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DL_Genomics_v10_basic-pytorch-fastq.ipynb
106719 lines (106718 with data), 2.2 MB
{
"cells": [
{
"cell_type": "markdown",
"metadata": {},
"source": [
"# Deep learning in genomics - Basic model with PyTorch"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"This notebook is based on the [jupyter notebook](https://nbviewer.jupyter.org/github/abidlabs/deep-learning-genomics-primer/blob/master/A_Primer_on_Deep_Learning_in_Genomics_Public.ipynb) from the publication [\"A primer on deep learning in genomics\"](https://www.nature.com/articles/s41588-018-0295-5) but uses the [PyTorch](https://pytorch.org) library."
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"# Notebook setup"
]
},
{
"cell_type": "code",
"execution_count": 6,
"metadata": {},
"outputs": [],
"source": [
"%reload_ext autoreload\n",
"%autoreload 2\n",
"%matplotlib inline"
]
},
{
"cell_type": "code",
"execution_count": 7,
"metadata": {},
"outputs": [],
"source": [
"from fastai import *\n",
"from fastai.vision import *"
]
},
{
"cell_type": "code",
"execution_count": 8,
"metadata": {},
"outputs": [],
"source": [
"from sklearn.preprocessing import LabelEncoder, OneHotEncoder"
]
},
{
"cell_type": "code",
"execution_count": 9,
"metadata": {},
"outputs": [],
"source": [
"import pdb"
]
},
{
"cell_type": "code",
"execution_count": 10,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"'1.0.39.dev0'"
]
},
"execution_count": 10,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"# fastai version\n",
"__version__"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"# Data setup"
]
},
{
"cell_type": "markdown",
"metadata": {
"heading_collapsed": true
},
"source": [
"## Load data from disk, generate dataframe, and save to disk"
]
},
{
"cell_type": "code",
"execution_count": 6,
"metadata": {
"hidden": true
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"/Users/MMP/Downloads/genomics\r\n"
]
}
],
"source": [
"!pwd"
]
},
{
"cell_type": "code",
"execution_count": 7,
"metadata": {
"hidden": true
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"/Volumes/HDD08/ugenomfit/data/SRR1993099.sra_1.fastq\r\n",
"/Volumes/HDD08/ugenomfit/data/SRR1993099.sra_2.fastq\r\n",
"/Volumes/HDD08/ugenomfit/data/SRR5665975.sra_1.fastq\r\n",
"/Volumes/HDD08/ugenomfit/data/SRR5665975.sra_2.fastq\r\n"
]
}
],
"source": [
"!ls /Volumes/HDD08/ugenomfit/data/*.fastq"
]
},
{
"cell_type": "code",
"execution_count": 8,
"metadata": {
"hidden": true
},
"outputs": [
{
"data": {
"text/plain": [
"PosixPath('/Volumes/HDD08/ugenomfit/data')"
]
},
"execution_count": 8,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"PATH_raw_data = Path('/Volumes/HDD08/ugenomfit/data/'); PATH_raw_data"
]
},
{
"cell_type": "code",
"execution_count": 9,
"metadata": {
"hidden": true
},
"outputs": [],
"source": [
"from Bio import SeqIO"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"hidden": true
},
"outputs": [],
"source": []
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"hidden": true
},
"outputs": [],
"source": []
},
{
"cell_type": "code",
"execution_count": 204,
"metadata": {
"hidden": true
},
"outputs": [],
"source": [
"def get_seqs(path, seq_per_file=500):\n",
" label, seq, score = [], [], []\n",
" for n, fn in enumerate((path).glob('*.fastq')):\n",
" \n",
" # print file number n\n",
" #print(n)\n",
" \n",
" # print file number n and filename fn\n",
" print(n, fn)\n",
" \n",
" # append sequences\n",
" for m, record in enumerate(SeqIO.parse(fn, 'fastq')):\n",
" \n",
" #print(m)\n",
" if m == seq_per_file: break # only read in the first m sequences per fastq file\n",
" \n",
" # append sequences\n",
" seq.append(str(record.seq))\n",
" score.append(record.letter_annotations['phred_quality'])\n",
" \n",
" # print genome name including contig number and sequence length\n",
" #print(\"%s %i\" % (record.id, len(record)))\n",
" \n",
" # append genome labels\n",
" label.append(str(record.id))\n",
" \n",
" #pdb.set_trace() # start debugger\n",
" \n",
" # break loop\n",
" #if n == 1: break\n",
" return label, seq, score"
]
},
{
"cell_type": "code",
"execution_count": 205,
"metadata": {
"hidden": true
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
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]
}
],
"source": [
"label, seq, score = get_seqs(PATH_raw_data)"
]
},
{
"cell_type": "code",
"execution_count": 206,
"metadata": {
"hidden": true
},
"outputs": [
{
"data": {
"text/plain": [
"['SRR1993099.sra.1',\n",
" 'SRR1993099.sra.2',\n",
" 'SRR1993099.sra.3',\n",
" 'SRR1993099.sra.4',\n",
" 'SRR1993099.sra.5',\n",
" 'SRR1993099.sra.6',\n",
" 'SRR1993099.sra.7',\n",
" 'SRR1993099.sra.8',\n",
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" 'SRR1993099.sra.469',\n",
" 'SRR1993099.sra.470',\n",
" 'SRR1993099.sra.471',\n",
" 'SRR1993099.sra.472',\n",
" 'SRR1993099.sra.473',\n",
" 'SRR1993099.sra.474',\n",
" 'SRR1993099.sra.475',\n",
" 'SRR1993099.sra.476',\n",
" 'SRR1993099.sra.477',\n",
" 'SRR1993099.sra.478',\n",
" 'SRR1993099.sra.479',\n",
" 'SRR1993099.sra.480',\n",
" 'SRR1993099.sra.481',\n",
" 'SRR1993099.sra.482',\n",
" 'SRR1993099.sra.483',\n",
" 'SRR1993099.sra.484',\n",
" 'SRR1993099.sra.485',\n",
" 'SRR1993099.sra.486',\n",
" 'SRR1993099.sra.487',\n",
" 'SRR1993099.sra.488',\n",
" 'SRR1993099.sra.489',\n",
" 'SRR1993099.sra.490',\n",
" 'SRR1993099.sra.491',\n",
" 'SRR1993099.sra.492',\n",
" 'SRR1993099.sra.493',\n",
" 'SRR1993099.sra.494',\n",
" 'SRR1993099.sra.495',\n",
" 'SRR1993099.sra.496',\n",
" 'SRR1993099.sra.497',\n",
" 'SRR1993099.sra.498',\n",
" 'SRR1993099.sra.499',\n",
" 'SRR1993099.sra.500',\n",
" ...]"
]
},
"execution_count": 206,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"#label"
]
},
{
"cell_type": "code",
"execution_count": 207,
"metadata": {
"hidden": true
},
"outputs": [],
"source": [
"#seq[-1][:100]"
]
},
{
"cell_type": "code",
"execution_count": 208,
"metadata": {
"hidden": true
},
"outputs": [
{
"data": {
"text/plain": [
"['ATCTACAAGAAGGGTGAAGTGCTTTTCGAATTTTGCCACTGCAAGTAATTGGTGCAATTGAAATACGAGCTTTCGTTCTCTAAGAGGATATAAAAATAAG',\n",
" 'TGTGCTCCATGTCGATATTTCGTGGAGCAAACCAAAAAAGATGCGGAACCTCTTAGCACTCCGCCTGGACATAGGCGGAGCATATTCCTCCTATAGGATG',\n",
" 'NACCCTTTATAAAAGCCTAGATGTAGCAGTGCGAAGCGAACTCGATACTTGCTCATCATTGATTTCGGCATCTTTGTATAGAAAACTACAAATGTCTGAC',\n",
" 'CGAATGGGACCTTGAATGGATTAACGAGATTCCCACTGTCCCTATCTACTATCTAGCGAAACCACAGCCAAGGGAACGGGCTTGGCAGAATCAGTGGGGA',\n",
" 'CACACCGCAGTAGATGGAAAACTCGAGTTTTACATGGAACAGGTAAATAAATTTCCTCCAATCTTGTACCAATGGTTTTTAGAAAACTTTCCTGATCCAA',\n",
" 'TAGGGGTTTCATCGTAGTTTATGTTACACCATTTCAGAATCTCGTAGATGTTTTCTTCTGCTCTTTTTATTAGCTTCTTCTGGTTTGTATCTTCTAAACG',\n",
" 'CCACGATGAGACTGTTCAGGTTAAACGTGGGCATCTTGCGATTCCATTGGTGAGCAGCGAAGGATTTGGTGGATTACTAGCTAATAGCAATCTATTTCAA',\n",
" 'AAGAACCACCGAAACATTAAAAGTGGGAATAATGTCGCATCAAATGGCGCCATGGATACCCATGTTTATTCAATCGTGCAAAAATAACACTGAACCGTTT',\n",
" 'CTTAAGTAACTAGTAGTATTACACTAGAAAGCTCCTCTTTCCACTGTCTCTTTCTCGCGTTTTATTCTTTTCCGTTTGAGACAAAAAAAGAGGAGCTTTC',\n",
" 'AAGCCAGTTATCCCTGTGGTAACTTTTCTGGCACCTCTAGCCTCAAATTCCGAGGGACTAAAGGATCGATAGGCCACACTTTCATGGTTTGTATTCACAC',\n",
" 'ATGCTATCCTAATCTAACCCTCGCCAACCTGTCTCCAAACTTACCCTCCATTACCCTACTGTCCACTCGTTACCCTGTCCCATTCAACCATACCACCCCA',\n",
" 'AATTTACATAAACAACTGGATCTTTCTCAAAATAATGAACGCAGGTTAATTGATTCCAGTAAAACAGAGACACTAAAAATAATTGATTTAAATAATACAT',\n",
" 'AGCCTTGGTGAACTTTCCTCCAATTACTTTTCCATTAAGTAAATATATGTTACCAATTTGTGATTTATAATACGGTTGGTTACCATACGAGGCATCGCTT',\n",
" 'TGGCTAATCAAAATATTACTGCCTGCTTTACCAGAAACACTTTAGAAAGATCGGATGGTACAGTACTAGCTCCCATAGTCAAACATGGAGACTTTTACTG',\n",
" 'CGGGCCCAAAGTTCAACTACGAGCTTTTTAACTGCAACAACTTTAATATACGCTATTGGAGCTGGGCCCGGTTGGAGCTGGAATTACCGCAGCTCCAACC',\n",
" 'ACTGATCCAACTTATGGATTTGTTTGGGGCATTAGAACTTTAGGATTTTTAGATTTGGCTTTGCTAACTCTGTCAATCATTTTAGTCAAAGAGAGGTTAA',\n",
" 'GCGAACTTCGATTCCTAAAAATTCTGTGCTGCTTTATTCTTTCTGAGCCTGGTATGGTTGAGGCGTTTTGAGAGTCTGATCTTATGGGAGTTTTTAGTTC',\n",
" 'GGGAGAGCAAGCACGAAGGTGAACATTGCCTACAAGAAAAAATGGATGTTTTATTGTCGCTTCCTCAACCGGAATTATTTAAGACCACGGTGATTCCGTT',\n",
" 'TACCGGTAGAAGGATTAGAGAACGCTGGTCAAGACGGTGGTATGTTGCATTTAGCTTTCAGCTTTAAGCCAAGATACACCATTAGCGTGAGTAAAAGAGA',\n",
" 'TGTGATCCTGAAAACCGCGCTTCTTACGTTGGACCATGATGATCACATTTATAAATATGGTTTTCTTTCCAATGCGCATTTCACTTTGTGTGAATTCAAT',\n",
" 'NAATAATAAAGAAGAACAACCGACGCTTATTGGGACAATAGGCGTTATACTTTGTTGATTGAGAATGAAAGTGACGATGAATATTCGGCTCTCAACAGAA',\n",
" 'AGGTAGTGACAATAAATAACGATACAGGGCCCAATCGGGTCTTGTAATTGGAATGAGTACAATGTAAATACCTTAACGAGGAACAATTGGAGAGCAAGTC',\n",
" 'ACTTGGAGGTTATAAAGTGCAAGGTAGCAAAAGTCTATTACAAATGCAGGAGCTGTATGAAACCGCCATGCAACTACAAAAAATTGGCTGTTGGTCTATC',\n",
" 'CTTCTTTTATATAAGCCAATCTTCCACACGAAAAACCGAGTAATCCAATTTACTTTTTCTACTTTTTTTTCATTATCAATCGATTCAGATGCCCAGAGAA',\n",
" 'GGGCCACAATCACAGTTTCCGCAGTATCCATCATCAGTTGGAACGCCTCTGAGCACTCCATCACCTGAGTCAGGTAATACATTTACTGATTCATCCTCAG',\n",
" 'ACAACAACTAATATACACTAATTGTCCTTGATAACAGAACTTGTTGTAGTTTTATTCCGTGGGGAGGAGGGTGAATTTTTTTTATTTAGTTTTAAAGAAC',\n",
" 'TCACAGACCTGTTATTGCCTCAAACTTCCATCGGCTTGAAACCGATAGTCCCGCTAAGAAGAGGGAAACCGGCAAATGCTAGCACCACTATTTAGTGGCG',\n",
" 'CAAGTCAATGTGAGGTTGTTCCTCCGTGGAACCCAACTTGTTGATACTAAGCTTCCCTAACCCGCTAACCGGTTTCAAAATGTATTGATGCTTGGGGGCA',\n",
" 'AAGTGGGTAAACTTACTTCTGGGCAACCAACGGCTAAGGCTATTATTATTTCTGAAGTTTGTTGTCATTTCACTAACGCTCTCAACAATGTAGTTTAGAT',\n",
" 'AATTTCAGACTTACAGATATCCCAATGTTTGTCTCACATCGGGATATCTGTAAGTCTGAAATTTCTTTCAATGAATCCAATGGACCCAAACATACAGTGA',\n",
" 'TAAAAAGTGTACTCTTTGAGAAATAATTTCTTGGTGGTACAGAGGGCTTGGATGCGGGAGCATCCTTTGTTCCAGTTGGTTTTTCCTTGTAATAAAACCT',\n",
" 'NAATGACCAATTGCTGAGAGGTTAAATAGAGATCAAAATAGTTCTTGTTAAAAAGTTTTTCAGTCAATTTAAGTAAAGCTTTGGCATTTGTTCTTTGATA',\n",
" 'ACCAGAATCTATTAGTGGCAGATAGGCCAGAAAAAATTGTTTACCTGGACGTTTTTTCCTTGAAAATTCTCTATAACAAGTTCCATGCCTTCTACTTTAC',\n",
" 'CAGTATATACACACTTCCTTTTATTTTCGTCTCATCTTGTATTTTCATTTGAAGGACGGAATATTTACTTTTCATGGCTTGTATTTTTACTCGATTCCAA',\n",
" 'TTCTAGAAGCTGGTACCCAGGATTCAGATTTCCAAGGTAATACACCGTCCATCCACATCTCATCAACTTCTTCTAAAGTTAGACCTTTTGTTTCTGGAAC',\n",
" 'CTGGGGATAGAGCATTGTAATTATTGCTCTTCAACGAGGAATTCCTAGTAAGCGCAAGTCATCAGCTTGCGTTGATTACGTCTCTGCCCTTTGTACACAC',\n",
" 'TATAGTTATCATTTTCAATTCTGGTTTCAGTAGTAGAAATGAATTTTTCTAAAACATTTTGCTTGTTGTCGCTTGCAGATGGTAGCCTTAAATTTGGTAC',\n",
" 'TGCACGCGTTTCTAGTGTCGATGCAAATGGTAATGAAATCAAAATTGGTGATACCATAGTAGAGAAAGTAGGTTCACGCAGAGAAGATCAGGTCCTGTAC',\n",
" 'AAAAAGAAATTCAAAAGCCACGAAGAGAGGGCGCCGATTCGTCTCAAGATAATTCAAATGAAAACTCGATTATATCCAATATGAGTGAAGTAGAAAAATT',\n",
" 'ATAAGGTGCATACGATGAAAAAGGTGATTTGTCATTTACAAGAGGTAGGTCGAAACAGAACATGAAAGTTGGTCGGTAGGTGGCATGCAGAGGTAGTGGG',\n",
" 'ATGTGGTAAAATTGGTAGCTAATCTATAATAGTTTATAATACCTCTACCAACAGCTAAGTAATGCATTAAAATGGTTTTCATTTCTTCATGAATTAATCT',\n",
" 'CACCACAATGGCTGGCCAATATGGTGGTTTCAGAGCTTGATGTTATTGCATTCTCTTTGTTGCTAGATTCGGTACTGGATATCGCGGATGTTGAATATGA',\n",
" 'TGGGTAGGGGAATCTCGCATTTCACTGGGCCAGCATCAGTTTTGGTGGCAGGATAAATCCATAGGAATGTAGCTTGCCTCGGTAAGTATTATAGCCTGTG',\n",
" 'AGGCGAACCATTAAGCAGGGAATCAAGGACTTTAAATTTGGTAGTGTAATAGGTGATGGCGCGTATTACACTACAAATGGAGATTTCATGTATCTAAAAA',\n",
" 'GGCGGTCCCTGAACATACGGGGACTTTCTCTTCCTTACAATTTCCTCCTCAGTTTGTCCACGGTGGGTTTTAGGTTCAACATACCTTCTTTTGGTCGATA',\n",
" 'AGGGGTTAGATGTGATTTCCATTAGGAAGTTCTGGTAGGAATTTTTATGCATATCCAACATCTTCAATAAAATGCCAAACATGCTGATATCATTATTCAT',\n",
" 'TCTGCTTACCAAAAATGGCCCACTAAAAGCTCTTCATTCAAATGTCCACGTTCAATTAAGTAACAAGGACTTCTTACATATTTAAAGTTTGAGAATAGGT',\n",
" 'GGGCGAAAGACTAATCAAATGTTCACCGTTAACATCTGTCGTATCGAACAAATCGGAAAAGTCCGTGACTTTAGTCGCAGTTCTTCTACGTAACTAGAAC',\n",
" 'NGGGCCTCACTAGCTTAGAGTTCATCTCTATATAACTATTTATACAGTTTTTTTATATTAGAGTGAGGGACATATAAACAAACGCGATAACTCGATGAAC',\n",
" 'GGGTACATTAGTGAACCACTTAAATATTATTTTCGAAGAAACTTTAAACTCATTGGATTCCAACTCATATGATGTCACTCAAAACGTGCTGAAAGAATGG',\n",
" 'TATTGTGTGGAGCAAAGAAATCACCGCGTTCTAGCATGGATTCGAATAAGGCGTCCTTGTGGCGTCGCTGAACCATAGCAGGCTAGCAACGGTGCACTTG',\n",
" 'TTGAATTGGGTACTTGAATGGCACCGTCATTAGTCATGTCTAGCCTCCATGTCTTGTCGACCCATCTCCAAACCATAGTGTTAGTCTCTTCAGGTAGATG',\n",
" 'TTGATAACTCAATATTGGTATCCTTCCCTATTTTTAAATTATTATTTACTGAATAGTATCTAACTTGATTTAAAAATCTCATTTTTATTTGAGTATTCGG',\n",
" 'GGGGGCATAATATATAATACAATCATGGGAGAAATTTCCAACAAAAAAGATCTAGTCTGGTTATAGCATTATGGGTGGCTGTATAAATATAATACAATCA',\n",
" 'CTTATTAATAATAGTGTGTATGCAACACCTGCATTTTTTAATACCTTGGGTTGGTTTACGACCTTTGCCATCGAAGGTGCAAACATGGCCATAATGATAT',\n",
" 'NTGGTGATTATGACCAAAATTTACTTCCCAGTTGATGAAACGCTTGATTTGCATCATAACTTCACTTTAAATGAATTTGAAGAATTGGACTTGTCCAACC',\n",
" 'NTCAAGTTGCTTTAATAGGTGATTTATTCATCCCGGAATCTCTAAAGGATATATTCAATAGTTTCAATGAACTGGCGGCAGAGAATCGTTTACAGCAAAA',\n",
" 'GACGTAGATATGGATATTGATGATACATCTGAGAACGTTGAAGATCCTTTGCTTATCAGGATCCATCCCTCATCTTTATCAAGATCGGAAGAGCACACGT',\n",
" 'ACCGAACCCCGCAGAAGATATCACAGCATGCTTTACCAAAAACGTCTTAGAACGGTCTGACGGCACTGTACTTGCACCTATCGTAAAATATGGAGACTTT',\n",
" 'TGTTTGCAAAGTTCAATCTTAGTAGATCCAAAGGTGGACCTAATCCTTTTGAGCCCCCCCCCTGGCAGAAAAGGAAAACACAATTTCTGATAGTAGTGGT',\n",
" 'GTGGTTGGTGTGCATAGAGTTGTTTGATGATGACGACGATAAATTTGTGGAAGCTGCCGAAGTTGACGGCAAAATGTATTCGAAGGTGCTTTGGTTGTAT',\n",
" 'CGATTGCTTGCTGTACATCCTGCTGTAGTTCTTGCTGAGATTGCTCAATTACAGGTGAAGGCTCTCTACTATACCTCGTTTCCGATTCTTCTAGAAATCG',\n",
" 'NCTGCTATGCTTACTTTTCTTTCCTTTTTTACTCTCCTTCTTGCTAACTCATCCTTAACCATTTCTTTGATATTATCTGATATCGTTAAATCGGTGCTGC',\n",
" 'NGGTACCCTAACTGAAGGAAAACTTACTGTAGTACATGAAACTGTTAGGGGTAATCGTCATAATTCTCAATCTTTGTTGCTTGGATTAACTGAAGGAATA',\n",
" 'ACCACCAAATGATCTTTACCACTGACGCAAGTTTTGCAAACACCTCCAATGATAAAATCATGTATATAGACTATGCTAACCTGACAAGGCACCTTCGAGA',\n",
" 'GTCGGAAACATGATGATTGAACAGGTCTGCGATGGGCACCAAAGCTGTCTCATGGTACGCGTCAATTTCAAATCCTCTTGATGATAAAGTATATGCCACC',\n",
" 'NCACACAATAGACTCGAATGATGAACTACCTGATCACCTTCTTATTGATTCAGGAGCTTCGCAAACGCTTGTCAGATCAGCCCATTATTTACACCATGCA',\n",
" 'AAGAGATAGATAAATATAGATAGATAATGGACGTAGTTATAGAACAGAAAATCGGTAGATCGAAAACACAGGGGAAAAAGAGGGAGAAAGGAGGAAGACA',\n",
" 'CAGCTAAAAGAATATTCATTAGTTCTATCCTTTCTTTTCAATCACTAACTTGAGCATCGTCATTGTATCTTGGTTCAGCGTCGAAAATAAGCTCGTATTT',\n",
" 'AAAAATTCTCATTCTGAACAACTTTGGTTCTGGAACGGATTCAGTTGGTAAACGACGACCAATGACTTGGTATTCTTTGAAATGAGCCACTGTTAAAGAT',\n",
" 'CTTAAAATCACGTACTGTTATCTCTATATTATCTCTATTCATTAACTGAGTATTTTCTCTAGATGCCAAAGCTTTTTGTACTTGGTCATCGTCTTTTTCA',\n",
" 'AGCGCCCCAAATAATACATTCTTCGTCGGAGTTCATTACTAGCACGAGAAGCATCTTACTCATCTCTCCAAGGTCCATTTATAATACCCAACGACAGCAA',\n",
" 'AGTTTCTAGCTGATATTCGGTCCAAGTTTTACCTTGGTCTAAAGAGTAATAAAATTCGGATTGAGGATCGTCGCCTTCATCCGCATTATACGGTACAGCC',\n",
" 'TGCGGAGTAATTGAAGTAAGTCTATCAGAAGATCTGATTTTTTCATCTATTTCTGGTTCTTTATTAAAGACGTCTAAACCGAGATGGTTGATTCGTCCCG',\n",
" 'CCAGAAAAACACACATCACGTATTTTAACGAATCAGATGTCGACTGGTCTAGTGCTATTGATTATCAATGTCCTGATTGTTTAATCGGCAAAAGCACCAA',\n",
" 'ACGGTGTTCTCACAGTTATTCGCTGAGATGACGCATAGTTAGGTGATCTTCCTCTAATAATAAGAGGAGGCGTTTTCATTTCTTGCAAATACACAAACAT',\n",
" 'NAGCACAGACAATGGATGCCTCACAGTTAATTATATCACCGAAATGATAATCCTCGCCTATCATTTCGGTGATATAATTAACTGTGAGGCATCCATTGTC',\n",
" 'NGGGTTTCCACTATGCTCTGTTGTTTTGCCTATTGGCGAGGGCATTTTGTCTAAATGGCGAGACCCACTCTTCCTTACCTTTTCGCTCATTGGACACAAC',\n",
" 'GTTGGTTTTGGTTTCGGTTGTGAAAAGTTTTTTGGTATGATATTTTGCAAGTAGCATATATTTCTTGTGTGAGAAAGGTATATTTTGTATGTTTTGTATG',\n",
" 'TGAATGCTAGAACGTGGAAAATGAATTCCAGCTCCGCTTCATTGAATAAGTAAAGAAACTATAAAGGTAGTGGGATTTCACTGGCGCCGAAGCTCCCACT',\n",
" 'GGCGGAAAAAGCTTAAGAATATGTTATTTTACAAATCAGAGCACTGACACATATAGAGAGCTATATGATATGAGTGAGAGCAACTCTCCCGTATATGCTA',\n",
" 'AACCATGATGGATATATTACATTTGATGAAATGCTAACCATTGTGGCGAGTGTTTATAAAATGATGGAGTCTATGATTACACTTAATGAGGATGAGGCAA',\n",
" 'NGGTGTTTGTGGTGTGTGATTTCTTTTTTTGATTTTTTCTTTTGCAGTTGTATTCCCATACATTAAATTGTTCGTGGCACATGAAAAAAAAAAAATAAAA',\n",
" 'CATGTGTAAATCTTAAGAATTGTAGATATATTCTATTTTTTAATGAAACTTTTTCAACAAATTAGGTTTCGTGGTCTAGTCGATTATGGCATCTACTTAA',\n",
" 'AGGGAGATTCTGCAAATTTGAACAGGGTGGCTACCAATTTACTAGCAAATGCCACTCAAAAAAGTGTGAATGGATCTAATCCTAGTGTAAGAATCAGAAG',\n",
" 'TGATTTACTTGGTTATGGTAAATACATAAATATATATATAGAAACGGCAAATTACCCACATTTGCATTTGTATTAATAACACTAAAGATAATATTCATAA',\n",
" 'NGCGCTTGTCCACAATCACCATAAAACCCAAAACTGAGCTCGAGAGAATAGTTGACGAACGGAAGCTGGATATCAACATAAAATAATGAGCTTACCCGAT',\n",
" 'GCTCCAAACTGTCTCTGGATGAGGCTTTCAAGAAAATTGATGCAATCACAGTCAAAGATGTTAAGGCTTGGACCGGTAAGAGATTATGGGACCAAGATAT',\n",
" 'ATGCTTGCTAACTTATTACCGTCAATAGAATACTTGAGTCAGAGTGCTTGAAGGAGAACTTTTCTTTCTTTTTTTCCTTCTCGTTCTATGTCGAATATTT',\n",
" 'NCCACATAACCTTCCCGGATTCTCGCTTTCAGCATAGCTAGGTGCGTTGTCTCTTATTCTATTATCATTAATTTTCTTATCGGGATTTGGAACTCTGTCG',\n",
" 'AAAGGAATTAGGAATGTAGGTAGGTACACCGAAACTAACTGACACTTCTGGTTACATTCCTTACGATGTGCTAAAAACAAGCTTGTCCATGACCCAGAAG',\n",
" 'CATATGTGGCTATGGTTATGGACTGGACGGTAATATCCGTTATATTTACACTGGTTACGCCACATCATCCTATAGTGAGCATTCTCTGCTGTCTACAATC',\n",
" 'AACGCAAGAGTGAGAGTCAGATAACAATTCAAGGCAACACCAATCAAAAAAGTGGAGCCCAGGAAAGTTGTGGGAAGAATGATAACACAAAATCGAGAAG',\n",
" 'GGAGTCAGTTCGTAGTACAACCATGTTTTTTCGATGGGCTTATCCTTACCATCCACCCTCTTGACTATGGTTTTTTTCGTCTCATGTATATCTATAATAT',\n",
" 'NCTGCTACCTGCTTTCAGAATCCTAATGATTTCAAAATGGATAACTTTACCTGTCTCTCAAATTCAGGTCTATTATCTCTCCACAAGATGCAAGCATCAA',\n",
" 'TGAACAAGTAACTGAAAGAAAAGAAAACCATCGAAAATGAGATGCAACATAATAATAATATAATAGGAGCAACAACACTGTATATGATACCAATACAGCC',\n",
" 'AGTTCCTGCATTTTTAAGCAGTCACTATGTGCCTTTCATTCATTAGCAAAGGTGATGCAACAAAAGCAAGTCCCACTGGACCTTTCATATGACATAATCA',\n",
" 'NCCCACTTTCCTTTTGTCCTTATTGGAAAGTACTTCTGAAAACGCCACTGAGTTTGCCACCAGTTTCAATAATTTGATAGTAGACGACCTTGCACACGGC',\n",
" 'GGGCCCAATGTCTGGAAACATATATATACCGGCTTTACCATTGCTGTAAAGGGAATATGATGTAAGTGCAACAACAATAAACGCTACAGTTTCTGTATTT',\n",
" 'TCATTAAACGACAGACGAGGCACATCCAAAACTCTATTATTTTGTTCCACTTCACCCACTCTGAATTTTATGTCAAAGATATCTGGAAATATTTGACATA',\n",
" 'TCGCCGCTATCACCGACGCTATTCTTATTTCCACCAGACGTTTCTACTTCAAATTGAATTAAGACACTCTTGTGAAGGGATCTGATATACCATGATTGGT',\n",
" 'TGTTCACCCTTGAGAATTTACTGGATGTAGCAATATTGTGAGCTTTTGCTGCTCTTGGTTTTGAACTATTTGTTCTATGATAATTACGAGTTGTAACCTT',\n",
" 'TTGACAAAAGTCAATGGCAACACACCTTGTTTCTTCAAGTTTGTCTCATGAATTCTTGCAAAAGACTTAACTAAAAGAATCTCTCCGCCTAAAAATCTTG',\n",
" 'GGGACAGATCGAGCTAAAGAGGCAGCTAATTCAGTTGTTAGTGAGATATTCAAAAAAAATCACAAGGGACTGATGGAACTAGGAGTACTGAATAAGTCTT',\n",
" 'AGACATGTTGACGAAGCTATTAGATTGTTTCAAGCTTCCACAATGGACACAGCGTCTCTTCTGTGCAATAGGACTTAATTCTAACTTGGCTAATGATTCT',\n",
" 'TGATGTGGAGAATAAGGTGCATACGATGAAAAAGCAAAAGCAATAGTGCATTGTGATGTGGAGAATAAGGGGCATACGATGAAAAAGGTGATTTGTCATT',\n",
" 'TCTGATTCTTCTCAGGAGCCAAGGAAAGATACTGAAAATGTAAGAACAGACGAAGTAGACGAAGCGGATGAGGGCTATGTTAGATATCTGTGTGGAGCGA',\n",
" 'AGGTTCCATTCTCCATGCAGTTTGGACGCCAAGTCCTTATATTCCTTCATTTTAGCGGCTCTCGCAGAATTTAATGTATCTTTCAACGATGCGATCTGCT',\n",
" 'CCCGAGTTGTAATTTGGAGAGGGCAACTTTAGGTCCTGTAACCGGGATTGCCTTAGTAACGGCGAGTGCAGCGGCAAAAGCTCAAATTTGAAATCTAATA',\n",
" 'TCAAATCATCAAAATTCTCAAAATAATTAATGCCCAAATTTCTATATTAGGAAAGTGTTGCATTTCTATGATATCTAGCCTAAGGCGGAGCCCTTTTTTT',\n",
" 'AGCGCACATAATTACGGAACATTGCAATAGCGTTCGGAGGTAAAGTACCGGGAATGCTTTACAATGAATCAGCTATTAGCGGATATTGACCAACCAACAC',\n",
" 'TCTTTAATGAGGACAAAAACATCAATCTGATATCACTGATATTGTAAGTAGTTTGCAATTACAGTTCGAATCATCGGAAGAAGCAGATAAAGATCGGAAG',\n",
" 'GCTCATTACCCGGTTTTGAAAACCTTACAATTAATATCATATTTCACCCGAACTTTTATGAAAAGATTGTTTCTTTCTTTGATACCTATTTCAACAGTTT',\n",
" 'TGTCTCCAGAAGTTGTTAAGGCGCTTGGCGGTGCTCCAAAGCCAGATTACCCAATTGCCACTCAAGATACGTTGACAGAATATGATGCCTTTTTGTTTGG',\n",
" 'AAAAAAATATAAGAACCATCCAATCGACAGAACGTTTCAGTAGATCAAATCTAAAAAACGCTCAAAATCTCGGTAATACTGCTATTAATGACATAAATAC',\n",
" 'NCGCGCCTGTGAGAAGTTCCAAACAAGAACAGATCCATGCTAGTATTGTTTCCACATTATTAGCGCTGATGGATGGTATGGACAATAGAGGCCAAGTCAT',\n",
" 'NAGCGACGGGCGACTTGCGTTTGATGTACCGAGGTAGAATCAGGGGAAATTTTGGCTATAATGATGACGATGCCATCTGCTGAAAGATTTTCATTCAGAG',\n",
" 'NAATTTCGGAAATATTGCTACTTGCAGAATTGGAGGCCGATGTTACTGCCTTTATGGGCGAGACATATTTATCATTATCCTCTTTATGGGAGCTATTCTT',\n",
" 'GGGTGGTAAATTCCATCTAAAGCTAAATATTGGCGAGAGACCGATAGCGAACAAGTACAGTGATGGAAAGATGAAAAGAACTTTGAAAAGTGCCTTCGAA',\n",
" 'CAAGTAATGATGGTGGAAAATCCTTTTCTGAGATCAAGTCTTCTCTAGAAAGGAACGAAAATAGTCCTATCAGCATTTCTGATTGTGGCTTTGCCAAGAC',\n",
" 'ACAGAACAGAGTTTGGATGCAACTTGACACCATGAACCAGGAGCAGCACACAGATCAATAACAACCTTCGATTTTTCTAAGAAGTGGCCATACTTTTCAT',\n",
" 'TTGAAGGCTACAAAGGCTGTACCTTTAGCCAACCCCGTAGACTTATCGATAACAGGTAATGCGTATTTAACGCTGCCAAATTTACTGAAGTGCGGAGTCA',\n",
" 'ATGTCATTTTGCGTGGGGATAAATCATTTGTATACGACTTAGATGTACAAATGATTTATCCCCACGCAAAATGACATTGCAATTCACCAGCAAGCACCCA',\n",
" 'CTTGCCCTCCAATTGTTCCTTGTTAAGGTATTTACATTGTACTCATTCCAATTACAAGACCCGAATGGGCCCTGTATCGTTATTTATTGTCACTACCTCC',\n",
" 'TTCAAATCGCGGTGGGATTAATATAATGTGGCGTTCATAGTGAAATGTGGCTCCAAAGTATAAGCGTAAATGCGTTTGCTTATCGAACCGCAAGTAACTT',\n",
" 'TGGGAACGACGGTTCGTCTTTAAAAAATAATGACAGCAGTAGTACTACGGCCACTAACAGTGACAATAATGTGGCCTCAGCAAGAAGCAGCATGGCTATA',\n",
" 'TCATCAGATCTATGATCCTAGCCATTGCCATGTTCATTGTCATTTGGCCAGTCACTATGGGTATCCTTACTGGTATAGGCCATAAGGTCGGGTCCCACGA',\n",
" 'AAGGCAGTGATCCTATAACATTTTCACAACAAGCGCCAAATACGCGGTCGTAGTCATAATTTTTATATGGTAAACGATCAGATGCTAATACAGGAGCTTC',\n",
" 'AGAGATAAGTGTGATAACTGTAGTATGTTTTCGCCAAAATTTAGAAAGGATGGTTTTACAAAAATCTTCCTTTCTAAATTTTGGCGAAAACATACTACAG',\n",
" 'GCGCCTCACAATCACGTCTAACGTTGAAGGAACCGCTTACATCTAAAGGTGTTGAAGCTCCTTATAGCAGTTTGAAAAAGACATATAGTGCGGAAAACGT',\n",
" 'GTACAATGTGAGAATATGGACAAAAGGAAGGCGAGGGTGGCAAAAAGAGGAGTCAAAAATAGATAGCGTTTATTTTATTATAGCAGCTCAGAGGAACGCG',\n",
" 'ATTTCTTTTAGCCTCGCAACTTGTACTTTTCATCACTTTTCTTGTAATTTAGCAAGGGGGGTCAGTGAAATTCCAGTAATTTCGAAGCCAGTCAGCGTTC',\n",
" 'CACTTCCTTTAACAAGACCGAATGGAAGAATCACCCGTCTTTTTGCATCAAACGTCACCATTTCTCCATCTAAAACACATTCTTTAACACTATCTGTAAA',\n",
" 'GGGTCTATTTCTTTTCTGTCATAATATTTGTCAGTGTCCCAAGTTTTCATCTTCAACAGTTGATTGACTTCTTTGTGGTATGCCTCGATATATTTTTCTT',\n",
" 'NGCCATTTACTTAAAAAAAAAAAAAAAAAAAATTCCCCCACTTTTACCTTTCCATTTTTCCTTTTTCTTTCACTTTTTTTTGGTAAAAACGGTATTTGGA',\n",
" 'NTCAAACTTTACTACTGAAGGGAGGATAGGAGTAAAGTTTGAATGGGGGTAGGGTGATGTATGATATCCGTTGGGTTTGGTTTCGGTTGGGAAGAGTTTT',\n",
" 'CAGACCTTTTGATTCTTTTGGAAAGCTATTACAAGCCTATCAGTTTCTGAATACGTTTGGTTCGAAAGCTGCAAAGTTGGGTTCACTCCCTGAAGGGGGT',\n",
" 'GGAGGCTAAACATTTGAAAGAAATAGCTTTGAAGGACTATGACTACAAACATGGAAACATTTACGAACAGAAAAATATACCGAAAAAGGTATTTTATTCG',\n",
" 'AGTTTTCTTCTTTTTCTTTTTCTTGGAGGTAGATTCAGATGCAGGTGATTTATTTGCTGTAGATGCAGCCTTGGATGTCTTACTCTTTGTATTTGTCATC',\n",
" 'TATACTGTAGCATCCGTGTGCATATGCCACAGTATATACCACTCTCAAACTTACCCTACTCAGATCGGAAGAGCACACGTCTGAACTCCAGTCACTAGCT',\n",
" 'NGTATACATATTCATAGCAACAGTAATCAAGTCCACATTACCTGTACGTTCGGGGTAAAAAGGAGTCCAGGAGCCAAAGGAAAGCCAAGAGCAAGGAGAA',\n",
" 'ATAACAACAACAGGCTTTGTTGGAATTGCAAGTTTCTAAGGAAGATTTATACCAAACCTTTGCCAGAACTGTTGAATCCGTTAACGTCATCGTTTCCATC',\n",
" 'TATATACATGAGAAGAACGGCATAGTGCGTGTTTATGCTTAAATGCGTACTTATATGCGTCTATTTATGTAGGATGAAAGGTAGTCTAGTACCTTCTGTG',\n",
" 'GAGACAAGTTTATCAGGATTGGATTAGAATAGGATTAGGGTAGTGTTAGGGTAGTGTTAGGGTAGTGTGGTGTAGTGTGTGGGTGTAGGTGTGGGTGTGG',\n",
" 'GCGGTTTTTGTGTGCCTTTATAAACTGGAATCGCTTGTGCTTTGCCCATCGCAGTCAAAAGAGAACGGGTGTTGTAGTCAGTGTTCTCTGGCGGTGCGTT',\n",
" 'TGAATAGCCTATACATGCAGAGATTAAATTTGATCCAACACCAGTAAATCCTTAGTTAAGTCATCGCATTATGGTTTATCTTATTTGGTCTTCCGTACAC',\n",
" 'TGATCGTCAGATCTGCCTAGTCTCTATACAGCGTGTTTAATTGACATGGGTTGATGCGTTTTGAGAGATACAATTTGGGAAGAAATTCCCAGAGTGTGTT',\n",
" 'AATATATATATGTATATGTATATGTACATATATATGTATATACTATCTTAACAACCTTTAACCTTCCGAGCTATTGATTTTTGATCCTCACTTCAGCGGC',\n",
" 'NTTGATATGTTTGTGGTCAATGCTACTTATTAACTGAATTGCTAAATCACTGTAGCTCTTGGTTTGGAAGGAAATTAATTTTTTCAAATTAGAAGAGTCA',\n",
" 'CTGGTGTATGTTAAGTCAGATACTTACAGATTTCCTGACGTTCATGACGCTATCCAAGTACAAGTTAACCATTTATTGAATTCTCAGGAGCAACGGGTCC',\n",
" 'AGCGAGACCGTTCCTGATTTATTCATACCACCCCATCTGATGAAAAGACGTCATCAGCGATATTAGAAGATGAAACCCGAAGAAAGGCTTTGAGAAATAA',\n",
" 'GTTGGTGATAAGAAATTGAGTAAAAGAAAAGGTGATATGTCTATCTCGGATTTAAAAAGACAGGAAGTTTTGCCAGAAGCTTTGATTAACTTTTGTGCGC',\n",
" 'AGGCATTTGAATTACTATAACATGGTTTCGATAAGAAGGTATTTGCGGGTGCCGAATGAGTTGAAACCATGTTATAGTAATTCAAATGCCTATTTTTTAT',\n",
" 'GGCTGAGATAGGTACATTAAAAGTTCGTCAGAATTGTATAGTAGTTTTGAAATATTTTTCCAGTTAACTTTATCGTTTAGTTTCATTTCCAATAGTTGCC',\n",
" 'GATAAAGAAAAGGCAAGAAGATAATCTAGACATATTTCCAATTCCATATTAGAGTCCGACCACGATTGCTCAGCAGCCATTTGTGGAGGCAGTACTGTCT',\n",
" 'GTAGGTCGAAACAGAACATGAAAGTTGATCGGTAGGTAGCATGCAGAGGTAGTTTCAAGATGACAGGTTATGAAGATATGGTGCAAAAGACAAATGGATG',\n",
" 'GCGGTAATTCCAGCTCCAATAGCGTATATTAAAGTTGTTGCAGTTAAAAAGCTCGTAGTTGAACTTTGGGCCCGGTTGGCCGGTCCGATTTTTTCATGTA',\n",
" 'GAAGAAATTCAACCAAGCGCGGGTAAACGGCGGGAGTAACTATGATTCTCTTAAGGTAGCCAAATGCCTCGTCATCTAATTAGTGACGCGTATGAATGGA',\n",
" 'TCGCTACCCTCTACTGTATCGGCTAAGCTGGACATGATGTTATGTTCGTACGTATCCTTATATATGTTAATACACCGGTGCAATAACTTCTCTTAAAATC',\n",
" 'NGTGGGAATACTGCCAGCTGGGACTGAGGACTGCGACGTAAGTCAAGGATGCTGGCATAATGGTTATATACCGCCCGTCTTGAAACACGGACCAAGGAGC',\n",
" 'GTAGTAAACCTATCTCGCTACCCCAAGTCCGACATCGATATCTTCGTTTATTTAACGTATGATAAGAATCTTACAAATAATCCTCAGGACGACACTGCTA',\n",
" 'TCGTATTGGTGTCACCGCTCAAAATGGAGCAGTGAATAATAATGCAGAGTCTTTTGAAATATTCAAAATGCAATTTTTTAATGGCGTGATTGAAGATTCT',\n",
" 'GGCGATGATGGTGACAATGACAGTGAGGCAAATATGCATAAACAAAAATCTGGATAGTGGCGATGAAAAGGATGCTGACGCTTCTGTAAACAGCGGCGAT',\n",
" 'GAACAGTTCATTCGGATAATTGGTTTTTGCGGCTGTCTGATCAGGCATTGCCGCGAAGCTACCATCCGCTGGATTATGGCTGAACGCCTTTAAGTCAGAA',\n",
" 'GATTATTTTTGTTTTAAATTCCTCATCTTCCGAACTTACGCCCAACTATTATTTAATTCATTCATTCATTAAGCAATCCATACGTCCATTCATTCATTCA',\n",
" 'TATTTTAATTATTCCTGGATTTGGTATTATTTCACATGTAGTATCAACATATTCTAAAAAACCTGTATTTGGTGAAATTTCAATGGTATATGCTATGGCT',\n",
" 'ACTAACAGAGAGATTTTTGTTTAAGTCTTTCATTAAAGGGTTGAACTTGTTCGAGAGTCATATCAATGACTTCAACAATCAATTTAGATTGCAATTGCCC',\n",
" 'GAAGAATGTCAAAATAGATTACCTAATACAGGTATTGATGGCGATAATTTCCTGCCAGAATCAATGTTATGGCTGTTGATGACAGGTGGTGTGCCAACTT',\n",
" 'CCTCAAAAAGGCCAAAAAGGGTGTGACTGTAGATTGTGGGTTACTTGCTGTCAAATGACATGAAAATCTCTGCCTGCATGATCCCTGTCAAAATTCGAAA',\n",
" 'GCGCTTGGTTGAATTTCTTCACTTTGACATTCAGAGCACTGAACAGAAATCACATTGCGTCAACATCACTTTCTGACCATCGCAATGCTATGTTTTAATT',\n",
" 'TTGATGTATCTGCAGCACTTCATCCAGATCTTTTTCAATTCCTTTTCGATAGTCTTGGACCTTATTTTGGTAGCACGCGACTTCAAATCTCTTGCGAGCC',\n",
" 'AGAAGAACCAAAGGTGGAACTACTGGTTGGAATGACGGATGATTTAAATGATTCAGAGAATATAGAAGTGGAGGTTGTTGTAGAAGAAATGACAAGGGAA',\n",
" 'GCGGACTATACCATCCCACTACACTCCTATTAATAACGGTAACTATTCTATGTTTTCTTACTCCTATGTCTATTCATCTTTCATCTGACTACCTAATACT',\n",
" 'AAACACCCTGAGGCAATTGAATTCACGGGTGACTCTTTGAATGCATTGCCTATCGATCACAGACTCACTATTGCAAACGGTTTTTATACCAGTCGATCAA',\n",
" 'GGCAGAGATAAAAGGATAGATAGCAATGGACATGGCCAACCAGTTGCTAGATGAATTAGCACATGGAAATTTTTCCCACCTAACGCTAAACTTGTCCCAA',\n",
" 'TCCATTGAATGCCTTATAAAACAACTATAGATTGCATAGAAGAGTTAACTACTCAATGCTTTTTGTCAAAGCTTACTGATGATGATGTGTCTACTTTCAG',\n",
" 'GAGGTAAGGTATGTTCTGCCTTTTCCTCGTTGATATTGTTCTCGGACTTTGAGGAAGTTTCGTCAACATTATCTTTGTTAGGCACATCTATGTCGAAGGT',\n",
" 'CTGCTAGTAATACTTATGCAAGAATCTACGTCTAATGAGGTGCTCACGTTTTGCAATGATGATATAAATAGGGACAGTAATCTAATATAGACAAGTGGGC',\n",
" 'NGCGCAATTAACCAAGTCCTTTTATTTTTTTAATGGTTTATTTATGAATTGTTTATGTTTATGTTCTTTATACTCAAAATCAATAAGTGCTTATTTTAGC',\n",
" 'GACCCACCGGATATTTGTAAATTTCCGCTTCCGGAAGTGATTGCCCGGATATCAATTGGATGAATGGGTTCAAATGAACATTTATTACCCGGAAGGTTAT',\n",
" 'TCGGAGTTATTGTGGAAAAAACAACATGCTGCCACCAAGAACGGTTTTTTTGTTTACTTTGGTCCATTAATCGAAAAAGGTCACTATGCAAGTTTGGAGC',\n",
" 'TCCCCGGCCATTCGGTGCTATCCATGATCCGCTCACATATTTCTGAATATGTAGCCACATGTGGGATGATGTCCTGGGCCAAGGCGAGTTCCAAATAAAA',\n",
" 'TTGAGACTCGGAAACAGGCTCTTCCAAAGATTGTGAGTTTGTGTCCTCTTTAAAATCCTGTATGCTGTCGCCTTTTTCCGAGTCTCAACTATCTACACAA',\n",
" 'AAGTCCAAAATCTCATCACATTAACCTGAATGTTTCTCTAAAAAATTGGTTACTTGGCAGGGGACTAAGGTCAAACATCCTCTAATACCCTATATTGAAA',\n",
" 'CTTTGATGTCTGAACCTGACTCTGAAATCATTGATTTTTATCCTGAAGAATTTCCCATAGATATGAATGGTAAGAAGATGTCCTGGCAAGGCATAACGTT',\n",
" 'GGCCATTTTTGGTAAGCAGAACTGGCGATGCGGGATGAACCGAACGTAGAGTTAAGGTGCCGGAATACACGCTCATCAGTTCTGCTTACCAAAAATGGCC',\n",
" 'TGGGGCAAAATTCAAACTACCGGTTACGCAACTGCCTTGAAAATTTTGTTTGAAATCAACGACACTGATGAATTCACCAAACAACATATTGTTGGTAAGT',\n",
" 'TAGGCAAATGTCTATATGAGCATGTTTTGATAGATGTATCTTTTGCTGATTTCTTTTTGAAAAAATTATTGAATTACTCGAACGGGTTTTTATCTTCTTT',\n",
" 'AGAGCTAGATGAGCTTGCCAACTACGGGATCTTCACTCCGCAGCAAGAGCCCGACAACCAAGATTCTGTTTTCCAATGTCCGGGCGAACCAGAACTGGCG',\n",
" 'CAAGCAAAACAAAAGAACTCTCAGAAAAGGTTATAATACAGGTGCTGGTAGGAGTAAGTACGTTCCTAGGGCTTGGTATTTATCGGGATGAAGTGATCAT',\n",
" 'ACAGGTAGTCGCTAGTATAAAGCATTTACAAAGTCATGAGAATCAACAATAACATTTTCGTCCTTTATGTCTCTATGAACAATTCCTTGGTCATGTAAAT',\n",
" 'TAAGTGACGGGCGATGAGTAACGATACCCAATTTCACAAGGATTTGGGGTTGGACTTCTTGGACACTGCCGAGCTGCTTGTAGCTATTGAAGAAGAATTT',\n",
" 'TTATCCATGATAATGGACAAGTTCGAACAGCAATTCGAAGATTTGGACACCAGTGTTAACGTATATGAAGATATGGGTGTGAATTCGGATGCCATGCTGG',\n",
" 'GACTAGTGGAGGTCTGTAGTAGAAAAGTCTTTGCGGTCATGATTCTTTTTTTGTTTTTTTTTTTTACTAGAAAATGTAGGTAAAAAAAATCAGCAACCCA',\n",
" 'AAAATATCGTCAGGGCTTAACAATCTTATTGAAGCATCTATAGAACCTTGAAATGGGCCCACCCCAAATCTTTCTGTTGAAAGGACTTGGCCAAGTGAGA',\n",
" 'CTGGTAAAAGACGCAATCTATGGTCTTGATCATTAGATGTCTTTCCTGGTCTTCCAAACTTCTGTCTAGTAATATGGGCAATAAGCGGTTAAATATCATT',\n",
" 'TACATAATATATCAAATTGTGGCATGCTTAGCGCCGATCTTGTGTGCAATTGATATCTAGTTTCAACTACTCTATTTATCTTGTATCTTGCAGTATTCAA',\n",
" 'CCTTGTTGATCTACCTTTACCCAAGAAGGACGAATTACACCCGGAAGATGGACCAGTAATCTTAGATATTGTAGGTACTGATGGTAACGGACAGAATACT',\n",
" 'TTGGTGACTCTAATGCCTATACTACTATCAACAGTAAGAAAAGATCATTAGAAGATAATGAAACTGAAATTAAGGTATCACGAGACACATGGAATACTAA',\n",
" 'TGGATTCAGTACACACATGACATCCTGCGAATCTCATGTGTGTACTGAATCCATCTCCTCTGCAATTGTTTCCACGGCTACCGTTACTGTTAGCGGTGCC',\n",
" 'GTGGAGTTCGTCGTACCAAATTTCCTATGAAATGATGTTGCGTTGTATATATACCATGTCCCGGGGACAGACGCTAACAATAAAAGTATGATCGCGGAAA',\n",
