{
"cells": [
{
"cell_type": "markdown",
"id": "65a47279-f0c5-4367-8323-b4a9b1e96891",
"metadata": {},
"source": [
"# Polar Heatmap"
]
},
{
"cell_type": "code",
"execution_count": 1,
"id": "f45649f5-4213-47b1-b1a4-7a24573a890f",
"metadata": {
"execution": {
"iopub.execute_input": "2024-04-26T12:17:15.968392Z",
"iopub.status.busy": "2024-04-26T12:17:15.968392Z",
"iopub.status.idle": "2024-04-26T12:17:18.419118Z",
"shell.execute_reply": "2024-04-26T12:17:18.419118Z"
}
},
"outputs": [],
"source": [
"import numpy as np\n",
"import pandas as pd\n",
"from scipy.interpolate import griddata\n",
"\n",
"from lets_plot import *"
]
},
{
"cell_type": "code",
"execution_count": 2,
"id": "3d04285b-e631-41c0-9dc7-a09b3ad68e61",
"metadata": {
"execution": {
"iopub.execute_input": "2024-04-26T12:17:18.419118Z",
"iopub.status.busy": "2024-04-26T12:17:18.419118Z",
"iopub.status.idle": "2024-04-26T12:17:18.434797Z",
"shell.execute_reply": "2024-04-26T12:17:18.434797Z"
}
},
"outputs": [
{
"data": {
"text/html": [
"\n",
" \n",
" \n",
" "
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"LetsPlot.setup_html()"
]
},
{
"cell_type": "code",
"execution_count": 3,
"id": "48bee431-7aa0-4fb8-8026-9ca157b5a190",
"metadata": {
"execution": {
"iopub.execute_input": "2024-04-26T12:17:18.434797Z",
"iopub.status.busy": "2024-04-26T12:17:18.434797Z",
"iopub.status.idle": "2024-04-26T12:17:19.399913Z",
"shell.execute_reply": "2024-04-26T12:17:19.399913Z"
}
},
"outputs": [
{
"data": {
"text/html": [
" \n",
" "
],
"text/plain": [
""
]
},
"execution_count": 3,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"max_r = 100\n",
"max_theta = 2.0 * np.pi\n",
"number_points = 5_000\n",
"np.random.seed(42)\n",
"\n",
"grid_r, grid_theta = np.meshgrid(\n",
" np.linspace(0, max_r, 200), # r\n",
" np.linspace(0.0, max_theta, 100) # theta\n",
")\n",
"\n",
"points = np.random.rand(number_points, 2) * [max_r, max_theta]\n",
"values = points[:,0] * np.sin(points[:,1])**2 * np.cos(points[:,1])**2\n",
"data = griddata(points, values, (grid_r, grid_theta), method='cubic',fill_value=0)\n",
"\n",
"df = {\n",
" 'x': grid_theta.flatten(), \n",
" 'y': grid_r.flatten(), \n",
" 'z': data.flatten()\n",
"}\n",
"\n",
"p = ggplot(df) + \\\n",
" geom_tile(aes('x', 'y', color='z', fill='z'), size=1, tooltips='none') + \\\n",
" scale_brewer(['color', 'fill'], palette='Spectral', direction=-1) + \\\n",
" theme(axis_title=element_blank())\n",
"\n",
"gggrid([\n",
" p + coord_cartesian() + ggtitle(\"Rectangular Heatmap\"),\n",
" p + coord_polar() + theme(legend_position='none') + ggtitle(\"Polar Heatmap\"),\n",
"])"
]
}
],
"metadata": {
"kernelspec": {
"display_name": "Python 3 (ipykernel)",
"language": "python",
"name": "python3"
},
"language_info": {
"codemirror_mode": {
"name": "ipython",
"version": 3
},
"file_extension": ".py",
"mimetype": "text/x-python",
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.10.13"
}
},
"nbformat": 4,
"nbformat_minor": 5
}