body stringlengths 26 98.2k | body_hash int64 -9,222,864,604,528,158,000 9,221,803,474B | docstring stringlengths 1 16.8k | path stringlengths 5 230 | name stringlengths 1 96 | repository_name stringlengths 7 89 | lang stringclasses 1
value | body_without_docstring stringlengths 20 98.2k |
|---|---|---|---|---|---|---|---|
def _remove_temp_handler():
'\n Remove temporary handler if it exists\n '
if (TEMP_HANDLER and (TEMP_HANDLER in logging.root.handlers)):
logging.root.handlers.remove(TEMP_HANDLER) | -8,479,857,811,240,753,000 | Remove temporary handler if it exists | hubblestack/log.py | _remove_temp_handler | instructure/hubble | python | def _remove_temp_handler():
'\n \n '
if (TEMP_HANDLER and (TEMP_HANDLER in logging.root.handlers)):
logging.root.handlers.remove(TEMP_HANDLER) |
def setup_console_logger(log_level='error', log_format='%(asctime)s [%(levelname)-5s] %(message)s', date_format='%H:%M:%S'):
'\n Sets up logging to STDERR, allowing for configurable level, format, and\n date format.\n '
_remove_temp_handler()
rootlogger = logging.getLogger()
handler = logging.S... | 547,214,475,094,259,900 | Sets up logging to STDERR, allowing for configurable level, format, and
date format. | hubblestack/log.py | setup_console_logger | instructure/hubble | python | def setup_console_logger(log_level='error', log_format='%(asctime)s [%(levelname)-5s] %(message)s', date_format='%H:%M:%S'):
'\n Sets up logging to STDERR, allowing for configurable level, format, and\n date format.\n '
_remove_temp_handler()
rootlogger = logging.getLogger()
handler = logging.S... |
def setup_file_logger(log_file, log_level='error', log_format='%(asctime)s,%(msecs)03d [%(levelname)-5s] [%(name)s:%(lineno)d] %(message)s', date_format='%Y-%m-%d %H:%M:%S', max_bytes=100000000, backup_count=1):
'\n Sets up logging to a file. By default will auto-rotate those logs every\n 100MB and keep one ... | -1,951,438,289,589,759,200 | Sets up logging to a file. By default will auto-rotate those logs every
100MB and keep one backup. | hubblestack/log.py | setup_file_logger | instructure/hubble | python | def setup_file_logger(log_file, log_level='error', log_format='%(asctime)s,%(msecs)03d [%(levelname)-5s] [%(name)s:%(lineno)d] %(message)s', date_format='%Y-%m-%d %H:%M:%S', max_bytes=100000000, backup_count=1):
'\n Sets up logging to a file. By default will auto-rotate those logs every\n 100MB and keep one ... |
def setup_splunk_logger():
'\n Sets up logging to splunk.\n '
_remove_temp_handler()
rootlogger = logging.getLogger()
handler = hubblestack.splunklogging.SplunkHandler()
handler.setLevel(logging.SPLUNK)
rootlogger.addHandler(handler)
global SPLUNK_HANDLER
SPLUNK_HANDLER = handler | -5,930,119,731,152,631,000 | Sets up logging to splunk. | hubblestack/log.py | setup_splunk_logger | instructure/hubble | python | def setup_splunk_logger():
'\n \n '
_remove_temp_handler()
rootlogger = logging.getLogger()
handler = hubblestack.splunklogging.SplunkHandler()
handler.setLevel(logging.SPLUNK)
rootlogger.addHandler(handler)
global SPLUNK_HANDLER
SPLUNK_HANDLER = handler |
def emit_to_splunk(message, level, name):
'\n Emit a single message to splunk\n '
if isinstance(message, (list, dict)):
message = filter_logs(message, remove_dots=False)
if (SPLUNK_HANDLER is None):
return False
handler = SPLUNK_HANDLER
handler.emit(MockRecord(message, level, t... | -7,925,935,624,446,416,000 | Emit a single message to splunk | hubblestack/log.py | emit_to_splunk | instructure/hubble | python | def emit_to_splunk(message, level, name):
'\n \n '
if isinstance(message, (list, dict)):
message = filter_logs(message, remove_dots=False)
if (SPLUNK_HANDLER is None):
return False
handler = SPLUNK_HANDLER
handler.emit(MockRecord(message, level, time.asctime(), name))
retur... |
def workaround_salt_log_handler_queues():
'\n Build a fake log handler and add it to LOGGING_STORE_HANDLER and LOGGING_NULL_HANDLER\n '
class _FakeLogHandler(object):
level = 10
count = 0
def handle(self, _record):
' Receive a record and increase the count '
... | 905,797,758,034,563,600 | Build a fake log handler and add it to LOGGING_STORE_HANDLER and LOGGING_NULL_HANDLER | hubblestack/log.py | workaround_salt_log_handler_queues | instructure/hubble | python | def workaround_salt_log_handler_queues():
'\n \n '
class _FakeLogHandler(object):
level = 10
count = 0
def handle(self, _record):
' Receive a record and increase the count '
self.count += 1
flh = _FakeLogHandler()
import salt.log.setup as sls
s... |
def filter_logs(opts_to_log, remove_dots=True):
'\n Filters out keys containing certain patterns to avoid sensitive information being sent to logs\n Works on dictionaries and lists\n This function was located at extmods/modules/conf_publisher.py previously\n '
filtered_conf = _remove_sensitive_info(... | 5,361,334,341,806,947,000 | Filters out keys containing certain patterns to avoid sensitive information being sent to logs
Works on dictionaries and lists
This function was located at extmods/modules/conf_publisher.py previously | hubblestack/log.py | filter_logs | instructure/hubble | python | def filter_logs(opts_to_log, remove_dots=True):
'\n Filters out keys containing certain patterns to avoid sensitive information being sent to logs\n Works on dictionaries and lists\n This function was located at extmods/modules/conf_publisher.py previously\n '
filtered_conf = _remove_sensitive_info(... |
def _remove_sensitive_info(obj, patterns_to_filter):
'\n Filter known sensitive info\n '
if isinstance(obj, dict):
obj = {key: _remove_sensitive_info(value, patterns_to_filter) for (key, value) in obj.items() if (not any(((patt in key) for patt in patterns_to_filter)))}
elif isinstance(obj, li... | 3,576,416,888,570,603,000 | Filter known sensitive info | hubblestack/log.py | _remove_sensitive_info | instructure/hubble | python | def _remove_sensitive_info(obj, patterns_to_filter):
'\n \n '
if isinstance(obj, dict):
obj = {key: _remove_sensitive_info(value, patterns_to_filter) for (key, value) in obj.items() if (not any(((patt in key) for patt in patterns_to_filter)))}
elif isinstance(obj, list):
obj = [_remove... |
def handle(self, _record):
' Receive a record and increase the count '
self.count += 1 | 3,950,741,304,086,814,000 | Receive a record and increase the count | hubblestack/log.py | handle | instructure/hubble | python | def handle(self, _record):
' '
self.count += 1 |
@power_session(envs=ENVS, logsdir=Folders.runlogs)
def tests(session: PowerSession, coverage, pkg_specs):
'Run the test suite, including test reports generation and coverage reports. '
rm_folder(Folders.site)
rm_folder(Folders.reports_root)
rm_file(Folders.coverage_intermediate_file)
rm_file((Folder... | -4,468,099,125,579,665,400 | Run the test suite, including test reports generation and coverage reports. | noxfile.py | tests | texnofobix/python-genbadge | python | @power_session(envs=ENVS, logsdir=Folders.runlogs)
def tests(session: PowerSession, coverage, pkg_specs):
' '
rm_folder(Folders.site)
rm_folder(Folders.reports_root)
rm_file(Folders.coverage_intermediate_file)
rm_file((Folders.root / 'coverage.xml'))
session.install_reqs(setup=True, install=True... |
@power_session(python=PY38, logsdir=Folders.runlogs)
def flake8(session: PowerSession):
'Launch flake8 qualimetry.'
session.install('-r', str((Folders.ci_tools / 'flake8-requirements.txt')))
session.run2('pip install -e .[flake8]')
rm_folder(Folders.flake8_reports)
rm_file(Folders.flake8_intermediat... | 7,663,644,602,271,633,000 | Launch flake8 qualimetry. | noxfile.py | flake8 | texnofobix/python-genbadge | python | @power_session(python=PY38, logsdir=Folders.runlogs)
def flake8(session: PowerSession):
session.install('-r', str((Folders.ci_tools / 'flake8-requirements.txt')))
session.run2('pip install -e .[flake8]')
rm_folder(Folders.flake8_reports)
rm_file(Folders.flake8_intermediate_file)
session.run('fl... |
@power_session(python=[PY37])
def docs(session: PowerSession):
"Generates the doc and serves it on a local http server. Pass '-- build' to build statically instead."
session.install_reqs(phase='docs', phase_reqs=['mkdocs-material', 'mkdocs', 'pymdown-extensions', 'pygments'])
if session.posargs:
ses... | -3,700,643,923,249,329,000 | Generates the doc and serves it on a local http server. Pass '-- build' to build statically instead. | noxfile.py | docs | texnofobix/python-genbadge | python | @power_session(python=[PY37])
def docs(session: PowerSession):
session.install_reqs(phase='docs', phase_reqs=['mkdocs-material', 'mkdocs', 'pymdown-extensions', 'pygments'])
if session.posargs:
session.run2(('mkdocs -f ./docs/mkdocs.yml %s' % ' '.join(session.posargs)))
else:
session.ru... |
@power_session(python=[PY37])
def publish(session: PowerSession):
'Deploy the docs+reports on github pages. Note: this rebuilds the docs'
session.install_reqs(phase='mkdocs', phase_reqs=['mkdocs-material', 'mkdocs', 'pymdown-extensions', 'pygments'])
session.run2('mkdocs build -f ./docs/mkdocs.yml')
if ... | -5,760,951,214,420,701,000 | Deploy the docs+reports on github pages. Note: this rebuilds the docs | noxfile.py | publish | texnofobix/python-genbadge | python | @power_session(python=[PY37])
def publish(session: PowerSession):
session.install_reqs(phase='mkdocs', phase_reqs=['mkdocs-material', 'mkdocs', 'pymdown-extensions', 'pygments'])
session.run2('mkdocs build -f ./docs/mkdocs.yml')
if (not Folders.site_reports.exists()):
raise ValueError("Test rep... |
@power_session(python=[PY37])
def release(session: PowerSession):
'Create a release on github corresponding to the latest tag'
from setuptools_scm import get_version
from setuptools_scm.version import guess_next_dev_version
version = []
def my_scheme(version_):
version.append(version_)
... | 3,323,425,240,592,413,000 | Create a release on github corresponding to the latest tag | noxfile.py | release | texnofobix/python-genbadge | python | @power_session(python=[PY37])
def release(session: PowerSession):
from setuptools_scm import get_version
from setuptools_scm.version import guess_next_dev_version
version = []
def my_scheme(version_):
version.append(version_)
return guess_next_dev_version(version_)
current_tag ... |
@nox.session(python=False)
def gha_list(session):
'(mandatory arg: <base_session_name>) Prints all sessions available for <base_session_name>, for GithubActions.'
