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@aaronspring
Created May 5, 2021 17:03
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LR sklearn-xarray with loop over grid
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{
"cells": [
{
"cell_type": "markdown",
"metadata": {},
"source": [
"# West Africa Jun-Aug case demo using GEFS SubX hindcasts (1999-2015) and forecasts (2017-2020).\n",
"\n",
"This demo uses Extended Logistic Regression as a simple example of a ML method:\n",
"\n",
"1. Download data:\n",
" 1. GEFS reforecasts and forecasts of week 3-4 precip, made every Wednesday.\n",
" 2. Download matching CHIRPS data.\n",
"3. Train \"ML\" model on 1999-2015 Jun-Aug hindcast period.\n",
"4. Generate calibrated forecasts for 2017-2020 test period\n",
"5. Verify against observations using RPSS.\n",
"\n",
"- Created on Sat Nov 21 2020 @author: @awr: https://renkulab.io/gitlab/awr/s2sforecast/-/blob/master/notebooks/S2Sforecast.ipynb\n",
"- Converted to xarray: Thu Apr 22 2021 @author: aaron.spring\n",
"\n",
"Todo:\n",
"\n",
"- Ensure that each grid point is trained individually: Looks like currently all grids are individual samples.\n",
"- Use ensemble members `M`, currently using `forecast.mean('M')`\n",
"- Write into nice wrappers.\n",
"\n",
"Relies on:\n",
"\n",
"- `sklearn`: https://scikit-learn.org/stable/modules/linear_model.html#logistic-regression\n",
"- `xarray`: http://xarray.pydata.org/en/stable/reshaping.html#stack-and-unstack\n",
"- `sklearn-xarray`: https://phausamann.github.io/sklearn-xarray/"
]
},
{
"cell_type": "code",
"execution_count": 1,
"metadata": {},
"outputs": [],
"source": [
"#!pip install git+https://github.com/phausamann/sklearn-xarray # sklearn wrapper for xarray"
]
},
{
"cell_type": "code",
"execution_count": 2,
"metadata": {},
"outputs": [],
"source": [
"#!pip install git+https://github.com/xarray-contrib/xskillscore.git"
]
},
{
"cell_type": "code",
"execution_count": 3,
"metadata": {},
"outputs": [],
"source": [
"from subprocess import call\n",
"import xarray as xr\n",
"import matplotlib.pyplot as plt\n",
"import numpy as np\n",
"\n",
"from sklearn_xarray import wrap, Target\n",
"from sklearn.linear_model import LogisticRegression\n",
"\n",
"from xskillscore import rps"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"# Get data\n",
"\n",
"The datasets are downloaded as week 3-4 anomalies for W Africa domain, with the climatology subtracted.\n",
"\n",
"- A Python dictionary can be set up for each of the S2S models, for precip and 2mT biweekly averages (we have this already at IRI)\n",
"- Getting other variables at daily resolution is starightforward, but someone will need to prepare these dictionary entries\n",
"- The obs data is regridded using IRIDL to the S2S model grid (here the SubX 1-deg grid)"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Training"
]
},
{
"cell_type": "code",
"execution_count": 4,
"metadata": {},
"outputs": [],
"source": [
"download=True\n",
"download=False"
]
},
{
"cell_type": "code",
"execution_count": 5,
"metadata": {},
"outputs": [],
"source": [
"fname = 'GEFS_pra_hc.nc'\n",
"dset_url = 'http://iridl.ldeo.columbia.edu/SOURCES/.Models/.SubX/.EMC/.GEFS/.hindcast/.pr/S/(0000%206%20Jan%201999)/(0000%2028%20Dec%202015)/RANGEEDGES/S/(days%20since%201999-01-01)/streamgridunitconvert/Y/1/20/RANGE/X/-20/10/RANGE/L/(14)/(28)/RANGEEDGES/%5BL%5Daverage/S/(Jun-Aug)/VALUES/SOURCES/.Models/.SubX/.EMC/.GEFS/.hindcast/.dc9915/.pr/Y/1/20/RANGE/X/-20/10/RANGE/L/(14)/(28)/RANGEEDGES/%5BL%5Daverage/S/to366daysample/%5BYR%5Daverage/S/sampleDOY/sub/c%3A/0.001/(m3%20kg-1)/%3Ac/mul/c%3A/1000/(mm%20m-1)/%3Ac/mul/c%3A/86400/(s%20day-1)/%3Ac/mul/c%3A/7.0//units//days/def/%3Ac/mul/data.nc'\n",
"if download:\n",
" call(['curl','-k',dset_url, '-o',fname])\n",
"\n",
"x = xr.open_dataset(fname)['aprod']\n",
"\n",
"fname = 'GEFS_CHIRPS_pra_hc.nc'\n",
"dset_url = 'http://iridl.ldeo.columbia.edu/SOURCES/.Models/.SubX/.EMC/.GEFS/.hindcast/.pr/Y/1/20/RANGE/X/-20/10/RANGE/S/(0000%206%20Jan%201999)/(0000%2028%20Dec%202015)/RANGEEDGES/S/(Jun-Aug)/VALUES/L/(14)/(28)/RANGEEDGES/%5BL%5D//keepgrids/average/L/S/add/0/RECHUNK//name//T/def/2/%7Bexch%5BL/S%5D//I/nchunk/NewIntegerGRID/replaceGRIDstream%7Drepeat/use_as_grid/SOURCES/.UCSB/.CHIRPS/.v2p0/.daily-improved/.global/.0p25/.prcp/Y/1/20/RANGE/X/-20/10/RANGE/%5BX/Y%5DregridLinear/T/(days%20since%201960-01-01)/streamgridunitconvert/dup/pentadAverage/pentadmean/%5BT%5D/regridLinear/sub/T/14/runningAverage/c%3A/7.0//units//days/def/%3Ac/mul/T/2/index/.T/SAMPLE/nip/data.nc'\n",
"if download:\n",
" call(['curl','-k',dset_url, '-o',fname])\n",
"\n",
"y = xr.open_dataset(fname)['aprod']"
]
},
{
"cell_type": "code",
"execution_count": 6,
"metadata": {},
"outputs": [],
"source": [
"# align time\n",
"x = x.rename({'S':'T'}).assign_coords(T=y['T'])"
]
},
{
"cell_type": "code",
"execution_count": 7,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"[<matplotlib.lines.Line2D at 0x7fbe45157590>]"
]
},
"execution_count": 7,
