625 lines
20 KiB
Python
625 lines
20 KiB
Python
"""
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================================================================================
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This file is part of the AMUN source code, a program to perform
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Newtonian or relativistic magnetohydrodynamical simulations on uniform or
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adaptive mesh.
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Copyright (C) 2018-2019 Grzegorz Kowal <grzegorz@amuncode.org>
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This program is free software: you can redistribute it and/or modify
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it under the terms of the GNU General Public License as published by
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the Free Software Foundation, either version 3 of the License, or
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(at your option) any later version.
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This program is distributed in the hope that it will be useful,
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but WITHOUT ANY WARRANTY; without even the implied warranty of
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MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
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GNU General Public License for more details.
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You should have received a copy of the GNU General Public License
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along with this program. If not, see <http://www.gnu.org/licenses/>.
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================================================================================
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module: AMUN
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Python module with subroutines to read AMUN code HDF5 files.
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The only requirements for this module are:
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- h5py
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- numpy
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--------------------------------------------------------------------------------
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"""
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import h5py as h5
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import numpy as np
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import os.path as op
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import sys
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def amun_compatible(fname):
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'''
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Subroutine checks if the HDF5 file is AMUN compatible.
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Arguments:
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fname - the HDF5 file name;
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Return values:
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ret - True or False;
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Examples:
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comp = amun_compatible('p000010_00000.h5')
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'''
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try:
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f = h5.File(fname, 'r')
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# check if the file is written in the AMUN format or at least contains
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# necessary groups
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#
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ret = True
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if 'code' in f.attrs:
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if f.attrs['code'].astype(str) != "AMUN":
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print("'%s' contains attribute 'code'", \
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" but it is not set to 'AMUN'!" % fname)
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ret = False
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elif not 'attributes' in f or \
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not 'coordinates' in f or \
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not 'variables' in f:
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print("'%s' misses one of these groups: ", \
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"'attributes', 'coordinates' or 'variables'!" % fname)
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ret = False
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f.close()
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except:
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print("It seems '%s' is not an HDF5 file!" % fname)
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ret = False
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return ret
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def amun_attribute(fname, aname):
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'''
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Subroutine to read global attributes from AMUN HDF5 snapshots.
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Arguments:
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fname - the HDF5 file name;
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aname - the attribute name;
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Return values:
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ret - the value of the attribute;
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Examples:
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time = amun_attribute('p000010_00000.h5', 'time')
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'''
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if not amun_compatible(fname):
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return False
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try:
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f = h5.File(fname, 'r')
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g = f['attributes']
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if aname in g.attrs:
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attr = g.attrs[aname]
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if attr.dtype.type is np.string_:
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ret = np.squeeze(attr).astype(str)
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else:
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ret = np.squeeze(attr)
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else:
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print("Attribute '%s' cannot be retrieved from '%s'!" % (aname, fname))
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ret = False
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f.close()
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except:
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print("Attribute '%s' cannot be retrieved from '%s'!" % (aname, fname))
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ret = False
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return ret
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def amun_coordinate(fname, iname):
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'''
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Subroutine to read coordinate items from AMUN HDF5 snapshots.
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Arguments:
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fname - the HDF5 file name;
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iname - the item name;
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Return values:
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ret - the values of the item;
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Examples:
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bounds = amun_coordinate('p000010_00000.h5', 'bounds')
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'''
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if not amun_compatible(fname):
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return False
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try:
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f = h5.File(fname, 'r')
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g = f['coordinates']
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if iname in g:
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item = g[iname]
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if item.dtype.type is np.string_:
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ret = np.squeeze(item).astype(str)
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else:
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ret = np.squeeze(item)
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else:
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print("Coordinate item '%s' cannot be retrieved from '%s'!" % (iname, fname))
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ret = False
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f.close()
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except:
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print("Coordinate item '%s' cannot be retrieved from '%s'!" % (iname, fname))
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ret = False
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return ret
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def amun_dataset(fname, vname, shrink = 1, progress = False):
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'''
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Subroutine to read datasets from AMUN HDF5 snapshots.
