diff --git a/docs/source/nested_samplers/index.rst b/docs/source/nested_samplers/index.rst
index f91f927ed7..076b25d37a 100644
--- a/docs/source/nested_samplers/index.rst
+++ b/docs/source/nested_samplers/index.rst
@@ -7,4 +7,4 @@ Nested samplers
     nested_sampler
     nested_ellipsoid_sampler
     nested_rejection_sampler
-
+    nested_multinest_sampler
diff --git a/docs/source/nested_samplers/nested_multinest_sampler.rst b/docs/source/nested_samplers/nested_multinest_sampler.rst
new file mode 100644
index 0000000000..43e75376a3
--- /dev/null
+++ b/docs/source/nested_samplers/nested_multinest_sampler.rst
@@ -0,0 +1,7 @@
+*****************
+MultiNest sampler
+*****************
+
+.. currentmodule:: pints
+
+.. autoclass:: MultiNestSampler
diff --git a/examples/README.md b/examples/README.md
index f8a937edaf..2e75e3d33e 100644
--- a/examples/README.md
+++ b/examples/README.md
@@ -76,6 +76,7 @@ relevant code.
 
 ### Nested sampling
 - [Ellipsoidal nested sampling](./sampling/nested-ellipsoidal-sampling.ipynb)
+- [MultiNest sampling](./sampling/nested-multinest.ipynb)
 - [Rejection nested sampling](./sampling/nested-rejection-sampling.ipynb)
 
