recovered
under
bad
over
"
],
"text/plain": [
"![](\"https://i.stack.imgur.com/dAFPL.png\")
"
]
},
{
"cell_type": "markdown",
"id": "18fefdbf",
"metadata": {
"slideshow": {
"slide_type": "slide"
}
},
"source": [
"Or this one [CC BY-SA Joshua Doubek / pickthis.io]\n",
"\n",
"![](\"https://the-geophysicist.com/wp-content/uploads/2015/03/FlatSpotPickthis1.png\")
"
]
},
{
"cell_type": "markdown",
"id": "7dbbe033",
"metadata": {
"slideshow": {
"slide_type": "slide"
}
},
"source": [
"## The recipe\n",
"\n",
"- Get the data from the figure\n",
"- Figure out the colours in the colourmap\n",
"- Put the colours in the right order\n",
"- Do a reverse look-up from colour to scalar\n",
"- Move the data to the right scale\n",
"\n",
"Under some assumptions:\n",
"\n",
"- We know the polarity of the data\n",
"- We know the range of the data\n",
"- The data are spatial continous"
]
},
{
"cell_type": "markdown",
"id": "7db63da6",
"metadata": {
"slideshow": {
"slide_type": "slide"
}
},
"source": [
"## Start with some data"
]
},
{
"cell_type": "code",
"execution_count": 465,
"id": "f60b4386",
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"array([[0.19770541, 0.1982454 , 0.19934656, 0.20095198, 0.20307213],\n",
" [0.19888639, 0.19942497, 0.20052332, 0.20212445, 0.20423853],\n",
" [0.20128211, 0.20181772, 0.20291015, 0.20450218, 0.20660354],\n",
" [0.20488359, 0.20541459, 0.20649783, 0.20807578, 0.21015748],\n",
" [0.20966076, 0.21018566, 0.21125674, 0.21281609, 0.21487181]])"
]
},
"execution_count": 465,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"import scipy.ndimage as snd\n",
"import numpy as np\n",
"import matplotlib.pyplot as plt\n",
"\n",
"rng = np.random.default_rng(1111)\n",
"raw = rng.random((300, 300))\n",
"arr = snd.gaussian_filter(raw, 15)\n",
"arr = (arr - arr.min()) / (arr.max() - arr.min())\n",
"arr[:5, :5]"
]
},
{
"cell_type": "code",
"execution_count": 466,
"id": "b5f0e246",
"metadata": {
"slideshow": {
"slide_type": "slide"
}
},
"outputs": [
{
"data": {
"text/plain": [
"