def test_data_column_lengths(self):
# TODO: use this when soft=False
#
#with self.assertRaises(ValueError):
# ColumnDataSource(data=dict(a=[10, 11], b=[20, 21, 22]))
#
#ds = ColumnDataSource()
#with self.assertRaises(ValueError):
# ds.data = dict(a=[10, 11], b=[20, 21, 22])
#
#ds = ColumnDataSource(data=dict(a=[10, 11]))
#with self.assertRaises(ValueError):
# ds.data["b"] = [20, 21, 22]
#
#ds = ColumnDataSource(data=dict(a=[10, 11], b=[20, 21]))
#with self.assertRaises(ValueError):
# ds.data.update(dict(a=[10, 11, 12]))
with warnings.catch_warnings(record=True) as warns:
ColumnDataSource(data=dict(a=[10, 11], b=[20, 21, 22]))
self.assertEquals(len(warns), 1)
self.assertEquals(
str(warns[0].message),
"ColumnDataSource's columns must be of the same length. Current lengths: ('a', 2), ('b', 3)"
)
ds = ColumnDataSource()
with warnings.catch_warnings(record=True) as warns:
ds.data = dict(a=[10, 11], b=[20, 21, 22])
self.assertEquals(len(warns), 1)
self.assertEquals(
str(warns[0].message),
"ColumnDataSource's columns must be of the same length. Current lengths: ('a', 2), ('b', 3)"
)
ds = ColumnDataSource(data=dict(a=[10, 11]))
with warnings.catch_warnings(record=True) as warns:
ds.data["b"] = [20, 21, 22]
self.assertEquals(len(warns), 1)
self.assertEquals(
str(warns[0].message),
"ColumnDataSource's columns must be of the same length. Current lengths: ('a', 2), ('b', 3)"
)
ds = ColumnDataSource(data=dict(a=[10, 11], b=[20, 21]))
with warnings.catch_warnings(record=True) as warns:
ds.data.update(dict(a=[10, 11, 12]))
self.assertEquals(len(warns), 1)
self.assertEquals(
str(warns[0].message),
"ColumnDataSource's columns must be of the same length. Current lengths: ('a', 3), ('b', 2)"
)
def test_data_accepts_dataframe_arg(self, pd):
data = dict(a=[1, 2], b=[2, 3])
df = pd.DataFrame(data)
ds = ColumnDataSource()
assert ds.data == {}
ds.data = df
assert set(df.columns).issubset(set(ds.column_names))
for key in data.keys():
assert isinstance(ds.data[key], np.ndarray)
assert list(df[key]) == list(ds.data[key])
assert isinstance(ds.data['index'], np.ndarray)
assert [0, 1] == list(ds.data['index'])
assert set(ds.column_names) - set(df.columns) == set(["index"])
def test_data_accepts_groupby_arg(self, pd):
from bokeh.sampledata.autompg import autompg as df
group = df.groupby(by=['origin', 'cyl'])
ds = ColumnDataSource()
assert ds.data == {}
ds.data = group
s = group.describe()
assert len(ds.column_names) == 49
assert isinstance(ds.data['origin_cyl'], np.ndarray)
for key in s.columns.values:
k2 = "_".join(key)
assert isinstance(ds.data[k2], np.ndarray)
assert list(s[key]) == list(ds.data[k2])
def test_data_accepts_dataframe_column_categoricalindex(self, pd):
columns = pd.CategoricalIndex(['a', 'b'])
data = [[0, 2], [1, 3]]
df = pd.DataFrame(columns=columns, data=data)
ds = ColumnDataSource()
assert ds.data == {}
ds.data = df
assert set(df.columns).issubset(set(ds.column_names))
for key in columns:
assert isinstance(ds.data[key], np.ndarray)
assert list(df[key]) == list(ds.data[key])
assert isinstance(ds.data['index'], np.ndarray)
assert [0, 1] == list(ds.data['index'])
assert set(ds.column_names) - set(df.columns) == set(["index"])
def make_ajax_query_plot(data):
source_query = ColumnDataSource()
source_query.data = data
plot = figure(plot_height=300, sizing_mode='scale_width')
plot.line('x', 'y', source=source_query, line_width=4)
plot.circle('x',
'y',
source=source_query,
size=8,
fill_color="white",
color="red")
script, div = components(plot)
return script, div
def test_data_accepts_groupby_with_None_subindex_name(self, pd):
