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',
... |
{'id': '0', 'type': 'module', 'children': ['1']},{'id': '1', 'type': 'function_definition', 'children': ['2', '3', '5']},{'id': '2', 'type': 'function_name', 'children': [], 'value': 'compare_clades'},{'id': '3', 'type': 'parameters', 'children': ['4']},{'id': '4', 'type': 'identifier', 'children': [], 'value': 'pw'},{... | def compare_clades(pw):
names = sorted(set([i for i in pw]))
for i in range(0, 4):
wi, bt = {}, {}
for a in names:
for b in pw[a]:
if ';' not in a or ';' not in b:
continue
pident = pw[a][b]
cA, cB = a.split(';')[i],... |
{'id': '0', 'type': 'module', 'children': ['1']},{'id': '1', 'type': 'function_definition', 'children': ['2', '3', '5']},{'id': '2', 'type': 'function_name', 'children': [], 'value': 'searchAccession'},{'id': '3', 'type': 'parameters', 'children': ['4']},{'id': '4', 'type': 'identifier', 'children': [], 'value': 'acc'}... | def searchAccession(acc):
out, error = entrez('genome', acc)
for line in out.splitlines():
line = line.decode('ascii').strip()
if 'Assembly_Accession' in line or 'BioSample' in line:
newAcc = line.split('>')[1].split('<')[0].split('.')[0].split(',')[0]
if len(newAcc) > 0:... |
{'id': '0', 'type': 'module', 'children': ['1']},{'id': '1', 'type': 'function_definition', 'children': ['2', '3', '11']},{'id': '2', 'type': 'function_name', 'children': [], 'value': '_configure_logger'},{'id': '3', 'type': 'parameters', 'children': ['4', '5', '6', '7', '8', '9', '10']},{'id': '4', 'type': 'identifier... | def _configure_logger(fmt, quiet, level, fpath,
pre_hooks, post_hooks, metric_grouping_interval):
level = getattr(logging, level.upper())
global _GLOBAL_LOG_CONFIGURED
if _GLOBAL_LOG_CONFIGURED:
return
def wrap_hook(fn):
@wraps(fn)
def processor(logger, method_name, event_dic... |
{'id': '0', 'type': 'module', 'children': ['1']},{'id': '1', 'type': 'function_definition', 'children': ['2', '3', '6']},{'id': '2', 'type': 'function_name', 'children': [], 'value': 'combine_modifiers'},{'id': '3', 'type': 'parameters', 'children': ['4', '5']},{'id': '4', 'type': 'identifier', 'children': [], 'value':... | def combine_modifiers(self, graphemes):
result = []
temp = ""
count = len(graphemes)
for grapheme in reversed(graphemes):
count -= 1
if len(grapheme) == 1 and unicodedata.category(grapheme) == "Lm" \
and not ord(grapheme) in [712, 716]:
... |
{'id': '0', 'type': 'module', 'children': ['1']},{'id': '1', 'type': 'function_definition', 'children': ['2', '3', '9']},{'id': '2', 'type': 'function_name', 'children': [], 'value': 'check_mismatches'},{'id': '3', 'type': 'parameters', 'children': ['4', '5', '6', '7', '8']},{'id': '4', 'type': 'identifier', 'children'... | def check_mismatches(read, pair, mismatches, mm_option, req_map):
if pair is False:
mm = count_mismatches(read)
if mm is False:
return False
if mismatches is False:
return True
if mm <= mismatches:
return True
r_mm = count_mismatches(read)
... |
{'id': '0', 'type': 'module', 'children': ['1']},{'id': '1', 'type': 'function_definition', 'children': ['2', '3', '4']},{'id': '2', 'type': 'function_name', 'children': [], 'value': 'get_steam'},{'id': '3', 'type': 'parameters', 'children': []},{'id': '4', 'type': 'block', 'children': ['5', '25', '33', '47', '61', '84... | def get_steam():
helper = lambda udd: Steam(udd) if os.path.exists(udd) else None
plat = platform.system()
if plat == 'Darwin':
return helper(paths.default_osx_userdata_path())
if plat == 'Linux':
return helper(paths.default_linux_userdata_path())
if plat == 'Windows':
possible_dir = winutils.find... |
{'id': '0', 'type': 'module', 'children': ['1']},{'id': '1', 'type': 'function_definition', 'children': ['2', '3', '8']},{'id': '2', 'type': 'function_name', 'children': [], 'value': 'generate_barcodes'},{'id': '3', 'type': 'parameters', 'children': ['4', '5']},{'id': '4', 'type': 'identifier', 'children': [], 'value':... | def generate_barcodes(nIds, codeLen=12):
def next_code(b, c, i):
return c[:i] + b + (c[i+1:] if i < -1 else '')
def rand_base():
return random.choice(['A', 'T', 'C', 'G'])
def rand_seq(n):
return ''.join([rand_base() for _ in range(n)])
hpf = re.compile('aaaa|cccc|gggg|tttt', re.... |
{'id': '0', 'type': 'module', 'children': ['1']},{'id': '1', 'type': 'ERROR', 'children': ['2']},{'id': '2', 'type': 'function_definition', 'children': ['3', '4', '8']},{'id': '3', 'type': 'function_name', 'children': [], 'value': 'parse_fasta_annotations'},{'id': '4', 'type': 'parameters', 'children': ['5', '6', '7']}... | def parse_fasta_annotations(fastas, annot_tables, trans_table):
if annot_tables is not False:
annots = {}
for table in annot_tables:
for cds in open(table):
ID, start, end, strand = cds.strip().split()
annots[ID] = [start, end, int(strand)]
for fasta i... |
{'id': '0', 'type': 'module', 'children': ['1']},{'id': '1', 'type': 'function_definition', 'children': ['2', '3', '5']},{'id': '2', 'type': 'function_name', 'children': [], 'value': 'find_consensus'},{'id': '3', 'type': 'parameters', 'children': ['4']},{'id': '4', 'type': 'identifier', 'children': [], 'value': 'bases'... | def find_consensus(bases):
nucs = ['A', 'T', 'G', 'C', 'N']
total = sum([bases[nuc] for nuc in nucs if nuc in bases])
try:
top = max([bases[nuc] for nuc in nucs if nuc in bases])
except:
bases['consensus'] = ('N', 'n/a')
bases['consensus frequency'] = 'n/a'
bases['referen... |
{'id': '0', 'type': 'module', 'children': ['1']},{'id': '1', 'type': 'function_definition', 'children': ['2', '3', '5']},{'id': '2', 'type': 'function_name', 'children': [], 'value': 'print_consensus'},{'id': '3', 'type': 'parameters', 'children': ['4']},{'id': '4', 'type': 'identifier', 'children': [], 'value': 'genom... | def print_consensus(genomes):
cons = {}
for genome, contigs in list(genomes.items()):
cons[genome] = {}
for contig, samples in list(contigs.items()):
for sample, stats in list(samples.items()):
if sample not in cons[genome]:
cons[genome][sample] = ... |
{'id': '0', 'type': 'module', 'children': ['1']},{'id': '1', 'type': 'function_definition', 'children': ['2', '3', '6']},{'id': '2', 'type': 'function_name', 'children': [], 'value': 'parse_cov'},{'id': '3', 'type': 'parameters', 'children': ['4', '5']},{'id': '4', 'type': 'identifier', 'children': [], 'value': 'cov_ta... | def parse_cov(cov_table, scaffold2genome):
size = {}
mapped = {}
for line in open(cov_table):
line = line.strip().split('\t')
if line[0].startswith('
samples = line[1:]
samples = [i.rsplit('/', 1)[-1].split('.', 1)[0] for i in samples]
continue
s... |
{'id': '0', 'type': 'module', 'children': ['1']},{'id': '1', 'type': 'function_definition', 'children': ['2', '3', '8']},{'id': '2', 'type': 'function_name', 'children': [], 'value': 'print_genome_matrix'},{'id': '3', 'type': 'parameters', 'children': ['4', '5', '6', '7']},{'id': '4', 'type': 'identifier', 'children': ... | def print_genome_matrix(hits, fastas, id2desc, file_name):
out = open(file_name, 'w')
fastas = sorted(fastas)
print('
print('
for fasta in fastas:
line = [fasta]
for other in fastas:
if other == fasta:
average = '-'
else:
averag... |
{'id': '0', 'type': 'module', 'children': ['1']},{'id': '1', 'type': 'ERROR', 'children': ['2', '298', '304']},{'id': '2', 'type': 'function_definition', 'children': ['3', '4', '17']},{'id': '3', 'type': 'function_name', 'children': [], 'value': 'calc_thresholds'},{'id': '4', 'type': 'parameters', 'children': ['5', '6'... | def calc_thresholds(rbh, file_name, thresholds = [False, False, False, False], stdevs = 2):
calc_threshold = thresholds[-1]
norm_threshold = {}
for pair in itertools.permutations([i for i in rbh], 2):
if pair[0] not in norm_threshold:
norm_threshold[pair[0]] = {}
norm_threshold[p... |
{'id': '0', 'type': 'module', 'children': ['1']},{'id': '1', 'type': 'function_definition', 'children': ['2', '3', '8']},{'id': '2', 'type': 'function_name', 'children': [], 'value': '_update_property'},{'id': '3', 'type': 'parameters', 'children': ['4', '5', '6', '7']},{'id': '4', 'type': 'identifier', 'children': [],... | def _update_property(tree_to_update, xpath_root, xpaths, values):
def update_element(elem, idx, root, path, vals):
has_root = bool(root and len(path) > len(root) and path.startswith(root))
path, attr = get_xpath_tuple(path)
if attr:
removed = [get_element(elem, path)]
... |
{'id': '0', 'type': 'module', 'children': ['1']},{'id': '1', 'type': 'function_definition', 'children': ['2', '3', '9']},{'id': '2', 'type': 'function_name', 'children': [], 'value': 'validate_complex_list'},{'id': '3', 'type': 'parameters', 'children': ['4', '5', '6']},{'id': '4', 'type': 'identifier', 'children': [],... | def validate_complex_list(prop, value, xpath_map=None):
if value is not None:
validate_type(prop, value, (dict, list))
if prop in _complex_definitions:
complex_keys = _complex_definitions[prop]
else:
complex_keys = {} if xpath_map is None else xpath_map
for id... |
{'id': '0', 'type': 'module', 'children': ['1']},{'id': '1', 'type': 'function_definition', 'children': ['2', '3', '9']},{'id': '2', 'type': 'function_name', 'children': [], 'value': 'validate_dates'},{'id': '3', 'type': 'parameters', 'children': ['4', '5', '6']},{'id': '4', 'type': 'identifier', 'children': [], 'value... | def validate_dates(prop, value, xpath_map=None):
if value is not None:
validate_type(prop, value, dict)
date_keys = set(value)
if date_keys:
if DATE_TYPE not in date_keys or DATE_VALUES not in date_keys:
if prop in _complex_definitions:
complex... |
{'id': '0', 'type': 'module', 'children': ['1']},{'id': '1', 'type': 'function_definition', 'children': ['2', '3', '5']},{'id': '2', 'type': 'function_name', 'children': [], 'value': 'getCharacterSet'},{'id': '3', 'type': 'parameters', 'children': ['4']},{'id': '4', 'type': 'identifier', 'children': [], 'value': 'self'... | def getCharacterSet(self):
'''Get a character set with individual members or ranges.
Current index is on '[', the start of the character set.
'''
chars = u''
c = None
cnt = 1
start = 0
while True:
escaped_slash = False
c = self.next... |
{'id': '0', 'type': 'module', 'children': ['1']},{'id': '1', 'type': 'function_definition', 'children': ['2', '3', '8']},{'id': '2', 'type': 'function_name', 'children': [], 'value': 'getSequence'},{'id': '3', 'type': 'parameters', 'children': ['4', '5']},{'id': '4', 'type': 'identifier', 'children': [], 'value': 'self... | def getSequence(self, level=0):
'''Get a sequence of nodes.'''
seq = []
op = ''
left_operand = None
right_operand = None
sequence_closed = False
while True:
c = self.next()
if not c:
break
if c and c not in self.... |
{'id': '0', 'type': 'module', 'children': ['1']},{'id': '1', 'type': 'function_definition', 'children': ['2', '3', '8']},{'id': '2', 'type': 'function_name', 'children': [], 'value': 'process'},{'id': '3', 'type': 'parameters', 'children': ['4', '5', '6', '7']},{'id': '4', 'type': 'identifier', 'children': [], 'value':... | def process(self, data, type, history):
if type in history:
return
if type.enum():
return
history.append(type)
resolved = type.resolve()
value = None
if type.multi_occurrence():
value = []
else:
if len(resolved) > 0:... |
{'id': '0', 'type': 'module', 'children': ['1']},{'id': '1', 'type': 'function_definition', 'children': ['2', '3', '8']},{'id': '2', 'type': 'function_name', 'children': [], 'value': '_process_tz'},{'id': '3', 'type': 'parameters', 'children': ['4', '5', '6', '7']},{'id': '4', 'type': 'identifier', 'children': [], 'val... | def _process_tz(self, dt, naive, tz):
def _tz(t):
if t in (None, 'naive'):
return t
if t == 'local':
if __debug__ and not localtz:
raise ValueError("Requested conversion to local timezone, but `localtz` not installed.")
t = localtz
if not isinstance(t, tzinfo):
if __debug__ and not local... |
{'id': '0', 'type': 'module', 'children': ['1']},{'id': '1', 'type': 'function_definition', 'children': ['2', '3', '8']},{'id': '2', 'type': 'function_name', 'children': [], 'value': '__dfs'},{'id': '3', 'type': 'parameters', 'children': ['4', '5', '6', '7']},{'id': '4', 'type': 'identifier', 'children': [], 'value': '... | def __dfs(self, v, index, layers):
if index == 0:
path = [v]
while self._dfs_parent[v] != v:
path.append(self._dfs_parent[v])
v = self._dfs_parent[v]
self._dfs_paths.append(path)
return True
for neighbour in self._graph[v]:
... |
{'id': '0', 'type': 'module', 'children': ['1']},{'id': '1', 'type': 'function_definition', 'children': ['2', '3', '10']},{'id': '2', 'type': 'function_name', 'children': [], 'value': 'login'},{'id': '3', 'type': 'parameters', 'children': ['4', '5', '6', '7']},{'id': '4', 'type': 'identifier', 'children': [], 'value': ... | def login(self, username, password, login_token=None):
if login_token is None:
token_doc = self.post(action='query', meta='tokens', type='login')
login_token = token_doc['query']['tokens']['logintoken']
login_doc = self.post(
action="clientlogin", username=username, p... |
{'id': '0', 'type': 'module', 'children': ['1']},{'id': '1', 'type': 'function_definition', 'children': ['2', '3', '6']},{'id': '2', 'type': 'function_name', 'children': [], 'value': 'cut_levels'},{'id': '3', 'type': 'parameters', 'children': ['4', '5']},{'id': '4', 'type': 'identifier', 'children': [], 'value': 'nodes... | def cut_levels(nodes, start_level):
final = []
removed = []
for node in nodes:
if not hasattr(node, 'level'):
remove(node, removed)
continue
if node.attr.get('soft_root', False):
remove(node, removed)
continue
if node.level == start_lev... |
{'id': '0', 'type': 'module', 'children': ['1']},{'id': '1', 'type': 'function_definition', 'children': ['2', '3', '7']},{'id': '2', 'type': 'function_name', 'children': [], 'value': 'S'},{'id': '3', 'type': 'parameters', 'children': ['4', '5']},{'id': '4', 'type': 'identifier', 'children': [], 'value': 'Document'},{'i... | def S(Document, *fields):
result = []
for field in fields:
if isinstance(field, tuple):
field, direction = field
result.append((field, direction))
continue
direction = ASCENDING
if not field.startswith('__'):
field = field.replace('__', '.')
