Update app.py

app.py

@@ -22,36 +22,12 @@ sns.set_theme()
 dir = Path(__file__).resolve().parent
 www_dir = Path(__file__).parent.resolve() / "www"
 
-df = pd.read_csv(Path(__file__).parent / "penguins.csv", na_values="NA")
-numeric_cols: List[str] = df.select_dtypes(include=["float64"]).columns.tolist()
-species: List[str] = df["Species"].unique().tolist()
-species.sort()
-
 ### UI ###
 app_ui = ui.page_fillable(
     shinyswatch.theme.minty(),
     ui.layout_sidebar(
         ui.sidebar(
             ui.input_file("tile_image", "Choose an Image", accept=[".tif", ".tiff", ".png"], multiple=False),
-            # Artwork by @allison_horst
-            ui.input_selectize(
-                "xvar",
-                "X variable",
-                numeric_cols,
-                selected="Bill Length (mm)",
-            ),
-            ui.input_selectize(
-                "yvar",
-                "Y variable",
-                numeric_cols,
-                selected="Bill Depth (mm)",
-            ),
-            ui.input_checkbox_group(
-                "species", "Filter by species", species, selected=species
-            ),
-            ui.hr(),
-            ui.input_switch("by_species", "Show species", value=True),
-            ui.input_switch("show_margins", "Show marginal plots", value=True),
         ),
         #ui.output_image("uploaded_image"),  # display the uploaded sidewalk tile image, for some reason doesn't work on all accepted files
         ui.output_plot("prediction_plots", fill=True),
@@ -273,101 +249,6 @@ def server(input: Inputs, output: Outputs, session: Session):
         plt.tight_layout()
         
         return fig
-    
-
-
-
-    
-    
-    @reactive.Calc
-    def filtered_df() -> pd.DataFrame:
-        """Returns a Pandas data frame that includes only the desired rows"""
-
-        # This calculation "req"uires that at least one species is selected
-        req(len(input.species()) > 0)
-
-        # Filter the rows so we only include the desired species
-        return df[df["Species"].isin(input.species())]
-
-    @output
-    @render.plot
-    def scatter():
-        """Generates a plot for Shiny to display to the user"""
-
-        # The plotting function to use depends on whether margins are desired
-        plotfunc = sns.jointplot if input.show_margins() else sns.scatterplot
-
-        plotfunc(
-            data=filtered_df(),
-            x=input.xvar(),
-            y=input.yvar(),
-            palette=palette,
-            hue="Species" if input.by_species() else None,
-            hue_order=species,
-            legend=False,
-        )
-
-    @output
-    @render.ui
-    def value_boxes():
-        df = filtered_df()
-
-        def penguin_value_box(title: str, count: int, bgcol: str, showcase_img: str):
-            return ui.value_box(
-                title,
-                count,
-                {"class_": "pt-1 pb-0"},
-                showcase=ui.fill.as_fill_item(
-                    ui.tags.img(
-                        {"style": "object-fit:contain;"},
-                        src=showcase_img,
-                    )
-                ),
-                theme_color=None,
-                style=f"background-color: {bgcol};",
-            )
-
-        if not input.by_species():
-            return penguin_value_box(
-                "Penguins",
-                len(df.index),
-                bg_palette["default"],
-                # Artwork by @allison_horst
-                showcase_img="penguins.png",
-            )
-
-        value_boxes = [
-            penguin_value_box(
-                name,
-                len(df[df["Species"] == name]),
-                bg_palette[name],
-                # Artwork by @allison_horst
-                showcase_img=f"{name}.png",
-            )
-            for name in species
-            # Only include boxes for _selected_ species
-            if name in input.species()
-        ]
-
-        return ui.layout_column_wrap(*value_boxes, width = 1 / len(value_boxes))
-
-
-# "darkorange", "purple", "cyan4"
-colors = [[255, 140, 0], [160, 32, 240], [0, 139, 139]]
-colors = [(r / 255.0, g / 255.0, b / 255.0) for r, g, b in colors]
-
-palette: Dict[str, Tuple[float, float, float]] = {
-    "Adelie": colors[0],
-    "Chinstrap": colors[1],
-    "Gentoo": colors[2],
-    "default": sns.color_palette()[0],  # type: ignore
-}
-
-bg_palette = {}
-# Use `sns.set_style("whitegrid")` to help find approx alpha value
-for name, col in palette.items():
-    # Adjusted n_colors until `axe` accessibility did not complain about color contrast
-    bg_palette[name] = mpl_colors.to_hex(sns.light_palette(col, n_colors=7)[1])  # type: ignore
 
 
 app = App(