"""Create shareable plots from evaluate_mql8_correctness.py evidence (Matplotlib)."""
import argparse
import json
from pathlib import Path

import matplotlib
matplotlib.use('Agg')
import matplotlib.pyplot as plt
from matplotlib import font_manager
import numpy as np


def main():
    parser = argparse.ArgumentParser(description=__doc__)
    parser.add_argument('directory', type=Path)
    args = parser.parse_args()
    out = args.directory
    font = Path('C:/Windows/Fonts/msyh.ttc')
    if font.exists():
        font_manager.fontManager.addfont(str(font))
        plt.rcParams['font.family'] = font_manager.FontProperties(fname=str(font)).get_name()
    plt.rcParams.update({'font.size': 9, 'axes.spines.top': False, 'axes.spines.right': False,
                         'axes.unicode_minus': False, 'svg.fonttype': 'none', 'figure.facecolor': 'white'})
    summary = json.loads((out / 'summary.json').read_bytes())
    full = np.load(out / 'full/curves.npz')
    startup = np.load(out / 'startup/curves.npz')
    fig, axes = plt.subplots(4, 2, figsize=(13, 13), constrained_layout=True)
    selected = [
        (startup, summary['startup']['groups']['pressure']['worstAbsolute']['key'], '绝对压力', 'kPa', 1e-3, .002, 1000),
        (startup, summary['startup']['groups']['temperature']['worstAbsolute']['key'], '温度', 'K', 1, .002, 1000),
        (full, 'amesim_mecmas21_1.x', '1 号质量块位移', 'mm', 1000, 50, 1),
        (full, summary['full']['groups']['force']['worstAbsolute']['key'], '接触力（最差曲线）', 'kN', .001, 50, 1),
    ]
    for (data, key, title, unit, scale, end, ts), (left, right) in zip(selected, axes):
        mask = data['time'] <= end
        t = data['time'][mask] * ts
        native, ame = data['platform|' + key][mask] * scale, data['amesim|' + key][mask] * scale
        left.plot(t, native, color='#1368a8', linewidth=1.6, label='当前平台')
        left.plot(t, ame, color='#e07832', linestyle='--', linewidth=1.2, label='本次 Amesim')
        left.set_title(title + '  ·  ' + key, fontsize=9)
        left.legend(fontsize=8)
        right.plot(t, native - ame, color='#925034', linewidth=1.1)
        right.axhline(0, color='#888888', linewidth=.6)
        right.set_title('平台 − Amesim；切换点保留', fontsize=9)
        for ax in (left, right):
            ax.set_xlabel('时间 / ' + ('ms' if ts == 1000 else 's'))
            ax.set_ylabel(unit)
            ax.grid(alpha=.18)
    fig.suptitle('八路模型正确性初评 · 当前代码与本次 Amesim 执行\n启动段采样 0.1 ms；循环全程采样 10 ms；曲线重合不等于事件输出一致', fontsize=13)
    fig.savefig(out / 'comparison.png', dpi=160)
    fig.savefig(out / 'comparison.svg')
    plt.close(fig)

    fig, axes = plt.subplots(3, 2, figsize=(13, 10), constrained_layout=True)
    # Show each of the eight physical contacts; full curve metrics still include
    # the large event difference. The second column localizes away from events.
    for i in range(1, 9):
        key = f'amesim_lstp00a_{i}.force'
        t = full['time']
        error = full['platform|' + key] - full['amesim|' + key]
        axes[0, 0].plot(t, error / 1000, linewidth=.8, label=str(i))
        quiet = (t >= .1)
        for event in summary['full']['signalEvents']:
            quiet &= np.abs(t - event) > .0200001
        visible = np.where(quiet, error, np.nan)
        axes[0, 1].plot(t, visible, linewidth=.8, label=str(i))
    axes[0, 0].set(title='8 路接触力差：全部共同采样点', ylabel='差值 / kN')
    axes[0, 1].set(title='诊断视图：t≥0.1 s，避开切换前后 0.02 s', ylabel='差值 / N')
    axes[0, 0].legend(title='支路', ncol=4, fontsize=7)
    for row, (quantity, label) in enumerate([('enthalpy_flow', '节点焓流 / W'), ('mass_flow', '节点质量流 / kg/s')], 1):
        key = summary['default']['groups'][quantity]['worstRelative']['key']
        for column in range(2):
            ax = axes[row, column]
            t = full['time']
            mask = (t >= .1) & (t <= .5)
            n, a = full['platform|' + key], full['amesim|' + key]
            if column == 0:
                ax.plot(t[mask], n[mask], color='#1368a8', label='当前平台')
                ax.plot(t[mask], a[mask], '--', color='#e07832', label='本次 Amesim')
                ax.legend(fontsize=8)
                ax.set_ylabel(label)
                ax.set_title(key, fontsize=9)
            else:
                ax.plot(t[mask], (n-a)[mask], color='#925034')
                ax.set_ylabel('绝对差，沿用左侧单位')
                ax.set_title('小量差异单列，避免峰值归一化掩盖')
    for ax in axes.flat:
        ax.grid(alpha=.18)
        ax.set_xlabel('时间 / s')
    fig.suptitle('问题定位 · 切换点误差与小流量差异分开评价\n右上筛选只用于诊断；全部采样点仍进入主报告统计', fontsize=13)
    fig.savefig(out / 'diagnostics.png', dpi=160)
    fig.savefig(out / 'diagnostics.svg')
    plt.close(fig)

    data = np.load(out / 'volume-startup/curves.npz')
    fig, axes = plt.subplots(1, 2, figsize=(12, 4), constrained_layout=True)
    for ax, key, label, scale in [(axes[0], 'amesim_pnch012_15.vol', '有效气室容积 / L', 1000),
                                 (axes[1], 'amesim_pnch012_15.volume_work', '气室体积功率 / TW', 1e-12)]:
        mask = data['time'] <= 8e-8
        for prefix, name, color, style in [('platform', '当前平台', '#1368a8', '-'), ('amesim', '本次 Amesim', '#e07832', '--')]:
            ax.plot(data['time'][mask]*1e9, data[prefix+'|'+key][mask]*scale, style, color=color, label=name)
        ax.set(xlabel='时间 / ns', ylabel=label)
        ax.grid(alpha=.18)
        ax.legend()
    fig.suptitle('最初 80 ns：容积下限与体积功率 · 采样间隔 2 ns', fontsize=13)
    fig.savefig(out / 'volume-startup.png', dpi=160)
    fig.savefig(out / 'volume-startup.svg')
    plt.close(fig)


if __name__ == '__main__':
    main()