" 'NTCTTCATAGATTCGAGAATGACGTCCTCTTTGTAGTGTGACGTTTCGAAGTATCTCAAGATATCTGAGTAGTGTAATGATACTATTTGATCCGTGAGTT',\n",
" 'AAGTATGGTCCAAGAATATAATCGTTGTCTTCAGAGATCGGAAGAGCACACGTCTGAACTCCAGTCACTAGCTTATCTCGTATGCCGTCTTCTGCTTGAA',\n",
" 'AAATAGAATCCAAAATGTTAAAAAGTCTTTGAAGAATAAGCCAGCCTTGTTGGTACCCTCCAGGTAAAGGTACGATAAATGTTTGGCATCTGCAGTAGAC',\n",
" 'NAGAACTGTTGAATAATCTGGTGTAGTTTGTGTGGGTCAAAGAACTGTTGGTGATTGGTACTTGACCACCTGTTACAATGATTTGTAATTGACTGCTTTC',\n",
" 'TACGGTTAATACTTTCCTCTTCGTCTTTTTCTACACCCTCGTTTAGTTGCTTCTTATTCCTTCCCGCTTTCCTGCACTAACATTTTGCTGCATTACACTA',\n",
" 'CGGCTGAGTATCGAACAGAATCCTGGTTCTCCTCGAGGCCTATATGTAGGTACGCCAAAAAGGGCTCCTTTACTTCGAAGCGCGAGGTCGTATACCTAAT',\n",
" 'GCGGCTATGGTTCTTGTTCTCTAGGGGATGCCTTTAGATGTAGTGGTTGTCCCTACTTGGGTCTTCCTGCTTTCAAGCCTGGTCAACCTATCAATTTGGA',\n",
" 'NGCTCACCTTGATCCTGTTTAATACAAGAAGAAGGTACGCATTGAGATCATTATAGTCGAATGTTAAACAATTCATGTCTCCCGGAAAATTCTCCACAGG',\n",
" 'ACCGATTGCAACACAAATAAGTGCCTTATACTTACCTGGTCCAGTAAATGCGGGGAACCTGGCCTCAATTATCACACATGGCGTATCGTCTGTGTTTGGC',\n",
" 'TAAAAGATGATTTAGAATTTGTTATTTCGGCTAGAGAATGGAGCTCGGTTGTTTCTTTTGCCAATTTTGATATATACAAAAAGCAATTTCAGAGTGTTCA',\n",
" 'NCTATTATTTCAACTCCCTACCACATGTGTTTCCATGGCGCCTATTCAATTAAAAATTGATTTATTGAGCGGGCAGTTTTATTTTAGGAATCCTACTCCA',\n",
" 'AATGCAGTTACATATTTGAAGGAATCGGATATTGAATGGTCTAACGCTAGGACATATCAATGTCCTGACTGTCTAATCGGCAAAAGCACGAAACATAGAC',\n",
" 'GTCGCACATGAATAGACTACAAAAACAAAGATGCAAGTCGTCCCAATTCAACATGAGGTCTTCTGGAGTTCTAGCCAGAGGCTCTACGGCAGTGGTCCTA',\n",
" 'TGCGAAATCACTTTTCAGTGCGCGCAATAGCGAATGGATAACAACAGATGACAATAAGACAACAACTAAGGAGAAATTTATCAAAGAAAACCATTGAATA',\n",
" 'TACCTTTATAGTTTCTTTACAATGTCAAACTAGAGTCAAGCTCAACAGGGTCTTCTTTCCCCGCTGATTCTGCCAAGCCCGTTCCCTTGGCTGTGGTTTC',\n",
" 'NGGGTCAATCATAGCATCACGAAATGAGCTCTCGTATCTCGTTTTAACCAACGGAATATAACTAGGAACCTGATCAAACAAGTTTGCTTCATCTTTTCTC',\n",
" 'TTTTAGAGGAGTTACCAATTCATTTAAGACCATGCCTTTTTCAGCATGATAATTACAAGAGAACGCCCTTGCATTATTCTTGCCAGTATGGCTTATCTGA',\n",
" 'GCGCCAAAACTCCCATATCAAGGGGTGAGTATACCTTTCTGAAACCTTGGTGGGATGAAATCAGCGCCGGTGCCAAGAATGCCGTGGCTAAGCTATTAGA',\n",
" 'GGCTTTTAACGAATATTTTGTGTAACTGCAAGAACTACTAGGGTTTGATGTACCTTGCTCATTAAACCCTAGTAGTTCTGGCTTTTAACGAATATTTTGT',\n",
" 'ATAGCATTACATTTAGAATCTGAATTATTCGACAAGTCAAAGGGATTGATTTGGAAGTCTTTTTCCAATGAAGTTGAAGCCATTTTTTCGGAAAGGCTAT',\n",
" 'TGTGGGAATTAAAATGCGAGCGGACATCATCTTGGTTAATGGTTGATGCCTGGGAATCTTTACAATCAAGTTATACAAGGACAGCAAAAGTCTTGGACCA',\n",
" 'TGTTGTGATTTGTCATTGAATGTGATGAAAAGCTCCTCCAGTCGCCTCGACTTGGCTTGACTTGTCTTGGCTTTTTTGGTTTATTCTTTCTGTCCTGAGA',\n",
" 'GGCATCCGTTAGGTAAAATATAAAGAAAGTGCGCCAGATTTTGGTGGAGGAAAAAAGAGAGAGGAAAAGGAGTGAGAGAAAGTAATGACGAAAAGCAAAA',\n",
" 'TCGGCAGCATCGTATCTTGATACAGTTCCAGATGAGCATCATGATTTCAGAAAACCCACCGCCAAGGTTGTAACGACGCAACTGACTATTGCTACTTCAC',\n",
" 'NATCACGCGGCACTAAAGTTGTTTGATTGTAATAGTAATACTGCTATTGAGGTTTTCTTCTTCAGGGCTGCTCACAACGGGATATATTTGAATTGACAGG',\n",
" 'NCGGCAACGAAACAAGAAATGTGTCAGTTCCATACTGATGAATACATTGATTTTTTATCGAGGGTTACTCCAGATAATTTAGAAATGTTTAAAAGAGAAA',\n",
" 'TTTGAATTCTTTGAAATAGATTGCTATTAGCTAGTAATCCACCAAATCCTTCGCTGCTCACCAATAGAATCGCAAGATGCCCACGATGAGACTGTTCAGG',\n",
" 'ATGATGATGACGATGATGACGACGATGATGACGACGACGACGACGACGATGAGGACGATGATGATGATGACGACGATGATGATGACGATGATGATGATGA',\n",
" 'GTATTTGCATTTGTTGGACATGTACTGAATACAGACGACACACCGGTAATTGAAAAAGAACTGGATTGACCTGATCCTGCACTAGTATACAATACAATTG',\n",
" 'AGGAGAACTCTTGATGAAAAATTGAGATCCATTGATTGGAGGAACCGTCTTCAATCAATGGATCTCAATTTTTCATCAAGAGTTCTCCTTCGATAAATTC',\n",
" 'CAGTCATCATCATTCTCTTCTGGTTCTTCCTCATTATCCGCTTCAATGTGCATACCGGGTAATGGGTTGCCGATCTTCTTGTAATCAGTCTTAGACTACT',\n",
" 'GAGGCATTCAGTCCTGTCACGTAAAACATTTCTGTCACGCTACCACCATATTCTGTAATTTTTTTTTGAATCGCCAAGTCAGTACGCTCTAAAGGATTTG',\n",
" 'AAAAAAAAAGAGAGCTATGTAGGTTGATTGTGTTGTTCTATGTAGTGCCCTTTATTTTTCTTTGGATTTAAATTTACAGACACATTATATCTTGAGGTTT',\n",
" 'TAATCCCCAAAAGAAAAAAAAAAATGTGACATTTCATAATGCATGTTTCGAGTGTGTTTTCTATTTACTGCGGTAAGATGAATAAAAGTTAGGGAATGTT',\n",
" 'TGATTTAGCTTTTGCTGTCTTTCGCTTAGTTCACCTCTACCGCAGTAGTCTACTCTGAAGTTTGCCATTATAGAATCTACCACGATAAGGCGATAATCTC',\n",
" 'TTTATATTCTGCTTATCACGTTTGCATGGTTTTTGATTTATTTCTTAGGTGTTTCTTGATGAAAGCAATATCCACTTCTAAACCTAAAAAAAACATAAAC',\n",
" 'CTCGTAAAGTAACAAAATTGATCCATTTTAAATTAACAAGAATGTTACCGCTTTAAAACTAAACTGTAAACAGTATCGAATGACATTTACGGTAACGGGC',\n",
" 'GATCCCTTAAACAGTGCACTACAGGAAAATTCAGATGGTGTAAAAAACTCATATAGAGTGAATATTGATCTCGGACCTGCCAAAGTCGTTTCTAGAAAGC',\n",
" 'ACCGTCTTAAACAAGAACGAAAAGAAAGCCAGAGAATTGATTGGCAAATTGGGTTTGAAGCAAATCCCAGGTATCATCAGAGTCACTTTCAGGAAGAAGG',\n",
" 'CGTCGTCAGATGTTGTAATCGACACACAAGGATCATTGTTTTCGAAACATCCGTTCTCAACCAGGTCTAGTATTATCATATTCATGGTTCTCTCCACCAC',\n",
" 'ATAGAATAGTTACCGTTATTGGTAGGAGTGTGGTGGGGTGGTATAGTCCGCATTGGGATGTTACTTTCCTGTTATGGCATGGATTTCCCTTTAGGGTCTC',\n",
" 'NACTTTACTGTCAAGTATGTCTATGGTGACAAAATCGGAAGAGCACACGTCTGAACTCCAGTCACTAGCTTATCTCGTATGCCGTCTTCTGCTTGACAAA',\n",
" 'NCGAATGTAAATTTTTATGCTACACACGCCAGATAGACCTCTCATAATTAATTGACATGCGACCTTGTTATTGATATGAATGCCATTAAGATCGGAAGAG',\n",
" 'NGCCAGGTCGTACTGATAACTGCAGCAGGTCTCCAGGGTGAACAGCCTCTAGTTGATAGAATAATGTAGATAAGGGAAGTCGGCAAAATAGATCTGTAAC',\n",
" 'GTGCGCCTGGTGAAGGTGTGCATTTCAGGCAAGAGAGTAATTCTCATATATAAAATCATGCGAAAATACAATAAAAGACGTTAACTTGATGGCATGTAAG',\n",
" 'TGTAGATCCAGAGACGTATAGGATTAAATCTATTGTGAAAAAACTCAAAGTTCAGACTCCCTAGTGAATCAGCATACGTGAAATATAATAAAAATATTAC',\n",
" 'GTATGAAAAACTCATGAATCGAAAGAAAAGAGGAATTGTGGTTATGACTTTGGGTTCGAGAGGGGTGCTTTTCTGTTCGCACGAAAGCCCTGAAGTACAA',\n",
" 'ACAGGTGAAAAAGCAAAAGCAATAGTGCATTGTGATGTGGAGAATAAGGTGTTATGGGTGGAGGACAATTGAAAAAACTCAAAGATTGAGAAGAAAGAAG',\n",
" 'TTTTACTATGCCTGCCACCATCCATTTGTCTTTTGCACCATATCTTCCCCTTATGATATGTTCCACCTTTGTTCTTCCGGTTTCTACACTCTTTATCTCT',\n",
" 'GTCTCAATACTGCCGCCGACATTCTGTCCCACATACTAAATCTCTTCCCGTCATTAATAGAAGTAAAAAATCTTCTTGGAATGACGATAGTTCTTCTATA',\n",
" 'NCGGAGACATCAGCGTGGTGCAAATACCACCCGAACAACTAGTAATAGTAGTTTCCATAGTTAGCAACTCGGTTTTAGTAGAGGCGACATCTTCTTCATT',\n",
" 'ATCGCGATTCATCGCCTGGTAGTGCTGGAGGAACTGCGCAGGTAAGAAGAGCCTGTCCTGATACAATGCTACGCCAGCCATTTCACATAGCAAACGGCCC',\n",
" 'CCGCCCCCTAGAAAAAAAAGAAACGGACGGGCCTGGGCCCGCACAGCCTCGAGCAGGGTCACTTCGCGCCATATCGGCGGCTATTTCAAAAAAAGAAGTT',\n",
" 'GAACAGTGCAACAGTGGTAATATGGAGTTACCCACTTATGATATGGCCACAATGGAAGGCAAAGGCAACCAGGTTCCTCTAAGTATGAACAGCGACTTTT',\n",
" 'TAGTCTTCGAGTTTGTCCATTTTTTTGGAGAAGTATTCGTATAACTGGGACATTGATAATCGGGATGATGTCCTTTGAAGGTATTGTTTCCCAATCTTAT',\n",
" 'TAGCTGTACCCACGGCTATGCCCGGTTGCATGGTTTTCTTGACCATGTCATCGTTGGTGACATCTGCCAGTGCCTCCCACAAACATTTTTCTGCCAACGA',\n",
" 'AAGAAGAAGAAGAAGAACTAGAAGAACCAGTACTGCCTCTTCTAACGCTTCGGGGTCTTCTTCCAAGTCTAATTCCGGCTCTTCTGGTTCTTCTAGTTCT',\n",
" 'AGCAATTCTGATCGTGCTTCTCCGGCCTCGAACAATAACACAACAAAGGAATCCGCATCTGTTGTGTTATTGTTCGAGGCCGGAGAAGCACGATCAGAAT',\n",
" 'TGTTTTAATGCTTACTATGACCAGTGCTTTGATTGGCTCGTCTTGTTGATTAACATTTGCTACTGCAATCGGAATGCCAGTTTCTACTACACATTCCATT',\n",
" 'NTTTCCGGTAATAAAAGTTCGGGTAAGATTTCTTTTCCAAACGAGCTTACGTGTCGCATCGACAAATATGGCGAGTGCTCTTATATAAGTAGGCAACATC',\n",
" 'NTGACACAGGATGTACTACTACTGCTCATGGTTCACACCAGCATAAGAGGGCCGTTGCAGTTACATACGTTTACGAAACAGTCACTGTCGATAAAAATGG',\n",
" 'GAGGTTGAGCCTGGATTCCACTGCTGGAGAATGTCCAAGAAGCAAGCAGATCACAGAAAATTGTCACTGAGAGGTTGAGCCTGGATTCCACTGCTGGAGA',\n",
" 'TTGCTGAAAACCTGTCTCGCAGTGGGAGATTTCAAGTGGTCGTCCTAAATACCAGAGGTTGTGCACGTTCCAAAATTACCACCAGAAATTTATTTACAGC',\n",
" 'GATTCCTTCCGGCCAAAACTACACTCAACAACAATTACAATATCAATTACACCAGCAACTGCAATTGCAACAGCATCAGCAAGTTCAGCTGCAGCAGTAT',\n",
" 'GGGTGGTGTCAGCCATGACGTATCAGTATTGCTTTGCTGACGATCCAAGATATAATAGTATCGTTCCATGACAGACGGGTCAGTAAACACGGCGGGAATG',\n",
" 'AGCTGGAACCACAACTGAAATGCAAAGATGCTGCCTCGTCCGTCTTTGAAGTTATATACCTGGAAACGACAACGGTGGATCCGTCAGTTACAGCAAAATT',\n",
" 'TTGAAATGACTGATTTTACAAACAACAAACACTGAAAATTCTGAAATTAATGAGATATTTACACATTAAACATCAAAAGTTTTCTCAAGGAACATGTATT',\n",
" 'CGGAGACTTTGTATCTGTCCATTATGTTAATGGCAAGATACAAAGTCTCCGGTAATAAGCCGAATTTATTATGGATTTTAACCAACCAATTAACTAGGAT',\n",
" 'NGGTAAGGACAAACACAAAGATTTAACCAAGTCAGAAGTTTGGTTGTCAACGTTCAAAACACCGTTAGAACGAGACAAATCCAAAGCAGAAACTTCTGAA',\n",
" 'CTATTGGATAACCGTATCGAAGATAATTATAGGGTTTGTGTTATCCTAGTCAGTTCTCCAGGCTCCAGTAAGTCTACTATTACGGAAAAACTTTGTCAAA',\n",
" 'CTGCTGCGGTTATCAGTACGACCTGGCATGAAAACTATTCCTTCCTGTGGATTTTCACGGGCCATCACAAACGCACCGGAGCCAGCAAAGGTGCAGGCCT',\n",
" 'AACGATGTAGTTATTATGACCTCATAATATGAGAACTTTTTCCTCAAGTATTTTTAAGTTATTCTGTGTGTCATGACTCTCACTTCGTCATATTTTATGT',\n",
" 'TCGGCACCTTACGAGAAATCAAAGTCTTTGGGTTCTGGGGGGCATGGTCGCAAGGCTGAAACTTAAAGGAATTGACGAAAGAGCACCACCAAGAGTAGAA',\n",
" 'TGGGCAGGCAGGCAGCTAAGCTATTAACGAGAACCTCGAGTCGTTTGGCCTGGCAAAGTATTGGGACCTCAAGGAATATTTCTACCATCAGACAACAAAT',\n",
" 'CTGAAGCTGAGAAGAGCAAGGTCACCGCAGTGAGATGTAAGAAGTGCAGAACCAAATTGGCGTTATCTACATCTTTCATCGCGCATGACCCACCAAGTAA',\n",
" 'GAAGATCCCTCTATTGATTGCCTACTGTTGACCACCAAGGCAATCAATAGAGGGATCTTCGTTAAATTTCCGAACAACTTTTTGTCTGTCTCTTGGGTCA',\n",
" 'NGCCCAATTGATAATTTATACTATGGTCTAGTCACAAAGTTCTCTGTCCCTATTAGTATAAAAACAAAACATGCTTGTGATTGATTTTGTCCCTCCGCCA',\n",
" 'TTATGGTTTTTAGAGTCTATAGAAACCATAATGTTATCCTGCCACACTTCGACCCACTTACCAGTGCTGAATCGAATAACGGTGACATCTCTACCAATGA',\n",
" 'GGCGGTAAAAATACGATTTACGCTCAACCCGGTGATCGATTCATCATTAAAACCCCTGGTGGTGGGGGATTTGGACAATACAAGGATTAAAGCATTTCTT',\n",
" 'TTGCTAGAGTTATTCAGATGAATAATAGTTTACAAAACAATCTACAGAACAATATGAATAATAGCAATAACAATAACATCATCAGGATACAGCAACTTAT',\n",
" 'NATTTAATGTTGCTGGGTTTCATTTCGTTTTATTATCTTAATTTTCCAGGACCCTTCGCTGTTTCAGGCCGATCGGAATTAAACAGCTAAGGGTCCTGGA',\n",
" 'NGCGCCAGTGAAATACCACTACCTTTATAGTTTCTTTACTTATTCAATGAAGCGGAGCTGGAATTCATTTTCCACGTTCTAGCATTCAAGGTCCCATTCG',\n",
" 'AAGAAAAGGATTGAATATGGGAGCTCATATGTTGGCCAAAGAGAATGGCAAGGTGTCAGAAAAAGATAGCTCTAAAACCGTCAAGGATGAAGCACCAATC',\n",
" 'CTACGGAATTGCTTCATGATGAATATATCACGGAGATAGCTGAAGCCAATTCCTCATTAGCCCCGCTAGTCAAGTTAGCAAGATTGAAGAAAGTAACTGA',\n",
" 'AAAGGTTCAAGTGCACCCTCGAGAACCCTGGATCCAAAAAGTTATAACATAGTTGCTTCAGAAACTACTACTCCGGTGACAAACAGGGTTATTCCGAGAT',\n",
" 'CACCTCTGACGACGTACTTAGCCTTCAAGACATTTTCATTTACATCTTAAACTACTATAAAACAACCTTTAGACTTACGTTTGCTACTCTCATGGTCTCA',\n",
" 'GGGCAGAAATCACATTGCGTCAACATCACTTTCTGACCATCGCAATGCTATGTTTTAATTAGACAGTCAGATTCCCCTTGTCCGTACCAGTTCTAAGTTG',\n",
" 'AACATAAAAAATGTAGAGGTCGAGTTTAGATGCAAGTTCAAGGAGCGAAAGGTGGATGGGTAGGTTATATAGGGATATAGCACAGAGATATATAGCAAAG',\n",
" 'CAGGTGAATTGGAAAATGCTGAGAGGGTAAACGACTTAAAAAGGGCGCATGATGAAGTTGGAGAAGAGAGCAATAAGTCCAGTGTAATAGAAACCAACAA',\n",
" 'GTGAAGAATCCAAGAAACTTTACTGTGTTTACGTTGCCGTTGGACAAAAAAGATCTACCGTTGATCAATTGGTCCAAACTTTGNAANAACATGACGCCAT',\n",
" 'TTTATGTTTACGTTTACTCCATTTATTATATTGCTGTTAATGGTGTCGCATCCGATACAATGATTATGTTCAATAAAGCGGACNGGNCGTTGTTCATCGG',\n",
" 'GTGGGAACCGCTTTAGGGCCCTCAGTGATGGTGTGTTTATGCTTAAATGCGTACTTATATGCGTCTAAGTATTACGTGATTTTCTGCCCCTTACCCTTGT',\n",
" 'ACCAGGAATATCATATTCAGTTCCAACAAGGCTTATGACCTTGACGGAACTGAATATGATATTCCTGGTTTGATAATGAAATGGAAATCAGACGGTAAAC',\n",
" 'CAGGGATGACTCTGTGACACCACATTAGATATCCACCACCACCTTTCATGGTCATCAGAGGATGTAGCTTACCCCTTATACTTTGGTACGGCCTACATCT',\n",
" 'TCTGTCTTGAAGCTGATTGGAAAGAATTTTAGTCAGCGCTTTCACACCTTCTTGCATCATAACGTTTATTGGTATAGGTCCATCCTCTGAAAGTACCTCC',\n",
" 'ACTACAGACCCGCCTGAAAGTAGACACATCATCATCAGTAAGCTTTGACAAAAAGCATTGAGTAACTAACTCTTCTATGCAATCTATAGCTGTTTTATAA',\n",
" 'GTGTCTTTTGTTTGTTTCTTGTAACAAATCATAGCGAGCAGTTTGAAAATTATTACAAAACCAAAATACGTCTCTAGTAGTGCTACCATAGAATTTATTG',\n",
" 'AAACGTTGTTGCTGGTTCTGACTTGAGAAGAACCTCCATCATTGGTACCATCGGTCCAAAGACCAACAACCCAGAAACGTTGGTTGCTTTGAGAAAGGCT',\n",
" 'TGGGGATGTTATTCTTTTCAAATTCGAAACAAACAAGTTTTACGGACAACTTCCCAAAAGCGATGCACTGCAATTGAAGTTTAGCAGATTTTCATTGGAT',\n",
" 'GGGGGCATCAGTATTCAATTGTCAAAGGTGAAATTCTTGGATTTATTGAAGACTAACTACTGCGAAAGCATTTGCCAAGGACGTTTTCATTAATCAAGAA',\n",
" 'GTCGCATCCCCGGTTCATTTTCTGCGTTTCCATCTTGCACTTCAATAGCATATCTTTGTTAACGAAGCATCTGTGCTTCATTTTGTAGAACAAAAATGCA',\n",
" 'GCCGCATGGGATAATGTGTACTAATAACATAAATACTAGTCAATAGATGATATTACGATTTCACACCAACAATGGTGACTAGCACTCACCTTTGTTGGAG',\n",
" 'CCAGATTACTTTCAAGTAGAGAGGTTAAAGAAAGACGAAATGCTTGAGACAACCATAAGCTGGCAAGAGCTGGACGGTTTTGGGGAGCTCAGCACTCACG',\n",
" 'GACGTTAACCATGACGATATCGTCAATTTCTGGGTATTTGTTTTCATAAAATCTGCAATGAGAAGTGGACATTATTTGGTGTATTATAGAAGGTGCGTGA',\n",
" 'TTGGCTTTTGGTAGAGGCTCGCCACCATTAGCTTTCACTGCGTCACTCAATATTAATTTACGGGCTTTCAAAACCTTGGTGAAGTATTTCGTTTCAGGCC',\n",
" 'CAGATAGATCCCAGTAAAGGCCTCGCAAAGTGGTATATATACCATACCTACCTTCCCAGAGTAGATAAATACAAACGGCAAACGCACTGAAAAAAAGCAA',\n",
" 'TAGAGAAATTAGAACAGCGTATCCAAACTTGATTTCAGTTCCACTTCACCGGTTTTCAATTCCTTTTCGAATTCTTGTTTCTTTTCGTCGACTTTCTCCA',\n",
" 'CTGGCGGGGGTAATGCATGGCGTTTAGTTTTGGGGTTTGACCTTACTTTTTTGAAGAAGACTTTACTCAAGAGTGTAAGCTCCCTTGGAGGAGGACATAT',\n",
" 'ACACAAGAAATATATGCTACTTGCAAAAAGGCAGAAAAAGGGAAACTGAAGGGAGGATAGTAGTAAAGTTTGAATGGTGGTAGTGTAATGTATGATATCC',\n",
" 'TCCAAAAATAAAGCAACTACTTTTTCACACACCACATGCATCACTGTATAAATGGAACTTCAAGAAGGACGAATGGAATAAAATCGGAAGAGCACACGTC',\n",
" 'AGTCACTTCCTGGTGCTACTTCCATGGTTTCATATTCCGGATTTTTGAAGTAGTGACCAAAATTGTACAAATTTCTAATAGTTAAAACACTTGATATTAA',\n",
" 'ATCTTTCTTGATTTTGTGGGTGGTGGTGCATGGCCGTTCTTAGTTGGTGGAGTGATTTGTCTGCTTAATTGCTTCGTATCTTTTTTTCGACTCAGATTGC',\n",
" 'GTCGGCTACTGAACTGGTTATAGAATATACTGATTCGAAAGCAATTAGTTTAGGAACGGATTTGGGGTATGACTGGAGCAGTTGTTCCAATTCGTTCCTA',\n",
" 'GGCGGAATCTTGAGCATTACTTCTAGAATTCTCATTGTGGATCTCTTATCCGACATTGTTCACCCAAATAGGGTTACGGGTATGCTGGTATTGAATGCAG',\n",
" 'CTGGGGTGATTGCTCGATTTCGTAACGAAAGTTTTGTTTATAAAAACCGCGAAAACCTTCTGTAACAGATAGATTTTTACAGCGCTGATATACAATGACA',\n",
" 'TTACCAGAAACGATTTACAGTTTTGATCCATGCATTGCACTACATTTTGCCGAACTTGTCGTGGATTTCAGAAGTTGTAATTATTATATGGACATAATGG',\n",
" 'ACTATGGGAATGCCTGTATTACCAGTACACCACTTTTCAAATGCTACAGGGTTATTCTCCCATTTTATATCTAAAGTGTCCAATCGATAAGGCATTCCCA',\n",
" 'AAGTAGCTGTAGAACATGCCTTAAGGAAGAAAAGAATGATAATGGCATCCCCTTCCCCTGCCCTAGAAAGTGGCCGGTATTTCTGTTCTTCAGTAAGGCA',\n",
" 'CAACCCTCGCTACTTATCAGGTAAGCCCAGCCAACCATTTTGTTCCTCACTTTGGTGGCAACATTGGAGCCAACAACAACAATCCAACCCTCGCTACTTA',\n",
" 'AAAAATAGGATTGAAATGGATGATTCTTGTCCACCTTATGAATTAGATTCCGAAATTGAGACTTGTTATCCAGGAAAAGGTCATCAATTTCGGAATCTAA',\n",
" 'TTTCAATACACAAATAGGTTTGCTTATGGTGGTATTTCTTGAACAAGTAGTTTTTCGTCCTGTGGCAATAGTAATTCAGCTGGATTCAAAAGCCTTGATG',\n",
" 'GAAGTACTATATCCGAAACTAAAGGCTACTGATGAAGATAATAAGAAACAAAAAAAGAAGAAGGCAACAAATACTAGTGAAACGCCACAAAACTCTCTAC',\n",
" 'GCAGATAGCTCGTCTGAGAAAGGAAGTAAATCCAATAACTCCATTTGGGATAGTGTTTCTTGCCATTGTTTATTGAAATATAGCTTCCTGATAGAGGAGA',\n",
" 'GGTGAGTTGTTACACACTCCTTAGCAGATTCCGACTTCCATAGCCACCATCCGACTGTCTAGATGAACTAACACCTTTTGTGGTGTCTGATGAGCGTGTA',\n",
" 'CTCGGAAAAACTGAAAGGCACTCTTCGGAAAAACCTCTTTTATGGAGAGTGTTCTGGGGCAGAAACCAAAACGGCGGAACGCGTCCGGAAAAACATACAT',\n",
" 'TCTGGATATCTGAAGGCTGACCATAAATACATCTATAAAGCCATCTTTTTTCAATCGCAGTGGCTCTTTCAGGTTCCAAAATTATAGTATAGTCATGTTG',\n",
" 'ATTTCAAGGCATTCCCCCAAGTTTGAATTCTTTGAAATAGATTGCTATTAGCTAGTAATCTATTTCAAAGAATTCAAACTTGGGGGAATGCCTTGTTGAA',\n",
" 'TAGCGTAGTTGGTTGACTCTAACACGTTTATAATTGAATGCGATAACCTTAAAAAGTTTCCTACTATGGCATTGGAGAATTGGATTCTCAGATTCTCAAA',\n",
" 'TTCGAATAGGGGACAATCTCTAATTTCATCACGCACTAATTCGTATACGTCATCTCTATCCAAGCCATACTTGAATAACATGAGAAGGATAAAACGATCT',\n",
" 'CGGCACATAATTCATCTATTTATGCAATTCCTACAATAAATGTTGATATCTTCATGGAAATTTCTTAAGCACAAACTTGTATTTAATATCCTACATAAAG',\n",
" 'GTTGTATTGAAACGGTTTTAATACAACACACTGTGGAGATTAGATCGGAAGAGCACACGTCTGAACTCCAGTCACTAGCTTATCTCGTATGCCGTCTTCT',\n",
" 'AGTGGAGCGTTAACATCTTTCATTTGCCTAACAGTTTCAATTAGTGCTACAGGTTCCTTGGATTCCCTATCTCTTAAAACCACCACACCCTTGATCTAAG',\n",
" 'AAGATAACTTTGCCAAATGTACACTGCTGTTAGTACACAACTAATGAGTATCCATGTATGCAAAAAATAGTCGAGTTCCGAAGACAAAGACGACAAAAGA',\n",
" 'TGTCGATGATTGTTAGATTTTATTACAATTGGAAAAAGACTGAAAGAGGCCTTACCGTGAGAGGGAAATTGAGTAAGTTATCAAAGAATAAAAGAAAAAA',\n",
" 'GGCAGATCCAAAGCGCAAGTGATGGAATGTGATCATTAAAGGCTATAACAGACTTGTATCGATGAGTTGTGTGTATGCGTTTGGGTCTAATGGGCAAAGA',\n",
" 'TAGCATACTCAGGATAACATATATTAATGACGACTCGTTTGCTCCAACTCACTCGTCCTCATTACAGATTATTATCCCTACCTCTCCAGAAACCCTTCAA',\n",
" 'GGCGGAGATAATAGCCGACAGGATAATTGGAAATAGCCAAAGGATGGCGAACCTCAAAATTCGTCGTACAAAGTTCAAAAGTGTCTTGTATCATATACTA',\n",
" 'CTCGAAGAATTAGGTGCTTCACCTAATTCTTCGAGCAAGTACTCTCTAGATCGGAAGAGCACACGTCTGAACTCCAGTCACTAGCTTATCTCGTATGCCG',\n",
" 'TTCAGGCAAAAAATACTTGGCTGCCAAGGCAAACTTGTTCTTTTCACCCAGCGGACTTGCTGAAGCCAATTTTGCAGTCTCTTCATTTAATATCTTAGCG',\n",
" 'TAAGTTATGAGAAGCTGTCATCGATGTTAGAGGAAGCTGAAACGCAAGGATTGATAATGTAATAGGATCAATGAATATAAACATATAAAACGGAATGAGG',\n",
" 'GCCCCAATCCAATAGTCACGAAAGGAGTTTTACTCTCATCGTACAATTCCCATATCAATTCATCTGTTCCAACTTGCCACCTCAATCTTTTCTGTATTAC',\n",
" 'CACCTTCTGTATAAAAAAAGAAATTATCATAGAAGAGAATGATGTTTACATCTCTCCGTTGAAATTGAAGATAAGTTAGTAAAAAGATCATATAGATGAT',\n",
" 'ATTACGAACTAGAAACCAGTGGAAATAACAATAACGCTAATCAAGACACCACAACAGTTCCCGATCATCTACCAAATCCAGTTGGTCAGCAAGACTCTTT',\n",
" 'CAAGTTCAAATGTGGGTCTATCGAGCATGTTTATCCAATAAAAGATGCTGGAAATGCGCTCTGTATGAATGCATTAATTATGTTGTACCGAAAAAGAAAG',\n",
" 'AAATAATCCGGTCGAAAGAGATATTAATTCGATATATTATTTATTTAAATTAAATATAATTAAAAGATCGGAAGAGCACACGTCTGAACTCCAGTCACTA',\n",
" 'GGGCGGTACTTACGGTGATATCCAATTCTTTAACACTATTTACAAACTTTTTGCATATATCAGTCTTATCTGGGTAAAATTTCATAAACATTTTTTCTAC',\n",
" 'TTGGAGGATAAGTATAGTGCTACGAAGATTATTTCCGAATCGCAAAACAACGACAAGACTTTTGCCAAAGAAGTATTGTCCAAGATTTTGGGTGAAAATG',\n",
" 'ACACTAGATTTTGCACTAGAGTAGGACGTCTTTTTAGAATAGACATCGAACGGAAATGCATCCTCATCGCTAGCGCCCGAATTGGAATCACTATCGCTAG',\n",
" 'ACCTCTTCTACTACCTCTTCTACTACCTCCTCTACTACCTCCTCTACTACCTCTATCTTTTCTGTTACGTCTAGCTCCTCATCCATTACATTGTCCTCAT',\n",
" 'CGCATCAACTTTGTTTTCTTTTGCGTCTCCATTTTGCTTTTCAGCCTCTTCATCTTCATCATCACCTTCCGTACGTAAAACATCATAAACAGACTTCTGG',\n",
" 'TGTTGGTTATCCCCGATTATACTACCCTTCCTTGATAATGTTGACGAGTCGATACTAATACTTCGTTCAGGAGAATATGATCTTGTGGAGAATGAATCAG',\n",
" 'TTTTACGAGGCAGGTGGAAATTTCATTGATGCCGCAAACAACTGCCAAAACGAGCAATCAGAAGAATGGATTGGTGAATGGATACAGTCCAGAAGGTTAC',\n",
" 'TTTACATTTAAAGGGACGGTTGAAAGTGGACAGAGGAAAAGGTGCGGAAATGGCTGATTTTGATTGTTTATGTTTTGTGTGATGATTTTACATTTTTGCA',\n",
" 'CCTCTTTAAGATTGATTGATCTTTCTGGATGTGAAAATATTACAGATAAAACTATAGAAAGAATAGTCAATTTAGCCCCTAAATTACGTAATGTTTTTCT',\n",
" 'CCTTATTCAATCTTTGCTATAAAAAATGGCCCAAAATCTCACATTGGAAGACATTTGATGACCTCATTTCTTTCAATGAAGAGCCTAACGGAGTTGACTA',\n",
" 'AGGGGGACGAGAAATATATGAATCTTGGAACAGTTTTTGGGATTCATTGTTATCAAATGCCAAAAACTGTTCCAAGATTCATATATTTCTCGTCCCCCTC',\n",
" 'TAAAACCCATACGCGTAATGAAAGTGAACGTAGGTTGGAGCCTCGCAAGAGGTGCACAATCGACCGATCCTGATGTCTTCGGATGGATTTTACACCCAAA',\n",
" 'GAGTGGATGGTTCTTGCCAATGAATATTTATCTTCATTGTACATGGTAATACAAATGGCAATTTGACATTCTCTGTTCATCTCTACGAATCTCAAAGTGT',\n",
" 'ACTTTAACCTGACCTTAATTATCGATTCTAATACTATCTGAGTTTAAAGAACTTGCGGGGAAGAAATACGGAAAACATAGAAAGGCGATGGCAGATGAAG',\n",
" 'GTGGTACTGCTGCTATAGGCTGGTCAAGTCTGAAGCTCTATGCCAGTTACAAAAGATGTCAGGAACTTGAAAAGATCAATGAATTTATTGAACAAAGTTG',\n",
" 'TACCCAAGTCAAGCCTACTTTAAGTTTCAAGCAGGATTACGAAGACTTCGAACCTGAAGAAGGCGAAGAAGAAGAAGAGGAAGACGATCAAGGCAAGTGA',\n",
" 'TCGACAAGTTTAGTAAGAAATTGACGCCTTTTAATATACAAGTAAGGGAGTTAACAGGCGATATGCAATTGACAAAAGCGGAAATTTTAGCAATTCAAGT',\n",
" 'GACAAACTGAATTTTAGGCTCGAAAAACTATGTTGGGATGAAAAAATCATTGCTATTGTAGTGGAACTGTCTAAAGATAAAGATGGATGCATAATTGATG',\n",
" 'GATCTTAATTGGCATATTTGCATGACCTGTCCCACACAACTCAGAACATGCTCCATAGAAGACACCTTCTCTTTGAATTAAAGCAGAAACTTGATTTAAT',\n",
" 'AGCAATCATAAAGAGAGAAGCTCTAAGAACGATCGATTCAGTTTTCGCCCTAGATTTACTTTTTCCAGGTTTCTCACAGGAAATAATCAATCCTGATTTG',\n",
" 'AAGCACGGTCGTTTTAGGTTTTACCAACTGCGGCTAATCTTTTTTTATACTGAGCGTATTGGAACGTTATCGATAAGAAGAGAGCGTCTAAGCGAACAAT',\n",
" 'CATCGGCAGAACCGCTACGAGCCTCCACCAGAGTTTCCTCTGGCTTCACCCTATTCAGGCATAGTTCACCATCTTTCGGGTCCCAACAGCTATGCTCTTA',\n",
" 'CGAGGAATAGTTTTCATGCCAGGTCGTACTGATAACCGCAGCAGGTCTCCAAGGTGAACAGCCTCTAGTTGATAGAATAATGTAGATAAGGGAAGTCGGC',\n",
" 'GAGAGGAGAGAGAAATGTATAATGGCAAGGATAGAGCACAAAACTCCTATCAGCCAATGTACCAAAGACCTATGCAGGTACAAGGACAACAGCAAGCTCA',\n",
" 'ATTTTCTTGATTGGTCTGACTTTAAATTTGCTCCCATCCGCGAATCCACTATCTCTCGTGCTATGACTTCTCGTTATTTCAAGGATCTTGACAAGTTTGC',\n",
" 'TGGCCTAAAATATACAAACCACCCCAAAACATTTCCTGGGAAAAAGATTGTTTATATCGCACCAATGAAAGCATTAGTACGTGAAAGGGTTGATGACTGG',\n",
" 'AGGACCAAAAAATCGAAATCGATGATAAATCTAGTACTGATTTGGAACAAGAAAGAATTGAGAAGGAAAGACTTTATGAACAACGTAAACAAGAAATTTT',\n",
" 'GCGGAGGATAGAGTGGTAACTAAAAAGATTTGGATAACTTGAAAGGCGAAATAAGCTTGTTGAGTGAAATATTCCACATTTTGCTTAGATGGAGCACCTT',\n",
" 'CTTCACGGTAACGTAACTGAATGTGGAGACGTCGGCACGAGCCCTGGGAGGAGTTAACACGCTTGAGCGCCATCCATTTTCAGGGCTAGTTCATTCGGCC',\n",
" 'GTAATGGATTCACTATTGGACGAACGGTCATCTATTGAGGGCGTACTATTTGTAGTCCTGTATTTGATATTTGTATCACTATTTCGTTGAATATATGGTT',\n",
" 'GTTGTACTGAGTGTACATTTGCAGTATTAGCAGCTTGGTAATAGTTTGTTCCTTGGGGTTGTATGGATTGTAGCTGAGGCTGTTGAGCTGGATTAGGTGG',\n",
" 'GGAGTGTGGTGAGGTAGTATAGTCCGCATTGGGATGTTACTATCCTGTTATGGCATGGATTTCCCTTTAGGGTCTCTGAAGCGTATTTCCGTCACCGAAA',\n",
" 'CTAGTCCAATTGTACCTCCTCCCATGATAGTAAAACGTGAAGGTATATAATCCAGTGACAATGCCTTATCAGATGAAATTATCTGGGCTCTCGGGTTACT',\n",
" 'ATAACCCCATAAATGTTGGGTAGTTTTCTCATTTTCACGTATAACGTATCATTAATGTACATGTAATAGAGATAGAACCACGTGTGTAGAATAGATTCAA',\n",
" 'GCGGTGAGCCAATAATAAAGAATGAAAACGAGAACATAAATATTGAATTTCTTCAATCATTGGAAGTCCAACCTATCGACAGCCCAGCCATTTTTTCTCC',\n",
" 'GTAAGCGGATTTAGCTCAGTTGGGAGAGCGCCAGACTGAAGAAAAACTTCGGTCAAGTCATCTGGAGGTCCTGTGTTCGATCCACAGAATTCGCATTCCT',\n",
" 'AATTTGGCGGTGCCATCAGGATTTACTCGCACATTGTGGCCATTCCCTCGGAGATGAAGTGTGTCCTGAACCATATTTTTTAACATTTTTTTGAACTAAT',\n",
" 'TTGGGACCCTTGATTTAATTGCTTCTAACAAAGCGTTTCTATTTTCTGTGGGATTTAATACGACCAGCAAGTCAGGCTTAACCTGCTTTGATGTTTCATT',\n",
" 'CAGATATTTTAGTATTATTAGTTTTACCATTTACTGATAGAAGTGTAGTAAGAGGTAATACTTTTAAAGTATTATCTAAATTCTTCTTCTTTATCTTTGT',\n",
" 'TGTCCCTGATATTGTTCCCCTATTTCGGTTTCAATCTTCATACTTCTCACAATGGATATTCGCTCCAATGGCTTAGTAGCTGCCAGAATTGGCCCCTTAG',\n",
" 'AATGTTGTTAGATCCTTTATGATCAGATCAGCCAAAAGGGTTTGATAGGCCTCAAGAGGTACGTCCGGGAGATATCCAAGATAATTTAATTAGAAAAATG',\n",
" 'GCGTACGACCCAGAACGTCTAAGGGCATCACAGACCTGTTATTGCCTCAAACTTCCATCGACTTGAAACCGATAGTCCCTCTAAGAAGTGGATAACCAGC',\n",
" 'CAAGCAGGTTTCCGTCAAAACGAAGATACCTTACTAGTAGGTGCTACAGATGGTGTCGGTACTAAATTAATCATTGCCCAAGAGACCGGGATTCATAATA',\n",
" 'AACGGACGAAAAAGAGGATGAAGGTGATAATGAACATAGGGAATATCCCCTAGCAGTTGAACTAAAACCATTTACGAATAGAGTTGGAGGTCAACTGCTA',\n",
" 'TTCTGGTACTGTCTGTACGTCAAGTAAGATTCGAAAGAAAATTGGGCAATCGAGAACCCAGAAATGATTAATTTCCACGGGATATTAGGATGGTCGAGAA',\n",
" 'ATCCCACCACGTAGTAAGTCATAAAAAAAAAAGAATATTATTTAATTAACACTTTAAGAATTTTACTCTTCATTATAACAATATCGAATAATGATAATAT',\n",
" 'GTACGATACACTTCCGCTCAGGTCCTTGTCCTTTAACGAGGCCTTACCATTCTTTTGTTACTCTATTGATCCAGTTCAGCAAAGGCAGTGTGATCTAAGA',\n",
" 'GAGTGATACTCTTTGGAGTTAACTTGAAATTGCTGGCCTTTTCATTGGATGTTTTTTTTCCAAAGAGAGGTTTCTCTGCGTGCTTGAGGTATAATGCAAG',\n",
" 'GCCGGTCATTGGTGAGGCTTATATGTTCAGTTTGCATTACTGATTTCACAGTATCCGCAGGAAAAATACTGGCGTTGAATGCCAATCCAGTGCTCCCTCC',\n",
" 'TTCACCAACACGTGCCATTTTCCAGAAGGCCCCCAAAACCTCATGATTTTTGTAACGATCTAGGAGAGACGGCTACTGCCCCCATAAGAACATGAACAAA',\n",
" 'CGCTCAAAAAGATTGCTTTCTCAAAAGCGTCAAAATCAAGGTTAGTTATACCCCCAAATTGCGACTGCCGGTAGACCTCCGTTTCAAAGTTGTGAAACTC',\n",
" 'ATTTTCTTCTTCGCTTTCAACTTCACTTTCTCCGGACGATTCAGAATCAGAAGAAGTGAATTCATCAGAAGAGCTAACATAATCATCAGGAACTTCACCA',\n",
" 'GCGAAGATATAATTTTCAATTATGTGCCCGGTCCCGGAACTAAACTAATTCAATATGAACACAACGGACGAACTTTAGAAGCTATAACTGCTACACTAGT',\n",
" 'TTATTGATTGAGTCGCTTCCAAAAGTCCCAATTCTAGAATATTACAATGATGAATCAAATCCTTATCCTCTGGATCGTACTTAGACATAATACTCTTAAG',\n",
" 'AATGCGGACTATACCACCCCACCACACTCCTACCAATAACGGTAACTTTTCACAACCGAAATCAAAACCAACGGATATCATACATTACACTACCACCATT',\n",
" 'TGGTAAATAGTGTTGAAGAAATAAGAGAAGGAGATGCCCTAGAAAACAGAATGTTCTTATTTAAATAAGTAAACTCAAAAGAAAAAAAAAGGAAGGAAGT',\n",
" 'GTAGCATGCAAGTTCTCATCGGAACGAAATTAGTGACTGAAGGAATTGACATTAAGCAATTGATGATGGTGATCATGCTTGATAATAGACTTAATATTAT',\n",
" 'TAAAGTTTGAAACTTGTTCTAGTTGAAACAAAGCCGGTGATGTTACTTACTACTAAGTCTAAGCGACCCTTAATGGTCCCTCTCCTGGCCGTAGCACTGA',\n",
" 'GTGAGTAGAGAGATTTCATCACCTTCCAAGAATTGTTCTATCACAACCTGCTTGCCCGACCATGACGGAAACGACAATTTTTTCAAAAGACCTTTTCCTA',\n",
" 'CTCTCTGGACAGTTACTTTGCACAACAAACTGAGAATTTTCAACATCTGGGCAGATGGTAGTGATTTCAACTAAATCGCTTTTCATGATACGCTTCCAAA',\n",
" 'GATACTGTACAAAAAGAAAAAAATGATACTGTTTCAGGTTTGAGAGAAAAAATAGTTGCACTGGAAAATATACTAAAGGAAGAAAGGAAAGCCAAAAAAC',\n",
" 'AGCAAAGATTAATTGACCTGAGAACCATGAATTCAGGGGTAACTGCGCTTGGAATGGGAAATCAAACACTAATGCAATCAGAAATTTTATGCTGCAAATT',\n",
" 'TGGTATATCATTTTGAGGAATTTTCCAAATAGAGTTGAAGCCTTCCTTATTGCTAGTGATATTAGCATCGTTTACTGAATTGAAATTTTCTTGCTTTATA',\n",
" 'AGTCTTACCAGTACCTCCATCACCAACAAGAACTAACTTGAAAGTGGGAACCTCGGCATTGTTTTGAGCAGGTGCTGACATTACGAACTTATATAGGTAG',\n",
" 'GTCGCTCATGCTGTAAGTCTTAGGTTCTAATATCTTAGCTGATCATTTATTAATGGTTATTTTAACTGGTTTACTATTTAATTTTATGTTAATTAATTTA',\n",
" 'GTTATATTGCTCCTTGCAACGATCAAGGCATTCCAAAAGATCTTCATCGTCACCATCATCCTTCCAAAAACCTACAATTTCCTCTCCATTTTTGATGAAT',\n",
" 'TTTAGTAAGCTCTTTTTGATTCTCAAATCCGGCGTCAACCATACCAGCAGAGGAAGCATCAGCACCAGCACGCTCCCAAGCATTAAGCTCAGGAAATGCA',\n",
" 'GTGCAAATCGATCGTCGAATTTGGGTATAGGGGCGAAAGACTAATCGAACCATCTAGTAGCTGGTTCCTGCCGAAGTTTCCCTCAGGATAGCAGAAGCTC',\n",
" 'GTGCCTTTTCCGGTTCTCACCAAGACGCCATTAAGAAGGGGTTCACCTTGAGCACACTTCTTGTTTTGTAAGTTGAAACCCTTCTTAATGGCGTCTTGGG',\n",
" 'TCGGCATAGTTTATGGTTAAGACTACGACGGTATCTGATCATCTTCGATCCCCTAACTTTCGTTCTTGATTAATAAAAACGTCCTTGGCAAATGCTTTCG',\n",
" 'TGCCAGTGAAATACCACTACCTTTATAGTTTCTTTACTTATTCAATGAAGCGAAACTGGAATTCATTTTCCACGTTCTAGCATTCAAGGTCCCATTCGGG',\n",
" 'CGATCTTGTGTGCAATTGATATCTAGTTTCAACTACTCTATTTATCTTGTATCTTGCAGTATTCAAACACGCTAACTCGAAAAACTAACTTTAATTGTCC',\n",
" 'TCGGCCAGTTGGTTATTGACTATCTGTGCGATTCCCCTTCCTGCATAAAAATAAACACAATCTTAATACGCCATACGTTGACTCCATTTTTTGCTCGTTT',\n",
" 'TTGGCCTAGACTCGAGTGCTATCTTTTTTAATGCCATTACTTCAAGACAGCTTCTGGAGTTCAATCAACTTCTTCGGAAAATATAAAAAAGCACTAATTA',\n",
" 'AACCACCACTACCTTTTGTTACAGTTGCTTGAAGATTACCACCAACAGATCGGAAGAGCACACGTCTGAACTCCAGTCACTAGCTTATCTCGTATGCCGT',\n",
" 'CAGTGTTCTATCTACACAACCATCATTAGCCATAATTCTTGTCCCCAAAGGTTCACCGGTATTTTTATTAATCAAAACGCAAGCAGTATCTCCGAATGCA',\n",
" 'AAGGATTGGCTCTAAGGGTCGGGTAGTGAGGGCCTTGGTCAGACGCAGCGGGCGTGCTTGAGGCATTTGGCTACCTTAAGAGAGTCATAGTTACTCCCGC',\n",
" 'TTTCCAGCCGCAGATATGACCACCAACAGATTTTTCACTAGGAACGGAAAAAAACTAAATGAAAAATCTGTTGGTGGTCATATCTGCGGCTGGAAATTCC',\n",
" 'CCAAGCTTTTACAACTATATCTAAACACAAGGAAAAAAGAGAATTGGATAACCGGCGATTTTGGTCTCTTGAACCCATTGACAGACGCGTTAATATCAAT',\n",
" 'GCAGATCAAATGCTGGCTTTTTTTAGACATATCAACCCCTAAATGGGTTTAGCGGATAACAAATATATATCAATAGTAATATAAGGTATATTCAATAGAG',\n",
" 'CCTTTACAAATGCAACCTTTATCAAGAACTTCAAGTTCAAGTGTTAATGTCACAGCGATGAGAAGTACATCTGCAGGTAATTCAATTACAGCGAACGCTC',\n",
" 'TGGAGATTGAATAGGTGAGTTCTCCTCTCTATAAGCAGCATTTGGCGTCTTAAATACAATAACATCATCATCTATATCGTCTGTCCTTCTTGAATGACTG',\n",
" 'TGCGAGAAAGAGGTCCTCTGCAGTGTTCATGCCACAAAAACTTGTCAATTTATTACCACAATCGTTCAACGACGAACTGTCGTTGACCCCTGGCAAGAAA',\n",
" 'TCTCAGCAGTGCCCTCCCAACTTTCCTCAGATATATCAGTAGCAGTAGAAAGTTCTATGGTCTCAGCAGTGAGATCGGAAGAGCACACGTCTGAACTCCA',\n",
" 'ACGGGTTCATTTGAGATGCCTGAATGTAAAATTCGTACTGCTCTGGGCAGTTATATGGAACATAAATTCTTGGATTTTTAGCGCCTGGCGTATCTATTTT',\n",
" 'TCCGTAAAACTTGTTTGTTTCGAATTTGAAAAGAATAACATCCCCAACCTCAGATGATACCGCCAATTCCAATGTTTCCGATGCAAAGGAGATATTGGAA',\n",
" 'TTTCCGTTTGCGGGTTCAGCGTAGGCTGCATAGAGGTACCTTTAACTTGCGCAATATGGACCACATTATTATTGATTGTTAGAAGTACCGGAACCCATGA',\n",
" 'CCACTACTGCTAACAACTCCACAAAGGACACAGCCACCACTTCAATAACCGCCGCCATCAGTATTCAATTGTCAGAGGTGAAATTCTTGGATTTATTGAA',\n",
" 'GGGAAAATAGTGGCATATTAAGCAAGATTGTATGGTTCTTGCTTAATATGCCACTATTTTCCCAGCGGCGTGCGTTTGAACTCTTGAGGTGCATTCTGAC',\n",
" 'ACGAGGAAGAGGAAGAACAATTGGAAAAGCAAAAGATTCTGCTAAAGAACAGAAGAAGAAATAACGAAAGAGAAGGAAGAGCTAGAACGTAAAGTGAGAG',\n",
" 'GCCACAAGTTTATTAAACTCTTTAAGCATATCATCCTGTTCCCTAATATCGCCGTAACTAATGGAATATTCTAAATAGCAGGCAATTAGTGAATTTAGTA',\n",
" 'AACTAAGACACTGGCCTGAAACTGGTTTTTAATAAAAGCTAGTATCGTAGTAAAAACATCGAGGATAGAGTCCTCGCGACGGTCGTGTAATGGATAAACC',\n",
" 'CAGTTGATCTTTGGAATGAAATATTGTCTAAAGAAGATCCTACAAACGCTCTTCTAGAATTAAATATTTTTGCTGCGCAAGGGGGCTCATCTTTAATCAG',\n",
" 'ACTTGACCCAAGAAATTTCCCTGCTTCGTTATAAAAGCATAACTTATCGCTACTGGCTTTTAAGGTAGCGTAGCCATCACCACTCCAAGTCTTGTGTTTT',\n",
" 'GGTATTTCCGAAGTAATAATTACAGGTGTAAATATCTAAATCCCTGAAAGCTAGATCCGAACTCATAGCTGAATTGTCCGTGCCATGCGTCCCCACGATA',\n",
" 'TGACACAATAGATACCGATAGTGTTAGCTATAACGGAGTTGCCAAATTCCGGAGAAATAGCGTAGATATACCGCTACAGACACATAACAGACTGGAAGTA',\n",
" 'ATATCTGATTATAAAAGTATGAGAACAAGAAAATTAAGGAGCCTCCATAATAAGGTGCTTTTAATTGAGAATGAATGTTCATTAGTTGCTATATTGATGG',\n",
" 'TGGCCTATAATTGAGGTCCCGCATGAATGACGTAATGATACAACAACTGTCTCCCCTTTAAGCTAAGTGAAATTGAAATCGTAGTGAAGATGCTATGTAC',\n",
" 'TACTCCCATTACAAACTAAAATCTTACTTTTATTTTCTTTTGCCCTCTCTGTCGCTCTGCCTTAACTACGTATTTCTCGCCGAGAAAAACTTCAATTTAA',\n",
" 'CTGGCATGATATACTACTTTGTAGAGCTGACTAATTTAGGCATACAGGAAAACACAAGCAGTAATAATAACAACAACAATAATCATGGTGACGATGAAAA',\n",
" 'AATTAGTGACTCAATAATAATACAGAGACCGTACAAAAATAAGAGATACTGCACTTGCGCGGCTGATAGAGATTTCTTTCTTTCTACGCTGGGATAGTTT',\n",
" 'CTTCTTCTAATTCTGAGTGGTGCGCCAGATGGACATATGAACATGCTAAGGTAAAGTTAGTACCATTAGAAGATCCCTTGAATACCTTTAAAGAGTCATA',\n",
" 'TCACGAGTTAAAATACCTAATTCAGGCTTGCCTACTAAAGCCAAAGTAGTGTAAGGTTTTAATTTCAAAATCAGGTCCGATTTCTCTTTGATTATGTTAT',\n",
" 'CCCCATCTCTTAGGATCGACTAACCCACGTCCAACTGCTGTTGACATGAAACCTTTCCCCACTTCAGTCTTCAAAATTCTCATTTGAATATTTGCTACTA',\n",
" 'TACATCGCGAAGATAGAATCTTAGATCACACTGCCTTTGCTGAGCTAGATCAATAGAGTAACAAAAGAATGGTAAGGCCTCGTTAAAGGACAAGGACCTG',\n",
" 'AAATATCTACATCCTTATGCCGTCTGTGTCTGTACGTTGAAGTGTATACCATAGTGGAGATTGTCGTTCAACGGATACTCTTTTATAATAGCTTCACCAT',\n",
" 'TGATTTGTTACTTTTGCTAGTTTTGTGTGACTTTCCTTTGTTTTATCGAACTTGTCAATGAAATCTCGCATTGTTATCATCTCATAATACAAATCTGAAA',\n",
" 'CATTAAATGCATAATAACCATTGCAGCAATGATAAAAGGTACTAAATAATGTAACGCAAAGAATCTCTGGATTAGAGGGTTAGATACTGAGCTTTTAATG',\n",
" 'AATTCCCACGAAAAAAAGGAGAGTAGCAACGAAGGTAAGGGGCAGAAAATCACGTAATACTTCTAGAGTATGATCCAATATCAAAGGAAATGCTTTAGGG',\n",
" 'ACGGGGAATAAGGGTTCGATTCCGGAGAGGAAGCCTGAGAAACGGCTACCACATCCAAGGAAGGCAGCAGGCGCGCAAATTACCCAATCCTAATTCAGGA',\n",
" 'GTCAGAATCCTCGAGTTCCTCTTTTACTATTGGCGTTCTCCATATCAAATCATCGTCAGTACTTTTTTCACTGTAGCTCGTTGCCACTCTGTACGGCATT',\n",
