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October 5, 2021 08:14
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matplotlib-without-line.ipynb
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| { | |
| "nbformat": 4, | |
| "nbformat_minor": 0, | |
| "metadata": { | |
| "colab": { | |
| "name": "matplotlib-without-line.ipynb", | |
| "provenance": [], | |
| "collapsed_sections": [], | |
| "authorship_tag": "ABX9TyO5B+Rf6sq/PCvHhKwxuocS", | |
| "include_colab_link": true | |
| }, | |
| "kernelspec": { | |
| "name": "python3", | |
| "display_name": "Python 3" | |
| }, | |
| "language_info": { | |
| "name": "python" | |
| } | |
| }, | |
| "cells": [ | |
| { | |
| "cell_type": "markdown", | |
| "metadata": { | |
| "id": "view-in-github", | |
| "colab_type": "text" | |
| }, | |
| "source": [ | |
| "<a href=\"https://colab.research.google.com/gist/beiz23/22a83eff08148f71fa5c8e06424167b9/matplotlib-without-line.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>" | |
| ] | |
| }, | |
| { | |
| "cell_type": "markdown", | |
| "metadata": { | |
| "id": "DLuYz8cMCVRU" | |
| }, | |
| "source": [ | |
| "# 線なしでplotする方法\n" | |
| ] | |
| }, | |
| { | |
| "cell_type": "markdown", | |
| "metadata": { | |
| "id": "NEtiXTU_CBG1" | |
| }, | |
| "source": [ | |
| "## Axes.plot()で指定" | |
| ] | |
| }, | |
| { | |
| "cell_type": "markdown", | |
| "metadata": { | |
| "id": "Vf_EwHI9_J1r" | |
| }, | |
| "source": [ | |
| "### linestyle='None'" | |
| ] | |
| }, | |
| { | |
| "cell_type": "code", | |
| "metadata": { | |
| "colab": { | |
| "base_uri": "https://localhost:8080/", | |
| "height": 265 | |
| }, | |
| "id": "zW5yvr2jEacZ", | |
| "outputId": "d8ea8f0b-aa8c-4c1f-eee6-0a602ca20031" | |
| }, | |
| "source": [ | |
| "import numpy as np\n", | |
| "import matplotlib.pyplot as plt\n", | |
| "\n", | |
| "X = np.linspace(0, 1, 20) #0~1の範囲で均等に20点を生成する\n", | |
| "Y = np.sin(X * 2 * np.pi) # np.pi = 3.14...\n", | |
| "\n", | |
| "fig, ax = plt.subplots()\n", | |
| "ax.plot(X, Y, linestyle='None', marker='o') # {'None', ' ', ''}のいずれか。\n", | |
| "\n", | |
| "fig.show()" | |
| ], | |
| "execution_count": null, | |
| "outputs": [ | |
| { | |
| "output_type": "display_data", | |
| "data": { | |
| "image/png": 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m5P1mqgvQtyRZsP5cYHxB+ykdb1YUeZjG2PItbSI4JSJeSN7/GjhlknonSipL2i5p/GJ/MnAwIg4n2/uBSXu+JK1JPqM8NjaWMmyz/FixaJj1KxcwPDiAgOHBga6sd2v9q+moIUkPAO+ts+vq2o2ICEkxycecHhEVSWcA2yTtAV6ZSqARsRHYCNXF66dyrFne9fo0xpZvTRNBRCyZbJ+k30iaFREvSJoFvDjJZ1SSn/skPQwsAv4TGJR0XHJXMBuoHMM5mJlZCmmbhkaA1cn71cA9EytImiHphOT9TGAx8GREBPAQcHGj483MrL3SJoINwPmSngaWJNtIKkm6NalzFlCW9DOqF/4NEfFksu8bwNckjVLtM/hOynjMzGyKVP3FPF9KpVKUy+Vuh2FmliuSdkZEaWK5nyw2Mys4JwIzs4LzpHNmZk30++yvTgRmZg0UYfZXNw2ZmTVQhNlfnQjMzBoowuyvTgRmZg0UYfZXJwIzswaKMPurO4vNzBoY7xD2qCEzswLr99lf3TRkZlZwTgRmZgXnRGBmVnBOBGZmBefOYrMC6Pe5ciydVHcEkk6SdL+kp5OfM+rU+ZSk3TWv340vYC/pNknP1OxbmCYeMzva+Fw5lYOHCN6eK2fLLq8Ma1Vpm4bWAQ9GxHzgwWT7CBHxUEQsjIiFwLnAq8B/11RZO74/InanjMfMJijCXDmWTtpEsBzYnLzfDKxoUv9i4L6IeDXl95pZi4owV46lkzYRnBIRLyTvfw2c0qT+KuD2CWXXSXpM0o3ji9zXI2mNpLKk8tjYWIqQzYqlCHPlWDpNE4GkByQ9Xue1vLZeVBc/nnQBZEmzgAXA1priq4APAB8BTqK6mH1dEbExIkoRURoaGmoWtpklijBXjqXTdNRQRCyZbJ+k30iaFREvJBf6Fxt81GeBH0fEGzWfPX438Zqk7wJfbzFuM2tREebKsXTSDh8dAVYDG5Kf9zSoewnVO4Dfq0kiotq/8HjKeMysjn6fK8fSSdtHsAE4X9LTwJJkG0klSbeOV5I0F5gD/M+E438gaQ+wB5gJ/EPKeMzMbIpS3RFExEvAeXXKy8AVNdu/BI76dSQizk3z/WZmlp6fLDazvucnqxtzIjCzvjb+ZPX4Q3XjT1YDTgYJTzpnZn3NT1Y350RgZn3NT1Y350RgZn3NT1Y350RgZn3NT1Y3585iM+trfrK6OScCM+t7frK6MScCM2vK4/D7mxOBmTXkcfj9z53FZtaQx+H3PycCM2vI4/D7nxOBmTXkcfj9z4nAzBrqhXH4W3ZVWLxhG/PW3cviDdvYsqvSse8uAncWm1lD3R6H787q9nMiMLOmujkOv1FntRNBNlI1DUn6c0lPSHpLUqlBvWWS9koalbSupnyepEeT8jslTU8Tj5n1pjRNO+6sbr+0fQSPAyuBRyarIGkacDPwaeBs4BJJZye7rwdujIj3AS8Dl6eMx8x6zHjTTuXgIYK3m3ZaTQburG6/VIkgIn4eEc0GE58DjEbEvoh4HbgDWJ4sWH8ucFdSbzPVBezNrI+kfQ6hFzqr+10nRg0NA8/VbO9Pyk4GDkbE4QnldUlaI6ksqTw2Nta2YM0sW2mbdlYsGmb9ygUMDw4gYHhwgPUrF7h/IENNO4slPQC8t86uqyPinuxDqi8iNgIbAUqlUnTqe80snVMHB6jUuehPpWnHk8a1V9NEEBFLUn5HBZhTsz07KXsJGJR0XHJXMF5uZn1k7dIzjxj+CW7a6TWdaBraAcxPRghNB1YBIxERwEPAxUm91UDH7jDMrDPctNP7VL0eH+PB0p8B/woMAQeB3RGxVNKpwK0RcWFS70LgJmAasCkirkvKz6DaeXwSsAu4NCJea/a9pVIpyuXyMcdtZlZEknZGxFFD/VMlgm5xIjAzm7rJEoHnGjIzKzgnAjOzgnMiMDMrOCcCM7OCy2VnsaQx4NljPHwm8NsMw8kDn3Mx+Jz7X9rzPT0ihiYW5jIRpCGpXK/XvJ/5nIvB59z/2nW+bhoyMys4JwIzs4IrYiLY2O0AusDnXAw+5/7XlvMtXB+BmZkdqYh3BGZmVsOJwMys4Po2EUhaJmmvpFFJ6+rsP0HSncn+RyXN7XyU2WrhnL8m6UlJj0l6UNLp3YgzS83OuabeZySFpFwPNWzlfCV9Nvl7fkLSf3Q6xqy18O/6NEkPSdqV/Nu+sBtxZknSJkkvSnp8kv2S9K3kz+QxSR9O9YUR0XcvqtNd/wI4A5gO/Aw4e0KdvwK+nbxfBdzZ7bg7cM6fAv4gef/lIpxzUu9dwCPAdqDU7bjb/Hc8n+qU7jOS7T/sdtwdOOeNwJeT92cDv+x23Bmc98eBDwOPT7L/QuA+QMDHgEfTfF+/3hGcA4xGxL6IeJ3qmgfLJ9RZDmxO3t8FnCdJHYwxa03POSIeiohXk83tVFeFy7NW/p4BvglcD/yuk8G1QSvn+5fAzRHxMkBEvNjhGLPWyjkH8O7k/XuA5zsYX1tExCPAgQZVlgPfi6rtVFd7nHWs39eviWAYeK5me39SVrdOVJfKfAU4uSPRtUcr51zrcqq/UeRZ03NObpnnRMS9nQysTVr5O34/8H5J/ytpu6RlHYuuPVo5578HLpW0H/gJ8JXOhNZVU/3/3lDTNYut/0i6FCgBn+h2LO0k6R3APwOXdTmUTjqOavPQJ6ne8T0iaUFEHOxqVO11CXBbRPyTpD8Fvi/pQxHxVrcDy4t+vSOoAHNqtmcnZXXrSDqO6i3lSx2Jrj1aOWckLQGuBi6KFpYF7XHNzvldwIeAhyX9kmpb6kiOO4xb+TveT3VN8Dci4hngKaqJIa9aOefLgR8CRMRPgROpTs7Wz1r6/96qfk0EO4D5kuZJmk61M3hkQp0RYHXy/mJgWyS9MDnV9JwlLQJuoZoE8t52DE3OOSJeiYiZETE3IuZS7Re5KCLyus5pK/+ut1C9G0DSTKpNRfs6GWTGWjnnXwHnAUg6i2oiGOtolJ03Anw+GT30MeCViHjhWD+sL5uGIuKwpCuBrVRHHWyKiCckXQuUI2IE+A7VW8hRqp0yq7oXcXotnvMNwDuBHyX94r+KiIu6FnRKLZ5z32jxfLcCF0h6EngTWBsRub3TbfGc/w74d0lfpdpxfFnOf6lD0u1UE/rMpO/jGuB4gIj4NtW+kAuBUeBV4Aupvi/nf15mZpZSvzYNmZlZi5wIzMwKzonAzKzgnAjMzArOicDMrOCcCMzMCs6JwMys4P4fItLN3Xo6mxYAAAAASUVORK5CYII=\n", | |
