{
  "nbformat": 4,
  "nbformat_minor": 0,
  "metadata": {
    "colab": {
      "provenance": []
    },
    "kernelspec": {
      "name": "python3",
      "display_name": "Python 3"
    },
    "language_info": {
      "name": "python"
    }
  },
  "cells": [
    {
      "cell_type": "markdown",
      "source": [
        "# [講義] Matplotlib 実践編\n",
        "データ構造化プログラムでよく利用される、折れ線グラフ、棒グラフ、ヒートマップを題材に、Matplotlibの実践的な機能をご紹介します。\n",
        "\n",
        "# 目次\n",
        "1. MatplotlibのAPI\n",
        "1. 折れ線グラフ\n",
        "1. 棒グラフ\n",
        "1. ヒートマップ\n",
        "1. 出力・保存"
      ],
      "metadata": {
        "id": "Kjg36p71slom"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "# 本講義で使用するファイルのダウンロード\n",
        "\n",
        "本講義で使用するファイルを、下のコードを実行してダウンロードしておきましょう。"
      ],
      "metadata": {
        "id": "lIRPJA2wHcIw"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "! git clone https://github.com/tendo-sms/python_intermediate_2022\n",
        "! ls"
      ],
      "metadata": {
        "id": "YihWpGOXHreB"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "source": [
        "# MatplotlibのAPI\n",
        "ここでは、MatplotlibのAPIについて紹介します。Matplotlibでグラフを描く際の関数・メソッドの呼び出し方法には大きく分けて以下の2種類の方法があります。\n",
        "- Axesインターフェース (オブジェクト指向インタフェース)\n",
        "- pyplotインターフェース\n",
        "\n",
        "これらを混同して使用してしまうと思い通りの動作にならないこともありますので、しっかり使い分けられるようにしましょう。"
      ],
      "metadata": {
        "id": "E6HiKOrUKC4F"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "## Matplotlibの構成要素\n",
        "以降の説明のために、Matplotlibで表示されるオブジェクトの構成要素を説明します。\n",
        "\n",
        "Matplotlibでグラフを描く際の構成要素として、描画領域全体のFigureと個々のプロット領域であるAxesがあります。\n",
        "\n",
        "また、個々の部品(目盛りラベル、グラフ自体、軸のラベルなど)それぞれのことをArtistと呼びます。\n",
        "\n",
        "これらは階層構造になっていて、Figureオブジェクトの中に複数のAxes、Axesオブジェクトの中に複数のArtistオブジェクトを持っています。\n",
        "\n",
        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)"
      ],
      "metadata": {
        "id": "sHZDzNvVwRfN"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "## Axesインターフェース\n",
        "ここではMatplotlibの一つ目のAPIであるAxesインターフェースについて説明します。\n",
        "\n",
        "Axesインターフェースでは、FigureオブジェクトやAxesオブジェクトを明示的に生成して操作します。\n",
        "\n",
        "操作対象が分かりやすくなるため、こちらの方法で図を作成することが推奨されています。\n",
        "\n",
        "後で説明するpyplotインターフェースであっても、裏ではこの方法で実行されています。\n",
        "\n",
        "本講義でも、こちらのインターフェースを使って説明をします。"
      ],
      "metadata": {
        "id": "7RGPyQ8WRhsB"
      }
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "rvNu2g-msi0O"
      },
      "outputs": [],
      "source": [
        "import matplotlib.pyplot as plt\n",
        "\n",
        "# Figureオブジェクトの作成\n",
        "fig = plt.figure()\n",
        "\n",
        "# Axesオブジェクトの作成\n",
        "ax = fig.subplots()\n",
        "\n",
        "# グラフの作成\n",
        "ax.plot([1, 2, 3, 4, 5, 6, 7], [0, 0.1, 0.25, 0.7, 1, 0.8, 0.2])\n",
        "\n",
        "# グラフの表示\n",
        "fig.show()\n",
        "\n",
        "# 終了時はcloseを実行するようにしましょう。環境によってはメモリを圧迫することがあります。\n",
        "# closeを実行してしまうと表示が消えてしまうので、今回はコメントアウトしています。\n",
        "# plt.close(fig)"
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "# pyplotインターフェース\n",
        "pyplotインターフェースは、最後に作成されたFigureやAxesに対して処理を行います。\n",
        "\n",
        "Google ColaboratoryやJupyter Notebookのようなインタラクティブな操作や、簡単な動作確認をしたい時には便利な方法です。\n",
        "\n",
