MixtureModels.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "*c* argument looks like a single numeric RGB or RGBA sequence, which should be avoided as value-mapping will have precedence in case its length matches with *x* & *y*.  Please use the *color* keyword-argument or provide a 2-D array with a single row if you intend to specify the same RGB or RGBA value for all points.\n",
      "*c* argument looks like a single numeric RGB or RGBA sequence, which should be avoided as value-mapping will have precedence in case its length matches with *x* & *y*.  Please use the *color* keyword-argument or provide a 2-D array with a single row if you intend to specify the same RGB or RGBA value for all points.\n",
      "*c* argument looks like a single numeric RGB or RGBA sequence, which should be avoided as value-mapping will have precedence in case its length matches with *x* & *y*.  Please use the *color* keyword-argument or provide a 2-D array with a single row if you intend to specify the same RGB or RGBA value for all points.\n",
      "*c* argument looks like a single numeric RGB or RGBA sequence, which should be avoided as value-mapping will have precedence in case its length matches with *x* & *y*.  Please use the *color* keyword-argument or provide a 2-D array with a single row if you intend to specify the same RGB or RGBA value for all points.\n",
      "*c* argument looks like a single numeric RGB or RGBA sequence, which should be avoided as value-mapping will have precedence in case its length matches with *x* & *y*.  Please use the *color* keyword-argument or provide a 2-D array with a single row if you intend to specify the same RGB or RGBA value for all points.\n",
      "*c* argument looks like a single numeric RGB or RGBA sequence, which should be avoided as value-mapping will have precedence in case its length matches with *x* & *y*.  Please use the *color* keyword-argument or provide a 2-D array with a single row if you intend to specify the same RGB or RGBA value for all points.\n",
      "*c* argument looks like a single numeric RGB or RGBA sequence, which should be avoided as value-mapping will have precedence in case its length matches with *x* & *y*.  Please use the *color* keyword-argument or provide a 2-D array with a single row if you intend to specify the same RGB or RGBA value for all points.\n",
      "*c* argument looks like a single numeric RGB or RGBA sequence, which should be avoided as value-mapping will have precedence in case its length matches with *x* & *y*.  Please use the *color* keyword-argument or provide a 2-D array with a single row if you intend to specify the same RGB or RGBA value for all points.\n",
      "*c* argument looks like a single numeric RGB or RGBA sequence, which should be avoided as value-mapping will have precedence in case its length matches with *x* & *y*.  Please use the *color* keyword-argument or provide a 2-D array with a single row if you intend to specify the same RGB or RGBA value for all points.\n",
      "*c* argument looks like a single numeric RGB or RGBA sequence, which should be avoided as value-mapping will have precedence in case its length matches with *x* & *y*.  Please use the *color* keyword-argument or provide a 2-D array with a single row if you intend to specify the same RGB or RGBA value for all points.\n",
      "*c* argument looks like a single numeric RGB or RGBA sequence, which should be avoided as value-mapping will have precedence in case its length matches with *x* & *y*.  Please use the *color* keyword-argument or provide a 2-D array with a single row if you intend to specify the same RGB or RGBA value for all points.\n",
      "*c* argument looks like a single numeric RGB or RGBA sequence, which should be avoided as value-mapping will have precedence in case its length matches with *x* & *y*.  Please use the *color* keyword-argument or provide a 2-D array with a single row if you intend to specify the same RGB or RGBA value for all points.\n",
      "*c* argument looks like a single numeric RGB or RGBA sequence, which should be avoided as value-mapping will have precedence in case its length matches with *x* & *y*.  Please use the *color* keyword-argument or provide a 2-D array with a single row if you intend to specify the same RGB or RGBA value for all points.\n",
      "*c* argument looks like a single numeric RGB or RGBA sequence, which should be avoided as value-mapping will have precedence in case its length matches with *x* & *y*.  Please use the *color* keyword-argument or provide a 2-D array with a single row if you intend to specify the same RGB or RGBA value for all points.\n",
      "*c* argument looks like a single numeric RGB or RGBA sequence, which should be avoided as value-mapping will have precedence in case its length matches with *x* & *y*.  Please use the *color* keyword-argument or provide a 2-D array with a single row if you intend to specify the same RGB or RGBA value for all points.\n",
      "*c* argument looks like a single numeric RGB or RGBA sequence, which should be avoided as value-mapping will have precedence in case its length matches with *x* & *y*.  Please use the *color* keyword-argument or provide a 2-D array with a single row if you intend to specify the same RGB or RGBA value for all points.\n",
      "*c* argument looks like a single numeric RGB or RGBA sequence, which should be avoided as value-mapping will have precedence in case its length matches with *x* & *y*.  Please use the *color* keyword-argument or provide a 2-D array with a single row if you intend to specify the same RGB or RGBA value for all points.\n",
      "*c* argument looks like a single numeric RGB or RGBA sequence, which should be avoided as value-mapping will have precedence in case its length matches with *x* & *y*.  Please use the *color* keyword-argument or provide a 2-D array with a single row if you intend to specify the same RGB or RGBA value for all points.\n",
      "*c* argument looks like a single numeric RGB or RGBA sequence, which should be avoided as value-mapping will have precedence in case its length matches with *x* & *y*.  Please use the *color* keyword-argument or provide a 2-D array with a single row if you intend to specify the same RGB or RGBA value for all points.\n",
      "*c* argument looks like a single numeric RGB or RGBA sequence, which should be avoided as value-mapping will have precedence in case its length matches with *x* & *y*.  Please use the *color* keyword-argument or provide a 2-D array with a single row if you intend to specify the same RGB or RGBA value for all points.\n",
      "*c* argument looks like a single numeric RGB or RGBA sequence, which should be avoided as value-mapping will have precedence in case its length matches with *x* & *y*.  Please use the *color* keyword-argument or provide a 2-D array with a single row if you intend to specify the same RGB or RGBA value for all points.\n",
      "*c* argument looks like a single numeric RGB or RGBA sequence, which should be avoided as value-mapping will have precedence in case its length matches with *x* & *y*.  Please use the *color* keyword-argument or provide a 2-D array with a single row if you intend to specify the same RGB or RGBA value for all points.\n",
      "*c* argument looks like a single numeric RGB or RGBA sequence, which should be avoided as value-mapping will have precedence in case its length matches with *x* & *y*.  Please use the *color* keyword-argument or provide a 2-D array with a single row if you intend to specify the same RGB or RGBA value for all points.\n",
      "*c* argument looks like a single numeric RGB or RGBA sequence, which should be avoided as value-mapping will have precedence in case its length matches with *x* & *y*.  Please use the *color* keyword-argument or provide a 2-D array with a single row if you intend to specify the same RGB or RGBA value for all points.\n",
      "*c* argument looks like a single numeric RGB or RGBA sequence, which should be avoided as value-mapping will have precedence in case its length matches with *x* & *y*.  Please use the *color* keyword-argument or provide a 2-D array with a single row if you intend to specify the same RGB or RGBA value for all points.\n",
      "*c* argument looks like a single numeric RGB or RGBA sequence, which should be avoided as value-mapping will have precedence in case its length matches with *x* & *y*.  Please use the *color* keyword-argument or provide a 2-D array with a single row if you intend to specify the same RGB or RGBA value for all points.\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "*c* argument looks like a single numeric RGB or RGBA sequence, which should be avoided as value-mapping will have precedence in case its length matches with *x* & *y*.  Please use the *color* keyword-argument or provide a 2-D array with a single row if you intend to specify the same RGB or RGBA value for all points.\n",
      "*c* argument looks like a single numeric RGB or RGBA sequence, which should be avoided as value-mapping will have precedence in case its length matches with *x* & *y*.  Please use the *color* keyword-argument or provide a 2-D array with a single row if you intend to specify the same RGB or RGBA value for all points.\n",
      "*c* argument looks like a single numeric RGB or RGBA sequence, which should be avoided as value-mapping will have precedence in case its length matches with *x* & *y*.  Please use the *color* keyword-argument or provide a 2-D array with a single row if you intend to specify the same RGB or RGBA value for all points.\n",
      "*c* argument looks like a single numeric RGB or RGBA sequence, which should be avoided as value-mapping will have precedence in case its length matches with *x* & *y*.  Please use the *color* keyword-argument or provide a 2-D array with a single row if you intend to specify the same RGB or RGBA value for all points.\n",
      "*c* argument looks like a single numeric RGB or RGBA sequence, which should be avoided as value-mapping will have precedence in case its length matches with *x* & *y*.  Please use the *color* keyword-argument or provide a 2-D array with a single row if you intend to specify the same RGB or RGBA value for all points.\n",
      "*c* argument looks like a single numeric RGB or RGBA sequence, which should be avoided as value-mapping will have precedence in case its length matches with *x* & *y*.  Please use the *color* keyword-argument or provide a 2-D array with a single row if you intend to specify the same RGB or RGBA value for all points.\n",
      "*c* argument looks like a single numeric RGB or RGBA sequence, which should be avoided as value-mapping will have precedence in case its length matches with *x* & *y*.  Please use the *color* keyword-argument or provide a 2-D array with a single row if you intend to specify the same RGB or RGBA value for all points.\n",
      "*c* argument looks like a single numeric RGB or RGBA sequence, which should be avoided as value-mapping will have precedence in case its length matches with *x* & *y*.  Please use the *color* keyword-argument or provide a 2-D array with a single row if you intend to specify the same RGB or RGBA value for all points.\n",
      "*c* argument looks like a single numeric RGB or RGBA sequence, which should be avoided as value-mapping will have precedence in case its length matches with *x* & *y*.  Please use the *color* keyword-argument or provide a 2-D array with a single row if you intend to specify the same RGB or RGBA value for all points.\n",
      "*c* argument looks like a single numeric RGB or RGBA sequence, which should be avoided as value-mapping will have precedence in case its length matches with *x* & *y*.  Please use the *color* keyword-argument or provide a 2-D array with a single row if you intend to specify the same RGB or RGBA value for all points.\n",
      "*c* argument looks like a single numeric RGB or RGBA sequence, which should be avoided as value-mapping will have precedence in case its length matches with *x* & *y*.  Please use the *color* keyword-argument or provide a 2-D array with a single row if you intend to specify the same RGB or RGBA value for all points.\n",
      "*c* argument looks like a single numeric RGB or RGBA sequence, which should be avoided as value-mapping will have precedence in case its length matches with *x* & *y*.  Please use the *color* keyword-argument or provide a 2-D array with a single row if you intend to specify the same RGB or RGBA value for all points.\n",
      "*c* argument looks like a single numeric RGB or RGBA sequence, which should be avoided as value-mapping will have precedence in case its length matches with *x* & *y*.  Please use the *color* keyword-argument or provide a 2-D array with a single row if you intend to specify the same RGB or RGBA value for all points.\n",
      "*c* argument looks like a single numeric RGB or RGBA sequence, which should be avoided as value-mapping will have precedence in case its length matches with *x* & *y*.  Please use the *color* keyword-argument or provide a 2-D array with a single row if you intend to specify the same RGB or RGBA value for all points.\n",
      "*c* argument looks like a single numeric RGB or RGBA sequence, which should be avoided as value-mapping will have precedence in case its length matches with *x* & *y*.  Please use the *color* keyword-argument or provide a 2-D array with a single row if you intend to specify the same RGB or RGBA value for all points.\n",
      "*c* argument looks like a single numeric RGB or RGBA sequence, which should be avoided as value-mapping will have precedence in case its length matches with *x* & *y*.  Please use the *color* keyword-argument or provide a 2-D array with a single row if you intend to specify the same RGB or RGBA value for all points.\n",
      "*c* argument looks like a single numeric RGB or RGBA sequence, which should be avoided as value-mapping will have precedence in case its length matches with *x* & *y*.  Please use the *color* keyword-argument or provide a 2-D array with a single row if you intend to specify the same RGB or RGBA value for all points.\n",
      "*c* argument looks like a single numeric RGB or RGBA sequence, which should be avoided as value-mapping will have precedence in case its length matches with *x* & *y*.  Please use the *color* keyword-argument or provide a 2-D array with a single row if you intend to specify the same RGB or RGBA value for all points.\n",
      "*c* argument looks like a single numeric RGB or RGBA sequence, which should be avoided as value-mapping will have precedence in case its length matches with *x* & *y*.  Please use the *color* keyword-argument or provide a 2-D array with a single row if you intend to specify the same RGB or RGBA value for all points.\n",
      "*c* argument looks like a single numeric RGB or RGBA sequence, which should be avoided as value-mapping will have precedence in case its length matches with *x* & *y*.  Please use the *color* keyword-argument or provide a 2-D array with a single row if you intend to specify the same RGB or RGBA value for all points.\n",
      "*c* argument looks like a single numeric RGB or RGBA sequence, which should be avoided as value-mapping will have precedence in case its length matches with *x* & *y*.  Please use the *color* keyword-argument or provide a 2-D array with a single row if you intend to specify the same RGB or RGBA value for all points.\n",
      "*c* argument looks like a single numeric RGB or RGBA sequence, which should be avoided as value-mapping will have precedence in case its length matches with *x* & *y*.  Please use the *color* keyword-argument or provide a 2-D array with a single row if you intend to specify the same RGB or RGBA value for all points.\n",
      "*c* argument looks like a single numeric RGB or RGBA sequence, which should be avoided as value-mapping will have precedence in case its length matches with *x* & *y*.  Please use the *color* keyword-argument or provide a 2-D array with a single row if you intend to specify the same RGB or RGBA value for all points.\n",
      "*c* argument looks like a single numeric RGB or RGBA sequence, which should be avoided as value-mapping will have precedence in case its length matches with *x* & *y*.  Please use the *color* keyword-argument or provide a 2-D array with a single row if you intend to specify the same RGB or RGBA value for all points.\n",
      "*c* argument looks like a single numeric RGB or RGBA sequence, which should be avoided as value-mapping will have precedence in case its length matches with *x* & *y*.  Please use the *color* keyword-argument or provide a 2-D array with a single row if you intend to specify the same RGB or RGBA value for all points.\n",
      "*c* argument looks like a single numeric RGB or RGBA sequence, which should be avoided as value-mapping will have precedence in case its length matches with *x* & *y*.  Please use the *color* keyword-argument or provide a 2-D array with a single row if you intend to specify the same RGB or RGBA value for all points.\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "*c* argument looks like a single numeric RGB or RGBA sequence, which should be avoided as value-mapping will have precedence in case its length matches with *x* & *y*.  Please use the *color* keyword-argument or provide a 2-D array with a single row if you intend to specify the same RGB or RGBA value for all points.\n",
      "*c* argument looks like a single numeric RGB or RGBA sequence, which should be avoided as value-mapping will have precedence in case its length matches with *x* & *y*.  Please use the *color* keyword-argument or provide a 2-D array with a single row if you intend to specify the same RGB or RGBA value for all points.\n",
      "*c* argument looks like a single numeric RGB or RGBA sequence, which should be avoided as value-mapping will have precedence in case its length matches with *x* & *y*.  Please use the *color* keyword-argument or provide a 2-D array with a single row if you intend to specify the same RGB or RGBA value for all points.\n",
      "*c* argument looks like a single numeric RGB or RGBA sequence, which should be avoided as value-mapping will have precedence in case its length matches with *x* & *y*.  Please use the *color* keyword-argument or provide a 2-D array with a single row if you intend to specify the same RGB or RGBA value for all points.\n",
      "*c* argument looks like a single numeric RGB or RGBA sequence, which should be avoided as value-mapping will have precedence in case its length matches with *x* & *y*.  Please use the *color* keyword-argument or provide a 2-D array with a single row if you intend to specify the same RGB or RGBA value for all points.\n",
      "*c* argument looks like a single numeric RGB or RGBA sequence, which should be avoided as value-mapping will have precedence in case its length matches with *x* & *y*.  Please use the *color* keyword-argument or provide a 2-D array with a single row if you intend to specify the same RGB or RGBA value for all points.\n",
      "*c* argument looks like a single numeric RGB or RGBA sequence, which should be avoided as value-mapping will have precedence in case its length matches with *x* & *y*.  Please use the *color* keyword-argument or provide a 2-D array with a single row if you intend to specify the same RGB or RGBA value for all points.\n",
      "*c* argument looks like a single numeric RGB or RGBA sequence, which should be avoided as value-mapping will have precedence in case its length matches with *x* & *y*.  Please use the *color* keyword-argument or provide a 2-D array with a single row if you intend to specify the same RGB or RGBA value for all points.\n"
     ]
    },
    {
     "data": {
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\n",
      "text/plain": [
       "<Figure size 720x720 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "*c* argument looks like a single numeric RGB or RGBA sequence, which should be avoided as value-mapping will have precedence in case its length matches with *x* & *y*.  Please use the *color* keyword-argument or provide a 2-D array with a single row if you intend to specify the same RGB or RGBA value for all points.\n",
      "*c* argument looks like a single numeric RGB or RGBA sequence, which should be avoided as value-mapping will have precedence in case its length matches with *x* & *y*.  Please use the *color* keyword-argument or provide a 2-D array with a single row if you intend to specify the same RGB or RGBA value for all points.\n",
      "*c* argument looks like a single numeric RGB or RGBA sequence, which should be avoided as value-mapping will have precedence in case its length matches with *x* & *y*.  Please use the *color* keyword-argument or provide a 2-D array with a single row if you intend to specify the same RGB or RGBA value for all points.\n",
      "*c* argument looks like a single numeric RGB or RGBA sequence, which should be avoided as value-mapping will have precedence in case its length matches with *x* & *y*.  Please use the *color* keyword-argument or provide a 2-D array with a single row if you intend to specify the same RGB or RGBA value for all points.\n",
      "*c* argument looks like a single numeric RGB or RGBA sequence, which should be avoided as value-mapping will have precedence in case its length matches with *x* & *y*.  Please use the *color* keyword-argument or provide a 2-D array with a single row if you intend to specify the same RGB or RGBA value for all points.\n",
      "*c* argument looks like a single numeric RGB or RGBA sequence, which should be avoided as value-mapping will have precedence in case its length matches with *x* & *y*.  Please use the *color* keyword-argument or provide a 2-D array with a single row if you intend to specify the same RGB or RGBA value for all points.\n",
      "*c* argument looks like a single numeric RGB or RGBA sequence, which should be avoided as value-mapping will have precedence in case its length matches with *x* & *y*.  Please use the *color* keyword-argument or provide a 2-D array with a single row if you intend to specify the same RGB or RGBA value for all points.\n",
      "*c* argument looks like a single numeric RGB or RGBA sequence, which should be avoided as value-mapping will have precedence in case its length matches with *x* & *y*.  Please use the *color* keyword-argument or provide a 2-D array with a single row if you intend to specify the same RGB or RGBA value for all points.\n",
      "*c* argument looks like a single numeric RGB or RGBA sequence, which should be avoided as value-mapping will have precedence in case its length matches with *x* & *y*.  Please use the *color* keyword-argument or provide a 2-D array with a single row if you intend to specify the same RGB or RGBA value for all points.\n",
      "*c* argument looks like a single numeric RGB or RGBA sequence, which should be avoided as value-mapping will have precedence in case its length matches with *x* & *y*.  Please use the *color* keyword-argument or provide a 2-D array with a single row if you intend to specify the same RGB or RGBA value for all points.\n",
      "*c* argument looks like a single numeric RGB or RGBA sequence, which should be avoided as value-mapping will have precedence in case its length matches with *x* & *y*.  Please use the *color* keyword-argument or provide a 2-D array with a single row if you intend to specify the same RGB or RGBA value for all points.\n",
      "*c* argument looks like a single numeric RGB or RGBA sequence, which should be avoided as value-mapping will have precedence in case its length matches with *x* & *y*.  Please use the *color* keyword-argument or provide a 2-D array with a single row if you intend to specify the same RGB or RGBA value for all points.\n",
      "*c* argument looks like a single numeric RGB or RGBA sequence, which should be avoided as value-mapping will have precedence in case its length matches with *x* & *y*.  Please use the *color* keyword-argument or provide a 2-D array with a single row if you intend to specify the same RGB or RGBA value for all points.\n",
      "*c* argument looks like a single numeric RGB or RGBA sequence, which should be avoided as value-mapping will have precedence in case its length matches with *x* & *y*.  Please use the *color* keyword-argument or provide a 2-D array with a single row if you intend to specify the same RGB or RGBA value for all points.\n",
      "*c* argument looks like a single numeric RGB or RGBA sequence, which should be avoided as value-mapping will have precedence in case its length matches with *x* & *y*.  Please use the *color* keyword-argument or provide a 2-D array with a single row if you intend to specify the same RGB or RGBA value for all points.\n",
      "*c* argument looks like a single numeric RGB or RGBA sequence, which should be avoided as value-mapping will have precedence in case its length matches with *x* & *y*.  Please use the *color* keyword-argument or provide a 2-D array with a single row if you intend to specify the same RGB or RGBA value for all points.\n",
      "*c* argument looks like a single numeric RGB or RGBA sequence, which should be avoided as value-mapping will have precedence in case its length matches with *x* & *y*.  Please use the *color* keyword-argument or provide a 2-D array with a single row if you intend to specify the same RGB or RGBA value for all points.\n",
      "*c* argument looks like a single numeric RGB or RGBA sequence, which should be avoided as value-mapping will have precedence in case its length matches with *x* & *y*.  Please use the *color* keyword-argument or provide a 2-D array with a single row if you intend to specify the same RGB or RGBA value for all points.\n",
      "*c* argument looks like a single numeric RGB or RGBA sequence, which should be avoided as value-mapping will have precedence in case its length matches with *x* & *y*.  Please use the *color* keyword-argument or provide a 2-D array with a single row if you intend to specify the same RGB or RGBA value for all points.\n",
      "*c* argument looks like a single numeric RGB or RGBA sequence, which should be avoided as value-mapping will have precedence in case its length matches with *x* & *y*.  Please use the *color* keyword-argument or provide a 2-D array with a single row if you intend to specify the same RGB or RGBA value for all points.\n",
      "*c* argument looks like a single numeric RGB or RGBA sequence, which should be avoided as value-mapping will have precedence in case its length matches with *x* & *y*.  Please use the *color* keyword-argument or provide a 2-D array with a single row if you intend to specify the same RGB or RGBA value for all points.\n",
      "*c* argument looks like a single numeric RGB or RGBA sequence, which should be avoided as value-mapping will have precedence in case its length matches with *x* & *y*.  Please use the *color* keyword-argument or provide a 2-D array with a single row if you intend to specify the same RGB or RGBA value for all points.\n",
      "*c* argument looks like a single numeric RGB or RGBA sequence, which should be avoided as value-mapping will have precedence in case its length matches with *x* & *y*.  Please use the *color* keyword-argument or provide a 2-D array with a single row if you intend to specify the same RGB or RGBA value for all points.\n",
      "*c* argument looks like a single numeric RGB or RGBA sequence, which should be avoided as value-mapping will have precedence in case its length matches with *x* & *y*.  Please use the *color* keyword-argument or provide a 2-D array with a single row if you intend to specify the same RGB or RGBA value for all points.\n",
      "*c* argument looks like a single numeric RGB or RGBA sequence, which should be avoided as value-mapping will have precedence in case its length matches with *x* & *y*.  Please use the *color* keyword-argument or provide a 2-D array with a single row if you intend to specify the same RGB or RGBA value for all points.\n",
      "*c* argument looks like a single numeric RGB or RGBA sequence, which should be avoided as value-mapping will have precedence in case its length matches with *x* & *y*.  Please use the *color* keyword-argument or provide a 2-D array with a single row if you intend to specify the same RGB or RGBA value for all points.\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "*c* argument looks like a single numeric RGB or RGBA sequence, which should be avoided as value-mapping will have precedence in case its length matches with *x* & *y*.  Please use the *color* keyword-argument or provide a 2-D array with a single row if you intend to specify the same RGB or RGBA value for all points.\n",
