def Local_E_Z(iz, it, cut):
global Zi, Ri, pot
option = 1
if cut == None:
cut = core.jcut
dZ = core.Zi[1] - core.Zi[0]
dR = core.Ri[1] - core.Ri[0]
Sep_ip = core.getiparrs_hor(0.95, 1., core.jcut)[-1]
# dphi/dZ
potim1 = core.getcutvalue_hor(core.pot[:, iz, it], cut - 1, option)
poti = core.getcutvalue_hor(core.pot[:, iz, it], cut, option)
potip1 = core.getcutvalue_hor(core.pot[:, iz, it], cut + 1, option)
dphidZ_N = -(potip1 - potim1) / (2. * dZ)
#Plotting
L = np.array([x for x in range(0, len(dphidZ_N))])
unit = (core.Rmax - core.Rmin) / 100
R = np.array([L[ip] * unit + core.Rmin for ip in range(0, len(dphidZ_N))])
plt.title('Local $E_y$-field')
plt.xlabel('$R(m)$')
plt.ylabel('$E_y$')
plt.plot(R[:], dphidZ_N[:], 'go')
plt.axvline(x=Sep_ip * unit + core.Rmin,
color='b',
linestyle='dashed',
linewidth=2)
plt.legend()
plt.show()
def Mag_N_flux():
'''Writes on text the Z-component of the magnetic drifts flux.'''
option = 1
start = 0
time_range = 200
cut = accuracy / 2
#new_file = open("Norm_Magnetic_Fluxes_higher@%s.txt" %(cut),'a')
new_file = open("Norm_Magnetic_Fluxes_Bottom.txt", 'a')
new_file.write("Magnetic" + "\t" + "R" + "\t" + "psi" + "\n")
br = core.getcutvalue_hor(core.bfield[:, 0], cut, 1)
ne_all = np.array([[
core.getcutvalue_hor(core.ne[:, iz, it], cut, option)
for iz in range(core.Nplanes)
] for it in range(start, start + time_range)])
print("ne_all done...")
for Flux_ip in range(0, accuracy):
if math.isnan(br[Flux_ip]) == True:
pass
else:
Mag = core.magnetic_flux_norm(cut, Flux_ip, ne_all)
R = (Rmin + unitR * Flux_ip)
psi = core.psii[Flux_ip]
new_file.write(str(Mag) + "\t" + str(R) + "\t" + str(psi) + "\n")
new_file.close()
return ("Done!")
def z_variation_E_z_field(iz, it, cut):
global Zi, Ri, pot
option = 1
if cut == None:
cut = core.jcut
dZ = core.Zi[1] - core.Zi[0]
dR = core.Ri[1] - core.Ri[0]
Sep_ip = core.getiparrs_hor(0.95, 1., core.jcut)[-1]
field_value = []
for cut_plane in range(cut - 20, cut + 20):
# dphi/dZ
potim1 = core.getcutvalue_hor(core.pot[:, iz, it], cut_plane - 1,
option)
poti = core.getcutvalue_hor(core.pot[:, iz, it], cut_plane, option)
potip1 = core.getcutvalue_hor(core.pot[:, iz, it], cut_plane + 1,
option)
dphidZ_N = -(potip1 - potim1) / (2. * dZ)
field_value.append(dphidZ_N[Sep_ip - 1])
#Plotting
L = np.array([x for x in range(0, len(field_value))])
unit = (core.Zmax - core.Zmin) / 100
R = np.array(
[L[ip] * unit + core.Zmin for ip in range(0, len(field_value))])
plt.title('Local $E_y$-field at a vertical line')
plt.xlabel('$Z(m)$')
plt.ylabel('$E_y$')
plt.plot(R[:], field_value[:], 'go')
plt.legend()
plt.show()
def phi_tilda(cut):#loads all potential and density matrices that we will take the derivative.
