from typing import Optional, List
from highcharts_core.options.series.base import SeriesBase
from highcharts_core.options.series.data.venn import VennData
from highcharts_core.options.plot_options.venn import VennOptions
from highcharts_core.utility_functions import mro__to_untrimmed_dict
[docs]class VennSeries(SeriesBase, VennOptions):
"""Options to configure a Venn series.
A Venn diagram displays all possible logical relations between a collection of
different sets. The sets are represented by circles, and the relation between the
sets are displayed by the overlap or lack of overlap between them. The venn
diagram is a special case of Euler diagrams, which can also be displayed by this
series type.
.. tabs::
.. tab:: Venn Diagram
.. figure:: ../../../_static/venn-example.png
:alt: Venn Example Chart
:align: center
.. tab:: Euler Diagram
.. figure:: ../../../_static/venn-example-euler.png
:alt: Euler Example Chart
:align: center
"""
def __init__(self, **kwargs):
super().__init__(**kwargs)
@property
def data(self) -> Optional[List[VennData]]:
"""Collection of data that represents the series. Defaults to
:obj:`None <python:None>`.
While the series type returns a collection of :class:`VennData` instances,
it accepts as input three different types of data:
.. tabs::
.. tab:: Object Collection
A one-dimensional collection of :class:`VennData` objects or objects
coercable to :class:`VennData`.
:rtype: :class:`list <python:list>` of :class:`VennData` or
:obj:`None <python:None>`
"""
return self._data
@data.setter
def data(self, value):
if not value:
self._data = None
else:
self._data = VennData.from_array(value)
@classmethod
def _get_kwargs_from_dict(cls, as_dict):
kwargs = {
'accessibility': as_dict.get('accessibility', None),
'allow_point_select': as_dict.get('allowPointSelect', None),
'animation': as_dict.get('animation', None),
'class_name': as_dict.get('className', None),
'clip': as_dict.get('clip', None),
'color': as_dict.get('color', None),
'cursor': as_dict.get('cursor', None),
'custom': as_dict.get('custom', None),
'dash_style': as_dict.get('dashStyle', None),
'data_labels': as_dict.get('dataLabels', None),
'description': as_dict.get('description', None),
'enable_mouse_tracking': as_dict.get('enableMouseTracking', None),
'events': as_dict.get('events', None),
'include_in_data_export': as_dict.get('includeInDataExport', None),
'keys': as_dict.get('keys', None),
'label': as_dict.get('label', None),
'linked_to': as_dict.get('linkedTo', None),
'marker': as_dict.get('marker', None),
'on_point': as_dict.get('onPoint', None),
'opacity': as_dict.get('opacity', None),
'point': as_dict.get('point', None),
'point_description_formatter': as_dict.get('pointDescriptionFormatter', None),
'selected': as_dict.get('selected', None),
'show_checkbox': as_dict.get('showCheckbox', None),
'show_in_legend': as_dict.get('showInLegend', None),
'skip_keyboard_navigation': as_dict.get('skipKeyboardNavigation', None),
'states': as_dict.get('states', None),
'sticky_tracking': as_dict.get('stickyTracking', None),
'threshold': as_dict.get('threshold', None),
'tooltip': as_dict.get('tooltip', None),
'turbo_threshold': as_dict.get('turboThreshold', None),
'visible': as_dict.get('visible', None),
'animation_limit': as_dict.get('animationLimit', None),
'boost_blending': as_dict.get('boostBlending', None),
'boost_threshold': as_dict.get('boostThreshold', None),
'color_axis': as_dict.get('colorAxis', None),
'color_index': as_dict.get('colorIndex', None),
'color_key': as_dict.get('colorKey', None),
'connect_ends': as_dict.get('connectEnds', None),
'connect_nulls': as_dict.get('connectNulls', None),
'crisp': as_dict.get('crisp', None),
'crop_threshold': as_dict.get('cropThreshold', None),
'data_sorting': as_dict.get('dataSorting', None),
'drag_drop': as_dict.get('dragDrop', None),
'find_nearest_point_by': as_dict.get('findNearestPointBy', None),
'get_extremes_from_all': as_dict.get('getExtremesFromAll', None),
'linecap': as_dict.get('linecap', None),
'line_width': as_dict.get('lineWidth', None),
'negative_color': as_dict.get('negativeColor', None),
'point_interval': as_dict.get('pointInterval', None),
'point_interval_unit': as_dict.get('pointIntervalUnit', None),
'point_placement': as_dict.get('pointPlacement', None),
'point_start': as_dict.get('pointStart', None),
'relative_x_value': as_dict.get('relativeXValue', None),
'shadow': as_dict.get('shadow', None),
'soft_threshold': as_dict.get('softThreshold', None),
'stacking': as_dict.get('stacking', None),
'step': as_dict.get('step', None),
'zone_axis': as_dict.get('zoneAxis', None),
'zones': as_dict.get('zones', None),
'data': as_dict.get('data', None),
'id': as_dict.get('id', None),
'index': as_dict.get('index', None),
'legend_index': as_dict.get('legendIndex', None),
'name': as_dict.get('name', None),
'stack': as_dict.get('stack', None),
'x_axis': as_dict.get('xAxis', None),
'y_axis': as_dict.get('yAxis', None),
'z_index': as_dict.get('zIndex', None),
'border_dash_style': as_dict.get('borderDashStyle', None),
'brighten': as_dict.get('brighten', None),
'cluster': as_dict.get('cluster', None)
}
return kwargs
def _to_untrimmed_dict(self, in_cls = None) -> dict:
untrimmed = mro__to_untrimmed_dict(self, in_cls = in_cls)
return untrimmed