save plots in sentiment evaluation
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		| @ -43,6 +43,7 @@ | ||||
|     "import re\n", | ||||
|     "import matplotlib.pyplot as plt\n", | ||||
|     "import matplotlib\n", | ||||
|     "import datetime\n", | ||||
|     "matplotlib.rc('font', family='symbola', size=16)" | ||||
|    ] | ||||
|   }, | ||||
| @ -116,7 +117,7 @@ | ||||
|     "        pred_X = np.array([sentiment_score(x) for x in predicted_sentiment_vectors_list[i]])\n", | ||||
|     "        pred_Y = np.array([x[2] for x in predicted_sentiment_vectors_list[i]])\n", | ||||
|     "        plt.plot(pred_X, pred_Y, style[i], alpha=0.5)\n", | ||||
|     "    #plt.savefig(\"val-error_sentiment-plot\" + str(datetime.datetime.now()) +  \".png\", bbox_inches='tight')\n", | ||||
|     "    plt.savefig(\"val-error_sentiment-plot\" + str(datetime.datetime.now()) +  \".png\", bbox_inches='tight')\n", | ||||
|     "\n", | ||||
|     "    # sentiment score axis\n", | ||||
|     "    top_X = np.array([x[0] for x in top_sentiments])\n", | ||||
| @ -138,7 +139,7 @@ | ||||
|     "        pred_X = np.array([x[0] for x in predicted_sentiment_vectors_list[i]])\n", | ||||
|     "        pred_Y = np.array([x[1] for x in predicted_sentiment_vectors_list[i]])\n", | ||||
|     "        plt.plot(pred_X, pred_Y, style[i], alpha=0.5)\n", | ||||
|     "    #'plt.savefig(\"val-error_positive-negative-plot\" + str(datetime.datetime.now()) + \".png\", bbox_inches='tight')\n", | ||||
|     "    plt.savefig(\"val-error_positive-negative-plot\" + str(datetime.datetime.now()) + \".png\", bbox_inches='tight')\n", | ||||
|     "    plt.show()" | ||||
|    ] | ||||
|   }, | ||||
|  | ||||
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