polylines-are-just-numbers.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "94716c54",
   "metadata": {},
   "source": [
    "# Polylines are just numbers\n",
    "\n",
    "By [Allison Parrish](https://www.decontextualize.com/)\n",
    "\n",
    "In this notebook, I review some methods for manipulating polylines: transforming them and filtering them. Before proceeding, I advise you to review [this notebook on drawing with vsketch](lines-and-asemic-vsketch.ipynb) and install the vsketch and Bezmerizing libraries."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 62,
   "id": "a58f8216",
   "metadata": {},
   "outputs": [],
   "source": [
    "import vsketch\n",
    "from bezmerizing import Polyline\n",
    "import numpy as np\n",
    "from numpy.random import uniform, normal\n",
    "import random"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "a5f99b62",
   "metadata": {},
   "source": [
    "## Doing math on polylines\n",
    "\n",
    "We've been representing polylines so far as a Python list of lists. For example:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "a8ad6693",
   "metadata": {},
   "outputs": [],
   "source": [
    "pline = [[10, -30], [-15, -10], [-20, 10], [-10, 30], [25, 45], [55, 0], [20, -10]]"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "452d95af",
   "metadata": {},
   "source": [
    "This is a polyline with a number of points, each of which is represented as a list with two items (one for the X coordinate, the other for the Y coordinate.) As a quick review, here's how to draw this polyline with vsketch (make sure to install vsketch before proceeding):"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "edde3dc0",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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AkJwYAIDkxAAAJCcGACA5MQAAyYkBAEhODABAcmIAAJITAwCQnBgAgOTEAAAkJwYAIDkxAADJiQEASE4MAEByYgAAkhMDAJCcGACA5MQAACQnBgAgOTEAAMmJAQBITgwAQHJiAACSEwMAkNxm6Q9owc7OTulPAOAH/Lt5OGLgGBcvXlz4Z7e3t8f7EAAOOHfuXOlP6IIYOMbm5mZsbW0t9LO7u7sjfw0ADM/NAAAkJwYAIDkxAADJiQEASE4MAEByYgAAkhMDAJCcGACA5E7s7e3tlf4IAKAcLwMAkJwYAIDkxAAAJCcGACA5MQAAyYkBAEhODABAcmIAAJITAwCQ3P8BNNE2lRPWzoQAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "vsk = vsketch.Vsketch()\n",
    "vsk.size(\"100mm\", \"100mm\")\n",
    "vsk.scale(\"1mm\")\n",
    "vsk.polygon(pline)\n",
    "vsk.display()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "f730b029",
   "metadata": {},
   "source": [
    "We already discussed how to transform how a polyline is drawn using vsketch's `.pushMatrix()` method and the various transformation functions like `.translate()`, `.rotate()`, and `.scale()`:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "ff4bfd3d",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "vsk = vsketch.Vsketch()\n",
    "vsk.size(\"100mm\", \"100mm\")\n",
    "vsk.scale(\"1mm\")\n",
    "vsk.stroke(1)\n",
    "vsk.polygon(pline)\n",
    "with vsk.pushMatrix():\n",
    "    vsk.stroke(2)\n",
    "    vsk.translate(25, 25) # move over and down\n",
    "    vsk.rotate(-np.pi) # rotate -180 degrees\n",
    "    vsk.scale(0.5) # half size\n",
    "    vsk.polygon(pline)\n",
    "vsk.display()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "ae592c73",
   "metadata": {},
   "source": [
    "This is all well and good! It turns out that we can accomplish these same transformations by doing math on the polylines directly, which also opens up a few other powerful techniques for manipulating polylines beyond the three basic transformation functions (translate, rotate, scale).\n",
    "\n",
    "To illustrate: you can translate a polyline by adding a fixed value to each coordinate of the polyline. Here's how to do that in Python, using a `for` loop:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "4be316b6",
   "metadata": {},
   "outputs": [],
   "source": [
    "pline_translated = []\n",
    "for coord in pline:\n",
    "    pline_translated.append([coord[0]+5, coord[1]+5])"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "9c2e271c",
   "metadata": {},
   "source": [
    "And the same thing with a list comprehension:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "2464b90d",
   "metadata": {},
   "outputs": [],
   "source": [
    "pline_translated = [[x+5, y+5] for x, y in pline]"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "95b8ca82",
   "metadata": {},
   "source": [
