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def check_ddir(d): expanded = os.path.expanduser(d) if os.path.isdir(expanded): message = ((('Downloads will be saved to ' + c.y) + d) + c.w) return dict(valid=True, message=message, value=expanded) else: message = ((('Not a valid directory: ' + c.r) + d) + c.w) return dict(valid=False, message=message)
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check whether dir is a valid directory .
train
false
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def johnson_lindenstrauss_min_dim(n_samples, eps=0.1): eps = np.asarray(eps) n_samples = np.asarray(n_samples) if (np.any((eps <= 0.0)) or np.any((eps >= 1))): raise ValueError(('The JL bound is defined for eps in ]0, 1[, got %r' % eps)) if (np.any(n_samples) <= 0): raise ValueError(('The JL bound is defined for n_samples greater than zero, got %r' % n_samples)) denominator = (((eps ** 2) / 2) - ((eps ** 3) / 3)) return ((4 * np.log(n_samples)) / denominator).astype(np.int)
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find a safe number of components to randomly project to the distortion introduced by a random projection p only changes the distance between two points by a factor in an euclidean space with good probability .
train
false
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def sum_percentile(image, selem, out=None, mask=None, shift_x=False, shift_y=False, p0=0, p1=1): return _apply(percentile_cy._sum, image, selem, out=out, mask=mask, shift_x=shift_x, shift_y=shift_y, p0=p0, p1=p1)
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return the local sum of pixels .
train
false
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def get_ccx_by_ccx_id(course, coach, ccx_id): try: ccx = CustomCourseForEdX.objects.get(id=ccx_id, course_id=course.id, coach=coach) except CustomCourseForEdX.DoesNotExist: return None return ccx
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finds a ccx of given coach on given master course .
train
false
43,084
@require_POST @login_required def unwatch_locale(request, product=None): kwargs = {'locale': request.LANGUAGE_CODE} if (product is not None): kwargs['product'] = product ReviewableRevisionInLocaleEvent.stop_notifying(request.user, **kwargs) return HttpResponse()
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stop watching a locale for revisions ready for review .
train
false
43,085
def binom_test_reject_interval(value, nobs, alpha=0.05, alternative='two-sided'): if (alternative in ['2s', 'two-sided']): alternative = '2s' alpha = (alpha / 2) if (alternative in ['2s', 'smaller']): x_low = (stats.binom.ppf(alpha, nobs, value) - 1) else: x_low = 0 if (alternative in ['2s', 'larger']): x_upp = (stats.binom.isf(alpha, nobs, value) + 1) else: x_upp = nobs return (x_low, x_upp)
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rejection region for binomial test for one sample proportion the interval includes the end points of the rejection region .
train
false
43,086
@register.inclusion_tag('inclusion.html') def inclusion_one_param(arg): return {'result': ('inclusion_one_param - Expected result: %s' % arg)}
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expected inclusion_one_param __doc__ .
train
false
43,090
def fadein(clip, duration, initial_color=None): if (initial_color is None): initial_color = (0 if clip.ismask else [0, 0, 0]) initial_color = np.array(initial_color) def fl(gf, t): if (t >= duration): return gf(t) else: fading = ((1.0 * t) / duration) return ((fading * gf(t)) + ((1 - fading) * initial_color)) return clip.fl(fl)
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makes the clip progressively appear from some color .
train
false
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def is_finite(builder, val): val_minus_val = builder.fsub(val, val) return builder.fcmp_ordered('ord', val_minus_val, val_minus_val)
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return a condition testing whether *val* is a finite .
train
false
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def _unit_quat_constraint(x): return (1 - (x * x).sum())
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constrain our 3 quaternion rot params to have norm <= 1 .
train
false
43,093
def get_num_jobs(not_yet_run=False, running=False, finished=False, **filter_data): filter_data['extra_args'] = rpc_utils.extra_job_filters(not_yet_run, running, finished) return models.Job.query_count(filter_data)
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see get_jobs() for documentation of extra filter parameters .
train
false
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def bench_R11(): a = [(random() + (random() * I)) for w in range(1000)]
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a = [random() + random()*i for w in [0 .
train
false
43,095
def _norm(x): return np.sqrt(squared_norm(x))
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return sqrt .
train
false
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def __get_ssh_interface(vm_): return config.get_cloud_config_value('ssh_interface', vm_, __opts__, default='public_ips', search_global=False)
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return the ssh_interface type to connect to .
