from plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType import copy as _copy class YBins(_BaseTraceHierarchyType): # end # --- @property def end(self): """ Sets the end value for the y axis bins. The last bin may not end exactly at this value, we increment the bin edge by `size` from `start` until we reach or exceed `end`. Defaults to the maximum data value. Like `start`, for dates use a date string, and for category data `end` is based on the category serial numbers. The 'end' property accepts values of any type Returns ------- Any """ return self["end"] @end.setter def end(self, val): self["end"] = val # size # ---- @property def size(self): """ Sets the size of each y axis bin. Default behavior: If `nbinsy` is 0 or omitted, we choose a nice round bin size such that the number of bins is about the same as the typical number of samples in each bin. If `nbinsy` is provided, we choose a nice round bin size giving no more than that many bins. For date data, use milliseconds or "M" for months, as in `axis.dtick`. For category data, the number of categories to bin together (always defaults to 1). If multiple non-overlaying histograms share a subplot, the first explicit `size` is used and all others discarded. If no `size` is provided,the sample data from all traces is combined to determine `size` as described above. The 'size' property accepts values of any type Returns ------- Any """ return self["size"] @size.setter def size(self, val): self["size"] = val # start # ----- @property def start(self): """ Sets the starting value for the y axis bins. Defaults to the minimum data value, shifted down if necessary to make nice round values and to remove ambiguous bin edges. For example, if most of the data is integers we shift the bin edges 0.5 down, so a `size` of 5 would have a default `start` of -0.5, so it is clear that 0-4 are in the first bin, 5-9 in the second, but continuous data gets a start of 0 and bins [0,5), [5,10) etc. Dates behave similarly, and `start` should be a date string. For category data, `start` is based on the category serial numbers, and defaults to -0.5. If multiple non-overlaying histograms share a subplot, the first explicit `start` is used exactly and all others are shifted down (if necessary) to differ from that one by an integer number of bins. The 'start' property accepts values of any type Returns ------- Any """ return self["start"] @start.setter def start(self, val): self["start"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "histogram" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ end Sets the end value for the y axis bins. The last bin may not end exactly at this value, we increment the bin edge by `size` from `start` until we reach or exceed `end`. Defaults to the maximum data value. Like `start`, for dates use a date string, and for category data `end` is based on the category serial numbers. size Sets the size of each y axis bin. Default behavior: If `nbinsy` is 0 or omitted, we choose a nice round bin size such that the number of bins is about the same as the typical number of samples in each bin. If `nbinsy` is provided, we choose a nice round bin size giving no more than that many bins. For date data, use milliseconds or "M" for months, as in `axis.dtick`. For category data, the number of categories to bin together (always defaults to 1). If multiple non- overlaying histograms share a subplot, the first explicit `size` is used and all others discarded. If no `size` is provided,the sample data from all traces is combined to determine `size` as described above. start Sets the starting value for the y axis bins. Defaults to the minimum data value, shifted down if necessary to make nice round values and to remove ambiguous bin edges. For example, if most of the data is integers we shift the bin edges 0.5 down, so a `size` of 5 would have a default `start` of -0.5, so it is clear that 0-4 are in the first bin, 5-9 in the second, but continuous data gets a start of 0 and bins [0,5), [5,10) etc. Dates behave similarly, and `start` should be a date string. For category data, `start` is based on the category serial numbers, and defaults to -0.5. If multiple non-overlaying histograms share a subplot, the first explicit `start` is used exactly and all others are shifted down (if necessary) to differ from that one by an integer number of bins. """ def __init__(self, arg=None, end=None, size=None, start=None, **kwargs): """ Construct a new YBins object Parameters ---------- arg dict of properties compatible with this constructor or an instance of :class:`plotly.graph_objs.histogram.YBins` end Sets the end value for the y axis bins. The last bin may not end exactly at this value, we increment the bin edge by `size` from `start` until we reach or exceed `end`. Defaults to the maximum data value. Like `start`, for dates use a date string, and for category data `end` is based on the category serial numbers. size Sets the size of each y axis bin. Default behavior: If `nbinsy` is 0 or omitted, we choose a nice round bin size such that the number of bins is about the same as the typical number of samples in each bin. If `nbinsy` is provided, we choose a nice round bin size giving no more than that many bins. For date data, use milliseconds or "M" for months, as in `axis.dtick`. For category data, the number of categories to bin together (always defaults to 1). If multiple non- overlaying histograms share a subplot, the first explicit `size` is used and all others discarded. If no `size` is provided,the sample data from all traces is combined to determine `size` as described above. start Sets the starting value for the y axis bins. Defaults to the minimum data value, shifted down if necessary to make nice round values and to remove ambiguous bin edges. For example, if most of the data is integers we shift the bin edges 0.5 down, so a `size` of 5 would have a default `start` of -0.5, so it is clear that 0-4 are in the first bin, 5-9 in the second, but continuous data gets a start of 0 and bins [0,5), [5,10) etc. Dates behave similarly, and `start` should be a date string. For category data, `start` is based on the category serial numbers, and defaults to -0.5. If multiple non-overlaying histograms share a subplot, the first explicit `start` is used exactly and all others are shifted down (if necessary) to differ from that one by an integer number of bins. Returns ------- YBins """ super(YBins, self).__init__("ybins") # 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.histogram.YBins constructor must be a dict or an instance of :class:`plotly.graph_objs.histogram.YBins`""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.histogram import ybins as v_ybins # Initialize validators # --------------------- self._validators["end"] = v_ybins.EndValidator() self._validators["size"] = v_ybins.SizeValidator() self._validators["start"] = v_ybins.StartValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("end", None) self["end"] = end if end is not None else _v _v = arg.pop("size", None) self["size"] = size if size is not None else _v _v = arg.pop("start", None) self["start"] = start if start is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False from plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType import copy as _copy class XBins(_BaseTraceHierarchyType): # end # --- @property def end(self): """ Sets the end value for the x axis bins. The last bin may not end exactly at this value, we increment the bin edge by `size` from `start` until we reach or exceed `end`. Defaults to the maximum data value. Like `start`, for dates use a date string, and for category data `end` is based on the category serial numbers. The 'end' property accepts values of any type Returns ------- Any """ return self["end"] @end.setter def end(self, val): self["end"] = val # size # ---- @property def size(self): """ Sets the size of each x axis bin. Default behavior: If `nbinsx` is 0 or omitted, we choose a nice round bin size such that the number of bins is about the same as the typical number of samples in each bin. If `nbinsx` is provided, we choose a nice round bin size giving no more than that many bins. For date data, use milliseconds or "M" for months, as in `axis.dtick`. For category data, the number of categories to bin together (always defaults to 1). If multiple non-overlaying histograms share a subplot, the first explicit `size` is used and all others discarded. If no `size` is provided,the sample data from all traces is combined to determine `size` as described above. The 'size' property accepts values of any type Returns ------- Any """ return self["size"] @size.setter def size(self, val): self["size"] = val # start # ----- @property def start(self): """ Sets the starting value for the x axis bins. Defaults to the minimum data value, shifted down if necessary to make nice round values and to remove ambiguous bin edges. For example, if most of the data is integers we shift the bin edges 0.5 down, so a `size` of 5 would have a default `start` of -0.5, so it is clear that 0-4 are in the first bin, 5-9 in the second, but continuous data gets a start of 0 and bins [0,5), [5,10) etc. Dates behave similarly, and `start` should be a date string. For category data, `start` is based on the category serial numbers, and defaults to -0.5. If multiple non-overlaying histograms share a subplot, the first explicit `start` is used exactly and all others are shifted down (if necessary) to differ from that one by an integer number of bins. The 'start' property accepts values of any type Returns ------- Any """ return self["start"] @start.setter def start(self, val): self["start"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "histogram" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ end Sets the end value for the x axis bins. The last bin may not end exactly at this value, we increment the bin edge by `size` from `start` until we reach or exceed `end`. Defaults to the maximum data value. Like `start`, for dates use a date string, and for category data `end` is based on the category serial numbers. size Sets the size of each x axis bin. Default behavior: If `nbinsx` is 0 or omitted, we choose a nice round bin size such that the number of bins is about the same as the typical number of samples in each bin. If `nbinsx` is provided, we choose a nice round bin size giving no more than that many bins. For date data, use milliseconds or "M" for months, as in `axis.dtick`. For category data, the number of categories to bin together (always defaults to 1). If multiple non- overlaying histograms share a subplot, the first explicit `size` is used and all others discarded. If no `size` is provided,the sample data from all traces is combined to determine `size` as described above. start Sets the starting value for the x axis bins. Defaults to the minimum data value, shifted down if necessary to make nice round values and to remove ambiguous bin edges. For example, if most of the data is integers we shift the bin edges 0.5 down, so a `size` of 5 would have a default `start` of -0.5, so it is clear that 0-4 are in the first bin, 5-9 in the second, but continuous data gets a start of 0 and bins [0,5), [5,10) etc. Dates behave similarly, and `start` should