Jan-07-2021, 07:13 PM

Hello,

I have the following function:

Any help would be appreciated

Thanks

Matt

I have the following function:

def custom_hurst(timeseries): series = timeseries.iloc[-360:,0] max_window = len(series) min_window = 15 ndarray_likes = [np.ndarray] if "pandas.core.series" in sys.modules.keys(): ndarray_likes.append(pd.core.series.Series) if type(series) not in ndarray_likes: series = np.array(series) if "pandas.core.series" in sys.modules.keys() and type(series) == pd.core.series.Series: if series.isnull().values.any(): raise ValueError("Series contains NaNs") series = series.values elif np.isnan(np.min(series)): raise ValueError("Series contains NaNs") def to_inc(x): incs = x[1:] - x[:-1] return incs def to_pct(x): pcts = x[1:] / x[:-1] - 1. return pcts def RS_func(series): incs = to_pct(series) mean_inc = np.sum(incs) / len(incs) deviations = incs - mean_inc Z = np.cumsum(deviations) R = max(Z) - min(Z) S = np.std(incs, ddof=1) return R / S err = np.geterr() np.seterr(all='raise') max_window = max_window or len(series)-1 window_sizes = [15,30,45,90,180,360] RS = [] for w in window_sizes: rs = [] for start in range(0, len(series), w): if (start+w)>len(series): break _ = RS_func(series[start:start+w]) if _ != 0: rs.append(_) RS.append(np.mean(rs)) A = np.vstack([np.log10(window_sizes), np.ones(len(RS))]).T H, c = np.linalg.lstsq(A, np.log10(RS), rcond=-1)[0] np.seterr(**err) c = 10**c return Hbut when I use it to produce a column of H values corresponding with the time series, it remains static and gives me the same data for each row.

df['Range'] = df.apply(lambda x: custom_hurst(df), axis=1)

```
Output: Range
Date
1983-03-30 29.40 0.672943
1983-03-31 29.29 0.672943
1983-04-04 29.44 0.672943
1983-04-05 29.71 0.672943
1983-04-06 29.90 0.672943
... ...
2020-12-30 48.31 0.672943
2020-12-31 48.42 0.672943
2021-01-04 47.35 0.672943
2021-01-05 49.80 0.672943
2021-01-06 50.52 0.672943
```

how can I have it applied dynamically so that it incorporates the previous 360 values in a rolling fashion instead of just the last 360 in the df? I've tried rolling functions, for loops, changing the code, but nothing seems to work.Any help would be appreciated

Thanks

Matt