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(Used in Xtriage) N)rrr)rr(rr)r4rrr%r%r&rMs zbinned_data.as_simple_table)N) NTTNTTriNNr?)N)rrrr*rrr%r%r%r&r-s  rcCs*i}x tt|D]}||||<qW|S)N)rr])r+r{ir%r%r&make_lookup_dictYsrr>FcCs|dkrdddggS|dkrhdddgdddgdddgdddgdddgdddgg}|rd|dddg|Sg}xxt| |dD]d}x^t| |dD]J}xDt| |dD]0}|s|dks|dks|dkr||||fqWqWq~W|S)Nrr>)rEr)layersinclude_origin offset_listixZiyizr%r%r&get_offset_list_s  rcCsNddlm}||}ttt|| }|j || dS)Nr)col)r+r) scitbx.matrixrr miller_indexlistvec3_intr+as_vec3_doubleras_intcustomized_copyr)r#offsetrr+r%r%r&offset_indicesus  rc@sJeZdZdZdddZddZddZd d Zd d Zd dZ ddZ e e e e e fddZ dddZ ddZdddZdddZdddZdd d!Zd"d#Zdd$d%Zd&d'Zd(d)Zd*d+Zd,d-Zd.d/Zd0d1Zd2d3Zdd4d5Zd6d7Zd8d9Zdd:d;Zdd?Z!d@dAZ"dBdCZ#dDdEZ$ddGdHZ%dIdJZ&ddLdMZ'dNdOZ(dPdQZ)dRdSZ*ddTdUZ+dVdWZ,dXdYZ-dZd[Z.d\d]Z/d^d_Z0ddadbZ1ddddeZ2dfdgZ3ddhdiZ4djdkZ5dldmZ6ddndoZ7ddpdqZ8ddsdtZ9ddvdwZ:ddxdyZ;ddzd{ZdddZ?dddZ@dddZAdddZBddZCdddZDdddZEdddZFddZGdddZHdddZIddZJdddZKddZLdddZMdddZNddZOdddZPdddZQdddZRdddZSdddZTdddZUddZVddZWdd„ZXddĄZYddƄZZdddȄZ[dddʄZ\dd̄Z]dd΄Z^ddЄZ_dS)r:a Basic class for handling sets of Miller indices (h,k,l), including sorting and matching functions, symmetry handling, generation of R-free flags, and extraction of associated statistics. Does not actually contain data, but this can be added using the array(...) method. NcCs0|dks ttj||||_||_d|_dS)N)NFT)r!r r;_copy_constructor_indices_anomalous_flag_binner)r4r8r+r-r%r%r&r*s  z set.__init__cCs(tj|||j|_|j|_d|_dS)N)r r;rrrr)r4otherr%r%r&rszset._copy_constructorcCs|jS)zz Return a reference to the internal array of indices. :returns: a cctbx.array_family.flex.miller_index array )r)r4r%r%r&r+sz set.indicescCs|jS)z6Indicate whether the set or array is anomalous or not.)r)r4r%r%r&r-szset.anomalous_flagcCs |S)z5Return the number of reflections in the set or array.)r+r.)r4r%r%r&r.szset.sizecCst||j|jdS)zd Create a copy of the set, keeping references to the same crystal symmetry and indices. )r8r+r-)r:rr)r4r%r%r&copyszset.copycCsb|}|dk r tj|d}|dkr2d}n t|}ttj||d| | dS)z Create a copy of the set, also copying the crystal symmetry and indices. :returns: a set object with all-new attributes. N) parameters)r7space_group_symbol)r8r+r-) r7r rr,r^r:r r;r+ deep_copyr-)r4r7rr%r%r&rs   z set.deep_copycCsL|tkr |}|tkr|}|tkr,|}tjj|||d}t|||dS)z Create a copy of the set, optionally changing the symmetry, indices, and/or anomalous flag (default = keep all unmodified). )r7r,)r8r+r-)rr+r-r r;rr:)r4r8r+r-r7r,r%r%r&rs zset.customized_copycCsJ|dk r||jkst|dk r<||jkst|D]2\}} || d|| d|| dqPWd} tt || tt || tt || } } } | }d}d}t |dX}xPt|D]D\}} | | }t ||||d| |d| |d| f|d qWWdQRXdS) ak Write out Miller indices as pseudo-waters for visualization. Note that this treats the indices as literal coordinates (times a scale factor), and the distances between points will not correspond to the distances in reciprocal space. See cctbx/miller/display.py and crys3d/hklview for an alternative (but less lightweight) approach. Nrr>rTdz/CRYST1%9.3f%9.3f%9.3f%7.2f%7.2f%7.2f P1 zCHETATM%5d O HOH %5d %8.3f%8.3f%8.3f 1.00 1.00 O w)r})r!r7 expand_to_p1r+rint enumeraterEr\absreciprocal_parametersopenreciprocal_space_vectorrA)r4 file_namerucr+hkli_mimiscaleshskslrpZc1fmtfmtZofrsvr%r%r&miller_indices_as_pdb_files, $   zset.miller_indices_as_pdb_filecCs|dkrtj}|j||d|}|dk r|}|}|d}t |d||d|dkr|j |d}t |d|d| d}t |d ||d| dk r| }t |d ||d|dk r|dkr|r|jd d |jdd } | j} | ddks.t| ddksDt| d } | d } | dkr|d|d krt |d| | |d| | d7} | dkrt |d| | |d|r|s|rt |d||d|dk r|r|r|\} }t |d||dt |d|||dt|tr|rt |d| |d|S)z1Display comprehensive Miller set or array summaryN)rrTzSystematic absences:)r}r) selectionz.Systematic absences not included in following:zCentric reflections:zResolution range: %.6g %.6gr>)n_bins) use_binningrTz&Completeness in resolution range: %.6gz&Completeness with d_max=infinity: %.6gz0Anomalous completeness in resolution range: %.6gzBijvoet pairs:zLone Bijvoet mates:zMean anomalous difference: %.4f)!r~rrrr,is_unique_set_under_symmetrysys_absent_flagsrrrAselect centric_flagsr7resolution_ranger+r. setup_binner completenessr(rFr!rMr-is_xray_intensity_arrayis_xray_amplitude_arrayanomalous_completenessmatch_bijvoet_matespairs n_singlesrr# is_real_arrayanomalous_signal)r4rr no_sys_absrr n_sys_abs n_centric d_max_minZcompleteness_d_max_d_minr(Zn_obs n_completeasumatchesr%r%r&show_comprehensive_summarysd           zset.show_comprehensive_summaryc Cs|dkrtj}|j|dx|D]v}||}||}|\}}|j|d}| d} |j |ddd} d} t | || || f|d| q(WdS) z6 Display the completeness in resolution bins. N)reflections_per_bin)d_maxTF)rBrurxz%3d: %-17s %4.2f %6d)r}) r~rrr(r@rrrrrr|rAflush) r4routrBselZself_selrr/ZcomplZn_refd_rangerr%r%r&show_completenessGs      zset.show_completenesscCs8|dks|dkst|jtjj||ddS)NFT)r-)r8)r-r!rr r;reflection_intensity_symmetry)r4r%r%r&rYsz!set.reflection_intensity_symmetrycCs2|}|r|j|d}|j||dS)z Generate a boolean Miller array flagging those reflections which are systematically absent under the current symmetry. )r-)r) space_groupZ(build_derived_reflection_intensity_groupr-r# is_sys_absentr+)r4 integral_onlyZeffective_groupr%r%r&r_s  zset.sys_absent_flagscCst|||S)zG Generate a boolean Miller array flagging centric reflections. )r#r is_centricr+)r4r%r%r&rkszset.centric_flagscCst||||S)a Generate a Miller array (with integer data) indicating the multiplicity of each unique reflection. (If the set or array is already symmetry-unique, the multiplicity will be 1 for every reflection.) :returns: array object with flex.int data )r#rZ multiplicityr+r-)r4r%r%r&multiplicitiessszset.multiplicitiescCst|||S)N)r#repsilonr+)r4r%r%r&epsilonssz set.epsilonscCst|||S)N)r#r7rjr+)r4r%r%r&rjsz set.d_star_sqcCs t|t||dS)Ng?)r#rpowr7rjr+)r4r%r%r& d_star_cubedszset.d_star_cubedcCst|||S)zW Generate a double Miller array containing the resolution d of each index. )r#r7rir+)r4r%r%r& d_spacingsszset.d_spacingscCst|||S)N)r#r7rlr+)r4r%r%r&sin_theta_over_lambda_sqszset.sin_theta_over_lambda_sqcCst|||||S)z[ Generate a double Miller array containing the scattering angle of each index. )r#r7rmr+)r4rrrsr%r%r&rmsz set.two_thetacCst||S)z; High-resolution limit. :returns: Python float )r d_star_sq_as_dr7Z max_d_star_sqr+)r4r%r%r&r/sz set.d_mincCs||S)N)r7min_max_d_star_sqr+)r4r%r%r&rszset.min_max_d_star_sqc Cs|rtdd|D\}}|dkrt|}|d}t|d|||dd}||\}}t |t |}}||fStdd|DSdS)z Low- and high-resolution limits. :returns: Python tuple of floats Modified 2020-10-02 to allow return of maximum defined instead of -1 if F000 present cSsg|]}t|qSr%)r r)rorjr%r%r&rqsz!set.d_max_min..r)rrrNr>cSsg|]}t|qSr%)r r)rorjr%r%r&rqs) rtrrr+indexrrr7r r) r4$d_max_is_highest_defined_if_infiniterr/Z indices_copyrZ new_indicesZd_max_d_star_sqZd_min_d_star_sqr%r%r&rs   z set.d_max_mincCs t|S)N) index_spanr+)r4r%r%r&rszset.index_spancCs|}||fS)z!Return the range of h,k,l indices)rminr\)r4spanr%r%r&min_max_indicesszset.min_max_indicescCs&|j|}|dkrd}n||}|S)ae Returns the element `ary` coresponding to the `miller_index` if `miller_index exists, otherwise returns None. :param miller_index: Miller index as a 3-tuple :type miller_index: tuple :param ary: any array (e.g. self.data(), self.sigmas()) :type ary: sequence (list, array, etc) :returns: type of contents of `ary`, or None N)r first_index)r4aryrfirstr{r%r%r&at_first_indexs zset.at_first_indexcCs |j|S)aC Returns the first index of the item matching `miller_index`. If the `miller_index` is not found in `self`, then returns ``None``. :param miller_index: Miller index as a 3-tuple :type miller_index: tuple :returns: int, None -- index of first occurrence of `miller_index` or None )rr )r4rr%r%r&r s zset.first_indexc Cs|\}}tt|d|d}tt|d|d}tt|d|d}d|||gks`t|dd\}}}d||d||d||fS)zR Returns the effective resolution limits along the reciprocal space axes. rr>rTNg?)rr\rr!r7r) r4min_mimax_miZmax_hZmax_kZmax_lastbstcstr%r%r&d_min_along_a_b_c_stars zset.d_min_along_a_b_c_star{Gz?cCsd|d|S)NrTr>)r/)r4 tolerancer%r%r&!minimum_wavelength_based_on_d_minsz%set.minimum_wavelength_based_on_d_mincCs|S)zSynonym for d_max_min().)r)r4r%r%r&rszset.resolution_range2c Cs,|j|j|||||||||d dS)a Given an isotropic or anisotropic displacement or B-factor, alculate resolution-dependent scale factors corresponding to the indices. (Note that to simply apply one of the input parameters to an existing Miller array, you can call array.apply_debye_waller_factors) :param u_iso: Isotropic displacement (in Angstroms) :param b_iso: Isotropic B-factor (8*pi^2*u_iso^2) :param u_cart: Anisotropic displacement tensor :param b_cart: Anisotropic B-factor :param u_star: Anisotropic displacement tensor in fractional space :param u_cif: Anisotropic displacement tensor, dimensionless basis :returns: cctbx.miller.array object ) r<u_isob_isou_cartb_cartu_cifu_star exp_arg_limittruncate_exp_arg)r)r#r7debye_waller_factorsr+) r4rrrrrrrrr%r%r&r s zset.debye_waller_factorscCs|jdd\}}|S)z#Return the number of Bijvoet pairs.F)#assert_is_unique_set_under_symmetry)rrr.)r4rrr%r%r&n_bijvoet_pairss zset.n_bijvoet_pairscCst||ddS)zg Return a copy of the set using the same indices but with the anomalous flag set to false. F)r8r+r-)r:r+)r4r%r%r&as_non_anomalous_set"szset.as_non_anomalous_setcCst||ddS)zf Return