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HAPs Notebook

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Florent Guiotte 2018-03-30 12:10:46 +02:00
parent 862c3abe96
commit 43d36230a1
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{
"cells": [
{
"cell_type": "markdown",
"metadata": {},
"source": [
"# Histogram APs"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"import sys\n",
"from pathlib import Path\n",
"import numpy as np\n",
"import matplotlib.pyplot as plt\n",
"\n",
"triskele_path = Path('../triskele/python/')\n",
"sys.path.append(str(triskele_path.resolve()))\n",
"import triskele"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"# Specific Utils\n",
"\n",
"def DFC_filter(raster):\n",
" raster[raster > 1e4] = raster[raster < 1e4].max()\n",
"\n",
"def show(im):\n",
" plt.figure(figsize=(16*2,3*2))\n",
" plt.imshow(im)\n",
" plt.colorbar()\n",
" plt.show()"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"raster_p = Path('../Data/phase1_rasters/Intensity_C3/UH17_GI3F051_TR.tif')\n",
"raster = triskele.read(raster_p)\n",
"DFC_filter(raster)"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"show(raster)"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"area = np.array([25, 100, 500, 1e3, 5e3, 10e3, 50e3, 100e3, 150e3])\n",
"\n",
"t = triskele.Triskele(raster, verbose=False)\n",
"attributes = t.filter(tree='tos-tree',\n",
" area=area\n",
" )\n",
"attributes.shape"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"a = attributes\n",
"i = 3\n",
"show(a[:,:,i].astype(np.float) - a[:,:,i+1])"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"patch_size = 5\n",
"\n",
"### \n",
"amp = int((patch_size - 1 ) / 2)\n",
"\n",
"stack = list()\n",
"for i in range(-amp, amp+1):\n",
" ai = i if i > 0 else None\n",
" bi = i if i < 0 else None\n",
" ci = -bi if bi is not None else None\n",
" di = -ai if ai is not None else None\n",
"\n",
" for j in range(-amp, amp+1):\n",
" offset = np.zeros(raster.shape)\n",
" aj = j if j > 0 else None\n",
" bj = j if j < 0 else None\n",
" cj = -bj if bj is not None else None\n",
" dj = -aj if aj is not None else None\n",
" print('{}:{} {}:{} - {}:{} {}:{}'.format(ai, bi, ci, di, aj, bj, cj, dj))\n",
" offset[ai:bi, aj:bj] = raster[ci:di, cj:dj]\n",
" stack.append(offset)\n",
"\n",
"offset_stack = np.stack(stack, axis=2)\n",
"offset_stack.shape"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"offset_stack[-3,-3,:].reshape(-1,1)"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"show(offset_stack[:,:,0])"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"del offset_stack"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"hist = np.stack(raster, raster[:]"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"np.repeat(100,10)"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"import pandas as pd"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"pstl = list()\n",
"\n",
"for c, p in [(100, .06), (60, .1), (12, .5), (20, .3)]:\n",
" st = np.random.binomial(np.repeat(c,1e7), p)\n",
" pst = pd.DataFrame(st, columns=['{} - {}'.format(c, p)])\n",
" pstl.append(pst)\n",
" \n",
"psta = pd.concat(pstl)\n",
"pd.options.display.float_format = '{:.2f}'.format\n",
"display(psta.describe())\n",
"psta.hist(figsize=(16, 9))\n",
"plt.show()"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": []
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"pd.concat([pst, pst], axis=1)"
]
}
],
"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"
}
},
"nbformat": 4,
"nbformat_minor": 2
}