Dataset Viewer
Auto-converted to Parquet Duplicate
sequence
stringlengths
1.25k
34.6k
code
stringlengths
75
8.58k
{'id': '0', 'type': 'module', 'children': ['1']},{'id': '1', 'type': 'function_definition', 'children': ['2', '3', '5']},{'id': '2', 'type': 'function_name', 'children': [], 'value': 'parse_paren_group'},{'id': '3', 'type': 'parameters', 'children': ['4']},{'id': '4', 'type': 'identifier', 'children': [], 'value': 'par...
def parse_paren_group(paren_string): def max_depth(s): depth = 0 max_depth = 0 for c in s: if c == '(': depth += 1 max_depth = max(max_depth, depth) elif c == ')': depth -= 1 return max_depth return [max_dep...
{'id': '0', 'type': 'module', 'children': ['1']},{'id': '1', 'type': 'function_definition', 'children': ['2', '3', '9']},{'id': '2', 'type': 'function_name', 'children': [], 'value': 'gather_categories'},{'id': '3', 'type': 'parameters', 'children': ['4', '5', '6']},{'id': '4', 'type': 'identifier', 'children': [], 'va...
def gather_categories(imap, header, categories=None): if categories is None: return {"default": DataCategory(set(imap.keys()), {})} cat_ids = [header.index(cat) for cat in categories if cat in header and "=" not in cat] table = OrderedDict() conditions = defaultdict(set) for i...
{'id': '0', 'type': 'module', 'children': ['1']},{'id': '1', 'type': 'function_definition', 'children': ['2', '3', '10']},{'id': '2', 'type': 'function_name', 'children': [], 'value': 'color_mapping'},{'id': '3', 'type': 'parameters', 'children': ['4', '5', '6', '7']},{'id': '4', 'type': 'identifier', 'children': [], '...
def color_mapping(sample_map, header, group_column, color_column=None): group_colors = OrderedDict() group_gather = gather_categories(sample_map, header, [group_column]) if color_column is not None: color_gather = gather_categories(sample_map, header, [color_column]) for group in group_gathe...
{'id': '0', 'type': 'module', 'children': ['1']},{'id': '1', 'type': 'function_definition', 'children': ['2', '3', '29']},{'id': '2', 'type': 'function_name', 'children': [], 'value': 'shuffle_genome'},{'id': '3', 'type': 'parameters', 'children': ['4', '5', '6', '12', '15', '16', '19', '22', '23', '26']},{'id': '4', '...
def shuffle_genome(genome, cat, fraction = float(100), plot = True, \ alpha = 0.1, beta = 100000, \ min_length = 1000, max_length = 200000): header = '>randomized_%s' % (genome.name) sequence = list(''.join([i[1] for i in parse_fasta(genome)])) length = len(sequence) shuffled = [] wh...
{'id': '0', 'type': 'module', 'children': ['1']},{'id': '1', 'type': 'function_definition', 'children': ['2', '3', '11']},{'id': '2', 'type': 'function_name', 'children': [], 'value': 'sam2fastq'},{'id': '3', 'type': 'parameters', 'children': ['4', '5', '8']},{'id': '4', 'type': 'identifier', 'children': [], 'value': '...
def sam2fastq(sam, singles = False, force = False): L, R = None, None for line in sam: if line.startswith('@') is True: continue line = line.strip().split() bit = [True if i == '1' else False \ for i in bin(int(line[1])).split('b')[1][::-1]] while len(...
{'id': '0', 'type': 'module', 'children': ['1']},{'id': '1', 'type': 'function_definition', 'children': ['2', '3', '6']},{'id': '2', 'type': 'function_name', 'children': [], 'value': 'sort_sam'},{'id': '3', 'type': 'parameters', 'children': ['4', '5']},{'id': '4', 'type': 'identifier', 'children': [], 'value': 'sam'},{...
def sort_sam(sam, sort): tempdir = '%s/' % (os.path.abspath(sam).rsplit('/', 1)[0]) if sort is True: mapping = '%s.sorted.sam' % (sam.rsplit('.', 1)[0]) if sam != '-': if os.path.exists(mapping) is False: os.system("\ sort -k1 --buffer-size=%sG -T ...
