ó ¹™xTc@ s_ddlmZddlmZddlmZddlZddlZddd„ƒYZdS(iÿÿÿÿ(tdivision(tflex(tfloorNt NDimTablecB seeZd„ZeeƒZd„Zd„Zd„Zd„Zd„Zd„Z d„Z d„Z RS( c C st|tjƒr$t|dƒ}ntƒ}tjd|jƒƒjdƒ|_ t tjd|jƒƒjdƒƒ|_ |jƒg|_ g|_ g|_g|_g|_tjdƒ}x$t|j ƒD]}|j|jƒƒ}|j jt|jdƒƒƒ|j jt|jdƒƒƒ|jjt |jdƒƒƒ|jdƒjƒjƒ}|d ks”|d ks”|d ks”|d kr§|jjtƒn|jjtƒ|jj|j ||j ||j|ƒqÑWtjtj|jƒd ƒ|_tjd|jƒƒr*t}nt}|jƒ}xØ|r|jƒ}|jƒ}t|ƒ|j krxq?n|r¾t|d ƒ} g|d|j d!D]} t| ƒ^q£} n<t||j ƒ} g|d |j !D]} t| ƒ^qâ} |j|j| ƒ| ƒq?W|S(s…Loads rotamer or Ramachandran data from a text file, returning a new object. Can pass in either a file handle or a file nametrs : +"(.+)"$is : +(\d+)$s&: +([^ ]+) +([^ ]+) +([^ ]+) +([^ ]+)$iiittruetyestont1itfirst( t isinstancettypest StringTypestfileRtretsearchtreadlinetgrouptourNametinttnDimtminValtmaxValtnBinstdoWraptwBintcompiletrangetappendtfloattlowertstriptTruetFalseRtgridt lookupTabletsplittlent setValueAttwhereIs( tinfiletndttdata_retitmatchRt valueFirsttstfieldstvaltfldtcoords((sG/public2/ftp/pub/ccp4/6.5/ccp4-6.5/lib/py2/mmtbx/rotamer/n_dim_table.pytcreateFromTextsN $*      01!     0)cC skg}x^t|jƒD]M}|jttt|||j||j|ƒ|j|dƒƒƒqW|S(s2Given a set of coordinates, return the bin indicesi( RRRRtminRRRR(tselfR2tbinR+((sG/public2/ftp/pub/ccp4/6.5/ccp4-6.5/lib/py2/mmtbx/rotamer/n_dim_table.pyR'HsKcC s||j|j|ƒGiven bin indices, return a single index into the linear arrayiiiÿÿÿÿ(RRtwrapbinR(R5R6tidxR+tiBin((sG/public2/ftp/pub/ccp4/6.5/ccp4-6.5/lib/py2/mmtbx/rotamer/n_dim_table.pyR7Us   cC sÊd}xpt|jdƒD][}|j|||ƒ}|jd||j|dƒ}||7}||j|d9}qW|jd}|j|||ƒ}|jd||j|dƒ}||7}|S(s™Given bin indices, return a single index into the linear array. If no bin can be found after wrapping is applied, the edge of the table is used.ii(RRR8tclampInclusiveR(R5R6R9R+R:((sG/public2/ftp/pub/ccp4/6.5/ccp4-6.5/lib/py2/mmtbx/rotamer/n_dim_table.pytbin2index_limitds     cC st|t||ƒƒS(s>Forces theVal into the range from minVal to maxVal (inclusive)(tmaxR4(R5RttheValR((sG/public2/ftp/pub/ccp4/6.5/ccp4-6.5/lib/py2/mmtbx/rotamer/n_dim_table.pyR;tscC s$|j|r||j|S|SdS(s>Wrap bin indices for each dimension in which it is appropriateN(RR(R5R:tdim((sG/public2/ftp/pub/ccp4/6.5/ccp4-6.5/lib/py2/mmtbx/rotamer/n_dim_table.pyR8ys cC sOg}xBt|jƒD]1}|j|j||j|||dƒqW|S(sDReturns coordinates for the center of the bin given by these indicesgà?(RRRRR(R5R6tptR+((sG/public2/ftp/pub/ccp4/6.5/ccp4-6.5/lib/py2/mmtbx/rotamer/n_dim_table.pytcenterOf…s/c C sxd}|j|ƒ}|j|ƒ}g}g}dg|j}x‚t|jƒD]q}||||kr‚|j||dƒn|j||dƒ|jt|||||j|ƒƒqPWx¬td|j>ƒD]—} d} xjt|jƒD]Y}| d|>@dkr2||||<| d||9} qõ||||<| ||9} qõW|| |j|j|ƒ7}qÙW|S(s|Estimates the value of the density trace at a given position, using linear interpolation. This algorithm basically consults the 2^n bins nearest in space to the input point, and weights their contributions according to their distances. To get a feeling for how it works, work out a linear interpolation in one dimension ( a...x.......b -- what is x in terms of a and b? )(trivial) and then in two dimensions (still fairly easy -- do one dimension first, then interpolate between those results). In dimensions very near the edge of the table, no interpolation is performed in that dimension (it would be impossible to do so, anyway, because there's no 2nd value to interpolate out *to*). pt - the point at which the value should be estimated returns - the approximate value of the density trace at the specified pointiigð?( R'RARRRtabsRR#R<( R5R@tvaluetva_homet va_home_ctrt va_neighbort va_contribt va_currentR?R6tcoeff((sG/public2/ftp/pub/ccp4/6.5/ccp4-6.5/lib/py2/mmtbx/rotamer/n_dim_table.pytvalueAts*."( t__name__t __module__R3t staticmethodR'R&R7R<R;R8RARJ(((sG/public2/ftp/pub/ccp4/6.5/ccp4-6.5/lib/py2/mmtbx/rotamer/n_dim_table.pyRs ,       (( t __future__Rtscitbx.array_familyRtmathRRR R(((sG/public2/ftp/pub/ccp4/6.5/ccp4-6.5/lib/py2/mmtbx/rotamer/n_dim_table.pyts