if field[0] == '-':
direction = DESCENDING
if field... |
{'id': '0', 'type': 'module', 'children': ['1']},{'id': '1', 'type': 'function_definition', 'children': ['2', '3', '6']},{'id': '2', 'type': 'function_name', 'children': [], 'value': 'valid'},{'id': '3', 'type': 'parameters', 'children': ['4', '5']},{'id': '4', 'type': 'identifier', 'children': [], 'value': 'self'},{'i... | def valid(self, cnpj):
if len(cnpj) != 14:
return False
tam = 12
nums = cnpj[:tam]
digs = cnpj[tam:]
tot = 0
pos = tam-7
for i in range(tam, 0, -1):
tot = tot + int(nums[tam-i])*pos
pos = pos - 1
if pos < 2:
... |
{'id': '0', 'type': 'module', 'children': ['1']},{'id': '1', 'type': 'function_definition', 'children': ['2', '3', '8']},{'id': '2', 'type': 'function_name', 'children': [], 'value': 'arrayuniqify'},{'id': '3', 'type': 'parameters', 'children': ['4', '5']},{'id': '4', 'type': 'identifier', 'children': [], 'value': 'X'}... | def arrayuniqify(X, retainorder=False):
s = X.argsort()
X = X[s]
D = np.append([True],X[1:] != X[:-1])
if retainorder:
DD = np.append(D.nonzero()[0],len(X))
ind = [min(s[x:DD[i+1]]) for (i,x) in enumerate(DD[:-1])]
ind.sort()
return ind
else:
return [D,s] |
{'id': '0', 'type': 'module', 'children': ['1']},{'id': '1', 'type': 'function_definition', 'children': ['2', '3', '6']},{'id': '2', 'type': 'function_name', 'children': [], 'value': 'equalspairs'},{'id': '3', 'type': 'parameters', 'children': ['4', '5']},{'id': '4', 'type': 'identifier', 'children': [], 'value': 'X'},... | def equalspairs(X, Y):
T = Y.copy()
R = (T[1:] != T[:-1]).nonzero()[0]
R = np.append(R,np.array([len(T)-1]))
M = R[R.searchsorted(range(len(T)))]
D = T.searchsorted(X)
T = np.append(T,np.array([0]))
M = np.append(M,np.array([0]))
A = (T[D] == X) * D
B = (T[D] == X) * (M[D] + 1)
r... |
{'id': '0', 'type': 'module', 'children': ['1']},{'id': '1', 'type': 'function_definition', 'children': ['2', '3', '22']},{'id': '2', 'type': 'function_name', 'children': [], 'value': 'loadSV'},{'id': '3', 'type': 'parameters', 'children': ['4', '5', '8', '11', '14', '17', '20']},{'id': '4', 'type': 'identifier', 'chil... | def loadSV(fname, shape=None, titles=None, aligned=False, byteorder=None,
renamer=None, **kwargs):
[columns, metadata] = loadSVcols(fname, **kwargs)
if 'names' in metadata.keys():
names = metadata['names']
else:
names = None
if 'formats' in metadata.keys():
formats =... |
{'id': '0', 'type': 'module', 'children': ['1']},{'id': '1', 'type': 'function_definition', 'children': ['2', '3', '22']},{'id': '2', 'type': 'function_name', 'children': [], 'value': 'loadSVrecs'},{'id': '3', 'type': 'parameters', 'children': ['4', '5', '8', '11', '14', '17', '20']},{'id': '4', 'type': 'identifier', '... | def loadSVrecs(fname, uselines=None, skiprows=0, linefixer=None,
delimiter_regex=None, verbosity=DEFAULT_VERBOSITY, **metadata):
if delimiter_regex and isinstance(delimiter_regex, types.StringType):
import re
delimiter_regex = re.compile(delimiter_regex)
[metadata, inferedlines,... |
{'id': '0', 'type': 'module', 'children': ['1']},{'id': '1', 'type': 'function_definition', 'children': ['2', '3', '9', '13']},{'id': '2', 'type': 'function_name', 'children': [], 'value': 'dflt_interval'},{'id': '3', 'type': 'parameters', 'children': ['4', '5']},{'id': '4', 'type': 'identifier', 'children': [], 'value... | def dflt_interval(self, cd_id: str) -> (int, int):
LOGGER.debug('RevocationCache.dflt_interval >>>')
fro = None
to = None
for rr_id in self:
if cd_id != rev_reg_id2cred_def_id(rr_id):
continue
entry = self[rr_id]
if entry.rr_delta_frame... |
{'id': '0', 'type': 'module', 'children': ['1']},{'id': '1', 'type': 'function_definition', 'children': ['2', '3', '13', '15']},{'id': '2', 'type': 'function_name', 'children': [], 'value': 'parse'},{'id': '3', 'type': 'parameters', 'children': ['4', '8']},{'id': '4', 'type': 'typed_parameter', 'children': ['5', '6']},... | def parse(base_dir: str, timestamp: int = None) -> int:
LOGGER.debug('parse >>> base_dir: %s, timestamp: %s', base_dir, timestamp)
if not isdir(base_dir):
LOGGER.info('No cache archives available: not feeding cache')
LOGGER.debug('parse <<< None')
return None
... |
{'id': '0', 'type': 'module', 'children': ['1']},{'id': '1', 'type': 'function_definition', 'children': ['2', '3', '6']},{'id': '2', 'type': 'function_name', 'children': [], 'value': '_convert_hbf_meta_val_for_xml'},{'id': '3', 'type': 'parameters', 'children': ['4', '5']},{'id': '4', 'type': 'identifier', 'children': ... | def _convert_hbf_meta_val_for_xml(key, val):
if isinstance(val, list):
return [_convert_hbf_meta_val_for_xml(key, i) for i in val]
is_literal = True
content = None
if isinstance(val, dict):
ret = val
if '@href' in val:
is_literal = False
else:
cont... |
{'id': '0', 'type': 'module', 'children': ['1']},{'id': '1', 'type': 'function_definition', 'children': ['2', '3', '6']},{'id': '2', 'type': 'function_name', 'children': [], 'value': 'validate_params_match'},{'id': '3', 'type': 'parameters', 'children': ['4', '5']},{'id': '4', 'type': 'identifier', 'children': [], 'val... | def validate_params_match(method, parameters):
argspec = inspect.getargspec(method)
default_length = len(argspec.defaults) if argspec.defaults is not None else 0
if isinstance(parameters, list):
if len(parameters) > len(argspec.args) and argspec.varargs is None:
raise InvalidParamsError(... |
{'id': '0', 'type': 'module', 'children': ['1']},{'id': '1', 'type': 'function_definition', 'children': ['2', '3', '9']},{'id': '2', 'type': 'function_name', 'children': [], 'value': 'addcols'},{'id': '3', 'type': 'parameters', 'children': ['4', '5', '6']},{'id': '4', 'type': 'identifier', 'children': [], 'value': 'X'}... | def addcols(X, cols, names=None):
if isinstance(names,str):
names = [n.strip() for n in names.split(',')]
if isinstance(cols, list):
if any([isinstance(x,np.ndarray) or isinstance(x,list) or \
isinstance(x,tuple) for x in cols]):
assert all([len(x... |
{'id': '0', 'type': 'module', 'children': ['1']},{'id': '1', 'type': 'function_definition', 'children': ['2', '3', '16']},{'id': '2', 'type': 'function_name', 'children': [], 'value': 'replace'},{'id': '3', 'type': 'parameters', 'children': ['4', '5', '6', '7', '10', '13']},{'id': '4', 'type': 'identifier', 'children':... | def replace(X, old, new, strict=True, cols=None, rows=None):
if cols == None:
cols = X.dtype.names
elif isinstance(cols, str):
cols = cols.split(',')
if rows == None:
rows = np.ones((len(X),), bool)
if strict:
new = np.array(new)
for a in cols:
if X.dt... |
{'id': '0', 'type': 'module', 'children': ['1']},{'id': '1', 'type': 'function_definition', 'children': ['2', '3', '11']},{'id': '2', 'type': 'function_name', 'children': [], 'value': 'rowstack'},{'id': '3', 'type': 'parameters', 'children': ['4', '5', '8']},{'id': '4', 'type': 'identifier', 'children': [], 'value': 's... | def rowstack(seq, mode='nulls', nullvals=None):
'''
Vertically stack a sequence of numpy ndarrays with structured dtype
Analog of numpy.vstack
Implemented by the tabarray method
:func:`tabular.tab.tabarray.rowstack` which uses
:func:`tabular.tabarray.tab_rowstack`.