train
false
43,099
def test_function_execution(): s = '\n def x():\n return str()\n x' (func, evaluator) = get_definition_and_evaluator(s) assert (len(evaluator.execute(func)) == 1) assert (len(evaluator.execute(func)) == 1)
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weve been having an issue of a mutable list that was changed inside the function execution .
train
false
43,100
def _get_connect_string(backend, user='openstack_citest', passwd='openstack_citest', database='openstack_citest'): if (backend == 'mysql'): backend = 'mysql+mysqldb' elif (backend == 'postgres'): backend = 'postgresql+psycopg2' return ('%(backend)s://%(user)s:%(passwd)s@localhost/%(database)s' % locals())
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try to get a connection with a very specific set of values .
train
false
43,101
@pytest.mark.cmd @pytest.mark.django_db def test_export_language(capfd, export_dir, cd_export_dir): call_command('export', '--language=language0') (out, err) = capfd.readouterr() assert ('language0.zip' in out) assert ('language1.zip' not in out)
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export a language .
train
false
43,102
def thrift_library(name, srcs=[], deps=[], optimize=[], deprecated=False, **kwargs): thrift_library_target = ThriftLibrary(name, srcs, deps, optimize, deprecated, blade.blade, kwargs) blade.blade.register_target(thrift_library_target)
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thrift_library target .
train
false
43,103
def validate_is_instance(instance, classes): if (not isinstance(classes, tuple)): classes = (classes,) correct_instance = isinstance(instance, classes) if (not correct_instance): raise ValueError(('Expected instance type %s found %s' % (classes, type(instance))))
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usage validate_is_instance validate_is_instance(a .
train
false
43,104
def persist_clipboard(): clipboard = QtWidgets.QApplication.clipboard() event = QtCore.QEvent(QtCore.QEvent.Clipboard) QtWidgets.QApplication.sendEvent(clipboard, event)
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persist the clipboard x11 stores only a reference to the clipboard data .
train
false
43,106
def _SinglePropertyIndex(prop_name, direction): index = entity_pb.Index() prop = index.add_property() prop.set_name(prop_name) prop.set_direction(direction) return index
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creates a single property index for the given name and direction .
train
false
43,108
def ipStr(ip): w = ((ip >> 24) & 255) x = ((ip >> 16) & 255) y = ((ip >> 8) & 255) z = (ip & 255) return ('%i.%i.%i.%i' % (w, x, y, z))
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generate ip address string from an unsigned int .
train
false
43,109
def getOverhangSpan(elementNode): return getCascadeFloatWithoutSelf((2.0 * getLayerHeight(elementNode)), elementNode, 'overhangSpan')
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get the overhang span .
train
false
43,110
def col_delete(cols_selected): if (len(cols_selected) < 1): flash('No collections selected to delete!', 'error') else: for source_id in cols_selected: delete_collection(source_id) flash(('%s %s deleted' % (len(cols_selected), ('collection' if (len(cols_selected) == 1) else 'collections'))), 'notification') return redirect(url_for('index'))
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deleting multiple collections from the index .
train
false
43,111
def partition_by_cut(cut, rag): nodes1 = [n for (i, n) in enumerate(rag.nodes()) if cut[i]] nodes2 = [n for (i, n) in enumerate(rag.nodes()) if (not cut[i])] sub1 = rag.subgraph(nodes1) sub2 = rag.subgraph(nodes2) return (sub1, sub2)
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compute resulting subgraphs from given bi-parition .
train
false
43,113
def is_running(proxyname): return {'result': _is_proxy_running(proxyname)}
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checks for if a process with a given name is running or not .
train
false
43,115
def get_length_audio(audiopath, extension): try: audio = AudioSegment.from_file(audiopath, extension.replace('.', '')) except: print ('Error in get_length_audio(): %s' % traceback.format_exc()) return None return int((len(audio) / 1000.0))
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returns length of audio in seconds .
train
false
43,116
def update_many(path, points): if (not points): return points = [(int(t), float(v)) for (t, v) in points] points.sort(key=(lambda p: p[0]), reverse=True) with open(path, 'r+b', BUFFERING) as fh: if (CAN_FADVISE and FADVISE_RANDOM): posix_fadvise(fh.fileno(), 0, 0, POSIX_FADV_RANDOM) return file_update_many(fh, points)
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update_many path is a string points is a list of points .
train
false
43,118
def decode_base64_and_inflate(string): return zlib.decompress(base64.b64decode(string), (-15))
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base64 decodes and then inflates according to rfc1951 .
