{
"cells": [
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Use this notebook to obtain \"expected\" values for \n",
"```\n",
"test_geom_imshow_alpha.py\n",
"```\n",
"test suite."
]
},
{
"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()\n"
]
},
{
"cell_type": "code",
"execution_count": 2,
"metadata": {},
"outputs": [],
"source": [
"LetsPlot.set_theme(flavor_solarized_light())"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"### Greyscale image"
]
},
{
"cell_type": "code",
"execution_count": 3,
"metadata": {},
"outputs": [],
"source": [
"arr = np.array([\n",
" [50, 150, 200],\n",
" [200, 100, 50]\n",
" ])\n"
]
},
{
"cell_type": "code",
"execution_count": 4,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Normalization: 0.0002799034118652344\n",
"Clipping: 6.794929504394531e-05\n",
"image_2d: 0.00014400482177734375\n",
"png.Writer: 0.0012731552124023438\n",
"base64: 4.887580871582031e-05\n"
]
},
{
"data": {
"text/html": [
" \n",
" "
],
"text/plain": [
""
]
},
"execution_count": 4,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"ggplot() + geom_imshow(arr, alpha=.5)"
]
},
{
"cell_type": "code",
"execution_count": 5,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Normalization: 0.0002148151397705078\n",
"Clipping: 0.0002758502960205078\n",
"image_2d: 0.0001251697540283203\n",
"png.Writer: 0.00023508071899414062\n",
"base64: 4.1961669921875e-05\n"
]
},
{
"data": {
"text/html": [
" \n",
" "
],
"text/plain": [
""
]
},
"execution_count": 5,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"# 'norm' = False\n",
"ggplot() + geom_imshow(arr, norm=False, alpha=.5)"
]
},
{
"cell_type": "code",
"execution_count": 6,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"LA add alpha: 5.817413330078125e-05\n",
"Normalization: 0.0004942417144775391\n",
"Clipping: 5.1975250244140625e-05\n",
"image_2d: 0.0001399517059326172\n",
"png.Writer: 0.0002028942108154297\n",
"base64: 3.409385681152344e-05\n"
]
},
{
"data": {
"text/html": [
" \n",
" "
],
"text/plain": [
""
]
},
"execution_count": 6,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"# With NaN-s\n",
"arr_nan = np.array([\n",
" [50., np.nan, 200.],\n",
" [np.nan, 100., 50.]\n",
" ])\n",
"\n",
"ggplot() + geom_imshow(arr_nan, alpha=0.5)"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"### Alpha + cmap"
]
},
{
"cell_type": "code",
"execution_count": 7,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Normalization: 0.00017714500427246094\n",
"Clipping: 0.00016498565673828125\n",
"image_2d: 4.8160552978515625e-05\n",
"png.Writer: 0.007149696350097656\n",
"base64: 0.00011801719665527344\n"
]
},
{
"data": {
"text/html": [
" \n",
" "
],
"text/plain": [
""
]
},
"execution_count": 7,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"ggplot() + geom_imshow(arr, cmap=\"magma\", alpha=0.5)"
]
},
{
"cell_type": "code",
"execution_count": 8,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Normalization: 0.00024199485778808594\n",
"Clipping: 0.000186920166015625\n",
"image_2d: 5.412101745605469e-05\n",
"png.Writer: 0.007398843765258789\n",
"base64: 0.0001480579376220703\n"
]
},
{
"data": {
"text/html": [
" \n",
" "
],
"text/plain": [
""
]
},
"execution_count": 8,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"# With NaN-s\n",
"arr_nan = np.array([\n",
" [50., np.nan, 200.],\n",
" [np.nan, 100., 50.]\n",
" ])\n",
"\n",
"ggplot() + geom_imshow(arr_nan, cmap=\"magma\", alpha=0.5)"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"### Color image"
]
},
{
"cell_type": "code",
"execution_count": 9,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Normalization: 2.288818359375e-05\n",
"Clipping: 0.00014495849609375\n",
"image_2d: 3.409385681152344e-05\n",
"png.Writer: 0.00011992454528808594\n",
"base64: 3.218650817871094e-05\n"
]
},
{
"data": {
"text/html": [
" \n",
" "
],
"text/plain": [
""
]
},
"execution_count": 9,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"# RGB image\n",
"\n",
"A2x3x3 = np.array([\n",
" [[255, 0, 0], [0, 255, 0], [0, 0, 255]],\n",
" [[0, 255, 0], [0, 0, 255], [255, 0, 0]]\n",
" ])\n",
"\n",
"ggplot() + geom_imshow(A2x3x3)"
]
},
{
"cell_type": "code",
"execution_count": 10,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Normalization: 9.298324584960938e-05\n",
"Clipping: 0.00023794174194335938\n",
"image_2d: 3.910064697265625e-05\n",
"png.Writer: 0.0002899169921875\n",
"base64: 3.600120544433594e-05\n"
]
},
{
"data": {
"text/html": [
" \n",
" "
],
"text/plain": [
""
]
},
"execution_count": 10,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"ggplot() + geom_imshow(A2x3x3, alpha=0.5)"
]
},
{
"cell_type": "code",
"execution_count": 11,
"metadata": {},
"outputs": [],
"source": [
"# RGBA image (with alpha channel)\n",
"\n",
"A2x3x4 = np.array([\n",
" [[1, 0, 0, 1], [0, 1, 0, 1], [0, 0, 1, 1]],\n",
" [[0, 1, 0, 0.3], [0, 0, 1, 0.3], [1, 0, 0, 0.3]]\n",
" ])"
]
},
{
"cell_type": "code",
"execution_count": 12,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Normalization: 3.790855407714844e-05\n",
"Clipping: 0.00010609626770019531\n",
"image_2d: 5.4836273193359375e-05\n",
"png.Writer: 0.00015616416931152344\n",
"base64: 3.314018249511719e-05\n"
]
},
{
"data": {
"text/html": [
" \n",
" "
],
"text/plain": [
""
]
},
"execution_count": 12,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"ggplot() + geom_imshow(A2x3x4)"
]
},
{
"cell_type": "code",
"execution_count": 13,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Normalization: 5.984306335449219e-05\n",
"Clipping: 8.511543273925781e-05\n",
"image_2d: 9.012222290039062e-05\n",
"png.Writer: 0.0002319812774658203\n",
"base64: 4.1961669921875e-05\n"
]
},
{
"data": {
"text/html": [
" \n",
" "
],
"text/plain": [
""
]
},
"execution_count": 13,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"ggplot() + geom_imshow(A2x3x4, alpha=0.5)"
]
},
{
"cell_type": "code",
"execution_count": 14,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"{'mapping': {},\n",
" 'data_meta': {},\n",
" 'theme': {'flavor': 'solarized_light'},\n",
" 'kind': 'plot',\n",
" 'scales': [],\n",
" 'layers': [{'geom': 'image',\n",
" 'mapping': {},\n",
" 'data_meta': {},\n",
" 'href': 'data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAAMAAAACCAYAAACddGYaAAAAHElEQVR4nGP4z8DQwPAfiBn+gzCDGpBQAwqqAQBuAwft32FBFAAAAABJRU5ErkJggg==',\n",
" 'xmin': -0.5,\n",
" 'ymin': -0.5,\n",
" 'xmax': 2.5,\n",
" 'ymax': 1.5}],\n",
" 'metainfo_list': []}"
]
},
"execution_count": 14,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"_.as_dict()"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": []
}
],
"metadata": {
"kernelspec": {
"display_name": "Python 3",
"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": "3.7.13"
}
},
"nbformat": 4,
"nbformat_minor": 4
}