diff --git a/Match_LOFAR_combined_final.ipynb b/Match_LOFAR_combined_final.ipynb
index 072d019..fd05652 100644
--- a/Match_LOFAR_combined_final.ipynb
+++ b/Match_LOFAR_combined_final.ipynb
@@ -42,7 +42,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 2,
+   "execution_count": 3,
    "metadata": {
     "collapsed": true
    },
@@ -53,7 +53,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 3,
+   "execution_count": 4,
    "metadata": {
     "collapsed": true
    },
@@ -64,7 +64,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 4,
+   "execution_count": 5,
    "metadata": {
     "collapsed": true
    },
@@ -75,7 +75,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 5,
+   "execution_count": 6,
    "metadata": {
     "collapsed": true
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@@ -86,7 +86,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 6,
+   "execution_count": 7,
    "metadata": {
     "collapsed": false
    },
@@ -112,7 +112,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 7,
+   "execution_count": 8,
    "metadata": {
     "collapsed": true
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@@ -124,7 +124,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 8,
+   "execution_count": 9,
    "metadata": {
     "collapsed": true
    },
@@ -135,7 +135,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 9,
+   "execution_count": 10,
    "metadata": {
     "collapsed": true
    },
@@ -154,7 +154,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 10,
+   "execution_count": 11,
    "metadata": {
     "collapsed": true
    },
@@ -169,7 +169,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 11,
+   "execution_count": 12,
    "metadata": {
     "collapsed": true
    },
@@ -184,7 +184,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 12,
+   "execution_count": 13,
    "metadata": {
     "collapsed": true
    },
@@ -199,7 +199,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 13,
+   "execution_count": 14,
    "metadata": {
     "collapsed": true
    },
@@ -210,7 +210,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 14,
+   "execution_count": 15,
    "metadata": {
     "collapsed": true
    },
@@ -228,7 +228,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 15,
+   "execution_count": 16,
    "metadata": {
     "collapsed": true
    },
@@ -239,7 +239,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 16,
+   "execution_count": 17,
    "metadata": {
     "collapsed": true
    },
@@ -251,7 +251,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 17,
+   "execution_count": 18,
    "metadata": {
     "collapsed": false
    },
@@ -263,7 +263,7 @@
        "       'W1magErr', 'i', 'iErr'], dtype='<U8')"
       ]
      },
-     "execution_count": 17,
+     "execution_count": 18,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -274,7 +274,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 18,
+   "execution_count": 19,
    "metadata": {
     "collapsed": false
    },
@@ -289,7 +289,7 @@
        "       'Isl_id'], dtype='<U16')"