train
false
43,120
def write_gif_with_image_io(clip, filename, fps=None, opt='wu', loop=0, colors=None, verbose=True): if (colors is None): colors = 256 if (not IMAGEIO_FOUND): raise ImportError("Writing a gif with imageio requires ImageIO installed, with e.g. 'pip install imageio'") if (fps is None): fps = clip.fps quantizer = ('wu' if (opt != 'nq') else 'nq') writer = imageio.save(filename, duration=(1.0 / fps), quantizer=quantizer, palettesize=colors) verbose_print(verbose, ('\n[MoviePy] Building file %s with imageio\n' % filename)) for frame in clip.iter_frames(fps=fps, progress_bar=True, dtype='uint8'): writer.append_data(frame)
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writes the gif with the python library imageio .
train
false
43,121
def betweenness_centrality_parallel(G, processes=None): p = Pool(processes=processes) node_divisor = (len(p._pool) * 4) node_chunks = list(chunks(G.nodes(), int((G.order() / node_divisor)))) num_chunks = len(node_chunks) bt_sc = p.map(_betmap, zip(([G] * num_chunks), ([True] * num_chunks), ([None] * num_chunks), node_chunks)) bt_c = bt_sc[0] for bt in bt_sc[1:]: for n in bt: bt_c[n] += bt[n] return bt_c
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parallel betweenness centrality function .
train
false
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def test_world_should_be_able_to_absorb_classs(): assert (not hasattr(world, 'MyClass')) if (sys.version_info < (2, 6)): return class MyClass: pass world.absorb(MyClass) assert hasattr(world, 'MyClass') assert_equals(world.MyClass, MyClass) assert isinstance(world.MyClass(), MyClass) world.spew('MyClass') assert (not hasattr(world, 'MyClass'))
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world should be able to absorb class .
train
false
43,123
def export_patchset(start, end, output=u'patches', **kwargs): return git.format_patch(u'-o', output, ((start + u'^..') + end), **kwargs)
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export patches from start^ to end .
train
false
43,124
@contextlib.contextmanager def try_target_cell(context, cell): if cell: with nova_context.target_cell(context, cell) as cell_context: (yield cell_context) else: (yield context)
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if cell is not none call func with context .
train
false
43,125
def _future_completed(future): exc = future.exception() if exc: log.debug('Failed to run task on executor', exc_info=exc)
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helper for run_in_executor() .
train
true
43,126
def connect_to_zookeeper(hostlist, credentials): client = KazooClient(hostlist, timeout=5, max_retries=3, auth_data=[('digest', ':'.join(credentials))]) client.make_acl = functools.partial(make_digest_acl, *credentials) client.start() return client
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create a connection to the zookeeper ensemble .
train
false
43,127
def assert_cloudtrail_arn_is_valid(trail_arn): pattern = re.compile('arn:.+:cloudtrail:.+:\\d{12}:trail/.+') if (not pattern.match(trail_arn)): raise ValueError(('Invalid trail ARN provided: %s' % trail_arn))
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ensures that the arn looks correct .
train
false
43,128
def polar_to_cartesian(r, start_angles, end_angles): cartesian = (lambda r, alpha: ((r * cos(alpha)), (r * sin(alpha)))) points = [] for (r, start, end) in zip(r, start_angles, end_angles): points.append(cartesian(r, ((end + start) / 2))) return zip(*points)
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translate polar coordinates to cartesian .
train
true
43,129
def print_items(items): for item in items: print_item(item)
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train
false
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def crc(data): return crc_finalize(crc_update(CRC_INIT, data))
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compute crc-32c checksum of the data .
train
false
43,135
def safe_sparse_dot(a, b, dense_output=False): if (issparse(a) or issparse(b)): ret = (a * b) if (dense_output and hasattr(ret, 'toarray')): ret = ret.toarray() return ret else: return fast_dot(a, b)
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dot product that handle the sparse matrix case correctly uses blas gemm as replacement for numpy .
train
false
43,136
def volume_get_all_by_instance_uuid(context, instance_uuid): return IMPL.volume_get_all_by_instance_uuid(context, instance_uuid)
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get all volumes belonging to a instance .
train
false
43,137
def _stateMeetsRule(state, rule): if rule.HasField('phase'): if (rule.phase != state.phase): return False if rule.HasField('min_level'): if (state.level < rule.min_level): return False if rule.HasField('max_level'): if (state.level > rule.max_level): return False for stage in rule.stage: if (stage not in state.stage): return False for stage in rule.not_stage: if (stage in state.stage): return False return True
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returns true if the given state meets the given rule logic copied from caffes net::statemeetsrule() .
