Topics created by Lammy

Hey @Lammy have you solved this in the end?

I'm trying to handle this arrows misplacement problem with my tick data (single-tick value).
The only solution that I've found is to call:

cerebro = bt.Cerebro(stdstats=False) cerebro.addobserver(bt.Observers.BuySell)

This way the arrows will be printed above/under the priceline and maybe, as in my case, too close to it. But I think is better to have it too close than not having at all!

Errata Corrige: this solution will lead to many problems when plotting more than one datas, I'm currently looking for another option to solve it!

Here is an example of what I did:

Generating the lines and params tuples by passing in list(df.columns)

def get_extra_df_columns(self, df_columns: list[str] = []) -> list[tuple]: lines: tuple = () params: tuple(tuple) = () for column in df_columns: if column not in ['symbol', 'open', 'high', 'low', 'close', 'volume']: lines = lines + (column,) params = params + ( (column, -1), ) return [lines, params]

Creating the subclass by parsing the df to be parsed then returning it with the subclass attributes set dynamically:

def _create_data_feeder(self, database: Database, df: pd.DataFrame ): lines, params = database.get_extra_df_columns(df_columns=list(df.columns) ) return type('PandasDataFeed', (bt.feeds.PandasData, ), {'lines':lines, 'params':params} )

Adding the dataframe to cerebro via the created data_feeder subclass

self.data_feeder = self._create_data_feeder(database=database, df=df) self.cerebro.adddata(self.data_feeder(dataname=df, name=symbol ))

The extra columns in the df are vwap and supertrend and are accessible without hardcoding the lines and params

class TestStrategy(bt.Strategy): def __init__(self): for i, d in enumerate(self.datas): bt.ind.SMA(d.supertrend, period=1, subplot=False, plotname='supertrend') bt.ind.SMA(d.vwap, period=1, subplot=False, plotname='vwap')