mpl_colors.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "cbd946ab-7824-47f4-ad69-6c39f7c3d210",
   "metadata": {},
   "source": [
    "# Colores de matplotlib en el módulo mpl_colors\n",
    "\n",
    "Matplotlib permite representar cualquier color a través de su código de color (https://matplotlib.org/stable/tutorials/colors/colors.html)\n",
    "\n",
    "Matplotlib permite trabajar con nombres de colores. Los colores se agrupan en tablas de colores con nombre y en mapas de colores (colormaps). Los colors maps proporcionan generalente transiciones suaves entre varios colores. Los colores en cada colormap se diferencian por su código de color, pero no tienen nombre."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "70483017-3f28-400c-9dd9-bf179117caaa",
   "metadata": {},
   "outputs": [],
   "source": [
    "%load_ext autoreload\n",
    "%autoreload 2"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "de05c4ec-0512-464e-8c9a-e99b153151ce",
   "metadata": {},
   "outputs": [],
   "source": [
    "import matplotlib.colors as mcolors\n",
    "\n",
    "from mpl_colors import MplColors as mplc"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "7845964d-4020-4b51-ab18-d8d8406ad8ac",
   "metadata": {},
   "source": [
    "# Nombres de colores\n",
    "\n",
    "Matplotlib tiene un diccionario con los nombres de colores asociado a un código de color hexadecimal RGB:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "7d8a5950-7f25-4080-9102-e4bcf3c626a2",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Número de colores con nombre en matplotlib: 148\n",
      "Nombres de colores en matplotlib:\n",
      " dict_keys(['aliceblue', 'antiquewhite', 'aqua', 'aquamarine', 'azure', 'beige', 'bisque', 'black', 'blanchedalmond', 'blue', 'blueviolet', 'brown', 'burlywood', 'cadetblue', 'chartreuse', 'chocolate', 'coral', 'cornflowerblue', 'cornsilk', 'crimson', 'cyan', 'darkblue', 'darkcyan', 'darkgoldenrod', 'darkgray', 'darkgreen', 'darkgrey', 'darkkhaki', 'darkmagenta', 'darkolivegreen', 'darkorange', 'darkorchid', 'darkred', 'darksalmon', 'darkseagreen', 'darkslateblue', 'darkslategray', 'darkslategrey', 'darkturquoise', 'darkviolet', 'deeppink', 'deepskyblue', 'dimgray', 'dimgrey', 'dodgerblue', 'firebrick', 'floralwhite', 'forestgreen', 'fuchsia', 'gainsboro', 'ghostwhite', 'gold', 'goldenrod', 'gray', 'green', 'greenyellow', 'grey', 'honeydew', 'hotpink', 'indianred', 'indigo', 'ivory', 'khaki', 'lavender', 'lavenderblush', 'lawngreen', 'lemonchiffon', 'lightblue', 'lightcoral', 'lightcyan', 'lightgoldenrodyellow', 'lightgray', 'lightgreen', 'lightgrey', 'lightpink', 'lightsalmon', 'lightseagreen', 'lightskyblue', 'lightslategray', 'lightslategrey', 'lightsteelblue', 'lightyellow', 'lime', 'limegreen', 'linen', 'magenta', 'maroon', 'mediumaquamarine', 'mediumblue', 'mediumorchid', 'mediumpurple', 'mediumseagreen', 'mediumslateblue', 'mediumspringgreen', 'mediumturquoise', 'mediumvioletred', 'midnightblue', 'mintcream', 'mistyrose', 'moccasin', 'navajowhite', 'navy', 'oldlace', 'olive', 'olivedrab', 'orange', 'orangered', 'orchid', 'palegoldenrod', 'palegreen', 'paleturquoise', 'palevioletred', 'papayawhip', 'peachpuff', 'peru', 'pink', 'plum', 'powderblue', 'purple', 'rebeccapurple', 'red', 'rosybrown', 'royalblue', 'saddlebrown', 'salmon', 'sandybrown', 'seagreen', 'seashell', 'sienna', 'silver', 'skyblue', 'slateblue', 'slategray', 'slategrey', 'snow', 'springgreen', 'steelblue', 'tan', 'teal', 'thistle', 'tomato', 'turquoise', 'violet', 'wheat', 'white', 'whitesmoke', 'yellow', 'yellowgreen'])\n"
     ]
    }
   ],
   "source": [
    "print('Número de colores con nombre en matplotlib:', len(mcolors.cnames))\n",
    "print('Nombres de colores en matplotlib:\\n', mcolors.cnames.keys())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "4eaf9b9e-d6c5-41b0-a498-0a2d59074a53",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 900x50 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Colors displayed by color name\n",
    "mplc.display_all_named_colors()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "8b484550-5665-42a6-b80b-d2ad9f31f5b7",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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oV64cPvvssyLdC33kyBGYzWbVn+Ntei1atMChQ4dw6NAhfPXVV1i0aBGuXr2KyMjIQt+ocj+MhfzidnNzK/BWJltcjm9D6dGjBzw9Pe3Hr/yO6z179tTso02bNqFNmzYICgpS5Y3tHLN3794ixU9UEN6mQqUmNDQUQ4YMwX/+8x9ER0drvs/Ly0Pbtm3x22+/4a233sLDDz8MT09P5OXloWnTprrFia+vr+qzxWKBh4eH5h5ii8WiKjKvXLmCX375Jd/7K20ntOTkZJhMJvj5+am+DwgIKNI6X716FVWqVCmwT3JyMgICAjRFkb+/P0wmU4G3KSQnJ+v+jB8UFGT//k6BgYGavrGxsfD09MSKFSswd+5cGI1GtGzZEpMnT7bf63o3rFu3Dlu3bsWXX36pKaazsrJw48YNeHp6wmw2Y9GiRYiPj8ehQ4fsMT366KNo0aIFqlWrhpkzZyIuLi7fZV29ehXBwcEFxuPstnScVm/bOrMfZs2aheDgYKxZswaTJ0+Gm5sb2rVrh6lTp6J69eoFxu7IlnNnzpxBrVq1dPucPXsWADRFk2Ns169fR15enm7OO7ZduXIFIqK6FeVOYWFhBS6ruBzHp+1WBNsxw3Y7zfDhwzF8+HDdedxZxCqKgv79+2Pz5s0ICAhw+l7x5cuXo3bt2khNTcWaNWswb9489O7dG/Hx8fY+tn1050UCAKhZsyYOHToEAJg/fz4WLFigmb+Pj49qbEZERKBOnTpo1qwZpk+fjkmTJuUb2/0wFvRcvXoVQUFB9luZ8lu2yWRChQoVVO2KoiAgIMC+bNt/HfNX71h/5coVfPHFF4WeK4j+ChbjVKrGjBmDxYsXY9SoUXjwwQdV3x07dgxHjx7F0qVL0a9fP3t7QQ/0FFf58uXh7u6OxYsX5/s9cPskn5OTg+TkZNVB2vbQW2EqVKiAixcvFtjHz88P33zzDUREVZD//vvvyMnJsceS37SXLl3StP/222+q9bDRe7DSZDIhOjoa0dHRuHHjBnbs2IFRo0ahXbt2uHDhwl17u8WxY8eQk5OjeiuEzYIFC7BgwQJs2LAB3bp1w5EjR2A0GvHII4+o+oWFhcHPzw/Hjh0rcFlF3Q/ObMu/Mq3efvD09MT48eMxfvx4XLlyxX6VvEuXLqqHfYsiKioK8+fPx8aNGxETE6PbZ+PGjTCZTGjdunWBsZUrVw6KoujmvGNb+fLloSgK9u/fr/sGFse20npHuW37x8bG6r6tB7hdBNtcunQJQ4cORf369fHjjz9i+PDhmDVrVpGXV7t2bXux3KZNG+Tm5mLhwoVYt26d/Rew1q1bw2Qy4fPPP8fAgQPt07q7u9un3bRpU5GXafs14OjRowX2ux/Ggp4KFSrgyy+/RF5eXr4Fue14ffXqVVVBLiK4fPkyGjdubO8H3M7fSpUq2fvZjvV3Kl++POrWrYt33nlHd5m2f2QQ/RW8TYVKlZ+fH0aOHIl169Zpnly3HZQdT9jz5s0r8Tg6d+6MU6dOwc/PD40aNdL82a4KtWnTBgA0rxdbtWpVkZbToUMHnDx5ssCfdR977DHcvHkTGzduVLUvX77c/n1B0yYlJeG7777TTKsoij3+oipbtiy6d++OoUOH4o8//rBfPb0b+vfvj927d2v+gNsPF+7evRstWrQAcPuEl5uba79iaHPy5EkkJycXeqWvQ4cO2L17t+pWBEd/ZVs+9thj2LVrl73guHNaDw8P3X9wFKRixYro378/evfujRMnTjj9PvB//etfqFOnDt577z3dN/+sWbMG27dvx4svvljorzyenp4IDw/H+vXrkZGRYW9PTU3FF198oerbuXNniAh+/fVX3XHlzK0eJalmzZqoXr06jh49qhtXo0aNUKZMGQC3X+fYu3dvKIqC+Ph4TJo0CR988AHWr19f7OVPmTIF5cqVw9ixY+1vIwkMDMSAAQPs73//q44cOQIA+T4AaXO/jYU7487IyMDSpUsLXDYArFixQtX+6aefIi0tzf697R+gjsf1Tz75RPOGlM6dO+PYsWOoVq2abt6wGKcS4brb1envzvEBTpu0tDQJCgqyP3hke4AzKytLqlWrJiEhIbJq1SrZunWrDB06VGrUqKF5SCi/hz/79esnnp6emlhatWolDz74oP3zzZs3pUGDBhIcHCzTp0+XhIQE2bZtmyxYsEB69OghBw4cEBGR3NxcadmypVitVnn33Xdl+/btEhcXJ2FhYUV6gDMlJUUefPBB8fLykokTJ8r27dvls88+k+joaNm1a5eIiNy6dUvq1q0rZcqUkRkzZkhCQoLExcWJ2WyWjh07qubn+ADn77//LpUqVZKAgACZP3++bNu2TV599VVRFEWGDBlS6L4Quf0AW0xMjKxbt0727t0ry5cvl9DQUAkJCVE9yOfMA5xbtmyRtWvXyuLFiwWA9OjRQ9auXStr166VtLS0AqeFzgOc58+fl7Jly0qlSpXkww8/lF27dsnChQslLCxMPD095fjx4wXO8+LFixIYGCj+/v4yc+ZM2blzp3z66afy0ksvyU8//SQiRd+Wthjv3PfHjx+XMmXKSI0aNWTFihWyZcsW6dOnj+ZhMttDa2vXrtXEGB4eLhMmTJCNGzfK3r17Ze7cueLn5yfNmjWz91m2bJkYjUZZtmxZgesrcvshteDgYPH19ZV33nlHdu3aJfHx8TJkyBAxmUzSqlUr1b4oKEe2b98uBoNBWrRoIRs2bJB169ZJ48aNpXLlyuJ4Ghk4cKB4eHjIm2++KV988YXs2rVLVq5cKS+//LLMmTPH3s9xTN7J2Qc49WJ23Ee7du0Sq9Uqbdu2lVWrVsnevXtlw4YN8u6770r37t3t/UaPHi0Gg0F27Nhhb+vSpYuULVtWTp8+XWA8tgc4HR8MFxGZMmWKAJCPPvrI3paeni5RUVFiMBikd+/esnr1atm3b59s3bpVZs6cKTVr1hQ3Nzf7Q48it48BzZs3l8TERElMTJR9+/bJvHnzJCQkRKxWqxw8eLDAGO+HsaAnOztb2rRpI2azWUaMGCHx8fGyefNmGTt2rP1B3by8PGnXrp2YzWYZN26cJCQkyPTp08XLy0saNGigeqC5b9++oiiKjBgxQrZv3y4zZsyQoKAg8fb2Vh1jf/vtNwkJCZFatWrJnDlzZOfOnbJ582aZPXu2dOrUSS5cuFCk+IkKwmKc7pqCTpTz58/XFOMiIklJSRIVFSVlypSRcuXKSY8ePeT8+fMlXoyL3C7Ix4wZIzVr1hSLxSI+Pj7y8MMPy+uvvy6XL1+297tx44YMGDBAypYtKx4eHhIVFSXHjx8vUjEuInL9+nUZNmyYVKlSRcxms/j7+0unTp1UBWRycrIMHjxYAgMDxWQySUhIiMTGxmrehuFYjIuInDt3Tp555hnx8/MTs9ksNWvWlKlTp6reDlHQvpg+fbpERERI+fLlxWKxSJUqVeSFF17QFEIApFWrVoWury1O2/51/Dtz5kyB0+oV4yIiP//8szz77LMSGhoqVqtVqlSpIr169Sry2wwuXLggAwYMkICAADGbzRIUFCQ9e/aUK1eu2PsUZVvaYnTc9z/88IN06dJFfHx8xGKxSL169WTJkiWqPgUVIDExMdKoUSMpV66cWK1WCQsLk9dff12uXbtm72Mr9hznm59r165JTEyM1KpVS9zc3MTLy0vCw8PlP//5j+aNKQXliIjI559/LnXr1rXnyHvvvWcfh44WL14sTZo0EU9PT3F3d5dq1arJc889J99++629T0HFeL9+/YqUK84U4yIiR48elZ49e4q/v7+YzWYJCAiQyMhImTt3roj87x8djtMlJydLlSpVpHHjxpKZmZlvPAUV47du3ZIqVapI9erVVW9+yc3NleXLl0tUVJSUL19eTCaT+Pj4SHh4uLz11lty8eJF1Xwcx5bRaJQqVapI9+7d5fDhwwVuL5t7fSzk59atWzJ27FipXr26WCwW8fPzk8jISPn6669VfUaOHCkhISFiNpslMDBQXn75Zbl+/bpqXpmZmfLGG2+Iv7+/uLm5SdOmTSUxMVH3GHv16lV59dVXpWrVqmI2m8XX11caNmwoo0ePlps3bxY5fqL8KCL//0g9ERERERGVKt4zTkRERETkIizGiYiIiIhchMU4EREREZGLsBgnIiIiInIRFuNERERERC7CYpyIiIiIyEVMd2OmGRkZyMrKuhuzJiIiIiJyGYvFAjc3txKbX4kX4xkZGXB3dy/p2RIRERERuVxAQADOnDlTYgV5iRfj+V8Rj3H47KnTp6VOW31t03M+6s9BRVkeAE+HZTZ4VdvH+5i2rc632jbzsMKXh1i9wFQq1tBOZ379PU2bIXSDtu3ncarPnnhE00dJzCg0BuPIXzVt7peba9pMdZ7Rzn9mWdVnc8UkTR/D7hPahU57VN2n+XZNF4+XPtfGVX+ops18q716Xis+0y7v/bKaJuPy/dp+DpSU57RtDfpr2kwpgwqdl7UIg9Z0vpt2edNCNW1Go97UB9QffZrq9NHJ0xjHfNPLZS1rx4E6rd6qT8aBVzQ9lOMP6kz3tvpjmxmaHqbXRmjnVU/RtBkmt1X3+TBTO6/kA5o2JbKB+vMsxzEOWKZla+d1MlfbFlP4NjQ9HKFtrP6U6qPh+iZNF+XEn9rpgrS5ZejSTvXZ/Nzv2j7f79S2NdmjXl7105o+Rvdumjbrc9ptan7MYezX1B5rzL+d07Sh3WB1DJUf0/bRYU42a9oMm/PUDY9010743SuaJmXNenXDzg+1fQ5o80/xVx+rDY9Ha/pYLmvzyLhpkqbNlPxvdcPzezR9DIuOa9rwvJf6c7l/a/tYdfIIPpoW05qXVZ+VJk9oJ/OvoTOvAPVHD+2+MWbq7K8Zo7SzGtjfIShvbR+PZO38s/3U8w6sqZ0OettBh+889ed62uMRgnXy1OJwbqiwTNvHa7O2ze8NbZtpuvpzuS3aPnoXQ/3bqD8b12v7GNO0bRa9c5bjtq+k7WLV7gsYHealVNH2MWuP1TBe17YZUhwaqmr7wENn/uUdGn7QmU47BhzbUlJSULlyZWRlZd27xXj+HAPWWwEvnTadQWcpwqz0Gh03mqfOvL10YvDWSW7NMcSqE4PO/B0YDNrpDG7a6Qwe2sQyuKlv+Tdqg4Ji1hYKjoxe2srO5KGNy1RGu20USxl1HzedOE06+8JhOxt19pfZoo3LonOgMTtsZ4NRZ395aeMyWhwTSUsx66yzm/ZRC3NW4QPS6lb4L0Ymi3bfKzpppF+Mq2PVlgmA/rgoQh8dVq8yOq0OxbgxXdOjSHGZtNvY5KmNS/HWzs1oVcel6IwLk86YVowO209nXFjMeZo2s86+MOmMV00fve3nrZ6ZIVcnHzy1MaCMTjFuUG9Di5vOP1x08tvgcJxUPLXjxOiuvZhiNWhjsDiOMTftKcds0Xl0ycMhBr3jsg5zhk5xZ3XYXh7a5SlWnXwwOMRaRru/FHedYtwhTw3e2n1oSdMpxt21x1yz47mgjN55QGe8OuaDTgyw6v3Pt7X9TB7qfajoxADvwo8FRS7G3XTOpY7nHrPO8jy0hZwxW91P/yG5ws/Ttyd2yBG96smi02hx2F5W7TrrHnJ18kFzKPPQuaipd+xxHD5GnelMOvmgW4w7TquzL6w6RbVjHaB3YtMtxnO0bQbHY6DePtQrxh0bipC3+baVLD7ASURERETkIizGiYiIiIhchMU4EREREZGLsBgnIiIiInIRFuNERERERC7CYpyIiIiIyEVYjBMRERERuQiLcSIiIiIiF2ExTkRERETkIizGiYiIiIhchMU4EREREZGLsBgnIiIiInIRFuNERERERC7CYpyIiIiIyEVYjBMRERERuQiLcSIiIiIiF2ExTkRERETkIizGiYiIiIhchMU4EREREZGLsBgnIiIiInIRFuNERERERC7CYpyIiIiIyEVYjBMRERERuQiLcSIiIiIiF2ExTkRERETkIizGiYiIiIhchMU4EREREZGLsBgnIiIiInIRFuNERERERC7CYpyIiIiIyEVYjBMRERERuQiLcSIiIiIiF2ExTkRERETkIizGiYiIiIhcxFR6i8pw+GzU6XNTpy1F25RVyKzzazQ6LDNNZ95GnRhSbmnbzI4NmTox6MzfQV6edrq8DJ3p0tO1bRl5qo+5yNZ0UbK1bRo3czVNOek665Oq3TZKljqFlAxtnIYcnX1xUz2vPJ39lZ2ljSvrlnZfyC319jLk6uyvm1ZNkzHLMZG0lGyddXbY7gCQl6GbhE7LzdLue0UvTfWGj+74caQTp6apaOsiN1N1WhXVJ2Outo+iadFZZo52G5vStHEpKdq5GTLVy1R0xqZJZ0wruertp+iMi9xsbVt2rrbNpDdeHfvobb8U9bwMKTr5kKYzXap2nBvy1NswO0O0fXTy2+CQy0qadpwY89I0bTl52v2T5TjGMnI0fcxZ2n2NdIcYbhYltwFzmubADEOmw/zTdZaXqZMPeQ6xpurk8i1t/ikOeaq3Dy06+8t4SydPHc8FqTrHV71jT6rDqd2kcxCx6p2ftOtjSlfvQ0UnBrjrHQs81R9ztPvGmKmzvzKKcO4x6VxHzNHmiDFbfdzXv/pY+HkaAJDnkCPaVAay9BodtlemzjlZuxkAnXzQnOKt2nEI0clvx01j1JnOqLNfLTrz0pSNOvs+S2e8Gh22jd6Jzayzzkad+Rsc56+3D3X2hWY76+WtXpaox0WKzpj+qxQR0R6h/4I///wTwcHBuFnEgycRERER0f3Cy8sLFy9ehI+PT4nMr8SvjCuKgps3b+LChQvw9vYu6dnT30xKSgoqV67MfKFCMVfIGcwXKirmCjnDli+Kov87b3HctdtUvL29mdRUZMwXKirmCjmD+UJFxVwhV+EDnERERERELsJinIiIiIjIRUq8GLdarYiLi4PVqn17BZEj5gsVFXOFnMF8oaJirpAz7ka+lPjbVIiIiIiIqGh4mwoRERERkYuwGCciIiIichEW40RERERELsJinIiIiIjIRViMExERERG5SLGK8Tlz5qBq1apwc3NDw4YNsX///gL77927Fw0bNoSbmxvCwsIwd+7cYgVL9x9ncmX9+vWIiopChQoV4O3tjWbNmmHbtm2lGC25mrPHFpuvvvoKJpMJ9evXv7sB0j3D2VzJzMzE6NGjERISAqvVimrVqmHx4sWlFC25mrP5snLlStSrVw8eHh4IDAzE888/j+Tk5FKKllxl37596NKlC4KCgqAoCjZu3FjoNCVS44qTVq9eLWazWRYsWCBJSUkybNgw8fT0lHPnzun2P336tHh4eMiwYcMkKSlJFixYIGazWdatW+fsouk+42yuDBs2TCZPniwHDx6UkydPSmxsrJjNZvnuu+9KOXJyBWfzxebGjRsSFhYmbdu2lXr16pVOsORSxcmVrl27SpMmTSQhIUHOnDkj33zzjXz11VelGDW5irP5sn//fjEYDPL+++/L6dOnZf/+/fLggw9Kt27dSjlyKm1btmyR0aNHy6effioAZMOGDQX2L6ka1+liPDw8XAYPHqxqq1WrlsTExOj2HzFihNSqVUvVNmjQIGnatKmzi6b7jLO5oqdOnToyfvz4kg6N7kHFzZdevXrJmDFjJC4ujsX4P4SzuRIfHy8+Pj6SnJxcGuHRPcbZfJk6daqEhYWp2mbNmiXBwcF3LUa69xSlGC+pGtep21SysrLw3//+F23btlW1t23bFl9//bXuNImJiZr+7dq1w7fffovs7GynruLT/aM4ueIoLy8Pqamp8PX1vRsh0j2kuPmyZMkSnDp1CnFxcXc7RLpHFCdXPv/8czRq1AhTpkxBpUqVUKNGDQwfPhy3bt0qjZDJhYqTLxEREbh48SK2bNkCEcGVK1ewbt06dOrUqTRCpvtISdW4JmcWeu3aNeTm5qJixYqq9ooVK+Ly5cu601y+fFm3f05ODq5du4bAwEBnQqD7RHFyxdH06dORlpaGnj173o0Q6R5SnHz5+eefERMTg/3798NkcupQRvex4uTK6dOn8eWXX8LNzQ0bNmzAtWvXMGTIEPzxxx+8b/xvrjj5EhERgZUrV6JXr17IyMhATk4Ounbtig8++KA0Qqb7SEnVuMV6gFNRFNVnEdG0FdZfr53+fpzNFZuPP/4Y48aNw5o1a+Dv73+3wqN7TFHzJTc3F8888wzGjx+PGjVqlFZ4dA9x5tiSl5cHRVGwcuVKhIeHo2PHjpgxYwaWLl3Kq+P/EM7kS1JSEl599VWMHTsW//3vf7F161acOXMGgwcPLo1Q6T5TEjWuU5eTypcvD6PRqPnX5O+//675l4FNQECAbn+TyQQ/Pz9nFk/3keLkis2aNWvwwgsvYO3atXj88cfvZph0j3A2X1JTU/Htt9/i8OHDeOWVVwDcLrhEBCaTCdu3b0dkZGSpxE6lqzjHlsDAQFSqVAk+Pj72ttq1a0NEcPHiRVSvXv2uxkyuU5x8mTRpEpo3b44333wTAFC3bl14enri0UcfxcSJE/mLPtmVVI3r1JVxi8WChg0bIiEhQdWekJCAiIgI3WmaNWum6b99+3Y0atQIZrPZmcXTfaQ4uQLcviLev39/rFq1ivfn/YM4my/e3t744YcfcOTIEfvf4MGDUbNmTRw5cgRNmjQprdCplBXn2NK8eXP89ttvuHnzpr3t5MmTMBgMCA4OvqvxkmsVJ1/S09NhMKjLI6PRCOB/Vz2JgBKscZ163FP+94qgRYsWSVJSkrz22mvi6ekpZ8+eFRGRmJgYefbZZ+39ba99ef311yUpKUkWLVrEVxv+QzibK6tWrRKTySSzZ8+WS5cu2f9u3LjhqlWgUuRsvjji21T+OZzNldTUVAkODpbu3bvLjz/+KHv37pXq1avLiy++6KpVoFLkbL4sWbJETCaTzJkzR06dOiVffvmlNGrUSMLDw121ClRKUlNT5fDhw3L48GEBIDNmzJDDhw/bX4N5t2pcp4txEZHZs2dLSEiIWCwWeeSRR2Tv3r327/r16yetWrVS9d+zZ480aNBALBaLhIaGyocfflicxdJ9yJlcadWqlQDQ/PXr16/0AyeXcPbYcicW4/8szubKTz/9JI8//ri4u7tLcHCwREdHS3p6eilHTa7ibL7MmjVL6tSpI+7u7hIYGCh9+vSRixcvlnLUVNp2795dYB1yt2pcRYS/uRARERERuUKx3qZCRERERER/HYtxIiIiIiIXYTFOREREROQiLMaJiIiIiFyExTgRERERkYuwGCciIiIichEW40RERERELsJinIiIiIjIRViMExERERG5CItxIiIiIiIXYTFOREREROQi/wc5nXI1ggUJEAAAAABJRU5ErkJggg==",
      "text/plain": [
       "<Figure size 900x50 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Colors displayed by hex RGB code\n",
    "mplc.display_all_named_colors(sorted_by_name=False)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "6f2d8b34-27c6-4794-8045-ff8c16149fdb",
   "metadata": {},
   "source": [
    "Para visualizar algunos de los colores con nombre utilizamos la función __display_some_named_colors__. Como parámetro tiene una lista con los colores que queremos visualizar; por defecto se muestran los 3 colores del modelo RGB. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "id": "123e86a3-342b-4b85-ae91-81b9715a90fb",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Selected colors\n",
      "red, #FF0000\n",
      "green, #008000\n",
      "blue, #0000FF\n"
     ]
    },
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "<Figure size 900x50 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "mplc.display_some_named_colors()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "id": "beff356f-0b18-43ad-a043-3a9233ebaeb6",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Selected colors\n",
      "aqua, #00FFFF\n",
      "aquamarine, #7FFFD4\n",
      "azure, #F0FFFF\n"
     ]
    },
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "<Figure size 900x50 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "mplc.display_some_named_colors(['aqua', 'aquamarine', 'azure'])"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "6a781699-e067-4ff0-9d24-4d2cef7fa539",
   "metadata": {},
   "source": [
    "# Tablas de colores con nombres\n",
    "Matplotlib ofrece diccionarios de colores con nombre asociado a su código de color.\n",
    "\n",
    "Las tablas de colores disponibles se muestran con la función __get_color_table_names()__:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "id": "09ab9c52-84af-44ae-9617-2b67990e20e5",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "dict_keys(['base', 'css4', 'tableau', 'xkcd'])"
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "mplc.get_color_table_names()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "de8651c7-e09a-4a7a-a431-31275e61b331",
   "metadata": {},
   "source": [
    "Para ver todos los colores en cada color table utilizamos la función __display_color_tables()__:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "id": "48b9c30c-9fed-4180-9615-19997a77be86",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Number of colors in the color tables\n",
      "Color table base. Number of colors 8\n",
      "Color table css4. Number of colors 148\n",
      "Color table tableau. Number of colors 10\n",
      "Color table xkcd. Number of colors 949\n"
     ]
    },
    {
     "data": {
      "image/png": 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RkfoAJ/LgE0lWrFghnp6eotFoxM7OTt566y2D8CZSN4yLPAhSH330keh0OtFoNOLo6CihoaHy448/GswzNowXFRXJ+PHjxcbGRlQqlTz8HsTmzZuld+/eYmpqKu7u7rJ8+XKJj4+vN4wHBQXJjh07pG/fvqLVasXV1VViY2MNjlVfGK8df/vtt8XJyUk0Go107dpVAgICZNmyZU3WD0BmzJghcXFx4uHhIRqNRry8vCQhIcFg3s8//yzz588XJycnMTMzE19fX9mzZ0+d5/rzzz+XoUOHSrdu3USr1Ur37t1lwoQJcvbsWYP97ty5I7NnzxY3NzfRaDTSpUsX8fPzk4iICCkrK9PPCwkJqfN8NeTmzZsyc+ZM6dmzp5iZmUn37t0lKChIMjMzm1wrIvLjjz/KnDlzxMXFRTQajdjb20tQUJBcvHhRP6ewsFCmT58ujo6OolarRafTSXh4uMELOpG6YVxE5Nq1azJp0iSxtbUVjUYjvXv3lpUrV0p1dbV+TmNhfPXq1RIQECB2dnai1WrFxcVF3nnnnWZ90gwRPbtUIg38dQsiIiIiImpTPGeciIiIiEghDONERERERAphGCciIiIiUgjDOBERERGRQhjGiYiIiIgUwjBORERERKQQdVtsWl5eXu9f6yMiIiIiepJptVqYmZm12n6tHsbLy8vRsaMbgPzW3pqIiIiISFEODg7IyclptUDe6mH8wTvi+QCuA7Bq7e1pobXSFTy17v6f0hU83az37VO6hKfWvmClK3iK8cltM8F8atvM3bt3lS7hqVVSUoIePXqgoqLi8Q3j/2UFhvE20Hq/FaFHsFvbmIWF0hU8tfjMtiE+ufQEsrLi/2hPEl7ASURERESkEIZxIiIiIiKFMIwTERERESmEYZyIiIiISCEM40RERERECmEYJyIiIiJSCMM4EREREZFCGMaJiIiIiBTCME5EREREpBCGcSIiIiIihTCMExEREREphGGciIiIiEghDONERERERAphGCciIiIiUgjDOBERERGRQhjGiYiIiIgUwjBORERERKQQhnEiIiIiIoUwjBMRERERKYRhnIiIiIhIIQzjREREREQKYRgnIiIiIlIIwzgRERERkUIYxomIiIiIFMIwTkRERESkEIZxIiIiIiKFMIwTERERESmEYZyIiIiISCEM40RERERECmEYJyIiIiJSCMM4EREREZFCGMaJiIiIiBTCME5EREREpBCGcSIiIiIihajbbuuSttv6WVaudAFPL3ZsG7t3T+kKnlp8ZtsQn1x6ApWU8H+0ttIWz61KRKQ1N7x79y6cnZ1RVlbWmtsSERERESnO0tISeXl5sLa2bpX9Wv2dcZVKhbKyMly/fh1WVlatvT09ZUpKStCjRw/2CzWJvULGYL9Qc7FXyBi1/aJSqVptzzY7TcXKyopNTc3GfqHmYq+QMdgv1FzsFVIKL+AkIiIiIlIIwzgRERERkUJaPYybmpoiKioKpqamrb01PYXYL9Rc7BUyBvuFmou9QsZoi35p9U9TISIiIiKi5uFpKkRERERECmEYJyIiIiJSCMM4EREREZFCGMaJiIiIiBTCME5EREREpJAWhfG4uDi4ubnBzMwMfn5+yMjIaHR+eno6/Pz8YGZmBnd3d6xfv75FxdKTx5he2bVrF0aMGIGuXbvCysoKgwcPxqFDh9qxWlKasT9bah07dgxqtRr9+/dv2wLpsWFsr/z888+IiIiATqeDqakpPDw8sHnz5naqlpRmbL8kJCSgX79+MDc3h6OjI6ZOnYrCwsJ2qpaUcvToUbzyyivo3r07VCoV9uzZ0+SaVsm4YqTExETRaDSyadMmyc7Oljlz5oiFhYVcu3at3vlXr14Vc3NzmTNnjmRnZ8umTZtEo9HIjh07jD00PWGM7ZU5c+bIihUr5JtvvpFLly5JeHi4aDQaOX36dDtXTkowtl9qFRcXi7u7u4wcOVL69evXPsWSolrSK2PHjpVBgwZJcnKy5OTkyIkTJ+TYsWPtWDUpxdh+ycjIkA4dOsgnn3wiV69elYyMDOnbt6+MGzeunSun9vbVV19JRESE7Ny5UwDI7t27G53fWhnX6DDu7+8v06dPNxjz8vKShQsX1jv/d7/7nXh5eRmMTZs2TX75y18ae2h6whjbK/Xx9vaW6Ojo