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@kwilcox
Created June 22, 2017 19:34
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{
"cells": [
{
"cell_type": "markdown",
"metadata": {},
"source": [
"# Try creating profile with pocean core"
]
},
{
"cell_type": "code",
"execution_count": 1,
"metadata": {
"collapsed": true
},
"outputs": [],
"source": [
"%matplotlib inline\n",
"import os\n",
"import ctd\n",
"import pytz\n",
"import datetime\n",
"\n",
"from pocean.dsg.profile.im import IncompleteMultidimensionalProfile"
]
},
{
"cell_type": "code",
"execution_count": 2,
"metadata": {
"collapsed": true
},
"outputs": [],
"source": [
"fname='dCTD001.cnv'"
]
},
{
"cell_type": "code",
"execution_count": 3,
"metadata": {
"collapsed": true
},
"outputs": [],
"source": [
"#kw = dict(compression='gzip')\n",
"#cast = ctd.DataFrame.from_cnv(fname, **kw)\n",
"cast = ctd.DataFrame.from_cnv(fname)"
]
},
{
"cell_type": "code",
"execution_count": 4,
"metadata": {},
"outputs": [
{
"data": {
"image/png": 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atIsPymoAOHdCccjJRDpGhS5d3h1/X85jJZvJyjQmDurFZ04YyiePHci0Ebo6VFKLCl26\ntOaWCKUVtfTIzmThv5/34Z2IRFKRxtCly2pqifD5++ezYGM1t80crzKXlKdCly5r6659zFu3kynD\nenPNySPCjiNyxFTo0iXVNTZzxe/nkZ2ZwRfPOCrsOCKdQmPo0iW9u76KHXsauO+aaZw7UWezSHpQ\noUuX0hJx5q+v4j+fXU5edianji4MO5JIp1GhS5cQiTg/e2kVTywoo2JPA33zsnnguhPonq0DoZI+\nVOiS9qr2NvLTF1fx5/mbmDG+PxdPGcw54/uTp4m3JM3of7SkpbUVtbxVWskbayp5c00l9c0tXHfK\nCG7/1ETdfUjSlgpd0sr2mnrueHYZz32wHYAhfbpzyfGD+cKpIxjdv2fI6UTiS4UuKc3deXV1BXNX\nlDNv7U7WVuylW4bx9XPHcMmUwQzvlxd2RJGEUaFLytpeU88tjy7i3fVV5GVncsLIvnx62lBmTCj+\ncMZEka5EhS4p67XVO3h3fRXfnTmeL5w2Uvf+lC5PPwGSsvoX5AJwzJBeKnMRVOiSoiIRZ+uufQA8\n/t7mkNOIJAcNuUjKqalr4muPLuK11RWMKsrjMycMCzuSSFJQoUvK+eXLq3mrtJI7Zh3NZ08cTmaG\nzisXARW6pJDNVXW8trqCx97bzMxjBmrKW5EDHLLQzewbMXyMve5+TyflEQFgd30Ty7fuZumWGpZv\n3c3CTdVs2FkHwFFFeXx35viQE4okn/b20G8Ffgcc6m/amwAVuhyx5pYIzy/dzn1vrOP94EbNAMUF\nORwzuDfXnTKC08cWcVRhni7fF2lDe4X+sLvfcagVzEyX4slhiUScko3VvLNuJ+9tqGLhxmr2NrZw\nVGEe3zp/LJMG9+LoQb0o6pkTdlSRlHDIQnf3b5tZBnC5uz9+sHXikkzS1s7aBmbP28hfFpSxZdc+\nzGBccU8umzqEM8cWcfa4/mToQKdIh7V7UNTdI2b2FaDNQhfpiGeXbOV7T33AnoZmThtdyHdmjufM\nMUX06pEVdjSRlBfrWS5zzOxbwGPA3v0L3b0qLqkkbf34uZUM6t2dX181hTHFmv1QpDPFWuhfCN7e\n3GqZA7q7rnRIdV0jF04aoDIXiYOYCt3dR8Y7iKS/5pYIdY0t5OtOQSJxEfNPlplNAiYCufuXuftD\n8Qgl6WnXviYA+uZlh5xEJD3FVOhmdjtwFtFCfw6YCbwJqNAlJvVNLXznySUA9MtXoYvEQ6yzLV4O\nzAC2u/v1wHGATg6WmD1Rspm5K3dw6wXjuGjSwLDjiKSlWAt9n7tHgGYzKwB20M4BUTN7wMx2mNnS\nVst+YGZbzGxx8Lio1fu+a2alZrbKzC44nC9GktcHW2oo6pnDzWeP1jnmInES6xh6iZn1Bv4ALABq\ngfntbPMg8Bs+PizzS3f/WesFZjYRuBI4GhgEvGxmY929JcZ8kuR272umIFcHQ0XiKdazXL4cPP29\nmb0AFLj7kna2ed3MRsSYYxbwqLs3AOvNrBSYDsyLcXtJYu7O4s27mDq8T9hRRNJazHcsMrNLzewX\nwFeBUUfwOb9iZkuCIZn9P+GDgda3nSkLlkkaeHVVBdt313P6mMKwo4iktZgK3cz+m+isih8AS4Ev\nmtlvD+Pz/Y7oL4PJwDbg5/s/RRvr+kGy3GhmJWZWUlFRcRgRJJGWbqnha39exNjifC45Xr+jReIp\n1kHNM4FJ7u4AZjabaLl3iLuX739uZn8Ang1elgFDW606BNh6kI9xL3AvwLRp09osfUke//H0Urpn\nZ/Lg9dPJ6ZYZdhyRtBbrkMsqoPWNG4cChxxDb4uZtT5f7RKie/sAzwBXmlmOmY0ExtD+QVdJYpGI\n88i7m1i4aRc3nnEUg3p3DzuSSNpr745Ffyc69NELWGFm84PXJwJvt7Ptn4lejFRoZmXA7cBZZjY5\n+BgbgC8CuPsyM3scWA40AzfrDJfU9v2nl/LIu5s4YUQfrpg6tP0NROSItTfk8rN23n9Q7n5VG4vv\nP8T6PwJ+dLifT5LDjt31/Pj5lfx10Ra+cOpIvv+JCTrvXCRB2rvBxWuJCiKprbklwg//sYJH5m/C\n3fnaOaP56owxKnORBGpvyGUPBznbBMDdCzo9kaSkR9/bzINvb+DSKYP52owxjCjUnQlFEq29PfSe\nAGZ2B7AdeJjoKYafBTShdRfn7izcVM19b6zn+aXbmTiwgDsvO5bsbjFf3iAinSjW0xYvcPcTW73+\nnZm9C/wkDpkkBbg733z8fZ5atIWeud342jmj+fLZo1XmIiGKtdBbzOyzwKNEh2CuAnQWShf2+ppK\nnlq0hS+ecRRfmzGGPN20QiR0se5OXQ18GigPHlcEy6SLWrChCjP4qspcJGnEOjnXBqITaInQ0NzC\nkwvKmD6ir