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How to use set_format method in tappy

Best Python code snippet using tappy_python

classic.py

Source:classic.py

...238        for sample in sample_list:239            # grab reads from both sides of breakpoint240            read_batch, many = gather_all_reads(sample, chromA, posA, ciA, chromB, posB, ciB, z, max_reads)241            if many:242                var.genotype(sample.name).set_format('GT', './.')243                continue244            # initialize counts to zero245            ref_span, alt_span = 0, 0246            ref_seq, alt_seq = 0, 0247            alt_clip = 0248            # ref_ciA = ciA249            # ref_ciB = ciB250            ref_ciA = [0,0]251            ref_ciB = [0,0]252            for query_name in sorted(read_batch.keys()):253                fragment = read_batch[query_name]254                # boolean on whether to write the fragment255                write_fragment = False256                # -------------------------------------257                # Check for split-read evidence258                # -------------------------------------259                # get reference sequences260                for read in fragment.primary_reads:261                    is_ref_seq_A = fragment.is_ref_seq(read, var, chromA, posA, ciA, min_aligned)262                    is_ref_seq_B = fragment.is_ref_seq(read, var, chromB, posB, ciB, min_aligned)263                    if (is_ref_seq_A or is_ref_seq_B):264                        p_reference = prob_mapq(read)265                        ref_seq += p_reference266                        read.set_tag('XV', 'R')267                        write_fragment = True268                # get non-reference split-read support269                for split in fragment.split_reads:270                    split_lr = split.is_split_straddle(chromA, posA, ciA,271                                                       chromB, posB, ciB,272                                                       o1_is_reverse, o2_is_reverse,273                                                       svtype, split_slop)274                    # p_alt = prob_mapq(split.query_left) * prob_mapq(split.query_right)275                    p_alt = (prob_mapq(split.query_left) * split_lr[0] + prob_mapq(split.query_right) * split_lr[1]) / 2.0276                    if split.is_soft_clip:277                        alt_clip += p_alt278                    else:279                        alt_seq += p_alt280                    if p_alt > 0:281                        split.tag_split(p_alt)282                        write_fragment = True283                # -------------------------------------284                # Check for paired-end evidence285                # -------------------------------------286                # tally spanning alternate pairs287                if svtype == 'DEL' and posB - posA < 2 * fragment.lib.sd:288                    alt_straddle = False289                else:290                    alt_straddle = fragment.is_pair_straddle(chromA, posA, ciA,291                                                             chromB, posB, ciB,292                                                             o1_is_reverse, o2_is_reverse,293                                                             min_aligned,294                                                             fragment.lib)295                # check both sides if inversion (perhaps should do this for BND as well?)296                if svtype in ('INV'):297                    alt_straddle_reciprocal = fragment.is_pair_straddle(chromA, posA, ciA,298                                                                        chromB, posB, ciB,299                                                                        not o1_is_reverse,300                                                                        not o2_is_reverse,301                                                                        min_aligned,302                                                                        fragment.lib)303                else:304                    alt_straddle_reciprocal = False305                if alt_straddle or alt_straddle_reciprocal:306                    if svtype == 'DEL':307                        p_conc = fragment.p_concordant(var_length)308                        if p_conc is not None:309                            p_alt = (1 - p_conc) * prob_mapq(fragment.readA) * prob_mapq(fragment.readB)310                            alt_span += p_alt311                            # # since an alt straddler is by definition also a reference straddler,312                            # # we can bail out early here to save some time313                            # p_reference = p_conc * prob_mapq(fragment.readA) * prob_mapq(fragment.readB)314                            # ref_span += p_reference315                            # continue316                            fragment.tag_span(p_alt)317                            write_fragment = True318                    else:319                        p_alt = prob_mapq(fragment.readA) * prob_mapq(fragment.readB)320                        alt_span += p_alt321                        fragment.tag_span(p_alt)322                        write_fragment = True323                # # tally spanning reference pairs324                if svtype == 'DEL' and posB - posA < 2 * fragment.lib.sd:325                    ref_straddle_A = False326                    ref_straddle_B = False327                else:328                    ref_straddle_A = fragment.is_pair_straddle(chromA, posA, ref_ciA,329                                                               chromA, posA, ref_ciA,330                                                               False, True,331                                                               min_aligned,332                                                               fragment.lib)333                    ref_straddle_B = fragment.is_pair_straddle(chromB, posB, ref_ciB,334                                                               chromB, posB, ref_ciB,335                                                               False, True,336                                                               min_aligned,337                                                               fragment.lib)338                if ref_straddle_A or ref_straddle_B:339                    # don't allow the pair to jump the entire variant, except for340                    # length-changing SVs like deletions341                    if not (ref_straddle_A and ref_straddle_B) or svtype == 'DEL':342                        p_conc = fragment.p_concordant(var_length)343                        if p_conc is not None:344                            p_reference = p_conc * prob_mapq(fragment.readA) * prob_mapq(fragment.readB)345                            ref_span += (ref_straddle_A + ref_straddle_B) * p_reference / 2346                            fragment.tag_span(1 - p_conc)347                            write_fragment = True348                # write to BAM if requested349                if alignment_outpath is not None and  write_fragment:350                    for read in fragment.primary_reads + [split.read for split in fragment.split_reads]:351                        out_bam_written_reads = write_alignment(read, out_bam, out_bam_written_reads)352            if debug:353                print '--------------------------'354                print 'ref_span:', ref_span355                print 'alt_span:', alt_span356                print 'ref_seq:', ref_seq357                print 'alt_seq:', alt_seq358                print 'alt_clip:', alt_clip359            # in the absence of evidence for a particular type, ignore the reference360            # support for that type as well361            if (alt_seq + alt_clip) < 0.5 and alt_span >= 1:362                alt_seq = 0363                alt_clip = 0364                ref_seq = 0365            if alt_span < 0.5 and (alt_seq + alt_clip) >= 1:366                alt_span = 0367                ref_span = 0368            if alt_span + alt_seq == 0 and alt_clip > 0:369                # discount any SV that's only supported by clips.370                alt_clip = 0371            if ref_seq + alt_seq + ref_span + alt_span + alt_clip > 0:372                # get bayesian classifier373                if var.info['SVTYPE'] == "DUP": is_dup = True374                else: is_dup = False375                alt_splitters = alt_seq + alt_clip376                QR = int(split_weight * ref_seq) + int(disc_weight * ref_span)377                QA = int(split_weight * alt_splitters) + int(disc_weight * alt_span)378                gt_lplist = bayes_gt(QR, QA, is_dup)379                best, second_best = sorted([ (i, e) for i, e in enumerate(gt_lplist) ], key=lambda(x): x[1], reverse=True)[0:2]380                gt_idx = best[0]381                # print log probabilities of homref, het, homalt382                if debug:383                    print gt_lplist384                # set the overall variant QUAL score and sample specific fields385                var.genotype(sample.name).set_format('GL', ','.join(['%.0f' % x for x in gt_lplist]))386                var.genotype(sample.name).set_format('DP', int(ref_seq + alt_seq + alt_clip + ref_span + alt_span))387                var.genotype(sample.name).set_format('RO', int(ref_seq + ref_span))388                var.genotype(sample.name).set_format('AO', int(alt_seq + alt_clip + alt_span))389                var.genotype(sample.name).set_format('QR', QR)390                var.genotype(sample.name).set_format('QA', QA)391                # if detailed:392                var.genotype(sample.name).set_format('RS', int(ref_seq))393                var.genotype(sample.name).set_format('AS', int(alt_seq))394                var.genotype(sample.name).set_format('ASC', int(alt_clip))395                var.genotype(sample.name).set_format('RP', int(ref_span))396                var.genotype(sample.name).set_format('AP', int(alt_span))397                try:398                    var.genotype(sample.name).set_format('AB', '%.2g' % (QA / float(QR + QA)))399                except ZeroDivisionError:400                    var.genotype(sample.name).set_format('AB', '.')401                # assign genotypes402                gt_sum = 0403                for gt in gt_lplist:404                    try:405                        gt_sum += 10**gt406                    except OverflowError:407                        gt_sum += 0408                if gt_sum > 0:409                    gt_sum_log = math.log(gt_sum, 10)410                    sample_qual = abs(-10 * (gt_lplist[0] - gt_sum_log)) # phred-scaled probability site is non-reference in this sample411                    phred_gq = min(-10 * (second_best[1] - best[1]), 200)412                    var.genotype(sample.name).set_format('GQ', int(phred_gq))413                    var.genotype(sample.name).set_format('SQ', sample_qual)414                    var.qual += sample_qual415                    if gt_idx == 1:416                        var.genotype(sample.name).set_format('GT', '0/1')417                    elif gt_idx == 2:418                        var.genotype(sample.name).set_format('GT', '1/1')419                    elif gt_idx == 0:420                        var.genotype(sample.name).set_format('GT', '0/0')421                else:422                    var.genotype(sample.name).set_format('GQ', '.')423                    var.genotype(sample.name).set_format('SQ', '.')424                    var.genotype(sample.name).set_format('GT', './.')425            else:426                var.genotype(sample.name).set_format('GT', './.')427                var.qual = 0428                var.genotype(sample.name).set_format('GQ', '.')429                var.genotype(sample.name).set_format('SQ', '.')430                var.genotype(sample.name).set_format('GL', '.')431                var.genotype(sample.name).set_format('DP', 0)432                var.genotype(sample.name).set_format('AO', 0)433                var.genotype(sample.name).set_format('RO', 0)434                # if detailed:435                var.genotype(sample.name).set_format('AS', 0)436                var.genotype(sample.name).set_format('ASC', 0)437                var.genotype(sample.name).set_format('RS', 0)438                var.genotype(sample.name).set_format('AP', 0)439                var.genotype(sample.name).set_format('RP', 0)440                var.genotype(sample.name).set_format('QR', 0)441                var.genotype(sample.name).set_format('QA', 0)442                var.genotype(sample.name).set_format('AB', '.')443        # after all samples have been processed, write444        vcf_out.write(var.get_var_string() + '\n')445        if var.info['SVTYPE'] == 'BND':446            var2.qual = var.qual447            var2.active_formats = var.active_formats448            var2.genotype = var.genotype449            vcf_out.write(var2.get_var_string() + '\n')450    # throw warning if we've lost unpaired breakends451    if breakend_dict:452        logging.warning('Unpaired breakends found in file. These will not be present in output.')453    # close the files454    vcf_in.close()455    vcf_out.close()456    if alignment_outpath is not None:...