 ### Analysing sampling results
diff --git a/examples/sampling/nested-ellipsoidal-sampling.ipynb b/examples/sampling/nested-ellipsoidal-sampling.ipynb
index a5f0464e2c..ed5ff196b4 100644
--- a/examples/sampling/nested-ellipsoidal-sampling.ipynb
+++ b/examples/sampling/nested-ellipsoidal-sampling.ipynb
@@ -25,9 +25,8 @@
    "outputs": [
     {
      "data": {
-      "image/png": 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Gu/KfdNreZ413lKlsJbnAcrDuOzuptYKcTGhnJxwvX81AE4RSRc2+ldYvVh9/az5/aH3r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\nf9ajMeVaQKDZAAAAAElFTkSuQmCC\n",
       "text/plain": [
-       "<matplotlib.figure.Figure at 0x26de8c2abe0>"
+       "<Figure size 640x480 with 1 Axes>"
       ]
      },
      "metadata": {},
@@ -73,9 +72,7 @@
   {
    "cell_type": "code",
    "execution_count": 2,
-   "metadata": {
-    "collapsed": true
-   },
+   "metadata": {},
    "outputs": [],
    "source": [
     "# Create an object with links to the model and time series\n",
@@ -90,19 +87,20 @@
     "    [0.02, 600, sigma * 1.5])\n",
     "\n",
     "# Create a nested ellipsoidal rejectection sampler\n",
-    "sampler = pints.NestedController(log_likelihood, log_prior, method=pints.NestedEllipsoidSampler)\n",
+    "controller = pints.NestedController(log_likelihood, log_prior,\n",
+    "                                    method=pints.NestedEllipsoidSampler)\n",
     "\n",
     "# Set number of iterations\n",
-    "sampler.set_iterations(8000)\n",
+    "controller.set_iterations(8000)\n",
     "\n",
     "# Set the number of posterior samples to generate\n",
-    "sampler.set_n_posterior_samples(1600)\n",
+    "controller.set_n_posterior_samples(1600)\n",
     "\n",
     "# Do proposals in parallel\n",
-    "sampler.set_parallel(True)\n",
+    "controller.set_parallel(True)\n",
     "\n",
     "# Use dynamic enlargement factor\n",
-    "sampler._sampler.set_dynamic_enlargement_factor(1)"
+    "controller._sampler.set_dynamic_enlargement_factor(1)"
    ]
   },
   {
@@ -126,295 +124,283 @@
       "Total number of iterations: 8000\n",
       "Total number of posterior samples: 1600\n",
       "Iter. Eval. Time m:s Delta_log(z) Acceptance rate\n",
-      "0     1       0:05.6 -inf          1             \n",
-      "0     2       0:05.6 -inf          1             \n",
-      "0     21      0:05.6 -inf          1             \n",
-      "0     41      0:05.7 -inf          1             \n",
-      "0     61      0:05.7 -inf          1             \n",
-      "0     81      0:05.8 -inf          1             \n",
-      "0     101     0:05.8 -inf          1             \n",
-      "0     121     0:05.8 -inf          1             \n",
-      "0     141     0:05.9 -inf          1             \n",
-      "0     161     0:05.9 -inf          1             \n",
-      "0     181     0:06.0 -inf          1             \n",
-      "0     201     0:06.0 -inf          1             \n",
-      "0     221     0:06.1 -inf          1             \n",
-      "0     241     0:06.1 -inf          1             \n",
-      "0     261     0:06.2 -inf          1             \n",
-      "0     281     0:06.2 -inf          1             \n",
-      "0     301     0:06.3 -inf          1             \n",
-      "0     321     0:06.3 -inf          1             \n",
-      "0     341     0:06.4 -inf          1             \n",
-      "0     361     0:06.5 -inf          1             \n",
-      "0     381     0:06.5 -inf          1             \n",
-      "1     404     0:06.6 -inf          0.25          \n",
-      "20    424     0:06.6 -11961.96419  0.833333333   \n",
-      "40    444     0:06.6 -8352.604183  0.909090909   \n",
-      "60    464     0:06.7 -6359.778919  0.9375        \n",
-      "80    488     0:06.7 -5275.768444  0.909090909   \n",
-      "100   520     0:06.8 -4590.47119   0.833333333   \n",
-      "120   544     0:06.8 -4326.757781  0.833333333   \n",
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+      "2020  7552    0:03.5 -55.23597     0.282438479   \n",
+      "2040  7624    0:03.5 -53.88833634  0.282392027   \n",
+      "2060  7648    0:03.5 -54.66614817  0.284216336   \n",
+      "2080  7696    0:03.6 -53.45769117  0.285087719   \n",
+      "2100  7744    0:03.6 -51.98519733  0.285947712   \n",
+      "2120  7768    0:03.6 -51.17825974  0.287730727   \n",
+      "2140  7792    0:03.6 -50.00652823  0.289502165   \n",
+      "2160  7816    0:03.6 -48.85928924  0.291262136   \n",
+      "2180  7840    0:03.7 -47.60709827  0.293010753   \n",
+      "2200  7888    0:03.7 -46.36975578  0.293803419   \n",
+      "2220  7936    0:03.7 -45.36400819  0.294585987   \n",
+      "2240  7960    0:03.7 -44.40379443  0.296296296   \n",
+      "2260  8008    0:03.8 -43.37884559  0.297055731   \n",
+      "2280  8032    0:03.8 -42.37863     0.298742138   \n",
+      "2300  8080    0:03.8 -41.28009682  0.299479167   \n",
+      "2320  8128    0:03.8 -40.17353108  0.300207039   \n",
+      "2340  8176    0:03.8 -39.14941559  0.300925926   \n",
+      "2360  8224    0:03.9 -38.19518844  0.30163599182 \n",
+      "2380  8296    0:03.9 -37.25561755  0.30141844    \n",
+      "2400  8344    0:03.9 -36.40634374  0.302114804   \n",
+      "2420  8392    0:03.9 -35.60994144  0.302802803   \n",
+      "2440  8464    0:04.0 -34.87512373  0.302579365   \n",
+      "2460  8536    0:04.0 -34.16634369  0.302359882   \n",
+      "2480  8608    0:04.0 -33.3955272   0.30214425    \n",
+      "2500  8704    0:04.1 -32.61374645  0.30105973    \n",
+      "2520  8800    0:04.1 -31.7605235   0.3           \n",
+      "2540  8896    0:04.1 -30.95834595  0.298964218   \n",
+      "2560  8968    0:04.1 -30.1417354   0.298786181   \n",
+      "2580  9064    0:04.2 -29.42320848  0.297783933518\n",
+      "2600  9160    0:04.2 -28.75689739  0.296803652968\n",
+      "2620  9280    0:04.2 -28.07536486  0.295045045045\n",
+      "2640  9352    0:04.3 -27.26312631  0.294906166   \n",
+      "2660  9472    0:04.3 -26.55106143  0.293209877   \n",
+      "2680  9592    0:04.4 -25.87066475  0.291557876   \n",
+      "2700  9688    0:04.4 -25.19214443  0.290697674   \n",
+      "2720  9784    0:04.4 -24.55372365  0.289855072   \n",
+      "2740  9952    0:04.5 -23.96427412  0.286850921273\n",
+      "2760  10072   0:04.5 -23.42173159  0.285359801   \n",
+      "2780  10216   0:04.5 -22.84380605  0.283211084   \n"
      ]
     },
     {
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "2840  6448    0:30.4 -27.47903096  0.46957672    \n",
-      "2860  6496    0:30.5 -26.70709881  0.469160105   \n",
-      "2880  6532    0:31.0 -25.93762189  0.469667319   \n",
-      "2900  6576    0:31.0 -25.27702144  0.469559585   \n",
-      "2920  6596    0:31.1 -24.61540232  0.471271788   \n",
-      "2940  6620    0:31.1 -24.0467441   0.47266881    \n",
-      "2960  6644    0:31.2 -23.48313358  0.474055093   \n",
-      "2980  6668    0:31.2 -22.93188037  0.475430759   \n",
-      "3000  6692    0:31.3 -22.39463485  0.476795931   \n",
-      "3020  6720    0:31.3 -21.89199034  0.477848101   \n",
-      "3040  6748    0:31.3 -21.38515542  0.478890989288\n",
-      "3060  6780    0:31.4 -20.8674129   0.479623824   \n",
-      "3080  6808    0:31.4 -20.37271826  0.480649189   \n",
-      "3100  6836    0:31.5 -19.84836779  0.481665631   \n",
-      "3120  6876    0:31.6 -19.29009278  0.481778876   \n",
-      "3140  6904    0:31.6 -18.73268854  0.482779828   \n",
-      "3160  6948    0:31.7 -18.1433521   0.482590104   \n",
-      "3180  6988    0:31.7 -17.54468311  0.482695811   \n",
-      "3200  7036    0:32.6 -16.94597411  0.482218204   \n",
-      "3220  7060    0:32.6 -16.43274182  0.483483483   \n",
-      "3240  7084    0:32.7 -15.98274995  0.484739677   \n",
-      "3260  7108    0:32.7 -15.56086098  0.485986881   \n",
-      "3280  7140    0:32.8 -15.26496322  0.486646884273\n",
-      "3300  7180    0:32.8 -14.90929632  0.486725664   \n",
-      "3320  7220    0:32.9 -14.56597025  0.486803519   \n",
-      "3340  7252    0:32.9 -14.2088416   0.48744892    \n",
-      "3360  7292    0:33.0 -13.83524883  0.487521764   \n",
-      "3380  7332    0:33.1 -13.45993124  0.487593768   \n",
-      "3400  7372    0:33.1 -13.08426307  0.487664945   \n",
-      "3420  7400    0:33.2 -12.67106451  0.488571429   \n",
-      "3440  7428    0:33.2 -12.27595072  0.489470689   \n",
-      "3460  7452    0:33.3 -11.91206828  0.490640953   \n",
-      "3480  7484    0:33.3 -11.55856633  0.491247883   \n",
-      "3500  7516    0:33.4 -11.19961339  0.491849354   \n",
-      "3520  7548    0:33.4 -10.83760494  0.492445439   \n",
-      "3540  7584    0:34.0 -10.4824231   0.492761693   \n",
-      "3560  7624    0:34.0 -10.36336527  0.492801772   \n",
-      "3580  7656    0:34.1 -10.0575758   0.493384785   \n",
-      "3600  7692    0:34.1 -9.776437933  0.493691717   \n",
-      "3620  7716    0:34.2 -9.517409977  0.494805904866\n",
-      "3640  7740    0:34.2 -9.276152848  0.495912807   \n",
-      "3660  7768    0:34.3 -9.039111206  0.496742671   \n",
-      "3680  7800    0:34.4 -8.798967429  0.497297297   \n",
-      "3700  7836    0:34.4 -8.552023806  0.497579344   \n",
-      "3720  7864    0:34.5 -8.29645501   0.498392283   \n",
-      "3740  7892    0:34.5 -8.04755083   0.499199146   \n",
-      "3760  7920    0:34.6 -7.807561001  0.5           \n",
-      "3780  7964    0:34.6 -7.56765474   0.49973559    \n",
-      "3800  8004    0:35.4 -7.335283629  0.499736981   \n",
-      "3820  8028    0:35.5 -7.11477005   0.500786576   \n",
-      "3840  8056    0:35.5 -6.900830111  0.501567398   \n",
-      "3860  8080    0:35.5 -6.689921705  0.502604167   \n",
-      "3880  8108    0:35.6 -6.487720734  0.503373119   \n",
-      "3900  8144    0:35.7 -6.29099825   0.503615702   \n",
-      "3920  8172    0:35.7 -6.094812697  0.504374678   \n",
-      "3940  8208    0:35.8 -5.905216015  0.504610656   \n",
-      "3960  8236    0:35.8 -5.72046549   0.505359877   \n",
-      "3980  8260    0:35.9 -5.538291728  0.506361323   \n",
-      "4000  8292    0:35.9 -5.361538973  0.506842372   \n",
-      "4020  8324    0:36.0 -5.183169443  0.507319536   \n",
-      "4040  8356    0:36.0 -5.005499661  0.507792860734\n",
-      "4060  8384    0:36.1 -4.8302518    0.508517034   \n",
-      "4080  8432    0:36.1 -4.661826     0.50796812749 \n",
-      "4100  8468    0:36.2 -4.499569064  0.508180466   \n",
-      "4120  8512    0:37.2 -4.341571823  0.507889546   \n",
-      "4140  8552    0:37.2 -4.18961608   0.507850834   \n",
-      "4160  8600    0:37.3 -4.041397337  0.507317073   \n",
-      "4180  8652    0:37.4 -3.897877916  0.506543868   \n",
-      "4200  8700    0:37.4 -3.759561273  0.506024096   \n",
-      "4220  8752    0:37.5 -3.62655309   0.505268199   \n",
-      "4240  8836    0:37.6 -3.495091471  0.502607871   \n",
-      "4260  8892    0:37.6 -3.367122903  0.50164861    \n",
-      "4280  8960    0:37.7 -3.243861381  0.5           \n",
-      "4300  9012    0:38.6 -3.123581891  0.499303298   \n",
-      "4320  9036    0:38.6 -3.005269354  0.500231589   \n",
-      "4340  9064    0:38.6 -2.891499668  0.500923361   \n",
-      "4360  9088    0:38.7 -2.782204296  0.501841621   \n",
-      "4380  9116    0:38.7 -2.675514353  0.502524094   \n",
-      "4400  9140    0:38.8 -2.570142208  0.503432494   \n",
-      "4420  9176    0:38.8 -2.467872788  0.503646308113\n",
-      "4440  9212    0:38.9 -2.369097611  0.503858375   \n",
-      "4460  9248    0:38.9 -2.274235917  0.504068716094\n",
-      "4480  9284    0:39.0 -2.182427352  0.504277353   \n",
-      "4500  9328    0:39.1 -2.092884827  0.504032258   \n",
-      "4520  9348    0:39.1 -2.005826719  0.505140814   \n",
-      "4540  9376    0:39.1 -1.921487903  0.505793226   \n",
-      "4560  9404    0:39.2 -1.839416046  0.506441582   \n",
-      "4580  9428    0:39.2 -1.766283029  0.507310589   \n",
-      "4600  9464    0:39.3 -1.68907854   0.507502207   \n",
-      "4620  9484    0:39.3 -1.625758745  0.508586526   \n",
-      "4640  9512    0:39.4 -1.552340948  0.509218613   \n",
-      "4660  9536    0:39.9 -1.481584005  0.510070053   \n",
-      "4680  9564    0:39.9 -1.413641665  0.51069402    \n",
-      "4700  9596    0:40.0 -1.348443856  0.511091779   \n",
-      "4720  9620    0:40.0 -1.285759203  0.511930586   \n",
-      "4740  9652    0:40.1 -1.225563026  0.51232166    \n",
-      "4760  9692    0:40.1 -1.167871931  0.512268618   \n",
-      "4780  9732    0:40.2 -1.11271321   0.512216031   \n",
-      "4800  9772    0:40.3 -1.059999624  0.512163892   \n",
-      "4820  9796    0:40.3 -1.009452042  0.512984249   \n",
-      "4840  9824    0:40.4 -0.960922     0.513582343   \n",
-      "4860  9844    0:40.4 -0.914457     0.514612452   \n",
-      "4880  9872    0:40.5 -0.870034     0.515202703   \n",
-      "4900  9900    0:40.5 -0.827619     0.515789474   \n",
-      "4920  9920    0:40.6 -0.787142     0.516806723   \n",
-      "4940  9952    0:40.6 -0.748524     0.517169179   \n",
-      "4960  9984    0:40.6 -0.711621     0.517529215   \n",
-      "4980  10016   0:40.7 -0.676434     0.517886855   \n",
-      "5000  10044   0:40.7 -0.642811     0.518457072   \n",
-      "5020  10080   0:40.8 -0.610705     0.518595041   \n",
-      "5040  10128   0:40.8 -0.580168     0.518092105   \n",
-      "5060  10176   0:40.9 -0.551077     0.517594108   \n",
-      "5080  10212   0:40.9 -0.524139     0.517733388   \n",
-      "Convergence obtained with Delta_z = -0.4989821806669852\n",
+      "2800  10408   0:04.6 -22.09995184  0.279776179   \n",
+      "2820  10648   0:04.7 -21.41645945  0.275175644   \n",
+      "2840  10888   0:04.7 -20.78000114  0.27078566    \n",
+      "2860  11032   0:04.8 -20.1637183   0.268999248   \n",
+      "2880  11248   0:04.8 -19.5526662   0.265486726   \n",
+      "2900  11488   0:04.9 -18.97763979  0.261544011544\n",
+      "2920  11512   0:04.9 -18.44690078  0.262778978   \n",
+      "2940  11536   0:04.9 -17.96067126  0.264008621   \n",
+      "2960  11560   0:04.9 -17.47690226  0.265232975   \n",
+      "2980  11584   0:05.0 -17.02573917  0.266452074392\n",
+      "3000  11632   0:05.0 -16.56928077  0.267094017094\n",
+      "3020  11656   0:05.0 -16.05887861  0.26830135    \n",
+      "3040  11704   0:05.0 -15.59176215  0.268931352   \n",
+      "3060  11728   0:05.0 -15.15365307  0.270127119   \n",
+      "3080  11776   0:05.1 -14.74566629  0.270745429   \n",
+      "3100  11824   0:05.1 -14.35002456  0.271358543   \n",
+      "3120  11872   0:05.1 -13.94509984  0.271966527   \n",
+      "3140  11920   0:05.1 -13.53108802  0.272569444   \n",
+      "3160  11968   0:05.2 -13.10397468  0.273167358   \n",
+      "3180  12040   0:05.5 -12.68366924  0.273195876   \n",
+      "3200  12088   0:05.5 -12.27565596  0.273785079   \n",
+      "3220  12160   0:05.6 -11.90813289  0.273809524   \n",
+      "3240  12232   0:05.6 -11.57460592  0.273833671   \n",
+      "3260  12304   0:05.6 -11.26359059  0.273857527   \n",
+      "3280  12352   0:05.7 -10.95230794  0.274431058   \n",
+      "3300  12448   0:05.7 -10.63986426  0.273904382   \n",
+      "3320  12520   0:05.7 -10.3084927   0.273927393   \n",
+      "3340  12640   0:05.8 -9.982245527  0.272875817   \n",
+      "3360  12760   0:05.8 -9.665141923  0.27184466    \n",
+      "3380  12856   0:05.8 -9.363992994  0.27135517    \n",
+      "3400  13000   0:05.9 -9.077547011  0.26984127    \n",
+      "3420  13024   0:05.9 -8.800253657  0.270912548   \n",
+      "3440  13048   0:05.9 -8.519722373  0.27197976    \n",
+      "3460  13072   0:05.9 -8.247647886  0.273042929   \n",
+      "3480  13120   0:06.0 -7.984743749  0.273584906   \n",
+      "3500  13144   0:06.0 -7.733175907  0.274639046   \n",
+      "3520  13168   0:06.0 -7.483880226  0.275689223   \n",
+      "3540  13192   0:06.0 -7.254079353  0.27673546    \n",
+      "3560  13216   0:06.0 -7.041901551  0.277777778   \n",
+      "3580  13288   0:06.1 -6.836967371  0.277777778   \n",
+      "3600  13312   0:06.1 -6.629032166  0.278810409   \n",
+      "3620  13360   0:06.1 -6.426446653  0.279320988   \n",
+      "3640  13408   0:06.1 -6.225515828  0.279827798278\n",
+      "3660  13456   0:06.2 -6.031947439  0.280330882   \n",
+      "3680  13504   0:06.2 -5.843808341  0.280830281   \n",
+      "3700  13552   0:06.2 -5.787320962  0.281326034   \n",
+      "3720  13600   0:06.2 -5.61894694   0.281818182   \n",
+      "3740  13648   0:06.3 -5.456057773  0.282306763285\n",
+      "3760  13696   0:06.3 -5.296345372  0.282791817   \n",
+      "3780  13744   0:06.3 -5.137836688  0.283273381295\n",
+      "3800  13792   0:06.3 -4.981586905  0.283751493   \n",
+      "3820  13864   0:06.4 -4.826679516  0.283719548   \n",
+      "3840  13912   0:06.4 -4.676516155  0.284191829   \n",
+      "3860  13984   0:06.4 -4.52872951   0.284157833   \n",
+      "3880  14032   0:06.4 -4.378514312  0.284624413   \n",
+      "3900  14128   0:06.5 -4.229306577  0.284090909   \n",
+      "3920  14200   0:06.5 -4.08070624   0.284057971   \n",
+      "3940  14296   0:06.5 -3.93405467   0.283534830167\n",
+      "3960  14392   0:06.6 -3.792094172  0.283018868   \n",
+      "3980  14464   0:06.6 -3.653519387  0.282992036405\n",
+      "4000  14560   0:06.6 -3.518837665  0.282485876   \n",
+      "4020  14704   0:06.7 -3.38983364   0.281040268   \n",
+      "4040  14824   0:06.7 -3.264060202  0.280088741   \n",
+      "4060  14896   0:06.7 -3.141193572  0.280077263   \n",
+      "4080  15040   0:06.8 -3.018934061  0.278688525   \n",
+      "4100  15160   0:06.8 -2.899261397  0.277777778   \n",
+      "4120  15304   0:06.9 -2.783967384  0.276435856146\n",
+      "4140  15472   0:06.9 -2.672989351  0.274681529   \n",
+      "4160  15664   0:07.0 -2.564737245  0.272536687631\n",
+      "4180  15808   0:07.0 -2.459201609  0.271287642783\n",
+      "4200  15976   0:07.1 -2.357441004  0.269645609   \n",
+      "4220  16144   0:07.1 -2.258938054  0.268038618   \n",
+      "4240  16312   0:07.2 -2.16333826   0.266465561   \n",
+      "4260  16408   0:07.2 -2.071096406  0.266116942   \n",
+      "4280  16624   0:07.3 -1.982445048  0.263806706   \n",
+      "4300  16840   0:07.3 -1.896223859  0.261557178   \n",
+      "4320  16864   0:07.3 -1.81305814   0.262390671   \n",
+      "4340  16888   0:07.4 -1.732327649  0.263221737   \n",
+      "4360  16912   0:07.4 -1.654376338  0.264050388   \n",
+      "4380  16936   0:07.4 -1.606478796  0.264876633   \n",
+      "4400  16960   0:07.4 -1.534327053  0.265700483   \n",
+      "4420  16984   0:07.4 -1.464710995  0.266521949   \n",
+      "4440  17032   0:07.5 -1.397420719  0.266955267   \n",
+      "4460  17080   0:07.5 -1.332990582  0.267386091   \n",
+      "4480  17104   0:07.5 -1.270724455  0.268199234   \n",
+      "4500  17152   0:07.5 -1.210489818  0.268624642   \n",
+      "4520  17200   0:07.6 -1.152744424  0.269047619   \n",
+      "4540  17224   0:07.6 -1.097437572  0.269852592   \n",
+      "4560  17296   0:07.6 -1.044385639  0.269886364   \n",
+      "4580  17320   0:07.6 -0.993696     0.270685579   \n",
+      "4600  17368   0:07.6 -0.945292     0.271098538   \n",
+      "4620  17440   0:07.7 -0.899011     0.271126761   \n",
+      "4640  17512   0:07.7 -0.854709     0.271154745208\n",
+      "4660  17584   0:07.7 -0.812413     0.271182495   \n",
+      "4680  17656   0:07.8 -0.77206      0.271210014   \n",
+      "4700  17728   0:07.8 -0.733482     0.271237304   \n",
+      "4720  17824   0:07.8 -0.696646     0.270890725   \n",
+      "4740  17944   0:07.9 -0.661566     0.270177839   \n",
+      "4760  18016   0:07.9 -0.628182     0.270208901   \n",
+      "4780  18088   0:07.9 -0.596343     0.270239711   \n",
+      "4800  18184   0:08.0 -0.566022     0.269905533   \n",
+      "4820  18208   0:08.0 -0.537168     0.27066487    \n",
+      "4840  18232   0:08.0 -0.509791     0.271422162   \n",
+      "Convergence obtained with Delta_z = -0.4992372601682291\n",
       "Done!\n"
      ]
     }
    ],
    "source": [
-    "samples = sampler.run()\n",
+    "samples = controller.run()\n",
     "print('Done!')"
    ]
   },
@@ -432,12 +418,14 @@
    "outputs": [
     {
      "data": {
-      "image/png": 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EgEYFMTMzq5S3Lz4zM7OGcoEyM7NSqmZEXTNrMuP/6YqiI5j1mguUNQ0P6V69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\nnrLOiwAAAABJRU5ErkJggg==\n",
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\n",
       "text/plain": [
-       "<matplotlib.figure.Figure at 0x26df2a39e80>"
+       "<Figure size 432x432 with 3 Axes>"
       ]
      },
-     "metadata": {},
+     "metadata": {
+      "needs_background": "light"
+     },
      "output_type": "display_data"
     }
    ],
@@ -464,12 +452,14 @@
    "outputs": [
     {
      "data": {
-      "image/png": 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pxMbG8v7773P11VdTVVUFwDPPPEPnzp2POI7OnTtz3XXXUVxcjNaav//970RG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\nHui9v8X7eHJTxSbE6eytn9c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7jkAZjBgCg0m46RVWPjmKqJDAZo5eCCHE0TjRCc4upVS8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\nVOs5FEd0WtNQPoyOaTne6fo8xg5J2/4NAoMR8XQ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\n",
       "text/plain": [
-       "<matplotlib.figure.Figure at 0x26df3d27160>"
+       "<Figure size 576x216 with 1 Axes>"
       ]
      },
-     "metadata": {},
+     "metadata": {
+      "needs_background": "light"
+     },
      "output_type": "display_data"
     }
    ],
@@ -494,13 +484,13 @@
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "marginal log-likelihood = -375.348895962891 ± 0.07908966826933428\n"
+      "marginal log-likelihood = -382.18988862037673 ± 0.0783612067991932\n"
      ]
     }
    ],
    "source": [
-    "print('marginal log-likelihood = ' + str(sampler.marginal_log_likelihood())\n",
-    "      + ' ± ' + str(sampler.marginal_log_likelihood_standard_deviation()))"
+    "print('marginal log-likelihood = ' + str(controller.marginal_log_likelihood())\n",
+    "      + ' ± ' + str(controller.marginal_log_likelihood_standard_deviation()))"
    ]
   },
   {
@@ -519,12 +509,12 @@
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "effective sample size = 1597.4248390822784\n"
+      "effective sample size = 1578.7847256966925\n"
      ]
     }
    ],
    "source": [
-    "print('effective sample size = ' + str(sampler.effective_sample_size()))"
+    "print('effective sample size = ' + str(controller.effective_sample_size()))"
    ]
   }
  ],
@@ -544,7 +534,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.6.3"
+   "version": "3.9.2"
   }
  },
  "nbformat": 4,
diff --git a/examples/sampling/nested-multinest.ipynb b/examples/sampling/nested-multinest.ipynb
new file mode 100644
index 0000000000..da02fddd3e
--- /dev/null
+++ b/examples/sampling/nested-multinest.ipynb
@@ -0,0 +1,1330 @@
+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "# MultiNest sampling\n",
+    "\n",
+    "This example demonstrates how to use MultiNest sampling [1] to sample from the posterior distribution for a logistic model fitted to model-simulated data.\n",
+    "\n",
+    "[1] \"MultiNest: an efficient and robust Bayesian inference tool for cosmology and particle physics.\"\n",
+    "Feroz, F., M. P. Hobson, and M. Bridges. Monthly Notices of the Royal Astronomical Society 398.4 (2009): 1601-1614."
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "MultiNest works similarly to [ellipsoidal nested sampling](nested-ellipsoidal-sampling.ipynb) by proposing points using the prior but constraining the proposals such that they lie within ellipsoids of known high density. A key difference is that MultiNest uses (potentially) many ellipsoids to generate proposals, unlike ellipsoidal nested sampling, which uses only a single ellipsoid."
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Ellipsoids and ellipsoid trees"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "We illustrate this using the `Ellipsoid()` and `EllipsoidTree()` classes in PINTS. Whilst users do not need these to perform inference, we use them here to visualise the ellipses generated by fitting to two-dimensional data.\n",
+    "\n",
+    "We first generate some sample data which we'll fit bounding ellipses to."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 1,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "import pints\n",
+    "import pints.toy as toy\n",
+    "import numpy as np\n",
+    "import matplotlib.pyplot as plt"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "We'll first draw some data from the [AnnulusLogPDF](../toy/http://localhost:8888/notebooks/pints/examples/toy/distribution-annulus.ipynb) example. Note that the ellipsoid tree methods work only within the unit cube, so we transform all points to lie within the [0,1]^2 range."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 432x288 with 1 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "n = 400\n",
+    "log_pdf = pints.toy.AnnulusLogPDF()\n",
+    "draws = log_pdf.sample(n)\n",
+    "gaussian = pints.MultivariateGaussianLogPrior([0, 0], [[100, 0], [0, 100]])\n",
+    "draws = [gaussian.convert_to_unit_cube(x) for x in draws]\n",
+    "draws = np.vstack(draws)\n",
+    "\n",
+    "plt.scatter(draws[:, 0], draws[:, 1])\n",
+    "plt.show()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Now we'll fit an ellipsoid tree to the data, which provides an ellipsoidal decomposition of the domain covered by the sample draws."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 3,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "from pints._nested.__init__ import Ellipsoid\n",
+    "from pints._nested._multinest import EllipsoidTree\n",
+    "\n",
+    "iteration = 600 # this number can be ignored for understanding this method for now\n",
+    "ellipsoid_tree = EllipsoidTree(draws, iteration)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Now plotting the ellipsoids (here, because the domain is 2D, these are actually ellipses) resultant from the spatial decomposition."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 4,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 432x288 with 1 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "def plot_2d_ellipsoid(ellipsoid):\n",
+    "    A = ellipsoid.weight_matrix()\n",
+    "    c = ellipsoid.centroid()\n",
+    "\n",
+    "    U, D, V = np.linalg.svd(A)\n",
+    "\n",
+    "    # major and minor axes\n",
+    "    a = 1 / np.sqrt(D[0])\n",
+    "    b = 1 / np.sqrt(D[1])\n",
+    "\n",
+    "    # generate x and y\n",
+    "    theta = np.linspace(0, 2 * np.pi, 1000)\n",
+    "    state_1 = a * np.cos(theta)\n",
+    "    state_2 = b * np.sin(theta)\n",
+    "    state = np.vstack((state_1, state_2))\n",
+    "    z = np.matmul(V, state)\n",
+    "    x = z[0, :] + c[0]\n",
+    "    y = z[1, :] + c[1]\n",
+    "\n",
+    "    plt.plot(x, y)\n",
+    "\n",
+    "def plot_2d_ellipsoid_tree_leaves(ellipsoid_tree):\n",
+    "    ellipsoids = ellipsoid_tree.leaf_ellipsoids()\n",
+    "    for ellipsoid in ellipsoids:\n",
+    "        plot_2d_ellipsoid(ellipsoid)\n",
+    "        \n",
+    "plot_2d_ellipsoid_tree_leaves(ellipsoid_tree)\n",
+    "plt.scatter(draws[:, 0], draws[:, 1])\n",
+    "plt.show()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "This ellipsoidal decomposition in stochastic: each replicate can yield a different decomposition."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 5,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 432x288 with 1 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 432x288 with 1 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 432x288 with 1 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 432x288 with 1 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "nreps = 4\n",
+    "for i in range(nreps):\n",
+    "    ellipsoid_tree = EllipsoidTree(draws, iteration)\n",
+    "\n",
+    "    plot_2d_ellipsoid_tree_leaves(ellipsoid_tree)\n",
+    "    plt.scatter(draws[:, 0], draws[:, 1])\n",
+    "    plt.show()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "In MultiNest, this ellipsoidal decomposition would be used to generate proposals which have an improved change of being accepted as part of a nested sampling algorithm. In PINTS' implementation of the ellipsoidal tree, we can sample uniformly within these ellipsoid set. This accounts for the overlap in the ellipses to ensure uniform sampling within the set."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 6,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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wFShlDWVc9fLV+BvOwVMxk8gwyii/gAmJzC8hzTlh9uotdvj3dO7X7uVZkxoyqXAyGnp7fqMblPd5THuKI7ITPwl8i4+M4VH7rcw2seazWHPRD5b/gFUVa7AdfpAjdbq5rb/2AGx7FTY8D1XbT2y/exvkpQuGnSrSGvppyqLSch57cwcV9Z4Ove4UZSO32d5hd7+vMmD4jQDtjpBIhNuv47ApaKowtelePbI743oVWDoAzWzNz25/FqSCt3I6sTHxyZIbE2nHoX1Wx5TXuZnyvM5SmcFoYyvP0naBbhWtkirJfiOnpuKwKeFV3BXKJ/ze/lc+1IfxHf/dNBEfnRL7q7j9Os+vLovzJbj9Ove8uJG752/Alanh1XqjFq2gxbcTSf+o2jTh3y2/d7Cuz3k/gAMfwn+uBsD/+AheCkzhSX0Gzc6isMkrzakn3YLuM+LWv3/MXfM3tEmYF7ucuJzmCSAup0axy4mKwUOO52jM6s2AW34T3j972iCcmmp67slQ7/Yz76aRZNnjr71wXTkAK+dczP6501k55+KkA3tlxUoCzQOQek7cvrokZo8ilzPpPqtjBHCo3sch2ZU831GL9KpoNFWEfw9ViHB44KLS8hTOjsfsNwo9R7HLyaM3jOCha4fh1FS6U83vtP9jvdGfb+s/oUWkHmpoFa2kS4kkaNZxN3cFQLHXhPeHPl8cQkCfC1h03TYu8v2J5wMXc4P6Ie/Y7+Vbvmf4xUsft/s7SdM20gL9M+CWv33Eyr01yQ+MIBR+FxrQkTg1lYeuHcbKORez9yuCvrKMnCsfAO2EHXjG6GIevWEEagfX8ChyOZkxuhhXZnwKuaUASMDR5qNkim6W97JiUWk5Nc3W1SbK69xMnrucqYMLTYVmSMS5sZOBD0l8zqyqiPA2VQjG984PrxoiKyje9/LmpAJsUWk5k+cup8+cJUyeu5xFpeXh36jY5UQQ/M0fnzmKA3OnM3VwIfe8uJG75m/A49e5x/EyNgzuV+7CJzTThKWT+aWFEkxWkzL6uyqvc9N7zhJ6z1nCkJ+/EfU55y3byQGjMw8EvsYU7+O8bkzke7bFvGX7EWuW/vskniZNqqQF+qfM79/ayar9tW0+L3LJGzvoo0LlNr0AWV1gyHXhc0PC4+75G1KqlQLJzRsQbWJIpVRuKmRpWYzoaTedtKzMGSeiQxL7IMrr3MxfU0akISI/U4sySxTQQB1Bx56E8Pecn6mhRJypS8nKvTWm/oOQ+SJSWJs9b3lrBmvkJDBjdHHciub+RZt5dtWh8G/nwMuVfMTmTldQn1Fsau5SheDWiSXtXpWpWXsBMDzWKyq33+BH8zeEP1/kb11JAff4v8u13l9yRBbwK/9j8NI3oKVtikyatpEW6J8SHr/Or5Zs40/L97T7GpEZf6ZmDCmDtsyB00ANukdihUeqJJP7qhDcOLY4fG8r7VkRwlSgxWqnIUZ0HkG5byO/un6o9aQVQ1uyUv26jBL8Hr9BfmbQbJJHE32USrYZvYATDs79c6eTabclDVmMJGS+MNPYzZ430Wrm+dVlUf8fKg6SJbw8VTnQcsLUpWTFjirGlOQlfE4B8as24cde8CG6pwjD2zXh+Ubr5wFwZcabAzfJftzg+wV/t82CbYvgbxfCkU0Jr5mm/aQF+qfA7spGrn3iQ/7+wf6TvlYijfeNVRvBXcuDnyhhQXkyKfiJ0KVk4brysKCystHrUkYJtETaKcD1/a/naPNR9OzVKdveTyZU0O3X8fh1BHCFugaAj4zhcSuCk71HpLBu62omdlXVXQS13ANGl4RmqPI6d0LTXrHLyf650/ndzSOjfjtHl6Uo9mq8lVeSiuEm9NxWSkAAG4XTfw5ffwuMAPzjcti6KOl107SdtEA/xby07jDXPrGS6iYf//n6eIoTDMBUMNOCICgo/7Q02Jy4TmaFBWWiqAlT7awNRAqqRDb6yOOSaacN1YNQvf34xcq5TPztsyk50xIJtdQ+h4HA4Kvqm+w2itko+0WtPiBY5+ZkiBTWVs9rtT32Ow3JTZuQJ+XsDk1Yod+uyJWBvdMK7AUfI+ovxGgZQLHLGV7BWBF6bqs6QKF70GMsfPs96H4OvPQ12PBcu567I3DrBsd9Aap8fgKfdvH7U0g6bPEU0eIL8MCrW3lp3WEm9i3gj7eMpmtuBrOnDeKu+RvafV0p45OQQgPO4beBCtkiGDnj9uuWNVhC5oQ+c5a0+1kgWlDNGF3M3RafLVnYYEWdm0Wl5fz0lS145Ewy+/yZxvwnue91P3B5Qg09Ua2WVLlRfZ8hShnf992JRLBiR1V436LScpp98fVtzLCqhqgIQZ85S8IVJM3iwK18BLMm9OTZVYfC/y+TXQD40sDg7++wKe367JHf6VXnFLLV+29e2LmMq/pcxYTsO/jdW3uoqHNbKhEhQs9tFXYZpcRkd4EvvQIv3AqLvhtsKj4yPjPXjHq3n9pmHw2eoBB22BSy7Da65QUriSZiR7Obt4838EFtIzuaPRyL+T2LHRpak5+K3XWISjc2v4yqzXOmkBboHUhkHQ6bItANyQ8uGcAPLxmAqgS1rBmji00bPqRKndsfVyAqdC2FfNzSzgBxOLxPlxKnploKj5ONT48d7FbXk0DvBJNHkcsZob3n4j74LZwlT6MWP8mv36tmxuh7Lc9Nli2ajB6iip/bnuETYxCvGxOB6H6m85btTFqrRhHwxQklvL7xiGm2b2QUzMJ15dw4tjiujAIEk6NiY/bH9SrglfXlNPuCv+Eu2QOv4mSS3MSVLw9s90QWcsLurt3Nzz78GdtrtvOVoV+hrzqTn72yNXzdRO9qfqYW/v7NJlbTicqeBbNegP/eBIvvhLwe0Du6dG+jx88n+2tYta+ajYfr2XusybRMdIhuuRkML85jXO98ArrBc6sPUVHvIbdfHtmDXOzTgwJ8aFYGUwty6et0kG0LGihq/AFe2XWM/YEAcqgLhuThr/Tw/7YfATijhHpKAl0IcQXwR4Idi56WUs6N2V8C/AdwtR4zR0q5tGMf9fQmtg5HwJDYVYW+nbPCwjzEg9cMM9UoFYJOpmRYOecMFD42hnKxUsov+DISJey8XLLpSHhgOmwnLG2JtFtNEWRn2BIO6Fjlvz3acmjQR2r3hq8LLQe+h7P4Odz5/+G+D6r50dgfUZhZmPBaAlLufFTsctJYX83ftd8B8CP/98LlhCPNHKnYz79oUrzMCrdfZ8WOqrjOTmZNphesPcRHe2uitH4fdnbknU+fg0tR/dPAJKEohKYIy/flsbdK2el/lud3PE+OPYc/Tf0TU0umMnnuctPPYZZ1+uA1w8L/Nyv3a1VJEi0DZj4DT1+G5/kvM833GAfdwTBbmyKQgN46hoYX5zKgSzb1B2ujzCN2VeGmsT3ompvBwepmNpTV8b/twRaEUhXovbI41juT4w0evtApj/vH9KarQwt/36HndGVq1Lb4sQMy24ZelIneIwtfNyf/OtLIHV4f3R1nRmenVHqKqgR7il4GHCbYU3SWlHJbxDFPAaVSyv8TQgwFlkopeye67tmW+p9qQ+QQZkW4FBEcMFIGwwYF1g0RrLha+Zgn7H/mdt/dvGWcG75u7HUiU70jVxaRrc1Cg/Hbz6xl2dZK0/uFOu3EDhApg0vkRI8vIGrQm3+HOp16vI/MW46maHxzxDeZNXgW2fYTNUPa00xDAPt/MYVVv7qMsWIXX/P/mA9j+oweaK3Jnqy3p8upkeWwtWl1ENuhKNk9Yhkh9vGa435+57+JP+s3mB4T+g1jTXxCbUYr+BB7/kcoqo8vDPwC3x/9fVwZLiBxCYJQw5A8p4YQwWSvhII7CSve/R/nr7iZ14xJ/Mj/vfB2BfjORf34wSUDyNDUlMfX+LnvcMQpEB4dpdaHbJ2FQtFSodXC7Jc2Jlx1SVUQ6JON3juHTJvCE8N6cVWhq82f71Rwsqn/44E9Usp9rRd7AbgO2BZxjIRwc8Y8oKL9j3vmYRjScjCGbMORWsvUwYU8v7osbtBECl0pwaYKcu22NhXsesMYzz6jGz+1Pcd7vpF4sZtOCpEhkKE/ZkgpWXuglkxNpcVEYBa5nHECtbbFn1JnndiWa2bavaba0Ksvp6FyBHk93uRPpX/iX1v+xS2Db+GWwbfQJbNLuyJ5hub54D/XME7ZyY9834sT5pF230SrDkHQDNbWomqSoBAPCcK2RtFsln15Qz+XO2yv8roxif2ye9T+0Kpnxuji8GStZBxGy1+FlrsRRADNM5IXbr6f7Qezmf6H9eH3M6SxxmLVjcq0LEAKBHSDu94z+JZ+NXfaXuXpwFVsa9UDDeDVDRX8+IrBQGqRQbuaPZSNyEM6VdT9TYhaHyLiJQw9pyJIakITukTb04ha0YJnZAFf33KA7/Qs5IF+RSincYPtVKJcioHIQNjDrdsieQi4TQhxGFgKfN/sQkKI24UQa4UQa6uqqswOOePw6wb3LNhouT/PqcWF6UUmiSS+dtu97zoqPwt8g95KJQ/b/k0isZqKENl4uJ7qZh8zRhdbJvuYCdRkT24WDRObKZmfqYEMCkzD35na/bcRKPsBPTNH8vTmp7nspcu48507qdTXAKk5LQHOte1hgTIHjm1n7YQ/87Z6gennMnuuyGdvTzu4SCJDNtsTqfOA/6t4sPNH7QkyiM6SDU3YhxsPM3H0JrL7/omsPk+g5W7CXz8K/dA9PDhhLtsPZse9n02eAJoa/fsk60bV1qzgHUcbuPaJldS7/TwVuJoGmcm3ba9HHRPK7k30/YS2r6huYPq6XSg2Bfsnx9F2N5gGXLr9etgXkQpKi462qorMihb+WlbFd7cdxGt0XBG9jqajwhZnAf+WUvYArgKeEULEXVtK+ZSUcpyUclxhYWJb6JlAiy/AN/+zlldKy7lqRDcybNEf2ampCMFJRV+0p5zux8Yw/hi4npm2d/mB+gpWYicVIfLG5iNoquAnVwyOy1C9cWxxux2RupSmWZSRSVNmyTzupiIO7/gCr1//Ol8f/nW2VW/D2eNZsgc+QkbRC9hyNoMwLwGgovMddTH/VX9BdbPON5RfcrTb1MSZtxHPNXvaIIpdTgwpUYVokzC3Cg8NCcLZ0wbFCdFkVJHPvf7vMFwc4LfaXxEYgIGSUYa98zvUuh7jypev5K2j/6CHK5uM+pto3v1TOntu49FrLg1r77Hvp9+QZNltlt/JyWQFSyn5x4f7mf6nD9lxNFhbvYEsFuuTuExZh5Po2kahSc+sZENoknmjqo4vb95PidPOLzt3Jqu5Y/MuhAR9cy0/71fEq8fq+PbWA21KMvs0ScXkUg70jPh/j9ZtkXwDuAJASvmxECID6Awc64iHPB2pb/HzlX99wqbDdcy9YQS3jC8xrTF9MiGKbSFWW/xD4EZ6iOP8SHuJbOFmbmAWRsz83eIL0HvOElO7OQRNSUs2H2Fy/87ktUYzRLZRO9lQwWRL9USVEdfvVfnhmB9yx6g7GPTrP6LlbEbN3o6WtwFpqOjuEvSWvugt/dDdPRlOGXO1pxmuHOAN/Vx+4v8WDb5sPnp5M4/eMCJshw39hnfP3xBlG479vKmWUIAT/oq7528wnQQq6tzMGF3crnr4/zNG8RtxFfepSwhkHuaBLllIW1AoKr4S7hr7Iy7vfTnF2eamEKvvuN7ttyxVbBXJlExB8AZ0fvryFhauPxzn1/mfMYbbbO8wQuznEzkk6ryQE/nGscXhSpEhZ7/WI4tvbT3AOTmZvDCyH7k2lQJF7dDGKxAcX3eUdCFDEfxsdzlDFn5CYN3xuDHzWZOKQF8DDBBC9CEoyG8BvhhzzCHgEuDfQoghQAZwdthUTKhv8XPbP1az82gj/3fbWKYNCxaTMrNFW7U962jsNgVvRD11icK9/m/TKJ3cblvCEHGQu/13cJxgKriqiLCdNLaw1NqDNazYURUeEFMHdYm7X1vt1iFzRewgi21gHEmikMrIiaCbbTTlRwYDOmrmQWzZ21Ez92HvvBwh3sFmQI7Py3NewTb3DDa1TMZobWARef9EtuH2ZtxGDngrIZNKYg6AogRAO4biOIqacRQlowzVeZjnFD85tXncWVdOxtEi7mUmum84j86YxIzhiQWN1Xec59RMQyihDeGJEbh9Ot/4zxo+2ltt6uzfbQS7KfVTKvhEHxJ3fijcM/Su6lLywp5j/DtPZ1RuJs+P7EeOLajBh8bhotJyyx6wbSVUVbNTlY+MvY009cvB1jeH8n2N7fIfnCqSCnQpZUAIcSewjGBI4j+llFuFEA8Da6WUi4F7gL8LIe4mqCh+VX5WnTNOMfUtfm79xyp2HW3ib18ay9TB8cIuklSEuVNT8fj1k7LHek2aY0gUHgp8ha2yN7+0/Ytljh8zNzCLd+yXWPYVdfv1uOibBWvLGNsrP+qFTbS8Ngtviw1LjKS8zh1OuonUiFsSJPNECuLQtSVqq1bel76iglu11+mVtYa1GQ5W2LuyJdsPeevJYj1SKhi+TkhfZ477OrNgVzW/XVGDhwwQuSDtUfdpq9PSrL9oMkFY5HJSXt+A0OpQtBoUew2KVk1mVj09uzZxqOEQugyeKw0VNVDM+MKruGHYZCqPdeVPb/+HO33/YaHyKgcun860FASMqSNaETT7AuHVQuxKqk3hicCLa8q4/9Ut+AKhptTxuHEAkGeXYPJVh8oThzAybTSNyEc0+9nyzh6uePtw3DMkyvlQBAgRzBVJ5gvRFMFD1w4Lf2ZZ50bJUAkMyEU0+nFXeSyVkk+bdMeiNnDgeDMX/fZd7KqSkjAH63A0VQgMKcODYe3BmqhswI5mgDjMr7WnOVfZxQajH78P3MT7xjmkWmQ1NjwsURhZZK/RSHNOiy+QNKHKqqOOGZGhf73nLEFgMEnZxlfVZVyqrMePjZf0KfwpcD2VFAAGQqtBdZajOI6g2KtQ7MdRHdUgoicPqWdg+POQgVyknkmmLZsmtx2pO8HIQOoOkLZgeVlpA6kipQ0QqMLgzkv6cl7/AnSpYxgGbt1Ni7+Fj/Yd5u0dh2j0NZHlDDCwCByOFqo91RxtqsJrtEQ/h2Gji7OIYV36MsA1gIH5AxmQP4CS3BI0xSSDc9cyWPhNEApM/12wLVxrgTQrARy7z+p3sgrBNctcDjW1eHn9Ye5dsDFp+O1QcYCljp/yw8APWConRQUExCbGSVXgm1iI1BTsq6tQWpWTUN5EZCillZkrRI7DRqM3XnGIHZ+h7yoU0ikV8I0vRGbacKysRPEacVFbp4p0k+gOoMkbYPiDywCYd9M5fGFczyRnBElka461v6XSIFoRQXNJ7AufioYvMLhR/YAf2V6iSFSz3ujPPwJX8ZYxDn+SxVps3LTZ54qNbTfT/EghZMyqXEEsYQFTs49/PflrLgusoIc4To3M5hn9Mp4JXB42MSVqvfar64cxaaCNGU+9SrX3GIqtAWFrQGj1KLZGbJobp8NHc6AJITomwkEVKtn2bAoyCuiU0YnOzs50cnaislbjwx0Bauqy6eIs4seXnsv1KTR3jqJ6L7zybTi8BobO4M0ed3H3G5VxzbFD5YFjNVurOPTYdwCwNGtoqmDeTSP5+atbaPQkj0D6lvo6P9Oe4wLv4zRm9CDLYTNtRi4B/4h8jO5OtDXHUWuts0djOzxFUuxyMrJnHks3HzU91+yzQrQiY2Sq+CZ1Qanz0XtvCx+1s/VgW0m3oDtJfAGDbz8TnHy+c2G/lIU5mDcmDhG7lH1kxgjG9SpI6BwzJOTabXEvfCoavkThJf1CFuvncZP6Pt9RF/Ok/U8cl7ks1C9giT6RTbIvZlp7rMMr2bLbKnoilIRTkaCcb3JhLhmrHeJXJYfg/34OlVv4KoKVjOA3vlt4yxiHF3tUt5/INHqrZ75v6jWmk9TDrZPUK+sPM+/tTRxtrKWLC758Xg90w8+zn+yjurmFgmyV60d35/z+XVEVFVW0/lFUMtQMsrSs8B+H6kBYxTNPS/Lxk9GpH3ztTfjoj/DuXKZse5OvGdfxD67Ei731GwwS+w4uKi23zLQ1c3o+tHirqY3ar0seWbItJWFux89XbG+xzhhAmeyKsHDI3vfyZhoLHRhFmdj2NCQU5hA0l2VoimXpi36F2ZYCPbL2jpX/QGnRse2sJzAsn4k9Oyf9nJ8GaQ09CVJKfvTiRl4pLed3XxjJjWPbqC2RPAtQFYLf3TwSIKXIESvt4f5Fm037RVqhYHCBsplZ6nIuVdZhEwblshNv6eNYaQznE2MQDWSb2oOTkYqWl8gcFf0ZJP1EBecp25mgbOM8dTsF1AfNCj0nBrvSD7uBRftSt+takcg0cUZSs49lj3+LaepaKmQBfwtcwwv61LBgDxGa9KzeP7N3YFFpedIoLrW1plEiHrT9h6/ZlvFF30/5yBgeZbaL/B1qDZ2f1lYj6n1krK3GSOE9F8DjM0eZ/qaLSsu558UNJEv3iP3ske9Id5cT++SuHMFg5YQhdLafeh05bXI5CeYt28GTK/Zy7+UDufPiAe26Rird3J2aSoampFS0y8yWaZa+nwqhpXceTVyirOcKdQ1TlE1kCD+GFOxVemHrNYE+wyZAtxHQZSg4spNdNqVUbTOzTGfNy9eGSA7tWMcAYx/DlQMMFQfJFa225dxi6H0+9Lkw2Mgj6/TQjE5nJs9dTknDWu62vcR4ZSdVMo9/B6bxon4RVbiAE2UYrCbY3908Mm5iS6VcwR0X9eOfKw9YKCmSO9VF3Kst4B+BK/ll4EuWprEMTaXk8hJ2G37eHT+Y0h3HU1J+YsdK5DhpC1bXqahz07lbFuUjXXyxeyd+Ozj11Xt7SZtc2snznxziyRV7mTW+hDum9m/3dVKpaOj26ymFxQmICw87mRhpSTAkq86dzcvGFF42puDAx3jbPn46vIYh3k1Q8QYcmH/iCXK6g6snuEogr2ewJGqGC5yu4N/2TH45EX7/zhGaAyCQZOAjz6Zzx5gi2LEUWo4zo7mK4QMOsO/AfjoFjtJXqSSfhmDlIAU8ip3tRgn/s02hz4jJjJ5yNeT3Sa0/XpowQc3bx82+YYwX27nTtojZ2ovcZVvI28ZY5utT2Z8zjjKLd9SQsk15AiFsimBA1xwevWFEXPhuPg08ov2T6eonvKFcxKOBL0Zp5rFjobnAzqaAjwf7FdHL6aBXjMkvz6nR7AvE+ZYix8rJ5E6Ut5bwMPMPVR1tRnXZeFZKFizcTg/V9pmt7NIaugVrD9Qw6++rOK9fZ/7xlXHY1GBSTnuW5B2RhANBYX7rxJJwOc9UtQ2rGPBU9q2cc3GwsEzdIajcApVboWY/1JcFtzWUB7vQtBd7TlDLzusBBX1b//SBzgOh04BwK700J0fQvHBCqPYVFdyiruAm9T0KRBM+LZf/6WN52TOGVcYQmiIqOFpFt6SioYfMFRA0J2b4a7lVfYfbba+TgY/dw37IsJt+DsqJpLfYFa1UwHt+V4TfoOyac7Ep5hN6srHZ1gJoVp/FbMxJm8A7pRtKrRd7aU27zJSpkja5tJHKBg9X//lDpJRoisLRBk/CxgSp/HDtXepZRSO0ZZII2RGtolKsQrusbPVRGDp46sFTB+5acNeB3w1SDwp6wwh+As0JNmfwb80JmZ0gqxDs1qVf03QsZu+MAz/3DznCl3I34t/6OlqgkYBU2CT78rExlG1iINdeMY1p550btzJaVFqeNCwQYESeh9eu9FH+ycsUVizHToC39LH8zXYrX7r2iqSmnECfbAID8yja1sD6O6Yk/YxWQj0V02cyQtUmza4T6JtDYEAu9o+PoTT4LSfCkyVtcmkDvoDBd59dR707WDEwlLBTXuc2jVRJlOkYSVvS5q1iYEPntnViKHI5E0alJMtgTIiiQmZB8E+a0xrzd2BUeLt2jY8Pl7/GntVLGe7fxLdtS7CxGN7+LXyQB50HBU1teT0ht4gZjlzeUHbgwYGKjkYAJz4KRR1dRS19xFGGKAcp8tbAIujk6MQLxmU845/KbtkD/LDNJMsy0jkr7QqBvjloVR4eOK9fws+XrArkyTZzAcLfm6mv4WATgV7ZBPrlYi+tPqk+tO0lraHH8NV/fsK7u9pWtSBSk03VJJMoQsBKM26P6SaVFcSvl2znqQ/2tfm8NGc5vmao3AZHN8HRzVC9J2hqqy8HI7HzvkU6KJOFbJO9KHf0585vfIPz/13F4fr4wmn5mRqZ9vgw3OdXl+EZlIveM4svNKv8+dpzEt4zmSO+I0yfyaKBAv1yCPTPxf5BJT3tWlpD/yyZ+8b2NgtzOKHJtqVOdHs041TriVgV2zLjWKOHl0sP0z0vAwEcqfecHeF6aU4eexb0PDf4JxLDgJZq8DWyfNN+/v7OVpoCAj82vGhUyTyacAIiqBhMHwHdiymvN29BWNviD0d3lde5mb1gIwgIaAK9RxZqRQuvba3jg9KjPHTtMMv3MlkVyLa2KrQqYRG6jlmdJrWsmUDfHESfbGYP7530Hh1NWqC3crzJy1Pv70t+YAyp1ok2ewnbWuQo2RKurVq1YUjueXEjTd4Ar915PgO65qR0XprPOYoC2YVAIRdf1JeGvMFRQtKuKgjdiFMMUjV5hBKVAv1yQAF1fyMQLCWdqBBWKlUgQ6bPRPZ0RUBuhhaX3BdZMNmqIbrwGahHWqBHFlOHd034OU8FHVUP/YxGSsl9L29Oud1bZAbiydSJjm3oYFWLO0Qim3ayc8146oN9fLD7OA9eMywtzNO0m1AN+42t2Z2zpw1i/9zprJxzcZTfqLbZvE69GVJT0HtmoRxxo7ScUHgSNdIwqymvqcI0zDdRCSNDmvchaPEbzH5pY7iGv9V47F4TwAu8eLTW+ianiLSGDry55Shvb6skw6bgMalaGEso6iTWPpZqnWizYkaPzxyVVBhbafTtsXV/tPc485bt5KoR3bjl3FOfDJHm7Od4U1BgF+Y4orYvKi237OGZqSm0+OPHnN4jE2wKtlbtPJKEK9XYW8T8P2QWba/r0K/LqCqfZuPx/gv68xe9iQVHa/hWz0+3kc/nXqDXu/08sHgrPVxOjjak7pW26hVqFtYYm9wQW8yotsXP7JeCbewSCea2li21oqymhTv+u54+nbP4zY3nWNcUSZOmDYSEpBITJz5v2U7Lgmx2m4okujSuTRV4S7JQqj0oTfE5Dol8TLF1ZfytZsVQw5Jmb+Ck80EiJxSHTQlfL7LK5PHDVdy/u5ztTW6GZLe9vWB7+dybXH7z5g6qm7x4AwZmyrlFDgN5To3ZL22M6xXq9uvhdmNmZhCzlw6CM/89L26kz5wlpq3ZQkS2aAtl1SU7J5IWX4Bv/b+16Ibk718eR06GSQnWNGnaQSjhxxcwWFRazuS5y+kzZ0lCu3m928+NY4vDY0YVgomTeiAzbORVeuKOb4+PSZcyPEbb09IxlsjG6JHX80SsNGZ0yccmYMGnbHZJSaALIa4QQuwUQuwRQswx2f+4EGJD659dQoi6Dn/SU8C2igae/+QQXz2vT3i5GIshMe1l6NcNS61DlzLOIx4i0XIx8sW7e/4G7l+02fLY0AsVOaGEGg5bXt+Q3D1/A7sqG/nzF8fQp3OW5bFp0rSVrrnBLlDLd1RGvZuJyHNqcZ2I3vW6yTYgvzEoIBMpSJG0p9F2WwnZ5K0CIEJK2XW/f5+hqp1Fx2r5NEPDkwp0IYQKPAlcCQwFZgkhhkYeI6W8W0o5Sko5Cvgz8PIpeNYORUrJr5duJ8+p8cNLBli+DKGXKNZxmaxzuJXzJtWXTgL/XXXIUkC3tfO6lJKHFm9l2dZKfn71UC4ceOY36U5zeuG0q3TNdbBiR1VKZg1NEXFN1A2nSqDAgWdvQ1j5CQl7sw5WkSuBZm+gzY2220J+psa8m4JFylJZDezZVEWF18+mpk8vwSgVG/p4YI+Uch+AEOIF4Dpgm8Xxs4AHO+bxTh3v7qriwz3HeeDqoeRlaglDCM16habS/NnsR589bVDKfQ4lhAV0pN28dyfr8C+rF+0v7+7lmVUH+faUvnxtcp+k906Tpj2M7ZVvWWM8EpdT46Frh8WF/hndg6Ug1IqWuHNqW6LDFmPzPurcfjRFkJ+pUdfit6zrHkleho0Wv2652rYKOkglBFM/2gJDcnmzqp6ROZ9OiYtUTC7FQFnE/w+3botDCNEL6AMst9h/uxBirRBibVXVZ9dDWkrJA4u2oCqCh1/fxuS5wcdtSwhhqGlsIsy08Rmji5n3hZFR51vZ6eGEKSXStLJyb02b7vni2rKgZ35UET+5YnDS506Tpr1kJqgHXuxycmDudP4wcxRZDht3z9+AEuGQl4BelIlS40V4rHve3vPixnBAglkTlUy7jcdnjiLXmVxfrfcEyHbYcDk1BEEtPPTvRDJg9rRBcabYWITfQNT6eLHseNLn6Cg6OsrlFuAlKaXpryGlfAp4CoKp/x1875R57M2dlNWemF1DQvPRG0aknKr70LXDEmraZs6b2KiYUNZboiJHsc1xExG6Z+R9XK3aygUDOvPYTSPjIhDSpOlI3t5mrZ2H3k2rUs8yT0Nm2bDtiw9VjESXMuHYC43nVMdNbYsfp6amFDocIjbizEqYqcfclBc4OOT2UuJ0WBzVcaSioZcDkYHKPVq3mXEL8PzJPtSp5h8r98dtS2R/NiOkaYc0epdTIz/TemZP5MScMbqY8/rFF7dyamqbaptHlikN3ae2xY8QcM05Rdhtn/ugpjSnmHq3dSnlect28tDiraaCVhUCvVsmwpDMKumUVPtNZLJsixIUoq3jP1WU48Fgiw/rmjr82makoqGvAQYIIfoQFOS3AF+MPUgIMRjIBz7u0CfsYLYfacBnkTzU1upoZrZ1K5I5Mdcfqo/aJ4AbxxazYkdVSunSqhDMGF3M5LnL4+5jSPjjO7u5OZ1AlOYzJNF7rEuJq28u7moPCz6pwJWpARK3SdJRImL7h7YFq/FvVnAPUmwX2RxA9Rl8WNvEF7t3atdztYWkAl1KGRBC3AksA1Tgn1LKrUKIh4G1UsrFrYfeArwgP6vyjSnywifWjZRTiUBpb4OLRE5MM61FAs+vLmPWhJ5xyUpmzJrQM3w9q/ukSXOqCXa/anusd1ZnJ9WGga28GRuEi3U5NQVvwEi5LIdVA4pUUISI6koUuk5kka7QyjoyoSgRdlVwTpaTD2sbkVKe8iS+z0353PsXbea5VYcIzfexzWtTSaE3K7+pKYLsDBt1LX7L+uWJZvJkAyDUY3HFjqqoKJdV+2rRpUQVglkTeoa7GI186C3qPfHXO1XF9tOkicQsEzoZTk3F0ycbd+8sHO8eRfiitXJNERiQtNl0R5TJteppejIEijMJDM/nwZx8vjuu10lf73NfPvf+RZt5dlW0Zq4bkiy7SotPjxPEVlq4lVc9svRnbDW4RCVvnZqatD2m26/z+sYjZDlO/FRfGFfCf781Keo4KSW/f3sX9R4/iiBKo0mUXZcmTUeSSonayPrnrkwt2OGwkx1R54sT5hAcY8n0WkFw/E2eu5zZ0wbx6+uH89Br26hv42rB7dd5fnVZm3xXkShA7CdQan0AzPvkAN1V2yktS/258JI9v7rMdLtZclAi52XYbCElDt2Ly19Hnr+OrEATQgZ/xljnSiJTx6M3jAhPBomoc/sTZoT6dYOfvrKZPy/fw8xxPfntTSNTDr9Mk6ajCZWn+MPMUTjUaBHj1FQevGYYK+dczOMzR+HxG9TqOjLXjloVn+ofIpl4jTSJ/GThJp76YB/1bj8XDSrkkeuGm2Z7W9FeYQ7xwhxAtATAb+DNtp0Sx2sknwsNPdEPFCkkwcJ56Qvwz4XLmdqwB1dTBYW+Kuwy2puvo1Cn5VGeUcyBll4YxoUoimqZgBBqzhxbRD8V3H6dX7y2NawFOWxBO+OdU/tzz+UDEUJww9gebbxqmjQdS0iJ+PXS7RxrDEZ7XDiwkKtGdAdOjDWje3AsKNWpl9dNhDdgsONIIw9cPZSvntcbpdUsGrvqtlpFqCkkJLUFASj1Pow8jYptdR12XTM+FwI9lR8oJCQjNeYM3cOIhi0Mb9xGtt6MjsIxRyHbc4bQYMvBrTqRgGb4yQ00Uug7zuCmHZzTuIWnv/8J5157I/deeg4/fXVb3CTR4gvw0OKt7W5aG9nlxRsw0FRB/y7Z6cqJaU4rQpFg9W4/D766hUUbKrj09+9xz+UDw8LUKHCA30A0tM08kkgZksDXzz+REW0VkWaWHd7RNnQAUe/H6JNNt/xTW2/mcyHQZ03oGWdDNyMkIDXDz9i69Yxq2IQmAxx09uTjnEnsdfbCr9gTXsOhGPx8hMS2YyXL//lX8rsX8+CltzF3XXSlt1RMLW3R3iPrNKdJc7qR59T4wy2juX5MDx5dup0fvrABRYAuwXAoKNWepHbyWBKNjeIUItYSlaMe16sgKjmvyRNok6M3FqXeh64Ibrq4b7uvkQqfC4E+rlcBz60+lFLoU9/m/VxY/T7Zegs7s/qz1jUWd1ZhyrO1gUr24JFcd8s1PLdwGXtf/X84n3mMvgWTWJ83MqVruJwajZ5Am5d96dDENKc7Fw4s5Pz+nVm+4xi/e2snO4424lhfg4zJYLarCl+b3JuX1h2mutnXpnsISDkIwEpzj9xu1pBm+jndeXndYdPmHGbYmgL4gS7F2Skd317OeoEeCqNKJsxthp8p1SsZ1rSdY/bOvNFlGkczugHgSjHmFIIe+ZDj45GNoHe/iUuq3mVyzUc4A82sLJhEotAWTRE0+9ouzOHTKR+aJs3JoiqCy4Z25bKhXfnBeztZWHYc2476KI+iTzf4Wwo9fmNXsQK4dWJJh61UzUIgPX6Dcb0KeGTGCNMIOjOkO4BTUdjVbO347QjOeoFu1VAikly9mWuOLSXfc5y1eaNZnX8uhjjhBW9rokRFnfuEc1Vx8EaXy5lS8yFjGjbiU+ysyY8OIXU5NerdwTj2Fl8gJXNMLOnQxDRnIhndMskUOey89TwUIfDrBtVNPo43efEGdIQQfLTnOL99a5fp+aF2kCfTwSsRyRq/PzJjBON6FSSNe1eFoJNQ2NWGvqrt4awX6MnMEN381dxS9xaG4eGNoqvZ7Tj59Pii1hcsjBC8X3A+dsPHxLo11Nrz2ZPVL7w7y2FjQ2uD3T5zlqR0j2QJTWnSnAmsb2hhdG5muOqipip0y8ugW15G+JgxJfn848P9popOfqZ2ShPmUsm8Do27RCW1dSk5eriRhqK2lTJoK2e9QE9Ut7iz9zhXH12MPyODr/7qt/St1tqdNhwipCnHXUcIlne+iHx/HVOPv8tRR1eabEF7WuTLkeh58zJsNHgCaQGe5qygRTfY3uzm+yVdkx5rZYG02t6eEh1mWI3HyDIBIZJF0xmNPuqkk4aATq4tcfGx9nLWC3SrhhL5vhpmHH2NgLCxoOBqBlRrYUdI7yRastUPpwoRlcQTuwwzhMpbhZdyS/mLTKn+kKVdrwCibd+zpw1izsJNeCIKiNlVhcduOictwNOcVWxqbEGX4DvuZvKLyxMKX6uMT7PtsXZvswzuVJk6uJD/rjoUF1GjSxm+JgTHejK/l2gJ5q4ccnsZfooaXpz1Aj30A967YCOBVqHu1Fu4pnIphlB4pft11Gu5KYf8WcWphmrBrD1Ywz0vbkSXEiEgU1Nw+w1cmRr1LX7qtTzW5Y1hUt0nFLkrqMoujrJ95zk1Mh02PIGgZ797bgY/uXJwWpinOevY3BjUfP+7bA/eZuvyGWCtKZsFAiSze1sRq9VPHVzIwnXlluGRkVnhqQRNCHfrBOP1Mzwn6eHt4qwX6BB8MfZVNfGn5XtQpM5VlcvI0ltY2H0G9VoeEHyRRv3iLerdwfrhZpOtgLAGHhmnGtIq1h6sifJ4SwktfoPbJpbwyIwR4fCnUmMkIxq3MqFuDa84i5i3bCfVzV7WHaxl6eaj9O+Szf/dOoYJfU99uc00aT4rtje7UfwGnmZ/VAy6mfBN1CIyFiuTZeT2WOHdu5OTj/bWRJUQMNPMY2lLqHCoC1OZp21hmG3hcyHQAcb1DjaQmFSzmiLvUd4ovIxjji5Rx4SjWUx+RU0RzPvCyPBLZha/es+LG03v/fzqMh6ZMSJ8zqLScp5/eivjj39EJ1815XWd+OXr29FUwb2XD+T2Kf3SzSjSnPVsb/JAg980oShWUCZKAoolkUk0NqYcgsLbbBJIJXBYJrhfLMJnkKEIDqcF+skzqV8nhhhHGNOwkU05w9iT3T/pOaoQGFKm7FSx+lFjt89btpPjmYMYLT5heMM23ut8AQCdshzcefGAFD9RmjRnLoaUbGtsQWkyt42bOR1TbSiTaBy2t6xue+5nRrHDnhboHYH0ebi0ajk1Wn4wuScFdCn5g0WfQTMveiLNIESLLxDUBtQMDjp70q9lH+/J80EIKhtObdJBmjSnC/9YV4YXsFkI9EinY2xZ6/I6d3isFZsoW8UW9vb2tKYzS1yy7B/aqgAmEu/dHRqVXus2fSdLSut6IcQVQoidQog9Qog5FsfcLITYJoTYKoR4rmMf8+T5aMFz0NLI/zpPJaBoKZ8XW6oWrEvsTuybb3qNWRN6cqzRw5/e2c35v1kR3r4nqx9ZegvdvJVAOtMzzeeHJ9ceBEBpshZukU7HyDEHJ7Ris3LSUwcXxplx2tqfF05knUaWon585ijLmjOGlOyfOx2X01y+uJwanew2avynTqAn1dCFECrwJHAZcBhYI4RYLKXcFnHMAOA+YLKUslYI0cX8ap8Nxw8dYP0bi9nfaTiVGcljXiMxc9BYedEPVLu5bWJJuEC+Alw2rCtNngCT5y7Hr0scrbZxAZQ5gyVuizxHqM8pTmd6pvncUG0Ex08olM+KkC09UaMYt1+P8l/FRqa0tT9v6JxbW4MZYrHKVQkpZA9dOywuVFpTBA9dO4zVmvxsBTowHtgjpdwHIIR4AbgO2BZxzLeAJ6WUtQBSymMd/aAnw4fzn8Ge4eSdLNOuTUmJddAkyh57ZMYIvnVBX17dUMGrG8pZtrWSHIeNSX07sXp/Dd7W+HIJeFUntZqLvvoxvpxuQpHmc0SmK4P6gAEmHYoiCQnJZNEkIRONWa9PCazYUWUZUx4qthXZ5tHMZ2bVZxSiI24SOXB37z9CbUAnYEhsSlvrSyYnFYFeDES2/DkMTIg5ZiCAEGIlwUbSD0kp34y9kBDiduB2gJKSkvY8b5s5unc3e9eu5rybb6Vgd367skBjTSFWMbHZDhvX/PlDNpfXAzChTwHfOL8v144q4vy5y8PCPIQEGrO7M0w5nhbmaT5X9OqZy9a65oQlcyOrJibKoA7h9uuWWnx5nds0pnxyv4JwO8dIv1jI1BNpv490qEpO2NNdTg0h4O75G5i3bGdYeJuN6U5aUOTWBgIU2lM3/aZKR8XG2YABwEXALODvQghX7EFSyqeklOOklOMKCws76NaJ+Xjh82Rk5zDmyuuYOrjt94wtxdnkDXDrhBLsavxX1+QLYLcp3HflYD6aczHzvz2JTLvK+EfetizwdURm01hdhd93aov2pElzOuF1KAx3ZZFlt06Bj4zcnT1tUMK2ccmwcoh+tLeGRaXlpn6xu+dvoPecJUyeu5xfvLbVVPN3OTW8AYPaFr9li8hICkICvYMjbUKkoqGXA5EVq3q0bovkMLBaSukH9gshdhEU8Gs65CnbSd3RI+xbv4aJN8zkjZ21LFxn/iUnQgJ/fGc3j76xnRavTqOJhzrTrnLzuJ7cfelA8jJPzLqLSsuZ/dJG/Lq1M0bkdYY6aDhWSacen86qJU2azxIpJYfcXiZpGRxK4Kf0GzB7QdA2PmN0MWsP1rSrgbNTUy01dwmW2Z6RSUZWmClqoe5nZhp6Zqsi2KKfmiJdqQj0NcAAIUQfgoL8FuCLMccsIqiZ/0sI0ZmgCSZ5MeNTzIa3l6IoCiMvvZJpT21sV/ypU1MZVpRLpl0l027jeJOXlXuOU9vipygvgx9fYZ2WP2/ZzoTCHOC6iQM5cvAN3E2NbX62NGnOROoDOm5DsnFXddIxGdlfYOG68nb1CXj0hhEJi+6disYwtS3+uDh6OCHQ3capEehJTS5SygBwJ7AM2A68KKXcKoR4WAhxbethy4BqIcQ2YAUwW0pZfUqeOEX0QICt771D/3MnkV3QqV0/Wqg+yxNfHMNjN41kVE8X72w/Fi7jWVHvSbi8SnZPRcAfPzgMwHubkxfJT5PmbKDKF1zlNtSnlncR1V8gBjVJD11VCO6ev4EWn3VkSZHLeUpChkMTUSROpVWgf4YaOlLKpcDSmG0PRPxbAj9q/XNacGjzBjyNDQydMhVIzakSSX6mxoPXDAun6lvN8KGQqbvnb4jzjie7pyHBJ4Immuc+3E1W/3RFxTRnPy9vPRL8hze1FXNcf4EIjNbkIqtxFtLoa1v8qIpAj6m6GhmdkiyL1KrGkxXlde64BMRZlwb7IHxmGvqZytuvL8OnOrj8xUomz13O1MGFKTlVil1O/jBzFKUPXB4W5pEJDWbordlhsQ6R2dMGoamJNQilte+WxzCf0dOkOdv417rgalR4kws1hWB2tZUcDSlRqYxt3ZDkZ2pRiUKhYnszRhfz6A0jws2lzRKT2mrtEYI4R+ufWjsvfZY29DOOV9aXUbVtPQcye6ELlfI6N/PXlDHz3J4JkwtuM0kkSJTQYEZkIlJI2/7ZK5tp9plfQ5GhuHQl3eQ5zVnPotJymlrFszAZE1l2NTxWnJpCwJCWLRlD2rVZ3LfVGK9r8VP6wOWm+2IbQ8fGkbe1+Y2U8Y5WT+tnC7TDF5AKZ6VAf2LBe1xleDnkPBGc49clSzYdofSBy5k8d7npD7NiR1XctvYI2dj2VPOW7aTZZ34dTQZfVr+wpVP/05z1zFu2E9lZC9ob/dFCrdjljGonZzVOQ8dGCvPYuG+rc1MdY1Zx5GbNchLVd4ml41OJojkrBfrYw+8AcDgj+gcJOzPb4O1uq+09dE7kDJ/ox87UW2tTZGTz43Tqf5qznIo6N3Szgy7jhFts6YtE4y5ZH1Gz+ukConJR2tWmzkQim41vp6aSoSntavh+MpyVNvSuvqCm3WzLMt1vNUubbW9PfZWpgwujbGdWqEKQFWgG4J7rzk07RNOc9RS5nEibAjFZ0y6nFvf+W0WwJItsgaCGfePY4ij5KwmGPlolEiWKWIPkYciqEFG2+QevGRZn23dop1bknpUaepOWwxEtPis0VAXNavYur3Mzee7yuKVcbEH8RLicGit2VCW1u4dCInM3lrFleQY3TErXQU9z9jN72iC+v7sMGTghGJ2aykPXDos7NtX+Alas2FEVp1Alahvn9uvc1Zq+P3VwYdjflmoDi1C1xVgiVwFfv6w/P2uoSen528NZp6H7PR6y/Y0ct3eO2h6qdgaYerQjs8JiZ+qHrh2Wku3LqalcPbJ7wqVirHe9uuwgnXqWIJSz7qdIkyaOGaOL6ds9BwfxYyHE/Ys20+++pZbXCHUeSkYi02oi31h5nZtnVx2KK9WbjDyTsrkzRhezcs7F7J87nZVzLuayoW2r9tpWzjop8vKKUgBq7a7wNgHMHN8zrvvJyjkXU+xyJpzFQ8cm+klDL+aNY4uZv6bM8rhil5P9c6eHPeZ9fvI6u3bspjnz06lrkybNZ82i0nJ2Bvx4cjRTu/X9izbz7KpDCYVoqLJiMqGeyLR6KgIQUrAE4Q01qj9FCtxZJ9Bfem8TAA223PC2UPlMM1J1kBZbvAAhIb1yzsUs2XTE0sYWCrGKtN3lBBrICLh586gtJY0jTZozmdC7H8JsNfz8amuFKJJYpcuM3p3ix2xoHJ5ssS8z6lJwgIYSipwmxf06grNOoLc0NADgVqN/zFDWViypOkjNXoDYruOJPNqhZWVkXHuxpwKA/Vq3dFJRmrOe0LsvmvwoR1qAeMHclloticwm9y/azMq98bbqMSV5polEHUEqWn8o5T+toadIV3uwZoNbyYjbN/uljXFCPRVBHSIjwkPtcmpxtr9E3D1/Q1xsbA93BS1KBrVafjqpKM1ZT/gdV0RUrF/ku59KBEsIV6Z1PXErTX/Vvtrwv2eMDnYJU9vYaCJTU1KWGbGkNfQ2MrlPLgYCXYkP4PHrkrtaBWtIsEfO1FZOmtBSMVIDj21WAVj2EgTCoVGhV0eROr3dBziUWQJCpJOK0pz1hN5xKUBEaOKR7/6sCT3jzoPgHBBLkydgaapMFCETOf7nLdsZV98lEZoquGFsj3ArSQjWfbJS7haVljP64bfoPWcJvecs4TvPrQfAeQq6FcFZKNBTIdZ2F+uJjv1hrHqI/uK1rVHbHrp2GFqSHyrU6aSHu5wMw8eezL4pz+5p0pzJhFfD4oSGHvvuPzJjBLdNLAlr6qoQ3DaxhNyMeGUpsrRuLIk0/cjx39aVsV1VmP9JWVQYs8dvXpcl1A8hUhFsbtXQP955vE33TZWzTqCvMrGbmZGKUyWEVRhibYuf0Q+/FTUxzPvCyKR2OQmM9B/AJzQC3Qe2yXSTJs2ZSmg1bGuVtWarYQgK9b2PXsWBudPZ++hVPDJjhGUeiNXYtNL0Q4TGfyor48ipodmnx6X+W8kSs0Qk2Wqq+ceKvUnv2x7OOoFe4wMFic1I7nFOdXZONNvXtvijWlUB4XBIK+y6lx61O+l0zgQ++OnlaWGe5nPDjNHFFOU5uX5sD9PVsBVWQ9Bqe6ymb0ZFnTuliqipGGTMgi7M5Iu0K2BIjla3pHDVtpOSQBdCXCGE2CmE2COEmGOy/6tCiCohxIbWP9/s+EdNDUdOMFwxw0hePD9Vu3Uyz7tZUlKiyWJw0y5sMsD/qy1Khyum+dzh8em8ufUofVqVoFTGgNUQTDQ0Q5q+lXJV5HIGV9U3jUzlsZMSGvshu7npo2kK+I0Oja6JJKlAF0KowJPAlcBQYJYQYqjJofOllKNa/zzdwc+ZMtPPDabQZ+mJZ8C22K3b8uUnW8oJaTCyYTNHHV04rHZKhyum+VyxqLSc4w0eWgJGyjVUTpZkkWwzRhdbjvG2RN24/ToPLd4aZzePRNoVhM9oV8P6VEhFQx8P7JFS7pNS+oAXgOtOydN0AFdMDtYz76O1hKNW/jBzFH+YOSphJEsiUlmWRRJaypklLgxs2o0rUM+6vDHhY9Ok+bwwb9nOoFYdMZxCXb8SCfV8ixBFq+0hQhUV3X49LJzNxr+V0J81oWebEpDq3P6EBbxkq4Zuleh4sqRSnKsYiAzqPAxMMDnuRiHEFGAXcLeUMi4QVAhxO3A7QEnJqelw7+raHUW18b1R2bzwxelxJTIfnzkqJUEee97Mc3uyZNORlMphhpZycKIwjyIEhqFzbv06quyd2JfZO3xsmjSfFyrq3KBnQ4yCpEvJ3fM3sPZgTVyTGYAHrxnG7Jc2RglLTRU8eE18Ua8QoXDjUISaLmVcU4wQZk0yQseN61XAPS9ubFeD6jgyVESdr80luVOlo6otvgY8L6X0CiG+DfwHiCtYLKV8CngKYNy4caekZYdqs9G5Zy+O7tkV94OGlndAQqFudt7CdeXhWT2yx2hscfvYpVxkB5Rn//Es+f56Xu9yBQiRDldM87kjz6nhDRjBEroxSOC/qw4xrldBmwSuFVbhxqGOYrFYNbWYMbqYu+dvSOHTJUYCMkNF8ehtMuW0hVQEejkQGQPUo3VbGClldcR/nwYeO/lHaz89hw1nw1tLWfjG1pR/0LrKFg7vrKW6vImP1pRzhU/FJxQaFUmlKjlsBOPOQz+6VauqqYMLmbdsZ1zT6Mv7ZrG/YS1HcnpxILN3XMeVNGk+DwgBBCRkmAs0CW0WuFa0pZGNVbOL0PYO0T4dCigC4dE7Rts3IRWBvgYYIIToQ1CQ3wJ8MfIAIUR3KWVrK2+uBbZ36FO2kZ7DRrJuyauIo3shM960E1ruSEOyZ/0xSt86RNWhRgDsThvZXoOAEDgMQY5foLYa/CqaDf773FZm3jQYmz1oV4t8ye5ftJn/rjoUF/UCYP/weQj4+Mmjc3isOHGMbJo0Zyt1LX5EwMBI4JPqKL+SVbcxRQh6z1kSrnOen6nR5AmE48tD43btwRoWritvU0/hRMiMoMwQ7sApi3JJKtCllAEhxJ3AMkAF/iml3CqEeBhYK6VcDPxACHEtEABqgK+ekqdNkV4jRuHIzGJQ855gan0MQsC0Xy5n3FGDIl3huGJwMF/hqml9uPHC3vT/6RvhGVSRUKgL+gRUBvtU6t6v5P+V1jD2yt4Mv7AYtbUmQ6jsZyxuv85zLyxmwoF3mXTTF+mUFuZpPscUuZwcCMhg+F6CYzqCqYMLoxSsEKGxHfrbzC/m9uum4/lkkBlBcSs8OlOHn5q66CnZ0KWUS4GlMdseiPj3fcB9Hfto7cdmtzNgwnk0vvsuWqfz8Sv2qP09fQpX1EoMIVia6WOrpoOEj9/ZiS3PHrUcMgRU2iSVtgCrHAFKAgr3FOfz4Yu72fp+OZd8dSgf1zbyX4sfPzvQyMjy/9G9/yAm3jDzlH7uNGlOd2ZPG8RdpfvRbUprTZfo/R3lV1pUWs7CdeUdYyoxQYjEMfBmyMyQhq6fsiiXsy5TNMTIy67CLv0Mb9wWtb3Er3Bjs516RfLvHC9b7Xo4hCpkX7dcDgnQCx1c+8NRXPmdEfi9Oi8/to4l83ea/rg2w8/VlW+iILnyzh+hqB1bfzlNmjONGaOLuX5oNwCEXSE/U8Pl1NoVTpwIM4doR9IeE7iRpYE7gNDlKQtXPit7igJ06zcAZ69BjD68kS05w/ArGi5dcG2LnTpF8kK2F4/JdFZe5+YPM0fFhUhBsI3d7GmDEELQd1QhRQNcvPfcTox1x7BrGm9m+tFbJwchDS6tWk5n33FWlFzLfd3Tzs80aQAu79eZ57c0sfjeCzknJzPhsVbOymScjvkdMtuG0hws732qwpXPWg0d4LpvfJMsvYWpnk0ICdf6MlCAl7N8psIcTuQ7zLtpZFTSgsupMe8LI6Nepowsjcu/OYwNLhjqt3Fjsx2bBKRk6vH3GdCyj5UFk9impoV5mjQhutqD46rSmzin4/5Fm7l7/gbK69xtzio93fI7JCCzbIjmwCkNVz5rNXSA4kFDGDrlYpSV7/ONmZez9o0WXBd2o2HjActzJHDPixsxpKTI5eTBa4Yl1AiEEEyfOYh/P7eVSxtVZjRpHPe+w7Cm7XziGktp3qhT5tFOk+ZMpNARFOjHfAHT/YtKy/nFa1stnZVWYY2RTB1c2OFOzZMhz+XgmE0hXwoeOYXVVc9qgQ5w0Ze/yaEtm/h4wZN0GfAtZt0ylO1Ow9T7HSLkFE2UiBQXfz65Ox+sPMzEI2/R3b+bdbmjWO06N508lCZNDF3sQbFT6YsX2LFJfWZYmVMix6RyihJ32sPkfgXcfuNwZm7cy19nnMP5+Tmn7F5ntckFwJmTy9hrvo3ur8db/woBn5dHZozg8ZmjUsrWMqt1HNnoObQUXLZqOxcElmL492BzXoieeT7F+ZnpWudp0sTgUBS62G2UeXxx+1JxZuY5NSbPXR5VrTF2THZU4k5HrK4PVLvZ1BgsFjg8+9Su1s96DR2g9mgumQVXU1PxGi8/+hDX3vuzsJBNpg1AtEawqLQ8uq6DlAxo3stF1e/RBNzwozkc2OLCtraS664fTY9B+afqY6VJc8bSx+lgf4s3bnsqzsxmXyDc8CK0inbYlFMS1dIRppuKOjcbG1soybDj0k6tyD3rBbqhG+zfdJxB511A976DWPaXx3n+/nu48s57mDE6aAq5K0mdhpBGEJt15vLXMaX6Q3q5yzjq6MJbhZcxZ8Jk+ozSOXawgeX/2c4tPx+P3XnWf81p0rSJXk47H9Q2AfGmEivtWgCZdpVmX3w5j1MhzPMztQ6JFy9yOdnc6OacnFPvSzvrTS7V5c34PTo9BuczZPKF3PTzXxHw+Xn+/tm888+/cmlvZ9JlVYPHHyXMO3uPc/mx/3Hr4Rfo5qnk/YLJvNT9erILg9lfmkPl0q8OpanWw0evnJpWU2nSnMn0djo44vXz4vrDKZlKXE6Nx2eOosV36mLLIwlVcjzZ8EcBfO+yARz0+BiZJESzIzjrVcfK/fUAdOubB0CPwcP4ym+f4IPn/s2m/73B5uXL+FK/c1jk6cIBrSse1US4Gzpdvcfp4SlnQPMeCn3V+ISNDXnnsD5vFG41M8752a1vHiOm9mDzisMMn1JE5x6nzhGSJs2ZRh+nA4DHPthrql2rQoQjzSJjz62iX/IzNTx+I+paTk1tl+auCsHMc3sGuxm1VlVtL+f1K6BHHxdsrGbEp6Chn/UCva7KjU1TyCnICG9zZGZx6TfvYNw1N7JuySJ2fPQ+lzWuA6BJzaLJlkVA2FCkQabuJifQiEqwW/dRRxfeKzifndkD8Konrmnm/Dx3eh92rj7Khwv2cN1doxCnkec9TZrPkn6ZQYFeaeiY5U8bUvL4zFHhyqXzlu1k6uBCmjzxoY6RddFjk5DaI5B1KVm4rpxxvQqYPW2QaZJhqhyodrOqrgkFGJub1a5rtIWzXqA3HveQ09lpKkxdXbtxyde/w0Vf/gZHdu+kfOd2/v7aKrICzahSxxAKxxyF7MnqS5WjkApHd1ps8csml1MzjWTJyNI496o+fLhgN0f21FM0wHUqPmKaNGccAzODSX4yR4PKeIHrytTiehJYOSezWsMgrTJKUwl8iCUU3bZyTrCtg9XKIBnldW5W1TcxIsdJju3Ul/446wW61x2g0u2l331L0aVEFYJZE3qGu6JEx5N3oqXXtDb/cA9de6JrSmx8+j0XD8CZo7F+2cG0QE+TppUMVUFtCaDnxLeQEwRrpaQqhOvc/igturzOzeyXNgLxjTESOV1jCdnPY+uwW1VWNUNRBesbWvhqceeUjj9ZznqBvr+ykYomL3r2iZKZz646xIK1h/EGjKhjy+vcaIpAU0VKSywB3DqxJKrZRaxWcc/Lm/h2t064t1RTc6SZgu6nftmVJs2ZgFHnw8i3x22XQL27bUpV7Hj169KyIU2qGnue07xfaUgZfH51WVhJtJokAjkaPkNyniu7LR+n3Zz1Ar260Yc0MV3HCvMQfkMiRNCMUpfgpTLrOGSWFCGBZyqr+Z5wsnPVESZd379dnyNNmrONvADUOG1ITUH4T4zHUNTZyfbdNFtpR2rs5XXuhMK42RdgUWl5VOeiSJNOZO9Ts7BmAKOTA6Tk+MEG6Jx3Up8nFVIS6EKIK4A/Emxw8bSUcq7FcTcCLwHnSinXdthTngReIbG3tW6xtBb4IUK2tUisQpyaFTicAZmrjjLhun4oSto5mibNl4d05w/N9Rh5GurxYJJRZLRYe2zfqWDWym70w2/FTQB+XYazxGcv2BjV0Wj2gmiTzuxpg6KOCaF3zkDU+3lkxVayFOWUZ40njUMXQqjAk8CVwFBglhBiqMlxOcAPgdUd/ZAng1+Aw0xFT4Lbr2MldwWYVnxLVOFtvfDRUu9jwbJ0XHqaNADfH1OCAmR1y4qrhz5jdDGP3jAihdR7iZ0ABaKZnkotfZVqBqrHGKBWMSyjjl27dnHs2DH8/sQmnDoLv1lFnZuHFm+NE9R+Q/LQ4q3RB8fIC6kpyDwN9bjHtITIqSAVDX08sEdKuQ9ACPECcB2wLea4XwK/AWZ36BOeJEVF2WgHW4K2jzbKdcNCs7dqZDt72iDLrNMDNh0DyZK39uHo5kzXd0nzuSfLpjI820nOsGwW3jYpbn+kJt3nviVICQKDrkoT3ZRGOotmOivNZAjzqo0Azz23O/zvgoICevXqRe/evRk0aBAZGSfCjq36j1ptB6JMsvOW7Yyz4xudHSAESpUH+HRqtKci0IuBsoj/HwYmRB4ghBgD9JRSLhFCnFYC/cpJPXn/4C5yETQka0glJZkBLy5vI86AD7vux2H40fQAulDQFYWAUPGrNpqbnARqa1FzcxHqiYbRVgLdq0CFatDTp4SdNWnSfN45Ny+L547U4DckWsSSONJmXZyXQZGoo5+tmh5KPXahY0iok04O6S7qpZNGaScrO5eKRj+dcrP4zoV9mTqgAI/HQ11dHTU1NVRUVLB9+3ZKS0tRVZWBAwcyceJESkpKmD1tUJyJJ2T+SVYaZFFpuanQ1wszwKsjGoKC/9Oo0X7STlEhhAL8nhQaQwshbgduBygpiW/efCpwdQvGjb/+5QmUDOtEnzlLsOkB+tcdpm99OSWNx+jZdIxuzTXkexvI0FP3ru/+328AUHJysHXpgta9O3OOSQ6oOVRmFlCW04Wy7C54bUFPfrnNYKzXRn1z2+NZ06Q5Gzk3L4t/lB9nc2MLY/KCEWChSBTp9zDKVkl/z3Gy7H480sYBPZ/DhosjRi7+iJSkYpeTN0z8WsGJoarVmdmVey+/gHGFki1btrBp0ya2b99Oz549mTZtGo/eMMI0lj1RdmroWWORAozOGSjH3Ag6rldqMlIR6OVAZKv6Hq3bQuQAw4F3W5N3ugGLhRDXxjpGpZRPAU8BjBs37lT1b42ia+9chIAPlm7m0C9fZ96hrQyoO4zdCC7TWmwOyrK7sKOghBpHDrUZudQ6clCyMqkJKHhVjYCiokiJTeqohk62MPj6yM6McinoDQ3odXUEjh3DX1HB5KOHubChLnx/A0FlZj6HcrpypOs4bAUTGdDShJQynTma5nPP+fk5CGBFTWNYoP9m8XpGyDIGOqpQkRw28litF3LYyMMwcftZCUuzMOKfvrIlaKe/8kouueQSNmzYwPvvv8/TTz/N2LFjWfGjadjt0aGU08/pHhd3HspOtSr3a3TOAE1BPRqMpPm0yminItDXAAOEEH0ICvJbgC+Gdkop64Fw1LwQ4l3g3tMhyiVQVUXDwoVIOZC6vQbXbljKrvwevNZ3MtsKerPL1ZPjzrxgC+8IXE6Nh64dZuplD+27OMGP8+rqfTzzysc4yg9R0lhJr8ZKShorGbLnbdaOn8hPNi1lz5QnyRgxAueoUWRNGE/GsGEI21kfRZomTRSd7TbOyXHybk0jP+jRiX8sfJOLjVJUVbJX78RmvRsN8oSpIjbM0Cx8OISZsI3seGS32xk/fjwjR47k3Xff5eOPP+bQoUPcfPPNFBYWAsFJYeG66AAIAeFaL1bmGL2bE3wGWQ0B5t488lMzsSaVIFLKgBDiTmAZwbDFf0optwohHgbWSikXn+qHbCu+w4c5/sST1L/+OgQCcNGTAHx12oNUOZMH+AsRn2HWlga1103oy3UT+rKotDwqlMkZ8HNnE1RPupLBshT3xk00LV9OFaBkZeEcN5as8RPImjQRx5AhaQ0+zeeCiwty+dPBSn73f3/DU3OcciOftYEeNMmMqOOKXU7TcGErrJyQsfZuh8PBtGnTGDBgAM/NX8DjT/6Nt7wDcOQV0uILmOaWhMrqmsWxS0VgdMkgp8bH3Os/3QY3KamEUsqlwNKYbQ9YHHvRyT9W+zDcbqr+/AQ1zzyDUBTyvziL/Fmz+OaTO/hik4NCNY8qkse1hkKYzOJV20LspFDQORfhV+hyzmiKvngLAIHqalo++YTm1as59t5Kmt97H4DazDzExMkMv+lqsiZNRHGm+5KmOfvw+Xw4dm1Fd3TmUF4nSo924oiRa3psW23QVhEqobDj2LG9qd7BopZBXCi2c7l9J2/UK9RK85K3ocnCLCnJKHSATeEbfbp+6sEPZ80a371lK+X3/Aj/wUPk3XQjhd//PksqAsybv5Ny1aBBGAz2qWyznxDoVlliHemNjp0Unrn/I3zeE2FWrx/yMG+jg3LPuYgJ51Lgrmf0sV1MqNzG2Pff4fDypQiHg6yJE8m54gpyLr0ENSddijfNmU9NTQ0vvPACNceqyJ5yNYExE1COHAATIexqTcOfPHd53Ip5UWk5Dy3eGg4jzM/UePCaYcyeNoi752+Ii20LNYIH4jK9j/s13mAw0x3buMS+myXeobiJLwEQkhHFJpOGXpwFHp3Fq/czZ3yfdn477eOsEOgNS5dScd9PUTsVUPLvf5M1cQL3L9p8ohG0gO12nXO9NnIMQaMicWoqN44tZuG68rhQpamDC01fnI5AURWM1njVWKeNBKqdefyv17n8r9e5aHqAi7yH+WXXepqWL6fpvvso/7nGhqKhvNVlBIcGjeGHV5+TDoFMc8axb98+FixYgJSSL992Kx7dwUuVtcy9fCAPvrIlbkxePbJ7nIPzvpc3s/ZgDfM/KYtK/KltCRbrmnfTyISN4GMbwIe07hbsvOMbyFX27Zyn7ecd/wAik1ginbCxYY1GhorR2YG6t5Ejn0LceSxnfMei+tdeo/yee8kYPpw+CxaQNXECi0rLTwjzVjY4gi/CaK8azkh7ZMaIcDaaIKgFKAKeXXUoqgH0fS9vNs0MjWVRaXlc81pTWh8sWUNcv2rjf5m96fazn9Lvf29z8JdP8Hqf8yg5tp85a5/l9y/8hKM/+QnL/rsE2UFNcdOkOdVs3ryZZ555huzsbG6//Xb69+/PNYUuWnSDrJ7ZUWMyNFZX7KgydXA+v7osLosTTqTtJ8o0jc3ejFyZ18hM1gV60FOtZ0RGXdzzWClReo+gicZW3vKpxJ3HcsZq6ItKy3nt34u5+60n2N21P8oPHqZ3p04APLR4a9zM3KBIdmsGI302/v6DC3BkBpdRIZNIoipskZ7xRM9jpkGE7hHC2+KnosVrWcwnltBLIYTgl3sF5cOu4a9DpzO8ej8XHi7lwsMbyP7lvez9z59w3XgjeTNmoHXtkvS6adJ8Fqxbt47XXnuNXr16MWvWrHC25iRXNgWayqvH6nhqdO+4sXa3VTRJAkWmos7N4zNHmdZYiTwmRGxy0Xa9C/1t1Yyxl/OO7GZ6fuSEIEXQ3KJUeVE8OrOvO/Vx57GckRr6otJy5j73EV9/91+UZ3fmp2O/wpzXd7GotJxFpeWWVRJXOfxkSEHpW/G1jJNpy8nSdhOFSIWQhsTd7Of9AzUpCfPY+NrQM0ihsLlzP54YdRO3Xvkg88bOQuvalarHH2fPxRdTdsedNK9aldba05xWbNiwgddee43+/ftz6623RqXe2xTB9V3yebOqnhp/fCq/lbarJogEK3IFS2xkZ1jrrZHXjawfE9TGM3H1H43wu8lqKjNdsUfKBaObEzJU1LImJHwmptAzUkOft2wnN29aQq6vmZ+ddztuLQNSKH5TZZM4++ewcXkZwy/sQXa+I7wvmcAucjlNS2jG2t9iidzeUO0GA44niLQRBC0yZvG1Zl57n6qxc8T59JrzAL4DB6hbuJC6hS9z6J13cAwcSMGXv0Tu1VejZESHgKVJ82mya9cuXn31Vfr06UPm4ClM/f2HceOoe4OOT0rO+fuH2A41h3M+ZowuNk3NF8DEvvl8sr82TgNXFRFWhqwKb0F85ExsEMPkR99htJHJQLWKnXpw5Ru5Yg+NSQkE+uQgmvwox70pFBU7NZyRGrpRXsa0g5/wWt/JHMjrHt5eUedOqPneOrGEG78yHCnhg/m7ovYlsnc5NZXenZzcNX9DlG199oKN4Zna6vzI7dXlzQAcV81L86pCIAna8lt8Ae6evyHKFj91cGFcfbFILd7euzdd7rmH/iuW0/1XvwIhOHL/z9kz9WKO/fGPBGpqLD9jmjSnimPHjrFgwQK6detG9pAp/OzVbXE+qvsXbeaPr2xF1PnQe2Qhae1E1DrGZowu5saxxVHvvwTWH6pnfJ/8uHtGCjarsZmfGd86MtYPVl7vYY/emU5KCy7REj4upKjNnjYIpxZ0hMocDdv+JjI/pTR/M85IgX5zxRoMIXip/0VR2zPt1j37BMFOI3mFTsZf3Yd9G6rYu/5YeP/UwYWm5zk1hRvHFrNyb7wwjCyhaXV+5PaKXXXoQJUabwoRnLAH1rn91Lb4o174W//+cZyjVwA3jo2PlVccDlw33kCfRa9Q8u9/4xwzhuq//o09F19C5aNz8VceI02aTwOv18uLL76I3W5n1qxZ/H75fmvnpi5Ry5uRORrSFUy/9xsnapKv2FEV5xtz+3VW7auNu2/kebOnDUJTo1WhyMbSIUJ+sMjJBuCQHpwwipWG8LGKEPSZs4R5y3Zyw9gi1AF54NHp6ZafWpq/GWecQJdScnHVVkq7DabGeaIDiKoImn3WpgzJiRrmIy/tSWFJDiue3RE0g3Ai8ysWt9/g+dVlpvvgRAlNq/ND26WUHNpWTWaPTLSYiSdkZrHC7ddZubfGNJ7W6r4QdKRmTZxAzyefoO+S18mdNo2aZ59l76WXcuQXv8B3OHnkTpo0J8PSpUuprq7mpptuIjc319I0GVJm1CNu8OkE+pzI6A6dk+zcWKKONxs8MVj50VqwU29k0C1CoOtShoX+/H3H8eRqPDKihI9+cvFnGkZ8xgl0f3kF9mNHKbnikqhQIsOqeHkEoRlbVRUu/+YwpCFZ9vet6H4joQ09laayyWzoVYcaqT3awoTze8SFZZ2M6zLRc0cuHy9+8QCf3PJ9+r35Bnk33EDdSwvZe8UVHH34YQJVVamHXKZJkyK7du1i48aNXHDBBfTpE0ywSRbKJ3SJeqgZo4sTIyvo4pNAv/uWkqGZiysrx2joXvOW7TRtUBHrc0s0lqplJi7hidsugea+