        "一方でどのグラフについて操作しているか分かりづらいため、細かい調整をしたり、複数のグラフを描きたい時には避けた方が良いです。"
      ],
      "metadata": {
        "id": "Qpc2wUMmsIdf"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "import matplotlib.pyplot as plt\n",
        "\n",
        "# グラフの作成\n",
        "plt.plot([1, 2, 3, 4, 5, 6, 7], [0, 0.1, 0.25, 0.7, 1, 0.8, 0.2])\n",
        "\n",
        "# グラフの表示\n",
        "plt.show()\n",
        "\n",
        "# plt.close()"
      ],
      "metadata": {
        "id": "ExSIu2Outtg3"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "source": [
        "# 折れ線グラフのプロット\n",
        "\n",
        "折れ線グラフは「plot」というメソッドを使用します。\n",
        "\n",
        "実際のデータ構造化プログラムでは、スペクトルデータの可視化などによく利用されます。\n",
        "\n",
        "plotメソッドには引数で表示するためのデータを渡しますが、グラフの表示設定も引数で記述出来ます。\n",
        "\n",
        "まずは例を見てみましょう。"
      ],
      "metadata": {
        "id": "wL0Y3qpQuHsw"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "import matplotlib.pyplot as plt\n",
        "\n",
        "fig = plt.figure()\n",
        "ax = fig.subplots()\n",
        "\n",
        "# X軸データ\n",
        "data_x = [1, 2, 3, 4, 5, 6, 7]\n",
        "# Y軸データ\n",
        "data_y = [0, 0.1, 0.25, 0.7, 1, 0.8, 0.2]\n",
        "\n",
        "# グラフの作成\n",
        "ax.plot(data_x, data_y, linestyle=\"--\", linewidth=2.0, color=\"b\", marker=\"s\", label=\"legend1\")\n",
        "\n",
        "ax.legend(labels=[\"legend1\"], loc=\"upper left\", fontsize=12)  # 凡例表示\n",
        "\n",
        "fig.show()\n",
        "\n",
        "# plt.close(fig)"
      ],
      "metadata": {
        "id": "p3xJc6tkuM9e"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "source": [
        "よく使われる引数を紹介します。\n",
        "\n",
        "| 引数(省略形) | 説明 | 例 |\n",
        "| --- | --- | --- |\n",
        "| linestyle(ls) | 線の種類 | \"-\" (直線), \"--\" (破線), \":\" (点線), \"\" (線を表示しない) |\n",
        "| linewidth(lw) | 線の太さ。float形式で設定します | 2.0 |\n",
        "| color(c) | 線の色 | \"b\" (青), \"m\" (マゼンタ), \"r\" (赤), \"#00FF00\"(16進のカラーコードも記述出来ます) |\n",
        "| marker | マーカーの形状 | \".\" (点), \"^\" (▲), \"s\", (■) |\n",
        "| markeredgecolor(mec) | マーカーの枠の色 | \"b\", \"m\", \"r\"など |\n",
        "| markerfacecolor(mfc) | マーカーの中の色 | \"b\", \"m\", \"r\"など |\n",
        "| markersize(ms) | マーカーの大きさ | 10 |\n",
        "| label | プロットの名称。凡例に表示される | \"sample_legend\" |\n",
        "\n",
        "設定する際は、キーワード引数として記述します。\n",
        "\n",
        "色やマーカーの形状などはMatplotlibで豊富に用意されていて、簡単に変更出来ます。公式ドキュメントにも記載がありますので、好みの設定を探してみましょう。\n",
        "\n",
        "線の種類\n",
        "https://matplotlib.org/stable/api/_as_gen/matplotlib.lines.Line2D.html#matplotlib.lines.Line2D.set_linestyle\n",
        "\n",
        "色の設定\n",
        "https://matplotlib.org/stable/gallery/color/named_colors.html\n",
        "\n",
        "マーカーの設定\n",
        "https://matplotlib.org/stable/api/markers_api.html"
      ],
      "metadata": {
        "id": "PY0voyHeWJxp"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "### 凡例\n",
        "凡例は、「plot」メソッドの引数「label」に値を設定するだけでは表示されません。\n",
        "```\n",
        "ax.legend(labels=[\"legend1\"], loc=\"upper left\", fontsize=12)  # 凡例表示\n",
        "```\n",
        "のように、凡例表示のための「legend」メソッドを呼ぶ必要があります。\n",
        "\n",
        "legendメソッドにも引数で設定を記述出来ます。よく使われる引数に以下のようなものがあります。\n",
        "\n",
        "| 引数(省略形) | 説明 | 例 |\n",
        "| --- | --- | --- |\n",
        "| handles | 凡例を表示するArtist。リスト形式で設定 | [line1, line2] |\n",
