def test_stack_agg(self):
query = Query.from_vegalite({
'mark': 'bar',
'encoding': {
'x': {
'type': 'nominal',
'field': 'n1',
},
'y': {
'type': 'quantitative',
'field': 'q1',
'stack': 'zero',
'aggregate': 'sum'
},
'detail': {
'type': 'nominal',
'field': 'n2'
},
'color': {
'type': 'quantitative',
'field': 'q2',
'aggregate': 'mean'
}
}
})
assert is_valid(Task(data, query), True) == True
def __mutate_spec(self, base_spec: Spec, props: List[str], prop_index: int,
seen: Set[Spec], specs: List[Spec]):
# base case
if (prop_index == len(props)):
self.model.post_improve(base_spec, props)
base_spec['data'] = {'url': self.data_url}
# within a group, don't repeat the same specs
if not (base_spec in seen):
seen.add(base_spec)
query = Query.from_vegalite(base_spec)
if (is_valid(Task(self.data, query))):
specs.append(base_spec)
# recursive case
else:
prop_to_mutate = props[prop_index]
for enum in self.model.get_enums(prop_to_mutate):
spec = deepcopy(base_spec)
self.model.mutate_prop(spec, prop_to_mutate, enum)
# recursive call
self.__mutate_spec(spec, props, prop_index + 1, seen, specs)
return
def test_is_valid():
data = Data(fields=[Field('foo', 'number')])
invalid = Query.from_vegalite({
'mark': 'text',
'encoding': {
'x': {'field': 'foo', 'type': 'quantitative'}
}
})
assert is_valid(Task(data, invalid)) == False
valid = Query.from_vegalite({
'mark': 'point',
'encoding': {
'x': {'field': 'foo', 'type': 'quantitative'}
}
})
assert is_valid(Task(data, valid)) == True
def test_one_bar(self):
query = Query.from_vegalite({
'mark': 'bar',
'encoding': {
'y': {
'type': 'quantitative',
'field': 'q1'
}
}
})
assert is_valid(Task(data, query), True) == True
def test_row_only(self):
query = Query.from_vegalite({
'mark': 'point',
'encoding': {
'row': {
'type': 'nominal',
'field': 'n1'
}
}
})
assert is_valid(Task(data, query), True) == False
def test_only_one_agg(self):
query = Query.from_vegalite({
'mark': 'point',
'encoding': {
'x': {
'type': 'quantitative',
'field': 'q1'
},
'y': {
'type': 'quantitative',
'field': 'q2',
'aggregate': 'mean'
}
}
})
assert is_valid(Task(data, query), True) == False
def test_heatmap(self):
query = Query.from_vegalite({
'mark': 'rect',
'encoding': {
'x': {
'type': 'nominal',
'field': 'n1',
},
'y': {
'type': 'ordinal',
'field': 'q1',
'bin': True
}
}
})
assert is_valid(Task(data, query), True) == True
def test_hist(self):
query = Query.from_vegalite({
'mark': 'bar',
'encoding': {
'x': {
'type': 'quantitative',
'field': 'q1',
'bin': True
},
'y': {
'type': 'quantitative',
'aggregate': 'count'
}
}
})
assert is_valid(Task(data, query), True) == True
def test_scatter(self):
query = Query.from_vegalite({
'mark': 'point',
'encoding': {
'x': {
'type': 'quantitative',
'field': 'q1',
},
'y': {
'type': 'quantitative',
'field': 'q2'
},
'color': {
'type': 'nominal',
'field': 'n2'
},
'size': {
'type': 'quantitative',
'field': 'q3'
}
}
})
assert is_valid(Task(data, query), True) == True
def test_stack_q_q(self):
query = Query.from_vegalite({
'mark': 'area',
'encoding': {
'x': {
'type': 'quantitative',
'field': 'q1',
'scale': {
'zero': False
}
},
'y': {
'type': 'quantitative',
'field': 'q2',
'stack': 'zero'
},
'color': {
'type': 'nominal',
'field': 'n1'
}
}
})
assert is_valid(Task(data, query), True) == True
