def broadcast_ts(ts, params_len, new_columns):
"""Broadcast time series `ts` to match the length of `new_columns` through tiling."""
if checks.is_series(ts) or len(new_columns) > ts.shape[1]:
return ts.vbt.wrap(reshape_fns.tile(ts.values, params_len, axis=1),
columns=new_columns)
else:
return ts.vbt.wrap(ts, columns=new_columns)
def tile(self, n, as_columns=None):
tiled = reshape_fns.tile(self._obj, n, along_axis=1)
if as_columns is not None:
new_columns = index_fns.combine(
as_columns,
reshape_fns.to_2d(self._obj).columns)
return self.wrap_array(tiled.values, columns=new_columns)
return tiled
def tile(self, n, as_columns=None):
"""See `vectorbt.utils.reshape_fns.tile`.
Use `as_columns` as a top-level column level."""
tiled = reshape_fns.tile(self._obj, n, axis=1)
if as_columns is not None:
new_columns = index_fns.combine_indexes(as_columns, self.columns)
return self.wrap_array(tiled.values, columns=new_columns)
return tiled