py_mazars.py
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	#!/usr/bin/env python3

	import numpy as np


	class Mazars:
	def __init__(self, **kwargs):
	self.K0 = kwargs.pop("K0", 1e-4)
	self.At = kwargs.pop("At", 1.0)
	self.Bt = kwargs.pop("Bt", 5e3)
	self.Ac = kwargs.pop("Ac", 0.8)
	self.Bc = kwargs.pop("Bc", 1391.3)

	self.E = kwargs.pop("E", 25e9)
	self.nu = kwargs.pop("nu", 0.2)

	self.dam = 0

	self.Gf = 0
	self.ε_p = 0
	self.σ_p = 0

	def compute_step(self, ε, σ, dam, trace):
	dam_t = 0
	# dam_c = 0

	if trace:
	import pdb
	pdb.set_trace()

	σ = self.E * ε
	if ε > self.K0:
	dam_t = 1 - self.K0*(1 - self.At)/ε - \
	self.At * np.exp(-self.Bt*(ε - self.K0))
	# dam_c = 1 - self.K0*(1 - self.Ac)/ε - \
	# self.Ac * np.exp(-self.Bc*(ε - self.K0))

	dam = max(dam, dam_t)
	dam = min(dam, 1)

	σ = (1 - dam) * σ
	return σ, dam

	# def compute(self, **kwargs):
	# epsilons = np.array(kwargs['epsilons'], copy=False)
	# sigmas = np.array(kwargs['sigmas'], copy=False)
	# damages = np.array(kwargs['damages'], copy=False)

	# for t, ε in enumerate(epsilons):
	# σ = 0.
	# dam = 0.
	# self.compute_step(ε, σ, dam)

	# self.Gf = self.Gf + (σ + σ_p) * (ε - ε_p) / 2.
	# self.σ_p = σ
	# self.ε_p = ε

	# sigmas[t] = σ
	# damages[t] = self.dam
	# return self.Gf