Comments (5)
You should also override _get_prices
to store OHLC data.
def _get_prices(self, keys: List[str]=['Open', 'High', 'Low', 'Close']) -> Dict[str, np.ndarray]:
prices = {}
for symbol in self.trading_symbols:
get_price_at = lambda time: \
self.original_simulator.price_at(symbol, time)[keys]
if self.multiprocessing_pool is None:
p = list(map(get_price_at, self.time_points))
else:
p = self.multiprocessing_pool.map(get_price_at, self.time_points)
prices[symbol] = np.array(p)
return prices
def _process_data(self) -> np.ndarray:
data = self.prices
macd_features = []
for pair, ohlc_data in data.items():
open = ohlc_data[:, 0]
high = ohlc_data[:, 1]
low = ohlc_data[:, 2]
close = ohlc_data[:, 3]
pair_macd = calculate_macd_from_ohlc(open, high, low, close)
macd_features.append(pair_macd)
signal_features = np.column_stack(macd_features)
return signal_features
from gym-mtsim.
Hi @dancydancy,
You can override this function in order to add your own indicators.
You can download data from MetaTrader using the download_data
method of MtSimulator
. Here is an example code. In case you want to put your own data frames into the simulator instead of downloading from MetaTrader, it might be helpful to read the source code of the download_data
.
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Thank-you :)
from gym-mtsim.
Hi @AminHP, could you provide an example of how to override the _process_data function with a simple indicator like MACD if you get a chance. I am having a lot of trouble figuring out how to add the data produced by the indicator to the signal_features being returned. Thanks in advance
from gym-mtsim.
When I do exactly this I get the error: AttributeError: 'NoneType' object has no attribute 'shape'
. Any ideas? Sorry if this is a stupid question, my python knowledge is rather limited
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from gym-mtsim.