{"published":"2025-05-08 12:00:00","blog_title":"Bus error\u3068Segmentation fault\u306b\u56f0\u3063\u305f\u3089\u898b\u308b\u30d6\u30ed\u30b0","description":"\u666e\u901a\u306e\u7d2f\u7a4d\u5206\u5e03\u306fy\u8ef8\u306f0\u304b\u30891\u306b\u5411\u304b\u3063\u3066\u5897\u3048\u3066\u3044\u304f \u4eca\u56de\u306f1\u304b\u30890\u306b\u5411\u304b\u3063\u3066\u6e1b\u3063\u3066\u3044\u304f\u7d2f\u7a4d\u5206\u5e03\u3092\u66f8\u304f \u3042\u3068\u3001\u7e26\u8ef8\u30920~1\u306e\u7bc4\u56f2\u306b\u53ce\u307e\u308b\u3088\u3046\u306b\u898f\u683c\u5316\u3059\u308b\u5fc5\u8981\u304c\u3042\u308b import matplotlib.pyplot as plt import numpy as np val1, base1 = np.histogram(input1, bins=nbins2) cumulative1 = np.cumsum(val1)/len(input1) # \u898f\u683c\u5316\u3057\u3066\u308b\u306e\u306f\u3053\u3053 weight1 = np.ones(len(input1))/float(len(input1)) fig = plt.figur\u2026","width":"100%","image_url":"https://cdn.image.st-hatena.com/image/square/23ff597bd045490499b097f036afb3ec0665a0d5/backend=imagemagick;height=80;version=1;width=80/https%3A%2F%2Fcdn.user.blog.st-hatena.com%2Fcircle_image%2F88409737%2F1514352962196085","provider_name":"Hatena Blog","author_url":"https://blog.hatena.ne.jp/coffee_kabu/","url":"https://coffee-guhaw.hateblo.jp/entry/2025/05/08/120000","blog_url":"https://coffee-guhaw.hateblo.jp/","html":"<iframe src=\"https://hatenablog-parts.com/embed?url=https%3A%2F%2Fcoffee-guhaw.hateblo.jp%2Fentry%2F2025%2F05%2F08%2F120000\" title=\"\u3010matplotlib\u30111\u304b\u30890\u306b\u5909\u5316\u3059\u308b\u7d2f\u7a4d\u5206\u5e03(cdf)\u3092\u66f8\u304f - 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>","author_name":"coffee_kabu","provider_url":"https://hatena.blog","type":"rich","title":"\u3010matplotlib\u30111\u304b\u30890\u306b\u5909\u5316\u3059\u308b\u7d2f\u7a4d\u5206\u5e03(cdf)\u3092\u66f8\u304f","height":"190","categories":["python","numpy","matplotlib"],"version":"1.0"}