| "text/plain": [ | |
| "<Figure size 432x288 with 1 Axes>" | |
| ] | |
| }, | |
| "metadata": { | |
| "needs_background": "light" | |
| } | |
| } | |
| ] | |
| }, | |
| { | |
| "cell_type": "code", | |
| "metadata": { | |
| "colab": { | |
| "base_uri": "https://localhost:8080/" | |
| }, | |
| "id": "7VDL84N5AokP", | |
| "outputId": "e63b3b8a-1e5e-4280-a5d5-66e8b54fe50d" | |
| }, | |
| "source": [ | |
| "X" | |
| ], | |
| "execution_count": null, | |
| "outputs": [ | |
| { | |
| "output_type": "execute_result", | |
| "data": { | |
| "text/plain": [ | |
| "array([0. , 0.05263158, 0.10526316, 0.15789474, 0.21052632,\n", | |
| " 0.26315789, 0.31578947, 0.36842105, 0.42105263, 0.47368421,\n", | |
| " 0.52631579, 0.57894737, 0.63157895, 0.68421053, 0.73684211,\n", | |
| " 0.78947368, 0.84210526, 0.89473684, 0.94736842, 1. ])" | |
| ] | |
| }, | |
| "metadata": {}, | |
| "execution_count": 2 | |
| } | |
| ] | |
| }, | |
| { | |
| "cell_type": "code", | |
| "metadata": { | |
| "colab": { | |
| "base_uri": "https://localhost:8080/" | |
| }, | |
| "id": "nqoUSqtLAp0w", | |
| "outputId": "8268b430-58ff-428a-d1d3-4b8181ea04fa" | |
| }, | |
| "source": [ | |
| "Y" | |
| ], | |
| "execution_count": null, | |
| "outputs": [ | |
| { | |
| "output_type": "execute_result", | |
| "data": { | |
| "text/plain": [ | |
| "array([ 0.00000000e+00, 3.24699469e-01, 6.14212713e-01, 8.37166478e-01,\n", | |
| " 9.69400266e-01, 9.96584493e-01, 9.15773327e-01, 7.35723911e-01,\n", | |
| " 4.75947393e-01, 1.64594590e-01, -1.64594590e-01, -4.75947393e-01,\n", | |
| " -7.35723911e-01, -9.15773327e-01, -9.96584493e-01, -9.69400266e-01,\n", | |
| " -8.37166478e-01, -6.14212713e-01, -3.24699469e-01, -2.44929360e-16])" | |
| ] | |
| }, | |
| "metadata": {}, | |
| "execution_count": 3 | |
| } | |
| ] | |
| }, | |
| { | |
| "cell_type": "markdown", | |
| "metadata": { | |
| "id": "_rr1nB9x_XXO" | |
| }, | |
| "source": [ | |
| "### linewidth=0" | |
| ] | |
| }, | |
| { | |
| "cell_type": "code", | |
| "metadata": { | |
| "colab": { | |
| "base_uri": "https://localhost:8080/", | |
| "height": 265 | |
| }, | |
| "id": "Ai-QrWeeJHFQ", | |
| "outputId": "c5913054-43c3-498f-aa13-cec68fbf4ee4" | |
| }, | |
| "source": [ | |
| "import numpy as np\n", | |
| "import matplotlib.pyplot as plt\n", | |
| "\n", | |
| "X = np.linspace(0, 1, 20) #0~1の範囲で均等に20点を生成する\n", | |
| "Y = np.sin(X * 2 * np.pi) # np.pi = 3.14...\n", | |
| "\n", | |