if (len(session.posargs) != 1):
raise ValueError('This session has a mandatory argument: <base_session_name>')
session_func = globals()[s... | 4,695,728,447,206,028,000 | (mandatory arg: <base_session_name>) Prints all sessions available for <base_session_name>, for GithubActions. | noxfile.py | gha_list | texnofobix/python-genbadge | python | @nox.session(python=False)
def gha_list(session):
if (len(session.posargs) != 1):
raise ValueError('This session has a mandatory argument: <base_session_name>')
session_func = globals()[session.posargs[0]]
try:
session_func.parametrize
except AttributeError:
sessions_list = ... |
def _query_for_quote(symbol):
'\n 返回请求某个合约的合约信息的 query_pack\n 调用次函数应该全部都是sdk的代码主动请求合约信息\n 用户请求合约信息一定是 PYSDK_api 开头的请求，因为用户请求的合约信息在回测时带有 timestamp 参数，是不应该调用此函数的\n '
symbol_list = (symbol if isinstance(symbol, list) else [symbol])
op = Operation(ins_schema.rootQuery)
query = op.multi_symbol_in... | -8,257,304,933,987,689,000 | 返回请求某个合约的合约信息的 query_pack
调用次函数应该全部都是sdk的代码主动请求合约信息
用户请求合约信息一定是 PYSDK_api 开头的请求，因为用户请求的合约信息在回测时带有 timestamp 参数，是不应该调用此函数的 | tqsdk/utils.py | _query_for_quote | Al-Wang/tqsdk-python | python | def _query_for_quote(symbol):
'\n 返回请求某个合约的合约信息的 query_pack\n 调用次函数应该全部都是sdk的代码主动请求合约信息\n 用户请求合约信息一定是 PYSDK_api 开头的请求，因为用户请求的合约信息在回测时带有 timestamp 参数，是不应该调用此函数的\n '
symbol_list = (symbol if isinstance(symbol, list) else [symbol])
op = Operation(ins_schema.rootQuery)
query = op.multi_symbol_in... |
def _query_for_init():
'\n 返回某些类型合约的 query\n todo: 为了兼容旧版提供给用户的 api._data["quote"].items() 类似用法，应该限制交易所 ["SHFE", "DCE", "CZCE", "INE", "CFFEX", "KQ"]\n '
op = Operation(ins_schema.rootQuery)
query = op.multi_symbol_info(class_=['FUTURE', 'INDEX', 'OPTION', 'COMBINE', 'CONT'], exchange_id=['SHFE', '... | -7,600,899,964,340,058,000 | 返回某些类型合约的 query
todo: 为了兼容旧版提供给用户的 api._data["quote"].items() 类似用法，应该限制交易所 ["SHFE", "DCE", "CZCE", "INE", "CFFEX", "KQ"] | tqsdk/utils.py | _query_for_init | Al-Wang/tqsdk-python | python | def _query_for_init():
'\n 返回某些类型合约的 query\n todo: 为了兼容旧版提供给用户的 api._data["quote"].items() 类似用法，应该限制交易所 ["SHFE", "DCE", "CZCE", "INE", "CFFEX", "KQ"]\n '
op = Operation(ins_schema.rootQuery)
query = op.multi_symbol_info(class_=['FUTURE', 'INDEX', 'OPTION', 'COMBINE', 'CONT'], exchange_id=['SHFE', '... |
def _quotes_add_night(quotes):
'为 quotes 中应该有夜盘但是市价合约文件中没有夜盘的品种，添加夜盘时间'
for symbol in quotes:
product_id = quotes[symbol].get('product_id')
if (quotes[symbol].get('trading_time') and product_id):
key = f"{quotes[symbol].get('exchange_id')}.{product_id}"
if ((key in night_... | 198,753,870,435,223,900 | 为 quotes 中应该有夜盘但是市价合约文件中没有夜盘的品种，添加夜盘时间 | tqsdk/utils.py | _quotes_add_night | Al-Wang/tqsdk-python | python | def _quotes_add_night(quotes):
for symbol in quotes:
product_id = quotes[symbol].get('product_id')
if (quotes[symbol].get('trading_time') and product_id):
key = f"{quotes[symbol].get('exchange_id')}.{product_id}"
if ((key in night_trading_table) and (not quotes[symbol]['... |
def _bisect_value(a, x, priority='right'):
'\n 返回 bisect_right() 取得下标对应的值，当插入点距离前后元素距离相等，priority 表示优先返回右边的值还是左边的值\n a: 必须是已经排序好（升序排列）的 list\n bisect_right : Return the index where to insert item x in list a, assuming a is sorted.\n '
assert (priority in ['left', 'right'])
insert_index = bisect_... | -4,910,537,497,647,901,000 | 返回 bisect_right() 取得下标对应的值，当插入点距离前后元素距离相等，priority 表示优先返回右边的值还是左边的值
a: 必须是已经排序好（升序排列）的 list
bisect_right : Return the index where to insert item x in list a, assuming a is sorted. | tqsdk/utils.py | _bisect_value | Al-Wang/tqsdk-python | python | def _bisect_value(a, x, priority='right'):
'\n 返回 bisect_right() 取得下标对应的值，当插入点距离前后元素距离相等，priority 表示优先返回右边的值还是左边的值\n a: 必须是已经排序好（升序排列）的 list\n bisect_right : Return the index where to insert item x in list a, assuming a is sorted.\n '
assert (priority in ['left', 'right'])
insert_index = bisect_... |
def testcase_readergroup_add(self):
'tests groups=groups+[newgroups]'
groupssnapshot = list(readergroups())
groups = readergroups()
groups = (groups + [self.pinpadgroup])
self.assertEqual(groups, (groupssnapshot + [self.pinpadgroup]))
groups = (groups + [self.biogroup, self.pinpadgroup])
sel... | 2,148,898,669,865,351,000 | tests groups=groups+[newgroups] | cacreader/pyscard-2.0.2/smartcard/test/framework/testcase_readergroups.py | testcase_readergroup_add | kyletanyag/LL-Smartcard | python | def testcase_readergroup_add(self):
groupssnapshot = list(readergroups())
groups = readergroups()
groups = (groups + [self.pinpadgroup])
self.assertEqual(groups, (groupssnapshot + [self.pinpadgroup]))
groups = (groups + [self.biogroup, self.pinpadgroup])
self.assertEqual(groups, (groupssnap... |
def testcase_readergroup_iadd(self):
'test groups+=[newgroups]'
groupssnapshot = list(readergroups())
groups = readergroups()
groups += [self.pinpadgroup]
self.assertEqual(groups, (groupssnapshot + [self.pinpadgroup]))
groups += [self.biogroup, self.pinpadgroup]
self.assertEqual(groups, (gro... | -4,554,897,509,285,952,500 | test groups+=[newgroups] | cacreader/pyscard-2.0.2/smartcard/test/framework/testcase_readergroups.py | testcase_readergroup_iadd | kyletanyag/LL-Smartcard | python | def testcase_readergroup_iadd(self):
groupssnapshot = list(readergroups())
groups = readergroups()
groups += [self.pinpadgroup]
self.assertEqual(groups, (groupssnapshot + [self.pinpadgroup]))
groups += [self.biogroup, self.pinpadgroup]
self.assertEqual(groups, (groupssnapshot + [self.pinpad... |
def testcase_readergroup_radd(self):
'test groups=[newgroups]+groups'
groupssnapshot = list(readergroups())
groups = readergroups()
zgroups = ([self.pinpadgroup] + groups)
self.assertEqual(groups, groupssnapshot)
self.assertEqual(zgroups, (groupssnapshot + [self.pinpadgroup]))
self.assertTru... | 6,720,619,275,553,248,000 | test groups=[newgroups]+groups | cacreader/pyscard-2.0.2/smartcard/test/framework/testcase_readergroups.py | testcase_readergroup_radd | kyletanyag/LL-Smartcard | python | def testcase_readergroup_radd(self):
groupssnapshot = list(readergroups())
groups = readergroups()
zgroups = ([self.pinpadgroup] + groups)
self.assertEqual(groups, groupssnapshot)
self.assertEqual(zgroups, (groupssnapshot + [self.pinpadgroup]))
self.assertTrue(isinstance(zgroups, type([])))... |
def testcase_readergroup_append(self):
'test groups.append(newgroups)'
groupssnapshot = list(readergroups())
groups = readergroups()
groups.append(self.pinpadgroup)
self.assertEqual(groups, (groupssnapshot + [self.pinpadgroup]))
groups.append(self.pinpadgroup)
self.assertEqual(groups, (group... | 8,593,865,738,370,409,000 | test groups.append(newgroups) | cacreader/pyscard-2.0.2/smartcard/test/framework/testcase_readergroups.py | testcase_readergroup_append | kyletanyag/LL-Smartcard | python | def testcase_readergroup_append(self):
groupssnapshot = list(readergroups())
groups = readergroups()
groups.append(self.pinpadgroup)
self.assertEqual(groups, (groupssnapshot + [self.pinpadgroup]))
groups.append(self.pinpadgroup)
self.assertEqual(groups, (groupssnapshot + [self.pinpadgroup])... |
def testcase_readergroup_insert(self):
'test groups.insert(i,newgroups)'
groupssnapshot = list(readergroups())
groups = readergroups()
groups.insert(0, self.pinpadgroup)
self.assertEqual(groups, (groupssnapshot + [self.pinpadgroup]))
groups.insert(1, self.pinpadgroup)
self.assertEqual(groups... | 8,374,669,445,519,692,000 | test groups.insert(i,newgroups) | cacreader/pyscard-2.0.2/smartcard/test/framework/testcase_readergroups.py | testcase_readergroup_insert | kyletanyag/LL-Smartcard | python | def testcase_readergroup_insert(self):
groupssnapshot = list(readergroups())
groups = readergroups()
groups.insert(0, self.pinpadgroup)
self.assertEqual(groups, (groupssnapshot + [self.pinpadgroup]))
groups.insert(1, self.pinpadgroup)
self.assertEqual(groups, (groupssnapshot + [self.pinpadg... |
def load_parallel_component(file_descr, graph: Graph, prev_layer_id):
'\n Load ParallelComponent of the Kaldi model.\n ParallelComponent contains parallel nested networks.\n VariadicSplit is inserted before nested networks.\n Outputs of nested networks concatenate with layer Concat.\n\n :param file_d... | -6,662,843,149,624,463,000 | Load ParallelComponent of the Kaldi model.
