def setUp(self):
self.config = HistogramPlotConfigurator(data_source=TEST_DF)
self.config.x_col_name = "a"
self.desc = PlotDescriptor(x_col_name="a", plot_config=self.config,
plot_title="Plot 0")
self.config2 = BarPlotConfigurator(data_source=TEST_DF)
self.config2.x_col_name = "a"
self.config2.y_col_name = "b"
self.desc2 = PlotDescriptor(x_col_name="a", y_col_name="b",
plot_config=self.config2,
plot_title="Plot 1")
self.config3 = ScatterPlotConfigurator(data_source=TEST_DF)
self.config3.x_col_name = "a"
self.config3.y_col_name = "b"
self.desc3 = PlotDescriptor(x_col_name="a", y_col_name="b",
plot_config=self.config3,
plot_title="Plot 2")
self.config4 = ScatterPlotConfigurator(data_source=TEST_DF)
self.config4.x_col_name = "a"
self.config4.y_col_name = "b"
self.config4.z_col_name = "d"
self.desc4 = PlotDescriptor(x_col_name="a", y_col_name="b",
z_col_name="d", plot_config=self.config4,
plot_title="Plot 3")
self.model = DataFramePlotManager(contained_plots=[self.desc],
data_source=TEST_DF)
self.target_dir = join(HERE, "test_dir")
if isdir(self.target_dir):
rmtree(self.target_dir)
def test_add_plot_to_custom_container2(self):
canvas = MultiCanvasManager()
plot = Plot()
desc = PlotDescriptor(plot=plot)
canvas.add_plot_to_container(desc,
container=canvas.container_managers[2])
self.assert_valid_canvas(canvas, cont_idx=2, num_plots=1)
def test_round_trip_df_plotter_with_hist(self):
config = HistogramPlotConfigurator(data_source=TEST_DF)
config.x_col_name = "Col_4"
desc = PlotDescriptor(x_col_name="Col_4",
plot_config=config,
plot_title="Plot 1")
self.assert_df_plotter_roundtrip(desc)
def test_add_remove_plot(self):
canvas = MultiCanvasManager()
plot = Plot()
desc = PlotDescriptor(plot=plot)
canvas.add_plot_to_container(desc)
self.assert_valid_canvas(canvas, num_plots=1)
canvas.remove_plot_from_container(desc)
self.assert_valid_canvas(canvas, num_plots=0)
def test_round_trip_df_plotter_bar(self):
config6 = BarPlotConfigurator(data_source=TEST_DF)
config6.x_col_name = "Col_3"
config6.y_col_name = "Col_1"
desc6 = PlotDescriptor(x_col_name="Col_3",
y_col_name="Col_1",
plot_config=config6,
plot_title="Plot 6")
self.assert_df_plotter_roundtrip(desc6)
def test_round_trip_df_plotter_with_line_plot(self):
config5 = LinePlotConfigurator(data_source=TEST_DF)
config5.x_col_name = "Col_1"
config5.y_col_name = "Col_2"
desc5 = PlotDescriptor(x_col_name="Col_1",
y_col_name="Col_2",
plot_config=config5,
plot_title="Plot 5")
self.assert_df_plotter_roundtrip(desc5)
def test_round_trip_df_plotter_with_scatter(self):
config3 = ScatterPlotConfigurator(data_source=TEST_DF)
config3.x_col_name = "Col_1"
config3.y_col_name = "Col_2"
desc3 = PlotDescriptor(x_col_name="Col_1",
y_col_name="Col_2",
plot_config=config3,
plot_title="Plot 3")
self.assert_df_plotter_roundtrip(desc3)
def test_round_trip_df_plotter_with_bar(self):
config2 = BarPlotConfigurator(data_source=TEST_DF)
config2.x_col_name = "Col_1"
config2.y_col_name = "Col_2"
desc2 = PlotDescriptor(x_col_name="Col_1",
y_col_name="Col_2",
plot_config=config2,
plot_title="Plot 2")
self.assert_df_plotter_roundtrip(desc2)
def test_round_trip_df_plotter_with_colored_scatter(self):
config4 = ScatterPlotConfigurator(data_source=TEST_DF)
config4.x_col_name = "Col_1"
config4.y_col_name = "Col_2"
config4.z_col_name = "Col_3"
desc4 = PlotDescriptor(x_col_name="Col_1",
y_col_name="Col_2",
z_col_name="Col_3",
plot_config=config4,
plot_title="Plot 4")
self.assert_df_plotter_roundtrip(desc4)
def test_round_trip_df_plotter_heatmap_types(self):
config7 = HeatmapPlotConfigurator(data_source=TEST_DF2)
config7.x_col_name = "Col_1"
config7.y_col_name = "Col_2"
config7.z_col_name = "Col_3"
desc7 = PlotDescriptor(x_col_name="Col_1",
y_col_name="Col_2",
z_col_name="Col_3",
plot_config=config7,
plot_title="Plot 8")
self.assert_df_plotter_roundtrip(desc7)
def test_round_trip_df_plotter_cmap_scatter_type(self):
config = ScatterPlotConfigurator(data_source=TEST_DF)
config.x_col_name = "Col_1"
config.y_col_name = "Col_2"
config.z_col_name = "Col_4"
desc = PlotDescriptor(x_col_name="Col_1",
y_col_name="Col_2",
z_col_name="Col_4",
plot_config=config,
plot_title="Plot 7")
# Skipping the color_ attribute since it behaves strangely and is a
# proxy for the renderer color attribute anyway:
self.assert_df_plotter_roundtrip(desc, adtl_ignore=["color_"])
def preprocess_plot_list(self, plot_list):
""" Pre-process the list of plots so they can be embedded in manager.
