def test_compute_temperature():
vx = np.array([0.1, 0.2])
vy = np.array([10.1, 0.3])
vz = np.array([23.4, 42.5])
m = np.array([2.3, 3.4])
temperature = Ptcls.compute_temperature(vx, vy, vz, m)
assert temperature > 0
def test_compute_kinetic_energies():
vx = np.array([0.1, 0.2])
vy = np.array([10.1, 0.3])
vz = np.array([23.4, 42.5])
m = np.array([2.3, 3.4])
kinetic_energies = Ptcls.compute_kinetic_energies(vx, vy, vz, m)
for i in range(2):
assert abs(kinetic_energies[i] -
0.5 * m[i] * (vx[i]**2 + vy[i]**2 + vz[i]**2)) < 1.0e-7
def run_simulation(n_wells, dt, tmax, num_dump = 1):
# initialize particles
n_ions = n_wells**3
ptcls = Ptcls.Ptcls()
ptcls.set_nptcls(2 * n_ions)
# ions
lattice_spacing = 1.0e-6
xmin = -0.5 * (n_wells - 1) * lattice_spacing
for i in range(n_ions):
ptcls.x()[i] = xmin + lattice_spacing * ((i / (n_wells**0)) % n_wells)
ptcls.y()[i] = xmin + lattice_spacing * ((i / (n_wells**1)) % n_wells)
ptcls.z()[i] = xmin + lattice_spacing * ((i / (n_wells**2)) % n_wells)
ptcls.ptclList[3:6,:n_ions] = 0
ptcls.ptclList[6,:n_ions] = fund_charge
ptcls.ptclList[7,:n_ions] = ion_mass
#electrons
ptcls.ptclList[0:3,n_ions:] = np.random.normal(
0.0, 0.5 * abs(xmin), ptcls.ptclList[0:3,n_ions:].shape)
electron_temperature = 3.0
electron_mass = 9.10938291e-31
kB = 1.3806e-23
vThermal = np.sqrt(kB * electron_temperature / electron_mass)
ptcls.ptclList[3:6,n_ions:] = np.random.normal(
0.0, vThermal, ptcls.ptclList[3:6,n_ions:].shape)
ptcls.ptclList[6,n_ions:] = -fund_charge
ptcls.ptclList[7,n_ions:] = electron_mass
ctx = cl.create_some_context(interactive = True)
queue = cl.CommandQueue(ctx)
coulomb_acc = CoulombAcc.CoulombAcc(ctx, queue)
accelerations = [coulomb_acc]
updater = BorisUpdater.BorisUpdater(ctx, queue)
xd = cl_array.to_device(queue, ptcls.x())
yd = cl_array.to_device(queue, ptcls.y())
zd = cl_array.to_device(queue, ptcls.z())
vxd = cl_array.to_device(queue, ptcls.vx())
vyd = cl_array.to_device(queue, ptcls.vy())
vzd = cl_array.to_device(queue, ptcls.vz())
qd = cl_array.to_device(queue, ptcls.q())
md = cl_array.to_device(queue, ptcls.m())
t = 0.0
while t < tmax:
np.save('ptcls' + str(i) + '.npy',ptcls.ptclList[0:3,:])
t = updater.update(
xd, yd, zd, vxd, vyd, vzd, qd, md, accelerations, t, dt,
num_dump)
xd.get(queue, ptcls.x())
yd.get(queue, ptcls.y())
zd.get(queue, ptcls.z())
np.savetxt('ptcls' + str(num_dump) + '.txt',ptcls.ptclList[0:3,:])
def test_takeSteps():
numSteps = 3
ptcls = Ptcls.Ptcls()
ptcls.numPtcls = 10
ptcls.init_ptcls()
# initial mean velocity of particles
ptcls.ptclList[5] = 20.0 * np.ones_like(ptcls.ptclList[5])
history = np.ndarray([numSteps, ptcls.numPtcls])
updater = BendKickUpdater.BendKickUpdater(testCtx, testQueue)
updater.trapConfiguration.Bz = 1.0e-6
accelerations = [cla0, cla1]
for i in range(numSteps):
history[i] = ptcls.vz().copy()
take_steps(10, 1.0e-6, ptcls, updater, accelerations)
def __init__(self, ctx=None, queue=None):
self.accList = []
self.ptcls = Ptcls.Ptcls()
self.t = 0.0
self.ctx = ctx
self.queue = queue
if self.ctx == None:
self.ctx = cl.create_some_context()
if self.queue == None:
self.queue = cl.CommandQueue(
self.ctx,
properties=cl.command_queue_properties.PROFILING_ENABLE)
self.trapConfiguration = TrapConfiguration.TrapConfiguration()
self.updater = BendKickUpdater.BendKickUpdater(self.ctx, self.queue)
self.updater.trapConfiguration = self.trapConfiguration
def test_initPtcls():
ptcls = Ptcls.Ptcls()
ptcls.numPtcls = 10
ptcls.init_ptcls()
# initial mean velocity of particles
ptcls.ptclList[5] = 20.0 * np.ones_like(ptcls.ptclList[5])
def test_temperature_of_particles():
ptcls = Ptcls.Ptcls()
ptcls.vth = 1.0e4
ptcls.set_nptcls(10)
ptcls.init_ptcls()
assert ptcls.temperature() > 0
def run_simulation(n_ions, dt, tmax, num_dump=1):
# initialize particles
ptcls = Ptcls.Ptcls()
ptcls.set_nptcls(2 * n_ions)
density = 1.0e+18
volume = n_ions / density
l = (3 * volume / 4 / np.pi)**(1. / 3.)