1i6NHkMt7ZeJEyfK4sWLJSoqimH8GWFsrxw4cECsra2lsLCwPcqjx4yx/bJy5Upxd3c3GFuzZo04Ozu3WY30+GlOGG+tjGvUaSoVFRX49ttvMXLkSIPxkSNH4p///Ge9azIzM+vMHzVqFE6dOoXKykqj3sWnJ0dLeuVRNTU1KC0tRZcuXdqiRHqMtLRftmzZgitXriAqKqqtS6THREt6Ze/evRg4cCBiYmLg5OQET09PzJ8/H/fv32+PkklBLemXgIAA5OXl4auvvoKI4NatW9ixYweCgoLao2R6grRWxlUbc9CCggJUV1ejW7duBuPdunVDfn5+vWvy8/PrnV9VVYWCggI4OjoaUwI9IVrSK49avXo17t27hwkTJrRFifQYaUm//PDDD1i4cCEyMjKgVhv1o4yeYC3platXr+Lrr7+GmZkZdu/ejYKCAoSFhaGoqIjnjT/lWtIvAQEBSEhIwMSJE1FeXo6qqiqMHTsWn376aXuUTE+Q1sq4LbqAU6VSGXwtInXGmppf3zg9fYztlVrbt2/HkiVLkJSUBHt7+7Yqjx4zze2X6upqTJo0CdHR0fD09Gyv8ugxYszPlpqaGqhUKiQkJMDf3x9jxoxBbGwsPvvsM747/owwpl+ys7Mxe/ZsREZG4ttvv8XBgweRk5OD6dOnt0ep9IRpjYxr1NtJdnZ2MDExqfNq8vbt23VeGdRycHCod75arYatra0xh6cnSEt6pVZSUhLeeecd/P3vf8fw4cPbskx6TBjbL6WlpTh16hTOnDmDmTNnAngQuEQEarUahw8fxrBhw9qldmpfLfnZ4ujoCCcnJ1hbW+vH+vTpAxFBXl4eevXq1aY1k3Ja0i/Lly/H888/jwULFgAAfHx8YGFhgRdeeAHLli3jb/RJr7UyrlHvjGu1Wvj5+SE5OdlgPDk5GQEBAfWuGTx4cJ35hw8fxsCBA6HRaIw5PD1BWtIrwIN3xKdMmYJt27bx/LxniLH9YmVlhe+//x5ZWVn62/Tp09G7d29kZWVh0KBB7VU6tbOW/Gx5/vnncePGDZSVlenHLl26hA4dOsDZ2blN6yVltaRffvrpJ3ToYBiPTExMAPz3XU8ioBUzrlGXe8p/PyIoPj5esrOzZe7cuWJhYSG5ubkiIrJw4UKZPHmyfn7tx7588MEHkp2dLfHx8fxow2eEsb2ybds2UavVsnbtWrl586b+VlxcrNRDoHZkbL88ip+m8uwwtldKS0vF2dlZxo8fL+fPn5f09HTp1auXvPvuu0o9BGpHxvbLli1bRK1WS1xcnFy5ckW+/vprGThwoPj7+yv1EKidlJaWypkzZ+TMmTMCQGJjY+XMmTP6j8Fsq4xrdBgXEVm7dq3odDrRarXi6+sr6enp+vtCQkLkpZdeMph/5MgRGTBggGi1WnF1dZV169a15LD0BDKmV1566SUBUOcWEhLS/oWTIoz92fIwhvFni7G9cuHCBRk+fLh07NhRnJ2dZd68efLTTz+1c9WkFGP7Zc2aNeLt7S0dO3YUR0dHefPNNyUvL6+dq6b2lpaW1mgOaauMqxLh71yIiIiIiJTQok9TISIiIiKi/x3DOBERERGRQhjGiYiIiIgUwjBORERERKQQhnEiIiIiIoUwjBMRERERKYRhnIiIiIhIIQzjREREREQKYRgnIiIiIlIIwzgRERERkUIYxomIiIiIFPL/4AoU8r/GtBMAAAAASUVORK5CYII=",
      "text/plain": [
       "<Figure size 900x50 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 900x50 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 900x50 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 900x50 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "mplc.display_color_tables()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "8b91afa5-a24f-4b7d-bb7b-c234a8ac916f",
   "metadata": {},
   "source": [
    "Para ver algunos mejor algunos colores y sus nombres en las color tables de muchos colores podemos utilizar la función __display_colors_in_color_table__, que tiene dos parámetros\n",
    "\n",
    "* ctable_name, nombre de la color table (por defecto 'tableau')\n",
    "* ncolors, número de colores que se muestran (10 por defecto).\n",
    "\n",
    "Para un número de colores dados, los colores son seleccionados para que haya la mayor separación entre ellos en la lista de la tabla de colores."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 45,
   "id": "4c6911a3-816e-4969-9cd2-7200f1f85afb",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Color table css4: number of colors 148. 15 colors are displayed\n",
      "Color codes. Formats: hex RGBA, hex. RGBA\n",
      "aliceblue, #f0f8ff\n",
      "blueviolet, #8a2be2\n",
      "darkblue, #00008b\n",
      "darkorchid, #9932cc\n",
      "dimgray, #696969\n",
      "goldenrod, #daa520\n",
      "lavender, #e6e6fa\n",
      "lightpink, #ffb6c1\n",
      "linen, #faf0e6\n",
      "mediumvioletred, #c71585\n",
      "orange, #ffa500\n",
      "plum, #dda0dd\n",
      "seagreen, #2e8b57\n",
      "tan, #d2b48c\n",
      "yellowgreen, #9acd32\n"
     ]
    },
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "<Figure size 900x50 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "mplc.display_colors_in_color_table(ctable_name='css4', ncolors=15)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "5b008f63-b0e0-44d3-9493-be197bdc1286",
   "metadata": {},
   "source": [
    "# Colormaps\n",
    "\n",
    "A diferencia de las tablas de colores, los mapas de colores (colormaps) son conjuntos de colores sin nombre, lo que permite crear tablas de muchos colores y tonalidades. La mayor parte están diseñadas para conseguir conjuntos de colores con cambios suaves entre ellos. Otras reproducen las tablas de colores. La función __print_colormaps_names__ nos muestra los nombres de los colormaps disponibles y el número de colores en cada colormap."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "id": "a9f1a055-1889-44b9-ab02-9ef72e960054",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Accent: 8 colors, Accent_r: 8 colors, Blues: 256 colors, Blues_r: 256 colors, BrBG: 256 colors\n",
      "BrBG_r: 256 colors, BuGn: 256 colors, BuGn_r: 256 colors, BuPu: 256 colors, BuPu_r: 256 colors\n",
      "CMRmap: 256 colors, CMRmap_r: 256 colors, Dark2: 8 colors, Dark2_r: 8 colors, GnBu: 256 colors\n",
      "GnBu_r: 256 colors, Greens: 256 colors, Greens_r: 256 colors, Greys: 256 colors, Greys_r: 256 colors\n",
      "OrRd: 256 colors, OrRd_r: 256 colors, Oranges: 256 colors, Oranges_r: 256 colors, PRGn: 256 colors\n",
      "PRGn_r: 256 colors, Paired: 12 colors, Paired_r: 12 colors, Pastel1: 9 colors, Pastel1_r: 9 colors\n",
      "Pastel2: 8 colors, Pastel2_r: 8 colors, PiYG: 256 colors, PiYG_r: 256 colors, PuBu: 256 colors\n",
      "PuBuGn: 256 colors, PuBuGn_r: 256 colors, PuBu_r: 256 colors, PuOr: 256 colors, PuOr_r: 256 colors\n",
      "PuRd: 256 colors, PuRd_r: 256 colors, Purples: 256 colors, Purples_r: 256 colors, RdBu: 256 colors\n",
      "RdBu_r: 256 colors, RdGy: 256 colors, RdGy_r: 256 colors, RdPu: 256 colors, RdPu_r: 256 colors\n",
      "RdYlBu: 256 colors, RdYlBu_r: 256 colors, RdYlGn: 256 colors, RdYlGn_r: 256 colors, Reds: 256 colors\n",
      "Reds_r: 256 colors, Set1: 9 colors, Set1_r: 9 colors, Set2: 8 colors, Set2_r: 8 colors\n",
      "Set3: 12 colors, Set3_r: 12 colors, Spectral: 256 colors, Spectral_r: 256 colors, Wistia: 256 colors\n",
      "Wistia_r: 256 colors, YlGn: 256 colors, YlGnBu: 256 colors, YlGnBu_r: 256 colors, YlGn_r: 256 colors\n",
      "YlOrBr: 256 colors, YlOrBr_r: 256 colors, YlOrRd: 256 colors, YlOrRd_r: 256 colors, afmhot: 256 colors\n",
      "afmhot_r: 256 colors, autumn: 256 colors, autumn_r: 256 colors, binary: 256 colors, binary_r: 256 colors\n",
      "bone: 256 colors, bone_r: 256 colors, brg: 256 colors, brg_r: 256 colors, bwr: 256 colors\n",
