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def removeGcodeFile(gcodeFilePath): if ('alterations' not in gcodeFilePath): os.remove(gcodeFilePath) print ('removeGeneratedFiles deleted ' + gcodeFilePath) return if ('example_' not in gcodeFilePath): os.remove(gcodeFilePath) print ('removeGeneratedFiles deleted ' + gcodeFilePath)
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remove gcode file .
train
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def filter_list(complete_list, browsers): table = {} for entry in complete_list: candidate = (entry[1].text_content(), entry[2].text_content()) for name in browsers: found = False if (name.lower() in candidate[1].lower()): for version in browsers[name]: if (version.lower() in candidate[1].lower()): if (table.get(name) is None): table[name] = [] table[name].append(candidate) browsers[name].remove(version) found = True break if found: break return table
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filter the received list based on a look up table .
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def entoken(textstream, positions=False, chars=False, start_pos=0, start_char=0, **kwargs): pos = start_pos char = start_char t = Token(positions=positions, chars=chars, **kwargs) for text in textstream: t.text = text if positions: t.pos = pos pos += 1 if chars: t.startchar = char char = (char + len(text)) t.endchar = char (yield t)
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takes a sequence of unicode strings and yields a series of token objects .
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def _get_queryset(klass): if hasattr(klass, '_default_manager'): return klass._default_manager.all() return klass
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return a queryset or a manager .
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def read_bad_channels(fid, node): nodes = dir_tree_find(node, FIFF.FIFFB_MNE_BAD_CHANNELS) bads = [] if (len(nodes) > 0): for node in nodes: tag = find_tag(fid, node, FIFF.FIFF_MNE_CH_NAME_LIST) if ((tag is not None) and (tag.data is not None)): bads = tag.data.split(':') return bads
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read bad channels .
train
false
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def passwd(passwd, user='', alg='sha1', realm=None): digest = ((hasattr(hashlib, alg) and getattr(hashlib, alg)) or None) if digest: if realm: digest.update('{0}:{1}:{2}'.format(user, realm, passwd)) else: digest.update(passwd) return ((digest and digest.hexdigest()) or False)
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this function replaces the $catalina_home/bin/digest .
train
true
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def genVersion(*args, **kwargs): return ('from incremental import Version\n__version__=%r' % Version(*args, **kwargs)).encode('ascii')
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a convenience for generating _version .
train
false
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def write_qual_line(demultiplexed_qual_f, qual_seq, label_line, keep_barcode, bc_len): if keep_barcode: final_seq = qual_seq else: final_seq = qual_seq[bc_len:] qual_line_size = 60 current_qual_scores_lines = [] for slice in range(0, len(final_seq), qual_line_size): current_segment = final_seq[slice:(slice + qual_line_size)] current_qual_scores_lines.append(' '.join(map(str, current_segment))) demultiplexed_qual_f.write(('>%s\n' % label_line)) demultiplexed_qual_f.write('\n'.join(current_qual_scores_lines)) demultiplexed_qual_f.write('\n')
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writes quality score sequence out in proper format demultiplexed_qual_f: open file object to write label/qual scores to .
train
false
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@vm_ref_cache_from_instance def get_vm_ref(session, instance): uuid = instance.uuid vm_ref = (search_vm_ref_by_identifier(session, uuid) or _get_vm_ref_from_name(session, instance.name)) if (vm_ref is None): raise exception.InstanceNotFound(instance_id=uuid) return vm_ref
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get reference to the vm through uuid or vm name .
train
false
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def validate_next_url(next_url): if next_url.startswith('//'): return False if (not ((next_url[0] == '/') or next_url.startswith(settings.DOMAIN) or next_url.startswith(settings.CAS_SERVER_URL) or next_url.startswith(settings.MFR_SERVER_URL))): return False return True
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non-view helper function that checks next_url .
train
false
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def getVersion(): with open(os.path.join(REPO_DIR, 'VERSION'), 'r') as versionFile: return versionFile.read().strip()
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get version from local file .
train
true
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def format_dot(dotfilename, format=None): cmd = (u"dot -T%s -O '%s'" % (format, dotfilename)) try: CommandLine(cmd).run() except IOError as ioe: if (u'could not be found' in str(ioe)): raise IOError(u"Cannot draw directed graph; executable 'dot' is unavailable") else: raise ioe else: logger.info((u'Converting dotfile: %s to %s format' % (dotfilename, format)))
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dump a directed graph .
train
false
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def _StartIOLoop(callback): io_loop = ioloop.IOLoop.current() try: httpclient.AsyncHTTPClient.configure('tornado.curl_httpclient.CurlAsyncHTTPClient') httpclient.AsyncHTTPClient(io_loop=io_loop, max_clients=100) except: logging.exception('failed to configure tornado AsyncHTTPClient to use pycurl') io_loop.add_callback(callback) io_loop.start()
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creates a new ioloop object .
