#angmom = ort.angmom_fixed(ang_mode, phi)
angmom = ort.angmom_beta_phi(a, b, phi)
#print angmom
# calculate radar variables
alpha_cov = ort.avg_polcov(angmom, alpha_a, alpha_c)
avar_hh = alpha_cov[0]
avar_vv = alpha_cov[1]
avar_hv = alpha_cov[2]
acov_hh_vv = alpha_cov[3]
acov_hh_hv = alpha_cov[4]
acov_vv_hv = alpha_cov[5]
adp = alpha_cov[6]
zdr, ldr, kdp, rhohv, zh, rhoxh = ort.radar(wavl, avar_hh, avar_vv, avar_hv,
acov_hh_vv, acov_hh_hv, acov_vv_hv,
adp)
# compare to simultaneous tr
psi_dp = 0.5 * np.pi
svar_h, svar_v, scov_hv = ort.cov_sim(alpha_cov, psi_dp)
zdr_str, ldrj, kdpj, rhohv_str, zh_str, rhoxhj = ort.radar(
wavl, svar_h, svar_v, avar_hv, scov_hv, acov_hh_hv, acov_vv_hv, adp)
phi_dp = 180. / np.pi * np.angle(scov_hv)
# plot distribution
plt.figure(0)
v = np.linspace(0., 1., 1000)
theta = np.arccos(1. - 2. * v)
beta = ort.beta_dist(v, a, b)
plt.plot(theta * 180. / np.pi, beta, 'b-', lw=3.)
#a = 7.
#b = 7.
sig_deg = 180. * np.sqrt(2. / (b1 - 1.)) / np.pi
#sig_deg = 35.
print sig_deg
angmom1 = ort.angmom_beta(a1, b1)
angmom2 = ort.angmom_beta(a2, b2)
angmom = (w1 * np.array(angmom1) + w2 * np.array(angmom2))
angmom_g = ort.angmom_gauss(sig_deg)
print angmom_g
print angmom1
# calculate radar variables
avar_hh, avar_vv, avar_hv, acov_hh_vv, adp = ort.avg_polcov(
angmom, alpha_a, alpha_c)
zdr, ldr, kdp, rhohv, zh = ort.radar(wavl, avar_hh, avar_vv, avar_hv,
acov_hh_vv, adp)
print zdr, ldr, kdp, rhohv, zh
avar_hh, avar_vv, avar_hv, acov_hh_vv, adp = ort.avg_polcov(
angmom_g, alpha_a, alpha_c)
zdr, ldr, kdp, rhohv, zh = ort.radar(wavl, avar_hh, avar_vv, avar_hv,
acov_hh_vv, adp)
print zdr, ldr, kdp, rhohv, zh
# plot beta distribution
x = (1. - np.cos(np.linspace(fc(0.), fc(1.), 201))) / 2.
ang = np.arccos(1. - 2. * x) * 180. / np.pi
beta_av = (w1 * ort.beta_dist(x, a1, b1) + w2 * ort.beta_dist(x, a2, b2))
#plt.plot(x, beta_av, 'r--', lw=3.)
plt.plot(ang, beta_av, 'r--', lw=3.)
ax = plt.gca()
eps_mix = maxwell_garnett(eps_ice, vfrac_inc)
alpha_a_sp, alpha_a_sp, alpha_c_sp = sp.oblate_polz(eps_mix, dmax / 2.,
thick / 2.)
# set orientation distribution
amp = 18.
mod = 0.
a = (amp - 2) * mod + 1
b = amp * (1 - mod) + 2 * mod - 1
angmom = ort.angmom_beta(a, b)
# calculate radar variables
alp_cov_arr = ort.avg_polcov(angmom, alpha_a, alpha_c)
alp_cov_arr_sp = ort.avg_polcov(angmom, alpha_a_sp, alpha_c_sp)
zdr, ldr, kdp, rhohv, zh, rhoxh = ort.radar(wavl, alp_cov_arr)
zdr_sp, ldr_sp, kdp_sp, rhohv_sp, zh_sp, rhoxh = ort.radar(
wavl, alp_cov_arr_sp)
#print zdr, ldr, kdp, rhohv, zh
# plot radar variables
fig = plt.figure(1)
ax = fig.add_subplot(2, 2, 1)
plt.plot(vfrac_inc, zdr, 'r-', lw=3.)
plt.plot(vfrac_inc, zdr_sp, 'b-', lw=3.)