        "| labels | 凡例を表示するArtistのラベル。リストで設定 | [\"legend1\", \"legend2\"] |\n",
        "| fontsize | フォントサイズ。intもしくは\"small\"などの文字列で設定 | 15, \"small\", \"large\"など |\n",
        "| alignment | 凡例枠内の文字揃え | \"center\", \"left\", \"right\" |\n",
        "| loc | 凡例の表示位置 | \"best\" (重ならないよう自動設定), \"upper left\" (左上), \"lower right\" (右下), \"center\" (中央) など |\n"
      ],
      "metadata": {
        "id": "I6jl6AlaATQF"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "# 軸の最大値、最小値\n",
        "\n",
        "Matplotlibのデフォルトでは、グラフの表示範囲はデータの存在範囲に合わせたものになります。\n",
        "\n",
        "軸の範囲を指定してグラフを描画したい場合は、「set_xlim」、「set_ylim」で範囲指定が出来ます。"
      ],
      "metadata": {
        "id": "wBhoXrLrd7ZH"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "import matplotlib.pyplot as plt\n",
        "\n",
        "fig = plt.figure()\n",
        "ax = fig.subplots()\n",
        "\n",
        "data_x = [1, 2, 3, 4, 5, 6, 7]\n",
        "data_y = [0, 0.1, 0.25, 0.7, 1, 0.8, 0.2]\n",
        "\n",
        "# 表示範囲の指定\n",
        "ax.set_xlim(3, 6)  # いくつ以上、いくつ以下の範囲をプロットするか\n",
        "\n",
        "ax.plot(data_x, data_y, linestyle=\"--\", linewidth=2.0, color=\"b\", marker=\"s\")\n",
        "\n",
        "fig.show()\n",
        "\n",
        "# plt.close(fig)"
      ],
      "metadata": {
        "id": "cfMTOHjld0_n"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "source": [
        "## ログスケール\n",
        "\n",
        "plotメソッドでのグラフ表示の際、軸をログスケール表示に変更することも出来ます。\n",
        "\n",
        "X軸のみ、Y軸のみ、両対数いずれにも対応できます。\n",
        "\n",
        "Axesオブジェクトに対して、set_xscaleもしくはset_yscaleメソッドで \"log\" という値を指定することで設定出来ます。\n",
        "\n",
        "以下は、指数関数を対数軸で表示する例です。\n",
        "実行してみましょう。"
      ],
      "metadata": {
        "id": "qc5VTWDGgtLg"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "import numpy as np\n",
        "import matplotlib.pyplot as plt\n",
        "\n",
        "fig = plt.figure()\n",
        "ax = fig.subplots()\n",
        "\n",
        "# X軸のデータ\n",
        "data_x = np.arange(0.1, 20.0, 0.1)\n",
        "# Y軸のデータ(指数関数)\n",
        "data_y = np.exp(data_x)\n",
        "\n",
        "# 対数軸に設定\n",
        "ax.set_yscale(\"log\")\n",
        "\n",
        "ax.plot(data_x, data_y)\n",
        "fig.show()\n",
        "# plt.close(fig)"
      ],
      "metadata": {
        "id": "Lgg9M0bel74d"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "source": [
        "# グラフの装飾\n",
        "ここからはグラフの軸や凡例など、より詳細な設定について見ていきます。\n",
        "\n",
        "## メモリラベルの表示設定\n",
        "メモリのラベルの表示方法を変更するためによく使われるのが「ticker」と「formatter」です。\n",
        "\n",
        "Matplotlibでは何も設定をしなくても軸のメモリをある程度見やすいように整えてくれますが、細かい設定をしたいこともあります。\n",
        "\n",
        "### ticker\n",
        "軸のメモリについて細かく調整したいときにtickerを使用します。\n",
        "メモリの間隔を設定したり、メモリ表示の最大数を設定したりすることで、グラフの軸を調整出来ます。\n",
        "\n",
        "Axesインターフェースでは、set_major_locatorメソッドなどで設定します。\n",
        "\n",
        "### formatter\n",
        "formatterはメモリラベルの表記フォーマットを設定できます。複数のラベルを同じフォーマットで成形したい時に便利な方法です。\n",
        "\n",
        "set_major_fomatterなどで設定します。\n"
      ],
      "metadata": {
        "id": "8p_Vgid7pX9K"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "下の例では、メモリのラベルは4刻み、メモリの線は2刻みにして、Y軸の表記を10<sup>3</sup>ではなく、1.0e+3というような指数表記にしてみます。"
      ],
      "metadata": {
        "id": "YyWcTqneHoIz"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "import numpy as np\n",
