def getSpectraAndDisp(k0, nK, nW, root, comp=0):
files = glob(root)
numFiles = len(files)
d = pg.GData(files[0])
dg = pg.GInterpNodal(d, 2, 'ns')
x, val = dg.interpolate(0)
evolution = np.zeros((numFiles, len(x[0])))
spectrum = np.zeros((numFiles, nK))
t = np.zeros(numFiles)
for i, f in enumerate(files):
d = pg.GData(f)
t[i] = d.time
dg = pg.GInterpNodal(d, 2, 'ns')
x, val = dg.interpolate(comp)
evolution[i, :] = val
valf = fftpack.fft(val)
spectrum[i, :] = np.abs(valf[1:(nK + 1)])**2
k = fftpack.fftfreq(len(val), x[0][1] - x[0][0])
k = 2 * np.pi * k[1:(nK + 1)] / k0
x = x[0] * k0 / 2 / np.pi
disp = np.zeros((nW, nK))
for i in range(nK):
ft = fftpack.fft(spectrum[:, i])
disp[:, i] = np.abs(ft[1:(nW + 1)])**2
omega = fftpack.fftfreq(numFiles, t[1] - t[0])
omega = 2 * np.pi * omega[1:(nW + 1)]
return x, k, t, omega, evolution, spectrum, disp
def getMoments(polyOrder, pre, numInterp):
d = postgkyl.GData("%s-sod-shock_neut_M0_1.bp" % pre)
dg = postgkyl.GInterpModal(d, polyOrder, "ms", numInterp=numInterp)
X, m0 = dg.interpolate()
d = postgkyl.GData("%s-sod-shock_neut_M1i_1.bp" % pre)
dg = postgkyl.GInterpModal(d, polyOrder, "ms", numInterp=numInterp)
X, m1i = dg.interpolate()
d = postgkyl.GData("%s-sod-shock_neut_M2_1.bp" % pre)
dg = postgkyl.GInterpModal(d, polyOrder, "ms", numInterp=numInterp)
X, m2 = dg.interpolate()
d = postgkyl.GData("%s-sod-shock_neut_M3i_1.bp" % pre)
dg = postgkyl.GInterpModal(d, polyOrder, "ms", numInterp=numInterp)
X, m3i = dg.interpolate()
u = m1i / m0 # Velocity.
nvt2 = m2 - m0 * u**2 # Pressure (density*temperature).
q = m3i - (3 * u * m2 - 3 * u**2 * m1i + u**3 * m0
) # Plasma-frame heat-flux.
Xn = X[0]
dx = Xn[1] - Xn[0]
# Cell-center coordinates.
Xc = linspace(Xn[0] + 0.5 * dx, Xn[-1] - 0.5 * dx, Xn.shape[0] - 1)
return Xc, m0, u, nvt2, q
def calcEnergyError(pre, p):
# Inputs:
# pre - prefix for file name.
# p - polynomial order (used for assisting in distinguishing between different prefixes).
# Outputs:
# t - array of time data.
# err - normalized error ( abs(err - err[0])/err[0] ) in the total energy.
# Read in electron data.
d = postgkyl.GData("%s-conservation-test-%s_elc_intM2Thermal.bp" %
(pre, p))
elcM2Thermal = 0.5 * elcMass * d.getValues()
d = postgkyl.GData("%s-conservation-test-%s_elc_intM2Flow.bp" % (pre, p))
elcM2Flow = 0.5 * elcMass * d.getValues()
# Read in proton data.
d = postgkyl.GData("%s-conservation-test-%s_ion_intM2Thermal.bp" %
(pre, p))
ionM2Thermal = 0.5 * ionMass * d.getValues()
d = postgkyl.GData("%s-conservation-test-%s_ion_intM2Flow.bp" % (pre, p))
ionM2Flow = 0.5 * ionMass * d.getValues()