option = 1
t_start = 550
t_end = 650
planes = core.Nplanes
#loading density
n_e=core.loader.calcNeTotal()
n_tot = np.asarray([[core.getcutvalue_hor(n_e[:,iz,it],(cut),option) for iz in range(0,planes)] for it in range(t_start,t_end)])
#loading arrays of potential: phi[it,iz,ip]
phim = np.asarray([[core.getcutvalue_hor(core.pot[:,iz,it],(cut-1)%len(core.Zi),option) for iz in range(0,planes)] for it in range(t_start,t_end)])
print('array 1 loaded')
phi = np.asarray([[core.getcutvalue_hor(core.pot[:,iz,it],cut,option) for iz in range(0,planes)] for it in range(t_start,t_end)])
print('array 2 loaded')
phip = np.asarray([[core.getcutvalue_hor(core.pot[:,iz,it],(cut+1)%len(core.Zi),option) for iz in range(0,planes)] for it in range(t_start,t_end)])
print('array 3 loaded')
#toroidal averaging: phi_tor[it,ip]
phim_tor = phim.mean(axis=1)
phi_tor = phi.mean(axis=1)
phip_tor = phip.mean(axis=1)
n_tor = n_tot.mean(axis=1)
#time averaging: phi_av[ip]
phim_av = phim_tor.mean(axis=0)
phi_av = phi_tor.mean(axis=0)
phip_av = phip_tor.mean(axis=0)
n_av = n_tor.mean(axis=0)
#phi_tilda: dphi[it,iz,ip]
dphim = np.asarray(phim[:,:,:] - phim_av[np.newaxis,np.newaxis,:])
dphi = np.asarray(phi[:,:,:] - phi_av[np.newaxis,np.newaxis,:])
dphip = np.asarray(phip[:,:,:] - phip_av[np.newaxis,np.newaxis,:])
return phim,phi,phip,n_tot,n_av,phim_av,phi_av,phip_av
def i_heat_N_flux():
'''Writes on text the Z-component of the exb and parallel ion heat flux.'''
option = 1
start = 0
time_range = 200
cut = accuracy / 2
#new_file = open("Norm_i_heat_Fluxes@%s.txt" %(cut),'a')
new_file = open("Norm_i_heat_Fluxes_Bottom.txt", 'a')
new_file.write("Eq_exb" + "\t" + "Tur_exb" + "\t" + "Eq_par" + "\t" +
"Tur_par" + "\t" + "R" + "\t" + "psi" + "\n")
br = core.getcutvalue_hor(core.bfield[:, 0], cut, 1)
temp = np.array(
[[core.getcutvRvZ(iz, it, cut) for iz in range(core.Nplanes)]
for it in range(start, start + time_range)])
VZ_all = temp[:, :, 1, :]
print("VZ_all done...")
ne_all = np.array([[
core.getcutvalue_hor(core.ne[:, iz, it], cut, option)
for iz in range(core.Nplanes)
] for it in range(start, start + time_range)])
print("ne_all done...")
Ti_perp_all = np.array([[
core.map_array(core.i_T_perp, (iz - 1) % core.Nplanes, it, cut)
for iz in range(core.Nplanes)
] for it in range(start, start + time_range)])
print("Ti_perp_all done...")
Ei_para_all = np.array([[
core.map_array(core.i_E_para, (iz - 1) % core.Nplanes, it, cut)
for iz in range(core.Nplanes)
] for it in range(start, start + time_range)])
print("Ei_para_all done...")