24nJ5JEDrmHbmY3tvcBYllH0ssLS7eztaaeL511JHO0iUhna2/36jYzqzzE+w24hWBu\nFUl/kYgz++0NDO3bnTPGFIUdR0Raaa/QXwM+1c46czopiyQ5d+eH/1jBwk27+Mllx+qiIZEk0955\n6NcnKogkt7LqOr71xPu8s66K604ZwRXThoQdSUQOoCNaEpNbn1jC0i27ufPSY/jMCUMx0965SLLR\nVSDSru019cxbt5MvnTWKK6cPU5mLJCkVurRrbUUtAMcP0z1BRZJZrLegKzaz+83s+eD1RDO7Ib7R\nJFmU7ogW+rB+PUJOIiKHEuse+oPAi8Cg4PVq4OvxCCTJZ9nWGgrzsxnUKzfsKCJyCLEWeqG7Pw5E\nANy9Gc3l0mXUNbZQ0D1LY+ciSS7WQt9rZv0I5kY3s5OAmrilkqTSEnG66ZxzkaQX62mL3yB6I+dR\nZvYWUARcHrdUklQamyN0y9Dxc5Fk126hm1kGkAucCYwjern/KndvinM2SQJ1jc3MX1/FjAn9w44i\nIu1ot9DdPWJmP3f3k4FlCcgkSWTO8nL2NDRz9YnDw44iIu2I9e/ol8zsMtNRsS6lobmFvyzcQmaG\nMX6g7jgokuw6MoaeBzSbWT3RYRfXTaLT29/f38brqyu4Y9bRFORmhR1HRNoR6w0utHvWBb2+uoLC\n/Bw+p+EWkZQQU6Gb2RltLXf31zs3jiST7bvrOaowT9PkiqSIWIdcbm31PBeYDiwAzun0RJI09jW2\n0C8/O+wYIhKjWIdcPnKTCzMbCvwkLokkKTS3RNhcXcekwTpMIpIqDvdqkTJgUmcGkeTyjw+2sauu\niTPH6vxzkVQR6xj6rwku+yf6S2Ay8H68Qkn4nv9gO4N7d+e8icVhRxGRGMU6hl7S6nkz8Gd3fysO\neSQJNLdEKNlYzdThvcnUAVGRlBHrGPrs/c/NrA8wNG6JJHQrt++hsraBCycNCDuKiHRArDe4eNXM\nCsysL9Ghlj+a2S/iG03C8vbaSgCmj+wXchIR6YhYD4r2cvfdwKXAH919KnBu/GJJmArzcwCoqm0M\nOYmIdESshd7NzAYCnwaejWMeSQKry2vJzsxgTHF+2FFEpANiLfQ7iN6CrtTd3zOzo4A1h9rAzIaa\n2StmtsLMlpnZLcHyvmY2x8zWBG/7BMvNzH5lZqVmtsTMjj+SL0wOj7uzcGM1ffKyyM3KDDuOiHRA\nTIXu7k+4+7Hu/uXg9Tp3v6ydzZqBb7r7BOAk4GYzmwjcBsx19zHA3OA1wExgTPC4Efhdh78aOWJ3\nPLuc+RuqOGNMUdhRRKSDYj0o+pPgoGiWmc01s0oz+9yhtnH3be6+MHi+B1gBDAZmAfvPmpkNXBw8\nnwU85FHvAL2DYR5JkJq6Jv7nnY1cPnUId112bNhxRKSDYh1yOT84KPpJoleJjuWj87sckpmNAKYA\n7wLF7r4NoqUP7L8UcTCwudVmZcEySZBlW2toanFmTR6kCblEUlCshb5/MuyLiF5UVBXrJzCzfOAv\nwNeDXwoHXbWNZf6xlcxuNLMSMyupqKiINYbEYMX2PQBMGKj5W0RSUayF/nczWwlMA+aaWRFQ395G\nZpZFtMz/5O5PBYvL9w+lBG93BMvL+OgFS0OArQd+THe/192nufu0oiKN83amFdt2U5if8+FpiyKS\nWmI9KHobcDIwLbg5dB3RMe+DCm5Xdz+wwt1bX4T0DHBt8Pxa4OlWy68JznY5CajZPzQjibFy+24m\n6FZzIikr1oOiPYCb+deZJ4OI7q0fyqnA54FzzGxx8LgIuBM4z8zWAOcFrwGeA9YBpcAfgC935AuR\nI1dV20hxQW7YMUTkMMU6Odcfid7Q4pTgdRnwBIe4yMjd36TtcXGAGW2s70R/aUhImiNOVqYOhoqk\nqljH0Ee5+0+AJgB338fBy1pSkLuzr7GF7MzDnSJfRMIW609vo5l1JzjrxMxGAQ1xSyUJV1nbyJ6G\nZkYU5oUdRUQOU6xDLrcDLwBDzexPRMfHr4tXKEm8jTv3AqjQRVJYu4UenK2ykuhMiycRHWq5xd0r\n45xNEmj77uhZqMU9dVBUJFW1W+ju7mb2t2DK3H8kIJOEYPGmXZjB8H49wo4iIocp1jH0d8zshLgm\nkdC8vrqCh+Zt5FPHDiIvJ9ZROBFJNrH+9J4N3GRmG4C9RIdd3N01g1OKW7CxmhsfLmFU/3z+c9ak\nsOOIyBGItdBnxjWFhGb22xvIy+7GwzdMp1ePrPY3EJGkdchCN7Nc4CZgNPABcL+7NycimCRGZW0D\nRT01f4tIOmhvDH020Uv8PyC6l/7zuCeShPmfdzby9tqdnDFWk5yJpIP2hlwmuvsxAGZ2PzA//pEk\nEV5ZuYP/eHop54zvz7cvGBd2HBHpBO0VetP+J+7eHD0lXVJZfVML//XyGv7wxjomDCzg11dNoZsu\n9xdJC+0V+nFmtv+mFAZ0D17vP8tFd0JIIWvK93DjwwtYX7mXT08bwv++aKJOUxRJI4f8aXZ33fY9\nTUQizq1PLqFmXxP/c8OJnDamMOxIItLJ9Ld2F/H0+1tYvHkX37togspcJE2p0LuAmrom7nx+JccO\n6cWlU3TfbZF0pUJPc4s37+KKe95mZ20jP7x4EhkZOrAtkq50RCwN7alv4qVl5TwyfxMLNlZTmJ/D\nA9edwLFDeocdTUTiSIWeRnbWNvCDvy/nxWXbaWyOMLxfD/79kxO5YtoQCnJ1Wb9IulOhp4nSHbV8\n4cH3KN9dz9XTh/Gp4wZx/LDe6NoBka5DhZ4GqvY2cvnv36ZbRgaP3ngSU4b1CTuSiIRAhZ4Gnl2y\nlV11TTz3tdOZOEjXeol0VTrLJQ3sqY9OgBlxDzmJiIRJhZ7i3J031lQA0ZtViEjXpUJPcdt31/PO\nuipmTR7E508aHnYcEQmRCj3FbdxZB8DMSQN00ZBIF6dCT3F/encTvXtkcepozc8i0tWp0FPcvsZm\ninvm0lMXDol0eSr0FFfX2EJdUzPNLZGwo4hIyFToKe7T04ayuWofizfvCjuKiIRMhZ7ipg6PXhW6\ntqI25CQiEjYVeorrl58NwM69jSEnEZGwqdBTXPesTLIyjZp9Te2vLCJpLW6FbmZDzewVM1thZsvM\n7JZg+Q/MbIuZLQ4eF7Xa5rtmVmpmq8zsgnhlSyfrK/fS1OIM6d097CgiErJ4Ts7VDHzT3ReaWU9g\ngZnNCd73S3f/WeuVzWwicCVwNDAIeNnMxrp7Sxwzprxn3t+KGZw3cUDYUUQkZHHbQ3f3be6+MHi+\nB1gBHOqGlrOAR929wd3XA6XA9HjlSxcrtu1mVFE+A3rlhh1FREKWkDF0MxsBTAHeDRZ9xcyWmNkD\nZrZ/8u7BwOZWm5Vx6F8AAvTpkU1lbUPYMUQkCcS90M0sH/gL8HV33w38DhgFTAa2AT/fv2obm39s\nPlgzu9HMSsyspKKiIk6pU0dlbQN987LDjiEiSSCuhW5mWUTL/E/u/hSAu5e7e4u7R4A/8K9hlTJg\naKvNhwBbD/yY7n6vu09z92lFRUXxjJ/03J0FG6uZqjsUiQjxPcvFgPuBFe7+i1bLB7Za7RJgafD8\nGeBKM8sxs5HAGGB+vPKlg3WVe6mua/rw4iIR6drieZbLqcDngQ/MbHGw7HvAVWY2mehwygbgiwDu\nvszMHgeWEz1D5mad4XJoJRuqAJg2QoUuInEsdHd/k7bHxZ87xDY/An4Ur0zp5n/e2cSIfj04qjA/\n7CgikgQ6gqhJAAAQ9ElEQVR0pWgKW12+h/OP1o0tRCRKhZ6i3J2IO1Waw0VEAir0FGVmnD2uPy+v\nKA87iogkCRV6CmpsjvD22kpeWl7OUYV5YccRkSQRz7NcpJO1RJy7XljJn97ZyN7GFjIzTPcSFZEP\nqdBTyK/mruHe19fxiWMHMuu4QZwyupD8HH0LRSRKbZBCMoOzWaYO68P5R2t2RRH5KI2hp5AnF5SR\nm5XBRccMbH9lEelyVOgp5KxxRdQ3Rcjppm+biHychlxSQH1TC799pZSH39nI9JF96aPZFUWkDSr0\nJBeJOLN+8xaryvdw6ZTB/PCSSWFHEpEkpb/dk1xGhpGXkwnAHRdPoke2fgeLSNvUDkksEnHunruG\nJWU1nDq6H3nZmWFHEpEkpj30JPbPlTu4e+4aLjpmIP999VSiU8yLiLRNhZ7EttXsA+Cb54+lV4+s\nkNOISLJToSexwvwcAHbvaw45iYikAhV6EluwsRqAEYU9Qk4iIqlAhZ6k5q4o54G31nPx5EH0zNVw\ni4i0T4WepH78/EpG98/nR5ccE3YUEUkRKvQkVFnbwNZd+zhxZD/yNJuiiMRIhZ5kmlsiXHP/fFoi\nzudOGh52HBFJISr0JLO6vJbl23bz/U9MYNyAnmHHEZEUokJPMve9uY6cbhlcoPnORaSDVOhJZEnZ\nLv62aAvXnDyc/gW5YccRkRSjQk8Sjc0Rvv3kEop65vDVGWPCjiMiKUinUCSJO59fycrte7jvmmkU\n6LxzETkM2kNPEm+VVnLa6ELOnVgcdhQRSVHaQ08CG3fuZVX5HmobNGeLiBw+FXqIIhHnmfe38t2n\nPiAvO5ObzhoVdiQRSWEq9BC0RJw/vLGOP727kc1V+5g6vA+/vfp4BvTSmS0icvhU6CH4yYsruee1\ndZx8VD9uvWA8MycNICtThzNE5Mio0BPs6cVbuOe1dXz2xGGaeEtEOpV2CxNo0846bn1yCdNH9OX2\nTx0ddhwRSTNxK3QzyzWz+Wb2vpktM7P/EywfaWbvmtkaM3vMzLKD5TnB69Lg/SPilS0s//hgG43N\nEf7ryslkd9PvUhHpXPFslQbgHHc/DpgMXGhmJwF3Ab909zFANXBDsP4NQLW7jwZ+GayXVvY2NJNh\n/7q1nIhIZ4pboXtUbfAyK3g4cA7wZLB8NnBx8HxW8Jrg/TMszW5zP7Iwj4hDWXVd2FFEJA3F9e9+\nM8s0s8XADmAOsBbY5e77r6ApAwYHzwcDmwGC99cA/eKZL9FeXlFOdrcM+vTIDjuKiKShuBa6u7e4\n+2RgCDAdmNDWasHbtvbG/cAFZnajmZWYWUlFRUXnhY2zt0sreX7pdm6ZMYY+eSp0Eel8CTky5+67\ngFeBk4DeZrb/dMkhwNbgeRkwFCB4fy+gqo2Pda+7T3P3aUVFRfGO3mlWbN8DwNXTh4WcRETSVTzP\ncikys97B8+7AucAK4BXg8mC1a4Gng+fPBK8J3v9Pd//YHnqqqm9qAaBHTmbISUQkXcXzwqKBwGwz\nyyT6i+Nxd3/WzJYDj5rZD4FFwP3B+vcDD5tZKdE98yvjmC3h6ptayDDI1hWhIhIncSt0d18CTGlj\n+Tqi4+kHLq8HrohXnrC4O4s272LO8nIG9e5Omp24IyJJRJf+x0lNXRN/XVTGn+dvZlX5HnpkZ/Lr\nqz72+01EpNOo0DtZJJhJ8RdzVtPQHOHYIb348aXH8KnjBpGfo39uEYkfNUwnu+f1ddz1wkrOn1jM\n12aMYdLgXmFHEpEuQoXeiSIR52+LtnDCiD7c8/mpGi8XkYTSKRedZGdtA1fcM49V5Xu4ZMoQlbmI\nJJz20DvB2opa7nx+JYs2VfPzK47j0uMHt7+RiEgnU6EfgY079/KDZ5bxyqoKumUYXzprFJdNHRJ2\nLBHpolToh+n9zbv4zL3z6JaRwbfOH8unTxhK/566J6iIhEeFfpj+45ll9MvL4ckvnczAXt3DjiMi\nooOih2vV9t1cOGmAylxEkoYK/TDUN7VQ3xShr6bBFZEkokI/DGsrojdiGthLY+Yikjw0ht5BCzZW\n8Z/PriAr0zhtTGHYcUREPqRC74DlW3dz+e/nkZfdjR9feqzOahGRpKJC74BNVXW4w6+vmsLZ4/uH\nHUdE5CM0hh6jd9bt5Ht//QCAusaWkNOIiHyc9tBjsLmqjv81u4TCnjn84tPHcebY1LmXqYh0HSr0\nGDzw1noamiM89IXpDO3bI+w4IiJt0pBLDDburGN0/3yVuYgkNRV6DLIyjfpmjZuLSHJTobfD3Vm1\nfQ+ji/LDjiIickgq9HY8uaCMDTvrOF0HQkUkyanQD2HhpmruemEl04b34erpw8KOIyJySDrLpQ17\nG5r52UurePDtDQwoyOWOWZPIzNAt5UQkuanQ2/Cdvyzh2SXb+PxJw/n2hePomZsVdiQRkXap0A+w\nrWYfLy0r57pTRvCD/+/osOOIiMRMY+it7G1o5qaHF2AGN5w2Muw4IiIdoj30Vr7x+GKWbt3N7z83\nVRcRiUjK0R56K+W7GxhVlMd5E4vDjiIi0mEq9FYumTKY1eW1LNpUHXYUEZEOU6G3UlwQvWHFUwu3\nhJxERKTjNIYO1NQ18e2/vM+Ly8oZ3T+fm84aFXYkEZEOU6EDf3hjHS8uK+cTxwzkp1ccS49s/bOI\nSOqJ25CLmeWa2Xwze9/MlpnZ/wmWP2hm681scfCYHCw3M/uVmZWa2RIzOz5e2Vr7zpNL+M0rpRQX\n5HDbzPEqcxFJWfFsrwbgHHevNbMs4E0zez54363u/uQB688ExgSPE4HfBW/jZm1FLY+VbOazJw7j\n3z85kdyszHh+OhGRuIrbHrpH1QYvs4KHH2KTWcBDwXbvAL3NbGC88gF0Dwp8TP98lbmIpLy4nuVi\nZplmthjYAcxx93eDd/0oGFb5pZnlBMsGA5tbbV4WLIubgb1yyc3KYMPOunh+GhGRhIhrobt7i7tP\nBoYA081sEvBdYDxwAtAX+E6welvTGX5sj97MbjSzEjMrqaioOKJ875fVUN8UYVR/3bxCRFJfQs5D\nd/ddwKvAhe6+LRhWaQD+CEwPVisDhrbabAiwtY2Pda+7T3P3aUVFh3/TiZ+/tIrLf/c2vbpncZZu\nXiEiaSCeZ7kUmVnv4Hl34Fxg5f5xcTMz4GJgabDJM8A1wdkuJwE17r4tXvl6ZHfjimlD+Oc3z9S8\nLSKSFuJ5lstAYLaZZRL9xfG4uz