The idea here is to automate evaluation of background scans on IRMS systems. For now, look at
| Scan time / s | m/z | Cup | file name end (.csv/.dxf) |
|---|---|---|---|
| 60 | 32 | 2 | *_O2 |
| 300 | 44 | 2 | *_CO2_2 |
| 300 | 44 | 3 | *_CO2_3 |
| 60 | 40 | 3 | *_Ar |
| 60 | 18 | 3 | *_H2O |
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take folder path as cmd line argument
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get all files with csv extension
- make sure they are named like we expect
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read in appropriate column using std.csv
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calculate standard deviation of the appropriate column using dstats.summary.stdev (https://github.com/DlangScience/dstats)
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for 44 calculate slope using dstats.regress.linearRegress or going with this: https://en.wikipedia.org/wiki/Simple_linear_regression#Fitting_the_regression_line or take inspiration from here: http://machinelearningmastery.com/implement-simple-linear-regression-scratch-python
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place results into a text file of appropriate format for copy pasting into confluence table / excel