# 注释 ## 使用文本框进行注释 先看一个简单的例子: In [1]: ```py import numpy.random import matplotlib.pyplot as plt %matplotlib inline fig = plt.figure(1, figsize=(5,5)) fig.clf() ax = fig.add_subplot(111) ax.set_aspect(1) x1 = -1 + numpy.random.randn(100) y1 = -1 + numpy.random.randn(100) x2 = 1. + numpy.random.randn(100) y2 = 1. + numpy.random.randn(100) ax.scatter(x1, y1, color="r") ax.scatter(x2, y2, color="g") # 加上两个文本框 bbox_props = dict(boxstyle="round", fc="w", ec="0.5", alpha=0.9) ax.text(-2, -2, "Sample A", ha="center", va="center", size=20, bbox=bbox_props) ax.text(2, 2, "Sample B", ha="center", va="center", size=20, bbox=bbox_props) # 加上一个箭头文本框 bbox_props = dict(boxstyle="rarrow", fc=(0.8,0.9,0.9), ec="b", lw=2) t = ax.text(0, 0, "Direction", ha="center", va="center", rotation=45, size=15, bbox=bbox_props) bb = t.get_bbox_patch() bb.set_boxstyle("rarrow", pad=0.6) ax.set_xlim(-4, 4) ax.set_ylim(-4, 4) plt.show() ``` 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Xi61QQMIu2cLrgNEXmIorMRV7lstlIjE1EYS3PWrl8JUuyljh5i1OnTmX37t306dOnytSPBx54gJiYGB555BF27txZYX9xcbE9h89fXnvtNQD+8Ic/VOlhBgO/PTmtdS6SVFxjKe9pWbBgUib7UMvbwEb54WmsKZZoUzSlFuvcVGxUrM+BknXr1jFlyhQaNWrEtddea5/837NnDwsWLKCwsJDBgwdz6623Ata2SP/4f//gnnvuoWvXrgwZMgQVpVi5ciU7t+/k5ltuZsHXC1zey2wx24MGgH2oWRWOAhwfHU9ijFXU0vun8z9/+x++zvia1q1bs2nTJrKysqhXrx5vvfVWlddt164d06dPZ/To0XTq1Il+/fqRkpJCSUkJ+/fvZ8WKFTRs2JCtW7dWeS0be/bscRqlnTp1ilWrVrFhwwZq1arF1KlTPb5WIJGyLsFwOjfsTP1a1sRbbwMF5UWz2FJs92YA8KMkMzMzk5SUFL799lt+/PFHsrOzKSwspH79+lx//fUMHz6c4cOHO50zZswY4uLieOONN5g5cybxCfFc3fNqXn/ndRbMW8A3C77xyobKCueVUhX2x0TFAPDXP/+VB+59gBdffJEFCxYQGxvLrbfeysSJEyv0z3N1HYC//e1vdO7cmcmTJ7Ns2TIWLVpE7dq1adKkCX/+858ZNmyYV59h//79vPDCC/btcXFxNG3alLvuuotHH32UlJQUj64XaKQzsOAXRrddd9XhuDzuOh7//vvvzJ49mzFjxvh076rwZo0Go1qdz5gxg9GjRzNjxgzuuOMO340PM1577TXGjh2LyeT7IFA6AwtBweg+duVbLYU7JZYSl3Nttly2uKg44qLiatxaDuGEDFcFvzEyJcUxj2/9kfWcKjjltN+kTCFLXk6MTaS4oNhprs0WYHAlYrZcNiG0iCcnhB225p/dG3evsK9zw84hayZg885s+Ww2PA0q+IK7+TXBc0TkhLDFVZfgiTdMdHt8VFRUhYqBqigsLeTk+ZOcyD/BifwTnDx/stJUj/joeGJMMV7dwx9GjhyJ2WyOqPk4s9kcVPEWkRPcEuq+c97O98XFxVFaWkpR0YXggE3EXImXLThQZC6ixFJCiaXEo5w2x/w1MKbawR2V2V9dOXv2LImJiUETOYmuCi6protVz507l/bt29OhQ4cqI5yuoqU2qlrZ3ptqBl8rHyJ1Mervv/+e3377zV477CsSXRX8wp+lAUNJ27Zt2bx5M6WlpU7desHYuTNP10919Ba9rXwIpP2hoqioiC1bttC2rfuOKUYjIidEFO3btycxMZH58+dTUFBQ6bHlh502jBx+RqJQ+crvv//OnDlzSE5OJjk5OWj3leGq4JLqOlwF68T2smXL2LxlM3GXxNHyspbExcahlKJWTC17FQFAibmEYnOxvQzNpEzERsU6HeMP+cX5lFhKnLbFmGI8EtEScwnnS847DVfL2x/uaK0pLCzk0KFDnDx5ks6dO9OrVy9D5uM8Ha6KyAluMbqPWyBxZWtJSQlfrvqSrB+ziCWWa5pdQ6u6rYJq1+7Tu/li6xf22ttoUzS3dbzNYzt2n97N2kPWJpdXN7066Pb7i1LKvvhP8+bNiYqKMvTaInJCjSDcvc7q9GNRnRCRE2oMrupd3dW3CpGDRFcFQRAQkRMiAFeVEdVhcZ5QJ1vXFGS4KkQE1W3eK9znEasDMicnCGGMzCP6j8zJCYIgICInuCCQc0UyD2XF23lE+d58R4arghOBnCuSeShnPJ1HlO/NNTInJ/hEIOeKZB7KO2wi6KpDsnxvnouctD8XBMIvOlveexN8R+bkBCcCmXMWrvls5RfIzvg0I+TzXuVbXTkSLt9bdUFETnDC6NW3gnVtf6guvfOSEpLC6nurLshwVaiAkatvBfPakURmj0xy9+c6BRtmDZkl350P+O3JKaWmK6WOKaV+MsIgQQg24TiMDlevtzrid3RVKfUn4BwwU2t9hYv9El0VqsRshpwcsFhCc/8fDv3AF9u+AOC2DrdxZdMr7fu6dYN67pd7EEJEUFNIlFItgPkicoI3lI9oHvounbvugnD777JoEfi55opHGB3hDbeIsdGIyAlhjbsEV6vQabRWJNSycEX3kiquFDh++SmGs7+ZAi5y2buyGbdkHJuPbsaC1ZX1N+G3JiQQh1We3Pjx4+3vU1NTSU1NDcZthTDGXURz0eh0thz7mdef6kjBeRPX9C7ijvtCs/DLfcOSWLciLqD3cJcPZ/s+fBUld99vdRa5nJwccnJyvD4v6CInCO5Yf2Q92buy2dJsMgxoBvPf580JFwOETOgCTWX5cMGgOg1pyztIzz//vEfnSZ6cEBLKRzQBThWcIuPTDPLO50G3D2HAXaAsvDnhYma+FZgV6sMVfyO8nkSMwzEJOhAYkUIyG1gFtFVKHVBK3em/WUKkY0uRSEpIctruOIdUE4SuvBiZlImujbr6PX9WVQpK9q5shs8ZXi2SoP3F7+Gq1vqvRhgi1DzS26TTvXH3CkX79WvVZ+6wudYHrtVBal1ygP+b2Zw3J1xMu8tLuPq64hBZbAzlh4j2z4qxQ0Z3idc1rS5WKh6EkOIqs9/2oKe3SScrCwZ/ao3ODx2Vz1V/qv4C5ygwuftzmTtsblA7iribBwyHJOhAIHNyQkipbFiVlQWDB2uKihRDR+Xz2ItnMWDh9ZASiDpZIxpqJiUkRVyKiQ3x5ISQ42pYFYkC5yneNNMsn19n8wwrE6uaVhcrnpxgCEa2545kgasq6ulpxNN23MajG+0CB555hjWtLlY8OcFv3M0z+fLg+CtwWmtU2QmO78MFm8C489Q8TeL1N7+uJnWDEZET/Mao7Hp/Ba60tJTo6Av/pQMtcL4m0gZSYMIxeBDqhGMROSEs8FfgzGazXeA+fvttdu/YQau2benWowedunQx3F4jvVdH3EWbqzrOpEx0btiZiTdMDCsPLVDfkzfInJzgN/72YzNiiBoVFQXAk/fey0fTprHj55+ZMXUqr4wbx7dff+35xTzE0yipt3OVns6XlT/um+HfsOHuDWElcBAeXZfFkxP8pqp5psrwV+AsFgsmk/W3euvmzeQdO8bL777LlT178sPKlcx86y3efuUVzKWlpA8e7PVn8wdfvRhPh7M1aV7NH0TkBEPw5YEzIopqE7hXnnwSrTV1kpK4vGtXAK7s1Yvo6Gg+nDqV//zrX1Y7DRI6T4aVrryY4XOG071x97AvhjcKT4ffgUSGq0JIMDpN5FReHl/OnMnh/fspOH/evr3L1Vdz54MPktyqFR+88QbzP/3UAOt9T8M4VXAqoovhyxMO6SqyuLQQdIwcoprNZqKioigpLubNCRP45IMPeHTCBAYOG0Z8rVr2czZ//z3/fvFFiouKeOuzz6h90UVV3sfWT87XpplV1YjKAtH+EVZNMwXBhtFpIkWFhdRKTCQmNpbMF17g3NmzTPnnP0moVYu0gQOJT7AGRDr/8Y+MffZZ6jds6JHAGYHjXOX6I+s5VXAqKPcVnBGRE4KGkWkib73yCts2b+bgvn38KS2N1H796HbNNTz3xhtYtOblcePQWtN30CC70F3erVsgPlal2OYqXbUjD7d8tkhFRE4ICkbMwdnSRB4fM4YtGzbQrUcPGjVrxvxPP2X9qlXcescdDLn9dp6fMgWTUkx+9lmKi4oYMGwYcfHxAfhUnuNPBFrwDxE5IeAYOQeXs3Ah61et4qW336Zbjx5ER0cz7M47efXpp/lixgwubdiQP6Wl8cxrr1FQUMB7r79Ov4yMoIhcVZn9kvIRGiS6KgQUXwWu4Px5vvrkE+BCmghA3vHjmEwmOnbpQnR0NKUlJbTp0IEnJk7kzG+/sXDOHPs5L739Nv+blUXtiy8OyGdzJJStxI1sjhCJiMgJ/pOdDX37Wl/ZFx4yXwVOa82/X3yR1cuWUVLs3CSzbv36nD55kqMHDwJgioqitKSEVm3b8j9jx5KTlcWh/fvt3t+ljRoZ+lEBl583VJn9NWWdBn+Q4argH9nZkJEBBWUPeG4uzJ1Llk73eYiqlOJvd99Nvfr1iYmNZe1333H1ddcB0LxVK1I6dGDm229z72OP0bhZM7unV1xYSN2kJC6uU8fJ+/OXJ759gklHN1iHoL/i8vOGikhcetBoxJMT/GPy5AsPPEBBAVnjlvsscBaLhdLSUpomJxNfqxZfzJzJ/xs1itnvvw9Amw4d6DtoEOtXreKjadPYu3MnAHnHjvHz5s00bNLE8O4jG46sv+AlfTAOCgrIbg19R0Df2wrI/mCc3/W7QuAQT07wi+xL8pg8wvo+cxXoX9MZvHk8RRbvBM5isVBYUECtxES7F3YqL49rrruO3unpfPbhh5jNZm6/+25GPfggRYWFLF24kMVffUWLNm0oOH+eIwcP8p8vvgjYHFxBaQGTm+yD1pDxFyiIsW7PNW9mLoQkehoOZVPhjlQ8RArZ2VavCiAzE9ID/4Bl78omY/ZACizWebPYX9LRn86jRMd77cGtXLqUb774goeefpqGTZrw6F13cUndujw1aRK/bt/OB2+8wc+bNjF05Ehuv+ceANbk5PDLli1s3byZ5q1acfPQobRo08brz6E1rFsRW2EVMFvFAyPSoPW3AKTV6QqbNrO4pcXp2KSEJL9rUn3tuxbqfm2hwtOKBxG5SKD8vFhCgnWeKMBC1/fjvheWE9yZDp/Og1LvBQ5gdU4O/54wAYBL6tXj1+3bmfzhh/Zi+12//ML0KVOsQjdqFLfffbf9XH86AGsNrz51MZ/PSOShp89yx3359n3lRS4hOsHqrX09jsVnNrq8nu0YwCvhcZUsHOltyf3FU5GTOblIwMW8mN2rCyB55/Osb/wUOIAeqanc/eij7N+zh03r1jFu4kQu79oVs9mM1po27dsz+uGH6dSlC5/PmMEnH3xgP9cIgQMqXcDacTWrzFsmOs2/OVJQWsC4JeO8jniGQ9+1SEVETvCJ7F3Z/Hz8Z78Fzmw2298XFxXRtHlzGjVtyn8mT+bg3r1ERUVhLi3FYrHYhe4P3bvzzqRJfPnxxz7b7yhwcXGahx4CpbRboeveuLvdq3LsrJGUkFTh2H1n9olghREicpFAZqZ1iGojIcG6zRE3uWy+Mnn1ZIq39/FL4EpLS+2lWjt+/pl2l1/OtE8+4b7HHycmJoZH77qL/bt3Ex0Tg8VisXt0/zN2LNf3788fe/XyyXZHgVPRRcybp5gyBd5/X7kUutiouAqT+elt0lk0YhGzhsyqEFVtXqe51zZJdDZw+C1ySql+SqlflFI7lVKPG2GU4GUWe3q6dQ4uLc36Kj8fZ5uzW7zY+srI8Fvo8n680m8PzlZs//wjj/D0Aw+wYfVq6jdowI0DBjDi3nuJjo7m8TFjOLR/P9HR0RQVFDD3v/8lPiGBJ199leRWrby222mIGl1Il7HP06+fdd/o0c5C99N6a/h0fO/xlc6Nta/fnqSEJLo26srcYXOZeMNErwUrHPquRSp+BR6UUlHAduBG4BDwPfBXrfU2h2Mk8FCeKiKhhk9C9+1rFTdH0tJgkW+9zLKyYOAgMyXFUX43vHzmgQfY/P33PPjUU/zhyitp2KSJfd/ir75i5ltvcT4/nzGZmaz97jtysrL4OCuLpsnJXt+rvMDFDh/GV8/cV+F7nT4d7rpLY5vTdtdPrrJ/p5oa8QwmweondxWwS2u9t+ymnwCDgG2VnVSjcVMh4Ch04ZzFbivVMkLgNq1bx6Z163jwqae4/uabiYqKQmuNxWIhKiqKtIEDiY6J4X/feYeXx43j0oYNeeuTT/wWOFNMMZ0ffoGJd1cUOLB6dKCchM4Vlf07BaMYX4TUM/wVuabAAYe/DwJX+3nNyMZdJDSQ6R6ZmVYxdUwxKT9n5wFGtyw/eugQecePc0X37naBU0o5RUv73HQTXa+6iqOHDlG/USPqN2jg9X3KBxnmzYulX7+XKj3ngtB5fbugEA