    "If we draw both of these polylines, you can see that the new polyline that we've constructed is a \"translation\" of the original:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "fb9b95dc",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "vsk = vsketch.Vsketch()\n",
    "vsk.size(\"100mm\", \"100mm\")\n",
    "vsk.scale(\"1mm\")\n",
    "vsk.stroke(1)\n",
    "vsk.polygon(pline)\n",
    "vsk.stroke(2)\n",
    "vsk.polygon(pline_translated)\n",
    "vsk.display()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "257e5d48",
   "metadata": {},
   "source": [
    "You can use the same basic idiom to scale a polyline:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "b316d372",
   "metadata": {},
   "outputs": [],
   "source": [
    "pline_scaled = [[x*0.5, y*0.5] for x, y in pline]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "10503dd9",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "vsk = vsketch.Vsketch()\n",
    "vsk.size(\"100mm\", \"100mm\")\n",
    "vsk.scale(\"1mm\")\n",
    "vsk.stroke(1)\n",
    "vsk.polygon(pline)\n",
    "vsk.stroke(2)\n",
    "vsk.polygon(pline_scaled)\n",
    "vsk.display()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "15cfff91",
   "metadata": {},
   "source": [
    "Rotation is a bit trickier, but we can still do it with the same idiom:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "1da685fa",
   "metadata": {},
   "outputs": [],
   "source": [
    "t = np.pi * -0.5 # 90 degrees counter-clockwise\n",
    "pline_rotated = [[x*np.cos(t)-y*np.sin(t), x*np.sin(t)+y*np.cos(t)] for x, y in pline]"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "438935fa",
   "metadata": {},
   "source": [
    "(For the curious, the formula in the list comprehension above is the [rotation matrix](https://en.wikipedia.org/wiki/Rotation_matrix).)\n",
    "\n",
    "Here's what it looks like:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "226e1986",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "vsk = vsketch.Vsketch()\n",
    "vsk.size(\"100mm\", \"100mm\")\n",
    "vsk.scale(\"1mm\")\n",
    "vsk.stroke(1)\n",
    "vsk.polygon(pline)\n",
    "vsk.stroke(2)\n",
    "vsk.polygon(pline_rotated)\n",
    "vsk.display()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "96b7c290",
   "metadata": {},
   "source": [
    "### Gluing together polylines\n",
    "\n",
    "Representing polylines as lists has another advantage: we can take two polylines and \"glue\" them together, simply by concatenating the lists that represent those polylines. For example, here's another polyline:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "7d3631d5",
   "metadata": {},
   "outputs": [],
   "source": [
    "pline2 = [[45, -25], [55, -10], [65, -25]]"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "f2957d08",
   "metadata": {},
   "source": [
    "And here's that polyline, drawn along with our first polyline:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "91db20d1",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "vsk = vsketch.Vsketch()\n",
    "vsk.size(\"100mm\", \"100mm\")\n",
    "vsk.scale(\"1mm\")\n",
    "vsk.stroke(1)\n",
    "vsk.polygon(pline)\n",
    "vsk.stroke(2)\n",
    "vsk.polygon(pline2)\n",
    "vsk.display()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "6b046e68",
   "metadata": {},
   "source": [
    "You can combine these two polylines into a single polyline using the `+` operator, which, when both its operands are lists, returns a new list with all of the elements of the original list:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "6a601585",
   "metadata": {},
   "outputs": [],
   "source": [
    "pline_combo = pline + pline2"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "id": "50f7e161",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[[10, -30],\n",
       " [-15, -10],\n",
       " [-20, 10],\n",
       " [-10, 30],\n",
       " [25, 45],\n",
       " [55, 0],\n",
       " [20, -10],\n",
       " [45, -25],\n",
       " [55, -10],\n",
       " [65, -25]]"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pline_combo"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "4592582d",
   "metadata": {},
   "source": [
