{"author_name":"xef","provider_url":"https://hatena.blog","image_url":"https://cdn-ak.f.st-hatena.com/images/fotolife/x/xef/20120316/20120316014121.png","version":"1.0","author_url":"https://blog.hatena.ne.jp/xef/","blog_url":"https://xef.hatenadiary.org/","categories":["Python"],"description":"wikipedia:\u6b63\u898f\u5206\u5e03\u306e\u56f3\u3092\u53c2\u8003\u306b\u3002\u6b63\u898f\u5206\u5e03\uff08\u306e\u7406\u8ad6\u5024\uff09\u306fGnuplot\u3084R\u306e\u30d7\u30ed\u30c3\u30bf\u306a\u3069\u65b0\u3057\u3044\u30c4\u30fc\u30eb\u3092\u4f7f\u3046\u3055\u3044\u521d\u3081\u306b\u63cf\u304f\u3053\u3068\u306b\u3057\u3066\u3044\u308b\u3002\u5909\u6570\u306e\u540d\u524d\u304c\u3042\u307e\u308a\u53ef\u611b\u304f\u306a\u3044\u3002 import numpy as np from matplotlib import pyplot as plt sigmas = [0.2, 1.0, 5.0, 0.5] myus = [0, 0, 0, -2] x = np.arange(-5., 5., 0.001) for v in zip(sigmas,myus): y = (1./np.sqrt(2*np.pi*v[0])) * np.exp(-(x - v[\u2026","provider_name":"Hatena Blog","width":"100%","blog_title":"Soleil cou coupe","type":"rich","html":"<iframe src=\"https://hatenablog-parts.com/embed?url=https%3A%2F%2Fxef.hatenadiary.org%2Fentry%2F20120315%2F1331829958\" title=\"numpy+matplotlib\u3067\u6b63\u898f\u5206\u5e03 - Soleil cou coupe\" class=\"embed-card embed-blogcard\" scrolling=\"no\" frameborder=\"0\" style=\"display: block; width: 100%; height: 190px; max-width: 500px; margin: 10px 0px;\"></iframe>","url":"https://xef.hatenadiary.org/entry/20120315/1331829958","height":"190","title":"numpy+matplotlib\u3067\u6b63\u898f\u5206\u5e03","published":"2012-03-15 01:45:58"}