Rc @sdZddlmZddlZddlZddljZddlZ ddl j Z ddl j ZddljZddlmZddljZddljZddlmZddljZddljZddlmZddljZdejej fdYZ!ej"j#dd d e!fd YZ$d e!fd YZ%de%fdYZ&de!fdYZ'de'fdYZ(de'fdYZ)de!fdYZ*de*fdYZ+de!fdYZ,de!fdYZ-de!fdYZ.d e!fd!YZ/d"e!fd#YZ0ej1e!Z2xCd"d d ddd ddddf D]Z3ej"j#ie2e36quWej"j#dej1e*dS($sx Classes for the efficient drawing of large collections of objects that share most properties, e.g., a large number of line segments or polygons. The classes are not meant to be as flexible as their single element counterparts (e.g., you may not be able to select all line styles) but they are meant to be fast for common use cases (e.g., a large set of solid line segemnts) i(tprint_functionN(t docstring(tallow_rasterization(t_patht CollectioncBseZdZejgejZd1e_ej Z gZ d2d2d2dd2d2d2d2d2dd2d2dddZ edZed Zd Zd Zd Zd ZdZdZdZedZdZdZdZdZdZdZdZ dZ!dZ"dZ#dZ$dZ%dZ&dZ'd Z(d!Z)d"Z*d#Z+d$Z,d%Z-d&Z.d'Z/d(Z0e0Z1d)Z2e2Z3d*Z4d+Z5d,Z6d-Z7e7Z8d.Z9e9Z:Z;d/Z<d0Z=RS(3sj Base class for Collections. Must be subclassed to be usable. All properties in a collection must be sequences or scalars; if scalars, they will be converted to sequences. The property of the ith element of the collection is:: prop[i % len(props)] Keyword arguments and default values: * *edgecolors*: None * *facecolors*: None * *linewidths*: None * *antialiaseds*: None * *offsets*: None * *transOffset*: transforms.IdentityTransform() * *offset_position*: 'screen' (default) or 'data' * *norm*: None (optional for :class:`matplotlib.cm.ScalarMappable`) * *cmap*: None (optional for :class:`matplotlib.cm.ScalarMappable`) * *hatch*: None * *zorder*: 1 *offsets* and *transOffset* are used to translate the patch after rendering (default no offsets). If offset_position is 'screen' (default) the offset is applied after the master transform has been applied, that is, the offsets are in screen coordinates. If offset_position is 'data', the offset is applied before the master transform, i.e., the offsets are in data coordinates. If any of *edgecolors*, *facecolors*, *linewidths*, *antialiaseds* are None, they default to their :data:`matplotlib.rcParams` patch setting, in sequence form. The use of :class:`~matplotlib.cm.ScalarMappable` is optional. If the :class:`~matplotlib.cm.ScalarMappable` matrix _A is not None (ie a call to set_array has been made), at draw time a call to scalar mappable will be made to set the face colors. iitsolidg@tscreenicKsFtjj|tjj||| |j||j||j||j||j ||j | |j | |j | |j | |j|d|_tjddggtj|_|dk r#tj|}d|_|dk r||_||_q#||_nd|_|j|d|_dS(s= Create a Collection %(Collection)s iiiN(ii(tartisttArtistt__init__tcmtScalarMappablet set_edgecolort set_facecolort set_linewidtht set_linestyletset_antialiasedtset_pickradiustset_urlst set_hatchtset_offset_positiont set_zordertNonet_uniform_offsetstnptarraytfloat_t_offsetst asanyarraytshapet _transOffsett _path_effectstupdatet_paths(tselft edgecolorst facecolorst linewidthst linestylest antialiasedstoffsetst transOffsettnormtcmapt pickradiusthatchturlstoffset_positiontzordertkwargs((sP/opt/xtal/ccp4-6.5-linux32/lib/python2.7/site-packages/matplotlib/collections.pyR Ps0           !        cCsyt|fSWn_tk rrtj|rst|rsyt|dWnttfk rgqoX|SqsnXtddS(Nis1val must be a float or nonzero sequence of floats(tfloatt TypeErrortcbooktiterabletlent ValueError(tval((sP/opt/xtal/ccp4-6.5-linux32/lib/python2.7/site-packages/matplotlib/collections.pyt _get_values  cCsWtj|s|f}nyt|dWn#ttfk rRtdnX|S(Nis.val must be a bool or nonzero sequence of them(R4R5tboolR3t IndexError(R8((sP/opt/xtal/ccp4-6.5-linux32/lib/python2.7/site-packages/matplotlib/collections.pyt _get_bools cCs|jS(N(R!