Update app.py

app.py

@@ -3,6 +3,7 @@ import sys
 import time
 import io
 import json
+from pathlib import Path
 from utils import print_with_line_number
 
 # Add the parent directory to the Python path
@@ -17,8 +18,10 @@ import math
 from typing import Optional
 from shiny import App, render, ui, reactive, Inputs, Outputs, Session, req
 import ipyleaflet as L
+from ipywidgets import Layout
 from htmltools import css
 import numpy as np
+import pandas as pd
 # from PIL import Image
 from shinywidgets import output_widget, reactive_read, register_widget
 from geopy.geocoders import Nominatim
@@ -106,19 +109,31 @@ data_to_map = {
 }
 
 # gradient_settings = {
-#     "structure parameter": {0: 'blue', 0.6: 'cyan', 1.0: 'lime'},
-#     "Chlorophylla+b content (µg/cm2)": {0: 'green', 0.6: 'lime', 1.0: 'yellow'},
-#     "Carotenoids content (µg/cm2)": {0: 'orange', 0.6: 'red', 1.0: 'maroon'},
-#     "Equivalent Water content (cm)": {0: 'navy', 0.6: 'blue', 1.0: 'aqua'},
-#     "Leaf Mass per Area (g/cm2)": {0: 'purple', 0.6: 'fuchsia', 1.0: 'pink'}
+#     "structure parameter": {0.2: 'rgba(0, 0, 255, 1.0)', 0.6: 'rgba(0, 255, 255, 1.0)', 1.0: 'rgba(0, 255, 0, 1.0)'},
+#     "Chlorophylla+b content (µg/cm2)": {0.2: 'rgba(0, 128, 0, 1.0)', 0.6: 'rgba(127, 255, 0, 1.0)', 1.0: 'rgba(255, 255, 0, 1.0)'},
+#     "Carotenoids content (µg/cm2)": {0.2: 'rgba(255, 69, 0, 1.0)', 0.6: 'rgba(255, 0, 0, 1.0)', 1.0: 'rgba(139, 0, 0, 1.0)'},
+#     "Equivalent Water content (cm)": {0.2: 'rgba(0, 0, 139, 1.0)', 0.6: 'rgba(65, 105, 225, 1.0)', 1.0: 'rgba(0, 191, 255, 1.0)'},
+#     "Leaf Mass per Area (g/cm2)": {0.2: 'rgba(75, 0, 130, 1.0)', 0.6: 'rgba(148, 0, 211, 1.0)', 1.0: 'rgba(255, 20, 147, 1.0)'}
 # }
 
+gradient_parula = {
+    0.0: 'rgba(128, 0, 128, 1.0)',     # purple
+    0.2: 'rgba(0, 0, 255, 1.0)',       # blue
+    0.4: 'rgba(0, 255, 255, 1.0)',     # cyan
+    0.5: 'rgba(0, 250, 154, 1.0)',     # mediumspringgreen
+    0.6: 'rgba(50, 205, 50, 1.0)',     # lime
+    0.7: 'rgba(173, 255, 47, 1.0)',    # greenyellow
+    0.8: 'rgba(255, 255, 0, 1.0)',     # yellow
+    0.9: 'rgba(255, 165, 0, 1.0)',     # orange
+    1.0: 'rgba(255, 0, 0, 1.0)'        # red
+}
+
 gradient_settings = {
-    "structure parameter": {0.2: 'rgba(0, 0, 255, 1.0)', 0.6: 'rgba(0, 255, 255, 1.0)', 1.0: 'rgba(0, 255, 0, 1.0)'},
-    "Chlorophylla+b content (µg/cm2)": {0.2: 'rgba(0, 128, 0, 1.0)', 0.6: 'rgba(127, 255, 0, 1.0)', 1.0: 'rgba(255, 255, 0, 1.0)'},
-    "Carotenoids content (µg/cm2)": {0.2: 'rgba(255, 69, 0, 1.0)', 0.6: 'rgba(255, 0, 0, 1.0)', 1.0: 'rgba(139, 0, 0, 1.0)'},
-    "Equivalent Water content (cm)": {0.2: 'rgba(0, 0, 139, 1.0)', 0.6: 'rgba(65, 105, 225, 1.0)', 1.0: 'rgba(0, 191, 255, 1.0)'},
-    "Leaf Mass per Area (g/cm2)": {0.2: 'rgba(75, 0, 130, 1.0)', 0.6: 'rgba(148, 0, 211, 1.0)', 1.0: 'rgba(255, 20, 147, 1.0)'}
+    "structure parameter": gradient_parula,
+    "Chlorophylla+b content (µg/cm2)": gradient_parula,
+    "Carotenoids content (µg/cm2)": gradient_parula,
+    "Equivalent Water content (cm)": gradient_parula,
+    "Leaf Mass per Area (g/cm2)": gradient_parula
 }
 
 print_with_line_number("Finish loading the ANN model!")
@@ -174,11 +189,18 @@ app_ui = ui.page_fluid(
         ui.span("3.Currently, the analysis does not support multiple polygons. The application will only recognize the last polygoned area."),
         ui.br(),
         ui.span("4.After analyzing the data of the drawn area, the webpage may experience slower loading speeds and delays. Please be patient and wait after performing an operation."),
+        ui.br(),
+        ui.strong("If you are unable to zoom in or out of the map using the mouse scroll wheel, please use the slide bar provided above to zoom directly.", style="color: green;"),
+        ui.br(),
+        ui.strong("We strongly recommend that you use a smaller scale to view the heat map (17 or 18 zoom level), as it will retain more details.", style="color: red;")
     ),
     ui.layout_sidebar(
         ui.panel_sidebar(
             ui.div(
-                ui.input_slider("zoom", "Map zoom level", value=12, min=1, max=18),
+                ui.div(
+                    ui.input_date("date", "Date:"), 
+                    ui.input_slider("zoom", "Map zoom level", value=12, min=1, max=18),
+                ),
                 ui.div(
                     ui.input_numeric("lat", "Latitude", value=38.53667742),
                     ui.input_numeric("long", "Longitude", value=-121.75387309),
@@ -195,14 +217,15 @@ app_ui = ui.page_fluid(
                 ui.output_text("Cm_range"),
                 style=css(display="flex", justify_content="center", align_items="center", gap="2rem"),
             ),
-            ui.strong("If you are unable to zoom in or out of the map using the mouse scroll wheel, please use the slide bar provided above to zoom directly."),
+            ui.img(src="legend.png"),
         ),
     ),
     output_widget("map"),
     ui.strong("Must analyze (to renew the image information) before downloading polygoned area tif file."),
     ui.div(
         ui.input_action_button("analyze", "Analyze", class_="btn-success"),
-        ui.download_button("download_polygon", "Download polygoned area data as tif", class_="btn-success"),
+        ui.download_button("download_polygon", "Download spectral data as tif", class_="btn-success"),
+        ui.download_button("download_output", "Download spectral and output data as csv", class_="btn-success"),
         style=css(display="flex", justify_content="center", align_items="center", gap="2rem"),
     ),
 )
@@ -212,10 +235,11 @@ def server(input, output, session):
     # Initialize Earth Engine
     ee.Initialize(credentials)
     
-    global address_line, polygoned_image
+    global address_line, polygoned_image, output_df
     address_line = None
     polygoned_image = None
     polygon_data = reactive.Value([])
+    output_df = pd.DataFrame()
     N = reactive.Value("structure parameter")
     Cab = reactive.Value("Chlorophylla+b content (µg/cm2)")
     Ccx = reactive.Value("Carotenoids content (µg/cm2)")
@@ -278,8 +302,7 @@ def server(input, output, session):
     # Check API status
     asset_roots = ee.data.getAssetRoots()
     if asset_roots:
-        print("Active Project ID:", asset_roots[0]['id'])
-        print("API is connected and working: ", asset_roots)
+        print("API is connected and working.")
     else:
         print("API is not connected or not working.")
 
@@ -295,6 +318,7 @@ def server(input, output, session):
         
         # Initialize and display when the session starts (1)
         map = L.Map(center=(current_gps['location']['lat'],  current_gps['location']['lng']), zoom=12, scroll_wheel_zoom=True)
+        map.layout = Layout(height='600px')
 
         @reactive.isolate()
         def update_text_inputs(lat: Optional[float], long: Optional[float]) -> None:
@@ -413,7 +437,12 @@ def server(input, output, session):
 
             heatmap_data = []
             data_values = output_datasets[data_to_map[layer_name]]
+
+            q03 = np.percentile(data_values, 3)
+            q97 = np.percentile(data_values, 97) 
             min_value = min(data_values)
+            if min_value < 0:
+                min_value = 0
             max_value = max(data_values)
 
             if (data_to_map[layer_name] == "N"):
@@ -428,7 +457,13 @@ def server(input, output, session):
                 Cm.set(layer_name + ": " + str(min_value) + " ~ " + str(max_value))
                 
             for coord, n in zip(output_datasets["Coordinates"], data_values):
-                normalized_value = (n - min_value) / (max_value - min_value)
+                # normalized_value = (n - min_value) / (max_value - min_value)
+                if n <= q03:
+                    normalized_value = 0
+                elif n >= q97:
+                    normalized_value = 1
+                else:
+                    normalized_value = (n - q03) / (q97 - q03)
                 heatmap_data.append([coord[1], coord[0], normalized_value])
                      
             # Generate new heatmap for this dataset
@@ -447,6 +482,7 @@ def server(input, output, session):
     @reactive.Effect
     @reactive.event(input.analyze, ignore_none=True, ignore_init=True)
     def _():
+        global output_df
         if not polygon_data.get():
             return
         ui.modal_show(m)
@@ -456,7 +492,8 @@ def server(input, output, session):
         print("Polygon: " , polygon)
         
         # Define Sentinel-2 image collection ("2021-01-01", "2021-12-31")
-        today = ee.Date(datetime.today().strftime('%Y-%m-%d'))  # 获取当天日期并转换为ee.Date格式
+        current_date = input.date()
+        today = ee.Date(input.date().strftime('%Y-%m-%d')) 
         start_date = today.advance(-15, 'day')
 
         print("Start Date: ", start_date.format('YYYY-MM-dd').getInfo(), "| End Date: ", today.format('YYYY-MM-dd').getInfo())
@@ -477,6 +514,17 @@ def server(input, output, session):
         retry = 5
         while(sentinel2.size().getInfo() == 0):
             if(retry == 0):
+                ui.update_date("date", label="Date:", value=current_date)
+                ui.modal_remove()
+                error_modal = ui.modal(
+                    "Please do not choose a date that is too far in the future. This application will search for remote sensing data within the two weeks prior to the selected date.",
+                    title="Something wrong happened, try \"Analyze\" again ",
+                    easy_close=True,
+                    size="xl",
+                    footer=None,
+                    fade=True
+                )
+                ui.modal_show(error_modal)
                 print("fail to fecth image.")
                 return
             print("wait for fetching.")
@@ -499,7 +547,7 @@ def server(input, output, session):
         polygon_area = polygon.area().getInfo()
         num = math.ceil(polygon_area / scale / scale)
         if (num > 4999):
-            per_area = math.ceil(polygon_area / 4999)
+            per_area = math.ceil(polygon_area / 4998)
             scale = math.ceil(math.pow(per_area, 1.0/2))
 
         print("polygon_area(m2): ", polygon_area, "scale: ", scale)
@@ -531,12 +579,17 @@ def server(input, output, session):
 
         # Convert to NumPy arrays
         coords = np.array(coords)
-        print("coords: ", coords)
+        # print("coords: ", coords)
         input_data = np.array(input_data)
-        print("input_bands: ", input_data)
+        # print("input_bands: ", input_data)
 
         output_datasets = runModel(input_data, loaded_scaler_X, loaded_scaler_Y, model)
 
+        # Combine all data
+        data_combined = np.column_stack((coords, input_data, output_datasets['N'], output_datasets['Cab'], output_datasets['Ccx'], output_datasets['Cw'], output_datasets['Cm']))
+        # Convert to DataFrame
+        output_df = pd.DataFrame(data_combined, columns=labels)
+        
         print_with_line_number("Add a dataset for the coordinates")
         output_datasets['Coordinates'] = coords
 
@@ -549,7 +602,7 @@ def server(input, output, session):
         print("Current navbar page: ", input.navbar_id())
     
     @session.download(
-        filename=lambda: f"image-{date.today().isoformat()}-{np.random.randint(100, 999)}.tif"
+        filename=lambda: f"image-{input.date().isoformat()}-{np.random.randint(100, 999)}.tif"
     )
     async def download_polygon():
         # # Replace this with your ee.Image object
@@ -587,5 +640,29 @@ def server(input, output, session):
             yield buf.getvalue()
 
         print("Image downloaded successfully!")
-    
-app = App(app_ui, server)
+
+    @session.download(
+        filename=lambda: f"data-{input.date().isoformat()}-{np.random.randint(100, 999)}.csv"
+    )
+    def download_output():
+        global output_df
+        # Check if data is available
+        if output_df.empty:
+            print("No data available for download.")
+            return
+        
+        # Convert dataframe to CSV and encode to bytes
+        csv_data = output_df.to_csv(index=False).encode()
+        
+        # Create a StringIO buffer for textual data
+        with io.BytesIO() as buf:
+            buf.write(csv_data)
+            # Reset the buffer's position to the beginning
+            buf.seek(0)
+            # Create and return a streaming response
+            yield buf.getvalue()
+
+        print("Data downloaded successfully!")
+
+static_dir = Path(__file__).parent / "assets"
+app = App(app_ui, server, static_assets=static_dir)