       ]
      },
-     "execution_count": 18,
+     "execution_count": 19,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -314,7 +314,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 19,
+   "execution_count": 20,
    "metadata": {
     "collapsed": true
    },
@@ -325,7 +325,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 20,
+   "execution_count": 21,
    "metadata": {
     "collapsed": true
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@@ -344,7 +344,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 21,
+   "execution_count": 22,
    "metadata": {
     "collapsed": true
    },
@@ -355,7 +355,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 22,
+   "execution_count": 23,
    "metadata": {
     "collapsed": true
    },
@@ -373,7 +373,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 23,
+   "execution_count": 24,
    "metadata": {
     "collapsed": true
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@@ -387,7 +387,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 24,
+   "execution_count": 25,
    "metadata": {
     "collapsed": true
    },
@@ -410,7 +410,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 25,
+   "execution_count": 26,
    "metadata": {
     "collapsed": true
    },
@@ -421,7 +421,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 26,
+   "execution_count": 27,
    "metadata": {
     "collapsed": true
    },
@@ -432,7 +432,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 27,
+   "execution_count": 28,
    "metadata": {
     "collapsed": true
    },
@@ -443,7 +443,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 28,
+   "execution_count": 29,
    "metadata": {
     "collapsed": true
    },
@@ -457,7 +457,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 29,
+   "execution_count": 30,
    "metadata": {
     "collapsed": false
    },
@@ -495,7 +495,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 30,
+   "execution_count": 31,
    "metadata": {
     "collapsed": true
    },
@@ -506,7 +506,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 31,
+   "execution_count": 32,
    "metadata": {
     "collapsed": false
    },
@@ -515,9 +515,9 @@
      "name": "stderr",
      "output_type": "stream",
      "text": [
-      "/home/jsm/programs/soft/anaconda3/lib/python3.6/site-packages/astropy/table/column.py:954: RuntimeWarning: invalid value encountered in less\n",
+      "/home/jsm/programs/soft/anaconda3/lib/python3.6/site-packages/astropy/table/column.py:965: RuntimeWarning: invalid value encountered in less\n",
       "  return getattr(self.data, op)(other)\n",
-      "/home/jsm/programs/soft/anaconda3/lib/python3.6/site-packages/astropy/table/column.py:954: RuntimeWarning: invalid value encountered in greater_equal\n",
+      "/home/jsm/programs/soft/anaconda3/lib/python3.6/site-packages/astropy/table/column.py:965: RuntimeWarning: invalid value encountered in greater_equal\n",
       "  return getattr(self.data, op)(other)\n"
      ]
     }
@@ -543,7 +543,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 32,