a copy of the set using the same indices but with the anomalous flag set to true. T)r8r+r-)r:r+)r4r%r%r&as_anomalous_set,szset.as_anomalous_setcCs||gddkst|dkr,d}nH|dk rRd|||k}n"|dk rh||k}n |dk}t|||dS)z Set the anomalous flag automatically depending on whether the data contain Bijvoet pairs (optionally given minimum cutoffs). :returns: a copy of the set with (maybe) a new anomalous flag NrFrT)r8r+r-)rr!r+r.r"r:)r4Zmin_n_bijvoet_pairsZmin_fraction_bijvoet_pairsr-r%r%r&auto_anomalous6s zset.auto_anomalouscCs tj|||dS)zG Determine whether the indices in the set are symmetry-unique. )space_group_typer-r<)r)rr,rr-r+)r4r%r%r&rMs z set.is_unique_set_under_symmetrycCs tj|||dS)N)r&r-r<)r)unique_under_symmetry_selectionr,rr-r+)r4r%r%r&r'Vs z#set.unique_under_symmetry_selectioncCs*|}||kr |S||S)N)r'r.r+r)r4rr%r%r&unique_under_symmetry\szset.unique_under_symmetrycCs||S)z Indicate whether the array is entirely contained within the reciprocal space asymmetric unit (ASU). Warning: this calls map_to_asu internally, so it is better to simply call map_to_asu without checking in many cases. ) map_to_asur+all_eq)r4r%r%r& is_in_asuasz set.is_in_asucCsD|}|}|dkr d}t|||t|||S)z Convert all indices to lie within the canonical asymmetric unit for the current space group (while preserving anomalous flag). Required for many downstream steps. NT)r+rr-r)r,rr:)r4rr-r%r%r&r)js  zset.map_to_asuư>cCs|dkst|dkr6t||tdS|dk rPt|||dS|dk}|rd|}|}|dk r||d|9}t||||d}|r| | |dt k}|SdS)a] Generate the complete set of Miller indices expected for the current symmetry, excepting systematic absences. :param d_min_tolerance: tolerance factor for d_min (avoid precision errors) :param d_min: High-resolution limit (default = d_min of current set) :param d_max: Low-resolution limit (default = d_max of current set) )FTr)r8r-r+N)r8r- max_indexr>)r8r-r/r) r-r!r+r.r:rrrHr/rrr fp_eps_double)r4rKr/rr-Zd_min_was_noneZ d_min_exactr{r%r%r&rLzs4   zset.complete_setr>c Cs|dks t|rZ|rZ|}|||rD|||j|||||ddS|s|j||d}t | t d| d|S| dk stg} xLt| | D].\} } | dkr| |q| || | qWt| | dd S) a Calculate the (fractional) completeness of the array relative to the theoretical complete set, either overall or in resolution bins. By default the current low-resolution limit will be used. :param d_min_tolerance: tolerance factor for d_min (avoid precision errors) :param d_max: Low-resolution limit (default = d_max of current set) :param multiplier: Factor to multiply the result by (usually 1 or 100) :param as_non_anomalous_array: Report values for non-anomalous array rF)rrK return_failr multiplieras_non_anomalous_array)rKrr>g?Nz%5.3f)r(rr)r!r-r1merge_equivalentsr#set_observation_typeuse_binning_ofrrLrr+r.r\r(rrFrMrEr) r4rrKr/rr0r1mergedrLrZn_givenrr%r%r&rs2     zset.completenesscCst|dS)NT)rboolr+r.)r4r%r%r& all_selectionszset.all_selectioncCsD|dk st|dkr |}|r*|}||}t|||S)a  Select a subset of reflections. :param selection: flex.bool or flex.size_t selection :param negate: select the inverse of the selection array :param anomalous_flag: anomalous flag for the new set :returns: a new set with a subset of indices N)r+r!r-rr:)r4rnegater-rr%r%r&rs z set.selectcCs||S)zl Select only acentric reflections. :returns: A Miller set or array (depending on object type). )rrr)r4r%r%r&rIszset.select_acentriccCs||S)zk Select only centric reflections. :returns: A Miller set or array (depending on object type). )rrr)r4r%r%r&rJszset.select_centriccCs|j|| dS)N)rr8)rrr)r4r8r%r%r&remove_systematic_absencess zset.remove_systematic_absencescCsp|}|}|ds"tt|}|dk rL|dkrL||d|kM}|dk rl|dkrl||d|kM}|S)ze Obtain the selection (flex.bool array) corresponding to the specified resolution range. rNr>)r7rjrall_ger!rsqrt)r4rr/r{rjZd_starr%r%r&resolution_filter_selections  zset.resolution_filter_selectionrcCs|j|j||d|dS)a; Select a subset within the indicated resolution range. Returns a new miller array (does not change existing array) :param d_max: Low-resolution cutoff :param d_min: High-resolution cutoff :param negate: Select outside this range instead :returns: set or array depending on object type )rr/)rr8)rr<)r4rr/r8r%r%r&resolution_filters  zset.resolution_filterTcCs8|r||st||ks&tt||S)N)is_similar_symmetryr!r- match_indicesr+)r4rassert_is_similar_symmetryr%r%r&r? szset.match_indicescCs"|j||d}||dS)z Match the indices in the current set and another set, and return a set (or array) containing only those reflections present in both. Assumes that both sets are already in the asymmetric unit (ASU). )rr@r>)r?rrcolumn)r4rr@rr%r%r& common_sets zset.common_setcCsF|j||d}|r|rt|}||d||dgS)zn Like common_set(other), but returns a tuple containing matching copies of both sets (or arrays). )rr@r>r)r?Z have_singlesr!rrrA)r4rr@assert_no_singlesrrr%r%r& common_setss zset.common_setscCs||j||ddS)z Match the indices in the current set and another set, and return a set (or array) containing reflections which are present only in the current set. Assumes that both sets are already in the asymmetric unit. )rr@r>)rr?singles)r4rr@r%r%r&lone_set+sz set.lone_setcCs.|j||d}||d||dgS)zq Like lone_set(other), but returns a tuple containing the reflections unique to each set (or array). )rr@r>r)r?rrE)r4rr@rr%r%r& lone_sets5s z set.lone_setscCsl|dkst|dk s t|dk rP|}t|||d}n|}t||d}||fS)z Group Bijvoet mates (or Friedel mates) together, returning an object that allows enumeration over matching pairs and/or singletons. )NTN)r!)r-r!r+r,r)rr)r4r!rrr%r%r&r@s  zset.match_bijvoet_mates resolutionc Cs |dks t|dkst|dkr>tj|||ddS|dkr|}t| d||}t| d|| }||k}t | d}||d t|||}tj||ddStjt|||ddSd S) z Generate the selection array (flex.size_t object) to reorder the array by resolution or Miller index. :param by_value: sort type, must be "resolution" or "packed_indices" :param reverse: invert order :returns: flex.size_t object )rHpacked_indices asu_indices)FTrHT)rreversestablerJFrg{Gz?N)r!rsort_permutationr7rjr+rr)r,rrrdoubler. set_selected iselectionrpack as_double) r4by_valuerKrJZasu_indices_anomrZfriedel_mate_flagsrrr%r%r&rMSs(       zset.sort_permutationcCs||j||dS)zs Reorder reflections by resolution or Miller index. :param by_value: 'resolution' or 'packed_indices' )rSrK)rrM)r4rSrKr%r%r&sortuszset.sort皙?@cnscCsN|dks t|r|dkst|s4|j|||||dS|j||||||dSdS)a Create an array of R-free flags for the current set, keeping anomalous pairs together. Requires that the set already be unique under symmetry, and generally assumes that the set is in the ASU. :param fraction: fraction of reflections to flag for the test set :param max_free: limit on size of test set, overrides fraction :param lattice_symmetry_max_delta: limit on lattice symmetry calculation :param use_lattice_symmetry: given the current symmetry, determine the highest possible lattice symmetry and generate flags for that symmetry, then expand to the current (lower) symmetry if necessary. This is almost always a good idea. :param use_dataman_shells: generate flags in thin resolution shells to avoid bias due to non-crystallographic symmetry. :param n_shells: number of resolution shells if use_dataman_shells=True :param format: convention of the resulting flags. 'cns' will return a boolean array (True = free), 'ccp4' will return an integer array from 0 to X (0 = free, X dependent on fraction), 'shelx' will return an integer array with values 1 (work) or -1 (free). :returns: a boolean or integer Miller array, depending on format. )rYccp4shelxr)fractionmax_freeuse_dataman_shellsn_shellsformat)r\r] max_deltar^r_r`N)r!generate_r_free_flags_basic)generate_r_free_flags_on_lattice_symmetry)r4r\r]Zlattice_symmetry_max_deltaZuse_lattice_symmetryr^r_r`r%r%r&generate_r_free_flags~s  zset.generate_r_free_flagscCstj||dS)z{Get crystal symmetry of the miller set :returns: a new crystal.symmetry object :rtype: cctbx.crystal.symmetry )r7r,)r r;r7r,)r4r%r%r&r8szset.crystal_symmetryc Cs|} | dkrtd| } |rH|d} | | } |sTt|dk r|dkrl|dksttd|dkst|dkst|dk r|dk stt | ||t | }|dkst|dkst|r|rt|dkst|dkst|dkst| } | | } t j| |d}tj| |dd }| j|t| dd }|}|}|}|}d}|s|r|d krtd tj|||d }ntj|||d}n`t}t||d}x0t|D]$}t|}t |}|!