Files
astaroth/analysis/python/astar/data/read.py
2020-01-14 14:23:24 +08:00

308 lines
11 KiB
Python

'''
Copyright (C) 2014-2020, Johannes Pekkila, Miikka Vaisala.
This file is part of Astaroth.
Astaroth 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.
Astaroth 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 Astaroth. If not, see <http://www.gnu.org/licenses/>.
'''
# This module is for reading data.
import numpy as np
#Optional YT interface
try:
import yt
yt_present = True
except ImportError:
yt_present = False
def set_dtype(endian, AcRealSize):
if endian == 0:
en = '>'
elif endian == 1:
en = '<'
type_instruction = en + 'f' + str(AcRealSize)
print("type_instruction", type_instruction)
my_dtype = np.dtype(type_instruction)
return my_dtype
def read_bin(fname, fdir, fnum, minfo, numtype=np.longdouble):
'''Read in a floating point array'''
filename = fdir + fname + '_' + fnum + '.mesh'
datas = np.DataSource()
read_ok = datas.exists(filename)
my_dtype = set_dtype(minfo.contents['endian'], minfo.contents['AcRealSize'])
if read_ok:
print(filename)
array = np.fromfile(filename, dtype=my_dtype)
timestamp = array[0]
array = np.reshape(array[1:], (minfo.contents['AC_mx'],
minfo.contents['AC_my'],
minfo.contents['AC_mz']), order='F')
else:
array = None
timestamp = None
return array, timestamp, read_ok
def read_meshtxt(fdir, fname, dbg_output):
with open(fdir+fname) as f:
filetext = f.read().splitlines()
contents = {}
for line in filetext:
line = line.split()
if line[0] == 'int':
contents[line[1]] = np.int(line[2])
if dbg_output:
print(line[1], contents[line[1]])
elif line[0] == 'size_t':
contents[line[1]] = np.int(line[2])
if dbg_output:
print(line[1], contents[line[1]])
elif line[0] == 'int3':
contents[line[1]] = [np.int(line[2]), np.int(line[3]), np.int(line[4])]
if dbg_output:
print(line[1], contents[line[1]])
elif line[0] == 'real':
contents[line[1]] = np.float(line[2])
if dbg_output:
print(line[1], contents[line[1]])
elif line[0] == 'real3':
contents[line[1]] = [np.float(line[2]), np.float(line[3]), np.float(line[4])]
if dbg_output:
print(line[1], contents[line[1]])
else:
print(line)
print('ERROR: ' + line[0] +' not recognized!')
return contents
def DERX(array, dx):
output = np.zeros_like(array)
for i in range(3, array.shape[0]-3): #Keep boundary poits as 0
output[i,:,:] =( -45.0*array[i-1,:,:] + 45.0*array[i+1,:,:]
+ 9.0*array[i-2,:,:] - 9.0*array[i+2,:,:]
- array[i-3,:,:] + array[i+3,:,:] )/(60.0*dx)
return output
def DERY(array, dy):
output = np.zeros_like(array)
for i in range(3,array.shape[1]-3):
output[:,i,:] =( -45.0*array[:,i-1,:] + 45.0*array[:,i+1,:]
+ 9.0*array[:,i-2,:] - 9.0*array[:,i+2,:]
- array[:,i-3,:] + array[:,i+3,:] )/(60.0*dy)
return output
def DERZ(array, dz):
output = np.zeros_like(array)
for i in range(3, array.shape[2]-3):
output[:,:,i] =( -45.0*array[:,:,i-1] + 45.0*array[:,:,i+1]
+ 9.0*array[:,:,i-2] - 9.0*array[:,:,i+2]
- array[:,:,i-3] + array[:,:,i+3] )/(60.0*dz)
return output
def curl(aa, minfo):
dx = minfo.contents['AC_dsx']
dy = minfo.contents['AC_dsy']
dz = minfo.contents['AC_dsz']
return (DERY(aa[2], dy)-DERZ(aa[1], dz),
DERZ(aa[0], dz)-DERX(aa[2], dx),
DERX(aa[1], dx)-DERY(aa[0], dy))
class MeshInfo():
'''Object that contains all mesh info'''
def __init__(self, fdir, dbg_output=False):
self.contents = read_meshtxt(fdir, 'mesh_info.list', dbg_output)
class Mesh:
'''Class tha contains all 3d mesh data'''
def __init__(self, fnum, fdir=""):
fnum = str(fnum)
self.framenum = fnum.zfill(10)
self.minfo = MeshInfo(fdir)
self.lnrho, self.timestamp, self.ok = read_bin('VTXBUF_LNRHO', fdir, fnum, self.minfo)
if self.ok:
self.ss, timestamp, ok = read_bin('VTXBUF_ENTROPY', fdir, fnum, self.minfo)
self.accretion, timestamp, ok = read_bin('VTXBUF_ACCRETION', fdir, fnum, self.minfo)
#TODO Generalize is a dict. Do not hardcode!
