Join the 1-day Testing & QA Summit featuring 15+ Expert Speakers.Register for FREE! Join TestMu Conference

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:...

Automation Testing Tutorials

Learn to execute automation testing from scratch with LambdaTest Learning Hub. Right from setting up the prerequisites to run your first automation test, to following best practices and diving deeper into advanced test scenarios. LambdaTest Learning Hubs compile a list of step-by-step guides to help you be proficient with different test automation frameworks i.e. Selenium, Cypress, TestNG etc.