{ "cells": [ { "cell_type": "markdown", "metadata": {}, "source": [ "Create renewal movie with tides at Point Atkinson" ] }, { "cell_type": "code", "execution_count": 4, "metadata": { "collapsed": false }, "outputs": [], "source": [ "from matplotlib import pylab\n", "import matplotlib.pyplot as plt\n", "import matplotlib.patches as patches\n", "import netCDF4 as nc\n", "import numpy as np\n", "from salishsea_tools import tidetools, stormtools\n", "\n", "from salishsea_tools import (nc_tools,viz_tools)\n", "\n", "from nowcast import figures, analyze\n", "\n", "import os\n", "import glob\n", "from matplotlib import animation\n", "\n", "import datetime\n", "import types\n", "\n", "%matplotlib inline" ] }, { "cell_type": "code", "execution_count": 5, "metadata": { "collapsed": true }, "outputs": [], "source": [ "start = datetime.datetime(2015,12,1)\n", "end = datetime.datetime(2016,1,28)\n", "\n", "numdays = (end-start).days\n", "dates = [start + datetime.timedelta(days=num)\n", " for num in range(0, numdays+1)]" ] }, { "cell_type": "code", "execution_count": 6, "metadata": { "collapsed": false }, "outputs": [], "source": [ "results_home = '/results/SalishSea/nowcast/'\n", "bathy = nc.Dataset('/data/nsoontie/MEOPAR/NEMO-forcing/grid/bathy_meter_SalishSea2.nc')\n", "\n", "thalweg = np.loadtxt('/data/nsoontie/MEOPAR/tools/bathymetry/thalweg_working.txt', dtype=int, unpack=True)" ] }, { "cell_type": "code", "execution_count": 7, "metadata": { "collapsed": false }, "outputs": [], "source": [ "files = analyze.get_filenames(start,end,'1d','grid_T',results_home)" ] }, { "cell_type": "code", "execution_count": 8, "metadata": { "collapsed": true }, "outputs": [], "source": [ "def combine_files(files, var, jss, iss):\n", "\n", " time = np.array([])\n", " var_list = []\n", "\n", " for f in files:\n", " G = nc.Dataset(f)\n", " var_tmp = G.variables[var][:]\n", " var_tmp=var_tmp[:,:,jss,iss]\n", " \n", " var_list.append(var_tmp)\n", " t = nc_tools.timestamp(G, np.arange(var_tmp.shape[0]))\n", " try:\n", " for ind in range(len(t)):\n", " t[ind] = t[ind].datetime\n", " except TypeError:\n", " t = t.datetime\n", " time = np.append(time, t)\n", "\n", " var_ary = np.concatenate(var_list, axis=0)\n", " return var_ary, time" ] }, { "cell_type": "code", "execution_count": 9, "metadata": { "collapsed": false }, "outputs": [], "source": [ "#load \n", "f = nc.Dataset(files[0])\n", "temp = combine_files(files,'votemper',thalweg[0],thalweg[1])\n", "\n", "#f.variables['vosaline'][:,:,thalweg[0],thalweg[1]]\n", "\n", "zlevels = f.variables['deptht']" ] }, { "cell_type": "code", "execution_count": 10, "metadata": { "collapsed": false }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "59\n" ] } ], "source": [ "time = temp[1]\n", "temp=temp[0]\n", "framess = temp.shape[0]\n", "framess\n", "\n", "x, z = np.meshgrid(np.arange(thalweg.shape[1]), zlevels)\n", "\n", "print(framess)" ] }, { "cell_type": "code", "execution_count": 11, "metadata": { "collapsed": false }, "outputs": [], "source": [ "#Making an initial image i.e. our first ssh reading\n", "def init():\n", " return axl\n", " \n", "#The full range of images that will make up the animation\n", "def thalweg_tides(t):\n", " axl.clear()\n", " temp_tzyx = np.ma.masked_values(temp[t, :,:], 0)\n", " \n", " cs = [6.9, 7, 7.5, 8, 8.5, 9, 9.8, 9.9, 10.3, 10.5, 11, 11.5, 12, 13, 14,\n", " 15, 16, 17, 18, 19]\n", " mesh=axl.contourf(x,-z,temp_tzyx,cs,cmap=cmap,extend='both')\n", " \n", " timestamp = time[t]\n", " axl.set_title(timestamp.strftime('%d-%b-%y %H:%M'))\n", " axl.set_xlabel('X Index')\n", " axl.set_ylabel('Depth [m]')\n", " axl.text(50,-400,'Strait of \\n Juan de Fuca')\n", " axl.text(670,-430,'Strait of \\n Georgia')\n", " #axl.add_patch(patches.Rectangle(\n", " # (450, 0), # (x,y)\n", " # 255, # width\n", " # -350, # height\n", " #fill=False,edgecolor='r',linewidth=2)\n", "#)\n", "\n", " return mesh" ] }, { "cell_type": "code", "execution_count": 12, "metadata": { "collapsed": false }, "outputs": [ { "data": { "image/png": 