PYTHON: Split module into submodules.
Signed-off-by: Grzegorz Kowal <grzegorz@amuncode.org>
This commit is contained in:
parent
c1c68c3516
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@ -5,7 +5,7 @@ with open("README.md", "r", encoding="utf-8") as fh:
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setuptools.setup(
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name="amunpy",
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version="0.6",
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version="0.6.1",
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author="Grzegorz Kowal",
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author_email="grzegorz@amuncode.org",
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description="Python Interface for the AMUN code's snapshots",
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@ -0,0 +1,23 @@
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# -*- coding: utf-8 -*-
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"""
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Package AmunPy is the Python interface to handle datasets produced by
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the AMUN code (https://amuncode.org).
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The package is released under GNU General Public License v3.
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See file LICENSE for more details.
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"""
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from .amunxml import *
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from .amunh5 import *
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from .integrals import *
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__all__ = [ 'AmunXML', 'amun_attribute', 'amun_coordinate', 'amun_dataset', 'amun_integrals' ]
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__author__ = "Grzegorz Kowal"
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__copyright__ = "Copyright 2018-2021, Grzegorz Kowal <grzegorz@amuncode.org>"
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__version__ = "0.6.1"
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__maintainer__ = "Grzegorz Kowal"
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__email__ = "grzegorz@amuncode.org"
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455
python/amunpy/src/amunpy/amunh5.py
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455
python/amunpy/src/amunpy/amunh5.py
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@ -0,0 +1,455 @@
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"""
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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) 2018-2021 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 package are:
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- h5py
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- numpy
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--------------------------------------------------------------------------------
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"""
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from .interpolation import interpolate
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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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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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with h5.File(fname, 'r') as f:
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if 'codes' in f.attrs:
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if f.attrs['code'].astype(str) == "AMUN":
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return True
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else:
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print("'%s' contains attribute 'code'," % fname, \
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" but it is not 'AMUN'!")
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return False
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elif 'attributes' in f and 'coordinates' in f and \
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'variables' in f:
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return True
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else:
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print("'%s' misses one of these groups:" % fname, \
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"'attributes', 'coordinates' or 'variables'!")
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return False
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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 or None;
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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 None
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with h5.File(fname, 'r') as f:
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if aname in f['attributes'].attrs:
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attr = f['attributes'].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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return ret
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else:
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print("Attribute '%s' cannot be found in '%s'!" % (aname, fname))
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return None
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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 value of the item or None;
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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 None
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with h5.File(fname, 'r') as f:
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if iname in f['coordinates']:
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return np.array(f['coordinates'][iname])
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else:
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print("Coordinate item '%s' not found in group 'coordinate' of '%s'!" % (iname, fname))
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return None
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def amun_dataset(fname, vname, shrink=1, interpolation='rebin', 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 None
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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, 'adiabatic_index')
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# get block dimensions and the maximum level
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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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# get the base block dimensions
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#
