class BBands(IndicatorAbstract):
def __init__(
self, _period: int = 26, _use_key: str = 'closeprice',
_rate: float = 2.0, _idx_key: str = 'time',
_ret_key=('upband', 'midband', 'downband')
):
super().__init__()
self.use_key = _use_key
self.idx_key = _idx_key
self.keys = [self.idx_key] + list(_ret_key)
self.data = DataStruct(
self.keys, self.idx_key
)
self.period = _period
self.rate = _rate
self.buf = deque(maxlen=self.period)
def _addOne(self, _data_struct: DataStruct):
index_value = _data_struct.index()[0]
self.buf.append(_data_struct.getColumn(self.use_key)[0])
mean = statistics.mean(self.buf)
std = statistics.pstdev(self.buf, mu=mean)
self.data.addRow([
index_value, mean + self.rate * std, mean, mean - self.rate * std
], self.keys)
class BBands(IndicatorAbstract):
def __init__(self,
_period: int = 26,
_use_key: str = 'closeprice',
_rate: float = 2.0,
_idx_key: str = 'time',
_ret_key=('upband', 'midband', 'downband')):
super().__init__()
self.use_key = _use_key
self.idx_key = _idx_key
self.keys = [self.idx_key] + list(_ret_key)
self.data = DataStruct(self.keys, self.idx_key)
self.period = _period
self.rate = _rate
self.buf = deque(maxlen=self.period)
def _addOne(self, _data_struct: DataStruct):
index_value = _data_struct.index()[0]
self.buf.append(_data_struct.getColumn(self.use_key)[0])
mean = statistics.mean(self.buf)
std = statistics.pstdev(self.buf, mu=mean)
self.data.addRow([
index_value, mean + self.rate * std, mean, mean - self.rate * std
], self.keys)
class AdaBBands(IndicatorAbstract):
def __init__(
self, _period: int, _use_key: str,
_init_n: int = 20, _min_n: int = 20, _max_n: int = 60,
_rate: float = 2.0, _idx_key: str = 'time'
):
super().__init__()
self.use_key = _use_key
self.idx_key = _idx_key
self.keys = [self.idx_key, 'upband', 'midband', 'downband']
self.data = DataStruct(
self.keys, self.idx_key
)
self.period = _period
self.rate = _rate
self.buf = []
self.prev_std = None
self.dynamic_n = float(_init_n)
self.min_n = _min_n
self.max_n = _max_n
def _addOne(self, _data_struct: DataStruct):
index_value = _data_struct.index()[0]
self.buf.append(_data_struct.getColumn(self.use_key)[0])
if len(self.data) > self.period:
const_std = statistics.pstdev(self.buf[-self.period:])
self.dynamic_n *= const_std / self.prev_std
self.dynamic_n = max(self.min_n, self.dynamic_n)
self.dynamic_n = min(self.max_n, self.dynamic_n)
tmp_n = int(round(self.dynamic_n))
mean = statistics.mean(self.buf[-tmp_n:])
std = statistics.pstdev(self.buf[-tmp_n:])
self.data.addRow(
[index_value, mean + self.rate * std,
mean, mean - self.rate * std],
self.keys
)
self.prev_std = const_std
else:
if len(self.data) == self.period:
self.prev_std = statistics.pstdev(self.buf)
self.data.addRow(
[index_value, None, None, None],
self.keys
)
class KDJ(IndicatorAbstract):
def __init__(
self,
_k_period: int = 20,
_d_period: int = 3,
_j_period: int = 3,
_close_key: str = 'closeprice',
_high_key: str = 'highprice',
_low_key: str = 'lowprice',
_idx_key: str = 'time',
_ret_key=('k', 'd', 'j')
):
super().__init__()
self.k_period = _k_period
self.d_period = _d_period
self.j_period = _j_period
self.close_key = _close_key
self.high_key = _high_key
self.low_key = _low_key
self.idx_key = _idx_key
self.keys = [self.idx_key] + list(_ret_key)
self.high_buf = deque(maxlen=self.k_period)
self.low_buf = deque(maxlen=self.k_period)
self.k_buf = deque(maxlen=self.d_period)
self.data = DataStruct(
self.keys, self.idx_key
)
def _addOne(self, _data: DataStruct):
index_value = _data.index()[0]
closeprice = _data[self.close_key][0]
highprice = _data[self.high_key][0]