+   "execution_count": 33,
    "metadata": {
     "collapsed": true
    },
@@ -556,7 +556,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 33,
+   "execution_count": 34,
    "metadata": {
     "collapsed": false
    },
@@ -567,7 +567,7 @@
        "11"
       ]
      },
-     "execution_count": 33,
+     "execution_count": 34,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -585,7 +585,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 34,
+   "execution_count": 35,
    "metadata": {
     "collapsed": true
    },
@@ -596,7 +596,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 35,
+   "execution_count": 36,
    "metadata": {
     "collapsed": false
    },
@@ -609,7 +609,7 @@
        "         309428,   319368,    95816,    34128])"
       ]
      },
-     "execution_count": 35,
+     "execution_count": 36,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -627,7 +627,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 36,
+   "execution_count": 37,
    "metadata": {
     "collapsed": true
    },
@@ -638,7 +638,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 37,
+   "execution_count": 38,
    "metadata": {
     "collapsed": true
    },
@@ -656,7 +656,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 38,
+   "execution_count": 39,
    "metadata": {
     "collapsed": true
    },
@@ -667,7 +667,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 40,
    "metadata": {
     "collapsed": true
    },
@@ -679,7 +679,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 41,
    "metadata": {
     "collapsed": true
    },
@@ -725,23 +725,11 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 1,
+   "execution_count": 42,
    "metadata": {
     "collapsed": true
    },
-   "outputs": [
-    {
-     "ename": "NameError",
-     "evalue": "name 'search_around_sky' is not defined",
-     "output_type": "error",
-     "traceback": [
-      "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
-      "\u001b[0;31mNameError\u001b[0m                                 Traceback (most recent call last)",
-      "\u001b[0;32m<ipython-input-1-240a63d46585>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m()\u001b[0m\n\u001b[0;32m----> 1\u001b[0;31m idx_lofar, idx_i, d2d, d3d = search_around_sky(\n\u001b[0m\u001b[1;32m      2\u001b[0m     coords_lofar, coords_combined[selection], radius*u.arcsec)\n",
-      "\u001b[0;31mNameError\u001b[0m: name 'search_around_sky' is not defined"
-     ]
-    }
-   ],
+   "outputs": [],
    "source": [
     "idx_lofar, idx_i, d2d, d3d = search_around_sky(\n",
     "    coords_lofar, coords_combined[selection], radius*u.arcsec)"
@@ -749,7 +737,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 42,
+   "execution_count": 43,
    "metadata": {
     "collapsed": true
    },
@@ -767,7 +755,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 43,
+   "execution_count": 44,
    "metadata": {
     "collapsed": true
    },
@@ -780,7 +768,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 45,
    "metadata": {
     "collapsed": true