(R"((sP/opt/xtal/ccp4-6.5-linux32/lib/python2.7/site-packages/matplotlib/collections.pyt get_pathsscCs tdS(N(tNotImplementedError(R"((sP/opt/xtal/ccp4-6.5-linux32/lib/python2.7/site-packages/matplotlib/collections.pyt set_pathsscCs|jS(N(t _transforms(R"((sP/opt/xtal/ccp4-6.5-linux32/lib/python2.7/site-packages/matplotlib/collections.pytget_transformsscCsD|j}t|tj r@t|dr@|j|j}n|S(Nt_as_mpl_transform(Rt isinstancet transformst TransformthasattrRBtaxes(R"tt((sP/opt/xtal/ccp4-6.5-linux32/lib/python2.7/site-packages/matplotlib/collections.pytget_offset_transforms  cCs=|j}|j}|j}|j}|jsgg|D]}|j|^q=}|j}n|js|j|}|j}ntj |tj }tj j |r|j tj}nd|_|rtj|j||j||j}|j|}n!tjddgddgg}|S(Niii(ii(t get_transformRIRR=t is_affinettransform_path_non_affinet get_affinettransform_non_affineRRRtmat isMaskedArraytfilledtnanRtmpathtget_path_collection_extentstfrozenRAtinverse_transformedRDtBbox(R"t transDatat transformR)R(tpathstptresult((sP/opt/xtal/ccp4-6.5-linux32/lib/python2.7/site-packages/matplotlib/collections.pyt get_datalims*     "  !cCs|jtjS(N(R]RDtIdentityTransform(R"trenderer((sP/opt/xtal/ccp4-6.5-linux32/lib/python2.7/site-packages/matplotlib/collections.pytget_window_extentsc Cs|j}|j}|j}|j}|jr1g}x|jD]}|j}|dddf|dddf}}|j|}|j|}|jt j t |||j qLW|j dkr1|j|dddf}|j|dddf}t ||}q1ntj|tj}d|_|jsg|D]}|j|^q_}|j}n|js|j|}|j}ntjj|r|jtj}n||||fS(s&Point prep for drawing and hit testingNiiii(ii(RJRIRR=t have_unitstverticestconvert_xunitstconvert_yunitstappendRStPathtziptcodestsizeRRRRRKRLRMRNRORPRQRR( R"RYR)R(RZtpathRbtxstys((sP/opt/xtal/ccp4-6.5-linux32/lib/python2.7/site-packages/matplotlib/collections.pyt_prepare_pointss8      -)   cCs|jsdS|j|jj|j|j|j\}}}}|j}|j||j |j |j r|j |j n|j dk r|j|j n|jr?x|jD]a}|j|||j||j|||j|j|j|j|j|j|jqWnX|j||j||j|||j|j|j|j|j|j|j |j|j|jjdS(N(t get_visiblet open_groupt __class__t__name__tget_gidtupdate_scalarmappableRmtnew_gct _set_gc_cliptset_snaptget_snapt_hatchRtget_sketch_paramsRtset_sketch_paramstget_path_effectstdraw_path_collectionRURAt get_facecolort get_edgecolort _linewidthst _linestylest _antialiasedst_urlst_offset_positiontrestoret close_group(R"R_RYR)R(RZtgctpe((sP/opt/xtal/ccp4-6.5-linux32/lib/python2.7/site-packages/matplotlib/collections.pytdraws4         cCs ||_dS(N(t _pickradius(R"tpr((sP/opt/xtal/ccp4-6.5-linux32/lib/python2.7/site-packages/matplotlib/collections.pyRscCs|jS(N(R(R"((sP/opt/xtal/ccp4-6.5-linux32/lib/python2.7/site-packages/matplotlib/collections.pytget_pickradiussc Cst|jr|j||S|js5tifS|jtkrP|j}nDyt|j}Wn.tk rt j d|j|j}nX|j \}}}}t j |j|j||j||j|||dk|j }t|dktd|fS(s Test whether the mouse event occurred in the collection. Returns True | False, ``dict(ind=itemlist)``, where every item in itemlist contains the event. s4Collection picker %s could not be converted to floatitind(tcallablet _containsRntFalset_pickertTrueRR2R3twarningstwarnRmRtpoint_in_path_collectiontxtyRURAtget_offset_positionR6tdict(R"t mouseeventR,RYR)R(RZR((sP/opt/xtal/ccp4-6.5-linux32/lib/python2.7/site-packages/matplotlib/collections.pytcontains!s(      cCs(|dkrdg|_n ||_dS(N(RR(R"R.