|qWtt"|d|}|}|j#tj |$|dddd}|j|dd}|%}|jtj| | &dd}|}|r|'}| | (}|)|}|j||*d}|)|}|+|st|S)a Generate R-free flags by converting to the highest possible lattice symmetry (regardless of intensity symmetry), creating flags, and expanding back to the original symmetry. This is a safeguard against reflections that are correlated due to twinning being split between the work and test sets. This method should usually not be called directly, but rather through set.generate_r_free_flags(...). rz9An array of size zero is given for Free R flag generationr>Ng?z?R-free flags fraction must be greater than 0 and less than 0.5.F)ra)r7rZassert_is_compatible_unit_cell)r8rrZzPCCP4 convention not available when generating R-free flags in resolution shells.)n_refl fraction_freer)r`T)rrK)r+rK)rr)r7r)r8)r+r),r+r.rr-rrrrr!rfloat!change_of_basis_op_to_niggli_cell change_basisr groupr7r r;r#rrrNr)r2average_bijvoet_matesrassign_r_free_flags_by_shellsassign_random_r_free_flagssize_trr random_doublerMextendrrrjrrgenerate_bijvoet_matesinverserBrr*)r4r\r]raZreturn_integer_arrayZ n_partitionsr^r_r`Z n_originalZ n_non_anorZcb_op_to_niggliZtmp_maZ lattice_groupZ lattice_xsZ tmp_flagsZn_non_ano_lat_symrgr{Zn_timesiitmpr+r%r%r&rcs                           z-set.generate_r_free_flags_on_lattice_symmetrycCs|dkr|dkstd|r,|dkr,td|dk rD|dkrDtd|r|d}|d }|d }|d } |d } ||} ~n|st | } |dk rt ||t d| }|r|d krtd t j| ||d } nt j| ||d} |s| } nH| |} | | | | | | | | ks^t | jtj|| dddd} |s|j| dS~ |d krd}t| d}n<|dkrd}t| d}nd}t| d}|}|| }| d|}|||||||ks>t |||||d||ksht ~~~|| | ||~ || | |d~ |j|dS)z Generate R-free flags, without taking lattice symmetry into account (not recommended). Should not normally be called directly - use generate_r_free_flags(...) instead. rg?z?R-free flags fraction must be greater than 0 and less than 0.5.zOYou must use at least 5 resolution shells when assigning R-free flags this way.NzQThe maximum number of free reflections must either be None, or a positive number.r>+rXrZzPCCP4 convention not available when generating R-free flags in resolution shells.)rerfr)rerfr`T)rrK)r+rK)rr[rFrT)rr-rpairs_hemisphere_selectionrErr.rrr!r+rr\rrlrmrrprrMr7rjr#rr6rOr)r4r\r]r^r_r`rZsel_ppZsel_pmZsel_spZsel_smrgr{r+Ztest_flag_valueZ result_fullZi_ppZi_pp_spZr_ppr%r%r&rb+s                    zset.generate_r_free_flags_basiccCsPtj|dd}|r"|d9}n|dtj9}|j|j|||ddS)N)r.g?ihrT)r<phasesrs)r) rror.mathpir#rZnearest_valid_phasesr+)r4rs random_phasesr%r%r&0random_phases_compatible_with_phase_restrictionss  z4set.random_phases_compatible_with_phase_restrictionscCs8t|trt|}tj|tj||| | dS)a&Get a transformation of the miller set with a new basis specified by cb_op :param cb_op: object describing the desired transformation of the basis :type cb_op: string or sgtbx.change_of_basis_operator :returns: a new miller set with the new basis :rtype: cctbx.miller.set )r8r+) rr^r change_of_basis_opr:rr r;riapplyr+)r4cb_opr%r%r&ris  zset.change_basiscCsL|dk st|dk s t|dk s0tt||||dS)N)rr-r+build_iselection)r,r!r+r-expand_to_p1_iselectionr)r4rr%r%r&rszset.expand_to_p1_iselectioncCs6|j|d}t||j|d}|r2||jfS|S)zGet a transformation of the miller set to spacegroup P1 :returns: a new set of parameters (symmetry, miller indices, anomalous_flag) in spacegroup P1 :rtype: set(cctbx.crystal.symmetry, cctbx.miller.indices, boolean) )r)r8r+r-)rr:cell_equivalent_p1r+r-rP)r4return_iselectionproxyr{r%r%r&rs   zset.expand_to_p1cCs&|dksttj|tj|dS)NF)r8)r-r!r:rr r;patterson_symmetry)r4r%r%r&rszset.patterson_symmetryUUUUUU?ruc Cs<|dkr|dkr|}tj|||||||||d S)z Calculate real-space grid for FFT given array crystal symmetry, d_min, and desired resolution-dependent spacing. 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N) r7r/resolution_factorstepsymmetry_flagsr,mandatory_factors max_primeassert_shannon_sampling)r/r crystal_griddingr7r,)r4rr/ grid_steprrrrr%r%r&rs zset.crystal_griddingcCs>t|||}|}|j||||dS)N)r+r) asu_map_extZasymmetric_maprrr+rstructure_factorsr7volume)r4Z asu_map_datan_realZasu_mr+r%r%r&structure_factors_from_asu_maps z"set.structure_factors_from_asu_mapc Cs|dkr |dkr |s$tt|tjr8|}t|tjsTt|tj sTt|dks`tt|tjrt | }| s|rt| |kstt|t||}q|s|}n|s|}t | }||}|r|t|}||9}|dkr0|}|rVtjj||| |dd}ntjj|| |dd}|!} t"|| dS) a Run FFT on a real-space map to calculate structure factors corresponding to the current set of Miller indices. :param map: flex.double map with 3D flex.grid accessor :param in_place_fft: perform the FFT in place instead of creating a copy of the map first :param use_scale: perform volume-scaling using current unit cell :param anomalous_flag: determines anomalous_flag for output array :param use_sg: use space-group symmetry :returns: array with same Miller indices and complex_double data rr )FTNT)rr-r< complex_mapconjugate_flag)r-r<rr)r6r)# focus_size_1dnd is_0_basedr!rrrrRrNcomplex_doublerreal_to_complex_3dfocus is_paddedrr rgridZm_real set_focusrcomplex_to_complex_3dforwardr7rrrproductr-rfrom_maprr+rr#) r4mapZ in_place_fft use_scaler-use_sgfftrrrr%r%r&structure_factors_from_mapsJ$   "     zset.structure_factors_from_mapc CsLddlm} |dkr&| jj|||dS| jj|||||||| d|||dS)a Calculate structure factors for an :py:class:`cctbx.xray.structure` object corresponding to the current set of Miller indices. Can use either FFT or direct summation. :param xray_structure: :py:class:`cctbx.xray.structure` object :param algorithm: switch method to calculate structure factors - can be 'direct' or 'fft' :returns: array with same Miller indices and complex_double data r)xrayZdirect)xray_structurer6 cos_sin_table)r6rgrid_resolution_factorquality_factoru_baseb_base wing_cutoffexp_table_one_over_step_size)rr6 algorithm)cctbxrrZfrom_scatterers_directZfrom_scatterers) r4rrrrrrrrrrr%r%r&!structure_factors_from_scatterers s$ z%set.structure_factors_from_scatterersc Csddlm}t}t}x4|D](\}}||j| ||q$Wt j |||j |j |||dj}t||S)z A miller.array whose data N(h) are the normalisations to convert between E's and F's: E(h) = F(h) / N(h) The argument wilson_plot shall feature attributes - wilson_intensity_scale_factor - wilson_b r)eltbx)Z form_factorsrwilson_intensity_scale_factorwilson_br+r7r)rrrrNZshared_gaussian_form_factorsitemsrEZxray_scatteringwk1995Zfetchr)Zamplitude_normalisationrrr+r7rnormalisationsr#) r4 asu_contents wilson_plotrrZ gaussiansZ chemical_typeZ multiplicyrr%r%r&amplitude_normalisations1s    zset.amplitude_normalisationsc Cs(|j||j|||||||| ddS)N)rrrrrrrr) f_obs_factorf_calc)f_obs_minus_f_calcrr) r4rrZstructure_factor_algorithmrrrrrrr%r%r&!f_obs_minus_xray_structure_f_calcKsz%set.f_obs_minus_xray_structure_f_calccCs|s|dks|dkst|s0|dks0|dks0t|r|dkr@d}|dkrLd}tt||d}||krtt||d}n|rtt||d}|dkst|dk st|dks|dkst|jt|||||d|S)z` Create internal resolution binner object; required for many other methods to work. rg?N)r5) r!rr]r+r7r.rr5r()r4rr/ auto_binningrrZ n_per_binr%r%r&r_s$ zset.setup_binnerr-C6?cs|dks t||ks0|d|krFt|dgS|}dt|}t |d||d}|}|fdd} | } t | |krt d|d| } g} x|t | D]p\} } | t | dkr.| | | d}}| ||gq| t | dkr| | d| | }}| ||gqWg}xt | D]\} }|\}}| dkr|||k}|||kM}n@| t | dkr||k}||||kM}n||k}|||kM}| |qtW|t |d}|t |d}| d| ddkrX|d t |d}| ||B|}g}xdt |D]X\} }| d|krt |ddkr|t |d|B|t |d<n | |qfW|}|S) z Create resolution bins on a logarithmic scale. 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(2009) Acta Crystallogr D Biol Crystallogr. 65:1283-91. r>rTTg?rcstdtg}}x8|tkrRtdt|}|||7}qWtt|}tdt|}|||S)Nr>)ryr;exprr\rEr)r9Zlnss_minri)lnsss0s1rr%r& get_limitss   z#set.log_binning..get_limitsrVN)r!r+r.rr6rTrrpow2logr]rrEr)r4Z&n_reflections_in_lowest_resolution_binepsZmax_number_of_binsZmin_reflections_in_binZd_spacings_sortedsss2rrr9rrrid1d2Z selectionsprr/rrspZnew_selectionsZnew_selsir%)rrrrr& log_binningxsd         ""zset.log_binningcCs|s|dk st|s |dk s t|r8|dks8|dks8t|rj|}t|}t|}~|dkrjd}|dksvtt||f\}}|jt| | |||dS)NrgMbp?g)r5) r!rrrr\rsortedrr5r7r+)r4rrr/d_star_sq_steprr%r%r&setup_binner_d_star_sq_steps$     zset.setup_binner_d_star_sq_steph㈵>cCs$|jdd\}}|dk r$t||} n|} |dk r)r5)rrr\rr=r.rrrNrErrr5r7)r4rZmin_binsZmax_binsrr/ d_toleranceZ d_max_dataZ d_min_dataZ d_max_workZ d_min_workZ working_dataZ n_ref_workZ this_d_tolrr9Z d_star_sq_minZ d_star_sq_maxrrBZ this_limitr%r%r&setup_binner_d_star_sq_bin_sizes4         z#set.setup_binner_d_star_sq_bin_size绽|=cCs~|dks t|dkstt|ts0t|ts0t|dk rD|dksDt|dk rX|dksXt|dksdt|dkspt|}|t|}|dd|dd}||k}|d7}| dd||}|dkr||d|dk}|dkr ||d|dk}| dkst|rRt dt | t |} |rNt|| n| }|| ksttd|| f| t |}t} | |d|dkr| d|dd|n| t d|dd|| d} xBtd|D]4} t | |} | || d|| | krPqW|dkrR| d|dd|n| |dd||jt|| dS) Nrg?r>rg?rTz7n_bins (%i) must be <= number of unique d-spacings (%i))r5)r!rrrjrrrrMrPinsertr.r\rrgrrNreserverErrr5r7)r4rr/rrrrjdeltaZiselZ n_bins_calcr9mrBrr%r%r&setup_binner_counting_sortedsV                z set.setup_binner_counting_sortedcCs|jS)zU Return a reference to the current resolution binner (or None if undefined). )r)r4r%r%r&r(7sz set.binnercCst|||_|jS)z| Use the resolution binning of the specified binner object (does not need to be from an identically sized set). )r(r)r4r5r%r%r&r=s zset.use_binningcCs|j|dS)zp Use the resolution binning of the specified set (does not need to be an identical set of indices). )r5)rr()r4rr%r%r&r4Eszset.use_binning_ofcCs$||st|j|_|jS)zQ Use the exact binner of another set, which must have identical indices. )r+r*r!r)r4rr%r%r& use_binner_ofLszset.use_binner_ofcCs d|_dS)N)r)r4r%r%r& clear_binnerTszset.clear_binnercCsD|r||st||ks&tt||j||dS)zu Combine two Miller sets. Both must have the same anomalous flag, and similar symmetry is also assumed. )r8r+r-)r>r!r-r:r concatenater+)r4rr@r%r%r&rWszset.concatenatecCs|dk r$|dkstdddg|}|dk rT|dkr<|dks@tt|||d}n$d||gksdtt||||d}||S)Nrrr)r+ slice_axis slice_index)r+r slice_start slice_end)r!rZ simple_slicer+Z multi_slicer)r4axisZ axis_indexrrrrr%r%r&r ds   z set.slicecCs&t|dkst||k}||S)zA Remove all reflections with the specified Miller index. r )r]r!r+r)r4hklseler%r%r& delete_index|s zset.delete_indexcCs@t|d}x |D]}|||kM}qW||S)z] Delete multiple reflections, as specified by the Miller indices of another set. T)rr6r+r.r)r4rrrr%r%r&delete_indicesszset.delete_indicescCsF|r |S|}|}||| t||ddS)zk If the array is not already anomalous, expand the miller indices to generate anomalous pairs. T)r8r+r-)r-rrr+rrprr:)r4rr+r%r%r&generate_bivoet_matess zset.generate_bivoet_mates)N)NN)Nr?)NF)Nr?)rN)F)F)F)r)NNNNNNrF)NN)r,NNN)Fr,NNr>N)FN)F)NN)rrr)T)T)TF)T)T)T)rHF)rHF)rUrVrWTFrXrY)rUrVrWFNFrXrY)rUrVFrXrY)F)T)F)rNNNNruT)FFNF)NFrNNNNN)NFNNNNN)rrFrr)rrrr)TNNN)rrrNNr)rrNNr)T)NNNNN)`rrr__doc__r*rr+r-r.rrrrr#r"rrrrrrrrrrjrrrrmr/rrrrr r rrrr r"r#r$r%rr'r(r+r)rLrr7rrIrJr9r<r=r?rBrDrFrGrrMrTrdr8rcrbr|rirrrrrrrrrrrrrrr(rr4rrrr rrrr%r%r%r&r:}sJ      4              # &        "  )  l Q    5    G  $ 2   r:cCs~|dk r@||gddkstt|t||||}n:t|t|||||}|dk rz|j|d}|S)a Given crystal symmetry, anomalous flag, and resolution limits, create a complete set object. :param crystal_symmetry: cctbx.crystal.symmetry object :param anomalous_flag: Boolean, indicates whether to generate anomalous indices :param d_min: High-resolution limit (optional if max_index is specified) :param d_max: Low-resolution limit (optional) :param max_index: highest-resolution Miller index :returns: a set object NrT)r) rr!r:Zindex_generatorr,rZto_arrayr7r=)r8r-r/rr-r{r%r%r&rHs(    rHcCsFt|dkstt}x|D]}||qW|dj|dS)Nr)r+)r]r!Zunion_of_indices_registryupdater+ras_array)Z miller_setsZuoimsr%r%r& union_of_setss  rc @sVeZdZdZdddZddZeeeeeeeeef dd Zd d Zd d Z ddZ dS) array_infozf Container for metadata associated with a Miller array, including labels read from a data file. NFc Cst|tdS)N)rlocals) r4source source_typehistoryrr5systematic_absences_eliminatedcrystal_symmetry_from_filetype_hints_from_filerrr%r%r&r*s zarray_info.