      "bwr_r: 256 colors, cividis: 256 colors, cividis_r: 256 colors, cool: 256 colors, cool_r: 256 colors\n",
      "coolwarm: 256 colors, coolwarm_r: 256 colors, copper: 256 colors, copper_r: 256 colors, cubehelix: 256 colors\n",
      "cubehelix_r: 256 colors, flag: 256 colors, flag_r: 256 colors, gist_earth: 256 colors, gist_earth_r: 256 colors\n",
      "gist_gray: 256 colors, gist_gray_r: 256 colors, gist_heat: 256 colors, gist_heat_r: 256 colors, gist_ncar: 256 colors\n",
      "gist_ncar_r: 256 colors, gist_rainbow: 256 colors, gist_rainbow_r: 256 colors, gist_stern: 256 colors, gist_stern_r: 256 colors\n",
      "gist_yarg: 256 colors, gist_yarg_r: 256 colors, gnuplot2: 256 colors, gnuplot2_r: 256 colors, gnuplot: 256 colors\n",
      "gnuplot_r: 256 colors, gray: 256 colors, gray_r: 256 colors, hot: 256 colors, hot_r: 256 colors\n",
      "hsv: 256 colors, hsv_r: 256 colors, inferno: 256 colors, inferno_r: 256 colors, jet: 256 colors\n",
      "jet_r: 256 colors, magma: 256 colors, magma_r: 256 colors, nipy_spectral: 256 colors, nipy_spectral_r: 256 colors\n",
      "ocean: 256 colors, ocean_r: 256 colors, pink: 256 colors, pink_r: 256 colors, plasma: 256 colors\n",
      "plasma_r: 256 colors, prism: 256 colors, prism_r: 256 colors, rainbow: 256 colors, rainbow_r: 256 colors\n",
      "seismic: 256 colors, seismic_r: 256 colors, spring: 256 colors, spring_r: 256 colors, summer: 256 colors\n",
      "summer_r: 256 colors, tab10: 10 colors, tab10_r: 10 colors, tab20: 20 colors, tab20_r: 20 colors\n",
      "tab20b: 20 colors, tab20b_r: 20 colors, tab20c: 20 colors, tab20c_r: 20 colors, terrain: 256 colors\n",
      "terrain_r: 256 colors, turbo: 256 colors, turbo_r: 256 colors, twilight: 510 colors, twilight_r: 510 colors\n",
      "twilight_shifted: 510 colors, twilight_shifted_r: 510 colors, viridis: 256 colors, viridis_r: 256 colors, winter: 256 colors\n",
      "winter_r: 256 colors\n"
     ]
    }
   ],
   "source": [
    "mplc.print_colormaps_names()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "400f023a-e64b-4d0a-a436-804e48dad5e5",
   "metadata": {},
   "source": [
    "## Ver los colores en cada colormap\n",
    "\n",
    "Los nombres de los colormaps nos dan una indicación de su contenido, pero lo que nos interesa es ver esos colores. Para esto se utiliza la función __display_colormaps__. Como parámetro es el listado de los colormaps que quieres visualizar. Si no le pasas ningún parámetro, display_colormaps(), se muestran todos los colormaps (el proceso se puede interrumpir a intervalor regulares)."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "id": "8fbca7a0-5fee-40f1-a47a-2fa84ce600a2",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "<Figure size 900x50 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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z81Puanfs2BERERGIiorCw4cPUadOHSQkJGDHjh1YvXo17O3tn3peFy1ahMjISISEhGD8+PGoUaMGrl27hp07d2LNmjUAgPnz5yMiIgKvv/46JkyYAL1ej5iYGJw9exYJCQlFXqjY2dkhOjoab7/9Njp37ozhw4cjOzsbCxYswIMHD/DRRx89NTbg0TfZjh49Gj169EDdunWh1+uxd+9enD59GpMnT37m/kT0ktD046NEVC6dOnVK+vfvLzVq1BC9Xi8mk0mCgoJk5syZ8vPPPyv9LBaLfPzxx+Lv7y+Ojo7i4eEh77zzjly/fl01XmFf+pOZmSmTJk0SX19fcXR0FE9PT4mKipL79++r+vn6+kqnTp2sYix4+sW6detU7XFxcQJAjh8/rmoveOLF7du3lbYtW7ZI48aNxWg0ire3t0ycOFG2b99u9eUvbdq0kYYNG8r+/fulWbNmYjAYxNPTU6ZOnSq5ubnPPJ9Xr16V9u3bi6urqwBQnYuPPvpIatasKQaDQRo0aCCxsbFKrI/D/3/pT0xMjPj5+Ymjo6PUr19f1qxZo+rXv39/AVDkz5UrV1T9f/jhB+natau4ubmJs7OzhIWFyYkTJ6yOoWDcJ/d/UsH5L+onLi5O1d9sNsuYMWOkWrVqotfrJTAwUBISEp55TgscOXJEOnbsKO7u7mIwGMTPz8/qqS2JiYnSrl07MZlM4uTkJCEhIbJlyxZVn6K+9GfTpk3SokULMRqNYjKZJCwsTA4dOqTqU1huiTz6AqYBAwZI/fr1xWQyiYuLiwQGBsrf//73Mv1CIyIq33Qij/3/jYiIrLRt2xZ37tzB2bNntQ6FiIh+Z7hmnIiIiIhIIyzGiYiIiIg0wmUqREREREQa4Z1xIiIiIiKNsBgnIiIiItIIi3EiIiIiIo08ly/9ycrKKvTb+4iIiIiIXmR6vR5Go7HUxiv1YjwrKwsuHl6wpBf+LXZERERERC+qatWq4cqVK6VWkJd6MZ6TkwNL+n14R62EncG5tIe32fzOQVqHoIj8T1OtQ/hVyBCtI1CE3NyhdQgAgGGt+mgdgqJVt39rHYKi3qgRWoegWHq6rtYhKBpHVNU6BMWxdTO0DkHxarsIrUNQVE9upHUIAIBKf3TXOgTF37/drHUIivDwcK1DUKRnlJ/3xOo+Q7UOQdHhp9e0DkEx27uy1iEAADLTzJjw2qvIyckpv8V4ATuDc7koxp1NrlqHoHAz6LQO4Vcmg9YRKOyd7LUOAQDg5Fp6/3L6rVzsy8c5AQA3JyetQ1A46U1ah6AwObtoHYLC6OiodQgKUznKF1dD+cgXt3KUKwZD+XntN5nKx98HAKArPx+hcy1H70V2pvKTu04u5aeeK23lJ/uIiIiIiF4yLMaJiIiIiDTCYpyIiIiISCMsxomIiIiINMJinIiIiIhIIyzGiYiIiIg0wmKciIiIiEgjLMaJiIiIiDTCYpyIiIiISCMsxomIiIiINMJinIiIiIhIIyzGiYiIiIg0wmKciIiIiEgjLMaJiIiIiDTCYpyIiIiISCMsxomIiIiINMJinIiIiIhIIyzGiYiIiIg0wmKciIiIiEgjLMaJiIiIiDTCYpyIiIiISCMsxomIiIiINMJinIiIiIhIIyzGiYiIiIg0wmKciIiIiEgjLMaJiIiIiDTCYpyIiIiISCMsxomIiIiINMJinIiIiIhIIyzGiYiIiIg0wmKciIiIiEgjLMaJiIiIiDTCYpyIiIiISCMsxomIiIiINOLwvAbOz854XkPbJCPdrHUIiofZonUIv0rP1joChSXTonUIAIBMc5bWISjSLOXjnADAw8xMrUNQZOakax2CIj0jTesQFFm5uVqHoEgvR/lizi4f+aLPeG5vtTbLzi4/r/3p6eXj7wMA6Rn5WoegMJej96L89PLzOpeZ5qR1CACAzLTSryt1IlKqFeIvv/wCHx8fpKWVnz8gEREREVFpcHFxQUpKCtzd3UtlvFK/XNfpdEhLS8P169fh5uZW2sPT78zDhw9RvXp15gs9E3OFbMF8oeJirpAtCvJFp9OV2pjP7X9nbm5uTGoqNuYLFRdzhWzBfKHiYq6QVvgBTiIiIiIijbAYJyIiIiLSSKkX4waDAbNmzYLBYCjtoel3iPlCxcVcIVswX6i4mCtki+eRL6X+NBUiIiIiIioeLlMhIiIiItIIi3EiIiIiIo2wGCciIiIi0giLcSIiIiIijbAYJyIiIiLSSImK8ZiYGNSqVQtGoxHBwcFITEx8av8DBw4gODgYRqMRtWvXxpIlS0oULL14bMmVDRs2ICIiApUrV4abmxtatmyJnTt3lmG0pDVbX1sKHDp0CA4ODmjSpMnzDZDKDVtzJTs7G9OmTYOvry8MBgP8/PywYsWKMoqWtGZrvqxZswaNGzeGs7MzPD09MXDgQNy9e7eMoiWtfPPNN4iMjISXlxd0Oh02bdr0zH1KpcYVG33xxRfi6OgosbGxcu7cORk7dqyYTCb58ccfC+1/+fJlcXZ2lrFjx8q5c+ckNjZWHB0d5auvvrJ1anrB2JorY8eOlY8//liOHTsmFy9elClTpoijo6OcPHmyjCMnLdiaLwUePHggtWvXlvbt20vjxo3LJljSVElypUuXLtKiRQvZvXu3XLlyRY4ePSqHDh0qw6hJK7bmS2JiotjZ2cknn3wily9flsTERGnYsKF07dq1jCOnsrZt2zaZNm2arF+/XgDIxo0bn9q/tGpcm4vx5s2by4gRI1Rt9evXl8mTJxfa//3335f69eur2oYPHy4hISG2Tk0vGFtzpTCvvPKKzJkzp7RDo3KopPnSq1cvmT59usyaNYvF+EvC1lzZvn27uLu7y927d8siPCpnbM2XBQsWSO3atVVtn376qfj4+Dy3GKn8KU4xXlo1rk3LVHJycnDixAm0b99e1d6+fXscPny40H2OHDli1b9Dhw749ttvkZuba9NdfHpxlCRXnpSfnw+z2YyKFSs+jxCpHClpvsTFxSE5ORmzZs163iFSOVGSXNm8eTOaNWuG6OhoeHt7w9/fHxMmTEBmZmZZhEwaKkm+hIaGIiUlBdu2bYOI4NatW/jqq6/QqVOnsgiZXiClVeM62DLpnTt3YLFYULVqVVV71apVkZqaWug+qamphfbPy8vDnTt34OnpaUsI9IIoSa486W9/+xvS09PRs2fP5xEilSMlyZdLly5h8uTJSExMhIODTS9l9AIrSa5cvnwZBw8ehNFoxMaNG3Hnzh2MHDkS9+7d47rx37mS5EtoaCjWrFmDXr16ISsrC3l5eejSpQs+++yzsgiZXiClVeOW6AOcOp1O9buIWLU9q39h7fT7Y2uuFEhISMDs2bOxdu1aVKlS5XmFR+VMcfPFYrGgb9++mDNnDvz9/csqPCpHbHltyc/Ph06nw5o1a9C8eXO88cYbWLhwIVauXMm74y8JW/Ll3LlzGDNmDGbOnIkTJ05gx44duHLlCkaMGFEWodILpjRqXJtuJ3l4eMDe3t7qavLnn3+2ujIoUK1atUL7Ozg4oFKlSrZMTy+QkuRKgbVr12Lw4MFYt24dwsPDn2eYVE7Ymi9msxnffvstkpKSMHr0aACPCi4RgYODA3bt2oV27dqVSexUtkry2uLp6Qlvb2+4u7srbQ0aNICIICUlBXXr1n2uMZN2SpIv8+fPR6tWrTBx4kQAQGBgIEwmE1q3bo0PPviA/9EnRWnVuDbdGdfr9QgODsbu3btV7bt370ZoaGih+7Rs2dKq/65du9CsWTM4OjraMj29QEqSK8CjO+IDBgxAfHw81+e9RGzNFzc3N5w5cwanTp1SfkaMGIF69erh1KlTaNGiRVmFTmWsJK8trVq1wo0bN5CWlqa0Xbx4EXZ2dvDx8Xmu8ZK2SpIvGRkZsLNTl0f29vYAfr3rSQSUYo1r08c95ddHBC1fvlzOnTsn48aNE5PJJFevXhURkcmTJ0u/fv2U/gWPfRk/frycO3dOli9fzkcbviRszZX4+HhxcHCQRYsWyc2bN5WfBw8eaHUIVIZszZcn8WkqLw9bc8VsNouPj490795dvvvuOzlw4IDUrVtXhgwZotUhUBmyNV/i4uLEwcFBYmJiJDk5WQ4ePCjNmjWT5s2ba3UIVEbMZrMkJSVJUlKSAJCFCxdKUlKS8hjM51Xj2lyMi4gsWrRIfH19Ra/XS9OmTeXAgQPKtv79+0ubNm1U/ffv3y9BQUGi1+ulZs2asnjx4pJMSy8gW3KlTZs2AsDqp3///mUfOGnC1teWx7EYf7nYmivnz5+X8PBwcXJyEh8fH/nLX/4iGRkZZRw1acXWfPn000/llVdeEScnJ/H09JS3335bUlJSyjhqKmv79u17ah3yvGpcnQj/50JEREREpIUSPU2FiIiIiIh+OxbjREREREQaYTFORERERKQRFuNERERERBphMU5EREREpBEW40REREREGmExTkRERESkERbjREREREQaYTFORERERKQRFuNERERERBphMU5EREREpJH/A+R2tKV6LJf2AAAAAElFTkSuQmCC",
      "text/plain": [
       "<Figure size 900x50 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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MwRPz1tYc1MR6MofyYp+EHJzl48kc1OTDHByV6JXfy9uubH/pbdG5Huvufmdz1IYc3J23snw88drZ5qiuObgSWxU5lN5mDupyUHPeapeDbfsekNskFw8fPqy+zfivAlG2GdfZ/3JyHFOzv/S2NxoOTzaUNWneJyGH2jbvk5BD+bE6h21nY+pjbXOh1FjF2+piqz4H6H5t+Et0yu/lbVe2XxFbRc1YdTpXbZv3Scihts3rjRx0TradjamNLT2Hy2+kKt5ovZGDlJ7Xw6rw1EREREREVBE240REREREGmEzTkRERESkETbjREREREQaYTNORERERKQRNuNERERERBphM05EREREpBE240REREREGmEzTkRERESkETbjREREREQaYTNORERERKQRNuNERERERBphM05EREREpBE240REREREGmEzTkRERESkETbjREREREQaYTNORERERKQRNuNERERERBphM05EREREpBE240REREREGmEzTkRERESkETbjREREREQaYTNORERERKQRNuNERERERBphM05EREREpBE240REREREGmEzTkRERESkETbjREREREQaYTNORERERKQRNuNERERERBphM05EREREpBE240REREREGmEzTkRERESkETbjREREREQaMVbdqe8BAAQl9hHbtrMxNftLb5dASs1Z4mTb2Zi6WCk1R1XnoC+139m2u/t1Tub4rXOV3nZ2/uqQg5pYT+ZQXuyTkIOzfDyZg5p8al4OjtvOxtTGlt4sEeX38rYr2196W0q9Nbr3Llr5fvFmDvqKt93dLzr153J3XmdzeSIHZ3NU1xxcia2KHEpvMwd1Oag5r7s5iN5x29mY2lj75et78DiPN+Migjp16uD+/SaPfy61r7jMdyIi8jBnXS8REXlMnTp1IKWvIPxGHm/GdTod7t+/j59//hmBgYGePj09Ye7du4cmTZqwXqhSrBVSg/VCrmKtkBq2etHpdJUHu6jKblMJDAxkUZPLWC/kKtYKqcF6IVexVkgrfICTiIiIiEgjbMaJiIiIiDTi8WbcbDZj/vz5MJvNnj41PYFYL+Qq1gqpwXohV7FWSI2qqBedePJxUCIiIiIichlvUyEiIiIi0gibcSIiIiIijbAZJyIiIiLSCJtxIiIiIiKNsBknIiIiItKIW8346tWr0bx5c/j6+qJz587IyMioMP7AgQPo3LkzfH19ER4ejrVr17q1WKp51NTKtm3bEB8fjwYNGiAwMBDdunVDenq6F1dLWlP73mJz+PBhGI1GdOjQoWoXSNWG2lr53//+hzlz5sBqtcJsNqNFixZITk720mpJa2rrZePGjWjfvj38/f1hsVgwbtw43L5920urJa0cPHgQgwcPRuPGjaHT6bBjx45Kj/FIjysq/eMf/xAfHx9Zt26dZGdny9SpUyUgIEAuX77sNP7ChQvi7+8vU6dOlezsbFm3bp34+PjI1q1b1U5NNYzaWpk6daosWrRIjh8/Lj/99JPMnj1bfHx85NSpU15eOWlBbb3Y5OXlSXh4uPTr10/at2/vncWSptyplSFDhkjXrl1l7969cvHiRfn222/l8OHDXlw1aUVtvWRkZIher5fly5fLhQsXJCMjQ9q2bSvDhg3z8srJ21JSUmTOnDny1VdfCQDZvn17hfGe6nFVN+NdunSRiRMnKsZat24ts2bNcho/Y8YMad26tWLstddek5iYGLVTUw2jtlaciYyMlMTERE8vjaohd+tlxIgR8u6778r8+fPZjNcSamslNTVVgoKC5Pbt295YHlUzauvlww8/lPDwcMXYihUrJCwsrMrWSNWPK824p3pcVbepPHz4EJmZmejXr59ivF+/fjhy5IjTY44ePeoQ379/f5w8eRJFRUWqruJTzeFOrZRVUlKC/Px81KtXryqWSNWIu/Wyfv16nD9/HvPnz6/qJVI14U6t7Ny5E9HR0Vi8eDFCQ0MRERGBt99+Gw8ePPDGkklD7tRLbGwscnJykJKSAhHB9evXsXXrVgwcONAbS6YaxFM9rlHNpLdu3UJxcTEaNWqkGG/UqBFyc3OdHpObm+s0/tGjR7h16xYsFouaJVAN4U6tlLVkyRIUFBTgT3/6U1UskaoRd+rl3LlzmDVrFjIyMmA0qnoroxrMnVq5cOECDh06BF9fX2zfvh23bt3CpEmTcOfOHd43/oRzp15iY2OxceNGjBgxAoWFhXj06BGGDBmClStXemPJVIN4qsd16wFOnU6n+FlEHMYqi3c2Tk8etbVi88UXX2DBggXYvHkzGjZsWFXLo2rG1XopLi7GyJEjkZiYiIiICG8tj6oRNe8tJSUl0Ol02LhxI7p06YLnnnsOS5cuxYYNG3h1vJZQUy/Z2dmYMmUK5s2bh8zMTKSlpeHixYuYOHGiN5ZKNYwnelxVl5OCg4NhMBgcfpu8ceOGw28GNiEhIU7jjUYj6tevr2Z6qkHcqRWbzZs34+WXX8aWLVvQt2/fqlwmVRNq6yU/Px8nT55EVlYW3njjDQCPGy4RgdFoxJ49e/Dss896Ze3kXe68t1gsFoSGhiIoKMg+1qZNG4gIcnJy0LJlyypdM2nHnXr54IMP0L17d0yfPh0A0K5dOwQEBKBHjx547733+C/6ZOepHlfVlXGTyYTOnTtj7969ivG9e/ciNjbW6THdunVziN+zZw+io6Ph4+OjZnqqQdypFeDxFfGxY8di06ZNvD+vFlFbL4GBgfj+++9x+vRp+9fEiRPRqlUrnD59Gl27dvXW0snL3Hlv6d69O65evYr79+/bx3766Sfo9XqEhYVV6XpJW+7Uyy+//AK9XtkeGQwGAL9e9SQCPNjjqnrcU379iKBPPvlEsrOz5c0335SAgAC5dOmSiIjMmjVLRo0aZY+3fezLtGnTJDs7Wz755BN+tGEtobZWNm3aJEajUVatWiXXrl2zf+Xl5WmVAnmR2nopi5+mUnuorZX8/HwJCwuT4cOHyw8//CAHDhyQli1byiuvvKJVCuRFautl/fr1YjQaZfXq1XL+/Hk5dOiQREdHS5cuXbRKgbwkPz9fsrKyJCsrSwDI0qVLJSsry/4xmFXV46puxkVEVq1aJVarVUwmk3Tq1EkOHDhg3zdmzBiJi4tTxO/fv186duwoJpNJmjVrJmvWrHFnWqqB1NRKXFycAHD4GjNmjPcXTppQ+95SGpvx2kVtrZw9e1b69u0rfn5+EhYWJn/5y1/kl19+8fKqSStq62XFihUSGRkpfn5+YrFY5MUXX5ScnBwvr5q8bd++fRX2IVXV4+pE+G8uRERERERacOvTVIiIiIiI6LdjM05EREREpBE240REREREGmEzTkRERESkETbjREREREQaYTNORERERKQRNuNERERERBphM05EREREpBE240REREREGmEzTkRERESkETbjREREREQa+T+ubgQm4s4HBgAAAABJRU5ErkJggg==",
      "text/plain": [
       "<Figure size 900x50 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 900x50 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 900x50 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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mM6ZOnYrjx48jIyMDGzZswKVLl9C7d2/cvXu30LkTUckwGCcqI7Nnz4aIYNy4cbh//75deXZ2tnYLte7duwOA3Yf/jh49itOnTxd6Kzm1zLbtxx9/jDt37pTLbejUH+r6IFdEtNu/2crMzMQnn3xiyFu/fj1MJhO6dOlS6FiFvZvcs2dPXLt2DYsXL0a7du1QsWJFANZjtG3bNhw9erRULlEBgK5du2L//v3aO7yA9UOLmzdvLnGf6vF70HfLa9asiVGjRmHYsGH48ccfyzSIKuh89O/fH+np6cjNzUVERITdV0hICABof1wpISHB0P6jjz56oEtJHMnOzsamTZvg7++Pxx57zOn2bdu2RWBgoN0dbrZs2YLbt2/jySefLLR9nz59cPbsWbvLRfR69OiB27dvY/v27Yb8devWaeWFtU1JScHx48ft2iqKgm7duhU6P1tVqlTB4MGD8fzzzyMjI6PM/hgV0V8d76ZCVEbat2+P5cuXY+LEiWjTpg1iY2PRrFkzZGdn48SJE1i5ciWaN2+OAQMGICQkBM899xzee+89mEwm9OnTR7ubSt26dTFlypQCx4mOjkbv3r0xa9Ys/P777+jYsaN2N5Xw8HCMHDmyzNcaHR0NDw8PDBs2DDNnzkRWVhaWL1+OmzdvOqzv5+eH2NhY/PLLLwgODsbOnTuxatUqxMbGGq6rdqRFixbYuHEjNm3ahIYNG8LLy0t7x7J79+5QFAV79uzBwoULtTY9e/bU7iNdWsH43Llz8emnn6JHjx6YO3cuvL29sWLFCu3ONCV551V9Z3XlypWoWLEivLy80KBBg2L9tqBt27bo378/wsLCULVqVZw+fRoffvgh2rdvjwoVKjg9l+Jq0aIFtm7diuXLl6NNmzYwmUyIiIjA008/jYSEBPTt2xeTJk1CZGQk3N3dcfnyZRw4cACPP/44nnjiCTRp0gQjRozA4sWL4e7ujp49e+LUqVPaHT5sqUF0UdeNT506FdnZ2ejYsSMCAgJw6dIlvPfeezh58iTWrFkDNzc3re7du3exc+dOANbbFwLWzwTcuHEDPj4+2r3D3dzcEB8fj5EjR2L8+PEYNmwYzp07h5kzZyI6OrrIPx41efJkbNq0CY8//jji4uIQGRmJe/fu4dChQ+jfvz+6deuGZ599FkuXLkVMTAxSU1PRokULHDlyBK+99hr69u1b6P6dMmUK1q1bh379+uHll19GUFAQduzYgWXLliE2NrbAz4roDRgwAM2bN0dERASqV6+OixcvYvHixQgKCrL7Y0lEVEpc+elRor+CkydPSkxMjNSrV088PDzEx8dHwsPDZd68efLbb79p9XJzc+WNN96Q4OBgcXd3F39/fxkxYoRcunTJ0J/t3VRErHfmmDVrlgQFBYm7u7sEBgZKbGys3Lx501AvKChI+vXrZzdH9W4qmzdvNuSvWbNGAMjRo0cN+eodSPR3Evn000+lZcuW4uXlJbVr15YZM2bIrl277O5M0bVrV2nWrJkcPHhQIiIixNPTUwIDA2XOnDmSnZ1d5PFMTU2VXr16ScWKFQWA3bEIDw8XAPLFF19oeb/++qsAED8/P7FYLA7Xolecu6mIiCQlJUnbtm3F09NTAgICZMaMGdpdL27duqXVK+i4Oxpn8eLF0qBBA3FzcxMAsmbNmsIPSJ64uDiJiIiQqlWriqenpzRs2FCmTJkiN27c0OrExMSIj4+PXVtHx8B2vQXdTSUjI0MGDx4sVapUEUVRDP1kZ2fLW2+9pe0LX19fCQ0NlfHjx8u5c+e0en/88YdMmzZNatSoIV5eXtKuXTtJTk62u1uIiPVYOrp7i63Vq1dLZGSkVKtWTcxms1StWlV69+4tn3/+uV1ddW2OvhyNtX79egkLCxMPDw8JCAiQF198UTIzM4uck4jIzZs3ZdKkSVKvXj1xd3eXGjVqSL9+/eTMmTNanfT0dJkwYYIEBgaK2WyWoKAgmT17tmRlZdkdC9vjc/HiRRk+fLj4+fmJu7u7hISEyJtvvim5ubl267U9lyIib7/9tnTo0EH8/f3Fw8ND6tWrJ2PGjJHU1NRirY+InKeI2FyYRkRUhqKionDjxo0i78n8qOrVqxdSU1Pt7iBDRETkCC9TISIqoalTpyI8PBx169ZFRkYGEhISkJiYiNWrV7t6akRE9IhgME5EVEK5ubmYN28e0tLSoCgKmjZtig8//BAjRowotTFEBLm5uYXWcXNzK5O75BARUdnjZSpERA+xtWvXYvTo0YXWOXDggHZXEiIierQwGCcieoilp6cX+cejQkJCtNs4EhHRo4XBOBERERGRi/CP/hARERERuUiZfIAzKyvL4V8cJCIiIiJ6lHl4eMDLy6vU+iv1YDwrKwsVK1RCjmSXdtdERERERC4VEBCACxculFpAXurB+P3795Ej2WhaJRxuihsUKACst9xS/1VEvQWXYlNuTMNBmaK7sia/PvLy8x8rSn5dax2Toa6hrZJfBpigKLZ96coVU36/ipJ3OzGTsR9Fl1Z06bx55RUay7TH+XOy1jFp9aEo+XVNNmldORSTtdzQTjeuSV9XbasuX1+mG0s7HbpyKPkXOtn2o81RX4789Tso049r15d+S+jaKlpbXblaB7p8h3Xz5mTSt9X3bayr2Iyjv5Wc7tTll9n0o9j0pRjqO26rTdPQl2LItz2V+mPjsFx7rBgOhe3/pkLHUbS0ybYcinb41bUZ+oIuDZstpxi3rlovfxxFV67otp9i6MeUtzbjuLrvcsP8FcOc1X7V82vKa6t2pE+r/erbGrey/hirZflrV3Qn2ppdQJmDtP5/KzE+zvs4UP6/eeUiEH1d0dUStZ2athj7EgHEojU0pEXsyiEW5H8syZLXn7WutcxxW+Nji/WxOgeLxdivWKzrMfRl0cpgsUnblUM3joM5FLQ+Q7+wmaMY0hABLBbjObApy0+rebbnJK+dxSYNfV312OraFlRmUeehO126OYihH3Vsm7raNHSPLeo4+cuz7hVdWjcn3XaDqPPR1dUfRv189YdFnzaMo69jU2Y3jqNy3VJsywpKo6i6unLDqbQdF9at6WiNsCmTvGNn0dfLP8xauWEc7bCIdR5aW2s/6nOECPL7zTuPFt2zCmzLdWMZ+gFgETGMq+Zp89I9L+mfpSx5Kdu2+jnbl+n7Ms5Dd0StZYptjr6drkyxpnMlF6fTTuL+/fsPbzCuclPc4GYyW3+ASP4PGJsfT4UG447KdD9+Sx6MKyZDX46CcUPgXmAwrgbXJQnGbcrUx0r+HAsPxk3GtE0wrtgG4/oXAcUOxpXCg3FFKZtg3AT7vvTRR6HBuJJfR5tz4XUfKBjPP+QFlylqnrGvwoJx27IyC8b1aRjLSyMYV/Nt+yo4GFfsgnHj1ix5MG7sq2TBuDZOocG4YjgW+afdcTCu347qyVPLVI7S+v+txPi4yGBc95O61ILx/OBVDZANQXOhwbiurbPBuF3Q7EwwrlurbTBuKW4wLigsGM/vS4x9qW0NwXje8S5uMF5YwF2sYDx/H2iPLcZxnQ3GjWXqOLp0aQbjNumCgnGHwXYhbYsbfNulUURdXXmRwXgh5Q8SjBuC7wcMxg3jllIwLrqxrP0UEYw7LFNzHPUNXW0UHozry5S8cgtKHT/ASURERETkIgzGiYiIiIhchME4EREREZGLMBgnIiIiInIRBuNERERERC7CYJyIiIiIyEUYjBMRERERuQiDcSIiIiIiF2EwTkRERETkIgzGiYiIiIhchME4EREREZGLMBgnIiIiInIRBuNERERERC7CYJyIiIiIyEUYjBMRERERuQiDcSIiIiIiF2EwTkRERETkIgzGiYiIiIhchME4EREREZGLMBgnIiIiInIRBuNERERERC7CYJyIiIiIyEUYjBMRERERuQiDcSIiIiIiF2EwTkRERETkIgzGiYiIiIhchME4EREREZGLMBgnIiIiInIRBuNERERERC7CYJyIiIiIyEUYjBMRERERuQiDcSIiIiIiF2EwTkRERETkIgzGiYiIiIhcxFxWHedKLmABFCgAFED3ryJKXi3FptyYhoMyRff6Ib8+8vLzH+vrWuuY8uuKydhWyS8DTFAUm7705Yopv19FgaJY+zb0o+jSii6NvLS10FimPc6fk7WOSasPRcmvKzZpXTkUk7Xc0E43rklfV22rLl9flte3KT9tGAdK/ss5237Udvq02p82jrFMP65dX/otoWuraG115Wod6PId1s2bk0nfVt+3sa5iM462FhhOXX6ZTT+KTV+Kob7jtto0DX0phnzbU6k/Ng7LtceK4VDY/m8qdBxFS5tsy6Foh19dm6Ev6NKw2XL67aZrlz+OoitXdNtPMfRjylubcVzdd7lh/ophzmq/6vk15bVVO9Kn1X71bY1bWX+M1bL8tSu6E23NLqDMQVr/v5UYH4vociW/XASiryu6WqK2U9MWY18igFi0hoa0iF05xGLNAwBY8vqz1rWWOW5rfGyxPlbnYLEY+xWLdT2GvixaGSw2abty6MZxMIeC1mfoFzZzFEMaIoDFYjwHNmX5aTXP9pzktbPYpKGvqx5bXduCyizqPHSnSzcHMfSjjm1TV5uG7rFFHSd/eda9okvr5qTbbhB1Prq6+sOon6/+sOjThnH0dWzK7MZxVK5bim1ZQWkUVVdXbjiVtuPCujUdrRE2ZZJ37Cz6evmHWSs3jKMdFrHOQ2tr7Ud9jhBBfr9559Gie1aBbbluLEM/ACwihnHVPG1euucl/bOUJS9l21Y/Z/syfV/GeeiOqKEfOGqnP/6KNS9XclHaSj0YFxH4+voi5daJ0u6aiIiIiMilfH19dW80PLhSD8YVRcHt27dx6dIlVKpUqbS7pz+Z33//HXXr1uV+oSJxr5AzuF+ouLhXyBnqftH/dvxBldllKpUqVeKmpmLjfqHi4l4hZ3C/UHFxr5Cr8AOcREREREQuwmCciIiIiMhFSj0Y9/T0xPz58+Hp6VnaXdOfEPcLFRf3CjmD+4WKi3uFnFEW+0WR0vw4KBERERERFRsvUyEiIiIichEG40RERERELsJgnIiIiIjIRRiMExERERG5CINxIiIiIiIXKVEwvmzZMjRo0ABeXl5o06YNkpKSCq1/6NAhtGnTBl5eXmjYsCFWrFhRosnSo8eZvbJ161ZER0ejevXqqFSpEtq3b4/PP/+8HGdLrubsc4vqiy++gNlsRqtWrcp2gvTQcHav/PHHH5g7dy6CgoLg6emJRo0a4YMPPiin2ZKrObtfEhIS0LJlS1SoUAGBgYEYPXo00tPTy2m25CqHDx/GgAEDUKtWLSiKgu3btxfZplRiXHHSxo0bxd3dXVatWiUpKSkyadIk8fHxkYsXLzqs//PPP0uFChVk0qRJkpKSIqtWrRJ3d3fZsmWLs0PTI8bZvTJp0iR544035Ouvv5azZ8/K7Nmzxd3dXY4fP17OMydXcHa/qG7duiUNGzaUXr16ScuWLctnsuRSJdkrAwcOlLZt20piYqJcuHBBvvrqK/niiy/KcdbkKs7ul6SkJDGZTPLuu+/Kzz//LElJSdKsWTMZNGhQOc+cytvOnTtl7ty58vHHHwsA2bZtW6H1SyvGdToYj4yMlAkTJhjyQkNDJS4uzmH9mTNnSmhoqCFv/Pjx0q5dO2eHpkeMs3vFkaZNm8rChQtLe2r0ECrpfnnqqafkpZdekvnz5zMY/4twdq/s2rVLKleuLOnp6eUxPXrIOLtf3nzzTWnYsKEhb8mSJVKnTp0ymyM9fIoTjJdWjOvUZSr379/HN998g169ehnye/Xqhf/9738O2yQnJ9vV7927N44dO4bs7Gyn3sWnR0dJ9ooti8WCzMxMVKtWrSymSA+Rku6XNWvW4Pz585g/f35ZT5EeEiXZK5988gkiIiIQHx+P2rVrIzg4GNOnT8e9e/fKY8rkQiXZLx06dMDly5exc+dOiAiuXbuGLVu2oF+/fuUxZXqElFaMa3Zm0Bs3biA3Nxc1a9Y05NesWRNpaWkO26SlpTmsn5OTgxs3biAwMNCZKdAjoiR7xdbbb7+NO3fuYOjQoWUxRXqIlGS/nDt3DnFxcUhKSoLZ7NRTGT3CSrJXfv75Zxw5cgReXl7Ytm0bbty4gYkTJyIjI4PXjf/JlWS/dOjQAQkJCXjqqaeQlZWFnJwcDBw4EO+99155TJkeIaUV45boA5yKohjSImKXV1R9R/n05+PsXlFt2LABCxYswKZNm1CjRo2ymh49ZIq7X3JzczF8+HAsXLgQwcHB5TU9eog489xisVigKAoSEhIQGRmJvn374p133sHatWv57vhfhDP7JSUlBS+++CLmzZuHb775Brt378aFCxcwYcKE8pgqPWJKI8Z16u0kf39/uLm52b2a/O233+xeGagCAgIc1jebzfDz83NmeHqElGSvqDZt2oQxY8Zg8+bN6NmzZ1lOkx4Szu6XzMxMHDt2DCdOnMALL7wAwBpwiQjMZjP27NmD7t27l8vcqXyV5LklMDAQtWvXRuXKlbW8Jk2aQERw+fJlNG7cuEznTK5Tkv3y+uuvo2PHjpgxYwYAICwsDD4+PujcuTMWLVrE3+iTprRiXKfeGffw8ECbNm2QmJhoyE9MTESHDh0ctmnfvr1d/T179iAiIgLu7u7ODE+PkJLsFcD6jvioUaOwfv16Xp/3F+LsfqlUqRK+//57nDx5UvuaMGECQkJCcPLkSbRt27a8pk7lrCTPLR07dsSVK1dw+/ZtLe/s2bMwmUyoU6dOmc6XXKsk++Xu3bswmYzhkZubG4D8dz2JgFKMcZ36uKfk3yJo9erVkpKSIpMnTxYfHx9JTU0VEZG4uDgZOXKkVl+97cuUKVMkJSVFVq9ezVsb/kU4u1fWr18vZrNZli5dKlevXtW+bt265aolUDlydr/Y4t1U/jqc3SuZmZlSp04dGTx4sPzwww9y6NAhady4sYwdO9ZVS6By5Ox+WbNmjZjNZlm2bJmcP39ejhw5IhERERIZGemqJVA5yczMlBMnTsiJEycEgLzzzjty4sQJ7TaYZRXjOh2Mi4gsXbpUgoKCxMPDQ1q3bi2HDh3SymJiYqRr166G+gcPHpTw8HDx8PCQ+vXry/Lly0syLD2CnNkrXbt2FQB2XzExMeU/cXIJZ59b9BiM/7U4u1dOnz4tPXv2FG9vb6lTp45MnTpV7t69W86zJldxdr8sWbJEmjZtKt7e3hIYGCjPPPOMXL58uZxnTeXtwIEDhcYhZRXjKiL8nQsRERERkSuU6G4qRERERET04BiMExERERG5CINxIiIiIiIXYTBOREREROQiDMaJiIiIiFyEwTgRERERkYswGCciIiIichEG40RERERELsJgnIiIiIjIRRiMExERERG5CINxIiIiIiIX+X8UG2Or1aG61wAAAABJRU5ErkJggg==",