**Parameters**
... |
{'id': '0', 'type': 'module', 'children': ['1']},{'id': '1', 'type': 'function_definition', 'children': ['2', '3', '11']},{'id': '2', 'type': 'function_name', 'children': [], 'value': 'colstack'},{'id': '3', 'type': 'parameters', 'children': ['4', '5', '8']},{'id': '4', 'type': 'identifier', 'children': [], 'value': 's... | def colstack(seq, mode='abort',returnnaming=False):
assert mode in ['first','drop','abort','rename'], \
'mode argument must take on value "first","drop", "rename", or "abort".'
AllNames = utils.uniqify(utils.listunion(
[list(l.dtype.names) for l in seq]))
Na... |
{'id': '0', 'type': 'module', 'children': ['1']},{'id': '1', 'type': 'function_definition', 'children': ['2', '3', '20']},{'id': '2', 'type': 'function_name', 'children': [], 'value': 'getjp2image'},{'id': '3', 'type': 'parameters', 'children': ['4', '5', '8', '11', '14', '17']},{'id': '4', 'type': 'identifier', 'child... | def getjp2image(date,
sourceId=None,
observatory=None,
instrument=None,
detector=None,
measurement=None):
'''
Helioviewer.org and JHelioviewer operate off of JPEG2000 formatted image data generated from science-quality FITS files. U... |
{'id': '0', 'type': 'module', 'children': ['1']},{'id': '1', 'type': 'function_definition', 'children': ['2', '3', '20', '26']},{'id': '2', 'type': 'function_name', 'children': [], 'value': 'loads_loader'},{'id': '3', 'type': 'parameters', 'children': ['4', '10']},{'id': '4', 'type': 'typed_parameter', 'children': ['5'... | def loads_loader(load_module: types.ModuleType, pairs: Dict[str, str]) -> Optional[JSGValidateable]:
cntxt = load_module._CONTEXT
possible_type = pairs[cntxt.TYPE] if cntxt.TYPE in pairs else None
target_class = getattr(load_module, possible_type, None) if isinstance(possible_type, str) else None
if tar... |
{'id': '0', 'type': 'module', 'children': ['1']},{'id': '1', 'type': 'function_definition', 'children': ['2', '3', '9', '11']},{'id': '2', 'type': 'function_name', 'children': [], 'value': 'get_cred_def'},{'id': '3', 'type': 'parameters', 'children': ['4', '5']},{'id': '4', 'type': 'identifier', 'children': [], 'value'... | async def get_cred_def(self, cd_id: str) -> str:
LOGGER.debug('_BaseAgent.get_cred_def >>> cd_id: %s', cd_id)
rv_json = json.dumps({})
with CRED_DEF_CACHE.lock:
if cd_id in CRED_DEF_CACHE:
LOGGER.info('_BaseAgent.get_cred_def: got cred def for %s from cache', cd_id)
... |
{'id': '0', 'type': 'module', 'children': ['1']},{'id': '1', 'type': 'function_definition', 'children': ['2', '3', '18']},{'id': '2', 'type': 'function_name', 'children': [], 'value': 'convert_nexson_format'},{'id': '3', 'type': 'parameters', 'children': ['4', '5', '6', '9', '12', '15']},{'id': '4', 'type': 'identifier... | def convert_nexson_format(blob,
out_nexson_format,
current_format=None,
remove_old_structs=True,
pristine_if_invalid=False,
sort_arbitrary=False):
if not current_format:
current_... |
{'id': '0', 'type': 'module', 'children': ['1']},{'id': '1', 'type': 'function_definition', 'children': ['2', '3', '5']},{'id': '2', 'type': 'function_name', 'children': [], 'value': '_inplace_sort_by_id'},{'id': '3', 'type': 'parameters', 'children': ['4']},{'id': '4', 'type': 'identifier', 'children': [], 'value': 'u... | def _inplace_sort_by_id(unsorted_list):
if not isinstance(unsorted_list, list):
return
sorted_list = [(i.get('@id'), i) for i in unsorted_list]
sorted_list.sort()
del unsorted_list[:]
unsorted_list.extend([i[1] for i in sorted_list]) |
{'id': '0', 'type': 'module', 'children': ['1']},{'id': '1', 'type': 'function_definition', 'children': ['2', '3', '9']},{'id': '2', 'type': 'function_name', 'children': [], 'value': 'cull_nonmatching_trees'},{'id': '3', 'type': 'parameters', 'children': ['4', '5', '6']},{'id': '4', 'type': 'identifier', 'children': []... | def cull_nonmatching_trees(nexson, tree_id, curr_version=None):
if curr_version is None:
curr_version = detect_nexson_version(nexson)
if not _is_by_id_hbf(curr_version):
nexson = convert_nexson_format(nexson, BY_ID_HONEY_BADGERFISH)
nexml_el = get_nexml_el(nexson)
tree_groups = nexml_el[... |
{'id': '0', 'type': 'module', 'children': ['1']},{'id': '1', 'type': 'function_definition', 'children': ['2', '3', '18', '30']},{'id': '2', 'type': 'function_name', 'children': [], 'value': '_validate'},{'id': '3', 'type': 'parameters', 'children': ['4', '5', '9']},{'id': '4', 'type': 'identifier', 'children': [], 'val... | def _validate(self, val: list, log: Optional[Logger] = None) -> Tuple[bool, List[str]]:
errors = []
if not isinstance(val, list):
errors.append(f"{self._variable_name}: {repr(val)} is not an array")
else:
for i in range(0, len(val)):
v = val[i]
... |
{'id': '0', 'type': 'module', 'children': ['1']},{'id': '1', 'type': 'function_definition', 'children': ['2', '3', '14', '16']},{'id': '2', 'type': 'function_name', 'children': [], 'value': '_sync_revoc'},{'id': '3', 'type': 'parameters', 'children': ['4', '5', '9']},{'id': '4', 'type': 'identifier', 'children': [], 'v... | async def _sync_revoc(self, rr_id: str, rr_size: int = None) -> None:
LOGGER.debug('Issuer._sync_revoc >>> rr_id: %s, rr_size: %s', rr_id, rr_size)
(cd_id, tag) = rev_reg_id2cred_def_id__tag(rr_id)
try:
await self.get_cred_def(cd_id)
except AbsentCredDef:
LOGGER.d... |
{'id': '0', 'type': 'module', 'children': ['1']},{'id': '1', 'type': 'function_definition', 'children': ['2', '3', '12']},{'id': '2', 'type': 'function_name', 'children': [], 'value': 'add_namespace_uri'},{'id': '3', 'type': 'parameters', 'children': ['4', '5', '6', '9']},{'id': '4', 'type': 'identifier', 'children': [... | def add_namespace_uri(self, ns_uri, prefix=None, schema_location=None):
assert ns_uri
if ns_uri in self.__ns_uri_map:
ni = self.__lookup_uri(ns_uri)
new_ni = copy.deepcopy(ni)
if prefix:
self.__check_prefix_conflict(ni, prefix)
new_ni.p... |
{'id': '0', 'type': 'module', 'children': ['1']},{'id': '1', 'type': 'function_definition', 'children': ['2', '3', '14']},{'id': '2', 'type': 'function_name', 'children': [], 'value': 'get_schemaloc_string'},{'id': '3', 'type': 'parameters', 'children': ['4', '5', '8', '11']},{'id': '4', 'type': 'identifier', 'children... | def get_schemaloc_string(self, ns_uris=None, sort=False, delim="\n"):
if not ns_uris:
ns_uris = six.iterkeys(self.__ns_uri_map)
if sort:
ns_uris = sorted(ns_uris)
schemalocs = []
for ns_uri in ns_uris:
ni = self.__lookup_uri(ns_uri)
if ni.s... |
{'id': '0', 'type': 'module', 'children': ['1']},{'id': '1', 'type': 'function_definition', 'children': ['2', '3', '20']},{'id': '2', 'type': 'function_name', 'children': [], 'value': 'tab_join'},{'id': '3', 'type': 'parameters', 'children': ['4', '5', '8', '11', '14', '17']},{'id': '4', 'type': 'identifier', 'children... | def tab_join(ToMerge, keycols=None, nullvals=None, renamer=None,
returnrenaming=False, Names=None):
'''
Database-join for tabular arrays.
Wrapper for :func:`tabular.spreadsheet.join` that deals with the coloring
and returns the result as a tabarray.
Method calls::
data = t... |
{'id': '0', 'type': 'module', 'children': ['1']},{'id': '1', 'type': 'function_definition', 'children': ['2', '3', '26']},{'id': '2', 'type': 'function_name', 'children': [], 'value': 'aggregate'},{'id': '3', 'type': 'parameters', 'children': ['4', '5', '8', '11', '14', '17', '20', '23']},{'id': '4', 'type': 'identifie... | def aggregate(self, On=None, AggFuncDict=None, AggFunc=None, AggList =
None, returnsort=False,KeepOthers=True, keyfuncdict=None):
if returnsort:
[data, s] = spreadsheet.aggregate(X=self,
On=On,
AggFuncDict=AggFuncDict,
... |
{'id': '0', 'type': 'module', 'children': ['1']},{'id': '1', 'type': 'function_definition', 'children': ['2', '3', '15']},{'id': '2', 'type': 'function_name', 'children': [], 'value': 'argsort'},{'id': '3', 'type': 'parameters', 'children': ['4', '5', '9', '12']},{'id': '4', 'type': 'identifier', 'children': [], 'value... | def argsort(self, axis=-1, kind='quicksort', order=None):
index_array = np.core.fromnumeric._wrapit(self, 'argsort', axis,
kind, order)
index_array = index_array.view(np.ndarray)
return index_array |
{'id': '0', 'type': 'module', 'children': ['1']},{'id': '1', 'type': 'function_definition', 'children': ['2', '3', '8']},{'id': '2', 'type': 'function_name', 'children': [], 'value': '_finalize_namespaces'},{'id': '3', 'type': 'parameters', 'children': ['4', '5']},{'id': '4', 'type': 'identifier', 'children': [], 'valu... | def _finalize_namespaces(self, ns_dict=None):
if ns_dict:
for ns, alias in six.iteritems(ns_dict):
self._collected_namespaces.add_namespace_uri(ns, alias)
self._collected_namespaces.add_namespace_uri(
ns_uri=idgen.get_id_namespace(),
prefix=idgen.get_i... |
{'id': '0', 'type': 'module', 'children': ['1']},{'id': '1', 'type': 'function_definition', 'children': ['2', '3', '7']},{'id': '2', 'type': 'function_name', 'children': [], 'value': 'update_empty_fields'},{'id': '3', 'type': 'parameters', 'children': ['4', '5']},{'id': '4', 'type': 'identifier', 'children': [], 'value... | def update_empty_fields(self, **kwargs):
if self._is_deprecated is None:
self._is_deprecated = kwargs.get('is_deprecated')
if self._is_dubious is None:
self._is_dubious = kwargs.get('is_dubious')
if self._is_synonym is None:
self._is_synonym = kwargs.get('is_s... |
{'id': '0', 'type': 'module', 'children': ['1']},{'id': '1', 'type': 'function_definition', 'children': ['2', '3', '19', '25']},{'id': '2', 'type': 'function_name', 'children': [], 'value': 'get_creds'},{'id': '3', 'type': 'parameters', 'children': ['4', '5', '9', '14']},{'id': '4', 'type': 'identifier', 'children': []... | async def get_creds(self, proof_req_json: str, filt: dict = None, filt_dflt_incl: bool = False) -> (Set[str], str):
LOGGER.debug('HolderProver.get_creds >>> proof_req_json: %s, filt: %s', proof_req_json, filt)
if filt is None:
filt = {}
rv = None
creds_json = await anoncreds.... |
{'id': '0', 'type': 'module', 'children': ['1']},{'id': '1', 'type': 'function_definition', 'children': ['2', '3', '7']},{'id': '2', 'type': 'function_name', 'children': [], 'value': 'summary'},{'id': '3', 'type': 'parameters', 'children': ['4', '5', '6']},{'id': '4', 'type': 'identifier', 'children': [], 'value': 'pro... | def summary(processors, metrics, context):
def display_header(processors, before='', after=''):
print(before, end=' ')
for processor in processors:
processor.display_header()
print(after)
def display_separator(processors, before='', after=''):
print(before, end=' ')
... |
{'id': '0', 'type': 'module', 'children': ['1']},{'id': '1', 'type': 'function_definition', 'children': ['2', '3', '13']},{'id': '2', 'type': 'function_name', 'children': [], 'value': 'run_experiment'},{'id': '3', 'type': 'parameters', 'children': ['4', '5', '6', '7', '10']},{'id': '4', 'type': 'identifier', 'children'... | def run_experiment(experiment, roleouts, episodes, in_cloud=False,
dynProfile=None):
def run():
if dynProfile is None:
maxsteps = len(experiment.profile)
else:
maxsteps = dynProfile.shape[1]
na = len(experiment.agents)
ni = roleouts * episod... |
{'id': '0', 'type': 'module', 'children': ['1']},{'id': '1', 'type': 'function_definition', 'children': ['2', '3', '14']},{'id': '2', 'type': 'function_name', 'children': [], 'value': 'total_cost'},{'id': '3', 'type': 'parameters', 'children': ['4', '5', '8', '11']},{'id': '4', 'type': 'identifier', 'children': [], 'va... | def total_cost(self, p=None, p_cost=None, pcost_model=None):
p = self.p if p is None else p
p_cost = self.p_cost if p_cost is None else p_cost
pcost_model = self.pcost_model if pcost_model is None else pcost_model
p = 0.0 if not self.online else p
if pcost_model == PW_LINEAR:
... |
{'id': '0', 'type': 'module', 'children': ['1']},{'id': '1', 'type': 'function_definition', 'children': ['2', '3', '6']},{'id': '2', 'type': 'function_name', 'children': [], 'value': 'offers_to_pwl'},{'id': '3', 'type': 'parameters', 'children': ['4', '5']},{'id': '4', 'type': 'identifier', 'children': [], 'value': 'se... | def offers_to_pwl(self, offers):
assert not self.is_load
g_offers = [offer for offer in offers if offer.generator == self]
gt_zero = [offr for offr in g_offers if round(offr.quantity, 4) > 0.0]
valid = [offer for offer in gt_zero if not offer.withheld]
p_offers = [v for v in vali... |
{'id': '0', 'type': 'module', 'children': ['1']},{'id': '1', 'type': 'function_definition', 'children': ['2', '3', '6']},{'id': '2', 'type': 'function_name', 'children': [], 'value': 'bids_to_pwl'},{'id': '3', 'type': 'parameters', 'children': ['4', '5']},{'id': '4', 'type': 'identifier', 'children': [], 'value': 'self... | def bids_to_pwl(self, bids):
assert self.is_load
vl_bids = [bid for bid in bids if bid.vLoad == self]
gt_zero = [bid for bid in vl_bids if round(bid.quantity, 4) > 0.0]
valid_bids = [bid for bid in gt_zero if not bid.withheld]
p_bids = [v for v in valid_bids if not v.reactive]
... |
{'id': '0', 'type': 'module', 'children': ['1']},{'id': '1', 'type': 'function_definition', 'children': ['2', '3', '5']},{'id': '2', 'type': 'function_name', 'children': [], 'value': 'DoxyfileParse'},{'id': '3', 'type': 'parameters', 'children': ['4']},{'id': '4', 'type': 'identifier', 'children': [], 'value': 'file_co... | def DoxyfileParse(file_contents):
data = {}
import shlex
lex = shlex.shlex(instream = file_contents, posix = True)
lex.wordchars += "*+./-:"
lex.whitespace = lex.whitespace.replace("\n", "")
lex.escape = ""
lineno = lex.lineno
token = lex.get_token()
key = token
last_token = ""
key_toke... |
{'id': '0', 'type': 'module', 'children': ['1']},{'id': '1', 'type': 'function_definition', 'children': ['2', '3', '7']},{'id': '2', 'type': 'function_name', 'children': [], 'value': 'DoxySourceScan'},{'id': '3', 'type': 'parameters', 'children': ['4', '5', '6']},{'id': '4', 'type': 'identifier', 'children': [], 'value... | def DoxySourceScan(node, env, path):
default_file_patterns = [
'*.c', '*.cc', '*.cxx', '*.cpp', '*.c++', '*.java', '*.ii', '*.ixx',
'*.ipp', '*.i++', '*.inl', '*.h', '*.hh ', '*.hxx', '*.hpp', '*.h++',
'*.idl', '*.odl', '*.cs', '*.php', '*.php3', '*.inc', '*.m', '*.mm',
'*.py',
]
defaul... |
{'id': '0', 'type': 'module', 'children': ['1']},{'id': '1', 'type': 'function_definition', 'children': ['2', '3', '9']},{'id': '2', 'type': 'function_name', 'children': [], 'value': '_quadratic_costs'},{'id': '3', 'type': 'parameters', 'children': ['4', '5', '6', '7', '8']},{'id': '4', 'type': 'identifier', 'children'... | def _quadratic_costs(self, generators, ipol, nxyz, base_mva):
npol = len(ipol)
rnpol = range(npol)
gpol = [g for g in generators if g.pcost_model == POLYNOMIAL]
if [g for g in gpol if len(g.p_cost) > 3]:
logger.error("Order of polynomial cost greater than quadratic.")
... |
{'id': '0', 'type': 'module', 'children': ['1']},{'id': '1', 'type': 'function_definition', 'children': ['2', '3', '6']},{'id': '2', 'type': 'function_name', 'children': [], 'value': '_gh'},{'id': '3', 'type': 'parameters', 'children': ['4', '5']},{'id': '4', 'type': 'identifier', 'children': [], 'value': 'self'},{'id'... | def _gh(self, x):
Pgen = x[self._Pg.i1:self._Pg.iN + 1]
Qgen = x[self._Qg.i1:self._Qg.iN + 1]
for i, gen in enumerate(self._gn):
gen.p = Pgen[i] * self._base_mva
gen.q = Qgen[i] * self._base_mva
Sbus = self.om.case.getSbus(self._bs)
Vang = x[self._Va.i1:se... |
{'id': '0', 'type': 'module', 'children': ['1']},{'id': '1', 'type': 'function_definition', 'children': ['2', '3', '6']},{'id': '2', 'type': 'function_name', 'children': [], 'value': 'performAction'},{'id': '3', 'type': 'parameters', 'children': ['4', '5']},{'id': '4', 'type': 'identifier', 'children': [], 'value': 'se... | def performAction(self, action):
gs = [g for g in self.case.online_generators if g.bus.type !=REFERENCE]
assert len(action) == len(gs)
logger.info("Action: %s" % list(action))
for i, g in enumerate(gs):
g.p = action[i]
NewtonPF(self.case, verbose=False).solve()
... |
{'id': '0', 'type': 'module', 'children': ['1']},{'id': '1', 'type': 'function_definition', 'children': ['2', '3', '20', '28']},{'id': '2', 'type': 'function_name', 'children': [], 'value': 'blt'},{'id': '3', 'type': 'parameters', 'children': ['4', '12']},{'id': '4', 'type': 'typed_parameter', 'children': ['5', '6']},{... | def blt(f: List[SYM], x: List[SYM]) -> Dict[str, Any]:
J = ca.jacobian(f, x)
nblock, rowperm, colperm, rowblock, colblock, coarserow, coarsecol = J.sparsity().btf()
return {
'J': J,
'nblock': nblock,
'rowperm': rowperm,
'colperm': colperm,
'rowblock': rowblock,
... |
{'id': '0', 'type': 'module', 'children': ['1']},{'id': '1', 'type': 'function_definition', 'children': ['2', '3', '5']},{'id': '2', 'type': 'function_name', 'children': [], 'value': 'sort_generators'},{'id': '3', 'type': 'parameters', 'children': ['4']},{'id': '4', 'type': 'identifier', 'children': [], 'value': 'self'... | def sort_generators(self):
self.generators.sort(key=lambda gn: gn.bus._i) |
{'id': '0', 'type': 'module', 'children': ['1']},{'id': '1', 'type': 'function_definition', 'children': ['2', '3', '12']},{'id': '2', 'type': 'function_name', 'children': [], 'value': 'create'},{'id': '3', 'type': 'parameters', 'children': ['4', '5', '6', '9']},{'id': '4', 'type': 'identifier', 'children': [], 'value':... | def create(self, dotdata, prog="dot", format="xdot"):
import os, tempfile
from dot2tex.dotparsing import find_graphviz
progs = find_graphviz()
if progs is None:
logger.warning("GraphViz executables not found.")