__init__cCs&d|_|j|t|ds"d|_dS)Nrr)r__dict__rhasattrrr)r4stater%r%r& __setstate__s  zarray_info.__setstate__c Cs|tkr|j}|tkr|j}|tkr*|j}|tkr8|j}|tkrF|j}|tkrT|j}|tkrb|j}|tkrp|j}| tkr~|j } t ||||||||| d S)zw Create a modified copy of the array_info object, keeping all attributes that are not explicitly modified. ) rrrrr5rrrrr) rrrrrr5rrrrrr) r4rrrrr5rrrrrr%r%r&rs8zarray_info.customized_copycCs>g}|jdk r||j|jr*|d|jr:|d|S)Nr5r)rrpr5rEr)r4part_2r%r%r&as_string_part_2s    zarray_info.as_string_part_2cCs"|}t|dkrd|SdS)z A combined representation of the data labels extracted from the input file. This is generally how downstream programs will identify and select Miller arrays. r,N)rr]rb)r4rr%r%r& label_strings zarray_info.label_stringcCsxg}|jdk r |t|jn|jdk r:|t|j|}t|dkr^|d|t|dkrndSd|S)NrrNone:)rrEr^rrr]rb)r4r{rr%r%r&__str__s    zarray_info.__str__) NNNNFFNNN) rrrrr*rrrrrrr%r%r%r&rs.    rcCs@|dkrtdSy|jjdt|fStk r:dSXdS)Nz , size=%dZUnknown)r^ __class__rr] Exception)r#r%r%r&raw_array_summary's r c @seZdZdZdddZddZddZd d Zd d Zd dZ ddZ ddZ ddZ ddZ ddZdddZddZddZd d!Zd"d#Zd$d%Zd&d'Zd(d)Zd*d+Zd,d-Zd.d/Zd0d1Zd2d3Zd4d5Zd6d7Zeeeeeeeeedf d8d9Zdd;d<Z eeeeefd=d>Z!d?d@Z"dAdBZ#dCdDZ$dEdFZ%dGdHZ&ddIdJZ'dKdLZ(ddNdOZ)ddPdQZ*ddTdUZ+ddXdYZ,dZd[Z-dd]d^Z.dd`daZ/ddcddZ0ddedfZ1ddgdhZ2ddidjZ3ddkdlZ4ddmdnZ5ddodpZ6ddrdsZ7ddtduZ8ddwdxZ9ddzd{Z:dd}d~Z;ddZ<dddZ=dddZ>dddZ?ddZ@dddZAddZBdddZCddZDddZEdddZFdddZGddZHddZIdddZJddZKdddZLdddZMdddZNdddZOdddZPdddZQdddZRdddZSdddZTdddZUdddZVdddZWdddZXddZYdddZZddd„Z[dddĄZ\dddƄZ]dddȄZ^dddʄZ_ddd̄Z`dddτZadddфZbdddӄZcdddՄZddddׄZedddلZfdddۄZgdddބZhdddZiddZjddZkdddZldddZmdddZndddZodddZpdddZqddZrddZsddZtdddZuddZvddZwdddZxdؐddZyddZzddZ{ddZ|dِd d Z}dڐd d Z~d dZddZddZddZddZddZddZddZddZdېdd Zdܐd!d"Zdݐd$d%Zdސd'd(Zd)d*Zdߐd,d-Zdd0d1Zdd2d3Zdd5d6Zdd7d8Zdd:d;Zdd<d=Zdd>d?Zdd@dAZddBdCZdgddfdDdEZddFdGZddKdLZddMdNZdOdPZddRdSZddTdUZddVdWZddXdYZddZd[Zdd\d]ZeeZd^d_Zd`daZddddeZddfdgZdhdiZddldmZddodpZdqdrZddsdtZdudvZdwdxZddydzZdd{d|Zdd}d~ZddZddZddZddZdddZdddZejdfddZdddZdddZdddZdS(r#z Extension of the set class with addition of data and (optional) sigmas flex arrays, plus an optional array_info object and an optional flag for the observation type (amplitude, intensity, or reconstructed amplitude). NcCs(t||||_||_d|_d|_dS)N)r:r_data_sigmas_info_observation_type)r4r6rrr%r%r&r*4s  zarray.__init__cCs0t|||j|_|j|_|j|_|j|_dS)N)r:rr r rr)r4rr%r%r&r;s  zarray._copy_constructorcCs ||_|S)N)r)r4infor%r%r&set_infoBszarray.set_infocCs@ddlm}t|tr|}|dks6t||js6t||_|S)Nr)observation_types) cctbx.xrayrrr#observation_typeanyr!r)r4rrr%r%r&r3Hs   zarray.set_observation_typecCsddlm}||S)z1 Flag the array as X-ray amplitudes (F). r)r)rrr3 amplitude)r4rr%r%r&#set_observation_type_xray_amplitudePs z)array.set_observation_type_xray_amplitudecCsddlm}||S)z2 Flag the array as X-ray intensities (I). r)r)rrr3 intensity)r4rr%r%r&#set_observation_type_xray_intensityWs z)array.set_observation_type_xray_intensitycCs|jS)N)r )r4r%r%r&r^sz array.datacCs|jS)N)r )r4r%r%r&rasz array.sigmascCs*|dk r ||ks t||_dS)N)r.r+r!r )r4rr%r%r& set_sigmasdszarray.set_sigmasccs\|dk r6xJt|||D] }|Vq&Wn"x t||D] }|VqJWdS)N)rrr+r)r4itemr%r%r&__iter__is   zarray.__iter__cCs|jS)zB Return the associated info object, or None if undefined. )r)r4r%r%r&rqsz array.infor?cCsTtj|||d|dk rPt|trP|j}|dk rPt|d||d|S)N)rrzWavelength: %.4f)r})r:rrrrrrrA)r4rrrrr%r%r&rws  z array.show_comprehensive_summarycCs|jS)z Return the (experimental) data type, if defined. See the module cctbx.xray.observation_types for details. :returns: an object from cctbx.xray.observation_types )r)r4r%r%r&rszarray.observation_typecCsn|dk st|dk s t||kscCsbd}|dk r^|dkr^d}||kd}|}t|t|}||kr^d}|S)NrTF)rr.rrg)r4Zcritical_ratiorr{Z suspectedallratior%r%r&r+ s zarray.sigmas_are_sensiblecCs&|dkr|S||dkSdS)Nr)rr)r4r%r%r&enforce_positive_sigmas s zarray.enforce_positive_sigmascCs|s t|dk st|s(t||dk}||}|||k}t||d||}t||d}d|||d|||}td|}|j||d | }|S)a Takes in an intensity array (including negatives) and spits out amplitudes. The basic assumption is that P(Itrue) \propto exp(-(Itrue-Iobs)**2/(2*s)) where Itrue>=0 (positivity constraint on error free amplitudes). For amplitudes, this results in P(Ftrue) \propto 2 Ftrue exp( -(Ftrue**2-Iobs)**2/(2s) ) A Gaussian approximation is fitted to the Mode of this distribution. An analytical solution exists and is implemented below. This method does not require any Wilson statistics assumptions. Nrg@g?g@)rr) rr!rr+rrrr;rr3r7)r4Z i_sig_levelZi_sigidetZf_saddleZs_saddler{r%r%r&enforce_positive_amplitudes s  *z!array.enforce_positive_amplitudesxtal_3_7cCsddlm}|dks$|s$t|j|jd}||}|dkrptdt |dd dd | D| dkrt |||j}n$||| |}t ||j|j}|r||S) z Given an intensity/F^2 array (or undefined observation type), return the equivalent amplitudes. Note that negative intensities will be discarded; for French-Wilson treatment, call the separate array.french_wilson() method. r)rN)rOZcrystalszUnknown f_sq_as_f algorithm=%s z Possible choices are: z, cSsg|] }t|qSr%)r)rorr%r%r&rq sz#array.f_sq_as_f..)rrrrr!Zarray_f_sq_as_f_xtal_3_7Zarray_f_sq_as_f_crystalsget RuntimeErrorrrbkeysrr#rrZsigma_fr)r4rrr converters converterr{rr%r%r& f_sq_as_f s   * zarray.f_sq_as_fsimplec Cs |dks tddlm}|dks0|s0t|dkrTt|||j }n|dkr|||}t||j |j }ntt }t }xTt ||D]>\}}||d|dtd|ttdt||qWt|||d}|r||S) zP Convert amplitudes (and associated sigmas, if present) to intensities. )rWZshelxlr)rNrWrTg{Gz?)r6rr)r!rrrrrr#Zarray_f_as_f_sqrf_sqZ sigma_f_sqrrNrrEr\rr) r4rrr{rUrXZs_sqrrr%r%r& f_as_f_sq s"   , zarray.f_as_f_sqcCsL|r(t|t||dS|s4t| rH|j |dS|S)z Convert the array to simple amplitudes if not already in that format. Only valid for complex (i.e. F,PHI), intensity, or amplitude arrays. )r6rr)r) r"r#rrrrrrr!rrV)r4rr%r%r&r7 s  zarray.as_amplitude_arraycCs<|r|j|dS|s$t|s8|j|dS|S)z Convert the array to intensities if not already in that format. Only valid for complex (F,PHI), amplitude, or intensity arrays. )r)r"r7rYrr!r)r4rr%r%r&as_intensity_array s   zarray.as_intensity_arrayc Cs|s|st|dks,tddlm}|rr|}|j dd}|j |dd}|j |dd}nF|dk s~t|rd}nd }|| ||} t||| }|S) as Adjust a complex array (map coefficients) or phase array corresponding to a shift of all coordinates by new_xyz_frac = old_xyz_frac + shift_frac. If a phase array, must specify whether it is in degrees. Only makes sense in P1 F'=exp( i 2 pi h.(x+shift_frac)) -> F' = F exp ( i 2 pi h.shift_frac) phase_shift = 2 * pi * h . shift_frac )rr>r)rF)rs) phase_sourcersNgv@gn!@)r"rr!rrnumberrr amplitudesrxtranslational_shiftphase_transferr+rdotr#r) r4Z shift_fracrsrr]Z phases_radZnew_phases_radr{cZ phase_shiftr%r%r&r^ s"      zarray.translational_shiftcCs|}|}|s(|rDt||||n>|dkrft|||nt|||||t t |||||  |S)z Convert all indices to lie within the canonical asymmetric unit for the current space group (while preserving anomalous flag). Required for many downstream steps. N) r+rrr"r$r)r,rr-r#r:rr3)r4rsrrir%r%r&r)' s$       zarray.map_to_asucCs|r||st||ks.t||ksBtt||}|||stt| }| }|dk r||}|dk r||}t |||d |S)N)r6rr) r>r!r+r.r-r? permutationrr*rrr#r3)r4rr@rrirr%r%r& adopt_setA s  zarray.adopt_setcCsV||kst|dk rP||ksDt|dk sPt|j||d}t||jr||kst| }n|||}| | d| | d|dkrd}nlt||jr||kst| }n|||}| | d| | d|j ||dS)N)rr@rr>)rr)rr.r+r!rr?rrr rrOrArr#)r4rZdata_substituteZsigmas_substituter@rrrr%r%r& matching_setO s0      zarray.matching_setFc Cs||\}}|r,dt|d}t|t|}}d}|rtjjt |||d}dt|d}|j t | |j }n(t ||} | dkrt ||| }|j||dS)Ng?g@r>)xyzr)r)rDrrrrrscitbxrygaussian_fit_1d_analyticalr;r-rr.sumr) r4rZresolution_dependentror scale_factorrUZss_otherdenr%r%r&rp sz array.scalecCs||}}|r|j|d}|rdt|tjs2t||\}}|j|d}||\}} | |}| |} | | } | | } d} | dk r| | } |j | | | dS)N)r)r[)rr+r)rrrrrr!rDr_rGrrFr+rr)r4rrZreplace_phasesrrkZs_cZc_oZs_lZc_lZolZd_newZi_newZ sigmas_newr%r%r& complete_with s       zarray.complete_withr>cCs||kst|dks$t|j|d\}}|j|d\}}|} |rtt|t|} | dkrtt|t|| } ||| } | ||| || || } | | | | t | | |d} | j | dS)N)rr)r8r+r-)r)r-r!rrDrGrrjrrrpr+r:r8r#)r4rrZscale_for_lonesscale_for_matchesZf1_cZf2_cZf1_lZf2_lscale_k1rm