{
"cells": [
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## The `extent` parameter in `geom_imshow()` \n",
"\n",
"A list of four numbers: `[left, right, bottom, top]` that\n",
"defines the image bounding box\n",
"in terms of 'data coordinates'."
]
},
{
"cell_type": "code",
"execution_count": 1,
"metadata": {},
"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": "markdown",
"metadata": {},
"source": [
"The default `extent` is derived from the image's array dimentions: `[-0.5, ncol-0.5, -0.5, nrow-0.5]`.\n"
]
},
{
"cell_type": "code",
"execution_count": 2,
"metadata": {},
"outputs": [
{
"data": {
"text/html": [
" \n",
" "
],
"text/plain": [
""
]
},
"execution_count": 2,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"# An 2x2 pix image by default has extent [-0.5, 1.5, -0.5, 1.5]\n",
"arr = np.array([\n",
" [[150, 0, 0], [0, 150, 0]],\n",
" [[0, 0, 150], [150, 150, 0]]\n",
" ])\n",
"\n",
"ggplot() + geom_imshow(arr)"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## When does image `extent` need to be set explicitly\n",
"\n",
"Let's assume that our image doesn't exist in vacuum but is related to some data, \n",
"and the image' bounding box in the 'data coordinates' is: \n",
"\n",
"- `(x, y) = (0, -1)`\n",
"- `(width, height) = (8, 3)`.\n",
"\n",
"The image `extent` in this case would be: `[0, 8, -1, 3]`."
]
},
{
"cell_type": "code",
"execution_count": 3,
"metadata": {},
"outputs": [],
"source": [
"# Generate demo data.\n",
"cov0=[[1, -.8], \n",
" [-.8, 1]] \n",
"cov1=[[ 10, .1],\n",
" [.1, .1]]\n",
"\n",
"x0, y0 = np.random.multivariate_normal(mean=[4,0], cov=cov0, size=400).T\n",
"x1, y1 = np.random.multivariate_normal(mean=[4,1], cov=cov1, size=400).T\n",
"\n",
"data = dict(\n",
" x = np.concatenate((x0,x1)),\n",
" y = np.concatenate((y0,y1))\n",
")"
]
},
{
"cell_type": "code",
"execution_count": 4,
"metadata": {},
"outputs": [
{
"data": {
"text/html": [
" \n",
" "
],
"text/plain": [
""
]
},
"execution_count": 4,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"ggplot(data, aes('x', 'y')) + geom_density2d() + ggsize(620, 300)"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Let's show the data and the image on the same plot."
]
},
{
"cell_type": "code",
"execution_count": 5,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"WARN: The function geom_image() is deprecated and and will be removed in future releases.\n",
" Please, use geom_imshow() instead.\n"
]
},
{
"data": {
"text/html": [
" \n",
" "
],
"text/plain": [
""
]
},
"execution_count": 5,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"(ggplot(data, aes('x', 'y')) + \n",
" geom_image(arr, extent=[0, 8, -1, 3]) + \n",
" geom_density2d(color=\"yellow\") + \n",
" ggsize(620, 300) + \n",
" flavor_high_contrast_dark())"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"# \n",
"## Flipping and transposing image using `extent`"
]
},
{
"cell_type": "code",
"execution_count": 6,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"(225, 225, 3)"
]
},
"execution_count": 6,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"# Load image file.\n",
"from PIL import Image\n",
"import requests\n",
"from io import BytesIO\n",
"\n",
"response = requests.get('https://github.com/JetBrains/lets-plot-docs/raw/master/source/examples/cookbook/images/fisher_boat.png')\n",
"\n",
"image = Image.open(BytesIO(response.content))\n",
"boat_arr = np.asarray(image)\n",
"boat_arr.shape\n"
]
},
{
"cell_type": "code",
"execution_count": 7,
"metadata": {},
"outputs": [
{
"data": {
"text/html": [
" \n",
" "
],
"text/plain": [
""
]
},
"execution_count": 7,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"ggplot() + geom_imshow(image_data=boat_arr)"
]
},
{
"cell_type": "code",
"execution_count": 8,
"metadata": {},
"outputs": [
{
"data": {
"text/html": [
" \n",
" "
],
"text/plain": [
""
]
},
"execution_count": 8,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"dim = 100\n",
"\n",
"ext_base = [0, dim, 0, dim]\n",
"ext_flip_x = [dim, 0, 0, dim]\n",
"ext_flip_y = [0, dim, dim, 0]\n",
"ext_transpose = [dim, 0, dim, 0]\n",
"\n",
"label_data = dict(\n",
" x = [50, 150, 150, 50],\n",
" y = [200, 200, 0, 0],\n",
" label = [\"original\", \"flip columns\", \"flip rows\", \"transpose\"]\n",
")\n",
"\n",
"(ggplot() + \n",
" geom_imshow(\n",
" boat_arr, \n",
" extent=[v + dim if i in (2, 3) else v for i, v in enumerate(ext_base)]\n",
" ) + \n",
" geom_imshow(\n",
" boat_arr, \n",
" extent=[v + dim for v in ext_flip_x]\n",
" ) + \n",
" geom_imshow(\n",
" boat_arr, \n",
" extent=[v + dim if i in (0, 1) else v for i, v in enumerate(ext_flip_y)]\n",
" ) + \n",
" geom_imshow(\n",
" boat_arr, \n",
" extent=ext_transpose\n",
" ) + \n",
" geom_hline(yintercept=100, color=\"yellow\", tooltips=\"none\") + \n",
" geom_vline(xintercept=100, color=\"yellow\", tooltips=\"none\") + \n",
" geom_label(aes(\"x\", \"y\", label=\"label\"), data=label_data) +\n",
" ggsize(700, 700)\n",
")"
]
}
],
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"display_name": "Python 3 (ipykernel)",
"language": "python",
"name": "python3"
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