def test_interestingness_1_2_0(global_var):
from lux.vis.Vis import Vis
from lux.vis.Vis import Clause
from lux.interestingness.interestingness import interestingness
df = pytest.car_df
y_clause = Clause(attribute="Name", channel="y")
color_clause = Clause(attribute="Cylinders", channel="color")
new_vis = Vis([y_clause, color_clause])
new_vis.refresh_source(df)
new_vis
# assert(len(new_vis.data)==color_cardinality*group_by_cardinality)
assert interestingness(new_vis, df) < 0.01
def test_interestingness_1_2_0():
from lux.vis.Vis import Vis
from lux.vis.Vis import Clause
from lux.interestingness.interestingness import interestingness
df = pd.read_csv("lux/data/car.csv")
y_clause = Clause(attribute = "Name", channel = "y")
color_clause = Clause(attribute = 'Cylinders', channel = "color")
new_vis = Vis([y_clause, color_clause])
new_vis.refresh_source(df)
new_vis
#assert(len(new_vis.data)==color_cardinality*group_by_cardinality)
assert(interestingness(new_vis, df)<0.01)
def test_refresh_inplace():
df = pd.DataFrame({
'date': ['2020-01-01', '2020-02-01', '2020-03-01', '2020-04-01'],
'value': [10.5, 15.2, 20.3, 25.2]
})
assert df.data_type['nominal'][0] == 'date'
from lux.vis.Vis import Vis
vis = Vis(["date", "value"], df)
df['date'] = pd.to_datetime(df['date'], format="%Y-%m-%d")
assert df.data_type['temporal'][0] == 'date'
vis.refresh_source(df)
assert vis.mark == "line"
assert vis.get_attr_by_channel("x")[0].attribute == "date"
assert vis.get_attr_by_channel("y")[0].attribute == "value"
def test_colored_bar_chart():
from lux.vis.Vis import Vis
from lux.vis.Vis import Clause
df = pd.read_csv("lux/data/car.csv")
x_clause = Clause(attribute="MilesPerGal", channel="x")
y_clause = Clause(attribute="Origin", channel="y")
color_clause = Clause(attribute='Cylinders', channel="color")
new_vis = Vis([x_clause, y_clause, color_clause])
new_vis.refresh_source(df)
#make sure dimention of the data is correct
color_cardinality = len(df.unique_values['Cylinders'])
group_by_cardinality = len(df.unique_values['Origin'])
assert (len(new_vis.data.columns) == 3)
assert (
len(new_vis.data) == 15 > group_by_cardinality <
color_cardinality * group_by_cardinality
) # Not color_cardinality*group_by_cardinality since some combinations have 0 values
def test_colored_line_chart():
from lux.vis.Vis import Vis
from lux.vis.Vis import Clause
df = pd.read_csv("lux/data/car.csv")
df["Year"] = pd.to_datetime(
df["Year"],
format='%Y') # change pandas dtype for the column "Year" to datetype
x_clause = Clause(attribute="Year", channel="x")
y_clause = Clause(attribute="MilesPerGal", channel="y")
color_clause = Clause(attribute='Cylinders', channel="color")
new_vis = Vis([x_clause, y_clause, color_clause])
new_vis.refresh_source(df)
#make sure dimention of the data is correct
color_cardinality = len(df.unique_values['Cylinders'])
group_by_cardinality = len(df.unique_values['Year'])
assert (len(new_vis.data.columns) == 3)
assert (
len(new_vis.data) == 60 > group_by_cardinality <
color_cardinality * group_by_cardinality
) # Not color_cardinality*group_by_cardinality since some combinations have 0 values
def test_refresh_inplace():
df = pd.DataFrame({
'date': ['2020-01-01', '2020-02-01', '2020-03-01', '2020-04-01'],
'value': [10.5, 15.2, 20.3, 25.2]
})
with pytest.warns(
UserWarning,
match="Lux detects that the attribute 'date' may be temporal."):
df._repr_html_()
assert df.data_type_lookup["date"] == "temporal"
from lux.vis.Vis import Vis
vis = Vis(["date", "value"], df)
df['date'] = pd.to_datetime(df['date'], format="%Y-%m-%d")
df.maintain_metadata()
assert df.data_type['temporal'][0] == 'date'
vis.refresh_source(df)
assert vis.mark == "line"
assert vis.get_attr_by_channel("x")[0].attribute == "date"
assert vis.get_attr_by_channel("y")[0].attribute == "value"
def test_refresh_inplace():
df = pd.DataFrame(
{
"date": ["2020-01-01", "2020-02-01", "2020-03-01", "2020-04-01"],
"value": [10.5, 15.2, 20.3, 25.2],
}
)
with pytest.warns(UserWarning, match="Lux detects that the attribute 'date' may be temporal."):
df._ipython_display_()
assert df.data_type["date"] == "temporal"
from lux.vis.Vis import Vis
vis = Vis(["date", "value"], df)
df["date"] = pd.to_datetime(df["date"], format="%Y-%m-%d")
df.maintain_metadata()
inverted_data_type = lux.config.executor.invert_data_type(df.data_type)
assert inverted_data_type["temporal"][0] == "date"
vis.refresh_source(df)
assert vis.mark == "line"
assert vis.get_attr_by_channel("x")[0].attribute == "date"
assert vis.get_attr_by_channel("y")[0].attribute == "value"