train
false
43,138
def make_gax_sinks_api(client): channel = make_secure_channel(client._connection.credentials, DEFAULT_USER_AGENT, ConfigServiceV2Client.SERVICE_ADDRESS) generated = ConfigServiceV2Client(channel=channel) return _SinksAPI(generated, client)
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create an instance of the gax sinks api .
train
false
43,139
def _log_compute_error(instance_uuid, retry): exc = retry.get('exc') if (not exc): return hosts = retry.get('hosts', None) if (not hosts): return (last_host, last_node) = hosts[(-1)] LOG.error(_LE('Error from last host: %(last_host)s (node %(last_node)s): %(exc)s'), {'last_host': last_host, 'last_node': last_node, 'exc': exc}, instance_uuid=instance_uuid)
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if the request contained an exception from a previous compute build/resize operation .
train
false
43,140
def get_documented_in_docstring(name, module=None, filename=None): try: (obj, real_name) = import_by_name(name) lines = pydoc.getdoc(obj).splitlines() return get_documented_in_lines(lines, module=name, filename=filename) except AttributeError: pass except ImportError as e: print((u"Failed to import '%s': %s" % (name, e))) return {}
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find out what items are documented in the given objects docstring .
train
false
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def requires_confirmation(user): return (_security.confirmable and (not _security.login_without_confirmation) and (user.confirmed_at is None))
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returns true if the user requires confirmation .
train
false
43,143
def set_host_attribute(attribute, value, **host_filter_data): assert host_filter_data hosts = models.Host.query_objects(host_filter_data) models.AclGroup.check_for_acl_violation_hosts(hosts) for host in hosts: host.set_or_delete_attribute(attribute, value)
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set host attribute .
train
false
43,144
def write_conf(conf_file, conf): if (not isinstance(conf, list)): raise SaltInvocationError('Configuration must be passed as a list') content = '' for line in conf: if isinstance(line, (six.text_type, six.string_types)): content += line elif isinstance(line, dict): for key in list(line.keys()): out_line = None if isinstance(line[key], (six.text_type, six.string_types, six.integer_types, float)): out_line = ' = '.join((key, '{0}'.format(line[key]))) elif isinstance(line[key], dict): out_line = ' = '.join((key, line[key]['value'])) if ('comment' in line[key]): out_line = ' # '.join((out_line, line[key]['comment'])) if out_line: content += out_line content += '\n' with salt.utils.fopen(conf_file, 'w') as fp_: fp_.write(content) return {}
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write out an lxc configuration file this is normally only used internally .
train
true
43,146
def _thread_done(gt, *args, **kwargs): kwargs['group'].thread_done(kwargs['thread'])
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callback function to be passed to greenthread .
train
false
43,147
def _get_user_project_membership(user, project, cache='user'): if user.is_anonymous(): return None if (cache == 'user'): return user.cached_membership_for_project(project) return project.cached_memberships_for_user(user)
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cache param determines how memberships are calculated trying to reuse the existing data in cache .
train
false
43,148
def _syscmd_uname(option, default=''): if (sys.platform in ('dos', 'win32', 'win16')): return default try: f = os.popen(('uname %s 2> %s' % (option, DEV_NULL))) except (AttributeError, OSError): return default output = f.read().strip() rc = f.close() if ((not output) or rc): return default else: return output
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interface to the systems uname command .
train
false
43,149
def _update_ssl_config(opts): if (opts['ssl'] is None): return import ssl for (key, prefix) in (('cert_reqs', 'CERT_'), ('ssl_version', 'PROTOCOL_')): val = opts['ssl'].get(key) if (val is None): continue if ((not isinstance(val, string_types)) or (not val.startswith(prefix)) or (not hasattr(ssl, val))): message = "SSL option '{0}' must be set to one of the following values: '{1}'.".format(key, "', '".join([val for val in dir(ssl) if val.startswith(prefix)])) log.error(message) raise salt.exceptions.SaltConfigurationError(message) opts['ssl'][key] = getattr(ssl, val)
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resolves string names to integer constant in ssl configuration .
train
true
43,150
def random_degree_sequence_graph(sequence, seed=None, tries=10): DSRG = DegreeSequenceRandomGraph(sequence, seed=seed) for try_n in range(tries): try: return DSRG.generate() except nx.NetworkXUnfeasible: pass raise nx.NetworkXError(('failed to generate graph in %d tries' % tries))
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return a simple random graph with the given degree sequence .
