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@surajRathi
Created January 29, 2024 10:58
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Python Implementation of PID and simple geometric controllers with animation code.
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{
"cells": [
{
"cell_type": "markdown",
"source": [
"# Imports"
],
"metadata": {
"cell_id": "00005-99f0a7f6-375a-49f2-b226-36fa4b49b8eb",
"id": "KqEuqt2iHeyU",
"deepnote_cell_type": "markdown"
}
},
{
"cell_type": "code",
"metadata": {
"cell_id": "00006-19756491-dce6-4e73-a883-2d76823f9ee9",
"deepnote_to_be_reexecuted": false,
"execution_millis": 3719,
"execution_start": 1642179687620,
"id": "WqvbyVS9DJQ2",
"source_hash": "8b84073a",
"deepnote_cell_type": "code"
},
"source": [
"import numpy as np\n",
"import math\n",
"\n",
"import matplotlib.pyplot as plt\n",
"import seaborn as sns\n",
"\n",
"sns.set_style(\"darkgrid\")\n",
"\n",
"import matplotlib.patches as mp_patches\n",
"from matplotlib.animation import FuncAnimation\n",
"from matplotlib import rc\n",
"\n",
"rc(\"animation\", html=\"jshtml\")\n"
],
"outputs": [],
"execution_count": 1
},
{
"cell_type": "markdown",
"source": [
"# Helpers"
],
"metadata": {
"id": "mMO5Q4qQQs96",
"cell_id": "00003-dca43f21-015f-4be9-ae65-a8319fe4176e",
"deepnote_cell_type": "markdown"
}
},
{
"cell_type": "code",
"metadata": {
"id": "tZJYRCsRvISj",
"cell_id": "00004-76b74b8c-6f75-4ced-8a3d-0dcbafe3f731",
"deepnote_to_be_reexecuted": false,
"source_hash": "50e66ea3",
"execution_start": 1642179691355,
"execution_millis": 5,
"deepnote_cell_type": "code"
},
"source": [
"from typing import Tuple\n",
"import numpy as np\n",
"# https://www.desmos.com/calculator/acagoky1yo\n",
"\n",
"Point2 = np.ndarray # np.ndarray[2,]\n",
"\n",
"def dist(p1: Point2, p2: Point2):\n",
" return np.linalg.norm(p2 - p1)\n",
"\n",
"class LineSegment:\n",
" def __init__(self, p1: Point2, p2: Point2):\n",
" # Line segment from `p1` to `p2`\n",
"\n",
" self.p1 = p1\n",
" self.p2 = p2\n",
"\n",
" self.v = p2 - p1 # Direction Vector\n",
" factor = np.linalg.norm(self.v)\n",
" if factor == 0:\n",
" raise ValueError(\"Cannot make line segment from two coincident points.\")\n",
" self.v /= factor\n",
"\n",
" self.L = self.horiz_dist(self.p2) # Length of the segment\n",
"\n",
" def perp_dist(self, p: Point2): # Rename -> perp_dist\n",
" # Perpendicular distance of `p` from the line\n",
" return np.cross(self.v, p - self.p1)\n",
"\n",
" def horiz_dist(self, p: Point2):\n",
" # Distance from `p1` to the projection of `p` onto the line\n",
" return np.dot(self.v, p - self.p1)\n",
"\n",
" def parametric(self, horiz_dist: float):\n",
" # The point `horiz_dist` away from `p1` on the line\n",
" return self.p1 + self.v * horiz_dist"
],
"outputs": [],
"execution_count": 2
},
{
"cell_type": "code",
"metadata": {
"id": "3C5-2wQzQuQh",
"cell_id": "00005-fd70f733-ab33-4759-9ea3-b562210abeca",
"deepnote_to_be_reexecuted": false,
"source_hash": "63e320",
"execution_start": 1642179691380,
"execution_millis": 6,
"deepnote_cell_type": "code"
},
"source": [
"def animate(x_s, y_s, yaw_s, v_s, path=None, ref_x=None, ref_y=None, figsize=(12,8)):# -> plt.animation.FuncAnimation:\n",
" f, ax = plt.subplots(1,1, figsize=figsize)\n",
"\n",
" ax.set_aspect('equal', 'box')\n",