        "import matplotlib.pyplot as plt\n",
        "from matplotlib import ticker\n",
        "\n",
        "fig = plt.figure()\n",
        "ax = fig.subplots()\n",
        "\n",
        "data_x = np.arange(0.1, 20.0, 0.1)\n",
        "data_y = np.exp(data_x)\n",
        "\n",
        "# メジャーロケータ（ラベル付きのメモリ）を4刻みで設定\n",
        "ax.xaxis.set_major_locator(ticker.MultipleLocator(4))\n",
        "\n",
        "# マイナーロケータ（ラベル無しの細かいメモリ）を2刻みで設定\n",
        "ax.xaxis.set_minor_locator(ticker.MultipleLocator(2))\n",
        "\n",
        "# Y軸をログスケールに設定\n",
        "ax.set_yscale(\"log\")\n",
        "\n",
        "# 縦軸の表記を10^3ではなく1.0e+3という指数表記に統一\n",
        "ax.yaxis.set_major_formatter(ticker.StrMethodFormatter(\"{x:.1e}\"))\n",
        "\n",
        "ax.plot(data_x, data_y)\n",
        "fig.show()\n",
        "# plt.close(fig)"
      ],
      "metadata": {
        "id": "QbwwqIWSpXl7"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "source": [
        "formatterでは数値の表記だけでなく、日付表記の変更にもよく利用されます。\n",
        "\n",
        "データはPythonのdatetimeオブジェクトなどの形で渡し、matplotlib.dates.DateFormatterで表記方法を指定します。"
      ],
      "metadata": {
        "id": "2iXP9hcbY5W-"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "import datetime\n",
        "import matplotlib.pyplot as plt\n",
        "from matplotlib.dates import DateFormatter\n",
        "\n",
        "fig = plt.figure()\n",
        "ax = fig.subplots()\n",
        "\n",
        "# X軸データをdatetime形式で用意\n",
        "data_x = [\n",
        "    datetime.datetime(2022, 12, 1, 14, 00),\n",
        "    datetime.datetime(2022, 12, 1, 15, 00),\n",
        "    datetime.datetime(2022, 12, 1, 16, 00),\n",
        "    datetime.datetime(2022, 12, 1, 17, 00)\n",
        "]\n",
        "data_y = [0, 0.5, 1, 0.2]\n",
        "\n",
        "# メモリの表示位置を設定\n",
        "ax.set_xticks(data_x)\n",
        "\n",
        "# メモリの表記を設定(datetimeのstrftimeの形式で設定する)\n",
        "ax.xaxis.set_major_formatter(DateFormatter(\"%Y/%m/%d\\n%H:%M\"))\n",
        "\n",
        "ax.plot(data_x, data_y)\n",
        "fig.show()\n",
        "# plt.close(fig)"
      ],
      "metadata": {
        "id": "Ph_6VWI2ZvbN"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "source": [
        "## グラフのタイトル、軸のラベル、グリッド線\n",
        "グラフにタイトルを付けるには、「set_title」メソッドを使用します。\n",
        "\n",
        "同様に、軸のラベル設定は、「set_xlabel」、「set_ylabel」を使用します。\n",
        "\n",
        "グリッド線は、最近のMatplotlibの最近のバージョンではデフォルトで非表示になっており、表示する場合は「grid」メソッドを使用します。"
      ],
      "metadata": {
        "id": "eU3XwpMcFJO2"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "import matplotlib.pyplot as plt\n",
        "\n",
        "fig = plt.figure()\n",
        "ax = fig.subplots()\n",
        "\n",
        "data_x = [1, 2, 3, 4, 5, 6, 7]\n",
        "data_y = [0, 0.1, 0.25, 0.7, 1, 0.8, 0.2]\n",
        "\n",
        "# タイトルを設定\n",
        "ax.set_title(\"タイトル\")\n",
        "\n",
        "# X軸のラベル設定\n",
        "ax.set_xlabel(\"X軸のラベル\")\n",
        "\n",
        "# Y軸のラベル設定\n",
        "ax.set_ylabel(\"Y軸のラベル\")\n",
        "\n",
        "# グリッド線を表示\n",
        "ax.grid(True)\n",
        "\n",
        "ax.plot(data_x, data_y)\n",
        "fig.show()\n",
        "# plt.close(fig)"
      ],
      "metadata": {
        "id": "V_dFfib5HHc1"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "source": [
