def test_brush_indices_change(self, small_df, populated_config):
ds = DataSource(small_df, None)
bp = BoxPlotWidget(ds, 0, 0, 1.0, 400)
bp.build()
ds.brushed_indices = [1, 2, 3]
assert bp.figure_widget.data[0].selectedpoints == ds.brushed_indices
def test_brush_indices_change(self, small_df, populated_config):
ds = DataSource(small_df, None)
hw = HistogramWidget(ds, 0, 0, 1.0, 400)
hw.build()
ds.brushed_indices = [1, 2, 3]
assert hw.figure_widget.data[1].selectedpoints == ds.brushed_indices
assert hw.figure_widget.data[0].visible
def test_plot_invisible_with_no_data(self, small_df, populated_config):
ds = DataSource(small_df)
hw = HistogramWidget(ds, 0, 0, 1.0, 400)
ds.brushed_indices = []
assert not hw.figure_widget.data[1].visible
ds.brushed_indices = [0]
assert hw.figure_widget.data[1].visible
def test_on_selection_constraint_ranges_reset(self, small_df,
populated_config):
ds = DataSource(small_df, None)
ps = ParallelCoordinatesWidget(ds, 0, 0, 1.0, 400)
dimensions = ps.figure_widget.data[0].dimensions
assert len(dimensions) != 0
dimensions = fill_sample_constraint_range(dimensions, "a", [2, 5])
ps._on_selection_helper(None, dimensions)
ds.brushed_indices = [1, 2]
assert ps.constraint_ranges == {}
def test_constraint_range_reset_data_source(self, small_df,
populated_config, type):
ds = DataSource(small_df)
ps = ParallelCoordinatesWidget(ds, 0, 0, 1.0, 400)
ds.selection_type = type
dimensions = ps.figure_widget.data[0].dimensions
assert len(dimensions) != 0
dimensions = fill_sample_constraint_range(dimensions, "a", [2, 5])
ps._on_selection_helper(None, dimensions)
assert ps.constraint_ranges == {}
def test_on_selection_helper_no_ranges_deselect(self, small_df,
populated_config):
ds = DataSource(small_df, None)
ps = ParallelCoordinatesWidget(ds, 0, 0, 1.0, 400)
ds.brushed_indices = [1, 2]
old_dimensions = deepcopy(
ps.figure_widget.data[0].dimensions) # no constraint ranges
dimensions = ps.figure_widget.data[0].dimensions
dimensions = fill_sample_constraint_range(dimensions, "a", [2, 5])
ps._on_selection_helper(None, dimensions)
assert len(ds) != 0
ps._on_selection_helper(None, old_dimensions) # trigger deselect
assert len(ds.brushed_indices) == ds.len
def test_with_data_source(mpg_df):
from pandas_visual_analysis import VisualAnalysis, DataSource
df = mpg_df
ds = DataSource(df)
VisualAnalysis(ds)
def test_normalize_select_false(self, small_df, populated_config):
ds = DataSource(small_df, None)
hw = HistogramWidget(ds, 0, 0, 1.0, 400)
hw.normalize.value = False
assert hw.figure_widget.data[0].histnorm == ""
assert hw.figure_widget.data[1].histnorm == ""
def test_on_selection(self, small_df, populated_config):
ds = DataSource(small_df, None)
bp = BoxPlotWidget(ds, 0, 0, 1.0, 400)
points = PointsObject([1, 2, 3])
bp.on_selection(None, points, None)
assert ds.brushed_indices == set(points.point_inds)
def test_on_selection(self, small_df, populated_config):
ds = DataSource(small_df, None)
ps = ParallelCoordinatesWidget(ds, 0, 0, 1.0, 400)
points = PointsObject([1, 2, 3])
ps.on_selection(None, points, None)
assert sum(list(ps.figure_widget.data[0].line.color)) == 3
assert ds.brushed_indices == set(points.point_inds)
def test_brush_indices_change(self, small_df, populated_config):
ds = DataSource(small_df, None)
ps = ParallelCoordinatesWidget(ds, 0, 0, 1.0, 400)
dimensions = ps.figure_widget.data[0].dimensions
assert len(dimensions) != 0
dimensions = fill_sample_constraint_range(dimensions, "a", [1.5, 5])
ps.figure_widget.data[0].dimensions = dimensions
ps.change_initiated = False
ds.brushed_indices = [1, 2, 3]
assert sum(list(ps.figure_widget.data[0].line.color)) == 3
dimensions = ps.figure_widget.data[0].dimensions
for dimension in dimensions:
if dimension.label == "a":
assert dimension["constraintrange"] is None
break
def test_base_widget_abstract_methods(small_df):
BaseWidget.__abstractmethods__ = set()
class Dummy(BaseWidget):
pass
d = Dummy(DataSource(small_df), 0, 0, 1.0, 400)
d.on_deselection(None, None)
d.observe_brush_indices_change(None)
d.build()
d.on_selection(None, None, None)
d.set_observers()
def test_on_selection_helper_int_range(self, small_df, populated_config):
def on_selection_assert(trace, points, state):