be a date string. For category data, `start` is based on the category serial numbers, and defaults to -0.5. If multiple non-overlaying histograms share a subplot, the first explicit `start` is used exactly and all others are shifted down (if necessary) to differ from that one by an integer number of bins. """ def __init__(self, arg=None, end=None, size=None, start=None, **kwargs): """ Construct a new XBins object Parameters ---------- arg dict of properties compatible with this constructor or an instance of :class:`plotly.graph_objs.histogram.XBins` end Sets the end value for the x axis bins. The last bin may not end exactly at this value, we increment the bin edge by `size` from `start` until we reach or exceed `end`. Defaults to the maximum data value. Like `start`, for dates use a date string, and for category data `end` is based on the category serial numbers. size Sets the size of each x axis bin. Default behavior: If `nbinsx` is 0 or omitted, we choose a nice round bin size such that the number of bins is about the same as the typical number of samples in each bin. If `nbinsx` is provided, we choose a nice round bin size giving no more than that many bins. For date data, use milliseconds or "M" for months, as in `axis.dtick`. For category data, the number of categories to bin together (always defaults to 1). If multiple non- overlaying histograms share a subplot, the first explicit `size` is used and all others discarded. If no `size` is provided,the sample data from all traces is combined to determine `size` as described above. start Sets the starting value for the x axis bins. Defaults to the minimum data value, shifted down if necessary to make nice round values and to remove ambiguous bin edges. For example, if most of the data is integers we shift the bin edges 0.5 down, so a `size` of 5 would have a default `start` of -0.5, so it is clear that 0-4 are in the first bin, 5-9 in the second, but continuous data gets a start of 0 and bins [0,5), [5,10) etc. Dates behave similarly, and `start` should be a date string. For category data, `start` is based on the category serial numbers, and defaults to -0.5. If multiple non-overlaying histograms share a subplot, the first explicit `start` is used exactly and all others are shifted down (if necessary) to differ from that one by an integer number of bins. Returns ------- XBins """ super(XBins, self).__init__("xbins") # 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.histogram.XBins constructor must be a dict or an instance of :class:`plotly.graph_objs.histogram.XBins`""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.histogram import xbins as v_xbins # Initialize validators # --------------------- self._validators["end"] = v_xbins.EndValidator() self._validators["size"] = v_xbins.SizeValidator() self._validators["start"] = v_xbins.StartValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("end", None) self["end"] = end if end is not None else _v _v = arg.pop("size", None) self["size"] = size if size is not None else _v _v = arg.pop("start", None) self["start"] = start if start is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False from plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType import copy as _copy class Unselected(_BaseTraceHierarchyType): # marker # ------ @property def marker(self): """ The 'marker' property is an instance of Marker that may be specified as: - An instance of :class:`plotly.graph_objs.histogram.unselected.Marker` - A dict of string/value properties that will be passed to the Marker constructor Supported dict properties: color Sets the marker color of unselected points, applied only when a selection exists. opacity Sets the marker opacity of unselected points, applied only when a selection exists. Returns ------- plotly.graph_objs.histogram.unselected.Marker """ return self["marker"] @marker.setter def marker(self, val): self["marker"] = val # textfont # -------- @property def textfont(self): """ The 'textfont' property is an instance of Textfont that may be specified as: - An instance of :class:`plotly.graph_objs.histogram.unselected.Textfont` - A dict of string/value properties that will be passed to the Textfont constructor Supported dict properties: color Sets the text font color of unselected points, applied only when a selection exists. Returns ------- plotly.graph_objs.histogram.unselected.Textfont """ return self["textfont"] @textfont.setter def textfont(self, val): self["textfont"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "histogram" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ marker :class:`plotly.graph_objects.histogram.unselected.Marke r` instance or dict with compatible properties textfont :class:`plotly.graph_objects.histogram.unselected.Textf ont` instance or dict with compatible properties """ def __init__(self, arg=None, marker=None, textfont=None, **kwargs): """ Construct a new Unselected object Parameters ---------- arg dict of properties compatible with this constructor or an instance of :class:`plotly.graph_objs.histogram.Unselected` marker :class:`plotly.graph_objects.histogram.unselected.Marke r` instance or dict with compatible properties textfont :class:`plotly.graph_objects.histogram.unselected.Textf ont` instance or dict with compatible properties Returns ------- Unselected """ super(Unselected, self).__init__("unselected") # 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.histogram.Unselected constructor must be a dict or an instance of :class:`plotly.graph_objs.histogram.Unselected`""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.histogram import unselected as v_unselected # Initialize validators # --------------------- self._validators["marker"] = v_unselected.MarkerValidator() self._validators["textfont"] = v_unselected.TextfontValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("marker", None) self["marker"] = marker if marker is not None else _v _v = arg.pop("textfont", None) self["textfont"] = textfont if textfont is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False from plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType import copy as _copy class Stream(_BaseTraceHierarchyType): # maxpoints # --------- @property def maxpoints(self): """ Sets the maximum number of points to keep on the plots from an incoming stream. If `maxpoints` is set to 50, only the newest 50 points will be displayed on the plot. The 'maxpoints' property is a number and may be specified as: - An int or float in the interval [0, 10000] Returns ------- int|float """ return self["maxpoints"] @maxpoints.setter def maxpoints(self, val): self["maxpoints"] = val # token # ----- @property def token(self): """ The stream id number links a data trace on a plot with a stream. See https://plot.ly/settings for more details. The 'token' property is a string and must be specified as: - A non-empty string Returns ------- str """ return self["token"] @token.setter def token(self, val): self["token"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "histogram" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ maxpoints Sets the maximum number of points to keep on the plots from an incoming stream. If `maxpoints` is set to 50, only the newest 50 points will be displayed on the plot. token The stream id number links a data trace on a plot with a stream. See https://plot.ly/settings for more details. """ def __init__(self, arg=None, maxpoints=None, token=None, **kwargs): """ Construct a new Stream object Parameters ---------- arg dict of properties compatible with this constructor or an instance of :class:`plotly.graph_objs.histogram.Stream` maxpoints Sets the maximum number of points to keep on the plots from an incoming stream. If `maxpoints` is set to 50, only the newest 50 points will be displayed on the plot. token The stream id number links a data trace on a plot with a stream. See https://plot.ly/settings for more details. Returns ------- Stream """ super(Stream, self).__init__("stream") # 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.histogram.Stream constructor must be a dict or an instance of :class:`plotly.graph_objs.histogram.Stream`""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.histogram import stream as v_stream # Initialize validators # --------------------- self._validators["maxpoints"] = v_stream.MaxpointsValidator() self._validators["token"] = v_stream.TokenValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("maxpoints", None) self["maxpoints"] = maxpoints if maxpoints is not None else _v _v = arg.pop("token", None) self["token"] = token if token is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False from plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType import copy as _copy class Selected(_BaseTraceHierarchyType): # marker # ------ @property def marker(self): """ The 'marker' property is an instance of Marker that may be specified as: - An instance of :class:`plotly.graph_objs.histogram.selected.Marker` - A dict of string/value properties that will be passed to the Marker constructor Supported dict properties: color Sets the marker color of selected points. opacity Sets the marker opacity of selected points. Returns ------- plotly.graph_objs.histogram.selected.Marker """ return self["marker"] @marker.setter def marker(self, val): self["marker"] = val # textfont # -------- @property def textfont(self): """ The 'textfont' property is an instance of Textfont that may be specified as: - An instance of :class:`plotly.graph_objs.histogram.selected.Textfont` - A dict of string/value properties that will be passed to the Textfont constructor Supported dict properties: color Sets the text font color of selected points. Returns ------- plotly.graph_objs.histogram.selected.Textfont """ return self["textfont"] @textfont.setter def textfont(self, val): self["textfont"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "histogram" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ marker :class:`plotly.graph_objects.histogram.selected.Marker` instance or dict with compatible properties textfont :class:`plotly.graph_objects.histogram.selected.Textfon t` instance or dict with compatible properties """ def __init__(self, arg=None, marker=None, textfont=None, **kwargs): """ Construct a new Selected object Parameters ---------- arg dict of properties compatible with this constructor or an instance of :class:`plotly.graph_objs.histogram.Selected` marker :class:`plotly.graph_objects.histogram.selected.Marker` instance or dict with compatible properties textfont :class:`plotly.graph_objects.histogram.selected.Textfon t` instance or dict with compatible properties Returns ------- Selected """ super(Selected, self).