def __init__(self, varfile='', datadir='data/', proc=-1, ivar=-1,
quiet=False, trimall=False, format='native',
param=None, dim=None, index=None, run2D=False,
magic=None, setup=None):
"""
Description:
-----------
Read VAR files from pencil code. if proc < 0, then load all data
and assemble. otherwise, load VAR file from specified processor.
format -- one of (['native', 'n'], ['ieee-le', 'l'],
['ieee-be', 'B']) for byte-ordering
Params:
------
varfile=''
datadir='data/'
proc=-1
ivar=-1
quiet=False
trimall=False
format='native'
param=None
dim=None
index=None
run2D=False
"""
if (setup is not None):
datadir=os.path.expanduser(setup.datadir)
dim=setup.dim
param=setup.param
index=setup.index
run2D=setup.run2D
else:
datadir = os.path.expanduser(datadir)
if dim is None:
dim = read_dim(datadir,proc)
if param is None:
param = read_param(datadir=datadir, quiet=quiet)
if index is None:
index = read_index(datadir=datadir)
if dim.precision == 'D':
precision = 'd'
else:
precision = 'f'
if param.lwrite_aux:
totalvars = dim.mvar+dim.maux
else:
totalvars = dim.mvar
# read index.pro to get positions and "names"
# of variables in f(mx,my,mz,nvar)
# Thomas: seems useless now ?
#exec(index) # this loads the indicies.
if (not varfile):
if ivar < 0:
varfile='var.dat'
else:
varfile='VAR'+str(ivar)
if proc < 0:
procdirs = natural_sort([s for s in os.listdir(datadir) if s.startswith('proc')])
else:
procdirs = ['proc'+str(proc)]
#global array
if (not run2D):
f = N.zeros((totalvars, dim.mz, dim.my, dim.mx),
dtype=precision)
else:
if dim.ny == 1:
f = N.zeros((totalvars, dim.mz, dim.mx), dtype=precision)
else:
f = N.zeros((totalvars, dim.my, dim.mx), dtype=precision)
x = N.zeros(dim.mx, dtype=precision)
y = N.zeros(dim.my, dtype=precision)
z = N.zeros(dim.mz, dtype=precision)
for directory in procdirs:
proc = int(directory[4:])
procdim = read_dim(datadir, proc)
if (not quiet):
print(("reading data from processor %i of %i ..." \
% (proc, len(procdirs))))
mxloc = procdim.mx
myloc = procdim.my
mzloc = procdim.mz
#read data
filename = os.path.join(datadir,directory,varfile)
infile = npfile(filename, endian=format)
if (not run2D):
f_loc = infile.fort_read(precision,
shape=(-1, mzloc, myloc, mxloc))
else:
if dim.ny == 1:
f_loc = infile.fort_read(precision,
shape=(-1, mzloc, mxloc))
else:
f_loc = infile.fort_read(precision,
shape=(-1, myloc, mxloc))
raw_etc = infile.fort_read(precision)
infile.close()
t = raw_etc[0]
x_loc = raw_etc[1:mxloc+1]
y_loc = raw_etc[mxloc+1:mxloc+myloc+1]
z_loc = raw_etc[mxloc+myloc+1:mxloc+myloc+mzloc+1]
if (param.lshear):
shear_offset = 1
deltay = raw_etc[-1]
else:
shear_offset = 0
dx = raw_etc[-3-shear_offset]
dy = raw_etc[-2-shear_offset]
dz = raw_etc[-1-shear_offset]
if len(procdirs) > 1:
# calculate where the local processor will go in
# the global array
#
# Don't overwrite ghost zones of processor to the left (and
# accordingly in y and z direction--makes a difference on the
# diagonals)
#
# recall that in NumPy, slicing is NON-INCLUSIVE on the right end
# ie, x[0:4] will slice all of a 4-digit array, not produce
# an error like in idl.
if procdim.ipx == 0:
i0x = 0
i1x = i0x+procdim.mx
i0xloc = 0
i1xloc = procdim.mx
else:
i0x = procdim.ipx*procdim.nx+procdim.nghostx
i1x = i0x+procdim.mx-procdim.nghostx
i0xloc = procdim.nghostx
i1xloc = procdim.mx
if procdim.ipy == 0:
i0y = 0
i1y = i0y+procdim.my
i0yloc = 0
i1yloc = procdim.my
else:
i0y = procdim.ipy*procdim.ny+procdim.nghosty
i1y = i0y+procdim.my-procdim.nghosty
i0yloc = procdim.nghosty
i1yloc = procdim.my
if procdim.ipz == 0:
i0z = 0
i1z = i0z+procdim.mz
i0zloc = 0
i1zloc = procdim.mz
else:
i0z = procdim.ipz*procdim.nz+procdim.nghostz
i1z = i0z+procdim.mz-procdim.nghostz
i0zloc = procdim.nghostz
i1zloc = procdim.mz
x[i0x:i1x] = x_loc[i0xloc:i1xloc]
y[i0y:i1y] = y_loc[i0yloc:i1yloc]
z[i0z:i1z] = z_loc[i0zloc:i1zloc]
if (not run2D):
f[:, i0z:i1z, i0y:i1y, i0x:i1x] = \
f_loc[:, i0zloc:i1zloc, i0yloc:i1yloc, i0xloc:i1xloc]
else:
if dim.ny == 1:
f[:, i0z:i1z, i0x:i1x] = \
f_loc[:, i0zloc:i1zloc, i0xloc:i1xloc]
else:
f[:, i0y:i1y, i0x:i1x] = \
f_loc[:, i0yloc:i1yloc, i0xloc:i1xloc]
else:
f = f_loc
x = x_loc
y = y_loc
z = z_loc
#endif MPI run
#endfor directories loop
if (magic is not None):
if ('bb' in magic):
# compute the magnetic field before doing trimall
aa = f[index['ax']-1:index['az'],...]
self.bb = curl(aa,dx,dy,dz,run2D=param.lwrite_2d)
if (trimall): self.bb=self.bb[:, dim.n1:dim.n2+1,
dim.m1:dim.m2+1, dim.l1:dim.l2+1]
if ('jj' in magic):
# compute the electric current field before doing trimall
aa = f[index['ax']-1:index['az'],...]
self.jj = curl2(aa,dx,dy,dz)
if (trimall): self.jj=self.jj[:, dim.n1:dim.n2+1,
dim.m1:dim.m2+1, dim.l1:dim.l2+1]
if ('vort' in magic):
# compute the vorticity field before doing trimall
uu = f[index['ux']-1:index['uz'],...]
self.vort = curl(uu,dx,dy,dz,run2D=param.lwrite_2d)
if (trimall):
if (param.lwrite_2d):
if (dim.nz == 1):
self.vort=self.vort[:, dim.m1:dim.m2+1,
dim.l1:dim.l2+1]
else:
self.vort=self.vort[:, dim.n1:dim.n2+1,
dim.l1:dim.l2+1]
else:
self.vort=self.vort[:, dim.n1:dim.n2+1,
dim.m1:dim.m2+1, dim.l1:dim.l2+1]
# trim the ghost zones of the global f-array if asked
if trimall:
self.x = x[dim.l1:dim.l2+1]
self.y = y[dim.m1:dim.m2+1]
self.z = z[dim.n1:dim.n2+1]
if (not run2D):
self.f = f[:, dim.n1:dim.n2+1, dim.m1:dim.m2+1, dim.l1:dim.l2+1]
else:
if dim.ny == 1:
self.f = f[:, dim.n1:dim.n2+1, dim.l1:dim.l2+1]
else:
self.f = f[:, dim.m1:dim.m2+1, dim.l1:dim.l2+1]
else:
self.x = x
self.y = y
self.z = z
self.f = f
self.l1 = dim.l1
self.l2 = dim.l2+1
self.m1 = dim.m1
self.m2 = dim.m2+1
self.n1 = dim.n1
self.n2 = dim.n2+1
# Assign an attribute to self for each variable defined in
# 'data/index.pro' so that e.g. self.ux is the x-velocity
for key,value in list(index.items()):
# print key,value
if key != 'global_gg':
setattr(self,key,self.f[value-1,...])