      "*c* argument looks like a single numeric RGB or RGBA sequence, which should be avoided as value-mapping will have precedence in case its length matches with *x* & *y*.  Please use the *color* keyword-argument or provide a 2-D array with a single row if you intend to specify the same RGB or RGBA value for all points.\n",
      "*c* argument looks like a single numeric RGB or RGBA sequence, which should be avoided as value-mapping will have precedence in case its length matches with *x* & *y*.  Please use the *color* keyword-argument or provide a 2-D array with a single row if you intend to specify the same RGB or RGBA value for all points.\n",
      "*c* argument looks like a single numeric RGB or RGBA sequence, which should be avoided as value-mapping will have precedence in case its length matches with *x* & *y*.  Please use the *color* keyword-argument or provide a 2-D array with a single row if you intend to specify the same RGB or RGBA value for all points.\n",
      "*c* argument looks like a single numeric RGB or RGBA sequence, which should be avoided as value-mapping will have precedence in case its length matches with *x* & *y*.  Please use the *color* keyword-argument or provide a 2-D array with a single row if you intend to specify the same RGB or RGBA value for all points.\n",
      "*c* argument looks like a single numeric RGB or RGBA sequence, which should be avoided as value-mapping will have precedence in case its length matches with *x* & *y*.  Please use the *color* keyword-argument or provide a 2-D array with a single row if you intend to specify the same RGB or RGBA value for all points.\n",
      "*c* argument looks like a single numeric RGB or RGBA sequence, which should be avoided as value-mapping will have precedence in case its length matches with *x* & *y*.  Please use the *color* keyword-argument or provide a 2-D array with a single row if you intend to specify the same RGB or RGBA value for all points.\n",
      "*c* argument looks like a single numeric RGB or RGBA sequence, which should be avoided as value-mapping will have precedence in case its length matches with *x* & *y*.  Please use the *color* keyword-argument or provide a 2-D array with a single row if you intend to specify the same RGB or RGBA value for all points.\n",
      "*c* argument looks like a single numeric RGB or RGBA sequence, which should be avoided as value-mapping will have precedence in case its length matches with *x* & *y*.  Please use the *color* keyword-argument or provide a 2-D array with a single row if you intend to specify the same RGB or RGBA value for all points.\n",
      "*c* argument looks like a single numeric RGB or RGBA sequence, which should be avoided as value-mapping will have precedence in case its length matches with *x* & *y*.  Please use the *color* keyword-argument or provide a 2-D array with a single row if you intend to specify the same RGB or RGBA value for all points.\n",
      "*c* argument looks like a single numeric RGB or RGBA sequence, which should be avoided as value-mapping will have precedence in case its length matches with *x* & *y*.  Please use the *color* keyword-argument or provide a 2-D array with a single row if you intend to specify the same RGB or RGBA value for all points.\n",
      "*c* argument looks like a single numeric RGB or RGBA sequence, which should be avoided as value-mapping will have precedence in case its length matches with *x* & *y*.  Please use the *color* keyword-argument or provide a 2-D array with a single row if you intend to specify the same RGB or RGBA value for all points.\n",
      "*c* argument looks like a single numeric RGB or RGBA sequence, which should be avoided as value-mapping will have precedence in case its length matches with *x* & *y*.  Please use the *color* keyword-argument or provide a 2-D array with a single row if you intend to specify the same RGB or RGBA value for all points.\n",
      "*c* argument looks like a single numeric RGB or RGBA sequence, which should be avoided as value-mapping will have precedence in case its length matches with *x* & *y*.  Please use the *color* keyword-argument or provide a 2-D array with a single row if you intend to specify the same RGB or RGBA value for all points.\n",
      "*c* argument looks like a single numeric RGB or RGBA sequence, which should be avoided as value-mapping will have precedence in case its length matches with *x* & *y*.  Please use the *color* keyword-argument or provide a 2-D array with a single row if you intend to specify the same RGB or RGBA value for all points.\n",
      "*c* argument looks like a single numeric RGB or RGBA sequence, which should be avoided as value-mapping will have precedence in case its length matches with *x* & *y*.  Please use the *color* keyword-argument or provide a 2-D array with a single row if you intend to specify the same RGB or RGBA value for all points.\n",
      "*c* argument looks like a single numeric RGB or RGBA sequence, which should be avoided as value-mapping will have precedence in case its length matches with *x* & *y*.  Please use the *color* keyword-argument or provide a 2-D array with a single row if you intend to specify the same RGB or RGBA value for all points.\n",
      "*c* argument looks like a single numeric RGB or RGBA sequence, which should be avoided as value-mapping will have precedence in case its length matches with *x* & *y*.  Please use the *color* keyword-argument or provide a 2-D array with a single row if you intend to specify the same RGB or RGBA value for all points.\n",
      "*c* argument looks like a single numeric RGB or RGBA sequence, which should be avoided as value-mapping will have precedence in case its length matches with *x* & *y*.  Please use the *color* keyword-argument or provide a 2-D array with a single row if you intend to specify the same RGB or RGBA value for all points.\n",
      "*c* argument looks like a single numeric RGB or RGBA sequence, which should be avoided as value-mapping will have precedence in case its length matches with *x* & *y*.  Please use the *color* keyword-argument or provide a 2-D array with a single row if you intend to specify the same RGB or RGBA value for all points.\n",
      "*c* argument looks like a single numeric RGB or RGBA sequence, which should be avoided as value-mapping will have precedence in case its length matches with *x* & *y*.  Please use the *color* keyword-argument or provide a 2-D array with a single row if you intend to specify the same RGB or RGBA value for all points.\n",
      "*c* argument looks like a single numeric RGB or RGBA sequence, which should be avoided as value-mapping will have precedence in case its length matches with *x* & *y*.  Please use the *color* keyword-argument or provide a 2-D array with a single row if you intend to specify the same RGB or RGBA value for all points.\n",
      "*c* argument looks like a single numeric RGB or RGBA sequence, which should be avoided as value-mapping will have precedence in case its length matches with *x* & *y*.  Please use the *color* keyword-argument or provide a 2-D array with a single row if you intend to specify the same RGB or RGBA value for all points.\n",
      "*c* argument looks like a single numeric RGB or RGBA sequence, which should be avoided as value-mapping will have precedence in case its length matches with *x* & *y*.  Please use the *color* keyword-argument or provide a 2-D array with a single row if you intend to specify the same RGB or RGBA value for all points.\n",
      "*c* argument looks like a single numeric RGB or RGBA sequence, which should be avoided as value-mapping will have precedence in case its length matches with *x* & *y*.  Please use the *color* keyword-argument or provide a 2-D array with a single row if you intend to specify the same RGB or RGBA value for all points.\n",
      "*c* argument looks like a single numeric RGB or RGBA sequence, which should be avoided as value-mapping will have precedence in case its length matches with *x* & *y*.  Please use the *color* keyword-argument or provide a 2-D array with a single row if you intend to specify the same RGB or RGBA value for all points.\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "*c* argument looks like a single numeric RGB or RGBA sequence, which should be avoided as value-mapping will have precedence in case its length matches with *x* & *y*.  Please use the *color* keyword-argument or provide a 2-D array with a single row if you intend to specify the same RGB or RGBA value for all points.\n",
      "*c* argument looks like a single numeric RGB or RGBA sequence, which should be avoided as value-mapping will have precedence in case its length matches with *x* & *y*.  Please use the *color* keyword-argument or provide a 2-D array with a single row if you intend to specify the same RGB or RGBA value for all points.\n",
      "*c* argument looks like a single numeric RGB or RGBA sequence, which should be avoided as value-mapping will have precedence in case its length matches with *x* & *y*.  Please use the *color* keyword-argument or provide a 2-D array with a single row if you intend to specify the same RGB or RGBA value for all points.\n",
      "*c* argument looks like a single numeric RGB or RGBA sequence, which should be avoided as value-mapping will have precedence in case its length matches with *x* & *y*.  Please use the *color* keyword-argument or provide a 2-D array with a single row if you intend to specify the same RGB or RGBA value for all points.\n",
      "*c* argument looks like a single numeric RGB or RGBA sequence, which should be avoided as value-mapping will have precedence in case its length matches with *x* & *y*.  Please use the *color* keyword-argument or provide a 2-D array with a single row if you intend to specify the same RGB or RGBA value for all points.\n",
      "*c* argument looks like a single numeric RGB or RGBA sequence, which should be avoided as value-mapping will have precedence in case its length matches with *x* & *y*.  Please use the *color* keyword-argument or provide a 2-D array with a single row if you intend to specify the same RGB or RGBA value for all points.\n",
      "*c* argument looks like a single numeric RGB or RGBA sequence, which should be avoided as value-mapping will have precedence in case its length matches with *x* & *y*.  Please use the *color* keyword-argument or provide a 2-D array with a single row if you intend to specify the same RGB or RGBA value for all points.\n",
      "*c* argument looks like a single numeric RGB or RGBA sequence, which should be avoided as value-mapping will have precedence in case its length matches with *x* & *y*.  Please use the *color* keyword-argument or provide a 2-D array with a single row if you intend to specify the same RGB or RGBA value for all points.\n"
     ]
    },
    {
     "data": {
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\n",
      "text/plain": [
       "<Figure size 720x720 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "*c* argument looks like a single numeric RGB or RGBA sequence, which should be avoided as value-mapping will have precedence in case its length matches with *x* & *y*.  Please use the *color* keyword-argument or provide a 2-D array with a single row if you intend to specify the same RGB or RGBA value for all points.\n",
      "*c* argument looks like a single numeric RGB or RGBA sequence, which should be avoided as value-mapping will have precedence in case its length matches with *x* & *y*.  Please use the *color* keyword-argument or provide a 2-D array with a single row if you intend to specify the same RGB or RGBA value for all points.\n",
      "*c* argument looks like a single numeric RGB or RGBA sequence, which should be avoided as value-mapping will have precedence in case its length matches with *x* & *y*.  Please use the *color* keyword-argument or provide a 2-D array with a single row if you intend to specify the same RGB or RGBA value for all points.\n",
      "*c* argument looks like a single numeric RGB or RGBA sequence, which should be avoided as value-mapping will have precedence in case its length matches with *x* & *y*.  Please use the *color* keyword-argument or provide a 2-D array with a single row if you intend to specify the same RGB or RGBA value for all points.\n",
      "*c* argument looks like a single numeric RGB or RGBA sequence, which should be avoided as value-mapping will have precedence in case its length matches with *x* & *y*.  Please use the *color* keyword-argument or provide a 2-D array with a single row if you intend to specify the same RGB or RGBA value for all points.\n",
      "*c* argument looks like a single numeric RGB or RGBA sequence, which should be avoided as value-mapping will have precedence in case its length matches with *x* & *y*.  Please use the *color* keyword-argument or provide a 2-D array with a single row if you intend to specify the same RGB or RGBA value for all points.\n",
      "*c* argument looks like a single numeric RGB or RGBA sequence, which should be avoided as value-mapping will have precedence in case its length matches with *x* & *y*.  Please use the *color* keyword-argument or provide a 2-D array with a single row if you intend to specify the same RGB or RGBA value for all points.\n",
      "*c* argument looks like a single numeric RGB or RGBA sequence, which should be avoided as value-mapping will have precedence in case its length matches with *x* & *y*.  Please use the *color* keyword-argument or provide a 2-D array with a single row if you intend to specify the same RGB or RGBA value for all points.\n",
      "*c* argument looks like a single numeric RGB or RGBA sequence, which should be avoided as value-mapping will have precedence in case its length matches with *x* & *y*.  Please use the *color* keyword-argument or provide a 2-D array with a single row if you intend to specify the same RGB or RGBA value for all points.\n",
      "*c* argument looks like a single numeric RGB or RGBA sequence, which should be avoided as value-mapping will have precedence in case its length matches with *x* & *y*.  Please use the *color* keyword-argument or provide a 2-D array with a single row if you intend to specify the same RGB or RGBA value for all points.\n",
      "*c* argument looks like a single numeric RGB or RGBA sequence, which should be avoided as value-mapping will have precedence in case its length matches with *x* & *y*.  Please use the *color* keyword-argument or provide a 2-D array with a single row if you intend to specify the same RGB or RGBA value for all points.\n",
      "*c* argument looks like a single numeric RGB or RGBA sequence, which should be avoided as value-mapping will have precedence in case its length matches with *x* & *y*.  Please use the *color* keyword-argument or provide a 2-D array with a single row if you intend to specify the same RGB or RGBA value for all points.\n",
      "*c* argument looks like a single numeric RGB or RGBA sequence, which should be avoided as value-mapping will have precedence in case its length matches with *x* & *y*.  Please use the *color* keyword-argument or provide a 2-D array with a single row if you intend to specify the same RGB or RGBA value for all points.\n",
      "*c* argument looks like a single numeric RGB or RGBA sequence, which should be avoided as value-mapping will have precedence in case its length matches with *x* & *y*.  Please use the *color* keyword-argument or provide a 2-D array with a single row if you intend to specify the same RGB or RGBA value for all points.\n",
      "*c* argument looks like a single numeric RGB or RGBA sequence, which should be avoided as value-mapping will have precedence in case its length matches with *x* & *y*.  Please use the *color* keyword-argument or provide a 2-D array with a single row if you intend to specify the same RGB or RGBA value for all points.\n",
      "*c* argument looks like a single numeric RGB or RGBA sequence, which should be avoided as value-mapping will have precedence in case its length matches with *x* & *y*.  Please use the *color* keyword-argument or provide a 2-D array with a single row if you intend to specify the same RGB or RGBA value for all points.\n",
      "*c* argument looks like a single numeric RGB or RGBA sequence, which should be avoided as value-mapping will have precedence in case its length matches with *x* & *y*.  Please use the *color* keyword-argument or provide a 2-D array with a single row if you intend to specify the same RGB or RGBA value for all points.\n",
      "*c* argument looks like a single numeric RGB or RGBA sequence, which should be avoided as value-mapping will have precedence in case its length matches with *x* & *y*.  Please use the *color* keyword-argument or provide a 2-D array with a single row if you intend to specify the same RGB or RGBA value for all points.\n",
      "*c* argument looks like a single numeric RGB or RGBA sequence, which should be avoided as value-mapping will have precedence in case its length matches with *x* & *y*.  Please use the *color* keyword-argument or provide a 2-D array with a single row if you intend to specify the same RGB or RGBA value for all points.\n",
      "*c* argument looks like a single numeric RGB or RGBA sequence, which should be avoided as value-mapping will have precedence in case its length matches with *x* & *y*.  Please use the *color* keyword-argument or provide a 2-D array with a single row if you intend to specify the same RGB or RGBA value for all points.\n",
      "*c* argument looks like a single numeric RGB or RGBA sequence, which should be avoided as value-mapping will have precedence in case its length matches with *x* & *y*.  Please use the *color* keyword-argument or provide a 2-D array with a single row if you intend to specify the same RGB or RGBA value for all points.\n",
      "*c* argument looks like a single numeric RGB or RGBA sequence, which should be avoided as value-mapping will have precedence in case its length matches with *x* & *y*.  Please use the *color* keyword-argument or provide a 2-D array with a single row if you intend to specify the same RGB or RGBA value for all points.\n",
      "*c* argument looks like a single numeric RGB or RGBA sequence, which should be avoided as value-mapping will have precedence in case its length matches with *x* & *y*.  Please use the *color* keyword-argument or provide a 2-D array with a single row if you intend to specify the same RGB or RGBA value for all points.\n",
      "*c* argument looks like a single numeric RGB or RGBA sequence, which should be avoided as value-mapping will have precedence in case its length matches with *x* & *y*.  Please use the *color* keyword-argument or provide a 2-D array with a single row if you intend to specify the same RGB or RGBA value for all points.\n",
      "*c* argument looks like a single numeric RGB or RGBA sequence, which should be avoided as value-mapping will have precedence in case its length matches with *x* & *y*.  Please use the *color* keyword-argument or provide a 2-D array with a single row if you intend to specify the same RGB or RGBA value for all points.\n",
      "*c* argument looks like a single numeric RGB or RGBA sequence, which should be avoided as value-mapping will have precedence in case its length matches with *x* & *y*.  Please use the *color* keyword-argument or provide a 2-D array with a single row if you intend to specify the same RGB or RGBA value for all points.\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "*c* argument looks like a single numeric RGB or RGBA sequence, which should be avoided as value-mapping will have precedence in case its length matches with *x* & *y*.  Please use the *color* keyword-argument or provide a 2-D array with a single row if you intend to specify the same RGB or RGBA value for all points.\n",
      "*c* argument looks like a single numeric RGB or RGBA sequence, which should be avoided as value-mapping will have precedence in case its length matches with *x* & *y*.  Please use the *color* keyword-argument or provide a 2-D array with a single row if you intend to specify the same RGB or RGBA value for all points.\n",
      "*c* argument looks like a single numeric RGB or RGBA sequence, which should be avoided as value-mapping will have precedence in case its length matches with *x* & *y*.  Please use the *color* keyword-argument or provide a 2-D array with a single row if you intend to specify the same RGB or RGBA value for all points.\n",
      "*c* argument looks like a single numeric RGB or RGBA sequence, which should be avoided as value-mapping will have precedence in case its length matches with *x* & *y*.  Please use the *color* keyword-argument or provide a 2-D array with a single row if you intend to specify the same RGB or RGBA value for all points.\n",
      "*c* argument looks like a single numeric RGB or RGBA sequence, which should be avoided as value-mapping will have precedence in case its length matches with *x* & *y*.  Please use the *color* keyword-argument or provide a 2-D array with a single row if you intend to specify the same RGB or RGBA value for all points.\n",
      "*c* argument looks like a single numeric RGB or RGBA sequence, which should be avoided as value-mapping will have precedence in case its length matches with *x* & *y*.  Please use the *color* keyword-argument or provide a 2-D array with a single row if you intend to specify the same RGB or RGBA value for all points.\n",
      "*c* argument looks like a single numeric RGB or RGBA sequence, which should be avoided as value-mapping will have precedence in case its length matches with *x* & *y*.  Please use the *color* keyword-argument or provide a 2-D array with a single row if you intend to specify the same RGB or RGBA value for all points.\n",
      "*c* argument looks like a single numeric RGB or RGBA sequence, which should be avoided as value-mapping will have precedence in case its length matches with *x* & *y*.  Please use the *color* keyword-argument or provide a 2-D array with a single row if you intend to specify the same RGB or RGBA value for all points.\n",
      "*c* argument looks like a single numeric RGB or RGBA sequence, which should be avoided as value-mapping will have precedence in case its length matches with *x* & *y*.  Please use the *color* keyword-argument or provide a 2-D array with a single row if you intend to specify the same RGB or RGBA value for all points.\n",
      "*c* argument looks like a single numeric RGB or RGBA sequence, which should be avoided as value-mapping will have precedence in case its length matches with *x* & *y*.  Please use the *color* keyword-argument or provide a 2-D array with a single row if you intend to specify the same RGB or RGBA value for all points.\n",
      "*c* argument looks like a single numeric RGB or RGBA sequence, which should be avoided as value-mapping will have precedence in case its length matches with *x* & *y*.  Please use the *color* keyword-argument or provide a 2-D array with a single row if you intend to specify the same RGB or RGBA value for all points.\n",
      "*c* argument looks like a single numeric RGB or RGBA sequence, which should be avoided as value-mapping will have precedence in case its length matches with *x* & *y*.  Please use the *color* keyword-argument or provide a 2-D array with a single row if you intend to specify the same RGB or RGBA value for all points.\n",
      "*c* argument looks like a single numeric RGB or RGBA sequence, which should be avoided as value-mapping will have precedence in case its length matches with *x* & *y*.  Please use the *color* keyword-argument or provide a 2-D array with a single row if you intend to specify the same RGB or RGBA value for all points.\n",
      "*c* argument looks like a single numeric RGB or RGBA sequence, which should be avoided as value-mapping will have precedence in case its length matches with *x* & *y*.  Please use the *color* keyword-argument or provide a 2-D array with a single row if you intend to specify the same RGB or RGBA value for all points.\n",
      "*c* argument looks like a single numeric RGB or RGBA sequence, which should be avoided as value-mapping will have precedence in case its length matches with *x* & *y*.  Please use the *color* keyword-argument or provide a 2-D array with a single row if you intend to specify the same RGB or RGBA value for all points.\n",
      "*c* argument looks like a single numeric RGB or RGBA sequence, which should be avoided as value-mapping will have precedence in case its length matches with *x* & *y*.  Please use the *color* keyword-argument or provide a 2-D array with a single row if you intend to specify the same RGB or RGBA value for all points.\n",
      "*c* argument looks like a single numeric RGB or RGBA sequence, which should be avoided as value-mapping will have precedence in case its length matches with *x* & *y*.  Please use the *color* keyword-argument or provide a 2-D array with a single row if you intend to specify the same RGB or RGBA value for all points.\n",
      "*c* argument looks like a single numeric RGB or RGBA sequence, which should be avoided as value-mapping will have precedence in case its length matches with *x* & *y*.  Please use the *color* keyword-argument or provide a 2-D array with a single row if you intend to specify the same RGB or RGBA value for all points.\n",
      "*c* argument looks like a single numeric RGB or RGBA sequence, which should be avoided as value-mapping will have precedence in case its length matches with *x* & *y*.  Please use the *color* keyword-argument or provide a 2-D array with a single row if you intend to specify the same RGB or RGBA value for all points.\n",
      "*c* argument looks like a single numeric RGB or RGBA sequence, which should be avoided as value-mapping will have precedence in case its length matches with *x* & *y*.  Please use the *color* keyword-argument or provide a 2-D array with a single row if you intend to specify the same RGB or RGBA value for all points.\n",
      "*c* argument looks like a single numeric RGB or RGBA sequence, which should be avoided as value-mapping will have precedence in case its length matches with *x* & *y*.  Please use the *color* keyword-argument or provide a 2-D array with a single row if you intend to specify the same RGB or RGBA value for all points.\n",
      "*c* argument looks like a single numeric RGB or RGBA sequence, which should be avoided as value-mapping will have precedence in case its length matches with *x* & *y*.  Please use the *color* keyword-argument or provide a 2-D array with a single row if you intend to specify the same RGB or RGBA value for all points.\n",
      "*c* argument looks like a single numeric RGB or RGBA sequence, which should be avoided as value-mapping will have precedence in case its length matches with *x* & *y*.  Please use the *color* keyword-argument or provide a 2-D array with a single row if you intend to specify the same RGB or RGBA value for all points.\n",
      "*c* argument looks like a single numeric RGB or RGBA sequence, which should be avoided as value-mapping will have precedence in case its length matches with *x* & *y*.  Please use the *color* keyword-argument or provide a 2-D array with a single row if you intend to specify the same RGB or RGBA value for all points.\n",
      "*c* argument looks like a single numeric RGB or RGBA sequence, which should be avoided as value-mapping will have precedence in case its length matches with *x* & *y*.  Please use the *color* keyword-argument or provide a 2-D array with a single row if you intend to specify the same RGB or RGBA value for all points.\n",
      "*c* argument looks like a single numeric RGB or RGBA sequence, which should be avoided as value-mapping will have precedence in case its length matches with *x* & *y*.  Please use the *color* keyword-argument or provide a 2-D array with a single row if you intend to specify the same RGB or RGBA value for all points.\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "*c* argument looks like a single numeric RGB or RGBA sequence, which should be avoided as value-mapping will have precedence in case its length matches with *x* & *y*.  Please use the *color* keyword-argument or provide a 2-D array with a single row if you intend to specify the same RGB or RGBA value for all points.\n",