5L/VUX/BU5j8ah48ePt79PTU0lNTXVz9tGNoZnsdvm7PxIFjZS4GzF8/Hx8cTFx3Pk4EEaNW1qG344EUlQAAAgAElEQVTYKx5W5+SQ0rEj9Rs04JJ69Xy6V8UgQ5x9Dq4qrEIH7spgQ1ltEM7efqDIyckhJyfH6/P8nZO7Bhivte5X9vc4wKK1fsXhGJmTc8TDxN1wGooY0dHXFkV15PCBA/z1hhu4/uabeezFF4mLj8dkMmGxWNj/66+8/OST3DZyJDfecotPdpefg1PDhrBw/MNef5dmM7gwHwjdv5NTInYZNW3NiKBUPCilorEGHm4ADgPrkMBD1YSgBMtXjFyTYeXSpZw8fpwmyck0S06mUbNmfP3ZZ/zzH/9gyN/+xtA776RV27bs3bWL/777LmuXL+ftzz83JMjAsMGQku2XEITTD49USASxrEspdRPwBhAFfKC1nlhuv4hcNcXIjr6PjxnDlvXrOX/+PBfXqQNKMWHqVK7o3p15//0vk555hkuSkoiKiiIhMZHTeXn8e9Ys2l1+udd2uxM48N3bCaaoeCqm4SS6oUBqVwW/MHIObtrLL5M1Zw5P/+tftG7XjnNnz/LS44+zce1aPs/JoUVKCnt27mTZwoXkHTtGizZt6NmnD81atPD6Xo4CFxNrRv1lCMWtvgL8EyZ3w8PMHpmGCo0RYlpTxE+WJKwJBGjYa5QHp7WmsKCAnzdsIG3gQLr36EF0TAzn8/P5dft2bhwwgEZNm2KxWGiZkkJyq1Yu5+48pWIUNQrV5j4mr7YKhtEPfN75PMMjnP4GFCTqWhEp66quBKCKAYwJMtiGqEopEmrV4tiRI8TFxxMdE8PuHTsYdcstXHXttTz72mvE16rF5zNmcOzwYYMFTtGv34Xyq0UjFnnUCcRdlYmrsisg7GpUpdC/IiJygcDgOlGXeNN5xEN7/BU4rbVdqP6ekcG4snZIDRo3ZsuGDZw4epS/Z2Twx2uv5enJk0moVYttP/7IyqVL2bnN9/xxdwLnDVWtleCq7Kp+rfo+2+wOqWE1HhmuGo0HFQ3haI+RaSLLs7MpOH+e9IwMAO588EEevesu+nfvzi1Dh/Ls66+jlOK3U6f4dPp0fjt1inadOvn08fwWuLIh/+SO6ymoW/kw0VUVg9F5cv6uzyqdgisiImc0wapo8LSKwQN7jFz4ed6sWfz4ww+0TEmh1/XXA9Du8su54777+Gz6dM6eOcPeXbvY8fPPrFi8mNwlS3h/7lyfVtUyROBsPwCNgLre3T9QC0b7UxImi1hXREQuFBgRMDCgigF8F7jz+fm89NhjPDBuHI2aNUNrzfaffmLi448Tn5BA30GDiImNBaBO3bpk/O1vNLnsMv7zr39x/1/+QkxMDE2Tk3lvzhzadOjgtd1GDFEdfwAyV0Fu8oV1Gzz1gMJxwehwtCmUSAqJ0VRV0RDsVuWV3M8fD277li28/eqrTHznHRJq1bJvX7VsGS/8v/9HcVERE6ZNo2efPk7nFRcVsWfnTpLq1yehVi2fFp1xEjhTMfM6j6ffxN7ef4flurNkt4bJtyRBd//WahCCg+TJhZLKPDWD2x75ao8/AmcrpLdVM8x86y16pKbSpkMHlFKsWraMf2Zm0rZTJ+584AG6XG3t2VBaUkJ0TIxfH8VJ4ChkHoPpR7ZvPxYhWhtDMAYRuXDAldiFQuTK4e8cXGFBAUop4uLjObR/P4N79KB7z548/tJLtGjTBqUUy7OzeeXJJ2nbqROj7r/fLnRGLToTZypmnmWgVeBs+PI9VqMSO8EZEblQ485LgOAPVydPhjzrojNZ9GPwln9SVOJdP7iiwkLmzZrF97m57N6xg4RatRjw5z9z48CBnDx+nEdGjuSyli15/KWXaJmS4iR0Hf7wB/56111c6WO7cnAxB9fxKfptnOh8UJB/LITQIiIXalx5bEnW+R5694bly63bAuk9lBPaLNIZzDyK8K5l+fn8fB6+/XZKS0u56OKLad6mDft27WJ1Tg7devTgrrFjqVO3Lg/dfjvNW7d2EroVixfzxN13c13fvjz3+uvEJ7he5aoyXAYZlAw1azoicqHGlcjZ8OSBdDeM8mZ41a0bbLSuD+qrwOWfO8fwG2+kSXIy9z3+OB27dLGni+QuWcILjzxCwyZNeODJJ7kkKYkHhw+ndfv2PDphgl3oVi5dSrPmzWneunXVNyxHpVFUGWrWaETkQk354Wp5KhtaGTHUzc6G/v3BYvFZ4ArOn+fPZQGFcS+/TP2GDe393gBMJhOb1q7l8TFjuKxlSyZMnUreiRM8fPvtdOzcmYefeYbW7dsbMwfna5pIAKgpBfDhjiwuHWocV9BKqrg2Z6W4S+D1ppRr8mQoE6PdtKKIeABatCn1OMjw0dSpHD10iJ59+tCgcWNMJpO9NlUphcViocvVV/P8lCls/v57subO5fKuXZny8cesWb6ct199ldKSEu8+exnhLHDeLhwthBYROaNxrBMFq7c2a1bV66IGkPt4m6ncD8Ckp+vw2Ye1qjjDypARI+iXkcG0l18me948wFrZYLFY7GsxWCwWrklNpe+gQXz58cecO3uWy7t1Y+bChTz41FP2hGBvCFeBAymAr45IxYORVFYnWlV1guP8Uu/e7ku2PF2QplzZ1/0JH8Kd9/PAWx159ak6APz5zvOVfpwGjRvz8LPPUlpaykuPP47Wmn4ZGfYhq62dEkBKhw78sHIlWmu01nT4wx88+87KEc4CJ1RPROSMpLI6UdvLFa7E8amnKkZgs7OhfXvYtw+aN4eJE91f04Ww3p/eETrCAw/gsdDVb9CAzBdegGefZeITTwDYhc6xKP/QgQM0aNyYi+rUqfp7ckN1EDgpgK9+iMiFA67Ecfly58BEeSF0F9BwxIWw3m8dtRoidLZlBPf9+iuH9u2j1/XX2z07b4MN1UHgQArgqyMyJ2ckmZmBm3vzJujgiItecvffD1OnWne/+pRnc3Q2oevZpw8Tn3jCPkeXf+4cH7/9NkcPHWLAX/5SYd1UT6guAmfDm0acQugRT85IfO0M0rs3LFlij4YaJo6VzBH669G99PjjFBcVsXv7drLnzWP6V1/5vapWdRA4ofoheXKhprwQmUzwwgvWObnKjqsqR27yZFi/Hk6dct5XLj9v2jSr0AE89uKZKoUOIO/4caa88AJZc+diiorio6+/pr0PgYYKAvfMBvotH2fdKcm9QhVIMnB1wZuCfU8y/H1IQvZF6I4fOcL0N99k2OjRtExJqfL48rgUuBf/RHaTAib3BEwmMm96gfRhT1V5LaFmIiIX7lTmbXXtCvXL1g/w1qPxsZzMF6FzXDjaG1wOUV/rS/buxWT8xaFxpdnE3Du+8W7eS0q9agw1u+IhGAvJ+IPjSlvlBS42Fn7+2dhVuJKSrB5cJfWyvgQjDBO4sjm4yT0vCBxAQZTFu0TbAK1gJlRvIk/kqsN/9PKRUrggRJ06QXHxhe2eRlFtuIrwzpplHaJW4dX4InTeUGmQITPTOh/pA/alBBcOJ7uJDxFoIaKJPJHzNdUi1HTvbhWi+n4uc+dYM1uF9+aKQAldlVHU9HQyb3qBBPOF/5KeJNo61ZLWPUXGX6xtzAXBhs8ip5QaqpT6WSllVkp1M9KoiKeyfDojcu3S062C6YH35gqjhc7TNJH0YU8x945vnNY2rWo+rkItaYx12AsEvUZYCE98DjwopdoDFuA/QKbWeoOb44IbeKguffsrmyAPk8lzX4IR5Ql0Hlzfj/uyeLdzoCXtdBKLtnaXwEOEE7ToqlJqGeEkchA2IhEJTLt/Kw+81RHwXuiCkehrG6461pJ64gEK1Z+aLXKCcfTty7TFKTzANMBzofNY4Hz5QSp3TnZrpJa0BuKpyFWaA6CUWox1bfHyPKm1nu+pMePHj7e/T01NJTU11dNThUDhhbjcz1sAPMA0j0rAvBI4d62pKrO73Dnpc+eSPkIWsIl0cnJyyMnJ8f5EW/8vX1/AMqBbJfu14ANZWVqnpVlfWVnGnpeVpXVCgtZWPbK+9+DYqdxnP+WxF3/TPxw+XOH1/aHDeuiocxq0jouz6IULK7E1Le2CDbZXWlrln8+Xc4SIpExbqtQoowr0fWviL7jGFw/Hdt7AgRfy7JYvh6++utCLzua55eW573tXHoemA/ezE1K2um286eTBxZiZNy9Kiu2F0OOJErp6ARnAAaAAOAosdHNcUFS9WuLO6/LVW+nateJ5XbtW9NxMJr+8oan3/VzBo3Py4KJLKvfgHD+/px6lP+cIEQkeenJ+D1ervEG4i5xNaLp2tb68HR76c193D6uvIpeUVPG8pCTX13MUOm+Eosxux6HroxN+uyBwFOiFXcd59z14Oyz3dSgvRBQicp5QXmiC6R1UJmS+eivuPDlX97Jt91YoHK7lKHR2gSNd5siEoCAi5wmuHv5gTWZX5a356uHExl64XmysdZuRQ7xydtuEzi5wSl0YIgtCABGR84RQilyg5pbciaNRQzwX3u807rUKXLC9YaFG46nI1ex+cu4aTAarFKy6VmZU1gvPEXfNPwXBAKRppqfYHti8POvf9etXL8EJJT50ITbkntXxh0EwHBE5ITg4/kj8/POFHL1AeMPVpfmCEBRqdmdg4QJGdkl2dS1bW6cNG6yJxz72sfOI6torUAgpsiRhJONr5YSv13KxmLVg7ZQiDQRChwxXIxlvVgIL5rV8pRoOV6UVVOCQ4WqkEu6L9PiCp5/Jz9buoaBC5+LSAu8W5xH8RkQuXHH14Hu7SI8RrdQDcS1HKvtM5b8DiawKvuBJMp0/L8I5Gbg84VIT6S5R2JeaViM/UyC+H3efqfx3EBvrXM1RTZKNs3Zm6YQJCZrxaMajEyYk6Kyd4W93dQBJBvaScJrvcTX/ZVtwOhjzYsHMHXQ31wfuF8l2PK4aJBtL4CEweDonJ56cjXBqxuiua8iECYFvMxTspgXeeK3h8u8jhAVEmieXn5/Pjh072LlzJ6dPn6bYcQFmI/jtN+dFncG6mv0llxh7H08oLrbaU57YWKhVC86XNaqsVcu6zUhcfQ+O9y/7PmJjY7n00ktp27Ytbdq0IT4+3vd7upprK+9Z2z5nIJONhWpFRFU8HDlyhHnz5tG8eXPatWtHgwYNiI2NRSkDGxIXFlofcJutSkFi4oWHKjER/HmQvSUvD0pKnLfFxkK9eoG978mTlYtcvXporSkuLubQoUPs2LGDo0ePctttt5GUlGSsLeXFDwIbeJDARrUiYkQuLy+Pzz//nPT0dFq1amWgZS4oLIT8fOv72Fg4d85Z9OrWtQqd43GBEr/CQjh92vX9A0n5+9qo5P5btmxh1apV/PWvf+Wiiy4KrH2BIpzmZAWPiJg8uR9//JHOnTsHXuDA+gDXq2d9FRc7P+haW4XNJgJFRdbX6dPWbYGwpW5diIuzvvwRuMJCq4d28mTVtjreNybG+qri/pdffjktW7Zk27Zt3tkVTjl/UjIWsYR1WZfWmp07dzJ06NBQm3KB/HzX4hcIDys+3v/rlvfMiourFkwf7tuuXTu+++47rrrqKs9OMLLkTBAqIaw9ud9//x3A+LkeT0hMtA7RbNjm6Kobv//uWpQNplmzZpw4cQKz2ezZCeHmOQUq2VkIOWHtyRUVFfkXtfMH27DN1dyb41A2nMWvsLBi8CIQ98jPxwTEKkVxcTEJjmJRXXBYehGQwEMEEdaenNba2AiqtzjO0dkEzsi5Mg8ZNWoUJpOJ/fv3e3eiO4/NKFEuNz+pzp5FL1ni2bnh6DnZ2kYtWiQCF0GEtch5gtls5r333qN3794kJSURGxtLw4YN6dy5M3//+9+ZP3++8Td1JX4BxjCxj4mp0ua0tDRMJhPJyclYLBb3B7qan7z7bs+CCNWw2F6onoT1cLUqzGYzt9xyC9nZ2dStW5dbbrmFZs2aUVxczJYtW5g1axbbt29nwIABoTbVb3xKw7Hl+TkOratI8di9ezdLyryxgwcPsnDhQm6++WbP73n6tDWg4IloSf85IQhUa5GbPXs22dnZdOnSheXLl1fI0SooKGDdunUhsi4MqGxe0Q3vvfceAP/4xz/417/+xbvvvute5MqLqA1bEEEETAgD/BquKqUmKaW2KaU2K6XmKKXqGGWYJ6xatQqwzlm5SkJNSEigd+/eTtvOnj3LpEmTuP7662nWrBlxcXE0aNCAQYMGsWbNGpf3MZlM9OnTh+PHjzN69GgaNWpE7dq16dWrFytWrACsZWeZmZkkJycTHx9Pp06d+OKLLypca8aMGZhMJj766CMWLFhAz549qV27NklJSQwdOpRdu3Z59R2sXbuW2267jUaNGhEXF0dycjL33HMPR44csR7gxdC6tLSUGTNmcPHFF/P888/TuXNnvvnmGw4fPuz+pOgw+J0Mp3w7Iezwd05uEdBJa90Z2AGM898kz6lfvz4A27dv9/icrVu38vTTTxMdHc2AAQPIzMwkLS2NpUuXct1115Ht5iH57bff6NWrF5s3b2b48OHceuut/PDDD6Snp7Nx40b69OnDggULGDRoECNvv50D+/czbNgw1n73ncvrzZkzh4yMDJKTkxk7diw9evTgyy+/5JprrmHHjh0efZbp06fTq1cvsrOzueGGG3jkkUe48soref/997nyyis5cOCAx98LwFdffcWxY8cYNmwYCQkJjB49GrPZzPTp0ysebAs6uIreGhlEqErAvO2xJ9Q8PKni9+QFZAD/62K7z10Gjh07pj/66CO3+zdu3KhjY2O1yWTSI0aM0HPmzNF79+6t9JpnzpzRJ0+erLD94MGDukmTJrpDhw4V9imltFJK33vvvU7bP/74Y62U0nXq1NEDBw7URUVFWhcUaH34sF4xd65WSumMm26ybivjww8/tF9vwYIFTtebMmWKVkrpG264wWn7yJEjtVJK79u3z75t+/btOiYmRqekpOjDhw87Hb9kyRIdFRWlMzIyrPfOy7O+HOxwRXp6ulZK6dWrV2uttc7Ly9OxsbG6RYsW2mKxOB+cl6f1oUNOr2kvvKDzb7rJuG4lnizAHU7dY4SggoddSIwUufnAcBfbff4QVYmc1lp/9tlnunHjxnbhUErppKQknZGRoefPn+/V/R588EGtlNIHDhxw2q6U0rVr19bnzp1z2m42m3V0dLQ2mUx6z5491o0OD3+Lyy7TrZo3t24rwyZyN954Y4X7m81m3bp16wqC5krkxo4dq5VS+ptvvqn4QQoK9OD+/XV0dLQ+t3PnBSE6fNit0O3du1ebTCbdvn17p+233nqrVkrphQsXOp/gSuReeknn5+e7vL5PeCJgInI1Fk9FrsoJFaXUYqCRi11Paq3nlx3zFFCstZ5lgHPpFUOHDiUjI4Nly5axcuVKNm7cSG5uLvPmzWPevHnccccdzJgxw+mclStXMmXKFFavXs2JEycqtG06dOgQzZo1c9rWtm1bEsvll5lMJho2bEhBQQEtWrSoYFvTRo34fvNml3aXnyu0Xe/aa69l9+7dbNq0ieTkZLefe/Xq1QDk5OSwdu3aCztKS6GggOPHj2M2m9n+6690u+IK675KStDef/99tNbceeedTttHjRrFnDlzeO+99+jXr9+FHa4it6FIAs7MtJaEORbWhzrfTggrqhQ5rXVaZfuVUqOA/sAN7o4ZP368/X1qaiqpqame2ucR0dHRpKWlkVbWUdZisfDll18yevRoZs6cSUZGBoMGDQJg7ty53HbbbdSqVYu0tDRat25NYmIiJpOJZcuWsXz5coqKiirco04d1zGV6Oho530OD390dDSlpaUuk28bNmzo8nqNGll/T86cOVPpZz558iQAkyZNcnuMUop8W++5SrDNu0VFRXH77bc77evXrx8NGjRg/vz5HDt27ILdriK3Rve280TApFKhxpCTk0NOTo7X5/kVGlNK9QMeBXprrd22t3AUuWBgMpkYOnQoP/30ExMmTGDZsmV2kXvmmWeIj4/nhx9+oF27dk7nHTp0iOXLl/t3c8eH35bA68JzOnbsmMvTjx49CrgXVRt16tRBKcWZM2eoXbv2hR0nT1orEFzhpgTt66+/tkdjy3uwjkyfPp1x4xxiS0Y0EKgMTwVM8u1qBOUdpOeff96j8/yN//8biAUWl2Xkr9Za3+fnNQ3D9vBrhzyuXbt2ccUVV1QQOIvFQm5urjE3tj38MTFuD8nJyeHpp5922mY2m8nNzUUpRdeuXV2fWFYr2qNrVzZs2MB3331H//79L+x3lbsWEwMmk9s8OVtu3IABA1x6mLbUkg8++MBZ5IKBCJjgJ36JnNY6xShDfGH27Nlceuml3HDDDRXKno4ePWp/eK+77jr79pYtW7Jjxw6OHDlC48aNAasIjh8/nm3btgWtVnbp0qUsWLDAKdF26tSp7N69m+uvv57LLrus4kkObZMeGDGCd2fO5JGxY0lJSSElpeyfosyTLD59mrXr1/OnG2+s1Ns6cOAAWVlZJCUl8fnnnxPrZsi5a9cucnNz+fbbb7nxxhv9+uzSgVcIJmGQyek769atY8qUKTRq1Ihrr73WPvm/Z88eFixYQGFhIYMHD+bWW2+1n/PII49wzz330LVrV4YMGUJMTAwrV65k27ZtDBgwwPBaV0cv0pEBAwaQkZFBRkYGrVu3ZtOmTWRlZVGvXj3eeust1xcrKIAy77RdmzZMnzyZ0ZmZdOrUiX79+pGSkkJJSQn79+9nxYoVNGzYkK1bt1Zq3wcffIDFYuH22293K3AAd911F7m5ubz77rv+iZz0kROCjSchWH9eBDCF5MCBA3ratGk6IyNDt2vXTl988cU6NjZWN2nSRN988836v//9r8vzZsyYobt06aITExP1pZdeqocMGaK3bNmix48fr00mk16+fLnT8Uop3adPH5fXatGihW7ZsqXLfampqdpkMjlts6WQfPTRR/rrr7/WPXr00ImJibpu3br6tttu0zt37qxwnVGjRmmTyaT3bdpUIW3jpxUr9KhRo3Tz5s11XFycrlevnr7iiiv0Pffco5ctW+b2u9PamrKSnJysTSaT/umnnyo99vz58/qSSy7RcXFx+sSJEy6PmTZtWtUpJJLyIRgEwc6Tc3uDAOfJVTccRc5ryhKNPcl7CwUickIw8VTkqn2rpRpFCHrZGU449pETIppqPSdXIwl02kagkbw2IciEtciVLTkWajMMRSkV2m7HAcajzyZpIUIQCWuRi4uLc1l9UJ0ZOXIkI0eODLUZhqO1pqioqNIIrSCEgrCek6tduzalpaVVljgJoefIkSPUrVuXqKioUJsiCE6EtciZTCbatGnjcX81IXTs2LGDtm3bhtoMQahAWIscwBVXXMEPP/xQeXdaIaTs3r2bbdu20bFjx1CbIggVUIGe2FdKaX/vsWfPHrKysujYsSNt27alYcOGmExhr88Rjdls5vDhw+zYsYMdO3YwePBge5mcIASDssBklZGuaiFyYG0t9Msvv7Bjxw5+++03oqKiIjpKGc5orTGbzdSvX5+UlBQ6dOhQZdcUQTCaiBM5R7TWlAR6ZfiawrffwptvWt8/9BB4WJcaExPj/Y+MFOYLBhLRIicYRPli+YSEC8XyRgtSZfcSBB8QkRPcYxOw9evh1CnnfWlpVlEzWpD69rWuplX+XosW+X5NoUbjqciFdTKwEADKe1SumDzZeb8sFi1UYyREWdMoL2COBLJYXgrzhRAhnpwASUnQvbvz3JvRK2BJYb4QImROrqaRnQ0DB1rXgQDrCltffVVRcCQSKoQ5Micn+Id0ChEiBJmTq2lMnnzBiwPre5vHJggRiIicIAgRjYhcTUOinEINQwIPNREJKggRgFQ8CIIQ0XgqcjJcjQSys61lU337Wt8LgmDHZ09OKfVPYCCggZPAKK31ARfHiScXSKTwXaihBHy4qpS6SGv9e9n7B4HOWuu7XBwnIhdIpPBdqKEEfLhqE7gyagN5vl5LEAQhUPg1J6eUelEptR8YCbxsjEmCV0hKiCBUSqXDVaXUYqCRi11Paq3nOxz3BNBOa32ni2vIcDXQSEqIUAMxpHZVa53m4f1mAd+42zl+/Hj7+9TUVFJTUz28rOARUmcq1ABycnLIycnx+jx/Ag8pWuudZe8fBK7SWo9wcZx4coIgGE4wupBMVEq1A8zAr8C9flxLEAQhIEjFgyAI1RKpePAWqRoQhIhEPDmQqgFBqIaIJ+cN7lanEgSh2iMiJwhCRCMiB1I1IAgRjMzJ2ZCqAUGoVkjTTEEQIhoJPIQ7krIiCEFBPLlQICkrguA34smFM5KyIghBQ0ROEISIRkQuFEjKiiAEDZmTCxWSsiIIfiEpJIIgRDQSeBAEQUBEThCECEdEThCEiEZEThCEiEZEThCEiEZEThCEiEZEThCEiEZEThCEiEZEThCEiEZEThCEiEZEThCEiEZEThCEiMZvkVNKZSqlLEqpJCMMEgRBMBK/RE4pdRmQBuwzxpzAkpOTE2oT7IgtrhFbKhIudkB42eIp/npyrwGPGWFIMAinfyCxxTViS0XCxQ4IL1s8xWeRU0oNAg5qrX800B5BEARDia5sp1JqMdDIxa6ngHFAX8fDDbRLEATBEHzqDKyUuhxYApwv29QMOARcpbU+Xu5YaQssCEJACFr7c6XUHqC71vqU3xcTBEEwEKPy5MRbEwQhLAn4QjaCIAihJKgVD+GQOKyU+qdSarNSapNSaklZrl+obJmklNpWZs8cpVSdENkxVCn1s1LKrJTqFiIb+imlflFK7VRKPR4KG8rsmK6UOqaU+ilUNjjYcplSalnZv80WpdRDIbQlXim1tuy52aqUmhgqWxxsilJKbVRKza/suKCJXBglDr+qte6ste4CzAOeC6Eti4BOWuvOwA6sEetQ8BOQAXwXipsrpaKAqUA/oCPwV6VUh1DYAnxYZkc4UAI8orXuBFwD3B+q70VrXQj0KXtu/gD0UUpdGwpbHHgY2EoV02XB9OTCInFYa/27w5+1gbwQ2rJYa20p+3Mt1ih1KOz4RWu9I6AfVq0AAAJdSURBVBT3LuMqYJfWeq/WugT4BBgUCkO01iuA06G4d3m01ke11pvK3p8DtgFNQmiPLZsiFogCQhZoVEo1A/oD71NF+lpQRC7cEoeVUi8qpfYDI4GXQ21PGaOBb0JtRIhoChxw+Ptg2TahDKVUC6Ar1h/DUNlgUkptAo4By7TWW0NlC/A68ChgqerASpOBvSGcEocrseVJrfV8rfVTwFNKqSewfll3hsqWsmOeAoq11rNCaUcIkehXJSilagNfAA+XeXQhoWzU0aVs7jhbKZWqtc4Jth1KqVuA41rrjUqp1KqON0zktNZpbgy6HGgJbFZKgXVItl4pVSFxONC2uGAWAfaeqrJFKTUKq9t9QyjtCDGHAMcA0GVYvbkaj1IqBvgS+F+t9bxQ2wOgtT6jlFoAXAnkhMCEnsBApVR/IB64WCk1U2t9h6uDAz5c1Vpv0Vo31Fq31Fq3xPqft1ugBK4qlFIpDn8OAjaGwo4yW/phdbkHlU3shgOhKM/7AUhRSrVQSsUCw4CvQmBHWKGsXsEHwFat9RshtqW+UuqSsvcJWIOIIXl2tNZPaq0vK9OTvwBL3QkchKZpZqiHJhOVUj+VzS2kApkhtOXfWIMfi8tC4W+FwgilVIZS6gDWCN4CpdTCYN5fa10KPABkY42Wfaq13hZMG2wopWYDq4C2SqkDSqmATWV4QC/gdqyRzI1lr1BFfhsDS8uem7XAfK31khDZUp5KNUWSgQVBiGik/bkgCBGNiJwgCBGNiJwgCBGNiJwgCBGNiJwgCBGNiJwgCBGNiJwgCBGNiJwgCBHN/wc1kGrP5JMFvQAAAABJRU5ErkJggg==) `text()` 函数接受 `bbox` 参数来绘制文本框。 ```py bbox_props = dict(boxstyle="rarrow,pad=0.3", fc="cyan", ec="b", lw=2) t = ax.text(0, 0, "Direction", ha="center", va="center", rotation=45, size=15, bbox=bbox_props) ``` 可以这样来获取这个文本框,并对其参数进行修改: ```py bb = t.get_bbox_patch() bb.set_boxstyle("rarrow", pad=0.6) ``` 可用的文本框风格有: | class | name | attrs | | --- | --- | --- | | LArrow | larrow | pad=0.3 | | RArrow | rarrow | pad=0.3 | | Round | round | pad=0.3,rounding_size=None | | Round4 | round4 | pad=0.3,rounding_size=None | | Roundtooth | roundtooth | pad=0.3,tooth_size=None | | Sawtooth | sawtooth | pad=0.3,tooth_size=None | | Square | square | pad=0.3 | In [2]: ```py import matplotlib.patches as mpatch import matplotlib.pyplot as plt styles = mpatch.BoxStyle.get_styles() figheight = (len(styles)+.5) fig1 = plt.figure(figsize=(4/1.5, figheight/1.5)) fontsize = 0.3 * 72 ax = fig1.add_subplot(111) for i, (stylename, styleclass) in enumerate(styles.items()): ax.text(0.5, (float(len(styles)) - 0.5 - i)/figheight, stylename, ha="center", size=fontsize, transform=fig1.transFigure, bbox=dict(boxstyle=stylename, fc="w", ec="k")) # 去掉轴的显示 ax.spines['right'].set_color('none') ax.spines['top'].set_color('none') ax.spines['left'].set_color('none') ax.spines['bottom'].set_color('none') plt.xticks([]) plt.yticks([]) plt.show() ``` 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) 各个风格的文本框如上图所示。 ## 使用箭头进行注释 In [3]: ```py plt.figure(1, figsize=(3,3)) ax = plt.subplot(111) ax.annotate("", xy=(0.2, 0.2), xycoords='data', xytext=(0.8, 0.8), textcoords='data', arrowprops=dict(arrowstyle="->", connectionstyle="arc3"), ) plt.show() ``` 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之前介绍了 `annotate` 中 `xy, xycoords, xytext, textcoords` 参数的含义,通常我们把 `xy` 设在 `data` 坐标系,把 `xytext` 设在 `offset` 即以注释点为原点的参考系。 箭头显示是可选的,用 `arrowprops` 参数来指定,接受一个字典作为参数。 