Merge pull request #40 from ksunden/artists

Introduce artist classes, starting with Line

Author: tacaswell

data_prototype/artist.py

@@ -0,0 +1,236 @@
+from bisect import insort
+from typing import Sequence
+
+import numpy as np
+
+from .containers import DataContainer, ArrayContainer, DataUnion
+from .description import Desc, desc_like
+from .conversion_edge import Edge, Graph, TransformEdge
+
+
+class Artist:
+    required_keys: dict[str, Desc]
+
+    # defaults?
+    def __init__(
+        self, container: DataContainer, edges: Sequence[Edge] | None = None, **kwargs
+    ):
+        kwargs_cont = ArrayContainer(**kwargs)
+        self._container = DataUnion(container, kwargs_cont)
+
+        edges = edges or []
+        self._visible = True
+        self._graph = Graph(edges)
+        self._clip_box: DataContainer = ArrayContainer(
+            {"x": "parent", "y": "parent"},
+            **{"x": np.asarray([0, 1]), "y": np.asarray([0, 1])}
+        )
+
+    def draw(self, renderer, graph: Graph) -> None:
+        return
+
+    def set_clip_box(self, container: DataContainer) -> None:
+        self._clip_box = container
+
+    def get_clip_box(self, container: DataContainer) -> DataContainer:
+        return self._clip_box
+
+    def get_visible(self):
+        return self._visible
+
+    def set_visible(self, visible):
+        self._visible = visible
+
+
+class CompatibilityArtist:
+    """A compatibility shim to ducktype as a classic Matplotlib Artist.
+
+    At this time features are implemented on an "as needed" basis, and many
+    are only implemented insofar as they do not fail, not necessarily providing
+    full functionality of a full MPL Artist.
+
+    The idea is to keep the new Artist class as minimal as possible.
+    As features are added this may shrink.
+
+    The main thing we are trying to avoid is the reliance on the axes/figure
+
+    Ultimately for useability, whatever remains shimmed out here may be rolled in as
+    some form of gaurded option to ``Artist`` itself, but a firm dividing line is
+    useful for avoiding accidental dependency.
+    """
+
+    def __init__(self, artist: Artist):
+        self._artist = artist
+
+        self._axes = None
+        self.figure = None
+        self._clippath = None
+        self._visible = True
+        self.zorder = 2
+        self._graph = Graph([])
+
+    @property
+    def axes(self):
+        return self._axes
+
+    @axes.setter
+    def axes(self, ax):
+        self._axes = ax
+
+        if self._axes is None:
+            self._graph = Graph([])
+            return
+
+        desc: Desc = Desc(("N",), coordinates="data")
+        xy: dict[str, Desc] = {"x": desc, "y": desc}
+        self._graph = Graph(
+            [
+                TransformEdge(
+                    "data",
+                    xy,
+                    desc_like(xy, coordinates="axes"),
+                    transform=self._axes.transData - self._axes.transAxes,
+                ),
+                TransformEdge(
+                    "axes",
+                    desc_like(xy, coordinates="axes"),
+                    desc_like(xy, coordinates="display"),
+                    transform=self._axes.transAxes,
+                ),
+            ],
+            aliases=(("parent", "axes"),),
+        )
+
+    def set_figure(self, fig):
+        self.figure = fig
+
+    def is_transform_set(self):
+        return True
+
+    def get_mouseover(self):
+        return False
+
+    def get_clip_path(self):
+        self._clippath
+
+    def set_clip_path(self, path):
+        self._clippath = path
+
+    def get_animated(self):
+        return False
+
+    def get_visible(self):
+        return self._visible
+
+    def set_visible(self, visible):
+        self._visible = visible
+
+    def draw(self, renderer, graph=None):
+        if not self.get_visible():
+            return
+
+        if graph is None:
+            graph = Graph([])
+        self._artist.draw(renderer, graph + self._graph)
+
+
+class CompatibilityAxes:
+    """A compatibility shim to add to traditional matplotlib axes.
+
+    At this time features are implemented on an "as needed" basis, and many
+    are only implemented insofar as they do not fail, not necessarily providing
+    full functionality of a full MPL Artist.
+
+    The idea is to keep the new Artist class as minimal as possible.
+    As features are added this may shrink.
+
+    The main thing we are trying to avoid is the reliance on the axes/figure
+
+    Ultimately for useability, whatever remains shimmed out here may be rolled in as
+    some form of gaurded option to ``Artist`` itself, but a firm dividing line is
+    useful for avoiding accidental dependency.
+    """
+
+    def __init__(self, axes):
+        self._axes = axes
+        self.figure = None
+        self._clippath = None
+        self._visible = True
+        self.zorder = 2
+        self._children: list[tuple[float, Artist]] = []
+
+    @property
+    def axes(self):
+        return self._axes
+
+    @axes.setter
+    def axes(self, ax):
+        self._axes = ax
+
+        if self._axes is None:
+            self._graph = Graph([])
+            return
+
+        desc: Desc = Desc(("N",), coordinates="data")
+        xy: dict[str, Desc] = {"x": desc, "y": desc}
+        self._graph = Graph(
+            [
+                TransformEdge(
+                    "data",
+                    xy,
+                    desc_like(xy, coordinates="axes"),
+                    transform=self._axes.transData - self._axes.transAxes,
+                ),
+                TransformEdge(
+                    "axes",
+                    desc_like(xy, coordinates="axes"),
+                    desc_like(xy, coordinates="display"),
+                    transform=self._axes.transAxes,
+                ),
+            ],
+            aliases=(("parent", "axes"),),
+        )
+
+    def set_figure(self, fig):
+        self.figure = fig
+
+    def is_transform_set(self):
+        return True
+
+    def get_mouseover(self):
+        return False
+
+    def get_clip_path(self):
+        self._clippath
+
+    def set_clip_path(self, path):
+        self._clippath = path
+
+    def get_animated(self):
+        return False
+
+    def draw(self, renderer, graph=None):
+        if not self.visible:
+            return
+        if graph is None:
+            graph = Graph([])
+
+        graph = graph + self._graph
+
+        for _, c in self._children:
+            c.draw(renderer, graph)
+
+    def add_artist(self, artist, zorder=1):
+        insort(self._children, (zorder, artist), key=lambda x: x[0])
+
+    def set_xlim(self, min_=None, max_=None):
+        self.axes.set_xlim(min_, max_)
+
+    def set_ylim(self, min_=None, max_=None):
+        self.axes.set_ylim(min_, max_)
+
+    def get_visible(self):
+        return self._visible
+
+    def set_visible(self, visible):
+        self._visible = visible

