from typing import Optional, List
from highcharts_core.options.series.base import SeriesBase
from highcharts_core.options.series.data.vector import VectorData, VectorDataCollection
from highcharts_core.options.plot_options.vector import VectorOptions
from highcharts_core.utility_functions import mro__to_untrimmed_dict, is_ndarray
[docs]class VectorSeries(SeriesBase, VectorOptions):
"""Options to configure a Vector series.
A vector plot is a type of cartesian chart where each point has an X and Y
position, a length and a direction. Vectors are drawn as arrows.
.. figure:: ../../../_static/vector-example.png
:alt: Vector Example Chart
:align: center
"""
def __init__(self, **kwargs):
super().__init__(**kwargs)
@classmethod
def _data_collection_class(cls):
"""Returns the class object used for the data collection.
:rtype: :class:`DataPointCollection <highcharts_core.options.series.data.collections.DataPointCollection>`
descendent
"""
return VectorDataCollection
@classmethod
def _data_point_class(cls):
"""Returns the class object used for individual data points.
:rtype: :class:`DataBase <highcharts_core.options.series.data.base.DataBase>`
descendent
"""
return VectorData
@property
def data(self) -> Optional[List[VectorData] | VectorDataCollection]:
"""Collection of data that represents the series. Defaults to
:obj:`None <python:None>`.
While the series type returns a collection of :class:`VectorData` instances,
it accepts as input different types of data:
.. tabs::
.. tab:: 4D Collection
.. code-block::
series = VectorSeries()
series.data = [
[0, 0, 10, 90],
[0, 1, 5, 180],
[1, 1, 2, 270]
]
A collection of four-dimensional numerical values. Each member of the
collection will be interpreted as :meth:`x <VectorData.x>`,
:meth:`y <VectorData.y>`, :meth:`length <VectorData.length>`, and
:meth:`direction <VectorData.direction>`, respectively.
.. tab:: Object Collection
A one-dimensional collection of :class:`VectorData` objects.
:rtype: :class:`list <python:list>` of :class:`VectorData` or
:class:`VectorDataCollection` or
:obj:`None <python:None>`
"""
return self._data
@data.setter
def data(self, value):
if not is_ndarray(value) and not value:
self._data = None
else:
self._data = VectorData.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),
'legend_symbol': as_dict.get('legendSymbol', 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),
'sonification': as_dict.get('sonification', 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),
'inactive_other_points': as_dict.get('inactiveOtherPoints', None),
'linecap': as_dict.get('linecap', None),
'line_width': as_dict.get('lineWidth', None),
'negative_color': as_dict.get('negativeColor', None),
'point_description_format': as_dict.get('pointDescriptionFormat', 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),
'cluster': as_dict.get('cluster', None),
'rotation_origin': as_dict.get('rotationOrigin', None),
'vector_length': as_dict.get('vectorLength', None)
}
return kwargs
def _to_untrimmed_dict(self, in_cls = None) -> dict:
untrimmed = mro__to_untrimmed_dict(self, in_cls = in_cls)
return untrimmed