    "The number of points in the new polyline is exactly the sum of the number of points of the two polylines that came together to create it:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "id": "f3f1c2aa",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "10"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "len(pline_combo)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "id": "50ad5423",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "10"
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "len(pline) + len(pline2)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "9f436d89",
   "metadata": {},
   "source": [
    "Here's what the new polyline looks like:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "id": "037b4bc3",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "vsk = vsketch.Vsketch()\n",
    "vsk.size(\"100mm\", \"100mm\")\n",
    "vsk.scale(\"1mm\")\n",
    "vsk.stroke(1)\n",
    "vsk.polygon(pline_combo)\n",
    "vsk.display()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "f96ce913",
   "metadata": {},
   "source": [
    "### Polyline transformations with Bezmerizing"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "1e649311",
   "metadata": {},
   "source": [
    "The Bezmerizing library's `Polyline` class has a method for each of these transformations, which returns another `Polyline` with that transformation applied:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "id": "b5844582",
   "metadata": {},
   "outputs": [],
   "source": [
    "bzline = Polyline(pline)\n",
    "bzline_rotated = bzline.rotate(np.pi * -0.5)\n",
    "bzline_translated = bzline.translate(-10, 5)\n",
    "bzline_scaled = bzline.scale(0.75)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "b3754a3b",
   "metadata": {},
   "source": [
    "And here's what those look like. (Remember that you need to get the actual vertices of a `Polyline` object with its `.vertices` attribute if you want to draw the polyline with vsketch.)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "id": "81c77618",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "vsk = vsketch.Vsketch()\n",
    "vsk.size(\"100mm\", \"100mm\")\n",
    "vsk.scale(\"1mm\")\n",
    "vsk.stroke(1)\n",
    "vsk.polygon(bzline.vertices)\n",
    "vsk.stroke(2)\n",
    "vsk.polygon(bzline_rotated.vertices)\n",
    "vsk.stroke(3)\n",
    "vsk.polygon(bzline_translated.vertices)\n",
    "vsk.stroke(4)\n",
    "vsk.polygon(bzline_scaled.vertices)\n",
    "vsk.display()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "547ab800",
   "metadata": {},
   "source": [
    "Oh, and by the way, you can combine two `Polyline` objects with the `+` operator as well:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "id": "138c4113",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "bzline_combo = bzline + bzline_rotated + bzline_translated + bzline_scaled\n",
    "vsk = vsketch.Vsketch()\n",
    "vsk.size(\"100mm\", \"100mm\")\n",
    "vsk.scale(\"1mm\")\n",
    "vsk.polygon(bzline_combo.vertices) # one big line!\n",
    "vsk.display()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "9b522e6d",
   "metadata": {},
   "source": [
    "## More sophisticated transformations\n",
    "\n",
    "All of this seems pretty goofy, since it's just duplicating what we can already do with vsketch's transformation functions. But stick with me here. In this section, I'm going to show some examples of transformations that you can perform on polylines that are more sophisticated than your basic rotates, translates and scales.\n",
    "\n",
    "First, I'm going to make a more interesting polyline by taking the polyline formed by the Catmull-Rom spline of our example polylines:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "id": "b75b3044",
   "metadata": {},
   "outputs": [],
   "source": [
    "pts = Polyline(pline_combo).catmull_spline(-0.5).to_polyline(20)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "id": "e0612b59",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "vsk = vsketch.Vsketch()\n",
    "vsk.size(\"100mm\", \"100mm\")\n",
    "vsk.scale(\"1mm\")\n",
    "vsk.polygon(pts)\n",
    "vsk.display()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "78a684bf",
   "metadata": {},
   "source": [
    "### Making polylines noisy"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "1afa342f",
   "metadata": {},
   "source": [
    "One thing we can do with this polyline is add a little bit of noise to each point, like so:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "id": "417e00ac",
   "metadata": {},
