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Jc@ sdZddklZddkZddkZddkZddklZddkl Z ddk i Z ddk l Z ddkiZddkiZddkiZddkiZddkiZddkTde ieifd YZd efd YZd e ieifd YZde ieifdYZdZe e e e e dZ!dZ"dde#dZ$dS(sS The image module supports basic image loading, rescaling and display operations. i(tdivisionN(tma(trcParams(tallow_rasterization(t*t AxesImagec B seZdZheid6eid6eid6eid6eid6ei d6ei d6ei d6ei d 6ei d 6eid 6eid 6eid 6eid6eid6eid6eid6ZegZeiD]\ZZeeefq[ZeiZdZd)d)d)d)d)dde dZ!dZ"dZ#dZ$ddZ%e&dZ'dZ(e dZ)dZ*dZ+dZ,d Z-d!Z.d"Z/d#Z0d$Z1d%Z2d&Z3d'Z4d(Z5RS(*itnearesttbilineartbicubictspline16tspline36thanningthammingthermitetkaisertquadrictcatromtgaussiantbesseltmitchelltsinctlanczostblackmancC sdt|iiiS(NsAxesImage(%g,%g;%gx%g)(ttupletaxestbboxtbounds(tself((s6/usr/lib64/python2.6/site-packages/matplotlib/image.pyt__str__7sg@c K stii|tii||||djotd}n||_||_|i ||i |||_ |i ||i | ||_d|_|i| dS(s interpolation and cmap default to their rc settings cmap is a colors.Colormap instance norm is a colors.Normalize instance to map luminance to 0-1 extent is data axes (left, right, bottom, top) for making image plots registered with data plots. 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Additional kwargs are matplotlib.artist properties s image.originN(tmartisttArtistt__init__tcmtScalarMappabletNoneRtorigint_extenttset_filternormt set_filterradt _filterradtset_interpolationt set_resampleRt_imcachetupdate( Rtaxtcmaptnormt interpolationR#textentt filternormt filterradtresampletkwargs((s6/usr/lib64/python2.6/site-packages/matplotlib/image.pyR:s          cC s.|idjotdn|iid S(s+Get the numrows, numcols of the input images"You must first set the image arrayiN(t_AR"t RuntimeErrortshape(R((s6/usr/lib64/python2.6/site-packages/matplotlib/image.pytget_sizeescC s tii||d|_dS(sw Set the alpha value used for blending - not supported on all backends ACCEPTS: float N(RRt set_alphaR"R*(Rtalpha((s6/usr/lib64/python2.6/site-packages/matplotlib/image.pyR9lscC s&d|_d|_tii|dS(sb Call this whenever the mappable is changed so observers can update state N(R"R*t _rgbacacheR R!tchanged(R((s6/usr/lib64/python2.6/site-packages/matplotlib/image.pyR<vs  g?c&C s|idjotdn|i\}}}}||}||}||iii}||iii} |iid \} } |djo|iii ||| } t dt | |i } |iii ||| }t| t ||i }t| |}|}|| || }|||| }||}||iii}ntd| }| djo|iii||| }t dt ||i }|iii||| }t| t ||i }|idjot| || |}nt||}|}|||| }|||| }||}||iii} ntd| }||ijp||ijod|_||_||_n|idjo!|iitijoNt|iidjo5ti|i||ddfd}t|_n|idjo%|i|i|i }||_n |i}ti!|||fd}t|iidjo|i"i#|_n t|_||_|idjo|i$qn |i}|ii%i&}t'i(i|d}|i)||i*|i+\} } | djp | djodS|i,|i-|i.|i/|i0||iii || }||iii|| }|ii1i2\}}} }!t3| dt3|d}"t3|!dt3|d}#|"|9}"|#|9}#|i4|||"| }$|#| }%|i5|$||%| |i6t |"dt |#dd|i7d |i |S( Ns9You must first set the image array or the image attributeiitupperiig?R.tradius(8R5R"R6t get_extentRtviewLimtwidththeightR7tx0tmaxtintR'tx1tmintslicety0ty1R#t _oldxslicet _oldysliceR*tdtypetnptuint8tlent_imagetfrombytetFalset is_grayscaleR;tto_rgbat_alphat fromarrayR-tis_grayt flipud_intpatcht get_facecolortmcolorstcolorConvertertset_bgt reset_matrixR8R(t_interpdt_interpolationR)t _resampleRtextentstroundtapply_translationt