xTc@ sdZddlmZddlmZmZddlmZddlmZddlmZddlm Z ddlm Z dd lm Z dd lm Z dd lm Z dd lmZdd lmZmZmZddlmZmZddlmZmZddlZddlZddlZddlZdZdZdefdYZ defdYZ!defdYZ"defdYZ#defdYZ$dS(s Classes for MolProbity validation, combining all other analyses in mmtbx.validation, which use the same APIs for storing and displaying results. i(tdivision(t validationtresidue(tmodel_properties(t experimental(t rna_validate(t clashscore(t restraints(tramalyze(trotalyze(tcbetadev(twaters(t make_headertmake_sub_headert format_value(tslots_getstate_setstatet+slots_getstate_setstate_default_initializer(tnull_outtSorryNs clashscore = True .type = bool ramalyze = True .type = bool rotalyze = True .type = bool cbetadev = True .type = bool nqh = True .type = bool rna = True .type = bool model_stats = True .type = bool restraints = True .type = bool rfactors = True .type = bool real_space = True .type = bool waters = True .type = bool seq = True .type = bool xtriage = False .type = bool cC stjjtjS(s7 Default flags for analyses to perform (all True). (tlibtbxtphiltparsetmaster_phil_strtextract(((sR/public2/ftp/pub/ccp4/6.5/ccp4-6.5/lib/py2/mmtbx/validation/molprobity/__init__.pytmolprobity_flags:st molprobitycB seZdZd:Zddddddd d d d d dddddddddgZdZd;d;d;d;d;d;d;d;d;d;d;eed;eddeeed;d;ddZ dZ e j eeedZ dZdZed Zed!Zd"Zed#Zd$Zd%Zd&Zd'Zd(Zd)Zd*Zd+Zd,Zd-Zd.Zd/Zd0Z d1Z!d2Z"ed3Z#d4Z$d5Z%d6Z&d7Z'd8Z(d9Z)RS(<sc Comprehensive validation. At a minimum this performs the standard MolProbity analyses (ramalyze, rotalyze, cbetadev, clashscore). If a geometry restraints manager is available, the deviations from standard covalent geometry will also be displayed. Passing an fmodel object enables the re-calculation of R-factors and real-space correlation. :param pdb_hierarchy: model PDB hierarchy (required) :param xray_structure: model X-ray scatterers :param fmodel: mmtbx.f_model.manager object, after bulk solvent/scaling :param fmodel_neutron: separate Fmodel manager for neutron data (used in phenix.refine for join X/N refinement) :param geometry_restraints_manager: geometry restraints extracted by mmtbx.monomer_library.pdb_interpretation :param sequences: parsed sequence objects (from iotbx.bioinformatics) :param crystal_symmetry: cctbx.crystal.symmetry object :param flags: object containing boolean flags for analyses to perform :param header_info: extracted statistics from PDB file header :param raw_data: input data before French-Wilson treatment, etc. :param unmerged_data: separate unmerged intensities for merging statistics :param all_chain_proxies: object containing restraints information and advanced selections from mmtbx.monomer_library.pdb_interpretation :param keep_hydrogens: don't discard and replace existing hydrogens for clashscore calculation :param nuclear: use nuclear hydrogen distances (for neutron experiments) :param save_probe_unformatted_file: file name for Probe output suitable for display in Coot :param show_hydrogen_outliers: show geometry outliers for hydrogen atoms :param min_cc_two_fofc: Fo-Fc map cutoff for real-space outliers :param n_bins_data: Number of resolution bins for data statistics :param count_anomalous_pairs_separately: count F+ and F- as separate reflections (default=False) :param outliers_only: only display validation outliers :param use_pdb_header_resolution_cutoffs: use resolution cutoff(s) specified in PDB header for data statistics iiRR R tclashest nqh_flipstrnaRt missing_atomst data_statst neutron_statst real_spacetcrystal_symmetryt model_statsR t header_infotmergingtsequencetxtriaget_multi_criteriont file_namecC sgx*|jD]\}}t|||q Wx3|jD](}t||s7t||dq7q7WdS(N(titemstsetattrt __slots__thasattrtNone(tselftstatetnametvalue((sR/public2/ftp/pub/ccp4/6.5/ccp4-6.5/lib/py2/mmtbx/validation/molprobity/__init__.pyt __setstate__s g?i t500cC s\x!|jD]}t||dq W|jj|dkr||dk rX|j}q||dk r||jd|}q|n||_|dkr|dk r|jj|_n| |_ |dkrt }n|j r|j rt j d|d|dt dt|_ n|jrTtjd|d|d|dt dt|_n|jrtjd|d|dt dt|_n|jrtjd||_qn|jr|jrtjjddr|dk rtjd|d |d|d d|_qn|jrStjd|d |d |d | dt dt|_n|jr|dk rtjd|d|d| d| d||_n|dk r|j r|dk st!t j"d|d|d |d| dt#| dd|_ n|dk rE|j$rEt%j&d|d|dt dtdt|_%n|dk r|r| dk r|j'd| j(d| j)}n|j*rt+j,|d| d|d||_-n|j.rt.j.d|d|d|dt|_.n|j/rt+j/d|d|d ||_/n| dk rht+j0d!|jd"|j1d#|j2d$| d%|d||_3n|j4rd&dl5}t6|j1j7}| dk r|j8d'| \}}n |j}|j9j4j:d(|d)|d*| d+t |_4qn|dk r4|j*r4t+j,|d|dt|_;n|j<d,krXt=||_>ndS(-NR!t pdb_hierarchyt outliers_onlytouttquiett data_versionR0t suitenametgeometry_restraints_managertparamstsave_probe_unformatted_filetnucleartkeep_hydrogenstverbosetxray_structuretall_chain_proxiest ignore_hdtligand_selectiontcdltuse_cdlt sequencestlogtinclude_secondary_structuretextract_coordinatestd_mintd_maxtraw_datatn_binst count_anomalous_pairs_separatelytfmodelt collect_alltcc_mintf_obstf_modelt r_free_flagstunmerged_i_obst anomalousitothert miller_obst miller_calct unmerged_obsttext_outi(?R+R*R-tatomst reset_i_seqR@textract_xray_structureR!RRR#Rtcontains_proteinRRtTrueR R tnqhRRt contains_rnaRRtenvt has_moduleRtrna_validationtFalseRR"Rtmodel_statisticsRtAssertionErrortcombinedtgetattrtseqR%Rtresolution_filterRJRKtrfactorsRtdata_statisticsRR R tmerging_and_model_statisticsRSRTR$R&tmmtbx.scaling.xtriagetabst#set_observation_type_xray_amplitudet common_setstscalingtxtriage_analysesRt models_sizetmulti_criterion_viewR'(R.R4R@ROtfmodel_neutronR:R!RFtflagsR#RLt unmerged_dataRAR>R=R<tshow_hydrogen_outlierstmin_cc_two_fofct n_bins_dataRNR5t!use_pdb_header_resolution_cutoffsR(RCtrotamer_libraryR0tmmtbxRStobs((sR/public2/ftp/pub/ccp4/6.5/ccp4-6.5/lib/py2/mmtbx/validation/molprobity/__init__.pyt__init__s                                                 