import sys, os
sys.path.insert(0, os.path.abspath('.'))
import warnings; warnings.filterwarnings('ignore')
import numpy as np, pandas as pd
import matplotlib.pyplot as plt
import invest_data as D
FONT = D.setup_matplotlib()
np.random.seed(D.SEED)
print('中文字体:', FONT, '| 数据目录:', D.DATA_DIR)

中文字体: Noto Sans CJK SC | 数据目录: /data/docs/investing/long-term-investing/data

import mplfinance as mpf
def to_mpf(df):
    """把内部 OHLCV(小写) 转成 mplfinance 需要的格式(首字母大写)。"""
    out = df.rename(columns={"open":"Open","high":"High","low":"Low","close":"Close","volume":"Volume"})
    return out[["Open","High","Low","Close","Volume"]]
print("mplfinance ready")

mplfinance ready

fig, ax = plt.subplots(figsize=(7, 5))
# 阳线：开10 收14 高15 低9
# 阴线：开14 收10 高15 低9
def draw_candle(ax, x, o, c, h, l, up_color="#c0392b", down_color="#16a085"):
    color = up_color if c >= o else down_color
    ax.plot([x, x], [l, h], color="black", lw=1)                 # 影线
    ax.add_patch(plt.Rectangle((x-0.2, min(o,c)), 0.4, abs(c-o)+0.001,
                               color=color, zorder=3))            # 实体
draw_candle(ax, 1, 10, 14, 15, 9)   # 阳线
draw_candle(ax, 2, 14, 10, 15, 9)   # 阴线
ax.text(1, 16, "阳线\n收>开\n(A股红)", ha="center")
ax.text(2, 16, "阴线\n收<开\n(A股绿)", ha="center")
ax.annotate("上影线", (1, 14.7), (1.3, 15.5), arrowprops=dict(arrowstyle="->"))
ax.annotate("下影线", (1, 9.3), (1.3, 8.2), arrowprops=dict(arrowstyle="->"))
ax.annotate("实体", (1.2, 12), (1.5, 12.5), arrowprops=dict(arrowstyle="->"))
ax.set_xlim(0, 3.2); ax.set_ylim(7, 18); ax.set_xticks([])
ax.set_title("K 线结构示意（A股配色：红涨绿跌）")
plt.tight_layout(); plt.show()

mt = D.load_a_price("600519")
mt_recent = to_mpf(mt).iloc[-250:]   # 最近约一年
mc = mpf.make_marketcolors(up="#c0392b", down="#16a085", inherit=True)  # A股红涨绿跌
style = mpf.make_mpf_style(marketcolors=mc, gridstyle=":", base_mpf_style="yahoo",
                           rc={"font.sans-serif": [FONT], "font.family": "sans-serif", "axes.unicode_minus": False})
mpf.plot(mt_recent, type="candle", style=style, mav=(20, 60), volume=True,
         title=f"\n贵州茅台 600519 日线 + MA20/60 + 成交量 {D.source_tag(mt)}",
         ylabel="价格(元)", ylabel_lower="成交量", figsize=(12, 7))

findfont: Failed to find font weight semibold, now using 500.

mt_long = to_mpf(mt).iloc[-600:]
mpf.plot(mt_long, type="candle", style=style, mav=(20, 60, 250), volume=True,
         title=f"\n贵州茅台 日线 + MA20/60/250(年线) {D.source_tag(mt)}",
         ylabel="价格(元)", ylabel_lower="成交量", figsize=(12, 7))
print("三条均线：MA20(短期情绪) / MA60(中期趋势) / MA250(长期牛熊分界)")

三条均线：MA20(短期情绪) / MA60(中期趋势) / MA250(长期牛熊分界)

def to_monthly(df):
    o = df["open"].resample("ME").first()
    h = df["high"].resample("ME").max()
    l = df["low"].resample("ME").min()
    c = df["close"].resample("ME").last()
    v = df["volume"].resample("ME").sum()
    m = pd.DataFrame({"Open":o,"High":h,"Low":l,"Close":c,"Volume":v}).dropna()
    return m

mt_m = to_monthly(mt)
mpf.plot(mt_m, type="candle", style=style, mav=(12,), volume=True,
         title=f"\n贵州茅台 月线 + MA12(月) {D.source_tag(mt)}",
         ylabel="价格(元)", ylabel_lower="月成交量", figsize=(12, 7))
print(f"月线共 {len(mt_m)} 根，时间跨度 {mt_m.index[0].date()} → {mt_m.index[-1].date()}")

月线共 90 根，时间跨度 2019-01-31 → 2026-06-30

aapl = D.load_us_price("AAPL")
aapl_recent = to_mpf(aapl).iloc[-250:]
mc_us = mpf.make_marketcolors(up="#16a085", down="#c0392b", inherit=True)  # 美股绿涨红跌
style_us = mpf.make_mpf_style(marketcolors=mc_us, gridstyle=":", base_mpf_style="yahoo",
                              rc={"font.sans-serif": [FONT], "font.family": "sans-serif", "axes.unicode_minus": False})
mpf.plot(aapl_recent, type="candle", style=style_us, mav=(20, 60, 250), volume=True,
         title=f"\nApple AAPL 日线 + MA20/60/250 {D.source_tag(aapl)}",
         ylabel="Price($)", ylabel_lower="Volume", figsize=(12, 7))

04 · 看懂 K 线与技术面¶

本章学什么 / 读完会什么¶

4.1 一根 K 线怎么读¶

4.2 茅台真实日线 K 线 + 均线 + 成交量¶

4.3 加上 MA250（年线）：长期趋势的「牛熊分界」¶

4.4 月线视角：把噪音抹掉，只看大趋势¶

4.5 苹果真实 K 线（美股配色：绿涨红跌）¶

4.6 关键认知：技术面对长期投资者的「有限作用」¶

本章小结¶