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@fmaussion
Created September 4, 2019 15:09
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{
"cells": [
{
"cell_type": "code",
"execution_count": 3,
"metadata": {},
"outputs": [],
"source": [
"import numpy as np\n",
"import xarray as xr\n",
"import pandas as pd\n",
"import matplotlib.pyplot as plt\n",
"import progressbar\n",
"from scipy import stats"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Test thick file "
]
},
{
"cell_type": "code",
"execution_count": 7,
"metadata": {},
"outputs": [
{
"data": {
"image/png": 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\n",
"text/plain": [
"<Figure size 432x288 with 2 Axes>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"f = '/home/mowglie/disk/TMP_Data/GLOBAL_ITMIX/composite/RGI60-01/RGI60-01.00001_thickness.tif'\n",
"da = xr.open_rasterio(f)\n",
"da.plot();"
]
},
{
"cell_type": "code",
"execution_count": 8,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"<xarray.DataArray ()>\n",
"array(7638770.751953)"
]
},
"execution_count": 8,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"da.sum() * da.attrs['res'][0]**2"
]
},
{
"cell_type": "code",
"execution_count": 10,
"metadata": {},
"outputs": [
{
"data": {
"image/png": 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m3BsRK3tVkLQ38BngLRHxkKQLgHfT3OnvBv4ceNMuDPkpDLfRN2YWg2TwTZ/oo5BbMzhL0gSNwb84Ii4FiIjvd5z/a+Dz5endwPKOlx9WyuhRPif+FzHGmHkwD/dOVySJZl/wzRHx/o7ygzuq/Vvg5vJ4HXCKpKWSjgBWANcA1wIrJB0haZJG7F3Xq2/P9I0xJknF1TvHA6cCN0naUMreBrxO0nNLV98B/n+AiNgo6RIagXYHcGZETAFIOgu4HBgH1kTExl4d2+gbY8w8qLR656vM7Zi6rMdrzgfOn6P8sl6vm81QG/2QmFrWsgduy+eT2ds2E0mbuQ9qCbCpaMhaaZP7KMbVEzQrtVODWsJzNZG7j/dgrc9hgD7PCLFjyIWjoTb6xjyFATIQZvfEWTaNMWZE8CYqxhgzYtjoG2PMiOBNVBYbwXRLlGu0iLCpdMcJpibrpF/up+DZ13ZqpQbOCJFtgmYl4Tmzt20/20ntwTxoEbkV7sF+2+C2NfiDznAbfWNm4y1yzQISATu8iYoxxowOdu8YY8yIYJ++McaMGGGj3x1J+wIfA36Bxtv6JuBW4FPA4TS5JU6OiAdKAqIPAq8CHgFOj4gbenYwptbUyG1ZUFP7uyau0lQmbXI/BbIEGWE51U6t1Le1ROw++fVTonslITdDbj/jOnVSn1WimdSevS0N9TtAdtiF3IW+XB8EvhARPw/8MrAZOAe4MiJWAFeW5wCvpMkctwI4A7hggcdmdkcs5JoFJKLx6WeOQWXBjL6kpwP/hiZ9KBHxRET8kGYrr4tKtYuAV5fHJwGfiIargH1npRk1xphFRkxNj6WOQWUhR3YE8APg45K+IeljkvYCDir7QwJ8DzioPE5t+yXpjJntx7Y//qMFHL4xxjyVCKWOQWUhjf4S4HnABRFxNPBjnnTlABARwTx/kEfE6ohYGRErJ5buXW2wxhjTxkzunWF27yykkLsV2BoRM5v9fprG6H9f0sERsa24b+4p53ttBzYnIdixrCUit0WszGx3mUtlnKlTJ0VzNaGtWpRsotIApdkduP/HWp9DLSF80Nqp0E81ovHrDzMLNtOPiO8Bd0n6uVJ0As2uL+uA00rZacDnyuN1wBvUcBzwYIcbyBhjBoIa2yUuJgu9Tv93gYvL3o23A2+k+aK5RNKbgTuBk0vdy2iWa26hWbL5xgUemzHGzIsoQu4ws6BGPyI2ACvnOHXCHHUDOHMhx2OMMbtKDfeOpOXAJ2gWsgSwOiI+2HH+rcD7gGdExL294pgknQa8o7z0jyLiInrgiFxjjJkHlVbm7ADeGhE3SNoHuF7S+ojYVL4QXgF8t6N+ZxzTsTRxTMdK2h84j2ZyHaWddRHxQLeOh9rox1h7SuPplneYSnfcx0jHTPRvtQjYBH0VB2ulIR6kX9+ZWeGgpUTOXL8+jrlKP5WIqGP0i165rTx+WNJmmiXqm4APAH/Ak3ondMQxAVdJmoljegmwPiLuB5C0HlgFfLJb30Nt9I2ZzUAZfLNbMo/lmAdKuq7j+eqIWD27kqTDgaOBqyWdBNwdEd9sPDo/oVscUyq+qRMbfWOMmQfz8OnfGxFzaZo/QdLewGeAt9C4fN5G49pZMDwvMsaYJIGYnh5LHW1ImqAx+BdHxKXAz9JkMvimpO/QxCrdIOn/o3sc07zjm2z0jTFmHkTy6EVZjXMhsDki3g8QETdFxDMj4vCIOJzGVfO8EvPULY7pcuAVkvaTtB/Nr4TLe/U99O6dXRVq217ftJGoU0vIzYhxlcaToUbqW+hzut6WvjSdaKOf4mCtqVc/BeHEfZH5sPoazV2DSkIucDxwKnCTpA2l7G0RcVmX+nPGMUXE/ZLeDVxb6r1rRtTtxtAbfWM6sZBrFpwK6/Qj4qu0fJ2V2f7M465xTBGxBliT7dtG3xhj5sEgZ9DMYKNvjDFJApiettE3xpjRIBjANK3zY6iNfgiml7SkVm55hxkhNyMkpQThWiJtRkRLUMv/nco/VUtYrhC1Oz1RZywp324fI6NrCbmpBQfjlfIL14jI7bOOM+yplYfa6Bszm1qbjBvTlSG/x2z0jTEmzWBvhZjBRt8YY+aDZ/rGGDMiBIRX7ywiYzC1tHeVVoE1IQJlRNpa4mA1kbGS+JyJXk21U2l2NL2kvSFNtbz5lKBeoZ9sO5kI4UppuVNRsn0UaVN9tRnZWuNNY6NvzMCQMcTG7BJ27xhjzAhho2+MMSOCg7OMMWa0cHDWItMmXtWIyM1EwKYE2D6mTR60qMrUgodU1GnvMQfRt5lYTLQrsH2dFKaibROfeSbiO6PMVxqPWm6eavdxFq/eMWaAGPKf3mbwGfaobxt9Y4zJktkWa8Cx0TfGmDQa+l+T3mfIGGPmQ4VNciUtl/RlSZskbZR0dil/t6QbJW2QdIWkQ0q5JH1I0pZy/nkdbZ0m6bZynNY2/KGe6ccYTE22VGr5Us4IsLXE1WpibyIqtdqetBnhL0Gt9Lft/tRoH3M/J2qZy1dLOE2Quy8S4mpGPM2kwU4Mpy1kWf2OkE1EUCfYAbw1Im6QtA9wvaT1wJ9FxDsBJP0e8N+B/wi8ElhRjmOBC4BjJe0PnAespLnbrpe0LiIe6NaxZ/pmt6LWl5QxczKzTj9z9GomYltE3FAePwxsBg6NiIc6qu3Fk9OGk4BPRMNVwL6SDgZOBNZHxP3F0K8HVvXqe6hn+sYY029qr96RdDhwNHB1eX4+8AbgQeClpdqhwF0dL9tayrqVd8UzfWOMmQ95n/6Bkq7rOM6Y3ZSkvYHPAG+ZmeVHxNsjYjlwMXBW7eG3Gn1Jvytpv53tQNK4pG9I+nx5foSkq4sg8SlJk6V8aXm+pZw/fGf7NMaYAeDeiFjZcazuPClpgsbgXxwRl87x+ouBf1ce3w0s7zh3WCnrVt6VjHvnIOBaSTcAa4DLI+YViHw2jb/qaeX5nwIfiIi1kj4KvJlGlHgz8EBE/AtJp5R6r21rvDUit0XjyaSjTYm0mfTLk5WiGBMiWi3BjoRoXGXjWiql2c20UymiMiNmRkL0S4mila7x2JJEFHHi+qTaSYxZFUTjfue3r+HekSTgQmBzRLy/o3xFRNxWnp4E3FIerwPOkrSWRsh9MCK2Sboc+OOOifkrgHN79d1qGiLiHTSK8YXA6cBtkv5Y0s8m3thhwK8CH+t4oy8DPl2qXAS8uuMNXlQefxo4odQ3Jk3fQ/LNaBE0k4bM0ZvjgVOBl5XlmRskvQp4j6SbJd1IY8DPLvUvA24HtgB/DfwngIi4H3g3cG053lXKupISciMiJH0P+B