Removed try/except block

Block was there to handle older version of FilterPy. GitHub
issue 49.

05-Multivariate-Gaussians.ipynb

@@ -345,7 +345,7 @@
      "data": {
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truncated
       "text/plain": [
-       "<matplotlib.figure.Figure at 0x71fb908>"
+       "<matplotlib.figure.Figure at 0x75df898>"
       ]
      },
      "metadata": {},
@@ -420,7 +420,7 @@
      "data": {
       "image/png": 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truncated
       "text/plain": [
-       "<matplotlib.figure.Figure at 0x8539128>"
+       "<matplotlib.figure.Figure at 0x89200f0>"
       ]
      },
      "metadata": {},
@@ -585,7 +585,7 @@
      "data": {
       "image/png": 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truncated
       "text/plain": [
-       "<matplotlib.figure.Figure at 0x727db00>"
+       "<matplotlib.figure.Figure at 0x47fbb00>"
       ]
      },
      "metadata": {},
@@ -626,9 +626,9 @@
    "outputs": [
     {
      "data": {
-      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAr8AAAD9CAYAAAC1Fh+gAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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 truncated
+      "image/png": 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truncated
       "text/plain": [
-       "<matplotlib.figure.Figure at 0x7503080>"
+       "<matplotlib.figure.Figure at 0x8b4cc50>"
       ]
      },
      "metadata": {},
@@ -665,7 +665,7 @@
      "data": {
       "image/png": 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truncated
       "text/plain": [
-       "<matplotlib.figure.Figure at 0x88758d0>"
+       "<matplotlib.figure.Figure at 0x8d245f8>"
       ]
      },
      "metadata": {},
@@ -707,7 +707,7 @@
      "data": {
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truncated
       "text/plain": [
-       "<matplotlib.figure.Figure at 0x8745da0>"
+       "<matplotlib.figure.Figure at 0x7a2c390>"
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      },
      "metadata": {},
@@ -740,7 +740,7 @@
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truncated
       "text/plain": [
-       "<matplotlib.figure.Figure at 0x8745198>"
+       "<matplotlib.figure.Figure at 0x7a4cf60>"
       ]
      },
      "metadata": {},
@@ -775,7 +775,7 @@
      "data": {
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truncated
       "text/plain": [
-       "<matplotlib.figure.Figure at 0x88ceef0>"
+       "<matplotlib.figure.Figure at 0x8aedb70>"
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      "metadata": {},
@@ -821,7 +821,7 @@
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truncated
       "text/plain": [
-       "<matplotlib.figure.Figure at 0x8981d30>"
+       "<matplotlib.figure.Figure at 0x92b81d0>"
       ]
      },
      "metadata": {},
@@ -865,7 +865,7 @@
      "data": {
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       "text/plain": [
-       "<matplotlib.figure.Figure at 0x8815ac8>"
+       "<matplotlib.figure.Figure at 0x8b36860>"
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@@ -925,7 +925,7 @@
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truncated
       "text/plain": [
-       "<matplotlib.figure.Figure at 0x8f15d30>"
+       "<matplotlib.figure.Figure at 0x8cdba90>"
       ]
      },
      "metadata": {},
@@ -958,7 +958,7 @@
      "data": {
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truncated
       "text/plain": [
-       "<matplotlib.figure.Figure at 0x87d7da0>"
+       "<matplotlib.figure.Figure at 0x92fab70>"
       ]
      },
      "metadata": {},
@@ -1070,7 +1070,7 @@
      "data": {
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truncated
       "text/plain": [
-       "<matplotlib.figure.Figure at 0x8808630>"
+       "<matplotlib.figure.Figure at 0x8ce3cf8>"
       ]
      },
      "metadata": {},
@@ -1103,7 +1103,7 @@
      "data": {
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truncated
       "text/plain": [
-       "<matplotlib.figure.Figure at 0x884b710>"
+       "<matplotlib.figure.Figure at 0x8b583c8>"
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      },
      "metadata": {},
@@ -1146,7 +1146,7 @@
      "data": {
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truncated
       "text/plain": [
-       "<matplotlib.figure.Figure at 0x880c780>"
+       "<matplotlib.figure.Figure at 0x8e29e48>"
       ]
      },
      "metadata": {},
@@ -1201,7 +1201,7 @@
      "data": {
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truncated
       "text/plain": [
-       "<matplotlib.figure.Figure at 0x88db4a8>"