   "outputs": [],
   "source": [
    "noisy_pts = []\n",
    "for coord in pts:\n",
    "    noisy_pts.append([coord[0]+uniform(-1, 1), coord[1]+uniform(-1, 1)])"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "f8be39cd",
   "metadata": {},
   "source": [
    "This code is creating a new polyline based on the original, in which a small random number (drawn from a uniform distribution) is added to each point. We end up with a line that is a bit squiggly:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "id": "0c3c0ad9",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "vsk = vsketch.Vsketch()\n",
    "vsk.size(\"100mm\", \"100mm\")\n",
    "vsk.scale(\"1mm\")\n",
    "vsk.polygon(noisy_pts)\n",
    "vsk.display()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "90492419",
   "metadata": {},
   "source": [
    "We can also *condition* the extent of the noise based on some other factor, such as the Y coordinate of the point:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "id": "e4cf5769",
   "metadata": {},
   "outputs": [],
   "source": [
    "noise_by_x_pts = []\n",
    "for coord in pts:\n",
    "    factor = coord[1] * 0.1\n",
    "    noise_by_x_pts.append([coord[0]+uniform(-factor, factor), coord[1]+uniform(-factor, factor)])"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "db56e259",
   "metadata": {},
   "source": [
    "Here you can see that the line gets noisier as the Y coordinate gets further from 0 (in this sketch, further away from the horizontal midline):"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "id": "18349efe",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "vsk = vsketch.Vsketch()\n",
    "vsk.size(\"100mm\", \"100mm\")\n",
    "vsk.scale(\"1mm\")\n",
    "vsk.stroke(1)\n",
    "vsk.polygon(pts)\n",
    "vsk.stroke(2)\n",
    "vsk.polygon(noise_by_x_pts)\n",
    "vsk.display()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "7508e414",
   "metadata": {},
   "source": [
    "Here's an example of using Python's `enumerate()` function to tell us how far along the polyline we are in the `for` loop, and increasing the amount of noise as we approach the end of the polyline:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "id": "9be002fb",
   "metadata": {},
   "outputs": [],
   "source": [
    "gradual_noise_pts = []\n",
    "for i, coord in enumerate(pts):\n",
    "    factor = (i / len(pts)) * 4 # goes from 0 to 4 as we traverse the list\n",
    "    gradual_noise_pts.append([coord[0]+uniform(-factor, factor),\n",
    "                              coord[1]+uniform(-factor, factor)])"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "1e9527ae",
   "metadata": {},
   "source": [
    "Here's what that looks like:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "id": "7f419fac",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "vsk = vsketch.Vsketch()\n",
    "vsk.size(\"100mm\", \"100mm\")\n",
    "vsk.scale(\"1mm\")\n",
    "vsk.stroke(1)\n",
    "vsk.polygon(pts)\n",
    "vsk.stroke(2)\n",
    "vsk.polygon(gradual_noise_pts)\n",
    "vsk.display()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "008c657c",
   "metadata": {},
   "source": [
    "Using `enumerate()`, we can also selectively apply noise to a subset of points. The following example adds noise to every fifth point in the polyline:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "id": "2c51b194",
   "metadata": {},
   "outputs": [],
   "source": [
    "skip_noise_pts = []\n",
    "for i, coord in enumerate(pts):\n",
    "    if i % 5 == 0:\n",
    "        skip_noise_pts.append([coord[0]+uniform(-5, 5),\n",
    "                              coord[1]+uniform(-5, 5)])\n",
    "    else:\n",
    "        skip_noise_pts.append(coord)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "f951a4e6",
   "metadata": {},
   "source": [
    "This gives us a nice spiky look:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "id": "c14d11d6",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "vsk = vsketch.Vsketch()\n",
    "vsk.size(\"100mm\", \"100mm\")\n",
    "vsk.scale(\"1mm\")\n",
    "vsk.stroke(1)\n",
    "vsk.polygon(pts)\n",
    "vsk.stroke(2)\n",
    "vsk.polygon(skip_noise_pts)\n",
    "vsk.display()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "ddf09f95",
   "metadata": {},
   "source": [
