from plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType import copy as _copy class Meanline(_BaseTraceHierarchyType): # class properties # -------------------- _parent_path_str = "violin" _path_str = "violin.meanline" _valid_props = {"color", "visible", "width"} # color # ----- @property def color(self): """ Sets the mean line color. The 'color' property is a color and may be specified as: - A hex string (e.g. '#ff0000') - An rgb/rgba string (e.g. 'rgb(255,0,0)') - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') - A named CSS color: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgrey, darkgreen, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, grey, green, greenyellow, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgrey, lightgreen, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, red, rosybrown, royalblue, rebeccapurple, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen Returns ------- str """ return self["color"] @color.setter def color(self, val): self["color"] = val # visible # ------- @property def visible(self): """ Determines if a line corresponding to the sample's mean is shown inside the violins. If `box.visible` is turned on, the mean line is drawn inside the inner box. Otherwise, the mean line is drawn from one side of the violin to other. The 'visible' property must be specified as a bool (either True, or False) Returns ------- bool """ return self["visible"] @visible.setter def visible(self, val): self["visible"] = val # width # ----- @property def width(self): """ Sets the mean line width. The 'width' property is a number and may be specified as: - An int or float in the interval [0, inf] Returns ------- int|float """ return self["width"] @width.setter def width(self, val): self["width"] = val # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ color Sets the mean line color. visible Determines if a line corresponding to the sample's mean is shown inside the violins. If `box.visible` is turned on, the mean line is drawn inside the inner box. Otherwise, the mean line is drawn from one side of the violin to other. width Sets the mean line width. """ def __init__(self, arg=None, color=None, visible=None, width=None, **kwargs): """ Construct a new Meanline object Parameters ---------- arg dict of properties compatible with this constructor or an instance of :class:`plotly.graph_objs.violin.Meanline` color Sets the mean line color. visible Determines if a line corresponding to the sample's mean is shown inside the violins. If `box.visible` is turned on, the mean line is drawn inside the inner box. Otherwise, the mean line is drawn from one side of the violin to other. width Sets the mean line width. Returns ------- Meanline """ super(Meanline, self).__init__("meanline") if "_parent" in kwargs: self._parent = kwargs["_parent"] return # Validate arg # ------------ if arg is None: arg = {} elif isinstance(arg, self.__class__): arg = arg.to_plotly_json() elif isinstance(arg, dict): arg = _copy.copy(arg) else: raise ValueError( """\ The first argument to the plotly.graph_objs.violin.Meanline constructor must be a dict or an instance of :class:`plotly.graph_objs.violin.Meanline`""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) self._validate = kwargs.pop("_validate", True) # Populate data dict with properties # ---------------------------------- _v = arg.pop("color", None) _v = color if color is not None else _v if _v is not None: self["color"] = _v _v = arg.pop("visible", None) _v = visible if visible is not None else _v if _v is not None: self["visible"] = _v _v = arg.pop("width", None) _v = width if width is not None else _v if _v is not None: self["width"] = _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False