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Last active July 26, 2017 20:58
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Analysis of NCAR 1-degree grid.ipynb
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{
"cells": [
{
"cell_type": "code",
"execution_count": 1,
"metadata": {
"collapsed": true
},
"outputs": [],
"source": [
"import urllib.request\n",
"import os.path\n",
"import tarfile\n",
"import scipy.io\n",
"import netCDF4\n",
"import numpy\n",
"import matplotlib.pyplot as plt\n",
"%matplotlib inline"
]
},
{
"cell_type": "code",
"execution_count": 2,
"metadata": {
"collapsed": true
},
"outputs": [],
"source": [
"def fetch_file_from_web(url, filename=None):\n",
" \"\"\"Download file from url and optionally names it as filename\"\"\"\n",
" if filename is None: local_file = os.path.split(url)[-1]\n",
" else: local_file = filename\n",
" if not os.path.isfile(local_file):\n",
" print('\\rDownload file %s ...'%local_file, end='')\n",
" urllib.request.urlretrieve(url, local_file)\n",
" print('\\rDone.', end='')"
]
},
{
"cell_type": "code",
"execution_count": 3,
"metadata": {
"collapsed": true
},
"outputs": [],
"source": [
"fetch_file_from_web('ftp://ftp.cgd.ucar.edu/pub/njn01/CESM_GFDL/grids/cesm.pop.gx1v6.grid.info.20170303.tar.gz')"
]
},
{
"cell_type": "code",
"execution_count": 4,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"<TarInfo 'cesm.pop.gx1v6.grid.info.20170303' at 0x191f17a3b38> 0\n",
"<TarInfo 'cesm.pop.gx1v6.grid.info.20170303/README' at 0x191f17a3c00> 899\n",
"<TarInfo 'cesm.pop.gx1v6.grid.info.20170303/gx1v6_domain_size.F90' at 0x191f17a3cc8> 1760\n",
"<TarInfo 'cesm.pop.gx1v6.grid.info.20170303/gx1v6.pop.gridinfo.20170303.nc' at 0x191f17a3d90> 19177868\n",
"<TarInfo 'cesm.pop.gx1v6.grid.info.20170303/gx1v6_vert_grid' at 0x191f17a3e58> 2280\n",
"<TarInfo 'cesm.pop.gx1v6.grid.info.20170303/gx1v6_POP_DomainSizeMod.F90' at 0x191f17a3f20> 1899\n",
"<TarInfo 'cesm.pop.gx1v6.grid.info.20170303/pop_in' at 0x191f1874048> 1644\n",
"<TarInfo 'cesm.pop.gx1v6.grid.info.20170303/gx1v6_region_ids' at 0x191f1874110> 790\n",
"<TarInfo 'cesm.pop.gx1v6.grid.info.20170303/grid.F90' at 0x191f18741d8> 104766\n"
]
}
],
"source": [
"# Open the tar file\n",
"TF = tarfile.open('cesm.pop.gx1v6.grid.info.20170303.tar.gz','r')\n",
"# Show list of files in tarfile\n",
"for m in TF.getmembers(): print(m, m.size)"
]
},
{
"cell_type": "code",
"execution_count": 5,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"ANGLE (384, 320)\n",
"ANGLET (384, 320)\n",
"DXT (384, 320)\n",
"DXU (384, 320)\n",
"DYT (384, 320)\n",
"DYU (384, 320)\n",
"HT (384, 320)\n",
"HTE (384, 320)\n",
"HTN (384, 320)\n",
"HU (384, 320)\n",
"HUS (384, 320)\n",
"HUW (384, 320)\n",
"KMT (384, 320)\n",
"KMU (384, 320)\n",
"REGION_MASK (384, 320)\n",
"TAREA (384, 320)\n",
"TLAT (384, 320)\n",
"TLONG (384, 320)\n",
"UAREA (384, 320)\n",
"ULAT (384, 320)\n",
"ULONG (384, 320)\n",
"dz (60,)\n",
"dzw (60,)\n",
"z_t (60,)\n",
"z_w (60,)\n",
"z_w_bot (60,)\n",
"z_w_top (60,)\n"
]
}
],
"source": [
"# Find the member we are looking for\n",
"member = [m for m in TF.getmembers() if 'gx1v6.pop.gridinfo.20170303.nc' in m.name][0]\n",
"# Open the netcdf file via a file-like object\n",
"nc = scipy.io.netcdf.netcdf_file(TF.extractfile(member), 'r', mmap=False)\n",
"# List variables and shapes in file\n",
"for v in nc.variables: print(v, nc.variables[v].shape)"
]
},
{
"cell_type": "code",
"execution_count": 6,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"OrderedDict([('title', b'giaf.c2b4m.tidal.port.010'),\n",
" ('history',\n",
" b'Fri Mar 3 14:53:21 2017: ncks -v ULAT,ULONG,TLAT,TLONG,KMU,KMT,DXU,DXT,DYU,DYT,REGION_MASK,UAREA,TAREA,HU,HUS,HUW,HT,HTN,HTE,ANGLE,ANGLET,z_t,z_w,z_w_top,z_w_bot,dz,dzw giaf.c2b4m.tidal.port.010.pop.h.nstep1.0001-01-02-03600.nc gx1v6.pop.gridinfo.20170303.nc\\nnone'),\n",
" ('Conventions',\n",
" b'CF-1.0; http://www.cgd.ucar.edu/cms/eaton/netcdf/CF-current.htm'),\n",
" ('contents', b'Diagnostic and Prognostic Variables'),\n",
" ('source', b'CCSM POP2, the CCSM Ocean Component'),\n",
" ('revision', b'$Id: tavg.F90 80840 2016-09-29 13:32:09Z jet $'),\n",
" ('calendar', b'All years have exactly 365 days.'),\n",
" ('start_time',\n",
" b'This dataset was created on 2017-02-24 at 15:20:22.7'),\n",
" ('cell_methods',\n",
" b'cell_methods = time: mean ==> the variable values are averaged over the time interval between the previous time coordinate and the current one. cell_methods absent ==> the variable values are at the time given by the current time coordinate.'),\n",
" ('nsteps_total', 1),\n",
" ('tavg_sum', 3600.0),\n",
" ('NCO', b'\"4.5.5\"')])"
]
},
"execution_count": 6,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"# Global attributes\n",
"nc._attributes"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"# All data has the same shape which means staggering must be determined from values"
]
},
{
"cell_type": "code",
"execution_count": 7,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"ULONG @ j=0, i=0:3 : [ 321.12500894 322.25000897 323.375009 324.50000903]\n",
"ULONG @ j=0, i=N-7:N : [ 315.50000878 316.62500881 317.75000884 318.87500887 320.0000089 ]\n",
"TLONG @ j=0, i=0:3 : [ 320.56250892 321.68750895 322.81250898 323.93750901]\n",
"TLONG @ j=0, i=N-7:N : [ 314.93750876 316.0625088 317.18750883 318.31250886 319.43750889]\n"
]
},
{
"data": {
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5/3ikeJoHDp/PfSdfwGMHz+Wrzz6HZ4s9ns1jBzKjNd3UcU3DLfuRlrMyA9Ghb4SJ39/P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\nGBs2tZnyAAAAAElFTkSuQmCC\n",
"text/plain": [
"<matplotlib.figure.Figure at 0x191f18847b8>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"plt.subplot(121)\n",
"v = nc.variables['ULONG']\n",
"plt.pcolormesh( v[:] ); plt.colorbar(); plt.xlabel('i'); plt.ylabel('j'); plt.title('ULONG');\n",
"print('ULONG @ j=0, i=0:3 :', v[0,:4])\n",
"print('ULONG @ j=0, i=N-7:N :', v[0,-5:])\n",
"plt.subplot(122)\n",
"v = nc.variables['TLONG']\n",
"plt.pcolormesh( v[:] ); plt.colorbar(); plt.xlabel('i'); plt.ylabel('j'); plt.title('TLONG');\n",
"print('TLONG @ j=0, i=0:3 :', v[0,:4])\n",
"print('TLONG @ j=0, i=N-7:N :', v[0,-5:])"
]
},
{
"cell_type": "code",
"execution_count": 8,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"ULAT @ j=0, i=0:3 : [-78.95289509 -78.95289509 -78.95289509 -78.95289509]\n",
"ULAT @ j=0, i=N-7:N : [-78.95289509 -78.95289509 -78.95289509 -78.95289509 -78.95289509]\n",
"ULAT max 89.977342085\n",
"TLAT @ j=0, i=0:3 : [-79.22052261 -79.22052261 -79.22052261 -79.22052261]\n",
"TLAT @ j=0, i=N-7:N : [-79.22052261 -79.22052261 -79.22052261 -79.22052261 -79.22052261]\n",
"TLAT max 89.7064096419\n"
]
},
{
"data": {
"image/png": 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BUmP7gd2HN/ntiXQNcAdwh6q+v/z+Zgptf6Z6YqmIHAXuWbuwJVk7FT9F0BU1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\nQmCC\n",
"text/plain": [
"<matplotlib.figure.Figure at 0x191f3ce60b8>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"plt.subplot(121)\n",
"v = nc.variables['ULAT']\n",
"plt.pcolormesh( v[:] ); plt.colorbar(); plt.xlabel('i'); plt.ylabel('j'); plt.title('ULAT');\n",
"print('ULAT @ j=0, i=0:3 :', v[0,:4])\n",
"print('ULAT @ j=0, i=N-7:N :', v[0,-5:])\n",
"print('ULAT max', v[:].max())\n",
"plt.subplot(122)\n",
"v = nc.variables['TLAT']\n",
"plt.pcolormesh( v[:] ); plt.colorbar(); plt.xlabel('i'); plt.ylabel('j'); plt.title('TLAT');\n",
"print('TLAT @ j=0, i=0:3 :', v[0,:4])\n",
"print('TLAT @ j=0, i=N-7:N :', v[0,-5:])\n",
"print('TLAT max', v[:].max())"
]
},
{
"cell_type": "code",
"execution_count": 9,
"metadata": {},
"outputs": [
{
"data": {
"image/png": 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IIOEuFoSWVSSxKYn65581MxHZChzE6c76u6rOEpEDqtrJd1yA/f7HQa+dCkwF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\ndWe1cf995T1o8loG79mPS+GqT5WYGrq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ASUVORK5CYII=\n",
"text/plain": [
"<matplotlib.figure.Figure at 0x191f4092be0>"
]
},
"metadata": {},
"output_type": "display_data"
},
{
"data": {
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lU9Qkb1hP+IQJZ69sAlu1JHzCBJI3rC+Qqx1vTW3QpEkTrrrqKurXr0+NGjVo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\n407HzMxK407HzMxK407HzMxK8y8PQkpmRmmZHQAAAABJRU5ErkJggg==\n",
"text/plain": [
"<matplotlib.figure.Figure at 0x191f3bf2d30>"
]
},
"metadata": {},
"output_type": "display_data"
},
{
"data": {
"image/png": 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X+KJPO6LeXEBoGmy47WJ6zV3OmZZkgoYd0WQjN0ceJ06X1bzzDg5Mm07Nu+76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\nFf1Hv0e5sIpeh2aMMUHBEk0+HUzYzZc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"text/plain": [
"<matplotlib.figure.Figure at 0x191f4128780>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"def lplt():\n",
" j = numpy.arange(nc.variables['TLONG'].shape[0])\n",
" plt.plot(j+1, nc.variables['ULAT'][:].min(axis=-1),'s-',label='ULAT min');\n",
" plt.plot(j+1, nc.variables['ULAT'][:].max(axis=-1),'.-',label='ULAT max');\n",
" plt.plot(j+0.5, nc.variables['TLAT'][:].min(axis=-1),'o-',label='TLAT min');\n",
" plt.plot(j+0.5, nc.variables['TLAT'][:].max(axis=-1),'x-',label='TLAT max');\n",
" plt.legend(loc='upper left'); plt.xlabel('j'); plt.ylabel('Latitude ($^{\\circ}N$)')\n",
" plt.grid()\n",
"lplt(); plt.title('Meridional resolution range');\n",