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rm = amun_attribute(fname, 'bdims')
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if rm is None:
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rm = amun_attribute(fname, 'domain_base_dims')
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if rm is None:
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rm = amun_attribute(fname, 'rdims')
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if rm is None:
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return None
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# build the list of supported variables
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#
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variables = []
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with h5.File(fname, 'r') as f:
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for var in f['variables'].keys():
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variables.append(var)
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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 None
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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 None
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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 None
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# determine the actual maximum level from the blocks
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#
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levs = []
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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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levs = np.append(levs, [amun_coordinate(lname, 'levels')])
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ml = int(levs.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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with h5.File(lname, 'r') as f:
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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) \
|
||||
- np.roll(g['magy'][:,:,:,:], 1, axis=2)) \
|
||||
/ dx[levels[:]-1] \
|
||||
- 0.5 * (np.roll(g['magx'][:,:,:,:], -1, axis=1) \
|
||||
- np.roll(g['magx'][:,:,:,:], 1, axis=1)) \
|
||||
/ dy[levels[:]-1]
|
||||
else:
|
||||
wx = 0.5 * (np.roll(g['magz'][:,:,:,:], -1, axis=1) \
|
||||
- np.roll(g['magz'][:,:,:,:], 1, axis=1)) \
|
||||
/ dy[levels[:]-1]
|
||||
wy = - 0.5 * (np.roll(g['magz'][:,:,:,:], -1, axis=2) \
|
||||
- np.roll(g['magz'][:,:,:,:], 1, axis=2)) \
|
||||
/ dx[levels[:]-1]
|
||||
wz = 0.5 * (np.roll(g['magy'][:,:,:,:], -1, axis=2) \
|
||||
- np.roll(g['magy'][:,:,:,:], 1, axis=2)) \
|
||||
/ dx[levels[:]-1] \
|
||||
- 0.5 * (np.roll(g['magx'][:,:,:,:], -1, axis=1) \
|
||||
- np.roll(g['magx'][:,:,:,:], 1, axis=1)) \
|
||||
/ dy[levels[:]-1]
|
||||
dataset = np.sqrt(wx * wx + wy * wy + wz * wz)
|
||||
else:
|
||||
dataset = g[vname][:,:,:,:]
|
||||
|
||||
# rescale all blocks to the effective resolution
|
||||
#
|
||||
for l in range(dblocks):
|
||||
nn = 2**(ml - levels[l])
|
||||
if nn <= shrink:
|
||||
method = 'rebin'
|
||||
else:
|
||||
method = interpolation
|
||||
cm = np.array(bm[0:ndims] * nn / shrink, dtype=np.int32)
|
||||
ibeg = coords[0:ndims,l] * cm[0:ndims]
|
||||
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] = interpolate(dataset[:,:,:,l], cm, ng, method=method)
|
||||
else:
|
||||
ib, jb = ibeg[0], ibeg[1]
|
||||
ie, je = iend[0], iend[1]
|
||||
ret[jb:je,ib:ie] = interpolate(dataset[0,:,:,l], cm, ng, method=method)
|
||||
|
||||
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()
|
||||
|
||||
return ret
|
||||
@ -36,15 +36,9 @@
|
||||
|
||||
--------------------------------------------------------------------------------
|
||||
"""
|
||||
import h5py as h5
|
||||
import numpy as np
|
||||
from .interpolation import interpolate
|
||||
import os.path as op
|
||||
import sys
|
||||
try:
|
||||
from scipy.interpolate import splrep, splev, interp1d, pchip_interpolate
|
||||
scipy_available = True
|
||||
except ImportError:
|
||||
scipy_available = False
|
||||
try:
|
||||
from xxhash import *
|
||||
xxhash_available = True
|
||||
@ -831,667 +825,3 @@ class AmunXML:
|
||||
sys.stdout.flush()
|
||||
|
||||
return arr
|
||||
|
||||
|
||||
def amun_compatible(fname):
|
||||
'''
|
||||
Subroutine checks if the HDF5 file is AMUN compatible.
|
||||
|
||||
Arguments:
|
||||
|
||||
fname - the HDF5 file name;
|
||||
|
||||
Return values:
|
||||
|
||||
True or False;
|
||||
|
||||
Examples:
|
||||
|
||||
comp = amun_compatible('p000010_00000.h5')
|
||||
|
||||
'''
|
||||
with h5.File(fname, 'r') as f:
|
||||
if 'codes' in f.attrs:
|
||||
if f.attrs['code'].astype(str) == "AMUN":
|
||||
return True
|
||||
else:
|
||||
print("'%s' contains attribute 'code'," % fname, \
|
||||
" but it is not 'AMUN'!")
|
||||
return False
|
||||
elif 'attributes' in f and 'coordinates' in f and \
|
||||
'variables' in f:
|
||||
return True
|
||||
else:
|
||||
print("'%s' misses one of these groups:" % fname, \
|
||||
"'attributes', 'coordinates' or 'variables'!")
|
||||
return False
|
||||
|
||||
|
||||
def amun_attribute(fname, aname):
|
||||
'''
|
||||
Subroutine to read global attributes from AMUN HDF5 snapshots.
|
||||
|
||||
Arguments:
|
||||
|
||||
fname - the HDF5 file name;
|
||||
aname - the attribute name;
|
||||
|
||||
Return values:
|
||||
|
||||
ret - the value of the attribute or None;
|
||||
|
||||
Examples:
|
||||
|
||||
time = amun_attribute('p000010_00000.h5', 'time')
|
||||
|
||||
'''
|
||||
if not amun_compatible(fname):
|
||||
return None
|
||||
|
||||
with h5.File(fname, 'r') as f:
|
||||
if aname in f['attributes'].attrs:
|
||||
attr = f['attributes'].attrs[aname]
|
||||
if attr.dtype.type is np.string_:
|
||||
ret = np.squeeze(attr).astype(str)
|
||||
else:
|
||||
ret = np.squeeze(attr)
|
||||
return ret
|
||||
else:
|
||||
print("Attribute '%s' cannot be found in '%s'!" % (aname, fname))
|
||||
return None
|
||||
|
||||
|
||||
def amun_coordinate(fname, iname):
|
||||
'''
|
||||
Subroutine to read coordinate items from AMUN HDF5 snapshots.
|
||||
|
||||
Arguments:
|
||||
|
||||
fname - the HDF5 file name;
|
||||
iname - the item name;
|
||||
|
||||
Return values:
|
||||
|
||||
ret - the value of the item or None;
|
||||
|
||||
Examples:
|
||||
|
||||
bounds = amun_coordinate('p000010_00000.h5', 'bounds')
|
||||
|
||||
'''
|
||||
if not amun_compatible(fname):
|
||||
return None
|
||||
|
||||
with h5.File(fname, 'r') as f:
|
||||
if iname in f['coordinates']:
|
||||
return np.array(f['coordinates'][iname])
|
||||
else:
|
||||
print("Coordinate item '%s' not found in group 'coordinate' of '%s'!" % (iname, fname))
|
||||
return None
|
||||
|
||||
|
||||
def amun_dataset(fname, vname, shrink=1, interpolation='rebin', progress=False):
|
||||
'''
|
||||
Subroutine to read datasets from AMUN HDF5 snapshots.