uux, timestamp, ok = read_bin('VTXBUF_UUX', fdir, fnum, self.minfo)
uuy, timestamp, ok = read_bin('VTXBUF_UUY', fdir, fnum, self.minfo)
uuz, timestamp, ok = read_bin('VTXBUF_UUZ', fdir, fnum, self.minfo)
self.uu = (uux, uuy, uuz)
uux = []
uuy = []
uuz = []
aax, timestamp, ok = read_bin('VTXBUF_AX', fdir, fnum, self.minfo)
aay, timestamp, ok = read_bin('VTXBUF_AY', fdir, fnum, self.minfo)
aaz, timestamp, ok = read_bin('VTXBUF_AZ', fdir, fnum, self.minfo)
self.aa = (aax, aay, aaz)
aax = []
aay = []
aaz = []
#self.aa[0][:,:,:] = 0.0
#self.aa[1][:,:,:] = 0.0
#self.aa[2][:,:,:] = 0.0
#for i in range(0, self.aa[0].shape[0]):
# self.aa[0][:,i,:] = float(i)
self.xx = np.arange(self.minfo.contents['AC_mx']) * self.minfo.contents['AC_dsx']
self.yy = np.arange(self.minfo.contents['AC_my']) * self.minfo.contents['AC_dsy']
self.zz = np.arange(self.minfo.contents['AC_mz']) * self.minfo.contents['AC_dsz']
self.xmid = int(self.minfo.contents['AC_mx']/2)
self.ymid = int(self.minfo.contents['AC_my']/2)
self.zmid = int(self.minfo.contents['AC_mz']/2)
def Bfield(self, get_jj = False):
self.bb = curl(self.aa, self.minfo)
if get_jj:
self.jj = curl(self.bb, self.minfo)
def yt_conversion(self):
if yt_present:
self.ytdict = dict(density = (np.exp(self.lnrho)*self.minfo.contents['AC_unit_density'], "g/cm**3"),
uux = (self.uu[0]*self.minfo.contents['AC_unit_velocity'], "cm/s"),
uuy = (self.uu[1]*self.minfo.contents['AC_unit_velocity'], "cm/s"),
uuz = (self.uu[2]*self.minfo.contents['AC_unit_velocity'], "cm/s"),
bbx = (self.bb[0]*self.minfo.contents['AC_unit_magnetic'], "gauss"),
bby = (self.bb[1]*self.minfo.contents['AC_unit_magnetic'], "gauss"),
bbz = (self.bb[2]*self.minfo.contents['AC_unit_magnetic'], "gauss"),
)
bbox = self.minfo.contents['AC_unit_length'] \
*np.array([[self.xx.min(), self.xx.max()], [self.yy.min(), self.yy.max()], [self.zz.min(), self.zz.max()]])
self.ytdata = yt.load_uniform_grid(self.ytdict, self.lnrho.shape, length_unit="cm", bbox=bbox)
else:
print("ERROR. No YT support found!")
