import pandas as pd
import numpy as np
import matplotlib.pyplot as plt
from scipy.optimize import curve_fit

# --- Dati ---
df = pd.read_csv("data.csv")
df["time_s"] = df["time since start [ms]"] / 1000.0

T_INF   = 22.99  # temperatura ambiente media ponderata [°C]
T_START = 115.0  # inizio finestra di fit [s]
T0      = T_START  # t0 coincide con il primo punto
W_ZERO_START = 115.9
W_ZERO_END   = 117.2

mask = df["time_s"] >= T_START
t_fit = df.loc[mask, "time_s"].values
T_fit = df.loc[mask, "temp_obj IR [C]"].values

# Pesi espliciti: w=0 nell'intervallo escluso, w=1 altrove
# curve_fit usa sigma come deviazione standard -> sigma grande = peso nullo
sigma = np.where(
    (t_fit >= W_ZERO_START) & (t_fit <= W_ZERO_END),
    1e10,   # peso ~ 0
    1.0     # peso pieno
)

# --- Modello con A e tau liberi (ottimizza R²) ---
def modello(t, A, tau):
    return T_INF + A * np.exp(-(t - T0) / tau)

A0   = T_fit[0] - T_INF
tau0 = 20.0

popt, pcov = curve_fit(
    modello, t_fit, T_fit,
    p0=[A0, tau0],
    sigma=sigma,
    absolute_sigma=True,
    method="trf",
    bounds=([0, 0.1], [np.inf, np.inf])
)
A_fit, tau_fit = popt
perr = np.sqrt(np.diag(pcov))

# --- R² (solo sui punti con peso pieno) ---
mask_w = (t_fit < W_ZERO_START) | (t_fit > W_ZERO_END)
T_pred_w = modello(t_fit[mask_w], *popt)
ss_res = np.sum((T_fit[mask_w] - T_pred_w) ** 2)
ss_tot = np.sum((T_fit[mask_w] - T_fit[mask_w].mean()) ** 2)
r2 = 1 - ss_res / ss_tot

print(f"A   = {A_fit:.4f} ± {perr[0]:.4f} °C")
print(f"tau = {tau_fit:.4f} ± {perr[1]:.4f} s")
print(f"R²  = {r2:.6f}  (calcolato sui punti con peso pieno)")

# --- Curva continua ---
t_curve = np.linspace(T_START, df["time_s"].max(), 500)
T_curve = modello(t_curve, *popt)

# --- Plot ---
fig, ax = plt.subplots(figsize=(12, 5))

ax.plot(t_fit, T_fit,
        color="steelblue", linewidth=0.8, label="Dati raw (temp_obj)")
ax.axvspan(W_ZERO_START, W_ZERO_END,
           color="orange", alpha=0.25, label=f"Zona esclusa [{W_ZERO_START}–{W_ZERO_END} s]")
ax.plot(t_curve, T_curve,
        color="tomato", linewidth=2, linestyle="--",
        label=f"Fit: $T_{{\\infty}}$ + {A_fit:.2f}·exp(-(t-{T0})/{tau_fit:.2f})")

ax.set_xlabel("Tempo [s]")
ax.set_ylabel("Temperatura [°C]")
ax.set_title(f"Fit con pesi espliciti (w=0 in [{W_ZERO_START}–{W_ZERO_END} s])  |  R² = {r2:.4f}")
ax.legend()
ax.grid(True, alpha=0.3)

plt.tight_layout()
plt.savefig("fit_raffreddamento_intero.png", dpi=150, bbox_inches="tight")
plt.show()