return None
if not progs.has_key(prog):
... |
{'id': '0', 'type': 'module', 'children': ['1']},{'id': '1', 'type': 'function_definition', 'children': ['2', '3', '6']},{'id': '2', 'type': 'function_name', 'children': [], 'value': 'format'},{'id': '3', 'type': 'parameters', 'children': ['4', '5']},{'id': '4', 'type': 'identifier', 'children': [], 'value': 'file_metr... | def format(file_metrics, build_metrics):
def indent(elem, level=0):
i = "\n" + level*" "
if len(elem):
if not elem.text or not elem.text.strip():
elem.text = i + " "
if not elem.tail or not elem.tail.strip():
elem.tail = i
for ele... |
{'id': '0', 'type': 'module', 'children': ['1']},{'id': '1', 'type': 'function_definition', 'children': ['2', '3', '8']},{'id': '2', 'type': 'function_name', 'children': [], 'value': 'governor'},{'id': '3', 'type': 'parameters', 'children': ['4', '5', '6', '7']},{'id': '4', 'type': 'identifier', 'children': [], 'value'... | def governor(self, Xgov, Pgov, Vgov):
governors = self.governors
omegas = 2 * pi * self.freq
F = zeros(Xgov.shape)
typ1 = [g.generator._i for g in governors if g.model == CONST_POWER]
typ2 = [g.generator._i for g in governors if g.model == GENERAL_IEEE]
F[typ1, 0] = 0
... |
{'id': '0', 'type': 'module', 'children': ['1']},{'id': '1', 'type': 'function_definition', 'children': ['2', '3', '9']},{'id': '2', 'type': 'function_name', 'children': [], 'value': 'generator'},{'id': '3', 'type': 'parameters', 'children': ['4', '5', '6', '7', '8']},{'id': '4', 'type': 'identifier', 'children': [], '... | def generator(self, Xgen, Xexc, Xgov, Vgen):
generators = self.dyn_generators
omegas = 2 * pi * self.freq
F = zeros(Xgen.shape)
typ1 = [g._i for g in generators if g.model == CLASSICAL]
typ2 = [g._i for g in generators if g.model == FOURTH_ORDER]
omega = Xgen[typ1, 1]
... |
{'id': '0', 'type': 'module', 'children': ['1']},{'id': '1', 'type': 'function_definition', 'children': ['2', '3', '7']},{'id': '2', 'type': 'function_name', 'children': [], 'value': '_const_pf_constraints'},{'id': '3', 'type': 'parameters', 'children': ['4', '5', '6']},{'id': '4', 'type': 'identifier', 'children': [],... | def _const_pf_constraints(self, gn, base_mva):
ivl = array([i for i, g in enumerate(gn)
if g.is_load and (g.q_min != 0.0 or g.q_max != 0.0)])
vl = [gn[i] for i in ivl]
nvl = len(vl)
ng = len(gn)
Pg = array([g.p for g in vl]) / base_mva
Qg = array([g.q... |
{'id': '0', 'type': 'module', 'children': ['1']},{'id': '1', 'type': 'function_definition', 'children': ['2', '3', '7']},{'id': '2', 'type': 'function_name', 'children': [], 'value': '_voltage_angle_diff_limit'},{'id': '3', 'type': 'parameters', 'children': ['4', '5', '6']},{'id': '4', 'type': 'identifier', 'children':... | def _voltage_angle_diff_limit(self, buses, branches):
nb = len(buses)
if not self.ignore_ang_lim:
iang = [i for i, b in enumerate(branches)
if (b.ang_min and (b.ang_min > -360.0))
or (b.ang_max and (b.ang_max < 360.0))]
iangl = array([i for... |
{'id': '0', 'type': 'module', 'children': ['1']},{'id': '1', 'type': 'function_definition', 'children': ['2', '3', '5']},{'id': '2', 'type': 'function_name', 'children': [], 'value': '_clipPrices'},{'id': '3', 'type': 'parameters', 'children': ['4']},{'id': '4', 'type': 'identifier', 'children': [], 'value': 'self'},{'... | def _clipPrices(self):
if self.guaranteeOfferPrice:
for offer in self.offers:
if offer.accepted and offer.clearedPrice < offer.price:
offer.clearedPrice = offer.price
if self.guaranteeBidPrice:
for bid in self.bids:
if bid.accep... |
{'id': '0', 'type': 'module', 'children': ['1']},{'id': '1', 'type': 'function_definition', 'children': ['2', '3', '9']},{'id': '2', 'type': 'function_name', 'children': [], 'value': 'gpu_iuwt_decomposition'},{'id': '3', 'type': 'parameters', 'children': ['4', '5', '6', '7', '8']},{'id': '4', 'type': 'identifier', 'chi... | def gpu_iuwt_decomposition(in1, scale_count, scale_adjust, store_smoothed, store_on_gpu):
ker = SourceModule(
)
wavelet_filter = (1./16)*np.array([1,4,6,4,1], dtype=np.float32)
wavelet_filter = gpuarray.to_gpu_async(wavelet_filter)
detail_coeffs = gpuarray.empty([scale_count-scale_adjust, in1.shape[0], ... |
{'id': '0', 'type': 'module', 'children': ['1']},{'id': '1', 'type': 'function_definition', 'children': ['2', '3', '8']},{'id': '2', 'type': 'function_name', 'children': [], 'value': 'gpu_iuwt_recomposition'},{'id': '3', 'type': 'parameters', 'children': ['4', '5', '6', '7']},{'id': '4', 'type': 'identifier', 'children... | def gpu_iuwt_recomposition(in1, scale_adjust, store_on_gpu, smoothed_array):
wavelet_filter = (1./16)*np.array([1,4,6,4,1], dtype=np.float32)
wavelet_filter = gpuarray.to_gpu_async(wavelet_filter)
max_scale = in1.shape[0] + scale_adjust
if smoothed_array is None:
recomposition = gpuarray.zeros([... |
{'id': '0', 'type': 'module', 'children': ['1']},{'id': '1', 'type': 'function_definition', 'children': ['2', '3', '5']},{'id': '2', 'type': 'function_name', 'children': [], 'value': 'from_config'},{'id': '3', 'type': 'parameters', 'children': ['4']},{'id': '4', 'type': 'identifier', 'children': [], 'value': 'config'},... | def from_config(config):
matrix = {}
variables = config.keys()
for entries in product(*config.values()):
combination = dict(zip(variables, entries))
include = True
for value in combination.values():
for reducer in value.reducers:
if reducer.pattern == '-':... |
{'id': '0', 'type': 'module', 'children': ['1']},{'id': '1', 'type': 'function_definition', 'children': ['2', '3', '71']},{'id': '2', 'type': 'function_name', 'children': [], 'value': 'moresane_by_scale'},{'id': '3', 'type': 'parameters', 'children': ['4', '5', '8', '11', '14', '17', '20', '23', '26', '29', '32', '35',... | def moresane_by_scale(self, start_scale=1, stop_scale=20, subregion=None, sigma_level=4, loop_gain=0.1,
tolerance=0.75, accuracy=1e-6, major_loop_miter=100, minor_loop_miter=30, all_on_gpu=False,
decom_mode="ser", core_count=1, conv_device='cpu', conv_mode='linear', e... |
{'id': '0', 'type': 'module', 'children': ['1']},{'id': '1', 'type': 'function_definition', 'children': ['2', '3', '16']},{'id': '2', 'type': 'function_name', 'children': [], 'value': 'load_or_create'},{'id': '3', 'type': 'parameters', 'children': ['4', '5', '8', '11', '14']},{'id': '4', 'type': 'identifier', 'children... | def load_or_create(cls, filename=None, no_input=False, create_new=False, **kwargs):