train
false
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def set_win32_cert_path(): if hasattr(sys, 'frozen'): prog_path = os.path.dirname(sys.executable) crt_path = os.path.join(prog_path, 'ca-certificates.crt') else: cur_path = os.path.dirname(__file__) crt_path = os.path.join(cur_path, 'packaging', 'datadog-agent', 'win32', 'install_files', 'ca-certificates.crt') import tornado.simple_httpclient log.info(('Windows certificate path: %s' % crt_path)) tornado.simple_httpclient._DEFAULT_CA_CERTS = crt_path
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in order to use tornado .
train
false
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def scp_between_remotes(src, dst, port, s_passwd, d_passwd, s_name, d_name, s_path, d_path, limit='', log_filename=None, timeout=600, src_inter=None, dst_inter=None): if limit: limit = ('-l %s' % limit) if (src and src.lower().startswith('fe80')): if (not src_inter): raise SCPError('When using ipv6 linklocal address must assign ', 'the interface the neighbour attache') src = ('%s%%%s' % (src, src_inter)) if (dst and dst.lower().startswith('fe80')): if (not dst_inter): raise SCPError('When using ipv6 linklocal address must assign ', 'the interface the neighbour attache') dst = ('%s%%%s' % (dst, dst_inter)) command = ('scp -v -o UserKnownHostsFile=/dev/null -o PreferredAuthentications=password -r %s -P %s %s@\\[%s\\]:%s %s@\\[%s\\]:%s' % (limit, port, s_name, src, s_path, d_name, dst, d_path)) password_list = [] password_list.append(s_passwd) password_list.append(d_passwd) return remote_scp(command, password_list, log_filename, timeout)
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copy files from a remote host to another remote host .
train
false
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def getNewRepository(): return ExportRepository()
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get the repository constructor .
train
false
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def get_all_headers(message, key): return message.get_all(key)
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given an httpmessage .
train
false
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def get_rnd_shuffle(builder): fnty = ir.FunctionType(ir.VoidType(), (rnd_state_ptr_t,)) fn = builder.function.module.get_or_insert_function(fnty, 'numba_rnd_shuffle') fn.args[0].add_attribute('nocapture') return fn
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get the internal function to shuffle the mt taste .
train
false
47,783
def filePathDelta(origin, destination): commonItems = 0 path1 = origin.path.split(os.sep) path2 = destination.path.split(os.sep) for (elem1, elem2) in zip(path1, path2): if (elem1 == elem2): commonItems += 1 else: break path = (['..'] * (len(path1) - commonItems)) return (path + path2[commonItems:])
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return a list of strings that represent c{destination} as a path relative to c{origin} .
train
false
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def servermods(): cmd = '{0} -l'.format(_detect_os()) ret = [] out = __salt__['cmd.run'](cmd).splitlines() for line in out: if (not line): continue if ('.c' in line): ret.append(line.strip()) return ret
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return list of modules compiled into the server cli example: .
train
true
47,785
def java_import(jvm_view, import_str): gateway_client = jvm_view._gateway_client command = ((((((proto.JVMVIEW_COMMAND_NAME + proto.JVM_IMPORT_SUB_COMMAND_NAME) + jvm_view._id) + u'\n') + escape_new_line(import_str)) + u'\n') + proto.END_COMMAND_PART) answer = gateway_client.send_command(command) return_value = get_return_value(answer, gateway_client, None, None) return return_value
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imports the package or class specified by import_str in the jvm view namespace .
train
false
47,789
def process_projection_requirements(figure, *args, **kwargs): ispolar = kwargs.pop(u'polar', False) projection = kwargs.pop(u'projection', None) if ispolar: if ((projection is not None) and (projection != u'polar')): raise ValueError((u'polar=True, yet projection=%r. Only one of these arguments should be supplied.' % projection)) projection = u'polar' if (projection == u'polar'): kwargs.setdefault(u'resolution', 1) if (isinstance(projection, six.string_types) or (projection is None)): projection_class = get_projection_class(projection) elif hasattr(projection, u'_as_mpl_axes'): (projection_class, extra_kwargs) = projection._as_mpl_axes() kwargs.update(**extra_kwargs) else: raise TypeError((u'projection must be a string, None or implement a _as_mpl_axes method. Got %r' % projection)) key = figure._make_key(*args, **kwargs) return (projection_class, kwargs, key)
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handle the args/kwargs to for add_axes/add_subplot/gca .
train
false
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def get_user_scope(module, position): user_stmt = module.get_statement_for_position(position) if (user_stmt is None): def scan(scope): for s in scope.children: if (s.start_pos <= position <= s.end_pos): if isinstance(s, (tree.Scope, tree.Flow)): return (scan(s) or s) elif (s.type in ('suite', 'decorated')): return scan(s) return None return (scan(module) or module) else: return user_stmt.get_parent_scope(include_flows=True)
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returns the scope in which the user resides .