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Arguments:
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fname - the HDF5 file name;
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vname - the variable name;
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shrink - the shrink factor (must be the power of 2 and not larger
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than the block size);
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progress - the progress bar switch;
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Return values:
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ret - the array of values for the variable;
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Examples:
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dn = amun_dataset('p000010_00000.h5', 'dens')
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'''
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if not amun_compatible(fname):
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return False
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try:
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dname = op.dirname(fname)
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if progress:
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sys.stdout.write("Data file path:\n '%s'\n" % (dname))
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# get attributes necessary to reconstruct the domain
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#
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eqsys = amun_attribute(fname, 'eqsys')
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eos = amun_attribute(fname, 'eos')
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nr = amun_attribute(fname, 'isnap')
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nc = amun_attribute(fname, 'nprocs')
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nl = amun_attribute(fname, 'nleafs')
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if eos == 'adi':
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gm = amun_attribute(fname, 'gamma')
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# prepare array to hold data
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#
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ndims = amun_attribute(fname, 'ndims')
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nn = amun_attribute(fname, 'ncells')
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bm = np.array([nn, nn, nn])
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if ndims == 2:
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bm[2] = 1
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ng = amun_attribute(fname, 'nghosts')
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ml = amun_attribute(fname, 'maxlev')
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f = h5.File(fname, 'r')
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if 'rdims' in f['attributes'].attrs:
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rm = amun_attribute(fname, 'rdims')
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elif 'bdims' in f['attributes'].attrs:
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rm = amun_attribute(fname, 'bdims')
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else:
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rm = amun_attribute(fname, 'domain_base_dims')
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f.close()
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# build the list of supported variables
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#
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variables = []
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f = h5.File(fname, 'r')
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for var in f['variables'].keys():
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variables.append(var)
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f.close()
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# add derived variables if possible
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#
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variables.append('level')
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if 'velx' in variables and 'vely' in variables and 'velz' in variables:
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variables.append('velo')
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variables.append('divv')
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variables.append('vort')
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if 'magx' in variables and 'magy' in variables and 'magz' in variables:
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variables.append('magn')
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variables.append('divb')
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variables.append('curr')
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if (eqsys == 'hd' or eqsys == 'mhd') and eos == 'adi' \
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and 'pres' in variables:
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variables.append('eint')
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if 'dens' in variables and 'pres' in variables:
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variables.append('temp')
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if (eqsys == 'hd' or eqsys == 'mhd') \
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and 'dens' in variables \
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and 'velx' in variables \
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and 'vely' in variables \
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and 'velz' in variables:
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variables.append('ekin')
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if (eqsys == 'mhd' or eqsys == 'srmhd') \
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and 'magx' in variables \
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and 'magy' in variables \
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and 'magz' in variables:
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variables.append('emag')
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if eqsys == 'hd' and 'ekin' in variables and 'eint' in variables:
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variables.append('etot')
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if eqsys == 'mhd' and 'eint' in variables \
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and 'ekin' in variables \
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and 'emag' in variables:
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variables.append('etot')
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if (eqsys == 'srhd' or eqsys == 'srmhd') and 'velo' in variables:
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variables.append('lore')
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# check if the requested variable is in the variable list
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#
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if not vname in variables:
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print('The requested variable cannot be extracted from the file datasets!')
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return False
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# check if the shrink parameter is correct (block dimensions should be
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# divisible by the shrink factor)
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#
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shrink = max(1, int(shrink))
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if shrink > 1:
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if (nn % shrink) != 0:
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print('The block dimension should be divisible by the shrink factor!')
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return False
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sh = shrink
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while(sh > 2 and sh % 2 == 0):
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sh = int(sh / 2)
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if (sh % 2) != 0:
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print('The shrink factor should be a power of 2!')
