def test_tomso_open(self):
with common.tomso_open('data/test.txt', 'rb') as f:
lines = f.read().decode('utf-8').split('\n')
with common.tomso_open('data/test.txt.gz', 'rb') as f:
lines_gz = f.read().decode('utf-8').split('\n')
for line, line_gz in zip(lines, lines_gz):
self.assertEqual(line, line_gz)
def load_astero_results(filename):
"""Reads a set of MESA results from one of the optimization routines
in the `astero` module.
Parameters
----------
filename: str
Filename of the file containing the results.
Returns
-------
data: structured array
Array with all the results.
"""
with tomso_open(filename, 'rb') as f:
lines = [line.replace(b'D', b'E') for line in f.readlines()]
# the last column results for `search_type = simplex` fits have a
# nameless column that says what kind of simplex step was taken.
# we have to give it a name ourselves
names = [name.decode('utf-8') for name in lines[1].split()]
N_columns = len(lines[2].split())
if len(names) == N_columns - 1:
names.append('step_type')
data = np.genfromtxt(lines[2:-4], dtype=None, names=names)
return data
def load_profile(filename):
"""Reads a MESA profile and returns the global data and profile
data in two structured arrays. Uses builtin `gzip` module to read
files ending with `.gz`.
Parameters
----------
filename: str
Filename of the MESA profile to load.
Returns
-------
header: structured array
Global data for the stellar model. e.g. total mass, luminosity.
The keys for the array are the MESA variable names as in
`profile.columns`.
data: structured array
Profile data for the stellar model. e.g. radius, pressure.
The keys for the array are the MESA variable names as in
`profile.columns`.
"""
with tomso_open(filename, 'rb') as f:
lines = f.readlines()
header = np.genfromtxt(lines[1:3], names=True)
data = np.genfromtxt(lines[5:], names=True)
return header, data
def load_history(filename):
"""Reads a MESA history file and returns the global data and history
data in two structured arrays. Uses builtin `gzip` module to read
files ending with `.gz`.
Parameters
----------
filename: str
Filename of the MESA history file to load.
Returns
-------
header: structured array
Global data for the evolutionary run. e.g. initial parameters.
The keys for the array are the MESA variable names as in
`history.columns`.
data: structured array
History data for the run. e.g. age, effective temperature.
The keys for the array are the MESA variable names as in
`history.columns`.
"""
with tomso_open(filename, 'rb') as f:
lines = f.readlines()
header = np.genfromtxt(lines[1:3], names=True)
data = np.genfromtxt(lines[5:], names=True)
return header, data
def load_mode(filename):
"""Reads a GYRE mode file and returns the global data and mode profile
data in two structured arrays. Uses builtin `gzip` module to read
files ending with `.gz`.
Parameters
----------
filename: str
Filename of the GYRE mode file to load.
Returns
-------
header: structured array
Global data for the frequency calculation. e.g. initial parameters.
The keys for the array are the GYRE variable names as in
the ``&output`` namelist in the GYRE input file.
data: structured array
Mode data for the frequency calculation. e.g. mode frequencies.
The keys for the array are the GYRE variable names as in
the ``&output`` namelist in the GYRE input file.
"""
with tomso_open(filename, 'rb') as f:
lines = f.readlines()
# catch case of no global data
if lines[1] == '\n':
header = []
else:
header = np.genfromtxt(lines[2:4], names=True)
data = np.genfromtxt(lines[5:], names=True)
return header, data
def load_sample(filename):
"""Reads a MESA sample file that describes a model from one of the
optimization routines in the `astero` module.
Parameters
----------
filename: str
Filename of the file containing the result.
Returns
-------
d: dict
A dictionary containing all the results.
"""
with tomso_open(filename, 'rb') as f:
# lines = [line.split() for line in f.read().decode('utf-8').split('\n')
# if line.strip()]
lines = [
line.decode('utf-8').split() for line in f.readlines()
if line.strip()
]
d = {}
ell = 0
for line in lines:
if line[0][:2] == 'l=':
ell = int(line[0][-1])
d['l%i' % ell] = {
'n': [],
'chi2': [],
'mdl': [],
'cor': [],
'obs': [],
'err': [],
'logE': []
}
elif len(line) == 7:
d['l%i' % ell]['n'].append(int(line[0]))
d['l%i' % ell]['chi2'].append(float(line[1]))
d['l%i' % ell]['mdl'].append(float(line[2]))
d['l%i' % ell]['cor'].append(float(line[3]))
d['l%i' % ell]['obs'].append(float(line[4]))
d['l%i' % ell]['err'].append(float(line[5]))
d['l%i' % ell]['logE'].append(float(line[6]))
else:
key = ''.join([word + ' ' for word in line[:-1]])[:-1]
# if key == 'mass/Msun':
# key = 'initial mass'
value = float(line[-1].replace('D', 'e'))
d[key] = value
return d
def load_gyre(filename):
"""Reads a GYRE stellar model file and returns the global data and
point-wise data in a pair of NumPy record arrays. Uses builtin
`gzip` module to read files ending with `.gz`.
Parameters
----------
filename: str
Filename of the GYRE file.
Returns
-------
header: structured array
Global data for the stellar model. e.g. total mass, luminosity.
data: structured array
Profile data for the stellar model. e.g. radius, pressure.
"""
def replace(s):
# handles annoying Fortran formatting
t = s[:]
t = t.replace(b'D', b'E')
t = t.replace(b'+', b'E+')
t = t.replace(b'-', b'E-')
t = t.replace(b'EE', b'E')
t = t.replace(b' E-', b' -')
return t
with tomso_open(filename, 'rb') as f:
lines = [replace(line) for line in f.readlines()]
header_length = len(lines[0].split())
if header_length == 4:
version = 1
elif header_length == 5:
version = int(lines[0].split()[-1])
else:
raise ValueError("header should have 4 or 5 components but "
"it appears to have %i" % header_length)
header = np.loadtxt(lines[:1], dtype=gyre_header_dtypes[version])
data = np.loadtxt(lines[1:], dtype=gyre_data_dtypes[version])
return header, data
def load_summary(filename):
"""Reads a GYRE summary file and returns the global data and mode data
in two structured arrays. Uses builtin `gzip` module to read
files ending with `.gz`.
Parameters
----------
filename: str
Filename of the GYRE summary file to load.
Returns
-------
header: structured array
Global data for the frequency calculation. e.g. initial parameters.
The keys for the array are the GYRE variable names as in
the ``&output`` namelist in the GYRE input file.
data: structured array
Mode data for the frequency calculation. e.g. mode frequencies.
The keys for the array are the GYRE variable names as in
the ``&output`` namelist in the GYRE input file.
"""
with tomso_open(filename, 'rb') as f:
lines = f.readlines()
# catch case of no global data
# just try to load header and give up on failure
try:
header = np.genfromtxt(lines[2:4], names=True)
except IndexError:
header = None
data = np.genfromtxt(lines[5:], names=True)
return header, data