Merge pull request #3 from Kitware/vue3

feat(vue23): Support vue2 and vue3 with latest plotly lib

examples/requirements.txt

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+trame
+plotly
+pandas

examples/vue2/charts-resizable-client.py

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+import plotly.graph_objects as go
+import plotly.figure_factory as ff
+
+from trame.app import get_server
+from trame.ui.vuetify import SinglePageLayout
+from trame.widgets import vuetify, plotly
+
+import numpy as np
+import pandas as pd
+
+# -----------------------------------------------------------------------------
+# Trame setup
+# -----------------------------------------------------------------------------
+
+server = get_server()
+server.client_type = "vue2"
+state, ctrl = server.state, server.controller
+
+# -----------------------------------------------------------------------------
+# Charts handling
+# -----------------------------------------------------------------------------
+
+contour_raw_data = pd.read_json(
+    "https://raw.githubusercontent.com/plotly/datasets/master/contour_data.json"
+)
+scatter_raw_data = pd.read_json(
+    "https://raw.githubusercontent.com/plotly/datasets/master/scatter_data.json"
+)
+polar_data = pd.read_csv(
+    "https://raw.githubusercontent.com/plotly/datasets/master/polar_dataset.csv"
+)
+
+scatter_data = scatter_raw_data["Data"]
+
+
+def clean_data(data_in):
+    """
+    Cleans data in a format which can be conveniently
+    used for drawing traces. Takes a dictionary as the
+    input, and returns a list in the following format:
+
+    input = {'key': ['a b c']}
+    output = [key, [a, b, c]]
+    """
+    key = list(data_in.keys())[0]
+    data_out = [key]
+    for i in data_in[key]:
+        data_out.append(list(map(float, i.split(" "))))
+
+    return data_out
+
+
+def create_ternary_fig(**kwargs):
+    contour_dict = contour_raw_data["Data"]
+
+    # Defining a colormap:
+    colors = [
+        "#8dd3c7",
+        "#ffffb3",
+        "#bebada",
+        "#fb8072",
+        "#80b1d3",
+        "#fdb462",
+        "#b3de69",
+        "#fccde5",
+        "#d9d9d9",
+        "#bc80bd",
+    ]
+    colors_iterator = iter(colors)
+
+    fig = go.Figure()
+
+    for raw_data in contour_dict:
+        data = clean_data(raw_data)
+
+        a = [inner_data[0] for inner_data in data[1:]]
+        a.append(data[1][0])  # Closing the loop
+
+        b = [inner_data[1] for inner_data in data[1:]]
+        b.append(data[1][1])  # Closing the loop
+
+        c = [inner_data[2] for inner_data in data[1:]]
+        c.append(data[1][2])  # Closing the loop
+
+        fig.add_trace(
+            go.Scatterternary(
+                text=data[0],
+                a=a,
+                b=b,
+                c=c,
+                mode="lines",
+                line=dict(color="#444", shape="spline"),
+                fill="toself",
+                fillcolor=colors_iterator.__next__(),
+            )
+        )
+
+    fig.update_layout(
+        margin=dict(l=50, r=50, t=50, b=50),
+    )
+    return fig
+
+
+def create_polar_fig(**kwargs):
+    fig = go.Figure()
+    fig.add_trace(
+        go.Scatterpolar(
+            r=polar_data["x1"].tolist(),
+            theta=polar_data["y"].tolist(),
+            mode="lines",
+            name="Figure 8",
+            line_color="peru",
+        )
+    )
+    fig.add_trace(
+        go.Scatterpolar(
+            r=polar_data["x2"].tolist(),
+            theta=polar_data["y"].tolist(),
+            mode="lines",
+            name="Cardioid",
+            line_color="darkviolet",
+        )
+    )
+    fig.add_trace(
+        go.Scatterpolar(
+            r=polar_data["x3"].tolist(),
+            theta=polar_data["y"].tolist(),
+            mode="lines",
+            name="Hypercardioid",
+            line_color="deepskyblue",
+        )
+    )
+
+    fig.update_layout(
+        # title = 'Mic Patterns',
+        margin=dict(l=20, r=20, t=20, b=20),
+        showlegend=False,
+    )
+    return fig
+
+
+def create_streamline_fig(**kwargs):
+    x = np.linspace(-3, 3, 100)
+    y = np.linspace(-3, 3, 100)
+    Y, X = np.meshgrid(x, y)
+    u = -1 - X**2 + Y
+    v = 1 + X - Y**2
+
+    # Create streamline figure
+    fig = ff.create_streamline(
+        x.tolist(),
+        y.tolist(),
+        u.tolist(),
+        v.tolist(),
+        arrow_scale=0.1,
+    )
+    fig.update_layout(
+        # title = 'Mic Patterns',
+        margin=dict(l=20, r=20, t=10, b=10),
+        showlegend=False,
+    )
+    return fig
+
+
+def create_contour_fig(**kwargs):
+    fig = go.Figure(
+        data=go.Contour(
+            z=[
+                [2, 4, 7, 12, 13, 14, 15, 16],
+                [3, 1, 6, 11, 12, 13, 16, 17],
+                [4, 2, 7, 7, 11, 14, 17, 18],
+                [5, 3, 8, 8, 13, 15, 18, 19],
+                [7, 4, 10, 9, 16, 18, 20, 19],
+                [9, 10, 5, 27, 23, 21, 21, 21],
+                [11, 14, 17, 26, 25, 24, 23, 22],
+            ],
+            contours={
+                "coloring": "heatmap",
+                "showlabels": True,
+                "labelfont": {
+                    "size": 12,
+                    "color": "black",
+                },
+            },
+            line_smoothing=1,
+        )
+    )
+    fig.update_layout(
+        # title = 'Mic Patterns',
+        margin=dict(l=20, r=20, t=10, b=10),
+        showlegend=False,
+    )
+    return fig
+
+
+# -----------------------------------------------------------------------------
+# GUI
+# -----------------------------------------------------------------------------
+
+
+state.trame__title = "Charts"
+
+with SinglePageLayout(server) as layout:
+    layout.title.set_text("Many charts")
+
+    with layout.content:
+        with vuetify.VContainer(fluid=True, classes="fill-height"):
+            with vuetify.VRow(style="height: 50%;"):
+                with vuetify.VCol():
+                    plotly.Figure(
+                        create_polar_fig(),
+                        display_mode_bar=("false",),
+                    )
+                with vuetify.VCol():
+                    plotly.Figure(
+                        create_ternary_fig(),
+                        display_mode_bar=("false",),
+                    )
+            with vuetify.VRow(style="height: 50%;"):
+                with vuetify.VCol():
+                    plotly.Figure(
+                        create_contour_fig(),
+                        display_mode_bar=("false",),
+                    )
+                with vuetify.VCol():
+                    plotly.Figure(
+                        create_streamline_fig(),
+                        display_mode_bar=("false",),
+                    )
+
+# -----------------------------------------------------------------------------
+# Main
+# -----------------------------------------------------------------------------
+
+if __name__ == "__main__":
+    server.start()