{"id":7371,"date":"2025-01-31T12:00:08","date_gmt":"2025-01-31T03:00:08","guid":{"rendered":"https:\/\/home.hirosaki-u.ac.jp\/relativity\/?page_id=7371"},"modified":"2025-01-31T12:55:40","modified_gmt":"2025-01-31T03:55:40","slug":"sympy-%e3%81%a7%e9%ab%98%e3%81%95-h-%e3%81%8b%e3%82%89%e3%81%ae%e6%96%9c%e6%96%b9%e6%8a%95%e5%b0%84%e3%81%ae%e6%9c%80%e5%a4%a7%e5%88%b0%e9%81%94%e8%b7%9d%e9%9b%a2%e3%82%92%e6%b1%82%e3%82%81%e3%82%8b","status":"publish","type":"page","link":"https:\/\/home.hirosaki-u.ac.jp\/relativity\/%e3%82%b3%e3%83%b3%e3%83%94%e3%83%a5%e3%83%bc%e3%82%bf%e6%bc%94%e7%bf%92\/%e9%ab%98%e3%81%95-h-%e3%81%8b%e3%82%89%e3%81%ae%e6%96%9c%e6%96%b9%e6%8a%95%e5%b0%84%e3%81%ae%e6%9c%80%e5%a4%a7%e5%88%b0%e9%81%94%e8%b7%9d%e9%9b%a2%e3%82%92%e6%b1%82%e3%82%81%e3%82%8b%e6%ba%96\/sympy-%e3%81%a7%e9%ab%98%e3%81%95-h-%e3%81%8b%e3%82%89%e3%81%ae%e6%96%9c%e6%96%b9%e6%8a%95%e5%b0%84%e3%81%ae%e6%9c%80%e5%a4%a7%e5%88%b0%e9%81%94%e8%b7%9d%e9%9b%a2%e3%82%92%e6%b1%82%e3%82%81%e3%82%8b\/","title":{"rendered":"SymPy \u3066\u3099\u9ad8\u3055 h \u304b\u3089\u306e\u659c\u65b9\u6295\u5c04\u306e\u6700\u5927\u5230\u9054\u8ddd\u96e2\u3092\u6c42\u3081\u308b"},"content":{"rendered":"
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\u5730\u9762\u304b\u3089\u9ad8\u3055 $h$ \u306e\u5730\u70b9\u304b\u3089\u7a7a\u6c17\u62b5\u6297\u306a\u3057\u306e\u659c\u65b9\u6295\u5c04\u3092\u884c\u3046\u3068\uff0c\u521d\u901f\u5ea6\u306e\u5927\u304d\u3055\u3092\u4e00\u5b9a\u3068\u3057\u305f\u5834\u5408\uff0c\u6c34\u5e73\u65b9\u5411\u306e\u5230\u9054\u8ddd\u96e2\u304c\u6700\u5927\u3068\u306a\u308b\u306e\u306f\u6253\u3061\u4e0a\u3052\u89d2\u5ea6\uff08\u4ef0\u89d2\uff09\u304c\u4f55\u5ea6\u306e\u3068\u304d\u304b\u3092 Python \u306e SymPy \u3092\u4f7f\u3063\u3066\uff08\u304b\u3064 SciPy \u3084 NumPy \u3092\u4f7f\u308f\u305a\u306b\uff09\u6c42\u3081\u308b\u3002<\/p>\n

update: 2025.01.31<\/p>\n<\/div>\n<\/div>\n<\/div>\n

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\u30e9\u30a4\u30d6\u30e9\u30ea\u306e import<\/h3>\n<\/div>\n<\/div>\n<\/div>\n
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In\u00a0[1]:<\/div>\n
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from<\/span> sympy.abc<\/span> import<\/span> *<\/span>\r\nfrom<\/span> sympy<\/span> import<\/span> *<\/span> \r\n\r\n# SymPy Plotting Backends (SPB) \u3067\u30b0\u30e9\u30d5\u3092\u63cf\u304f<\/span>\r\nfrom<\/span> spb<\/span> import<\/span> *<\/span>\r\n\r\n# \u30b0\u30e9\u30d5\u3092 SVG \u3067 Notebook \u306b\u30a4\u30f3\u30e9\u30a4\u30f3\u8868\u793a<\/span>\r\n%<\/span>config<\/span> InlineBackend.figure_formats = ['svg']\r\n\r\ninit_printing<\/span>()<\/span>\r\n<\/pre>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n
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\u904b\u52d5\u65b9\u7a0b\u5f0f\u306e\u89e3<\/h3>\n
\u521d\u671f\u6761\u4ef6\u3092 $t = 0$ \u3067<\/p>\n
$$x(0) = 0, \\quad y(0) = h, \\quad v_x(0)\u00a0 = v_0 \\cos\\theta, \\quad v_y(0) = v_0 \\sin \\theta$$<\/p>\n
\u3068\u3057\u305f\u3068\u304d\u306e\u89e3\u306f<\/p>\n
\\begin{eqnarray}
\nx(t) &=& v_0 \\cos\\theta\\cdot t \\\\
\ny(t) &=& h + v_0 \\sin\\theta\\cdot t -\\frac{1}{2} g t^2
\n\\end{eqnarray}<\/p>\n
\u7121\u6b21\u5143\u5316\u3055\u308c\u305f\u659c\u65b9\u6295\u5c04\u306e\u89e3<\/h3>\n
\u3053\u306e\u7cfb\u306b\u7279\u5fb4\u7684\u306a\u6642\u9593 $\\displaystyle \\tau \\equiv \\frac{v_0}{g}$ \u304a\u3088\u3073\u9577\u3055 $\\displaystyle \\ell \\equiv v_0 \\tau = \\frac{v_0^2}{g}$ \u3067\u89e3\u3092\u7121\u6b21\u5143\u5316\u3059\u308b\u3068\uff0c<\/p>\n
\\begin{eqnarray}
\nT &\\equiv& \\frac{t}{\\tau} \\\\
\nH &\\equiv& \\frac{h}{\\ell} \\\\
\nX &\\equiv& \\frac{x}{\\ell} = \\cos\\theta\\cdot T \\\\
\nY&\\equiv& \\frac{y}{\\ell} = H+ \\sin\\theta\\cdot T -\\frac{1}{2} T^2 \\\\
\n\\end{eqnarray}<\/p>\n
\u8a73\u7d30\u306f\u4ee5\u4e0b\u306e\u30da\u30fc\u30b8<\/p>\n