ParallelComponent contains parallel nested networks.
VariadicSplit is inserted before nested networks.
Outputs of nested networks concatenate with layer Concat.
:param file_descr: descriptor of the model file
:param graph: graph with the topology.
:param prev_layer_id: id of ... | tools/mo/openvino/tools/mo/front/kaldi/loader/loader.py | load_parallel_component | 3Demonica/openvino | python | def load_parallel_component(file_descr, graph: Graph, prev_layer_id):
'\n Load ParallelComponent of the Kaldi model.\n ParallelComponent contains parallel nested networks.\n VariadicSplit is inserted before nested networks.\n Outputs of nested networks concatenate with layer Concat.\n\n :param file_d... |
def load_kaldi_model(graph, nnet_path):
'\n Structure of the file is the following:\n magic-number(16896)<Nnet> <Next Layer Name> weights etc.\n :param nnet_path:\n :return:\n '
nnet_name = None
if isinstance(nnet_path, str):
file_desc = open(nnet_path, 'rb')
nnet_name = get_n... | 4,593,314,106,552,690,000 | Structure of the file is the following:
magic-number(16896)<Nnet> <Next Layer Name> weights etc.
:param nnet_path:
:return: | tools/mo/openvino/tools/mo/front/kaldi/loader/loader.py | load_kaldi_model | 3Demonica/openvino | python | def load_kaldi_model(graph, nnet_path):
'\n Structure of the file is the following:\n magic-number(16896)<Nnet> <Next Layer Name> weights etc.\n :param nnet_path:\n :return:\n '
nnet_name = None
if isinstance(nnet_path, str):
file_desc = open(nnet_path, 'rb')
nnet_name = get_n... |
def printProgressBar(iteration, total, prefix='', suffix='', decimals=1, length=100, fill='█', printEnd='\r'):
'\n Call in a loop to create terminal progress bar\n @params:\n iteration - Required : current iteration (Int)\n total - Required : total iterations (Int)\n prefix ... | -4,832,368,723,198,576,000 | Call in a loop to create terminal progress bar
@params:
iteration - Required : current iteration (Int)
total - Required : total iterations (Int)
prefix - Optional : prefix string (Str)
suffix - Optional : suffix string (Str)
decimals - Optional : pos... | src/utils/console_functions.py | printProgressBar | MariusDgr/AudioMining | python | def printProgressBar(iteration, total, prefix=, suffix=, decimals=1, length=100, fill='█', printEnd='\r'):
'\n Call in a loop to create terminal progress bar\n @params:\n iteration - Required : current iteration (Int)\n total - Required : total iterations (Int)\n prefix - O... |
def portfolio_metrics(weights, avg_xs_returns, covariance_matrix):
' Compute basic portfolio metrics: return, stdv, sharpe ratio '
portfolio_return = np.sum((weights * avg_xs_returns))
portfolio_stdv = np.sqrt(np.dot(weights.T, np.dot(weights, covariance_matrix)))
portfolio_sharpe = (portfolio_return / ... | -7,040,679,439,820,220,000 | Compute basic portfolio metrics: return, stdv, sharpe ratio | portfolio_functions.py | portfolio_metrics | MaxGosselin/portfolio_optimizer | python | def portfolio_metrics(weights, avg_xs_returns, covariance_matrix):
' '
portfolio_return = np.sum((weights * avg_xs_returns))
portfolio_stdv = np.sqrt(np.dot(weights.T, np.dot(weights, covariance_matrix)))
portfolio_sharpe = (portfolio_return / portfolio_stdv)
tickers = covariance_matrix.columns
... |
def simulate_portfolios(iters, xs_stats, covariance_matrix):
' What we want here is to randomly generate portfolios that will sit \n inside the efficiency frontier for illustrative purposes '
simulations = []
while (iters > 1):
weights = np.random.random(len(xs_stats.columns))
weights... | -4,991,181,571,714,116,000 | What we want here is to randomly generate portfolios that will sit
inside the efficiency frontier for illustrative purposes | portfolio_functions.py | simulate_portfolios | MaxGosselin/portfolio_optimizer | python | def simulate_portfolios(iters, xs_stats, covariance_matrix):
' What we want here is to randomly generate portfolios that will sit \n inside the efficiency frontier for illustrative purposes '
simulations = []
while (iters > 1):
weights = np.random.random(len(xs_stats.columns))
weights... |
def solve_minvar(xs_avg, covariance_matrix):
' Solve for the weights of the minimum variance portfolio \n\n Constraints:\n sum of weights = 1,\n weights bound by [0, 0.2],\n\n Returns the weights and the jacobian used to generate the solution.\n \n '
def __minv... | -3,516,912,878,263,464,000 | Solve for the weights of the minimum variance portfolio
Constraints:
sum of weights = 1,
weights bound by [0, 0.2],
Returns the weights and the jacobian used to generate the solution. | portfolio_functions.py | solve_minvar | MaxGosselin/portfolio_optimizer | python | def solve_minvar(xs_avg, covariance_matrix):
' Solve for the weights of the minimum variance portfolio \n\n Constraints:\n sum of weights = 1,\n weights bound by [0, 0.2],\n\n Returns the weights and the jacobian used to generate the solution.\n \n '
def __minv... |
def solve_maxsharpe(xs_avg, covariance_matrix):
' Solve for the weights of the maximum Sharpe ratio portfolio \n\n Constraints:\n sum of weights = 1,\n weights bound by [0, 0.2],\n\n Returns the weights and the jacobian used to generate the solution.\n \n '
def... | -6,017,148,510,320,264,000 | Solve for the weights of the maximum Sharpe ratio portfolio
Constraints:
sum of weights = 1,
weights bound by [0, 0.2],
Returns the weights and the jacobian used to generate the solution. | portfolio_functions.py | solve_maxsharpe | MaxGosselin/portfolio_optimizer | python | def solve_maxsharpe(xs_avg, covariance_matrix):
' Solve for the weights of the maximum Sharpe ratio portfolio \n\n Constraints:\n sum of weights = 1,\n weights bound by [0, 0.2],\n\n Returns the weights and the jacobian used to generate the solution.\n \n '
def... |
def solve_for_target_return(xs_avg, covariance_matrix, target):
' Solve for the weights of the minimum variance portfolio which has\n a specific targeted return.\n\n Constraints:\n sum of weights = 1,\n weights bound by [0, 0.2],\n portfolio return = target return,\n\n... | 6,640,005,835,390,372,000 | Solve for the weights of the minimum variance portfolio which has
a specific targeted return.
Constraints:
sum of weights = 1,
weights bound by [0, 0.2],
portfolio return = target return,
Returns the weights and the jacobian used to generate the solution. | portfolio_functions.py | solve_for_target_return | MaxGosselin/portfolio_optimizer | python | def solve_for_target_return(xs_avg, covariance_matrix, target):
' Solve for the weights of the minimum variance portfolio which has\n a specific targeted return.\n\n Constraints:\n sum of weights = 1,\n weights bound by [0, 0.2],\n portfolio return = target return,\n\n... |
def __minvar(weights, xs_avg, covariance_matrix):
' Anonymous function to compute stdv '
return np.sqrt(np.dot(weights.T, np.dot(weights, covariance_matrix))) | 7,441,897,879,151,888,000 | Anonymous function to compute stdv | portfolio_functions.py | __minvar | MaxGosselin/portfolio_optimizer | python | def __minvar(weights, xs_avg, covariance_matrix):
' '
return np.sqrt(np.dot(weights.T, np.dot(weights, covariance_matrix))) |
def __max_by_min_sharpe(weights, xs_avg, covariance_matrix):
' Anonymous function to compute sharpe ratio, note that since scipy only minimizes we go negative. '
pm = portfolio_metrics(weights, xs_avg, covariance_matrix)
return ((- pm['return']) / pm['stdv']) | -6,553,485,962,850,862,000 | Anonymous function to compute sharpe ratio, note that since scipy only minimizes we go negative. | portfolio_functions.py | __max_by_min_sharpe | MaxGosselin/portfolio_optimizer | python | def __max_by_min_sharpe(weights, xs_avg, covariance_matrix):
' '
pm = portfolio_metrics(weights, xs_avg, covariance_matrix)
return ((- pm['return']) / pm['stdv']) |
def __minvar(weights, xs_avg, covariance_matrix):
' Anonymous function to compute stdv '
return np.sqrt(np.dot(weights.T, np.dot(weights, covariance_matrix))) | 7,441,897,879,151,888,000 | Anonymous function to compute stdv | portfolio_functions.py | __minvar | MaxGosselin/portfolio_optimizer | python | def __minvar(weights, xs_avg, covariance_matrix):
' '
return np.sqrt(np.dot(weights.T, np.dot(weights, covariance_matrix))) |
def __match_target(weights):
' Anonymous function to check equality with the target return '
return np.sum((weights * xs_avg)) | -6,367,836,879,853,125,000 | Anonymous function to check equality with the target return | portfolio_functions.py | __match_target | MaxGosselin/portfolio_optimizer | python | def __match_target(weights):
' '
return np.sum((weights * xs_avg)) |
def _base_parse(fh, builder, IndentationSetupF=False):
'Parses pattern definitions of the form:\n \n [ \t] => grid 4;\n [:intersection([:alpha:], [\\X064-\\X066]):] => space 1;\n\n In other words the right hand side *must* be a character set.\n\n ADAP... | -2,264,336,187,077,974,500 | Parses pattern definitions of the form:
[ ] => grid 4;
[:intersection([:alpha:], [\X064-\X066]):] => space 1;
In other words the right hand side *must* be a character set.
ADAPTS: result to contain parsing information. | quex/input/files/specifier/counter.py | _base_parse | Liby99/quex | python | def _base_parse(fh, builder, IndentationSetupF=False):
'Parses pattern definitions of the form:\n \n [ \t] => grid 4;\n [:intersection([:alpha:], [\\X064-\\X066]):] => space 1;\n\n In other words the right hand side *must* be a character set.\n\n ADAP... |
def _check_grid_values_integer_multiples(CaMap):
"If there are no spaces and the grid is on a homogeneous scale,\n => then the grid can be transformed into 'easy-to-compute' spaces.\n "
grid_value_list = []
min_info = None
for (character_set, info) in CaMap:
if (info.cc_type == E_Charac... | -6,188,627,997,836,072,000 | If there are no spaces and the grid is on a homogeneous scale,
=> then the grid can be transformed into 'easy-to-compute' spaces. | quex/input/files/specifier/counter.py | _check_grid_values_integer_multiples | Liby99/quex | python | def _check_grid_values_integer_multiples(CaMap):
"If there are no spaces and the grid is on a homogeneous scale,\n => then the grid can be transformed into 'easy-to-compute' spaces.\n "
grid_value_list = []
min_info = None
for (character_set, info) in CaMap:
if (info.cc_type == E_Charac... |
def check_defined(CaMap, SourceReference, CCT):
'Checks whether the character counter type has been defined in the \n map.\n \n THROWS: Error in case that is has not been defined.\n '
for (character_set, info) in CaMap:
if (info.cc_type == CCT):
return
error.warning(("Setup d... | -7,588,525,549,289,565,000 | Checks whether the character counter type has been defined in the
map.