train
false
47,791
def dup_expand(polys, K): if (not polys): return [K.one] f = polys[0] for g in polys[1:]: f = dup_mul(f, g, K) return f
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multiply together several polynomials in k[x] .
train
false
47,793
@contextmanager def check_mongo_calls(num_finds=0, num_sends=None): with check_mongo_calls_range(num_finds, num_finds, num_sends, num_sends): (yield)
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instruments the given store to count the number of calls to find and the number of calls to send_message which is for insert .
train
false
47,795
@app.route('/cookies') def view_cookies(hide_env=True): cookies = dict(request.cookies.items()) if (hide_env and ('show_env' not in request.args)): for key in ENV_COOKIES: try: del cookies[key] except KeyError: pass return jsonify(cookies=cookies)
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returns cookie data .
train
true
47,796
def _parse_acl(acl, user, group): comps = acl.split(':') vals = {} vals['type'] = 'acl' if (comps[0] == 'default'): vals['type'] = 'default' comps.pop(0) if ((comps[0] == 'user') and (not comps[1])): comps[1] = user elif ((comps[0] == 'group') and (not comps[1])): comps[1] = group vals[comps[0]] = comps[1] octal = 0 vals['permissions'] = {} if ('r' in comps[2]): octal += 4 vals['permissions']['read'] = True else: vals['permissions']['read'] = False if ('w' in comps[2]): octal += 2 vals['permissions']['write'] = True else: vals['permissions']['write'] = False if ('x' in comps[2]): octal += 1 vals['permissions']['execute'] = True else: vals['permissions']['execute'] = False vals['octal'] = octal return vals
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parse a single acl rule .
train
true
47,798
def make_datadog_service(options): app_key = os.environ['DATADOG_APP_KEY'] api_key = os.environ['DATADOG_API_KEY'] host = socket.getfqdn((options['host'] or '')) return DatadogMetricsService(api_key=api_key, app_key=app_key, host=host)
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create a datadog service instance for interacting with datadog .
train
false
47,799
def _get_added_exploration_change_list(exploration_id): return [{'cmd': collection_domain.CMD_ADD_COLLECTION_NODE, 'exploration_id': exploration_id}]
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generates a change list for adding an exploration to a collection .
train
false
47,800
def getMatrixTetragrid(prefix, xmlElement): matrixTetragrid = getMatrixTetragridC(None, prefix, xmlElement) matrixTetragrid = getMatrixTetragridM(matrixTetragrid, prefix, xmlElement) matrixTetragrid = getMatrixTetragridMatrix(matrixTetragrid, prefix, xmlElement) matrixTetragrid = getMatrixTetragridR(matrixTetragrid, prefix, xmlElement) return matrixTetragrid
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get the matrix tetragrid from the xmlelement .
train
false
47,801
def load_context(context): file_path = _get_context_filepath() if os.path.exists(file_path): with io.open(file_path, encoding='utf-8') as f: for line in f: execute(line, context)
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load a context object in place from user data directory .
train
true
47,802
def dup_rr_prs_gcd(f, g, K): result = _dup_rr_trivial_gcd(f, g, K) if (result is not None): return result (fc, F) = dup_primitive(f, K) (gc, G) = dup_primitive(g, K) c = K.gcd(fc, gc) h = dup_subresultants(F, G, K)[(-1)] (_, h) = dup_primitive(h, K) if K.is_negative(dup_LC(h, K)): c = (- c) h = dup_mul_ground(h, c, K) cff = dup_quo(f, h, K) cfg = dup_quo(g, h, K) return (h, cff, cfg)
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computes polynomial gcd using subresultants over a ring .
train
false
47,803
def openblas_threads_text(): header = '\n extern "C"\n {\n void openblas_set_num_threads(int);\n void goto_set_num_threads(int);\n int openblas_get_num_threads(void);\n }\n ' return header
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c header for openblas threads interface .
train
false
47,804
def make_hidden_alias(argument_table, existing_name, alias_name): current = argument_table[existing_name] copy_arg = _copy_argument(argument_table, existing_name, alias_name) copy_arg._UNDOCUMENTED = True if current.required: copy_arg.required = False current.required = False current._DOCUMENT_AS_REQUIRED = True
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create a hidden alias for an existing argument .
train
false
47,805
def detached(logfile=None, pidfile=None, uid=None, gid=None, umask=0, workdir=None, **opts): if (not resource): raise RuntimeError('This platform does not support detach.') workdir = (os.getcwd() if (workdir is None) else workdir) signals.reset('SIGCLD') set_effective_user(uid=uid, gid=gid) (logfile and open(logfile, 'a').close()) (pidfile and create_pidlock(pidfile)) return DaemonContext(umask=umask, workdir=workdir)
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detach the current process in the background .