result_dataZresult_indicesrr%r%r&combine s("& z array.combinerc Cs|j|||d}t||}|}|} | dk rB| } |} | dk rZ| } |d} | } | dkr~|}nL|| | }| dk r| | | || dk r| | | ||j || | dS)N)rKr/rr>r)r+rr) rLr?r+rrrrEr.rrresizer) r4rKr/rZnew_data_valueZnew_sigmas_valuecsrrrirrrgr%r%r&complete_array s(   zarray.complete_arrayrHcCs|dks t|dkr&tj|||d}np|dkrFtj|| dd}nP|dkrltjt|| dd}n*t|trtd|ntj|| dd}|S) aH Generate the selection array (flex.size_t object) to reorder the array by resolution, Miller index, data values, or absolute data values. :param by_value: sort type, must be "resolution", "packed_indices", "data", or "abs" :param reverse: invert order :returns: flex.size_t object )FT)rHrIrJ)rSrKrT)rrKrLrzUnknown: by_value=%s) r!r:rMrrrrr^ ValueError)r4rSrKr{r%r%r&rM s   zarray.sort_permutationcCs4|}|rt|}tt|||S)N)rr"rrr#r:rr)r4rr%r%r&r szarray.patterson_symmetryc Cs|dk st|dk s t|dk s0t|dk s@td}d}ttd|jj d}|dk r|dksvt| dkst|| |||d}|j}n|dk r|dkst| dkstt |t jstt| ||||d}|j}nJ|dks t|}||j}| dk rV| |j}|j}t||j|dj||d|}|r|dk st||fS|S)z- Generate the equivalent P1 dataset. N)rr#)rr-r+r)FT)rr-r+rrs)r8r+r-)rr)r,r!r+r-rZexpand_to_p1_complexZ expand_to_p1_hendrickson_lattmanrPr rrrrrrNZexpand_to_p1_phasesrrrPr:rr#r3) r4Z phase_degrZ p1_sigmasrPZ expand_typep1Zp1_datar{r%r%r&r sZ     zarray.expand_to_p1cCs.t|trt|}|dks$|dkrJ|s0tt||||d}n| rjt |||d}n`| s| s|rt |||d}n(|rt|||d}ntdd}|dk rt|tjst|}tttj|||j|d|j|d|S) NFT)r indices_indata_inrs)rrxry)r+rz#Unsupported miller.array data type.)r8r+r-)r6rr)rr^r r}rr!Zchange_basis_phases_doubler+rr"Zchange_basis_complex_doublerr!rr~rr$Z change_basis_hendrickson_lattmanrQrrrNr#r:r r;rir-r3r)r4rrsr{Z result_sigmasr%r%r&ri sJ        zarray.change_basiscCs|s t|j|||d\}}||ks8t||}}|t|}t|}t t |d}dt j dt ||S)z The factor phi_{sym} quantifying whether complex structure factors are invariant under the given symmetry operator, as used in Superflip. Ref: J. Appl. Cryst. (2008). 41, 975-984 )r@rTr )r"r!rDrir.rrr(rrargryrz mean_weighted)r4opr@rZop_fZcc_sfweightsrr%r%r&symmetry_agreement_factor@ s   zarray.symmetry_agreement_factorcCs|s t||s"t||ks6t|rZt||||dSt|||t|dj |dSdS)N)r6r)r[) r"r!r+r*r-r#rrrr_)r4rrr%r%r&rR s zarray.f_obs_minus_f_calc绽|=cCs<|dk stt|dr"|}t|tjsFt|tjsFtt|tjsnt|tjsnt|tjsntt|tjr|dkrt}n t|d}|| | |d}t|tjr|}nt |}| dk stt|tjrt |t | | ||||dSt |t | | ||||dS)a2Combines phases of phase_source with self's data if real (keeping the sign of self's data) or with self's amplitudes if complex. Centric reflections are forced to be compatible with the phase restrictions. phase_source can be a miller.array or a plain flex array. epsilon is only used when phase_source is a complex array. If both the real and the imaginary part of phase_source[i] < epsilon the phase is assumed to be 0. deg is only used if phase_source is an array of doubles. deg=True indicates that the phases are given in degrees, deg=False indicates phases are given in radians. phase_integrator_n_steps is only used if phase_source is an array of Hendrickson-Lattman coefficients. The centroid phases are determined on the fly using the given step size. Nr)n_steps)rr< hendrickson_lattman_coefficients)r6rr)rr!rrrrrNr#phase_integratorrr+rr#r_r)r4r[rrsZphase_integrator_n_steps integratorrr%r%r&r_` sN       zarray.phase_transfercCs&dtjt|}||S)NrT)ryrzrrorr.r_)r4r{r%r%r&randomize_phases szarray.randomize_phasescCsd|s t|dks |dks t|dkrB|dkr8t}n t|d}t|||||ddS)N)r)rr<r)r6r)r$r!rr#rr+r)r4rrr%r%r&phase_integrals s  zarray.phase_integralscCs|dk stt|tr>t||dks6t|}t|}t|tjsht|tj shtt|tjrt|}n|}t j j ||d}t |}t|}|dkstt||}||dt jS)Nr)phi1phi2)rr!rr#rorderr+rzrrNrhry phase_errorrrjrz)r4r[rwp2erZsum_wZsum_wer%r%r&mean_weighted_phase_error s     zarray.mean_weighted_phase_errorcCs|dk stt|tr>t||dks6t|}t|}t|tjsht|tj shtt|tjrt|}n|}t t j j ||d}|dt jS)Nr)rrr)rr!rr#rrr+rzrrNmeanrhryrrz)r4r[rwrrr%r%r&mean_phase_error s   zarray.mean_phase_errorcCsh|s t|dkr(t|d}ddl}|dkrD|dd}tj | ||||d}|j |dS)z* Add random error to reflections. NTri@B)rramplitude_errorphase_error_deg random_seed)r) r"r!rr6r+r.randomrandintr)randomize_amplitude_and_phaserr)r4rrrrrnew_datar%r%r&r s  z#array.randomize_amplitude_and_phasecCsx|dk st|}|r |}|\}}|d}||}d}|dk rb||}tt ||dd||S)zm Returns an array object with DANO (i.e. F(+) - F(-)) as data, and optionally SIGDANO as sigmas. NrvF)r-) rr!rKrZmiller_indices_in_hemisphereZminusradditive_sigmasr#r:)r4rK tmp_arrayrrrrirr%r%r&anomalous_differences s   zarray.anomalous_differencescCsJ|dks t|dk st|\}}d|}|j||ddS)N)rvrXz+-F)rr-)r!rrrrrrA)r4Z plus_or_minusrri_columnr%r%r&hemisphere_acentrics s    zarray.hemisphere_acentricscs4|dk st|\tfdddDS)Ncs$g|]}j|ddqS)F)rr-)rrrA)ror)rrr%r&rq sz/array.hemispheres_acentrics..)rr>)rr!rrt)r4r%)rrr&hemispheres_acentrics s   zarray.hemispheres_acentricscCs|r|st|s|}|r4|j|||d}|}|ddkrRdS||}| } | } t | | dS| dk stg} xT| D]D} | | } || }| | \}}| |j|||dqWt| | ddS) z Return the percent of acentric reflections with both h,k,l and -h,-k,-l observed (only meaningful for amplitude and intensity arrays). By default this is calculated relative to the complete set. )rr/rKFrg?N)rr/relative_to_complete_setz%5.3f)r(rr)r-rr!rkrLrrrrr.rrr(rDrrarErr)r4rrKrr/rr5rZmerged_acentricZ n_acentricZ anom_diffsresultsrBrZ array_selZ d_max_binZ d_min_binr%r%r&r s.   zarray.anomalous_completenessc Cs|s |S|}|dk rf|}|}|d}|dkrT|j|d}|d}|dk r|r|r| \}}| } | |} | dkr| d| |kr| } | |}|S)z Convert anomalous array into nonanomalous if the number of Bijvoet pairs is too small compared to the number of lone Bijvoet mates. NTr)rg?)r-rr,rrrrrrrrr.rr1r2r#r3) r4 thresholdrrrrrrrrZ n_lone_matesr5r%r%r&6convert_to_non_anomalous_if_ratio_pairs_lone_less_than& s(        z}{\frac{1}{2} (<|F(+)|>^2 + <|F(-)|>^2)}} :param use_binning: If 'True' the anomalous signal will be calculated for each bin of the data set individually :type use_binning: boolean :returns: the anomalous signal :rtype: float or cctbx.miller.binned_data NrrTz%7.4f)r(rr)r(r!rrrrVrr.rrrryr;rDrrErr) r4robsZf_plusZf_minusZ mean_sq_diffZ mean_sum_sqrrBrr%r%r&r? s(    zarray.anomalous_signalc Cs|s t|st|}|s6tddd|S||}t |}| |}t }| |}|dk rt||k}| |}| |}t||}|rt||||Stddd|S)N)rr!r-rr.rrrrrMrrnormal_distribution quantilesrlinear_regressionis_well_definedr y_intercept) r4rZdIrfr< distributionrerfitr%r%r&anomalous_probability_plot_ s$       z array.anomalous_probability_plotcCsF||gddkst|r>tdd}||||}|r|}t t d|}| |d}t t d|}| |d}||}|s|rt |S|j|d}|Snz|dk stg} xR|D]B} || } || } d} | dkrt | } | | qWt|| d d SndSdS) aTGet phase entropy as measured in terms of an base-360 entropy (base-2 for centrics). An entropy of 0, indicates that the phase uncertainity is as low as possible An entropy of 1 however, indicates that the uncertainty is maximal: all phases are equally likely! :param return_binned_data: if 'True' you receive a binned object rather then a raw array :type return_binned_data: boolean :param exponentiate: whether or not to exponentiate the entropy. 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NT)r8r+r-)r6rr)r-rrr+rrprr"rr(r$rr#r:)r4rr+rrr%r%r&rqWs0     zarray.generate_bijvoet_matesc Cs&|r||st|st|s*t|r>|dk s>t|}|r\|s\|}n|st|rt|}|j||d\}}|st| | S| |g}xf| D]V}| |}t| || |}|s|dq||qWt||ddS)a Calculate correlation coefficient between two arrays (either globally or binned). :param other: another array of real numbers :param use_binning: calculate CC in resolution bins (default = calculate a single global value) :param assert_is_similar_symmetry: check that arrays have compatible crystal symmetry :returns: a Python float (if use_binning=False), or a binned_data object N)rr@z%6.3f)r(rr)r>r!rr(r-rqrDrlinear_correlationrr4rDrrrrE coefficientr) r4rrr@lhsrrBr correlationr%r%r&rus2      zarray.correlationcCs"|dkrtj}||ks*t|r~|dk r~xt||D]*\}}t|t ||t j ||d|dqNWn| dkrxt||D]\}}t|t |||dqWn\| |kstx>t||| D]"\}}}t|t ||||dqW|S)z"Listing of Miller indices and dataN)rs)r}) r~rrr.r+r!r"rrAr^rZabs_argr)r4rrrsrrirr%r%r& show_arrays( $zarray.show_arraycCs||}}||s t|}|}|}t|}||}||}||}tj ||||d} | } | } | } d} | | }|dkrt | d} ddlm}|j| | | dd\} } t| }| | krdSt| || || |d S) z1 Compute Fourier Shell Correlation (FSC) )rrrrrrr) smoothingrT)rerf half_windowdegreeN)rid_invfsc)r+r*r!rrrrMrr rrirr.rrhrZsavitzky_golay_filterr)r4r bin_widthrrdsrrrrUrrirrrJrr%r%r&rs0          z array.fscM?cCs\|dkr4|dk st|j||d}|s@tdddSn |dks@td}x*t|jD]}|j||krT|}PqTWd}d}|dk rB|j|}|dk rB|d} | dkrd} |d} | t|jkrt|jd} d} |d kr|j| |k|j| |kgdd k} | s|rB|j| | } |j| | } dd l m }|j | | d dd j \}}}||}|d d ||}|d k|d kg}|dd krB| t |d |}| t |d |}||d krdt||}nh|dkrB|dkrBd|d|}}t||}t||}||kr(|}n|}t||dkrBd}|dkrP|}t||dS)zf Compute Fourier Shell Correlation (FSC) and derive resolution based on specified cutoff. 