def getCategoryName(self, sentenceGraph, e1, e2, directed=True):
# Dummies are potential entities that do not exist in the
# training data. If both entities of an interaction are dummies
# it can't exist in the training data and is therefore a negative
if e1[2] or e2[2]:
return "neg"
e1 = e1[0]
e2 = e2[0]
interactions = sentenceGraph.getInteractions(e1, e2)
if not directed:
interactions.extend(sentenceGraph.getInteractions(e2, e1))
types = set()
for interaction in interactions:
types.add(interaction.attrib["type"])
types = list(types)
types.sort()
categoryName = ""
for name in types:
if categoryName != "":
categoryName += "---"
categoryName += name
if categoryName != "":
return categoryName
else:
return "neg"
def getWx(wxtypes, wxvisibilities):
from com.raytheon.uf.common.dataplugin.gfe.weather import WeatherCoverage, WeatherIntensity, WeatherAttribute
from com.raytheon.edex.plugin.gfe.config import SimpleWeatherTypeConfig
types = ArrayList()
for t in wxtypes:
symbol, description, cov, inten, attr = \
check(t, (str, str, list, list, list), "Error in WeatherType")
coverages = ArrayList()
intensities = ArrayList()
attributes = ArrayList()
for c in cov:
csym, cdes = check(c, (str, str), "Error in Weather Coverage", t)
coverages.add(WeatherCoverage(csym, cdes))
for i in inten:
isym, ides = check(i, (str, str), "Error in Weather Intensity", t)
intensities.add(WeatherIntensity(isym, ides))
for a in attr:
asym, ades = check(a, (str, str), "Error in Weather Attributes", t)
attributes.add(WeatherAttribute(asym, ades))
types.add(SimpleWeatherTypeConfig(symbol, description, coverages,
intensities, attributes))
vis = ArrayList()
for v in wxvisibilities:
vis.add(v)
return (vis, types)
def getWx(wxtypes, wxvisibilities):
from com.raytheon.uf.common.dataplugin.gfe.weather import WeatherCoverage, WeatherIntensity, WeatherAttribute
from com.raytheon.edex.plugin.gfe.config import SimpleWeatherTypeConfig
types = ArrayList()
for t in wxtypes:
symbol, description, cov, inten, attr = \
check(t, (str, str, list, list, list), "Error in WeatherType")
coverages = ArrayList()
intensities = ArrayList()
attributes = ArrayList()
for c in cov:
csym, cdes = check(c, (str, str), "Error in Weather Coverage", t)
coverages.add(WeatherCoverage(csym, cdes))
for i in inten:
isym, ides = check(i, (str, str), "Error in Weather Intensity", t)
intensities.add(WeatherIntensity(isym, ides))
for a in attr:
asym, ades = check(a, (str, str), "Error in Weather Attributes", t)
attributes.add(WeatherAttribute(asym, ades))
types.add(
SimpleWeatherTypeConfig(symbol, description, coverages,
intensities, attributes))
vis = ArrayList()
for v in wxvisibilities:
vis.add(v)
return (vis, types)
def lord_types(self):
"""Return a set of names of all lords in this legion."""
types = set()
for creature in self.creatures:
if creature.is_lord:
types.add(creature.name)
return types
def getCategoryName(self, sentenceGraph, e1, e2, directed=True):
# Dummies are potential entities that do not exist in the
# training data. If both entities of an interaction are dummies
# it can't exist in the training data and is therefore a negative
if e1[2] or e2[2]:
return "neg"
e1 = e1[0]
e2 = e2[0]
interactions = sentenceGraph.getInteractions(e1, e2)
if not directed:
interactions.extend(sentenceGraph.getInteractions(e2, e1))
types = set()
for interaction in interactions:
types.add(interaction.attrib["type"])
types = list(types)
types.sort()
categoryName = ""
for name in types:
if categoryName != "":
categoryName += "---"
categoryName += name
if categoryName != "":
return categoryName
else:
return "neg"
def lord_types(self):
"""Return a set of names of all lords in this legion."""
types = set()
for creature in self.creatures:
if creature.is_lord:
types.add(creature.name)
return types
def types():
types = set()
for t in _.__dict__.values():
if isinstance(t, Type):
types.add(t)
t = list(t)
return t
def getCategoryName(self, sentence1, sentence2, e1, e2, directed=True):
"""
Example class. Multiple overlapping edges create a merged type.
