.. _isotopes:

=======================
Isotopes & Decay Chains
=======================

Curie provides access to isotopic masses and decay data, which is a collection from the NNDC's Nudat2, the wallet cards,
the atomic mass evaluation, and ENDF (for decay branching ratios and some half-lives).  This is provided by the `Isotope`
class.  For a complete list of methods and attributes, see the Curie :ref:`api`.

Examples::

	ip = ci.Isotope('115INm')
	ip = ci.Isotope('Cu-67')
	print(ip.dose_rate(units='mR/h'))
	ip = ci.Isotope('58NI')
	print(ip.abundance)

	ip = ci.Isotope('135CEm')
	print(ip.dc)
	ip = ci.Isotope('235U')
	print(ip.get_NFY(E=0.0253))

	ip = ci.Isotope('221AT')
	print(ip.decay_const())
	print(ip.decay_const('m', True))

	ip = ci.Isotope('226RA')
	print(ip.half_life())
	print(ip.optimum_units())
	print(ip.half_life(ip.optimum_units()))

	ip = ci.Isotope('Co-60')
	print(ip.gammas(I_lim=1.0))

	ip = ci.Isotope('64CU')
	print(ip.gammas())
	print(ip.gammas(xrays=True, dE_511=1.0))

	ip = ci.Isotope('Pt-193m')
	print(ip.electrons(I_lim=5.0, E_lim=(10.0, 130.0)))

	ip = ci.Isotope('35S')
	print(ip.beta_minus())

	ip = ci.Isotope('18F')
	print(ip.beta_plus())

	ip = ci.Isotope('210PO')
	print(ip.alphas(I_lim=1.0))

	ip = ci.Isotope('Co-60')
	print(ip.dose_rate(activity=3.7E10, units='R/hr'))


Curie also has a general-purpose implementation of the Batemann equations for a radioactive decay chain.
The `DecayChain` class can calculate the activity of any isotope in a decay chain for a specified initial
activity, or production rate.  The decay chain is a collection of all isotopes originating from a "parent"
radionuclide.  The class is also capable of fitting a production rate or initial activity to a set
of observed decays, or retrieving these from gamma-ray spectra.

Examples::

	dc = ci.DecayChain('Ra-225', R=[[1.0, 1.0], [0.5, 1.5], [2.0, 6]], units='d')
	print(dc.R_avg)
	print(dc.isotopes)
	dc.plot()

	sp = ci.Spectrum('eu_calib_7cm.Spe')
	sp.isotopes = ['152EU']
	sp.saveas('test_spec.json')

	dc = ci.DecayChain('152EU', A0=3.7E3, units='h')
	dc.get_counts([sp], EoB='01/01/2016 08:39:08')
	dc.get_counts(['eu_calib_7cm.Spe'], EoB='01/01/2016 08:39:08', peak_data='test_spec.json')

	print(dc.decays('152EU', t_start=1, t_stop=2))
	print(dc.decays('152EU', t_start=50, t_stop=50.1, units='y'))
	print(dc.activity('152EU', time=0))
	print(dc.activity('152EU', time=13.537, units='y'))
	print(dc.fit_A0())
	dc.plot()

	dc = ci.DecayChain('152EU', R=[[3E5, 36.0]], units='d')
	dc.get_counts(['eu_calib_7cm.Spe'], EoB='01/01/2016 08:39:08', peak_data='test_spec.json')
	dc.get_counts([sp], EoB='01/01/2016 08:39:08')
	dc.fit_R()
	print(dc.fit_R())
	print(dc.R_avg)
	print(dc.isotopes)
	dc.plot()

	dc = ci.DecayChain('99MO', A0=350E6, units='d')
	dc.plot()