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3AK8HZpP8C+yIiLi4ulPorkkBiug+Mu+zSP5/eH5u/SeAVwD7kvyCzczMzBye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"text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "#Setting up a blank figure\n", "fig, axl = plt.subplots(1, 1, figsize=(20, 8))\n", "land_colour = 'burlywood'\n", "axl.set_axis_bgcolor(land_colour)\n", "\n", "font = {'size' :16}\n", "\n", "plt.rc('font', **font)\n", "\n", "cmap = plt.get_cmap('jet')\n", "cmap.set_bad(land_colour)\n", "mesh = thalweg_tides(0)\n", "cbar = plt.colorbar(mesh, ax=axl)\n", "\n", "cbar.set_ticks([6.9, 7, 7.5, 8, 8.5, 9, 9.8, 9.9, 10.3, 10.5, 11, 11.5, 12, 13, 14,\n", " 15, 16, 17, 18, 19])\n", "cbar.set_label('Temperature [deg C]')\n", "\n", "\n", "\n", " " ] }, { "cell_type": "code", "execution_count": 13, "metadata": { "collapsed": false }, "outputs": [], "source": [ " \n", "\n", "#The animation function \n", "anim = animation.FuncAnimation(fig, thalweg_tides,frames=framess, blit=True, repeat=True)\n", "\n", "#A line that makes it all work\n", "mywriter = animation.FFMpegWriter(fps=5)\n", "\n", "#Save in current folder\n", "anim.save('ThalwegTemp_Animation.mp4',writer=mywriter,bitrate=-1,dpi=200)\n", "\n", "#Show as a pop-up window\n", "#plt.show()" ] }, { "cell_type": "code", "execution_count": 14, "metadata": { "collapsed": false }, "outputs": [ { "name": "stderr", "output_type": "stream", "text": [ "/home/nsoontie/anaconda/lib/python2.7/site-packages/matplotlib/axes/_base.py:1057: UnicodeWarning: Unicode equal comparison failed to convert both arguments to Unicode - interpreting them as being unequal\n", " if aspect == 'normal':\n", "/home/nsoontie/anaconda/lib/python2.7/site-packages/matplotlib/axes/_base.py:1062: UnicodeWarning: Unicode equal comparison failed to convert both arguments to Unicode - interpreting them as being unequal\n", " elif aspect in ('equal', 'auto'):\n" ] }, { "ename": "IndexError", "evalue": "integer sequences in slices must be sorted and cannot have duplicates", "output_type": "error", "traceback": [ "\u001b[1;31m---------------------------------------------------------------------------\u001b[0m", "\u001b[1;31mIndexError\u001b[0m Traceback (most recent call last)", "\u001b[1;32m\u001b[0m in \u001b[0;36m\u001b[1;34m()\u001b[0m\n\u001b[0;32m 10\u001b[0m \u001b[0mcmap\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mset_bad\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;34m'SeaGreen'\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m 11\u001b[0m \u001b[0mmesh\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0max\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mpcolormesh\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mlons\u001b[0m\u001b[1;33m[\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m]\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mlats\u001b[0m\u001b[1;33m[\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m]\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mbathy\u001b[0m\u001b[1;33m[\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m]\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mcmap\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mcmap\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m---> 12\u001b[1;33m \u001b[0max\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mplot\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mlons\u001b[0m\u001b[1;33m[\u001b[0m\u001b[0mthalweg\u001b[0m\u001b[1;33m[\u001b[0m\u001b[1;36m0\u001b[0m\u001b[1;33m,\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m]\u001b[0m\u001b[1;33m,\u001b[0m\u001b[0mthalweg\u001b[0m\u001b[1;33m[\u001b[0m\u001b[1;36m1\u001b[0m\u001b[1;33m,\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m]\u001b[0m\u001b[1;33m]\u001b[0m\u001b[1;33m,\u001b[0m\u001b[0mlats\u001b[0m\u001b[1;33m[\u001b[0m\u001b[0mthalweg\u001b[0m\u001b[1;33m[\u001b[0m\u001b[1;36m0\u001b[0m\u001b[1;33m,\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m]\u001b[0m\u001b[1;33m,\u001b[0m\u001b[0mthalweg\u001b[0m\u001b[1;33m[\u001b[0m\u001b[1;36m1\u001b[0m\u001b[1;33m,\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m]\u001b[0m\u001b[1;33m]\u001b[0m\u001b[1;33m,\u001b[0m\u001b[0mmarker\u001b[0m\u001b[1;33m=\u001b[0m\u001b[1;34m'.'