9rZv80syKiQyyLgZuC9Z8DLgJKgTrg+jhm40u6eEhE0kzcCt3d\nlwBT2lh+zkHWd+DmeOUREUl3mstFRCRNqNBFRNKECl1EJE2o0EVE0oQKXUQkTajQRUTShApdRCRN\nqNBFRNKECl1EJE2o0EVE0oQKXUQkTajQRUTShEXnxEpNZlYBbGxntUKgMgFxjlSq5ARljYdUyQnK\nGg/j3L3nkX6QlL7Fvbu3e2cKMytx92mJyHMkUiUnKGs8pEpOUNZ4MLOSzvg4GnIREUkTKnQRkTTR\nFQr93rADxChVcoKyxkOq5ARljYdOyZnSB0VFRORfusIeuohIl5AWhW5mt5jZUjNbZmZfP8g6Z5nZ\n4mCd1xKdsVWOQ2Y1s15m9nczez9YJ643yz7gcz9gZjvMbGmrZX3NbI6ZrQne9jnIttcG66wxs2uT\nNauZTTazecG/7RIz+0wy5my1boGZbTGz38Qz55FmNbNhZvaSma0ws+VmNiKJs/4k+P6vMLNfmZkl\nOOcVweePmNlBz8AxswvNbJWZlZrZbTF9QndP6QcwCVgK9CB6GubLwJgD1ukNLAeGBa/7J3HW7wF3\nBc+LgCogO0H5zgCOB5a2WvYT4Lbg+W37sx2wXV9gXfC2T/C8T5JmHbv/3xwYBGwDeidbzlbr3g08\nAvwmWb//wfteBc4LnucDPZIxK3AK8BaQGTzmAWclOOcEYFzwbzbtINtlAmuBo4Bs4H1gYnufLx32\n0CcA77h7nbs3A68BlxywztXAU+6+CcDddyQ4436xZHWgZ7DXkE+00JsTEc7dXw8+X2uzgNnB89nA\nxW1segEwx92r3L0amANcGLegHH5Wd1/t7muC51uBHUR/cSZVTgAzmwoUAy/FK19rh5vVzCYC3dx9\nTvBxat29LhmzEv35yiVakjlAFlAep5ht5nT3Fe6+qp1NpwOl7r7O3RuBR4l+fYeUDoW+FDjDzPqZ\nWQ/gImDoAeuMBfqY2atmtsDMrkl4yqhYsv6GaPFvBT4AbnH3SGJjfkSxu28DCN72b2OdwcDmVq/L\ngmWJFkvWD5nZdKI/2GsTkK21dnOaWQbwc+DWBGc7UCz/pmOBXWb2lJktMrOfmllmQlNGtZvV3ecB\nrxD9y2wb8KK7r0hoytgc1s9USl8pCtHfdmZ2F9G9wlqif5ocuEfbDZgKzAC6A/PM7B13X52EWS8A\nFgPnAKOAOWb2hrvvTmTWDmprDDKpT58ys4HAw8C1If/CPJgvA8+5++Y4DvF2lm7A6cAUYBPwGHAd\ncH+ImdpkZqOJ7jANCRbNMbMzgj3pZHJYP1PpsIeOu9/v7se7+xlE/7xZc8AqZcAL7r7X3SuB14Hj\nEp0TYsp6PdHhIXf3UmA9MD7ROVspD8pvfwm2NVxVxkf/0hhC9C+MRIslK2ZWAPwD+L67v5PAfPvF\nkvNk4CtmtgH4GXCNmd2ZuIgfivX7vygYHmgG/kZ03DjRYsl6CdFhz1p3rwWeB05KYMZYHdbPVFoU\nupn1D94OAy4F/nzAKk8Dp5tZt2Co40QglD+zYsi6iehfEphZMdGDJ+sSmfEAzwD7z1q5lui/5YFe\nBM43sz7BmQXnB8sSrd2sZpYN/BV4yN2fSGC21trN6e6fdfdh7j4C+BbRvLGd6dC5Yvn+v0d0SHP/\nsYhziJ6EkGixZN0EnBl0QRZwJiF1QTveA8aY2cjg/+yVRL++Q4vX0d1EPoA3iP4Heh+YESy7Cbip\n1Tq3BussBb6erFmJnnnxEtHx86XA5xKY7c9ExxWbiO4h3AD0A+YS/UtiLtA3WHcacF+rbb8AlAaP\n65M1K/C5YJvFrR6Tky3nAR/jOhJzlsuRfP/PA5YE/28fJM5nZh3B9z8TuIdoiS8HfhFCzkuC5w1E\nD8i+GKw7iOgw2/5tLwJWEz3G879j+Xy6UlREJE2kxZCLiIio0EVE0oYKXUQkTajQRUTShApdRCRN\nqNClSzCz3mb25Vav25wd0sw+E8zCuMzMftJqeY6ZPRbMfPdu69kEzWy6mb0ezIy30szuC653EEko\nFbp0Fb2JXk6PmfUFbid6gdl04Pbgoqh+wE+JXh9wNFBsZjOC7W8Aqt19NPBL4K7gYxUDTwDfcfdx\nRC8rfwE44ju4i3SUCl26ijuBUWa2GHiXtmeHPApY7e4VwTYvA5cFz1vP5PckMCOYEfNmYLZHJ33C\no55097jN4CdyMCp06SpuA9a6+2SiVwq2NZNdKTDezEaYWTei06/un0/jw9nvPDpfSQ3RKxMnAQsS\n8hWItEOFLl1RmzPZBXvrXyI6W+AbwAb+NRtmys0oKV2PCl26ooPOZOfuf3f3E939ZGAV/5oN88Nt\ngr33XkRny1xGdGpmkdCp0KWr2MO/DlQedHbIVrNh9iF6EPW+YJvWM/ldDvzToxMh/Qa41sxO3P+J\nzOxzZjYgzl+PyMek/A0uRGLh7jvN7K3gZr3PA/9JdIpSgDvcff9twu42s+NaLd9/E5T7gYfNrJTo\nnvmVwcctN7MrgZ8FvwwiROfbfyr+X5XIR2m2RRGRNKEhFxGRNKFCFxFJEyp0EZE0oUIXEUkTKnQR\nkTShQhcRSRMqdBGRNKFCFxFJE/8PWXjK6Cn8mssAAAAASUVORK5CYII=\n",
"text/plain": [
"<matplotlib.figure.Figure at 0x7f9f6eea1080>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"downcast, upcast = cast.split()\n",
"fig, ax = downcast['t090C'].plot()"
]
},
{
"cell_type": "code",
"execution_count": 5,
"metadata": {},
"outputs": [
{
"data": {
"text/html": [
"<div>\n",
"<style>\n",
" .dataframe thead tr:only-child th {\n",
" text-align: right;\n",
" }\n",
"\n",
" .dataframe thead th {\n",
" text-align: left;\n",
" }\n",
"\n",
" .dataframe tbody tr th {\n",
" vertical-align: top;\n",
" }\n",
"</style>\n",
"<table border=\"1\" class=\"dataframe\">\n",
" <thead>\n",
" <tr style=\"text-align: right;\">\n",
" <th></th>\n",
" <th>t090C</th>\n",
" <th>t190C</th>\n",
" <th>c0S/m</th>\n",
" <th>c1S/m</th>\n",
" <th>flC</th>\n",
" <th>turbWETntu0</th>\n",
" <th>sbeox0V</th>\n",
" <th>sbeox1V</th>\n",
" <th>bat</th>\n",
" <th>xmiss</th>\n",