a_ws = (3 / (4 * np.pi * density))**(1. / 3.)
l = l / a_ws
# electron plasma frequency is used to scale time t -> t * w_e
w_e = np.sqrt(density * fund_charge_SI**2 / (electron_mass_SI * Epsilon))
# ions
i = 0
while i < n_ions:
xt = (np.random.random() - 0.5) * l * 2
yt = (np.random.random() - 0.5) * l * 2
zt = (np.random.random() - 0.5) * l * 2
rt = np.sqrt(xt**2 + yt**2 + zt**2)
if rt <= l:
ptcls.x()[i] = xt
ptcls.y()[i] = yt
ptcls.z()[i] = zt
i += 1
ptcls.ptclList[3:6, :n_ions] = 0
ptcls.ptclList[6, :n_ions] = fund_charge
ptcls.ptclList[7, :n_ions] = ion_mass
#electrons
i = 0
while i < n_ions:
xt = (np.random.random() - 0.5) * l * 2
yt = (np.random.random() - 0.5) * l * 2
zt = (np.random.random() - 0.5) * l * 2
rt = np.sqrt(xt**2 + yt**2 + zt**2)
if rt <= l:
ptcls.x()[n_ions + i] = xt
ptcls.y()[n_ions + i] = yt
ptcls.z()[n_ions + i] = zt
i += 1
electron_temperature = 3.0
vThermal = np.sqrt(kB * electron_temperature / electron_mass_SI)
vThermal = vThermal / (a_ws * w_e)
ptcls.ptclList[3:6, n_ions:] = np.random.normal(
0.0, vThermal, ptcls.ptclList[3:6, n_ions:].shape)
ptcls.ptclList[6, n_ions:] = -fund_charge
ptcls.ptclList[7, n_ions:] = electron_mass
ctx = cl.create_some_context(interactive=True)
queue = cl.CommandQueue(ctx)
coulomb_acc = CoulombAccScaled.CoulombAccScaled(ctx, queue)
accelerations = [coulomb_acc]
updater = BorisUpdater.BorisUpdater(ctx, queue)
xd = cl_array.to_device(queue, ptcls.x())
yd = cl_array.to_device(queue, ptcls.y())
zd = cl_array.to_device(queue, ptcls.z())
vxd = cl_array.to_device(queue, ptcls.vx())
vyd = cl_array.to_device(queue, ptcls.vy())
vzd = cl_array.to_device(queue, ptcls.vz())
qd = cl_array.to_device(queue, ptcls.q())
md = cl_array.to_device(queue, ptcls.m())
t = 0.0
while t < tmax:
#np.save('data\ptcls' + str(t) + '.npy',ptcls.ptclList[0:6,:])
np.savetxt('data\ptcls' + str(t) + '.txt', ptcls.ptclList[0:6, :])
t = updater.update(xd, yd, zd, vxd, vyd, vzd, qd, md, accelerations, t,
dt, num_dump)
xd.get(queue, ptcls.x())
yd.get(queue, ptcls.y())
zd.get(queue, ptcls.z())
vxd.get(queue, ptcls.vx())
vyd.get(queue, ptcls.vy())
vzd.get(queue, ptcls.vz())
np.savetxt('data\ptcls' + str(t) + '.txt', ptcls.ptclList[0:6, :])