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Calculate an unphased Patterson map. )rr/rrrr)rf_pattr+ sharpeningorigin_peak_removal)r patterson_mapr) r4rr/rrrrr+rLrMrKr%r%r&rN?s zarray.patterson_mapcCs$ddlm}|j|||||ddS)z8 Write reflections to a SHELX-format .hkl file. r)hklf)rB file_objectnormalise_if_format_overflowfull_dynamic_range scale_rangeN)Z iotbx.shelxrOZ!miller_array_export_as_shelx_hklf)r4rPrQrRrSrOr%r%r&export_as_shelx_hklfYs zarray.export_as_shelx_hklfcCs$ddlm}|||||||ddS)z1 Write reflections to a CNS-format file. r)export_as_cns_hkl)rPrr array_names r_free_flagsN)Ziotbx.cns.miller_arrayrU)r4rPrrrVrWimplementationr%r%r&rUis zarray.export_as_cns_hklcCs$ddlm}|||||||ddS)a Write data in unmerged scalepack format. :param file_object: filehandle-like object :param file_name: output file to write :param batch_numbers: integer array indicating the batch (image) numbers corresponding to the indices (optional) :param spindle_flags: integer array indicating the position of the reflections on the detector (optional) r)writer)Zi_obsrPr batch_numbers spindle_flags%scale_intensities_for_scalepack_mergeN)Z'iotbx.scalepack.no_merge_original_indexrY)r4rPrrZr[r\rYr%r%r&export_as_scalepack_unmergedzs z"array.export_as_scalepack_unmergedr projectdatasetc Cs`|dkr.|r*|jr*|jd}nd}|j|||||||| d} | } | j|ddS)zU Simple version of write_mtz for a single array, typically map coefficients NrF)column_root_label column_typeslabel_decoratortitle crystal_name project_name dataset_namerr)r)rras_mtz_dataset mtz_objectwrite) r4rrarbrcrdrerfrgrrZ mtz_datasetrir%r%r& write_mtzszarray.write_mtzc CsPddl} |dkr&|} | dk r&| j}|dkr2d}| jj|||||||||d S)z Generate an iotbx.mtz.dataset object for the array, which can be extended with additional arrays and eventually written to an MTZ file. rNg?)rarbrcrdrerfrgrr)Z iotbx.mtzrrrmtzZmiller_array_as_mtz_dataset) r4rarbrcrdrerfrgrriotbxrr%r%r&rhs zarray.as_mtz_datasetcCsddl}|j||jS)Nr) iotbx.cifcifmiller_arrays_as_cif_block cif_block)r4 array_typermr%r%r& as_cif_blockszarray.as_cif_blockglobalcCsB|dkrtj}ddl}|jj}|j|d||<t||ddS)Nr)rr)r})r~rrnromodelrsrA)r4rrrZ data_namermror%r%r& as_cif_simples  zarray.as_cif_simplecCs$ddl}|jj||||||ddS)z$ Write phases to .phs file. rN)r4rscale_amplitudesrx phases_degfigures_of_merit)Z iotbx.phasesrxZmiller_array_as_phases_phs)r4rrwrxrxryrmr%r%r& as_phases_phss zarray.as_phases_phscCsB|dkr4ddlm}|}|jdd|||}t|||S)z Overriden version of set.amplitude_normalisation which computes the Wilson parameters from the array data if wilson_plot is None. Nr) statisticsrX)r)rr{r7rrr:r)r4rrr{rr%r%r&rs    zarray.amplitude_normalisationscCs t|||S)N)normalised_amplitudes)r4rrr%r%r&r|szarray.normalised_amplitudesc Cs|dkrdS|r$|dk s$t|r4|dks4t|dk rT||ksTt|s`t||ksxt|s`|dkrdS|}|r|}nt|}|dk r|dkst|t ||k}| |}| |}|dk r| |}|dkr:t ||t t |St |||t |t |Sg}xZ| D]J} || }d} |dk r| |} || || || qrWt||ddS)a& The analytical expression for the least squares scale factor. K = sum(w * yo * yc) / sum(w * yc^2) If the optional cutoff_factor argument is provided, only the reflections whose magnitudes are greater than cutoff_factor * max(yo) will be included in the calculation. Nrr>z%7.4f)r(rr)rr(r!r.r"rrrrr\rrjrrDrrErlr) r4rr}rrrcalcrrrBZ weights_selr%r%r&rlsH             zarray.scale_factorcCsDddl}ddlm}|jj||||jdj}|dk r<||S|SdS)zg Class method for building an array from a CIF file (or filehandle). Depends on iotbx.cif. rN)builders)rP file_pathdata_block_namedata_structure_builder)rnr~rocctbx_data_structures_from_cifmiller_array_builder miller_arrays)clsrPrrrmr~arraysr%r%r&from_cif0s  zarray.from_cifcCs`|s t|}|||}d||t|d|}|d7}t |d}|S)a Extinction parameter x, where Fc is multiplied by: k[1 + 0.001 x Fc^2 wavelength^3 / sin(2theta)]^(-1/4) See SHELX-97 manual, page 7-7 for more information. Note: The scale factor, k, is not applied nor calculated by this function. The scale factor should be calculated and applied ***AFTER*** the application of the extinction corrections. gMbP?r r>gп) r"r!rZrr7Z sin_two_thetar+ryrr)r4rerrr:Z sin_2_theta correctionr%r%r&shelxl_extinction_correctionAs   z"array.shelxl_extinction_correctioncCs |||}|j||dS)N)r)rrr)r4rerrrr%r%r&"apply_shelxl_extinction_correctionUs z(array.apply_shelxl_extinction_correction皙?皙?cCs||st|r.t|}n |}|}t|dkrXdSt |}t ||}|dkr|dS|||9}t t |t |} | dkrdS|d| 9}|d| 9}d|d|} | |} d| } |} || || k|| || kB}|r|||fS|S)z Preconditions (not checked explicitly): self is amplitude array, f_calc is complex array or amplitude array. rNr>) r+r*r!r"rrrrrrrjr\)r4rZ offset_lowZ offset_highZalso_return_x_and_yrerfZsum_xxZsum_xyrZm_lowZb_lowZm_highZb_highr{r%r%r&"f_obs_f_calc_fan_outlier_selectionYs4         z(array.f_obs_f_calc_fan_outlier_selectioncCs|dks |s |s t|s,t|dk scCstddl}|}|j|}|}t|tt|t|}t | |} t|}t} x| D]} t| |} t|t| } t | | } | |}| | }d}| dkr |dkst ||}tdt|dkrd}dt jt |}| |qvWx:tddD],}| |k}d|d||kr$Pq$W|rf|j|d S|j|d S) z Remove reflections corresponding to a cone shape in reciprocal space with the apex at the origin. Used to simulate incomplete data due to poor alignment of the crystal with the goniometer axis. rNg?gMbP?rr>gY@T)r)rr7fractionalization_matrixrsqr transposerrNrryr;r`r+r!rrzacosrErrr.r)r4Zfraction_percentZvertex axis_point_1 axis_point_2r8rhfmr axis_lengthZopening_anglespointZpoint_minus_vertexZpoint_minus_vertex_length numerator denominatorZopening_angle_deg_for_pointrJZoarr%r%r& remove_cones>         zarray.remove_coner cCs*|dkrdS|jdd}d\}}}xt||||D]\}}}} ||} |ddkr|ddkr|||kr|dkr| |df}|ddkr|ddkr|||kr|dkr| |df}|ddkr|ddkr|||kr|dkr| |df}|||gddkrLPqLW|||gddksh|d|d|dgddkr | \} } dd} | | d| d}| | d| d}| | d| d}| \}}}|dks|ddkr||f}|dks|ddkr||f}|dks|ddkr ||f}|||fS) NT)rK)NNNr>rrTcSs4t||kr|St||kr |St||kr0|SdS)N)r)r-r.r%r%r&helpers    zBarray.ellipsoidal_resolutions_and_indices_by_sigma..helper) rrTrr+rrr7rrrr)r4 sigma_cutoffrh_cutk_cutl_cutrrrrirrrrZhmZkmZlmZdhZdkdlr%r%r&,ellipsoidal_resolutions_and_indices_by_sigmas<   , , 4 " z2array.ellipsoidal_resolutions_and_indices_by_sigmac Cs|dkrdS|jdd}ggg}}}xt||||D]\}}}}||} |ddkr|ddkr|||d| f|ddkr|ddkr|||d| f|ddkrP|ddkrP|||d| fqPWtdtdxtt t |t t |t |D]} d} yd || } Wnt k rP| } YnXyd || } Wn2t k rt | dkr| } n| } YnXyd || }Wnt k rd }YnXt| | |qWdS) NT)rKr>rrTz0a* b* c*zAd h F/sigma d k F/sigma d l F/sigmaz z%7.3f %4d %8.3fr?) rrTrr+rrrErArr\r]r strip)r4rrrrrrrriZdata_over_sigmarZblancrrrr%r%r&*show_mean_data_over_sigma_along_a_b_c_stars@  &   z0array.show_mean_data_over_sigma_along_a_b_c_starcCs|j|d\}}}|}t|d|d}t|d|d}t|d|d}|||gddkrv|St| d} | } | } xlt |D]\\} } | | }t|d|d|d|d|d|d}|dkrd| | <qW|j| dS)N)rr>rrTFT)r)rr7rrrrrr6r+r.rrrrryr;r)r4rrrrrZehmZekmelmrrrrrrrUr%r%r&ellipsoidal_truncation_by_sigmas" 6 z%array.ellipsoidal_truncation_by_sigmac Cs|}t|d}||k||k@}|}t|}||}|||||} d} | dk r| |} |j | | dS)z Randomly shuffle reflections within a given resolution range. Used for control refinements to validate the information content of a dataset. TN)rr) rrrr6r.rPrandom_permutationrrOrr) r4rr/rZall_iselZrange_selectionZ range_iselr<Zrange_isel_permutedrrr%r%r&permute_d_range!s    zarray.permute_d_rangecCsT|s dS|}||}|}|ddkr@| S||}| S)z Determine whether the array contains unmerged experimental observations or not. In some files only the centric reflections will appear to be unmerged, so we specifically check the acentrics (if present). FTr)rrrrrr)r4rZcentricsZacentric_flagsZ acentricsr%r%r&is_unmerged_intensity_array3s    z!array.is_unmerged_intensity_arrayc Cs|s t|s8|j|d}|d}t|||dS|dk sHtg}xX|D]H}||}| |} | dkr| dqZ| | j ||dqZWt ||ddS)a Calculate the correlation between two randomly assigned pools of unmerged data ("CC 1/2"). If desired the mean over multiple trials can be taken. See Karplus PA & Diederichs K (2012) Science 336:1030-3 for motivation. This method assumes that the reflections still have the original indices and maps them to the ASU first; the underlying compute_cc_one_half function skips this method. )r-rI)n_trials return_n_reflNrz%6.3f)r(rr)rr!rr)rTcompute_cc_one_halfr(rDrrr.rE cc_one_halfr) r4rrr-rrrrBr bin_arrayr%r%r&rDs"      zarray.cc_one_halfcCs>|s t|s|jt|dd}|jdd}|| dk}|dkr`d}nJt | }t | }|} dt|} | d| | d| }|r||fS|S|dk stg} xX|D]H} || } || }|dkr| dq| |j|d qWt|| d d S) u Calculation of CC1/2 by the 'sigma-tau' method, avoiding the random assignment into half-datasets of the above method. See Assmann et al., J. Appl. Cryst. (2016). 49, 1021–1028. var_y is the variange of the average intensities across the unique reflections of a resolution shell. var_e is the average variance of the observations contributing to the merged intensities r>)rT)rrrTg?N)rz%6.3f)r(rr)rr!rrrNr.r2r#r redundanciesrrrmean_and_varianceunweighted_sample_variancerr(rDrrEcc_one_half_sigma_taur)r4rrZintensities_copyZmerging_internalr5rZinternal_variancesZmavZvar_yZvar_errBrrr%r%r&ras6     zarray.cc_one_half_sigma_taucCsj|s t|jdd}|d}|st|||dd}t ||jdd}| sbtt ||j d}| }t ||jd} | } || st|r|| fS|r|j| dd|fS|j| ddS|d k st|j|d g} xV|D]F} || } || }|d krD| d n| |qWt|| d d S)z Calculate the correlation of the anomalous differences of two randomly assigned half-datasets (starting from unmerged data). T)r-rIF)unmerged_indices unmerged_dataunmerged_sigmasZweighted)r8r+r-)r6r)rrN)rrz%6.3f)r(rr)rr!rr)rTsplit_unmergedr+rrr:rr#data_1rdata_2r*rrr.r(r4rDrrrE"half_dataset_anomalous_correlationr)r4rZreturn_n_pairsZreturn_split_datasetsrsplit_datasetsZbase_setZarray1Zdano1Zarray2Zdano2rrBrrr%r%r&rsL        z(array.half_dataset_anomalous_correlationcOs |j||S)z> Alias for array.half_dataset_anomalous_correlation() )r)r4argsrr%r%r&cc_anomsz array.cc_anomcCs|s t|jdd}|s0|}|}|j |d}t t | }t t | }|dks|t||S)aICalculate R_anom, which measures the agreement between Friedel mates. Unlike CC_anom and various other R-factors (such as R_pim, which it is usually compared