# Read in electromagnetic field data.
d = postgkyl.GData("%s-conservation-test-%s_fieldEnergy.bp" % (pre, p))
fieldEnergy = 0.5 * epsilon0 * d.getValues()
t = d.getGrid()[0]
err = calcNormError(elcM2Flow[:, 0] + elcM2Thermal[:, 0] +
ionM2Flow[:, 0] + ionM2Thermal[:, 0] +
fieldEnergy[:, 0])
return t, err
def getMoments(polyOrder, pre, numInterp):
d = postgkyl.GData("%s-sod-shock_neut_M0_1.bp" % pre)
dg = postgkyl.GInterpModal(d, polyOrder, "ms", numInterp=numInterp)
X, m0 = dg.interpolate()
d = postgkyl.GData("%s-sod-shock_neut_M1i_1.bp" % pre)
dg = postgkyl.GInterpModal(d, polyOrder, "ms", numInterp=numInterp)
X, m1i = dg.interpolate()
d = postgkyl.GData("%s-sod-shock_neut_M2_1.bp" % pre)
dg = postgkyl.GInterpModal(d, polyOrder, "ms", numInterp=numInterp)
X, m2 = dg.interpolate()
d = postgkyl.GData("%s-sod-shock_neut_M3i_1.bp" % pre)
dg = postgkyl.GInterpModal(d, polyOrder, "ms", numInterp=numInterp)
X, m3i = dg.interpolate()
u = m1i/m0 # velocity
nvt2 = m2 - m0*u**2 # ptcl internal energy
q = m3i - (3*u*m2 - 3*u**2*m1i + u**3*m0) # heat-flux
Xn = X[0]; dx = Xn[1]-Xn[0]
# cell-center coordinates
Xc = linspace(Xn[0]+0.5*dx, Xn[-1]-0.5*dx, Xn.shape[0]-1)
return Xc, m0, u, nvt2, q
def calcEnergyError(pre):
d = postgkyl.GData("%s-relax_neut_intM2Thermal.bp" % pre)
m2Thermal = d.getValues()
d = postgkyl.GData("%s-relax_neut_intM2Flow.bp" % pre)
m2Flow = d.getValues()
t = d.getGrid()[0]
err = calcNormError(m2Flow + m2Thermal)
return t, err
def calcMeanSpect(fn, lo, up):
d = postgkyl.GData("%s_00%d.bp" % (fn, lo))
s = d.getValues()
g = d.getGrid()
dx = g[0][1] - g[0][0]
gc = linspace(g[0][0] + 0.5 * dx, g[0][-1] - 0.5 * dx, g[0].shape[0] - 1)
for i in range(lo + 1, up + 1):
d = postgkyl.GData("%s_00%d.bp" % (fn, i))
s = s + d.getValues()
return gc, sqrt(s / (up - lo + 1))
def calc_ke_dke(root_file_name, initFrame, finalFrame, dim, Vol):
#function to calculate all the total kinetic energy and the rate of dissipation of KE
#root_file_name is the name of the file before the numbers start
#initFrame is the first frame and finalFrame is the final frame
#dim gives the dimension of the simulation (2 = 2D, 3 = 3D)
#Vol = the volume of the grid
#returns the kinetic energy and dissipation of KE
#calculate integrated kinetic energy
ke = np.zeros((1, (finalFrame - initFrame + 1)))
dEk = ke
f = postgkyl.GData(root_file_name + str(initFrame) + '.bp')
grid = f.getGrid()
dx = grid[0][1] - grid[0][0]
dy = grid[1][1] - grid[1][0]
dt = (finalTime - initTime + 1) / (finalFrame - initFrame + 1)
r = 0
if dim == 3:
dz = grid[2][1] - grid[2][0]
elif dim == 2:
dz = 1
for c in range(initFrame, finalFrame + 1):
frame = postgkyl.GData(root_file_name + "%d.bp" % c)
data = frame.getValues()
if dim == 2:
rho = data[:, :, 0]
px = data[:, :, 1]
py = data[:, :, 2]
pz = data[:, :, 3]
elif dim == 3:
rho = data[:, :, :, 0]
px = data[:, :, :, 1]
py = data[:, :, :, 2]
pz = data[:, :, :, 3]
u = px / (rho * V0)
v = py / (rho * V0)
w = pz / (rho * V0)
e = rho * (u**2 + v**2 + w**2)
ke[0, r] = np.sum(e, axis=(0, 1, 2)) * dx * dy * dz * Vol
r += 1
r = 0
for i in range(initFrame, finalFrame - 1):
dEk[0, r] = -(ke[0, i + 1] - ke[0, i]) / dt
r += 1
return ke, dEk
def calcEnergyError(pre):
d = postgkyl.GData("%s-sonic-sod-shock_neut_intM2Thermal.bp" % pre)
m2Thermal = d.getValues()
