bMh 8dZgdZddlmZddlmZddlZddlm Z m Z m Z ddl m Z mZdd lmZmZmZmZdd ZGd dZGddeZGddeZGddeZGddeZGddeZGddeZdS)z*1D and 2D Wavelet packet transform module.)BaseNodeNode WaveletPacketNode2DWaveletPacket2DNodeNDWaveletPacketND) OrderedDict)productN)dwt dwt_max_levelidwt)Wavelet _check_dtype)dwt2dwtnidwt2idwtnadcg}t|dz D](}fd|Dfd|dddDz})|S)Nr cg|]}|zSr).0pathxs U/var/www/html/test/jupyter/venv/lib/python3.11/site-packages/pywt/_wavelet_packets.py z&get_graycode_order..s>>>t!d(>>>cg|]}|zSrr)rrys rrz&get_graycode_order..sDDDt!d(DDDr )range)levelrr"graycode_orderis `` rget_graycode_orderr(ssVN 519  EE>>>>~>>>DDDD~ddd/CDDDE r ceZdZdZdZdZdZdZd!dZd!dZ dZ d Z d Z d Z ed Zd"dZedZedZdZdZd#dZdZd$dZdZdZdZedZedZd#dZd%dZd%dZd Z dS)&ra BaseNode for wavelet packet 1D and 2D tree nodes. The BaseNode is a base class for `Node` and `Node2D`. It should not be used directly unless creating a new transformation type. It is included here to document the common interface of 1D and 2D node and wavelet packet transform classes. Parameters ---------- parent : Parent node. If parent is None then the node is considered detached (ie root). data : 1D or 2D array Data associated with the node. 1D or 2D numeric array, depending on the transform type. node_name : A name identifying the coefficients type. See `Node.node_name` and `Node2D.node_name` for information on the accepted subnodes names. Nc||_|O|j|_|j|_|jdz|_|j|_|j|z|_|j|_n#d|_d|_d|_d|_d|_||_|jd|_ ntj |j |_ | dS)Nr r )parentwaveletmoder%maxlevel _maxlevelraxesdata _data_shapenpasarrayshape_init_subnodes)selfr,r2 node_names r__init__zBaseNode.__init__:s  !>DL DI)DJ#_DN i/DI DIIDLDIDIDIDJ  9 #D  !z$//5D  r cF|jD]}||ddSN)PARTS _set_noder8parts rr7zBaseNode._init_subnodesUs4J ' 'D NN4 & & & & ' 'r Tctr<NotImplementedErrorr8r@r2 overwrites r_create_subnodezBaseNode._create_subnodeY!###r c |||s*||||S||||fi|}||||Sr<)_validate_node_name _get_noder>)r8node_clsr@r2rEkwargsnodes r_create_subnode_basezBaseNode._create_subnode_base\su   &&& (T^^D11=>>$'' 'xdD33F33 tT""" r c"t||Sr<)getattrr?s rrJzBaseNode._get_nodeestT"""r c(t|||dSr<)setattrr8r@rMs rr>zBaseNode._set_nodehsdD!!!!!r c2||ddSr<r>r?s r _delete_nodezBaseNode._delete_nodek tT"""""r c||jvrEtddd|jD|dS)N'Subnode name must be in [{}], not '{}'., c3 K|] }d|zV dSz'%s'Nrrps r z/BaseNode._validate_node_name..ps*WwWwghX^abXbWwWwWwWwWwWwr )r= ValueErrorformatjoinr?s rrIzBaseNode._validate_node_namensV tz ! !FMMdiiWwWwlplvWwWwWwNwNwy}~~  " !r cjtjz}tfdt d|dzDS)zThe path to the current node in tuple form. The length of the tuple is equal to the number of decomposition levels. cJg|]}|dz jz|jz Sr )PART_LEN)rnrr8s rrz'BaseNode.path_tuple..zsD111AaC.q>?111r r )rlenrftupler$)r8nlevrs` @r path_tuplezBaseNode.path_tuplersj y4yy$-'11111$QQ//11122 2r r,cp|dvsJ|j|jS|j4|jtt |jj|jzS|dkr"|j|j|Sn>|dkr8|j D]0}t||d}|||}||cS1dSz Try to find the