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nsh-envsnsh-envs
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syncronizing work before syncing with PowerHouse
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-1161
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‎.ipynb_checkpoints/carbontracker_height_projection-checkpoint.ipynb

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{
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"cells": [
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{
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"cell_type": "code",
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"execution_count": 1,
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"id": "596e621e-bba2-45fa-b2e9-71a6bf2942fa",
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"metadata": {},
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"outputs": [],
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"source": [
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"import numpy as np\n",
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"import matplotlib.pyplot as plt"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 2,
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"id": "27ee8bd5-8655-4ccf-b894-942e22dbaa77",
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"metadata": {},
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"outputs": [],
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"source": [
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"ct_mean_height = np.array([33,109,255,477,814,1273,1835,2556,3315,4205,5026,5603,6186,6771,7355,8086,\n",
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" 8816,9400,10131,11011,11749,12492,13393,14304,15226,16322,17446,18459,20380,\n",
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" 24376,29834,35623,42602,123210])\n",
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"upper_bound = np.array([23.08374,53.95842,92.69418,139.3762,194.109,272.8005,352.0846,472.145,634.403,\n",
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" 799.2552,1009.179,1223.671,1667.5,2132.778,2621.598,3136.516,3680.622,4257.58,\n",
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" 4871.828,5528.92,6235.908,7001.659,7837.523,8758.652,9786.779,10955.83,12322.15,\n",
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" 13988.12,16262.5])\n",
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"lower_bound = np.array([0.0,23.22038,54.24406,93.13342,139.964,194.8293,273.6455,352.986,473.0139,635.087,\n",
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" 800.0614,1011.88,1230.12,1685.043,2164.47,2670.521,3205.939,3773.771,4377.638,\n",
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" 5021.379,5709.135,6447.051,7244.244,8112.182,9066.722,10130.23,11337.5,12741.79,\n",
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" 14435.87])"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 29,
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"id": "6cfcebae-d1ff-4c3e-a4bb-27d0c9cc7aeb",
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"metadata": {},
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"outputs": [
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{
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"data": {
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"text/plain": [
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"(26, 29)"
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]
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},
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"execution_count": 29,
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"metadata": {},
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"output_type": "execute_result"
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}
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],
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"source": []
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},
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{
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"cell_type": "code",
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"execution_count": 33,
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"id": "60abf1d2-c060-4ffa-9a23-e30fa44d2c24",
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"metadata": {},
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"outputs": [
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{
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"[ 33 109 255 477 814 1273 1835 2556 3315 4205 5026 5603\n",
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" 6186 6771 7355 8086 8816 9400 10131 11011 11749 12492 13393 14304\n",
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" 15226 16322]\n",
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"[ 11.54187 15.36902 19.22506 23.12139 27.0725 38.9856 39.21955\n",
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" 59.5795 80.69455 82.0841 104.5588 105.8955 218.69 223.8675\n",
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" 228.564 232.9975 237.3415 241.9045 247.095 253.7705 263.3865\n",
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" 277.304 296.6395 323.235 360.0285 412.8 492.325 623.165\n",
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" 913.315 ]\n"
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]
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}
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],
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"source": [
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"print(ct_mean_height[:26])\n",
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"print(dehm_mean_height)"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 34,
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"id": "c73c788e-a0f9-4bae-963c-d09b8ecf32da",
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"metadata": {},
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"outputs": [
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{
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"data": {
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"text/plain": [
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"<matplotlib.image.AxesImage at 0x7f60bcbfcbe0>"
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]
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},
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"execution_count": 34,
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"metadata": {},
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"output_type": "execute_result"
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},
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{
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"data": {
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"image/png": "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",
98+
"text/plain": [
99+
"<Figure size 640x480 with 1 Axes>"
100+
]
101+
},
102+
"metadata": {},
103+
"output_type": "display_data"
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}
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],
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"source": [
107+
"nz = 29\n",
108+
"nzp = 26\n",
109+
"projection = np.zeros((nz,nzp))\n",
110+
"dehm_mean_height = (upper_bound + lower_bound)/2\n",
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"\n",
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"hdiff = abs(dehm_mean_height.reshape(-1,1) - ct_mean_height[:nzp])\n",
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"for i in range(nz):\n",
114+
" j = np.argmin(hdiff[i,:])\n",
115+
" projection[i,j] = 1\n",
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"\n",
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"plt.imshow(projection)"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 10,
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"id": "d277bc6a-3968-4e32-ae9e-85e597a7dacf",
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"metadata": {},
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"outputs": [
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{
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"0.3333333333333333\n"
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]
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}
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],
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"source": [
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"up=3\n",
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"down=0\n",
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"d = 1\n",
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"L = (up-down)\n",
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"v = np.zeros(3)\n",
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"f = (d-down)/L\n",
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"print(f)"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
147+
"id": "b75c5487-794e-453f-8edd-54f721161148",
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"metadata": {},
149+
"outputs": [],
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"source": []
151+
}
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],
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"metadata": {
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"kernelspec": {
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"display_name": "Python 3 (ipykernel)",
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"language": "python",
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"name": "python3"
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},
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"language_info": {
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"codemirror_mode": {
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"name": "ipython",
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"version": 3
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},
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"file_extension": ".py",
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"mimetype": "text/x-python",
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"name": "python",
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"nbconvert_exporter": "python",
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"pygments_lexer": "ipython3",
169+
"version": "3.10.12"
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}
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},
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"nbformat": 4,
173+
"nbformat_minor": 5
174+
}

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