done

lib/python3.11/site-packages/plotly/graph_objs/histogram2dcontour/_ybins.py

@@ -0,0 +1,187 @@
+#                   --- 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 = "histogram2dcontour"
+    _path_str = "histogram2dcontour.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<n>" 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<n>" 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.histogram2dcontour.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<n>" 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.histogram2dcontour.YBins
+constructor must be a dict or
+an instance of :class:`plotly.graph_objs.histogram2dcontour.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