THROWS: Error in case that is has not been defined. | quex/input/files/specifier/counter.py | check_defined | Liby99/quex | python | def check_defined(CaMap, SourceReference, CCT):
'Checks whether the character counter type has been defined in the \n map.\n \n THROWS: Error in case that is has not been defined.\n '
for (character_set, info) in CaMap:
if (info.cc_type == CCT):
return
error.warning(("Setup d... |
def __sm_newline_default(self):
"Default newline: '(\n)|(\r\n)'\n "
sm = DFA.from_character_set(NumberSet(ord('\n')))
if Setup.dos_carriage_return_newline_f:
sm.add_transition_sequence(sm.init_state_index, [ord('\r'), ord('\n')])
return sm | 1,336,341,528,381,798,700 | Default newline: '(
)|(
)' | quex/input/files/specifier/counter.py | __sm_newline_default | Liby99/quex | python | def __sm_newline_default(self):
"Default newline: '(\n)|(\r\n)'\n "
sm = DFA.from_character_set(NumberSet(ord('\n')))
if Setup.dos_carriage_return_newline_f:
sm.add_transition_sequence(sm.init_state_index, [ord('\r'), ord('\n')])
return sm |
def __sm_whitespace_default(self):
"Try to define default whitespace ' ' or '\t' if their positions\n are not yet occupied in the count_command_map.\n "
sm_whitespace = DFA.from_character_set(NumberSet.from_integer_list([ord(' '), ord('\t')]))
sm_whitespace = beautifier.do(repeat.do(sm_whitesp... | -5,222,298,472,099,206,000 | Try to define default whitespace ' ' or ' ' if their positions
are not yet occupied in the count_command_map. | quex/input/files/specifier/counter.py | __sm_whitespace_default | Liby99/quex | python | def __sm_whitespace_default(self):
"Try to define default whitespace ' ' or '\t' if their positions\n are not yet occupied in the count_command_map.\n "
sm_whitespace = DFA.from_character_set(NumberSet.from_integer_list([ord(' '), ord('\t')]))
sm_whitespace = beautifier.do(repeat.do(sm_whitesp... |
def _consistency_check(self):
"\n Required defintions:\n -- WHITESPACE (Default done automatically) => Assert.\n -- NEWLINE (Default done automatically) => Assert.\n\n Inadmissible 'eat-into'.\n -- SUPPRESSOR shall not eat into [NEWLINE]\n -- NEWLINE shall... | -4,516,450,391,270,619,000 | Required defintions:
-- WHITESPACE (Default done automatically) => Assert.
-- NEWLINE (Default done automatically) => Assert.
Inadmissible 'eat-into'.
-- SUPPRESSOR shall not eat into [NEWLINE]
-- NEWLINE shall not eat into [WHITESPACE, BADSPACE, SUSPEND, SUPPRESSOR]
-- WHITESPACE shall not eat in... | quex/input/files/specifier/counter.py | _consistency_check | Liby99/quex | python | def _consistency_check(self):
"\n Required defintions:\n -- WHITESPACE (Default done automatically) => Assert.\n -- NEWLINE (Default done automatically) => Assert.\n\n Inadmissible 'eat-into'.\n -- SUPPRESSOR shall not eat into [NEWLINE]\n -- NEWLINE shall... |
def get_enrollment_dates(course):
'Takes a course object and returns student dates of enrollment.\n Useful for handling late registrations and modified deadlines.\n\n Example:\n course.get_enrollment_date()'
url_path = posixpath.join('api', 'v1', 'courses', course['course_id'], 'enrollments')
api_u... | -5,592,095,403,443,192,000 | Takes a course object and returns student dates of enrollment.
Useful for handling late registrations and modified deadlines.
Example:
course.get_enrollment_date() | scripts/canvas.py | get_enrollment_dates | hsmohammed/rudaux | python | def get_enrollment_dates(course):
'Takes a course object and returns student dates of enrollment.\n Useful for handling late registrations and modified deadlines.\n\n Example:\n course.get_enrollment_date()'
url_path = posixpath.join('api', 'v1', 'courses', course['course_id'], 'enrollments')
api_u... |
def get_assignments(course):
'Takes a course object and returns\n a Pandas data frame with all existing assignments and their attributes/data\n\n Example:\n course.get_assignments()'
url_path = posixpath.join('api', 'v1', 'courses', course['course_id'], 'assignments')
api_url = urllib.parse.urljoin... | 2,791,318,408,290,562,000 | Takes a course object and returns
a Pandas data frame with all existing assignments and their attributes/data
Example:
course.get_assignments() | scripts/canvas.py | get_assignments | hsmohammed/rudaux | python | def get_assignments(course):
'Takes a course object and returns\n a Pandas data frame with all existing assignments and their attributes/data\n\n Example:\n course.get_assignments()'
url_path = posixpath.join('api', 'v1', 'courses', course['course_id'], 'assignments')
api_url = urllib.parse.urljoin... |
def get_assignment_lock_date(course, assignment):
"Takes a course object and the name of a Canvas assignment and returns the due date. Returns None if no due date assigned.\n \n Example:\n course.get_assignment_due_date('worksheet_01')"
assignments = get_assignments(course)
assignments = assignment... | 3,708,928,769,583,871,500 | Takes a course object and the name of a Canvas assignment and returns the due date. Returns None if no due date assigned.
Example:
course.get_assignment_due_date('worksheet_01') | scripts/canvas.py | get_assignment_lock_date | hsmohammed/rudaux | python | def get_assignment_lock_date(course, assignment):
"Takes a course object and the name of a Canvas assignment and returns the due date. Returns None if no due date assigned.\n \n Example:\n course.get_assignment_due_date('worksheet_01')"
assignments = get_assignments(course)
assignments = assignment... |
def get_assignment_due_date(course, assignment):
"Takes a course object and the name of a Canvas assignment and returns the due date. Returns None if no due date assigned.\n \n Example:\n course.get_assignment_due_date('worksheet_01')"
assignments = get_assignments(course)
assignments = assignments... | 5,000,143,287,905,871,000 | Takes a course object and the name of a Canvas assignment and returns the due date. Returns None if no due date assigned.
Example:
course.get_assignment_due_date('worksheet_01') | scripts/canvas.py | get_assignment_due_date | hsmohammed/rudaux | python | def get_assignment_due_date(course, assignment):
"Takes a course object and the name of a Canvas assignment and returns the due date. Returns None if no due date assigned.\n \n Example:\n course.get_assignment_due_date('worksheet_01')"
assignments = get_assignments(course)
assignments = assignments... |
def get_assignment_unlock_date(course, assignment):
"Takes a course object and the name of a Canvas assignment and returns the due date. Returns None if no due date assigned.\n \n Example:\n course.get_assignment_unlock_date('worksheet_01')"
assignments = get_assignments(course)
assignments = assig... | 8,767,283,540,079,634,000 | Takes a course object and the name of a Canvas assignment and returns the due date. Returns None if no due date assigned.
Example:
course.get_assignment_unlock_date('worksheet_01') | scripts/canvas.py | get_assignment_unlock_date | hsmohammed/rudaux | python | def get_assignment_unlock_date(course, assignment):
"Takes a course object and the name of a Canvas assignment and returns the due date. Returns None if no due date assigned.\n \n Example:\n course.get_assignment_unlock_date('worksheet_01')"
assignments = get_assignments(course)
assignments = assig... |
def get_assignment_id(course, assignment):
"Takes a course object and the name of a Canvas assignment and returns the Canvas ID.\n \n Example:\n course.get_assignment_id('worksheet_01')"
assignments = get_assignments(course)
assignments = assignments[['name', 'id']].query('name == @assignment')
... | 3,881,977,869,741,318,700 | Takes a course object and the name of a Canvas assignment and returns the Canvas ID.
Example:
course.get_assignment_id('worksheet_01') | scripts/canvas.py | get_assignment_id | hsmohammed/rudaux | python | def get_assignment_id(course, assignment):
"Takes a course object and the name of a Canvas assignment and returns the Canvas ID.\n \n Example:\n course.get_assignment_id('worksheet_01')"
assignments = get_assignments(course)
assignments = assignments[['name', 'id']].query('name == @assignment')
... |
def get_grades(course, assignment):
"Takes a course object, an assignment name, and get the grades for that assignment from Canvas.\n \n Example:\n course.get_grades(course, 'worksheet_01')"
assignment_id = get_assignment_id(course, assignment)
url_path = posixpath.join('api', 'v1', 'courses', cour... | 2,481,858,038,511,870,500 | Takes a course object, an assignment name, and get the grades for that assignment from Canvas.
Example:
course.get_grades(course, 'worksheet_01') | scripts/canvas.py | get_grades | hsmohammed/rudaux | python | def get_grades(course, assignment):
"Takes a course object, an assignment name, and get the grades for that assignment from Canvas.\n \n Example:\n course.get_grades(course, 'worksheet_01')"
assignment_id = get_assignment_id(course, assignment)
url_path = posixpath.join('api', 'v1', 'courses', cour... |
def grades_need_posting(course, assignment):
"Takes a course object, an assignment name, and get the grades for that assignment from Canvas.\n \n Example:\n course.get_grades(course, 'worksheet_01')"
assignment_id = get_assignment_id(course, assignment)
url_path = posixpath.join('api', 'v1', 'cours... | 997,278,230,784,641,700 | Takes a course object, an assignment name, and get the grades for that assignment from Canvas.
Example:
course.get_grades(course, 'worksheet_01') | scripts/canvas.py | grades_need_posting | hsmohammed/rudaux | python | def grades_need_posting(course, assignment):
"Takes a course object, an assignment name, and get the grades for that assignment from Canvas.\n \n Example:\n course.get_grades(course, 'worksheet_01')"
assignment_id = get_assignment_id(course, assignment)
url_path = posixpath.join('api', 'v1', 'cours... |
def post_grade(course, assignment, student, score):
"Takes a course object, an assignment name, student id, and score to upload. Posts to Canvas.\n\n Example:\n course.post_grades(dsci100, 'worksheet_01', '23423', 10)"
assignment_id = get_assignment_id(course, assignment)
url_post_path = posixpath.joi... | -5,043,899,444,181,111,000 | Takes a course object, an assignment name, student id, and score to upload. Posts to Canvas.