7NUqP9gE9LWh8Rf9DjpX8B/AGwT3l+APDDiNhRnneKDj8RJCJih6QHS/17M2M0xpi+UGFeERFfZe7f9Zd1qR/AmV3OraHxwqTI+PTPlnQ98F7gn4FfjIjfAZ7Pk/6muV73a8A9EXF9djAZJJ0xI4zseOTHNZs2xphWFLljUMnM9PcHfiMi7uwsjIjpYti7cTzw6+UnyzIan/4HadaXLimz/U7RYUaQ2CppCfB04L7ZjRYxZDXAHgcvH+BLa4zZLRlyq9Nq9CPivB7nNvc4dy5FUJD0EuD3I+L1kv4WeA2wFjgN+Fx5ybry/Ovl/JfaBONI7JHbJmhmxNWUkJtpJyOKZsTBzD6xGTUkFVVZ5w5PCXaZdhLBV20CYmYsGdTPBc8ZkTaTpjhTp9JnlSHV16BNmwdsOPNlMdbp/zfgv0jaQuOzv7CUXwgcUMr/C3DOIozNDDmZFSPG7CxZ186gfU910peI3Ij4CvCV8vh24Jg56jwG/GY/xmOMMTuNN1ExxpjRYZBn8RmG2+irPXPldCYjZUuWw1RWy5RPvz2gJROokwmMyTCW0RgSaKx9PBl/83QmKCgVyNRepc0pnfEjZ1xJY5l2WmvAeOIaZ3SczHhq+dAzn/lQMuRva7iNfgUyaZPNEFHB4BvTlQH312cYeaNvjDHzwkbfGGNGh5Y9XQYep1Y2xpgRYqhn+iGYWtryW6tF+JvO+PQzQm5GpJ3on5CbEeMyomgt4a+WOJgRT5eM92cq1s/3XUukHU9MU2ulOcyMpxbT/YzPsHvHmMGhXwbfDA79NvgWco0xZpSw0TfGmBHCRt8YY0YDMfyrd4bb6AtiomUrtZbzZKIGE0Lu+NIdrXUyWRknJhPtJJyKGd/2xJKp1joZf+nkeHs7GVFvKhGRm3lfU9O9L/REYrzVolIzgnpi6pgS5vs45lrtZO6vWnWqYJ++MYNFm8E3ux99FXJh6N07/g8xxpj5EMmjB5KWS/qypE2SNko6u5T/maRbJN0o6bOS9u14zbmStki6VdKJHeWrStkWSa0p6W30jTFmHlTKp78DeGtEHAUcB5wp6ShgPfALEfFLwLd4ciOqo4BTgOcAq4C/lDQuaRz4CPBK4CjgdaVuV+zeMcaY+VBnY/RtwLby+GFJm4FDI+KKjmpX0ewiCHASsDYiHgfuKJtNzexLsqXsU4KktaXupm59D7fRHw9inxbhs8XdNz7ZLuqNJwTPTBrZyYl2kTbTzh4T21vrZFLxZpgYa3/vtYTcDBn/7ZKW5RVLKl2bDLWE8AwZQTjDdCINads1htx7fyIVEt9OrXZaiXmt3jlQ0nUdz1eXPb5/CkmHA0cDV8869SbgU+XxoTRfAjNsLWUAd80qP7bXoIbb6Bszi4wxMrsXfTP4M+S/W++NiJW9KkjaG/gM8JaIeKij/O00LqCLd3KUXbHRN8aYeVBryaakCRqDf3FEXNpRfjrwa8AJETHT293A8o6XH1bK6FE+JxZyjTFmPtRZvSPgQmBzRLy/o3wV8AfAr0fEIx0vWQecImmppCOAFcA1wLXACklHSJqkEXvX9erbM31jjMmSMOhJjgdOBW6StKGUvQ34ELAUWN98L3BVRPzHiNgo6RIagXYHcGZETAFIOgu4HBgH1kTExl4dD7fRVzDWIsSOtURwTkzUic5cloikzQh2SxJ1lo4nBOHEmCcTIm1G9Mz0lfG114sE3XW/fq1I2gxLEp/DdLT/KK/xvrNkxpNhScIf39bXsvEdffPrizrunYj4KnMvM7msx2vOB86fo/yyXq+bzXAbfWNm0U/DZwaDfgu5TsNgjDGjhI2+McaMEDb6xhgzIjjL5uIyNhYsXdY7OrUtfXAmAjYTlbrX5BOtdTJRsssqibQZAXbPJe1jzjA51j7mjPCXuc5LtOvRq7VE0YmUOJ2JXK0kiqYE4fYo2cz99fh0u+nI9LV0rP29Pzo10fP85NgOdlS6hils9I0xZvHoq8HHm6gYY8xIYfeOMcaMCvWCsxYNG31jjJkPNvpzI2k58AngIJrLtDoiPihpf5p0oYcD3wFOjogHSi6KDwKvAh4BTo+IG3r1MT42zf57P9KrSit7Tz7eWicTuZoRv/aeaO8rw17j7QJsRtTLsOd4exrnqYRgt+dY+5hr7am6tEVYHq8kwGbYnhA8JxJC+HjC0kwlUiJnROOpRJ1M+uVMOxlBeMnY0p7n24TemtSKyF1MFlIB6bYzzDnAlRGxAriyPIdm55cV5TgDuGABx2Z2U9oMvjG7iqYjdQwqC2b0I2LbzEw9Ih4GNtMk/T8JuKhUuwh4dXl8EvCJaLgK2FfSwQs1PmOMmTfZDJuDa/P7k1p51s4wB5WtwgC+R+P+geYLYfYOMIcyC0lnSLpO0nXbH3x0wcZsjDFzUWmP3EVjwY1+t51hAMoGAfO6PBGxOiJWRsTKiafvUXGkxhiTYMhn+gu6eqfLzjDfl3RwRGwr7pt7SnmvnWHmZHwseNrSx3qOoS3CNSPSZiJOM+mOM9GkeySE04zfepxERGlGoE7cvbWEyIx4ukwJYbllLpO5NrWYSKTKbhsv5ATsDNujzr/8Y4l2Hp9uF1gz4n3m3ukngzyLz7BgM/1uO8PQ7OpyWnl8GvC5jvI3qOE44MEON5AxKTIG1JhdwjP9rnTbGeY9wCWS3gzcCZxczl1Gs1xzC82SzTcu4NiMMWb+hNMwdKXHzjAAJ8xRP4AzF2o8xhizq3idvjHGjBoRuaMHkpZL+rKkTZI2Sjq7lP9meT4taeWs15wraYukWyWd2FG+qpRtkXTO7L5mM9RpGMYJ9m5JDzzZIrBmolszwmnaJBk1AAAQjElEQVQmAjbTzkRC7N1zvD2yN9NOhoxwmiG1Z6/qBFa1vfdMpGiun/bxZoTTlDidGPP2aN82cNlYe18/nu4dAQswQeL+SlzmxxJi7x4t/6OZqN6aVJrpzwSv3iBpH+B6SeuBm4HfAP7qp/psAltPAZ4DHAJ8UdKR5fRHgJfTLHO/VtK6iNjUreOhNvrGzKbWl50xc1JJpC2LVLaVxw9L2gwcGhHrAZp1MD/FScDaiHgcuEPSFuCYcm5LRNxeXre21LXRN8aYGsxDyD1Q0nUdz1dHxOqntPfTwavdOBS4quN5Z/Dq7KDWY3sNykbfGGPmwTyM/r0RsbJXhV7BqwuFjb4xxmQJWkXaLF2CV7vRK3h1XkGtQ230x8emefpk7/w7e7QIV3staRdFMxGceyYE4VzEaSL6NyHGpSJyK/m/M4LmZKKvWumM+xlx206ddNoZQTgTmJYRe/caax9zRoDNkBGWH5ma7Hm+VhrxLDWE3B7Bq91YB/yNpPfTCLkrgGtoVpGukHQEjbE/BfitXg0NtdE3ZjaDZfDNbkmdiX634NWlwP8AngH8g6QNEXFiRGyUdAmNQLsDODMipgAknQVcDowDayJiY6+ObfSNMSZJreCsluDVz3Z5zfnA+XOUX0aT0SCFjb4xxmSJwd4gJYONvjHGzIfhtvnDbfSXaIqDJnuvctp7Se/Uy5m9W1NCbqKdDBkRLSOcjid+g2bayUSCZiJKM/vSZqixV2yt/WYzpCJpSUTS0n6NM+LqeKV/+SfU3s54YpVLJnV3WzR3v1MvD3vunaE2+sbMppaxNmZOArB7xxhjRojhtvk2+sYYMx/s3jHGmBHCq3cWkXFNtwq1+4z1Pp+JSs1EDe6ZEGAzUakpkTYhLGcEspQAO9beVy0hLeOPHyQhN7XfbEbATly+jNg7aGSu4XTqMx+ggLsB3woxw1AbfWNmYyHXLCRNcNZwW30bfWOMmQ8D9MNjZ7DRN8aYeeCZvjHGjAr26S8u40yz//iPe9dpEdIykbTL1F4nJQgnhNN6Yu+uRzoCTGb2Qq1EZjzbWyJc6yT8BRIpiMcTn+dj0T6izBXOiJmZKOypjG8iYdSmo452kllwkEkH3T+ce8cYY0YLu3eMMWZEiHltlziQ2OgbY8x88EzfGGNGiOG2+cNt9Mc1zT7jvSNu2wSwfcZ777ELMJGQ2jKpg/dJRO1m2CshIE6kRNF2MW7ZgP2W3V5hkXStyN8nElGyE7SL7hkey0T/JphOpHrOkBHdaxnHVF99RNOD9T8xX+rcAcYYMwoETXBW5uiBpOWSvixpk6SNks4u5ftLWi/ptvJ3v1IuSR+StEXSjZKe19HWaaX+bZJOa3sLNvrGGJNEBIrc0cIO4K0RcRRwHHCmpKOAc4ArI2IFcGV5DvBKYEU5zgAugOZLAjgPOBY4Bjhv5ouiGzb6xhgzHyJyR88mYltE3FAePwxsBg4FTgIuKtUuAl5dHp8EfCIargL2lXQwcCKwPiLuj4gHgPXAql59D5TRl7RK0q3lJ8w57a8wxpg+kzf6B0q6ruM4Y67mJB0OHA1cDRwUEdvKqe8BB5XHhwJ3dbxsaynrVt6VgRFyJY0DHwFeTjPwayWti4hN3V4zzjT7tkTktomwT2tJvZxlz0T65cmECJkRYCcSwZDjmWyTKYGs0l6xmXTGieFkrk+rUJtYctf+aQ4eUwlhfioxz0vt65uIks2IxpnUym3Rv2P9XGww49PPcW9ErOxVQdLewGeAt0TEQ9KT7zUiQqqvYg/STP8YYEtE3B4RTwBraX7SGJPGqZXNQqPp6dTR2o40QWPwL46IS0vx94vbhvL3nlJ+N7C84+WHlbJu5V0ZJKM/758pxhjTX5KunZZfk2qm9BcCmyPi/R2n1gEzK3BOAz7XUf6GsornOODB4ga6HHiFpP2KgPuKUtaVgXHvZCl+sTMAnnFItfRaxhjTTlArIvd44FTgJkkbStnbgPcAl0h6M3AncHI5dxnwKmAL8AjwRoCIuF/Su4FrS713RcT9vToeJKOf+pkSEauB1QArfnGPwYraMMbs/lSQECLiq3QXzE6Yo34AZ3Zpaw2wJtv3IBn9a4EVko6gMfanAL/V6wVjitZ0xe3n2yMmMxGBe6VSIrdWSQmwE0oIdonZyHiinQyZvlKCcOI6t2W1HSda/foZv38tbSAjij5RKXVwTqSts29thr4KrH3Em6hUIiJ2SDqLxh81DqyJiI2LPCwzZFjINQuOjX49IuIyGt+VMcYMHhEwNdy/YAbK6BtjzMDjmb4xxowQNvqLh8gIub2F2omE2JRJL5wRaSdSIm2d0IlMO2OJ8aRSGWfc6JXE3rbI3jGC7RX8+pnUyv3bPTgn0mb20e0ntdI4DxRB+2qCAWeojb4xs6lh8I3pTkAM1pfrfLHRN8aYLIGFXGOMGSns0188xonWrQP3HGv3vC5LBAUta/GRL01snZcJhhpL+G4zvvjpWnvVJZpJ9ZXQRaYr/DNNJHz6Ewoea/E3Z9b7b09lkazj185lvmz/d86MJ9NXhlQQXIW+lo7t4PHpPpoyG/3hpobBN4NDxqffZvDNcNFXgz+TcG2IGXmjb4wxaQIY8o3RbfSNMWY+eKZvjDGjgtMwLCpjtAu1e7W4eJeqXYCdSIhfE4l2MgLseC39ILGWuJbYm9sKsU5fbe9qnGB7SybJtu33IBcMVYvtiUUAtQThWtQKvBqvkIlz6dgOHp2arDCaBAHhdfrGDA5tBt/sfvTN4M/giFxjjBkhhtynP1i/GY0xZpCJaFbvZI4WJK2RdI+kmzvKflnS1yXdJOnvJT2t49y5krZIulXSiR3lq0rZFknntPVro2+MMfOhwsbohf8JrJpV9jHgnIj4ReCzwH8FkHQUzW6Czymv+UtJ45LGgY8ArwSOAl5X6nZlqN07UrQGV7WJp8sSAmyGnJBb5zt2OpFNMSMIT0f/8kRmpK+UINzyeY6pjl8/I/Zm6OdOXhnxeayPmThTmUorCMJ7jD/RxwCtIKbq/N9ExD9JOnxW8ZHAP5XH62l2EnwncBKwNiIeB+6QtAU4ptTbEhG3A0haW+pu6tavZ/pmt8JC7ujR3xQMNEJu5oADJV3XcZyR6GEjjdEG+E1geXl8KHBXR72tpaxbeVeGeqZvjDF9J79k896IWDnP1t8EfEjSO4F1wBPzfH0rNvrGGJMkgFjAJZsRcQvwCgBJRwK/Wk7dzZOzfoDDShk9yufE7h1jjMkSZROVzLETSHpm+TsGvAP4aDm1DjhF0lJJRwArgGuAa4EVko6QNEkj9q7r1Ydn+ma3YkLtEbnG7Aq1hFxJnwReQuP73wqcB+wt6cxS5VLg4wARsVHSJTQC7Q7gzIhmJYaks2gE33FgTURs7NlvDHGggaQfAHcuUvcHAvcuUt9z4fF0Z5DGAh5PGws1np+JiGfsSgOSvkAzvgz3RsTsJZmLzlAb/cVE0nU7IdIsGB5PdwZpLODxtDFo49ndsE/fGGNGCBt9Y4wZIWz0d57Viz2AWXg83RmksYDH08agjWe3wj59Y4wZITzTN8aYEcJG3xhjRomIGLkD+A5wE7ABuK6U7U+T1e628ne/Uv504O+Bb9IkQ3rjrLaeRpPk6MMdZc8v7W8BPsSTbrRufVQZDzBV2tgArOsoPwK4uoznU8BkKV9anm8p5w+vPJ5nAVcAm2mCSg6f73hqjAV4acd12QA8Brx6ka/Ne0vZZn76Hlmse+dPgZvL8do+3Tv70aQPvpEmuvQXOvpdBdxa2j9nZ8fjYw77t9gDWJQ33dyYB84qe+/MzQWcA/xpefy2jsfPAO6fudFK2QeBv+Gnjf41wHGAgH8EXtnSR5XxAD/q8n4vAU4pjz8K/E55/J+Aj5bHpwCfqjyerwAvL4/3Bvac73hqflalfP9SPu+x1Lo2wL8C/pkmgnIc+DrwksW6d2jyu6ynidDfiya0/2l9uD5/BpxXHv88cGV5PA58G3h2Gd83gaN2Zjw+5rAHiz2ARXnTc9+YtwIHl8cHA7eWx+cCf1n+CY+gmUmMlXPPB9YCp1OMfnntLR3tvg74q5Y+ao3nKUa/1LsXWFKevxC4vDy+HHhhebyk1FON8dBs6PDVCuOpcm06XnsGcPEiX5sXAtcDewB7AtcB/5JFundoNup4Z8frLwRO7sP1+QfgRR31vg0c1NlPx7jP3ZnxLLatGcRjVH36AVwh6fqOHNcHRcS28vh7NDcfwIdp/iH/L83P1rMjYrokRPpz4PdntX0ojbtnhs781t362OXxlHPLSt7uqyS9upQdAPwwInbMMZ6f5OIu5x8s9WuM50jgh5IulfQNSX9WdvmZ73hU6drMcArwycW8NhHxdeDLwLZyXB4Rm1m8e+ebwCpJe0o6kMYdtrwP1+ebwG8ASDoG+BmaLJHdcsTvzHjMLEY14dq/joi7S0a79ZJu6TwZESH9ZEuuE2n8ky8DfrbU/z/AG4DLImKrNP8EX7P62OXxRMRDNLlF7pb0bOBLkm6iufnnS43rswR4EXA08F0aV83pwOfmOZZfjYibK1wbJB0M/CLNrHBnqXFtnkljfA8r9dZLehHwaGYAC3DvXCHpBcDXgB/QuJt2NqvYfMbzHuCDkjbQfAl9Yxf6NUlGcqYfEXeXv/fQCEnHAN8vRmHGONxTqr8RuDQatgB30PgfXwicJek7wPuAN0h6D00u68M6uuvMbz1nH5XG09nO7TT+9KOB+4B9Jc18wXeO5yc5usv5pwP3VRrPVmBDRNxeZl5/BzxvJ8azsca1KZwMfDYitpfni3Vt/i1wVUT8KCJ+ROO7fyGLe++cHxHPjYiX0/y6+tZCX5+IeCgi3hgRz6WZRD0DuJ3uuePnPR7MUxg5oy9pL0n7zDym2bDgZpoc1KeVaqfx5Iz0u8AJpf5BwM8Bt0fE6yPiWRFxOI2L5xMRcU75GfuQpOPU/AR4Q0dbT+mj1ngk7SdpaSk/EDge2BQRQeNKeM0cbXX28RrgS8CeNcZDIwbuK2kmq+HLdmI8/5tGAN7VsczwOp507bCI1+a7wIslLZE0AbwY2LyI9864pANK+S8BvwRcsdDXR9K+anLAA/x74J/Kr7I5c8TPdzylvplNDICw0M+DZkXAN3ly2drbS/kBwJU0y8q+COxfyg+hWXZ4E80N/NtztHk6P716Z2Wp+20aP6q69VFrPDQrQm4q7dwEvHnWe76GRrj7W2BpKV9Wnm8p559d8/oAL6dZjncT8D95clVPdjwvrjiWw2lmg7OF3b5fG5rVKX/Fk0tZ37/I986yMo5NwFXAc/t0fV5I84viVprc8ft19Puqcu7bM+3MdzyLbWsG9XAaBmOMGSFGzr1jjDGjjI2+McaMEDb6xhgzQtjoG2PMCGGjb4wxI4SNvjHGjBA2+sYYM0LY6JvdAkkvkHSjpGUlUnWjpF9Y7HEZM2g4OMvsNkj6I5rIzD2ArRHxJ4s8JGMGDht9s9tQ8rRcS7Mz1r+KCGdsNGYWdu+Y3YkDaBK07UMz4zfGzMIzfbPbIGkdzU5mR9Ds1HTWIg/JmIFjVDdRMbsZkt4AbI+Iv1GzQ9fXJL0sIr602GMzZpDwTN8YY0YI+/SNMWaEsNE3xpgRwkbfGGNGCBt9Y4wZIWz0jTFmhLDRN8aYEcJG3xhjRoj/ByRVLIBF+UwNAAAAAElFTkSuQmCC\n",
"text/plain": [
"<Figure size 432x288 with 2 Axes>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"f = '/home/mowglie/disk/TMP_Data/GLOBAL_ITMIX/surface_DEMs_RGI60/surface_DEMs_RGI60-01/surface_DEM_RGI60-01.00001.tif'\n",
"de = xr.open_rasterio(f)\n",
"de.plot();"
]
},
{
"cell_type": "code",
"execution_count": 11,
"metadata": {},
"outputs": [
{
"data": {
"image/png": 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\n",
"text/plain": [
"<Figure size 432x288 with 2 Axes>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"bed = de - da.data\n",
"bed.plot();"
]
},
{
"cell_type": "code",
"execution_count": 14,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"<xarray.DataArray ()>\n",
"array(0.)"