df = pd.DataFrame({
"A": [1, 2, 3, 4] * 2,
"B": [10, 20, 30, 40] * 2,
"C": range(8)
})
group = df.groupby(['A', [10, 20, 30, 40] * 2])
ds = ColumnDataSource()
assert ds.data == {}
ds.data = group
s = group.describe()
assert len(ds.column_names) == 17
assert isinstance(ds.data['index'], np.ndarray)
for key in s.columns.values:
k2 = "_".join(key)
assert isinstance(ds.data[k2], np.ndarray)
assert list(s[key]) == list(ds.data[k2])
def test_data_column_lengths(self):
# TODO: use this when soft=False
#
#with self.assertRaises(ValueError):
# ColumnDataSource(data=dict(a=[10, 11], b=[20, 21, 22]))
#
#ds = ColumnDataSource()
#with self.assertRaises(ValueError):
# ds.data = dict(a=[10, 11], b=[20, 21, 22])
#
#ds = ColumnDataSource(data=dict(a=[10, 11]))
#with self.assertRaises(ValueError):
# ds.data["b"] = [20, 21, 22]
#
#ds = ColumnDataSource(data=dict(a=[10, 11], b=[20, 21]))
#with self.assertRaises(ValueError):
# ds.data.update(dict(a=[10, 11, 12]))
with warnings.catch_warnings(record=True) as warns:
ColumnDataSource(data=dict(a=[10, 11], b=[20, 21, 22]))
self.assertEquals(len(warns), 1)
self.assertEquals(str(warns[0].message), "ColumnDataSource's columns must be of the same length")
ds = ColumnDataSource()
with warnings.catch_warnings(record=True) as warns:
ds.data = dict(a=[10, 11], b=[20, 21, 22])
self.assertEquals(len(warns), 1)
self.assertEquals(str(warns[0].message), "ColumnDataSource's columns must be of the same length")
ds = ColumnDataSource(data=dict(a=[10, 11]))
with warnings.catch_warnings(record=True) as warns:
ds.data["b"] = [20, 21, 22]
self.assertEquals(len(warns), 1)
self.assertEquals(str(warns[0].message), "ColumnDataSource's columns must be of the same length")
ds = ColumnDataSource(data=dict(a=[10, 11], b=[20, 21]))
with warnings.catch_warnings(record=True) as warns:
ds.data.update(dict(a=[10, 11, 12]))
self.assertEquals(len(warns), 1)
self.assertEquals(str(warns[0].message), "ColumnDataSource's columns must be of the same length")
def test_data_column_lengths(self):
# TODO: use this when soft=False
#
#with pytest.raises(ValueError):
# ColumnDataSource(data=dict(a=[10, 11], b=[20, 21, 22]))
#
#ds = ColumnDataSource()
#with pytest.raises(ValueError):
# ds.data = dict(a=[10, 11], b=[20, 21, 22])
#
#ds = ColumnDataSource(data=dict(a=[10, 11]))
#with pytest.raises(ValueError):
# ds.data["b"] = [20, 21, 22]
#
#ds = ColumnDataSource(data=dict(a=[10, 11], b=[20, 21]))
#with pytest.raises(ValueError):
# ds.data.update(dict(a=[10, 11, 12]))
with warnings.catch_warnings(record=True) as warns:
ColumnDataSource(data=dict(a=[10, 11], b=[20, 21, 22]))
assert len(warns) == 1
assert str(warns[0].message) == "ColumnDataSource's columns must be of the same length. Current lengths: ('a', 2), ('b', 3)"
ds = ColumnDataSource()
with warnings.catch_warnings(record=True) as warns:
ds.data = dict(a=[10, 11], b=[20, 21, 22])
assert len(warns) == 1
assert str(warns[0].message) == "ColumnDataSource's columns must be of the same length. Current lengths: ('a', 2), ('b', 3)"
ds = ColumnDataSource(data=dict(a=[10, 11]))
with warnings.catch_warnings(record=True) as warns:
ds.data["b"] = [20, 21, 22]
assert len(warns) == 1
assert str(warns[0].message) == "ColumnDataSource's columns must be of the same length. Current lengths: ('a', 2), ('b', 3)"
ds = ColumnDataSource(data=dict(a=[10, 11], b=[20, 21]))
with warnings.catch_warnings(record=True) as warns:
ds.data.update(dict(a=[10, 11, 12]))
assert len(warns) == 1
assert str(warns[0].message) == "ColumnDataSource's columns must be of the same length. Current lengths: ('a', 3), ('b', 2)"