forked from kubapok/paranormal-or-skeptic-ISI-public
324 lines
6.6 KiB
Plaintext
324 lines
6.6 KiB
Plaintext
{
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"cells": [
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{
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"cell_type": "code",
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"execution_count": 1,
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"metadata": {},
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"outputs": [],
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"source": [
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"import numpy as np\n",
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"import pandas as pd\n",
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"import patoolib\n",
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"import os\n",
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"import patoolib\n",
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"from sklearn.preprocessing import LabelEncoder\n",
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"from sklearn.naive_bayes import GaussianNB, MultinomialNB\n",
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"from sklearn.pipeline import Pipeline\n",
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"from sklearn.feature_extraction.text import TfidfVectorizer"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"## TRENING"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"#### ROZPAKOWANIE I WCZYTANIE"
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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": 2,
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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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"patool: Extracting train/in.tsv.xz ...\n",
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"patool: running \"\"C:\\Program Files\\Git\\mingw64\\bin\\xz.EXE\"\" -c -d -- train/in.tsv.xz > train/in.tsv\n",
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"patool: with shell=True\n",
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"patool: ... train/in.tsv.xz extracted to `train/'.\n"
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]
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}
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],
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"source": [
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"EXPECTED_FILE = open('train/expected.tsv', 'r', encoding=\"utf-8\")\n",
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"\n",
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"patoolib.extract_archive(\"train/in.tsv.xz\", outdir=\"train/\")\n",
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"TRAIN = open('train/in.tsv', 'r', encoding=\"utf-8\")"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"#### WRZUCENIE DO ZMIENNYCH"
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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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"source": [
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"EXPECTED = []\n",
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"for line in EXPECTED_FILE:\n",
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" EXPECTED.append(line)"
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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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"outputs": [],
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"source": [
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"TRAIN_DATA = []\n",
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"for line in TRAIN:\n",
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" TRAIN_DATA.append(line)"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"#### ZAMKNIECIE ZMIENNYCH PLIKOW I USUNIECIE ROZPAKOWANIA"
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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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"EXPECTED_FILE.close()\n",
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"TRAIN.close()\n",
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"#os.remove(\"train/in.tsv\")"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"#### MODEL TRENINGOWY"
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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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"outputs": [],
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"source": [
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"EXPECTED_ENCODER = LabelEncoder().fit_transform(EXPECTED)"
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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": 7,
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"metadata": {},
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"outputs": [],
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"source": [
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"PIPE = Pipeline(steps=[(\"TF-IDF\",TfidfVectorizer()), (\"BAYES\", MultinomialNB())])"
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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": 8,
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"metadata": {},
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"outputs": [],
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"source": [
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"TRAIN_MODEL = PIPE.fit(TRAIN_DATA, EXPECTED_ENCODER)"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"## FUNKCJE"
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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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"metadata": {},
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"outputs": [],
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"source": [
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"def BayesFit(MODEL, DOC):\n",
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" PREDICTION = MODEL.predict(DOC)\n",
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" return PREDICTION"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"## PLIK DEV-0"
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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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{
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"patool: Extracting dev-0/in.tsv.xz ...\n",
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"patool: running \"\"C:\\Program Files\\Git\\mingw64\\bin\\xz.EXE\"\" -c -d -- dev-0/in.tsv.xz > dev-0/in.tsv\n",
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"patool: with shell=True\n",
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"patool: ... dev-0/in.tsv.xz extracted to `dev-0/'.\n"
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]
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}
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],
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"source": [
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"patoolib.extract_archive(\"dev-0/in.tsv.xz\", outdir=\"dev-0/\")\n",
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"INFILE = open('dev-0/in.tsv', 'r', encoding=\"utf-8\")\n",
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"\n",
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"OUTFILE = open(\"dev-0/out.tsv\", \"w\")"
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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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"ALL_DOC = INFILE.readlines()"
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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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"metadata": {},
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"outputs": [],
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"source": [
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"RESULT = BayesFit(TRAIN_MODEL, ALL_DOC)"
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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": 13,
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"metadata": {},
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"outputs": [],
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"source": [
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"for x in RESULT:\n",
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" OUTFILE.write(str(x) + '\\n')"
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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": 14,
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"metadata": {},
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"outputs": [],
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"source": [
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"INFILE.close()\n",
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"OUTFILE.close()\n",
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"#os.remove(\"dev-0/in.tsv\")"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"## PLIK TEST-A"
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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": 15,
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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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"patool: Extracting test-A/in.tsv.xz ...\n",
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"patool: running \"\"C:\\Program Files\\Git\\mingw64\\bin\\xz.EXE\"\" -c -d -- test-A/in.tsv.xz > test-A/in.tsv\n",
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"patool: with shell=True\n",
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"patool: ... test-A/in.tsv.xz extracted to `test-A/'.\n"
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]
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}
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],
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"source": [
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"patoolib.extract_archive(\"test-A/in.tsv.xz\", outdir=\"test-A/\")\n",
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"INFILE = open('test-A/in.tsv', 'r', encoding=\"utf-8\")\n",
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"\n",
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"OUTFILE = open(\"test-A/out.tsv\", \"w\")"
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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": 16,
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"metadata": {},
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"outputs": [],
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"source": [
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"ALL_DOC = INFILE.readlines()"
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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": 17,
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"metadata": {},
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"outputs": [],
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"source": [
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"RESULT = BayesFit(TRAIN_MODEL, ALL_DOC)"
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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": 18,
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"metadata": {},
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"outputs": [],
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"source": [
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"for x in RESULT:\n",
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" OUTFILE.write(str(x) + '\\n')"
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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": 19,
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"metadata": {},
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"outputs": [],
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"source": [
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"INFILE.close()\n",
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"OUTFILE.close()\n",
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"#os.remove(\"test-A/in.tsv\")"
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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": null,
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"metadata": {},
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"outputs": [],
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"source": []
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}
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],
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"metadata": {
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"kernelspec": {
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"display_name": "Python 3",
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"language": "python",
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"name": "python3"
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},
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"language_info": {
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"codemirror_mode": {
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"name": "ipython",
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"version": 3
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},
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"file_extension": ".py",
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"mimetype": "text/x-python",
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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": "3.8.5"
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}
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},
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"nbformat": 4,
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"nbformat_minor": 4
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}
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