{
"cells": [
{
"cell_type": "code",
"execution_count": 1,
"metadata": {
"execution": {
"iopub.execute_input": "2024-04-17T07:28:59.747542Z",
"iopub.status.busy": "2024-04-17T07:28:59.747461Z",
"iopub.status.idle": "2024-04-17T07:29:00.067332Z",
"shell.execute_reply": "2024-04-17T07:29:00.067114Z"
}
},
"outputs": [
{
"data": {
"text/html": [
"\n",
" \n",
" \n",
" "
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"import numpy as np\n",
"from lets_plot import *\n",
"\n",
"LetsPlot.setup_html()"
]
},
{
"cell_type": "code",
"execution_count": 2,
"metadata": {
"execution": {
"iopub.execute_input": "2024-04-17T07:29:00.081010Z",
"iopub.status.busy": "2024-04-17T07:29:00.080830Z",
"iopub.status.idle": "2024-04-17T07:29:00.082544Z",
"shell.execute_reply": "2024-04-17T07:29:00.082357Z"
}
},
"outputs": [],
"source": [
"np.random.seed(42)"
]
},
{
"cell_type": "code",
"execution_count": 3,
"metadata": {
"execution": {
"iopub.execute_input": "2024-04-17T07:29:00.083747Z",
"iopub.status.busy": "2024-04-17T07:29:00.083592Z",
"iopub.status.idle": "2024-04-17T07:29:00.086160Z",
"shell.execute_reply": "2024-04-17T07:29:00.085957Z"
}
},
"outputs": [],
"source": [
"cov0=[[1, -.8], \n",
" [-.8, 1]] \n",
"cov1=[[1, .8], \n",
" [.8, 1]] \n",
"cov2=[[ 10, .1],\n",
" [.1, .1]]\n",
"\n",
"x0, y0 = np.random.multivariate_normal(mean=[-2,0], cov=cov0, size=400).T\n",
"x1, y1 = np.random.multivariate_normal(mean=[2,0], cov=cov1, size=400).T\n",
"x2, y2 = np.random.multivariate_normal(mean=[0,1], cov=cov2, size=400).T\n",
"\n",
"data = dict(\n",
" x = np.concatenate((x0,x1,x2)),\n",
" y = np.concatenate((y0,y1,y2))\n",
")"
]
},
{
"cell_type": "code",
"execution_count": 4,
"metadata": {
"execution": {
"iopub.execute_input": "2024-04-17T07:29:00.087193Z",
"iopub.status.busy": "2024-04-17T07:29:00.087077Z",
"iopub.status.idle": "2024-04-17T07:29:00.123521Z",
"shell.execute_reply": "2024-04-17T07:29:00.123325Z"
}
},
"outputs": [
{
"data": {
"text/html": [
" \n",
" "
],
"text/plain": [
""
]
},
"execution_count": 4,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"p = ggplot(data, aes('x', 'y')) + ggsize(600,300) \\\n",
"+ geom_point(color='black', alpha=.1)\n",
"p"
]
},
{
"cell_type": "code",
"execution_count": 5,
"metadata": {
"execution": {
"iopub.execute_input": "2024-04-17T07:29:00.124443Z",
"iopub.status.busy": "2024-04-17T07:29:00.124353Z",
"iopub.status.idle": "2024-04-17T07:29:00.289401Z",
"shell.execute_reply": "2024-04-17T07:29:00.289185Z"
}
},
"outputs": [
{
"data": {
"text/html": [
" \n",
" "
],
"text/plain": [
""
]
},
"execution_count": 5,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"# Basic density \n",
"p + geom_density2d(color='red')"
]
},
{
"cell_type": "code",
"execution_count": 6,
"metadata": {
"execution": {
"iopub.execute_input": "2024-04-17T07:29:00.290694Z",
"iopub.status.busy": "2024-04-17T07:29:00.290611Z",
"iopub.status.idle": "2024-04-17T07:29:00.460602Z",
"shell.execute_reply": "2024-04-17T07:29:00.460365Z"
}
},
"outputs": [
{
"data": {
"text/html": [
" \n",
" "
],
"text/plain": [
""
]
},
"execution_count": 6,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"# Set contour color by \"level\".\n",
"# - change defailt position and size of colorbar.\n",
"p + geom_density2d(aes(color='..level..')) \\\n",
"+ scale_color_gradient(low='dark_green', high='yellow', guide=guide_colorbar(barheight=10, barwidth=300)) \\\n",
"+ theme(legend_position='bottom')"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"### Filling contours by level"
]
},
{
"cell_type": "code",
"execution_count": 7,
"metadata": {
"execution": {
"iopub.execute_input": "2024-04-17T07:29:00.462269Z",
"iopub.status.busy": "2024-04-17T07:29:00.462109Z",
"iopub.status.idle": "2024-04-17T07:29:00.631975Z",
"shell.execute_reply": "2024-04-17T07:29:00.631766Z"
}
},
"outputs": [
{
"data": {
"text/html": [
" \n",
" "
],
"text/plain": [
""
]
},
"execution_count": 7,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"p1 = ggplot(data, aes('x', 'y')) + ggsize(600,300)\n",
"\n",
"# Filled polygons are not always working well - see the missing polygon in the middle. \n",
"p1 + geom_polygon(aes(fill='..level..'), stat='density2d') + coord_fixed()"
]
},
{
"cell_type": "code",
"execution_count": 8,
"metadata": {
"execution": {
"iopub.execute_input": "2024-04-17T07:29:00.633503Z",
"iopub.status.busy": "2024-04-17T07:29:00.633401Z",
"iopub.status.idle": "2024-04-17T07:29:00.824968Z",
"shell.execute_reply": "2024-04-17T07:29:00.824739Z"
}
},
"outputs": [
{
"data": {
"text/html": [
" \n",
" "
],
"text/plain": [
""
]
},
"execution_count": 8,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"# 'density2df' is not dependent on the poligons order and works a lot better.\n",
"p1 + geom_density2df(aes(fill='..level..'))"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"### geom_bin2d is another way to plot density"
]
},
{
"cell_type": "code",
"execution_count": 9,
"metadata": {
"execution": {
"iopub.execute_input": "2024-04-17T07:29:00.827450Z",
"iopub.status.busy": "2024-04-17T07:29:00.827366Z",
"iopub.status.idle": "2024-04-17T07:29:00.832220Z",
"shell.execute_reply": "2024-04-17T07:29:00.832034Z"
}
},
"outputs": [
{
"data": {
"text/html": [
" \n",
" "
],
"text/plain": [
""
]
},
"execution_count": 9,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"p1 + geom_bin2d()"
]
},
{
"cell_type": "code",
"execution_count": 10,
"metadata": {
"execution": {
"iopub.execute_input": "2024-04-17T07:29:00.833351Z",
"iopub.status.busy": "2024-04-17T07:29:00.833228Z",
"iopub.status.idle": "2024-04-17T07:29:00.836985Z",
"shell.execute_reply": "2024-04-17T07:29:00.836814Z"
}
},
"outputs": [
{
"data": {
"text/html": [
" \n",
" "
],
"text/plain": [
""
]
},
"execution_count": 10,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"# Adjust the tile size - make them square and bigger.\n",
"# Show density instead of count.\n",
"p1 + geom_bin2d(aes(fill='..density..'), binwidth=[1, 1])"
]
}
],
"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": 2
}