{
"cells": [
{
"cell_type": "markdown",
"id": "c284f51c-72ac-4e19-981d-43fc79570b16",
"metadata": {},
"source": [
"# `geom_spoke()`"
]
},
{
"cell_type": "code",
"execution_count": 1,
"id": "45bd1cf4-dcec-460e-8a92-8e7cb9b15ea6",
"metadata": {
"execution": {
"iopub.execute_input": "2025-07-17T16:54:16.260953Z",
"iopub.status.busy": "2025-07-17T16:54:16.260456Z",
"iopub.status.idle": "2025-07-17T16:54:16.263680Z",
"shell.execute_reply": "2025-07-17T16:54:16.263470Z"
}
},
"outputs": [],
"source": [
"import numpy as np\n",
"\n",
"from lets_plot import *"
]
},
{
"cell_type": "code",
"execution_count": 2,
"id": "6a9633c3-f3fa-43b6-bd85-5c55169c223b",
"metadata": {
"execution": {
"iopub.execute_input": "2025-07-17T16:54:16.264781Z",
"iopub.status.busy": "2025-07-17T16:54:16.264679Z",
"iopub.status.idle": "2025-07-17T16:54:16.266516Z",
"shell.execute_reply": "2025-07-17T16:54:16.266348Z"
}
},
"outputs": [
{
"data": {
"text/html": [
"\n",
" \n",
" \n",
" "
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"LetsPlot.setup_html()"
]
},
{
"cell_type": "code",
"execution_count": 3,
"id": "8208a625-fa5f-40e2-83dc-f7a033cb051e",
"metadata": {
"execution": {
"iopub.execute_input": "2025-07-17T16:54:16.267292Z",
"iopub.status.busy": "2025-07-17T16:54:16.267166Z",
"iopub.status.idle": "2025-07-17T16:54:16.269757Z",
"shell.execute_reply": "2025-07-17T16:54:16.269572Z"
}
},
"outputs": [],
"source": [
"def cartesian_to_polar(xarray, yarray, rscale):\n",
" rarray = np.sqrt(xarray**2 + yarray**2)\n",
" return rarray / rarray.max() * rscale, np.arctan2(yarray, xarray)\n",
"\n",
"def get_data(n, a, b, vector_field):\n",
" d = (b - a) / (n - 1)\n",
" xrange = np.linspace(a, b, n)\n",
" yrange = np.linspace(a, b, n)\n",
" X, Y = np.meshgrid(xrange, yrange)\n",
" R, A, Z = vector_field(X, Y, d)\n",
" z = [None] * X.shape[0] * X.shape[1] if Z is None else Z.reshape(-1)\n",
" return dict(x=X.reshape(-1), y=Y.reshape(-1), r=R.reshape(-1), a=A.reshape(-1), z=z)\n",
"\n",
"def vector_field(f):\n",
" def field(xarray, yarray, d):\n",
" return *cartesian_to_polar(*f(xarray, yarray), d), None\n",
" return field\n",
"\n",
"def gradient_field(f):\n",
" def field(xarray, yarray, d):\n",
" Z = f(xarray, yarray)\n",
" return *cartesian_to_polar(*reversed(np.gradient(Z, d)), d), Z\n",
" return field"
]
},
{
"cell_type": "markdown",
"id": "6c2e3974-aad5-4f62-bac4-6afa1327bf6f",
"metadata": {},
"source": [
"#### 1. Plot Vector Field"
]
},
{
"cell_type": "code",
"execution_count": 4,
"id": "bb63ad78-fce0-40e0-b31d-870f71cab410",
"metadata": {
"execution": {
"iopub.execute_input": "2025-07-17T16:54:16.270490Z",
"iopub.status.busy": "2025-07-17T16:54:16.270421Z",
"iopub.status.idle": "2025-07-17T16:54:16.272033Z",
"shell.execute_reply": "2025-07-17T16:54:16.271854Z"
}
},
"outputs": [],
"source": [
"n = 11\n",
"a, b = -5, 5\n",
"vector_field_data = get_data(n, a, b, vector_field(lambda xarray, yarray: (yarray, -xarray)))"
]
},
{
"cell_type": "code",
"execution_count": 5,
"id": "a5e48193-c5f1-49c3-9b83-c83b46cf4943",