2di8Ol8q6mR5/qfFGecU9e3fB8D4SyewcuzY8Pbec5YkPbe8zs39izazYkewnOb4HCdTDjTw9r+2UZzn5HB92xMB8lvDHxMVyF9UWs77/91JCZLvf7SLu64cFFWTItUQRjMUIeLSmGMz5yAijPKGEcz4xUN0/u53OP63v1H74gKqF77Cpr4XUNv3QqSWYRlymSZNqni9Xl577TUycvJ5YLXBN95aQpHLydTBhXHJfLHYDjWj98kh0Ccb+5Y6IKhUuf0SBYj0QDk1lTEleaYm0ZC5M1FNlz5zloQds4maWTTIDPooNSgYURUfja4ZyDw7YnMNjis+e/34s3+CNuIvrwBAK44WNInClyKJTBpa7XfzYVaAveuP8c0sF06btQ3eDFU5YYcLOUciCWWd/ubFzfRpkmy26xxoiE9UMjs3VUIZb6HrheyAZqGbkWGUWrdudH/wQfoteZ1VXYfwhe1v88+3f82MPe9jMwKfWsusNGcnH3/8MY2NjbxeV8Them/YPLFwXTk3ji0Or1DNxq3wG6hlzRhFmWEt/cRO4pJ8DlSbC+GQOTLRqiDST2UWdBDCLTWEAHtEhJpUBIGBeYhGPz1bLE78lDnjBLr0+QAQDkfU9lkTepodnpSPNT/bcqF5Wx0/LuhMjzzrHz/y3cvP1PjdF06UxYyPYW3NcNtexfmNKgHg44ygkHX7de558USETOy5bS2yGCl82xpPv7TGxi/H3Mr3L7qLvXk9+PaWxTy5/PeMPraL8jp32gyTps0cOXKEd999lzqRw2F/dHErt19nyaYj4f9bmTNt+xpBlwQGRBfqMmSwQfv+udPDq1wrrTo2EiURbr/Oih1V3DqxxFSoB2RQVDoVI+xgDfTNQWbayNrdwI8/o6iWWM44k0tY2hnRoX/jehXw3KpDmAcEJmapcPOVq4ey5vX9/GRYJ/wX5fOzpdvi6kkk816bVWd87j9b6B3QWOb00RIxfepSctf8DTy0eGs41jZ0rlnWqqYI7DbF0vGbzHEUIlZbCU0Ee1w9+Nnk2zn36Da+s/lVfv3RU6zsPoKnhl+DzCpIm2HSpMyCBQsAWOPtbrq/tsVv2gEoEuE3sB1oItA/F8NlR6kLKnKRGr1Vt6AQrohscDhR9dTKZ1VR5+aRGSMA4iPKWm8756ohOLJy+dV7uynrk012lZffXjz4tBkTZ5yGbmstPB84fjxq+7xlO9slzAGK8oOhjBfdOojDO2poeu0wt/TtEn55VCFMwwOTsePjI1zo0dihBdhkNxfEdW5/nAnGTNuf94WRuDLtpteAE4I60fJSU4PJFpEO0FjtZk23oXzn4nv595ArGXtsB0+98xi37Pxf2gyTJiV8Ph8tLS1BJ2iuebp8MpyayuR+BagHmsAdwD/UhWwVqJEr8WSr0SZPIGoVHNLsrZJ+QmPn9Y1H4oS+1mpquWZML64eWUS3C4rJs9v4eMaY00aYwxko0LWi4KzvOxSdvt/ejtqRiTnDLijmhnvH0uIL0Hl1HZc023AaQW164bryKKGbKCrEMCSfvL6fd/6zHUdRJivyDCyNc8SXCIDoF3DlnGAoVCLHaWT1N6vlpV+XLFh7KCrW1vQ4VWP+oEv41iU/YXW3oXxl+5v88d0/0r/u8KfSuTzNmcv27dvxeDxceOGFCW3SZkSaKv/7rUl86dyeOHY2BOPSe2Vz28SSsAYNyce835D84rWtcdsT+btGP/yWqf/JKfwYUjD84eWMePZj1jQ08+sBxRTa40vrfpakZHIRQlwB/JFgx6KnpZRzY/Z/B7gD0IEm4HYp5bYOflYAHAMHgqbh2bSZ3MsuC2+38lC7nBqNnoCprc6s11/XPrk8XxCgj9/PWK+NIT6VTQ6dDXognO5rVYhLSsm5mZl8/Mpejh1sZNCEblx02yA6bznKPS9uTBj+WF7nZvTDb4WXopFpz5HPa3YNJaLDUuhvq/uZRQNYcTzTxaPjv8zyI1v5/saF/OG9P7Gw/4Vc9IjKXdM/u+SJNKcvmzZtwuVyUVpjY+G68pRDchUBv795VNQ79ciMEfxSSr68eT8fDlH46rkDos5JFJUSorbFHxcFZtaNLFn0Ta7w0CgdBPLstBQ70Y66UV3uYAfl04ikGroQQgWeBK4EhgKzhBBDYw57Tko5Qko5CngM+H1HP2gIJSODjCFDaPnkk6jtVrPuQ9cO43c3jzTd9zuLXn+HGty86wzwrxwvuzWdMV6VbzZmcHGZwcqFe5j/8k5cboNOuqBrQDDQp3Bug2D7v3bx6h820FTr5fJvDOOSrw7BpqnMGF3M724eiaYk1lci7YqRac8hrCYEsxD8VGLnE5GpKWHtanX3YXz74tm8XTKOm3ev4GeLfs1f/rqY0Q+/lXaUpgnjdrvZt28fw4cP57dv7UpoDonFkJiWqX51QwW73j6I2+Pn4uVbWLD+cHhfqtFhZmbCUH2YIpeTijo3z68uS/i8+aKFY1ouvlGdwKujbK09Lc2PqZhcxgN7pJT7pJQ+4AXgusgDpJQNEf/NInHi40mTM/Ui3Bs34q+sDG+zijIJORsj9+VnajhsSlytlBAhZ0qNKlma5edvuR5WZPhBEWxaUcb5VXBbUwZfb8zgy00ZXNfiYJzXRr3UmXrbYL70q0kMOLdrfE9QC3luJeZjkx9CXVtiibQJJnMUpYKqCPy6jPoRm+1O/jj6Zu4773bsup/fvf8El25Yxj0vrOf+RSd3vzRnBwcOHEBKyYABA9plmos1PYbe5cqqFrQtdfiybNy75aBpdFgizJ4lNs0/kQLkxEe26mfV8HPAJrCX1iAC8rQ0P6Yi0IuByNz3w63bohBC3CGE2EtQQ/+B2YWEELcLIdYKIdZWVVmnrCcj5/LLAWhY+kbK54Rs0o/PHIXHb1Dnjq6VEhnH3eSJLt/ZpMDajAAv5Hrp9pX+LO0OC7O8LM708UqWl/9ke/hznocPe6gMPb8Im4nW8IvXtuLXzc0+iWa/0EuzqLScZl98WVFaP0NoYkrmKIKE5nwAdENa1o/e0GUgd0z9ER91H87Xty3lkZV/480VqTUASXN2c+DAAWw2G8XFxe1u7hBpQnlo8dbwu6xWeVAPNuHtmcXP1x8IHxMa14neabNnSWWchOimNLJ88BiaXdloW2pRGv2W1/2s6TCnqJTySSllP+AnwP0WxzwlpRwnpRxXWGhezCoVHP364RwzhtrnnkPqwR/FrLCO2RLOqm55KC7cLE04hF+X/Pad3Xzr2kEcyRTstOvs0QyO2SQ2u3WFtUWl5ZZhWoaUCTWMqPRlkwkhROjzppJxeuvEkoSJHclosmfy6Llf4vHRNzO49hBPLv8dS/65qM3XSXN2cfToUbp164bNZmt3slzofTTra2DbWY9S5aGqdyYrqhui9lkJVwHhlpKRAQypatd5Tg19bHf2dumBbWcdamUw/T+2V8HpQioCvRyIzNrp0brNiheAGSfxTClR8KXb8JeV0fTee0BqDSYgcYGfVARiRZ07oXnHjFBFRjNCacex1eAgGHseemlSeQFT0TgUEYyxBXh85iiM9traheCtXuO586K7qXbm8sO3n+T4U39PN9X4HHP8+HFCilrsGHE5NfIzNQRB/4wVIdOHmX1aSNA21mB363xty37eq2kM7zObQARwXr8CFq4rj1P0QmbVREgBF9zYn10FhUypr6ZXnZHSeP8sSSXKZQ0wQAjRh6AgvwX4YuQBQogBUsrdrf+dDuzmFJNz6aVoPXtS9ac/k33RRSk1mIDEnnG3X7eMJAkRKpuZavPoRB2UgKhr/OK1raZRLotKy1GSPFeqhBYfkS92siSPRJTndOFHU77PfVteZvzvf49nyxa6//rXqNlZJ/2sac4cdF2nubkZl8sV3maWaAfB2kUtFmNQQEINWuiSX3Xvyj/1Zr6yeR9PDOlFoLw5TqFThWDWhJ6WvUg9gcTKj1QFyrjOvFTVwNgDO3j88gsonnH6CfBYkgp0KWVACHEnsIxg2OI/pZRbhRAPA2ullIuBO4UQlwJ+oBb4yql8aAChaRT+4AdUzJ5Nw5KlFLkyLYtjRWLW+SQSXUqcmppwP1j3DI0lkSfc5dSiwg3NrhMyJbVXmIcmKLOJyu3XcdiUuM+brJxvLMKZSd6v59Jlw9tUzvst2z/Zwk/Hfx17UfeUJr00Zz4eT9AUkRHTGcusy1ei1aYkOGYSKV73L9hEt86ZdB9fyDe3HiBjXyOyzh1lR9elZP6aMkszZaLhZORo+EcWILJsXHFoBxfiprj4zHiHU7KhSymXSikHSin7SSl/1brtgVZhjpTyh1LKYVLKUVLKqVJKaxtDB5I7/SocQ4Zw7He/48dTepouuWIbT4SWgla249ByKmTXjswWjSWVzMlEL+9D1w6z3BfCynkjIGkYpAD2PnoVB+ZOtzSt1Ln9BPTo6/fvkmX6XUb+Hbn9xrHFzBjTgw9GX87DF9xOflMNv3//z9gP7jX1Y6Q5+/D7g6s8TTthyrDya+VZRGuFKK9zM3vaoISOzqPHW6h95zDOSg+evjn4xnfGyIx+Z/26JMkQiUIqEOiXg29iIcIm+E22pPf+HUyaNCn1i3zGnHGZopEIRaHbAz8nUFnJhOUvmraois3wBMJx4Wax6ZGODgF0y8vgDwlszZFRKLGOl0Wl5ZaFtszaXyW6fiwSmDm+Z0oO1dh/x+KPqZmw+1gzAV3H5dTCNsPHZ44yrd0e2WRj3rKdrCroz70X3AHAbz94ksHl20/LeN00HYuqBsdSIBCMxFpUWs49L240NXfUe/yoSSTtXfM3JF0lerw6xoZqtM21yGwN33ld8Q/KRUbY6A2ZPKpLKhAozsQ3uSuB/rmolW6+2KJw7P3lFBcXM2jQ6ef8tOLMK84VQ+bo0eTfeiu1//0vZVcUIh3RQjKyoWskZtliIWFulgWa59RMbeESGP3wWzR5AuHomFC/UQPzpB+z9ldWJFp6rthRxco5F3P/os1xxYRiJ6dkpqZY/AZ4AwaPzzyRvXf3/A2mx8YWBjuQ1527L/w+v/j4Hzz88dPMDXwJuNj03DRnHmZmlCuHdgagdH8Vt79hnj4fQsqTT3wLIQC1ogWl2kNgQC56r2z0kmyUSjfqUTdKjRcCMmxGDJkepQIyz47exYne3QkOFdHgQ/ukCrXWx0H7VrKVRr7whS/E55OcxpzxAh2g8K67aHr/fb7x7j9ZP/VHNNqjHXJtSQCwipbJ0OJtzSHMnIpWoY8QXArePX8D85btjLMxxw6WqYMLeXbVIdPrVNS5WVRaHpdibdZrNHICS7WZRuxkmKiJR+z+404Xsy/4Hr/8+GnuW/MMDUvPIfeqq1K6b5r2YyZsrVaChhHA4ymjpuYjbLYchFDw++sJBOrxB+rRdTfS8GMYPgzpQxp+jtQ3s6+iiWtLFAI9VQypsHmrjbqjnSkqOcyx2jKGuHrQku2kzptHrcdFoy8beYqMAUIEJwjhNdC21KHub0LvmYVelInRvbV0rzuAcOtkKILizlnsqXdjONVgyJcuUY57UA81o9R4EUCBaGGIqOCI0oWSkpJT8tynCvFZhZmNGzdOrl27tsOu596yld0338L6wgE8NPHrUUXFVSEwpIx6wc1K1CZyhgqCYX5tEYip4NRUbhxbzIodVZS3OnZiNW2BpCXWLsKJDFGr5ym2GNBt6ZAU+7nNni8UwmX2nebj5+kdz5G5aytFcx8l79prU7pvmtSIFOB5To1mXyDKEVjg9PLQVZmMK26gxX0Qj6cCj6ccj6cCr7cSLGqU+g0NVc3EaXcihIaiaCiKnV2VLehGAFXoKMJAVXRsQifD5sFp85peK2Co1HrzqHYXcKS5G+VN3aho6kZFc3cafTmn4mtBiqAGbhQ4MLJsyIygAD+3Vz7+Fj+79tbiq/agVHsREd+XisF0+zYyRIBXvcPZOfe6BHf5bBBCrJNSjjPbd1Zo6ADO4cOo+dK3mfCfJ7ll1zu8MOjS8D6zyBQrTdwqbLHI5QwLxrssTA/twe3Xo8wlZl3Ns+yqqSCdPW2QpRkErCNx2mJ+cWVqUcdKTkTBxE4Y5masUYwedDll3/0eFXPuQ2RkkNua6Zvm5IicQAUGGeIwQ7ocpHduGcU5FRRlHSXP0QiNsH0HCKGR4eiOI6M7+fkTOViXw/KdXjLVMvY3DONgQyH1HifNgUwChmbaA+CWOUssbdvjtQMMtR/mTWMgGZqbPEcDBRm1FGTUUZBRS6Gzmgnd1pGpnVAmjrsL2FvXm731fdhd25eyxuIO0eaFBFHnC9dRh+D7uvj68cH/nE/QVHks0lQpmWg7SIHi5n++AXR2nZrJ5lRy1gh0gAvn3MHqvTv5yodvUpHdmZU9RpuG6kXGe8diFrYYEp5tqZMS2/swEcnWSLFNLSJNKslWDGY+hFjBm6EpePxG3HM4NRUp4xOWQsI8si9q5LXNlvg9/+8vHPra16m4dzbq0y6yxo9P/KHTJETXPbz00SKmlWylf/4+euWUkakFQwc9ATvlTUVsqhrGkeauHGnuxvw7biEjo5hgrb3WyeCNxJO62buTyKdTobsYqlchfA4OuLtYXFXicjTQO+8YVw5uwtOyiQH5e5nQfT0Add5cthwfwqaqYWw6PhS/Yd0DoC2YZXau2FEV9c4PUqsYYDvOxkB3qtVOPHoaZoIm46wxuYQwfD4Ofe3reDZv5q6J32ZHQa82nR/SOs3skIlMFZoqyLLbqHf7TZe+HU1IoJqZOcwQkNSmamZ/vdsi2kAA++dOb9MzB2prOXjblwhUVtLr2WfIGDy4Ted/npFS0tS0g+PH36Gm9iMaGkpbbduCQw092N/Qi/31Jeyv78WR5q5RWm7kuxL6fVNNVIv9nRO9byoGMx0bOGS4+NDfN7w9P1Nj+jndw83Zzd5Dj6eC2tpVrNi0mGzWkqW5afE7WVM5mg/LJ7Cvvk+bvzPRupS0eu/7RKw2SpRaLtL2UGHk8Y5/AI/PHH3a5k8kMrmcdQIdgoLjwMxbqDl6nB9P/i4H8sxbYcWSrM1cnwTLzT9ERIO0xUbdXiIHWmigpnLPVFrpRWL1Waw09GT4jxzhwKwvgiLo89JL2AoK2nyNzwtSGtTVfcKxqrc4fvwdPJ7DgCAneyj5+RP59f8y+fhwDzx6gj64BH0gQJuinEKY/c6LSsstzY6TbAfop1bzkvccPGhR4yJVFq0/yMJVrzMw9wPGdt2IQ/Wxu7Yvq49NZ0PVEGpbzIvUxZJM6Qi9292VBi7VdlEjM1nmG0RXV3a73u1Pi0QC/YyOQ7fClp9PyT+exqdq/Pqjv1HceCyl85IJOqtY7uII+zokjqrJz9TCZXCtgqFExLGpPEuo4twfZo5KqRluW+LCrerMt7cwkda9Oz3+/Gf049WU3/0jpL/9ZQfOVpqb97F3729Z+dEU1pfeSkXFC2RnDWTw4F9z/uSPGT9+MQMG/JTrJn4BoWQnvFZIATGLCU+G1e+caIxs1buiYDDcdiTstG9ro/EZY3rxzPfu4Oe3vcDlU9cwcMADjOjm4bZBf+b+iU/SMzu1RLVk1RBnTxtEP62eS7VdNMgM/ucbiKbZT8uiW6lyVgp0AHvPnsw579sAzF35N4qaEpfrjRXKZqQq3KxeJFUE4883PHi5aZJOiFsnlnAggWYhwHKgRRZEsqItYZxtLUSWCs4Rw+n28C9oWb2aY787Zb1Qziik1Dl2bBnr1t3CqtWXceDg38jOHsiwoY8z5YK1jBz5d4qLZuJwnMh8njG6OC6ZLpb8Vqd2KuYVTRFhJUIVIjz5tyXTt0E62Wd0Yoh6jKm9HSlVQE2EzZZNz55fYdKk5Xgy78FmHODnE+dxZe+3EQSLZQ3oEl83KNQ/NxG9RRUX2HbTpGSzzDeIzq6c07boVqqcVU7RWGTPXvz0vG8zd+VfmffBX/jZed/iQF6R6bEtvkBcq6pYrJKRYs+xiiIJVXSExEJ1/ppg+Xkrx63EWkuKdEpamUvaWsc5UZ2ZVGOe48/RuHfwFC7+97/JnnIBWeed16ZnOlswDC/lFfM5dOgfeDyHycjoQf9+P6Fbtxk4HFaOxRPEOvYisXJqRxIb0gvmiXUQ/c65LBLtANb6e9LTUUfzjo/x+gcRqTdGrhDb8u4oisav3x1MXdP9fGnofG4a+Bq9c8t4avNXON7kQ1NEdO5HgvlL13XeeustVq9eTZ8+fbjlllt43OGwPuEM4qy0oYcIOXA611Twq4+eIiPg44FJ32BHQW/T49tiX04mzEKpz2aaUbL4cbDuHxo6PxUbn1WsfUdoIe25duw5joCPJ977A101ybA3XkPNyzupZzqTkFLnyJGX2b//T3i8FeTljaWk5zcoLLw0HImSCon8OrdNLInLII7ELPzUSgkwE/yzF2y0TKDrrdRwkX0vOwOFfBzoRayB0SySLNl7eeKzSqb1Xs7NA1/lk6Oj+dumr8ZdH8zHSX19PS+//DIHDx5kwoQJXH755eGyBWcKnzunaCQhwRuoKOfXK5+iwFPPr8Z/mbVdh5gen4qwTFWYWQ22kKOqvfHsbXE0tUeLjkVKiXQHMDw60qdjeHXu/n/raGn24URgI7jUUxF0ytC446J+oEu2VzTw4d7j1Hr8ZGdoeHSdJr+BjkQHfICrqYqvbF5E7nkTKLzzOwi7grCrKHYV4VARSWp+dMTn+7RpaNzCjh3309i4mdycc+jX717y88/j1Q0Vbf4siRzwTk0lQ1NSKo8cen+toprMjoXEmcdjbIc5x3aEjYHulAaKCQldK2Ul2diL/axX9n6bmwa+xjPbvsC7hy+IOz7SKSqlpLS0lGXLlmEYBldffTUjR45M8klPTz7XAj2S0Xe9wMMfP02f+gr+PuJaXu17PrHVs1IJx0tVi7F62UMv7qhfWNe8sHrpXU6NDQ92TGLOotJyfvvmTvz1HkZkO7mwSw415U1kenW62WwMzM4g1wC92Q+nMATTEgGK04bitCEyteC/M22tf2tsqWvh3xsOc0TX8SOpROLVlNPODhqadI7WN3Hr0LeZUvwmDnsBA/r/jK5dr0EI0e7VVLKwVZdTwxswUnKIprJyjDw2JHytxoMrw8Y5xh76KlVsD3Thk0BPMjQtYTa22diLjOKKTrCT/PjcJynKquDH7z+ELyZmPfSMR44cYdmyZRw4cIDevXtz3XXXkZ+fn/Qznq58LjJFUyGzWxfuveB7/Hjd83xn86v0bKzk/865Hl05seQK2ZcTaX6Juh7BCbvjjWOLWbiu3DRJCYLlc82WrZoqmHluT9NzUym5a4X06/jKmvBVNLF36zHy9tfzH2w4yIEmoMlNAIVqBDUByea6Fvr3cdFndBeUbA0lw4ZwqCgOle8t2MjBJg9uJH4gAASQdM1z8va9FzLlt+9xuN6NQrCIfuiPggj/2w44ERQE/Pyk9EU8mfkYX/8eY4pdSK+B4fZjuAMYLYHWv/0Eqt0YLQGkJ0AvCQ8SXX+73m9Qu2AvxzfWobocqC4HtjwHap4DtcCBmuuI0/pPpZYfErg2UcePxv6LwQV7+PjIRIYP/jkXdDsRh2+VufyL17bGPUvs8944ttiy3k+928/jM0dZmv8iqahz8/jMUQlNKSFCfWwr6ty4MrU4G7ZTU3nouuFIOYxXl7zJEA7TTfMw+dKr+OMHFSn7dmInrOhM5Ux69vwumU13M6brTlYdGRF1/x+c351XX32V0tJSnE4n06dPZ+zYsSjKWRsLkpqGLoS4AvgjwXH4tJRybsz+HwHfJDiuq4CvSykPJrrmZ6Ghh14Oj8/PV7a9yczdy9nQuR+/GXcbdRk5UUvJWK1HEIw+eWTGiJTjzBMlKUU+00OLt4Y19fxMjQevOdGpKLJOh183wlmjkR2NrJBS4j/chHt7NRWbq8iocqO1LntrMNiNwT50DmNQjkEFBpWt5pAQViuCZBplItuuGZccWsu961/gl+O/ykdFwy3r0IQ/my4592dv4ELQCcGlaAxDZR06XRBc1M1FoN6LdEfHLAcEZBQ6sXUK/tnq9vKXDWXs0wNUIjHoOD8DBLVXt6ece8b+hfyMWp7ZNpOPj4yPMy+kmuNg9b07bIrpai90n1R+j9Cxox9+q81drCIT68ze882bN7N48WIAOvcfxZ+3CJr80ROA2XeeaKxN7ldAWU0jPx/3Pd4pu4I3D15LvdvHoFydKwobqK/YhxCCCRMmMGXKFJzO06+pc3s4KQ1dBD00TwKXAYeBNUKIxVLKbRGHlQLjpJQtQojvAo8BM0/+0TuWyCiV/wy7iupO3fnmmhd54t3HefqirzNj5tVhx5BZuvt/Vx1iXK8CZk8bxOyXNibNBA31H00mGLIc5gMhdO6i0vK4+9W5/cxesDHqc4UI1HpoXnWElo1V6HVepIBydNYTYAM6O9CpSVHc1rn9CTVYq+2JUsRDpqnIbMUVPUbzxZ1vM3PX//io+7CkHaGEKnC4MthT52YPsDpiGip2OZl51xjuX7SZl1YdogsKXRAUoVAsFSb5NQbWePDuqaOX3+A3BAe6B8kBDPb5dba/uptpmU60rlmoefZ2l1CtbzrOfROeJNfexO/X3cGeumAGZVtaI0am37elGmjkajDR9SG6GUxdO1oS+nVJlsNmaQ4cMWIEPXv25M0332TH9jXc6HCwQRayK9AJn3DEVQcNkSgabOXeGkCiSwWht9BLL2dSl0Y8DTW0VNmZNGkSEydOJDc3t82f50wlFZPLeGCPlHIfgBDiBeA6ICzQpZQrIo5fBdzWkQ/ZkUQL2Ol4dn6B8h/8kJ+8/WcKhynIkd9I2FRi3rKdrJxzcZRWbUWeUwsvS62080QhYotKyxPWnfEbMmqwB2o91L95APemKhBQ19XJc94Ar7lbaDS9QmokekaryWr2tEGWTl9DSvbPnU6fOUtObFNU5g+4mLs3LOCc43vZVNjfspZ95D3MtNWQEHt+dRk6cAiDoEEieNxTdT72PnoV0pCM/+kbFKPQA4XeKPRFZTw2OnsUqv8VbLwV0ASZxTnYi7PZFPDzp20VrGs8kT5vtZqQUnLnmGfp5Kzht2u/HxbmYN4a0er7inwfrd7NuhZ/uCqm2fuWrCBbqBnMuF4FSYW/FcnyG1wuF7fccgvPvr2WDz78gNG2w4xUD3PUyGXL+qM8l6tz85Th2GwnxJL5s0iyhY9Oopn+WYfQFJ1eAQ8O5SCVjTl8cfp0RowYEdcO7/NAKgK9GCiL+P9hYEKC478BvGG2QwhxO3A7cNrUGc4YNIjeC1/iyP0/p+p3v6dl9ScMKbqSbT7zuNTQS1ufRJgDNHoDYaFfXudm9kvRGrWVthWK0011FQDQ/MlRahfvRQjIntKDlbkK9765vc3ZgbEI4uOY3X6de17cyN3zN7TL5mxWPx3g3Z5j+NaW17js0Bo2FfaP+nxmJFslWNmMdSnDE60iBFVSZwPRnzEH6INKXxQG6jamNnnJXNVIX13yBzSasbFTBlc72+v8PLZwS9QzAVRWvsYA11Ze3PWFKGFulow2Y3SxpZIQ23nKyv6caIKdMbqYtQdrEoYxht69tjZDMXvORPzfugbKvQPJFW76qjX0VmoYpRxi1/uH+NUHr+JyuXC5XGRkZDCzUGddSw1IHTs6mcJHtvChiWDpu5LiUgBWVI5ju7eERunk8XPPbdNzn010qFNUCHEbMA640Gy/lPIp4CkI2tA78t4ng5qdTfHjv6duwngqf/MYj9k28tiQ63i/eFTcsYoQ9JmzJKXiRnqMY8mvyygnl5WwqqhzM2/ZzpSKexW5nDS+d5j6N/bjGOAi/8aB2FwOfm1iNmorijDvuATmJYnhhHBVLEwUkVmusYLDp2q812MUl5St48mRN+CxOShyOROafBIJsUSx/CGhaLW/EdiEziZ0MPz8NwBKNmj1Xgajhv/chB07AgJQ/uIe/t8re1jl83IkR+W75/+F3KyBXDn+DrbU7U7qdH3o2mEJVxxm35nZMVYkSkIKETITrj1YY+lohfhG4lbPkKhJdIN0siFQzAaKceKnq9LIA5cWU11dTX19PU1NTQS8XgZmGVQ1Bwig0CAzqDDyaJAZGA4v44t3sfrIGFa3BO+dqCXj54FUBHo50DPi/z1at0UhhLgU+BlwoZTSvNL9aYwQgvxZs8icOJGKn8zhvjXPMunIVv5/e+ceH1V55vHve85cMklIJiHhkkAIt3CRS4MgYFCLN1BUUGvrhe72s66tdnu37equtvYm7qKV7ra2snVb1yrV1ppCAWlRsYoGkbvhIiEESMIlIfdk7vPuH5MJk8mZmZMgSUje7+czn0wmJ3Oe886Z5zzneZ/39/xixq202JI7tgs7gJ620Kpv85H/0Hp0IWJ+uXKcDlPL862a4NF5Y2l8/SiOGVlk3jm5o4KjO8v7jch1Omjz+k1Njrl8AR5bW9qpPC7W+ESuco3uoiSAd3JnsqSihBm1R9g3ejoLJ2ebWrloxF1zR8d1SpGEO9/EIjyeEignyAZC42IBCtCZic4MqTPba+FqHPh8NZQHDnNi1+fYULGflDRrp3Z+0YQdX6Qmf3Qqx8w28TBzToTThIlSLvfMyzNUT4x04M5ka5fWjN94eXeHCmIkLqz40nK5+mrjOvRHivd1+iztuofvTv8v/EGdVw+Hmqacj8bQQMGMQ98OTBRCjCXkyO8E7o7cQAhRCDwLLJZSmlPC6qfYx44l/6UXqV29mqt+8QyFtWX8ctpS3h31Kc4v3u1MLIcXPikTqSeGq1zmn/HRLATOpRM6leP1NA8aXalilkTzCWGiI6jICLt4VxVPb7DgLrFyRWM5d3/97phpqQdfMZ4QjuTHy0IVS2u2nSAgZdyIPdH1OZxOiB5TP7CfAPsJsIZQ5JqPxrUpx5kHTGwYx49IJtAkOfjKYbaV1lN4zVisI5I7Jlqj51LCmvzRzjx6G6smaPP6Y7YzDP+fWclcqyZo9foTfpYCmD0ms2N8I/cVaWNM6QoDExI548jPUtfcfL1wNXlpVaw5/GXq3JndurANZMyWLd4IrCJUtvi/UsqfCCF+CHwopVwrhNgMTAdOtv/LcSll3F5jfVG22F3cBw5w8tHv4f7oIz4cNomfz7yN0ylDL9j+cqMiHaMculUTrLxjZseJW19cRtvuGnK+P69TJYZReZtBYAQYt+iDT14G2Gw5YMXy5RCU5L/0Ytxyu8j2fWZryHtyTOExB/MStFMzD/Lg7Gd4cvtX0esnMxcLc7EwGQ0NgSXLgWNaFo7pWSz8vw+oaowvUWzG7ujxNaOVH7n83+wdmdG+zNoYSazzLl6KzeWqYu++L9HScohLpj7FiBGDr6XheS8sklJuADZEvfa9iOfXdvmnAUDSlCnkv/x76l98iWn/+RS/evNJXpx8PcXjr8CvhYYuXtTXHQR0qksOn8DRVS4p9s4fmW1UKq0lJ7n/x1v4a2tb3LLChZOzDRcrxXKyRvlaqy5A0mURSawl5rG+tPGwjxtP86ZNQPw7DZcv0Ok23Ew6pkcTfu3XyegUUWTaI9oZVreGNPjHOo+yoX4iHxHgOTxkIHjn1kKOvVdF6pbjNG85wVPobMTGBnxEZrnNVLdEEk59mY3Io6Pa7tyRGVUgdTfNF652iiRe5df8nF0cPPR9IMCnZv6aoUMNp+oGNYNqpWhPELpO5j98nvdyplH7+OPcW7qeRRXb+PW0m9k7ejqzxjjb62GNyW3Phyf6chlN/oXrgiNpcPk6Oa03pI+RBLm3VWM7ImFZ4ewxmaZXRcaqIon1mtEdxV1zR3e5NU+EdeQIAo2NFG+voNVjrplBmESljkbH1OqJn2bwBc6Vh0aPafgzq2/zdboDavCkc7BuAgtHv8sbx6/CEwhVTSU7k9hsC/JwXS1WglyBheuwch9J/BN2tuFnHT624mdkRHrKmWw1FT03uHwdx5LImUcGEMW7qkx3MQpT1eAi/6H1HYvhupvmM6qKMUqxpVjOcPzINxhSv5O0tJlcMvUpkpO738FoMDCotFzOl+JdVbz+3KvcWvIqeS1naJ1WyMpxN7BNM+66E/mlKd5VFXNJdTh1EB09xyP83kVPvEl6g5dVJHOaIP9KG9XIHncU6inFu6r41su7u/RRteqClZ+Z2a3cZt3zz3N6xRN8fulPqBXdlzXtbns8s6kJo2gyXmnpBGc5/zrnZ7xfPYf/Lb0HEKxqrxWPdnw5CJZg40asZKNRSRD/7GEULZvEn/edNLUcvztEd7yKdfwOq45A0uaL3yFXE3D33DzTk9AQUoOMvthHpthSrK3ckL+Za8dsISg1pk78Bnl5/4ymDe44dNB1LLpQLCvM5Vc//xrXv7+Z4Y88QtqJch5b+zgbi79t2ECjyySPQSWf02FlxW3TeetgTbfSAOHb2+oGF/sJ8F3ayETwHKlciyXu7W/xrqpud5FJxMpNhwybYoej2+4g/aGovNXfMwfWE733RI0i0h1du0f9YF1p3NLSsoZxrCtfRFHuB9w16VUyk3WWFeYafjbVSP4HD5+hhRU2DxkZSeR/WMvJ/9jOjrUfdymBPV8iNYtidTPShWDFbdNNrZINytBK6hSbeSna9XtPdnktx+nAaW/gcwV/4j+v+D6L8t9k28nZ/Nfen5Cff/+gd+aJUKPTA4TVSubye0i/aQkfz5sPwK/efJL1+ZfzSsFC6pPSyEi2dopKY9WVp9gtLCvM5ZvdlNKNXpyzmwD30cpjJPMYySy1BPGdaWN9VX3cPHpVg4sH/7CnQzZVF6JHaZJ4FxCjv8Wb+PLX1eHVLLgs3Y/Oe1q6lqhGu9WgAYqZFMjaIzfg0N1cn7+FT4934/Z8ivQ4zSECwO5kjYLvXobnSAMVrx3mS80WriGFlbgpjaq1Cqf0croxqRle5h+OzGOlWYJSsqww17TMswS8/iBWXZhaQ1Hf5usYUymD1NeX8GjRGoTnbQSSD07NYmPFtdR5RndoLCnioxz6eaA7nRxas5lV//cWy0r/xs1Ht7L4WAkbJyxg+re+0mnbeIuIoHtlhpFOK3KSrxrJ/bTyWc3OAyRx6ukd1ONDSndHCzCjlYKR0V9Ayo7b5kinnkiRMJ790RFzIskDz+HDnEkb1kXaGEIOLFbOW4jEfWFjHUuiCb3IPHr3EPzx8O1cOXU2ye7/pqRkEQtybuT18rn4pXHP2OoGF0IIXm9u4+HGOuYj+DJJPEMyL+DlN3gIYJwHN1p0NCsvnfeOnFPvCesSJUqPhBfRdQdfUOJ0WEmxW0zNUfzm7S3MdNZx8tRruFzHcFjSaXPcys+3zWL/mVRynA5WLFHliGZRDv08CZ1oC1m5KYc/VC7k3vI3WfbxFvRvbuP0Zz9L5hf+EeuIEXGXbIP56otolcXoSb6RTgfzFk1i1MRsnl35Hos8Fq4mlXfw8ypedpmspn+x5HiHQ0/kgMP2x5ICjo6Y40keLL0kG9fuPaReWmQoNrVwcjZ/2dP1Vj26nDMWsY7FzKRjtNOP14YtkoCULJn3AG1tN3Dw0KPcOv4Vrsz5GxsrruH96stwBzprjoQnyMOSt28CJbTwdZL4AnbGofEDXB1RdrSUbnQZ58pNh7pcxM0kcHpavdXo8nUS6SreVdUR5QuCjBpSzczsj5g9fDejh1RTflTgdF7GuLFfJzt7Mbpu54aiHu160KMmRS8AnrIyan/1LE0bN4IQpN90E7svv4kHtzfHLRk0qnKJVWNtRsN77EPryUTwGWzcgpV0NMoI8Bd8bMZHQ4KvdbhRdaz6YqMIMZYUcKTN8e5E9i1KpvKBLzPql8/whrMgYdml0X6MSLRvM40gjI7XzGSlLgRHVtwIhAS7/vGXv6BoxGtMcFbg9tv44NQstlbP5UjDWEDrpPkdzW1Y+QZJvI2fH2puoGsJafQ51dPOWD0lepw8njM88NyzjEv7iKlDD5FubyYoBWUN4zjcNIcVd38Nu314r9p4MaM6FvUR3soq6p5/noY//hHpctFSOJfV2XN4w5HHyIyUHq9si7Vo6J6oqoFIR2wDrsPKbdiYhI4fyQf4+Ss+3sWP22A/gsSpoMgcrtHy71jNh43QheDN6lfwlB9h/09fYOUb5V0iTTMXlkgeKd7HS9uOx9SkiTzWp2NUoIQpGp9JxVmXYQlnonRZRUSFTOjz28uI5HKuyn2Py0buxK57afQMYU/NJeytvYTD9eNp8aUavtdd2PgXkvgBbfyNrmWd4fEwU70TTfRdUTThc2Lh5GzW7z3Z5a4m1SZ5/OYUCkdW0ti4k8bGnbjdlQA0e1MpPTuJj2qnsP/sJLwys991l7oYUA69j/HX11O/Zg31v3uRQF0dtvx8Mu66k/Rly3rUGDneiryMZCsNbb64C4n+ecoI7IcamO8RDEfDg+RD/LyLn634TWulGwk0xerSFKsBQySzTx/gR+8/x5nP38/97kld3qO7rcui9T/iYWZVptHxhh1Sfpxcs9EFJ/KiNzYT8lL3UJC+i+lZ+0m2hi6vVS0j+Lh+PBVNeVQ251DdMhJv0IYAfksKbiRfos3QzqNPLOn2ys3cblw4g0E/Hk81m/ft4J39JaRZKhjrPMXw5FOI9ouMzTYMZ/qlpKfPwumcw5tlTlb+NbFImSI+yqH3E4JeL82bNlH/0hpcu3YhkpJIu2kJGXfcQdKMGaabKJjtBhS9ND7dYUUIOhz+d64vYEiNm31vHaMICyPRCCLZT4D38bODAAcIGGbd48kI9CT3muZp5ZdvP82InKH80/yvcqy5a+TZ3ebC4x/eYMqW6DRFd7otmekPa6apd3ifuvAzNv04BRllFGQcYYKzHIclpHUXlIIzbdmcbstmlGsYY13DeMKVQp07g2ZfKi3eFNwBO7nOZNNdioyOv3jnMR5fX4JdayDd3kS6rYksRwuLp2qMSDmLy3UMt7saKc99Rnb7CFJTJ5GaMpnU1Mmkp19KUlJOjxuDKGKjHHo/xH3gAPVrfk/junVIlwtbfj7py5aSfvPNrD8TW+MbuqeZEe/2u1P39tcP4Wj0UISFBViZ1K450oZkV7tzPzFEZ1tzaOL1k9R4sQV8/Pi91UxtrOTxxd/kPcuwmNsaTZTGum2PFzWHMRJ16s74hqPhWPl0o8UzYcwIZwmCZDnOkp9+ktyUKnJSq8l21DLaUYewdrXRF7CgWzJIdaRRVuOjzafhC9jwBS0EpIYmJHZdYtHB6/eTbIXRGZJUm5dAoBW/v4Vg0CgBBxZLGg5HXvtjDMntP1NTC7BaL96myxcbyqH3YwItLTRv2kRj8Z9p274dgH3ZE9icW8j7OdNotqUYTnSF68YTkej2Ozq6DTvBNASF6MzGwqXo5BFaMCKSLNjyhvC747W853aznwCtZuwQkGTpmjZx+Nx8f9tvmF5bztNzl7N55MyY72GmR2skZiL0ihhd5s0Km0WvBjYjkxCeZ+iOcFbHe71+iOsbA9xLEkfnJFGf10Lxjt14vPXkpnn49EQb+Zk+AoFWqusbKDtdhya82DQfmgiC0Mh1ppCR4kAIgRAWdD0FiyU14mcqNmsmNnsWdls2Nls2NlsWuj64tcb7C+ctzqW4cOipqThvvx3n7bfjrazkqe/8jDkfl/DN3X/ga3teZW/WeLbmTGf1ay6WFd4KmOs+EyaW7GuY6Ncz2sv3mpC8jZ+32/OhE5NsFN88A++xJrzHm/iMW+cOUgi29+HcT4AKTVIa9FNGgC5NwyQkWTVA4mpfRp7XdIp/2/4Co1pqeGb+cjYPj+3MI+VkzeZdE+mhx2qGYKT3kj/U0amWO9KmyP8z22LQqHQT4ouZBZo8XJHXhGtfLcmzhrHg1gKEJrhlzkLD45gOuAwuMtervPWARUXo/YyxD61HSsmExiqKqvdRVL2X0S01BBGkzCok9corSVmwgKSpU/jznpNxKyzClRvLCnNjRquRJXUQW58kOnUQdPvZ8tZRdm+rIs8tmSp00mQoXxpEUkWQwwT5mABlBDlGgFNIkqw6d8wchu1PL7Nkz0a81iQav/UIX9qvx7w4mdG6jlXyGWtszEr5ht/bTFVRNPHuiqobXIbHazTB66tpo7XkJK0fnEIGJWnXjWHIlaM66d8rBg8qQr+ICJcJljlHUeYcxfNTFpPXfJob6g7wOXc5NatWUbNqFXpmJnOKitiwoIh3UsbwnbdPGTocM/01I4kV/YcbCIffT0uycPUNE7n6holAqL460OTlnXePsXXrCfKDgknoXM251ZAeKalvbSFl/fvYWoPYrruHrPvuxj4xh5yfvt3tksQwRpFwdGRu1QSpSZZzE8LdqLD4wbrSLtG0JCQXEI9Yq0/j5efDd1S+Whfu/WdxlZ7Fe6wJNEHyzGzSrs3DMlSlPhTGKIfez+iyYlQIaobmMuW+xYwrzMVfW0vr1q20vLuV1q1baVq3jvHAy1nD2JGWx47U0dTkT+Guz13FskvPNeLOjTGRaZR2MNI1SSRLK4TAkm5n4ZICGnNS2u8cWkgFLmtr4pqGk3zK00aWI5NA+ijsw2cAcPaFCqCC39mTKBMalTLISYJUE6ROh+VF45D+IMISW0cuVvoiEl9QkmyzsOt718fdDjpH+/F0VxLJBZiVc7AT6nI0U7NyT5qTkys+INAYqmyxjkwhbVE+KbOHow+xJXwvxeDGlEMXQiwGfkaoY9GvpZRPRP39SkIdjWYAd0op//gJ2zloSNTJ3pKVRfrSpaQvXYoMBvEcPEjbhzto27mTBTt2MK/8Q9j7GmLzKioKCrBPmUzSlCk8OmEoD+/wUy/PfeSxhKwS6c4k4pbJmVznSeHZJ4spOFHK+MZqAgh2DiugePwVnBqRyrvfvhxfrRv/mTb8dS4CdR5yjzeSUdPGwiBYECGlqvUnqFp/Ai3Fgj7EjpZmQ498DLEztMGLjkYjkmakoeqjWfujo/14tfOJVB0jL852YAQaI9EYjmAkGnlojEUjt72iiCBoDT5s+WnYx44iaXImloykuPtQKCJJmEMXQujAx8B1QCWhHqN3SSn3R2yTD6QB3wbWmnHoKof+ySOlxFdVhWvHDlwfleI5cAD3wYMEW1o6tmlwpFGZPJSGjOFMunQqM2ZOwJKdhSUrC0t2NrrTyYIn/x43/SGlRLrdBJqa8J8+jffECXwnKvFWVOAuLcVz5AgEg0hdpzQzn5JhU3hrVCF1jnRTuWsZkAQaPfjr3QTq3ASavASaPKGfzV4CTV6CzV7DspMgkhagkSBNSBqRtAEuJJpd586ifIRNR7PrCJuOsGkITQNdIDTB117ezalWD37Aj0QQ0pjWEOiEIhqt/fEvReOYM8qJ9AaQngDSGyDoDRBs9RNs8xFs9dFU5yLY4iM5SpzX1z7PUE6QowT47vJCrDmp6Bl2VbutiMt5lS0KIeYDj0kpF7X//jCAlHKFwba/Bf6iHHr/QUqJr7IS94EDeI9W4D1+DO+xY/iOHcdfY5wDDlqstAorbosVj2ZFQ6IhGeqwkESQYGMj0tc1crVkZ2OfOgXHJZeQNG06yZfNYd3hRtNlht06roAk2Bpy7u/uPcWrWytwBELllukRjzQEDiAFgdOiowekOWWqnmIRaMlW9BQrWvtDT7GiDbHy43eOcKDNw0mCnEV2mNHbzUgUFzfnOymaC5yI+L0SmNtDQ74IfBEgLy8vwdaKTwIhBLbRo7GNHt3lb0GXC39tLf6aWvy1Nfhrawk0NCBdLhqP1XCo/DR+l5sku4UpuU6yhqYirFb09DS0tHT0tDQsw4ZhGz0Ka24uWnJyl30sK0y9IMu7hS7Q0+zoaXauHjWEppHJMYTNOvdZlVIifcFzUbUviAxIZCAIQclXXthJfasHCwILId8fJBT5Bwhlgay6xhevGs+VlwxH2HU0mxaK9q06Qo8dXV/u1Fn3p324fJ3FtHqi365QGNGrk6JSytXAaghF6L25b0VXNIcjprMfBlze+yb1GLP16UIIhE0Hmw4G2ldLbipoz3ufW9ZuVCFzbQ8uUonmRxSK88WMQ68CIr/xo9pfUygGHBfa6XZnYZRC0V3MOPTtwEQhxFhCjvxO4O4LapVC0Ycop6u4WEnYJFqGJNW+AmwCDgCvSClLhRA/FELcAiCEmCOEqATuAJ4VQpReSKMVCoVC0RVTOXQp5QZgQ9Rr34t4vp1QKkahUCgUfUTCCF2hUCgUFwfKoSsUCsUAQTl0hUKhGCAoh65QKBQDhD7TQxdC1ADH+mTnvUcWUNvXRvRz1BglRo1RYgbTGI2RUmYb/aHPHPpgQAjxYSzNBUUINUaJUWOUGDVGIVTKRaFQKAYIyqErFArFAEE59AvL6r424CJAjVFi1BglRo0RKoeuUCgUAwYVoSsUCsUAQTl0hUKhGCAoh/4JIIRYLIQ4JIQoE0I8ZPD3bwkh9gsh9goh3hBCjOkLO/uSRGMUsd3tQggphBh0JWhmxkgI8dn2c6lUCPFSb9vY15j4ruUJId4SQuxq/77d2Bd29hlSSvU4jwehvsFHgHGADdgDTI3aZiGQ3P78AeDlvra7v41R+3ZDgL8DJcDsvra7v40RMBHYBWS0/z6sr+3uh2O0Gnig/flUoKKv7e7Nh4rQz5/LgDIpZbmU0gv8HlgauYGU8i0pZVv7ryUMPqnhhGPUzo+A/wDcvWlcP8HMGN0H/EJKWQ8gpTzTyzb2NWbGSAJp7c/TgepetK/PUQ79/DFqoh2v3c29wMYLalH/I+EYCSFmAaOllOt707B+hJnzqAAoEEJsFUKUCCEW95p1/QMzY/QYsLy94c4G4Ku9Y1r/oFebRA92hBDLgdnAVX1tS39CCKEBPwW+0Mem9HcshNIunyZ0l/d3IcR0KWVDXxrVz7gL+K2U8ikhxHzgBSHENCllsK8N6w1UhH7+mGqiLYS4Fvh34BYppaeXbOsvJBqjIcA0YIsQogKYB6wdZBOjZs6jSmCtlNInpTwKfEzIwQ8WzIzRvcArAFLK94EkQsJdgwLl0M+fjibaQggboSbaayM3EEIUAs8ScuaDLe8JCcZIStkopcySUuZLKfMJzTPcIqX8sG/M7RMSnkdAMaHoHCFEFqEUTHkv2tjXmBmj48A1AEKIKYQcek2vWtmHKId+nkgTTbSBlUAq8AchxG4hRPRJOKAxOUaDGpNjtAk4K4TYD7wFfEdKebZvLO59TI7Rg8B9Qog9wBrgC7K95GUwoJb+KxQKxQBBRegKhUIxQFAOXaFQKAYIyqErFArFAEE5dIVCoRggKIeuUCgUAwTl0BUKhWKAoBy6QqFQDBD+H5inWWZfINlhAAAAAElFTkSuQmCC\n",
+      "text/plain": [
+       "<Figure size 432x288 with 1 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "test_draws = ellipsoid_tree.sample_leaf_ellipsoids(1000)\n",
+    "test_draws = np.vstack(test_draws)\n",
+    "\n",
+    "plot_2d_ellipsoid_tree_leaves(ellipsoid_tree)\n",
+    "plt.scatter(test_draws[:, 0], test_draws[:, 1])\n",
+    "plt.show()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "# Inference for the egg box problem"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "We now illustrate inference for the [egg box problem](distribution-simple-egg-box.ipynb): this problem is highly multimodal and causes issues for MCMC methods. Here, for ease of visualisation and to further separate the modes, we transform the dimensions."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 7,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "class ExampleToy(pints.LogPDF):\n",
+    "    def __init__(self, sigma, r):\n",
+    "        self._sigma = sigma\n",
+    "        self._r = r\n",
+    "        self._log_toy = pints.toy.SimpleEggBoxLogPDF(self._sigma, self._r)\n",
+    "\n",
+    "    def __call__(self, x):\n",
+    "        x1 = np.copy(x)\n",
+    "        x1[0] = -15 + 30 * x[0]\n",
+    "        x1[1] = -15 + 30 * x[1]\n",
+    "        return self._log_toy(x1)\n",
+    "\n",
+    "    def n_parameters(self):\n",
+    "        return 2\n",
+    "\n",
+    "log_pdf = ExampleToy(2, 4)\n",
+    "log_prior = pints.UniformLogPrior(\n",
+    "    [0.0, 0.0],\n",
+    "    [1.0, 1.0])"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "We set up the MultiNest sampler."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 8,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "controller = pints.NestedController(log_pdf, log_prior, method=pints.MultiNestSampler)\n",
+    "\n",
+    "# Set number of iterations\n",
+    "controller.set_iterations(2000)\n",
+    "\n",
+    "# Set the number of posterior samples to generate\n",
+    "controller.set_n_posterior_samples(500)\n",
+    "\n",
+    "# Set threshold for updating ellipsoids as sampling runs\n",
+    "controller.sampler().set_f_s_threshold(1.1)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "We run the sampler: note that the ellipsoid tree may be updated as the sampler runs, resulting in differing numbers of ellipsoids in the decomposition over time."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 9,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Running MultiNest sampler\n",
+      "Number of active points: 400\n",
+      "Total number of iterations: 2000\n",
+      "Total number of posterior samples: 500\n",
+      "Iter. Eval. Time m:s Delta_log(z) Acceptance rate Ellipsoid count\n",
+      "0     1       0:00.0 -inf          1               0             \n",
+      "0     2       0:00.0 -inf          1               0             \n",
+      "0     21      0:00.0 -inf          1               0             \n",
+      "0     41      0:00.0 -inf          1               0             \n",
+      "0     61      0:00.0 -inf          1               0             \n",
+      "0     81      0:00.0 -inf          1               0             \n",
+      "0     101     0:00.0 -inf          1               0             \n",
+      "0     121     0:00.0 -inf          1               0             \n",
+      "0     141     0:00.0 -inf          1               0             \n",
+      "0     161     0:00.0 -inf          1               0             \n",
+      "0     181     0:00.0 -inf          1               0             \n",
+      "0     201     0:00.0 -inf          1               0             \n",
+      "0     221     0:00.0 -inf          1               0             \n",
+      "0     241     0:00.0 -inf          1               0             \n",
+      "0     261     0:00.0 -inf          1               0             \n",
+      "0     281     0:00.0 -inf          1               0             \n",
+      "0     301     0:00.0 -inf          1               0             \n",
+      "0     321     0:00.0 -inf          1               0             \n",
+      "0     341     0:00.0 -inf          1               0             \n",
+      "0     361     0:00.0 -inf          1               0             \n",
+      "0     381     0:00.0 -inf          1               0             \n",
+      "1     401     0:00.0 -inf          1               0             \n",
+      "20    420     0:00.1 -26.47739611  1               0             \n",
+      "40    443     0:00.1 -22.06893535  0.930232558     0             \n",
+      "60    464     0:00.1 -20.16303672  0.9375          0             \n",
+      "80    492     0:00.1 -18.72417949  0.869565217     0             \n",
+      "100   516     0:00.1 -17.55932358  0.862068966     0             \n",
+      "120   540     0:00.1 -16.67071423  0.857142857     0             \n",
+      "140   566     0:00.1 -15.66892492  0.843373494     0             \n",
+      "160   596     0:00.1 -14.77194615  0.816326531     0             \n",
+      "180   620     0:00.1 -14.01585566  0.818181818     0             \n",
+      "200   660     0:00.1 -13.34918485  0.769230769     0             \n",
+      "220   683     0:00.2 -12.68690594  0.777385159     6             \n",
+      "240   707     0:00.2 -12.13777023  0.781758958     6             \n",
+      "260   732     0:00.2 -11.68683326  0.78313253      6             \n",
+      "280   755     0:00.2 -11.25090396  0.788732394     6             \n",
+      "300   784     0:00.4 -10.8236012   0.78125         11            \n",
+      "320   816     0:00.4 -10.39824234  0.769230769     11            \n",
+      "340   846     0:00.4 -9.991615809  0.762331838565  11            \n",
+      "360   876     0:00.4 -9.534076237  0.756302521     11            \n",
+      "380   904     0:00.4 -9.111864914  0.753968254     11            \n",
+      "400   935     0:00.6 -8.706732445  0.747663551     13            \n",
+      "420   961     0:00.6 -8.337575378  0.748663102     13            \n",
+      "440   985     0:00.6 -7.977897313  0.752136752     13            \n",
+      "460   1011    0:00.6 -7.640450991  0.752864157     13            \n",
+      "480   1038    0:00.6 -7.293486624  0.752351097     13            \n",
+      "500   1067    0:00.7 -6.947293048  0.749625187     13            \n",
+      "520   1092    0:00.7 -6.631936042  0.751445087     13            \n",
+      "540   1118    0:00.7 -6.335494849  0.752089136     13            \n",
+      "560   1148    0:00.7 -6.057167873  0.748663102     13            \n",
+      "580   1179    0:00.8 -5.767704678  0.744544288     13            \n",
+      "600   1206    0:00.8 -5.501849863  0.744416873     12            \n",
+      "620   1232    0:00.8 -5.254619699  0.745192308     12            \n",
+      "640   1257    0:00.8 -5.01461809   0.746791132     12            \n",
+      "660   1281    0:00.9 -4.78781536   0.749148695     12            \n",
+      "680   1309    0:00.9 -4.570258569  0.748074807     12            \n",
+      "700   1340    0:00.9 -4.357508482  0.744680851     12            \n",
+      "720   1365    0:01.0 -4.154203071  0.74611399      12            \n",
+      "740   1388    0:01.0 -3.966046137  0.748987854251  12            \n",
+      "760   1416    0:01.0 -3.785922085  0.748031496063  12            \n",
+      "780   1445    0:01.0 -3.611913047  0.746411483     12            \n",
+      "800   1468    0:01.1 -3.446687328  0.749063670412  11            \n",
+      "820   1494    0:01.1 -3.286209601  0.749542962     11            \n",
+      "840   1526    0:01.1 -3.131452924  0.746003552     11            \n",
+      "860   1561    0:01.2 -2.982720609  0.740740741     11            \n",
+      "880   1593    0:01.2 -2.840834815  0.737636211     11            \n",
+      "900   1634    0:01.2 -2.704020298  0.729335494     11            \n",
+      "920   1661    0:01.3 -2.569379437  0.729579699     11            \n",
+      "940   1686    0:01.3 -2.440368763  0.730948678     11            \n",
+      "960   1715    0:01.3 -2.324819484  0.730038023     11            \n",
+      "980   1744    0:01.3 -2.207803647  0.729166667     11            \n",
+      "1000  1773    0:01.4 -2.095292865  0.728332119     11            \n",
+      "1020  1796    0:01.4 -1.988131432  0.730659025788  11            \n",