__init__("selected") # 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.histogram.Selected constructor must be a dict or an instance of :class:`plotly.graph_objs.histogram.Selected`""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.histogram import selected as v_selected # Initialize validators # --------------------- self._validators["marker"] = v_selected.MarkerValidator() self._validators["textfont"] = v_selected.TextfontValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("marker", None) self["marker"] = marker if marker is not None else _v _v = arg.pop("textfont", None) self["textfont"] = textfont if textfont is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False from plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType import copy as _copy class Marker(_BaseTraceHierarchyType): # autocolorscale # -------------- @property def autocolorscale(self): """ Determines whether the colorscale is a default palette (`autocolorscale: true`) or the palette determined by `marker.colorscale`. Has an effect only if in `marker.color`is set to a numerical array. In case `colorscale` is unspecified or `autocolorscale` is true, the default palette will be chosen according to whether numbers in the `color` array are all positive, all negative or mixed. The 'autocolorscale' property must be specified as a bool (either True, or False) Returns ------- bool """ return self["autocolorscale"] @autocolorscale.setter def autocolorscale(self, val): self["autocolorscale"] = val # cauto # ----- @property def cauto(self): """ Determines whether or not the color domain is computed with respect to the input data (here in `marker.color`) or the bounds set in `marker.cmin` and `marker.cmax` Has an effect only if in `marker.color`is set to a numerical array. Defaults to `false` when `marker.cmin` and `marker.cmax` are set by the user. The 'cauto' property must be specified as a bool (either True, or False) Returns ------- bool """ return self["cauto"] @cauto.setter def cauto(self, val): self["cauto"] = val # cmax # ---- @property def cmax(self): """ Sets the upper bound of the color domain. Has an effect only if in `marker.color`is set to a numerical array. Value should have the same units as in `marker.color` and if set, `marker.cmin` must be set as well. The 'cmax' property is a number and may be specified as: - An int or float Returns ------- int|float """ return self["cmax"] @cmax.setter def cmax(self, val): self["cmax"] = val # cmid # ---- @property def cmid(self): """ Sets the mid-point of the color domain by scaling `marker.cmin` and/or `marker.cmax` to be equidistant to this point. Has an effect only if in `marker.color`is set to a numerical array. Value should have the same units as in `marker.color`. Has no effect when `marker.cauto` is `false`. The 'cmid' property is a number and may be specified as: - An int or float Returns ------- int|float """ return self["cmid"] @cmid.setter def cmid(self, val): self["cmid"] = val # cmin # ---- @property def cmin(self): """ Sets the lower bound of the color domain. Has an effect only if in `marker.color`is set to a numerical array. Value should have the same units as in `marker.color` and if set, `marker.cmax` must be set as well. The 'cmin' property is a number and may be specified as: - An int or float Returns ------- int|float """ return self["cmin"] @cmin.setter def cmin(self, val): self["cmin"] = val # color # ----- @property def color(self): """ Sets themarkercolor. It accepts either a specific color or an array of numbers that are mapped to the colorscale relative to the max and min values of the array or relative to `marker.cmin` and `marker.cmax` if set. 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 - A number that will be interpreted as a color according to histogram.marker.colorscale - A list or array of any of the above Returns ------- str|numpy.ndarray """ return self["color"] @color.setter def color(self, val): self["color"] = val # coloraxis # --------- @property def coloraxis(self): """ Sets a reference to a shared color axis. References to these shared color axes are "coloraxis", "coloraxis2", "coloraxis3", etc. Settings for these shared color axes are set in the layout, under `layout.coloraxis`, `layout.coloraxis2`, etc. Note that multiple color scales can be linked to the same color axis. The 'coloraxis' property is an identifier of a particular subplot, of type 'coloraxis', that may be specified as the string 'coloraxis' optionally followed by an integer >= 1 (e.g. 'coloraxis', 'coloraxis1', 'coloraxis2', 'coloraxis3', etc.) Returns ------- str """ return self["coloraxis"] @coloraxis.setter def coloraxis(self, val): self["coloraxis"] = val # colorbar # -------- @property def colorbar(self): """ The 'colorbar' property is an instance of ColorBar that may be specified as: - An instance of :class:`plotly.graph_objs.histogram.marker.ColorBar` - A dict of string/value properties that will be passed to the ColorBar constructor Supported dict properties: bgcolor Sets the color of padded area. bordercolor Sets the axis line color. borderwidth Sets the width (in px) or the border enclosing this color bar. dtick Sets the step in-between ticks on this axis. Use with `tick0`. Must be a positive number, or special strings available to "log" and "date" axes. If the axis `type` is "log", then ticks are set every 10^(n*dtick) where n is the tick number. For example, to set a tick mark at 1, 10, 100, 1000, ... set dtick to 1. To set tick marks at 1, 100, 10000, ... set dtick to 2. To set tick marks at 1, 5, 25, 125, 625, 3125, ... set dtick to log_10(5), or 0.69897000433. "log" has several special values; "L", where `f` is a positive number, gives ticks linearly spaced in value (but not position). For example `tick0` = 0.1, `dtick` = "L0.5" will put ticks at 0.1, 0.6, 1.1, 1.6 etc. To show powers of 10 plus small digits between, use "D1" (all digits) or "D2" (only 2 and 5). `tick0` is ignored for "D1" and "D2". If the axis `type` is "date", then you must convert the time to milliseconds. For example, to set the interval between ticks to one day, set `dtick` to 86400000.0. "date" also has special values "M" gives ticks spaced by a number of months. `n` must be a positive integer. To set ticks on the 15th of every third month, set `tick0` to "2000-01-15" and `dtick` to "M3". To set ticks every 4 years, set `dtick` to "M48" exponentformat Determines a formatting rule for the tick exponents. For example, consider the number 1,000,000,000. If "none", it appears as 1,000,000,000. If "e", 1e+9. If "E", 1E+9. If "power", 1x10^9 (with 9 in a super script). If "SI", 1G. If "B", 1B. len Sets the length of the color bar This measure excludes the padding of both ends. That is, the color bar length is this length minus the padding on both ends. lenmode Determines whether this color bar's length (i.e. the measure in the color variation direction) is set in units of plot "fraction" or in *pixels. Use `len` to set the value. nticks Specifies the maximum number of ticks for the particular axis. The actual number of ticks will be chosen automatically to be less than or equal to `nticks`. Has an effect only if `tickmode` is set to "auto". outlinecolor Sets the axis line color. outlinewidth Sets the width (in px) of the axis line. separatethousands If "true", even 4-digit integers are separated showexponent If "all", all exponents are shown besides their significands. If "first", only the exponent of the first tick is shown. If "last", only the exponent of the last tick is shown. If "none", no exponents appear. showticklabels Determines whether or not the tick labels are drawn. showtickprefix If "all", all tick labels are displayed with a prefix. If "first", only the first tick is displayed with a prefix. If "last", only the last tick is displayed with a suffix. If "none", tick prefixes are hidden. showticksuffix Same as `showtickprefix` but for tick suffixes. thickness Sets the thickness of the color bar This measure excludes the size of the padding, ticks and labels. thicknessmode Determines whether this color bar's thickness (i.e. the measure in the constant color direction) is set in units of plot "fraction" or in "pixels". Use `thickness` to set the value. tick0 Sets the placement of the first tick on this axis. Use with `dtick`. If the axis `type` is "log", then you must take the log of your starting tick (e.g. to set the starting tick to 100, set the `tick0` to 2) except when `dtick`=*L* (see `dtick` for more info). If the axis `type` is "date", it should be a date string, like date data. If the axis `type` is "category", it should be a number, using the scale where each category is assigned a serial number from zero in the order it appears. tickangle Sets the angle of the tick labels with respect to the horizontal. For example, a `tickangle` of -90 draws the tick labels vertically. tickcolor Sets the tick color. tickfont Sets the color bar's tick label font tickformat Sets the tick label formatting rule using d3 formatting mini-languages which are very similar to those in Python. For numbers, see: https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format And for dates see: https://github.com/d3/d3-3.x-api- reference/blob/master/Time-Formatting.md#format We add one item to d3's date formatter: "%{n}f" for fractional seconds with n digits. For example, *2016-10-13 09:15:23.456* with tickformat "%H~%M~%S.%2f" would display "09~15~23.46" tickformatstops A tuple of :class:`plotly.graph_objects.histogr am.marker.colorbar.Tickformatstop` instances or dicts with compatible properties tickformatstopdefaults When used in a template (as layout.template.dat a.histogram.marker.colorbar.tickformatstopdefau lts), sets the default property values to use for elements of histogram.marker.colorbar.tickformatstops ticklen Sets the tick length (in px). tickmode Sets the tick mode for this axis. If "auto", the number of ticks is set via `nticks`. If "linear", the placement of the ticks is determined by a starting position `tick0` and a tick step `dtick` ("linear" is the default value if `tick0` and `dtick` are provided). If "array", the placement of the ticks is set via `tickvals` and the tick text is `ticktext`. ("array" is the default value if `tickvals` is provided). tickprefix Sets a tick label prefix. ticks Determines whether ticks are drawn or not. If "", this axis' ticks are not drawn. If "outside" ("inside"), this axis' are drawn outside (inside) the axis lines. ticksuffix Sets a tick label suffix. ticktext Sets the text displayed at the ticks position via `tickvals`. Only has an effect if `tickmode` is set to "array". Used with `tickvals`. ticktextsrc Sets the source reference on plot.ly for ticktext . tickvals Sets the values at which ticks on this axis appear. Only has an effect if `tickmode` is set to "array". Used with `ticktext`. tickvalssrc Sets the source reference on plot.ly for tickvals . tickwidth Sets the tick width (in px). title :class:`plotly.graph_objects.histogram.marker.c olorbar.Title` instance or dict with compatible properties titlefont Deprecated: Please use histogram.marker.colorbar.title.font instead. Sets this color bar's title font. Note that the title's font used to be set by the now deprecated `titlefont` attribute. titleside Deprecated: Please use histogram.marker.colorbar.title.side instead. Determines the location of color bar's title with respect to the color bar. Note that the title's location used to be set by the now deprecated `titleside` attribute. x Sets the x position of the color bar (in plot fraction). xanchor Sets this color bar's horizontal position anchor. This anchor binds the `x` position to the "left", "center" or "right" of the color bar. xpad Sets the amount of padding (in px) along the x direction. y Sets the y position of the