"metadata": {},
"output_type": "execute_result"
},
{
"data": {
"image/png": 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\n",
"text/plain": [
"<Figure size 432x288 with 1 Axes>"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
}
],
"source": [
"X,Y=10,15\n",
"x.isel(X=X,Y=Y).mean('M').plot()\n",
"\n",
"y.isel(X=X,Y=Y).plot()"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Test"
]
},
{
"cell_type": "code",
"execution_count": 8,
"metadata": {},
"outputs": [],
"source": [
"# Forecasts\n",
"fname = 'GEFS_pra_fc.nc'\n",
"dset_url = 'https://iridl.ldeo.columbia.edu/SOURCES/.Models/.SubX/.EMC/.GEFS/.forecast/.pr/S/(0000%202%20Aug%202017)/(0000%201%20Sep%202020)/RANGEEDGES/S/7/STEP/S/(Jun-Aug)/VALUES/Y/1/20/RANGE/X/-20/10/RANGE/L/(14)/(28)/RANGEEDGES/%5B/L%5Daverage/SOURCES/.Models/.SubX/.EMC/.GEFS/.hindcast/.dc9915/.pr/Y/1/20/RANGE/X/-20/10/RANGE/L/(14)/(28)/RANGEEDGES/%5B/L%5Daverage/S/pentadAverage/S/pentadmean/%5BS%5DregridLinear/sub/c%3A/0.001/(m3%20kg-1)/%3Ac/mul/c%3A/1000/(mm%20m-1)/%3Ac/mul/c%3A/86400/(s%20day-1)/%3Ac/mul/c%3A/7.0//units//days/def/%3Ac/mul/data.nc'\n",
"if download:\n",
" call(['curl','-k',dset_url, '-o',fname])\n",
"xf = xr.open_dataset(fname)['aprod']\n",
"\n",
"# CHIRPS matching forecast targets \n",
"fname = 'GEFS_CHIRPS_pra_fc.nc'\n",
"dset_url = 'http://iridl.ldeo.columbia.edu/SOURCES/.Models/.SubX/.EMC/.GEFS/.forecast/.pr/S/(0000%202%20Aug%202017)/(0000%201%20Sep%202020)/RANGEEDGES/S/7/STEP/S/(Jun-Aug)/VALUES/Y/1/20/RANGE/X/-20/10/RANGE/L/(14)/(28)/RANGEEDGES/%5BL%5D//keepgrids/average/L/S/add/0/RECHUNK//name//T/def/2/%7Bexch%5BL/S%5D//I/nchunk/NewIntegerGRID/replaceGRIDstream%7Drepeat/use_as_grid/SOURCES/.UCSB/.CHIRPS/.v2p0/.daily-improved/.global/.0p25/.prcp/Y/1/20/RANGE/X/-20/10/RANGE/%5BX/Y%5DregridLinear/T/(days%20since%201960-01-01)/streamgridunitconvert/dup/pentadAverage/pentadmean/%5BT%5D/regridLinear/sub/T/14/runningAverage/c%3A/7.0//units//days/def/%3Ac/mul/T/2/index/.T/SAMPLE/data.nc'\n",
"if download:\n",
" call(['curl','-k',dset_url, '-o',fname])\n",
"yf = xr.open_dataset(fname)['aprod']"
]
},
{
"cell_type": "code",
"execution_count": 9,
"metadata": {},
"outputs": [],
"source": [
"# align time\n",
"xf = xf.rename({'S':'T'}).assign_coords(T=yf['T'])"
]
},
{
"cell_type": "code",
"execution_count": 10,
"metadata": {},
"outputs": [],
"source": [
"def rename_dims(ds):\n",
" return ds.rename({\"X\":\"longitude\", \"Y\":\"latitude\", \"T\": \"valid_time\"})"
]
},
{
"cell_type": "code",
"execution_count": 11,
"metadata": {},
"outputs": [],
"source": [
"x = rename_dims(x)\n",
"xf = rename_dims(xf)\n",
"y = rename_dims(y)\n",
"yf = rename_dims(yf)"
]
},
{
"cell_type": "code",
"execution_count": 12,
"metadata": {},
"outputs": [],
"source": [
"# not ensemble mean\n",
"xf2 = xf.copy().rename({'M':'member'})\n",
"x2 = x.copy().rename({'M':'member'})"
]
},
{
"cell_type": "code",
"execution_count": 13,
"metadata": {},
"outputs": [],
"source": [
"download=False\n",
"# use only ensemble member mean\n",
"member_mean=True\n",
"if member_mean:\n",
" x = x.mean('M')\n",
" xf = xf.mean('M')\n",
" quantile_dim=['T']\n",
"else:\n",
" quantile_dim=['M','T']"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"### land-sea mask"
]
},
{
"cell_type": "code",
"execution_count": 14,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"<matplotlib.collections.QuadMesh at 0x7fbe44ddf650>"
]
},
"execution_count": 14,
"metadata": {},
"output_type": "execute_result"
},
{
"data": {
"image/png": 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Jt9qutfBN3RHSJ0w2uIiIodbHmYOkzYA38Ogs2ldI+rjtte3urZU5SDqjRfL9wDLbX6kdaUTEMDH92ltpxMeAzajWnQZ4TUl7fbsb61YrbUlVLPliOX45sAI4UdLhtt8ykWgjIoZFP/ZWavBM240zXP+XpBvr3Fg3c/gD4Pm21wFI+hjVzKwvBH4wkUgjIoZKf2cO6yXtZftHAKXnUtu1eKB+5rArsBVVVRJlfxfb6yXVatyIiIhp91fAN0tvJQFPAmq1IdfNHP4FuEHSFeUBzwP+qQyK+8aEw42IGBL9Wq1UBjDvD8wF9qb67e54b6VPSVoCHFQe8M6ychvAX0846hngyF2mvpDd0tW1qgYjopf6dJxDqdk52vaHqJYVnZC66zkIOALY3/aXgU0lHVTjvnMk3TOyDkRJmy3pMkm3l9fHj3HvPEm3SVop6dR6HyciYhqZaiXnOltvfFvSmZIOlfT0ka3OjXXXc/go8GyqSZsAHgTOqnHfucC8prRTgcttzwUuL8cbKcWhs4CjgH2ABZL2qRlrRMS0kettPfIcYF/gPcAHyvav495R1G1zONj20yV9H8D2LyVt3u4m21dJ2rMp+RjgsLL/aeAK4O1N1xwErLR9B4CkC8p9N9eMNyJievRpmwOA7cMne2/dksPa8tf8yHoOOzD5gtJOtu8CKK87trhmV+BnDcerSlpERH/p44n3JD1B0hmSrpd0naQPS3pCnXvrZg5nABcBO0r6R+BbwD9NMt46WrXwtPx6JS2UtEzSsrWkV21ETJ+6VUo9rFa6APgF1cDlY8v+5+vcWLe30nmSrqNqlBbwUtu3TC5W7pa0s+27JO0M3NPimlXA7g3HuwGrW1yH7UVUCxGxrWb3cQEvIoZSf0+fMdv26Q3H/yDppXVuHLfkUHoWzZY0m+pH/Hzgc1Q/8LMnGexi4PiyfzzQam6ma4G5kuaUto3jyn0REX2lz0sO35R0nKRNyvanwNfq3Niu5HAdVXWOgD2AX5b97YCfAnPGu1nS+VSNz9tLWgW8G3gv8AVJJ5b3eEW5dhfgk7bn214n6RRgKTALOMf2ijofKCJiWvV3fcUbgLcBny3Hs4DfSHobYNvbjnXjuJmD7TkAks4GFtteUo6PAl7QLirbC8Y4dUSLa1cD8xuOlwBL2j0jIqJnelsqaMv2NqWWZy7VBKoj6Ve2u7duV9Zn2j6p4Y2/Lun08W6IiJgR+jhzkPR64M1U7bY3AM8Cvk2LP9Cb1c0c1kj6O+A/qL6K/0O1Mlx0UbspODK9RkQf6OPMgSpjeCZwje3DJT0V+Ps6N9btyrqAalHqi8q2A4+Olo6ImLH6vEH697Z/DyBpC9u3Uk3C11bdrqz3UeVAERHRqL9LDqskbQd8GbhM0i8ZY1hAs3ZdWU9r9wZ1romIGEp9PgjO9sts/8r2acD/Az4FvLTOve1KDq+X9MA450