Vpar_all = np.array([[
core.map_array(core.e_u_para, (iz - 1) % core.Nplanes, it, cut)
for iz in range(core.Nplanes)
] for it in range(start, start + time_range)])
print("Vpar_all done...")
for Flux_ip in range(0, accuracy):
if math.isnan(br[Flux_ip]) == True:
pass
else:
exb, par = core.i_heat_flux_norm(cut, Flux_ip, VZ_all, ne_all,
Ti_perp_all, Ei_para_all,
Vpar_all)
R = (Rmin + unitR * Flux_ip)
psi = core.psii[Flux_ip]
new_file.write(
str(exb) + "\t" + str(par) + "\t" + str(R) + "\t" + str(psi) +
"\n")
new_file.close()
return ("Done!")
def theta_psi_der(cut):# takes the d/dtheta and d/dpsi derivatives of a phi[it,iz,ip] along a cut.
global Zi,Ri,pot,jcut,bfield,B2,unitR
option=1
R_len = len(core.Ri)
if cut==None:
cut = core.jcut
dZ = core.Zi[1] - core.Zi[0]
dR = core.Ri[1] - core.Ri[0]
phim,phi,phip,n_tot,n_av,phim_av,phi_av,phip_av = phi_tilda(cut)
#d/dZ of total phi
arrim1 = phim
arri = phi
arrip1 = phip
darrdZ = (arrip1-arrim1)/(2.*dZ)
#d/dZ of average phi
arravm1 = phim_av
arrav = phi_av
arravp1 = phip_av
darravdZ = (arravp1-arravm1)/(2.*dZ)
#d/dR of total phi
arriplus = np.roll(arri,-1,axis=2)
arriminus = np.roll(arri,1,axis=2)
darrdR = (arriplus-arriminus)/(2.*dR)
darrdR[0] = (arri[1]-arri[0])/dR
darrdR[-1] = (arri[-1]-arri[-2])/dR
#d/dR of average phi
arravplus = np.roll(arrav,-1)
arravminus = np.roll(arrav,1)
darravdR = (arravplus-arravminus)/(2.*dR)
darravdR[0] = (arrav[1]-arrav[0])/dR
darravdR[-1] = (arrav[-1]-arrav[-2])/dR
BRi = core.getcutvalue_hor(core.bfield[:,0],cut,option)
BZi = core.getcutvalue_hor(core.bfield[:,1],cut,option)
Bzetai = core.getcutvalue_hor(core.bfield[:,2],cut,option)
Bp = np.sqrt(np.square(BRi)+np.square(BZi))
B = np.sqrt(np.square(BRi)+np.square(BZi)+np.square(Bzetai))
R = np.array([ip*core.unitR+core.Rmin for ip in range(0,R_len)])+core.Rmaj
darrdtheta = (1/(Bp))*(BRi*darrdR + BZi*darrdZ)
darrdpsi = (1/(Bp))*(-BRi*darrdZ + BZi*darrdR)
darravdtheta = (1/(Bp))*(BRi*darravdR + BZi*darravdZ)
darravdpsi = (1/(Bp))*(-BRi*darravdZ + BZi*darravdR)
return -darrdtheta/B, -darrdpsi/B, n_tot, n_av, -darravdtheta/B,-darravdpsi/B
def thita_psi_der(arr,cut):# takes the d/dtheta and d/dpsi derivatives of a [Z,R] array along a cut. Returns simple derivatives and divided by B.
