def test_missing(self):
fm = FeatureMatrix('test',self.missing_info)
self.assertEqual(fm.features, ['feature1','feature2'])
self.assertEqual(fm.possible_values,{'+','-'})
#Error, there should be a default default value?
fm.validate()
def test_missing(self):
fm = FeatureMatrix('test', self.missing_info)
self.assertEqual(fm.features, ['feature1', 'feature2'])
self.assertEqual(fm.possible_values, {'+', '-'})
#Error, there should be a default default value?
fm.validate()
def load_feature_matrix_csv(name, path, delimiter, stop_check = None, call_back = None):
"""
Load a FeatureMatrix from a column-delimited text file
Parameters
----------
name : str
Informative identifier to refer to feature system
path : str
Full path to text file
delimiter : str
Character to use for spliting lines into columns
stop_check : callable, optional
Optional function to check whether to gracefully terminate early
call_back : callable, optional
Optional function to supply progress information during the function
Returns
-------
FeatureMatrix
FeatureMatrix generated from the text file
"""
text_input = []
with open(path, encoding='utf-8-sig', mode='r') as f:
reader = DictReader(f, delimiter = delimiter)
lines = list(reader)
if call_back is not None:
call_back('Reading file...')
call_back(0, len(lines))
for i, line in enumerate(lines):
if stop_check is not None and stop_check():
return
if call_back is not None:
call_back(i)
if line:
if len(line.keys()) == 1:
raise(DelimiterError)
if 'symbol' not in line:
raise(KeyError)
#Compat
newline = {}
for k,v in line.items():
if k == 'symbol':
newline[k] = v
elif v is not None:
newline[k] = v[0]
text_input.append(newline)
feature_matrix = FeatureMatrix(name,text_input)
feature_matrix.validate()
return feature_matrix
def load_feature_matrix_csv(name, path, delimiter, stop_check = None, call_back = None):
"""
Load a FeatureMatrix from a column-delimited text file
Parameters
----------
name : str
Informative identifier to refer to feature system
path : str
Full path to text file
delimiter : str
Character to use for spliting lines into columns
stop_check : callable, optional
Optional function to check whether to gracefully terminate early
call_back : callable, optional
Optional function to supply progress information during the function
Returns
-------
FeatureMatrix
FeatureMatrix generated from the text file
"""
text_input = []
with open(path, encoding='utf-8-sig', mode='r') as f:
reader = DictReader(f, delimiter = delimiter)
lines = list(reader)
if call_back is not None:
call_back('Reading file...')
call_back(0, len(lines))
for i, line in enumerate(lines):
if stop_check is not None and stop_check():
return
if call_back is not None:
call_back(i)
if line:
if len(line.keys()) == 1:
raise(DelimiterError)
if 'symbol' not in line:
raise(KeyError)
#Compat
newline = {}
for k,v in line.items():
if k == 'symbol':
newline[k] = v
elif v is not None:
newline[k] = v[0]
text_input.append(newline)
feature_matrix = FeatureMatrix(name,text_input)
feature_matrix.validate()
return feature_matrix
def test_missing_with_default(self):
fm = FeatureMatrix('test',self.missing_with_default_info)
self.assertEqual(fm.features, ['feature1','feature2'])
self.assertEqual(fm.possible_values,{'+','-','n'})
fm.validate()
self.assertEqual(fm['b','feature2'], 'n')
def test_missing_with_default(self):
fm = FeatureMatrix('test', self.missing_with_default_info)
self.assertEqual(fm.features, ['feature1', 'feature2'])
self.assertEqual(fm.possible_values, {'+', '-', 'n'})
fm.validate()
self.assertEqual(fm['b', 'feature2'], 'n')