" 'TCCTCCCAGGGCTCACACCAAAAAAGATACAGTGCAGCTTACATTCTTGATCGATGTGCTCAAAATATACGCTCAAATTGAGAAGAAAGAAATAAAGAAG',\n",
" 'CAGATGGCAATGCAACAGCAAAGAATTGACCCCAGCCAATACCATAGGGTTTCAAGTACGACATGGAAATGATGTTTTGAGGTGAAGAGATTGGTGAAGA',\n",
" 'TTGGACATTGTATATTGTACATTATCGTAGAGAGATCCGGTTGTCTTTAAGGGACCGAAAAAAAGAAAGAAATCTCAGGACATCAGAAATGTACGAAGGC',\n",
" 'TTCTTTTGGTCAATTGATATTCCATACTTGTTTCCTGCATTTATTCAATAATGCAATTCCTCTTGATAAAACAATACACAGTTCGTTGACATTCAGCTTT',\n",
" 'CTACTGTACGATACACTTCCGCTCAGGTCCTTGTCCTTTAACGAGGCCTTACTACTCTTTTGCATTTCTAATCTCTTTCTCGGTCCAGCTAATTTTACTA',\n",
" 'AGAGTCTTTAATGAAGAAATGAGAACGCCTTTCTGGACTTAAAAATTCATACTTTTGCATTCTGATAGAGTGTAGTATTCATATCTAACAGAATGCAAAA',\n",
" 'TACGAGAAATCAAAGTCTTTGGGTTCTGGGGGGAGTATGGTCCTTGCGATAATGACATTGGCATACCGCCAAAATTTCCAATAGGTCCTCTGTAAGACAT',\n",
" 'TGACGAAAGAGTCAACTTGGTGGAATTGGGTGTCTACGTCTCTGATATCAGAGCTCACTTGGCCCAATACTACATGTTCCAAACCGCCCACCCAACTGAA',\n",
" 'GCGCTATGCAGGTGCAAATCTCCAGCAGCAGCAAAGAAAATTCAGTTAATAAGAAATCTCACTAAGATAAGCGACTGTCTGTCCCCTTCAAGCACAACAT',\n",
" 'CTCTTATTCTACTCCGTAAACGATACTTGCAACGTGATGTTTTCTTCCTCCTCCCACAACCGTGCTATGCTCCCATCTTCTCTTGTGCAAAGAAATAACG',\n",
" 'GTGGTGTTATCTTAGTATAATTGGAACCAATGGACTGGAGGATGATGAGGATGTATTGGTCCCGGAGGAGGCATTAGAAGATATTTGTGCGCTCGTAAAA',\n",
" 'AACCCGTTTACGAACTGATGAGAAAAGGGTTTAAGTGTGTGATAATACTATTAATAGCTAAAAGAGCAGAGAGCTTTACGATGTTGTATGTTGTTTTATA',\n",
" 'AAGGTGACAGGTTATGAAGATATGGTGCAAAAGACAAATGGATGGTAGCAGGCATAGTAAAATGATGGTGTGGAAGACATAGATGGTATTTGTTTTGCAT',\n",
" 'AAAAAACCAAAAACGCACCGGACTGTAACGAGCTACTAAAATATTGCGAATACCACTTCCACAAACATTGCTCAAAAGTATCTCTTTGCTATATATCTCT',\n",
" 'AAATGGATTTTTTTGTTTTGGCAAGAGCATGAGAGCTTTTACTGGGCAAGAAGACAAGAGATGGAGAGTCCAGCCGGGCCTGCGCTTAAGTGCGCGGTCT',\n",
" 'GCGGAGATTATTGAAAGTCGGCATTGGCTACCATGAAATGAGTTGGAAGCTTGAAAAAGTAAGGAAGAATAATTTTGCAAGAAACTAGGGTAGGACTACT',\n",
" 'TGCGTTAACACCGTTATTGGGTGTTGGTATATGTGTCTCAGTACAATTTGGTGTGAATGAGGCGATGAAAAGATTTTTCCAAAATTACAACGCTTCTAAG',\n",
" 'AAGTCTTATGCCTTGGATACTGTAAGTGGCGAAACTGACGACTTGATTGGCTACGGTAGATTCGTAGAATTCAATAAAGACATCTCTTTGGAGCAAATTG',\n",
" 'ACGGGCAGATGCTGTCTCCACTATTAACTTGTTACGCCAAAGAGGGATTTCACTACACATTTTATCAGGGGATGACGATGGAGCCGTTCGTTCTATGGCA',\n",
" 'CGCGCATAACTGCTGAAAATAAACCTTACCGTCTTGAATGAATTTGACCAAGCCCTGGTCCTTATCTTTAACAACAATTTCATCAATGTGTGACCAAATG',\n",
" 'GGGGAGTTTAAATAGCTTGGGCAATAGTGCATATTTACATGTGCCTAGAAATCCGAGCAAGAGCAGGAGGGGGAGTTCTACTTTATCAGCGTCTTTATCA',\n",
" 'CGGTACTATCTTGTGATAAAAAGTTGTTTTGACATGTGATCTGCACAGATTTTATAATGTAATAAGCAAGAATACATTATCAAACGAACAATACTGGTAA',\n",
" 'TTTTAGTTTAAAATTTCGTTTAATCTAAAAATACTTGTATCTAATGATTTAAGGACTTTTGAACTATTTACAAGATCGAGTCTCGCCCTCTTCTTTCAGC',\n",
" 'TAAATGTTTTTATTGATAATTGAGCGAAAGTGGTAGAAAGTATGTACTGGCTATTTTTCTTCCAAATATAACCGAGACCGAACAAAATTTAAACAAAACA',\n",
" 'GTGGCAGGATAAATCCATAGGAATGTAGCTTGCCTCGGTAAGTATTATAGCCTGTGGGAATACTGCCAGCTGGGACTGAGGACTGTGACGTAAGTCAAGG',\n",
" 'GTGCGGTATCAAAATGTTCCACACTGTTCCTATCTTTCTATGCCTTTCCGCATTGGGACGAACTTTGCGCGAAGTGGAAATAATGAGTGACATTAGTCAG',\n",
" 'GAGCATTGGAAGCCTGTTGATGTAGAGGTCGAGTTTAGATGCAAGTTCAAGGAGTCAAAGGGGGATGGCTTTTGCCATTTGTGAGAGTTGTGCGGCAGCA',\n",
" 'GCTGGTTGTTGTTGTGGTTGTTGTTGTTGTAAAGGAGCTTGAAATTGAGACAGAGACTGTTGTTGCTTCTGTAATCTCTGTAGTTCCTGCAATTGCTTCA',\n",
" 'CTCGGTAAGTATTATAGCCTATAAGAATACTGCCAGCTGGGACTGAGGACTGCGACGTAAGTCAAGGATGCTGGCATAATGGTTATATGCCGCCCGTCTT',\n",
" 'CTGGATAGTTCGTCAGCCATTTCATTTGCAAAAGCATCAGCTTCACTACTATTCTCGATAGACTTATATTTTAGCCTTGCACTTTGCAAATTCCTAATTA',\n",
" 'TGCTTTATTAACGTCTATTCTACAAGCCTTTTGAGCATCCGTACTACCTCTGGTGTTGTCTCTACTGCCACTGGTTCAGTCACTTTATCCTCTAACGCTT',\n",
" 'TCGATCCACTTGTATATTTGGATGAATTTTTGAGGAATTCTGAACCAGTCCTAAAACGAGTAAATAGGACCGGCAATTCTTCAAGCAATAAACAGGAATA',\n",
" 'CCAATTTGGGTAATTTCAGTTACAGTTATTTTTTAACCATAACACAAAATTCGCGGGGTTTTTTTACATGAAATTTGTGTATTTTAGCATTCATTAGCAG',\n",
" 'GTCCTTGCAAAAAAATATTAAAATTGAGACCAAATAAAGATCCTGAATCATAATATATACGTGTGTACTTCACTTTCTATAGAGGAAAAAAAGCTAAAAA',\n",
" 'CATGTCTAGCCACCATTCGCCATTAGATTTGGGCTGCTTCAGTCATGATAAACCGACAGTTTCTGAATTTAACCTTCCGTCAAGCTTCCCGAATACTATA',\n",
" 'TTTGCACGACCTAGTTCGAATGACTTGATGTAGGTTGGAAGTCCATTGGCATGTAAAAGTTCGGTGGTACATCTGTCGGTAAATTTCCCGTCCAAATATT',\n",
" 'AGATATAATAGAGATTTTGATTGACATCATATGAGTTGGAATCCAATGAGTTTAAAGTTTCTTCGAAAATAATATTTAAGTGGTCCACTAATGTAACCCA',\n",
" 'TTGTGAAAAGTTTTTTGGTATGATATATGCTACTTGCAAAATATCATACCAAAAAACTTTTCACAACCGAAACCAAAACCAACGGATATCATACATTACA',\n",
" 'TAGTATGATATCCTGAAGAGATTGAACTCTTTTTTCTCGGTTTTTTGTGCACTTGAGAATTAGGAGGGTTACCACGACGAACTGATATTGTACTGGATTT',\n",
" 'TGACAGGGCTCAATGGCGGTAGATGATCTGATTTTCGAGTAACTACAGTTCTCGACCTGACCCAATGGAAAGATCTCAGCGGGTCGTTTATGATACCAAA',\n",
" 'TGTTGTGGATAATAGTGATTCGACGTCTAACAGCCCCATAGACCCTATTCTATTGAGTACTAAAGTCGAACATGGTGATTTGACCGAATTTATGGAAATA',\n",
" 'ACCTGTGCGAACTACAAGCACTACCGCCCCTTGAATGAACACCAAAAGATGTGTGTAAGTTAAAAAGTCCGAACGAATTTATCCTTATGTAACTTACACA',\n",
" 'GCACGTCTTCCTCTAAAGCAGTTCTTAGCGGATAACCCCAAAAAAGTTCTTGTTCTTGACGGTGGTCAAAGAACAGAACTGGAAAACAGAGGTATCAAAG',\n",
" 'GTCAATTCCTCTGCTTNGCTTTTCAAATCTGCTGAAGTAGCATCAGTGGAAAGTGTTATTGGGTAAACTTTACCAGAATGTCTAATATTGAACTCAAACG',\n",
" 'TTGATACACCTTTGGTNGGAATGTATGTCTCGCTAGAAACTGGAGAAGGCCGTCCTGAGGCCGGAAACCATCTCACCCTTAGGGAGGCAATCGGAGGGCC',\n",
" 'AGCTTAACGTCCAGCTTCAAGGAACGCACTAAACCTCTTGGCACAATGGTCCTAATCAACTTTCTCTCCTTCAAATCAGTAAACAGTGTTCCGTCAGACA',\n",
" 'TTTTCCACGTTCTAGCATTCAAGGTCCGCTTCATTGAATAAGTAAAGAAACTATAAAGGTAGTGGTATTTCACTGGCGTCGAAGCTTCCACTTATTCTAC',\n",
" 'GTCGAAGTCTACATGAAGAACTTTACCCGTCTGTATATCTAGTAATATGTTTTCACAGTGCCTATCACCTAGATCTAATATATGGCCAACCATTGCCATG',\n",
" 'TGGGGTCACTGAGAACAGCCCTTTACAATTACCTATTAGCAAGAAACACCAATGGGCAGTTTTTGCTTCGTTTAGAAGATACAAACCAGAAGAAGCTAAT',\n",
" 'GATTTGGTGGATTACTAGCTAATAGCAATCTATTTCAAGGCATTCCCCCAAGTTTGAATTCTTTGAAATAGATTGCTATTAGCTAGTAATCCACCAAATC',\n",
" 'AAAGTCAACACATTAGTTCTTTTGTCATGAAATAAAAAATCTCTGAACACTACCGTTCTACAACGTGGTTTGTTCGTTAGTTCGTCAACAGTAGCAAATT',\n",
" 'TATATTATATTTCATAGTAGCCTGTGAGACACCGAATGCTTGATGTGTTCCCTTAAGTAACTAGTAGTATTACACTAGAAAGCTCCTCTTTTTTTGTCTC',\n",
" 'ATCCGGGTTGAAGACATTGTCAGGTGGGGAGTTTGGCTGGGGCGGCACATCTGTTAAACGATAACGCAGATGTCCTAAGGGGGGCTTATGGAGAACAGAA',\n",
" 'AGGTGGATAGTAGATGGTGAAAAAGTGGTATAACGTATGTATTAAGGGCAGTTATACAATATTTGGGGCCGCCGAATGAGATATAGATATTAAAATGTGG',\n",
" 'TGTAGTTTTTCACACTTGGATTCTAGATGAGATGCCTTCTGCTTGAAGTGCTTCAATTCTATTTCTGTATCATTTAATTTAGTTTCTAGATGCGTCATAT',\n",
" 'CTATTATACTACATCAACACACTTGCACAACATATACTATTTCCGTCCAAGCAAGTGTTAGATATGACATATGAATTGATACAGTTCATATGGAATACGA',\n",
" 'GCATTCGATGTATTAACGGATATGGATATTTATTTACGCTTTTGCTTTTGTTGACGTTGTTTATTGTTAGCTTTGAAATGTGCGAAGGAATTAGGTATTT',\n",
" 'AGCTCGTAGTTGAACTTTGGGCCCGGAGATCGGAAGAGCGTCGTGTAGGGAAAGAGTGTAGATCTCGGTGGTCGCCGTATCATTAAAAAAAAACAAAAAG',\n",
" 'TAACCTCTCTTTGACTAAAATGATTGACAGAGTTAGCAAAGCCAAATCTAAAAATCCTAAAGTTCTAATGCCCCAAACAAATCCATAAGTTGGATCAGTG',\n",
" 'GGGGATTGTTATTATTGTGGAATAATCGTTCAGACTGTTCATGTTTAAGAAGGAAGGACTTCAATCTTAAACATGAACTAAAAACTCCAATAAGATCAGA',\n",
" 'GTGGGAATAAGATCCATTTGCCAAAAAGAAACCAAATATGATAGAATATAGCAACATAAAAAATTGAGTGCAAGTTGGAGAGAATCGCTTCCGACTTGAT',\n",
" 'ATCTGCCTTAATGAAAATTGCTGACAGTTGTTTAGTTCACCGAATACCCCTTTCTTGATCTTGCCAATGGTACCGATACCGCCGTCTATTATGGTCGTAC',\n",
" 'ATGCAAGATTTGTGGTAAGAGATTCAACGAATCGTCAAATTTAAGCAAACATATTAAGACCCATCAGAAAAAATACAAGTGCTCTGACTGTTCCAAAAGC',\n",
" 'AGCGTCATCATTAACTAAACCTATATCAGTATCCTTCAAATTGCTAATACTTATCATCTTTTCTTCCTCTCCGGCATCTTCTTGATCTTCATCCCTGTTT',\n",
" 'GCCAACATGCGCCGTCGGTAATTCCAGCTGGACCAACCGGGCCCAAAGTTCAACTACGAGCTTTTTAACTGCAACAACTTTAATATACGCTATTGGAGCT',\n",
" 'GAGAAGGTCAGATATAACTAGAACTTGTCCACTGGTACCGTTACCTGCACCGATACCTATTGTTGGTACTGAGAGTTTAGATGTTATGAACTGAGCCATC',\n",
" 'TTGGCTTATATAAAAGAAGACGTGCTATAAGCGAAAACACCTTTGTTTAGAGCACGTCTTCTTTTATATAAGCCAATCTTCCACACGAAAAACCGAGTAA',\n",
" 'GATTGGATCAGGTGAGGAAGTACTCAATGGTGGTCTGACATATTTTTTAGTGGATGTCATATCAGAGTCCGCTGAGGATGAATCAGTAAATGTATTACCT',\n",
" 'TTGCTCTGTCAGAATCCGAATTGAAACTGGATATTATAGTGCTAAGTATATAGACTTCTGTTTTGTTCTTTAAAACTAAATAAAAAAAATTCACCCTCCT',\n",
" 'AGGTTCAGACACAATAAGGATTGACAGATTGAGAGCTCTTTCTTGATTTTGTGGGCGGTGGTGCATGGCCGGTCTTAGTTGGTGGAGTGATTTGGCTGTT',\n",
" 'CCCTTGATTTCTGATGATGATCAAGATAGAAGCCTGGAAAATTTTGTAAGGGGTTTCAAAGATATGATTGCATCGAAAAATTCCACTGCCCCCAAGCATC',\n",
" 'CCAGACCATCTAAACTACATTGTTGAGAGCGTTAGTGAAATGACAACAAACTTCAGAAATAATAATAGCCTTAGCCGTTGGTTGCCCAGAAGTAAGTTTA',\n",
" 'GTTGATACGCCATACGAATTTCAATTGAAACTGATAACCACGTCAGGAACATTATGGTCTGAAAAGGTTATATTGCGTACACATAAGATGACTGACATGT',\n",
" 'GTGGTGATTTAATACCTTGAACATTTTTATGGTCGCAGCGACGGTGGTAATGCTGTCGGCGTCGTTGCTTTTGATGTTAGATTAGTCACTGTTGTGAGAA',\n",
" 'TTCTTTATTGGTATTCTTTCAGTCATTATTCAGATTGAACTTCGGATCAGTGAAAATTGTTGGTTACCCTTTAAACTGTAACACTACAAAGAAATTAAGT',\n",
" 'ACAACTGAGCAATCGTTTACAAAATTTATTGAGGGAAAAACCATCATCTTTTCAGCTTGCTAAAGAAAGAGCCAAACACTCGACACTTTTTCTTCACATG',\n",
" 'GTGAAGTGACTTTGAAGTACGGTATTGAGTCCATGTTGAAGCACTATGTGGATGAAGTGAAAGAAGTGATTCAGATCATGGATCCTGAGCAAGAAATAGC',\n",
" 'GGGGGTTCCTAATCGGGTTTTTCACTCCTTTTATTACTTCGGCAATTAATTTCTACTACGGTTACGTTTTCATGGGTTGCTTAGCGTTTTCATATTTTTA',\n",
" 'CCGCCTTATTAACAACGAGCCTGTTTCCATGCCACATGAACCCATTGAAGGTCTCGATGGGTTCATGTGGCATGGAAACAGGCTCGTTGTTAATAAGGCG',\n",
" 'AAAAAATCCAAAATCCTATAGAAATTCCATTAAGAACAAATTCAGATCCACAGCCGTTGAGATTGCGAATATTGAACTAGATAAAGAAGCGGAATCTGAA',\n",
" 'TTTTAGAAATGATTTCTGGATTCATTTTACTTAGATCCATTTTGTTACTTAACATATTGTCCTTGGATGCCACGGCTTCAACGTTACTAGGGTTAACAAC',\n",
" 'AGGAAAGTTTTGGTGCTAAGATTGATTTGATGGAATTGCTCGTATTTATTTCCGAATAATTTTTCTACTTCACTCAAATCAATCTTAGCACCAAAACTTT',\n",
" 'TCCAGAGGACAAAGCAAGCCAATATTCATCACACCCCACAAAGATGAATCTCTGTTAAAGGTTGTCAAAGAACATAGAAAAAAGTACATATCTTCATCAA',\n",
" 'TGAGGGGGTGGTAGCTAATCTATAATAGTTTATAATGCCCCTATTAGAAGTATTGTAATAAAATTAAATAAACATGGCTATTGTTCTCATGGTATTTTAG',\n",
" 'ACAGAGAATGTATAAAGATGGTCTCATTGAAAATAAAAAAAATTTTACTCCTGGTGTCATTGTTAAATGCAATCGAGGCCTATAGTAACGATACAATATA',\n",
" 'TTTTACACCCAAACACTCGCATAGACGTTAGACTCCTTGGTCCGTGTTTCAAGACGGGCGGCATATAACCATTATGCCAGCATCCTTGACTTACGTCGCA',\n",
" 'TTGAAACCACCATAATTTCATCCAATTTCTCCGGGTTGACAGCACCAAATGCAATAGCCATCCAAAACGCCACGTACAACCCGGAGAAATTGGATGAAAT',\n",
" 'ATTAGTCGAAGTCGGCCGTGTCGTTTTGATCAAAAAGGGTCAATCCGCAGGTAAATTGGCTGCTATCGTTGAAATTATCGACCAAAAGAAGGTATGTTGA',\n",
" 'TGTGGCTATTTCCCTTATCTACTTCTTCCGATGATTCGAACTGTAATTGCAAACTACTTACAATATCAGTGATATCAGATTGATGTTTTTGTCCATAGTA',\n",
" 'GGGTATAGGGGCGAAAGACTAATCGAACCATCTAGTAGCTGGTTTCTGCTGAAGTTTCCCTCAGGATAGCAGAAGCTCGTATCAGTTTTATGAGGTAAAG',\n",
" 'AGTTTAGTGCCGGCTGCTCACTCGTTCAATGAACACACAGTTACTATCCCTGCAACAGTGGATTTACCAAATCCGGTACAAGATACCCCAAGCGAAAGAT',\n",
" 'CCGCCGGGTAACACATATTGAAAAATGGCTGTTTACAGTGGGCCTCACTAGCTTAGAGTTCATCTCTATATAACTATTTATACCGTTTTTTTATATTAGA',\n",
" 'TCATGTCATTGGCCAAAAAGTAATGTAATACATCGTCATATACCGATTTTCTTAAGGCAGGTTTCTTGGGAATCAAAGGCGCAATTTCTACAATATTTCC',\n",
" 'TTTAGTGATTCAGAAGCTGCCTTAACAGACAACAAAGGCTTAATCTCAGCAGATCGTAACAACAAGGCTACTCTACTGCTTACAATACCCCGTTGTACAT',\n",
" 'GCGTCGTTGGTTAGGTATTGGATGGAAGCCTAGTATGTTGAGTTATGAGAGGACTCCATGAACCGATGAATTTTTGAATGAGGCCCCCTCTCCTGAAAAC',\n",
" 'AGATTATGATTCATTGTTTTAGATAGCATAGGCAGTGTGAAAAAGATGAAGGACCTAAATAACACAAAAGGAAATACGAAAAGTGAGGGATCAATTGAAA',\n",
" 'CTAGGCAACAGCTCAATTTTACATGGCGACGATAACAACGGATGCAACCCCAAACTAAAGGCAATTTGTATTTTAAACTTGTGGCACCAAACGTATCACT',\n",
" 'GAAGGTTAAGCTTGCTAAAATGGCAGGTACTAATGCAGTAATTGGCCAGATATATGACCTTTTTTTGTATAAGCCACCCTCCATATTTCCCGATCTTTTA',\n",
" 'ATTACACAGGTGAGCCGGGTTATCATTCAATGCCTTCATGATCTCTTTCATTGGCGTTTCATGATCTAATCTGTGAATTTGTAAAAGGTCTATATATGTG',\n",
" 'GGGCCCTCAGTGATGGTATTTTATAATTTATATGCTCCTCTTGCATTTGTGTCTCTACTTCTTGTTCGCCTGGAGGGAACTTCTTCATTTGTATTAGCAT',\n",
" 'TGATAAAGATGAGGGATGGATCCTGATAAGCAAAGGATCTTCAACGTTCTCAGATGTATCATCAATATCCATATCTACGTCTAGATCGGAAGAGCGTCGT',\n",
" 'GAAAGGATAAGGATATTTGCGTGTACTTTCACTTGTATGGAAATTATTGATGGTGGGTACGGAGATATTTGATGGAAGCAAGTACTTTTTAGATACCCAG',\n",
" 'GGAGCGTACTGAACCATGTTATCGATGATCTTGTGTGGAATACTCTTATAAATGGAGTGAACATTTGTATACCCCTTGTGTGCGTGTGGGGGATACAAAG',\n",
" 'CAATCTTTACAACCAAACGCAGTTCTCCACGAAGTACTTCAACTCGAACTCCTCTCCCTCGTTGACTTCTTCCACTTCTAACTCATCCTCTCCATACAAC',\n",
" 'GGACAGAAAGAGACGATAATGATGATTATCTGTTTCAGCGATCTCTACTATACCTCGTTTCCGATTCTTCTAGAAATCGCTGAAACAGATAATCATCATT',\n",
" 'CCACTTCCTATTAAGGCAGTTACACGACCACAACTGTCTCTAACTTCCAATTCTAATACAGATTTGGCATTAGCTTCTTCTTCTACAGATACATTATCCT',\n",
" 'ACAGTTCCCTCCTTGTAACTTCAAACCAGAGTATGATGTTCCTTACCCGTTTACCAGTCACAGCTTTTGTATTAGAAACATTTTGAGCAGAAACACCTTT',\n",
" 'CTATACTTTCGTCAGATGAAAATTCTTCCTTGTAATATATCTTTAAAAATAAATCGCGAGCCTCTTTATATCGTTCGTCTTCTTTGAGAGCTTGGCCTTG',\n",
" 'AAGGATTTGAAATTGCTGTGGATTTGGTACACAAATGGAACGACGAGTTTGGGTTGGAAATTCCAAAAGGCTTCCTAGACGTTAGTGAGGATAATCATGA',\n",
" 'TTGTCATCGCTTAAGTATTGTGATGAAACGAACTTAGTCTTAGGCCAGCAACAGAAAGAATCTAAGCCAACACACACAATAGACTCGAATGATGAACTAC',\n",
" 'TTGCCTTGTCCCCCCGCGCCCCGGCCACAAAGAGGAAGCTATTTGCCACCGAGCTTCCTCTTTTGACTCCAGGCCGGAATAAAGTAGCTTCCGCAAAACT',\n",
" 'GTTCGAATAGTTTCACCTCCGCCATCGGTTCGAAAATCAACTTCAACAGTAAGTGGGATTGGTTAGATGAATTTGACAAAGAAGACGAAGAAATGTATAA',\n",
" 'AAGTCTTCACATGAGGACTATAGAACTACCATCCAGGAATTATAGAGGAAATTAACTGAATCAGAGATCTATTTTGAAACATTCATTTACATGTAATTGT',\n",
" 'GTTTGAGAAAGACTTCAAAAGATATAACGAAATTTTAAATGAAAGAAAGAAGATTCAAGAAGATCTTAAAAAAAAGAAAGAACAATTGGCCAAGAAGAAA',\n",
" 'GGGGGCTCACATTCAAAGGATACTGCACATCTACTGATGGTAAATAATTGATGGTGTTATTATTACTGGGAAGAGGATACTGGTAGTAACTATCAGTGAT',\n",
" 'AAACTCGCCTTTGATTTTCCTTGTTTATACGCTGTTGGTGATTACGGAAATGTTATTGTGGCTGTACCGTATAATGCGGATGAAGACGACGATCCTCAAT',\n",
" 'GTGGTCACATTGCCGGGAACTCCACAAACAGAACATTTAATCAACAGGAAATTTTTGGAACACTGCAATCCAGGCCTAATTTTAGTCAACTTGGGAAGAG',\n",
" 'GATAAACCCAACGGAATTTTGTTGTCTCATCAGTAAATGAGATGAAATAGGATGGTGCACTTTTTGGTAGGTTGTGAACTGGACCAAATATGTCAGTATG',\n",
" 'TTCAATTTGCTTCATCAATTAGCGTGAAGAAACCATCCCAACAAAATAAACACTTTAGCTTGCATGTAATTTTAGGTGCAGTGGTAGATCCAGATACCTT',\n",
" 'GTTTCATGAAATCTTTTGAAAAATGGAAAAATGGCTCAAATATTATAAACGCCGCTGACTTTGCTGAAAAGTTTGATAATATAGATATGCCATACAAGAT',\n",
" 'AGGATGAAAAAGATGACACTGACACTACTACTTCTTCGTCCACTTCTACATCATCATCGTAATCGTCATCGTCATCGTCATCGACATCGTCTTCATCGAA',\n",
" 'GAAAGGTATATTTTGTATGTTTTGTATGTTCCCGTGCGTTTCCGTTTTTTCCAAAGTGACAGGTGCCCCGAGTAACCCAGGTCCTCACTATTTTTTACTG',\n",
" 'GAAACCACAGCCAAGGGAACGGGCTTGGCAGAATCAGCGGGGAAAGAAGACCCTGTTGAACTTGACTCTAGTTTGACATTGTGAAGAGACATAGAAGGGG',\n",
" 'ACATTTATTCCTCATTGATCCTATCTTTCAATCCTAATAAGCGACAATATTCTTAGCATATACGGGAGAGTTGCTCTCACTCATATCATATAGCTCTCTA',\n",
" 'TAAGAAGCAAAAACAAAGTTTTCATATTAAGCCATCGTAAAGGTTTAAGGCACCAATAATAGAGGGATCGACTTTAGAACCTTCTCTGAATTCGTCCAGC',\n",
" 'TATGAATAATGCTTTTTGTAATGTTGTCTGCTGCCCGCGTTTGGTCATTAATCATCGTCATCCATAGTCATGGGAATTTAGTAGTCAATCGCCTGTCCAA',\n",
" 'CTTAGTATGAAAGGAATGCCCTTTGTAAATTAACGTAAATTATAACGTTTTCGAAAAAAAAAATTGATTTCGTCCAGGATCGAACTGGGGACGTTCTGTG',\n",
" 'GGGCGAGCTATACGCAGTAAAACACAGTATACTTCTATCATCGTTACTTAAAACCATTCTTGGCCTTATTTTACTTCTTAGAGAGTTTCTTCTGGTTCTT',\n",
" 'TTCTCGCAATAGAAGACCACTAAACTCTCAATTGATAAATGTTGATGTCGATTTCAATTATCAATGATGGTATATTATGAATATTATCTTTAGTGTTATT',\n",
" 'CGTTATCATTCCATACTGTGGCTTCATTCCTGTATTTTATGAGTTTGCTGAAGGATTCGGGGGCAATAGTGTCACGGTGGTCAAAACCTTTAGCGTCTCA',\n",
" 'CTTTCTTATTTCTATTTTATGTGCATGGAAAATATATTATCACACATCTTACCATCTCATCATGGACATGTCACTTCTGATTCTCATGTAATCTAATAAT',\n",
" 'GCTAAAGTCCTTTTGGTGTGTCAATGGAACACCACGTAATTGTGAAATAGCTTCCATGCTTGCTAACTTATTACCGTCAATAGAAGACTTGAGTCAGAGG',\n",
" 'CCACTGTTGAATCTCGTACCTCAAAAGGGAATGCACCTCCTGTTTCATCTAGAAATCCATCAGGACAATCGAATAGAAGTAACATTAAAATAACTCAGCA',\n",
" 'AATAATTAGATAAAACTAGTGACATATGTCACTAATTAACTATATAGTCACTAATACTGTATATATAGCCGACACAGGCTACACAAAACACAAACGCAAA',\n",
" 'GTCTCCAAACACATCAGACAACCTAGCGTATATGATTTGTTTGGTAGACAGCACTAAAGACACACTATAGTCTAACGAACAAAAAACAGACGCTAGATTA',\n",
" 'TAGTGAATCGTCTGAAAATTCGTCTGAAGAATTGTATTCTATTTTTTCATTTTTTTTAATTCTTTGGCAATTACTGTCTTCTTCATTCTCATAAAATGCA',\n",
" 'AGCTTTTGATTAGACCCATAAACTCCTCAGCATCTACACTGTACGAATTCGCCCTGGAATGTTTTACCAAGGGTGGTAAGAGAGACGGTATGGCATGGAG',\n",
" 'CCAAATGGGGAAGTGTGCATATCCATTCTACACTTCCCTGGTGATGATCCTAACATGTACGAATTAGCGGAAGAAAGATGGTCGCCAGTGCAAAGTGTAG',\n",
" 'GCAGGCGGTAATTTGTTAAGAATAAAAGAGCTACTTTTTGAATTGTTCTACTATAAATGGAAAAGGAGTACTCCACATGCTCAATTTAAGAGGTTAAAGA',\n",
" 'GTTCAGCAGATACACGTCTCTTCCCAATTTCTTGTTAAGGTTACGGCCAATGCTTCGGTTGTTGAGCTTGTTACCGAATAAGCCGTGAAGAATGATAATA',\n",
" 'ACATCTCTTCACCAGGGTCAAAATTTGATCAGACTGTTCTTGAGGTAATGTAGTAACGGCGTACGCCTTTGAATTGGTCACCAGTGTAGCCATCGAAGTA',\n",
" 'GCCGGTATATATATGTTTCCAGACATTGGGCCCAAAAATCCTATAAAAATGATAATTCCAAAAATGATTAGTCTTTGATCCTTGGAAAAATAAGTATATG',\n",
" 'CTGTAATAAACCTCTGTTATTCTCAATTAATTGTGAATCAAATATTGAGACATACTCCGAAGGTGGCTCTGAAAATCGTGGAGTATAGTCATTAAACGAC',\n",
" 'GCAACACTAGCTGGATAACTTCAATGATTAGTGAAGTAAAACGCAAGGTGGAGGGAAAATCTATGCTGAATGATGAGGAAGATTTGCATTTATCCAAAGC',\n",
" 'ATAAGAAGAAACAAACTTCATCCTTAAAGTTGGCACCAATACAAACAACACAGCGAATACAAAAATGTTTCTCGCACATCTCCAAACACGACTAACACGA',\n",
" 'AATACATTGATTGGTGCACAAAACATTTCTTACAATACATTGATTGGTGCACAAAACAAAGAAACCGGTGAAGTCAACAAGGCTTATGACCTTGACGGAA',\n",
" 'TACTTACTCAGTGAGCCTTCTGCCTTTTTAAATCATCGCTTTCAATCTGCCATGTTATTTTAATATGCTTCAAGTTATCTTCTTTTTTATCAGTCACCAA',\n",
" 'TATTAGAATAACAGAATCATTAGCCAAGTTAGAATTAAGTCCTATTGCACAGAAGAGACGCTGTGTCCATTGTGGAAGCTTGAAACAATCTAATAGCTTC',\n",
" 'ATCATTTTACTATGCCTGCCACCATCCATTTGTCTTTTGCACCATATCTTCATAACCTGTCACCTTGAAACTACCTTTGTATGTCACCTACCGACCAACT',\n",
" 'ACAATTCACAGTAGTACTTAGAATCTTCACTCATTAGCCCATCTATGGTGTCTTTACCATCAGTCATACATTTAATATGCTGCCAAGTGTCACAGCTATC',\n",
" 'ACCAACTAATAAGACATATTATTTCTAAACGAAAGCAAGCGCGGACCAGATCCAGATGCTTGCTTCAAGAGATCAACGAGTTAAAGAGTTACCAAGGCAA',\n",
" 'AGGGCCTAAAATTTCCCTCTCCAAATTACAACTCGGGGACCGAAGGTATTTGATTTCCAATTTGAGGTTTTGTCGCTTCACTTGCCGGTACTCAAGTGAC',\n",
" 'TAATTTTGTTCTGTTGTAGTTAGACGTAGTGGAAAACTTTAAGTCTACTGAGTCTTGAGACCTTATCACCCTTTGAAGGTTTCTTGCAAATGAGCGTGGT',\n",
" 'GGCGTCAACGTTAGTGTTCAACAAACTGCGTAAAAAAATTTAGACGGGAAACCGAACTTATTGATAAACGTTAGTAAAAAATGTGCATAATGGATTTCAC',\n",
" 'TTATCTGCTTCTTCCGATGATTCGAACTGTAATTGCAAACTACTTACAATATCAGTGCGAACCATTTGAAGAATAAGATCAGAGTAAAGACCGCACGGAA',\n",
" 'TTATTACGACGATTTGGTTCGGTTTGCTTTATAGGATTCGGCTGTTCTGTGTAGTCATATAGCTTCAATAACGATTTTGAGAATATTAGCTTTATGAATT',\n",
" 'GGCTTCATTACCACCACCAGTTCCGGTGGAGACGAAACAACCAGCGACCTTATCATGCAAAGCACCCTTAGCCTATAACCCACCGGTACGGTCCCAGAAA',\n",
" 'CATCTTCTTCAATGTCTTCGTAATCCAGTTTTCTCCTTTTGTTTTTACAGAACCATCTATTCAAAGGTACCCGTACTAAATCATTTCCGGAATCAATAAC',\n",
" 'CAATGAAGTTGGTTGACAACGGTGAACTCTATTTCCTGGTCTGAATTTGCAAAATTTTAAAACGTGCTTTAACATCAGGTAATGGAAAATAAAATTCTCT',\n",
" 'ATTATAAGATCTATATCTTTTACTATTTGGACAAGTTGGCTAATTTGATAGGCAATTGAATAAGAAGGAACTCTGTATCTCAACACATCACATGTCTACT',\n",
" 'CAGTCAAGCCATTGAAAATTACACAAAAGGCAATTAACAGTCCGATCATAAGACCGTCATCGTCTAATGGAGTTCCAACAACCTCAAGAAAACCTTCAGG',\n",
" 'CTGCATTTCCAAACAACTCGACTCTTCGAAGGCACTTTTCAAAGTTCTTTTCATCTTTCCATCACTGTACTTGTTCGCTATCGGTCTCTCGCCAATATTT',\n",
" 'ACCAATTTACTTTCGGTGTAAGGAGAACTAAACTCATCCATAATAAACTGCATATTTTGAAAAAGACAGATTATTGAGGTATCACTACTTTCAAGGTCAG',\n",
" 'ATTGGCAAAAATGGGTAAGACACAAAAGAAGAATAGTAAGGGACGTTTAGATAGATACTATTATCTAGCAAAGGAGAAAGGTTATCGTGCTCGTTCATCC',\n",
" 'GATGCTGAAGAAAACCATGACGACGAAGAAGATGAAAATGAAGAGGAAGATAGACAAGTAGATCAAGCTTCAAAAAACAAAGAATCGAAACGTAAAGCAC',\n",
" 'CCTTGCTCAGCTCTGGCCATTTCTACAATATCAAAATTTGATAAATTGCTGGACAGCTTAACTTACGATATTGTAGAAATGGCCAGAGCTGAGCAAGGCG',\n",
" 'GAGCCCATTCGGGTCTTGTAATTGGAATGAGTACAATGTAAATACCTTAACAAGGAACAATTGGAGGGCAAGTCTGGTGCCAGGGAGGTAGTGACAATAA',\n",
" 'GCATGGTGTAGGATATATTAAAAACCGCTCGAAATTATAGAGGTGAAATTACAAGTTACTTGCGGTTCGATAAGCAAACGCATTTACGCTTATACTTTGG',\n",
" 'TTTGTTATACTACTATTTGAAGCTGGTAAAGTTGGATCAAAAAACTTAATGTTACTATTCAAACCACTTTTGTAAAGGTTGAGAACGCAATCTTTCAATT',\n",
" 'TGATCCTGCTGTAGCGTACCGTTTGCTAAGCCTTCATAGTAAAGTTCCTCGTGAAACTGGTTTCTCAACACAATGATGATGATGGCCACTGGAGTGCATA',\n",
" 'ACAATTGAAGAACAAAGAGGTTGCTGCCTTGGTTATTCACGGTAAGTTACCTTTGTACGCTTTGGAGAAAAAATTAGGTGATACTATGAGAGTGGTTGCG',\n",
" 'CAAAAAACTATTATCTAGAGATAAGTGTGATAACTGTAGTATGTTTTCGCCAAAATTTAGAAAGGAAGATTTTTGTAAAACCATCCTTTCTAAATTTTGG',\n",
" 'TGGACAGGTTTTCATAGTGTCATTTACTTGACGCGGATGTAGCAGGTACAGTATTAGTACTTCCCTCCTTGCGCGAGTGAAGAGACTTATCATTCGATAC',\n",
" 'AAAGTTTGCAAAAATCAGCCAAAACTGTGCTCGTATTCTGGTGGTCATTAGACACTCGCAATATTATTACACCACATCGCGTTCCTCTGAGCTGCTATAA',\n",
" 'AGAATAAAGAAGAAAGGAAAACAGAAGAAGAATTGGAAAGGCAATTTCAGAAAATGATGCAAGAATCCATAGACGCAAGGAAAAGCGAAAAGGTTTTTGA',\n",
" 'TAGTCGATGCCCCGTCTACTAAACCTATTTGTACGGAACGAGCTTATCATCAGGAACTATATCTCAACATTTGAGGTTTACAGATAGTGTTAAAGAATGG',\n",
" 'AACGAATTCACCTGATTGCAGCTGTAAAAGCAGTAAAATCAATCAAACCAATACGGACAACCTTACGATACGATGAGGCAATCACCTATAATAAAGATAT',\n",
" 'TGCCCGGACAGTTTGCTTCATGGAGCAGTTTTTTCCGTACTATCAGAGCGGCAAACATGAGTGCTTGTATAAGTTTAGAGAATTGAGAAAAGCTCATTTC',\n",
" 'GACAGGTGCCCCGAGTAACCCAGTTCCTCACTATTTTTTACTGCGGAAGCGGAAGCGGAAAATACAGAAACGCGCGGGAACATACAAAACATACAAAATA',\n",
" 'CCGAACATCTTTCCAAACTTAACGTATTATAATGAAAAATTAGAATGTATTTCATTAGGTTCTACAAAACTTTCCAGGCCTTTTGATTCTTTTGGAAAGC',\n",
" 'TAAAATTACAATGCTCTTGTTTTCACATTTTTCGAATATGTTTCGTAATTGTTACGCGTTCCATTTGAGAAGCAATTGTGAGTTAATCACTGTCAAAAGG',\n",
" 'AAAACGTCTCAACCAAGCACGCTATGTACACACATCTATCCTTCAAACTTATGGGGGTGTTTTAAAAAGCACCTGACTTTTTCAATTGAACATAGCAGGC',\n",
" 'GAGTAGGGTAAGTTTGAGAGTGGTATATACTGTGGCATATGCACACGGATGCTACAGTATATAGATCGGAAGAGCGTCGTGTAGGGAAAGAGTGTAGATC',\n",
" 'GAACGTACAGGTAATGTGGACTTGATTACTGTTGCTATGAATATGTATACCCAAGATGTTTCTCCTAATTTGGATTTCTCTGACTTGACCTCTGTCCTAG',\n",
" 'GTGGCGAATTGACGGATAGTGAAAGCCCAACCGTGCAAACCGGAACCGAAGGCAACGGTACCTCTGGCTGGGTAAACTTGGACATCACCCCAAACTTCAT',\n",
" 'TATGCATATGATCCAATATCAAAGGAAATGATAGCATTGAAGGATGAGACTAATCCAATTGAGGAGTGGCAGCATATAGAACAGCTAAAGGGTAATGCTG',\n",
" 'CCACACCCACATATCCACACTCATACATACACCCACACCCACACACCATACATATACCCACACCCACACCTACACCCACACACTACACCACACTACCCTA',\n",
" 'GACAGCAATAACCAGCGACTGTTTGAAGAAAAGATGACTGTTAGTAAAATACCCATATGGCTAGATTGTGATCCTGGTCATGATGATGCCATAGCCATTT',\n",
" 'CATGCGATGACTTAACTAAGGATTTACTGGTGTTGGATCAAATTTAATCTCTGCATGTATAGGCTATTCAATAATCATGAGGCGTTAAAGGATAGTTTAA',\n",
" 'CAAGGCATTCCCCCAAGTTTGAATTCTTTGAAATAGATTGCTATTAGCTAGTAATCCACCAAATCCTTCACTGCTCACCAATGGAATCGCAAGATGCCCA',\n",
" 'AGTAGGGAATGGTATAAATATTATCGTACGAAAAAATTTATACCATTCCCTACTGAAGTATGTAATTCAAAATATATATATGTATATGTATATGTACATA',\n",
" 'TCAACTTTTTTCATGTTTAAAGATGGTGATCCCATATCCTATGTTTTTCCTGGATACTTCACAACAGAAATGAGAAATATTGATGCCATTATGGATTGGG',\n",
" 'CGTAATATACTAGTGTTTCTTTGGTGTCGTAAGCTGATGAGTAACCAATAAATTCGTCTAACTTCAAAGTAACGACATGAAACTGGTTGCCTTCACTTTC',\n",
" 'GCTAGAGCACCACGAGGTAAGACACCGGCATTCATAGTTTTCAAATATTCCACTTTTTCGCTCTCTTCTCTTAGCACCGAAAACATTCTTGAAACTTTAG',\n",
" 'ATTGAAGAACCACAATTTTTTATCATCGACTTTGGCATTTCCCTTCGTCAAACCATTCAAATTAAAAATGGTTTCCAATTCCTCCATTGAAAAACACTCA',\n",
" 'GAATGAGTTGAAACCATGTTATAGTAATTCAAATGCCTATTTTTTATATCACTTCTATGTGTACTCTTCTTTAGTTTTTCTAAAGATCATCTCTTAACAT',\n",
" 'ATTTCATCAAGCATTGTACAGGAAATAAAAGTGACACCAATTGACCAGATAATTAAACCGAACGATATGCTCAAAAGCTTCCCAGGTCCTTTGGGTAGTG',\n",
" 'GTGTGAAGAGTAGGCGGAATTCAATAACGATTGGAATTCCGCCTACTCTTCACACAATCCCCATGATTCTGTCTAAGGATAACGACGTCGGGAAAGTCAT',\n",
" 'ATCCGGTGCCGTAAATGCAAAACAAATACCATCTATGTCTTCCACACCATCATTTTACTATGCTTGCCACCATCCATTTGTCTTTTGCACCATATCTTCA',\n",
" 'TAGAACCAAACGTCCTATTCTATTATTCCATGCTAATATATTCGAGCAATACGCCTGCTTTGAACACTCTAATTTTTTCAAAGTAAAAGTCCTGGTTCGC',\n",
" 'TTCTTTCCCCGTTGATTCTGCCAAGCCCGTTCCCTTGGCTATGGTTTCGCTAGATAGTAGATAGGGACAGTGGGAATCTCGTTAATCCATTCATACGCGT',\n",
" 'ATACCAGTATCCTTTTATATGTTAATACACCGGTGCAATAACTTCTCTTAAAATCCTTCAACCTAGTTTTAGCTTTTTTTTGTTTTTGTTGGTGTGATTA',\n",
" 'GACCAAGGAGTCTAACTGCTATGCTCTTACTCAAATCCATCCGAAGACATCAGGATCGGTCGATTGTGCACCTCTTGCGAGGCCCCAACCTACGTTCACT',\n",
" 'GTGAATTACATAAATGGGGTGTGTTTGTACAGCACCAAAGCTCAAGACATAACTCTGGGCTTCCTTCATCCGCCAATTCTTCGAGAATTAGCGGGTCGTT',\n",
" 'GTCAGCGTCAAATGCTGTTTTTTCAATCAATTTTTCTTTGCCGGTTTGTTGGTCAATGTATTTGGTGATCAGTTTTGGCTGACCCATTGCATTCACATTA',\n",
" 'TCATAAGGATGGAAACCAACAACAGCAGCAACAGCAGCAACAAGAAGAAAACGGCGAACAAAAATCTGTGTTTCCATCCTTATGAGATTTGAATAATCCA',\n",
" 'GCACCCAAGACCTTTCCGCCAAGTGCACCGTTGCTAGACTGCTATGGTTCAGCGACGCCACAAGGACGCCTTATTCGTATCCATCTATATTGTGTGGAGC',\n",
" 'CATTCATTAAGCAATCCATACGTCCATTCATTCATTCAGTTTTCTCTTTGTCTATTACTGTCATTTTATTTTCAAATCCAATTGTCCTTTAGGACACTAA',\n",
" 'AAAATTTTAATTCCTGTTGGAATTGCAATAATCATTAGTGCAGATAGGAAATATGTTCTAAGATCTGCATCTAATCCTACAATATATATATGATGTGATC',\n",
" 'TTCCAAGAACTTTAATTTACTCTTGAAAGTATCAGAATCGAAATAGCAACCCTTTAACCATTGCTGGTTTGAGCTTGTTAAAGAGTTAGCATGCAAAATT',\n",
" 'GCCAATTCTTTCCTGAAAGAAGCAGCTTGCTGGAAAGTTGGCACACCACCTGTCATCAACAGCCATAACATTGATTCTGGCAGGAAATTATCGCCATCAA',\n",
" 'TGAGCGGTGAGAACAAGGGAAATCTCGTAAGAATAGGAAACAACCTAACCTCATTTACTAAGAGAACTCGCAGGAAAAGATATCTTTTTGAGGCACAATT',\n",
" 'GTGAAGCAGAAGACAAGCACGCCCGCTACGTCTGACCAAGGCCGTCTACAACAAGGCACGCAAGTAGTCCACCTAGCAAAGCAAGCCCCACCAAGCAGTC',\n",
" 'AGTTCTGAGAAAGAAAAGGTAAAACACGCAATGCCTATCAATCAACCGTCGGGACAGATTAAGTTAACTAATGTTTCATTAGTGAGATTAAAAAAGGCTC',\n",
" 'TAGCAATGGAACTTCTGTGATTTCCTCCTCAGTAATTTCTTCTTTAGACACTTCTTCTTTAGTCATTTCTTCCTCAGTCACTTCTTCTCTAGTCACTTCT',\n",
" 'CACTACACTCCTATTAATAACGGTAACTATTCTATGTTTTCTTACTCCTATGTCTATTCATCTTTCATCTGACTACCTAATACTATGCAAATATGTAAAA',\n",
" 'GTGGGCTTTTCAACAATGATCAAGTTCTAAATCACGCCATTGAATTCACGGGTGACTCTTTGAATGCATTGCCTATCGATCACAGACTCACTATTGCTAC',\n",
" 'CGTATCATTGGGTATAGTCGGGTGTTGTTCTACAAACGTTTCTAGCTGTTTATCATCAAATCCGGTCAATTGCTTCTGTAAGATAGCAATTTCCTTACCA',\n",
" 'TAAGGCCTCGTTAAAGGACAAGGACTTGAGCGGAAGTGTATCGTACAGTAGACGGAGTATACTAGTATAGTCTATAGTCCGTGGAATTCTAAGTGCCAGC',\n",
" 'GTAGGCATTGAAGAGTACCTACAGGAAGATGGTTCAAAGAACGAGGATATCAAAGTAAATATTGTCCAAGATGAGCCTGTTAATGTCGAAAAAATGGATA',\n",
" 'CAAGTGCATTTATTGAATGTTTTTGGGAATGCAAGTAGCAATACTATTGTAAAAGTACTACTATTTCTCTGTATCATACGCTTTTACTACTATTCCTCAC',\n",
" 'AACTATGCTCGGCCACCGTTCACACATGCCGAAGATTTGAGTGTCACATCAACAGGCTTTCGGACGACTGAATACCAACAGCATCAAGCTGATTTGGCAT',\n",
" 'TGTCGCACATATAGCATGAGCATACGCTCTAGAGGATTGTACCATTGTCACTACTAGATATACATATAAACAAATAAGAAGCATCGATACATAACAACAA',\n",
" 'TTTGAAGTTTTTATTTTTAACACCACCTCTTTTCATGGTACCATTTGCACGCTCCAAACTTGCATAGTGACCTTTTTCGATTAATGGACCAAAGTAAACA',\n",
" 'AGTGGGTTATCCTGAGGGAAAGATTCACCAAAGTGGAAGCGCTCGGTTCGCTGATCTCATTGCTGGGCGTGGTGTTAATTGTAAGGCCTTCATTTTTATT',\n",
" 'AGTCTCAACTATCTACACAAATACCTAGTTCTTTCGGTCCTCTTCAATGTCACTGACAACTTCAGAAACCTCTTCACTCAGGTTGTCAGTGACATTGAAG',\n",
" 'AAAAAGGCTAAATGTCAGGGATGAGATTTTGGACTTAGACTTAAAATTTCACCACATTAACCTGAATGTTTCTCTAAAAAATTGGTTACTTGGCAGGGGA',\n",
" 'TTAGCATTCTTGTTACTTATTAATAAAACAGGTTCTCCGCGAATATTTCTTGCCCTCTCAGCATCAGAAAGTAAAGGATATTGTGCACGAACAGCTGTTA',\n",
" 'CGCTTTACCTCATAAAACTGATACGAGTTTCTGCTATCCTGAGGGAAACTCGTATCAGTTTTATGAGGTAAAGCGAATGATTAGAGGTTCCGGGGTCGAA',\n",
" 'ATTGATGTTCTCTATGGTGTAACGAATCGATTTGCCTGCCTCCTTCAAAATGTTGAAGAAGTTATTTTGGAAGAATGAGCTTAACTTGTTTTCAGAACCG',\n",
" 'GAATTAAGTCAACAACTTTTGCGGAACTTTCAGGCTCATCTATTTCAAAGGTTAAATCTAAAGACTTGATCTCGTCAGTGGTCCTCAATAATTTGATCAA',\n",
" 'GGTGATAATCATGGGCGCCAGTTCTGGTTCGCCCGGACATTGGAAAACAGAATCTTGGTTGTCGGGCTCTTGCTGCGGAGTGAAGATCCCGTAGTTGGCA',\n",
" 'AATGGCTCAAATACAAAATACCGACTTTGCAGATTAGATGGATCCCTAAAACGAAGTGCATAGTTGCGGTATTTTGTATTTGAGCCATTTAAAATAGTCT',\n",
" 'GATCAATACTACCAGTTTCTCCATGGACCGGTGTTTCAATGTAATAATAATCGTCATCTTCAAAAAAGATATGGTTGAACATGAAGCTAAACTGGTGTTT',\n",
" 'AGGCGGGGACGGACACTTAGTTTGCGTCGGGATTGGAAGCGATATAATCGACCGTTTCACCAACACTTCTCAACTCATCAGCCACTTTGTCAGGGATTTC',\n",
" 'GCCATTTTCGTCAGCAACTTTGCTCATTAGTTCATCTACCTTATCGTTGTCCACCAGCATGGCATCCGAATTCACACCCATATCTTCATATACGTTAACA',\n",
" 'CTGTAGTAGAAAAGTCTTTGCGGTCATGATTCTTTTTTTGTTTTTTTTTTCCACACATATTTATTGGTCTCCTAGTACATCAAAGAGCATTTTAATGGGT',\n",
" 'TTTGGGCAACACTACCATATAAGTTATTTACGTCTTTGGACAATATAAGATGGTCTTTGGGTGCACATAATATTTGCTTTCAAAATAAATTTCTGGCCAC',\n",
" 'GAAGGAACTCCAGATCAACCAAATAATAACCGAAAAGATGATAAACTGCACAAAAAAAGAGGCGATTCAGATGAGGACTTAAGCCCTATATGGCATTGTG',\n",
" 'CGGTGCATTTTTCGAAAGAACGCGAGACAAACAGGACAATTAAAGTTAGTTTTTCGAGTTAGCGTGTTTGAATACTGCAAGATACAAGATAAATAGAGTA',\n",
" 'CGTGGAAATATTAAAGGTATTCTGTCCGTTGACCAGTAATCTTAGATATTTTAGGCCCTGAATTCCGGAGGCAACGATAGCAGCAGACGTGGCAATATTA',\n",
" 'CGGGTCCTTTCATCTCGGATTGTCCGTATTGGTTTGATTGATTTTACTGCTTTTGCAGCTGCAATCAGGTGAATTCGTTTCTTCGATCTCGGAGGTTCTA',\n",
" 'TTTGTTATCTCTGTGGTAGAAATAGGGCACCATGTGGTATACTCTGTTGTGGCACCGCTAACAGTAACGGTAGCCGTGGAAACAATTGCAGAGGAGATGG',\n",
" 'CAGATCGTTACTTTTTCAAAGTGAAAAATATTGTTGTATTGCAGGATGCGCCATCTAATACTTCAGTTCAATCTATTTCCGCGATCATACTTTTATTGTT',\n",
" 'AAAATGATAAAAGGGAAATTAGAAAGACCAAATAATTTGCCTTTTGGATGGATTTACTTCGCCTTTTAGAACAAAAAACAAATCCTACCATTGGTTGATC',\n",
" 'CTGAAGACAACGATTATATTCTTGGACCATACTTCAGATCGGAAGAGCGTCGTGTAGGGAAAGAGTGTAGATCTCGGTGGTCGCCGTATCATTAAAAAAA',\n",
" 'CGCGGTTGAGAAAATTATCAACAGACAGATTATTGCATTGTTCACAGTTTTAATCGTGCTAATTTTAATTTCTTCAATTGGTAATGTTATTATGTCTACT',\n",
" 'CCAATCGAAAACCTATTCAAATACAGGGCTGTTAAGGCATCTCACAGTAAGAATATCAACTCCACTTTGCCGGCCTGGAATGGGTCTAACTCTAGCAATG',\n",
" 'GCAGCGTAAAAGGATGAGGCTACTGGGAAGAAGAAAGAAGAAAAGTGCAAGATGAATAGCCAGTGCAATATATACATGTATACTTAACAGATATGGAATG',\n",
" 'CGAGGAGAACCAGGATTCTGTTCGATACTCAGCCGCTTCGTGGATATTCTCTTGGATACTTTAAACATGGACCTACACTTAGCCTGCGCTTAGCCTACAA',\n",
" 'ACCAAAGTCAATCGATCAATGCATCTGAAAAAATTCACCTTCACCAAAGTAGATCAATTGACGTCATTTACTGAAACGAATGTGCAGGGTTTACAAGTCA',\n",
" 'TCTCTCTCCACGCTGGATAACACGGAATACTCAAACAATAATGGCAATTTCTTGTTCACCTTGAATTCACAGAATCTGTTATCTGTTCATAGGCAGGAGG',\n",
" 'CATCGAAAGTGATGGTAGCCCCTTTTGATACAGCCAATTTGATAATGCTAGGGACCATCGCTAAAAGATCTGGCGTTTCAATTGAGGTATGTAACTGTTG',\n",
" 'AACCATTCTGAGTCATTCTAGTGACCGTTCGGCCGCTGAAAAAAGAAATATATAATGTTTTTAATGCTGATTTCCTATAATAAGCCAGGTTTTAAAAAAA',\n",
" 'CATGTTTTAACCACCATGTTTGAAAACACGGTGGTTAAAACATGAATAATCTTGTCCAGTTTCAGCTGCTGTAGTATCCTTGCCAATTCCTCTGGACCTT',\n",