        "上の例のようにデフォルト設定のまま日本語のタイトルを付けようとすると文字化けしてしまい、正しく表示されません。\n",
        "\n",
        "これはMatplotlibのデフォルトフォントが日本語に対応していないためです。\n",
        "\n",
        "グラフ内に日本語を表示するには、日本語対応のフォントに変更する必要があります。\n",
        "\n",
        "以下では、Googleによって開発されたフリーフォントである「Noto Sans JP」を使用して日本語を表示します。\n",
        "\n",
        "フォントファイルは講義の最初に必要ファイルとしてダウンロードし、python_intermediate_2022/04_matplotlib/NotoSansJP-Medium.otf に配置してあります。\n",
        "\n",
        "このファイルは以下のページからも取得出来ます。\n",
        "\n",
        "https://fonts.google.com/noto/specimen/Noto+Sans+JP?query=noto+sans+jp"
      ],
      "metadata": {
        "id": "NyK-HUrGHoZM"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "from pathlib import Path\n",
        "import matplotlib.pyplot as plt\n",
        "from matplotlib import font_manager\n",
        "\n",
        "# フォントファイルをMatplotlibに認識させる\n",
        "fp = font_manager.FontProperties(fname=Path.cwd().joinpath(\"python_intermediate_2022\", \"04_matplotlib\", \"NotoSansJP-Medium.otf\"))\n",
        "\n",
        "fig = plt.figure()\n",
        "ax = fig.subplots()\n",
        "\n",
        "# フォントの設定\n",
        "hfont = {\"fontproperties\": fp, \"size\": 15}\n",
        "ax.set_title(\"グラフのタイトル\", **hfont)\n",
        "\n",
        "# X軸のラベル設定\n",
        "ax.set_xlabel(\"X軸のラベル\", **hfont)\n",
        "\n",
        "# Y軸のラベル設定\n",
        "ax.set_ylabel(\"Y軸のラベル\", **hfont)\n",
        "\n",
        "# グリッド線を表示\n",
        "ax.grid()\n",
        "\n",
        "ax.plot([1, 2, 3, 4], [0, 0.5, 1, 0.2])\n",
        "fig.show()\n",
        "\n",
        "# plt.close(fig)"
      ],
      "metadata": {
        "id": "VvN2auOlO3vP"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "source": [
        "今度は日本語が正しく表示されました。今回はフリーフォントをダウンロードしてそれを使用しましたが、そのシステムにインストール済みのフォントをMatplotlibが認識してくれていることもあります。その場合はset_titleメソッドの引数にフォントを指定するだけで日本語が表示出来ます。\n",
        "\n",
        "指定できるフォント一覧は以下のようなコードで確認することが出来ます。"
      ],
      "metadata": {
        "id": "bDcJEcgR20rg"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "import matplotlib.font_manager as fm\n",
        "\n",
        "font_list = [f.name for f in fm.fontManager.ttflist]\n",
        "\n",
        "font_list"
      ],
      "metadata": {
        "id": "LlPJ96L54LwA"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "source": [
        "# 棒グラフ\n",
        "続いて棒グラフについて説明します。棒グラフは「bar」というメソッドを使用します。\n",
        "\n",
        "データ構造化プログラムのスペクトルデータの可視化には、折れ線グラフだけでなく棒グラフもよく使用されます。\n",
        "\n",
        "折れ線グラフと同様に、引数で表示するデータや表示設定を記述します。"
      ],
      "metadata": {
        "id": "kopql3BEuNq6"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "import matplotlib.pyplot as plt\n",
        "\n",
        "fig = plt.figure()\n",
        "ax = fig.subplots()\n",
        "\n",
        "# X軸データ\n",
        "x = [1, 2, 3, 4, 5]\n",
        "\n",
        "# グラフの高さデータ\n",
        "height = [100, 200, 300, 400, 500]\n",
        "\n",
        "# 棒グラフの作成\n",
        "ax.bar(x, height, width=1.0, linewidth=2.0, edgecolor=\"k\", facecolor=\"c\", align=\"edge\")\n",
        "\n",
        "fig.show()\n",
        "# plt.close(fig)"
      ],
      "metadata": {
        "id": "HWuUc2AvuRIr"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "source": [
        "よく使われる引数を紹介します。\n",
        "\n",
        "| 引数(省略形) | 説明 | 例 |\n",
        "| --- | --- | --- |\n",