"plt.figure();\n",
"lplt(); plt.xlim(184,190); plt.ylim(-1,1); plt.title('Equatorial meridional resolution');\n",
"plt.figure();\n",
"lplt(); plt.xlim(50,55); plt.ylim(-53,-50); plt.title('Southern Ocean meridional resolution');"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Observations:\n",
"- Grid is 320 x 384 points (longitude x latitude)\n",
"- Nominally 1.125 degree zonal resolution\n",
"- NE indexing conventions since ULONG(0,0) is east of TLONG(0,0) and ULAT(0,0) is north of TLAT(0,0)\n",
" - this is the same as FMS and MOM6\n",
"- mesh has two singularities (poles) with northern singularity twisted away from north pole"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"# Construct a supergrid\n",
"\n",
"- This supergrid will be twice as fine as model grid so model cells can be constructed by combining four cells appropriately\n",
"- Data is symmetric so that supergrid mesh node locations are one row/column longer than cell areas"
]
},
{
"cell_type": "code",
"execution_count": 10,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Coarse mesh = 320 x 384, supergrid = 640 x 768\n"
]
}
],
"source": [
"nj,ni = nc.variables['TAREA'].shape\n",
"print('Coarse mesh = %i x %i, supergrid = %i x %i'%(ni,nj,2*ni,2*nj))\n",
"x = numpy.zeros((2*nj+1,2*ni+1))\n",
"y = numpy.zeros((2*nj+1,2*ni+1))\n",
"area = numpy.zeros((2*nj,2*ni))\n",
"dx = numpy.zeros((2*nj+1,2*ni))\n",
"dy = numpy.zeros((2*nj,2*ni+1))\n",
"# Fill in known values\n",
"x[1::2,1::2] = nc.variables['TLONG'][:,:]\n",
"y[1::2,1::2] = nc.variables['TLAT'][:,:]\n",
"x[2::2,2::2] = nc.variables['ULONG'][:,:]\n",
"y[2::2,2::2] = nc.variables['ULAT'][:,:]"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Super grid node positions\n",
"\n",
"- The model T-cell centers and T corners correspond to data in the CESM grid file\n",
" - these are the [1::2,1::2] and [::2,::2] nodes in the supergrid\n",
"- The model u-point and v-point (C-grid nomenclature) are not porovided and need to be interpolated/extrapolated"
]
},
{
"cell_type": "code",
"execution_count": 11,
"metadata": {},
"outputs": [
{
"data": {
"image/png": 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KzslbdQNhbQ1i1XatMXl335f+PQg8hNYjiyEkj7SlA0aCI22LssSq7cqNvJmtMLOTu6+B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\nupMWVzYEAAAAAElFTkSuQmCC\n",
"text/plain": [
"<matplotlib.figure.Figure at 0x191f3f1d320>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"# Plot longitude for the four corners of mesh\n",
"plt.subplot(221); plt.pcolormesh(x[-19:,:20]); plt.colorbar(); # top-left\n",
"plt.subplot(222); plt.pcolormesh(x[-19:,-19:]); plt.colorbar(); # top-right\n",
"plt.subplot(223); plt.pcolormesh(x[:20,:20]); plt.colorbar(); # bottom-left\n",
"plt.subplot(224); plt.pcolormesh(x[:20,-19:]); plt.colorbar(); # bottom-right"
]
},
{
"cell_type": "code",
"execution_count": 12,
"metadata": {
"collapsed": true
},
"outputs": [],
"source": [
"def av_longs(x0, x1):\n",
" \"\"\"Returns average of x0 and x1, taking into account periodicity\"\"\"\n",
" dx = numpy.abs( x1 - x0 )\n",
" xa = 0.5 * ( x0 + x1 )\n",
" xa[dx>180] = xa[dx>180] + 180.\n",
" return xa"
]
},
{
"cell_type": "code",
"execution_count": 13,
"metadata": {
"collapsed": true
},
"outputs": [],
"source": [
"# Apply zonal periodicity on q-point longitude\n",
"x[2::2,0] = x[2::2,-1]\n",
"# Meridionally average for v-point longitude\n",
"x[2:-1:2,1::2] = av_longs( x[1:-2:2,1::2] , x[3::2,1::2] )\n",
"# Longitude of southern edge by copying first q row\n",
"x[0,:] = x[2,:]\n",
"# Meridionally average for u-point longitude\n",
"x[1:-1:2,::2] = av_longs( x[:-2:2,::2] , x[2::2,::2] )\n",
"# Zonally average for top-row of v-point longitude\n",
"x[-1,1::2] = av_longs( x[-1,:-1:2] , x[-1,2::2])"
]
},
{
"cell_type": "code",
"execution_count": 14,
"metadata": {},
"outputs": [
{
"data": {
"image/png": 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FozqR1IyorjGrnwSOA7YADwAfG1ZGqZ/GlcAfmdkvsutqvuaVSGP0DSO737Vp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\n",
"text/plain": [
"<matplotlib.figure.Figure at 0x191f40f2be0>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"# Plot longitude for the four corners of mesh\n",
"plt.subplot(221); plt.pcolormesh(x[-19:,:20]); plt.colorbar(); # top-left\n",
"plt.subplot(222); plt.pcolormesh(x[-19:,-19:]); plt.colorbar(); # top-right\n",
"plt.subplot(223); plt.pcolormesh(x[:20,:20]); plt.colorbar(); # bottom-left\n",
"plt.subplot(224); plt.pcolormesh(x[:20,-19:]); plt.colorbar(); # bottom-right"
]
},
{
"cell_type": "code",
"execution_count": 15,
"metadata": {},
"outputs": [
{
"data": {
"image/png": 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beycuBlbj8jQz+4OSa5WdRTlOMIlr2429E5961yI7TjokrG039k5cDKzeW13H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\ndxzHaQFu7B3HcVqAG3vHcZwW8P8BiT88XPgnn/8AAAAASUVORK5CYII=\n",
"text/plain": [
"<matplotlib.figure.Figure at 0x191f67176a0>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"# Plot latitude for the four corners of mesh\n",
"plt.figure()\n",
"plt.subplot(221); plt.pcolormesh(y[-19:,:20]); plt.colorbar(); # top-left\n",
"plt.subplot(222); plt.pcolormesh(y[-19:,-19:]); plt.colorbar(); # top-right\n",
"plt.subplot(223); plt.pcolormesh(y[:20,:20]); plt.colorbar(); # bottom-left\n",
"plt.subplot(224); plt.pcolormesh(y[:20,-19:]); plt.colorbar(); # bottom-right"
]
},
{
"cell_type": "code",
"execution_count": 16,
"metadata": {
"collapsed": true
},
"outputs": [],
"source": [
"# Apply zonal periodicity on latitude q-points\n",
"y[2::2,0] = y[2::2,-1]\n",
"# Longitudinally average for u-point latitude\n",
"y[1::2,2:-1:2] = 0.5*( y[1::2,1:-2:2] + y[1::2,3::2])\n",
"y[1::2,0] = 0.5*( y[1::2,1] + y[1::2,-2])\n",
"y[1::2,-1] = y[1::2,0]\n",
"# Longitudinally average for u-point latitude\n",
"y[::2,1:-1:2] = 0.5*( y[::2,:-2:2] + y[::2,2::2])\n",
"#y[::2,-2] = 0.5*( y[::2,-3] + y[::2,-1] )\n",
"# Latitude of southern edge q-points\n",
"y[0,:] = y[1,:] + ( y[1,:] - y[2,:] )"
]
},
{
"cell_type": "code",
"execution_count": 17,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"y max: 89.977342085\n"
]
},
{
"data": {
"image/png": 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2BPbwJa0ys93p14uAbXnnO04bM3GoxF5Q1jZw6bF/BFwNvJok5sjbzezAgPJc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\nDb7jOM6M4A2+4zjOjOANvuM4zozw/wHznAOWIcxOCAAAAABJRU5ErkJggg==\n",
"text/plain": [
"<matplotlib.figure.Figure at 0x191f3d8cac8>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"# Plot latitude for the four corners of mesh\n",
"plt.figure()\n",
"plt.subplot(221); plt.pcolormesh(y[-19:,:20]); plt.colorbar(); # top-left\n",
"plt.subplot(222); plt.pcolormesh(y[-19:,-19:]); plt.colorbar(); # top-right\n",
"plt.subplot(223); plt.pcolormesh(y[:20,:20]); plt.colorbar(); # bottom-left\n",
"plt.subplot(224); plt.pcolormesh(y[:20,-19:]); plt.colorbar(); # bottom-right\n",
"print('y max:',y.max())"
]
},
{
"cell_type": "code",
"execution_count": 18,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"(-180, 180)"
]
},
"execution_count": 18,
"metadata": {},
"output_type": "execute_result"
},
{
"data": {
"image/png": 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6tPGEmAkd25lzn485iz12YBR7QBc6mtDEOYSv4hnqhHH4+/ZyDXFQmhymZT2W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\n0Utwlp42OMvg5EKVM+e9J+9tzMrF4rQ2G4uZdXBq5cytDyJ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"text/plain": [
"<matplotlib.figure.Figure at 0x191f4111860>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"plt.figure(figsize=(15,7))\n",
"s=8\n",
"plt.plot( x[::s,::s].flatten(), y[::s,::s].flatten(), 'k.');\n",
"plt.plot( x[::s,::s].flatten()-360, y[::s,::s].flatten(), 'k.');\n",
"plt.xlim(-180,180)"
]
},
{
"cell_type": "code",
"execution_count": 19,
"metadata": {},
"outputs": [
{
"data": {
"image/png": 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BnAsg6VDg5oiYGhE7JF0G3AUMAG6JiLWV+kfEWklLgHXADuDSiNiZ+lwC3Ars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\nAYdkCBkNwB3PAAAAAElFTkSuQmCC\n",
"text/plain": [
"<matplotlib.figure.Figure at 0x191f554f7f0>"
]
},
"metadata": {},
"output_type": "display_data"
},
{
"data": {
"image/png": 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KUH9EbAZeknRssulMYA0FqL1XWV/9buQDmE3pTpmfAddkXU+V+r4LbAJ2UnoX\ncgkwHngEWAc8DIxLtb8meS1rgVk5qP90St3lZ4CVyWN2EV4DcCLwdFL7auDaZHvua6/yWt7P3ruS\nClE/pbsFVyWP57r/fxao/plAe/Lv537gsKLUXu3hKTHMzKzMcBpKMjOzAXAwmJlZGQeDmZmVcTCY\nmVkZB4OZmZVxMJjVkaQfZ12DWa18u6qZmZVxj8GsjiS90n8rs3xzMJiZWRkHg5mZlXEwmJlZGQeD\nmZmVcTCYmVkZ365qZmZl3GMwM7MyDgYzMyvjYDAzszIOBjMzK+NgMDOzMg4GMzMr42AwM7My/x9B\nqr2JId0TxQAAAABJRU5ErkJggg==\n",
"text/plain": [
"<matplotlib.figure.Figure at 0x191f564c400>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"# How zonally uniform are coordinates\n",
"plt.figure()\n",
"plt.plot( numpy.mod( x[3,1:]-x[3,:-1], 360 )*ni/360, label='x[j=1]');\n",
"plt.plot( numpy.mod( x[2,1:]-x[2,:-1], 360 )*ni/360, label='x[j=1]');\n",
"plt.plot( numpy.mod( x[1,1:]-x[1,:-1], 360 )*ni/360, label='x[j=0]');\n",
"plt.plot( numpy.mod( x[0,1:]-x[0,:-1], 360 )*ni/360, label='x[j=0]');\n",
"plt.ylim( 0.5-1e-5, 0.5+1e-5); plt.xlabel('i'); plt.legend(); plt.title('$\\delta_i$ x[j=0:3,:] / (360/ni) ');\n",
"plt.figure()\n",
"plt.plot( y[3,1:]-y[3,:-1], label='y[j=1]');\n",
"plt.plot( y[2,1:]-y[2,:-1], label='y[j=1]');\n",
"plt.plot( y[1,1:]-y[1,:-1], label='y[j=0]');\n",