" ax.set_xlim(x_s.min() - 5, x_s.max() + 5)\n",
" ax.set_ylim(y_s.min() - 5, y_s.max() + 5)\n",
"\n",
" scatter = ax.scatter((0,), (0,), color='red', s=5)\n",
" frame = 0\n",
" global arrow\n",
" arrow = ax.arrow(x=x_s[frame], y=y_s[frame], dx=v_s[frame] * np.cos(yaw_s[frame]), dy=v_s[frame] * np.sin(yaw_s[frame]), color='black')\n",
"\n",
" ellipse = None\n",
" if ref_x is not None:\n",
" ellipse = ax.add_patch(mp_patches.Ellipse((ref_x[0],ref_y[0]), 0.4, 0.4, alpha=0.4, color='orange'))\n",
" else:\n",
" ellipse = ax.add_patch(mp_patches.Ellipse((0,0), 0.4, 0.4, alpha=0.4, color='orange'))\n",
" if path is not None:\n",
" ax.plot(*zip(*path), color='blue')\n",
"\n",
" def anim_func(frame, ax):\n",
" new_xy = np.vstack((scatter.get_offsets(), [[x_s[frame], y_s[frame]]]))\n",
" scatter.set_offsets(new_xy)\n",
"\n",
" arrow_new = ax.arrow(x=x_s[frame], y=y_s[frame], dx=v_s[frame] * np.cos(yaw_s[frame]), dy=v_s[frame] * np.sin(yaw_s[frame]), color='black')\n",
"\n",
" if ref_x is not None:\n",
" ellipse.center= (ref_x[frame],ref_y[frame])\n",
" else:\n",
" ellipse.center =(0,0)\n",
" global arrow\n",
" to_rem = arrow\n",
" arrow = arrow_new\n",
" to_rem.remove()\n",
"\n",
" return scatter, arrow, to_rem, ellipse # Return all mpl objects changed in this frame\n",
"\n",
" anim = FuncAnimation(f, anim_func, fargs=(ax,), frames=len(x_s), interval=25, blit=True)\n",
"\n",
" plt.close()\n",
" return anim"
],
"outputs": [],
"execution_count": 3
},
{
"cell_type": "markdown",
"source": [
"# The Bicycle Model"
],
"metadata": {
"cell_id": "00007-e1041034-9a7c-41b0-a573-b5cfc7b25424",
"id": "pt1EPElxBfA-",
"tags": [],
"deepnote_cell_type": "markdown"
}
},
{
"cell_type": "markdown",
"source": [
"## Theory"
],
"metadata": {
"cell_id": "00008-4cfcd53f-bed0-40d3-b3d8-95100bb235d9",
"id": "k1cIAzY2HgWf",
"jp-MarkdownHeadingCollapsed": true,
"tags": [],
"deepnote_cell_type": "markdown"
}
},
{
"cell_type": "markdown",
"source": [],
"metadata": {
"cell_id": "00009-9b47811a-cca0-4e76-84e5-7bdaf8a653cc",
"id": "XoejYIu3B4hV",
"deepnote_cell_type": "markdown"
}
},
{
"cell_type": "markdown",
"source": [
"![image.png](data:image/png;base64,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)"
],
"metadata": {
"cell_id": "8040eae3-ea45-4647-abd4-88cc44513283",
"tags": [],
"id": "SGWe24BvN1Ax",
"deepnote_cell_type": "markdown"
}
},
{
"cell_type": "markdown",
"source": [
"State:\n",
"- Position: $(x, y)$\n",
"- Yaw: $\\theta$ $[\\theta \\in (-\\pi, \\pi)]$\n",
"- Velocity: $v$\n",
" \n",
"Control Inputs\n",
"- Acceleration: $a$\n",
"- Steering Angle: $\\delta$\n",
"\n",
"Update: \n",
"$\\begin{bmatrix}x'\\\\y' \\end{bmatrix} = \\begin{bmatrix}x\\\\y \\end{bmatrix} + v*dt\\begin{bmatrix}cos(\\theta)\\\\sin(\\theta) \\end{bmatrix}$ \n",
" \n",
"$v' = v + a * dt$ \n",
" \n",
"$\\theta' = \\theta + \\dfrac{v}{L}tan(\\delta) * dt$"
],
"metadata": {
"cell_id": "00010-e6b9cb99-23d8-4c00-927d-a75a471fb480",
"id": "oJdDYQqDCByT",
"deepnote_cell_type": "markdown"
}
},
{
"cell_type": "markdown",
"source": [
"## Code"
],
"metadata": {
"cell_id": "00011-81dd395d-395f-4e7c-8ba7-1782119966c8",
"id": "Rze63ftOHiNS",
"deepnote_cell_type": "markdown"
}
},
{
"cell_type": "markdown",
"source": [],
"metadata": {
"cell_id": "c2053682-93fe-43ee-8662-896585e39242",
"tags": [],