def export_csv(self):
csvfile = open("grid.csv.%s" % self.framenum, "w")
csvfile.write("xx, yy, zz, rho, uux, uuy, uuz, bbx, bby, bbz\n")
ul = self.minfo.contents['AC_unit_length']
uv = self.minfo.contents['AC_unit_velocity']
ud = self.minfo.contents['AC_unit_density']
um = self.minfo.contents['AC_unit_magnetic']
for kk in np.arange(3, self.zz.size-3):
for jj in np.arange(3, self.yy.size-3):
for ii in np.arange(3, self.xx.size-3):
#print(self.xx.size, self.yy.size, self.zz.size)
linestring = "%e, %e, %e, %e, %e, %e, %e, %e, %e, %e\n"% (self.xx[ii]*ul, self.yy[jj]*ul, self.zz[kk]*ul,
np.exp(self.lnrho[ii, jj, kk])*ud,
self.uu[0][ii, jj, kk]*uv, self.uu[1][ii, jj, kk]*uv,
self.uu[2][ii, jj, kk]*uv,
self.bb[0][ii, jj, kk]*um, self.bb[1][ii, jj, kk]*um,
self.bb[2][ii, jj, kk]*um)
csvfile.write(linestring)
csvfile.close()
def export_raw(self):
uv = self.minfo.contents['AC_unit_velocity']
ud = self.minfo.contents['AC_unit_density']
um = self.minfo.contents['AC_unit_magnetic']
print(self.lnrho.shape, set_dtype(self.minfo.contents['endian'], self.minfo.contents['AcRealSize']))
f = open("rho%s.raw" % self.framenum, 'w+b')
binary_format =(np.exp(self.lnrho)*ud).tobytes()
f.write(binary_format)
f.close()
f = open("uux%s.raw" % self.framenum, 'w+b')
binary_format =(self.uu[0]*uv).tobytes()
f.write(binary_format)
f.close()
f = open("uuy%s.raw" % self.framenum, 'w+b')
binary_format =(self.uu[1]*uv).tobytes()
f.write(binary_format)
f.close()
f = open("uuz%s.raw" % self.framenum, 'w+b')
binary_format =(self.uu[2]*uv).tobytes()
f.write(binary_format)
f.close()
f = open("bbx%s.raw" % self.framenum, 'w+b')
binary_format =(self.bb[0]*um).tobytes()
f.write(binary_format)
f.close()
f = open("bby%s.raw" % self.framenum, 'w+b')
binary_format =(self.bb[1]*um).tobytes()
f.write(binary_format)
f.close()
f = open("bbz%s.raw" % self.framenum, 'w+b')
binary_format =(self.bb[2]*um).tobytes()
f.write(binary_format)
f.close()
def parse_ts(fdir, fname):
with open(fdir+fname) as f:
filetext = f.read().splitlines()
var = {}
line = filetext[0].split()
for i in range(len(line)):
line[i] = line[i].replace('VTXBUF_', "")
line[i] = line[i].replace('UU', "uu")
line[i] = line[i].replace('_total', "tot")
line[i] = line[i].replace('ACCRETION', "acc")
line[i] = line[i].replace('A', "aa")
line[i] = line[i].replace('LNRHO', "lnrho")
line[i] = line[i].replace('ENTROPY', "ss")
line[i] = line[i].replace('X', "x")
line[i] = line[i].replace('Y', "y")
line[i] = line[i].replace('Z', "z")
tsdata = np.loadtxt(fdir+fname,skiprows=1)
for i in range(len(line)):
var[line[i]] = tsdata[:,i]
var['step'] = np.int64(var['step'])
print("HERE ARE ALL KEYS FOR TS DATA:")
print(var.keys())
return var
class TimeSeries:
'''Class for time series data'''
def __init__(self, fdir="", fname="timeseries.ts"):
self.var = parse_ts(fdir, fname)