{"id":1187,"date":"2020-05-02T00:00:00","date_gmt":"2020-05-01T15:00:00","guid":{"rendered":"https:\/\/www.ishikawasekkei.com\/?p=1187"},"modified":"2020-05-02T14:49:31","modified_gmt":"2020-05-02T05:49:31","slug":"python-matplotlib-love-formula","status":"publish","type":"post","link":"https:\/\/www.ishikawasekkei.com\/index.php\/2020\/05\/02\/python-matplotlib-love-formula\/","title":{"rendered":"Python matplotlib \u611b\u306e\u65b9\u7a0b\u5f0f\uff1f"},"content":{"rendered":"\n

\u3000\u4eca\u65e5\u3082\u898b\u306b\u6765\u3066\u304f\u3060\u3055\u3063\u3066\u3001\u3042\u308a\u304c\u3068\u3046\u3054\u3056\u3044\u307e\u3059\u3002\u77f3\u5ddd\u3055\u3093\u3067\u3059\u3002<\/p>\n\n\n\n

\u3000\u660e\u65e5\u304b\u3089\u30b4\u30fc\u30eb\u30c7\u30f3\u30a6\u30a3\u30fc\u30af\u3067\u3059\u306d\u3002\u3060\u3051\u3069\u3069\u3053\u304b\u3078\u304a\u51fa\u304b\u3051\u3059\u308b\u3053\u3068\u3082\u306a\u304b\u306a\u304b\u96e3\u3057\u3044\u72b6\u6cc1\u3067\u3059\u3088\u306d\u3002\u3053\u3046\u3044\u3046\u72b6\u6cc1\u306a\u306e\u3067\u3001\u3053\u306e\u3054\u308d\u3001SNS\u3092\u898b\u308b\u6642\u9593\u304c\u3061\u3087\u3063\u3074\u308a\u5897\u3048\u3066\u304d\u307e\u3057\u305f\u3002\u5148\u65e5\u3001\u305f\u3076\u3093\u30c4\u30a4\u30c3\u30bf\u30fc\u3060\u3068\u601d\u3046\u306e\u3067\u3059\u3051\u3069\u3001\u30a8\u30d7\u30ed\u30f3\u306b\u66f8\u304b\u308c\u305f\u65b9\u7a0b\u5f0f\u306e\u8a71\u984c\u304c\u304a\u3059\u3059\u3081\u3067\u51fa\u3066\u304d\u307e\u3057\u305f\u3002\u78ba\u304b\u3001\u5965\u3055\u307e\u304b\u3089\u3082\u3089\u3063\u305f\u30a8\u30d7\u30ed\u30f3\u306b\u8b0e\u306e\u6570\u5f0f\u304c\u63cf\u304b\u308c\u3066\u3042\u3063\u3066\u3001\u3069\u3046\u3057\u3066\u3082\u6c17\u306b\u306a\u3063\u305f\u306e\u3067\u3001\u63cf\u753b\u3057\u3066\u307f\u305f\u3089\u3001\u5965\u3055\u307e\u306e\u65b9\u306e\u30a8\u30d7\u30ed\u30f3\u306b\u3059\u3067\u306b\u305d\u306e\u63cf\u753b\u7d50\u679c\u304c\u63cf\u304b\u308c\u3066\u3042\u3063\u305f\u3068\u3044\u3046\u304a\u8a71\u3067\u3057\u305f\u3002\u307c\u304f\u306f\u3001\u3068\u3063\u3055\u306b\u3001\u300c\u3053\u308c\u3092\u3061\u3087\u3063\u3068\u63cf\u753b\u3057\u3066\u307f\u305f\u3044\u300d\u3068\u3044\u3046\u6b32\u6c42\u306b\u304b\u3089\u308c\u307e\u3057\u3066\u3001\u304a\u8a66\u3057\u306bmatplotlib\u3092\u4f7f\u3063\u3066\u30d7\u30ed\u30c3\u30c8\u3057\u3066\u307f\u308b\u3053\u3068\u306b\u3057\u3066\u307f\u307e\u3057\u305f\u3002<\/p>\n\n\n\n