+      "1040  1819    0:01.4 -1.884870668  0.7329105       11            \n",
+      "1060  1846    0:01.4 -1.786987721  0.733056708     11            \n",
+      "1080  1876    0:01.4 -1.69338007   0.731707317     11            \n",
+      "1100  1906    0:01.5 -1.603866777  0.730411686587  13            \n",
+      "1120  1933    0:01.5 -1.518491298  0.730593607     13            \n",
+      "1140  1963    0:01.5 -1.437176066  0.729366603     13            \n",
+      "1160  1991    0:01.5 -1.360031158  0.729101194     13            \n",
+      "1180  2024    0:01.6 -1.287147831  0.726600985     13            \n",
+      "1200  2054    0:01.6 -1.217963249  0.725513906     11            \n",
+      "1220  2080    0:01.6 -1.152163621  0.726190476     11            \n",
+      "1240  2107    0:01.6 -1.0894747    0.726420621     11            \n",
+      "1260  2138    0:01.7 -1.029964191  0.724971231     11            \n",
+      "1280  2167    0:01.7 -0.973633     0.724391624     11            \n",
+      "1300  2196    0:01.7 -0.920013425  0.723830735     12            \n",
+      "1320  2222    0:01.8 -0.869149     0.724478595     12            \n",
+      "1340  2247    0:01.8 -0.821071     0.725500812     12            \n",
+      "1360  2273    0:01.8 -0.775557     0.726107848     12            \n",
+      "1380  2303    0:01.8 -0.732664     0.725170783     12            \n",
+      "1400  2333    0:01.9 -0.692227     0.724262804     13            \n",
+      "1420  2358    0:01.9 -0.654673     0.725229826     13            \n",
+      "1440  2386    0:01.9 -0.618655     0.725075529     13            \n",
+      "1460  2420    0:01.9 -0.584537     0.722772277     13            \n",
+      "1480  2452    0:01.9 -0.552342     0.721247563     13            \n",
+      "1500  2478    0:02.0 -0.522013     0.721847931     12            \n",
+      "Convergence obtained with Delta_z = -0.499001402113894\n",
+      "Done!\n"
+     ]
+    }
+   ],
+   "source": [
+    "samples = controller.run()\n",
+    "print('Done!')"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "We can plot the samples over the target density, and the draws appear to be a reasonable fit to the underlying density."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 10,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 432x288 with 1 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "# Contour plot of pdf\n",
+    "levels = np.linspace(-100, 0, 20)\n",
+    "x = np.linspace(0, 1, 100)\n",
+    "y = np.linspace(0, 1, 100)\n",
+    "X, Y = np.meshgrid(x, y)\n",
+    "Z = [[np.exp(log_pdf([i, j])) for i in x] for j in y]\n",
+    "\n",
+    "plt.figure()\n",
+    "plt.contour(X, Y, Z, colors='k')\n",
+    "plt.scatter(samples[:, 0], samples[:, 1], marker='.')\n",
+    "plt.show()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Throughout sampling, the number of ellipsoids in the decomposition can vary. We can, however, visualise the final decomposition used to draw sample points: note that, these ellipsoids will likely be smaller than the distribution of draws near the end of a sample run."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 11,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 432x288 with 1 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "et = controller.sampler().ellipsoid_tree()\n",
+    "plot_2d_ellipsoid_tree_leaves(et)\n",
+    "draws = [log_prior.convert_to_unit_cube(x) for x in samples]\n",
+    "draws = np.vstack(draws)\n",
+    "\n",
+    "plt.scatter(draws[:, 0], draws[:, 1], marker='.')\n",
+    "plt.show()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "We can print the effective sample size..."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 12,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "effective sample size = 1329.7641810152445\n"
+     ]
+    }
+   ],
+   "source": [
+    "print('effective sample size = ' + str(controller.effective_sample_size()))"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "...and print our estimate of the marginal likelihood."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 13,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "marginal log-likelihood = -5.455629903164397 ± 0.05887368649303134\n"
+     ]
+    }
+   ],
+   "source": [
+    "print('marginal log-likelihood = ' + str(controller.marginal_log_likelihood())\n",
+    "      + ' ± ' + str(controller.marginal_log_likelihood_standard_deviation()))"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Goodwin oscillator ODE model\n",
+    "We now use MultiNest to perform inference for the [Goodwin Oscillator model](../toy/model-goodwin-oscillator.ipynb), which can prove tricky for MCMC methods due to ripples in the posterior surface [1].\n",
+    "\n",
+    "[1] Estimating Bayes factors via thermodynamic integration and population MCMC. Ben Calderhead and Mark Girolami, 2009, Computational Statistics and Data Analysis."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 14,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 432x288 with 3 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "model = pints.toy.GoodwinOscillatorModel()\n",
+    "real_parameters = model.suggested_parameters()\n",
+    "times = model.suggested_times()\n",
+    "values = model.simulate(real_parameters, times)\n",
+    "\n",
+    "noise1 = 0.001\n",
+    "noise2 = 0.01\n",
+    "noise3 = 0.1\n",
+    "noisy_values = np.array(values, copy=True)\n",
+    "noisy_values[:, 0] += np.random.normal(0, noise1, len(times))\n",
+    "noisy_values[:, 1] += np.random.normal(0, noise2, len(times))\n",
+    "noisy_values[:, 2] += np.random.normal(0, noise3, len(times))\n",
+    "\n",
+    "plt.figure()\n",
+    "plt.subplot(3, 1, 1)\n",
+    "plt.plot(times, noisy_values[:, 0], 'b')\n",
+    "plt.subplot(3, 1, 2)\n",
+    "plt.plot(times, noisy_values[:, 1], 'g')\n",
+    "plt.subplot(3, 1, 3)\n",
+    "plt.plot(times, noisy_values[:, 2], 'r')\n",
+    "plt.show()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 15,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Running MultiNest sampler\n",
+      "Number of active points: 400\n",
+      "Total number of iterations: 20000\n",
+      "Total number of posterior samples: 2000\n",
+      "Iter. Eval.  Time m:s Delta_log(z) Acceptance rate Ellipsoid count\n",
+      "0     1        0:00.0 -inf          1               0             \n",
+      "0     2        0:00.0 -inf          1               0             \n",
+      "0     21       0:00.1 -inf          1               0             \n",
+      "0     41       0:00.2 -inf          1               0             \n",
+      "0     61       0:00.4 -inf          1               0             \n",
+      "0     81       0:00.6 -inf          1               0             \n",
+      "0     101      0:00.7 -inf          1               0             \n",
+      "0     121      0:00.8 -inf          1               0             \n",
+      "0     141      0:00.9 -inf          1               0             \n",
+      "0     161      0:01.1 -inf          1               0             \n",
+      "0     181      0:01.2 -inf          1               0             \n",
+      "0     201      0:01.3 -inf          1               0             \n",
+      "0     221      0:01.4 -inf          1               0             \n",
+      "0     241      0:01.5 -inf          1               0             \n",
+      "0     261      0:01.6 -inf          1               0             \n",
+      "0     281      0:01.8 -inf          1               0             \n",
+      "0     301      0:01.9 -inf          1               0             \n",
+      "0     321      0:02.0 -inf          1               0             \n",
+      "0     341      0:02.1 -inf          1               0             \n",
+      "0     361      0:02.2 -inf          1               0             \n",
+      "0     381      0:02.4 -inf          1               0             \n",
+      "1     401      0:02.5 -inf          1               0             \n",
+      "20    420      0:02.6 -3898615.859  1               0             \n",
+      "40    440      0:02.7 -1495897.382  1               0             \n",
+      "60    460      0:02.9 -958726.4035  1               0             \n",
+      "80    483      0:03.0 -620400.6978  0.963855422     0             \n",
+      "100   507      0:03.2 -457686.3768  0.934579439     0             \n",
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+      "9260  49197    2:24.6 -8.111349479  0.189765764     13            \n",
+      "9280  49239    2:24.7 -7.922758724  0.190012081     13            \n",
+      "9300  49281    2:24.9 -7.738361889  0.190257973     12            \n",
+      "9320  49324    2:25.0 -7.561224262  0.19049955      12            \n",
+      "9340  49363    2:25.1 -7.39076479   0.190756285     12            \n"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "9360  49412    2:25.2 -7.224806038  0.190973639     12            \n",
+      "9380  49453    2:25.3 -7.059287298  0.19122174      12            \n",
+      "9400  49507    2:25.5 -6.896832277  0.191418739     12            \n",
+      "9420  49547    2:25.6 -6.741212594  0.191669888     12            \n",
+      "9440  49592    2:25.7 -6.590507261  0.191901122     12            \n",
+      "9460  49635    2:25.8 -6.444746493  0.192139738     12            \n",
+      "9480  49687    2:25.9 -6.302223922  0.192342808     12            \n",
+      "9500  49736    2:26.2 -6.162441386  0.192557159     11            \n",
+      "9520  49778    2:26.2 -6.018761071  0.192798412     11            \n",
+      "9540  49821    2:26.3 -5.876014301  0.193035349     11            \n",
+      "9560  49851    2:26.4 -5.734472367  0.19332268306   11            \n",
+      "9580  49897    2:26.5 -5.593907546  0.193547084     11            \n",
+      "9600  49947    2:26.7 -5.453987827  0.193755424     11            \n",
+      "9620  49979    2:26.7 -5.316109307  0.194033764     11            \n",
+      "9640  50013    2:26.8 -5.177289955  0.194303912     11            \n",
+      "9660  50045    2:26.9 -5.039143771  0.194581529     11            \n",
+      "9680  50098    2:27.0 -4.904401714  0.19477645      11            \n",
+      "9700  50136    2:27.2 -4.773769716  0.195029757     10            \n",
+      "9720  50169    2:27.3 -4.645863124  0.195302297     10            \n",
+      "9740  50212    2:27.4 -4.520004976  0.195535212     10            \n",
+      "9760  50245    2:27.5 -4.396628408  0.195807002     10            \n",
+      "9780  50279    2:27.5 -4.272196976  0.1960745       10            \n",
+      "9800  50316    2:27.7 -4.148821038  0.196329834     13            \n",
+      "9820  50363    2:27.8 -4.028162844  0.196545444     13            \n",
+      "9840  50399    2:27.9 -3.909234986  0.196803936     13            \n",
+      "9860  50429    2:28.0 -3.793298621  0.19708569      13            \n",
+      "9880  50465    2:28.1 -3.68131967   0.197343454     13            \n",
+      "9900  50508    2:28.3 -3.572307598  0.197573242     1             \n",
+      "9920  50551    2:28.4 -3.466243726  0.197802636     1             \n",
+      "9940  50599    2:28.5 -3.362231731  0.198011913     1             \n",
+      "9960  50643    2:28.6 -3.260612005  0.19823657      1             \n",
+      "9980  50677    2:28.6 -3.162088784  0.198500308     1             \n",
+      "10000 50722    2:28.8 -3.065357802  0.198720242     11            \n",
+      "10020 50753    2:28.9 -2.970708257  0.198995095     11            \n",
+      "10040 50799    2:29.0 -3.033440054  0.199210302     11            \n",
+      "10060 50846    2:29.1 -2.939760312  0.199421163224  11            \n",
+      "10080 50900    2:29.2 -2.848432532  0.199603960396  11            \n",
+      "10100 50964    2:29.4 -2.758075969  0.199746855     12            \n",
+      "10120 50998    2:29.5 -2.669348498  0.200007905     12            \n",
+      "10140 51029    2:29.6 -2.582887355  0.200280472     12            \n",
+      "10160 51074    2:29.7 -2.51053117   0.200497296     12            \n",
+      "10180 51112    2:29.8 -2.427590831  0.200741442     12            \n",
+      "10200 51165    2:29.9 -2.347141174  0.200925835     1             \n",
+      "10220 51214    2:30.0 -2.268984247  0.201125674     1             \n",
+      "10240 51259    2:30.1 -2.19254603   0.201340962     1             \n",
+      "10260 51318    2:30.3 -2.118087463  0.201500452     1             \n",
+      "10280 51363    2:30.4 -2.045369311  0.20171497      1             \n",
+      "10300 51403    2:30.5 -2.050694508  0.201948905     13            \n",
+      "10320 51446    2:30.6 -1.980619249  0.202170591     13            \n",
+      "10340 51496    2:30.7 -1.912498738  0.202364177235  13            \n",
+      "10360 51533    2:30.8 -1.845712468  0.202608883     13            \n",
+      "10380 51575    2:30.9 -1.780404274  0.202833415     13            \n",
+      "10400 51610    2:31.0 -1.716745688  0.203085335     13            \n",
+      "10420 51642    2:31.1 -1.654243978  0.203348815     13            \n",
+      "10440 51688    2:31.2 -1.593281034  0.203556387     13            \n",
+      "10460 51735    2:31.3 -1.533760105  0.203759618     13            \n",
+      "10480 51784    2:31.4 -1.475686876  0.203954538     13            \n",
+      "10500 51826    2:31.6 -1.419189481  0.204176876     1             \n",
+      "10520 51860    2:31.7 -1.364308425  0.204430626     1             \n",
+      "10540 51913    2:31.8 -1.310955036  0.204608545     1             \n",
+      "10560 51973    2:31.9 -1.259040694  0.204758304     1             \n",
+      "10580 52030    2:32.0 -1.208648409  0.20491962      1             \n",
+      "10600 52110    2:32.3 -1.159634988  0.204989364     1             \n",
+      "10620 52177    2:32.4 -1.112260089  0.205110377     1             \n",
+      "10640 52219    2:32.5 -1.066446574  0.205330091     1             \n",
+      "10660 52267    2:32.6 -1.022015917  0.205525671     1             \n",
+      "10680 52310    2:32.7 -0.979101     0.205740705     1             \n",
+      "10700 52348    2:32.8 -0.937575     0.205975206     1             \n",
+      "10720 52398    2:32.9 -0.897351     0.206161775     1             \n",
+      "10740 52433    2:33.0 -0.858589342  0.206407472     1             \n",
+      "10760 52471    2:33.1 -0.821255     0.206640933     1             \n",
+      "10780 52512    2:33.2 -0.824242     0.206862143     1             \n",
+      "10800 52547    2:33.3 -0.788372     0.207106833     1             \n",
+      "10820 52581    2:33.4 -0.753874     0.207355168     1             \n",
+      "10840 52627    2:33.5 -0.720680643  0.207555479     1             \n",
+      "10860 52660    2:33.5 -0.688704401  0.207807118     1             \n",
+      "10880 52697    2:33.6 -0.657879     0.208042526     1             \n",
+      "10900 52729    2:33.8 -0.628205     0.208297502341  1             \n",
+      "10920 52769    2:33.8 -0.599691     0.208520308     1             \n",
+      "10940 52804    2:33.9 -0.572286795  0.208762689871  1             \n",
+      "10960 52839    2:34.0 -0.545952     0.209004748     1             \n",
+      "10980 52881    2:34.1 -0.520693     0.209218574     1             \n",
+      "Convergence obtained with Delta_z = -0.49886900881665497\n",
+      "Done!\n"
+     ]
+    }
+   ],
+   "source": [
+    "# Create an object with links to the model and time series\n",
+    "problem = pints.MultiOutputProblem(model, times, values)\n",
+    "\n",
+    "# Create a log posterior\n",
+    "log_prior = pints.UniformLogPrior([1, 1, 0.01, 0.01, 0.01], [10, 10, 1, 1, 1])\n",
+    "log_likelihood = pints.GaussianKnownSigmaLogLikelihood(problem, [noise1, noise2, noise3])\n",
+    "log_posterior = pints.LogPosterior(log_likelihood, log_prior)\n",
+    "\n",
+    "# Run MCMC on the noisy data\n",
+    "controller = pints.NestedController(log_likelihood, log_prior, method=pints.MultiNestSampler)\n",
+    "# Set number of iterations\n",
+    "controller.set_iterations(20000)\n",
+    "\n",
+    "# Set the number of posterior samples to generate\n",
+    "controller.set_n_posterior_samples(2000)\n",
+    "\n",
+    "# Set threshold for updating ellipsoids as sampling runs\n",
+    "controller.sampler().set_f_s_threshold(1.01)\n",
+    "\n",
+    "samples = controller.run()\n",
+    "print('Done!')"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "The approach produces samples close to the generating parameter values."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 16,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 1080x1080 with 25 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "import pints.plot\n",
+    "\n",
+    "pints.plot.pairwise(samples, kde=True, ref_parameters=real_parameters)\n",
+    "plt.show()"
+   ]
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.9.2"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 2
+}
diff --git a/examples/sampling/nested-rejection-sampling.ipynb b/examples/sampling/nested-rejection-sampling.ipynb
index 9a5f9c2c5c..74685f55fc 100644
--- a/examples/sampling/nested-rejection-sampling.ipynb
+++ b/examples/sampling/nested-rejection-sampling.ipynb
@@ -27,9 +27,8 @@
    "outputs": [
     {
      "data": {
-      "image/png": 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mQBWgJVDfWzX7p7fWgrmowJhPjTHNjTHNy5Url3vBqkLBGMPYxXtoGpbJjcse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\nUl79Py8Vf46yyd8dAAAAAElFTkSuQmCC\n",
       "text/plain": [
-       "<matplotlib.figure.Figure at 0x269e9f3dbe0>"
+       "<Figure size 640x480 with 1 Axes>"
       ]
      },
      "metadata": {},
@@ -92,13 +91,14 @@
     "    [0.02, 600, sigma * 1.5])\n",
     "\n",
     "# Create a nested ellipsoidal rejectection sampler\n",
-    "sampler = pints.NestedController(log_likelihood, log_prior, method=pints.NestedRejectionSampler)\n",
+    "controller = pints.NestedController(log_likelihood, log_prior,\n",
+    "                                    method=pints.NestedRejectionSampler)\n",
     "\n",
     "# Set number of iterations\n",
-    "sampler.set_iterations(3000)\n",
+    "controller.set_iterations(3000)\n",
     "\n",
     "# Set the number of posterior samples to generate\n",
-    "sampler.set_n_posterior_samples(300)"
+    "controller.set_n_posterior_samples(300)"
    ]
   },
   {
@@ -143,169 +143,169 @@
       "0     341     0:00.0 -inf          1             \n",
       "0     361     0:00.0 -inf          1             \n",
       "0     381     0:00.0 -inf          1             \n",
-      "1     401     0:00.0 -inf          1             \n",
-      "20    421     0:00.0 -12522.86197  0.952380952381\n",
-      "40    443     0:00.1 -8692.935714  0.930232558   \n",
-      "60    464     0:00.1 -6749.535314  0.9375        \n",
-      "80    487     0:00.1 -5960.760661  0.91954023    \n",
-      "100   508     0:00.1 -5169.161112  0.925925926   \n",
-      "120   538     0:00.1 -4484.11497   0.869565217   \n",
-      "140   565     0:00.1 -4045.815411  0.848484848   \n",
-      "160   595     0:00.1 -3457.238432  0.820512821   \n",
-      "180   624     0:00.1 -3156.197327  0.803571429   \n",
-      "200   657     0:00.1 -2915.104877  0.778210117   \n",
-      "220   702     0:00.1 -2656.953402  0.728476821   \n",
-      "240   741     0:00.1 -2518.454139  0.703812317   \n",
-      "260   771     0:00.1 -2328.10491   0.700808625   \n",
-      "280   820     0:00.2 -2195.132374  0.666666667   \n",
-      "300   865     0:00.2 -2082.977906  0.64516129    \n",
-      "320   915     0:00.2 -1942.591729  0.621359223301\n",
-      "340   963     0:00.2 -1800.001913  0.603907638   \n",
-      "360   998     0:00.2 -1689.27647   0.602006689   \n",
-      "380   1043    0:00.2 -1604.018798  0.590979782   \n",
-      "400   1114    0:00.2 -1492.391812  0.56022409    \n",
-      "420   1165    0:00.3 -1399.565096  0.549019608   \n",
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+      "2580  297016   0:50.8 -11.51509843  0.00869811473 \n",
+      "2600  312037   0:53.3 -11.29343101  0.00834304014 \n",
+      "2620  326262   0:55.7 -10.95623882  0.00804021334 \n",
+      "2640  344124   0:58.7 -10.62452491  0.00768058093 \n",
+      "2660  360308   1:01.4 -10.3098841   0.00739077764 \n",
+      "2680  377458   1:04.3 -10.0042378   0.00710765983 \n",
+      "2700  407716   1:09.3 -9.708113539  0.00662875998 \n",
+      "2720  430348   1:13.1 -9.412404812  0.00632634644 \n",
+      "2740  445634   1:15.6 -9.133782756  0.0061540673  \n",
+      "2760  461597   1:18.3 -8.858494678  0.00598442748 \n"
      ]
     },
     {
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "2780  352438   0:38.4 -14.39155097  0.00789687477 \n",
-      "2800  370071   0:42.8 -14.02172634  0.00757430256 \n",
-      "2820  403182   0:52.8 -13.6535636   0.00700130592 \n",
-      "2840  419444   0:57.0 -13.56274993  0.00677733126 \n",
-      "2860  433167   1:00.5 -13.22855669  0.00660863698 \n",
-      "2880  450780   1:05.1 -12.90779864  0.00639460012 \n",
-      "2900  475464   1:11.2 -12.57087746  0.00610444066 \n",
-      "2920  497775   1:16.3 -12.24281505  0.00587082181 \n",
-      "2940  523789   1:22.0 -11.90509479  0.00561723689 \n",
-      "2960  553972   1:24.9 -11.587114    0.00534709125 \n",
-      "2980  584939   1:27.3 -11.29146672  0.00509803452 \n",
-      "3000  608174   1:29.2 -10.9867037   0.00493604531 \n",
+      "2780  494454   1:23.8 -8.59312693   0.00562691528 \n",
+      "2800  513224   1:27.1 -8.327023384  0.00545996287 \n",
+      "2820  527710   1:29.5 -8.07206578   0.00534789782 \n",
+      "2840  570810   1:36.8 -7.829762015  0.00497887484 \n",
+      "2860  611144   1:43.6 -7.5831031    0.00468281309 \n",
+      "2880  635213   1:47.6 -7.337569902  0.0045367691  \n",
+      "2900  667476   1:53.1 -7.109125217  0.00434733074 \n",
+      "2920  695999   1:57.8 -6.883899604  0.00419782087 \n",
+      "2940  742824   2:05.7 -6.665736839  0.00396000129 \n",
+      "2960  789070   2:13.5 -6.45399732   0.00375315404 \n",
+      "2980  825905   2:19.7 -6.243942136  0.00360991151 \n",
+      "3000  861019   2:25.7 -6.042052004  0.00348586308 \n",
       "Done!\n"
      ]
     }
    ],
    "source": [
-    "samples = sampler.run()\n",
+    "samples = controller.run()\n",
     "print('Done!')"
    ]
   },
@@ -316,6 +316,13 @@
     "## Plot posterior samples versus true parameter values (dashed lines)"
    ]
   },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "The nested rejection sampler is quite inefficient at generating posterior samples because it generates proposals by sampling directly from the prior: if the prior is wide relative to the region of high probability mass, then the probability a proposal passes the current threshold is typically low. [Nested ellipsoidal sampling](nested-ellipsoidal-sampling.ipynb) improves on this dramatically by sampling from ellipsoids known to contain high density regions."
+   ]
+  },
   {
    "cell_type": "code",
    "execution_count": 4,
@@ -323,12 +330,14 @@
    "outputs": [
     {
      "data": {
-      "image/png": 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F8DZJswEi4tGI+EBE7AN8j2z/cd4cjVKJbU67uV5Iw/PT9KK6UC5im4mI36bnP5Ede+vc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\ns+zGZMXp6oi4MU3+naQRqfU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\n",
       "text/plain": [
-       "<matplotlib.figure.Figure at 0x269e9f399b0>"
+       "<Figure size 432x432 with 3 Axes>"
       ]
      },
-     "metadata": {},
+     "metadata": {
+      "needs_background": "light"
+     },
      "output_type": "display_data"
     }
    ],
@@ -350,12 +359,14 @@
    "outputs": [
     {
      "data": {
-      "image/png": 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P8VpykhNHYPsi5niuDEz7dW/k+jF7eSdkOB+FvkeCjWGhpybLPFVgd2koURccF3NOrYiI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\ni8Visfg91uCxWCwWi8Xi9/wf/t2Lb67gbm4AAAAASUVORK5CYII=\n",
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\n",
       "text/plain": [
-       "<matplotlib.figure.Figure at 0x269f5080470>"
+       "<Figure size 648x648 with 9 Axes>"
       ]
      },
-     "metadata": {},
+     "metadata": {
+      "needs_background": "light"
+     },
      "output_type": "display_data"
     }
    ],
@@ -380,12 +391,14 @@
    "outputs": [
     {
      "data": {
-      "image/png": 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EWyd/X97x5qotPOyaQGyvsJL/6nX4mmJpf8mj9IkJ4pJevkwcMci1do2FjIwM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\nbn4fEQ+k4reLw/Lpdksq93txaBYAX5W0gWyq9RS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\n",
       "text/plain": [
-       "<matplotlib.figure.Figure at 0x269f4f14390>"
+       "<Figure size 576x216 with 1 Axes>"
       ]
      },
-     "metadata": {},
+     "metadata": {
+      "needs_background": "light"
+     },
      "output_type": "display_data"
     }
    ],
@@ -415,13 +428,13 @@
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "marginal log-likelihood = -368.1116589772709 ± 0.08064572183322265\n"
+      "marginal log-likelihood = -387.9780391557456 ± 0.08039718473286823\n"
      ]
     }
    ],
    "source": [
-    "print('marginal log-likelihood = ' + str(sampler.marginal_log_likelihood())\n",
-    "      + ' ± ' + str(sampler.marginal_log_likelihood_standard_deviation()))"
+    "print('marginal log-likelihood = ' + str(controller.marginal_log_likelihood())\n",
+    "      + ' ± ' + str(controller.marginal_log_likelihood_standard_deviation()))"
    ]
   },
   {
@@ -438,19 +451,22 @@
    "outputs": [
     {
      "data": {
-      "image/png": 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IIiIyzEwvz6MoJ52XN+ztv3IcxDKQ4GtmdhFwCsHotVvDIc8iIjLMpKQY1VOK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\n8MtoB5pZBTAOmGBmeRG7xhP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\n",
       "text/plain": [
-       "<matplotlib.figure.Figure at 0x269f562b748>"
+       "<Figure size 432x288 with 1 Axes>"
       ]
      },
-     "metadata": {},
+     "metadata": {
+      "needs_background": "light"
+     },
      "output_type": "display_data"
     }
    ],
    "source": [
-    "v_log_likelihood = sampler.log_likelihood_vector()\n",
-    "v_log_likelihood = v_log_likelihood[:-sampler._sampler.n_active_points()]\n",
-    "X = sampler.prior_space()\n",
+    "n_active_points = controller.sampler().n_active_points()\n",
+    "v_log_likelihood = controller.log_likelihood_vector()\n",
+    "v_log_likelihood = v_log_likelihood[:-n_active_points]\n",
+    "X = controller.prior_space()\n",
     "X = X[:-1]\n",
     "plt.plot(X, v_log_likelihood)\n",
     "plt.xlabel('prior volume enclosed by X(L) > L')\n",
@@ -481,18 +497,20 @@
    "outputs": [
     {
      "data": {
-      "image/png": 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iRtmD4ydx4074/bkgi2cevl+ZK2xzblUt4dR0KXZaly7PWXfeqekSxt640BLa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\nNh2xJWVP6rcEMjQRSOoY0FG0miRokaKJwTUKFJnB6TZKCMGJ1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sLWu6zHq72Wn9YTdmx2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\nSUVORK5CYII=\n",
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\n",
       "text/plain": [
-       "<matplotlib.figure.Figure at 0x269f525f048>"
+       "<Figure size 1080x432 with 3 Axes>"
       ]
      },
-     "metadata": {},
+     "metadata": {
+      "needs_background": "light"
+     },
      "output_type": "display_data"
     }
    ],
    "source": [
-    "m_active = sampler.active_points()\n",
-    "m_inactive = sampler.inactive_points()\n",
+    "m_active = controller.active_points()\n",
+    "m_inactive = controller.inactive_points()\n",
     "\n",
     "f, axarr = plt.subplots(1,3,figsize=(15,6))\n",
     "axarr[0].scatter(m_inactive[:,0],m_inactive[:,1])\n",
@@ -529,21 +547,25 @@
   {
    "cell_type": "code",
    "execution_count": 10,
-   "metadata": {},
+   "metadata": {
+    "scrolled": true
+   },
    "outputs": [
     {
      "data": {
-      "image/png": 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M+4lMIhgR8TkfRD5FuSOmeImIiJQs+Z20fAlwEbAfwDm3GS1HD76dq6BKHERGF8392g/2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lbWecbcvycvi33diXbtmhVoautQoXp9tq1agLVLRfSMzdg3bwLGpV1xaNbznedLCg9Gr2jJfPWt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\nCXyZ9AZ5cG4N+B1QSLFTnw3A9lhJs0l9M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\n",
       "text/plain": [
-       "<matplotlib.figure.Figure at 0x269f552ef98>"
+       "<Figure size 648x648 with 9 Axes>"
       ]
      },
-     "metadata": {},
+     "metadata": {
+      "needs_background": "light"
+     },
      "output_type": "display_data"
     }
    ],
    "source": [
-    "samples_new = sampler.sample_from_posterior(1000)\n",
+    "samples_new = controller.sample_from_posterior(1000)\n",
     "\n",
     "pints.plot.pairwise(samples_new, kde=True)\n",
     "\n",
@@ -567,7 +589,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.6.3"
+   "version": "3.7.7"
   }
  },
  "nbformat": 4,
diff --git a/pints/__init__.py b/pints/__init__.py
index f9f8153848..9c799a2274 100644
--- a/pints/__init__.py
+++ b/pints/__init__.py
@@ -241,6 +241,7 @@ def version(formatted=False):
 from ._nested import NestedController
 from ._nested._rejection import NestedRejectionSampler
 from ._nested._ellipsoid import NestedEllipsoidSampler
+from ._nested._multinest import MultiNestSampler
 