"metadata": {
"execution": {
"iopub.execute_input": "2025-07-17T16:54:16.272696Z",
"iopub.status.busy": "2025-07-17T16:54:16.272626Z",
"iopub.status.idle": "2025-07-17T16:54:16.304362Z",
"shell.execute_reply": "2025-07-17T16:54:16.304077Z"
}
},
"outputs": [
{
"data": {
"text/html": [
" \n",
" "
],
"text/plain": [
""
]
},
"execution_count": 5,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"ggplot(vector_field_data, aes('x', 'y', color='r')) + \\\n",
" geom_spoke(aes(angle='a', radius='r'), \\\n",
" arrow=arrow(type='closed', angle=12, length=15)) + \\\n",
" scale_color_gradient(low='#3288bd', high='#d53e4f', guide='none') + \\\n",
" coord_fixed(xlim=[a, b], ylim=[a, b]) + \\\n",
" ggsize(500, 500) + \\\n",
" theme_minimal() + \\\n",
" theme(axis_text=element_text(margin=10), axis_title='blank')"
]
},
{
"cell_type": "markdown",
"id": "6f14a6ee-1173-4ee1-a0e6-e1212bed151f",
"metadata": {},
"source": [
"#### 2. Plot Gradient of a Scalar Field"
]
},
{
"cell_type": "code",
"execution_count": 6,
"id": "37cdc646-d4cc-44ce-bff2-71306299c3e5",
"metadata": {
"execution": {
"iopub.execute_input": "2025-07-17T16:54:16.305478Z",
"iopub.status.busy": "2025-07-17T16:54:16.305405Z",
"iopub.status.idle": "2025-07-17T16:54:16.307291Z",
"shell.execute_reply": "2025-07-17T16:54:16.307032Z"
}
},
"outputs": [],
"source": [
"gradient_field_data = get_data(21, -2*np.pi, 2*np.pi, gradient_field(lambda xarray, yarray: np.sin(xarray) + np.cos(yarray)))"
]
},
{
"cell_type": "code",
"execution_count": 7,
"id": "52db3359-3841-4bc4-9a63-56126df011a6",
"metadata": {
"execution": {
"iopub.execute_input": "2025-07-17T16:54:16.308319Z",
"iopub.status.busy": "2025-07-17T16:54:16.308179Z",
"iopub.status.idle": "2025-07-17T16:54:16.309741Z",
"shell.execute_reply": "2025-07-17T16:54:16.309570Z"
}
},
"outputs": [],
"source": [
"p = ggplot(gradient_field_data, aes('x', 'y')) + coord_fixed() + theme_void() + scale_viridis(['color', 'fill'])"
]
},
{
"cell_type": "code",
"execution_count": 8,
"id": "b4ede698-83b4-42df-8446-7cf309ebb0f3",
"metadata": {
"execution": {
"iopub.execute_input": "2025-07-17T16:54:16.310397Z",
"iopub.status.busy": "2025-07-17T16:54:16.310329Z",
"iopub.status.idle": "2025-07-17T16:54:16.316454Z",
"shell.execute_reply": "2025-07-17T16:54:16.316286Z"
}
},
"outputs": [
{
"data": {
"text/html": [
" \n",
" "
],
"text/plain": [
""
]
},
"execution_count": 8,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"p + geom_bin2d(aes(fill='z'), stat='identity')"
]
},
{
"cell_type": "code",
"execution_count": 9,
"id": "32043345-6a07-4699-b29b-bbc685745a6d",
"metadata": {
"execution": {
"iopub.execute_input": "2025-07-17T16:54:16.317153Z",
"iopub.status.busy": "2025-07-17T16:54:16.317084Z",
"iopub.status.idle": "2025-07-17T16:54:16.324049Z",
"shell.execute_reply": "2025-07-17T16:54:16.323884Z"
}
},
"outputs": [
{
"data": {
"text/html": [
" \n",
" "
],
"text/plain": [
""
]
},
"execution_count": 9,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"p + geom_spoke(aes(angle='a', radius='r', color='z'), arrow=arrow(type='closed', angle=15))"