data_prototype/containers.py

@@ -82,14 +82,15 @@ class NoNewKeys(ValueError): ...
 
 
 class ArrayContainer:
-    def __init__(self, **data):
+    def __init__(self, coordinates: dict[str, str] | None = None, /, **data):
+        coordinates = coordinates or {}
         self._data = data
         self._cache_key = str(uuid.uuid4())
         self._desc = {
             k: (
-                Desc(v.shape, v.dtype)
+                Desc(v.shape, coordinates.get(k, "auto"))
                 if isinstance(v, np.ndarray)
-                else Desc((), type(v))
+                else Desc(())
             )
             for k, v in data.items()
         }
@@ -117,7 +118,7 @@ def update(self, **data):
 
 class RandomContainer:
     def __init__(self, **shapes):
-        self._desc = {k: Desc(s, np.dtype(float)) for k, s in shapes.items()}
+        self._desc = {k: Desc(s) for k, s in shapes.items()}
 
     def query(
         self,
@@ -171,7 +172,7 @@ def __init__(
         def _split(input_dict):
             out = {}
             for k, (shape, func) in input_dict.items():
-                self._desc[k] = Desc(shape, np.dtype(float))
+                self._desc[k] = Desc(shape)
                 out[k] = func
             return out
 
@@ -196,7 +197,7 @@ def query(
         # if hash_key in self._cache:
         #    return self._cache[hash_key], hash_key
 
-        desc = Desc(("N",), np.dtype("f8"))
+        desc = Desc(("N",))
         xy = {"x": desc, "y": desc}
         data_lim = graph.evaluator(
             desc_like(xy, coordinates="data"),
@@ -243,8 +244,8 @@ def __init__(self, raw_data, num_bins: int):
         self._raw_data = raw_data
         self._num_bins = num_bins
         self._desc = {
-            "edges": Desc((num_bins + 1 + 2,), np.dtype(float)),
-            "density": Desc((num_bins + 2,), np.dtype(float)),
+            "edges": Desc((num_bins + 1 + 2,)),
+            "density": Desc((num_bins + 2,)),
         }
         self._full_range = (raw_data.min(), raw_data.max())
         self._cache: MutableMapping[Union[str, int], Any] = LFUCache(64)
@@ -256,7 +257,7 @@ def query(
     ) -> Tuple[Dict[str, Any], Union[str, int]]:
         dmin, dmax = self._full_range
 
-        desc = Desc(("N",), np.dtype("f8"))
+        desc = Desc(("N",))
         xy = {"x": desc, "y": desc}
         data_lim = graph.evaluator(
             desc_like(xy, coordinates="data"),
@@ -302,8 +303,8 @@ def __init__(self, series: pd.Series, *, index_name: str, col_name: str):
         self._index_name = index_name
         self._col_name = col_name
         self._desc = {
-            index_name: Desc((len(series),), series.index.dtype),
-            col_name: Desc((len(series),), series.dtype),
+            index_name: Desc((len(series),)),
+            col_name: Desc((len(series),)),
         }
         self._hash_key = str(uuid.uuid4())
 
@@ -343,9 +344,9 @@ def __init__(
 
         self._desc: Dict[str, Desc] = {}
         if self._index_name is not None:
-            self._desc[self._index_name] = Desc((len(df),), df.index.dtype)
+            self._desc[self._index_name] = Desc((len(df),))
         for col, out in self._col_name_dict.items():
-            self._desc[out] = Desc((len(df),), df[col].dtype)
+            self._desc[out] = Desc((len(df),))
 
         self._hash_key = str(uuid.uuid4())