((sP/opt/xtal/ccp4-6.5-linux32/lib/python2.7/site-packages/matplotlib/collections.pyRFs cCs|jS(N(R(R"((sP/opt/xtal/ccp4-6.5-linux32/lib/python2.7/site-packages/matplotlib/collections.pytget_urlsLscCs ||_dS(sk Set the hatching pattern *hatch* can be one of:: / - diagonal hatching \ - back diagonal | - vertical - - horizontal + - crossed x - crossed diagonal o - small circle O - large circle . - dots * - stars Letters can be combined, in which case all the specified hatchings are done. If same letter repeats, it increases the density of hatching of that pattern. Hatching is supported in the PostScript, PDF, SVG and Agg backends only. Unlike other properties such as linewidth and colors, hatching can only be specified for the collection as a whole, not separately for each member. ACCEPTS: [ '/' | '\\' | '|' | '-' | '+' | 'x' | 'o' | 'O' | '.' | '*' ] N(Rx(R"R-((sP/opt/xtal/ccp4-6.5-linux32/lib/python2.7/site-packages/matplotlib/collections.pyROscCs|jS(s#Return the current hatching pattern(Rx(R"((sP/opt/xtal/ccp4-6.5-linux32/lib/python2.7/site-packages/matplotlib/collections.pyt get_hatchoscCsFtj|tj}d|_|jdkr9||_n ||_dS(s Set the offsets for the collection. *offsets* can be a scalar or a sequence. ACCEPTS: float or sequence of floats iiN(ii(RRRRRRR(R"R(((sP/opt/xtal/ccp4-6.5-linux32/lib/python2.7/site-packages/matplotlib/collections.pyt set_offsetsss   cCs!|jdkr|jS|jSdS(s8 Return the offsets for the collection. N(RRR(R"((sP/opt/xtal/ccp4-6.5-linux32/lib/python2.7/site-packages/matplotlib/collections.pyt get_offsetsscCs(|dkrtdn||_dS(si Set how offsets are applied. If *offset_position* is 'screen' (default) the offset is applied after the master transform has been applied, that is, the offsets are in screen coordinates. If offset_position is 'data', the offset is applied before the master transform, i.e., the offsets are in data coordinates. Rtdatas*offset_position must be 'screen' or 'data'N(Rsdata(R7R(R"R/((sP/opt/xtal/ccp4-6.5-linux32/lib/python2.7/site-packages/matplotlib/collections.pyRs cCs|jS(s Returns how offsets are applied for the collection. If *offset_position* is 'screen', the offset is applied after the master transform has been applied, that is, the offsets are in screen coordinates. If offset_position is 'data', the offset is applied before the master transform, i.e., the offsets are in data coordinates. (R(R"((sP/opt/xtal/ccp4-6.5-linux32/lib/python2.7/site-packages/matplotlib/collections.pyRs cCs2|dkrtjd}n|j||_dS(s Set the linewidth(s) for the collection. *lw* can be a scalar or a sequence; if it is a sequence the patches will cycle through the sequence ACCEPTS: float or sequence of floats spatch.linewidthN(RtmpltrcParamsR9R(R"tlw((sP/opt/xtal/ccp4-6.5-linux32/lib/python2.7/site-packages/matplotlib/collections.pyRs cCs |j|S(salias for set_linewidth(R(R"R((sP/opt/xtal/ccp4-6.5-linux32/lib/python2.7/site-packages/matplotlib/collections.pytset_linewidthsscCs |j|S(salias for set_linewidth(R(R"R((sP/opt/xtal/ccp4-6.5-linux32/lib/python2.7/site-packages/matplotlib/collections.pytset_lwscCsyztjj}tj|rl||kr:||g}qy|tjkr`|tj|g}qytn tj|rpyg}x|D]}tj|r||kr|j||q0|tjkr|j|tj|q0tqtj|r't |dkr'|j|qtqWWqytk rlt |dkr`|}qmtqyXn tWn!tk rtd|nX||_ dS(s Set the linestyle(s) for the collection. ACCEPTS: ['solid' | 'dashed', 'dashdot', 'dotted' | (offset, on-off-dash-seq) ] is'Do not know how to convert %s to dashesN( t backend_basestGraphicsContextBasetdashdR4tis_string_liket ls_mapperR7R5ReR6R(R"tlsRtdashesR((sP/opt/xtal/ccp4-6.5-linux32/lib/python2.7/site-packages/matplotlib/collections.pyRs:      !    