def _matches(self, series):
equals = self._get_equals_function(series)
if len(self.as_dict) != len(series):
return False
for key in self.as_dict:
if not equals(series[key], self.as_dict[key]):
return False
return True
def _matches(self, series):
equals = self._get_equals_function(series)
if len(self.as_dict) != len(series):
return False
for key in self.as_dict:
if not equals(series[key], self.as_dict[key]):
return False
return True
def lists_match(list1, list2, places=None):
"""
Compares two lists and returns True if they are exactly the same, False
otherwise.
places: int
The number of decimal places to check when comparing data values.
Defaults to None, in which case full equality is checked (good for
ints, but not for floats).
"""
return len(list1) == len(list2) and \
all([equals(list1[i], list2[i], places=places)
for i in xrange(len(list1))])
def lists_match(list1, list2, places=None):
"""
Compares two lists and returns True if they are exactly the same, False
otherwise.
places: int
The number of decimal places to check when comparing data values.
Defaults to None, in which case full equality is checked (good for
ints, but not for floats).
"""
return len(list1) == len(list2) and \
all([equals(list1[i], list2[i], places=places)
for i in xrange(len(list1))])
def _matches(self, dataframe):
expected_num_rows = len(self.as_list)
if expected_num_rows != dataframe.shape[0]:
return False
row_lengths = map(len, self.as_list)
if len(set(row_lengths)) != 1:
# row lengths are not all the same
return False
expected_num_columns = row_lengths[0]
if expected_num_columns != dataframe.shape[1]:
return False
for i, row in enumerate(self.as_list):
actual_row = dataframe.ix[i].tolist()
for j, expected in enumerate(row):
if not equals(actual_row[j], expected, places=self.places):
return False
return True
def _matches(self, dataframe):
expected_num_rows = len(self.as_list)
if expected_num_rows != dataframe.shape[0]:
return False
row_lengths = map(len, self.as_list)
if len(set(row_lengths)) != 1:
# row lengths are not all the same
return False
expected_num_columns = row_lengths[0]
if expected_num_columns != dataframe.shape[1]:
return False
for i, row in enumerate(self.as_list):
actual_row = dataframe.ix[i].tolist()
for j, expected in enumerate(row):
if not equals(actual_row[j], expected, places=self.places):
return False
return True
def _numeric_equals(self, val1, val2):
return equals(val1, val2, self.places)
def _numeric_equals(self, val1, val2):
return equals(val1, val2, self.places)