" 'GGTCGTGTAATGGGTACACCCATTGGAATCTGGTTTTCTCATCTGTAAACGATATAAAGTAAGAAGGTGCACTTTTCGGTAAGTGATGTACAGGACCAAA',\n",
" 'CCCTTCCTTGATAATGTTGACACGTCGCACTCTCATGGGTTGTTCTTCCTTGATTCTTTGTTTTTGAAGTGGAGGTCGCACATGAATAGACTACAAAAAC',\n",
" 'GAAGGATCATATACGTGTAAATATTTATCCCATCTGATAGCCCAAGAAGTCGCTGATTCACTGAATTTAACGGAATAAGTAAAATAAACTTCATTATCAT',\n",
" 'AATGCCTCGTCATCTAATTAGTGACGCGCATGAATGGATTAACGAGATTCCCACTGTCCCTATCTACTATCTAGCGAAACCACAGCCAAGGGAACGGGCT',\n",
" 'ATTTTCTAGGGAAAGTGGTGAAAGTGAAACTGTAGTCAACAAGTATTTAGATTTCAATCAAAATGATGCGTTCAAACTTTATCTAATGATCGACTCTGAA',\n",
" 'ACTTCTGTTGTTTTGGGATGAGCACCCAACACACATAAATGTAAAGGTGTCAATGATTCGGCATCTCCGAACGCGGAAACGTCATCAATAGGGATTTCAT',\n",
" 'GGGAGTTTTGGCGCCAGTGAAATACCACTACCTTTATAGTTTCTTTACTTATTCAATGAAGCGGAGCTGGAATTCATTTTCCACGTTCTAGCATTCAAGG',\n",
" 'GGGTGTAAAAGCTAAGAAGGGGGAGAAAAACTGGCTTTTAACGAATATTTTGTGTAACTGCAAGAACTACTAGGGTTTGATGTACCTTGCTCATTAAACC',\n",
" 'ATTACGTTATGACTTAGGCGGAAAACCTTTGCTATATGCCGAAACAAAAGTCGATATTTTAAACACTGACCATTTCTGTTCGCTGTATCAGAGGAGTAAA',\n",
" 'ATTACTGTCTGCTAATAACATGATTTTTACGCCCATTTTTTCACCATCTACAGTCATGATTCCACCTTTCTTGATATTTATTTCATGATTGAAATGGTCC',\n",
" 'AACTTACTGTGCGTGGAAGAGCAATCAATTACAGGATTTTAAACATGAAATTTTTTATTTTCCTCGTTCATTTTCGTTGCGGGAAACTTCCAGAAGTATA',\n",
" 'AGGCAGATACGCAGAGATAAGCAGAGTACGCACTAGTGAACTTTTTTAGCACGCACATTACGCACTTTATATATATGCTATAAGATGCAGCAGCGGACGC',\n",
" 'GCATCATGATTTCAGAAAACCCACCGAAGGTTCCCGTCATCTTTATATCGTCTGCTTGCGTATAATCTAGGCCACTTTTTTAGTAGAATTGAGAACGAAA',\n",
" 'CGCTCCTTAACATCATACAACCGAGTACTTGACATGGAGATAGTAGGCAAGTAAACCAAAGTCCTTTTTTCAAAAGTAGAAAACTTGAGCACTTATTTCC',\n",
" 'CCACCCGCATAGTTGACAGTAACATCACATTTGTCTTTATTCAGATGAGCAGCTTCTTCTATAGAGTCACCACCAGATATGCTACAGTACTCATAGAGCC',\n",
" 'GGCCTCGTCAAACGGTGGAGAGAGTCGCTAGGTGATCGTCAGATCTGCCTAGTCTCTATACAGCGTGTTTAATTGACATGGGTTGATGCGTATTGAGAGA',\n",
" 'CAACTCCACATTATATTCTTCAGTACCGTCCATACCTTCAATGATGTCCATATCTTCACTATCACTTTGACTACCGTCGGCTGCTCCAAACCTTAACTTT',\n",
" 'CACACCGGTAATTGAAAAAGAACTGGATTCAGTACATGTCCAACAAATGCAAATGCTAACGTTTTGTATTTGCATTTGTTGGACATGTACTGAATACAGA',\n",
" 'GCTGGAAAATGAAAACACTCTATCCTACAGAATAAGAAGTGAAGTAACAACCATGGATTTTGCTGACTTGAAGTTGGGCATCAAAGTTCCCAAGATTTTT',\n",
" 'AGAGGAGGAAGAAATGGAAAACAAATTTGCTCCTCCTCCAAAGCAATCAGAACCAACTATTATCTCACCAAAACCCTTCTCCAAGCCACAAGAACCTGTG',\n",
" 'CTCAAACTTCCATCGGCTTGAAACCGATAGTTCCTCTAAGAAGTGGATAACCAGCAAAAGCTAGCACCATTATTTAGAAGGTTAAGGGCTCGTTCTTTTT',\n",
" 'GCGCGCGATTGTATAACTGGGACGTTCAGAGAAGGCAAGACTTGAAGCAGGCTCAAGAAGGGACTAAAAACCTCAAGATATAATGTGTCTGTAAATTTAA',\n",
" 'GTTCAATGATCGTGTTTTCGGTGCAGCATATTTTGTTGTCAGTCCTTACACTTTAACATTTTGAGATCTAGTATCCAGCTTGTAAACAATAACATTCCCT',\n",
" 'AAGGTTATGAATTGGATCCCGAGTCATGTTTGGCAAACGTTTCATATGCTAGAGCCTTGAATAGTGAACATCAAATGGAACTTGTTGAACAATTGGGTGA',\n",
" 'GGTGTTATTTTGGGGCCTACTATATTTGGTCAAATTCCAAACTATACAAACACAATTTTCCCTACATCATCGATCCTGGGGCTAAATTTAGTGGCGAATT',\n",
" 'GTTTAAACTTTTTTTTTTCAGTTGCGAATATCTCTTAGTGCAAATTGGAAAACAAGAGAGCTCACACAACACTAAATACGTTGGGTAACGATACATAGCC',\n",
" 'ATTTTTATACTGAATTTAAGAGCGGGCAGCGCCGTTACGGCCCAATATATGCAATTCCCAACCGCCGATATTCATGTTGTATTTTATTATGGCGTGCTTT',\n",
" 'CAACCAAATCTATGCTATTGAAAAGCCAGAAGTCTTCAGATCTGCCGAAGACAACGTAGTTACCACCGGCAGATCTGAAGACTTCTGGCTTTTCAATAGC',\n",
" 'AGATTTTTTCTGGTGGGTAACAAGATTGACCTTTATAAGGAAAGGCAGGTAACCCATTATGATGTGGTGCAAATGGTTCAGGAAATGCAACTGAAACATG',\n",
" 'CAAAATTTCATACCAAAAAACTTTTCACAACCGAAACCAAAACCAACGGATATCATACATTACACTACCACCATTCAAACTTTACTACTATCCTCCCTTC',\n",
" 'TGTCACCATAGACATACTTGACAGTAAAGTATAGATCTGGAGAGCGGCGTCTAGGGAAAGAGGGCAGATCTCGGTGGTCGCCGTATCATTACCAAAAACA',\n",
" 'TAATGGCATTCATATCAATAACAAGGTCGCATGTCAATTAATTATGAGAGGTCTATCTGGCGTGTGTAGCATAAAAATTTACATTCGCCAGATCGGAAGA',\n",
" 'ATTGGCTTTAAGGGTCGGGGAGGGAGGGGCTTGGGTAAGCCCACCCAGCAAACCACAAGCACGCCCGCCGCCTCTGACCCAGGCCCTCCCCACCCCACCC',\n",
" 'TTGCCTGAAATGCACACCTTCACCAGGCGCACACTGGTTCAAAAATAGTAAACAAAATCATGCGAAAATACAATAAAAGACGTTAACTTGATAGAATGAA',\n",
" 'ATATGCAAGGAACTGACCTAAGCCCTAAGTTTACCTTTGTTTCTCTATTTGAATCAATAGATTTAATCCTATACGTCTCTGGATCTACAGTGCAAAAACT',\n",
" 'CTGGGCCTCTGGTAACGTGAATAATCCTTGTATCCACCTGCCGACTCTGCTTGCTGCTACAAGGATTATTCACGTTACCAGAGGCCCAGGGAAGTATCTC',\n",
" 'CGTGCTGTTCTGCTTACTGCCCCGTTTCACATATGACAGTTTTCAAAAATTTTTCTTCCCAATCAATATCACTTAAATCATCTTCTTCATCTTGGTAAAA',\n",
" 'TTAAGCATATCGTGCGAGATGACGTTTACTCCTGACGCGCTTAATGAGAAGCGGTTAAGTGAAGAGTAATAGTGCTCGCAATTTGACAGAAATGACACCA',\n",
" 'GATACTGAAGTGGCAATTCACTTTGTTCTTAGCGTCTATGGCCGGTGTAGGTGCATTTACCTTCTACGAACTTTATTTCACTTCAGATTATGTCAAGGGC',\n",
" 'AGGCACCACACCCCTGATGTCTCCGGTTACTACTATTAATGCTAAGGCGAACATATTAACAACTACAGAAACTTCCACGGTCGAAACAACTATAACAACA',\n",
" 'TGCGTCAGCAGCAGCAGACCAGCGTGGATGTGGAGCTGTTGCACACGATGCTAGCGCGAGCCGCTGCGCTTGTCCATGCCGACACTATAGCATACATGTG',\n",
" 'TAATAAATAGCCGCCCACATCGGAATATCGAATAAAAGCTAGGCGTTGTTGGTAATATCATACTCTCTACAACAACTGGTAAAGAACTTCTTTTTTTGAA',\n",
" 'CAGGGTCTTACGAGGCCATGATATTAGGTAATCCCATCGGTAAGACAATGGGAGAAGCTGGAACGGATATGGCTTCTTCAAAAGTTGGCGGAGGTGGACA',\n",
" 'CGGGCCAACCGTTAGTTCTTTCCCTTGAGAGGAGATATGGGTCCACTTGGAGGCGATCTGCCAAAGAAAGGACTTTGTTCACTAAAAGAATGACCATCAT',\n",
" 'CAGGGACTTAATACAATCAAGTGATATCCATTCCTAACATGGGTGTTCCTAAAATATCAACCATTCGCGGTGATATGAAAGTCCAGTACAAGATCGTTGT',\n",
" 'ATGGAGGTAAAAACCACTTGTGCTAAGTTAGCTTTAACGTTGGTGGCAGCATTCTTCTTGCCAGAAGATGAAGATGAAGCTGAAGAAGAAGAAGAAGAAC',\n",
" 'GTAACGGAAATAGTAATAAATCATTGTTTTCCTCCCTTCATGTCCTACGATGGACACTTTGAATGAAAACAATGATTTATTACTATTTCCGTTACATACA',\n",
" 'ATCGCGCCTGCCAAAATCGGAGCAATGAACCATGACGCAATAATTTGAGAAACACCATTCCAACCTCAAACGACACCGTTAGCTTCACTGGCTGCAATCC',\n",
" 'TCGGATTTCCGAACTCTATAAAAAAGAGATAACAGAGCAGTGGTGAACTTTATATATTTACTCCTTGGTTATCTTATTATCAAATTACAACTCTTTATTA',\n",
" 'GGTAGCGATTTGTTCAGTACTCTCAGAAGAAGAAGCAACTTTGGAAGAAGACTTGGTGACCGAAGATTCGGAAATCAGAGTAGTAGTGGAAGCAATTGTA',\n",
" 'CTGCCCTCTAGCAACTCCTATGCTTTATGCGTTCTAAACTGTATGACATCTTTTGAATAGCCTTCCTCTTCCTCAAAGACCACCGAAGCCCCGTAGCAAC',\n",
" 'TCATTCGGGGCGAAGAGGAATATTACTTGAGCAGTCTTCAGGCTGTTCTTAACTTCATTATGAACTTGACTGCACGTTCCAAAATTACCACCAGAAATTT',\n",
" 'CCACCTTCCTCATCGTTAGGTTGTTGCTCTTGCTGAAGCAGTACTTGTTGCTGCTGTTGCAAAAAATGTTGTTGGTATTGCTGGAGTTGTTCCTGTTGTT',\n",
" 'ATTGGTAAGGATCCAGACGATTTTGGTGATGGATATACAAGGTTTCATGAAGATCTGTCACCTAGACTTCCGTTGGAATATACAACAGACATTCCCGCCG',\n",
" 'CACTTTAGACAAATTGGGTTACGACTCAAAGAAGCAGGACGGCGATTTCGGTAATGTTGCACTAAGAAAGGCAATGTTACGAACGATTGACTACATCAGA',\n",
" 'CCGCTGTGTACAAATGAGGCAAAAGAGGTAAAATGTTTGAGAAAAGATTCCTTTCTTCAGCAATCCTTTTCTTGCATTAAATACATGTTCCTTGAGAAAA',\n",
" 'AAGATCTCTATCAGCATAGAAATATTCATCAAAATCGAGATATCCTAGTTAATTGGTTGGTTAAAATCCATAATAAATTCGGCTTATTACCGGAGACTTT',\n",
" 'TTTGGATTTCCAAACCAACAAGAGACTTTGTGATGAAATCGCCACTATCCAATCCAAGAGATTGAGAAACAAGATTGCTGGTTACACCACCCATTTGATG',\n",
" 'CCCTGATTTTCAATCATTTCAGCTACTTTATTGGGCTGGAGCGTCTTTAAAGAGTCTACTAGGTTAACCATAGGTTTCAACCTATCATTAACCTCAATAA',\n",
" 'GGCTCGAGCCCTGGGAGGAGTTATCTTTTCTTCTTAACAGTTTATCACCCCGGAATTGGTTTATCCGGAGATGGGGTCTTATGGCTGGGAGAGGGCTGCA',\n",
" 'TTGGAGAGGCAGAAAGCTTTCTGCCTTATATACTTTTTTTTTTCCCGTCGGGTTTGGGGACCATCCCTTTAAATTTAGCGCCCAAAACACCGGCGGACGG',\n",
" 'GCAATTAAGCAGACAAATCACTCCACCAACTAAGAACGGCCATGCACCACTACCCACAAAATCAAGAAAGAGCTCTCAATCTGTCAATCCTTATTGTGTC',\n",
" 'ACCGGATGTACCTATTAACCAGTAAGCAACATTCTTTGAGGTCTTCAAACGTGATTCTATAGGGTTTGATTCTGAAGCAACATGTGGTTTAAAAACAGGG',\n",
" 'GACCCTCTTGATGAAGTGTCCCTCTGATGATTCCTTACTTGGTGGGTCATGCGCGATGAAAGATGTAGATAACGCCAATTTGGTTCTGCACTTCTTACAT',\n",
" 'ACTTTTTGTCTGTCTCTTGGGGCAATGCTTCCATCTAGCCTCATATAGGTTACGGAGGGCATATACTTTGTGAATTACTTGTTTAAAAAGTATATGCCCC',\n",
" 'TTTCAACCTTTTCAGAAATCGCAGGCAACATGATCGTATTTCAGGGGTTTTCTTATCCAGTAGAGTGGCGGAGGGACAAAATCAATCACAAGCATGTTTT',\n",
" 'ATGAATATCAATCACAATTCCATAGCTCAAATCAGTTCTTCTTTGTCCATGTTATTATCGAAATACAAGAAGAACTGATTTGAGCTATGGAATTGTGATT',\n",
" 'GTTTTATCTACAGAGTTCCGAAACATTGTTAAGTGCCTGTTCTTATATAATTAAACTGTACTTTCTGTAAAAGTCAATTTGTGGCTGGCGCATCCACGGT',\n",
" 'GTGGAGGTTGCTGCTGGTTGGCTAGCTAAGGAGGCGTGAAGATCAGTGGTTTCGCTGAGGGCACTCCTTGATTTATCTGAGATATGCATTGAAGATTGGC',\n",
" 'TTAATTTTCCAGGACCCTTCGCTGTTTAATTCCGATCGGCCTGAAACAGCGAAGGGTCCTGGAAAATTAAGATAATAAAACGAAATGAAACCCAGCAACA',\n",
" 'GTGGCACCTCTAGCCTCAAATCCCGAGGGACTAAAGGATCGATAGGCCACACTTTCATGGTTTGTATTCACACTGAAAATCAAAATCAAGGGGGTTTTTA',\n",
" 'CGTTCTTATTTACATTTTCGTGTACCGTTACAGTAGATGAAGCAGTTCTATCTTTCTCTTTTCCCCCCTCAGGGATGACAGAAGTTAGTTTGTCATCATT',\n",
" 'TACCCTGTTTGCTACGTTTACTTTTGTTTATCATCTTCAGTTACGTCCAAATTTACGGTTTCTTTGCTATCGTTATTGTCGTCACAATTGTTTGTCTTAT',\n",
" 'CGGAATAACCCTGTTTGTCACCGGAGTAGTAGTTTCTGAAGCAACTATGTTATAACTTTTTGGATCCAGGGTTCTCGAGGGTGCACTTGAACCTTTTAGA',\n",
" 'GGTGGCAGGCATAGTAAAATGATGGTGTGGAAGACATAGATGGTATTTTGTTTTGCATTTACGGCACCGGATGCGGGCGATAATGACTGGAAGAGATTTA',\n",
" 'ACAATTAACGATCAACTTAGAACTGGTACGGACAAGGGGAATCTGACTGTCTAATTAAAACATAGCATTGCGATGGTCAGAAAGTGATGTTGACGCAATG',\n",
" 'ACGCTTTGAAGTTCCTATTCCGAAGTTCCTATTCTCTAGAAAGTATAGGAACTTCAGAGCGCTTTTGAAAACCAAAAGCGCTCTGAAGACGCACTTTCAA',\n",
" 'GTGGCAGAATGATGAAGTTGGAGAAGAGAGCAATAAGTCCAGTGTGATAATAACCATTCTGAACAGCTCCTTTTGGATCCATTATTTGTAACCCATTGTT',\n",
" 'GGCGTCATGTTGTTCCAAAGTTTGGACCAATTGAGCAACGGTAGATCTTTTTTGTCCAACGGGTCAACAATAATAGAGAACTTAATGGCGTCATGTTGTT',\n",
" 'AATCACTGCCACGATACACATCACCGTGGACAACGATGGCCGGAAATGCTTCGGGTGTTTCATTGACTCCTGAATGGGGATAAGTAGGCCTATATCTTCA',\n",
" 'TCCTTTGATATTGGATCATACCCTAGAAGTATTACGTGATTTTCTGCCCCTTACCCTTGTTCCCACGAAAAAAAGGAGAGTAGCAACAAGGGTAAGGGGC',\n",
" 'AACCTTCACCATAGTTATGTTCCGCTATTACGGTCCATGGTTTACCGTCTGATTTCCATTTCATTATCAAACCAGGAATATCATATTCAGTTCCGTCAAG',\n",
" 'GTTGAAAAAATCCATGGTTCAAGGCCGATTGTATGCTATGGTCAATTCAAAGAAACTTTGTTGGAATTAGCTCATACTTTATATTCAGACCTCAGGTTTT',\n",
" 'TTCAANTTNCTGCCCTNTCANNTTTCGANNNNNNNNNNNNGNCCTACCANNNNNNCNNCGGNNAACGGGGAATAAGGGTTCGATTTCGGGGAGGGAGCCT',\n",
" 'AGTATGTTTCAAAAACCTCAATCTGTCCATTGAATGCCTTATAAAACAGCTATAGATTGCATAGAAGAGTTAGTTACTCAATGCTTTTTGTCAAAGCTTA',\n",
" 'CCAAGTCCTCCACTTTTCGTATCTTATTTTTTTTGAAGCATAGGGGACGAGACTGTCTGTAATTTATGGCGAAGTATGACAAGAAAGATTCAAACTTTGT',\n",
" 'CCTGGGCCATGTATAGACTTGGGGGATTCGTAAGAACCGTGAGGGAAGTTCATACGGACAATGTTCAAACCAGCCTTTCTCAAAGCAACCAAGGTTTCTG',\n",
" 'CAAAAGCGATGCACTGCAATTGAAGTTTAGCAGATTTTCATTGGATGATTCAAAAACTATTTTAGTTGATGTTTCGTATAAAGCCTTGTTTAACGTTCGT',\n",
" 'CGTAAGGTGCCGAGTGGGTCATTAAAAAAACATCACTTGATTCCTAGTCGGCATAGTTTATGGTTAAGACTACGACGGTATCTGATCATCTTCGATCCCC',\n",
" 'CTCTCGGGATGCATTTTTGTAGAACAAAAAAGAAGTATAGATTCTTCGTTGGTAAAATAGCGCTTTCGCGTTGCATTTCTGTTCTGTAAAAATGCAGCTC',\n",
" 'ACCTGGACAACTAGTTTAGTTCCGAGATTCTGCGCTTCCATTGAGTCTTATGACTGTTTCTCAGTTTTCATGTCATCTTTTGACGCCGCATGGGATAATG',\n",
" 'TGCATAAACCTATATAATTTCCCATTCCAATTTCAGTGCCTGAAATAATTTCAAGCCGTGAGTGCTGAGCTCCCCAAAACCGTCCAGCTCTTGCCAGCTT',\n",
" 'CTTTAATGACCTAGGAAATAAACAATGGTTGAAAATTTGTAAAGTGCAATCTGTTTACTAATCAGTTTTTGTCTTCATATTTTTGTGTCTTTTCTGCTGC',\n",
" 'GGATGATGGTTGGAAAATATTGTTTTGGTTTAGTATTTTTCTACCAATTCTACTAATTTTCTGGAGATTGTTATGGCCTGAAACGAAATACTTCACCAAG',\n",
" 'AACCGGTAAAGAATTTTTTACTGAAGATATATTTGGAACCATACATGGGCATGGTTCCAAATATATCTTCAGTAAAAAATTCTTTACCGGTTGGGTTGTT',\n",
" 'GTTAGAGAGAACGATAAGAGGAAATTTGAAAAGGAAGAATTATTGCCGGAAAGTCAATTGAAGGAATGGTTGGAGAAAGACGACGAAAAGAAACAAGAAT',\n",
" 'GAGTGTAAGCTGGCCTGTTTTCTTTACCGTCACCTACGCAGTGCGAGCCAAGAAAAAAATAAAATGATACAAAGAAAAAAAAAAGTTGAGCAATGTACTA',\n",
" 'AAGCGGAAAATACGGAAACGCGCGAGAACATACAAAACATACAAAATATACCTTTCTCACACAAGAAATATATGCTACTTGCAAAATATCATACCAAAAA',\n",
" 'TATTCCATTCGTCCTTCTTGAAGTTCCATTTATACAGTGATGCATGTGGTGTGTGAAAAAGTAGTTGCTTTATTTTTTCACACACCGCATGCATCACTGT',\n",
" 'AGGCTCGTGATGTTTTCCAATCTCTAGTTAGCGATTCGATACGTGATATACTGGAAAAGGAAGAGACAAAGCAGCGTCCTGCTGATTTAATATCAAGTGT',\n",
" 'CAGGATAGTTCCGCCGATGAAGAAGACAATAAAAACGTACCCAAGAAGGGTAGAATCGGCAAGGTACAGAAGGACATTAAGATGGGTAAGATAACAATTG',\n",
" 'CAGTCATACCCCAAATCCGTTCCTAAACTAATTGCTTTCGAATCAGTATATTCTATAACCAGTTCAGTAGCCGACATAGAATATACTGATTCGAAAGCCA',\n",
" 'CTTTCATTTTCGTCCTGAGGGGTGAAAATTCCATGACAAACGTCTCTGGTGCTTCAGAAAAGGCTTTAATAAAACCCCAAGTATTTTTAGACCTGTAAAT',\n",
" 'TCGATTATACACCTACTTTCATCGTACACCATAGGTTGGAAGTGCTGCATAATACATTGCTTAATACAAGCAAGCAGTCTCTCGCCATTCATATTTCAGT',\n",
" 'AATGGTGAGGTCCGAAAGCAATCCGTGCTCTTGCTCATCAGCACCGTTATTACGACGTATAAAATCAAATACTTCATTTATTTGTTTTGAAACGTGCCGC',\n",
" 'ACCAGGTATTTCAATCATGCAACGGACAAATAATGTCAAAAGCACTGAAAGATAATTCGTCCATCCAAAATTTCATCAAAGAAGTTGCATGGAGAGATTT',\n",
" 'CTACTGTCTCCGCAGGCATCCGTGCATGGCATCCCGCGGAAGGGACCCTGAAAATATATGAAGTAGCTGTAGAACATGCCTTACGGAAGAACAGAAATAC',\n",
" 'ACAACCCTCGCTACTTATCAGGTTGGCTGGGCTTACCTGATAAGTAGCGAGGGTTGGATTGTTGTTGTTGGCTCCAATGTTGCCACCAAAGTGAGGAACA',\n",
" 'GATTCTCAGCAAAAAAACTTTAAATTTGCTAGTGAAGCCGTCGGAAACGATACTTTGGAGCATGGTAAGGATACCATCAAAAAAAATAGGATTGAAATGG',\n",
" 'GTGGAGTTTATTAAAGAACGATTACACAACCTAGAAGAACATGACTCTTCATGGAAAATCCCAAATCCTACTTACTCATTCAAGAAAGCCTTCTTGAAAA',\n",
" 'TTATTCCCTGTACATTTAGATTATCTAAGTCCATAACATCCGTATTTTCTCTTGAGAAACCATTTACACCATCTTGTAGAGAGTTTTGTGGCGTTTCACT',\n",
" 'TGGACCTGATGACAATAGCGAGACGAATCCTATCTTGTTGACTAGGAGGATGGCGTCCATATATTTTGATAATGCTGGTATATCGAAACAGATTCATGTT',\n",
" 'CTCAAACTTTAAATATGTAAGAAGTCCTTGTTACTTAATTGAACGTGGACATTTGAATGAAGAGCTTTTAGTGGGCCATTTTTGGTAAGCAGAACTGGCG',\n",
" 'ATAAATGATTTAGCTCCCTCATACTGATTGAAGAACAGTATGAGGGAGCTAAATCATTTATACACGGAAAAATTAGTGAAGGATTTTTTGGTGGGGTCTC',\n",
" 'TAAAATATGTGTATATAAGAATAGACAAAAGGAAGAATATATAAAAGGAAAAAAACATTTCGAGTGACTTGTAATCAAAACTCGAAAGTATGTATTGTTA',\n",
" 'ACCATACCATAGCACTCTTTGAGTTTCCTCTAATCAGGTTCCACCAAACAGATACCCCGGTGTTTCACGGAATGGTACGTTTGATATCGCTGATTTGAGA',\n",
" 'CGCGATTTATTCTTGTGCGTAGCCGCAATTATAAAGGTCCGGAATATCTCTCCGACTATTGTCATCGTCGAATTTCTTCTGGAAGGGACGGCAGTAACAA',\n",
" 'GTCTGAAAATAATTGAGAATGAAGAAGAGAAGATCAAGCGTGTCAAAATGCAACAAGAGGCTTTACGTCGGAAGTTGTCTGAGTATAAGAATCCATTCTT',\n",
" 'CGCACAATCAAATCAGCGCCATAGAGCTCGACCAAGAATTGCTCAATACGCTGATTTGATTGTGCTAGAGTGTGTATAAAGGAAGATTATTTTGAAAATT',\n",
" 'AAACTCCACAGTGTGTTGTATTAAAACCGTTTCAATACAACAAGATCGGAAGAGCGTCGTGTAGGGAAAGAGTGTAGATCTCGGTGGTCGCCGTATCATT',\n",
" 'GTTGGGTTCAAAGGAAATAACGGTGTGGTGGTTTTAAGAGATAGGGAATCCAAGGAACCTGTAGCACTAATTGAAACTGTTAGGCAAATGAAAGATGTTA',\n",
" 'TACAGCAAGAGCGTCTGAATATCTCCTTTGCTCACTTTGGTGTCTGGTGTCTTTATACCTCTCGTATGCCATTCTCGACTCTTTGATGGTTCGATGGATC',\n",
" 'ATGGGCAGGCGATTTCTCTGAAATTTCTGTTTTTTCGTTGACTCCTATCTGCATTCTTATCTTGATCTTTTCATCATCTGAACCTCCAGTAACTCTATAC',\n",
" 'CTCTCCGTCTGTTATCTCCACATCCTACCAGATTCCCGTCATTTGTCAGCATCACGCTGTGGTTCCTACCGTACGCTATCTTCCTGACTATTGCTCCATC',\n",
" 'ATTTCTTTTGCTTGGAAATGAAAGCATGTTTGTAAATTCTGTTGTAGGGACTTAGTGATCGTGTTCAAATAATTGCCAAATGGAGAAGGGTTTGCAGCGG',\n",
" 'TGTAATATGCTGCTCTTCATAATGTAAGCTTATCTTTATCGAATCGTGTGAAAAACTACTATTGCGATAAACCTTTACGGTTCCCTGAGATTGAATTAGT',\n",
" 'AGAGAGTACTTGCTCGAAGAATTAGGTGAAGCACCTAATTCTTCGAGCAGATCGGAAGAGCGTCGTGTAGGGAAAGAGTGTAGATCTCGGGGGTCGCCGT',\n",
" 'TCAATTAATCATTTGATGGAAGATGCTGCTTGCGGAAGTATCACGTTGTCAATTGTACCAGTGGGTTAAACATGGTGTTGTCTTAAGTGATACCGGTGAC',\n",
" 'TCCATTGTTGATAAAGGCTATAATATTAGGTATACAGAATATACTAGAAGTTCTCCTCGAGGATATAGGAATCTTCAAAATGGAATCTATATTTCTACAT',\n",
" 'CTATTATACGCGAGCATACCTCAAACTTCACGAGCCAAGATTGTTTATGAAATCAGGACAAGAGCTAACCTTCGATATTCAAACTAGTACGTTGAAGTTA',\n",
" 'GGCCCGATGATTGATTATCCACATCAACTTTTGGTGAAATTCGAGAGAAAATAAATGGGAAGTGAACGAGCAATAGGCAATCAACAAAAAAAAAAAAGGG',\n",
" 'CGTTGCCACAACTTGCATCACTGTCGTTTTCCTCCTTCTTCAGCATGTTTATTCTTTCTGTCCTTTCCCGTTTCTCTATCTCTAAGGGAGTTTCTTCCGC',\n",
" 'TACGGAACACATCAACTTGTAACGACAACAATGCAAAATACCGGGAGACATATCACTTCTTTTCGCTTAGAATGATTTACAATGGCATACACTTAGAAAA',\n",
" 'TTTAATTATATTTAATTTAAATAAATAATATATCGAATTAATATCTCTTTCGACCGGATTATTTAAGATCGGAAGAGCGTCGTGTAGGGAAAGAGTGTAG',\n",
" 'CTAGCGTAACATTTTGCGGTTTACTGAATGCCCTGGATGGTGTCACATCTTCTGAAGAAACTATTACATTCATGACTACCAATCATCCTGAAAAGCTAGA',\n",
" 'AAGCCTTTGAAAATGTGTAGAGATGTTGGTAAAGTTACAGGTTGTTTTGACATTCCTCCATAAGTGAGCATCAAAGCATTATTTTCCAACTTACGTGCTA',\n",
" 'GAGGACGCCATTTTGAAGATGCATCAGTCAGATGATTCTAGTGATAGCGATTCTAGCGATAGTGATTCCAATTCGGGCGCTAGCGATGAGGATGCATTTC',\n",
" 'TAGGGGTCATTGAGGTCACTTTTGGAGTTGATAGTGTGCTGCTACTTGAGGATACTGGCACCAAGGTGGAAGAGGGTGAAGAAGTACGGCTATCGACTGT',\n",
" 'AGAGGGGCTCAGTTTGGTAAGGCTCAACAAACCAAAAATACCTACAAGGATAGGTCTCTAACTAACAAAAAGACTACTGATGAGCAACCAAAAATCCAGA',\n",
" 'CCTCTTCTGCGTCACTAATGGGGTCATCCTTAGACGGATCAGTGTCAACTCCAGGGAGTAACGCTTCAAACACTACATCTGGTGGCAAGTTGAAAATACA',\n",
" 'AAAGCGATAAAAAGTATAAAGCAGGTGAAAGTAACACTGCCAACTACACTTGTGATTACCACAGTAGTTGGCAGTGTTACTTTCACCTGCTTTATACTTT',\n",
" 'AGACCCGAATGGGGCCTGTATCGTTATTTATTGTCACTACCTCCCTGAATTAGGATTGGGTAATTTGCGCGCCTGCTGCCTTCCTTGGATGTGGCCAGGT',\n",
" 'AACAACGATGCATCTGTAATTCGGCTATACTTGTCTAGAAAAACATTACGTAATTTAGGGGCTAAATTGACTATTCTTTCTATAGTTTTATCTGTAATAT',\n",
" 'ATCCTTCAATGCTATCATTTCCTTTGATATTGGATCATATGCATAGTACCGAGAAACTAGTGCGAAGTAGTGATCAGGTATTGCTGTTATTTGATGAGTA',\n",
" 'CTGGGATTCGTATCTCAGGTACTGAAAACGGTGGTGGGTTGTAGTGGTCATTGTCGATAGGCTGATGAGGTCCTTCCCTTTTCAGTACCTGAGATACGAA',\n",
" 'CTGCGACGTAAGTCAAGGATGCTGGCATAATGGTTATATGCCGCCCGTCTTGAAACACGGACCAAGGAGTCTAACGTCTATGCGAGTGTTTGGGTGTAAA',\n",
" 'CAAGAAGAAGGCACTATTGAAACTAGACAACCCGATTCCAAAAGGTCTGTTGGATACTTTGCCTCGTAGGAACTCCCCTGAGTTTACGGAAATGAGATAT',\n",
" 'CGAAGGTCACCAAGAGAAAGAGGCTCGGTATTCTTCGTCACTATAAATTTTGAAAAGGGATCACTACTATGTATAGTGGTTGATGGTCGAATTACCAGTT',\n",
" 'TTACGCGCCTTTAAAAAAGTTGGTCTTAATGTAAACATGAACCATAGCACACAATTTAAGACATCAGCTGTCAAATGACCATAAAATTGTCCTGCCAGCT',\n",
" 'AATAGATTGTTGATTTATTTTGATTAAGCTGTTGTTTGTTGGGGAAGAGACTCACTTTGCTGGTGTCCGACTTGTTTATGTTCTTCAACAGCACCTTCTT',\n",
" 'TCTATCTTCGTGCAGTAAATGAACTTCATCAATAATTAGTAATTTGACCTTTGAAACCAAATCGTTGTCGCCGTTTGCTTTACGGGTGACAACGTCTCAT',\n",
" 'GCACAGCGTAATATGAGGAATTTTGTTTTGACAACACAACCCTTTAATTTTCTCATTGTTTTCATCAATTATGCATCCATCTTTATCTTTAGACAGTTCC',\n",
" 'AGAAGGTCAATTAAGATTATTAGATACTGATACTTCTATAGTTGTATCTGTAGATACACATATTAGATTCGTTGTAACAGCTGCTGATGTTATTCATGAT',\n",
" 'TTACTTTTTCCATCTTCAAACATCGTTAAATTATTAGGTCTAAAAAACTCGCTCAAATCCATTCTTGGTAAGCTACTTTCAGTGGTATAATCAATACCAT',\n",
" 'CCCAAAGTTGTCCTCTCCAAATTACAACTCGGGCATCGAAGGTACCAGATTTCAAATTTGAGCTTTTGCCGCTTTACTCGCCGTTACTAAGGCAATCCCG',\n",
" 'ACGGACCAAGGAGTCTAACGTCTATGCGAGTGTTTGGGTGTAAAACCCATACGCGTAATGAAAGTGAACGTAGGTTGGGGCCTCGCAAGAGGTGCACAAT',\n",
" 'CCAAGGCCGTCTACAATAAGGCATGCAAGTAGTTCGTCTAGCAGAGTAAGTCCCACCAAGTAGTCCACAAGCACGCCCGCTGCGTCTGACCCAGGCCCTC',\n",
" 'GCCCTTAGACGTTCTGGGCCGCACGCGCGCTACACTGACGGAGCCAGCGAGTCTAACCTTGGCCGAGAGGTCTTGGTAATCTTGTGAAACTCCGTCGTGC',\n",
" 'GCGGCGGATAAATCTGAAGAGTTCGTACCGACAATAATCACGTCAGAAACGGCAAACTTGTCAAGATCCTTGAAATAACGAGAAGTCATAGCACGAGAGA',\n",
" 'GTAATAACAATGGTGGCATCATGCACATCTTTAGGATCTAGCAAAGAATCACCGGTTAACTCTACAACTTTATCTCCAGTCACTGATGTTATTTTCTTTC',\n",
" 'CCGACTAGTTTGTGTGTTAGAGTCATCTCCGTTCAACCAATCACTCCATTCATTGTCACTATCACTACTACCGCTACTGTTGGTTGACTTTACATCGTCT',\n",
" 'TGAGAGCCAAGAACAAGAACAAGAACAAGAACAACAAACTCCGGGCACATCTCTAGCCCCAACTGTAGCATTGGCCGTTTTAATGAGTTTCTTGCCGAAA',\n",
" 'GAGCGTGTATTCCGGCACCTTAACTCTACGTTCGGTGCCGGAATACACGCTCATCAGACACCACAAAAGGTGTTAGTTCATCTAGACAGCCGGACGGTGG',\n",
" 'GGGCGTACTATTTGTAGTTCTAACGATATGATTGATTTGATCTCACAGGATAGAGTTAATTATGGACTTGAAAACATCAAAACTACACGTTTGGGTGGTA',\n",
" 'TACAACAACAAGTCAGGAAATTACTTCTTCATTACCACCTGTTACCAGTGCGACAGCAAGTCAGGAAATTACTTCATCATTACCACCATACCTCCACCTA',\n",
" 'GTTTTTTGGTATGATATATGCTACTTGCAAAATATCATACCAAAAAACTTTTCACAACCGAAACCAAAACCAACGGATATCATACATTACACTACCACCA',\n",
" 'AAAACTATACCCTGACACTGCAAGAGGGTCTTCGTGGCAGAAGCCAACTCATTGTCCATATTTTGACAGATCTCGCTTTGAGATTCAACGATAGTAACCC',\n",
" 'GATCTGTTAGAAATTACTAAGCGAATGGGGAGAATTTCCGTTGCTTTGATGCCACCTTTACTATTTCTAACGTTGAGGCCATCACCGTTATCTCACACGT',\n",
" 'TACTGGTTGATGATACTATTAGTTTCAAAAATCAAGCTCTGCAACGAATTGACCATATCATCAACCAGTATTGACGCGCCGGTGGTAAGACTCAAACAGA',\n",
" 'AACCGGGCCCATTTTTAAAGGGATCTGATTGGCCAGGGCCGGCCGCAACTGCATCACCCGGACGACCAATCAGCGCGGAGAAACAGGCCTAGAAATGAAA',\n",
" 'GGGGGATGTTGGAAGAACAAGAATAGGACATTAAATCAACTTACTCTTCCAACATCCCTCATTGGGACGGTTAATTAGTTCAAAAAAATGTTAAAAAATA',\n",
" 'AAGGTAGTAGAGGGTGTTTCGGAATCCGGTGGCATTATCCTATTTCTGGGGACAAGACAAGGCCAGAAAAGAGCGCTTGAGGAAGCTGCTAATACGACAT',\n",
" 'TAGTAGAGATAACAGGTACAATAATTAAGAAATAAGCGAAGTAGATAAATGTAGCGATTTGTCTCATTAAGACATAAGGTACTTCTACATGGCATGCTCC',\n",
" 'CAAAGATTAGCATTATCTAAGAGCTTCCCTTTGCATTGTTGCATGTTTATCAAAGCAACTATTTCTTAGCTTTCTGTGTGATGTTAGTGATTCTGCACTG',\n",
" 'AGCAGGTATTGTACTTTATCACACCAGTTATACTACCTTCTGTGTTATTGATCTATTGCAGTTTTATAGAGTGATCTGTCCAAAGATTCTTTTCAAGAAT',\n",
" 'GAGAGCTCTTTCTTGATTTTGTGGGTGGTGGTGCATGGCCGTTCTTAGTTGGTGGAGTGATTTGTCTGCTTAATTGCGATAACGAACGAGACCTTAACCT',\n",
" 'CGGACACAAAATCAGAGGCAACTTGAATGTCAAGAGCACCAGTGGCAAAGTAGTCCAAAAAGAATAGAGGTTCAGCACCTTGTACCACCAAATCGTTAAC',\n",
" 'CCTGATCAGTTTGTGCCACATAGCGAATCAATTAAAGAAAAACCCAATACGTTTGAACAAGATAAAGAAGGCGAGCAAACGGACGAAAAAGAGGATGAAG',\n",
" 'TGCAGGCTTTTATTCATGTTTGATCTTAAGACGATTCTCGACCATCCTAATATCCCGTGGAAATTAATCATTTCTGGGTTCTCGATTGCCCAATTTTCTT',\n",
" 'ATATTATTTATGATAACTTTCAGACCGCACGAAAATATCCCACCACGTAGTAAGTCATAAAAAAAAAAGAATATTATTTAATTAACACTTTAAGAATTTT',\n",
" 'AAGATTCTATCTTCGCGATGTAGTAAAACTAGCTAGACCGAGAAAGAGACTAGAAATGCAAAAGGCACTTCTAGTCTCTTTCTCGGTCTAGCTAGTTTTA',\n",
" 'TATCAGTACCAAATGCACTCGCATCATTATGCACGGCACTTGTCTCAGCGGTCTATACTCTGTGCCATTTACCCATAACTCTCACGATTATCCACATTTT',\n",
" 'ACAGTGAGGGGCCTTATCTTAATGATGAGAAACCTTGCCGCTGAAAACCAGGAAATACCCCAAAAGAGATGAAAGTAAGATATGGAAACTACTTATTAGT',\n",
" 'GCCGGATCGATTTACTTTGCAAAGTTGATATTGTTACTGATTTGTTCATGTTCTTATGGGGGCAGTAGCCGTCTCTCCTAGATCGTTACAAAAATCATGA',\n",
" 'TGAAGAAGGTTGCGATGGCGTTACTGATTTATACGTGGGGATCTACGATGATCTTGTTAGCACTAATTTCACAGACAGGATAGCTGCGTGGGAGAATATT',\n",
" 'TATGGTAGAAAGATCAAAAATGCGCAGAATAACAGGGAATTGGAAGATTTCGACAAATATTTCGAAAAGGAAGCAGAAAATGATGAAGATTCAGAAGTTA',\n",
" 'GTGACATCATTAGGTGATGCATCTACTGATTTTTCTTCCTCTGTAGATTGATCAGTGCCTTCACGCTCTTCTTCCTGATCAGTTTTTTTTTCTTCCTCAC',\n",
" 'ATATAATGTACACCGATTCGGTTTCGGAATCATCTTTGTCGTACTATTTATCAAAGTACCATAACAAACCTTGTTGTTCAATCGATTTGAATCATTACAG',\n",
" 'GGGGTGGTATAGTCCGCATTGGGATATTATCTAATATGTGTATTTCCGTCACCGAAAAAGGCAGAAAAAGGGAAACTGAAGGGAGGATAGTAGTAAAGTT',\n",
" 'AGATAGTTAAACGTATACGTTTGTATAGATAAAAGTTCTCAAAAACTTCCTTCCTTTTTTTTTCTTTTGAGTTTACTTATTTAAATAAGAACATTCTGTT',\n",
" 'CATAGAACTCGCGTATCTGTTCGGTTATACAGCCTTCCTTAATTGGTGGTAATTCACCCTTACGATTCCTTGTCGCCCAACTGTTTTTTCTAGATAATAG',\n",
" 'CAGTCTCGAAAATGATCGAGGATTTCAGGATGAAATTATGTATGAAATTAAGATGAACGAATTTGTCAAGCCATTAAATATCATCAAAGTAAATTTGATC',\n",
" 'CCTCAATAACTTTATTTGAATCGATCTTCACGGAAGTGCGGTCATTCTACGAAGACGAAAAGTCTGGCCTAATCAAAGTGGTAAAATTCAGAACTGGTGC',\n",
" 'TCCTCCCTATCTGCTTTTGTTTATTACAGTTGAAGGCTACTTGTGCCGTTCGTGTGAAAAAATACTCGATGAAAAAAAAAAAAAAACATGAATACCATGA',\n",
" 'ACATTTTTCACTACCCTAAACTCAATTCTTCCTTCAATTCGGATATAGATACTTCTTCTTTCTGTTTTTTGGCTTTCCTTTCTTCCTTTAGTATATTTTC',\n",
" 'ATTTATAGTCTTGAACCTATTTTTATTTCTTTTCAATTCTGAATACAGTCTATTCCTCATTCTTAGATCCCATAATTTTACCCCACCCTCCATGTCACCA',\n",
" 'GAGAACGGTAGCAGCGATGAGGATCTAAAGTCATTGAATGTACGCGACGACATGAAACCTTCTGATAACATCAGTACTAATACTAATATTCATGAGCCTC',\n",
" 'TTTTTTGTCTTCTGCTGTATAAGCTTGCTATCATTAAAAGTCGTATGTGGCATTTTGAATTTTGCCATCTCTTAAATACAAAAAATAGTGTAAATGGTAC',\n",
" 'TTAATGTAAGTATACTGCATCTTTTAAATATGATGCTGTTAAAATAGCCCAGATATATCCCTGAATGATACCAATAGCGAATTCTAACATCATAATGGCT',\n",
" 'AATAATCCTCAGGACGACGATTCGCAAAGCAAAATGATGTCTTCTCAAATATCATCTCTCATACCACATTGTATCACTAGTATAACGCTAGCCTTAGTTG',\n",
" 'TGGGTGATGCTGGTATTAAATCTGCCATTCAAGGCTCTAATGTTCCTAACCCTGATGAGGCCGTCCCTAGGTTTGTTTCTGGTGCTATGGCTAAAACTGG',\n",
" 'CCCACTAAAAGCTCTTCATTCAAATGTCCACGTTCAATTAAGTAACAAGGACTTCTTACATATTTAAAGTTTGAGAATAGGTCAAGGTCATTTCGACCCC',\n",
" 'CCTAATTTGGATTTTTCTGACTTGACCTCTGTCCTAGATGTGGTTGAGCGTTGTAATAAGATCCCAGTATCGCAAAGAGCACCATACGGTGGTGACTTGG',\n",
" 'TTTTGTTGGTTTCTAGGACCATCGTAATGATTAATAGGGACGGTCGGGGGCATCAGTATTCAATTGTCAGAGGTGAAATTCTTGGATTTATTGAAGATTA',\n",
" 'CTTTTGTTCTACTGGAGATTTCTGTTCTCCATGAGTTCCCCTTAGGATATCTGCGTTATCGTTTAACAGATGTGCTGTCCCAGCCAAACTCACCACCTGA',\n",
" 'GGTGCATTTTTAAAATATGAAATGAAGATACCGCAGTACCAATTATTTTCGCAGTACAAATAATGCGCGGCCGGTGCATTTTTCGAAAGAACGCGAGACA',\n",
" 'GCCAGCTGGGACTGAGGACTGCGACGTAAGTCAAGGATACTGGCATAATGGTTATATGCCGCCCGTCTTGAAACACCGTTGGGTAGAAACCTTAAAAGTT',\n",
" 'GAGGCGACAACCAAGTGACCATCATAATAAAAAAATGAAAATGAAAACGAAAACAAAAACGAATAAACTTTTTGAAAGCGGACAAGATAGTTTTGATAAT',\n",
" 'GTTGGTGGTAATCTTCAAGCAACTGTAACAAAAGGTAGTGGTGGTTCCTATGAATCCCTACCTTTTGTTACAATTGCTTTAAAATTACCTCCAAGACCAA',\n",
" 'GTGATGGGGCAGCAAAAGGAAGTAAAACAGGCGAAGGAGAAGATGATGATTTGGCGGATGATGATTTCGAAGAAGATGAAGACGAAGAATGGATAATTGA',\n",
" 'TTGCGTCAACATCACTTTCTGACCATCGCAATGCTATATTTTAATTAGACAGTCAGATTCCCCTTGTCCGTACCAATTCTAAGTTGATCGTTAATTGTAG',\n",
" 'TTGGTAAATGTTTCAGAGTGTTAATTACAACCTTATACGTTGCTTCTCTGGTATTCACTAATGAGTTGTATCCCATGAGAGCCGGAATTTCCAGCCGCAG',\n",
" 'ACAAGCTTTATTTCCATTGATACGGCAATCTTTCAATGGCTCTAATCTGGAAAATATCAATTACGAAAAACTGATTTTGACTATAAATACATACAAAGGA',\n",
" 'CAGAGTTATTCGTTTCATCGTCAATGTCGTTATTGTCCAACTTGTACATTACGATAAAGATAGCGATGAGTGCCACTCTAAATGGTATCACAATGTGGAG',\n",
" 'GTAGGTGAAGAAGGTGCTGTAGCAGACTGATCGGCAGCAACAGTTTTAACATTTTGGTTATTGACCATCACCTTAGGTACAACGGGAGCGTTCGCTGTAA',\n",
" 'TGTGTTGCTCTGTATTGTCTTGACTATTTGCGTGTTCATTTAAAGAAAAACCTCAGTATGGATAGAGATACTAAATTAGCTTTTAGGCTGAGGGGCAGTC',\n",
" 'AGAGAGGTAGCTAGTGGGACTTCCAGTAGATAATTTTTCGTCTAATTGTTCTAAAGACAAGATGTTTGAGGGGGAAATTGTAGATTCGCCTACCCAAGTA',\n",
" 'CACTGCTGAGACCATAGAACTTTCTACTGCTACTGATATATCTGAGGAAAGTTGGGAGGGCACTGCTGAGACAGATCGGAAGAGCGTCGTGTAGGGAAAG',\n",
" 'ATCAAGATTGATAACGACTCAATTTTGGACGAGTTTAACGAGAAGAGTTGATCTTTATAATATTGCAGAAATTGCTAGAGACTCAAAAATAGATACGCCA',\n",
" 'CATCCCATATTCTGACTGAACCATTACTATGCCCAGTTAGTAAAGCAGATCTGGTCTCATGCCTTCTAATATTTCTGGTGGCAGAAATACCACCTTTTAA',\n",
" 'GCCTTAATTGAATGACTAGATGGGTGCTTGTTAACGAAGGCGTGCTGCTATTCATGAAGCTGTTGCATTGTACTGTACAGTAATGTTTCGAGCCGGATCA',\n",
" 'CACCCGATCCCTAGTCGGCATAGTTTATGGTTAAGACTACGACGGTATCTGATCATCTTCGATCCCCTAACTTTCGTTCTTGATTAATGAAAACGTCCTT',\n",
" 'AGGTGCATTCTGACGTTAGTTTAGATATTAAAGCCGGCAAATATCTACTGATTTTTCACCATTCATTCAAAGAACTGCACACGATAGAATTTTGCCGGCT',\n",
" 'GATTGCAGAGAACCATAAATGGTTCGGTAAACCACTACATTGCAGTTGAGTACGGCAGTCATCTAATAAGGTACGGTTTAGCCGTTCAGCTCTTCACGTG',\n",
" 'GAGATATAGGCAACTGAAGTTTAATTCTCTGGTACTAAGCAATTTTGCGCTCAATAGCTTGTTACATGTAATAGATTTTTATCAGATAAAGGATAGGGTT',\n",
" 'ATACGAACCCTTTCAATACCTACATACTGACATATTTGGTCCAGTTCACAACCTACCAAAAAGTGCACCATCCTATTTCATCTCATTTACTGATGAGACA',\n",
" 'GGGGGCTCATCTTTAATCAGTTTAATCATTTCCTAACGCGTCGCGTCTTTTCCTATTCCTGAGACTTTTTTTCTTTACGTTCCTAATAGTGAAATGTGAC',\n",
" 'CTTGAAAAGAAGCATTTCGGCGGGACCTACTTTAAATCTTGCCAAGAAGCCGAATAATCTGTCCTCAAATGAAAACACTAGATATTTTACTATCATGTAC',\n",
" 'ACAACATCGGAAATACCACTGTGGGTTTTGTAACTTCTCCTCAGTGGTATTTCCGATGTTGTGCAGTTAAGAGATGAGTTTCCGGATGAATTAATTGTTG',\n",
" 'AAATCGGCTTTTGCCTCTTCAGAATCGTCTTCTTCATCTATTTCGTCATTTTTGCTGTCTTTTAACGTCATCTAGGGCATCTATTTTTCTCCACAAATAG',\n",
" 'GGCCGGGAATGAAATCATCATCTCACATCCAGTCTACAGGGATCTTTTTCTTTACAAACTCTTATTCGCATAAACATTCATATTTTTGATTAGGTAATTG',\n",
" 'TAGAATTATCATTATATTATAATAAGTATCTCATTAATATCTAAACGATTACCTAATAATAGGATTACTTAATATGCTGAATATAATAAACAATAATTCG',\n",
" 'TATATTTCTTGTGTGAGAAAGGTATATTTTGTATGTTTTGTATGTTCCCGCGCGTTTCCGTATTTTCCGCTTCCGCTTCCGCAGTAAAAAATAGTGAGGA',\n",
" 'GCATGTTATGAAATGCATATAATCGTTACAATCCCGAACTCGTGCGTGGGCTATTCAGTATAACCCGAATGGTATTGTTAGATATGCTTTATAATGCTGG',\n",
" 'CTGTTAATTTCATAAAACACGTTTTAGTACCAGAAAATCGTGTTATAGCACCGTTTTAGCAGTGATTTTTAAAATTGTCCAAGGTGCCAATAAATACTGG',\n",
" 'AGTTAGTACCATTAGAAGATCCCTTGAATACCTTTAATGAGGGCGATGCAAAAGCATTCTATGACTCTTTAAAGGTATTCAAGGGATCTTCTAATGGTAC',\n",
" 'TTAGTATTTATTTCTCGAATTTTTTTGGCGTATTTCGTCATCTGAAAATAACATAATCAAAGAGAAATCGGACCTGATTTTGAAATTAAAACCTTACACA',\n",
" 'GATGGCGCTCAAGCGTGTTACCTATTCTCTACCGTCAGGGTTGATATGATGCCTTGACGAGTAGGTAGGCGTGGAGGTCAGTGATGAGGCCTAGACCGTA',\n",
" 'AAGCTTACTGATGATGATGTGTCTACTTTCAGGCGGGTCTGTAGTAAGGAGAATGACATTATAAAGCTGGCACTTAGAATTCCACGGACTATAGACTATA',\n",
" 'AGCGGGATAATTAGTCAGGTAAAAGGGGAACAGGAAAGAAGACGAGAATTGCATTTAAACAGCTCTTTACGAGGCTAAAATATCTACATCCTTATGCCGT',\n",
" 'CATGCAGGGCGCTGACAGTTAGTGCTGTCGTATCCTGTAAGTGTGACAGGATACGACAGCACTAACTGTCAGCGAATTTTGATTTGTTACTTTTGCTAGT',\n",
" 'TATATATATACATAAATAGGATTAAGATATAGTCCGAACAATATAGTGATATATTGATAATAGTTTTCAAATATGTAACTATTTAAACATTAAAAGCTCA',\n",
" 'AGTGAGTTGGAAGGAAGGACTGAAGTGAACCATGCTAATACAAATGAAGAAGTTCCCTCCAGGCGAACAAAAAGTAGAGACACAAATGCAAGAGGAGCAT',\n",
" 'AACAACTTTAATATACGCTATTGGAGCTGGAATTACCGCGGTTGCTGGCACCAGACTTGTCCTCCAATTGTTTCTCGTTAAGGTATTTACATTGTACTCA',\n",
" 'CGCGGGGAAAGGCAAATATAATAGGCCACCTGGCCGGTGTACAATAAAAAATCTCTAAAGAAGGGCATTCCAACTCTTCCTTTCGACATAAGAGTAAAAC',\n",
" 'TTTTTGCTAACATTGTCTAAATTATCATTTTCTGCAATATCGTCAGAATACTCAAGAAGTTCTTTCAAAGTAGAATAATCTTGTTCAGAAGAAAGAAATA',\n",
" 'TCGCAGCACCTGTTCTAACATATTCGTTGTTATCTTCCCTATTGGATGCCATGGATGCGGATAGCCCATTTGCGCAAGCATTGGTGTTAGGGGTAGCGTT',\n",
" 'ACCCGAAAAAAAGAAAGAAATCTCAGGACATCAGAAATGTACGAAGGCAAATGTATATCTCAATATTTAAGAAGGTAATTAAGCATTAAAAGGATTTTTT',\n",
" 'AAAGTTCAACAGGATTTGTTATTGCCACACGTAGAAAACGGTGACATTATTTTGATTGGTGCAACGACAGAAAATCCAAGTTTTCAGCTGAACAATGCTC',\n",
" 'TTCCGCTCAGGTCCTTGTCCTTTAACGAGGCCTTACTACTCTTTTGTTACTCTATTGATCCAGCTCAGCAAAGGGAGTGTGATCTAAGATTCTATCTTCG',\n",
" 'GCCTTTCTGGACTTAAAAATTCATACTTTTGCATTCTGTTAGATATGAATACTACACTCTATCAGAATGCAAAAGTATGAATTTTTAAGTCCAGAAAGGC',\n",
" 'GCACCTAAATAAGACTCTAATTTATAGTCCAAAAATGTGGAAACAAAACTGAAAGGATAGATCAATGTCTTACAGAGGACCTATTGGAAATTTTGGCGGT',\n",
" 'CCGTAGTTGAAAACGGCTTCAGCAACTTCGACTGGGTAGGTTTCAGTTGGGTGGGCGGTTTGGAACATGTAGTATTGGGCCAAGTGAGCTCTGATATCAG',\n",
" 'ACTGTGCACCATGGAAATTGAAAACGAAAGTATGTACCGACTACTTTATTTTTGCAGGCCGGAAATCAAGCGATGAATGAGACATTCTTCTGTTTTCTAT',\n",
" 'AATAAACTGATGAGGATGTGCTAACAGATGAGGTTAGTAAGGGTACCGATTCGTTGTTTTCTGATGCAGAGTCTGTTGTGGGAGATGTGGTAGCGTTATT',\n",
" 'TGTATTCTGGTGTTTTCCCTCCTTACACTGTTCCTGTGGGCGTTTTGTCTGGTCAGAAGAATGTTCAATGGTTCTTTGATGCCTGTGAGCCAACTCTGAT',\n",