"""
e1Id = e1.get("id")
e2Id = e2.get("id")
allInteractions = sentence1.interSentenceInteractions + sentence2.interSentenceInteractions
interactions = []
#if len(allInteractions) > 0:
# print len(allInteractions)
for interaction in allInteractions:
if interaction.get("e1") == e1Id and interaction.get("e2") == e2Id:
interactions.append(interaction)
types = set()
for interaction in interactions:
types.add(interaction.get("type"))
types = list(types)
types.sort()
categoryName = ""
for name in types:
if categoryName != "":
categoryName += "---"
categoryName += name
if categoryName != "":
return categoryName
else:
return "neg"
def all_instruments(type=None, date=None):
# type: (str, Union[str, datetime, date]) -> pd.DataFrame
"""
获取某个国家市场的所有合约信息。使用者可以通过这一方法很快地对合约信息有一个快速了解，目前仅支持中国市场。
:param type: 需要查询合约类型，例如：type='CS'代表股票。默认是所有类型
:param date: 查询时间点
其中type参数传入的合约类型和对应的解释如下：
========================= ===================================================
合约类型 说明
========================= ===================================================
CS Common Stock, 即股票
ETF Exchange Traded Fund, 即交易所交易基金
LOF Listed Open-Ended Fund，即上市型开放式基金
INDX Index, 即指数
Future Futures，即期货，包含股指、国债和商品期货
========================= ===================================================
"""
env = Environment.get_instance()
if date is None:
dt = env.trading_dt
else:
dt = pd.Timestamp(date).to_pydatetime()
dt = min(dt, env.trading_dt)
if type is not None:
if isinstance(type, six.string_types):
type = [type]
types = set()
for t in type:
if t == "Stock":
types.add("CS")
elif t == "Fund":
types.update(["ETF", "LOF"])
else:
types.add(t)
else:
types = None
result = env.data_proxy.all_instruments(types, dt)
if types is not None and len(types) == 1:
data = []
for i in result:
instrument_dic = {k: v for k, v in i.__dict__.items() if not k.startswith("_")}
data.append(instrument_dic)
return pd.DataFrame(data)
return pd.DataFrame(
[
[i.order_book_id, i.symbol, i.type, i.listed_date, i.de_listed_date]
for i in result
],
columns=["order_book_id", "symbol", "type", "listed_date", "de_listed_date"],
)
def find_simple(self, seen):
types = set()
for type in self.types:
if type.is_promotion:
types.add(type.types)
else:
type.add(type)
return types
def infer(self):
p = self._signature_param
evaluator = self.parent_context.evaluator
types = set()
if p.default is not p.empty:
types.add(create(evaluator, p.default))
if p.annotation is not p.empty:
annotation = create(evaluator, p.annotation)
types |= annotation.execute_evaluated()
return types
def infer(self):
p = self._signature_param
evaluator = self.parent_context.evaluator
types = set()
if p.default is not p.empty:
types.add(create(evaluator, p.default))
if p.annotation is not p.empty:
annotation = create(evaluator, p.annotation)
types |= annotation.execute_evaluated()
return types
def dfs(self, types, seen):
for type in self.types:
if type not in seen:
seen.add(type)
type = resolve_type_chain(type)
seen.add(type)
if type.is_promotion:
type.dfs(types, seen)
elif not type.is_uninitialized:
types.add(type)
def __cast_to_general_type(self):
types = set()
for coordinate in self._coordinates:
if isinstance(coordinate, numbers.Number):
types.add(type(coordinate))
else:
coordinate = self._parse(coordinate, (int, float, complex))
types.add(type(coordinate))
for i in (complex, float, int):
if i in types:
self._coordinates = [i(elem) for elem in self._coordinates]
break
def add_type(self, seen, type, types):
if type not in seen:
if type.is_unresolved:
seen.add(type)
new_type = type.resolve()
if new_type is not type:
seen.add(new_type)
self.add_type(seen, new_type, types)
type = new_type
else:
types.add(type)
else:
types.add(type)
return type
def getMergedEntityType(self, entities):
"""
If a single token belongs to multiple entities of different types,
a new, composite type is defined. This type is the alphabetically
ordered types of these entities joined with '---'.
"""
types = set()
for entity in entities:
types.add(entity.get("type"))
types = list(types)
types.sort()
typeString = ""
for type in types:
if typeString != "":
typeString += "---"
typeString += type
return typeString
def getMergedEntityType(self, entities):
"""
If a single token belongs to multiple entities of different types,
a new, composite type is defined. This type is the alphabetically
ordered types of these entities joined with '---'.