# Special treatment for vector quantities
if 'uu' in index:
self.uu = self.f[index['ux']-1:index['uz'],...]
if 'aa' in index:
self.aa = self.f[index['ax']-1:index['az'],...]
self.t = t
self.dx = dx
self.dy = dy
self.dz = dz
if param.lshear:
self.deltay = deltay
# do the rest of magic after the trimall (i.e. no additional curl...)
self.magic = magic
if self.magic is not None:
self.magicAttributes(param)
def __init__(self,
varfile='',
datadir='data/',
proc=-1,
ivar=-1,
quiet=False,
trimall=False,
format='native',
param=None,
dim=None,
index=None,
run2D=False,
magic=None,
setup=None):
"""
Description:
-----------
Read VAR files from pencil code. if proc < 0, then load all data
and assemble. otherwise, load VAR file from specified processor.
format -- one of (['native', 'n'], ['ieee-le', 'l'],
['ieee-be', 'B']) for byte-ordering
Params:
------
varfile=''
datadir='data/'
proc=-1
ivar=-1
quiet=False
trimall=False
format='native'
param=None
dim=None
index=None
run2D=False
"""
if (setup is not None):
datadir = os.path.expanduser(setup.datadir)
dim = setup.dim
param = setup.param
index = setup.index
run2D = setup.run2D
else:
datadir = os.path.expanduser(datadir)
if dim is None:
dim = read_dim(datadir, proc)
if param is None:
param = read_param(datadir=datadir, quiet=quiet)
if index is None:
index = read_index(datadir=datadir)
if dim.precision == 'D':
precision = 'd'
else:
precision = 'f'
if param.lwrite_aux:
totalvars = dim.mvar + dim.maux
else:
totalvars = dim.mvar
# read index.pro to get positions and "names"
# of variables in f(mx,my,mz,nvar)
# Thomas: seems useless now ?
#exec(index) # this loads the indicies.
if (not varfile):
if ivar < 0:
varfile = 'var.dat'
else:
varfile = 'VAR' + str(ivar)
if proc < 0:
procdirs = natural_sort(
filter(lambda s: s.startswith('proc'), os.listdir(datadir)))
else:
procdirs = ['proc' + str(proc)]
#global array
if (not run2D):
f = N.zeros((totalvars, dim.mz, dim.my, dim.mx), dtype=precision)
else:
if dim.ny == 1:
f = N.zeros((totalvars, dim.mz, dim.mx), dtype=precision)
else:
f = N.zeros((totalvars, dim.my, dim.mx), dtype=precision)
x = N.zeros(dim.mx, dtype=precision)
y = N.zeros(dim.my, dtype=precision)
z = N.zeros(dim.mz, dtype=precision)
for directory in procdirs:
proc = int(directory[4:])
procdim = read_dim(datadir, proc)
if (not quiet):
print "reading data from processor %i of %i ..." \
% (proc, len(procdirs))
mxloc = procdim.mx
myloc = procdim.my
mzloc = procdim.mz
#read data
filename = os.path.join(datadir, directory, varfile)
infile = npfile(filename, endian=format)
if (not run2D):
f_loc = infile.fort_read(precision,
shape=(-1, mzloc, myloc, mxloc))
else:
if dim.ny == 1:
f_loc = infile.fort_read(precision,
shape=(-1, mzloc, mxloc))
else:
f_loc = infile.fort_read(precision,
shape=(-1, myloc, mxloc))
raw_etc = infile.fort_read(precision)
infile.close()
t = raw_etc[0]
x_loc = raw_etc[1:mxloc + 1]
y_loc = raw_etc[mxloc + 1:mxloc + myloc + 1]
z_loc = raw_etc[mxloc + myloc + 1:mxloc + myloc + mzloc + 1]
if (param.lshear):
shear_offset = 1
deltay = raw_etc[-1]
else:
shear_offset = 0
dx = raw_etc[-3 - shear_offset]
dy = raw_etc[-2 - shear_offset]
dz = raw_etc[-1 - shear_offset]
if len(procdirs) > 1:
# calculate where the local processor will go in
# the global array
#
# Don't overwrite ghost zones of processor to the left (and
# accordingly in y and z direction--makes a difference on the
# diagonals)
#
# recall that in NumPy, slicing is NON-INCLUSIVE on the right end
# ie, x[0:4] will slice all of a 4-digit array, not produce
# an error like in idl.
if procdim.ipx == 0:
i0x = 0
i1x = i0x + procdim.mx
i0xloc = 0
i1xloc = procdim.mx
else:
i0x = procdim.ipx * procdim.nx + procdim.nghostx
i1x = i0x + procdim.mx - procdim.nghostx
i0xloc = procdim.nghostx
i1xloc = procdim.mx
if procdim.ipy == 0:
i0y = 0
i1y = i0y + procdim.my
i0yloc = 0
i1yloc = procdim.my
else:
i0y = procdim.ipy * procdim.ny + procdim.nghosty
i1y = i0y + procdim.my - procdim.nghosty
i0yloc = procdim.nghosty
i1yloc = procdim.my
if procdim.ipz == 0:
i0z = 0
i1z = i0z + procdim.mz
i0zloc = 0
i1zloc = procdim.mz
else:
i0z = procdim.ipz * procdim.nz + procdim.nghostz
i1z = i0z + procdim.mz - procdim.nghostz
i0zloc = procdim.nghostz
i1zloc = procdim.mz
x[i0x:i1x] = x_loc[i0xloc:i1xloc]
y[i0y:i1y] = y_loc[i0yloc:i1yloc]
z[i0z:i1z] = z_loc[i0zloc:i1zloc]
if (not run2D):
f[:, i0z:i1z, i0y:i1y, i0x:i1x] = \
f_loc[:, i0zloc:i1zloc, i0yloc:i1yloc, i0xloc:i1xloc]
else:
if dim.ny == 1:
f[:, i0z:i1z, i0x:i1x] = \
f_loc[:, i0zloc:i1zloc, i0xloc:i1xloc]
else:
f[:, i0y:i1y, i0x:i1x] = \
f_loc[:, i0yloc:i1yloc, i0xloc:i1xloc]
else:
f = f_loc
x = x_loc
y = y_loc
z = z_loc
#endif MPI run
#endfor directories loop
if (magic is not None):
if ('bb' in magic):
# compute the magnetic field before doing trimall
aa = f[index['ax'] - 1:index['az'], ...]
self.bb = curl(aa, dx, dy, dz, run2D=param.lwrite_2d)
if (trimall):
self.bb = self.bb[:, dim.n1:dim.n2 + 1, dim.m1:dim.m2 + 1,
dim.l1:dim.l2 + 1]
if ('jj' in magic):
# compute the electric current field before doing trimall
aa = f[index['ax'] - 1:index['az'], ...]
self.jj = curl2(aa, dx, dy, dz)
if (trimall):
self.jj = self.jj[:, dim.n1:dim.n2 + 1, dim.m1:dim.m2 + 1,
dim.l1:dim.l2 + 1]
if ('vort' in magic):
# compute the vorticity field before doing trimall
uu = f[index['ux'] - 1:index['uz'], ...]