global Zi,Ri,pot,jcut,bfield,B2,unitR
option=1
darrdR = R_der(arr)[cut,:]
darrdZ = Z_der(arr,cut)
BRi = core.getcutvalue_hor(core.bfield[:,0],cut,option)
BZi = core.getcutvalue_hor(core.bfield[:,1],cut,option)
Bzetai = core.getcutvalue_hor(core.bfield[:,2],cut,option)
Bp = np.sqrt(np.square(BRi)+np.square(BZi))
B = np.sqrt(np.square(BRi)+np.square(BZi)+np.square(Bzetai))
darrdtheta = (1/(Bp))*(-BRi*darrdZ + BZi*darrdR)
darrdpsi = (1/(Bp))*(BRi*darrdR + BZi*darrdZ)
return darrdtheta, darrdpsi
def psi_cont():
Rmin = core.loader.Rmin
Rmax = core.loader.Rmax
Zmin = core.loader.Zmin
Zmax = core.loader.Zmax
unitR = (Rmax - Rmin) / 100
unitZ = (Zmax - Zmin) / 100
R_points = [ip * unitR + Rmin for ip in range(100)]
Z_points = [ip * unitZ + Zmin for ip in range(100)]
psi = []
for cut in range(100):
psi.append(core.getcutvalue_hor(core.psin[:], cut, 1))
psi = np.reshape(psi, (100, 100))
fig, ax = plt.subplots()
contour_levels = np.arange(0, 1.7, 0.05)
CS = plt.contour(R_points, Z_points, psi, contour_levels)
CB = plt.colorbar(CS, extend='both')
#plt.clabel(CS, inline=1, fontsize=10)
plt.xlabel("R(m)")
plt.ylabel("Z(m)")
ax.plot(core.loader.RZ[core.sepInds, 0], core.loader.RZ[core.sepInds, 1],
'k--')
plt.axhline(y=0.0, color='k', linestyle='--')
plt.axvline(x=core.Rmaj, color='k', linestyle='--')
plt.title(r'$\Psi$ contours')
plt.show()
def contour_banana_plot(R_star, Z_star, W_star):
'''Contour plot of the normalized toroidal momentum branches, i.e., the banana orbits.'''
psin_star_p, psin_star_m = psi_star(R_star, Z_star, W_star)
psi_list = []
for cut in range(len(core.Zi)):
psi_list.append(core.getcutvalue_hor(core.psin[:], cut, 1))
psi_mat = np.reshape(psi_list, (len(core.Ri), len(core.Zi)))
fig, ax = plt.subplots(figsize=(10, 10))
contour_levels = np.arange(0.9, 1.2, 0.05)
CS = plt.contour(R, Z, psi_mat, contour_levels, colors='y')
#CB = plt.colorbar(CS, extend='both')
p_levels = np.arange(-0.06468, 1.6884, 0.5)
m_levels = np.arange(-0.06468, 1.9245, 0.5)
CP = plt.contour(R, Z, psin_star_p, p_levels, colors='b', linewidths=2)
CM = plt.contour(R, Z, psin_star_m, m_levels, colors='r', linewidths=2)
#print("pmax",np.nanmax(psin_star_p))
#print("pmin",np.nanmin(psin_star_p))
#print("mmax",np.nanmax(psin_star_m))
#print("mmin",np.nanmin(psin_star_p))
#CB = plt.colorbar(CP, extend='both')
#CD = plt.colorbar(CM, extend='both')
#plt.clabel(CP, inline=1,fmt='%.2E', fontsize=10)
plt.xlabel("R(m)")
plt.ylabel("Z(m)")
ax.plot(core.loader.RZ[core.sepInds, 0], core.loader.RZ[core.sepInds, 1],
'k--')
plt.title('Banana Orbits, $R_\star = %s,\,\, E_i = %s\, eV$' %
(R_star, W_star))
plt.show()
def Particle_N_flux():
'''Writes on text the Z-component (normal to a horizontal line) of the particle fluxes (exb and parallel components).'''
option = 1
start = 0
time_range = 200
cut = accuracy / 2
#new_file = open("Norm_Particle_Fluxes_higher@%s.txt" %(cut),'a')
new_file = open("Norm_Particle_Fluxes_Top.txt", 'a')
new_file.write("ExB" + "\t" + "Par" + "\t" + "R" + "\t" + "psi" + "\n")
br = core.getcutvalue_hor(core.bfield[:, 0], cut, 1)
#loading arrays
temp = np.array(
[[core.getcutvRvZ(iz, it, cut) for iz in range(core.Nplanes)]
for it in range(start, start + time_range)])
VZ_all = temp[:, :, 1, :]
print("VZ_all done...")
ne_all = np.array([[
core.getcutvalue_hor(core.ne[:, iz, it], cut, option)
for iz in range(core.Nplanes)
] for it in range(start, start + time_range)])
print("ne_all done...")