cC scd|j|j|jgkr"dSddlm}|jd|jjd|jjd|jj S(s Compute overall measure of (protein!) structure quality based on an empirical formula combining clashscore, rotamer outliers, and Ramachandran favored statistics. The result is on approximately the same scale as resolution. i(tutilsRtrota_outtrama_favN( R-RR Rtmmtbx.validationRtmolprobity_scoretget_clashscoret out_percentt fav_percent(R.R((sR/public2/ftp/pub/ccp4/6.5/ccp4-6.5/lib/py2/mmtbx/validation/molprobity/__init__.pyRs  cC s|jdk r+|jjjd|n|jdk rtdd||jjd|dd|jdk rtdd||jjd|ddn|jdk rtdd||jjd|ddqn|j dk rtdd||j jddd|n|j dk rRtdd||j jd|ddntd d||j dk rtd d||j jd|ddd |n|j dk rtd d||j jd|ddd |n|j dk r%td d||j jd|ddd |n|jdk r`tdd||jjd|ddn|jdk rtdd||jjd|ddn|jdk rtdd||jjd|ddd |n|stdd||jd|ddd|n|S(sK Comprehensive output with individual outlier lists, plus summary. R6sExperimental datatprefixs s Residues with poor real-space CCsSuspicious water moleculessModel propertiessGeometry restraintssMolprobity validationsRamachandran anglesR5sSidechain rotamerssC-beta deviationss Bad clashessAsn/Gln/His flipssRNA validationtSummarytshow_percentilesN(R&R-tsummarize_issuestshowRR R R R R"RRR R RRRt show_summary(R.R6R5tsuppress_summaryR((sR/public2/ftp/pub/ccp4/6.5/ccp4-6.5/lib/py2/mmtbx/validation/molprobity/__init__.pyR,sR"""" cC sd}}}}}}|jdk r;|jj}n|jdk rb|jj\}}n|jdk r|jj|jj}}|jj}na|j dk r|j j|j j}}|j j}|jdkr|j j }|j j }qn|j }t dt|jdddt|jdddt|jdddt|jddd|d |d |d |d |d |d|dt|j dd S(s Condense results into a compact object - for compatibility with (now obsolete) mmtbx.validation_summary, and use in high-throughput analyses t rama_outliersRt rama_favoredRtrotamer_outlierstc_beta_deviationst n_outliersRt bond_rmsdt angle_rmsdtmpscoreRJtr_worktr_freetprogramtrefinement_programN(R-RRRtget_bonds_angles_rmsdsRRRRJR#t rms_bondst rms_anglesRtsummaryRjRR R (R.RRRRRRJR((sR/public2/ftp/pub/ccp4/6.5/ccp4-6.5/lib/py2/mmtbx/validation/molprobity/__init__.pyt summarize[s8   cO s|jj||S(s@ Print summary of outliers or scores for each analysis. (RR(R.targstkwds((sR/public2/ftp/pub/ccp4/6.5/ccp4-6.5/lib/py2/mmtbx/validation/molprobity/__init__.pyR~scC s?|rt|jddSt|jdt|jddSdS(Nt r_work_outerR(RjRR-R#(R.t outer_shell((sR/public2/ftp/pub/ccp4/6.5/ccp4-6.5/lib/py2/mmtbx/validation/molprobity/__init__.pyRs cC s?|rt|jddSt|jdt|jddSdS(Nt r_free_outerR(RjRR-R#(R.R((sR/public2/ftp/pub/ccp4/6.5/ccp4-6.5/lib/py2/mmtbx/validation/molprobity/__init__.pyRs cC s6|jdk r|jjS|jdk r2|jjSdS(N(RR-RJR#(R.