train
false
43,151
def assert_naming(warns, fname, n_warn): from nose.tools import assert_true assert_true((sum((('naming conventions' in str(ww.message)) for ww in warns)) == n_warn)) for ww in warns: if ('naming conventions' in str(ww.message)): assert_true((fname in ww.filename), msg=('"%s" not in "%s"' % (fname, ww.filename)))
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assert a non-standard naming scheme was used while saving or loading parameters warns : list list of warnings from warnings .
train
false
43,152
def dlls_in_subdirs(directory): filelist = [] for (root, dirs, files) in os.walk(directory): filelist.extend(dlls_in_dir(root)) return filelist
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returns a list * .
train
false
43,153
def test_skip_dt_decorator(): check = 'A function whose doctest we need to skip.\n\n >>> 1+1\n 3\n ' val = doctest_bad.__doc__ nt.assert_equal(check, val, "doctest_bad docstrings don't match")
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doctest-skipping decorator should preserve the docstring .
train
false
43,154
def getThicknessMultipliedPath(path, thicknessMultiplier): for (pointIndex, point) in enumerate(path): path[pointIndex] = complex((point.real * thicknessMultiplier), point.imag) return path
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get thickness multiplied path .
train
false
43,155
def filterPairValues(values): retVal = [] if ((not isNoneValue(values)) and hasattr(values, '__iter__')): retVal = filter((lambda x: (isinstance(x, (tuple, list, set)) and (len(x) == 2))), values) return retVal
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returns only list-like values with length 2 .
train
false
43,156
def addToMenu(master, menu, repository, window): metaFilePath = archive.getSkeinforgePluginsPath('meta.py') settings.addPluginsParentToMenu(skeinforge_meta.getPluginsDirectoryPath(), menu, metaFilePath, skeinforge_meta.getPluginFileNames())
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add a tool plugin menu .
train
false
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def latestClass(oldClass): module = reflect.namedModule(oldClass.__module__) newClass = getattr(module, oldClass.__name__) newBases = [latestClass(base) for base in newClass.__bases__] try: newClass.__bases__ = tuple(newBases) return newClass except TypeError: if (newClass.__module__ == '__builtin__'): return newClass ctor = getattr(newClass, '__metaclass__', type) return ctor(newClass.__name__, tuple(newBases), dict(newClass.__dict__))
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get the latest version of a class .
train
false
43,162
def find_common_elements(source_preferences, target_preferences): src = dict(source_preferences) tgt = dict(target_preferences) inter = np.intersect1d(src.keys(), tgt.keys()) common_preferences = zip(*[(src[item], tgt[item]) for item in inter if ((not np.isnan(src[item])) and (not np.isnan(tgt[item])))]) if common_preferences: return (np.asarray([common_preferences[0]]), np.asarray([common_preferences[1]])) else: return (np.asarray([[]]), np.asarray([[]]))
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returns the preferences from both vectors .
train
false
43,163
def test_slug(): schema = vol.Schema(cv.slug) for value in (None, 'hello world'): with pytest.raises(vol.MultipleInvalid): schema(value) for value in (12345, 'hello'): schema(value)
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test slug validation .
train
false
43,164
def get_qualified_path(name): import sys import os path = sys.path try: path = ([os.path.dirname(__file__)] + path) except NameError: pass for dir in path: fullname = os.path.join(dir, name) if os.path.exists(fullname): return fullname return name
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return a more qualified path to name .
train
false
43,165
def _quotes_historical_yahoo(ticker, date1, date2, asobject=False, adjusted=True, cachename=None, ochl=True): fh = fetch_historical_yahoo(ticker, date1, date2, cachename) try: ret = _parse_yahoo_historical(fh, asobject=asobject, adjusted=adjusted, ochl=ochl) if (len(ret) == 0): return None except IOError as exc: warnings.warn((u'fh failure\n%s' % exc.strerror[1])) return None return ret
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get historical data for ticker between date1 and date2 .
