Exporting measurement data

Up to this point, you parsed the readings of your measurements of Lu-177 from the Hidex 300 SL automatic liquid scintillator counter CSV files, and processed them to get the background, sample and net measurements. You have all this information organized and stored in tables, and you made some plots of the measurements.

The next thing you may want to do is exporting the tables to text file for further processing or reporting. You may also want to export the plots to images to be used in reports or presentations. Let’s see how you can do this using the Hidex300 class.

Save tables

Save background measurements table

Create a new folder to store the measurements’ results. Let’s say that you create a folder called output_files inside the measurements folder where you had the input_files folder:

measurements/
    input_files/
        Lu-177_2023_11_30.csv
        Lu-177_2023_12_06.csv
        Lu-177_2023_12_12.csv
        Lu-177_2023_12_22.csv
    output_files/

Take the processor from the previous section. Define the path to the folder that contains the input files:

>>> folder_path = 'output_files'

Let’s export the background measurements to a CSV file. To do this, use the processor.export_table() method and specify the type of measurement you want to process and the output folder to save the file:

>>> processor.export_table(kind='background', folder_path=output_folder)
Background measurements CSV saved to "output_files" folder.

Now if you navigate to the output_files folder you will find a file called background.csv containing all the quantities of interest for the background measurements for each cycle and repetition in CSV format:

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 (%)
1,1,1,83.97,140,1.0,100,2023-11-30 08:44:20,100.0,0 days 00:00:00,0.0,139.95,11.830046491878212,8.453052155682895
1,1,2,87.57,146,1.0,100,2023-11-30 08:51:04,100.0,0 days 00:06:44,404.0,145.95,12.080976781701056,8.277476383488219
2,1,1,92.36,154,1.0,100,2023-12-06 10:23:19,100.0,6 days 01:38:59,524339.0,153.93333333333334,12.40698727868024,8.059974412308515
2,1,2,87.56,146,1.0,100,2023-12-06 10:30:03,100.0,6 days 01:45:43,524743.0,145.93333333333334,12.080286972308784,8.277949044524064
3,1,1,82.16,137,1.0,100,2023-12-12 08:41:22,100.0,11 days 23:57:02,1036622.0,136.93333333333334,11.701851705321399,8.545656065229844
3,1,2,82.77,138,1.0,100,2023-12-12 08:48:04,100.0,12 days 00:03:44,1037024.0,137.95,11.745211790342479,8.5141078581678
4,1,1,98.36,164,1.0,100,2023-12-22 08:47:48,100.0,22 days 00:03:28,1901008.0,163.93333333333334,12.803645314258487,7.810275710202412
4,1,2,76.17,127,1.0,100,2023-12-22 08:54:28,100.0,22 days 00:10:08,1901408.0,126.95,11.267209059922514,8.875312374889731

Note

To export measurements tables using the processor.export_table() method, you need to parse the readings first using the processor.parse_readings() method and and process the readings using the processor.process_readings() method. Otherwise, you will get an error.

Save sample measurements table

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

>>> processor.export_table(kind='sample', folder_path=output_folder)
Background measurements CSV saved to "output_files" folder.

Now if you navigate to the output_files folder you will find a file called sample.csv containing all the quantities of interest for the sample measurements for each cycle and repetition in CSV format:

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 (%)
1,2,1,252623.23,374237,1.125,100,2023-11-30 08:47:44,88.88888888888889,0 days 00:00:00,0.0,374256.63703703706,611.7651812885701,0.16346141143464313
1,2,2,251953.09,373593,1.124,100,2023-11-30 08:54:28,88.9679715302491,0 days 00:06:44,404.0,373595.9223013048,611.2249359289139,0.1636058906006906
2,2,1,134111.43,209724,1.066,100,2023-12-06 10:26:44,93.80863039399624,6 days 01:39:00,524340.0,209680.15947467164,457.9084618945927,0.21838425869277625
2,2,2,134390.68,210125,1.066,100,2023-12-06 10:33:27,93.80863039399624,6 days 01:45:43,524743.0,210116.76047529702,458.38494791528336,0.2181572507011761
3,2,1,72225.71,116255,1.035,100,2023-12-12 08:44:45,96.61835748792271,11 days 23:57:01,1036621.0,116305.49114331724,341.03590887664194,0.29322425409510633
3,2,2,72340.56,116440,1.035,100,2023-12-12 08:51:27,96.61835748792271,12 days 00:03:43,1037023.0,116490.43478260869,341.30695097318,0.2929913959117054
4,2,1,25236.95,41565,1.012,100,2023-12-22 08:51:10,98.81422924901186,22 days 00:03:26,1901006.0,41562.82938076417,203.86963820236736,0.4905095279599058
4,2,2,25656.06,42239,1.012,100,2023-12-22 08:57:50,98.81422924901186,22 days 00:10:06,1901406.0,42253.06324110672,205.55549917505667,0.48648661992174325

Save net measurements table

Next, you can export the radionuclide net measurements in the same way you just did for the background and sample measurements. Just use the processor.export_table() method specifying the type of measurements net:

>>> processor.export_table(kind='net', folder_path=output_folder)
Net measurements CSV saved to "output_files" folder.

Now if you navigate to the output_files folder you will find a file called net.csv containing all the quantities of interest for the sample measurements for each cycle and repetition in CSV format:

Cycle,Repetition,Elapsed time,Elapsed time (s),Count rate (cpm),Counts,Counts uncertainty,Counts uncertainty (%)
1,1,0 days 00:00:00,0.0,252539.26,374116.68703703705,611.8795527201714,0.16355313032577887
1,2,0 days 00:06:44,404.0,251865.52,373449.9723013048,611.3443156694146,0.16370179703110896
2,1,6 days 01:39:00,524340.0,134019.07,209526.22614133832,458.076514141475,0.21862490561562173
2,2,6 days 01:45:43,524743.0,134303.12,209970.8271419637,458.5441023594463,0.21838467209991003
3,1,11 days 23:57:01,1036621.0,72143.55,116168.5578099839,341.2366106921275,0.29374265905089897
3,2,12 days 00:03:43,1037023.0,72257.79,116352.48478260869,341.50898199404463,0.29351240983990595
4,1,22 days 00:03:26,1901006.0,25138.59,41398.89604743083,204.27129684343197,0.4934220869305253
4,2,22 days 00:10:06,1901406.0,25579.890000000003,42126.11324110672,205.86406495818233,0.4886851625259837

Save plots

Save background measurements plot

Now that you have exported the measurement tables to CSV files, let’s export the measurements plots to PNG images. To export the background measurements plot, use the processor.export_plot() method and specify the type of measurement you want to process and the output folder to save the file:

>>> processor.export_plot(kind='background', folder_path=output_folder)
Background measurements PNG saved to "output_files" folder.

Now if you navigate to the output_files folder you will find a file called background.png containing plots of the quantities of interest for the background measurements in terms of time.

Save sample measurements plot

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

>>> processor.export_plot(kind='sample', folder_path=output_folder)
Background measurements PNG saved to "output_files" folder.

Now if you navigate to the output_files folder you will find a file called sample.png containing plots of the quantities of interest for the sample measurements in terms of time.

Save net measurements plot

Next, you can export the radionuclide net measurements plot in the same way you just did for the background and sample measurements. Just use the processor.export_plot() method specifying the type of measurements net:

>>> processor.export_plot(kind='net', folder_path=output_folder)
Net measurements PNG saved to "output_files" folder.

Now if you navigate to the output_files folder you will find a file called net.png containing plots of the quantities of interest for the net measurements in terms of time.