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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 | |
# Green Village ++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++ | |
# Function to load and parse the JSON data | |
def load_data(filename): | |
with open(filename, 'r') as file: | |
data = json.load(file) | |
return data | |
# Color codes updated with hexadecimal values for compatibility | |
color_codes = { | |
"residential": "#ADD8E6", # Light Blue | |
"commercial": "#90EE90", # Light Green | |
"community_facilities": "#FFFF00", # Yellow | |
"school": "#FFFF00", # Yellow | |
"healthcare_facility": "#FFFF00", # Yellow | |
"green_space": "#90EE90", # Light Green | |
"utility_infrastructure": "#90EE90", # Light Green | |
"emergency_services": "#FF0000", # Red | |
"cultural_facilities": "#D8BFD8", # Light Purple | |
"recreational_facilities": "#D8BFD8", # Light Purple | |
"innovation_center": "#90EE90", # Light Green | |
"elderly_care_home": "#FFFF00", # Yellow | |
"childcare_centers": "#FFFF00", # Yellow | |
"places_of_worship": "#D8BFD8", # Light Purple | |
"event_spaces": "#D8BFD8", # Light Purple | |
"guest_housing": "#FFA500", # Orange | |
"pet_care_facilities": "#FFA500", # Orange | |
"public_sanitation_facilities": "#A0A0A0", # Grey | |
"environmental_monitoring_stations": "#90EE90", # Light Green | |
"disaster_preparedness_center": "#A0A0A0", # Grey | |
"outdoor_community_spaces": "#90EE90" # Light Green | |
} | |
# Function to draw the grid layout with color coding | |
def draw_grid(data): | |
# Create a figure and a grid of subplots | |
fig, ax = plt.subplots(figsize=(12, 12)) | |
# Setting the grid size | |
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) | |
# Plotting each building with its assigned color from the color_codes dictionary | |
for building in data['buildings']: | |
# Extracting the building details | |
coords = building['coords'] | |
b_type = building['type'] | |
size = building['size'] | |
color = color_codes.get(b_type, '#FFFFFF') # Default color is white if not specified | |
# Plotting the building on the grid with color | |
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') | |
# Draw roads | |
for road in data.get('roads', []): # Check for roads in the data, default to empty list if not found | |
start, end = road['start'], road['end'] | |
# Determine if the road is vertical or horizontal based on start and end coordinates | |
if start[0] == end[0]: # Vertical road | |
for y in range(min(start[1], end[1]), max(start[1], end[1]) + 1): | |
ax.add_patch(plt.Rectangle((start[0], nrows-y-1), 1, 1, color=road['color'])) | |
else: # Horizontal road | |
for x in range(min(start[0], end[0]), max(start[0], end[0]) + 1): | |
ax.add_patch(plt.Rectangle((x, nrows-start[1]-1), 1, 1, color=road['color'])) | |
# Reverse the y-axis numbers | |
# ax.invert_yaxis() | |
# Setting labels and title | |
ax.set_xlabel('Columns') | |
ax.set_ylabel('Rows') | |
ax.set_title('Village Layout with Color Coding') | |
return fig | |
# Streamlit application starts here | |
def main(): | |
st.title('Green Smart Village Application') | |
# Creating three columns | |
col1, col2, col3 = st.columns(3) | |
with col1: | |
st.header("Today's Agenda") | |
# Example content for 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") | |
# Load and display the data with color coding | |
data = load_data('grid.json') # Ensure this path is correct | |
fig = draw_grid(data) | |
st.pyplot(fig) | |
# Interactivity: Selecting a building to display sensor data | |
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 view sensors:", options=building_options) | |
selected_index = building_options.index(selected_building) | |
sensors = data['buildings'][selected_index]['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() | |