cm_eof_amplitudes.ipynb

{
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   "source": [
    "import numpy as np\n",
    "import matplotlib.pyplot as plt \n",
    "from matplotlib.colors import LogNorm\n",
    "import cmocean as cmo\n",
    "import xarray as xr \n",
    "import cartopy\n",
    "import cartopy.crs as ccrs\n",
    "from scipy.io import loadmat\n",
    "from scipy.interpolate import interp1d\n",
    "from tqdm import tqdm\n",
    "import warnings \n",
    "warnings.filterwarnings('ignore')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "# LOAD EOFS\n",
    "cm26_eof_path = '/Users/jakesteinberg/Documents/CPT/models/CM2.6_EOF_analysis_w_amplitudes.nc'\n",
    "cmEOF = xr.open_dataset(cm26_eof_path)\n",
    "# shift EOF longitudes to match with modes \n",
    "lon01 = cmEOF.lon.data\n",
    "eofu1_a = np.concatenate((cmEOF.eof1u_mag[:,:,lon01 >= 0].data, cmEOF.eof1u_mag[:,:,lon01 < 0].data),axis=2)\n",
    "lon1 = np.concatenate((lon01[lon01 >= 0], lon01[lon01 < 0]+360))\n",
    "lat1 = cmEOF.lat.data"
   ]
  },
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       "</style><div class='xr-wrap'><div class='xr-header'><div class='xr-obj-type'>xarray.Dataset</div></div><ul class='xr-sections'><li class='xr-section-item'><input id='section-e8cca8a8-6dbb-4bc5-88d7-bc1f27c88517' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-e8cca8a8-6dbb-4bc5-88d7-bc1f27c88517' class='xr-section-summary'  title='Expand/collapse section'>Dimensions:</label><div class='xr-section-inline-details'><ul class='xr-dim-list'><li><span class='xr-has-index'>lat</span>: 270</li><li><span class='xr-has-index'>lon</span>: 360</li><li><span class='xr-has-index'>time</span>: 73</li><li><span class='xr-has-index'>zl</span>: 50</li></ul></div><div class='xr-section-details'></div></li><li class='xr-section-item'><input id='section-556f778b-0d25-4943-8ee6-d3d6b1cabf9a' class='xr-section-summary-in' type='checkbox'  checked><label for='section-556f778b-0d25-4943-8ee6-d3d6b1cabf9a' class='xr-section-summary' >Coordinates: <span>(4)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>zl</span></div><div class='xr-var-dims'>(zl)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>5.034 15.1 ... 5.185e+03 5.395e+03</div><input id='attrs-fa4a4b97-72c2-400a-8077-0cc56dcd415f' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-fa4a4b97-72c2-400a-8077-0cc56dcd415f' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-42475e1d-55ea-4333-a4c3-0cc5f7eddcb4' class='xr-var-data-in' type='checkbox'><label for='data-42475e1d-55ea-4333-a4c3-0cc5f7eddcb4' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><pre class='xr-var-data'>array([5.033550e+00, 1.510065e+01, 2.521935e+01, 3.535845e+01, 4.557635e+01,\n",
       "       5.585325e+01, 6.626175e+01, 7.680285e+01, 8.757695e+01, 9.862325e+01,\n",
       "       1.100962e+02, 1.221067e+02, 1.349086e+02, 1.487466e+02, 1.640538e+02,\n",
       "       1.813125e+02, 2.012630e+02, 2.247773e+02, 2.530681e+02, 2.875508e+02,\n",
       "       3.300078e+02, 3.823651e+02, 4.467263e+02, 5.249824e+02, 6.187031e+02,\n",
       "       7.286921e+02, 8.549935e+02, 9.967153e+02, 1.152376e+03, 1.319997e+03,\n",
       "       1.497562e+03, 1.683057e+03, 1.874788e+03, 2.071252e+03, 2.271323e+03,\n",
       "       2.474043e+03, 2.678757e+03, 2.884898e+03, 3.092117e+03, 3.300086e+03,\n",
       "       3.508633e+03, 3.717567e+03, 3.926813e+03, 4.136251e+03, 4.345864e+03,\n",
       "       4.555566e+03, 4.765369e+03, 4.975209e+03, 5.185111e+03, 5.395023e+03])</pre></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>lat</span></div><div class='xr-var-dims'>(lat)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>-81.11 -80.69 -80.26 ... 89.18 89.6</div><input id='attrs-ae34712e-2adb-4404-aa34-4e8748d4d9be' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-ae34712e-2adb-4404-aa34-4e8748d4d9be' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-bce0a9a5-15e5-46f6-95fb-51c70ce58f21' class='xr-var-data-in' type='checkbox'><label for='data-bce0a9a5-15e5-46f6-95fb-51c70ce58f21' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><pre class='xr-var-data'>array([-81.108632, -80.686238, -80.263845, ...,  88.753955,  89.176348,\n",