    },
@@ -792,7 +780,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 46,
    "metadata": {
     "collapsed": false
    },
@@ -801,7 +789,8 @@
      "name": "stderr",
      "output_type": "stream",
      "text": [
-      "  1%|          | 3.54K/306K [00:57<2:39:17, 31.6it/s]"
+      "100%|██████████| 312k/312k [4:12:03<00:00, 20.6it/s]\n",
+      "100%|██████████| 311874/311874 [00:00<00:00, 430902.00it/s]\n"
      ]
     }
    ],
@@ -811,7 +800,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 46,
+   "execution_count": 68,
    "metadata": {
     "collapsed": true
    },
@@ -824,20 +813,11 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 47,
+   "execution_count": 69,
    "metadata": {
     "collapsed": false
    },
-   "outputs": [
-    {
-     "name": "stderr",
-     "output_type": "stream",
-     "text": [
-      "/disk2/jsm/prog/anaconda/envs/py36/lib/python3.6/site-packages/numpy/ma/core.py:3399: UserWarning: Warning: converting a masked element to nan.\n",
-      "  _data[indx] = dval\n"
-     ]
-    }
-   ],
+   "outputs": [],
    "source": [
     "(lofar[\"lr_index\"][idx_lofar_unique], \n",
     " lofar[\"lr_dist\"][idx_lofar_unique], \n",
@@ -846,7 +826,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 48,
+   "execution_count": 70,
    "metadata": {
     "collapsed": true
    },
@@ -865,7 +845,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 49,
+   "execution_count": 71,
    "metadata": {
     "collapsed": true
    },
@@ -877,7 +857,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 50,
+   "execution_count": 72,
    "metadata": {
     "collapsed": true
    },
@@ -888,7 +868,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 51,
+   "execution_count": 73,
    "metadata": {
     "collapsed": true
    },
@@ -910,7 +890,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 52,
+   "execution_count": 74,
    "metadata": {
     "collapsed": true
    },
@@ -922,7 +902,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 53,
+   "execution_count": 75,
    "metadata": {
     "collapsed": true
    },
@@ -934,20 +914,11 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 54,
+   "execution_count": 76,
    "metadata": {
     "collapsed": false
    },
-   "outputs": [
-    {
-     "name": "stderr",
-     "output_type": "stream",
-     "text": [
-      "/disk2/jsm/prog/anaconda/envs/py36/lib/python3.6/site-packages/numpy/lib/function_base.py:2813: UserWarning: Warning: converting a masked element to nan.\n",
-      "  res = array(outputs, copy=False, subok=True, dtype=otypes[0])\n"
-     ]
-    }
-   ],
+   "outputs": [],
    "source": [
     "completeness_t = completeness_v(lofar[\"lrt\"], thresholds, q0)\n",
     "reliability_t = reliability_v(lofar[\"lrt\"], thresholds, q0)\n",
@@ -956,7 +927,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 55,
+   "execution_count": 77,
    "metadata": {
     "collapsed": true
    },
@@ -969,18 +940,70 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 56,
+   "execution_count": 83,
    "metadata": {