"plt.plot( y[0,1:]-y[0,:-1], label='y[j=0]');\n",
"plt.xlabel('i'); plt.legend(); plt.title('$\\delta_i$ y[j=0:3,:]');"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Cell area\n",
"\n",
"- T-cell and q-cell areas are provided in the CESM grid file\n",
"- We need to find supergrid cells that when combined in groups of four give the same values"
]
},
{
"cell_type": "code",
"execution_count": 20,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"OrderedDict([('long_name', b'area of T cells'),\n",
" ('units', b'centimeter^2'),\n",
" ('coordinates', b'TLONG TLAT'),\n",
" ('_FillValue', 9.969209968386869e+36),\n",
" ('missing_value', 9.969209968386869e+36)])"
]
},
"execution_count": 20,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"nc.variables['TAREA']._attributes"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Note: _Units of area are cm$^2$_"
]
},
{
"cell_type": "code",
"execution_count": 21,
"metadata": {
"scrolled": false
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"TAREA @ j=0:3, i=0 : [ 1.12478609e+09 1.45745047e+09 1.52530781e+09 1.59303254e+09]\n",
"TAREA @ j=0, i=0:3 : [ 1.12478609e+09 1.12464644e+09 1.12436015e+09 1.12393160e+09]\n",
"UAREA @ j=0:3, i=0 : [ 1.42348938e+09 1.49141155e+09 1.55920406e+09 1.62686101e+09]\n",
"UAREA @ j=0, i=0:3 : [ 1.42348938e+09 1.42348938e+09 1.42348938e+09 1.42348938e+09]\n"
]
},
{
"data": {
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F4UnHpfuPRe29vDhtJy67gom1aZd7Y9wewesgfaJiWEn5NxcnD4evmwFTQ6ejr2U47Ntw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\nUFBQUFAQoCiGgoKCgoIA/z+OadGjzkYBugAAAABJRU5ErkJggg==\n",
"text/plain": [
"<matplotlib.figure.Figure at 0x191f3cf5ac8>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"Tarea = nc.variables['TAREA'][:]*1e-4\n",
"Uarea = nc.variables['UAREA'][:]*1e-4\n",
"plt.subplot(121)\n",
"plt.pcolormesh( Tarea[:] ); plt.colorbar(); plt.xlabel('i'); plt.ylabel('j'); plt.title('TAREA');\n",
"print('TAREA @ j=0:3, i=0 :', Tarea[:4,0])\n",
"print('TAREA @ j=0, i=0:3 :', Tarea[0,:4])\n",
"plt.subplot(122)\n",
"plt.pcolormesh( Uarea[:] ); plt.colorbar(); plt.xlabel('i'); plt.ylabel('j'); plt.title('UAREA');\n",
"print('UAREA @ j=0:3, i=0 :', Uarea[:4,0])\n",
"print('UAREA @ j=0, i=0:3 :', Uarea[0,:4])"
]
},
{
"cell_type": "code",
"execution_count": 22,
"metadata": {},
"outputs": [
{
"data": {
"image/png": 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SQqMCmDp/KIMui8HbCa1zZ2g1uYvIq8BNwCljzIgm1g8BXgPGAr82xjzt9Cjb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\n",
"text/plain": [
"<matplotlib.figure.Figure at 0x191f55ae860>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"plt.plot( numpy.arange(ni)+0.5, Tarea[2,:], label='TAREA[j=2]');\n",
"plt.plot( numpy.arange(ni)+1, Uarea[1,:], label='UAREA[j=1]');\n",
"plt.plot( numpy.arange(ni)+0.5, Tarea[1,:], label='TAREA[j=1]');\n",
"plt.plot( numpy.arange(ni)+1, Uarea[0,:], label='UAREA[j=0]');\n",
"plt.plot( numpy.arange(ni)+0.5, Tarea[0,:], label='TAREA[j=0]');\n",
"plt.xlabel('i'); plt.legend(); plt.title('Areas along southern-most row');"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Info from Gokhan: ___The first row of TAREA is all land and not used in the model and was corrected to be zonally constant in later versions of file___"
]
},
{
"cell_type": "code",
"execution_count": 23,
"metadata": {},
"outputs": [
{
"data": {
"image/png": 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tqVGjBvXr16dhw4Ya65S6uLjg7u6eNdY9+zDK3PRl1skcKDB8+HCdmR51MXny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8w/Bv2DYN/6u1yk3U7lihWUvPYa9pJSgkePJvqB+/Frf/4bPEiHpKKohsJMPQWZlZScMFBZWPNL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\n",
"text/plain": [
"<matplotlib.figure.Figure at 0x191f3fb6f60>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"plt.plot( numpy.arange(ni)+1, Uarea[-1,:], label='UAREA[j=N]');\n",
"plt.plot( numpy.arange(ni)+0.5, Tarea[-1,:], label='TAREA[j=N]');\n",
"plt.plot( numpy.arange(ni)+1, Uarea[-2,:], label='UAREA[j=N-1]');\n",
"plt.plot( numpy.arange(ni)+0.5, Tarea[-2,:], label='TAREA[j=N-1]');\n",
"plt.plot( numpy.arange(ni)+1, Uarea[-3,:], label='UAREA[j=N-2]');\n",
"plt.plot( numpy.arange(ni)+0.5, Tarea[-3,:], label='TAREA[j=N-2]');\n",
"plt.xlabel('i'); plt.legend(); plt.title('Areas along northern-most row');"
]
},
{
"cell_type": "code",
"execution_count": 24,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"0.0 : j(ULAT==0)=186 is the equator\n",
"[ 72.4135549 72.60423283 73.07920762 73.76156976 74.56052597\n",
" 75.39576853 76.20871395 76.96275386 77.63834567 78.22727339\n",
" 78.72798153 79.14235405 79.47369505 79.72554494 79.9010238\n",
" 80.00248635 80.03135232 79.98803274 79.87191193 79.68137499\n",
" 79.41389638 79.06623679 78.63483733 78.11656152 77.51001862\n",
" 76.81779391 76.04994927 75.22896695 74.3955437 73.61289675\n",
" 72.96476997 72.54148071] : ULAT(end,::10) is around the singularity\n",
"2.54387631582e+14 is area of northern hemisphere (m^2)\n",
"6362943.42484 is apparent readius of planet (m)\n"
]
}
],
"source": [
"# ULAT[186,:] = 0 so TAREA[187:] spans the northern hemisphere\n",
"print( nc.variables['ULAT'][186,0], ': j(ULAT==0)=186 is the equator')\n",
"print( nc.variables['ULAT'][-1,::10], ': ULAT(end,::10) is around the singularity')\n",
"print( Tarea[187:,:].sum(), 'is area of northern hemisphere (m^2)' )\n",
"print( numpy.sqrt( Tarea[187:,:].sum() *0.5 / numpy.pi ), 'is apparent readius of planet (m)' )"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"### This significant mismatch in $R_e$ appears to be because of a hole around the singularity"
]
},
{
"cell_type": "code",
"execution_count": 25,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"(0.125, 0.125, 0.0, 0.0) unit test\n",
"(1423355067.5751183, 1423489379.3685248, -134311.79340648651, -9.4353913245259806e-05) UAREA[0,0]\n",
"(1457461025.8924561, 1457450466.3793309, 10559.513125181198, 7.2451952013255397e-06) TAREA[1,0]\n"
]
},
{
"data": {
"image/png": 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DwgZC/EPo26Qv/WP706RGk2KVbYwh5edfOPHOO6SuWYNPSAhhfftS47bBBF50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\nvn37mDp1KjNmzIgp7mjlNYtYWqJIC/C3gHUJ3A5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"text/plain": [
"<matplotlib.figure.Figure at 0x191f3ecdc88>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"def latlon_area(dlambda, phiS, phiN, R=6370e3):\n",
" d2r = numpy.pi / 180.\n",
" return (R * R) * ( d2r * dlambda ) * ( numpy.sin( d2r * phiN ) - numpy.sin( d2r * phiS ) )\n",
"def cerr(val, ans):\n",
" return val, ans, val-ans, (val-ans)/abs(ans)\n",
"print( cerr( latlon_area( 90, 0, 90, R=1 )/numpy.pi/4, 0.125), 'unit test' )\n",
"print( cerr( latlon_area( x[0,2] - x[0,0], y[1,0], y[3,0]), Uarea[0,0] ) , 'UAREA[0,0]')\n",
"print( cerr( latlon_area( x[0,2] - x[0,0], y[2,0], y[4,0]), Tarea[1,0] ) , 'TAREA[1,0]')\n",
"a = latlon_area( x[0,2] - x[0,0], y[0:-2:2,0], y[2::2,0], R=6369.977e3)\n",
"plt.plot( ( a[1:187] - Tarea[1:187,0] ) / a[1:187], label='f($\\phi$)-TAREA')\n",
"b = latlon_area( x[0,2] - x[0,0], y[1:-2:2,0], y[3::2,0], R=6369.977e3)\n",
"plt.plot( ( b[1:187] - Uarea[1:187,0] ) / b[1:187], label='f($\\phi$)-UAREA')\n",
"c = latlon_area( x[0,2] - x[0,0], (y[0:-5:2,0]+y[2:-3:2,0])/2, (y[2:-3:2,0]+y[4:-1:2,0])/2, R=6370e3)\n",
"plt.plot( ( c[1:187] - Uarea[1:187,0] ) / c[1:187], label='f($<\\phi>$)-UAREA')\n",
"d = 0.5 * ( Tarea[:-1,0] + Tarea[1:,0] )\n",
"plt.plot( ( d[1:187] - Uarea[1:187,0] ) / d[1:187], label='<TAREA>-UAREA')\n",
"plt.legend(); plt.title('Fractional difference between analytic and file');"
]
},
{
"cell_type": "code",
"execution_count": 26,
"metadata": {},
"outputs": [
{
"data": {
"image/png": 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sdlqU+EWk1WrwGyD1yufOncuwYcPo0KEDF110EVOmTOGee+6JJ/RLLrmEnTt3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\nSf8KlBV7AAAAAElFTkSuQmCC\n",
"text/plain": [
"<matplotlib.figure.Figure at 0x191f3e829b0>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"Tarea[0,:] = latlon_area( x[0,2] - x[0,0], y[0,0], y[2,0] );\n",
"plt.plot( numpy.arange(ni)+0.5, Tarea[2,:], label='TAREA[j=2]');\n",
"plt.plot( numpy.arange(ni)+1, Uarea[1,:], label='UAREA[j=1]');\n",
"plt.plot( numpy.arange(ni)+0.5, Tarea[1,:], label='TAREA[j=1]');\n",
"plt.plot( numpy.arange(ni)+1, Uarea[0,:], label='UAREA[j=0]');\n",
"plt.plot( numpy.arange(ni)+0.5, Tarea[0,:], label='TAREA[j=0]');\n",
"plt.xlabel('i'); plt.legend(); plt.title('Areas along southern-most row after fix');"
]
},
{
"cell_type": "code",
"execution_count": 27,
"metadata": {
"scrolled": false
},
"outputs": [
{
"data": {
