def sphericalDatapoint(theta, phi):
# Expect theta and rho to be in radians
# theta is the angle from the +z-axis to the coordinate vector
# rho is the angle from the +x-axis to projection of the coordinate
# vector onto the xy-plane
sin_theta = numerix.sin(theta)
print(sin_theta)
cos_theta = numerix.cos(theta)
sin_phi = numerix.sin(phi)
#print(len(sin_phi))
cos_phi = numerix.cos(phi)
return sin_theta * getCellVariableDatapoint.remote(
[[sin_theta * cos_phi], [sin_theta * sin_phi], [cos_theta]])
def _plot(self):
var = self.vars[0]
mesh = var.mesh
U, V = var.numericValue
U = numerix.take(U, self.indices)
V = numerix.take(V, self.indices)
ang = numerix.arctan2(V, U)
mag = numerix.sqrt(U**2 + V**2)
datamin, datamax = self._autoscale(vars=(mag, ),
datamin=self._getLimit('datamin'),
datamax=self._getLimit('datamax'))
mag = numerix.where(mag > datamax, datamax, mag)
mag = numerix.ma.masked_array(mag, mag < datamin)
if self.log:
mag = numerix.log10(mag)
mag = numerix.ma.masked_array(mag, numerix.isnan(mag))
U = mag * numerix.cos(ang)
V = mag * numerix.sin(ang)
self._quiver.set_UVC(U, V)
self.axes.set_xlim(xmin=self._getLimit('xmin'),
xmax=self._getLimit('xmax'))
self.axes.set_ylim(ymin=self._getLimit('ymin'),
ymax=self._getLimit('ymax'))
def _plot(self):
var = self.vars[0]
mesh = var.mesh
U, V = var.numericValue
U = numerix.take(U, self.indices)
V = numerix.take(V, self.indices)
ang = numerix.arctan2(V, U)
mag = numerix.sqrt(U**2 + V**2)
datamin, datamax = self._autoscale(vars=(mag,),
datamin=self._getLimit('datamin'),
datamax=self._getLimit('datamax'))
mag = numerix.where(mag > datamax, datamax, mag)
mag = numerix.ma.masked_array(mag, mag < datamin)
if self.log:
mag = numerix.log10(mag)
mag = numerix.ma.masked_array(mag, numerix.isnan(mag))
U = mag * numerix.cos(ang)
V = mag * numerix.sin(ang)
self._quiver.set_UVC(U, V)
self.axes.set_xlim(xmin=self._getLimit('xmin'),
xmax=self._getLimit('xmax'))
self.axes.set_ylim(ymin=self._getLimit('ymin'),
ymax=self._getLimit('ymax'))
def _plot(self):
from scipy.interpolate import griddata
var = self.vars[0]
mesh = var.mesh
xmin, ymin = mesh.extents['min']
xmax, ymax = mesh.extents['max']
N = 100
X = numerix.linspace(xmin, xmax, N)
Y = numerix.linspace(ymin, ymax, N)
grid_x, grid_y = numerix.mgrid[xmin:xmax:N * 1j, ymin:ymax:N * 1j]
if isinstance(var, FaceVariable):
C = mesh.faceCenters
elif isinstance(var, CellVariable):
C = mesh.cellCenters
U = griddata(C.value.T, var.value[0], (grid_x, grid_y), method='cubic')
V = griddata(C.value.T, var.value[1], (grid_x, grid_y), method='cubic')
lw = self.linewidth
if isinstance(lw, (FaceVariable, CellVariable)):
lw = griddata(C.value.T,
lw.value, (grid_x, grid_y),
method='cubic')
color = self.color
if isinstance(color, (FaceVariable, CellVariable)):
color = griddata(C.value.T,
color.value, (grid_x, grid_y),
method='cubic',
fill_value=color.min())
U = U.T
V = V.T
ang = numerix.arctan2(V, U)
mag = numerix.sqrt(U**2 + V**2)
datamin, datamax = self._autoscale(vars=(mag, ),
datamin=self._getLimit('datamin'),
datamax=self._getLimit('datamax'))
mag = numerix.where(mag > datamax, numerix.nan, mag)
mag = numerix.where(mag < datamin, numerix.nan, mag)
if self.log:
mag = numerix.log10(mag)
U = mag * numerix.cos(ang)
V = mag * numerix.sin(ang)
# if self._stream is not None:
# # the following doesn't work, nor does it help to `add_collection` first
# # self._stream.arrows.remove()
# self._stream.lines.remove()
self.axes.cla()
self._stream = self.axes.streamplot(X,
Y,
U,
V,
linewidth=lw,
color=color,
**self.kwargs)
self.axes.set_xlim(xmin=self._getLimit('xmin'),
xmax=self._getLimit('xmax'))
self.axes.set_ylim(ymin=self._getLimit('ymin'),
ymax=self._getLimit('ymax'))
stats = []
Phieq = fp.DiffusionTerm(var=Phi) == fp.ImplicitSourceTerm(coeff=-k / epsilon,
var=c)
eq = ceq & psieq & Phieq
x, y = mesh.cellCenters
X, Y = mesh.faceCenters
Phi.faceGrad.constrain(0.,
where=mesh.physicalFaces["top"]
| mesh.physicalFaces["bottom"])
Phi.constrain(0., where=mesh.physicalFaces["left"])
Phi.constrain(sin(Y / 7.), where=mesh.physicalFaces["right"])
c0 = 0.5
c1 = 0.04
c.setValue(c0 + c1 *
(cos(0.2 * x) * cos(0.11 * y) +
(cos(0.13 * x) * cos(0.087 * y))**2 + cos(0.025 * x - 0.15 * y) *
(cos(0.07 * x - 0.02 * y))))
Phi.setValue(0.)
