Merge pull request #92 from predict-idlab/figure_dict_input

🔥 add support for figure dict input + propagate _grid_str

Author: jvdd

plotly_resampler/figure_resampler/figure_resampler.py

@@ -55,8 +55,18 @@ def __init__(
             if isinstance(figure, BaseFigure):  # go.FigureWidget or AbstractFigureAggregator
                 # A base figure object, we first copy the layout and grid ref
                 f.layout = figure.layout
+                f._grid_str = figure._grid_str
                 f._grid_ref = figure._grid_ref
                 f.add_traces(figure.data)
+            elif isinstance(figure, dict) and (
+                "data" in figure or "layout" in figure # or "frames" in figure  # TODO
+            ):
+                # A dict with data, layout or frames
+                f.layout = figure.get("layout")
+                f._grid_str = figure.get("_grid_str")
+                f._grid_ref = figure.get("_grid_ref")
+                f.add_traces(figure.get("data"))
+                # f.add_frames(figure.get("frames")) TODO
             elif isinstance(figure, (dict, list)):
                 # A single trace dict or a list of traces
                 f.add_traces(figure)

plotly_resampler/figure_resampler/figure_resampler_interface.py

@@ -113,6 +113,7 @@ def __init__(
             # call __init__ with the correct layout and set the `_grid_ref` of the
             # to-be-converted figure
             f_ = self._figure_class(layout=figure.layout)
+            f_._grid_str = figure._grid_str
             f_._grid_ref = figure._grid_ref
             super().__init__(f_)
 

plotly_resampler/figure_resampler/figurewidget_resampler.py

@@ -59,8 +59,17 @@ def __init__(
         if isinstance(figure, BaseFigure):  # go.Figure or go.FigureWidget or AbstractFigureAggregator
             # A base figure object, we first copy the layout and grid ref
             f.layout = figure.layout
+            f._grid_str = figure._grid_str
             f._grid_ref = figure._grid_ref
             f.add_traces(figure.data)
+        elif isinstance(figure, dict) and (
+            "data" in figure or "layout" in figure # or "frames" in figure  # TODO
+        ):
+            f.layout = figure.get("layout")
+            f._grid_str = figure.get("_grid_str")
+            f._grid_ref = figure.get("_grid_ref")
+            f.add_traces(figure.get("data"))
+            # f.add_frames(figure.get("frames")) TODO
         elif isinstance(figure, (dict, list)):
             # A single trace dict or a list of traces
             f.add_traces(figure)

tests/test_figure_resampler.py

@@ -648,7 +648,7 @@ def test_fr_add_empty_trace():
     assert len(fig.hf_data[0]["y"]) == 0
 
 
-def test_fr_from_dict():
+def test_fr_from_trace_dict():
     y = np.array([1] * 10_000)
     base_fig = {
         "type": "scatter",
@@ -668,6 +668,24 @@ def test_fr_from_dict():
     assert fr_fig.data[0].uid in fr_fig._hf_data
 
