IOSACal is written in Python 3, and it makes heavy use of the NumPy library
for the internal management of calibration curves and calibrated samples.
Calibration curves, radiocarbon dates and calibrated curves are handled
ndarray objects are matrices that can be
easily manipulated through slicing, flipping, summing and other typical
Generation of plots is done through Matplotlib, another Python
library built on top of NumPy. Matplotlib can natively read
ndarray objects and plot them in a graphical form. Far from being
just a set of plotting functions, Matplotlib allows the drawing of
complex plots like those created by IOSACal.
Development happens in a public git repository at GitLab.
The IntCal09 calibration curve has a varying resolution: data spacing changes from 5 years for the range from 0 to 11.2 to cal kBP, 10 yrs for 11.2–15 cal kBP, 20 yrs for 15–25 cal kBP, 50 yrs for 25–40 cal kBP, and 100 yrs for 40–50 cal kBP [REI2009]. Other curves follow a similar pattern.
This means that the output intervals would follow these limitations. IOSACal uses the interp function of NumPy to perform linear interpolation of the calibration curves and obtain more fine-grained results, particularly concerning probability intervals.
|[REI2009]||Reimer PJ, Baillie MGL, Bard E, Bayliss A, Beck JW, Blackwell PG, Bronk Ramsey C, Buck CE, Burr GS, Edwards RL, Friedrich M, Grootes PM, Guilderson TP, Hajdas I, Heaton TJ, Hogg AG, Hughen KA, Kaiser KF, Kromer B, McCormac FG, Manning SW, Reimer RW, Richards DA, Southon JR, Talamo S, Turney CSM, van der Plicht J, Weyhenmeyer CE. 2009. IntCal09 and Marine09 radiocarbon age calibration curves, 0–50,000 years cal BP. Radiocarbon 51(4):1111–50.|