|
||||
|
||||
Arguments:
|
||||
|
||||
fname - the HDF5 file name;
|
||||
vname - the variable name;
|
||||
shrink - the shrink factor (must be the power of 2 and not larger
|
||||
than the block size);
|
||||
progress - the progress bar switch;
|
||||
|
||||
Return values:
|
||||
|
||||
ret - the array of values for the variable;
|
||||
|
||||
Examples:
|
||||
|
||||
dn = amun_dataset('p000010_00000.h5', 'dens')
|
||||
|
||||
'''
|
||||
if not amun_compatible(fname):
|
||||
return None
|
||||
|
||||
dname = op.dirname(fname)
|
||||
|
||||
if progress:
|
||||
sys.stdout.write("Data file path:\n '%s'\n" % (dname))
|
||||
|
||||
# get attributes necessary to reconstruct the domain
|
||||
#
|
||||
eqsys = amun_attribute(fname, 'eqsys')
|
||||
eos = amun_attribute(fname, 'eos')
|
||||
nr = amun_attribute(fname, 'isnap')
|
||||
nc = amun_attribute(fname, 'nprocs')
|
||||
nl = amun_attribute(fname, 'nleafs')
|
||||
if eos == 'adi':
|
||||
gm = amun_attribute(fname, 'adiabatic_index')
|
||||
|
||||
# get block dimensions and the maximum level
|
||||
#
|
||||
ndims = amun_attribute(fname, 'ndims')
|
||||
nn = amun_attribute(fname, 'ncells')
|
||||
bm = np.array([nn, nn, nn])
|
||||
if ndims == 2:
|
||||
bm[2] = 1
|
||||
ng = amun_attribute(fname, 'nghosts')
|
||||
ml = amun_attribute(fname, 'maxlev')
|
||||
|
||||
# get the base block dimensions
|
||||
#
|
||||
rm = amun_attribute(fname, 'bdims')
|
||||
if rm is None:
|
||||
rm = amun_attribute(fname, 'domain_base_dims')
|
||||
if rm is None:
|
||||
rm = amun_attribute(fname, 'rdims')
|
||||
if rm is None:
|
||||
return None
|
||||
|
||||
# build the list of supported variables
|
||||
#
|
||||
variables = []
|
||||
with h5.File(fname, 'r') as f:
|
||||
for var in f['variables'].keys():
|
||||
variables.append(var)
|
||||
|
||||
# add derived variables if possible
|
||||
#
|
||||
variables.append('level')
|
||||
if 'velx' in variables and 'vely' in variables and 'velz' in variables:
|
||||
variables.append('velo')
|
||||
variables.append('divv')
|
||||
variables.append('vort')
|
||||
if 'magx' in variables and 'magy' in variables and 'magz' in variables:
|
||||
variables.append('magn')
|
||||
variables.append('divb')
|
||||
variables.append('curr')
|
||||
if (eqsys == 'hd' or eqsys == 'mhd') and eos == 'adi' \
|
||||
and 'pres' in variables:
|
||||
variables.append('eint')
|
||||
if 'dens' in variables and 'pres' in variables:
|
||||
variables.append('temp')
|
||||
if (eqsys == 'hd' or eqsys == 'mhd') \
|
||||
and 'dens' in variables \
|
||||
and 'velx' in variables \
|
||||
and 'vely' in variables \
|
||||
and 'velz' in variables:
|
||||
variables.append('ekin')
|
||||
if (eqsys == 'mhd' or eqsys == 'srmhd') \
|
||||
and 'magx' in variables \
|
||||
and 'magy' in variables \
|
||||
and 'magz' in variables:
|
||||
variables.append('emag')
|
||||
if eqsys == 'hd' and 'ekin' in variables and 'eint' in variables:
|
||||
variables.append('etot')
|
||||
if eqsys == 'mhd' and 'eint' in variables \
|
||||
and 'ekin' in variables \
|
||||
and 'emag' in variables:
|
||||
variables.append('etot')
|
||||
if (eqsys == 'srhd' or eqsys == 'srmhd') and 'velo' in variables:
|
||||
variables.append('lore')
|
||||
|
||||
# check if the requested variable is in the variable list
|
||||
#
|
||||
if not vname in variables:
|
||||
print('The requested variable cannot be extracted from the file datasets!')
|
||||
return None
|
||||
|
||||
# check if the shrink parameter is correct (block dimensions should be
|
||||
# divisible by the shrink factor)
|
||||
#
|
||||
shrink = max(1, int(shrink))
|
||||
if shrink > 1:
|
||||
if (nn % shrink) != 0:
|
||||
print('The block dimension should be divisible by the shrink factor!')