"id": "p2dhLWGcN1A7",
"deepnote_cell_type": "markdown"
}
},
{
"cell_type": "markdown",
"source": [
"\n",
"$\\theta_{norm} = ((\\theta + \\pi) \\mod 2\\pi) - \\pi$"
],
"metadata": {
"cell_id": "6357e9ad-a78d-4b29-9cd7-227aabe6d8d9",
"tags": [],
"id": "MGatoeymN1A7",
"deepnote_cell_type": "markdown"
}
},
{
"cell_type": "code",
"metadata": {
"cell_id": "00013-347abbd2-8ffe-4372-88ce-8b487922298d",
"deepnote_to_be_reexecuted": false,
"execution_millis": 2,
"execution_start": 1642179691397,
"id": "w1lXSn7mRtFA",
"source_hash": "b5f0d96",
"deepnote_cell_type": "code"
},
"source": [
"def normalize_angle(angle: float) -> float:\n",
" return (angle + np.pi) % (2 * np.pi) - np.pi\n"
],
"outputs": [],
"execution_count": 4
},
{
"cell_type": "code",
"metadata": {
"cell_id": "00014-1a184ccb-aab1-427f-a5b8-78626ec51e4d",
"deepnote_to_be_reexecuted": false,
"execution_millis": 5,
"execution_start": 1642179691407,
"id": "lyz7FKB3RtFA",
"source_hash": "d59418d3",
"deepnote_output_heights": [
21.199996948242188
],
"deepnote_cell_type": "code"
},
"source": [
"from dataclasses import dataclass\n",
"import numpy as np\n",
"\n",
"\n",
"@dataclass # Creates __init__ and __repr__ automatically\n",
"class BicycleModel:\n",
" # State\n",
" x: float = 0.0\n",
" y: float = 0.0\n",
" theta: float = 0.0\n",
" v: float = 0.0\n",
"\n",
" # Model Parameters\n",
" dt: float = 0.1\n",
"\n",
" L: float = 3.0 # [m] Wheel base of vehicle (distance between front and rear axels)\n",
" max_steer: float = np.radians(30.0) # [radians] Max steering angle\n",
"\n",
" def update(self, throttle: float, delta: float) -> float:\n",
"\n",
" delta = np.clip(delta, -self.max_steer, self.max_steer)\n",
"\n",
" self.x += self.v * np.cos(self.theta) * self.dt\n",
" self.y += self.v * np.sin(self.theta) * self.dt\n",
"\n",
" self.theta += self.v / self.L * np.tan(delta) * self.dt\n",
" self.theta = normalize_angle(self.theta)\n",
"\n",
" self.v += throttle * dt\n"
],
"outputs": [],
"execution_count": 5
},
{
"cell_type": "markdown",
"source": [
"## Examples\n"
],
"metadata": {
"id": "mGijpzpLTU9k",
"cell_id": "00016-2aed829d-3258-429a-abcd-432d738aa5b0",
"deepnote_cell_type": "markdown"
}
},
{
"cell_type": "code",
"metadata": {
"cell_id": "00016-a91113f8-df4b-47e3-8871-5d3e0c614ab6",
"deepnote_to_be_reexecuted": false,
"execution_millis": 413,
"execution_start": 1642179691474,
"id": "zPVs7-_zRtFB",
"source_hash": "660c2119",
"deepnote_output_heights": [
249.96875
],
"colab": {
"base_uri": "https://localhost:8080/",
"height": 0
},
"outputId": "e2e734b3-e5e4-4ce1-de72-4cf24b99365b",
"deepnote_cell_type": "code"
},
"source": [
"T = 30\n",
"dt = 0.1\n",
"\n",
"model = BicycleModel(x=0, y=0, theta=0, v=5)\n",
"\n",
"x_pos = []\n",
"y_pos = []\n",
"\n",
"for i in range(int(T / dt)):\n",
" model.update(0, 0.1)\n",
"\n",
" x_pos.append(model.x)\n",
" y_pos.append(model.y)\n",
"\n",
"\n",
"\n",
"figure, axes = plt.subplots(1,1, figsize=(4,4))\n",
"axes.axis('equal')\n",
"axes.plot(x_pos, y_pos, 'o-', markersize=0.1)\n",
"plt.show()"
],
"outputs": [
{
"output_type": "display_data",
"data": {
"text/plain": [
"<Figure size 400x400 with 1 Axes>"
],
"image/png": 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\n"
},
"metadata": {}
}
],
"execution_count": 6
},
{
"cell_type": "code",
"metadata": {