value of maximum decomposition level if it is not specified explicitly. Parameters ---------- evaluate_from : {'parent', 'subnodes'} )r,subnodesNr,rn) r0r2r%rminr6r-r,_evaluate_maxlevelr=rPr8 evaluate_fromr9rMr%s rrpzBaseNode._evaluate_maxlevel}s 66666 > %> ! Y ": DIO$$dl!4!44 4 H $ ${&{55mDDD' j ( (!Z % % tY55# 33MBBE($ tr c|j|jS|d|_|j|d|_|jS)Nr,)rrrn)r0rpr8s rr/zBaseNode.maxlevelsV > %> !00x0HH > !!44:4NNDN~r c,|j|j dSr<)rrfrts rr9zBaseNode.node_namesy$-))r ch|j|jkr|Std)a2 Decompose node data creating DWT coefficients subnodes. Performs Discrete Wavelet Transform on the `~BaseNode.data` and returns transform coefficients. Note ---- Descends to subnodes and recursively calls `~BaseNode.reconstruct` on them. z$Maximum decomposition level reached.)r%r/ _decomposer`rts r decomposezBaseNode.decomposes2 : % %??$$ $CDD Dr ctr<rBrts rrwzBaseNode._decomposerGr FcH|js|jS||S)aX Reconstruct node from subnodes. Parameters ---------- update : bool, optional If True, then reconstructed data replaces the current node data (default: False). Returns: - original node data if subnodes do not exist - IDWT of subnodes otherwise. )has_any_subnoder2 _reconstruct)r8updates r reconstructzBaseNode.reconstructs+# 9   (((r ctr<rBrts rr|zBaseNode._reconstructrGr c||||}|2|r0|js)|||}|S)a Returns subnode or None (see `decomposition` flag description). Parameters ---------- part : Subnode name decompose : bool, optional If the param is True and corresponding subnode does not exist, the subnode will be created using coefficients from the DWT decomposition of the current node. (default: True) )rIrJis_emptyrx)r8r@rxsubnodes r get_subnodezBaseNode.get_subnodes^   &&&..&& ?y?? NN   nnT**Gr cdt|z}t|tr4 d|}n#t$rt |wxYwt|t rp|j/t||j|jzkrtd|r6| |d|jd||jdS|St |)a Find node represented by the given path. Similar to `~BaseNode.get_subnode` method with `decompose=True`, but can access nodes on any level in the decomposition tree. Parameters ---------- path : str String composed of node names. See `Node.node_name` and `Node2D.node_name` for node naming convention. Notes ----- If node does not exist yet, it will be created by decomposition of its parent node. zMInvalid path parameter type - expected string or tuple of strings but got %s.r+NzPath length is out of range.r T) type isinstancerirb TypeErrorstrr/rhrf IndexErrorr)r8rerrmsgs r __getitem__zBaseNode.__getitem__s$137::> dE " " ( (wwt}} ( ( (''' ( dC $ )II  === !?@@@ ''Qt}_(=tDD(** F## #s ?Ac"t|tr[|jDt|jt|z|j|jzkrt d|r||d|jd}|F||d|jd||d|jd}||||jd<dSt|trtj |j |_ ntj ||_ t|}|j j|kr!|j ||_ dSdSt!dt#|z)a Set node or node's data in the decomposition tree. Nodes are identified by string `path`. Parameters ---------- path : str String composed of node names. data : array or BaseNode subclass. NzPath length out of range.r Fz9Invalid path parameter type - expected string but got %s.)rrr/rhrrfrrrFrr4r5r2rdtypeastyperr)r8rr2rrs r __setitem__zBaseNode.