apply_scalingtresizet _filternorm(&Rt magnificationtxmintxmaxtymintymaxtdxintvtdyintvtsxtsytnumrowstnumcolsRCtix0RFtix1txslicetxmin_oldRItiy0RJtiy1tyslicetymin_oldtimtxtfctbgttxttytltbtrttt widthDisplayt heightDisplaytrxtry((s6/usr/lib64/python2.6/site-packages/matplotlib/image.pyt make_images          /(            #c O s|ipdS|iidjp|iidjotidn|i|i}|djodS|i |_ |ii i \}}}}|i \} } |it|t|||ii i| | dS(Ntlinears,Images are not supported on non-linear axes.(t get_visibleRt get_xscalet get_yscaletwarningstwarnRtget_image_magnificationR"tget_urlt_urlRRt$get_transformed_clip_path_and_affinet draw_imageRdtfrozen( RtrenderertargsR4R|RRRRtclippathtaffine((s6/usr/lib64/python2.6/site-packages/matplotlib/image.pytdraws  *c C st|io|i||S|i|i}}|i\}}}}||jo||}}n||jo||}}n|dj oD|dj o7||jo$||jo||jo ||j}nt}|hfS(sH Test whether the mouse event occured within the image. N(tcallablet _containstxdatatydataR?R"RS( Rt mouseeventR}tyRjRkRlRmtinside((s6/usr/lib64/python2.6/site-packages/matplotlib/image.pytcontainss  7c C s|i}|djodS|o=|i\}}|i|id|i||n|i|i\}}}ti ||||dS(s&Write the image to png file with fnameNi( RR"R8R_R(Rgt flipud_outt as_rgba_strt_pngt write_png( RtfnametnoscaleR|RrRstrowstcolstbuffer((s6/usr/lib64/python2.6/site-packages/matplotlib/image.pyR s     cC st|dot||_nti||_|iitijo-ti|iiti  ot dn|ii d jp*|ii djo'|ii dd jot dnd|_d|_d|_d|_dS( sI Set the image array ACCEPTS: numpy/PIL Image A tgetpixels#Image data can not convert to floatiiiis!Invalid dimensions for image dataN(ii(ii(thasattrt pil_to_arrayR5tcbooktsafe_masked_invalidRMRNROtcan_casttfloatt TypeErrortndimR7R"R*R;RKRL(RtA((s6/usr/lib64/python2.6/site-packages/matplotlib/image.pytset_datas3*   cC s|i|dS(sq retained for backwards compatibility - use set_data instead ACCEPTS: numpy array A or PIL ImageN(R(RR((s6/usr/lib64/python2.6/site-packages/matplotlib/image.pyt set_array3s cC s||_|\}}}}||f||ff}|ii||iio|ii||fn|iio|ii||fndS(sW extent is data axes (left, right, bottom, top) for making image plots N(R$Rtupdate_datalimt _autoscaleXontset_xlimt _autoscaleYontset_ylim(RR0RjRkRlRmtcorners((s6/usr/lib64/python2.6/site-packages/matplotlib/image.pyt set_extent@s   cC s|iS(s Return the interpolation method the image uses when resizing. One of 'nearest', 'bilinear', 'bicubic', 'spline16', 'spline36', 'hanning', 'hamming', 'hermite', 'kaiser', 'quadric', 'catrom', 'gaussian', 'bessel', 'mitchell', 'sinc', 'lanczos', (Ra(R((s6/usr/lib64/python2.6/site-packages/matplotlib/image.pytget_interpolationNscC sT|djotd}n|i}||ijotdn||_dS(s? Set the interpolation method the image uses when resizing. ACCEPTS: ['nearest' | 'bilinear' | 'bicubic' | 'spline16' | 'spline36' | 'hanning' | 'hamming' | 'hermite' | 'kaiser' | 'quadric' | 'catrom' | 'gaussian' | 'bessel' | 'mitchell' | 'sinc' | 'lanczos' | ] simage.interpolationsIllegal interpolation stringN(R"RtlowerR`t ValueErrorRa(Rts((s6/usr/lib64/python2.6/site-packages/matplotlib/image.pyR(Xs  cC s(|djotd}n||_dS(sZ set whether or not image resampling is used ACCEPTS: True|False simage.resampleN(R"RRb(Rtv((s6/usr/lib64/python2.6/site-packages/matplotlib/image.pyR)hs cC s|iS(s!return the image resample boolean(Rb(R((s6/usr/lib64/python2.6/site-packages/matplotlib/image.pyt get_resampleqscC su|idj o|iS|i}|\}}|idjod|d|ddfSd|dd|dfSdS(s.get the image extent: left, right, bottom, topR=gg?N(R$R"R8R#(RtszRrRs((s6/usr/lib64/python2.6/site-packages/matplotlib/image.pyR?us  cC s!