import warnings
warnings.filterwarnings("ignore")

# specify the system
from RBG_Maxwell.Collision_database.select_system import which_system

plasma_system = 'Fusion_system'
which_system(plasma_system)

from RBG_Maxwell.Collision_database.Fusion_system.collision_type import collision_type_for_all_species

from RBG_Maxwell.Unit_conversion.main import determine_coefficient_for_unit_conversion, unit_conversion
import numpy as np

# import the main class Plasma
from RBG_Maxwell.Plasma.main import Plasma

# give the quantities in SI
# the spatial grid is chosen to be dx=dy=dz=10**(-4) m
dx = dy = 10**(-5)
dz = 1.

# velocity is roughly 10**(6) m/s
v = 5*10**6

# charge
Q = 1.6*10**(-19) 

# momentum is roughly 10**(-30)kg*10**7m/s
momentum = 10**(-23)
# the momentum grid is set to be 
# npy=100, npx=npz=1, half_px=half_pz=half_py~10**(-23)
# hence dpy~10**(-26), dpx and dpz have no effect 
dp = (10**(-25)*10**(-23)*10**(-23))**(1/3)

# the total number of particles are 5*10**(-13)/(1.6*10**(-19))
# put these particles in 71 spatial grids in z direction
# in 201 spatial grids in y direction
# and 100 momentum grids
# in each phase grid we have dn = 21.89755448111554
# the average value of distribution is roughly 
dn = 0.2189755448111554
f = dn/(dp**3*dx*dy*dz)
df = f

# time scale
dt = 10**(-13)

E = 0 
B = 10


# Now find the coefficient
hbar, c, lambdax, epsilon0 = determine_coefficient_for_unit_conversion(dt, dx, dx*dy*dz, dp, dp**3,\
                                              5*10**(-14)/(1.6*10**(-19)), dn, v, E, B)

conversion_table = \
unit_conversion('SI_to_LHQCD', coef_J_to_E=lambdax, hbar=hbar, c=c, k=1., epsilon0=epsilon0)
conversion_table_reverse = \
unit_conversion('LHQCD_to_SI', coef_J_to_E=lambdax, hbar=hbar, c=c, k=1., epsilon0=epsilon0)

# time step, and spatial infinitesimals
# dt is 10**(-13) s, dx = dy = dz = 10**(-5) m
dt, dx, dy, dz = 10**(-13)*conversion_table['second'], \
                 10**(-5)*conversion_table['meter'], \
                 10**(-5)*conversion_table['meter'], \
                 10**(-5)*conversion_table['meter']
dt_upper_limit = float(10**(-1)*conversion_table['second'])
dt_lower_limit = float(10**(-9)*conversion_table['second'])
# we have only one type of particle e-
num_particle_species = 1

# treat the electron as classical particles
particle_type = np.array([0])

# masses, charges and degenericies are
masses, charges, degeneracy = np.array([9.11*10**(-31)*conversion_table['kilogram']]), \
                              np.array([-1.6*10**(-19)*conversion_table['Coulomb']]),\
                              np.array([1.])

# momentum grids
npx, npy, npz = 1, 201, 1

# half_px, half_py, half_pz
# momentum range for x and z direction are not import in this case
half_px, half_py, half_pz = np.array([9.11*10**(-31)*5*10**6*conversion_table['momentum']]), \
                            np.array([9.11*10**(-31)*5*10**6*conversion_table['momentum']]),\
                            np.array([9.11*10**(-31)*5*10**6*conversion_table['momentum']])

dpx, dpy, dpz = 2*half_px/npx, 2*half_py/npy, 2*half_pz/npz
par_list=[m1**2*c**2, m2**2*c**2, (2*math.pi*hbar)**3, hbar**2*c, d_sigma/(hbar**2)]

# load the collision matrix
flavor, collision_type, particle_order = collision_type_for_all_species()
expected_collision_type = ['2TO2']

# number of spatial grids
# the maximum spatial gird is limited by CUDA, it's about nx*ny*nz~30000 for each card
nx_o, ny_o, nz_o = [1], [251], [111]

# value of the left boundary
# this is the 
x_left_bound_o, y_left_bound_o, z_left_bound_o = [-0.5*dx],\
                                                 [-125.5*dy],\
                                                 [-55.5*dz]