       "        89.598742])</pre></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>lon</span></div><div class='xr-var-dims'>(lon)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>-279.9 -278.9 ... 78.05 79.05</div><input id='attrs-e0994a13-de6c-4876-b6ae-b569852cd371' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-e0994a13-de6c-4876-b6ae-b569852cd371' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-587b30c6-7a67-48e0-a11d-46eefde118d3' class='xr-var-data-in' type='checkbox'><label for='data-587b30c6-7a67-48e0-a11d-46eefde118d3' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><pre class='xr-var-data'>array([-279.95, -278.95, -277.95, ...,   77.05,   78.05,   79.05])</pre></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>time</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>object</div><div class='xr-var-preview xr-preview'>0201-01-03 12:00:00 ... 0201-12-29 12:00:00</div><input id='attrs-720ae481-4a9d-4513-af01-f3460a587722' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-720ae481-4a9d-4513-af01-f3460a587722' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-24c2d284-6f2f-4ef5-88f6-3271c81ce1a2' class='xr-var-data-in' type='checkbox'><label for='data-24c2d284-6f2f-4ef5-88f6-3271c81ce1a2' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><pre class='xr-var-data'>array([cftime.DatetimeJulian(0201-01-03 12:00:00),\n",
       "       cftime.DatetimeJulian(0201-01-08 12:00:00),\n",
       "       cftime.DatetimeJulian(0201-01-13 12:00:00),\n",
       "       cftime.DatetimeJulian(0201-01-18 12:00:00),\n",
       "       cftime.DatetimeJulian(0201-01-23 12:00:00),\n",
       "       cftime.DatetimeJulian(0201-01-28 12:00:00),\n",
       "       cftime.DatetimeJulian(0201-02-02 12:00:00),\n",
       "       cftime.DatetimeJulian(0201-02-07 12:00:00),\n",
       "       cftime.DatetimeJulian(0201-02-12 12:00:00),\n",
       "       cftime.DatetimeJulian(0201-02-17 12:00:00),\n",
       "       cftime.DatetimeJulian(0201-02-22 12:00:00),\n",
       "       cftime.DatetimeJulian(0201-02-27 12:00:00),\n",
       "       cftime.DatetimeJulian(0201-03-04 12:00:00),\n",
       "       cftime.DatetimeJulian(0201-03-09 12:00:00),\n",
       "       cftime.DatetimeJulian(0201-03-14 12:00:00),\n",
       "       cftime.DatetimeJulian(0201-03-19 12:00:00),\n",
       "       cftime.DatetimeJulian(0201-03-24 12:00:00),\n",
       "       cftime.DatetimeJulian(0201-03-29 12:00:00),\n",
       "       cftime.DatetimeJulian(0201-04-03 12:00:00),\n",
       "       cftime.DatetimeJulian(0201-04-08 12:00:00),\n",
       "       cftime.DatetimeJulian(0201-04-13 12:00:00),\n",
       "       cftime.DatetimeJulian(0201-04-18 12:00:00),\n",
       "       cftime.DatetimeJulian(0201-04-23 12:00:00),\n",
       "       cftime.DatetimeJulian(0201-04-28 12:00:00),\n",
       "       cftime.DatetimeJulian(0201-05-03 12:00:00),\n",
       "       cftime.DatetimeJulian(0201-05-08 12:00:00),\n",
       "       cftime.DatetimeJulian(0201-05-13 12:00:00),\n",
       "       cftime.DatetimeJulian(0201-05-18 12:00:00),\n",
       "       cftime.DatetimeJulian(0201-05-23 12:00:00),\n",
       "       cftime.DatetimeJulian(0201-05-28 12:00:00),\n",
       "       cftime.DatetimeJulian(0201-06-02 12:00:00),\n",
       "       cftime.DatetimeJulian(0201-06-07 12:00:00),\n",
       "       cftime.DatetimeJulian(0201-06-12 12:00:00),\n",
       "       cftime.DatetimeJulian(0201-06-17 12:00:00),\n",
       "       cftime.DatetimeJulian(0201-06-22 12:00:00),\n",
       "       cftime.DatetimeJulian(0201-06-27 12:00:00),\n",
       "       cftime.DatetimeJulian(0201-07-02 12:00:00),\n",
       "       cftime.DatetimeJulian(0201-07-07 12:00:00),\n",
       "       cftime.DatetimeJulian(0201-07-12 12:00:00),\n",
       "       cftime.DatetimeJulian(0201-07-17 12:00:00),\n",
       "       cftime.DatetimeJulian(0201-07-22 12:00:00),\n",
       "       cftime.DatetimeJulian(0201-07-27 12:00:00),\n",
       "       cftime.DatetimeJulian(0201-08-01 12:00:00),\n",
       "       cftime.DatetimeJulian(0201-08-06 12:00:00),\n",
       "       cftime.DatetimeJulian(0201-08-11 12:00:00),\n",
       "       cftime.DatetimeJulian(0201-08-16 12:00:00),\n",