Vpar_all = np.array([[
core.map_array(core.e_u_para, (iz - 1) % core.Nplanes, it, cut)
for iz in range(core.Nplanes)
] for it in range(start, start + time_range)])
print("Vpar_all done...")
for Flux_ip in range(0, accuracy):
if math.isnan(br[Flux_ip]) == True:
pass
else:
exb, par = core.particle_fluxes_norm(cut, Flux_ip, ne_all, VZ_all,
Vpar_all)
R = (Rmin + unitR * Flux_ip)
psi = core.psii[Flux_ip]
new_file.write(
str(exb) + "\t" + str(par) + "\t" + str(R) + "\t" + str(psi) +
"\n")
new_file.close()
return ("Done!")
def e_mag_heat_N_flux():
'''Writes on text the Z-component of the magnetic drifts electron heat flux.'''
option = 1
start = 0
time_range = 200
cut = accuracy / 2
#new_file = open("Norm_e_mag_heat_Fluxes@%s.txt" %(cut),'a')
new_file = open("Norm_e_mag_heat_Fluxes_Top.txt", 'a')
new_file.write("Magnetic" + "\t" + "R" + "\t" + "psi" + "\n")
br = core.getcutvalue_hor(core.bfield[:, 0], cut, 1)
ne_all = np.array([[
core.getcutvalue_hor(core.ne[:, iz, it], cut, option)
for iz in range(core.Nplanes)
] for it in range(start, start + time_range)])
print("ne_all done...")
Te_perp_all = np.array([[
core.map_array(core.e_T_perp, (iz - 1) % core.Nplanes, it, cut)
for iz in range(core.Nplanes)
] for it in range(start, start + time_range)])
print("Te_perp_all done...")
Ee_para_all = np.array([[
core.map_array(core.e_E_para, (iz - 1) % core.Nplanes, it, cut)
for iz in range(core.Nplanes)
] for it in range(start, start + time_range)])
print("Ee_para_all done...")
for Flux_ip in range(0, accuracy):
if math.isnan(br[Flux_ip]) == True:
pass
else:
mag = core.mag_e_heat_flux_norm(cut, Flux_ip, ne_all, Te_perp_all,
Ee_para_all)
R = (Rmin + unitR * Flux_ip)
psi = core.psii[Flux_ip]
new_file.write(str(mag) + "\t" + str(R) + "\t" + str(psi) + "\n")
new_file.close()
return ("Done!")
def write_mat():
B_R = np.array([
core.getcutvalue_hor(core.bfield[:, 0], cut, 1)
for cut in range(0, len(L))
])
B_Z = np.array([
core.getcutvalue_hor(core.bfield[:, 1], cut, 1)
for cut in range(0, len(L))
])
B_zeta = np.array([
core.getcutvalue_hor(core.bfield[:, 2], cut, 1)
for cut in range(0, len(L))
])
ne_all = np.array([[[
core.getcutvalue_hor(core.ne[:, iz, it], cut, 1)
for iz in range(0, core.Nplanes)
] for cut in range(0, len(L))] for it in range(0, 889)])
#pot_all = np.array([[[core.getcutvalue_hor(core.pot[:,iz,it],cut,1) for iz in range(0,core.Nplanes)]for cut in range(0,len(L))] for it in range(490,690)])
np.save(trgt + 'B_R_mid_CMOD', B_R)
np.save(trgt + 'B_Z_mid_CMOD', B_Z)
np.save(trgt + 'B_zeta_mid_CMOD', B_zeta)
np.save(trgt + 'ne_mid_CMOD', ne_all)
def loading_fun():
'''Function that reads the 2D values of psin,R,B,Bp,b_zeta and phi.'''
