+ [j'8^RIHtHt^RIt^RIHtHtHtH t H t H t H t ^RI HtHtHtHtHtHtHt^RIHtHt.R OtR RltRtRRltR tRR ltR tR#))partialreduceN)_prep_axes_wavedecnwavedecwavedec2wavedecnwaverecwaverec2waverecn)iswtiswt2iswtnswtswt2 swt_max_levelswtn)_modes_per_axis_wavelets_per_axisc nVR8XdBVR8wd \R4hRVRVRR/p\\3RVR R/VBp\\3/VBpRp MBVR 8Xd.RVR VRV/p\\3RV/VBp\\ 3/VBpR p M\R V 24hV!V4p .p \ V 4p V 'd)\P!V ^,4p V .V ,pM%V Uu.uFp\P!V4NK pp\V 4FpV V,VV&V!V4pVPVP8wd6T\VPUu.uFp\V4NK up4,pV PV4V 'dX VV&K\P!VV,4VV&K V #uupiuupi)aForward 1D multiresolution analysis. It is a projection onto the wavelet subspaces. Parameters ---------- data: array_like Input data wavelet : Wavelet object or name string Wavelet to use level : int, optional Decomposition level (must be >= 0). If level is None (default) then it will be calculated using the `dwt_max_level` function. axis: int, optional Axis over which to compute the DWT. If not given, the last axis is used. Currently only available when ``transform='dwt'``. transform : {'dwt', 'swt'} Whether to use the DWT or SWT for the transforms. mode : str, optional Signal extension mode, see `Modes` (default: 'symmetric'). This option is only used when transform='dwt'. Returns ------- [cAn, {details_level_n}, ... {details_level_1}] : list For more information, see the detailed description in `wavedec` See Also -------- imra, swt Notes ----- This is sometimes referred to as an additive decomposition because the inverse transform (``imra``) is just the sum of the coefficient arrays [1]_. The decomposition using ``transform='dwt'`` corresponds to section 2.2 while that using an undecimated transform (``transform='swt'``) is described in section 3.2 and appendix A. This transform does not share the variance partition property of ``swt`` with `norm=True`. It does however, result in coefficients that are temporally aligned regardless of the symmetry of the wavelet used. The redundancy of this transform is ``(level + 1)``. References ---------- .. [1] Donald B. Percival and Harold O. Mofjeld. Analysis of Subtidal Coastal Sea Level Fluctuations Using Wavelets. Journal of the American Statistical Association Vol. 92, No. 439 (Sep., 1997), pp. 868-880. https://doi.org/10.2307/2965551 r periodization0transform swt only supports mode='periodization'waveletaxisnormTlevel trim_approxdwtmodeFunrecognized transform: ) ValueErrorrrr rr lennp zeros_likerangeshapetuplesliceappend)datarrr transformrkwargsforwardinverseis_swt wav_coeffs mra_coeffsncztmpcjrecszs&&&&&& J/home/luca/screen-checking/.venv/lib/python3.14/site-packages/pywt/_mra.pymrar9snE ? "BD DWfdFDA#GUGGG$)&) e WfdFDA'99&9',V,3I;?@@JJ ZB MM*Q- (ebj*44Ar}}Q4 2YAAcl 99 "e<2U2Y<=>C# CF]]3q6*CF %5=s F-F2 c\RV4#)aInverse 1D multiresolution analysis via summation. Parameters ---------- mra_coeffs : list of ndarray Multiresolution analysis coefficients as returned by `mra`. Returns ------- rec : ndarray The reconstructed signal. See Also -------- mra References ---------- .. [1] Donald B. Percival and Harold O. Mofjeld. Analysis of Subtidal Coastal Sea Level Fluctuations Using Wavelets. Journal of the American Statistical Association Vol. 92, No. 439 (Sep., 1997), pp. 868-880. https://doi.org/10.2307/2965551 cW,#N)xys&&r8imra..squ)r)r0s&r8imrarC{s0 $j 11rBc  VR8Xd`VR8wd \R4hVf\RVP44pRVRVRR/p\\3R VR R/VBp\\ 3/VBpM@VR 8Xd,RVR VRV/p\\ 3R V/VBp\\3/VBpM\R V 24hV!V4p .p \V 4p \P!V ^,4p V .p \^V 4F>pT PW,Uu.uFp\P!V4NK up4K@ V ^,V ^&V!V 4pVPVP8wd6T\VPUu.uFp\V4NK up4,pV PV4W^&\^V 4Fp.p\^4FpW,V,p W,V,W,V&V!V 4pVPVP8wd6T\VPUu.uFp\V4NK up4,pVPV4WV,V&K V P\V44K V #uupiuupiuupi)aUForward 2D multiresolution analysis. It is a projection onto wavelet subspaces. Parameters ---------- data: array_like Input data wavelet : Wavelet object or name string, or 2-tuple of wavelets Wavelet to use. This can also be a tuple containing a wavelet to apply along each axis in `axes`. level : int, optional Decomposition level (must be >= 0). If level is None (default) then it will be calculated using the `dwt_max_level` function. axes : 2-tuple of ints, optional Axes over which to compute the DWT. Repeated elements are not allowed. Currently only available when ``transform='dwt2'``. transform : {'dwt2', 'swt2'} Whether to use the DWT or SWT for the transforms. mode : str or 2-tuple of str, optional Signal extension mode, see `Modes` (default: 'symmetric'). This option is only used when transform='dwt2'. Returns ------- coeffs : list For more information, see the detailed description in `wavedec2` Notes ----- This is sometimes referred to as an additive decomposition because the inverse transform (``imra2``) is just the sum of the coefficient arrays [1]_. The decomposition using ``transform='dwt'`` corresponds to section 2.2 while that using an undecimated transform (``transform='swt'``) is described in section 3.2 and appendix A. This transform does not share the variance partition property of ``swt2`` with `norm=True`. It does however, result in coefficients that are temporally aligned regardless of the symmetry of the wavelet used. The redundancy of this transform is ``3 * level + 1``. See Also -------- imra2, swt2 References ---------- .. [1] Donald B. Percival and Harold O. Mofjeld. Analysis of Subtidal Coastal Sea Level Fluctuations Using Wavelets. Journal of the American Statistical Association Vol. 92, No. 439 (Sep., 1997), pp. 868-880. https://doi.org/10.2307/2965551 rrrc38"TFp\V4xK R#5ir<r.0ss& r8 mra2..=*Q a((*raxesrTrrdwt2rr)r minr%rrr rr r!r"r#r$r(r&r')r)rrrNr*rr+r,r-r/r0r1r2r3r5r4r6r7dcoeffsns&&&&&& r8mra2rSsUnF ? "BD D ==$**==EWfdFDA$HeHHH%*6* f WfdFDA(:%:6:(-f-3I;?@@JJ ZB jm$A #C 1b\ jm= 0). If level is None (default) then it will be calculated using the `dwt_max_level` function. axes : tuple of ints, optional Axes over which to compute the DWT. Repeated elements are not allowed. transform : {'dwtn', 'swtn'} Whether to use the DWT or SWT for the transforms. mode : str or tuple of str, optional Signal extension mode, see `Modes` (default: 'symmetric'). This option is only used when transform='dwtn'. Returns ------- coeffs : list For more information, see the detailed description in `wavedecn`. See Also -------- imran, swtn Notes ----- This is sometimes referred to as an additive decomposition because the inverse transform (``imran``) is just the sum of the coefficient arrays [1]_. The decomposition using ``transform='dwt'`` corresponds to section 2.2 while that using an undecimated transform (``transform='swt'``) is described in section 3.2 and appendix A. This transform does not share the variance partition property of ``swtn`` with `norm=True`. It does however, result in coefficients that are temporally aligned regardless of the symmetry of the wavelet used. The redundancy of this transform is ``(2**n - 1) * level + 1`` where ``n`` corresponds to the number of axes transformed. References ---------- .. [1] Donald B. Percival and Harold O. Mofjeld. Analysis of Subtidal Coastal Sea Level Fluctuations Using Wavelets. Journal of the American Statistical Association Vol. 92, No. 439 (Sep., 1997), pp. 868-880. https://doi.org/10.2307/2965551 rrrc38"TFp\V4xK R#5ir<rFrGs& r8rJmran..arLrMrrNrTrrdwtnrr)rr%rr rPrrrrrr r!r"r#r$r(itemsr&r'listkeys)r)rrrNr*r axes_shapesndim_transformwaveletsr+r,r-modesr/r0r1r2r3r5kvr6r7rQdkeyss&&&&&& r8mranrd"sn)rosR%EDD7 ;dN26jZ>qhrB