Warn when SPA is reloaded #614
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| # Forecast functions | ||
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| def get_num_intervals(end, start, deltat): |
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E302 expected 2 blank lines, found 1
| K = get_num_intervals(start, max(history.index), deltat) | ||
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| # find number of deltat intervals covering dataWindowLength in history | ||
| N = get_num_intervals(start - K*deltat, |
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E226 missing whitespace around arithmetic operator
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| # find number of deltat intervals covering dataWindowLength in history | ||
| N = get_num_intervals(start - K*deltat, | ||
| start - K*deltat - dataWindowLength, |
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E226 missing whitespace around arithmetic operator
| # calculate base time for resample, minutes out of phase with midnight | ||
| midnight = resample_start.replace(hour=0, minute=0, second=0) | ||
| first_after_midnight = resample_start - \ | ||
| int((resample_start - midnight) / deltat) * deltat |
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E127 continuation line over-indented for visual indent
| base=base).mean() | ||
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| # extract window from resampled history | ||
| return idata.loc[(idata.index>=resample_start) & |
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E225 missing whitespace around operator
| trend='n', | ||
| order=order) | ||
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| # if not provided, generate guess of model parameters, helps overcome |
| # if not provided, generate guess of model parameters, helps overcome | ||
| # non-stationarity | ||
| if not start_params: | ||
| # generate a list with one entry '0' for each AR or MA parameter |
| # generate a list with one entry '0' for each AR or MA parameter | ||
| # plus an entry '1' for the variance parameter | ||
| start_params = [] | ||
| for i in range(0, order[0]+order[2]): |
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E226 missing whitespace around arithmetic operator
| end=end, | ||
| freq=pd.to_timedelta(deltat)) | ||
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| f_intervals = len(idr-1) # first time in idr is last data point |
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E226 missing whitespace around arithmetic operator
E261 at least two spaces before inline comment
| # return the requested forecast times | ||
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| return f[fdr] | ||
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W391 blank line at end of file
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