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return False
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# determine the actual maximum level from the blocks
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#
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ml = 0
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for n in range(nc):
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fname = 'p%06d_%05d.h5' % (nr, n)
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lname = op.join(dname, fname)
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dblocks = amun_attribute(lname, 'dblocks')
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if dblocks > 0:
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levels = amun_coordinate(lname, 'levels')
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ml = max(ml, levels.max())
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# prepare dimensions of the output array and allocate it
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#
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dm = np.array(rm[0:ndims] * bm[0:ndims] * 2**(ml - 1) / shrink, \
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dtype = np.int32)
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ret = np.zeros(dm[::-1])
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# iterate over all subdomain files
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#
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nb = 0
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for n in range(nc):
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fname = 'p%06d_%05d.h5' % (nr, n)
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lname = op.join(dname, fname)
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dblocks = amun_attribute(lname, 'dblocks')
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if dblocks > 0:
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levels = amun_coordinate(lname, 'levels')
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coords = amun_coordinate(lname, 'coords')
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dx = amun_coordinate(lname, 'dx')
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dy = amun_coordinate(lname, 'dy')
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dz = amun_coordinate(lname, 'dz')
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f = h5.File(lname, 'r')
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g = f['variables']
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if vname == 'level':
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dataset = np.zeros(g[variables[0]].shape)
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for l in range(dblocks):
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dataset[:,:,:,l] = levels[l]
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elif vname == 'velo':
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dataset = np.sqrt(g['velx'][:,:,:,:]**2 \
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+ g['vely'][:,:,:,:]**2 \
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+ g['velz'][:,:,:,:]**2)
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elif vname == 'magn':
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dataset = np.sqrt(g['magx'][:,:,:,:]**2 \
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+ g['magy'][:,:,:,:]**2 \
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+ g['magz'][:,:,:,:]**2)
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elif vname == 'eint':
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dataset = 1.0 / (gm - 1.0) * g['pres'][:,:,:,:]
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elif vname == 'ekin':
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dataset = 0.5 * g['dens'][:,:,:,:] * (g['velx'][:,:,:,:]**2 \
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+ g['vely'][:,:,:,:]**2 \
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+ g['velz'][:,:,:,:]**2)
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elif vname == 'emag':
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dataset = 0.5 * (g['magx'][:,:,:,:]**2 \
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+ g['magy'][:,:,:,:]**2 \
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+ g['magz'][:,:,:,:]**2)
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elif vname == 'etot':
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dataset = 1.0 / (gm - 1.0) * g['pres'][:,:,:,:] \
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+ 0.5 * g['dens'][:,:,:,:] * (g['velx'][:,:,:,:]**2 \
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+ g['vely'][:,:,:,:]**2 \
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+ g['velz'][:,:,:,:]**2)
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if eqsys == 'mhd':
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dataset += 0.5 * (g['magx'][:,:,:,:]**2 \
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+ g['magy'][:,:,:,:]**2 \
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+ g['magz'][:,:,:,:]**2)
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elif vname == 'temp':
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dataset = g['pres'][:,:,:,:] / g['dens'][:,:,:,:]
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elif vname == 'lore':
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dataset = 1.0 / np.sqrt(1.0 - (g['velx'][:,:,:,:]**2 \
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+ g['vely'][:,:,:,:]**2 \
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+ g['velz'][:,:,:,:]**2))
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elif vname == 'divv':
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dataset = np.zeros(g['velx'].shape)
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fields = [ 'velx', 'vely', 'velz' ]
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h = (dx, dy, dz)
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for i in range(ndims):
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v = fields[i]
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dataset += 0.5 * (np.roll(g[v][:,:,:,:], -1, axis = 2) \
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- np.roll(g[v][:,:,:,:], 1, axis = 2)) \
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/ h[i][levels[:] - 1]
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elif vname == 'divb':
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dataset = np.zeros(g['magx'].shape)
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fields = [ 'magx', 'magy', 'magz' ]
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h = (dx, dy, dz)
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for i in range(ndims):
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v = fields[i]
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dataset += 0.5 * (np.roll(g[v][:,:,:,:], -1, axis = 2) \
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- np.roll(g[v][:,:,:,:], 1, axis = 2)) \
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/ h[i][levels[:] - 1]
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elif vname == 'vort':
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if ndims == 3:
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wx = 0.5 * (np.roll(g['velz'][:,:,:,:], -1, axis = 1) \
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- np.roll(g['velz'][:,:,:,:], 1, axis = 1)) \
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/ dy[levels[:]-1] \
