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import streamlit as st | |
import numpy as np | |
import matplotlib.pyplot as plt | |
import optuna | |
# T铆tulo de la aplicaci贸n | |
st.title("Optimization tool") | |
# Selecci贸n de la funci贸n | |
func_user = st.selectbox("Choose a function:", ("cuadratic", "sine", "gaussian")) | |
# ("sin(x/10)", "(x-2)^2", "exp-(x-4)^2") | |
# Definici贸n de las funciones a optimizar | |
def func_cuadratic(x): | |
return (x - 2) ** 2 | |
def func_sine(x): | |
return np.sin(x / 10) | |
def func_gauss(x): | |
return np.exp(-((x - 4) ** 2)) | |
# Mostrar la f贸rmula de la funci贸n seleccionada y asignar la funci贸n correspondiente | |
if func_user == "cuadratic": | |
st.latex(r"(x - 2)^2") | |
func_to_use = func_cuadratic | |
elif func_user == "sine": | |
st.latex(r"sin({ x \over 10 })") | |
func_to_use = func_sine | |
else: | |
st.latex(r"e^{-(x-4)^2}") | |
func_to_use = func_gauss | |
# Selecci贸n de la direcci贸n de optimizaci贸n | |
opt_user = st.selectbox("Choose the optimization direction:", ("minimize", "maximize")) | |
# Entrada de los l铆mites inferiores y superiores | |
x_low = st.number_input("Please, give me the lower bound:", value=-10) | |
x_upp = st.number_input("Please, give me the upper bound:", value=10) | |
# Definici贸n de la funci贸n objetivo para Optuna | |
def objective(trial): | |
x = trial.suggest_float("x", x_low, x_upp) | |
return func_to_use(x) | |
# Crear el estudio de Optuna | |
study = optuna.create_study(direction=opt_user) | |
# Ejecutar la optimizaci贸n | |
study.optimize(objective, n_trials=500) | |
# Obtener el valor 贸ptimo de x y la funci贸n en ese punto | |
x_opt = study.best_params["x"] | |
y_opt = func_to_use(x_opt) | |
# Mostrar los resultados de la optimizaci贸n | |
st.write(f"The critical point found is ({x_opt:,.4f}, {y_opt:,.4f}).") | |
# Visualizaci贸n de los resultados | |
x_to_use = np.linspace(x_low, x_upp) | |
plt.title("Plot of critical point within interval given by user") | |
plt.xlabel("x axis") | |
plt.ylabel("y axis") | |
plt.plot(x_to_use, func_to_use(x_to_use)) | |
plt.scatter(x_opt, func_to_use(x_opt), c="red") | |
plt.annotate( | |
f"({x_opt:,.2f}, {y_opt:,.2f})", | |
(x_opt, y_opt), | |
textcoords="offset points", | |
ha="center", | |
) | |
# Mostrar la gr谩fica en Streamlit | |
st.pyplot(plt) | |