def omega_m(model):
z, w_x, c2_x, PP, gamma, model_name = model_check(model)
label1 = model_name + 'z = %s,' %z + ' $w_x$ = %s,' %w_x + ' $c^2_x$ = %s,' %c2_x + ' $\Gamma$ = %s' %gamma
omega_m = var.back_vars(model)[0]; omega_x = var.back_vars(model)[1]
semilogx(cc.a, omega_m, next(linecycler), linewidth = 2, label = label1 + ' :: $\Omega_m$' )
semilogx(cc.a, omega_x, next(linecycler),linewidth = 2, label = label1 + ' :: $\Omega_x$')
legend(loc = 'best', prop = {'size':9}) #, ncol = 3
xlabel('a')
xlim((4 * 10**-2, 1.0))
ylim((-0.05 , 1.05))
def h(model):
z, w_x, c2_x, PP, gamma, model_name = model_check(model)
label1 = model_name + 'z = %s,' %z + ' $w_x$ = %s,' %w_x + ' $c^2_x$ = %s,' %c2_x + ' $\Gamma$ = %s' %gamma
h = var.back_vars(model)[2]
loglog(cc.a, h, next(linecycler), linewidth = 2, label = label1)
legend(loc = 'best', prop = {'size':9})
xlim((10**-1, 1.0))
ylim(( 1.0, 0.2 * 10**2))
xlabel('a')
ylabel('h(a)')
def w_x(model):
w_x = var.back_vars(model)[3]
semilogx(cc.a, w_x, next(linecycler), linewidth = 2, label = model)
legend(loc = 'best')
xlabel('a')
ylabel('$w_x(a)$')