       "       cftime.DatetimeJulian(0201-08-21 12:00:00),\n",
       "       cftime.DatetimeJulian(0201-08-26 12:00:00),\n",
       "       cftime.DatetimeJulian(0201-08-31 12:00:00),\n",
       "       cftime.DatetimeJulian(0201-09-05 12:00:00),\n",
       "       cftime.DatetimeJulian(0201-09-10 12:00:00),\n",
       "       cftime.DatetimeJulian(0201-09-15 12:00:00),\n",
       "       cftime.DatetimeJulian(0201-09-20 12:00:00),\n",
       "       cftime.DatetimeJulian(0201-09-25 12:00:00),\n",
       "       cftime.DatetimeJulian(0201-09-30 12:00:00),\n",
       "       cftime.DatetimeJulian(0201-10-05 12:00:00),\n",
       "       cftime.DatetimeJulian(0201-10-10 12:00:00),\n",
       "       cftime.DatetimeJulian(0201-10-15 12:00:00),\n",
       "       cftime.DatetimeJulian(0201-10-20 12:00:00),\n",
       "       cftime.DatetimeJulian(0201-10-25 12:00:00),\n",
       "       cftime.DatetimeJulian(0201-10-30 12:00:00),\n",
       "       cftime.DatetimeJulian(0201-11-04 12:00:00),\n",
       "       cftime.DatetimeJulian(0201-11-09 12:00:00),\n",
       "       cftime.DatetimeJulian(0201-11-14 12:00:00),\n",
       "       cftime.DatetimeJulian(0201-11-19 12:00:00),\n",
       "       cftime.DatetimeJulian(0201-11-24 12:00:00),\n",
       "       cftime.DatetimeJulian(0201-11-29 12:00:00),\n",
       "       cftime.DatetimeJulian(0201-12-04 12:00:00),\n",
       "       cftime.DatetimeJulian(0201-12-09 12:00:00),\n",
       "       cftime.DatetimeJulian(0201-12-14 12:00:00),\n",
       "       cftime.DatetimeJulian(0201-12-19 12:00:00),\n",
       "       cftime.DatetimeJulian(0201-12-24 12:00:00),\n",
       "       cftime.DatetimeJulian(0201-12-29 12:00:00)], dtype=object)</pre></li></ul></div></li><li class='xr-section-item'><input id='section-07e1c442-bbab-4dad-9431-37d30eaca1fa' class='xr-section-summary-in' type='checkbox'  checked><label for='section-07e1c442-bbab-4dad-9431-37d30eaca1fa' class='xr-section-summary' >Data variables: <span>(6)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span>EOF1u</span></div><div class='xr-var-dims'>(zl, lat, lon)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-14aa0541-c727-4c87-a57c-d946ffe6587f' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-14aa0541-c727-4c87-a57c-d946ffe6587f' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-4937e47c-fdcb-4e41-a9d7-7dca6d9e3876' class='xr-var-data-in' type='checkbox'><label for='data-4937e47c-fdcb-4e41-a9d7-7dca6d9e3876' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><pre class='xr-var-data'>[4860000 values with dtype=float32]</pre></li><li class='xr-var-item'><div class='xr-var-name'><span>EOF1v</span></div><div class='xr-var-dims'>(zl, lat, lon)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-4c763de7-4a0e-476c-96de-3aba503802da' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-4c763de7-4a0e-476c-96de-3aba503802da' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-7aa33059-6880-45a8-b6a3-b310f847f5c4' class='xr-var-data-in' type='checkbox'><label for='data-7aa33059-6880-45a8-b6a3-b310f847f5c4' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><pre class='xr-var-data'>[4860000 values with dtype=float32]</pre></li><li class='xr-var-item'><div class='xr-var-name'><span>pvaru</span></div><div class='xr-var-dims'>(lat, lon)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-96c61f48-1534-4dd0-ad90-b5a84ae4dccb' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-96c61f48-1534-4dd0-ad90-b5a84ae4dccb' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-c15b3e02-9187-4392-af53-a29fa4c3e4ef' class='xr-var-data-in' type='checkbox'><label for='data-c15b3e02-9187-4392-af53-a29fa4c3e4ef' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><pre class='xr-var-data'>array([[nan, nan, nan, ..., nan, nan, nan],\n",
       "       [nan, nan, nan, ..., nan, nan, nan],\n",
       "       [nan, nan, nan, ..., nan, nan, nan],\n",
       "       ...,\n",
       "       [nan, nan, nan, ..., nan, nan, nan],\n",
       "       [nan, nan, nan, ..., nan, nan, nan],\n",