{'id': '0', 'type': 'module', 'children': ['1']},{'id': '1', 'type': 'function_definition', 'children': ['2', '3', '12']},{'id': '2', 'type': 'function_name', 'children': [], 'value': 'crossmap'},{'id': '3', 'type': 'parameters', 'children': ['4', '5', '6', '7', '8', '9', '10', '11']},{'id': '4', 'type': 'identifier', ...
def crossmap(fas, reads, options, no_shrink, keepDB, threads, cluster, nodes): if cluster is True: threads = '48' btc = [] for fa in fas: btd = bowtiedb(fa, keepDB) F, R, U = reads if F is not False: if U is False: u = False for i, f in...
{'id': '0', 'type': 'module', 'children': ['1']},{'id': '1', 'type': 'function_definition', 'children': ['2', '3', '6']},{'id': '2', 'type': 'function_name', 'children': [], 'value': 'bit_by_bit'},{'id': '3', 'type': 'parameters', 'children': ['4', '5']},{'id': '4', 'type': 'identifier', 'children': [], 'value': 'self'...
def bit_by_bit(self, in_data): if isinstance(in_data, str): in_data = [ord(c) for c in in_data] register = self.NonDirectInit for octet in in_data: if self.ReflectIn: octet = self.reflect(octet, 8) for i in range(8): topbit = re...
{'id': '0', 'type': 'module', 'children': ['1']},{'id': '1', 'type': 'function_definition', 'children': ['2', '3', '6']},{'id': '2', 'type': 'function_name', 'children': [], 'value': 'parse_ggKbase_tables'},{'id': '3', 'type': 'parameters', 'children': ['4', '5']},{'id': '4', 'type': 'identifier', 'children': [], 'valu...
def parse_ggKbase_tables(tables, id_type): g2info = {} for table in tables: for line in open(table): line = line.strip().split('\t') if line[0].startswith('name'): header = line header[4] = 'genome size (bp)' header[12] = ' ...
{'id': '0', 'type': 'module', 'children': ['1']},{'id': '1', 'type': 'function_definition', 'children': ['2', '3', '8']},{'id': '2', 'type': 'function_name', 'children': [], 'value': 'top_hits'},{'id': '3', 'type': 'parameters', 'children': ['4', '5', '6', '7']},{'id': '4', 'type': 'identifier', 'children': [], 'value'...
def top_hits(hits, num, column, reverse): hits.sort(key = itemgetter(column), reverse = reverse) for hit in hits[0:num]: yield hit
{'id': '0', 'type': 'module', 'children': ['1']},{'id': '1', 'type': 'function_definition', 'children': ['2', '3', '8']},{'id': '2', 'type': 'function_name', 'children': [], 'value': 'numBlast_sort'},{'id': '3', 'type': 'parameters', 'children': ['4', '5', '6', '7']},{'id': '4', 'type': 'identifier', 'children': [], 'v...
def numBlast_sort(blast, numHits, evalueT, bitT): header = [' 'qstart', 'qend', 'tstart', 'tend', 'evalue', 'bitscore'] yield header hmm = {h:[] for h in header} for line in blast: if line.startswith(' continue line = line.strip().split('\t') line[10], l...
{'id': '0', 'type': 'module', 'children': ['1', '64', '67', '75', '267']},{'id': '1', 'type': 'function_definition', 'children': ['2', '3', '9', '47']},{'id': '2', 'type': 'function_name', 'children': [], 'value': 'numDomtblout'},{'id': '3', 'type': 'parameters', 'children': ['4', '5', '6', '7', '8']},{'id': '4', 'type...
def numDomtblout(domtblout, numHits, evalueT, bitT, sort): if sort is True: for hit in numDomtblout_sort(domtblout, numHits, evalueT, bitT): yield hit return header = [' 'query name', 'query accession', 'qlen', 'full E-value', 'full score', 'full bias', ...
End of preview. Expand in Data Studio

No dataset card yet

Downloads last month
16