global psin, unitR, unitZ, phi, B, Bp, Bzetai, R, Z, Rmin, Rmax, Zmin, Zmax
option = 1
Rmax = np.amax(core.RZ[:, 0])
Rmin = np.amin(core.RZ[:, 0])
Zmax = np.amax(core.RZ[:, 1])
Zmin = np.amin(core.RZ[:, 1])
unitR = (Rmax - Rmin) / len(core.Ri)
unitZ = (Zmax - Zmin) / len(core.Zi)
phi = np.asarray([[
core.getcutvalue_hor(core.pot[:, iz, 0], cut, option)
for iz in range(0, core.Nplanes)
] for cut in range(0, len(core.Zi))]).mean(axis=1)
psin = np.asarray([
core.getcutvalue_hor(core.psin[:], cut, option)
for cut in range(0, len(core.Zi))
])
BRi = np.asarray([
core.getcutvalue_hor(core.bfield[:, 0], cut, option)
for cut in range(0, len(core.Zi))
])
BZi = np.asarray([
core.getcutvalue_hor(core.bfield[:, 1], cut, option)
for cut in range(0, len(core.Zi))
])
Bzetai = np.asarray([
core.getcutvalue_hor(core.bfield[:, 2], cut, option)
for cut in range(0, len(core.Zi))
])
Bp = np.sqrt(np.square(BRi) + np.square(BZi))
B = np.sqrt(np.square(BRi) + np.square(BZi) + np.square(Bzetai))
R = np.array([ip * unitR + Rmin for ip in range(0, len(core.Zi))])
Z = np.array([ip * unitZ + Zmin for ip in range(0, len(core.Zi))])
return psin, phi, B, Bp, Bzetai, R, Z
def shear(
it, cut
): #takes the d/dpsi of E_psi/RBp and multiplies with (RBp)^2/B to find the shear.
'''Calculates the Burrell shear along a cut at a particular time.'''
option = 1
c = 3.0e8
dZ = core.Zi[1] - core.Zi[0]
dR = core.Ri[1] - core.Ri[0]
unitR = (core.loader.Rmax - core.loader.Rmin) / len(core.Ri)
dphidpsi = two_d_psi_der(it)
arrim1 = dphidpsi[(cut - 1) % len(core.Zi), :]
arri = dphidpsi[cut, :]
arrip1 = dphidpsi[(cut + 1) % len(core.Zi), :]
darrdZ = (arrip1 - arrim1) / (2. * dZ)
arriplus = np.roll(arri, -1)
arriminus = np.roll(arri, 1)
darrdR = (arriplus - arriminus) / (2. * dR)
darrdR[0] = (arri[1] - arri[0]) / dR
darrdR[-1] = (arri[-1] - arri[-2]) / dR
BRi = core.getcutvalue_hor(core.bfield[:, 0], cut, option)
BZi = core.getcutvalue_hor(core.bfield[:, 1], cut, option)
Bzetai = core.getcutvalue_hor(core.bfield[:, 2], cut, option)
Bp = np.sqrt(np.square(BRi) + np.square(BZi))
Bmag = np.sqrt(np.square(BRi) + np.square(BZi) + np.square(Bzetai))
L = np.array([x for x in range(0, len(core.Ri))])
R = np.array(
[L[ip] * unitR + core.loader.Rmin
for ip in range(0, len(core.Ri))]) + core.Rmaj
doubledpsi = (1 / Bp) * (BRi * darrdZ - BZi * darrdR)
Shear = ((np.square(R) * np.square(Bp)) / Bmag) * doubledpsi
return Shear
def pot0_contour_plot(time):
pot0_all = np.array([
core.getcutvalue_hor(core.pot0[:, time], cut, 1)
for cut in range(0, 100)
])
fig, ax = plt.subplots()
CS = plt.contourf(R_points, Z_points, pot0_all)
CB = plt.colorbar(CS, extend='both')
plt.clabel(CS, inline=1, fmt='%.2E', fontsize=10)
plt.xlabel("R(m)")
plt.ylabel("Z(m)")
ax.plot(core.loader.RZ[core.sepInds, 0], core.loader.RZ[core.sepInds, 1],
'k--')
plt.title('Pot0 Contours, t=%d' % (time))
plt.show()
def av_pot0_contour_plot():
pot0_all = np.array([[
core.getcutvalue_hor(core.pot0[:, time], cut, 1)
for cut in range(0, 100)
] for time in range(500, 650)])
pot0_av = pot0_all.mean(axis=0)
fig, ax = plt.subplots()
CS = plt.contourf(R_points, Z_points, pot0_av)
CB = plt.colorbar(CS, extend='both')
plt.clabel(CS, inline=1, fmt='%.2E', fontsize=10)
plt.xlabel("R(m)")
plt.ylabel("Z(m)")
ax.plot(core.loader.RZ[core.sepInds, 0], core.loader.RZ[core.sepInds, 1],
'k--')
plt.title('Averaged Pot0 Contours')
plt.show()
def X_den():
'''Writes on text the density on a line at the X-point.'''
