def power2vtk(powerfiles=["power_mag.dat"], datadir="data/", destination="power", thickness=1):
"""
Convert power spectra from PencilCode format to vtk.
call signature::
power2vtk(powerfiles = ['power_mag.dat'],
datadir = 'data/', destination = 'power.vtk', thickness = 1):
Read the power spectra stored in the power*.dat files
and convert them into vtk format.
Write the result in *destination*.
Keyword arguments:
*powerfiles*:
The files containing the power spectra.
*datadir*:
Directory where the data is stored.
*destination*:
Destination file.
*thickness*:
Dimension in z-direction. Setting it 2 will create n*m*2 dimensional
array of data. This is useful in Paraview for visualizing the spectrum
in 3 dimensions. Note that this will simply double the amount of data.
"""
# this should correct for the case the user types only one variable
if len(powerfiles) > 0:
if len(powerfiles[0]) == 1:
powerfiles = [powerfiles]
# read the grid dimensions
grid = pc.read_grid(datadir=datadir, trim=True, quiet=True)
# leave k0 to 1 now, will fix this later
k0 = 1.0
# leave dk to 1 now, will fix this later
dk = 1.0
# open the destination file
fd = open(destination + ".vtk", "wb")
# read the first power spectrum
t, power = pc.read_power(datadir + powerfiles[0])
fd.write("# vtk DataFile Version 2.0\n")
fd.write("power spectra\n")
fd.write("BINARY\n")
fd.write("DATASET STRUCTURED_POINTS\n")
if thickness == 1:
fd.write("DIMENSIONS {0:9} {1:9} {2:9}\n".format(len(t), power.shape[1], 1))
else:
fd.write("DIMENSIONS {0:9} {1:9} {2:9}\n".format(len(t), power.shape[1], 2))
fd.write("ORIGIN {0:8.12} {1:8.12} {2:8.12}\n".format(float(t[0]), k0, 0.0))
fd.write("SPACING {0:8.12} {1:8.12} {2:8.12}\n".format(t[1] - t[0], dk, 1.0))
if thickness == 1:
fd.write("POINT_DATA {0:9}\n".format(power.shape[0] * power.shape[1]))
else:
fd.write("POINT_DATA {0:9}\n".format(power.shape[0] * power.shape[1] * 2))
for powfile in powerfiles:
# read the power spectrum
t, power = pc.read_power(datadir + powfile)
fd.write("SCALARS " + powfile[:-4] + " float\n")
fd.write("LOOKUP_TABLE default\n")
if thickness == 1:
for j in range(power.shape[1]):
for i in range(len(t)):
fd.write(struct.pack(">f", power[i, j]))
else:
for k in [1, 2]:
for j in range(power.shape[1]):
for i in range(len(t)):
fd.write(struct.pack(">f", power[i, j]))
fd.close()
def lo_pass(self, kthresh):
pass
def filter_field(self, k, dk=1.):
shell = self.get_shell(k)
hat = (self.fft).copy()
hat[~shell] = 0
return (self._ifftn(hat, **self._extra_fft_args)).real
if __name__ == "__main__":
import pencil as pc
import pylab as P
import os
import pickle
from .utils import pc_en_spec
datadir = os.path.expanduser(
'~/vc/pencil-code/samples/helical-MHDturb/data/')
t, pcpow = pc.read_power('power_kin.dat', datadir=datadir)
var = pc.read_var(datadir=datadir)
power2 = 0.5 * abs(
fpack.fftn(pc.dot2(var.f[0:3, 3:-3, 3:-3, 3:-3])) /
var.f[0, 3:-3, 3:-3, 3:-3].size)
spec = pc_en_spec(var)
q = FourierFilter(power2)
spec2 = na.array([power2[q.get_shell(bin)].sum() for bin in range(q.nx)])
P.loglog(pcpow[-1, :], 'rx', markersize=10)
P.loglog(spec)
P.loglog(spec2)
P.show()
def power2vtk(powerfiles=['power_mag.dat'],
datadir='data/',
destination='power',
thickness=1):
"""
Convert power spectra from PencilCode format to vtk.
call signature::
power2vtk(powerfiles = ['power_mag.dat'],
datadir = 'data/', destination = 'power.vtk', thickness = 1):
Read the power spectra stored in the power*.dat files
and convert them into vtk format.