| "fig, ax = plt.subplots()\n", | |
| "ax.plot(X, Y, linewidth=0, marker='o')\n", | |
| "fig.show()" | |
| ], | |
| "execution_count": null, | |
| "outputs": [ | |
| { | |
| "output_type": "display_data", | |
| "data": { | |
| "image/png": "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\n", | |
| "text/plain": [ | |
| "<Figure size 432x288 with 1 Axes>" | |
| ] | |
| }, | |
| "metadata": { | |
| "needs_background": "light" | |
| } | |
| } | |
| ] | |
| }, | |
| { | |
| "cell_type": "markdown", | |
| "metadata": { | |
| "id": "XQ2zi5W7_aSI" | |
| }, | |
| "source": [ | |
| "### ls=''" | |
| ] | |
| }, | |
| { | |
| "cell_type": "code", | |
| "metadata": { | |
| "colab": { | |
| "base_uri": "https://localhost:8080/", | |
| "height": 265 | |
| }, | |
| "id": "MtW3rlNCCGoE", | |
| "outputId": "da19cbaa-f3be-4b55-aee8-fb4aa350a0f6" | |
| }, | |
| "source": [ | |
| "import numpy as np\n", | |
| "import matplotlib.pyplot as plt\n", | |
| "\n", | |
| "X = np.linspace(0, 1, 20) #0~1の範囲で均等に20点を生成する\n", | |
| "Y = np.sin(X * 2 * np.pi) # np.pi = 3.14...\n", | |
| "\n", | |
| "fig, ax = plt.subplots()\n", | |
| "ax.plot(X, Y, ls='', marker='o')\n", | |
| "fig.show()" | |
| ], | |
| "execution_count": null, | |
| "outputs": [ | |
| { | |
| "output_type": "display_data", | |
| "data": { | |
| "image/png": 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\n", | |
| "text/plain": [ | |
| "<Figure size 432x288 with 1 Axes>" | |
| ] | |
| }, | |
| "metadata": { | |
| "needs_background": "light" | |
| } | |
| } | |
| ] | |
| }, | |
| { | |
| "cell_type": "markdown", | |
| "metadata": { | |
| "id": "s-hbWO5a_cPm" | |
| }, | |
| "source": [ | |
| "### フォーマット指定: 'o'" | |
| ] | |
| }, | |
| { | |
| "cell_type": "code", | |
| "metadata": { | |
| "colab": { | |
| "base_uri": "https://localhost:8080/", | |
| "height": 265 | |
| }, | |
| "id": "f0UTZC36P7KR", | |
| "outputId": "fc0209c7-2caa-4c4a-b5af-39265b8bcc09" | |
| }, | |
| "source": [ | |
| "import numpy as np\n", | |
| "import matplotlib.pyplot as plt\n", | |
| "\n", | |
| "X = np.linspace(0, 1, 20) #0~1の範囲で均等に20点を生成する\n", | |
| "Y = np.sin(X * 2 * np.pi) # np.pi = 3.14...\n", | |
| "\n", | |
| "fig, ax = plt.subplots()\n", | |
| "ax.plot(X, Y, 'o') # 'o'部分は、'[マーカー][線][色]'の順で指定。\n", | |
| "ax.plot(X, Y + 0.2, '.-r') # \n", | |
| "\n", | |
| "\n", | |
| "fig.show()" | |
| ], | |
| "execution_count": null, | |
| "outputs": [ | |
| { | |
| "output_type": "display_data", | |
| "data": { | |
| "image/png": 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\n", | |
| "text/plain": [ | |
| "<Figure size 432x288 with 1 Axes>" | |
| ] | |
| }, | |
| "metadata": { | |