" 'ATCTGAGGTTTTTGTTTGGCCTCGAACTTTTCCTGTCTGTGGATCTCCTGGTTTGGAAACAAGCTTTCCTCCATAGGCAAAATGGATACTACGGTACGAA',\n",
" 'TATAAAACAACCTTTAGACTTACGTTTGCTACTCTCATGGTCTCAATACTGCTGCCGACATTCTGTCCCACATACTAAATCTCTTCCCGTCATTATCGCT',\n",
" 'ATTACAGCCGTATGGGTCTACTTGATAGTAAAATTTGAAGAGCATTGGAAGCCTGTTGATGTAGAGGTCGAGTTTAGATGCAAGTTCAAGGAGCGAAAGG',\n",
" 'TGCCCAAAGAAAAAGTTGCAAAGATATGAAAACTCCACAGTGTGTTGTATTGAAACGGTTTTAATTGTCCTATAACAAAAGCACAGAAATCTCTCACCGT',\n",
" 'GAAATTCATTGTAGATTTTCAGTTTCATCACTTGTGGACTTTCTTATTCAAAATTCGCAAAATGGTCTTTCTCCTCCTAAAAGCTGATGAATTCAAATGG',\n",
" 'ATTCACACCAAATTGTACTGAGACACATATACCAACACCCAATAACGGTGTTAACGCACAGGGATAGTGGCAGAGTATTTGAACGTGAAAGATCTACGTC',\n",
" 'AGCAGCAAGAGATGCTACTTGTACATAGGGAACTCGTAAAACACGCTTGACATTTTTGACAATTTGCTCCAAAGAGATGTCTTTATTGAATTCTACGAAT',\n",
" 'TTCGGTCTTTTTGACTGCGAAGAACTATCGCAATTTCTTCCTTCGACAATATCCTTAATATATTCACTCTTTTCTGCAGGCGTTGTGTGAGAACGAATAT',\n",
" 'TGCTTCTCTTAACAATTTCAAAATTCAGGTTTCGGAAATTGTTAAGAGAAGCAACGAAAAAGCCTACAACAAGTATCACGATGAACTGAATTCCATTCTT',\n",
" 'GGCCGGACCTTGTTTCTGCATTGTGGGCATTTGATAAAGACGCTGATAAAGTAGAACTCCCCCTCCTGCTCTTGCTCGGATTTCTAGGCACATGTAAATA',\n",
" 'CAATCATTTCAATAAATAGCCGACATACATCCTAGATGCTATAAGCTGTACGTGCTTTTACCGTTAGATTCTTGGCTGTTTCAATGTCGTCCATTTTGTT',\n",
" 'GTGAACTTGAAACAGACGTAGATGGCTTCAAAGATGTGTACAGGATGACGCTTAGCCAAGAAAGGTTTAGATAGACGCACAAGACATCGCTGAAAGAAGA',\n",
" 'TTTACAACTTGATATTCTAATATGAATAATGAATAATGAATAATTTAATTAATTGTTTTGTTTAAATTTTGTTCGGTCTCGGTTATATTTGGAAGAAAAA',\n",
" 'GGGCGGCATATAACCATTATGCCAGCATCCTTGACTTACGTCACAGTCCTCAGTCCCAGCTGGCAGTATTCCCACAGGCTATAATACTTACCGAGGCAAG',\n",
" 'CGACGATGTTTTAGTGGAGTACGAATTAGTTAAAGATACTATCGACTTTGAAGCCATTGTCAAAGAACATTTTGATACCGCACTCCTCGCGAGCTTTTGC',\n",
" 'ATGGGACAGGACGATTTACTTTTTAGTATGGATGATGTTCTACAAGAGGTCTTCAGAATACAGCTCTATTTGAATAAGATGCTGCCGCACAACTCTCACA',\n",
" 'CTGAGCCATTGCTTGTTCCTGGTCCTGTTGGTACTGATACTGTAAGTATTCATCTTGGGAGATTGGATTACCGAAAATGTCGTAGTACGCTGGTTGTTGT',\n",
" 'AATCCATCCGAAGACATCAGGATCGGTCGATTGTGCACCTCTTGCGAGGTCCCAACCTACGTTCACTTTCATTACGCGTATGGGTTTTACACCCAAACAC',\n",
" 'GGGGCTTGATAGGATCCAGGAGATTATAGATACCCACGACTGGTTAAATTGTGAAGTTCAACCGGCTACTAAAATAAGAGAGGAAATTCCTAATGAAATG',\n",
" 'AAGCGGAACCTGAGGTGAAGCTGGTGACGGATGCAGCGAATGCAATAGAAGTAGTGGAAGCGGTGGAAGCAAGAAACGATTGAACCAGATACTGTAGTAG',\n",
" 'GTGAGATTTTGGGCCATTTTTTATAGCAAAGATTGAATAAGGCGCATTTTTCTTCAAAGCTTTATTGTACGATCTGACTAAGTTATCTTTTAATAATTGG',\n",
" 'TTGTCACCAGTCGAAGCCGATTCTCTGGAATGACTTGAGTTGTCTTGCATTCTAAATAAGGCCAACTAACCTAGTTGAATATACTGCTAATGAATGCTAA',\n",
" 'AGAAATGAAGAGGTCTTCTTTCATTTGTTCCTTTCTTTTCGCACTGCATGTCATCAATGAAGCATTCTTAATAATGTACATTATTCTATCATGATCGTTT',\n",
" 'GAAGAGGAATCTGAAACAGTTGTTGGTGGGTTTTTAGGAGATAGTGACATAAGCGGCTGCTCATTGCTCATTTGCCTATAAGTTTGATTTGCCAAATTAT',\n",
" 'GCTTAAACTCACATAGCTATCGCATTTTATCACAGAAGCTTTCATTTTTTTTAACTTTTACATGCCAATGGATTTCCAACCTACATCAAGTCATTCGAAC',\n",
" 'AGATTTTGATTGACATCATATGAGTTGGAATCCAATGAGTTTAAAGTTTCTTCGAAAATAATATTTAAGTGGTCCACTAATGTACCCCAATCTTTTTTAT',\n",
" 'CGGGAACATACAAAACATACAAAATATACCTTTCTCACACAAGAAATATATGCTACTTGCAAAATATCATACCAAAAAACTTTTCACAACCGAAAAAGGC',\n",
" 'AACGCATCTGAAAAGGCTTAACGACAAAATTCAAATTAAAATAGGCTCGACGATAGAGTACCAAAAGAAACCTGGAAAGTTGCATTCAGTGAAATGTCAA',\n",
" 'GGGGGTCAATGGCGGTAGATGATCTGGTGACTAAATCCAATGAAAAGAGCACAAACAGTTTCCATATAATTAGGAGCAGTCTACAATCAAGCAGTAAATT',\n",
" 'CAGCATTTTATCAATGCCATTCAATGCCATAGATCCATCGACTTTTGTTTTTTGCAGTTGAATCAATAAAGACCTGACTAATTTACCCGTAGCTATATTC',\n",
" 'GATGGCTTCATGCTTTTCAGTTTCATTATTGGCACGAGGAGCAGTCGTTGAGCCAATAATGAAACTGAAAAGCATGAAGCCATCTGGGGGGGACCGGTGG',\n",
" 'CAGCATTCAAGAAATCGTTGAACATTTCTTTGACAATTTTTCTGTTAGCAGATGACTCATCAGACCAAAATGATTCGCTAATAAATGGAATAGTAGACCA',\n",
" ...]"
]
},
"execution_count": 208,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"#seq"
]
},
{
"cell_type": "code",
"execution_count": 209,
"metadata": {
"hidden": true
},
"outputs": [
{
"data": {
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" ...]"
]
},
"execution_count": 209,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"#score"
]
},
{
"cell_type": "code",
"execution_count": 210,
"metadata": {
"hidden": true
},
"outputs": [
{
"data": {
"text/plain": [
"(2000, 2000, 2000)"
]
},
"execution_count": 210,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"len(label), len(seq), len(score)"
]
},
{
"cell_type": "code",
"execution_count": 211,
"metadata": {
"hidden": true
},
"outputs": [],
"source": [
"col_names = ['label', 'sequence', 'score']"
]
},
{
"cell_type": "code",
"execution_count": 212,
"metadata": {
"hidden": true
},
"outputs": [],
"source": [
"fastq_df = pd.DataFrame({'label': label, 'sequence': seq, 'score': score})"
]
},
{
"cell_type": "code",
"execution_count": 213,
"metadata": {
"hidden": true
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"<class 'pandas.core.frame.DataFrame'>\n",
"RangeIndex: 2000 entries, 0 to 1999\n",
"Data columns (total 3 columns):\n",
"label 2000 non-null object\n",
"sequence 2000 non-null object\n",
"score 2000 non-null object\n",
"dtypes: object(3)\n",
"memory usage: 47.0+ KB\n"
]
}
],
"source": [
"fastq_df.info()"
]
},
{
"cell_type": "code",
"execution_count": 214,
"metadata": {
"hidden": true
},
"outputs": [
{
"data": {
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" <th>score</th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>0</th>\n",
" <td>SRR1993099.sra.1</td>\n",
" <td>ATCTACAAGAAGGGTGAAGTGCTTTTCGAATTTTGCCACTGCAAGT...</td>\n",
" <td>[31, 31, 31, 35, 35, 35, 35, 35, 39, 32, 39, 3...</td>\n",
" </tr>\n",
" <tr>\n",
" <th>1</th>\n",
" <td>SRR1993099.sra.2</td>\n",
" <td>TGTGCTCCATGTCGATATTTCGTGGAGCAAACCAAAAAAGATGCGG...</td>\n",
" <td>[34, 34, 31, 37, 37, 37, 37, 37, 38, 39, 38, 3...</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2</th>\n",
" <td>SRR1993099.sra.3</td>\n",
" <td>NACCCTTTATAAAAGCCTAGATGTAGCAGTGCGAAGCGAACTCGAT...</td>\n",
" <td>[2, 16, 28, 35, 35, 37, 37, 37, 39, 38, 35, 38...</td>\n",
" </tr>\n",
" <tr>\n",
" <th>3</th>\n",
" <td>SRR1993099.sra.4</td>\n",
" <td>CGAATGGGACCTTGAATGGATTAACGAGATTCCCACTGTCCCTATC...</td>\n",
" <td>[31, 31, 31, 37, 37, 37, 37, 37, 37, 35, 39, 3...</td>\n",
" </tr>\n",
" <tr>\n",
" <th>4</th>\n",
" <td>SRR1993099.sra.5</td>\n",
" <td>CACACCGCAGTAGATGGAAAACTCGAGTTTTACATGGAACAGGTAA...</td>\n",
" <td>[34, 34, 34, 37, 37, 37, 37, 37, 39, 39, 39, 3...</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"</div>"
],
"text/plain": [
" label sequence \\\n",
"0 SRR1993099.sra.1 ATCTACAAGAAGGGTGAAGTGCTTTTCGAATTTTGCCACTGCAAGT... \n",
"1 SRR1993099.sra.2 TGTGCTCCATGTCGATATTTCGTGGAGCAAACCAAAAAAGATGCGG... \n",
"2 SRR1993099.sra.3 NACCCTTTATAAAAGCCTAGATGTAGCAGTGCGAAGCGAACTCGAT... \n",
"3 SRR1993099.sra.4 CGAATGGGACCTTGAATGGATTAACGAGATTCCCACTGTCCCTATC... \n",
"4 SRR1993099.sra.5 CACACCGCAGTAGATGGAAAACTCGAGTTTTACATGGAACAGGTAA... \n",
"\n",
" score \n",
"0 [31, 31, 31, 35, 35, 35, 35, 35, 39, 32, 39, 3... \n",
"1 [34, 34, 31, 37, 37, 37, 37, 37, 38, 39, 38, 3... \n",
"2 [2, 16, 28, 35, 35, 37, 37, 37, 39, 38, 35, 38... \n",
"3 [31, 31, 31, 37, 37, 37, 37, 37, 37, 35, 39, 3... \n",
"4 [34, 34, 34, 37, 37, 37, 37, 37, 39, 39, 39, 3... "
]
},
"execution_count": 214,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"fastq_df.head()"
]
},
{
"cell_type": "code",
"execution_count": 215,
"metadata": {
"hidden": true
},
"outputs": [
{
"data": {
"text/html": [
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" <th>label</th>\n",
" <th>sequence</th>\n",
" <th>score</th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>1995</th>\n",
" <td>SRR5665975.sra.496</td>\n",
" <td>AGCTCCCTCGTTCGCTCTCCTGTTCCGACCCTGCCGCTTACCGGAT...</td>\n",
" <td>[23, 33, 23, 31, 11, 26, 37, 34, 36, 31, 31, 1...</td>\n",
" </tr>\n",
" <tr>\n",
" <th>1996</th>\n",
" <td>SRR5665975.sra.497</td>\n",
" <td>AGCAGGGCGGCATTCAGGTGCTGCTGGAAAAACTGCAAAGTGGCGG...</td>\n",
" <td>[34, 34, 34, 34, 34, 38, 38, 38, 38, 38, 38, 3...</td>\n",
" </tr>\n",
" <tr>\n",
" <th>1997</th>\n",
" <td>SRR5665975.sra.498</td>\n",
" <td>TTCTATACCATTAAAGAAGCCGAACGCGGCGTGGTAACACGCTTTG...</td>\n",
" <td>[34, 34, 34, 34, 34, 38, 37, 38, 38, 38, 38, 3...</td>\n",
" </tr>\n",
" <tr>\n",
" <th>1998</th>\n",
" <td>SRR5665975.sra.499</td>\n",
" <td>TACCGTGCCGTTAAAATCGGCTCCCACCAGCAGCTGAATCGCACCG...</td>\n",
" <td>[34, 34, 34, 34, 34, 37, 34, 34, 35, 38, 38, 3...</td>\n",
" </tr>\n",
" <tr>\n",
" <th>1999</th>\n",
" <td>SRR5665975.sra.500</td>\n",
" <td>TATATATGAGTAAACTTGGTCTGACAGTTACCAATGCTTAATCAGT...</td>\n",
" <td>[34, 34, 34, 34, 34, 36, 38, 38, 38, 38, 36, 3...</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"</div>"
],
"text/plain": [
" label sequence \\\n",
"1995 SRR5665975.sra.496 AGCTCCCTCGTTCGCTCTCCTGTTCCGACCCTGCCGCTTACCGGAT... \n",
"1996 SRR5665975.sra.497 AGCAGGGCGGCATTCAGGTGCTGCTGGAAAAACTGCAAAGTGGCGG... \n",
"1997 SRR5665975.sra.498 TTCTATACCATTAAAGAAGCCGAACGCGGCGTGGTAACACGCTTTG... \n",
"1998 SRR5665975.sra.499 TACCGTGCCGTTAAAATCGGCTCCCACCAGCAGCTGAATCGCACCG... \n",
"1999 SRR5665975.sra.500 TATATATGAGTAAACTTGGTCTGACAGTTACCAATGCTTAATCAGT... \n",
"\n",
" score \n",
"1995 [23, 33, 23, 31, 11, 26, 37, 34, 36, 31, 31, 1... \n",
"1996 [34, 34, 34, 34, 34, 38, 38, 38, 38, 38, 38, 3... \n",
"1997 [34, 34, 34, 34, 34, 38, 37, 38, 38, 38, 38, 3... \n",
"1998 [34, 34, 34, 34, 34, 37, 34, 34, 35, 38, 38, 3... \n",
"1999 [34, 34, 34, 34, 34, 36, 38, 38, 38, 38, 36, 3... "
]
},
"execution_count": 215,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"fastq_df.tail()"
]
},
{
"cell_type": "code",
"execution_count": 216,
"metadata": {
"hidden": true
},
"outputs": [],
"source": [
"# save to H5 file (csv is making problems with the list in score column)\n",
"fastq_df.to_hdf('fastq_df.h5', key='df')"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Data frame setup"
]
},
{
"cell_type": "code",
"execution_count": 11,
"metadata": {},
"outputs": [],
"source": [
"# load csv file into pandas data frame\n",
"fastq_df = pd.read_hdf('fastq_df.h5', key='df')# index_col=0)"
]
},
{
"cell_type": "code",
"execution_count": 12,
"metadata": {},
"outputs": [
{
"data": {
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" <td>[31, 31, 31, 35, 35, 35, 35, 35, 39, 32, 39, 3...</td>\n",
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" <tr>\n",
" <th>1</th>\n",
" <td>SRR1993099.sra.2</td>\n",
" <td>TGTGCTCCATGTCGATATTTCGTGGAGCAAACCAAAAAAGATGCGG...</td>\n",
" <td>[34, 34, 31, 37, 37, 37, 37, 37, 38, 39, 38, 3...</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2</th>\n",
" <td>SRR1993099.sra.3</td>\n",
" <td>NACCCTTTATAAAAGCCTAGATGTAGCAGTGCGAAGCGAACTCGAT...</td>\n",
" <td>[2, 16, 28, 35, 35, 37, 37, 37, 39, 38, 35, 38...</td>\n",
" </tr>\n",
" <tr>\n",
" <th>3</th>\n",
" <td>SRR1993099.sra.4</td>\n",
" <td>CGAATGGGACCTTGAATGGATTAACGAGATTCCCACTGTCCCTATC...</td>\n",
" <td>[31, 31, 31, 37, 37, 37, 37, 37, 37, 35, 39, 3...</td>\n",
" </tr>\n",
" <tr>\n",
" <th>4</th>\n",
" <td>SRR1993099.sra.5</td>\n",
" <td>CACACCGCAGTAGATGGAAAACTCGAGTTTTACATGGAACAGGTAA...</td>\n",
" <td>[34, 34, 34, 37, 37, 37, 37, 37, 39, 39, 39, 3...</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"</div>"
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"text/plain": [
" label sequence \\\n",
"0 SRR1993099.sra.1 ATCTACAAGAAGGGTGAAGTGCTTTTCGAATTTTGCCACTGCAAGT... \n",
"1 SRR1993099.sra.2 TGTGCTCCATGTCGATATTTCGTGGAGCAAACCAAAAAAGATGCGG... \n",
"2 SRR1993099.sra.3 NACCCTTTATAAAAGCCTAGATGTAGCAGTGCGAAGCGAACTCGAT... \n",
"3 SRR1993099.sra.4 CGAATGGGACCTTGAATGGATTAACGAGATTCCCACTGTCCCTATC... \n",
"4 SRR1993099.sra.5 CACACCGCAGTAGATGGAAAACTCGAGTTTTACATGGAACAGGTAA... \n",
"\n",
" score \n",
"0 [31, 31, 31, 35, 35, 35, 35, 35, 39, 32, 39, 3... \n",
"1 [34, 34, 31, 37, 37, 37, 37, 37, 38, 39, 38, 3... \n",
"2 [2, 16, 28, 35, 35, 37, 37, 37, 39, 38, 35, 38... \n",
"3 [31, 31, 31, 37, 37, 37, 37, 37, 37, 35, 39, 3... \n",
"4 [34, 34, 34, 37, 37, 37, 37, 37, 39, 39, 39, 3... "
]
},
"execution_count": 12,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"# show pandas data frame head\n",
"fastq_df.head()"
]
},
{
"cell_type": "code",
"execution_count": 13,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"<class 'pandas.core.frame.DataFrame'>\n",
"Int64Index: 2000 entries, 0 to 1999\n",
"Data columns (total 3 columns):\n",
"label 2000 non-null object\n",
"sequence 2000 non-null object\n",
"score 2000 non-null object\n",
"dtypes: object(3)\n",
"memory usage: 62.5+ KB\n"
]
}
],
"source": [
"fastq_df.info()"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"### Target variables setup"
]
},
{
"cell_type": "code",
"execution_count": 14,
"metadata": {},
"outputs": [],
"source": [
"def recode_label(label):\n",
"\n",
" if label.find('SRR1993099') != -1:\n",
" return 0\n",
" \n",
" elif label.find('SRR5665975') != -1:\n",
" return 1\n",
" \n",
" else:\n",
" return np.nan"
]
},
{
"cell_type": "code",
"execution_count": 15,
"metadata": {},
"outputs": [],
"source": [
"fastq_df['label_recoded'] = fastq_df['label'].apply(recode_label)"
]
},
{
"cell_type": "code",
"execution_count": 16,
"metadata": {},
"outputs": [
{
"data": {
"text/html": [
"<div>\n",
"<style scoped>\n",
" .dataframe tbody tr th:only-of-type {\n",
" vertical-align: middle;\n",
" }\n",
"\n",
" .dataframe tbody tr th {\n",
" vertical-align: top;\n",
" }\n",
"\n",
" .dataframe thead th {\n",
" text-align: right;\n",
" }\n",
"</style>\n",
"<table border=\"1\" class=\"dataframe\">\n",
" <thead>\n",
" <tr style=\"text-align: right;\">\n",
" <th></th>\n",
" <th>label</th>\n",
" <th>sequence</th>\n",
" <th>score</th>\n",
" <th>label_recoded</th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>0</th>\n",
" <td>SRR1993099.sra.1</td>\n",
" <td>ATCTACAAGAAGGGTGAAGTGCTTTTCGAATTTTGCCACTGCAAGT...</td>\n",
" <td>[31, 31, 31, 35, 35, 35, 35, 35, 39, 32, 39, 3...</td>\n",
" <td>0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>1</th>\n",
" <td>SRR1993099.sra.2</td>\n",
" <td>TGTGCTCCATGTCGATATTTCGTGGAGCAAACCAAAAAAGATGCGG...</td>\n",
" <td>[34, 34, 31, 37, 37, 37, 37, 37, 38, 39, 38, 3...</td>\n",
" <td>0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2</th>\n",
" <td>SRR1993099.sra.3</td>\n",
" <td>NACCCTTTATAAAAGCCTAGATGTAGCAGTGCGAAGCGAACTCGAT...</td>\n",
" <td>[2, 16, 28, 35, 35, 37, 37, 37, 39, 38, 35, 38...</td>\n",
" <td>0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>3</th>\n",
" <td>SRR1993099.sra.4</td>\n",
" <td>CGAATGGGACCTTGAATGGATTAACGAGATTCCCACTGTCCCTATC...</td>\n",
" <td>[31, 31, 31, 37, 37, 37, 37, 37, 37, 35, 39, 3...</td>\n",
" <td>0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>4</th>\n",
" <td>SRR1993099.sra.5</td>\n",
" <td>CACACCGCAGTAGATGGAAAACTCGAGTTTTACATGGAACAGGTAA...</td>\n",
" <td>[34, 34, 34, 37, 37, 37, 37, 37, 39, 39, 39, 3...</td>\n",
" <td>0</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"</div>"
],
"text/plain": [
" label sequence \\\n",
"0 SRR1993099.sra.1 ATCTACAAGAAGGGTGAAGTGCTTTTCGAATTTTGCCACTGCAAGT... \n",
"1 SRR1993099.sra.2 TGTGCTCCATGTCGATATTTCGTGGAGCAAACCAAAAAAGATGCGG... \n",
"2 SRR1993099.sra.3 NACCCTTTATAAAAGCCTAGATGTAGCAGTGCGAAGCGAACTCGAT... \n",
"3 SRR1993099.sra.4 CGAATGGGACCTTGAATGGATTAACGAGATTCCCACTGTCCCTATC... \n",
"4 SRR1993099.sra.5 CACACCGCAGTAGATGGAAAACTCGAGTTTTACATGGAACAGGTAA... \n",
"\n",
" score label_recoded \n",
"0 [31, 31, 31, 35, 35, 35, 35, 35, 39, 32, 39, 3... 0 \n",
"1 [34, 34, 31, 37, 37, 37, 37, 37, 38, 39, 38, 3... 0 \n",
"2 [2, 16, 28, 35, 35, 37, 37, 37, 39, 38, 35, 38... 0 \n",
"3 [31, 31, 31, 37, 37, 37, 37, 37, 37, 35, 39, 3... 0 \n",
"4 [34, 34, 34, 37, 37, 37, 37, 37, 39, 39, 39, 3... 0 "
]
},
"execution_count": 16,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"fastq_df.head()"
]
},
{
"cell_type": "code",
"execution_count": 17,
"metadata": {},
"outputs": [
{
"data": {
"text/html": [
"<div>\n",
"<style scoped>\n",
" .dataframe tbody tr th:only-of-type {\n",
" vertical-align: middle;\n",
" }\n",
"\n",
" .dataframe tbody tr th {\n",
" vertical-align: top;\n",
" }\n",
"\n",
" .dataframe thead th {\n",
" text-align: right;\n",
" }\n",
"</style>\n",
"<table border=\"1\" class=\"dataframe\">\n",
" <thead>\n",
" <tr style=\"text-align: right;\">\n",
" <th></th>\n",
" <th>label</th>\n",
" <th>sequence</th>\n",
" <th>score</th>\n",
" <th>label_recoded</th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>1995</th>\n",
" <td>SRR5665975.sra.496</td>\n",
" <td>AGCTCCCTCGTTCGCTCTCCTGTTCCGACCCTGCCGCTTACCGGAT...</td>\n",
" <td>[23, 33, 23, 31, 11, 26, 37, 34, 36, 31, 31, 1...</td>\n",
" <td>1</td>\n",
" </tr>\n",
" <tr>\n",
" <th>1996</th>\n",
" <td>SRR5665975.sra.497</td>\n",
" <td>AGCAGGGCGGCATTCAGGTGCTGCTGGAAAAACTGCAAAGTGGCGG...</td>\n",
" <td>[34, 34, 34, 34, 34, 38, 38, 38, 38, 38, 38, 3...</td>\n",
" <td>1</td>\n",
" </tr>\n",
" <tr>\n",
" <th>1997</th>\n",
" <td>SRR5665975.sra.498</td>\n",
" <td>TTCTATACCATTAAAGAAGCCGAACGCGGCGTGGTAACACGCTTTG...</td>\n",
" <td>[34, 34, 34, 34, 34, 38, 37, 38, 38, 38, 38, 3...</td>\n",
" <td>1</td>\n",
" </tr>\n",
" <tr>\n",
" <th>1998</th>\n",
" <td>SRR5665975.sra.499</td>\n",
" <td>TACCGTGCCGTTAAAATCGGCTCCCACCAGCAGCTGAATCGCACCG...</td>\n",
" <td>[34, 34, 34, 34, 34, 37, 34, 34, 35, 38, 38, 3...</td>\n",
" <td>1</td>\n",
" </tr>\n",
" <tr>\n",
" <th>1999</th>\n",
" <td>SRR5665975.sra.500</td>\n",
" <td>TATATATGAGTAAACTTGGTCTGACAGTTACCAATGCTTAATCAGT...</td>\n",
" <td>[34, 34, 34, 34, 34, 36, 38, 38, 38, 38, 36, 3...</td>\n",
" <td>1</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"</div>"
],
"text/plain": [
" label sequence \\\n",
"1995 SRR5665975.sra.496 AGCTCCCTCGTTCGCTCTCCTGTTCCGACCCTGCCGCTTACCGGAT... \n",
"1996 SRR5665975.sra.497 AGCAGGGCGGCATTCAGGTGCTGCTGGAAAAACTGCAAAGTGGCGG... \n",
"1997 SRR5665975.sra.498 TTCTATACCATTAAAGAAGCCGAACGCGGCGTGGTAACACGCTTTG... \n",
"1998 SRR5665975.sra.499 TACCGTGCCGTTAAAATCGGCTCCCACCAGCAGCTGAATCGCACCG... \n",
"1999 SRR5665975.sra.500 TATATATGAGTAAACTTGGTCTGACAGTTACCAATGCTTAATCAGT... \n",
"\n",
" score label_recoded \n",
"1995 [23, 33, 23, 31, 11, 26, 37, 34, 36, 31, 31, 1... 1 \n",
"1996 [34, 34, 34, 34, 34, 38, 38, 38, 38, 38, 38, 3... 1 \n",
"1997 [34, 34, 34, 34, 34, 38, 37, 38, 38, 38, 38, 3... 1 \n",
"1998 [34, 34, 34, 34, 34, 37, 34, 34, 35, 38, 38, 3... 1 \n",
"1999 [34, 34, 34, 34, 34, 36, 38, 38, 38, 38, 36, 3... 1 "
]
},
"execution_count": 17,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"fastq_df.tail()"
]
},
{
"cell_type": "code",
"execution_count": 18,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"<class 'pandas.core.frame.DataFrame'>\n",
"Int64Index: 2000 entries, 0 to 1999\n",
"Data columns (total 4 columns):\n",
"label 2000 non-null object\n",
"sequence 2000 non-null object\n",
"score 2000 non-null object\n",
"label_recoded 2000 non-null int64\n",
"dtypes: int64(1), object(3)\n",
"memory usage: 78.1+ KB\n"
]
}
],
"source": [
"fastq_df.info()"
]
},
{
"cell_type": "code",
"execution_count": 19,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"array([0, 0, 0, 0, ..., 1, 1, 1, 1])"
]
},
"execution_count": 19,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"# setup target a\n",
"targA = fastq_df['label_recoded'].values; targA"
]
},
{
"cell_type": "code",
"execution_count": 20,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"array([1, 1, 1, 1, ..., 0, 0, 0, 0])"
]
},
"execution_count": 20,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"# setup target b = not(target a)\n",
"targB = np.logical_not(fastq_df['label_recoded'].values).astype(int); targB"
]
},
{
"cell_type": "code",
"execution_count": 21,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"([[0, 1], [0, 1], [0, 1], [0, 1]], '...', [[1, 0], [1, 0], [1, 0], [1, 0]])"
]
},
"execution_count": 21,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"# zip together target a and target b to get target\n",
"targ = [[a,b] for a, b in zip(targA, targB)]; targ[:4], '...', targ[-4:]#, len(targ)"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Dataset setup for training with basic PyTorch"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"### Setup sqeuence to array function"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"#### 3D encoding of fastq sequence"
]
},
{
"cell_type": "code",
"execution_count": 24,
"metadata": {},
"outputs": [],
"source": [
"# open sequence array function\n",
"def open_fastq_array(seq:str, score:list, seq_len=None)->np.array:\n",
" \"Return `List` object with np.array created from sequence string `seq`.\"\n",
" \n",
" if seq_len != None:\n",
" seq = seq[:seq_len]\n",
" score = score[:seq_len]\n",
" \n",
" int_enc = LabelEncoder() # setup class instance to encode the four different bases to integer values (1D)\n",
" #one_hot_enc = OneHotEncoder(categories=[range(4)]) # setup one hot encoder to encode integer encoded classes (1D) to one hot encoded array (4D)\n",
" \n",
" enc = int_enc.fit_transform(list(seq)) # bases (ACGT) to int (0,1,2,3)\n",
" enc = np.array(enc).reshape(-1,1) # reshape to get rank 2 array (from rank 1 array)\n",
" #enc = one_hot_enc.fit_transform(enc) # encoded integer encoded bases to sparse matrix (sparse matrix dtype)\n",
" #enc = enc.toarray().T#.reshape(1,-1,4) # export sparse matrix to np array\n",
" \n",
" # one-hot-encode base position\n",
" adenosine = enc == 0\n",
" thymine = enc == 3\n",
" cytosine = enc == 1\n",
" \n",
" # base pair encoding: AT = False, GC = True\n",
" # https://stackoverflow.com/questions/32192163/python-and-operator-on-two-boolean-lists-how\n",
" basepair_enc = np.array([not(a or t) for a, t in zip(adenosine, thymine)]).astype('int')*255\n",
" \n",
" # strandpostion encodes the position of A/C or T/G on the the strand: A or C = False, T or G = True\n",
" strandposition_enc = np.array([not(a or c) for a, c in zip(adenosine, cytosine)]).astype('int')*255\n",
" \n",
" score_enc = np.array(score)\n",
" \n",
" enc = np.stack((basepair_enc, strandposition_enc, score_enc), axis=0)\n",
" \n",
" enc = enc/255\n",
" \n",
" return enc"
]
},
{
"cell_type": "code",
"execution_count": 25,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"(array([[1. , 0. , 0. , 0. , ..., 1. , 0. , 0. , 1. ],\n",
" [1. , 0. , 1. , 0. , ..., 1. , 1. , 0. , 1. ],\n",
" [0.121569, 0.129412, 0.121569, 0.137255, ..., 0.121569, 0.101961, 0.090196, 0.031373]]),\n",
" (3, 50))"
]
},
"execution_count": 25,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"seq_len = 50 # None !\n",
"n = 750\n",
"test_fastq_arr = open_fastq_array(fastq_df.sequence[n], np.multiply(fastq_df.score[n],1), seq_len); test_fastq_arr, test_fastq_arr.shape"
]
},
{
"cell_type": "code",
"execution_count": 26,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"GATACTGAAGTGGCAATTCACTTTGTTCTTAGCGTCTATGGCCGGTGTAGGTGCATTTACCTTCTACGAACTTTATTTCACTTCAGATTATGTCAAGGGC\n",
"\n",
"\n",
"[31, 33, 31, 35, 37, 37, 35, 37, 39, 39, 30, 35, 37, 39, 41, 40, 41, 41, 41, 40, 40, 40, 41, 37, 40, 39, 39, 40, 41, 41, 41, 40, 40, 40, 40, 41, 41, 41, 40, 41, 40, 38, 40, 41, 40, 15, 31, 26, 23, 8, 28, 14, 31, 37, 36, 32, 39, 38, 38, 35, 38, 39, 41, 40, 39, 36, 36, 39, 27, 30, 35, 33, 31, 34, 34, 34, 25, 34, 32, 32, 34, 34, 34, 34, 32, 34, 29, 34, 34, 34, 34, 34, 31, 34, 34, 32, 31, 34, 35, 30]\n"
]
}
],
"source": [
"print(fastq_df.sequence[n])\n",
"print('\\n')\n",
"print(fastq_df.score[n])"
]
},
{
"cell_type": "code",
"execution_count": 27,
"metadata": {},
"outputs": [],
"source": [
"# https://stackoverflow.com/questions/11352047/finding-moving-average-from-data-points-in-python\n",
"# https://stackoverflow.com/questions/13728392/moving-average-or-running-mean/27681394#27681394\n",
"data = fastq_df.score[n]\n",
"window_width = 10\n",
"cumsum_vec = np.cumsum(np.insert(data, 0, 0)) \n",
"ma_vec = (cumsum_vec[window_width:] - cumsum_vec[:-window_width]) / window_width"
]
},
{
"cell_type": "code",
"execution_count": 28,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"[<matplotlib.lines.Line2D at 0x1a1f9b0b00>]"
]
},
"execution_count": 28,
"metadata": {},
"output_type": "execute_result"
},
{
"data": {
"image/png": 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\n",
"text/plain": [
"<Figure size 432x288 with 1 Axes>"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
}
],
"source": [
"plt.plot(data)\n",
"plt.plot(ma_vec)"
]
},
{
"cell_type": "code",
"execution_count": 29,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"<matplotlib.image.AxesImage at 0x1a1fa3ef28>"
]
},
"execution_count": 29,
"metadata": {},
"output_type": "execute_result"
},
{
"data": {
"image/png": "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\n",
"text/plain": [
"<Figure size 432x288 with 1 Axes>"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
}
],
"source": [
"# visualize opened sequence as 2D image\n",
"plt.imshow(test_fastq_arr.reshape(1,-1,3), aspect='auto')\n",
"#plt.axis('off');"
]
},
{
"cell_type": "code",
"execution_count": 30,
"metadata": {},
"outputs": [],
"source": [
"# show channels separately"
]
},
{
"cell_type": "code",
"execution_count": 31,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"<matplotlib.image.AxesImage at 0x1a20c01eb8>"
]
},
"execution_count": 31,
"metadata": {},
"output_type": "execute_result"
},
{
"data": {
"image/png": "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\n",
"text/plain": [
"<Figure size 432x288 with 1 Axes>"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
}
],
"source": [
"plt.imshow(test_fastq_arr[0,:].reshape(1,-1), aspect='auto', cmap='gray')"
]
},
{
"cell_type": "code",
"execution_count": 32,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"<matplotlib.image.AxesImage at 0x1a20cc15f8>"
]
},
"execution_count": 32,
"metadata": {},
"output_type": "execute_result"
},
{
"data": {
"image/png": "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\n",
"text/plain": [
"<Figure size 432x288 with 1 Axes>"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
}
],
"source": [
"plt.imshow(test_fastq_arr[1,:].reshape(1,-1), aspect='auto', cmap='gray')"
]
},
{
"cell_type": "code",
"execution_count": 33,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"<matplotlib.image.AxesImage at 0x1a20d18b38>"
]
},
"execution_count": 33,
"metadata": {},
"output_type": "execute_result"
},
{
"data": {
"image/png": "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\n",
"text/plain": [
"<Figure size 432x288 with 1 Axes>"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
}
],
"source": [
"plt.imshow(test_fastq_arr[2,:].reshape(1,-1), aspect='auto', cmap='gray')"
]
},
{
"cell_type": "code",
"execution_count": 34,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"<matplotlib.image.AxesImage at 0x1a1f8f6748>"
]
},
"execution_count": 34,
"metadata": {},
"output_type": "execute_result"
},
{
"data": {
"image/png": "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\n",
"text/plain": [
"<Figure size 432x288 with 1 Axes>"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
}
],
"source": [
"# show score with 3 channels (copied 3x)\n",
"plt.imshow(np.concatenate(([test_fastq_arr[2,:].reshape(-1,1), test_fastq_arr[2,:].reshape(-1,1), test_fastq_arr[2,:].reshape(-1,1)]), axis=1).reshape(1,-1,3), aspect='auto')"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"### Setup datasets"
]
},
{
"cell_type": "code",
"execution_count": 189,
"metadata": {},
"outputs": [],
"source": [
"#next(iter(zip(fastq_df['sequence'].values, fastq_df['score'].values)))"
]
},
{
"cell_type": "code",
"execution_count": 35,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"2000"
]
},
"execution_count": 35,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"# generate sequence array float tensor for every sequence in pandas data frame column Sequences (x data)\n",
"seq_len = 100\n",
"x = [tensor(open_fastq_array(seq, score, seq_len)).type(torch.float) for seq, score in zip(fastq_df['sequence'].values, fastq_df['score'].values)]; len(x)"
]
},
{
"cell_type": "code",
"execution_count": 36,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"torch.Size([2000, 3, 100])"
]
},
"execution_count": 36,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"# stack all tensors together in a single tensor\n",
"x = torch.stack(x); x.shape\n",
"#x = torch.stack(x).view((-1,4,50,1)); x.shape # --> torch.Size([2000, 4, 50, 1])"
]
},
{
"cell_type": "code",
"execution_count": 37,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"tensor([[0., 1.],\n",
" [0., 1.],\n",
" [0., 1.],\n",
" ...,\n",
" [1., 0.],\n",
" [1., 0.],\n",
" [1., 0.]])"
