Upload app3.py

app3.py

@@ -0,0 +1,65 @@
+import streamlit as st
+import numpy as np
+from scipy.integrate import odeint
+import plotly.graph_objects as go
+import time
+import pandas as pd
+
+# Define the Lorenz system
+def lorenz_system(current_state, t, sigma, rho, beta):
+    x, y, z = current_state
+    dx_dt = sigma * (y - x)
+    dy_dt = x * (rho - z) - y
+    dz_dt = x * y - beta * z
+    return [dx_dt, dy_dt, dz_dt]
+
+# Set up the sidebar
+st.sidebar.title('Lorenz System Parameters')
+sigma = st.sidebar.slider('Sigma', 0.0, 50.0, 10.0)
+rho = st.sidebar.slider('Rho', 0.0, 50.0, 28.0)
+beta = st.sidebar.slider('Beta', 0.0, 50.0, 2.67)
+
+x0_1 = st.sidebar.number_input('Initial x for 1st system', value=1.0)
+y0_1 = st.sidebar.number_input('Initial y for 1st system', value=1.0)
+z0_1 = st.sidebar.number_input('Initial z for 1st system', value=1.0)
+
+x0_2 = st.sidebar.number_input('Initial x for 2nd system', value=1.0)
+y0_2 = st.sidebar.number_input('Initial y for 2nd system', value=1.0)
+z0_2 = st.sidebar.number_input('Initial z for 2nd system', value=1.0)
+
+# Define the time points for the simulation
+t = np.linspace(0, 4, 1000)
+
+# Solve the Lorenz system
+solution_1 = odeint(lorenz_system, (x0_1, y0_1, z0_1), t, args=(sigma, rho, beta))
+solution_2 = odeint(lorenz_system, (x0_2, y0_2, z0_2), t, args=(sigma, rho, beta))
+
+# Create a 3D plot of the solutions
+plot_slot = st.empty()
+
+stop = st.checkbox('Stop')
+
+i = 0
+while i < len(t) and not stop:
+    fig = go.Figure(data=[
+        go.Scatter3d(x=solution_1[:i, 0], y=solution_1[:i, 1], z=solution_1[:i, 2], mode='lines', line=dict(color='red'), name='System 1'),
+        go.Scatter3d(x=solution_2[:i, 0], y=solution_2[:i, 1], z=solution_2[:i, 2], mode='lines', line=dict(color='blue'), name='System 2')
+    ])
+
+    fig.update_layout(scene=dict(xaxis=dict(range=[min(min(solution_1[:, 0]), min(solution_2[:, 0])), max(max(solution_1[:, 0]), max(solution_2[:, 0]))]),
+                                 yaxis=dict(range=[min(min(solution_1[:, 1]), min(solution_2[:, 1])), max(max(solution_1[:, 1]), max(solution_2[:, 1]))]),
+                                 zaxis=dict(range=[min(min(solution_1[:, 2]), min(solution_2[:, 2])), max(max(solution_1[:, 2]), max(solution_2[:, 2]))]),
+                                 camera=dict(eye=dict(x=2*np.cos(i/10), y=2*np.sin(i/10), z=0.1))),
+                     width=800, height=600)
+
+    plot_slot.plotly_chart(fig)
+
+    i += 1
+    time.sleep(0.2)
+
+if st.button('Export Data'):
+    df_1 = pd.DataFrame(solution_1, columns=['x_1', 'y_1', 'z_1'])
+    df_2 = pd.DataFrame(solution_2, columns=['x_2', 'y_2', 'z_2'])
+    df_1.to_csv('lorenz_data_1.csv')
+    df_2.to_csv('lorenz_data_2.csv')
+    st.write('Data exported successfully!')