color bar (in plot fraction). yanchor Sets this color bar's vertical position anchor This anchor binds the `y` position to the "top", "middle" or "bottom" of the color bar. ypad Sets the amount of padding (in px) along the y direction. Returns ------- plotly.graph_objs.histogram.marker.ColorBar """ return self["colorbar"] @colorbar.setter def colorbar(self, val): self["colorbar"] = val # colorscale # ---------- @property def colorscale(self): """ Sets the colorscale. Has an effect only if in `marker.color`is set to a numerical array. The colorscale must be an array containing arrays mapping a normalized value to an rgb, rgba, hex, hsl, hsv, or named color string. At minimum, a mapping for the lowest (0) and highest (1) values are required. For example, `[[0, 'rgb(0,0,255)'], [1, 'rgb(255,0,0)']]`. To control the bounds of the colorscale in color space, use`marker.cmin` and `marker.cmax`. Alternatively, `colorscale` may be a palette name string of the following list: Greys,YlGnB u,Greens,YlOrRd,Bluered,RdBu,Reds,Blues,Picnic,Rainbow,Portland ,Jet,Hot,Blackbody,Earth,Electric,Viridis,Cividis. The 'colorscale' property is a colorscale and may be specified as: - A list of colors that will be spaced evenly to create the colorscale. Many predefined colorscale lists are included in the sequential, diverging, and cyclical modules in the plotly.colors package. - A list of 2-element lists where the first element is the normalized color level value (starting at 0 and ending at 1), and the second item is a valid color string. (e.g. [[0, 'green'], [0.5, 'red'], [1.0, 'rgb(0, 0, 255)']]) - One of the following named colorscales: ['aggrnyl', 'agsunset', 'algae', 'amp', 'armyrose', 'balance', 'blackbody', 'bluered', 'blues', 'blugrn', 'bluyl', 'brbg', 'brwnyl', 'bugn', 'bupu', 'burg', 'burgyl', 'cividis', 'curl', 'darkmint', 'deep', 'delta', 'dense', 'earth', 'edge', 'electric', 'emrld', 'fall', 'geyser', 'gnbu', 'gray', 'greens', 'greys', 'haline', 'hot', 'hsv', 'ice', 'icefire', 'inferno', 'jet', 'magenta', 'magma', 'matter', 'mint', 'mrybm', 'mygbm', 'oranges', 'orrd', 'oryel', 'peach', 'phase', 'picnic', 'pinkyl', 'piyg', 'plasma', 'plotly3', 'portland', 'prgn', 'pubu', 'pubugn', 'puor', 'purd', 'purp', 'purples', 'purpor', 'rainbow', 'rdbu', 'rdgy', 'rdpu', 'rdylbu', 'rdylgn', 'redor', 'reds', 'solar', 'spectral', 'speed', 'sunset', 'sunsetdark', 'teal', 'tealgrn', 'tealrose', 'tempo', 'temps', 'thermal', 'tropic', 'turbid', 'twilight', 'viridis', 'ylgn', 'ylgnbu', 'ylorbr', 'ylorrd']. Appending '_r' to a named colorscale reverses it. Returns ------- str """ return self["colorscale"] @colorscale.setter def colorscale(self, val): self["colorscale"] = val # colorsrc # -------- @property def colorsrc(self): """ Sets the source reference on plot.ly for color . The 'colorsrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["colorsrc"] @colorsrc.setter def colorsrc(self, val): self["colorsrc"] = val # line # ---- @property def line(self): """ The 'line' property is an instance of Line that may be specified as: - An instance of :class:`plotly.graph_objs.histogram.marker.Line` - A dict of string/value properties that will be passed to the Line constructor Supported dict properties: autocolorscale Determines whether the colorscale is a default palette (`autocolorscale: true`) or the palette determined by `marker.line.colorscale`. Has an effect only if in `marker.line.color`is set to a numerical array. In case `colorscale` is unspecified or `autocolorscale` is true, the default palette will be chosen according to whether numbers in the `color` array are all positive, all negative or mixed. cauto Determines whether or not the color domain is computed with respect to the input data (here in `marker.line.color`) or the bounds set in `marker.line.cmin` and `marker.line.cmax` Has an effect only if in `marker.line.color`is set to a numerical array. Defaults to `false` when `marker.line.cmin` and `marker.line.cmax` are set by the user. cmax Sets the upper bound of the color domain. Has an effect only if in `marker.line.color`is set to a numerical array. Value should have the same units as in `marker.line.color` and if set, `marker.line.cmin` must be set as well. cmid Sets the mid-point of the color domain by scaling `marker.line.cmin` and/or `marker.line.cmax` to be equidistant to this point. Has an effect only if in `marker.line.color`is set to a numerical array. Value should have the same units as in `marker.line.color`. Has no effect when `marker.line.cauto` is `false`. cmin Sets the lower bound of the color domain. Has an effect only if in `marker.line.color`is set to a numerical array. Value should have the same units as in `marker.line.color` and if set, `marker.line.cmax` must be set as well. color Sets themarker.linecolor. It accepts either a specific color or an array of numbers that are mapped to the colorscale relative to the max and min values of the array or relative to `marker.line.cmin` and `marker.line.cmax` if set. coloraxis Sets a reference to a shared color axis. References to these shared color axes are "coloraxis", "coloraxis2", "coloraxis3", etc. Settings for these shared color axes are set in the layout, under `layout.coloraxis`, `layout.coloraxis2`, etc. Note that multiple color scales can be linked to the same color axis. colorscale Sets the colorscale. Has an effect only if in `marker.line.color`is set to a numerical array. The colorscale must be an array containing arrays mapping a normalized value to an rgb, rgba, hex, hsl, hsv, or named color string. At minimum, a mapping for the lowest (0) and highest (1) values are required. For example, `[[0, 'rgb(0,0,255)'], [1, 'rgb(255,0,0)']]`. To control the bounds of the colorscale in color space, use`marker.line.cmin` and `marker.line.cmax`. Alternatively, `colorscale` may be a palette name string of the following list: Greys,YlGnBu,Greens,YlOrRd,Bluered,RdBu,R eds,Blues,Picnic,Rainbow,Portland,Jet,Hot,Black body,Earth,Electric,Viridis,Cividis. colorsrc Sets the source reference on plot.ly for color . reversescale Reverses the color mapping if true. Has an effect only if in `marker.line.color`is set to a numerical array. If true, `marker.line.cmin` will correspond to the last color in the array and `marker.line.cmax` will correspond to the first color. width Sets the width (in px) of the lines bounding the marker points. widthsrc Sets the source reference on plot.ly for width . Returns ------- plotly.graph_objs.histogram.marker.Line """ return self["line"] @line.setter def line(self, val): self["line"] = val # opacity # ------- @property def opacity(self): """ Sets the opacity of the bars. The 'opacity' property is a number and may be specified as: - An int or float in the interval [0, 1] - A tuple, list, or one-dimensional numpy array of the above Returns ------- int|float|numpy.ndarray """ return self["opacity"] @opacity.setter def opacity(self, val): self["opacity"] = val # opacitysrc # ---------- @property def opacitysrc(self): """ Sets the source reference on plot.ly for opacity . The 'opacitysrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["opacitysrc"] @opacitysrc.setter def opacitysrc(self, val): self["opacitysrc"] = val # reversescale # ------------ @property def reversescale(self): """ Reverses the color mapping if true. Has an effect only if in `marker.color`is set to a numerical array. If true, `marker.cmin` will correspond to the last color in the array and `marker.cmax` will correspond to the first color. The 'reversescale' property must be specified as a bool (either True, or False) Returns ------- bool """ return self["reversescale"] @reversescale.setter def reversescale(self, val): self["reversescale"] = val # showscale # --------- @property def showscale(self): """ Determines whether or not a colorbar is displayed for this trace. Has an effect only if in `marker.color`is set to a numerical array. The 'showscale' property must be specified as a bool (either True, or False) Returns ------- bool """ return self["showscale"] @showscale.setter def showscale(self, val): self["showscale"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "histogram" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ autocolorscale Determines whether the colorscale is a default palette (`autocolorscale: true`) or the palette determined by `marker.colorscale`. Has an effect only if in `marker.color`is set to a numerical array. In case `colorscale` is unspecified or `autocolorscale` is true, the default palette will be chosen according to whether numbers in the `color` array are all positive, all negative or mixed. cauto Determines whether or not the color domain is computed with respect to the input data (here in `marker.color`) or the bounds set in `marker.cmin` and `marker.cmax` Has an effect only if in `marker.color`is set to a numerical array. Defaults to `false` when `marker.cmin` and `marker.cmax` are set by the user. cmax Sets the upper bound of the color domain. Has an effect only if in `marker.color`is set to a numerical array. Value should have the same units as in `marker.color` and if set, `marker.cmin` must be set as well. cmid Sets the mid-point of the color domain by scaling `marker.cmin` and/or `marker.cmax` to be equidistant to this point. Has an effect only if in `marker.color`is set to a numerical array. Value should have the same units as in `marker.color`. Has no effect when `marker.cauto` is `false`. cmin Sets the lower bound of the color domain. Has an effect only if in `marker.color`is set to a numerical array. Value should have the same units as in `marker.color` and if set, `marker.cmax` must be set as well. color Sets themarkercolor. It accepts either a specific color or an array of numbers that are mapped to the colorscale relative to the max and min values of the array or relative to `marker.cmin` and `marker.cmax` if set. coloraxis Sets a reference to a shared color axis. References to these shared color axes are "coloraxis", "coloraxis2", "coloraxis3", etc. Settings for these shared color axes are set in the layout, under `layout.coloraxis`, `layout.coloraxis2`, etc. Note that multiple color scales can be linked to the same color axis. colorbar :class:`plotly.graph_objects.histogram.marker.ColorBar` instance or dict with compatible properties colorscale Sets the colorscale. Has an effect only if in `marker.color`is set to a numerical array. The colorscale must be an array containing arrays mapping a normalized value to an rgb, rgba, hex, hsl, hsv, or named color string. At minimum, a mapping for the lowest (0) and highest (1) values are required. For example, `[[0, 'rgb(0,0,255)'], [1, 'rgb(255,0,0)']]`. To control the bounds of the colorscale in color space, use`marker.cmin` and `marker.cmax`. Alternatively, `colorscale` may be a palette name string of the following list: Greys,YlGnBu,Greens,YlOrRd,Bluered,RdBu ,Reds,Blues,Picnic,Rainbow,Portland,Jet,Hot,Blackbody,E arth,Electric,Viridis,Cividis. colorsrc Sets the source reference on plot.ly for color . line :class:`plotly.graph_objects.histogram.marker.Line` instance or dict with compatible properties opacity Sets the opacity of the bars. opacitysrc Sets the source reference on plot.ly for opacity . reversescale Reverses the color