U1BuG0Og+LiBg6/V1yeESdHkqN2mUOnwC2qXFNRMTMNCCZw0S1G+dQq1U7ImImEv09zmEq6vZWioiIZgZtqLfVUXeRM0nPlLRe0rGd+ijNkjlERExFh6bsrrvIWbnufVTTC3VNMoeIiKno3HoOjyxyZvthqum2j2lx3V8AX6L1jNYdU3cN6adIunxkLWhJ+5UR0xERM9oEurJuP7L2TNkWNr1V20XOJO0KvAw4u4sfCahfcvgE8A5gLYDt5VRdWCMiZrb6JYc1tg9s2BY1vVOdRc7+DXi77fUdi38MdedWeqzt70kbxb6uC/FERAwO129srqHOImcHAheU3+LtgfmS1tn+cseiKCYy8d5ePLqG9LHAXZ0OJiJi4HSuK+sji5wBP6eqnXnVRo8qyygASDoXuLgbGQPUzxxOplqK86mSfg78mGpm1oiIGa1T4xzGWuRM0knlfNfbGRrVnXjvDuAFkrYCNrH9YHfDiogYEB0cBNdqkbOxMgXbr+vck0cbN3MoS8m1SgfA9ge7EFNExGCo30114LQrOYzMq7Q31YIRi8vxS4CruhVURMQgEK27GA2DWnMrSboUePpIdVKZpvuLk32opL2BzzckPRl4l+1/a7jmMOArVO0bABfafs9knxkR0Q0d7K3UV+o2SO8BPNxw/DCw52Qfavs24AB4ZCj4z6lWmGt2te0XT/Y5ERFdN0OrlUZ8FviepIuovoqXAZ/pUAxHAD+y/ZMOvV9ExPSZyZmD7X+U9HXg0JJ0gu3vdyiG44Dzxzj3bEk3Ug0E+SvbK5ovKEPQFwJsyWM7FNJgOHKX/dtes3T1jdMQScQM1dv1obuqVuYgaQ9gDQ1VP5L2sP3TqTxc0ubA0VRTczS7HniS7V9Lmk+1Burc5ovKEPRFANtq9pD+M0VE3xrSX5261Upf49Gv4DHAHOA2YN8pPv8o4HrbdzefsP1Aw/4SSR+VtL3tNVN8ZkREx8zoBmnbf9h4LOnpwBs68PwFjFGlJOmJwN22LekgqkkC7+3AMyMiOmZGVys1s329pGdO5cGSHgu8kIZMpmmY+LHAGyWtA34HHGd7SP8ZImIgzeBBcMCokdKbAE8HfjGVB9v+LfCEprSzG/bPBM6cyjMiIrpuJmcOPDpSGqqpur9GtRJRRMSMJVKtdLPtjUZES3oFUxglHRExFIY0c6i7Elyrrqat0iIiZg6DNrjWNmjazcp6FDAf2FXSGQ2ntiUrwUVEzNhqpdXAMqqBatc1pD8IvLVbQUVEDIyZmDnYvhG4UdJ5tlNSGEB1pthoJ1Nw9LdO/BvXkf8OWpuRJQdJX7D9p8D3pdFfge39uhZZRMQgmImZA/Dm8pppsyMimg3xxHvj9layfVfZfZPtnzRuwJu6H15ERP8S1dxKdbZBU7cr6wtbpB3VyUAiIgaSXW8bMO3aHN5IVUJ4sqTlDae2Af67m4FFRAyCYa1Watfm8Dng68A/A6c2pD9o+76uRRURMQhm6sR7tu8H7qeaWhtJOwJbAltL2nqqi/1ERAy6QWxPqKNWm4Okl0i6HfgxcCVwJ1WJIiJiRpvpDdL/ADwL+KHtOcARpM0hImY6M7QN0nUzh7W27wU2kbSJ7W8CB3QvrIiIwSDX2wZN3Sm7fyVpa+Aq4DxJ95CJ92aMOtMzDNLUCv30eaZr6otO6Kfvra8M4A9/HXVLDsdQLdX5VuAS4EfAS7oVVETEIBhZ7GfGlhxs/6bh8NOdeLCkO6lmd10PrLN9YNN5AR+mmjL8t8DrbF/fiWdHRHTEgLYn1NFuENyDtC40CbDtbaf4/MNtrxnj3FHA3LIdDHysvEZE9I1B7IlUR7txDtuMd77LjgE+Y9vANZK2k7Rzw3xPERE9N4hVRnXUbXPoBgOXSrpO0sIW53cFftZwvKqkbUTSQknLJC1by0NdCjUiogUDG1xvGzB1eyt1wyG2V5dR15dJutX2VQ3n1eKeVmtKLAIWAWyr2YP3LxARg21If3V6VnKwvbq83gNcBBzUdMkqYPeG492oli2NiOgbneytJGmepNskrZR0aovzr5a0vGzfltS1vtA9yRwkbSVpm5F94EXATU2XLQZeq8qzgPvT3hARfadDI6QlzQLOouqMsw+wQNI+TZf9GPjjsgrn6ZRak27oVbXSTsBFVW9VNgU+Z/sSSScB2D4bWELVjXUlVVfWE3oUa0REa+5ob6WDgJW27wCQdAFVx5ybH3mc/e2G66+hqlHpip5kDuXDjyoOlUxhZN/AydMZV0TERFSD4Go3OmwvaVnD8aLSZjqiVSec8brvn0gXJ0DtZYN0DJFBmgaijmH7PNNlur63vpqmo37JYU3zYN8mtTrhAEg6nCpzeG7tp09QMoeIiCmYQMmhnVqdcCTtB3wSOKpMiNoVvRznEBEx2DyBrb1rgbmS5kjaHDiOqmPOIyTtAVwIvMb2DzvzIVpLySEiYtKMOjTAzfY6SacAS4FZwDm2VzR11HkX8ATgo6VDz6h56TolmUNExFR0cOI920uoemo2pjV21Hk98PqOPXAcyRwiIiars11Z+0oyh4iIqZiJU3ZHREQbw5k3JHOIiJiKDnZl7SvJHCIiJsvA+mQOERHRQDglh4iIftFumo5pnV4jmUNERIySzCEiIjZiJjLx3kBJ5hARMQVpc4iIiCaGDcNZdEjmEBExWSZtDhER0cJwFhx6s56DpN0lfVPSLZJWSHpzi2sOk3S/pBvK9q5exBoRMR7ZtbZB06uSwzrgL21fL2kb4DpJl9m+uem6q22/uAfxRUTUM4A//HX0JHOwfRdwV9l/UNItVItrN2cOERH9y4b1w1mv1PNlQiXtCfwR8N0Wp58t6UZJX5e07xj3L5S0TNKytTzUzVAjIkaz620DpqcN0pK2Br4EvMX2A02nrweeZPvXkuYDXwbmNr+H7UXAIoBtNXvw/gUiYrAN4A9/HT0rOUjajCpjOM/2hc3nbT9g+9dlfwmwmaTtpznMiIixGdjgetuA6UnJQdXK2J8CbrH9wTGueSJwt21LOogqI7t3GsOMiGjD4OFsc+hVtdIhwGuAH0i6oaS9E9gDHllQ+1jgjZLWAb8DjrOHtPwWEYNrSH+WetVb6VuA2lxzJnDm9EQUETEJZmh7K2WEdETEVKTkEBERGxvMbqp1JHOIiJgsk1lZIyKihZQcIiJilGQOERGxERuvX9/rKLoimUNExFQM4OjnOpI5RERMRaqVIiJiI84a0hER0UpKDhERsbE0SEdERLORKbuHUDKHiIipGNIpu3u+TGhExKAy4A2utdUhaZ6k2yStlHRqi/OSdEY5v1zS0zv9mUYkc4iImCyXxX7qbG1ImgWcBRwF7AMskLRP02VHUS2XPBdYCHyssx/oUckcIiKmoIMlh4OAlbbvsP0wcAFwTNM1xwCfceUaYDtJO3f2E1WGqs3hQX655hv+z580JW8PrOlFPJOQWLtjkGKFwYq3L2Od1frnsjnWJ031OQ/yy6Xf2PCFumvbbylpWcPxItuLGo53BX7WcLwKOLjpPVpdsytwV80YahuqzMH2Ds1pkpbZPrAX8UxUYu2OQYoVBivemR6r7XkdfLtWq2M2FznqXNMRqVaKiOgPq4DdG453A1ZP4pqOSOYQEdEfrgXmSpojaXPgOGBx0zWLgdeWXkvPAu633fEqJRiyaqUxLGp/Sd9IrN0xSLHCYMWbWDvE9jpJpwBLgVnAObZXSDqpnD8bWALMB1YCvwVO6FY88pDOCxIREZOXaqWIiBglmUNERIwylJmDpPdLurUML79I0nYN595Rhp7fJunIHob5CEmvkLRC0gZJBzak7ynpd5JuKNvZvYyzxNQy1nKu777bEZJOk/Tzhu9yfq9jatZu6oR+IulOST8o3+Wy9ndML0nnSLpH0k0NabMlXSbp9vL6+F7G2O+GMnMALgOeZns/4IfAOwDKUPTjgH2BecBHy5D1XrsJ+BPgqhbnfmT7gLKdNM1xtdIy1j7+bht9qOG7XNLrYBrVnDqh3xxevst+HOdwLtV/h41OBS63PRe4vBzHGIYyc7B9qe115fAaqr7AUA09v8D2Q7Z/TNXif1AvYmxk+xbbt/U6jjrGibUvv9sBUmfqhKjJ9lXAfU3JxwCfLvufBl46nTENmqHMHJr8GfD1sj/W0PN+NkfS9yVdKenQXgczjkH4bk8pVY3n9GGVwiB8f40MXCrpOkkLex1MTTuNjAkorzv2OJ6+NrDjHCR9A3hii1N/a/sr5Zq/BdYB543c1uL6aenLWyfeFu4C9rB9r6RnAF+WtK/tB7oWKJOOtWff7SMBjBM31eyVp5eYTgc+QPWHQ7/o+fc3QYfYXi1pR+AySbeWv9ZjSAxs5mD7BeOdl3Q88GLgCD86mGPahp43axfvGPc8BDxU9q+T9CPgKUBXGwAnEys9/G5H1I1b0ieAi7sczkT1/PubCNury+s9ki6iqhbr98zhbkk7276rzGR6T68D6mdDWa0kaR7wduBo279tOLUYOE7SFpLmUM2J/r1exFiHpB1GGnUlPZkq3jt6G9WY+vq7bZrW+GVUDev9pM7UCX1B0laSthnZB15E/32frSwGji/7xwNjlYKDAS45tHEmsAVVcRfgGtsnlaHoXwBupqpuOtl2z1cHl/Qy4CPADsDXJN1g+0jgecB7JK0D1gMn2W5uZJtWY8Xar99tg3+RdABVVc2dwBt6Gk2TsaZO6HFYY9kJuKj8f2tT4HO2L+ltSBuTdD5wGLC9pFXAu4H3Al+QdCLwU+AVvYuw/2X6jIiIGGUoq5UiImJqkjlERMQoyRwiImKUZA4RETFKMoeIiBglmUNERIySzGEGk/TrLrzn0SPTTUt66WRmFpV0RfN04DWuv03S0S3O7dk4bfOwKJ/rVQ3Hh0q6eRg/a/RGMofoKNuLbb+3HL6Uavrp6fBq210dUdxnU5DvCTySOdi+mmpt4YiOSOYQqPJ+STeVBVxeWdIPK3+V/6eqxZPOUxkWK2l+SfuWpDMkXVzSXyfpTEnPAY4G3l8WhNmrsUQgaXtJd5b9x0i6oMyY+nngMQ2xvUjSdyRdL+mLkrau8XmeIelGSd8BTm5In1U+57XlWW8o6ZtI+qiqRYwulrRE0rHl3J2S3iXpW8ArxoqnPPPKMkvp0qbpOprj20vSJeXaqyU9taS/RNJ3Vc3C+w1JO5X0P9ajixR9v0xd8V7g0JL21nr/0hETYDvbDN2AX5fXl1MtkDSLamqEnwI7U00/cD/VJHCbAN8BngtsSTW99Jxy//nAxWX/dcCZZf9c4NiG510BHFj2twfuLPtvo5ouAmA/quk3DizXXAVsVc69HXhXi8/xyPuW4+XAH5f99wM3lf2FwN+V/S2oJjCcAxwLLCmf8YnAL0fipppq428aYh4VD7AZ8G1gh5L+ypHPM8b3fjkwt+wfDPxX2X88j85a8HrgA2X/q1SzoAJsTTVlxWEj33nD++458lmzZZvqNqxzK8XEPBc439VcSHdLuhJ4JvAA8D3bqwAk3UD1A/Rr4A5Xi/pAlTlMZU7/5wFnANheLml5SX8WVbXUf5cCy+ZUGdSYJD0O2M72lSXps1Srq0E1Qdx+I6UC4HFUEwQ+F/ii7Q3A/0j6ZtPbfr5NPHsDT+PRubxmUU233iq+rYHnAF8s10KVUUGVCX++lDo2B0a+3/8GPijpPOBC26sa7o3oimQOAa3XEhjxUMP+eqr/Zib7y7SOR6syt2w612qSLwGX2V4wgWdojPcaOfcXtpdulCj97zbv+Zvx4pH0h8AK28+uEd8mwK9sH9Di3EeAD9peLOkw4DQA2++V9DWqNoVrJE1mSvWICUmbQ0BVVfLKUie/A9Vf8uNNt30r8GRJe5bjV45x3YPANg3HdwLPKPvHNqRfBbwaQNLTqKqWoFri9RBJf1DOPVbSU8b7ILZ/Bdwv6bkl6dUNp5cCb5S0WXm/p6iacvpbwMtL28NOVFU2rYwVz23ADpKeXdI3k7TvGPE9APxY0ivKtZK0fzn9OODnZX9kamkk7WX7B7bfR1UV9lRGf7cRHZXMIQAuoqqnvxH4L6o69v8Z62LbvwPeBFxSGmrvpmqbaHYB8NelEXUv4F+pfpy/TVV/P+JjwNalOulvKBmT7V9QtWGcX85dQ/XD2M4JwFmlQfp3DemfpJpS/HpVXT4/TlUS+hLVYjsjad9t9XnGisfVms/HAu+TdCNwA1XV0VheDZxYrl3Bo2tFn0ZV3XQ1sKbh+reo6ixwY/k8X6f691pXGt7TIB0dlym7Y1IkbW3716oqv88Cbrf9oR7FcgXwV7YnvUJew+d5AlXmdMh4GWQ/KiW5i20/rdexxOBLySEm689LA/UKquqQj/cwlvuAc9ViENwEXFw+z9XA6QOYMRxK1atpTbtrI+pIySGiSySdBRzSlPxh2//ei3giJiKZQ0REjJJqpYiIGCWZQ0REjJLMISIiRknmEBERo/x/UPd7gAEagaEAAAAASUVORK5CYII=\n",
"text/plain": [
"<Figure size 432x288 with 2 Axes>"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
}
],
"source": [
"lmask = y.notnull().all(['valid_time'])\n",
"lmask.plot()"
]
},
{
"cell_type": "code",
"execution_count": 15,
"metadata": {},
"outputs": [
{
"data": {
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"<style>/* CSS stylesheet for displaying xarray objects in jupyterlab.\n",
" *\n",
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":root {\n",
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" --xr-background-color-row-even: var(--jp-layout-color1, white);\n",
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" --xr-font-color3: rgba(255, 255, 255, 0.38);\n",
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".xr-wrap {\n",
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".xr-text-repr-fallback {\n",
" /* fallback to plain text repr when CSS is not injected (untrusted notebook) */\n",
" display: none;\n",
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".xr-header {\n",
" padding-top: 6px;\n",
" padding-bottom: 6px;\n",
" margin-bottom: 4px;\n",
" border-bottom: solid 1px var(--xr-border-color);\n",
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"\n",
".xr-header > div,\n",
".xr-header > ul {\n",
" display: inline;\n",
" margin-top: 0;\n",
" margin-bottom: 0;\n",
"}\n",
"\n",
".xr-obj-type,\n",
".xr-array-name {\n",
" margin-left: 2px;\n",
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".xr-obj-type {\n",
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".xr-sections {\n",
" padding-left: 0 !important;\n",
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" grid-template-columns: 150px auto auto 1fr 20px 20px;\n",
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"\n",
".xr-section-item {\n",
" display: contents;\n",
"}\n",
"\n",
".xr-section-item input {\n",
" display: none;\n",
"}\n",
"\n",
".xr-section-item input + label {\n",
" color: var(--xr-disabled-color);\n",
"}\n",
"\n",
".xr-section-item input:enabled + label {\n",
" cursor: pointer;\n",
" color: var(--xr-font-color2);\n",
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".xr-section-item input:enabled + label:hover {\n",
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".xr-section-summary {\n",
" grid-column: 1;\n",
" color: var(--xr-font-color2);\n",
" font-weight: 500;\n",
"}\n",
"\n",
".xr-section-summary > span {\n",
" display: inline-block;\n",
" padding-left: 0.5em;\n",
"}\n",
"\n",
".xr-section-summary-in:disabled + label {\n",
" color: var(--xr-font-color2);\n",
"}\n",
"\n",
".xr-section-summary-in + label:before {\n",
" display: inline-block;\n",
" content: '►';\n",
" font-size: 11px;\n",
" width: 15px;\n",
" text-align: center;\n",
"}\n",
"\n",
".xr-section-summary-in:disabled + label:before {\n",
" color: var(--xr-disabled-color);\n",
"}\n",
"\n",
".xr-section-summary-in:checked + label:before {\n",
" content: '▼';\n",
"}\n",
"\n",
".xr-section-summary-in:checked + label > span {\n",
" display: none;\n",
"}\n",
"\n",
".xr-section-summary,\n",
".xr-section-inline-details {\n",
" padding-top: 4px;\n",
" padding-bottom: 4px;\n",
"}\n",
"\n",
".xr-section-inline-details {\n",
" grid-column: 2 / -1;\n",
"}\n",
"\n",
".xr-section-details {\n",
" display: none;\n",
" grid-column: 1 / -1;\n",
" margin-bottom: 5px;\n",
"}\n",
"\n",
".xr-section-summary-in:checked ~ .xr-section-details {\n",
" display: contents;\n",
"}\n",
"\n",
".xr-array-wrap {\n",
" grid-column: 1 / -1;\n",