self.vort = curl(uu, dx, dy, dz, run2D=param.lwrite_2d)
if (trimall):
if (param.lwrite_2d):
if (dim.nz == 1):
self.vort = self.vort[:, dim.m1:dim.m2 + 1,
dim.l1:dim.l2 + 1]
else:
self.vort = self.vort[:, dim.n1:dim.n2 + 1,
dim.l1:dim.l2 + 1]
else:
self.vort = self.vort[:, dim.n1:dim.n2 + 1,
dim.m1:dim.m2 + 1,
dim.l1:dim.l2 + 1]
# trim the ghost zones of the global f-array if asked
if trimall:
self.x = x[dim.l1:dim.l2 + 1]
self.y = y[dim.m1:dim.m2 + 1]
self.z = z[dim.n1:dim.n2 + 1]
if (not run2D):
self.f = f[:, dim.n1:dim.n2 + 1, dim.m1:dim.m2 + 1,
dim.l1:dim.l2 + 1]
else:
if dim.ny == 1:
self.f = f[:, dim.n1:dim.n2 + 1, dim.l1:dim.l2 + 1]
else:
self.f = f[:, dim.m1:dim.m2 + 1, dim.l1:dim.l2 + 1]
else:
self.x = x
self.y = y
self.z = z
self.f = f
self.l1 = dim.l1
self.l2 = dim.l2 + 1
self.m1 = dim.m1
self.m2 = dim.m2 + 1
self.n1 = dim.n1
self.n2 = dim.n2 + 1
# Assign an attribute to self for each variable defined in
# 'data/index.pro' so that e.g. self.ux is the x-velocity
for key, value in index.items():
# print key,value
if key != 'global_gg':
setattr(self, key, self.f[value - 1, ...])
# Special treatment for vector quantities
if index.has_key('uu'):
self.uu = self.f[index['ux'] - 1:index['uz'], ...]
if index.has_key('aa'):
self.aa = self.f[index['ax'] - 1:index['az'], ...]
self.t = t
self.dx = dx
self.dy = dy
self.dz = dz
if param.lshear:
self.deltay = deltay
# do the rest of magic after the trimall (i.e. no additional curl...)
self.magic = magic
if self.magic is not None:
self.magicAttributes(param)
def read(self,
var_file='',
sim=None,
datadir='data',
proc=-1,
ivar=-1,
quiet=True,
trim_all=False,
trimall=False,
dim=None,
magic=None):
"""
Read VAR files from pencil code. If proc < 0, then load all data
and assemble. otherwise, load VAR file from specified processor.
The file format written by output() (and used, e.g. in var.dat)
consists of the followinig Fortran records:
1. data(mx, my, mz, nvar)
2. t(1), x(mx), y(my), z(mz), dx(1), dy(1), dz(1), deltay(1)
Here nvar denotes the number of slots, i.e. 1 for one scalar field, 3
for one vector field, 8 for var.dat in the case of MHD with entropy.
but, deltay(1) is only there if lshear is on! need to know parameters.
call signature:
read(var_file='', datadir='data/', proc=-1, ivar=-1,
quiet=True, trimall=False,
magic=None, sim=None)
Keyword arguments:
var_file: Name of the VAR file.
sim: Simulation sim object.
magic: Values to be computed from the data, e.g. B = curl(A).
trimall: Trim the data cube to exclude ghost zones.
quiet: Flag for switching off output.
datadir: Directory where the data is stored.
proc: Processor to be read. If -1 read all and assemble to one array.
ivar: Index of the VAR file, if var_file is not specified.
"""
import numpy as np
import os
from scipy.io import FortranFile
from pencilnew.math.derivatives import curl, curl2
from pencilnew import read
if sim is not None:
datadir = os.path.expanduser(sim.datadir)
dim = sim.dim
param = read.param(datadir=sim.datadir, quiet=True)
index = read.index(datadir=sim.datadir)
else:
datadir = os.path.expanduser(datadir)
if dim is None:
dim = read.dim(datadir, proc)
if param is None:
param = read.param(datadir=datadir, quiet=quiet)
if index is None:
index = read.index(datadir=datadir)
run2D = param.lwrite_2d
if dim.precision == 'D':
precision = 'd'
else:
precision = 'f'
if param.lwrite_aux:
total_vars = dim.mvar + dim.maux
else:
total_vars = dim.mvar
if not var_file:
if ivar < 0:
var_file = 'var.dat'
else:
var_file = 'VAR' + str(ivar)
if proc < 0:
proc_dirs = self.__natural_sort(
filter(lambda s: s.startswith('proc'), os.listdir(datadir)))
else:
proc_dirs = ['proc' + str(proc)]