CollegeData.py

Source:CollegeData.py

...24    total_schools = json.loads(res.text)["results"]25    return [x["slug"] for x in total_schools]26def find_specific_function(title):27    if "Freshman" in title:28        return freshman_admission_reqs.set_format()29    elif "Applying" in title:30        return applying_for_admission()31    elif "Selection" in title:32        return selection_of_student33    else:34        return profile_of_fall_admission35class CollegeData:36    def __init__(self):37        self.build_id = get_build_id()38        school_nums = get_total_school_nums()39        self.slugs = get_total_school_slugs(school_nums)40    def get_total_school_data(self):41        school = dict()42        num = 143        start = time.time()44        with tqdm(total=len(self.slugs)) as bar:45            i = 046            while i < len(self.slugs):47                slug = self.slugs[i]48                try:49                    # print(slug)50                    overview, admission, campus, money, academic, student = dict(), dict(), dict(), dict(), dict(), dict()51                    num += 152                    self.__set_overview(slug, overview, admission)53                    self.__set_admission(slug, admission)54                    self.__set_money(slug, money)55                    self.__set_academic(slug, academic)56                    self.__set_campus(slug, campus)57                    self.__set_student(slug, student)58                    school.update({59                        slug: {60                            "overview": overview,61                            "admissions": admission,62                            "moneys": money,63                            "academics": academic,64                            "campus": campus,65                            "students": student66                        }67                    })68                    i += 169                    bar.update(1)70                except ValueError:71                    continue72        end = time.time()73        print("++++++++ College Data Total ++++++++")74        print(end - start)75        print("++++++++++++++++++++++++++++++++++++")76        return school77    def __set_overview(self, slug, overview, admission):78        # print(f"{slug} overview")79        link = f"https://www.collegedata.com/_next/data/{self.build_id}/college-search/{slug}.json"80        res = requests.get(link)81        if res.text and "profile" in json.loads(res.text)["pageProps"]:82            profile = json.loads(res.text)["pageProps"]["profile"]83            entrance_difficulty = profile["bodyContent"][0]["data"]["children"][0]["data"]["value"][0]84            overview.update({85                "name": profile["name"],86                "website": profile["website"],87                "overview": profile["description"]88            })89            admission.update({90                "entrance_difficulty": entrance_difficulty91            })92        else:93            console = Console()94            console.print(f"{slug} overview", style="bold red")95    def __set_admission(self, slug, admission):96        # print(f"{slug} admission")97        link = f"https://www.collegedata.com/_next/data/{self.build_id}/college-search/{slug}/admission.json"98        res = requests.get(link)99        if res.text and "profile" in json.loads(res.text)["pageProps"]:100            profile = json.loads(res.text)["pageProps"]["profile"]101            for el in profile["bodyContent"]:102                data = el["data"]103                title = data["title"]104                if "Freshman" in title:105                    freshman_admission_reqs.set_format(data["children"], admission)106                elif "Applying" in title:107                    applying_for_admission.set_format(data["children"], admission)108                elif "Selection" in title:109                    selection_of_student.set_format(data["children"], admission)110                else:111                    profile_of_fall_admission.set_format(data["children"], admission)112        else:113            console = Console()114            console.print(f"{slug} admission", style="bold red")115    def __set_money(self, slug, money):116        # print(f"{slug} money")117        link = f"https://www.collegedata.com/_next/data/{self.build_id}/college-search/{slug}/money-matters.json"118        res = requests.get(link)119        if res.text and "profile" in json.loads(res.text)["pageProps"]:120            profile = json.loads(res.text)["pageProps"]["profile"]121            