train
false
43,166
def get_marker_style(line): style = {} style['alpha'] = line.get_alpha() if (style['alpha'] is None): style['alpha'] = 1 style['facecolor'] = color_to_hex(line.get_markerfacecolor()) style['edgecolor'] = color_to_hex(line.get_markeredgecolor()) style['edgewidth'] = line.get_markeredgewidth() style['marker'] = line.get_marker() markerstyle = MarkerStyle(line.get_marker()) markersize = line.get_markersize() markertransform = (markerstyle.get_transform() + Affine2D().scale(markersize, (- markersize))) style['markerpath'] = SVG_path(markerstyle.get_path(), markertransform) style['markersize'] = markersize style['zorder'] = line.get_zorder() return style
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get the style dictionary for matplotlib marker objects .
train
true
43,168
def _reloader_child(server, app, interval): lockfile = os.environ.get('BOTTLE_LOCKFILE') bgcheck = FileCheckerThread(lockfile, interval) try: bgcheck.start() server.run(app) except KeyboardInterrupt: pass (bgcheck.status, status) = (5, bgcheck.status) bgcheck.join() if status: sys.exit(status)
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start the server and check for modified files in a background thread .
train
true
43,169
def IsPythonFile(filename): if (os.path.splitext(filename)[1] == '.py'): return True try: with open(filename, 'rb') as fd: encoding = tokenize.detect_encoding(fd.readline)[0] with py3compat.open_with_encoding(filename, mode='r', encoding=encoding) as fd: fd.read() except UnicodeDecodeError: encoding = 'latin-1' except (IOError, SyntaxError): return False try: with py3compat.open_with_encoding(filename, mode='r', encoding=encoding) as fd: first_line = fd.readlines()[0] except (IOError, IndexError): return False return re.match('^#!.*\\bpython[23]?\\b', first_line)
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return true if filename is a python file .
train
false
43,170
@raises(TypeError) def test_extra_kwarg(): w = wcs.WCS() with NumpyRNGContext(123456789): data = np.random.rand(100, 2) w.wcs_pix2world(data, origin=1)
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issue #444 .
train
false
43,172
@decorators.which('arp') def arp(): ret = {} out = __salt__['cmd.run']('arp -an') for line in out.splitlines(): comps = line.split() if (len(comps) < 4): continue if (__grains__['kernel'] == 'SunOS'): if (':' not in comps[(-1)]): continue ret[comps[(-1)]] = comps[1] elif (__grains__['kernel'] == 'OpenBSD'): if ((comps[0] == 'Host') or (comps[1] == '(incomplete)')): continue ret[comps[1]] = comps[0] else: ret[comps[3]] = comps[1].strip('(').strip(')') return ret
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return the arp table from the minion .
train
true
43,174
def test_hdf5_load_all(): skip_if_no_h5py() import h5py (handle, filename) = tempfile.mkstemp() dataset = random_one_hot_dense_design_matrix(np.random.RandomState(1), num_examples=10, dim=5, num_classes=3) with h5py.File(filename, 'w') as f: f.create_dataset('X', data=dataset.get_design_matrix()) f.create_dataset('y', data=dataset.get_targets()) trainer = yaml_parse.load((load_all_yaml % {'filename': filename})) trainer.main_loop() os.remove(filename)
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train using an hdf5 dataset with all data loaded into memory .
train
false
43,175
def weighted_lottery(weights, _random=random.random): total = sum(weights.itervalues()) if (total <= 0): raise ValueError('total weight must be positive') r = (_random() * total) t = 0 for (key, weight) in weights.iteritems(): if (weight < 0): raise ValueError(('weight for %r must be non-negative' % key)) t += weight if (t > r): return key raise ValueError(('weighted_lottery messed up: r=%r, t=%r, total=%r' % (r, t, total)))
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randomly choose a key from a dict where values are weights .
train
false
43,176
def item_method(fn): fn._item_method = True return fn
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flag method as an item method .
train
false
43,177
def raw_incron(user): if (__grains__['os_family'] == 'Solaris'): cmd = 'incrontab -l {0}'.format(user) else: cmd = 'incrontab -l -u {0}'.format(user) return __salt__['cmd.run_stdout'](cmd, rstrip=False, runas=user, python_shell=False)
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return the contents of the users incrontab cli example: .
train
true
43,179
def _get_prerequisite_milestone(prereq_content_key): milestones = milestones_api.get_milestones('{usage_key}{qualifier}'.format(usage_key=prereq_content_key, qualifier=GATING_NAMESPACE_QUALIFIER)) if (not milestones): log.warning('Could not find gating milestone for prereq UsageKey %s', prereq_content_key) return None if (len(milestones) > 1): log.warning('Multiple gating milestones found for prereq UsageKey %s', prereq_content_key) return milestones[0]
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get gating milestone associated with the given content usage key .