 
 #
diff --git a/pints/_log_priors.py b/pints/_log_priors.py
index 27064efda2..7b038ac6e8 100644
--- a/pints/_log_priors.py
+++ b/pints/_log_priors.py
@@ -877,7 +877,7 @@ def pseudo_cdf(self, xs):
             u_2 = \int_{-\infty}^{\theta_2} \pi_2(\theta_2|\theta_1)d\theta_2
 
         So that we return a vector of cdfs (u_1,u_2,...,u_d).
-        Note that, this function is mainly to facilitate Multinest sampling
+        Note that, this function is mainly to facilitate MultiNest sampling
         since the distribution (u_1,u_2,...,u_d) is uniform within the unit
         cube.
         """
@@ -934,7 +934,7 @@ def pseudo_icdf(self, ps):
             u_2 = \int_{-\infty}^{\theta_2} \pi_2(\theta_2|\theta_1)d\theta_2
 
         So that we return a vector of icdfs (theta_1,theta_2,...,theta_d)
-        Note that, this function is mainly to facilitate Multinest sampling
+        Note that, this function is mainly to facilitate MultiNest sampling
         since the distribution (u_1,u_2,...,u_d) is uniform within the unit
         cube.
         """
diff --git a/pints/_nested/__init__.py b/pints/_nested/__init__.py
index d06a7ccf75..22c294116f 100644
--- a/pints/_nested/__init__.py
+++ b/pints/_nested/__init__.py
@@ -9,6 +9,7 @@
 from __future__ import print_function, unicode_literals
 import pints
 import numpy as np
+import scipy.special
 
