class DictAccessorTests(unittest.TestCase):
a = np.arange(10)
b = np.arange(10)
array_dict = {"a": a, "b": b}
data = df.Dataframe(array_dict)
def testSetNewItemCorrect(self):
"""Make sure the item set to a new key matches the item held in the data frame"""
c = np.arange(10)
c = c + 10
self.data['c'] = c
self.assertEqual(c.all(), self.data['c'].all())
def testSetItemBadInputType(self):
"""A new column must be a numpy array"""
c = "fart"
self.assertRaises(df.dfException, self.data.__setitem__, 'c', c)
def testSetItemBadInputLength(self):
"""A new column must be the right length"""
c = np.arange(2)
self.assertRaises(df.dfException, self.data.__setitem__, 'c', c)
#consider tests for when you try to set an EXISTING column
def testSetExistingItemCorrect(self):
"""A replacement for an existing column must equal the np array replacing it"""
c = np.arange(10)
c = c + 10
self.data['b'] = c
self.assertEqual(c.all(), self.data['b'].all())
def testGetItemCorrect(self):
"""The data returned by __getdata__ must match the actual data"""
self.assertEqual(self.data.data['a'].all(), self.data['a'].all())
def testAppendedRowCorrect(self):
"""The appended row must match the row that was passed to Dataframe.append()"""
data = df.Dataframe(self.array_dict)
new_row = {"a": 2, "b": 3}
data.append(new_row)
for key, value in data.data.items():
self.assertEqual(data[key][-1], new_row[key])
def testColNumsIntialized(self):
"""When initialized with an array_dict, the proper number of columns should be listed"""
a = np.arange(10)
b = np.arange(10) + 2
array_dict = {"a": a, "b": b}
data = df.Dataframe(array_dict)
self.assertEqual(data.numcols(), 2)
def testBadRowInputType(self):
"""Type mismatch between append argument and numpy array must raise exception"""
a = np.arange(10)
b = np.arange(10)
array_dict = {"a": a, "b": b}
data = df.Dataframe(array_dict)
new_row = {"a": "f", "b": "u"}
self.assertRaises(df.dfException, data.append, new_row)
def testBadRowKeys(self):
"""Having a mismatch in keys should raise an error"""
a = np.arange(10)
b = np.arange(10)
array_dict = {"a": a, "b": b}
data = df.Dataframe(array_dict)
new_row = {"a": 2, "f": 4}
self.assertRaises(df.dfException, data.append, new_row)
def testCorrectInitialization(self):
"""The data in the data frame should match the data in the array_dict"""
a = np.arange(100)
b = np.arange(100)
b = b + 10
array_dict = {"item1": a, "item2": b}
frame = df.Dataframe(array_dict=array_dict)
for key, value in frame.data.items():
self.assertEqual(frame.data[key].all(), array_dict[key].all())
def _load_timeseries_data(self):
self.gts = df.Dataframe()
self.gts.SQL_load_data(
self.interface_proc,
'gas_proc_data_tbl',
conditions=[
"timestamp >= '%s'" % self.run_info.info['ss_start'],
"timestamp < '%s'" % self.run_info.info['ss_stop']
]) #This line needs to automatically load the units
def testNewRowNumber(self):
"""After append, the dataframe must have the right number of rows"""
a = np.arange(10)
b = np.arange(10)
array_dict = {"a": a, "b": b}
data = df.Dataframe(array_dict)
new_row = {"a": 2, "b": 3}
data.append(new_row)
for key, value in data.data.items():
self.assertEqual(data.nRows, data[key].size)
def testColNumsAfterColumnAdd(self):
"""After adding a column, the number of columns should be incremented by one"""
data = df.Dataframe(self.array_dict)
c = np.arange(10)
data['c'] = c
self.assertEqual(data.numcols(), 3)
def testColNumsEmpty(self):
"""When initialized with an empty array_dict, the proper number of columns should be listed"""
data = df.Dataframe()
self.assertEqual(data.numcols(), 0)
def testRowNumsInitialized(self):
"""When initialized with an array_dict, the proper number of rows should be listed"""
data = df.Dataframe(self.array_dict)
self.assertEqual(data.numrows(), 10)
def testRowNumsEmpty(self):
"""When array dict is empty, the number of rows should be given as zero"""
data = df.Dataframe()
self.assertEqual(data.numrows(), 0)
def testBadRowInputLength(self):
"""Having the wrong length of row to append (not enough/too many keys) should raise an error"""
data = df.Dataframe(self.array_dict)
new_row = {"a": 2}
self.assertRaises(df.dfException, data.append, new_row)