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fieldsWrapper.py
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#!/usr/bin/env python
# -*- coding: utf-8 -*-
import numpy as np
import matplotlib.pyplot as plt
from fieldlib import *
from finite_differences import *
#from finite_differences_x import *
def field_smoother(field):
field_smooth = np.zeros(len(field), dtype = 'complex128')
field_tmp = np.zeros(len(field), dtype = 'complex128')
field_tmp[0] = field[0]
field_tmp[len(field) - 1] = field[len(field) - 1]
for i in range(1, len(field) - 1):
field_tmp[i] = 0.5 * field[i] + 0.25 * (field[i - 1] + \
field[i + 1])
field_smooth[0] = field_tmp[0]
field_smooth[len(field) - 1] = field_tmp[len(field) - 1]
for i in range(1, len(field) - 1):
field_smooth[i] = 0.5 * field_tmp[i] + 0.25 * (field_tmp[i - 1] + \
field_tmp[i + 1])
if 1 == 0:
plt.plot(np.real(field), label = 're before')
plt.plot(np.real(field_smooth), label = 're after')
plt.legend()
plt.show()
plt.plot(np.imag(field), label = 'im before')
plt.plot(np.imag(field_smooth), label = 'im after')
plt.legend()
plt.show()
return field_smooth
def eigenfunctions_from_field_file(pars,suffix,center_only,plot,setTime=-1,smooth_field = False, scale_field = True):
field = fieldfile('field'+suffix,pars)
nz = int(field.nz)
nx = int(field.nx)
if (setTime == -1):
field.set_time(field.tfld[setTime])
# print 'Reading eigenfunctions are at t = ', field.tfld[setTime]
else:
isetTime = np.argmin(abs(np.array(field.tfld)-setTime))
field.set_time(field.tfld[isetTime])
# print 'Reading eigenfunctions are at t = ', field.tfld[isetTime]
if center_only:
ikx_grid = [0]
phi = np.zeros(nz,dtype='complex128')
apar = np.zeros(nz,dtype='complex128')
else:
#print("nx",nx,"nx/2",nx/2,"floor(nx/2)",np.floor(nx/2))
ikxmin = int( -np.ceil(nx/2)+1)
ikx_grid = np.arange(nx)+ikxmin
#ikx_grid = np.arange(-int(np.floor(nx/2)+1),int(np.floor(nx/2)+1))
#print("ikx_grid",ikx_grid)
phi = np.zeros(nx*nz,dtype='complex128')
apar = np.zeros(nx*nz,dtype='complex128')
if 'n0_global' in pars:
phase_fac = -np.e**(-2.0*np.pi*(0.0+1.0J)*int(pars['n0_global']) * float(pars['q0']))
else:
phase_fac = -1.0
if float(pars['shat']) > 0.:
for i in ikx_grid:
this_phi = field.phi()[:,0,i]*phase_fac**i
phi[(i-ikx_grid[0])*nz:(i-ikx_grid[0]+1)*nz]=this_phi
if int(pars['n_fields']) > 1 and float(pars['beta']) !=0:
this_apar = field.apar()[:,0,i]*phase_fac**i
apar[(i-ikx_grid[0])*nz:(i-ikx_grid[0]+1)*nz]=\
this_apar
else:
for i in ikx_grid:
#print("ikx_grid",ikx_grid)
this_phi = field.phi()[:,0,-int(i)]*phase_fac**i
#print("len(this_phi)",len(this_phi))
#print("(i-ikx_grid[0])*nz,(i-ikx_grid[0]+1)*nz",(i-ikx_grid[0])*nz,(i-ikx_grid[0]+1)*nz)
#print("len(phi)",len(phi))
phi[(i-ikx_grid[0])*nz:(i-ikx_grid[0]+1)*nz]=this_phi
if pars['n_fields'] > 1 and pars['beta'] !=0:
this_apar = field.apar()[:,0,-i]*phase_fac**i
apar[(i-ikx_grid[0])*nz:(i-ikx_grid[0]+1)*nz]=\
this_apar
# Normalize phi and apar by highest value so that the peak abs val = 1
if scale_field:
phi = phi/np.max(abs(field.phi()[:,0,:]))
if int(pars['n_fields']) > 1 and float(pars['beta']) !=0:
apar = apar/np.max(abs(field.apar()[:,0,:]))
if plot:
if (setTime == -1):
figTitle='t = '+ str(field.tfld[setTime])
else:
figTitle='t = '+ str(field.tfld[isetTime])
if center_only:
figTitle = figTitle+' center only'
else:
figTitle = figTitle+' entire simulation domain'
plt.plot(np.real(phi),label='Re(phi)')
plt.plot(np.imag(phi),label='Im(phi)')
plt.plot(abs(phi),label='abs(phi)')
plt.title(figTitle)
plt.legend()
plt.show()
if plot and pars['n_fields'] > 1 and pars['beta'] !=0:
plt.plot(np.real(apar),label='Re(apar)')
plt.plot(np.imag(apar),label='Im(apar)')
plt.plot(abs(apar),label='abs(apar)')
plt.title(figTitle)
plt.legend()
plt.show()
return phi, apar
def eigenfunction_average(z_grid,jacobian,kperp,omega_d,field,name):
ave_kperp2 = 0.