train
false
47,806
def coerce_to_dtype(dtype, value): name = dtype.name if name.startswith('datetime64'): if (name == 'datetime64[D]'): return make_datetime64D(value) elif (name == 'datetime64[ns]'): return make_datetime64ns(value) else: raise TypeError(("Don't know how to coerce values of dtype %s" % dtype)) return dtype.type(value)
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make a value with the specified numpy dtype .
train
true
47,807
def filename_priority(filename, cover_names): return [idx for (idx, x) in enumerate(cover_names) if (x in filename)]
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sort order for image names .
train
false
47,808
def pcasvd(data, keepdim=0, demean=True): (nobs, nvars) = data.shape x = np.array(data) if demean: m = x.mean(0) else: m = 0 x -= m (U, s, v) = np.linalg.svd(x.T, full_matrices=1) factors = np.dot(U.T, x.T).T if keepdim: xreduced = (np.dot(factors[:, :keepdim], U[:, :keepdim].T) + m) else: xreduced = data keepdim = nvars ('print reassigning keepdim to max', keepdim) evals = ((s ** 2) / (x.shape[0] - 1)) return (xreduced, factors[:, :keepdim], evals[:keepdim], U[:, :keepdim])
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principal components with svd parameters data : ndarray .
train
false
47,811
def run_test_on_partitions(job, test, partitions, mountpoint_func, tag, fs_opt, do_fsck=True, **dargs): for p in partitions: p.set_fs_options(fs_opt) parallel(partitions, 'setup_before_test', mountpoint_func=mountpoint_func) mountpoint = mountpoint_func(partitions[0]) job.run_test(test, tag=tag, partitions=partitions, dir=mountpoint, **dargs) parallel(partitions, 'unmount') if do_fsck: parallel(partitions, 'fsck')
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run a test that requires multiple partitions .
train
false
47,813
def parseXML(xml): xmlObj = BeautifulSoup.BeautifulStoneSoup(xml, convertEntities=BeautifulSoup.BeautifulStoneSoup.XHTML_ENTITIES) if xmlObj: mainTag = xmlObj.find() if mainTag: return parseTags(mainTag) return None
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parse a xml string .
train
false
47,814
def test_blackbody_synphot(): fac = ((np.pi * ((const.R_sun / const.kpc) ** 2)) * u.sr) with np.errstate(all=u'ignore'): flux = (blackbody_nu(([100, 1, 1000, 10000.0, 100000.0] * u.AA), 5000) * fac) assert (flux.unit == FNU) assert (np.log10(flux[0].value) < (-143)) np.testing.assert_allclose(flux.value[1:], [0, 2.01950807e-34, 3.78584515e-26, 1.90431881e-27], rtol=0.01)
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test that it is consistent with iraf synphot bbfunc .
train
false
47,815
def _get_modules_conf(): if ('systemd' in __grains__): return '/etc/modules-load.d/salt_managed.conf' return '/etc/modules'
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return location of modules config file .
train
false
47,816
def _process_file(full_path, template_linters, options, summary_results, out): num_violations = 0 directory = os.path.dirname(full_path) file_name = os.path.basename(full_path) for template_linter in template_linters: results = template_linter.process_file(directory, file_name) results.print_results(options, summary_results, out)
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for each linter .
train
false
47,817
def pattern_convert(grammar, raw_node_info): (type, value, context, children) = raw_node_info if (children or (type in grammar.number2symbol)): return pytree.Node(type, children, context=context) else: return pytree.Leaf(type, value, context=context)
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converts raw node information to a node or leaf instance .
train
true
47,818
def getElementsByTagName(iNode, name): matches = [] matches_append = matches.append slice = [iNode] while (len(slice) > 0): c = slice.pop(0) if (c.nodeName == name): matches_append(c) slice[:0] = c.childNodes return matches
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return a list of all child elements of c{inode} with a name matching c{name} .
train
false
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def round_to_seconds(dt): rounding = 0 if (dt.microsecond >= 500000): rounding = 1 return (dt + datetime.timedelta(0, rounding, (- dt.microsecond)))
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round a datetime to the nearest second .
train
false
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def test_ascii_fancy(): o = nikola.utils.slugify(u'The quick brown fox jumps over the lazy dog!-123.456', lang=u'en') assert (o == u'the-quick-brown-fox-jumps-over-the-lazy-dog-123456') assert isinstance(o, nikola.utils.unicode_str)
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test an ascii string .
train
false
47,823
def _mkdir(newdir): if os.path.isdir(newdir): pass elif os.path.isfile(newdir): raise OSError(("a file with the same name as the desired dir, '%s', already exists." % newdir)) else: (head, tail) = os.path.split(newdir) if (head and (not os.path.isdir(head))): _mkdir(head) if tail: os.mkdir(newdir)
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works the way a good mkdir should :) - already exists .