    "**Exercise**: Make a variation on the above sketch where the noise is applied not every $n$ points, but at (approximately) evenly-spaced distances from the beginning to the end of the polyline."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "89bdf44a",
   "metadata": {},
   "source": [
    "**Advanced example**: One potential thing we can do here is create several variations on the same polyline, by adding noise to the polyline's points, then running it through Catmull-Rom. (In this example, I'm applying noise to our original polyline, not the Catmull-Rom spline in the previous examples.)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "id": "7bd1f564",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "vsk = vsketch.Vsketch()\n",
    "vsk.size(\"200mm\", \"50mm\")\n",
    "vsk.scale(\"1mm\")\n",
    "for i in range(10):\n",
    "    # figures get noisier from left to right\n",
    "    noisy = [[x+uniform(-i, i), y+uniform(-i, i)] for x, y in pline_combo]\n",
    "    noisy_curve = Polyline(noisy).catmull_spline(-0.5).to_polyline(20)\n",
    "    with vsk.pushMatrix():\n",
    "        vsk.translate(-100 + (i * 20), 0)\n",
    "        vsk.scale(0.2)\n",
    "        vsk.polygon(noisy_curve)\n",
    "vsk.display()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "52b37269",
   "metadata": {},
   "source": [
    "### Skews, sines, and more\n",
    "\n",
    "Of course, we don't need to limit ourselves to randomness. We can apply *any* mathematical function to the points in the polyline. For example, you can [*shear* (or skew)](https://en.wikipedia.org/wiki/Shear_mapping) the polyline like so, by adding a factor of the Y coordinate to the X coordinate, and a factor of the X coordinate to the Y coordinate:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "id": "a3b831f7",
   "metadata": {},
   "outputs": [],
   "source": [
    "shear_pts = []\n",
    "angle_x = np.pi * -0.25\n",
    "angle_y = 0\n",
    "for coord in pts:\n",
    "    shear_pts.append([coord[0]+angle_x*coord[1],\n",
    "                      coord[1]+angle_y*coord[0]])"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "2907c3a3",
   "metadata": {},
   "source": [
    "Applying the shear with a zero Y angle and a slight X angle creates an italic effect:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "id": "ba68ea16",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "vsk = vsketch.Vsketch()\n",
    "vsk.size(\"100mm\", \"100mm\")\n",
    "vsk.scale(\"1mm\")\n",
    "vsk.stroke(1)\n",
    "vsk.polygon(pts)\n",
    "vsk.stroke(2)\n",
    "vsk.polygon(shear_pts)\n",
    "vsk.display()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "47b30459",
   "metadata": {},
   "source": [
    "Using `enumerate()`, we can apply the shear effect differently along the polyline:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "id": "d6ab2764",
   "metadata": {},
   "outputs": [],
   "source": [
    "gradual_shear_pts = []\n",
    "angle_x = np.pi * -0.25\n",
    "angle_y = 0\n",
    "for i, coord in enumerate(pts):\n",
    "    factor = i / len(pts) # goes from 0 to 1\n",
    "    gradual_shear_pts.append([coord[0]+angle_x*coord[1]*factor,\n",
    "                      coord[1]+angle_y*coord[0]*factor])"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "bbd366df",
   "metadata": {},
   "source": [
    "You can see that this applies no shear at the beginning of the figure, escalating to full shear by the end:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "id": "439bea10",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "vsk = vsketch.Vsketch()\n",
    "vsk.size(\"100mm\", \"100mm\")\n",
    "vsk.scale(\"1mm\")\n",
    "vsk.stroke(1)\n",
    "vsk.polygon(pts)\n",
    "vsk.stroke(2)\n",
    "vsk.polygon(gradual_shear_pts)\n",
    "vsk.display()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "c1e6f216",
   "metadata": {},
   "source": [
    "You can create a wavy line by applying a sine/cosine functions to each point, using either the position of that point:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "id": "e8237b45",
   "metadata": {},
   "outputs": [],
   "source": [
    "wavy_pts = []\n",
    "amp = 5 # adjust to make waves higher\n",
    "freq_mult = 0.125 # adjust frequency of waves\n",
    "for coord in pts:\n",
    "    wavy_pts.append([coord[0] + np.sin(coord[0]*freq_mult)*amp,\n",