| "needs_background": "light" | |
| } | |
| } | |
| ] | |
| }, | |
| { | |
| "cell_type": "code", | |
| "metadata": { | |
| "colab": { | |
| "base_uri": "https://localhost:8080/", | |
| "height": 265 | |
| }, | |
| "id": "ZGDVmv9RVGRj", | |
| "outputId": "e05c1b65-dc0a-44dd-a6fa-d085a8f2b242" | |
| }, | |
| "source": [ | |
| "import numpy as np\n", | |
| "import matplotlib.pyplot as plt\n", | |
| "\n", | |
| "X = np.linspace(0, 1, 20) \n", | |
| "Y = np.sin(X * 2 * np.pi)\n", | |
| "\n", | |
| "fig, ax = plt.subplots()\n", | |
| "ax.plot(X, Y, 'o')\n", | |
| "ax.plot(X, Y + 0.2, '.-r')\n", | |
| "ax.plot(X, Y+0.4, 'oC4', X, Y+0.6, 'oC5') #C4は4番目の色\n", | |
| "\n", | |
| "fig.show()" | |
| ], | |
| "execution_count": null, | |
| "outputs": [ | |
| { | |
| "output_type": "display_data", | |
| "data": { | |
| "image/png": 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\n", | |
| "text/plain": [ | |
| "<Figure size 432x288 with 1 Axes>" | |
| ] | |
| }, | |
| "metadata": { | |
| "needs_background": "light" | |
| } | |
| } | |
| ] | |
| }, | |
| { | |
| "cell_type": "markdown", | |
| "metadata": { | |
| "id": "vssT7zszCgRK" | |
| }, | |
| "source": [ | |
| "## Line2Dのメソッドで、plot後に指定する" | |
| ] | |
| }, | |
| { | |
| "cell_type": "markdown", | |
| "metadata": { | |
| "id": "XZjcEtHR_g2-" | |
| }, | |
| "source": [ | |
| "### Line2D.set_linestyle('')\n" | |
| ] | |
| }, | |
| { | |
| "cell_type": "code", | |
| "metadata": { | |
| "id": "u9gjcsU6SS2V", | |
| "colab": { | |
| "base_uri": "https://localhost:8080/", | |
| "height": 265 | |
| }, | |
| "outputId": "8ef6da1b-95b3-4be0-d8b5-43dab9214b44" | |
| }, | |
| "source": [ | |
| "import numpy as np\n", | |
| "import matplotlib.pyplot as plt\n", | |
| "\n", | |
| "X = np.linspace(0, 1, 20) #0~1の範囲で均等に20点を生成する\n", | |
| "Y = np.sin(X * 2 * np.pi) # np.pi = 3.14...\n", | |
| "\n", | |
| "fig, ax = plt.subplots()\n", | |
| "line, = ax.plot(X, Y, marker='o') #Line2Dのlistが返されるので、0番目だけ取得\n", | |
| "line.set_linestyle('')\n", | |
| "\n", | |
| "fig.show()" | |
| ], | |
| "execution_count": null, | |
| "outputs": [ | |
| { | |
| "output_type": "display_data", | |
| "data": { | |
| "image/png": "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\n", | |
| "text/plain": [ | |
| "<Figure size 432x288 with 1 Axes>" | |
| ] | |
| }, | |
| "metadata": { | |
| "needs_background": "light" | |
| } | |
| } | |
| ] | |
| }, | |
| { | |
| "cell_type": "markdown", | |
| "metadata": { | |
| "id": "zTdWGSRz_qVq" | |
| }, | |
| "source": [ | |
| "### Line2D.set_linewidth(0)" | |
| ] | |
| }, | |
| { | |
| "cell_type": "code", | |
| "metadata": { | |
| "colab": { | |
| "base_uri": "https://localhost:8080/", | |