train
true
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def need(): return s3_rest_controller()
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restful crud controller .
train
false
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def _removeOldBackRefs(senderkey, signal, receiver, receivers): try: index = receivers.index(receiver) except ValueError: return False else: oldReceiver = receivers[index] del receivers[index] found = 0 signals = connections.get(signal) if (signals is not None): for (sig, recs) in connections.get(signal, {}).iteritems(): if (sig != signal): for rec in recs: if (rec is oldReceiver): found = 1 break if (not found): _killBackref(oldReceiver, senderkey) return True return False
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kill old sendersback references from receiver this guards against multiple registration of the same receiver for a given signal and sender leaking memory as old back reference records build up .
train
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def draw(): get_current_fig_manager().canvas.draw()
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redraw the current figure .
train
false
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def _get_table_str(table): table_str = '' col_size = [max((len(str(val)) for val in column)) for column in zip(*table)] for line in table: table_str += '\n' table_str += ' '.join(('{0:<{1}}'.format(val, col_size[i]) for (i, val) in enumerate(line))) return table_str
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pretty print a table provided as a list of lists .
train
false
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def json_hook(obj): if ('$dt' in obj): x = obj['$dt'] return datetime.strptime(x, '%Y-%m-%dT%H:%M:%S.%f') return obj
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json object hook .
train
false
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def bi_zeros(nt): kf = 2 if ((not isscalar(nt)) or (floor(nt) != nt) or (nt <= 0)): raise ValueError('nt must be a positive integer scalar.') return specfun.airyzo(nt, kf)
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compute nt zeros and values of the airy function bi and its derivative .
train
false
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def l2norm(a): return np.sqrt(np.sum((np.abs(a) ** 2)))
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return the *l2* norm of *a* .
train
false
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@register.as_tag def signup_form(*args): return get_profile_form()()
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returns the signup form: {% signup_form as form %} {{ form }} .
train
false
47,840
def getSubDirectories(testdir): subdirs = [os.path.join(testdir, d) for d in filter(os.path.isdir, [os.path.join(testdir, dd) for dd in os.listdir(testdir)])] for d in copy(subdirs): subdirs.extend(getSubDirectories(os.path.join(testdir, d))) return subdirs
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recursively builds a list of all subdirectories in the test suite .
train
false
47,842
def pathlist2filename(pathlist): fullpath = '' for elem in pathlist: fullpath = os.path.join(fullpath, elem) try: return fullpath.decode('utf-8') except UnicodeDecodeError: charenc = chardet.detect(fullpath)['encoding'] return fullpath.decode(charenc)
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convert a multi-file torrent file path entry to a filename .
train
false
47,845
def test_power_schedule(backend_default): sch = PowerSchedule(step_config=2, change=0.5) target_lr = [1.0, 1.0, 0.5, 0.5, 0.25, 0.25, 0.125, 0.125] for (e, lr) in enumerate(target_lr): assert np.allclose(lr, sch.get_learning_rate(learning_rate=1.0, epoch=e))
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test the powerschedule class .
train
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@testing.requires_testing_data def test_morph_source_spaces(): src = read_source_spaces(fname_fs) src_morph = read_source_spaces(fname_morph) src_morph_py = morph_source_spaces(src, 'sample', subjects_dir=subjects_dir) _compare_source_spaces(src_morph, src_morph_py, mode='approx')
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test morphing of source spaces .
train
false
47,851
@world.absorb def css_has_text(css_selector, text, index=0, strip=False): if text: wait_for((lambda _: css_text(css_selector, index=index))) actual_text = css_text(css_selector, index=index) if strip: actual_text = actual_text.strip() text = text.strip() return (actual_text == text)
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return a boolean indicating whether the element with css_selector has text .
train
false
47,852
def _formatparam(param, value=None, quote=True): if ((value is not None) and (len(value) > 0)): if isinstance(value, tuple): param += '*' value = utils.encode_rfc2231(value[2], value[0], value[1]) if (quote or tspecials.search(value)): return ('%s="%s"' % (param, utils.quote(value))) else: return ('%s=%s' % (param, value)) else: return param
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convenience function to format and return a key=value pair .
train
true
47,853
def get_test_data(delta=0.05): from matplotlib.mlab import bivariate_normal x = y = np.arange((-3.0), 3.0, delta) (X, Y) = np.meshgrid(x, y) Z1 = bivariate_normal(X, Y, 1.0, 1.0, 0.0, 0.0) Z2 = bivariate_normal(X, Y, 1.5, 0.5, 1, 1) Z = (Z2 - Z1) X = (X * 10) Y = (Y * 10) Z = (Z * 500) return (X, Y, Z)
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return a tuple x .