]
},
"execution_count": 37,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"# setup target data floar tensor (y data)\n",
"y = tensor(targ).view(-1,2).type(torch.float); y # multi-label\n",
"#y = tensor(targA).type(torch.float); y # classification with single label"
]
},
{
"cell_type": "code",
"execution_count": 38,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"(2000, 2000)"
]
},
"execution_count": 38,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"# verify total dataset length\n",
"len(x), len(y)"
]
},
{
"cell_type": "code",
"execution_count": 39,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"(tensor([[0.0000, 0.0000, 1.0000, 1.0000, 1.0000, 1.0000, 1.0000, 1.0000, 0.0000,\n",
" 1.0000, 0.0000, 0.0000, 0.0000, 0.0000, 1.0000, 1.0000, 1.0000, 1.0000,\n",
" 0.0000, 1.0000, 0.0000, 1.0000, 1.0000, 1.0000, 0.0000, 1.0000, 1.0000,\n",
" 0.0000, 1.0000, 1.0000, 1.0000, 1.0000, 1.0000, 0.0000, 0.0000, 1.0000,\n",
" 1.0000, 1.0000, 0.0000, 0.0000, 1.0000, 1.0000, 1.0000, 1.0000, 0.0000,\n",
" 1.0000, 0.0000, 1.0000, 1.0000, 1.0000, 1.0000, 1.0000, 1.0000, 1.0000,\n",
" 0.0000, 1.0000, 1.0000, 0.0000, 1.0000, 1.0000, 1.0000, 0.0000, 1.0000,\n",
" 1.0000, 1.0000, 1.0000, 1.0000, 1.0000, 1.0000, 0.0000, 1.0000, 1.0000,\n",
" 1.0000, 1.0000, 1.0000, 1.0000, 1.0000, 0.0000, 1.0000, 0.0000, 1.0000,\n",
" 0.0000, 0.0000, 0.0000, 0.0000, 1.0000, 1.0000, 0.0000, 1.0000, 0.0000,\n",
" 0.0000, 0.0000, 1.0000, 1.0000, 1.0000, 1.0000, 1.0000, 1.0000, 0.0000,\n",
" 1.0000],\n",
" [1.0000, 0.0000, 0.0000, 0.0000, 0.0000, 1.0000, 1.0000, 1.0000, 0.0000,\n",
" 1.0000, 0.0000, 0.0000, 0.0000, 0.0000, 1.0000, 0.0000, 0.0000, 1.0000,\n",
" 0.0000, 1.0000, 0.0000, 1.0000, 1.0000, 1.0000, 0.0000, 1.0000, 0.0000,\n",
" 0.0000, 1.0000, 1.0000, 1.0000, 0.0000, 1.0000, 0.0000, 0.0000, 1.0000,\n",
" 0.0000, 1.0000, 0.0000, 0.0000, 0.0000, 1.0000, 0.0000, 1.0000, 0.0000,\n",
" 1.0000, 0.0000, 0.0000, 1.0000, 1.0000, 1.0000, 0.0000, 1.0000, 0.0000,\n",
" 0.0000, 1.0000, 0.0000, 0.0000, 1.0000, 1.0000, 1.0000, 0.0000, 1.0000,\n",
" 1.0000, 1.0000, 0.0000, 1.0000, 1.0000, 0.0000, 0.0000, 1.0000, 0.0000,\n",
" 1.0000, 1.0000, 1.0000, 1.0000, 1.0000, 0.0000, 1.0000, 0.0000, 1.0000,\n",
" 0.0000, 0.0000, 0.0000, 0.0000, 0.0000, 1.0000, 0.0000, 0.0000, 0.0000,\n",
" 0.0000, 0.0000, 1.0000, 1.0000, 1.0000, 0.0000, 1.0000, 1.0000, 0.0000,\n",
" 0.0000],\n",
" [0.0078, 0.0627, 0.1098, 0.1373, 0.1373, 0.1451, 0.1451, 0.1451, 0.1529,\n",
" 0.1490, 0.1373, 0.1490, 0.1451, 0.1529, 0.1569, 0.1569, 0.1569, 0.1569,\n",
" 0.1569, 0.1490, 0.1490, 0.1490, 0.1569, 0.1333, 0.1137, 0.1451, 0.1255,\n",
" 0.1059, 0.1529, 0.1412, 0.1490, 0.1490, 0.1255, 0.1451, 0.1490, 0.1490,\n",
" 0.1490, 0.1490, 0.1529, 0.1137, 0.1529, 0.1529, 0.1569, 0.1569, 0.1569,\n",
" 0.1569, 0.1529, 0.1529, 0.1569, 0.1490, 0.1412, 0.1412, 0.1333, 0.1412,\n",
" 0.1412, 0.1373, 0.1529, 0.1412, 0.1490, 0.1412, 0.1529, 0.1529, 0.1529,\n",
" 0.1137, 0.1333, 0.1412, 0.1412, 0.1373, 0.1451, 0.1373, 0.1333, 0.1333,\n",
" 0.1333, 0.1333, 0.1333, 0.1333, 0.1373, 0.1373, 0.1412, 0.1412, 0.1412,\n",
" 0.1373, 0.1373, 0.1373, 0.1373, 0.1373, 0.1333, 0.1255, 0.1216, 0.1255,\n",
" 0.1333, 0.1333, 0.1333, 0.1333, 0.1216, 0.1333, 0.1333, 0.1333, 0.1333,\n",
" 0.0980]]), tensor([0., 1.]))"
]
},
"execution_count": 39,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"# check x and y data\n",
"i = 2\n",
"x[i], y[i]"
]
},
{
"cell_type": "code",
"execution_count": 40,
"metadata": {},
"outputs": [],
"source": [
"# split dataset into train and valid TensorDataset for NN training\n",
"#train_ds = TensorDataset(x[:1500],y[:1500])\n",
"#valid_ds = TensorDataset(x[-500:],y[-500:])"
]
},
{
"cell_type": "code",
"execution_count": 41,
"metadata": {},
"outputs": [],
"source": [
"# split dataset into train and valid TensorDataset for NN training\n",
"train_ds = TensorDataset(x[250:1750],y[250:1750])\n",
"valid_ds = TensorDataset(torch.cat((x[:250], x[-250:])), torch.cat((y[:250], y[-250:])))"
]
},
{
"cell_type": "code",
"execution_count": 42,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"(1500, 500)"
]
},
"execution_count": 42,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"# verify train and valid dataset length\n",
"len(train_ds), len(valid_ds)"
]
},
{
"cell_type": "code",
"execution_count": 43,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"tensor([250., 250.])"
]
},
"execution_count": 43,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"# check the number of classes in the y target\n",
"torch.cat((y[:250], y[-250:])).sum(dim=0)"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"# Model setup"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Basic model for PyTorch training"
]
},
{
"cell_type": "markdown",
"metadata": {
"heading_collapsed": true
},
"source": [
"### Conv calculations"
]
},
{
"cell_type": "markdown",
"metadata": {
"hidden": true
},
"source": [
"http://cs231n.github.io/convolutional-networks/<br>\n",
"\"We can compute the spatial size of the output volume as a function of the input volume size (W), the receptive field size of the Conv Layer neurons (F), the stride with which they are applied (S), and the amount of zero padding used (P) on the border. You can convince yourself that the correct formula for calculating how many neurons “fit” is given by (W−F+2P)/S+1. For example for a 7x7 input and a 3x3 filter with stride 1 and pad 0 we would get a 5x5 output. With stride 2 we would get a 3x3 output. \""
]
},
{
"cell_type": "code",
"execution_count": 377,
"metadata": {
"hidden": true
},
"outputs": [
{
"data": {
"text/plain": [
"5.0"
]
},
"execution_count": 377,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"((7-3+2*0)/1)+1"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"hidden": true
},
"outputs": [],
"source": []
},
{
"cell_type": "code",
"execution_count": 389,
"metadata": {
"hidden": true
},
"outputs": [
{
"data": {
"text/plain": [
"39.0"
]
},
"execution_count": 389,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"((50-12+2*0)/1)+1"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"hidden": true
},
"outputs": [],
"source": []
},
{
"cell_type": "code",
"execution_count": 369,
"metadata": {
"hidden": true
},
"outputs": [
{
"data": {
"text/plain": [
"36.0"
]
},
"execution_count": 369,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"((39-4+2*0)/1)+1"
]
},
{
"cell_type": "code",
"execution_count": 380,
"metadata": {
"hidden": true
},
"outputs": [
{
"data": {
"text/plain": [
"36.0"
]
},
"execution_count": 380,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"(39+2*0-1*(4-1)-1)/1+1"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"hidden": true
},
"outputs": [],
"source": []
},
{
"cell_type": "code",
"execution_count": 379,
"metadata": {
"hidden": true
},
"outputs": [
{
"data": {
"text/plain": [
"9.0"
]
},
"execution_count": 379,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"288/32"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"hidden": true
},
"outputs": [],
"source": []
},
{
"cell_type": "code",
"execution_count": 392,
"metadata": {
"hidden": true
},
"outputs": [
{
"data": {
"text/plain": [
"torch.Size([1, 32, 89])"
]
},
"execution_count": 392,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"nn.Conv1d(in_channels=3, out_channels=32, kernel_size=12)(torch.rand((1,3,100))).shape"
]
},
{
"cell_type": "code",
"execution_count": 393,
"metadata": {
"hidden": true
},
"outputs": [
{
"data": {
"text/plain": [
"torch.Size([1, 32, 22])"
]
},
"execution_count": 393,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"nn.MaxPool1d(kernel_size=4)(torch.rand((1,32,89))).shape"
]
},
{
"cell_type": "code",
"execution_count": 394,
"metadata": {
"hidden": true
},
"outputs": [
{
"data": {
"text/plain": [
"704"
]
},
"execution_count": 394,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"32*22"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"hidden": true
},
"outputs": [],
"source": []
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"### Model setup"
]
},
{
"cell_type": "code",
"execution_count": 44,
"metadata": {},
"outputs": [],
"source": [
"# set dropout\n",
"drop_p = 0.2"
]
},
{
"cell_type": "code",
"execution_count": 45,
"metadata": {},
"outputs": [],
"source": [
"# inplace=True seems to generate problems?"
]
},
{
"cell_type": "code",
"execution_count": 60,
"metadata": {},
"outputs": [],
"source": [
"net_basic = nn.Sequential(nn.Conv1d(in_channels=3, out_channels=32, kernel_size=12),\n",
" nn.MaxPool1d(kernel_size=4),\n",
" Flatten(),\n",
" nn.Dropout(drop_p),\n",
" nn.Linear(in_features=288, out_features=16),\n",
" nn.ReLU(),\n",
" nn.Dropout(drop_p),\n",
" nn.Linear(in_features=16, out_features=2),\n",
" #Debugger() # optional debugger layer\n",
" )"
]
},
{
"cell_type": "code",
"execution_count": 61,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"Sequential(\n",
" (0): Conv1d(3, 32, kernel_size=(12,), stride=(1,))\n",
" (1): MaxPool1d(kernel_size=4, stride=4, padding=0, dilation=1, ceil_mode=False)\n",
" (2): Lambda()\n",
" (3): Dropout(p=0.2)\n",
" (4): Linear(in_features=288, out_features=16, bias=True)\n",
" (5): ReLU()\n",
" (6): Dropout(p=0.2)\n",
" (7): Linear(in_features=16, out_features=2, bias=True)\n",
")"
]
},
"execution_count": 61,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"# check network architecture\n",
"net_basic"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"# initialize weights with kaiming normal initialization\n",
"#apply_init(net_basic, nn.init.kaiming_normal_)"
]
},
{
"cell_type": "code",
"execution_count": 62,
"metadata": {},
"outputs": [],
"source": [
"net_ext = nn.Sequential(nn.Conv1d(in_channels=3, out_channels=32, kernel_size=12), # channels set to 3 !!!\n",
" nn.MaxPool1d(kernel_size=4),\n",
" Flatten(),\n",
" nn.Dropout(drop_p),\n",
" nn.Linear(in_features=704, out_features=512), # seq len 50bp --> 288, 100 bp --> 704\n",
" nn.ReLU(),\n",
" nn.Dropout(drop_p),\n",
" nn.Linear(512, 256),\n",
" nn.ReLU(),\n",
" nn.Dropout(drop_p),\n",
" nn.Linear(256, 16),\n",
" nn.ReLU(),\n",
" nn.Dropout(drop_p),\n",
" nn.Linear(in_features=16, out_features=2),\n",
" #Debugger() # optional debugger layer\n",
" )"
]
},
{
"cell_type": "code",
"execution_count": 63,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"Sequential(\n",
" (0): Conv1d(3, 32, kernel_size=(12,), stride=(1,))\n",
" (1): MaxPool1d(kernel_size=4, stride=4, padding=0, dilation=1, ceil_mode=False)\n",
" (2): Lambda()\n",
" (3): Dropout(p=0.2)\n",
" (4): Linear(in_features=704, out_features=512, bias=True)\n",
" (5): ReLU()\n",
" (6): Dropout(p=0.2)\n",
" (7): Linear(in_features=512, out_features=256, bias=True)\n",
" (8): ReLU()\n",
" (9): Dropout(p=0.2)\n",
" (10): Linear(in_features=256, out_features=16, bias=True)\n",
" (11): ReLU()\n",
" (12): Dropout(p=0.2)\n",
" (13): Linear(in_features=16, out_features=2, bias=True)\n",
")"
]
},
"execution_count": 63,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"net_ext"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"# Model training"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Train basic model with PyTorch"
]
},
{
"cell_type": "code",
"execution_count": 54,
"metadata": {},
"outputs": [],
"source": [
"# set batch size\n",
"bs = 64"
]
},
{
"cell_type": "code",
"execution_count": 55,
"metadata": {},
"outputs": [],
"source": [
"# setup DataLoader for NN training from TensorDatasets for NN training\n",
"train_dl = DataLoader(train_ds, batch_size=bs, shuffle=True)\n",
"valid_dl = DataLoader(valid_ds, batch_size=bs*2, shuffle=False)"
]
},
{
"cell_type": "code",
"execution_count": 64,
"metadata": {},
"outputs": [],
"source": [
"# set optimizer type, parameters, and hyperparameters\n",
"opt = optim.SGD(net_ext.parameters(), lr=1e-3, momentum=0.9)"
]
},
{
"cell_type": "code",
"execution_count": 65,
"metadata": {},
"outputs": [],
"source": [
"# training loop extended from https://github.com/fastai/fastai_docs/blob/master/dev_nb/mnist_sample.py\n",
"\n",
"\n",
"# simple loss function for batch\n",
"def simple_loss_batch(model, loss_func, xb, yb, opt=None):\n",
" loss = loss_func(model(xb), yb)\n",
"\n",
" if opt is not None:\n",
" loss.backward()\n",
" opt.step()\n",
" opt.zero_grad()\n",
"\n",
" return loss.item(), len(xb)\n",
"\n",
"\n",
"# simple fit function\n",
"def simple_fit(epochs, model, loss_func, opt, train_dl, valid_dl):\n",
" \n",
" epoch_list = []\n",
" train_loss_list = []\n",
" valid_loss_list = []\n",
" acc_list = []\n",
" y_hat_list = []\n",
" y_true_list = []\n",
" \n",
" print('epoch\\ttrain loss\\tvalid loss\\taccuaracy')\n",
" \n",
" for epoch in range(epochs):\n",
" \n",
" model.train()\n",
" train_losses, train_nums = zip(*[simple_loss_batch(model, loss_func, xb, yb, opt) for xb, yb in train_dl])\n",
" \n",
" # loss calculation for every epoch\n",
" train_loss = np.sum(np.multiply(train_losses, train_nums)) / np.sum(train_nums)\n",
" train_loss_list.append(train_loss)\n",
" \n",
" model.eval()\n",
" with torch.no_grad():\n",
" valid_losses, valid_nums = zip(*[simple_loss_batch(model, loss_func, xb, yb)\n",
" for xb,yb in valid_dl])\n",
" \n",
" # calculations for accuracy_thres metric: \n",
" y_hat = [model(xb) for xb, _ in valid_dl]\n",
" y_true = [yb for _, yb in valid_dl]\n",
" \n",
" y_hat_list.append(torch.cat(y_hat).cpu().numpy())\n",
" y_true_list.append(torch.cat(y_true).cpu().numpy())\n",
" \n",
" \n",
" valid_loss = np.sum(np.multiply(valid_losses, valid_nums)) / np.sum(valid_nums)\n",
" acc = accuracy_thresh(torch.cat(y_hat), torch.cat(y_true))\n",
" \n",
" epoch_list.append(epoch)\n",
" valid_loss_list.append(valid_loss)\n",
" acc_list.append(acc.item())\n",
" \n",
" print(f'{epoch}\\t{train_loss:.6f}\\t{valid_loss:.6f}\\t{acc.detach().item():.3f}')\n",
" \n",
" # print training (https://matplotlib.org/tutorials/introductory/usage.html#sphx-glr-tutorials-introductory-usage-py)\n",
" #pdb.set_trace()\n",
" plt.subplot(2,1,1)\n",
" plt.title('Training')\n",
" plt.ylabel('Loss')\n",
" plt.plot(train_loss_list, label='Train loss')\n",
" plt.plot(valid_loss_list, label='Valid loss')\n",
" plt.legend(loc=1)\n",
" \n",
" plt.subplot(2,1,2)\n",
" plt.xlabel('Training batch')\n",
" plt.ylabel('Accuracy')\n",
" plt.plot(acc_list, label='Accuracy metric')\n",
" plt.legend(loc=1)\n",
" \n",
" plt.show()\n",
" \n",
" #pdb.set_trace()\n",
" \n",
" return epoch_list, train_loss_list, valid_loss_list, acc_list, y_hat_list, y_true_list"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": []
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": []
},
{
"cell_type": "code",
"execution_count": 66,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"epoch\ttrain loss\tvalid loss\taccuaracy\n",
"0\t0.693186\t0.693182\t0.499\n",
"1\t0.693204\t0.693153\t0.503\n",
"2\t0.693081\t0.693116\t0.501\n",
"3\t0.693150\t0.693076\t0.504\n",
"4\t0.693020\t0.693041\t0.502\n",
"5\t0.692747\t0.693009\t0.501\n",
"6\t0.692681\t0.692978\t0.500\n",
"7\t0.692994\t0.692953\t0.502\n",
"8\t0.692920\t0.692922\t0.502\n",
"9\t0.692949\t0.692880\t0.502\n",
"10\t0.693081\t0.692854\t0.502\n",
"11\t0.692592\t0.692815\t0.502\n",
"12\t0.692503\t0.692781\t0.502\n",
"13\t0.692525\t0.692747\t0.502\n",
"14\t0.692492\t0.692722\t0.502\n",
"15\t0.692239\t0.692688\t0.500\n",
"16\t0.692376\t0.692644\t0.502\n",
"17\t0.692239\t0.692607\t0.502\n",
"18\t0.691883\t0.692575\t0.500\n",
"19\t0.692364\t0.692538\t0.502\n",
"20\t0.692577\t0.692507\t0.502\n",
"21\t0.691961\t0.692468\t0.502\n",
"22\t0.692306\t0.692431\t0.502\n",
"23\t0.691950\t0.692394\t0.502\n",
"24\t0.692125\t0.692349\t0.502\n",
"25\t0.692072\t0.692317\t0.502\n",
"26\t0.691791\t0.692281\t0.502\n",
"27\t0.691938\t0.692242\t0.502\n",
"28\t0.691577\t0.692197\t0.502\n",
"29\t0.691598\t0.692155\t0.502\n",
"30\t0.691627\t0.692110\t0.502\n",
"31\t0.691120\t0.692069\t0.502\n",
"32\t0.691198\t0.692019\t0.504\n",
"33\t0.691571\t0.691980\t0.502\n",
"34\t0.691697\t0.691932\t0.504\n",
"35\t0.690999\t0.691888\t0.504\n",
"36\t0.691030\t0.691844\t0.504\n",
"37\t0.690864\t0.691796\t0.503\n",
"38\t0.690711\t0.691741\t0.503\n",
"39\t0.691257\t0.691686\t0.503\n",
"40\t0.690717\t0.691630\t0.506\n",
"41\t0.691076\t0.691582\t0.504\n",
"42\t0.690412\t0.691535\t0.501\n",
"43\t0.690690\t0.691473\t0.502\n",
"44\t0.690613\t0.691407\t0.505\n",
"45\t0.690124\t0.691348\t0.503\n",
"46\t0.690265\t0.691282\t0.504\n",
"47\t0.689863\t0.691218\t0.504\n",
"48\t0.689845\t0.691139\t0.514\n",
"49\t0.690080\t0.691063\t0.519\n",
"50\t0.689912\t0.690995\t0.516\n",
"51\t0.689417\t0.690920\t0.515\n",
"52\t0.689531\t0.690843\t0.513\n",
"53\t0.689689\t0.690757\t0.519\n",
"54\t0.689382\t0.690673\t0.520\n",
"55\t0.689317\t0.690581\t0.524\n",
"56\t0.688781\t0.690491\t0.520\n",
"57\t0.688356\t0.690382\t0.530\n",
"58\t0.689030\t0.690286\t0.530\n",
"59\t0.688369\t0.690179\t0.530\n",
"60\t0.688492\t0.690064\t0.538\n",
"61\t0.687759\t0.689943\t0.549\n",
"62\t0.687371\t0.689819\t0.537\n",
"63\t0.687753\t0.689685\t0.541\n",
"64\t0.687421\t0.689547\t0.550\n",
"65\t0.686498\t0.689402\t0.543\n",
"66\t0.687519\t0.689247\t0.559\n",
"67\t0.686917\t0.689096\t0.548\n",
"68\t0.686764\t0.688936\t0.560\n",
"69\t0.686158\t0.688763\t0.560\n",
"70\t0.686069\t0.688577\t0.559\n",
"71\t0.684509\t0.688382\t0.558\n",
"72\t0.685404\t0.688174\t0.561\n",
"73\t0.684864\t0.687948\t0.569\n",
"74\t0.684759\t0.687708\t0.582\n",
"75\t0.684776\t0.687479\t0.583\n",
"76\t0.683977\t0.687219\t0.600\n",
"77\t0.683270\t0.686942\t0.611\n",
"78\t0.683050\t0.686637\t0.614\n",
"79\t0.682465\t0.686359\t0.594\n",
"80\t0.682490\t0.686044\t0.591\n",
"81\t0.681683\t0.685676\t0.607\n",
"82\t0.681614\t0.685292\t0.624\n",
"83\t0.680359\t0.684910\t0.619\n",
"84\t0.679998\t0.684468\t0.630\n",
"85\t0.680103\t0.684027\t0.628\n",
"86\t0.676816\t0.683520\t0.632\n",
"87\t0.676740\t0.683041\t0.623\n",
"88\t0.675846\t0.682484\t0.623\n",
"89\t0.676053\t0.681866\t0.625\n",
"90\t0.674309\t0.681192\t0.646\n",
"91\t0.672838\t0.680552\t0.630\n",
"92\t0.670839\t0.679765\t0.640\n",
"93\t0.670264\t0.678969\t0.637\n",
"94\t0.668094\t0.678123\t0.639\n",
"95\t0.667275\t0.677209\t0.634\n",
"96\t0.664619\t0.676264\t0.630\n",
"97\t0.664151\t0.675003\t0.652\n",
"98\t0.660884\t0.674045\t0.633\n",
"99\t0.660526\t0.672472\t0.670\n"
]
},
{
"data": {
"image/png": 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\n",
"text/plain": [
"<Figure size 432x288 with 2 Axes>"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
}
],
"source": [
"epoch_list, train_loss_list, valid_loss_list, acc_list, y_hat_list, y_true_list = \\\n",
"simple_fit(100, net_ext, F.binary_cross_entropy_with_logits, opt, train_dl, valid_dl)"
]
},
{
"cell_type": "code",
"execution_count": 189,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"epoch\ttrain loss\tvalid loss\taccuaracy\n",
"0\t0.600008\t0.698840\t0.730\n",
"1\t0.600969\t0.692987\t0.754\n",
"2\t0.591435\t0.694584\t0.740\n",
"3\t0.590053\t0.726944\t0.745\n",
"4\t0.580916\t0.710283\t0.761\n",
"5\t0.578672\t0.691073\t0.766\n",
"6\t0.550475\t0.783644\t0.759\n",
"7\t0.551840\t0.728513\t0.725\n",
"8\t0.511100\t0.645424\t0.742\n",
"9\t0.477625\t0.601255\t0.758\n",
"10\t0.456785\t0.645737\t0.756\n",
"11\t0.442627\t0.645925\t0.762\n",
"12\t0.420643\t0.681195\t0.752\n",
"13\t0.414291\t0.653433\t0.771\n",
"14\t0.390119\t0.661066\t0.759\n",
"15\t0.398398\t0.662051\t0.762\n",
"16\t0.390466\t0.648082\t0.756\n",
"17\t0.379322\t0.663783\t0.759\n",
"18\t0.358088\t0.672894\t0.764\n",
"19\t0.354025\t0.589842\t0.761\n",
"20\t0.328923\t0.669425\t0.749\n",
"21\t0.321054\t0.649121\t0.755\n",
"22\t0.311118\t0.712536\t0.738\n",
"23\t0.301067\t0.652746\t0.765\n",
"24\t0.285428\t0.629220\t0.767\n",
"25\t0.260498\t0.682674\t0.756\n",
"26\t0.276493\t0.574018\t0.778\n",
"27\t0.253138\t0.694934\t0.772\n",
"28\t0.247854\t0.610086\t0.771\n",
"29\t0.222541\t0.645830\t0.774\n",
"30\t0.209061\t0.650343\t0.773\n",
"31\t0.200769\t0.687456\t0.785\n",
"32\t0.179572\t0.709553\t0.769\n",
"33\t0.180749\t0.774029\t0.745\n",
"34\t0.192882\t0.725102\t0.764\n",
"35\t0.178563\t0.729063\t0.765\n",
"36\t0.149825\t0.765506\t0.766\n",
"37\t0.147145\t1.034499\t0.708\n",
"38\t0.174870\t0.781429\t0.776\n",
"39\t0.144159\t0.802195\t0.767\n",
"40\t0.131060\t0.854645\t0.761\n",
"41\t0.136966\t0.828336\t0.770\n",
"42\t0.133186\t0.762249\t0.787\n",
"43\t0.105571\t0.849186\t0.775\n",
"44\t0.122262\t0.844431\t0.778\n",
"45\t0.107422\t0.905494\t0.772\n",
"46\t0.113981\t0.947686\t0.774\n",
"47\t0.117640\t0.898519\t0.774\n",
"48\t0.121868\t0.886691\t0.761\n",
"49\t0.094232\t0.975407\t0.774\n",
"50\t0.095446\t0.992864\t0.765\n",
"51\t0.071117\t0.989448\t0.776\n",
"52\t0.074443\t1.045420\t0.760\n",
"53\t0.092074\t1.139346\t0.766\n",
"54\t0.104444\t1.074740\t0.766\n",
"55\t0.079712\t1.034687\t0.778\n",
"56\t0.064200\t1.077385\t0.775\n",
"57\t0.079801\t1.081241\t0.764\n",
"58\t0.074012\t1.148977\t0.775\n",
"59\t0.069318\t1.057150\t0.779\n",
"60\t0.066116\t1.079945\t0.785\n",
"61\t0.057789\t1.200273\t0.783\n",
"62\t0.054620\t1.227744\t0.781\n",
"63\t0.082043\t1.052702\t0.782\n",
"64\t0.059303\t1.055774\t0.785\n",
"65\t0.046304\t1.231521\t0.771\n",
"66\t0.060480\t1.226312\t0.769\n",
"67\t0.046170\t1.159201\t0.778\n",
"68\t0.059823\t1.118133\t0.778\n",
"69\t0.057867\t1.215457\t0.774\n",
"70\t0.045398\t1.440445\t0.780\n",
"71\t0.055527\t1.173359\t0.778\n",
"72\t0.026502\t1.198999\t0.788\n",
"73\t0.050406\t1.329501\t0.783\n",
"74\t0.047807\t1.365044\t0.780\n",
"75\t0.071096\t1.466850\t0.742\n",
"76\t0.081313\t1.081146\t0.781\n",
"77\t0.050600\t1.198028\t0.791\n",
"78\t0.042069\t1.241070\t0.792\n",
"79\t0.053071\t1.252994\t0.784\n",
"80\t0.049959\t1.222919\t0.783\n",
"81\t0.029138\t1.209314\t0.789\n",
"82\t0.025282\t1.262562\t0.793\n",
"83\t0.029588\t1.304021\t0.800\n",
"84\t0.031792\t1.316379\t0.776\n",
"85\t0.025328\t1.497033\t0.768\n",
"86\t0.029323\t1.330743\t0.794\n",
"87\t0.041144\t1.392384\t0.775\n",
"88\t0.028810\t1.442146\t0.768\n",
"89\t0.021767\t1.563584\t0.776\n",
"90\t0.029792\t1.423503\t0.778\n",
"91\t0.039070\t1.344595\t0.778\n",
"92\t0.035106\t1.303546\t0.782\n",
"93\t0.039416\t1.443949\t0.772\n",
"94\t0.027232\t1.367880\t0.785\n",
"95\t0.026759\t1.472693\t0.765\n",
"96\t0.033403\t1.563091\t0.777\n",
"97\t0.041169\t1.195002\t0.780\n",
"98\t0.032048\t1.313511\t0.782\n",
"99\t0.026892\t1.345648\t0.774\n"
]
},
{
"data": {
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\n",
"text/plain": [
"<Figure size 432x288 with 2 Axes>"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
}
],
"source": [
"epoch_list, train_loss_list, valid_loss_list, acc_list, y_hat_list, y_true_list = \\\n",
"simple_fit(100, net_basic, F.binary_cross_entropy_with_logits, opt, train_dl, valid_dl)"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": []
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": []
},
{
"cell_type": "code",
"execution_count": 107,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"epoch\ttrain loss\tvalid loss\taccuaracy\n",
"0\t1.371970\t0.696539\t0.500\n",
"1\t0.696707\t0.696480\t0.500\n",
"2\t0.697074\t0.696417\t0.500\n",
"3\t0.695681\t0.696226\t0.500\n",
"4\t0.695758\t0.695596\t0.501\n",
"5\t0.693720\t0.695053\t0.502\n",
"6\t0.694791\t0.690298\t0.516\n",
"7\t0.688263\t0.675530\t0.544\n",
"8\t0.674950\t0.666396\t0.560\n",
"9\t0.670432\t0.659084\t0.579\n",
"10\t0.677925\t0.655983\t0.571\n",
"11\t0.656405\t0.650133\t0.586\n",
"12\t0.638581\t0.645817\t0.591\n",
"13\t0.655663\t0.648113\t0.588\n",
"14\t0.644254\t0.636351\t0.595\n",
"15\t0.630278\t0.639689\t0.593\n",
"16\t0.619500\t0.635785\t0.596\n",
"17\t0.606352\t0.630704\t0.598\n",
"18\t0.598676\t0.624586\t0.604\n",
"19\t0.592306\t0.626076\t0.702\n",
"20\t0.573242\t0.634095\t0.717\n",
"21\t0.568907\t0.620779\t0.719\n",
"22\t0.565677\t0.622736\t0.727\n",
"23\t0.587092\t0.604220\t0.725\n",
"24\t0.560995\t0.602932\t0.713\n",
"25\t0.572560\t0.618692\t0.690\n",
"26\t0.574700\t0.641713\t0.716\n",
"27\t0.566129\t0.612188\t0.709\n",
"28\t0.543026\t0.638103\t0.718\n",
"29\t0.551711\t0.609380\t0.735\n",
"30\t0.532072\t0.618821\t0.719\n",
"31\t0.521952\t0.598805\t0.731\n",
"32\t0.528623\t0.596957\t0.740\n",
"33\t0.538127\t0.597971\t0.750\n",
"34\t0.525686\t0.624572\t0.749\n",
"35\t0.523117\t0.610410\t0.746\n",
"36\t0.509817\t0.586393\t0.737\n",
"37\t0.511274\t0.563802\t0.745\n",
"38\t0.506470\t0.586676\t0.746\n",
"39\t0.500257\t0.566416\t0.751\n",
"40\t0.491141\t0.678903\t0.719\n",
"41\t0.495457\t0.706104\t0.712\n",
"42\t0.478790\t0.576873\t0.756\n",
"43\t0.496459\t0.591434\t0.762\n",
"44\t0.484647\t0.567143\t0.752\n",
"45\t0.454350\t0.652034\t0.736\n",
"46\t0.467685\t0.631881\t0.762\n",
"47\t0.441062\t0.628231\t0.764\n",
"48\t0.432558\t0.645268\t0.766\n",
"49\t0.432982\t0.593906\t0.760\n",
"50\t0.408090\t0.635339\t0.738\n",
"51\t0.398988\t0.588624\t0.744\n",
"52\t0.389442\t0.611914\t0.746\n",
"53\t0.373924\t0.687262\t0.735\n",
"54\t0.419359\t0.606331\t0.743\n",
"55\t0.357737\t0.575221\t0.766\n",
"56\t0.364890\t0.552775\t0.752\n",
"57\t0.363465\t0.540843\t0.763\n",
"58\t0.359347\t0.597735\t0.764\n",
"59\t0.345149\t0.615227\t0.731\n",
"60\t0.351536\t0.565720\t0.755\n",
"61\t0.344474\t0.574307\t0.775\n",
"62\t0.321339\t0.552784\t0.759\n",
"63\t0.323181\t0.504611\t0.767\n",
"64\t0.369851\t0.563915\t0.773\n",
"65\t0.346979\t0.514322\t0.770\n",
"66\t0.319618\t0.599161\t0.762\n",
"67\t0.310739\t0.566852\t0.777\n",
"68\t0.318942\t0.679680\t0.752\n",
"69\t0.340984\t0.578580\t0.763\n",
"70\t0.317372\t0.571931\t0.774\n",
"71\t0.318382\t0.586695\t0.774\n",
"72\t0.298995\t0.573917\t0.768\n",
"73\t0.295511\t0.591484\t0.775\n",
"74\t0.301912\t0.560778\t0.778\n",
"75\t0.310328\t0.564150\t0.768\n",
"76\t0.298854\t0.520424\t0.780\n",
"77\t0.285616\t0.587342\t0.774\n",
"78\t0.280010\t0.622988\t0.758\n",
"79\t0.304257\t0.551934\t0.772\n",
"80\t0.290606\t0.548367\t0.779\n",
"81\t0.266198\t0.616557\t0.769\n",
"82\t0.266748\t0.573087\t0.772\n",
"83\t0.272947\t0.586215\t0.763\n",
"84\t0.262585\t0.597090\t0.766\n",
"85\t0.263206\t0.598995\t0.763\n",
"86\t0.269885\t0.560366\t0.781\n",
"87\t0.259418\t0.615895\t0.781\n",
"88\t0.249674\t0.687953\t0.762\n",
"89\t0.247300\t0.655393\t0.763\n",
"90\t0.248695\t0.593479\t0.769\n",
"91\t0.246898\t0.646350\t0.766\n",
"92\t0.257592\t0.609962\t0.777\n",
"93\t0.220078\t0.670860\t0.767\n",
"94\t0.263447\t0.647673\t0.754\n",
"95\t0.239727\t0.702018\t0.755\n",
"96\t0.222175\t0.687992\t0.767\n",
"97\t0.223623\t0.682237\t0.762\n",
"98\t0.214033\t0.720977\t0.753\n",
"99\t0.240869\t0.622681\t0.773\n"
]
},
{
"data": {