    "                     coord[1] + np.cos(coord[1]*freq_mult)*amp])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "id": "3582dde5",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "vsk = vsketch.Vsketch()\n",
    "vsk.size(\"100mm\", \"100mm\")\n",
    "vsk.scale(\"1mm\")\n",
    "vsk.stroke(1)\n",
    "vsk.polygon(pts)\n",
    "vsk.stroke(2)\n",
    "vsk.polygon(wavy_pts)\n",
    "vsk.display()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "f2d16351",
   "metadata": {},
   "source": [
    "... or the index of that point:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "id": "4818fea0",
   "metadata": {},
   "outputs": [],
   "source": [
    "wavy_idx_pts = []\n",
    "amp = 5 # adjust to make waves higher\n",
    "freq_mult = 0.5 # adjust frequency of waves\n",
    "for i, coord in enumerate(pts):\n",
    "    wavy_idx_pts.append([coord[0] + np.sin(i*freq_mult)*amp,\n",
    "                         coord[1] + np.cos(i*freq_mult)*amp])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "id": "26f1eab5",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "vsk = vsketch.Vsketch()\n",
    "vsk.size(\"100mm\", \"100mm\")\n",
    "vsk.scale(\"1mm\")\n",
    "vsk.stroke(1)\n",
    "vsk.polygon(pts)\n",
    "vsk.stroke(2)\n",
    "vsk.polygon(wavy_idx_pts)\n",
    "vsk.display()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "b9093b6e",
   "metadata": {},
   "source": [
    "(See [the Imitating Line Thickness notebook](imitating-line-thickness-variation.ipynb) for an example of performing variations along the normal of a polyline, e.g., at right angles to its direction of movement, rather than variations that depend on the X and Y coordinates.)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "cd7ddef1",
   "metadata": {},
   "source": [
    "### Filtering polylines\n",
    "\n",
    "Finally, we can write some Python code to *filter* polylines. For example, the following code returns a polyline with only points whose Y coordinate is greater than zero in our example polyline:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 43,
   "id": "311664a2",
   "metadata": {},
   "outputs": [],
   "source": [
    "bottom_pline = []\n",
    "for coord in pts:\n",
    "    if coord[1] > 0:\n",
    "        bottom_pline.append(coord)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "a8377532",
   "metadata": {},
   "source": [
    "Here's what it looks like when we draw it:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 44,
   "id": "d4346439",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "vsk = vsketch.Vsketch()\n",
    "vsk.size(\"100mm\", \"100mm\")\n",
    "vsk.scale(\"1mm\")\n",
    "vsk.polygon(bottom_pline)\n",
    "vsk.display()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "6e4bf427",
   "metadata": {},
   "source": [
    "Or we can grab only the portion of the polyline whose X coordinate is less than, say, 30:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 45,
   "id": "dbe7e45c",
   "metadata": {},
   "outputs": [],
   "source": [
    "left_pline = []\n",
    "for coord in pts:\n",
    "    if coord[0] < 30:\n",
    "        left_pline.append(coord)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "8b914af7",
   "metadata": {},
   "source": [
    "In this case, our \"slice\" of the polyline actually breaks that polyline into several slices that aren't connected. Our method for \"filtering\" a polyline is pretty crude, so you'll notice in the following sketch that there is a segment that connects (what should be) two discontinuous parts."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 46,
   "id": "b0b62251",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "vsk = vsketch.Vsketch()\n",
    "vsk.size(\"100mm\", \"100mm\")\n",
    "vsk.scale(\"1mm\")\n",
    "vsk.polygon(left_pline)\n",
    "vsk.display()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "f595ada6",
   "metadata": {},
   "source": [
    "**Advanced example**: Here's some code that draws polylines filtered from the original polyline, based on how far each point is from evenly-spaced points on the polyline:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 47,
   "id": "de0098ba",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "import math\n",
    "vsk = vsketch.Vsketch()\n",
    "vsk.size(\"200mm\", \"50mm\")\n",
    "vsk.scale(\"1mm\")\n",
    "# how many points to skip\n",
    "step = int(len(pts) / 10)\n",
    "# iterate from zero up to the number of points, with step\n",