tuition_and_expenses.set_format(profile, money)122            for content in profile["bodyContent"]:123                data = content["data"]124                title = data["title"]125                if "Applying" in title:126                    applying_for_financial_aid.set_format(data["children"], money)127                elif "Profile" in title:128                    profile_of_financial_aid.set_format(data["children"], money)129                elif "Financial" in title:130                    financial_aid_programs.set_format(data["children"], money)131        else:132            console = Console()133            console.print(f"{slug} money", style="bold red")134    def __set_academic(self, slug, academic):135        # print(f"{slug} academic")136        link = f"https://www.collegedata.com/_next/data/{self.build_id}/college-search/{slug}/academics.json"137        res = requests.get(link)138        if res.text and "profile" in json.loads(res.text)["pageProps"]:139            profile = json.loads(res.text)["pageProps"]["profile"]140            general_information.set_format(profile, academic)141            for content in profile["bodyContent"]:142                data = content["data"]143                title = data["title"]144                if "Undergraduate" in title:145                    undergraduate_education.set_format(data["children"], academic)146                elif "Curriculum" in title:147                    curriculum_and_graduation_requirements.set_format(data["children"], academic)148                elif "Faculty" in title:149                    faculty_and_instruction.set_format(data["children"], academic)150                elif "Advanced" in title:151                    advanced_placement.set_format(data["children"], academic)152                elif "Academic Resources" in title:153                    academic_resources.set_format(data["children"], academic)154                elif "Academic Support Services" in title:155                    academic_support_services.set_format(data["children"], academic)156                elif "Graduate/Professional" in title:157                    school_education.set_format(data["children"], academic)158        else:159            console = Console()160            console.print(f"{slug} academic", style="bold red")161    def __set_campus(self, slug, campus):162        # print(f"{slug} campus")163        link = f"https://www.collegedata.com/_next/data/{self.build_id}/college-search/{slug}/campus-life.json"164        res = requests.get(link)165        if res.text and "profile" in json.loads(res.text)["pageProps"]:166            profile = json.loads(res.text)["pageProps"]["profile"]167            for content in profile["bodyContent"]:168                data = content["data"]169                title = data["title"]170                if title == "Location and Setting":171                    location_and_setting.set_format(data["children"], campus)172                elif title == "Housing":173                    housing.set_format(data["children"], campus)174                elif title == "Security":175                    security.set_format(data["children"], campus)176                elif title == "Personal Support Services":177                    personal_support_services.set_format(data["children"], campus)178                elif title == "Sports & Recreation":179                    sports_and_recreation.set_format(data["children"], campus)180        else:181            console = Console()182            console.print(f"{slug} campus", style="bold red")183    def __set_student(self, slug, student):184        # print(f"{slug} student")185        link = f"https://www.collegedata.com/_next/data/{self.build_id}/college-search/{slug}/students.json"186        res = requests.get(link)187        if res.text and "profile" in json.loads(res.text)["pageProps"]:188            profile = json.loads(res.text)["pageProps"]["profile"]189            for content in profile["bodyContent"]:190                data = content["data"]191                title = data["title"]192                if title == "Student Body":193                    student_body.set_format(data["children"], student)194                elif "Undergraduate Retention" in title:195                    undergraduate_retention_and_graduation.set_format(data["children"], student)196                elif title == "After Graduation":197                    after_graduation.set_format(data["children"], student)198        else:199            console = Console()...

