def test_cast_list_of_list_to_sa1(self):
test = [[1,2.,'a'],[2,4.,'b'],[4,5.,'g']]
names = ['ints','floats','strings']
correct_1 = np.array([(1, 2.0, 'a'), (2, 4.0, 'b'), (4, 5.0, 'g')],dtype=[('f0', '<i8'), ('f1', '<f8'), ('f2', 'S1')])
correct_2 = np.array([(1, 2.0, 'a'), (2, 4.0, 'b'), (4, 5.0, 'g')], dtype=[('ints', '<i8'), ('floats', '<f8'), ('strings', 'S1')])
self.assertTrue(np.array_equal(correct_1, utils.cast_list_of_list_to_sa(test)))
self.assertTrue(np.array_equal(correct_2, utils.cast_list_of_list_to_sa(test, names)))
def test_cast_list_of_list_to_sa2(self):
L = [[None, None, None],
['a', 5, None],
['ab', 'x', None]]
ctrl = np.array(
[('', '', ''),
('a', '5', ''),
('ab', 'x', '')],
dtype=[('f0', 'S2'),
('f1', 'S1'),
('f2', 'S1')])
conv = utils.cast_list_of_list_to_sa(L)
self.assertTrue(np.array_equal(conv, ctrl))
L = [[None, u'\u05dd\u05d5\u05dc\u05e9', 4.0, 7],
[2, 'hello', np.nan, None],
[4, None, None, 14L]]
ctrl = np.array(
[(-999, u'\u05dd\u05d5\u05dc\u05e9', 4.0, 7),
(2, u'hello', np.nan, -999L),
(4, u'', np.nan, 14L)],
dtype=[('int', int), ('ucode', 'U5'), ('float', float),
('long', long)])
conv = utils.cast_list_of_list_to_sa(
L,
col_names=['int', 'ucode', 'float', 'long'])
self.assertTrue(uft.array_equal(ctrl, conv))
def test_col_fewer_than_n_nonzero(self):
M = cast_list_of_list_to_sa(
[[0,2,3], [0,3,4], [1,4,5]],
col_names=['height','weight', 'age'])
arguments = [{'func': col_fewer_than_n_nonzero, 'vals': 2}]
M = remove_cols_where(M, arguments)
correct = cast_list_of_list_to_sa(
[[2,3], [3,4], [4,5]],
col_names=['weight', 'age'])
self.assertTrue(np.array_equal(M, correct))
def test_col_val_eq_any(self):
M = cast_list_of_list_to_sa(
[[1,2,3], [1,3,4], [1,4,5]],
col_names=['height','weight', 'age'])
arguments = [{'func': col_val_eq_any, 'vals': None}]
M = remove_cols_where(M, arguments)
correct = cast_list_of_list_to_sa(
[[2,3], [3,4], [4,5]],
col_names=['weight', 'age'])
self.assertTrue(np.array_equal(M, correct))
def test_col_fewer_than_n_nonzero(self):
M = cast_list_of_list_to_sa(
[[0,2,3], [0,3,4], [1,4,5]],
col_names=['height','weight', 'age'])
arguments = [{'func': col_fewer_than_n_nonzero, 'vals': 2}]
M = remove_cols_where(M, arguments)
correct = cast_list_of_list_to_sa(
[[2,3], [3,4], [4,5]],
col_names=['weight', 'age'])
self.assertTrue(np.array_equal(M, correct))
def test_col_val_eq_any(self):
M = cast_list_of_list_to_sa(
[[1,2,3], [1,3,4], [1,4,5]],
col_names=['height','weight', 'age'])
arguments = [{'func': col_val_eq_any, 'vals': None}]
M = remove_cols_where(M, arguments)
correct = cast_list_of_list_to_sa(
[[2,3], [3,4], [4,5]],
col_names=['weight', 'age'])
self.assertTrue(np.array_equal(M, correct))
def add_legend(self):
"""
Adds a legend that shows which trial number in a summary graph
corresponds to which Trial
"""
if self.__exp is None:
raise ReportError('No experiment provided for this report. '
'Cannot add legend.')
list_of_tuple = [(str(i), str(trial)) for i, trial in
enumerate(self.__exp.trials)]
table = cast_list_of_list_to_sa(list_of_tuple, col_names=('Id', 'Trial'))
# display 10 at a time to give pdfkit an easier time with page breaks
start_row = 0
n_trials = len(list_of_tuple)
while start_row < n_trials:
self.add_table(table[start_row:start_row+9])
start_row += 9
def add_legend(self):
"""
Adds a legend that shows which trial number in a summary graph
corresponds to which Trial
"""
if self.__exp is None:
raise ReportError('No experiment provided for this report. '
'Cannot add legend.')
list_of_tuple = [(str(i), str(trial))
for i, trial in enumerate(self.__exp.trials)]
table = cast_list_of_list_to_sa(list_of_tuple,
col_names=('Id', 'Trial'))
# display 10 at a time to give pdfkit an easier time with page breaks
start_row = 0
n_trials = len(list_of_tuple)
while start_row < n_trials:
self.add_table(table[start_row:start_row + 9])
start_row += 9
def test_remove_rows_where(self):
M = [[1,2,3], [2,3,4], [3,4,5]]
col_names = ['heigh','weight', 'age']
lables= [0,0,1]
M = diogenes.utils.cast_list_of_list_to_sa(
M,
col_names=col_names)
arguments = [{'func': row_val_eq, 'col_name': 'heigh', 'vals': 1},
{'func': row_val_lt, 'col_name': 'weight', 'vals': 3},
{'func': row_val_between, 'col_name': 'age', 'vals':
(3, 4)}]
res = remove_rows_where(
M,
arguments)
ctrl = cast_list_of_list_to_sa([[2,3,4],[3,4,5]],col_names=['heigh','weight', 'age'])
self.assertTrue(np.array_equal(res, ctrl))