Write the result in *destination*.
Keyword arguments:
*powerfiles*:
The files containing the power spectra.
*datadir*:
Directory where the data is stored.
*destination*:
Destination file.
*thickness*:
Dimension in z-direction. Setting it 2 will create n*m*2 dimensional
array of data. This is useful in Paraview for visualizing the spectrum
in 3 dimensions. Note that this will simply double the amount of data.
"""
# this should correct for the case the user types only one variable
if (len(powerfiles) > 0):
if (len(powerfiles[0]) == 1):
powerfiles = [powerfiles]
# read the grid dimensions
grid = pc.read_grid(datadir=datadir, trim=True, quiet=True)
# leave k0 to 1 now, will fix this later
k0 = 1.
# leave dk to 1 now, will fix this later
dk = 1.
# open the destination file
fd = open(destination + '.vtk', 'wb')
# read the first power spectrum
t, power = pc.read_power(datadir + powerfiles[0])
fd.write('# vtk DataFile Version 2.0\n'.encode('utf-8'))
fd.write('power spectra\n'.encode('utf-8'))
fd.write('BINARY\n'.encode('utf-8'))
fd.write('DATASET STRUCTURED_POINTS\n'.encode('utf-8'))
if (thickness == 1):
fd.write('DIMENSIONS {0:9} {1:9} {2:9}\n'.format(
len(t), power.shape[1], 1).encode('utf-8'))
else:
fd.write('DIMENSIONS {0:9} {1:9} {2:9}\n'.format(
len(t), power.shape[1], 2).encode('utf-8'))
fd.write('ORIGIN {0:8.12} {1:8.12} {2:8.12}\n'.format(float(t[0]), k0,
0.).encode('utf-8'))
fd.write('SPACING {0:8.12} {1:8.12} {2:8.12}\n'.format(
t[1] - t[0], dk, 1.).encode('utf-8'))
if (thickness == 1):
fd.write('POINT_DATA {0:9}\n'.format(power.shape[0] *
power.shape[1]).encode('utf-8'))
else:
fd.write('POINT_DATA {0:9}\n'.format(power.shape[0] * power.shape[1] *
2).encode('utf-8'))
for powfile in powerfiles:
# read the power spectrum
t, power = pc.read_power(datadir + powfile)
fd.write(('SCALARS ' + powfile[:-4] + ' float\n').encode('utf-8'))
fd.write('LOOKUP_TABLE default\n'.encode('utf-8'))
if (thickness == 1):
for j in range(power.shape[1]):
for i in range(len(t)):
fd.write(struct.pack(">f", power[i, j]))
else:
for k in [1, 2]:
for j in range(power.shape[1]):
for i in range(len(t)):
fd.write(struct.pack(">f", power[i, j]))
fd.close()
def power2vtk(powerFiles = ['mag_spec.dat'], destination = 'spectra.vtk', mulz = 2):
"""
Convert slices from PencilCode format to vtk.
call signature::
power2vtk(specFiles = ['mag_spec'], destination = 'spectra.vtk')
Read the power files and convert their content into vtk format.
Write the result in *destination*.
NB: The z-dimension is used for the time.
Keyword arguments:
*powerFiles*:
The files containing the spectra. The files have to be in the 'data' directory.
*destination*:
Destination file.
*mulz*:
Multiplication of the data in z-direction.
Use mulz=2 if you want to do fancy animations in Paraview.