d = postgkyl.GData("%s-sonic-sod-shock_neut_intM2Flow.bp" % pre)
m2Flow = d.getValues()
t = d.getGrid()[0]
eErr = calcNormError(m2Flow + m2Thermal)
d = postgkyl.GData("%s-sonic-sod-shock_neut_intM1i.bp" % pre)
m1i = d.getValues()
mErr = calcNormError(m1i)
return t, eErr, mErr
def getJ(fr):
data = pg.GData("%s_elc_M1i_%d.bp" % (baseNm, fr))
dg = pg.data.GInterpModal(data, 2, "ms")
XX, m1e = dg.interpolate()
data = pg.GData("%s_ion_M1i_%d.bp" % (baseNm, fr))
dg = pg.data.GInterpModal(data, 2, "ms")
XX, m1i = dg.interpolate()
Jg = 0.159*ones(Ji.shape, float)
Xn = XX[0]; dx = Xn[1]-Xn[0]
Xc = linspace(Xn[0]+0.5*dx, Xn[-1]-0.5*dx, Xn.shape[0]-1)
return Xc, m1i, -m1e+Jg
def getRawGrid(dataFile, **opKey):
pgData = pg.GData(dataFile) #.Read data with pgkyl.
dimOut = pgData.getNumDims()
xNodal = pgData.getGrid()
#.If desired, output cell center values of grid coordinates instead of nodal coordinates.
if 'location' in opKey:
if opKey['location'] == 'center':
xOut = [[] for i in range(dimOut)]
for i in range(dimOut):
nNodes = np.shape(xNodal[i])[0]
xOut[i] = np.zeros(nNodes - 1)
xOut[i] = np.multiply(
0.5, xNodal[i][0:nNodes - 1] + xNodal[i][1:nNodes])
else:
xOut = xNodal
else:
xOut = xNodal
nxOut = np.zeros(dimOut, dtype='int')
lxOut = np.zeros(dimOut, dtype='double')
dxOut = np.zeros(dimOut, dtype='double')
for i in range(dimOut):
nxOut[i] = np.size(xOut[i])
lxOut[i] = xOut[i][-1] - xOut[i][0]
dxOut[i] = xOut[i][1] - xOut[i][0]
return xOut, dimOut, nxOut, lxOut, dxOut
def test_LoadBpFrame(self):
data = pg.GData('data/frame_0.bp')
nd = data.getNumDims()
assert (isinstance(nd, int))
self.assertEqual(nd, 2)
nc = data.getNumComps()
assert (isinstance(nc, int))
self.assertEqual(nc, 8)
lo, up = data.getBounds()
assert (isinstance(lo, np.ndarray))
assert (isinstance(up, np.ndarray))
self.assertEqual(len(lo), 2)
self.assertEqual(len(up), 2)
nc = data.getNumCells()
assert (isinstance(nc, np.ndarray))
assert (isinstance(nc[0], np.int64))
assert (isinstance(nc[1], np.int64))
self.assertEqual(nc[0], 64)
self.assertEqual(nc[1], 32)
grid = data.peakGrid()
assert (isinstance(grid, list))
self.assertEqual(len(grid), 2)
assert (isinstance(grid[0], np.ndarray))
assert (isinstance(grid[1], np.ndarray))
self.assertEqual(grid[0].shape, (64, ))
self.assertEqual(grid[1].shape, (32, ))
values = data.peakValues()
assert (isinstance(values, np.ndarray))
self.assertEqual(values.shape, (64, 32, 8))
def test_LoadBpHistory(self):
data = pg.GData('data/hist_')
nd = data.getNumDims()
assert (isinstance(nd, int))
self.assertEqual(nd, 1)
nc = data.getNumComps()
assert (isinstance(nc, int))
self.assertEqual(nc, 8)
lo, up = data.getBounds()
assert (isinstance(lo, np.ndarray))
assert (isinstance(up, np.ndarray))
self.assertEqual(len(lo), 1)
self.assertEqual(len(up), 1)
nc = data.getNumCells()
assert (isinstance(nc, np.ndarray))
assert (isinstance(nc[0], np.int64))
self.assertEqual(nc[0], 7641)
grid = data.peakGrid()
assert (isinstance(grid, list))
self.assertEqual(len(grid), 1)
assert (isinstance(grid[0], np.ndarray))
self.assertEqual(grid[0].shape, (7641, ))
values = data.peakValues()
assert (isinstance(values, np.ndarray))
self.assertEqual(values.shape, (7641, 8))
def getGrid(dataFile, p, basisType, **opKey):
pgData = pg.GData(dataFile) #.Read data with pgkyl.
