An open source radiocarbon (14C) calibration software. Written in Python
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What's new in IOSACal
Release news for IOSACal.
Release 0.5 (in progress)
This release brings the new IntCal20 calibration data and several
improvements for different use cases, plus one important bug fix.
- the project has moved to **Codeberg** for source code hosting and issue
tracking. The new Git repository is at with a default branch name of
- there is an official **Code of Conduct** that all contributors
(including the maintainter) will need to follow
- the documentation has seen some improvements, in particular in the
*Contributing* section. Overall, making contributions easier from both
expert and novice users is a major theme in this release.
- interactive use in Jupyter notebooks is made easier with
CalibrationCurve that can be created in many ways (such as loading
from an arbitrary file, or from a standard calibration curve called
by shorthand)
- fixed a bug that made plots with AD/CE setting incorrect
(contributed by Karl Håkansson)
- add IntCal20 calibration data (contributed by Wesley Weatherbee)
On the technical side:
- the command line interface is now based on the Click library
- most code is now covered by tests, based on pytest
- Python 3.6 or above required
- requires Numpy 1.18 and Matplotlib 3.0
Release 0.4 (released 2018-05-08)
The main highlight of this release are the new classes for summed probability
distributions (SPD) and paleodemography, contributed by Mario Gutiérrez-Roig
as part of his work for the PALEODEM_ project at IPHES_.
.. _IPHES:
On the technical side:
- requires NumPy 1.14, SciPy 1.1 and Matplotlib 2.2
- removed dependencies on obsolete functions
- improved the command line interface
Release 0.3 (released 2016-04-15)
- use ``genfromtxt`` to import calibration curves
- improved documentation
- intervals as a well-defined type
- restore AD/BC dates in both text and graphic output
Release 0.2 (released 2014-02-14)
Main highlights:
- new function to combine multiple determinations (Ward & Wilson 1978)
- a simple and straightforward set of commands to get started
- amazing interactive mode with IPython Notebook
- plotting multiple dates in a stacked plot actually works
- added several older calibration curves (useful to check published data)
On the technical side:
- works with Python 3 only, dropped compatibility with Python 2
- requires NumPy 1.8 and Matplotlib 1.3
- calibration curves and calibrated ages are ``ndarray`` objects, super-easy
to work with
Known issues:
- AD/BC dates in output are not available, all dates are given as CalBP