to), this requires merged data. .. math:: R_{anom} = \dfrac{\sum_{hkl}{|I_{hkl} - I_{-h,-k,-l}|}}{\sum_{hkl}{\left \langle I_{hkl} \right \rangle}} T)r-)rr)rr!rr)rr2r#rrkrBrrjrr)r4rrrrrr%r%r&r_anoms    z array.r_anomc Cs|dk rd|krdks"nt|dk s.t|}|rF|}|sRttj|ddd}|dkrzt dt |}| |}|j |d d \}}d || || }|d } |j|| d } |r| S| S)a  Apply a twin law to the data, returning an array of the same original type. :params twin_law: a valid twin law expressed as h,k,l operations :params alpha: predicted twin fraction (0 to 0.5) :returns: a new array with synthetically twinned data Ngg?i )r_dent_denr>z>The determinant of the provided twin law is not equal to unityF)rr@g?gY@)rr)r!r)rrYrr rt_mxrU determinantrr}rirDrrrrV) r4twin_lawalpharr new_arrayxaxbr new_sigmasZtwinnedr%r%r& twin_datas*"     zarray.twin_datacCs~|dk rd|krdks"nt|dk s.t|}|rF|}|sRttj|ddd}|dkrzt dt |}| |}|j |d d \}}| | kst|}|}|}|} d ||||dd |} d} tdd |d ||dd |} |dk rR| tt|d || d } |j| | dj|d} |rz| S| S)a Detwin data using a known twin fraction, returning an array with the same original data type. :params twin_law: a valid twin law expressed as h,k,l operations :params alpha: predicted twin fraction (0 to 0.5) :returns: a new array with detwinned data Ngg?ri )rrr>z>The determinant of the provided twin law is not equal to unityF)rr@g?g@rT)rr)r)r!r)rrYrr rrUrrr}rirDr.rrryr;rrrrBrV)r4rrrrrZi_old1Zi_old2Zs_old1Zs_old2rrZtmp_multZ detwinnedr%r%r& detwin_datas< "     * " zarray.detwin_datac Cs|dkrtj}|}td|d|dkr0|}n||dkrB|}nj|dkrT|}nX|dkrf|}nFyt|}Wn6t k r}zt d|t |fWdd}~XYnX| rtd |dtd ||dn td |dtd ||f|d|}td ||d|dkr^|dkr^td|dtd|dtd|d|r|j|d}t||} | } || } || } tdt| |dt| dkrtdt| |d| }|j|d} td|dtj j!| d|d| |fS)a- Encapsulates a variety of reindexing operations, including handling for a variety of corner cases. :param change_of_basis: Python str for change-of-basis operator :param eliminate_invalid_indices: remove reflections with non-integral indices :returns: new Miller array NzChange of basis:)r}to_reference_settingZto_primitive_settingZto_niggli_cellZto_inverse_handzAThe change-of-basis operator '%s' is invalid (original error: %s)z< Change of basis operator in both h,k,l and x,y,z notation:z z- Change of basis operator in x,y,z notation:z %s [Inverse: %s]z Determinant:rz@ **************************************************************z@ W A R N I N G: This change of basis operator changes the hand!)r<z" Mean value for kept reflections:z% Mean value for invalid reflections:)rz) Crystal symmetry after change of basis:z )rr)"r~rrAZ'change_of_basis_op_to_reference_settingZ'change_of_basis_op_to_primitive_settingrhZ"change_of_basis_op_to_inverse_handr r}rvrr^Zc_invr1is_zeroZas_hklZas_xyzrrrarUrZ%apply_results_in_non_integral_indicesr+rr6r.rrrr]rir r;r)r4change_of_basiseliminate_invalid_indicesrrBrrrirZtossrZ keep_arrayZ toss_arrayZprocessed_arrayr%r%r&apply_change_of_basis s\      "           zarray.apply_change_of_basisMbP?cCs|dkrtj}||gddks$t|}|} | } td|d| j|dd|}|} td|d| j|dd|dkrt |}| } | | kr|rtd|d| }n td | } |} d | krd krVnn^|rVt d }| |}|d | d krVtd|d||}|} | } | | s| }| |} td||dtdt||dtdt| |d|}| }t|||}||krtdd|dttj| |d}|j|d}|j dd|d\}}|rD|!sD|"#}|rf|$}|%}|j&|d}td|d|j|dd|S)a Encapsulates all operations required to convert the original data to a different symmetry (e.g. as suggested by Xtriage). This includes reindexing and adjusting the unit cell parameters if necessary, and expansion to P1 (for moving to lower symmetry) or merging equivalents. :param space_group_symbol: Python str for space group symbol (any format) :param space_group_info: Pre-defined sgtbx.space_group_info object :param volume_warning_threshold: Cutoff for relative change in unit cell volume beyond which a warning is issued. :param expand_to_p1_if_necessary: When moving to lower symmetry, expand the data to P1 first. :param remove_systematic_absences: eliminate reflections that are systematically absent in the new symmetry. :param merge_non_unique: merge reflections that are no longer symmetry- unique under the new symmetry. :param log: filehandle-like object :returns: Miller array in the new symmetry Nr>zCurrent symmetry:)r}z )rrzNiggli cell symmetry:z1Changing to lower symmetry, expanding to P1 firstzIThis operation will result in incomplete data without symmetry expansion!za,-b,-crzReindexing with a,-b,-cz5Coercing unit cell into parameters compatible with %sz Old cell: %sz New cell: %sz3This operation will change the unit cell volume by zmore than %.1f%%.r)r7r,)r8rT)rrr)rzNew Miller array:)'r~rrr!r8rrArZ niggli_cellr r,rjZn_smxrwarningswarnr7rr\Zis_reference_settingr}rirZis_compatible_unit_cellZaverage_unit_cellr^rr UserWarningr r;rrrr2r#rr9rF)r4rr,Zvolume_warning_thresholdZexpand_to_p1_if_necessaryr9Zmerge_non_uniquerrBsymmZspace_group_oldZspace_group_newr7r\rZ unit_cell_newZ unit_cell_oldZ volume_startZ volume_newZvolume_change_fractionZsymm_newZma_oldr/r%r%r&change_symmetry^sx       $           zarray.change_symmetrycCst|j||dS)a For each possible space group sharing the same basic intensity symmetry, show a list of possible systematically absent reflections and corresponding I/sigmaI. Note that if the data have already been processed in a specific space group rather than the basic point group, for example P212121 instead of P222, all systematically absent reflections are likely to have been removed already. :returns: a systematic_absences_info object )rr)systematic_absences_infor)r4rrr%r%r&%show_all_possible_systematic_absencess z+array.show_all_possible_systematic_absences@cCs:ddl}|jdstdddlm}|j||||dS)z Detect translational pseudosymmetry and twinning, using methods in Xtriage. Returns a mmtbx.scaling.twin_analyses.twin_law_interpretation object. (Requires mmtbx to be configured to be functional.) rNmmtbxz)mmtbx is required for this functionality.) twin_analyses)r4r/completeness_as_non_anomalousr)libtbx.load_envenv has_module ImportErrorZ mmtbx.scalingranalyze_intensity_statistics)r4r/rrrrr%r%r&rs  z"array.analyze_intensity_statisticscCs|j|dS)z Convenience method for identifying twinned data. 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Requires mmtbx. )r/)r has_twinning)r4r/r%r%r&rszarray.has_twinningcCsZ|r t|dtdks td}d}|s8t||d}x|D]}t||d}|r||\} } |j| | d}|j| | d} | |} nd} |dkr|| }n|j |d| d}|jt | t | d } |dkr| }q>|j | dd }q>W|d k}||d|j|d|d }||\}} |j||d}|S) Nry??)rr)r)r+rr>F)rro)r)rgư>)rrr!rrrDrr+r!rrrrNr.rrO)r4rrrZaverage_with_ccZ sum_arrayZ sum_n_arrayrZ offset_arrayZoffset_array_matchingZ self_matchingZ self_arrayweightZ count_arrayrZsum_array_matchingrr%r%r&average_neighborssF          zarray.average_neighbors)NN)Nr?)T)Nr?)rX)rXN)r@rAN)rGrH)rL)rOrH)rW)rO)rW)N)N)T)NT)F)FF)Tr>r>)rHNNrr)rHF)NF)N)T)rFN)NN)NN)F)FrHNNT)F)N)FFF)FrAN)rTrA)F)F)FN)FN)FN)F)F)rrNr?)NFFF)FN)FF)F)F)NN)N) NNNNNNTrF)FFFF)FF)FFF)FF)FF)FFF)r)F)rN)rN)r>)r>)r>)N)F)F)rNT)FNr?)F)FT)Nr?N)r)NNrr)r"NNNNTFT) r)NNNNNruTN)N)r)r"N)Nr7r7r"N) rr)NNNNruTN)r)NNNNruTN) r)NNNruTNFF)NFFN)NNNNF) NNNNNr r^r_N)NNNr r^r_N)Nrt)TNNN)N)N)NNF)NNN)rrF)NNN)rrrF)r )r )Fr>FF)FF)FFF)TN)NNrTTTN)rNN)r)r>FNN)rrrrr*rrr3rrrrrrrrrr.rrr!rr"r$rr%rr&rrrrrr:r'r)r,rRr"rr2r=r?rFr+rKrNrVrYr7rZr^r)rcrdrrnrrrurMrrrir~rr_rrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrjrrrrrrrrrrrrrrrrrzr]rrxr2r1rrkr*rrrrrr r r r rqrrrr r!r'r$r-r1r6rArGrJrNrTrUr]rkrhrsrvrzrr|rlr classmethodrrrrrrrrrrrrrrrrrrrrr~rrrrrr%r%r%r&r#.sx                  )         4 '  ?        0 ( $       " 2                        $     %:  <!>     .  # (   +-    /<Vr#c@seZdZdddZddZdS) rF{Gz?@Nc Cs||_d|_d|_|}|dks,|jdkr0dS|j}|dk rh|}|dk rh|j|||dshd|_|j}|dk r|dkr|} | dk r| }|dk r|} | |krd|_dS)NT)rZrelative_length_toleranceZabsolute_angle_toleranceF) rBunit_cell_is_compatiblespace_group_is_compatiblerrr7rHrbuild_derived_point_group) r4rBrCrDrErZucfrZsgfZsgZpoint_group_from_filer%r%r&r*s2  z?crystal_symmetry_is_compatible_with_symmetry_from_file.__init__cCs|j}g}d|t|fg}|js\|d|dt|jdt|g|js|d|dt|j dt| gt |dkrt |d krd g}d d |d|dfd g|SdS)Nz %s: %sz unit cellz Unit cell from file: z Working unit cell: z space groupz Space group from file: z Working space group: rrTzcrystal symmetryrz$Working %s is not compatible with %sz from reflection file:) rBr^rrrErprr7rr,r]rb)r4Zdata_descriptionmawhatmsgr%r%r&format_error_message7s,    zKcrystal_symmetry_is_compatible_with_symmetry_from_file.format_error_message)rrN)rrrr*rr%r%r%r&rFs rFc@s2eZdZdZd ddZddZddZd d ZdS) r|z! E-values and related statistics NcCs|s t|||}||}tt||d|d |_ t |}t t |d|_|dkd|_dS)N)r8r+)r6rr>rVT)rr!rrr#r:r8r+r%r_arrayrrrjr_sum_e_sq_minus_1r_n_e_greater_than_2)r4rBrrrrrr%r%r&r*Rs  znormalised_amplitudes.__init__cCs|jS)N)r)r4r%r%r&r#`sznormalised_amplitudes.arraycCs|j|jS)N)rrr.)r4r%r%r&mean_e_sq_minus_1csz'normalised_amplitudes.mean_e_sq_minus_1cCsd|j|jS)NgY@)rrr.)r4r%r%r&percent_e_sq_gt_2fsz'normalised_amplitudes.percent_e_sq_gt_2)N)rrrrr*r#rrr%r%r%r&r|Os  r|c@steZdZdZdddZddZd d Zd d Zd dZddZ ddZ ddZ ddZ ddZ ddZd ddZdS)!r2a Wrapper for merging redundant observations to obtain a symmetry-unique array. This also calculates some useful statistics resulting from the merging operation. Normally this would not be instantiated directly, but instead obtained by calling array.merge_equivalents(...). rNTc Cs|dks td|_d|_d}d|_|_|_|_d|_d|_| j j }t j t jt jt jd|d}|dk r:|}|jdd} yN|dkr||| | | |d} n||| | | } WnDtk r} z$dt| krtt| d Wdd} ~ XYnXd}~t| d r| j|_nt| tjrTt|} | jdd} |dk r|d krt j| | | | || |d } nH|d krt | | | | || } | j!