 try:
     from scipy.special import logsumexp
@@ -49,6 +50,10 @@ def __init__(self, log_prior):
         self._accept_count = 0
         self._n_evals = 0
 
+        # multiple ellipsoid indicator
+        self._multiple_ellipsoids = False
+        self._ellipsoid_count = 0
+
     def active_points(self):
         """
         Returns the active points from nested sampling run.
@@ -414,6 +419,8 @@ def _initialise_logger(self):
             self._logger.add_time('Time m:s')
             self._logger.add_float('Delta_log(z)')
             self._logger.add_float('Acceptance rate')
+            if self._sampler._multiple_ellipsoids:
+                self._logger.add_float('Ellipsoid count')
 
     def _initial_points(self):
         """
@@ -429,8 +436,12 @@ def _initial_points(self):
             # Show progress
             if self._logging and i >= self._next_message:
                 # Log state
-                self._logger.log(0, self._sampler._n_evals,
-                                 self._timer.time(), self._diff, 1.0)
+                if not self._sampler._multiple_ellipsoids:
+                    self._logger.log(0, self._sampler._n_evals,
+                                     self._timer.time(), self._diff, 1.0)
+                else:
+                    self._logger.log(0, self._sampler._n_evals,
+                                     self._timer.time(), self._diff, 1.0, 0.0)
 
                 # Choose next logging point
                 if i > self._message_warm_up:
@@ -667,6 +678,10 @@ def run(self):
 
         return self._m_posterior_samples
 
+    def sampler(self):
+        """ Returns the underlying :class:`NestedSampler` object. """
+        return self._sampler
+
     def sample_from_posterior(self, posterior_samples):
         """
         Draws posterior samples based on nested sampling run using importance
@@ -780,13 +795,188 @@ def _update_logger(self):
             self._i_message += 1
             if self._i_message >= self._next_message:
                 # Log state
-                self._logger.log(self._i_message, self._sampler._n_evals,
-                                 self._timer.time(), self._diff,
-                                 float(self._sampler._accept_count /
-                                       (self._sampler._n_evals -
-                                        self._sampler._n_active_points)))
+                if not self._sampler._multiple_ellipsoids:
+                    self._logger.log(self._i_message, self._sampler._n_evals,
+                                     self._timer.time(), self._diff,
+                                     float(self._sampler._accept_count /
+                                           (self._sampler._n_evals -
+                                            self._sampler._n_active_points)))
+                else:
+                    self._logger.log(self._i_message, self._sampler._n_evals,
+                                     self._timer.time(), self._diff,
+                                     float(self._sampler._accept_count /
+                                           (self._sampler._n_evals -
+                                            self._sampler._n_active_points)),
+                                     self._sampler._ellipsoid_count)
 
                 # Choose next logging point
                 if self._i_message > self._message_warm_up:
                     self._next_message = self._message_interval * (
                         1 + self._i_message // self._message_interval)
+
+
+class Ellipsoid():
+    """
+    A class to represent N dimensional ellipsoids, which are needed by both
+    ellipsoidal nested sampling and MultiNest.
+
+    In "center form" the equation of an ellipsoid is given by:
+
+    ``(x-c).T * A * (x-c) = 1``
+
+    where ``A`` is a NxN dimensional positive definite symmetric matrix and
+    ``c`` is a N dimensional vector indicating the center of the ellipsoid.
+
+    Parameters
+    ----------
+    A : NxN dimensional positive definite symmetric matrix
+        represents the orientation and size of ellipsoid
+    c : N dimensional vector
+        center of ellipsoid
+    """
+    def __init__(self, A, c):
+
+        self._c = c
+        self._n_parameters = len(c)
+
+        if A.shape != (self._n_parameters, self._n_parameters):
+            raise ValueError(
+                'Sigma must have same dimension as mean, or be a square ' +
+                'matrix with the same dimension as the center.')
+        self._A = np.copy(A)
+
+        # calculate useful quantities
+        self._A_inv = np.linalg.inv(A)
+        # don't calculate volume unless needed
+        self._volume = None
+
+        # don't cache points unless constructed using minimum_volume_ellipsoid
+        self._points = None
+        self._n_points = 0
+
+    def set_points(self, points):
+        """ Sets points contained within bounding ellipsoid. """
+        self._points = points
+        self._n_points = len(points)
+
+    def centroid(self):
+        """ Returns centroid of ellipsoid. """
+        return self._c
+
+    def enlarge(self, enlargement_factor):
+        """ Enlarges ellipsoid by a factor. """
+        self._A *= (1 / enlargement_factor)
+        self._A_inv *= enlargement_factor
+        self._volume = None
+
+    @staticmethod
+    def mahalanobis_distance(point, A, c):
+        """
+        Finds Mahalanobis distance between a point and the centroid of
+        of an ellipsoid.
+        """
+        return np.matmul(np.matmul(point - c, A), point - c)
+
+    @classmethod
+    def minimum_volume_ellipsoid(cls, points):
+        """
+        Creates an approximate minimum bounding ellipsoid in "center form":
+        ``(x-c).T * A * (x-c) = 1``.
+        """
+        cov = np.cov(np.transpose(points))
+        cov_inv = np.linalg.inv(cov)
+        c = np.mean(points, axis=0)
+        dist = np.zeros(len(points))
+        for i in range(len(points)):
+            dist[i] = Ellipsoid.mahalanobis_distance(points[i], cov_inv, c)
+        enlargement_factor = np.max(dist)
+        A = (1.0 / enlargement_factor) * cov_inv
+        obj = cls(A, c)
+        obj.set_points(points)
+        return obj
+
+    def n_points(self):
+        """ Returns number of points within bounding ellipsoid. """
+        return self._n_points
+
+    def points(self):
+        """ Returns points within bounding ellipsoid. """
+        return self._points
+
+    def sample(self, npts, enlargement_factor=1):
+        """
+        Draws ``npts`` random uniform points from within the ellipsoid.
+
+        Most of this functionality has been borrowed from:
+        http://www.astro.gla.ac.uk/~matthew/blog/?p=368
+        """
+        ndims = self._n_parameters
+        covmat = self._A_inv * enlargement_factor
+        cent = self._c
+
+        # calculate eigen_values (e) and eigen_vectors (v)
+        eigen_values, eigen_vectors = np.linalg.eig(covmat)
+        idx = (-eigen_values).argsort()[::-1][:ndims]
+        e = eigen_values[idx]
+        v = eigen_vectors[:, idx]
+        e = np.diag(e)
+
+        # generate radii of hyperspheres
+        rs = np.random.uniform(0, 1, npts)
+
+        # generate points
+        pt = np.random.normal(0, 1, [npts, ndims])
+
+        # get scalings for each point onto the surface of a unit
+        # hypersphere
+        fac = np.sum(pt**2, axis=1)
+
+        # calculate scaling for each point to be within the unit
+        # hypersphere with radii rs
+        fac = (rs**(1 / ndims)) / np.sqrt(fac)
+        pnts = np.zeros((npts, ndims))
+
+        # scale points to the ellipsoid using the eigen_values and rotate
+        # with the eigen_vectors and add centroid
+        d = np.sqrt(np.diag(e))
+        d.shape = (ndims, 1)
+
+        for i in range(0, npts):
+            # scale points to a uniform distribution within unit
+            # hypersphere
+            pnts[i, :] = fac[i] * pt[i, :]
+            pnts[i, :] = np.dot(
+                np.multiply(pnts[i, :], np.transpose(d)),
+                np.transpose(v)
+            ) + cent
+
+        if npts > 1:
+            return pnts
+        else:
+            return pnts[0]
+
+    def volume(self):
+        """
+        Calculates volume of ellipsoid.
+        See: https://math.stackexchange.com/questions/2751632/solve-for-volume-of-ellipsoid-mathbb-x-mathbf-mut-sigma-1-mathbb-x # noqa
+        """
+        if self._volume is None:
+            d = self._n_parameters
+            r = np.linalg.det(self._A_inv)
+            vol = (
+                (np.pi**(d / 2.0) / scipy.special.gamma((d / 2.0) + 1.0))
+                * np.sqrt(r)
+            )
+            # cache volume calculation to avoid recomputation
+            self._volume = vol
+        return self._volume
+
+    def weight_matrix(self):
+        """ Returns weight matrix. """
+        return self._A
+
+    def within_ellipsoid(self, point):
+        """ Determines if point is within ellipsoid. """
+        return Ellipsoid.mahalanobis_distance(point,
+                                              self.weight_matrix(),
+                                              self.centroid()) <= 1
diff --git a/pints/_nested/_ellipsoid.py b/pints/_nested/_ellipsoid.py
index c0bd9204de..bc7bbdccb9 100644
--- a/pints/_nested/_ellipsoid.py
+++ b/pints/_nested/_ellipsoid.py
@@ -10,6 +10,7 @@
 from __future__ import print_function, unicode_literals
 import pints
 import numpy as np
+from pints._nested.__init__ import Ellipsoid
 
 
 class NestedEllipsoidSampler(pints.NestedSampler):
@@ -69,13 +70,19 @@ class NestedEllipsoidSampler(pints.NestedSampler):
                 )
             endif
         endif
+        L_min = min(L)
+        indexmin = min_index(L)
         theta* = ellipsoid_sample(enlargement_factor, A, c)
         while p(theta*|X) < L_min:
             theta* = ellipsoid_sample(enlargement_factor, A, c)
         endwhile
+        X_t = exp(-t / n_active_points)
+        w_t = X_t - X_t-1
+        Z = Z + L_min * w_t
         theta_indexmin = theta*
         L_indexmin = p(theta*|X)
 
+
     If the parameter ``dynamic_enlargement_factor`` is true, the enlargement
     factor is shrunk as the sampler runs, to avoid inefficiencies in later
     iterations. By default, the enlargement factor begins at 1.1.
@@ -88,7 +95,7 @@ class NestedEllipsoidSampler(pints.NestedSampler):
 
         Z = Z + (1 / n_active_points) * (L_1 + L_2 + ..., + L_n_active_points)
 
-    The posterior samples are generated as described in [2] on page 849 by
+    The posterior samples are generated as described in [2]_ on page 849 by
     weighting each dropped sample in proportion to the volume of the
     posterior region it was sampled from. That is, the probability
     for drawing a given sample j is given by::
@@ -105,6 +112,9 @@ class NestedEllipsoidSampler(pints.NestedSampler):
            Pia Mukherjee, David Parkinson, Andrew R. Liddle, 2008.
            arXiv: arXiv:astro-ph/0508461v2 11 Jan 2006
            https://doi.org/10.1086/501068
+    .. [2] "Nested Sampling for General Bayesian Computation", John Skilling,
+           Bayesian Analysis 1:4 (2006).
+           https://doi.org/10.1214/06-BA127
     """
 
     def __init__(self, log_prior):
@@ -128,8 +138,11 @@ def __init__(self, log_prior):
         # Dynamically vary the enlargement factor
         self._dynamic_enlargement_factor = False
         self._alpha = 0.2
-        self._A = None
-        self._centroid = None
+        self._ellipsoid = None
+
+    def ellipsoid(self):
+        """ Returns ellipsoid used in sampling. """
+        return self._ellipsoid
 
     def set_dynamic_enlargement_factor(self, dynamic_enlargement_factor):
         """
@@ -199,10 +212,10 @@ def ask(self, n_points):
         sampling regime).
         """
         i = self._accept_count
-        if (i + 1) % self._n_rejection_samples == 0:
+        if self._rejection_phase and (i + 1) > self._n_rejection_samples:
             self._rejection_phase = False
             # determine bounding ellipsoid
-            self._A, self._centroid = self._minimum_volume_ellipsoid(
+            self._ellipsoid = Ellipsoid.minimum_volume_ellipsoid(
                 self._m_active[:, :self._n_parameters]
             )
 
@@ -215,7 +228,7 @@ def ask(self, n_points):
             # update bounding ellipsoid if sufficient samples taken
             if ((i + 1 - self._n_rejection_samples)
                     % self._ellipsoid_update_gap == 0):
-                self._A, self._centroid = self._minimum_volume_ellipsoid(
+                self._ellipsoid = Ellipsoid.minimum_volume_ellipsoid(
                     self._m_active[:, :self._n_parameters])
             # From Feroz-Hobson (2008) below eq. (14)
             if self._dynamic_enlargement_factor:
@@ -225,8 +238,8 @@ def ask(self, n_points):
                 )
                 self._enlargement_factor = 1 + f
             # propose by sampling within ellipsoid
-            self._proposed = self._ellipsoid_sample(
-                self._enlargement_factor, self._A, self._centroid, n_points)
+            self._proposed = self._ellipsoid.sample(
+                n_points, self._enlargement_factor)
         return self._proposed
 
     def set_enlargement_factor(self, enlargement_factor=1.1):
@@ -267,81 +280,6 @@ def set_ellipsoid_update_gap(self, ellipsoid_update_gap=100):
             raise ValueError('Ellipsoid update gap must exceed 1.')
         self._ellipsoid_update_gap = ellipsoid_update_gap
 
-    def _minimum_volume_ellipsoid(self, points, tol=0.0):
-        """
-        Finds an approximate minimum bounding ellipse in "center form":
-        ``(x-c).T * A * (x-c) = 1``.
-        """
-        cov = np.cov(np.transpose(points))
-        cov_inv = np.linalg.inv(cov)
-        c = np.mean(points, axis=0)
-        dist = np.zeros(len(points))
-        for i in range(len(points)):
-            dist[i] = np.matmul(np.matmul(points[i] - c, cov_inv),
-                                points[i] - c)
-        enlargement_factor = np.max(dist)
-        A = (1 - tol) * (1.0 / enlargement_factor) * cov_inv
-        return A, c
-
-    def _ellipsoid_sample(self, enlargement_factor, A, centroid, n_points):
-        """
-        Draws from the enlarged bounding ellipsoid.
-        """
-        if n_points > 1:
-            return self._draw_from_ellipsoid(
-                np.linalg.inv((1 / enlargement_factor) * A),
-                centroid, n_points)
-        else:
-            return self._draw_from_ellipsoid(
-                np.linalg.inv((1 / enlargement_factor) * A), centroid, 1)[0]
-
-    def _draw_from_ellipsoid(self, covmat, cent, npts):
-        """
-        Draw ``npts`` random uniform points from within an ellipsoid with a
-        covariance matrix covmat and a centroid cent, as per:
-        http://www.astro.gla.ac.uk/~matthew/blog/?p=368
-        """
-        try:
-            ndims = covmat.shape[0]
-        except IndexError:  # pragma: no cover
-            ndims = 1
-
-        # calculate eigen_values (e) and eigen_vectors (v)
-        eigen_values, eigen_vectors = np.linalg.eig(covmat)
-        idx = (-eigen_values).argsort()[::-1][:ndims]
-        e = eigen_values[idx]
-        v = eigen_vectors[:, idx]
-        e = np.diag(e)
-
-        # generate radii of hyperspheres
-        rs = np.random.uniform(0, 1, npts)
-
-        # generate points
-        pt = np.random.normal(0, 1, [npts, ndims])
-
-        # get scalings for each point onto the surface of a unit hypersphere
-        fac = np.sum(pt**2, axis=1)
-
-        # calculate scaling for each point to be within the unit hypersphere
-        # with radii rs
-        fac = (rs**(1 / ndims)) / np.sqrt(fac)
-        pnts = np.zeros((npts, ndims))
-
-        # scale points to the ellipsoid using the eigen_values and rotate with
-        # the eigen_vectors and add centroid
-        d = np.sqrt(np.diag(e))
-        d.shape = (ndims, 1)
-
-        for i in range(0, npts):
-            # scale points to a uniform distribution within unit hypersphere
-            pnts[i, :] = fac[i] * pt[i, :]
-            pnts[i, :] = np.dot(
-                np.multiply(pnts[i, :], np.transpose(d)),
-                np.transpose(v)
-            ) + cent
-
-        return pnts
-
     def name(self):
         """ See :meth:`pints.NestedSampler.name()`. """
         return 'Nested ellipsoidal sampler'
diff --git a/pints/_nested/_multinest.py b/pints/_nested/_multinest.py
new file mode 100644
index 0000000000..313b4b9326
--- /dev/null
+++ b/pints/_nested/_multinest.py
@@ -0,0 +1,565 @@
+#
+# MultiNest sampler implementation.
+#
+# This file is part of PINTS (https://github.com/pints-team/pints/) which is
+# released under the BSD 3-clause license. See accompanying LICENSE.md for
+# copyright notice and full license details.
+#
+#
+from __future__ import absolute_import, division
+from __future__ import print_function, unicode_literals
+import pints
+import numpy as np
+import scipy.special
+import scipy.cluster.vq
+from pints._nested.__init__ import Ellipsoid
+import warnings
+
+
+class MultiNestSampler(pints.NestedSampler):
+    r"""
+    Creates a MultiNest nested sampler that estimates the marginal likelihood
+    and generates samples from the posterior.
+
+    This is the form of nested sampler described in [1]_, where multiple
+    ellipsoids are drawn around surviving particles (typically with an
+    enlargement factor to avoid missing prior mass), and then random samples
+    are drawn from within the bounds of the ellipsoids (accounting for any
+    overlap between them). By sampling in the space of surviving particles,
+    the efficiency of this algorithm aims to improve upon simple rejection
+    sampling. In this version of the method, we assume a constant number of
+    active points.
+
+    This algorithm has the following steps:
+
+    Initialise::
+
+        Z = 0
+
+    Draw samples from prior::
+
+        for i in 1:n_active_points:
+            theta_i ~ p(theta), i.e. sample from the prior
+            L_i = p(theta_i|X)
+        endfor
+        L_min = min(L)
+        indexmin = min_index(L)
+
+    Run rejection sampling for ``n_rejection_samples`` to generate an initial
+    sample of active points, along with updated values of ``L_min`` and
+    ``indexmin``.
+
+    Transform all active points into the unit cube via the cumulative
+    distribution function of the priors:
+
+    .. math::
+        u_i = \int_{-\infty}^{\theta_i} \pi(\theta') d\theta'
+
+    Fit transformed active points using minimum volume bounding ellipsoids
+    (that potentially overlap) based on Algorithm 1 in [1]_. Explicitly
+    this algorithm seeks to minimise a quantity ``F(S)>=1`` representing the
+    ratio of the total volume overlapping ellipsoids to the volume of prior
+    space remaining.
+
+    We accomplish ``F_S`` minimisation by constructing a binary tree with
+    ellipsoids (E above) as its leaves. The algorithm we follow has some
+    differences versus that reported in [1]_ based on our experimentation
+    during development (and a Matlab version of the algorithm here:
+    https://github.com/farhanferoz/MultiNest), and the pseudocode for this is::
+
+        EllipsoidTree(t, u, ef):
+            calculate bounding ellipsoid E and its volume V(E)
+            V(S) = exp(-t/n_active_points) * ef; t is iteration, and
+                S is prior volume remaining, ef is the enlargement factor
+            enlarge E so that V(E) = max(V(E), V(S))
+            if n_active_points > min_points:
+                using k-means algorithm partition active points into subsets
+                    u_1 and u_1 of size n_1 and n_2
+                num_tries = 0
+                while num_tries < max_tries and n_1 and n_2 are too small
+                    using k-means algorithm partition active points into
+                        subsets u_1 and u_1 of size n_1 and n_2
+                    num_tries += 1
+                if n_1 and n_2 are large enough:
+                    recursion = 0
+                    (A) find E_1 and E_2 (bounding ellipsoids of each point
+                        set) and their volumes V(E_1) and V(E_2)
+                    enlarge E_k (k=1,2) so that V(E_k) = max(V(E_k), V(S_k)),
+                        where V(S_k) = n_k V(S) / n_active_points
+                    for j in 1:n_active_points
+                        assign u^{j} to S_k such that
+                        h_k(u^{j}) = min(h_1(u^{j}), h_2(u^{j}))
+                    endfor
+                    recursion += 1
+                    if recursion < max_recursion and clusters are too small:
+                       go back to (A)
+                    if clusters large enough:
+                        if V(E_1) + V(E_2) < V(E) or V(E) > 2 V(S):
+                            left_branch = EllipsoidTree(t, u_1, ef)
+                            right_branch = EllipsoidTree(t, u_2, ef)
+
+            left_branch = Null
+            right_branch = Null
+            leaf = E
+
+    In the above, h_k(u_i) = (V(E_k) / V(S_k)) * d(u_i, S_k) and
+    d(u_i, S_k) = (u_i-mu_k)' (f_k C_k)^-1 (u_i-mu_k) is the Mahalanobis
+    distance from u_i to the centroid mu_k; f_k is a factor that ensures it is
+    a bounding ellipsoid; and C_k is the empirical covariance matrix of the
+    subset S_k.
+
+    From then on, in each iteration (t), the following occurs::
+
+        V(E_k) = max(V(E_k),
+            exp(-(t + 1) / n_active_points) * n_k / n_active_points)
+        V(S_k) = (n_k / n_active_points) * exp(-(t + 1) / n_active_points)
+        F(S) = (1 / V(S)) sum_{k=1}^{K} V(E_k)
+        if F(S) > f_s_threshold:
+            ellipsoid_tree = EllipsoidTree(t, u, ef)
+        endif
+        L_min = min(L)
+        indexmin = min_index(L)
+        theta* = ellipsoids_tree.sample()
+        X_t = exp(-t / n_active_points)
+        w_t = X_t - X_t-1
+        Z = Z + L_min * w_t
+        theta_indexmin = theta*
+        L_indexmin = p(theta*|X)
+
+    At the end of iterations, there is a final ``Z`` increment::
+
+        Z = Z + (1 / n_active_points) * (L_1 + L_2 + ..., + L_n_active_points)
+
+    The posterior samples are generated as described in [2]_ on page 849 by
+    weighting each dropped sample in proportion to the volume of the
+    posterior region it was sampled from. That is, the probability
+    for drawing a given sample j is given by::
+
+        p_j = L_j * w_j / Z
+
+    where j = 1, ..., n_iterations.
+
+    Extends :class:`NestedSampler`.
+
+    References
+    ----------
+    .. [1] "MultiNest: an efficient and robust Bayesian inference tool for
+           cosmology and particle physics."
+           Feroz, F., M. P. Hobson, and M. Bridges.
+           Monthly Notices of the Royal Astronomical Society 398.4 (2009):
+           1601-1614.
+    .. [2] "Nested Sampling for General Bayesian Computation", John Skilling,
+           Bayesian Analysis 1:4 (2006).
+           https://doi.org/10.1214/06-BA127
+    """
+
+    def __init__(self, log_prior):
+        super(MultiNestSampler, self).__init__(log_prior)
+
+        # Enlargement factor for ellipsoid
+        self.set_enlargement_factor()
+
+        # Minimal gaps between updating ellipsoid
+        self.set_ellipsoid_update_gap()
+
+        # Initial phase of rejection sampling
+        # Number of nested rejection samples before starting ellipsoidal
+        # sampling
+        self.set_n_rejection_samples()
+        self.set_initial_phase(True)
+
+        self.set_f_s_threshold()
+
+        self._multiple_ellipsoids = True
+        self._needs_sensitivities = False
+
+        self._f_s_minimisation_called = False
+
+        self._convert_to_unit_cube = log_prior.convert_to_unit_cube
+        self._convert_from_unit_cube = log_prior.convert_from_unit_cube
+        self._ellipsoid_tree = None
+
+    def ask(self, n_points):
+        """
+        If in initial phase, then uses rejection sampling. Afterwards,
+        points are drawn from uniformly from within the ellipsoid set
+        produced by ellipsoid tree.
+        """
+        i = self._accept_count
+        if self._rejection_phase:
+            if (i + 1) > self._n_rejection_samples:
+                self._rejection_phase = False
+                # determine bounding ellipsoids
+                samples = self._m_active[:, :self._n_parameters]
+                m_active_transformed = ([self._convert_to_unit_cube(x)
+                                         for x in samples])
+                self._ellipsoid_tree = EllipsoidTree(
+                    m_active_transformed, i, self._enlargement_factor)
+                self._ellipsoid_count = (
+                    self._ellipsoid_tree.n_leaf_ellipsoids())
+            else:
+                if n_points > 1:
+                    self._proposed = self._log_prior.sample(n_points)
+                else:
+                    self._proposed = self._log_prior.sample(n_points)[0]
+                self._ellipsoid_count = 0
+        else:
+            self._ellipsoid_tree.update_leaf_ellipsoids(i)
+            if ((i + 1 - self._n_rejection_samples)
+                    % self._ellipsoid_update_gap == 0):
+                if self._ellipsoid_tree.f_s() > self._f_s_threshold:
+                    samples = self._m_active[:, :self._n_parameters]
+                    m_active_transformed = ([self._convert_to_unit_cube(x)
+                                             for x in samples])
+                    self._ellipsoid_tree = EllipsoidTree(
+                        m_active_transformed, i, self._enlargement_factor)
+            u = self._ellipsoid_tree.sample_leaf_ellipsoids(n_points)
+            if n_points > 1:
+                self._proposed = [self._convert_from_unit_cube(x) for x in u]
+            else:
+                self._proposed = self._convert_from_unit_cube(u[0])
+            self._ellipsoid_count = self._ellipsoid_tree.n_leaf_ellipsoids()
+        return self._proposed
+
+    def ellipsoid_tree(self):
+        """ Returns ellipsoid tree based on final iteration. """
+        return self._ellipsoid_tree
+
+    def ellipsoid_update_gap(self):
+        """
+        Returns the ellipsoid update gap used in the algorithm (see
+        :meth:`set_ellipsoid_update_gap()`).
+        """
+        return self._ellipsoid_update_gap
+
+    def enlargement_factor(self):
+        """
+        Returns the enlargement factor used in the algorithm (see
+        :meth:`set_enlargement_factor()`).
+        """
+        return self._enlargement_factor
+
+    def f_s_threshold(self):
+        """
+        Returns threshold for ``F_S`` above which the ellipsoid tree is
+        refitted.
+        """
+        return self._f_s_threshold
+
+    def in_initial_phase(self):
+        """ See :meth:`pints.NestedSampler.in_initial_phase()`. """
+        return self._rejection_phase
+
+    def n_hyper_parameters(self):
+        """ See :meth:`TunableMethod.n_hyper_parameters()`. """
+        return 4
+
+    def n_rejection_samples(self):
+        """
+        Returns the number of rejection samples used in the algorithm (see
+        :meth:`set_n_rejection_samples()`).
+        """
+        return self._n_rejection_samples
+
+    def name(self):
+        """ See :meth:`pints.NestedSampler.name()`. """
+        return 'MultiNest sampler'
+
+    def needs_initial_phase(self):
+        """ See :meth:`pints.NestedSampler.needs_initial_phase()`. """
+        return True
+
+    def set_ellipsoid_update_gap(self, ellipsoid_update_gap=100):
+        """
+        Sets the minimum frequency with which the ellipsoid tree is refitted.
+
+        A higher rate of this parameter means each sample will be more
+        efficiently produced, yet the cost of re-computing the ellipsoid
+        may mean it is better to update this not each iteration -- instead,
+        with gaps of ``ellipsoid_update_gap`` between each update. By default,
+        the ellipsoid is updated every 100 iterations.
+        """
+        ellipsoid_update_gap = int(ellipsoid_update_gap)
+        if ellipsoid_update_gap <= 1:
+            raise ValueError('Ellipsoid update gap must exceed 1.')
+        self._ellipsoid_update_gap = ellipsoid_update_gap
+
+    def set_enlargement_factor(self, enlargement_factor=1.1):
+        """
+        Sets the factor (>=1) by which to increase the minimal volume
+        ellipsoidal in rejection sampling.
+
+        A higher value means it is less likely that areas of high probability
+        mass will be missed. A low value means that rejection sampling is more
+        efficient.
+        """
+        if enlargement_factor < 1:
+            raise ValueError('Enlargement factor must not be less than 1.')
+        self._enlargement_factor = enlargement_factor
+
+    def set_f_s_threshold(self, h=1.1):
+        """
+        Sets threshold for ``F_S`` when ellipsoid trees are refit. The default
+        value is 1.1.
+        """
+        if h <= 1:
+            raise ValueError('F_S threshold factor must exceed 1.')
+        self._f_s_threshold = h
+
+    def set_hyper_parameters(self, x):
+        """
+        The hyper-parameter vector is ``[# active points, # rejection samples,
+        enlargement factor, ellipsoid update gap]``.
+
+        See :meth:`TunableMethod.set_hyper_parameters()`.
+        """
+        self.set_n_active_points(x[0])
+        self.set_n_rejection_samples(x[1])
+        self.set_enlargement_factor(x[2])
+        self.set_ellipsoid_update_gap(x[3])
+
+    def set_initial_phase(self, in_initial_phase):
+        """ See :meth:`pints.NestedSampler.set_initial_phase()`. """
+        self._rejection_phase = bool(in_initial_phase)
+
+    def set_n_rejection_samples(self, rejection_samples=200):
+        """
+        Sets the number of rejection samples to take before proceeding to the
+        ellipsoid tree sampling phase.
+        """
+        if rejection_samples < 0:
+            raise ValueError('Must have non-negative rejection samples.')
+        self._n_rejection_samples = rejection_samples
+
+
+class EllipsoidTree():
+    """
+    Builds a binary tree with ellipsoids as leaf nodes which is used to
+    minimise ``F_S`` as in Algorithm 1 in [1]_.
+    """
+    def __init__(self, points, iteration, enlargement_factor=1):
+        n_points = len(points)
+        if n_points < 1:
+            raise ValueError(
+                "More than one point is needed in an EllipsoidTree.")
+        for point in points:
+            if min(point) < 0 or max(point) > 1:
+                raise ValueError(
+                    "Points must be in unit cube.")
+        self._n_points = n_points
+        self._dimensions = len(points[0])
+        self._max_tries = 50
+        self._max_recursion = 50
+        self._min_points_to_split = 50
+        self._points = points
+        if iteration < 1:
+            raise ValueError(
+                "iteration must be >= 1."
+            )
+        self._iteration = iteration
+        self._left = None
+        self._right = None
+
+        # step 1 in Algorithm 1
+        # calculate volume of space
+        self._V_S = self.vs() * enlargement_factor
+        self._enlargement_factor = enlargement_factor
+        # calculate bounding ellipsoid
+        self._ellipsoid = Ellipsoid.minimum_volume_ellipsoid(points)
+
+        V_E = self._ellipsoid.volume()
+
+        # step 2 in Algorithm 1
+        self.compare_enlarge(self._ellipsoid, self._V_S)
+
+        # not in algorithm but safeguard against small ellipsoids
+        if n_points > self._min_points_to_split:
+            # step 3 in Algorithm 1
+            _, assignments = scipy.cluster.vq.kmeans2(
+                points, 2, minit="points")
+            ntries = 0
+            # ensures against small clusters
+            threshold = self._dimensions + 5
+            too_small = (sum(assignments == 0) < threshold or
+                         sum(assignments == 1) < threshold)
+            while (ntries < self._max_tries and too_small):  # pragma: no cover
+                centers, assignment = (
+                    scipy.cluster.vq.kmeans2(points, 2, minit="points"))
+                too_small = (sum(assignments == 0) < threshold or
+                             sum(assignments == 1) < threshold)
+                ntries += 1
+            # steps 4-13 in Algorithm 1
+            if not too_small:
+                ellipsoid_1, ellipsoid_2, success = self.split_ellipsoids(
+                    points, assignments, 0)
+                if success:
+                    # steps 14+ in Algorithm 1
+                    V_E_1 = ellipsoid_1.volume()
+                    V_E_2 = ellipsoid_2.volume()
+
+                    if (V_E_1 + V_E_2 < V_E) or (V_E > 2 * self._V_S):
+                        self._left = EllipsoidTree(ellipsoid_1.points(),
+                                                   iteration)
+                        self._right = EllipsoidTree(ellipsoid_2.points(),
+                                                    iteration)
+
+    def compare_enlarge(self, ellipsoid, V_S):
+        """
+        Compares the volume of an ellipsoid to V_S and, if it is smaller,
+        enlarges it so that it has the same volume.
+        """
+        r = V_S / ellipsoid.volume()
+        if r > 1:
+            ellipsoid.enlarge(r)
+
+    def count_within_leaf_ellipsoids(self, point):
+        """
+        Determines the number of ellipsoids a point is contained within.
+        """
+        leaves = self.leaf_ellipsoids()
+        count = 0
+        for leaf in leaves:
+            if leaf.within_ellipsoid(point):
+                count += 1
+        return count
+
+    def ellipsoid(self):
+        """ Returns bounding ellipsoid of tree. """
+        return self._ellipsoid
+
+    def f_s(self):
+        """
+        Returns ``F_S`` representing ratio of ellipsoid volume to total prior
+        volume.
+        """
+        return self.leaf_ellipsoids_volume() / self._V_S
+
+    def h_k(self, point, ellipsoid, V_S_k):
+        """ Calculates ``h_k`` as in eq. (23) in [1]_."""
+        d = Ellipsoid.mahalanobis_distance(point,
+                                           ellipsoid.weight_matrix(),
+                                           ellipsoid.centroid())
+        return ellipsoid.volume() * d / V_S_k
+
+    def leaf_ellipsoids(self):
+        """ Returns leaf ellipsoids of tree. """
+        if self._left is None and self._right is None:
+            return [self.ellipsoid()]
+        else:
+            return (self._left.leaf_ellipsoids() +
+                    self._right.leaf_ellipsoids())
+
+    def leaf_ellipsoids_volume(self):
+        """ Returns volume of leaf ellipsoids. """
+        if self._left is None and self._right is None:
+            return self.ellipsoid().volume()
+        else:
+            return (self._left.leaf_ellipsoids_volume() +
+                    self._right.leaf_ellipsoids_volume())
+
+    def n_leaf_ellipsoids(self):
+        """ Counts the leaf ellipsoids. """
+        if self._left is None and self._right is None:
+            return 1
+        else:
+            return (self._left.n_leaf_ellipsoids() +
+                    self._right.n_leaf_ellipsoids())
+
+    def sample_leaf_ellipsoids(self, ndraws):
+        """
+        Draws uniform samples from within leaf ellipsoids accounting for their
+        overlap.
+        """
+        # calculate relative volumes of ellipsoids
+        leaves = self.leaf_ellipsoids()
+        volumes = [ell.volume() for ell in leaves]
+        volume_tot = sum(volumes)
+        volumes_rel = [vol / volume_tot for vol in volumes]
+
+        # propose ellipsoid in proportion to its volume
+        draws = []
+        naccepted = 0
+        while naccepted < ndraws:
+            k = np.random.choice(len(volumes), p=volumes_rel)
+            ellipsoid = leaves[k]
+            test_point = ellipsoid.sample(1)
+            n_e = self.count_within_leaf_ellipsoids(test_point)
+            if n_e == 1:
+                naccepted += 1
+                draws.append(test_point)
+            elif n_e > 1:
+                paccept = 1.0 / n_e
+                if paccept > np.random.uniform():
+                    naccepted += 1
+                    draws.append(test_point)
+            elif n_e < 1:  # pragma: no cover
+                raise RuntimeError("Point not in any ellipse.")
+        return draws
+
+    def split_ellipsoids(self, points, assignments, recursion):
+        """
+        Performs steps 4-13 in Algorithm 1 in [1]_, where the points are
+        partitioned into two ellipsoids to minimise a measure ``h_k``.
+        """
+        # step 4 in Algorithm 1
+        ellipsoids = []
+        for i in range(2):
+            points_temp = np.array(points)[np.where(assignments == i)]
+            try:
+                el = Ellipsoid.minimum_volume_ellipsoid(points_temp)
+                ellipsoids.append(el)
+            except np.linalg.LinAlgError as e:
+                warnings.warn('LinAlgError encountered when contructing ' +
+                              'minimum volume ellipse: ' + str(e))
+                return -1, -1, False
+
+        # step 5 in Algorithm 1
+        V_S_ks = [self.vsk(el) for el in ellipsoids]
+        for i in range(2):
+            self.compare_enlarge(ellipsoids[i], V_S_ks[i])
+
+        # step 6 in Algorithm 1
+        n = self._n_points
+        assignments_new = np.zeros(n, dtype=np.uint8)
+        for i in range(n):
+            h_k_max = float('inf')
+            for j in range(2):
+                h_k = self.h_k(points[i], ellipsoids[j], V_S_ks[j])
+                if h_k < h_k_max:
+                    assignments_new[i] = j
+                    h_k_max = h_k
+
+        # from https://github.com/farhanferoz/MultiNest/blob/master/MatlabMultiNest/NSMain/optimal_ellipsoids.m # noqa
+        threshold = self._dimensions + 1
+        n1 = sum(assignments_new == 0)
+        n2 = sum(assignments_new == 1)
+        if recursion > self._max_recursion:  # pragma: no cover
+            success = False
+        elif n1 < threshold or n2 < threshold:  # pragma: no cover
+            ellipsoids[0], ellipsoids[1], success = self.split_ellipsoids(
+                points, assignments, recursion + 1)
+        else:
+            success = True
+        return ellipsoids[0], ellipsoids[1], success
+
+    def update_leaf_ellipsoids(self, iteration):
+        """
+        Updates ellipsoids according to p.1605 (bottom-right text) in [1]_
+        according to iteration.
+        """
+        self._iteration = iteration
+        self._V_S = self.vs() * self._enlargement_factor
+        leaves = self.leaf_ellipsoids()
+        [self.compare_enlarge(ell, self.vsk(ell)) for ell in leaves]
+
+    def vs(self):
+        """ Calculates volume of total space. """
+        return np.exp(-self._iteration / self._n_points)
+
+    def vsk(self, ellipsoid):
+        """ Calculates subvolume of ellipsoid. """
+        n_points = ellipsoid.n_points()
+        if n_points > self._n_points:
+            raise ValueError(
+                "Number of points in ellipsoid may not exceed that in tree.")
+        return ellipsoid.n_points() * self._V_S / self._n_points
diff --git a/pints/_nested/_rejection.py b/pints/_nested/_rejection.py
index 7cb25431e0..b33cd66550 100644
--- a/pints/_nested/_rejection.py
+++ b/pints/_nested/_rejection.py
@@ -56,7 +56,7 @@ class NestedRejectionSampler(pints.NestedSampler):
 