|
||||
return None
|
||||
sh = shrink
|
||||
while(sh > 2 and sh % 2 == 0):
|
||||
sh = int(sh / 2)
|
||||
if (sh % 2) != 0:
|
||||
print('The shrink factor should be a power of 2!')
|
||||
return None
|
||||
|
||||
# determine the actual maximum level from the blocks
|
||||
#
|
||||
levs = []
|
||||
for n in range(nc):
|
||||
fname = 'p%06d_%05d.h5' % (nr, n)
|
||||
lname = op.join(dname, fname)
|
||||
dblocks = amun_attribute(lname, 'dblocks')
|
||||
if dblocks > 0:
|
||||
levs = np.append(levs, [amun_coordinate(lname, 'levels')])
|
||||
ml = int(levs.max())
|
||||
|
||||
# prepare dimensions of the output array and allocate it
|
||||
#
|
||||
dm = np.array(rm[0:ndims] * bm[0:ndims] * 2**(ml - 1) / shrink, \
|
||||
dtype=np.int32)
|
||||
ret = np.zeros(dm[::-1])
|
||||
|
||||
# iterate over all subdomain files
|
||||
#
|
||||
nb = 0
|
||||
for n in range(nc):
|
||||
fname = 'p%06d_%05d.h5' % (nr, n)
|
||||
lname = op.join(dname, fname)
|
||||
dblocks = amun_attribute(lname, 'dblocks')
|
||||
if dblocks > 0:
|
||||
levels = amun_coordinate(lname, 'levels')
|
||||
coords = amun_coordinate(lname, 'coords')
|
||||
dx = amun_coordinate(lname, 'dx')
|
||||
dy = amun_coordinate(lname, 'dy')
|
||||
dz = amun_coordinate(lname, 'dz')
|
||||
with h5.File(lname, 'r') as f:
|
||||
g = f['variables']
|
||||
if vname == 'level':
|
||||
dataset = np.zeros(g[variables[0]].shape)
|
||||
for l in range(dblocks):
|
||||
dataset[:,:,:,l] = levels[l]
|
||||
elif vname == 'velo':
|
||||
dataset = np.sqrt(g['velx'][:,:,:,:]**2 \
|
||||
+ g['vely'][:,:,:,:]**2 \
|
||||
+ g['velz'][:,:,:,:]**2)
|
||||
elif vname == 'magn':
|
||||
dataset = np.sqrt(g['magx'][:,:,:,:]**2 \
|
||||
+ g['magy'][:,:,:,:]**2 \
|
||||
+ g['magz'][:,:,:,:]**2)
|
||||
elif vname == 'eint':
|
||||
dataset = 1.0 / (gm - 1.0) * g['pres'][:,:,:,:]
|
||||
elif vname == 'ekin':
|
||||
dataset = 0.5 * g['dens'][:,:,:,:] * (g['velx'][:,:,:,:]**2 \
|
||||
+ g['vely'][:,:,:,:]**2 \
|
||||
+ g['velz'][:,:,:,:]**2)
|
||||
elif vname == 'emag':
|
||||
dataset = 0.5 * (g['magx'][:,:,:,:]**2 \
|
||||
+ g['magy'][:,:,:,:]**2 \
|
||||
+ g['magz'][:,:,:,:]**2)
|
||||
elif vname == 'etot':
|
||||
dataset = 1.0 / (gm - 1.0) * g['pres'][:,:,:,:] \
|
||||
+ 0.5 * g['dens'][:,:,:,:] * (g['velx'][:,:,:,:]**2 \
|
||||
+ g['vely'][:,:,:,:]**2 \
|
||||
+ g['velz'][:,:,:,:]**2)
|
||||
if eqsys == 'mhd':
|
||||
dataset += 0.5 * (g['magx'][:,:,:,:]**2 \
|
||||
+ g['magy'][:,:,:,:]**2 \
|
||||
+ g['magz'][:,:,:,:]**2)
|
||||
elif vname == 'temp':
|
||||
dataset = g['pres'][:,:,:,:] / g['dens'][:,:,:,:]
|
||||
elif vname == 'lore':
|
||||
dataset = 1.0 / np.sqrt(1.0 - (g['velx'][:,:,:,:]**2 \
|
||||
+ g['vely'][:,:,:,:]**2 \
|
||||
+ g['velz'][:,:,:,:]**2))
|
||||
elif vname == 'divv':
|
||||
dataset = np.zeros(g['velx'].shape)
|
||||
fields = [ 'velx', 'vely', 'velz' ]
|
||||
h = (dx, dy, dz)
|
||||
for i in range(ndims):
|
||||
v = fields[i]
|
||||
dataset += 0.5 * (np.roll(g[v][:,:,:,:], -1, axis=2) \
|
||||
- np.roll(g[v][:,:,:,:], 1, axis=2)) \
|
||||
/ h[i][levels[:] - 1]
|
||||
elif vname == 'divb':
|
||||
dataset = np.zeros(g['magx'].shape)
|
||||
fields = [ 'magx', 'magy', 'magz' ]
|
||||
h = (dx, dy, dz)
|
||||
for i in range(ndims):
|
||||
v = fields[i]
|
||||
dataset += 0.5 * (np.roll(g[v][:,:,:,:], -1, axis=2) \
|
||||