ave_omegad = 0.
denom = 0.
for i in np.arange(len(field)-1):
ave_kperp2 = ave_kperp2 + (kperp[i]**2*abs(field[i])**2 +\
kperp[i+1]**2*abs(field[i+1])**2)/2.*\
(z_grid[i+1]-z_grid[i])/jacobian[i]
ave_omegad = ave_omegad + (omega_d[i]*abs(field[i])**2 +\
omega_d[i+1]*abs(field[i+1])**2)/2.*\
(z_grid[i+1]-z_grid[i])/jacobian[i]
denom = denom + (abs(field[i])**2 +abs(field[i+1])**2)/2.*\
(z_grid[i+1]-z_grid[i])/jacobian[i]
ave_kperp2 = ave_kperp2/denom
ave_kperp = np.sqrt(ave_kperp2)
#print name + ' weighted k_perp^2 =', ave_kperp2
#print( name + ' weighted k_perp =', ave_kperp)
ave_omegad = ave_omegad/denom
#print( name + ' weighted omega_d =', ave_omegad)
return ave_kperp, ave_omegad
def eigenfunction_squared(z_grid,jacobian,field):
ave_sq_int = 0.
ave_int_sq = 0.
for i in np.arange(len(field)-1):
ave_sq_int = ave_sq_int + ((field[i])**2 +\
(field[i+1])**2)/2.*\
(z_grid[i+1]-z_grid[i])/jacobian[i]
ave_int_sq = ave_int_sq + (field[i] +\
field[i+1])/2.*\
(z_grid[i+1]-z_grid[i])/jacobian[i]
ave_sq_int = abs(ave_sq_int)
#print( 'int phi**2 =', ave_sq_int)
ave_int_sq= abs(ave_int_sq)**2
#print( ' (int phi)**2 =', ave_int_sq)
return ave_sq_int, ave_int_sq
def kz_from_dfielddz(zgrid, jacobian, field, plot, name, zstart = 0., zend = 0.):
dfielddz = np.empty(len(field)-1,dtype='complex128')
for i in range(len(field)-1):
dfielddz[i] = (field[i+1]-field[i])/\
(zgrid[i+1]-zgrid[i])*jacobian[i]
if plot:
zg_plot = zgrid[:-1]
plt.plot(zg_plot, np.abs(dfielddz), label = 'abs d'+name+'/dz')
plt.plot(zg_plot, np.real(dfielddz), label = 'real d'+name+'/dz')
plt.plot(zg_plot, np.imag(dfielddz), label = 'imag d'+name+'/dz')
plt.plot(zgrid, np.abs(field), label = 'abs '+name)
plt.plot(zgrid, jacobian, label = 'jacobian')
plt.legend()
plt.xlabel('z')
plt.show()
sum_ddz = 0.
denom = 0.