"image/png": 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H329nLQ0K1wOvAi8AEviNE/T4zDaTthZW/BOAEcAIM5De+s1tcvfhWdfZ/GY9m9he0VwUF8GEfmFYzcYG67rdEiFAnKCT2um53bDudfjxMTBbwWWHvd/AGTd3dMmUAz9C4hdw0UtgOIUeaSIlVBaAd0hHl+TEkRK+uhMCY+DMe9rmfBWnwtJbwGSFDW/C2tfU9sNjIbgX5O9Xv6/nPAR+XVWASF4NPc46/n23gGjtg7KFEHdLKV9s4/IcVXx8vNy4ceOxf9DtBqQ6yaB+PkRKXG431Q4H1Q4XSDfC7cTttGNzOKiy2amsqsJqy8OzKhNraTKe+77Eu/QADmFhoxzA744+7DT2xx0xjMCgECL8rZRXO0nMLGV3VilBPhb+Orkf04Z0xWDQwaFdrXkZfngI+p4PF78E714MfhEw94uOLhk47fBqPBSnwBXvwcBLOrpELbfpXfjmXvjzOgjq2dGlOTF2/g+W1LR/B1wMl/4XPHxa/vnCJEhdC4NngtGsegHvXAC5u+HmVeAZAIlfwr7voGC/Wt/thMmPw5l3gqMK/t0Pep8LMxce16EIITZJKeOPut5xBIVUKWV0qz58HFodFNqalJC5BbZ/jExaBbm7ETWBJkOEs9MVTYbogsU3BJ+gcDYVerKywI+ALj3569SBjO8bWq/nkF9ezcG8CuIi/RvtbWgtJCW8dgZ4BsL1y1WX+4dH4PdX4b4/1B9hR1r/pqpYPfwhMBpu/vWEpQWO29tTIG0dnPVXmPRwR5em/Tmr4bVRYPaGobPhh4chbCDMToCAFlR9TjssGK/SlyF9YerTkPo7rHoWZrytAsWRXE5wVKi00SHfzocNb8FfdoNP64dyWxoUWpo+anQfx/HZU58Q0G04dBuuvoiqYkjfCFlb6Zazk67ZO6FkB6LcBuVwKYAH2ItMpH8YwjZLGIFdYvDyDSAlM4fiogKqpYF/iiFURE9iWOxAzo/tQoinUf2SePh1bOVhr4SKPAjs3nFlaInsHZC/Fy58/vD31e8CWPOiSts09odYV0kGvHE2RI2CCX+HiLiG61SXqRZk12GNv98Ue6WqEKLHwvBrVFpg33Lod37Lt9FRipJVQDBaYMuHMOEfYDye6uMUsHGhOu6rP1Mt9dABsOR6SLgKblqhWv6HHPgJynNV8Dhk9fMqIJz9N9i5BD64TC0fenXTv4dGExj96y+Ln6fSoVs/hHF3t+khNuZ4zmrruhinK88A6HOu+kdNxJQSHJUqD1uSAQUHMOTvx5y0B3NuKsa037BQSQTeRHr542+o5MLK9ZD+JqmpoYhvbbhFOQYk0mhB+ISDbxfVSgnoriro4N6qFeIdergSdFar7mnmFsjZqbr6Ay8B/1ZcWiIl7FiiWknlOXDOg3Dm3Sq36rDBL0/Drs9hypOqe93RdnwKBhMMmn54WWS8+n72fnP0oPD7a1BVBMlr4I2zYMA06DURfMJV6233MtjyAdjL1DZv/lWlpkB9V7+9Akg4866G217/hvoOL39XlWnl0/DLv6Dv1JO/t7DzM/X/5Mdh+XzY/z30v6Bjy9SeqorVuek5AXpNUsv6nAuX/gc+nqPO81l/UctzdsHiq8Bpg9xdMPkJ9fe36jkYfDmc8wCcfS+s/Y/6m7zgmWMrS2g/1ZDY9A6MvbPdx6GaDQpCiDIar/wF4NkuJTqdCAEWb/UvIBq6j8EERAFSSn7dn09mcRUXxEWox4RKCXl7kHuXE5C8iQPlFpbmm8i2GQl2ltHHWE4vWUZEyQYsiV8g3HXmL1t81f4cVeCuc18niw/Yy+G7f0DUGaoc9gq1LGwQjLmt8a6wlGpw6+cn1SB9xBDVM/rpMbV81E3w/YMqD+ofBR9fDfHXw3n/BwjI3Az5+1Re3zf86N9V1jb47gEwe8LgK1SFY/E+tu/b7VaVV+9zwSvo8HKDEfqep3K3TjuYmpgxVlmo/vAGz4Tzn1F/xGtfh91f1tmWWQWcfufDF7fDp9fBdctUq/GXf8HKp9R6Fm8YeePhz1UVw+oXoc8U6D5GLTvrr2oQ88BPtY2JY1aWrQJWeweVHUsgarQ6ptUvwOb3TlxQOBRsbSUw6aGm13M5Vcs+pPfx73P1C+qcTX68/nc74CLVUFj5tGpo+YSr3wGrP/S5XJWzslAFBaufShkBmDxg3D2tL0/8PPjfn9QMyl4Tj+vQjqbZoCCl9G3XvXdiQgjO7ht65EIIG4AIG4DfWTAcGOqW7MgoYfWBfBbsy2NTShFOtyTa38LMvgbG+BfS25BFgC0NIYxqto3ZC0L6qPRGQHcoPAiJS1WlmL5RBQqzVeUp1y9QleCAi1WFbPJUFfqmd1WF7xUCF78Mw64GYYBNi1SO84+fwD8arvkcuo+DFU/Cmpdgz9fqj8lVrY7JNB9G3qBazj5hDb8IlwN+/bdKq3gFq/TE/25UedwR18KE+fXzq81J/R1KM9Qf8pH6Xaha+Clrmv6j2vCWStWdeZfq+U38B5x9n0qbledCRT50iVW9NQDphs9ugB8fVZXDyqdgyFVQVQjf/E3NKOl9LpSkw9d/BVuxmlFyyJDZ6rh/eVq1SFuajnG7VSps7WtwcCWM/BNc+FzLPtsaObtUGuSC51TwG3qVOtelmWp2THtyOeHre1QQAvU9NTUL5/sHYN1/1WBw3TTOscrZpRoEcbNUY+hIFzyrLir78k7w7wYFB9QkhpizwK+bOp+gxg3aaqbWgGnQ7Q2VeWhnrR5o7ignzUBzBympdPDD7hy+3ZHFr/vzsddcgOdnNdEn3Jc+YT70DvNhamwXIgO9jrKxDPXLv3GRqgzrihoNI65TrSHLEdvJ3qmCQvwN9Wdi/PEzrP2vCkjdx6p01dr/wvbFqoXtF6Eqe4uXqlBddqgogLJMiLsSzn9aDcCm/q4q8G0JKpBMeVJ1w4/WGv7qbtj+Mdx3oGEvw14Jz/RUufwLngVbqRp/iBqlKjp7JbwYC93iYc4nze+nrm/uU4EVVA9ixtvqD3fhVDX1MH6eGlyWbpV6G3tH/c9v+QC++LOqUGYuOvpAYlkOvH+pqqR9I9Q0xgM/wLRX1bG1hc3vweb3VaokpI8Kemtehnv3qUqu4A94Zbg6nrPva9k23S7I3Kq2Z/Vr2WfslSro7v1GtbJ3LFE9wD+tbJhCyUmE/45TDRtHlRoM7nve4fddDkjfoH5HU35XKUJ7uTovkx6GuCvUeo4qWDBRpXxv/a3p87HpXdXLAzW+MuH+w+9t+QCKUlSj4iRKC7b77KOO0tmDQl02h4u92WXsyixlV2YJ+3PL+SO3nIIKOyaD4NJh3bh1Qi96hTY+hU5Kycp9eSz4bguR5PDnsyKJ8Teqyia0b7113W6JBIytmU6bf0D1MMpzVerKUQHCqLrUJo/D6aIjZWxWLezMzdD9TJj61OGWW+4eNc5RlqXyrAMuhuf7q5b5jLcaL0fCbLXNmDNVj8ZpU7NJLnxeBYhv74N5yw+nd1rCaYeEK1XPYvobhwcfS9LhzXPUGMKAi2HKP5sepN+aAMvuBs8gNU01amTj60kJH10BSavUVNtBl6nU2AczVA9o3rdqrOJ4OKrghViozFeTG2a8rc5BaD+4esnh9d65SE2rveoTNa4ljJD6mzqWAz+q8zTgYug5HvYuV42PoiTVc531fuMt8COPNWG2Goi/4FkY9SfY/olKoUx/A4ZcWX/d9y5RKcibV8EncyFvL1y1WAX/xC/UlE97mSpn16Hqd9zirVKcmVth2isqqB4K8ocGl5sr3+I5qtK/4j11Hk5yOih0YulFlbz1axKLN6RS7XTTI9ibLv5WuvhbCfX1INjbgr+nmc+3ZLD2YCHRQV5U2p0UVzr488TeXDqsG7/uz+PnPbnsySqjvNpJhd2J2WhgUFc/hkYFMKZnMOcOCG//ay7cLtj8rhrbqCyEYXNUb2PDW6qX4hsBeXvApwuUZ6tKqm4Lsa6tH6kZP9YAlTKLGAK/PAMlaWqbXWLhhu/bruyFSSr1FDXq6OtmbVfjMqUZMOpmGH+fmlZb18aFsOweNd5R90K8ykJYMEH1vIZeVTMLbpuaGXXuo9BtROP7dNjUnPi6vb0Nb6kgMP0NNY03e4daPn0BDJl1eL3dX6nyghrYtwaoQGLxUem5zG1Qknp4/ciRqre35iXVCr/w3yo9U5GvXof0UQ2EQ/Z8A4tnq0HbM2ta5G43vHWOalzcvvFwD3b3MjX4e/6zcMZNUJ4HC8+Dwj/U+55BaiygzxTVI6s7LdlRpSr3P36C4XNVL2n0baoBcjRSnlQ9gaPRQUEjv7yaD9emsi+3jOwSG1nFVeSX22tTTsHeFu46tw9XjoymotrJY1/tYunWw/cJign2Ynj3QPw9zfh6mKi0u9iWXsyOjBJsDjdDogJ4bNoghkapP7KSSgcZxVX07+Lb9sGiqljl39e9AdIFI+bBxAdUxZm4VOXzHTa4c3P9qYJ1ud2QsUlVlocqIHtFzXYXwJUfQK9z2rbcx6KyUN36YPP76rjG36/SGl5Bqrf1xllqssDV/2uYPsneqa4jcNpUcAsfrFrZlfkqrTX5ifq3+XA51PrluXDTSpUmcTlVWsgnDG74QaXBvrxDpVtuXw8eRwwx5u5WQSN3twpmvSapytfirSrMrG1qYDR6zOHAWJGvUkIHV9bfVsQQuO5rtQ9HlbrWxOwJt6yufz6T16iLv8beAcOvVcHo7XPVWNgtqw+PyxSnqiDaY7wKBM2N1zhs8Om16vsKj4Ubf1JjbqcZHRS0RkkpKa92UlThINTXA09L/W7vqn15JOVXcHbfUHqEND77x+Fy8+XWTJ5evoe8smrO6hNCRnEVB/PUuET/Lr7cNakP5w3q0mxwkFKSWlhJmK+1QTmaVJKuWreBMfWXu91qeVMzi47mZGr1Ze9Qs8WSVql0R/RoFTDKsuC235se3K0oUBXpoRa0rVTNhvn9VTUW8KeV4B2s3vvlWTU5wGBSgWbuFyrN8tkNcOVH0P/Cw9t1u9t2GqTbpdKJFTW3zHDZ1cyzmHEw51PVm1jxT5j7pUo/Henja+rPCANV/p4TWl8mp10NUg+4GIJ6tH47J7GTIigIIaYCLwFG4C0p5dNHvH8d8CyQUbPoVSllEwlhRQeFk0d5tZNXft7Ptzuy6Rvuy7DoAPw9zSxcncTB/Ar6hvswNTaCMT2DGRYdQHGlg305ZezNLmNjSiEbkosorLBjNRs4u08oUwZ1oX8XX/w9zfh7qd5Jp71flJRq/GPvN6oFm7MLLl9U//qLlkrfBIvOVymcuUtVvn3BBFUB9jtf5elH3Qwpv6kK+ra1J/6eTFsT1P2A+pynehf9zofL32l8XaddjaEcmhXmFaTSZlqzOjwoCCGMwD5gMurWcxuA2VLKxDrrXAfESylvb+l2dVA4+bnckq+2ZbJoTRI7Mkpw1zTC6/6qRQd5MTImiGHRAezLKeP7XTlkl9rqbScy0JML4yK4aHBX+nXxxeZ0YXO48DAZ8bN2soBhr2w4C+xYbPsYPr9JpVyytqrppLetUz2H5f9Q01sBLvmPGrfpCGteUpMHzF5w+4bWXWypNelE3ObiaEYBB2oe3YkQYjFwCZDY7Ke0U56xZubTpcO6UVLlYH1SIdvSignz86BPmC99w30I9vGo95nHpg1iV2Yp6UVVlNocFFfa+e2PAt7+NYk3fjnYYB8+HiYiAz2JCvKiV6gPvUK96dfFlwERfpiNp9CdR1vqeAICqEHi3F2q4gW44v3DqaTJj6sprsWpajC4o4y9U40N+ITpgNCB2rOnMBOYKqW8seb1NcAZdXsFNT2Fp4A8VK/iHillWnPb1T2FzqWows4PiTnkltmwmo14mI3Y7C4yiqtIL6oipaCC5IIKHC71e2w1GxgSGUDPUB/yyqrJKbXhcLm5dFg3ZsVHEeht4Y+8chauTuLH3TkM7ubPOf3DmTQgjHC/029wsR63S11wZfVrOLvG7VaD1McbfLST1smQProcOO+IoDBKSnlHnXWCgXIpZbUQ4hbgCillg+kfQoibgJsAoqOjR6SkpLRLmbVTk9PlJr2oip2ZJWxMLmJTShEZxVWE+XrQxd9KRbWTDclFeJjUlNrNqcVYTAYm9A0lMUv1ToSAW8f34i+T+2KHd8kSAAAgAElEQVQ6HXsaWqd3MgSFMcCjUsrzal7/HUBK2egE4JoxiEIpZbP3NNA9Ba019maX8f7aZNYnFXLB4AiuHt2dEB8PpJTszy3n7V+T+HhjGqN7BvHy7GFYzUZ+TMzh1/35TOgXyrQhXTvXGIZ22jkZgoIJlRKahJpdtAG4Skq5q846EVLKrJqfpwP3SylHN7ddHRS09vLZpnQeWLoDD5ORKrsLu8uNl8VIpd3FlIHh/HP6YEJ9PY6+IU07CXX4QLOU0imEuB34DjUldaGUcpcQ4nFgo5TyS+BOIcQ0wAkUAte1V3k07WhmjIhkUDc/nvtuH92DvbgwLoK4bv4sXJPEc9/vY8oLvzBrZDRDowIYFh1AiI8HLrfELSUeJoPuSWinBX3xmqa1wIHcMh75chfrkwprB7Xriu3mxz8vHcyQqA5+spumNaHD00ftRQcFrSPZHC52ZZayPb2YMpsTo0HgdEk+XJdCfnk1c8fE8NcpffG1NnGrjSO8syaJj9an8sENZxB2us9+0jqUDgqadgKV2hw8u3wvH6xLwSgEg7r5MyI6kJExgYzsEUSIT8OxiK+3Z/HnjzYDcMHgLvxnThM3rtO0NqCDgqZ1gO3pxXy7M5tNyUVsSy+m2qluPtgr1Juz+oQyc0Qksd382ZhcyFVvrSOumz9je4fw8k/7eeOaEZw3qEsHH4F2uurwgWZN64ziIgOIi1TjCnanmx0ZJWxILmTdwQI+Wp/KO78lM7ibP2lFlXQL8OTNufH4WE38kJjDQ0t3MrpnMP6eLUs9HS+7041bSqzmk/9ZANqJo3sKmnaClFQ6WLo1g4T1qRRW2Pn0ljF0D1Z3ot2eXsylr63horiujOwRxO6sUlIKKjAaDFhNBrwsRkJ9PQj3sxLh78nYXsEEerfyjrBApd3J7AVrSSms5C+T+3LVqGh90d5pTqePNO0k5nbLBrcV/79vdrNglbrPk7+nmZ6h3rglVDtcVNid5JVVY3OodJTZKBjfN4yLh0TgdEkO5JWTlFdBoLeFARG+9Av3ZWh0AB6mhr0At1tyyweb+HF3DnGRAWxNK6ZvuA+PThvE2F5t9Exh7aSjg4KmnWIcLjcbkgvpEeJNFz9rg+sepJSUVjlJKqjgmx1ZfLE1g5zSagBMBkF0sBeFFXaKKx0ARAV58uCFA5kyMLzetp76djdv/HKQhy8ayLwzY/g+MYcnv04krbCKuWO68/fzBzT7fItKu5M3VyXx895c5oyKZuaIyPZ/Ap923HRQ0LTTnMst2ZFRgo+Hie7BXpiNBqSU5JRWsyW1iBd+3Me+nHLG9Q5hamwXquwuUgsreX9tClePjuaJS2Jrg4XN4eKZ5XtZuCaJniHe/HP6YEbGBNZLKVXanSzblsVz3+8lt6yaqCBP0gqrGBoVwMMXDyQy0BN7zcB6twBPfTHfSUYHBU3r5JwuNx+sTeH5H/ZRanPWLp86qAuvXjWs0TGE3/7I595PtpFZYsPLYiQu0p+u/p7syixlf24ZbgnDogN48MIBDI8O5H+bM3jq2z3kl1fX286w6ADuPKcPE/qFNhkcKqqd7MgoYUd6CUHeFsb3C2106m5jpJQ66BwjHRQ0TQOgyu6izObAy8OEp9mI8SipnjKbg5/35LIltZjNqUVkl9gY2NWPuMgARsYEMq53SL0KudTm4OvtWbjcEovRQEmVg3d+SyajuIrYbn7Edw8i2NtCoLeF3FIbB/LK2Z9Tzh955biPqH6GRPpz7oBwLoiLoFeoT4Oy7cku5eGlu9idVcrkgeFcPKQr4/qEnJ7P0GhjOihomtZhHC43n2/O4J3fkkkrqqSspqdiENA92JteoT4M6urH0KgA4iL9ySqxsWJPLj/vVcEI1LO+z+4bSkywN92DvVi5N5eFa5Lxs5o4u28oK/bkUmpzEubrwQMXDtB3sj0KHRQ0TTtp2BwuiirtBHpZjnpdRFZJFd/uyOabHVlszyipHacAmD0qir+d159Abwt2p5tV+/J4+ef9bE8vYVzvEP5+QX8CvSy43JJKu4uk/HL+yKsgp9RGbDd/zuwdQrcAzwZlO5BbTlJ+BT1CvBkY4XdaDpzroKBp2inP7ZZkldpIzq8g2MdC/y5+DdZxudW9p55dvpeyamcjW6H2Fuignv3taTbickuqnW6ySqrqpbECvcyM7RXC6F7BjO4RRO8wnxb3QCrtTtYnFeJrNTGie1C99z7ZmEbC+lTumtSHCf3CWvgNtB0dFDRN61Ryy2z8vDsXUM8J9zAb6RHsTY9Qb7zMRvbllrHmQAGbU4twuyUmowGzQRAV5EXfcF+6B3uxP7eM1fsL+O2PfLJKbAAEe1uIDvbCz2rG12pCCIHN4cLmcCGEwNtixMtiIqO4ks0pxdhdqmfz2LRBXDs2BoBvd6j7XJmNBqqdbs4bFM5DFw0kMrDljz/dnVVKnzCfVl9kqIOCpmlaK0kpSS2sZN3BQtYnF5JdYqPM5qDM5kQCHiYDVrMRKVWaqtLuwt/TzLg+IZzZO4QP1qbwQ2IO953Xj2HRAVy3cAOx3fxYdN0oPliXwqs/H8AlJdOHduOGs3rQN9y3ybLYnW5e/Xk/r638g/lT+/Ons3u26ph0UNA0TesgDpebez/dxhdbMzEbBTHB3nx6yxgCvNStSTKKq3htxQH+tzkdm8PNyJhAPC0mbHYXbikZ1NWPUT2CCfPz4NEvd7Ers5TLhnXjkYsH4e/Vuntj6aCgaZrWgVxuyeNf7WLtwULeuX4kEf6eDdYpqrDz0fpUvtuVjRACT7MBtxt2ZJRQ5VBjICE+Fv5v+mCmHOcddHVQ0DRNO0U5XG52ZpSwP6ecSQPCCG7hRX3N0bfO1jRNO0WZjQaGRQcyLDrwhO9bXwaoaZqm1dJBQdM0Tat1yo0pCCHygJRWfjwEyG/D4pwqOuNxd8Zjhs553J3xmOHYj7u7lDL0aCudckHheAghNrZkoOV00xmPuzMeM3TO4+6Mxwztd9w6faRpmqbV0kFB0zRNq9XZgsKCji5AB+mMx90Zjxk653F3xmOGdjruTjWmoGmapjWvs/UUNE3TtGbooKBpmqbV6jRBQQgxVQixVwhxQAgxv6PL0x6EEFFCiBVCiN1CiF1CiLtqlgcJIX4QQuyv+f/EXzvfzoQQRiHEFiHEsprXPYQQ62qO+WMhhKWjy9jWhBABQoglQog9Ned8TCc51/fU/H7vFEIkCCGsp9v5FkIsFELkCiF21lnW6LkVyss1ddt2IcTw49l3pwgKQggj8BpwPjAQmC2EGNixpWoXTuCvUsoBwGjgzzXHOR/4SUrZB/ip5vXp5i5gd53X/wJeqDnmIuCGDilV+3oJWC6l7A8MQR3/aX2uhRDdgDuBeCllLGAEruT0O9/vAFOPWNbUuT0f6FPz7ybg9ePZcacICsAo4ICU8qCU0g4sBi7p4DK1OSlllpRyc83PZahKohvqWN+tWe1d4NKOKWH7EEJEAhcCb9W8FsA5wJKaVU7HY/YDzgbeBpBS2qWUxZzm57qGCfAUQpgALyCL0+x8SylXAYVHLG7q3F4CvCeVtUCAECKitfvuLEGhG5BW53V6zbLTlhAiBhgGrAPCpZRZoAIHcOIfENu+XgT+Bhx6wnswUCylPPTA3tPxfPcE8oBFNWmzt4QQ3pzm51pKmQE8B6SigkEJsInT/3xD0+e2Teu3zhIUGnvq9mk7F1cI4QN8BtwtpSzt6PK0JyHERUCulHJT3cWNrHq6nW8TMBx4XUo5DKjgNEsVNaYmj34J0APoCnij0idHOt3Od3Pa9Pe9swSFdCCqzutIILODytKuhBBmVED4UEr5v5rFOYe6kzX/53ZU+drBmcA0IUQyKi14DqrnEFCTXoDT83ynA+lSynU1r5eggsTpfK4BzgWSpJR5UkoH8D9gLKf/+Yamz22b1m+dJShsAPrUzFCwoAamvuzgMrW5mlz628BuKeXzdd76Eri25udrgS9OdNnai5Ty71LKSCllDOq8/iylnAOsAGbWrHZaHTOAlDIbSBNC9KtZNAlI5DQ+1zVSgdFCCK+a3/dDx31an+8aTZ3bL4G5NbOQRgMlh9JMrdFprmgWQlyAakEagYVSyn92cJHanBBiHPArsIPD+fV/oMYVPgGiUX9Ul0spjxzEOuUJISYA90opLxJC9ET1HIKALcDVUsrqjixfWxNCDEUNrluAg8A8VEPvtD7XQojHgFmo2XZbgBtROfTT5nwLIRKACajbY+cAjwBLaeTc1gTHV1GzlSqBeVLKVj+zuNMEBU3TNO3oOkv6SNM0TWsBHRQ0TdO0WjooaJqmabVMR1/l5BISEiJjYmI6uhiapmmnlE2bNuW35BnNp1xQiImJYePGVg+sa5qmdUpCiJSWrKfTR5qmaVqtU66noGma1h7255SRVlQJgEAwskcQPh6dr4rsfEesaVqHqna62JRSRP8ufgR5W+otv/HdjbjcksemDaJPuO9Rt7ViTy6bUoq469w+mI2tT3zszChh2qurcde5bGvG8Ej+fcWQVm1PSom6puzUc8pdvBYfHy/1mIKmNW9vdhnhfh4EeB39WTMOh4P09HRsNluD98qrnZTbnIT5eWBoppKTUtbegU1AoxVilcNFld2FzeHCLcFsFIT4eGA0qHWLKu1UVLswCHU3N18PE75WU6PbklJSUuWkvFrdGNXLYiTQy9zqiji/vBqH002wjwcAFXYnldUuwv08MB1DsJESiivt2F3uesd2IlmtViIjIzGbzfWWCyE2SSnjj/Z53VPQtNNMbqmNi19dTWxXP5bcMhZDIxVTld3FG6v+IL2oisv7WujRNZSYmJh6lWq1w8X+3HI8pCQi0Kteq76u4ko7aUVV1G1gBnlZ6OJvxWQ04HS5ySiuwlHlINBgwM/ThKfZSFaJDYvJQM8Qb0qqHDiKq+jp60GIjwdZJTaKKu14WEz0DPVuUK6Uwkq8HS66+3hgMgqyS2z4elmIDPQEwOZ043C6mwwqdZXbHDjyK4jw9yTUVwUFh8vN3uwy/D3NRAV5tfi7zyqpwllWjUCoYwv1Pqag0hS3W3Iwv4IwXw/8PM1NrielpKCggPT0dHr06NGqfemgoGmnmbdWJ2F3utmcWsySzelcER9V7/2Ve3N56IudpBVW4Ws1MaVbCNnVJqqLquga4InRIJBSkl5chRBgMRgoqrA3GhQqqp2kFVXhaTbiX1NZ2V1uCsvtlNqchPhaKCy343BJuvhbCfXxqK2kLSYDyQWVHMyvoNrpxtdqJtzPihCCqCAvvCxGMoqrKKp01O7b7ZakFFbicLmJCfaurSClhJxSGw6XG7vLjd2pbv0V4GkhMsizyV6OlJLsUhtmo4HgOsdnNhoI9rGQX1ZNqK8HVrOxwWfLbU5cbjc+VjNGg6CgvJq8smqCvS34e1pILqggKb+CHiHHHxiKKu1U2p0YhEez6wkhCA4OJi8vr9X70kFB045Bpd3JrsxSEjNLie3mx4juQW227YpqJz/uzuGiuK6tTjsUVdj5YG0KlwztSkZRFU9/u4fzBnbB38uMzeHigc938tnmdHqGepPwp9GMjAlk565Egn08KCyvpsrhIibYi/JqJxXVTroFeuJyS7JLbFQ7XHjUqRxtDhfJBRVYjAZigr3qVXxBXhYyiqvIrukN9ArzxstSv7rxtZrpHuRFSkElZpMgKtCzXqs+yNtCUaWD7BIbflYTJqOBnDIbNoeLHiHe+FoPt5jDfD2QEvLKq/HxMBHq64HTJckpteEukEQHeSGESmFVVLvwshjxshgprXJQaXcRGejVoEcV6uNBQbmd3NJqooMP9xYcLjeZxVWUVDkAVRF7W4xUVDvxs5rpGqCOo3uwF8kFlSQXVNIz1LvJwFRpd5JdYiPQy0JAIykwt5TklVXjZTHh3YKB7+Mdy9BBQeuUpJSkFVYRFeTZ7B9RSkEFqw/ksz2thG3pxezLKas3GHlFfCR/P38AgU2kVo7Fyz/v541fDpJZbOPWCb1ql1dUO1mw6iBJ+RXklNooqXLw3OVDiO3m32Abi9YkUWl38eeJvXG6JBe98ivPfb+XO87pzZ/e38S2tGLuOKc3t5/TGw+TquA9zEa6BXjiZzWRWljJgdwKJBJvDxNBXhacbklOSTWFlXYi/FV6xuFyk1xQgUAQE+LVoCXsaTHSK9Sb8monXhYjRkPjLWU/TzO9w3wwGUWDbQgh6BZg5UBuOTll1fh7mmtb4nUDwqF1u/hbCffzqHc+TQZBRnEVB/LKcbklDpe7zntqfx4mNR5xJFNNbyGvrBqfChNSytpekBvo4mfFy8NEaZWDUpsDT4uJqCCv2v37Ws1EB3qSUlhJdomNrgGeDfbhcLlJKajE6ZKUV1eSV2Yk3N+KX520V3GlA7vLXRts2psOClqnczCvnAeX7uS3Pwq4c1If/jK5b6Pr5ZbZmPrir1Q5XAR4mYmLDGDKwHDiIgPo18WXD9el8uavB/lxdy7PXzGECf1a/+RLm8PFJxvSMBoEz/+wlwn9QhkQ4YfT5eaOhC2s2JtLVKAX4X4eHMyrYMmm9AZBoczm4J3fkpk6qAt9a2buzB0Tw7u/J/PdrmzKq528cc0IzhvUpdEy+FrN9Ar1IaWgAocLImsqIbNR4Gs1UVzpoIufFbdUwdLpkvQM9a4NLkcSQjSovBvjaVGf//zzz7nsssvYvXs3/fv3r3nPRLCPBwXl1ZRWObCYDHTxb1i51t1nXcE1g73ZpTa8LEb8rFa8PUxU2p2UVjmpsDvpGmBtsrIN9fGgsNxOes1U1UPfU1d/a22vycfDRFcaL5O/l4UQu4v8mh5M3fEAt5SkFlTicksqsvaTmpbBkLHnkFJQQYiPBxH+VgDyyqo5sGsbby5bwiuvvHK0r/O46aCgdRout+S1FQd4dcUBPEwGxvUO4eWf9uNpNtZrmR/y5dZMqhwuPrt1DMOjAxtUHPPP788lQ7tyR8IW/v6/Haz628RWT4tctj2LokoHr141jEe/TOSej7fyxe1n8vhXify8J5f/mz6Yq86IBmDeovWs3JsLDKq3jffXplBqc/Lnib1rl90zuS9f78jCZBAsuWUsA7v6NVsOq9lI7zBfnG53vco+0NtCaUEFpTYnRRV2quwuugc3TAkdj4SEBMaNG8fixYt59NFHa5eH+XlQXOnA4XLTK9TnmFNrAV6WerOwXC5Xg2VNMRkN9A7zweWWmIwGTEbR7CysxnTxt9aMvVTSx+yLxaR+R7KKq6iwO4kO8mLpDzvZuHEjl0+fRlaJjfzyalxuia/VRIWtmnPOGsNl540/pv22lg4KWqfx9Y4snv9hHxcOjuCRiwcS7OPB3R9v5V/L9+BpNnDdmfVnayzZlM6QqIBmxw0GRPgxf2p/bnxvI9/tyuaiuK6tKtv7vyfTO8yHCwdHYDUZufG9jcx4/Td2ZpRy64RetQEBYGL/MFZ8sYuDeeX0DPUB1Bz/hauTGN83lMGRh3sQ/p5mvr3rLKxmY4suxHrsq10kZjb+WO9KuwuQSKkGiVsaAAd29eORiwc1u055eTlr1qxhxYoVTJs2rV5QeP6553j3vfcQBgMXXXABTz/9NAcOHOCWW24hLy8Po9HIp59+SlpaGs899xzLli0D4Pbbbyc+Pp7rrruOmJgYrr/+er7//ntuv/12ysrKWLBgAXa7nd69e/P+++/j5eVFTk4Ot9xyCwcPHgTg9ddf59tvvyUkJIS77roLgAceeIDw8HDuvPPO2jImJyczdepUxo0bx9q1axkyZAjz5s3jkUceITc3l0Xvvkdg94HsTM3h/x74G3t378LhdHL/Px6k/8xLefjhh6mqqmL16tXMnz+fjdt2kpyaTmZaKkEhwfz1jtv497//zbJlyygvL+eOO+5g48aNCCF45JFHmDFjRovORUvooKB1qHUHCyiuUmmJLv5Wwnw9jjlvanO4+GhdKhXVTu6Y1KfJ9TYkFeLjYeLl2cNqW5vPXzGEaoeLR79KJDrYi3P6hwOQmFnKnuwynrik+coM4Jz+YXQP9mLh6qRWBYWtacVsSy/hsWmDEEJw7sBwZsVH8fHGNKYN6cp9U/rVW39ivzBgFyv25tUGheU7s8kvt3PjWQ2nIYb4ND9jpaVMRoHDKTEfQ0BoqaVLlzJ16lT69u1LUFAQmzdvZvjw4Xz77bcsXbqUDevX4+XlRWGheojcnDlzmD9/PtOnT8dms+F2u0lLS2t2H1arldWrVwNQUFDAn/70JwAefPBB3n77be644w7uvPNOxo8fz+eff47L5aK8vJyuXbty2WWXcdddd+F2u1m8eDHr169vsP0DBw7w6aefsmDBAkaOHMlHH33E6tWr+fLLL3numX/xXsKn3D//Cc48ewIvvvYGtooyLph0FldcciGPP/44Gzdu5NVXXwVgz55H2Z+4nTc/+Zq+3YLZuv632v088cQT+Pv7s2PHDgCKioqO/wTUoYOC1mHeWZPEo18l1lsW4W9lysBwpgzqwhk9gpqdyldR7eSLrZm88vN+skrUhVeXjYikWyMDegBb0ooYEuVfL/1gNhp45aphXPTyah7+Yhdje4VgNRv5bHM6ZqNoUSVvMAiuGxvDY18lsjWtmKFRAQ3WcbjcCGj0eN77PRlvi5HLhnerXfbItIGM7hXEBYMjGsyKiQryoneYDyv25HLDOBUEEtanEh3kxZm9Qo5a3uY016J3uSVlNgf+nq2/SKwpCQkJ3H333QBceeWVJCQkMHz4cH788UfmzZuHl5ea/RMUFERZWRkZGRlMnz4dUJV9S8yaNav25507d/Lggw9SXFxMeXk55513HgA///wz7733HgBGoxF/f3/8/f0JDg5my5Yt5OTkMGzYMIKDgxtsv0ePHgwePBiAQYMGMWnSJIQQDB48mOTkZPw8zWxYs5Jff1rOu2+osQGbzUZqamqj5b3s0ksY0Su8wSD9jz/+yOLFi2tfBwYGtuj4W0oHBa1DJKxP5dGvEpkyMJzbz+lNTmk1mcVVrDmQz8cb03j39xRGdA9k4bUj8a+ZGeJ0uXnhx318tyuHnBIbZTVXsw6LDuCuSX2Y/78d/Lw7h2vGxDTYX5Xdxe6sMm4d33DswMNk5PFLYpn95lr+s/IP7jynN19szWBS//AWzyq6PD6K57/fx6I1Sbx05TAANqUU8tW2LLanF7Mrs5Rgbwsf3zym3sVQhRV2lm3PYlZ8VL1BWS+LienDIpvc3zn9w1i0JomKaifZpTbWHizkb1P7NXqhWlsxGkSL8vDHqqCggJ9//pmdO3cihMDlciGE4Jlnnmn0dhFN3YXBZDLhdh+eXXTkFdre3t61P1933XUsXbqUIUOG8M4777By5cpmy3jjjTfyzjvvkJ2dzfXXX9/oOh4eh3tkBoOh9rXBYMDpdNaW/bPPPqNfv/q9v3Xr1jXYnre3d6Ozttr7Fhr6LqnaCff5lnT+8fkOxvcN5ZWrhhEXGcDkgeFcOzaGBXPj2fLQFP41YzDb04uZteB38sqqKbU5uOHdjby24g8i/K3MGBHJ/VP78/4No/jfrWOZNTKKmGAvftyd2+g+d2SU4HJLhkU3bMUDjOkVzLQhXfnvL3/w/toU8svtzBjRdKV8JB8PE1eMjOLr7VnsyS7l/iXbmfH673xcM6PoqjOiKa92Mu+dDZRUqvnt5dVO7vt0G3anm2vGdD+m73BivzAcLsnqA/kkrEvFZBBcPiLq6B88CS1ZsoS5c+eSkpJCcnIyaWlp9OjRg9WrVzNlyhQWLlxIZaWa/VNYWIifnx+RkZEsXboUgOrqaiorK+nevTuJiYlUV1dTUlLCTz/91OQ+y8rKiIiIwOFw8OGHH9YunzRpEq+//jqgBqRLS9X4yvTp01m+fDkbNmyo7VW0xnnnnccrr7xSG9i2bNkCgK+vL2VlZS3axpQpU2rTTND26SMdFLQT6tONafz1k22M7hHMG9eMaHQ6o6fFyKyR0bx97UhSCiq54o3fuew/v7HmQD7/N30w799wBo9OG8StE3pxVp9QhBAIIZg0IJzf/yigoqYHUdeWVPWH01hq55AHLhyA2SB47KtEgrwtjO971OeR1HPd2BjcUnLBS7+yZHM6N5/dk00Pncunt4zlkYsHsWBuPKkFldz0/kYO5pUz8/XfWLkvj8cvGVQ7hbSl4mMC8fUw8d3ObD7bnM6UQeG1t2g41SQkJNSmgg6ZMWMGH330EVOnTmXatGnEx8czdOhQnnvuOQDef/99Xn75ZeLi4hg7dizZ2dlERUVxxRVXEBcXx5w5cxg2bFiT+3ziiSc444wzmDx5cu30V4CXXnqJFStWMHjwYEaMGMGuXbsAsFgsTJw4kSuuuAKjsfEpuC3x0EMP4XA4iIuLIzY2loceegiAiRMnkpiYyNChQ/n444+b3caDDz5IUVERsbGxDBkyhBUrVrS6PI3RN8TT2kxJpYNPN6Ux54zutXPP61q4OonHlyUyrncIb1wzokVXZ25KKWTeog0YDILX54xgTK+GudxDfvsjn6veXMd/rx7B1Nj6c/FveX8Tu7NL+eW+ic3u761fD/Lk17u5bmwMj047+iDzkR5aupP9uWU8fNGgRqd/frE1g7sWb8UgwNvDxH/mDOesPscWfA657cNNfLszGynhgxvOYFyf1o0n7N69mwEDBrTqs52F2+1m+PDhfPrpp/Tp0/RkhpNFY+dU3xBPO+Ge+nY3izekUVBh5/6ph1tfUkpe+mk/L/64n6mDuvDS7KFNXvB0pBHdg/j+nvEYDeKoLeGRMUH4Wk38tDunXlCQUrI5tYixzQSUQ64dG4PN4WJmK1MxT1wa2+z7lwztRn65nWXbM3l25hB6h/m0aj8AE/qF8c2ObKKDvFp0bFrrJCYmctFFFzF9+vRTIiAcLx0UOrG2HLBKzCzl441p+HuaeevXg8wcEUmvmumSH6xL5cUf9zNjeCT/mjH4mG8O1sW/ZbNLzFScdYwAABaYSURBVEYDE/qFsWJvLm63rB10zSqxkVtWzbDoo8/SMBsN3H5O+/7h3zCuR+2soeMxsV8YHiYDc8d0b9cB5s5u4MCBtdctdAb/396dx0dVn3sc/3yTAGGRRQigCavgAoIsUai7uNStYusGV69brXVBq1d7q15tXaqt1nurrdSlLrWtaxUVrVZ84YJaZQcREFlkCQIhYUmIkhDy3D/OSRxjlslMhiEzz/v1yos5h9+ZeY4/nCfnd87v+fk9hTS0sqiMk+5/n+F3vMX5j8/gf6csYcn66G5y1cXMuPP1RXRu24pJVxxKdqtMbp28EDNj5spN3DZ5Icfsl8M9Zw5tljLCDTnugO4UbatgfsGWmn1zVwev67vJ3FLl7NGG939xDBcfFn+CaWnDyK5+8falJ4U08+/lRYyd+CHrtn7N8Qf0oLBkOxPfWcZZD/2blUVlMb3n1MWFfLismGuO25d9cjpw/Qn78f7SIp74cCWX/30OvfZsx33jhu+SBUeO2jeHzAwxNeIppHlrNtMmK4P9ezZc4qEl6r5HdtxXCdnZ2RQXF3tiSAHV6ylEO3ejLj58lAbKK3fy2bpSpn2+kfunLqVft/Y8dsHBNeWAVxd/xWkTP+DSv81i0hWHNWld2h07q7jr9cXsk9O+phTDuaN689zMNdz+2iLat87kmZ+Mqqm1n2id27VmZJ8uvLVoA9cevy+ZGWLu6i0Mye1UU3PGfVteXh4FBQVx1eB3u4/qlddi5UkhhVVUVjHh6Tm8u2QjFWHJ4DH7d+e+ccPoGDFRqnfXdjwwfgTnPz6d65+fz4PnjfjOvYa1W77m4+XFnD48t+Y3/p1Vxs0vfcqKojIevzC/pvRBVmYGv/7hgVz2t9nccfqBUa2125x+ODyXGyct4LxHp3PPmUNZsHYr5zdxHkA6adWqVcyrdLnU40khhT383nKmLNrABd/rw6j+XRma14ncemqyHz6wGzeedAB3vr6YP727/FuVNgF+/doi3vh0Pc/NWsP944bRtX0brn1uHv9csI6rxwyoqRlUbUTvLky/6dikLF4+7uBeZGWIX76ykBN+P43yyiqG9WreUgDOpSpPCilqWeE2/vj2Mk4duhe3jW34MclqlxzRj9mrNvPA28s4b3SfmiGfLV9VMHVxISP7dOHTtVs56f73GZDTgVmrNnPzKQdwyRH963y/ZCSE6s89K78XI/p04aqn57K0sJSRfTwpOBeNhA6ySjpR0hJJyyTdUMff/17SvPDnc0lb6nof1zRVVcaNkz6hbevMRksWR5LEhDEDgjUEZhfU7H/1k3VU7KzittMG89pVh5PbuS1zVm/m7jOG1JsQdgf75HTgpSsP5e3rjo76sVbn0l3CrhQkZQITgeOBAmCmpMlmVlMW08yujWh/FVD/vHQXtadnrGbmys387syhTS59cGBuJ4b37szfP17FhYf2JSNDvDi7gP177sHgvTsiiZeuOIzC0u3kdWnX+BsmWZuszG8VoHPONazRKwVJEyTFcu19CLDMzFaYWQXwLDC2gfbjgWdi+BwXoaKyirvf+IzDBnTlzCYUdIt0/vf6sKKojA+XF7F84zbmrdnCGSPyaoaDWmdltIiE4JxrumiGj3oS/Jb/fDgcFO1AcS4QuepFQbjvOyT1AfoBb9fz95dKmiVplj8217ANJUFJ6bEH5cY8pn/ykL3o2r41f/1oFZPmFJAhGDs8thXFnHMtS6NJwcxuBgYCjwEXAksl3SXpu4Xpv62ub6T6ZseMA14ws531xPCImeWbWX5OTmzFw9JFYWlQQz6nY+wVM9tkZXLOwb2YungDz85Yw5H75tB9Dx+Tdy4dRHWj2YKpjuvDn0qgC/CCpHsaOKwAiKwqlgd8WU/bcfjQUbMoLCkHoEecX+Lnjg6e6y8uq+CMEbFPhHHOtSzR3FO4WtJs4B7gQ2CImV0OjAQaWi16JjBQUj9JrQm++CfX8f77ESSZj2KI39VSWBokhe5xXCkA5HZuy/GDetCpbSuOH9Sj8QOccykhmqePugE/MrNVkTvNrErSqfUdZGaVkiYAbwKZwONmtlDS7cAsM6tOEOOBZ80LrzSLwtLtZGWIPZth2cR7zjiIzV9VkN0q9kVFnHMtSzRJ4XVgU/WGpD2AQWY23cwWN3Sgmb0eHh+575e1tm+NOlrXqMKScrp1aNMspZQ7tWtVsz6ycy49RHNP4UFgW8R2WbjP7YYKS8vjHjpyzqWvaJKCIod2zKwKL4+x2yosLad7C12r1zmXfNEkhRXhzeZW4c/PgPRZhqiF2Vi6nRx/fNQ5F6NoksJlwKHAWoLHTEcBlyYyKBebHTurKNpW4VcKzrmYNToMZGaFBI+Tut1c0bbmeRzVOZe+Gk0KkrKBHwODgZpxCTO7OIFxuRhUT1zz2cfOuVhFM3z0N4L6R98H3iOYmRz7Ku8uYaonrvXwKwXnXIyiSQoDzOwWoMzMngROAYYkNiwXi+q6R36l4JyLVTRJYUf45xZJBwKdgL4Ji8jFrLCkHAm6dYh/NrNzLj1FM9/gkXA9hZsJahd1AG5JaFQuJoWl5XRt35qszIQuqOecS2ENJgVJGUCJmW0GpgG779qLzucoOOfi1uCvlOHs5Qm7KBYXpw0lPpvZORefaMYZ3pJ0vaRekvas/kl4ZK7JCku3e1JwzsUlmnsK1fMRrozYZ/hQ0m5lZ5UFs5n9cVTnXByimdHcb1cE4uKzqayCnVXmj6M65+ISzYzm8+vab2Z/bf5wXKy+maPgVwrOudhFM3x0cMTrbOBYYA7gSWE38s0ynH6l4JyLXTTDR1dFbkvqRFD6wu1GNtbUPfIrBedc7GKZ5fQVMLC5A3HxqR4+yvGk4JyLQzT3FF4leNoIgiQyCHg+kUG5pissLadT21Zkt8pMdijOuRYsmnsK90a8rgRWmVlBguJxMdpQ4nMUnHPxiyYprAbWmdl2AEltJfU1s5UJjcw1SWFpuc9RcM7FLZp7Cv8AqiK2d4b73G6ksKTc5yg45+IWTVLIMrOK6o3wdVS1mSWdKGmJpGWSbqinzdmSFklaKOnp6MJ2kcyMjaVe98g5F79oho82SjrNzCYDSBoLFDV2kKRMYCJwPFAAzJQ02cwWRbQZCNwIHGZmmyV1j+Uk0t3idaVU7KzyJ4+cc3GLJilcBjwl6YFwuwCoc5ZzLYcAy8xsBYCkZ4GxwKKINj8BJoaluTGzwmgDd7B9x07+9O5yHnp3OR2zszhq35xkh+Sca+Gimby2HBgtqQMgM4t2feZcYE3EdgEwqlabfQEkfQhkArea2b9qv5GkS4FLAXr37h3lx6ceM2P5xjLmrdnCJwVbeGdJIWs2fc3pw/bmf04Z5FcKzrm4RTNP4S7gHjPbEm53Aa4zs5sbO7SOfVZrO4tgItzRQB7wvqQDqz+r5iCzR4BHAPLz82u/R0oxM56buYZJc9eyT04HhvXqRI+O2Uz7vIgpi9ZTsPlrANq3zmRoXmfu+uEQjhjoVwjOueYRzfDRSWZ2U/VGOPZ/MsHynA0pAHpFbOcBX9bR5mMz2wF8IWkJQZKYGUVcLZqZMW1pEZ+vL+Wo/XIY2L0DJdsruWnSAv65YB39u7Vn8boSnpmxGoDWWRkcMaAbVx4zgPw+Xeif04HMjLryrnPOxS6apJApqY2ZlUMwTwGIZpxiJjBQUj9gLTAO+I9abV4GxgN/kdSNYDhpRbTBt1TTVxRz75QlzFy5GYA7X19M367tqKisorC0nF+cuD8/PTJYrmJlcRlfbtnO8N6dad8mmu5yzrnYRfMt83dgqqQnwu2LgCcbO8jMKiVNAN4kuF/wuJktlHQ7MCt8mulN4ARJiwjmP/zczIpjOZGW4jevL+bhaSvovkcb7hg7mKP36857n29kyqINbP16BxPPHcHw3l1q2vfP6UD/nA5JjNg5l05k1vgQvaQTgeMI7hNsBvYysysbPiox8vPzbdasWcn46LjNXLmJsx76iDNH5nHH2ANp29rrFDnndg1Js80sv7F20VZJXU8wq/kMgvUUFscRW1p4avoq/vLhF1Qn3e07dnLDi5+Q27ktt5022BOCc263VO/wkaR9Ce4DjAeKgecIriyO2UWxtViri7/iV68spLLKmLN6C/ecOZQ/vbOM5RvLePLiQ/zegHNut9XQt9NnwPvAD8xsGYCka3dJVC3cH99eSkaGuOyI/jw8bTnLCrfx+YZSfjQ81yeYOed2aw0NH51BMGz0jqQ/SzqWuuceuAgri8qYNHct547qzQ0n7c/D541kZXEZHdu24uZTByU7POeca1C9Vwpm9hLwkqT2wOnAtUAPSQ8CL5nZlF0UY4vyh7eX0ipTXH70PgCcMLgnb15zJJVVxp7to6oj6JxzSdPojWYzKzOzp8zsVIIJaPOAOiueprvlG7fx8ty1nDeqz7fKWPfasx39urVPYmTOORedJq3RbGabzOxhMxuTqIBasj9MXUqbrEx+etQ+yQ7FOedi0qSk4Oo3e9VmXpn3JRce1tcL0znnWixPCs1gZ5Vxy8uf0rNjNhOOGZDscJxzLmaeFJrBU9NXsWhdCbecOsjnIDjnWjRPCnEq2lbO795cwuEDunHykJ7JDsc55+LiSSFOd7/xGdt37OTW0wYj+TQO51zL5kkhDkXbynlxTgH/ObovA7p7JVPnXMvnSSEObyxYR5XBOQf3aryxc861AJ4U4vDq/HXs26MD+/XcI9mhOOdcs/CkEKN1W79mxspN/GDo3skOxTnnmo0nhRj985N1AJx6kCcF51zq8KQQo1fnf8mQ3E5e08g5l1I8KcRgVXEZ8wu28oOD9kp2KM4516w8KcTgtXDo6BS/n+CcSzGeFJrIzJg870tG9ulCbue2yQ7HOeealSeFJnp+1hqWbCjlrJF5yQ7FOeeanSeFJliz6Stuf3URo/vvydn5PmHNOZd6EpoUJJ0oaYmkZZK+s1qbpAslbZQ0L/y5JJHxxKOqyrjuH/ORxL1nHURGhtc5cs6lnoTVeZaUCUwEjgcKgJmSJpvZolpNnzOzCYmKozmYGY9+sIIZX2zinjOHktelXbJDcs65hEhk8f9DgGVmtgJA0rPAWKB2UtglPinYwowvNjXabmeVsbG0nPUl29lQsp0NJeVsKNlOeWUVxx3Qw+8lOOdSWiKTQi6wJmK7ABhVR7szJB0JfA5ca2ZrajeQdClwKUDv3r1jCuaj5cX85o3Pomqb3SqDnh2z6d4xm2G9OtOzUzZ7d8rmjJF5Xh7bOZfSEpkU6vr2tFrbrwLPmFm5pMuAJ4Ex3znI7BHgEYD8/Pza7xGVCw/ry/hRjSeUDIn2rTP9y985l5YSmRQKgMhHdPKALyMbmFlxxOafgbsTFUybrEzaZGUm6u2dcy4lJPLpo5nAQEn9JLUGxgGTIxtIiqwTcRqwOIHxOOeca0TCrhTMrFLSBOBNIBN43MwWSrodmGVmk4GrJZ0GVAKbgAsTFY9zzrnGySymIfqkkbQRWBXj4d2AomYMp6VIx/NOx3OG9DzvdDxnaPp59zGznMYatbikEA9Js8wsP9lx7GrpeN7peM6QnuedjucMiTtvL3PhnHOuhicF55xzNdItKTyS7ACSJB3POx3PGdLzvNPxnCFB551W9xScc841LN2uFJxzzjXAk4JzzrkaaZMUGlvbIRVI6iXpHUmLJS2U9LNw/56S3pK0NPyzS7JjbW6SMiXNlfRauN1P0vTwnJ8LZ9WnFEmdJb0g6bOwz7+XJn19bfjv+1NJz0jKTrX+lvS4pEJJn0bsq7NvFfhD+N32iaQR8Xx2WiSFiLUdTgIGAeMlDUpuVAlRCVxnZgcAo4Erw/O8AZhqZgOBqeF2qvkZ3y6Tcjfw+/CcNwM/TkpUiXU/8C8z2x84iOD8U7qvJeUCVwP5ZnYgQbWEcaRef/8FOLHWvvr69iRgYPhzKfBgPB+cFkmBiLUdzKwCqF7bIaWY2TozmxO+LiX4ksglONcnw2ZPAqcnJ8LEkJQHnAI8Gm6LoNruC2GTVDznjsCRwGMAZlZhZltI8b4OZQFtJWUB7YB1pFh/m9k0gtI/kerr27HAXy3wMdC5Vl25JkmXpFDX2g65SYpll5DUFxgOTAd6mNk6CBIH0D15kSXEfcB/A1Xhdldgi5lVhtup2N/9gY3AE+Gw2aOS2pPifW1ma4F7gdUEyWArMJvU72+ov2+b9fstXZJCNGs7pAxJHYAXgWvMrCTZ8SSSpFOBQjObHbm7jqap1t9ZwAjgQTMbDpSRYkNFdQnH0ccC/YC9gfYEwye1pVp/N6RZ/72nS1JodG2HVCGpFUFCeMrMJoW7N1RfToZ/FiYrvgQ4DDhN0kqCYcExBFcOncPhBUjN/i4ACsxserj9AkGSSOW+BjgO+MLMNprZDmAScCip399Qf9826/dbuiSFRtd2SAXhWPpjwGIz+7+Iv5oMXBC+vgB4ZVfHlihmdqOZ5ZlZX4J+fdvMzgXeAc4Mm6XUOQOY2XpgjaT9wl3HEqx/nrJ9HVoNjJbULvz3Xn3eKd3fofr6djJwfvgU0mhga/UwUyzSZkazpJMJfoOsXtvhziSH1OwkHQ68Dyzgm/H1mwjuKzwP9Cb4n+osM6t9E6vFk3Q0cL2ZnSqpP8GVw57AXOA8MytPZnzNTdIwgpvrrYEVwEUEv+ildF9Lug04h+Bpu7nAJQRj6CnT35KeAY4mKI+9AfgV8DJ19G2YHB8geFrpK+AiM5sV82enS1JwzjnXuHQZPnLOORcFTwrOOedqeFJwzjlXw5OCc865Gp4UnHPO1fCk4FosSV0lzQt/1ktaG7EdVZVMSU9EPOtfX5srJZ3bTDEXSOrchPZjwmfPG2ozQNK8+KNzLpgq71yLZGbFwDAASbcC28zs3sg24TPcMrOq774DmNlFUXzOxPijjdkYoAj4OIkxuDTiVwou5YS/OX8q6SFgDrCXpEckzQrr8P8you0HkoZJypK0RdJvJc2X9JGk7mGbX0u6JqL9byXNULA+x6Hh/vaSXgyPfSb8rGH1hHhDePz0cJIdksaG23MlTZHUXdI+BBOzfh5e/RwqqaekV8K6+fMljQrfM0vSY+H5vSEpOzH/dV2q86TgUtUg4DEzGx5W1rzBzPIJ1h04vp71NDoB75nZQcBHwMX1vLfM7BDg50B1grkKWB8e+1uCCrX12Rwe/zBQXY5kGjA6LG43iWBdjOUEM5Z/Z2bDzOzfBOuCvGVmQ4GRfLOGxH7AfWY2GPiaFl462iWPJwWXqpab2cyI7fGS5hBcORxAkDRq+9rM3ghfzwb61vPek+poczhBmQXMbD6wsIHYngn/fIqgmBsEpQumSFoA/BcwuJ5jjyZIJphZZUQV3GVmtiCK2J1rkCcFl6rKql9IGkiwMtuY8DfsfwF1Da9URLzeSf333MrraFNX+eL61FVbZiLBymFDgCvqia+h4yPr/DQUu3MN8qTg0kFHoBQoCUsOfz8Bn/EBcDaApCHUfSVS7Zzwz/HAh+HrTsDa8Mb4BRFtS4E9IrbfAS4LPyczXIHNuWbjScGlgzkE5ZU/Bf7MN1/EzemPQK6kT4Drws/aWk/bdpJmAJeHbQFuBV4C3iOoilntFeDs8Ab0ocAE4PvhMNMsYP/mPhGX3rxKqnPNIFzgJcvMtofDVVOAgRFLRDrXIvi4o3PNowMwNUwOAn7qCcG1RH6l4JxzrobfU3DOOVfDk4JzzrkanhScc87V8KTgnHOuhicF55xzNf4fJivM/jiXmPkAAAAASUVORK5CYII=\n",
"text/plain": [
"<Figure size 432x288 with 2 Axes>"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
}
],
"source": [
"epoch_list, train_loss_list, valid_loss_list, acc_list, y_hat_list, y_true_list = \\\n",
"simple_fit(100, net_basic, F.binary_cross_entropy_with_logits, opt, train_dl, valid_dl)"
]
},
{
"cell_type": "code",
"execution_count": 67,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"epoch\ttrain loss\tvalid loss\taccuaracy\n",
"0\t0.658045\t0.671267\t0.659\n",
"1\t0.652980\t0.669551\t0.676\n",
"2\t0.651719\t0.668037\t0.669\n",
"3\t0.649410\t0.666265\t0.676\n",
"4\t0.645394\t0.664330\t0.692\n",
"5\t0.645252\t0.662575\t0.681\n",
"6\t0.641279\t0.660533\t0.698\n",
"7\t0.636218\t0.659120\t0.671\n",
"8\t0.629247\t0.656899\t0.677\n",
"9\t0.623807\t0.654257\t0.703\n",
"10\t0.619121\t0.652034\t0.703\n",
"11\t0.618074\t0.649751\t0.717\n",
"12\t0.610844\t0.647621\t0.716\n",
"13\t0.601699\t0.646370\t0.696\n",
"14\t0.595913\t0.643815\t0.716\n",
"15\t0.587498\t0.641450\t0.736\n",
"16\t0.577872\t0.639797\t0.743\n",
"17\t0.571490\t0.638065\t0.745\n",
"18\t0.566312\t0.638226\t0.739\n",
"19\t0.561791\t0.637432\t0.740\n",
"20\t0.556113\t0.633740\t0.758\n",
"21\t0.534192\t0.633511\t0.755\n",
"22\t0.541909\t0.634215\t0.754\n",
"23\t0.524961\t0.634212\t0.755\n",
"24\t0.515958\t0.635336\t0.756\n",
"25\t0.503872\t0.634158\t0.769\n",
"26\t0.504490\t0.634829\t0.774\n",
"27\t0.494999\t0.636360\t0.768\n",
"28\t0.493730\t0.640360\t0.758\n",
"29\t0.488740\t0.638435\t0.761\n",
"30\t0.474786\t0.636142\t0.771\n",
"31\t0.468697\t0.639209\t0.773\n",
"32\t0.474395\t0.638434\t0.775\n",
"33\t0.454396\t0.640421\t0.774\n",
"34\t0.459810\t0.643354\t0.770\n",
"35\t0.456054\t0.642142\t0.768\n",
"36\t0.446133\t0.645068\t0.763\n",
"37\t0.443928\t0.638287\t0.776\n",
"38\t0.423286\t0.649250\t0.769\n",
"39\t0.434491\t0.645325\t0.770\n",
"40\t0.430204\t0.641156\t0.777\n",
"41\t0.419782\t0.652996\t0.770\n",
"42\t0.429173\t0.637892\t0.775\n",
"43\t0.405471\t0.639552\t0.775\n",
"44\t0.414111\t0.644627\t0.771\n",
"45\t0.415027\t0.638239\t0.776\n",
"46\t0.409829\t0.635334\t0.772\n",
"47\t0.405076\t0.637748\t0.775\n",
"48\t0.394109\t0.633053\t0.772\n",
"49\t0.386970\t0.636771\t0.770\n",
"50\t0.395037\t0.632543\t0.772\n",
"51\t0.400225\t0.630145\t0.772\n",
"52\t0.394049\t0.627286\t0.773\n",
"53\t0.394742\t0.646423\t0.761\n",
"54\t0.396491\t0.624830\t0.776\n",
"55\t0.395750\t0.621041\t0.772\n",
"56\t0.378376\t0.630463\t0.770\n",
"57\t0.387218\t0.621423\t0.781\n",
"58\t0.378060\t0.615496\t0.770\n",
"59\t0.369797\t0.623715\t0.772\n",
"60\t0.367281\t0.617218\t0.771\n",
"61\t0.377425\t0.613702\t0.770\n",
"62\t0.371295\t0.610784\t0.776\n",
"63\t0.361208\t0.611896\t0.775\n",
"64\t0.361268\t0.612056\t0.783\n",
"65\t0.365679\t0.610537\t0.784\n",
"66\t0.352907\t0.611373\t0.787\n",
"67\t0.361158\t0.609819\t0.787\n",