pgInterp = pg.GInterpModal(pgData, p, basisType) #.Interpolate data.
xNodal, dataInterp = pgInterp.interpolate()
dimOut = np.shape(xNodal)[0] #.Number of dimensions in data.
#.If desired, output cell center values of grid coordinates instead of nodal coordinates.
if 'location' in opKey:
if opKey['location'] == 'center':
xOut = [[] for i in range(dimOut)]
for i in range(dimOut):
nNodes = np.shape(xNodal[i])[0]
xOut[i] = np.zeros(nNodes - 1)
xOut[i] = np.multiply(
0.5, xNodal[i][0:nNodes - 1] + xNodal[i][1:nNodes])
else:
xOut = xNodal
else:
xOut = xNodal
nxOut = np.zeros(dimOut, dtype='int')
lxOut = np.zeros(dimOut, dtype='double')
dxOut = np.zeros(dimOut, dtype='double')
for i in range(dimOut):
nxOut[i] = np.size(xOut[i])
lxOut[i] = xOut[i][-1] - xOut[i][0]
dxOut[i] = xOut[i][1] - xOut[i][0]
return xOut, dimOut, nxOut, lxOut, dxOut
def getDist(pre, fr):
d = postgkyl.GData("%s-bi-maxwellian-relax_neut_%d.bp" % (pre, fr))
dg = postgkyl.GInterpModal(d, 2, "ms")
XX, fv = dg.interpolate()
X, V = meshgrid(XX[1], XX[2])
return X, V, fv
def plotFig(nr,nc,i,fr, showX=False):
print("Working on %d ..." % i)
data = pg.GData("s3-oscc-E_ions_%d.bp" % fr)
dg = pg.data.GInterpModal(data, 2, "ms")
XX, q = dg.interpolate()
tm = data.time
wx, wy = wR(tm)
qEx = fexact(wx, wy)
f = subplot(nr,nc,i)
pcolormesh(XX[1], XX[2], transpose(q[3,:,:,0]))
plot(WX, WY, 'w', linewidth=0.5)
if showX:
xlabel("$v_x$")
ylabel('$v_y$')
grid()
axis('image')
f = subplot(nr,nc,i+1)
pcolormesh(VX, VY, qEx)
plot(WX, WY, 'w', linewidth=0.5)
if showX:
xlabel("$v_x$")
grid()
axis('image')
def getInterpData(dataFile, p, basisType, **opKey):
pgData = pg.GData(dataFile) #.Read data with pgkyl.
pgInterp = pg.GInterpModal(pgData, p, basisType) #.Interpolate data.
if 'comp' in opKey:
xOut, dataOut = pgInterp.interpolate(opKey['comp'])
else:
xOut, dataOut = pgInterp.interpolate()
return dataOut
def plotP(p, fName):
for i in range(1, 11):
print("Woroking on %s_%d.bp ... " % (fName, i))
data = pg.GData("%s_%d.bp" % (fName, i))
T = data.peakGrid()
v = data.peakValues()
tp, vp = mkPoincare(T[0], v)
p.scatter(2 * pi * array(tp) / tper, array(vp), 0.1, marker='.')
