예제 #1
0
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()
예제 #2
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    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()
예제 #3
0
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()
예제 #4
0
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()
예제 #5
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    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',
예제 #6
0
파일: show_fit.py 프로젝트: belfhi/plotdata
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: