.124           100 2023-11-30 08:54:28      88.967972  0 days 00:06:44            404.0  373595.922301          611.224936                0.163606
2      2       2           1         134111.43            209724      1.066           100 2023-12-06 10:26:44      93.808630  6 days 01:39:00         524340.0  209680.159475          457.908462                0.218384
3      2       2           2         134390.68            210125      1.066           100 2023-12-06 10:33:27      93.808630  6 days 01:45:43         524743.0  210116.760475          458.384948                0.218157
4      3       2           1          72225.71            116255      1.035           100 2023-12-12 08:44:45      96.618357 11 days 23:57:01        1036621.0  116305.491143          341.035909                0.293224
5      3       2           2          72340.56            116440      1.035           100 2023-12-12 08:51:27      96.618357 12 days 00:03:43        1037023.0  116490.434783          341.306951                0.292991
6      4       2           1          25236.95             41565      1.012           100 2023-12-22 08:51:10      98.814229 22 days 00:03:26        1901006.0   41562.829381          203.869638                0.490510
7      4       2           2          25656.06             42239      1.012           100 2023-12-22 08:57:50      98.814229 22 days 00:10:06        1901406.0   42253.063241          205.555499                0.486487

Process net measurements#

When measuring the activity of a radionuclide, you are often interested in the net measurements derived from the sample and background measurements, rather than in the sample measurement itself. You can process the radionuclide net measurements in the same way you just did for the background and sample measurements. Just use the processor.process_readings() method specifying the type of measurements net:

>>> processor.process_readings(kind='net')

Then inspect the net measurements by calling the processor.net attribute:

>>> print(processor.net)
   Cycle  Repetition     Elapsed time  Elapsed time (s)  Count rate (cpm)        Counts  Counts uncertainty  Counts uncertainty (%)
0      1           1  0 days 00:00:00               0.0         252539.26 374116.687037          611.879553                0.163553
1      1           2  0 days 00:06:44             404.0         251865.52 373449.972301          611.344316                0.163702
2      2           1  6 days 01:39:00          524340.0         134019.07 209526.226141          458.076514                0.218625
3      2           2  6 days 01:45:43          524743.0         134303.12 209970.827142          458.544102                0.218385
4      3           1 11 days 23:57:01         1036621.0          72143.55 116168.557810          341.236611                0.293743
5      3           2 12 days 00:03:43         1037023.0          72257.79 116352.484783          341.508982                0.293512
6      4           1 22 days 00:03:26         1901006.0          25138.59  41398.896047          204.271297                0.493422
7      4           2 22 days 00:10:06         1901406.0          25579.89  42126.113241          205.864065                0.488685

This table compiles all the quantities of interest for the net measurements for each cycle and repetition: elapsed time, count rate, and counts value and uncertainty. See more details about these quantities in the Topic guide.