     "collapsed": true
    },
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "0.3580000000000002"
+      ]
+     },
+     "execution_count": 83,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "# Maximum of the average\n",
+    "thresholds_fine[np.argmax(average_t_fine)]"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 84,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "0.5860000000000004"
+      ]
+     },
+     "execution_count": 84,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "# Crossing point of completeness and reliability\n",
+    "thresholds_fine[np.argmin(np.abs(completeness_t_fine-reliability_t_fine))]"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 85,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Value selected for the paper\n",
+    "threshold_sel = 0.639"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 86,
+   "metadata": {},
    "outputs": [],
    "source": [
-    "threshold_sel = thresholds_fine[np.argmax(average_t_fine)]"
+    "threshold_sel = 0.639"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 57,
+   "execution_count": 87,
    "metadata": {
     "collapsed": false
    },
@@ -988,18 +1011,18 @@
     {
      "data": {
       "text/plain": [
-       "<matplotlib.text.Text at 0x7f2203609c88>"
+       "Text(0,0.5,'Completeness/Reliability')"
       ]
      },
-     "execution_count": 57,
+     "execution_count": 87,
      "metadata": {},
      "output_type": "execute_result"
     },
     {
      "data": {
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T0rclnmU8s2yPjY0ttNj+wcYGZs405a7ffBNOnoTffjPTR4sRe3t72rZtS9u2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Mur6rYkZzXbLwVeAFzRTGu5DTj9qfYdVFZJkmbanoyDAEmeDrwKOHPSU18IrElyOvB94M8G/mIk\nSXPOQM8RrKoNwIZJ6y5tLd8ITHn946n2nSVjMY1mmuyTndknU7Nfdmaf7Gxs+mQPx8GHgYOnWP9T\nelcS1T8Zm9+pGWSfTZ99Nn322fTNWp+laspzzCVJkiRJc9QgzxGUJEmSJA0hC8FGktck2ZzkziTn\ndp1nGCRZnOTvk9ye5LYk7+o607BIMi/JzUnWd51lGDQXvFib5NtJ7kjye11n6lqS/9j83XwryaeT\n7Nt1pi4kuTzJj5J8q7XumUn+Lsl3m+8HdZlRo2N3Y3WSf5fkliS3JrkhyYu6yDks+n1vk+SlSbYm\n+ZPZzDeM+umzJMclmWj+x39xtjMOmz7+Lg9Msi7JN5s+O62LnMNkqrFx0vYk+e9Nn96S5CWDyGEh\nSO9NPfBRepfpPhp4Y5Kju001FLYC51TV0cDLgbfbL094F3BH1yGGyIeBv62q5wMvYsz7JslhwDuB\nZVX1QnoXCjml21SdWQW8ZtK6c4GNVXUksLF5LD2lPsfqu4FXVtVvAxcwxucn9fvepmn3l8AXZjfh\n8Omnz5IsBFYCr6+q3wL+dNaDDpE+f8/eDtxeVS8CjgNWtK6WPK5WsfPY2PZa4Mjm6wzgkkGEsBDs\nOQa4s6ruqqrHgc8AJ3WcqXNVdV9VfaNZ/iW9N/eHdZuqe0kWAf8K+HjXWYZBkgOBPwQ+AVBVj1fV\nA92mGgrzgf2SzAcWAP/YcZ5OVNX1wM8mrT4JuKJZvgL4N7MaSqNqt2N1Vd1QVT9vHn6Z3r0bx1W/\n723OBq5iF/ejHDP99NmfA5+tqnsAqmrc+62fPivggOZeqfvTGxO2zm7M4bKLsbHtJOB/Vs+XgYXN\nfWNnlIVgz2HAD1qPt2DB8yRJDgdeDHyl2yRD4WLgPwHbuw4yJI4Afgz8j2a67Meby96Praq6F7gI\nuAe4D/hFVY39p+0th1bVfc3yD4FDuwyjkTHdsfp04JqBJhpuu+2vZvbCGxjQ0YYR1M/v2FHAQUk2\nJfl6kjfNWrrh1E+ffYTerXL+EbgVeFdV+R7qqc1KbWIhqN1Ksj+9TwuXT7rR8dhJ8q+BH1XV17vO\nMkTmAy8BLqmqFwMPM+ZT/Zpz3k6iVyT/M+DpSf59t6mGU/UuXe3lqzWjkvxLeoXge7rOMuQuBt7j\nm/JpmQ/8Lr2ZQa8G3pdkylvA6AmvBibojYdLgY8keUa3kQQWgjvcCyxuPV7UrBt7SfamVwR+qqo+\n23WeIXAs8Pok36M3/eGPknyy20id2wJsqaodR4vX0isMx9kJwN1V9eOq+