]
},
{
"cell_type": "markdown",
"id": "3232e0ce-b989-4374-a749-3dceed9fd9af",
"metadata": {},
"source": [
"#### 3. Parameter `pivot`"
]
},
{
"cell_type": "code",
"execution_count": 10,
"id": "799e4da4-222f-471c-891e-8c11f2a37d5b",
"metadata": {
"execution": {
"iopub.execute_input": "2025-07-17T16:54:16.324838Z",
"iopub.status.busy": "2025-07-17T16:54:16.324724Z",
"iopub.status.idle": "2025-07-17T16:54:16.326674Z",
"shell.execute_reply": "2025-07-17T16:54:16.326492Z"
}
},
"outputs": [],
"source": [
"def get_plot(pivot):\n",
" n = 4\n",
" a, b = -2, 2\n",
" r = .75\n",
" pivot_data = get_data(n, a, b, gradient_field(lambda xarray, yarray: xarray**2 + yarray**2))\n",
" title = \"pivot={0}{1}\".format(pivot, \" (default)\" if pivot == 'tail' else \"\")\n",
" return ggplot(pivot_data, aes('x', 'y')) + \\\n",
" geom_spoke(aes(angle='a'), radius=r, pivot=pivot) + \\\n",
" geom_point() + \\\n",
" coord_fixed() + \\\n",
" xlim(a - r, b + r) + ylim(a - r, b + r) + \\\n",
" ggtitle(title) + \\\n",
" theme_void() + theme(plot_title=element_text(hjust=0.5))"
]
},
{
"cell_type": "code",
"execution_count": 11,
"id": "386e5ccf-1cf9-4297-aa6a-1c382198e70e",
"metadata": {
"execution": {
"iopub.execute_input": "2025-07-17T16:54:16.327266Z",
"iopub.status.busy": "2025-07-17T16:54:16.327197Z",
"iopub.status.idle": "2025-07-17T16:54:16.332714Z",
"shell.execute_reply": "2025-07-17T16:54:16.332539Z"
}
},
"outputs": [
{
"data": {
"text/html": [
" \n",
" "
],
"text/plain": [
""
]
},
"execution_count": 11,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"gggrid([get_plot('tail'), get_plot('mid'), get_plot('tip')], ncol=3)"
]
},
{
"cell_type": "markdown",
"id": "ff8fcd76-437b-4ea1-a0a0-5179f7b33f87",
"metadata": {},
"source": [
"#### 4. On Map"
]
},
{
"cell_type": "code",
"execution_count": 12,
"id": "6368c818-a489-4fec-a8d9-45a8370539d2",
"metadata": {
"execution": {
"iopub.execute_input": "2025-07-17T16:54:16.333351Z",
"iopub.status.busy": "2025-07-17T16:54:16.333282Z",
"iopub.status.idle": "2025-07-17T16:54:16.334842Z",
"shell.execute_reply": "2025-07-17T16:54:16.334669Z"
}
},
"outputs": [],
"source": [
"map_data = get_data(30, 0, 40, vector_field(lambda xarray, yarray: (np.sin(yarray / 4), np.cos(xarray / 4))))"
]
},
{
"cell_type": "code",
"execution_count": 13,
"id": "833e79ad-19d7-4c17-97e2-1c24d582d201",
"metadata": {
"execution": {
"iopub.execute_input": "2025-07-17T16:54:16.335494Z",
"iopub.status.busy": "2025-07-17T16:54:16.335365Z",
"iopub.status.idle": "2025-07-17T16:54:16.345749Z",
"shell.execute_reply": "2025-07-17T16:54:16.345570Z"
}
},
"outputs": [
{
"data": {
"text/html": [
" \n",
" "
],
"text/plain": [
""
]
},
"execution_count": 13,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"ggplot() + \\\n",
" geom_livemap(zoom=5) + \\\n",
" geom_spoke(aes('x', 'y', angle='a', radius='r'), data=map_data, arrow=arrow(type='closed', angle=15))"
]
}
],
"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
}