"68\t0.347360\t0.613273\t0.770\n",
"69\t0.349129\t0.607440\t0.784\n",
"70\t0.344639\t0.612261\t0.779\n",
"71\t0.349366\t0.609736\t0.781\n",
"72\t0.340633\t0.608269\t0.778\n",
"73\t0.337523\t0.609756\t0.782\n",
"74\t0.337851\t0.603425\t0.776\n",
"75\t0.338317\t0.600124\t0.780\n",
"76\t0.331778\t0.600510\t0.785\n",
"77\t0.345647\t0.597805\t0.785\n",
"78\t0.332167\t0.597638\t0.778\n",
"79\t0.327097\t0.605721\t0.776\n",
"80\t0.332425\t0.590131\t0.780\n",
"81\t0.322174\t0.593386\t0.768\n",
"82\t0.329464\t0.587970\t0.780\n",
"83\t0.327846\t0.587624\t0.766\n",
"84\t0.307773\t0.583129\t0.781\n",
"85\t0.317225\t0.583281\t0.780\n",
"86\t0.307033\t0.581399\t0.778\n",
"87\t0.300173\t0.582370\t0.780\n",
"88\t0.311444\t0.581488\t0.778\n",
"89\t0.306976\t0.577578\t0.774\n",
"90\t0.299719\t0.578659\t0.778\n",
"91\t0.302968\t0.577078\t0.778\n",
"92\t0.295295\t0.573874\t0.778\n",
"93\t0.279673\t0.574223\t0.780\n",
"94\t0.294916\t0.571024\t0.778\n",
"95\t0.296918\t0.568598\t0.776\n",
"96\t0.279232\t0.571082\t0.779\n",
"97\t0.281773\t0.566349\t0.775\n",
"98\t0.284984\t0.562295\t0.774\n",
"99\t0.279957\t0.557542\t0.780\n"
]
},
{
"data": {
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3798k+3333Xe59dZbeemll2oauAEeeughkpOTkVIybNgwYmNjeeGFF5g7dy5Go5Hg4GBeeOGFJsnDMc3SwC2EGAHMAvTAx1LKl+tJcz3wDNpggx1Syn+cbp8XUgN3Y1msduasP8y7q5MoLLcy9dIwHh0RhbNJjepWGiClNvbE5Kr18DpRUSoc+g2Sf9O6ExcdPbvjGV21m3/hEUBqwUU6tE4OvaZpwWfnfCjPPb6Ne5AWnDxCtN5oQmgdC4rTtADU7z5o27vOYS6krrMtwUU1zkIIoQcSgSuBVGATMElKuadWmo7At8AQKWWBECJASpl9uv22hGBxTLHFyhsrEvnszxQi/Fx57fp4erQ7h2MjlNanJFPr0VV4GJx9tBu/s7fWjVmnPz51TXEqlGZrQcjsqXV+KMvRbvIlGdpUNeGXa92GD62BDR9oP/VO0HkEdL1e6zSRuRMyE7Su1cXp2rZSakHDPQjyDmhtLGGXadVp4ZeB2fPMg4WUUJGvBSmPENXofwoXW7DoBzwjpRxevfwYgJTypVppXgESpZQfn+l+W1KwOObPpFz+NT+BjKIKro4LZmr/MBU0lAtf4RFtDIqz16nTOOzaz2M96SpLYevn8Oe72rxqQgdturK310t0iQjVSi1CaAMWTS7VVXI6QGhVZEWp2mh9hLber5PWW0+p42LrOhsC1C4DpwKXnJCmE4AQ4g+0qqpnpJTLTtyREOIO4A6Adu3OYvTsBerSSD+WPngZ7/x6gHkbj7J4Rzrxbb14eFgnLut4Ft1EFeVcOpOR7Cd2t3Zy03pu9b4djq6HlD+0thCbRRv4KUR16aHgFPszaMc1uWmN/PmHtIChr77FSakGOJ6l5ggW9V2xE4s3BqAjMAgIBdYJIWKllHVGg0kpPwI+Aq1k0fRZbX4eZiNPjIrmwSs6sWBrKh+vS+amTzYytlswT14djZ+bU3NnUVGajsGkVWuFV/fi2bsXAmt9E7bbtAGnNgsgtTuHqB40qqu+nflEVI93OaRVn1WVah0EjM5adZvZS83u3AjNESxSgba1lkOB9HrSrJdSWoFkIcR+tOCx6fxk8cLj6mRgSr8wru/VlvfXHOSDNUms3p/Ds6NjGNu9gcFkitJS6A2g9wBOM++ayVWbV6sgRQssJhctSFSWaFVkIk2bswyhBRqji1ZlZnRRpY/TaI5gsQnoKIQIB9KAicCJPZ0WAZOAz4QQfmjVUofOay4vUGajnhlXdmJ0fBCPLtjJg99sZ83+bJ4bG3vuRoUrysXG2Vu7+euMx8eVSKl1/a3I00oo0qG9ynK0SSP1Jq0t5FiJRafXgoreVN3oX92tWEptWafX3jO5VreftGzn/QyllDbgPmA5sBf4Vkq5WwjxnBBidHWy5UCeEGIPsBr4l5Qy73zn9UIWGeDON3f0ZcaVnfgxIYOrZq3jt8QcWspcX4py1gxOdQcgCqG1jXi116ab96t+AFmbWK29w2DWJql02LUgYq1g0IjRLP/hm+oJO1OhJIO33nyde+69Tyul5CVpPb3yDlX3HkuHwiO4ublCURrpBxK4btwYbcr7EwwaNIj6OuWcan1za5ZBeVLKn4GfT1j3VK3fJTCj+qWcgkGvY/rQjvSP9OPBb7Zx86cbiQv15J5BkQyLDkSnU0VqRWmQzqCN83A5+aFTk6bcxrzlfzJ8wi013YrnLb2bV//zsjYa3mY5PklnZREgtHTVk2cGu0rmv/eMNuOxwUkbn3Kssd5m0aamryrT2lMu8NLJhZ075Yz0bO/NyhkDeXl8V4oqrNw1ZwuDXlvDu6sOkFl08vw0iqKcmesmTOCnn5dS6dCB3kjK4SOkp6cz4PKBlFqsDB01nh5DxtD1ion8sCEFguK1korQQVA8KRVuxF55I7gHU1ElmTjtLuIuvYIbpt5JRXm5NmgxN1F7Tk3Ofq20YrdqU/HnHWTuf1+la3RnYqO78Ogj/wLAbrczdepUYmNj6dq1K2+++SYAb7/9NtHR0cTFxTFx4sQm/yzUdB8thJNBm3/qup6hLN2VydcbjvDaikTe+CWR/pF+XBMXzPCYNni6qHYN5SK1dKZW5dOU2nSFkSdNIFHD19eXPn36sGzZMsaMGcO8efO44YYbEEJgNptZuHAhHh4e5Obm0rdvX0aPHXu8u6cQ2tQnQgfugXzwv69w8QkiYc9SEhIS6NGjh/ZQMO/w4z22Kgq1RwpU5JOelsqjL7zFluXf4O3uxLBJ97Loy//SNrwjaalH2bVrFwCFhVon0Zdffpnk5GScnJxq1jUlVbJoYQx6HdfEBzP3jr789q9B3DMoksN55TyyIIFeL/7CbZ9vZm1iDg6HattQlDMxadIk5s2bB8C8efOYNGkSoD0h7/HHHycuLo4rrriCtLQ0srJO/fCxtWvXMnnyZADi4uKIi4vTenc5e2lPu/TrqAUvoyv4dWRTciGDhgzFP7o/hjbR3Djxetb+8RcRPgYOJSVy/22TWbbwGzxcnWv2eeONNzJnzhwMhqYvB6iSRQvW3teVh4d35p/DOrErrZifEtJZsDWVlXuziPB3ZfqQjqrbrXLxOE0J4FwaO3YsM2bMqHkKXo8ePQD46quvyMnJYcuWLRiNRsLCwuqdlry2Bh9+Jqq78wrd8c4qQmg9rly8wdkH74592PHXGpYvXcJ777/Ht998zafvv8WSJUtYu3Ytixcv5vnnn2f37t1NGjRUyaIVEELQNdSTx67qwh8zh/DmDfGYDXoe+nY7CalNX1xVlJbEzc2NQYMGccstt9SUKgCKiooICAjAaDSyevVqDh8+fNr9XH755Xz11VcA7Nq1i4SEhNOmv+SSS/jtt9/Izc3Fbrczd+5cBg4aRG5RGQ5Xf669ZTrP//sVtu5JwqEzcvToUQYPHswrr7xCYWEhpaWlZ3/ytaiSRSvjZNAzrnsoQ7sEMvT133hy0S4W3tMfveo5pSinNGnSJMaPH19THQVw4403cs0119CrVy+6detGVNRpnlAJ3H333UybNo24uDi6detGnz59Tps+KCiIl156icGDByOl5KqrrmLMmDHs2LGDadOm4XBoj0V+6T+vYXcNZPLVgykqKkJKyUMPPYSX12nm5moE9QzuVuyH7Wk8MG87z4+J4aZ+YYA2TXpWsYX2vq6n31hRzgM1RXnTOpuJBFU1VCs2Oj6Y/pG+vLJ8P9klFpYkZDD09d8Y/Noa1ibmNHf2FEW5gKhg0YoJIXhuTCyVVgfD3lzLvV9vxd1sIMLfjenztnE0v7y5s6goygVCBYtWroO/Gw9e2RGTXseL42JZMv0yPp7SC4dDcueXW6iosjd3FpVWrqVUlTe3s/0cVbBQuGdQJBufuIIbL2mPXicI83Nl1sTu7M0s5rHvE9SYDKXZmM1m8vLyVMA4S1JK8vLyMJsb/0Ao1RtKqdfgqAAeuqITb/ySSHqhhVeuiyPMTzV6K+dXaGgoqamp5OSoNrSzZTabCQ0NbfT2qjeUckpSSr7fmsYzP+7Gancwc0QUN18a1vDAIkVRLhqqN5Ry1oQQXNszlF8eGkjfCF+e+XEP/5qfgNXuaO6sKYpynqlgoTSojaeZ2VN788DQjszfksodX2ymvMrW3NlSFOU8Ous2CyFEByBVSlkphBgExAFfnPi8bOXiJoTgoSs74e/uxFM/7OKGD9fTra0X5VV27A4HN/ULo2d77+bOpqIo50hTNHAvAHoJISKBT4DFwNfAVU2wb+UCM7lve/zdnXhi4S5SC9JxMRkoq7LxY0IG9w2O5P4hkRj0qsCqKC1NUwQLh5TSJoQYB7wlpXxHCLGtCfarXKCGx7RheEybmuUSi5WnF+9m1q8HWHsghzHxwfi7mwnwcCI22BNnk74Zc6soSlNoimBhFUJMAm4Grqlep56w04q4m428cX03BncO4KkfdvHMj3tq3nNzMjCqaxDX9gyld5i36kmlKBeppggW04C7gBellMlCiHBgThPsV7nIXBMfzKiuQRSUV5FTWklaQQVLd2XyY0I632w+yqiuQcya2E1VUynKRahJx1kIIbyBtlLK00/Ufg6ocRYXrvIqG5+sS+b1XxIZ2y2Y16/vpqZEV5QLxJmOs2iK3lBrgNHV+9oO5AghfpNSzjjbfSstg4vJwP1DO6LTCV5dvh+zUc9L47uqKilFuYg0RTWUp5SyWAhxGzBbSvm0EOK8lyyUC9+9gyOxWO28syqJnJJK7hsSSfd2Wnfb3elFzFl/BH93J2Zc2amZc6ooyomaIlgYhBBBwPXAE02wP6UFm3FlJ1ydDLy/Oolx7/9J7zAtWGxKKUAnwCEhNtiDYbV6WymK0vyaoqXxOWA5cFBKuUkIEQEcaIL9Ki2QEIK7Bnbgz8eG8tTV0WQWW8gpqeTJUV3Y+MQVdAny4PGFuygoq2rurCqKUouaSFC5oOxOL2LMu38wKi6IWRO7I6VkR2oRKbll9OvgS6BH46dYVhTlZOezgTsUeAfoD0jgd+ABKWXq2e5baX1igj25f0hH3lyZiI+rifWH8tmbUVzzflQbd4bHtOHuQR0wG9VgP0U5X5qiGmo22hQfwUAI8GP1OkVplHsGdyAm2IPZf6QA8MLYWBbf15+ZI6PwdjEx69cDjH3vD5KyS5s3o4rSipx1NZQQYruUsltD6841VQ3VsuSXVZFRVEF0kMdJXWxX78/mn9/uwGK188SoLgzs5E+wpzM6NXZDUf6281YNBeQKISYDc6uXJwF5TbBfpRXzcTXh42qq973BnQP4efplPDBvG08s3AWAi0lPfKgXsyZ1I8BdtWsoSlNripJFO+BdoB9am8WfwHQp5ZGzz96ZUyWL1sfukGw7UkBiVimJWSV8vfEIV3QJ4P0bezZ31hTlonHeShbVQWH0CQd/EHjrbPetKKej1wl6hfnQK8wHAH93J15dvp9luzIYERsEQE5JJZ/+kUwHfzeu6BKAl0v9pRVFUU6vKaqh6jMDFSyU8+yOyyNYkpDB//2wm34RfqQVVnD7F5tJK6wAtODSL8KXh4d3pltbr5rtpJSsO5BLlyAP/N2dmiv7inJBO1fTf6qWRuW8M+p1vHJdHPllVdz+5Wau+++f2B2SH+8bwOL7+nPn5REkZZcy4b9/Mmf9YaSU5JdVcfecrUz5dCP3z91KSxl3pChN7VyVLNR/nNIsYkM8ufPyCN5fc5D4UE8+mtKrZiBfXKgXd1wewYPfbOfJRbtYdyCHrUcKKSyvYmhUAL/uy2bFnqw6D3ZSFEXT6AZuIUQJ9QcFAThLKc9VIKqXauBWjqmyOVi5N4shUQH1DtxzOCRvrzrArF8P0DHAjTdv6EbnQHdGzlqH1e5gxUMDMRmOF7rtDkmJxUphuRUfNxMeZvVsL6XlONMGbjXdh9JqHc4ro42nGSeDFlDW7M9m6uxNPDmqC7ddFsGutCKeWLSLhNRCjv2bmAw6RsS04YbebekX4avGdigXvfM5zuJvE0KMAGYBeuBjKeXLp0h3HfAd0FtKqSKB0qTa+7rWWR7UOYDLO/kz69cDZBZZmP1nCj6uJu4dFImPqwkPZyM7UwtZuC2NxTvSCfFyZnS3YMZ2C6FzG/dmOgtFOT/Oe8lCCKEHEoErgVRgEzBJSrnnhHTuwBLABNzXULBQJQulKSRmlTBy1jrsDskNvdry+FVd8HSpW+1ksdpZvjuT77em8XtSLnaHpFd7b96e1J1gL+dmyrmiNM4FWw0lhOgHPCOlHF69/BiAlPKlE9K9BawEHgYeVsFCOV9W7M7E09nIJRG+DabNLa1k8fZ03vglEbNRz4c39aBne59Tps8usbBgSxqbU/IZEduGMd1C6rSPKMr5diEHi+uAEVLK26qXbwIukVLeVytNd+BJKeW11Y9trTdYCCHuAO4AaNeuXc/Dhw+fj1NQlJMcyCqpGdPxzOgYJvVuV6c9Y1daEbN+PcCqfdnYHZIAdyeySyoJ9HBi8iXt8XQxUlppo8RiI62ggqMF5aQXVmDQ6XBzMuDhbOC+IR0Z2Mm/Gc9SaYku5GAxARh+QrDoI6W8v3pZB6wCpkopU04XLGpTJQuluRWWV3H/3G2sO5BLbIgHjwyPIj7Ui9dW7GfOhsN4ORu5vldbJvRqSwd/V9YeyOXD3w7y58HjU6kZdILdlpJkAAAgAElEQVQ2nmba+bgQ4uWMQ0JppZU9GcUUlFlZfF9/IvzdmvEslZbmQg4Wp62GEkJ4AgeBY/NPtwHygdGnCxgqWCgXArtD8sP2NN74JZHUggrMRh1VNgdT+oXx0JWd8HQ+udttdrEFIQTuZgNOBt1Js+wCpBdWMOrtdQS4m1l476W4mAxkl1h4eek+AtzNPHhFR/V8D6VRLuRgYUBr4B4KpKE1cP9DSrn7FOnXoEoWykWm0mbn6w1H2JlaxK2XhRMT7HnW+1x3IIcpn25kbLcQLu/kxzOL91BeZcNql0QGuPHG9fHEhXo1vCNFqeWC7TorpbQJIe5De263HvhUSrlbCPEcsFlKufh850lRmpqTQc+0/uFNus/LOvrz0BWdeOOXRBZuS6NHOy9euS6e9MIKHpmfwLj3/+TugR24b0jkKUsZO44WsiO1kKvjgk85Bbyi1EcNylOUi4jDIXl52T6CPc3c1C8MfXUjelGFlWd/3M33W9No5+PCc2NiGNQ5oGY7KSX/W3eI/yzbj90hMRt1TOjZltsvi6Cdr0tznY5yAbhgq6HOFRUsFAX+TMrlyUW7OJRbRu8wb7q19aJLkAc/78xg5d5sRsa24Y7LI5i78QgLt6UhEDx5dRdu6tu+3rYSpeVTwUJRWqlKm52P1yWzfHcm+zJLqLI5MOoFT1zVhZsvDasJClnFFmYuSGD1/hxGdQ3ipWu71sx7ZXdINqfks3RXJnsyinl4WGf6hJ96/Ihy8VLBQlEUbHYHB3PKcHXSE+p9cnWTwyH5aN0hXl2+H09nI14uRpBQWGElv6wKJ4MOD2cjJRYrH93Ui8urx3n8eTCX91cf5JYBYQyJCjzfp6U0IRUsFEU5Y5tT8vly/WFsDqlNG23UM7CzP4M7B1BhtXPTJxs5mF3KC+Ni+etgHgu3paHXCfRC8NGUnnXaR5SLiwoWiqI0maJyKzfP3sj2o4UY9YK7Bnbgpr7tmfbZJpKyS/l0am/6R/oBWjWYSX/yeJFKmx2jTqdm6r3AqGChKEqTKq208dkfyYyIDSIyQBtFnl9WxT/+t56UvDJigj05kl9OTkklod7OjOoaxMiuQeSUVPLD9jRW7s3C392Jl8fH1QSWxrA7JMm5pUQGqJl+m4IKFoqinBe5pZU8Mj+Biio77XxcCPIys+NoIesO5GJzaPcXH1cTw2PasP5QHsm5ZUzs3ZaZI6Pwcvl7Yz1sdgcPfLOdJQkZPDKiM/cMijwXp9SqXLCD8hRFaVn83Jz4dGrvk9YXllexen82Xi4mBkT6YdTrsFjtvLkykf+tPcR3W1KJDvKgZ3tvwv1csdodVNkdVNkcWKwOLFY7ns5GbrykHQEeZhwOySPzE1iSkEF0kAevLNuPQHD3oA7NcNatjypZKIpy3u1JL2bprgw2pxSw7WgBFqujzvsmvQ4no46yShsGvY6JvdtSXmVn/pZUZlzZiXsGdWDGtztYvCOdR0Z05u6BHeq0kUgpOZpfQYi3c83ARaV+qmShKMoFKzrYg+hgDwCsdgdFFVZMBh0mvQ6jXldzgz+cV8b7qw/y9YYj2BySewd34P4hkQgheOP6eCTwyrL9zN+SynU9QxkaFchvidnM3XiU5Nwy+kb48Pak7gS4mwEotliZu+EIVruDEG9nQrxc6N7OC6NePVOkIapkoSjKBS+1oJx9GSUM7RJQpwRhszv4fmsa3205yqaUgpr1vcO86Rvhy//WHcLdbOSN6+NJzCrl3VUHKCi31tn3FV0C+d+Unq12BLtq4FYUpVVJzi3j9wM59I3wpWOg1lNqX2Yx98zZyqHcMgAGRPoxc2QUHfzdSCus4IftabyzKonXJsRzXc/Q5sx+s1HBQlEUBa3L70e/HaRXmE/NCPRjHA7JDR/9xb7MEn55aCBtPM1UVNl5a2UiBr3ggaGdWvxjb1WwUBRFOQMpuWWMmLWWfhG+/HNYZx6Yt42DOVpJpHs7L979Rw9CvJxP2i6tsIKEo4Vc2sEPT5eTH2p1sVDBQlEU5QzN/iOZZ3/cg06Av7sTr0/oRlGFlUcXJGDQC14eH8fwmMCado31h/K4a84WCsutGPWC/pF+jOkWzDVxwRgussZyFSwURVHOkMMhuX/eNow6wdPXxOBd/WCo5Nwy7vlqK3sziunezot/XtmZ9MIKnli0k3Y+Ljw5Kpr1h/JYsjOD1IIKOvi78siIKIZFB1JaaWPz4QJSCyq4Ji7obw9APF9UsFAURWkCVruD7zan8u6qA6QXWQC4rKMf7/6jR80z1aWUrNiTxSvL9nEwp4xgTzOZxRaqB7Dj5WLkoSs6ceMl7RoseVRU2XE2nb/nqatgoSiK0oQqbXa+3XSUwnIrdw/qUO9N32Z38N2WVH7dm0V0sCeXhPvg5mTgP8v28efBPDoGuPHxzb1o7+tas43FauflpfvYkVpIcm4ZheVW7hwYwWMju5yX81LBQlEU5QIhpeSXPVk8siABH1cTC+/uj6eLEbtDcs9XW1ixJ4u+4b5E+LuSU1LJij1ZfHBjD0Z2DTrneVMjuBVFUS4QQgiGxbTBy8XE5I83cOeczXxxyyX8++e9LN+dxVNXR3PLgHAAqmwOJnz4F4/MT6BLkAdhfq519lVisbLtSCGezkbiQj3P22BCVbJQFEU5jxZtS+PBb7YT1cadfZkl3DognP+7OrpOmtSCcka9/TshXs68NL4r+zNL2J1exJYjBexJL65pC+ng78p1PdsyrnsIbTzNjcqPqoZSFEW5QM1aeYA3VyZyVdc2vDupR70PhPp1bxa3fn78nuZq0tM11JM+4b70DvMmvbCC+VtS2ZRSQMcAN36ZMbBReVHBQlEU5QIlpWTz4QLiQj1xMpy659Ove7OosNqJCfakvY9LvUElObeMrGILfSN8G5UX1WahKIpygRJC0DvMp8F0Q7sENpgm3M+V8BPaNc6Fi2uooaIoitIsVLBQFEVRGtRi2iyEEDnA4bPYhR+Q20TZuVi0xnOG1nnerfGcoXWe99895/ZSSv+GErWYYHG2hBCbz6SRpyVpjecMrfO8W+M5Q+s873N1zqoaSlEURWmQChaKoihKg1SwOO6j5s5AM2iN5wyt87xb4zlD6zzvc3LOqs1CURRFaZAqWSiKoigNUsFCURRFaVCrDxZCiBFCiP1CiCQhxMzmzs+5IoRoK4RYLYTYK4TYLYR4oHq9jxDiFyHEgeqf3s2d16YmhNALIbYJIX6qXg4XQmyoPudvhBAX5vMuz4IQwksIMV8Isa/6mvdr6ddaCPFQ9d/2LiHEXCGEuSVeayHEp0KIbCHErlrr6r22QvN29f0tQQjRo7HHbdXBQgihB94DRgLRwCQhRPTpt7po2YB/Sim7AH2Be6vPdSbwq5SyI/Br9XJL8wCwt9byf4A3q8+5ALi1WXJ1bs0Clkkpo4B4tPNvsddaCBECTAd6SSljAT0wkZZ5rT8DRpyw7lTXdiTQsfp1B/BBYw/aqoMF0AdIklIeklJWAfOAMc2cp3NCSpkhpdxa/XsJ2s0jBO18P69O9jkwtnlyeG4IIUKBUcDH1csCGALMr07SEs/ZA7gc+ARASlklpSykhV9rtIlRnYUQBsAFyKAFXmsp5Vog/4TVp7q2Y4AvpGY94CWEaNTj91p7sAgBjtZaTq1e16IJIcKA7sAGIFBKmQFaQAECmi9n58RbwCOAo3rZFyiUUtqql1viNY8AcoDZ1dVvHwshXGnB11pKmQa8BhxBCxJFwBZa/rU+5lTXtsnuca09WNT3PMIW3ZdYCOEGLAAelFIWN3d+ziUhxNVAtpRyS+3V9SRtadfcAPQAPpBSdgfKaEFVTvWprqMfA4QDwYArWhXMiVratW5Ik/29t/ZgkQq0rbUcCqQ3U17OOSGEES1QfCWl/L56ddaxYmn1z+zmyt850B8YLYRIQatiHIJW0vCqrqqAlnnNU4FUKeWG6uX5aMGjJV/rK4BkKWWOlNIKfA9cSsu/1sec6to22T2utQeLTUDH6h4TJrQGscXNnKdzorqu/hNgr5TyjVpvLQZurv79ZuCH8523c0VK+ZiUMlRKGYZ2bVdJKW8EVgPXVSdrUecMIKXMBI4KITpXrxoK7KEFX2u06qe+QgiX6r/1Y+fcoq91Lae6touBKdW9ovoCRceqq/6uVj+CWwhxFdq3TT3wqZTyxWbO0jkhhBgArAN2crz+/nG0dotvgXZo/3ATpJQnNp5d9IQQg4CHpZRXCyEi0EoaPsA2YLKUsrI589fUhBDd0Br1TcAhYBral8MWe62FEM8CN6D1/NsG3IZWP9+irrUQYi4wCG0q8izgaWAR9Vzb6sD5LlrvqXJgmpSyUc+fbvXBQlEURWlYa6+GUhRFUc6AChaKoihKg1SwUBRFURpkaDjJxcHPz0+GhYU1dzYURVEuKlu2bMk9k2dwt5hgERYWxubNjWrkVxRFabWEEIfPJJ2qhlIURVEa1GJKFoqinFtSSjalFFBaaQXAoNPRN8IXk0F952wNVLBQFKVBmUUWHlmQwNrEnDrrn7kmmqn9w5spV8r5pIKFoij1slqtHDl6lMKSMgrLrdzcxcD93dvVlCTyy6ow6ovYu3dvne0cUiIQiPqmsGuk8io7xRXWmhnw9DrwdXVCr2vCg7RwZrOZ0NBQjEZjo7ZXwUJRlDrKKm18+NtB2pnKiAj2w+ATSvsgI229nXEy6mvSpRaUU1RuJSrYA1EdGRxSsj+zBCeDjjA/V3RNEDFKLVaSc8sJNepwrj5+YYUVd7OB9r6uZ73/1kBKSV5eHqmpqYSHN64kqCobFeUiZndIHI6mnbLn9RWJvLM6CT9nQaC/H2F+rnTwd60TKADcnAzYpaTCaq9ZV1Zpw2p3UFppI62ggtrTCdU3tZCUkpwSCxmFFfW+X2G1czivHCejjgh/V0J9XAj1cSHAw4miCitFFdYmO28pZb15aAmEEPj6+mKxWBq9D1WyUJSLlJSS8e//QZcgD16+Nq5J9nkkr5wv16dwfc+2BHoYCfF2OWVaVyft9lFaacPFpP1eVGFFJwS+biZySioxGXT4uprIK6sir7QKg14Q6u2Mi8mAlJL0wgryyqoAMBp0+Lk51ey/yuYgJbcMnU4Q5uuKXnf8u62fmxOF5VbSCytwczKcVB0lpaSs0oaLk+Gk0k1ZpQ0ngw6Dvu535YM5ZVisdlxMelxMBjzMBlyc6t4iLVY7NofE1aSvKU01ht1RnT+T/qR8/F2lFitCiJrrcSpnk19QwUJRLlqbDxewI7WIvRklPDIiCh9X01nv89UV+9HrBDOGdSI/Lfm0aY16HWajnlKLjQB37QZdbLHhbjbQxsOMzS7JKraQXVKJlBJ3sxGL1c7B7DICPJywWO0UVVjxd3fCYnWQUWTB1WTA2aSn0monObcMh0MS4e96Uo8rnRCEeDlzMKeUrGILwV7ONe9JKUktqKCgvIo2nmYC3M0171ntDg7llOHjWjcQVtkclFfZcDUZsDskOSWVZJdYcDEZ8Hd3Qi8gp7SKEotWkjEb9Pi5O+HlYvxbVW1Wu4O80iryyiqxOyQ6IfB2MeLn5nRSyc3mcJBTUomryYCHc/3tDFa7gyP5FRj0go4BbmcdEE5HBQulVTmSV06otzO6FtAwOnfjEZwMOiptDr7fmsptl0Wc1f52HC3kxx3p3D8kkkAPM/lpDW/j5mQgv6wKh5RUVNmx2R14OpsRQhDird3AhdBKAmajHpvdQXqRhaxirTokyNMZf3cnrHYHB7JLOZKvXZ/DeeUAhPu7smzJj4wfP569e/cSFRVVc2xXJ4NWainVgpGfmxNGvY4j+eUUW6zodYLCMiv+bk41N9HCcisSSZHFRrCUNeuPBYEQb2fMRj12h4OCciu5JZUczisDtK7CgR5mjHoduaWVpBaUk12iI8zXFXOtG31OiYWs4sp6H0d3rJrLw2zE29VESYWV/HIreWVVeDob8XdzwsXJQInFSmpBBTsTdpCTlcHE8WPwrVXqOravn1f/wbdfz+GTD98/p4ECVJuF0kIUllfx/pokLLXqz0/0R1Iul7+6mv8s29eoY6zal8XSnY16bszfJqXk6w1HSMourff9onIrSxIymNArlB7tvJi78cjfrm8/mFPKa8v3s2xXJjkllfz75734upq44/IzDzquToaaQFFssSIQuJm176A6IWjr40Kot0vNzdSg19HOx4UwX1fCfF3xd9dugEa9jrbezlTa7BzMKUUnoIO/Ky4mA3PnzmXAgAHMmzfvpOO38XTG28VEfrmV/VklJGaVUGyxEuLlTBsPMxabvc7fREF5FUIIbHYH5VXH15dYbOiROFWXYPQ6rUqscxt32vu40Nbbhag27gR6mPFxNdExwI0wP1ccDjiUU0Z5lQ0pJRlFFVoJycmAv5vppFegh5lOge6E+bni6Wwk1Efbr7+7E6WVNpJySknMKiE5twydEOQfSWTDb7+SVlhBVrGlzjXOLCwjPKorb7/9dp1gda6okoVy1ooqrHieoph8Jo4N9vp43SGySyrp3s6LXu19uLSDL95nWLUyZ/1hXluRiMXqYMaVnU5632K188TCnQB8/Hsyo7sFExPsCUCxxcr0udvq3JhHxwfz8LDONSWQ1fuzuf2LLdgdkoeHdeLewZEIISivsvHKsv0czCnlmdExdPB3a/TnUNvu9GIeX7gTT2cjn07tTc/23nXeX7gtlUqbg0l92rE7vZhH5iewKaWAPuE+Z7T/8iobt3+xmUM5ZXXWPz8mBnfzydfy2R93syf95Ee2S6C80obJoMNmlwjBGd+4ooM9ePqamJpld7ORNp5mSipstPNxwWjQUVpayh9//MHq1asZPXo0zzzzTE36V155hS+//BKdTsew4SP45xPPkLBnP/9+fAYF+Xno9HpefOdTErdn8dl/3+G773/AYrXz1nMziYiK49ZbpxHTOZJp06bxw5Jl3Hbn3fzpqOSjjz6iqqqKyMhIvvzySzxdXMjKyuLayXdx6NAhAD744AOWLl2Kl7cPoybdyqGcMj547QXcvP2YPn06wZ5a6SolJYURI0YwYMAA1q9fT3x8PNOmTePpp58mOzubr776ij59+uBhcPD4Ew+yfcdOKq1W/vXYE0waP4Z/P/8sFRUVbNn4Fzff/SCpyUnk52SSdvQIzu7eTJl2C4//7z1++uknSktLuf/++9m8eTNCCJ5++mmuvfbaM7oWZ0IFC+WsLEnI4P65W3lkRBR3Dezwt7a1OyTLd2fy4dpD7DhaiI+riUh/N+ZuPMLsP1JOeaOsz08J2jf+D9YkMTo+mMiAujft91YnkZJXznv/6MHTi3fx+MJdfH/3pdgdknvmbGX9oTyujgtCpxPklVbx/pqDpBdW8OqEePZnlnDvV1uJauNOp0B3XluRSG5pFVfHBfHwdztIySvHzcnAVbPWMXNkFDf3Czujaq7yKhvbjxaSnFvGdT1DcTIcv8mu3peNEODpbOTGj9fzwY09GRwVAGjBde7Go8SHehIT7Em4nyvP/7iHuRuPnHGwePqH3STnlvHZtN64m41sOZxPQbmViX3andH2xwhApxNY7VpPIqezbKwNcDcT4H58edGiRYwYMYJOnTrh4+PD1q1b6dGjB0uXLmXRokVs2LABFxcX8vPz8fF0ZsyDdzJz5kzGjRuHxWIhJaeE9RlafVphRRUCgdmox2TUUVxhA0BnMPHZ90sJ83PFWlbM7bffDsCTTz7JJ598wv3338/06dMZOHAgCxcuxG63U1paSnBwMOPHj2f6Aw9wMLuExd/PZ8Vvv9cEimOSkpL47rvv+Oijj+jduzdff/01v//+O4sXL+bf//43ixYt4sUXX2To0KHMnj2bwsJC+vTpw/VjRvHcc8+xefNm3nnnHXJLK3n+uWfZunUrny1YioebK2l7js+H9/zzz+Pp6cnOndqXooKCgrO6FidSwUJptE0p+Tz07XaMeh2vLt9Pn3AferRr+MZeUWVn/pajfPx7Mofzymnv68LzY2O5rkcoziY9VTYHCamF/PO7HUz+eAPvT+7B4M4Bp9xfUnYJ+zJLuH9IJF/8dZjHF+7kmzv61vzDHsgq4b+/HWRc9xBGxQVhczh4YN52vvwrhZ1pxfyelMtrE+K5rmcooN2M319zkFeX7yevrIp9mSV4u5j4dGpv/N2c8HU18fHvyXz2ZwohXs7Mvb0vHfxdeXRBAs/+uIelOzOZPrQj/SN9EUJQVmlj3qajrNidib26m2tZlZ3ErJKaZYdDclO/sJpzWrU/m7hQLz65uRdTZ2/kti82c8+gDky9NIyUvHL2Z5Xw8viuALiYDIztHsI3m4/y9DXRFJZbmf1HMlnF1aW0MG9iQzxrgtEP29P4bksq9w+JZFD159pQQK5dAjhRRlEFOSXak0qj2ng06fQfc+fO5cEHHwRg4sSJzJ07lx49erBy5UqmTZuGi4vWSO3j40NJSQlpaWmMGzcO0AahBfnpsUuJzS4pLNfGZuiEwNmop9JmRwLDrhmPTgjcTAbWbdjFk08+SWFhIaWlpQwfPhyAVatW8cUXXwCg1+vx9PTE09MTX19fdiXsID0jk149e9AlLOSkcwgPD6drV+1axcTEMHToUIQQdO3alZSUFABWrFjB4sWLee211wCwWCwcOXKkZh9CCPzdzfi4OnH9+LFEt/PHpNeRWSs4r1y5sk5Vnbd3w/+Lf4cKFkqjHMwp5fYvNhPq7cxnU/vwj4/XM33uNpZMv+y0VVIOh+T6D/9iZ1oR3dp6MXNEFMNi2tTp+mgy6OgV5sP8uy5l6uyN3P75Zl4cF8uEnm3r/ca+JCETIWBy3/aEejvz6IKdfLc5lQm9QjmcV85j3+/E1cnAk6O6AFoV0/wtqTz30x4cEh66olNNoADtH/PewZH4upp4fKG27Ve3XUKgh9ar5olRXWjr48LhvHIeurJjTbXNp1N78+3mo7y2IpHJn2wgJtiD3mE+fL81lWKLjZhgD7xctLSuTgaGRPnTq70PLy/dx/fb0mqCRV5pJduPFvLA0I74uTkx9/a+zFywk3dWJfHR2kMEeZpxNem5Jj64Js+T+rTjy/WHuf7DvziQXYpRp6ONp5lluzO1z1Svo2uoJ93aevHNpqP0bO/NA0M7NubSn8TNyUBOSSUuJn2TBoq8vDxWrVrFrl27EEJgt9sRQvDKK68gazVOH1Nfm4272YDJaKC8yorV7iDY04zFYqkZ3CelxKE34eZkQKcTTJ06lUWLFhEfH89nn33GmjVrTpvH2267jc8++4zMzExuv+3WetM4OR1vmNbpdDXLOp0Om81Wk48FCxbQuXPnOttu2LDhpP25ubnhVk832fo+k6akGriVv62owsrU2Rsx6ASfTe1DO18X3p7UnYwiC48v3HnahtZ1SbnsTCviuTExLLznUkZ2DTrllA3+7k7Mu6MvvcN8eHTBToa9tZZvNh2h0la3EXvJznR6h/kQ6GFmQs+29Anz4dkfd9P7xZUMem0Nmw8X8OSo6JreJEIIXhgbi6vJwMTebZk+NLLe40/s047v7urH/LsupVPg8boRIQQ3XxrGU9dE16nfF0JwQ+92/P7oYP5zbVcsVjtf/JXCgI5+LLznUpZMv4yvbuvLV7f15fNb+vCv4VEMjgpgfI8Qth0p5FCO1mbyW2IOUsKQ6mond7OR927swcoZAxnXPYT0QgsTerWt068+OtiDS8J9yCqu5J5BHfh95mDWPjKYzU9ewYc39WRa/zAAvvzrMAa9YNbEbmfdv/8YF5M2zsHL+ey77tY2f/58pkyZwuHDh0lJSeHo0aOEh4fz+++/M2zYMD799FPKy7VeU/n5+Xh4eBAaGsqiRYsAqKysxFJRQVSHDhxM3IfdWoWjspxff/0Vg16Hs0mP3QFVdgfu1Y3yJSUlBAUFYbVa+eqrr2ryMnToUD744AMA7HY7xcVa+824ceNYtmwZmzZtqimFNMbw4cN55513av53tm3bBoC7uzslJSVntI9hw4bx7rvv1iw3dTVUzajFi/3Vs2dPqZwfX/6VIts/+pNcfzC3zvr3Vh+Q7R/9SS7ennbKbad8skH2euEXWWm1n/HxrDa7XLQtVY58a61s/+hPsv/Lv8rUgnIppZT7M4tl+0d/kp//mVyTPim7RI5973f50Lxtcs76FHkgq7je/ZZX2s44D41htztkicXaYLrMogoZPvMn+fryfVJKKe/7eqvs+fwv0m531Ju+rNIqrbaTP7+KKpu0WE9/TharTRZVVJ1B7qXcs2fPGaWTUkqb3SEdjvrz21gDBw6US5curbNu1qxZ8q677pJSSvnSSy/JLl26yPj4ePnYY49JKaVMTEyUgwcPll27dpU9evSQBw8elGUWq5x61/0yIrKjHDVqlBw3bpycPXu2zCqqkMGhbeWaHUmysvpze//992VYWJgcOHCgvO++++TNN98spZQyMzNTjh49WsbGxsr4+Hj5559/1uTpzjvvlI8++mi955CcnCxjYmJqlm+++Wb53XffnfReeXm5vOOOO2RsbKyMiYmRo0aNklJKmZeXJ3v16iXj4+PlvHnz5NNPPy1fffXVmv2tXr26Jm1JSYmcMmWKjImJkXFxcXLBggUn5ae+awpslmdwjxWyhQxv79Wrl1QPPzo/Jn20nqwSC7/OGFin2OtwSIa/tZb/b+/ew6uqzwWPf9/cCJBAAiQkkkBSSLjJJVwVrVWoiJWWqj0V2rHWeh7HVq312HPG6XjU057jWMfejnU60mr19DhatVpph1qoWlQQ5BK5UwIBQrgkISQhwdz3O3+stcMOZGevhOzsJPv9PE+e7LX2b639LhfuN+t3TYiL4Y/3XnnBI/GB8lo+++P3eODafO7tRhWIqrJufwX3/t9CMlMSefWuBTz7wSF+/k4RG7+3qN3gq/7m1mc3cejUWd797tXM/sFaFk/N4Mm/mxHRmPbu3cvkyZMjGkNPUO8682AAABhUSURBVFVOn21iWGI88QHVZA3NTrtRYnxsuyfHrvD5fMyaNYtXX32VvLyeqdYLp47uqYhsVdU5oY61aijTJeW1DWw6VMnSaZkXJIOYGOEbV+ay+/gZPjp0+oJjn1t/mIS4GL4yv2s9bvxEhKsnpvPMrbM5dOosd/1mK3/cfpz5uSP7daIAuGnWGEqr6ln5XjFnGlraqqDMxRMRRiYNapcoAAbFxZCcGN/tke979uxhwoQJLFq0qF8kiotlycJ0yZ93ncSnsDSgcTXQjQVjSB0Sz3Pr208VUXW2ide3lXLjzDEXjETtqgUTRvHDm6fzYXElxafOcsP0zIs6X19w3dQMhiTE8rO/FBEXI1yZNyrSIQ14IkLuqKHt5qPqiilTplBcXMyPfvSjHo6sb7JkYbrkDztOkJeeFPSxPTE+lq/MH8uaPWWUuFM2ALy0uYSGZh+3X5nTI3HcNCuL/7ZkEpcMT+T6SzN65JyRNCQhjiVTM2hq9TEnJ5VhHQyMi4SBUk1tLv5eWrIwnpWdaWDz4dMh/5K/9bIcYkV44cPDALy9t4xn1hVzxYSRTMoY1mPxfPPq8ax/cOFFP6n0FTfNcrrv9pUqqMTERCorKy1hDADqrmeRmNj96lobZ2E8+9POE6jC0hDJImN4IjdMz+S3m49SU9/Ma1tLmZSRzA+WXdrjMYV78rTedMWEkTy1ooBFk/tGssjKyqK0tJSKiorQhU2f518pr7ssWUSp/9x4hN8XHuORz09lWtZwT8f8cccJJmUkMyE9dM+R26/I5c2Pj/P6tlLuvmY89y3K79EBWwORiLQbaBdp8fHx3V5VzQw8liyi1KtbS9l+tJob//d67l2Yx7euGU98kEFaJ2rq2VhcyZYjVTzQwSR9HZmZncIPb55G3uhkT1OAGGP6NksWUaiusYVdx2q49bJxnGlo5id/2c+q7ce4Kj+N2eNSGZMymO1Hq9laUs3Ww6c5XuOsPTAqKYEvFlw4900wt8ztXhdZY0zfE9ZkISJLgJ8BscCvVPXx897/CXCNuzkESFfVFPe9VmCn+16Jqn4hnLFGk21Hqmj1KddOGc1V+WlcNzWDFzYcbpvt1S9jWCKzc1L5+7GpzMlJZXLmsKBPH8aYgS1syUJEYoGngWuBUmCziKxS1T3+Mqp6f0D5e4GCgFPUq+rMcMUXzT46dJrYGGGWO9Po56Zl8rlpmTS3+thz/AwnauqZlpXCmIClKo0x0S3kn4kico+IdKfSeR5wQFWLVbUJeBlY1kn5FcBL3fgc00WbDlVy6ZjhF8xcGR8bw4zsFJZcmmmJwhjTjpc6hQycp4JXRGSJeO+rOAY4GrBd6u67gIiMA3KBdwJ2J4rIFhHZKCJfDHLcnW6ZLda9z5uG5la2H61hvsdFcowxBjwkC1V9CMgDngW+DhSJyGMiEmpZtI6SSrDRPcuB11Q1cO7pse7kVl8BftrR56nqSlWdo6pz0tLSQl2KAT4+Wk1Tq495OZYsjDHeeWqtdKexPen+tACpwGsi8kQnh5UC2QHbWcDxIGWXc14VlKoed38XA3+lfXuG6aZNxacRgbmWLIwxXeClzeLbIrIVeAJYD0xT1W8Cs4HOVgPfDOSJSK6IJOAkhFUdnH8iTvL5MGBfqogMcl+PAq4A9px/rGlPVdl8+DR3v7iNZ9Yd7LDMR4crmZQxjOFD+sbcQ8aY/sFLb6hRwE2qeiRwp6r6RGRpsINUtUVE7gH+jNN19jlV3S0i38dZbMOfOFYAL2v7CWgmA8+IiA8noT0e2IvKXOj9ogp+vHY/hSXVxMUI/2/nCSZlDuMz+eeq55pafGw9UsVyG/9gjOkiL8liNdC2OIGIJANTVHWTqu7t7EBVXe0eH7jv4fO2H+3guA3ANA+xGeBAeR13PL+F0cMH8YNlU1k6/RKWr9zIA698zOr7Pt221sOu4zU0NPuscdsY02Ve2ix+AdQFbJ9195k+QFX5H2/sZHBCLG986wpuvTyH1KEJPPWVAuoaW3jgle34fEpLq4+395YBMNeShTGmi7w8WUhgFZFb/WTThPQRr24tZdOh0zx+07R2i7jkj07m4aVT+d4bO1n61AccqTzL2aZWJmUkd3uxF2NM9PLypV8sIt/m3NPEt4Di8IVkvKqsa+Sx1XuZm5PKl+dkX/D+innZ7DxWw47Sam6encXscalcOcFWYDPGdJ2XZHEX8O/AQzjjJN4G7gxnUMabf1u9l7ONLTx24zRiYi4c1iIi/M+brOnHGHPxQiYLVS3H6fZq+pC6xhZ+X3iMry/IJS/IEqfGGNNTQiYLEUkE7gCmAm1r8qnqN8IYlwlhx9FqfAqfmWgj140x4eelN9RvcOaHug5YhzMSuzacQZnQCo9WAzAzKyXCkRhjooGXZDFBVf8ZOKuqLwA3YGMgIq6wpIrxaUNtJLYxpld4SRbN7u9qEbkUGA7khC0iE5KqUlhSTYEtV2qM6SVeekOtdNezeAhnbqck4J/DGpXp1NHT9VSebaJgrFVBGWN6R6fJQkRigDOqWgW8B3yqV6IynSo8WgVAQbY9WRhjeken1VCq6gPu6aVYjEeFJdUMSYglf3RSpEMxxkQJL20Wa0XkuyKSLSIj/D9hj8wEta2kihlZKcTFelqOxBhjLpqXNgv/eIq7A/YpViUVEQ3Nrew5foY7r7L//MaY3uNlBHdubwRivNl1rIYWn1pPKGNMr/IygvtrHe1X1f/o+XBMKIUl7mC8bOsJZYzpPV6qoeYGvE4EFgHbAEsWPayitpGRQxM6nBTQr/BoFdkjBpOWbNOMG2N6j5dqqHsDt0VkOM4UIKYHbSqu5JaVG0lOjKNgbCrzclL5xpW5DElof4sKS6qZm2P9C4wxvas73Wk+AfJ6OpBo94cdxxkcH8vnZ1zCyZp6nlyzn9U7T7Yrc7KmgRM1DVYFZYzpdV7aLP6A0/sJnOQyBXglnEFFG59PWbunjM/kp/HYjdPw+ZQZ/7KGwpIqvjQ7q61cYYkzGG/WOGvcNsb0Li9tFk8GvG4BjqhqaZjiiUo7jtVQdqaRxVNHAxATI8wcm9LWmO1XeLSahLgYpmQOi0SYxpgo5qUaqgTYpKrrVHU9UCkiOWGNKsqs2X2S2Bhh4aT0tn0F2SnsO3mGT5pa2vYVllRx6SXDSIizwXjGmN7l5VvnVcAXsN3q7jM9ZM2eMubnjiBlSELbvoKxqfgUdpTWANDc6mNHaY2NrzDGRISXZBGnqk3+Dfd1QiflTRccrKjjQHkdi6eMbrff34i9zW2n2HeilsYWn800a4yJCC/JokJEvuDfEJFlwKnwhRRd1uwuA2Dx1Ix2+1OHJpA7amhbu0XbTLP2ZGGMiQAvDdx3AS+KyM/d7VKgw1HdpuvW7DnJtDHDuSRl8AXvFWSn8F7RqbbFjtKTB3HJ8MQOzmKMMeEV8slCVQ+q6mU4XWanquoCVT3g5eQiskRE/iYiB0TkwQ7e/4mIfOz+7BeR6oD3bhORIvfntq5cVF/W0NzKmt0nWb3zBK9vK6WwpPqCKii/grEpnKprpLSqnsKSKgrGpiASfHS3McaEi5dxFo8BT6hqtbudCjygqg+FOC4WeBq4FudpZLOIrFLVPf4yqnp/QPl7gQL39QjgEWAOzhiPre6xVV28vj7nt5uP8siq3W3bInD9tIwOy/qrnN7ZV87hyk9YPm9sr8RojDHn81INdb2qfs+/oapVIvI5nGVWOzMPOKCqxQAi8jKwDNgTpPwKnAQBcB2wVlVPu8euBZYAL3mIt0/bc/wMqUPiefnOywFISoxjTAdVUAATM5JJjI/h+Q2HAadayhhjIsFLsogVkUGq2gggIoMBL7PYjQGOBmyXAvM7Kigi44Bc4J1Ojh3j4TP7vP3lteSPTmZiRnLIsvGxMUzPSuGjQ6eJjRGmZ1myMMZEhpfeUP8JvC0id4jIHcBa4AUPx3VUua4d7ANYDrymqq1dOVZE7hSRLSKypaKiwkNI4fW7raX88K19Qd9XVQ6U1ZE/OnSi8PN3lZ2cmczghNiLjtEYY7rDSwP3E8C/ApNxGrnfAsZ5OHcpkB2wnQUcD1J2Oe2rmDwdq6orVXWOqs5JS0vzEFJ4PfvBIX69/hA+X8c58URNA7WNLeR7eKrwK8hObffbGGMiweu8ESdxRnHfjLOexV4Px2wG8kQkV0QScBLCqvMLichEIBX4MGD3n4HFIpLqNqgvdvf1WVVnm9hz4gwNzT6OVdd3WGZ/WS0A+elJns87NyeVpEFxXDMp8snQGBO9grZZiEg+zhf8CqAS+C0gqnqNlxOraouI3IPzJR8LPKequ0Xk+8AWVfUnjhXAy6qqAceeFpEf4CQcgO/7G7v7qo3FlW2vD5TXkT1iyAVlisrqALpUDTUyaRA7Hlnc6YJIxhgTbp01cO8D3gc+7x9XISL3d1L+Aqq6Glh93r6Hz9t+NMixzwHPdeXzestbu06SGB/D1RPPTfy34WAlg+JiaGzxUVReyzUBkwL67S+rZVTSIFKHdm22FEsUxphI66wa6mac6qd3ReSXIrKIjhueo4rPpzz0+13802s7aG49N7/ihoOnuHz8SEYlDeJAeV2Hx+4vqyV/tPcqKGOM6SuCJgtVfUNVbwEmAX8F7gdGi8gvRGRxL8XX5+w9eYZTdY2U1zbyzr5yAMrONHCw4iwLxo8kLz2Jog6Shc+nFJV3rSeUMcb0FV56Q51V1RdVdSlOr6SPgQum7ogW7xc5cyimDonnpY9KAPjwoNNesWD8KCakJ3GgvI6AJhgAjlXX80lTK3n2ZGGM6Ye6tIqOqp5W1WdUdWG4Aurr3i+qYFJGMrdeNo51+ysorfqEDQdPMXxwPJMzh5E3OonahhbKaxvbHVdU7vaEsicLY0w/ZEuudUF9UyubD1Xx6bxRfHmuMwzklS2lbDhYyWWfGkFsjDAhzXlyOL/dYr+/J1S6JQtjTP9jyaILNh2qpKnVx6fz0shKHcJn8tN4fv0hSqvqWTB+FAAT3GqmIndMhd/+slpGDxvE8CHxvR63McZcLEsWXfB+0SkS4mKYlzsCgBXzxnKmwVkje8H4kQCkJQ1iWGIcByraP1kUdXGaD2OM6UssWXTB+0UVzM8dQWK8M0fTwknppCcPYlTSICa4o7JFhLzRyW0D8MDpCXWgvI48q4IyxvRTXmadNcDJmgb2l9XxpdlZbfviY2N44kvTaWhubbco0YS0JN7eV9a2XVpVT31zq42xMMb0W/Zk4dH7Rc6stp/Oaz9H09UT01lyaWa7fXmjkzhV10TV2Sbg3JxQeVYNZYzppyxZnGfL4dPU1DdfsP+9olOkJQ9ikocZY8e7VVL+dot1+ysQwcZYGGP6LUsWAarONnHLyo185+XCdoPqSqs+4S97yrhmYpqnNbDz0v09our469/K+c3GI3x1/liGJVpPKGNM/2TJIsDG4kpafcq7f6vgT7tOAs6CRQ+/uRsRuO+z+Z7Oc8nwwQyOj+XD4kq+++p2JmUk89ANU8IZujHGhJUliwAbDlYyNCGWKZnDeHTVbs40NPPWrpO8s6+cf7g2P+ha2eeLiREmpCfxh+3HqWts4akVBW09qIwxpj+yZBFgw8FTzMsdweM3T+NUXSOPrtrNI6t2MyVzGF9fkNOlc/m70j7y+anWsG2M6fes66zLP3Ps8rljmZ6Vwtcuz+H5DYcRgV9+bQ5xsV3Lq19fkMOUzGEsn5sdurAxxvRxlixc/pljL3dHYj+wOJ8NB09x7ZTRzMhO6fL5ZmSndOs4Y4zpiyxZuAJnjgVIToznz9+5ylPvJ2OMGeiszcIVOHOsnyUKY4xxWLIAjp7+pN3MscYYY9qzZIFTBQXnZo41xhjTniULnCqowJljjTHGtBf1yUJV2XCwkgXjR1obhTHGBBH1yaK0qp7KukargjLGmE5EfdfZ7BFD+PiRxcTaU4UxxgQV9ckCsNlgjTEmhKivhjLGGBOaJQtjjDEhSeAiP/2ZiFQARy7iFKOAUz0UTn8RjdcM0Xnd0XjNEJ3X3dVrHqeqaaEKDZhkcbFEZIuqzol0HL0pGq8ZovO6o/GaITqvO1zXbNVQxhhjQrJkYYwxJiRLFuesjHQAERCN1wzRed3ReM0Qndcdlmu2NgtjjDEh2ZOFMcaYkCxZGGOMCSnqk4WILBGRv4nIARF5MNLxhIuIZIvIuyKyV0R2i8h97v4RIrJWRIrc36mRjrWniUisiBSKyB/d7VwR2eRe829FJCHSMfY0EUkRkddEZJ97zy8f6PdaRO53/23vEpGXRCRxIN5rEXlORMpFZFfAvg7vrTj+3f1+2yEis7r7uVGdLEQkFngauB6YAqwQkSmRjSpsWoAHVHUycBlwt3utDwJvq2oe8La7PdDcB+wN2P4h8BP3mquAOyISVXj9DHhLVScBM3Cuf8DeaxEZA3wbmKOqlwKxwHIG5r1+Hlhy3r5g9/Z6IM/9uRP4RXc/NKqTBTAPOKCqxaraBLwMLItwTGGhqidUdZv7uhbny2MMzvW+4BZ7AfhiZCIMDxHJAm4AfuVuC7AQeM0tMhCveRhwFfAsgKo2qWo1A/xe40yMOlhE4oAhwAkG4L1W1feA0+ftDnZvlwH/oY6NQIqIZHbnc6M9WYwBjgZsl7r7BjQRyQEKgE3AaFU9AU5CAdIjF1lY/BT4J8Dnbo8EqlW1xd0eiPf8U0AF8Gu3+u1XIjKUAXyvVfUY8CRQgpMkaoCtDPx77Rfs3vbYd1y0J4uOFrEY0H2JRSQJ+B3wHVU9E+l4wklElgLlqro1cHcHRQfaPY8DZgG/UNUC4CwDqMqpI24d/TIgF7gEGIpTBXO+gXavQ+mxf+/RnixKgeyA7SzgeIRiCTsRicdJFC+q6uvu7jL/Y6n7uzxS8YXBFcAXROQwThXjQpwnjRS3qgIG5j0vBUpVdZO7/RpO8hjI9/qzwCFVrVDVZuB1YAED/177Bbu3PfYdF+3JYjOQ5/aYSMBpEFsV4ZjCwq2rfxbYq6o/DnhrFXCb+/o24M3eji1cVPW/q2qWqubg3Nt3VPWrwLvAl9xiA+qaAVT1JHBURCa6uxYBexjA9xqn+ukyERni/lv3X/OAvtcBgt3bVcDX3F5RlwE1/uqqror6Edwi8jmcvzZjgedU9d8iHFJYiMiVwPvATs7V338Pp93iFWAszv9wf6eq5zee9XsicjXwXVVdKiKfwnnSGAEUAv9FVRsjGV9PE5GZOI36CUAxcDvOH4cD9l6LyL8At+D0/CsE/h6nfn5A3WsReQm4Gmcq8jLgEeD3dHBv3cT5c5zeU58At6vqlm59brQnC2OMMaFFezWUMcYYDyxZGGOMCcmShTHGmJAsWRhjjAnJkoUxxpiQLFmYAUlERorIx+7PSRE5FrDtaeZREfl1wFiFYGXuFpGv9lDMpSKS0oXyC92+852VmSAiH198dCbaxYUuYkz/o6qVwEwAEXkUqFPVJwPLuH3QRVV9F54BVPV2D5/z9MVH220LgVPAxgjGYKKEPVmYqOL+pb1LRP4PsA3IFJGVIrLFXQvh4YCyH4jITBGJE5FqEXlcRLaLyIciku6W+VcR+U5A+cdF5CNx1khZ4O4fKiK/c499yf2smUFCfNA9fpM7eBARWeZuF4rIGhFJF5HxOIPO/tF9WlogIhki8qa7bsF2EZnvnjNORJ51r+9PIpIYnv+6ZiCzZGGi0RTgWVUtcGcrfVBV5+Cs+3BtkDVNhgPrVHUG8CHwjSDnFlWdB/wj4E889wIn3WMfx5nxN5gq9/hnAP+0LO8Bl7mTAr6Osy7JQZwR2v9LVWeq6gactVnWqup0YDbn1vCYCPxUVacC9QyAabpN77NkYaLRQVXdHLC9QkS24TxpTMZJJuerV9U/ua+3AjlBzv16B2WuxJlyAlXdDuzuJLaX3N8v4kyEB84UDmtEZCfwD8DUIMdejZNkUNWWgFmFD6jqTg+xGxOUJQsTjc76X4hIHs5Kegvdv8jfAjqqpmkKeN1K8Pa+xg7KdDRNdDAdzb/zNM5qb9OAbwWJr7PjA+dC6ix2Y4KyZGGi3TCgFjjjTu18XRg+4wPgywAiMo2On1z8bnF/rwDWu6+HA8fcBvnbAsrWAskB2+8Cd7mfE+uumGdMj7BkYaLdNpyprHcBv+TcF3RPegoYIyI7gAfcz6oJUnaIiHwEfNMtC/Ao8AawDmeWUb83gS+7Dd8LgHuA69zqqi3ApJ6+EBO9bNZZY8LMXXwnTlUb3GqvNUBewHKfxvR5VndpTPglAW+7SUOA/2qJwvQ39mRhjDEmJGuzMMYYE5IlC2OMMSFZsjDGGBOSJQtjjDEhWbIwxhgT0v8HwoE+L7DLQS4AAAAASUVORK5CYII=\n",
"text/plain": [
"<Figure size 432x288 with 2 Axes>"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
}
],
"source": [
"epoch_list, train_loss_list, valid_loss_list, acc_list, y_hat_list, y_true_list = \\\n",
"simple_fit(100, net_ext, F.binary_cross_entropy_with_logits, opt, train_dl, valid_dl)"
]
},
{
"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": "3.6.6"
}
},
"nbformat": 4,
"nbformat_minor": 2
}