def _check_to_int(self, x, prop):
"""check that an incoming value can be converted to an integer and returne the int version of it, or raise an error"""
if(not fields_funks._is_number(x)):
raise(EMFError("""Conductor property '%s' must be numeric. It cannot be set to: %s""" % (prop, repr(x))))
elif(int(x) != float(x)):
raise(EMFError("""Conductor property '%s' must be an integer. It cannot be set to: %s""" % (prop, repr(x))))
return(int(x))
def _write_FLD_entries(ofile, *entries):
"""format entries and writes them into a .FLD file targeted by ofile"""
for entry in entries:
if (fields_funks._is_number(entry)):
if (_is_int(entry)):
w = '{:< d} \n'.format(int(entry))
else:
w = '{:< .2f} \n'.format(float(entry))
if ('.' in w):
idx = w.index('.')
if ('0' in w[:idx]):
idx = w.index('0')
if (not fields_funks._is_number(w[idx - 1])):
w = w[:idx] + w[idx + 1:]
else:
w = str(entry) + '\n'
ofile.write(w)
def read_DAT(file_path):
"""Read a DAT file, which can have some funky extra characters if the numbers are too large (percent signs)
args:
file_path - string, path to DAT file
returns:
pandas DataFrame with 'Bx','By','Bprod','Bmax','Ex','Ey','Eprod',
and 'Emax' columns, and the distance ('x') in the index"""
#check that the target file is a DAT
fields_funks._check_extension(
file_path, 'DAT', """Input file must have a '.DAT' extension.""")
#load data
und_message = 'Electric Field cannot be computed for underground circuit'
und_only = False
with open(file_path, 'r') as ifile:
#read through the header
line = ifile.readline()
while (not ('----' in line)):
line = ifile.readline()
if (und_message in line):
und_only = True
#get the data
data = [[] for i in range(9)]
line = ifile.readline()
while (line):
if (line):
#check strange % signs printed with large numbers
if (line[0][0] == '%'):
line += ifile.readline()
l = [i.replace('%', '') for i in line.split()]
if (l and all([fields_funks._is_number(i) for i in l])):
for i in range(5):
data[i].append(float(l[i]))
if (not (und_only)):
for i in range(5, 9):
data[i].append(float(l[i]))
else:
for i in range(5, 9):
data[i].append(0.)
line = ifile.readline()
return (pd.DataFrame(data=dict(
zip(['Bx', 'By', 'Bprod', 'Bmax', 'Ex', 'Ey', 'Eprod', 'Emax'],
data[1:])),
index=data[0]))
def _check_to_float(self, value, prop):
"""check that an incoming value can be converted to a float and return the float version of it, or raise an error"""
if(not fields_funks._is_number(value)):
raise(EMFError("""Conductor property '%s' must be numeric. It cannot be set to: %s""" % (prop, repr(value))))
return(float(value))