"""Plotting helpers using Matplotlib."""

from __future__ import annotations

from pathlib import Path
from typing import Iterable

import matplotlib.pyplot as plt
import numpy as np
from sklearn.calibration import calibration_curve
from sklearn.metrics import precision_recall_curve, roc_curve


def plot_reliability_curve(
    y_true: Iterable[float],
    y_score: Iterable[float],
    *,
    path: str | Path,
    n_bins: int = 10,
) -> None:
    """Save a reliability curve plot."""

    prob_true, prob_pred = calibration_curve(y_true, y_score, n_bins=n_bins)
    fig, ax = plt.subplots(figsize=(4, 4))
    ax.plot(prob_pred, prob_true, marker="o", label="Model")
    ax.plot([0, 1], [0, 1], linestyle="--", color="gray", label="Perfect")
    ax.set_xlabel("Predicted probability")
    ax.set_ylabel("Observed frequency")
    ax.set_title("Reliability curve")
    ax.legend()
    fig.tight_layout()
    Path(path).parent.mkdir(parents=True, exist_ok=True)
    fig.savefig(path)
    plt.close(fig)


def plot_precision_recall(
    y_true: Iterable[float],
    y_score: Iterable[float],
    *,
    path: str | Path,
) -> None:
    """Save a precision-recall curve."""

    precision, recall, _ = precision_recall_curve(y_true, y_score)
    fig, ax = plt.subplots(figsize=(4, 4))
    ax.plot(recall, precision, label="Model")
    ax.set_xlabel("Recall")
    ax.set_ylabel("Precision")
    ax.set_title("Precision-Recall curve")
    ax.set_xlim([0, 1])
    ax.set_ylim([0, 1])
    fig.tight_layout()
    Path(path).parent.mkdir(parents=True, exist_ok=True)
    fig.savefig(path)
    plt.close(fig)


def plot_roc_curve(
    y_true: Iterable[float],
    y_score: Iterable[float],
    *,
    path: str | Path,
) -> None:
    """Save an ROC curve plot."""

    fpr, tpr, _ = roc_curve(y_true, y_score)
    fig, ax = plt.subplots(figsize=(4, 4))
    ax.plot(fpr, tpr, label="Model")
    ax.plot([0, 1], [0, 1], linestyle="--", color="gray")
    ax.set_xlabel("False positive rate")
    ax.set_ylabel("True positive rate")
    ax.set_title("ROC curve")
    ax.set_xlim([0, 1])
    ax.set_ylim([0, 1])
    fig.tight_layout()
    Path(path).parent.mkdir(parents=True, exist_ok=True)
    fig.savefig(path)
    plt.close(fig)