try:
# framework is running
from .startup_choice import *
except ImportError as _excp:
# class is imported by itself
if (
'attempted relative import with no known parent package' in str(_excp)
or 'No module named \'omfit_classes\'' in str(_excp)
or "No module named '__main__.startup_choice'" in str(_excp)
):
from startup_choice import *
else:
raise
from omfit_classes.omfit_ascii import OMFITascii
import numpy as np
__all__ = ['OMFITcsv']
_defaults = {
'delimiter': None,
'comments': ['#', '!', '%'],
'fmt': '%.18e',
'missing_values': ['nan', 'NAN', "N/A", "???"],
'filling_values': np.nan,
}
[docs]class OMFITcsv(SortedDict, OMFITascii):
r"""
OMFIT class used to interface with Comma Separated Value files
This class makes use of the np.genfromtxt and np.savetxt methods http://docs.scipy.org/doc/np/user/basics.io.genfromtxt.html
:param filename: filename passed to OMFITascii class
:param delimiter: delimiter character that is used to separate the values
:param comments: charachter or list of characters that will be recognized as comments
:param fmt: format used to save the data to file
:param missing_values: The set of strings corresponding to missing data
:param filling_values: The set of values to be used as default when the data are missing
:param \**kw: keyword dictionary passed to OMFITascii class
"""
def __init__(
self,
filename,
delimiter=_defaults['delimiter'],
comments=_defaults['comments'],
fmt=_defaults['fmt'],
missing_values=_defaults['missing_values'],
filling_values=_defaults['filling_values'],
**kw,
):
OMFITascii.__init__(self, filename, **kw)
SortedDict.__init__(self)
if delimiter == ' ':
delimiter = None
for k in _defaults:
self.OMFITproperties.setdefault(k, eval(k))
self.dynaLoad = True
[docs] @dynaLoad
def load(self):
"""
Method used to load the content of the file specified in the .filename attribute
:return: None
"""
with open(self.filename, 'r') as f:
lines = f.read()
# try to find out what is the comment used
# and use pound as the default comment style
if not isinstance(self.OMFITproperties['comments'], str):
for comment in self.OMFITproperties['comments']:
if comment in lines:
self.OMFITproperties['comments'] = comment
break
if not isinstance(self.OMFITproperties['comments'], str):
self.OMFITproperties['comments'] = self.OMFITproperties['comments'][0]
self['data'] = np.array([])
try:
self['data'] = np.genfromtxt(
self.filename,
delimiter=self.OMFITproperties['delimiter'],
comments=self.OMFITproperties['comments'],
missing_values=self.OMFITproperties['missing_values'],
filling_values=self.OMFITproperties['filling_values'],
invalid_raise=True,
)
except Exception as _excp:
try:
tmpFile = []
other = []
nonochar = re.sub(r'[0-9\n\r\+-\. \teEdD' + re.escape(self.OMFITproperties['delimiter']) + ']', '', string.printable)
with open(self.filename, 'r') as f:
for line in f.readlines():
if re.search('[' + nonochar + ']', line) is None:
tmpFile.append(line)
else:
other.append(line)
tmp = OMFITascii('')
with open(tmp.filename, 'w') as f:
f.writelines(tmpFile)
try:
self['data'] = np.genfromtxt(
tmp.filename,
delimiter=self.OMFITproperties['delimiter'],
missing_values=self.OMFITproperties['missing_values'],
filling_values=self.OMFITproperties['filling_values'],
invalid_raise=True,
)
except Exception:
self['data'] = np.genfromtxt(
tmp.filename,
delimiter=self.OMFITproperties['delimiter'],
skip_header=1,
missing_values=self.OMFITproperties['missing_values'],
filling_values=self.OMFITproperties['filling_values'],
invalid_raise=True,
)
with open(tmp.filename, 'r') as f:
header = f.readline()
with open(tmp.filename, 'w') as f:
f.writelines(header)
self['header'] = np.genfromtxt(
tmp.filename,
delimiter=self.OMFITproperties['delimiter'],
missing_values=self.OMFITproperties['missing_values'],
filling_values=self.OMFITproperties['filling_values'],
invalid_raise=True,
)
self['other'] = other
except Exception:
self['data'] = np.genfromtxt(
self.filename,
delimiter=self.OMFITproperties['delimiter'],
comments=self.OMFITproperties['comments'],
missing_values=self.OMFITproperties['missing_values'],
filling_values=self.OMFITproperties['filling_values'],
invalid_raise=False,
)
self['data'] = np.atleast_2d(self['data'])
# if there is no delimiter, then it's a vertical array and data should be transposed
if (self.OMFITproperties['delimiter'] is None and ' ' not in lines) or (
self.OMFITproperties['delimiter'] is not None and self.OMFITproperties['delimiter'] not in lines
):
self['data'] = self['data'].T
[docs] @dynaSave
def save(self):
"""
Method used to save the content of the object to the file specified in the .filename attribute
:return: None
"""
if self.OMFITproperties['delimiter'] is None:
np.savetxt(self.filename, self['data'], fmt=self.OMFITproperties['fmt'])
else:
np.savetxt(self.filename, self['data'], delimiter=self.OMFITproperties['delimiter'], fmt=self.OMFITproperties['fmt'])
def __save_kw__(self):
"""
:return: kw dictionary used to save the attributes to be passed when reloading from OMFITsave.txt
"""
tmp = self.OMFITproperties.copy()
for k in _defaults:
if self.OMFITproperties[k] is _defaults[k] or self.OMFITproperties[k] == _defaults[k]:
tmp.pop(k)
return tmp