train
false
47,854
def _breadcrumbs(location=None, first_caption='Planet Earth'): breadcrumbs = [(first_caption, reverse(locations))] if (location is not None): for loc in location.path: url = reverse(locations, args=(loc.uid,)) breadcrumbs.append((loc, url)) return breadcrumbs
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return the breadcrumb trail leading to location .
train
false
47,855
def _compress(compress): if (compress in ('bz2', 'bzip2', 'j')): compression = 'j' ext = 'bz2' elif (compress in ('gz', 'gzip', 'z')): compression = 'z' ext = 'gz' elif (compress in ('xz', 'a', 'J')): compression = 'J' ext = 'xz' return (compression, ext)
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resolve compression flags .
train
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@verbose def make_ad_hoc_cov(info, verbose=None): info = pick_info(info, pick_types(info, meg=True, eeg=True, exclude=[])) info._check_consistency() grad_std = 5e-13 mag_std = 2e-14 eeg_std = 2e-07 logger.info(('Using standard noise values (MEG grad : %6.1f fT/cm MEG mag : %6.1f fT EEG : %6.1f uV)' % ((10000000000000.0 * grad_std), (1000000000000000.0 * mag_std), (1000000.0 * eeg_std)))) data = np.zeros(len(info['ch_names'])) for (meg, eeg, val) in zip(('grad', 'mag', False), (False, False, True), (grad_std, mag_std, eeg_std)): data[pick_types(info, meg=meg, eeg=eeg)] = (val * val) return Covariance(data, info['ch_names'], info['bads'], info['projs'], nfree=0)
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create an ad hoc noise covariance .
train
false
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def cache_ns_key(namespace, increment=False): ns_key = ('ns:%s' % namespace) if increment: try: ns_val = cache.incr(ns_key) except ValueError: log.info(('Cache increment failed for key: %s. Resetting.' % ns_key)) ns_val = epoch(datetime.datetime.now()) cache.set(ns_key, ns_val, None) else: ns_val = cache.get(ns_key) if (ns_val is None): ns_val = epoch(datetime.datetime.now()) cache.set(ns_key, ns_val, None) return ('%s:%s' % (ns_val, ns_key))
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returns a key with namespace value appended .
train
false
47,860
def rmsle(actual, predicted): return np.sqrt(msle(actual, predicted))
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computes the root mean squared log error .
train
false
47,861
def wrap_exceptions(fun): def wrapper(self, *args, **kwargs): try: return fun(self, *args, **kwargs) except EnvironmentError as err: if (self.pid == 0): if (0 in pids()): raise AccessDenied(self.pid, self._name) else: raise if (err.errno in (errno.ENOENT, errno.ESRCH)): if (not pid_exists(self.pid)): raise NoSuchProcess(self.pid, self._name) else: raise ZombieProcess(self.pid, self._name, self._ppid) if (err.errno in (errno.EPERM, errno.EACCES)): raise AccessDenied(self.pid, self._name) raise return wrapper
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call callable into a try/except clause and translate enoent .
train
false
47,862
def register_optimizer(name, opt): if (name in predefined_optimizers): raise ValueError(('Optimizer name already taken: %s' % name)) predefined_optimizers[name] = opt
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add a optimizer which can be referred to by name in mode .
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def njit(*args, **kws): if ('nopython' in kws): warnings.warn('nopython is set for njit and is ignored', RuntimeWarning) if ('forceobj' in kws): warnings.warn('forceobj is set for njit and is ignored', RuntimeWarning) kws.update({'nopython': True}) return jit(*args, **kws)
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equivalent to jit see documentation for jit function/decorator for full description .
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def output_xml(data, code, headers=None): resp = make_response(dumps({'response': data}), code) resp.headers.extend((headers or {})) return resp
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makes a flask response with a xml encoded body .
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def getAbsoluteFolderPath(filePath, folderName=''): absoluteFolderPath = os.path.dirname(os.path.abspath(filePath)) if (folderName == ''): return absoluteFolderPath return os.path.join(absoluteFolderPath, folderName)
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get the absolute folder path .
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def values(): data = salt.config.master_config(__opts__['conf_file']) return data
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returns a dictionary of field names to statistical values for a particular category id defined in idmap .
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def isNumPosStrValue(value): return ((value and isinstance(value, basestring) and value.isdigit() and (int(value) > 0)) or (isinstance(value, int) and (value > 0)))
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returns true if value is a string with a positive integer representation .