" display: grid;\n",
" grid-template-columns: 20px auto;\n",
"}\n",
"\n",
".xr-array-wrap > label {\n",
" grid-column: 1;\n",
" vertical-align: top;\n",
"}\n",
"\n",
".xr-preview {\n",
" color: var(--xr-font-color3);\n",
"}\n",
"\n",
".xr-array-preview,\n",
".xr-array-data {\n",
" padding: 0 5px !important;\n",
" grid-column: 2;\n",
"}\n",
"\n",
".xr-array-data,\n",
".xr-array-in:checked ~ .xr-array-preview {\n",
" display: none;\n",
"}\n",
"\n",
".xr-array-in:checked ~ .xr-array-data,\n",
".xr-array-preview {\n",
" display: inline-block;\n",
"}\n",
"\n",
".xr-dim-list {\n",
" display: inline-block !important;\n",
" list-style: none;\n",
" padding: 0 !important;\n",
" margin: 0;\n",
"}\n",
"\n",
".xr-dim-list li {\n",
" display: inline-block;\n",
" padding: 0;\n",
" margin: 0;\n",
"}\n",
"\n",
".xr-dim-list:before {\n",
" content: '(';\n",
"}\n",
"\n",
".xr-dim-list:after {\n",
" content: ')';\n",
"}\n",
"\n",
".xr-dim-list li:not(:last-child):after {\n",
" content: ',';\n",
" padding-right: 5px;\n",
"}\n",
"\n",
".xr-has-index {\n",
" font-weight: bold;\n",
"}\n",
"\n",
".xr-var-list,\n",
".xr-var-item {\n",
" display: contents;\n",
"}\n",
"\n",
".xr-var-item > div,\n",
".xr-var-item label,\n",
".xr-var-item > .xr-var-name span {\n",
" background-color: var(--xr-background-color-row-even);\n",
" margin-bottom: 0;\n",
"}\n",
"\n",
".xr-var-item > .xr-var-name:hover span {\n",
" padding-right: 5px;\n",
"}\n",
"\n",
".xr-var-list > li:nth-child(odd) > div,\n",
".xr-var-list > li:nth-child(odd) > label,\n",
".xr-var-list > li:nth-child(odd) > .xr-var-name span {\n",
" background-color: var(--xr-background-color-row-odd);\n",
"}\n",
"\n",
".xr-var-name {\n",
" grid-column: 1;\n",
"}\n",
"\n",
".xr-var-dims {\n",
" grid-column: 2;\n",
"}\n",
"\n",
".xr-var-dtype {\n",
" grid-column: 3;\n",
" text-align: right;\n",
" color: var(--xr-font-color2);\n",
"}\n",
"\n",
".xr-var-preview {\n",
" grid-column: 4;\n",
"}\n",
"\n",
".xr-var-name,\n",
".xr-var-dims,\n",
".xr-var-dtype,\n",
".xr-preview,\n",
".xr-attrs dt {\n",
" white-space: nowrap;\n",
" overflow: hidden;\n",
" text-overflow: ellipsis;\n",
" padding-right: 10px;\n",
"}\n",
"\n",
".xr-var-name:hover,\n",
".xr-var-dims:hover,\n",
".xr-var-dtype:hover,\n",
".xr-attrs dt:hover {\n",
" overflow: visible;\n",
" width: auto;\n",
" z-index: 1;\n",
"}\n",
"\n",
".xr-var-attrs,\n",
".xr-var-data {\n",
" display: none;\n",
" background-color: var(--xr-background-color) !important;\n",
" padding-bottom: 5px !important;\n",
"}\n",
"\n",
".xr-var-attrs-in:checked ~ .xr-var-attrs,\n",
".xr-var-data-in:checked ~ .xr-var-data {\n",
" display: block;\n",
"}\n",
"\n",
".xr-var-data > table {\n",
" float: right;\n",
"}\n",
"\n",
".xr-var-name span,\n",
".xr-var-data,\n",
".xr-attrs {\n",
" padding-left: 25px !important;\n",
"}\n",
"\n",
".xr-attrs,\n",
".xr-var-attrs,\n",
".xr-var-data {\n",
" grid-column: 1 / -1;\n",
"}\n",
"\n",
"dl.xr-attrs {\n",
" padding: 0;\n",
" margin: 0;\n",
" display: grid;\n",
" grid-template-columns: 125px auto;\n",
"}\n",
"\n",
".xr-attrs dt,\n",
".xr-attrs dd {\n",
" padding: 0;\n",
" margin: 0;\n",
" float: left;\n",
" padding-right: 10px;\n",
" width: auto;\n",
"}\n",
"\n",
".xr-attrs dt {\n",
" font-weight: normal;\n",
" grid-column: 1;\n",
"}\n",
"\n",
".xr-attrs dt:hover span {\n",
" display: inline-block;\n",
" background: var(--xr-background-color);\n",
" padding-right: 10px;\n",
"}\n",
"\n",
".xr-attrs dd {\n",
" grid-column: 2;\n",
" white-space: pre-wrap;\n",
" word-break: break-all;\n",
"}\n",
"\n",
".xr-icon-database,\n",
".xr-icon-file-text2 {\n",
" display: inline-block;\n",
" vertical-align: middle;\n",
" width: 1em;\n",
" height: 1.5em !important;\n",
" stroke-width: 0;\n",
" stroke: currentColor;\n",
" fill: currentColor;\n",
"}\n",
"</style><pre class='xr-text-repr-fallback'>&lt;xarray.DataArray &#x27;aprod&#x27; ()&gt;\n",
"array(403)</pre><div class='xr-wrap' hidden><div class='xr-header'><div class='xr-obj-type'>xarray.DataArray</div><div class='xr-array-name'>'aprod'</div></div><ul class='xr-sections'><li class='xr-section-item'><div class='xr-array-wrap'><input id='section-686dfb05-9f71-422f-b930-fcc78719f341' class='xr-array-in' type='checkbox' checked><label for='section-686dfb05-9f71-422f-b930-fcc78719f341' title='Show/hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-array-preview xr-preview'><span>403</span></div><div class='xr-array-data'><pre>array(403)</pre></div></div></li><li class='xr-section-item'><input id='section-254bc092-5427-40ee-a77b-94fa70dc0027' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-254bc092-5427-40ee-a77b-94fa70dc0027' class='xr-section-summary' title='Expand/collapse section'>Coordinates: <span>(0)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'></ul></div></li><li class='xr-section-item'><input id='section-d66e92a8-7d3a-404d-900c-b5bb3a40c8c0' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-d66e92a8-7d3a-404d-900c-b5bb3a40c8c0' class='xr-section-summary' title='Expand/collapse section'>Attributes: <span>(0)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'></dl></div></li></ul></div></div>"