"cell_id": "00018-51303515-61a3-4485-9278-ce135472490b",
"deepnote_to_be_reexecuted": false,
"execution_millis": 544,
"execution_start": 1642179691897,
"id": "_Mz5Of2pRtFC",
"source_hash": "effc124e",
"colab": {
"base_uri": "https://localhost:8080/",
"height": 0
},
"outputId": "19529734-cde4-45c9-a290-232b59b896bc",
"deepnote_output_heights": [
306.96875
],
"deepnote_cell_type": "code"
},
"source": [
"T = 10\n",
"dt = 0.1\n",
"\n",
"t = np.linspace(0, T, int(T / dt)) # np.array([0, dt, 2*dt, 3*dt .... T - 2*dt, T - dt, T])\n",
"\n",
"throttle = np.zeros_like(t) # Constant Velocity\n",
"steer = np.sin(np.pi * (t / 5)) # An interesting steer function\n",
"\n",
"model = BicycleModel(x=0,y=0,theta=0,v=5)\n",
"\n",
"# Initialize arrays to store the state\n",
"x_s = np.zeros_like(t)\n",
"y_s = np.zeros_like(t)\n",
"yaw_s = np.zeros_like(t)\n",
"v_s = np.zeros_like(t)\n",
"\n",
"\n",
"# Run Model\n",
"for i in range(len(t)):\n",
" model.update(throttle[i], steer[i])\n",
"\n",
" # Save the updated state\n",
" x_s[i] = model.x\n",
" y_s[i] = model.y\n",
" yaw_s[i] = model.theta\n",
" v_s[i] = model.v\n",
"\n",
"\n",
"# Plotting\n",
"plt.figure(figsize=(8,5))\n",
"plt.gca().axis('equal')\n",
"\n",
"plt.quiver(\n",
" x_s, y_s, # Postions\n",
" np.cos(yaw_s), np.sin(yaw_s), # arrow's direction\n",
" scale = 40\n",
" )\n",
"plt.show()"
],
"outputs": [
{
"output_type": "display_data",
"data": {
"text/plain": [
"<Figure size 800x500 with 1 Axes>"
],
"image/png": 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\n"
},
"metadata": {}
}
],
"execution_count": 7
},
{
"cell_type": "code",
"metadata": {
"cell_id": "00021-7a731ab9-2207-43b6-ae1a-124b5fbeb608",
"colab": {
"base_uri": "https://localhost:8080/",
"height": 0
},
"deepnote_output_heights": [
610.984375
],
"deepnote_to_be_reexecuted": false,
"execution_millis": 17924,
"execution_start": 1642179692379,
"id": "LD52QGS6RtFD",
"outputId": "1cffa68d-c2cf-4265-d5b0-1cb59ed09767",
"source_hash": "e400f11f",
"deepnote_cell_type": "code"
},
"source": [
"animate(x_s, y_s, yaw_s, v_s)"
],
"outputs": [
{
"output_type": "execute_result",
"data": {
"text/plain": [
"<matplotlib.animation.FuncAnimation at 0x7b273006f130>"
],
"text/html": [
"\n",
"<link rel=\"stylesheet\"\n",
"href=\"https://maxcdn.bootstrapcdn.com/font-awesome/4.4.0/css/font-awesome.min.css\">\n",
"<script language=\"javascript\">\n",
" function isInternetExplorer() {\n",
" ua = navigator.userAgent;\n",
" /* MSIE used to detect old browsers and Trident used to newer ones*/\n",
" return ua.indexOf(\"MSIE \") > -1 || ua.indexOf(\"Trident/\") > -1;\n",
" }\n",
"\n",
" /* Define the Animation class */\n",
" function Animation(frames, img_id, slider_id, interval, loop_select_id){\n",
" this.img_id = img_id;\n",
" this.slider_id = slider_id;\n",
" this.loop_select_id = loop_select_id;\n",
" this.interval = interval;\n",
" this.current_frame = 0;\n",
" this.direction = 0;\n",
" this.timer = null;\n",
" this.frames = new Array(frames.length);\n",
"\n",
" for (var i=0; i<frames.length; i++)\n",
" {\n",
" this.frames[i] = new Image();\n",
" this.frames[i].src = frames[i];\n",
" }\n",
" var slider = document.getElementById(this.slider_id);\n",
" slider.max = this.frames.length - 1;\n",
" if (isInternetExplorer()) {\n",