train
false
43,181
def _generate_urls(mbid): for level in LEVELS: (yield ((ACOUSTIC_BASE + mbid) + level))
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generates acousticbrainz end point urls for given mbid .
train
false
43,182
def monomial_count(V, N): from sympy import factorial return ((factorial((V + N)) / factorial(V)) / factorial(N))
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computes the number of monomials .
train
false
43,183
def validate_trust_root(openid_request): trusted_roots = getattr(settings, 'OPENID_PROVIDER_TRUSTED_ROOT', None) if (not trusted_roots): return True if ((not hasattr(openid_request, 'trust_root')) or (not openid_request.trust_root)): log.error('no trust_root') return False trust_root = TrustRoot.parse(openid_request.trust_root) if (not trust_root): log.error('invalid trust_root') return False if ((not hasattr(openid_request, 'return_to')) or (not openid_request.return_to)): log.error('empty return_to') return False if (not trust_root.validateURL(openid_request.return_to)): log.error('invalid return_to') return False if (not any((r for r in trusted_roots if fnmatch.fnmatch(trust_root, r)))): log.error('non-trusted root') return False return True
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only allow openid requests from valid trust roots .
train
false
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def getEndGeometryXMLString(output): addEndXMLTag(0, 'fabmetheus', output) return output.getvalue()
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get the string representation of this object info .
train
false
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def id_to_ec2_id(instance_id, template='i-%08x'): return (template % int(instance_id))
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convert an instance id to an ec2 id .
train
false
43,187
def induce_pcfg(start, productions): pcount = {} lcount = {} for prod in productions: lcount[prod.lhs()] = (lcount.get(prod.lhs(), 0) + 1) pcount[prod] = (pcount.get(prod, 0) + 1) prods = [ProbabilisticProduction(p.lhs(), p.rhs(), prob=(pcount[p] / lcount[p.lhs()])) for p in pcount] return PCFG(start, prods)
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induce a pcfg grammar from a list of productions .
train
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def source(object): print(('In file: %s' % inspect.getsourcefile(object))) print(inspect.getsource(object))
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require a package source .
train
false
43,189
def make_loopable(clip, cross): d = clip.duration clip2 = clip.fx(transfx.crossfadein, cross).set_start((d - cross)) return CompositeVideoClip([clip, clip2]).subclip(cross, d)
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makes the clip fade in progressively at its own end .
train
false
43,190
def mvstdtprob(a, b, R, df, ieps=1e-05, quadkwds=None, mvstkwds=None): kwds = dict(args=(a, b, R, df), epsabs=0.0001, epsrel=0.01, limit=150) if (not (quadkwds is None)): kwds.update(quadkwds) (res, err) = integrate.quad(funbgh2, *chi.ppf([ieps, (1 - ieps)], df), **kwds) prob = (res * bghfactor(df)) return prob
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probability of rectangular area of standard t distribution assumes mean is zero and r is correlation matrix notes this function does not calculate the estimate of the combined error between the underlying multivariate normal probability calculations and the integration .
train
false
43,191
@Memoize def cycle_color(s): return next(dg['cyc'])(s)
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cycle the colors_shuffle .
train
false
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def accuracy_score(y_true, y_pred, normalize=True, sample_weight=None): (y_type, y_true, y_pred) = _check_targets(y_true, y_pred) if y_type.startswith('multilabel'): differing_labels = count_nonzero((y_true - y_pred), axis=1) score = (differing_labels == 0) else: score = (y_true == y_pred) return _weighted_sum(score, sample_weight, normalize)
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accuracy classification score .
train
false
43,193
def test_close_process_when_aborted(): with pipeline.get_cat_pipeline(pipeline.PIPE, pipeline.PIPE) as pl: assert (len(pl.commands) == 1) assert (pl.commands[0]._process.poll() is None) pl.abort() pipeline_wait(pl)
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process leaks must not occur when the pipeline is aborted .
train
false
43,195
def list_known_phylogenetic_metrics(): result = [] for name in dir(qiime.beta_metrics): if name.startswith('dist_'): result.append(name[5:]) result.sort() return result
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lists known phylogenetic metrics from cogent .
