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Update text.ipynb (aimacode#644)
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text.ipynb

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@@ -18,7 +18,8 @@
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"outputs": [],
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"source": [
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"from text import *\n",
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"from utils import open_data"
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"from utils import open_data\n",
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"from notebook import psource"
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]
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},
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{
@@ -55,46 +56,11 @@
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},
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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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"collapsed": true
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},
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"outputs": [],
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"source": [
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"%psource UnigramWordModel"
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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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"collapsed": true
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},
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"outputs": [],
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"source": [
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"%psource NgramWordModel"
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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": 4,
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"metadata": {
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"collapsed": true
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},
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"outputs": [],
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"source": [
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"%psource UnigramCharModel"
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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": 6,
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"metadata": {
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"collapsed": true
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},
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"execution_count": null,
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"metadata": {},
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"outputs": [],
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"source": [
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"%psource NgramCharModel"
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"psource(UnigramWordModel, NgramWordModel, UnigramCharModel, NgramCharModel)"
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]
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},
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{
@@ -117,7 +83,7 @@
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},
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{
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"cell_type": "code",
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"execution_count": 8,
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"execution_count": 2,
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"metadata": {},
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"outputs": [
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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": 12,
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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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"name": "stdout",
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"output_type": "stream",
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"text": [
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"Conditional Probabilities Table: {'myself': 1, 'to': 2, 'at': 2, 'pleased': 1, 'considered': 1, 'will': 1, 'intoxicated': 1, 'glad': 1, 'certain': 2, 'in': 2, 'now': 2, 'sitting': 1, 'unusually': 1, 'approaching': 1, 'by': 1, 'covered': 1, 'standing': 1, 'allowed': 1, 'surprised': 1, 'keenly': 1, 'afraid': 1, 'once': 2, 'crushed': 1, 'not': 4, 'rapt': 1, 'simulating': 1, 'rapidly': 1, 'quite': 1, 'describing': 1, 'wearied': 1} \n",
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"Conditional Probabilities Table: {'now': 2, 'glad': 1, 'keenly': 1, 'considered': 1, 'once': 2, 'not': 4, 'in': 2, 'by': 1, 'simulating': 1, 'intoxicated': 1, 'wearied': 1, 'quite': 1, 'certain': 2, 'sitting': 1, 'to': 2, 'rapidly': 1, 'will': 1, 'describing': 1, 'allowed': 1, 'at': 2, 'afraid': 1, 'covered': 1, 'approaching': 1, 'standing': 1, 'myself': 1, 'surprised': 1, 'unusually': 1, 'rapt': 1, 'pleased': 1, 'crushed': 1} \n",
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"\n",
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"Conditional Probability of 'once' give 'i was': 0.05128205128205128 \n",
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"\n",
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"Next word after 'i was': not\n"
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"Next word after 'i was': wearied\n"
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]
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}
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],
@@ -198,7 +164,7 @@
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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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"execution_count": 4,
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"metadata": {},
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"outputs": [
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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": 4,
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"execution_count": 5,
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"metadata": {},
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"outputs": [
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{
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"not it of before most regions multitudes the a three\n",
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"the inhabitants of so also refers to the cube with\n",
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"the service of education waxed daily more numerous than the\n"
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"hearing as inside is confined to conduct by the duties\n",
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"all and of voice being in a day of the\n",
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"party they are stirred to mutual warfare and perish by\n"
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]
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}
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],
@@ -283,23 +249,22 @@
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},
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{
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"cell_type": "code",
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"execution_count": 19,
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"execution_count": 6,
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"metadata": {},
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"outputs": [
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{
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"it again stealing away through the ranks of his nephew but he laughed most immoderately\n",
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"exclaiming that he henceforth exchanged them for the artist s pencil how great and glorious\n",
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"compound now for nothing worse but however all that is quite out of the question\n",
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"accordance with precedent and for the sake of secrecy he must condemn him to perpetual\n"
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"leave them at cleveland this christmas now pray do not ask you to relate or\n",
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"meaning and both of us sprang forward in the direction and no sooner had they\n",
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"palmer though very unwilling to go as well from real humanity and good nature as\n",
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"time about what they should do and they agreed he should take orders directly and\n"
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]
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}
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],
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"source": [
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"data = open_data(\"EN-text/flatland.txt\").read()\n",
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"data += open_data(\"EN-text/gutenberg.txt\").read()\n",
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"data += open_data(\"EN-text/sense.txt\").read()\n",
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"\n",
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"wordseq = words(data)\n",
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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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"collapsed": true
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},
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"execution_count": null,
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"metadata": {},
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"outputs": [],
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"source": [
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"%psource viterbi_segment"
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"psource(viterbi_segment)"
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]
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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": 4,
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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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"source": [
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"flatland = open_data(\"EN-text/flatland.txt\").read()\n",
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"wordseq = words(flatland)\n",
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"P = UnigramTextModel(wordseq)\n",
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"P = UnigramWordModel(wordseq)\n",
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"text = \"itiseasytoreadwordswithoutspaces\"\n",
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"\n",
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"s, p = viterbi_segment(text,P)\n",
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},
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"outputs": [],
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"source": [
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"%psource IRSystem"
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"psource(IRSystem)"
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]
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},
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{
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},
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"outputs": [],
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"source": [
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"%psource UnixConsultant"
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"psource(UnixConsultant)"
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]
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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": 9,
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"execution_count": 4,
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"metadata": {},
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"outputs": [
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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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"execution_count": 5,
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"metadata": {},
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"outputs": [
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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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"execution_count": 6,
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"metadata": {},
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"outputs": [
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{
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},
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"cell_type": "code",
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"execution_count": 6,
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"execution_count": 7,
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"metadata": {},
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"outputs": [
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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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"collapsed": true
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},
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"execution_count": null,
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"metadata": {},
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"outputs": [],
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"source": [
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"%psource PermutationDecoder"
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"psource(PermutationDecoder)"
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]
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},
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{
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"name": "python",
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"nbconvert_exporter": "python",
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"pygments_lexer": "ipython3",
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"version": "3.5.2+"
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"version": "3.5.3"
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}
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},
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"nbformat": 4,

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