      "*c* argument looks like a single numeric RGB or RGBA sequence, which should be avoided as value-mapping will have precedence in case its length matches with *x* & *y*.  Please use the *color* keyword-argument or provide a 2-D array with a single row if you intend to specify the same RGB or RGBA value for all points.\n",
      "*c* argument looks like a single numeric RGB or RGBA sequence, which should be avoided as value-mapping will have precedence in case its length matches with *x* & *y*.  Please use the *color* keyword-argument or provide a 2-D array with a single row if you intend to specify the same RGB or RGBA value for all points.\n",
      "*c* argument looks like a single numeric RGB or RGBA sequence, which should be avoided as value-mapping will have precedence in case its length matches with *x* & *y*.  Please use the *color* keyword-argument or provide a 2-D array with a single row if you intend to specify the same RGB or RGBA value for all points.\n",
      "*c* argument looks like a single numeric RGB or RGBA sequence, which should be avoided as value-mapping will have precedence in case its length matches with *x* & *y*.  Please use the *color* keyword-argument or provide a 2-D array with a single row if you intend to specify the same RGB or RGBA value for all points.\n",
      "*c* argument looks like a single numeric RGB or RGBA sequence, which should be avoided as value-mapping will have precedence in case its length matches with *x* & *y*.  Please use the *color* keyword-argument or provide a 2-D array with a single row if you intend to specify the same RGB or RGBA value for all points.\n",
      "*c* argument looks like a single numeric RGB or RGBA sequence, which should be avoided as value-mapping will have precedence in case its length matches with *x* & *y*.  Please use the *color* keyword-argument or provide a 2-D array with a single row if you intend to specify the same RGB or RGBA value for all points.\n",
      "*c* argument looks like a single numeric RGB or RGBA sequence, which should be avoided as value-mapping will have precedence in case its length matches with *x* & *y*.  Please use the *color* keyword-argument or provide a 2-D array with a single row if you intend to specify the same RGB or RGBA value for all points.\n"
     ]
    },
    {
     "data": {
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\n",
      "text/plain": [
       "<Figure size 720x720 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "*c* argument looks like a single numeric RGB or RGBA sequence, which should be avoided as value-mapping will have precedence in case its length matches with *x* & *y*.  Please use the *color* keyword-argument or provide a 2-D array with a single row if you intend to specify the same RGB or RGBA value for all points.\n",
      "*c* argument looks like a single numeric RGB or RGBA sequence, which should be avoided as value-mapping will have precedence in case its length matches with *x* & *y*.  Please use the *color* keyword-argument or provide a 2-D array with a single row if you intend to specify the same RGB or RGBA value for all points.\n",
      "*c* argument looks like a single numeric RGB or RGBA sequence, which should be avoided as value-mapping will have precedence in case its length matches with *x* & *y*.  Please use the *color* keyword-argument or provide a 2-D array with a single row if you intend to specify the same RGB or RGBA value for all points.\n",
      "*c* argument looks like a single numeric RGB or RGBA sequence, which should be avoided as value-mapping will have precedence in case its length matches with *x* & *y*.  Please use the *color* keyword-argument or provide a 2-D array with a single row if you intend to specify the same RGB or RGBA value for all points.\n",
      "*c* argument looks like a single numeric RGB or RGBA sequence, which should be avoided as value-mapping will have precedence in case its length matches with *x* & *y*.  Please use the *color* keyword-argument or provide a 2-D array with a single row if you intend to specify the same RGB or RGBA value for all points.\n",
      "*c* argument looks like a single numeric RGB or RGBA sequence, which should be avoided as value-mapping will have precedence in case its length matches with *x* & *y*.  Please use the *color* keyword-argument or provide a 2-D array with a single row if you intend to specify the same RGB or RGBA value for all points.\n",
      "*c* argument looks like a single numeric RGB or RGBA sequence, which should be avoided as value-mapping will have precedence in case its length matches with *x* & *y*.  Please use the *color* keyword-argument or provide a 2-D array with a single row if you intend to specify the same RGB or RGBA value for all points.\n",
      "*c* argument looks like a single numeric RGB or RGBA sequence, which should be avoided as value-mapping will have precedence in case its length matches with *x* & *y*.  Please use the *color* keyword-argument or provide a 2-D array with a single row if you intend to specify the same RGB or RGBA value for all points.\n",
      "*c* argument looks like a single numeric RGB or RGBA sequence, which should be avoided as value-mapping will have precedence in case its length matches with *x* & *y*.  Please use the *color* keyword-argument or provide a 2-D array with a single row if you intend to specify the same RGB or RGBA value for all points.\n",
      "*c* argument looks like a single numeric RGB or RGBA sequence, which should be avoided as value-mapping will have precedence in case its length matches with *x* & *y*.  Please use the *color* keyword-argument or provide a 2-D array with a single row if you intend to specify the same RGB or RGBA value for all points.\n",
      "*c* argument looks like a single numeric RGB or RGBA sequence, which should be avoided as value-mapping will have precedence in case its length matches with *x* & *y*.  Please use the *color* keyword-argument or provide a 2-D array with a single row if you intend to specify the same RGB or RGBA value for all points.\n",
      "*c* argument looks like a single numeric RGB or RGBA sequence, which should be avoided as value-mapping will have precedence in case its length matches with *x* & *y*.  Please use the *color* keyword-argument or provide a 2-D array with a single row if you intend to specify the same RGB or RGBA value for all points.\n",
      "*c* argument looks like a single numeric RGB or RGBA sequence, which should be avoided as value-mapping will have precedence in case its length matches with *x* & *y*.  Please use the *color* keyword-argument or provide a 2-D array with a single row if you intend to specify the same RGB or RGBA value for all points.\n",
      "*c* argument looks like a single numeric RGB or RGBA sequence, which should be avoided as value-mapping will have precedence in case its length matches with *x* & *y*.  Please use the *color* keyword-argument or provide a 2-D array with a single row if you intend to specify the same RGB or RGBA value for all points.\n",
      "*c* argument looks like a single numeric RGB or RGBA sequence, which should be avoided as value-mapping will have precedence in case its length matches with *x* & *y*.  Please use the *color* keyword-argument or provide a 2-D array with a single row if you intend to specify the same RGB or RGBA value for all points.\n",
      "*c* argument looks like a single numeric RGB or RGBA sequence, which should be avoided as value-mapping will have precedence in case its length matches with *x* & *y*.  Please use the *color* keyword-argument or provide a 2-D array with a single row if you intend to specify the same RGB or RGBA value for all points.\n",
      "*c* argument looks like a single numeric RGB or RGBA sequence, which should be avoided as value-mapping will have precedence in case its length matches with *x* & *y*.  Please use the *color* keyword-argument or provide a 2-D array with a single row if you intend to specify the same RGB or RGBA value for all points.\n",
      "*c* argument looks like a single numeric RGB or RGBA sequence, which should be avoided as value-mapping will have precedence in case its length matches with *x* & *y*.  Please use the *color* keyword-argument or provide a 2-D array with a single row if you intend to specify the same RGB or RGBA value for all points.\n",
      "*c* argument looks like a single numeric RGB or RGBA sequence, which should be avoided as value-mapping will have precedence in case its length matches with *x* & *y*.  Please use the *color* keyword-argument or provide a 2-D array with a single row if you intend to specify the same RGB or RGBA value for all points.\n",
      "*c* argument looks like a single numeric RGB or RGBA sequence, which should be avoided as value-mapping will have precedence in case its length matches with *x* & *y*.  Please use the *color* keyword-argument or provide a 2-D array with a single row if you intend to specify the same RGB or RGBA value for all points.\n",
      "*c* argument looks like a single numeric RGB or RGBA sequence, which should be avoided as value-mapping will have precedence in case its length matches with *x* & *y*.  Please use the *color* keyword-argument or provide a 2-D array with a single row if you intend to specify the same RGB or RGBA value for all points.\n",
      "*c* argument looks like a single numeric RGB or RGBA sequence, which should be avoided as value-mapping will have precedence in case its length matches with *x* & *y*.  Please use the *color* keyword-argument or provide a 2-D array with a single row if you intend to specify the same RGB or RGBA value for all points.\n",
      "*c* argument looks like a single numeric RGB or RGBA sequence, which should be avoided as value-mapping will have precedence in case its length matches with *x* & *y*.  Please use the *color* keyword-argument or provide a 2-D array with a single row if you intend to specify the same RGB or RGBA value for all points.\n",
      "*c* argument looks like a single numeric RGB or RGBA sequence, which should be avoided as value-mapping will have precedence in case its length matches with *x* & *y*.  Please use the *color* keyword-argument or provide a 2-D array with a single row if you intend to specify the same RGB or RGBA value for all points.\n",
      "*c* argument looks like a single numeric RGB or RGBA sequence, which should be avoided as value-mapping will have precedence in case its length matches with *x* & *y*.  Please use the *color* keyword-argument or provide a 2-D array with a single row if you intend to specify the same RGB or RGBA value for all points.\n",
      "*c* argument looks like a single numeric RGB or RGBA sequence, which should be avoided as value-mapping will have precedence in case its length matches with *x* & *y*.  Please use the *color* keyword-argument or provide a 2-D array with a single row if you intend to specify the same RGB or RGBA value for all points.\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "*c* argument looks like a single numeric RGB or RGBA sequence, which should be avoided as value-mapping will have precedence in case its length matches with *x* & *y*.  Please use the *color* keyword-argument or provide a 2-D array with a single row if you intend to specify the same RGB or RGBA value for all points.\n",
      "*c* argument looks like a single numeric RGB or RGBA sequence, which should be avoided as value-mapping will have precedence in case its length matches with *x* & *y*.  Please use the *color* keyword-argument or provide a 2-D array with a single row if you intend to specify the same RGB or RGBA value for all points.\n",
      "*c* argument looks like a single numeric RGB or RGBA sequence, which should be avoided as value-mapping will have precedence in case its length matches with *x* & *y*.  Please use the *color* keyword-argument or provide a 2-D array with a single row if you intend to specify the same RGB or RGBA value for all points.\n",
      "*c* argument looks like a single numeric RGB or RGBA sequence, which should be avoided as value-mapping will have precedence in case its length matches with *x* & *y*.  Please use the *color* keyword-argument or provide a 2-D array with a single row if you intend to specify the same RGB or RGBA value for all points.\n",
      "*c* argument looks like a single numeric RGB or RGBA sequence, which should be avoided as value-mapping will have precedence in case its length matches with *x* & *y*.  Please use the *color* keyword-argument or provide a 2-D array with a single row if you intend to specify the same RGB or RGBA value for all points.\n",
      "*c* argument looks like a single numeric RGB or RGBA sequence, which should be avoided as value-mapping will have precedence in case its length matches with *x* & *y*.  Please use the *color* keyword-argument or provide a 2-D array with a single row if you intend to specify the same RGB or RGBA value for all points.\n",
      "*c* argument looks like a single numeric RGB or RGBA sequence, which should be avoided as value-mapping will have precedence in case its length matches with *x* & *y*.  Please use the *color* keyword-argument or provide a 2-D array with a single row if you intend to specify the same RGB or RGBA value for all points.\n",
      "*c* argument looks like a single numeric RGB or RGBA sequence, which should be avoided as value-mapping will have precedence in case its length matches with *x* & *y*.  Please use the *color* keyword-argument or provide a 2-D array with a single row if you intend to specify the same RGB or RGBA value for all points.\n",
      "*c* argument looks like a single numeric RGB or RGBA sequence, which should be avoided as value-mapping will have precedence in case its length matches with *x* & *y*.  Please use the *color* keyword-argument or provide a 2-D array with a single row if you intend to specify the same RGB or RGBA value for all points.\n",
      "*c* argument looks like a single numeric RGB or RGBA sequence, which should be avoided as value-mapping will have precedence in case its length matches with *x* & *y*.  Please use the *color* keyword-argument or provide a 2-D array with a single row if you intend to specify the same RGB or RGBA value for all points.\n",
      "*c* argument looks like a single numeric RGB or RGBA sequence, which should be avoided as value-mapping will have precedence in case its length matches with *x* & *y*.  Please use the *color* keyword-argument or provide a 2-D array with a single row if you intend to specify the same RGB or RGBA value for all points.\n",
      "*c* argument looks like a single numeric RGB or RGBA sequence, which should be avoided as value-mapping will have precedence in case its length matches with *x* & *y*.  Please use the *color* keyword-argument or provide a 2-D array with a single row if you intend to specify the same RGB or RGBA value for all points.\n",
      "*c* argument looks like a single numeric RGB or RGBA sequence, which should be avoided as value-mapping will have precedence in case its length matches with *x* & *y*.  Please use the *color* keyword-argument or provide a 2-D array with a single row if you intend to specify the same RGB or RGBA value for all points.\n",
      "*c* argument looks like a single numeric RGB or RGBA sequence, which should be avoided as value-mapping will have precedence in case its length matches with *x* & *y*.  Please use the *color* keyword-argument or provide a 2-D array with a single row if you intend to specify the same RGB or RGBA value for all points.\n",
      "*c* argument looks like a single numeric RGB or RGBA sequence, which should be avoided as value-mapping will have precedence in case its length matches with *x* & *y*.  Please use the *color* keyword-argument or provide a 2-D array with a single row if you intend to specify the same RGB or RGBA value for all points.\n",
      "*c* argument looks like a single numeric RGB or RGBA sequence, which should be avoided as value-mapping will have precedence in case its length matches with *x* & *y*.  Please use the *color* keyword-argument or provide a 2-D array with a single row if you intend to specify the same RGB or RGBA value for all points.\n",
      "*c* argument looks like a single numeric RGB or RGBA sequence, which should be avoided as value-mapping will have precedence in case its length matches with *x* & *y*.  Please use the *color* keyword-argument or provide a 2-D array with a single row if you intend to specify the same RGB or RGBA value for all points.\n",
      "*c* argument looks like a single numeric RGB or RGBA sequence, which should be avoided as value-mapping will have precedence in case its length matches with *x* & *y*.  Please use the *color* keyword-argument or provide a 2-D array with a single row if you intend to specify the same RGB or RGBA value for all points.\n",
      "*c* argument looks like a single numeric RGB or RGBA sequence, which should be avoided as value-mapping will have precedence in case its length matches with *x* & *y*.  Please use the *color* keyword-argument or provide a 2-D array with a single row if you intend to specify the same RGB or RGBA value for all points.\n",
      "*c* argument looks like a single numeric RGB or RGBA sequence, which should be avoided as value-mapping will have precedence in case its length matches with *x* & *y*.  Please use the *color* keyword-argument or provide a 2-D array with a single row if you intend to specify the same RGB or RGBA value for all points.\n",
      "*c* argument looks like a single numeric RGB or RGBA sequence, which should be avoided as value-mapping will have precedence in case its length matches with *x* & *y*.  Please use the *color* keyword-argument or provide a 2-D array with a single row if you intend to specify the same RGB or RGBA value for all points.\n",
      "*c* argument looks like a single numeric RGB or RGBA sequence, which should be avoided as value-mapping will have precedence in case its length matches with *x* & *y*.  Please use the *color* keyword-argument or provide a 2-D array with a single row if you intend to specify the same RGB or RGBA value for all points.\n",
      "*c* argument looks like a single numeric RGB or RGBA sequence, which should be avoided as value-mapping will have precedence in case its length matches with *x* & *y*.  Please use the *color* keyword-argument or provide a 2-D array with a single row if you intend to specify the same RGB or RGBA value for all points.\n",
      "*c* argument looks like a single numeric RGB or RGBA sequence, which should be avoided as value-mapping will have precedence in case its length matches with *x* & *y*.  Please use the *color* keyword-argument or provide a 2-D array with a single row if you intend to specify the same RGB or RGBA value for all points.\n",
      "*c* argument looks like a single numeric RGB or RGBA sequence, which should be avoided as value-mapping will have precedence in case its length matches with *x* & *y*.  Please use the *color* keyword-argument or provide a 2-D array with a single row if you intend to specify the same RGB or RGBA value for all points.\n",
      "*c* argument looks like a single numeric RGB or RGBA sequence, which should be avoided as value-mapping will have precedence in case its length matches with *x* & *y*.  Please use the *color* keyword-argument or provide a 2-D array with a single row if you intend to specify the same RGB or RGBA value for all points.\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "*c* argument looks like a single numeric RGB or RGBA sequence, which should be avoided as value-mapping will have precedence in case its length matches with *x* & *y*.  Please use the *color* keyword-argument or provide a 2-D array with a single row if you intend to specify the same RGB or RGBA value for all points.\n",
      "*c* argument looks like a single numeric RGB or RGBA sequence, which should be avoided as value-mapping will have precedence in case its length matches with *x* & *y*.  Please use the *color* keyword-argument or provide a 2-D array with a single row if you intend to specify the same RGB or RGBA value for all points.\n",
      "*c* argument looks like a single numeric RGB or RGBA sequence, which should be avoided as value-mapping will have precedence in case its length matches with *x* & *y*.  Please use the *color* keyword-argument or provide a 2-D array with a single row if you intend to specify the same RGB or RGBA value for all points.\n",
      "*c* argument looks like a single numeric RGB or RGBA sequence, which should be avoided as value-mapping will have precedence in case its length matches with *x* & *y*.  Please use the *color* keyword-argument or provide a 2-D array with a single row if you intend to specify the same RGB or RGBA value for all points.\n",
      "*c* argument looks like a single numeric RGB or RGBA sequence, which should be avoided as value-mapping will have precedence in case its length matches with *x* & *y*.  Please use the *color* keyword-argument or provide a 2-D array with a single row if you intend to specify the same RGB or RGBA value for all points.\n",
      "*c* argument looks like a single numeric RGB or RGBA sequence, which should be avoided as value-mapping will have precedence in case its length matches with *x* & *y*.  Please use the *color* keyword-argument or provide a 2-D array with a single row if you intend to specify the same RGB or RGBA value for all points.\n",
      "*c* argument looks like a single numeric RGB or RGBA sequence, which should be avoided as value-mapping will have precedence in case its length matches with *x* & *y*.  Please use the *color* keyword-argument or provide a 2-D array with a single row if you intend to specify the same RGB or RGBA value for all points.\n",
      "*c* argument looks like a single numeric RGB or RGBA sequence, which should be avoided as value-mapping will have precedence in case its length matches with *x* & *y*.  Please use the *color* keyword-argument or provide a 2-D array with a single row if you intend to specify the same RGB or RGBA value for all points.\n"
     ]
    },
    {
     "data": {
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\n",
      "text/plain": [
       "<Figure size 720x720 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "*c* argument looks like a single numeric RGB or RGBA sequence, which should be avoided as value-mapping will have precedence in case its length matches with *x* & *y*.  Please use the *color* keyword-argument or provide a 2-D array with a single row if you intend to specify the same RGB or RGBA value for all points.\n",
      "*c* argument looks like a single numeric RGB or RGBA sequence, which should be avoided as value-mapping will have precedence in case its length matches with *x* & *y*.  Please use the *color* keyword-argument or provide a 2-D array with a single row if you intend to specify the same RGB or RGBA value for all points.\n",
      "*c* argument looks like a single numeric RGB or RGBA sequence, which should be avoided as value-mapping will have precedence in case its length matches with *x* & *y*.  Please use the *color* keyword-argument or provide a 2-D array with a single row if you intend to specify the same RGB or RGBA value for all points.\n",
      "*c* argument looks like a single numeric RGB or RGBA sequence, which should be avoided as value-mapping will have precedence in case its length matches with *x* & *y*.  Please use the *color* keyword-argument or provide a 2-D array with a single row if you intend to specify the same RGB or RGBA value for all points.\n",
      "*c* argument looks like a single numeric RGB or RGBA sequence, which should be avoided as value-mapping will have precedence in case its length matches with *x* & *y*.  Please use the *color* keyword-argument or provide a 2-D array with a single row if you intend to specify the same RGB or RGBA value for all points.\n",
      "*c* argument looks like a single numeric RGB or RGBA sequence, which should be avoided as value-mapping will have precedence in case its length matches with *x* & *y*.  Please use the *color* keyword-argument or provide a 2-D array with a single row if you intend to specify the same RGB or RGBA value for all points.\n",
      "*c* argument looks like a single numeric RGB or RGBA sequence, which should be avoided as value-mapping will have precedence in case its length matches with *x* & *y*.  Please use the *color* keyword-argument or provide a 2-D array with a single row if you intend to specify the same RGB or RGBA value for all points.\n",
      "*c* argument looks like a single numeric RGB or RGBA sequence, which should be avoided as value-mapping will have precedence in case its length matches with *x* & *y*.  Please use the *color* keyword-argument or provide a 2-D array with a single row if you intend to specify the same RGB or RGBA value for all points.\n",
      "*c* argument looks like a single numeric RGB or RGBA sequence, which should be avoided as value-mapping will have precedence in case its length matches with *x* & *y*.  Please use the *color* keyword-argument or provide a 2-D array with a single row if you intend to specify the same RGB or RGBA value for all points.\n",
      "*c* argument looks like a single numeric RGB or RGBA sequence, which should be avoided as value-mapping will have precedence in case its length matches with *x* & *y*.  Please use the *color* keyword-argument or provide a 2-D array with a single row if you intend to specify the same RGB or RGBA value for all points.\n",
      "*c* argument looks like a single numeric RGB or RGBA sequence, which should be avoided as value-mapping will have precedence in case its length matches with *x* & *y*.  Please use the *color* keyword-argument or provide a 2-D array with a single row if you intend to specify the same RGB or RGBA value for all points.\n",
      "*c* argument looks like a single numeric RGB or RGBA sequence, which should be avoided as value-mapping will have precedence in case its length matches with *x* & *y*.  Please use the *color* keyword-argument or provide a 2-D array with a single row if you intend to specify the same RGB or RGBA value for all points.\n",
      "*c* argument looks like a single numeric RGB or RGBA sequence, which should be avoided as value-mapping will have precedence in case its length matches with *x* & *y*.  Please use the *color* keyword-argument or provide a 2-D array with a single row if you intend to specify the same RGB or RGBA value for all points.\n",
      "*c* argument looks like a single numeric RGB or RGBA sequence, which should be avoided as value-mapping will have precedence in case its length matches with *x* & *y*.  Please use the *color* keyword-argument or provide a 2-D array with a single row if you intend to specify the same RGB or RGBA value for all points.\n",
      "*c* argument looks like a single numeric RGB or RGBA sequence, which should be avoided as value-mapping will have precedence in case its length matches with *x* & *y*.  Please use the *color* keyword-argument or provide a 2-D array with a single row if you intend to specify the same RGB or RGBA value for all points.\n",
      "*c* argument looks like a single numeric RGB or RGBA sequence, which should be avoided as value-mapping will have precedence in case its length matches with *x* & *y*.  Please use the *color* keyword-argument or provide a 2-D array with a single row if you intend to specify the same RGB or RGBA value for all points.\n",
      "*c* argument looks like a single numeric RGB or RGBA sequence, which should be avoided as value-mapping will have precedence in case its length matches with *x* & *y*.  Please use the *color* keyword-argument or provide a 2-D array with a single row if you intend to specify the same RGB or RGBA value for all points.\n",
      "*c* argument looks like a single numeric RGB or RGBA sequence, which should be avoided as value-mapping will have precedence in case its length matches with *x* & *y*.  Please use the *color* keyword-argument or provide a 2-D array with a single row if you intend to specify the same RGB or RGBA value for all points.\n",
      "*c* argument looks like a single numeric RGB or RGBA sequence, which should be avoided as value-mapping will have precedence in case its length matches with *x* & *y*.  Please use the *color* keyword-argument or provide a 2-D array with a single row if you intend to specify the same RGB or RGBA value for all points.\n",