train
false
43,196
def getPage(url, contextFactory=None, response_transform=None, *args, **kwargs): def _clientfactory(url, *args, **kwargs): url = to_unicode(url) timeout = kwargs.pop('timeout', 0) f = client.ScrapyHTTPClientFactory(Request(url, *args, **kwargs), timeout=timeout) f.deferred.addCallback((response_transform or (lambda r: r.body))) return f from twisted.web.client import _makeGetterFactory return _makeGetterFactory(to_bytes(url), _clientfactory, contextFactory=contextFactory, *args, **kwargs).deferred
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download a web page as a string .
train
false
43,197
@register.tag('with') def do_with(parser, token): bits = token.split_contents() remaining_bits = bits[1:] extra_context = token_kwargs(remaining_bits, parser, support_legacy=True) if (not extra_context): raise TemplateSyntaxError(('%r expected at least one variable assignment' % bits[0])) if remaining_bits: raise TemplateSyntaxError(('%r received an invalid token: %r' % (bits[0], remaining_bits[0]))) nodelist = parser.parse(('endwith',)) parser.delete_first_token() return WithNode(None, None, nodelist, extra_context=extra_context)
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adds one or more values to the context for caching and easy access .
train
false
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def getSegmentsFromXIntersections(xIntersections, y): segments = [] end = len(xIntersections) if ((len(xIntersections) % 2) == 1): end -= 1 for xIntersectionIndex in xrange(0, end, 2): firstX = xIntersections[xIntersectionIndex] secondX = xIntersections[(xIntersectionIndex + 1)] if (firstX != secondX): segments.append(getSegmentFromPoints(complex(firstX, y), complex(secondX, y))) return segments
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get endpoint segments from the x intersections .
train
false
43,200
def build_doc(doc, opts): doclist = doc.split(u'\n') newdoc = [] flags_doc = [] for line in doclist: linelist = line.split() if (not linelist): continue if (u',' in linelist[0]): flag = linelist[0].split(u',')[0] else: flag = linelist[0] attr = opts.get(flag) if (attr is not None): linelist[0] = (u'%s :\n ' % str(attr)) newline = u' '.join(linelist) newdoc.append(newline) elif line[0].isspace(): flags_doc.append(line) return format_params(newdoc, flags_doc)
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build docstring from doc and options parameters rep_doc : string documentation string opts : dict dictionary of option attributes and keys .
train
false
43,201
def GetVersionNamespace(version): ns = nsMap[version] if (not ns): ns = serviceNsMap[version] versionId = versionIdMap[version] if (not versionId): namespace = ns else: namespace = ('%s/%s' % (ns, versionId)) return namespace
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get version namespace from version .
train
true
43,202
def YamlDumper(aff4object): aff4object.Flush() result = {} for (attribute, values) in aff4object.synced_attributes.items(): result[attribute.predicate] = [] for value in values: value = value.ToRDFValue() result[attribute.predicate].append([value.__class__.__name__, value.SerializeToString(), str(value.age)]) return yaml.dump(dict(aff4_class=aff4object.__class__.__name__, _urn=aff4object.urn.SerializeToString(), attributes=result, age_policy=aff4object.age_policy))
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dumps the given aff4object into a yaml representation .
train
false
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def get_default_fields(): default_field = DEFAULT_FIELD default_field.update({'name': 'id', 'type': 'string', 'multiValued': 'false'}) return [default_field]
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returns a list of default fields for the solr schema .
train
false
43,204
def prompt_choice_for_config(cookiecutter_dict, env, key, options, no_input): rendered_options = [render_variable(env, raw, cookiecutter_dict) for raw in options] if no_input: return rendered_options[0] return read_user_choice(key, rendered_options)
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prompt the user which option to choose from the given .
train
true
43,205
def name_or_value(value): try: if issubclass(value, amqp_object.AMQPObject): return value.NAME except TypeError: pass if isinstance(value, frame.Method): return value.method.NAME if isinstance(value, amqp_object.AMQPObject): return value.NAME return canonical_str(value)
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will take frame objects .
train
false
43,206
def get_yaml_from_table(table): header = {'cols': list(six.itervalues(table.columns))} if table.meta: header['meta'] = table.meta return get_yaml_from_header(header)
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return lines with a yaml representation of header content from the table .
train
false
43,207
@retry_on_failure def test_gethostbyaddr(): socket.gethostbyaddr('localhost') socket.gethostbyaddr('127.0.0.1') if (is_cli and (not is_net40)): socket.gethostbyaddr('<broadcast>')
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tests socket .
train
false
43,208
@register.assignment_tag def assignment_two_params(one, two): return ('assignment_two_params - Expected result: %s, %s' % (one, two))
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expected assignment_two_params __doc__ .
train
false