Example:
course.post_grades(dsci100, 'worksheet_01', '23423', 10) | scripts/canvas.py | post_grade | hsmohammed/rudaux | python | def post_grade(course, assignment, student, score):
"Takes a course object, an assignment name, student id, and score to upload. Posts to Canvas.\n\n Example:\n course.post_grades(dsci100, 'worksheet_01', '23423', 10)"
assignment_id = get_assignment_id(course, assignment)
url_post_path = posixpath.joi... |
def make_kinetic_precond(kpointset, c0, eps=0.1, asPwCoeffs=True):
'\n Preconditioner\n P = 1 / (||k|| + ε)\n\n Keyword Arguments:\n kpointset --\n '
nk = len(kpointset)
nc = kpointset.ctx().num_spins()
if ((nc == 1) and (nk == 1) and (not asPwCoeffs)):
kp = kpointset[0]
g... | 1,352,622,070,274,955,300 | Preconditioner
P = 1 / (||k|| + ε)
Keyword Arguments:
kpointset -- | python_module/sirius/ot/ot_precondition.py | make_kinetic_precond | electronic-structure/SIRIUS | python | def make_kinetic_precond(kpointset, c0, eps=0.1, asPwCoeffs=True):
'\n Preconditioner\n P = 1 / (||k|| + ε)\n\n Keyword Arguments:\n kpointset --\n '
nk = len(kpointset)
nc = kpointset.ctx().num_spins()
if ((nc == 1) and (nk == 1) and (not asPwCoeffs)):
kp = kpointset[0]
g... |
def checkpoints(self):
'runs movement to levels -- checkpoint when leaving area'
return {'0': self.game, '1': self.good_ending_and_continue, 'bad': self.bad_ending, '3': self.woods_area} | -567,931,036,030,381,100 | runs movement to levels -- checkpoint when leaving area | chapters/chapter2.py | checkpoints | JordanLeich/Alpha-Zombie-Survival-Game | python | def checkpoints(self):
return {'0': self.game, '1': self.good_ending_and_continue, 'bad': self.bad_ending, '3': self.woods_area} |
def good_ending_and_continue(self):
'Simply plays the good ending scene and then drops the player into chapter 2.'
self.good_ending()
Chapter3().game() | 7,323,980,889,246,625,000 | Simply plays the good ending scene and then drops the player into chapter 2. | chapters/chapter2.py | good_ending_and_continue | JordanLeich/Alpha-Zombie-Survival-Game | python | def good_ending_and_continue(self):
self.good_ending()
Chapter3().game() |
def game(self):
'start of ch2'
self.start()
print_sleep('Upon driving the car through the broken roads area, the sun is certainly dwindling and time in the carsays 2:35 AM.\nYou continue to grow yourself tired and restless from everything that had led to this point\n', 2.5)
choices = [str(x) for x in ra... | 8,245,839,575,077,191,000 | start of ch2 | chapters/chapter2.py | game | JordanLeich/Alpha-Zombie-Survival-Game | python | def game(self):
self.start()
print_sleep('Upon driving the car through the broken roads area, the sun is certainly dwindling and time in the carsays 2:35 AM.\nYou continue to grow yourself tired and restless from everything that had led to this point\n', 2.5)
choices = [str(x) for x in range(1, 3)]
... |
def woods_area(self):
'Checkpoint save 3'
player1.checkpoint_save('3')
print_sleep('You have successfully gathered up some sticks and still need a source of flame to begin the campfire.\n', 2)
choices = [str(x) for x in range(1, 3)]
choice_options = ['You can either test your luck in creating a fire... | -3,674,613,718,898,177,000 | Checkpoint save 3 | chapters/chapter2.py | woods_area | JordanLeich/Alpha-Zombie-Survival-Game | python | def woods_area(self):
player1.checkpoint_save('3')
print_sleep('You have successfully gathered up some sticks and still need a source of flame to begin the campfire.\n', 2)
choices = [str(x) for x in range(1, 3)]
choice_options = ['You can either test your luck in creating a fire by (1) Creating fr... |
def __init__(self, mesh):
'*mesh* is the mesh Function.'
self.mesh = asfunction(mesh) | -8,804,555,952,250,433,000 | *mesh* is the mesh Function. | moviemaker3/math/angle.py | __init__ | friedrichromstedt/moviemaker3 | python | def __init__(self, mesh):
self.mesh = asfunction(mesh) |
def __call__(self, ps):
'Returns the arctan2. The (y, x) coordinate is in the last \n dimension.'
meshT = self.mesh(ps).T
return numpy.arctan2(meshT[0], meshT[1]).T | 5,408,430,055,512,316,000 | Returns the arctan2. The (y, x) coordinate is in the last
dimension. | moviemaker3/math/angle.py | __call__ | friedrichromstedt/moviemaker3 | python | def __call__(self, ps):
'Returns the arctan2. The (y, x) coordinate is in the last \n dimension.'
meshT = self.mesh(ps).T
return numpy.arctan2(meshT[0], meshT[1]).T |
def corners_nd(dims, origin=0.5):
'generate relative box corners based on length per dim and\n origin point.\n\n Args:\n dims (float array, shape=[N, ndim]): array of length per dim\n origin (list or array or float): origin point relate to smallest point.\n\n Returns:\n float array, sh... | 8,539,276,352,659,929,000 | generate relative box corners based on length per dim and
origin point.
Args:
dims (float array, shape=[N, ndim]): array of length per dim
origin (list or array or float): origin point relate to smallest point.
Returns:
float array, shape=[N, 2 ** ndim, ndim]: returned corners.
point layout example: (... | det3d/core/bbox/box_np_ops.py | corners_nd | motional/polarstream | python | def corners_nd(dims, origin=0.5):
'generate relative box corners based on length per dim and\n origin point.\n\n Args:\n dims (float array, shape=[N, ndim]): array of length per dim\n origin (list or array or float): origin point relate to smallest point.\n\n Returns:\n float array, sh... |
def rbbox2d_to_near_bbox(rbboxes):
"convert rotated bbox to nearest 'standing' or 'lying' bbox.\n Args:\n rbboxes: [N, 5(x, y, xdim, ydim, rad)] rotated bboxes\n Returns:\n bboxes: [N, 4(xmin, ymin, xmax, ymax)] bboxes\n "
rots = rbboxes[(..., (- 1))]
rots_0_pi_div_2 = np.abs(limit_pe... | -1,301,025,159,006,912,300 | convert rotated bbox to nearest 'standing' or 'lying' bbox.
Args:
rbboxes: [N, 5(x, y, xdim, ydim, rad)] rotated bboxes
Returns:
bboxes: [N, 4(xmin, ymin, xmax, ymax)] bboxes | det3d/core/bbox/box_np_ops.py | rbbox2d_to_near_bbox | motional/polarstream | python | def rbbox2d_to_near_bbox(rbboxes):
"convert rotated bbox to nearest 'standing' or 'lying' bbox.\n Args:\n rbboxes: [N, 5(x, y, xdim, ydim, rad)] rotated bboxes\n Returns:\n bboxes: [N, 4(xmin, ymin, xmax, ymax)] bboxes\n "
rots = rbboxes[(..., (- 1))]
rots_0_pi_div_2 = np.abs(limit_pe... |
def rotation_2d(points, angles):
'rotation 2d points based on origin point clockwise when angle positive.\n\n Args:\n points (float array, shape=[N, point_size, 2]): points to be rotated.\n angles (float array, shape=[N]): rotation angle.\n\n Returns:\n float array: same shape as points\n... | -8,212,063,425,262,677,000 | rotation 2d points based on origin point clockwise when angle positive.
Args:
points (float array, shape=[N, point_size, 2]): points to be rotated.
angles (float array, shape=[N]): rotation angle.
Returns:
float array: same shape as points | det3d/core/bbox/box_np_ops.py | rotation_2d | motional/polarstream | python | def rotation_2d(points, angles):
'rotation 2d points based on origin point clockwise when angle positive.\n\n Args:\n points (float array, shape=[N, point_size, 2]): points to be rotated.\n angles (float array, shape=[N]): rotation angle.\n\n Returns:\n float array: same shape as points\n... |
def rotation_box(box_corners, angle):
'rotation 2d points based on origin point clockwise when angle positive.\n\n Args:\n points (float array, shape=[N, point_size, 2]): points to be rotated.\n angle (float): rotation angle.\n\n Returns:\n float array: same shape as points\n '
rot... | 6,605,383,920,097,669,000 | rotation 2d points based on origin point clockwise when angle positive.
Args:
points (float array, shape=[N, point_size, 2]): points to be rotated.
angle (float): rotation angle.
Returns:
float array: same shape as points | det3d/core/bbox/box_np_ops.py | rotation_box | motional/polarstream | python | def rotation_box(box_corners, angle):
'rotation 2d points based on origin point clockwise when angle positive.\n\n Args:\n points (float array, shape=[N, point_size, 2]): points to be rotated.\n angle (float): rotation angle.\n\n Returns:\n float array: same shape as points\n '
rot... |
def center_to_corner_box3d(centers, dims, angles=None, origin=(0.5, 0.5, 0.5), axis=2):
'convert kitti locations, dimensions and angles to corners\n\n Args:\n centers (float array, shape=[N, 3]): locations in kitti label file.\n dims (float array, shape=[N, 3]): dimensions in kitti label file.\n ... | 4,548,306,000,528,166,000 | convert kitti locations, dimensions and angles to corners
Args:
centers (float array, shape=[N, 3]): locations in kitti label file.
dims (float array, shape=[N, 3]): dimensions in kitti label file.
angles (float array, shape=[N]): rotation_y in kitti label file.
origin (list or array or float): origin ... | det3d/core/bbox/box_np_ops.py | center_to_corner_box3d | motional/polarstream | python | def center_to_corner_box3d(centers, dims, angles=None, origin=(0.5, 0.5, 0.5), axis=2):
'convert kitti locations, dimensions and angles to corners\n\n Args:\n centers (float array, shape=[N, 3]): locations in kitti label file.\n dims (float array, shape=[N, 3]): dimensions in kitti label file.\n ... |
def center_to_corner_box2d(centers, dims, angles=None, origin=0.5):
'convert kitti locations, dimensions and angles to corners.\n format: center(xy), dims(xy), angles(clockwise when positive)\n\n Args:\n centers (float array, shape=[N, 2]): locations in kitti label file.\n dims (float array, sha... | 7,772,419,611,600,366,000 | convert kitti locations, dimensions and angles to corners.
format: center(xy), dims(xy), angles(clockwise when positive)
Args:
centers (float array, shape=[N, 2]): locations in kitti label file.
dims (float array, shape=[N, 2]): dimensions in kitti label file.
angles (float array, shape=[N]): rotation_y in... | det3d/core/bbox/box_np_ops.py | center_to_corner_box2d | motional/polarstream | python | def center_to_corner_box2d(centers, dims, angles=None, origin=0.5):
'convert kitti locations, dimensions and angles to corners.\n format: center(xy), dims(xy), angles(clockwise when positive)\n\n Args:\n centers (float array, shape=[N, 2]): locations in kitti label file.\n dims (float array, sha... |
@numba.jit(nopython=True)
def iou_jit(boxes, query_boxes, eps=1.0):
'calculate box iou. note that jit version runs 2x faster than cython in\n my machine!\n Parameters\n ----------\n boxes: (N, 4) ndarray of float\n query_boxes: (K, 4) ndarray of float\n Returns\n -------\n overlaps: (N, K) n... | -7,542,823,905,533,092,000 | calculate box iou. note that jit version runs 2x faster than cython in
my machine!