lowprice = _data[self.low_key][0]
self.high_buf.append(highprice)
self.low_buf.append(lowprice)
high_mean = statistics.mean(self.high_buf)
low_mean = statistics.mean(self.low_buf)
k = 100 * (closeprice - high_mean) / (high_mean - low_mean)
self.k_buf.append(k)
d = statistics.mean(self.k_buf)
j = self.j_period * k - (self.j_period - 1) * d
self.data.addRow(
[index_value, k, d, j],
self.keys
)
class AdaBBands(IndicatorAbstract):
def __init__(self,
_period: int,
_use_key: str,
_init_n: int = 20,
_min_n: int = 20,
_max_n: int = 60,
_rate: float = 2.0,
_idx_key: str = 'time'):
super().__init__()
self.use_key = _use_key
self.idx_key = _idx_key
self.keys = [self.idx_key, 'upband', 'midband', 'downband']
self.data = DataStruct(self.keys, self.idx_key)
self.period = _period
self.rate = _rate
self.buf = []
self.prev_std = None
self.dynamic_n = float(_init_n)
self.min_n = _min_n
self.max_n = _max_n
def _addOne(self, _data_struct: DataStruct):
index_value = _data_struct.index()[0]
self.buf.append(_data_struct.getColumn(self.use_key)[0])
if len(self.data) > self.period:
const_std = statistics.pstdev(self.buf[-self.period:])
self.dynamic_n *= const_std / self.prev_std
self.dynamic_n = max(self.min_n, self.dynamic_n)
self.dynamic_n = min(self.max_n, self.dynamic_n)
tmp_n = int(round(self.dynamic_n))
mean = statistics.mean(self.buf[-tmp_n:])
std = statistics.pstdev(self.buf[-tmp_n:])
self.data.addRow([
index_value, mean + self.rate * std, mean,
mean - self.rate * std
], self.keys)
self.prev_std = const_std
else:
if len(self.data) == self.period:
self.prev_std = statistics.pstdev(self.buf)
self.data.addRow([index_value, None, None, None], self.keys)
class FastBBands(IndicatorAbstract):
def __init__(
self, _period: int = 26, _rate: float = 2.0,
_ignore_mean: bool = False,
_use_key: str = 'closeprice', _idx_key: str = 'time',
_ret_key=('upband', 'midband', 'downband')
):
super().__init__()
self.use_key = _use_key
self.idx_key = _idx_key
self.keys = [self.idx_key] + list(_ret_key)
self.data = DataStruct(
self.keys, self.idx_key
)
self.period = _period
self.rate = _rate
self.ignore_mean = _ignore_mean
self.buf = deque(maxlen=self.period)
self.mean = 0.0
self.sum_of_pow = 0.0
def _addOne(self, _data_struct: DataStruct):
value = _data_struct[self.use_key][0]
index = _data_struct.index()[0]
if len(self.buf) >= self.period:
last_value = self.buf.popleft()
self.buf.append(value)
self.sum_of_pow += value ** 2
self.sum_of_pow -= last_value ** 2
if not self.ignore_mean:
self.mean += (value - last_value) / self.period
else:
n = len(self.buf)
self.buf.append(value)
self.sum_of_pow += value ** 2
if not self.ignore_mean:
self.mean = (self.mean * n + value) / len(self.buf)
std = math.sqrt(
self.sum_of_pow / len(self.buf) - self.mean ** 2
)
self.data.addRow([
index, self.mean + self.rate * std,
self.mean, self.mean - self.rate * std
], self.keys)
class MACD(IndicatorAbstract):
def __init__(
self,
_fast_period: int = 12,
_slow_period: int = 26,
_macd_period: int = 9,
_use_key: str = 'closeprice',
_idx_key: str = 'time',
_ret_key=('value', 'avg', 'diff')
):
super().__init__()
self.fast_period = _fast_period
self.slow_period = _slow_period
self.macd_period = _macd_period
self.use_key = _use_key
self.idx_key = _idx_key
self.keys = [self.idx_key] + list(_ret_key)
self.fast_value = None
self.slow_value = None
self.macd_avg = None
self.data = DataStruct(
self.keys, self.idx_key
)
def _addOne(self, _data: DataStruct):
index_value = _data.index()[0]
price = _data[self.use_key][0]
if self.fast_value is None and self.slow_value is None \