]
},
"execution_count": 14,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"bed.where((da.data > 0) & (bed.data < 0)).sum() * da.attrs['res'][0]**2"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## OK, go"
]
},
{
"cell_type": "code",
"execution_count": 15,
"metadata": {},
"outputs": [],
"source": [
"odf = pd.read_hdf('rgi62_era5_df.h5', 'df')"
]
},
{
"cell_type": "code",
"execution_count": 22,
"metadata": {},
"outputs": [
{
"name": "stderr",
"output_type": "stream",
"text": [
" 99% (216489 of 216502) |############### | Elapsed Time: 0:20:01 ETA: 0:00:00"
]
}
],
"source": [
"vol = np.full(len(odf), np.NaN)\n",
"vol_bsl = np.full(len(odf), np.NaN)\n",
"for i, (rid, reg) in enumerate(zip(odf.index, progressbar.progressbar(odf.O1Region))):\n",
" fpath_c = '/home/mowglie/disk/TMP_Data/GLOBAL_ITMIX/composite/RGI60-{}/{}_thickness.tif'.format(reg, rid)\n",
" fpath_d = '/home/mowglie/disk/TMP_Data/GLOBAL_ITMIX/surface_DEMs_RGI60/surface_DEMs_RGI60-{}/surface_DEM_{}.tif'.format(reg, rid)\n",
" try:\n",
" with xr.open_rasterio(fpath_c) as da:\n",
" vol[i] = da.sum() * da.attrs['res'][0]**2\n",
" with xr.open_rasterio(fpath_d) as de:\n",
" bed = de - da.data\n",
" vol_bsl[i] = bed.where((da.data > 0) & (bed.data < 0)).sum() * da.attrs['res'][0]**2\n",
" except:\n",
" pass"
]
},
{
"cell_type": "code",
"execution_count": 23,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"array([7.63877075e+06, 1.69764600e+07, 5.96934619e+07, ...,\n",
" 2.50689258e+08, 1.06820602e+05, 1.48931555e+07])"
]
},
"execution_count": 23,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"vol"
]
},
{
"cell_type": "code",
"execution_count": 24,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"array([ 0. , 0. , 0. , ...,\n",
" -359846.64916992, 0. , 0. ])"
]
},
"execution_count": 24,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"vol_bsl"
]
},
{
"cell_type": "code",
"execution_count": 25,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"973\n",
"982\n"
]
}
],
"source": [
"print(np.sum(~np.isfinite(vol)))\n",
"vol[vol == 0] = np.NaN\n",
"print(np.sum(~np.isfinite(vol)))\n",
"odf['vol_itmix_m3'] = vol"
]
},
{
"cell_type": "code",
"execution_count": 27,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"55402\n",
"0\n"
]
}
],
"source": [
"print(np.sum(~np.isfinite(vol_bsl)))\n",
"vol_bsl[~np.isfinite(vol_bsl)] = 0\n",
"print(np.sum(~np.isfinite(vol_bsl)))\n",
"odf['vol_bsl_itmix_m3'] = np.abs(vol_bsl)"
]
},
{
"cell_type": "code",
"execution_count": 28,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"0.15193551737212563"
]
},
"execution_count": 28,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"odf['vol_bsl_itmix_m3'].sum() / odf['vol_itmix_m3'].sum()"
]
},
{
"cell_type": "code",
"execution_count": 29,
"metadata": {},
"outputs": [
{
"name": "stderr",
"output_type": "stream",
"text": [
"/home/mowglie/.pyvirtualenvs/py3/lib/python3.5/site-packages/pandas/core/generic.py:2377: PerformanceWarning: \n",
"your performance may suffer as PyTables will pickle object types that it cannot\n",
"map directly to c-types [inferred_type->mixed,key->block3_values] [items->['GLIMSId', 'BgnDate', 'EndDate', 'O1Region', 'O2Region', 'Name', 'check_geom', 'GlacierType', 'TerminusType', 'GlacierStatus', 'unique_id']]\n",
"\n",
" return pytables.to_hdf(path_or_buf, key, self, **kwargs)\n"
]
}
],
"source": [
"odf.to_hdf('rgi62_era5_itmix_nocorr_df.h5', key='df', mode='w')"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Correct for no vol data "
]
},
{
"cell_type": "code",
"execution_count": 31,
"metadata": {},
"outputs": [],
"source": [
"dfs = odf[['Area', 'vol_itmix_m3']].copy().dropna()\n",
"dfs['vol_itmix_m3'] = dfs['vol_itmix_m3'] * 1e-9"
]
},
{
"cell_type": "code",
"execution_count": 32,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"linfit in log 1.3241016673237342 0.03583913841744416\n"
]
}
],
"source": [
"# Fit in log space \n",
"dfl = np.log(dfs).dropna()\n",
"slope, intercept, r_value, p_value, std_err = stats.linregress(dfl.Area.values, dfl.vol_itmix_m3.values)\n",
"print('linfit in log', slope, np.exp(intercept))"
]
},
{
"cell_type": "code",
"execution_count": 33,
"metadata": {},
"outputs": [],
"source": [
"vol_vas = np.exp(intercept) * (odf['Area'] ** slope)"
]
},
{
"cell_type": "code",
"execution_count": 39,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"(163146.47164254752, 158156.59837634105, 134126.99377621617)"
]
},