      "text/plain": [
       "<Figure size 900x50 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "mplc.display_colormaps(['tab10', 'tab20', 'brg', 'hsv', 'gist_rainbow', 'twilight_shifted'])"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "2538288c-2dc4-4d20-a9de-e7b5845b25b5",
   "metadata": {},
   "source": [
    "## Extraer colores de un colormap\n",
    "\n",
    "Algunos colormaps tienen muchos colores y queremos verlos con más detalle. Para realizar esta tarea tenemos dos funciones: __display_colors_in_colormap__ y __get_colors_in_colormap__.\n",
    "\n",
    "La función __display_colors_in_colormap__ muestra un número de colores determinado seleccionados de manera que la separación entre colores sea máxima (por ejemplo, si en colormap de 256 colores pedimos 3 colores, devolvera el primero, el último y el del medio). Los parámetros de la esta función son: \n",
    "\n",
    "* El nombre del colormap (por defecto 'hsv')\n",
    "* El número de colores que se van a mostrar (por defecto 10).\n",
    "\n",
    "Si el número de colores que se desean ver excede el de colores en el colormap, habrá puntos con el mismo color. \n",
    "\n",
    "Haz una prueba utilizando:\n",
    "\n",
    "* El colormap 'tab10' con 10 puntos y con 20 puntos; verás que con 20 puntos cada dos puntos tienen el mismo color.\n",
    "* El colormap 'tab10' con 3 puntos y asignado al parámetro correlative los valores Tue y False"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "id": "fa7733a1-e837-403e-94a4-b14d5eb96fab",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Colormap tab10: number of colors 10. 10 colors are displayed\n",
      "Color codes. Formats: RGBA, hex. RGBA\n",
      "(0.12156862745098039, 0.4666666666666667, 0.7058823529411765, 1.0), #1f77b4ff\n",
      "(1.0, 0.4980392156862745, 0.054901960784313725, 1.0), #ff7f0eff\n",
      "(0.17254901960784313, 0.6274509803921569, 0.17254901960784313, 1.0), #2ca02cff\n",
      "(0.8392156862745098, 0.15294117647058825, 0.1568627450980392, 1.0), #d62728ff\n",
      "(0.5803921568627451, 0.403921568627451, 0.7411764705882353, 1.0), #9467bdff\n",
      "(0.5490196078431373, 0.33725490196078434, 0.29411764705882354, 1.0), #8c564bff\n",
      "(0.8901960784313725, 0.4666666666666667, 0.7607843137254902, 1.0), #e377c2ff\n",
      "(0.4980392156862745, 0.4980392156862745, 0.4980392156862745, 1.0), #7f7f7fff\n",
      "(0.7372549019607844, 0.7411764705882353, 0.13333333333333333, 1.0), #bcbd22ff\n",
      "(0.09019607843137255, 0.7450980392156863, 0.8117647058823529, 1.0), #17becfff\n"
     ]
    },
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "<Figure size 900x50 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "mplc.display_colors_in_colormap('tab10', 10)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "a82df66b-9a38-4444-ac53-7d8f4ec6deae",
   "metadata": {},
   "source": [
    "La otra función es __get_colors_in_colormap__. La función tiene 2 parámetros:\n",
    "\n",
    "* cmap_name, nombre del colormap\n",
    "* indexes, una lista de valores enteros que corrresponden a la posición de los colores que queremos extraer del colormap (recordemos que el colormap no tiene nombres de color); es posible extraer un rango consecutivo de índices con la función slice, por ejemplo slice(3:5) extrae los elementos 3, 4 y 5. Recuerda también que el primer elemento tiene índice 0.    "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "id": "b795189e-cad9-4200-b424-c85b4a54d5f5",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Colormap gist_rainbow: number of colors 256.\n",
      "Color codes. Formats: RGBA, hex. RGBA\n",
      "0, #ff0029ff\n",
      "1, #ff0023ff\n",
      "2, #ff001eff\n",
      "3, #ff0019ff\n",
      "4, #ff0013ff\n",
      "5, #ff000eff\n",
      "6, #ff0009ff\n",
      "7, #ff0003ff\n",
      "8, #ff0200ff\n",
      "9, #ff0700ff\n",
      "10, #ff0d00ff\n",
      "11, #ff1200ff\n",
      "12, #ff1800ff\n",
      "13, #ff1d00ff\n",
      "14, #ff2200ff\n",
      "15, #ff2800ff\n",
      "16, #ff2d00ff\n",
      "17, #ff3300ff\n",
      "18, #ff3800ff\n",
      "19, #ff3d00ff\n"
     ]
    },
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "<Figure size 900x50 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "cmap_name = 'gist_rainbow'\n",
    "indexes = [slice(0,20)]\n",
    "\n",
    "mplc.get_colors_in_colormap(cmap_name, indexes)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "c6fd48cb-67e9-4b44-a277-67637b872a20",
   "metadata": {},
   "source": [
    "Podemos observar la gradualidad en los tonos de rojo, que son difícilmente distinguibles a la vista a pesar de corresponder a códigos de color diferentes"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "c936dfef-5c60-48bf-9c64-35d34d67be67",
   "metadata": {},
   "source": [
    "Prueba ahora con el colormap y los colores a extraer que quieras:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 44,
   "id": "b87ba03d-d81f-4ee6-b4c6-858e5d1d1a78",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Colormap hsv: number of colors 256.\n",
      "Color codes. Formats: RGBA, hex. RGBA\n",
      "20, #ff7600ff\n",
      "21, #ff7c00ff\n",
      "22, #ff8200ff\n",
      "23, #ff8800ff\n",
      "24, #ff8e00ff\n",
      "25, #ff9400ff\n",
      "26, #ff9a00ff\n",
      "27, #ff9f00ff\n",
      "28, #ffa500ff\n",
      "29, #ffab00ff\n",
      "30, #ffb100ff\n",
      "31, #ffb700ff\n",
      "32, #ffbd00ff\n",
      "33, #ffc300ff\n",
      "34, #ffc900ff\n",
      "35, #ffcf00ff\n",
      "36, #ffd500ff\n",
      "37, #ffdb00ff\n",
      "38, #ffe000ff\n",
      "39, #ffe600ff\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 900x50 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "cmap_name = 'hsv'\n",
    "indexes = [slice(20,40)]\n",
    "\n",
    "mplc.get_colors_in_colormap(cmap_name, indexes)"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3 (ipykernel)",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.10.12"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}