|o d|_n d|_dS(sy Set whether the resize filter norms the weights -- see help for imshow ACCEPTS: 0 or 1 iiN(Rh(RR1((s6/usr/lib64/python2.6/site-packages/matplotlib/image.pyR%s cC s|iS(sreturn the filternorm setting(Rh(R((s6/usr/lib64/python2.6/site-packages/matplotlib/image.pytget_filternormscC s-t|}|djpt||_dS(s Set the resize filter radius only applicable to some interpolation schemes -- see help for imshow ACCEPTS: positive float iN(RtAssertionErrorR'(RR2R((s6/usr/lib64/python2.6/site-packages/matplotlib/image.pyR&s cC s|iS(sreturn the filterrad setting(R'(R((s6/usr/lib64/python2.6/site-packages/matplotlib/image.pyt get_filterradsN(6t__name__t __module__tzorderRQtNEARESTtBILINEARtBICUBICtSPLINE16tSPLINE36tHANNINGtHAMMINGtHERMITEtKAISERtQUADRICtCATROMtGAUSSIANtBESSELtMITCHELLtSINCtLANCZOStBLACKMANR`tdictt_[1]titemstkRt _interpdrtkeyst interpnamesRR"RSRR8R9R<RRRRRRRRRR(R)RR?R%RR&R(((s6/usr/lib64/python2.6/site-packages/matplotlib/image.pyRsb                 9   #  g        tNonUniformImagecB seeZdZddZdZdZdZdZdZdZ d Z d Z RS( cK s9|idd}ti|||ti||dS(sx kwargs are identical to those for AxesImage, except that 'interpolation' defaults to 'nearest' R/RN(tpopRRR((RR,R4tinterp((s6/usr/lib64/python2.6/site-packages/matplotlib/image.pyRs g?c C s2|idjotdn|iii\}}}}|iii\}}}} t|dt|d} t| dt|d} | |9} | |9} t i |i |i |i| | ||||||f|i |i} |iii} tii| d}| i||i| _| S(Ns"You must first set the image arrayg?i(R5R"R6RR@RRRcRdRQtpcolort_Axt_AyR`RaRZR[R\R]RUR^RT(RRiRCRItv_widthtv_heightRRRRRARBR|R~R((s6/usr/lib64/python2.6/site-packages/matplotlib/image.pyRs"    c C sti|ti}ti|ti}ti|}t|idjpAt|idjp+|idd!|id|idfjotdnt|id jotdnt|idjo$|idd jotdnt|idjo+|iddjo|idd!|_nt|idjo|iti jo>|i |i |d i ti }|i i |_qti|d d d d tifdd}d |d d d d df ,+**(1 /%     cG stddS(NsMethod not supported(tNotImplementedError(RR((s6/usr/lib64/python2.6/site-packages/matplotlib/image.pyRscC s>|djo|djotdnti||dS(NRRs?Only nearest neighbor and bilinear interpolations are supported(snearestsbilinear(R"RRR((RR((s6/usr/lib64/python2.6/site-packages/matplotlib/image.pyR(scC sL|idjotdn|id|id|id|idfS(NsMust set data firstii(R5R"R6RR(R((s6/usr/lib64/python2.6/site-packages/matplotlib/image.pyR?scC sdS(N((RR((s6/usr/lib64/python2.6/site-packages/matplotlib/image.pyR%scC sdS(N((RR((s6/usr/lib64/python2.6/site-packages/matplotlib/image.pyR&scC s7|idj otdntii||dS(Ns'Cannot change colors after loading data(R5R"R6R R!tset_norm(RR.((s6/usr/lib64/python2.6/site-packages/matplotlib/image.pyRscC s7|idj otdntii||dS(Ns'Cannot change colors after loading data(R5R"R6R R!tset_cmap(RR-((s6/usr/lib64/python2.6/site-packages/matplotlib/image.pyRs( RRRRRRR(R?R%R&RR(((s6/usr/lib64/python2.6/site-packages/matplotlib/image.pyRs  -      t PcolorImagecB s\eZdZddddddZddZedZdZdZ dZ RS( s Make a pcolor-style plot with an irregular rectangular grid. 