"image/png": 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+G/t4pbDSW0PrrugAAOgr2xttH5m6HyXpeZI+LelKSeekwc6R9P7UfaWkrbYP\nsX2SpJMlXTvPvMcbHctogCwy7aXdEgpgUBb5bmn6+3LZ39HzKPPW0NYqOgAAOmyTpI/YvlHSPyh7\ndOIDkt4g6Xm2b5f03PRZEXGzpCsk3SLprySdHxF7Zs3Ebr8h0bXGS+MGt8BAMrB9v63v064kiWVm\nuUnSpenNn2uSroiID9j+uKQrbJ8r6bOSXixlFZ3tUUW3WyUrOgAA+iQibpT0tILyByQ9Z8I4F0u6\nuOHQalFXo2TwVwMX+ZH7eefH7aHtWnaLfmDJ27g17dXeBX4aPb/6hnbozNxzVr2iAwAA+9TZplwo\nCRxaiwwYstHxPucX0KLJ4Miyz9u0bfE1BgAAVsLALyw0a5krlw3ZnmVvZ7Z1I4ayWgeymAAAYFyT\njZ3e3xI6tEsDGLYVyHzquio4Mr5KVvGroP9bHQAAlNaL5G8VW1zScp/f41nB5eOq7+J2715o2fLf\nQXUmhdJqPku4onsRAAAYWdU2I2YgGVweDrJBWZWkkL0WAIAV0GY7tNbbQPvcqipj2ckZt7g2i99z\nqd+CVwVHRt9LdV8ZHDct1K4fdiu+JwEA0G+j3xHsotqfA+xiq6mJxK2NK3UkhPVq66BsYr5d/IKp\nKRmUlpcQFuniqs3jraEAAKCSNe3t/8tghqrrLdM+YB32Et9bByIRBAAApTTakKrzSlUfrnq1mUyQ\nyMyP7TZdD45jEsJ9erBHAQCANjXaaOpD0taUNm/XHMK78evQheSrCzG0ZcEfmp+mzVtGu2K4Sw4A\nACYanTUnCRyIIScbk7BOuqPB74qlfNd1FHs4AABYfiOoiYZdXxPLrvzMAy+UyXQpAexSLGU1dRWv\nxhfITDL+PbjqVwt7uHcBADAsnThTvazkoG8J4jLWy6okZk28fbUJbb3RtUhdsTQ5j0nTXmS6TUyz\nynySTnz3NohEEACAVdDVZKFvSVjT67Gt7dTV/WMRXVimOpLReZaj6nyrzqPK9MtOu4lpzjPtReZT\nVcev6HY7OgAAhi5iscZKFxrLUn8TrL4lsn2MoQ+WdYWqbAxNXxlr4kpkE+uqK7czd2H/mAOJIAAA\nXbZoIjivVZrnKiRzHW9QLmzS8nXlikpT67/Jq2RV5tPUtJuMedHpzzvPZcSxJB05ugAAQCO62EDh\n6mC785jXKp0ckLqRZC4rAS6aT13zGJ92U9Ote/pV5jlLF/alOfQzagAAhqKtK4JVLTvGvl/l69I2\n7VIsy9RDDAXKAAAgAElEQVTEs211WUYS1NQ8pq3XZT9Tuaxt19NjiEQQAACU02ZjZ2jJ2TJ15Tmr\nrunpVZ6FNfgj7o1dPSw7v2XOuwdYAwAAYLYhJAnL/D2/rvx2YF5Rw7hrMTalD0nBMmPsw/pY1BJ+\nl7Drhr30AACgnLYTl2VdtVpmMtTGyzCqGnhDeWnaXM9tzLsL+1UXYmgZawAAgDnYPkHSuyQdIykk\nXRIRv2H7Ikk/KmlXGvS1EfHBNM6Fks6VtEfST0TEh5Ye+CK68Ir0Zfz4dpV5NjnfMvOepO0Ecqi6\nmFy0FVNX1kVX4uigmWtmkBUdAACz7Zb0UxHxSdtHSLrO9lWp369FxK/mB7Z9iqStkp4s6VhJV9t+\nUkTsWWrUTejKLYVtxdGFBHncPI1fksf99S2BGNpVxSJdiaMnyqwtKjoAAMZExE5JO1P3g7ZvlXTc\nlFHOlnR5RDws6U7b2yWdLunjjQfbhrINsjZu9ZykK79JlteVq61oVhfXfZdi6lIsK2TmWqWiAwBg\nOtubJT1N0jWSvl3Sq22/XNI2ZSdTv6Cs7vxEbrR7NKE+tX2epPMk6cQTTuhfQlFFl259XGQ9d+EH\nx+vQ1f1k2VYl8ejacnQtnkX1fHkqRV9nRbdfJXfiiXOEDgBA+2wfLuk9kl4TEV+y/VZJr1f2OMXr\nJb1J0o9UmWZEXCLpEknactppUUugVRssXU8I2nhWcJquXAFdVM8btoPR5e3U5dhm6XPscyi9tHVX\ndPtVclu21FPJAQCwRLYPUlY3/lFEvFeSIuLeXP+3SfpA+rhD0gm50Y9PZd1UV4Ooy0lZkS7dqjqP\nrieaQ9H3hKJv8fct3o4otdZWuqIDAGAOti3p7ZJujYg358o3pccqJOlFkm5K3VdK+mPbb1b2DP3J\nkq5dYsjt6NttrXU2KPuWBKPf+rrt+xr3Cijz1lAqOgAADvTtkl4m6VO2r09lr5X0EtunKrtj5i5J\nr5KkiLjZ9hWSblH2IrbzeZFaSW3+fMMi2nxRDVbDKiRJq7AMK6rMlqGiAwBgTET8rSQX9PrglHEu\nlnRxpRnZ7TWk+pKc9O2qYxG2cbcNNZkZ0nIPaVmTMm8NXU5FBwAAuqWJhlFXE4++3xI6rwE2flfe\nELbpEJZxCViLAABgefp6m2cVq/IGUXTLkJKfIS1ri1jLAACgO1bhNs+yltnY7cs66RsSlgOxTnqD\nLQUAAFbLog3RVUyaaJyjLPaVwWBLAwDQZW29LGYVk6GyhnRVEquFJG4xA1t/w1paAABQDj99sJgy\n64/1hioGlqTUhvU2EWsGAAAsZpGG1pCToSYbqENer20i6WgG67URrFUAANCeeRt4JDrT0XBGF7Ff\ndgpbAwAA9M+0BiVJItAekr3eYEsBAIDVUrUhSuIITEZit7LYsgAAYNjmaeiSPKKPSOqQw94AAABQ\n1aQGNQkiuoCEDyWwlwAAANSFq4uoG0kdGsKeBQAA0CaeaRwWEjt0BHsiAABAn4wSCRLCfiEBRMew\nRwIAAPRRPrEgKewmkj90GHsnAABA340nHCSG7SDxQ4+wtwIAAKwabh9dLhJA9BB7LQAAwKriZy7q\nRcKHFcLeDAAAMDRlEpqhJYskeRgY9ngAAAAcaFpi1NckkWQPeARHAwAAc7B9gqR3STpGUki6JCJ+\nw/ZRkt4tabOkuyS9OCK+kMa5UNK5kvZI+omI+FALoQOLI6ECem9t1gC2T7D9Edu32L7Z9k+m8qNs\nX2X79vT/sblxLrS93fZttp/f5AIAANCS3ZJ+KiJOkfRMSefbPkXSBZI+HBEnS/pw+qzUb6ukJ0s6\nU9Jv297QSuQAgMGbmQiKig4AgANExM6I+GTqflDSrZKOk3S2pEvTYJdKemHqPlvS5RHxcETcKWm7\npNOXGzUAAJmZiSAVHQAA09neLOlpkq6RdExE7Ey9Pqfs1lEpqzvvzo12Tyormt55trfZ3rZr165G\nYgYADFuZK4KPqLOio5IDAKwC24dLeo+k10TEl/L9IiKUPT9YSURcEhFbImLLxo0ba4oUAIB9SieC\ndVd0VHIAgL6zfZCyuvGPIuK9qfhe25tS/02S7kvlOySdkBv9+FQGAMDSlUoEqegAANifbUt6u6Rb\nI+LNuV5XSjondZ8j6f258q22D7F9kqSTJV27rHgBAMgr89ZQKjoAAA707ZJeJunZtq9Pf2dJeoOk\n59m+XdJz02dFxM2SrpB0i6S/knR+ROxpJ3QAwNCV+RGYUUX3KdvXp7LXKqvYrrB9rqTPSnqxlFV0\ntkcV3W5R0QEAVlBE/K0kT+j9nAnjXCzp4saCAgCgpJmJIBUdAAAAAKyWSm8NBQAAAAD0H4kgAAAA\nAAwMiSAAAAAADAyJIAAAAAAMDIkgAAAAAAwMiSAAAAAADAyJIAAAAAAMDIkgAAAAAAwMiSAAAAAA\nDAyJIAAAAAAMDIkgAAAAAAwMiSAAAAAADAyJIAAAAAAMDIkgAAAAAAwMiSAAAAAADAyJIAAAAAAM\nDIkgAAAAAAwMiSAAAAAADAyJIAAAAAAMDIkgAAAAAAzMzETQ9jts32f7plzZRbZ32L4+/Z2V63eh\n7e22b7P9/KYCBwCgbdSRAIC+KnNF8J2Sziwo/7WIODX9fVCSbJ8iaaukJ6dxftv2hrqCBQCgY94p\n6kgAQA/NTAQj4mOSPl9yemdLujwiHo6IOyVtl3T6AvEBANBZ1JEAgL5a5BnBV9u+Md0W89hUdpyk\nu3PD3JPKAAAYkoXqSNvn2d5me9uuXbuajhUAMEDzJoJvlfQESadK2inpTVUnQCUHAFhRC9eREXFJ\nRGyJiC0bN26sOz4AAOZLBCPi3ojYExF7Jb1N+25t2SHphNygx6eyomlQyQEAVk4ddSQAAE2bKxG0\nvSn38UWSRm9Lu1LSVtuH2D5J0smSrl0sRAAA+oM6EgDQB+uzBrB9maQzJB1t+x5JPyfpDNunSgpJ\nd0l6lSRFxM22r5B0i6Tdks6PiD3NhA4AQLuoIwEAfeWIaDsGbdmyJbZdy0lRABgCb9hwXURsaTuO\nvqCOBIBhWHb9uMhbQwEAAAAAPUQiCAAAAAADQyIIAAAAAANDIggAAAAAAzPzraEAAKBFEdLu3W1H\nAQBYMVwRBAAAAICBIREEAAAAgIEhEQQAAACAgSERBAAAAICB4WUxAAB0GS+LAQA0gCuCAAAAADAw\nJIIAAAAAMDAkggAAAAAwMDwjCABAl/GMIACgAVwRBAAAAICBIREEAAAAgIHh1lAAALqMW0MBAA3g\niiAAAAAADAyJIAAAAAAMDLeGAgDQddwaCgCoGVcEAQAAAGBgZiaCtt9h+z7bN+XKjrJ9le3b0//H\n5vpdaHu77dtsP7+pwAEAaBt1JACgr8rcGvpOSW+R9K5c2QWSPhwRb7B9Qfr8M7ZPkbRV0pMlHSvp\nattPiog99YYNAEAnvFNN15G8NRQA0ICZVwQj4mOSPj9WfLakS1P3pZJemCu/PCIejog7JW2XdHpN\nsQIA0CnUkQCAvpr3GcFjImJn6v6cpGNS93GS7s4Nd08qO4Dt82xvs71t165dc4YBAEDn1FtHPvBA\nc5ECAAZr4ZfFRERIijnGuyQitkTElo0bNy4aBgAAnVNLHfm4xzUQGQBg6OZNBO+1vUmS0v/7UvkO\nSSfkhjs+lQEAMBTUkQCAzps3EbxS0jmp+xxJ78+Vb7V9iO2TJJ0s6drFQgQAoFeoIwEAnTfzraG2\nL5N0hqSjbd8j6eckvUHSFbbPlfRZSS+WpIi42fYVkm6RtFvS+bwxFACwqpZSR9rSepmXfAMAUN7M\nmiUiXjKh13MmDH+xpIsXCQoAgD6gjgQA9BWnGAEA6DquCAIAakbNAgBAl3FrKACgAdQsAAB0GYkg\nAKABC/+OIAAAAACgX0gEAQAAAGBgSAQBAAAAYGBIBAEAAABgYEgEAQAAAGBgSAQBAAAAYGBIBAEA\nAABgYEgEAQAAAGBgSAQBAAAAYGBIBAEAAABgYEgEAQAAAGBgSAQBAAAAYGBIBAEAAABgYEgEAQAA\nAGBgSAQBAAAAYGBIBAEAAABgYEgEAQAAAGBgSAQBAAAAYGDWFxnZ9l2SHpS0R9LuiNhi+yhJ75a0\nWdJdkl4cEV9YLEwAAPqFOhIA0GV1XBH87og4NSK2pM8XSPpwRJws6cPpMwAAQ0QdCQDopCZuDT1b\n0qWp+1JJL2xgHgAA9BF1JACgExZNBEPS1bavs31eKjsmInam7s9JOqZoRNvn2d5me9uuXbsWDAMA\ngM6pp468//5lxAoAGJiFnhGU9KyI2GH7ayVdZfvT+Z4REbajaMSIuETSJZK0ZcuWwmEAAOixeurI\n006jjgQA1G6hK4IRsSP9v0/S+ySdLule25skKf2/b9EgAQDoG+pIAECXzZ0I2j7M9hGjbknfI+km\nSVdKOicNdo6k9y8aJAAAfUIdCQDoukVuDT1G0vtsj6bzxxHxV7b/QdIVts+V9FlJL148TAAAeoU6\nEgDQaXMnghHxGUlPLSh/QNJzFgkKAIA+o44EAHRdEz8fAQAAAADoMBJBAAAAABgYEkEAAAAAGBgS\nQQAAAAAYGBJBAAAAABgYEkEAAAAAGBgSQQAAAAAYGBJBAAAAABgYEkEAAAAAGBgSQQAAAAAYGBJB\nAAAAABgYEkEAAAAAGBgSQQAAAAAYGBJBAAAAABgYEkEAAAAAGBgSQQAAAAAYGBJBAAAAABgYEkEA\nAAAAGBgSQQAAAAAYGBJBAAAAABgYEkEAAAAAGJjGEkHbZ9q+zfZ22xc0NR8AAPqE+hEA0AWNJIK2\nN0j6LUkvkHSKpJfYPqWJeQEA0BfUjwCArmjqiuDpkrZHxGci4quSLpd0dkPzAgCgL6gfAQCdsN7Q\ndI+TdHfu8z2SnpEfwPZ5ks5LHx/2hg03NRRLFx0t6f62g1iSIS2rNKzlHdKySsNa3qaX9fENTrvr\nZtaPUkEdedhhQ6kjh3ScScNa3iEtqzSs5R3SskrNLu9S68emEsGZIuISSZdIku1tEbGlrViWbUjL\nO6RllYa1vENaVmlYyzukZe2qodaRQ1pWaVjLO6RllYa1vENaVmm1lrepW0N3SDoh9/n4VAYAwJBR\nPwIAOqGpRPAfJJ1s+yTbB0vaKunKhuYFAEBfUD8CADqhkVtDI2K37R+X9CFJGyS9IyJunjLKJU3E\n0WFDWt4hLas0rOUd0rJKw1reIS3rUs1RP0rD2h5DWlZpWMs7pGWVhrW8Q1pWaYWW1xHRdgwAAAAA\ngCVq7AflAQAAAADdRCIIAAAAAAPTeiJo+0zbt9nebvuCtuOpm+27bH/K9vW2t6Wyo2xfZfv29P+x\nbcc5L9vvsH2f7ZtyZROXz/aFaVvfZvv57UQ9nwnLepHtHWn7Xm/7rFy/Pi/rCbY/YvsW2zfb/slU\nvqrbdtLyrtz2tX2o7Wtt35CW9edT+Upu2z5b9fpRWu06ckj1o0QdmcpXbvsOqX6UBlhHRkRrf8oe\nlL9D0hMkHSzpBkmntBlTA8t4l6Sjx8p+RdIFqfsCSW9sO84Flu87JZ0m6aZZyyfplLSND5F0Utr2\nG9pehgWX9SJJP10wbN+XdZOk01L3EZL+KS3Tqm7bScu7cttXkiUdnroPknSNpGeu6rbt698Q6se0\nnCtbRw6pfpyyvCv3HZriH0wdOaT6McU/qDqy7SuCp0vaHhGfiYivSrpc0tktx7QMZ0u6NHVfKumF\nLcaykIj4mKTPjxVPWr6zJV0eEQ9HxJ2StivbB3phwrJO0vdl3RkRn0zdD0q6VdJxWt1tO2l5J+nt\n8kbmofTxoPQXWtFt22NDrR+lFakjh1Q/StSRWtE6ckj1ozS8OrLtRPA4SXfnPt+j6TtXH4Wkq21f\nZ/u8VHZMROxM3Z+TdEw7oTVm0vKt6vZ+te0b020xo1sFVmZZbW+W9DRlZ8VWftuOLa+0gtvX9gbb\n10u6T9JVETGIbdszQ1nvQ6sjh3icrdx3aN6Q6sgh1I/SsOrIthPBIXhWRJwq6QWSzrf9nfmekV1X\nXtnf8Fj15ZP0VmW3bp0qaaekN7UbTr1sHy7pPZJeExFfyvdbxW1bsLwruX0jYk/6Xjpe0um2nzLW\nf+W2LTprsHXkKi9bzkp+h44MqY4cSv0oDauObDsR3CHphNzn41PZyoiIHen/fZLep+xy8b22N0lS\n+n9fexE2YtLyrdz2joh70xfGXklv077bAXq/rLYPUval/0cR8d5UvLLbtmh5V3n7SlJEfFHSRySd\nqRXetj01iPU+wDpyUMfZKn+HDqmOHGL9KA2jjmw7EfwHSSfbPsn2wZK2Srqy5ZhqY/sw20eMuiV9\nj6SblC3jOWmwcyS9v50IGzNp+a6UtNX2IbZPknSypGtbiK82oy+F5EXKtq/U82W1bUlvl3RrRLw5\n12slt+2k5V3F7Wt7o+0jU/ejJD1P0qe1otu2x1a6fpQGW0cO6jhbxe9QaVh15JDqR2mAdeSib5tZ\n9E/SWcreQHSHpNe1HU/Ny/YEZW8SukHSzaPlk/Q4SR+WdLukqyUd1XasCyzjZcpuCfgPZfdFnztt\n+SS9Lm3r2yS9oO34a1jWP5D0KUk3Kvsy2LQiy/osZbc93Cjp+vR31gpv20nLu3LbV9K3SPrHtEw3\nSfrZVL6S27bPf6tcP6blW+k6ckj145TlXbnv0BT7YOrIIdWPKfZB1ZFOCwAAAAAAGIi2bw0FAAAA\nACwZiSAAAAAADAyJIAAAAAAMDIkgAAAAAAwMiSAAAAAADAyJIAAAAAAMDIkgAAAAAAwMiSAAAAAA\nDAyJIAAAAAAMDIkgAAAAAAwMiSAAAAAADAyJIAAAAAAMDIkgAAAAAAwMiSAAAAAADAyJIAAAAAAM\nDIkgAAAAAAwMiSAAAAAADAyJIAAAAAAMDIkgAAAAAAwMiSAAAAAADAyJIAAAAAAMDIkgAAAAAAwM\niSAAAAAADAyJIAAAAAAMDIkgAAAAAAwMiSAAAAAADAyJIAAAAAAMDIkgAAAAAAwMiSAAAAAADAyJ\nIAAAAAAMDIkgAAAAAAwMiSAAAAAADMx62wFIkv21IX119Cn9Kfd5vHtW/7LTWXScJuOoc/rTp+dc\n8ajb3r87379omEXGnXf6bc67znEVkf2Nd5fpVzTMIuM2Pf225z3eLSkmdM/qHwVlk6Yz7zzaGrfK\ndOaZx07pQxFxZsHgKLCvjixTNzRRx8wz/a7Esfh02qwnmpp+m/OuMm7puqCJeqLpeqjsuG3MO2ee\n7/+y4ywyj7bGnTadOuax7PqxE4lgVsGdkbo3pL9R99qE8irDrFUor2O608ZtYpplxz2wn72m9bQX\nrK+rV91diWPe7jXtzT7s3p395bvHP69SdwfiiFTZ7U1/i3TvSZ+j5Dh9Gr5onD3aV2HNs84k6SLp\naKGCUR1Z9Xu/ybpqcr1Sf7286DTnG9fOxulKnTG0+nNNe3tVr6xSnRkRC9eNo+7xOmbWOFXrmC4N\nX7X+Leq+aMn1I7eGAgAAAMDAkAgCAAAAwMCQCAIAAADAwJAIAgAAAMDAkAgCAAAAwMCQCAIAAADA\nwJAIAgAAAMDAkAgCAAAAwMCQCAIAAADAwJAIAgAAAMDAkAgCAAAAwMCQCAIAAADAwJAIAgAAAMDA\nkAgCAAAAwMCQCAIAAADAwJAIAgAAAMDAkAgCAAAAwMA4ItqOQbZvkvSVtuNYwNGS7m87iDn1OXaJ\n+NvU59ilfsff59gl6dCIeErbQfRFz+vIvu+rxN+ePscu9Tv+Pscu9Tv+pdaP68ua0QxfiYgtbQcx\nL9vb+hp/n2OXiL9NfY5d6nf8fY5dyuJvO4ae6W0duQr7KvG3o8+xS/2Ov8+xS/2Of9n1I7eGAgAA\nAMDAkAgCAAAAwMB0JRG8pO0AFtTn+Pscu0T8bepz7FK/4+9z7FL/41+2Pq+vPscuEX+b+hy71O/4\n+xy71O/4lxp7J14WAwAAAABYnq5cEQQAAAAALMnSEkHbP2T7Ztt7bU98k4/tM23fZnu77Qty5UfZ\nvsr27en/Y5cTefn52/4G29fn/r5k+zWp30W2d+T6ndWl2NNwd9n+VIpvW9Xxm1Jy3Z9g+yO2b0n7\n2U/m+i193U/aj3P9bfs3U/8bbZ9WdtxlKBH/S1Pcn7L997afmutXuB8tS4nYz7D9r7n94WfLjrsM\nJeL/f3Kx32R7j+2jUr+21/07bN/n7OcOivp3er9vQoXv30p1n+3Hpe+8h2y/ZWxaT0/7wfa0vp3K\nD7H97lR+je3NbcWf+l2Yhr/N9vNT2RHevx693/avp36vsL0r1++VXYo9lX80lY1i/NpU3od1/2jb\nf2H7087q0Tfkhi+17mcdx85U+g6YczsUHgMl1vnS4rf9PNvXpTivs/3s3DiF+1GHYt9s+99z8f1O\nbpw+rPuXev/vmb22T+3Yup+YN9W630fEUv4kfZOkb5D0UUlbJgyzQdIdkp4g6WBJN0g6JfX7FUkX\npO4LJL1xWbHPM/+0LJ+T9Pj0+SJJP73MmKvGLukuSUcvuuxtxC9pk6TTUvcRkv4pt+8sdd1P249z\nw5wl6S8lWdIzJV1TdtyOxP9tkh6bul8win/aftSh2M+Q9IF5xu1C/GPDf7+k/68L6z7N/zslnSbp\npgn9O7vfN7hOynx/Va77JB0m6VmSfkzSW8amd21av07r+wWp/L9K+p3UvVXSu1uM/5Q03CGSTkrj\nbyiY9nWSvjN1v2J8WbsWuya0cfqw7iU9WtJ3p2EOlvQ3uX1n5rqfFktumMrfAXNuh8JjoGPxP03S\nsan7KZJ25OZTuB91KPbNmvw93/l1Pzbdb5Z0RwfXfWHepJr3+6VdEYyIWyPithmDnS5pe0R8JiK+\nKulySWenfmdLujR1Xyrphc1EOlHV+T9H2Y712UajKmfRddf5dR8ROyPik6n7QUm3SjpuaRHub9p+\nPHK2pHdF5hOSjrS9qeS4TZsZQ0T8fUR8IX38hKTjlxzjJIusv16s+zEvkXTZUiIrISI+JunzUwbp\n8n7flDLfn5Xrvoj4ckT8rcZ+aD6tz6+JiE9E1jJ4V26e+Wn9qaTnlDhj3Ej8qfzyiHg4Iu6UtD1N\nJ78sT5L0tcoSknm0FvuMWDq57iPi3yLiI5KUpvVJVftub6ruq7QcM46BzsQfEf8YEf+Sym+W9Cjb\nh5SIs/XYJ+nLuh/zkjTOvBqJfUreVOt+37VnBI+TdHfu8z3a15g/JiJ2pu7PSTpmmYHNMf+tOrCB\n9up0SfgdXu7tlWVjD0lXp1sUzptj/KZUmr+zW26eJumaXPEy1/20/XjWMGXGbVrVGM5VduZpZNJ+\ntAxlY/+2tD/8pe0nVxy3SaVjsP1oSWdKek+uuM11X0aX9/umlPn+qrPuOy6NXzStR+YTEbsl/auk\nx7UUf5ltPrpyln+r3Q+kW5/+1PYJHY390nRL2f/MJXu9Wve2j1R2x8GHc8Wz1n1TdV/V5Zh2DEyz\n7PjzfkDSJyPi4VxZ0X7UpdhPSvH9te3vyM2jb+v+h3Vge70L677q/OZa9+uzBqjC9tWSvq6g1+si\n4v11zSciwnbtrzudFn+V+ds+WNJ/lnRhrvitkl6vrKH2eklvkvQji8acm2cdsT8rInak+6Gvsv3p\ndIa/7Phzq3HdH66sYfyaiPhSKm503Q+Z7e9Wlgg+K1c8cz9q2SclnRgRDzl7XvTPJJ3cckzz+H5J\nfxcR+StwXV/3K6mu769Zuv79O8sc42+V9LLc5z+XdFlEPGz7Vcoaa3vVrdhfmo7BI5TVRS9Tdma+\nUBfXve11ZQ3j34yIz6TiA9a9pGdPmkZTmjoGlqUo/nQy8o2SvidXXGk/Woax2Hcqq0cfsP10SX+W\nO6naSRPW/TMk/VtE5J9r79y6b1KtiWBEPHfBSeyQlD/LdHwqk6R7bW+KiJ3p8ud9C87rANPit11l\n/i9Qdmbn3ty0H+m2/TZJH6gj5tz0F449Inak//fZfp+yS9YfU0/Wve2DlB20fxQR781Nu9F1X2Da\nfjxrmINKjNu0MvHL9rdI+j1l96A/MCqfsh8tw8zYcycIFBEftP3bto8uM+4SVInhgLsOWl73ZXR5\nv59bDd9fddZ9O7T/7Xz5aY3mc09q7D9G0gMtxT91X3f2Aqr1iLhuVJb/nlH23fMrEfGYLsWeOwYf\ntP3Hyo7Bd6lH617Z75jdHhG/PiooWvcVY5k1zLTvgKrLMe0YmGbZ8cv28ZLeJ+nlEXHHqHzKftSJ\n2NOVy4dT93W275D0JPVo3SfT6tG2133V+c217rt2a+g/SDrZ9knpqtpWSVemfldKOid1nyOptiuM\nJVWZ/wHP7aQdcORFkgrfqteQmbHbPiyd/ZDtw5Sdmbqp7PgNKxO/Jb1d0q0R8eaxfste99P245Er\nJb3cmWdK+td0+0KZcZs2MwbbJ0p6r6SXRcQ/5cqn7UfLUCb2r0v7i2yfrux78IEy4y5BqRhsP0bS\ndyl3LHRg3ZfR5f2+KWW+P2ur+9L6/JLtZ6b9/OW5cfLT+kFlLxqadXWlqfivlLTV2ds0T1J2Vf7a\n3DRn1aP/Wdmz4J2J3fZ6Oqk0OjH5fSquRzu77m3/orIk9TX5mZRc903VfZWWY8YxMM1S43d2++1f\nKHuZyd+NZjBjP+pK7Bttb0jdT1C27j/Tl3Wf4l6T9GLlng/s2LqfpN79Pkq+FWfRP2UN8HuUnUG4\nV9KHUvmxkj6YG+4sZW98vEPZLaWj8scpu1f9dklXSzpqWbFPm39B/Icpa1Q+Zmz8P5D0KUk3po24\nqUuxK3tj0Q3p7+a+rXtltyZGWr/Xp7+z2lr3Rfuxsrf7/VjqtqTfSv0/pf3fCFV4DCx5nc+K//ck\nfSG3rrfN2o86FPuPp9huUPaim2/r07pPn1+h7GHx/HhdWPeXKbtl6D+Ufd+f26f9vqF1UrbuqFz3\nKXtL7OclPZTW9+htc1uUNV7ukPQWSU7lh0r6E2UvF7hW0hNajv91afjbNPZ2O0mfkfSNY2W/nDt2\nPxiFIiAAAAIkSURBVDLev+3YldX/1ymra26W9Bva9za/zq97ZVcQQlmSN/puf2WVdV8Uixb8Dphn\nH9KEY6DEOl9a/JL+h6Qv59b19cpejjRxP+pQ7D+QYrte2eMW39+ndZ/6nSHpE2MxdGndF+ZNde/3\no8oBAAAAADAQXbs1FAAAAADQMBJBAAAAABgYEkEAAAAAGBgSQQAAAAAYGBJBABgQ2++wfZ/tWn5a\nwvZf2f6i7cLf57T9m7YfqmNeAACgPiSCADAs75R0Zo3T+1+SXlbUw/YWSY+tcV4AAKAmJIIAMCAR\n8TFlvz33CNtfn67sXWf7b2x/Y4XpfVjSg+Pl6ceG/5ek/75ozAAAoH7rbQcAAGjdJcp++PZ228+Q\n9NuSnr3gNH9c0pURsdP2wgECAIB6kQgCwIDZPlzSt0n6k1zCdkjq939I+oWC0XZExPOnTPNYST8k\n6YxagwUAALUhEQSAYVuT9MWIOHW8R0S8V9J755jm0yQ9UdL2lFw+2vb2iHjiQpECAIDa8IwgAAxY\nRHxJ0p22f0iSnHnqgtP8i4j4uojYHBGbJf0bSSAAAN1CIggAA2L7Mkkfl/QNtu+xfa6kl0o61/YN\nkm6WdHaF6f2NpD+R9Jw0vYm3jAIAgO5wRLQdAwAAAABgibgiCAAAAAADQyIIAAAAAANDIggAAAAA\nA0MiCAAAAAADQyIIAAAAAANDIggAAAAAA0MiCAAAAAADQyIIAAAAAAPz/wP5445EQSEqbQAAAABJ\nRU5ErkJggg==\n",
"text/plain": [
"<matplotlib.figure.Figure at 0x191f68a5b00>"
]
},
"metadata": {},
"output_type": "display_data"
},
{
"data": {
"image/png": 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DwfmsQG116BK8DaxSC1Dkt1LQipW4jRtbOXa4owEAgDiQDCaYCA6pIjWkZelc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\nfyDWBRbg7ldLsim9nz1lnIs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BAAAAAMgMiSAAAAAAZIZEEAAAAAAyQyIIAAAAAJkhEQQA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\nXFUAAAAASUVORK5CYII=\n",
"text/plain": [
"<matplotlib.figure.Figure at 0x191f3e0da20>"
]
},
"metadata": {},
"output_type": "display_data"
},
{
"data": {
"image/png": 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YpU2SJEmSSmzJpS0iKhHxOxHx8Dz7/kFEfDYiPhcRJyPiZSsbU5IkSZI2p+XM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\nIuLNKx1U5dU41WD3mUkOHW3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"text/plain": [
"<matplotlib.figure.Figure at 0x191f3ec0b38>"
]
},
"metadata": {},
"output_type": "display_data"
},
{
"data": {
"image/png": 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SJmcnNfLdEUlqin13lSCjBwAAAKApjB4YXQjyIs+98JxGD4ymNKP0EOgBAAAAaApTs1MV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\nBHoAAAAA0GQI9AAAAACgyfz/FO+Ro0UHakkAAAAASUVORK5CYII=\n",
"text/plain": [
"<matplotlib.figure.Figure at 0x191f552aac8>"
]
},
"metadata": {},
"output_type": "display_data"
},
{
"data": {
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2a/iwq+3cMS1/5B1qO3dMw4ddna3Na/abHx3VlUPdevS2A7pyqFvzo6M3HRsAoDjooQMA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\nDgAAoFMaOgAAgE7tAG7gUhYu2ClSAAAAAElFTkSuQmCC\n",
"text/plain": [
"<matplotlib.figure.Figure at 0x191f557bc18>"
]
},
"metadata": {},
"output_type": "display_data"
},
{
"data": {
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UG/YjHKXrip6Tvb9Dti7rnfsid2390hJ9l9saf0seEbYp4Bc9beHXFTp7ktAr\n1qwl6LpF9sWXT2yGfdsr69One2b8Arb5p3m2df3oF22dcxNjs9d+t2LWbX8KtTXhs6MOEWdO7spM\nD/oRx7IjGoIF84Vb1PehXtYrCEeItN7yvnIxQibQRFRqpMfeQJlSUbEcOyUFWIwwiinjj8ZF1EsR\nVZGCb0phl9LmZnv/fWhK8RYjdmLFSFpKZt69t1SUrD1APHbOxjykWuSnT8b9qpoi7GJE8FC7uYJu\nsF5Pu14BlthOyvYUkRhbv70tSdRpuG5cCmVMmf62++wMLRazn04Zdz7i0z6lC/E20HYoZTBnBdC+\n10O06/a9LzDlFRfxK5s2N3TrRAnB3u+bfsbdh7LfYzn6ETXdMy5KxJnZcyX9hKSXbr35h5I+JOmX\nJL1Q0kck3eac++S2/Osk3aHNT4Lf65x762AbY98TVyo6l/rMiyo/TtTN8bLm2ZayjxBlXldmFGVD\ntmIX5MjxJ6dMjCCLFT4xoi3UZq7gS4nuhW10hUiO4OoXj2Gx0yeuhsVdvnC8aH9i0TZGsJWIgsVy\nouWifudJ6ST5jI0I5s1vi9u3WAHaH+kaEHIDbfQdn5DtcxfuNymCLWx/nDALt+cRNK1iMW302W4v\nHO6L1A216Y/uDdv1RgD30iel00a1ftHnGu34o14nnTq+v5t2Lv/uFVztlE+pN/rXifxdNtNqMxx9\n7MTBAhFAddr27cTlx6gVQAP+Buv0B+0CaaJ9Ffybeu8cpR5TM2dsxEbiflTSW5xz/6WZXSfpGZJ+\nUNI7nHP3mNldku6S9Foze7Gk2yW9RNILJL3dzL7IORfO8TBJpws8fDOOdfSS2bnCLKJ+qRc199ka\nE7nLFWE+f6aKjvnqxUTHhqJec4mwHAGWFpHKaC86yhYvuMbYzBFWIYEzJGJCImqsQBsSQLGiJUWE\nnWYKoWKRuQrSL+fkbOQctia5kbezBAEav2BJv80hMTometYnJlPElxQWcT7/U0RcfGQt32apSF2u\nEGxv9wpAX52e/YiPoo2P/PWlm/ZF/vpFYMjfHDu+dT/DZWMja8kvi5d6xYs3KthwK7atTqWER07W\na1myHmnz/WgpRYg4M3uOpK+V9J2S5Jx7UtKTZvYqSS/fFrtP0jslvVbSqyS90Tn3hKQPm9lDkl4m\n6V3hRiQr9IqBEpkoye82imhz1Pw29fs0Voj1lY8RZL31M8SUb1uWoPKKozQbvnIxws3XfrNedMSr\np1xsNGm+szWIAAAgAElEQVQqQRYrxmL8DIkdn4jx+xYe+Pt8ShVdofMzRmT1iZ5YIRUVpYsURTlz\n5sYKrhrmy9XKmAVKcoRhWmrk+LlssmHx2Bux66nbH41LE3E+QXjuTFc8TQQFl8dGjAjcRJ72r5Ex\nkcGYSF1OxC/Hbkz07+LvbdF21K/ZRrvODhew6S/TirJZN8q286Vf8LlWO91I10mnjs/WZb2+CKLX\nhwvfm9u6Hg1GAPfdaPnQv4+eZvvFVEggBuz6bfg3d1YdjfEnlnl12x4xkbgXSfpjST9tZl8i6X2S\nvk/SDc65x7ZlPibphu3nmyS9u1H/ke22Hpxs6tUpW8S82LdbKc7HGBE41H7q3LShOiliLPRd7gqG\nKSmYJeaTzZW2mDOHLEpQqYCNAqIsxzefnR1twRMrxmJFWAkBVlp09dbpE54DT4UY8ZQikFLnpZUQ\nX8yFG8DGz4/LEYLxKZHDtofE3nBqZNpcNWkjDH0C66KOT3x5BOFOZPkGSUHB1LouQsfSJwJ99dvH\np1f4tUWVdGEvVvhtfPB8FxBOPht+u/2iLyfSd95KyWwLPskv+nx1mrRTPcOisCWwstI82yLt4tsL\nOztCC72EhJRv0ZhY4df5ziP+Npv9gi5WBHbaHxBtwbhcrBDzlAuJu5APtREj4q5I+nJJ3+Oce4+Z\n/ag2qZMXOOecJYavzOxOSXdK0pXrn6OTCdIps4TaXv0pInIDEbeMeqmpklJ+RKzPbvQKhwXSFmPL\ntMvFCDGf7f2oUZrYy7IREd3LEWFDNkK2cgTYGPHVrhuKePlEl7/dxEhdSBD23PCDdfrm0o2cLxcj\nhKIWTElMoRw1R27BeWtSXvSwZMpjctsj5trlpFfGtNcc7Ift9BcYEoFhAdQXgYuPhPXVCYm9jV+B\n8p02w8Kwt15gH0IRwaG6Q0Jwv86Z325G2yVSMqOid4kRvxibnVTMQou7tMuFy+z/HbPAS9teykIv\nsTaH/OyzE/7ONf4fpl+oub1/YhkbhatB4MWIuEckPeKce8/271/WRsR93MxudM49ZmY3Snp8+/2j\nkm5p1L95u20P59y9ku6VpKd/4U3uZOZInJQh0hSfrRlrOydNUuofRI1Jd+yzP+blzyF/S0TIfH7k\nLOxRYk7ZNDb7xVGOjalEWa4gC0XAYgRZigjbtBVXPkd8la6zqVdi4ZOYlS8ThdzISNqa5r5dteFl\n+6fgzJ3oasQrA0KcJ/ySuRMzQ+2d6UQaOB7nznQ108b5hR++euatd1HH813//LiTTp0zj0BtDqLb\nx8db3pmar3rYCb9m9M2fgngita7VdkQwGCFrRPJiI4A50b925K8d9fPZCAq+jo2wH9FibAKb7chc\nJ9rXbFf+Ok3aKZ59ZTblXLdMT6pn04+QTflsJkQAw3Yv7XTt73/XbqvXpuc5N7hASrDVXfGhKFz/\n/XNknKgIgyLOOfcxM/uomX2xc+5Dkl4h6QPb/14t6Z7tv2/aVnlA0hvM7PXaLGxyq6T39jZi437Z\n3TNVwE6qjZjnZOz+pQiwofZThV5pQRYqW0KU+erFzCvLiZoN2siKxKUJs5i0xSFhFiWwIuq068VG\nyUoKslghtrHpWfQkcV5dSvnUqF9MvSHBEyOoUkRT6iqPJVagXDpCVwPtKE+OeExdvXIXMRpqK0bk\nXQwcQ1GsARv94s4vDIcEYbvOnsBp1AsJQX8E7PI87crvRfRaA/qphN9+tG8r4JztDex8ou9SRPlF\nX7POlUCdpAhfQPBFi72tDe++jInEFbLZ3OabexdK8fTN6fPZjxF9zXKbsmHhtynb9S1W+HV9CAuz\ndmw4Rwh22wuXSY2O9Qq1yOdakXl1mcSuTvk9kn5huzLlH0n6B9qcm/vN7A5JD0u6TZKccw+a2f3a\niLxrkl7TuzKlNmr49HR4MDcFWdG4hDpDAi8nonZRt2fgliK+Qm1FR+Mi0vZC9XMiZN4yBaJkMXan\nmEc2RZSsRIQsJlUxR4SNEWCxYqqE6EpNy4wVm0N1NvUGonMD94YYQZQ2Zy5dYJV8tcCSrw4oSenX\nEHgF28AzJzY9s5Oa57E7ZKvjnzfyFKrb375/sRB/nZCfoaiWP2WyK0o2ZftFXqict0xUOuTAvljX\n/+DKka1yzfMVXm2yVSdFiF20GysAu+mdSfP7At/HpEf6bUYcn9w5gwNl5nixe6hcf/lA2YEb0ZDw\n8bXVFLGxYi1HYM0pynJS3ptEiTjn3PslfYXnq1cEyt8t6e5YJ8ykK6fl01XGzolLFZIx4m5oUFc6\nhbKEcAv5HF1/TBQtav7W9OKslI3UaFmfOItdyKNPnAUX/RgQZzGCJSZFMVeU+cuME2MlUjA3ZfuE\nXnokbmy65VC7F+0kR9/yhNUcEbexqZ6xpKzomEufULo6JNg8A+hQFKwjqALRreaAO5QyufM55F97\nkN6ut6nbjl4NCxFvaqT293nvnFm3bLv8hU97UbvuMdg7T7YTHyd75VKigCHRt1emHanyRP7aUb/9\nQePZnt+XUbf+iF/zXFxp28yM9u2L5PO0RV227e770bURXpAmUMa613iyKDP/thKvbYha2KXthyf6\nFyv8hso363jf8dek9Uxqi7LTVvGYe61ffIWfBeH9iI3ARRXrZezPerGRuEkxOV1Z4D1xuQ/6FHE4\nJAT7hF/puv2Ru3KCLNWHLBGWEfHabFs+jTFnbtkcUbMcYZYruNrlUqJkMaIsJSqWIsZSRVh/imae\n2IsRW0MCK/oVBpn3yBLz3Y5h9cqYlSAH56j1LPQRSpFMep1AJ8VzuO22zyGB2B6Yd1MfmwJt/zuf\nEAylo6YKQJ+gGxJ/fcJvN1hs7l+u6Guncsake4bEXsfvxly1IbEXXr3y5OLTxubmS5/Yawu3mLl8\nqWKvN60zYGMorbNrIyVC2CPe2rb3jmtcJG0K4df2YSits2OnVaevXrj+gCiUAvPmwm20hWKbOX6k\nG0sdIs6kqyfTiLixc+QmicaNSJPsa6PPborQCm2Pf/FyWaGXI8Zi7EwRKZPqFGQxkaScKFlOhCwl\nTTE3FTNFgMWKr1TRFRJbYwRWiVcPRK1oOVNUTjoOsZZC8msFWsVTV9KMSfEM+hQh6C7b8Q26YlIy\nA9+b3/e+FNPBNMmdDYu0K+ncW7ab1hmTFulrtz1Y9ZXZlDtplOkRIU1bPSmesSt9tsv1+ZuT1tmu\nN5TOGWqrWS8myrdfp1xap7fMCIEWmwo6tp2c9nYMpk4O3PNiUg5TUyDHpDEuOQeuTRUiTnI69Yi4\nEouUxJIzBy/2V+rBuW0Tfd8r6iIFWer2UqLMVzZ+EZLx4sxnd4p5ZkPizG+zX9jkpDHmCbh0cZad\nhhkURHGCMFaUpbzKICRcckVY2N7Qjz7jI3Mx7ey1mXG/nCqNskYROOb9boOrOg7Vb682ODjg2Ear\nenzeiyCFom/N9MAhYTYUCfLYDQ30UiKFV3XmjQr6IoIhu91B+Zk3AuhN/xuI/G38a6eddcvI45/s\nrBPx60YE28ejG+1rp20OzeWLifQ1I3wbG+1jMxzp64vweW1GRPp2dTordjbqlEjr3HgdE5Hzz7vs\nROpKir6edkJt9dnv2x76fihK146YeUWUZ1Of7+02Q21PRSkhWIWIM5OuO702eTtjF0uJrZ/STqrQ\nim2jhCAL+RC2EZf6lrMkvhS34Ievbk60zFcvVZBt2pk/YpaT4rikIIsRYinplrFRMZ9vwXlpCamY\nfaKif75cX+rluB96oubNTSziUtuowW4qu0FinxAbY/tqhhCOTQmKFZ6hSJDUHACFVp/sPz59IjUk\nDH1+n7WEyL4dT/mYaNqufmSUzh9Va0eRfPPc2lEa/750ImCywahsTqSv47NnPsnwYiftSFv6Ai4x\nEcluhCs+whf0NWruWvriLb56585/fceLtuFj0mczbDddyOW2H2s3p+xYgTaXwEuhDhEnpyuJ6ZRT\nrV6Zajc2GldCAOZ+J6WJsc13+YKst/zAfLKQzTnfWbbxIdxe7AIafQItdzXG5vex7x0rIdCixGWE\noIqJkuVGyFIiYykLlWxslEmX7BV4CemesTb77KbYSC23335ylUn8mIOrLb/GRORCts9Td91i595t\nGCp7VefhwcwuahSw4V0EpEHfeT0L3Xd7o3ceweXxbS9a1LHhEWieKF27vm9f2vvgOx6nHZ/9kTdf\ntK+9v+37nC/S17bbuTc2Inw7nzurX3baCUf4LnwvGeG78GNMhO/SSu/CLbt6CfP5dm1v/t6v5/c7\nI+LXsBeyGSX8RkTmQm30bQ9+74usDdx3pPgfraJtj2Rq4VeHiDPpupPpX6Y6VyQupWxuJG6wbuTK\nhTHtpUTeckVZX1tTvVA6J3K2sZ2ezrixFRZgMemMXRvpqZlt/6J9LxQ964rFvKhZrDDz1d3Ujxdl\nKTakdDE2Pso27vtNG4NFom11bCfXGPChvh9Dg+yE11lBzXmesf8p5+A0Ysk1XzRmv73+74Nt9AhO\nn3iQ0oXfVfkjQaEfinz+nHj8990jugIpQrwGFmPx1W0LvrO2mIoQem2xFCP0rrZTSFtCz+dvqtCT\nus+QVKEnec5VR/x002H3Vunc1tnsQ7NcubROX73Oip3bupuWM0TfhS9pws/n21Ab3jqtP0tE4lIF\nUm/5CFNZgmzi51UVIu5ETtcVesVAyQhdzspsMe3HvJ9pzOInOeIuHOmIF2ChtlPe2eUXTf1pjOF2\npxFkOYKrXS42PTBGmGXtw4CYKhUxW0KQpcxf89WX4vpTjo1Q2djvh8RW3KIlw6QKpdPMJ1VpgVcr\nQ68C8JE7g7A9kJe6EcK98u2vfL+AR9jbn+fW/X4vgthooz2g7Xs5dzudtL0Ufrd8+7tdamJj4OpJ\nAe214U46qY2dtL2LtNGzgXrhKN+uz4RekH6uk73XFJy57svQz3Sy1/c2A+7uax2G0jl9qZyd1zZY\n+HvJl6a576/vpe1DqZznnmOa8z6+YCpnW3g0jo3vZeztMpf2+9M6g/UiF6QJ1e+zEZxjmuDHzpte\nkVdErA0/KXIEVqnVJ5dMs6xCxJm5WSJxPlJeeNutGxlti/olfJz4G3oPVOz8sSGfUgRZ0EbCSn45\naYybNsbPNdu0ORwFjF9SvxEBy4iaSZEpmSsUaN16cWmuvrqh+ikRsvQoW7pgCwmy4YVM+okRYLGi\nK1VknY58OedQBOeQaUcqQhPvfZw1og0xx7DZ44f6y5ncoC9nrv85d97TTl8fO3fh6+FMFniWhAe4\np565er6ooi/qdbkce1c0dH58i4z0tQfjZ+5EJy0fQ/f5mChf+9j5IpPter50zm5bLTE9EN3b2N2v\nMxjdk3TePq7exVzavrUjQN1FXULP6M6iLj2rjF4sMBMT7RpK67yw3U3t3LTRitIpHOkKRe9iV/Hs\niwBuPOq/YQyv9NnCl77ZKdPub3HPifFz4CKfgAs+tuoQcZKuFBZxpV72mrVqZYIw7H8f1FCaVX87\nfb7HRo+G7KUIsqCN2MhahDDzldvYGxYJJVZo3JQZHz0Ll2vOAYsTJTlpjXMLtJT5ZV3RPE3UrE9M\n+W3El72oE/xmWzdoc/ipESvAYoVXqsDKjc6VaLtW2kKtSc7x2kXdTiLP4a79YVE2LApjhOBZT3u7\nCGDo3hcSfrvBqK+eT/SFxN7uu7adc2cdsbex4TURKZ66Qm8j2Fr1IoXept1hsVdC6J3ppPvD4EAa\n56atfqHnfVYUEHqheZfNay80/7OT8pkzd0/KTOvceOTzPST6Nj6PEH4XfoRFW98cWZ8979y/ls2N\nl3li0O/HsEDs1omwHzGWX/pdcpWIOKfrTuJXpxyKOo0lVwDGirdSCw2kCq49+wlLqffZ7F1OPUKI\nbdqMLJewBHuOINuUi0jBHFgE5KLujCs15sw1i1mdMUZcjomajU1lHCPIUqNkOWKsL8oRGrQPC7v+\nh0aM4ImPxCUKt5GRuE2bx5JkuaE9CE3hYjAaMY9tv83+8nvL9Ec8i0L2rm77j8+/iyX7e+z2pYZ6\n5xlaf+pnN3XTdReKsW7Z/bS/tg3PQi/mr7//8vK4lM7Lc7wfJZJ8A/h2u635boHFWnwvVW+nce61\n1ZPG2U4H3ezffhpnO4VzZ6dJThqnz+/2axY2/rSOrafMzu9OimpGSueuXJvYd/GFym72I7ASbMTq\nnZfthe+5Q2IqNY2zYz8mcyB69cn0Z8ccIixFkKZSh4gzp6cliLgSjJk7lzq5PyUyFyXwBlMn49MO\nL2zm1IkUL71lo1PhUlLehsXJplx6xEyKE2ebcukCbePXcqmNse8qK5nWODadMVag9c0n80cHe8pn\nRMjCQq+vTv/NPy4iFyHqEsVXrtCaKqJ22rPs/ZycBZYI7+MkMnGyT3j19W2fSOzrN23B5U1P7KR+\negade3OAwzbae98XBQxF/5ptde1dfu5E3dS9lkORvp3Yi4n0pUT4uvuyi7S5i3qbMsNpnDHRvU29\nfdpRonNZ537ejg5dRARbx69zfFzXVmfRE3fiOQ/p0b1NmeHniy/C59vuu3ZiUjo7i7Zsy0n7QiP0\nLr52uV3ZmIjfpQ/+8pf2m/X2BXaTK8E6TR9899923/T7GVwQptXGnuVg5M13rsemVI5/ZrXnTZak\nDhGn7gtKxzJmrlvXVrrgS4kWxrysd+x7oIJzefqieQnpipftxA/IU8rHCrNN2TixNPWLp0supz9V\nFO2ybhmRtmQULSWdMTVylhM1CwmjscJssH6EIIsVYbmiq5SoWltU7iRhv1MjcCGpNyQcfSIxRRDG\niEBfpK3Zd3zt7Wy0B+ttwXfeK9Bcp61NnUY7PeJgZ29I6LXtNAeGl2Kr0eYuWtgo17yv+4Sib96e\nL42zLfKa9U89oqB5//WJvHOd7AlEn8iLmau386v7HLps8fyiTFuQDoulGKF35qy7omWE0NsJoaF0\nTl/dTf0IsXdRtv9a6SuXIvp25UPRvpAA9Iq/Zh2vqAmLwB2dFT89tnf0RQZ3JaS4CFdb5CSLsoji\nORHAUlQi4lzxOXElUy5jRFawbqQfMS/jHU6RHHqY59XvXVClgEDrayN6vlymSOsvGyewpn4xdexL\nqXOjar42ffVrTH1MSXssIdxyRNtlXf/3NYm2mPb22x7/8FqbUCtFeJCXKO68L58eehaEhVK37HB0\not0Hh6J5+8KsndoXrtuJAAba9c8S6rZ3MWevk5LXbN9nwxN560QL/OXC9X2RO18UzS809uqHTmdb\neLnufDfvXc73LOkMXAN9rnFcTi8G3+0IkadN130O+hZYaQ6gT60rInaCsTng3z2jL0XlJU3fTjzp\np7598EdSu+mbu/1oltuU3ZVr2gynaKaU73tNg0+sb+r4x+PnPXNDQ3M1L9vtRp07NjzHLsS5615z\nMZwXztrY/HCwzMKMUi0izsqKrlzGiDUpLWIXI9pi7Q6JNykvqrZpO13ApUZBS0ZNm+xuKs19PPf8\nAror2z4W5+o+4DapIf3n4/ziRth92HbTX7r22u3uPywuHwBtW+1989Xb1O0OJM4vbp7hdvd/3d1P\n9dns7+7X5+ZDYqBdZ3t1m+Wabfm2bepfbtvd0H2/Up7KBYcqvrk1m8GA7zz3PDUC85J2A82heUjZ\nxJhNuMbOFS+szt3m4TUmTXL3K3wtKZFLkpOO2Sa1n6WKxpj5d0M+9M2zG6zb035oT/raC73DL2wr\nNAcovmzsSoH9NuLmPIUWRtmr57EVbNdb39euP/1yqN1N2WF7UlwExLtkfrDdyH2bKPJyIS4j7Z/Y\nebCs77k51MbF+CJg80QumL65N8bw1G8+40PRsJhIqM/ekN29ej33u+EIYJeltUsVIs65aSf++fAd\n+JwT2OwQsWHaE3O9nXPHrkMP243wO7ik7unWQnpHPJdfgJ1tbfpEnq/OrryvzrlOPOV3ZZvi7NJG\n++K+EHN7gmJrY29yecOGPILk4uanRrlznbV+z9r1Ld8Sy50Vuuy8M4g47bHZvPH6UlDa+7TD/3D3\nRLwCUZ32Df8peW6Gu/PSaP+pPUHnLuruuDhXe6lI+3ab5WNtNMtuyncFaJvmr3pPBWw9lRHle6pn\n0LmJCvRFQfb31d9GxIMr8f6a8iPTRRtj57td9J95nwVLk7ooSR85PxTELFyS2kac0BuwMSjmcu3G\ni7C+Oqmr9vWVzxVkUr+giBVnseJlUz9ugQ5v24H7UKxA87cdOJ/RfsYf09C4zX+ues6Ld9/6+lPI\nn/Q6F3UT3x83VG+/7eF7eMwYOMVep06hDI+5tUkqdYg4ma6dD0/uLhmxSRFcfbQH2228YrHH5ElA\nmPT5FXqY7Ykc17W1H/3w1Ldzb71LX533gr4QO746dr4n2i59deE6oYdu6CJ1/r7iuzk9tROxEWmB\nT7lTj0A67QjgpgDYFzQ7wdywsRO81hQcXR+aNi/37bRTrrlPlz64jhAIpU926u7a79R3e+332+gK\nrwsfvFGwcBquT9AEo8w9wzmvkHP913v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"text/plain": [
"<matplotlib.figure.Figure at 0x191f5597f28>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"def Tarea_from_area(area):\n",
" tmp = area[:,:-1:2] + area[:,1::2] # i-sum\n",
" return tmp[:-1:2,:] + tmp[1::2,:] # j-sum\n",
"\n",
"def Uarea_from_area(area):\n",
" tmp = numpy.roll(area, -1, axis=0) # j-shift\n",
" tmp[-1,:]=tmp[-2,:] # Top BC ???\n",
" tmp = numpy.roll(tmp, -1, axis=1) # i-shift\n",
" tmp = tmp[:,:-1:2] + tmp[:,1::2] # i-sum\n",
" return tmp[:-1:2,:] + tmp[1::2,:] # j-sum\n",
"\n",
"def mismatch(area, Tarea, Urea):\n",
" return Tarea - Tarea_from_area(area), Uarea - Uarea_from_area(area)\n",
"\n",
"# Start by trivial assignment from TAREA\n",
"area = numpy.zeros((2*nj, 2*ni))\n",
"area[::2,::2] = 0.25 * Tarea\n",
"area[1::2,::2] = 0.25 * Tarea\n",
"area[::2,1::2] = 0.25 * Tarea\n",
"area[1::2,1::2] = 0.25 * Tarea\n",
"area0 = 1.*area\n",
"\n",
"Tmismatch,Umismatch = mismatch(area,Tarea,Uarea)\n",
"plt.figure(figsize=(15,6))\n",
"plt.subplot(121); plt.pcolormesh(Tmismatch/Tarea, cmap='seismic'); plt.colorbar(orientation='horizontal');\n",
"plt.clim((-1e-14,1e-14)); plt.title('(Initial) Fractional area for T-cell');\n",
"plt.subplot(122); plt.pcolormesh(Umismatch[1:-1,:]/Uarea[1:-1,:], cmap='seismic'); plt.colorbar(orientation='horizontal');\n",
"plt.clim((-1e-3,1e-3)); plt.title('(Initial) Fractional area for q-cell');\n",
"\n",
"# Adjust difference between sub-cells with T-cell\n",
"delA = Uarea - numpy.roll(Uarea, 1, axis=0) # delta_j Uarea\n",
"delA[0,:] = 2. * delA[1,:] - delA[2,:] # Extrapolate for slope on southern edge\n",
"da = 0.25 * 0.25 * 0.25 * ( delA + 3.*numpy.roll(delA, 1, axis=1) ) # at west\n",
"area[::2,::2] -= da\n",
"area[1::2,::2] += da\n",
"da = 0.25 * 0.25 * 0.25 * ( 3.*delA + numpy.roll(delA, 1, axis=1) ) # at east\n",
"area[::2,1::2] -= da\n",
"area[1::2,1::2] += da\n",
"\n",
"delA = Uarea - numpy.roll(Uarea, 1, axis=1) # delta_i Uarea\n",
"da = 0.25 * 0.25 * 0.25 * ( delA + 3.*numpy.roll(delA, 1, axis=1) ) # at south\n",
"da[0,:] = 0.25 * 0.25 * 0.25 * delA[0,:] # \n",
"area[::2,::2] -= da\n",
"area[::2,1::2] += da\n",
"da = 0.25 * 0.25 * 0.25 * ( 3.*delA + numpy.roll(delA, 1, axis=1) ) # at north\n",
"da[0,:] = 0.25 * 0.25 * 0.25 * 3.*delA[0,:] # \n",
"area[1::2,::2] -= da\n",
"area[1::2,1::2] += da\n",
"\n",
"Tmismatch,Umismatch = mismatch(area,Tarea,Uarea)\n",
"plt.figure(figsize=(15,6))\n",
"plt.subplot(121); plt.pcolormesh(Tmismatch/Tarea, cmap='seismic'); plt.colorbar(orientation='horizontal');\n",
"plt.clim((-1e-14,1e-14)); plt.title('Fractional area for T-cell');\n",
"plt.subplot(122); plt.pcolormesh(Umismatch[1:-1,:]/Uarea[1:-1,:], cmap='seismic'); plt.colorbar(orientation='horizontal');\n",
"plt.clim((-1e-3,1e-3)); plt.title('Fractional area for q-cell');\n",
"\n",
"plt.figure(figsize=(15,6));\n",
"plt.plot(area0[:20,0],'s');\n",
"plt.plot(area0[:20,1],'^');\n",
"plt.plot(area[:20,0],'o');\n",
"plt.plot(area[:20,1],'.');\n",
"plt.title('Sub-cell areas at i=0:1, j=0:20')\n",
"\n",
"plt.figure(figsize=(15,6));\n",
"plt.plot(area0[600,:50],'s');\n",
"plt.plot(area0[601,:50],'^');\n",
"plt.plot(area[600,:50],'o');\n",
"plt.plot(area[601,:50],'.');\n",
"plt.title('Sub-cell areas at i=0:50, j=600:601')\n",
"\n",
"plt.figure(figsize=(15,6))\n",
"plt.plot( numpy.arange(80.25,100,0.5), area[160:200,0],'x');\n",
"plt.plot( numpy.arange(80.25,100,0.5), area[160:200,1],'.');\n",
"plt.plot( numpy.arange(80.5,100), 0.25*Tarea[80:100,0],'s');\n",
