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How to use collected method in Selene

Best Python code snippet using selene_python

balance_data.py

Source:balance_data.py

1import numpy as np2import pandas as pd3import os4import cv25from collections import Counter6from input_choices import \7    input_w, input_a, input_s, input_d, \8    input_wa, input_wd, input_ws, input_wsa, \9    input_wsd, input_sa, input_sd, input_nk10from random import shuffle11# for looking at and balancing data sets12# train_data = np.load('data/training_data-1.npy', allow_pickle=True)13# data_frame = pd.DataFrame(train_data)14# print(data_frame.head())15# print(Counter(data_frame[1].apply(str)))16# for data in train_data:17#     img = data[0]18#     choice = data[1]19#     cv2.imshow('test', img)20#     print(choice)21#     print(img.shape)22#     if cv2.waitKey(25) & 0xFF == ord('q'):23#         cv2.destroyAllWindows()24#         break25# all possible inputs26collected_input_w = []27collected_input_a = []28collected_input_s = []29collected_input_d = []30collected_input_wa = []31collected_input_wd = []32collected_input_ws = []33collected_input_wsa = []34collected_input_wsd = []35collected_input_sa = []36collected_input_sd = []37collected_input_nk = []38# load data39starting_value = 140while True:41    file_name = 'data/training_data-{}.npy'.format(starting_value)42    if os.path.isfile(file_name):43        # load existing data44        print('training_data-{}.npy exists! Loading data...'.format(starting_value))45        curr_data_set = np.load(file_name, allow_pickle=True)46        # analyze data47        data_frame = pd.DataFrame(curr_data_set)48        print(Counter(data_frame[1].apply(str)))49        # split data into singular arrays defined above50        for data in curr_data_set:51            img = data[0]52            choice = data[1]53            if choice == input_w:54                collected_input_w.append([img, choice])55            elif choice == input_a:56                collected_input_a.append([img, choice])57            elif choice == input_s:58                collected_input_s.append([img, choice])59            elif choice == input_d:60                collected_input_d.append([img, choice])61            elif choice == input_wa:62                collected_input_wa.append([img, choice])63            elif choice == input_wd:64                collected_input_wd.append([img, choice])65            elif choice == input_ws:66                collected_input_ws.append([img, choice])67            elif choice == input_wsa:68                collected_input_wsa.append([img, choice])69            elif choice == input_wsd:70                collected_input_wsd.append([img, choice])71            elif choice == input_sa:72                collected_input_sa.append([img, choice])73            elif choice == input_sd:74                collected_input_sd.append([img, choice])75            elif choice == input_nk:76                collected_input_nk.append([img, choice])77            else:78                print("No match for data found!")79        starting_value += 180    else:81        break82collected_data = [collected_input_w, collected_input_a, collected_input_s, collected_input_d,83                  collected_input_wa, collected_input_wd, collected_input_ws, collected_input_wsa,84                  collected_input_wsd, collected_input_sa, collected_input_sd, collected_input_nk]85total_len = 086highest_nb_input = 087input_idx = 188for cdi in collected_data:89    total_len += len(cdi)90    print(f"Len of current cdi: {len(cdi)}")91    if len(cdi) > highest_nb_input:92        highest_nb_input = len(cdi)93    input_idx += 194avg_len = total_len / input_idx95print(f"Average amount of inputs: {avg_len}")96print(f"Highest number of inputs: {highest_nb_input}")97max_samples_allowed = int(highest_nb_input / 2)98balanced_data = []99for cdi in collected_data:100    curr_cdi = cdi101    while len(curr_cdi) < max_samples_allowed:102        print(f"curr_cdi len {len(curr_cdi)}")103        curr_cdi += curr_cdi104    if len(curr_cdi) >= max_samples_allowed:105        cdi_limited = curr_cdi[:max_samples_allowed]106        print(f"FINAL curr_cdi len {len(cdi_limited)}")107        balanced_data += cdi_limited108    else:109        balanced_data += cdi110shuffle(balanced_data)111# analyze data112data_frame = pd.DataFrame(balanced_data)113print(Counter(data_frame[1].apply(str)))114np.save("data/training_data_balanced.npy", balanced_data)115# avg_len = (len(collected_input_w) + len(collected_input_a) + len(collected_input_s) + len(collected_input_d)116#            + len(collected_input_wa) + len(collected_input_wd) + len(collected_input_ws) + len(collected_input_wsa)117#            + len(collected_input_wsd) + len(collected_input_sa) + len(collected_input_sd) + len(collected_input_nk)) \...

NCBI_Biosample_batch.py

Source:NCBI_Biosample_batch.py

1#!/opt/Python/2.7.3/bin/python2import sys3from collections import defaultdict4import numpy as np5import re6import os7import argparse8import glob9from Bio import SeqIO10sys.path.append('/rhome/cjinfeng/BigData/software/ProgramPython/lib')11from utility import gff_parser, createdir12def usage():13    test="name"14    message='''15python CircosConf.py --input circos.config --output pipe.conf16    '''17    print message18def runjob(script, lines):19    cmd = 'perl /rhome/cjinfeng/software/bin/qsub-pbs.pl --maxjob 30 --lines %s --interval 120 --resource nodes=1:ppn=12,walltime=100:00:00,mem=20G --convert no %s' %(lines, script)20    #print cmd 21    os.system(cmd)22def fasta_id(fastafile):23    fastaid = defaultdict(str)24    for record in SeqIO.parse(fastafile,"fasta"):25        fastaid[record.id] = 126    return fastaid27#RIL1    1       /rhome/cjinfeng/Rice/RIL/Illumina_correct/RIL1_0/RIL1_0_CGTACG_FC153L5_p1.fq.gz28def read_list(infile):29    data = defaultdict(lambda : int())30    with open (infile, 'r') as filehd:31        for line in filehd:32            line = line.rstrip()33            if len(line) > 2: 34                unit = re.split(r'\t',line)35                ril  = re.sub(r'RIL', r'', unit[0])36                data[ril] = 137    return data38def NCBI_biosample(rils, tsv):39    ofile = open(tsv, 'a')40    for ril in sorted(rils.keys(), key=int):41        #print ril42        print >> ofile, 'RIL%s\tnot collected\tPRJNA316308\tOryza Sativa\tnot collected\tNipponbare x HEG4 RIL%s\tTemperate Japonica\tnot collected\tSeedling\tnot collected\tLeaf\tSusan Wessler\tnot collected\tnot collected\tnot collected\tnot collected\tnot collected\tnot collected\tnot collected\tnot collected\tnot collected\tnot collected\tnot collected\tnot collected\tnot collected\tnot collected\tnot collected\tnot collected\tnot collected\tnot collected\tnot collected\tnot collected' %(ril, ril) 43    ofile.close()44def main():45    parser = argparse.ArgumentParser()46    parser.add_argument('-i', '--input')47    parser.add_argument('-o', '--output')48    parser.add_argument('-v', dest='verbose', action='store_true')49    args = parser.parse_args()50    try:51        len(args.input) > 052    except:53        usage()54        sys.exit(2)55    #cp Plant.1.0.tsv RILs_272.NCBI_biosample.tsv56    os.system('cp ../input/Plant.1.0.tsv RILs_272.NCBI_biosample.tsv')57    rils = read_list(args.input) 58    NCBI_biosample(rils, 'RILs_272.NCBI_biosample.tsv')59if __name__ == '__main__':...

01.py

Source:01.py

1cost = float(input())2num_of_months = int(input())3collected = 0.04for i in range(1, num_of_months + 1):5    if i % 2 != 0:6        collected -= collected * 0.167    elif i % 4 == 0:8        collected += collected * 0.259    collected += cost * 0.2510if collected >= cost:11    print(f"Bravo! You can go to Disneyland and you will have {(collected - cost):.2f}lv. for souvenirs.")12else:...

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