    "for i in range(0, len(pts), step):\n",
    "    # only the points that are closer than 20mm to the current point\n",
    "    filtered = [[x, y] for x, y in pts\n",
    "                if math.dist([x, y], [pts[i][0], pts[i][1]]) < 20]\n",
    "    with vsk.pushMatrix():\n",
    "        vsk.translate(-100 + i*1.25, 0)\n",
    "        vsk.scale(0.2)\n",
    "        vsk.stroke(1)\n",
    "        vsk.strokeWeight(1)\n",
    "        vsk.polygon(pts)\n",
    "        vsk.stroke(2)\n",
    "        vsk.strokeWeight(4)\n",
    "        vsk.polygon(filtered)\n",
    "vsk.display()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "76f185d8",
   "metadata": {},
   "source": [
    "## Asemic cursive example\n",
    "\n",
    "Let's put all of these techniques together into one example, creating a page of asemic cursive writing. We'll do this by first writing a function that generates an asemic glyph, and then combine several of those glyphs into one \"connected\" glyph. We'll skew that slightly to give it a cursive look, and then filter it to remove subsets of points. Here's a function for generating a glyph:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 48,
   "id": "23fb72ec",
   "metadata": {},
   "outputs": [],
   "source": [
    "def glyph():\n",
    "    xgrid = [0, 0.5, 1, 1.5, 2]\n",
    "    ygrid = [0, 0.333, 1, 1.333, 2]\n",
    "    pts = []\n",
    "    for i in range(6):\n",
    "        pts.append([random.choice(xgrid), random.choice(ygrid)])\n",
    "    return pts"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "0a2837fd",
   "metadata": {},
   "source": [
    "Here's what one of these glyphs looks like:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 50,
   "id": "389ac9d3",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "vsk = vsketch.Vsketch()\n",
    "vsk.size(\"100mm\", \"100mm\")\n",
    "vsk.scale(\"1mm\")\n",
    "with vsk.pushMatrix():\n",
    "    vsk.scale(40)\n",
    "    vsk.polygon(glyph())\n",
    "vsk.display()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "4f16f3af",
   "metadata": {},
   "source": [
    "Now, we'll chain together several of these glyphs. In the code below, I generate $n$ glyphs. As I generate each glyph, I translate it over a bit (so it'll fall next to the previous glyph, instead of on top of it) and add it to the ongoing flat list of glyphs (which ends up being one big polyline):"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 51,
   "id": "e4e2cb82",
   "metadata": {},
   "outputs": [],
   "source": [
    "cursive_line = []\n",
    "for i in range(16):\n",
    "    this_glyph = glyph()\n",
    "    translated = [[x + i * 2.5, y] for x, y in this_glyph]\n",
    "    cursive_line += translated"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "934a8aba",
   "metadata": {},
   "source": [
    "Here's what it looks like when we draw it:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 52,
   "id": "b88c21f7",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "vsk = vsketch.Vsketch()\n",
    "vsk.size(\"200mm\", \"50mm\")\n",
    "vsk.scale(\"1mm\")\n",
    "with vsk.pushMatrix():\n",
    "    vsk.scale(5)\n",
    "    vsk.polygon(cursive_line)\n",
    "vsk.display()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "3676e564",
   "metadata": {},
   "source": [
    "If we use Bezmerizing to turn this into a Bezier spline, we do indeed get something that looks like handwriting:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 53,
   "id": "04aaa293",
   "metadata": {},
   "outputs": [],
   "source": [
    "cursive_curve = Polyline(cursive_line).catmull_spline(-0.75).to_polyline(20)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 54,
   "id": "06fdf61d",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "vsk = vsketch.Vsketch()\n",
    "vsk.size(\"200mm\", \"50mm\")\n",
    "vsk.scale(\"1mm\")\n",
    "with vsk.pushMatrix():\n",
    "    vsk.scale(5)\n",
    "    vsk.polygon(cursive_curve)\n",
    "vsk.display()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "734b90a8",
   "metadata": {},
   "source": [
    "Adding a bit of shear to this gives the effect of tilting the cursive to the right:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 55,
   "id": "0ad353af",
   "metadata": {},
   "outputs": [],
   "source": [
    "shear_cursive = []\n",
    "angle_x = np.pi * -0.25\n",
    "angle_y = 0\n",