      "*c* argument looks like a single numeric RGB or RGBA sequence, which should be avoided as value-mapping will have precedence in case its length matches with *x* & *y*.  Please use the *color* keyword-argument or provide a 2-D array with a single row if you intend to specify the same RGB or RGBA value for all points.\n",
      "*c* argument looks like a single numeric RGB or RGBA sequence, which should be avoided as value-mapping will have precedence in case its length matches with *x* & *y*.  Please use the *color* keyword-argument or provide a 2-D array with a single row if you intend to specify the same RGB or RGBA value for all points.\n",
      "*c* argument looks like a single numeric RGB or RGBA sequence, which should be avoided as value-mapping will have precedence in case its length matches with *x* & *y*.  Please use the *color* keyword-argument or provide a 2-D array with a single row if you intend to specify the same RGB or RGBA value for all points.\n",
      "*c* argument looks like a single numeric RGB or RGBA sequence, which should be avoided as value-mapping will have precedence in case its length matches with *x* & *y*.  Please use the *color* keyword-argument or provide a 2-D array with a single row if you intend to specify the same RGB or RGBA value for all points.\n",
      "*c* argument looks like a single numeric RGB or RGBA sequence, which should be avoided as value-mapping will have precedence in case its length matches with *x* & *y*.  Please use the *color* keyword-argument or provide a 2-D array with a single row if you intend to specify the same RGB or RGBA value for all points.\n",
      "*c* argument looks like a single numeric RGB or RGBA sequence, which should be avoided as value-mapping will have precedence in case its length matches with *x* & *y*.  Please use the *color* keyword-argument or provide a 2-D array with a single row if you intend to specify the same RGB or RGBA value for all points.\n",
      "*c* argument looks like a single numeric RGB or RGBA sequence, which should be avoided as value-mapping will have precedence in case its length matches with *x* & *y*.  Please use the *color* keyword-argument or provide a 2-D array with a single row if you intend to specify the same RGB or RGBA value for all points.\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "*c* argument looks like a single numeric RGB or RGBA sequence, which should be avoided as value-mapping will have precedence in case its length matches with *x* & *y*.  Please use the *color* keyword-argument or provide a 2-D array with a single row if you intend to specify the same RGB or RGBA value for all points.\n",
      "*c* argument looks like a single numeric RGB or RGBA sequence, which should be avoided as value-mapping will have precedence in case its length matches with *x* & *y*.  Please use the *color* keyword-argument or provide a 2-D array with a single row if you intend to specify the same RGB or RGBA value for all points.\n",
      "*c* argument looks like a single numeric RGB or RGBA sequence, which should be avoided as value-mapping will have precedence in case its length matches with *x* & *y*.  Please use the *color* keyword-argument or provide a 2-D array with a single row if you intend to specify the same RGB or RGBA value for all points.\n",
      "*c* argument looks like a single numeric RGB or RGBA sequence, which should be avoided as value-mapping will have precedence in case its length matches with *x* & *y*.  Please use the *color* keyword-argument or provide a 2-D array with a single row if you intend to specify the same RGB or RGBA value for all points.\n",
      "*c* argument looks like a single numeric RGB or RGBA sequence, which should be avoided as value-mapping will have precedence in case its length matches with *x* & *y*.  Please use the *color* keyword-argument or provide a 2-D array with a single row if you intend to specify the same RGB or RGBA value for all points.\n",
      "*c* argument looks like a single numeric RGB or RGBA sequence, which should be avoided as value-mapping will have precedence in case its length matches with *x* & *y*.  Please use the *color* keyword-argument or provide a 2-D array with a single row if you intend to specify the same RGB or RGBA value for all points.\n",
      "*c* argument looks like a single numeric RGB or RGBA sequence, which should be avoided as value-mapping will have precedence in case its length matches with *x* & *y*.  Please use the *color* keyword-argument or provide a 2-D array with a single row if you intend to specify the same RGB or RGBA value for all points.\n",
      "*c* argument looks like a single numeric RGB or RGBA sequence, which should be avoided as value-mapping will have precedence in case its length matches with *x* & *y*.  Please use the *color* keyword-argument or provide a 2-D array with a single row if you intend to specify the same RGB or RGBA value for all points.\n",
      "*c* argument looks like a single numeric RGB or RGBA sequence, which should be avoided as value-mapping will have precedence in case its length matches with *x* & *y*.  Please use the *color* keyword-argument or provide a 2-D array with a single row if you intend to specify the same RGB or RGBA value for all points.\n",
      "*c* argument looks like a single numeric RGB or RGBA sequence, which should be avoided as value-mapping will have precedence in case its length matches with *x* & *y*.  Please use the *color* keyword-argument or provide a 2-D array with a single row if you intend to specify the same RGB or RGBA value for all points.\n",
      "*c* argument looks like a single numeric RGB or RGBA sequence, which should be avoided as value-mapping will have precedence in case its length matches with *x* & *y*.  Please use the *color* keyword-argument or provide a 2-D array with a single row if you intend to specify the same RGB or RGBA value for all points.\n",
      "*c* argument looks like a single numeric RGB or RGBA sequence, which should be avoided as value-mapping will have precedence in case its length matches with *x* & *y*.  Please use the *color* keyword-argument or provide a 2-D array with a single row if you intend to specify the same RGB or RGBA value for all points.\n",
      "*c* argument looks like a single numeric RGB or RGBA sequence, which should be avoided as value-mapping will have precedence in case its length matches with *x* & *y*.  Please use the *color* keyword-argument or provide a 2-D array with a single row if you intend to specify the same RGB or RGBA value for all points.\n",
      "*c* argument looks like a single numeric RGB or RGBA sequence, which should be avoided as value-mapping will have precedence in case its length matches with *x* & *y*.  Please use the *color* keyword-argument or provide a 2-D array with a single row if you intend to specify the same RGB or RGBA value for all points.\n",
      "*c* argument looks like a single numeric RGB or RGBA sequence, which should be avoided as value-mapping will have precedence in case its length matches with *x* & *y*.  Please use the *color* keyword-argument or provide a 2-D array with a single row if you intend to specify the same RGB or RGBA value for all points.\n",
      "*c* argument looks like a single numeric RGB or RGBA sequence, which should be avoided as value-mapping will have precedence in case its length matches with *x* & *y*.  Please use the *color* keyword-argument or provide a 2-D array with a single row if you intend to specify the same RGB or RGBA value for all points.\n",
      "*c* argument looks like a single numeric RGB or RGBA sequence, which should be avoided as value-mapping will have precedence in case its length matches with *x* & *y*.  Please use the *color* keyword-argument or provide a 2-D array with a single row if you intend to specify the same RGB or RGBA value for all points.\n",
      "*c* argument looks like a single numeric RGB or RGBA sequence, which should be avoided as value-mapping will have precedence in case its length matches with *x* & *y*.  Please use the *color* keyword-argument or provide a 2-D array with a single row if you intend to specify the same RGB or RGBA value for all points.\n",
      "*c* argument looks like a single numeric RGB or RGBA sequence, which should be avoided as value-mapping will have precedence in case its length matches with *x* & *y*.  Please use the *color* keyword-argument or provide a 2-D array with a single row if you intend to specify the same RGB or RGBA value for all points.\n",
      "*c* argument looks like a single numeric RGB or RGBA sequence, which should be avoided as value-mapping will have precedence in case its length matches with *x* & *y*.  Please use the *color* keyword-argument or provide a 2-D array with a single row if you intend to specify the same RGB or RGBA value for all points.\n",
      "*c* argument looks like a single numeric RGB or RGBA sequence, which should be avoided as value-mapping will have precedence in case its length matches with *x* & *y*.  Please use the *color* keyword-argument or provide a 2-D array with a single row if you intend to specify the same RGB or RGBA value for all points.\n",
      "*c* argument looks like a single numeric RGB or RGBA sequence, which should be avoided as value-mapping will have precedence in case its length matches with *x* & *y*.  Please use the *color* keyword-argument or provide a 2-D array with a single row if you intend to specify the same RGB or RGBA value for all points.\n",
      "*c* argument looks like a single numeric RGB or RGBA sequence, which should be avoided as value-mapping will have precedence in case its length matches with *x* & *y*.  Please use the *color* keyword-argument or provide a 2-D array with a single row if you intend to specify the same RGB or RGBA value for all points.\n",
      "*c* argument looks like a single numeric RGB or RGBA sequence, which should be avoided as value-mapping will have precedence in case its length matches with *x* & *y*.  Please use the *color* keyword-argument or provide a 2-D array with a single row if you intend to specify the same RGB or RGBA value for all points.\n",
      "*c* argument looks like a single numeric RGB or RGBA sequence, which should be avoided as value-mapping will have precedence in case its length matches with *x* & *y*.  Please use the *color* keyword-argument or provide a 2-D array with a single row if you intend to specify the same RGB or RGBA value for all points.\n",
      "*c* argument looks like a single numeric RGB or RGBA sequence, which should be avoided as value-mapping will have precedence in case its length matches with *x* & *y*.  Please use the *color* keyword-argument or provide a 2-D array with a single row if you intend to specify the same RGB or RGBA value for all points.\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "*c* argument looks like a single numeric RGB or RGBA sequence, which should be avoided as value-mapping will have precedence in case its length matches with *x* & *y*.  Please use the *color* keyword-argument or provide a 2-D array with a single row if you intend to specify the same RGB or RGBA value for all points.\n",
      "*c* argument looks like a single numeric RGB or RGBA sequence, which should be avoided as value-mapping will have precedence in case its length matches with *x* & *y*.  Please use the *color* keyword-argument or provide a 2-D array with a single row if you intend to specify the same RGB or RGBA value for all points.\n",
      "*c* argument looks like a single numeric RGB or RGBA sequence, which should be avoided as value-mapping will have precedence in case its length matches with *x* & *y*.  Please use the *color* keyword-argument or provide a 2-D array with a single row if you intend to specify the same RGB or RGBA value for all points.\n",
      "*c* argument looks like a single numeric RGB or RGBA sequence, which should be avoided as value-mapping will have precedence in case its length matches with *x* & *y*.  Please use the *color* keyword-argument or provide a 2-D array with a single row if you intend to specify the same RGB or RGBA value for all points.\n",
      "*c* argument looks like a single numeric RGB or RGBA sequence, which should be avoided as value-mapping will have precedence in case its length matches with *x* & *y*.  Please use the *color* keyword-argument or provide a 2-D array with a single row if you intend to specify the same RGB or RGBA value for all points.\n",
      "*c* argument looks like a single numeric RGB or RGBA sequence, which should be avoided as value-mapping will have precedence in case its length matches with *x* & *y*.  Please use the *color* keyword-argument or provide a 2-D array with a single row if you intend to specify the same RGB or RGBA value for all points.\n",
      "*c* argument looks like a single numeric RGB or RGBA sequence, which should be avoided as value-mapping will have precedence in case its length matches with *x* & *y*.  Please use the *color* keyword-argument or provide a 2-D array with a single row if you intend to specify the same RGB or RGBA value for all points.\n",
      "*c* argument looks like a single numeric RGB or RGBA sequence, which should be avoided as value-mapping will have precedence in case its length matches with *x* & *y*.  Please use the *color* keyword-argument or provide a 2-D array with a single row if you intend to specify the same RGB or RGBA value for all points.\n"
     ]
    },
    {
     "data": {
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\n",
      "text/plain": [
       "<Figure size 720x720 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "*c* argument looks like a single numeric RGB or RGBA sequence, which should be avoided as value-mapping will have precedence in case its length matches with *x* & *y*.  Please use the *color* keyword-argument or provide a 2-D array with a single row if you intend to specify the same RGB or RGBA value for all points.\n",
      "*c* argument looks like a single numeric RGB or RGBA sequence, which should be avoided as value-mapping will have precedence in case its length matches with *x* & *y*.  Please use the *color* keyword-argument or provide a 2-D array with a single row if you intend to specify the same RGB or RGBA value for all points.\n",
      "*c* argument looks like a single numeric RGB or RGBA sequence, which should be avoided as value-mapping will have precedence in case its length matches with *x* & *y*.  Please use the *color* keyword-argument or provide a 2-D array with a single row if you intend to specify the same RGB or RGBA value for all points.\n",
      "*c* argument looks like a single numeric RGB or RGBA sequence, which should be avoided as value-mapping will have precedence in case its length matches with *x* & *y*.  Please use the *color* keyword-argument or provide a 2-D array with a single row if you intend to specify the same RGB or RGBA value for all points.\n",
      "*c* argument looks like a single numeric RGB or RGBA sequence, which should be avoided as value-mapping will have precedence in case its length matches with *x* & *y*.  Please use the *color* keyword-argument or provide a 2-D array with a single row if you intend to specify the same RGB or RGBA value for all points.\n",
      "*c* argument looks like a single numeric RGB or RGBA sequence, which should be avoided as value-mapping will have precedence in case its length matches with *x* & *y*.  Please use the *color* keyword-argument or provide a 2-D array with a single row if you intend to specify the same RGB or RGBA value for all points.\n",
      "*c* argument looks like a single numeric RGB or RGBA sequence, which should be avoided as value-mapping will have precedence in case its length matches with *x* & *y*.  Please use the *color* keyword-argument or provide a 2-D array with a single row if you intend to specify the same RGB or RGBA value for all points.\n",
      "*c* argument looks like a single numeric RGB or RGBA sequence, which should be avoided as value-mapping will have precedence in case its length matches with *x* & *y*.  Please use the *color* keyword-argument or provide a 2-D array with a single row if you intend to specify the same RGB or RGBA value for all points.\n",
      "*c* argument looks like a single numeric RGB or RGBA sequence, which should be avoided as value-mapping will have precedence in case its length matches with *x* & *y*.  Please use the *color* keyword-argument or provide a 2-D array with a single row if you intend to specify the same RGB or RGBA value for all points.\n",
      "*c* argument looks like a single numeric RGB or RGBA sequence, which should be avoided as value-mapping will have precedence in case its length matches with *x* & *y*.  Please use the *color* keyword-argument or provide a 2-D array with a single row if you intend to specify the same RGB or RGBA value for all points.\n",
      "*c* argument looks like a single numeric RGB or RGBA sequence, which should be avoided as value-mapping will have precedence in case its length matches with *x* & *y*.  Please use the *color* keyword-argument or provide a 2-D array with a single row if you intend to specify the same RGB or RGBA value for all points.\n",
      "*c* argument looks like a single numeric RGB or RGBA sequence, which should be avoided as value-mapping will have precedence in case its length matches with *x* & *y*.  Please use the *color* keyword-argument or provide a 2-D array with a single row if you intend to specify the same RGB or RGBA value for all points.\n",
      "*c* argument looks like a single numeric RGB or RGBA sequence, which should be avoided as value-mapping will have precedence in case its length matches with *x* & *y*.  Please use the *color* keyword-argument or provide a 2-D array with a single row if you intend to specify the same RGB or RGBA value for all points.\n",
      "*c* argument looks like a single numeric RGB or RGBA sequence, which should be avoided as value-mapping will have precedence in case its length matches with *x* & *y*.  Please use the *color* keyword-argument or provide a 2-D array with a single row if you intend to specify the same RGB or RGBA value for all points.\n",
      "*c* argument looks like a single numeric RGB or RGBA sequence, which should be avoided as value-mapping will have precedence in case its length matches with *x* & *y*.  Please use the *color* keyword-argument or provide a 2-D array with a single row if you intend to specify the same RGB or RGBA value for all points.\n",
      "*c* argument looks like a single numeric RGB or RGBA sequence, which should be avoided as value-mapping will have precedence in case its length matches with *x* & *y*.  Please use the *color* keyword-argument or provide a 2-D array with a single row if you intend to specify the same RGB or RGBA value for all points.\n",
      "*c* argument looks like a single numeric RGB or RGBA sequence, which should be avoided as value-mapping will have precedence in case its length matches with *x* & *y*.  Please use the *color* keyword-argument or provide a 2-D array with a single row if you intend to specify the same RGB or RGBA value for all points.\n",
      "*c* argument looks like a single numeric RGB or RGBA sequence, which should be avoided as value-mapping will have precedence in case its length matches with *x* & *y*.  Please use the *color* keyword-argument or provide a 2-D array with a single row if you intend to specify the same RGB or RGBA value for all points.\n",
      "*c* argument looks like a single numeric RGB or RGBA sequence, which should be avoided as value-mapping will have precedence in case its length matches with *x* & *y*.  Please use the *color* keyword-argument or provide a 2-D array with a single row if you intend to specify the same RGB or RGBA value for all points.\n",
      "*c* argument looks like a single numeric RGB or RGBA sequence, which should be avoided as value-mapping will have precedence in case its length matches with *x* & *y*.  Please use the *color* keyword-argument or provide a 2-D array with a single row if you intend to specify the same RGB or RGBA value for all points.\n",
      "*c* argument looks like a single numeric RGB or RGBA sequence, which should be avoided as value-mapping will have precedence in case its length matches with *x* & *y*.  Please use the *color* keyword-argument or provide a 2-D array with a single row if you intend to specify the same RGB or RGBA value for all points.\n",
      "*c* argument looks like a single numeric RGB or RGBA sequence, which should be avoided as value-mapping will have precedence in case its length matches with *x* & *y*.  Please use the *color* keyword-argument or provide a 2-D array with a single row if you intend to specify the same RGB or RGBA value for all points.\n",
      "*c* argument looks like a single numeric RGB or RGBA sequence, which should be avoided as value-mapping will have precedence in case its length matches with *x* & *y*.  Please use the *color* keyword-argument or provide a 2-D array with a single row if you intend to specify the same RGB or RGBA value for all points.\n",
      "*c* argument looks like a single numeric RGB or RGBA sequence, which should be avoided as value-mapping will have precedence in case its length matches with *x* & *y*.  Please use the *color* keyword-argument or provide a 2-D array with a single row if you intend to specify the same RGB or RGBA value for all points.\n",
      "*c* argument looks like a single numeric RGB or RGBA sequence, which should be avoided as value-mapping will have precedence in case its length matches with *x* & *y*.  Please use the *color* keyword-argument or provide a 2-D array with a single row if you intend to specify the same RGB or RGBA value for all points.\n",
      "*c* argument looks like a single numeric RGB or RGBA sequence, which should be avoided as value-mapping will have precedence in case its length matches with *x* & *y*.  Please use the *color* keyword-argument or provide a 2-D array with a single row if you intend to specify the same RGB or RGBA value for all points.\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "*c* argument looks like a single numeric RGB or RGBA sequence, which should be avoided as value-mapping will have precedence in case its length matches with *x* & *y*.  Please use the *color* keyword-argument or provide a 2-D array with a single row if you intend to specify the same RGB or RGBA value for all points.\n",
      "*c* argument looks like a single numeric RGB or RGBA sequence, which should be avoided as value-mapping will have precedence in case its length matches with *x* & *y*.  Please use the *color* keyword-argument or provide a 2-D array with a single row if you intend to specify the same RGB or RGBA value for all points.\n",
      "*c* argument looks like a single numeric RGB or RGBA sequence, which should be avoided as value-mapping will have precedence in case its length matches with *x* & *y*.  Please use the *color* keyword-argument or provide a 2-D array with a single row if you intend to specify the same RGB or RGBA value for all points.\n",
      "*c* argument looks like a single numeric RGB or RGBA sequence, which should be avoided as value-mapping will have precedence in case its length matches with *x* & *y*.  Please use the *color* keyword-argument or provide a 2-D array with a single row if you intend to specify the same RGB or RGBA value for all points.\n",
      "*c* argument looks like a single numeric RGB or RGBA sequence, which should be avoided as value-mapping will have precedence in case its length matches with *x* & *y*.  Please use the *color* keyword-argument or provide a 2-D array with a single row if you intend to specify the same RGB or RGBA value for all points.\n",
      "*c* argument looks like a single numeric RGB or RGBA sequence, which should be avoided as value-mapping will have precedence in case its length matches with *x* & *y*.  Please use the *color* keyword-argument or provide a 2-D array with a single row if you intend to specify the same RGB or RGBA value for all points.\n",
      "*c* argument looks like a single numeric RGB or RGBA sequence, which should be avoided as value-mapping will have precedence in case its length matches with *x* & *y*.  Please use the *color* keyword-argument or provide a 2-D array with a single row if you intend to specify the same RGB or RGBA value for all points.\n",
      "*c* argument looks like a single numeric RGB or RGBA sequence, which should be avoided as value-mapping will have precedence in case its length matches with *x* & *y*.  Please use the *color* keyword-argument or provide a 2-D array with a single row if you intend to specify the same RGB or RGBA value for all points.\n",
      "*c* argument looks like a single numeric RGB or RGBA sequence, which should be avoided as value-mapping will have precedence in case its length matches with *x* & *y*.  Please use the *color* keyword-argument or provide a 2-D array with a single row if you intend to specify the same RGB or RGBA value for all points.\n",
      "*c* argument looks like a single numeric RGB or RGBA sequence, which should be avoided as value-mapping will have precedence in case its length matches with *x* & *y*.  Please use the *color* keyword-argument or provide a 2-D array with a single row if you intend to specify the same RGB or RGBA value for all points.\n",
      "*c* argument looks like a single numeric RGB or RGBA sequence, which should be avoided as value-mapping will have precedence in case its length matches with *x* & *y*.  Please use the *color* keyword-argument or provide a 2-D array with a single row if you intend to specify the same RGB or RGBA value for all points.\n",
      "*c* argument looks like a single numeric RGB or RGBA sequence, which should be avoided as value-mapping will have precedence in case its length matches with *x* & *y*.  Please use the *color* keyword-argument or provide a 2-D array with a single row if you intend to specify the same RGB or RGBA value for all points.\n",
      "*c* argument looks like a single numeric RGB or RGBA sequence, which should be avoided as value-mapping will have precedence in case its length matches with *x* & *y*.  Please use the *color* keyword-argument or provide a 2-D array with a single row if you intend to specify the same RGB or RGBA value for all points.\n",
      "*c* argument looks like a single numeric RGB or RGBA sequence, which should be avoided as value-mapping will have precedence in case its length matches with *x* & *y*.  Please use the *color* keyword-argument or provide a 2-D array with a single row if you intend to specify the same RGB or RGBA value for all points.\n",
      "*c* argument looks like a single numeric RGB or RGBA sequence, which should be avoided as value-mapping will have precedence in case its length matches with *x* & *y*.  Please use the *color* keyword-argument or provide a 2-D array with a single row if you intend to specify the same RGB or RGBA value for all points.\n",
      "*c* argument looks like a single numeric RGB or RGBA sequence, which should be avoided as value-mapping will have precedence in case its length matches with *x* & *y*.  Please use the *color* keyword-argument or provide a 2-D array with a single row if you intend to specify the same RGB or RGBA value for all points.\n",
      "*c* argument looks like a single numeric RGB or RGBA sequence, which should be avoided as value-mapping will have precedence in case its length matches with *x* & *y*.  Please use the *color* keyword-argument or provide a 2-D array with a single row if you intend to specify the same RGB or RGBA value for all points.\n",
      "*c* argument looks like a single numeric RGB or RGBA sequence, which should be avoided as value-mapping will have precedence in case its length matches with *x* & *y*.  Please use the *color* keyword-argument or provide a 2-D array with a single row if you intend to specify the same RGB or RGBA value for all points.\n",
      "*c* argument looks like a single numeric RGB or RGBA sequence, which should be avoided as value-mapping will have precedence in case its length matches with *x* & *y*.  Please use the *color* keyword-argument or provide a 2-D array with a single row if you intend to specify the same RGB or RGBA value for all points.\n",