"""
types = set()
for entity in entities:
types.add(entity.get("type"))
types = list(types)
types.sort()
typeString = ""
for type in types:
if typeString != "":
typeString += "---"
typeString += type
return typeString
def all_instruments(type=None, date=None):
"""
获取某个国家市场的所有合约信息。使用者可以通过这一方法很快地对合约信息有一个快速了解，目前仅支持中国市场。
:param str type: 需要查询合约类型，例如：type='CS'代表股票。默认是所有类型
:param date: 查询时间点
:type date: `str` | `datetime` | `date`
:return: `pandas DataFrame` 所有合约的基本信息。
其中type参数传入的合约类型和对应的解释如下：
========================= ===================================================
合约类型 说明
========================= ===================================================
CS Common Stock, 即股票
ETF Exchange Traded Fund, 即交易所交易基金
LOF Listed Open-Ended Fund，即上市型开放式基金
FenjiMu Fenji Mu Fund, 即分级母基金
FenjiA Fenji A Fund, 即分级A类基金
FenjiB Fenji B Funds, 即分级B类基金
INDX Index, 即指数
Future Futures，即期货，包含股指、国债和商品期货
========================= ===================================================
:example:
获取中国市场所有分级基金的基础信息:
.. code-block:: python3
:linenos:
[In]all_instruments('FenjiA')
[Out]
abbrev_symbol order_book_id product sector_code symbol
0 CYGA 150303.XSHE null null 华安创业板50A
1 JY500A 150088.XSHE null null 金鹰500A
2 TD500A 150053.XSHE null null 泰达稳健
3 HS500A 150110.XSHE null null 华商500A
4 QSAJ 150235.XSHE null null 鹏华证券A
...
"""
env = Environment.get_instance()
if date is None:
dt = env.trading_dt
else:
dt = pd.Timestamp(date).to_pydatetime()
dt = min(dt, env.trading_dt)
if type is not None:
if isinstance(type, six.string_types):
type = [type]
types = set()
for t in type:
if t == 'Stock':
types.add('CS')
elif t == 'Fund':
types.update(['ETF', 'LOF', 'SF', 'FenjiA', 'FenjiB', 'FenjiMu'])
else:
types.add(t)
else:
types = None
result = env.data_proxy.all_instruments(types, dt)
if types is not None and len(types) == 1:
return pd.DataFrame([i._ins_dict for i in result])
return pd.DataFrame(
[[i.order_book_id, i.symbol, i.type, i.listed_date, i.de_listed_date] for i in result],
columns=['order_book_id', 'symbol', 'type', 'listed_date', 'de_listed_date'])
def all_instruments(type=None, date=None):
"""
获取某个国家市场的所有合约信息。使用者可以通过这一方法很快地对合约信息有一个快速了解，目前仅支持中国市场。
:param str type: 需要查询合约类型，例如：type='CS'代表股票。默认是所有类型
:param date: 查询时间点
:type date: `str` | `datetime` | `date`
:return: `pandas DataFrame` 所有合约的基本信息。
其中type参数传入的合约类型和对应的解释如下：
========================= ===================================================
合约类型 说明
========================= ===================================================
CS Common Stock, 即股票
ETF Exchange Traded Fund, 即交易所交易基金
LOF Listed Open-Ended Fund，即上市型开放式基金
FenjiMu Fenji Mu Fund, 即分级母基金
FenjiA Fenji A Fund, 即分级A类基金
FenjiB Fenji B Funds, 即分级B类基金
INDX Index, 即指数
Future Futures，即期货，包含股指、国债和商品期货
========================= ===================================================
:example:
获取中国市场所有分级基金的基础信息:
.. code-block:: python3
:linenos:
[In]all_instruments('FenjiA')
[Out]
abbrev_symbol order_book_id product sector_code symbol
0 CYGA 150303.XSHE null null 华安创业板50A
1 JY500A 150088.XSHE null null 金鹰500A
2 TD500A 150053.XSHE null null 泰达稳健
3 HS500A 150110.XSHE null null 华商500A
4 QSAJ 150235.XSHE null null 鹏华证券A
...
"""
env = Environment.get_instance()
if date is None:
dt = env.trading_dt
else:
dt = pd.Timestamp(date).to_pydatetime()
dt = min(dt, env.trading_dt)
if type is not None:
if isinstance(type, six.string_types):
type = [type]
types = set()
for t in type:
if t == "Stock":
types.add("CS")
elif t == "Fund":
types.update(["ETF", "LOF", "SF", "FenjiA", "FenjiB", "FenjiMu"])
else:
types.add(t)
else:
types = None
result = env.data_proxy.all_instruments(types, dt)
if types is not None and len(types) == 1:
return pd.DataFrame([i.__dict__ for i in result])
return pd.DataFrame(
[
[i.order_book_id, i.symbol, i.type, i.listed_date, i.de_listed_date]
for i in result
],
columns=["order_book_id", "symbol", "type", "listed_date", "de_listed_date"],
)
