def diff_P_Delta_m(BP, **cosmo):
diff_P_Delta_m_0 = (var.power_spectra_linear("wcdm_%s" %cc.w_x, BP, **cosmo) - var.power_spectra_linear("wcdm_%s" %cc.w_x, BP, **cosmo))/var.power_spectra_linear("wcdm_%s" %cc.w_x, BP, **cosmo)
diff_P_Delta_m = (var.power_spectra_linear("gwcdm_%s" %cc.gamma, BP, **cosmo) - var.power_spectra_linear("wcdm_%s" %cc.w_x, BP, **cosmo))/var.power_spectra_linear("wcdm_%s" %cc.w_x, BP, **cosmo)
#diff_P_Delta_m = (var.power_spectra_linear("gwcdm_%s" %cc.gamma_0, BP, **cosmo) - var.power_spectra_linear("lcdm", BP, **cosmo))/var.power_spectra_linear("lcdm", BP, **cosmo)
semilogx(cc.k, diff_P_Delta_m_0 * 100, next(linecycler), linewidth = 2)
semilogx(cc.k, diff_P_Delta_m * 100, next(linecycler), linewidth = 2, label = "$\Gamma$: %s" %cc.gamma)
legend(loc = 'best')
axvline(x = 0.17 * 10**-2, color='r', ls = '--') # vertical line at k_eq
axvline(x = 0.14 * 10**-1, color='b', ls = '-.') # vertical line at k_eq
xlim((cc.k_min, cc.k_max))
xlabel('k')
ylabel('$P^{\Gamma}_m$(k, a = 1) - $P^{\Lambda}_m$(k, a = 1)/$P^{\Lambda}_m$(k, a = 1) %')
def P_Delta_m(model, lcdm_model, **cosmo):
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
P_Delta_m = var.power_spectra_linear(model, lcdm_model, **cosmo)
loglog(cc.k, P_Delta_m, next(linecycler), linewidth = 2, label = label1)
legend(loc = 'best', prop = {'size':9})
axvline(x = 0.17 * 10**-2, color='r', ls = '--') # vertical line at k_eq
axvline(x = 0.14 * 10**-1, color='b', ls = '-.') # vertical line at k_eq
xlim((cc.k_min, cc.k_max))
xlabel('k')
ylabel('$P_m$(k, a = 1)')
