def test_same_value_filter_instance(self):
inst = self.table[0]
filter_ = SameValue(self.attr_disc, self.value_disc)(inst)
self.assertEqual(filter_, inst[self.attr_disc] == self.value_disc)
filter_n = SameValue(self.attr_disc, self.value_disc, negate=True)(inst)
self.assertEqual(filter_n, inst[self.attr_disc] != self.value_disc)
def test_create_groups_table_include_unselected(self):
group_indices = random.sample(range(0, len(self.zoo)), 20)
selection = np.zeros(len(self.zoo), dtype=np.uint8)
selection[group_indices[:10]] = 1
selection[group_indices[10:]] = 2
table = create_groups_table(self.zoo, selection)
self.assertEqual(
len(SameValue(table.domain["Selected"], "Unselected")(table)),
len(self.zoo) - len(group_indices))
def test_same_value_filter_table(self):
test_pairs = (
(self.attr_cont, 4, self.value_cont),
(self.attr_disc, "mammal", self.value_disc),
(self.attr_meta, "girl", self.value_meta),
)
for var_index, value, num_value in test_pairs:
filter_ = SameValue(var_index, value)(self.table)
self.assertTrue(
all(inst[var_index] == num_value for inst in filter_))
filter_inverse = SameValue(var_index, value,
negate=True)(self.table)
self.assertTrue(
all(inst[var_index] != num_value for inst in filter_inverse))
self.assertEqual(
len(filter_) + len(filter_inverse), len(self.table))
for t1, t2 in itertools.combinations(test_pairs, 2):
pos1, val1, r1 = t1
pos2, val2, r2 = t2
filter_1 = SameValue(pos1, val1)(self.table)
filter_2 = SameValue(pos2, val2)(self.table)
filter_12 = SameValue(pos2, val2)(SameValue(pos1,
val1)(self.table))
filter_21 = SameValue(pos1, val1)(SameValue(pos2,
val2)(self.table))
self.assertEqual(len(filter_21), len(filter_12))
self.assertTrue(len(filter_1) >= len(filter_12))
self.assertTrue(len(filter_2) >= len(filter_12))
self.assertTrue(
all(inst[pos1] == r1 and inst[pos2] == r2 and inst in filter_21
for inst in filter_12))
self.assertTrue(
all(inst[pos1] == r1 and inst[pos2] == r2 and inst in filter_12
for inst in filter_21))
def test_reprs(self):
flid = IsDefined(negate=True)
flhc = HasClass()
flr = Random()
fld = FilterDiscrete(self.attr_disc, None)
flsv = SameValue(self.attr_disc, self.value_disc, negate=True)
flc = FilterContinuous(self.vs[0], FilterContinuous.Less, 5)
flc2 = FilterContinuous(self.vs[1], FilterContinuous.Greater, 3)
flv = Values([flc, flc2], conjunction=False, negate=True)
flvf = ValueFilter(self.attr_disc)
fls = FilterString("name", FilterString.Equal, "Aardvark", case_sensitive=False)
flsl = FilterStringList("name", ["Aardvark"], case_sensitive=False)
flrx = FilterRegex("name", "^c...$")
filters = [flid, flhc, flr, fld, flsv, flc, flv, flvf, fls, flsl, flrx]
for f in filters:
repr_str = repr(f)
new_f = eval(repr_str)
self.assertEqual(repr(new_f), repr_str)
def commit(self):
averages = None
if self.data is not None:
if self.group_var is None:
averages = self.average_table(self.data)
else:
parts = []
for value in self.group_var.values:
svfilter = SameValue(self.group_var, value)
v_table = self.average_table(svfilter(self.data))
parts.append(v_table)
# Using "None" as in OWSelectRows
# Values is required because FilterDiscrete doesn't have
# negate keyword or IsDefined method
deffilter = Values(
conditions=[FilterDiscrete(self.group_var, None)],
negate=True)
v_table = self.average_table(deffilter(self.data))
parts.append(v_table)
averages = Orange.data.Table.concatenate(parts, axis=0)
self.Outputs.averages.send(averages)