\u001b[0m\u001b[1;33m,\u001b[0m\u001b[0mcolor\u001b[0m\u001b[1;33m=\u001b[0m\u001b[1;34m'k'\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m 13\u001b[0m \u001b[1;31m#iss=450; iee=706\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m 14\u001b[0m \u001b[1;31m#ax.plot(lons[thalweg[0,iss:iee],thalweg[1,iss:iee]],lats[thalweg[0,iss:iee],thalweg[1,iss:iee]],\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n", "\u001b[1;32mnetCDF4/_netCDF4.pyx\u001b[0m in \u001b[0;36mnetCDF4._netCDF4.Variable.__getitem__ (netCDF4/_netCDF4.c:30844)\u001b[1;34m()\u001b[0m\n", "\u001b[1;32m/home/nsoontie/anaconda/lib/python2.7/site-packages/netCDF4/utils.pyc\u001b[0m in \u001b[0;36m_StartCountStride\u001b[1;34m(elem, shape, dimensions, grp, datashape, put)\u001b[0m\n\u001b[0;32m 220\u001b[0m \u001b[1;31m# duplicate indices in the sequence)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m 221\u001b[0m \u001b[0mmsg\u001b[0m \u001b[1;33m=\u001b[0m \u001b[1;34m\"integer sequences in slices must be sorted and cannot have duplicates\"\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m--> 222\u001b[1;33m \u001b[1;32mraise\u001b[0m \u001b[0mIndexError\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mmsg\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m 223\u001b[0m \u001b[1;31m# convert to boolean array.\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m 224\u001b[0m \u001b[1;31m# if unlim, let boolean array be longer than current dimension\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n", "\u001b[1;31mIndexError\u001b[0m: integer sequences in slices must be sorted and cannot have duplicates" ] }, { "data": { "image/png": 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ze1Vz2eG/5uS9xhBPZ3G0xlSKk+af173/06saWfjCaj75zxr2+dxELpkxgdNP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"text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "grid = nc.Dataset('/data/nsoontie/MEOPAR/NEMO-forcing/grid/bathy_meter_SalishSea2.nc')\n", "\n", "lats = grid.variables['nav_lat']\n", "lons = grid.variables['nav_lon']\n", "bathy = grid.variables['Bathymetry']\n", "\n", "fig, ax = plt.subplots(1, 1, figsize=(10, 8))\n", "viz_tools.set_aspect(ax, coords='map', lats=lats)\n", "cmap = plt.get_cmap('Blues')\n", "cmap.set_bad('SeaGreen')\n", "mesh = ax.pcolormesh(lons[:], lats[:], bathy[:], cmap=cmap)\n", "ax.plot(lons[thalweg[0,:],thalweg[1,:]],lats[thalweg[0,:],thalweg[1,:]],marker='.',color='k')\n", "#iss=450; iee=706\n", "#ax.plot(lons[thalweg[0,iss:iee],thalweg[1,iss:iee]],lats[thalweg[0,iss:iee],thalweg[1,iss:iee]],\n", "# marker='.',color='r')\n", "iss=0; iee=300\n", "ax.plot(lons[thalweg[0,iss:iee],thalweg[1,iss:iee]],lats[thalweg[0,iss:iee],thalweg[1,iss:iee]],\n", " marker='.',color='y')\n", "iss=300; iee=600\n", "ax.plot(lons[thalweg[0,iss:iee],thalweg[1,iss:iee]],lats[thalweg[0,iss:iee],thalweg[1,iss:iee]],\n", " marker='.',color='b')\n", "\n", "\n", "\n", "ax.set_xlim([-126,-122])\n", "ax.set_ylim([47,51])\n", "\n", "ax.tick_params(\\\n", " axis='x', # changes apply to the x-axis\n", " which='both', # both major and minor ticks are affected\n", " bottom='off', # ticks along the bottom edge are off\n", " top='off', # ticks along the top edge are off\n", " labelbottom='off') # labels along the bottom edge are off\n", "\n", "ax.tick_params(\\\n", " axis='y', # changes apply to the x-axis\n", " which='both', # both major and minor ticks are affected\n", " left='off', # ticks along the bottom edge are off\n", " right='off', # ticks along the top edge are off\n", " labelleft='off') # labels along the bottom edge are off\n" ] }, { "cell_type": "code", "execution_count": 18, "metadata": { "collapsed": true }, "outputs": [], "source": [ "fig.savefig('diff_thalweg.png',dpi=300)" ] }, { "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": "3.4.4" } }, "nbformat": 4, "nbformat_minor": 0 }