cCs |j|S(salias for set_linestyle(R(R"R((sP/opt/xtal/ccp4-6.5-linux32/lib/python2.7/site-packages/matplotlib/collections.pytset_linestylesscCs |j|S(salias for set_linestyle(R(R"R((sP/opt/xtal/ccp4-6.5-linux32/lib/python2.7/site-packages/matplotlib/collections.pyt set_dashesscCs2|dkrtjd}n|j||_dS(sm Set the antialiasing state for rendering. ACCEPTS: Boolean or sequence of booleans spatch.antialiasedN(RRRR<R(R"taa((sP/opt/xtal/ccp4-6.5-linux32/lib/python2.7/site-packages/matplotlib/collections.pyRs cCs |j|S(salias for set_antialiased(R(R"R((sP/opt/xtal/ccp4-6.5-linux32/lib/python2.7/site-packages/matplotlib/collections.pytset_antialiasedsscCs|j||j|dS(s  Set both the edgecolor and the facecolor. ACCEPTS: matplotlib color arg or sequence of rgba tuples .. seealso:: :meth:`set_facecolor`, :meth:`set_edgecolor` For setting the edge or face color individually. N(R R (R"tc((sP/opt/xtal/ccp4-6.5-linux32/lib/python2.7/site-packages/matplotlib/collections.pyt set_colors cCst|_y"|jdkr*t|_nWntk r>nX|dkr[tjd}n||_t j j ||j |_ dS(sm Set the facecolor(s) of the collection. *c* can be a matplotlib color arg (all patches have same color), or a sequence of rgba tuples; if it is a sequence the patches will cycle through the sequence. If *c* is 'none', the patch will not be filled. ACCEPTS: matplotlib color arg or sequence of rgba tuples tnonespatch.facecolorN(Rt _is_filledtlowerRtAttributeErrorRRRt_facecolors_originaltmcolorstcolorConvertert to_rgba_arrayt_alphat _facecolors(R"R((sP/opt/xtal/ccp4-6.5-linux32/lib/python2.7/site-packages/matplotlib/collections.pyR s    cCs |j|S(salias for set_facecolor(R (R"R((sP/opt/xtal/ccp4-6.5-linux32/lib/python2.7/site-packages/matplotlib/collections.pytset_facecolorsscCs|jS(N(R(R"((sP/opt/xtal/ccp4-6.5-linux32/lib/python2.7/site-packages/matplotlib/collections.pyR}scCs$|jdkr|jS|jSdS(Ntface(t _edgecolorstget_facecolors(R"((sP/opt/xtal/ccp4-6.5-linux32/lib/python2.7/site-packages/matplotlib/collections.pyR~#s cCst|_y"|jdkr*t|_nWntk r>nXy,|jdkrjd|_d|_dSWntk r~nX|dkrtj d}n||_t j j ||j |_dS(s Set the edgecolor(s) of the collection. *c* can be a matplotlib color arg (all patches have same color), or a sequence of rgba tuples; if it is a sequence the patches will cycle through the sequence. If *c* is 'face', the edge color will always be the same as the face color. If it is 'none', the patch boundary will not be drawn. ACCEPTS: matplotlib color arg or sequence of rgba tuples RRNspatch.edgecolor(Rt _is_strokedRRRRt_edgecolors_originalRRRRRRR(R"R((sP/opt/xtal/ccp4-6.5-linux32/lib/python2.7/site-packages/matplotlib/collections.pyR *s"       cCs |j|S(salias for set_edgecolor(R (R"R((sP/opt/xtal/ccp4-6.5-linux32/lib/python2.7/site-packages/matplotlib/collections.pytset_edgecolorsIscCs|dk r=yt|Wq=tk r9tdq=Xntjj||y"tjj|j |j |_ Wnt tt fk rnXy4|jdkrtjj|j|j |_nWnt tt fk rnXdS(s Set the alpha tranparencies of the collection. *alpha* must be a float or *None*. ACCEPTS: float or None salpha must be a float or NoneRN(RR2R3RRt set_alphaRRRRRRRR;RR(R"talpha((sP/opt/xtal/ccp4-6.5-linux32/lib/python2.7/site-packages/matplotlib/collections.pyRMs"    cCs|jS(N(R(R"((sP/opt/xtal/ccp4-6.5-linux32/lib/python2.7/site-packages/matplotlib/collections.pytget_linewidthsfscCs|jS(N(R(R"((sP/opt/xtal/ccp4-6.5-linux32/lib/python2.7/site-packages/matplotlib/collections.pytget_linestylesjscCs|jdkrdS|jjdkr4tdn|jdsGdS|jrn|j|j|j|_n'|j r|j|j|j|_ ndS(sb If the scalar mappable array is not none, update colors from scalar data Nis&Collections can only map rank 1 arraysR( t_ARtndimR7t check_updateRtto_rgbaRRRR(R"((sP/opt/xtal/ccp4-6.5-linux32/lib/python2.7/site-packages/matplotlib/collections.pyRsns  cCstjj|||j|_|j|_|j|_|j|_|j|_|j|_|j |_ |j |_ |j |_ |j |_ |j |_ |j|_dS(s"copy properties from other to selfN(RRt update_fromRRRRRRRRRxRR*R+(R"tother((sP/opt/xtal/ccp4-6.5-linux32/lib/python2.7/site-packages/matplotlib/collections.pyR~s           (iiN(>Rqt __module__t__doc__RRRRRRDR^RR@RR t staticmethodR9R<R=R?RARIR]R`RmRRRRRRRRRRRRRRRRRRRRRRR RR}RR~tget_edgecolorsR RRRt get_linewidthRt get_dashest get_linestyleRsR(((sP/opt/xtal/ccp4-6.5-linux32/lib/python2.7/site-packages/matplotlib/collections.pyRs*   %       )%   %       *               s Valid Collection keyword arguments: * *edgecolors*: None * *facecolors*: None * *linewidths*: None * *antialiaseds*: None * *offsets*: None * *transOffset*: transforms.IdentityTransform() * *norm*: None (optional for :class:`matplotlib.cm.ScalarMappable`) * *cmap*: None (optional for :class:`matplotlib.cm.ScalarMappable`) *offsets* and *transOffset* are used to translate the patch after rendering (default no offsets) If any of *edgecolors*, *facecolors*, *linewidths*, *antialiaseds* are None, they default to their :data:`matplotlib.rcParams` patch setting, in sequence form. tPathCollectioncBsMeZdZejddZdZdZdZ e dZ RS(s> This is the most basic :class:`Collection` subclass. cKs*tj|||j|||_dS(ss *paths* is a sequence of :class:`matplotlib.path.Path` instances. %(Collection)s N(RR R?t_sizes(R"RZtsizesR1((sP/opt/xtal/ccp4-6.5-linux32/lib/python2.7/site-packages/matplotlib/collections.pyR s  cCs ||_dS(N(R!(R"RZ((sP/opt/xtal/ccp4-6.5-linux32/lib/python2.7/site-packages/matplotlib/collections.pyR?scCs|jS(N(R!(R"((sP/opt/xtal/ccp4-6.5-linux32/lib/python2.7/site-packages/matplotlib/collections.pyR=scCs|jS(N(R(R"((sP/opt/xtal/ccp4-6.5-linux32/lib/python2.7/site-packages/matplotlib/collections.pyt get_sizesscCsg|jdk rWg|jD]2}tjjtj||jjd^q|_ nt j ||S(NgR@( RRRDtAffine2DtscaleRtsqrttfiguretdpiR@RR(R"R_R((sP/opt/xtal/ccp4-6.5-linux32/lib/python2.7/site-packages/matplotlib/collections.pyRsEN( RqRRRtdedent_interpdRR R?R=RRR(((sP/opt/xtal/ccp4-6.5-linux32/lib/python2.7/site-packages/matplotlib/collections.pyRs   tPolyCollectioncBsAeZejdedZedZeZe dZ RS(cKs-tj||||_|j||dS(s *verts* is a sequence of ( *verts0*, *verts1*, ...) where *verts_i* is a sequence of *xy* tuples of vertices, or an equivalent :mod:`numpy` array of shape (*nv*, 2). *sizes* is *None* (default) or a sequence of floats that scale the corresponding *verts_i*. The scaling is applied before the Artist master transform; if the latter is an identity transform, then the overall scaling is such that if *verts_i* specify a unit square, then *sizes_i* is the area of that square in points^2. If len(*sizes*) < *nv*, the additional values will be taken cyclically from the array. *closed*, when *True*, will explicitly close the polygon. %(Collection)s N(RR Rt set_verts(R"tvertsRtclosedR1((sP/opt/xtal/ccp4-6.5-linux32/lib/python2.7/site-packages/matplotlib/collections.pyR s cCsutjj|r3|jtjjtj}n|rLg|_x,|D]}t|r,tjj|rtjj |tj dg}n-tj |}tj |tj dg}tj |j ddtjj}tjj|(tjj|dx;t|D]-}||}|||||d!