- np.roll(g[v][:,:,:,:], 1, axis=2)) \
|
||||
/ h[i][levels[:] - 1]
|
||||
elif vname == 'vort':
|
||||
if ndims == 3:
|
||||
wx = 0.5 * (np.roll(g['velz'][:,:,:,:], -1, axis=1) \
|
||||
- np.roll(g['velz'][:,:,:,:], 1, axis=1)) \
|
||||
/ dy[levels[:]-1] \
|
||||
- 0.5 * (np.roll(g['vely'][:,:,:,:], -1, axis=0) \
|
||||
- np.roll(g['vely'][:,:,:,:], 1, axis=0)) \
|
||||
/ dz[levels[:]-1]
|
||||
wy = 0.5 * (np.roll(g['velx'][:,:,:,:], -1, axis=0) \
|
||||
- np.roll(g['velx'][:,:,:,:], 1, axis=0)) \
|
||||
/ dz[levels[:]-1] \
|
||||
- 0.5 * (np.roll(g['velz'][:,:,:,:], -1, axis=2) \
|
||||
- np.roll(g['velz'][:,:,:,:], 1, axis=2)) \
|
||||
/ dx[levels[:]-1]
|
||||
wz = 0.5 * (np.roll(g['vely'][:,:,:,:], -1, axis=2) \
|
||||
- np.roll(g['vely'][:,:,:,:], 1, axis=2)) \
|
||||
/ dx[levels[:]-1] \
|
||||
- 0.5 * (np.roll(g['velx'][:,:,:,:], -1, axis=1) \
|
||||
- np.roll(g['velx'][:,:,:,:], 1, axis=1)) \
|
||||
/ dy[levels[:]-1]
|
||||
else:
|
||||
wx = 0.5 * (np.roll(g['velz'][:,:,:,:], -1, axis=1) \
|
||||
- np.roll(g['velz'][:,:,:,:], 1, axis=1)) \
|
||||
/ dy[levels[:]-1]
|
||||
wy = - 0.5 * (np.roll(g['velz'][:,:,:,:], -1, axis=2) \
|
||||
- np.roll(g['velz'][:,:,:,:], 1, axis=2)) \
|
||||
/ dx[levels[:]-1]
|
||||
wz = 0.5 * (np.roll(g['vely'][:,:,:,:], -1, axis=2) \
|
||||
- np.roll(g['vely'][:,:,:,:], 1, axis=2)) \
|
||||
/ dx[levels[:]-1] \
|
||||
- 0.5 * (np.roll(g['velx'][:,:,:,:], -1, axis=1) \
|
||||
- np.roll(g['velx'][:,:,:,:], 1, axis=1)) \
|
||||
/ dy[levels[:]-1]
|
||||
dataset = np.sqrt(wx * wx + wy * wy + wz * wz)
|
||||
elif vname == 'curr':
|
||||
if ndims == 3:
|
||||
wx = 0.5 * (np.roll(g['magz'][:,:,:,:], -1, axis=1) \
|
||||
- np.roll(g['magz'][:,:,:,:], 1, axis=1)) \
|
||||
/ dy[levels[:]-1] \
|
||||
- 0.5 * (np.roll(g['magy'][:,:,:,:], -1, axis=0) \
|
||||
- np.roll(g['magy'][:,:,:,:], 1, axis=0)) \
|
||||
/ dz[levels[:]-1]
|
||||
wy = 0.5 * (np.roll(g['magx'][:,:,:,:], -1, axis=0) \
|
||||
- np.roll(g['magx'][:,:,:,:], 1, axis=0)) \
|
||||
/ dz[levels[:]-1] \
|
||||
- 0.5 * (np.roll(g['magz'][:,:,:,:], -1, axis=2) \
|
||||
- np.roll(g['magz'][:,:,:,:], 1, axis=2)) \
|
||||
/ dx[levels[:]-1]
|
||||
wz = 0.5 * (np.roll(g['magy'][:,:,:,:], -1, axis=2) \
|
||||
- np.roll(g['magy'][:,:,:,:], 1, axis=2)) \
|
||||
/ dx[levels[:]-1] \
|
||||
- 0.5 * (np.roll(g['magx'][:,:,:,:], -1, axis=1) \
|
||||
- np.roll(g['magx'][:,:,:,:], 1, axis=1)) \
|
||||
/ dy[levels[:]-1]
|
||||
else:
|
||||
wx = 0.5 * (np.roll(g['magz'][:,:,:,:], -1, axis=1) \
|
||||
- np.roll(g['magz'][:,:,:,:], 1, axis=1)) \
|
||||
/ dy[levels[:]-1]
|
||||
wy = - 0.5 * (np.roll(g['magz'][:,:,:,:], -1, axis=2) \
|
||||
- np.roll(g['magz'][:,:,:,:], 1, axis=2)) \
|
||||
/ dx[levels[:]-1]
|
||||
wz = 0.5 * (np.roll(g['magy'][:,:,:,:], -1, axis=2) \
|
||||
- np.roll(g['magy'][:,:,:,:], 1, axis=2)) \
|
||||
/ dx[levels[:]-1] \
|
||||
- 0.5 * (np.roll(g['magx'][:,:,:,:], -1, axis=1) \
|
||||
- np.roll(g['magx'][:,:,:,:], 1, axis=1)) \
|
||||
/ dy[levels[:]-1]
|
||||
dataset = np.sqrt(wx * wx + wy * wy + wz * wz)
|
||||
else:
|
||||
dataset = g[vname][:,:,:,:]
|
||||
|
||||
# rescale all blocks to the effective resolution
|
||||
#
|
||||
for l in range(dblocks):
|
||||
nn = 2**(ml - levels[l])
|
||||
if nn <= shrink:
|
||||
method = 'rebin'
|
||||
else:
|
||||
method = interpolation
|
||||
