{"provider_url":"https://hatena.blog","blog_title":"Bus error\u3068Segmentation fault\u306b\u56f0\u3063\u305f\u3089\u898b\u308b\u30d6\u30ed\u30b0","url":"https://coffee-guhaw.hateblo.jp/entry/2025/06/28/000000","author_name":"coffee_kabu","description":"\u70b9\u7dda\u306e\u88dc\u52a9\u7dda \u25a0 \u53c2\u8003 : \u3010Python@matplotlib\u3011matplotlib \u306b\u3066\u6a2a\u3001\u7e26\u306e\u88dc\u52a9\u7dda\u3092\u63cf\u304f\u65b9\u6cd5\u306b\u3064\u3044\u3066\u4e0a\u306e\u4f8b\u3067\u306f fig, ax = plt.subplots(figsize=(5,5)) \u306e\u3088\u3046\u306bax\u3068\u304b\u66f8\u3044\u3066\u308b\u3051\u3069\u3001\u305d\u308c\u3057\u306a\u304f\u3066\u3082\u3044\u3051\u308b\u3063\u307d\u3044 xdata = np.arange(0, 6.28, 0.1) ydata = np.sin(xdata) plt.figure(figsize=(10,6)) plt.plot(xdata, ydata) plt.hlines(0.8, -0.8, 0.8, \"blue\", linestyles='dashed') # hli\u2026","height":"190","published":"2025-06-28 00:00:00","image_url":"https://cdn-ak.f.st-hatena.com/images/fotolife/c/coffee_kabu/20250401/20250401142152.png","version":"1.0","author_url":"https://blog.hatena.ne.jp/coffee_kabu/","type":"rich","blog_url":"https://coffee-guhaw.hateblo.jp/","categories":["python","matplotlib","\u8ad6\u6587"],"width":"100%","provider_name":"Hatena Blog","title":"\u3010python\u3011\u70b9\u7dda\u306e\u88dc\u52a9\u7dda\u3068\u9818\u57df\u5857\u308a\u3064\u3076\u3057\u3092\u30b0\u30e9\u30d5\u306b\u5f15\u304d\u305f\u3044\u5834\u5408","html":"<iframe src=\"https://hatenablog-parts.com/embed?url=https%3A%2F%2Fcoffee-guhaw.hateblo.jp%2Fentry%2F2025%2F06%2F28%2F000000\" title=\"\u3010python\u3011\u70b9\u7dda\u306e\u88dc\u52a9\u7dda\u3068\u9818\u57df\u5857\u308a\u3064\u3076\u3057\u3092\u30b0\u30e9\u30d5\u306b\u5f15\u304d\u305f\u3044\u5834\u5408 - Bus error\u3068Segmentation fault\u306b\u56f0\u3063\u305f\u3089\u898b\u308b\u30d6\u30ed\u30b0\" class=\"embed-card embed-blogcard\" scrolling=\"no\" frameborder=\"0\" style=\"display: block; width: 100%; height: 190px; max-width: 500px; margin: 10px 0px;\"></iframe>"}