Update app.py

app.py

@@ -1,162 +1,98 @@
-import faicons as fa
+from shiny import App, ui, render, reactive
+from shinywidgets import render_widget
+from ipyleaflet import Map, TileLayer, GeoJSON, LayersControl
+import pandas as pd
+import numpy as np
 import plotly.express as px
-
-# Load data and compute static values
-from shared import app_dir, tips
-from shinywidgets import render_plotly
-
-from shiny import reactive, render
-from shiny.express import input, ui
-
-bill_rng = (min(tips.total_bill), max(tips.total_bill))
-
-# Add page title and sidebar
-ui.page_opts(title="Restaurant tipping", fillable=True)
-
-with ui.sidebar(open="desktop"):
-    ui.input_slider(
-        "total_bill",
-        "Bill amount",
-        min=bill_rng[0],
-        max=bill_rng[1],
-        value=bill_rng,
-        pre="$",
-    )
-    ui.input_checkbox_group(
-        "time",
-        "Food service",
-        ["Lunch", "Dinner"],
-        selected=["Lunch", "Dinner"],
-        inline=True,
+import plotly.graph_objects as go
+from plotly.subplots import make_subplots
+import matplotlib.pyplot as plt
+from ipywidgets import Output
+import rasterio
+import json
+
+# ---- 1. Load Data ----
+# Example file paths (replace with actual paths or S3 calls)
+wealth_tif_path = "data/wealth_map.tif"
+improvement_csv_path = "data/poverty_improvement_by_state.csv"
+
+# Read CSV
+improvement_data = pd.read_csv(improvement_csv_path)
+
+# Load raster stack
+wealth_stack = rasterio.open(wealth_tif_path)
+
+# Time periods corresponding to bands
+time_periods = [
+    "1990–1992", "1993–1995", "1996–1998", "1999–2001", "2002–2004",
+    "2005–2007", "2008–2010", "2011–2013", "2014–2016", "2017–2019"
+]
+
+# ---- 2. UI ----
+app_ui = ui.page_fluid(
+    ui.h2("Africa Wealth Map Dashboard (Python Version)"),
+    ui.layout_sidebar(
+        ui.panel_sidebar(
+            ui.input_slider("time_index", "Select Time Period (Years):", 1, 10, 1),
+            ui.input_select("color_palette", "Select Color Palette:", {
+                "viridis": "Viridis", "plasma": "Plasma", "magma": "Magma",
+                "inferno": "Inferno", "Spectral": "Spectral (Brewer)"
+            }),
+            ui.input_slider("opacity", "Map Opacity:", 0.2, 1.0, 0.8, step=0.1)
+        ),
+        ui.panel_main(
+            ui.output_text("current_year_range"),
+            ui.output_plot("iwi_histogram"),
+            ui.output_plot("trend_plot"),
+            ui.output_plot("clicked_ts_plot")
+        )
     )
-    ui.input_action_button("reset", "Reset filter")
-
-# Add main content
-ICONS = {
-    "user": fa.icon_svg("user", "regular"),
-    "wallet": fa.icon_svg("wallet"),
-    "currency-dollar": fa.icon_svg("dollar-sign"),
-    "ellipsis": fa.icon_svg("ellipsis"),
-}
-
-with ui.layout_columns(fill=False):
-    with ui.value_box(showcase=ICONS["user"]):
-        "Total tippers"
-
-        @render.express
-        def total_tippers():
-            tips_data().shape[0]
-
-    with ui.value_box(showcase=ICONS["wallet"]):
-        "Average tip"
-
-        @render.express
-        def average_tip():
-            d = tips_data()
-            if d.shape[0] > 0:
-                perc = d.tip / d.total_bill
-                f"{perc.mean():.1%}"
-
-    with ui.value_box(showcase=ICONS["currency-dollar"]):
-        "Average bill"
-
-        @render.express
-        def average_bill():
-            d = tips_data()
-            if d.shape[0] > 0:
-                bill = d.total_bill.mean()
-                f"${bill:.2f}"
-
-
-with ui.layout_columns(col_widths=[6, 6, 12]):
-    with ui.card(full_screen=True):
-        ui.card_header("Tips data")
-
-        @render.data_frame
-        def table():
-            return render.DataGrid(tips_data())
-
-    with ui.card(full_screen=True):
-        with ui.card_header(class_="d-flex justify-content-between align-items-center"):
-            "Total bill vs tip"
-            with ui.popover(title="Add a color variable", placement="top"):
-                ICONS["ellipsis"]
-                ui.input_radio_buttons(
-                    "scatter_color",
-                    None,
-                    ["none", "sex", "smoker", "day", "time"],
-                    inline=True,
-                )
-
-        @render_plotly
-        def scatterplot():
-            color = input.scatter_color()
-            return px.scatter(
-                tips_data(),
-                x="total_bill",
-                y="tip",
-                color=None if color == "none" else color,
-                trendline="lowess",
-            )
-
-    with ui.card(full_screen=True):
-        with ui.card_header(class_="d-flex justify-content-between align-items-center"):
-            "Tip percentages"
-            with ui.popover(title="Add a color variable"):
-                ICONS["ellipsis"]
-                ui.input_radio_buttons(
-                    "tip_perc_y",
-                    "Split by:",
-                    ["sex", "smoker", "day", "time"],
-                    selected="day",
-                    inline=True,
-                )
-
-        @render_plotly
-        def tip_perc():
-            from ridgeplot import ridgeplot
-
-            dat = tips_data()
-            dat["percent"] = dat.tip / dat.total_bill
-            yvar = input.tip_perc_y()
-            uvals = dat[yvar].unique()
-
-            samples = [[dat.percent[dat[yvar] == val]] for val in uvals]
-
-            plt = ridgeplot(
-                samples=samples,
-                labels=uvals,
-                bandwidth=0.01,
-                colorscale="viridis",
-                colormode="row-index",
-            )
-
-            plt.update_layout(
-                legend=dict(
-                    orientation="h", yanchor="bottom", y=1.02, xanchor="center", x=0.5
-                )
-            )
-
-            return plt
-
-
-ui.include_css(app_dir / "styles.css")
-
-# --------------------------------------------------------
-# Reactive calculations and effects
-# --------------------------------------------------------
-
-
-@reactive.calc
-def tips_data():
-    bill = input.total_bill()
-    idx1 = tips.total_bill.between(bill[0], bill[1])
-    idx2 = tips.time.isin(input.time())
-    return tips[idx1 & idx2]
-
-
-@reactive.effect
-@reactive.event(input.reset)
-def _():
-    ui.update_slider("total_bill", value=bill_rng)
-    ui.update_checkbox_group("time", selected=["Lunch", "Dinner"])
+)
+
+# ---- 3. Server ----
+def server(input, output, session):
+
+    selected_band = reactive.Calc(lambda: input.time_index())
+
+    @output
+    @render.text
+    def current_year_range():
+        return time_periods[input.time_index() - 1]
+
+    @output
+    @render.plot
+    def iwi_histogram():
+        band_index = input.time_index() - 1
+        band_data = wealth_stack.read(band_index + 1).flatten()
+        band_data = band_data[(band_data > 0) & (band_data <= 1)]
+        plt.figure(figsize=(6, 4))
+        plt.hist(band_data, bins=20, color="skyblue", edgecolor="white")
+        plt.title("IWI Histogram")
+        plt.xlabel("IWI")
+        plt.ylabel("Frequency")
+        return plt.gcf()
+
+    @output
+    @render.plot
+    def trend_plot():
+        mean_iwi = []
+        for i in range(1, 11):
+            band_data = wealth_stack.read(i).flatten()
+            band_data = band_data[(band_data > 0) & (band_data <= 1)]
+            mean_iwi.append(np.mean(band_data))
+
+        fig = go.Figure()
+        fig.add_trace(go.Scatter(x=time_periods, y=mean_iwi, mode='lines+markers'))
+        fig.update_layout(title="Average IWI Over Time", xaxis_title="Period", yaxis_title="Mean IWI")
+        return fig
+
+    @output
+    @render.plot
+    def clicked_ts_plot():
+        # Placeholder until integrated with map click logic
+        fig = go.Figure()
+        fig.update_layout(title="Click on map to load time series")
+        return fig
+
+# ---- 4. App ----
+app = App(app_ui, server)