Update app.py

app.py

@@ -1,140 +1,34 @@
-import altair as alt
-import gradio as gr
-import numpy as np
-import pandas as pd
-from vega_datasets import data
-
-
-def make_plot(plot_type):
-    if plot_type == "scatter_plot":
-        cars = data.cars()
-        return alt.Chart(cars).mark_point().encode(
-            x='Horsepower',
-            y='Miles_per_Gallon',
-            color='Origin',
-        )
-    elif plot_type == "heatmap":
-        # Compute x^2 + y^2 across a 2D grid
-        x, y = np.meshgrid(range(-5, 5), range(-5, 5))
-        z = x ** 2 + y ** 2
-
-        # Convert this grid to columnar data expected by Altair
-        source = pd.DataFrame({'x': x.ravel(),
-                            'y': y.ravel(),
-                            'z': z.ravel()})
-        return alt.Chart(source).mark_rect().encode(
-            x='x:O',
-            y='y:O',
-            color='z:Q'
-        )
-    elif plot_type == "us_map":
-        states = alt.topo_feature(data.us_10m.url, 'states')
-        source = data.income.url
-
-        return alt.Chart(source).mark_geoshape().encode(
-            shape='geo:G',
-            color='pct:Q',
-            tooltip=['name:N', 'pct:Q'],
-            facet=alt.Facet('group:N', columns=2),
-        ).transform_lookup(
-            lookup='id',
-            from_=alt.LookupData(data=states, key='id'),
-            as_='geo'
-        ).properties(
-            width=300,
-            height=175,
-        ).project(
-            type='albersUsa'
-        )
-    elif plot_type == "interactive_barplot":
-        source = data.movies.url
-
-        pts = alt.selection(type="single", encodings=['x'])
-
-        rect = alt.Chart(data.movies.url).mark_rect().encode(
-            alt.X('IMDB_Rating:Q', bin=True),
-            alt.Y('Rotten_Tomatoes_Rating:Q', bin=True),
-            alt.Color('count()',
-                scale=alt.Scale(scheme='greenblue'),
-                legend=alt.Legend(title='Total Records')
-            )
-        )
-
-        circ = rect.mark_point().encode(
-            alt.ColorValue('grey'),
-            alt.Size('count()',
-                legend=alt.Legend(title='Records in Selection')
-            )
-        ).transform_filter(
-            pts
-        )
-
-        bar = alt.Chart(source).mark_bar().encode(
-            x='Major_Genre:N',
-            y='count()',
-            color=alt.condition(pts, alt.ColorValue("steelblue"), alt.ColorValue("grey"))
-        ).properties(
-            width=550,
-            height=200
-        ).add_selection(pts)
+import altair
 
-        plot = alt.vconcat(
-            rect + circ,
-            bar
-        ).resolve_legend(
-            color="independent",
-            size="independent"
-        )
-        return plot
-    elif plot_type == "radial":
-        source = pd.DataFrame({"values": [12, 23, 47, 6, 52, 19]})
-
-        base = alt.Chart(source).encode(
-            theta=alt.Theta("values:Q", stack=True),
-            radius=alt.Radius("values", scale=alt.Scale(type="sqrt", zero=True, rangeMin=20)),
-            color="values:N",
-        )
-
-        c1 = base.mark_arc(innerRadius=20, stroke="#fff")
-
-        c2 = base.mark_text(radiusOffset=10).encode(text="values:Q")
-
-        return c1 + c2
-    elif plot_type == "multiline":
-        source = data.stocks()
-
-        highlight = alt.selection(type='single', on='mouseover',
-                                fields=['symbol'], nearest=True)
-
-        base = alt.Chart(source).encode(
-            x='date:T',
-            y='price:Q',
-            color='symbol:N'
-        )
-
-        points = base.mark_circle().encode(
-            opacity=alt.value(0)
-        ).add_selection(
-            highlight
-        ).properties(
-            width=600
-        )
-
-        lines = base.mark_line().encode(
-            size=alt.condition(~highlight, alt.value(1), alt.value(3))
-        )
+import gradio as gr
+from math import sqrt
+import matplotlib
 
-        return points + lines
+matplotlib.use("Agg")
 
+import matplotlib.pyplot as plt
+import numpy as np
+import plotly.express as px
+import pandas as pd
 
-with gr.Blocks() as demo:
-    button = gr.Radio(label="Plot type",
-                      choices=['scatter_plot', 'heatmap', 'us_map',
-                               'interactive_barplot', "radial", "multiline"], value='scatter_plot')
-    plot = gr.Plot(label="Plot")
-    button.change(make_plot, inputs=button, outputs=[plot])
-    demo.load(make_plot, inputs=[button], outputs=[plot])
 
+def outbreak(date):
+  if date:
+    # start_day = start_day
+    # final_day = date
+    # x = np.arange(start_day, final_day + 1)
+    fig = plt.figure()
+    plt.plot(y)
+    plt.title("観客数予測")
+    plt.ylabel("観客数")
+    plt.xlabel("Days since Day 0")
+    return fig
+
+demo = gr.Interface(
+    fn=outbreak,
+    inputs='checkbox',
+    outputs=gr.Plot()
+)
 
 if __name__ == "__main__":
-    demo.launch()
+    demo.launch()