content: # -*- coding: UTF-8 -*-
  
  
  import numpy as np
  import matplotlib.pyplot as plt #for figures
  #from mpl_toolkits.basemap import Basemap #to render maps
  import math
  
  from GrowYourIC import tracers, positions, geodyn, geodyn_trg, geodyn_static, plot_data, data, geodyn_analytical_flows
  
  #plt.rcParams['figure.figsize'] = (8.0, 3.0) #size of figures
  cm = plt.cm.get_cmap('viridis_r')
  
  #V = 0.2 # translation velocity
  #S2 = 1/5.
  
  #Yoshida = geodyn_analytical_flows.Yoshida96(V, S=S2)
  #file = "Fig/Yoshida_{}_S2_{}".format(V, S2)
  #print(file)
  
  V = [0.2, 0.4]
  S2 = [1/5., 4/5., 2.]
      
  for vitesse in V:
      for value_S in S2: 
          Yoshida = geodyn_analytical_flows.Yoshida96(vitesse, S=value_S)
          file = "Fig/Yoshida_{}_S2_{}".format(vitesse, value_S)
          print(file)
  
          npoints = 50 #number of points in the x direction for the data set. 
          data_set = data.PerfectSamplingCut(npoints, rICB = 1.)
          data_set.method = "bt_point"
  
          # Age plot with velocity field
          proxy = geodyn.evaluate_proxy(data_set, Yoshida, proxy_type="age", verbose = False)
          data_set.plot_c_vec(Yoshida, proxy=proxy, nameproxy="age")
          plt.savefig(file+"_age.pdf")
  
  
  # accumulated deformation
  #proxy = geodyn.evaluate_proxy(data_set, Yoshida, proxy_type="vMises_acc", verbose = False)
  #data_set.plot_c_vec(Yoshida, proxy=proxy, cm=cm, nameproxy="vMises_acc")
  #plt.savefig(file+"_vM_acc.pdf")
  #data_set.plot_c_vec(Yoshida, proxy=np.log10(proxy), cm=cm, nameproxy="log_vMises_acc")
  #plt.savefig(file+"_log_vM_acc.pdf")
  
  # tracers with age
  #tracers.Swarm(5, Yoshida, Yoshida.tau_ic/400, "ici", plane="meridional")
  
  
  #data_set = data.PerfectSamplingCut(20, rICB = 1.)
  #data_set.method = "bt_point"
  #proxy = geodyn.evaluate_proxy(data_set, Yoshida, proxy_type="age", verbose = False)
  #data_set.plot_c_vec(Yoshida, proxy=proxy, nameproxy="age")
  
  #plt.show()
  
  #proxy = geodyn.evaluate_proxy(data_set, Yoshida, proxy_type="vMises_tau_ic", verbose = False)
  #data_set.plot_c_vec(Yoshida, proxy=proxy, cm=cm, nameproxy="vMises_tau_ic")
  #proxy = geodyn.evaluate_proxy(data_set, Yoshida, proxy_type="vMises_acc", verbose = False)
  #data_set.plot_c_vec(Yoshida, proxy=proxy, cm=cm, nameproxy="vMises_acc")
  
  
  #Karato = geodyn_analytical_flows.Model_LorentzForce()
  #proxy = geodyn.evaluate_proxy(data_set, Karato, proxy_type="vMises_tau_ic", verbose = False)
  #data_set.plot_c_vec(Karato, proxy=proxy, cm=cm, nameproxy="vMises_tau_ic")
  
  #Karato.P = 1e-4
  #proxy = geodyn.evaluate_proxy(data_set, Karato, proxy_type="vMises_tau_ic", verbose = False)
  #data_set.plot_c_vec(Karato, proxy=proxy, cm=cm, nameproxy="vMises_tau_ic")
  
  #proxy = geodyn.evaluate_proxy(data_set, Karato, proxy_type="age", verbose = False)
  #data_set.plot_c_vec(Karato, proxy=proxy, cm=cm, nameproxy="age")
  
  
  
  
  #proxy = geodyn.evaluate_proxy(data_set, Yoshida, proxy_type="age", verbose = False)
  #data_set.plot_c_vec(Yoshida, proxy=proxy, cm=cm, nameproxy="age")
  #plt.savefig(file+"_tage.pdf")
  
  
  #proxy = geodyn.evaluate_proxy(data_set, Yoshida, proxy_type="vMises_tau_ic", verbose = False)
  #data_set.plot_c_vec(Yoshida, proxy=proxy, cm=cm, nameproxy="vMises_tau_ic")
  #plt.savefig(file+"_t_vM.pdf")
  
  #proxy = geodyn.evaluate_proxy(data_set, Yoshida, proxy_type="vMises_cart", verbose = False)
  #data_set.plot_c_vec(Yoshida, proxy=proxy, cm=cm, nameproxy="vMises_cart")
  #plt.savefig("Yoshida_vM.pdf")
  
  #Karato.P = 1e4
  #proxy_1 = geodyn.evaluate_proxy(data_set, Karato, proxy_type="vMises_tau_ic", verbose = False)
  #data_set.plot_c_vec(Karato, proxy=proxy_1, cm=cm, nameproxy="vMises_tau_ic")
  
  
  
  #npoints = 50 #number of points in the x direction for the data set. 
  #data_set = data.PerfectSamplingCut(npoints, rICB = 1.)
  #data_set.method = "bt_point"
  #proxy_2 = geodyn.evaluate_proxy(data_set, Karato, proxy_type="age", verbose = False)
  #data_set.plot_c_vec(Karato, proxy=proxy_2, cm=cm, nameproxy="age")
  
  #npoints = 100 #number of points in the x direction for the data set. 
  #data_set = data.PerfectSamplingCut(npoints, rICB = 1.)
  #data_set.method = "bt_point"
  #proxy = geodyn.evaluate_proxy(data_set, Yoshida, proxy_type="vMises_acc", verbose = False)
  #data_set.plot_c_vec(Yoshida, proxy=proxy, cm=cm, nameproxy="vMises_acc")
  
  
  plt.show()