cut = accuracy / 2
new_file = open("density_LFS@%s.txt" % (cut), 'a')
new_file.write("den" + "\t" + "R" + "\t" + "psi" + "\n")
br = core.getcutvalue_hor(core.bfield[:, 0], cut, 1)
for Flux_ip in range(0, accuracy):
if math.isnan(br[Flux_ip]) == True:
pass
else:
_, _, _, _, n = core.norm_parallel_flux(cut, Flux_ip)
R = (Rmin + unitR * Flux_ip)
psi = core.psii[Flux_ip]
new_file.write(str(n) + "\t" + str(R) + "\t" + str(psi) + "\n")
new_file.close()
return ("Done!")
def z_variation_E_r_field(iz, it, cut):
global Zi, Ri, pot
option = 1
if cut == None:
cut = core.jcut
dZ = core.Zi[1] - core.Zi[0]
dR = core.Ri[1] - core.Ri[0]
Sep_ip = core.getiparrs_hor(0.95, 1., core.jcut)[-1]
field_value = []
for cut_plane in range(cut - 20, cut + 20):
# dphi/dR
dphidR_N = []
lengthR = len(
core.getcutvalue_hor(core.pot[:, iz, it], cut_plane, option))
iterlistR = list(range(0, lengthR))
potrm10 = core.getcutvalue_hor(core.pot[:, iz, it], cut_plane,
option)[lengthR - 1]
potrp10 = core.getcutvalue_hor(core.pot[:, iz, it], cut_plane,
option)[1]
dphidR_N.append(-(potrp10 - potrm10) / (2. * dR))
for i in iterlistR[1:-1]:
potrm1 = core.getcutvalue_hor(core.pot[:, iz, it], cut_plane,
option)[i - 1]
potrp1 = core.getcutvalue_hor(core.pot[:, iz, it], cut_plane,
option)[i + 1]
dphidR_N.append(-(potrp1 - potrm1) / (2. * dR))
potrm1L = core.getcutvalue_hor(core.pot[:, iz, it], cut_plane,
option)[lengthR - 2]
potrp1L = core.getcutvalue_hor(core.pot[:, iz, it], cut_plane,
option)[0]
dphidR_N.append(-(potrp1L - potrm1L) / 2 * dR)
field_value.append(dphidR_N[Sep_ip - 1])
#Plotting
L = np.array([x for x in range(0, len(field_value))])
unit = (core.Zmax - core.Zmin) / 100
R = np.array(
[L[ip] * unit + core.Zmin for ip in range(0, len(field_value))])
plt.title('Local $E_r$-field at a vertical line')
plt.xlabel('$Z(m)$')
plt.ylabel('$E_r$')
plt.plot(R[:], field_value[:], 'go')
plt.legend()
plt.show()
def Radial_E_field(iz, it, cut):
global Zi, Ri, pot
option = 1
if cut == None:
cut = core.jcut
dZ = core.Zi[1] - core.Zi[0]
dR = core.Ri[1] - core.Ri[0]
Sep_ip = core.getiparrs_hor(0.95, 1., core.jcut)[-1]
# dphi/dR
dphidR_N = []
lengthR = len(core.getcutvalue_hor(core.pot[:, iz, it], cut, option))
iterlistR = list(range(0, lengthR))
potrm10 = core.getcutvalue_hor(core.pot[:, iz, it], cut,
option)[lengthR - 1]
potrp10 = core.getcutvalue_hor(core.pot[:, iz, it], cut, option)[1]
dphidR_N.append(-(potrp10 - potrm10) / (2. * dR))
