def test_update_list_make_copies_false(self):
trace1 = Scatter(x=[1, 2, 3], y=[2, 1, 2])
trace2 = Scatter(x=[1, 2, 3], y=[3, 2, 1])
data = Data([trace1, trace2])
update = dict(x=[2, 3, 4], y=[1, 2, 3], line=Line())
data.update(update, make_copies=False)
assert data[0]["line"] is data[1]["line"]
def test_append_scatter():
expected = Figure(
data=Data([Scatter(x=[1, 2, 3], y=[2, 3, 4], xaxis="x5", yaxis="y5")]),
layout=Layout(
xaxis1=XAxis(domain=[0.0, 0.2888888888888889], anchor="y1"),
xaxis2=XAxis(domain=[0.35555555555555557, 0.6444444444444445],
anchor="y2"),
xaxis3=XAxis(domain=[0.7111111111111111, 1.0], anchor="y3"),
xaxis4=XAxis(domain=[0.0, 0.2888888888888889], anchor="y4"),
xaxis5=XAxis(domain=[0.35555555555555557, 0.6444444444444445],
anchor="y5"),
xaxis6=XAxis(domain=[0.7111111111111111, 1.0], anchor="y6"),
yaxis1=YAxis(domain=[0.575, 1.0], anchor="x1"),
yaxis2=YAxis(domain=[0.575, 1.0], anchor="x2"),
yaxis3=YAxis(domain=[0.575, 1.0], anchor="x3"),
yaxis4=YAxis(domain=[0.0, 0.425], anchor="x4"),
yaxis5=YAxis(domain=[0.0, 0.425], anchor="x5"),
yaxis6=YAxis(domain=[0.0, 0.425], anchor="x6"),
),
)
trace = Scatter(x=[1, 2, 3], y=[2, 3, 4])
fig = tls.make_subplots(rows=2, cols=3)
fig.append_trace(trace, 2, 2)
d1, d2 = strip_dict_params(fig["data"][0], expected["data"][0])
assert d1 == d2
d1, d2 = strip_dict_params(fig["layout"], expected["layout"])
assert d1 == d2
def test_figure_json_encoding(self):
df = pd.DataFrame(columns=["col 1"], data=[1, 2, 3])
s1 = Scatter3d(x=numeric_list, y=np_list, z=mixed_list)
s2 = Scatter(x=df["col 1"])
data = Data([s1, s2])
figure = Figure(data=data)
js1 = _json.dumps(s1, cls=utils.PlotlyJSONEncoder, sort_keys=True)
js2 = _json.dumps(s2, cls=utils.PlotlyJSONEncoder, sort_keys=True)
assert (
js1 == '{"type": "scatter3d", "x": [1, 2, 3], '
'"y": [1, 2, 3, null, null, null, "2014-01-05T00:00:00"], '
'"z": [1, "A", "2014-01-05T00:00:00", '
'"2014-01-05T01:01:01", "2014-01-05T01:01:01.000001"]}'
)
assert js2 == '{"type": "scatter", "x": [1, 2, 3]}'
# Test JSON encoding works
_json.dumps(data, cls=utils.PlotlyJSONEncoder, sort_keys=True)
_json.dumps(figure, cls=utils.PlotlyJSONEncoder, sort_keys=True)
# Test data wasn't mutated
np_array = np.array([1, 2, 3, np.NaN, np.NAN, np.Inf, dt(2014, 1, 5)])
for k in range(len(np_array)):
if k in [3, 4]:
# check NaN
assert np.isnan(np_list[k]) and np.isnan(np_array[k])
else:
# non-NaN
assert np_list[k] == np_array[k]
assert set(data[0]["z"]) == set(
[
1,
"A",
dt(2014, 1, 5),
dt(2014, 1, 5, 1, 1, 1),
dt(2014, 1, 5, 1, 1, 1, 1),
]
)
def test_append_scatter3d():
expected = Figure(
data=Data([
Scatter3d(x=[1, 2, 3], y=[2, 3, 4], z=[1, 2, 3], scene="scene1"),
Scatter3d(x=[1, 2, 3], y=[2, 3, 4], z=[1, 2, 3], scene="scene2"),
]),
layout=Layout(
scene1=Scene(domain={
"y": [0.575, 1.0],
"x": [0.0, 1.0]
}),
scene2=Scene(domain={
"y": [0.0, 0.425],
"x": [0.0, 1.0]
}),
),
)
fig = tls.make_subplots(rows=2,
cols=1,
specs=[[{
"is_3d": True
}], [{
"is_3d": True
}]])
trace = Scatter3d(x=[1, 2, 3], y=[2, 3, 4], z=[1, 2, 3])
fig.append_trace(trace, 1, 1)
fig.append_trace(trace, 2, 1)
d1, d2 = strip_dict_params(fig["data"][0], expected["data"][0])
assert d1 == d2
d1, d2 = strip_dict_params(fig["data"][1], expected["data"][1])
assert d1 == d2
d1, d2 = strip_dict_params(fig["layout"], expected["layout"])
assert d1 == d2
def test_dict_instantiation_graph_obj_error_2():
assert Data([Annotations()]) == [[]]
def test_dict_instantiation_graph_obj_error_0():
assert Annotations([Data()]) == [[]]
def test_dict_instantiation_key_error_2():
assert Data([{"marker": "not-a-dict"}]) == [{"marker": "not-a-dict"}]
def test_dict_instantiation_type_error():
assert Data([{"type": "invalid_type"}]) == [{"type": "invalid_type"}]
def test_dict_instantiation_key_error():
assert Data([{"not-a-key": "anything"}]) == [{"not-a-key": "anything"}]
def test_dict_instantiation():
Data([{"type": "scatter"}])
def test_default_scatter():
assert Data([{}]) == list([{}])
def test_weird_instantiation(): # Python allows this...
assert Data({}) == []
def test_trivial():
assert Data() == list()