||t|dkr>|jgdS|j}|j}||d||df}tj|}|j|j rg|D]%}g|D]}||f^q^q}n2g|D]%}g|D]}||f^q^q}|j|dS(sH set the positions of the events to the specified value R6iNg@( RRFR6Rtget_lineoffsettget_linelengthRRR$R2(R"R(R*R+R/R0R1R((sP/opt/xtal/ccp4-6.5-linux32/lib/python2.7/site-packages/matplotlib/collections.pyt set_positionss       2/cCsl|dks-t|dr1t|dkr1dS|j}tj|tj|g}|j|dS(sC add one or more events at the specified positions R6iN(RRFR6R4RthstackRR7(R"tpositionR(((sP/opt/xtal/ccp4-6.5-linux32/lib/python2.7/site-packages/matplotlib/collections.pyt add_positionss  cCs|jS(sN True if the eventcollection is horizontal, False if vertical (R%(R"((sP/opt/xtal/ccp4-6.5-linux32/lib/python2.7/site-packages/matplotlib/collections.pyR2scCs|jrdSdS(sf get the orientation of the event line, may be: [ 'horizontal' | 'vertical' ] R"R#(R2(R"((sP/opt/xtal/ccp4-6.5-linux32/lib/python2.7/site-packages/matplotlib/collections.pytget_orientationscCs]|j}x-t|D]\}}tj|||(R"R)R2((sP/opt/xtal/ccp4-6.5-linux32/lib/python2.7/site-packages/matplotlib/collections.pytset_orientations   cCs|jS(sE get the length of the lines used to mark each event (R&(R"((sP/opt/xtal/ccp4-6.5-linux32/lib/python2.7/site-packages/matplotlib/collections.pyR6scCs||jkrdS|j}|j}|jr@dnd}x>|D]6}||d|d|f<||d|d|f|D]6}||d|d|f<||d|d|fR?R6R@R5RARRR(((sP/opt/xtal/ccp4-6.5-linux32/lib/python2.7/site-packages/matplotlib/collections.pyR!>s. U           tCircleCollectioncBs8eZdZejdZdZedZRS(s7 A collection of circles, drawn using splines. cKsEtj||||_|jtjtjjg|_ dS(sf *sizes* Gives the area of the circle in points^2 %(Collection)s N( RR RRRDR^RSRft unit_circleR!(R"RR1((sP/opt/xtal/ccp4-6.5-linux32/lib/python2.7/site-packages/matplotlib/collections.pyR >s cCs|jS(sreturn sizes of circles(R(R"((sP/opt/xtal/ccp4-6.5-linux32/lib/python2.7/site-packages/matplotlib/collections.pyRKscCseg|jD]B}tjjtj||jjdtjtj^q |_ t j ||S(NgR@( RRDRRRRRRRR@RR(R"R_R((sP/opt/xtal/ccp4-6.5-linux32/lib/python2.7/site-packages/matplotlib/collections.pyROsR( RqRRRRR RRR(((sP/opt/xtal/ccp4-6.5-linux32/lib/python2.7/site-packages/matplotlib/collections.pyRD:s tEllipseCollectioncBs;eZdZejddZdZedZRS(s8 A collection of ellipses, drawn using splines. tpointscKstj||dtj|j|_dtj|j|_tj|jtjd|_||_ |j t j g|_ tjjg|_dS(s *widths*: sequence lengths of first axes (e.g., major axis lengths) *heights*: sequence lengths of second axes *angles*: sequence angles of first axes, degrees CCW from the X-axis *units*: ['points' | 'inches' | 'dots' | 'width' | 'height' | 'x' | 'y' | 'xy'] units in which majors and minors are given; 'width' and 'height' refer to the dimensions of the axes, while 'x' and 'y' refer to the *offsets* data units. 'xy' differs from all others in that the angle as plotted varies with the aspect ratio, and equals the specified angle only when the aspect ratio is unity. Hence it behaves the same as the :class:`~matplotlib.patches.Ellipse` with axes.transData as its transform. Additional kwargs inherited from the base :class:`Collection`: %(Collection)s g?gf@N(RR RRtravelt_widthst_heightsRt_anglest_unitsRRDR^R@RSRfRER!(R"twidthstheightstanglestunitsR1((sP/opt/xtal/ccp4-6.5-linux32/lib/python2.7/site-packages/matplotlib/collections.pyR ^s#  c Csg|_|j}|j}|jdkr3d}n|jdkr[|jj|jj}n|jdkr|jj|jj}n|jdkr|j}n|jdkr|jd}ng|jdkr|jj}nI|jd kr|jj}n+|jd krd }nt d |jt j }xbt |j |j|jD]E\}}}|j||||j|}|jj|qIW|jdkr|jjjj} d | ddddf<|j|| ndS(sB Calculate transforms immediately before drawing. RiRRtinchesRGgR@twidththeighttdotsg?sunrecognized units: %siNi(R@RGRRLtbboxRRtviewLimRSRR7RDRRgRIRJRKRRReRXRMt get_matrixtcopyR( R"taxtfigtsct_affineRRtattranstm((sP/opt/xtal/ccp4-6.5-linux32/lib/python2.7/site-packages/matplotlib/collections.pyt_set_transformss8       +&cCs|jtj||dS(N(R`RR(R"R_((sP/opt/xtal/ccp4-6.5-linux32/lib/python2.7/site-packages/matplotlib/collections.pyRs ( RqRRRRR R`RR(((sP/opt/xtal/ccp4-6.5-linux32/lib/python2.7/site-packages/matplotlib/collections.pyRFZs $ %tPatchCollectioncBs#eZdZedZdZRS(s A generic collection of patches. This makes it