mapping if true. Has an effect only if in `marker.color`is set to a numerical array. If true, `marker.cmin` will correspond to the last color in the array and `marker.cmax` will correspond to the first color. showscale Determines whether or not a colorbar is displayed for this trace. Has an effect only if in `marker.color`is set to a numerical array. """ def __init__( self, arg=None, autocolorscale=None, cauto=None, cmax=None, cmid=None, cmin=None, color=None, coloraxis=None, colorbar=None, colorscale=None, colorsrc=None, line=None, opacity=None, opacitysrc=None, reversescale=None, showscale=None, **kwargs ): """ Construct a new Marker object Parameters ---------- arg dict of properties compatible with this constructor or an instance of :class:`plotly.graph_objs.histogram.Marker` autocolorscale Determines whether the colorscale is a default palette (`autocolorscale: true`) or the palette determined by `marker.colorscale`. Has an effect only if in `marker.color`is set to a numerical array. In case `colorscale` is unspecified or `autocolorscale` is true, the default palette will be chosen according to whether numbers in the `color` array are all positive, all negative or mixed. cauto Determines whether or not the color domain is computed with respect to the input data (here in `marker.color`) or the bounds set in `marker.cmin` and `marker.cmax` Has an effect only if in `marker.color`is set to a numerical array. Defaults to `false` when `marker.cmin` and `marker.cmax` are set by the user. cmax Sets the upper bound of the color domain. Has an effect only if in `marker.color`is set to a numerical array. Value should have the same units as in `marker.color` and if set, `marker.cmin` must be set as well. cmid Sets the mid-point of the color domain by scaling `marker.cmin` and/or `marker.cmax` to be equidistant to this point. Has an effect only if in `marker.color`is set to a numerical array. Value should have the same units as in `marker.color`. Has no effect when `marker.cauto` is `false`. cmin Sets the lower bound of the color domain. Has an effect only if in `marker.color`is set to a numerical array. Value should have the same units as in `marker.color` and if set, `marker.cmax` must be set as well. color Sets themarkercolor. It accepts either a specific color or an array of numbers that are mapped to the colorscale relative to the max and min values of the array or relative to `marker.cmin` and `marker.cmax` if set. coloraxis Sets a reference to a shared color axis. References to these shared color axes are "coloraxis", "coloraxis2", "coloraxis3", etc. Settings for these shared color axes are set in the layout, under `layout.coloraxis`, `layout.coloraxis2`, etc. Note that multiple color scales can be linked to the same color axis. colorbar :class:`plotly.graph_objects.histogram.marker.ColorBar` instance or dict with compatible properties colorscale Sets the colorscale. Has an effect only if in `marker.color`is set to a numerical array. The colorscale must be an array containing arrays mapping a normalized value to an rgb, rgba, hex, hsl, hsv, or named color string. At minimum, a mapping for the lowest (0) and highest (1) values are required. For example, `[[0, 'rgb(0,0,255)'], [1, 'rgb(255,0,0)']]`. To control the bounds of the colorscale in color space, use`marker.cmin` and `marker.cmax`. Alternatively, `colorscale` may be a palette name string of the following list: Greys,YlGnBu,Greens,YlOrRd,Bluered,RdBu ,Reds,Blues,Picnic,Rainbow,Portland,Jet,Hot,Blackbody,E arth,Electric,Viridis,Cividis. colorsrc Sets the source reference on plot.ly for color . line :class:`plotly.graph_objects.histogram.marker.Line` instance or dict with compatible properties opacity Sets the opacity of the bars. opacitysrc Sets the source reference on plot.ly for opacity . reversescale Reverses the color mapping if true. Has an effect only if in `marker.color`is set to a numerical array. If true, `marker.cmin` will correspond to the last color in the array and `marker.cmax` will correspond to the first color. showscale Determines whether or not a colorbar is displayed for this trace. Has an effect only if in `marker.color`is set to a numerical array. Returns ------- Marker """ super(Marker, self).__init__("marker") # 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.histogram.Marker constructor must be a dict or an instance of :class:`plotly.graph_objs.histogram.Marker`""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.histogram import marker as v_marker # Initialize validators # --------------------- self._validators["autocolorscale"] = v_marker.AutocolorscaleValidator() self._validators["cauto"] = v_marker.CautoValidator() self._validators["cmax"] = v_marker.CmaxValidator() self._validators["cmid"] = v_marker.CmidValidator() self._validators["cmin"] = v_marker.CminValidator() self._validators["color"] = v_marker.ColorValidator() self._validators["coloraxis"] = v_marker.ColoraxisValidator() self._validators["colorbar"] = v_marker.ColorBarValidator() self._validators["colorscale"] = v_marker.ColorscaleValidator() self._validators["colorsrc"] = v_marker.ColorsrcValidator() self._validators["line"] = v_marker.LineValidator() self._validators["opacity"] = v_marker.OpacityValidator() self._validators["opacitysrc"] = v_marker.OpacitysrcValidator() self._validators["reversescale"] = v_marker.ReversescaleValidator() self._validators["showscale"] = v_marker.ShowscaleValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("autocolorscale", None) self["autocolorscale"] = autocolorscale if autocolorscale is not None else _v _v = arg.pop("cauto", None) self["cauto"] = cauto if cauto is not None else _v _v = arg.pop("cmax", None) self["cmax"] = cmax if cmax is not None else _v _v = arg.pop("cmid", None) self["cmid"] = cmid if cmid is not None else _v _v = arg.pop("cmin", None) self["cmin"] = cmin if cmin is not None else _v _v = arg.pop("color", None) self["color"] = color if color is not None else _v _v = arg.pop("coloraxis", None) self["coloraxis"] = coloraxis if coloraxis is not None else _v _v = arg.pop("colorbar", None) self["colorbar"] = colorbar if colorbar is not None else _v _v = arg.pop("colorscale", None) self["colorscale"] = colorscale if colorscale is not None else _v _v = arg.pop("colorsrc", None) self["colorsrc"] = colorsrc if colorsrc is not None else _v _v = arg.pop("line", None) self["line"] = line if line is not None else _v _v = arg.pop("opacity", None) self["opacity"] = opacity if opacity is not None else _v _v = arg.pop("opacitysrc", None) self["opacitysrc"] = opacitysrc if opacitysrc is not None else _v _v = arg.pop("reversescale", None) self["reversescale"] = reversescale if reversescale is not None else _v _v = arg.pop("showscale", None) self["showscale"] = showscale if showscale is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False from plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType import copy as _copy class Hoverlabel(_BaseTraceHierarchyType): # align # ----- @property def align(self): """ Sets the horizontal alignment of the text content within hover label box. Has an effect only if the hover label text spans more two or more lines The 'align' property is an enumeration that may be specified as: - One of the following enumeration values: ['left', 'right', 'auto'] - A tuple, list, or one-dimensional numpy array of the above Returns ------- Any|numpy.ndarray """ return self["align"] @align.setter def align(self, val): self["align"] = val # alignsrc # -------- @property def alignsrc(self): """ Sets the source reference on plot.ly for align . The 'alignsrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["alignsrc"] @alignsrc.setter def alignsrc(self, val): self["alignsrc"] = val # bgcolor # ------- @property def bgcolor(self): """ Sets the background color of the hover labels for this trace The 'bgcolor' 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 - A list or array of any of the above Returns ------- str|numpy.ndarray """ return self["bgcolor"] @bgcolor.setter def bgcolor(self, val): self["bgcolor"] = val # bgcolorsrc # ---------- @property def bgcolorsrc(self): """ Sets the source reference on plot.ly for bgcolor . The 'bgcolorsrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["bgcolorsrc"] @bgcolorsrc.setter def bgcolorsrc(self, val): self["bgcolorsrc"] = val # bordercolor # ----------- @property def bordercolor(self): """ Sets the border color of the hover labels for this trace. The 'bordercolor' 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 - A list or array of any of the above Returns ------- str|numpy.ndarray """ return self["bordercolor"] @bordercolor.setter def bordercolor(self, val): self["bordercolor"] = val # bordercolorsrc # -------------- @property def bordercolorsrc(self): """ Sets the source reference on plot.ly for bordercolor . The 'bordercolorsrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["bordercolorsrc"] @bordercolorsrc.setter def bordercolorsrc(self, val): self["bordercolorsrc"] = val # font # ---- @property def font(self): """ Sets the font used in hover labels. The 'font' property is an instance of Font that may be specified as: - An instance of :class:`plotly.graph_objs.histogram.hoverlabel.Font` - A dict of string/value properties that will be passed to the Font constructor Supported dict properties: color colorsrc Sets the source reference on plot.ly for color . family HTML font family - the typeface that will be applied by the web browser. The web browser will only be able to apply a font if it is available on the system which it operates. Provide multiple font families, separated by commas, to indicate the preference in which to apply fonts if they aren't available on the system. The plotly service (at https://plot.ly or on-premise) generates images on a server, where only a select number of fonts are installed and supported. These include "Arial", "Balto", "Courier New", "Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow", "Raleway", "Times New Roman". familysrc Sets the source reference on plot.ly for family . size sizesrc Sets the source reference on plot.ly for size . Returns ------- plotly.graph_objs.histogram.hoverlabel.Font """ return self["font"] @font.setter def font(self, val): self["font"] = val # namelength # ---------- @property def namelength(self): """ Sets the default length (in number of characters) of the trace name in the hover labels for all traces. -1 shows the whole name regardless of length. 