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The output formats available depend on the backend being used. Arguments: *fname*: A string containing a path to a filename, or a Python file-like object. If *format* is *None* and *fname* is a string, the output format is deduced from the extension of the filename. *arr*: A 2D array. Keyword arguments: *vmin*/*vmax*: [ None | scalar ] *vmin* and *vmax* set the color scaling for the image by fixing the values that map to the colormap color limits. If either *vmin* or *vmax* is None, that limit is determined from the *arr* min/max value. *cmap*: cmap is a colors.Colormap instance, eg cm.jet. If None, default to the rc image.cmap value. *format*: One of the file extensions supported by the active backend. Most backends support png, pdf, ps, eps and svg. *origin* [ 'upper' | 'lower' ] Indicates where the [0,0] index of the array is in the upper left or lower left corner of the axes. 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For RGBA images the return value is MxNx4 cS s4|id|idd}ti|ti}|S(sreturn a 1D array of floatstrawii(ttostringtmodeRNt fromstringRO(R|tx_strR}((s6/usr/lib64/python2.6/site-packages/matplotlib/image.pyttoarray<stRGBAtRGBXtLiitRGBisUnknown image modei(R6R7(R2RR7tconvertRR6(tpilImageR5R|R}((s6/usr/lib64/python2.6/site-packages/matplotlib/image.pyR6s(       g?Rc C stii|\}}tii|\}}t|} | i\} } } d} t| | |}t| | |}|i}|o1ddki }|i d||fd| }n|djoddk l }nO|djodd k l}n.|d jodd kl}n td dd kl}|d||fd| }||}|iddddgdddtdgdg}tii|\}}|i| dddtdd|i|d| |S(s make a thumbnail of image in *infile* with output filename *thumbfile*. *infile* the image file -- must be PNG or PIL readable if you have `PIL `_ installed *thumbfile* the thumbnail filename *scale* the scale factor for the thumbnail *interpolation* the interpolation scheme used in the resampling *preview* if True, the default backend (presumably a user interface backend) will be used which will cause a figure to be raised if :func:`~matplotlib.pyplot.show` is called. If it is False, a pure image backend will be used depending on the extension, 'png'->FigureCanvasAgg, 'pdf'->FigureCanvasPDF, 'svg'->FigureCanvasSVG See examples/misc/image_thumbnail.py. .. htmlonly:: :ref:`misc-image_thumbnail` Return value is the figure instance containing the thumbnail idiNR"R#s.png(R s.pdf(tFigureCanvasPDFs.svg(tFigureCanvasSVGs0Can only handle extensions 'png', 'svg' or 'pdf'(R!iitaspecttautoR$txtickstyticksR3R/R(RRtsplitRRR7RRtmatplotlib.pyplottpyplotRR(R tmatplotlib.backends.backend_pdfR<tmatplotlib.backends.backend_svgR=RR)R!tadd_axesRStimshowRR+(tinfilet thumbfiletscaleR/tpreviewtbasedirRtbaseouttextoutR|RRtdepthR#RBRAt extensiontpltR R-R!R.R,R((s6/usr/lib64/python2.6/site-packages/matplotlib/image.pyt thumbnail\s4&  "     3(%Rt __future__RRRtnumpyRNRt matplotlibRtmatplotlib.artisttartistRRtmatplotlib.colorstcolorsR\t matplotlib.cmR tmatplotlib.cbookRtmatplotlib._imageRQtmatplotlib._pngRRR!RRRRRR"R/RRSRS(((s6/usr/lib64/python2.6/site-packages/matplotlib/image.pyts.  iro %% &