cm = np.array(bm[0:ndims] * nn / shrink, dtype=np.int32)
|
||||
ibeg = coords[0:ndims,l] * cm[0:ndims]
|
||||
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] = interpolate(dataset[:,:,:,l], cm, ng, method=method)
|
||||
else:
|
||||
ib, jb = ibeg[0], ibeg[1]
|
||||
ie, je = iend[0], iend[1]
|
||||
ret[jb:je,ib:ie] = interpolate(dataset[0,:,:,l], cm, ng, method=method)
|
||||
|
||||
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()
|
||||
|
||||
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)
|
||||
|
||||
|
||||
def interpolate(a, newshape, nghosts, method = 'rebin'):
|
||||
'''
|
||||
Subroutine rescales the block by interpolating its values.
|
||||
'''
|
||||
if (method == 'rebin' or not scipy_available):
|
||||
|
||||
# calculate the indices in order to remove the ghost zones
|
||||
#
|
||||
if a.ndim == 3:
|
||||
ib = nghosts
|
||||
jb = nghosts
|
||||
kb = nghosts
|
||||
ie = a.shape[2] - nghosts
|
||||
je = a.shape[1] - nghosts
|
||||
ke = a.shape[0] - nghosts
|
||||
if (a.shape[0] == 1):
|
||||
kb = 0
|
||||
ke = 1
|
||||
|
||||
return rebin(a[kb:ke,jb:je,ib:ie], newshape)
|
||||
else:
|
||||
ib = nghosts
|
||||
jb = nghosts
|
||||
ie = a.shape[1] - nghosts
|
||||
je = a.shape[0] - nghosts
|
||||
|
||||
return rebin(a[jb:je,ib:ie], newshape)
|
||||
|
||||
elif (method == 'monotonic' or method == 'pchip'):
|
||||
|
||||
dims = np.arange(a.ndim)
|
||||
|
||||
q = a
|
||||
|
||||
for n in dims:
|
||||
|
||||
d2 = np.roll(q,-1, axis=0) + np.roll(q, 1, axis=0) - 2.0 * q
|
||||
q = q - d2 / 24.0
|
||||
|
||||
d = np.array(q.shape)
|
||||
|
||||
xo = (np.arange(0.5, a.shape[n]) - nghosts) / (a.shape[n] - 2 * nghosts)
|
||||
xn = np.arange(0.5, newshape[n]) / newshape[n]
|
||||
|
||||
u = q.reshape([d[0], int(q.size / d[0])])
|
||||
f = np.zeros([newshape[n], int(q.size / d[0])])
|
||||
for i in range(int(q.size / d[0])):
|
||||
f[:,i] = pchip_interpolate(xo, u[:,i], xn)
|
||||
|
||||
d[0] = newshape[n]
|
||||
f = f.reshape(d)
|
||||
|
||||
q = f.transpose(np.roll(dims, -1))
|
||||
|
||||
return q
|
||||
|
||||
elif (method == 'spline'):
|
||||
|
||||
dims = np.arange(a.ndim)
|
||||
|
||||
q = a
|
||||
|
||||
for n in dims:
|
||||
|
||||
d2 = np.roll(q,-1, axis=0) + np.roll(q, 1, axis=0) - 2.0 * q
|
||||
q = q - d2 / 24.0
|
||||
|
||||
d = np.array(q.shape)
|
||||
|
||||
xo = (np.arange(0.5, a.shape[n]) - nghosts) / (a.shape[n] - 2 * nghosts)
|
||||
xn = np.arange(0.5, newshape[n]) / newshape[n]
|
||||
|
||||
u = q.reshape([d[0], int(q.size / d[0])])
|
||||
f = np.zeros([newshape[n], int(q.size / d[0])])
|
||||
for i in range(int(q.size / d[0])):
|
||||
t = splrep(xo, u[:,i], k=5, s=0.0)
|
||||
f[:,i] = splev(xn, t)
|
||||
|
||||
d[0] = newshape[n]
|
||||
f = f.reshape(d)
|
||||
|
||||
q = f.transpose(np.roll(dims, -1))
|
||||
|
||||
return q
|
||||
|
||||
else:
|
||||
|
||||
dims = np.arange(a.ndim)
|
||||
|
||||
q = a
|
||||
|
||||
for n in dims:
|
||||
|
||||
d2 = np.roll(q,-1, axis=0) + np.roll(q, 1, axis=0) - 2.0 * q
|
||||
q = q - d2 / 24.0
|
||||
|
||||
d = np.array(q.shape)
|
||||
|
||||
xo = (np.arange(0.5, a.shape[n]) - nghosts) / (a.shape[n] - 2 * nghosts)
|
||||
xn = np.arange(0.5, newshape[n]) / newshape[n]
|
||||
|
||||
u = q.reshape([d[0], int(q.size / d[0])])
|
||||
f = np.zeros([newshape[n], int(q.size / d[0])])
|
||||