easier to assign a color map to a heterogeneous collection of patches. This also may improve plotting speed, since PatchCollection will draw faster than a large number of patches. c Ks|rd}g|D]}||^q}g|D]}|j^q5}g|D]}|j^qT}g|D]}|j^qs} g|D]}|j^q} tj|d|d|d|d| d| ntj|||j|dS(s} *patches* a sequence of Patch objects. This list may include a heterogeneous assortment of different patch types. *match_original* If True, use the colors and linewidths of the original patches. If False, new colors may be assigned by providing the standard collection arguments, facecolor, edgecolor, linewidths, norm or cmap. If any of *edgecolors*, *facecolors*, *linewidths*, *antialiaseds* are None, they default to their :data:`matplotlib.rcParams` patch setting, in sequence form. The use of :class:`~matplotlib.cm.ScalarMappable` is optional. If the :class:`~matplotlib.cm.ScalarMappable` matrix _A is not None (ie a call to set_array has been made), at draw time a call to scalar mappable will be made to set the face colors. cSs&|jr|jSddddgS(Ni(tget_fillR}(tpatch((sP/opt/xtal/ccp4-6.5-linux32/lib/python2.7/site-packages/matplotlib/collections.pytdetermine_facecolors  R#R$R%R&R'N(R~RRtget_antialiasedRR R?( R"tpatchestmatch_originalR1RdR[R$R#R%R&R'((sP/opt/xtal/ccp4-6.5-linux32/lib/python2.7/site-packages/matplotlib/collections.pyR s   cCs;g|D]!}|jj|j^q}||_dS(N(RJttransform_pathtget_pathR!(R"RfR[RZ((sP/opt/xtal/ccp4-6.5-linux32/lib/python2.7/site-packages/matplotlib/collections.pyR?s+(RqRRRR R?(((sP/opt/xtal/ccp4-6.5-linux32/lib/python2.7/site-packages/matplotlib/collections.pyRas  .tTriMeshcBsGeZdZdZdZdZedZedZ RS(s Class for the efficient drawing of a triangular mesh using Gouraud shading. A triangular mesh is a :class:`~matplotlib.tri.Triangulation` object. cKstj||||_d|_t|_tjj|_ t j |j j dd|jj ddf}|j j|dS(Ntgouraudii(RR t_triangulationt_shadingRRRDRWtunitt_bboxRR8RtreshapeRtupdate_from_data_xy(R"t triangulationR1R((sP/opt/xtal/ccp4-6.5-linux32/lib/python2.7/site-packages/matplotlib/collections.pyR s   cCs#|jdkr|jn|jS(N(R!RR?(R"((sP/opt/xtal/ccp4-6.5-linux32/lib/python2.7/site-packages/matplotlib/collections.pyR=s cCs|j|j|_dS(N(tconvert_mesh_to_pathsRlR!(R"((sP/opt/xtal/ccp4-6.5-linux32/lib/python2.7/site-packages/matplotlib/collections.pyR?scCsutj}|j}tj|j|dtjf|j|dtjffdd}g|D]}||^q_S(s Converts a given mesh into a sequence of :class:`matplotlib.path.Path` objects for easier rendering by backends that do not directly support meshes. This function is primarily of use to backend implementers. .taxisi(RSRftget_masked_trianglesRRRtnewaxisR(ttriRft trianglesRR((sP/opt/xtal/ccp4-6.5-linux32/lib/python2.7/site-packages/matplotlib/collections.pyRs s  &cCs |jsdS|j|jj|j}|j}|j}tj|j |dtj f|j |dtj ffdd}|j |j |}|j}|j||j|jd|j||||j|j|j|jjdS(N.Rtii(RnRoRpRqRJRlRuRRRRvRRsRRtRuRRtdraw_gouraud_trianglesRURR(R"R_RYRwRxRRR((sP/opt/xtal/ccp4-6.5-linux32/lib/python2.7/site-packages/matplotlib/collections.pyRs     &     ( RqRRR R=R?RRsRR(((sP/opt/xtal/ccp4-6.5-linux32/lib/python2.7/site-packages/matplotlib/collections.pyRjs    tQuadMeshcBs_eZdZeddZdZdZedZdZ dZ e dZ RS( s Class for the efficient drawing of a quadrilateral mesh. A quadrilateral mesh consists of a grid of vertices. The dimensions of this array are (*meshWidth* + 1, *meshHeight* + 1). Each vertex in the mesh has a different set of "mesh coordinates" representing its position in the topology of the mesh. For any values (*m*, *n*) such that 0 <= *m* <= *meshWidth* and 0 <= *n* <= *meshHeight*, the