How to use generate_raw_table method in autotest

Best Python code snippet using autotest_python

regression.py

Source:regression.py

...49        return default50class Sample(object):51    """ Collect test results in same environment to a sample """52    def __init__(self, type, arg):53        def generate_raw_table(test_dict):54            ret_dict = []55            tmp = []56            type = category = None57            for i in test_dict:58                line = i.split('|')[1:]59                if not type:60                    type = line[0:2]61                if type != line[0:2]:62                    ret_dict.append('|'.join(type + tmp))63                    type = line[0:2]64                    tmp = []65                if "e+" in line[-1]:66                    tmp.append("%.0f" % float(line[-1]))67                elif 'e-' in line[-1]:68                    tmp.append("%.2f" % float(line[-1]))69                elif not (re.findall("[a-zA-Z]", line[-1]) or is_int(line[-1])):70                    tmp.append("%.2f" % float(line[-1]))71                else:72                    tmp.append(line[-1])73                if category != i.split('|')[0]:74                    category = i.split('|')[0]75                    ret_dict.append("Category:" + category.strip())76                    ret_dict.append(self.categories)77            ret_dict.append('|'.join(type + tmp))78            return ret_dict79        if type == 'file':80            files = arg.split()81            self.files_dict = []82            for i in range(len(files)):83                fd = open(files[i], "r")84                f = []85                for line in fd.readlines():86                    line = line.strip()87                    if re.findall("^### ", line):88                        if "kvm-userspace-ver" in line:89                            self.kvmver = line.split(':')[-1]90                        elif "kvm_version" in line:91                            self.hostkernel = line.split(':')[-1]92                        elif "guest-kernel-ver" in line:93                            self.guestkernel = line.split(':')[-1]94                        elif "session-length" in line:95                            self.len = line.split(':')[-1]96                    else:97                        f.append(line.strip())98                self.files_dict.append(f)99                fd.close()100        elif type == 'database':101            jobid = arg102            self.kvmver = get_test_keyval(jobid, "kvm-userspace-ver")103            self.hostkernel = get_test_keyval(jobid, "kvm_version")104            self.guestkernel = get_test_keyval(jobid, "guest-kernel-ver")105            self.len = get_test_keyval(jobid, "session-length")106            self.categories = get_test_keyval(jobid, "category")107            idx = exec_sql("select job_idx from tko_jobs where afe_job_id=%s"108                           % jobid)[-1]109            data = exec_sql("select test_idx,iteration_key,iteration_value"110                            " from tko_perf_view where job_idx=%s" % idx)111            testidx = None112            job_dict = []113            test_dict = []114            for line in data:115                s = line.split()116                if not testidx:117                    testidx = s[0]118                if testidx != s[0]:119                    job_dict.append(generate_raw_table(test_dict))120                    test_dict = []121                    testidx = s[0]122                test_dict.append(' | '.join(s[1].split('--')[0:] + s[-1:]))123            job_dict.append(generate_raw_table(test_dict))124            self.files_dict = job_dict125        self.version = " userspace: %s\n host kernel: %s\n guest kernel: %s" % (126            self.kvmver, self.hostkernel, self.guestkernel)127        nrepeat = len(self.files_dict)128        if nrepeat < 2:129            print "`nrepeat' should be larger than 1!"130            sys.exit(1)131        self.desc = """ - Every Avg line represents the average value based on *%d* repetitions of the same test,132   and the following SD line represents the Standard Deviation between the *%d* repetitions.133 - The Standard deviation is displayed as a percentage of the average.134 - The significance of the differences between the two averages is calculated using unpaired T-test that135   takes into account the SD of the averages.136 - The paired t-test is computed for the averages of same category.137""" % (nrepeat, nrepeat)...

plots.py

Source:plots.py

...93    94    95def compute_FMR_FNMR_FDR(impostors_per_demographic_eval, genuines_per_demographic_eval, thresholds, far_thresholds,tablefmt="plain"):96    97    def generate_raw_table(performance_dict):98        """99        Generates a simple table where axis X and Y are respectivelly the values of demographics        100        and \tau respectivelly101        """102        demographics_vs_fmerit = np.array([np.round(performance_dict[d],4) for d in performance_dict])        103        return demographics_vs_fmerit104    def generate_tabulate_table(raw_table, header, demographics):105        """106        """107        extended_table = np.concatenate((np.array([demographics]).T, raw_table), axis=1)108        return tabulate.tabulate(extended_table, headers=header, tablefmt=tablefmt)109    def generate_fdr_table(fmrs_taus, fnmrs_taus):110        fdrs = []111        for i in range(fmrs_taus.shape[1]):112            fdr_tau = fairness_metric.compute_fdr(fmrs_taus[:,i],fnmrs_taus[:,i])113            fdrs.append(fdr_tau)114        return fdrs115    def generate_fdr_table_tabulate(fdr_raw_table, header):116        return tabulate.tabulate([fdr_raw_table], headers=header, tablefmt=tablefmt)117    FMR_raw, FNMR_raw = scoring.compute_fmr_fnmr_multiple_threshold(impostors_per_demographic_eval, genuines_per_demographic_eval, thresholds)118    header = [""] + [k for k in far_thresholds]119    demographics = [k for k in FMR_raw]120    121    print("##############################################")122    print("################## FMR #######################")123    print("##############################################")124    raw_table_fmr = generate_raw_table(FMR_raw)    125    print(generate_tabulate_table(raw_table_fmr, header, demographics))126    127    print("##############################################")128    print("################## FNMR #######################")129    print("##############################################")130    raw_table_fnmr = generate_raw_table(FNMR_raw)131    print(generate_tabulate_table(raw_table_fnmr, header, demographics))132    133    134    print("##############################################")135    print("################## FDR #######################")136    print("##############################################")137    fdr_raw_table = generate_fdr_table(raw_table_fmr, raw_table_fnmr)...

main.py

Source:main.py

...7from  wordle_table import  generate_words_table, generate_answers_table8from  data_gen import  build_answer_table, build_word_table,build_answer_list, build_word_list9if __name__ == '__main__':10    regenerate_data()11    generate_raw_table()12    filter_raw_table()13    build_answer_table()14    build_word_table()15    build_answer_list()...

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