" // switch from oninput to onchange because IE <= 11 does not conform\n",
" // with W3C specification. It ignores oninput and onchange behaves\n",
" // like oninput. In contrast, Microsoft Edge behaves correctly.\n",
" slider.setAttribute('onchange', slider.getAttribute('oninput'));\n",
" slider.setAttribute('oninput', null);\n",
" }\n",
" this.set_frame(this.current_frame);\n",
" }\n",
"\n",
" Animation.prototype.get_loop_state = function(){\n",
" var button_group = document[this.loop_select_id].state;\n",
" for (var i = 0; i < button_group.length; i++) {\n",
" var button = button_group[i];\n",
" if (button.checked) {\n",
" return button.value;\n",
" }\n",
" }\n",
" return undefined;\n",
" }\n",
"\n",
" Animation.prototype.set_frame = function(frame){\n",
" this.current_frame = frame;\n",
" document.getElementById(this.img_id).src =\n",
" this.frames[this.current_frame].src;\n",
" document.getElementById(this.slider_id).value = this.current_frame;\n",
" }\n",
"\n",
" Animation.prototype.next_frame = function()\n",
" {\n",
" this.set_frame(Math.min(this.frames.length - 1, this.current_frame + 1));\n",
" }\n",
"\n",
" Animation.prototype.previous_frame = function()\n",
" {\n",
" this.set_frame(Math.max(0, this.current_frame - 1));\n",
" }\n",
"\n",
" Animation.prototype.first_frame = function()\n",
" {\n",
" this.set_frame(0);\n",
" }\n",
"\n",
" Animation.prototype.last_frame = function()\n",
" {\n",
" this.set_frame(this.frames.length - 1);\n",
" }\n",
"\n",
" Animation.prototype.slower = function()\n",
" {\n",
" this.interval /= 0.7;\n",
" if(this.direction > 0){this.play_animation();}\n",
" else if(this.direction < 0){this.reverse_animation();}\n",
" }\n",
"\n",
" Animation.prototype.faster = function()\n",
" {\n",
" this.interval *= 0.7;\n",
" if(this.direction > 0){this.play_animation();}\n",
" else if(this.direction < 0){this.reverse_animation();}\n",
" }\n",
"\n",
" Animation.prototype.anim_step_forward = function()\n",
" {\n",
" this.current_frame += 1;\n",
" if(this.current_frame < this.frames.length){\n",
" this.set_frame(this.current_frame);\n",
" }else{\n",
" var loop_state = this.get_loop_state();\n",
" if(loop_state == \"loop\"){\n",
" this.first_frame();\n",
" }else if(loop_state == \"reflect\"){\n",
" this.last_frame();\n",
" this.reverse_animation();\n",
" }else{\n",
" this.pause_animation();\n",
" this.last_frame();\n",
" }\n",
" }\n",
" }\n",
"\n",
" Animation.prototype.anim_step_reverse = function()\n",
" {\n",
" this.current_frame -= 1;\n",
" if(this.current_frame >= 0){\n",
" this.set_frame(this.current_frame);\n",
" }else{\n",
" var loop_state = this.get_loop_state();\n",
" if(loop_state == \"loop\"){\n",
" this.last_frame();\n",
" }else if(loop_state == \"reflect\"){\n",
" this.first_frame();\n",
" this.play_animation();\n",
" }else{\n",
" this.pause_animation();\n",
" this.first_frame();\n",
" }\n",
" }\n",
" }\n",
"\n",
" Animation.prototype.pause_animation = function()\n",
" {\n",
" this.direction = 0;\n",
" if (this.timer){\n",
" clearInterval(this.timer);\n",
" this.timer = null;\n",
" }\n",
" }\n",
"\n",
" Animation.prototype.play_animation = function()\n",
" {\n",
" this.pause_animation();\n",
" this.direction = 1;\n",
" var t = this;\n",
" if (!this.timer) this.timer = setInterval(function() {\n",