       "       [nan, nan, nan, ..., nan, nan, nan]], dtype=float32)</pre></li><li class='xr-var-item'><div class='xr-var-name'><span>pvarv</span></div><div class='xr-var-dims'>(lat, lon)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-64bb304e-c2a6-4ab7-8948-4a3feb2a62ab' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-64bb304e-c2a6-4ab7-8948-4a3feb2a62ab' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-4cf4937f-6bec-47f8-8198-d9586863bf3f' class='xr-var-data-in' type='checkbox'><label for='data-4cf4937f-6bec-47f8-8198-d9586863bf3f' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><pre class='xr-var-data'>array([[nan, nan, nan, ..., nan, nan, nan],\n",
       "       [nan, nan, nan, ..., nan, nan, nan],\n",
       "       [nan, nan, nan, ..., nan, nan, nan],\n",
       "       ...,\n",
       "       [nan, nan, nan, ..., nan, nan, nan],\n",
       "       [nan, nan, nan, ..., nan, nan, nan],\n",
       "       [nan, nan, nan, ..., nan, nan, nan]], dtype=float32)</pre></li><li class='xr-var-item'><div class='xr-var-name'><span>eof1u_mag</span></div><div class='xr-var-dims'>(time, lat, lon)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-16e896b4-f5d3-4274-916f-ee60815d19d1' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-16e896b4-f5d3-4274-916f-ee60815d19d1' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-48851be9-d715-4522-9079-1aa4f37ad5d8' class='xr-var-data-in' type='checkbox'><label for='data-48851be9-d715-4522-9079-1aa4f37ad5d8' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><pre class='xr-var-data'>[7095600 values with dtype=float32]</pre></li><li class='xr-var-item'><div class='xr-var-name'><span>eof1v_mag</span></div><div class='xr-var-dims'>(time, lat, lon)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-7e883a20-384a-4b7b-9dce-c606ad53bf34' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-7e883a20-384a-4b7b-9dce-c606ad53bf34' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-829813c7-7d5e-4b47-8c8d-07da07508c1d' class='xr-var-data-in' type='checkbox'><label for='data-829813c7-7d5e-4b47-8c8d-07da07508c1d' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><pre class='xr-var-data'>[7095600 values with dtype=float32]</pre></li></ul></div></li><li class='xr-section-item'><input id='section-b43a5f1f-79e3-4b99-9b17-3e6b3e405b77' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-b43a5f1f-79e3-4b99-9b17-3e6b3e405b77' class='xr-section-summary'  title='Expand/collapse section'>Attributes: <span>(0)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'></dl></div></li></ul></div></div>"
      ],
      "text/plain": [
       "<xarray.Dataset>\n",
       "Dimensions:    (lat: 270, lon: 360, time: 73, zl: 50)\n",
       "Coordinates:\n",
       "  * zl         (zl) float64 5.034 15.1 25.22 ... 4.975e+03 5.185e+03 5.395e+03\n",
       "  * lat        (lat) float64 -81.11 -80.69 -80.26 -79.84 ... 88.75 89.18 89.6\n",
       "  * lon        (lon) float64 -279.9 -278.9 -277.9 -276.9 ... 77.05 78.05 79.05\n",
       "  * time       (time) object 0201-01-03 12:00:00 ... 0201-12-29 12:00:00\n",
       "Data variables:\n",
       "    EOF1u      (zl, lat, lon) float32 ...\n",
       "    EOF1v      (zl, lat, lon) float32 ...\n",
       "    pvaru      (lat, lon) float32 ...\n",
       "    pvarv      (lat, lon) float32 ...\n",
       "    eof1u_mag  (time, lat, lon) float32 ...\n",
       "    eof1v_mag  (time, lat, lon) float32 ..."
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "cmEOF"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [],
   "source": [
    "lon_check = 310\n",
    "lat_check = -40\n",
    "i1 = np.where((lon1 > lon_check) & (lon1 < lon_check+1))[0][0]\n",
    "j1 = np.where((lat1 >= lat_check) & (lat1 < lat_check+0.5))[0][0]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[<matplotlib.lines.Line2D at 0x7f89af8e3710>]"
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "f, ax = plt.subplots(1,1,figsize=(10,4))\n",
    "ax.plot(np.arange(len(cmEOF.time)),eofu1_a[:,j1,i1],linestyle='-',color='k')\n",
    "ax.plot(np.arange(len(cmEOF.time)),eofu1_a[:,j1-1,i1],linestyle='-')\n",
    "ax.plot(np.arange(len(cmEOF.time)),eofu1_a[:,j1+1,i1],linestyle='-')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python [conda env:cpt]",
   "language": "python",
   "name": "conda-env-cpt-py"
  },
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