__setitem__s{ dC  5 )DIT*T]T]-JJJ !<=== 8**4$-+@%HH?((a o)>EEE"..tAdmO/DeLLG04T]^^,---dH--1 " 49 5 5DII " 4 0 0DI$T**9?e++ $ 0 0 7 7DIII,+')-d455 5r c||}|j}d|_|r#|jr||jdSdSdS)z Remove node from the tree. Parameters ---------- path : str String composed of node names. N)r,r9rV)r8rrMr,s r __delitem__zBaseNode.__delitem__5s^Dz   0dn 0    / / / / / 0 0 0 0r c|jduSr<)r2rts rrzBaseNode.is_emptyHsyD  r cDtfdjDS)Nc3FK|]}|duVdSr<rJ)rr@r8s rr_z+BaseNode.has_any_subnode..Ns4KK4>>$''t3KKKKKKr )anyr=rts`rr{zBaseNode.has_any_subnodeLs(KKKK KKKKKKr cHgfd}||S)z Returns leaf nodes. Parameters ---------- decompose : bool, optional (default: True) c|j|jkr|js|dSs|js|dSdSNFT)r%r/rappendr{)rMrxresults rcollectz(BaseNode.get_leaf_nodes..collect[s^zT]**4=* d###u T%9  d###u4r rx)walk)r8rxrrs ` @rget_leaf_nodeszBaseNode.get_leaf_nodesPsF       'Y /// r rc|i}||g|Ri|rJ|j|jkr<|jD]6}|||}||||||3dSdSdS)as Traverses the decomposition tree and calls ``func(node, *args, **kwargs)`` on every node. If `func` returns True, descending to subnodes will continue. Parameters ---------- func : callable Callable accepting `BaseNode` as the first param and optional positional and keyword arguments args : func params kwargs : func keyword params decompose : bool, optional If True (default), the method will also try to decompose the tree up to the `maximum level `. N)r%r/r=rrr8funcargsrLrxr@rs rrz BaseNode.walkfs& >F 4 &t & & &v & & @4: +E+E  @ @**4;;&LLtVY???  @ @+E+E @ @r c|i}|j|jkr:|jD]2}|||}||||||3||g|Ri|dS)a Walk tree and call func on every node starting from the bottom-most nodes. Parameters ---------- func : callable Callable accepting :class:`BaseNode` as the first param and optional positional and keyword arguments args : func params kwargs : func keyword params decompose : bool, optional (default: False) N)r%r/r=r walk_depthrs rrzBaseNode.walk_depths" >F : % %  F F**4;;&&&tT69EEE T#D###F#####r c@|jdzt|jzS)Nz: )rrr2rts r__str__zBaseNode.__str__sy4#di..00r NTr,)FT)rNT)!__name__ __module__ __qualname____doc__rfr=r:r7rFrNrJr>rVrIpropertyrkrpr/r9rxrwr~r|rrrrrr{rrrrrr rrrs#0H E6'''$$$$###"""###@@@22X2:  X **X*EEE$$$$))))$$$$*$$$$$$L#5#5#5J000&!!X!LLXL,@@@@6$$$$411111r rc:eZdZdZdZdZeefZdZd dZdZ d Z dS) rz WaveletPacket tree node. Subnodes are called `a` and `d`, just like approximation and detail coefficients in the Discrete Wavelet Transform. rrr NTc>|t|||SN)rKr@r2rE)rNrrDs rrFzNode._create_subnodes((($T3<)>> >r c|jrpd\}}||j||j|||j||j|n`t |j|j|j|j \}}||j|||j|||j||jfS)zq See also -------- dwt : for 1D Discrete Wavelet Transform output coefficients. NNNaxis) rrJArFDr r2r-r.r1)r8data_adata_ds rrwzNode._decomposes = 1'NFF~~df%%-$$TVV444~~df%%-$$TVV444 DL$)&*i111NFF   0 0 0   0 0 0~~df%%t~~df'='===r cd\}}||j||j}}||}||}||t dt |||j|j|j}|j 4|j |j kr$|td|j D}|r||_ |S)Nrz>Node is a leaf node and cannot be reconstructed from subnodes.rc,g|]}t|Srslicerszs rrz%Node._reconstruct.. F F Frr F F Fr ) rJrrr~r`rr-r.r1r3r6rir2)r8r}rrnode_anode_drecs rr|zNode._reconstructs#//1G1G  ''))F  ''))F >fn/00 0vvt|TYTYOOOC+I!111% F FT5E F F FGGH  Jr r) rrrrrrr=rfrFrwr|rr rrrsj A A qDEH>>>>>>>(r rcLeZdZdZdZdZdZdZeeeefZdZ d d Z d Z d Z d Z dS)rz WaveletPacket tree node. Subnodes are called 'a' (LL), 'h' (HL), 'v' (LH) and 'd' (HH), like approximation and detail coefficients in the 2D Discrete Wavelet Transform rhvrr NTc>|t|||Sr)rNrrDs rrFzNode2D._create_subnodes(((&t$3<)>> >r c |jrd\}}}}n.t|j|j|j|j\}\}}}||j|||j|||j |||j || |j| |j | |j| |j fS)q See also -------- dwt2 : for 2D Discrete Wavelet Transform output coefficients. NNNNr1) rrr2r-r.r1rFLLLHHLHHrJ)r8data_lldata_lhdata_hldata_hhs rrwzNode2D._decomposes = I1G .GWgwwTY didiHHH 1G0gw TWg... TWg... TWg... TWg...tw'')@)@tw'')@)@B Br cd\}}}}||j||j||j||jf\}}}} ||}||}||}| | }||||t d|jz||||ff} t| |j |j |j } |j 4| j |j kr$| td|j D} |r| |_| S)NrSTree is missing data - all subnodes of `%s` node are None. Cannot reconstruct node.rc,g|]}t|Srrrs rrz'Node2D._reconstruct..rr )rJrrrrr~r`rrr-r.r1r3r6rir2) r8r}rrrrnode_llnode_lhnode_hlnode_hhcoeffsrs rr|zNode2D._reconstructsx-C*'7 NN47 # #T^^DG%<%< NN47 # #T^^DG%<%< = +'7  ))++G  ))++G  ))++G  ))++G OGO57;yA  w99F didiHHHC+I!111% F FT5E F F FGGH  Jr c|jd|jd|jd|jdidfd|Ddfd|DfS)Nhhhllhllr+c,g|]}|dS)r rrr^expanded_pathss rrz)Node2D.expand_2d_path..'#<<.(rr )rrrrrb)r8rrs @rexpand_2d_pathzNode2D.expand_2d_path sz GT GT GT GT   <<<>>>BBB$@?????r rc\eZdZdZfdZdZdZdZdZdZ dd Z dd Z d Z dZ xZS)raV WaveletPacket tree node. Unlike Node and Node2D self.PARTS is a dictionary. For 1D: self.PARTS has keys 'a' and 'd' For 2D: self.PARTS has keys 'aa', 'ad', 'da', 'dd' For 3D: self.PARTS has keys 'aaa', 'aad', 'ada', 'daa', ..., 'ddd' Parameters ---------- parent : Parent node. If parent is None then the node is considered detached (ie root). data : 1D or 2D array Data associated with the node. 1D or 2D numeric array, depending on the transform type. node_name : string A name identifying the coefficients type. See `Node.node_name` and `Node2D.node_name` for information on the accepted subnodes names. ndim : int The number of data dimensions. ndim_transform : int The number of dimensions that are to be transformed. ct|||||_t|_t d|jzD]}d|jd|< ||_||_dS)N)r,r2r9)adr+) superr:rfr r=r rbndimndim_transform)r8r,r2r9rrkey __class__s rr:zNodeND.__init__Fs T/8  : : :&  ]] Xdm35 , ,C'+DJrwws|| $ $ ,r cdSr<rrts rr7zNodeND._init_subnodesPs  r c|j|Sr<)r=r?s rrJzNodeND._get_nodeUsz$r cJ||jvrtd||j|<dS)Nz invalid part)r=r`rSs rr>zNodeND._set_nodeXs/ tz ! !