      "*c* argument looks like a single numeric RGB or RGBA sequence, which should be avoided as value-mapping will have precedence in case its length matches with *x* & *y*.  Please use the *color* keyword-argument or provide a 2-D array with a single row if you intend to specify the same RGB or RGBA value for all points.\n",
      "*c* argument looks like a single numeric RGB or RGBA sequence, which should be avoided as value-mapping will have precedence in case its length matches with *x* & *y*.  Please use the *color* keyword-argument or provide a 2-D array with a single row if you intend to specify the same RGB or RGBA value for all points.\n",
      "*c* argument looks like a single numeric RGB or RGBA sequence, which should be avoided as value-mapping will have precedence in case its length matches with *x* & *y*.  Please use the *color* keyword-argument or provide a 2-D array with a single row if you intend to specify the same RGB or RGBA value for all points.\n",
      "*c* argument looks like a single numeric RGB or RGBA sequence, which should be avoided as value-mapping will have precedence in case its length matches with *x* & *y*.  Please use the *color* keyword-argument or provide a 2-D array with a single row if you intend to specify the same RGB or RGBA value for all points.\n",
      "*c* argument looks like a single numeric RGB or RGBA sequence, which should be avoided as value-mapping will have precedence in case its length matches with *x* & *y*.  Please use the *color* keyword-argument or provide a 2-D array with a single row if you intend to specify the same RGB or RGBA value for all points.\n",
      "*c* argument looks like a single numeric RGB or RGBA sequence, which should be avoided as value-mapping will have precedence in case its length matches with *x* & *y*.  Please use the *color* keyword-argument or provide a 2-D array with a single row if you intend to specify the same RGB or RGBA value for all points.\n",
      "*c* argument looks like a single numeric RGB or RGBA sequence, which should be avoided as value-mapping will have precedence in case its length matches with *x* & *y*.  Please use the *color* keyword-argument or provide a 2-D array with a single row if you intend to specify the same RGB or RGBA value for all points.\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "*c* argument looks like a single numeric RGB or RGBA sequence, which should be avoided as value-mapping will have precedence in case its length matches with *x* & *y*.  Please use the *color* keyword-argument or provide a 2-D array with a single row if you intend to specify the same RGB or RGBA value for all points.\n",
      "*c* argument looks like a single numeric RGB or RGBA sequence, which should be avoided as value-mapping will have precedence in case its length matches with *x* & *y*.  Please use the *color* keyword-argument or provide a 2-D array with a single row if you intend to specify the same RGB or RGBA value for all points.\n",
      "*c* argument looks like a single numeric RGB or RGBA sequence, which should be avoided as value-mapping will have precedence in case its length matches with *x* & *y*.  Please use the *color* keyword-argument or provide a 2-D array with a single row if you intend to specify the same RGB or RGBA value for all points.\n",
      "*c* argument looks like a single numeric RGB or RGBA sequence, which should be avoided as value-mapping will have precedence in case its length matches with *x* & *y*.  Please use the *color* keyword-argument or provide a 2-D array with a single row if you intend to specify the same RGB or RGBA value for all points.\n",
      "*c* argument looks like a single numeric RGB or RGBA sequence, which should be avoided as value-mapping will have precedence in case its length matches with *x* & *y*.  Please use the *color* keyword-argument or provide a 2-D array with a single row if you intend to specify the same RGB or RGBA value for all points.\n",
      "*c* argument looks like a single numeric RGB or RGBA sequence, which should be avoided as value-mapping will have precedence in case its length matches with *x* & *y*.  Please use the *color* keyword-argument or provide a 2-D array with a single row if you intend to specify the same RGB or RGBA value for all points.\n",
      "*c* argument looks like a single numeric RGB or RGBA sequence, which should be avoided as value-mapping will have precedence in case its length matches with *x* & *y*.  Please use the *color* keyword-argument or provide a 2-D array with a single row if you intend to specify the same RGB or RGBA value for all points.\n",
      "*c* argument looks like a single numeric RGB or RGBA sequence, which should be avoided as value-mapping will have precedence in case its length matches with *x* & *y*.  Please use the *color* keyword-argument or provide a 2-D array with a single row if you intend to specify the same RGB or RGBA value for all points.\n"
     ]
    },
    {
     "data": {
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\n",
      "text/plain": [
       "<Figure size 720x720 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "*c* argument looks like a single numeric RGB or RGBA sequence, which should be avoided as value-mapping will have precedence in case its length matches with *x* & *y*.  Please use the *color* keyword-argument or provide a 2-D array with a single row if you intend to specify the same RGB or RGBA value for all points.\n",
      "*c* argument looks like a single numeric RGB or RGBA sequence, which should be avoided as value-mapping will have precedence in case its length matches with *x* & *y*.  Please use the *color* keyword-argument or provide a 2-D array with a single row if you intend to specify the same RGB or RGBA value for all points.\n",
      "*c* argument looks like a single numeric RGB or RGBA sequence, which should be avoided as value-mapping will have precedence in case its length matches with *x* & *y*.  Please use the *color* keyword-argument or provide a 2-D array with a single row if you intend to specify the same RGB or RGBA value for all points.\n",
      "*c* argument looks like a single numeric RGB or RGBA sequence, which should be avoided as value-mapping will have precedence in case its length matches with *x* & *y*.  Please use the *color* keyword-argument or provide a 2-D array with a single row if you intend to specify the same RGB or RGBA value for all points.\n",
      "*c* argument looks like a single numeric RGB or RGBA sequence, which should be avoided as value-mapping will have precedence in case its length matches with *x* & *y*.  Please use the *color* keyword-argument or provide a 2-D array with a single row if you intend to specify the same RGB or RGBA value for all points.\n",
      "*c* argument looks like a single numeric RGB or RGBA sequence, which should be avoided as value-mapping will have precedence in case its length matches with *x* & *y*.  Please use the *color* keyword-argument or provide a 2-D array with a single row if you intend to specify the same RGB or RGBA value for all points.\n",
      "*c* argument looks like a single numeric RGB or RGBA sequence, which should be avoided as value-mapping will have precedence in case its length matches with *x* & *y*.  Please use the *color* keyword-argument or provide a 2-D array with a single row if you intend to specify the same RGB or RGBA value for all points.\n",
      "*c* argument looks like a single numeric RGB or RGBA sequence, which should be avoided as value-mapping will have precedence in case its length matches with *x* & *y*.  Please use the *color* keyword-argument or provide a 2-D array with a single row if you intend to specify the same RGB or RGBA value for all points.\n",
      "*c* argument looks like a single numeric RGB or RGBA sequence, which should be avoided as value-mapping will have precedence in case its length matches with *x* & *y*.  Please use the *color* keyword-argument or provide a 2-D array with a single row if you intend to specify the same RGB or RGBA value for all points.\n",
      "*c* argument looks like a single numeric RGB or RGBA sequence, which should be avoided as value-mapping will have precedence in case its length matches with *x* & *y*.  Please use the *color* keyword-argument or provide a 2-D array with a single row if you intend to specify the same RGB or RGBA value for all points.\n",
      "*c* argument looks like a single numeric RGB or RGBA sequence, which should be avoided as value-mapping will have precedence in case its length matches with *x* & *y*.  Please use the *color* keyword-argument or provide a 2-D array with a single row if you intend to specify the same RGB or RGBA value for all points.\n",
      "*c* argument looks like a single numeric RGB or RGBA sequence, which should be avoided as value-mapping will have precedence in case its length matches with *x* & *y*.  Please use the *color* keyword-argument or provide a 2-D array with a single row if you intend to specify the same RGB or RGBA value for all points.\n",
      "*c* argument looks like a single numeric RGB or RGBA sequence, which should be avoided as value-mapping will have precedence in case its length matches with *x* & *y*.  Please use the *color* keyword-argument or provide a 2-D array with a single row if you intend to specify the same RGB or RGBA value for all points.\n",
      "*c* argument looks like a single numeric RGB or RGBA sequence, which should be avoided as value-mapping will have precedence in case its length matches with *x* & *y*.  Please use the *color* keyword-argument or provide a 2-D array with a single row if you intend to specify the same RGB or RGBA value for all points.\n",
      "*c* argument looks like a single numeric RGB or RGBA sequence, which should be avoided as value-mapping will have precedence in case its length matches with *x* & *y*.  Please use the *color* keyword-argument or provide a 2-D array with a single row if you intend to specify the same RGB or RGBA value for all points.\n",
      "*c* argument looks like a single numeric RGB or RGBA sequence, which should be avoided as value-mapping will have precedence in case its length matches with *x* & *y*.  Please use the *color* keyword-argument or provide a 2-D array with a single row if you intend to specify the same RGB or RGBA value for all points.\n",
      "*c* argument looks like a single numeric RGB or RGBA sequence, which should be avoided as value-mapping will have precedence in case its length matches with *x* & *y*.  Please use the *color* keyword-argument or provide a 2-D array with a single row if you intend to specify the same RGB or RGBA value for all points.\n",
      "*c* argument looks like a single numeric RGB or RGBA sequence, which should be avoided as value-mapping will have precedence in case its length matches with *x* & *y*.  Please use the *color* keyword-argument or provide a 2-D array with a single row if you intend to specify the same RGB or RGBA value for all points.\n",
      "*c* argument looks like a single numeric RGB or RGBA sequence, which should be avoided as value-mapping will have precedence in case its length matches with *x* & *y*.  Please use the *color* keyword-argument or provide a 2-D array with a single row if you intend to specify the same RGB or RGBA value for all points.\n",
      "*c* argument looks like a single numeric RGB or RGBA sequence, which should be avoided as value-mapping will have precedence in case its length matches with *x* & *y*.  Please use the *color* keyword-argument or provide a 2-D array with a single row if you intend to specify the same RGB or RGBA value for all points.\n",
      "*c* argument looks like a single numeric RGB or RGBA sequence, which should be avoided as value-mapping will have precedence in case its length matches with *x* & *y*.  Please use the *color* keyword-argument or provide a 2-D array with a single row if you intend to specify the same RGB or RGBA value for all points.\n",
      "*c* argument looks like a single numeric RGB or RGBA sequence, which should be avoided as value-mapping will have precedence in case its length matches with *x* & *y*.  Please use the *color* keyword-argument or provide a 2-D array with a single row if you intend to specify the same RGB or RGBA value for all points.\n",
      "*c* argument looks like a single numeric RGB or RGBA sequence, which should be avoided as value-mapping will have precedence in case its length matches with *x* & *y*.  Please use the *color* keyword-argument or provide a 2-D array with a single row if you intend to specify the same RGB or RGBA value for all points.\n",
      "*c* argument looks like a single numeric RGB or RGBA sequence, which should be avoided as value-mapping will have precedence in case its length matches with *x* & *y*.  Please use the *color* keyword-argument or provide a 2-D array with a single row if you intend to specify the same RGB or RGBA value for all points.\n",
      "*c* argument looks like a single numeric RGB or RGBA sequence, which should be avoided as value-mapping will have precedence in case its length matches with *x* & *y*.  Please use the *color* keyword-argument or provide a 2-D array with a single row if you intend to specify the same RGB or RGBA value for all points.\n",
      "*c* argument looks like a single numeric RGB or RGBA sequence, which should be avoided as value-mapping will have precedence in case its length matches with *x* & *y*.  Please use the *color* keyword-argument or provide a 2-D array with a single row if you intend to specify the same RGB or RGBA value for all points.\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "*c* argument looks like a single numeric RGB or RGBA sequence, which should be avoided as value-mapping will have precedence in case its length matches with *x* & *y*.  Please use the *color* keyword-argument or provide a 2-D array with a single row if you intend to specify the same RGB or RGBA value for all points.\n",
      "*c* argument looks like a single numeric RGB or RGBA sequence, which should be avoided as value-mapping will have precedence in case its length matches with *x* & *y*.  Please use the *color* keyword-argument or provide a 2-D array with a single row if you intend to specify the same RGB or RGBA value for all points.\n",
      "*c* argument looks like a single numeric RGB or RGBA sequence, which should be avoided as value-mapping will have precedence in case its length matches with *x* & *y*.  Please use the *color* keyword-argument or provide a 2-D array with a single row if you intend to specify the same RGB or RGBA value for all points.\n",
      "*c* argument looks like a single numeric RGB or RGBA sequence, which should be avoided as value-mapping will have precedence in case its length matches with *x* & *y*.  Please use the *color* keyword-argument or provide a 2-D array with a single row if you intend to specify the same RGB or RGBA value for all points.\n",
      "*c* argument looks like a single numeric RGB or RGBA sequence, which should be avoided as value-mapping will have precedence in case its length matches with *x* & *y*.  Please use the *color* keyword-argument or provide a 2-D array with a single row if you intend to specify the same RGB or RGBA value for all points.\n",
      "*c* argument looks like a single numeric RGB or RGBA sequence, which should be avoided as value-mapping will have precedence in case its length matches with *x* & *y*.  Please use the *color* keyword-argument or provide a 2-D array with a single row if you intend to specify the same RGB or RGBA value for all points.\n",
      "*c* argument looks like a single numeric RGB or RGBA sequence, which should be avoided as value-mapping will have precedence in case its length matches with *x* & *y*.  Please use the *color* keyword-argument or provide a 2-D array with a single row if you intend to specify the same RGB or RGBA value for all points.\n",
      "*c* argument looks like a single numeric RGB or RGBA sequence, which should be avoided as value-mapping will have precedence in case its length matches with *x* & *y*.  Please use the *color* keyword-argument or provide a 2-D array with a single row if you intend to specify the same RGB or RGBA value for all points.\n",
      "*c* argument looks like a single numeric RGB or RGBA sequence, which should be avoided as value-mapping will have precedence in case its length matches with *x* & *y*.  Please use the *color* keyword-argument or provide a 2-D array with a single row if you intend to specify the same RGB or RGBA value for all points.\n",
      "*c* argument looks like a single numeric RGB or RGBA sequence, which should be avoided as value-mapping will have precedence in case its length matches with *x* & *y*.  Please use the *color* keyword-argument or provide a 2-D array with a single row if you intend to specify the same RGB or RGBA value for all points.\n",
      "*c* argument looks like a single numeric RGB or RGBA sequence, which should be avoided as value-mapping will have precedence in case its length matches with *x* & *y*.  Please use the *color* keyword-argument or provide a 2-D array with a single row if you intend to specify the same RGB or RGBA value for all points.\n",
      "*c* argument looks like a single numeric RGB or RGBA sequence, which should be avoided as value-mapping will have precedence in case its length matches with *x* & *y*.  Please use the *color* keyword-argument or provide a 2-D array with a single row if you intend to specify the same RGB or RGBA value for all points.\n",
      "*c* argument looks like a single numeric RGB or RGBA sequence, which should be avoided as value-mapping will have precedence in case its length matches with *x* & *y*.  Please use the *color* keyword-argument or provide a 2-D array with a single row if you intend to specify the same RGB or RGBA value for all points.\n",
      "*c* argument looks like a single numeric RGB or RGBA sequence, which should be avoided as value-mapping will have precedence in case its length matches with *x* & *y*.  Please use the *color* keyword-argument or provide a 2-D array with a single row if you intend to specify the same RGB or RGBA value for all points.\n",
      "*c* argument looks like a single numeric RGB or RGBA sequence, which should be avoided as value-mapping will have precedence in case its length matches with *x* & *y*.  Please use the *color* keyword-argument or provide a 2-D array with a single row if you intend to specify the same RGB or RGBA value for all points.\n",
      "*c* argument looks like a single numeric RGB or RGBA sequence, which should be avoided as value-mapping will have precedence in case its length matches with *x* & *y*.  Please use the *color* keyword-argument or provide a 2-D array with a single row if you intend to specify the same RGB or RGBA value for all points.\n",
      "*c* argument looks like a single numeric RGB or RGBA sequence, which should be avoided as value-mapping will have precedence in case its length matches with *x* & *y*.  Please use the *color* keyword-argument or provide a 2-D array with a single row if you intend to specify the same RGB or RGBA value for all points.\n",
      "*c* argument looks like a single numeric RGB or RGBA sequence, which should be avoided as value-mapping will have precedence in case its length matches with *x* & *y*.  Please use the *color* keyword-argument or provide a 2-D array with a single row if you intend to specify the same RGB or RGBA value for all points.\n",
      "*c* argument looks like a single numeric RGB or RGBA sequence, which should be avoided as value-mapping will have precedence in case its length matches with *x* & *y*.  Please use the *color* keyword-argument or provide a 2-D array with a single row if you intend to specify the same RGB or RGBA value for all points.\n",
      "*c* argument looks like a single numeric RGB or RGBA sequence, which should be avoided as value-mapping will have precedence in case its length matches with *x* & *y*.  Please use the *color* keyword-argument or provide a 2-D array with a single row if you intend to specify the same RGB or RGBA value for all points.\n",
      "*c* argument looks like a single numeric RGB or RGBA sequence, which should be avoided as value-mapping will have precedence in case its length matches with *x* & *y*.  Please use the *color* keyword-argument or provide a 2-D array with a single row if you intend to specify the same RGB or RGBA value for all points.\n",
      "*c* argument looks like a single numeric RGB or RGBA sequence, which should be avoided as value-mapping will have precedence in case its length matches with *x* & *y*.  Please use the *color* keyword-argument or provide a 2-D array with a single row if you intend to specify the same RGB or RGBA value for all points.\n",
      "*c* argument looks like a single numeric RGB or RGBA sequence, which should be avoided as value-mapping will have precedence in case its length matches with *x* & *y*.  Please use the *color* keyword-argument or provide a 2-D array with a single row if you intend to specify the same RGB or RGBA value for all points.\n",
      "*c* argument looks like a single numeric RGB or RGBA sequence, which should be avoided as value-mapping will have precedence in case its length matches with *x* & *y*.  Please use the *color* keyword-argument or provide a 2-D array with a single row if you intend to specify the same RGB or RGBA value for all points.\n",
      "*c* argument looks like a single numeric RGB or RGBA sequence, which should be avoided as value-mapping will have precedence in case its length matches with *x* & *y*.  Please use the *color* keyword-argument or provide a 2-D array with a single row if you intend to specify the same RGB or RGBA value for all points.\n",
      "*c* argument looks like a single numeric RGB or RGBA sequence, which should be avoided as value-mapping will have precedence in case its length matches with *x* & *y*.  Please use the *color* keyword-argument or provide a 2-D array with a single row if you intend to specify the same RGB or RGBA value for all points.\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "*c* argument looks like a single numeric RGB or RGBA sequence, which should be avoided as value-mapping will have precedence in case its length matches with *x* & *y*.  Please use the *color* keyword-argument or provide a 2-D array with a single row if you intend to specify the same RGB or RGBA value for all points.\n",
      "*c* argument looks like a single numeric RGB or RGBA sequence, which should be avoided as value-mapping will have precedence in case its length matches with *x* & *y*.  Please use the *color* keyword-argument or provide a 2-D array with a single row if you intend to specify the same RGB or RGBA value for all points.\n",
      "*c* argument looks like a single numeric RGB or RGBA sequence, which should be avoided as value-mapping will have precedence in case its length matches with *x* & *y*.  Please use the *color* keyword-argument or provide a 2-D array with a single row if you intend to specify the same RGB or RGBA value for all points.\n",
      "*c* argument looks like a single numeric RGB or RGBA sequence, which should be avoided as value-mapping will have precedence in case its length matches with *x* & *y*.  Please use the *color* keyword-argument or provide a 2-D array with a single row if you intend to specify the same RGB or RGBA value for all points.\n",
      "*c* argument looks like a single numeric RGB or RGBA sequence, which should be avoided as value-mapping will have precedence in case its length matches with *x* & *y*.  Please use the *color* keyword-argument or provide a 2-D array with a single row if you intend to specify the same RGB or RGBA value for all points.\n",
      "*c* argument looks like a single numeric RGB or RGBA sequence, which should be avoided as value-mapping will have precedence in case its length matches with *x* & *y*.  Please use the *color* keyword-argument or provide a 2-D array with a single row if you intend to specify the same RGB or RGBA value for all points.\n",
      "*c* argument looks like a single numeric RGB or RGBA sequence, which should be avoided as value-mapping will have precedence in case its length matches with *x* & *y*.  Please use the *color* keyword-argument or provide a 2-D array with a single row if you intend to specify the same RGB or RGBA value for all points.\n",
      "*c* argument looks like a single numeric RGB or RGBA sequence, which should be avoided as value-mapping will have precedence in case its length matches with *x* & *y*.  Please use the *color* keyword-argument or provide a 2-D array with a single row if you intend to specify the same RGB or RGBA value for all points.\n"
     ]
    },
    {
     "data": {
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\n",
      "text/plain": [
       "<Figure size 720x720 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "*c* argument looks like a single numeric RGB or RGBA sequence, which should be avoided as value-mapping will have precedence in case its length matches with *x* & *y*.  Please use the *color* keyword-argument or provide a 2-D array with a single row if you intend to specify the same RGB or RGBA value for all points.\n",
      "*c* argument looks like a single numeric RGB or RGBA sequence, which should be avoided as value-mapping will have precedence in case its length matches with *x* & *y*.  Please use the *color* keyword-argument or provide a 2-D array with a single row if you intend to specify the same RGB or RGBA value for all points.\n",
      "*c* argument looks like a single numeric RGB or RGBA sequence, which should be avoided as value-mapping will have precedence in case its length matches with *x* & *y*.  Please use the *color* keyword-argument or provide a 2-D array with a single row if you intend to specify the same RGB or RGBA value for all points.\n",
      "*c* argument looks like a single numeric RGB or RGBA sequence, which should be avoided as value-mapping will have precedence in case its length matches with *x* & *y*.  Please use the *color* keyword-argument or provide a 2-D array with a single row if you intend to specify the same RGB or RGBA value for all points.\n",
      "*c* argument looks like a single numeric RGB or RGBA sequence, which should be avoided as value-mapping will have precedence in case its length matches with *x* & *y*.  Please use the *color* keyword-argument or provide a 2-D array with a single row if you intend to specify the same RGB or RGBA value for all points.\n",
      "*c* argument looks like a single numeric RGB or RGBA sequence, which should be avoided as value-mapping will have precedence in case its length matches with *x* & *y*.  Please use the *color* keyword-argument or provide a 2-D array with a single row if you intend to specify the same RGB or RGBA value for all points.\n",
      "*c* argument looks like a single numeric RGB or RGBA sequence, which should be avoided as value-mapping will have precedence in case its length matches with *x* & *y*.  Please use the *color* keyword-argument or provide a 2-D array with a single row if you intend to specify the same RGB or RGBA value for all points.\n",
      "*c* argument looks like a single numeric RGB or RGBA sequence, which should be avoided as value-mapping will have precedence in case its length matches with *x* & *y*.  Please use the *color* keyword-argument or provide a 2-D array with a single row if you intend to specify the same RGB or RGBA value for all points.\n",
      "*c* argument looks like a single numeric RGB or RGBA sequence, which should be avoided as value-mapping will have precedence in case its length matches with *x* & *y*.  Please use the *color* keyword-argument or provide a 2-D array with a single row if you intend to specify the same RGB or RGBA value for all points.\n",
      "*c* argument looks like a single numeric RGB or RGBA sequence, which should be avoided as value-mapping will have precedence in case its length matches with *x* & *y*.  Please use the *color* keyword-argument or provide a 2-D array with a single row if you intend to specify the same RGB or RGBA value for all points.\n",
      "*c* argument looks like a single numeric RGB or RGBA sequence, which should be avoided as value-mapping will have precedence in case its length matches with *x* & *y*.  Please use the *color* keyword-argument or provide a 2-D array with a single row if you intend to specify the same RGB or RGBA value for all points.\n",