        "| width | 棒の太さ。floatで設定する。デフォルトは0.8 | 1.0 (隣の棒との間隔を1.0とする相対値で設定する) |\n",
        "| linewidth(lw) | 棒の枠線の太さ。 | 2.0 |\n",
        "| edgecolor(ec) | 棒の枠線の色 | \"b\" (青), \"m\" (マゼンタ), \"r\" (赤) など |\n",
        "| facecolor(fc) | 棒の内部の色 | 同上 |\n",
        "| align | 棒の位置 | \"center\", \"edge\" |\n",
        "| label | プロットの名称。凡例に表示される | \"sample_legend\" |"
      ],
      "metadata": {
        "id": "HT_BqMacLRd6"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "# ログスケール\n",
        "棒グラフでも、折れ線グラフと同様に対数軸設定が出来ます。"
      ],
      "metadata": {
        "id": "4O9gb4A9Rp97"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "import matplotlib.pyplot as plt\n",
        "\n",
        "fig = plt.figure()\n",
        "ax = fig.subplots()\n",
        "\n",
        "x = [1, 2, 3, 4, 5]\n",
        "height = [100, 200, 300, 400, 500]\n",
        "\n",
        "# X軸をログスケールに設定\n",
        "ax.set_xscale(\"log\")\n",
        "\n",
        "# Y軸をログスケールに設定\n",
        "ax.set_yscale(\"log\")\n",
        "\n",
        "ax.bar(x, height, width=1.0, linewidth=2.0, edgecolor=\"k\", facecolor=\"c\", align=\"edge\")\n",
        "\n",
        "fig.show()\n",
        "# plt.close(fig)"
      ],
      "metadata": {
        "id": "ATiQHwSWW2YA"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "source": [
        "# ヒートマップ\n",
        "\n",
        "Matplotlibでヒートマップを作成する場合は、「imshow」メソッドを使用します。\n",
        "\n",
        "また、そのヒートマップに対応するカラーバーの作成には、「colorbar」メソッドを使用します。\n",
        "\n",
        "電子顕微鏡画像などの可視化には、ここで紹介するimshowメソッドが使用されます。\n",
        "\n",
        "まずは例を見てみましょう。"
      ],
      "metadata": {
        "id": "mqJ5gNV4uR9P"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "import matplotlib.pyplot as plt\n",
        "\n",
        "fig = plt.figure()\n",
        "ax = fig.subplots()\n",
        "\n",
        "# ヒートマップの2次元Arrayの作成\n",
        "data = [\n",
        "    [0.1, 0.2, 0.3, 0.4, 0.5], \n",
        "    [1, 1.3, 1.6, 2, 2.3],\n",
        "    [2.5, 2.7, 10, 2.7, 2.5],\n",
        "    [2.3, 2, 1.6, 1.3, 1],\n",
        "    [0.5, 0.4, 0.3, 0.2, 0.1]\n",
        "]\n",
        "\n",
        "# ヒートマップの作成\n",
        "im = ax.imshow(data)\n",
        "\n",
        "# カラーバーの作成\n",
        "fig.colorbar(im)\n",
        "\n",
        "# 目盛りの削除\n",
        "ax.set_axis_off()\n",
        "\n",
        "fig.show()\n",
        "# plt.close(fig)"
      ],
      "metadata": {
        "id": "Y3bQTqZBuWkl"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "source": [
        "このままだと色の変化が分かりづらいですね。\n",
        "\n",
        "ヒートマップは、表示したい数値（今回であれば0.1～10の値）を0～1に規格化し、その値に色を割り当てることで描かれています。\n",
        "\n",
        "その規格化の方法も、色の区切りを独自設定する、ログスケールにする、正負の範囲が対称なカラーバーにするなど、細かく設定出来ます。\n",
        "\n",
        "上で表示したグラフを、色の変化を分かりやすくするためにシンプルなログスケールで規格化し直してみましょう。"
      ],
      "metadata": {
        "id": "1FI9cl0h4u7w"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "import matplotlib.pyplot as plt\n",
        "from matplotlib.colors import LogNorm\n",
        "\n",
        "fig = plt.figure()\n",
        "ax = fig.subplots()\n",
        "\n",
        "data = [\n",
        "    [0.1, 0.2, 0.3, 0.4, 0.5], \n",
        "    [1, 1.3, 1.6, 2, 2.3],\n",
        "    [2.5, 2.7, 10, 2.7, 2.5],\n",
        "    [2.3, 2, 1.6, 1.3, 1],\n",
        "    [0.5, 0.4, 0.3, 0.2, 0.1]\n",
        "    ]\n",
        "\n",
        "# 規格化方法を指定して、ヒートマップを作成\n",