"execution_count": 39,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"vol_vas.sum(), dfs['vol_itmix_m3'].sum(), dfs['vol_itmix_m3'].sum() - (odf['vol_bsl_itmix_m3'].sum() * 1e-9)"
]
},
{
"cell_type": "code",
"execution_count": 40,
"metadata": {},
"outputs": [],
"source": [
"odf.loc[odf.vol_itmix_m3.isna(), 'vol_itmix_m3'] = vol_vas.loc[odf.vol_itmix_m3.isna()]"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Store "
]
},
{
"cell_type": "code",
"execution_count": 47,
"metadata": {},
"outputs": [
{
"name": "stderr",
"output_type": "stream",
"text": [
"/home/mowglie/.pyvirtualenvs/py3/lib/python3.5/site-packages/pandas/core/generic.py:2377: PerformanceWarning: \n",
"your performance may suffer as PyTables will pickle object types that it cannot\n",
"map directly to c-types [inferred_type->mixed,key->block3_values] [items->['GLIMSId', 'BgnDate', 'EndDate', 'O1Region', 'O2Region', 'Name', 'check_geom', 'GlacierType', 'TerminusType', 'GlacierStatus', 'unique_id']]\n",
"\n",
" return pytables.to_hdf(path_or_buf, key, self, **kwargs)\n"
]
}
],
"source": [
"odf.to_hdf('rgi62_era5_itmix_df.h5', key='df', mode='w')"
]
},
{
"cell_type": "code",
"execution_count": 48,
"metadata": {},
"outputs": [],
"source": [
"odf.to_csv('rgi62_era5_itmix_df.csv')"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"### Some checks "
]
},
{
"cell_type": "code",
"execution_count": 41,
"metadata": {},
"outputs": [],
"source": [
"dfs = odf[['Area', 'vol_itmix_m3']].copy().dropna()\n",
"dfs['vol_itmix_m3'] = dfs['vol_itmix_m3'] * 1e-9"
]
},
{
"cell_type": "code",
"execution_count": 42,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"(163146.47164254752, 158156.5983895423, 134126.99378941744)"
]
},
"execution_count": 42,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"vol_vas.sum(), dfs['vol_itmix_m3'].sum(), dfs['vol_itmix_m3'].sum() - (odf['vol_bsl_itmix_m3'].sum() * 1e-9)"
]
},
{
"cell_type": "code",
"execution_count": 43,
"metadata": {},
"outputs": [],
"source": [
"from matplotlib.colors import LogNorm\n",
"from mpl_toolkits.axes_grid1 import make_axes_locatable\n",
"from matplotlib.colorbar import ColorbarBase\n",
"from salem.graphics import ExtendedNorm\n",
"import copy"
]
},
{
"cell_type": "code",
"execution_count": 44,
"metadata": {},
"outputs": [],
"source": [
"xvas = np.array([0.01, 1, 10, 100, 1000, 10000])\n",
"vas = 0.034*(xvas**1.375)\n",
"fit = np.exp(intercept) * (xvas ** slope)"
]
},
{
"cell_type": "code",
"execution_count": 45,
"metadata": {},
"outputs": [],
"source": [
"xlim, ylim = [1e-2, 1e4], [1e-5, 1e4]\n",
"xlim_exp, ylim_exp = [-2, 4], [-5, 4]"
]
},
{
"cell_type": "code",
"execution_count": 46,
"metadata": {},
"outputs": [
{
"data": {
"image/png": 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\n",
"text/plain": [
"<Figure size 504x360 with 2 Axes>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"# Cmap norm\n",
"norm = ExtendedNorm([1, 10, 100, 200, 500, 1000], ncolors=256, extend='max')\n",
"cm = copy.deepcopy(plt.get_cmap('viridis'))\n",
"cm.set_under('white')\n",
"\n",
"# Figure and plot\n",
"f, ax = plt.subplots(1, 1, figsize=(7, 5))\n",
"\n",
"dfl.plot.hexbin(ax=ax, x=\"Area\", y=\"vol_itmix_m3\", norm=norm, cmap=cm, \n",
" colorbar=False, gridsize=70, linewidths=0.1);\n",
"\n",
"# Fit\n",
"ax.plot(np.log(xvas), np.log(vas), '--', color='C1', label='VAS (Bahr et al.)', linewidth=1)\n",
"ax.plot(np.log(xvas), np.log(fit), '--', color='C3', label='VAS (ITMIX)', linewidth=1)\n",
"\n",
"# Manipulate axes\n",
"ax.set_xlim(np.log(xlim))\n",
"ax.set_ylim(np.log(ylim))\n",
"\n",
"xt = [10.**e for e in np.arange(xlim_exp[0], xlim_exp[1]+1)]\n",
"xl = [\"10$^{\"+\"{:d}\".format(int(x))+\"}$\" for x in np.arange(xlim_exp[0], xlim_exp[1]+1)]\n",
"ax.set_xticks(np.log(xt))\n",
"ax.set_xticklabels(xl)\n",
"\n",
"yt = [10.**e for e in np.arange(ylim_exp[0], ylim_exp[1]+1)]\n",
"yl = [\"10$^{\"+\"{:d}\".format(int(x))+\"}$\" for x in np.arange(ylim_exp[0], ylim_exp[1]+1)]\n",
"ax.set_yticks(np.log(yt))\n",
"ax.set_yticklabels(yl)\n",
"\n",
"# Legend\n",
"plt.legend();\n",
"\n",
"ax.set_xlabel('Area (km$^{2}$)')\n",
"ax.set_ylabel('Volume (km$^{3}$)')\n",
"\n",
"# Colorbar\n",
"cax = make_axes_locatable(ax).append_axes('right', size='5%', pad=0.5)\n",
"ColorbarBase(cax, extend='max', orientation='vertical', cmap=cm, norm=norm, label='N Glaciers');"
]
},
{
"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": "3.5.2"
}
},
"nbformat": 4,
"nbformat_minor": 4
}
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