0-3 shows the first 0-3 characters, and an integer >3 will show the whole name if it is less than that many characters, but if it is longer, will truncate to `namelength - 3` characters and add an ellipsis. The 'namelength' property is a integer and may be specified as: - An int (or float that will be cast to an int) in the interval [-1, 9223372036854775807] - A tuple, list, or one-dimensional numpy array of the above Returns ------- int|numpy.ndarray """ return self["namelength"] @namelength.setter def namelength(self, val): self["namelength"] = val # namelengthsrc # ------------- @property def namelengthsrc(self): """ Sets the source reference on plot.ly for namelength . The 'namelengthsrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["namelengthsrc"] @namelengthsrc.setter def namelengthsrc(self, val): self["namelengthsrc"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "histogram" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ align Sets the horizontal alignment of the text content within hover label box. Has an effect only if the hover label text spans more two or more lines alignsrc Sets the source reference on plot.ly for align . bgcolor Sets the background color of the hover labels for this trace bgcolorsrc Sets the source reference on plot.ly for bgcolor . bordercolor Sets the border color of the hover labels for this trace. bordercolorsrc Sets the source reference on plot.ly for bordercolor . font Sets the font used in hover labels. namelength Sets the default length (in number of characters) of the trace name in the hover labels for all traces. -1 shows the whole name regardless of length. 0-3 shows the first 0-3 characters, and an integer >3 will show the whole name if it is less than that many characters, but if it is longer, will truncate to `namelength - 3` characters and add an ellipsis. namelengthsrc Sets the source reference on plot.ly for namelength . """ def __init__( self, arg=None, align=None, alignsrc=None, bgcolor=None, bgcolorsrc=None, bordercolor=None, bordercolorsrc=None, font=None, namelength=None, namelengthsrc=None, **kwargs ): """ Construct a new Hoverlabel object Parameters ---------- arg dict of properties compatible with this constructor or an instance of :class:`plotly.graph_objs.histogram.Hoverlabel` align Sets the horizontal alignment of the text content within hover label box. Has an effect only if the hover label text spans more two or more lines alignsrc Sets the source reference on plot.ly for align . bgcolor Sets the background color of the hover labels for this trace bgcolorsrc Sets the source reference on plot.ly for bgcolor . bordercolor Sets the border color of the hover labels for this trace. bordercolorsrc Sets the source reference on plot.ly for bordercolor . font Sets the font used in hover labels. namelength Sets the default length (in number of characters) of the trace name in the hover labels for all traces. -1 shows the whole name regardless of length. 0-3 shows the first 0-3 characters, and an integer >3 will show the whole name if it is less than that many characters, but if it is longer, will truncate to `namelength - 3` characters and add an ellipsis. namelengthsrc Sets the source reference on plot.ly for namelength . Returns ------- Hoverlabel """ super(Hoverlabel, self).__init__("hoverlabel") # 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.histogram.Hoverlabel constructor must be a dict or an instance of :class:`plotly.graph_objs.histogram.Hoverlabel`""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.histogram import hoverlabel as v_hoverlabel # Initialize validators # --------------------- self._validators["align"] = v_hoverlabel.AlignValidator() self._validators["alignsrc"] = v_hoverlabel.AlignsrcValidator() self._validators["bgcolor"] = v_hoverlabel.BgcolorValidator() self._validators["bgcolorsrc"] = v_hoverlabel.BgcolorsrcValidator() self._validators["bordercolor"] = v_hoverlabel.BordercolorValidator() self._validators["bordercolorsrc"] = v_hoverlabel.BordercolorsrcValidator() self._validators["font"] = v_hoverlabel.FontValidator() self._validators["namelength"] = v_hoverlabel.NamelengthValidator() self._validators["namelengthsrc"] = v_hoverlabel.NamelengthsrcValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("align", None) self["align"] = align if align is not None else _v _v = arg.pop("alignsrc", None) self["alignsrc"] = alignsrc if alignsrc is not None else _v _v = arg.pop("bgcolor", None) self["bgcolor"] = bgcolor if bgcolor is not None else _v _v = arg.pop("bgcolorsrc", None) self["bgcolorsrc"] = bgcolorsrc if bgcolorsrc is not None else _v _v = arg.pop("bordercolor", None) self["bordercolor"] = bordercolor if bordercolor is not None else _v _v = arg.pop("bordercolorsrc", None) self["bordercolorsrc"] = bordercolorsrc if bordercolorsrc is not None else _v _v = arg.pop("font", None) self["font"] = font if font is not None else _v _v = arg.pop("namelength", None) self["namelength"] = namelength if namelength is not None else _v _v = arg.pop("namelengthsrc", None) self["namelengthsrc"] = namelengthsrc if namelengthsrc is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False from plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType import copy as _copy class ErrorY(_BaseTraceHierarchyType): # array # ----- @property def array(self): """ Sets the data corresponding the length of each error bar. Values are plotted relative to the underlying data. The 'array' property is an array that may be specified as a tuple, list, numpy array, or pandas Series Returns ------- numpy.ndarray """ return self["array"] @array.setter def array(self, val): self["array"] = val # arrayminus # ---------- @property def arrayminus(self): """ Sets the data corresponding the length of each error bar in the bottom (left) direction for vertical (horizontal) bars Values are plotted relative to the underlying data. The 'arrayminus' property is an array that may be specified as a tuple, list, numpy array, or pandas Series Returns ------- numpy.ndarray """ return self["arrayminus"] @arrayminus.setter def arrayminus(self, val): self["arrayminus"] = val # arrayminussrc # ------------- @property def arrayminussrc(self): """ Sets the source reference on plot.ly for arrayminus . The 'arrayminussrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["arrayminussrc"] @arrayminussrc.setter def arrayminussrc(self, val): self["arrayminussrc"] = val # arraysrc # -------- @property def arraysrc(self): """ Sets the source reference on plot.ly for array . The 'arraysrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["arraysrc"] @arraysrc.setter def arraysrc(self, val): self["arraysrc"] = val # color # ----- @property def color(self): """ Sets the stoke color of the error bars. 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 # symmetric # --------- @property def symmetric(self): """ Determines whether or not the error bars have the same length in both direction (top/bottom for vertical bars, left/right for horizontal bars. The 'symmetric' property must be specified as a bool (either True, or False) Returns ------- bool """ return self["symmetric"] @symmetric.setter def symmetric(self, val): self["symmetric"] = val # thickness # --------- @property def thickness(self): """ Sets the thickness (in px) of the error bars. The 'thickness' property is a number and may be specified as: - An int or float in the interval [0, inf] Returns ------- int|float """ return self["thickness"] @thickness.setter def thickness(self, val): self["thickness"] = val # traceref # -------- @property def traceref(self): """ The 'traceref' property is a integer and may be specified as: - An int (or float that will be cast to an int) in the interval [0, 9223372036854775807] Returns ------- int """ return self["traceref"] @traceref.setter def traceref(self, val): self["traceref"] = val # tracerefminus # ------------- @property def tracerefminus(self): """ The 'tracerefminus' property is a integer and may be specified as: - An int (or float that will be cast to an int) in the interval [0, 9223372036854775807] Returns ------- int """ return self["tracerefminus"] @tracerefminus.setter def tracerefminus(self, val): self["tracerefminus"] = val # type # ---- @property def type(self): """ Determines the rule used to generate the error bars. If *constant`, the bar lengths are of a constant value. Set this constant in `value`. If "percent", the bar lengths correspond to a percentage of underlying data. Set this percentage in `value`. If "sqrt", the bar lengths correspond to the sqaure of the underlying data. If "data", the bar lengths are set with data set `array`. The 'type' property is an enumeration that may be specified as: - One of the following enumeration values: ['percent', 'constant', 'sqrt', 'data'] Returns ------- Any """ return self["type"] @type.setter def type(self, val): self["type"] = val # value # ----- @property def value(self): """ Sets the value of either the percentage (if `type` is set to "percent") or the constant (if `type` is set to "constant") corresponding to the lengths of the error bars. The 'value' property is a number and may be specified as: - An int or float in the interval [0, inf] Returns ------- int|float """ return self["value"] @value.setter def value(self, val): self["value"] = val # valueminus # ---------- @property def valueminus(self): """ Sets the value of either the percentage (if `type` is set to "percent") or the constant (if `type` is set to "constant") corresponding to the lengths of the error bars in the bottom (left) direction for vertical (horizontal) bars The 'valueminus' property is a number and may be specified as: - An int or float in the interval [0, inf] Returns ------- int|float """ return self["valueminus"] @valueminus.setter def valueminus(self, val): self["valueminus"] = val # visible # ------- @property def visible(self): """ Determines whether or not this set of error bars is visible. 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 width (in px) of the cross-bar at both ends of the error bars. 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 # property parent name # -------------------- @property def _parent_path_str(self): return "histogram" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ array Sets the data corresponding the length of each error bar. Values are plotted relative to the underlying data. arrayminus Sets the data corresponding the length of each error bar in the bottom (left) direction for vertical (horizontal) bars Values are plotted relative to the underlying data. arrayminussrc Sets the source reference on plot.ly for arrayminus . arraysrc Sets the source reference on plot.ly for array . color Sets the stoke color of the error bars. symmetric Determines whether or not the error bars have the same length in both direction (top/bottom for vertical bars, left/right for horizontal bars. thickness Sets the thickness (in px) of the error bars. traceref tracerefminus type Determines the rule used to generate the error bars. If *constant`, the bar lengths are of a constant value. Set this constant in `value`. If "percent", the bar lengths correspond to a percentage of underlying data. Set this percentage in `value`. If "sqrt", the bar lengths correspond to the sqaure of the underlying data. If "data", the bar lengths are set with data set `array`. value Sets the value of either the percentage (if `type` is set to "percent") or the constant (if `type` is set to "constant") corresponding to the lengths of the error bars. valueminus Sets the value of either the percentage (if `type` is set to "percent") or the constant (if `type` is set to "constant") corresponding to the lengths of the error bars in the bottom (left) direction for vertical (horizontal) bars visible Determines whether or not this set of error bars is visible. width Sets the width (in px) of the cross-bar at both ends of the error bars. """ def __init__( self, arg=None, array=None, arrayminus=None, arrayminussrc=None, arraysrc=None, color=None, symmetric=None, thickness=None, traceref=None, tracerefminus=None, type=None, value=None, valueminus=None, visible=None, width=None, **kwargs ): """ Construct a new ErrorY object Parameters ---------- arg dict of properties compatible with this constructor or an instance of :class:`plotly.graph_objs.histogram.ErrorY` array Sets the data corresponding the length of each error bar. Values are plotted relative to the underlying data. arrayminus Sets the data corresponding the length of each error bar in the bottom (left) direction for vertical (horizontal) bars Values are plotted relative to the underlying data. arrayminussrc Sets the source reference on plot.ly for arrayminus . arraysrc Sets the source reference on plot.ly for array . color Sets the stoke color of the error bars. symmetric Determines whether or not the error bars have the same length in both direction (top/bottom for vertical bars, left/right for horizontal bars. thickness Sets the thickness (in px) of the error bars. traceref tracerefminus type Determines the rule used to generate the error bars. If *constant`, the bar lengths are of a constant value. Set this constant in `value`. If "percent", the bar lengths correspond to a percentage of underlying data. Set this percentage in `value`. If "sqrt", the bar lengths correspond to the sqaure of the underlying data. If "data", the bar lengths are set with data set `array`. value Sets the value of either the percentage (if `type` is set to "percent") or the constant (if `type` is set to "constant") corresponding to the lengths of the error bars. valueminus Sets the value of either the percentage (if `type` is set to "percent") or the constant (if `type` is set to "constant") corresponding to the lengths of the error bars in the bottom (left) direction for vertical (horizontal) bars visible Determines whether or not this set of error bars is visible. width Sets the width (in px) of the cross-bar at both ends of the error bars. Returns ------- ErrorY """ super(ErrorY, self).__init__("error_y") # 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.histogram.ErrorY constructor must be a dict or an instance of :class:`plotly.graph_objs.histogram.ErrorY`""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.histogram import error_y as v_error_y # Initialize validators # --------------------- self._validators["array"] = v_error_y.ArrayValidator() self._validators["arrayminus"] = v_error_y.ArrayminusValidator() self._validators["arrayminussrc"] = v_error_y.ArrayminussrcValidator() self._validators["arraysrc"] = v_error_y.ArraysrcValidator() self._validators["color"] = v_error_y.ColorValidator() self._validators["symmetric"] = v_error_y.SymmetricValidator() self._validators["thickness"] = v_error_y.ThicknessValidator() self._validators["traceref"] = v_error_y.TracerefValidator() self._validators["tracerefminus"] = v_error_y.TracerefminusValidator() self._validators["type"] = v_error_y.TypeValidator() self._validators["value"] = v_error_y.ValueValidator() self._validators["valueminus"] = v_error_y.ValueminusValidator() self._validators["visible"] = v_error_y.VisibleValidator() self._validators["width"] = v_error_y.WidthValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("array", None) self["array"] = array if array is not None else _v _v = arg.pop("arrayminus", None) self["arrayminus"] = arrayminus if arrayminus is not None else _v _v = arg.pop("arrayminussrc", None) self["arrayminussrc"] = arrayminussrc if arrayminussrc is not None else _v _v = arg.pop("arraysrc", None) self["arraysrc"] = arraysrc if arraysrc is not None else _v _v = arg.pop("color", None) self["color"] = color if color is not None else _v _v = arg.pop("symmetric", None) self["symmetric"] = symmetric if symmetric is not None else _v _v = arg.pop("thickness", None) self["thickness"] = thickness if thickness is not None else _v _v = arg.pop("traceref", None) self["traceref"] = traceref if traceref is not None else _v _v = arg.pop("tracerefminus", None) self["tracerefminus"] = tracerefminus if tracerefminus is not None else _v _v = arg.pop("type", None) self["type"] = type if type is not None else _v _v = arg.pop("value", None) self["value"] = value if value is not None else _v _v = arg.pop("valueminus", None) self["valueminus"] = valueminus if valueminus is not None else _v _v = arg.pop("visible", None) self["visible"] = visible if visible is not None else _v _v = arg.pop("width", None) self["width"] = width if width is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False from plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType import copy as _copy class ErrorX(_BaseTraceHierarchyType): # array # ----- @property def array(self): """ Sets the data corresponding the length of each error bar. Values are plotted relative to the underlying data. The 'array' property is an array that may be specified as a tuple, list, numpy array, or pandas Series Returns ------- numpy.ndarray """ return self["array"] @array.setter def array(self, val): self["array"] = val # arrayminus # ---------- @property def arrayminus(self): """ Sets the data corresponding the length of each error bar in the bottom (left) direction for vertical (horizontal) bars Values are plotted relative to the underlying data. The 'arrayminus' property is an array that may be specified as a tuple, list, numpy array, or pandas Series Returns ------- numpy.ndarray """ return self["arrayminus"] @arrayminus.setter def arrayminus(self, val): self["arrayminus"] = val # arrayminussrc # ------------- @property def arrayminussrc(self): """ Sets the source reference on plot.ly for arrayminus . The 'arrayminussrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["arrayminussrc"] @arrayminussrc.setter def arrayminussrc(self, val): self["arrayminussrc"] = val # arraysrc # -------- @property def arraysrc(self): """ Sets the source reference on plot.ly for array . The 'arraysrc' property must be specified as a string or as a plotly.grid_objs.Column object Returns ------- str """ return self["arraysrc"] @arraysrc.setter def arraysrc(self, val): self["arraysrc"] = val # color # ----- @property def color(self): """ Sets the stoke color of the error bars. 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 # copy_ystyle # ----------- @property def copy_ystyle(self): """ The 'copy_ystyle' property must be specified as a bool (either True, or False) Returns ------- bool """ return self["copy_ystyle"] @copy_ystyle.setter def copy_ystyle(self, val): self["copy_ystyle"] = val # symmetric # --------- @property def symmetric(self): """ Determines whether or not the error bars have the same length in both direction (top/bottom for vertical bars, left/right for horizontal bars. The 'symmetric' property must be specified as a bool (either True, or False) Returns ------- bool """ return self["symmetric"] @symmetric.setter def symmetric(self, val): self["symmetric"] = val # thickness # --------- @property def thickness(self): """ Sets the thickness (in px) of the error bars. The 'thickness' property is a number and may be specified as: - An int or float in the interval [0, inf] Returns ------- int|float """ return self["thickness"] @thickness.setter def thickness(self, val): self["thickness"] = val # traceref # -------- @property def traceref(self): """ The 'traceref' property is a integer and may be specified as: - An int (or float that will be cast to an int) in the interval [0, 9223372036854775807] Returns ------- int """ return self["traceref"] @traceref.setter def traceref(self, val): self["traceref"] = val # tracerefminus # ------------- @property def tracerefminus(self): """ The 'tracerefminus' property is a integer and may be specified as: - An int (or float that will be cast to an int) in the interval [0, 9223372036854775807] Returns ------- int """ return self["tracerefminus"] @tracerefminus.setter def tracerefminus(self, val): self["tracerefminus"] = val # type # ---- @property def type(self): """ Determines the rule used to generate the error bars. If *constant`, the bar lengths are of a constant value. Set this constant in `value`. If "percent", the bar lengths correspond to a percentage of underlying data. Set this percentage in `value`. If "sqrt", the bar lengths correspond to the sqaure of the underlying data. If "data", the bar lengths are set with data set `array`. The 'type' property is an enumeration that may be specified as: - One of the following enumeration values: ['percent', 'constant', 'sqrt', 'data'] Returns ------- Any """ return self["type"] @type.setter def type(self, val): self["type"] = val # value # ----- @property def value(self): """ Sets the value of either the percentage (if `type` is set to "percent") or the constant (if `type` is set to "constant") corresponding to the lengths of the error bars. The 'value' property is a number and may be specified as: - An int or float in the interval [0, inf] Returns ------- int|float """ return self["value"] @value.setter def value(self, val): self["value"] = val # valueminus # ---------- @property def valueminus(self): """ Sets the value of either the percentage (if `type` is set to "percent") or the constant (if `type` is set to "constant") corresponding to the lengths of the error bars in the bottom (left) direction for vertical (horizontal) bars The 'valueminus' property is a number and may be specified as: - An int or float in the interval [0, inf] Returns ------- int|float """ return self["valueminus"] @valueminus.setter def valueminus(self, val): self["valueminus"] = val # visible # ------- @property def visible(self): """ Determines whether or not this set of error bars is visible. 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 width (in px) of the cross-bar at both ends of the error bars. 