for i in range(int(q.size / d[0])):
|
||||
t = interp1d(xo, u[:,i], kind=method)
|
||||
f[:,i] = t(xn)
|
||||
|
||||
d[0] = newshape[n]
|
||||
f = f.reshape(d)
|
||||
|
||||
q = f.transpose(np.roll(dims, -1))
|
||||
|
||||
return q
|
||||
|
||||
|
||||
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())
|
||||
130
python/amunpy/src/amunpy/integrals.py
Normal file
130
python/amunpy/src/amunpy/integrals.py
Normal file
@ -0,0 +1,130 @@
|
||||
"""
|
||||
================================================================================
|
||||
|
||||
This file is part of the AMUN source code, a program to perform
|
||||
Newtonian or relativistic magnetohydrodynamical simulations on uniform or
|
||||
adaptive mesh.
|
||||
|
||||
Copyright (C) 2018-2021 Grzegorz Kowal <grzegorz@amuncode.org>
|
||||
|
||||
This program is free software: you can redistribute it and/or modify
|
||||
it under the terms of the GNU General Public License as published by
|
||||
the Free Software Foundation, either version 3 of the License, or
|
||||
(at your option) any later version.
|
||||
|
||||
This program is distributed in the hope that it will be useful,
|
||||
but WITHOUT ANY WARRANTY; without even the implied warranty of
|
||||
MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
|
||||
GNU General Public License for more details.
|
||||
|
||||
You should have received a copy of the GNU General Public License
|
||||
along with this program. If not, see <http://www.gnu.org/licenses/>.
|
||||
|
||||
================================================================================
|
||||
|
||||
module: AMUN
|
||||
|
||||
Python module with subroutines to read AMUN code HDF5 files.
|
||||
|
||||
The only requirements for this package are:
|
||||
|
||||
- numpy
|
||||
|
||||
--------------------------------------------------------------------------------
|
||||
"""
|
||||
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))
|
||||
180
python/amunpy/src/amunpy/interpolation.py
Normal file
180
python/amunpy/src/amunpy/interpolation.py
Normal file
@ -0,0 +1,180 @@
|
||||
"""
|
||||
================================================================================
|
||||
|
||||
This file is part of the AMUN source code, a program to perform
|
||||
Newtonian or relativistic magnetohydrodynamical simulations on uniform or
|
||||
adaptive mesh.
|
||||
|
||||
Copyright (C) 2018-2021 Grzegorz Kowal <grzegorz@amuncode.org>
|
||||
|
||||
This program is free software: you can redistribute it and/or modify
|
||||
it under the terms of the GNU General Public License as published by
|
||||
the Free Software Foundation, either version 3 of the License, or
|
||||
(at your option) any later version.
|
||||
|
||||
This program is distributed in the hope that it will be useful,
|
||||
but WITHOUT ANY WARRANTY; without even the implied warranty of
|
||||
MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
|
||||
GNU General Public License for more details.
|
||||
|
||||
You should have received a copy of the GNU General Public License
|
||||
along with this program. If not, see <http://www.gnu.org/licenses/>.
|
||||
|
||||
================================================================================
|
||||
|
||||
module: AMUN
|
||||
|
||||
Python module with subroutines to read AMUN code HDF5 files.