" t.anim_step_forward();\n",
" }, this.interval);\n",
" }\n",
"\n",
" Animation.prototype.reverse_animation = function()\n",
" {\n",
" this.pause_animation();\n",
" this.direction = -1;\n",
" var t = this;\n",
" if (!this.timer) this.timer = setInterval(function() {\n",
" t.anim_step_reverse();\n",
" }, this.interval);\n",
" }\n",
"</script>\n",
"\n",
"<style>\n",
".animation {\n",
" display: inline-block;\n",
" text-align: center;\n",
"}\n",
"input[type=range].anim-slider {\n",
" width: 374px;\n",
" margin-left: auto;\n",
" margin-right: auto;\n",
"}\n",
".anim-buttons {\n",
" margin: 8px 0px;\n",
"}\n",
".anim-buttons button {\n",
" padding: 0;\n",
" width: 36px;\n",
"}\n",
".anim-state label {\n",
" margin-right: 8px;\n",
"}\n",
".anim-state input {\n",
" margin: 0;\n",
" vertical-align: middle;\n",
"}\n",
"</style>\n",
"\n",
"<div class=\"animation\">\n",
" <img id=\"_anim_imgfe72ac632f514b53be1135fc94dbe579\">\n",
" <div class=\"anim-controls\">\n",
" <input id=\"_anim_sliderfe72ac632f514b53be1135fc94dbe579\" type=\"range\" class=\"anim-slider\"\n",
" name=\"points\" min=\"0\" max=\"1\" step=\"1\" value=\"0\"\n",
" oninput=\"animfe72ac632f514b53be1135fc94dbe579.set_frame(parseInt(this.value));\">\n",
" <div class=\"anim-buttons\">\n",
" <button title=\"Decrease speed\" aria-label=\"Decrease speed\" onclick=\"animfe72ac632f514b53be1135fc94dbe579.slower()\">\n",
" <i class=\"fa fa-minus\"></i></button>\n",
" <button title=\"First frame\" aria-label=\"First frame\" onclick=\"animfe72ac632f514b53be1135fc94dbe579.first_frame()\">\n",
" <i class=\"fa fa-fast-backward\"></i></button>\n",
" <button title=\"Previous frame\" aria-label=\"Previous frame\" onclick=\"animfe72ac632f514b53be1135fc94dbe579.previous_frame()\">\n",
" <i class=\"fa fa-step-backward\"></i></button>\n",
" <button title=\"Play backwards\" aria-label=\"Play backwards\" onclick=\"animfe72ac632f514b53be1135fc94dbe579.reverse_animation()\">\n",
" <i class=\"fa fa-play fa-flip-horizontal\"></i></button>\n",
" <button title=\"Pause\" aria-label=\"Pause\" onclick=\"animfe72ac632f514b53be1135fc94dbe579.pause_animation()\">\n",
" <i class=\"fa fa-pause\"></i></button>\n",
" <button title=\"Play\" aria-label=\"Play\" onclick=\"animfe72ac632f514b53be1135fc94dbe579.play_animation()\">\n",
" <i class=\"fa fa-play\"></i></button>\n",
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" <button title=\"Last frame\" aria-label=\"Last frame\" onclick=\"animfe72ac632f514b53be1135fc94dbe579.last_frame()\">\n",
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" <button title=\"Increase speed\" aria-label=\"Increase speed\" onclick=\"animfe72ac632f514b53be1135fc94dbe579.faster()\">\n",
" <i class=\"fa fa-plus\"></i></button>\n",
" </div>\n",
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" class=\"anim-state\">\n",
" <input type=\"radio\" name=\"state\" value=\"once\" id=\"_anim_radio1_fe72ac632f514b53be1135fc94dbe579\"\n",
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" <input type=\"radio\" name=\"state\" value=\"reflect\" id=\"_anim_radio3_fe72ac632f514b53be1135fc94dbe579\"\n",
" >\n",
" <label for=\"_anim_radio3_fe72ac632f514b53be1135fc94dbe579\">Reflect</label>\n",
" </form>\n",
" </div>\n",
"</div>\n",
"\n",
"\n",
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