      "*c* argument looks like a single numeric RGB or RGBA sequence, which should be avoided as value-mapping will have precedence in case its length matches with *x* & *y*.  Please use the *color* keyword-argument or provide a 2-D array with a single row if you intend to specify the same RGB or RGBA value for all points.\n",
      "*c* argument looks like a single numeric RGB or RGBA sequence, which should be avoided as value-mapping will have precedence in case its length matches with *x* & *y*.  Please use the *color* keyword-argument or provide a 2-D array with a single row if you intend to specify the same RGB or RGBA value for all points.\n",
      "*c* argument looks like a single numeric RGB or RGBA sequence, which should be avoided as value-mapping will have precedence in case its length matches with *x* & *y*.  Please use the *color* keyword-argument or provide a 2-D array with a single row if you intend to specify the same RGB or RGBA value for all points.\n",
      "*c* argument looks like a single numeric RGB or RGBA sequence, which should be avoided as value-mapping will have precedence in case its length matches with *x* & *y*.  Please use the *color* keyword-argument or provide a 2-D array with a single row if you intend to specify the same RGB or RGBA value for all points.\n",
      "*c* argument looks like a single numeric RGB or RGBA sequence, which should be avoided as value-mapping will have precedence in case its length matches with *x* & *y*.  Please use the *color* keyword-argument or provide a 2-D array with a single row if you intend to specify the same RGB or RGBA value for all points.\n",
      "*c* argument looks like a single numeric RGB or RGBA sequence, which should be avoided as value-mapping will have precedence in case its length matches with *x* & *y*.  Please use the *color* keyword-argument or provide a 2-D array with a single row if you intend to specify the same RGB or RGBA value for all points.\n",
      "*c* argument looks like a single numeric RGB or RGBA sequence, which should be avoided as value-mapping will have precedence in case its length matches with *x* & *y*.  Please use the *color* keyword-argument or provide a 2-D array with a single row if you intend to specify the same RGB or RGBA value for all points.\n",
      "*c* argument looks like a single numeric RGB or RGBA sequence, which should be avoided as value-mapping will have precedence in case its length matches with *x* & *y*.  Please use the *color* keyword-argument or provide a 2-D array with a single row if you intend to specify the same RGB or RGBA value for all points.\n",
      "*c* argument looks like a single numeric RGB or RGBA sequence, which should be avoided as value-mapping will have precedence in case its length matches with *x* & *y*.  Please use the *color* keyword-argument or provide a 2-D array with a single row if you intend to specify the same RGB or RGBA value for all points.\n",
      "*c* argument looks like a single numeric RGB or RGBA sequence, which should be avoided as value-mapping will have precedence in case its length matches with *x* & *y*.  Please use the *color* keyword-argument or provide a 2-D array with a single row if you intend to specify the same RGB or RGBA value for all points.\n",
      "*c* argument looks like a single numeric RGB or RGBA sequence, which should be avoided as value-mapping will have precedence in case its length matches with *x* & *y*.  Please use the *color* keyword-argument or provide a 2-D array with a single row if you intend to specify the same RGB or RGBA value for all points.\n",
      "*c* argument looks like a single numeric RGB or RGBA sequence, which should be avoided as value-mapping will have precedence in case its length matches with *x* & *y*.  Please use the *color* keyword-argument or provide a 2-D array with a single row if you intend to specify the same RGB or RGBA value for all points.\n",
      "*c* argument looks like a single numeric RGB or RGBA sequence, which should be avoided as value-mapping will have precedence in case its length matches with *x* & *y*.  Please use the *color* keyword-argument or provide a 2-D array with a single row if you intend to specify the same RGB or RGBA value for all points.\n",
      "*c* argument looks like a single numeric RGB or RGBA sequence, which should be avoided as value-mapping will have precedence in case its length matches with *x* & *y*.  Please use the *color* keyword-argument or provide a 2-D array with a single row if you intend to specify the same RGB or RGBA value for all points.\n",
      "*c* argument looks like a single numeric RGB or RGBA sequence, which should be avoided as value-mapping will have precedence in case its length matches with *x* & *y*.  Please use the *color* keyword-argument or provide a 2-D array with a single row if you intend to specify the same RGB or RGBA value for all points.\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "*c* argument looks like a single numeric RGB or RGBA sequence, which should be avoided as value-mapping will have precedence in case its length matches with *x* & *y*.  Please use the *color* keyword-argument or provide a 2-D array with a single row if you intend to specify the same RGB or RGBA value for all points.\n",
      "*c* argument looks like a single numeric RGB or RGBA sequence, which should be avoided as value-mapping will have precedence in case its length matches with *x* & *y*.  Please use the *color* keyword-argument or provide a 2-D array with a single row if you intend to specify the same RGB or RGBA value for all points.\n",
      "*c* argument looks like a single numeric RGB or RGBA sequence, which should be avoided as value-mapping will have precedence in case its length matches with *x* & *y*.  Please use the *color* keyword-argument or provide a 2-D array with a single row if you intend to specify the same RGB or RGBA value for all points.\n",
      "*c* argument looks like a single numeric RGB or RGBA sequence, which should be avoided as value-mapping will have precedence in case its length matches with *x* & *y*.  Please use the *color* keyword-argument or provide a 2-D array with a single row if you intend to specify the same RGB or RGBA value for all points.\n",
      "*c* argument looks like a single numeric RGB or RGBA sequence, which should be avoided as value-mapping will have precedence in case its length matches with *x* & *y*.  Please use the *color* keyword-argument or provide a 2-D array with a single row if you intend to specify the same RGB or RGBA value for all points.\n",
      "*c* argument looks like a single numeric RGB or RGBA sequence, which should be avoided as value-mapping will have precedence in case its length matches with *x* & *y*.  Please use the *color* keyword-argument or provide a 2-D array with a single row if you intend to specify the same RGB or RGBA value for all points.\n",
      "*c* argument looks like a single numeric RGB or RGBA sequence, which should be avoided as value-mapping will have precedence in case its length matches with *x* & *y*.  Please use the *color* keyword-argument or provide a 2-D array with a single row if you intend to specify the same RGB or RGBA value for all points.\n",
      "*c* argument looks like a single numeric RGB or RGBA sequence, which should be avoided as value-mapping will have precedence in case its length matches with *x* & *y*.  Please use the *color* keyword-argument or provide a 2-D array with a single row if you intend to specify the same RGB or RGBA value for all points.\n",
      "*c* argument looks like a single numeric RGB or RGBA sequence, which should be avoided as value-mapping will have precedence in case its length matches with *x* & *y*.  Please use the *color* keyword-argument or provide a 2-D array with a single row if you intend to specify the same RGB or RGBA value for all points.\n",
      "*c* argument looks like a single numeric RGB or RGBA sequence, which should be avoided as value-mapping will have precedence in case its length matches with *x* & *y*.  Please use the *color* keyword-argument or provide a 2-D array with a single row if you intend to specify the same RGB or RGBA value for all points.\n",
      "*c* argument looks like a single numeric RGB or RGBA sequence, which should be avoided as value-mapping will have precedence in case its length matches with *x* & *y*.  Please use the *color* keyword-argument or provide a 2-D array with a single row if you intend to specify the same RGB or RGBA value for all points.\n",
      "*c* argument looks like a single numeric RGB or RGBA sequence, which should be avoided as value-mapping will have precedence in case its length matches with *x* & *y*.  Please use the *color* keyword-argument or provide a 2-D array with a single row if you intend to specify the same RGB or RGBA value for all points.\n",
      "*c* argument looks like a single numeric RGB or RGBA sequence, which should be avoided as value-mapping will have precedence in case its length matches with *x* & *y*.  Please use the *color* keyword-argument or provide a 2-D array with a single row if you intend to specify the same RGB or RGBA value for all points.\n",
      "*c* argument looks like a single numeric RGB or RGBA sequence, which should be avoided as value-mapping will have precedence in case its length matches with *x* & *y*.  Please use the *color* keyword-argument or provide a 2-D array with a single row if you intend to specify the same RGB or RGBA value for all points.\n",
      "*c* argument looks like a single numeric RGB or RGBA sequence, which should be avoided as value-mapping will have precedence in case its length matches with *x* & *y*.  Please use the *color* keyword-argument or provide a 2-D array with a single row if you intend to specify the same RGB or RGBA value for all points.\n",
      "*c* argument looks like a single numeric RGB or RGBA sequence, which should be avoided as value-mapping will have precedence in case its length matches with *x* & *y*.  Please use the *color* keyword-argument or provide a 2-D array with a single row if you intend to specify the same RGB or RGBA value for all points.\n",
      "*c* argument looks like a single numeric RGB or RGBA sequence, which should be avoided as value-mapping will have precedence in case its length matches with *x* & *y*.  Please use the *color* keyword-argument or provide a 2-D array with a single row if you intend to specify the same RGB or RGBA value for all points.\n",
      "*c* argument looks like a single numeric RGB or RGBA sequence, which should be avoided as value-mapping will have precedence in case its length matches with *x* & *y*.  Please use the *color* keyword-argument or provide a 2-D array with a single row if you intend to specify the same RGB or RGBA value for all points.\n",
      "*c* argument looks like a single numeric RGB or RGBA sequence, which should be avoided as value-mapping will have precedence in case its length matches with *x* & *y*.  Please use the *color* keyword-argument or provide a 2-D array with a single row if you intend to specify the same RGB or RGBA value for all points.\n",
      "*c* argument looks like a single numeric RGB or RGBA sequence, which should be avoided as value-mapping will have precedence in case its length matches with *x* & *y*.  Please use the *color* keyword-argument or provide a 2-D array with a single row if you intend to specify the same RGB or RGBA value for all points.\n",
      "*c* argument looks like a single numeric RGB or RGBA sequence, which should be avoided as value-mapping will have precedence in case its length matches with *x* & *y*.  Please use the *color* keyword-argument or provide a 2-D array with a single row if you intend to specify the same RGB or RGBA value for all points.\n",
      "*c* argument looks like a single numeric RGB or RGBA sequence, which should be avoided as value-mapping will have precedence in case its length matches with *x* & *y*.  Please use the *color* keyword-argument or provide a 2-D array with a single row if you intend to specify the same RGB or RGBA value for all points.\n",
      "*c* argument looks like a single numeric RGB or RGBA sequence, which should be avoided as value-mapping will have precedence in case its length matches with *x* & *y*.  Please use the *color* keyword-argument or provide a 2-D array with a single row if you intend to specify the same RGB or RGBA value for all points.\n",
      "*c* argument looks like a single numeric RGB or RGBA sequence, which should be avoided as value-mapping will have precedence in case its length matches with *x* & *y*.  Please use the *color* keyword-argument or provide a 2-D array with a single row if you intend to specify the same RGB or RGBA value for all points.\n",
      "*c* argument looks like a single numeric RGB or RGBA sequence, which should be avoided as value-mapping will have precedence in case its length matches with *x* & *y*.  Please use the *color* keyword-argument or provide a 2-D array with a single row if you intend to specify the same RGB or RGBA value for all points.\n",
      "*c* argument looks like a single numeric RGB or RGBA sequence, which should be avoided as value-mapping will have precedence in case its length matches with *x* & *y*.  Please use the *color* keyword-argument or provide a 2-D array with a single row if you intend to specify the same RGB or RGBA value for all points.\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "*c* argument looks like a single numeric RGB or RGBA sequence, which should be avoided as value-mapping will have precedence in case its length matches with *x* & *y*.  Please use the *color* keyword-argument or provide a 2-D array with a single row if you intend to specify the same RGB or RGBA value for all points.\n",
      "*c* argument looks like a single numeric RGB or RGBA sequence, which should be avoided as value-mapping will have precedence in case its length matches with *x* & *y*.  Please use the *color* keyword-argument or provide a 2-D array with a single row if you intend to specify the same RGB or RGBA value for all points.\n",
      "*c* argument looks like a single numeric RGB or RGBA sequence, which should be avoided as value-mapping will have precedence in case its length matches with *x* & *y*.  Please use the *color* keyword-argument or provide a 2-D array with a single row if you intend to specify the same RGB or RGBA value for all points.\n",
      "*c* argument looks like a single numeric RGB or RGBA sequence, which should be avoided as value-mapping will have precedence in case its length matches with *x* & *y*.  Please use the *color* keyword-argument or provide a 2-D array with a single row if you intend to specify the same RGB or RGBA value for all points.\n",
      "*c* argument looks like a single numeric RGB or RGBA sequence, which should be avoided as value-mapping will have precedence in case its length matches with *x* & *y*.  Please use the *color* keyword-argument or provide a 2-D array with a single row if you intend to specify the same RGB or RGBA value for all points.\n",
      "*c* argument looks like a single numeric RGB or RGBA sequence, which should be avoided as value-mapping will have precedence in case its length matches with *x* & *y*.  Please use the *color* keyword-argument or provide a 2-D array with a single row if you intend to specify the same RGB or RGBA value for all points.\n",
      "*c* argument looks like a single numeric RGB or RGBA sequence, which should be avoided as value-mapping will have precedence in case its length matches with *x* & *y*.  Please use the *color* keyword-argument or provide a 2-D array with a single row if you intend to specify the same RGB or RGBA value for all points.\n",
      "*c* argument looks like a single numeric RGB or RGBA sequence, which should be avoided as value-mapping will have precedence in case its length matches with *x* & *y*.  Please use the *color* keyword-argument or provide a 2-D array with a single row if you intend to specify the same RGB or RGBA value for all points.\n"
     ]
    },
    {
     "data": {
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Xn0p6ucb3VtJrxpg5xpjBiZcIAN/GniwAQVfrcqGkvY36s3t9ojFnyoWsU2rcfbK1drUxppWk140xS6y17+zltYMlDZakA1K5BgAgEuhkAQi6eDpZqyTtX+P7/SSt3vNJxphOkh6V1MNauyl2v7V29e7b9ZKmyS0/fou1drS1tthaW9yyZcv4fwIAGae83P2ikwUgyOIJWbMktTfGHGyMyZPUR9LzNZ9gjDlA0jOS+ltrP65xf74xpjD2taRzJS1MVvEAMlNpqbtNRyfL7rVvDwC1q3W50FpbaYwZJulVSdmSHrfWLjLGDN39+ChJv5XUQtJDxh0kVmmtLZbUWtK03fflSJporX0lJT8JgIwRW8ZLdSeruloqK/v6mB0ASEQ8e7JkrZ0uafoe942q8fXVkq7ey+tWSCra834AqI90hKzYIdElJYQsAHXDxHcAoZOuTpbEviwAdUfIAhA66e5kAUBdELIAhA6dLABhQMgCEDrpDFmxKxkBIFGELAChk46QlZ//zc8CgEQRsgCETjrmZNHJAlBfhCwAoRPrLsW6TakQC1l0sgDUFSELQOiUlEgNGkg5cU36qxuWCwHUFyELQOik+nBo6esBpCwXAqgrQhaA0ElHyMrKct0sOlkA6oqQBSB00hGyJEIWgPohZAEInXSFrIIClgsB1B0hC0DopDNk0ckCUFeELAChw3IhgDAgZAEIHZYLAYQBIQtA6LBcCCAMCFkAQoflQgBhQMgCECrV1W4Jj+VCAEFHyAIQKjt2uFuWCwEEHSELQKik43DomPx8qaxMqqpK/WcBiB5CFoBQiYWswsLUf1asWxbrngFAIghZAEIlFrLStVxY8zMBIBGELAChks6QFVuSZPM7gLogZAEIFTpZAMKCkAUgVAhZAMKCkAUgVFguBBAWhCwAoUInC0BYELIAhAohC0BYELIAhEpJiZSdLTVokPrPYrkQQH0QsgCESuxwaGNS/1l0sgDUByELQKjEQlY6NGrkwhwhC0BdELIAhEo6Q1ZWltS4McuFAOqGkAUgVNIZsiT3WXSyANQFIQtAqBCyAIQFIQtAqKQ7ZOXns1wIoG4IWQBChU4WgLAgZAEIFUIWgLAgZAEIFZYLAYQFIQtAaFhLJwtAeBCyAITGrl1SVRUhC0A4ELIAhEY6D4eOYbkQQF0RsgCEho+QVVAglZW5DhoAJIKQBSA0fIUsiW4WgMQRsgCEhq/lQomQBSBxhCwAoeGzk8XmdwCJImQBCA1CFoAwIWQBCA2WCwGECSELQGjQyQIQJoQsAKFByAIQJoQsAKERCzqNG6fvM1kuBFBXhCwAoVFS4kJPVhr/5KKTBaCuCFkAQiPdh0NLhCwAdUfIAhAaPkJWo0aSMSwXAkgcIQtAaPgIWca4JUo6WQASRcgCEBo+QpbkPpOQBSBRhCwAoVFSIhUWpv9z8/NZLgSQuLhCljHmfGPMUmPMcmPM8L083s8YM3/3r/eMMUXxvhYA4kUnC0CY1BqyjDHZkh6UdIGkjpL6GmM67vG0TyWdbq3tJOn3kkYn8FoAiMv27f5CFp0sAImKp5PVVdJya+0Ka225pMmSetR8grX2PWvtlt3fzpS0X7yvBYB4+epksfEdQF3EE7LaSfqixverdt/3XX4q6eU6vhYAvhPLhQDCJCeO55i93Gf3+kRjzpQLWafU4bWDJQ2WpAMOOCCOsgBkkvJy98tXJ4vlQgCJiqeTtUrS/jW+30/S6j2fZIzpJOlRST2stZsSea0kWWtHW2uLrbXFLVu2jKd2ABkkFnLoZAEIi3hC1ixJ7Y0xBxtj8iT1kfR8zScYYw6Q9Iyk/tbajxN5LQDEIxZyCFkAwqLW5UJrbaUxZpikVyVlS3rcWrvIGDN09+OjJP1WUgtJDxljJKlyd1dqr69N0c8CIMJ8hqz8fGnnTqmqSsrOTv/nAwinePZkyVo7XdL0Pe4bVePrqyVdHe9rASBRvjtZkluybNIk/Z8PIJyY+A4gFIIQslgyBJAIQhaAUPC9XChxhSGAxBCyAIQCnSwAYUPIAhAKhCwAYUPIAhAKLBcCCBtCFoBQiIWsWOBJJzpZAOqCkAUgFEpKpIYNpZy4Bs8kFyELQF0QsgCEgq/DoSWWCwHUDSELQCj4DFl0sgDUBSELQCj4DFmNGknGELIAJIaQBSAUfIYsY9ySIcuFABJByAIQCj5DluQ+m04WgEQQsgCEAiELQNgQsgCEgu+QxXIhgEQRsgCEgu+QRScLQKIIWQBCgZAFIGwIWQACr6pK2rGD5UIA4ULIAhB4O3a4WzpZAMKEkAUg8GLhhpAFIEwIWQACLwghi+VCAIkiZAEIvCCErIICaedOqbLSXw0AwoWQBSDwghKyJLpZAOJHyAIQeEEIWfn57paQBSBehCwAgReEkBX7bDa/A4gXIQtA4BGyAIQRIQtA4AUhZLFcCCBRhCwAgReEkEUnC0CiCFkAAq+kRMrJkfLy/NXA1YUAEkXIAhB4scOhjfFXQ2y5kE4WgHgRsgAEXixk+cRyIYBEEbIABF6QQhbLhQDiRcgCEHhBCFkNG7rlSjpZAOJFyAIQeEEIWca4GghZAOJFyAIQeEEIWZKrgeVCAPEiZAEIvKCErPx8OlkA4kfIAhB4QQlZLBcCSAQhC0DgBSlksVwIIF6ELACBZm1wQhbLhQASQcgCEGg7d0rV1cEIWSwXAkgEIQtAoG3f7m6DErJYLgQQL0IWgECLdY6CELJYLgSQCEIWgEALUshiuRBAIghZAAItFmoKC/3WIbmQtWuXVFnpuxIAYUDIAhBoQepk5ee7W/ZlAYgHIQtAoAUpZMVqYMkQQDwIWQACLYghi04WgHgQsgAEWpBCVmy5kE4WgHgQsgAEWpBCFsuFABJByAIQaCUlkjFSo0a+K2G5EEBiCFkAAi12bqExvithuRBAYghZAAItKIdDSywXAkgMIQtAoAUpZDEnC0AiCFkAAi1IIYtOFoBEELIABFqQQlbDhlJWFiELQHwIWQACLUghyxi3ZMhyIYB4ELIABFqQQpbkaqGTBSAecYUsY8z5xpilxpjlxpjhe3n8SGPM+8aYXcaYm/Z4bKUxZoExZq4xZnayCgeQGQhZAMIqp7YnGGOyJT0o6RxJqyTNMsY8b61dXONpmyXdIKnnd7zNmdbajfUtFkDmCVrIYrkQQLzi6WR1lbTcWrvCWlsuabKkHjWfYK1db62dJakiBTUCyGBBC1l0sgDEK56Q1U7SFzW+X7X7vnhZSa8ZY+YYYwYnUhyAzFZeLlVUELIAhFOty4WS9naYhU3gM0621q42xrSS9LoxZom19p1vfYgLYIMl6YADDkjg7QFEVZAOh47Jz5c+/9x3FQDCIJ5O1ipJ+9f4fj9Jq+P9AGvt6t236yVNk1t+3NvzRltri621xS1btoz37QFEWBBDFp0sAPGKJ2TNktTeGHOwMSZPUh9Jz8fz5saYfGNMYexrSedKWljXYgFkFkIWgDCrdbnQWltpjBkm6VVJ2ZIet9YuMsYM3f34KGPMvpJmS2oiqdoY8wtJHSXtI2maMSb2WROtta+k5kcBEDVBDFlcXQggXvHsyZK1drqk6XvcN6rG12vllhH39JWkovoUCCBzBTFkFRRIu3ZJlZVSTlx/ggLIVEx8BxBYQQ1ZEt0sALUjZAEIrCCGrPx8d8u+LAC1IWQBCKwghqxYLYQsALUhZAEIrCCHLJYLAdSGkAUgsGIhK7ZEFwQsFwKIFyELQGCVlEiNGknZ2b4r+RrLhQDiRcgCEFhBOxxaYrkQQPwIWQACK4ghi+VCAPEiZAEIrCCGLJYLAcSLkAUgsIIcslguBFAbQhaAwApiyGrQQMrKopMFoHaELACBFcSQZYyriZAFoDaELACBFcSQJbmaWC4EUBtCFoDACmrIys+nkwWgdoQsAIEV1JDFciGAeBCyAARSVZVUVhbckMVyIYDaELIABFIsxAQxZLFcCCAeOb4LAIC9iYWYIIasggLps898VwF8raKqQq998po2lW1SSXmJSstL3W1Fqfu6wt130v4n6X9++D8yxvguOSMQsgAEUtBDFsuFCIrK6kr1ndpXUz+a+q3HGuc2Vn5uvvLz8pVtsjVtyTSt3LpSD1zwgLIMi1mpRsgCEEhBDlksFyIoqqqr9ONnf6ypH03V3WffrSs6XqGCvALl5+WrcW7jbwQpa61ufv1m3ff+fSqtKNWjFz+q7Kxsj9VHHyELQCBt3+5ugxiyuLoQQVBtqzXkxSGasGCCRpw1QsNPGf69zzfG6N5z7lVhXqF+98/faUfFDj35oyeVm52bpoozDyELQCAFuZNVUCCVl0sVFVIufz/BA2utbnj5Bj324WP6zWm/0a9P/XVcrzPG6I4z7lB+Xr5ufv1mlVWU6akrnlLDnIYprjgzsSALIJCCHLLy890t+7Lgg7VWt7x+ix6c9aBu+uFN+t8z/jfh97jppJv00IUP6YWPX1D3id1VWs5v5lQgZAEIpCCHrFhNLBnChzvevkN/ev9PGnb8MP3xnD/W+UrBa4+/VmN6jNFbK9/SeU+ep207tyW5UhCyAARSGEIWnSyk210z7tLv3/m9ru58tf56wV/rPYph4LEDNeXyKfr3l//W2ePO1sYdG5NUKSRCFoCACnLIii0X0slCOt3//v267c3b1O+YfhrVfVTSRjBc3vFyPdv7WS1cv1BnjDlDG0o3JOV9QcgCEFAlJW5TeV6e70q+jeVCpNuo2aN042s36vKOl2tMzzFJH71w0eEXaXq/6Vq2eZmGv/H9VykifoQsAIEU1MOhJZYLkV4rtqzQz17+mS5sf6EmXDpBOVmpGQxw1sFn6Wddf6Yn5j6h+evmp+QzMg0hC0AglZRIhYW+q9g7lguRTr956zfKzcrVIxc/orzs1LZ2bzv1NjVr2Ey3vH5LSj8nUxCyAARSGDpZhCyk2ty1czVxwUT9/ISfq21h25R/XvNGzXX7abfr1U9e1WufvJbyz4s6QhaAQApDyGK5EKl225u3qXnD5vrVKb9K22def/z1OrjZwbr59ZtVVV2Vts+NIkIWgEAKcshiuRDp8M5n72j6sukafspwNWvYLG2f2yCnge4++27NXzdf4+ePT9vnRhEhC0AgBTlkNWggZWcTspA61loNf2O42ha21c+6/iztn9/rqF7q2q6rbn/zdu2o2JH2z48KQhaAQApyyDLG1cZyIVLl+aXP6/1V7+t3p/9OjXIbpf3zjTH60zl/0pfbv9RfZv4l7Z8fFYQsAIEU5JAluSVDOllIharqKv36zV/r8BaHa1DnQd7qOPXAU9XzyJ665917tL50vbc6woyQBSCQgh6y6GQhVcbPH6/FGxZrxFkjUjYTK173nH2PdlTs0P++nfgh1CBkAQig6moXYIIesuhkIdl2Vu7UHW/foeK2xbqsw2W+y9ER+xyhIV2G6OE5D2vpxqW+ywkdQhaAwCkrk6wNdshiuRCpMHLWSH2+7XPdc/Y99T78OVnuOOMONc5trF+9kb4xElFByAIQOEE+HDqG5UIk21e7vtKIGSPU7ZBuOvuQs32X81+t8ltp+CnD9dzS5zTjsxm+ywkVQhaAwAlLyKKThWT603t/0qayTbr77Lt9l/ItvzjxF2pX2E43vX6TrLW+ywkNQhaAwAlDyGK5EMm0rmSd/vz+n3VFxytU3LbYdznf0ji3sUacNUL/+fI/emrRU77LCQ1CFoDACUPIYrkQyXTnO3dqZ+VO3XnWnb5L+U5XdbpKRa2LdOs/blVldaXvckKBkAUgcMISsuhkIRlWbFmhh+c8rJ92/qkOb3G473K+U3ZWtu44/Q59uvVTTV823Xc5oUDIAhA4YQhZ+flSeblUUeG7EoTdH//1R2VnZeu3p//Wdym1uviIi9WusJ0emvWQ71JCgZAFIHDCELJitbFkiPrYvmu7JiyYoD5H91G7Ju18l1OrnKwcDekyRK9+8qqWb17uu5zAI2QBCJwwhKz8fHfLkiHqY8KCCSopL9HQLkN9lxK3q4+7WjlZORo1e5TvUgKPkAUgcMIQsmK1EbJQV9ZajZo9Ssfue6y6tuvqu5y4tSlso0s7XKrHP3xcZRVlvssJNEIWgMApKZGysqSGDX1X8t1YLkR9zY/Xb9UAACAASURBVFw1U/PWzdO1xdcGZrp7vK4rvk5bdm7RlEVTfJcSaIQsAIETOxw6yH/vsFyI+ho1Z5QK8wrV9+i+vktJ2GkHnqaOLTuyAb4WhCwAgRMLWUHGciHqY3PZZk1ZOEVXdbpKhQ0KfZeTMGOMriu+TrNWz9KsL2f5LiewCFkAAidMIYvlQtTFmLljtKtql4YWh2fD+576F/VXfm6+Rs4e6buUwCJkAQicMIQslgtRV7EN7yftf5I6te7ku5w6a9Kgifp36q9JCydpc9lm3+UEEiELQOCEIWSxXIi6emvlW1q2eVmoxjZ8l2uPv1Y7K3dqzNwxvksJJEIWgMAJU8hiuRCJGjV7lH7Q6Ae64qgrfJdSb51ad9LJ+5+skbNHqtpW+y4ncAhZAAInDCErL0/KzqaThcSs2b5G05ZM06BjB6lhToBnlCTguuOv0/LNy/XGijd8lxI4hCwAgROGkGUMh0QjcY9/+Lgqqys1uMtg36UkzWUdLlPLxi0Z57AXcYUsY8z5xpilxpjlxpjhe3n8SGPM+8aYXcaYmxJ5LQDsKQwhS3I1slyIeFVVV2n0B6N19sFn6/AWh/suJ2ka5DTQ1cddrRc+fkGfb/vcdzmBUmvIMsZkS3pQ0gWSOkrqa4zpuMfTNku6QdKf6vBaAPgva8MTsvLz6WQhfq8sf0Wfb/tc1xZf67uUpBvSZYistRo9Z7TvUgIlnk5WV0nLrbUrrLXlkiZL6lHzCdba9dbaWZIqEn0tANRUXi5VVoYjZLFciESMnD1S+xbsq0uOuMR3KUl3YLMD1f3w7nrkg0dUXlXuu5zAiCdktZP0RY3vV+2+Lx71eS2ADBSGw6FjWC5EvD7b+pmmL5uuqztfrdzsXN/lpMR1x1+n9aXr9cxHz/guJTDiCVl7Oz3Mxvn+cb/WGDPYGDPbGDN7w4YNcb49gKgJU8jKz5e2b/ddBcLgkQ8ekTFG13S5xncpKXPuoefqkOaHsAG+hnhC1ipJ+9f4fj9Jq+N8/7hfa60dba0tttYWt2zZMs63BxA1YQpZzZpJW7b4rgJBV15Vrkc/eFQXtb9IBzQ9wHc5KZNlsnRt8bWa8fkMLVi3wHc5gRBPyJolqb0x5mBjTJ6kPpKej/P96/NaABkoTCGrdWtp3TrfVSDonlvynNaVrgv1OYXxGnTsIDXIbqCH5zzsu5RAqDVkWWsrJQ2T9KqkjyQ9Za1dZIwZaowZKknGmH2NMask3SjpdmPMKmNMk+96bap+GADhF7aQVVrKvix8v1FzRunApgfqvEPP811KyrVo3EI9j+ypSQsnsQFecc7JstZOt9Yebq091Fo7Yvd9o6y1o3Z/vdZau5+1tom1ttnur7/6rtcCwHcJW8iSpPXr/daB4Fq+ebne/PRNDe4yWNlZ2b7LSYuBRQO1uWyzpi+b7rsU75j4DiBQwhiyWDLEdxk/b7yMjAYWDfRdStqcc+g5ap3fWmPnjfVdineELACBErtaj5CFsKu21Ro3f5y6HdJN7ZpkzvSinKwc9Tumn176+CVt3LHRdzleEbIABAqdLETFvz7/l1ZuXakBRQN8l5J2A48dqIrqCk1eONl3KV4RsgAESixkNW7st454tGrlbglZ2Jtx88YpPzdfPzryR75LSbtOrTupqHWRxs0b57sUrwhZAAKlpMQFrOwQ7BHOy5OaNydk4dvKKsr01OKndHnHy5Wfl++7HC8GFA3QrNWz9NGGj3yX4g0hC0CghOVw6BhmZWFvnl/6vL7a9VVGLhXGXHnMlco22RndzSJkAQgUQhaiYNz8cdq/yf4646AzfJfizb4F++q8w87TkwueVFV1le9yvCBkAQiUrVulpk19VxE/Qhb2tLZkrV5d/qqu6nSVskxm/zU7sGigVn21Sm+vfNt3KV5k9v/6AAJnzRqpTRvfVcSPkIU9TVowSVW2Sv079fddincXH36xmjZomrEzswhZAAIljCFr2zZp507flSAoxs4bq+PbHq8OLTv4LsW7RrmN1OuoXpr60VSVlJf4LiftCFkAAqOqynWF9t3XdyXx42gd1DRv7TzNWzcvoze872lg0UDtqNihZz56xncpaUfIAhAYGzZI1dXh62RJLBnCGT9/vHKyctTn6D6+SwmMk/Y/SYc0PyQjlwwJWQACY+1adxumkMVAUsRUVldqwoIJuqj9Rdqn8T6+ywkMY4wGdBqgtz59S59v+9x3OWlFyAIQGGvWuNswhSw6WYh5Y8UbWluylqXCvehf1F9WVhPmT/BdSloRsgAEBiELYTZu3jg1b9hcF7W/yHcpgXNI80N06gGnauy8sbLW+i4nbQhZAAIjFrLCtPG9USOpsJCN75nuq11fadqSaepzdB81yGngu5xAGlA0QEs3LdWs1bN8l5I2hCwAgbFmjdSsmdSwoe9KEsOsLDy9+GntrNzJUuH3uKLjFWqY0zCjjtkhZAEIjLVrw7VUGEPIwrh549T+B+11QrsTfJcSWE0bNlXPI3tq0sJJ2lW5y3c5aUHIAhAYYRtEGkPIymwrt67UPz/7pwYUDZAxxnc5gTawaKA2l23W9GXTfZeSFoQsAIFByEIYPTn/SUnSVZ2u8lxJ8HU7pJv2LdhX4+ZnxpJhju8C4NnOndLSpdKSJZIxUpMmX/9q2tTdFhRI2dm+K0XEWetCVpg2vce0bi1t2iRVVEi5ub6rQTpZazVu3jidfuDpOqjZQb7LCbycrBz1O6afHvj3A9q4Y2Pk54kRsjLFjh0uTC1aJC1e7H4tWiStWOFGbNemoMD9TXLGGdK550pnny21aJHyspE5Yuf/hbWTJbmJ9W3b+q0F6fXvL/+tZZuXafgpw32XEhoDiwbqvvfv0+SFkzWs6zDf5aQUISvKtm2TpkyRxoyRZs50rQJJysmRDj9cOvZYqV8/qWNH6cgjXbfqq6++/WvbNnf76afS009Ljz3mul7FxS5wnXuudOKJUl6e1x8X4RbGae8xNWdlEbIyy7h549Qwp6Eu73i571JC45jWx+jYfY/V2HljCVkImepq6c03pSeekJ55xrUGOnaUfvMb6ZhjpKOOkg47rO5rGpWV0qxZ0uuvS6+9Jt1zjzRihOt0nXmm1Lu3+5XDby0kJoyDSGMYSJqZdlXu0uSFk/WjI3+kJg2a+C4nVAYWDdQvX/2lFm9YrI4tO/ouJ2XY+B4Vn3zigtRBB0nnnCNNny4NGiT95z/SwoXS//6vdPnlUocO9ds0kpMj/fCH0m9/K737rtuIMm2a1L+/+5yrrnJdslGjXMAD4kTIQti88PEL2rJziwYWDfRdSuj0Pbqvsk125GdmEbLC7u23pdNPd92pu+5ynarJk93fWA89JB1/vFvaS5WmTaWePd1nLV8uPfecOzH32mulgw+W7r1X2r49dZ+PyAjjtPcYQlZmGjtvrNoWtlW3Q7r5LiV0Whe01gXtL9CT859UVXWV73JShpAVVp98Il16qVui+/RT6e67pc8/l15+2S3X+RiZnZUlXXKJ9P77bsnymGOkW26RDjjAdb42bkx/TQiNNWvcb9umTX1XkriCAqlxY0JWJllXsk4vL3tZVx1zlbKzuPq6LgZ0GqAvt3+pNz9903cpKUPICptt26Sbb3bLfq+9Jt15p7tqcPhwqV0739U5xrjw99prbrnyzDOl3/9eOvBA6cYbpc2bfVeIAIpNew/rLEdmZWWWiQsmqspWaeCxLBXW1cVHXKxmDZtFemYWISssKivdPqf27aX77nN7n5Ytk267zZ1QG1THH+824C9a5PaEPfCAW9KcNs13ZQiYsA4ijSFkZZZx88epuG1xpDdtp1rDnIbqfVRvPfPRM9q+K5rbSghZYfD6627cwrXXug7W7NnS44+H62+kjh2lsWNd7W3auKXOXr34Wwn/RchCWMxfN19z185lw3sSDCwaqB0VOzT1o6m+S0kJQlaQbdzowsi550plZdLUqW6j+3HH+a6s7o49Vvr3v90m/eeec+HrySe/nuGFjBXWae8xrVoRsjLF2LljlZuVq75H9/VdSuiduN+Jav+D9ho7b6zvUlKCkBVUb78tFRVJL73kNrUvXuwCV1g3rNSUmyvdeqs0d650xBFu/EP37tIXX/iuDJ6UlUlbt4a/k7Vxo1QV3QulIKmyulITFkxQ98O7q0VjTr2oL2OMBhQN0Nsr39ZnWz/zXU7SEbKCprLSzbs66yx3ydLMmW5Te4MGvitLvg4dpBkzpL/8xYXKo46SHn44vmN+EClhnvYe07q1+627aZPvSpBKry5/VetK17FUmESxg7XHzx/vuZLkI2QFyWefubMB77xTGjhQmjNH6tzZd1WplZ0t/fzn0oIFbpP80KHSeee5Q+CQMaISsiSWDKNu7Lyx2qfxPrqg/QW+S4mMg5odpDMOOkPj5o2TjdjWEUJWUEyd6vYrzZ8vTZjgjsUpKPBdVfoccoj0xhvuCsoZM9y5iB984LsqpEmYp73HELKib0vZFj239Dn1Pbqv8rI5qzWZBnQaoGWbl2nmqpm+S0kqQpZvZWWue3P55W48w4cfSlde6bsqP4yRhgyR/vUvtxH+5JOl8dFrH+PbwjztPYaQFX1TFk1ReVU5S4UpcHnHy9Uop1HkjtkhZPm0ZIlbInv4YTdg9N13pUMP9V2Vf126uKXSE0+UBgxwy4kVFb6rQgqtWeMODGjZ0ncldUfIir6x88bqqJZH6bg2Ib7CO6AKGxTq0g6XavKiydpZGZ1zbwlZvrz5pjtoef166ZVXpD/+Ucqj/fxfLVu6+WC//KUbYNqtm/tvhUhas8aFlOwQn07StKn7vzAhK5qWblyqmatmamDRQJkoXOUdQAOKBmjrzq168eMXfZeSNIQsH554wm3ubtPGzYw67zzfFQVTTo705z+7OVr/+Y/rcM2a5bsqpEDsSJ0wM4aBpFE2fv54ZZms/14Jh+Q7++Cz1bawbaRmZhGy0qm6Wvr1r6Wf/MRdRfjee9LBB/uuKvj69XP/rbKzpVNPlcaM8V0Rkizs095jCFnRVG2rNX7+eJ176LlqUxiB36gBlZ2VrauOuUovL3tZ60ujsXJByEqXsjKpTx83WPSaa6Tp06VmzXxXFR6dO7sjeU45RRo0SLrpJuZpRUjYp73HELKi6e2Vb+vzbZ+z4T0NBhQNUJWt0sQFE32XkhSErHRYv94NF336abf36uGH3dRzJGaffdz+teuvd4dkDxgglZf7rgr1VFXl/i9CJwtBNXbeWDVt0FQ9jujhu5TIO6rVUerSpktkrjIkZKXa4sXSCSdI8+a5kHXzzdE4GseXnBzpb3+TRoxw88QuvlgqKfFdFeph/XrXlIxKyIr9PIiGkvISTV08Vb2O6qVGuY18l5MRBhYN1IdrP9SCdQt8l1JvhKxUeuMN6aST3FLhP//pzh5E/Rnj9rY9/rj0j39IZ57JlYchFoVp7zGtW7uTsbZs8V0JkmXq4qkqrShlqTCN+hzdRzlZOZHYAE/ISpUpU6QLLpD2399dQXj88b4rip5Bg6Rnn5UWLXKDS1es8F0R6iAK095jmJUVPWPnjdVhPzhMJ+1/ku9SMkbL/Jbqfnh3jZ8/XuVV4d4SQshKhUcekfr2dXOw3n1XOvBA3xVFV/furpu1ebPrGn74oe+KkKAoTHuPIWRFy2dbP9NbK9/SgE4DmI2VZkO6DNH60vV6dsmzvkupF0JWsv3pT9LgwdL557tN2k2b+q4o+mJhNi9POv10N+gVoUHIQlA99uFjMjIaUDTAdykZ59xDz9VBzQ7SqNmjfJdSL4SsZLFW+s1v3Mb2K65wy1iNG/uuKnN06OBmaR1wgAu4U6b4rghxWrNGat5catjQdyX1R8iKjoqqCj36waO6sP2FOrAZqxHplmWyNPi4wXpr5VtasnGJ73LqjJCVDNXV7ny9O++UfvpTadIkjsjxYb/9pBkz3NWcfftKjz7quyLEIQrT3mOaN3czc7kOI/yeW/qc1pSs0bXF1/ouJWP9pPNPlJOVo9FzRvsupc4IWfVVWekmuP/tb9KNN7r9WGE+gC3smjeXXnvNHVV0zTXSgw/6rgi1iMq0d8kdct2qFZ2sKBg5e6QObHqgzj/sfN+lZKzWBa11aYdLNWbuGJVVlPkup04IWfWxa5fUq5c0dqz0//6f24/F5kj/GjVyy7U9ekjDhrnBpQisqEx7j2Egafgt3bhUb376poZ0GaLsLP7R7NPQLkO1ZecWPb34ad+l1Akhq65KS90gzGnTpL/8xe3HImAFR4MG0t//7vbH3XSTW8pF4FgbrU6WRMiKglGzRyk3K1c/Pe6nvkvJeGccdIYOb3G4Rs0J5wZ4QlZdbN/uNlf/4x/SE0+4/VgIntxcaeJEqX9/F4