" <th>...</th>\n",
" <th>sigma-�11</th>\n",
" <th>depSM</th>\n",
" <th>sbeox0PS</th>\n",
" <th>sbeox1PS</th>\n",
" <th>sal00</th>\n",
" <th>sal11</th>\n",
" <th>svCM</th>\n",
" <th>svCM1</th>\n",
" <th>nbin</th>\n",
" <th>flag</th>\n",
" </tr>\n",
" <tr>\n",
" <th>Pressure [dbar]</th>\n",
" <th></th>\n",
" <th></th>\n",
" <th></th>\n",
" <th></th>\n",
" <th></th>\n",
" <th></th>\n",
" <th></th>\n",
" <th></th>\n",
" <th></th>\n",
" <th></th>\n",
" <th></th>\n",
" <th></th>\n",
" <th></th>\n",
" <th></th>\n",
" <th></th>\n",
" <th></th>\n",
" <th></th>\n",
" <th></th>\n",
" <th></th>\n",
" <th></th>\n",
" <th></th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>1.0</th>\n",
" <td>10.9243</td>\n",
" <td>10.9212</td>\n",
" <td>3.927643</td>\n",
" <td>3.927602</td>\n",
" <td>0.2611</td>\n",
" <td>0.1695</td>\n",
" <td>2.7249</td>\n",
" <td>2.5407</td>\n",
" <td>0.9603</td>\n",
" <td>78.6563</td>\n",
" <td>...</td>\n",
" <td>27.0323</td>\n",
" <td>0.991</td>\n",
" <td>101.383</td>\n",
" <td>99.542</td>\n",
" <td>35.3086</td>\n",
" <td>35.3112</td>\n",
" <td>1493.50</td>\n",
" <td>1493.49</td>\n",
" <td>18.0</td>\n",
" <td>False</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2.0</th>\n",
" <td>10.9190</td>\n",
" <td>10.9145</td>\n",
" <td>3.927209</td>\n",
" <td>3.926972</td>\n",
" <td>0.2428</td>\n",
" <td>0.1700</td>\n",
" <td>2.7235</td>\n",
" <td>2.5663</td>\n",
" <td>0.9534</td>\n",
" <td>78.7929</td>\n",
" <td>...</td>\n",
" <td>27.0333</td>\n",
" <td>1.981</td>\n",
" <td>101.274</td>\n",
" <td>101.439</td>\n",
" <td>35.3089</td>\n",
" <td>35.3108</td>\n",
" <td>1493.49</td>\n",
" <td>1493.48</td>\n",
" <td>62.0</td>\n",
" <td>False</td>\n",
" </tr>\n",
" <tr>\n",
" <th>3.0</th>\n",
" <td>10.9230</td>\n",
" <td>10.9194</td>\n",
" <td>3.927644</td>\n",
" <td>3.927486</td>\n",
" <td>0.2450</td>\n",
" <td>0.1870</td>\n",
" <td>2.7213</td>\n",
" <td>2.5907</td>\n",
" <td>0.9533</td>\n",
" <td>78.7963</td>\n",
" <td>...</td>\n",
" <td>27.0324</td>\n",
" <td>2.972</td>\n",
" <td>101.163</td>\n",
" <td>103.158</td>\n",
" <td>35.3089</td>\n",
" <td>35.3108</td>\n",
" <td>1493.53</td>\n",
" <td>1493.52</td>\n",
" <td>35.0</td>\n",
" <td>False</td>\n",
" </tr>\n",
" <tr>\n",
" <th>4.0</th>\n",
" <td>10.9223</td>\n",
" <td>10.9202</td>\n",
" <td>3.927599</td>\n",
" <td>3.927602</td>\n",
" <td>0.2523</td>\n",
" <td>0.1817</td>\n",
" <td>2.7205</td>\n",
" <td>2.6057</td>\n",
" <td>0.9521</td>\n",
" <td>78.8193</td>\n",
" <td>...</td>\n",
" <td>27.0322</td>\n",
" <td>3.962</td>\n",
" <td>101.131</td>\n",
" <td>104.082</td>\n",
" <td>35.3087</td>\n",
" <td>35.3107</td>\n",
" <td>1493.54</td>\n",
" <td>1493.53</td>\n",
" <td>35.0</td>\n",
" <td>False</td>\n",
" </tr>\n",
" <tr>\n",
" <th>5.0</th>\n",
" <td>10.9122</td>\n",
" <td>10.9103</td>\n",
" <td>3.926742</td>\n",
" <td>3.926738</td>\n",
" <td>0.2590</td>\n",
" <td>0.2068</td>\n",
" <td>2.7186</td>\n",
" <td>2.6230</td>\n",
" <td>0.9514</td>\n",
" <td>78.8325</td>\n",
" <td>...</td>\n",
" <td>27.0344</td>\n",
" <td>4.953</td>\n",
" <td>100.993</td>\n",
" <td>104.786</td>\n",
" <td>35.3094</td>\n",
" <td>35.3112</td>\n",
" <td>1493.52</td>\n",
" <td>1493.52</td>\n",
" <td>38.0</td>\n",
" <td>False</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"<p>5 rows × 23 columns</p>\n",
"</div>"
],
"text/plain": [
" t090C t190C c0S/m c1S/m flC turbWETntu0 \\\n",
"Pressure [dbar] \n",
"1.0 10.9243 10.9212 3.927643 3.927602 0.2611 0.1695 \n",
"2.0 10.9190 10.9145 3.927209 3.926972 0.2428 0.1700 \n",
"3.0 10.9230 10.9194 3.927644 3.927486 0.2450 0.1870 \n",
"4.0 10.9223 10.9202 3.927599 3.927602 0.2523 0.1817 \n",
"5.0 10.9122 10.9103 3.926742 3.926738 0.2590 0.2068 \n",
"\n",
" sbeox0V sbeox1V bat xmiss ... sigma-�11 depSM \\\n",
"Pressure [dbar] ... \n",
"1.0 2.7249 2.5407 0.9603 78.6563 ... 27.0323 0.991 \n",
"2.0 2.7235 2.5663 0.9534 78.7929 ... 27.0333 1.981 \n",
"3.0 2.7213 2.5907 0.9533 78.7963 ... 27.0324 2.972 \n",
"4.0 2.7205 2.6057 0.9521 78.8193 ... 27.0322 3.962 \n",
"5.0 2.7186 2.6230 0.9514 78.8325 ... 27.0344 4.953 \n",
"\n",
" sbeox0PS sbeox1PS sal00 sal11 svCM svCM1 nbin \\\n",
"Pressure [dbar] \n",
"1.0 101.383 99.542 35.3086 35.3112 1493.50 1493.49 18.0 \n",
"2.0 101.274 101.439 35.3089 35.3108 1493.49 1493.48 62.0 \n",
"3.0 101.163 103.158 35.3089 35.3108 1493.53 1493.52 35.0 \n",
"4.0 101.131 104.082 35.3087 35.3107 1493.54 1493.53 35.0 \n",
"5.0 100.993 104.786 35.3094 35.3112 1493.52 1493.52 38.0 \n",
"\n",
" flag \n",
"Pressure [dbar] \n",
"1.0 False \n",
"2.0 False \n",
"3.0 False \n",
"4.0 False \n",
"5.0 False \n",
"\n",
"[5 rows x 23 columns]"
]
},
"execution_count": 5,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"cast.head()"
]
},
{
"cell_type": "code",
"execution_count": 6,
"metadata": {},
"outputs": [
{
"data": {
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Xsqelncz0NL58xlhGFOp2cpI8VOjS6z25fDu/fmEdJQNyufC4EcwYVcgJo4t0b1BJOip0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\nKeL/Aw+t1rIlyfytAAAAAElFTkSuQmCC\n",
"text/plain": [
"<matplotlib.figure.Figure at 0x7f9f6cd81940>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"cast['t090C'].plot();"
]
},
{
"cell_type": "code",
"execution_count": 7,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"['* Sea-Bird SBE 9 Data File:',\n",
" '* FileName = D:\\\\CRUISE_DATA\\\\NREP17\\\\INSIDE\\\\CTD001.hex',\n",
" '* Software Version Seasave V 7.21d',\n",
" '* Temperature SN = 5475',\n",
" '* Conductivity SN = 3934',\n",
" '* Number of Bytes Per Scan = 37',\n",
" '* Number of Voltage Words = 4',\n",
" '* Number of Scans Averaged by the Deck Unit = 1',\n",
" '* System UpLoad Time = Jun 01 2017 11:28:16',\n",
" '* NMEA Latitude = 59 56.56 N',\n",
" '* NMEA Longitude = 005 08.46 W',\n",
" '* NMEA UTC (Time) = Jun 01 2017 11:19:12',\n",
" '* Store Lat/Lon Data = Append to Every Scan',\n",
" '* SBE 11plus V 5.1g',\n",
" '* number of scans to average = 1',\n",
" '* pressure baud rate = 9600',\n",
" '* NMEA baud rate = 4800',\n",
" '* GPIB address = 1',\n",
" '* advance primary conductivity 0.073 seconds',\n",
" '* advance secondary conductivity 0.073 seconds',\n",
" '* autorun on power up is disabled',\n",
" '* S>',\n",
" '** Ship: RV-ALLIANCE',\n",
" '** Cruise: NREP17',\n",
" '** Station:',\n",
" '** Depth:',\n",
" '* System UTC = Jun 01 2017 11:28:16',\n",
" '*END*']"
]
},
"execution_count": 7,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"cast.header"
]
},
{
"cell_type": "code",
"execution_count": 8,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"datetime.datetime(2017, 6, 1, 11, 19, 12)"
]
},
"execution_count": 8,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"time_header = next(x.split('= ')[1] for x in cast.header if 'NMEA UTC (Time) =' in x)\n",
"time = datetime.datetime.strptime(time_header,'%b %d %Y %H:%M:%S')\n",
"time"
]
},
{
"cell_type": "code",
"execution_count": 9,
"metadata": {
"collapsed": true
},
"outputs": [],
"source": [
"#cast['profile'], _ = cast.station # Is this a profile identifier?\n",
"cast['profile'], _ = os.path.splitext(fname)\n",
"cast['t'] = time\n",
"cast['x'] = cast.longitude\n",
"cast['y'] = cast.latitude\n",
"cast['z'] = cast.index\n",
"cast['station'] = '001'\n",
"cast['experiment'] = 'NREP17'\n",
"cast['flag'] = cast['flag'].astype(int) # bool columns are not supported in pocean (yet)"
]
},
{
"cell_type": "code",
"execution_count": 10,
"metadata": {},
"outputs": [
{
"data": {
"text/html": [
"<div>\n",
"<style>\n",
" .dataframe thead tr:only-child th {\n",
" text-align: right;\n",
" }\n",
"\n",
" .dataframe thead th {\n",
" text-align: left;\n",
" }\n",
"\n",
" .dataframe tbody tr th {\n",
" vertical-align: top;\n",
" }\n",
"</style>\n",
"<table border=\"1\" class=\"dataframe\">\n",
" <thead>\n",
" <tr style=\"text-align: right;\">\n",
" <th></th>\n",
" <th>t090C</th>\n",
" <th>t190C</th>\n",
" <th>c0S/m</th>\n",
" <th>c1S/m</th>\n",
" <th>flC</th>\n",
" <th>turbWETntu0</th>\n",
" <th>sbeox0V</th>\n",
" <th>sbeox1V</th>\n",
" <th>bat</th>\n",
" <th>xmiss</th>\n",
" <th>...</th>\n",
" <th>svCM1</th>\n",
" <th>nbin</th>\n",
" <th>flag</th>\n",
" <th>profile</th>\n",
" <th>t</th>\n",
" <th>x</th>\n",
" <th>y</th>\n",
" <th>z</th>\n",
" <th>station</th>\n",
" <th>experiment</th>\n",
" </tr>\n",
" <tr>\n",
" <th>Pressure [dbar]</th>\n",
" <th></th>\n",
" <th></th>\n",
" <th></th>\n",
" <th></th>\n",
" <th></th>\n",
" <th></th>\n",
" <th></th>\n",
" <th></th>\n",
" <th></th>\n",
" <th></th>\n",
" <th></th>\n",
" <th></th>\n",
" <th></th>\n",
" <th></th>\n",
" <th></th>\n",
" <th></th>\n",
" <th></th>\n",
" <th></th>\n",
" <th></th>\n",
" <th></th>\n",
" <th></th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>1.0</th>\n",
" <td>10.9243</td>\n",
" <td>10.9212</td>\n",
" <td>3.927643</td>\n",
" <td>3.927602</td>\n",
" <td>0.2611</td>\n",
" <td>0.1695</td>\n",
" <td>2.7249</td>\n",
" <td>2.5407</td>\n",
" <td>0.9603</td>\n",
" <td>78.6563</td>\n",
" <td>...</td>\n",
" <td>1493.49</td>\n",
" <td>18.0</td>\n",
" <td>0</td>\n",
" <td>dCTD001</td>\n",
" <td>2017-06-01 11:19:12</td>\n",
" <td>-5.141</td>\n",
" <td>59.942667</td>\n",
" <td>1.0</td>\n",
" <td>001</td>\n",
" <td>NREP17</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2.0</th>\n",
" <td>10.9190</td>\n",
" <td>10.9145</td>\n",
" <td>3.927209</td>\n",
" <td>3.926972</td>\n",
" <td>0.2428</td>\n",
" <td>0.1700</td>\n",
" <td>2.7235</td>\n",
" <td>2.5663</td>\n",
" <td>0.9534</td>\n",
" <td>78.7929</td>\n",
" <td>...</td>\n",
" <td>1493.48</td>\n",
" <td>62.0</td>\n",
" <td>0</td>\n",
" <td>dCTD001</td>\n",
" <td>2017-06-01 11:19:12</td>\n",
" <td>-5.141</td>\n",
" <td>59.942667</td>\n",
" <td>2.0</td>\n",
" <td>001</td>\n",
" <td>NREP17</td>\n",
" </tr>\n",
" <tr>\n",
" <th>3.0</th>\n",
" <td>10.9230</td>\n",
" <td>10.9194</td>\n",
" <td>3.927644</td>\n",
" <td>3.927486</td>\n",
" <td>0.2450</td>\n",
" <td>0.1870</td>\n",
" <td>2.7213</td>\n",
" <td>2.5907</td>\n",
" <td>0.9533</td>\n",
" <td>78.7963</td>\n",
" <td>...</td>\n",
" <td>1493.52</td>\n",
" <td>35.0</td>\n",
" <td>0</td>\n",
" <td>dCTD001</td>\n",
" <td>2017-06-01 11:19:12</td>\n",
" <td>-5.141</td>\n",
" <td>59.942667</td>\n",
" <td>3.0</td>\n",
" <td>001</td>\n",
" <td>NREP17</td>\n",
" </tr>\n",
" <tr>\n",
" <th>4.0</th>\n",
" <td>10.9223</td>\n",
" <td>10.9202</td>\n",
" <td>3.927599</td>\n",
" <td>3.927602</td>\n",
" <td>0.2523</td>\n",
" <td>0.1817</td>\n",
" <td>2.7205</td>\n",
" <td>2.6057</td>\n",
" <td>0.9521</td>\n",
" <td>78.8193</td>\n",
" <td>...</td>\n",
" <td>1493.53</td>\n",
" <td>35.0</td>\n",
" <td>0</td>\n",
" <td>dCTD001</td>\n",
" <td>2017-06-01 11:19:12</td>\n",
" <td>-5.141</td>\n",
" <td>59.942667</td>\n",
" <td>4.0</td>\n",
" <td>001</td>\n",
" <td>NREP17</td>\n",
" </tr>\n",
" <tr>\n",
" <th>5.0</th>\n",
" <td>10.9122</td>\n",
" <td>10.9103</td>\n",
" <td>3.926742</td>\n",
" <td>3.926738</td>\n",
" <td>0.2590</td>\n",
" <td>0.2068</td>\n",
" <td>2.7186</td>\n",
" <td>2.6230</td>\n",
" <td>0.9514</td>\n",
" <td>78.8325</td>\n",
" <td>...</td>\n",
" <td>1493.52</td>\n",
" <td>38.0</td>\n",
" <td>0</td>\n",
" <td>dCTD001</td>\n",
" <td>2017-06-01 11:19:12</td>\n",
" <td>-5.141</td>\n",
" <td>59.942667</td>\n",
" <td>5.0</td>\n",
" <td>001</td>\n",
" <td>NREP17</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"<p>5 rows × 30 columns</p>\n",
"</div>"
],
"text/plain": [
" t090C t190C c0S/m c1S/m flC turbWETntu0 \\\n",
"Pressure [dbar] \n",
"1.0 10.9243 10.9212 3.927643 3.927602 0.2611 0.1695 \n",
"2.0 10.9190 10.9145 3.927209 3.926972 0.2428 0.1700 \n",
"3.0 10.9230 10.9194 3.927644 3.927486 0.2450 0.1870 \n",
"4.0 10.9223 10.9202 3.927599 3.927602 0.2523 0.1817 \n",
"5.0 10.9122 10.9103 3.926742 3.926738 0.2590 0.2068 \n",
"\n",
" sbeox0V sbeox1V bat xmiss ... svCM1 nbin \\\n",
"Pressure [dbar] ... \n",
"1.0 2.7249 2.5407 0.9603 78.6563 ... 1493.49 18.0 \n",
"2.0 2.7235 2.5663 0.9534 78.7929 ... 1493.48 62.0 \n",
"3.0 2.7213 2.5907 0.9533 78.7963 ... 1493.52 35.0 \n",
"4.0 2.7205 2.6057 0.9521 78.8193 ... 1493.53 35.0 \n",
"5.0 2.7186 2.6230 0.9514 78.8325 ... 1493.52 38.0 \n",
"\n",
" flag profile t x y z \\\n",
"Pressure [dbar] \n",
"1.0 0 dCTD001 2017-06-01 11:19:12 -5.141 59.942667 1.0 \n",
"2.0 0 dCTD001 2017-06-01 11:19:12 -5.141 59.942667 2.0 \n",
"3.0 0 dCTD001 2017-06-01 11:19:12 -5.141 59.942667 3.0 \n",
"4.0 0 dCTD001 2017-06-01 11:19:12 -5.141 59.942667 4.0 \n",
"5.0 0 dCTD001 2017-06-01 11:19:12 -5.141 59.942667 5.0 \n",
"\n",
" station experiment \n",
"Pressure [dbar] \n",
"1.0 001 NREP17 \n",
"2.0 001 NREP17 \n",
"3.0 001 NREP17 \n",
"4.0 001 NREP17 \n",
"5.0 001 NREP17 \n",
"\n",
"[5 rows x 30 columns]"
]
},
"execution_count": 10,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"cast.head()"
]
},
{
"cell_type": "code",
"execution_count": 11,
"metadata": {
"collapsed": true
},
"outputs": [],
"source": [
"atts={\n",
" 'global': {\n",
" 'title': 'NREP17 001',\n",
" 'summary': 'Data from CTD',\n",
" 'institution': 'CMRE',\n",
" 'cdm_profile_variables': 'station, experiment',\n",
" 'subsetVariables': 'station, experiment',\n",
" 'comments': [ x + \"\\n\" for x in cast.header ]\n",
" },\n",
" 'longitude': {\n",
" 'units': 'degrees_east',\n",
" 'standard_name':'longitude'\n",
" },\n",
" 'latitude': {\n",
" 'units': 'degrees_north',\n",
" 'standard_name':'latitude'\n",
" },\n",
" 'z': {\n",
" 'units': 'dbar', # pressure\n",
" 'standard_name': 'depth',\n",
" 'positive':'down'\n",
" },\n",
" 'un': {\n",
" 'units': 'm/s',\n",
" 'standard_name':'eastward_sea_water_velocity'\n",
" },\n",
" 'vn': {\n",
" 'units': 'm/s',\n",
" 'standard_name':'northward_sea_water_velocity'\n",
" },\n",
" 'profile': {\n",
" 'cf_role': 'profile_id'\n",
" },\n",
" 'time': {\n",
" 'units': IncompleteMultidimensionalProfile.default_time_unit,\n",
" 'standard_name': 'time'\n",
" }\n",
"}"
]
},
{
"cell_type": "code",
"execution_count": 12,
"metadata": {
"collapsed": true
},
"outputs": [],
"source": [
"imp = IncompleteMultidimensionalProfile.from_dataframe(cast, output='test.nc', attributes=atts)\n",
"imp.close()"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"collapsed": true
},
"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": "3.5.3"
}
},
"nbformat": 4,
"nbformat_minor": 2
}
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