Recent Releases of hist-unmix
hist-unmix - Hist-unmin_v1.0.2
Hist-unmix is an open-sourced package, in Python language (ipynb-file), to separate susceptibility components of distorted hysteresis curves through a phenomenological model. The Hist-unmix package allows the user to adjust a forward model of up to three ferromagnetic components and a dia/paramagnetic contribution. Optimization of all of the parameters is achieved through least squares fit (Levenberg-Marquardt method) providing an uncertainty for the inverted parameters through a Monte Carlo error propagation. For each ferromagnetic component, it is possible to calculate magnetization saturation (Ms), magnetization saturation of remanence (Mrs), and the mean coercivity (Bc).
- Python
Published by bellon-donardelli over 2 years ago
hist-unmix - Hist-unmin_v1.0.1
Hist-unmix is an open-sourced package, in Python language (ipynb-file), to separate susceptibility components of distorted hysteresis curves through a phenomenological model. The Hist-unmix package allows the user to adjust a forward model of up to three ferromagnetic components and a dia/paramagnetic contribution. Optimization of all of the parameters is achieved through least squares fit (Levenberg-Marquardt method) providing uncertainty for the inverted parameters through a Monte Carlo error propagation. For each ferromagnetic component, it is possible to calculate magnetization saturation, magnetization saturation of remanence and the mean coercivity.
- Python
Published by bellon-donardelli almost 3 years ago
hist-unmix - Hist-unmin_v1.0.0
Hist-unmix is an open-sourced package, in python language (ipynb-file), to separate susceptibility components of distorted hysteresis curves through a phenomenological model. The Hist-unmix package allows the user to adjust a forward model of up to three ferromagnetic components and a dia/paramagnetic contribution. Optimization of all of the parameters is achieved through least squares fit (Levenberg-Marquardt method) providing an uncertainty for the inverted parameters through a Monte Carlo error propagation. For each ferromagnetic component, it is possible to calculate magnetization saturation, magnetization saturation of remanence and the mean coercivity.
- Python
Published by bellon-donardelli almost 3 years ago