Break hist calc into wap func, use hlc3.

vwap_backup
Tyler Goodlet 2020-11-13 12:31:07 -05:00
parent 0ab0957c6e
commit 4e8739d9ed
1 changed files with 36 additions and 15 deletions

View File

@ -14,47 +14,68 @@
# You should have received a copy of the GNU Affero General Public License
# along with this program. If not, see <https://www.gnu.org/licenses/>.
from typing import AsyncIterator
from typing import AsyncIterator, Optional
import numpy as np
from ..data._normalize import iterticks
def wap(
signal: np.ndarray,
weights: np.ndarray,
) -> np.ndarray:
"""Weighted average price from signal and weights.
"""
cum_weights = np.cumsum(weights)
cum_weighted_input = np.cumsum(signal * weights)
return cum_weighted_input / cum_weights, cum_weighted_input, cum_weights
async def _tina_vwap(
source, #: AsyncStream[np.ndarray],
ohlcv: np.ndarray, # price time-frame "aware"
anchors: Optional[np.ndarray] = None,
) -> AsyncIterator[np.ndarray]: # maybe something like like FspStream?
"""Streaming volume weighted moving average.
Calling this "tina" for now since we're using OHL3 instead of tick.
Calling this "tina" for now since we're using HLC3 instead of tick.
"""
# TODO: anchor to session start
if anchors is None:
# TODO:
# anchor to session start of data if possible
pass
a = ohlcv.array
ohl3 = (a['open'] + a['high'] + a['low']) / 3
chl3 = (a['close'] + a['high'] + a['low']) / 3
v = a['volume']
cum_v = np.cumsum(v)
cum_weights = np.cumsum(ohl3 * v)
vwap = cum_weights / cum_v
h_vwap, cum_wp, cum_v = wap(chl3, v)
# deliver historical output as "first yield"
yield vwap
yield h_vwap
weights_tot = cum_weights[-1]
w_tot = cum_wp[-1]
v_tot = cum_v[-1]
# vwap_tot = h_vwap[-1]
async for quote in source:
for tick in iterticks(quote, types=['trade']):
o, h, l, v = ohlcv.array[-1][
['open', 'high', 'low', 'volume']
]
v_tot += v
# c, h, l, v = ohlcv.array[-1][
# ['closes', 'high', 'low', 'volume']
# ]
yield ((((o + h + l) / 3) * v) + weights_tot) / v_tot
# this computes tick-by-tick weightings from here forward
size = tick['size']
price = tick['price']
v_tot += size
w_tot += price * size
# yield ((((o + h + l) / 3) * v) weights_tot) / v_tot
yield w_tot / v_tot