sequence stringlengths 1.19k 35k | code stringlengths 75 8.58k |
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{'id': '0', 'type': 'module', 'children': ['1']}, {'id': '1', 'type': 'function_definition', 'children': ['2', '3', '5']}; {'id': '2', 'type': 'function_name', 'children': [], 'value': 'values'}, {'id': '3', 'type': 'parameters', 'children': ['4']}; {'id': '4', 'type': 'identifier', 'children': [], 'value': 'self'}, {'... | def values(self):
def key(th):
return len(th.__class__.__mro__)
return sorted(dict.values(self), key=key, reverse=True) |
{'id': '0', 'type': 'module', 'children': ['1']}, {'id': '1', 'type': 'function_definition', 'children': ['2', '3', '5']}; {'id': '2', 'type': 'function_name', 'children': [], 'value': 'topological_sort'}, {'id': '3', 'type': 'parameters', 'children': ['4']}; {'id': '4', 'type': 'identifier', 'children': [], 'value': '... | def topological_sort(self):
graph = self.graph
in_degree = {}
for u in graph:
in_degree[u] = 0
for u in graph:
for v in graph[u]:
in_degree[v] += 1
queue = deque()
for u in in_degree:
if in_degree[u] == 0:
... |
{'id': '0', 'type': 'module', 'children': ['1']}, {'id': '1', 'type': 'function_definition', 'children': ['2', '3', '8']}; {'id': '2', 'type': 'function_name', 'children': [], 'value': '_music_lib_search'}, {'id': '3', 'type': 'parameters', 'children': ['4', '5', '6', '7']}; {'id': '4', 'type': 'identifier', 'children'... | def _music_lib_search(self, search, start, max_items):
response = self.contentDirectory.Browse([
('ObjectID', search),
('BrowseFlag', 'BrowseDirectChildren'),
('Filter', '*'),
('StartingIndex', start),
('RequestedCount', max_items),
('SortC... |
{'id': '0', 'type': 'module', 'children': ['1']}, {'id': '1', 'type': 'function_definition', 'children': ['2', '3', '5']}; {'id': '2', 'type': 'function_name', 'children': [], 'value': 'unique'}, {'id': '3', 'type': 'parameters', 'children': ['4']}; {'id': '4', 'type': 'identifier', 'children': [], 'value': 'seq'}, {'i... | def unique(seq):
cleaned = []
for each in seq:
if each not in cleaned:
cleaned.append(each)
return cleaned |
{'id': '0', 'type': 'module', 'children': ['1']}, {'id': '1', 'type': 'function_definition', 'children': ['2', '3', '5']}; {'id': '2', 'type': 'function_name', 'children': [], 'value': 'build_schema_info'}, {'id': '3', 'type': 'parameters', 'children': ['4']}; {'id': '4', 'type': 'identifier', 'children': [], 'value': ... | def build_schema_info(connection_alias):
connection = get_valid_connection(connection_alias)
ret = []
with connection.cursor() as cursor:
tables_to_introspect = connection.introspection.table_names(cursor, include_views=_include_views())
for table_name in tables_to_introspect:
if... |
{'id': '0', 'type': 'module', 'children': ['1']}, {'id': '1', 'type': 'function_definition', 'children': ['2', '3', '15']}; {'id': '2', 'type': 'function_name', 'children': [], 'value': 'fetchThreads'}, {'id': '3', 'type': 'parameters', 'children': ['4', '5', '6', '9', '12']}; {'id': '4', 'type': 'identifier', 'childre... | def fetchThreads(self, thread_location, before=None, after=None, limit=None):
threads = []
last_thread_timestamp = None
while True:
if limit and len(threads) >= limit:
break
candidates = self.fetchThreadList(
before=last_thread_timestamp, t... |
{'id': '0', 'type': 'module', 'children': ['1']}, {'id': '1', 'type': 'function_definition', 'children': ['2', '3', '9']}; {'id': '2', 'type': 'function_name', 'children': [], 'value': '_get_key_value'}, {'id': '3', 'type': 'parameters', 'children': ['4', '5', '6']}; {'id': '4', 'type': 'identifier', 'children': [], 'v... | def _get_key_value(self, key, is_hll=False):
'''
Returns the proper key value for the stats
@param key: the redis key
@param is_hll: the key is a HyperLogLog, else is a sorted set
'''
if is_hll:
return self.redis_conn.execute_command("PFCOUNT", key)
el... |
{'id': '0', 'type': 'module', 'children': ['1']}, {'id': '1', 'type': 'function_definition', 'children': ['2', '3', '6']}; {'id': '2', 'type': 'function_name', 'children': [], 'value': '_get_bin'}, {'id': '3', 'type': 'parameters', 'children': ['4', '5']}; {'id': '4', 'type': 'identifier', 'children': [], 'value': 'sel... | def _get_bin(self, key):
'''
Returns a binned dictionary based on redis zscore
@return: The sorted dict
'''
sortedDict = {}
for item in self.redis_conn.zscan_iter(key):
my_item = ujson.loads(item[0])
my_score = -item[1]
if my_score not ... |
{'id': '0', 'type': 'module', 'children': ['1']}, {'id': '1', 'type': 'function_definition', 'children': ['2', '3', '5']}; {'id': '2', 'type': 'function_name', 'children': [], 'value': '_is_viable_phone_number'}, {'id': '3', 'type': 'parameters', 'children': ['4']}; {'id': '4', 'type': 'identifier', 'children': [], 'va... | def _is_viable_phone_number(number):
if len(number) < _MIN_LENGTH_FOR_NSN:
return False
match = fullmatch(_VALID_PHONE_NUMBER_PATTERN, number)
return bool(match) |
{'id': '0', 'type': 'module', 'children': ['1']}, {'id': '1', 'type': 'function_definition', 'children': ['2', '3', '6']}; {'id': '2', 'type': 'function_name', 'children': [], 'value': '__encoded_params_for_signature'}, {'id': '3', 'type': 'parameters', 'children': ['4', '5']}; {'id': '4', 'type': 'identifier', 'childr... | def __encoded_params_for_signature(cls, params):
def encoded_pairs(params):
for k, v in six.iteritems(params):
if k == 'hmac':
continue
if k.endswith('[]'):
k = k.rstrip('[]')
v = json.dumps(list(map(str, v))... |
{'id': '0', 'type': 'module', 'children': ['1']}, {'id': '1', 'type': 'function_definition', 'children': ['2', '3', '5']}; {'id': '2', 'type': 'function_name', 'children': [], 'value': 'group_keys'}, {'id': '3', 'type': 'parameters', 'children': ['4']}; {'id': '4', 'type': 'identifier', 'children': [], 'value': 'self'}... | def group_keys(self):
for key in sorted(listdir(self._store, self._path)):
path = self._key_prefix + key
if contains_group(self._store, path):
yield key |
{'id': '0', 'type': 'module', 'children': ['1']}, {'id': '1', 'type': 'function_definition', 'children': ['2', '3', '5']}; {'id': '2', 'type': 'function_name', 'children': [], 'value': 'array_keys'}, {'id': '3', 'type': 'parameters', 'children': ['4']}; {'id': '4', 'type': 'identifier', 'children': [], 'value': 'self'}... | def array_keys(self):
for key in sorted(listdir(self._store, self._path)):
path = self._key_prefix + key
if contains_array(self._store, path):
yield key |
{'id': '0', 'type': 'module', 'children': ['1']}, {'id': '1', 'type': 'function_definition', 'children': ['2', '3', '36']}; {'id': '2', 'type': 'function_name', 'children': [], 'value': 'init_array'}, {'id': '3', 'type': 'parameters', 'children': ['4', '5', '6', '9', '12', '15', '18', '21', '24', '27', '30', '33']}; {'... | def init_array(store, shape, chunks=True, dtype=None, compressor='default',
fill_value=None, order='C', overwrite=False, path=None,
chunk_store=None, filters=None, object_codec=None):
path = normalize_storage_path(path)
_require_parent_group(path, store=store, chunk_store=chunk_sto... |
{'id': '0', 'type': 'module', 'children': ['1']}, {'id': '1', 'type': 'function_definition', 'children': ['2', '3', '26']}; {'id': '2', 'type': 'function_name', 'children': [], 'value': 'view'}, {'id': '3', 'type': 'parameters', 'children': ['4', '5', '8', '11', '14', '17', '20', '23']}; {'id': '4', 'type': 'identifier... | def view(self, shape=None, chunks=None, dtype=None,