],
"text/plain": [
"<xarray.DataArray 'aprod' ()>\n",
"array(403)"
]
},
"execution_count": 15,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"lmask.sum()"
]
},
{
"cell_type": "code",
"execution_count": 16,
"metadata": {},
"outputs": [],
"source": [
"def mask(ds): return ds.where(lmask)"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"# Train `ELR` with `sklearn-xarray`"
]
},
{
"cell_type": "code",
"execution_count": 17,
"metadata": {},
"outputs": [],
"source": [
"from sklearn_xarray import wrap\n",
"from sklearn.linear_model import LogisticRegression\n",
"\n",
"from sklearn_xarray import Target\n",
"from sklearn.preprocessing import LabelBinarizer, LabelEncoder\n",
"\n",
"import numpy as np"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": []
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"#### ways to improve\n",
"- have more variables as features\n",
"- member as sample"
]
},
{
"cell_type": "code",
"execution_count": 18,
"metadata": {},
"outputs": [],
"source": [
"#!pip install ipywidgets"
]
},
{
"cell_type": "code",
"execution_count": 19,
"metadata": {},
"outputs": [],
"source": [
"from tqdm import trange, tqdm_notebook"
]
},
{
"cell_type": "code",
"execution_count": 20,
"metadata": {},
"outputs": [],
"source": [
"def prepare(x,y, x2):\n",
" # category_edges\n",
" yt = y.quantile(q=[1/3,2/3], dim='valid_time')\n",
" xt = x.quantile(q=[1/3,2/3], dim='valid_time')\n",
"\n",
" # exceeding category_edges\n",
" yc=(y<=yt).astype(int)\n",
" xc=(x2<=xt).astype(int).mean('member') # cdfs \n",
"\n",
" # add category_obs: in which tercile is the observation\n",
" # workflow from https://github.com/phausamann/sklearn-xarray/issues/52\n",
" categories = np.tile(0, (x.sizes['valid_time'] ,x.sizes['longitude'], x.sizes['latitude']))\n",
"\n",
" categories = xr.concat([\n",
" xr.zeros_like(x).where((y < yt.isel(quantile=0, drop=True)).astype('int'),-1,0), # below normal\n",
" xr.zeros_like(x).where((y > yt.isel(quantile=1, drop=True)).astype('int'),1,0) # above normal\n",
" ],'category_').sum('category_')\n",
" x.coords['category_obs'] = (categories.dims, categories)\n",
" if 'quantile' in categories.coords:\n",
" del categories['quantile']\n",
"\n",
" # stack\n",
" xs=x.stack(spatial=['latitude','longitude']).rename({'valid_time':'sample'})\n",
" ys=y.stack(spatial=['latitude','longitude']).rename({'valid_time':'sample'})\n",
"\n",
" # matching #wrapper.predict_proba(X)\n",
" fill = xr.zeros_like(x.stack(spatial=['latitude','longitude']).isel(spatial=0,drop=True).expand_dims('feature').isel(feature=[0]*3)).rename({'valid_time':'sample'})\n",
" \n",
" return xs, ys, xc, yc, fill"
]
},
{
"cell_type": "code",
"execution_count": 21,
"metadata": {},
"outputs": [
{
"name": "stderr",
"output_type": "stream",
"text": [
"/opt/conda/lib/python3.7/site-packages/numpy/lib/nanfunctions.py:1390: RuntimeWarning: All-NaN slice encountered\n",
" overwrite_input, interpolation)\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"CPU times: user 219 ms, sys: 23.8 ms, total: 243 ms\n",
"Wall time: 239 ms\n"
]
}
],
"source": [
"%time xs, ys, xc, yc, fill = prepare(x,y, x2)"
]
},
{
"cell_type": "code",
"execution_count": 22,
"metadata": {},
"outputs": [],
"source": [
"def wrapper_fit_predict_proba_loop(xs, ys):\n",
" \n",
" elr_dict = {}\n",
" proba = []\n",
" for si in trange(xs.spatial.size, leave=True, position=0):\n",
"\n",
" X = xs.isel(spatial=si, drop=True)\n",
" Y = ys.isel(spatial=si, drop=True)\n",
"\n",
" # masking land\n",
" if Y.isnull().all():\n",
" proba.append(fill)\n",
" continue\n",
"\n",
" X = X.expand_dims('feature',axis=-1)\n",
"\n",
" Y = Target(coord=\"category_obs\", transform_func=LabelEncoder().fit_transform)(X)\n",
"\n",
" wrapper = wrap(LogisticRegression(fit_intercept=False))\n",
" wrapper.fit(X, Y)\n",
"\n",
" proba.append(wrapper.predict_proba(X))\n",
" # save wrapper for later use\n",
" elr_dict[si] = wrapper\n",
"\n",
" proba = xr.concat(proba,'spatial', compat='override', coords='minimal')\n",
" return elr_dict, proba"
]
},
{
"cell_type": "code",
"execution_count": 23,
"metadata": {},
"outputs": [
{
"name": "stderr",
"output_type": "stream",
"text": [
"100%|██████████| 620/620 [00:03<00:00, 204.36it/s]\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"CPU times: user 3.39 s, sys: 44.1 ms, total: 3.43 s\n",
"Wall time: 3.4 s\n"
]
}
],
"source": [
"%time elr_dict, proba = wrapper_fit_predict_proba_loop(xs, ys)"
]
},
{
"cell_type": "code",
"execution_count": 24,
"metadata": {},
"outputs": [],
"source": [
"def post(proba, xs):\n",
" # unstack\n",
" proba = proba.drop('category_obs').assign_coords(spatial=xs.coords['spatial'].sel(spatial=xs.spatial)).unstack('spatial')\n",
"\n",
" # rename back\n",
" proba = proba.rename({'feature':'category','sample':'valid_time'}).assign_coords(category=['below','normal','above'])\n",
"\n",
" # mask sea\n",
