def test_ma_transformer():
df = get_kdata(entity_id='stock_sz_000338',
start_timestamp='2019-01-01',
provider='joinquant')
t = MaTransformer(windows=[5, 10])
result_df = t.transform(df)
print(result_df)
def test_ma_transformer():
df = get_kdata(region=Region.CHN, entity_id='stock_sz_000338',
start_timestamp='2019-01-01', provider=Provider.JoinQuant,
index=['entity_id', 'timestamp'])
t = MaTransformer(windows=[5, 10])
result_df = t.transform(df)
print(result_df)
def test_ma_transformer():
df = get_kdata(
entity_id="stock_sz_000338",
start_timestamp="2019-01-01",
provider="joinquant",
index=["entity_id", "timestamp"],
)
t = MaTransformer(windows=[5, 10])
result_df = t.transform(df)
print(result_df)
def __init__(self,
entity_ids: List[str] = None,
entity_type: str = 'stock',
exchanges: List[str] = ['sh', 'sz'],
codes: List[str] = None,
the_timestamp: Union[str, pd.Timestamp] = None,
start_timestamp: Union[str, pd.Timestamp] = None,
end_timestamp: Union[str, pd.Timestamp] = None,
columns: List = None,
filters: List = None,
order: object = None,
limit: int = None,
provider: str = 'joinquant',
level: Union[str, IntervalLevel] = IntervalLevel.LEVEL_1DAY,
category_field: str = 'entity_id',
time_field: str = 'timestamp',
computing_window: int = 250,
keep_all_timestamp: bool = False,
fill_method: str = 'ffill',
effective_number: int = 10,
need_persist: bool = True,
dry_run: bool = True,
windows=[5, 10, 34, 55, 89, 144, 120, 250]) -> None:
self.factor_schema = get_ma_factor_schema(entity_type=entity_type,
level=level)
self.windows = windows
transformer: Transformer = MaTransformer(windows=windows)
super().__init__(entity_ids, entity_type, exchanges, codes,
the_timestamp, start_timestamp, end_timestamp,
columns, filters, order, limit, provider, level,
category_field, time_field, computing_window,
keep_all_timestamp, fill_method, effective_number,
transformer, None, need_persist, dry_run)
def test_ma():
factor = TechnicalFactor(codes=['000338'],
start_timestamp='2019-01-01',
end_timestamp='2019-06-10',
level=IntervalLevel.LEVEL_1DAY,
provider=Provider.JoinQuant,
computing_window=30,
transformer=MaTransformer(windows=[5, 10, 30]),
adjust_type='qfq')
print(factor.factor_df.tail())
# compare with east money manually
ma5 = factor.factor_df['ma5']
ma10 = factor.factor_df['ma10']
ma30 = factor.factor_df['ma30']
assert round(ma5.loc[('stock_sz_000338', '2019-06-10')], 2) <= 11.23
assert round(ma10.loc[('stock_sz_000338', '2019-06-10')], 2) <= 11.43
assert round(ma30.loc[('stock_sz_000338', '2019-06-10')], 2) <= 11.52
factor.move_on(to_timestamp='2019-06-17')
ma5 = factor.factor_df['ma5']
ma10 = factor.factor_df['ma10']
ma30 = factor.factor_df['ma30']
assert round(ma5.loc[('stock_sz_000338', '2019-06-17')], 2) <= 12.06
assert round(ma10.loc[('stock_sz_000338', '2019-06-17')], 2) <= 11.64
assert round(ma30.loc[('stock_sz_000338', '2019-06-17')], 2) <= 11.50
def __init__(self,
entity_ids: List[str] = None,
entity_type: str = 'stock',
exchanges: List[str] = ['sh', 'sz'],
codes: List[str] = None,
the_timestamp: Union[str, pd.Timestamp] = None,
start_timestamp: Union[str, pd.Timestamp] = None,
end_timestamp: Union[str, pd.Timestamp] = None,
columns: List = None,
filters: List = None,
order: object = None,
limit: int = None,
provider: str = 'joinquant',
level: IntervalLevel = IntervalLevel.LEVEL_1DAY,
need_persist: bool = False,
dry_run: bool = False,
# child added arguments
short_window=5,
long_window=10) -> None:
self.short_window = short_window
self.long_window = long_window
transformer = MaTransformer(windows=[short_window, long_window])
super().__init__(entity_ids, entity_type, exchanges, codes, the_timestamp, start_timestamp, end_timestamp,
columns, filters, order, limit, provider, level, 'entity_id', 'timestamp', long_window,
False, None, None, transformer, None, need_persist, dry_run)
def test_ma():
factor = TechnicalFactor(
provider="joinquant",
codes=["000338"],
start_timestamp="2019-01-01",
end_timestamp="2019-06-10",
level=IntervalLevel.LEVEL_1DAY,
computing_window=30,
transformer=MaTransformer(windows=[5, 10, 30]),
adjust_type="qfq",