##if not (zstart == 0. and zend == 0.):
if zstart == zend:
zstart = float(input("Enter start z: "))
zend = float(input("Enter end z: "))
startInd = np.argmin(abs(zgrid - zstart))
endInd = np.argmin(abs(zgrid - zend))
for i in range(startInd, endInd + 1):
sum_ddz = sum_ddz + 0.5*(abs(dfielddz[i])**2+\
abs(dfielddz[i+1])**2)*\
(zgrid[i+1]-zgrid[i])/jacobian[i]
denom = denom + 0.5*(abs(field[i])**2 + abs(field[i+1])**2)*\
(zgrid[i+1]-zgrid[i])/jacobian[i]
ave_kz = np.sqrt(sum_ddz/denom)
#print( name + ' averaged kz = ', ave_kz)
#print( 'Input to SKiM kz = ', ave_kz)
return ave_kz, zstart, zend
def fourierTrans(pars,zgrid,jacobian,field,plot,name):
zi=complex(0,1)
field_kz = np.empty(0,dtype='complex128')
nkz = 100
lkz = pars['nz0']/2
kz_grid = np.linspace(-lkz,lkz,nkz,endpoint=False)
for k in np.arange(len(kz_grid)):
this_field_kz = 0.
for i in np.arange(len(zgrid)-1):
this_field_kz = this_field_kz + 0.5*(field[i]*\
np.exp(zi*kz_grid[k]*zgrid[i])\
+field[i+1]*np.exp(zi*kz_grid[k]*zgrid[i+1]))*\
(zgrid[i+1]-zgrid[i])/jacobian[i]
field_kz = np.append(field_kz,this_field_kz)
if plot:
plt.plot(kz_grid,np.abs(field_kz),label='abs('+name+'_kz)')
plt.plot(kz_grid,np.real(field_kz),label='real('+name+'_kz)')
plt.plot(kz_grid,np.imag(field_kz),label='imag('+name+'_kz)')
plt.xlabel('kz')
plt.title('ky = '+str(pars['kymin']))
plt.legend()
plt.show()
kzstart = float(input("Enter start kz: "))
kzend = float(input("Enter end kz: "))
startInd = np.argmin(abs(kz_grid - kzstart))
endInd = np.argmin(abs(kz_grid - kzend))
sum_kz2 = 0.
denom = 0.
for i in range(len(kz_grid)-1):
sum_kz2 = sum_kz2 + 0.5*(kz_grid[i]**2*abs(field_kz[i])**2+\
kz_grid[i+1]**2*abs(field_kz[i+1])**2)*\
(kz_grid[i+1]-kz_grid[i])
denom = denom + 0.5*(abs(field_kz[i])**2 + \
abs(field_kz[i+1])**2)*(kz_grid[i+1]-kz_grid[i])
ave_kz = np.sqrt(sum_kz2/denom)
#print( name + ' averaged kz = ', ave_kz)
#print 'input to SKiM averaged kz = ', ave_kz/np.pi/pars['q0']/pars['major_R']
return field_kz, kz_grid
def LILO_eigenfunctions_from_field_file(pars,suffix,plot,setTime=-1):
field = fieldfile('field'+suffix,pars)
nz = int(field.nz)
nx = int(field.nx)
if (setTime == -1):
field.set_time(field.tfld[setTime])
print( 'Reading eigenfunctions are at t = ', field.tfld[setTime])
else:
isetTime = np.argmin(abs(np.array(field.tfld)-setTime))
field.set_time(field.tfld[isetTime])
print( 'Reading eigenfunctions are at t = ', field.tfld[isetTime])
if 1 == 0:
phi = np.zeros(nz,dtype='complex128')
apar = np.zeros(nz,dtype='complex128')
else:
phi = np.zeros(field.nx,dtype='complex128')
apar = np.zeros(field.nx,dtype='complex128')
if 1 == 1:
phi = field.phi()[nz/2,0,:]
apar = field.apar()[nz/2,0,:]
# Normalize phi and apar by highest value so that the peak abs val = 1
phi = phi/np.max(abs(field.phi()[nz/2,0,:]))
apar = apar/np.max(abs(field.apar()[nz/2,0,:]))
if plot:
if (setTime == -1):
figTitle='t = '+ str(field.tfld[setTime])
else:
figTitle='t = '+ str(field.tfld[isetTime])
plt.plot(np.real(phi),label='Re(phi)')
plt.plot(np.imag(phi),label='Im(phi)')
plt.plot(abs(phi),label='abs(phi)')
plt.title(figTitle)
plt.legend()
plt.show()
if plot and pars['n_fields'] > 1 and pars['beta'] !=0:
plt.plot(np.real(apar),label='Re(apar)')
plt.plot(np.imag(apar),label='Im(apar)')
plt.plot(abs(apar),label='abs(apar)')
plt.title(figTitle)
plt.legend()
plt.show()
return phi, apar