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- 0.5 * (np.roll(g['vely'][:,:,:,:], -1, axis = 0) \
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- np.roll(g['vely'][:,:,:,:], 1, axis = 0)) \
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/ dz[levels[:]-1]
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wy = 0.5 * (np.roll(g['velx'][:,:,:,:], -1, axis = 0) \
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- np.roll(g['velx'][:,:,:,:], 1, axis = 0)) \
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/ dz[levels[:]-1] \
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- 0.5 * (np.roll(g['velz'][:,:,:,:], -1, axis = 2) \
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- np.roll(g['velz'][:,:,:,:], 1, axis = 2)) \
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/ dx[levels[:]-1]
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wz = 0.5 * (np.roll(g['vely'][:,:,:,:], -1, axis = 2) \
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- np.roll(g['vely'][:,:,:,:], 1, axis = 2)) \
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/ dx[levels[:]-1] \
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- 0.5 * (np.roll(g['velx'][:,:,:,:], -1, axis = 1) \
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- np.roll(g['velx'][:,:,:,:], 1, axis = 1)) \
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/ dy[levels[:]-1]
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else:
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wx = 0.5 * (np.roll(g['velz'][:,:,:,:], -1, axis = 1) \
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- np.roll(g['velz'][:,:,:,:], 1, axis = 1)) \
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/ dy[levels[:]-1]
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wy = - 0.5 * (np.roll(g['velz'][:,:,:,:], -1, axis = 2) \
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- np.roll(g['velz'][:,:,:,:], 1, axis = 2)) \
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/ dx[levels[:]-1]
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wz = 0.5 * (np.roll(g['vely'][:,:,:,:], -1, axis = 2) \
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- np.roll(g['vely'][:,:,:,:], 1, axis = 2)) \
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/ dx[levels[:]-1] \
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- 0.5 * (np.roll(g['velx'][:,:,:,:], -1, axis = 1) \
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- np.roll(g['velx'][:,:,:,:], 1, axis = 1)) \
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/ dy[levels[:]-1]
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dataset = np.sqrt(wx * wx + wy * wy + wz * wz)
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elif vname == 'curr':
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if ndims == 3:
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wx = 0.5 * (np.roll(g['magz'][:,:,:,:], -1, axis = 1) \
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- np.roll(g['magz'][:,:,:,:], 1, axis = 1)) \
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/ dy[levels[:]-1] \
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- 0.5 * (np.roll(g['magy'][:,:,:,:], -1, axis = 0) \
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- np.roll(g['magy'][:,:,:,:], 1, axis = 0)) \
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/ dz[levels[:]-1]
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wy = 0.5 * (np.roll(g['magx'][:,:,:,:], -1, axis = 0) \
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- np.roll(g['magx'][:,:,:,:], 1, axis = 0)) \
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/ dz[levels[:]-1] \
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- 0.5 * (np.roll(g['magz'][:,:,:,:], -1, axis = 2) \
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- np.roll(g['magz'][:,:,:,:], 1, axis = 2)) \
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/ dx[levels[:]-1]
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wz = 0.5 * (np.roll(g['magy'][:,:,:,:], -1, axis = 2) \
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- np.roll(g['magy'][:,:,:,:], 1, axis = 2)) \
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/ dx[levels[:]-1] \
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- 0.5 * (np.roll(g['magx'][:,:,:,:], -1, axis = 1) \
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- np.roll(g['magx'][:,:,:,:], 1, axis = 1)) \
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/ dy[levels[:]-1]
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else:
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wx = 0.5 * (np.roll(g['magz'][:,:,:,:], -1, axis = 1) \
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- np.roll(g['magz'][:,:,:,:], 1, axis = 1)) \
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/ dy[levels[:]-1]
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wy = - 0.5 * (np.roll(g['magz'][:,:,:,:], -1, axis = 2) \
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- np.roll(g['magz'][:,:,:,:], 1, axis = 2)) \
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/ dx[levels[:]-1]
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wz = 0.5 * (np.roll(g['magy'][:,:,:,:], -1, axis = 2) \
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- np.roll(g['magy'][:,:,:,:], 1, axis = 2)) \
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/ dx[levels[:]-1] \
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- 0.5 * (np.roll(g['magx'][:,:,:,:], -1, axis = 1) \
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- np.roll(g['magx'][:,:,:,:], 1, axis = 1)) \
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/ dy[levels[:]-1]
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dataset = np.sqrt(wx * wx + wy * wy + wz * wz)
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else:
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dataset = g[vname][:,:,:,:]
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f.close()
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# rescale all blocks to the effective resolution
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#
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for l in range(dblocks):
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nn = 2**(ml - levels[l])
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cm = np.array(bm[0:ndims] * nn / shrink, dtype = np.int32)
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ibeg = coords[0:ndims,l] * cm[0:ndims]
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iend = ibeg + cm[0:ndims]
|
|
if ndims == 3:
|
|
ib, jb, kb = ibeg[0], ibeg[1], ibeg[2]
|
|
ie, je, ke = iend[0], iend[1], iend[2]
|
|
ret[kb:ke,jb:je,ib:ie] = rebin(dataset[ng:-ng,ng:-ng,ng:-ng,l], cm)
|
|
else:
|
|
ib, jb = ibeg[0], ibeg[1]
|
|
ie, je = iend[0], iend[1]
|
|
ret[jb:je,ib:ie] = rebin(dataset[ 0,ng:-ng,ng:-ng,l], cm)
|
|
|
|
nb += 1
|
|
|
|
# print progress bar if desired
|
|
#
|
|
if progress:
|
|
sys.stdout.write('\r')
|
|
sys.stdout.write("Reading '%s' from '%s': block %d from %d" \
|
|
% (vname, fname, nb, nl))
|
|
sys.stdout.flush()
|
|
|
|
if (progress):
|
|
sys.stdout.write('\n')
|
|
sys.stdout.flush()
|
|
|
|
except:
|
|
print("Dataset '%s' cannot be retrieved from '%s'!" % (vname, fname))
|
|
ret = False
|
|
|
|
return ret
|
|
|
|
|
|
def amun_integrals(field, filename, pathlist):
|
|
'''
|
|
get_integral: iterate over pathlist and read and merge field values from filename files in the provided paths
|
|
'''