for i in iterlistR[1:-1]:
potrm1 = core.getcutvalue_hor(core.pot[:, iz, it], cut, option)[i - 1]
potrp1 = core.getcutvalue_hor(core.pot[:, iz, it], cut, option)[i + 1]
dphidR_N.append(-(potrp1 - potrm1) / (2. * dR))
potrm1L = core.getcutvalue_hor(core.pot[:, iz, it], cut,
option)[lengthR - 2]
potrp1L = core.getcutvalue_hor(core.pot[:, iz, it], cut, option)[0]
dphidR_N.append(-(potrp1L - potrm1L) / 2 * dR)
#Plotting
L = np.array([x for x in range(0, len(dphidR_N))])
unit = (core.Rmax - core.Rmin) / 100
R = np.array([L[ip] * unit + core.Rmin for ip in range(0, len(dphidR_N))])
plt.title('Radial E-field')
plt.xlabel('$R(m)$')
plt.ylabel('$E_r$')
plt.plot(R[:], dphidR_N[:], 'go')
plt.axvline(x=Sep_ip * unit + core.Rmin,
color='b',
linestyle='dashed',
linewidth=2)
plt.legend()
plt.show()
def psi_der(arr, it,
cut): #takes the d/dpsi on the potential and divides by RBp
'''Takes a single derivative wrt psi along a cut.'''
option = 1
if cut == None:
cut = core.jcut
dZ = core.Zi[1] - core.Zi[0]
dR = core.Ri[1] - core.Ri[0]
unitR = (core.loader.Rmax - core.loader.Rmin) / len(core.Ri)
unitZ = (core.loader.Zmax - core.loader.Zmin) / len(core.Zi)
arrim1 = np.asarray([
core.getcutvalue_hor(arr[:, iz, it], (cut - 1) % len(core.Zi), option)
for iz in range(0, core.Nplanes)
]).mean(axis=0)
arri = np.asarray([
core.getcutvalue_hor(arr[:, iz, it], cut, option)
for iz in range(0, core.Nplanes)
]).mean(axis=0)
arrip1 = np.asarray([
core.getcutvalue_hor(arr[:, iz, it], (cut + 1) % len(core.Zi), option)
for iz in range(0, core.Nplanes)
]).mean(axis=0)
darrdZ = (arrip1 - arrim1) / (2. * dZ)
arriplus = np.roll(arri, -1)
arriminus = np.roll(arri, 1)
darrdR = (arriplus - arriminus) / (2. * dR)
darrdR[0] = (arri[1] - arri[0]) / dR
darrdR[-1] = (arri[-1] - arri[-2]) / dR
BRi = core.getcutvalue_hor(core.bfield[:, 0], cut, option)
BZi = core.getcutvalue_hor(core.bfield[:, 1], cut, option)
Bzetai = core.getcutvalue_hor(core.bfield[:, 2], cut, option)
Bp = np.sqrt(np.square(BRi) + np.square(BZi))
L = np.array([x for x in range(0, len(core.Ri))])
R = np.array(
[L[ip] * unitR + core.loader.Rmin
for ip in range(0, len(core.Ri))]) + core.Rmaj
darrdpsi = (1 / Bp) * (BRi * darrdZ - BZi * darrdR)
return -darrdpsi / (R * Bp)
def write_turb():
pot_all = np.array([[[
core.getcutvalue_hor(core.pot[:, iz, it], cut, 1)
for iz in range(0, core.Nplanes)
] for cut in range(0, len(L))] for it in range(490, 690)])
np.save('pot_turb_region', pot_all)