((sR/public2/ftp/pub/ccp4/6.5/ccp4-6.5/lib/py2/mmtbx/validation/molprobity/__init__.pyRJs cC sH|jdk rD|r+|jj|jjfS|jj|jjfSndS(N(RR-t d_max_outert d_min_outerRKRJ(R.R((sR/public2/ftp/pub/ccp4/6.5/ccp4-6.5/lib/py2/mmtbx/validation/molprobity/__init__.pyt d_max_minscC s,|jdk r(|jj\}}|SdS(N(RR-R(R.RR((sR/public2/ftp/pub/ccp4/6.5/ccp4-6.5/lib/py2/mmtbx/validation/molprobity/__init__.pyRscC s,|jdk r(|jj\}}|SdS(N(RR-R(R.RR((sR/public2/ftp/pub/ccp4/6.5/ccp4-6.5/lib/py2/mmtbx/validation/molprobity/__init__.pyRscC st|jddS(NR(RjRR-(R.((sR/public2/ftp/pub/ccp4/6.5/ccp4-6.5/lib/py2/mmtbx/validation/molprobity/__init__.pyRscC st|jddS(NR(RjRR-(R.((sR/public2/ftp/pub/ccp4/6.5/ccp4-6.5/lib/py2/mmtbx/validation/molprobity/__init__.pyRscC s|jdk r|jjSdS(N(RR-tpercent_allowed(R.((sR/public2/ftp/pub/ccp4/6.5/ccp4-6.5/lib/py2/mmtbx/validation/molprobity/__init__.pyt rama_alloweds cC st|jddS(NR(RjR R-(R.((sR/public2/ftp/pub/ccp4/6.5/ccp4-6.5/lib/py2/mmtbx/validation/molprobity/__init__.pyt rota_outliersscC st|jddS(NR(RjR R-(R.((sR/public2/ftp/pub/ccp4/6.5/ccp4-6.5/lib/py2/mmtbx/validation/molprobity/__init__.pytcbeta_outliersscC st|jddS(NRcS sdS(N(R-(((sR/public2/ftp/pub/ccp4/6.5/ccp4-6.5/lib/py2/mmtbx/validation/molprobity/__init__.pyts(RjR(R.((sR/public2/ftp/pub/ccp4/6.5/ccp4-6.5/lib/py2/mmtbx/validation/molprobity/__init__.pyRscC s%t|jdd}t|ddS(Ntalltb_mean(RjR"R-(R.t overall_stats((sR/public2/ftp/pub/ccp4/6.5/ccp4-6.5/lib/py2/mmtbx/validation/molprobity/__init__.pyt b_iso_meanscC st|jddS(Nt space_groupcS sdS(N(R-(((sR/public2/ftp/pub/ccp4/6.5/ccp4-6.5/lib/py2/mmtbx/validation/molprobity/__init__.pyRs(RjR!(R.((sR/public2/ftp/pub/ccp4/6.5/ccp4-6.5/lib/py2/mmtbx/validation/molprobity/__init__.pyRscC st|jddS(Ntspace_group_infocS sdS(N(R-(((sR/public2/ftp/pub/ccp4/6.5/ccp4-6.5/lib/py2/mmtbx/validation/molprobity/__init__.pyRs(RjR!(R.((sR/public2/ftp/pub/ccp4/6.5/ccp4-6.5/lib/py2/mmtbx/validation/molprobity/__init__.pyRscC st|jddS(Nt unit_cellcS sdS(N(R-(((sR/public2/ftp/pub/ccp4/6.5/ccp4-6.5/lib/py2/mmtbx/validation/molprobity/__init__.pyRs(RjR!(R.((sR/public2/ftp/pub/ccp4/6.5/ccp4-6.5/lib/py2/mmtbx/validation/molprobity/__init__.pyRscC st|jddS(Nttwin_law(RjRR-(R.((sR/public2/ftp/pub/ccp4/6.5/ccp4-6.5/lib/py2/mmtbx/validation/molprobity/__init__.pyRscC s%t|jdd}t|ddS(sm Returns the resolution bins containing F(model) statistics; see mmtbx.f_model_info for details. tinfotbinsN(RjRR-(R.t fmodel_info((sR/public2/ftp/pub/ccp4/6.5/ccp4-6.5/lib/py2/mmtbx/validation/molprobity/__init__.pytfmodel_statistics_by_resolutionscC s6|j}|dk r2ddlm}||SdS(sq Wrapper for fmodel_statistics_by_resolution(), returns object suitable for routines in wxtbx.plots. i(texport_bins_table_dataN(RR-tmmtbx.f_model_infoR(R.RR((sR/public2/ftp/pub/ccp4/6.5/ccp4-6.5/lib/py2/mmtbx/validation/molprobity/__init__.pytfmodel_statistics_graph_datas    cC sK|jj}|r%||jj8}n|jj}|dksCt||S(Ni(R"tn_atomst n_hydrogensRtn_reflRh(R.tassume_riding_hydrogensRR((sR/public2/ftp/pub/ccp4/6.5/ccp4-6.5/lib/py2/mmtbx/validation/molprobity/__init__.pytatoms_to_observations_ratios   cC s tdS(N(tNotImplementedError(R.