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kvedala/spirograph.ipynb

Last active July 2, 2020 15:20
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spirograph.ipynb
{
"nbformat": 4,
"nbformat_minor": 0,
"metadata": {
"colab": {
"name": "Spirograph",
"provenance": [],
"collapsed_sections": [],
"include_colab_link": true
},
"kernelspec": {
"name": "python3",
"display_name": "Python 3"
},
"widgets": {
"application/vnd.jupyter.widget-state+json": {
"9c9d9431b98341138c706efe57189d28": {
"model_module": "@jupyter-widgets/controls",
"model_name": "VBoxModel",
"state": {
"_view_name": "VBoxView",
"_dom_classes": [
"widget-interact"
],
"_model_name": "VBoxModel",
"_view_module": "@jupyter-widgets/controls",
"_model_module_version": "1.5.0",
"_view_count": null,
"_view_module_version": "1.5.0",
"box_style": "",
"layout": "IPY_MODEL_6b1b75c93d914023b2bafaec3c8d2ee6",
"_model_module": "@jupyter-widgets/controls",
"children": [
"IPY_MODEL_1822fe1d9ace44c8bf1b2d0643702d69",
"IPY_MODEL_d70bd65c7f794c92ba74258b3bf72dba",
"IPY_MODEL_4a8a24ffd8684a4f8d1f0188335a8b8d",
"IPY_MODEL_c002247f80ba4fc984ee21a06cb52f90",
"IPY_MODEL_eb24991ef5e34b1084036322c4f9f4db"
]
}
},
"6b1b75c93d914023b2bafaec3c8d2ee6": {
"model_module": "@jupyter-widgets/base",
"model_name": "LayoutModel",
"state": {
"_view_name": "LayoutView",
"grid_template_rows": null,
"right": null,
"justify_content": null,
"_view_module": "@jupyter-widgets/base",
"overflow": null,
"_model_module_version": "1.2.0",
"_view_count": null,
"flex_flow": null,
"width": null,
"min_width": null,
"border": null,
"align_items": null,
"bottom": null,
"_model_module": "@jupyter-widgets/base",
"top": null,
"grid_column": null,
"overflow_y": null,
"overflow_x": null,
"grid_auto_flow": null,
"grid_area": null,
"grid_template_columns": null,
"flex": null,
"_model_name": "LayoutModel",
"justify_items": null,
"grid_row": null,
"max_height": null,
"align_content": null,
"visibility": null,
"align_self": null,
"height": null,
"min_height": null,
"padding": null,
"grid_auto_rows": null,
"grid_gap": null,
"max_width": null,
"order": null,
"_view_module_version": "1.2.0",
"grid_template_areas": null,
"object_position": null,
"object_fit": null,
"grid_auto_columns": null,
"margin": null,
"display": null,
"left": null
}
},
"1822fe1d9ace44c8bf1b2d0643702d69": {
"model_module": "@jupyter-widgets/controls",
"model_name": "FloatSliderModel",
"state": {
"_view_name": "FloatSliderView",
"style": "IPY_MODEL_0ad5729b2f2946e8813bfc207d0de6e9",
"_dom_classes": [],
"description": "marker distance from centre of inner circle",
"step": 0.01,
"_model_name": "FloatSliderModel",
"orientation": "horizontal",
"max": 1,
"_view_module": "@jupyter-widgets/controls",
"_model_module_version": "1.5.0",
"value": 0.3,
"_view_count": null,
"disabled": false,
"_view_module_version": "1.5.0",
"min": 0,
"continuous_update": true,
"readout_format": ".2f",
"description_tooltip": null,
"readout": true,
"_model_module": "@jupyter-widgets/controls",
"layout": "IPY_MODEL_f231488cb2344280bf3bf5916f4838ed"
}
},
"d70bd65c7f794c92ba74258b3bf72dba": {
"model_module": "@jupyter-widgets/controls",
"model_name": "FloatSliderModel",
"state": {
"_view_name": "FloatSliderView",
"style": "IPY_MODEL_9ef6c899e5ec41aa95593f10022b6af7",
"_dom_classes": [],
"description": "Ratio of inner circle to outer",
"step": 0.01,
"_model_name": "FloatSliderModel",
"orientation": "horizontal",
"max": 1,
"_view_module": "@jupyter-widgets/controls",
"_model_module_version": "1.5.0",
"value": 0.8,
"_view_count": null,
"disabled": false,
"_view_module_version": "1.5.0",
"min": 0,
"continuous_update": true,
"readout_format": ".2f",
"description_tooltip": null,
"readout": true,
"_model_module": "@jupyter-widgets/controls",
"layout": "IPY_MODEL_6f9fe1823b1d451c856592605e272a54"
}
},
"4a8a24ffd8684a4f8d1f0188335a8b8d": {
"model_module": "@jupyter-widgets/controls",
"model_name": "IntSliderModel",
"state": {
"_view_name": "IntSliderView",
"style": "IPY_MODEL_151579360014468a925cc38966deb1e0",
"_dom_classes": [],
"description": "Number of rotations to simulate",
"step": 1,
"_model_name": "IntSliderModel",
"orientation": "horizontal",
"max": 500,
"_view_module": "@jupyter-widgets/controls",
"_model_module_version": "1.5.0",
"value": 214,
"_view_count": null,
"disabled": false,
"_view_module_version": "1.5.0",
"min": 1,
"continuous_update": true,
"readout_format": "d",
"description_tooltip": null,
"readout": true,
"_model_module": "@jupyter-widgets/controls",
"layout": "IPY_MODEL_4fe040a11d32448f8fa2531ab7181a8d"
}
},
"c002247f80ba4fc984ee21a06cb52f90": {
