def __fromfile(self, filename):
"""a private method to deduce and load a filename into a matrix object
Parameters:
----------
filename (str) : the name of the file
Returns:
-------
mat (or cov) object
"""
assert os.path.exists(filename),"LinearAnalysis.__fromfile(): " +\
"file not found:" + filename
ext = filename.split('.')[-1].lower()
if ext in ["jco", "jcb"]:
self.log("loading jco: "+filename)
m = Jco.from_binary(filename)
self.log("loading jco: "+filename)
elif ext in ["mat","vec"]:
self.log("loading ascii: "+filename)
m = Matrix.from_ascii(filename)
self.log("loading ascii: "+filename)
elif ext in ["cov"]:
self.log("loading cov: "+filename)
m = Cov.from_ascii(filename)
self.log("loading cov: "+filename)
elif ext in["unc"]:
self.log("loading unc: "+filename)
m = Cov.from_uncfile(filename)
self.log("loading unc: "+filename)
else:
raise Exception("linear_analysis.__fromfile(): unrecognized" +
" filename extension:" + str(ext))
return m
def __load_omitted_jco(self):
"""private: set the omitted jco attribute"""
if self.omitted_par_arg is None:
raise Exception("ErrVar.__load_omitted: omitted_arg is None")
if isinstance(self.omitted_par_arg, str):
if self.omitted_par_arg in self.jco.col_names:
# need to access attribute directly, not view of attribute
self.__omitted_jco = self._LinearAnalysis__jco.extract(
col_names=self.omitted_par_arg
)
else:
# must be a filename
self.__omitted_jco = self.__fromfile(self.omitted_par_arg)
# if the arg is an already instantiated Matrix (or jco) object
elif isinstance(self.omitted_par_arg, Jco) or isinstance(
self.omitted_par_arg, Matrix
):
self.__omitted_jco = Jco(
x=self.omitted_par_arg.newx(),
row_names=self.omitted_par_arg.row_names,
col_names=self.omitted_par_arg.col_names,
)
# if it is a list, then it must be a list
# of parameter names in self.jco
elif isinstance(self.omitted_par_arg, list):
for arg in self.omitted_par_arg:
if isinstance(arg, str):
assert arg in self.jco.col_names, (
"ErrVar.__load_omitted_jco: omitted_jco "
+ "arg str not in jco par_names: "
+ str(arg)
)
self.__omitted_jco = self._LinearAnalysis__jco.extract(
col_names=self.omitted_par_arg
)
def __fromfile(self, filename):
"""a private method to deduce and load a filename into a matrix object
Parameters:
----------
filename (str) : the name of the file
Returns:
-------
mat (or cov) object
"""
assert os.path.exists(filename),"LinearAnalysis.__fromfile(): " +\
"file not found:" + filename
ext = filename.split('.')[-1].lower()
if ext in ["jco", "jcb"]:
self.log("loading jco: " + filename)
m = Jco.from_binary(filename)
self.log("loading jco: " + filename)
elif ext in ["mat", "vec"]:
self.log("loading ascii: " + filename)
m = Matrix.from_ascii(filename)
self.log("loading ascii: " + filename)
elif ext in ["cov"]:
self.log("loading cov: " + filename)
m = Cov.from_ascii(filename)
self.log("loading cov: " + filename)
elif ext in ["unc"]:
self.log("loading unc: " + filename)
m = Cov.from_uncfile(filename)
self.log("loading unc: " + filename)
else:
raise Exception("linear_analysis.__fromfile(): unrecognized" +
" filename extension:" + str(ext))
return m