^,, , 4r c2||ddSr<rUr?s rrVzNodeND._delete_node]rWr c ||jvrdtdddt |jD|dS)NrYrZc3 K|] }d|zV dSr\rr]s rr_z-NodeND._validate_node_name..cs(JwJwZ[6TU:JwJwJwJwJwJwr )r=r`rarblistkeysr?s rrIzNodeND._validate_node_name`st tz ! !9@@JwJw_cdhdndsdsdudu_v_vJwJwJwAwAwy}~~@@ @ " !r NTcV|t||||j|jS)N)rKr@r2rErr)rNrrrrDs rrFzNodeND._create_subnodees5((&t$3<498<8K)MM Mr r,cx|dvsJ|j|jS|j4|jtt |jj|jzS|dkr"|j|j|SnB|dkr<|j D]"\}}|||}||cS#dSrm) r0r2r%rror6r-r,rpr=itemsrqs rrpzNodeND._evaluate_maxleveljs 66666 > %> ! Y ": DIO$$dl!4!44 4 H $ ${&{55mDDD' j ( (#':#3#3#5#5 % % 4# 33MBBE($ tr c jrdjD}n'tjjjj}|D]\}}||fdjDS)rci|]}|dSr<rrrs r z%NodeND._decompose..s5553S$555r rc3BK|]}|VdSr<r)rrr8s rr_z$NodeND._decompose..s/::s##::::::r ) rr=rr2r-r.r1rrF)r8coefsrr2s` rrwzNodeND._decomposes = M55$*555EEDL$)$)LLLE , ,IC  d + + + +::::tz::::r c6d|jD}d}|jD]5}||}||dz }|||<6|dkrtd|jzt ||j|j|j}|r||_ |S)Nci|]}|dSr<rrs rrz'NodeND._reconstruct..s222#t222r r r rr) r=rJr~r`rrr-r.r1r2)r8r}rnnodesrrMrs rr|zNodeND._reconstructs22tz222: 1 1C>>#&&D! "..00s Q;;57;yA   didiHHHC  Jr rr)rrrrr:r7rJr>rVrIrFrprwr| __classcell__rs@rrr+s4-----         ###@@@ MMMM 8 ; ; ;r rcBeZdZdZ d fd ZdZd fd Zd d ZxZS)ra Data structure representing Wavelet Packet decomposition of signal. Parameters ---------- data : 1D ndarray Original data (signal) wavelet : Wavelet object or name string Wavelet used in DWT decomposition and reconstruction mode : str, optional Signal extension mode for the `dwt` and `idwt` decomposition and reconstruction functions. maxlevel : int, optional Maximum level of decomposition. If None, it will be calculated based on the `wavelet` and `data` length using `pywt.dwt_max_level`. axis : int, optional The axis to transform. symmetricNr#ctd|dt|tst|}||_||_||_|tj|}|jdkr|j|j z|_d|jcxkr |j ksntd|j |_ |%t|j |j|j}nd|_ ||_dS)Nr+r z!Axis greater than data dimensions)rr:rrr-r.r1r4r5rr`r6 data_sizerr0)r8r2r-r.r/rrs rr:zWaveletPacket.__init__s tR((('7++ 'g&&G    :d##Dy1}} I 1  ----DI---- !DEEE!ZDN(DI)> MM!DN!r cDt|j|j|j|jffSr<)rr2r-r.r/rts r __reduce__zWaveletPacket.__reduce__s%DL$)T]CE Er Tc|jrZt|}|j'|j|jkr|d|jD}|r||_|S|jS)a  Reconstruct data value using coefficients from subnodes. Parameters ---------- update : bool, optional If True (default), then data values will be replaced by reconstruction values, also in subnodes. Nc,g|]}t|Srrrs rrz-WaveletPacket.reconstruct..@@@2U2YY@@@r r{rr~r r6r2r8r}r2rs rr~zWaveletPacket.reconstructt   77&&v..D~)tzT^/K/K@@@@@A !  Kyr naturalcH|dvrtd||jkrtd|jzgfd}||||dkrS|dkr)dDt}fd |DStd |d ) a Returns all nodes on the specified level. Parameters ---------- level : int Specifies decomposition `level` from which the nodes will be collected. order : {'natural', 'freq'}, optional - "natural" - left to right in tree (default) - "freq" - band ordered decompose : bool, optional If set then the method will try to decompose the data up to the specified `level` (default: True). Notes ----- If nodes at the given level are missing (i.e. the tree is partially decomposed) and `decompose` is set to False, only existing nodes will be returned. Frequency order (``order="freq"``) is also known as sequency order and "natural" order is sometimes referred to as Paley order. A detailed discussion of these orderings is also given in [1]_, [2]_. References ---------- ..