if trimall != False: trim_all = trimall
# Set up the global array.
if not run2D:
f = np.zeros((total_vars, dim.mz, dim.my, dim.mx), dtype=precision)
else:
if dim.ny == 1:
f = np.zeros((total_vars, dim.mz, dim.mx), dtype=precision)
else:
f = np.zeros((total_vars, dim.my, dim.mx), dtype=precision)
x = np.zeros(dim.mx, dtype=precision)
y = np.zeros(dim.my, dtype=precision)
z = np.zeros(dim.mz, dtype=precision)
for directory in proc_dirs:
proc = int(directory[4:])
procdim = read.dim(datadir, proc)
if not quiet:
print("Reading data from processor {0} of {1} ...".format( \
proc, len(proc_dirs)))
mxloc = procdim.mx
myloc = procdim.my
mzloc = procdim.mz
# Read the data.
file_name = os.path.join(datadir, directory, var_file)
infile = FortranFile(file_name)
if not run2D:
f_loc = infile.read_record(dtype=precision)
f_loc = f_loc.reshape((-1, mzloc, myloc, mxloc))
else:
if dim.ny == 1:
f_loc = infile.read_record(dtype=precision)
f_loc = f_loc.reshape((-1, mzloc, mxloc))
else:
f_loc = infile.read_record(dtype=precision)
f_loc = f_loc.reshape((-1, myloc, mxloc))
raw_etc = infile.read_record(precision)
infile.close()
t = raw_etc[0]
x_loc = raw_etc[1:mxloc + 1]
y_loc = raw_etc[mxloc + 1:mxloc + myloc + 1]
z_loc = raw_etc[mxloc + myloc + 1:mxloc + myloc + mzloc + 1]
if param.lshear:
shear_offset = 1
deltay = raw_etc[-1]
else:
shear_offset = 0
dx = raw_etc[-3 - shear_offset]
dy = raw_etc[-2 - shear_offset]
dz = raw_etc[-1 - shear_offset]
if len(proc_dirs) > 1:
# Calculate where the local processor will go in
# the global array.
#
# Don't overwrite ghost zones of processor to the left (and
# accordingly in y and z direction -- makes a difference on the
# diagonals)
#
# Recall that in NumPy, slicing is NON-INCLUSIVE on the right end
# ie, x[0:4] will slice all of a 4-digit array, not produce
# an error like in idl.
if procdim.ipx == 0:
i0x = 0
i1x = i0x + procdim.mx
i0xloc = 0
i1xloc = procdim.mx
else:
i0x = procdim.ipx * procdim.nx + procdim.nghostx
i1x = i0x + procdim.mx - procdim.nghostx
i0xloc = procdim.nghostx
i1xloc = procdim.mx
if procdim.ipy == 0:
i0y = 0
i1y = i0y + procdim.my
i0yloc = 0
i1yloc = procdim.my
else:
i0y = procdim.ipy * procdim.ny + procdim.nghosty
i1y = i0y + procdim.my - procdim.nghosty
i0yloc = procdim.nghosty
i1yloc = procdim.my
if procdim.ipz == 0:
i0z = 0
i1z = i0z + procdim.mz
i0zloc = 0
i1zloc = procdim.mz
else:
i0z = procdim.ipz * procdim.nz + procdim.nghostz
i1z = i0z + procdim.mz - procdim.nghostz
i0zloc = procdim.nghostz
i1zloc = procdim.mz
x[i0x:i1x] = x_loc[i0xloc:i1xloc]
y[i0y:i1y] = y_loc[i0yloc:i1yloc]
z[i0z:i1z] = z_loc[i0zloc:i1zloc]
if not run2D:
f[:, i0z:i1z, i0y:i1y, i0x:i1x] = \
f_loc[:, i0zloc:i1zloc, i0yloc:i1yloc, i0xloc:i1xloc]
else:
if dim.ny == 1:
f[:, i0z:i1z, i0x:i1x] = \
f_loc[:, i0zloc:i1zloc, i0xloc:i1xloc]
else:
f[:, i0y:i1y, i0x:i1x] = \
f_loc[:, i0yloc:i1yloc, i0xloc:i1xloc]
else:
f = f_loc
x = x_loc
y = y_loc
z = z_loc
if magic is not None:
if 'bb' in magic:
# Compute the magnetic field before doing trim_all.
aa = f[index.ax - 1:index.az, ...]
self.bb = curl(aa, dx, dy, dz, run2D=run2D)
if trim_all:
self.bb = self.bb[:, dim.n1:dim.n2 + 1, dim.m1:dim.m2 + 1,
dim.l1:dim.l2 + 1]
if 'jj' in magic:
# Compute the electric current field before doing trim_all.
aa = f[index.ax - 1:index.az, ...]
self.jj = curl2(aa, dx, dy, dz)
if trim_all:
self.jj = self.jj[:, dim.n1:dim.n2 + 1, dim.m1:dim.m2 + 1,
dim.l1:dim.l2 + 1]
if 'vort' in magic:
# Compute the vorticity field before doing trim_all.
uu = f[index.ux - 1:index.uz, ...]
self.vort = curl(uu, dx, dy, dz, run2D=run2D)
if trim_all:
if run2D:
if dim.nz == 1:
self.vort = self.vort[:, dim.m1:dim.m2 + 1,
dim.l1:dim.l2 + 1]
else:
self.vort = self.vort[:, dim.n1:dim.n2 + 1,
dim.l1:dim.l2 + 1]
else:
self.vort = self.vort[:, dim.n1:dim.n2 + 1,
dim.m1:dim.m2 + 1,
dim.l1:dim.l2 + 1]
# Trim the ghost zones of the global f-array if asked.
if trim_all:
self.x = x[dim.l1:dim.l2 + 1]
self.y = y[dim.m1:dim.m2 + 1]
self.z = z[dim.n1:dim.n2 + 1]
if not run2D:
self.f = f[:, dim.n1:dim.n2 + 1, dim.m1:dim.m2 + 1,
dim.l1:dim.l2 + 1]
else:
if dim.ny == 1:
self.f = f[:, dim.n1:dim.n2 + 1, dim.l1:dim.l2 + 1]
else:
self.f = f[:, dim.m1:dim.m2 + 1, dim.l1:dim.l2 + 1]
else:
self.x = x
self.y = y
self.z = z
self.f = f
self.l1 = dim.l1
self.l2 = dim.l2 + 1
self.m1 = dim.m1
self.m2 = dim.m2 + 1
self.n1 = dim.n1
self.n2 = dim.n2 + 1
# Assign an attribute to self for each variable defined in
# 'data/index.pro' so that e.g. self.ux is the x-velocity
for key in index.__dict__.keys():
if key != 'global_gg' and key != 'keys':
value = index.__dict__[key]
setattr(self, key, self.f[value - 1, ...])
# Special treatment for vector quantities.
if hasattr(index, 'uu'):
self.uu = self.f[index.ux - 1:index.uz, ...]
if hasattr(index, 'aa'):
self.aa = self.f[index.ax - 1:index.az, ...]
self.t = t
self.dx = dx
self.dy = dy
self.dz = dz
if param.lshear:
self.deltay = deltay
# Do the rest of magic after the trim_all (i.e. no additional curl...).
self.magic = magic
if self.magic is not None:
self.magic_attributes(param)