assert len(points.point_inds) == 4
assert isinstance(points.point_inds, list)
assert 0 not in points.point_inds
ds = DataSource(small_df, None)
ps = ParallelCoordinatesWidget(ds, 0, 0, 1.0, 400)
old_dimensions = deepcopy(
ps.figure_widget.data[0].dimensions) # no constraint ranges
assert len(old_dimensions) != 0
dimensions = fill_sample_constraint_range(old_dimensions, "a", [2, 5])
print(dimensions)
ps.on_selection = on_selection_assert
ps._on_selection_helper(None, dimensions)
def test_redraw_plot_keep_old_constraint_ranges(self, rand_float_df,
populated_config):
ds = DataSource(rand_float_df, None)
ps = ParallelCoordinatesWidget(ds, 0, 0, 0.2, 400)
dimensions = ps.figure_widget.data[0].dimensions
assert len(dimensions) != 0
dimensions = fill_sample_constraint_range(dimensions, "A", [1.5, 5])
ps.figure_widget.data[0].dimensions = dimensions
ps.selected_columns = ["A", "B"]
ps._redraw_plot()
updated_ranges = {
dim["label"]: dim["constraintrange"]
for dim in ps.figure_widget.data[0].dimensions
if dim["constraintrange"]
}
assert list(updated_ranges["A"]) == [1.5, 5]
def test_normal_few_cols_html(self, small_df, populated_config):
df = small_df.drop(columns=["a", "c"])
ds = DataSource(df, None)
with pytest.raises(ValueError):
ParallelCoordinatesWidget(ds, 0, 0, 1.0, 400)
def test_object_creation(self, small_df, populated_config):
ds = DataSource(small_df, None)
ParallelCoordinatesWidget(ds, 0, 0, 1.0, 400)
def test_multi_select(self, rand_float_df, populated_config):
ds = DataSource(rand_float_df, None)
ps = ParallelCoordinatesWidget(ds, 0, 0, 0.2, 400)
ps.multi_select.selected_options = ["A", "B"]
def test_basic_multi_select(self, rand_float_df, populated_config):
ds = DataSource(rand_float_df, None)
ps = ParallelCoordinatesWidget(ds, 0, 0, 0.2, 400)
assert ps.multi_select is not None
def test_normal_build(self, small_df, populated_config):
ds = DataSource(small_df, None)
hw = HistogramWidget(ds, 0, 0, 1.0, 400)
root_widget = hw.build()
assert isinstance(root_widget, widgets.VBox)
def test_column_select(self, small_df, populated_config):
ds = DataSource(small_df, None)
hw = HistogramWidget(ds, 0, 0, 1.0, 400)
hw.column_select.value = "b"
assert list(hw.figure_widget.data[0].x) == list(small_df["b"].values)
def test_on_deselection(self, small_df, populated_config):
ds = DataSource(small_df, None)
ds.brushed_indices = [0]
bp = BoxPlotWidget(ds, 0, 0, 1.0, 400)
bp.on_deselection(None, None)
assert len(ds.brushed_indices) == len(small_df)
def test_object_creation(self, small_df, populated_config):
ds = DataSource(small_df, None)
BoxPlotWidget(ds, 0, 0, 1.0, 400)
def test_init_with_data_source(self, small_df):
ds = DataSource(small_df, None)
assert VisualAnalysis(data=ds)
def test_box_points(self, small_df, populated_config):
ds = DataSource(small_df, None)
bp = BoxPlotWidget(ds, 0, 0, 1.0, 400)
bp.box_point_select.value = "outliers"
assert bp.figure_widget.data[0].boxpoints == "outliers"
def test_column_select(self, small_df, populated_config):
ds = DataSource(small_df, None)
bp = BoxPlotWidget(ds, 0, 0, 1.0, 400)
bp.column_select.value = "c"
assert list(bp.figure_widget.data[0].y) == list(small_df["c"].values)
def test_basic_multi_select(self, rand_cat_df, populated_config):
ds = DataSource(rand_cat_df, None)
ParallelCategoriesWidget(ds, 0, 0, 0.2, 400)
def test_normal_build(self, small_df, populated_config):
ds = DataSource(small_df, None)
ps = ParallelCoordinatesWidget(ds, 0, 0, 1.0, 400)
root_widget = ps.build()
assert isinstance(root_widget, widgets.HBox)
def test_on_deselection(self, small_df, populated_config):
ds = DataSource(small_df, None)
ds.brushed_indices = [0]
hw = HistogramWidget(ds, 0, 0, 1.0, 400)
hw.on_deselection(None, None)
assert len(ds.brushed_indices) == len(small_df)
def test_brush_indices_change(self, small_df, populated_config):
ds = DataSource(small_df, None)
pc = ParallelCategoriesWidget(ds, 0, 0, 1.0, 400)
ds.brushed_indices = [1, 2, 3]
assert sum(list(pc.figure_widget.data[0].line.color)) == 3
def test_normal_build(self, small_df, populated_config):
ds = DataSource(small_df, None)
bp = BoxPlotWidget(ds, 0, 0, 1.0, 400)
root_widget = bp.build()
assert isinstance(root_widget, widgets.VBox)