[1] M.V. Wickerhauser. Adapted Wavelet Analysis from Theory to Software. Wellesley. Massachusetts: A K Peters. 1994. ..[2] D.B. Percival and A.T. Walden. Wavelet Methods for Time Series Analysis. Cambridge University Press. 2000. DOI:10.1017/CBO9780511841040 rfreqInvalid order: KThe level cannot be greater than the maximum decomposition level value (%d)cL|jkr|dSdSrr%rrMr%rs rrz(WaveletPacket.get_level..collect,zU"" d###u4r rrrci|] }|j| Sr)r)rrMs rrz+WaveletPacket.get_level.."s999$di999r c(g|]}|v|Srr)rrrs rrz+WaveletPacket.get_level..$s"NNNTtv~~F4L~~~r zInvalid order name - .)r`r/rr()r8r%orderrxrr&rs ` @r get_levelzWaveletPacket.get_levelsD + + +6u6677 7 4= ?AEOPP P       'Y /// I  M f__99&999F/66NNNNN^NNN N=U===>> >r )rNr#rrT rrrrr:r r~r rrs@rrrs&BF""""""0EEE&8?8?8?8?8?8?8?8?r rcBeZdZdZ d fd ZdZd fd Zd d ZxZS)ra Data structure representing 2D Wavelet Packet decomposition of signal. Parameters ---------- data : 2D ndarray Data associated with the node. wavelet : Wavelet object or name string Wavelet used in DWT decomposition and reconstruction mode : str, optional Signal extension mode for the `dwt` and `idwt` decomposition and reconstruction functions. maxlevel : int Maximum level of decomposition. If None, it will be calculated based on the `wavelet` and `data` length using `pywt.dwt_max_level`. axes : 2-tuple of ints, optional The axes that will be transformed. smoothNr#cRtddt|tst|}||_||_t ||_ttj |jdkrtdrtj j dkrtdj|_fd|jD}|"t!t#||j}nd|_||_dS)Nr+zExpected two unique axes.z8WaveletPacket2D requires data with 2 or more dimensions.c*g|]}j|Srr6raxr2s rrz,WaveletPacket2D.__init__..NAAAdjnAAAr )rr:rrr-r.rir1rhr4uniquer`r5rr6r rror0)r8r2r-r.r/r1transform_sizers ` rr:zWaveletPacket2D.__init__=s tR((('7++ 'g&&G  $KK ry## $ $ ) )899 9  :d##Dy1}} NPPP!ZDNAAAAtyAAAN(^)<).frr rrs rr~zWaveletPacket2D.reconstructYrr rc |dvrtd|jkrtdjzg  fd}|||dkrzi fd DD]!\\}}}| |i|<"t dd } fd |D g D]#  fd |D$ S) a Returns all nodes from specified level. Parameters ---------- level : int Decomposition `level` from which the nodes will be collected. order : {'natural', 'freq'}, optional If `natural` (default) a flat list is returned. If `freq`, a 2d structure with rows and cols sorted by corresponding dimension frequency of 2d coefficient array (adapted from 1d case). decompose : bool, optional If set then the method will try to decompose the data up to the specified `level` (default: True). Notes ----- Frequency order (``order="freq"``) is also known as as sequency order and "natural" order is sometimes referred to as Paley order. A detailed discussion of these orderings is also given in [1]_, [2]_. References ---------- ..