#ax.set_ylim([0., 1.])
ax.set_xlim([0.05, 1.])
ax = fig.add_subplot(2, 2, 2)
plt.plot(vfrac_inc, np.log10(kdp), 'r-', lw=3.)
plt.plot(vfrac_inc, np.log10(kdp_sp), 'b-', lw=3.)
# calculate radar variables
alpha_cov = ort.avg_polcov(angmom, alpha_a, alpha_c)
avar_hh = alpha_cov[0]
avar_vv = alpha_cov[1]
avar_hv = alpha_cov[2]
acov_hh_vv = alpha_cov[3]
acov_hh_hv = alpha_cov[4]
acov_vv_hv = alpha_cov[5]
adp = alpha_cov[6]
# simultaneous tr
psi_dp = -73. * np.pi / 180.
svar_h, svar_v, scov_hv = ort.cov_sim(alpha_cov, psi_dp)
zdr, ldr, kdp, rhohv, zh, rhoxh = ort.radar(wavl, svar_h, svar_v, avar_hv,
scov_hv, acov_hh_hv, acov_vv_hv,
adp)
phi_dp = 180. / np.pi * np.arctan2(np.imag(scov_hv), np.real(scov_hv))
zh = zh - 1.
# plot distribution
plt.figure(0)
v = np.linspace(0., 1., 1000)
theta = np.arccos(1. - 2. * v)
beta = ort.beta_dist(v, a, b)
plt.plot(theta * 180. / np.pi, beta, 'b-', lw=1.)
ax = plt.gca()
#ax.set_ylim([0., 1.])
ax.set_xlim([0., 180.])
plt.savefig('dist.png')
sigv_agg = np.log10(sigv_agg) #print sigh_agg, zdr_agg, kdp_agg # compare to isolated pristine crystals #aobl_a, aobl_a, aobl_c = sp.oblate_polz(eps_ice, asp_inc/2., 1./2.) aprl_c, aprl_a, aprl_a = sp.prolate_polz(eps_ice, 1. / 2., asp_inc / 2.) vol_sph = np.pi / 6. * asp_inc**2. #aobl_a = aobl_a/vol_sph #aobl_c = aobl_c/vol_sph aprl_a = aprl_a / vol_sph aprl_c = aprl_c / vol_sph angmom_pr = ort.angmom_beta(a_inc, b_inc) #acov_arr = ort.avg_polcov(angmom_pr, aobl_a, aobl_c) acov_arr = ort.avg_polcov(angmom_pr, aprl_a, aprl_c) zdr, ldr, kdp, rhohv, zhh, rhoxh = ort.radar(wavl, acov_arr) sigh = np.log10(k**2. * acov_arr[0]) sigv = np.log10(k**2. * acov_arr[1]) # plot radar variables fig = plt.figure(1) ax = fig.add_subplot(2, 2, 1) plt.plot(vfrac_inc, zdr * vfrac_inc / vfrac_inc, 'r-', lw=3.) plt.plot(vfrac_inc, zdr_agg, 'b-', lw=3.) #ax.set_ylim([0., 1.]) #ax.set_xlim([0.05, 1.]) ax = fig.add_subplot(2, 2, 2) plt.plot(vfrac_inc, np.log10(kdp) * vfrac_inc / vfrac_inc, 'r-', lw=3.) plt.plot(vfrac_inc, np.log10(kdp_agg), 'b-', lw=3.) #ax.set_ylim([0., 1.])