Jvv939rY7A2LrVNYQJWQiKHRU7NGbeGF3W8TK1ym/lu5yMZ4zRkC5D9N4X72n+uvm+y0kYIStRX33l9vu8/740ebL04x/7rgjfJydHGjNGuvpqdxTPzTcTtAIkStPeY2Ihi99m4TRl4RRt3bmVDe8BMrBooBpkN9DDsx/2XUrCCFmJ2LpVOuccadYs6amn3FIUgi8ryx3KHduf9bOfcbhcQERp2ntM69auO/fVV74rQV2MnD1SR7U8SqcecKrvUrBbi8Yt1OuoXho/f7xKysN1Vi0hK16bN0vdurmJ4k8/zTmEYZOVJT3wgOtkPfigGxhbVeW7qowXpUGkMczKCq85q+do1upZGlo8lAnvATOkyxBtL9+uyQsn+y4lIXGFLGPM+caYpcaY5caY4Xt53BhjHtj9+HxjzHE1HltpjFlgjJlrjJmdzOLTZtMmF7AWLJCeecZdtYbwMUb6wx/c/qzHHnNLvQQtr6LayZIIWWE0cvZINc5trP6d+vsuBXs4af+TdHSro0M3Ab7WkGWMyZb0oKQLJHWU1NcY03GPp10gqf3uX4Mljdzj8TOttcdaa4vrX3KabdggnXWWtHix9Nxz7qw8hJcxbtzGnXdKTz4pDRjgZp3BizVr3MSNJk18V5I8hKxw2rpzqyYumKh+x/RT04YchxY0xhgN7TJUc9bM0ezV4enXxNPJ6ippubV2hbW2XNJkSXu2cnpIGmedmZKaGWPC/2/T9etdwPr4Y+mFF9wVhYiG226T7rrr66sPCVpexKa9R2llhpAVTuPmjVNZZRkb3gPsqk5XqXFu41B1s+IJWe0kfVHj+1W774v3OVbSa8aYOcaYwXUtNO3WrpXOPFP65BPppZfchndEy623uuXDyZOlfv0IWh5EbUaWJO2zj9sCSMgKD2utRs4eqRPanaDObTr7LgffoWnDpup7dF9NWjhJ23Zu811OXOIJWXv7N+aeFyd/33NOttYeJ7ekeL0x5rS9fogxg40xs40xszds2BBHWSm0erULWJ99Jr38sutmIZpuuUW69153tWjfvlJFhe+KMkrUpr1L7lStffYhZIXJ2yvf1pKNS+hihcDQ4qHaUbFDT85/0ncpcYknZK2StH+N7/eTtDre51hrY7frJU2TW378FmvtaGttsbW2uGXLlvFVnwpffimdcYa0apULWKef7q8WpMdNN7nRDk8/LfXpQ9BKoyh2siQGkobNyNkj1bxhc/U6qpfvUlCL4rbF6tKmi0bNGSUbgmF08YSsWZLaG2MONsbkSeoj6fk9nvO8pAG7rzI8UdI2a+0aY0y+MaZQkowx+ZLOlbQwifUn16pVLmCtXSu9+qp0KnNSMsaNN0r33++uHu3dWyov911R5JWVSdu2EbLg15rtazRtyTQNOnaQGuU28l0O4jC0eKgWrl+o9754z3cptao1ZFlrKyUNk/SqpI8kPWWtXWSMGWqMGbr7adMlrZC0XNIjkq7bfX9rSe8aY+ZJ+o+kl6y1ryT5Z0iOzz93Xat161zAOukk3xUh3X7xCzdLa9o0d/A3QSulojjtPYaQFR6PffiYKqsrNbR4aO1PRiD0ObqPCvMKQ3GeYU48T7LWTpcLUjXvG1Xjayvp+r28boWkonrWmHqffeb2YG3aJL3+unTCCb4rgi8/+5nbtTxsmHT55e6Q6QYNfFcVSVGckRVDyAqHquoqjZ4zWt0O6ab2Ldr7LgdxKsgrUP9O/fXYh4/pL+f9RS0at/Bd0ndi4vvKlW6JcMsW6Y03CFiQrr9eeughN7bj0kulnTt9VxRJUZz2HtO6tbRjh1Ra6rsSfJ+Xlr2kL776gg3vITS0eKh2Ve3Sw3OCfZ5hZoesFSvcEuG2bS5gHX+874oQFNdeK40e7S5+uOQS9zcmkirKnaxWrdwt3axgGzl7pNoWttUlR1ziuxQk6JjWx+j8w87X/TPvV2l5cP81k7kh65NPXAerpET6xz+kLl18V4SgueYa6fHHXQDv3p22RJKtWePGHfi8mDhVGEgafPPWztMry1/R0C5DlZMV184ZBMztp96ujTs26pEPHvFdynfKzJC1bJnrYO3YIb35ptSZ4XP4Dj/+sTR+vPTPf0oXXCBt3+67oshYu9aFkawI/ilEyAq+O2fcqSYNmmhY12G+S0EdnXzAyTr9wNN173v3alflLt/l7FUE/3irRWWldNFF0q5dLmAVBX9fPjzr188dv/Pee9J557nlZdRbVGdkSYSsoFu4fqGeXvy0buh6g5o3au67HNTD7afdrtXbV2vM3DG+S9mrzAtZOTlur81bb0mdOvmuBmHRu7ebCj9rljtiacsW3xWFXhSnvcewJyvYRswYoYK8Av3ixF/4LgX1dPbBZ6tru66651/3qKIqeIOkMy9kSW4v1tFH+64CYXPppdLUqdLcudLZZ7uRH6izKHeycnOlH/yAkBVESzYu0ZSFU3T98dcH+tJ/xMcYo9tPvV0rt67UpIWTfJfzLZkZsoC6uuQS6dlnpcWL3ZmWvs/ZDKnKSmn9+uiGLIlZWUF114y71Ci3kW784Y2+S0GSdD+8uzq17qS7371b1bbadznfQMgCEnXhhW6G1scfuwsovvzSd0Whs2GDZC0hC+m1fPNyTVgwQUO7DFWr/Fa+y0GSGGN026m3acnGJXrmo2d8l/MNhCygLs45x83Q+uIL6ZRT3EgQxC3KM7JiCFnBc/eMu5WXnaebTrrJdylIsss6XKYjWhyhO9+5M1AHRxOygLo64wx3her27S5oLVjgu6LQiPK09xhCVrB8uuVTjZs/ToOPG6w2hRFO9xkqOytbt55yq+atm6fpy6bX/oI0IWQB9XH88dI777hhT6efLs2c6buiUMiUTtZXX3EqU1Dc8+49yjJZuuXkW3yXghS58pgrdVCzg3TnjOB0swhZQH117Ci9+667nKxbNzchHt8rUzpZEt2sIPhi2xd6Yu4T+mnnn6pdk3a+y0GK5Gbn6paTbtHMVTP11sq3fJcjiZAFJMfBB0szZkiHHOKG3U6b5ruiQFu71mXSBg18V5I6hKzg+MO//iBJGn7KcM+VINUGdR6kNgVtNGLGCN+lSCJkAcnTpo07fqdLF+nyy6UxY3xXFFhRnpEVQ8gKhtXbV+vRDx7VwKKBOqDpAb7LQYo1zGmom066SW9++qbe/+J93+UQsoCkat5cev11N6x00CDpr3/1XVEgRXnaewwhKxju/de9qqyu1K2n3uq7FKTJkC5D1KJRi0B0swhZQLLl57s5WpdeKv3iF9Kvfy1VB2tAnm+Z0MniaB3/1pas1ag5o9S/qL8OaX6I73KQJvl5+frlib/US8te0odrPvRaCyELSIUGDaQpU6TBg6W773aHTHOZmSQ3hDQTQlbDhlLTpm6yPfy47737VF5Vrl+f8mvfpSDNhnUdpqYNmuqud+/yWgchC0iVnBxp1CjpD3+QJk92A0w571Bbt0rl5dEPWRKzsnzaULpBD81+SH2P7qv2Ldr7Lgdp1rRhUw3rOkxvr3xb23Zu81YHIQtIJWOkW25xXa1Zs6Qf/lBavtx3VV5lwoysGEKWPyNmjFBZRZluO/U236XAk1tOvkWf/vxTNW3Y1FsNhCwgHXr1ctPhN2+WTjxReu893xV5kwkzsmJatSJk+TBn9Rz97T9/05AuQ9ShZQff5cCTJg2aqCCvwGsNhCwgXU46yU2E/8EPpLPOkp56yndFXtDJQipVVlfqmheuUev81rq7292+y0GGI2QB6XTYYdL777vjeHr3dvu1AnL8Q7pkWsjavFmqqPBdSeb468y/6sO1H+qBCx5Qs4bNfJeDDEfIAtKtRQs3S6tPH2n4cGnIELcTPEOsXSs1biwVFvquJPVis7K4wjA9Vm5dqd++/VtdfPjFuqzDZb7LAQhZgBcNG0oTJrgZWo884g6XXrXKd1VpERvfYIzvSlKPgaTpY63VdS9dJyOj/7vw/2Qy4TcYAo+QBfiSlSWNGOH2Zi1c6I7jeSsYh5qmUiZMe48hZKXPU4ue0svLX9aIs0ZwfA4Cg5AF+HbFFdJ//uM2xHfrJv3xj5Hep5UJg0hjYiFr7Vq/dUTdlrItuuGVG1TctljDug7zXQ7wX4QsIAg6dHBB69JLpV/9yh0w/dVXvqtKiUwKWfvvLzVpktETO9LiV2/8Spt2bNLo7qOVnZXtuxzgvwhZQFAUFrqlw/vuk557zl2BuGiR76qSascOlx0zJWTl5koXXCA9/7xUVeW7mmia8dkMPfLBI/rlib9U5zadfZcDfAMhCwgSY6Qbb3SDS7dtk044wU2Lj4jYslmmhCxJ6tHDXV3473/7riR6dlXu0uAXB+ugZgfpd2f8znc5wLcQsoAgOu006YMPpKIiN+rh+uul0lLfVdXbl1+620wKWRde6Dpazz3nu5Louefde7Rk4xKNvGik8vPyfZcDfAshCwiqtm3d1YY33ig99JDUubMbZBpir73mLqosKvJdSfo0bSqdcYb07LO+K4mWJRuX6K5371Lfo/vq/MPO910OsFeELCDI8vLcHq0335R27ZJOOcXN1tq1y3dlCbNWmjTJnSiUKSMcYnr2lD7+WFqyzTwhHwAAGBxJREFUxHcl0VBtqzXkxSHKz83X/efd77sc4DsRsoAwOPNMacEC6cc/lu6+W+raVZo/33dVCZk1S/rkE6lvX9+VpN8ll7hbulnJccvrt+idz97Rfefep9YFrX2XA3wnQhYQFk2aSI895i5VW7dOKi52gauy0ndlcZk0yTXmLr3UdyXpt99+btYs+7Lq78H/PKj73r9PN3S9QYM6D/JdDvC9CFlA2Fx8sZsQ36OHWzo89VRp2TLfVX2vqipp8mS3CbxZhp7Z27Onu8IwdkA2Evfixy/qhldu0CVHXKI/n/dn3+UAtSJkAWG0zz5uptaECW6jT1GRO6Jn507fle3VP//pxjdceaXvSvzp0cPtS3vhBd+VhNOc1XPU++neOq7NcZp46USGjiIUCFlAWBnjUsvChdL550u33y4ddZRbTgzYsTwTJ0oFBVL37r4r8efoo6WDD2bJsC4+3/a5uk/qrpaNW+qFvi8wrgGhQcgCwq5dO+mZZ6TXX5caNnQtkwsuCMylbLt2SVOnSj/6kdSoke9q/DHGLRm+8Ya0fbvvasJj285tunDChSqrKNP0ftO1b0GGXZqKUCNkAVHRrZs0d670l79IM2dKxxwj/c//uMnxHr36qrR1a2ZeVbinHj2k8nL33wS1K68q12VPXaalm5bqmd7PqGPLjr5LAhJCyAKiJDdX+vnP3VCmH/9Yuv9+6fDDpSeekKqrvZQ0caLbQtatm5ePD5STT5ZatGDJMB7WWg19caj+8ek/9OjFj+qsg8/yXRKQMEIWEEWtWkmPPOKGUx16qPSTn7iRD88+m9awVVLitohdcYXLf5kuJ8ftS3vxRamiwnc1wTZixgg9MfcJ3XH6HRp47EDf5QB1QsgCoqxLF+lf/5LGj5e++sptjOrcWfr739MStp57Tiory+yrCvfUo4dbPp0xw3clwfXEh0/oN2/9Rv079dcdp9/huxygzghZQNQZI111ldsIP26c24neq5e73G3iRDfEKkUmTZL231866aSUfUTonHuuuz6B6e/fVlldqZteu0k/ef4n6nZINz16yaMyxvguC6gzQhaQKXJypP79pUWL3GTQrCypXz+pQwdpzJikr19t2uQ2ePft6z4KTn6+dM45rssXsEkbXq0vXa9zxp+j+96/T8OOH6aXrnxJedl5vssC6oU/+oBMk50t9e7tzj6cOtX9rT9okHTEEW6j/KZNSfmYp592J/5wVeG39ewpff65NG+e70qC4d+r/q0uo7to5qqZGtdznP524d8IWIgEQhaQqbKy3EGCH3zgdqfvu690441u7tZVV0nvvFOvVsvEia5JVlSUxJojont3t4rLkqH0yJxHdNqY05STlaP3fvKe+hf1910SkDSELCDTGePOQ3zvPddaueYad/nb6adLHTvWqbv1xRduY3ffvu7t8U2tWrl9apk8ymFn5U5d8/w1GvziYJ150Jmafc1sdW7T2XdZQFIRsgB8rVMn6W9/k1avdvu0mjd33a22bd3+rbfeimuj/JQprgnGUuF369nTzY797DPflaTfF9u+0GlPnKZHP3xUt516m1668iW1aNzCd1lA0hGyAHxb48bSwIGuuzV/vjRkiPTSS9JZZ0lt2rhu18svuysV92LSJOn446XDDktz3SHSo4e7zaRuVkVVhR794FF1Gd1FSzYu0bTe03TnWXdy2DMii5AF4Psdc4z0wAOuu/XUU250+5Qp0oUXSi1buiFYf/+7mzwqaelSt82LLtb3a9/ercZmQsiqrK7UmLljdMT/HaFrXrhGhzQ/RLOumaWeR/b0XRqQUoQsAPFp3NiNbp84UdqwwXW2evd2B1P36uXOzrnkEk36n9kyxqp3L+YT1KZHD+mf/5Q2b/ZdSWpUVVfpyflPqsODHTTouUFq3qi5Xuz7ot7/6fs6Yp8jfJcHpBwhC0DiGjRwnaxHHpHWrJHeflsaOlT2w7ma9FKhzrBvqW2XNlKfPtLIkdJHHzEUai969HBb3KZP911JclVVV2nywsk66qGj1H9af+Xn5uvZ3s9q9jWzddHhFzFgFBnD2AD+wVdcXGxnz57tuwzg/7d371Fy1uUBx7/POzuzm2EyCRACSEKAmFTIBKFQtAdFeqSaIgVRvHAS9NRjKd0NIOnxqPUGKljogcSKolCoFixRToMmurTSDRev5aI2iUDoTEgxSy6QkM2Gvc7M0z9+72xmd2d2ZnfnnSHzPp8973lvv3nf32Xm3Wfey2/MJD39lHL2nwh3XfE4H8/f6YKv7m63cu5c98TiO97hfkdx6VJ3dizE8nmYN8/9cPQDDzQ6N9O3f2A/G7Zu4OZf3MzvX/49qbkpbjj/Bt77pvfiiX2nN81LRJ5W1bPHLm9pRGaMMc3p/rVCNArv/9p5cOR57uxVJuOuiT36qBsK0YTnuQ5Qzzzz0HDGGXB0eJ4y8zy4+GL3IOfq1dDRAbHDrA/OF3teZP3W9fxo6494dPujZPNZTp1zKt+/7PtcdtplFlyZUAvfuz+TgfZ2SCbdES6ZdPOZTDDbmE7aRML9vlwiUXq+3LYyGdeZZDTqOimaaEilYONGN6RS49fdd1/l/Ncq31Opt1q0p5m2Z55xv9izZg285z2Q3dfD2vbHWTXrbtoXP8yq65S1M/+alx/ZDNu3w4MPwuc+x97Zp7D7B4/BJz/pbqifM4c/yHwekmV8Qzr4VOtq7rjox7zY9bzrPr6CTEZZsVyJtiiejB8iXunlniixqHvtxo1KR7syK3loeUvkULrWmEuXyei4fXe050km8kQkNzLMSuRY2Z4bl77g85+H885zPWUsWQLr1r2+r6yqKr/Z+Ruuf/R6zvz2mSxYs4CrH7qaHQd2sOqtq/jFx37BlvYtfHDJB5s2wMqQoZ12kiTx8EiSpJ12NrJx3PLlLGcFKyqmTZAgRYoEiZH5xSwmShTx/2LEeCfvZBGLRpYJQooUG9k4Ln8JEqPSjf2LEx+1z0LeMpQ+fpYrd7n0k6nHQvlixCpuu9b5CJSqVhyAZcBWIA18usR6Af7JX78J+ONqX1tqOOusszQQnZ2q8bhqNKrqjmNuiEbd8s7O2m6jFmkrDWO31dmp2to6uW1UGjyv/D5rle+p1HEt2tNMyxNPqF56qav2eFx11SrVn93/ol4bv1NXRu/Qv+WbI8PK6B16bfxO3dK5XVVVb76hT2ezT2ezT08hrX/JD/Uz3Khr+aD+ljdrL0eMatdcpEX1jW9UXbZMdeVK1VtuUb3vPtVHHlHdulX/c12vtrXmVZj+0BKpnKatNa+dnXlVVe3szGsintNoJKcexUNWPbIai2R1Zjw7kn6sfN69XU87zRX37W93ddto+XxeX3j1BV3/3Hr9ymNf0Q898CGdf9t85XpUrhc99+5z9Zaf36JbX9na6KzWTad2alzjGtWoUvQX0cio8UR/k0k7mb8b9IaR/E1121GNalzj2qmdVZW7XPqp1mOlbdc6H7UCPKUl4pmK92SJSAR4HvhzYAfwJHC5qj5TlOZC4GrgQuAtwNdU9S3VvLaUQO7JymRcR4t9feXTxOOuT6CFC6e/Daht2kricdiwwf1eR3//1LczGW1t7ozXdPY3ts6rreMNG1wv5dNpTzMlqu7q3003uQcLZ8+Ga66Bq68G7enhxtN/wFBf+bNOsXgLF3z7Mq64Atz3M8gjDBEbmff3xLHsZiEZTmEbp7akufJdL5DYlYF0Gg4cGLft/cziJd5ANyewk+PZx1Hs5Wj2cjSvMGdkujAMMGNaddHWBj/5iXJxhbciuOPsEXH47SaPhQtL3/idzcLdd8MXvgB79rj+X2+6CU48cVrZnJCqcmDwALsO7qK7t5tnXn6Gzbs3s3nPZrbs2ULvUO9I2gWzFnDWG87iokUXcdHiizjmiGOCy9jrUIYMp3M6fUzjWB2wNtoYYGDa24kTZxObWMjCqspdnL6SydZjYdtATfNRS9O5J+scIK2q2/wNrQUuAYoDpUuAf/WjuV+LyGwROR44qYrX1sett8Lw8MRphofdjRG33z79beTztU1byfAwXHstDEz/w1W1Mh1RTsrYOq+2jq+5Zvrtaao2OOi6wfrVr+CrX3V9lB57LNx8M1x1lbtKC7D2C/9DbnjiHuFzwzm+dM3LwKF/0DlKdUYp7OY4dnMcv+RcogIvnhxhzU+ibnVvr7upvrub797UzXMbuzmBbo5nJyfQzWKe52j2kuC18uUiRi8zOUBy1Lh46GcGfcTpZ8a46f6BOP/y8VZOH4zRR4whYgzSypA/XRiGaSFLC8PDwprVeb5+e+nON1taXL+vl1/u6va229xveF93nVs2ezbMmnXoynuBqjKUG+Lg0EF6h3rdeNCNi5ft7dvLroO72PXaLnb27nTTB3fRnx39RenItiNZeuxSPvLmj7B07lKWHruU1NwUydbkhG3b7G7lVoaZ5rE6YLUIsACGGWY1q7md26sqd3H6SiZbj4Vt58nXNB/1UM2ZrMuAZar6cX/+CuAtqrqyKM2PgX9Q1Z/7813Ap3BB1oSvLSWQM1nJpDsoA+csuJlduQWl03kCJ8wrva57B+SruFnC87+l1jptsyqu82rreCrbDjlFQAW0aNqt8OchN9jK8MAMsgNtZPvbyPa76Xzu0Pex+DF7eNMlGzjp/EdoaR19wPvdum3khvMV8/IH5qNFt4Tmqrw9NBqFS943PkBZtw6yZY69HjliDNHK4KhxTAaJMkx0JATK+vNZWg6FRUTIUfq8k+NX6cg0uPmx0wrkxZ21o0VQT1Bx47wIeU/IebhBIOcJAwfns+OXN/Dq1rE9u+aR1gPQth9t64HWHmg9AJIHUbfXMuOYCm15jzaN0Jb3mJGP0KYebfkIM9RjZr6FGfkII2cVRxW+TE2MW1yjLhpeZz097GAHecJzrPYQ5jGv6nIX0lcylXr0Rs56Ty4fsZY8925726T2NRXTOZNV6m0+tpTl0lTzWrcBkSuBKwFODOLcuN8bNcCO7CL29r2pfNptZR7vGTqyxpkyIwp1HkQdl2vPMBIdGQuHpgv/gL3YAF7rbuSoPlraXiPW2ofX+hpeax9e22tEZ+8msfQR+iJZntk/fvN7jnq1qmxk6aX48KBV/jcdAjbtHp82e1T51+SBAX8YzwNa/aEMFQRXXx75onEeD/XHfjWi/jIdPa+uhJ664fjjcMv8qvdUiajgKbQqRFSIKHjRXk66cBWvnfMt+l75I3QwSa5/FvnBJNnBJNmhmQwPJhkaTDJ8cAGS9/DUw1NBVPyxVzQt42taYRA39KDsKl8TZeqn4oKmMUT4/gfsIzapcu+j8vG2HvVYyEdbpLFnHqsJsnYA84vm5wEvVZkmVsVrAVDVO4E7wZ3JqiJfk5NIjJzJeqn7feXTJZOwq6f8ut7e0uvGplOtfdpmVVzn1dbxVLZtArcq+c8M9FY+qD3AZWSJjswP0Eo1py2SSXi2p23c8llJDfwjpECpC6FSdVDhAq1kEp7osd/qOxwlSdJLeI7VSZL00FN1uQvpq0k32XpMkkTRmuajHqo5R/8ksEhEThaRGPBhYP2YNOuBj4jzVqBHVXdW+dr6KHRpMJFoFP9u3Olvo9ZpK4lGD3XBUC+Frh6mY2ydV1tvS5ZMvz1NzZ2zYjGR6MTviUhUOPnIVyk+4xEhR6UzINEoXH5F6eBkxYr6vvULRGBJqpqPrytbNArL7S152FrBCqJM81h9mIgS5Qrcm7Wachenr2Sy9VjYdq3zUQ9V9fjuPz24BogA96jqjSJyFYCqfkvcbyTcjuuuoQ/4K1V9qtxrK+3Pni6cAnu6sPK2TeBeztTy6cLR4nF4clOMUxaO/26YyShLU/V97gNq/3SheX2zpwvt6cJyyt2TVVU/WfUerJ8s6yfL+sk6fG3p3D7pfrJm86rOpEfb6POH/pHhiEi/HhXv1//ozE64387O/GHbT5Y5fFg/WdZPVimU6Ser4QFVqSGwIEtVNZ1W7ehQTSZd8JBMuvl0OphtTCdtIqGaSrlxqfly20qnVZcvry7wSaVUu7rckEqNX3fvvZXzX6t8T6XeatGepub2pPfr/R2P6XXJu7Td+6Zel7xL7+94TPek949K91jXkP5pqmck2EryqsbpHQm05iT69dqOIc2kc1XtN53O64oV5YMkT8oHTdEW99qurrx2dOR1VtKlj7bkNeIdSheLunTpdH7cvld25DSZOBRceWQ1mcjqyo7suPTm8JXWtHZohyY1qZ56mtSkdmiHdmnXuOUrdIUu1+UV0yY0oSlNaUITI/OLdJG2aMtIIBHTmF6gF+hiXTwqwEhpSru0a1z+EpqYMKCKa3zUPgt5S2vp42e5cpdLP5l6FBWNalRjGlNRmXDbtc5HLZQLsuwHoo0xxhhjpqHc5cLm/GEpY4wxxpgGsyDLGGOMMSYAFmQZY4wxxgTAgixjjDHGmABYkGWMMcYYEwALsowxxhhjAmBBljHGGGNMACzIMsYYY4wJgAVZxhhjjDEBsCDLGGOMMSYAFmQZY4wxxgTAgixjjDHGmABYkGWMMcYYEwALsowxxhhjAmBBljHGGGNMACzIMsYYY4wJgAVZxhhjjDEBsCDLGGOMMSYAoqqNzsM4IvIy8H8B72YO8ErA+3i9CnPZIdzlD3PZIdzlt7KHV5jLX6+yL1DVY8YufF0GWfUgIk+p6tmNzkcjhLnsEO7yh7nsEO7yW9nDWXYId/kbXXa7XGiMMcYYEwALsowxxhhjAhDmIOvORmeggcJcdgh3+cNcdgh3+a3s4RXm8je07KG9J8sYY4wxJkhhPpNljDHGGBOYUAVZIvKPIvKciGwSkQdFZHbRus+ISFpEtorIuxuZz6CIyAdE5PcikheRs4uWnyQi/SLyO3/4ViPzGYRyZffXNX3bFxOR60Wku6i9L2x0noImIsv89k2LyKcbnZ96E5HtIrLZb++nGp2fIInIPSKyR0S2FC07SkQeFpH/9cdHNjKPQSpT/lB85kVkvog8IiLP+sf7a/3lDWv/UAVZwMNASlVPB54HPgMgIqcBHwaWAMuAb4pIpGG5DM4W4H3A4yXWZVT1DH+4qs75qoeSZQ9R24+1uqi9OxudmSD57fkN4C+A04DL/XYPmz/z27vZH+X/Du6zXOzTQJeqLgK6/Plm9R3Glx/C8ZnPAn+nqqcCbwU6/M96w9o/VEGWqv5UVbP+7K+Bef70JcBaVR1U1ReANHBOI/IYJFV9VlW3NjofjTBB2UPR9iF3DpBW1W2qOgSsxbW7aUKq+jiwb8ziS4Dv+tPfBd5b10zVUZnyh4Kq7lTV3/jTvcCzwAk0sP1DFWSN8THgIX/6BOAPRet2+MvC5GQR+a2IPCYib290ZuoorG2/0r9sfk8zXzrxhbWNiynwUxF5WkSubHRmGuBYVd0J7h8xMLfB+WmEMH3mEZGTgDOB/6aB7d9Srx3Vi4j8F3BciVWfVdUf+Wk+izut+L3Cy0qkPywfu6ym/CXsBE5U1b0ichbwQxFZoqoHAstoAKZY9qZp+2IT1QVwB/BlXDm/DNyK+9LRrJqyjSfpXFV9SUTmAg+LyHP+GQ8TDqH6zItIAvh34BOqekCk1CGgPpouyFLVCyZaLyIfBS4C3qmH+q/YAcwvSjYPeCmYHAarUvnLvGYQGPSnnxaRDLAYOKxukJ1K2Wmiti9WbV2IyF3AjwPOTqM1ZRtPhqq+5I/3iMiDuEuoYQqydovI8aq6U0SOB/Y0OkP1pKq7C9PN/pkXkSguwPqeqq7zFzes/UN1uVBElgGfAi5W1b6iVeuBD4tIq4icDCwCnmhEHhtBRI4p3OwtIqfgyr+tsbmqm9C1vX+QKbgU91BAM3sSWCQiJ4tIDPegw/oG56luROQIEZlZmAbeRfO3+VjrgY/60x8Fyp3Zbkph+cyLO2V1N/Csqt5WtKph7R+qzkhFJA20Anv9Rb8uPEnnX0L8GO4y4idU9aHSWzl8icilwNeBY4D9wO9U9d0i8n7gS7iy54AvquqGxuW09sqV3V/X9G1fTETuBc7AXTrYDvxN4X6FZuU/sr4GiAD3qOqNDc5S3fhfnB70Z1uAf2vm8ovI/cD5wBxgN/BF4IfAD4ATgReBD6hqU94cXqb85xOCz7yIvA34GbAZyPuL/x53X1ZD2j9UQZYxxhhjTL2E6nKhMcYYY0y9WJBljDHGGBMAC7KMMcYYYwJgQZYxxhhjTAAsyDLGGGOMCYAFWcYYY4wxAbAgyxhjjDEmABZkGWOMMcYE4P8BGaelD4LXofYAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<Figure size 720x720 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "*c* argument looks like a single numeric RGB or RGBA sequence, which should be avoided as value-mapping will have precedence in case its length matches with *x* & *y*.  Please use the *color* keyword-argument or provide a 2-D array with a single row if you intend to specify the same RGB or RGBA value for all points.\n",
      "*c* argument looks like a single numeric RGB or RGBA sequence, which should be avoided as value-mapping will have precedence in case its length matches with *x* & *y*.  Please use the *color* keyword-argument or provide a 2-D array with a single row if you intend to specify the same RGB or RGBA value for all points.\n",
      "*c* argument looks like a single numeric RGB or RGBA sequence, which should be avoided as value-mapping will have precedence in case its length matches with *x* & *y*.  Please use the *color* keyword-argument or provide a 2-D array with a single row if you intend to specify the same RGB or RGBA value for all points.\n",
      "*c* argument looks like a single numeric RGB or RGBA sequence, which should be avoided as value-mapping will have precedence in case its length matches with *x* & *y*.  Please use the *color* keyword-argument or provide a 2-D array with a single row if you intend to specify the same RGB or RGBA value for all points.\n",
      "*c* argument looks like a single numeric RGB or RGBA sequence, which should be avoided as value-mapping will have precedence in case its length matches with *x* & *y*.  Please use the *color* keyword-argument or provide a 2-D array with a single row if you intend to specify the same RGB or RGBA value for all points.\n",
      "*c* argument looks like a single numeric RGB or RGBA sequence, which should be avoided as value-mapping will have precedence in case its length matches with *x* & *y*.  Please use the *color* keyword-argument or provide a 2-D array with a single row if you intend to specify the same RGB or RGBA value for all points.\n",
      "*c* argument looks like a single numeric RGB or RGBA sequence, which should be avoided as value-mapping will have precedence in case its length matches with *x* & *y*.  Please use the *color* keyword-argument or provide a 2-D array with a single row if you intend to specify the same RGB or RGBA value for all points.\n",
      "*c* argument looks like a single numeric RGB or RGBA sequence, which should be avoided as value-mapping will have precedence in case its length matches with *x* & *y*.  Please use the *color* keyword-argument or provide a 2-D array with a single row if you intend to specify the same RGB or RGBA value for all points.\n",
      "*c* argument looks like a single numeric RGB or RGBA sequence, which should be avoided as value-mapping will have precedence in case its length matches with *x* & *y*.  Please use the *color* keyword-argument or provide a 2-D array with a single row if you intend to specify the same RGB or RGBA value for all points.\n",
      "*c* argument looks like a single numeric RGB or RGBA sequence, which should be avoided as value-mapping will have precedence in case its length matches with *x* & *y*.  Please use the *color* keyword-argument or provide a 2-D array with a single row if you intend to specify the same RGB or RGBA value for all points.\n",
      "*c* argument looks like a single numeric RGB or RGBA sequence, which should be avoided as value-mapping will have precedence in case its length matches with *x* & *y*.  Please use the *color* keyword-argument or provide a 2-D array with a single row if you intend to specify the same RGB or RGBA value for all points.\n",
      "*c* argument looks like a single numeric RGB or RGBA sequence, which should be avoided as value-mapping will have precedence in case its length matches with *x* & *y*.  Please use the *color* keyword-argument or provide a 2-D array with a single row if you intend to specify the same RGB or RGBA value for all points.\n",
      "*c* argument looks like a single numeric RGB or RGBA sequence, which should be avoided as value-mapping will have precedence in case its length matches with *x* & *y*.  Please use the *color* keyword-argument or provide a 2-D array with a single row if you intend to specify the same RGB or RGBA value for all points.\n",
      "*c* argument looks like a single numeric RGB or RGBA sequence, which should be avoided as value-mapping will have precedence in case its length matches with *x* & *y*.  Please use the *color* keyword-argument or provide a 2-D array with a single row if you intend to specify the same RGB or RGBA value for all points.\n",
      "*c* argument looks like a single numeric RGB or RGBA sequence, which should be avoided as value-mapping will have precedence in case its length matches with *x* & *y*.  Please use the *color* keyword-argument or provide a 2-D array with a single row if you intend to specify the same RGB or RGBA value for all points.\n",
      "*c* argument looks like a single numeric RGB or RGBA sequence, which should be avoided as value-mapping will have precedence in case its length matches with *x* & *y*.  Please use the *color* keyword-argument or provide a 2-D array with a single row if you intend to specify the same RGB or RGBA value for all points.\n",
      "*c* argument looks like a single numeric RGB or RGBA sequence, which should be avoided as value-mapping will have precedence in case its length matches with *x* & *y*.  Please use the *color* keyword-argument or provide a 2-D array with a single row if you intend to specify the same RGB or RGBA value for all points.\n",
      "*c* argument looks like a single numeric RGB or RGBA sequence, which should be avoided as value-mapping will have precedence in case its length matches with *x* & *y*.  Please use the *color* keyword-argument or provide a 2-D array with a single row if you intend to specify the same RGB or RGBA value for all points.\n",
      "*c* argument looks like a single numeric RGB or RGBA sequence, which should be avoided as value-mapping will have precedence in case its length matches with *x* & *y*.  Please use the *color* keyword-argument or provide a 2-D array with a single row if you intend to specify the same RGB or RGBA value for all points.\n",
      "*c* argument looks like a single numeric RGB or RGBA sequence, which should be avoided as value-mapping will have precedence in case its length matches with *x* & *y*.  Please use the *color* keyword-argument or provide a 2-D array with a single row if you intend to specify the same RGB or RGBA value for all points.\n",
      "*c* argument looks like a single numeric RGB or RGBA sequence, which should be avoided as value-mapping will have precedence in case its length matches with *x* & *y*.  Please use the *color* keyword-argument or provide a 2-D array with a single row if you intend to specify the same RGB or RGBA value for all points.\n",
      "*c* argument looks like a single numeric RGB or RGBA sequence, which should be avoided as value-mapping will have precedence in case its length matches with *x* & *y*.  Please use the *color* keyword-argument or provide a 2-D array with a single row if you intend to specify the same RGB or RGBA value for all points.\n",
      "*c* argument looks like a single numeric RGB or RGBA sequence, which should be avoided as value-mapping will have precedence in case its length matches with *x* & *y*.  Please use the *color* keyword-argument or provide a 2-D array with a single row if you intend to specify the same RGB or RGBA value for all points.\n",
      "*c* argument looks like a single numeric RGB or RGBA sequence, which should be avoided as value-mapping will have precedence in case its length matches with *x* & *y*.  Please use the *color* keyword-argument or provide a 2-D array with a single row if you intend to specify the same RGB or RGBA value for all points.\n",
      "*c* argument looks like a single numeric RGB or RGBA sequence, which should be avoided as value-mapping will have precedence in case its length matches with *x* & *y*.  Please use the *color* keyword-argument or provide a 2-D array with a single row if you intend to specify the same RGB or RGBA value for all points.\n",
      "*c* argument looks like a single numeric RGB or RGBA sequence, which should be avoided as value-mapping will have precedence in case its length matches with *x* & *y*.  Please use the *color* keyword-argument or provide a 2-D array with a single row if you intend to specify the same RGB or RGBA value for all points.\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "*c* argument looks like a single numeric RGB or RGBA sequence, which should be avoided as value-mapping will have precedence in case its length matches with *x* & *y*.  Please use the *color* keyword-argument or provide a 2-D array with a single row if you intend to specify the same RGB or RGBA value for all points.\n",
      "*c* argument looks like a single numeric RGB or RGBA sequence, which should be avoided as value-mapping will have precedence in case its length matches with *x* & *y*.  Please use the *color* keyword-argument or provide a 2-D array with a single row if you intend to specify the same RGB or RGBA value for all points.\n",
      "*c* argument looks like a single numeric RGB or RGBA sequence, which should be avoided as value-mapping will have precedence in case its length matches with *x* & *y*.  Please use the *color* keyword-argument or provide a 2-D array with a single row if you intend to specify the same RGB or RGBA value for all points.\n",
      "*c* argument looks like a single numeric RGB or RGBA sequence, which should be avoided as value-mapping will have precedence in case its length matches with *x* & *y*.  Please use the *color* keyword-argument or provide a 2-D array with a single row if you intend to specify the same RGB or RGBA value for all points.\n",
      "*c* argument looks like a single numeric RGB or RGBA sequence, which should be avoided as value-mapping will have precedence in case its length matches with *x* & *y*.  Please use the *color* keyword-argument or provide a 2-D array with a single row if you intend to specify the same RGB or RGBA value for all points.\n",
      "*c* argument looks like a single numeric RGB or RGBA sequence, which should be avoided as value-mapping will have precedence in case its length matches with *x* & *y*.  Please use the *color* keyword-argument or provide a 2-D array with a single row if you intend to specify the same RGB or RGBA value for all points.\n",
      "*c* argument looks like a single numeric RGB or RGBA sequence, which should be avoided as value-mapping will have precedence in case its length matches with *x* & *y*.  Please use the *color* keyword-argument or provide a 2-D array with a single row if you intend to specify the same RGB or RGBA value for all points.\n",
      "*c* argument looks like a single numeric RGB or RGBA sequence, which should be avoided as value-mapping will have precedence in case its length matches with *x* & *y*.  Please use the *color* keyword-argument or provide a 2-D array with a single row if you intend to specify the same RGB or RGBA value for all points.\n",
      "*c* argument looks like a single numeric RGB or RGBA sequence, which should be avoided as value-mapping will have precedence in case its length matches with *x* & *y*.  Please use the *color* keyword-argument or provide a 2-D array with a single row if you intend to specify the same RGB or RGBA value for all points.\n",
      "*c* argument looks like a single numeric RGB or RGBA sequence, which should be avoided as value-mapping will have precedence in case its length matches with *x* & *y*.  Please use the *color* keyword-argument or provide a 2-D array with a single row if you intend to specify the same RGB or RGBA value for all points.\n",
      "*c* argument looks like a single numeric RGB or RGBA sequence, which should be avoided as value-mapping will have precedence in case its length matches with *x* & *y*.  Please use the *color* keyword-argument or provide a 2-D array with a single row if you intend to specify the same RGB or RGBA value for all points.\n",
      "*c* argument looks like a single numeric RGB or RGBA sequence, which should be avoided as value-mapping will have precedence in case its length matches with *x* & *y*.  Please use the *color* keyword-argument or provide a 2-D array with a single row if you intend to specify the same RGB or RGBA value for all points.\n",
      "*c* argument looks like a single numeric RGB or RGBA sequence, which should be avoided as value-mapping will have precedence in case its length matches with *x* & *y*.  Please use the *color* keyword-argument or provide a 2-D array with a single row if you intend to specify the same RGB or RGBA value for all points.\n",
      "*c* argument looks like a single numeric RGB or RGBA sequence, which should be avoided as value-mapping will have precedence in case its length matches with *x* & *y*.  Please use the *color* keyword-argument or provide a 2-D array with a single row if you intend to specify the same RGB or RGBA value for all points.\n",
      "*c* argument looks like a single numeric RGB or RGBA sequence, which should be avoided as value-mapping will have precedence in case its length matches with *x* & *y*.  Please use the *color* keyword-argument or provide a 2-D array with a single row if you intend to specify the same RGB or RGBA value for all points.\n",
      "*c* argument looks like a single numeric RGB or RGBA sequence, which should be avoided as value-mapping will have precedence in case its length matches with *x* & *y*.  Please use the *color* keyword-argument or provide a 2-D array with a single row if you intend to specify the same RGB or RGBA value for all points.\n",
      "*c* argument looks like a single numeric RGB or RGBA sequence, which should be avoided as value-mapping will have precedence in case its length matches with *x* & *y*.  Please use the *color* keyword-argument or provide a 2-D array with a single row if you intend to specify the same RGB or RGBA value for all points.\n",
      "*c* argument looks like a single numeric RGB or RGBA sequence, which should be avoided as value-mapping will have precedence in case its length matches with *x* & *y*.  Please use the *color* keyword-argument or provide a 2-D array with a single row if you intend to specify the same RGB or RGBA value for all points.\n",
      "*c* argument looks like a single numeric RGB or RGBA sequence, which should be avoided as value-mapping will have precedence in case its length matches with *x* & *y*.  Please use the *color* keyword-argument or provide a 2-D array with a single row if you intend to specify the same RGB or RGBA value for all points.\n",
      "*c* argument looks like a single numeric RGB or RGBA sequence, which should be avoided as value-mapping will have precedence in case its length matches with *x* & *y*.  Please use the *color* keyword-argument or provide a 2-D array with a single row if you intend to specify the same RGB or RGBA value for all points.\n",
      "*c* argument looks like a single numeric RGB or RGBA sequence, which should be avoided as value-mapping will have precedence in case its length matches with *x* & *y*.  Please use the *color* keyword-argument or provide a 2-D array with a single row if you intend to specify the same RGB or RGBA value for all points.\n",
      "*c* argument looks like a single numeric RGB or RGBA sequence, which should be avoided as value-mapping will have precedence in case its length matches with *x* & *y*.  Please use the *color* keyword-argument or provide a 2-D array with a single row if you intend to specify the same RGB or RGBA value for all points.\n",