| "height": 265 | |
| }, | |
| "id": "ZIle5ewu9Ha7", | |
| "outputId": "2137b00d-d30b-4b7a-c5ce-f99bac81a5a7" | |
| }, | |
| "source": [ | |
| "import numpy as np\n", | |
| "import matplotlib.pyplot as plt\n", | |
| "\n", | |
| "X = np.linspace(0, 1, 20) #0~1の範囲で均等に20点を生成する\n", | |
| "Y = np.sin(X * 2 * np.pi) # np.pi = 3.14...\n", | |
| "\n", | |
| "fig, ax = plt.subplots()\n", | |
| "line, = ax.plot(X, Y, 'o-') #Line2Dのlistが返されるので、0番目だけ取得\n", | |
| "line.set_linewidth(0)\n", | |
| "\n", | |
| "fig.show()" | |
| ], | |
| "execution_count": null, | |
| "outputs": [ | |
| { | |
| "output_type": "display_data", | |
| "data": { | |
| "image/png": 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\n", | |
| "text/plain": [ | |
| "<Figure size 432x288 with 1 Axes>" | |
| ] | |
| }, | |
| "metadata": { | |
| "needs_background": "light" | |
| } | |
| } | |
| ] | |
| }, | |
| { | |
| "cell_type": "markdown", | |
| "metadata": { | |
| "id": "nhPmy9oEColC" | |
| }, | |
| "source": [ | |
| "## デフォルトパラメーターrcParamで指定" | |
| ] | |
| }, | |
| { | |
| "cell_type": "markdown", | |
| "metadata": { | |
| "id": "Z1XnEbmn_1RB" | |
| }, | |
| "source": [ | |
| "### matplotlib.rcParams" | |
| ] | |
| }, | |
| { | |
| "cell_type": "code", | |
| "metadata": { | |
| "id": "nVZfOzUARHNM", | |
| "colab": { | |
| "base_uri": "https://localhost:8080/", | |
| "height": 265 | |
| }, | |
| "outputId": "7a1431bf-dc3e-48e6-b293-c0ddd29a2bac" | |
| }, | |
| "source": [ | |
| "import numpy as np\n", | |
| "import matplotlib as mpl\n", | |
| "import matplotlib.pyplot as plt\n", | |
| "\n", | |
| "X = np.linspace(0, 1, 20) \n", | |
| "Y = np.sin(X * 2 * np.pi)\n", | |
| "\n", | |
| "mpl.rcParams['lines.linewidth'] = 0\n", | |
| "mpl.rcParams['lines.linestyle'] = ''\n", | |
| "mpl.rcParams['lines.marker'] = 'o'\n", | |
| "\n", | |
| "fig, ax = plt.subplots()\n", | |
| "ax.plot(X, Y)\n", | |
| "\n", | |
| "fig.show()" | |
| ], | |
| "execution_count": null, | |
| "outputs": [ | |
| { | |
| "output_type": "display_data", | |
| "data": { | |
| "image/png": 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\n", | |
| "text/plain": [ | |
| "<Figure size 432x288 with 1 Axes>" | |
| ] | |
| }, | |
| "metadata": { | |
| "needs_background": "light" | |
| } | |
| } | |
| ] | |
| }, | |
| { | |
| "cell_type": "markdown", | |
| "metadata": { | |
| "id": "Tg5je9Pd_-hv" | |
| }, | |
| "source": [ | |
| "### matplotlib.rc('lines', ...)" | |
| ] | |
| }, | |
| { | |
| "cell_type": "code", | |
| "metadata": { | |
| "colab": { | |
| "base_uri": "https://localhost:8080/", | |
| "height": 265 | |
| }, | |
| "id": "5EmSoehGPank", | |
| "outputId": "23f45004-018b-41d1-b2da-7b91d8dd3652" | |
