def test_stack_agg(self):
query = vl2asp({
"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(data_schema + query, True) == True
def main(): # pragma: no cover
parser = create_parser()
args = parser.parse_args()
if args.mode != Mode.optimize and (
args.type == QueryType.draco or args.type == QueryType.cql
):
print("Validation only works with full specs.", sys.stderr)
else:
logger.info(f"Processing query: {args.query.name} ...")
if args.type == QueryType.asp:
draco_query = args.query.read().split("\n")
else:
query_spec = json.load(args.query)
if args.type == QueryType.vl:
draco_query = vl2asp(query_spec)
elif args.type == QueryType.cql:
draco_query = cql2asp(query_spec)
print(draco_query)
if args.mode == Mode.violations:
result = run(
draco_query,
debug=args.debug,
files=["define.lp", "hard.lp", "soft.lp", "output.lp"],
silence_warnings=True,
)
if result:
print(result.violations, file=args.out)
elif args.mode == Mode.valid:
result = run(
draco_query,
debug=args.debug,
files=["define.lp", "hard.lp", "output.lp"],
silence_warnings=True,
)
print("valid" if result else "invalid", file=args.out)
elif args.mode == Mode.optimize:
result = run(draco_query, debug=args.debug)
if result:
print(json.dumps(result.as_vl()), file=args.out)
logger.info(f"Cost: {result.cost}")
outname = (
"stringIO" if isinstance(args.out, io.StringIO) else args.out.name
)
logger.info(f"Wrote Vega-Lite spec to {outname}")
# close open files
if args.query is not sys.stdin:
args.query.close()
if args.out is not sys.stdout:
args.out.close()
def test_one_bar(self):
query = vl2asp({
"mark": "bar",
"encoding": {
"y": {
"type": "quantitative",
"field": "q1"
}
}
})
assert is_valid(data_schema + query, True) == True
def test_row_only(self):
query = vl2asp({
"mark": "point",
"encoding": {
"row": {
"type": "nominal",
"field": "n1"
}
}
})
assert is_valid(data_schema + query, True) == False
def test_q_q_bar(self):
query = vl2asp({
"mark": "bar",
"encoding": {
"x": {
"type": "quantitative",
"field": "q1"
},
"y": {
"type": "quantitative",
"field": "q2"
},
},
})
assert is_valid(data_schema + query, True) == False
def test_only_one_agg(self):
query = vl2asp({
"mark": "point",
"encoding": {
"x": {
"type": "quantitative",
"field": "q1"
},
"y": {
"type": "quantitative",
"field": "q2",
"aggregate": "mean"
},
},
})
assert is_valid(data_schema + query, True) == False
def test_heatmap(self):
query = vl2asp({
"mark": "rect",
"encoding": {
"x": {
"type": "nominal",
"field": "n1"
},
"y": {
"type": "ordinal",
"field": "q1",
"bin": True
},
},
})
assert is_valid(data_schema + query, True) == True
def test_hist(self):
query = vl2asp({
"mark": "bar",
"encoding": {
"x": {
"type": "quantitative",
"field": "q1",
"bin": True
},
"y": {
"type": "quantitative",
"aggregate": "count"
},
},
})
assert is_valid(data_schema + query, True) == True
def test_scatter(self):
query = vl2asp({
"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(data_schema + query, True) == True
def test_stack_q_q(self):
query = vl2asp({
"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(data_schema + query, True) == True
def run_spec(data_schema, spec, relax_hard=False):
query = vl2asp(spec)
return run(data_schema + query, relax_hard=relax_hard)
def run_spec(data_schema, spec):
query = vl2asp(spec)
return run(data_schema + query)
