170 lines
100 KiB
Plaintext
170 lines
100 KiB
Plaintext
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{
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"cells": [
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{
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"cell_type": "code",
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"execution_count": 2,
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"metadata": {},
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"outputs": [],
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"source": [
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"%matplotlib inline"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 3,
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"metadata": {},
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"outputs": [
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{
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"data": {
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"image/png": "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"text/plain": [
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"<Figure size 432x288 with 1 Axes>"
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]
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},
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"metadata": {},
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"output_type": "display_data"
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}
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],
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"source": [
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"from __future__ import unicode_literals\n",
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"\n",
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"import matplotlib.pyplot as plt\n",
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"\n",
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"#plt.rc('font', family='Arial') \n",
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"\n",
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"#plt.rc('font', **{'sans-serif' : 'Arial', 'family' : 'sans-serif'}) \n",
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"\n",
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"plt.title('Développés et fabriqués')\n",
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"plt.xlabel(\"réactivité nous permettent d'être sélectionnés et adoptés\")\n",
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"plt.ylabel('André was here!')\n",
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"plt.text(0.2, 0.8, '😂')\n",
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"#plt.text(0.4, 0.2, 'AVA (check kerning)')\n",
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"\n",
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"plt.show()"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 5,
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"metadata": {},
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"outputs": [],
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"source": [
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"def sentiment_score(s):\n",
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" #(pos, neg, neu)^T\n",
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" return s[0] - s[1]"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 10,
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"metadata": {},
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"outputs": [],
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"source": [
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"import Emoji_Distance as edist\n",
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"import numpy as np"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 11,
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"metadata": {},
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"outputs": [],
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"source": [
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"list_emoticon_scores = np.array([sentiment_score(x) for x in edist.list_sentiment_emoticon_vectors])"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 23,
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"metadata": {},
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"outputs": [],
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"source": [
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"def plot_emoji_list(sentiment_vectors, unicode_repr, title=\"Emoji Space\"):\n",
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" \n",
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" # sentiment score axis\n",
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" X = np.array([sentiment_score(x) for x in sentiment_vectors])\n",
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" \n",
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" # neutral axis:\n",
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" Y = np.array([x[2] for x in sentiment_vectors])\n",
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" \n",
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" plt.title(title)\n",
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" plt.xlabel(\"sentiment score\")\n",
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" plt.ylabel(\"neutrality\")\n",
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" plt.xlim([-1,1])\n",
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" for i in range(len(X)):\n",
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" plt.text(X[i], Y[i], unicode_repr[i])\n",
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" plt.show()\n",
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" "
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]
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},
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{
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"cell_type": "code",
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"execution_count": 24,
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"metadata": {},
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"outputs": [
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{
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"data": {
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"image/png": "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
|
||
|
|
"text/plain": [
|
||
|
|
"<Figure size 432x288 with 1 Axes>"
|
||
|
|
]
|
||
|
|
},
|
||
|
|
"metadata": {},
|
||
|
|
"output_type": "display_data"
|
||
|
|
}
|
||
|
|
],
|
||
|
|
"source": [
|
||
|
|
"plot_emoji_list(sentiment_vectors=edist.list_sentiment_emoticon_vectors, unicode_repr=edist.list_emoticon_emojis, title=\"Emoticon Emoji space\")"
|
||
|
|
]
|
||
|
|
},
|
||
|
|
{
|
||
|
|
"cell_type": "code",
|
||
|
|
"execution_count": 25,
|
||
|
|
"metadata": {},
|
||
|
|
"outputs": [
|
||
|
|
{
|
||
|
|
"data": {
|
||
|
|
"image/png": "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
|
||
|
|
"text/plain": [
|
||
|
|
"<Figure size 432x288 with 1 Axes>"
|
||
|
|
]
|
||
|
|
},
|
||
|
|
"metadata": {},
|
||
|
|
"output_type": "display_data"
|
||
|
|
}
|
||
|
|
],
|
||
|
|
"source": [
|
||
|
|
"plot_emoji_list(sentiment_vectors=edist.list_sentiment_vectors, unicode_repr=edist.list_emojis, title=\"Full Emoji space\")"
|
||
|
|
]
|
||
|
|
},
|
||
|
|
{
|
||
|
|
"cell_type": "code",
|
||
|
|
"execution_count": null,
|
||
|
|
"metadata": {},
|
||
|
|
"outputs": [],
|
||
|
|
"source": []
|
||
|
|
}
|
||
|
|
],
|
||
|
|
"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": "3.6.5"
|
||
|
|
}
|
||
|
|
},
|
||
|
|
"nbformat": 4,
|
||
|
|
"nbformat_minor": 2
|
||
|
|
}
|