" proba = mask(proba)\n",
" return proba"
]
},
{
"cell_type": "code",
"execution_count": 25,
"metadata": {},
"outputs": [],
"source": [
"proba = post(proba, xs)"
]
},
{
"cell_type": "code",
"execution_count": 26,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"<xarray.plot.facetgrid.FacetGrid at 0x7fbe443e0b90>"
]
},
"execution_count": 26,
"metadata": {},
"output_type": "execute_result"
},
{
"data": {
"image/png": 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\n",
"text/plain": [
"<Figure size 936x648 with 13 Axes>"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
}
],
"source": [
"# show results\n",
"proba.isel(valid_time=[1,50,100,-1]).plot(row='category', col='valid_time', robust=True)"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": []
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"# predict out of sample"
]
},
{
"cell_type": "code",
"execution_count": 27,
"metadata": {},
"outputs": [
{
"name": "stderr",
"output_type": "stream",
"text": [
"/opt/conda/lib/python3.7/site-packages/numpy/lib/nanfunctions.py:1390: RuntimeWarning: All-NaN slice encountered\n",
" overwrite_input, interpolation)\n"
]
}
],
"source": [
"xfs, yfs, xfc, yfc, fill = prepare(xf,yf, xf2)"
]
},
{
"cell_type": "code",
"execution_count": 28,
"metadata": {},
"outputs": [],
"source": [
"def wrapper_predict_proba_loop(xfs, yfs, fill, elr_dict):\n",
" proba_outsample = []\n",
" for si in trange(xfs.spatial.size, leave=True, position=0):\n",
"\n",
" X = xfs.isel(spatial=si, drop=True)\n",
" Y = yfs.isel(spatial=si, drop=True)\n",
"\n",
" # masking land\n",
" if Y.isnull().all():\n",
" proba_outsample.append(fill)\n",
" continue\n",
"\n",
" X = X.expand_dims('feature',axis=-1)\n",
"\n",
" wrapper = elr_dict[si]\n",
"\n",
" proba_outsample.append(wrapper.predict_proba(X))\n",
" proba_outsample = xr.concat(proba_outsample,'spatial', compat='override', coords='minimal')\n",
" return proba_outsample"
]
},
{
"cell_type": "code",
"execution_count": 29,
"metadata": {},
"outputs": [
{
"name": "stderr",
"output_type": "stream",
"text": [
"100%|██████████| 620/620 [00:00<00:00, 713.87it/s]\n"
]
}
],
"source": [
"proba_outsample = wrapper_predict_proba_loop(xfs, yfs, fill, elr_dict)"
]
},
{
"cell_type": "code",
"execution_count": 30,
"metadata": {},
"outputs": [],
"source": [
"proba_outsample = post(proba_outsample, xfs)"
]
},
{
"cell_type": "code",
"execution_count": 31,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"<xarray.plot.facetgrid.FacetGrid at 0x7fbe45aacc10>"
]
},
"execution_count": 31,
"metadata": {},
"output_type": "execute_result"
},
{
"data": {
"image/png": 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\n",
"text/plain": [
"<Figure size 720x648 with 10 Axes>"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
}
],
"source": [
"proba_outsample.isel(valid_time=[2,20,40]).plot(col='category', robust=True, row='valid_time')"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"# Scoring"
]
},
{
"cell_type": "code",
"execution_count": 32,
"metadata": {},
"outputs": [],
"source": [
"xfc = mask(xfc).rename({'quantile':'category_edge'}).assign_coords(category_edge=['below','normal'])\n",
"yfc = mask(yfc).rename({'quantile':'category_edge'}).assign_coords(category_edge=['below','normal'])"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"# RPS climatology"
]
},
{
"cell_type": "code",
"execution_count": 33,
"metadata": {},
"outputs": [],
"source": [
"def rps_clim(yc, **kwargs):\n",
" \"\"\"RPS for climatology forecast\"\"\"\n",
" clim = xr.concat([xr.ones_like(yc.isel(category_edge=0))*.33,\n",
" xr.ones_like(yc.isel(category_edge=1))*.66,\n",
" ]\n",
" ,'category_edge')\n",
" rps_clim = rps(yc, clim, **kwargs)\n",
" return rps_clim"
]
},
{
"cell_type": "code",
"execution_count": 56,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"<matplotlib.collections.QuadMesh at 0x7fbe44307b50>"
]
},
"execution_count": 56,
"metadata": {},
"output_type": "execute_result"
},
{
"data": {
"image/png": 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\n",
"text/plain": [
"<Figure size 432x288 with 2 Axes>"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
}
],
"source": [
"rps_outofsample_clim = mask(rps_clim(yfc, category_edges=None, dim=['valid_time']))\n",
"\n",
"rps_outofsample_clim.plot(robust=True)"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## RPS elr"
]
},
{
"cell_type": "code",
"execution_count": 35,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"<xarray.plot.facetgrid.FacetGrid at 0x7fbe3fe7f110>"
]
},
"execution_count": 35,
"metadata": {},
"output_type": "execute_result"
},
{
"data": {
"image/png": 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\n",
"text/plain": [
"<Figure size 504x216 with 3 Axes>"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
}
],
"source": [
"proba_outsample_cum = proba_outsample.cumsum('category',skipna=False).drop_sel(category='above').rename({'category':'category_edge'})\n",
"t=2\n",
"proba_outsample_cum.isel(valid_time=t).plot(col='category_edge')"