)
print(factor.factor_df.tail())
# compare with east money manually
ma5 = factor.factor_df["ma5"]
ma10 = factor.factor_df["ma10"]
ma30 = factor.factor_df["ma30"]
assert round(ma5.loc[("stock_sz_000338", "2019-06-10")], 2) <= 11.23
assert round(ma10.loc[("stock_sz_000338", "2019-06-10")], 2) <= 11.43
assert round(ma30.loc[("stock_sz_000338", "2019-06-10")], 2) <= 11.52
factor.move_on(to_timestamp="2019-06-17")
ma5 = factor.factor_df["ma5"]
ma10 = factor.factor_df["ma10"]
ma30 = factor.factor_df["ma30"]
assert round(ma5.loc[("stock_sz_000338", "2019-06-17")], 2) <= 12.06
assert round(ma10.loc[("stock_sz_000338", "2019-06-17")], 2) <= 11.64
assert round(ma30.loc[("stock_sz_000338", "2019-06-17")], 2) <= 11.50
def __init__(
self,
region: Region,
entity_schema: EntityMixin = Stock,
provider: Provider = Provider.Default,
entity_provider: Provider = Provider.Default,
entity_ids: List[str] = None,
exchanges: List[str] = None,
codes: List[str] = None,
the_timestamp: Union[str, pd.Timestamp] = None,
start_timestamp: Union[str, pd.Timestamp] = None,
end_timestamp: Union[str, pd.Timestamp] = None,
columns: List = [
'id', 'entity_id', 'timestamp', 'level', 'open', 'close',
'high', 'low'
],
filters: List = None,
order: object = None,
limit: int = None,
level: Union[str, IntervalLevel] = IntervalLevel.LEVEL_1DAY,
category_field: str = 'entity_id',
time_field: str = 'timestamp',
computing_window: int = 10,
keep_all_timestamp: bool = False,
fill_method: str = 'ffill',
effective_number: int = None,
need_persist: bool = True,
dry_run: bool = True,
# added fields
short_window: int = 5,
long_window: int = 10) -> None:
self.factor_schema = get_ma_state_stats_schema(entity_type=EntityType(
entity_schema.__name__.lower()),
level=level)
self.short_window = short_window
self.long_window = long_window
transformer: Transformer = MaTransformer(
windows=[short_window, long_window], cal_change_pct=True)
accumulator = MaAccumulator(short_window=short_window,
long_window=long_window)
super().__init__(region, entity_schema, provider, entity_provider,
entity_ids, exchanges, codes, the_timestamp,
start_timestamp, end_timestamp, columns, filters,
order, limit, level, category_field, time_field,
computing_window, keep_all_timestamp, fill_method,
effective_number, transformer, accumulator,
need_persist, dry_run)
def __init__(self,
region: Region,
entity_schema: EntityMixin = Stock,
provider: Provider = Provider.Default,
entity_provider: Provider = Provider.Default,
entity_ids: List[str] = None,
exchanges: List[str] = None,
codes: List[str] = None,
the_timestamp: Union[str, pd.Timestamp] = None,
start_timestamp: Union[str, pd.Timestamp] = None,
end_timestamp: Union[str, pd.Timestamp] = None,
columns: List = [
'id', 'entity_id', 'timestamp', 'level', 'open', 'close',
'high', 'low'
],
filters: List = None,
order: object = None,
limit: int = None,
level: Union[str, IntervalLevel] = IntervalLevel.LEVEL_1DAY,
category_field: str = 'entity_id',
time_field: str = 'timestamp',
computing_window: int = None,
keep_all_timestamp: bool = False,
fill_method: str = 'ffill',
effective_number: int = None,
accumulator: Accumulator = None,
need_persist: bool = False,
dry_run: bool = False,
windows=[5, 10, 34, 55, 89, 144, 120, 250],
adjust_type: Union[AdjustType, str] = None) -> None:
self.adjust_type = adjust_type
self.factor_schema = get_ma_factor_schema(entity_type=EntityType(
entity_schema.__name__.lower()),
level=level)
self.windows = windows
transformer: Transformer = MaTransformer(windows=windows)
super().__init__(region, entity_schema, provider, entity_provider,
entity_ids, exchanges, codes, the_timestamp,
start_timestamp, end_timestamp, columns, filters,
order, limit, level, category_field, time_field,
computing_window, keep_all_timestamp, fill_method,
effective_number, transformer, accumulator,
need_persist, dry_run, adjust_type)
def __init__(self,
region: Region,
entity_schema: Type[EntityMixin] = Stock,
provider: Provider = Provider.Default,
entity_ids: List[str] = None,
exchanges: List[str] = None,
codes: List[str] = None,
the_timestamp: Union[str, pd.Timestamp] = None,