jXwWeAVHWcaJvfvmOLS\nfB/3qVXqT19jdZLfoTd1/6Tmnovjqp/+WgZ8phnT/gRYmWScp2r302dbgGur6uGq+glwPb1z48dV\nP312Gr3ptFVVd9I7l/f5s5RvVM1KbWIh2HMTcGSSI5qTV08Bru44U+eaudyfAO6oqg91nWcYVNV5\nVbWoqg6n93vyf6pqrI/0VNUPgR8kWdKsOh64vcNIw+Ae4OVJFjR/R8cz5hfQmeRq4M3N8puBz3eY\nRaNjt2N1kufQ++Dl1Kr6TgcZh8lu+6uqjqiqw5sxbS3wtqr6X7MfdWj0837w88DvJ5mfZAHwMsb7\n/3s/fXYPvXGQJIcCS4C7ZjXl6LkaeFNz9dCX0zvF5L7d7TRd82f6CUdRVW1N8g7gWnpX97u8qm7r\nONYwOBY4Fbg1yUSz7vyq2tBhJg2ns4FPNYPAXfQ+/RtbVfWVJGuBb9A7If5mxvTqhUk+Te8qcYck\n2QL8F+BCYE2S04HvA3/WXUKNil2N1UnOarZfCvxn4GB6R7YAtlbVsq4yd6nP/lJLP31WVXck+Vvg\nFnrXCvh4VU15C4Bx0Ofv2QXAqiS3AqE3HfknnYUeArsYG/eGJ/psA/A64E7gEQb0viq90zMkSZIk\nSePCqaGSJEmSNGYsBCVJkiRpzFgISpIkSdKYsRCUJEmSpDFjIShJkiRJY8ZCUBqgJAcnmWi+fpjk\n3mb5gSQzfq+9JMclWT/NfTYl2eny6knekuQjM5dOkqR/4hgpdctCUBqgqvppVS2tqqXApcBfNctL\n6d1/6Ckl8V6fkqQ5yTFS6paFoNSdeUn+OsltSb6QZD944tPHi5N8DXhXkmcluSrJTc3XsU27V7Y+\nSb05yQHN8+6fZG2Sbyf5VJq7Kic5vml3a5LLkzxtcqAkpyX5TpKvAsfOUj9IkjSZY6Q0YBaCUneO\nBD5aVb8FPAD829a2fapqWVWtAD5M71PSlzZtPt60eTfw9ubT0z8AHm3WvxhYDhwNPA84Nsm+wCrg\n5Kr6bWA+8B/aYZI8G/iv9Aa332/2lySpC46R0oBZCErdubuqJprlrwOHt7atbi2fAHwkyQRwNfCM\nJPsDXwI+lOSdwMKq2tq0/2pVbamq7cBE87xLmp/3nabNFcAfTsrzMmBTVf24qh6flEGSpNnkGCkN\nmHOrpe78qrW8Ddiv9fjh1vJewMur6rFJ+1+Y5H8DrwO+lOTVu3he/84lSaPGMVIaMI8ISsPvC8DZ\nOx4kWdp8/+dVdWtV/SVwE/D8p3iOzcDhSf5F8/hU4IuT2nwFeGVzFbe9gT+dqRcgSdKAOEZKvyEL\nQWn4vRNYluSW5nLaZzXrlyf5VpJbgF8D1+zqCZpPSk8D/ibJrfSuxnbppDb3AX8B3EhvSs0dM/1C\nJEmaYY6R0m8oVdV1BkmSJEnSLPKIoCRJkiSNGQtBSZIkSRozFoKSJEmSNGYsBCVJkiRpzFgISpIk\nSdKYsRCUJEmSpDFjIShJkiRJY8ZCUJIkSZLGzP8HBhk0N/lJ4x0AAAAASUVORK5CYII=\n",
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\n",
       "text/plain": [
-       "<matplotlib.figure.Figure at 0x7f1eb30514a8>"
+       "<Figure size 1080x432 with 2 Axes>"
       ]
      },
      "metadata": {},
@@ -1030,7 +1053,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 58,
+   "execution_count": 88,
    "metadata": {
     "collapsed": false
    },
@@ -1039,7 +1062,7 @@
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "0.358\n"
+      "0.639\n"
      ]
     }
    ],
@@ -1049,16 +1072,16 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 59,
+   "execution_count": 89,
    "metadata": {
     "collapsed": false
    },
    "outputs": [
     {
      "data": {
-      "image/png": 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1CwAsIv0jAEtnw4DYWvtfSdb6PaYL1tjmqiRXrVK+P8mZ41QQAOaR/hGAZTTKCCIAAMyM\nqaWTNdyeD1594Qxrwjwa62cuAAAAWF4CIgAAAEkERAAAADoBEQAAgCQC4lxw4DUAADAPnMUUAIC5\n5Et0mD4jiAAAzB3hEGZDQJwTu/fu80EIAADMlIAIAABAEgERAAC2LbPYWElABAAAIImzmAIAMEeM\nZsFsGUEEAAAgiYAIAMCcMHoIsycgAgAAkERABAAAoBMQ54xTDQMA2439n9nT/hwhIAIAAJBEQAQA\nYIaMXMF88TuIAABMnWA4f468Jg9efeGMa8IsGUEEAAAgiYA4txysDQDALNgP3d4ERAAAAJIIiADA\nFjD6ALCYBEQAAACSCIhzzzewAMCysX8D80tABAAAIImACAAAQCcgAgAARzEVeHsSEAEA2HLCBiyG\nHbOuAAAA24OQCPNPQAQAAFY1HOofvPrCGdaEaTHFFAAAgCRGEAEA2EKmlcJiMYIIAABAEgFxIeze\nu8+3bwAAwJYTEAEAAEgiIAIAANAJiAAAbAmHyCwXhz1tDwIiAAAASfzMBQAAE2SECRabEUQAAACS\nCIgAAAB0AiIAADAy04iXm4AIAACMxRlNl5eAuED8IwIAAFtJQFxAgiIAALAV/MwFAADHzJfXsByM\nIAIAAJBEQAQAAKATEAEAOCaml25fXvvlIyAuMP+QAADAJDlJDQAAm+LLalg+RhAXnJ+8AAAAJkVA\nBABgbL6g5ggDFstlw4BYVb9cVY9W1T1DZS+oqpur6v7+98Sh266sqkNVdbCqXjNUfnZV3d1vu6aq\navJPBwCmRx/JdiEAwPYxygjiO5PsWVG2N8ktrbXTk9zSr6eqzkhySZKX9m3eWlXH9W3eluRNSU7v\nl5X3CQCL5p3RR7KNHAmKwiIsrw0DYmvtj5L87xXFFyW5ri9fl+TiofIbWmtPtNYeSHIoyblVdXKS\nE1prt7bWWpLrh7YBgIWkjwRg2Wz2GMSTWmuP9OVPJjmpL+9K8tDQeg/3sl19eWU5ACwbfSQAC+uY\nT1LTv+1sE6jL51XV5VW1v6r2P/bYY5O866VlugfA/Jl0H6l/ZBbsX8D2stmA+Kk+JSb976O9/HCS\nU4fWO6WXHe7LK8tX1Vq7trV2TmvtnJ07d26yigAwE1vWR+ofAdhqmw2INyW5rC9fluTdQ+WXVNWz\nq+q0DA60v61PtXm8qs7rZ2a7dGgbAFgm+sjO7BbYXvy/L4cdG61QVe9Kcn6SF1XVw0n+fZKrk9xY\nVW9M8okkr0uS1tqBqroxyb1JnkxyRWvtqX5Xb87gbG/HJ3lfvwDAwtJHArBsNgyIrbXvW+OmC9ZY\n/6okV61Svj/JmWPVjrEd+ebmwasvnHFNAJafPpJlZjQItqdjPkkNAAAAy0FABAAAIImACAAATIiT\nUy0+AXFJ+ccEAADGJSACAPA0vmiG7WvDs5iyuFZ+uDuzKQAA07B77z77ngtKQAQAwKghkMQUUwAA\nYAs4Yc1iEhABAJbcyp30Izvudt6BlQTEbUQnAACsJCgCwxyDCACwDQiBwCiMIAIAAJBEQAQAAKAT\nELcZxxkAMG36nekabm/9PvPAe3CxCIjbnI4DAAA4QkAEAFhwvuwFJsVZTLcpHQkA03Sk33nw6gtn\nXJPtQT8PbJaACACwgIRAYCsIiCQZdDK+1QWA+bdWMBQYgUlwDCIAALClnBhxcRhB5PMcHwIA88mO\nNTAtRhABAOaYcAhMk4DIUUwBAIDZ0g8Ds2KKKQDADA0f4iEYArNmBJE1GUkEYNL0K0+3Xnvoh1lG\n3tPzT0AEAAAgiSmmjMBvJALAZK02imJkhe1i+L1uH3P+CIgAwFTd+vFPz7oKMyUIAvPMFFNG4jgI\nAABYfgIiAMAE+VIVRuf/Zf6YYspYhk/FDQCMxg4wsCiMIAIAHAM/VQEsEwERAGBMK0PfkSAoDMLm\n+N+ZHwIim+KfGIBjNdyXLGK/slEgXMTnBOAYRDZtZcfnuEQAAFhsAiIAwDr8qDdMh5MhzgcBEQCY\nmbWmmc7rDqJpo7D1du/dN7efAduBgMjErPetj2+EAJgXG/VJixBUAbaKgMjE+XYVgGO1VV8srtVH\nGbGA+WJwYXYERABgbg0Ht7XC3fDt4+xMrvZTFRutA0yXL2+mT0BkqvyTAzCujULaKMFO3wOLy2ji\ndAmIAMDSWG8KKQAbe8asK8D2s9EPCwMAALNhBJGZMV0AAIBROcPwdAiIzJx/dgAAmA+mmDJXTD8F\nAIDZERABAICFYkBh65hiylxab9qpYxcBAGBrGEFk7o0y7dTUVACA7cX+39YwgsjCGPcDwEgjAACM\nR0BkYa0WGH2LBACwvezeu+/zAwLDy2yOKaZsG2sFSqESAAAGjCCy9IYD4FrTTv0WIwDA4hplf4/R\nCIhsS6OMGg5/uPigAQBYPPbhxicgwgorw+Nq30itZ6NA6YMKAGDrOYxocwREmLBxT56z3m3rhUgH\nYQMAjMZ+0+imHhCrak+S/5rkuCRvb61dPe06wLRsNhiOu95q6/gQhMWifwTYWmZxjWaqAbGqjkvy\ni0leleThJB+uqptaa/dOsx6wKDYKh5MIoCv50ITp0z8CTI/RxPVNewTx3CSHWmsfT5KquiHJRUl0\ngDAntnK+/vDxmeNssxpnnmXJ6B8Bpsho4tqmHRB3JXlo6PrDSV4x5ToAM7KZ8LnZKbbzbrUf9F35\nPFYL1GutO3zb8O1OlLQw9I8AM2A08WjVWpveg1V9T5I9rbUf6tffkOQVrbUfXbHe5Uku71dfnOTg\nMT70i5L81THex3agnUajnUajnUajnb7gK1prO2ddiVnYZP94ZpJ7plrR0czre1q9xqNe45vXuqnX\neOa1Xi9urX3xNB5o2iOIh5OcOnT9lF72NK21a5NcO6kHrar9rbVzJnV/y0o7jUY7jUY7jUY70Y3d\nP87re0e9xqNe45nXeiXzWzf1Gs8812taj/WMaT1Q9+Ekp1fVaVX1rCSXJLlpynUAgHmjfwRgLkx1\nBLG19mRV/WiS92dwGu9fbq0dmGYdAGDe6B8BmBdT/x3E1tp7k7x3yg87semqS047jUY7jUY7jUY7\nkWRT/eO8vnfUazzqNZ55rVcyv3VTr/Fs+3pN9SQ1AAAAzK9pH4MIAADAnFrqgFhVe6rqYFUdqqq9\ns67PtFXVqVX1gaq6t6oOVNVbevkLqurmqrq//z1xaJsre3sdrKrXDJWfXVV399uuqaqaxXPaSlV1\nXFX9WVW9p1/XTitU1fOr6jeq6qNVdV9VfYN2OlpV/Xj/n7unqt5VVc/RTmxWDVzT3wd3VdXXrbHe\nH1fVHf3yl1X1P7e4Xuv2saPWe8J1WrXfW7HO9/f63F1Vf1JVL9vqevXHfUv/TDhQVT+2yu1Taa/+\neXRbVd3Z6/IzvXzNz6gV2x/VD0ywbke1UVW9rKr+tL9ev1NVJ6yx7cT2+dZpo+/t1z9XVecMrb+7\nqv7P0P/fL61xv/+5t9tdVfXbVfX8TdRt5DaqqmdV1a/08jur6vw17nOk1/5Y2qjf9rW9ngd6nZ7T\ny6+qqoeq6jPrPN65Q+17Z1V951a3UVX9i/5aHaiqn13n8dbqwyfSRlX13Kra1987B6rq6qH1v6Wq\nPlJVT9bg55LWquP39fu7q6p+t6petNa6SZLW2lJeMjjI/2NJvjLJs5LcmeSMWddrym1wcpKv68tf\nnOTPk5yR5OeS7O3le5P8bF8+o7fTs5Oc1tvvuH7bbUnOS1JJ3pfk22b9/LagvX4iya8neU+/rp2O\nbqPrkvxQX35Wkudrp6PaaFeSB5Ic36/fmOQHtJPLZi9J/nl//au/Hz40wja/meTSLazThn3sZuo9\ngXqt2u+tWOefJDmxL3/blOp15Dcrn5vB+R9+P8k/nkV79fv/or78zCQf6o+36mfUKtsf1Q9sZRtl\ncIbff9rX+cEk/3Ez78cJtdFXZ/D73B9Mcs7Q+ruT3DPC/b46yY6+/LNrtfGk2ijJFUl+pS9/aZLb\nkzxjlfsd6bU/xjbakeSuJC/r11+YL/R152Xwv/uZdR7vuUNtd3KSR49c34o26vX7iyQ7h973F6zy\neOv14RNpo/5cvnXof+6P0/cH+nvva5Ncn+R71mi7Hb29XjT0ev/0eq/vMo8gnpvkUGvt4621zya5\nIclFM67TVLXWHmmtfaQv/12S+zLYeb0ogzd6+t+L+/JFSW5orT3RWnsgyaEk51bVyUlOaK3d2gbv\nrOuHtlkKVXVKkguTvH2oWDsNqaovSfItSd6RJK21z7bW/ibaaTU7khxfVTsy+GD/y2gnNu+iJNe3\ngVuTPL+/P1bVvxl/ZZKtHEEcpY8dq96TsE6/N7zOn7TW/rpfvTWD35zcal+dQeD7h9bak0n+MMl3\nrVhnKu3V7//ISM0z+6Vl7c+oz1unH5iEtdroq5L8UV/n5iTfvcq2E93nW6uNWmv3tdYOHsP9/l5/\nbsnm3nvjttEZSf6gP/ajSf4myWq/77fha7/Kcxm3jV6d5K7W2p19+0+31p7qy7e21h7Z4PH+Yajt\nnpPBe3Y1k2qjr0xyf2vtsb7e72f1996qfXi/v4m0UX8uH+hln03ykfT3TmvtwdbaXUk+t0Z7JIOg\nWkmeV1WV5IQM9kvWtMwBcVeSh4auP5wVncR2UlW7k7w8g28vThr6R/xkkpP68lpttqsvryxfJr+Q\n5Cfz9H8w7fR0pyV5LMmv1GAq7tur6nnRTk/TWjuc5L9k8M3jI0n+trX2e9FObN64/dnFSW5prT0+\n4zrNtB9e0e+t5Y0ZjNpttXuSfHNVvbCqnpvBaOGpK9aZWnvV4JCKOzIYVbi5tbbevsGwtfqBSVir\njQ7kC2Hve3N0uyV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\n",
       "text/plain": [
-       "<matplotlib.figure.Figure at 0x7f1eb3051ba8>"
+       "<Figure size 1080x432 with 2 Axes>"
       ]
      },
      "metadata": {},
@@ -1081,7 +1104,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 60,
+   "execution_count": 90,
    "metadata": {
     "collapsed": true
    },
@@ -1100,7 +1123,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 61,
+   "execution_count": 91,
    "metadata": {
     "collapsed": true
    },
@@ -1111,7 +1134,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 62,
+   "execution_count": 92,
    "metadata": {
     "collapsed": true
    },
@@ -1126,7 +1149,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 63,
+   "execution_count": 93,
    "metadata": {
     "collapsed": true
    },
@@ -1137,7 +1160,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 64,
+   "execution_count": 94,
    "metadata": {
     "collapsed": false
    },
@@ -1146,8 +1169,6 @@
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "lr 1.0\n",
-      "lrt 1.0\n",
       "dec 1.0\n",
       "W1mag 1.0\n",
       "i 1.0\n",
@@ -1166,7 +1187,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 65,
+   "execution_count": 95,
    "metadata": {
     "collapsed": true
    },
@@ -1182,13 +1203,13 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 66,
+   "execution_count": 96,
    "metadata": {
     "collapsed": false
    },
    "outputs": [],
    "source": [
-    "pwl[columns_save].filled().write('lofar_pw_pdf.fits', format=\"fits\")"
+    "pwl[columns_save].filled().write('lofar_pw_lara.fits', format=\"fits\")"
    ]
   },
   {
@@ -1217,7 +1238,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.6.4"
+   "version": "3.6.5"
   }
  },
  "nbformat": 4,