1. Expand MultiConfigurators into a list of single plot configurators.
2. Convert Chaco containers and raw Configurators into descriptors.
"""
from ..plotting.multi_plot_config import BaseMultiPlotConfigurator
contained_plots = []
for i, desc in enumerate(plot_list):
if isinstance(desc, BasePlotContainer):
new_desc = embed_plot_in_desc(desc)
contained_plots.append(new_desc)
elif isinstance(desc, BaseMultiPlotConfigurator):
config_list = desc.to_config_list()
contained_plots += [
PlotDescriptor.from_config(x) for x in config_list
]
elif isinstance(desc, PlotDescriptor) and \
isinstance(desc.plot_config, BaseMultiPlotConfigurator):
config_list = desc.plot_config.to_config_list()
contained_plots += [
PlotDescriptor.from_config(x) for x in config_list
]
elif isinstance(desc, BaseSinglePlotConfigurator):
contained_plots.append(PlotDescriptor.from_config(desc))
elif isinstance(desc, PlotDescriptor):
contained_plots.append(desc)
else:
msg = "Unsupported object type to provided a plot in a " \
"DFPlotManager. Supported types are PlotDescriptor " \
"instances or PlotConfigurator instances but a {} was " \
"provided for item {}. Skipping...".format(type(desc), i)
logger.error(msg)
return contained_plots
def embed_plot_in_desc(plot):
""" Embed chaco plot in PlotDescriptor so it can be displayed in DFPlotter.
Parameters
----------
plot : BasePlotContainer
Chaco plot to be embedded.
"""
if isinstance(plot, Plot):
desc = PlotDescriptor(plot_type=CUSTOM_PLOT_TYPE,
plot=plot,
plot_config=BaseSinglePlotConfigurator(),
plot_title=plot.title,
x_axis_title=plot.x_axis.title,
y_axis_title=plot.y_axis.title,
frozen=True)
else:
msg = "Automatically embedding {} isn't supported.".format(type(plot))
logger.exception(msg)
raise ValueError(msg)
return desc
cust_plot1 = Plot(ArrayPlotData(x=[1, 2, 3], y=[1, 2, 3]))
cust_plot1.plot(("x", "y"))
cust_plot1.title = "Blah"
cust_plot1.x_axis.title = "x"
cust_plot1.y_axis.title = "y"
config6 = BarPlotConfigurator(data_source=TEST_DF, plot_title="plot 6")
config6.x_col_name = "Col_3"
config6.y_col_name = "Col_1"
config7 = MultiLinePlotConfigurator(data_source=TEST_DF)
config7.x_col_name = "Col_1"
config7.y_col_names = ["Col_1", "Col_2", "Col_4"]
desc7 = PlotDescriptor(plot_config=config7,
plot_title="Plot 7",
container_idx=1)
config9 = BarPlotConfigurator(data_source=TEST_DF, plot_title="plot 9")
config9.x_col_name = "Col_3"
config9.y_col_name = "Col_4"
config8 = ScatterPlotConfigurator(data_source=TEST_DF)
config8.x_col_name = "Col_1"
config8.y_col_name = "Col_2"
config8.z_col_name = "Col_4"
desc8 = PlotDescriptor(plot_config=config8,
plot_title="Plot 8",
container_idx=1)
analyzer = DataFrameAnalyzer(source_df=TEST_DF)
def _add_new_plot(self,
config,
position=None,
list_op="insert",
container=None,
initial_creation=True,
**desc_traits):
""" Build a new plot and add to the list of plots.
Parameters
----------
config : PlotConfigurator
Configuration object used to describe the plot to create.
position : int or None, optional
Where to insert the first plot in the list. Leave as None to append
it to the end of the current plot list.
list_op : str, optional
How to add the created description to the list of contained plots:
'insert' in the right position (default) or 'replace' an existing
plot?
desc_traits : dict, optional
Descriptor traits to override.
container : ConstraintsPlotContainerManager or None, optional
Container to add the plot to. If left as None, it's up to the
canvas' to select the container based on its configuration.
initial_creation : bool
Set to True during initial creation of a plot. Set to False when
loading a plot from disk (either from a save file or from a
custom template file)
"""
if position is None:
position = self.next_plot_id
msg = f"Generating {config.plot_type} plot..."
logger.log(ACTION_LEVEL, msg)
factory = self._factory_from_config(config)
desc = factory.generate_plot()
plot = desc["plot"]
if initial_creation:
self._initialize_config_plot_ranges(config, plot)
else:
self._apply_style_ranges(config, plot, factory)
desc["id"] = str(position)
# Store the config so it be recreated...
desc["plot_config"] = config
if self.source_analyzer:
desc["data_filter"] = self.source_analyzer.filter_exp
else:
desc["data_filter"] = ""
# If a container is specified, record it in the descriptor:
if isinstance(container, int):
desc["container_idx"] = container
container = None
elif isinstance(container, ConstraintsPlotContainerManager):
containers = self.canvas_manager.container_managers
desc["container_idx"] = containers.index(container)
desc.update(desc_traits)
desc = PlotDescriptor(**desc)
# Store the description into a list for display in UI
if list_op == "insert":
self.contained_plots.insert(position, desc)
else:
self.contained_plots[position] = desc
# ...and into a dict for quick access:
self.contained_plot_map[desc.id] = desc
self.canvas_manager.add_plot_to_container(desc,
position,
container=container)
if factory.inspector is not None:
self.inspectors[desc.id] = factory.inspector
self.next_plot_id += 1
return desc