]
},
{
"cell_type": "code",
"execution_count": 36,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"<xarray.plot.facetgrid.FacetGrid at 0x7fbe3e49c710>"
]
},
"execution_count": 36,
"metadata": {},
"output_type": "execute_result"
},
{
"data": {
"image/png": 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\n",
"text/plain": [
"<Figure size 504x216 with 3 Axes>"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
}
],
"source": [
"yfc.isel(valid_time=t).plot(col='category_edge')"
]
},
{
"cell_type": "code",
"execution_count": 37,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"<matplotlib.collections.QuadMesh at 0x7fbe3e33d0d0>"
]
},
"execution_count": 37,
"metadata": {},
"output_type": "execute_result"
},
{
"data": {
"image/png": 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\n",
"text/plain": [
"<Figure size 432x288 with 2 Axes>"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
}
],
"source": [
"rps_outofsample = rps(yfc, proba_outsample_cum,category_edges=None, dim=['valid_time'])\n",
"\n",
"rps_outofsample.plot(robust=True)"
]
},
{
"cell_type": "code",
"execution_count": 38,
"metadata": {},
"outputs": [],
"source": [
"# special color coding from @awr\n",
"levels=[-100,-10, -5, -1.25, 1.25, 2.5, 5, 7.5, 10, 12.5, 15, 17.5, 20, 100]\n",
"colors = [(0.11, 0.57, 1.0),(0.11, 0.57, 1.0),(0.0,1.0,1.0),(0.75, 0.75, 0.75),\n",
" (1.0, 1.0, 0.0),(1.0, 0.84, 0.0),(1.0, 0.65, 0.0),\n",
" (1.0, 0.55, 0.0),(1.0, 0.39, 0.28),(1.0, 0.27, 0.0),\n",
" (1.0, 0.0, 0.0),(1.0, 0.0, 1.0), (1.0, 0.0, 1.0)]\n",
"cticks=[-5,0,5,10,15,20]"
]
},
{
"cell_type": "code",
"execution_count": 39,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"Text(0.5, 1.0, 'ELR Forecast RPSS (%) GEFS Week 3-4 Precip JJA, 2017-2020 [out-sample]')"
]
},
"execution_count": 39,
"metadata": {},
"output_type": "execute_result"
},
{
"data": {
"image/png": 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\n",
"text/plain": [
"<Figure size 432x288 with 2 Axes>"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
}
],
"source": [
"# (1 - rps_lr / rps_clim)*100 in percent: positive means lr better than climatology\n",
"(100*(1 - rps_outofsample / rps_outofsample_clim)).plot.contourf(levels=levels, colors=colors, cbar_kwargs={'ticks':cticks}, extend='neither')\n",
"plt.title(f\"ELR Forecast RPSS (%) GEFS Week 3-4 Precip JJA, {yf.coords['valid_time'].min().dt.year.values}-{yf.coords['valid_time'].max().dt.year.values} [out-sample]\")"
]
},
{
"cell_type": "code",
"execution_count": 40,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"<matplotlib.collections.QuadMesh at 0x7fbe3e28ee90>"
]
},
"execution_count": 40,
"metadata": {},
"output_type": "execute_result"
},
{
"data": {
"image/png": 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\n",
"text/plain": [
"<Figure size 432x288 with 2 Axes>"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
}
],
"source": [
"(100*(1 - rps_outofsample / rps_outofsample_clim)).plot()"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## rps counting\n",
"counting means raw forecasts"
]
},
{
"cell_type": "code",
"execution_count": 43,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"<xarray.plot.facetgrid.FacetGrid at 0x7fbe3e0bb310>"
]
},
"execution_count": 43,
"metadata": {},
"output_type": "execute_result"
},
{
"data": {
"image/png": 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\n",
"text/plain": [
"<Figure size 504x216 with 3 Axes>"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
}
],
"source": [
"xfc.isel(valid_time=t).plot(col='category_edge', robust=True)"
]
},
{
"cell_type": "code",
"execution_count": 44,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"<xarray.plot.facetgrid.FacetGrid at 0x7fbe3de38710>"
]
},
"execution_count": 44,
"metadata": {},
"output_type": "execute_result"
},
{
"data": {
"image/png": 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\n",
"text/plain": [
"<Figure size 504x216 with 3 Axes>"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
}
],
"source": [
"yfc.isel(valid_time=t).plot(col='category_edge')"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"rps_counting = rps(yfc, xfc.mean('M'), category_edges=None, dim='valid_time')\n",
"\n",
"rps_counting.plot()"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## RPSS: elr vs counting"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"rpss = 1 - rps_outofsample / rps_counting # lr much better than counting\n",
"\n",
"rpss.plot()"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"(rpss*100).plot.contourf(levels=levels, colors=colors, cbar_kwargs={'ticks':cticks}, extend='neither')\n",
"plt.title(f\"ELR Forecast RPSS (%) GEFS Week 3-4 Precip JJA, {yf.coords['valid_time'].min().dt.year.values}-{yf.coords['valid_time'].max().dt.year.values} [out-sample]\")"
]
},
{
"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": "3.7.6"
},
"toc-autonumbering": true
},
"nbformat": 4,
"nbformat_minor": 4
}
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