    "for coord in cursive_curve:\n",
    "    shear_cursive.append([coord[0]+angle_x*coord[1],\n",
    "                      coord[1]+angle_y*coord[0]])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 56,
   "id": "0f42191e",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "vsk = vsketch.Vsketch()\n",
    "vsk.size(\"200mm\", \"50mm\")\n",
    "vsk.scale(\"1mm\")\n",
    "with vsk.pushMatrix():\n",
    "    vsk.scale(5)\n",
    "    vsk.polygon(shear_cursive)\n",
    "vsk.display()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "14b5c93f",
   "metadata": {},
   "source": [
    "Now (inspired by [Mirtha Dermisache](https://4columns.org/chejfec-sergio/mirtha-dermisache)), I'm going to cut off this cursive when it goes above or below a threshold on the Y axis:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 57,
   "id": "2c0da45e",
   "metadata": {},
   "outputs": [],
   "source": [
    "cutoff_cursive = []\n",
    "for coord in shear_cursive:\n",
    "    if coord[1] > 0.25 and coord[1] < 1.75:\n",
    "        cutoff_cursive.append(coord)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "c1bc3335",
   "metadata": {},
   "source": [
    "Here's the whole line with all of these transformations applied:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 58,
   "id": "ee092e6d",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "vsk = vsketch.Vsketch()\n",
    "vsk.size(\"200mm\", \"50mm\")\n",
    "vsk.scale(\"1mm\")\n",
    "with vsk.pushMatrix():\n",
    "    vsk.scale(5)\n",
    "    vsk.polygon(cutoff_cursive)\n",
    "vsk.display()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "ad333387",
   "metadata": {},
   "source": [
    "Okay! Now I'm going to make a function that includes *all* of these steps, and parameterize as many of the variables as possible:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 59,
   "id": "0a9c6969",
   "metadata": {},
   "outputs": [],
   "source": [
    "def clipped_cursive_line(pt_count=6,\n",
    "                         n_glyphs=16,\n",
    "                         spacing=2.5,\n",
    "                         catmull=-0.5,\n",
    "                         shear_angle=np.pi*-0.25,\n",
    "                         top_cutoff=0.25,\n",
    "                         bottom_cutoff=1.75):\n",
    "    xgrid = [0, 0.5, 1, 1.5, 2]\n",
    "    ygrid = [0, 0.333, 1, 1.333, 2]\n",
    "    cursive_line = []\n",
    "    # generate a number of glyphs\n",
    "    for i in range(n_glyphs):\n",
    "        pts = []\n",
    "        for j in range(pt_count):\n",
    "            pts.append([random.choice(xgrid), random.choice(ygrid)])\n",
    "        # translate each glyph over\n",
    "        translated = [[x + i * spacing, y] for x, y in pts]\n",
    "        # add to the big polyline\n",
    "        cursive_line += translated\n",
    "    # polyline -> bezier spline -> curvy polyline\n",
    "    cursive_curve = Polyline(cursive_line).catmull_spline(catmull).to_polyline(20)\n",
    "    # shear\n",
    "    shear_cursive = []\n",
    "    for coord in cursive_curve:\n",
    "        shear_cursive.append([coord[0]+shear_angle*coord[1], coord[1]])\n",
    "    # cutoff\n",
    "    cutoff_cursive = []\n",
    "    for coord in shear_cursive:\n",
    "        if coord[1] > 0.25 and coord[1] < 1.75:\n",
    "            cutoff_cursive.append(coord)\n",
    "    return cutoff_cursive"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "4bcf7d34",
   "metadata": {},
   "source": [
    "Here's the whole composition:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 60,
   "id": "7f1da7b3",
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "vsk = vsketch.Vsketch()\n",
    "vsk.size(\"150mm\", \"150mm\")\n",
    "vsk.scale(\"1mm\")\n",
    "for i in range(12):\n",
    "    with vsk.pushMatrix():\n",
    "        vsk.translate(0, i * 10)\n",
    "        vsk.scale(3)\n",
    "        vsk.polygon(clipped_cursive_line(pt_count=3+i, shear_angle=i*-0.1))\n",
    "vsk.display()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "a674aafa",
   "metadata": {},
   "source": [
    "## Advanced: Doing all this stuff with numpy and Shapely (the cool way)\n",
    "\n",
    "notes tk!"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3 (ipykernel)",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.9.16"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}