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Unverified Commit 05f230d1 authored by Mark Daoust's avatar Mark Daoust Committed by GitHub
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Smaller figure grid, remove tics from bar plots.

parent b2e03585
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Showing with 10 additions and 12 deletions
samples/core/tutorials/keras/basic_classification.ipynb
View file @ 05f230d1
...@@ -541,9 +541,6 @@ ...@@ -541,9 +541,6 @@
}, },
"cell_type": "code", "cell_type": "code",
"source": [ "source": [
"import matplotlib.pyplot as plt\n",
"%matplotlib inline\n",
"\n",
"plt.figure(figsize=(10,10))\n", "plt.figure(figsize=(10,10))\n",
"for i in range(25):\n", "for i in range(25):\n",
" plt.subplot(5,5,i+1)\n", " plt.subplot(5,5,i+1)\n",
...@@ -882,6 +879,8 @@ ...@@ -882,6 +879,8 @@
"\n", "\n",
"def plot_value_array(predictions_array, true_label):\n", "def plot_value_array(predictions_array, true_label):\n",
" plt.grid('off')\n", " plt.grid('off')\n",
" plt.xticks([])\n",
" plt.yticks([])\n",
" thisplot = plt.bar(range(10), predictions_array, color=\"#777777\")\n", " thisplot = plt.bar(range(10), predictions_array, color=\"#777777\")\n",
" plt.ylim([0, 1]) \n", " plt.ylim([0, 1]) \n",
" predicted_label = np.argmax(predictions_array)\n", " predicted_label = np.argmax(predictions_array)\n",
...@@ -961,16 +960,15 @@ ...@@ -961,16 +960,15 @@
"source": [ "source": [
"# Plot the first X test images, their predicted label, and the true label\n", "# Plot the first X test images, their predicted label, and the true label\n",
"# Color correct predictions in blue, incorrect predictions in red\n", "# Color correct predictions in blue, incorrect predictions in red\n",
"num_images = int(50)\n", "num_rows = 5\n",
"plt.figure(figsize=(24,20))\n", "num_cols = 3\n",
"num_images = num_rows*num_cols\n",
"plt.figure(figsize=(2*2*num_cols, 2*num_rows))\n",
"for i in range(num_images):\n", "for i in range(num_images):\n",
" plt.subplot(10,num_images / 5,2*i+1)\n", " plt.subplot(num_rows, 2*num_cols, 2*i+1)\n",
" plot_image(predictions[i], test_labels[i], test_images[i])\n", " plot_image(predictions[i], test_labels[i], test_images[i])\n",
" \n", " plt.subplot(num_rows, 2*num_cols, 2*i+2)\n",
" plt.subplot(10,num_images / 5,2*i+2)\n", " plot_value_array(predictions[i], test_labels[i])\n",
" plt.xticks([])\n",
" plt.yticks([])\n",
" plot_value_array(predictions[i], test_labels[i])"
], ],
"execution_count": 0, "execution_count": 0,
"outputs": [] "outputs": []
......
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