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import streamlit as st
import json
import matplotlib.pyplot as plt
import time
st.set_page_config(layout="wide")
# HIN Number +++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++
from SPARQLWrapper import SPARQLWrapper, JSON
from streamlit_agraph import agraph, TripleStore, Node, Edge, Config
import json
# Function to load JSON data
def load_data(filename):
with open(filename, 'r') as file:
data = json.load(file)
return data
# Dictionary for color codes
color_codes = {
"residential": "#ADD8E6",
"commercial": "#90EE90",
"community_facilities": "#FFFF00",
"school": "#FFFF00",
"healthcare_facility": "#FFFF00",
"green_space": "#90EE90",
"utility_infrastructure": "#90EE90",
"emergency_services": "#FF0000",
"cultural_facilities": "#D8BFD8",
"recreational_facilities": "#D8BFD8",
"innovation_center": "#90EE90",
"elderly_care_home": "#FFFF00",
"childcare_centers": "#FFFF00",
"places_of_worship": "#D8BFD8",
"event_spaces": "#D8BFD8",
"guest_housing": "#FFA500",
"pet_care_facilities": "#FFA500",
"public_sanitation_facilities": "#A0A0A0",
"environmental_monitoring_stations": "#90EE90",
"disaster_preparedness_center": "#A0A0A0",
"outdoor_community_spaces": "#90EE90",
# Add other types with their corresponding colors
}
# Function to draw the grid with optional highlighting
def draw_grid(data, highlight_coords=None):
fig, ax = plt.subplots(figsize=(12, 12))
nrows, ncols = data['size']['rows'], data['size']['columns']
ax.set_xlim(0, ncols)
ax.set_ylim(0, nrows)
ax.set_xticks(range(ncols+1))
ax.set_yticks(range(nrows+1))
ax.grid(True)
# Draw roads
for road in data.get('roads', []): # Default to empty list if no roads key
start = road['start']
end = road['end']
color = color_codes.get("road", '#898989') # Default color is gray for roads
ax.plot([start[1], end[1]], [nrows-start[0], nrows-end[0]], color=color, linewidth=2) # Adjust coordinates for matplotlib
# Draw buildings
for building in data['buildings']:
coords = building['coords']
b_type = building['type']
size = building['size']
color = color_codes.get(b_type, '#FFFFFF') # Default color is white if not specified
if highlight_coords and (coords[0], coords[1]) == tuple(highlight_coords):
highlighted_color = "#FFD700" # Gold for highlighting
ax.add_patch(plt.Rectangle((coords[1], nrows-coords[0]-size), size, size, color=highlighted_color, edgecolor='black', linewidth=2))
else:
ax.add_patch(plt.Rectangle((coords[1], nrows-coords[0]-size), size, size, color=color, edgecolor='black', linewidth=1))
ax.text(coords[1]+0.5*size, nrows-coords[0]-0.5*size, b_type, ha='center', va='center', fontsize=8, color='black')
ax.set_xlabel('Columns')
ax.set_ylabel('Rows')
ax.set_title('Village Layout with Color Coding')
return fig
"""
def draw_grid(data, highlight_coords=None):
fig, ax = plt.subplots(figsize=(12, 12))
nrows, ncols = data['size']['rows'], data['size']['columns']
ax.set_xlim(0, ncols)
ax.set_ylim(0, nrows)
ax.set_xticks(range(ncols+1))
ax.set_yticks(range(nrows+1))
ax.grid(True)
for building in data['buildings']:
coords = building['coords']
b_type = building['type']
size = building['size']
color = color_codes.get(b_type, '#FFFFFF') # Default color is white if not specified
if highlight_coords and (coords[0], coords[1]) == tuple(highlight_coords):
highlighted_color = "#FFD700" # Gold for highlighting
ax.add_patch(plt.Rectangle((coords[1], nrows-coords[0]-size), size, size, color=highlighted_color, edgecolor='black', linewidth=2))
else:
ax.add_patch(plt.Rectangle((coords[1], nrows-coords[0]-size), size, size, color=color, edgecolor='black', linewidth=1))
ax.text(coords[1]+0.5*size, nrows-coords[0]-0.5*size, b_type, ha='center', va='center', fontsize=8, color='black')
ax.set_xlabel('Columns')
ax.set_ylabel('Rows')
ax.set_title('Village Layout with Color Coding')
return fig
"""
# Main Streamlit app function
def main():
st.title('Green Smart Village Application')
# Divide the page into three columns
col1, col2, col3 = st.columns(3)
with col1:
st.header("Today's Agenda")
st.write("1. Morning Meeting\n2. Review Project Plans\n3. Lunch Break\n4. Site Visit\n5. Evening Wrap-up")
st.header("Agent Advisors")
st.write("Would you like to optimize your HIN number?")
st.header("My Incentive")
st.write("Total incentive for HIN optimization")
with col2:
st.header("Green Smart Village Layout")
data = load_data('grid.json') # Ensure this path is correct
# Dropdown for selecting a building
building_options = [f"{bld['type']} at ({bld['coords'][0]}, {bld['coords'][1]})" for bld in data['buildings']]
selected_building = st.selectbox("Select a building to highlight:", options=building_options)
selected_index = building_options.index(selected_building)
selected_building_coords = data['buildings'][selected_index]['coords']
# Draw the grid with the selected building highlighted
fig = draw_grid(data, highlight_coords=selected_building_coords)
st.pyplot(fig)
# Assuming sensors are defined in your data, display them
sensors = data['buildings'][selected_index].get('sensors', [])
st.write(f"Sensors in selected building: {', '.join(sensors)}")
with col3:
st.header("Check Your HIN Number")
config = Config(height=400, width=400, nodeHighlightBehavior=True, highlightColor="#F7A7A6", directed=True,
collapsible=True)
#based on Insurance Fraud
with open("data/fraud.json", encoding="utf8") as f:
fraud_file = json.loads(f.read())
st.session_state['fraud_topic'] = fraud_file
fraud_store = TripleStore()
for sub_graph in fraud_file["children"]:
fraud_store.add_triple(fraud_file["name"], "has_subgroup", sub_graph["name"], picture=fraud_file["img"])
for node in sub_graph["children"]:
node1 = node["role"]
link = "blongs_to"
node2 = sub_graph["name"]
pic = node["img"]
fraud_store.add_triple(node1, link, node2, picture=pic)
agraph(list(fraud_store.getNodes()), (fraud_store.getEdges()), config)
hin_number = st.text_input("Enter your HIN number:")
if hin_number:
st.write("HIN number details...") # Placeholder for actual HIN number check
if __name__ == "__main__":
main() |