Parameters
----------
boxes: (N, 4) ndarray of float
query_boxes: (K, 4) ndarray of float
Returns
-------
overlaps: (N, K) ndarray of overlap between boxes and query_boxes | det3d/core/bbox/box_np_ops.py | iou_jit | motional/polarstream | python | @numba.jit(nopython=True)
def iou_jit(boxes, query_boxes, eps=1.0):
'calculate box iou. note that jit version runs 2x faster than cython in\n my machine!\n Parameters\n ----------\n boxes: (N, 4) ndarray of float\n query_boxes: (K, 4) ndarray of float\n Returns\n -------\n overlaps: (N, K) n... |
@numba.jit(nopython=True)
def iou_3d_jit(boxes, query_boxes, add1=True):
'calculate box iou3d,\n ----------\n boxes: (N, 6) ndarray of float\n query_boxes: (K, 6) ndarray of float\n Returns\n -------\n overlaps: (N, K) ndarray of overlap between boxes and query_boxes\n '
N = boxes.shape[0]
... | -2,774,315,039,072,902,700 | calculate box iou3d,
----------
boxes: (N, 6) ndarray of float
query_boxes: (K, 6) ndarray of float
Returns
-------
overlaps: (N, K) ndarray of overlap between boxes and query_boxes | det3d/core/bbox/box_np_ops.py | iou_3d_jit | motional/polarstream | python | @numba.jit(nopython=True)
def iou_3d_jit(boxes, query_boxes, add1=True):
'calculate box iou3d,\n ----------\n boxes: (N, 6) ndarray of float\n query_boxes: (K, 6) ndarray of float\n Returns\n -------\n overlaps: (N, K) ndarray of overlap between boxes and query_boxes\n '
N = boxes.shape[0]
... |
@numba.jit(nopython=True)
def iou_nd_jit(boxes, query_boxes, add1=True):
'calculate box iou nd, 2x slower than iou_jit.\n ----------\n boxes: (N, ndim * 2) ndarray of float\n query_boxes: (K, ndim * 2) ndarray of float\n Returns\n -------\n overlaps: (N, K) ndarray of overlap between boxes and que... | -5,011,801,594,874,465,000 | calculate box iou nd, 2x slower than iou_jit.
----------
boxes: (N, ndim * 2) ndarray of float
query_boxes: (K, ndim * 2) ndarray of float
Returns
-------
overlaps: (N, K) ndarray of overlap between boxes and query_boxes | det3d/core/bbox/box_np_ops.py | iou_nd_jit | motional/polarstream | python | @numba.jit(nopython=True)
def iou_nd_jit(boxes, query_boxes, add1=True):
'calculate box iou nd, 2x slower than iou_jit.\n ----------\n boxes: (N, ndim * 2) ndarray of float\n query_boxes: (K, ndim * 2) ndarray of float\n Returns\n -------\n overlaps: (N, K) ndarray of overlap between boxes and que... |
def corner_to_surfaces_3d(corners):
'convert 3d box corners from corner function above\n to surfaces that normal vectors all direct to internal.\n\n Args:\n corners (float array, [N, 8, 3]): 3d box corners.\n Returns:\n surfaces (float array, [N, 6, 4, 3]):\n '
surfaces = np.array([[co... | -3,105,657,895,945,397,000 | convert 3d box corners from corner function above
to surfaces that normal vectors all direct to internal.
Args:
corners (float array, [N, 8, 3]): 3d box corners.
Returns:
surfaces (float array, [N, 6, 4, 3]): | det3d/core/bbox/box_np_ops.py | corner_to_surfaces_3d | motional/polarstream | python | def corner_to_surfaces_3d(corners):
'convert 3d box corners from corner function above\n to surfaces that normal vectors all direct to internal.\n\n Args:\n corners (float array, [N, 8, 3]): 3d box corners.\n Returns:\n surfaces (float array, [N, 6, 4, 3]):\n '
surfaces = np.array([[co... |
@numba.jit(nopython=True)
def corner_to_surfaces_3d_jit(corners):
'convert 3d box corners from corner function above\n to surfaces that normal vectors all direct to internal.\n\n Args:\n corners (float array, [N, 8, 3]): 3d box corners.\n Returns:\n surfaces (float array, [N, 6, 4, 3]):\n ... | 8,323,415,292,507,754,000 | convert 3d box corners from corner function above
to surfaces that normal vectors all direct to internal.
Args:
corners (float array, [N, 8, 3]): 3d box corners.
Returns:
surfaces (float array, [N, 6, 4, 3]): | det3d/core/bbox/box_np_ops.py | corner_to_surfaces_3d_jit | motional/polarstream | python | @numba.jit(nopython=True)
def corner_to_surfaces_3d_jit(corners):
'convert 3d box corners from corner function above\n to surfaces that normal vectors all direct to internal.\n\n Args:\n corners (float array, [N, 8, 3]): 3d box corners.\n Returns:\n surfaces (float array, [N, 6, 4, 3]):\n ... |
def assign_label_to_voxel(gt_boxes, coors, voxel_size, coors_range):
'assign a 0/1 label to each voxel based on whether\n the center of voxel is in gt_box. LIDAR.\n '
voxel_size = np.array(voxel_size, dtype=gt_boxes.dtype)
coors_range = np.array(coors_range, dtype=gt_boxes.dtype)
shift = coors_ran... | 8,134,859,055,966,454,000 | assign a 0/1 label to each voxel based on whether
the center of voxel is in gt_box. LIDAR. | det3d/core/bbox/box_np_ops.py | assign_label_to_voxel | motional/polarstream | python | def assign_label_to_voxel(gt_boxes, coors, voxel_size, coors_range):
'assign a 0/1 label to each voxel based on whether\n the center of voxel is in gt_box. LIDAR.\n '
voxel_size = np.array(voxel_size, dtype=gt_boxes.dtype)
coors_range = np.array(coors_range, dtype=gt_boxes.dtype)
shift = coors_ran... |
def assign_label_to_voxel_v3(gt_boxes, coors, voxel_size, coors_range):
'assign a 0/1 label to each voxel based on whether\n the center of voxel is in gt_box. LIDAR.\n '
voxel_size = np.array(voxel_size, dtype=gt_boxes.dtype)
coors_range = np.array(coors_range, dtype=gt_boxes.dtype)
shift = coors_... | 4,818,000,534,278,983,000 | assign a 0/1 label to each voxel based on whether
the center of voxel is in gt_box. LIDAR. | det3d/core/bbox/box_np_ops.py | assign_label_to_voxel_v3 | motional/polarstream | python | def assign_label_to_voxel_v3(gt_boxes, coors, voxel_size, coors_range):
'assign a 0/1 label to each voxel based on whether\n the center of voxel is in gt_box. LIDAR.\n '
voxel_size = np.array(voxel_size, dtype=gt_boxes.dtype)
coors_range = np.array(coors_range, dtype=gt_boxes.dtype)
shift = coors_... |
def image_box_region_area(img_cumsum, bbox):
'check a 2d voxel is contained by a box. used to filter empty\n anchors.\n Summed-area table algorithm:\n ==> W\n ------------------\n | | |\n |------A---------B\n | | |\n | | |\n |----- C---------D\n I... | 5,212,201,778,767,590,000 | check a 2d voxel is contained by a box. used to filter empty
anchors.
Summed-area table algorithm:
==> W
------------------
| | |
|------A---------B
| | |
| | |
|----- C---------D
Iabcd = ID-IB-IC+IA
Args:
img_cumsum: [M, H, W](yx) cumsumed image.
bbox: [N, 4](xyxy) boundi... | det3d/core/bbox/box_np_ops.py | image_box_region_area | motional/polarstream | python | def image_box_region_area(img_cumsum, bbox):
'check a 2d voxel is contained by a box. used to filter empty\n anchors.\n Summed-area table algorithm:\n ==> W\n ------------------\n | | |\n |------A---------B\n | | |\n | | |\n |----- C---------D\n I... |
def __init__(self):
'\n\t\tCreates the himesis graph representing the AToM3 model HContractUnitR03_ConnectedLHS\n\t\t'
self.is_compiled = True
super(HContractUnitR03_ConnectedLHS, self).__init__(name='HContractUnitR03_ConnectedLHS', num_nodes=0, edges=[])
self.add_edges([])
self['mm__'] = ['MT_pre__... | -8,516,995,704,198,999,000 | Creates the himesis graph representing the AToM3 model HContractUnitR03_ConnectedLHS | UML2ER/contracts/unit/HContractUnitR03_ConnectedLHS.py | __init__ | levilucio/SyVOLT | python | def __init__(self):
'\n\t\t\n\t\t'
self.is_compiled = True
super(HContractUnitR03_ConnectedLHS, self).__init__(name='HContractUnitR03_ConnectedLHS', num_nodes=0, edges=[])
self.add_edges([])
self['mm__'] = ['MT_pre__FamiliesToPersonsMM', 'MoTifRule']
self['MT_constraint__'] = 'return True'
s... |
def rand_permute_adj_matrix(matrix):
'Randomly permute the order of vertices in the adjacency matrix, while maintaining the connectivity\n between them.'
num_vertices = matrix.shape[0]
rand_order = np.arange(num_vertices)
np.random.shuffle(rand_order)
matrix_permuted = rearrange_adj_matrix(matrix... | 2,072,083,524,283,573,000 | Randomly permute the order of vertices in the adjacency matrix, while maintaining the connectivity
between them. | utils/graph_utils.py | rand_permute_adj_matrix | BrunoKM/rhoana_graph_tools | python | def rand_permute_adj_matrix(matrix):
'Randomly permute the order of vertices in the adjacency matrix, while maintaining the connectivity\n between them.'