 
+def test_fr_from_figure_dict():
+    y = np.array([1] * 10_000)
+    base_fig = go.Figure()
+    base_fig.add_trace(go.Scatter(y=y))
+
+    fr_fig = FigureResampler(base_fig.to_dict(), default_n_shown_samples=1000)
+    assert len(fr_fig.hf_data) == 1
+    assert (fr_fig.hf_data[0]["y"] == y).all()
+    assert len(fr_fig.data) == 1
+    assert len(fr_fig.data[0]["x"]) == 1_000
+    assert (fr_fig.data[0]["x"][0] >= 0) & (fr_fig.data[0]["x"][-1] < 10_000)
+    assert (fr_fig.data[0]["y"] == [1] * 1_000).all()
+
+    # assert that all the uuids of data and hf_data match
+    # this is a proxy for assuring that the dynamic aggregation should work
+    assert fr_fig.data[0].uid in fr_fig._hf_data
+
+
 def test_fr_empty_list():
     # and empty list -> so no concrete traces were added
     fr_fig = FigureResampler([], default_n_shown_samples=1000)
@@ -927,3 +945,57 @@ def test_fr_object_binary_data():
     assert fig.hf_data[0]["y"].dtype == "int64"
     assert fig.data[0]["y"].dtype == "int64"
     assert np.all(fig.data[0]["y"] == binary_series)
+
+
+def test_fr_copy_grid():
+    f = make_subplots(rows=2, cols=1)
+    f.add_scatter(y=np.arange(2_000), row=1, col=1)
+    f.add_scatter(y=np.arange(2_000), row=2, col=1)
+
+    ## go.Figure
+    assert isinstance(f, go.Figure)
+    assert f._grid_ref is not None
+    fr = FigureResampler(f)
+    assert fr._grid_ref is not None
+    assert fr._grid_ref == f._grid_ref
+    
+    ## go.FigureWidget
+    fw = go.FigureWidget(f)
+    assert fw._grid_ref is not None
+    assert isinstance(fw, go.FigureWidget)
+    fr = FigureResampler(fw)
+    assert fr._grid_ref is not None
+    assert fr._grid_ref == fw._grid_ref
+
+    ## FigureResampler
+    fr_ = FigureResampler(f)
+    assert fr_._grid_ref is not None
+    assert isinstance(fr_, FigureResampler)
+    fr = FigureResampler(fr_)
+    assert fr._grid_ref is not None
+    assert fr._grid_ref == fr_._grid_ref
+
+    ## FigureWidgetResampler
+    from plotly_resampler import FigureWidgetResampler
+    fwr = FigureWidgetResampler(f)
+    assert fwr._grid_ref is not None
+    assert isinstance(fwr, FigureWidgetResampler)
+    fr = FigureResampler(fwr)
+    assert fr._grid_ref is not None
+    assert fr._grid_ref == fwr._grid_ref
+
+    ## dict (with no _grid_ref)
+    f_dict = f.to_dict()
+    assert isinstance(f_dict, dict)
+    assert f_dict.get("_grid_ref") is None
+    fr = FigureResampler(f_dict)
+    assert fr._grid_ref is f_dict.get("_grid_ref")  # both are None
+
+    ## dict (with _grid_ref)
+    f_dict = f.to_dict()
+    f_dict["_grid_ref"] = f._grid_ref
+    assert isinstance(f_dict, dict)
+    assert f_dict.get("_grid_ref") is not None
+    fr = FigureResampler(f_dict)
+    assert fr._grid_ref is not None
+    assert fr._grid_ref == f_dict.get("_grid_ref")

tests/test_figurewidget_resampler.py

@@ -1534,24 +1534,42 @@ def test_fwr_time_based_data_s():
         assert (text == -hovertext).sum() == 1000
 
 
-def test_fwr_from_dict():
+def test_fwr_from_trace_dict():
     y = np.array([1] * 10_000)
     base_fig = {
         "type": "scatter",
         "y": y,
     }
 
-    fr_fig = FigureWidgetResampler(base_fig, default_n_shown_samples=1000)
-    assert len(fr_fig.hf_data) == 1
-    assert (fr_fig.hf_data[0]["y"] == y).all()
-    assert len(fr_fig.data) == 1
-    assert len(fr_fig.data[0]["x"]) == 1_000
-    assert (fr_fig.data[0]["x"][0] >= 0) & (fr_fig.data[0]["x"][-1] < 10_000)
-    assert (fr_fig.data[0]["y"] == [1] * 1_000).all()
+    fwr_fig = FigureWidgetResampler(base_fig, default_n_shown_samples=1000)
+    assert len(fwr_fig.hf_data) == 1
+    assert (fwr_fig.hf_data[0]["y"] == y).all()
+    assert len(fwr_fig.data) == 1
+    assert len(fwr_fig.data[0]["x"]) == 1_000
+    assert (fwr_fig.data[0]["x"][0] >= 0) & (fwr_fig.data[0]["x"][-1] < 10_000)
+    assert (fwr_fig.data[0]["y"] == [1] * 1_000).all()
 