def calcMomentumError(pre):
d = postgkyl.GData("%s-bi-maxwellian-relax_neut_intM1i_" % pre)
m1i = d.getValues()
t = d.getGrid()[0]
err1 = calcNormError(m1i[:, 0])
err2 = calcNormError(m1i[:, 1])
return t, err1, err2
def getEntropy(polyOrder, pre):
svals = zeros((100, ), float)
for i in range(0, 100):
d = postgkyl.GData("%s-relax_neut_%d.bp" % (pre, i))
dg = postgkyl.GInterpModal(d, polyOrder, "ms")
XX, fv = dg.interpolate()
svals[i] = calcEntropy(XX[0], XX[1], fv)
return svals
def plotFig(i, fr):
print("Working on %d ..." % i)
data = pg.GData("c4-oscc-E_ions_%d.bp" % fr)
dg = pg.data.GInterpModal(data, 2, "ms")
XX, q = dg.interpolate()
nx2 = int(q.shape[0] / 2)
nvx2 = int(q.shape[1] / 2)
return q[nx2, nvx2, :, 0]
def calcMomentumError(pre, p):
# Inputs:
# pre - prefix for file name.
# p - polynomial order (used for assisting in distinguishing between different prefixes).
# Outputs:
# t - array of time data.
# err - normalized error ( abs(err - err[0])/err[0] ) in the total momentum.
# Read in electron data.
d = postgkyl.GData("%s-conservation-test-%s_elc_intM1i.bp" % (pre, p))
elcM1i = elcMass * d.getValues()
# Read in proton data.
d = postgkyl.GData("%s-conservation-test-%s_ion_intM1i.bp" % (pre, p))
ionM1i = ionMass * d.getValues()
t = d.getGrid()[0]
err = calcNormError(elcM1i[:, 0] + ionM1i[:, 0])
return t, err
def plotFig(i,fr):
print("Working on %d ..." % i)
data = pg.GData("c5-oscc-E_ions_%d.bp" % fr)
dg = pg.data.GInterpModal(data, 2, "ms")
XX, q = dg.interpolate()
qsum = sum(q,axis=0)
nvx2 = int(q.shape[1]/2)
return qsum[nvx2,:].squeeze()
def plotFig(i, fr):
print("Working on %d ..." % i)
figure(i, figsize=(14, 8))
data_fieldEnergy = pg.GData("kink_fieldEnergy_")
t = data_fieldEnergy.getGrid()[0]
fieldEnergy = data_fieldEnergy.getValues()
ExEnergy = 0.5 * fieldEnergy[:, 0]
omegaCi = 0.0055277079839257
t = t * 0.0055277079839257
#param, R2, N = fitGrowth(t[40000:50000], ExEnergy[40000:50000])
subplot(1, 2, 1)
semilogy(t, ExEnergy, "k")
xlabel("$t (\Omega_{ci}^{-1})$")
ylabel("$\int E_x^2$")
xlim(0, 8)
ylim(1e-12, 1e-2)
data_field = pg.GData("kink_field_%d.bp" % fr)
dg_field = pg.data.GInterpModal(data_field, 2, "ms")
XX, Ex = dg_field.interpolate(0)
#center the grid values
for d in range(2):
XX[d] = 0.5 * (XX[d][:-1] + XX[d][1:])
#normalization for electric field
ionMass = 36
norm = (omegaCi * ionMass)**2 / math.sqrt(ionMass)
#computing ion larmor radius
vtIon = 0.0316227833333333
rhoi = vtIon / omegaCi
subplot(1, 2, 2)
pcolormesh(XX[0] / rhoi,
XX[1] / rhoi,
Ex[:, :, 0].transpose() / norm,
cmap="seismic",
shading="gouraud")
colorbar(label="$E_x$")
xlabel(r"$X(\rho_i)$")
ylabel(r"$Y(\rho_i)$")
title(r"$t=6 \Omega_{ci}^{-1}$")
tight_layout()
savefig("lhdi-ex-energy-and-ex.pdf")
def plotFig1D(i, lbl):
print("Working on %d ..." % i)
data = pg.GData("c6-oscc-E_ions_%d.bp" % i)
dg = pg.data.GInterpModal(data, 2, "ms")
XX, q = dg.interpolate()
numCells = q.shape
qSum = sum(q, axis=0)*(2.0*pi)/numCells[0]
plot(XX[1], qSum[:,int(numCells[2]/2),0], label=lbl)
grid()
def getExpRecon(pre, fr):
d = postgkyl.GData("%s-relax_neut_%d.bp" % (pre, fr))
q = d.getValues()
f0 = q[0, :, 0]
f1 = q[0, :, 2]
gcoeff = zeros((f0.shape[0], 2), float)
for i in range(f0.shape[0]):
gcoeff[i][0], gcoeff[i][1] = fitExp(f0[i], f1[i])
return gcoeff
def calcL2Error(pre, p):