[1] M.V. Wickerhauser. Adapted Wavelet Analysis from Theory to Software. Wellesley. Massachusetts: A K Peters. 1994. ..[2] D.B. Percival and A.T. Walden. Wavelet Methods for Time Series Analysis. Cambridge University Press. 2000. DOI:10.1017/CBO9780511841040 rrrcL|jkr|dSdSrrrs rrz*WaveletPacket2D.get_level..collectrr rrcHg|]}|j|fSr)rr)rrMr8s rrz-WaveletPacket2D.get_level..s;///;?$$TY//6///r lr)rr"c(g|]}|v|Srr)rrnodess rrz-WaveletPacket2D.get_level..s"MMMTtu}}U4[}}}r c(g|]}|v|Srr)rrrows rrz-WaveletPacket2D.get_level..s"III4TS[[SY[[[r )r`r/r setdefaultr(r) r8r%rrxrrow_pathcol_pathrMr&r9rr;s `` @@@rr zWaveletPacket2D.get_levells@ + + +6u6677 7 4= ?AEOPP P       'Y /// F??E////CI/// @ @*$8d<@  2..x88/DDDNMMMM^MMMEF   IIII>III r )r$Nr%rr!r"rs@rrr)s&?C""""""0EEE&========r rc<eZdZdZ dfd Zd fd Zd dZxZS) ra Data structure representing ND Wavelet Packet decomposition of signal. Parameters ---------- data : ND ndarray Data associated with the node. wavelet : Wavelet object or name string Wavelet used in DWT decomposition and reconstruction mode : str, optional Signal extension mode for the `dwt` and `idwt` decomposition and reconstruction functions. maxlevel : int, optional Maximum level of decomposition. If None, it will be calculated based on the `wavelet` and `data` length using `pywt.dwt_max_level`. axes : tuple of int, optional The axes to transform. The default value of `None` corresponds to all axes. r$Nc|td|tj}ntj|r|f}t |}t tj|t |krtdt |}6tjjdkrtdj}nt |}t dd||t|tst|}||_ ||_||_||_kjt |krtdj|_fd|jD}|"t't)||j }nd|_||_dS)Nz'If data is None, axes must be specifiedzExpected a set of unique axes.r zdata must be at least 1Dr+z9The number of axes exceeds the number of data dimensions.c*g|]}j|Srr*r+s rrz,WaveletPacketND.__init__..r-r )r`r$rr4isscalarrirhr.r5rr:rrr-r.r1rr6r rror0) r8r2r-r.r/r1rrr/rs ` rr:zWaveletPacketND.__init__s Lt|FGG G <##DD [   8DT{{ ry  3t99 , ,=>> >T  :d##DyA~~ !;<<<9DDt99D tR.< > > >'7++ 'g&&G   ,  y3t99$$ "4555!ZDNAAAAtyAAAN(^)<).rr rrs rr~zWaveletPacketND.reconstructrr c|jkrtd|jzgfd}|||S)ah Returns all nodes from specified level. Parameters ---------- level : int Decomposition `level` from which the nodes will be collected. decompose : bool, optional If set then the method will try to decompose the data up to the specified `level` (default: True). rcL|jkr|dSdSrrrs rrz*WaveletPacketND.get_level..collectrr r)r/r`r)r8r%rxrrs ` @rr zWaveletPacketND.get_levelsz 4= ?AEOPP P       'Y /// r )r$NNr)rrrrr:r~r rrs@rrrs(?C*"*"*"*"*"*"X&r r)rr)r__all__ collectionsr itertoolsr numpyr4_dwtr rr_extensions._pywtrr _multidimrrrrr(rrrrrrrrr rrNs$ 10 ( ( ($#####**********44444444////////////~1~1~1~1~1~1~1~1B 888888888vN?N?N?N?N?XN?N?N?b}}}}}X}}}@{?{?{?{?{?D{?{?{?|@@@@@f@@@Fooooofooooor