vertices at mesh coordinates (*m*, *n*), (*m*, *n* + 1), (*m* + 1, *n* + 1), and (*m* + 1, *n*) form one of the quadrilaterals in the mesh. There are thus (*meshWidth* * *meshHeight*) quadrilaterals in the mesh. The mesh need not be regular and the polygons need not be convex. A quadrilateral mesh is represented by a (2 x ((*meshWidth* + 1) * (*meshHeight* + 1))) numpy array *coordinates*, where each row is the *x* and *y* coordinates of one of the vertices. To define the function that maps from a data point to its corresponding color, use the :meth:`set_cmap` method. Each of these arrays is indexed in row-major order by the mesh coordinates of the vertex (or the mesh coordinates of the lower left vertex, in the case of the colors). For example, the first entry in *coordinates* is the coordinates of the vertex at mesh coordinates (0, 0), then the one at (0, 1), then at (0, 2) .. (0, meshWidth), (1, 0), (1, 1), and so on. *shading* may be 'flat', or 'gouraud' tflatcKstj||||_||_||_||_||_tjj |_ |j j |j |d|ddf|jj |d|ddf|_t j|jt j|_dS(Nii(RR t _meshWidtht _meshHeightt _coordinatest _antialiasedRmRDRWRnRoRqRpRRR(R"t meshWidtht meshHeightt coordinatesR.tshadingR1((sP/opt/xtal/ccp4-6.5-linux32/lib/python2.7/site-packages/matplotlib/collections.pyR Rs      cCs#|jdkr|jn|jS(N(R!RR?(R"((sP/opt/xtal/ccp4-6.5-linux32/lib/python2.7/site-packages/matplotlib/collections.pyR=ds cCs%|j|j|j|j|_dS(N(RsR|R}R~R!(R"((sP/opt/xtal/ccp4-6.5-linux32/lib/python2.7/site-packages/matplotlib/collections.pyR?isc Cstj}tj|r$|j}n|}tj|ddddf|ddddf|ddddf|ddddf|ddddffdd}|j||ddf}g|D]}||^qS(s Converts a given mesh into a sequence of :class:`matplotlib.path.Path` objects for easier rendering by backends that do not directly support quadmeshes. This function is primarily of use to backend implementers. iiiNRtii(RSRfRORPRRRRp(RRRRfRRGR((sP/opt/xtal/ccp4-6.5-linux32/lib/python2.7/site-packages/matplotlib/collections.pyRsms   c Cstj|r|j}n|}|ddddf}|ddddf}|ddddf}|ddddf}||||d} tj||| ||| ||| ||| f dd} | j||dddf} |jj|d|ddf} | ddddf} | ddddf} | ddddf}| ddddf}| | ||d}tj| | || ||||||| |f dd}|j||dddf}| |fS( s Converts a given mesh into a sequence of triangles, each point with its own color. This is useful for experiments using `draw_qouraud_triangle`. Niig@Rtiii(RORPRRRRpR}(R"RRRR[tp_atp_btp_ctp_dtp_centerRxRtc_atc_btc_ctc_dtc_centerR((sP/opt/xtal/ccp4-6.5-linux32/lib/python2.7/site-packages/matplotlib/collections.pytconvert_mesh_to_triangless:      &     cCs|jS(N(Ro(R"RX((sP/opt/xtal/ccp4-6.5-linux32/lib/python2.7/site-packages/matplotlib/collections.pyR]sc Csh|jsdS|j|jj|j|j}|j}|j}|jrt |jr|j |jdddf}|j |jdddf}t ||}qnt j|t j}d|_|j|jsU|jj|jjd|jjddf}|j|}|j|jj}tj}n |j}|js|j|}|j}n|j}|j||j|jd|jdkr|j|j |j!|\} } |j"|| | |j#nC|j$||j#|j |j!||||j%|j&|j' |j(|j)|jjdS(NiiiiRk(ii(*RnRoRpRqRrRJRIRRaR6RcRdRgRRRRRsRKR~RpRYRDR^RNRMRtRuRRRmRR|R}RyRUtdraw_quad_meshR}RRRR( R"R_RYR)R(RkRlRRRxR((sP/opt/xtal/ccp4-6.5-linux32/lib/python2.7/site-packages/matplotlib/collections.pyRsP     ""           ( RqRRRR R=R?RRsRR]RR(((sP/opt/xtal/ccp4-6.5-linux32/lib/python2.7/site-packages/matplotlib/collections.pyRz3s   * (4Rt __future__RRtnumpyRtnumpy.maROt matplotlibRtmatplotlib.cbookR4tmatplotlib.colorsRRt matplotlib.cmR Rtmatplotlib.transformsRDtmatplotlib.artistRRtmatplotlib.backend_basesRtmatplotlib.pathRjRSRtmatplotlib.mlabRRR RtinterpdR RRRRR R R R!RDRFRaRjRztkwdoctpatchstrtk(((sP/opt/xtal/ccp4-6.5-linux32/lib/python2.7/site-packages/matplotlib/collections.pyt sR   { $=/A T?F