# --- THIS FILE IS AUTO-GENERATED --- # Modifications will be overwitten the next time code generation run. from plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType import copy as _copy class YBins(_BaseTraceHierarchyType): _parent_path_str = "histogram2d" _path_str = "histogram2d.ybins" _valid_props = {"end", "size", "start"} @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 @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). The 'size' property accepts values of any type Returns ------- Any """ return self["size"] @size.setter def size(self, val): self["size"] = val @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. The 'start' property accepts values of any type Returns ------- Any """ return self["start"] @start.setter def start(self, val): self["start"] = val @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). 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. """ 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.histogram2d.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). 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. Returns ------- YBins """ super().__init__("ybins") if "_parent" in kwargs: self._parent = kwargs["_parent"] return 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.histogram2d.YBins constructor must be a dict or an instance of :class:`plotly.graph_objs.histogram2d.YBins`""" ) self._skip_invalid = kwargs.pop("skip_invalid", False) self._validate = kwargs.pop("_validate", True) self._set_property("end", arg, end) self._set_property("size", arg, size) self._set_property("start", arg, start) self._process_kwargs(**dict(arg, **kwargs)) self._skip_invalid = False