Removed gray background from 538 style.

white background renders better on cheap LCDs, and it will print better as well.

04_Gaussians/Gaussians.ipynb

@@ -1,7 +1,7 @@
 {
  "metadata": {
   "name": "",
-  "signature": "sha256:f315c4edb8acd4ca7bed4bf2ad1a08de3002a20feab253ac00f882073b882911"
+  "signature": "sha256:402152422ec6a095e6eb2472fe34e23b3492cab93a8573e7060446a06e2e7a07"
  },
  "nbformat": 3,
  "nbformat_minor": 0,
@@ -261,7 +261,7 @@
        "output_type": "pyout",
        "prompt_number": 1,
        "text": [
-        "<IPython.core.display.HTML at 0x7f7f2a69e128>"
+        "<IPython.core.display.HTML at 0x7fbf8631b128>"
        ]
       }
      ],
@@ -300,9 +300,9 @@
       {
        "metadata": {},
        "output_type": "display_data",
-       "png": 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truncated
+       "png": "iVBORw0KGgoAAAANSUhEUgAAAygAAAGkCAYAAADaGQF7AAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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 truncated
        "text": [
-        "<matplotlib.figure.Figure at 0x7f7f117465f8>"
+        "<matplotlib.figure.Figure at 0x7fbf65c837b8>"
        ]
       }
      ],
@@ -346,9 +346,9 @@
       {
        "metadata": {},
        "output_type": "display_data",
-       "png": 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truncated
        "text": [
-        "<matplotlib.figure.Figure at 0x7f7f09ead5c0>"
+        "<matplotlib.figure.Figure at 0x7fbf65b2a400>"
        ]
       }
      ],
@@ -423,9 +423,9 @@
       {
        "metadata": {},
        "output_type": "display_data",
-       "png": 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        "text": [
-        "<matplotlib.figure.Figure at 0x7f7f06501748>"
+        "<matplotlib.figure.Figure at 0x7fbf65a83748>"
        ]
       }
      ],
@@ -548,9 +548,9 @@
       {
        "metadata": {},
        "output_type": "display_data",
-       "png": 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        "text": [
-        "<matplotlib.figure.Figure at 0x7f7f06403668>"
+        "<matplotlib.figure.Figure at 0x7fbf62071978>"
        ]
       }
      ],
@@ -590,9 +590,9 @@
       {
        "metadata": {},
        "output_type": "display_data",
-       "png": 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truncated
        "text": [
-        "<matplotlib.figure.Figure at 0x7f7f09e03e80>"
+        "<matplotlib.figure.Figure at 0x7fbf65a8b780>"
        ]
       }
      ],
@@ -646,9 +646,9 @@
       {
        "metadata": {},
        "output_type": "display_data",
-       "png": 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truncated
+       "png": 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truncated
        "text": [
-        "<matplotlib.figure.Figure at 0x7f7f09e32f98>"
+        "<matplotlib.figure.Figure at 0x7fbf65a7beb8>"
        ]
       },
       {
@@ -782,10 +782,9 @@
        "output_type": "stream",
        "stream": "stdout",
        "text": [
-        "[  2.07782254e+00   2.92284291e+00   3.41939607e+00  -2.74017280e+00\n",
-        "  -9.35326550e-01   2.12233068e+00  -2.40918322e-01  -1.43619992e+00\n",
-        "   3.98720795e+00   6.65972692e-02   4.31909653e+00  -3.55998844e+00\n",
-        "   1.53055228e+00   2.65472646e+00   1.13045111e-03]\n"
+        "[ 3.39543572  3.92455822 -1.47839831 -1.33968944  4.64280739  3.57337785\n",
+        "  2.4334426  -2.65214049  0.09098526  0.59452311  3.72292568  4.64627724\n",
+        "  2.35639579  2.19228319  1.02386714]\n"
        ]
       }
      ],

04_Gaussians/Gaussians_Animations.ipynb

@@ -1,7 +1,7 @@
 {
  "metadata": {
   "name": "",
-  "signature": "sha256:a64f35e7df2ba17ebd70c1debdf2b30922efaea2cea89784b53ec3b424b2eadc"
+  "signature": "sha256:c9bc1ab3d4c4d98f1a764e1c04e56097cb0fd31b74ccc69ddffcc67d4d96ef4d"
  },
  "nbformat": 3,
  "nbformat_minor": 0,
@@ -247,7 +247,7 @@
        "output_type": "pyout",
        "prompt_number": 1,
        "text": [
-        "<IPython.core.display.HTML at 0x7fba31a08f98>"
+        "<IPython.core.display.HTML at 0x7f1f0bb83f60>"
        ]
       }
      ],
@@ -294,9 +294,9 @@
       {
        "metadata": {},
        "output_type": "display_data",
-       "png": 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truncated
+       "png": 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truncated
        "text": [
-        "<matplotlib.figure.Figure at 0x7fba1557def0>"
+        "<matplotlib.figure.Figure at 0x7f1ee8230438>"
        ]
       }
      ],