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 # property parent name # -------------------- @property def _parent_path_str(self): return "histogram" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ array Sets the data corresponding the length of each error bar. Values are plotted relative to the underlying data. arrayminus Sets the data corresponding the length of each error bar in the bottom (left) direction for vertical (horizontal) bars Values are plotted relative to the underlying data. arrayminussrc Sets the source reference on plot.ly for arrayminus . arraysrc Sets the source reference on plot.ly for array . color Sets the stoke color of the error bars. copy_ystyle symmetric Determines whether or not the error bars have the same length in both direction (top/bottom for vertical bars, left/right for horizontal bars. thickness Sets the thickness (in px) of the error bars. traceref tracerefminus type Determines the rule used to generate the error bars. If *constant`, the bar lengths are of a constant value. Set this constant in `value`. If "percent", the bar lengths correspond to a percentage of underlying data. Set this percentage in `value`. If "sqrt", the bar lengths correspond to the sqaure of the underlying data. If "data", the bar lengths are set with data set `array`. value Sets the value of either the percentage (if `type` is set to "percent") or the constant (if `type` is set to "constant") corresponding to the lengths of the error bars. valueminus Sets the value of either the percentage (if `type` is set to "percent") or the constant (if `type` is set to "constant") corresponding to the lengths of the error bars in the bottom (left) direction for vertical (horizontal) bars visible Determines whether or not this set of error bars is visible. width Sets the width (in px) of the cross-bar at both ends of the error bars. """ def __init__( self, arg=None, array=None, arrayminus=None, arrayminussrc=None, arraysrc=None, color=None, copy_ystyle=None, symmetric=None, thickness=None, traceref=None, tracerefminus=None, type=None, value=None, valueminus=None, visible=None, width=None, **kwargs ): """ Construct a new ErrorX object Parameters ---------- arg dict of properties compatible with this constructor or an instance of :class:`plotly.graph_objs.histogram.ErrorX` array Sets the data corresponding the length of each error bar. Values are plotted relative to the underlying data. arrayminus Sets the data corresponding the length of each error bar in the bottom (left) direction for vertical (horizontal) bars Values are plotted relative to the underlying data. arrayminussrc Sets the source reference on plot.ly for arrayminus . arraysrc Sets the source reference on plot.ly for array . color Sets the stoke color of the error bars. copy_ystyle symmetric Determines whether or not the error bars have the same length in both direction (top/bottom for vertical bars, left/right for horizontal bars. thickness Sets the thickness (in px) of the error bars. traceref tracerefminus type Determines the rule used to generate the error bars. If *constant`, the bar lengths are of a constant value. Set this constant in `value`. If "percent", the bar lengths correspond to a percentage of underlying data. Set this percentage in `value`. If "sqrt", the bar lengths correspond to the sqaure of the underlying data. If "data", the bar lengths are set with data set `array`. value Sets the value of either the percentage (if `type` is set to "percent") or the constant (if `type` is set to "constant") corresponding to the lengths of the error bars. valueminus Sets the value of either the percentage (if `type` is set to "percent") or the constant (if `type` is set to "constant") corresponding to the lengths of the error bars in the bottom (left) direction for vertical (horizontal) bars visible Determines whether or not this set of error bars is visible. width Sets the width (in px) of the cross-bar at both ends of the error bars. Returns ------- ErrorX """ super(ErrorX, self).__init__("error_x") # 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.histogram.ErrorX constructor must be a dict or an instance of :class:`plotly.graph_objs.histogram.ErrorX`""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.histogram import error_x as v_error_x # Initialize validators # --------------------- self._validators["array"] = v_error_x.ArrayValidator() self._validators["arrayminus"] = v_error_x.ArrayminusValidator() self._validators["arrayminussrc"] = v_error_x.ArrayminussrcValidator() self._validators["arraysrc"] = v_error_x.ArraysrcValidator() self._validators["color"] = v_error_x.ColorValidator() self._validators["copy_ystyle"] = v_error_x.CopyYstyleValidator() self._validators["symmetric"] = v_error_x.SymmetricValidator() self._validators["thickness"] = v_error_x.ThicknessValidator() self._validators["traceref"] = v_error_x.TracerefValidator() self._validators["tracerefminus"] = v_error_x.TracerefminusValidator() self._validators["type"] = v_error_x.TypeValidator() self._validators["value"] = v_error_x.ValueValidator() self._validators["valueminus"] = v_error_x.ValueminusValidator() self._validators["visible"] = v_error_x.VisibleValidator() self._validators["width"] = v_error_x.WidthValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("array", None) self["array"] = array if array is not None else _v _v = arg.pop("arrayminus", None) self["arrayminus"] = arrayminus if arrayminus is not None else _v _v = arg.pop("arrayminussrc", None) self["arrayminussrc"] = arrayminussrc if arrayminussrc is not None else _v _v = arg.pop("arraysrc", None) self["arraysrc"] = arraysrc if arraysrc is not None else _v _v = arg.pop("color", None) self["color"] = color if color is not None else _v _v = arg.pop("copy_ystyle", None) self["copy_ystyle"] = copy_ystyle if copy_ystyle is not None else _v _v = arg.pop("symmetric", None) self["symmetric"] = symmetric if symmetric is not None else _v _v = arg.pop("thickness", None) self["thickness"] = thickness if thickness is not None else _v _v = arg.pop("traceref", None) self["traceref"] = traceref if traceref is not None else _v _v = arg.pop("tracerefminus", None) self["tracerefminus"] = tracerefminus if tracerefminus is not None else _v _v = arg.pop("type", None) self["type"] = type if type is not None else _v _v = arg.pop("value", None) self["value"] = value if value is not None else _v _v = arg.pop("valueminus", None) self["valueminus"] = valueminus if valueminus is not None else _v _v = arg.pop("visible", None) self["visible"] = visible if visible is not None else _v _v = arg.pop("width", None) self["width"] = width if width is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False from plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType import copy as _copy class Cumulative(_BaseTraceHierarchyType): # currentbin # ---------- @property def currentbin(self): """ Only applies if cumulative is enabled. Sets whether the current bin is included, excluded, or has half of its value included in the current cumulative value. "include" is the default for compatibility with various other tools, however it introduces a half-bin bias to the results. "exclude" makes the opposite half-bin bias, and "half" removes it. The 'currentbin' property is an enumeration that may be specified as: - One of the following enumeration values: ['include', 'exclude', 'half'] Returns ------- Any """ return self["currentbin"] @currentbin.setter def currentbin(self, val): self["currentbin"] = val # direction # --------- @property def direction(self): """ Only applies if cumulative is enabled. If "increasing" (default) we sum all prior bins, so the result increases from left to right. If "decreasing" we sum later bins so the result decreases from left to right. The 'direction' property is an enumeration that may be specified as: - One of the following enumeration values: ['increasing', 'decreasing'] Returns ------- Any """ return self["direction"] @direction.setter def direction(self, val): self["direction"] = val # enabled # ------- @property def enabled(self): """ If true, display the cumulative distribution by summing the binned values. Use the `direction` and `centralbin` attributes to tune the accumulation method. Note: in this mode, the "density" `histnorm` settings behave the same as their equivalents without "density": "" and "density" both rise to the number of data points, and "probability" and *probability density* both rise to the number of sample points. The 'enabled' property must be specified as a bool (either True, or False) Returns ------- bool """ return self["enabled"] @enabled.setter def enabled(self, val): self["enabled"] = val # property parent name # -------------------- @property def _parent_path_str(self): return "histogram" # Self properties description # --------------------------- @property def _prop_descriptions(self): return """\ currentbin Only applies if cumulative is enabled. Sets whether the current bin is included, excluded, or has half of its value included in the current cumulative value. "include" is the default for compatibility with various other tools, however it introduces a half-bin bias to the results. "exclude" makes the opposite half-bin bias, and "half" removes it. direction Only applies if cumulative is enabled. If "increasing" (default) we sum all prior bins, so the result increases from left to right. If "decreasing" we sum later bins so the result decreases from left to right. enabled If true, display the cumulative distribution by summing the binned values. Use the `direction` and `centralbin` attributes to tune the accumulation method. Note: in this mode, the "density" `histnorm` settings behave the same as their equivalents without "density": "" and "density" both rise to the number of data points, and "probability" and *probability density* both rise to the number of sample points. """ def __init__( self, arg=None, currentbin=None, direction=None, enabled=None, **kwargs ): """ Construct a new Cumulative object Parameters ---------- arg dict of properties compatible with this constructor or an instance of :class:`plotly.graph_objs.histogram.Cumulative` currentbin Only applies if cumulative is enabled. Sets whether the current bin is included, excluded, or has half of its value included in the current cumulative value. "include" is the default for compatibility with various other tools, however it introduces a half-bin bias to the results. "exclude" makes the opposite half-bin bias, and "half" removes it. direction Only applies if cumulative is enabled. If "increasing" (default) we sum all prior bins, so the result increases from left to right. If "decreasing" we sum later bins so the result decreases from left to right. enabled If true, display the cumulative distribution by summing the binned values. Use the `direction` and `centralbin` attributes to tune the accumulation method. Note: in this mode, the "density" `histnorm` settings behave the same as their equivalents without "density": "" and "density" both rise to the number of data points, and "probability" and *probability density* both rise to the number of sample points. Returns ------- Cumulative """ super(Cumulative, self).__init__("cumulative") # 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.histogram.Cumulative constructor must be a dict or an instance of :class:`plotly.graph_objs.histogram.Cumulative`""" ) # Handle skip_invalid # ------------------- self._skip_invalid = kwargs.pop("skip_invalid", False) # Import validators # ----------------- from plotly.validators.histogram import cumulative as v_cumulative # Initialize validators # --------------------- self._validators["currentbin"] = v_cumulative.CurrentbinValidator() self._validators["direction"] = v_cumulative.DirectionValidator() self._validators["enabled"] = v_cumulative.EnabledValidator() # Populate data dict with properties # ---------------------------------- _v = arg.pop("currentbin", None) self["currentbin"] = currentbin if currentbin is not None else _v _v = arg.pop("direction", None) self["direction"] = direction if direction is not None else _v _v = arg.pop("enabled", None) self["enabled"] = enabled if enabled is not None else _v # Process unknown kwargs # ---------------------- self._process_kwargs(**dict(arg, **kwargs)) # Reset skip_invalid # ------------------ self._skip_invalid = False __all__ = [ "Cumulative", "ErrorX", "ErrorY", "Hoverlabel", "Marker", "Selected", "Stream", "Unselected", "XBins", "YBins", "hoverlabel", "marker", "selected", "unselected", ] from plotly.graph_objs.histogram import unselected from plotly.graph_objs.histogram import selected from plotly.graph_objs.histogram import marker from plotly.graph_objs.histogram import hoverlabel