+       "<matplotlib.figure.Figure at 0x8b6bfd0>"
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      "metadata": {},
@@ -1232,7 +1232,7 @@
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truncated
       "text/plain": [
-       "<matplotlib.figure.Figure at 0x89e3b70>"
+       "<matplotlib.figure.Figure at 0x7a14f98>"
       ]
      },
      "metadata": {},
@@ -1266,7 +1266,7 @@
      "data": {
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       "text/plain": [
-       "<matplotlib.figure.Figure at 0x86e52e8>"
+       "<matplotlib.figure.Figure at 0x8bc27f0>"
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      },
      "metadata": {},
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       "text/plain": [
-       "<matplotlib.figure.Figure at 0x89d4b00>"
+       "<matplotlib.figure.Figure at 0x8dd7358>"
       ]
      },
      "metadata": {},
@@ -1335,7 +1335,7 @@
      "data": {
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truncated
       "text/plain": [
-       "<matplotlib.figure.Figure at 0x8889b00>"
+       "<matplotlib.figure.Figure at 0x8bd0a58>"
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      },
      "metadata": {},
@@ -1375,7 +1375,7 @@
      "data": {
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truncated
       "text/plain": [
-       "<matplotlib.figure.Figure at 0x87af6a0>"
+       "<matplotlib.figure.Figure at 0x774c780>"
       ]
      },
      "metadata": {},
@@ -1405,7 +1405,7 @@
      "data": {
       "image/png": 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truncated
       "text/plain": [
-       "<matplotlib.figure.Figure at 0x88703c8>"
+       "<matplotlib.figure.Figure at 0x774c1d0>"
       ]
      },
      "metadata": {},
@@ -1418,12 +1418,10 @@
     "\n",
     "def plot_covariance(var_x, var_y, cov_xy):\n",
     "    P1 = [[var_x, cov_xy], [cov_xy, var_y]]\n",
-    "    try:\n",
-    "        plot_covariance_ellipse((10, 10), P1, axis_equal=False,\n",
-    "                                show_semiaxis=True)\n",
-    "    except:\n",
-    "        plot_covariance_ellipse((10, 10), P1, axis_equal=False)\n",
-    "        \n",
+    "\n",
+    "    plot_covariance_ellipse((10, 10), P1, axis_equal=False,\n",
+    "                            show_semiaxis=True)\n",
+    "\n",
     "    plt.xlim(4, 16)\n",
     "    plt.gca().set_aspect('equal')\n",
     "    plt.ylim(4, 16)\n",
@@ -1459,7 +1457,7 @@
      "data": {
       "image/png": 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truncated
       "text/plain": [
-       "<matplotlib.figure.Figure at 0x87a2978>"
+       "<matplotlib.figure.Figure at 0x8c2f8d0>"
       ]
      },
      "metadata": {},
@@ -1492,7 +1490,7 @@
      "data": {
       "image/png": 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truncated
       "text/plain": [
-       "<matplotlib.figure.Figure at 0x876bba8>"
+       "<matplotlib.figure.Figure at 0x8c527f0>"
       ]
      },
      "metadata": {},
@@ -1541,7 +1539,7 @@
      "data": {
       "image/png": 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truncated
       "text/plain": [
-       "<matplotlib.figure.Figure at 0x8905198>"
+       "<matplotlib.figure.Figure at 0x8c8c198>"
       ]
      },
      "metadata": {},
@@ -1571,7 +1569,7 @@
      "data": {
       "image/png": 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truncated
       "text/plain": [
-       "<matplotlib.figure.Figure at 0x9421908>"
+       "<matplotlib.figure.Figure at 0x8cf75f8>"
       ]
      },
      "metadata": {},
@@ -1607,7 +1605,7 @@
      "data": {
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truncated
       "text/plain": [
-       "<matplotlib.figure.Figure at 0x896b9b0>"
+       "<matplotlib.figure.Figure at 0x8cfef60>"
       ]
      },
      "metadata": {},
@@ -1636,7 +1634,7 @@
      "data": {
       "image/png": 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truncated
       "text/plain": [
-       "<matplotlib.figure.Figure at 0x946e6d8>"
+       "<matplotlib.figure.Figure at 0x8c97e10>"
       ]
      },
      "metadata": {},
@@ -1665,7 +1663,7 @@
      "data": {
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truncated
       "text/plain": [
-       "<matplotlib.figure.Figure at 0x7271b38>"
+       "<matplotlib.figure.Figure at 0x7a4eda0>"
       ]
      },
      "metadata": {},
@@ -1696,7 +1694,7 @@
      "data": {
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truncated
       "text/plain": [
-       "<matplotlib.figure.Figure at 0x8870240>"
+       "<matplotlib.figure.Figure at 0x8d14710>"
       ]
      },
      "metadata": {},