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def file_descriptors_used(pid): try: pid = int(pid) if (pid < 0): raise IOError(("Process pids can't be negative: %s" % pid)) except (ValueError, TypeError): raise IOError(('Process pid was non-numeric: %s' % pid)) try: return len(os.listdir(('/proc/%i/fd' % pid))) except Exception as exc: raise IOError(('Unable to check number of file descriptors used: %s' % exc))
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provides the number of file descriptors currently being used by a process .
train
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def locale_details(request, locale_code, leader_form=None, reviewer_form=None, editor_form=None): locale = get_object_or_404(Locale, locale=locale_code) leaders = locale.leaders.all().select_related('profile') reviewers = locale.reviewers.all().select_related('profile') editors = locale.editors.all().select_related('profile') active = active_contributors(from_date=(date.today() - timedelta(days=90)), locale=locale_code) user_can_edit = _user_can_edit(request.user, locale) return render(request, 'wiki/locale_details.html', {'locale': locale, 'leaders': leaders, 'reviewers': reviewers, 'editors': editors, 'active': active, 'user_can_edit': user_can_edit, 'leader_form': (leader_form or AddUserForm()), 'reviewer_form': (reviewer_form or AddUserForm()), 'editor_form': (editor_form or AddUserForm())})
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show the locale details page .
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def save_signal(sender, instance, **kw): if (not kw.get('raw')): save_translations(make_key(instance))
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use this signal on a model to iterate through all the translations added to the hold queue and save them all .
train
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def ensure_workdir_exists(context): ensure_context_attribute_exists(context, 'workdir', None) if (not context.workdir): context.workdir = os.path.abspath(WORKDIR) pathutil.ensure_directory_exists(context.workdir)
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ensures that the work directory exists .
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def vrrp_config_change(app, instance_name, priority=None, advertisement_interval=None, preempt_mode=None, accept_mode=None): config_change = vrrp_event.EventVRRPConfigChangeRequest(instance_name, priority, advertisement_interval, preempt_mode, accept_mode) return app.send_event(vrrp_event.VRRP_MANAGER_NAME, config_change)
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change configuration of an instance .
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def pnio_update_config(config): conf.contribs['PNIO_RTC'].update(config)
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update the pnio rtc config .
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@contextlib.contextmanager def unset_organization(): qapp = QApplication.instance() orgname = qapp.organizationName() qapp.setOrganizationName(None) try: (yield) finally: qapp.setOrganizationName(orgname)
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temporarily unset qapplication .
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def getLoopsWithCorners(corners, importRadius, loops, pointTable): for corner in corners: if (corner not in pointTable): addWithLeastLength(importRadius, loops, corner) pointTable[corner] = None return euclidean.getSimplifiedLoops(loops, importRadius)
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add corners to the loops .
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def _all_tags(repo): return [x for x in repo.tags() if (x[0] != 'tip')]
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returns all tags for the specified repo .
train
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def debug_unittest(testclass): run_unittest(testclass, debug=1)
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debug tests from a unittest .
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def fixed_ip_get_by_network_host(context, network_uuid, host): return IMPL.fixed_ip_get_by_network_host(context, network_uuid, host)
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get fixed ip for a host in a network .
train
false
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def build_article(url='', config=None, **kwargs): config = (config or Configuration()) config = extend_config(config, kwargs) url = (url or '') a = Article(url, config=config) return a
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returns a constructed article object without downloading or parsing .
train
false
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def S_hac_simple(x, nlags=None, weights_func=weights_bartlett): if (x.ndim == 1): x = x[:, None] n_periods = x.shape[0] if (nlags is None): nlags = int(np.floor((4 * ((n_periods / 100.0) ** (2.0 / 9.0))))) weights = weights_func(nlags) S = (weights[0] * np.dot(x.T, x)) for lag in range(1, (nlags + 1)): s = np.dot(x[lag:].T, x[:(- lag)]) S += (weights[lag] * (s + s.T)) return S
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inner covariance matrix for hac sandwich assumes we have a single time series with zero axis consecutive .
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def check_program(prog): tmp = init_app('which {0}'.format(prog)) if ((len(tmp) > 0) and ('/' in tmp)): return True else: return False
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check if program is installed and pathed properly .
train
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def pop_bilateral(image, selem, out=None, mask=None, shift_x=False, shift_y=False, s0=10, s1=10): return _apply(bilateral_cy._pop, image, selem, out=out, mask=mask, shift_x=shift_x, shift_y=shift_y, s0=s0, s1=s1)
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return the local number of pixels .
train
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def _get_data(): raw = read_raw_fif(raw_fname).crop(0.0, 5.0).load_data() data_picks = pick_types(raw.info, meg=True, eeg=True) other_picks = pick_types(raw.info, meg=False, stim=True, eog=True) picks = np.sort(np.concatenate((data_picks[::16], other_picks))) raw = raw.pick_channels([raw.ch_names[p] for p in picks]) raw.info.normalize_proj() ecg = RawArray(np.zeros((1, len(raw.times))), create_info(['ECG 063'], raw.info['sfreq'], 'ecg')) for key in ('dev_head_t', 'buffer_size_sec', 'highpass', 'lowpass', 'dig'): ecg.info[key] = raw.info[key] raw.add_channels([ecg]) src = read_source_spaces(src_fname) trans = read_trans(trans_fname) sphere = make_sphere_model('auto', 'auto', raw.info) stc = _make_stc(raw, src) return (raw, src, stc, trans, sphere)
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helper to get the data array .