and self.macd_avg is None:
self.fast_value = price
self.slow_value = price
macd_value = self.fast_value - self.slow_value
self.macd_avg = macd_value
else:
self.fast_value = (price - self.fast_value) / self.fast_period + self.fast_value
self.slow_value = (price - self.slow_value) / self.slow_period + self.slow_value
macd_value = self.fast_value - self.slow_value
self.macd_avg = (macd_value - self.macd_avg) / self.macd_period + self.macd_avg
macd_diff = macd_value - self.macd_avg
self.data.addRow(
[index_value, macd_value, self.macd_avg, macd_diff],
self.keys
)
class MACD(IndicatorAbstract):
def __init__(self,
_fast_period: int = 12,
_slow_period: int = 26,
_macd_period: int = 9,
_use_key: str = 'closeprice',
_idx_key: str = 'time',
_ret_key=('value', 'avg', 'diff')):
super().__init__()
self.fast_period = _fast_period
self.slow_period = _slow_period
self.macd_period = _macd_period
self.use_key = _use_key
self.idx_key = _idx_key
self.keys = [self.idx_key] + list(_ret_key)
self.fast_value = None
self.slow_value = None
self.macd_avg = None
self.data = DataStruct(self.keys, self.idx_key)
def _addOne(self, _data: DataStruct):
index_value = _data.index()[0]
price = _data[self.use_key][0]
if self.fast_value is None and self.slow_value is None \
and self.macd_avg is None:
self.fast_value = price
self.slow_value = price
macd_value = self.fast_value - self.slow_value
self.macd_avg = macd_value
else:
self.fast_value = (
price - self.fast_value) / self.fast_period + self.fast_value
self.slow_value = (
price - self.slow_value) / self.slow_period + self.slow_value
macd_value = self.fast_value - self.slow_value
self.macd_avg = (macd_value -
self.macd_avg) / self.macd_period + self.macd_avg
macd_diff = macd_value - self.macd_avg
self.data.addRow([index_value, macd_value, self.macd_avg, macd_diff],
self.keys)
class FastBBands(IndicatorAbstract):
def __init__(self,
_period: int = 26,
_rate: float = 2.0,
_ignore_mean: bool = False,
_use_key: str = 'closeprice',
_idx_key: str = 'time',
_ret_key=('upband', 'midband', 'downband')):
super().__init__()
self.use_key = _use_key
self.idx_key = _idx_key
self.keys = [self.idx_key] + list(_ret_key)
self.data = DataStruct(self.keys, self.idx_key)
self.period = _period
self.rate = _rate
self.ignore_mean = _ignore_mean
self.buf = deque(maxlen=self.period)
self.mean = 0.0
self.sum_of_pow = 0.0
def _addOne(self, _data_struct: DataStruct):
value = _data_struct[self.use_key][0]
index = _data_struct.index()[0]
if len(self.buf) >= self.period:
last_value = self.buf.popleft()
self.buf.append(value)
self.sum_of_pow += value**2
self.sum_of_pow -= last_value**2
if not self.ignore_mean:
self.mean += (value - last_value) / self.period
else:
n = len(self.buf)
self.buf.append(value)
self.sum_of_pow += value**2
if not self.ignore_mean:
self.mean = (self.mean * n + value) / len(self.buf)
std = math.sqrt(self.sum_of_pow / len(self.buf) - self.mean**2)
self.data.addRow([
index, self.mean + self.rate * std, self.mean,
self.mean - self.rate * std
], self.keys)
class OHLC(BarIndicatorAbstract):
def __init__(
self, _use_key: str, _idx_key: str = 'time',
_ret_key: typing.Sequence[str] = ('open', 'high', 'low', 'close')
):
super().__init__()
self.use_key = _use_key
self.idx_key = _idx_key
self.ret_key = _ret_key
self.data = DataStruct(
[self.idx_key] + list(self.ret_key),
self.idx_key
)
def _addOne(
self, _data_struct: DataStruct,
_idx: typing.Union[str, datetime] = None
):
tmp = _data_struct[self.use_key]
self.data.addRow(
(_idx, tmp[0], max(tmp), min(tmp), tmp[-1]),
[self.idx_key] + list(self.ret_key)
)