fill_value=None, filters=None, read_only=None,
synchronizer=None):
store = self._store
chunk_store = self._chunk_store
path = self._path
if read_only is None:
read_only = self._read_only
if ... |
{'id': '0', 'type': 'module', 'children': ['1']}, {'id': '1', 'type': 'function_definition', 'children': ['2', '3', '8']}; {'id': '2', 'type': 'function_name', 'children': [], 'value': 'image_field_data'}, {'id': '3', 'type': 'parameters', 'children': ['4', '5']}; {'id': '4', 'type': 'identifier', 'children': [], 'valu... | def image_field_data(request, include_empty_option=False):
try:
images = get_available_images(request, request.user.project_id)
except Exception:
exceptions.handle(request, _('Unable to retrieve images'))
images.sort(key=lambda c: c.name)
images_list = [('', _('Select Image'))]
for i... |
{'id': '0', 'type': 'module', 'children': ['1']}, {'id': '1', 'type': 'function_definition', 'children': ['2', '3', '9']}; {'id': '2', 'type': 'function_name', 'children': [], 'value': 'sort_flavor_list'}, {'id': '3', 'type': 'parameters', 'children': ['4', '5', '6']}; {'id': '4', 'type': 'identifier', 'children': [], ... | def sort_flavor_list(request, flavors, with_menu_label=True):
def get_key(flavor, sort_key):
try:
return getattr(flavor, sort_key)
except AttributeError:
LOG.warning('Could not find sort key "%s". Using the default '
'"ram" instead.', sort_key)
... |
{'id': '0', 'type': 'module', 'children': ['1']}, {'id': '1', 'type': 'function_definition', 'children': ['2', '3', '25']}; {'id': '2', 'type': 'function_name', 'children': [], 'value': 'image_list_detailed'}, {'id': '3', 'type': 'parameters', 'children': ['4', '5', '8', '11', '14', '17', '20', '23']}; {'id': '4', 'typ... | def image_list_detailed(request, marker=None, sort_dir='desc',
sort_key='created_at', filters=None, paginate=False,
reversed_order=False, **kwargs):
limit = getattr(settings, 'API_RESULT_LIMIT', 1000)
page_size = utils.get_page_size(request)
if paginate:
... |
{'id': '0', 'type': 'module', 'children': ['1']}, {'id': '1', 'type': 'function_definition', 'children': ['2', '3', '20']}; {'id': '2', 'type': 'function_name', 'children': [], 'value': 'metadefs_namespace_list'}, {'id': '3', 'type': 'parameters', 'children': ['4', '5', '8', '11', '14', '17']}; {'id': '4', 'type': 'ide... | def metadefs_namespace_list(request,
filters=None,
sort_dir='asc',
sort_key='namespace',
marker=None,
paginate=False):
if get_version() < 2:
return [], False, False
... |
{'id': '0', 'type': 'module', 'children': ['1']}, {'id': '1', 'type': 'function_definition', 'children': ['2', '3', '5']}; {'id': '2', 'type': 'function_name', 'children': [], 'value': 'sort_js_files'}, {'id': '3', 'type': 'parameters', 'children': ['4']}; {'id': '4', 'type': 'identifier', 'children': [], 'value': 'js_... | def sort_js_files(js_files):
modules = [f for f in js_files if f.endswith(MODULE_EXT)]
mocks = [f for f in js_files if f.endswith(MOCK_EXT)]
specs = [f for f in js_files if f.endswith(SPEC_EXT)]
other_sources = [f for f in js_files
if (not f.endswith(MODULE_EXT) and
... |
{'id': '0', 'type': 'module', 'children': ['1']}, {'id': '1', 'type': 'function_definition', 'children': ['2', '3', '10']}; {'id': '2', 'type': 'function_name', 'children': [], 'value': '_slice_mostly_sorted'}, {'id': '3', 'type': 'parameters', 'children': ['4', '5', '6', '7']}; {'id': '4', 'type': 'identifier', 'child... | def _slice_mostly_sorted(array, keep, rest, ind=None):
if ind is None:
ind = np.arange(len(array))
idx = np.argsort(np.concatenate([keep, ind[rest]]))
slices = []
if keep[0] > 0:
slices.append(slice(None, keep[0]))
slices.append([keep[0]])
windows = zip(keep[:-1], keep[1:])
f... |
{'id': '0', 'type': 'module', 'children': ['1']}, {'id': '1', 'type': 'function_definition', 'children': ['2', '3', '12', '24']}; {'id': '2', 'type': 'function_name', 'children': [], 'value': 'sort_servers_closest'}, {'id': '3', 'type': 'parameters', 'children': ['4']}; {'id': '4', 'type': 'typed_parameter', 'children'... | def sort_servers_closest(servers: Sequence[str]) -> Sequence[Tuple[str, float]]:
if not {urlparse(url).scheme for url in servers}.issubset({'http', 'https'}):
raise TransportError('Invalid server urls')
get_rtt_jobs = set(
gevent.spawn(lambda url: (url, get_http_rtt(url)), server_url)
fo... |
{'id': '0', 'type': 'module', 'children': ['1']}, {'id': '1', 'type': 'function_definition', 'children': ['2', '3', '6']}; {'id': '2', 'type': 'function_name', 'children': [], 'value': 'get_runs_by_id'}, {'id': '3', 'type': 'parameters', 'children': ['4', '5']}; {'id': '4', 'type': 'identifier', 'children': [], 'value'... | def get_runs_by_id(self, config_id):
d = self.data[config_id]
runs = []
for b in d.results.keys():
try:
err_logs = d.exceptions.get(b, None)
if d.results[b] is None:
r = Run(config_id, b, None, None , d.time_stamps[b], err_logs)
else:
r = Run(config_id, b, d.results[b]['loss'], d.results[... |
{'id': '0', 'type': 'module', 'children': ['1']}, {'id': '1', 'type': 'function_definition', 'children': ['2', '3', '9', '15']}; {'id': '2', 'type': 'function_name', 'children': [], 'value': 'spell'}, {'id': '3', 'type': 'parameters', 'children': ['4', '5']}; {'id': '4', 'type': 'identifier', 'children': [], 'value': '... | def spell(self, word: str) -> List[str]:
if not word:
return ""
candidates = (
self.known([word])
or self.known(_edits1(word))
or self.known(_edits2(word))
or [word]
)
candidates.sort(key=self.freq, reverse=True)
return ... |
{'id': '0', 'type': 'module', 'children': ['1']}, {'id': '1', 'type': 'function_definition', 'children': ['2', '3', '17', '19']}; {'id': '2', 'type': 'function_name', 'children': [], 'value': 'rank'}, {'id': '3', 'type': 'parameters', 'children': ['4', '12']}; {'id': '4', 'type': 'typed_parameter', 'children': ['5', '6... | def rank(words: List[str], exclude_stopwords: bool = False) -> Counter:
if not words:
return None
if exclude_stopwords:
words = [word for word in words if word not in _STOPWORDS]
return Counter(words) |
{'id': '0', 'type': 'module', 'children': ['1']}, {'id': '1', 'type': 'function_definition', 'children': ['2', '3', '16']}; {'id': '2', 'type': 'function_name', 'children': [], 'value': 'iter'}, {'id': '3', 'type': 'parameters', 'children': ['4', '5', '8', '11', '14']}; {'id': '4', 'type': 'identifier', 'children': [],... | def iter(self, offset=0, count=None, pagesize=None, **kwargs):
assert pagesize is None or pagesize > 0
if count is None:
count = self.null_count
fetched = 0
while count == self.null_count or fetched < count:
response = self.get(count=pagesize or count, offset=offs... |
{'id': '0', 'type': 'module', 'children': ['1']}, {'id': '1', 'type': 'function_definition', 'children': ['2', '3', '10']}; {'id': '2', 'type': 'function_name', 'children': [], 'value': 'list'}, {'id': '3', 'type': 'parameters', 'children': ['4', '5', '8']}; {'id': '4', 'type': 'identifier', 'children': [], 'value': 's... | def list(self, count=None, **kwargs):
return list(self.iter(count=count, **kwargs)) |
{'id': '0', 'type': 'module', 'children': ['1']}, {'id': '1', 'type': 'function_definition', 'children': ['2', '3', '7']}; {'id': '2', 'type': 'function_name', 'children': [], 'value': 'query'}, {'id': '3', 'type': 'parameters', 'children': ['4', '5']}; {'id': '4', 'type': 'identifier', 'children': [], 'value': 'self'}... | def query(self, **query):
return json.loads(self._get('', **query).body.read().decode('utf-8')) |
{'id': '0', 'type': 'module', 'children': ['1']}, {'id': '1', 'type': 'function_definition', 'children': ['2', '3', '28']}; {'id': '2', 'type': 'function_name', 'children': [], 'value': 'query'}, {'id': '3', 'type': 'parameters', 'children': ['4', '5', '8', '11', '14', '17', '20', '23', '26']}; {'id': '4', 'type': 'ide... | def query(self, area=None, date=None, raw=None, area_relation='Intersects',
order_by=None, limit=None, offset=0, **keywords):
query = self.format_query(area, date, raw, area_relation, **keywords)
self.logger.debug("Running query: order_by=%s, limit=%s, offset=%s, query=%s",
... |
{'id': '0', 'type': 'module', 'children': ['1']}, {'id': '1', 'type': 'function_definition', 'children': ['2', '3', '7']}; {'id': '2', 'type': 'function_name', 'children': [], 'value': 'get_suggested_type_names'}, {'id': '3', 'type': 'parameters', 'children': ['4', '5', '6']}; {'id': '4', 'type': 'identifier', 'childre... | def get_suggested_type_names(schema, output_type, field_name):
if isinstance(output_type, (GraphQLInterfaceType, GraphQLUnionType)):
suggested_object_types = []
interface_usage_count = OrderedDict()
for possible_type in schema.get_possible_types(output_type):
if not possible_type... |
{'id': '0', 'type': 'module', 'children': ['1']}, {'id': '1', 'type': 'function_definition', 'children': ['2', '3', '6']}; {'id': '2', 'type': 'function_name', 'children': [], 'value': 'suggestion_list'}, {'id': '3', 'type': 'parameters', 'children': ['4', '5']}; {'id': '4', 'type': 'identifier', 'children': [], 'value... | def suggestion_list(inp, options):
options_by_distance = OrderedDict()
input_threshold = len(inp) / 2
for option in options:
distance = lexical_distance(inp, option)
threshold = max(input_threshold, len(option) / 2, 1)
if distance <= threshold:
options_by_distance[option]... |
{'id': '0', 'type': 'module', 'children': ['1']}, {'id': '1', 'type': 'function_definition', 'children': ['2', '3', '6']}; {'id': '2', 'type': 'function_name', 'children': [], 'value': 'lexical_distance'}, {'id': '3', 'type': 'parameters', 'children': ['4', '5']}; {'id': '4', 'type': 'identifier', 'children': [], 'valu... | def lexical_distance(a, b):
d = [[i] for i in range(len(a) + 1)] or []
d_len = len(d) or 1
for i in range(d_len):
for j in range(1, len(b) + 1):
if i == 0:
d[i].append(j)
else:
d[i].append(0)
for i in range(1, len(a) + 1):
for j in ... |
{'id': '0', 'type': 'module', 'children': ['1']}, {'id': '1', 'type': 'function_definition', 'children': ['2', '3', '9']}; {'id': '2', 'type': 'function_name', 'children': [], 'value': 'arrange'}, {'id': '3', 'type': 'parameters', 'children': ['4', '5', '7']}; {'id': '4', 'type': 'identifier', 'children': [], 'value': ... | def arrange(df, *args, **kwargs):
flat_args = [a for a in flatten(args)]
series = [df[arg] if isinstance(arg, str) else
df.iloc[:, arg] if isinstance(arg, int) else
pd.Series(arg) for arg in flat_args]
sorter = pd.concat(series, axis=1).reset_index(drop=True)
sorter = sorter.... |
{'id': '0', 'type': 'module', 'children': ['1']}, {'id': '1', 'type': 'function_definition', 'children': ['2', '3', '6']}; {'id': '2', 'type': 'function_name', 'children': [], 'value': 'csort'}, {'id': '3', 'type': 'parameters', 'children': ['4', '5']}; {'id': '4', 'type': 'identifier', 'children': [], 'value': 'objs'}... | def csort(objs, key):
idxs = dict((obj, i) for (i, obj) in enumerate(objs))
return sorted(objs, key=lambda obj: (key(obj), idxs[obj])) |
{'id': '0', 'type': 'module', 'children': ['1']}, {'id': '1', 'type': 'function_definition', 'children': ['2', '3', '8']}; {'id': '2', 'type': 'function_name', 'children': [], 'value': 'fast_combine_pairs'}, {'id': '3', 'type': 'parameters', 'children': ['4', '5', '6', '7']}; {'id': '4', 'type': 'identifier', 'children... | def fast_combine_pairs(files, force_single, full_name, separators):
files = sort_filenames(files)
chunks = tz.sliding_window(10, files)
pairs = [combine_pairs(chunk, force_single, full_name, separators) for chunk in chunks]
pairs = [y for x in pairs for y in x]
longest = defaultdict(list)
for pa... |
{'id': '0', 'type': 'module', 'children': ['1']}, {'id': '1', 'type': 'function_definition', 'children': ['2', '3', '9']}; {'id': '2', 'type': 'function_name', 'children': [], 'value': 'align_bam'}, {'id': '3', 'type': 'parameters', 'children': ['4', '5', '6', '7', '8']}; {'id': '4', 'type': 'identifier', 'children': [... | def align_bam(in_bam, ref_file, names, align_dir, data):
config = data["config"]
out_file = os.path.join(align_dir, "{0}-sort.bam".format(names["lane"]))
samtools = config_utils.get_program("samtools", config)
bedtools = config_utils.get_program("bedtools", config)
resources = config_utils.get_resou... |
{'id': '0', 'type': 'module', 'children': ['1']}, {'id': '1', 'type': 'function_definition', 'children': ['2', '3', '6']}; {'id': '2', 'type': 'function_name', 'children': [], 'value': '_combine_regions'}, {'id': '3', 'type': 'parameters', 'children': ['4', '5']}; {'id': '4', 'type': 'identifier', 'children': [], 'valu... | def _combine_regions(all_regions, ref_regions):
chrom_order = {}
for i, x in enumerate(ref_regions):
chrom_order[x.chrom] = i
def wchrom_key(x):
chrom, start, end = x
return (chrom_order[chrom], start, end)
all_intervals = []
for region_group in all_regions:
for regio... |
{'id': '0', 'type': 'module', 'children': ['1']}, {'id': '1', 'type': 'function_definition', 'children': ['2', '3', '11']}; {'id': '2', 'type': 'function_name', 'children': [], 'value': '_add_meta'}, {'id': '3', 'type': 'parameters', 'children': ['4', '5', '8']}; {'id': '4', 'type': 'identifier', 'children': [], 'value... | def _add_meta(xs, sample=None, config=None):
out = []
for x in xs:
if not isinstance(x["path"], six.string_types) or not os.path.exists(x["path"]):
raise ValueError("Unexpected path for upload: %s" % x)
x["mtime"] = shared.get_file_timestamp(x["path"])
if sample:
... |
{'id': '0', 'type': 'module', 'children': ['1']}, {'id': '1', 'type': 'function_definition', 'children': ['2', '3', '12']}; {'id': '2', 'type': 'function_name', 'children': [], 'value': 'report'}, {'id': '3', 'type': 'parameters', 'children': ['4', '5', '6', '7', '8', '9', '10', '11']}; {'id': '4', 'type': 'identifier'... | def report(self, align_bam, ref_file, is_paired, bait_file, target_file,
variant_region_file, config):
dup_metrics = self._get_current_dup_metrics(align_bam)
align_metrics = self._collect_align_metrics(align_bam, ref_file)
gc_graph = None
insert_graph, insert_metrics, hybr... |
{'id': '0', 'type': 'module', 'children': ['1']}, {'id': '1', 'type': 'function_definition', 'children': ['2', '3', '14']}; {'id': '2', 'type': 'function_name', 'children': [], 'value': 'report'}, {'id': '3', 'type': 'parameters', 'children': ['4', '5', '6', '7', '8', '11']}; {'id': '4', 'type': 'identifier', 'children... | def report(self, align_bam, ref_file, gtf_file, is_paired=False, rrna_file="null"):
dup_metrics = self._get_current_dup_metrics(align_bam)
align_metrics = self._collect_align_metrics(align_bam, ref_file)
insert_graph, insert_metrics = (None, None)
if is_paired:
insert_graph, ... |
{'id': '0', 'type': 'module', 'children': ['1']}, {'id': '1', 'type': 'function_definition', 'children': ['2', '3', '5']}; {'id': '2', 'type': 'function_name', 'children': [], 'value': 'apply_recal'}, {'id': '3', 'type': 'parameters', 'children': ['4']}; {'id': '4', 'type': 'identifier', 'children': [], 'value': 'data'... | def apply_recal(data):
orig_bam = dd.get_align_bam(data) or dd.get_work_bam(data)
had_work_bam = "work_bam" in data
if dd.get_recalibrate(data) in [True, "gatk"]:
if data.get("prep_recal"):
logger.info("Applying BQSR recalibration with GATK: %s " % str(dd.get_sample_name(data)))
... |
{'id': '0', 'type': 'module', 'children': ['1']}, {'id': '1', 'type': 'function_definition', 'children': ['2', '3', '8']}; {'id': '2', 'type': 'function_name', 'children': [], 'value': '_prep_callable_bed'}, {'id': '3', 'type': 'parameters', 'children': ['4', '5', '6', '7']}; {'id': '4', 'type': 'identifier', 'children... | def _prep_callable_bed(in_file, work_dir, stats, data):
out_file = os.path.join(work_dir, "%s-merge.bed.gz" % utils.splitext_plus(os.path.basename(in_file))[0])
gsort = config_utils.get_program("gsort", data)
if not utils.file_uptodate(out_file, in_file):
with file_transaction(data, out_file) as tx_... |
{'id': '0', 'type': 'module', 'children': ['1']}, {'id': '1', 'type': 'function_definition', 'children': ['2', '3', '6']}; {'id': '2', 'type': 'function_name', 'children': [], 'value': 'fake_index'}, {'id': '3', 'type': 'parameters', 'children': ['4', '5']}; {'id': '4', 'type': 'identifier', 'children': [], 'value': 'i... | def fake_index(in_bam, data):
index_file = "%s.bai" % in_bam
if not utils.file_exists(index_file):
with file_transaction(data, index_file) as tx_out_file:
with open(tx_out_file, "w") as out_handle:
out_handle.write("name sorted -- no index")
return index_file |
{'id': '0', 'type': 'module', 'children': ['1']}, {'id': '1', 'type': 'function_definition', 'children': ['2', '3', '12']}; {'id': '2', 'type': 'function_name', 'children': [], 'value': 'sort'}, {'id': '3', 'type': 'parameters', 'children': ['4', '5', '6', '9']}; {'id': '4', 'type': 'identifier', 'children': [], 'value... | def sort(in_bam, config, order="coordinate", out_dir=None):
assert is_bam(in_bam), "%s in not a BAM file" % in_bam
if bam_already_sorted(in_bam, config, order):
return in_bam
sort_stem = _get_sort_stem(in_bam, order, out_dir)
sort_file = sort_stem + ".bam"
if not utils.file_exists(sort_file)... |
{'id': '0', 'type': 'module', 'children': ['1']}, {'id': '1', 'type': 'function_definition', 'children': ['2', '3', '9']}; {'id': '2', 'type': 'function_name', 'children': [], 'value': 'tobam_cl'}, {'id': '3', 'type': 'parameters', 'children': ['4', '5', '6']}; {'id': '4', 'type': 'identifier', 'children': [], 'value':... | def tobam_cl(data, out_file, is_paired=False):
do_dedup = _check_dedup(data)
umi_consensus = dd.get_umi_consensus(data)
with file_transaction(data, out_file) as tx_out_file:
if not do_dedup:
yield (sam_to_sortbam_cl(data, tx_out_file), tx_out_file)
elif umi_consensus:
... |
{'id': '0', 'type': 'module', 'children': ['1']}, {'id': '1', 'type': 'function_definition', 'children': ['2', '3', '9']}; {'id': '2', 'type': 'function_name', 'children': [], 'value': 'sam_to_sortbam_cl'}, {'id': '3', 'type': 'parameters', 'children': ['4', '5', '6']}; {'id': '4', 'type': 'identifier', 'children': [],... | def sam_to_sortbam_cl(data, tx_out_file, name_sort=False):
samtools = config_utils.get_program("samtools", data["config"])
cores, mem = _get_cores_memory(data, downscale=2)
tmp_file = "%s-sorttmp" % utils.splitext_plus(tx_out_file)[0]
sort_flag = "-n" if name_sort else ""
return ("{samtools} sort -@... |
{'id': '0', 'type': 'module', 'children': ['1']}, {'id': '1', 'type': 'function_definition', 'children': ['2', '3', '8']}; {'id': '2', 'type': 'function_name', 'children': [], 'value': 'samblaster_dedup_sort'}, {'id': '3', 'type': 'parameters', 'children': ['4', '5', '6', '7']}; {'id': '4', 'type': 'identifier', 'child... | def samblaster_dedup_sort(data, tx_out_file, tx_sr_file, tx_disc_file):
samblaster = config_utils.get_program("samblaster", data["config"])
samtools = config_utils.get_program("samtools", data["config"])
tmp_prefix = "%s-sorttmp" % utils.splitext_plus(tx_out_file)[0]
tobam_cmd = ("{samtools} sort {sort_... |
{'id': '0', 'type': 'module', 'children': ['1']}, {'id': '1', 'type': 'function_definition', 'children': ['2', '3', '6']}; {'id': '2', 'type': 'function_name', 'children': [], 'value': '_biobambam_dedup_sort'}, {'id': '3', 'type': 'parameters', 'children': ['4', '5']}; {'id': '4', 'type': 'identifier', 'children': [], ... | def _biobambam_dedup_sort(data, tx_out_file):
samtools = config_utils.get_program("samtools", data["config"])
cores, mem = _get_cores_memory(data, downscale=2)
tmp_file = "%s-sorttmp" % utils.splitext_plus(tx_out_file)[0]
if data.get("align_split"):
sort_opt = "-n" if data.get("align_split") and... |
{'id': '0', 'type': 'module', 'children': ['1']}, {'id': '1', 'type': 'function_definition', 'children': ['2', '3', '7']}; {'id': '2', 'type': 'function_name', 'children': [], 'value': '_prepare_bam_file'}, {'id': '3', 'type': 'parameters', 'children': ['4', '5', '6']}; {'id': '4', 'type': 'identifier', 'children': [],... | def _prepare_bam_file(bam_file, tmp_dir, config):
sort_mode = _get_sort_order(bam_file, config)
if sort_mode != "queryname":
bam_file = sort(bam_file, config, "queryname")
return bam_file |
{'id': '0', 'type': 'module', 'children': ['1']}, {'id': '1', 'type': 'function_definition', 'children': ['2', '3', '6']}; {'id': '2', 'type': 'function_name', 'children': [], 'value': '_concat_records'}, {'id': '3', 'type': 'parameters', 'children': ['4', '5']}; {'id': '4', 'type': 'identifier', 'children': [], 'value... | def _concat_records(items_by_key, input_order):
all_records = []
for (k, t) in input_order.items():
if t == "record":
all_records.append(k)
out_items_by_key = utils.deepish_copy(items_by_key)
out_input_order = utils.deepish_copy(input_order)
if len(all_records) > 1:
final... |
{'id': '0', 'type': 'module', 'children': ['1']}, {'id': '1', 'type': 'function_definition', 'children': ['2', '3', '7']}; {'id': '2', 'type': 'function_name', 'children': [], 'value': '_combine_files'}, {'id': '3', 'type': 'parameters', 'children': ['4', '5', '6']}; {'id': '4', 'type': 'identifier', 'children': [], 'v... | def _combine_files(tsv_files, work_dir, data):
header = "\t".join(["caller", "sample", "chrom", "start", "end", "svtype",
"lof", "annotation", "split_read_support", "paired_support_PE", "paired_support_PR"])
sample = dd.get_sample_name(data)
out_file = os.path.join(work_dir, "%s-prio... |
{'id': '0', 'type': 'module', 'children': ['1']}, {'id': '1', 'type': 'function_definition', 'children': ['2', '3', '5']}; {'id': '2', 'type': 'function_name', 'children': [], 'value': 'sort_filenames'}, {'id': '3', 'type': 'parameters', 'children': ['4']}; {'id': '4', 'type': 'identifier', 'children': [], 'value': 'fi... | def sort_filenames(filenames):
basenames = [os.path.basename(x) for x in filenames]
indexes = [i[0] for i in sorted(enumerate(basenames), key=lambda x:x[1])]
return [filenames[x] for x in indexes] |
{'id': '0', 'type': 'module', 'children': ['1']}, {'id': '1', 'type': 'function_definition', 'children': ['2', '3', '5']}; {'id': '2', 'type': 'function_name', 'children': [], 'value': 'sort_csv'}, {'id': '3', 'type': 'parameters', 'children': ['4']}; {'id': '4', 'type': 'identifier', 'children': [], 'value': 'in_file'... | def sort_csv(in_file):
out_file = "%s.sort" % in_file
if not (os.path.exists(out_file) and os.path.getsize(out_file) > 0):
cl = ["sort", "-k", "1,1", in_file]
with open(out_file, "w") as out_handle:
child = subprocess.Popen(cl, stdout=out_handle)
child.wait()
return o... |
{'id': '0', 'type': 'module', 'children': ['1']}, {'id': '1', 'type': 'function_definition', 'children': ['2', '3', '8']}; {'id': '2', 'type': 'function_name', 'children': [], 'value': 'hydra_to_vcf_writer'}, {'id': '3', 'type': 'parameters', 'children': ['4', '5', '6', '7']}; {'id': '4', 'type': 'identifier', 'childre... | def hydra_to_vcf_writer(hydra_file, genome_2bit, options, out_handle):
_write_vcf_header(out_handle)
brends = list(_get_vcf_breakends(hydra_file, genome_2bit, options))
brends.sort(key=attrgetter("chrom", "pos"))
for brend in brends:
_write_vcf_breakend(brend, out_handle) |
{'id': '0', 'type': 'module', 'children': ['1']}, {'id': '1', 'type': 'function_definition', 'children': ['2', '3', '7']}; {'id': '2', 'type': 'function_name', 'children': [], 'value': '_split_by_ready_regions'}, {'id': '3', 'type': 'parameters', 'children': ['4', '5', '6']}; {'id': '4', 'type': 'identifier', 'children... | def _split_by_ready_regions(ext, file_key, dir_ext_fn):
def _sort_by_size(region_w_bams):
region, _ = region_w_bams
_, start, end = region
return end - start
def _assign_bams_to_regions(data):
for i, region in enumerate(data["region"]):
work_bams = []
for ... |
{'id': '0', 'type': 'module', 'children': ['1']}, {'id': '1', 'type': 'ERROR', 'children': ['2', '137']}; {'id': '2', 'type': 'function_definition', 'children': ['3', '4', '9']}, {'id': '3', 'type': 'function_name', 'children': [], 'value': '_combine_variants'}; {'id': '4', 'type': 'parameters', 'children': ['5', '6', ... | def _combine_variants(in_vcfs, out_file, ref_file, config):
in_vcfs.sort()
wrote_header = False
with open(out_file, "w") as out_handle:
for in_vcf in (x[-1] for x in in_vcfs):
with open(in_vcf) as in_handle:
header = list(itertools.takewhile(lambda x: x.startswith("
... |
{'id': '0', 'type': 'module', 'children': ['1']}, {'id': '1', 'type': 'function_definition', 'children': ['2', '3', '18']}; {'id': '2', 'type': 'function_name', 'children': [], 'value': 'picard_sort'}, {'id': '3', 'type': 'parameters', 'children': ['4', '5', '6', '9', '12', '15']}; {'id': '4', 'type': 'identifier', 'ch... | def picard_sort(picard, align_bam, sort_order="coordinate",
out_file=None, compression_level=None, pipe=False):
base, ext = os.path.splitext(align_bam)
if out_file is None:
out_file = "%s-sort%s" % (base, ext)
if not file_exists(out_file):
with tx_tmpdir(picard._config) as tm... |
{'id': '0', 'type': 'module', 'children': ['1']}, {'id': '1', 'type': 'function_definition', 'children': ['2', '3', '7']}; {'id': '2', 'type': 'function_name', 'children': [], 'value': 'picard_fix_rgs'}, {'id': '3', 'type': 'parameters', 'children': ['4', '5', '6']}; {'id': '4', 'type': 'identifier', 'children': [], 'v... | def picard_fix_rgs(picard, in_bam, names):
out_file = "%s-fixrgs.bam" % os.path.splitext(in_bam)[0]
if not file_exists(out_file):
with tx_tmpdir(picard._config) as tmp_dir:
with file_transaction(picard._config, out_file) as tx_out_file:
opts = [("INPUT", in_bam),
... |
{'id': '0', 'type': 'module', 'children': ['1']}, {'id': '1', 'type': 'function_definition', 'children': ['2', '3', '6']}; {'id': '2', 'type': 'function_name', 'children': [], 'value': '_enforce_max_region_size'}, {'id': '3', 'type': 'parameters', 'children': ['4', '5']}; {'id': '4', 'type': 'identifier', 'children': [... | def _enforce_max_region_size(in_file, data):
max_size = 20000
overlap_size = 250
def _has_larger_regions(f):
return any(r.stop - r.start > max_size for r in pybedtools.BedTool(f))
out_file = "%s-regionlimit%s" % utils.splitext_plus(in_file)
if not utils.file_exists(out_file):
if _has... |
{'id': '0', 'type': 'module', 'children': ['1']}, {'id': '1', 'type': 'function_definition', 'children': ['2', '3', '10']}; {'id': '2', 'type': 'function_name', 'children': [], 'value': '_prep_vrn_file'}, {'id': '3', 'type': 'parameters', 'children': ['4', '5', '6', '7', '8', '9']}; {'id': '4', 'type': 'identifier', 'c... | def _prep_vrn_file(in_file, vcaller, work_dir, somatic_info, ignore_file, config):
if vcaller.startswith("vardict"):
variant_type = "vardict"
elif vcaller == "mutect":
variant_type = "mutect-smchet"
else:
raise ValueError("Unexpected variant caller for PhyloWGS prep: %s" % vcaller)
... |
{'id': '0', 'type': 'module', 'children': ['1']}, {'id': '1', 'type': 'function_definition', 'children': ['2', '3', '8']}; {'id': '2', 'type': 'function_name', 'children': [], 'value': 'concat'}, {'id': '3', 'type': 'parameters', 'children': ['4', '5']}; {'id': '4', 'type': 'identifier', 'children': [], 'value': 'bed_f... | def concat(bed_files, catted=None):
bed_files = [x for x in bed_files if x]
if len(bed_files) == 0:
if catted:
sorted_bed = catted.sort()
if not sorted_bed.fn.endswith(".bed"):
return sorted_bed.moveto(sorted_bed.fn + ".bed")
else:
retu... |
{'id': '0', 'type': 'module', 'children': ['1']}, {'id': '1', 'type': 'function_definition', 'children': ['2', '3', '5']}; {'id': '2', 'type': 'function_name', 'children': [], 'value': '_get_sv_callers'}, {'id': '3', 'type': 'parameters', 'children': ['4']}; {'id': '4', 'type': 'identifier', 'children': [], 'value': 'i... | def _get_sv_callers(items):
callers = []
for data in items:
for sv in data.get("sv", []):
callers.append(sv["variantcaller"])
return list(set([x for x in callers if x != "sv-ensemble"])).sort() |
{'id': '0', 'type': 'module', 'children': ['1']}, {'id': '1', 'type': 'function_definition', 'children': ['2', '3', '7']}; {'id': '2', 'type': 'function_name', 'children': [], 'value': 'get_sort_cmd'}, {'id': '3', 'type': 'parameters', 'children': ['4']}; {'id': '4', 'type': 'default_parameter', 'children': ['5', '6']}... | def get_sort_cmd(tmp_dir=None):
has_versionsort = subprocess.check_output("sort --help | grep version-sort; exit 0", shell=True).strip()
if has_versionsort:
cmd = "sort -V"
else:
cmd = "sort"
if tmp_dir and os.path.exists(tmp_dir) and os.path.isdir(tmp_dir):
cmd += " -T %s" % tmp... |
{'id': '0', 'type': 'module', 'children': ['1']}, {'id': '1', 'type': 'function_definition', 'children': ['2', '3', '15']}; {'id': '2', 'type': 'function_name', 'children': [], 'value': 'clean_file'}, {'id': '3', 'type': 'parameters', 'children': ['4', '5', '6', '9', '12']}; {'id': '4', 'type': 'identifier', 'children'... | def clean_file(in_file, data, prefix="", bedprep_dir=None, simple=None):
simple = "iconv -c -f utf-8 -t ascii | sed 's/ //g' |" if simple else ""
if in_file:
if not bedprep_dir:
bedprep_dir = utils.safe_makedir(os.path.join(data["dirs"]["work"], "bedprep"))
if prefix and os.path.base... |
{'id': '0', 'type': 'module', 'children': ['1']}, {'id': '1', 'type': 'function_definition', 'children': ['2', '3', '8']}; {'id': '2', 'type': 'function_name', 'children': [], 'value': '_sort_by_region'}, {'id': '3', 'type': 'parameters', 'children': ['4', '5', '6', '7']}; {'id': '4', 'type': 'identifier', 'children': ... | def _sort_by_region(fnames, regions, ref_file, config):
contig_order = {}
for i, sq in enumerate(ref.file_contigs(ref_file, config)):
contig_order[sq.name] = i
sitems = []
assert len(regions) == len(fnames), (regions, fnames)
added_fnames = set([])
for region, fname in zip(regions, fname... |
{'id': '0', 'type': 'module', 'children': ['1']}, {'id': '1', 'type': 'function_definition', 'children': ['2', '3', '9']}; {'id': '2', 'type': 'function_name', 'children': [], 'value': '_get_file_list'}, {'id': '3', 'type': 'parameters', 'children': ['4', '5', '6', '7', '8']}; {'id': '4', 'type': 'identifier', 'childre... | def _get_file_list(orig_files, out_file, regions, ref_file, config):
sorted_files = _sort_by_region(orig_files, regions, ref_file, config)
exist_files = [(c, x) for c, x in sorted_files if os.path.exists(x) and vcf_has_variants(x)]
if len(exist_files) == 0:
exist_files = [x for c, x in sorted_files ... |
{'id': '0', 'type': 'module', 'children': ['1']}, {'id': '1', 'type': 'function_definition', 'children': ['2', '3', '6']}; {'id': '2', 'type': 'function_name', 'children': [], 'value': 'sort_by_ref'}, {'id': '3', 'type': 'parameters', 'children': ['4', '5']}; {'id': '4', 'type': 'identifier', 'children': [], 'value': '... | def sort_by_ref(vcf_file, data):
out_file = "%s-prep.vcf.gz" % utils.splitext_plus(vcf_file)[0]
if not utils.file_uptodate(out_file, vcf_file):
with file_transaction(data, out_file) as tx_out_file:
header_file = "%s-header.txt" % utils.splitext_plus(tx_out_file)[0]
with open(head... |
{'id': '0', 'type': 'module', 'children': ['1']}, {'id': '1', 'type': 'function_definition', 'children': ['2', '3', '8']}; {'id': '2', 'type': 'function_name', 'children': [], 'value': 'align_to_sort_bam'}, {'id': '3', 'type': 'parameters', 'children': ['4', '5', '6', '7']}; {'id': '4', 'type': 'identifier', 'children'... | def align_to_sort_bam(fastq1, fastq2, aligner, data):
names = data["rgnames"]
align_dir_parts = [data["dirs"]["work"], "align", names["sample"]]
if data.get("disambiguate"):
align_dir_parts.append(data["disambiguate"]["genome_build"])
aligner_index = _get_aligner_index(aligner, data)
align_d... |
{'id': '0', 'type': 'module', 'children': ['1']}, {'id': '1', 'type': 'function_definition', 'children': ['2', '3', '12']}; {'id': '2', 'type': 'function_name', 'children': [], 'value': '_align_from_fastq'}, {'id': '3', 'type': 'parameters', 'children': ['4', '5', '6', '7', '8', '9', '10', '11']}; {'id': '4', 'type': '... | def _align_from_fastq(fastq1, fastq2, aligner, align_ref, sam_ref, names,
align_dir, data):
config = data["config"]
align_fn = TOOLS[aligner].align_fn
out = align_fn(fastq1, fastq2, align_ref, names, align_dir, data)
if isinstance(out, dict):
assert out.get("work_bam"), (dd... |
{'id': '0', 'type': 'module', 'children': ['1']}, {'id': '1', 'type': 'function_definition', 'children': ['2', '3', '9']}; {'id': '2', 'type': 'function_name', 'children': [], 'value': 'picard_prep'}, {'id': '3', 'type': 'parameters', 'children': ['4', '5', '6', '7', '8']}; {'id': '4', 'type': 'identifier', 'children':... | def picard_prep(in_bam, names, ref_file, dirs, data):
runner = broad.runner_from_path("picard", data["config"])
work_dir = utils.safe_makedir(os.path.join(dirs["work"], "bamclean", names["sample"]))
runner.run_fn("picard_index_ref", ref_file)
reorder_bam = os.path.join(work_dir, "%s-reorder.bam" %
... |
{'id': '0', 'type': 'module', 'children': ['1']}, {'id': '1', 'type': 'function_definition', 'children': ['2', '3', '8']}; {'id': '2', 'type': 'function_name', 'children': [], 'value': 'iterate_flattened_separately'}, {'id': '3', 'type': 'parameters', 'children': ['4', '5']}; {'id': '4', 'type': 'identifier', 'children... | def iterate_flattened_separately(dictionary, manually_sorted_keys=None):
if manually_sorted_keys is None:
manually_sorted_keys = []
for key in manually_sorted_keys:
if key in dictionary:
yield key, dictionary[key]
single_line_keys = [key for key in dictionary.keys() if
... |
{'id': '0', 'type': 'module', 'children': ['1']}, {'id': '1', 'type': 'function_definition', 'children': ['2', '3', '7']}; {'id': '2', 'type': 'function_name', 'children': [], 'value': 'gather_command_line_options'}, {'id': '3', 'type': 'parameters', 'children': ['4']}; {'id': '4', 'type': 'default_parameter', 'childre... | def gather_command_line_options(filter_disabled=None):
if filter_disabled is None:
filter_disabled = not SETTINGS.COMMAND_LINE.SHOW_DISABLED_OPTIONS
options = [opt for opt in get_inheritors(CommandLineOption)
if not filter_disabled or opt._enabled]
return sorted(options, key=lambda op... |
{'id': '0', 'type': 'module', 'children': ['1']}, {'id': '1', 'type': 'function_definition', 'children': ['2', '3', '37']}; {'id': '2', 'type': 'function_name', 'children': [], 'value': 'bar'}, {'id': '3', 'type': 'parameters', 'children': ['4', '5', '10', '13', '16', '19', '22', '25', '28', '31', '34']}; {'id': '4', '... | def bar(df, figsize=(24, 10), fontsize=16, labels=None, log=False, color='dimgray', inline=False,
filter=None, n=0, p=0, sort=None):
nullity_counts = len(df) - df.isnull().sum()
df = nullity_filter(df, filter=filter, n=n, p=p)
df = nullity_sort(df, sort=sort)
plt.figure(figsize=figsize)
(nul... |
{'id': '0', 'type': 'module', 'children': ['1']}, {'id': '1', 'type': 'function_definition', 'children': ['2', '3', '44']}; {'id': '2', 'type': 'function_name', 'children': [], 'value': 'heatmap'}, {'id': '3', 'type': 'parameters', 'children': ['4', '5', '8', '11', '14', '17', '20', '25', '28', '31', '34', '38', '41']}... | def heatmap(df, inline=False,
filter=None, n=0, p=0, sort=None,
figsize=(20, 12), fontsize=16, labels=True,
cmap='RdBu', vmin=-1, vmax=1, cbar=True
):
df = nullity_filter(df, filter=filter, n=n, p=p)
df = nullity_sort(df, sort=sort)
plt.figure(figsize=figsize... |
{'id': '0', 'type': 'module', 'children': ['1']}, {'id': '1', 'type': 'function_definition', 'children': ['2', '3', '32']}; {'id': '2', 'type': 'function_name', 'children': [], 'value': 'dendrogram'}, {'id': '3', 'type': 'parameters', 'children': ['4', '5', '8', '11', '14', '17', '20', '23', '26', '29']}; {'id': '4', '... | def dendrogram(df, method='average',
filter=None, n=0, p=0, sort=None,
orientation=None, figsize=None,
fontsize=16, inline=False
):
if not figsize:
if len(df.columns) <= 50 or orientation == 'top' or orientation == 'bottom':
figsize = (... |
{'id': '0', 'type': 'module', 'children': ['1']}, {'id': '1', 'type': 'function_definition', 'children': ['2', '3', '8']}; {'id': '2', 'type': 'function_name', 'children': [], 'value': 'nullity_sort'}, {'id': '3', 'type': 'parameters', 'children': ['4', '5']}; {'id': '4', 'type': 'identifier', 'children': [], 'value': ... | def nullity_sort(df, sort=None):
if sort == 'ascending':
return df.iloc[np.argsort(df.count(axis='columns').values), :]
elif sort == 'descending':
return df.iloc[np.flipud(np.argsort(df.count(axis='columns').values)), :]
else:
return df |
{'id': '0', 'type': 'module', 'children': ['1']}, {'id': '1', 'type': 'function_definition', 'children': ['2', '3', '20']}; {'id': '2', 'type': 'function_name', 'children': [], 'value': 'sortino_ratio'}, {'id': '3', 'type': 'parameters', 'children': ['4', '5', '8', '11', '14', '17']}; {'id': '4', 'type': 'identifier', ... | def sortino_ratio(returns,
required_return=0,
period=DAILY,
annualization=None,
out=None,
_downside_risk=None):
allocated_output = out is None
if allocated_output:
out = np.empty(returns.shape[1:])
return_1d = ... |
{'id': '0', 'type': 'module', 'children': ['1']}, {'id': '1', 'type': 'function_definition', 'children': ['2', '3', '17']}; {'id': '2', 'type': 'function_name', 'children': [], 'value': 'downside_risk'}, {'id': '3', 'type': 'parameters', 'children': ['4', '5', '8', '11', '14']}; {'id': '4', 'type': 'identifier', 'child... | def downside_risk(returns,
required_return=0,
period=DAILY,
annualization=None,
out=None):
allocated_output = out is None
if allocated_output:
out = np.empty(returns.shape[1:])
returns_1d = returns.ndim == 1
if len(returns) ... |
{'id': '0', 'type': 'module', 'children': ['1']}, {'id': '1', 'type': 'function_definition', 'children': ['2', '3', '5']}; {'id': '2', 'type': 'function_name', 'children': [], 'value': 'GetLoadingOrder'}, {'id': '3', 'type': 'parameters', 'children': ['4']}; {'id': '4', 'type': 'identifier', 'children': [], 'value': 's... | def GetLoadingOrder(self):
result = {}
for filename, mapping in self._file_mapping.iteritems():
loading_order = mapping['loading_order']
if loading_order is not None:
result[loading_order] = filename
return list(result[key] for key in sorted(result)) |
{'id': '0', 'type': 'module', 'children': ['1']}, {'id': '1', 'type': 'function_definition', 'children': ['2', '3', '5']}; {'id': '2', 'type': 'function_name', 'children': [], 'value': 'GetOrderKey'}, {'id': '3', 'type': 'parameters', 'children': ['4']}; {'id': '4', 'type': 'identifier', 'children': [], 'value': 'self'... | def GetOrderKey(self):
context_attributes = ['_type']
context_attributes.extend(ExceptionWithContext.CONTEXT_PARTS)
context_attributes.extend(self._GetExtraOrderAttributes())
tokens = []
for context_attribute in context_attributes:
tokens.append(getattr(self, context_attribute, None))
retu... |
{'id': '0', 'type': 'module', 'children': ['1']}, {'id': '1', 'type': 'function_definition', 'children': ['2', '3', '7']}; {'id': '2', 'type': 'function_name', 'children': [], 'value': 'AddShapePointObjectUnsorted'}, {'id': '3', 'type': 'parameters', 'children': ['4', '5', '6']}; {'id': '4', 'type': 'identifier', 'chil... | def AddShapePointObjectUnsorted(self, shapepoint, problems):
if (len(self.sequence) == 0 or
shapepoint.shape_pt_sequence >= self.sequence[-1]):
index = len(self.sequence)
elif shapepoint.shape_pt_sequence <= self.sequence[0]:
index = 0
else:
index = bisect.bisect(self.sequence, sha... |
{'id': '0', 'type': 'module', 'children': ['1']}, {'id': '1', 'type': 'function_definition', 'children': ['2', '3', '8']}; {'id': '2', 'type': 'function_name', 'children': [], 'value': 'GetStopTimes'}, {'id': '3', 'type': 'parameters', 'children': ['4', '5']}; {'id': '4', 'type': 'identifier', 'children': [], 'value': ... | def GetStopTimes(self, problems=None):
cursor = self._schedule._connection.cursor()
cursor.execute(
'SELECT arrival_secs,departure_secs,stop_headsign,pickup_type,'
'drop_off_type,shape_dist_traveled,stop_id,stop_sequence,timepoint '
'FROM stop_times '
'WHERE trip_id=? '
'... |
{'id': '0', 'type': 'module', 'children': ['1']}, {'id': '1', 'type': 'function_definition', 'children': ['2', '3', '5']}; {'id': '2', 'type': 'function_name', 'children': [], 'value': 'GetFrequencyStartTimes'}, {'id': '3', 'type': 'parameters', 'children': ['4']}; {'id': '4', 'type': 'identifier', 'children': [], 'val... | def GetFrequencyStartTimes(self):
start_times = []
for freq_tuple in self.GetFrequencyTuples():
(start_secs, end_secs, headway_secs) = freq_tuple[0:3]
run_secs = start_secs
while run_secs < end_secs:
start_times.append(run_secs)
run_secs += headway_secs
return start_times |
{'id': '0', 'type': 'module', 'children': ['1']}, {'id': '1', 'type': 'function_definition', 'children': ['2', '3', '6']}; {'id': '2', 'type': 'function_name', 'children': [], 'value': 'create'}, {'id': '3', 'type': 'parameters', 'children': ['4', '5']}; {'id': '4', 'type': 'identifier', 'children': [], 'value': 'filen... | def create(filename, spec):
from . import _segyio
if not structured(spec):
tracecount = spec.tracecount
else:
tracecount = len(spec.ilines) * len(spec.xlines) * len(spec.offsets)
ext_headers = spec.ext_headers if hasattr(spec, 'ext_headers') else 0
samples = numpy.asarray(spec.sample... |
{'id': '0', 'type': 'module', 'children': ['1']}, {'id': '1', 'type': 'function_definition', 'children': ['2', '3', '8']}; {'id': '2', 'type': 'function_name', 'children': [], 'value': 'rotation'}, {'id': '3', 'type': 'parameters', 'children': ['4', '5']}; {'id': '4', 'type': 'identifier', 'children': [], 'value': 'f'}... | def rotation(f, line = 'fast'):
if f.unstructured:
raise ValueError("Rotation requires a structured file")
lines = { 'fast': f.fast,
'slow': f.slow,
'iline': f.iline,
'xline': f.xline,
}
if line not in lines:
error = "Unknown line {}".for... |
{'id': '0', 'type': 'module', 'children': ['1']}, {'id': '1', 'type': 'function_definition', 'children': ['2', '3', '23']}; {'id': '2', 'type': 'function_name', 'children': [], 'value': 'from_array3D'}, {'id': '3', 'type': 'parameters', 'children': ['4', '5', '6', '9', '12', '17', '20']}; {'id': '4', 'type': 'identifie... | def from_array3D(filename, data, iline=189,
xline=193,
format=SegySampleFormat.IBM_FLOAT_4_BYTE,
dt=4000,
delrt=0):
data = np.asarray(data)
dimensions = len(data.shape)
if dime... |
{'id': '0', 'type': 'module', 'children': ['1']}, {'id': '1', 'type': 'function_definition', 'children': ['2', '3', '23']}; {'id': '2', 'type': 'function_name', 'children': [], 'value': 'open'}, {'id': '3', 'type': 'parameters', 'children': ['4', '5', '8', '11', '14', '17', '20']}; {'id': '4', 'type': 'identifier', 'ch... | def open(filename, mode="r", iline = 189,
xline = 193,
strict = True,
ignore_geometry = False,
endian = 'big'):
if 'w' in mode:
problem = 'w in mode would truncate the file'
solution =... |
{'id': '0', 'type': 'module', 'children': ['1']}, {'id': '1', 'type': 'function_definition', 'children': ['2', '3', '6']}; {'id': '2', 'type': 'function_name', 'children': [], 'value': 'calc_min_interval'}, {'id': '3', 'type': 'parameters', 'children': ['4', '5']}; {'id': '4', 'type': 'identifier', 'children': [], 'val... | def calc_min_interval(x, alpha):
n = len(x)
cred_mass = 1.0 - alpha
interval_idx_inc = int(np.floor(cred_mass * n))
n_intervals = n - interval_idx_inc
interval_width = x[interval_idx_inc:] - x[:n_intervals]
if len(interval_width) == 0:
print_('Too few elements for interval calculation')
... |
{'id': '0', 'type': 'module', 'children': ['1']}, {'id': '1', 'type': 'function_definition', 'children': ['2', '3', '6']}; {'id': '2', 'type': 'function_name', 'children': [], 'value': '_compute_gas_price'}, {'id': '3', 'type': 'parameters', 'children': ['4', '5']}; {'id': '4', 'type': 'identifier', 'children': [], 'va... | def _compute_gas_price(probabilities, desired_probability):
first = probabilities[0]
last = probabilities[-1]
if desired_probability >= first.prob:
return int(first.gas_price)
elif desired_probability <= last.prob:
return int(last.gas_price)
for left, right in sliding_window(2, proba... |
{'id': '0', 'type': 'module', 'children': ['1']}, {'id': '1', 'type': 'function_definition', 'children': ['2', '3', '12']}; {'id': '2', 'type': 'function_name', 'children': [], 'value': 'generate_X_grid'}, {'id': '3', 'type': 'parameters', 'children': ['4', '5', '6', '9']}; {'id': '4', 'type': 'identifier', 'children':... | def generate_X_grid(self, term, n=100, meshgrid=False):
if not self._is_fitted:
raise AttributeError('GAM has not been fitted. Call fit first.')
if self.terms[term].isintercept:
raise ValueError('cannot create grid for intercept term')
if self.terms[term].istensor:
... |
{'id': '0', 'type': 'module', 'children': ['1']}, {'id': '1', 'type': 'function_definition', 'children': ['2', '3', '6']}; {'id': '2', 'type': 'function_name', 'children': [], 'value': 'build_from_info'}, {'id': '3', 'type': 'parameters', 'children': ['4', '5']}; {'id': '4', 'type': 'identifier', 'children': [], 'value... | def build_from_info(cls, info):
terms = []
for term_info in info['terms']:
terms.append(SplineTerm.build_from_info(term_info))
return cls(*terms) |
{'id': '0', 'type': 'module', 'children': ['1']}, {'id': '1', 'type': 'function_definition', 'children': ['2', '3', '10']}; {'id': '2', 'type': 'function_name', 'children': [], 'value': 'sort_kate_imports'}, {'id': '3', 'type': 'parameters', 'children': ['4', '7']}; {'id': '4', 'type': 'default_parameter', 'children': ... | def sort_kate_imports(add_imports=(), remove_imports=()):
document = kate.activeDocument()
view = document.activeView()
position = view.cursorPosition()
selection = view.selectionRange()
sorter = SortImports(file_contents=document.text(), add_imports=add_imports, remove_imports=remove_imports,
... |
{'id': '0', 'type': 'module', 'children': ['1']}, {'id': '1', 'type': 'function_definition', 'children': ['2', '3', '5', '7']}; {'id': '2', 'type': 'function_name', 'children': [], 'value': '_get_line'}, {'id': '3', 'type': 'parameters', 'children': ['4']}; {'id': '4', 'type': 'identifier', 'children': [], 'value': 'se... | def _get_line(self) -> str:
line = self.in_lines[self.index]
self.index += 1
return line |
{'id': '0', 'type': 'module', 'children': ['1']}, {'id': '1', 'type': 'function_definition', 'children': ['2', '3', '22', '24']}; {'id': '2', 'type': 'function_name', 'children': [], 'value': '_add_comments'}, {'id': '3', 'type': 'parameters', 'children': ['4', '5', '17']}; {'id': '4', 'type': 'identifier', 'children':... | def _add_comments(
self,
comments: Optional[Sequence[str]],
original_string: str = ""
) -> str:
if self.config['ignore_comments']:
return self._strip_comments(original_string)[0]
if not comments:
return original_string
else:
return ... |
{'id': '0', 'type': 'module', 'children': ['1']}, {'id': '1', 'type': 'function_definition', 'children': ['2', '3', '9', '11']}; {'id': '2', 'type': 'function_name', 'children': [], 'value': '_wrap'}, {'id': '3', 'type': 'parameters', 'children': ['4', '5']}; {'id': '4', 'type': 'identifier', 'children': [], 'value': '... | def _wrap(self, line: str) -> str:
wrap_mode = self.config['multi_line_output']
if len(line) > self.config['line_length'] and wrap_mode != WrapModes.NOQA:
line_without_comment = line
comment = None
if '
line_without_comment, comment = line.split('
... |
{'id': '0', 'type': 'module', 'children': ['1']}, {'id': '1', 'type': 'function_definition', 'children': ['2', '3', '5']}; {'id': '2', 'type': 'function_name', 'children': [], 'value': 'get_formatter'}, {'id': '3', 'type': 'parameters', 'children': ['4']}; {'id': '4', 'type': 'identifier', 'children': [], 'value': 'nam... | def get_formatter(name):
for k in sorted(_FORMATTERS):
if k.startswith(name):
return _FORMATTERS[k] |
{'id': '0', 'type': 'module', 'children': ['1']}, {'id': '1', 'type': 'function_definition', 'children': ['2', '3', '5']}; {'id': '2', 'type': 'function_name', 'children': [], 'value': 'call_once'}, {'id': '3', 'type': 'parameters', 'children': ['4']}; {'id': '4', 'type': 'identifier', 'children': [], 'value': 'func'},... | def call_once(func):
argspec = inspect.getargspec(func)
if argspec.args or argspec.varargs or argspec.keywords:
raise ValueError('Can only decorate functions with no args', func, argspec)
@functools.wraps(func)
def _wrapper():
if not _wrapper.HasRun():
_wrapper.MarkAsRun()
_wrapper.return_va... |
{'id': '0', 'type': 'module', 'children': ['1']}, {'id': '1', 'type': 'function_definition', 'children': ['2', '3', '19']}; {'id': '2', 'type': 'function_name', 'children': [], 'value': 'paginate'}, {'id': '3', 'type': 'parameters', 'children': ['4', '5', '6', '7', '10', '13', '16']}; {'id': '4', 'type': 'identifier', ... | def paginate(self, model_class, order_by, page_num=1, page_size=100, conditions=None, settings=None):
'''
Selects records and returns a single page of model instances.
- `model_class`: the model class matching the query's table,
or `None` for getting back instances of an ad-hoc model.
... |
{'id': '0', 'type': 'module', 'children': ['1']}, {'id': '1', 'type': 'function_definition', 'children': ['2', '3', '6']}; {'id': '2', 'type': 'function_name', 'children': [], 'value': 'compute_memory_contents_under_schedule'}, {'id': '3', 'type': 'parameters', 'children': ['4', '5']}; {'id': '4', 'type': 'identifier',... | def compute_memory_contents_under_schedule(self, schedule):
out_degree = self._compute_initial_out_degree()
curr_memory_contents = set()
memory_contents_for_each_operation = []
for operation_id in schedule:
operation_name = self._operations[operation_id].name
for output_name in self.get_oper... |
{'id': '0', 'type': 'module', 'children': ['1']}, {'id': '1', 'type': 'function_definition', 'children': ['2', '3', '16', '18']}; {'id': '2', 'type': 'function_name', 'children': [], 'value': 'sort'}, {'id': '3', 'type': 'parameters', 'children': ['4', '5', '9', '14']}; {'id': '4', 'type': 'identifier', 'children': [],... | def sort(self, by: str, out: object = '', **kwargs) -> 'SASdata':
outstr = ''
options = ''
if out:
if isinstance(out, str):
fn = out.partition('.')
if fn[1] == '.':
libref = fn[0]
table = fn[2]
... |
{'id': '0', 'type': 'module', 'children': ['1']}, {'id': '1', 'type': 'function_definition', 'children': ['2', '3', '30']}; {'id': '2', 'type': 'function_name', 'children': [], 'value': 'find_items'}, {'id': '3', 'type': 'parameters', 'children': ['4', '5', '6', '9', '12', '15', '18', '21', '24', '27']}; {'id': '4', 't... | def find_items(self, q, shape=ID_ONLY, depth=SHALLOW, additional_fields=None, order_fields=None,
calendar_view=None, page_size=None, max_items=None, offset=0):
if shape not in SHAPE_CHOICES:
raise ValueError("'shape' %s must be one of %s" % (shape, SHAPE_CHOICES))
if depth... |
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