"""
# open the destination file for writing
fd = open(destination, 'wb')
# write the header
fd.write('# vtk DataFile Version 2.0\n')
fd.write('power spectra\n')
fd.write('BINARY\n')
# rad the first power spectrum
if (len(powerFiles[0]) > 1):
pfile = powerFiles[0]
else:
pfile = powerFiles
t, power = pc.read_power('data/'+pfile)
dimk = len(power[0,:])
dimt = len(t)
dt = t[1]-t[0]
fd.write('DATASET STRUCTURED_POINTS\n')
fd.write('DIMENSIONS {0:9} {1:9} {2:9}\n'.format(dimk, dimt, mulz))
fd.write('ORIGIN {0:8.12} {1:8.12} {2:8.12}\n'.format(0.0, 0.0, 0.0))
fd.write('SPACING {0:8.12} {1:8.12} {2:8.12}\n'.format(1.0, dt, 1.0))
fd.write('POINT_DATA {0:9}\n'.format(np.size(power)*mulz))
print 'writing ', pfile[:-4]
fd.write('SCALARS '+pfile[:-4]+' float\n')
fd.write('LOOKUP_TABLE default\n')
for k in range(mulz):
for j in range(dimt):
for i in range(dimk):
fd.write(struct.pack(">f", power[j,i]))
# run through all power files
if (len(powerFiles[0]) > 1):
for pfile in powerFiles[1:]:
t, power = pc.read_power('data/'+pfile)
print 'writing ', pfile[:-4]
fd.write('SCALARS '+pfile[:-4]+' float\n')
fd.write('LOOKUP_TABLE default\n')
for k in range(mulz):
for j in range(dimt):
for i in range(dimk):
fd.write(struct.pack(">f", power[j,i]))
fd.close()
for p, pb in enumerate(pb_ges[i]):
if p in plottimes:
#print('plotting',dd, p)
ax.loglog(krms, pb)
ax.set_xlim(1,dim.nxgrid//2)
ax.set_ylim(pb_ges[i][0,1], 1.5*pb_ges[i][0,:].max())
dirs = [d for d in listdir('.') if d.startswith('prandtl') and path.isdir(d)]
dirs = sorted(dirs, key=lambda a: float(a.split('_')[-1]))
print(dirs)
pb_ges = []
tb_ges = []
pr_numbers = {}
for dd in dirs:
tb, powerb = pc.read_power('power_mag.dat', datadir=dd)
pr_numeric = float(dd.split('_')[-1])
#print(nu_numeric)
pr_numbers[dd] = pr_numeric
pb_ges.append(powerb)
tb_ges.append(tb)
#print('tb_ges has : %i indices' % len(tb_ges))
dim = pc.read_dim(datadir=dirs[0])
krms = np.loadtxt(path.join(dirs[0],'power_krms.dat')).flatten()[:dim.nxgrid//2]
fig = plt.figure(figsize=fsize(.95))#figsize(width)
grid = Grid(fig, rect=[.08,.1,.9,.85], nrows_ncols=(2,2),
axes_pad=0., label_mode='L',
from helperfuncs import search_indx
from os import listdir, path
from scipy.optimize import curve_fit
try:
dim = pc.read_dim(datadir=dstart)
krms = np.loadtxt(path.join(dstart,'power_krms.dat')).flatten()[:dim.nxgrid//2]
print('krms shape: ', krms.shape)
p0 = (-12.92758524, 1.94666781, 3.4643292) #(-15.56, 2.20, 4.26)
except FileNotFoundError:
sys.exit(1)
#read in simulation parameters
dim = pc.read_dim(datadir=dstart)
pars = pc.read_param(datadir=dstart, quiet=True, param2=True)
xi = dim.nxgrid//2
t, powerb = pc.read_power('power_mag.dat', datadir=dstart)
print('t: ',t.shape, 'powerb: ',powerb.shape)
print('plotting at t = %g' % t[tfit])
# Simple plot setup
plotted = False
fig, ax = newfig(0.45, ratio=0.75)
#ax.set_xscale('log')
ax.set_yscale('log')
#ax.set_xlim(1,dim.nxgrid//2)
ax.set_xlim(10,50)
ax.set_ylim(round_exp(powerb[tfit,10]),1.5*max(powerb[tfit,:]))
#ax.set_ylim(1e-7, 1e-3)
clr = (0.9, 0.4, 0.4, 1.0)
for p,pb in enumerate(powerb):
try: