Tsnet_GPT / app.py
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Update app.py
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import streamlit as st
import tempfile
import matplotlib.pyplot as plt
import pickle
st.set_page_config(page_title="TSNet Transient Simulator", layout="wide")
st.title("๐ŸŒŠ TSNet Transient Simulation App")
# Step 1: Upload EPANET .inp File
st.header("1. Upload EPANET .inp File")
uploaded_file = st.file_uploader("Upload your .inp file", type=["inp"])
if uploaded_file is not None:
with tempfile.NamedTemporaryFile(delete=False, suffix=".inp") as temp_inp:
temp_inp.write(uploaded_file.read())
inp_path = temp_inp.name
st.success("File uploaded and saved.")
st.header("2. Set Simulation Parameters")
wave_speed = st.number_input("Wave Speed (m/s)", value=1000.0)
dt = st.number_input("Time Step (s)", value=0.01)
duration = st.number_input("Simulation Duration (s)", value=10.0)
if st.button("Run TSNet Simulation"):
import tsnet
from tsnet.network.model import TransientModel
from tsnet.simulation import MOCSimulator
net = TransientModel(inp_path)
net.set_wavespeed(wave_speed)
net.set_time(duration, dt)
for pipe in net.pipes():
if not hasattr(pipe, 'initial_head'):
pipe.initial_head = (pipe.start_node.head + pipe.end_node.head) / 2
sim = MOCSimulator(net, 'results')
with open("results.obj", "wb") as f:
pickle.dump(sim, f)
st.session_state["sim_results"] = "results.obj"
st.success("Simulation complete.")
if "sim_results" in st.session_state:
st.header("3. Plot Results")
sim = pickle.load(open(st.session_state["sim_results"], "rb"))
node_id = st.selectbox("Select Node to Plot Head", sim.node_name_list)
pipe_id = st.selectbox("Select Pipe to Plot Flow", sim.pipe_name_list)
head = sim.get_node_head(node_id)
flow = sim.get_link_flow(pipe_id)
fig1, ax1 = plt.subplots()
ax1.plot(sim.Time, head)
ax1.set_title(f"Head at Node {node_id}")
ax1.set_xlabel("Time (s)")
ax1.set_ylabel("Head (m)")
st.pyplot(fig1)
fig2, ax2 = plt.subplots()
ax2.plot(sim.Time, flow)
ax2.set_title(f"Flow in Pipe {pipe_id}")
ax2.set_xlabel("Time (s)")
ax2.set_ylabel("Flow (L/s)")
st.pyplot(fig2)