# number samples gives the number of sample points in MC integration
num_samples = 100

# Only specify one spatial region
number_regions = 1

# each spatial should use the full GPU, this number can be fractional if many regions are chosen
# and only one GPU is available
num_gpus_for_each_region = 0.1


# since only one region is specified, this will be empty
sub_region_relations = {'indicator': [[]],\
                        'position': [[]]}

# if np.ones are used, the boundaries are absorbing boundaries
# if np.zeros are used, it is reflection boundary
# numbers in between is also allowed
boundary_configuration = {}
for i_reg in range(number_regions):
    bound_x = np.ones([ny_o[i_reg], nz_o[i_reg]])
    bound_y = np.ones([nz_o[i_reg], nx_o[i_reg]])
    bound_z = np.ones([nx_o[i_reg], ny_o[i_reg]])
    boundary_configuration[i_reg] = (bound_x, bound_y, bound_z)

num_momentum_levels = 1

# iniital distribution function
f = {}
for i_reg in range(number_regions):
    f[i_reg] = np.zeros([num_momentum_levels, num_particle_species,\
                         nx_o[i_reg], ny_o[i_reg], nz_o[i_reg], npx, npy, npz])

# The initial velocity of the electrons is 1.87683*10**6 m/s, corresponds to the momentum value
# 9.11*10**(-31)*1.87683*10**6*conversion_table['momentum'] ~ 408.770512.
# The following code specifies the momentum grid index
dpy = 2*half_py/npy
a = 9.11*10**(-31)*1.87683*10**6*conversion_table['momentum']
ipy = [i for i in range(npy) if (-half_py+dpy*(i-0.5))<=a<=(-half_py+dpy*(i+1))][0]

dn_dv = 5*10**(-14)/(1.6*10**(-19))/(101*dx*dy*dz*dpx*dpy*dpz)

# e-, the first two indices correspond to num_momentum_levels=1, and num_particle_types=1
f[0][0, 0, 0,9,5:106,0,ipy,0] = dn_dv

# reshape the distribution function in different regions
for i_reg in range(number_regions):
    f[i_reg] = f[i_reg].reshape([num_momentum_levels, num_particle_species,\
                                 nx_o[i_reg]*ny_o[i_reg]*nz_o[i_reg]*npx*npy*npz])

'''
We add an external magnetic field of 10 T in the +y direction
'''
BBy = [10*conversion_table['Tesla']*np.ones(nx_o[0]*ny_o[0]*nz_o[0])]
BEx, BEy, BEz, BBx, BBz = [0],[0],[0],[0],[0]

plasma = Plasma(f,par_list, dt, dt_lower_limit, dt_upper_limit,\
                nx_o, ny_o, nz_o, dx, dy, dz, boundary_configuration, \
                x_left_bound_o, y_left_bound_o, z_left_bound_o, \
                int(npx[0]), int(npy[0]), int(npz[0]), half_px, half_py, half_pz,\
                masses, charges, sub_region_relations,\
                flavor, collision_type, particle_type,\
                degeneracy, expected_collision_type,\
                num_gpus_for_each_region,\
                hbar, c, lambdax, epsilon0, time_stride_back,\
                num_samples = 100, drift_order = 2,\
                rho_J_method="raw", GPU_ids_for_each_region = ["1"])

n_step = 10001
number_rho = []
EM = []
charged_rho = []
dis = []
VT= []
DT = []
import time
start_time = time.time()
for i_time in range(n_step):  
    
    # if i_time%1000 == 0:
    #     dis.append(plasma.acquire_values("Distribution"))            
    plasma.proceed_one_step(i_time, n_step, processes = {'VT':1., 'DT':1., 'CT':0.},\
                            BEx = BEx, BEy = BEy, BEz = BEz, BBx = BBx, BBy = BBy, BBz = BBz)
    if i_time%1000 == 0:     
        print('Updating the {}-th time step'.format(i_time))
        number_rho.append(plasma.acquire_values("number_rho/J"))
        charged_rho.append(plasma.acquire_values("Electric rho/J"))
    EM.append(plasma.acquire_values('EM fields on current region'))
end_time = time.time()