\u3000\u66f8\u304b\u308c\u3066\u3044\u305f\u65b9\u7a0b\u5f0f\u3001\u7d76\u5bfe\u306b\u899a\u3048\u3066\u304a\u3051\u306a\u3044\u3068\u601d\u3063\u3066\u3001\u3068\u3063\u3055\u306b\u30e1\u30e2\u3092\u3057\u307e\u3057\u305f\u3002\u30e1\u30e2\u306b\u306f\u624b\u66f8\u304d\u3067\u306f\u306a\u304f\u3066\u3001Google\u30ad\u30fc\u30d7\u3092\u4f7f\u3044\u307e\u3057\u305f\u3002\u30eb\u30fc\u30c8\u306e\u8a18\u53f7\u306a\u3069\u306e\u6570\u5f0f\u304c\u63cf\u3051\u306a\u304b\u3063\u305f\u306e\u3067\u3001\u30d7\u30ed\u30b0\u30e9\u30df\u30f3\u30b0\u7684\u306a\u6570\u5f0f\u306b\u7f6e\u304d\u63db\u3048\u3066\u3001\u30c6\u30ad\u30b9\u30c8\u3067\u4fdd\u5b58\u3057\u307e\u3057\u305f\u3002\u306a\u306e\u3067\u3001\u5f0f\u304c\u3042\u3063\u3066\u3044\u308b\u304b\u3069\u3046\u304b\u3061\u3087\u3063\u3074\u308a\u4e0d\u5b89\u306a\u306e\u3067\u3059\u3088\u306d\u3047\u3002<\/p>\n\n\n\n

x**2+(y-(x**2)**(1\/3))**2=1<\/pre>\n\n\n\n
\u3000\u74b0\u5883\u4f9d\u5b58\u306e\u8a18\u53f7\u3067\u66f8\u304f\u3068\u4ee5\u4e0b\u306e\u3088\u3046\u306b\u306a\u308a\u307e\u3059\u3002\u4ed6\u306e\u4eba\u305f\u3061\u3082\u3001\u3061\u3083\u3093\u3068\u8aad\u3081\u308b\u304b\u306a\u3041\u3002\u3002\u3002<\/p>\n\n\n\n
x\u00b2 + (y - \u221bx\u00b2)\u00b2 = 1<\/pre>\n\n\n\n
\u3000\u6700\u8fd1\u3001\u30c7\u30fc\u30bf\u30b5\u30a4\u30a8\u30f3\u30c6\u30a3\u30b9\u30c8\u306e\u5b66\u7fd2\u3067\u3001y=<\/code>\u306e\u5f62\u5f0f\u306b\u3059\u308c\u3070\u30b0\u30e9\u30d5\u304c\u63cf\u3051\u308b\u3001\u3068\u3044\u3046\u3053\u3068\u3092\u77e5\u3063\u3066\u3044\u305f\u306e\u3067\u3001\u307e\u305a\u306f\u3001\u5c55\u958b\u3059\u308b\u306e\u304b\u306a\u3041\u3001\u3068\u3001\u8abf\u67fb\u958b\u59cb\u3002\u3053\u306e\u5f0f\u3001\u307e\u3042\u307e\u3042\u8a71\u984c\u306b\u306a\u3063\u3066\u3044\u308b\u3088\u3046\u3067\u3059\u3002\u3044\u308d\u3044\u308d\u3068\u63a2\u3057\u3066\u3044\u308b\u3068\u3001\u5f0f\u3092\u5c55\u958b\u305b\u305a\u3068\u3082\u63cf\u753b\u3067\u304d\u305d\u3046\u306a\u8a18\u4e8b<\/a>\u306b\u51fa\u4f1a\u3044\u307e\u3057\u305f\u3002<\/p>\n\n\n\n
\u30b9\u30af\u30ea\u30d7\u30c8<\/h2>\n\n\n\n
\u3000\u4e0a\u8a18\u306eURL\u3092\u53c2\u8003\u306b\u4f5c\u3063\u305f\u30b9\u30af\u30ea\u30d7\u30c8\u306f\u4ee5\u4e0b\u306e\u901a\u308a\u3067\u3059\u3002\u30b7\u30f3\u30d7\u30eb\u3067\u3057\u3087\uff1f<\/p>\n\n\n\n
import numpy as np\nimport matplotlib.pyplot as plt\nfig, ax = plt.subplots()\n\ny, x = np.ogrid[-1.5:2:1000j, -1.75:1.75:1000j]\nplt.contour(\n    x.ravel(), y.ravel(), x**2 + (y - (x**2)**(1\/3))**2, [1])\nplt.show()\n<\/pre>\n\n\n\n
\u5b9f\u884c\u7d50\u679c<\/h2>\n\n\n\n
\"\"
\u30cf\u30fc\u30c8\u3067\u3059\u266a<\/figcaption><\/figure>\n\n\n\n
\u307e\u3068\u3081<\/h2>\n\n\n\n