synchTimes = [0, 5, 10, 20, 50, 100, 200, 400, 1000]
synchTimes.reverse()
t = synchTimes.pop()
d2fchemd2c * c + dfchemdc - fp.DiffusionTerm(coeff=kappa, var=c) +
fp.ImplicitSourceTerm(coeff=k, var=Phi))
stats = []
Phieq = fp.DiffusionTerm(var=Phi) == fp.ImplicitSourceTerm(coeff=-k / epsilon,
var=c)
eq = ceq & psieq & Phieq
x, y = mesh.cellCenters
X, Y = mesh.faceCenters
Phi.faceGrad.constrain(0., where=mesh.facesTop | mesh.facesBottom)
Phi.constrain(0., where=mesh.facesLeft)
Phi.constrain(sin(Y / 7.), where=mesh.facesRight)
c0 = 0.5
c1 = 0.04
c.setValue(c0 + c1 *
(cos(0.2 * x) * cos(0.11 * y) +
(cos(0.13 * x) * cos(0.087 * y))**2 + cos(0.025 * x - 0.15 * y) *
(cos(0.07 * x - 0.02 * y))))
Phi.setValue(0.)
synchTimes = [0, 5, 10, 20, 50, 100, 200, 400, 1000]
synchTimes.reverse()
t = synchTimes.pop()
#print(numerix.shape(m_cell_modified_sph_pol))
m_cell_sph = numerix.append(
m_cell_sph, (m_cell_modified_sph_pol),
axis=1) #Appending the m values in spherical polar coordinate
theta_sz = np.shape(theta_sorted)
size = theta_sz[0]
total_size = total_size + size # calculate total number of cells being covered during calculation
phi_value = phi_value + delta # phi is increased by delta at end of each loop
print('Total number of cells covered = ' + str(total_size))
#type(m_cell_sph)
######## Converted the spherical polar coordinates back to cartesian coordinate #####################
m_x = (m_cell_sph[0, :] * numerix.sin(m_cell_sph[2, :]) *
numerix.cos(m_cell_sph[1, :]))
m_y = (m_cell_sph[0, :] * numerix.sin(m_cell_sph[2, :]) *
numerix.sin(m_cell_sph[1, :]))
m_z = m_cell_sph[0, :] * numerix.cos(m_cell_sph[2, :])
m_cellcenters_cart_modified = numerix.array([[m_x], [m_y], [m_z]])
#numerix.shape(m_cellcenters_cart_modified)
m_cellcenters_cart_modified = numerix.reshape(m_cellcenters_cart_modified,
(3, total_size))
#mcell_new=m_cellcenters_cart_modified*CellVariable([1.0])
mcell_new = CellVariable(mesh=mesh, value=m_cellcenters_cart_modified)
def one_fourier (n):
mode = (-2.0/(n*pi))*numerix.sin(n*pi*x)*numerix.exp(-t*(pi**2)*(n**2))
return mode
magVolume = 1.0e-9 * (40e-9 * 40e-9) * (numerix.pi / 4.0) # in m^3
#magVolume=(numerix.pi/4)*length*width*thickness
delta = 43.0
Eb = delta * kBoltzmann * Temperature
Ku2 = Eb / magVolume
#Ku2 = 2.245e5 # in J/m^3
#print('Ku2 = '+str(Ku2))
D = alphaDamping * gamFac * kBoltzmann * Temperature / (
(1 + alphaDamping**2) * Msat * magVolume) # unit 1/s
# ### Calculation of uniaxial anisotropy field
th = numerix.pi / 6.0
ph = 0.0 * numerix.pi
ux = numerix.sin(th) * numerix.cos(ph)
uy = numerix.sin(th) * numerix.sin(ph)
uz = numerix.cos(th)
uAxis = numerix.array([[ux, uy, uz]])
#uAxis=numerix.array([[0.0,0.0,1.0]])
HuniaxBase = H_UniaxialAnisotropy(mAllCell, uAxis, Ku2, Msat)
print('Max_Huni=' + str(max(HuniaxBase[2, :])))
print('Min_Huni=' + str(min(HuniaxBase[2, :])))