     # assert that all the uuids of data and hf_data match
     # this is a proxy for assuring that the dynamic aggregation should work
-    assert fr_fig.data[0].uid in fr_fig._hf_data
+    assert fwr_fig.data[0].uid in fwr_fig._hf_data
+
+
+def test_fwr_from_figure_dict():
+    y = np.array([1] * 10_000)
+    base_fig = go.Figure()
+    base_fig.add_trace(go.Scatter(y=y))
+
+    fwr_fig = FigureWidgetResampler(base_fig.to_dict(), default_n_shown_samples=1000)
+    assert len(fwr_fig.hf_data) == 1
+    assert (fwr_fig.hf_data[0]["y"] == y).all()
+    assert len(fwr_fig.data) == 1
+    assert len(fwr_fig.data[0]["x"]) == 1_000
+    assert (fwr_fig.data[0]["x"][0] >= 0) & (fwr_fig.data[0]["x"][-1] < 10_000)
+    assert (fwr_fig.data[0]["y"] == [1] * 1_000).all()
+
+    # assert that all the uuids of data and hf_data match
+    # this is a proxy for assuring that the dynamic aggregation should work
+    assert fwr_fig.data[0].uid in fwr_fig._hf_data
 
 
 def test_fwr_empty_list():
@@ -1796,3 +1814,57 @@ def test_fwr_object_binary_data():
     assert fig.hf_data[0]["y"].dtype == "int64"
     assert fig.data[0]["y"].dtype == "int64"
     assert np.all(fig.data[0]["y"] == binary_series)
+
+
+def test_fwr_copy_grid():
+    f = make_subplots(rows=2, cols=1)
+    f.add_scatter(y=np.arange(2_000), row=1, col=1)
+    f.add_scatter(y=np.arange(2_000), row=2, col=1)
+
+    ## go.Figure
+    assert isinstance(f, go.Figure)
+    assert f._grid_ref is not None
+    fwr = FigureWidgetResampler(f)
+    assert fwr._grid_ref is not None
+    assert fwr._grid_ref == f._grid_ref
+    
+    ## go.FigureWidget
+    fw = go.FigureWidget(f)
+    assert fw._grid_ref is not None
+    assert isinstance(fw, go.FigureWidget)
+    fwr = FigureWidgetResampler(fw)
+    assert fwr._grid_ref is not None
+    assert fwr._grid_ref == fw._grid_ref
+
+    ## FigureWidgetResampler
+    fwr_ = FigureWidgetResampler(f)
+    assert fwr_._grid_ref is not None
+    assert isinstance(fwr_, FigureWidgetResampler)
+    fwr = FigureWidgetResampler(fwr_)
+    assert fwr._grid_ref is not None
+    assert fwr._grid_ref == fwr_._grid_ref
+
+    ## FigureResampler
+    from plotly_resampler import FigureResampler
+    fr = FigureResampler(f)
+    assert fr._grid_ref is not None
+    assert isinstance(fr, FigureResampler)
+    fwr = FigureWidgetResampler(fr)
+    assert fwr._grid_ref is not None
+    assert fwr._grid_ref == fr._grid_ref
+
+    ## dict (with no _grid_ref)
+    f_dict = f.to_dict()
+    assert isinstance(f_dict, dict)
+    assert f_dict.get("_grid_ref") is None
+    fwr = FigureWidgetResampler(f_dict)
+    assert fwr._grid_ref is f_dict.get("_grid_ref")  # both are None
+
+    ## dict (with _grid_ref)
+    f_dict = f.to_dict()
+    f_dict["_grid_ref"] = f._grid_ref
+    assert isinstance(f_dict, dict)
+    assert f_dict.get("_grid_ref") is not None
+    fwr = FigureWidgetResampler(f_dict)
+    assert fwr._grid_ref is not None
+    assert fwr._grid_ref == f_dict.get("_grid_ref")