\u3000\u63cf\u753b\u3001\u898b\u4e8b\u306b\u6210\u529f\u3057\u307e\u3057\u305f\u3002<\/p>\n\n\n\n
\u3000\u30de\u30cb\u30a2\u30c3\u30af\u306a\u611b\u306e\u544a\u767d\u3067\u3059\u3088\u306d\u3047\u3001\u3067\u3082\u3001\u5acc\u3044\u3058\u3083\u306a\u3044\u3067\u3059\u3002(\u7b11)<\/p>\n","protected":false},"excerpt":{"rendered":"
\u3000\u4eca\u65e5\u3082\u898b\u306b\u6765\u3066\u304f\u3060\u3055\u3063\u3066\u3001\u3042\u308a\u304c\u3068\u3046\u3054\u3056\u3044\u307e\u3059\u3002\u77f3\u5ddd\u3055\u3093\u3067\u3059\u3002 \u3000\u660e\u65e5\u304b\u3089\u30b4\u30fc\u30eb\u30c7\u30f3\u30a6\u30a3\u30fc\u30af\u3067\u3059\u306d\u3002\u3060\u3051\u3069\u3069\u3053\u304b\u3078\u304a\u51fa\u304b\u3051\u3059\u308b\u3053\u3068\u3082\u306a\u304b\u306a\u304b\u96e3\u3057\u3044\u72b6\u6cc1\u3067\u3059\u3088\u306d\u3002\u3053\u3046\u3044\u3046\u72b6\u6cc1\u306a\u306e\u3067\u3001\u3053\u306e\u3054\u308d\u3001SNS\u3092\u898b\u308b\u6642\u9593\u304c\u3061\u3087\u3063\u3074\u308a … <\/p>\n
“Python matplotlib \u611b\u306e\u65b9\u7a0b\u5f0f\uff1f” \u306e<\/span>\u7d9a\u304d\u3092\u8aad\u3080<\/a><\/p>\n","protected":false},"author":1,"featured_media":0,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[8,2],"tags":[],"class_list":["post-1187","post","type-post","status-publish","format-standard","hentry","category-program","category-blog"],"aioseo_notices":[],"_links":{"self":[{"href":"https:\/\/www.ishikawasekkei.com\/index.php\/wp-json\/wp\/v2\/posts\/1187","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/www.ishikawasekkei.com\/index.php\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/www.ishikawasekkei.com\/index.php\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/www.ishikawasekkei.com\/index.php\/wp-json\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"https:\/\/www.ishikawasekkei.com\/index.php\/wp-json\/wp\/v2\/comments?post=1187"}],"version-history":[{"count":6,"href":"https:\/\/www.ishikawasekkei.com\/index.php\/wp-json\/wp\/v2\/posts\/1187\/revisions"}],"predecessor-version":[{"id":1199,"href":"https:\/\/www.ishikawasekkei.com\/index.php\/wp-json\/wp\/v2\/posts\/1187\/revisions\/1199"}],"wp:attachment":[{"href":"https:\/\/www.ishikawasekkei.com\/index.php\/wp-json\/wp\/v2\/media?parent=1187"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/www.ishikawasekkei.com\/index.php\/wp-json\/wp\/v2\/categories?post=1187"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/www.ishikawasekkei.com\/index.php\/wp-json\/wp\/v2\/tags?post=1187"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}