((sR/public2/ftp/pub/ccp4/6.5/ccp4-6.5/lib/py2/mmtbx/validation/molprobity/__init__.pytas_mmcif_recordsscC s|jdkrdS|jjs|jdk rG|jj|jjn|jdk ro|jj|jjn|jdk r|jj|jjn|jdk r|jj|jjn|j dk r|jj|j jn|j dk r|jj|j jqn|jS(N( R'R-t is_populatedR tprocess_outlierstresultsR RR R R(R.((sR/public2/ftp/pub/ccp4/6.5/ccp4-6.5/lib/py2/mmtbx/validation/molprobity/__init__.pytas_multi_criterion_views  cC sX|jdk r|jjn|jdk r>|jjn|j}|jdS(N(RR-tdisplay_wx_plotsR R(R.tmc((sR/public2/ftp/pub/ccp4/6.5/ccp4-6.5/lib/py2/mmtbx/validation/molprobity/__init__.pyRs  cC stjjdddtjj}|dkr<tdnt|d}|j d|j d|j t|j |j d|j d|j dk r|j d |j j n|j dk r|j d |j j n|jdk r|j d |jj n|jdk r|j d |jj |jjdk r|j d |jj|j dqn|j d|jdS(s` Write a Python script for displaying outlier lists with click-to-recenter enabled. t relative_paths(cctbx_project/cootbx/validation_lists.pyttests+Can't find template Python script for Coot.tws-# script auto-generated by phenix.molprobity s s data = {} sdata['rama'] = %s sdata['rota'] = %s sdata['cbeta'] = %s sdata['probe'] = %s s4handle_read_draw_probe_dots_unformatted("%s", 0, 0) sshow_probe_dots(True, True) s/gui = coot_molprobity_todo_list_gui(data=data) N(RRctfind_in_repositoriestostpathtisfileR-RtopentwritetreadRt as_coot_dataR R Rt probe_filetclose(R.R(t coot_scripttf((sR/public2/ftp/pub/ccp4/6.5/ccp4-6.5/lib/py2/mmtbx/validation/molprobity/__init__.pytwrite_coot_scripts2        cC s-i}x |D]}d}|dkr4|j}n|dkrO|j}n|dkr^n|dkry|j}n|dkr|j}n|dkr|j}nl|dkr|j}nQ|dkr|j}n6|d kr|j}n|d kr|j }n||| 98%sRotamer outliersiis1%sC-beta outlierss%3d it0Rs%6.2fi(is Overall score(RRR-RRRR(R.Rt stat_info((sR/public2/ftp/pub/ccp4/6.5/ccp4-6.5/lib/py2/mmtbx/validation/molprobity/__init__.pytiter_molprobity_gui_fieldss ( RRRR+RRRRRfRR(((sR/public2/ftp/pub/ccp4/6.5/ccp4-6.5/lib/py2/mmtbx/validation/molprobity/__init__.pyRFs:  tpdb_header_infocB sYeZdZddddddddgZd d Zd Zejd e e d Z RS(sM Container for information extracted from the PDB header (if available). RJRKRRRRRt n_tls_groupsc C sx!|jD]}t||dq W|dk rddl}ddlm}|jjjd|}|j d|jj dd}|dk r|j |_ |j |_ |j |_|j|_n|jj|_t|j}xY|D]Q} | jdr| jj} t| d|_t| d|_PqqW|dk r|jj|j} | dk rt| |_qqndS(Ni(t"extract_rfactors_resolutions_sigmaR(t file_liness REMARK Final:i(R+R*R-tiotbx.pdb.hierarchyt iotbx.pdbRtpdbt hierarchytinputRtremark_sectionRRthighRJtlowRKtget_program_nameRRt readlinest startswithtstriptsplittfloatRRtextract_tls_paramst tls_paramsRR( R.tpdb_fileR4R0tiotbxRtpdb_intpublished_resultstlinestlinetfieldst tls_groups((sR/public2/ftp/pub/ccp4/6.5/ccp4-6.5/lib/py2/mmtbx/validation/molprobity/__init__.pyRs2          cC s"|jdk o!d|jjkS(Ntphenix(RR-tlower(R.