start_timestamp: Union[str, pd.Timestamp] = None,
end_timestamp: Union[str, pd.Timestamp] = None,
columns: List = None,
filters: List = None,
order: object = None,
limit: int = None,
level: Union[str, IntervalLevel] = IntervalLevel.LEVEL_1DAY,
category_field: str = 'entity_id',
time_field: str = 'timestamp',
computing_window: int = None,
keep_all_timestamp: bool = False,
fill_method: str = 'ffill',
effective_number: int = None,
need_persist: bool = False,
dry_run: bool = False,
factor_name: str = None,
clear_state: bool = False,
not_load_data: bool = False,
adjust_type: Union[AdjustType, str] = None,
windows=None) -> None:
if need_persist:
self.factor_schema = get_ma_factor_schema(
entity_type=entity_schema.__name__, level=level)
if not windows:
windows = [5, 10, 34, 55, 89, 144, 120, 250]
self.windows = windows
transformer: Transformer = MaTransformer(windows=windows)
super().__init__(region, entity_schema, provider,
entity_ids, exchanges, codes, the_timestamp,
start_timestamp, end_timestamp, columns, filters,
order, limit, level, category_field,
time_field, computing_window, keep_all_timestamp,
fill_method, effective_number, transformer,
None, need_persist, dry_run, factor_name, clear_state,
not_load_data, adjust_type)
def __init__(self,
entity_ids: List[str] = None,
entity_type: str = 'stock',
exchanges: List[str] = ['sh', 'sz'],
codes: List[str] = None,
the_timestamp: Union[str, pd.Timestamp] = None,
start_timestamp: Union[str, pd.Timestamp] = None,
end_timestamp: Union[str, pd.Timestamp] = None,
columns: List = None,
filters: List = None,
order: object = None,
limit: int = None,
provider: str = 'joinquant',
level: Union[str, IntervalLevel] = IntervalLevel.LEVEL_1DAY,
category_field: str = 'entity_id',
time_field: str = 'timestamp',
computing_window: int = 10,
keep_all_timestamp: bool = False,
fill_method: str = 'ffill',
effective_number: int = 10,
persist_factor: bool = True,
dry_run: bool = True,
# added fields
short_window: int = 5,
long_window: int = 10) -> None:
self.factor_schema = get_ma_state_stats_schema(entity_type=entity_type, level=level)
self.short_window = short_window
self.long_window = long_window
transformer: Transformer = MaTransformer(windows=[short_window, long_window])
acc = MaAccumulator(short_window=short_window, long_window=long_window)
super().__init__(entity_ids, entity_type, exchanges, codes, the_timestamp, start_timestamp,
end_timestamp, columns, filters, order, limit, provider, level, category_field, time_field,
computing_window, keep_all_timestamp, fill_method, effective_number, transformer, acc,
persist_factor, dry_run)
def __init__(
self,
entity_schema: Type[TradableEntity] = Stock,
provider: str = None,
entity_provider: str = None,
entity_ids: List[str] = None,
exchanges: List[str] = None,
codes: List[str] = None,
start_timestamp: Union[str, pd.Timestamp] = None,
end_timestamp: Union[str, pd.Timestamp] = None,
columns: List = None,
filters: List = None,
order: object = None,
limit: int = None,
level: Union[str, IntervalLevel] = IntervalLevel.LEVEL_1DAY,
category_field: str = "entity_id",
time_field: str = "timestamp",
computing_window: int = None,
keep_all_timestamp: bool = False,
fill_method: str = "ffill",
effective_number: int = None,
need_persist: bool = False,
only_compute_factor: bool = False,
factor_name: str = None,
clear_state: bool = False,
only_load_factor: bool = False,
adjust_type: Union[AdjustType, str] = None,
windows=None,
) -> None:
if need_persist:
self.factor_schema = get_ma_factor_schema(entity_type=entity_schema.__name__, level=level)
if not windows:
windows = [5, 10, 34, 55, 89, 144, 120, 250]
self.windows = windows
transformer: Transformer = MaTransformer(windows=windows)
super().__init__(
entity_schema,
provider,
entity_provider,
entity_ids,
exchanges,
codes,
start_timestamp,
end_timestamp,
columns,
filters,
order,
limit,
level,
category_field,
time_field,
computing_window,
keep_all_timestamp,
fill_method,
effective_number,
transformer,
None,
need_persist,
only_compute_factor,
factor_name,
clear_state,
only_load_factor,
adjust_type,
)