        "im = ax.imshow(data, norm=LogNorm())\n",
        "\n",
        "fig.colorbar(im)\n",
        "\n",
        "ax.set_axis_off()\n",
        "fig.show()\n",
        "# plt.close(fig)"
      ],
      "metadata": {
        "id": "oil4apyy5oc3"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "source": [
        "上の方法でも、値が小さい部分の変化が分かりやすくなりました。\n",
        "\n",
        "また、このデータはほとんどの値が0～3の間に収まっています。\n",
        "\n",
        "もし3以上の値は無視して良ければ、imshowの引数でvmin、vmaxを指定することでカラーバーの最小値、最大値を指定することもできます。\n",
        "\n",
        "この場合、最大値を超える値があることをカラーバーの端の形で表現出来ます。extend引数に \"both\", \"max\" 等を設定することで表示できます。"
      ],
      "metadata": {
        "id": "lXk1OmyN0PPL"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "import matplotlib.pyplot as plt\n",
        "\n",
        "fig = plt.figure()\n",
        "ax = fig.subplots()\n",
        "\n",
        "data = [\n",
        "    [0.1, 0.2, 0.3, 0.4, 0.5], \n",
        "    [1, 1.3, 1.6, 2, 2.3],\n",
        "    [2.5, 2.7, 10, 2.7, 2.5],\n",
        "    [2.3, 2, 1.6, 1.3, 1],\n",
        "    [0.5, 0.4, 0.3, 0.2, 0.1]\n",
        "    ]\n",
        "\n",
        "# vmin、vmaxでカラーバーの最小値、最大値を指定\n",
        "im = ax.imshow(data, vmin = 0, vmax = 3)\n",
        "fig.colorbar(im, extend=\"max\")  # extend=\"max\"で最大値を超える場合があることを表現\n",
        "\n",
        "ax.set_axis_off()\n",
        "fig.show()\n",
        "# plt.close(fig)"
      ],
      "metadata": {
        "id": "YE4RqURu2X1Z"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "source": [
        "上の例では、紺～黄色の変化をするMatplotlibのデフォルトのカラーマップを使用しました。\n",
        "\n",
        "独自のカラーマップを定義して利用することも出来ますし、Matplotlibではカラーマップが豊富に用意されており、簡単に変更出来ます。\n",
        "\n",
        "「jet」というカラーマップに変更するには、以下のように記述します。"
      ],
      "metadata": {
        "id": "9j3Dds-684RD"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "import matplotlib.pyplot as plt\n",
        "from matplotlib.pyplot import cm\n",
        "\n",
        "fig = plt.figure()\n",
        "ax = fig.subplots()\n",
        "\n",
        "data = [\n",
        "    [0.1, 0.2, 0.3, 0.4, 0.5], \n",
        "    [1, 1.3, 1.6, 2, 2.3],\n",
        "    [2.5, 2.7, 10, 2.7, 2.5],\n",
        "    [2.3, 2, 1.6, 1.3, 1],\n",
        "    [0.5, 0.4, 0.3, 0.2, 0.1]\n",
        "    ]\n",
        "\n",
        "im = ax.imshow(data, cmap=cm.jet)  # カラーマップをjetに設定\n",
        "fig.colorbar(im)\n",
        "\n",
        "ax.set_axis_off()\n",
        "fig.show()\n",
        "# plt.close(fig)"
      ],
      "metadata": {
        "id": "P6nu9tkS83mM"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "source": [
        "以下のページにMatplotlibで選べるカラーマップ一覧がまとめられています。\n",
        "\n",
        "表示するデータやその形式によっても、適切なカラーマップは変わるかもしれません。\n",
        "\n",
        "好みのカラーマップを探してみましょう。\n",
        "\n",
        "https://matplotlib.org/stable/tutorials/colors/colormaps.html"
      ],
      "metadata": {
        "id": "AGg5yHYBS7_7"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "# 出力・保存\n",
        "Matplotlibでグラフをファイルとして保存するときは、「savefig」メソッドを使用します。\n",
        "\n",
        "savefigメソッドでは、解像度や出力フォーマットなどを指定できます。"
      ],
      "metadata": {
        "id": "TwpCAZB8ubbt"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "import matplotlib.pyplot as plt\n",
        "\n",
        "fig = plt.figure()\n",
        "ax = fig.subplots()\n",
        "\n",
        "data = [\n",
        "    [0.1, 0.2, 0.3, 0.4, 0.5], \n",
