def test_repeat():
# wrapped repeat
chart1 = alt.Chart('data.csv').mark_point().encode(
x=alt.X(alt.repeat(), type='quantitative'),
y='y:Q',
).repeat(
['A', 'B', 'C', 'D'],
columns=2
)
dct1 = chart1.to_dict()
assert dct1['repeat'] == ['A', 'B', 'C', 'D']
assert dct1['columns'] == 2
assert dct1['spec']['encoding']['x']['field'] == {'repeat': 'repeat'}
# explicit row/col repeat
chart2 = alt.Chart('data.csv').mark_point().encode(
x=alt.X(alt.repeat('row'), type='quantitative'),
y=alt.Y(alt.repeat('column'), type='quantitative')
).repeat(
row=['A', 'B', 'C'],
column=['C', 'B', 'A']
)
dct2 = chart2.to_dict()
assert dct2['repeat'] == {'row': ['A', 'B', 'C'], 'column': ['C', 'B', 'A']}
assert 'columns' not in dct2
assert dct2['spec']['encoding']['x']['field'] == {'repeat': 'row'}
assert dct2['spec']['encoding']['y']['field'] == {'repeat': 'column'}
def test_repeat():
# wrapped repeat
chart1 = (alt.Chart("data.csv").mark_point().encode(
x=alt.X(alt.repeat(), type="quantitative"),
y="y:Q",
).repeat(["A", "B", "C", "D"], columns=2))
dct1 = chart1.to_dict()
assert dct1["repeat"] == ["A", "B", "C", "D"]
assert dct1["columns"] == 2
assert dct1["spec"]["encoding"]["x"]["field"] == {"repeat": "repeat"}
# explicit row/col repeat
chart2 = (alt.Chart("data.csv").mark_point().encode(
x=alt.X(alt.repeat("row"), type="quantitative"),
y=alt.Y(alt.repeat("column"), type="quantitative"),
).repeat(row=["A", "B", "C"], column=["C", "B", "A"]))
dct2 = chart2.to_dict()
assert dct2["repeat"] == {
"row": ["A", "B", "C"],
"column": ["C", "B", "A"]
}
assert "columns" not in dct2
assert dct2["spec"]["encoding"]["x"]["field"] == {"repeat": "row"}
assert dct2["spec"]["encoding"]["y"]["field"] == {"repeat": "column"}
def test_chart_infer_types():
data = pd.DataFrame({'x': pd.date_range('2012', periods=10, freq='Y'),
'y': range(10),
'c': list('abcabcabca')})
def _check_encodings(chart):
dct = chart.to_dict()
assert dct['encoding']['x']['type'] == 'temporal'
assert dct['encoding']['x']['field'] == 'x'
assert dct['encoding']['y']['type'] == 'quantitative'
assert dct['encoding']['y']['field'] == 'y'
assert dct['encoding']['color']['type'] == 'nominal'
assert dct['encoding']['color']['field'] == 'c'
# Pass field names by keyword
chart = alt.Chart(data).mark_point().encode(x='x', y='y', color='c')
_check_encodings(chart)
# pass Channel objects by keyword
chart = alt.Chart(data).mark_point().encode(x=alt.X('x'), y=alt.Y('y'),
color=alt.Color('c'))
_check_encodings(chart)
# pass Channel objects by value
chart = alt.Chart(data).mark_point().encode(alt.X('x'), alt.Y('y'),
alt.Color('c'))
_check_encodings(chart)
# override default types
chart = alt.Chart(data).mark_point().encode(alt.X('x', type='nominal'),
alt.Y('y', type='ordinal'))
dct = chart.to_dict()
assert dct['encoding']['x']['type'] == 'nominal'
assert dct['encoding']['y']['type'] == 'ordinal'
def _make_chart_type(chart_type):
data = pd.DataFrame({
"x": [28, 55, 43, 91, 81, 53, 19, 87],
"y": [43, 91, 81, 53, 19, 87, 52, 28],
"color": list("AAAABBBB"),
})
base = (alt.Chart(data).mark_point().encode(
x="x",
y="y",
color="color",
))
if chart_type in ["layer", "hconcat", "vconcat", "concat"]:
func = getattr(alt, chart_type)
return func(base.mark_square(), base.mark_circle())
elif chart_type == "facet":
return base.facet("color")
elif chart_type == "facet_encoding":
return base.encode(facet="color")
elif chart_type == "repeat":
return base.encode(alt.X(alt.repeat(),
type="quantitative")).repeat(["x", "y"])
elif chart_type == "chart":
return base
else:
raise ValueError(
"chart_type='{}' is not recognized".format(chart_type))
def _make_chart_type(chart_type):
data = pd.DataFrame({
'x': [28, 55, 43, 91, 81, 53, 19, 87],
'y': [43, 91, 81, 53, 19, 87, 52, 28],
'color': list('AAAABBBB'),
})
base = alt.Chart(data).mark_point().encode(
x='x',
y='y',
color='color',
)
if chart_type in ['layer', 'hconcat', 'vconcat', 'concat']:
func = getattr(alt, chart_type)
return func(base.mark_square(), base.mark_circle())
elif chart_type == 'facet':
return base.facet('color')
elif chart_type == 'facet_encoding':
return base.encode(facet='color')
elif chart_type == 'repeat':
return base.encode(
alt.X(alt.repeat(), type='quantitative')
).repeat(
['x', 'y']
)
elif chart_type == 'chart':
return base
else:
raise ValueError("chart_type='{}' is not recognized".format(chart_type))
def test_chart_infer_types():
data = pd.DataFrame(
{
"x": pd.date_range("2012", periods=10, freq="Y"),
"y": range(10),
"c": list("abcabcabca"),
}
)
def _check_encodings(chart):
dct = chart.to_dict()
assert dct["encoding"]["x"]["type"] == "temporal"
assert dct["encoding"]["x"]["field"] == "x"
assert dct["encoding"]["y"]["type"] == "quantitative"
assert dct["encoding"]["y"]["field"] == "y"
assert dct["encoding"]["color"]["type"] == "nominal"
assert dct["encoding"]["color"]["field"] == "c"
# Pass field names by keyword
chart = alt.Chart(data).mark_point().encode(x="x", y="y", color="c")
_check_encodings(chart)
# pass Channel objects by keyword
chart = (
alt.Chart(data)
.mark_point()
.encode(x=alt.X("x"), y=alt.Y("y"), color=alt.Color("c"))
)
_check_encodings(chart)
# pass Channel objects by value
chart = alt.Chart(data).mark_point().encode(alt.X("x"), alt.Y("y"), alt.Color("c"))
_check_encodings(chart)
# override default types
chart = (
alt.Chart(data)
.mark_point()
.encode(alt.X("x", type="nominal"), alt.Y("y", type="ordinal"))
)
dct = chart.to_dict()
assert dct["encoding"]["x"]["type"] == "nominal"
assert dct["encoding"]["y"]["type"] == "ordinal"
def test_layer_encodings():
chart = alt.LayerChart().encode(x="column:Q")
assert chart.encoding.x == alt.X(shorthand="column:Q")