######## Create matrix form of applied magnetic field ####################################
th = numerix.pi / 6.0
ph = 0.0 * numerix.pi
ux = numerix.sin(th) * numerix.cos(ph)
uy = numerix.sin(th) * numerix.sin(ph)
def sin(self):
return self._UnaryOperatorVariable(lambda a: numerix.sin(a))
vacuum = ~(ntype | ptype)
# Assigning material properties to each Cell
cdse_cdte = (CdSe() * ntype + CdTe() * ptype + Vacuum() * vacuum)
nFaces = mesh.facesLeft
pFaces = mesh.facesRight
illuminatedFaces =mesh.facesLeft
nContact = OhmicContact(faces=nFaces)
pContact = OhmicContact(faces=pFaces)
##graded doping
x_dummy = x.value*(x.value>=n_thickness)
y_dummy = (1e22*(x_dummy-n_thickness)/(p_thickness-n_thickness) + 1e17 )*(x.value>=n_thickness) #linear
y_dummy =1e21*abs(numerix.sin((x_dummy-n_thickness)*2e6))# abs(sin(x))
diode = Device(mesh=mesh,
temperature=300, # K
material=cdse_cdte,
dopants=(Donor(concentration=1e23 * ntype, # m**-3"
ionizationEnergy=-1.), # eV
Acceptor(concentration=y_dummy * ptype, # m**-3
ionizationEnergy=-1.)), # eV
traps=(ShockleyReadHallTrap(recombinationLevel=0, # eV
electronMinimumLifetime=3e-11, # s
holeMinimumLifetime=3e-11),), # s
contacts=(pContact, nContact))
diode.contacts[1].bias.value = 0. # V
import re import os # Setting up a mesh nx = 50 dx = 0.02 L = nx * dx mesh = Grid1D(nx=nx, dx=dx) # Defining the cell variable c = CellVariable(mesh=mesh, name=r"$c$") # Initialise c with a funky profile x = mesh.cellCenters[0] c.value = 0.0 c.setValue((0.3 * numerix.sin(2.0 * x * numerix.pi)) + 0.5) # Setting up the no-flux boundary conditions c.faceGrad.constrain(0.0, where=mesh.facesLeft) c.faceGrad.constrain(0.0, where=mesh.facesRight) # Provide value for diffusion and reaction coefficient D = 1.0 k = -2.0 # Specifying our alpha value. We will only use backwards Euler going forward alpha = 1 # Defining the equation with the reaction term. eq = TransientTerm() == DiffusionTerm(coeff=D) + ImplicitSourceTerm(coeff=k)
def make_tau(phase_):
theta_cell = numerix.arctan2(phase_.grad[1], phase_.grad[0])
a_cell = 1 + epsilon_m * numerix.cos(mm * theta_cell + theta_0)
return tau_0 * a_cell**2
tau = make_tau(phase)
tau_old = make_tau(phase.old)
source = (phase - lamda * uu * (1 - phase**2)) * (1 - phase**2)
theta = numerix.arctan2(phase.faceGrad[1], phase.faceGrad[0])
W = W_0 * (1 + epsilon_m * numerix.cos(mm * theta - theta_0))
W_theta = - W_0 * mm * epsilon_m * numerix.sin(mm * theta - theta_0)
# Build up the diffusivity matrix
I0 = Variable(value=((1,0), (0,1)))
I1 = Variable(value=((0,-1), (1,0)))
Dphase = W**2 * I0 + W * W_theta * I1
heat_eqn = TransientTerm() == DiffusionTerm(DD) + (phase - phase.old) / dt / 2.
phase_eqn = TransientTerm(tau) == DiffusionTerm(Dphase) + source
initialize()
solid_area = (np.array(phase.globalValue)>0).sum()*dx*dy # initial size of solid nucleus
if parallelComm.procID==0:
