{ "cells": [ { "cell_type": "markdown", "metadata": {}, "source": [ "Looking at qualities of tilt and things fom model runs with uniform vwinds (vtau = 0.2) and varying time scales." ] }, { "cell_type": "code", "execution_count": 4, "metadata": { "collapsed": true }, "outputs": [], "source": [ "import numpy as np\n", "import netCDF4 as nc\n", "import matplotlib.pyplot as plt\n", "from salishsea_tools import (nc_tools, viz_tools, gsw_calls)\n", "import numpy.ma as ma\n", "from matplotlib import animation, rc\n", "from scipy.optimize import curve_fit\n", "from visualisations import *\n", "%matplotlib inline" ] }, { "cell_type": "code", "execution_count": 2, "metadata": { "collapsed": true }, "outputs": [], "source": [ "rc('animation', html='html5')" ] }, { "cell_type": "code", "execution_count": 3, "metadata": { "collapsed": true }, "outputs": [], "source": [ "mesh_mask = nc.Dataset('/home/vdo/MEOPAR/NEMO-forcing/grid/mesh_mask201702.nc')\n", "new_domain = mesh_mask.variables['tmask'][0,:,334:,114:] \n", "lakebathy = nc.Dataset('/home/vdo/MEOPAR/NEMO-forcing/grid/lake_bathy201702.nc')\n", "lake_meshmask = nc.Dataset('/home/vdo/MEOPAR/NEMO-forcing/grid/lake_meshmask201702.nc')\n", "U24W = nc.Dataset('/ocean/vdo/MEOPAR/completed-runs/SalishSeaLake/24UW/SalishSea_1h_20170101_20170105_grid_T.nc')\n", "U24S = nc.Dataset('/ocean/vdo/MEOPAR/completed-runs/SalishSeaLake/24US/SalishSea_1h_20160601_20160605_grid_T.nc')\n", "U48W = nc.Dataset('/ocean/vdo/MEOPAR/completed-runs/SalishSeaLake/48UW/SalishSea_1h_20170101_20170105_grid_T.nc')\n", "U48S = nc.Dataset('/ocean/vdo/MEOPAR/completed-runs/SalishSeaLake/48US/SalishSea_1h_20160601_20160605_grid_T.nc')\n", "U72W = nc.Dataset('/ocean/vdo/MEOPAR/completed-runs/SalishSeaLake/72UW/SalishSea_1h_20170101_20170105_grid_T.nc')\n", "U72S = nc.Dataset('/ocean/vdo/MEOPAR/completed-runs/SalishSeaLake/72US/SalishSea_1h_20160601_20160605_grid_T.nc')" ] }, { "cell_type": "code", "execution_count": 10, "metadata": { "collapsed": true }, "outputs": [], "source": [ "def calc_rho(Sal, TempC, P):\n", " sqrSal = np.sqrt(Sal)\n", " R1 = ((((6.536332e-9 * TempC - 1.120083e-6) * TempC + 1.001685e-4)\n", " * TempC - 9.095290e-3) * TempC + 6.793952e-2) * TempC - 28.263737\n", " R2 = (((5.3875e-9 * TempC - 8.2467e-7) * TempC + 7.6438e-5)\n", " * TempC - 4.0899e-3) * TempC + 8.24493e-1\n", " R3 = (-1.6546e-6 * TempC + 1.0227e-4) * TempC - 5.72466e-3\n", " SIG = (4.8314e-4 * Sal + R3 * sqrSal + R2) * Sal + R1\n", " V350P = 1.0 / 1028.1063\n", " SVA = -SIG * V350P / (1028.1063 + SIG)\n", " rho = 28.106331 - SVA / (V350P * (V350P + SVA)) + 1000\n", " return rho" ] }, { "cell_type": "code", "execution_count": 5, "metadata": { "collapsed": true }, "outputs": [], "source": [ "file1 = U24W" ] }, { "cell_type": "code", "execution_count": 8, "metadata": { "collapsed": true }, "outputs": [], "source": [ "deptht = file1.variables['deptht'][:]\n", "yslicemask = 1 - new_domain[:,yslice,:]" ] }, { "cell_type": "code", "execution_count": null, "metadata": { "collapsed": true }, "outputs": [], "source": [] }, { "cell_type": "code", "execution_count": 56, "metadata": { "collapsed": true }, "outputs": [], "source": [ "def func(x,m,b):\n", " return m*x + b" ] }, { "cell_type": "code", "execution_count": 63, "metadata": { "collapsed": false }, "outputs": [ { "data": { "text/plain": [ "[]" ] }, "execution_count": 63, "metadata": {}, "output_type": "execute_result" }, { "data": { "image/png": "iVBORw0KGgoAAAANSUhEUgAAAXQAAAD8CAYAAABn919SAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\ndkSXIuQAAAAASUVORK5CYII=\n", "text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "yslice=200\n", "pressure1 = gsw_calls.generic_gsw_caller('gsw_p_from_z.m',\n", " [-np.expand_dims(file1.variables['deptht'][:], 1) * np.ones(284),\n", " (np.ones([284,40]) *np.expand_dims(file1.variables['nav_lat'][yslice,:][:],1)).T])\n", "deptht = file1.variables['deptht'][:]\n", "i = 0\n", "density1 = calc_rho(file1.variables['vosaline'][i,:,yslice,68:149],\n", " file1.variables['votemper'][i,:,yslice,68:149],\n", " pressure1[:, 68:149])\n", "rho = 1023.3\n", "index1 = (np.abs(density1 - rho)).argmin(axis=0)\n", "list_of_depths1 = np.zeros((81))\n", "for x in range(81):\n", " list_of_depths1[x] = deptht[index1[x]]\n", "popt, pcov = curve_fit(func, np.arange(0,81), list_of_depths1)\n", "plt.plot(np.arange(0,81), list_of_depths1, 'r.')\n", "plt.grid('on')\n", "plt.ylim(20,25)\n", "plt.plot(np.arange(0,81), func(np.arange(0,81), *popt), 'b-')" ] }, { "cell_type": "code", "execution_count": 141, "metadata": { "collapsed": false }, "outputs": [ { "data": { "text/plain": [ "(102, 40, 81)" ] }, "execution_count": 141, "metadata": {}, "output_type": "execute_result" } ], "source": [ "density1 = calc_rho(file1.variables['vosaline'][:,:,yslice,68:149],\n", " file1.variables['votemper'][:,:,yslice,68:149],\n", " pressure1[:, 68:149])\n", "rho = 1023.3\n", "density1.shape" ] }, { "cell_type": "code", "execution_count": 142, "metadata": { "collapsed": false }, "outputs": [], "source": [ "index1 = (np.abs(density1 - rho)).argmin(axis=1)\n", "list_of_depths1 = np.zeros((102, 81))\n", "for t in range(102):\n", " for x in range(81):\n", " list_of_depths1[t,x] = deptht[index1[t,x]]" ] }, { "cell_type": "code", "execution_count": 136, "metadata": { "collapsed": false }, "outputs": [ { "data": { "text/plain": [ "34.685756683349609" ] }, "execution_count": 136, "metadata": {}, "output_type": "execute_result" } ], "source": [ "list_of_depths1.max()" ] }, { "cell_type": "code", "execution_count": 147, "metadata": { "collapsed": false }, "outputs": [ { "data": { "text/plain": [ "24.100255966186523" ] }, "execution_count": 147, "metadata": {}, "output_type": "execute_result" } ], "source": [ "list_of_depths1[0,0]" ] }, { "cell_type": "code", "execution_count": 143, "metadata": { "collapsed": false }, "outputs": [ { "data": { "text/plain": [ "array([ 11.50931168, 12.51816654, 13.53541183, 12.51816654,\n", " 13.53541183, 14.56898212, 16.76117325, 16.76117325,\n", " 16.76117325, 16.76117325, 16.76117325, 18.00713539,\n", " 18.00713539, 19.48178482, 19.48178482, 19.48178482,\n", " 19.48178482, 21.38997841, 21.38997841, 21.38997841,\n", " 21.38997841, 21.38997841, 21.38997841, 21.38997841,\n", " 21.38997841, 21.38997841, 21.38997841, 21.38997841,\n", " 21.38997841, 21.38997841, 21.38997841, 21.38997841,\n", " 21.38997841, 21.38997841, 24.10025597, 24.10025597,\n", " 24.10025597, 24.10025597, 24.10025597, 24.10025597,\n", " 24.10025597, 24.10025597, 24.10025597, 24.10025597,\n", " 24.10025597, 24.10025597, 24.10025597, 24.10025597,\n", " 24.10025597, 24.10025597, 24.10025597, 24.10025597,\n", " 24.10025597, 24.10025597, 24.10025597, 24.10025597,\n", " 28.22991562, 28.22991562, 28.22991562, 28.22991562,\n", " 28.22991562, 28.22991562, 28.22991562, 28.22991562,\n", " 28.22991562, 28.22991562, 28.22991562, 28.22991562,\n", " 28.22991562, 28.22991562, 28.22991562, 28.22991562,\n", " 28.22991562, 28.22991562, 34.68575668, 34.68575668,\n", " 34.68575668, 34.68575668, 34.68575668, 34.68575668, 28.22991562])" ] }, "execution_count": 143, "metadata": {}, "output_type": "execute_result" } ], "source": [ "list_of_depths1[30,:]" ] }, { "cell_type": "code", "execution_count": 222, "metadata": { "collapsed": false }, "outputs": [ { "ename": "IndexError", "evalue": "too many indices for array", "output_type": "error", "traceback": [ "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m", "\u001b[0;31mIndexError\u001b[0m Traceback (most recent call last)", "\u001b[0;32m\u001b[0m in \u001b[0;36m\u001b[0;34m()\u001b[0m\n\u001b[1;32m 1\u001b[0m \u001b[0mi\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0;36m31\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m----> 2\u001b[0;31m \u001b[0mpopt\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mpcov\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mcurve_fit\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mfunc\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mnp\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0marange\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;36m0\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;36m81\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mlist_of_depths1\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0mi\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 3\u001b[0m \u001b[0mplt\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mplot\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mnp\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0marange\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;36m0\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;36m81\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mlist_of_depths1\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0mi\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m'r.'\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 4\u001b[0m \u001b[0mplt\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mgrid\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m'on'\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 5\u001b[0m \u001b[0mplt\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mylim\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;36m35\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;36m0\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n", "\u001b[0;31mIndexError\u001b[0m: too many indices for array" ] } ], "source": [ "i = 31\n", "popt, pcov = curve_fit(func, np.arange(0,81), list_of_depths1[i,:])\n", "plt.plot(np.arange(0,81), list_of_depths1[i,:], 'r.')\n", "plt.grid('on')\n", "plt.ylim(35,0)\n", "plt.plot(np.arange(0,81), func(np.arange(0,81), *popt), 'b-')\n", "print(popt[0])" ] }, { "cell_type": "code", "execution_count": null, "metadata": { "collapsed": true }, "outputs": [], "source": [] }, { "cell_type": "code", "execution_count": 193, "metadata": { "collapsed": true }, "outputs": [], "source": [ "file2 = U48S\n", "yslice=200\n", "pressure2 = gsw_calls.generic_gsw_caller('gsw_p_from_z.m',\n", " [-np.expand_dims(file2.variables['deptht'][:], 1) * np.ones(284),\n", " (np.ones([284,40]) *np.expand_dims(file2.variables['nav_lat'][yslice,:][:],1)).T])\n", "deptht = file2.variables['deptht'][:]\n", "density2 = calc_rho(file2.variables['vosaline'][:,:,yslice,68:149],\n", " file2.variables['votemper'][:,:,yslice,68:149],\n", " pressure2[:, 68:149])\n", "rho = 1023.3\n", "index2 = (np.abs(density2 - rho)).argmin(axis=1)\n", "list_of_depths2 = np.zeros((102, 81))\n", "for t in range(102):\n", " for x in range(81):\n", " list_of_depths2[t,x] = deptht[index2[t,x]]" ] }, { "cell_type": "code", "execution_count": 166, "metadata": { "collapsed": false }, "outputs": [ { "data": { "text/plain": [ "array([ 11.50931168, 10.50476551, 11.50931168, 11.50931168,\n", " 11.50931168, 13.53541183, 14.56898212, 16.76117325,\n", " 15.63428783, 15.63428783, 16.76117325, 18.00713539,\n", " 18.00713539, 19.48178482, 19.48178482, 21.38997841,\n", " 21.38997841, 21.38997841, 21.38997841, 21.38997841,\n", " 21.38997841, 21.38997841, 21.38997841, 21.38997841,\n", " 21.38997841, 24.10025597, 24.10025597, 24.10025597,\n", " 21.38997841, 21.38997841, 21.38997841, 21.38997841,\n", " 21.38997841, 21.38997841, 21.38997841, 21.38997841,\n", " 24.10025597, 21.38997841, 21.38997841, 24.10025597,\n", " 24.10025597, 24.10025597, 24.10025597, 24.10025597,\n", " 24.10025597, 24.10025597, 24.10025597, 24.10025597,\n", " 24.10025597, 24.10025597, 24.10025597, 28.22991562,\n", " 28.22991562, 28.22991562, 28.22991562, 24.10025597,\n", " 24.10025597, 24.10025597, 24.10025597, 28.22991562,\n", " 28.22991562, 28.22991562, 28.22991562, 28.22991562,\n", " 28.22991562, 28.22991562, 28.22991562, 28.22991562,\n", " 28.22991562, 28.22991562, 28.22991562, 28.22991562,\n", " 28.22991562, 28.22991562, 34.68575668, 34.68575668,\n", " 34.68575668, 34.68575668, 34.68575668, 34.68575668, 28.22991562])" ] }, "execution_count": 166, "metadata": {}, "output_type": "execute_result" } ], "source": [ "list_of_depths2[24,:]" ] }, { "cell_type": "code", "execution_count": 165, "metadata": { "collapsed": false }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "0.220573917549\n" ] }, { "data": { "image/png": "iVBORw0KGgoAAAANSUhEUgAAAXQAAAD8CAYAAABn919SAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\n", "text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "i = 24\n", "popt, pcov = curve_fit(func, np.arange(0,81), list_of_depths2[i,:])\n", "plt.plot(np.arange(0,81), list_of_depths2[i,:], 'r.')\n", "plt.grid('on')\n", "plt.ylim(35,0)\n", "plt.plot(np.arange(0,81), func(np.arange(0,81), *popt), 'b-')\n", "print(popt[0])" ] }, { "cell_type": "code", "execution_count": null, "metadata": { "collapsed": true }, "outputs": [], "source": [] }, { "cell_type": "code", "execution_count": 173, "metadata": { "collapsed": false }, "outputs": [], "source": [ "file3 = U72S\n", "yslice=200\n", "pressure3 = gsw_calls.generic_gsw_caller('gsw_p_from_z.m',\n", " [-np.expand_dims(file3.variables['deptht'][:], 1) * np.ones(284),\n", " (np.ones([284,40]) *np.expand_dims(file3.variables['nav_lat'][yslice,:][:],1)).T])\n", "deptht = file3.variables['deptht'][:]\n", "density3 = calc_rho(file3.variables['vosaline'][:,:,yslice,68:149],\n", " file3.variables['votemper'][:,:,yslice,68:149],\n", " pressure3[:, 68:149])\n", "rho = 1023.3\n", "index3 = (np.abs(density3 - rho)).argmin(axis=1)\n", "list_of_depths3 = np.zeros((102, 81))\n", "for t in range(102):\n", " for x in range(81):\n", " list_of_depths3[t,x] = deptht[index3[t,x]]" ] }, { "cell_type": "code", "execution_count": 195, "metadata": { "collapsed": false }, "outputs": [ { "data": { "text/plain": [ "array([ 0.5000003 , 0.5000003 , 0.5000003 , 0.5000003 ,\n", " 0.5000003 , 0.5000003 , 0.5000003 , 0.5000003 ,\n", " 0.5000003 , 0.5000003 , 0.5000003 , 0.5000003 ,\n", " 1.5000031 , 1.5000031 , 1.5000031 , 1.5000031 ,\n", " 1.5000031 , 1.5000031 , 3.50003052, 3.50003052,\n", " 2.50001144, 2.50001144, 2.50001144, 1.5000031 ,\n", " 0.5000003 , 0.5000003 , 0.5000003 , 1.5000031 ,\n", " 1.5000031 , 2.50001144, 5.50015068, 11.50931168,\n", " 14.56898212, 16.76117325, 19.48178482, 21.38997841,\n", " 24.10025597, 24.10025597, 24.10025597, 28.22991562,\n", " 28.22991562, 28.22991562, 28.22991562, 28.22991562,\n", " 28.22991562, 28.22991562, 28.22991562, 28.22991562,\n", " 28.22991562, 28.22991562, 34.68575668, 34.68575668,\n", " 34.68575668, 34.68575668, 34.68575668, 34.68575668,\n", " 34.68575668, 34.68575668, 34.68575668, 34.68575668,\n", " 34.68575668, 34.68575668, 34.68575668, 34.68575668,\n", " 34.68575668, 34.68575668, 34.68575668, 34.68575668,\n", " 34.68575668, 34.68575668, 34.68575668, 44.51772308,\n", " 44.51772308, 44.51772308, 44.51772308, 44.51772308,\n", " 44.51772308, 44.51772308, 44.51772308, 44.51772308, 24.10025597])" ] }, "execution_count": 195, "metadata": {}, "output_type": "execute_result" } ], "source": [ "list_of_depths3[87, :]" ] }, { "cell_type": "code", "execution_count": 225, "metadata": { "collapsed": false }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "0.214865763937\n" ] }, { "data": { "image/png": "iVBORw0KGgoAAAANSUhEUgAAAXQAAAD8CAYAAABn919SAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\n", "text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "i = 17\n", "popt, pcov = curve_fit(func, np.arange(0,81), list_of_depths3[i,:])\n", "plt.plot(np.arange(0,81), list_of_depths3[i,:], 'r.')\n", "plt.grid('on')\n", "plt.ylim(45,0)\n", "plt.plot(np.arange(0,81), func(np.arange(0,81), *popt), 'b-')\n", "print(popt[0])" ] }, { "cell_type": "code", "execution_count": 231, "metadata": { "collapsed": false }, "outputs": [ { "data": { "text/plain": [ "(57, 137)" ] }, "execution_count": 231, "metadata": {}, "output_type": "execute_result" }, { "data": { "image/png": "iVBORw0KGgoAAAANSUhEUgAAAXQAAAD8CAYAAABn919SAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\n", "text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "plt.contourf(lake_meshmask.variables['tmask'][0,:,210,:])\n", "plt.xlim(57,137)" ] }, { "cell_type": "code", "execution_count": 237, "metadata": { "collapsed": false }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "0.22120710873\n" ] }, { "data": { "image/png": "iVBORw0KGgoAAAANSUhEUgAAAXQAAAD8CAYAAABn919SAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nCnQRkYT4P519hxhNYu76AAAAAElFTkSuQmCC\n", "text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "yslice = 210\n", "deptht = file1.variables['deptht'][:]\n", "yslicemask = 1 - new_domain[:,yslice,:]\n", "pressure1 = gsw_calls.generic_gsw_caller('gsw_p_from_z.m',\n", " [-np.expand_dims(file1.variables['deptht'][:], 1) * np.ones(284),\n", " (np.ones([284,40]) *np.expand_dims(file1.variables['nav_lat'][yslice,:][:],1)).T])\n", "i = 30\n", "density1 = calc_rho(file1.variables['vosaline'][i,:,yslice,60:137],\n", " file1.variables['votemper'][i,:,yslice,60:137],\n", " pressure1[:, 60:137])\n", "rho = 1023.3\n", "index1 = (np.abs(density1 - rho)).argmin(axis=0)\n", "list_of_depths1 = np.zeros((77))\n", "for x in range(77):\n", " list_of_depths1[x] = deptht[index1[x]]\n", "popt, pcov = curve_fit(func, np.arange(0,77), list_of_depths1)\n", "plt.plot(np.arange(0,77), list_of_depths1, 'r.')\n", "plt.grid('on')\n", "plt.ylim(50,0)\n", "plt.plot(np.arange(0,77), func(np.arange(0,77), *popt), 'b-')\n", "print(popt[0])" ] }, { "cell_type": "code", "execution_count": 241, "metadata": { "collapsed": false }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "0.205390441908\n" ] }, { "data": { "image/png": "iVBORw0KGgoAAAANSUhEUgAAAXQAAAD8CAYAAABn919SAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nXm2xRgAAAABJRU5ErkJggg==\n", "text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "yslice = 210\n", "deptht = file2.variables['deptht'][:]\n", "yslicemask = 1 - new_domain[:,yslice,:]\n", "pressure1 = gsw_calls.generic_gsw_caller('gsw_p_from_z.m',\n", " [-np.expand_dims(file2.variables['deptht'][:], 1) * np.ones(284),\n", " (np.ones([284,40]) *np.expand_dims(file2.variables['nav_lat'][yslice,:][:],1)).T])\n", "i = 24\n", "density1 = calc_rho(file2.variables['vosaline'][i,:,yslice,60:137],\n", " file2.variables['votemper'][i,:,yslice,60:137],\n", " pressure1[:, 60:137])\n", "rho = 1023.3\n", "index1 = (np.abs(density1 - rho)).argmin(axis=0)\n", "list_of_depths1 = np.zeros((77))\n", "for x in range(77):\n", " list_of_depths1[x] = deptht[index1[x]]\n", "popt, pcov = curve_fit(func, np.arange(0,77), list_of_depths1)\n", "plt.plot(np.arange(0,77), list_of_depths1, 'r.')\n", "plt.grid('on')\n", "plt.ylim(50,0)\n", "plt.plot(np.arange(0,77), func(np.arange(0,77), *popt), 'b-')\n", "print(popt[0])" ] }, { "cell_type": "code", "execution_count": 248, "metadata": { "collapsed": false }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "0.217622892644\n" ] }, { "data": { "image/png": "iVBORw0KGgoAAAANSUhEUgAAAXQAAAD8CAYAAABn919SAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz\nAAALEgAACxIB0t1+/AAAHiZJREFUeJzt3Xt4VeWZ9/HvnZBAIAqimAKiQEVUDoKhSCRpA0hrPXak\n1dra0uqUtmNb7XQ66lt9nXZmira+Dq1a22oZsaXiAetZeymSMdHUA0oFRNRWiloL1gExtBxzv388\na7OTcNg72Un22iu/z3Wta+dZh507G/hl8axnPcvcHRERKXxF+S5AREQ6hwJdRCQhFOgiIgmhQBcR\nSQgFuohIQijQRUQSIqdAN7OTzWyNmb1mZpd2VlEiItJ+1tFx6GZWDLwCzATeBJ4FznX3lzqvPBER\nyVYuZ+iTgdfc/Y/uvh1YBJzZOWWJiEh79crh2KHAGy3abwIntN3JzOYAcwDKysoqhw0b1qFv1tzc\nTFFRfLv8VV9uVF9uVF/u4lzjK6+88ld3H5RxR3fv0AJ8Eri5RftzwPX7O6aystI7aunSpR0+tjuo\nvtyovtyovtzFuUbgOc8il3P5dfQW0PJ0+7BonYiI5EEugf4sMMrMRphZKfBp4L7OKUtERNqrw33o\n7r7TzL4G/BYoBua7+6pOq0xERNoll4uiuPtDwEOdVIuIiOQgnpd0RUSk3RToIiIJoUAXEUkIBbqI\nSEIo0EVEEkKBLiKSEAp0EZGEUKCLiCSEAl1EJCEU6CIiCaFAFxFJCAW6iEhCKNBFRBJCgS4ikhAK\ndBGRhFCgi4gkhAJdRCQhFOgiIgmhQBcRSQgFuohIQijQRUQSQoEuIpIQCnQRkYRQoIuIJIQCXUQk\nIRToIiIJoUAXEUkIBbqISEIo0EVEEkKBLiKSEAp0EZGEUKCLiCSEAl1EJCEU6CIiCaFAFxFJiIyB\nbmbzzWyDma1ssW6gmT1qZq9Grwd1bZkiIpJJNmfotwAnt1l3KbDE3UcBS6K2iIjkUcZAd/cngP9t\ns/pMYEH09QLgE51cl4iItJO5e+adzIYDD7j72Ki9yd0HRF8bsDHV3suxc4A5ABUVFZWLFi1qd5EH\nrlpF2TPP8PfJk9k8Zky7j+8OTU1NlJeX57uMfVJ9uVF9uYl7fRDvGqdNm7bM3Sdl3NHdMy7AcGBl\ni/amNts3ZvM+lZWV3m5PPeVeVubNRUXuZWWhHUNLly7Ndwn7pfpyo/pyE/f63ONdI/CcZ5GxHR3l\nst7MBgNErxs6+D6Z1dXB9u1YczNs3x7aIiKyh44G+n3A7Ojr2cC9nVPOXtTWQmkpzUVFUFoa2iIi\nsodshi3eBjQCo83sTTO7ALgKmGlmrwInRe2uUVUFS5aw9vzzYcmS0BYRkT30yrSDu5+7j00zOrmW\nfauqYt22bYxUmIuI7JPuFBURSQgFuohIQijQRUQSojADvbER5s4Nr3tri4j0QBkvisZOYyPMmBHG\npJeWwrx5cPHF6bZGwohID1V4Z+jRjUbs2hVeFy9u3daNRyLSQxVeoEc3GlFcHF5nzWrd1o1HItJD\nFV6XS3SjEXV1IbyrqmDcuNbtxsb9t0VEEqjwAh1CKLcM5pZt9bGLSA9VeF0umaiPXUR6qOQFuvrY\nRaSHKswul/3Jpo9dRCSBkhfosP8+dtBFUhFJpGQG+v60vWiqi6QikhAF0Yf+/e/D178+kcsugwcf\nhE2bcnizthdNdZFURBKiIAJ90CBoboZrroHTToOBA+G44+DCC2HRInjzzXa8WduLprpIKiIJURBd\nLl/6Eowa9QKTJ9fyzDNQXw8NDXDrrfCTn4R9jjgCamqgujq8Hn00FO3t19XeLpqKiCRAQQR6St++\nIYNTJ9U7d8Lvfx/Cvb4eHn0UfvWrsG3gQJg6NR3ylZXhhBzY8yKpiEgCFFSgt9WrVwjqykq46CJw\nhz/8IYR76iz+/vvDvmVlcMIJ6TP4qio44ID81i8i0pkKOtDbMoMjjwzLF78Y1q1fnz6Db2gIF1ib\nm0N3zIQJ6YCvroYPfCC/9YuI5CJRgb43FRXhZtFZs0L7/ffh6afTZ/E33QQ//nHY9sEPtu6HHzUq\n/JIQESkEiQ/0tg44AE46KSwAO3bA8wtW0HD3BuqbJnL//QO55Zaw7dCDtlM9rZSaYa9Ts7OO4845\nml41mr1RROKpxwV6WyXPNXLCN2ZwwvbtfKu0FP+vebx80Y3Ubz+Bhs01NDxxOnf/dQQwgvIb3qfq\nmDepfvUxqpufYErpNfR9/AGFuojEQo8P9LY3Gtndizlm5wqO8eXM4WY4fgZvPbaahuYq6u3DNLx5\nMv+28zs4V9Br6w6OP/sdas6BAQMOYexYOOSQfP9AItJTFcSNRV0q0+yMs2YxtPdfOad4Mdf3+TbL\nr1nC//YZyoNFp/PtXvMoPbic666DK64Yy6BBcMwxMGdOGCP/+uth5I2ISHfQGXo2szO2aQ8YN45T\n6uo4pbYaqg5k61a46aYX2LJlIg0NcOed4WIrwJAhrS+0jh0bfleIiHQ2BTpknp0xQ7tPHxg37r3d\nNzw1N8OqVenhkvX1cPvtYVv//nDiiemA/9CHwvEiIrlSoHeGxkYOX7gQeveGqiqKisJJ/bhx8NWv\nhl3+9Kf0WPj6enj44bC+tDSEeirgTzwRDjoofz+KiBQuBXquoul4R2zbBgsX7nM63iOOCMt554X2\nu+/Ck0+mA/7aa+Hqq8O2sWNbd9MMG9aNP4+IFCwFeq6iUTLW3JyejjeLYYwHHwxnnBEWgL/9DZ55\nJgR8QwP88pdw441h2+GHtw74Y47Zx8RjItKjKdBzFY2Sad62jaIcpuPd28RjL76YPoN/7LHwHwDI\nMPGYiPRYCvRcRaNk1s6fz8jzz++0m4x69YLjjw/LN76Rnnis5bw0qYnH+vTZc+KxAw/slDJEpIAo\n0DtDVRXrtm1jZBfeMdpy4rEvfCGsW78+9MOnRtJcdRX853+G7pjjjkufwVdXd1lZIhIjCvSu0E1z\nvVRUwFlnhQVaTzzW0AA335yeeGzIkBOYOTMd8kcdVUATj7X9PDWXjsheZQx0MxsG3ApUAA783N1/\nZGYDgduB4cBa4Gx339h1pRaIPD6Eem8Tj73wQgj4e+5p4sEHy1iwIGwbNKj11METJ4Zunthp+3nO\nmwcXX6yHfIvsRTb/hHcC33L3583sAGCZmT0KfAFY4u5XmdmlwKXAJV1XaoHY20Oo8xQ4JSUweXJY\nKitX8ZGP1LJmTbqL5skn4Te/Cfv26wdTpoSAr6kJffL9+uWl7Nbafp6LF8fm8xWJm4yB7u5vA29H\nX79vZquBocCZQG202wKgDgV6em6Y1BlkjB5CbRaetXr00eE5rQBvvZXuh29ogO9+N1yATV2UTZ3F\nT50azuq7XdvPc9asUGwMP1+RfDNvx+xRZjYceAIYC6xz9wHRegM2ptptjpkDzAGoqKioXLRoUYcK\nbWpqory8vEPHdoeW9R24ahUDli9n04QJbB4zJs+VBdl+fk1Nxbz0Un9efLE/K1b0Z/XqA9mxIwx6\nHzbsb4wfv4mxY99j/Pj3GDx4a6f1w++vvrafZz4+30L6+xdHca8P4l3jtGnTlrn7pIw7untWC1AO\nLAPOitqb2mzfmOk9KisrvaOWLl3a4WO7Q1Lr27rVvaHBfe5c91NPdR8wwD2cw7sPGeJ+9tnu113n\n/sIL7jt3dn993UX15Sbu9bnHu0bgOc8ip7O6DGZmJcBiYKG73x2tXm9mg939bTMbDGxo728dib/e\nvUN3y9Spod3cDC+91HpemjvuCNsOPDDMRZO60Dp5siYeE+lO2YxyMeAXwGp3v7bFpvuA2cBV0eu9\nXVKhxEpRUZhrZuzY9MRj69alL7Q2NMB3vhPWl5bCpEmtJx4bODB/tYskXTYzgkwFPgdMN7Pl0XIK\nIchnmtmrwElRW/amsRHmzg2veWofvnBhl73/4W818tl1c/np7EZWroS/Pvws937uTi761Fu4w39d\n28zpp4f5a8aNg6+e9RcWnnMf636zLLv6uvrzzeL9c6ov13qzOL5T65PClU2/TGctPbIP/amn3MvK\n3IuLw+vPfpaXdnNRUd6+/5Y+A31p0XT/917/5h87dp0fwHu7++EPH7jZP1v8a/+JfdVX9j7ed93Y\n5vinntr/B5/r55vl++/z88t0fK71tn3/fRzfafV1kbj/+3WPd410Zh+65CDTOOpuau+eDTIP37/v\njveobX6cWvsfOOwpdr5cx4vNY3jSaqgvmcWSXbUs5FzYBgO/sZmpOwZTTT3V2xqZ9NgTlO5vnHmu\nn2+mcextZ9PMdRx8e+tt+/77OL7T6pOCpklYu1oWzyztjnZzUVFev3/Ldq/exRxf/CJf73MTd3zv\nZf7c54O8YqO4peRL/MPkP7PGRnMJP2Bqcz39/+PbfOQjcPnl8MgjsHlzJ3++mcaxp2bT3Nfn195x\n8O2tt+377+P4TqtPCprO0LtaB55Z2hXtVrNB5uH7769t48ZRPH8+s88/n9lVR0NjIxse+BEN5SfT\n8M7o3ROP7doVLsqOH5++0FpTU8XgXD/fLP789vv5dfXfhyyO77T6pLBl0y/TWUuP7EOPiUKv7/33\n3R97zP3KK91nzHDv2zc9Hn7kSPfZs91vvtn95Zfdm5u7v758U325i3ONqA9dkqS8PMzRNWNGaO/Y\nAcuXp4dKPvQQe0w8ljqLnzAhzGsjknQKdClIJSXh4dof+hD88z+Hc/VXXkmPh6+v33PisVTAT5kS\nk4nHRDqZAl0SwQxGjw7LP/5jWJeaeCx1R+v3vheCv7g4TDyWuqN16lQ49ND81i/SGRToklhDh8LZ\nZ4cF4L33wr02qYC/4Qa4Nrr3efTo1vPDjxxZQA8AEYko0KXH6N8fTj45LADbtsGyZekumsWL4Re/\nCNsGD24d8Lt25a9ukWwp0KXH6t07zC9z4olwySXpicdSZ/D19XDnnWHfvn2rdz/8IzXxWFlZfusX\naUuBLhI9o7SotpaxVVWMfb+Rr2ysg6/Vsm5oFQ0NcPvt6/njH4dy+eXhkNRF2epqqD7kZaZufpiB\np0zZ+zNPc30Gamcf39Xvp2e+5k82Yxs7a9E49PxRffuQaW6VaC6UVH3vvut+//3u//qv7iee6F7S\na9fu8fBjbKV/5cOr/FclX/C1RSO6Zu6XfRzf4bmEumkumrj//XOPd41kOQ5dt/5Lz5bNM0tbGDgQ\nTjsNrr46jKB574r/R13RdP6dyznM32Thk0dw3o7/ZnjzHzn87y/z2SuP5MatX2TlrqNp3rZjj/dr\nd325Hp/h58v5/XJ9f8mJAl16tkxzq2SYC6VsZjUf6f07Li++ikfK/oGN1/+aF3pP4cd2EVXFz7D0\n7yfwT34D41jJIc3rOf3BL/ODH8BTT4WLsu2ur7PnjunuuWikS6kPXXq2bOZWacfxxVVVTDhuLBPq\n6vh67VB8Sj9eX/w89bf/mYZtH6L+lQoeiB6l3qdPuLiaGk1TVRVG4mSsrzt/vo68n+aSyRsFukhV\nVevgadvO4XgDRn7yeEZ+8nhmR5s3bAgjaVLL1VfD978fxr2PH58eSVNTA0OGdKCezv752vt+ub6/\ndJgCXaSbHXoonHVWWACamuB3vwt98vX1MH8+XH992DZyZOvx8KNH64Yn2TcFukielZfDSSeFBdIT\nj6XGwz/8MNx6a9h2yCGtA37iRE08JmkKdJGYaTnx2De/mZ54rOUNT/fcE/bt2zdMNjZs2HB27gxf\nl5fnt37JHwW6SMy1nHjsggvCuj//Od1F09AAdXVHsGBBGFwycWLrs3hNPNZzKNBFCtCQIfCpT4UF\n4IEHGigpqdkd8D/9KcybF7YddVTrC62aeCy5FOgiCVBevovaWvjYx0J72zZ4/vl0N83dd+858Vgq\n4MePD2f2UvgU6CIJ1Lt3evTgt78dJh5bvTrdRdNy4rEDDgj7pSYf08RjhUuBLtIDFBXBmDFh+cpX\nwrp169Jj4evr4YorwvqSEpg0KX0GP3VqmPJA4k+BLtJDHX44fOYzYQHYuDFMSZAaSTNvHvzwh2Hb\nmDGtL7QecUT+6pZ9U6CLCAAHHQSnnhoWgL//HZ59Nh3wt90GP/tZ2DZsWOt++DFjwv8CJL8U6CKy\nV2Vl8OEPhwXCBIorVqS7aOrqQsgDDBgQumZSAT9pUujHl+6lQBeRrBQXw4QJYfna18INT6+/ng74\nhgZ48MGwb+/e4eJq+hF+GkbTHRToIj1dB59AZBbGtI8cCZ//fFj3zjutb3j6wQ+iiceYyvhRW6j5\nWD+qD32F6i2/ZeiZk7L7frm2M/280brDFy5MDw8qVNk8BaOzFj2xKH9UX24SW18Hn0CUraYlv/Ml\npSf7lXaln1T0mPfrvX33E55G2B/981PW+M9L/slXFx3rzX2y+P7tbbetd29PgIrWNRcVdewpTt2A\nLJ9YpDN0kZ6sI08gascZbL+nH2f6rkeZ7o9AUTE7aj7K7x9/l/rmE2nwGh5eNp1bd9wAwCFb36H6\nileo3nohNf4/TNz2IiWZ6mlvvft6AtT27Vhzc4d+xjjRdWmRnqyrn0AUvX9zURGUllLyqU8wqfcK\nvll8HYvLzmP9dXewpvd4brYvcVrxI6zwsfyL/5ATeIYBze8y40/zudK+x6NFH6Op5KDM9WWqd29P\ngGpTYyE/ZUln6CI9WVc/gSh6/7Xz5zPy/PP3eD+rquKo8eM4qq6OC2qPhKr+vH3/czTc9gYNO6dQ\n/9pQ/qP5Mpqb/w/FO5wJPzdqzjiN6uLfUf2Zw6k4dVL76t3XE6Da1ligFOgiPV1XP4Goqop127Yx\nMvUeGd5/8OmT+NTpk4jmHWPzZqOxERoajPp6+Om9Q5i39Sz4NYwaBTU1VdTUVFE9CD7oYJnq3dv2\ntjUWKAW6iMTagQeGScdSE49t3w7LlqWnLbjnnvCUJ4APfKD1Ha3HHdezJh7LGOhm1gd4Augd7X+X\nu19pZgOB24HhwFrgbHff2HWlioiEbu69TTzWcjz8XXeFfVMTj6VCfvLk8FCQpMrmDH0bMN3dm8ys\nBGgws4eBs4Al7n6VmV0KXApc0oW1iojsoeXEY1/+clj3xhutA/7KK8NgyZISqKxMT1tQXQ0HH5zf\n+jtTxkCPxkA2Rc2SaHHgTKA2Wr8AqEOBLiIxMGwYnHtuWCA98Vgq5H/8Y7jmmrDt2GPD2fvBB1cw\nYkSYtKxQHwBiIa8z7GRWDCwDjgRucPdLzGyTuw+IthuwMdVuc+wcYA5ARUVF5aJFizpUaFNTE+Ux\nflii6suN6suN6muf7duLePnlA1ixoj8rVvRn5cr+bNkSzm8HDdrKuHHv7V5GjNiS94nHpk2btszd\nJ2XcMZu7j1ILMABYCowFNrXZtjHT8bpTNH9UX25UX27iXt/One433fSMX3+9+znnuA8Z4rvvaB0w\nwP2UU9znznWvr3ffurX766Mr7hR1901mthQ4GVhvZoPd/W0zGwxsaN/vHBGReCguhiOP3EJtLVx4\nYYjytWtbP+HpoYfCvqmJx1IXWquqwmyTcZDNKJdBwI4ozMuAmcDVwH3AbOCq6PXerixURKS7mMGI\nEWFpOfFYyweA/PCHMHdu2Hf8+Nbzww8dmp+6szlDHwwsiPrRi4A73P0BM2sE7jCzC4A/AWd3YZ0i\nInk1aBCceWZYALZsgaefTp/B33IL3BCmpWH48PRY+JoaOPro7rnQms0olxeBiXtZ/y4woyuKEhGJ\nu379YPr0sADs3AnLl6cD/re/hV/+Mmw7+ODwMJCZM7u2Jt0pKiLSCXr1Ck9qmjQJLr449MO/9lq6\nH37kyG6ooeu/hYhIz2MW5poZNQrOP797vqemzxURSQgFuohIQijQRUQSQoEuIpIQCnQRkYRQoIuI\nJIQCXUQkIRToIiIJoUAXEUkIBbqISEIo0EUk2Robwzy3jY0dP6az211Ec7mISHI1NsKMGbB9O5SW\nwpIl4YkU7Tlm3rww21ZntbOpoYN0hi4iyVVXF4J0167wWlfX/mMWL+7cdjY1dJACXUSSq7Y2nBUX\nF4fX2tr2HzNrVue2s6mhg9TlIiLJVVUVujjq6kKQZtPVsbdjxo3r3HYXUaCLSLJVVbU/RNse09nt\nLqIuFxGRhFCgi4gkhAJdRCQhFOgiIgmhQBcRSQgFuohIQijQRUQSQoEuIpIQCnQRkYRQoIuIJIQC\nXUQkIRToIiIJoUAXEUkIBbqISEIo0EVEEkKBLiKSEFkHupkVm9kLZvZA1B5oZo+a2avR60FdV6aI\niGTSnjP0i4DVLdqXAkvcfRSwJGqLiEieZBXoZnYYcCpwc4vVZwILoq8XAJ/o3NJERKQ9zN0z72R2\nFzAXOAD4F3c/zcw2ufuAaLsBG1PtNsfOAeYAVFRUVC5atKhDhTY1NVFeXt6hY7uD6suN6suN6std\nnGucNm3aMneflHFHd9/vApwG/CT6uhZ4IPp6U5v9NmZ6r8rKSu+opUuXdvjY7qD6cqP6cqP6chfn\nGoHnPEO+uju9svjlMBU4w8xOAfoAB5rZr4D1ZjbY3d82s8HAhnb/2hERkU6TsQ/d3S9z98PcfTjw\naeBxdz8PuA+YHe02G7i3y6oUEZGMchmHfhUw08xeBU6K2iIikifZdLns5u51QF309bvAjM4vSURE\nOkJ3ioqIJIQCXUQkIRToIiIJoUAXEUkIBbqISEIo0EVEEkKBLiKSEAp0EZGEUKCLiCSEAl1EJCEU\n6CIiCaFAFxFJCAW6iEhCKNBFRBJCgS4ikhAKdBGRhFCgi4gkhAJdRCQhFOgiIgmhQBcRSQgFuohI\nQijQRUQSQoEuIpIQCnQRkYRQoIuIJIQCXUQkIRToIiIJoUAXEUkIBbqISEIo0EVEEkKBLiKSEAp0\nEZGEUKCLiCSEAl1EJCEU6CIiCdErm53MbC3wPrAL2Onuk8xsIHA7MBxYC5zt7hu7pkwREcmkPWfo\n09x9grtPitqXAkvcfRSwJGqLiEie5NLlciawIPp6AfCJ3MsREZGOyqrLBXDgMTPbBfzM3X8OVLj7\n29H2vwAVezvQzOYAc6Jmk5mt6WCthwB/7eCx3UH15Ub15Ub15S7ONR6RzU7m7pl3Mhvq7m+Z2aHA\no8DXgfvcfUCLfTa6+0EdrTaLGp5r0d0TO6ovN6ovN6ovd4VQYyZZdbm4+1vR6wbgN8BkYL2ZDQaI\nXjd0VZEiIpJZxkA3s35mdkDqa+CjwErgPmB2tNts4N6uKlJERDLLpg+9AviNmaX2/7W7P2JmzwJ3\nmNkFwJ+As7uuTAB+3sXvnyvVlxvVlxvVl7tCqHG/supDFxGR+NOdoiIiCaFAFxFJiIIIdDM72czW\nmNlrZpb3O1LNbL6ZbTCzlS3WDTSzR83s1ei1y4ZwZlHfMDNbamYvmdkqM7soTjWaWR8ze8bMfh/V\n99041RfVUmxmL5jZA3GrLapnrZmtMLPlZvZc3Go0swFmdpeZvWxmq82sKi71mdno6HNLLZvN7OK4\n1JeL2Ae6mRUDNwAfB44FzjWzY/NbFbcAJ7dZF6epEHYC33L3Y4EpwIXRZxaXGrcB0939OGACcLKZ\nTYlRfQAXAatbtONUW0qcp+P4EfCIux8NHEf4LGNRn7uviT63CUAl8DfCcOxY1JcTd4/1AlQBv23R\nvgy4LAZ1DQdWtmivAQZHXw8G1uS7xha13QvMjGONQF/geeCEuNQHHEb4Bz0deCCOf76ECfEOabMu\nFjUC/YHXiQZdxK2+NjV9FHgyrvW1d4n9GTowFHijRfvNaF3cZDUVQnczs+HAROBpYlRj1KWxnHBD\n2qPuHqf65gH/CjS3WBeX2lJS03Esi6bXgPjUOAJ4B/jvqNvq5ugelrjU19Kngduir+NYX7sUQqAX\nHA+/4vM+HtTMyoHFwMXuvrnltnzX6O67PPyX9zBgspmNbbM9L/WZ2WnABndftq998v3ZRaqjz+/j\nhC61D7fcmOcaewHHAze6+0RgC226L+LwGZpZKXAGcGfbbXGoryMKIdDfAoa1aB8WrYubWE2FYGYl\nhDBf6O53R6tjVSOAu28ClhKuScShvqnAGdEzABYB083sVzGpbTeP93QcbwJvRv/rAriLEPBxqS/l\n48Dz7r4+asetvnYrhEB/FhhlZiOi36ifJkw7EDexmQrBwm29vwBWu/u1LTbFokYzG2RmA6Kvywj9\n+y/HoT53v8zdD3P34YS/a4+7+3lxqC0l7tNxuPtfgDfMbHS0agbwEjGpr4VzSXe3QPzqa798d+Jn\neeHiFOAV4A/Ad2JQz23A28AOwtnIBcDBhAtprwKPAQPzWF814b+LLwLLo+WUuNQIjAdeiOpbCfzf\naH0s6mtRZy3pi6KxqQ0YCfw+Wlal/k3ErMYJwHPRn/E9wEExq68f8C7Qv8W62NTX0UW3/ouIJEQh\ndLmIiEgWFOgiIgmhQBcRSQgFuohIQijQRUQSQoEuIpIQCnQRkYT4/yadVQLGDa9nAAAAAElFTkSu\nQmCC\n", "text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "file3 = U72S\n", "yslice = 210\n", "deptht = file3.variables['deptht'][:]\n", "yslicemask = 1 - new_domain[:,yslice,:]\n", "pressure1 = gsw_calls.generic_gsw_caller('gsw_p_from_z.m',\n", " [-np.expand_dims(file3.variables['deptht'][:], 1) * np.ones(284),\n", " (np.ones([284,40]) *np.expand_dims(file3.variables['nav_lat'][yslice,:][:],1)).T])\n", "i = 18\n", "density1 = calc_rho(file3.variables['vosaline'][i,:,yslice,60:137],\n", " file3.variables['votemper'][i,:,yslice,60:137],\n", " pressure1[:, 60:137])\n", "rho = 1023.3\n", "index1 = (np.abs(density1 - rho)).argmin(axis=0)\n", "list_of_depths1 = np.zeros((77))\n", "for x in range(77):\n", " list_of_depths1[x] = deptht[index1[x]]\n", "popt, pcov = curve_fit(func, np.arange(0,77), list_of_depths1)\n", "plt.plot(np.arange(0,77), list_of_depths1, 'r.')\n", "plt.grid('on')\n", "plt.ylim(50,0)\n", "plt.plot(np.arange(0,77), func(np.arange(0,77), *popt), 'b-')\n", "print(popt[0])" ] }, { "cell_type": "code", "execution_count": 254, "metadata": { "collapsed": false }, "outputs": [ { "data": { "text/plain": [ "(78, 159)" ] }, "execution_count": 254, "metadata": {}, "output_type": "execute_result" }, { "data": { "image/png": "iVBORw0KGgoAAAANSUhEUgAAAXQAAAD8CAYAAABn919SAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nmwAAAABJRU5ErkJggg==\n", "text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "plt.contourf(lake_meshmask.variables['tmask'][0,:,190,:])\n", "plt.xlim(78,159)" ] }, { "cell_type": "code", "execution_count": 258, "metadata": { "collapsed": false }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "0.176430320264\n" ] }, { "data": { "image/png": "iVBORw0KGgoAAAANSUhEUgAAAXQAAAD8CAYAAABn919SAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nQmCC\n", "text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "file1 = U24S\n", "yslice = 190\n", "deptht = file1.variables['deptht'][:]\n", "yslicemask = 1 - new_domain[:,yslice,:]\n", "pressure1 = gsw_calls.generic_gsw_caller('gsw_p_from_z.m',\n", " [-np.expand_dims(file1.variables['deptht'][:], 1) * np.ones(284),\n", " (np.ones([284,40]) *np.expand_dims(file1.variables['nav_lat'][yslice,:][:],1)).T])\n", "i = 28\n", "density1 = calc_rho(file1.variables['vosaline'][i,:,yslice,78:159],\n", " file1.variables['votemper'][i,:,yslice,78:159],\n", " pressure1[:, 78:159])\n", "rho = 1023.3\n", "index1 = (np.abs(density1 - rho)).argmin(axis=0)\n", "list_of_depths1 = np.zeros((81))\n", "for x in range(81):\n", " list_of_depths1[x] = deptht[index1[x]]\n", "popt, pcov = curve_fit(func, np.arange(0,81), list_of_depths1)\n", "plt.plot(np.arange(0,81), list_of_depths1, 'r.')\n", "plt.grid('on')\n", "plt.ylim(50,0)\n", "plt.plot(np.arange(0,81), func(np.arange(0,81), *popt), 'b-')\n", "print(popt[0])" ] }, { "cell_type": "code", "execution_count": 266, "metadata": { "collapsed": false }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "0.219928277\n" ] }, { "data": { "image/png": "iVBORw0KGgoAAAANSUhEUgAAAXQAAAD8CAYAAABn919SAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nIhGhQBcRiQgFuohIRCjQRUQi4v8D35XtBK+vsQYAAAAASUVORK5CYII=\n", "text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "file1 = U48S\n", "yslice = 190\n", "deptht = file1.variables['deptht'][:]\n", "yslicemask = 1 - new_domain[:,yslice,:]\n", "pressure1 = gsw_calls.generic_gsw_caller('gsw_p_from_z.m',\n", " [-np.expand_dims(file1.variables['deptht'][:], 1) * np.ones(284),\n", " (np.ones([284,40]) *np.expand_dims(file1.variables['nav_lat'][yslice,:][:],1)).T])\n", "i = 23\n", "density1 = calc_rho(file1.variables['vosaline'][i,:,yslice,78:159],\n", " file1.variables['votemper'][i,:,yslice,78:159],\n", " pressure1[:, 78:159])\n", "rho = 1023.3\n", "index1 = (np.abs(density1 - rho)).argmin(axis=0)\n", "list_of_depths1 = np.zeros((81))\n", "for x in range(81):\n", " list_of_depths1[x] = deptht[index1[x]]\n", "popt, pcov = curve_fit(func, np.arange(0,81), list_of_depths1)\n", "plt.plot(np.arange(0,81), list_of_depths1, 'r.')\n", "plt.grid('on')\n", "plt.ylim(50,0)\n", "plt.plot(np.arange(0,81), func(np.arange(0,81), *popt), 'b-')\n", "print(popt[0])" ] }, { "cell_type": "code", "execution_count": 270, "metadata": { "collapsed": false }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "0.192798937461\n" ] }, { "data": { "image/png": "iVBORw0KGgoAAAANSUhEUgAAAXQAAAD8CAYAAABn919SAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\n8iSOHrSlmQAAAABJRU5ErkJggg==\n", "text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "file1 = U72S\n", "yslice = 190\n", "deptht = file1.variables['deptht'][:]\n", "yslicemask = 1 - new_domain[:,yslice,:]\n", "pressure1 = gsw_calls.generic_gsw_caller('gsw_p_from_z.m',\n", " [-np.expand_dims(file1.variables['deptht'][:], 1) * np.ones(284),\n", " (np.ones([284,40]) *np.expand_dims(file1.variables['nav_lat'][yslice,:][:],1)).T])\n", "i = 18\n", "density1 = calc_rho(file1.variables['vosaline'][i,:,yslice,78:159],\n", " file1.variables['votemper'][i,:,yslice,78:159],\n", " pressure1[:, 78:159])\n", "rho = 1023.3\n", "index1 = (np.abs(density1 - rho)).argmin(axis=0)\n", "list_of_depths1 = np.zeros((81))\n", "for x in range(81):\n", " list_of_depths1[x] = deptht[index1[x]]\n", "popt, pcov = curve_fit(func, np.arange(0,81), list_of_depths1)\n", "plt.plot(np.arange(0,81), list_of_depths1, 'r.')\n", "plt.grid('on')\n", "plt.ylim(50,0)\n", "plt.plot(np.arange(0,81), func(np.arange(0,81), *popt), 'b-')\n", "print(popt[0])" ] }, { "cell_type": "code", "execution_count": 283, "metadata": { "collapsed": false }, "outputs": [ { "data": { "text/plain": [ "(55, 124)" ] }, "execution_count": 283, "metadata": {}, "output_type": "execute_result" }, { "data": { "image/png": "iVBORw0KGgoAAAANSUhEUgAAAXQAAAD8CAYAAABn919SAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\n", "text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "plt.contourf(lake_meshmask.variables['tmask'][0,:,220,:])\n", "plt.xlim(55,124)" ] }, { "cell_type": "code", "execution_count": 289, "metadata": { "collapsed": false }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "0.0994924732031\n" ] }, { "data": { "image/png": "iVBORw0KGgoAAAANSUhEUgAAAXQAAAD8CAYAAABn919SAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nBbqISCAU6CIigVCgi4gEQoEuIhKI/weqclyYW3mkkwAAAABJRU5ErkJggg==\n", "text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "file1 = U24S\n", "yslice = 220\n", "deptht = file1.variables['deptht'][:]\n", "yslicemask = 1 - new_domain[:,yslice,:]\n", "pressure1 = gsw_calls.generic_gsw_caller('gsw_p_from_z.m',\n", " [-np.expand_dims(file1.variables['deptht'][:], 1) * np.ones(284),\n", " (np.ones([284,40]) *np.expand_dims(file1.variables['nav_lat'][yslice,:][:],1)).T])\n", "i = 34\n", "density1 = calc_rho(file1.variables['vosaline'][i,:,yslice,55:124],\n", " file1.variables['votemper'][i,:,yslice,55:124],\n", " pressure1[:, 55:124])\n", "rho = 1023.3\n", "index1 = (np.abs(density1 - rho)).argmin(axis=0)\n", "list_of_depths1 = np.zeros((69))\n", "for x in range(69):\n", " list_of_depths1[x] = deptht[index1[x]]\n", "popt, pcov = curve_fit(func, np.arange(0,69), list_of_depths1)\n", "plt.plot(np.arange(0,69), list_of_depths1, 'r.')\n", "plt.grid('on')\n", "plt.ylim(50,0)\n", "plt.plot(np.arange(0,69), func(np.arange(0,69), *popt), 'b-')\n", "print(popt[0])" ] }, { "cell_type": "code", "execution_count": 299, "metadata": { "collapsed": false }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "0.110232567362\n" ] }, { "data": { "image/png": "iVBORw0KGgoAAAANSUhEUgAAAXQAAAD8CAYAAABn919SAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nLYQ6AAAAAElFTkSuQmCC\n", "text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "file1 = U48S\n", "yslice = 220\n", "deptht = file1.variables['deptht'][:]\n", "yslicemask = 1 - new_domain[:,yslice,:]\n", "pressure1 = gsw_calls.generic_gsw_caller('gsw_p_from_z.m',\n", " [-np.expand_dims(file1.variables['deptht'][:], 1) * np.ones(284),\n", " (np.ones([284,40]) *np.expand_dims(file1.variables['nav_lat'][yslice,:][:],1)).T])\n", "i = 30\n", "density1 = calc_rho(file1.variables['vosaline'][i,:,yslice,55:124],\n", " file1.variables['votemper'][i,:,yslice,55:124],\n", " pressure1[:, 55:124])\n", "rho = 1023.3\n", "index1 = (np.abs(density1 - rho)).argmin(axis=0)\n", "list_of_depths1 = np.zeros((69))\n", "for x in range(69):\n", " list_of_depths1[x] = deptht[index1[x]]\n", "popt, pcov = curve_fit(func, np.arange(0,69), list_of_depths1)\n", "plt.plot(np.arange(0,69), list_of_depths1, 'r.')\n", "plt.grid('on')\n", "plt.ylim(50,0)\n", "plt.plot(np.arange(0,69), func(np.arange(0,69), *popt), 'b-')\n", "print(popt[0])" ] }, { "cell_type": "code", "execution_count": 310, "metadata": { "collapsed": false }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "0.104066641258\n" ] }, { "data": { "image/png": "iVBORw0KGgoAAAANSUhEUgAAAXQAAAD8CAYAAABn919SAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\n+H+WiBArJBFkgwAAAABJRU5ErkJggg==\n", "text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "file1 = U72S\n", "yslice = 220\n", "deptht = file1.variables['deptht'][:]\n", "yslicemask = 1 - new_domain[:,yslice,:]\n", "pressure1 = gsw_calls.generic_gsw_caller('gsw_p_from_z.m',\n", " [-np.expand_dims(file1.variables['deptht'][:], 1) * np.ones(284),\n", " (np.ones([284,40]) *np.expand_dims(file1.variables['nav_lat'][yslice,:][:],1)).T])\n", "i = 23\n", "density1 = calc_rho(file1.variables['vosaline'][i,:,yslice,55:124],\n", " file1.variables['votemper'][i,:,yslice,55:124],\n", " pressure1[:, 55:124])\n", "rho = 1023.3\n", "index1 = (np.abs(density1 - rho)).argmin(axis=0)\n", "list_of_depths1 = np.zeros((69))\n", "for x in range(69):\n", " list_of_depths1[x] = deptht[index1[x]]\n", "popt, pcov = curve_fit(func, np.arange(0,69), list_of_depths1)\n", "plt.plot(np.arange(0,69), list_of_depths1, 'r.')\n", "plt.grid('on')\n", "plt.ylim(50,0)\n", "plt.plot(np.arange(0,69), func(np.arange(0,69), *popt), 'b-')\n", "print(popt[0])" ] }, { "cell_type": "code", "execution_count": 302, "metadata": { "collapsed": false }, "outputs": [ { "data": { "text/plain": [ "10.56484414" ] }, "execution_count": 302, "metadata": {}, "output_type": "execute_result" } ], "source": [ "28.22991562 - 4.12965965 - 13.53541183" ] }, { "cell_type": "code", "execution_count": 322, "metadata": { "collapsed": false }, "outputs": [ { "data": { "text/plain": [ "(82, 165)" ] }, "execution_count": 322, "metadata": {}, "output_type": "execute_result" }, { "data": { "image/png": "iVBORw0KGgoAAAANSUhEUgAAAXQAAAD8CAYAAABn919SAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nABJBoANAIgh0AEgEgQ4Aifg/y2TQ8N3RKY4AAAAASUVORK5CYII=\n", "text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "plt.contourf(lake_meshmask.variables['tmask'][0,:,180,:])\n", "plt.xlim(82,165)" ] }, { "cell_type": "code", "execution_count": 329, "metadata": { "collapsed": false }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "0.189358095762\n" ] }, { "data": { "image/png": "iVBORw0KGgoAAAANSUhEUgAAAXQAAAD8CAYAAABn919SAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz\nAAALEgAACxIB0t1+/AAAHEhJREFUeJzt3XuUVOWZ7/Hv00XfoOUm2HILFwUUULk0TZfEsRE9aozi\naMYYo4fjJcy4PN7OuAyZZK2ZzBpHljEJOjFGjjIy0REdL5EwMYlB2kStBkHNUUDRIAqIoggiXrj1\nc/7YVXRVd0PtvlRX1+7fZ61a3ftS1W+/C379rHfv/b7m7oiISOEryncDRESkYyjQRUQiQoEuIhIR\nCnQRkYhQoIuIRIQCXUQkItoV6GZ2lpm9YWZvmdncjmqUiIi0nrX1PnQziwHrgTOAzcCLwLfcfW3H\nNU9ERMJqT4VeDbzl7hvcfS+wGJjVMc0SEZHW6tGO9w4BNqVtbwamNT3JzOYAcwDKy8unDBs2rE0/\nrKGhgaIiDflno34KT30VjvopnFz20/r16z9y94HZzmtPoIfi7guABQBVVVW+atWqNn1OXV0dtbW1\nHdiyaFI/hae+Ckf9FE4u+8nM3glzXnv+nGwB0svtocl9IiKSB+0J9BeB0WY20sxKgIuBJR3TLBER\naa02D7m4+34z+9/A74AYsNDd13RYy0REpFXaNYbu7r8BftNBbRERkXbQpWsRkYhQoIuIRIQCXUQk\nIhToIiIRoUAXEYkIBbqISEQo0EVEIkKBLiISEQp0EZGIUKCLiESEAl1EJCIU6CIiEaFAFxGJCAW6\niEhEKNBFRCJCgS4iEhEKdBGRiFCgi4hEhAJdRCQiFOgiIhGhQBcRiQgFuohIRCjQRUQiQoEuIhIR\nCnQRkYhQoIuIRIQCXUQkIhToIiIRoUAXEYkIBbqISEQo0EVEIkKBLiISEQp0EZGIUKCLiESEAl1E\nJCKyBrqZLTSzbWb2Wtq+/mb2tJm9mfzaL7fNFBGRbMJU6PcDZzXZNxdY5u6jgWXJbRERyaOsge7u\nfwQ+brJ7FrAo+f0i4PwObpeIiLSSuXv2k8xGAEvdfUJye6e7901+b8CO1HYL750DzAGorKycsnjx\n4lY3sveaNZSvXMkX1dXsGj++1e/vTnbv3k1FRUW+m1EQ1FfhqJ/CyWU/zZgxY7W7V2U7r92Bntze\n4e5Zx9Grqqp81apVWX9ehkQCZs7E9+zBSkth2TKIx1v3Gd1IXV0dtbW1+W5GQVBfhaN+CieX/WRm\noQK9rXe5fGBmg5I/aBCwrY2fk11dHezdizU0wN69wbaIiDTT1kBfAsxOfj8beLJjmtOC2looKaGh\nqAhKSoJtERFppke2E8zsIaAWGGBmm4F/BOYBj5jZlcA7wEU5a2E8DsuWsXHhQkZdcUWwnUgElXpt\nbfNtyDwmItJNZA10d//WIQ7N7OC2HFo8zrt79jAqFd4zZwbDLyUlMH8+3HBDsB2LgRns3x8c03i7\niHQjhfekaHJMnQMHgq+PPda4vW9f5jGNt4tIN1J4gZ4cUycWC75eeGHjdnFx5jGNt4tIN5J1yKXL\nSY6pZ4yTn3CCxtBFpNsrvECHIKjTw7ql7ZSmF1BFRCKqMAM9rKYXUHWRVEQirPDG0Fuj6QVUXSQV\nkQiLdqA3vYCqi6QiEmHRHnJp6QKqiEhERTvQofkFUxGRiIr2kIuISDeiQBcRiQgFuohIRHS/QE8k\n4NZbg68iIhFSEBdF334btmwpwz2YTLHN9KCRiERYQVTot90Gl15aw9FHw6xZMG8ePPssfPZZKz9I\nDxqJSIQVRIV+/fVQXr6e7dvHkEjAkiXB/lgMTjopKLJraoKvo0YdpopPPWiUqtD1oJGIREhBBPpx\nx8F5571Hbe0YAD76CFasCEZQ6uth0SK4667g3IEDG8M9HoepU6FXr+QHNX3QCILx9JZWPmrtykia\nBExE8qwgAr2pAQPgnHOCFwQjKGvWBJmaev3618GxWAxOPDE95OMcMzeO1R9m5aNs201XRmp6rsbm\nRSQPCjLQm0qF9oknwt/+bbBv+/bGKj6RgF/+Eu6+Ozg2cCDUHDmA+Jc3UuMvUL1nNb3SVz5quhJS\n0+2GhuCD3Fs+t65OgS4inS4Sgd6SI4+Er30teEGQtWvXplXxzwzl134LALGG/ZywbidxHiduzxPv\nsZpjLrgQ+9OfGqvuCy+E1HbTCj39mMbmRSRPIhvoTcViwcJGJ5wAc+YAlPPx715kxUMbSBRNp37z\nUB78+Aru/mwO7IEBP4Cayd+gpuerxM8dQPUl46k43MpI6cdUnYtIHnSbQG9J/zOncvaZUzk7uX3g\nQA/WrUsfi+/P0udPhaeh6AY44YQ4NTVx4uuDzB49N954R03TScB0AVVEOlm3DvSmYjGYMCF4fec7\nwb4dOzLH4h96CO65Jzh25JGZd9RUV0NFBZkPMOkCqoh0EgV6Fv36wVlnBS8IxuLXrQtul0yF/H//\nd3CsqCj4YxAvKyX+5TeJ+/OMPvBWUMXrAqqI5JgCvZXSq/irrgr27dyZWcUvfuFE7vF/B6A/26mx\nlcRJEI+tovqcv+EIXUAVkRxQoHeAvn3hzDODF0BDQw/WPfQK9Y9vIbGvisRrp/Kbt8+GvVB0I0wY\ndRHx/m9Qc0Zv4v2PZUx756gREUGBnhNFRTD+2xMZ/+2JXJncl6rig6GaXiyun8w9K4FbgmGdpmPx\nvXvn8zcQkUKkQO8kzat4eP315DDNkx+QWFHEU08NBMDMmVD5IfFpTs34T4l/vowx3ziRoukaaxeR\nQ1Og50lREYwbB+M+SXDltcEdMTvLBrJizn3U//wlEu9P5ZEnq1nw5LHAsfSb/zHTanYQP7vfwSq+\nT598/xYi0pUo0PMtbUrfvnzIma/fwZm+DDhAA0W8wVgS1FBvcRJvz+Kf/omD88KPG9c4TBOPw9ix\nef5dRCSvFOj51nRK37RpBIpiMY63DRy/fz1XlCyGJybwybijWLmy8Y6aRx+Fe+8NPqpvXxg9+kTO\nOScI+GnTVMWLdCcK9HxrOqVv02kEIONYH+CMM4IXBGPx69c3Bvwf/lDCD3/YvIpPXXQ97rhguEdE\nokeB3hU0nTagpe1DKCoKQvq44+Dyy6GubhWTJ9dmVPGPPZZZxU+b1vgjVMWLRIcCvdBkWXTjKw8+\nSO/SUk4/Pc7pvRLQo46G79ey/sj4wQVBEgkyqvjjj8+s4o8/XlW8SCHKGuhmNgz4D6AScGCBu99h\nZv2Bh4ERwEbgInffkbumSrNFrltYdGPkvn3w4IMZx4pKSjhu2TKOuzzO5ZcHH7VrF7z4YmMV/8QT\ncN99wbE+fYLKPRXwNTVBZS8iXVuYCn0/8Pfu/pKZHQGsNrOngf8FLHP3eWY2F5gLfDd3TZVmi1y3\nsOiGhZwzpnfv4G/DzJnBtnswFp8+R82//EvjWh6pKj71UhUv0vVkDXR33wpsTX7/qZmtA4YAs4Da\n5GmLgDoU6Ll1mDtiUhV6w759FLVh0Q2z4LbHsWNh9uxg36efwsqVjSH/q1/BwoXBsd69m4/F9+uX\n099eRLIwdw9/stkI4I/ABOBdd++b3G/AjtR2k/fMAeYAVFZWTlm8eHGbGrp7924qKira9N4o6b1m\nDX1feYWdEyeya/z4jG2A8pUr+aK6utmxXePHt/tnu8PmzeWsWdObtWv7sHZtb95+uxcNDcFENMOH\nf8bxx+9i/PhdjBu3i+HDPyMWa/ePzRn9mwpH/RROLvtpxowZq929Ktt5oQPdzCqAZ4Fb3P1xM9uZ\nHuBmtsPdD1ujVVVV+apVq0L9vKbq6uqo1cyEWXV2P336aTAWnz5Us317cOyII5pX8f37d1rTstK/\nqXDUT+Hksp/MLFSgh7rLxcyKgceAB9398eTuD8xskLtvNbNBwLa2N1cK1RFHwGmnBS8Iqvi33soM\n+FtuaRyLHzs2cyx+3Di6dBUvUkjC3OViwH3AOnf/SdqhJcBsYF7y65M5aaEUFDMYPTp4XXZZsG/3\n7sw7apYuhfvvD46lqvj0O2q6UhUvUkjCVOjTgcuAV83sleS+fyAI8kfM7ErgHeCi3DRROkyWe9gP\nu+5pW8+Nx6l4NcGM+jpmzKiFGeDL6/jL6LNIfDnpYMj/679mVvHpAT9hQhuq+CxtIpHgKw8+CKWl\nWjFKosPdO+01ZcoUb6vly5e3+b3dySH76YUX3MvL3WOx4Os99zRul5S4l5a2fKw952Z77wsvHGze\np5+6P/OM+y23uJ97rvuAAe7BAI57RYX7aae5f//77kuXun/0UZZOONzvmrbdUFTUrB3SnP7vhZPL\nfgJWeYiM1ZOi3UWIe9gPue5pW8/N9t60e+MrKmDGjOCVOmXDhsZhmvp6mDcv+BiAMWMyFwXJqOIP\n97umbVtDg9Z1lUjRoyHdReoe9lis8R721HZx8aGPtefcbO89zB0BZnDMMXDppXDXXbB6NXzySZC9\nt94azF3z1FNw9dUwcWLwJOvMmfCDH8DS4vP5qHhQ1jY1FBVpXVeJFFXo3UUrZ3XMONaec7O9txV6\n9YJTTw1e0FjFp99RE1TxxwObGH3kx8Sr9xNvOIr4L6YxYdNTxE479WCbNi5cyKgrrlB1LpHRqgeL\n2kv3oeded++nzz6DVasyh2q2JW+o7dUrWOkpdbH1wIHnOf/86fltcAHo7v+mwiqY+9BFCkVLVfzG\njY0Bn0jAbbfB/v0A0zn22MyZJk84AXrof4UUKP3TlUgzg5Ejg9cllwT7Pv88GJN/4IG/sG3bMfz+\n9/DLXwbHevWCqVMbL7bW1MDAgflrv0hrKNCl2+nZE045BQ4c2ERt7TEZVXxqPP5HP0pV8cHF2fSn\nW1XFS1elf5bS7R2uik8N0zz9NDzwQHCsZ8/mVfxRR+Wv/SIpCnSRFqSq+FNOCbbd4Z13Mu+ouf32\nxip+1KjmVXxxcf7aL92TAl0kBDMYMSJ4XXxxsO+LLxqr+Pp6eOaZYLEoCP4gVFVlhryqeMk1Bbrk\nVwfOGdNsuyPacJg2lcfjfDWW4Kv76+CmWrwmzrtPrCbxyCYSDdNIbBzEj29vYP+B4Pm9UYO/pGbg\nX4jP7En8kpGc+Hk9xc8t7/jfvTXvDXFuxpw3be1j6Rxh5gfoqJfmcsm9guqnjppfpqXtEPOzLF++\nPPS8L21t0+dl/fy5olP8R7Hv+gVFj/sgthyco6acz/yveNZv7nG7P3H1b/39suEdP19OB5x7cM6b\nNvRxd6K5XKR766j5ZUKsodqmNnRAm8r37WJ6w5+Ybs8Fb8V5t2gk9ROuIvFqLxJew0/3X8ttd5cA\nGxnB28QPJIhTT5wXOGnPaxS3Z76cDjj34Jw3be1j6TSay0Xyp6Pml2lpO+wTe4drQw7msbFYjOGl\n7/PNawYwv+x7rIhNZ1dZJc/f/CS395jLFF7iWU7lOu5kKqvo3bCDUzbcz812G08UXcD7xcM6ro0h\nzz04501b+1g6jSp0yZ+OnF+mpe2OaEMu57FJHiurreXkeJyTzz8qeXwwmz54n8TD75LwaSQ2Dmb+\nxhv4UcP/gS9hxK0Q/+oF1JS+TPz8Sib+zxMpzuG8PBlz3rSlj6XTaC6XiFE/hVdIffXll/DSS5m3\nTW7ZEhwrK2t+R83RR3fczy6kfsonzeUiIqGUlcHJJwevlE2bMp9uveOO4AlXCG6vTF/1aeLEYJRE\nok2BLlKghg0LXhclF3/cswdefrmxgn/uOVi8ODhWVgZTpmQuCjJ4cP7aLrmhQBeJiNLSILBrauDG\nG4N9mzdnDtP827/Bj38cHPvKVzKHaVTFFz4FukiEDR0K3/hG8ILMKr6+Hl54AR5+ODhWWhpU8ekh\nryq+sCjQRbqR9Co+ZcuWzPnim1bxxxwzjldeaaziS0vz03bJToEu0s0NGdK8in/llcahmrq63ixf\nHhwrLYXJkzOr+CFD8td2yaRAF5EMpaUwbVrwuv56qKurZ8yY2oxl/e66C37yk+D8oUMzA37SJFXx\n+aJAF5GsBg8OHhS98MJge+/eoIpPD/n/+q/gWElJ8yp+6ND8tb07UaCLSKuVlAQLbldXB1U8wHvv\nZd5R8/Ofw09/GhxLr+JraoLAVxXf8RToItIhBg+GCy4IXhBU8X/+c+YF1/QqftKkzCp+2LD8tT0q\nFOgikhMlJcFSfVOnwnXXBfu2bs2s4n/xC5g/Pzg2eHBmwE+eHDwQJeEp0EWk0wwaBH/918ELYN++\n5lX8Y48Fx4qLG8fiU0+4DhsWrB4lLVOgi0jbdMAqSsW1tVTF41TtS3Dt7jq4tpb3R8apv/91Ek/t\nIPHJeH7x8wrmzw9m+h48GOJjthMvf4WaWZVMmT2Bspe7xkpPh13ZqbNWegqzCkZHvbRiUe6pn8JT\nX4XTYj/leKWn9PfuLenlLxZV+53FN/ol1et9pG04uOpTcWy/V9tKv87u8Idi3/aNJaO9oSg/Kz0d\ncmWnDljpCa1YJCI5k+OVntLfW8w+qnwlVbaaa/uugaJlvH9gACuK4iSGXUxi4yD+L1dx54Hr4AAM\n4j1qvlhB/PaPiO+ZypSGlZR3wkpPh1zZqRNXetKKRSLSep280lPTY0fHPmJW6e+Y971PeLb8LD4p\n6s/qHtP4WY/rOc2W82c7iZvf/A6nNDxLHz6huqGe6/ffzuKiS3inaCRe3PErPR1yZadOXOlJFbqI\ntF4XWOkpfbu4ro7JtbVMBq6pq4PaUXwwahT1979O/VMfk9g1nnvr+3Dnvv8AYFDFXmp+W0L8ijOJ\n7/sjU741hvLShna16bArO3XSSk9asShi1E/hqa/CiUo/7dsHr76aeUfNhg3BsR49Gu+LT91RM3x4\n6+6o0YpFIiKdJHUb5OTJcM01wb5t24L74lP3xt97L9x5Z3Ds6KMzFwSZMgV69sxf+8PIGuhmVgb8\nEShNnv+ou/+jmfUHHgZGABuBi9x9R+6aKiLSsY46Cs47L3gB7N8fVPHpDz/96lfBsR494KSTMh9+\nGjGia90XH6ZC3wOc5u67zawYeM7MngIuAJa5+zwzmwvMBb6bw7aKiORUauhl0iS4+upg34cfZgb8\nwoXws58FxyorG4dpysr6UF2d3yo+a6An74HcndwsTr4cmAXUJvcvAupQoItIxAwcCOeeG7wgqOJf\ney1zLD6o4idx002NVXxquGbkyM6r4kNdFDWzGLAaOBa4y92/a2Y73b1v8rgBO1LbTd47B5gDUFlZ\nOWVxatXaVtq9ezcVFRVtem93on4KT30Vjvopu507i3nppWI2bKhk7drevP76EXzxRVAv9+u3l3Hj\ndnHZZRsZO3Z3lk9q2YwZMzruoqi7HwAmmllf4Akzm9DkuJtZi38Z3H0BsACCu1zaehU4Klfac039\nFJ76Khz1Uzh9+9bxz/88HAieIWqs4ktIJAYwefIApk7NbRtadZeLu+80s+XAWcAHZjbI3bea2SBg\nW05aKCJSYGKxYOjlpJPg7/6u835u1idFzWxgsjLHzMqBM4DXgSXA7ORps4Enc9VIERHJLkyFPghY\nlBxHLwIecfelZpYAHjGzK4F3gIty2E4REckizF0u/w+Y1ML+7cDMXDRKRERaT5NziYhEhAJdRCQi\nFOgiIhGhQBcRiQgFuohIRCjQRUQiQoEuIhIRCnQRkYhQoIuIRIQCXUQkIhToIiIRoUAXEYkIBbqI\nSEQo0EVEIkKBLiISEQp0EZGIUKCLiESEAl1EJCIU6CIiEaFAFxGJCAW6iEhEKNBFRCJCgS4iEhEK\ndBGRiFCgi4hEhAJdRCQiFOgiIhGhQBcRiQgFuohIRCjQRUQiQoEuIhIRCnQRkYhQoIuIRIQCXUQk\nIkIHupnFzOxlM1ua3O5vZk+b2ZvJr/1y10wREcmmNRX69cC6tO25wDJ3Hw0sS26LiEiehAp0MxsK\nnAPcm7Z7FrAo+f0i4PyObZqIiLSGuXv2k8weBW4FjgBucvevm9lOd++bPG7AjtR2k/fOAeYAVFZW\nTlm8eHGbGrp7924qKira9N7uRP0UnvoqHPVTOLnspxkzZqx296ps5/XIdoKZfR3Y5u6rzay2pXPc\n3c2sxb8M7r4AWABQVVXltbUtfkRWdXV1tPW93Yn6KTz1VTjqp3C6Qj9lDXRgOnCemX0NKAN6m9kD\nwAdmNsjdt5rZIGBbLhsqIiKHl3UM3d2/5+5D3X0EcDHwjLtfCiwBZidPmw08mbNWiohIVu25D30e\ncIaZvQmcntwWEZE8CTPkcpC71wF1ye+3AzM7vkkiItIWelJURCQiFOgiIhGhQBcRiQgFuohIRCjQ\nRUQiQoEuIhIRCnQRkYhQoIuIRIQCXUQkIhToIiIRoUAXEYkIBbqISEQo0EVEIkKBLiISEQp0EZGI\nUKCLiESEAl1EJCIU6CIiEaFAFxGJCAW6iEhEKNBFRCJCgS4iEhEKdBGRiFCgi4hEhAJdRCQiFOgi\nIhGhQBcRiQgFuohIRCjQRUQiQoEuIhIRCnQRkYhQoIuIRIQCXUQkIhToIiIRoUAXEYmIHmFOMrON\nwKfAAWC/u1eZWX/gYWAEsBG4yN135KaZIiKSTWsq9BnuPtHdq5Lbc4Fl7j4aWJbcFhGRPGnPkMss\nYFHy+0XA+e1vjoiItFWoIRfAgT+Y2QHgHndfAFS6+9bk8feBypbeaGZzgDnJzd1m9kYb2zoA+KiN\n7+1O1E/hqa/CUT+Fk8t+Gh7mJHP37CeZDXH3LWZ2FPA0cC2wxN37pp2zw937tbW1IdqwKm24Rw5B\n/RSe+ioc9VM4XaGfQg25uPuW5NdtwBNANfCBmQ0CSH7dlqtGiohIdlkD3cx6mdkRqe+B/wG8BiwB\nZidPmw08matGiohIdmHG0CuBJ8wsdf5/uvtvzexF4BEzuxJ4B7god80EYEGOPz8q1E/hqa/CUT+F\nk/d+CjWGLiIiXZ+eFBURiQgFuohIRBREoJvZWWb2hpm9ZWZ6IjXJzIaZ2XIzW2tma8zs+uT+/mb2\ntJm9mfyas9tJC4mZxczsZTNbmtxWPzVhZn3N7FEze93M1plZXP3UnJndmPw/95qZPWRmZV2hn7p8\noJtZDLgLOBsYB3zLzMblt1Vdxn7g7919HFADXJPsG03L0LLrgXVp2+qn5u4AfuvuxwEnEfSX+imN\nmQ0BrgOq3H0CEAMupgv0U5cPdIJ73t9y9w3uvhdYTDDtQLfn7lvd/aXk958S/OcbgqZlaMbMhgLn\nAPem7VY/pTGzPsBfAfcBuPted9+J+qklPYByM+sB9ATeowv0UyEE+hBgU9r25uQ+SWNmI4BJwApC\nTsvQzcwHbgYa0vapnzKNBD4E/j05NHVv8tkT9VOa5IOWtwPvAluBT9z993SBfiqEQJcszKwCeAy4\nwd13pR/z4L7Ubn1vqpl9Hdjm7qsPdY76CQiqzsnA3e4+CfiMJsMG6idIjo3PIvgDOBjoZWaXpp+T\nr34qhEDfAgxL2x6a3CeAmRUThPmD7v54cremZcg0HTgvOa//YuA0M3sA9VNTm4HN7r4iuf0oQcCr\nnzKdDrzt7h+6+z7gceBkukA/FUKgvwiMNrORZlZCcPFhSZ7b1CVY8PjufcA6d/9J2iFNy5DG3b/n\n7kPdfQTBv59n3P1S1E8Z3P19YJOZjU3umgmsRf3U1LtAjZn1TP4fnElw/Srv/VQQT4qa2dcIxkBj\nwEJ3vyXPTeoSzOyrwJ+AV2kcG/4HgnH0R4CvkJyWwd0/zksjuxgzqwVucvevm9mRqJ8ymNlEggvH\nJcAG4HKCwk/9lMbMfgh8k+BOs5eBq4AK8txPBRHoIiKSXSEMuYiISAgKdBGRiFCgi4hEhAJdRCQi\nFOgiIhGhQBcRiQgFuohIRPx/neCnjx/w0AwAAAAASUVORK5CYII=\n", "text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "file1 = U24S\n", "yslice = 180\n", "deptht = file1.variables['deptht'][:]\n", "yslicemask = 1 - new_domain[:,yslice,:]\n", "pressure1 = gsw_calls.generic_gsw_caller('gsw_p_from_z.m',\n", " [-np.expand_dims(file1.variables['deptht'][:], 1) * np.ones(284),\n", " (np.ones([284,40]) *np.expand_dims(file1.variables['nav_lat'][yslice,:][:],1)).T])\n", "i = 31\n", "density1 = calc_rho(file1.variables['vosaline'][i,:,yslice,82:165],\n", " file1.variables['votemper'][i,:,yslice,82:165],\n", " pressure1[:, 82:165])\n", "rho = 1023.3\n", "index1 = (np.abs(density1 - rho)).argmin(axis=0)\n", "list_of_depths1 = np.zeros((83))\n", "for x in range(83):\n", " list_of_depths1[x] = deptht[index1[x]]\n", "popt, pcov = curve_fit(func, np.arange(0,83), list_of_depths1)\n", "plt.plot(np.arange(0,83), list_of_depths1, 'r.')\n", "plt.grid('on')\n", "plt.ylim(50,0)\n", "plt.plot(np.arange(0,83), func(np.arange(0,83), *popt), 'b-')\n", "print(popt[0])" ] }, { "cell_type": "code", "execution_count": 335, "metadata": { "collapsed": false }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "0.19253433918\n" ] }, { "data": { "image/png": "iVBORw0KGgoAAAANSUhEUgAAAXQAAAD8CAYAAABn919SAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nxMT/B+Cazc17x2/5AAAAAElFTkSuQmCC\n", "text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "file1 = U48S\n", "yslice = 180\n", "deptht = file1.variables['deptht'][:]\n", "yslicemask = 1 - new_domain[:,yslice,:]\n", "pressure1 = gsw_calls.generic_gsw_caller('gsw_p_from_z.m',\n", " [-np.expand_dims(file1.variables['deptht'][:], 1) * np.ones(284),\n", " (np.ones([284,40]) *np.expand_dims(file1.variables['nav_lat'][yslice,:][:],1)).T])\n", "i = 25\n", "density1 = calc_rho(file1.variables['vosaline'][i,:,yslice,82:165],\n", " file1.variables['votemper'][i,:,yslice,82:165],\n", " pressure1[:, 82:165])\n", "rho = 1023.3\n", "index1 = (np.abs(density1 - rho)).argmin(axis=0)\n", "list_of_depths1 = np.zeros((83))\n", "for x in range(83):\n", " list_of_depths1[x] = deptht[index1[x]]\n", "popt, pcov = curve_fit(func, np.arange(0,83), list_of_depths1)\n", "plt.plot(np.arange(0,83), list_of_depths1, 'r.')\n", "plt.grid('on')\n", "plt.ylim(50,0)\n", "plt.plot(np.arange(0,83), func(np.arange(0,83), *popt), 'b-')\n", "print(popt[0])" ] }, { "cell_type": "code", "execution_count": 339, "metadata": { "collapsed": false }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "0.16143727174\n" ] }, { "data": { "image/png": "iVBORw0KGgoAAAANSUhEUgAAAXQAAAD8CAYAAABn919SAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nRU5ErkJggg==\n", "text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "file1 = U72S\n", "yslice = 180\n", "deptht = file1.variables['deptht'][:]\n", "yslicemask = 1 - new_domain[:,yslice,:]\n", "pressure1 = gsw_calls.generic_gsw_caller('gsw_p_from_z.m',\n", " [-np.expand_dims(file1.variables['deptht'][:], 1) * np.ones(284),\n", " (np.ones([284,40]) *np.expand_dims(file1.variables['nav_lat'][yslice,:][:],1)).T])\n", "i = 21\n", "density1 = calc_rho(file1.variables['vosaline'][i,:,yslice,82:165],\n", " file1.variables['votemper'][i,:,yslice,82:165],\n", " pressure1[:, 82:165])\n", "rho = 1023.3\n", "index1 = (np.abs(density1 - rho)).argmin(axis=0)\n", "list_of_depths1 = np.zeros((83))\n", "for x in range(83):\n", " list_of_depths1[x] = deptht[index1[x]]\n", "popt, pcov = curve_fit(func, np.arange(0,83), list_of_depths1)\n", "plt.plot(np.arange(0,83), list_of_depths1, 'r.')\n", "plt.grid('on')\n", "plt.ylim(50,0)\n", "plt.plot(np.arange(0,83), func(np.arange(0,83), *popt), 'b-')\n", "print(popt[0])" ] }, { "cell_type": "code", "execution_count": 346, "metadata": { "collapsed": false }, "outputs": [ { "data": { "text/plain": [ "(95, 176)" ] }, "execution_count": 346, "metadata": {}, "output_type": "execute_result" }, { "data": { "image/png": "iVBORw0KGgoAAAANSUhEUgAAAXQAAAD8CAYAAABn919SAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz\nAAALEgAACxIB0t1+/AAAFRxJREFUeJzt3X+s3XV9x/HXi15aOgv1VqSrlcq1w5uRJhTTEYNzKJYO\nm2VIyZzEdEzN6pbJNGE/mCZKYpagE/ljMZgSwaZjKBEYzKAWCY6QOlglFYtwAwgipbRzXKHdOn7d\n9/4439OeXs6559f3nO/nfO7zkdzcc77n3HvePaf3dT7n/f18P19HhAAAo++4qgsAAJSDQAeATBDo\nAJAJAh0AMkGgA0AmCHQAyASBDgCZINABIBMEOgBkYmyYD7bwuMWxeOykYT4kAIy8F1858KuIeHO7\n+w010BePnaRzTvnjYT5k8g6vWVl1CaVavGdvTz831/PQ6+8EcvG9vf/0i07uN9RAx7EOr1mp6cmF\nOrh6pupSSnHiE8dJWtlTALd6Hk584jgt3lNCccA8QKBXqB5iSyZeqLqUUhzUUkkLuw7gZy+eaPk8\nHNRSHV7T25sEMN8Q6BU5vGalDq6e0aZzH6i6lPKskm7V2V0FcP15WDLxgjasmnrd7Ts0qenJcfU6\n8gfmEwK9AofXrNTTG8e0ZOIFbR7fWXU5pdoxMamnNy7Vqg4CuN5yWjIxre1n3tD6d66f1LTGab0A\nbRDoA9ZsZ189xJqNSEfdhlVTx4yq5zI9uVCxfu7nof6Gd+vqs/XsxRMan3r5mNsZtQNHEegDNj25\n8HXbDq6e0aZVU9mNzqVjA1h6/b+9UafPw+bxndoxMXmkR38sWjFAHYE+QPWdfbNtOveBLMO8bvP4\nTuncWj99Lt20nLafeYM266NFqB91cPVYR+0dYD4g0AekcWffbDmHeV19VD2XufrmzdTbObOx0xSo\nIdAHoHFn34ZMWyud6Daw29k8vvN1z+X26XOOtHfYaYr5jrVcBqA+v3w+h/mwbB7fqU3nPqCDq2ey\nO+oW6BYj9JI1zi8nzIej3t6pT5fsFq0a5IJAL1HO88tTd+x0yW7Rf0ceCPSSzO6bY7jqb6A71s+9\nI7aZabFTFXkg0EtS75vnOr98FPT6vHMkKnJBoJeAvnk6en3+60eivuWWJ0uuCBieeR/oZcyMoG8+\n2hqPRO3k/wOtGaRqXgd6ve/dL/rmo69+JGpnO1XptyNNbQPd9gmS7pW0qLj/tyPi87avlPRnkv6r\nuOtnIuLOQRVatvqMFKn/k0vQN8/DhlVT2rF+UoeeXNrmngtFqCNFnYzQX5J0XkQcsn28pPtsf7e4\n7ZqI+PLgyhuMxhkp/eLgoXwcmSnTZHmBRjEhdqIiSW0DPSJC0qHi6vHFVwyyqEFrnJHSL8I8L52+\nnuxERYo66qHbXiDpx5J+S9JXI+J+2x+QdJntP5G0S9LlEdH/kHfAmJGCdjr5f9G4E5XWC1LR0Vou\nEfFaRKyV9FZJZ9teI+laSW+XtFbSPklXN/tZ21ts77K96+WZwyWV3RuO5ERZtp95g5ZMvKDpyYWs\nIYNkdLU4V0T8WtI9ki6IiP1F0M9Iuk5qvvh1RGyNiHURsW7hcYv7r7hHR/vmzc9dCXRrw6opHVw9\nU8pMKaAMbQPd9pttv7G4vFjS+ZIetb2i4W4XSUp6FxErIKJsrPSI1HTSQ18haVvRRz9O0s0R8R3b\n222vVW0H6VOSPjG4MvtD3xyDMnulR/rpqFIns1weknRWk+2bB1JRyeibY9BmnxibUEdVsj9SlBUQ\nMWizT4zN/HRUJeszFtVP0kzfHINGPx0pyDbQG0/STJhjGDaP79SSiRf09MYxQh2VyDLQG6coln2i\nYmAuG1ZNMT8dlcmyhz49uVCxnr45ho9+OqqU3QidvjmqRj8dVckq0OmbIxX001GFbAKdvjlSQz8d\nw5ZND52+OVJDPx3DlsUInb45UkU/HcM08oFO3xypq/fTab1g0EY+0OtLl9JqQcrqS+0CgzTygQ4A\nqCHQASATBDoAZIJAB4BMEOgAkImRPrCIKYsYFamfqq6X6ZSp/RswwoF+9FD/aQ71x0hI9VR19b+l\nbk1PTugttzw5gIrQq7aBbvsESfdKWlTc/9sR8XnbyyR9S9Jpqp0k+kMRMT24Uo/Fof4YNSkuBVAP\n817nyB9ek84bEzobob8k6byIOGT7eEn32f6upE2S7o6Iq2xfIekKSX83wFqPqB/qv4lD/TFiNo/v\nlM6VbtXZSYRhfWC0pOefT+vTxnzXNtAjIiQdKq4eX3yFpAslvbfYvk3SDzWEQKdvjlGXSj+934HR\n9ulzkvq0gQ5nudheYHu3pAOS7oqI+yUtj4h9xV2ek7R8QDUewRK5yEW9VdhL77oMZQyMWHgsPR3t\nFI2I1ySttf1GSbfZXjPr9rAdzX7W9hZJWyTphAUn9lUsfXOge83CtqwJBVV+2qjyTSTVFlNXs1wi\n4te275F0gaT9tldExD7bK1QbvTf7ma2StkrS0oXLm4Z+J+ibA71p9img/rdUhipm7/Q6M6csqbaY\nOpnl8mZJrxRhvljS+ZK+KOkOSZdKuqr4fvugiqRvDvSmPhBaMvHCMdvLHBhVMXun/mm9CoeeXKpn\nL05zymYnI/QVkrbZXqBaz/3miPiO7R9Jutn2xyX9QtKHBlEg882B3jQOhGa3KcseGA1z9k7jp/Uq\n7NCkDmppErOUZutklstDks5qsv2/Jb1/EEU1om8OdK+KgdAw+ukpfFrfPL5Tm/XRJKdsJr2WS/3F\n49RyQHeqGggN8sTYKc1y27BqSrF+utI+fjPJBvrhNSv19MYx+uZAl6o8x+7m8Z1Hzs5Udtil9Gm9\n8d/57MUTVZdzRJKB3vhOnMKLB4yKVFoSZc9PT/FE8PVzxaY0Dz/JQK+vLZHSiwekLqWWRD3snt44\n1nfYpfAm1cr2M29I6gTgyQV6/cXbdO4Dyb14QMpSaklI5fTTU3qTaiWlfnpSgd744hHmyN3sueH9\nSHECQRn99NTepJpp/HdWPUof2fXQgVHWeDBOqgeplGH2/PRu1Fuvo3B0eCoLrhHoQEXqIZDqQSpl\nqf87a/O2O5dq37yVFE5gQqADFdp+5g3JHqRSpg2rprRj/aQOPbm0459JuW/eTAonMCHQgYptWDWV\n/briR0bZq6qtY9CqPoEJgQ5UrOoQGJZRaZ30q8p+elKzXBrnnwPzUT+zQcqcNYP+DHIJhLkkM0JP\n+eABYBiWTLwgPdHdjkOJcwWkaHY/fXry2OUBBjWrKYlAZ4lcoDcMhNLV2EqbbVBTVZMI9FE4eABI\nDQOh9NX76bMNaqpq5YF+5FB/Pi4CXWEgNBqavT6Dmq9eaaCzRC7QGwZCo6PV67Nj/aSmNV7qVNXK\nZrmwRC7QuxQWgkLvBrWeemWBzhK5AOazQayn3jbQbZ9q+x7bP7P9sO1PFduvtL3X9u7ia2OnD8oS\nuQBQ/nrqnfTQX5V0eUQ8aPtEST+2fVdx2zUR8eVuHpC+OQAcVV/npox+etsRekTsi4gHi8sHJT0i\nqae3kpnFx9M3B4AGZa6n3lUP3fZpks6SdH+x6TLbD9m+3nbTQ9xsb7G9y/auV17+Hx1cPSNp/qzr\nAHSi8e+h0z9qDvXPS7310o+Opy3aXiLpFkmfjogXbV8r6QuSovh+taSPzf65iNgqaasknbj0rdFX\ntUDGGj96z/UheJRO/IDh6ijQbR+vWpjfGBG3SlJE7G+4/TpJ3xlIhcA80bj+x8HVc/1pcqg/mmsb\n6LYt6euSHomIrzRsXxER+4qrF0nKdCVnYHhaHSo+G4f6o5lORujvlrRZ0k9t7y62fUbSJbbXqtZy\neUrSJwZSITDPbD/zBm2fPqfqMjCC2gZ6RNwnyU1uurP8cgBITBpAb5I6wQUAzEdlLQVAoANAAspY\nCoBAB4BE9LsUAIEOAAnZsGpKsX66p4OMCHQASEg//fShBvprJ9Qmy7COCwC0Vu+nS50vBSENO9AX\niSPcAGBAhhroCxa9xhFuADAgQw30kxb+3zAfDgDmlaEG+psWHBrmwwHAvMIsFwDIBIEOAJkg0AEg\nEwQ6AGSCQAeATBDoAJAJAh0AMkGgA0AmCHQAyETbQLd9qu17bP/M9sO2P1VsX2b7LtuPFd/HB18u\nAKCVTkbor0q6PCLOkPQuSX9p+wxJV0i6OyJOl3R3cR0AUJG2gR4R+yLiweLyQUmPSFop6UJJ24q7\nbZP0wUEVCQBor6seuu3TJJ0l6X5JyyNiX3HTc5KWt/iZLbZ32d41/fxMH6UCwPxRP2tRNzoOdNtL\nJN0i6dMR8WLjbRERkqLZz0XE1ohYFxHrxpexDxYAOlE/a9HTG8c6/pmOEtb28aqF+Y0RcWuxeb/t\nFcXtKyQd6LJeAMAcNqyaOnIquk50MsvFkr4u6ZGI+ErDTXdIurS4fKmk27uoEwDQRv2E0Z3qZIT+\nbkmbJZ1ne3fxtVHSVZLOt/2YpPXFdQBAibo5B3Pb5kxE3CfJLW5+f8ePBAAYKPZSAkAmCHQAyASB\nDgCZINABIBMEOgBkgkAHgEwQ6ACQCQIdADJBoANAJgh0AMgEgQ4AmSDQASATBDoAZIJAB4BMEOgA\nkAkCHQAyQaADQCYIdADIBIEOAJloG+i2r7d9wPaehm1X2t4766TRAIAKdTJC/4akC5psvyYi1hZf\nd5ZbFgCgW20DPSLulfT8EGoBAPShnx76ZbYfKloy463uZHuL7V22d00/P9PHwwEA5tJroF8r6e2S\n1kraJ+nqVneMiK0RsS4i1o0vYx8sAAxKTwkbEfsj4rWImJF0naSzyy0LANCtngLd9oqGqxdJ2tPq\nvgCA4RhrdwfbN0l6r6STbT8j6fOS3mt7raSQ9JSkTwywRgBAB9oGekRc0mTz1wdQCwCgD+ylBIBM\nEOgAkAkCHQAyQaADQCYIdADIBIEOAJkg0AEgEwQ6AGSCQAeATBDoAJAJAh0AMkGgA0AmCHQAyASB\nDgCZINABIBMEOgBkgkAHgEwQ6ACQibaBbvt62wds72nYtsz2XbYfK76PD7ZMAEA7nYzQvyHpglnb\nrpB0d0ScLunu4joAoEJtAz0i7pX0/KzNF0raVlzeJumDJdcFAOhSrz305RGxr7j8nKTlJdUDAOhR\n3ztFIyIkRavbbW+xvcv2runnZ/p9OABAC70G+n7bKySp+H6g1R0jYmtErIuIdePLmFQDAIPSa8Le\nIenS4vKlkm4vpxwAQK86mbZ4k6QfSZq0/Yztj0u6StL5th+TtL64DgCo0Fi7O0TEJS1uen/JtQAA\n+kBTGwAyQaADQCYIdADIBIEOAJkg0AEgEwQ6AGSCQAeATBDoAJAJAh0AMkGgA0AmCHQAyASBDgCZ\nINABIBMEOgBkgkAHgEwQ6ACQCQIdADJBoANAJgh0AMhE23OKzsX2U5IOSnpN0qsRsa6MogAA3esr\n0Avvi4hflfB7AAB9oOUCAJnoN9BD0g9s/9j2ljIKAgD0pt+Wy+9GxF7bp0i6y/ajEXFv4x2KoN8i\nSStWLujz4QAArfQ1Qo+IvcX3A5Juk3R2k/tsjYh1EbFufBkdHgAYlJ4T1vYbbJ9Yvyxpg6Q9ZRUG\nAOhOPy2X5ZJus13/Pf8SEd8rpSoAQNd6DvSI+LmkM0usBQDQB5raAJAJAh0AMkGgA0AmCHQAyASB\nDgCZINABIBMEOgBkgkAHgEwQ6ACQCQIdADJBoANAJgh0AMgEgQ4AmSDQASATBDoAZIJAB4BMEOgA\nkAkCHQAyQaADQCb6CnTbF9iesv247SvKKgoA0L2eA932AklflfQBSWdIusT2GWUVBgDoTj8j9LMl\nPR4RP4+IlyV9U9KF5ZQFAOhWP4G+UtIvG64/U2wDAFRgbNAPYHuLpC3F1UNr3/bMVMkPcbKkX5X8\nO8tGjeUZhTqpsTyjUOcwanxbJ3fqJ9D3Sjq14fpbi23HiIitkrb28Thzsr0rItYN6veXgRrLMwp1\nUmN5RqHOlGrsp+Xyn5JOtz1he6GkD0u6o5yyAADd6nmEHhGv2v6kpO9LWiDp+oh4uLTKAABd6auH\nHhF3SrqzpFp6NbB2TomosTyjUCc1lmcU6kymRkdE1TUAAErAof8AkImkA9329bYP2N7TsG2Z7bts\nP1Z8H2+47e+LZQimbP9+xXX+ke2Hbc/YXjfr/kOvs0WN/2j7UdsP2b7N9hsTrPELRX27be+w/ZYq\na2xVZ8Ntl9sO2ydXWWeL5/JK23uL53K37Y2p1Vhsv6z4f/mw7S9VWWOrOm1/q+F5fMr27qrrlCRF\nRLJfkn5P0jsl7WnY9iVJVxSXr5D0xeLyGZJ+ImmRpAlJT0haUGGdvy1pUtIPJa1r2F5JnS1q3CBp\nrLj8xaqfyxY1ntRw+a8kfS3F17vYfqpqkwR+IenkBJ/LKyX9dZP7plTj+yT9QNKi4vopqb7eDbdf\nLelzVdcZEWmP0CPiXknPz9p8oaRtxeVtkj7YsP2bEfFSRDwp6XHVlieopM6IeCQimh1EVUmdLWrc\nERGvFlf/Q7VjCVKr8cWGq2+QVN/pk9TrXbhG0t821Cgl9FzOIaUa/0LSVRHxUnGfA1XWOEedkiTb\nlvQhSTdVXaeUeMulheURsa+4/Jyk5cXlUVmKINU6Pybpu8XlpGq0/Q+2fynpI5I+V2xOrcYLJe2N\niJ/MuimpOiVdVrSwrm9oV6ZU4zskvcf2/bb/3fbvFNtTqrHReyTtj4jHiuuV1jmKgX5E1D7jME2n\nT7Y/K+lVSTdWXUszEfHZiDhVtfo+WXU9s9n+DUmf0dE3m1RdK+ntktZK2qdaqyA1Y5KWSXqXpL+R\ndHMxCk7VJTo6Oq/cKAb6ftsrJKn4Xv9I1tFSBAlIqk7bfyrpDyR9pHiDlBKrscGNki4uLqdU42rV\n+qU/sf1UUcuDtn9TCdUZEfsj4rWImJF0nY62ApKpUbUR7a1R84CkGdXWSkmpRkmS7TFJmyR9q2Fz\npXWOYqDfIenS4vKlkm5v2P5h24tsT0g6XdIDFdTXTjJ12r5AtZ7vH0bE/yZa4+kNVy+U9GhxOZka\nI+KnEXFKRJwWEaepFkrvjIjnUqqzPhAqXCSpPmsjmRol/atqO0Zl+x2SFqq28FVKNdatl/RoRDzT\nsK3aOoe197XHvcs3qfbR8BXV/kg+LulNku6W9Jhqe8OXNdz/s6rtVZ6S9IGK67youPySpP2Svl9l\nnS1qfFy1ft/u4utrCdZ4i2rB85Ckf5O0MsXXe9btT6mY5ZLYc7ld0k+L5/IOSSsSrHGhpH8uXvMH\nJZ2X6ust6RuS/rzJ/SupMyI4UhQAcjGKLRcAQBMEOgBkgkAHgEwQ6ACQCQIdADJBoANAJgh0AMgE\ngQ4Amfh/P1IbsjLeLTkAAAAASUVORK5CYII=\n", "text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "plt.contourf(lake_meshmask.variables['tmask'][0,:,170,:])\n", "plt.xlim(95,176)" ] }, { "cell_type": "code", "execution_count": 349, "metadata": { "collapsed": false }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "0.168350073508\n" ] }, { "data": { "image/png": "iVBORw0KGgoAAAANSUhEUgAAAXQAAAD8CAYAAABn919SAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nvzJboZAAAAAASUVORK5CYII=\n", "text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "file1 = U24S\n", "yslice = 170\n", "deptht = file1.variables['deptht'][:]\n", "yslicemask = 1 - new_domain[:,yslice,:]\n", "pressure1 = gsw_calls.generic_gsw_caller('gsw_p_from_z.m',\n", " [-np.expand_dims(file1.variables['deptht'][:], 1) * np.ones(284),\n", " (np.ones([284,40]) *np.expand_dims(file1.variables['nav_lat'][yslice,:][:],1)).T])\n", "i = 29\n", "density1 = calc_rho(file1.variables['vosaline'][i,:,yslice,95:176],\n", " file1.variables['votemper'][i,:,yslice,95:176],\n", " pressure1[:, 95:176])\n", "rho = 1023.3\n", "index1 = (np.abs(density1 - rho)).argmin(axis=0)\n", "list_of_depths1 = np.zeros((81))\n", "for x in range(81):\n", " list_of_depths1[x] = deptht[index1[x]]\n", "popt, pcov = curve_fit(func, np.arange(0,81), list_of_depths1)\n", "plt.plot(np.arange(0,81), list_of_depths1, 'r.')\n", "plt.grid('on')\n", "plt.ylim(50,0)\n", "plt.plot(np.arange(0,81), func(np.arange(0,81), *popt), 'b-')\n", "print(popt[0])" ] }, { "cell_type": "code", "execution_count": 356, "metadata": { "collapsed": false }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "0.167833407977\n" ] }, { "data": { "image/png": "iVBORw0KGgoAAAANSUhEUgAAAXQAAAD8CAYAAABn919SAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\ni4hEhAJdRCQiFOgiIhHx/wHQJja1kdyyPQAAAABJRU5ErkJggg==\n", "text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "file1 = U48S\n", "yslice = 170\n", "deptht = file1.variables['deptht'][:]\n", "yslicemask = 1 - new_domain[:,yslice,:]\n", "pressure1 = gsw_calls.generic_gsw_caller('gsw_p_from_z.m',\n", " [-np.expand_dims(file1.variables['deptht'][:], 1) * np.ones(284),\n", " (np.ones([284,40]) *np.expand_dims(file1.variables['nav_lat'][yslice,:][:],1)).T])\n", "i = 23\n", "density1 = calc_rho(file1.variables['vosaline'][i,:,yslice,95:176],\n", " file1.variables['votemper'][i,:,yslice,95:176],\n", " pressure1[:, 95:176])\n", "rho = 1023.3\n", "index1 = (np.abs(density1 - rho)).argmin(axis=0)\n", "list_of_depths1 = np.zeros((81))\n", "for x in range(81):\n", " list_of_depths1[x] = deptht[index1[x]]\n", "popt, pcov = curve_fit(func, np.arange(0,81), list_of_depths1)\n", "plt.plot(np.arange(0,81), list_of_depths1, 'r.')\n", "plt.grid('on')\n", "plt.ylim(50,0)\n", "plt.plot(np.arange(0,81), func(np.arange(0,81), *popt), 'b-')\n", "print(popt[0])" ] }, { "cell_type": "code", "execution_count": 362, "metadata": { "collapsed": false }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "0.196921154195\n" ] }, { "data": { "image/png": "iVBORw0KGgoAAAANSUhEUgAAAXQAAAD8CAYAAABn919SAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nMaFAFxGJCQW6iEhMKNBFRGLi/wPkQV41tod4BwAAAABJRU5ErkJggg==\n", "text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "file1 = U72S\n", "yslice = 170\n", "deptht = file1.variables['deptht'][:]\n", "yslicemask = 1 - new_domain[:,yslice,:]\n", "pressure1 = gsw_calls.generic_gsw_caller('gsw_p_from_z.m',\n", " [-np.expand_dims(file1.variables['deptht'][:], 1) * np.ones(284),\n", " (np.ones([284,40]) *np.expand_dims(file1.variables['nav_lat'][yslice,:][:],1)).T])\n", "i = 17\n", "density1 = calc_rho(file1.variables['vosaline'][i,:,yslice,95:176],\n", " file1.variables['votemper'][i,:,yslice,95:176],\n", " pressure1[:, 95:176])\n", "rho = 1023.3\n", "index1 = (np.abs(density1 - rho)).argmin(axis=0)\n", "list_of_depths1 = np.zeros((81))\n", "for x in range(81):\n", " list_of_depths1[x] = deptht[index1[x]]\n", "popt, pcov = curve_fit(func, np.arange(0,81), list_of_depths1)\n", "plt.plot(np.arange(0,81), list_of_depths1, 'r.')\n", "plt.grid('on')\n", "plt.ylim(50,0)\n", "plt.plot(np.arange(0,81), func(np.arange(0,81), *popt), 'b-')\n", "print(popt[0])" ] }, { "cell_type": "code", "execution_count": 370, "metadata": { "collapsed": false }, "outputs": [ { "data": { "text/plain": [ "(100, 194)" ] }, "execution_count": 370, "metadata": {}, "output_type": "execute_result" }, { "data": { "image/png": "iVBORw0KGgoAAAANSUhEUgAAAXQAAAD8CAYAAABn919SAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nrkJggg==\n", "text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "plt.contourf(lake_meshmask.variables['tmask'][0,:,160,:])\n", "plt.xlim(100,194)" ] }, { "cell_type": "code", "execution_count": 377, "metadata": { "collapsed": false }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "0.0947285231267\n" ] }, { "data": { "image/png": "iVBORw0KGgoAAAANSUhEUgAAAXQAAAD8CAYAAABn919SAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nhAJdRCQQ/w9qgnNofBhbRwAAAABJRU5ErkJggg==\n", "text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "file1 = U24S\n", "yslice = 160\n", "deptht = file1.variables['deptht'][:]\n", "yslicemask = 1 - new_domain[:,yslice,:]\n", "pressure1 = gsw_calls.generic_gsw_caller('gsw_p_from_z.m',\n", " [-np.expand_dims(file1.variables['deptht'][:], 1) * np.ones(284),\n", " (np.ones([284,40]) *np.expand_dims(file1.variables['nav_lat'][yslice,:][:],1)).T])\n", "i = 38\n", "density1 = calc_rho(file1.variables['vosaline'][i,:,yslice,100:194],\n", " file1.variables['votemper'][i,:,yslice,100:194],\n", " pressure1[:, 100:194])\n", "rho = 1023.3\n", "index1 = (np.abs(density1 - rho)).argmin(axis=0)\n", "list_of_depths1 = np.zeros((94))\n", "for x in range(94):\n", " list_of_depths1[x] = deptht[index1[x]]\n", "popt, pcov = curve_fit(func, np.arange(0,94), list_of_depths1)\n", "plt.plot(np.arange(0,94), list_of_depths1, 'r.')\n", "plt.grid('on')\n", "plt.ylim(50,0)\n", "plt.plot(np.arange(0,94), func(np.arange(0,94), *popt), 'b-')\n", "print(popt[0])" ] }, { "cell_type": "code", "execution_count": 385, "metadata": { "collapsed": false }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "0.140963722067\n" ] }, { "data": { "image/png": "iVBORw0KGgoAAAANSUhEUgAAAXQAAAD8CAYAAABn919SAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\niMSEAl1EJCYU6CIiMaFAFxGJif8PSlTURZx0kWYAAAAASUVORK5CYII=\n", "text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "file1 = U48S\n", "yslice = 160\n", "deptht = file1.variables['deptht'][:]\n", "yslicemask = 1 - new_domain[:,yslice,:]\n", "pressure1 = gsw_calls.generic_gsw_caller('gsw_p_from_z.m',\n", " [-np.expand_dims(file1.variables['deptht'][:], 1) * np.ones(284),\n", " (np.ones([284,40]) *np.expand_dims(file1.variables['nav_lat'][yslice,:][:],1)).T])\n", "i = 33\n", "density1 = calc_rho(file1.variables['vosaline'][i,:,yslice,100:194],\n", " file1.variables['votemper'][i,:,yslice,100:194],\n", " pressure1[:, 100:194])\n", "rho = 1023.3\n", "index1 = (np.abs(density1 - rho)).argmin(axis=0)\n", "list_of_depths1 = np.zeros((94))\n", "for x in range(94):\n", " list_of_depths1[x] = deptht[index1[x]]\n", "popt, pcov = curve_fit(func, np.arange(0,94), list_of_depths1)\n", "plt.plot(np.arange(0,94), list_of_depths1, 'r.')\n", "plt.grid('on')\n", "plt.ylim(50,0)\n", "plt.plot(np.arange(0,94), func(np.arange(0,94), *popt), 'b-')\n", "print(popt[0])" ] }, { "cell_type": "code", "execution_count": 393, "metadata": { "collapsed": false }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "0.150079157736\n" ] }, { "data": { "image/png": "iVBORw0KGgoAAAANSUhEUgAAAXQAAAD8CAYAAABn919SAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\n", "text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "file1 = U72S\n", "yslice = 160\n", "deptht = file1.variables['deptht'][:]\n", "yslicemask = 1 - new_domain[:,yslice,:]\n", "pressure1 = gsw_calls.generic_gsw_caller('gsw_p_from_z.m',\n", " [-np.expand_dims(file1.variables['deptht'][:], 1) * np.ones(284),\n", " (np.ones([284,40]) *np.expand_dims(file1.variables['nav_lat'][yslice,:][:],1)).T])\n", "i = 28\n", "density1 = calc_rho(file1.variables['vosaline'][i,:,yslice,100:194],\n", " file1.variables['votemper'][i,:,yslice,100:194],\n", " pressure1[:, 100:194])\n", "rho = 1023.3\n", "index1 = (np.abs(density1 - rho)).argmin(axis=0)\n", "list_of_depths1 = np.zeros((94))\n", "for x in range(94):\n", " list_of_depths1[x] = deptht[index1[x]]\n", "popt, pcov = curve_fit(func, np.arange(0,94), list_of_depths1)\n", "plt.plot(np.arange(0,94), list_of_depths1, 'r.')\n", "plt.grid('on')\n", "plt.ylim(50,0)\n", "plt.plot(np.arange(0,94), func(np.arange(0,94), *popt), 'b-')\n", "print(popt[0])" ] }, { "cell_type": "code", "execution_count": 401, "metadata": { "collapsed": false }, "outputs": [ { "data": { "text/plain": [ "(112, 191)" ] }, "execution_count": 401, "metadata": {}, "output_type": "execute_result" }, { "data": { "image/png": "iVBORw0KGgoAAAANSUhEUgAAAXYAAAD8CAYAAABjAo9vAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\n/wFdEGscN88vPAAAAABJRU5ErkJggg==\n", "text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "plt.contourf(lake_meshmask.variables['tmask'][0,:,150,:])\n", "plt.xlim(112,191)" ] }, { "cell_type": "code", "execution_count": 406, "metadata": { "collapsed": false }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "0.0937413592174\n", "24.1002559662\n", "14.5689821243\n" ] }, { "data": { "image/png": "iVBORw0KGgoAAAANSUhEUgAAAXQAAAD8CAYAAABn919SAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\n8l/XIQAAAABJRU5ErkJggg==\n", "text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "file1 = U24S\n", "yslice = 150\n", "deptht = file1.variables['deptht'][:]\n", "yslicemask = 1 - new_domain[:,yslice,:]\n", "pressure1 = gsw_calls.generic_gsw_caller('gsw_p_from_z.m',\n", " [-np.expand_dims(file1.variables['deptht'][:], 1) * np.ones(284),\n", " (np.ones([284,40]) *np.expand_dims(file1.variables['nav_lat'][yslice,:][:],1)).T])\n", "i = 36\n", "density1 = calc_rho(file1.variables['vosaline'][i,:,yslice,112:191],\n", " file1.variables['votemper'][i,:,yslice,112:191],\n", " pressure1[:, 112:191])\n", "rho = 1023.3\n", "index1 = (np.abs(density1 - rho)).argmin(axis=0)\n", "list_of_depths1 = np.zeros((79))\n", "for x in range(79):\n", " list_of_depths1[x] = deptht[index1[x]]\n", "popt, pcov = curve_fit(func, np.arange(0,79), list_of_depths1)\n", "plt.plot(np.arange(0,79), list_of_depths1, 'r.')\n", "plt.grid('on')\n", "plt.ylim(50,0)\n", "plt.plot(np.arange(0,79), func(np.arange(0,79), *popt), 'b-')\n", "print(popt[0])\n", "print(list_of_depths1.max())\n", "print(list_of_depths1.min())" ] }, { "cell_type": "code", "execution_count": 414, "metadata": { "collapsed": false }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "0.120969018173\n", "28.2299156189\n", "13.5354118347\n" ] }, { "data": { "image/png": "iVBORw0KGgoAAAANSUhEUgAAAXQAAAD8CAYAAABn919SAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nhAJdRCQmFOgiIjHx/wHiEn38VL5wrAAAAABJRU5ErkJggg==\n", "text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "file1 = U48S\n", "yslice = 150\n", "deptht = file1.variables['deptht'][:]\n", "yslicemask = 1 - new_domain[:,yslice,:]\n", "pressure1 = gsw_calls.generic_gsw_caller('gsw_p_from_z.m',\n", " [-np.expand_dims(file1.variables['deptht'][:], 1) * np.ones(284),\n", " (np.ones([284,40]) *np.expand_dims(file1.variables['nav_lat'][yslice,:][:],1)).T])\n", "i = 31\n", "density1 = calc_rho(file1.variables['vosaline'][i,:,yslice,112:191],\n", " file1.variables['votemper'][i,:,yslice,112:191],\n", " pressure1[:, 112:191])\n", "rho = 1023.3\n", "index1 = (np.abs(density1 - rho)).argmin(axis=0)\n", "list_of_depths1 = np.zeros((79))\n", "for x in range(79):\n", " list_of_depths1[x] = deptht[index1[x]]\n", "popt, pcov = curve_fit(func, np.arange(0,79), list_of_depths1)\n", "plt.plot(np.arange(0,79), list_of_depths1, 'r.')\n", "plt.grid('on')\n", "plt.ylim(50,0)\n", "plt.plot(np.arange(0,79), func(np.arange(0,79), *popt), 'b-')\n", "print(popt[0])\n", "print(list_of_depths1.max())\n", "print(list_of_depths1.min())" ] }, { "cell_type": "code", "execution_count": 421, "metadata": { "collapsed": false }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "0.153638220362\n", "28.2299156189\n", "13.5354118347\n" ] }, { "data": { "image/png": "iVBORw0KGgoAAAANSUhEUgAAAXQAAAD8CAYAAABn919SAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nRK5CYII=\n", "text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "file1 = U72S\n", "yslice = 150\n", "deptht = file1.variables['deptht'][:]\n", "yslicemask = 1 - new_domain[:,yslice,:]\n", "pressure1 = gsw_calls.generic_gsw_caller('gsw_p_from_z.m',\n", " [-np.expand_dims(file1.variables['deptht'][:], 1) * np.ones(284),\n", " (np.ones([284,40]) *np.expand_dims(file1.variables['nav_lat'][yslice,:][:],1)).T])\n", "i = 27\n", "density1 = calc_rho(file1.variables['vosaline'][i,:,yslice,112:191],\n", " file1.variables['votemper'][i,:,yslice,112:191],\n", " pressure1[:, 112:191])\n", "rho = 1023.3\n", "index1 = (np.abs(density1 - rho)).argmin(axis=0)\n", "list_of_depths1 = np.zeros((79))\n", "for x in range(79):\n", " list_of_depths1[x] = deptht[index1[x]]\n", "popt, pcov = curve_fit(func, np.arange(0,79), list_of_depths1)\n", "plt.plot(np.arange(0,79), list_of_depths1, 'r.')\n", "plt.grid('on')\n", "plt.ylim(50,0)\n", "plt.plot(np.arange(0,79), func(np.arange(0,79), *popt), 'b-')\n", "print(popt[0])\n", "print(list_of_depths1.max())\n", "print(list_of_depths1.min())" ] }, { "cell_type": "code", "execution_count": 430, "metadata": { "collapsed": false }, "outputs": [ { "data": { "text/plain": [ "(121, 213)" ] }, "execution_count": 430, "metadata": {}, "output_type": "execute_result" }, { "data": { "image/png": "iVBORw0KGgoAAAANSUhEUgAAAXQAAAD8CAYAAABn919SAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz\nAAALEgAACxIB0t1+/AAAFLhJREFUeJzt3W+MXNV9xvHnwX+IGxNnLYK7dXDYbMlKliWbaGtFpC2E\nOC7xGycg0eTF1opQHEUpChFq6/Ci5CVJk6CqiiI5wo5lpUlpcAKKSGqCSBFyCt0gAgbikj/gYBu7\nlA0sqgvB++uLudeeXc/s/Lszc+fM9yONdubO3Z3jI88zZ3733HMdEQIADL4L+t0AAEAxCHQASASB\nDgCJINABIBEEOgAkgkAHgEQQ6ACQCAIdABJBoANAIpb28sWWX7AiVix9Wy9fEgAG3qu/P/VSRLyj\n0X49DfQVS9+mKy/5y16+JAAMvB8d+6fnm9mPkgsAJIJAB4BEEOgAkAgCHQAS0dODosPo9Ia1/W6C\nJGnF4WP9bgKALiPQu2xmYnm/m5BZS6gDiSPQu+j49WOaHZ/rdzMyy7XicL/bAKCbCPQuOb1hrWbH\n57Ry7JV+N0WSNKtVOn79mP7o7t/0uykAuoRA75KZieVaOTaj/Rv39rspkqT9667UAW3W6Q2UXoBU\nMculC/LR+dZ1R/rdlLOmRg5p5dgrJarpAygaI/RMkbNRjm5bqpVjr2hq5FBhf7MIW9cd0YHxzTp+\n/ZhGjrzR7+a0jW8YQG0EuiphXuTItUyllmpTI4ekq6QD2ixpkEfqlI2AWgh0VerdsWWmsL9XplLL\nQlMjh3RwbEIx1u+WtO/o+CqtI9SB8wx9oOf17usKDOGylVoWKvMHTjMOakIzEyNMwwQWGPpAz2ej\nlD2Ei5TCv/XAODN2gIWGOtDPzhXvd0PQkrxsdHRbpfRSFD4cMOiGOtAxuPZv3KspfUIzEyOF/U1K\nOBh0DQPd9lskPSTpwmz/70bEbba/IOmTkv472/XWiLivWw0FFsqnYRaFM2kx6JoZob8u6ZqIeM32\nMkkP2/5h9twdEfHl7jUPqC8vvRRlVquoy2OgNQz0iAhJr2UPl2W36GajgGbt37hX+2euLORvMXsG\ng66pGrrtJZJ+JumPJX0tIh6x/WFJN9n+K0nTkm6JiOImc/fQoE/jG3ZFztrJz6Sl9IJB1NRaLhFx\nJiI2SXqnpM22N0j6uqR3S9ok6YSkr9T6Xds7bU/bnn5j7nRBzS5GZcpi+U7RR39MjRzSdVc9qtnx\nOZ3esHbeDRgELS3OFRG/k/SgpGsj4mQW9HOSviGp5tGpiNgdEZMRMbn8ghWdt7gg+VrljM5RrXoR\ns+oboY5B0DDQbb/D9tuz+yskfUjSL2yPVu32UUkDU3k8e3boVY8yOsd5tq47otnxuXm3o9uWEuoo\nvWZq6KOS9mV19Ask3RURP7C93/YmVQ6QPifpU91rZrGG8exQNC9fxKzawaMcMEX5NTPL5QlJV9TY\nPtWVFnVZN9ZuQXpqfdiz3ADKbugucMGBULQjr61TekGZDV2gA+3av3EvV31CqRHoQAvyA6aM0lFG\nBDrQAkovKDMCHWgRpReUFYEOtIHSC8qI9dCBNuQrPVbWY58f6sMwrbEf0zdrfXgOQ1+3gkAH2rR1\n3REd3DKhGS28yEbac9VPb1ibLYnQ20XMape40u7rVhHoQJvycxnOv8jGcqUcNDMTyzU7PiepdyP1\nfO2l8y3n7N0qBDrQgZrLBIxVRu0pBs3Z6/COvSJJPVkOofo1Fy6md3BsQsfFcsc5Ah3o0DAtE5Cv\ng5RfWKQX/87q16wl1b5ux1DNcmFGAnqhegnelBy/fkyxZebsKDlfP76bc/Lz0Xm9Za5T7et2DdUI\nfWZiuWJL/U96oCj5BawH+epHC0M6X9Su+htJN2f7nN6wVke3LW24zHV1X48ceaPQNgyaoQl0VllE\nL+W19QMazHJArYOQ9Ra1ywN1dnx+nKzr8MBws8tcV/d1dRsu+tUFSR7HWMxQBHo+zYo10NFL1aPX\nQQqWhQc+c4uVPQ6OTZy3vZN/d6sDsFptmNWqgfww7cRQBHpeauFyc+i1QSy95IOfhe+XxQZD+UHS\nau0erMxLLa0uc33e+3tdZdTe6TeFQZJ8oFd/0jM6R68NWuklL7W0835ZuH91bb2Vf3ejWS3Nvn51\nGwbpG1InBj7QGx1dp9SCfivzMgE1D3wWeK3d2fE5jSzyxbjW+7fIY135N6RhWTZg4AO90XQlSi0o\ngzxYKmeRVuvfqD0/tlSt14Ofha+f1+6LakP+YXp02ypd9Kv5s7RTHLU3DHTbb5H0kKQLs/2/GxG3\n2V4t6V8kXabKRaJviIiZ7jX1fPVPBz6HUgvKoLr0Ml9/Tl3P69TS/PdPL2eB5eXQaivHXil8WvH+\njXs1pU9oVqvOe/3URunNjNBfl3RNRLxme5mkh23/UNJ1kh6IiNtt75K0S9LfdbGt89Q7Er8QYY6y\nKNNMjLwUuVCv3i/VM8+qdevb9NZ1R3RQ8/v+6LZVyR0wbRjoERGSXsseLstuIWm7pKuz7fsk/UQ9\nDPR2D5wA/bTw/+uUPtHzYCnDRIHqmWe9aMPUyKF5r7N/5kodVHoHTJs69d/2EtuPSzol6f6IeETS\nmog4ke3yoqQ1XWrjeRqdDgwMil5f/ajdKYHtqPf+rH7/9usDJX/d1C5S0tRB0Yg4I2mT7bdL+p7t\nDQueD9tR63dt75S0U5LesuSithq5sMObOR0YGBSLzcSoVsQIvpffbOvN7mHmWfe0NMslIn5n+0FJ\n10o6aXs0Ik7YHlVl9F7rd3ZL2i1Jq5avqRn6iynDkXigm+YH32I6K8v0Y/mLWhcBYeZZ9zQzy+Ud\nkn6fhfkKSR+S9EVJ90raIen27Oc9RTfu3NfD3hw4Afoln4mxmEoothfq/Vr+In+tg1vOHZDsZ6kl\ndc2M0Ecl7bO9RJWa+10R8QPbP5V0l+0bJT0v6YaiG9fOKcjAoGo0UMlHuu0cxOvn8hcL36+8f7un\nmVkuT0i6osb2/5H0wW40SirHkXigl5r5f97O+ihleC/xHu6N0p4pWqmbL37SEDBMFltCYDEchKwt\nn5texiUZ2lXaQAdwvvpLCNTHQcja5l/ke35/DurcdAIdGCD1lxCoj7Jlffm3noXLAgzScsfVCHRg\nwNS7oMRi+6O+WssCDOrFMQh0YABRQilOzXXUB3RZgFIHeqOFt4Bhxai7WLX6c9CuNCU1uZZLr5Vh\nrQcAw2tq5JCuu+rRgVvrpXSBfu6Mtu4vHgQA9UyNHOrpwmlFKF2gc0FnAGWxdd2RgRqll6qGXoYz\n2gAgVz1NdBAuhlGqETqlFgBlM0ill9IEen59UEotAMqq7KWXUpRczpZauGgFgCFw/Pqx87YVMT2y\nFIHO4kEAhkU+gF2oiDnvfQ/0vNTSy6uoAEC/5APYhYpYbqCvgU6pBcAwOX79WN1p2UUsN9DXQKfU\nAmBQzI7PaaSDQkIz07I7XW6gb7NcmNUCYFDs37i361MXi1huoC+BTqkFwKDpxVmjnc55bxjoti+1\n/aDtp20/Zfuz2fYv2D5m+/Hstq3ZF+UEIgCDpjpsuxnq+QdHramNjTQzQn9T0i0RsV7S+yR9xvb6\n7Lk7ImJTdruvmResXkkRAAbJ/o17FVtmSlt6aRjoEXEiIh7L7s9KekatXKG2ytyKZTq6bSmjcwAD\nq8yll5Zq6LYvk3SFpEeyTTfZfsL2HtsjdX5np+1p29Ovx/9q5dgr2r9xb0uNBICyaLf00mo4t/PB\n0XSg214p6W5JN0fEq5K+LundkjZJOiHpK7V+LyJ2R8RkREz67W+l1AJg4G1dd6Sl0kuvJoI0Fei2\nl6kS5t+KiAOSFBEnI+JMRMxJ+obU+DLkSy48Q6kFwMCbGjnU0gi6VxNBmpnlYkl3SnomIr5atX20\narePSmp4ftPYipfaaSMAlE6zde5eTgRpZoT+fklTkq5ZMEXxS7aftP2EpA9I+lw3GwoAZZOXXupN\nMTy9YW1PJ4I0PPU/Ih6W5BpPNTVNEQBSlYf0gfHNNRfWypc36dVEkNJc4AIABlGZrmhEoANAhzo5\nu7NIBDoAdKiIhbWKQKADQAHKUHoh0AGgIP0uvfT9EnQAkIqpkUPSVdIBbT47/3xlD1+fEToAFKi6\n9NLJ2lXtlHAIdAAoWF566fTs0PzEpWZRcgGAgk2NHNLBsYmOzw7Nf//JJvdnhA4AXVDU2aGtfCgQ\n6ACQCAIdABJBoANAIgh0AEgEgQ4AiSDQASARBDoAJIJAB4BEEOgAkIiGgW77UtsP2n7a9lO2P5tt\nX237ftvPZj9Hut9cAEA9zYzQ35R0S0Ssl/Q+SZ+xvV7SLkkPRMTlkh7IHgMA+qRhoEfEiYh4LLs/\nK+kZSWslbZe0L9ttn6SPdKuRAIDGWqqh275M0hWSHpG0JiJOZE+9KGlNnd/ZaXva9vTMy3MdNBUA\nsJimA932Skl3S7o5Il6tfi4iQlLU+r2I2B0RkxExObKaY7AA0C1NJaztZaqE+bci4kC2+aTt0ez5\nUUmnutNEAEAzmpnlYkl3SnomIr5a9dS9knZk93dIuqf45gEAmtXMFYveL2lK0pO2H8+23Srpdkl3\n2b5R0vOSbuhOEwEAzWgY6BHxsCTXefqDxTYHANAujlICQCIIdABIBIEOAIkg0AEgEQQ6ACSCQAeA\nRBDoAJAIAh0AEkGgA0AiCHQASASBDgCJINABIBEEOgAkgkAHgEQQ6ACQCAIdABJBoANAIgh0AEgE\ngQ4AiWgY6Lb32D5l+3DVti/YPmb78ey2rbvNBAA00swI/ZuSrq2x/Y6I2JTd7iu2WQCAVjUM9Ih4\nSNLLPWgLAKADndTQb7L9RFaSGam3k+2dtqdtT8+8PNfBywEAFtNuoH9d0rslbZJ0QtJX6u0YEbsj\nYjIiJkdWcwwWALqlrYSNiJMRcSYi5iR9Q9LmYpsFAGhVW4Fue7Tq4UclHa63LwCgN5Y22sH2tyVd\nLeli2y9Iuk3S1bY3SQpJz0n6VBfbCABoQsNAj4iP19h8ZxfaAgDoAEcpASARBDoAJIJAB4BEEOgA\nkAgCHQASQaADQCIIdABIBIEOAIkg0AEgEQQ6ACSCQAeARBDoAJAIAh0AEkGgA0AiCHQASASBDgCJ\nINABIBEEOgAkomGg295j+5Ttw1XbVtu+3/az2c+R7jYTANBIMyP0b0q6dsG2XZIeiIjLJT2QPQYA\n9FHDQI+IhyS9vGDzdkn7svv7JH2k4HYBAFrUbg19TUScyO6/KGlNQe0BALSp44OiERGSot7ztnfa\nnrY9PfPyXKcvBwCoo91AP2l7VJKyn6fq7RgRuyNiMiImR1YzqQYAuqXdhL1X0o7s/g5J9xTTHABA\nu5qZtvhtST+VNGH7Bds3Srpd0odsPytpS/YYANBHSxvtEBEfr/PUBwtuCwCgAxS1ASARBDoAJIJA\nB4BEEOgAkAgCHQASQaADQCIIdABIBIEOAIkg0AEgEQQ6ACSCQAeARBDoAJAIAh0AEkGgA0AiCHQA\nSASBDgCJINABIBEEOgAkgkAHgEQ0vKboYmw/J2lW0hlJb0bEZBGNAgC0rqNAz3wgIl4q4O8AADpA\nyQUAEtFpoIekH9v+me2dRTQIANCeTksufxoRx2xfIul+27+IiIeqd8iCfqckja5d0uHLAQDq6WiE\nHhHHsp+nJH1P0uYa++yOiMmImBxZTYUHALql7YS1/VbbF+X3JW2VdLiohgEAWtNJyWWNpO/Zzv/O\nP0fEjwppFQCgZW0HekT8WtLGAtsCAOgARW0ASASBDgCJINABIBEEOgAkgkAHgEQQ6ACQCAIdABJB\noANAIgh0AEgEgQ4AiSDQASARBDoAJIJAB4BEEOgAkAgCHQASQaADQCIIdABIBIEOAIkg0AEgER0F\nuu1rbR+x/Uvbu4pqFACgdW0Huu0lkr4m6cOS1kv6uO31RTUMANCaTkbomyX9MiJ+HRFvSPqOpO3F\nNAsA0KpOAn2tpN9WPX4h2wYA6IOl3X4B2zsl7cwevrbpXS8c6fZrDpiLJb3U70aUHH3UGH20uEHv\nn3c1s1MngX5M0qVVj9+ZbZsnInZL2t3B6yTN9nRETPa7HWVGHzVGHy1uWPqnk5LLf0q63PaY7eWS\nPibp3mKaBQBoVdsj9Ih40/ZfS/o3SUsk7YmIpwprGQCgJR3V0CPiPkn3FdSWYUU5qjH6qDH6aHFD\n0T+OiH63AQBQAE79B4BEEOhdZnuP7VO2D9d47hbbYfviqm2fz5ZSOGL7L3rb2t6r1z+2b7L9C9tP\n2f5S1fah6h+pdh/Z3mT7P2w/bnva9uaq54axjy61/aDtp7P/M5/Ntq+2fb/tZ7OfI1W/k14/RQS3\nLt4k/bmk90o6vGD7paocUH5e0sXZtvWSfi7pQkljkn4laUm//w297h9JH5D0Y0kXZo8vGdb+WaSP\nDkr6cHZ/m6SfDHkfjUp6b3b/Ikn/lfXFlyTtyrbvkvTFlPuJEXqXRcRDkl6u8dQdkv5WUvVBjO2S\nvhMRr0fEbyT9UpUlFpJVp38+Len2iHg92+dUtn3o+keq20ch6W3Z/VWSjmf3h7WPTkTEY9n9WUnP\nqHLm+nZJ+7Ld9kn6SHY/yX4i0PvA9nZJxyLi5wueYjmFivdI+jPbj9j+d9t/km2nf865WdI/2P6t\npC9L+ny2fej7yPZlkq6Q9IikNRFxInvqRUlrsvtJ9hOB3mO2/0DSrZL+vt9tKbGlklZLep+kv5F0\nl233t0ml82lJn4uISyV9TtKdfW5PKdheKeluSTdHxKvVz0Wl1pL0tD4CvffGVanZ/dz2c6osmfCY\n7T9Uk8spDIEXJB2IikclzamyFgf9c84OSQey+/+qc+WCoe0j28tUCfNvRUTeNydtj2bPj0rKy3dJ\n9hOB3mMR8WREXBIRl0XEZaqE13sj4kVVlk74mO0LbY9JulzSo31sbr98X5UDo7L9HknLVVlYif45\n57ikq7L710h6Nrs/lH2UfYO7U9IzEfHVqqfuVeXDT9nPe6q2J9dPXV9tcdjZ/rakqyVdbPsFSbdF\nRM2vxxHxlO27JD0t6U1Jn4mIMz1rbB/U6h9JeyTtyabpvSFpR/Z1eej6R6rbR5+U9I+2l0r6P2Ur\nmg7j/6HM+yVNSXrS9uPZtlsl3a5Kye5GVWaU3SCl20+cKQoAiaDkAgCJINABIBEEOgAkgkAHgEQQ\n6ACQCAIdABJBoANAIgh0AEjE/wMEypySmWmhgwAAAABJRU5ErkJggg==\n", "text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "plt.contourf(lake_meshmask.variables['tmask'][0,:,140,:])\n", "plt.xlim(121,213)" ] }, { "cell_type": "code", "execution_count": 433, "metadata": { "collapsed": false }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "0.133079013342\n", "28.2299156189\n", "12.5181665421\n" ] }, { "data": { "image/png": "iVBORw0KGgoAAAANSUhEUgAAAXQAAAD8CAYAAABn919SAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nkUD8f7QG+Zm3DP+0AAAAAElFTkSuQmCC\n", "text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "file1 = U24S\n", "yslice = 140\n", "deptht = file1.variables['deptht'][:]\n", "yslicemask = 1 - new_domain[:,yslice,:]\n", "pressure1 = gsw_calls.generic_gsw_caller('gsw_p_from_z.m',\n", " [-np.expand_dims(file1.variables['deptht'][:], 1) * np.ones(284),\n", " (np.ones([284,40]) *np.expand_dims(file1.variables['nav_lat'][yslice,:][:],1)).T])\n", "i = 33\n", "density1 = calc_rho(file1.variables['vosaline'][i,:,yslice,121:213],\n", " file1.variables['votemper'][i,:,yslice,121:213],\n", " pressure1[:, 121:213])\n", "rho = 1023.3\n", "index1 = (np.abs(density1 - rho)).argmin(axis=0)\n", "list_of_depths1 = np.zeros((92))\n", "for x in range(92):\n", " list_of_depths1[x] = deptht[index1[x]]\n", "popt, pcov = curve_fit(func, np.arange(0,92), list_of_depths1)\n", "plt.plot(np.arange(0,92), list_of_depths1, 'r.')\n", "plt.grid('on')\n", "plt.ylim(50,0)\n", "plt.plot(np.arange(0,92), func(np.arange(0,92), *popt), 'b-')\n", "print(popt[0])\n", "print(list_of_depths1.max())\n", "print(list_of_depths1.min())" ] }, { "cell_type": "code", "execution_count": 438, "metadata": { "collapsed": false }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "0.125304531609\n", "28.2299156189\n", "12.5181665421\n" ] }, { "data": { "image/png": "iVBORw0KGgoAAAANSUhEUgAAAXQAAAD8CAYAAABn919SAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz\nAAALEgAACxIB0t1+/AAAGjJJREFUeJzt3X1wVNed5vHvTy0JBAKDece8iHfUtmN7UBwT27EwcYLj\nOPil1uOkMsWOnWVrazMbz05qwmS3dme3djaumq2svVtTUyG2YhLjKI4NA+OXeDxgxXjNeg1xYlst\nwASDgWDwC2Bk8ybx2z9ut2/rBdRqqSX16edTdUv33j6tPjrAo8u5555j7o6IiBS/ssGugIiI9A8F\nuohIIBToIiKBUKCLiARCgS4iEggFuohIIPoU6Ga2zMx2mtluM1vVX5USEZHes3zHoZtZAtgF3AQc\nAF4Fvu7uqf6rnoiI5KovV+hXA7vdfY+7nwEageX9Uy0REemt8j689xJgf9bxAeBznQuZ2UpgJUBV\nVdWi6dOn5/Vh586do6xMXf6gtsimtoipLWKhtcWuXbved/cJPZXrS6DnxN1XA6sB6urqfNu2bXl9\nn6amJurr6/uxZsVLbRFTW8TUFrHQ2sLM9uVSri+/wg4C2Zfb09LnRERkEPQl0F8F5pnZLDOrBO4G\nNvZPtUREpLfy7nJx9zYz+zbwHJAAGty9ud9qJiIivdKnPnR3fwZ4pp/qIiIifRDObWARkRKnQBcR\nCYQCXUQkEAp0EZFAKNBFRAKhQBcRCYQCXUQkEAp0EZFAKNBFRAKhQBcRCYQCXUQkEAp0EZFAKNBF\nRAKhQBcRCYQCXUQkEAp0EZFAKNBFRAKhQBcRCYQCXUQkEAp0EZFAKNBFRAKhQBcRCYQCXUQkEAp0\nEZFAKNBFRAKhQBcRCYQCXUQkEAp0EZFAKNBFRAKhQBcRCYQCXUQkEAp0EZFAKNBFRAKhQBcRCYQC\nXUQkED0Gupk1mNkRM3sz69zFZva8mb2V/jq2sNUUEZGe5HKF/giwrNO5VcAmd58HbEofi4jIIOox\n0N39ReDDTqeXA2vS+2uA2/q5XiIi0kvm7j0XMqsBnnL3y9LHx9x9THrfgKOZ427euxJYCTBp0qRF\njY2NeVW0tbWV6urqvN4bGrVFTG0RU1vEQmuLJUuWbHf3up7Klff1g9zdzey8vxXcfTWwGqCurs7r\n6+vz+pympibyfW9o1BYxtUVMbREr1bbId5TLYTObApD+eqT/qiQiIvnIN9A3AivS+yuADf1THRER\nyVcuwxZ/DmwFFpjZATO7F7gfuMnM3gK+mD4WEZFB1GMfurt//TwvLe3nuoiISB/oSVERkUAo0EVE\nAqFAFxEJRHEE+tatzFi7FrZuHeyaiIgMWUM/0LduhaVLmdXQAEuXKtRFRM5j6Ad6UxOcOYOdOwdn\nzkTHIiLSxdAP9Pp6qKzkXFkZVFZGxyIi0kWf53IpuMWLYdMm9jY0MPuee6LjrVujK/VMuGf2Fy8e\nvHqKiAyyoR/oAIsX887p08zOhPnSpVH3SyIBZtDWFl29b9qkUBeRkjX0u1w6S/ep094OZ8/G++pf\nF5ESVxxX6NnSferdXqGrf11ESljxBXq6T1196CIiHRVfoEMU3NnhndnPvlna+eapwl5EAlecgd6d\n7JullZXwwANw333xsW6Yikjgiu+m6Plk3yw9cwaefFI3TEWkpIQT6JmbpYlE9PXOOzse64apiAQu\nnC6XzjdLFy+Gyy/vePP0Bz9Qf7qIBCucQIfub5Z2fhhJ/ekiEqhwulwupHP/uvrTRSRApRHonfvX\n1Z8uIgEKq8vlfLrrXxcRCUxpBDp07F+/0ANIoOAXkaJUOoGecaEHkDR7o4gUsdLoQ892oQeQNHuj\niBSx0gv0Cz2AVFGhm6ciUrRKr8sllweQ1IcuIkWo9AIdzv8AUvaxiEiRKb0ul97YujWaLmDr1sGu\niYhIj0rzCj0Xmi5ARIpMUVyhb9gAP/vZTNatg5aWaDBKwWm6ABEpMkVxhb55MzQ0zKKhITouL4f5\n86G2FpLJeJs/H4YP76cPzV67VCNeRKQIFEWgP/ggLFu2hYkTryeVglQqulJ//XVYvx7OnYvKlZXB\n7NlxwGcCf+FCqK7u5YdqugARKTJFEegAVVXtLFoEixZ1PH/qFOzaFQV8JuhTKXj22Y5dMzNndryi\nr62NtrFjL/ChnUe/iIgMYUUT6OczfDh85jPRlu3sWfj97+OAz4R9U1P0SyBj8uSO3TaZsJ8wIZoF\noAMtOi0iQ1iPgW5m04GfApMAB1a7+4NmdjHwC6AG2Avc5e5HC1fV3qmoiLpaFi6E22+Pz7e3w759\nHYM+lYI1a+DEibjcuHGd+uhJkVz1J0w9sxcbplEvIjL05HKF3gb8hbv/xsxGAdvN7HngXwKb3P1+\nM1sFrAK+V7iq9o9EIupnnz0bbrklPu8OBw9Cc3MU9pnAf+IJ+PBDgCSwm9Ecp/bkDmq/XUXy7jjw\nZ86M+vBFRAZLj4Hu7oeAQ+n9E2bWAlwCLAfq08XWAE0UQaCfjxlMmxZtX/5yfN4d3nsPUr9spvnP\nH6KlbS4tluRX+67ikb+My1VVRf8byL4Zm0zCnDnRqBwRkUIzd8+9sFkN8CJwGfCOu49JnzfgaOa4\n03tWAisBJk2atKixsTGvira2tlLd66Eq/Wt0czNjfvtbjl15JR9deiknTpSzb98I9u0byd69I3jn\nnWj/8OF47GR5+TmmTTvJzJkfU1PzCTNmRF+nTfuEysrc2z7bUGiLoUJtEVNbxEJriyVLlmx397qe\nyuUc6GZWDfwa+Bt3X2dmx7ID3MyOuvuFxoxQV1fn27Zty+nzOmtqaqK+SMaCt7bCjh1Rl012F86e\nPR2HWM6dG1/NZw+xHDnywt+/mNqi0NQWMbVFLLS2MLOcAj2nzgAzqwCeBNa6+7r06cNmNsXdD5nZ\nFOBI/tUNS3U11NVFW7ZTp2Dnzrh/PhP2Tz8dramRUVPTMeQzQyzHdPn/j4hILJdRLgY8DLS4+w+z\nXtoIrADuT3/dUJAaBmT4cLjiimjLdvYs7N7dceRNc3M0kOb06bjc1KlRwI8aNZcdOzoOsRQRyeUK\n/VrgT4A3zOy36XPfJwryx83sXmAfcFdhqjhEXWgd0vO9dp5yFfX11AK1O5u4Y2k9LI3KtV9fz94p\nizs8MNXcDC+9NIX16+OqjB/f9enYZBKmTOlmLL2IBCuXUS4vAeeLhaX9W50ikT0TY+d1SM+3Rmke\n5RKVlczZtIk5ty7m1lvjj3/hhS3MmVPf5enYxkY4diwuN3p01wemkkmYMUNDLEVCpAF1+cieiTFz\nl9O96xql2a/lW66pqcsDTGZRKM+Y0XWI5eHDcchngv7pp/l0YjOAESPiIZbZYT97toZYihQz/fPN\nR/ZMjJ2vvO+8E7Zs6fkKPddyvbhTbxZNZTB5Mtx4Y8fXPvggDvnMzdhf/xoefTQuU1kJCxZ0ncVy\n3rzoNREZ2hTo+eg8EyPktkZpvuX6wbhxcN110Zbto4/ioM+E/bZt8MtfRlf8EP2OyR5imdkWLIiu\n9kVkaFCg5+tC65D29FpvyxXQ6NHwuc9FW7aTJ6Ox9Nn99M3N8I//GPUSQfQ/gswQy87DLEePHpDq\ni0gWBbp0q6oKrroq2rKdOQNvvdXxZmwqBc8/H72Wcckl3Y+8GTduYH8OkVKiQJdeqayESy+Ntmxt\nbfD22x376Fta4KGH4OOP43ITJ3btuqmtjfr9NcRSpG8U6NIvysujm6fz5sHXvhafP3cO9u/vOCd9\nKgWPPQbHj8flxozpejVfWwvTp2uIpUiuFOhSUGVl0dTCM2fCzTfH593h0KGuC5Bs3AgPPxyXGzmy\n63w3ySTMmhXdrBWRmAJdBoVZNJXB1KnRM1rZ3n+/6wIkmzbBT38alxk2LBplM358LVu2xGE/d66G\nWErpUqDLkDN+PFx/fbRlO3684wNTqRS89tpoNm+Oy2S6fjpf1S9YEN3oFQmZAr0YdJobZsbatdEl\nKvRpDpm8yw3kZ2XtX7R4Mdf4Vq55twnuqIc7YE9DA5O+/i12vlNF6pm9tFT9EamPpvHmtpNs+Idh\ntJ+LOuDNnNlTT5Oc9Qm1ZTtJfmECtbfOpfajVxj16uYB/TkK9WfQ578XUvzcfcC2RYsWeb5eeOGF\nvN9b1F5+2b2qyj2RcK+sdB82zM+VlX2674lE9PqPftSlXJf9/ig3kJ+VQ7kLtcWpsip/o/xK/0X5\nN/yv7a/9rrLH/TJ7wys47VEvfrRNZ59/2Z7z+xIP+mpb6S+V3+AfVE4ekj9vvm3R42e9/PJg/03v\nV6HlBbDNc8hYXaEPdd3MG2Pu0Zy7ULg5ZM5XbiA/K4dyF2qLYefaucx/x2X8Lv3YazQuso0y9pTN\nI/WZPyb1uzZafAEpT/Ji+7c4yYhoFV1gEu+SPNlC8r+doPbUvST9TZLtLUzkCMbg/Lz5tkU+cwZJ\n8dGAsKEuM29MIgEVFVBZybmysk/3SSTiuWE6leuy3x/lBvKzciiXT1uUJ2D+sH3c9m+m8v3hP+Rn\niT9le+Xnaa0cx56yuTxdvpy/TaziK/YsJ20EP3tvGd/2/82NvMBk3mUc73MdL7HSfswDZf+e58pu\nZn/5LPyOwf0z6NPfi4BW9yllukIf6rqZN2ZvQwOz77kner2Qc8icr9xAflYP5fqzLcqAWU1NzKqv\n5yuflluIX1PJwY3badmwi5aLriG1t4qW305n3dGr+fHxiuh7nobq70JtzTdIVu0hec1FUX/9u03U\n3HZlNMSywH8GfW4LKXq9WiS6r0plTdFCU1vEBrst3nuv6zQILS3whz/EZYYPj0bZZD8dm0zCnDnR\nhXJ/Gey2GEpCa4t+XVNURLo3YQLccEO0ZTt2rOu89C+/DD//eVymoqLjEMvMNn9+9EtApLcU6CIF\nMGYMfP7z0ZattTVaKDx7vpvXX4f16+P7lGVl0WIjnZ+OXbgwWoBc5HwU6CIDqLoaFi2KtmynTsWz\nWGaH/bPPxgNXIJpCofNDU7W1MHbswP4cMjQp0EWGgOHDo3uXl1/e8fzZs7BnT8dpEFpaonuZp07F\n5aZMgcmTr+DaazuG/YQJmsWylCjQRYawiorohuqCBXD77fH59nbYty/un29uhldeSfDII1G3Tsa4\ncV2v5pPJaL56BX14FOgiRSiRiPrZZ8+GW26JzjU1/YYbbqjn4MGOI2+am+GJJ+DDD+P3jxrV/UpT\nNTWarriYKdBFAmIG06ZF25e+FJ93736I5TPPwE9+EperqopuvnYO+zlzoonPZGjTH5FICTCLVoua\nOLHrQ6FHj3ZdaerFF2Ht2rhMRUU0nLJz0M+fH88HJoNPgS5S4saO7X6I5YkT8ULhmbB/7bWo+ybz\nPGJZWXT13nlJwYULo8VJZGAp0EWkW6NGwWc/G23ZTp6EXbu6Liv49NPR2rIZNTXdrx970UUD+mOU\nFAW6iPRKVRVccUW0ZTt7NhpLn+m2yVzVb94Mp0/H5aZO7frQVDIZLWwifaNAF5F+UVERh3O29nZ4\n++34Sj4T9g0N8PHHcbnx47v20SeT0Rh7DbHMjQJdRCIFWm0pUV/PXGDum03cWl8PX4jK+Q317J+2\nmNSTLbT880FSictJ7a2i8ZEKjp2K1wu8qLqN2svKSY4/QrL9DWqXTiU56yQzWp6j7MbuP7fb1Zv6\n+HP02+pSBZzZUoEuIlHgLF0aLXaRSESXxG1tHfcrK+GBB+C++/qlnFVWMuOBB5jxH+5jWVY5P9vG\n4YqppEiSaptPy8lLSX14K0/93wQNLIVnoyqPYAG1toNa20nSW0lW/E+S/3Efs/77v2LWmU+iVcUH\n4Oe4YLnOr1VWRtNhFyjUFegi0u3KWIO5CtVkP8BkDnCjPwckoGYd/H4TH7RfRAtJUiRpYSEpT9Lk\n1/Mo34AzwH+CSm5nATupPdNCkhaSNJNsb2Eeb1FJ++CuLlXg1aEU6CISr4zV05XonXfCli2DVm7c\nmeNcl/h/XGevdij30dkqdlRcTuru/0pq7W9Itc1nG5/ll/wLPL0wW4I25rKbpO+kNjGDZNn/Iulv\nsCCxmxFlpwrzc3R+rcCrQynQRaTblbGG+mpV2fujm5q4ur6eqxcvhn89jD0NDcy+ZxyfnHqPXeve\nJDX+C6TeriL1qtHy8U1s/KcRtLdHj8iaO7OmnKZ21AGSdVXUzjxJ8uj/ofaOWkZ/8er+X12qgH3o\nWrGoCKktYmqLmNoi1lNbnDkTD7HMnsly587otYxp0zqOuMnsjxtX+J8hm1YsEhE5j8pKuPTSaMvW\n1hYNsew8udmPfwyffBKXmzix+1ksJ08e3CGWPQa6mQ0HXgSGpcs/4e7/2cwuBn4B1AB7gbvc/Wjh\nqioiUljl5dGygPPmwfLl8flz52D//q5Pxz72GBw/HpcbM6b7sfTTpw9M0OdyhX4auNHdW82sAnjJ\nzJ4F7gA2ufv9ZrYKWAV8r4B1FREZFGVl0WpRM2fCzTfH593h3Xe7Bv2GDfDQQ3G5kSOjOXCWLSts\nPXsMdI862TNT5lekNweWA/Xp82uAJhToIlJCzKInWadMiYbxZ3v//Y599HPnDkB9crkpamYJYDsw\nF/g7d/+emR1z9zHp1w04mjnu9N6VwEqASZMmLWpsbMyroq2trVRrhVxAbZFNbRFTW8RCa4slS5bk\ndFO0V6NczGwMsB74M+Cl7AA3s6PufsGlajXKpX+oLWJqi5jaIhZaW+Q6yqVXi025+zHgBWAZcNjM\npqQ/bApwJJ+KiohI/+gx0M1sQvrKHDOrAm4CdgAbgRXpYiuADYWqpIiI9CyXUS5TgDXpfvQy4HF3\nf8rMtgKPm9m9wD7grgLWU0REepDLKJfXgau6Of8BsLTrO0REZDD0qg9dRESGLgW6iEggFOgiIoFQ\noIuIBEKBLiISCAW6iEggFOgiIoFQoIuIBEKBLiISCAW6iEggFOgiIoFQoIuIBEKBLiISCAW6iEgg\nFOgiIoFQoIuIBEKBLiISCAW6iEggFOgiIoFQoIuIBEKBLiISCAW6iEggFOgiIoFQoIuIBEKBLiIS\nCAW6iEggFOgiIoFQoIuIBEKBLiISCAW6iEggFOgiIoFQoIuIBEKBLiISCAW6iEggcg50M0uY2Wtm\n9lT6+GIze97M3kp/HVu4aoqISE96c4X+HaAl63gVsMnd5wGb0sciIjJIcgp0M5sG3AI8lHV6ObAm\nvb8GuK1/qyYiIr1h7t5zIbMngB8Ao4DvuvtXzeyYu49Jv27A0cxxp/euBFYCTJo0aVFjY2NeFW1t\nbaW6ujqv94ZGbRFTW8TUFrHQ2mLJkiXb3b2up3LlPRUws68CR9x9u5nVd1fG3d3Muv3N4O6rgdUA\ndXV1Xl/f7bfoUVNTE/m+NzRqi5jaIqa2iJVqW/QY6MC1wNfM7CvAcGC0mT0KHDazKe5+yMymAEcK\nWVEREbmwHvvQ3f2v3H2au9cAdwOb3f2bwEZgRbrYCmBDwWopIiI96ss49PuBm8zsLeCL6WMRERkk\nuXS5fMrdm4Cm9P4HwNL+r5KIiORDT4qKiARCgS4iEggFuohIIBToIiKBUKCLiARCgS4iEggFuohI\nIBToIiKBUKCLiARCgS4iEggFuohIIBToIiKBUKCLiARCgS4iEggFuohIIBToIiKBUKCLiARCgS4i\nEggFuohIIBToIiKBUKCLiARCgS4iEggFuohIIBToIiKBUKCLiARCgS4iEggFuohIIBToIiKBUKCL\niARCgS4iEggFuohIIBToIiKBUKCLiARCgS4iEggFuohIIMpzKWRme4ETQDvQ5u51ZnYx8AugBtgL\n3OXuRwtTTRER6UlvrtCXuPuV7l6XPl4FbHL3ecCm9LGIiAySvnS5LAfWpPfXALf1vToiIpKvnLpc\nAAf+2czagR+5+2pgkrsfSr/+LjCpuzea2UpgZfqw1cx25lnX8cD7eb43NGqLmNoipraIhdYWM3Mp\nZO7ecyGzS9z9oJlNBJ4H/gzY6O5jssocdfex+dY2hzpsy+ruKWlqi5jaIqa2iJVqW+TU5eLuB9Nf\njwDrgauBw2Y2BSD99UihKikiIj3rMdDNbKSZjcrsA18C3gQ2AivSxVYAGwpVSRER6VkufeiTgPVm\nlin/mLv/ysxeBR43s3uBfcBdhasmAKsL/P2LidoipraIqS1iJdkWOfWhi4jI0KcnRUVEAqFAFxEJ\nRFEEupktM7OdZrbbzErmiVQzm25mL5hZysyazew76fMXm9nzZvZW+mvBhosONWaWMLPXzOyp9HFJ\ntoWZjTGzJ8xsh5m1mNniEm6LP0//+3jTzH5uZsNLtS2GfKCbWQL4O+BmIAl83cySg1urAdMG/IW7\nJ4FrgH+b/tlLedqF7wAtWcel2hYPAr9y94XAFURtUnJtYWaXAP8OqHP3y4AEcDcl2BZQBIFONOZ9\nt7vvcfczQCPRtAPBc/dD7v6b9P4Jon+0l1Ci0y6Y2TTgFuChrNMl1xZmdhHwBeBhAHc/4+7HKMG2\nSCsHqsysHBgB/IESbYtiCPRLgP1ZxwfS50qKmdUAVwGvkOO0CwF6APhL4FzWuVJsi1nAe8BP0t1P\nD6WfESm5tkg/9Pg/gHeAQ8Bxd/8nSrAtoDgCveSZWTXwJHCfu3+U/ZpH406DH3tqZl8Fjrj79vOV\nKZW2ILoi/SPg7939KuBjOnUplEpbpPvGlxP9kpsKjDSzb2aXKZW2gOII9IPA9KzjaelzJcHMKojC\nfK27r0ufLsVpF64Fvpaem78RuNHMHqU02+IAcMDdX0kfP0EU8KXYFl8E3nb399z9LLAO+Dyl2RZF\nEeivAvPMbJaZVRLd8Ng4yHUaEBY9nvsw0OLuP8x6qeSmXXD3v3L3ae5eQ/R3YLO7f5PSbIt3gf1m\ntiB9aimQogTbgqir5RozG5H+97KU6F5TKbZFcTwpamZfIeo/TQAN7v43g1ylAWFm1wFbgDeI+42/\nT9SP/jgwg/S0C+7+4aBUchCYWT3wXXf/qpmNowTbwsyuJLo5XAnsAf6U6AKtFNvivwB/TDQq7DXg\nW0A1pdgWxRDoIiLSs2LochERkRwo0EVEAqFAFxEJhAJdRCQQCnQRkUAo0EVEAqFAFxEJxP8HcmSJ\nbDjBdG8AAAAASUVORK5CYII=\n", "text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "file1 = U48S\n", "yslice = 140\n", "deptht = file1.variables['deptht'][:]\n", "yslicemask = 1 - new_domain[:,yslice,:]\n", "pressure1 = gsw_calls.generic_gsw_caller('gsw_p_from_z.m',\n", " [-np.expand_dims(file1.variables['deptht'][:], 1) * np.ones(284),\n", " (np.ones([284,40]) *np.expand_dims(file1.variables['nav_lat'][yslice,:][:],1)).T])\n", "i = 27\n", "density1 = calc_rho(file1.variables['vosaline'][i,:,yslice,121:213],\n", " file1.variables['votemper'][i,:,yslice,121:213],\n", " pressure1[:, 121:213])\n", "rho = 1023.3\n", "index1 = (np.abs(density1 - rho)).argmin(axis=0)\n", "list_of_depths1 = np.zeros((92))\n", "for x in range(92):\n", " list_of_depths1[x] = deptht[index1[x]]\n", "popt, pcov = curve_fit(func, np.arange(0,92), list_of_depths1)\n", "plt.plot(np.arange(0,92), list_of_depths1, 'r.')\n", "plt.grid('on')\n", "plt.ylim(50,0)\n", "plt.plot(np.arange(0,92), func(np.arange(0,92), *popt), 'b-')\n", "print(popt[0])\n", "print(list_of_depths1.max())\n", "print(list_of_depths1.min())" ] }, { "cell_type": "code", "execution_count": 445, "metadata": { "collapsed": false }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "0.119954322235\n", "34.6857566833\n", "11.509311676\n" ] }, { "data": { "image/png": "iVBORw0KGgoAAAANSUhEUgAAAXQAAAD8CAYAAABn919SAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nRU5ErkJggg==\n", "text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "file1 = U72S\n", "yslice = 140\n", "deptht = file1.variables['deptht'][:]\n", "yslicemask = 1 - new_domain[:,yslice,:]\n", "pressure1 = gsw_calls.generic_gsw_caller('gsw_p_from_z.m',\n", " [-np.expand_dims(file1.variables['deptht'][:], 1) * np.ones(284),\n", " (np.ones([284,40]) *np.expand_dims(file1.variables['nav_lat'][yslice,:][:],1)).T])\n", "i = 21\n", "density1 = calc_rho(file1.variables['vosaline'][i,:,yslice,121:213],\n", " file1.variables['votemper'][i,:,yslice,121:213],\n", " pressure1[:, 121:213])\n", "rho = 1023.3\n", "index1 = (np.abs(density1 - rho)).argmin(axis=0)\n", "list_of_depths1 = np.zeros((92))\n", "for x in range(92):\n", " list_of_depths1[x] = deptht[index1[x]]\n", "popt, pcov = curve_fit(func, np.arange(0,92), list_of_depths1)\n", "plt.plot(np.arange(0,92), list_of_depths1, 'r.')\n", "plt.grid('on')\n", "plt.ylim(50,0)\n", "plt.plot(np.arange(0,92), func(np.arange(0,92), *popt), 'b-')\n", "print(popt[0])\n", "print(list_of_depths1.max())\n", "print(list_of_depths1.min())" ] }, { "cell_type": "code", "execution_count": 454, "metadata": { "collapsed": false }, "outputs": [ { "data": { "text/plain": [ "(130, 222)" ] }, "execution_count": 454, "metadata": {}, "output_type": "execute_result" }, { "data": { "image/png": "iVBORw0KGgoAAAANSUhEUgAAAXQAAAD8CAYAAABn919SAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz\nAAALEgAACxIB0t1+/AAAFG5JREFUeJzt3X+s3XV9x/Hnm5YL3Qr1VqTrKlfuOrwJadLiusaoG4rY\nYbMMhcRJlo6pscZsRAzZhphME/7Bn2RZjEsNYNcxnZMyCEFXJDhiOsFCEKt4ByhWaKE6rlCyDoS+\n98f5nnJ6ufeec+/5eT/n+Uhu7jnf7/ec8+knt6/7ue/v5/v5RmYiSVr8Tuh3AyRJnWGgS1IhDHRJ\nKoSBLkmFMNAlqRAGuiQVwkCXpEIY6JJUCANdkgqxtJcfNnLCsly29NRefqQkLXrP/vrQLzPzNc2O\n62mgL1t6Km86/U97+ZGStOh984l/+Fkrx1lykaRCGOiSVAgDXZIKYaBLUiF6elK0FEfWrWnr9cv2\nPdGhlkjSywz0BZiaGGnzHdYY6pI6zkCfpyPr1nB47dE232WEZfs60hxJOsZAn4cj69awf8tSlo8/\n09b7HGYFR9Y5SpfUWQb6PExNjLB8fIqd629o63228j72b1nBmKUXSR3kLJcW1Ustm8cm236vnetv\nYPn4Mx2oxUvSyxyht6Cx1LJ1dE9H3nPz2CS71m5qe8bMQvmXgVQeA70FnSq1NNo6uofd4xPs37KC\nUx7txx9Klnuk0hjoTdRLLRd1oNQy3c71N7CV95HjHX/rpqYYdaaNVBgDfQ5H1q05NjrvVKlluk7U\n5BeiXu5xlC6Vw0Cfw9TECHn+VFdDt1u/KJqpl3ucaSOVw0BvQb9Ct5vq5Z6piVGgNydm/cUhdZeB\nPsTqM22gN9MnrdlL3dU00CPiZOBu4KTq+K9n5ici4pPAB4FfVIdelZm3d6uh6rz6TJvDrOjJ5x24\neJzfvumnPfksaRi1MkJ/HjgvM5+LiBOB70TEN6p912bmZ7vXPHVbvfTSCy55IHVX00DPzASeq56e\nWH1lNxul3urVTJvdTDA14XRJqVtaqqFHxBLgPuB3gS9k5j0R8U7gsoj4c2AvcEVmTnWvqeqWXp70\n3bV2k6UXqUtaCvTMfAnYEBGvAm6OiHXAF4GrqY3WrwY+B7x/+msjYhuwDeDkJad0qNndd+Di8a5d\nUDSsto7ugXNhFy55IHXDvGa5ZOavIuIu4ILG2nlEfAm4bZbXbAe2A6wYWbUoSjXHrg49994ipyz2\nU/1EbG26ZO9Z7lHJWpnl8hrg11WYLwPeAXwqIlZn5sHqsHcDxfxX6fbVocPu5emSvWe5RyVrZYS+\nGthR1dFPAL6WmbdFxM6I2ECt5PIY8KHuNbN3LLV0X7300g/1co+lF5WolVkuDwLnzLB9a1da1EeW\nWnqnn0seONNGpfIGFxoqm8cmObz2KAcu7sMSl1KXGegaKltH93DRufdyeO3Rvs20kbrFQNfQ2Tq6\nx1sAqkgGuoaSpReVyEDXULL0ohIZ6Bpall5UmqFeD336yGz/lqUsH3/GKYtDpH6R03xH6Z2ex97t\nvxKcdz8chjbQ6/cLbbR8fIqd62/oU4vUD/WlCPZvWcEpj87nD9bOXpzU7b8SnHc/HIYy0I+sW8P+\nLUuBo8dt9+rQ4VRfE35+N/oY6VhI1i9o6yavjh0OQxno9bVapq8DbqlleG0em4Sx1o7dvX+iYzfr\nqP+lONPPY6fs3j9x7N6xhnrZhi7Qj13ePzZpgOuY+fwsbB3dc9wNttsJyamJEfL8Wph38+dx9/kT\nTOGSB6UbqlkuL4+GPPGp9mwemyTPn2qr9l0fXHQ7zLeO7jk2794pmmUbqhF6fTTkiU+1qx7AC5kh\nU9fLZZqPX4f++PZahinH0AR6Y6lF6oTGGTIL09ufx81jk+w+f4L9a49v75i19WIMRaA3nniy1KJO\n2jw2yW4mFvzaXv481j9rentdTrgcQxHojSeepE5qJ5D7MbiY6TO9cXc5ig90Z7Wo2xbbz9Ur2nuu\nd3IqxaIM9Ll+8KafoLLUIs2t8YSppZfFbdFNWzxw8fisU8XqtfLGL0stUnMuJ1yGpiP0iDgZuBs4\nqTr+65n5iYhYCfwrcCa1m0S/JzOnutfU4y+RnmmUPjUx8opLqC21SM3Vb9xt6WVxa2WE/jxwXmau\nBzYAF0TEG4ErgTsz8yzgzup5V9UvClo+/gz7tyw9rrxy4OJxDq89emx//cswl1rjcsKLX9MRemYm\n8Fz19MTqK4ELgbdW23cA3wb+tuMtrEyfR76bl2t+x/ade68BLrWhcTlhR+mLT0s19IhYEhEPAIeA\nOzLzHmBVZh6sDnkSWNWlNh5bHbE+4p5+KbOX80udUR+lT/8LWItDS4GemS9l5gbgtcCmiFg3bX9S\nG7W/QkRsi4i9EbH3haNHFtTIemA3XrLf+INXXw9DUvt2rr/B0ssiNa9ZLpn5K+Au4ALgqYhYDVB9\nPzTLa7Zn5sbM3DhywrJ5N7BxAaPp6j94llqkznIxr8WpaaBHxGsi4lXV42XAO4AfA7cCl1aHXQrc\n0unGTS+1zKTXl09Lw8DSy+LUygh9NXBXRDwIfI9aDf024BrgHRHxMHB+9byjZiq1TGeYS91h6WXx\naWWWy4PAOTNs/x/g7d1oFLg6ojQInPWyuAzkpf+tlFokdV/jEsFjrqM+8AYy0Ovrr3gjCqn/6jfR\nrt0co5Gj9kEzcIFuqUUaPPXSy/FGMNQHy0AFujeikAZTvfTSKMfxxtMDZqAC3dURpcE10/9LT5gO\nloEJdG9EIQ22mf5fuo76YBmYQJe0+NRvPH2AcUYnX5j1OEfwvWGgS1qw+qi9dsJ09guQpia8Z2kv\nGOiS2lI/YXqYFXMeZ629+wx0SW3bPDYJY7Pv373fWnsvGOiS2tbKRAZnxHSfgS6p6xrvWTrmxUhd\nY6BL6ol6rX1qYpSpifF+N+c4o5MvFPFLxkCX1DMzLyEwCEaKqO8b6JJ6ZqYlBAbBYVYUUd830CX1\n1M71N7Bz6k39bsbxxsqo7xvoknpuEJf3KGEZAwNdkjj+7kxzGeQRvIEuSRx/d6ZTHp3rdsuDW5Zp\nGugRcQbwT8AqIIHtmfn3EfFJ4IPAL6pDr8rM27vVUEnqtvrdmeZexmBwb+zRygj9ReCKzLw/Ik4B\n7ouIO6p912bmZ7vXPEnqrc1jk+xm9pk4g3xjj6aBnpkHgYPV48MR8RAwd5FJkhapraN75jxpu3Pq\nTQO7jMFchaJXiIgzgXOAe6pNl0XEgxFxfURMv4Ns/TXbImJvROx94eiRthorSf22dXQPy8efYWpi\npOkJ1F5r+aRoRCwHbgIuz8xnI+KLwNXU6upXA58D3j/9dZm5HdgOsGJkVda3T++I/VuWctG59w7k\ndCZJalS/sccUo8ynYNHtEX1LgR4RJ1IL8xszcxdAZj7VsP9LwG2tfuiRdWvYv+X4j14+/oxhLmlR\naLyxx+G1rU8W7PaFS63McgngOuChzPx8w/bVVX0d4N1AS6cI6mG+fPyZ47Z7Y2hJi8lCljHo9oVL\nrfxqeTOwFfhBRDxQbbsKuCQiNlAruTwGfKiVD5yaGGH5+NQrAtzRuaTFZr4D0V1rN3Hg4u7djq+V\nWS7fAWKGXfOec3502YkcXnuUi8YmDXBJi968c6xaE75bM2S8UlSSeqRxTfjpJ1M7EfAGuiT10Mtr\nwo9M29P+qN1Al6Qeqo/SX7m8QPs32ZjXhUWSpPbtXH8Dy8efOe7r8NqjbV+o5Ahdkvpg+gyZ3dRW\nemxnrnpPA/2lk+MV888laRjNNENm1083MTWx8NJLT0suL51U+63klEVJ6ryeBvqSk14yzCWpS3oa\n6KeO/F8vP06ShkpPA/3VS57r5cdJ0lBx2qIkFcJAl6QBUL9xBrzyfhGtMtAlaUBsHpskz59iamL6\nsgCtMdAlaUBsHd3D5rHJBV81aqBL0gBp556lBrokDZiFll4MdEkaMAstvRjoklQIA12SCtE00CPi\njIi4KyJ+FBE/jIiPVNtXRsQdEfFw9X20+82VJM2mlRH6i8AVmXk28EbgLyPibOBK4M7MPAu4s3ou\nSeqTpoGemQcz8/7q8WHgIWp3N70Q2FEdtgN4V7caKUlqbl419Ig4EzgHuAdYlZkHq11PAqtmec22\niNgbEXunnj7aRlMlSXNpOdAjYjlwE3B5Zj7buC8zE8iZXpeZ2zNzY2ZuHF3pOVhJ6paWEjYiTqQW\n5jdm5q5q81MRsbravxo41J0mSpJa0coslwCuAx7KzM837LoVuLR6fClwS+ebJ0lqVSs3iX4zsBX4\nQUQ8UG27CrgG+FpEfAD4GfCe7jRRktSKpoGemd8BYpbdb+9scyRJC+VZSkkaQI2rLrbKQJekAVVf\noKtVBrokDajG29K1wkCXpAG2c/0NLR9roEtSIQx0SSqEgS5JhTDQJakQBrokFcJAl6RCGOiSVAgD\nXZIKYaBLUiEMdEkqhIEuSYUw0CWpEAa6JBXCQJekQhjoklSIpoEeEddHxKGI2New7ZMR8UREPFB9\nbeluMyVJzbQyQv8ycMEM26/NzA3V1+2dbZYkab6aBnpm3g083YO2SJLa0E4N/bKIeLAqyYzOdlBE\nbIuIvRGxd+rp1m92Kkman4UG+heB3wE2AAeBz812YGZuz8yNmblxdKXnYCWpWxaUsJn5VGa+lJlH\ngS8BmzrbLEnSfC0o0CNidcPTdwP7ZjtWktQbS5sdEBFfAd4KnBYRjwOfAN4aERuABB4DPtTFNkqS\nWtA00DPzkhk2X9eFtkiS2uBZSkkqhIEuSYUw0CWpEAa6JBXCQJekQhjoklQIA12SCmGgS1IhDHRJ\nKoSBLkmFMNAlqRAGuiQVwkCXpEIY6JJUCANdkgphoEtSIQx0SSqEgS5JhWga6BFxfUQcioh9DdtW\nRsQdEfFw9X20u82UJDXTygj9y8AF07ZdCdyZmWcBd1bPJUl91DTQM/Nu4Olpmy8EdlSPdwDv6nC7\nJEnztNAa+qrMPFg9fhJY1aH2SJIWqO2TopmZQM62PyK2RcTeiNg79fTRdj9OkjSLhQb6UxGxGqD6\nfmi2AzNze2ZuzMyNoyudVCNJ3bLQhL0VuLR6fClwS2eaI0laqFamLX4F+C9gIiIej4gPANcA74iI\nh4Hzq+eSpD5a2uyAzLxkll1v73BbJEltsKgtSYUw0CWpEAa6JBXCQJekQhjoklQIA12SCmGgS1Ih\nDHRJKoSBLkmFMNAlqRAGuiQVwkCXpEIY6JJUCANdkgphoEtSIQx0SSqEgS5JhTDQJakQBrokFaLp\nPUXnEhGPAYeBl4AXM3NjJxolSZq/tgK98rbM/GUH3keS1AZLLpJUiHYDPYFvRcR9EbGtEw2SJC1M\nuyWXt2TmExFxOnBHRPw4M+9uPKAK+m0Aq9csafPjJEmzaWuEnplPVN8PATcDm2Y4ZntmbszMjaMr\nrfBIUrcsOGEj4jcj4pT6Y2AzsK9TDZMkzU87JZdVwM0RUX+ff8nMb3akVZKkeVtwoGfmT4D1HWyL\nJKkNFrUlqRAGuiQVwkCXpEIY6JJUCANdkgphoEtSIQx0SSqEgS5JhTDQJakQBrokFcJAl6RCGOiS\nVAgDXZIKYaBLUiEMdEkqhIEuSYUw0CWpEAa6JBXCQJekQrQV6BFxQURMRsQjEXFlpxolSZq/BQd6\nRCwBvgC8EzgbuCQizu5UwyRJ89POCH0T8Ehm/iQzXwC+ClzYmWZJkuarnUBfA/y84fnj1TZJUh8s\n7fYHRMQ2YFv19LkNr3t8stufOQ+nAb/sdyMGnH3UnH3UnH00t2b987pW3qSdQH8COKPh+WurbcfJ\nzO3A9jY+p2siYm9mbux3OwaZfdScfdScfTS3TvVPOyWX7wFnRcR4RIwA7wVubbdBkqSFWfAIPTNf\njIi/Av4DWAJcn5k/7FjLJEnz0lYNPTNvB27vUFv6YSBLQQPGPmrOPmrOPppbR/onMrMT7yNJ6jMv\n/ZekQhQd6BFxfUQcioh9M+y7IiIyIk5r2PaxahmDyYj4o962tj9m66OIuCwifhwRP4yITzdsH6o+\nmql/ImJDRHw3Ih6IiL0Rsalh31D1D0BEnBERd0XEj6qfl49U21dGxB0R8XD1fbThNUPVT3P00Weq\n/2cPRsTNEfGqhtfMv48ys9gv4A+BNwD7pm0/g9rJ3J8Bp1Xbzga+D5wEjAOPAkv6/W/oRx8BbwO+\nBZxUPT99WPtolv7ZDbyzerwF+Paw9k/1714NvKF6fArw31VffBq4stp+JfCpYe2nOfpoM7C02v6p\ndvuo6BF6Zt4NPD3DrmuBvwEaTyBcCHw1M5/PzJ8Cj1Bb3qBos/TRh4FrMvP56phD1fah66NZ+ieB\nU6vHK4AD1eOh6x+AzDyYmfdXjw8DD1G7avxCYEd12A7gXdXjoeun2fooM3dn5ovVYd+ldj0PLLCP\nig70mUTEhcATmfn9abtcyuBlrwf+ICLuiYj/jIjfr7bbRzWXA5+JiJ8DnwU+Vm0f+v6JiDOBc4B7\ngFWZebDa9SSwqno81P00rY8avR/4RvV4QX00VIEeEb8BXAX8Xb/bMuCWAiuBNwJ/DXwtIqK/TRoo\nHwY+mplnAB8FrutzewZCRCwHbgIuz8xnG/dlrY4w9FPqZuujiPg48CJwYzvvP1SBDqylVo/6fkQ8\nRu3Pm/sj4rdocSmDIfE4sCtr7gWOUltrwj6quRTYVT3+N17+U3ho+yciTqQWVDdmZr1vnoqI1dX+\n1UC9dDeU/TRLHxERfwH8MfBn1S8+WGAfDVWgZ+YPMvP0zDwzM8+kFlxvyMwnqS1b8N6IOCkixoGz\ngHv72Nx++ndqJ0aJiNcDI9QWDrKPag4A51aPzwMerh4PZf9Uf71dBzyUmZ9v2HUrtV9+VN9vadg+\nVP00Wx9FxAXUzuf9SWb+b8NLFtZH/T772+Uzy18BDgK/phbeH5i2/zGqWS7V849TO5s8STWLofSv\nmfqIWoD/M7APuB84b1j7aJb+eQtwH7VZCPcAvzes/VP9m99CrZzyIPBA9bUFeDVwJ7VfeN8CVg5r\nP83RR49Qq5XXt/1jO33klaKSVIihKrlIUskMdEkqhIEuSYUw0CWpEAa6JBXCQJekQhjoklQIA12S\nCvH/vAkeyQQVfLsAAAAASUVORK5CYII=\n", "text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "plt.contourf(lake_meshmask.variables['tmask'][0,:,130,:])\n", "plt.xlim(130,222)" ] }, { "cell_type": "code", "execution_count": 467, "metadata": { "collapsed": false }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "0.30990020178\n", "44.5177230835\n", "9.50243282318\n" ] }, { "data": { "image/png": "iVBORw0KGgoAAAANSUhEUgAAAXQAAAD8CAYAAABn919SAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nAAAASUVORK5CYII=\n", "text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "file1 = U24S\n", "yslice = 130\n", "deptht = file1.variables['deptht'][:]\n", "yslicemask = 1 - new_domain[:,yslice,:]\n", "pressure1 = gsw_calls.generic_gsw_caller('gsw_p_from_z.m',\n", " [-np.expand_dims(file1.variables['deptht'][:], 1) * np.ones(284),\n", " (np.ones([284,40]) *np.expand_dims(file1.variables['nav_lat'][yslice,:][:],1)).T])\n", "i = 40\n", "density1 = calc_rho(file1.variables['vosaline'][i,:,yslice,130:221],\n", " file1.variables['votemper'][i,:,yslice,130:221],\n", " pressure1[:, 130:221])\n", "rho = 1023.3\n", "index1 = (np.abs(density1 - rho)).argmin(axis=0)\n", "list_of_depths1 = np.zeros((91))\n", "for x in range(91):\n", " list_of_depths1[x] = deptht[index1[x]]\n", "popt, pcov = curve_fit(func, np.arange(0,91), list_of_depths1)\n", "plt.plot(np.arange(0,91), list_of_depths1, 'r.')\n", "plt.grid('on')\n", "plt.ylim(50,0)\n", "plt.plot(np.arange(0,91), func(np.arange(0,91), *popt), 'b-')\n", "print(popt[0])\n", "print(list_of_depths1.max())\n", "print(list_of_depths1.min())" ] }, { "cell_type": "code", "execution_count": 468, "metadata": { "collapsed": false }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "0.321790116226\n", "44.5177230835\n", "9.50243282318\n" ] }, { "data": { "image/png": "iVBORw0KGgoAAAANSUhEUgAAAXQAAAD8CAYAAABn919SAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nAElFTkSuQmCC\n", "text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "file1 = U48S\n", "yslice = 130\n", "deptht = file1.variables['deptht'][:]\n", "yslicemask = 1 - new_domain[:,yslice,:]\n", "pressure1 = gsw_calls.generic_gsw_caller('gsw_p_from_z.m',\n", " [-np.expand_dims(file1.variables['deptht'][:], 1) * np.ones(284),\n", " (np.ones([284,40]) *np.expand_dims(file1.variables['nav_lat'][yslice,:][:],1)).T])\n", "i = 35\n", "density1 = calc_rho(file1.variables['vosaline'][i,:,yslice,130:221],\n", " file1.variables['votemper'][i,:,yslice,130:221],\n", " pressure1[:, 130:221])\n", "rho = 1023.3\n", "index1 = (np.abs(density1 - rho)).argmin(axis=0)\n", "list_of_depths1 = np.zeros((91))\n", "for x in range(91):\n", " list_of_depths1[x] = deptht[index1[x]]\n", "popt, pcov = curve_fit(func, np.arange(0,91), list_of_depths1)\n", "plt.plot(np.arange(0,91), list_of_depths1, 'r.')\n", "plt.grid('on')\n", "plt.ylim(50,0)\n", "plt.plot(np.arange(0,91), func(np.arange(0,91), *popt), 'b-')\n", "print(popt[0])\n", "print(list_of_depths1.max())\n", "print(list_of_depths1.min())" ] }, { "cell_type": "code", "execution_count": 474, "metadata": { "collapsed": false }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "0.341672648507\n", "44.5177230835\n", "9.50243282318\n" ] }, { "data": { "image/png": "iVBORw0KGgoAAAANSUhEUgAAAXQAAAD8CAYAAABn919SAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\niFBCFxGJCCV0EZGI+H9jlQYVRThQ6wAAAABJRU5ErkJggg==\n", "text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "file1 = U72S\n", "yslice = 130\n", "deptht = file1.variables['deptht'][:]\n", "yslicemask = 1 - new_domain[:,yslice,:]\n", "pressure1 = gsw_calls.generic_gsw_caller('gsw_p_from_z.m',\n", " [-np.expand_dims(file1.variables['deptht'][:], 1) * np.ones(284),\n", " (np.ones([284,40]) *np.expand_dims(file1.variables['nav_lat'][yslice,:][:],1)).T])\n", "i = 29\n", "density1 = calc_rho(file1.variables['vosaline'][i,:,yslice,130:221],\n", " file1.variables['votemper'][i,:,yslice,130:221],\n", " pressure1[:, 130:221])\n", "rho = 1023.3\n", "index1 = (np.abs(density1 - rho)).argmin(axis=0)\n", "list_of_depths1 = np.zeros((91))\n", "for x in range(91):\n", " list_of_depths1[x] = deptht[index1[x]]\n", "popt, pcov = curve_fit(func, np.arange(0,91), list_of_depths1)\n", "plt.plot(np.arange(0,91), list_of_depths1, 'r.')\n", "plt.grid('on')\n", "plt.ylim(50,0)\n", "plt.plot(np.arange(0,91), func(np.arange(0,91), *popt), 'b-')\n", "print(popt[0])\n", "print(list_of_depths1.max())\n", "print(list_of_depths1.min())" ] }, { "cell_type": "code", "execution_count": 480, "metadata": { "collapsed": false }, "outputs": [ { "data": { "text/plain": [ "(126, 199)" ] }, "execution_count": 480, "metadata": {}, "output_type": "execute_result" }, { "data": { "image/png": "iVBORw0KGgoAAAANSUhEUgAAAXQAAAD8CAYAAABn919SAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nYII=\n", "text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "plt.contourf(lake_meshmask.variables['tmask'][0,:,120,:])\n", "plt.xlim(126,199)" ] }, { "cell_type": "code", "execution_count": 487, "metadata": { "collapsed": false }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "0.262344801496\n", "34.6857566833\n", "9.50243282318\n" ] }, { "data": { "image/png": "iVBORw0KGgoAAAANSUhEUgAAAXQAAAD8CAYAAABn919SAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\noQAAAABJRU5ErkJggg==\n", "text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "file1 = U24S\n", "yslice = 120\n", "deptht = file1.variables['deptht'][:]\n", "yslicemask = 1 - new_domain[:,yslice,:]\n", "pressure1 = gsw_calls.generic_gsw_caller('gsw_p_from_z.m',\n", " [-np.expand_dims(file1.variables['deptht'][:], 1) * np.ones(284),\n", " (np.ones([284,40]) *np.expand_dims(file1.variables['nav_lat'][yslice,:][:],1)).T])\n", "i = 34\n", "density1 = calc_rho(file1.variables['vosaline'][i,:,yslice,126:199],\n", " file1.variables['votemper'][i,:,yslice,126:199],\n", " pressure1[:, 126:199])\n", "rho = 1023.3\n", "index1 = (np.abs(density1 - rho)).argmin(axis=0)\n", "list_of_depths1 = np.zeros((73))\n", "for x in range(73):\n", " list_of_depths1[x] = deptht[index1[x]]\n", "popt, pcov = curve_fit(func, np.arange(0,73), list_of_depths1)\n", "plt.plot(np.arange(0,73), list_of_depths1, 'r.')\n", "plt.grid('on')\n", "plt.ylim(50,0)\n", "plt.plot(np.arange(0,73), func(np.arange(0,73), *popt), 'b-')\n", "print(popt[0])\n", "print(list_of_depths1.max())\n", "print(list_of_depths1.min())" ] }, { "cell_type": "code", "execution_count": 495, "metadata": { "collapsed": false }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "0.252267943271\n", "34.6857566833\n", "9.50243282318\n" ] }, { "data": { "image/png": "iVBORw0KGgoAAAANSUhEUgAAAXQAAAD8CAYAAABn919SAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz\nAAALEgAACxIB0t1+/AAAHrNJREFUeJzt3Xt4VOW59/HvnWAADXLUgBw2IIhVUEooGEFIJmqpuktb\nWqq2vvhqN21fdctV91bQLdbailZttZeHopVdarGUolY22lodkqoYrRykhXrAWg8gylZDhSog5H7/\neCZOiISZDJPMzOL3ua51zTxr1lq5k8gvy2c961nm7oiISOErynUBIiKSHQp0EZGIUKCLiESEAl1E\nJCIU6CIiEaFAFxGJiP0KdDObZGYvmtnLZjYzW0WJiEjrWabj0M2sGHgJOAXYADwLnOXuf81eeSIi\nkq79OUMfA7zs7q+4+05gITA5O2WJiEhrddiPffsCbzRpbwDGNt/IzKYD0wE6d+5c3r9//4y+WEND\nA0VF+d/lXyh1QuHUqjqzr1BqVZ3BSy+99I67H5ZyQ3fPaAG+DPysSfsc4NZ97VNeXu6ZqqmpyXjf\n9lQodboXTq2qM/sKpVbVGQArPI1c3p8/KRuBpqfb/RLrREQkB/Yn0J8FhprZIDMrAc4ElmSnLBER\naa2M+9DdfZeZXQg8AhQD89x9XdYqExGRVtmfi6K4+8PAw1mqRURE9kP+Xz4WEZG0KNBFRCJCgS4i\nEhEKdBGRiFCgi4hEhAJdRCQiFOgiIhGhQBcRiQgFuohIRCjQRUQiQoEuIhIRCnQRkYhQoIuIRIQC\nXUQkIhToIiIRoUAXEYkIBbqISEQo0EVEIkKBLiISEQp0EZGIUKCLiESEAl1EJCIU6CIiEaFAFxGJ\nCAW6iEhEKNBFRCJCgS4iEhEKdBGRiFCgi4hEhAJdRCQiFOgiIhGhQBcRiQgFuohIRCjQRUQiojAC\nva6OAQsWQF1drisREclbKQPdzOaZ2WYzW9tkXQ8ze9TM1ideu7dZhXV1UF3NoHnzoLpaoS4i0oJ0\nztB/Dkxqtm4mEHf3oUA80W4btbWwcyfW0AA7d4a2iIh8QspAd/fHgfearZ4MzE+8nw98Ict1JVVW\nQkkJDUVFUFIS2iIi8gnm7qk3MhsILHX34Yn2FnfvlnhvQH1jey/7TgemA5SVlZUvXLiw1UUeum4d\nnf/0Jz4cM4b3jz221fu3p23btlFaWprrMtJSKLWqzuwrlFpVZ1BVVbXS3Uen3NDdUy7AQGBtk/aW\nZp/Xp3Oc8vJyz1RNTU3G+7anQqnTvXBqVZ3ZVyi1qs4AWOFpZGymo1zeNrM+AInXzRkeR0REsiTT\nQF8CTEu8nwY8mJ1yREQkU+kMW/wVUAcMM7MNZnY+cB1wipmtB05OtNtPXR3MmaMhjCIiTXRItYG7\nn9XCR9VZriU9iXHp7NwZRr3E41BRkZNSRETySWHcKdpUYlw6u3drXLqISBOFF+iJcekUF2tcuohI\nEym7XPJORUXoZqmtDWGu7hYREaAQAx1CiDcP8ro6hbyIHNAKM9Cb04VSEZEC7EPfG10oFRGJSKDr\nQqmISES6XHShVEQkIoEOe79QKiJyAIlGl4uIiCjQRUSiQoEuIhIR0Q305jMyaoZGEYm46FwUbar5\njUY33wwzZujGIxGJtGieoTe/0ei++3TjkYhEXkEE+oYNUF9/UPo7NL/RaMoU3XgkIpFXEF0uc+bA\n7bePY8QIiMXCMnEidO3awg57u9FoxIg925rMS0QipiAC/ZvfhJ07X+HVVwczdy7ccgsUFcHo0aGr\nPBaDceOgc+cmOzW/0ahpW5N5iUgEFUSXy3HHwde+9jqPPgpbtkBNDVx+OXToADfcAKecAt26QVUV\nfP/78NRT8NFH+zigJvMSkQgqiEBvqmPH0EtyzTWwfDm89x489BBceCH84x8we3Y4W+/RA04/HW66\nCZ57DhoamhxEk3mJSAQVRJfLvnTpAqedFhaAd98NJ9zxOCxbBg8/HNb37BnO4GMxqK6uYOhjceyP\ntepDF5HIKPhAb65nzzCoZcqU0N64MQR7Y8AvXhzW9+1bQSxWQawPVPeD/v3RhVIRKWiRC/Tm+vaF\nc84Jizv87W8h3ONx+N3v4J57wnZD+n1I9aZ1xBrWUNXxDg5b9muFuogUlMgHelNmMGRIWL75zdCv\nvnZt4gx+7gbu3T2VuXwDtsNxX3qb2JlhMMyECXDoobmuXkRk3w6oQG+uqCiMoDnuOJgx9h12xUax\nYudxLCs6mXjf73DHHWHWgOJi+MxnGvvf4cQToVOnXFcvIrKnAzrQ91BRQYdlf+CE2lpOqKzk8oqu\nbN8ehkA29sFffz1ce20YaTNuXDLgR48OQyhFRHJJMdRUs5uROnVK3pn6/e/D++/DE08kA/6//iss\nXbqEO1djMTj00EOYMCGc/YuItCcF+r40G/Vy6Lo6Tv9zLad/uRJuquCd3z1LzT0bWLa9gmXrerN0\nKcBnmPUfH1F16kEf/zEYMiT034uItCUFektSTcF78830mjGDr+zcyVcS7Tf+/QbiO8dTs7WaeM1X\nWLSoIwD9+iWnKKiuDiNvRESyTYHeklRT8O6l3X/X3znXX+Zc7sFnvMH6L8/6ePz70qUwf3449FFH\nJQO+shJ69crlNyoiUaGe3pakmoK3hXZDURGUlGBVlRx1FHz72/Cb38DmzbB6Ndx4Y+iCuece+MpX\n4LDD4NOfhksuCXe1bt2a629cRAqVztBbks4UvHtpvzpvHoPPO+8TNyUVFcHIkWG55JIwedizzybv\nYL31VvjRj8JomTFjkt0zJ5ygIZIikh4F+r7sawreFtqv79jB4DTuMD3ooDCe/cQT4cor4cMPwxDJ\nxrtYr702jKzp1AnGj08G/KhRGiIpInunaGhrzeeHaaHdubKS6uoKqg+ugy61/OP71Ty+fUwI+P/5\ngMsfOxgId6xWViYD/thjNYJGRIKUgW5m/YFfAGWAA3e6+y1m1gP4NTAQeBWY6u71bVdqAUpjpExL\n7a4l1/Cv8Tj/+lXgzmo2F3WltriaeNVNxNeWsWRJ+BKHH54cKx+LweDBCniRA1U6Z+i7gEvcfZWZ\ndQFWmtmjwLlA3N2vM7OZwEzgsrYrtQBlMFJmrw/e2LmTwxveYqotZOrYY+G3s3j99dD33niT08KF\nYdMBA5IjaGIxOOKIXH3zItLeUo5ycfdN7r4q8X4r8DzQF5gMJAbiMR/4QlsVWbAyHCmzx4M3WngY\nx4ABcO658ItfhIdov/AC3HZbmHPmwQfD7JJ9+8KnPgUXXAD33x8eBiIi0WXunv7GZgOBx4HhwOvu\n3i2x3oD6xnazfaYD0wHKysrKFzaeSrbStm3bKC0tzWjf9tS8zkPXraPbc8+xZeRI3j/22Fa393aM\nVBoa4OWXS1m9ujurV3djzZpubN9ejJkzZMg2Ro2qZ9SoLQwatJHDDuuc8ni5Vqi/+3xWKLWqzqCq\nqmqlu49OuaG7p7UApcBK4EuJ9pZmn9enOkZ5eblnqqamJuN921M+1rljh/sTT7hffbX7xInuJSXu\n4F5cvNvHj3efPdu9ttZ9+/ZcV7p3+fgz3ZtCqdO9cGpVnQGwwtPI6bRuLDKzg4D7gAXufn9i9dtm\n1ifxeR9gc+v+5kh7KSkJQx9nzw7d8vX18MgjMHXqBnbsCMMjKyuhe3c49dQwq+SKFaErX0QKRzqj\nXAy4G3je3X/U5KMlwDTgusTrg21SoWTdwQeH4C4peYXKygFs2QJ//GPyAuvMmWG7rl1D0DdeZD3m\nGI2gEcln6YxyGQecA/zFzJ5LrLucEOSLzOx84DVgatuUKJ+Q5tj2FtuJYwxYsAA6dqRbRQWTJ8Pk\nyeGjt96CmprkKJoHE3+qy0q3EavYTvVXexGLwaBB7ftti8i+pQx0d38SaOm8rDq75UhK+zG2nZKS\ncAoOUF3NoB07YMGCsK7J3a29e8NZZ4UF4NX7V7HszDuJ/3MCyx6N8atHw/pBg/YcA9+7dzv/LERk\nD7pTtNBkcWy7NTQk1+1juoKBLz7CeQ0/4zyfixcV88K/3078yOnE4+Hwd98dtjvmmGS4N/bJi0j7\n0WyLhSaLY9sbZ4ZsHNuezte0jiV8auoILrwQHngA3nknXEC9/vow7/u8efClL0HPnuHRfJddFi7A\n/vOfbf6TETng6Qy90GQ4C+Qn+tDj8RZnhkzrayYUF0N5eVguvTSc8D/zTPIC649/DD/8YZiM7IQT\nkhdYx44NfyNEJHsU6IUog1kgPxHarZgZssVj7EVJCZx0UliuuiqcmT/5ZDLgr74avvvdMNLmpJOS\nAT9yZPjjICKZU6BLmzrkEPjsZ8MCYQx8bW0y4C+9NKzv3n3PWSSPPlpDJEVaS4Eu7ap7d/jiF8MC\nsGlTGCLZOA/8Aw+E9X36JC+wHnxwx9wVLFJAFOiSU336wNlnhwXglVeS498feyyMqoQKrrgi2T1T\nVQVlZbmsWiQ/KdAlrwweHJZvfAPcYd06mDt3PW+8MZRFi+Cuu8J2xx6bDPiJE6HbJ6aFEznwKNAl\nb5nB8OEwZcpGKiuHsns3rFqVfA7rXXfBT34SntdaXp4M+HHjwkVXkQONxqFLwSguDvO9z5wJf/hD\n8gLrFVeE0TU33hjmqGm8wHrNNbB8eXggt8iBQIEuQV0dzJkTXvfWzmSfdI6Zxj4DFizY6+cdO8LE\nkjq+13kOT95QR309PPwwXDTlTd5f/xZXXeWMHw/du+7mtGF/46aLXmX1amhYnp260q2zvX9erf49\nSnSkM8duthbNh55fPq71qafcO3d2Ly4Or3Pn7tl+6qlP7pxqn1Ttp55K+xgNRUUZHfOdTn198Tf/\n4N8unutH81cPvfLuPXjHp7DYbzvoYn/h6oXe0CmzutKucz+OmfVjNP/d5znVGZDmfOjqQ5fU88Ps\nba6XLM4pk2qfj+ecaeUxe/IWU/5+I1OIA7vZWNSfmmMuIL6ujLjHuO+jKXAV9GUcMZYR215L9W9X\n0r/b1oy+txbrbMX3mo2fV6t+jxIp6nKR1PPD7G2ul7Z4XmoL+3w858x+HrNvx3f4+kXd+e9O/4/X\nigazvuNw5n7tccYX1/F7JvF/fR4DfnghQ2+fwbf4KYvsq/zvQUek/b21WGcrvtds/Lxa9XuUSNEZ\nuqQ3P0wm+6Q5p0yqffaYcyZLx7TaWoZUVjKkooLpF9ThNXezdsBpLHv3eOLxzvyq/lzm/vMbsB2O\nuw1inz+DWMlyJv6ff+HQk8e0vs4068rG99aq36NESzr9Mtla1IeeXwql1lzU+dFH7k8/7X7tte7V\n1e6dOjU+h9V97Fj3yy93f+wx9w8+yG2dmSqUWlVngPrQRTLXoUOYEXLsWJg1C7Zvh6efTk5RcP31\ncO210LEjnHhiGP/evfuhjBsXZpYUyQUFukgaOnVKdmNfcw1s3QpPPJG8yenKKwFGMXNmuHO1cZKx\nESPCjU8i7UGBLpKBLl3gtNPCAuFBH7feuo633z6WZcvgoYfC+l69wtwzjQE/ZIhmkZS2o0AXyYJe\nvaCy8n8/HkjyxhvhzL1xJsnf/Cas79cvOUVBLBbaItmiQBdpA/37w7RpYXGHl19Ods889BDMnx+2\nO+qoZLhXVYU/DCKZUqCLtDEzGDo0LN/6FjQ0wF/+EgK+piZMEfzTn4Ztjz8+2T0zYULo2hFJlwJd\npJ0VFYXgPv54+M53wuRhK1cmz+Bvvz08i7W4GMaMSQZ8RUW4OCvSEl1/F8mxxgdoX3FFCPX6+vB6\n2WXhbP666xqHRcLJJ4fhkk8/Dbt25bpyyTc6QxfJM507J/vVf/AD+Mc/kkMk4/EQ/BC6YyZOTF5k\nHT5cQyQPdAp0kTzXtSuccUZYADZvDnfzNwb80qVh/WGHhQurjQF/5JEaInmgUaCLFJjDD4epU8MC\n8PrryeewxuOwaFFYP2BAsv89FoMjjshdzdI+FOgiBW7AADj33LC4w0svJcN9yRL4+c/DdkcfnQz4\nDh30Tz+K9FsViRAzGDYsLN/+drioumZN8gz+F78Io2iMExl51DaqP19KrM/znPT+Q5R+dlwYSlNX\nt+cMjana0Pp90jzGgAULwoQ5mR7zQJPODF7ZWjTbYn4plFpVZ/bsfLzOnyyp8qvtSq8sqvWSDrsc\n3Duw008sesqvPH2F15Sc6tuLOrfvk5RaOEbaT6tK5ylbbUizLYpIuzvoyRrG7X6ccV7D7KJr+WDi\naSyv2cmyhoksa6jmBw+N5BoeoRMfMv7D5VTf+BqxHcdT3vAninPwNKa0n1alpzMBGocucmBJPPWo\n8elKB089g1M6Ps6c4it5pnMl7/74Hn5bMpXpdhdvWW9mrT+fsQ119ORdJvtv+Un32aztMBIvap+n\nMaX9tCo9nQlQH7rIgSXxpKmWnq7UraKCyWOHMbm2Fiq38vZgqJn7EvH/+YBlb57Mkl93AlZQVrqN\nqhO2U72uF7EYDG6jpzG16mlVejqT+tCzrVDqdC+cWlVn9mVa69//7n733e5nn+3ep094ihO4Dxzo\nft557gsWuL/5Zu7rbG/qQxeRgjNwIJx3Xljc4cUXkzc4PfAAzJsXtjvmmOQQyYkTw7QF0vZSBrqZ\ndQIeBzomtl/s7leZWQ/g18BA4FVgqrvXt12pIpJPzMLY9qOPhgsuCNcj16xJBvy8eXDrrWG7UaOS\nNziNHw+HHJLr6qMpnYuiO4CYux8PjAQmmdkJwEwg7u5DgXiiLSIHqOLiENz/+Z/w+9+HScaeeAK+\n+90Q4D/+MUyaFM7WJ0wI6x9/PAxKkexIGeiJLpxtieZBicWByUBimn7mA19okwpFpCCVlISz8dmz\n4Y9/DAH/yCNhyuAPP4TvfS/ZHfPZz8IPfwgrVoQzfcmMhf72FBuZFQMrgSHAbe5+mZltcfduic8N\nqG9sN9t3OjAdoKysrHzhwoUZFbpt2zZKS0sz2rc9FUqdUDi1qs7sy4dat27twJo13Vi1qhurVnXn\ntddCP0xp6UeMHLmFUaO2MGzYRj71qfyfZKytf55VVVUr3X10yg3TuXLauADdgBpgOLCl2Wf1qfbX\nKJf8Uii1qs7sy8daN20Ko2TOPz+MmmkcQdO7dxhVc/fdYZRNPirIUS7uvsXMaoBJwNtm1sfdN5lZ\nH2Bz6/7miIgk9e4NZ58dFoBXXoE77niRjRuHEY/DvfeG9YMHJ+eLj8WgrCx3NeeblH3oZnaYmTV2\nrXQGTgFeAJYA0xKbTQMebKsiReTAM3gwnH76Ju69FzZtCs9h/clP4LjjYPHiEPy9e4cHe1x8MTz4\nIGzZkuuqcyudM/Q+wPxEP3oRsMjdl5pZHbDIzM4HXgOmtmGdInIAMwvBPXw4XHRRuHC6enXyOax3\n3RXCvqgIysuTY+DHjYODD8519e0nZaC7+5+BT+9l/btAdVsUJSKyL8XFMHp0WC67DHbsgGeeSQb8\nTTfB9deH57VWVCTHwI8ZE0bfRJUm5xKRgtexYxjbfvXVYex7fT387nehK2bbtjDm/aSToEcP+Nzn\n4IYbYNWq6A2R1K3/IhI5paXhJqZJk0L7vffCWPjGM/hLLw3ru3cPz2Ft7KIZNiz/h0juiwJdRCKv\nRw/44hfDAvDmm1BTk5ym4P77w/ojjkiOnqmuDo/3KyQKdBE54BxxBHzta2FxD0MkG5/D+sgj8Mtf\nhu2OPDLZ/15VFR7Qnc8U6CJyQDMLwX3kkfBv/xYCfu3aZMAvXAh33hm2HTEiefY+YQJ07Zrb2ptT\noIuINGEWgnvEiHBRddeucAG1sf997ly45ZbkSJtYDHr27MbYsdC5c25rV6CLiOxDhw5huOOYMTBr\nVhgiWVeXPIO/4QbYtWskV1wBJ56Y7IP/zGfCsMn2pGGLIiKt0LFjeMrd974Hy5eHETTXXfdnLrww\n3Kk6e3a4oalHDzj99DAm/rnnoKGh7WvTGbqIyH7o0gXGjn3v4+dSv/tuGEGzbFlYHn44rF+8ODzL\nui0p0EVEsqhnT/jyl8MCsHFjCPaqqrb/2gp0EZE21LcvnHNO+3wt9aGLiESEAl1EoquuDubMCa+Z\ntNPcZ8CCBa07RhtRl4uIRFNdXbgDaOfOMMXizTfDjBnpt+PxcJw0jjFoxw5YsCC9Y8TjYQrINqBA\nF5Foqq0NIbp7d3i9777WtWtrw3HS2McaGtI/Rm1tmwW6ulxEJJoqK8MZcXFxeJ0ypXXtysq0j9FQ\nVJT+MRrHN7YBnaGLSDRVVITujdraEKIVFeF+/ta0Ia1jvDpvHoPPOy/9Y7QRBbqIRFdFxZ4B2tp2\nmvu8vmMHgxvXpXOMNqIuFxGRiFCgi4hEhAJdRCQiFOgiIhGhQBcRiQgFuohIRCjQRUQiQoEuIhIR\nCnQRkYhQoIuIRIQCXUQkIhToIiIRoUAXEYkIBbqISEQo0EVEIkKBLiISEWkHupkVm9lqM1uaaPcw\ns0fNbH3itXvblSkiIqm05gz9YuD5Ju2ZQNzdhwLxRFtERHIkrUA3s37A6cDPmqyeDMxPvJ8PfCG7\npYmISGuYu6feyGwxMAfoAvyHu59hZlvcvVvicwPqG9vN9p0OTAcoKysrX7hwYUaFbtu2jdLS0oz2\nbU+FUicUTq2qM/sKpVbVGVRVVa1099EpN3T3fS7AGcDtifeVwNLE+y3NtqtPdazy8nLPVE1NTcb7\ntqdCqdO9cGpVndlXKLWqzgBY4Sny1d3pkMYfh3HA583sNKATcKiZ/RJ428z6uPsmM+sDbG71nx0R\nEcmalH3o7j7L3fu5+0DgTGCZu38dWAJMS2w2DXiwzaoUEZGU9mcc+nXAKWa2Hjg50RYRkRxJp8vl\nY+5eC9Qm3r8LVGe/JBERyYTuFBURiQgFuohIRCjQRUQiQoEuIhIRCnQRkYhQoIuIRIQCXUQkIhTo\nIiIRoUAXEYkIBbqISEQo0EVEIkKBLiISEQp0EZGIUKCLiESEAl1EJCIU6CIiEaFAFxGJCAW6iEhE\nKNBFRCJCgS4iEhEKdBGRiFCgi4hEhAJdRCQiFOgiIhGhQBcRiQgFuohIRCjQRUQiQoEuIhIRCnQR\nkYhQoIuIRIQCXUQkIhToIiIRoUAXEYkIBbqISEQo0EVEIqJDOhuZ2avAVmA3sMvdR5tZD+DXwEDg\nVWCqu9e3TZkiIpJKa87Qq9x9pLuPTrRnAnF3HwrEE20REcmR/elymQzMT7yfD3xh/8sREZFMpdXl\nAjjwmJntBua6+51AmbtvSnz+FlC2tx3NbDowPdHcZmYvZlhrL+CdDPdtT4VSJxROraoz+wqlVtUZ\n/Es6G5m7p97IrK+7bzSzw4FHgYuAJe7erck29e7ePdNq06hhRZPunrxVKHVC4dSqOrOvUGpVna2T\nVpeLu29MvG4GHgDGAG+bWR+AxOvmtipSRERSSxnoZnaImXVpfA+cCqwFlgDTEptNAx5sqyJFRCS1\ndPrQy4AHzKxx+3vd/fdm9iywyMzOB14DprZdmQDc2cbHz5ZCqRMKp1bVmX2FUqvqbIW0+tBFRCT/\n6U5REZGIUKCLiEREQQS6mU0ysxfN7GUzy5s7Us1snpltNrO1Tdb1MLNHzWx94rXNhnKmy8z6m1mN\nmf3VzNaZ2cX5WKuZdTKzP5nZmkSdV+djnY3MrNjMVpvZ0kQ7X+t81cz+YmbPmdmKxLq8q9XMupnZ\nYjN7wcyeN7OKPK1zWOJn2bi8b2Yz8qHWvA90MysGbgM+BxwDnGVmx+S2qo/9HJjUbF0+TomwC7jE\n3Y8BTgAuSPwM863WHUDM3Y8HRgKTzOwE8q/ORhcDzzdp52udUBhTd9wC/N7djwaOJ/xs865Od38x\n8bMcCZQDHxCGc+e+VnfP6wWoAB5p0p4FzMp1XU3qGQisbdJ+EeiTeN8HeDHXNe6l5geBU/K5VuBg\nYBUwNh/rBPoR/tHGgKX5/LsnTJ7Xq9m6vKoV6Ar8ncRAjXytcy91nwosz5da8/4MHegLvNGkvSGx\nLl+lNSVCrpjZQODTwDPkYa2JboznCDeqPerueVkncDNwKdDQZF0+1gnJqTtWJqbigPyrdRDwv8B/\nJ7qxfpa47yXf6mzuTOBXifc5r7UQAr1gefhTnTfjQs2sFLgPmOHu7zf9LF9qdffdHv5Xth8wxsyG\nN/s853Wa2RnAZndf2dI2+VBnE+MTP9PPEbrbJjT9ME9q7QCMAu5w908D/6RZl0We1PkxMysBPg/8\npvlnuaq1EAJ9I9C/SbtfYl2+ysspEczsIEKYL3D3+xOr87JWAHffAtQQrlHkW53jgM8nnhOwEIiZ\n2S/JvzqBgpm6YwOwIfF/ZACLCQGfb3U29Tlglbu/nWjnvNZCCPRngaFmNijxF/FMwrQD+SrvpkSw\ncJvv3cDz7v6jJh/lVa1mdpiZdUu870zo53+BPKvT3We5ez93H0j473GZu3+dPKsTCmfqDnd/C3jD\nzIYlVlUDfyXP6mzmLJLdLZAPteb6okKaFx5OA14C/gZcket6mtT1K2AT8BHhDON8oCfhYtl64DGg\nRx7UOZ7wv39/Bp5LLKflW63AccDqRJ1rgdmJ9XlVZ7OaK0leFM27OoHBwJrEsq7x30+e1joSWJH4\n/f8W6J6PdSZqPQR4F+jaZF3Oa9Wt/yIiEVEIXS4iIpIGBbqISEQo0EVEIkKBLiISEQp0EZGIUKCL\niESEAl1EJCL+Pw31wEqa513NAAAAAElFTkSuQmCC\n", "text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "file1 = U48S\n", "yslice = 120\n", "deptht = file1.variables['deptht'][:]\n", "yslicemask = 1 - new_domain[:,yslice,:]\n", "pressure1 = gsw_calls.generic_gsw_caller('gsw_p_from_z.m',\n", " [-np.expand_dims(file1.variables['deptht'][:], 1) * np.ones(284),\n", " (np.ones([284,40]) *np.expand_dims(file1.variables['nav_lat'][yslice,:][:],1)).T])\n", "i = 29\n", "density1 = calc_rho(file1.variables['vosaline'][i,:,yslice,126:199],\n", " file1.variables['votemper'][i,:,yslice,126:199],\n", " pressure1[:, 126:199])\n", "rho = 1023.3\n", "index1 = (np.abs(density1 - rho)).argmin(axis=0)\n", "list_of_depths1 = np.zeros((73))\n", "for x in range(73):\n", " list_of_depths1[x] = deptht[index1[x]]\n", "popt, pcov = curve_fit(func, np.arange(0,73), list_of_depths1)\n", "plt.plot(np.arange(0,73), list_of_depths1, 'r.')\n", "plt.grid('on')\n", "plt.ylim(50,0)\n", "plt.plot(np.arange(0,73), func(np.arange(0,73), *popt), 'b-')\n", "print(popt[0])\n", "print(list_of_depths1.max())\n", "print(list_of_depths1.min())" ] }, { "cell_type": "code", "execution_count": 502, "metadata": { "collapsed": false }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "0.216079292873\n", "34.6857566833\n", "8.50123596191\n" ] }, { "data": { "image/png": "iVBORw0KGgoAAAANSUhEUgAAAXQAAAD8CAYAAABn919SAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\njQAAAABJRU5ErkJggg==\n", "text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "file1 = U72S\n", "yslice = 120\n", "deptht = file1.variables['deptht'][:]\n", "yslicemask = 1 - new_domain[:,yslice,:]\n", "pressure1 = gsw_calls.generic_gsw_caller('gsw_p_from_z.m',\n", " [-np.expand_dims(file1.variables['deptht'][:], 1) * np.ones(284),\n", " (np.ones([284,40]) *np.expand_dims(file1.variables['nav_lat'][yslice,:][:],1)).T])\n", "i = 24\n", "density1 = calc_rho(file1.variables['vosaline'][i,:,yslice,126:199],\n", " file1.variables['votemper'][i,:,yslice,126:199],\n", " pressure1[:, 126:199])\n", "rho = 1023.3\n", "index1 = (np.abs(density1 - rho)).argmin(axis=0)\n", "list_of_depths1 = np.zeros((73))\n", "for x in range(73):\n", " list_of_depths1[x] = deptht[index1[x]]\n", "popt, pcov = curve_fit(func, np.arange(0,73), list_of_depths1)\n", "plt.plot(np.arange(0,73), list_of_depths1, 'r.')\n", "plt.grid('on')\n", "plt.ylim(50,0)\n", "plt.plot(np.arange(0,73), func(np.arange(0,73), *popt), 'b-')\n", "print(popt[0])\n", "print(list_of_depths1.max())\n", "print(list_of_depths1.min())" ] }, { "cell_type": "code", "execution_count": 508, "metadata": { "collapsed": false }, "outputs": [ { "data": { "text/plain": [ "(126, 192)" ] }, "execution_count": 508, "metadata": {}, "output_type": "execute_result" }, { "data": { "image/png": "iVBORw0KGgoAAAANSUhEUgAAAXQAAAD8CAYAAABn919SAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nEwa6JNWEgS5JNWGgS1JNGOiSVBP/Dx2/YTwrEI3UAAAAAElFTkSuQmCC\n", "text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "plt.contourf(lake_meshmask.variables['tmask'][0,:,110,:])\n", "plt.xlim(126,192)" ] }, { "cell_type": "code", "execution_count": 524, "metadata": { "collapsed": false }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "0.277936502877\n", "34.6857566833\n", "8.50123596191\n" ] }, { "data": { "image/png": "iVBORw0KGgoAAAANSUhEUgAAAXQAAAD8CAYAAABn919SAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nSUVORK5CYII=\n", "text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "file1 = U24S\n", "yslice = 110\n", "deptht = file1.variables['deptht'][:]\n", "yslicemask = 1 - new_domain[:,yslice,:]\n", "pressure1 = gsw_calls.generic_gsw_caller('gsw_p_from_z.m',\n", " [-np.expand_dims(file1.variables['deptht'][:], 1) * np.ones(284),\n", " (np.ones([284,40]) *np.expand_dims(file1.variables['nav_lat'][yslice,:][:],1)).T])\n", "i = 31\n", "density1 = calc_rho(file1.variables['vosaline'][i,:,yslice,126:191],\n", " file1.variables['votemper'][i,:,yslice,126:191],\n", " pressure1[:, 126:191])\n", "rho = 1023.3\n", "index1 = (np.abs(density1 - rho)).argmin(axis=0)\n", "list_of_depths1 = np.zeros((65))\n", "for x in range(65):\n", " list_of_depths1[x] = deptht[index1[x]]\n", "popt, pcov = curve_fit(func, np.arange(0,65), list_of_depths1)\n", "plt.plot(np.arange(0,65), list_of_depths1, 'r.')\n", "plt.grid('on')\n", "plt.ylim(50,0)\n", "plt.plot(np.arange(0,65), func(np.arange(0,65), *popt), 'b-')\n", "print(popt[0])\n", "print(list_of_depths1.max())\n", "print(list_of_depths1.min())" ] }, { "cell_type": "code", "execution_count": 526, "metadata": { "collapsed": false }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "0.328394329832\n", "34.6857566833\n", "3.50003051758\n" ] }, { "data": { "image/png": "iVBORw0KGgoAAAANSUhEUgAAAXQAAAD8CAYAAABn919SAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\npx5VgacAAAAASUVORK5CYII=\n", "text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "file1 = U48S\n", "yslice = 110\n", "deptht = file1.variables['deptht'][:]\n", "yslicemask = 1 - new_domain[:,yslice,:]\n", "pressure1 = gsw_calls.generic_gsw_caller('gsw_p_from_z.m',\n", " [-np.expand_dims(file1.variables['deptht'][:], 1) * np.ones(284),\n", " (np.ones([284,40]) *np.expand_dims(file1.variables['nav_lat'][yslice,:][:],1)).T])\n", "i = 27\n", "density1 = calc_rho(file1.variables['vosaline'][i,:,yslice,126:191],\n", " file1.variables['votemper'][i,:,yslice,126:191],\n", " pressure1[:, 126:191])\n", "rho = 1023.3\n", "index1 = (np.abs(density1 - rho)).argmin(axis=0)\n", "list_of_depths1 = np.zeros((65))\n", "for x in range(65):\n", " list_of_depths1[x] = deptht[index1[x]]\n", "popt, pcov = curve_fit(func, np.arange(0,65), list_of_depths1)\n", "plt.plot(np.arange(0,65), list_of_depths1, 'r.')\n", "plt.grid('on')\n", "plt.ylim(50,0)\n", "plt.plot(np.arange(0,65), func(np.arange(0,65), *popt), 'b-')\n", "print(popt[0])\n", "print(list_of_depths1.max())\n", "print(list_of_depths1.min())" ] }, { "cell_type": "code", "execution_count": 527, "metadata": { "collapsed": false }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "0.30016347103\n", "34.6857566833\n", "7.50062322617\n" ] }, { "data": { "image/png": "iVBORw0KGgoAAAANSUhEUgAAAXQAAAD8CAYAAABn919SAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\ngg==\n", "text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "file1 = U72S\n", "yslice = 110\n", "deptht = file1.variables['deptht'][:]\n", "yslicemask = 1 - new_domain[:,yslice,:]\n", "pressure1 = gsw_calls.generic_gsw_caller('gsw_p_from_z.m',\n", " [-np.expand_dims(file1.variables['deptht'][:], 1) * np.ones(284),\n", " (np.ones([284,40]) *np.expand_dims(file1.variables['nav_lat'][yslice,:][:],1)).T])\n", "i = 21\n", "density1 = calc_rho(file1.variables['vosaline'][i,:,yslice,126:191],\n", " file1.variables['votemper'][i,:,yslice,126:191],\n", " pressure1[:, 126:191])\n", "rho = 1023.3\n", "index1 = (np.abs(density1 - rho)).argmin(axis=0)\n", "list_of_depths1 = np.zeros((65))\n", "for x in range(65):\n", " list_of_depths1[x] = deptht[index1[x]]\n", "popt, pcov = curve_fit(func, np.arange(0,65), list_of_depths1)\n", "plt.plot(np.arange(0,65), list_of_depths1, 'r.')\n", "plt.grid('on')\n", "plt.ylim(50,0)\n", "plt.plot(np.arange(0,65), func(np.arange(0,65), *popt), 'b-')\n", "print(popt[0])\n", "print(list_of_depths1.max())\n", "print(list_of_depths1.min())" ] }, { "cell_type": "code", "execution_count": 534, "metadata": { "collapsed": false }, "outputs": [ { "data": { "text/plain": [ "(126, 185)" ] }, "execution_count": 534, "metadata": {}, "output_type": "execute_result" }, { "data": { "image/png": "iVBORw0KGgoAAAANSUhEUgAAAXQAAAD8CAYAAABn919SAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nLkmFMOiSVAiDLkmF+H9GfSvCa9vTrwAAAABJRU5ErkJggg==\n", "text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "plt.contourf(lake_meshmask.variables['tmask'][0,:,100,:])\n", "plt.xlim(126,185)" ] }, { "cell_type": "code", "execution_count": 544, "metadata": { "collapsed": false }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "0.527069445535\n", "44.5177230835\n", "6.50031042099\n" ] }, { "data": { "image/png": "iVBORw0KGgoAAAANSUhEUgAAAXQAAAD8CAYAAABn919SAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nCQkVdBGRkPj/TFhEyYuf9EAAAAAASUVORK5CYII=\n", "text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "file1 = U24S\n", "yslice = 100\n", "deptht = file1.variables['deptht'][:]\n", "yslicemask = 1 - new_domain[:,yslice,:]\n", "pressure1 = gsw_calls.generic_gsw_caller('gsw_p_from_z.m',\n", " [-np.expand_dims(file1.variables['deptht'][:], 1) * np.ones(284),\n", " (np.ones([284,40]) *np.expand_dims(file1.variables['nav_lat'][yslice,:][:],1)).T])\n", "i = 45\n", "density1 = calc_rho(file1.variables['vosaline'][i,:,yslice,126:185],\n", " file1.variables['votemper'][i,:,yslice,126:185],\n", " pressure1[:, 126:185])\n", "rho = 1023.3\n", "index1 = (np.abs(density1 - rho)).argmin(axis=0)\n", "list_of_depths1 = np.zeros((59))\n", "for x in range(59):\n", " list_of_depths1[x] = deptht[index1[x]]\n", "popt, pcov = curve_fit(func, np.arange(0,59), list_of_depths1)\n", "plt.plot(np.arange(0,59), list_of_depths1, 'r.')\n", "plt.grid('on')\n", "plt.ylim(50,0)\n", "plt.plot(np.arange(0,59), func(np.arange(0,59), *popt), 'b-')\n", "print(popt[0])\n", "print(list_of_depths1.max())\n", "print(list_of_depths1.min())" ] }, { "cell_type": "code", "execution_count": 549, "metadata": { "collapsed": false }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "0.506463779056\n", "44.5177230835\n", "6.50031042099\n" ] }, { "data": { "image/png": "iVBORw0KGgoAAAANSUhEUgAAAXQAAAD8CAYAAABn919SAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\n", "text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "file1 = U48S\n", "yslice = 100\n", "deptht = file1.variables['deptht'][:]\n", "yslicemask = 1 - new_domain[:,yslice,:]\n", "pressure1 = gsw_calls.generic_gsw_caller('gsw_p_from_z.m',\n", " [-np.expand_dims(file1.variables['deptht'][:], 1) * np.ones(284),\n", " (np.ones([284,40]) *np.expand_dims(file1.variables['nav_lat'][yslice,:][:],1)).T])\n", "i = 37\n", "density1 = calc_rho(file1.variables['vosaline'][i,:,yslice,126:185],\n", " file1.variables['votemper'][i,:,yslice,126:185],\n", " pressure1[:, 126:185])\n", "rho = 1023.3\n", "index1 = (np.abs(density1 - rho)).argmin(axis=0)\n", "list_of_depths1 = np.zeros((59))\n", "for x in range(59):\n", " list_of_depths1[x] = deptht[index1[x]]\n", "popt, pcov = curve_fit(func, np.arange(0,59), list_of_depths1)\n", "plt.plot(np.arange(0,59), list_of_depths1, 'r.')\n", "plt.grid('on')\n", "plt.ylim(50,0)\n", "plt.plot(np.arange(0,59), func(np.arange(0,59), *popt), 'b-')\n", "print(popt[0])\n", "print(list_of_depths1.max())\n", "print(list_of_depths1.min())" ] }, { "cell_type": "code", "execution_count": 555, "metadata": { "collapsed": false }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "0.542115173919\n", "44.5177230835\n", "6.50031042099\n" ] }, { "data": { "image/png": "iVBORw0KGgoAAAANSUhEUgAAAXQAAAD8CAYAAABn919SAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nXCHp1oKkzwAAAABJRU5ErkJggg==\n", "text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "file1 = U72S\n", "yslice = 100\n", "deptht = file1.variables['deptht'][:]\n", "yslicemask = 1 - new_domain[:,yslice,:]\n", "pressure1 = gsw_calls.generic_gsw_caller('gsw_p_from_z.m',\n", " [-np.expand_dims(file1.variables['deptht'][:], 1) * np.ones(284),\n", " (np.ones([284,40]) *np.expand_dims(file1.variables['nav_lat'][yslice,:][:],1)).T])\n", "i = 32\n", "density1 = calc_rho(file1.variables['vosaline'][i,:,yslice,126:185],\n", " file1.variables['votemper'][i,:,yslice,126:185],\n", " pressure1[:, 126:185])\n", "rho = 1023.3\n", "index1 = (np.abs(density1 - rho)).argmin(axis=0)\n", "list_of_depths1 = np.zeros((59))\n", "for x in range(59):\n", " list_of_depths1[x] = deptht[index1[x]]\n", "popt, pcov = curve_fit(func, np.arange(0,59), list_of_depths1)\n", "plt.plot(np.arange(0,59), list_of_depths1, 'r.')\n", "plt.grid('on')\n", "plt.ylim(50,0)\n", "plt.plot(np.arange(0,59), func(np.arange(0,59), *popt), 'b-')\n", "print(popt[0])\n", "print(list_of_depths1.max())\n", "print(list_of_depths1.min())" ] }, { "cell_type": "code", "execution_count": null, "metadata": { "collapsed": true }, "outputs": [], "source": [] }, { "cell_type": "code", "execution_count": null, "metadata": { "collapsed": true }, "outputs": [], "source": [] }, { "cell_type": "code", "execution_count": 179, "metadata": { "collapsed": true }, "outputs": [], "source": [ "density1 = calc_rho(file1.variables['vosaline'][:], file1.variables['votemper'][:], \n", " file1.variables['deptht'][:][np.newaxis, :, np.newaxis, np.newaxis])" ] }, { "cell_type": "code", "execution_count": 96, "metadata": { "collapsed": true }, "outputs": [], "source": [ "thalweg_pts = np.loadtxt('salishsealakethalweg.txt', delimiter=' ', dtype=int)" ] }, { "cell_type": "code", "execution_count": 98, "metadata": { "collapsed": true }, "outputs": [], "source": [ "depth = lake_meshmask.variables['gdept_0'][:]" ] }, { "cell_type": "code", "execution_count": 180, "metadata": { "collapsed": true }, "outputs": [], "source": [ "var = density1[0,...]\n", "dep_thal, distance, var_thal = load_thalweg(\n", " depth[0, ...], var, lakebathy['nav_lon'][:], lakebathy['nav_lat'][:],\n", " thalweg_pts)" ] }, { "cell_type": "code", "execution_count": 181, "metadata": { "collapsed": true }, "outputs": [], "source": [ "xx_thal = distance" ] }, { "cell_type": "code", "execution_count": 102, "metadata": { "collapsed": true }, "outputs": [], "source": [ "def _fill_in_bathy(variable, mesh_mask, thalweg_pts):\n", " \"\"\"For each horizontal point in variable, fill in first vertically masked\n", " point with the value just above.\n", " Use mbathy in mesh_mask file to determine level of vertical masking\n", "\n", " :arg variable: the variable to be filled\n", " :type variable: 2D numpy array\n", "\n", " :arg mesh_mask: Salish Sea NEMO model mesh_mask data\n", " :type mesh_mask: :py:class:`netCDF4.Dataset`\n", "\n", " :arg thalweg_pts: Salish Sea NEMO model grid indices along thalweg\n", " :type thalweg_pts: 2D numpy array\n", "\n", " :returns: newvar, the filled numpy array\n", " \"\"\"\n", " mbathy = mesh_mask.variables['mbathy'][0, :, :]\n", " newvar = np.copy(variable)\n", "\n", " mbathy = mbathy[thalweg_pts[:, 0], thalweg_pts[:, 1]]\n", " for i, level in enumerate(mbathy):\n", " newvar[level, i] = variable[level-1, i]\n", " return newvar" ] }, { "cell_type": "code", "execution_count": 182, "metadata": { "collapsed": false }, "outputs": [], "source": [ "var_plot = _fill_in_bathy(var_thal, lake_meshmask, thalweg_pts)" ] }, { "cell_type": "code", "execution_count": 190, "metadata": { "collapsed": false }, "outputs": [ { "data": { "text/plain": [ "" ] }, "execution_count": 190, "metadata": {}, "output_type": "execute_result" }, { "data": { "image/png": "iVBORw0KGgoAAAANSUhEUgAAAXMAAAD8CAYAAACFK0QrAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nov2FAl0AAAAAAElFTkSuQmCC\n", "text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "plt.contourf(ma.masked_equal(var_plot, 999.84259))\n", "plt.colorbar()" ] }, { "cell_type": "code", "execution_count": 199, "metadata": { "collapsed": false }, "outputs": [ { "data": { "text/plain": [ "(40, 880)" ] }, "execution_count": 199, "metadata": {}, "output_type": "execute_result" } ], "source": [ "fig, ax = plt.subplots()\n", "contour_thalweg(ax, density1, lakebathy, lake_meshmask, np.linspace())" ] }, { "cell_type": "code", "execution_count": 220, "metadata": { "collapsed": false }, "outputs": [], "source": [ "rho = 1023.8\n", "index1 = (np.abs(var_plot - rho)).argmin(axis=0)\n", "list_of_depths1 = np.zeros((880))\n", "for x in range(880):\n", " list_of_depths1[x] = deptht[index1[x]]" ] }, { "cell_type": "code", "execution_count": 192, "metadata": { "collapsed": false }, "outputs": [ { "data": { "text/plain": [ "(40, 880)" ] }, "execution_count": 192, "metadata": {}, "output_type": "execute_result" } ], "source": [ "xx_thal.shape" ] }, { "cell_type": "code", "execution_count": 221, "metadata": { "collapsed": false }, "outputs": [ { "data": { "text/plain": [ "[]" ] }, "execution_count": 221, "metadata": {}, "output_type": "execute_result" }, { "data": { "image/png": "iVBORw0KGgoAAAANSUhEUgAAAXQAAAD8CAYAAABn919SAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nhTDQJakQBrokFcJAl6RCGOiSVIj/B5ryj85cfeBkAAAAAElFTkSuQmCC\n", "text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "plt.plot(range(880), list_of_depths1, 'r.')" ] }, { "cell_type": "code", "execution_count": 556, "metadata": { "collapsed": false }, "outputs": [ { "data": { "text/plain": [ "67.5" ] }, "execution_count": 556, "metadata": {}, "output_type": "execute_result" } ], "source": [ "4.5*15" ] }, { "cell_type": "markdown", "metadata": { "collapsed": true }, "source": [ "Full set up is when one of the density points is at surface (~0.5 m). Tilt slope is calculated at the hour before full set up. Did it for every 10 grid points as per Susan's suggestion. (first one was at y = 200)" ] }, { "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": "3.6.0" } }, "nbformat": 4, "nbformat_minor": 2 }