# Inputs:
# pre - prefix for file name.
# p - polynomial order (used for assisting in distinguishing between different prefixes).
# Outputs:
# t - array of time data.
# err_elcL2 - normalized error ( abs(err - err[0])/err[0] ) in the electron L^2 norm (f_e^2).
# ion_elcL2 - normalized error ( abs(err - err[0])/err[0] ) in the proton L^2 norm (f_p^2).
# Read in electron data.
d = postgkyl.GData("%s-conservation-test-%s_elc_intL2.bp" % (pre, p))
elcL2 = d.getValues()
# Read in proton data.
d = postgkyl.GData("%s-conservation-test-%s_ion_intL2.bp" % (pre, p))
ionL2 = d.getValues()
t = d.getGrid()[0]
err_elcL2 = calcNormError(elcL2[:, 0])
err_ionL2 = calcNormError(ionL2[:, 0])
return t, err_elcL2, err_ionL2
def getPhi(fr):
data = pg.GData("n1-es-buneman_field_%d.bp" % fr)
dg = pg.data.GInterpModal(data, 2, "ms")
XX, E = dg.interpolate()
X1 = XX[0]
dx = X1[1] - X1[0]
phi = numpy.zeros((E.shape[0] + 1, 1), numpy.float)
for i in range(1, phi.shape[0]):
phi[i] = phi[i - 1] - dx * E[i - 1]
return phi - 0 * min(phi)
def plotFig(nr,nc,i,fr):
print("Working on %d ..." % i)
data = pg.GData("c6-oscc-E_ions_%d.bp" % fr)
dg = pg.data.GInterpModal(data, 2, "ms")
XX, q = dg.interpolate()
qSum = sum(q, axis=0)
subplot(nr,nc,i)
pcolormesh(XX[1], XX[2], transpose(qSum[:,:,0]))
grid()
axis('image')
def getData(i):
#print("Working on %d ..." % i)
data = pg.GData("s4-oscc-E_ions_%d.bp" % i)
dg = pg.data.GInterpModal(data, 2, "ms")
XX, q = dg.interpolate()
nx, nvx, nvy = q.shape[0], q.shape[1], q.shape[2]
qMid = q[int(nx/2),:,int(nvy/2)]
tm = data.time
tm = tm - tper*floor(tm/tper)
return tm, qMid
def plotFig(i):
print("Working on %d ..." % i)
data = pg.GData("c6-oscc-E_ions_M0_%d.bp" % i)
dg = pg.data.GInterpModal(data, 2, "ms")
XX, q0 = dg.interpolate()
data = pg.GData("c6-oscc-E_ions_M1i_%d.bp" % i)
dg = pg.data.GInterpModal(data, 2, "ms")
XX, nux = dg.interpolate(0)
XX, nuy = dg.interpolate(1)
ux = nux/q0
uy = nuy/q0
data = pg.GData("c6-oscc-E_ions_M2_%d.bp" % i)
dg = pg.data.GInterpModal(data, 2, "ms")
XX, q2 = dg.interpolate()
dx = 1/q2.shape[0]
vt = (q2-q0*(ux**2+uy**2))*0.5
return dx*vt.sum()