parser = argparse.ArgumentParser()
parser.add_argument('--no_input', action='store_true')
parser.add_argument('--create_new', action='store_true')
args = parser.parse_args()
if args.no_input:
... |
{'id': '0', 'type': 'module', 'children': ['1']},{'id': '1', 'type': 'function_definition', 'children': ['2', '3', '5']},{'id': '2', 'type': 'function_name', 'children': [], 'value': 'cleanup'},{'id': '3', 'type': 'parameters', 'children': ['4']},{'id': '4', 'type': 'identifier', 'children': [], 'value': 'self'},{'id':... | def cleanup(self):
self.pre_exit_trigger = True
self.logger.info("Shutting down %s, please wait a moment.", self.name)
for t in threading.enumerate():
if isinstance(t, TimerClass):
t.cancel()
self.logger.debug('Timers cancelled')
for i in self.objects:... |
{'id': '0', 'type': 'module', 'children': ['1']},{'id': '1', 'type': 'function_definition', 'children': ['2', '3', '8']},{'id': '2', 'type': 'function_name', 'children': [], 'value': 'write_puml'},{'id': '3', 'type': 'parameters', 'children': ['4', '5']},{'id': '4', 'type': 'identifier', 'children': [], 'value': 'self'... | def write_puml(self, filename=''):
def get_type(o):
type = 'program'
if isinstance(o, AbstractSensor):
type = 'sensor'
elif isinstance(o, AbstractActuator):
type = 'actuator'
return type
if filename:
s = open(fil... |
{'id': '0', 'type': 'module', 'children': ['1']},{'id': '1', 'type': 'function_definition', 'children': ['2', '3', '9']},{'id': '2', 'type': 'function_name', 'children': [], 'value': 'fit'},{'id': '3', 'type': 'parameters', 'children': ['4', '5', '6']},{'id': '4', 'type': 'identifier', 'children': [], 'value': 'self'},... | def fit(self, X, y=None):
N = X.shape[0]
if y is None:
y = np.zeros(N)
self.classes = list(set(y))
self.classes.sort()
self.n_classes = len(self.classes)
if not self.sigma:
self.sigma = median_kneighbour_distance(X)
self.gamma = self.si... |
{'id': '0', 'type': 'module', 'children': ['1']},{'id': '1', 'type': 'function_definition', 'children': ['2', '3', '11']},{'id': '2', 'type': 'function_name', 'children': [], 'value': 'predict_sequence'},{'id': '3', 'type': 'parameters', 'children': ['4', '5', '6', '7', '8']},{'id': '4', 'type': 'identifier', 'children... | def predict_sequence(self, X, A, pi, inference='smoothing'):
obsll = self.predict_proba(X)
T, S = obsll.shape
alpha = np.zeros((T, S))
alpha[0, :] = pi
for t in range(1, T):
alpha[t, :] = np.dot(alpha[t-1, :], A)
for s in range(S):
alpha[t,... |
{'id': '0', 'type': 'module', 'children': ['1']},{'id': '1', 'type': 'function_definition', 'children': ['2', '3', '15']},{'id': '2', 'type': 'function_name', 'children': [], 'value': 'add_bgcolor'},{'id': '3', 'type': 'parameters', 'children': ['4', '5', '6', '9', '12']},{'id': '4', 'type': 'identifier', 'children': [... | def add_bgcolor(self, colname, cmap='copper', mode='absmax',
threshold=2):
try:
cmap = cmap_builder(cmap)
except:
pass
data = self.df[colname].values
if len(data) == 0:
return
if mode == 'clip':
data = [min(x, threshold)... |
{'id': '0', 'type': 'module', 'children': ['1']},{'id': '1', 'type': 'function_definition', 'children': ['2', '3', '20']},{'id': '2', 'type': 'function_name', 'children': [], 'value': 'list'},{'id': '3', 'type': 'parameters', 'children': ['4', '5', '8', '11', '14', '17']},{'id': '4', 'type': 'identifier', 'children': [... | def list(self, filter=None, type=None, sort=None, limit=None, page=None):
schema = self.LIST_SCHEMA
resp = self.service.list(self.base, filter, type, sort, limit, page)
cs, l = self.service.decode(schema, resp, many=True, links=True)
return Page(cs, l) |
{'id': '0', 'type': 'module', 'children': ['1']},{'id': '1', 'type': 'function_definition', 'children': ['2', '3', '9']},{'id': '2', 'type': 'function_name', 'children': [], 'value': 'signup_handler'},{'id': '3', 'type': 'parameters', 'children': ['4', '5', '7']},{'id': '4', 'type': 'identifier', 'children': [], 'value... | def signup_handler(remote, *args, **kwargs):
if current_user.is_authenticated:
return redirect('/')
oauth_token = token_getter(remote)
if not oauth_token:
return redirect('/')
session_prefix = token_session_key(remote.name)
if not session.get(session_prefix + '_autoregister', False):... |
{'id': '0', 'type': 'module', 'children': ['1']},{'id': '1', 'type': 'function_definition', 'children': ['2', '3', '20']},{'id': '2', 'type': 'function_name', 'children': [], 'value': 'list_csv'},{'id': '3', 'type': 'parameters', 'children': ['4', '5', '8', '11', '14', '17']},{'id': '4', 'type': 'identifier', 'children... | def list_csv(self, filter=None, type=None, sort=None, limit=None, page=None):
return self.service.list(self.base, filter, type, sort, limit, page, format='csv').text |
{'id': '0', 'type': 'module', 'children': ['1']},{'id': '1', 'type': 'function_definition', 'children': ['2', '3', '12']},{'id': '2', 'type': 'function_name', 'children': [], 'value': 'list_logdir'},{'id': '3', 'type': 'parameters', 'children': ['4', '5', '6', '9']},{'id': '4', 'type': 'identifier', 'children': [], 'va... | def list_logdir(self, id, filter=None, sort=None):
schema = LogDirFileSchema()
resp = self.service.list(self.base+str(id)+'/logdir/', filter, sort)
return self.service.decode(schema, resp, many=True) |
{'id': '0', 'type': 'module', 'children': ['1']},{'id': '1', 'type': 'function_definition', 'children': ['2', '3', '5']},{'id': '2', 'type': 'function_name', 'children': [], 'value': '_init_report'},{'id': '3', 'type': 'parameters', 'children': ['4']},{'id': '4', 'type': 'identifier', 'children': [], 'value': 'self'},{... | def _init_report(self):
self.sections = []
self.section_names = []
try:
if os.path.isdir(self.directory) is False:
if self.verbose:
print("Created directory {}".format(self.directory))
os.mkdir(self.directory)
for this i... |
{'id': '0', 'type': 'module', 'children': ['1']},{'id': '1', 'type': 'function_definition', 'children': ['2', '3', '5']},{'id': '2', 'type': 'function_name', 'children': [], 'value': 'check_instance'},{'id': '3', 'type': 'parameters', 'children': ['4']},{'id': '4', 'type': 'identifier', 'children': [], 'value': 'functi... | def check_instance(function):
def wrapper(self, *args, **kwargs):
func_trans = {
"commit": manager.Manager,
"compare_config": manager.Manager,
"commit_check": manager.Manager,
"device_info": manager.Manager,
"diff_config... |
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