# =============================================================
# DISEÑO 2: FACTORIAL SIMPLE EN BLOQUES COMPLETOS AL AZAR (DBCA)
# Efecto del CaCl2 sobre la firmeza poscosecha del tomate de árbol
# (Solanum betaceum Cav.) — día 20
# Factor de bloqueo: temperatura de almacenamiento
# =============================================================

import numpy as np
import pandas as pd
from scipy import stats
from scipy.stats import studentized_range
from itertools import combinations
import matplotlib.pyplot as plt
import warnings
warnings.filterwarnings('ignore')

# ── 1. DATOS ──────────────────────────────────────────────────
datos = {
    'Ambiente (~22°C)': {
        'Control (0 mM)' : [28.3875,25.9746,28.9612,32.2875,25.6102],
        '570 mM CaCl2'   : [44.9103,51.8010,48.7163,44.0160,47.8617],
        '862 mM CaCl2'   : [46.4390,46.4302,49.1195,40.9295,41.6453],
    },
    '6°C': {
        'Control (0 mM)' : [37.8633,36.1512,41.1941,36.5495,34.6332],
        '570 mM CaCl2'   : [64.8695,58.4421,59.5566,53.8860,57.2313],
        '862 mM CaCl2'   : [62.1215,57.3262,63.1277,59.4176,60.5916],
    },
    '9°C': {
        'Control (0 mM)' : [32.2135,41.5387,34.4487,30.4807,37.6257],
        '570 mM CaCl2'   : [49.1608,54.5937,46.3533,48.7529,54.5481],
        '862 mM CaCl2'   : [59.0062,56.8512,55.7605,55.0558,50.5816],
    }
}

bloques = list(datos.keys())
trts    = ['Control (0 mM)','570 mM CaCl2','862 mM CaCl2']

registros = []
for bloque, trt_dict in datos.items():
    for trt, valores in trt_dict.items():
        for i, v in enumerate(valores, 1):
            registros.append({'bloque': bloque,'tratamiento': trt,'fruto': i,'firmeza': v})
df = pd.DataFrame(registros)

print('='*68)
print('DISEÑO EN BLOQUES COMPLETOS AL AZAR (DBCA) — DATOS')
print('='*68)
print(df.to_string(index=False))

print('\n' + '='*68)
print('MEDIAS POR CELDA')
print('='*68)
pivot = df.groupby(['bloque','tratamiento'])['firmeza'].mean().unstack('tratamiento')
print(pivot.round(4).to_string())

print('\n' + '='*68)
print('ESTADÍSTICAS DESCRIPTIVAS')
print('='*68)
desc = df.groupby('tratamiento')['firmeza'].agg(n='count',media='mean').round(4)
print(desc.to_string())

grand_mean = df['firmeza'].mean()
means_trt = {t: df[df.tratamiento==t]['firmeza'].mean() for t in trts}
means_blq = {b: df[df.bloque==b]['firmeza'].mean() for b in bloques}

print(f'\nGran media: {grand_mean:.4f}')

print('\nEfectos de tratamiento:')
for t in trts:
    print(f'{t}: {means_trt[t]-grand_mean:+.4f}')

print('\nEfectos de bloque:')
for b in bloques:
    print(f'{b}: {means_blq[b]-grand_mean:+.4f}')

plt.figure(figsize=(6,4))
plt.boxplot([df[df.tratamiento==t]['firmeza'] for t in trts])
plt.xticks([1,2,3], trts)
plt.ylabel('Firmeza')
plt.title('Boxplot por tratamiento')
plt.grid(True)
plt.show()

print('\nGráfica generada correctamente')