         Z = Z + (1 / n_active_points) * (L_1 + L_2 + ..., + L_n_active_points)
 
-    The posterior samples are generated as described in [1] on page 849 by
+    The posterior samples are generated as described in [1]_ on page 849 by
     weighting each dropped sample in proportion to the volume of the
     posterior region it was sampled from. That is, the probability
     for drawing a given sample j is given by::
diff --git a/pints/tests/test_nested_controller.py b/pints/tests/test_nested_controller.py
index 491abb0b97..80828ef585 100755
--- a/pints/tests/test_nested_controller.py
+++ b/pints/tests/test_nested_controller.py
@@ -12,6 +12,7 @@
 
 import pints
 import pints.toy
+from pints._nested.__init__ import Ellipsoid
 
 from shared import StreamCapture, TemporaryDirectory
 
@@ -194,6 +195,27 @@ def test_logging(self):
         for line in lines[5:]:
             self.assertTrue(pattern.match(line))
 
+    def test_logging_multiple_ellipsoid(self):
+        # Tests logging to screen and file.
+
+        # Log to screen
+        with StreamCapture() as c:
+            sampler = pints.NestedController(
+                self.log_likelihood, self.log_prior,
+                method=pints.MultiNestSampler)
+            sampler.set_n_posterior_samples(2)
+            sampler.set_iterations(20)
+            sampler.set_log_to_screen(True)
+            sampler.set_log_to_file(False)
+            samples, margin = sampler.run()
+        lines = c.text().splitlines()
+        self.assertEqual(lines[0], 'Running MultiNest sampler')
+        self.assertEqual(lines[1], 'Number of active points: 400')
+        self.assertEqual(lines[2], 'Total number of iterations: 20')
+        self.assertEqual(lines[3], 'Total number of posterior samples: 2')
+        self.assertEqual(lines[4], ('Iter. Eval. Time m:s Delta_log(z) ' +
+                                    'Acceptance rate Ellipsoid count'))
+
     def test_settings_check(self):
         # Tests the settings check at the start of a run.
         sampler = pints.NestedController(
@@ -344,5 +366,154 @@ def test_exception_on_multi_use(self):
             sampler.run()
 
 
+class TestEllipsoid(unittest.TestCase):
+
+    @classmethod
+    def setUpClass(cls):
+        """ Prepare for the test. """
+        cls.A = np.array([[1, 0.5], [0.5, 2]])
+        cls.c = np.array([3, 4])
+
+    def test_constructors(self):
+        # tests instantiation and errors
+
+        # basic construction
+        ellipsoid = Ellipsoid(self.A, self.c)
+        self.assertTrue(np.array_equal(self.A, ellipsoid.weight_matrix()))
+        self.assertTrue(np.array_equal(self.c, ellipsoid.centroid()))
+        self.assertTrue(ellipsoid.points() is None)
+        self.assertEqual(0, ellipsoid.n_points())
+
+        # errors
+        # different length vec
+        A = np.array([[1, 0.5], [0.5, 2]])
+        c = [1, 2, 3]
+        self.assertRaises(ValueError, Ellipsoid, A, c)
+
+        A = np.array([[1, 0.5], [0.5, 2, 3]])
+        c = [1, 2]
+        self.assertRaises(ValueError, Ellipsoid, A, c)
+
+    def test_enlarge_ellipsoid(self):
+        # tests that ellipsoid is properly enlarged
+
+        ellipsoid = Ellipsoid(self.A, self.c)
+        vol1 = ellipsoid.volume()
+        ef = 2
+        ellipsoid.enlarge(ef)
+        vol2 = ellipsoid.volume()
+        self.assertEqual(vol1 * ef, vol2)
+
+    def test_volume(self):
+        # tests volume calculation
+        ellipsoid = Ellipsoid(self.A, self.c)
+        self.assertAlmostEqual(ellipsoid.volume(), 2.3748208234474517)
+
+        A = np.array([[1, 0.5, 0.0], [0.5, 2, 0.0], [0.0, 0.0, 3.0]])
+        ellipsoid = Ellipsoid(A, [1, 2, 3])
+        self.assertAlmostEqual(ellipsoid.volume(), 1.828137922259353)
+
+    def test_mahalanobis_distance(self):
+        # tests that distance utility works
+        A = np.array([[1, 0], [0, 1]])
+        c = np.array([0, 0])
+        self.assertEqual(Ellipsoid.mahalanobis_distance([1, 0], A, c), 1)
+        self.assertEqual(Ellipsoid.mahalanobis_distance([0, 1], A, c), 1)
+        point = [1 / np.sqrt(2), 1 / np.sqrt(2)]
+        self.assertAlmostEqual(Ellipsoid.mahalanobis_distance(point, A, c), 1)
+
+    def test_sample(self):
+        # tests uniform sampling within ellipsoid
+
+        # single draws
+        ellipsoid = Ellipsoid(self.A, self.c)
+        draws = ellipsoid.sample(1)
+        self.assertTrue(len(draws), 1)
+
+        # default ellipsoid sampling
+        n = 1000
+        draws = ellipsoid.sample(n)
+        for draw in draws:
+            self.assertTrue(len(draw) == len(self.c))
+            dist = Ellipsoid.mahalanobis_distance(draw, self.A, self.c)
+            self.assertTrue(dist <= 1)
+
+        A = np.array([[1, 0.5, 0.0], [0.5, 2, 0.0], [0.0, 0.0, 3.0]])
+        c = [1, 2, 3]
+        ellipsoid = Ellipsoid(A, c)
+        draws = ellipsoid.sample(n)
+        for draw in draws:
+            self.assertTrue(len(draw) == len(c))
+            dist = Ellipsoid.mahalanobis_distance(draw, A, c)
+            self.assertTrue(dist <= 1)
+
+        # expanded ellipsoid sampling
+        n = 10000
+        ef = 2
+        draws = ellipsoid.sample(n, enlargement_factor=ef)
+        dists = np.zeros(n)
+        for k, draw in enumerate(draws):
+            self.assertTrue(len(draw) == len(c))
+            dist = Ellipsoid.mahalanobis_distance(draw, A, c)
+            dists[k] = dist
+            self.assertTrue(dist <= ef)
+        self.assertTrue(max(dists) > 1)
+        ef1 = 4
+        draws = ellipsoid.sample(n, enlargement_factor=ef1)
+        dists1 = np.zeros(n)
+        for k, draw in enumerate(draws):
+            self.assertTrue(len(draw) == len(c))
+            dist = Ellipsoid.mahalanobis_distance(draw, A, c)
+            dists1[k] = dist
+            self.assertTrue(dist <= ef1)
+        self.assertTrue(max(dists1) > max(dists))
+
+    def test_minimum_volume_ellipsoid(self):
+        # tests bounding ellipsoid creation
+
+        n = 10000
+        # 2D example
+        gaussian = pints.toy.GaussianLogPDF()
+        draws = gaussian.sample(n)
+        ellipsoid = Ellipsoid.minimum_volume_ellipsoid(draws)
+
+        # checks that points are held by bounding ellipsoid
+        self.assertTrue(np.array_equal(draws, ellipsoid.points()))
+        self.assertEqual(n, ellipsoid.n_points())
+
+        dists = np.zeros(n)
+        for k, draw in enumerate(draws):
+            dist = Ellipsoid.mahalanobis_distance(draw,
+                                                  ellipsoid.weight_matrix(),
+                                                  ellipsoid.centroid())
+            dists[k] = dist
+        self.assertTrue(max(dists) <= 1.1)
+        self.assertTrue(max(dists) > 0.9)
+
+        # 3D
+        sigma = np.array([[1, 0.5, 0.0], [0.5, 2, 0.0], [0.0, 0.0, 3.0]])
+        gaussian = pints.toy.GaussianLogPDF(mean=[1, 2, 3], sigma=sigma)
+        draws = gaussian.sample(n)
+        ellipsoid = Ellipsoid.minimum_volume_ellipsoid(draws)
+        self.assertTrue(np.array_equal(draws, ellipsoid.points()))
+        self.assertEqual(n, ellipsoid.n_points())
+        dists = np.zeros(n)
+        for k, draw in enumerate(draws):
+            dist = Ellipsoid.mahalanobis_distance(draw,
+                                                  ellipsoid.weight_matrix(),
+                                                  ellipsoid.centroid())
+            dists[k] = dist
+        self.assertTrue(max(dists) <= 1.1)
+        self.assertTrue(max(dists) > 0.9)
+
+    def test_within_ellipsoid(self):
+        # tests within_ellipsoid function
+        A = np.array([[1, 0], [0, 1]])
+        c = np.array([0, 0])
+        ellipsoid = Ellipsoid(A, c)
+        self.assertTrue(ellipsoid.within_ellipsoid(np.array([1, 0])))
+        self.assertFalse(ellipsoid.within_ellipsoid(np.array([1.01, 0])))
+
+
 if __name__ == '__main__':
     unittest.main()
diff --git a/pints/tests/test_nested_ellipsoid_sampler.py b/pints/tests/test_nested_ellipsoid_sampler.py
index ee0a857957..d66efa3940 100755
--- a/pints/tests/test_nested_ellipsoid_sampler.py
+++ b/pints/tests/test_nested_ellipsoid_sampler.py
@@ -11,6 +11,7 @@
 
 import pints
 import pints.toy
+from pints._nested.__init__ import Ellipsoid
 
 # Unit testing in Python 2 and 3
 try:
@@ -137,18 +138,13 @@ def test_ask_tell(self):
 
         # test that ellipses are estimated
         sampler = pints.NestedEllipsoidSampler(self.log_prior)
-        A1 = np.copy(sampler._A)
-        c1 = sampler._centroid
         sampler.set_n_rejection_samples(100)
         sampler.set_ellipsoid_update_gap(10)
         for i in range(5000):
             pt = sampler.ask(1)
             fx = self.log_likelihood(pt)
             sampler.tell(fx)
-        A2 = sampler._A
-        c2 = sampler._centroid
-        self.assertTrue(not np.array_equal(A1, A2))
-        self.assertTrue(not np.array_equal(c1, c2))
+        self.assertTrue(isinstance(sampler.ellipsoid(), Ellipsoid))
 
         # test multiple points being asked and tell'd
         sampler = pints.NestedEllipsoidSampler(self.log_prior)
@@ -168,11 +164,11 @@ def test_dynamic_enlargement_factor(self):
         # tests dynamic enlargement factor runs
         sampler = pints.NestedController(self.log_likelihood,
                                          self.log_prior)
-        sampler._sampler.set_dynamic_enlargement_factor(1)
+        sampler.sampler().set_dynamic_enlargement_factor(1)
         sampler.set_log_to_screen(False)
-        ef1 = sampler._sampler.enlargement_factor()
+        ef1 = sampler.sampler().enlargement_factor()
         sampler.run()
-        ef2 = sampler._sampler.enlargement_factor()
+        ef2 = sampler.sampler().enlargement_factor()
         self.assertTrue(ef2 < ef1)
 
     def test_sensitivities(self):
diff --git a/pints/tests/test_nested_multinest.py b/pints/tests/test_nested_multinest.py
new file mode 100644
index 0000000000..73bf2796a4
--- /dev/null
+++ b/pints/tests/test_nested_multinest.py
@@ -0,0 +1,277 @@
+#!/usr/bin/env python3
+#
+# Tests ellipsoidal nested sampler.
+#
+# This file is part of PINTS (https://github.com/pints-team/pints/) which is
+# released under the BSD 3-clause license. See accompanying LICENSE.md for
+# copyright notice and full license details.
+#
+from __future__ import division
+import unittest
+import numpy as np
+
+import pints
+import pints.toy
+from pints._nested._multinest import EllipsoidTree
+from pints._nested.__init__ import Ellipsoid
+
+# Unit testing in Python 2 and 3
+try:
+    unittest.TestCase.assertRaisesRegex
+except AttributeError:
+    unittest.TestCase.assertRaisesRegex = unittest.TestCase.assertRaisesRegexp
+
+
+class TestMultiNestSampler(unittest.TestCase):
+    """
+    Unit (not functional!) tests for :class:`MultiNestSampler`.
+    """
+
+    @classmethod
+    def setUpClass(cls):
+        """ Prepare for the test. """
+        # Create toy model
+        model = pints.toy.LogisticModel()
+        cls.real_parameters = [0.015, 500]
+        times = np.linspace(0, 1000, 1000)
+        values = model.simulate(cls.real_parameters, times)
+
+        # Add noise
+        np.random.seed(1)
+        cls.noise = 10
+        values += np.random.normal(0, cls.noise, values.shape)
+        cls.real_parameters.append(cls.noise)
+
+        # Create an object with links to the model and time series
+        problem = pints.SingleOutputProblem(model, times, values)
+
+        # Create a uniform prior over both the parameters and the new noise
+        # variable
+        cls.log_prior = pints.UniformLogPrior(
+            [0.01, 400],
+            [0.02, 600]
+        )
+
+        # Create a log-likelihood
+        cls.log_likelihood = pints.GaussianKnownSigmaLogLikelihood(
+            problem, cls.noise)
+
+    def test_getters_and_setters(self):
+        # tests various get() and set() methods.
+        controller = pints.NestedController(self.log_likelihood,
+                                            self.log_prior,
+                                            method=pints.MultiNestSampler)
+        self.assertEqual(controller.sampler().f_s_threshold(), 1.1)
+        controller.sampler().set_f_s_threshold(4)
+        self.assertEqual(controller.sampler().f_s_threshold(), 4)
+        self.assertRaises(ValueError, controller.sampler().set_f_s_threshold,
+                          0.5)
+        controller.sampler().set_ellipsoid_update_gap(43)
+        self.assertEqual(controller.sampler().ellipsoid_update_gap(), 43)
+        controller.sampler().set_enlargement_factor(4)
+        self.assertEqual(controller.sampler().enlargement_factor(), 4)
+        self.assertTrue(controller.sampler().in_initial_phase())
+        self.assertEqual(controller.sampler().n_hyper_parameters(), 4)
+        controller.sampler().set_n_rejection_samples(12)
+        self.assertEqual(controller.sampler().n_rejection_samples(), 12)
+        self.assertEqual(controller.sampler().name(),
+                         "MultiNest sampler")
+        self.assertTrue(controller.sampler().needs_initial_phase())
+        controller.sampler().set_hyper_parameters([100, 100, 2, 30])
+
+        # test errors
+        self.assertRaises(ValueError,
+                          controller.sampler().set_ellipsoid_update_gap,
+                          0)
+        self.assertRaises(ValueError,
+                          controller.sampler().set_enlargement_factor,
+                          0.5)
+        self.assertRaises(ValueError,
+                          controller.sampler().set_n_rejection_samples,
+                          -1)
+
+    def test_runs(self):
+        # tests that sampler runs
+        controller = pints.NestedController(self.log_likelihood,
+                                            self.log_prior,
+                                            method=pints.MultiNestSampler)
+        controller.set_iterations(450)
+        controller.set_log_to_screen(False)
+        controller.run()
+
+        # test getting ellipsoid tree post-run
+        et = controller.sampler().ellipsoid_tree()
+        self.assertTrue(et.n_leaf_ellipsoids() >= 1)
+
+    def test_multiple(self):
+        # tests that ask /tell work with multiple points
+
+        # test multiple points being asked and tell'd
+        sampler = pints.MultiNestSampler(self.log_prior)
+        pts = sampler.ask(50)
+        self.assertEqual(len(pts), 50)
+        fx = [self.log_likelihood(pt) for pt in pts]
+        proposed = sampler.tell(fx)
+        self.assertTrue(len(proposed) > 1)
+
+        # test with a longer run so that post-rejection sampling multiple
+        # point evaluation gets triggered
+        controller = pints.NestedController(self.log_likelihood,
+                                            self.log_prior,
+                                            method=pints.MultiNestSampler)
+        controller.set_iterations(450)
+        controller.set_log_to_screen(False)
+        controller.set_parallel(True)
+        controller.run()
+
+
+class TestEllipsoidTree(unittest.TestCase):
+    """
+    Unit tests for the Ellipsoid binary tree class.
+    """
+
+    @classmethod
+    def setUpClass(cls):
+        # prepare for tests
+        n = 1000
+        gaussian = pints.MultivariateGaussianLogPrior([0, 0], [[1, 0], [0, 1]])
+        cls.gaussian = gaussian
+        draws = gaussian.sample(n)
+        cls.draws = [gaussian.convert_to_unit_cube(x) for x in draws]
+
+    def unit_draws(self, n):
+        # helper function to produce unit draws
+        draws = self.gaussian.sample(n)
+        return [self.gaussian.convert_to_unit_cube(x) for x in draws]
+
+    def test_construction(self):
+        # tests construction
+
+        # above threshold draws
+        draws = self.unit_draws(20)
+        EllipsoidTree(draws, 1)
+        # below threshold draws
+        draws = self.unit_draws(5)
+        EllipsoidTree(draws, 1)
+
+        # check errors
+        # zero length points?
+        self.assertRaises(ValueError, EllipsoidTree, [], 1)
+        # negative iteration?
+        self.assertRaises(ValueError, EllipsoidTree, self.draws, -1)
+        # points within unit cube?
+        gaussian = pints.MultivariateGaussianLogPrior([5, 5], [[1, 0], [0, 1]])
+        draws = gaussian.sample(20)
+        self.assertRaises(ValueError, EllipsoidTree, draws, 1)
+
+    def test_getters(self):
+        # tests get()
+
+        tree = EllipsoidTree(self.draws, 100)
+
+        # leaf nodes
+        self.assertTrue(tree.n_leaf_ellipsoids() >= 1)
+        leaves = np.copy(tree.leaf_ellipsoids())
+        self.assertEqual(tree.n_leaf_ellipsoids(), len(leaves))
+        [self.assertTrue(isinstance(x, Ellipsoid)) for x in leaves]
+
+        # bounding ellipsoid
+        ellipsoid = tree.ellipsoid()
+        self.assertTrue(isinstance(ellipsoid, Ellipsoid))
+
+        # Check a given draw is within bounding ellipsoids
+        self.assertTrue(tree.count_within_leaf_ellipsoids(
+            self.draws[0]) >= 1)
+        self.assertTrue(tree.count_within_leaf_ellipsoids(
+            [-100, -100]) == 0)
+
+        # check f_s
+        self.assertTrue(tree.f_s() >= 1)
+
+        # updating triggers changes?
+        f_s_old = np.copy(tree.f_s())
+        tree.update_leaf_ellipsoids(1)
+        self.assertFalse(tree.f_s() == f_s_old)
+
+    def test_calculations(self):
+        # tests the calculations done
+
+        # vs
+        n = 20
+        iteration = 2
+        draws = self.unit_draws(n)
+        ellipsoidTree = EllipsoidTree(draws, iteration)
+        self.assertEqual(ellipsoidTree.vs(), np.exp(-iteration / n))
+
+        # vsk
+        n1 = 5
+        draws = self.unit_draws(n1)
+        ellipsoid = Ellipsoid.minimum_volume_ellipsoid(draws)
+        V_S = ellipsoidTree._V_S
+        self.assertEqual(ellipsoidTree.vsk(ellipsoid), n1 * V_S / n)
+
+        # more points in ellipsoid than tree?
+        n1 = 21
+        draws = self.unit_draws(n1)
+        ellipsoid = Ellipsoid.minimum_volume_ellipsoid(draws)
+        self.assertRaises(ValueError, ellipsoidTree.vsk, ellipsoid)
+
+        # hk
+        ellipsoid = ellipsoidTree.ellipsoid()
+        d = Ellipsoid.mahalanobis_distance(self.draws[0],
+                                           ellipsoid.weight_matrix(),
+                                           ellipsoid.centroid())
+        V_S_k = 1
+        self.assertEqual(ellipsoid.volume() * d / V_S_k,
+                         ellipsoidTree.h_k(self.draws[0], ellipsoid, V_S_k))
+
+    def test_sampling(self):
+        # tests sampling from leaf ellipsoids
+
+        # check all samples in leaf ellipsoids
+        tree = EllipsoidTree(self.draws, 100)
+        samples = tree.sample_leaf_ellipsoids(100)
+        for sample in samples:
+            self.assertTrue(tree.count_within_leaf_ellipsoids(
+                sample) >= 1)
+
+    def test_splitting(self):
+        # tests splitting and enlarging ellipsoids
+
+        # singular matrix error?
+        tree = EllipsoidTree(self.draws, 100)
+        points = np.array([[0, 0], [0.5, 0.5], [1, 1]])
+        assignments = np.array([0, 0, 0])
+        _, _, bool = tree.split_ellipsoids(points, assignments, 0)
+        self.assertFalse(bool)
+
+        # enlarging
+        ellipsoid = tree.ellipsoid()
+        tree.compare_enlarge(ellipsoid, 20)
+
+    def test_multiple_nodes(self):
+        # test that tree does actually split when supplied with multiple modes
+        # and that functions still run ok with multiple leaves
+
+        # need multiple replicates to ensure at least one splits
+        n = 400
+        nreps = 10
+        log_pdf = pints.toy.AnnulusLogPDF()
+        gaussian = pints.MultivariateGaussianLogPrior([0, 0],
+                                                      [[100, 0], [0, 100]])
+        n_leaves = []
+        for rep in range(nreps):
+            draws = log_pdf.sample(n)
+            draws = [gaussian.convert_to_unit_cube(x) for x in draws]
+            draws = np.vstack(draws)
+            ellipsoid_tree = EllipsoidTree(draws, 600)
+            n_leaf = ellipsoid_tree.n_leaf_ellipsoids()
+            n_leaves.append(n_leaf)
+            self.assertEqual(n_leaf, len(ellipsoid_tree.leaf_ellipsoids()))
+            self.assertTrue(ellipsoid_tree.leaf_ellipsoids_volume() > 0)
+            ellipsoid_tree.sample_leaf_ellipsoids(1000)
+        self.assertTrue(sum(np.array(n_leaves) > 1) > 1)
+
+
+if __name__ == '__main__':
+    unittest.main()