|
||||
|
||||
The only requirements for this package are:
|
||||
|
||||
- numpy
|
||||
- scipy (optional, for data interpolation)
|
||||
|
||||
--------------------------------------------------------------------------------
|
||||
"""
|
||||
import numpy as np
|
||||
try:
|
||||
from scipy.interpolate import splrep, splev, interp1d, pchip_interpolate
|
||||
scipy_available = True
|
||||
except ImportError:
|
||||
scipy_available = False
|
||||
|
||||
|
||||
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)
|
||||
|
||||
|
||||
def interpolate(a, newshape, nghosts, method = 'rebin'):
|
||||
'''
|
||||
Subroutine rescales the block by interpolating its values.
|
||||
'''
|
||||
if (method == 'rebin' or not scipy_available):
|
||||
|
||||
# calculate the indices in order to remove the ghost zones
|
||||
#
|
||||
if a.ndim == 3:
|
||||
ib = nghosts
|
||||
jb = nghosts
|
||||
kb = nghosts
|
||||
ie = a.shape[2] - nghosts
|
||||
je = a.shape[1] - nghosts
|
||||
ke = a.shape[0] - nghosts
|
||||
if (a.shape[0] == 1):
|
||||
kb = 0
|
||||
ke = 1
|
||||
|
||||
return rebin(a[kb:ke,jb:je,ib:ie], newshape)
|
||||
else:
|
||||
ib = nghosts
|
||||
jb = nghosts
|
||||
ie = a.shape[1] - nghosts
|
||||
je = a.shape[0] - nghosts
|
||||
|
||||
return rebin(a[jb:je,ib:ie], newshape)
|
||||
|
||||
elif (method == 'monotonic' or method == 'pchip'):
|
||||
|
||||
dims = np.arange(a.ndim)
|
||||
|
||||
q = a
|
||||
|
||||
for n in dims:
|
||||
|
||||
d2 = np.roll(q,-1, axis=0) + np.roll(q, 1, axis=0) - 2.0 * q
|
||||
q = q - d2 / 24.0
|
||||
|
||||
d = np.array(q.shape)
|
||||
|
||||
xo = (np.arange(0.5, a.shape[n]) - nghosts) / (a.shape[n] - 2 * nghosts)
|
||||
xn = np.arange(0.5, newshape[n]) / newshape[n]
|
||||
|
||||
u = q.reshape([d[0], int(q.size / d[0])])
|
||||
f = np.zeros([newshape[n], int(q.size / d[0])])
|
||||
for i in range(int(q.size / d[0])):
|
||||
f[:,i] = pchip_interpolate(xo, u[:,i], xn)
|
||||
|
||||
d[0] = newshape[n]
|
||||
f = f.reshape(d)
|
||||
|
||||
q = f.transpose(np.roll(dims, -1))
|
||||
|
||||
return q
|
||||
|
||||
elif (method == 'spline'):
|
||||
|
||||
dims = np.arange(a.ndim)
|
||||
|
||||
q = a
|
||||
|
||||
for n in dims:
|
||||
|
||||
d2 = np.roll(q,-1, axis=0) + np.roll(q, 1, axis=0) - 2.0 * q
|
||||
q = q - d2 / 24.0
|
||||
|
||||
d = np.array(q.shape)
|
||||
|
||||
xo = (np.arange(0.5, a.shape[n]) - nghosts) / (a.shape[n] - 2 * nghosts)
|
||||
xn = np.arange(0.5, newshape[n]) / newshape[n]
|
||||
|
||||
u = q.reshape([d[0], int(q.size / d[0])])
|
||||
f = np.zeros([newshape[n], int(q.size / d[0])])
|
||||
for i in range(int(q.size / d[0])):
|
||||
t = splrep(xo, u[:,i], k=5, s=0.0)
|
||||
f[:,i] = splev(xn, t)
|
||||
|
||||
d[0] = newshape[n]
|
||||
f = f.reshape(d)
|
||||
|
||||
q = f.transpose(np.roll(dims, -1))
|
||||
|
||||
return q
|
||||
|
||||
else:
|
||||
|
||||
dims = np.arange(a.ndim)
|
||||
|
||||
q = a
|
||||
|
||||
for n in dims:
|
||||
|
||||
d2 = np.roll(q,-1, axis=0) + np.roll(q, 1, axis=0) - 2.0 * q
|
||||
q = q - d2 / 24.0
|
||||
|
||||
d = np.array(q.shape)
|
||||
|
||||
xo = (np.arange(0.5, a.shape[n]) - nghosts) / (a.shape[n] - 2 * nghosts)
|
||||
xn = np.arange(0.5, newshape[n]) / newshape[n]
|
||||
|
||||
u = q.reshape([d[0], int(q.size / d[0])])
|
||||
f = np.zeros([newshape[n], int(q.size / d[0])])
|
||||
for i in range(int(q.size / d[0])):
|
||||
t = interp1d(xo, u[:,i], kind=method)
|
||||
f[:,i] = t(xn)
|
||||
|
||||
d[0] = newshape[n]
|
||||
f = f.reshape(d)
|
||||
|
||||
q = f.transpose(np.roll(dims, -1))
|
||||
|
||||
return q
|
||||
Loading…
x
Reference in New Issue
Block a user