|
|
# Initiate the return values with empty array and file number.
|
|
#
|
|
vals = np.array([])
|
|
num = 1
|
|
|
|
# Iterate over all paths provided in the list 'pathlist'.
|
|
#
|
|
for path in pathlist:
|
|
|
|
# Iterate over all files in the current path.
|
|
#
|
|
while True:
|
|
|
|
# Generate file name.
|
|
#
|
|
dfile = path + '/' + filename + '_' + str(num).zfill(2) + '.dat'
|
|
|
|
# Check if the file exists.
|
|
#
|
|
if op.isfile(dfile):
|
|
|
|
# Read values from the current integrals file.
|
|
#
|
|
lvals = read_integrals(dfile, field)
|
|
|
|
# Append to the return array.
|
|
#
|
|
vals = np.append(vals, lvals)
|
|
|
|
# Increase the number file.
|
|
#
|
|
num = num + 1
|
|
|
|
else:
|
|
|
|
# File does not exists, so go to the next path.
|
|
#
|
|
break
|
|
|
|
# Return appended values.
|
|
#
|
|
return vals
|
|
|
|
|
|
def read_integrals(filename, column):
|
|
'''
|
|
read_integrals: reads a given column from an integral file.
|
|
'''
|
|
# Open the given file and check if it is text file.
|
|
#
|
|
f = open(filename, 'r')
|
|
|
|
# Read fist line and store it in h, since it will be used to obtain the
|
|
# column headers.
|
|
#
|
|
l = f.readline()
|
|
h = l
|
|
|
|
# Read first line which is not comment in order to determine the number of
|
|
# columns and store the number of columns in nc. Calculate the column width
|
|
# and store it in wc.
|
|
#
|
|
while l.startswith('#'):
|
|
l = f.readline()
|
|
nc = len(l.rsplit())
|
|
wc = int((len(l) - 9) / (nc - 1))
|
|
|
|
# Split header line into a list.
|
|
#
|
|
lh = [h[1:9].strip()]
|
|
for i in range(nc - 1):
|
|
ib = i * wc + 10
|
|
ie = ib + wc - 1
|
|
lh.append(h[ib:ie].strip())
|
|
|
|
|
|
ic = lh.index(column)
|
|
|
|
# Read given column.
|
|
#
|
|
if (ic > -1):
|
|
lc = [float(l.split()[ic])]
|
|
for l in f:
|
|
lc.append(float(l.split()[ic]))
|
|
|
|
# Close the file.
|
|
#
|
|
f.close()
|
|
|
|
# Return values.
|
|
#
|
|
return(np.array(lc))
|
|
|
|
|
|
def rebin(a, newshape):
|
|
'''
|
|
Subroutine changes the size of the input array to to new shape,
|
|
by copying cells or averaging them.
|
|
'''
|
|
assert len(a.shape) == len(newshape)
|
|
|
|
m = a.ndim - 1
|
|
if (a.shape[m] > newshape[m]):
|
|
if a.ndim == 3:
|
|
nn = [newshape[0], int(a.shape[0] / newshape[0]),
|
|
newshape[1], int(a.shape[1] / newshape[1]),
|
|
newshape[2], int(a.shape[2] / newshape[2])]
|
|
return a.reshape(nn).mean(5).mean(3).mean(1)
|
|
else:
|
|
nn = [newshape[0], int(a.shape[0] / newshape[0]),
|
|
newshape[1], int(a.shape[1] / newshape[1])]
|
|
return a.reshape(nn).mean(3).mean(1)
|
|
else:
|
|
for n in range(a.ndim):
|
|
a = np.repeat(a, int(newshape[n] / a.shape[n]), axis = n)
|
|
return(a)
|
|
|
|
|
|
if __name__ == "__main__":
|
|
fname = './p000030_00000.h5'
|
|
|
|
ret = amun_attribute(fname, 'time')
|
|
print(ret)
|
|
ret = amun_attribute(fname, 'dims')
|
|
print(ret)
|
|
|
|
ret = amun_dataset(fname, 'dens')
|
|
print(ret.shape, ret.min(), ret.max())
|