import numpy as np
from sklearn.metrics import accuracy_score, confusion_matrix, f1_score


def show_digit(pixels):
    img = pixels.reshape(28, 28)
    for row in img:
        print(" ".join("#" if p > 0.5 else "." for p in row))


def explore(X_train, y_train, n=3):
    print("=" * 60)
    print("SAMPLE DIGITS")
    print("=" * 60)
    for i in range(n):
        print(f"\nLabel: {y_train[i]}")
        show_digit(X_train[i])

    unique, counts = np.unique(y_train, return_counts=True)
    print()
    print("=" * 60)
    print("LABEL DISTRIBUTION")
    print("=" * 60)
    for digit, count in zip(unique, counts):
        print(f"  {digit}: {count:5d}  ({100 * count / len(y_train):.1f}%)")
    print()


def dataset_summary(n_train, n_test):
    print("=" * 60)
    print("DATASET")
    print("=" * 60)
    total = n_train + n_test
    print(f"\n  train: {n_train}  ({100 * n_train / total:.0f}%)   test: {n_test}  ({100 * n_test / total:.0f}%)")
    print()


def evaluation(y_true, y_pred, clf_name):
    print("=" * 60)
    print(f"RESULTS: {clf_name}")
    print("=" * 60)
    print()
    accuracy = accuracy_score(y_true, y_pred)
    avg_f1 = f1_score(y_true, y_pred, average="macro")
    print(f"  accuracy                              {accuracy:>10.3f}")
    print(f"  average f1                            {avg_f1:>10.3f}")
    print()

    cm = confusion_matrix(y_true, y_pred, labels=list(range(10)))
    per_digit = cm.diagonal() / cm.sum(axis=1)
    print("Per-digit accuracy:")
    for digit, acc in enumerate(per_digit):
        bar = "+" * int(acc * 30)
        print(f"  {digit}: {acc:.3f}  {bar}")
    print()


def error_analysis(X, y_true, y_pred, n):
    errors = [
        (pixels, t, p)
        for pixels, t, p in zip(X, y_true, y_pred)
        if t != p
    ]
    shown = errors[:n]
    print("=" * 60)
    print(f"ERROR ANALYSIS ({len(shown)} of {len(errors)} misclassified)")
    print("=" * 60)
    for pixels, true_label, pred_label in shown:
        print(f"\n  true={true_label}  pred={pred_label}")
        show_digit(pixels)
    print()