From 4a3fd5e3cdb173532b5e28a01d1c45b6c4725e82 Mon Sep 17 00:00:00 2001 From: Maximilian Gruber Date: Tue, 17 Mar 2020 08:52:08 +0100 Subject: [PATCH] fix(propagate_DWT): adjust __all__ variable --- PyDynamic/uncertainty/propagate_DWT.py | 14 +++++++++++++- 1 file changed, 13 insertions(+), 1 deletion(-) diff --git a/PyDynamic/uncertainty/propagate_DWT.py b/PyDynamic/uncertainty/propagate_DWT.py index b14f70567..69fca70d0 100644 --- a/PyDynamic/uncertainty/propagate_DWT.py +++ b/PyDynamic/uncertainty/propagate_DWT.py @@ -12,7 +12,7 @@ from PyDynamic.uncertainty.propagate_filter import IIRuncFilter, get_initial_state, FIRuncFilter -__all__ = ["dwt", "wave_dec", "idwt", "wave_rec", "filter_design"] +__all__ = ["dwt", "wave_dec", "wave_dec_realtime", "idwt", "wave_rec", "filter_design"] def dwt(x, Ux, l, h, kind, states=None, realtime=False, subsample_start=1): @@ -40,6 +40,10 @@ def dwt(x, Ux, l, h, kind, states=None, realtime=False, subsample_start=1): only meaningfull in combination with isinstance(Ux, numpy.ndarray) "diag": point-wise standard uncertainties of non-stationary white noise "corr": single sided autocovariance of stationary (colored/corrlated) noise (default) + states: dictionary of internal high/lowpass-filter states + allows to continue at the last used internal state from previous call + realtime: Boolean + for realtime applications, no signal padding has to be done before decomposition Returns ------- @@ -51,6 +55,8 @@ def dwt(x, Ux, l, h, kind, states=None, realtime=False, subsample_start=1): subsampled high-pass output signal U_detail: np.ndarray subsampled high-pass output uncertainty + states: dictionary of internal high/lowpass-filter states + allows to continue at the last used internal state in next call """ # prolongate signals if no realtime is needed @@ -103,6 +109,10 @@ def idwt(c_approx, U_approx, c_detail, U_detail, l, h, kind, states=None, realti only meaningfull in combination with isinstance(Ux, numpy.ndarray) "diag": point-wise standard uncertainties of non-stationary white noise "corr": single sided autocovariance of stationary (colored/corrlated) noise (default) + states: dictionary of internal high/lowpass-filter states + allows to continue at the last used internal state from previous call + realtime: Boolean + for realtime applications, no signal padding has to be undone after reconstruction Returns ------- @@ -110,6 +120,8 @@ def idwt(c_approx, U_approx, c_detail, U_detail, l, h, kind, states=None, realti upsampled reconstructed signal Ux: np.ndarray upsampled uncertainty of reconstructed signal + states: dictionary of internal high/lowpass-filter states + allows to continue at the last used internal state in next call """ # upsample to double the length