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def _var_acf(coefs, sig_u): (p, k, k2) = coefs.shape assert (k == k2) A = util.comp_matrix(coefs) SigU = np.zeros(((k * p), (k * p))) SigU[:k, :k] = sig_u vecACF = L.solve((np.eye(((k * p) ** 2)) - np.kron(A, A)), vec(SigU)) acf = unvec(vecACF) acf = acf[:k].T.reshape((p, k, k)) return acf
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compute autocovariance function acf_y(h) for h=1 .
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def parse_multistring(db_string): if (not isinstance(db_string, basestring)): raise ValueError('Parsing into a multistring requires a string input.') strings = db_string.split(SEPARATOR) if (strings[(-1)] == PLURAL_PLACEHOLDER): strings = strings[:(-1)] plural = True else: plural = (len(strings) > 1) ms = multistring(strings, encoding='UTF-8') ms.plural = plural return ms
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parses a db_string coming from the db into a multistring object .
train
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def start_new_background_thread(target, args, kwargs=None): if (kwargs is None): kwargs = {} request = system_service_pb.StartBackgroundRequestRequest() response = system_service_pb.StartBackgroundRequestResponse() try: apiproxy_stub_map.MakeSyncCall('system', 'StartBackgroundRequest', request, response) except apiproxy_errors.ApplicationError as error: raise ERROR_MAP[error.application_error](error.error_detail) else: return background.EnqueueBackgroundThread(response.request_id(), target, args, kwargs)
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starts a new background thread .
train
false
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def dictitems(d): return list(d.items())
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a pickleable version of dict .
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def translations_for_field(field): if (field is None): return {} translation_id = getattr(field, 'id') qs = Translation.objects.filter(id=translation_id, localized_string__isnull=False) translations = dict(qs.values_list('locale', 'localized_string')) return translations
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return all the translations for a given field .
train
false
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def device_memory_depends(devmem, *objs): depset = getattr(devmem, '_depends_', []) depset.extend(objs)
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add dependencies to the device memory .
train
false
47,901
def associate_qos_with_type(context, specs_id, type_id): try: get_qos_specs(context, specs_id) res = volume_types.get_volume_type_qos_specs(type_id) if res.get('qos_specs', None): if (res['qos_specs'].get('id') != specs_id): msg = (_('Type %(type_id)s is already associated with another qos specs: %(qos_specs_id)s') % {'type_id': type_id, 'qos_specs_id': res['qos_specs']['id']}) raise exception.InvalidVolumeType(reason=msg) else: db.qos_specs_associate(context, specs_id, type_id) except db_exc.DBError: LOG.exception(_LE('DB error:')) LOG.warning(_LW('Failed to associate qos specs %(id)s with type: %(vol_type_id)s'), dict(id=specs_id, vol_type_id=type_id)) raise exception.QoSSpecsAssociateFailed(specs_id=specs_id, type_id=type_id)
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associate qos_specs with volume type .
train
false
47,902
@commands(u'endmeeting') @example(u'.endmeeting') def endmeeting(bot, trigger): if (not ismeetingrunning(trigger.sender)): bot.say(u"Can't do that, start meeting first") return if (not ischair(trigger.nick, trigger.sender)): bot.say(u'Only meeting head or chairs can do that') return meeting_length = (time.time() - meetings_dict[trigger.sender][u'start']) bot.say((u'\x02Meeting ended!\x0f total meeting length %d seconds' % meeting_length)) logHTML_end(trigger.sender) htmllog_url = (meeting_log_baseurl + quote((((trigger.sender + u'/') + figure_logfile_name(trigger.sender)) + u'.html'))) logplain((u'Meeting ended by %s, total meeting length %d seconds' % (trigger.nick, meeting_length)), trigger.sender) bot.say((u'Meeting minutes: ' + htmllog_url)) meetings_dict[trigger.sender] = Ddict(dict) del meeting_actions[trigger.sender]
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end a meeting .
train
false
47,904
def transpose_axes(data, axes, asaxes='CTZYX'): for ax in axes: if (ax not in asaxes): raise ValueError(('unknown axis %s' % ax)) shape = data.shape for ax in reversed(asaxes): if (ax not in axes): axes = (ax + axes) shape = ((1,) + shape) data = data.reshape(shape) data = data.transpose([axes.index(ax) for ax in asaxes]) return data
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return data with its axes permuted to match specified axes .
train
false