((sR/public2/ftp/pub/ccp4/6.5/ccp4-6.5/lib/py2/mmtbx/validation/molprobity/__init__.pytis_phenix_refinementsRcC s |jdk r)|d||jfIJn|r|jdk rX|d||jfIJn|jdk r|d||jfIJn|jdk r|d||jfIJqn|r|jdk r|d||jfIJn|jdk r|d||jfIJqndS(Ns%sRefinement program = %ss%sHigh resolution = %6.2fs%sR-work = %8.4fs%sR-free = %8.4fs%sRMS(bonds) = %8.4fs%sRMS(angles) = %6.2f(RR-RJRRRR(R.R6Rtinclude_r_factorstinclude_rms_geom((sR/public2/ftp/pub/ccp4/6.5/ccp4-6.5/lib/py2/mmtbx/validation/molprobity/__init__.pyRs"   N( RRRR+R-RR"RRR`R(((sR/public2/ftp/pub/ccp4/6.5/ccp4-6.5/lib/py2/mmtbx/validation/molprobity/__init__.pyRs    tresidue_multi_criterioncB seZdZejdddgZdZdZddedZ dZ dZ d Z d Z d Zd Zd ZdZedZddZedZRS(s Container for multiple outliers associated with a single residue. If data are used, this may include real-space statistics regardless of whether the residue is technically an outlier or not. toutlierstn_confsti_seqcK stj||g|_dS(N(RRR&(R.R((sR/public2/ftp/pub/ccp4/6.5/ccp4-6.5/lib/py2/mmtbx/validation/molprobity/__init__.pyRscC s;t|tr'|j|s'tn|jj|dS(N(t isinstanceRtis_same_residue_groupRhR&tappend(R.toutlier((sR/public2/ftp/pub/ccp4/6.5/ccp4-6.5/lib/py2/mmtbx/validation/molprobity/__init__.pyt add_outlierscC s|dk s$t|dks$txV|jD]K}|j rN| rNq.nt|j}||ksu||kr.tSq.WtS(Ni( R-RRhR&t is_outlierttypeRR`Rf(R.t outlier_typet outlier_typest retrieve_allR,totype((sR/public2/ftp/pub/ccp4/6.5/ccp4-6.5/lib/py2/mmtbx/validation/molprobity/__init__.pyt_find_outlier_types$cC s |jdS(Nt ramachandran(R4(R.((sR/public2/ftp/pub/ccp4/6.5/ccp4-6.5/lib/py2/mmtbx/validation/molprobity/__init__.pytis_ramachandran_outlierscC s |jdS(Ntrotamer(R4(R.((sR/public2/ftp/pub/ccp4/6.5/ccp4-6.5/lib/py2/mmtbx/validation/molprobity/__init__.pytis_rotamer_outlierscC s |jdS(Ntcbeta(R4(R.((sR/public2/ftp/pub/ccp4/6.5/ccp4-6.5/lib/py2/mmtbx/validation/molprobity/__init__.pytis_cbeta_outlierscC s |jdS(Ntclash(R4(R.((sR/public2/ftp/pub/ccp4/6.5/ccp4-6.5/lib/py2/mmtbx/validation/molprobity/__init__.pytis_clash_outlierscC s|jddddddgS(NR1tbondtangletdihedralt chiralityt planarity(R4(R.((sR/public2/ftp/pub/ccp4/6.5/ccp4-6.5/lib/py2/mmtbx/validation/molprobity/__init__.pytis_geometry_outliers cC sg}|jr"|jdn|jr>|jdn|jrZ|jdn|jrv|jdn|jr|jdnt|dkrdg}nd|jd j|fS( NtramatrotatcbR;tgeois---s%s %st,( R6R+R8R:R<RBRtid_strtjoin(R.R&((sR/public2/ftp/pub/ccp4/6.5/ccp4-6.5/lib/py2/mmtbx/validation/molprobity/__init__.pyt__str__s      cC s|jjS(N(tresidue_group_id_strt__hash__(R.((sR/public2/ftp/pub/ccp4/6.5/ccp4-6.5/lib/py2/mmtbx/validation/molprobity/__init__.pyRL scC st|j|jS(N(tcmpR((R.RW((sR/public2/ftp/pub/ccp4/6.5/ccp4-6.5/lib/py2/mmtbx/validation/molprobity/__init__.pyt__cmp__ scC szxH|jD]=}t|jdkr |j|j|j|jg}|Sq W|rkddl}|jgdSdgdSdS(Ntresidue_real_spaceii( R&R/Rtb_isotccttwo_fofcROtnumpytNaNR-(R.t use_numpy_NaNR,tvaluesRS((sR/public2/ftp/pub/ccp4/6.5/ccp4-6.5/lib/py2/mmtbx/validation/molprobity/__init__.pytget_real_space_plot_valuess g?cC s?