num_vertices = matrix.shape[0]
rand_order = np.arange(num_vertices)
np.random.shuffle(rand_order)
matrix_permuted = rearrange_adj_matrix(matrix... |
def ged_from_adj(adj_mat_1, adj_mat_2, directed=False, ged_function=graph_edit_dist.compare):
'Calculate the graph edit distance between two graphs'
if directed:
create_using = nx.DiGraph
else:
create_using = nx.Graph
g1 = nx.from_numpy_matrix(adj_mat_1, create_using=create_using())
... | -1,019,193,061,419,621,200 | Calculate the graph edit distance between two graphs | utils/graph_utils.py | ged_from_adj | BrunoKM/rhoana_graph_tools | python | def ged_from_adj(adj_mat_1, adj_mat_2, directed=False, ged_function=graph_edit_dist.compare):
if directed:
create_using = nx.DiGraph
else:
create_using = nx.Graph
g1 = nx.from_numpy_matrix(adj_mat_1, create_using=create_using())
g2 = nx.from_numpy_matrix(adj_mat_2, create_using=crea... |
def ged_from_adj_nx(adj_mat_1, adj_mat_2, directed=False):
'Calculate the graph edit distance between two graphs using the networkx implementation'
return ged_from_adj(adj_mat_1, adj_mat_2, directed=directed, ged_function=nx.graph_edit_distance) | -6,871,451,744,190,802,000 | Calculate the graph edit distance between two graphs using the networkx implementation | utils/graph_utils.py | ged_from_adj_nx | BrunoKM/rhoana_graph_tools | python | def ged_from_adj_nx(adj_mat_1, adj_mat_2, directed=False):
return ged_from_adj(adj_mat_1, adj_mat_2, directed=directed, ged_function=nx.graph_edit_distance) |
def ged_from_adj_ged4py(adj_mat_1, adj_mat_2, directed=False):
'Calculate the graph edit distance between two graphs using the ged4py implementation'
return ged_from_adj(adj_mat_1, adj_mat_2, directed=directed, ged_function=graph_edit_dist.compare) | -2,015,968,644,657,250,800 | Calculate the graph edit distance between two graphs using the ged4py implementation | utils/graph_utils.py | ged_from_adj_ged4py | BrunoKM/rhoana_graph_tools | python | def ged_from_adj_ged4py(adj_mat_1, adj_mat_2, directed=False):
return ged_from_adj(adj_mat_1, adj_mat_2, directed=directed, ged_function=graph_edit_dist.compare) |
def is_isomorphic_from_adj(adj_mat_1, adj_mat_2):
'Checks whether two graphs are isomorphic taking adjacency matrices as inputs'
g1 = nx.from_numpy_matrix(adj_mat_1, create_using=nx.DiGraph())
g2 = nx.from_numpy_matrix(adj_mat_2, create_using=nx.DiGraph())
return nx.is_isomorphic(g1, g2) | 5,955,937,699,591,090,000 | Checks whether two graphs are isomorphic taking adjacency matrices as inputs | utils/graph_utils.py | is_isomorphic_from_adj | BrunoKM/rhoana_graph_tools | python | def is_isomorphic_from_adj(adj_mat_1, adj_mat_2):
g1 = nx.from_numpy_matrix(adj_mat_1, create_using=nx.DiGraph())
g2 = nx.from_numpy_matrix(adj_mat_2, create_using=nx.DiGraph())
return nx.is_isomorphic(g1, g2) |
def train(self, epoch: int) -> None:
'\n Train an epoch\n\n Parameters\n ----------\n epoch : int\n Current number of epoch\n '
self.decoder.train()
self.encoder.train()
batch_time = AverageMeter()
data_time = AverageMeter()
losses = AverageMeter(tag... | 6,085,474,841,145,883,000 | Train an epoch
Parameters
----------
epoch : int
Current number of epoch | trainer/trainer.py | train | Renovamen/Image-Caption | python | def train(self, epoch: int) -> None:
'\n Train an epoch\n\n Parameters\n ----------\n epoch : int\n Current number of epoch\n '
self.decoder.train()
self.encoder.train()
batch_time = AverageMeter()
data_time = AverageMeter()
losses = AverageMeter(tag... |
def validate(self) -> float:
'\n Validate an epoch.\n\n Returns\n -------\n bleu4 : float\n BLEU-4 score\n '
self.decoder.eval()
if (self.encoder is not None):
self.encoder.eval()
batch_time = AverageMeter()
losses = AverageMeter()
top5accs =... | 3,469,363,881,887,474,700 | Validate an epoch.
Returns
-------
bleu4 : float
BLEU-4 score | trainer/trainer.py | validate | Renovamen/Image-Caption | python | def validate(self) -> float:
'\n Validate an epoch.\n\n Returns\n -------\n bleu4 : float\n BLEU-4 score\n '
self.decoder.eval()
if (self.encoder is not None):
self.encoder.eval()
batch_time = AverageMeter()
losses = AverageMeter()
top5accs =... |
def _get_all_query_string(self, changelist):
"\n If there's a default value set the all parameter needs to be provided\n however, if a default is not set the all parameter is not required.\n "
if self.default_filter_value:
return changelist.get_query_string({self.parameter_name: sel... | 7,343,347,246,114,303,000 | If there's a default value set the all parameter needs to be provided
however, if a default is not set the all parameter is not required. | djangocms_content_expiry/filters.py | _get_all_query_string | Aiky30/djangocms-content-expiry | python | def _get_all_query_string(self, changelist):
"\n If there's a default value set the all parameter needs to be provided\n however, if a default is not set the all parameter is not required.\n "
if self.default_filter_value:
return changelist.get_query_string({self.parameter_name: sel... |
@core.flake8ext
def hacking_no_locals(logical_line, physical_line, tokens, noqa):
'Do not use locals() or self.__dict__ for string formatting.\n\n Okay: \'locals()\'\n Okay: \'locals\'\n Okay: locals()\n Okay: print(locals())\n H501: print("%(something)" % locals())\n H501: LOG.info(_("%(something... | 7,383,045,247,385,087,000 | Do not use locals() or self.__dict__ for string formatting.
Okay: 'locals()'
Okay: 'locals'
Okay: locals()
Okay: print(locals())
H501: print("%(something)" % locals())
H501: LOG.info(_("%(something)") % self.__dict__)
Okay: print("%(something)" % locals()) # noqa | hacking/checks/dictlist.py | hacking_no_locals | UbuntuEvangelist/hacking | python | @core.flake8ext
def hacking_no_locals(logical_line, physical_line, tokens, noqa):
'Do not use locals() or self.__dict__ for string formatting.\n\n Okay: \'locals()\'\n Okay: \'locals\'\n Okay: locals()\n Okay: print(locals())\n H501: print("%(something)" % locals())\n H501: LOG.info(_("%(something... |
def deal_card():
'Return random card'
cards = [11, 2, 3, 4, 5, 6, 7, 8, 9, 10, 10, 10, 10]
card = random.choice(cards)
return card | -3,847,650,605,205,713,000 | Return random card | Programs/day_11_blackjack.py | deal_card | Yunram/python_training | python | def deal_card():
cards = [11, 2, 3, 4, 5, 6, 7, 8, 9, 10, 10, 10, 10]
card = random.choice(cards)
return card |
def calculate_score(cards):
'Take a list of cards and return the score'
if ((sum(cards) == 21) and (len(cards) == 2)):
return 0
if ((11 in cards) and (sum(cards) > 21)):
cards.remove(11)
cards.append(1)
return sum(cards) | 6,349,374,628,700,159,000 | Take a list of cards and return the score | Programs/day_11_blackjack.py | calculate_score | Yunram/python_training | python | def calculate_score(cards):
if ((sum(cards) == 21) and (len(cards) == 2)):
return 0
if ((11 in cards) and (sum(cards) > 21)):
cards.remove(11)
cards.append(1)
return sum(cards) |
def jupyterbook():
'\n Create content and TOC for building a jupyter-book version 0.8: https://jupyterbook.org/intro\n\n This function is called directly from bin/doconce\n '
if (len(sys.argv) < 2):
doconce_version()
print(docstring_jupyterbook)
print("Try 'doconce jupyterbook -... | 5,549,780,974,407,250,000 | Create content and TOC for building a jupyter-book version 0.8: https://jupyterbook.org/intro
This function is called directly from bin/doconce | lib/doconce/jupyterbook.py | jupyterbook | aless80/doconce | python | def jupyterbook():
'\n Create content and TOC for building a jupyter-book version 0.8: https://jupyterbook.org/intro\n\n This function is called directly from bin/doconce\n '
if (len(sys.argv) < 2):
doconce_version()
print(docstring_jupyterbook)
print("Try 'doconce jupyterbook -... |
def split_file(filestr, separator):
"Split the text of a doconce file by a regex string.\n\n Split the text of a doconce file by a separator regex (e.g. the values of\n the INLINE_TAGS dictionary from common.py) and return the chunks of text.\n Note that the first chunk contains any text before the first s... | -3,129,595,768,777,523,700 | Split the text of a doconce file by a regex string.
Split the text of a doconce file by a separator regex (e.g. the values of
the INLINE_TAGS dictionary from common.py) and return the chunks of text.
Note that the first chunk contains any text before the first separator.
:param str filestr: text string
:param str sepa... | lib/doconce/jupyterbook.py | split_file | aless80/doconce | python | def split_file(filestr, separator):
"Split the text of a doconce file by a regex string.\n\n Split the text of a doconce file by a separator regex (e.g. the values of\n the INLINE_TAGS dictionary from common.py) and return the chunks of text.\n Note that the first chunk contains any text before the first s... |
def split_ipynb(ipynb_text, filenames):
'Split a Jupyter notebook based on filenames present in its blocks\n\n Given the text of a Jupyter notebook marked with the output filename\n in comments (e.g. <!-- jupyter-book 02_mybook.ipynb -->), return a list of\n Jupyter notebooks separated accordingly.\n :p... | 985,091,436,715,346,400 | Split a Jupyter notebook based on filenames present in its blocks
Given the text of a Jupyter notebook marked with the output filename
in comments (e.g. <!-- jupyter-book 02_mybook.ipynb -->), return a list of
Jupyter notebooks separated accordingly.
:param str ipynb_text: ipynb code marked with individual filenames i... | lib/doconce/jupyterbook.py | split_ipynb | aless80/doconce | python | def split_ipynb(ipynb_text, filenames):
'Split a Jupyter notebook based on filenames present in its blocks\n\n Given the text of a Jupyter notebook marked with the output filename\n in comments (e.g. <!-- jupyter-book 02_mybook.ipynb -->), return a list of\n Jupyter notebooks separated accordingly.\n :p... |
def read_title_file(titles_opt, chapters, sec_list):
"Helper function to read and process a file with titles\n\n Read the file containing titles and process them according to the number of jupyter-book chapters and sections.\n len(sec_list) should be the same as len(chapters), and its elements can be empty li... | 1,563,216,286,263,243,000 | Helper function to read and process a file with titles
Read the file containing titles and process them according to the number of jupyter-book chapters and sections.
len(sec_list) should be the same as len(chapters), and its elements can be empty lists
:param str titles_opt: 'auto' or file containing titles
:param li... | lib/doconce/jupyterbook.py | read_title_file | aless80/doconce | python | def read_title_file(titles_opt, chapters, sec_list):
"Helper function to read and process a file with titles\n\n Read the file containing titles and process them according to the number of jupyter-book chapters and sections.\n len(sec_list) should be the same as len(chapters), and its elements can be empty li... |
def titles_to_chunks(chunks, title_list, sep, sep2=None, chapter_formatter='%02d_', tags=INLINE_TAGS):
'Helper function to extract assign titles to jupyter-book chapters/sections (here called chunks)\n\n Jupyter-book files must have a # header with the title (see doc jupyter-book >\n Types of content source f... | -4,218,107,978,038,146,000 | Helper function to extract assign titles to jupyter-book chapters/sections (here called chunks)
Jupyter-book files must have a # header with the title (see doc jupyter-book >
Types of content source files > Rules for all content types). This function
extracts title from the title file or from the headers given by the ... | lib/doconce/jupyterbook.py | titles_to_chunks | aless80/doconce | python | def titles_to_chunks(chunks, title_list, sep, sep2=None, chapter_formatter='%02d_', tags=INLINE_TAGS):
'Helper function to extract assign titles to jupyter-book chapters/sections (here called chunks)\n\n Jupyter-book files must have a # header with the title (see doc jupyter-book >\n Types of content source f... |
def create_title(chunk, sep, tags):
"Helper function to allow doconce jupyterbook to automatically assign titles in the TOC\n\n If a chunk of text starts with the section specified in sep, lift it up\n to a chapter section. This allows doconce jupyterbook to automatically use the\n section's text as title ... | 746,731,705,735,869,800 | Helper function to allow doconce jupyterbook to automatically assign titles in the TOC
If a chunk of text starts with the section specified in sep, lift it up
to a chapter section. This allows doconce jupyterbook to automatically use the
section's text as title in the TOC on the left
:param str chunk: text string
:pa... | lib/doconce/jupyterbook.py | create_title | aless80/doconce | python | def create_title(chunk, sep, tags):
"Helper function to allow doconce jupyterbook to automatically assign titles in the TOC\n\n If a chunk of text starts with the section specified in sep, lift it up\n to a chapter section. This allows doconce jupyterbook to automatically use the\n section's text as title ... |
def identify_format(text_list):
"Identify the appropriate formats to convert a list of DocOnce texts.\n\n Given a list of DocOnce texts, check if they contain code. If so, return the suffix\n '.ipynb' (for the Jupyter Notebook ipynb format), otherwise return '.md' (for\n the pandoc markdown format).\n :... | -6,315,886,050,878,515,000 | Identify the appropriate formats to convert a list of DocOnce texts.
Given a list of DocOnce texts, check if they contain code. If so, return the suffix
'.ipynb' (for the Jupyter Notebook ipynb format), otherwise return '.md' (for
the pandoc markdown format).
:param list[str] text_list: list of strings using DocOnce s... | lib/doconce/jupyterbook.py | identify_format | aless80/doconce | python | def identify_format(text_list):
"Identify the appropriate formats to convert a list of DocOnce texts.\n\n Given a list of DocOnce texts, check if they contain code. If so, return the suffix\n '.ipynb' (for the Jupyter Notebook ipynb format), otherwise return '.md' (for\n the pandoc markdown format).\n :... |
def create_toc_yml(basenames, nesting_levels, titles, dest='./', dest_toc='./', section_paths=None, section_titles=None):
'Create the content of a _toc.yml file\n\n Give the lists of paths, titles, and nesting levels, return the content of a _toc.yml file\n :param list[str] basenames: list of file bas... | -2,230,910,722,808,470,300 | Create the content of a _toc.yml file
Give the lists of paths, titles, and nesting levels, return the content of a _toc.yml file
:param list[str] basenames: list of file basenames for jupyter-book chapters or sections, i.e.
strings that can be used after the `file:` section in a _toc.yml
:param list[str] titles: list ... | lib/doconce/jupyterbook.py | create_toc_yml | aless80/doconce | python | def create_toc_yml(basenames, nesting_levels, titles, dest='./', dest_toc='./', section_paths=None, section_titles=None):
'Create the content of a _toc.yml file\n\n Give the lists of paths, titles, and nesting levels, return the content of a _toc.yml file\n :param list[str] basenames: list of file bas... |
def print_help_jupyterbook():
'Pretty print help string and command line options\n\n Help function to print help and formatted command line options for doconce jupyterbook\n '
print(docstring_jupyterbook)
print('Options:')
help_print_options(cmdline_opts=_registered_cmdline_opts_jupyterbook) | -513,857,317,894,164,030 | Pretty print help string and command line options
Help function to print help and formatted command line options for doconce jupyterbook | lib/doconce/jupyterbook.py | print_help_jupyterbook | aless80/doconce | python | def print_help_jupyterbook():
'Pretty print help string and command line options\n\n Help function to print help and formatted command line options for doconce jupyterbook\n '
print(docstring_jupyterbook)
print('Options:')
help_print_options(cmdline_opts=_registered_cmdline_opts_jupyterbook) |
def read_to_list(file):
'Read the content of a file to list\n\n Verify the existence of a file, then read it to a list by\n stripping newlines. The function aborts the program if the file does not exist.\n\n :param str file: Path to an existing file\n :return: list of strings\n :rtype: list[str]\n ... | -1,171,378,323,079,902,700 | Read the content of a file to list
Verify the existence of a file, then read it to a list by
stripping newlines. The function aborts the program if the file does not exist.
:param str file: Path to an existing file
:return: list of strings
:rtype: list[str] | lib/doconce/jupyterbook.py | read_to_list | aless80/doconce | python | def read_to_list(file):
'Read the content of a file to list\n\n Verify the existence of a file, then read it to a list by\n stripping newlines. The function aborts the program if the file does not exist.\n\n :param str file: Path to an existing file\n :return: list of strings\n :rtype: list[str]\n ... |
def get_link_destinations(chunk):
'Find any target of a link in HTML code\n\n Use regex to find tags with the id or name attribute, which makes them a possible target of a link\n :param str chunk: text string\n :return: destinations, destination_tags\n :rtype: Tuple[list[str], list[str]]\n '
(des... | 6,399,748,933,904,265,000 | Find any target of a link in HTML code
Use regex to find tags with the id or name attribute, which makes them a possible target of a link
:param str chunk: text string
:return: destinations, destination_tags
:rtype: Tuple[list[str], list[str]] | lib/doconce/jupyterbook.py | get_link_destinations | aless80/doconce | python | def get_link_destinations(chunk):
'Find any target of a link in HTML code\n\n Use regex to find tags with the id or name attribute, which makes them a possible target of a link\n :param str chunk: text string\n :return: destinations, destination_tags\n :rtype: Tuple[list[str], list[str]]\n '
(des... |
def fix_links(chunk, tag2file):
'Find and fix the the destinations of hyperlinks using HTML or markdown syntax\n\n Fix any link in a string text so that they can target a different html document.\n First use regex on a HTML text to find any HTML or markdown hyperlinks\n (e.g. <a href="#sec1"> or [sec1](#se... | 9,217,471,721,488,170,000 | Find and fix the the destinations of hyperlinks using HTML or markdown syntax
Fix any link in a string text so that they can target a different html document.
First use regex on a HTML text to find any HTML or markdown hyperlinks
(e.g. <a href="#sec1"> or [sec1](#sec1) ). Then use a dictionary to prepend the
filename ... | lib/doconce/jupyterbook.py | fix_links | aless80/doconce | python | def fix_links(chunk, tag2file):
'Find and fix the the destinations of hyperlinks using HTML or markdown syntax\n\n Fix any link in a string text so that they can target a different html document.\n First use regex on a HTML text to find any HTML or markdown hyperlinks\n (e.g. <a href="#sec1"> or [sec1](#se... |
def resolve_links_destinations(chunks, chunk_basenames):
'Fix links in jupyter-book chapters/sections so that they can target destinations in other files\n\n Prepend a filename to all links\' destinations e.g. <a href="#Langtangen_2012"> becomes\n <a href="02_jupyterbook.html#Langtangen_2012">\n :param lis... | 5,405,938,629,762,071,000 | Fix links in jupyter-book chapters/sections so that they can target destinations in other files
Prepend a filename to all links' destinations e.g. <a href="#Langtangen_2012"> becomes
<a href="02_jupyterbook.html#Langtangen_2012">
:param list[str] chunks: DocOnce texts consisting in Jupyter-book chapters/sections
:para... | lib/doconce/jupyterbook.py | resolve_links_destinations | aless80/doconce | python | def resolve_links_destinations(chunks, chunk_basenames):
'Fix links in jupyter-book chapters/sections so that they can target destinations in other files\n\n Prepend a filename to all links\' destinations e.g. <a href="#Langtangen_2012"> becomes\n <a href="02_jupyterbook.html#Langtangen_2012">\n :param lis... |
def fix_media_src(filestr, dirname, dest):
'Fix the (relative) path to any figure and movie in the DocOnce file.\n\n The generated .md and .ipynb files will be created in the path passed to `--dest`.\n This method fixes the paths of the image and movie files so that they can be found\n in generated .md and... | 358,296,290,649,753,860 | Fix the (relative) path to any figure and movie in the DocOnce file.
The generated .md and .ipynb files will be created in the path passed to `--dest`.
This method fixes the paths of the image and movie files so that they can be found
in generated .md and .ipynb files.
:param str filestr: text string
:param str dirnam... | lib/doconce/jupyterbook.py | fix_media_src | aless80/doconce | python | def fix_media_src(filestr, dirname, dest):
'Fix the (relative) path to any figure and movie in the DocOnce file.\n\n The generated .md and .ipynb files will be created in the path passed to `--dest`.\n This method fixes the paths of the image and movie files so that they can be found\n in generated .md and... |
def escape_chars(title):
'Wrap title in quotes if it contains colons, asterisks, bacticks'
if (re.search(':', title) or re.search('\\*', title) or re.search('\\`', title)):
title = title.replace('"', '\\"')
title = (('"' + title) + '"')
return title | -4,069,678,415,874,223,600 | Wrap title in quotes if it contains colons, asterisks, bacticks | lib/doconce/jupyterbook.py | escape_chars | aless80/doconce | python | def escape_chars(title):
if (re.search(':', title) or re.search('\\*', title) or re.search('\\`', title)):
title = title.replace('"', '\\"')
title = (('"' + title) + '"')
return title |
def mae(y_true, y_pred):
' Implementation of Mean average error\n '
return K.mean(K.abs((y_true - y_pred))) | 8,321,551,904,465,290,000 | Implementation of Mean average error | raynet/models.py | mae | paschalidoud/raynet | python | def mae(y_true, y_pred):
' \n '
return K.mean(K.abs((y_true - y_pred))) |
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