不同类型的绘制箭头方式: In [4]: ```py import matplotlib.pyplot as plt import matplotlib.patches as mpatches x1, y1 = 0.3, 0.3 x2, y2 = 0.7, 0.7 fig = plt.figure(1, figsize=(8,3)) fig.clf() from mpl_toolkits.axes_grid.axes_grid import AxesGrid from mpl_toolkits.axes_grid.anchored_artists import AnchoredText #from matplotlib.font_manager import FontProperties def add_at(ax, t, loc=2): fp = dict(size=10) _at = AnchoredText(t, loc=loc, prop=fp) ax.add_artist(_at) return _at grid = AxesGrid(fig, 111, (1, 4), label_mode="1", share_all=True) grid[0].set_autoscale_on(False) ax = grid[0] ax.plot([x1, x2], [y1, y2], ".") el = mpatches.Ellipse((x1, y1), 0.3, 0.4, angle=30, alpha=0.2) ax.add_artist(el) ax.annotate("", xy=(x1, y1), xycoords='data', xytext=(x2, y2), textcoords='data', arrowprops=dict(arrowstyle="-", #linestyle="dashed", color="0.5", patchB=None, shrinkB=0, connectionstyle="arc3,rad=0.3", ), ) add_at(ax, "connect", loc=2) ax = grid[1] ax.plot([x1, x2], [y1, y2], ".") el = mpatches.Ellipse((x1, y1), 0.3, 0.4, angle=30, alpha=0.2) ax.add_artist(el) ax.annotate("", xy=(x1, y1), xycoords='data', xytext=(x2, y2), textcoords='data', arrowprops=dict(arrowstyle="-", #linestyle="dashed", color="0.5", patchB=el, shrinkB=0, connectionstyle="arc3,rad=0.3", ), ) add_at(ax, "clip", loc=2) ax = grid[2] ax.plot([x1, x2], [y1, y2], ".") el = mpatches.Ellipse((x1, y1), 0.3, 0.4, angle=30, alpha=0.2) ax.add_artist(el) ax.annotate("", xy=(x1, y1), xycoords='data', xytext=(x2, y2), textcoords='data', arrowprops=dict(arrowstyle="-", #linestyle="dashed", color="0.5", patchB=el, shrinkB=5, connectionstyle="arc3,rad=0.3", ), ) add_at(ax, "shrink", loc=2) ax = grid[3] ax.plot([x1, x2], [y1, y2], ".") el = mpatches.Ellipse((x1, y1), 0.3, 0.4, angle=30, alpha=0.2) ax.add_artist(el) ax.annotate("", xy=(x1, y1), xycoords='data', xytext=(x2, y2), textcoords='data', arrowprops=dict(arrowstyle="fancy", #linestyle="dashed", color="0.5", patchB=el, shrinkB=5, connectionstyle="arc3,rad=0.3", ), ) add_at(ax, "mutate", loc=2) grid[0].set_xlim(0, 1) grid[0].set_ylim(0, 1) grid[0].axis["bottom"].toggle(ticklabels=False) grid[0].axis["left"].toggle(ticklabels=False) fig.subplots_adjust(left=0.05, right=0.95, bottom=0.05, top=0.95) plt.draw() plt.show() ``` ![](data:image/png;base64,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) 字典中,`connectionstyle` 参数控制路径的风格: | Name | Attr | | --- | --- | | angle | angleA=90,angleB=0,rad=0.0 | | angle3 | angleA=90,angleB=0 | | arc | angleA=0,angleB=0,armA=None,armB=None,rad=0.0 | | arc3 | rad=0.0 | | bar | armA=0.0,armB=0.0,fraction=0.3,angle=None | In [5]: ```py import matplotlib.pyplot as plt import matplotlib.patches as mpatches fig = plt.figure(1, figsize=(8,5)) fig.clf() from mpl_toolkits.axes_grid.axes_grid import AxesGrid from mpl_toolkits.axes_grid.anchored_artists import AnchoredText #from matplotlib.font_manager import FontProperties def add_at(ax, t, loc=2): fp = dict(size=8) _at = AnchoredText(t, loc=loc, prop=fp) ax.add_artist(_at) return _at grid = AxesGrid(fig, 111, (3, 5), label_mode="1", share_all=True) grid[0].set_autoscale_on(False) x1, y1 = 0.3, 0.3 x2, y2 = 0.7, 0.7 def demo_con_style(ax, connectionstyle, label=None): if label is None: label = connectionstyle x1, y1 = 0.3, 0.2 x2, y2 = 0.8, 0.6 ax.plot([x1, x2], [y1, y2], ".") ax.annotate("", xy=(x1, y1), xycoords='data', xytext=(x2, y2), textcoords='data', arrowprops=dict(arrowstyle="->", #linestyle="dashed", color="0.5", shrinkA=5, shrinkB=5, patchA=None, patchB=None, connectionstyle=connectionstyle, ), ) add_at(ax, label, loc=2) column = grid.axes_column[0] demo_con_style(column[0], "angle3,angleA=90,angleB=0", label="angle3,\nangleA=90,\nangleB=0") demo_con_style(column[1], "angle3,angleA=0,angleB=90", label="angle3,\nangleA=0,\nangleB=90") column = grid.axes_column[1] demo_con_style(column[0], "arc3,rad=0.") demo_con_style(column[1], "arc3,rad=0.3") demo_con_style(column[2], "arc3,rad=-0.3") column = grid.axes_column[2] demo_con_style(column[0], "angle,angleA=-90,angleB=180,rad=0", label="angle,\nangleA=-90,\nangleB=180,\nrad=0") demo_con_style(column[1], "angle,angleA=-90,angleB=180,rad=5", label="angle,\nangleA=-90,\nangleB=180,\nrad=5") demo_con_style(column[2], "angle,angleA=-90,angleB=10,rad=5", label="angle,\nangleA=-90,\nangleB=10,\nrad=0") column = grid.axes_column[3] demo_con_style(column[0], "arc,angleA=-90,angleB=0,armA=30,armB=30,rad=0", label="arc,\nangleA=-90,\nangleB=0,\narmA=30,\narmB=30,\nrad=0") demo_con_style(column[1], "arc,angleA=-90,angleB=0,armA=30,armB=30,rad=5", label="arc,\nangleA=-90,\nangleB=0,\narmA=30,\narmB=30,\nrad=5") demo_con_style(column[2], "arc,angleA=-90,angleB=0,armA=0,armB=40,rad=0", label="arc,\nangleA=-90,\nangleB=0,\narmA=0,\narmB=40,\nrad=0") column = grid.axes_column[4] demo_con_style(column[0], "bar,fraction=0.3", label="bar,\nfraction=0.3") demo_con_style(column[1], "bar,fraction=-0.3", label="bar,\nfraction=-0.3") demo_con_style(column[2], "bar,angle=180,fraction=-0.2", label="bar,\nangle=180,\nfraction=-0.2") #demo_con_style(column[1], "arc3,rad=0.3") #demo_con_style(column[2], "arc3,rad=-0.3") grid[0].set_xlim(0, 1) grid[0].set_ylim(0, 1) grid.axes_llc.axis["bottom"].toggle(ticklabels=False) grid.axes_llc.axis["left"].toggle(ticklabels=False) fig.subplots_adjust(left=0.05, right=0.95, bottom=0.05, top=0.95) plt.draw() plt.show() ``` ![](data:image/png;base64,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) `arrowstyle` 参数控制小箭头的风格: | Name | Attrs | | --- | --- | | `-` | None | | `->` | head_length=0.4,head_width=0.2 | | `-[` | widthB=1.0,lengthB=0.2,angleB=None | | ¦`-`¦ | widthA=1.0,widthB=1.0 | | `-`¦`>` | head_length=0.4,head_width=0.2 | | `<-` | head_length=0.4,head_width=0.2 | | `<->` | head_length=0.4,head_width=0.2 | | `<`¦`-` | head_length=0.4,head_width=0.2 | | `<`¦-¦`>` | head_length=0.4,head_width=0.2 | | `fancy` | head_length=0.4,head_width=0.4,tail_width=0.4 | | `simple` | head_length=0.5,head_width=0.5,tail_width=0.2 | | `wedge` | tail_width=0.3,shrink_factor=0.5 | In [6]: ```py import matplotlib.patches as mpatches import matplotlib.pyplot as plt styles = mpatches.ArrowStyle.get_styles() ncol=2 nrow = (len(styles)+1) // ncol figheight = (nrow+0.5) fig1 = plt.figure(1, (4.*ncol/1.5, figheight/1.5)) fontsize = 0.2 * 70 ax = fig1.add_axes([0, 0, 1, 1], frameon=False, aspect=1.) ax.set_xlim(0, 4*ncol) ax.set_ylim(0, figheight) def to_texstring(s): s = s.replace("<", r"$<$") s = s.replace(">", r"$>$") s = s.replace("|", r"$|$") return s for i, (stylename, styleclass) in enumerate(sorted(styles.items())): x = 3.2 + (i//nrow)*4 y = (figheight - 0.7 - i%nrow) # /figheight p = mpatches.Circle((x, y), 0.2, fc="w") ax.add_patch(p) ax.annotate(to_texstring(stylename), (x, y), (x-1.2, y), #xycoords="figure fraction", textcoords="figure fraction", ha="right", va="center", size=fontsize, arrowprops=dict(arrowstyle=stylename, patchB=p, shrinkA=5, shrinkB=5, fc="w", ec="k", connectionstyle="arc3,rad=-0.05", ), bbox=dict(boxstyle="square", fc="w")) ax.xaxis.set_visible(False) ax.yaxis.set_visible(False) plt.draw() plt.show() ``` 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)