        "    [1, 1.3, 1.6, 2, 2.3],\n",
        "    [2.5, 2.7, 10, 2.7, 2.5],\n",
        "    [2.3, 2, 1.6, 1.3, 1],\n",
        "    [0.5, 0.4, 0.3, 0.2, 0.1]\n",
        "  ]\n",
        "\n",
        "im = ax.imshow(data, vmin = 0, vmax = 3)\n",
        "fig.colorbar(im)\n",
        "\n",
        "# 余白あり\n",
        "fig.savefig(\"loose.png\", dpi=100, format=\"png\")\n",
        "\n",
        "# 余白を削除\n",
        "fig.savefig(\"tight.png\", dpi=100, format=\"png\", bbox_inches=\"tight\")\n",
        "\n",
        "# plt.close(fig)"
      ],
      "metadata": {
        "id": "7HSDH7Lyueab"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "source": [
        "よく使われる引数を紹介します。\n",
        "\n",
        "| 引数(省略形) | 説明 | 例 |\n",
        "| --- | --- | --- |\n",
        "| dpi | 画像の解像度 | 100 |\n",
        "| format | 出力フォーマット | \"png\"、\"jpg\"など |\n",
        "| bbox_inches | 余白の大きさ | \"tight\" |"
      ],
      "metadata": {
        "id": "VCjc_9RXUVix"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "# 演習問題\n",
        "\n",
        "それでは本講義で説明したことを思い出しながら、グラフを作成してみましょう。\n",
        "\n",
        "グラフ作成用のデータは用意してありますので、見本画像のようなグラフを作成し、\"practice.jpg\"という名前のJPEG形式の画像として保存してみてください。\n",
        "\n",
        "## 見本画像\n",
        "![practice.jpg](https://github.com/tendo-sms/python_intermediate_2022/raw/main/04_matplotlib/practice.jpg)"
      ],
      "metadata": {
        "id": "Is3RrVUmVnGA"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "import datetime\n",
        "import matplotlib.pyplot as plt\n",
        "from matplotlib.dates import DateFormatter\n",
        "\n",
        "data_x = [\n",
        "    datetime.datetime(2022, 12, 1, 14, 00),\n",
        "    datetime.datetime(2022, 12, 1, 15, 00),\n",
        "    datetime.datetime(2022, 12, 1, 16, 00),\n",
        "    datetime.datetime(2022, 12, 1, 17, 00)\n",
        "]\n",
        "oresen_data_y = [1, 1.5, 2, 2.2]\n",
        "\n",
        "bou_data_y = [0.2, 0.5, 1, 0.8]\n",
        "\n",
        "\n",
        "####### ここから回答例 #######\n",
        "\n",
        "fp = font_manager.FontProperties(fname=Path.cwd().joinpath(\"python_intermediate_2022\", \"04_matplotlib\", \"NotoSansJP-Medium.otf\"))\n",
        "\n",
        "fig = plt.figure()\n",
        "ax = fig.subplots()\n",
        "\n",
        "ax.set_xticks(data_x)\n",
        "ax.set_xticklabels(ax.get_xticklabels(), rotation=45)\n",
        "\n",
        "hfont = {\"fontproperties\": fp, \"size\": 15}\n",
        "ax.set_title(\"演習問題\", **hfont)\n",
        "\n",
        "ax.set_xlabel(\"X軸のラベル\", **hfont)\n",
        "\n",
        "ax.set_ylabel(\"Y軸のラベル\", **hfont)\n",
        "\n",
        "ax.xaxis.set_major_formatter(DateFormatter(\"%Y/%m/%d %H:%M\"))\n",
        "\n",
        "ax.plot(data_x, oresen_data_y, linestyle=\"-.\", linewidth=2.0, color=\"b\", marker=\"D\", label=\"折れ線\")\n",
        "ax.bar(data_x, bou_data_y, width=datetime.timedelta(hours=1)*0.8, linewidth=2.0, edgecolor=\"k\", facecolor=\"c\", label=\"棒\")\n",
        "\n",
        "ax.legend(prop=fp)\n",
        "\n",
        "ax.grid()\n",
        "\n",
        "fig.show()\n",
        "\n",
        "fig.savefig(\"practice.jpg\", dpi=300, format=\"jpg\")\n",
        "\n",
        "# fig.close()\n"
      ],
      "metadata": {
        "id": "wE3bEGj7dinz"
      },
      "execution_count": null,
      "outputs": []
    }
  ]
}