      "*c* argument looks like a single numeric RGB or RGBA sequence, which should be avoided as value-mapping will have precedence in case its length matches with *x* & *y*.  Please use the *color* keyword-argument or provide a 2-D array with a single row if you intend to specify the same RGB or RGBA value for all points.\n",
      "*c* argument looks like a single numeric RGB or RGBA sequence, which should be avoided as value-mapping will have precedence in case its length matches with *x* & *y*.  Please use the *color* keyword-argument or provide a 2-D array with a single row if you intend to specify the same RGB or RGBA value for all points.\n",
      "*c* argument looks like a single numeric RGB or RGBA sequence, which should be avoided as value-mapping will have precedence in case its length matches with *x* & *y*.  Please use the *color* keyword-argument or provide a 2-D array with a single row if you intend to specify the same RGB or RGBA value for all points.\n",
      "*c* argument looks like a single numeric RGB or RGBA sequence, which should be avoided as value-mapping will have precedence in case its length matches with *x* & *y*.  Please use the *color* keyword-argument or provide a 2-D array with a single row if you intend to specify the same RGB or RGBA value for all points.\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "*c* argument looks like a single numeric RGB or RGBA sequence, which should be avoided as value-mapping will have precedence in case its length matches with *x* & *y*.  Please use the *color* keyword-argument or provide a 2-D array with a single row if you intend to specify the same RGB or RGBA value for all points.\n",
      "*c* argument looks like a single numeric RGB or RGBA sequence, which should be avoided as value-mapping will have precedence in case its length matches with *x* & *y*.  Please use the *color* keyword-argument or provide a 2-D array with a single row if you intend to specify the same RGB or RGBA value for all points.\n",
      "*c* argument looks like a single numeric RGB or RGBA sequence, which should be avoided as value-mapping will have precedence in case its length matches with *x* & *y*.  Please use the *color* keyword-argument or provide a 2-D array with a single row if you intend to specify the same RGB or RGBA value for all points.\n",
      "*c* argument looks like a single numeric RGB or RGBA sequence, which should be avoided as value-mapping will have precedence in case its length matches with *x* & *y*.  Please use the *color* keyword-argument or provide a 2-D array with a single row if you intend to specify the same RGB or RGBA value for all points.\n",
      "*c* argument looks like a single numeric RGB or RGBA sequence, which should be avoided as value-mapping will have precedence in case its length matches with *x* & *y*.  Please use the *color* keyword-argument or provide a 2-D array with a single row if you intend to specify the same RGB or RGBA value for all points.\n",
      "*c* argument looks like a single numeric RGB or RGBA sequence, which should be avoided as value-mapping will have precedence in case its length matches with *x* & *y*.  Please use the *color* keyword-argument or provide a 2-D array with a single row if you intend to specify the same RGB or RGBA value for all points.\n",
      "*c* argument looks like a single numeric RGB or RGBA sequence, which should be avoided as value-mapping will have precedence in case its length matches with *x* & *y*.  Please use the *color* keyword-argument or provide a 2-D array with a single row if you intend to specify the same RGB or RGBA value for all points.\n",
      "*c* argument looks like a single numeric RGB or RGBA sequence, which should be avoided as value-mapping will have precedence in case its length matches with *x* & *y*.  Please use the *color* keyword-argument or provide a 2-D array with a single row if you intend to specify the same RGB or RGBA value for all points.\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x720 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "*c* argument looks like a single numeric RGB or RGBA sequence, which should be avoided as value-mapping will have precedence in case its length matches with *x* & *y*.  Please use the *color* keyword-argument or provide a 2-D array with a single row if you intend to specify the same RGB or RGBA value for all points.\n",
      "*c* argument looks like a single numeric RGB or RGBA sequence, which should be avoided as value-mapping will have precedence in case its length matches with *x* & *y*.  Please use the *color* keyword-argument or provide a 2-D array with a single row if you intend to specify the same RGB or RGBA value for all points.\n",
      "*c* argument looks like a single numeric RGB or RGBA sequence, which should be avoided as value-mapping will have precedence in case its length matches with *x* & *y*.  Please use the *color* keyword-argument or provide a 2-D array with a single row if you intend to specify the same RGB or RGBA value for all points.\n",
      "*c* argument looks like a single numeric RGB or RGBA sequence, which should be avoided as value-mapping will have precedence in case its length matches with *x* & *y*.  Please use the *color* keyword-argument or provide a 2-D array with a single row if you intend to specify the same RGB or RGBA value for all points.\n",
      "*c* argument looks like a single numeric RGB or RGBA sequence, which should be avoided as value-mapping will have precedence in case its length matches with *x* & *y*.  Please use the *color* keyword-argument or provide a 2-D array with a single row if you intend to specify the same RGB or RGBA value for all points.\n",
      "*c* argument looks like a single numeric RGB or RGBA sequence, which should be avoided as value-mapping will have precedence in case its length matches with *x* & *y*.  Please use the *color* keyword-argument or provide a 2-D array with a single row if you intend to specify the same RGB or RGBA value for all points.\n",
      "*c* argument looks like a single numeric RGB or RGBA sequence, which should be avoided as value-mapping will have precedence in case its length matches with *x* & *y*.  Please use the *color* keyword-argument or provide a 2-D array with a single row if you intend to specify the same RGB or RGBA value for all points.\n",
      "*c* argument looks like a single numeric RGB or RGBA sequence, which should be avoided as value-mapping will have precedence in case its length matches with *x* & *y*.  Please use the *color* keyword-argument or provide a 2-D array with a single row if you intend to specify the same RGB or RGBA value for all points.\n",
      "*c* argument looks like a single numeric RGB or RGBA sequence, which should be avoided as value-mapping will have precedence in case its length matches with *x* & *y*.  Please use the *color* keyword-argument or provide a 2-D array with a single row if you intend to specify the same RGB or RGBA value for all points.\n",
      "*c* argument looks like a single numeric RGB or RGBA sequence, which should be avoided as value-mapping will have precedence in case its length matches with *x* & *y*.  Please use the *color* keyword-argument or provide a 2-D array with a single row if you intend to specify the same RGB or RGBA value for all points.\n",
      "*c* argument looks like a single numeric RGB or RGBA sequence, which should be avoided as value-mapping will have precedence in case its length matches with *x* & *y*.  Please use the *color* keyword-argument or provide a 2-D array with a single row if you intend to specify the same RGB or RGBA value for all points.\n",
      "*c* argument looks like a single numeric RGB or RGBA sequence, which should be avoided as value-mapping will have precedence in case its length matches with *x* & *y*.  Please use the *color* keyword-argument or provide a 2-D array with a single row if you intend to specify the same RGB or RGBA value for all points.\n",
      "*c* argument looks like a single numeric RGB or RGBA sequence, which should be avoided as value-mapping will have precedence in case its length matches with *x* & *y*.  Please use the *color* keyword-argument or provide a 2-D array with a single row if you intend to specify the same RGB or RGBA value for all points.\n",
      "*c* argument looks like a single numeric RGB or RGBA sequence, which should be avoided as value-mapping will have precedence in case its length matches with *x* & *y*.  Please use the *color* keyword-argument or provide a 2-D array with a single row if you intend to specify the same RGB or RGBA value for all points.\n",
      "*c* argument looks like a single numeric RGB or RGBA sequence, which should be avoided as value-mapping will have precedence in case its length matches with *x* & *y*.  Please use the *color* keyword-argument or provide a 2-D array with a single row if you intend to specify the same RGB or RGBA value for all points.\n",
      "*c* argument looks like a single numeric RGB or RGBA sequence, which should be avoided as value-mapping will have precedence in case its length matches with *x* & *y*.  Please use the *color* keyword-argument or provide a 2-D array with a single row if you intend to specify the same RGB or RGBA value for all points.\n",
      "*c* argument looks like a single numeric RGB or RGBA sequence, which should be avoided as value-mapping will have precedence in case its length matches with *x* & *y*.  Please use the *color* keyword-argument or provide a 2-D array with a single row if you intend to specify the same RGB or RGBA value for all points.\n",
      "*c* argument looks like a single numeric RGB or RGBA sequence, which should be avoided as value-mapping will have precedence in case its length matches with *x* & *y*.  Please use the *color* keyword-argument or provide a 2-D array with a single row if you intend to specify the same RGB or RGBA value for all points.\n",
      "*c* argument looks like a single numeric RGB or RGBA sequence, which should be avoided as value-mapping will have precedence in case its length matches with *x* & *y*.  Please use the *color* keyword-argument or provide a 2-D array with a single row if you intend to specify the same RGB or RGBA value for all points.\n",
      "*c* argument looks like a single numeric RGB or RGBA sequence, which should be avoided as value-mapping will have precedence in case its length matches with *x* & *y*.  Please use the *color* keyword-argument or provide a 2-D array with a single row if you intend to specify the same RGB or RGBA value for all points.\n",
      "*c* argument looks like a single numeric RGB or RGBA sequence, which should be avoided as value-mapping will have precedence in case its length matches with *x* & *y*.  Please use the *color* keyword-argument or provide a 2-D array with a single row if you intend to specify the same RGB or RGBA value for all points.\n",
      "*c* argument looks like a single numeric RGB or RGBA sequence, which should be avoided as value-mapping will have precedence in case its length matches with *x* & *y*.  Please use the *color* keyword-argument or provide a 2-D array with a single row if you intend to specify the same RGB or RGBA value for all points.\n",
      "*c* argument looks like a single numeric RGB or RGBA sequence, which should be avoided as value-mapping will have precedence in case its length matches with *x* & *y*.  Please use the *color* keyword-argument or provide a 2-D array with a single row if you intend to specify the same RGB or RGBA value for all points.\n",
      "*c* argument looks like a single numeric RGB or RGBA sequence, which should be avoided as value-mapping will have precedence in case its length matches with *x* & *y*.  Please use the *color* keyword-argument or provide a 2-D array with a single row if you intend to specify the same RGB or RGBA value for all points.\n",
      "*c* argument looks like a single numeric RGB or RGBA sequence, which should be avoided as value-mapping will have precedence in case its length matches with *x* & *y*.  Please use the *color* keyword-argument or provide a 2-D array with a single row if you intend to specify the same RGB or RGBA value for all points.\n",
      "*c* argument looks like a single numeric RGB or RGBA sequence, which should be avoided as value-mapping will have precedence in case its length matches with *x* & *y*.  Please use the *color* keyword-argument or provide a 2-D array with a single row if you intend to specify the same RGB or RGBA value for all points.\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "*c* argument looks like a single numeric RGB or RGBA sequence, which should be avoided as value-mapping will have precedence in case its length matches with *x* & *y*.  Please use the *color* keyword-argument or provide a 2-D array with a single row if you intend to specify the same RGB or RGBA value for all points.\n",
      "*c* argument looks like a single numeric RGB or RGBA sequence, which should be avoided as value-mapping will have precedence in case its length matches with *x* & *y*.  Please use the *color* keyword-argument or provide a 2-D array with a single row if you intend to specify the same RGB or RGBA value for all points.\n",
      "*c* argument looks like a single numeric RGB or RGBA sequence, which should be avoided as value-mapping will have precedence in case its length matches with *x* & *y*.  Please use the *color* keyword-argument or provide a 2-D array with a single row if you intend to specify the same RGB or RGBA value for all points.\n",
      "*c* argument looks like a single numeric RGB or RGBA sequence, which should be avoided as value-mapping will have precedence in case its length matches with *x* & *y*.  Please use the *color* keyword-argument or provide a 2-D array with a single row if you intend to specify the same RGB or RGBA value for all points.\n",
      "*c* argument looks like a single numeric RGB or RGBA sequence, which should be avoided as value-mapping will have precedence in case its length matches with *x* & *y*.  Please use the *color* keyword-argument or provide a 2-D array with a single row if you intend to specify the same RGB or RGBA value for all points.\n",
      "*c* argument looks like a single numeric RGB or RGBA sequence, which should be avoided as value-mapping will have precedence in case its length matches with *x* & *y*.  Please use the *color* keyword-argument or provide a 2-D array with a single row if you intend to specify the same RGB or RGBA value for all points.\n",
      "*c* argument looks like a single numeric RGB or RGBA sequence, which should be avoided as value-mapping will have precedence in case its length matches with *x* & *y*.  Please use the *color* keyword-argument or provide a 2-D array with a single row if you intend to specify the same RGB or RGBA value for all points.\n",
      "*c* argument looks like a single numeric RGB or RGBA sequence, which should be avoided as value-mapping will have precedence in case its length matches with *x* & *y*.  Please use the *color* keyword-argument or provide a 2-D array with a single row if you intend to specify the same RGB or RGBA value for all points.\n",
      "*c* argument looks like a single numeric RGB or RGBA sequence, which should be avoided as value-mapping will have precedence in case its length matches with *x* & *y*.  Please use the *color* keyword-argument or provide a 2-D array with a single row if you intend to specify the same RGB or RGBA value for all points.\n",
      "*c* argument looks like a single numeric RGB or RGBA sequence, which should be avoided as value-mapping will have precedence in case its length matches with *x* & *y*.  Please use the *color* keyword-argument or provide a 2-D array with a single row if you intend to specify the same RGB or RGBA value for all points.\n",
      "*c* argument looks like a single numeric RGB or RGBA sequence, which should be avoided as value-mapping will have precedence in case its length matches with *x* & *y*.  Please use the *color* keyword-argument or provide a 2-D array with a single row if you intend to specify the same RGB or RGBA value for all points.\n",
      "*c* argument looks like a single numeric RGB or RGBA sequence, which should be avoided as value-mapping will have precedence in case its length matches with *x* & *y*.  Please use the *color* keyword-argument or provide a 2-D array with a single row if you intend to specify the same RGB or RGBA value for all points.\n",
      "*c* argument looks like a single numeric RGB or RGBA sequence, which should be avoided as value-mapping will have precedence in case its length matches with *x* & *y*.  Please use the *color* keyword-argument or provide a 2-D array with a single row if you intend to specify the same RGB or RGBA value for all points.\n",
      "*c* argument looks like a single numeric RGB or RGBA sequence, which should be avoided as value-mapping will have precedence in case its length matches with *x* & *y*.  Please use the *color* keyword-argument or provide a 2-D array with a single row if you intend to specify the same RGB or RGBA value for all points.\n",
      "*c* argument looks like a single numeric RGB or RGBA sequence, which should be avoided as value-mapping will have precedence in case its length matches with *x* & *y*.  Please use the *color* keyword-argument or provide a 2-D array with a single row if you intend to specify the same RGB or RGBA value for all points.\n",
      "*c* argument looks like a single numeric RGB or RGBA sequence, which should be avoided as value-mapping will have precedence in case its length matches with *x* & *y*.  Please use the *color* keyword-argument or provide a 2-D array with a single row if you intend to specify the same RGB or RGBA value for all points.\n",
      "*c* argument looks like a single numeric RGB or RGBA sequence, which should be avoided as value-mapping will have precedence in case its length matches with *x* & *y*.  Please use the *color* keyword-argument or provide a 2-D array with a single row if you intend to specify the same RGB or RGBA value for all points.\n",
      "*c* argument looks like a single numeric RGB or RGBA sequence, which should be avoided as value-mapping will have precedence in case its length matches with *x* & *y*.  Please use the *color* keyword-argument or provide a 2-D array with a single row if you intend to specify the same RGB or RGBA value for all points.\n",
      "*c* argument looks like a single numeric RGB or RGBA sequence, which should be avoided as value-mapping will have precedence in case its length matches with *x* & *y*.  Please use the *color* keyword-argument or provide a 2-D array with a single row if you intend to specify the same RGB or RGBA value for all points.\n",
      "*c* argument looks like a single numeric RGB or RGBA sequence, which should be avoided as value-mapping will have precedence in case its length matches with *x* & *y*.  Please use the *color* keyword-argument or provide a 2-D array with a single row if you intend to specify the same RGB or RGBA value for all points.\n",
      "*c* argument looks like a single numeric RGB or RGBA sequence, which should be avoided as value-mapping will have precedence in case its length matches with *x* & *y*.  Please use the *color* keyword-argument or provide a 2-D array with a single row if you intend to specify the same RGB or RGBA value for all points.\n",
      "*c* argument looks like a single numeric RGB or RGBA sequence, which should be avoided as value-mapping will have precedence in case its length matches with *x* & *y*.  Please use the *color* keyword-argument or provide a 2-D array with a single row if you intend to specify the same RGB or RGBA value for all points.\n",
      "*c* argument looks like a single numeric RGB or RGBA sequence, which should be avoided as value-mapping will have precedence in case its length matches with *x* & *y*.  Please use the *color* keyword-argument or provide a 2-D array with a single row if you intend to specify the same RGB or RGBA value for all points.\n",
      "*c* argument looks like a single numeric RGB or RGBA sequence, which should be avoided as value-mapping will have precedence in case its length matches with *x* & *y*.  Please use the *color* keyword-argument or provide a 2-D array with a single row if you intend to specify the same RGB or RGBA value for all points.\n",
      "*c* argument looks like a single numeric RGB or RGBA sequence, which should be avoided as value-mapping will have precedence in case its length matches with *x* & *y*.  Please use the *color* keyword-argument or provide a 2-D array with a single row if you intend to specify the same RGB or RGBA value for all points.\n",
      "*c* argument looks like a single numeric RGB or RGBA sequence, which should be avoided as value-mapping will have precedence in case its length matches with *x* & *y*.  Please use the *color* keyword-argument or provide a 2-D array with a single row if you intend to specify the same RGB or RGBA value for all points.\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "*c* argument looks like a single numeric RGB or RGBA sequence, which should be avoided as value-mapping will have precedence in case its length matches with *x* & *y*.  Please use the *color* keyword-argument or provide a 2-D array with a single row if you intend to specify the same RGB or RGBA value for all points.\n",
      "*c* argument looks like a single numeric RGB or RGBA sequence, which should be avoided as value-mapping will have precedence in case its length matches with *x* & *y*.  Please use the *color* keyword-argument or provide a 2-D array with a single row if you intend to specify the same RGB or RGBA value for all points.\n",
      "*c* argument looks like a single numeric RGB or RGBA sequence, which should be avoided as value-mapping will have precedence in case its length matches with *x* & *y*.  Please use the *color* keyword-argument or provide a 2-D array with a single row if you intend to specify the same RGB or RGBA value for all points.\n",
      "*c* argument looks like a single numeric RGB or RGBA sequence, which should be avoided as value-mapping will have precedence in case its length matches with *x* & *y*.  Please use the *color* keyword-argument or provide a 2-D array with a single row if you intend to specify the same RGB or RGBA value for all points.\n",
      "*c* argument looks like a single numeric RGB or RGBA sequence, which should be avoided as value-mapping will have precedence in case its length matches with *x* & *y*.  Please use the *color* keyword-argument or provide a 2-D array with a single row if you intend to specify the same RGB or RGBA value for all points.\n",
      "*c* argument looks like a single numeric RGB or RGBA sequence, which should be avoided as value-mapping will have precedence in case its length matches with *x* & *y*.  Please use the *color* keyword-argument or provide a 2-D array with a single row if you intend to specify the same RGB or RGBA value for all points.\n",
      "*c* argument looks like a single numeric RGB or RGBA sequence, which should be avoided as value-mapping will have precedence in case its length matches with *x* & *y*.  Please use the *color* keyword-argument or provide a 2-D array with a single row if you intend to specify the same RGB or RGBA value for all points.\n",
      "*c* argument looks like a single numeric RGB or RGBA sequence, which should be avoided as value-mapping will have precedence in case its length matches with *x* & *y*.  Please use the *color* keyword-argument or provide a 2-D array with a single row if you intend to specify the same RGB or RGBA value for all points.\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x720 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "import matplotlib.pyplot as plt\n",
    "import numpy as np\n",
    "from scipy.stats import norm\n",
    "import warnings\n",
    "warnings.filterwarnings('ignore')\n",
    "np.random.seed(0)\n",
    "\n",
    "X = np.linspace(-5,5,num=20)\n",
    "X0 = X*np.random.rand(len(X))+15 # Create data cluster 1\n",
    "X1 = X*np.random.rand(len(X))-15 # Create data cluster 2\n",
    "X2 = X*np.random.rand(len(X)) # Create data cluster 3\n",
    "X_tot = np.stack((X0,X1,X2)).flatten() # Combine the clusters to get the random datapoints from above\n",
    "\n",
    "class GM1D:\n",
    "\n",
    "    def __init__(self,X,iterations):\n",
    "        self.iterations = iterations\n",
    "        self.X = X\n",
    "        self.mu = None\n",
    "        self.pi = None\n",
    "        self.var = None\n",
    "  \n",
    "\n",
    "    def run(self):\n",
    "        \n",
    "\n",
    "        \"\"\"\n",
    "        Instantiate the random mu, pi and var\n",
    "        \"\"\"\n",
    "        self.mu = [-8,8,5]\n",
    "        self.pi = [1/3,1/3,1/3]\n",
    "        self.var = [5,3,1]\n",
    "        \n",
    "        \n",
    "        \n",
    "        \"\"\"\n",
    "        E-Step\n",
    "        \"\"\"\n",
    "        \n",
    "        for iter in range(self.iterations):\n",
    "\n",
    "            \"\"\"Create the array r with dimensionality nxK\"\"\"\n",
    "            r = np.zeros((len(X_tot),3))  \n",
    "\n",
    "  \n",
    "            \"\"\"\n",
    "            Probability for each datapoint x_i to belong to gaussian g \n",
    "            \"\"\"\n",
    "            for c,g,p in zip(range(3),[norm(loc=self.mu[0],scale=self.var[0]),\n",
    "                                       norm(loc=self.mu[1],scale=self.var[1]),\n",
    "                                       norm(loc=self.mu[2],scale=self.var[2])],self.pi):\n",
    "                r[:,c] = p*g.pdf(X_tot) # Write the probability that x belongs to gaussian c in column c. \n",
    "                                      # Therewith we get a 60x3 array filled with the probability that each x_i belongs to one of the gaussians\n",
    "            \"\"\"\n",
    "            Normalize the probabilities such that each row of r sums to 1 and weight it by mu_c == the fraction of points belonging to \n",
    "            cluster c\n",
    "            \"\"\"\n",
    "            for i in range(len(r)):\n",
    "                r[i] = r[i]/(np.sum(self.pi)*np.sum(r,axis=1)[i])\n",
    "\n",
    "\n",
    "            \"\"\"Plot the data\"\"\"\n",
    "\n",
    "            fig = plt.figure(figsize=(10,10))\n",
    "            ax0 = fig.add_subplot(111)\n",
    "\n",
    "\n",
    "            for i in range(len(r)):\n",
    "                ax0.scatter(self.X[i],0,c=np.array([r[i][0],r[i][1],r[i][2]]),s=100) \n",
    "\n",
    "\n",
    "            \"\"\"Plot the gaussians\"\"\"\n",
    "\n",
    "\n",
    "            for g,c in zip([norm(loc=self.mu[0],scale=self.var[0]).pdf(np.linspace(-20,20,num=60)),\n",
    "                            norm(loc=self.mu[1],scale=self.var[1]).pdf(np.linspace(-20,20,num=60)),\n",
    "                            norm(loc=self.mu[2],scale=self.var[2]).pdf(np.linspace(-20,20,num=60))],['r','g','b']):\n",
    "                ax0.plot(np.linspace(-20,20,num=60),g,c=c)\n",
    "            \n",
    "            \n",
    "            \n",
    "            \"\"\"M-Step\"\"\"\n",
    "    \n",
    "\n",
    "            \"\"\"calculate m_c\"\"\"\n",
    "            m_c = []\n",
    "            for c in range(len(r[0])):\n",
    "                m = np.sum(r[:,c])\n",
    "                m_c.append(m) # For each cluster c, calculate the m_c and add it to the list m_c\n",
    "\n",
    "            \"\"\"calculate pi_c\"\"\"\n",
    "            for k in range(len(m_c)):\n",
    "                self.pi[k] = (m_c[k]/np.sum(m_c)) # For each cluster c, calculate the fraction of points pi_c which belongs to cluster c\n",
    "\n",
    "            \"\"\"calculate mu_c\"\"\"\n",
    "            self.mu = np.sum(self.X.reshape(len(self.X),1)*r,axis=0)/m_c\n",
    "\n",
    "\n",
    "            \"\"\"calculate var_c\"\"\"\n",
    "            var_c = []\n",
    "\n",
    "            for c in range(len(r[0])):\n",
    "                var_c.append((1/m_c[c])*np.dot(((np.array(r[:,c]).reshape(60,1))*(self.X.reshape(len(self.X),1)-self.mu[c])).T,(self.X.reshape(len(self.X),1)-self.mu[c])))\n",
    "\n",
    "\n",
    "\n",
    "            plt.show()\n",
    "    \n",
    "\n",
    "GM1D = GM1D(X_tot,10)\n",
    "GM1D.run()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
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