dataset.py

Source:dataset.py

...3import torch4from datasets import Dataset, load_from_disk5def get_amazon_polarity(path_to_dataset: str) -> Dict[str, Dataset]:6    train_dataset = load_from_disk(os.path.join(path_to_dataset, "train"))7    train_dataset.set_format(8        type="torch",9        columns=["input_ids", "token_type_ids", "attention_mask", "labels"],10    )11    val_dataset = load_from_disk(os.path.join(path_to_dataset, "val"))12    val_dataset.set_format(13        type="torch",14        columns=["input_ids", "token_type_ids", "attention_mask", "labels"],15    )16    return {"train": train_dataset, "val": val_dataset}17def get_acronym_identification(path_to_dataset: str) -> Dict[str, Dataset]:18    train_dataset = load_from_disk(os.path.join(path_to_dataset, "train"))19    train_dataset.set_format(20        type="torch",21        columns=["input_ids", "token_type_ids", "attention_mask", "labels"],22    )23    val_dataset = load_from_disk(os.path.join(path_to_dataset, "val"))24    val_dataset.set_format(25        type="torch",26        columns=["input_ids", "token_type_ids", "attention_mask", "labels"],27    )28    return {"train": train_dataset, "val": val_dataset}29def get_swag(path_to_dataset: str) -> Dict[str, Dataset]:30    def set_format(row):31        return {32            "input_ids": torch.tensor(row["input_ids"]),33            "token_type_ids": torch.tensor(row["token_type_ids"]),34            "attention_mask": torch.tensor(row["attention_mask"]),35            "labels": row["labels"],36        }37    train_dataset = load_from_disk(os.path.join(path_to_dataset, "train"))38    train_dataset.set_transform(set_format)39    val_dataset = load_from_disk(os.path.join(path_to_dataset, "val"))40    val_dataset.set_transform(set_format)41    return {"train": train_dataset, "val": val_dataset}42GET_DATASET = {43    "amazon_polarity": get_amazon_polarity,44    "acronym_identification": get_acronym_identification,...

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