"model_module": "@jupyter-widgets/controls",
"model_name": "IntSliderModel",
"state": {
"_view_name": "IntSliderView",
"style": "IPY_MODEL_98c23b23b2234736b6af285243de20a6",
"_dom_classes": [],
"description": "Number of samples points to generate",
"step": 50,
"_model_name": "IntSliderModel",
"orientation": "horizontal",
"max": 10000,
"_view_module": "@jupyter-widgets/controls",
"_model_module_version": "1.5.0",
"value": 6950,
"_view_count": null,
"disabled": false,
"_view_module_version": "1.5.0",
"min": 100,
"continuous_update": true,
"readout_format": "d",
"description_tooltip": null,
"readout": true,
"_model_module": "@jupyter-widgets/controls",
"layout": "IPY_MODEL_bb39b729ad50408ba8451104adc08db9"
}
},
"eb24991ef5e34b1084036322c4f9f4db": {
"model_module": "@jupyter-widgets/output",
"model_name": "OutputModel",
"state": {
"_view_name": "OutputView",
"msg_id": "",
"_dom_classes": [],
"_model_name": "OutputModel",
"outputs": [
{
"output_type": "display_data",
"metadata": {
"tags": []
},
"image/png": 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},
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"model_name": "LayoutModel",
"state": {
"_view_name": "LayoutView",
"grid_template_rows": null,
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}
}
},
"cells": [
{
"cell_type": "markdown",
"metadata": {
"id": "view-in-github",
"colab_type": "text"
},
"source": [
"<a href=\"https://colab.research.google.com/gist/kvedala/7cc557bb2f0b30a3a1f8f2b282ac2192/spirograph.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
]
},
{
"cell_type": "code",
"metadata": {
"id": "UO_PprAYYbbP",
"colab_type": "code",
"colab": {}
},
"source": [
"import ipywidgets\n",
"import matplotlib.pyplot as plt\n",
"from matplotlib.animation import FuncAnimation\n",
"import numpy as np\n",
"plt.rcParams['animation.html'] = 'html5'"
],
"execution_count": 2,
"outputs": []
},
{
"cell_type": "code",
"metadata": {
"id": "q94VS6xBppP8",
"colab_type": "code",
"colab": {}
},
"source": [
"def get_curve(l, k, N=500, rot=40):\n",
" R = 5\n",
" t = np.linspace(0, rot*2*np.pi, N)\n",
" x = R * ( (1-k)*np.cos(t) + l*k*np.cos( (1-k)*t/k ) )\n",
" y = R * ( (1-k)*np.sin(t) - l*k*np.sin( (1-k)*t/k ) )\n",
" return x, y"
],
"execution_count": 5,
"outputs": []
},
{
"cell_type": "code",
"metadata": {
"id": "4M5IhY3oYsds",
"colab_type": "code",
"colab": {
"base_uri": "https://localhost:8080/",
"height": 641,
"referenced_widgets": [
"9c9d9431b98341138c706efe57189d28",
"6b1b75c93d914023b2bafaec3c8d2ee6",
"1822fe1d9ace44c8bf1b2d0643702d69",
"d70bd65c7f794c92ba74258b3bf72dba",
"4a8a24ffd8684a4f8d1f0188335a8b8d",
"c002247f80ba4fc984ee21a06cb52f90",
"eb24991ef5e34b1084036322c4f9f4db",
"0ad5729b2f2946e8813bfc207d0de6e9",
"f231488cb2344280bf3bf5916f4838ed",
"9ef6c899e5ec41aa95593f10022b6af7",
"6f9fe1823b1d451c856592605e272a54",
"151579360014468a925cc38966deb1e0",
"4fe040a11d32448f8fa2531ab7181a8d",
"98c23b23b2234736b6af285243de20a6",
"bb39b729ad50408ba8451104adc08db9",
"df3c2bdfcc0845f68402a3a2af5baf45"
]
},
"outputId": "5323e47f-772a-4636-90dc-ea8d679ed04c"
},
"source": [
"@ipywidgets.interact(l=ipywidgets.FloatSlider(value=0.1, min=0, max=1, step=0.01, description=\"marker distance from centre of inner circle\"),\n",
" k=ipywidgets.FloatSlider(value=0.8, min=0, max=1, step=0.01, description=\"Ratio of inner circle to outer\"),\n",
" rot=ipywidgets.IntSlider(value=20, min=1, max=500, step=1, description=\"Number of rotations to simulate\"),\n",
" N=ipywidgets.IntSlider(value=150, min=100, max=10000, step=50, description=\"Number of samples points to generate\"))\n",
"def change_param(l, k, rot, N):\n",
" x, y = get_curve(l, k, N, rot)\n",
" fig, ax = plt.subplots(figsize=(7,7))\n",
" curve, = ax.plot(x, y, '-k')\n",
" ax.set_xticks([])\n",
" ax.set_yticks([])\n",
" for spines in ax.spines:\n",
" ax.spines[spines].set_visible(False)\n",
" fig.tight_layout()\n",
" ax.axis('equal')\n",
" # ax.set_xlim(-5, 5)\n",
" # ax.set_ylim(-5, 5)"
],
"execution_count": 6,
"outputs": [
{
"output_type": "display_data",
"data": {
"application/vnd.jupyter.widget-view+json": {
"model_id": "9c9d9431b98341138c706efe57189d28",
"version_minor": 0,
"version_major": 2
},
"text/plain": [
"interactive(children=(FloatSlider(value=0.1, description='marker distance from centre of inner circle', max=1.…"
]
},
"metadata": {
"tags": []
}
}
]
},
{
"cell_type": "code",
"metadata": {
"id": "Rovbw0pdtWe1",
"colab_type": "code",
"colab": {}
},
"source": [
""
],
"execution_count": null,
"outputs": []
}
]
}
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