| }, | |
| "source": [ | |
| "import numpy as np\n", | |
| "import matplotlib \n", | |
| "import matplotlib.pyplot as plt\n", | |
| "\n", | |
| "X = np.linspace(0, 1, 20) \n", | |
| "Y = np.sin(X * 2 * np.pi)\n", | |
| "\n", | |
| "matplotlib.rc('lines', linewidth=0, linestyle='', marker='.')\n", | |
| "\n", | |
| "fig, ax = plt.subplots()\n", | |
| "ax.plot(X, Y)\n", | |
| "\n", | |
| "fig.show()" | |
| ], | |
| "execution_count": null, | |
| "outputs": [ | |
| { | |
| "output_type": "display_data", | |
| "data": { | |
| "image/png": 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\n", | |
| "text/plain": [ | |
| "<Figure size 432x288 with 1 Axes>" | |
| ] | |
| }, | |
| "metadata": { | |
| "needs_background": "light" | |
| } | |
| } | |
| ] | |
| }, | |
| { | |
| "cell_type": "markdown", | |
| "metadata": { | |
| "id": "wUQNlPViCyNs" | |
| }, | |
| "source": [ | |
| "## 散布図を使う" | |
| ] | |
| }, | |
| { | |
| "cell_type": "markdown", | |
| "metadata": { | |
| "id": "qljap5ZlAaGu" | |
| }, | |
| "source": [ | |
| "### Axes.scatter(x, y)" | |
| ] | |
| }, | |
| { | |
| "cell_type": "code", | |
| "metadata": { | |
| "colab": { | |
| "base_uri": "https://localhost:8080/", | |
| "height": 265 | |
| }, | |
| "id": "CMRiMnN6Rt1l", | |
| "outputId": "b5e3f82a-c7ef-4e0d-ec8b-55e79c5574c2" | |
| }, | |
| "source": [ | |
| "import numpy as np\n", | |
| "import matplotlib.pyplot as plt\n", | |
| "\n", | |
| "X = np.linspace(0, 1, 20) \n", | |
| "Y = np.sin(X * 2 * np.pi)\n", | |
| "\n", | |
| "fig, ax = plt.subplots()\n", | |
| "ax.scatter(X, Y)\n", | |
| "\n", | |
| "fig.show()" | |
| ], | |
| "execution_count": null, | |
| "outputs": [ | |
| { | |
| "output_type": "display_data", | |
| "data": { | |
| "image/png": 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m5P1mqgvQtyRZsP5cYHxB+ykdb1YUeZjG2PItbSI4JSJeSN7/GjhlknonSipL2i5p/GJ/MnAwIg4n2/uBSXu+JK1JPqM8NjaWMmyz/FixaJj1KxcwPDiAgOHBga6sd2v9q+moIUkPAO+ts+vq2o2ICEkxycecHhEVSWcA2yTtAV6ZSqARsRHYCNXF66dyrFne9fo0xpZvTRNBRCyZbJ+k30iaFREvSJoFvDjJZ1SSn/skPQwsAv4TGJR0XHJXMBuoHMM5mJlZCmmbhkaA1cn71cA9EytImiHphOT9TGAx8GREBPAQcHGj483MrL3SJoINwPmSngaWJNtIKkm6NalzFlCW9DOqF/4NEfFksu8bwNckjVLtM/hOynjMzGyKVP3FPF9KpVKUy+Vuh2FmliuSdkZEaWK5nyw2Mys4JwIzs4LzpHNmZk30++yvTgRmZg0UYfZXNw2ZmTVQhNlfnQjMzBoowuyvTgRmZg0UYfZXJwIzswaKMPurO4vNzBoY7xD2qCEzswLr99lf3TRkZlZwTgRmZgXnRGBmVnBOBGZmBefOYrMC6Pe5ciydVHcEkk6SdL+kp5OfM+rU+ZSk3TWv340vYC/pNknP1OxbmCYeMzva+Fw5lYOHCN6eK2fLLq8Ma1Vpm4bWAQ9GxHzgwWT7CBHxUEQsjIiFwLnAq8B/11RZO74/InanjMfMJijCXDmWTtpEsBzYnLzfDKxoUv9i4L6IeDXl95pZi4owV46lkzYRnBIRLyTvfw2c0qT+KuD2CWXXSXpM0o3ji9zXI2mNpLKk8tjYWIqQzYqlCHPlWDpNE4GkByQ9Xue1vLZeVBc/nnQBZEmzgAXA1priq4APAB8BTqK6mH1dEbExIkoRURoaGmoWtpklijBXjqXTdNRQRCyZbJ+k30iaFREvJBf6Fxt81GeBH0fEGzWfPX438Zqk7wJfbzFuM2tREebKsXTSDh8dAVYDG5Kf9zSoewnVO4Dfq0kiotq/8HjKeMysjn6fK8fSSdtHsAE4X9LTwJJkG0klSbeOV5I0F5gD/M+E438gaQ+wB5gJ/EPKeMzMbIpS3RFExEvAeXXKy8AVNdu/BI76dSQizk3z/WZmlp6fLDazvucnqxtzIjCzvjb+ZPX4Q3XjT1YDTgYJTzpnZn3NT1Y350RgZn3NT1Y350RgZn3NT1Y350RgZn3NT1Y3585iM+trfrK6OScCM+t7frK6MScCM2vK4/D7mxOBmTXkcfj9z53FZtaQx+H3PycCM2vI4/D7nxOBmTXkcfj9z4nAzBrqhXH4W3ZVWLxhG/PW3cviDdvYsqvSse8uAncWm1lD3R6H787q9nMiMLOmujkOv1FntRNBNlI1DUn6c0lPSHpLUqlBvWWS9koalbSupnyepEeT8jslTU8Tj5n1pjRNO+6sbr+0fQSPAyuBRyarIGkacDPwaeBs4BJJZye7rwdujIj3AS8Dl6eMx8x6zHjTTuXgIYK3m3ZaTQburG6/VIkgIn4eEc0GE58DjEbEvoh4HbgDWJ4sWH8ucFdSbzPVBezNrI+kfQ6hFzqr+10nRg0NA8/VbO9Pyk4GDkbE4QnldUlaI6ksqTw2Nta2YM0sW2mbdlYsGmb9ygUMDw4gYHhwgPUrF7h/IENNO4slPQC8t86uqyPinuxDqi8iNgIbAUqlUnTqe80snVMHB6jUuehPpWnHk8a1V9NEEBFLUn5HBZhTsz07KXsJGJR0XHJXMF5uZn1k7dIzjxj+CW7a6TWdaBraAcxPRghNB1YBIxERwEPAxUm91UDH7jDMrDPctNP7VL0eH+PB0p8B/woMAQeB3RGxVNKpwK0RcWFS70LgJmAasCkirkvKz6DaeXwSsAu4NCJea/a9pVIpyuXyMcdtZlZEknZGxFFD/VMlgm5xIjAzm7rJEoHnGjIzKzgnAjOzgnMiMDMrOCcCM7OCy2VnsaQx4NljPHwm8NsMw8kDn3Mx+Jz7X9rzPT0ihiYW5jIRpCGpXK/XvJ/5nIvB59z/2nW+bhoyMys4JwIzs4IrYiLY2O0AusDnXAw+5/7XlvMtXB+BmZkdqYh3BGZmVsOJwMys4Po2EUhaJmmvpFFJ6+rsP0HSncn+RyXN7XyU2WrhnL8m6UlJj0l6UNLp3YgzS83OuabeZySFpFwPNWzlfCV9Nvl7fkLSf3Q6xqy18O/6NEkPSdqV/Nu+sBtxZknSJkkvSnp8kv2S9K3kz+QxSR9O9YUR0XcvqtNd/wI4A5gO/Aw4e0KdvwK+nbxfBdzZ7bg7cM6fAv4gef/lIpxzUu9dwCPAdqDU7bjb/Hc8n+qU7jOS7T/sdtwdOOeNwJeT92cDv+x23Bmc98eBDwOPT7L/QuA+QMDHgEfTfF+/3hGcA4xGxL6IeJ3qmgfLJ9RZDmxO3t8FnCdJHYwxa03POSIeiohXk83tVFeFy7NW/p4BvglcD/yuk8G1QSvn+5fAzRHxMkBEvNjhGLPWyjkH8O7k/XuA5zsYX1tExCPAgQZVlgPfi6rtVFd7nHWs39eviWAYeK5me39SVrdOVJfKfAU4uSPRtUcr51zrcqq/UeRZ03NObpnnRMS9nQysTVr5O34/8H5J/ytpu6RlHYuuPVo5578HLpW0H/gJ8JXOhNZVU/3/3lDTNYut/0i6FCgBn+h2LO0k6R3APwOXdTmUTjqOavPQJ6ne8T0iaUFEHOxqVO11CXBbRPyTpD8Fvi/pQxHxVrcDy4t+vSOoAHNqtmcnZXXrSDqO6i3lSx2Jrj1aOWckLQGuBi6KFpYF7XHNzvldwIeAhyX9kmpb6kiOO4xb+TveT3VN8Dci4hngKaqJIa9aOefLgR8CRMRPgROpTs7Wz1r6/96qfk0EO4D5kuZJmk61M3hkQp0RYHXy/mJgWyS9MDnV9JwlLQJuoZoE8t52DE3OOSJeiYiZETE3IuZS7Re5KCLyus5pK/+ut1C9G0DSTKpNRfs6GWTGWjnnXwHnAUg6i2oiGOtolJ03Anw+GT30MeCViHjhWD+sL5uGIuKwpCuBrVRHHWyKiCckXQuUI2IE+A7VW8hRqp0yq7oXcXotnvMNwDuBHyX94r+KiIu6FnRKLZ5z32jxfLcCF0h6EngTWBsRub3TbfGc/w74d0lfpdpxfFnOf6lD0u1UE/rMpO/jGuB4gIj4NtW+kAuBUeBV4Aupvi/nf15mZpZSvzYNmZlZi5wIzMwKzonAzKzgnAjMzArOicDMrOCcCMzMCs6JwMys4P4fItLN3Xo6mxYAAAAASUVORK5CYII=\n", | |
| "text/plain": [ | |
| "<Figure size 432x288 with 1 Axes>" | |
| ] | |
| }, | |
| "metadata": { | |
| "needs_background": "light" | |
| } | |
| } | |
| ] | |
| } | |
| ] | |
| } |
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