"plt.plot( numpy.arange(81,100.5), 0.25*Uarea[80:100,0],'o');\n",
"plt.title('TAREA, UAREA and sub-cell areas at I=80:100, j=0');\n",
"\n",
"plt.figure(figsize=(15,6))\n",
"plt.pcolormesh(area); plt.colorbar(orientation='horizontal'); plt.title('Sub-cell areas');"
]
},
{
"cell_type": "code",
"execution_count": 28,
"metadata": {},
"outputs": [
{
"data": {
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SBQDPhGe3ogzNIC+VGuMtMGeU8jmAZ6QKdiJHJxDPm5/b84qiRR/L67Vl5BicxGhJPVrH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"text/plain": [
"<matplotlib.figure.Figure at 0x191f4133a20>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"def rhumb_dist(lon0, lat0, lon1, lat1, R=6370e3):\n",
" dphi2 = ( lat1 - lat0 )**2\n",
" dlam = numpy.mod( lon1 - lon0 + numpy.pi, 2.*numpy.pi)-numpy.pi\n",
" dlambda2 = dlam**2\n",
" return R * numpy.sqrt( dphi2 + numpy.cos( 0.5*(lat0+lat1) )**2 * dlambda2 )\n",
"def great_arc_length(lambda_A, phi_A, lambda_B, phi_B, R=6370e3):\n",
" \"\"\"Returns the great-arc distance between A and B using the arccosine formula\"\"\"\n",
" dlam = numpy.mod( lambda_B - lambda_A + numpy.pi, 2.*numpy.pi)-numpy.pi\n",
" return R * numpy.arccos( numpy.cos(phi_A) * numpy.cos(phi_B) * numpy.cos(dlam)\n",
" + numpy.sin(phi_A) * numpy.sin(phi_B) )\n",
"dx,dy = numpy.zeros((2*nj+1, 2*ni)), numpy.zeros((2*nj, 2*ni+1))\n",
"d2r = numpy.pi/180.\n",
"dx = rhumb_dist(d2r*x[:,:-1], d2r*y[:,:-1], d2r*x[:,1:], d2r*y[:,1:])\n",
"dy = rhumb_dist(d2r*x[:-1,:], d2r*y[:-1,:], d2r*x[1:,:], d2r*y[1:,:])\n",
"plt.figure(figsize=(15,5))\n",
"plt.subplot(121)\n",
"plt.pcolormesh(dx/1e3,cmap='nipy_spectral');plt.colorbar();plt.clim(5.,65.); plt.title('dx (km)');\n",
"plt.subplot(122)\n",
"plt.pcolormesh(dy/1e3,cmap='nipy_spectral');plt.colorbar();plt.clim(5.,65.); plt.title('dy (km)');"
]
},
{
"cell_type": "code",
"execution_count": 29,
"metadata": {},
"outputs": [
{
"data": {
"image/png": 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eyIpswq5Pu+Ox+f3Zrb88v3/WX/50fv/N38pMqStfysr61rtP63r+7C9nJi97\n//almXnVlkcvyExnufKbDAm59z3DzpDPz7S29ZfLSHta98y8OdO2bbfpQBbprhTS7Z4TTkn+3/yr\nwO+r6g4R+Qod68FXPeHURxZO9fjIwqkr5en2HmCPqu5I/76bpPPYn5qWKHHCKTETTr2zcKpFQdsS\ntTnOkqJE3VbVV4FXRGRutvCVJPODQotz3QNsSyOcziebcLoPOCoiW1N/xHUd18zdKzzhNMXnWTiL\ngHcETl0pVbd/H/h2Ggn1AvDPSH7gL8qE04o7C4FGI29DB5gwqQNsqObkRHf5lLHHGzu9Wvv9Oya0\nb1W2UpgcM5k211m7Zpb6Ipfl04TavfX+LHvrihey9Ai/+G9NapErs1DWH1525/z+pf/3/zy/v/GB\n7J5vvycL31v5k3zYbagc7TNsaJ+xc5+WpVeQN7OVxnR55u+QEyZENlCPwXq3chs6G1gdLUgtTUwK\n7XZ+9TmrmxPGh3bcZGxdbjK5qvkurF+vrd3lPRDJ7qv2e7Mr3500bWue3TS2/NZb2feyYk+2b/0U\nVm7Pz93H3N8+N7cqnylnrvwECNVR5zHtniE32A6BdouiRN1W1R8D3fwaizLh1EcWTvXUsrNwHGqt\n295ZONVS10l5jlNz3fbOwqkcn3Dn1JU663bFnYVCq5VLDwAgbwX8C9buvtrY400qi5z9/rVsXkI+\nJXQ2l2F2cxZzPrErS0dw8qJslbnJx382v//Or2Ux4dP3Pp7JP5KlE994e5ZKvPVoFiv+Ua7Lznk2\nO+edrVu63/PKD2CZ/i9ZqvSTl71vft+mdbDpHiZ2ZylIWpuy2PRcipMzsxTa1k+jp5uUIEczu3Ow\nPVYaP8g7BVKUA9Qx0qnZoL16ec6HlNPNg5luts/M/FSN/dn8gNzKbbl05Sbd9otZKg6Amfdl7W/T\nX5y4dPP8/rKfZnN83v5wZrq26T6O/t4H5/fX/X+Z7+zVm7bO7296MIuq/Luv/sX8/sd++5r5/b3m\n/HP/c/Z95e7/YJbWI1eeHdncilz5n8j0feZCk+7jZ9n9Z8/P/IYAEy93T5diV8Rrn53N07ArHNo0\n8/YbiaKOup3iIwuncnzdOqeu1Fm3vbNwqsUn3Dl1pea6XW1n0Wigq5bnzBwA7TVmCr41MdnQVmNi\nyg0fXw0seP9SZpKZfU82RLWmp9yQ1qQXmP2AMRM9tiuTfzBLg7DiJ1kaltYF2cTJiSNv0Q17jr12\nxtzTPqsjKEhpAAAdb0lEQVSzHLZ8M5dszuTG9JAzSb2QmSta785Mb3aVNpvl1JpDcqYqa1YxpqrG\nG9l7WhNhf6SeTsDZFo3Dx2gZE1PTmDZaG4yJaV+ms6Hw6Jn3ZG02uTszo568ML8S45RZ+e7ExZkp\nddnzmf4ff//m+f2VTxr5L2fnr3vMrMZ3XlbWTSbM2/Kxj5rkpCY01Z5v72Pvb5+bK48p5/TPsrQe\n+fcyK+iZurD1AOH6y9X3L8yKhbZ9TOoQ257spg811e0UH1k41VPjX1/OmFNj3fbOwqmedv9THGdJ\nUmPd9s7CqZaax6I7Y0zNdbtvZyEi08DfAcvS8+9W1T8UkXXAncBmEmveNap6JHQfAFpt5OjbtNeu\nzIljwg1zobD7jK1xU/dVsOzKWTakdPa9JtTw+SxEcPaXspDXyV3G3n+hCak1ts/c6luvG/v9dPf0\nAPYce629p31WZzly5bPlfm8gdNa8f/MV8wwbRrjX2mzN+9hV3QJhhDl/UsBPE2JUIkbK1G2dnKB1\n9uk0D2R11DrHpNA26eZnN2Z1PfFq5teYPc+siLcne9zsu7Iw6KmXM38HwMzm7Niyl7v7QqZfMvc6\nJ7PBT+8xfsDTshDpicOmPW06DpsqZCZL96KTJl2PmWhg72Pvb5+bK48tpym/fS/7vrYubB1BR/2Z\nep3YZ+o70A6hdothVHR7GMQk9TkBfFhV3w9cClwlIltJcqs/pKpbgIfoyLXuOEFGJ0W567ZTLqOj\n26XTt7PQhLmFaCfTTQkv7+c4SwLXbceJJypdqIg0ReTHJAttPJAuyBFa3q/z2hvnlg482Xq72ynO\nmCEat1VSlpJ0e2ammCnOqSejpNtlE+XgTvOiXyoipwPfFZFLOo4Hl/dT1e3AdoA1Kzdqe90qGoff\nzJ2Ts4tbP8VZxnZo7Og5P4WZvh+0x59nlmW0fg0z/yAXc21TZRibZfssk6bBpF/WFWY5VGPLtdhz\n7LX2np32UVuOXPlsue37mPfMvX8g3UGuHm1sua33YBoEOx9mVa7cvEgYZaRSIpSm29PnaPPQm7TO\nynxuzYNZHVn5xGvGr3F2VqcTB4rJASb3m2eckbXDxKHsG2uvzpYMbb5hdG+ZSZt+wqSol0D7zJqU\n3tZPMRtIrW59HOb+9rm58phy2vLb98q9b6COeh3LyW07RLRbT72GkdPtsim0EIGqvg58H7iK8PJ+\njtObEbTrum47pTCCul0WfTsLETkz/dWFiCwHPgI8S3h5P8fpyagM1V23nbIZFd0eBjFmqA3AN0Sk\nSbqkn6r+jYg8Qpfl/XrSatN4/S1a61fnxE0TOptLl3DQDhOtScrIbabO/a93l+fCGY3cDDdtJtDm\nETOENyaWxrEs62p7pcnGalccC61kZsxT9trcPTvMObly5OrF1Nc5gfcsWi+2fm292+fadjJtaOVR\njM7HUppua7NJa+0qmiZctLU2a8/C8tfNio5rVnSVQz4ktXnU6NIKs2rkcZMV2JiPpGVMpiHTk825\nbVaZy5merDywKl/OJGWfa8tjymnLn3sv+76BOuo8NlA7HC7oixod3S6dvp2Fqv4U+EAX+SECy/s5\nTk9G5INy3XZKZ0R0exj4DG6nUpbyMNxxelF33S7k4HacUmhL3NYHEZkWkcdE5Cci8pSI/FEqXyci\nD4jI8+m/a801t4jILhF5TkQ+auSXicgT6bE/EUnsJiKyTETuTOU7RGRz6fXh1IeSdHsUqXRkoc0m\nrXWn5WzxAC2TOsIey9nFQ3IbYmft64cC59u0G8Y2mQtnNfbPhlnFr73KrA533PgpbBhhO5BJzNpm\njY/D3tM+65Ry2PLlbNvG1jpIvcTUe6idjByAn9OTEn99zc3AflNEJoG/F5H7gH9KMgP7NhG5mWQG\n9hdE5CJgG3AxsBF4UETel4bPfg34DLADuJckKuo+4AbgiKpeICLbgC8C19KBtNo033g771841l2n\ncnJrg3/T+sS664W15QPIO91DUvN+tAj9tFg/RSPgjwj5KULnh3wi9pxm4Bux72Xf19TFKd+Oqb9c\nvdr6jmmfNUXS7/vIwnHKpaTwwgXMwL4auENVT6jqi8Au4Io0PHa1qj6qqgp8s+OauXvdDVw5N+pw\nnFMY59BZxymVyNDC9Bfa+rkZ0ul2Y+ftCs7A3gS8Yi7fk8o2pfud8tw1qjoLvAGcgeN0Uky3lxyV\nmqHmhup2RiZA84gJczPHouTWJPNGQB4YVuaG92b2qLzdPYTPDo11Kqu6XChgI9D/muF27lo73O5l\nYjDly5U7MHyOqpc3Bqj3gDyK+I/loKpe3vNWA8zALpWm0D5tOt82EaakXBsvD5hbQuYlyJs3ZyNM\nTzEhsiFT0iBye/+iJqnZ7ibfkKkKIus1YMYKtVsUS7QjiMFHFk7lSDtuK0LkDOy9wHnmsnNT2d50\nv1Oeu0ZEJoA1wCEcpwvD0O1RwTsLZ8mygBnY9wDb0gin84EtwGOpyeqoiGxN/RHXdVwzd69PAg+n\nfg3HGSt8noVTPeX9r7bQDGxVfUpE7gKeBmaBz6VmLIDPArcDy0mioO5L5V8HviUiu4DDJNFUjtOd\nGv+MqDZ0dqJBa+2K3PR9gNZaY3c3xwrLA/6I1mkBe/9KGwqb+Sl0eXcbcc7XYDNwWvtq4Edn7pyQ\n/6IjY22uHDYVgi238a+E3tPWiw0jLK3e1xYILyzRwbeQGdiqeitwaxf5TuCSLvLjwKf6FqatNN4+\nGbaP59oyoFNBXQv4ImCwsNWQHyHkvxhEHrp/ICVI1HuF/BpE1qtph5h268sSdl7H4GYop3pqHF7o\njDkl6raI7E4niv5YRHamskWbcOqdhVM93lk4daV83f5NVb3URAV2XfK3Y8LpVcBXU/MsZBNOt6Tb\nVal8fsIp8GWSCadBvLNwKkWod8SIM75UpNuLNuG08nkWjWMnaK2ezskbx4x9ffV0f/lb/eW5WOmA\nvd/KdTpiPkVopbBW9lNBQynKjYJoLja+u/8C8j6MXPnsqmMx7/lOwXos2h7HCsSi19Wu2xDayyfD\nuhPhj9CJwNydXuk6is5lsMT4EQaZfxFz/5iyWSL8F5Cvv1y9zhZsn855Lb0optvr50xLKdvTlRc7\n7siDItIC/kN6vNeE00fNtXMTS2eInHAqInMTTg/SBY+Gcqqnjp2F40CpE06B31DVvSJyFvCAiDyb\ne1RVE05T3AzlVI/7LJy6UqJuq+re9N8DwHeBK1jECacVZ51t0F49fWqGyJApKcbE9E7AJBOa1m/D\n5YxppxEYhhZepD40X8ueY81WoXt2lMOapELlzr1nTL1YuU1xUrQ9OsyK/ailGaqtyMnZsMkjwsQU\nTBsTMvlAWN+KUpbpqWj4blFiytZxLKa+Y9othrJ0W0RWAg1VPZbu/zbwf5JNEr2NUyecfkdEvkSS\nUXluwmlLRI6KyFaSjMrXAX9qrrkeeISICaduhnKqp46dheNAmbp9NkmuM0j+P/0dVf2eiPwDizTh\n1DsLp1rUI52cmlKibqvqC8D7u8irn3Ca4p2FUz0+snDqSo11u9rQ2TQlQmtV3sbdfDsU8lnQHxFK\nr3DC2vsnussDKcdzYa7W9jkRke7AYs8JrDKW8190PK8d9F8E3se8f85PM4hfw8htGzYLpnGupc9C\nBJ2YCNvBi/ojYlJoFChb1+uHneJjkNQfMe/Z67sr6HeJarcIaqnbKT6ycKqnxh+UM+bUWLe9s3Cq\nxcNinbpSc932zsKpFKHeQ3VnfKm7blc7z6IhtFYuy9m+AVoBO3qU/ETAT2HnTUwHpvUvC6TdCKXj\nCKQiV2v7DKUoD5wTSl3esxy23LmUIIHlWgP1MlC9W7nxa8RQzw9KE/t2KL5/GHb9zmOWon6BpSK3\n9DpnAH9M1DLJAeqp2wk+snCqp8YflDPm1Fi3vbNwqqfGH5Qz5tRYt/t2FiJyHkla27NJqmK7qn5F\nRNYBdwKbgd3ANap6pOe9VGmcmKG9Ir/6VOOEDe2cLCZfZuQnA3IbahqQB00+MdllbUbZmKyzoWs7\nQ2cjTGNR7xmql5MD1LuVH8+bFXsyQllny9RtELTZzJsSBzUx9ZP3O1bkeaMmtwySpXYh5VhoqPII\n6fYwiDHIzQL/UlUvArYCn0sX2ui6CIfj9GV0Egm6bjvlMjq6XTp9OwtV3aeqP0z3jwHPkORBDy3C\n4Tg9GZXFj1y3nbIZFd0eBoV8FukarR8gyV4YWoSj85obgRsBpqfWLLScTo0YxaH6wLo96brtjKZu\nl0V0ZyEiq4D/BPxzVT1qV9/rtQhHurrTdoDVqzZpe/lUzvYN0J4O+SOy4jVOtrrKZabdXx6y98fI\nc6txBWycIT+FxbojQtd22EcHKvdsRL1E1G9OHmqn5VlIbV9GcBhehm6vWbFRpd0uz05fJqPmj1jM\nehlmOUZQt8skKohYRCZJPqZvq+pfpeLQIhyO05sRsuu6bjulMkK6XTZ9O4t0Ae+vA8+o6pfMobmF\nMyC/CIfjBJmb5RqzDb0srttOiYySbg+DGDPUrwP/PfCEiPw4lf1rkpWaTlmEoycKcrJFa3n+sY3j\nARNTyPQ0a0Jep5rF5JN2pma7u7xtQ2QD8oIzO3OYoW1+Nnf+nrnnxZTbygvWS1S9G7ltQ9t+Mdj3\nWmTK020SnZCyQkFLJJg9YInIh8YQ2meEdLt0+nYWqvr3JJ1mN7ouwuE4QUZoGO667ZTKCOn2MPAZ\n3E7lLNVhuOP0o8667Z2FUz01/qCcMafGul1tZ9GA9nSTxkx+Vkp7OrOj22NB+VQxuU6YuFXrBwjJ\nre8g56ew4XXmBYqaOM21wXv2KkfE+1j/RdH6Ktwe0/k0Jf2o66+vSuzskWjIL7bE5aNOXXUbIkNn\nHadUSgovFJHzROT7IvK0iDwlIjel8nUi8oCIPJ/+u9Zcc4uI7BKR50Tko0Z+mYg8kR77kzRSChFZ\nJiJ3pvId6eQ9x+nOOIfOOk6paKkpEQrldkqPbQMuBq4Cvioic8OirwGfAbak21Wp/AbgiKpeAHwZ\n+OLAdeDUk3J1e+TwzsKplDJj0ReQ2+lq4A5VPaGqLwK7gCvSiXerVfVRVVWSTLT2mrl73Q1cOTfq\ncByLz7MoEwWZ1ZytHMinoLDzAAaR5+YfWLu+lCKnMcD/L+yl2v1Zg5Yv9/6zRl5W/QbkUcTboNeL\nyE7z9/Y0xcYpROZ22gQ8ai7bk8pm0v1O+dw1ryTF1lkReQM4Azh4ymuJFLbHx9Dr2lHwI4yavPNY\nDKX5S5aQf6UoHg3lVE6BX1YHVfXyvvdbYG4nxymbOmuam6Gcaol1AEZ+dAVzO+0FzjOXn5vK9qb7\nnfLcNSIyAawBDsWVzhkrStbtUaPakYVAe6pxaujsVNZn5UM7jTxnSuku16DpaeHyvJlogSto9ULC\n9xyk3Dl5oF6i6jfUHgF5DGU5+CJyO91GPrfTPcB3RORLwEYSR/ZjqtoSkaMispXEjHUd8Kcd93oE\n+CTwcOrXOLU8qgOFgg5qbhkFE9AoyGOvsZRmMlyizusY3AzlVE6JH1Sh3E6q+pSI3AU8TRJJ9TlV\nnUts9VngdmA5cF+6QdIZfUtEdgGHSaKpHKcr3lk4TlkopY3KFpLbSVVvBW7tIt8JXNJFfhz41ADF\ndMaFEnV7FPHOwqmcOjsBnfGmzrpdeehso1vobCA1RU4eSMUdlNuQUpMSI0puGtym44iRx6Dmt3Do\nnp3HBnofKy9aj6H2CKQKiaKmH1SnfTtk746xgy/k2qLXqF2lsT0C8qLlL7Euip4Tvnjhl3aSThjd\nCexV1Y+LyDrgTmAzsBu4RlWPpOfeQjKBtAV8XlXvT+WXkZlX7wVuSiMEl5HMJ7qMJGDjWlXd3as8\nHg3lVErdJy4548sQdPsmkommcyxqZgLvLJxqUUXacZvjLClK1G0RORf4J8CfGfGiZibwzsKpnhrH\nojtjTrxurxeRnWa7seNOfwz8ATlDXc/MBK+Y8+YyEGwiMjMBMJeZIEjFKcqF9lQjnzaDEucThJZA\nbQbmTYTkubThEfJBTJyBe/Z8XsT7RC0NW1K9F55n4R3BaBByNS2WvAaUkZ1ARD4OHFDVx0XkQ93O\nWYzMBB4N5VSLkluDw3FqQ3m6/evAJ0TkY8A0sFpE/oI0M4Gq7isxM8Ge2MwEboZyqsfNUE5dKUG3\nVfUWVT1XVTeTOK4fVtVPk2UTgFMzE2xL1145nywzwT7gqIhsTf0R13VcM3evnpkJ5qg4dFahrbQn\n8n1UPuQ1FAo7gNz29qGV6cqSx5DLOhu454DlGEo9RshjcDNUBPYTaQfkvY6Ns7zfsSEyZN1e1MwE\nboZyKscjnZy6UrZuq+oPgB+k+4dYxMwE3lk41eImJqeu1Fy3vbNwKiWZuFTjL8oZW+qu2xWnKBd0\nspFbuQ3Ip9COSTleVJ5LzTFceQwx9yy1fIPUY6g9AvIoahw6WRqD2ubHWd55rEpqrNs+snAqp86/\nvpzxps667Z2FUy01t+s6Y0zNdbtvZyEifw7MzSi8JJUFsx/2vV9LcxlO52RztEOruoVmDxeUDyVz\nZkGUyHsOUL6y6ivYHkbemC0y9h6dvE+l6rZQzaylXs8IHRs3eb9jQ2N0dHsYxFTp7WSZCufomv3Q\ncaJQjduGz+24bjtlMjq6XTp9OwtV/TuSSRuWUPZDx+mNJktPxmxDL4rrtlMmI6Tbw2ChPotQ9kPH\n6c9o/7Jy3XYWzmjr9kAM7ODul/0wTb17I8Cy6dNpTzZOsetpYFW3ocubgVDTkD+i2V08EL3uaY6F\nypeTL1I9dvqg+rJEvqciuj09tSYRjkpai3GWD+sZMSwR3V4IC3UD7U+zHtKR/fAUVHW7ql6uqpdP\nTq1c4OOcOiHtdtS2SCxIt6cmVlRWQGd0GXHdHoiFdhah7IeO0xsl+bUWsy0OrtvOwhh93R6ImNDZ\nvwQ+RLKy0x7gDwlkP3Scfgg6MhOXXLedMhkl3R4GfTsLVf3dwKGu2Q973yzZ2h0+ARsdYI9VKS+a\nsqNq1C6Pa1ORL1J9heRRjMgHVapuz7GYcwvsd2XruK7yxZxzEmJEdHsY+Axup3pq/EE5Y06Ndds7\nC6da5uy6jlM3aq7bFWedTcI+TwmdbQZCNSPkhEJeB5CPPI3y379ovQfbI4KlGg0y8oR0OEYugW9h\n2PKi5Rxx6qzbPrJwKmbppjtwnN7UW7e9s3CqRan1B+WMMTXX7UXJzeiMOSXFoovIn4vIARF50sjW\nicgDIvJ8+u9ac+wWEdklIs+JyEeN/DIReSI99iciic1ERJaJyJ2pfIeIbC7h7Z06U+N5FtV3Fqq0\nJyS32WyM7abMb0G5vV1D5rfS5JJtIfkwNvusnuUYwvtH1buVB9ov5peVqEZtEdxOZNZYEbkI2AZc\nnF7zVRGZS6jyNeAzwJZ0m7vnDcARVb0A+DLwxZhCdcW2dVnyMu9l269K+TDqqOx7FaBE3R45fGTh\nVE9JaZwLZo29GrhDVU+o6ovALuCKNKXHalV9VFUV+GbHNXP3uhu4cm7U4ThdqXGKcvdZONWiCq3o\ncfh6Edlp/t6uqtv7XBPKGrsJeNSctyeVzaT7nfK5a15Jiq2zIvIGcAZwMPYFnDGimG4vObyzcKon\n/pfVQVW9fOGP6Z011nFKZ4mOGmKofp7FZANa+QrNzwOIkFvj2QjIB8IaNTruuWjvWbQ9CqcoH+oH\ntV9ENqjqvo6ssXuB88x556ayvel+p9xes0dEJoA1wKEFlWoYcx0Wcs04yGOvCZ0/CDXuLNxn4VSL\nAm2N2xZGKGvsPcC2NMLpfBJH9mOpyeqoiGxN/RHXdVwzd69PAg+nfg3HOZXh6/ai4mYop2IUtBy7\nbpGssar6lIjcBTwNzAKfU9VWeqvPkkRWLQfuSzeArwPfEpFdJI70baUU3Kkp5en2KFJtZ5H2vHbF\nNQAxZqncamzWXGVNIO0Rloey14bOCd2z6nIH5KH2CLZTP5TSnIBFs8aq6q3ArV3kO4FLusiPA5+K\nLlCZgVKhe/V6RtFr6ipf6DWDUqJujyI+snCqxy05Tl2psW57Z+FUT40/KGfMqbFuu4PbqZjISUs1\n/uiculKebovItIg8JiI/EZGnROSPUvmipbOpPnR2Qk5ZWS1n/25HyG2q7EBoZ1nyHEXlg15b4Xvm\n5EXbY6KAHViBGqdxrjy99yiEqo6afFjP6Ee5un0C+LCqvikik8Dfi8h9wD8lSWdzm4jcTJLO5gsd\n6Ww2Ag+KyPvSII65dDY7gHtJ0tnch0lnIyLbSNLZXBsqkI8snOrxkYVTV8pLZaOq+mb652S6KYuY\nzsZ9Fk7FaK0jRpxxppBu901lkya6fBy4APj3qrpDRBYtnU31nYVCu5kXWZOGPTaIPGrWsj1lxNPD\nhcqXk4fe08jLqt+QvC8KWuNY9NLCPxumAe0v0UaHAoeOjbO817Eyw3M7KabbfVPZpCakS0XkdOC7\nInJJx/FK09m4GcqpnhrPcnXGnCHotqq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"text/plain": [
"<matplotlib.figure.Figure at 0x191f6706748>"
]
},
"metadata": {},
"output_type": "display_data"
},
{
"data": {
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mbPoZsEbSCuBJ4MwsFeYROjuZm51bSGle58lROKW4L5kqK7Cu1uSmbVNj6Gqt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\nQTEAAAAASUVORK5CYII=\n",
"text/plain": [
"<matplotlib.figure.Figure at 0x191f66bd198>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"# Because we are interpolating for missing values we have grid scale noise so we will smooth the grid lengths\n",
"# THIS IS A HACK!\n",
"plt.figure()\n",
"plt.subplot(121);plt.pcolormesh(dx[700:760,300:340]); plt.colorbar();\n",
"plt.subplot(122);plt.pcolormesh(dy[700:760,300:340]); plt.colorbar();\n",
"def smth(a):\n",
" fy = numpy.roll(a,axis=0,shift=-1) - a ; fy[-1,:] = 0 ;\n",
" da = fy - numpy.roll(fy,axis=0,shift=1); da[0,:] = fy[0,:] ;\n",
" a = a + 0.25 * da\n",
" fx = numpy.roll(a,axis=1,shift=-1) - a ;\n",
" da = fx - numpy.roll(fx,axis=1,shift=1);\n",
" a = a + 0.25 * da\n",
" return a\n",
"for n in range(2): dx = smth(dx)\n",
"for n in range(2): dy = smth(dy)\n",
"plt.figure()\n",
"plt.subplot(121);plt.pcolormesh(dx[700:760,300:340]); plt.colorbar();\n",
"plt.subplot(122);plt.pcolormesh(dy[700:760,300:340]); plt.colorbar();"
]
},
{
"cell_type": "code",
"execution_count": 30,
"metadata": {
"collapsed": true
},
"outputs": [],
"source": [
"# Create a mosaic-compatible grid file\n",
"with netCDF4.Dataset('ocean_hgrid.nc','w',format='NETCDF3_64BIT_OFFSET') as newfile:\n",
" newfile.title = 'Horizontal grid file derived from cesm.pop.gx1v6'\n",
" newfile.reference_url = '...'\n",
" # Dimensions\n",
" dj = newfile.createDimension('nj', 2*nj)\n",
" di = newfile.createDimension('ni', 2*ni)\n",
" djp1 = newfile.createDimension('njp1', 2*nj+1)\n",
" dip1 = newfile.createDimension('nip1', 2*ni+1)\n",
" # Variables\n",
" vj = newfile.createVariable('y','f',('njp1','nip1',))\n",
" vj.long_name = 'Geographic latitude'\n",
" vj.units = 'degrees N'\n",
" vi = newfile.createVariable('x','f',('njp1','nip1',))\n",
" vi.long_name = 'Geographic longitude'\n",
" vi.units = 'degrees E'\n",
" va = newfile.createVariable('area','f',('nj','ni',))\n",
" va.long_name = 'cell area'\n",
" va.units = 'm^2'\n",
" vx = newfile.createVariable('dx','f',('njp1','ni',))\n",
" vx.long_name = 'length of edge'\n",
" vx.units = 'm'\n",
" vy = newfile.createVariable('dy','f',('nj','nip1',))\n",
" vy.long_name = 'length of edge'\n",
" vy.units = 'm'\n",
" # Data\n",
" vj[:] = y[:]\n",
" vi[:] = x[:]\n",
" va[:] = area[:]\n",
" vx[:] = dx[:]\n",
" vy[:] = dy[:]"
]
},
{
"cell_type": "code",
"execution_count": 31,
"metadata": {},
"outputs": [
{
"data": {
"image/png": 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E4+G+pBqnS+nhDrnOyLAQdZmFESXvgY89ZjnpushaDWFZZBe2qE/kqQxYmuJ6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\n/wEqZ7j3vL9HEgAAAABJRU5ErkJggg==\n",
"text/plain": [
"<matplotlib.figure.Figure at 0x191f666b630>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"# Topography\n",
"H = nc.variables['HT'][:]/1e2\n",
"plt.pcolormesh(H); plt.colorbar();\n",
"with netCDF4.Dataset('ocean_topog.nc','w',format='NETCDF3_64BIT_OFFSET') as newfile:\n",
" newfile.title = 'Horizontal topography copied from cesm.pop.gx1v6'\n",
" newfile.reference_url = '...'\n",
" # Dimensions\n",
" dj = newfile.createDimension('nj', nj)\n",
" di = newfile.createDimension('ni', ni)\n",
" # Variables\n",
" vh = newfile.createVariable('depth','f',('nj','ni',))\n",
" vh.long_name = 'Depth of ocean bottom'\n",
" vh.units = 'm'\n",
" # Data\n",
" vh[:] = H[:]"
]
},
{
"cell_type": "code",
"execution_count": 32,
"metadata": {},
"outputs": [
{
"data": {
"image/png": 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z5bkO0xuBB8xsKfBA+OzUTNQXgDMVdNfB6Otky4W5mzXAlvB+C3BVDb/hOE7C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\nYII=\n",
"text/plain": [
"<matplotlib.figure.Figure at 0x191f3ea4588>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"# Wet/dry mask\n",
"M = 0.*H; M[H>0] =1.\n",
"plt.pcolormesh(M); plt.colorbar();\n",
"with netCDF4.Dataset('ocean_mask.nc','w',format='NETCDF3_64BIT_OFFSET') as newfile:\n",
" newfile.title = 'Wet/dry mask derived from cesm.pop.gx1v6'\n",
" newfile.reference_url = '...'\n",
" # Dimensions\n",
" dj = newfile.createDimension('nj', nj)\n",
" di = newfile.createDimension('ni', ni)\n",
" # Variables\n",
" vm = newfile.createVariable('mask','f',('nj','ni',))\n",
" vm.long_name = 'Depth of ocean bottom'\n",
" vm.units = 'nondim'\n",
" # Data\n",
" vm[:] = M[:]"
]
},
{
"cell_type": "code",
"execution_count": 33,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"dz= [ 10. 10. 10. 10. 10. 10.\n",
" 10. 10. 10. 10. 10. 10.\n",
" 10. 10. 10. 10. 10.19680786\n",
" 10.56448364 11.05995083 11.67807007 12.4241333 13.30967808\n",
" 14.35140991 15.57125854 16.99679565 18.66212463 20.60902405\n",
" 22.88852119 25.56247139 28.70574951 32.40837097 36.77772522\n",
" 41.94030762 48.04223633 55.24754333 63.73191833 73.66944885\n",
" 85.20892334 98.43658447 113.32466125 129.67199707 147.05343628\n",
" 164.80708313 182.09135437 198.02233887 211.85957336 223.1651001\n",
" 231.86494446 238.19448853 242.57217407 245.4677887 247.31013489\n",
" 248.44328308 249.11975098 249.51290894 249.7359314 249.85960388\n",
" 249.92674255 249.96244812 249.98109436]\n"
]
}
],
"source": [
"print('dz=',nc.variables['dz'][:]/1e2 )\n",
"#print('dzw=',nc.variables['dzw'][:]/1e2 )\n",
"#print('z_t=',nc.variables['z_t'][:]/1e2 )\n",
"#print('z_w=',nc.variables['z_w'][:]/1e2 )\n",
"#print('z_w_top=',nc.variables['z_w_top'][:]/1e2 )\n",
"#print('z_w_bot=',nc.variables['z_w_bot'][:]/1e2 )\n",
"dz = numpy.rint( nc.variables['dz'][:]/25 )/4\n",
"dz[-4] += 0.25\n",
"dz, dz.sum()\n",
"with netCDF4.Dataset('ocean_vgrid.nc','w',format='NETCDF3_64BIT_OFFSET') as newfile:\n",
" newfile.title = 'Vertical resolution derived from cesm.pop.gx1v6'\n",
" newfile.reference_url = '...'\n",
" # Dimensions\n",
" dk = newfile.createDimension('nk', dz.shape[0])\n",
" # Variables\n",
" v = newfile.createVariable('dz','f',('nk',))\n",
" v.long_name = 'Nominal thickness of level'\n",
" v.units = 'dz'\n",
" # Data\n",
" v[:] = dz[:]"
]
}
],
"metadata": {
"anaconda-cloud": {},
"kernelspec": {
"display_name": "Python [default]",
"language": "python",
"name": "python3"
},
"language_info": {
"codemirror_mode": {
"name": "ipython",
"version": 3
},
"file_extension": ".py",
"mimetype": "text/x-python",
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.5.3"
}
},
"nbformat": 4,
"nbformat_minor": 1
}
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