|jt\}}}}|dkr+dS||kr;tStS(N(RWRfR-R`(R.RQRPRQRRRO((sR/public2/ftp/pub/ccp4/6.5/ccp4-6.5/lib/py2/mmtbx/validation/molprobity/__init__.pytis_map_outliers   cC sg}|jr"|jdn |jd|jrK|jdn |jd|jrt|jdn |jd|jr|jdn |jd|rddl}g}x:|D]2}|dkr|j|jq|j|qW|S|S(Nii(R6R+R-R8R:R<RSRT(R.RUtyRSty_tyval((sR/public2/ftp/pub/ccp4/6.5/ccp4-6.5/lib/py2/mmtbx/validation/molprobity/__init__.pytget_outlier_plot_values"s,           N((RRRRR+RR-R-RfR4R6R8R:R<RBRJRLRNR`RWRXR\(((sR/public2/ftp/pub/ccp4/6.5/ccp4-6.5/lib/py2/mmtbx/validation/molprobity/__init__.pyR%s"          RwcB sbeZdZddgZedZejdZdZ dZ dZ dZ d Z RS( sb Container for generating multi-criterion plots and tables from separate lists of outliers. tresiduesRc C st|_i|_d}x|jjD]}|sZ|j rZ|j rZq+qZnx|jD]}|jdj }|dkrqgnt d|j d|j d|j d|jdj ddd |d t|j}|j}||j|<|d 7}qgWq+WdS( NitHOHtchain_idtresseqticodetresnametaltlocRR(R'i(RfRR]t only_modeltchainst is_proteintis_natresidue_groupst atom_groupsRbR%tidR`RaRRK( R.R4t include_allR(tchaint residue_groupRbRiRH((sR/public2/ftp/pub/ccp4/6.5/ccp4-6.5/lib/py2/mmtbx/validation/molprobity/__init__.pyR;s,         cC st|_x|D]}|jrz|jdkr7qn|j}||jkri|j|j|q|d|IJqtg}x|jD]t}|j}|jdks||krqn||jkr|j|j||j |q|d|IJqWqWdS(NR^smissing residue group '%s'( R`Rtis_single_residue_objectRbRKR]R-tsett atoms_infotadd(R.R&RGR,RHthave_idstatom((sR/public2/ftp/pub/ccp4/6.5/ccp4-6.5/lib/py2/mmtbx/validation/molprobity/__init__.pyRRs$      cC sD|jj|jd}|dkr@td|jn|S(NsCan't find residue '%s'(R]RRHR-t RuntimeError(R.Rmtresidue_validation((sR/public2/ftp/pub/ccp4/6.5/ccp4-6.5/lib/py2/mmtbx/validation/molprobity/__init__.pytget_residue_group_datags cC st|jjS(N(tsortedR]RV(R.((sR/public2/ftp/pub/ccp4/6.5/ccp4-6.5/lib/py2/mmtbx/validation/molprobity/__init__.pytdatamscC s#ddlm}|j|jS(Ni(tgraphics(RRytresidue_binnerRx(R.Ry((sR/public2/ftp/pub/ccp4/6.5/ccp4-6.5/lib/py2/mmtbx/validation/molprobity/__init__.pyt binned_datapscC sddl}g}x'|jD]}|j|jqW|j|j}tt|dt|d}tt|dt|d}i||fd6t|dt|dfd6t|dt|dfd6S( NiiitrhoitbiRQ(RSRxR+RWtarrayt transposetminR(R.RSRVR,trho_mintrho_max((sR/public2/ftp/pub/ccp4/6.5/ccp4-6.5/lib/py2/mmtbx/validation/molprobity/__init__.pyt get_y_limitsts ## !cC s>ddl}|jjjddddd|}|jdS(NitparentttitlesMolProbity multi-criterion plotR(twxtbx.plots.molprobitytplotsRtmulti_criterion_frameR-tShow(R.twxtbxtframe((sR/public2/ftp/pub/ccp4/6.5/ccp4-6.5/lib/py2/mmtbx/validation/molprobity/__init__.pyRs   (RRRR+RfRRtstderrRRvRxR{RR(((sR/public2/ftp/pub/ccp4/6.5/ccp4-6.5/lib/py2/mmtbx/validation/molprobity/__init__.pyRw5s      (%Rt __future__RRRRRRRRRRR R R tlibtbx.str_utilsR R RRRRt libtbx.utilsRRtlibtbx.load_envt libtbx.philtos.pathRRRRRRRR%Rw(((sR/public2/ftp/pub/ccp4/6.5/ccp4-6.5/lib/py2/mmtbx/validation/molprobity/__init__.pyts6     T:a