Wrap the moving averages in deephaven v2

[jmao-denver]

The MovingAverages is supported in legacy and documented. It needs to be migrated to the new API.

from deephaven_legacy.MovingAverages import ByEmaSimple
from deephaven import time_table
import random

ema1sec = ByEmaSimple('BD_SKIP','BD_SKIP','TIME',10,'SECONDS', type='LEVEL')

result = time_table('00:00:01').update(formulas=["Sym = (char)(int)random.randint(65, 70)", "Numbers = (int)random.randint(0, 100)"])

ema_data = result.view(formulas=["EMA_data = ema1sec.update(Timestamp, Numbers)"]).last_by()
ema_data_grouped = result.view(formulas=["Sym", "EMA_data = ema1sec.update(Timestamp, Numbers, Sym)"]).last_by(by=["Sym"]).sort(order_by=["Sym"])

It seems to me that during formula evaluation this will lead to a round-trip from Java to Python then back just to call 'ema1sec.update' if we wrap the result of 'ByEmaSimple' call in Python. What we want is to unwrap 'ema1sec' during formula parsing and generate evaluation code with the wrapped Java object.

The more generalized solution for minimizing Python/Java boundary crossing is to be addressed by #2363

[jmao-denver]

Per Pete, the design and implementation of MAs are to be reworked soon, we should definitely wait for that to be done first before take up this ticket.

[jmao-denver]

this ticket has been converted to a minimal port of the MA implementation in legacy to V2.

[jmao-denver]

Almost a one to one port, the 1st line in the code block is the only change required.

from deephaven.experimental.ema import ByEmaSimple
from deephaven import time_table
import random

def random_char():
    return random.choice(['A', 'B', 'C', 'D', 'E', 'F'])

ema1sec = ByEmaSimple('BD_SKIP','BD_SKIP','TIME',10,'SECONDS', type='LEVEL')

result = time_table('00:00:01').update(formulas=["Sym = (String)random_char()", "Numbers = (int)random.randint(0, 100)"])

ema_data = result.view(formulas=["EMA_data = ema1sec.update(Timestamp, Numbers)"]).last_by()
ema_data_grouped = result.view(formulas=["Sym", "EMA_data = ema1sec.update(Timestamp, Numbers, Sym)"]).last_by(by=["Sym"]).sort(order_by=["Sym"])