|_ntd| j}n$t "| | | | } d}~ | j#|_| j$|_| j%|_| j&|_| j'|_| j(|_njt| tj)r|}|jdd} t *|| | | } ~n tdt+| t+|ft,t|| j|-d| j |d.||_/| j0|_1dS)z :param miller_array: a non-unique array of experimental data :param algorithm: merging method (options are "gaussian" or "shelx") )rr[N)r6rrr#rI)rS)r6r)rz%merge_equivalents_exact: incompatiblez! (mismatch between Friedel mates)n_incompatible_flagsr)rr[z*Programming error (should be unreachable).zOcctbx.miller.merge_equivalents: unsupported array type: data: %s sigmas: %s)r8r+r-)r6rr)2r! _r_linear _r_square_r_int_r_merge_r_meas_r_pim_inconsistent_equivalentsrrr rr)Zmerge_equivalents_exact_boolZmerge_equivalents_exact_intZmerge_equivalents_complexZmerge_equivalents_hlrPr)rMr+rrQr^rrrrrNr:rZmerge_equivalents_obsZmerge_equivalents_shelxinconsistent_equivalentsZmerge_equivalents_realr_linearr_squarer_intr_merger_measr_pimrZmerge_equivalents_stringreprr#r-r3rr _redundancies) r4rBrrrrZ data_type_strZ merge_typeZ asu_arrayr<Z merge_extrZasu_setr%r%r&r*qs                           zmerge_equivalents.__init__cCs|jS)z) Return the merged Miller array. )r)r4r%r%r&r#szmerge_equivalents.arraycCs|jj|jdS)zq Return an array representing the redundancy or multiplicity of each reflection in the merged array. )r)rr#r )r4r%r%r&rszmerge_equivalents.redundanciescCs|jdkrdS|jj|jdS)z7R-linear = sum(abs(data - mean(data))) / sum(abs(data))N)r)rrr#)r4r%r%r&rs zmerge_equivalents.r_linearcCs|jdkrdS|jj|jdS)z5R-square = sum((data - mean(data))**2) / sum(data**2)N)r)rrr#)r4r%r%r&rs zmerge_equivalents.r_squarecCs|jS)N)r)r4r%r%r&rszmerge_equivalents.r_intcCs|jS)z Standard (but flawed) metric of dataset internal consistency. .. math:: R_{merge} = \dfrac{\sum_{hkl}{\sum_{i}{|I_{i}(hkl) - \left \langle I_{i}(hkl) \right \rangle|}}}{\sum_{hkl}{\sum_{i}{I_{i}(hkl)}}} )r)r4r%r%r&rszmerge_equivalents.r_mergecCs|jS)ao Alternate metric of dataset internal consistency. Explained in detail in Diederichs K & Karplus PA (1997) Nature Structural Biology 4:269-275. .. math:: R_{meas} = \dfrac{\sum_{hkl}{ {\left \{ N(hkl) / [N(hkl) - 1] \right \} }^{1/2} \times \sum_{i}{|I_{i}(hkl) - \left \langle I_{i}(hkl) \right \rangle|}}}{\sum_{hkl}{\sum_{i}{I_{i}(hkl)}}} )r)r4r%r%r&rszmerge_equivalents.r_meascCs|jS)aX Alternate metric of dataset internal consistency or quality. Explained in detail in Weiss MS (2001) J Appl Cryst 34:130-135. .. math:: R_{meas} = \dfrac{\sum_{hkl}{ {\left \{ 1 / [N(hkl) - 1] \right \} }^{1/2} \times \sum_{i}{|I_{i}(hkl) - \left \langle I_{i}(hkl) \right \rangle|}}}{\sum_{hkl}{\sum_{i}{I_{i}(hkl)}}} )r)r4r%r%r&rszmerge_equivalents.r_pimcCs|jdkr|jSdS)Nr)r)r4r%r%r&rs z*merge_equivalents.inconsistent_equivalentscCs$t|t|S)N)rrjr#rr)r4r%r%r&r_sigma szmerge_equivalents.r_sigmarr?cCs|dkrtj}|}|j|d|jdd}|dk}|}|dk rr||}| ||jdd}| } | dk r| |} | || jdd} ddddg} |dkr| dn | d | dkr| dn | d | g} d d | d D} xN|j D]>}|j j|ddg} |j |}||}|d krd| ddgn(| dt|| dt||j|dkr| dn| d|j||dks|j|dkr| dn| d|j|| dks| j|dkr| dn| d| j|| | dd t| | D} qW|dk rrt||jj|d| dk rt||j j|d|dk s| dk rt|d|dtt| ddd}dt| d |g| dd}ddd|dddg} x2|| gD]&}|dkr0| dn | dqWt||t| |ddt| }x*| D]"} t||t| |dqnWdS)N)rT)rr>r?ZMinZMaxZMeanzR-linearzR-squarecSsg|] }t|qSr%)r])rofieldr%r%r&rq%sz2merge_equivalents.show_summary..rF)rBrxz%dz%.3fz%.4fcSsg|]\}}t|t|qSr%)r\r])roZmax_lenr r%r%r&rq<s)r}z/In these sums single measurements are excluded.rVz%%%ds %%%ds %%%ds %%%dsZ RedundancyrUrrTzMean z(%%%ds %%%ds %%%ds %%%ds %%%ds %%%ds)r~rrrRrrrrrr4rrEr(rDr|rr.rprrr\rrArrjrrtrstrip)r4rrrrZred_meanrrZr_l_meanrZr_s_meanfieldslinesZ max_lengthsrBrrUrgrr%r%r&rs~                        zmerge_equivalents.show_summary)rNT)rNr?)rrrrr*r#rrrrrrrrr rr%r%r%r&r2js ]   r2c@seZdZdZd"ddZddZd#dd Zd$d d Zd%d d ZddZ ddZ ddZ ddZ ddZ ddZd&ddZddddgfddZd'd d!ZdS)(r$aN Container for an FFT from reciprocal space (complex double) into real space. Normally this is obtained by calling array.fft_map(...), not instantiated directly outside this module. If the input array is anomalous, the resulting map will be a flex.complex_double (with grid accessor), otherwise it will be a flex.double. Nc Cs2tj|||dkst||s4t||ksHtt| t j s\t||_ |st |}|}nt |}|}tjj|||| |t |dd}|dk r|ddkstt||d<d|_|s|||_n|||_dS)N)FTT)rr-r<rrZmap_gridrryF)r rrr-r!r7rHrrrrrrrrr n_complexrrgrZto_mapr+rrcomplex_real_map_accessedbackward _real_map _complex_map)r4rr*r+rfftrZcfftrr%r%r&r*Xs4   zfft_map.__init__cCs|jS)N)r)r4r%r%r&r-vszfft_map.anomalous_flagTcCs:|s*|js|rt|r$d|_|jSt|jSdS)zn Extract the real component of the FFT'd map. :returns: a flex.double object with grid accessor. TN)r-rrr!rrrealr)r4 direct_accessr%r%r&real_mapys zfft_map.real_mapcCs0|j|d}ddlm}|||||dS)zQ Create a map_manager object from real_map_unpadded version of this map )in_placer) map_manager)r5unit_cell_crystal_symmetryZunit_cell_gridr#)r4Ziotbx.map_managerrr8rI)r4rr#r5rr%r%r&r's   zfft_map.as_map_managercCsT|r|jrt|jdd}|s&|S|r:tj|d|St|t| SdS)z Extract the real component of the FFT'd map, removing any padding required for the FFT grid. :returns: a flex.double object with grid accessor. F)r)rN) rr!rrr Zunpad_in_placerrrr)r4rr{r%r%r&r4s   zfft_map.real_map_unpaddedcCs|s t|jS)N)r-r!r)r4r%r%r&rs zfft_map.complex_mapcCst|jddS)NF)r)r r{r)r4r%r%r&r{szfft_map.statisticscCs*|s|j|9_n|j|9_|S)N)r-rr)r4rr%r%r&rszfft_map.apply_scalingcCs|jdt|dS)Nr>)r)rrrrr)r4r%r%r&apply_fourier_scalingszfft_map.apply_fourier_scalingcCs|jd|dS)z/ Volume-scale the map values in place. r>)r)rr7r)r4r%r%r&r&szfft_map.apply_volume_scalingcCs@|}|dkr|Sd|}|r4t|}|j|dS)z. Sigma-scale the map values in place. rr>)r)r{r.r-rr)r4r{rr%r%r&r%s  zfft_map.apply_sigma_scalingcCs|j||jdd|dS)NF)r)rrverify_symmetry)Ztags peak_searchr)r4rrr%r%r&rs zfft_map.peak_searchz,Values outside boundaries are wrapped insidezfft_map from Phenixc Csddlm}|jdd}|dkr$d}|dkrRt|}|dkrRtdd|D}t|d ksbt|j||| |||t |d dS) zD Write the real component of the map to a CCP4-format file. r)mrcfileF)rN)rrrcSsg|] }|dqS)r>r%)rorgr%r%r&rqsz'fft_map.as_ccp4_map..r)rr7rgridding_first gridding_lastr5r) rmr rrtrr]r!Zwrite_ccp4_mapr7rrr)r4rr!r"rr r5r%r%r& as_ccp4_maps   zfft_map.as_ccp4_mapcCsnddlm}|jdd}|dkr$d}|dkrRt|}|dkrRtdd|D}|j|||||d dS) zD Write the real component of the map to a DSN6-format file. r)dsn6F)rN)rrrcSsg|] }|dqS)r>r%)rorgr%r%r&rqsz'fft_map.as_dsn6_map..)rr7r!r"r5)rmr$rrtrZwrite_dsn6_mapr7)r4rr!r"r$r5r%r%r& as_dsn6_maps   zfft_map.as_dsn6_map)N)T)TT)T)NT)NN)rrrrr*r-rr'r4rr{rrr&r%rr#r%r%r%r%r&r$Ps&    r$cCsPt|}d|tj|}dt||t|t|d}|S)NrVr ) rr;rrryrzr/r0r)rLrBrkrrDr%r%r&rCs(rCcCs|s t|r$|jdd|}|}|rD|jdd|}t||t | dd}|dk rx||}t |||S)NT)rr>)r) Zis_patterson_symmetryr!rrrYrr#rrrr.r$)rrKr+rLrMZi_pattr%r%r&rNs   "rNc Cs|dk r|dkst|dk r(|dks(t|dkr8|}dd|D}t|||d}|dk rh|j|d}|st|dk r|} | d|j| d}|dkr|S|j|d|dd SdS) NcSsg|]}|ddqS)r>rTr%)rorr%r%r&rqsz1structure_factor_box_from_map..)r8r-r-)r/)rrr)r+TF)rrr-r)r!rrHr=r+rErr) r8rrr-Z include_000r+r/r-rLr+r%r%r&structure_factor_box_from_maps0      r&c Csg}||dk}xvt|D]j}d}|dkr@ttd}d}}t||||d}|j}|j }t || } | | q Wt||} |r| |fS| S)z Implementation of array.cc_one_half, assuming that the reflections are already in the ASU. Because the implementation uses random numbers, the function has the option to calculate the mean over multiple trials. rr>i'N)rrrseed)rrrrrrr+rrrrr rrErjr.) ZunmergedrrZcc_allrer'rrrccrr%r%r&r2s(  rc@s*eZdZdZdddZejdfddZdS) ra Container for information about possible systematically absent reflections in the array, trying both the current space group and all intensity-equivalent groups (i.e. all possible screw axis combinations). This object would normally be instantiated directly from a Miller array, but is self-contained to enable saving as part of Xtriage results. :param obs: X-ray intensity (preferred) or amplitude array Nc Cs||_d|_|dk st|d}|r<|}d|_|sHt|s\| }| rl| }| |_ |j dk st|j }|j }|j|d}g|_d|_d|_x|D]}||}||}t|} | |jkr | |_t|dkrRt||jkr2t||_||} |j|| fqt|dkrv|j|dfq|j|dfqWdS)NFrIT)r,r) was_filteredinput_amplitudesrr!rTrrYrrr2r#r-rkr,Z&reflection_intensity_equivalent_groupsrjrrrrL"space_group_symbols_and_selectionsn_possible_maxZ n_found_maxrr+rPr]rrE) r4rr)Z all_groupsZ point_groupZ complete_selrjZ absent_selZ all_possibleZ n_possibleabsencesr%r%r&r*YsF         z!systematic_absences_info.__init__r?c Cs0|jdkrtd|d|S|jr,td|dx|jD]\}}d}t|t|jkrVd}|dkrxt|d||f|dq4|d krt|d ||f|dq4t|d ||f|dxtt|D]d\}}||}| |} d |} | dkrt|d | |dqt|d| || f|dqWq4W|S)z For each possible space group, show a list of possible systematically absent reflections and corresponding I/sigmaI. rzCNo systematic absences possible in any intensity-equivalent groups.)r}aPlease note that the input data were amplitudes, which means that weaker reflections may have been modified by French-Wilson treatment or discarded altogether, and the original intensities will not be recovered. For best results, use intensities as input. r?z (input space group)Fz%%s%s: no systematic absences possibleNz%s%s: no absences foundz%s%s:z(%4d, %4d, %4d)z %s: i/sigi = undefinedz %s: i/sigi = %6.1f) r,rAr*r+r^r,rr+rr) r4rrZ group_infor-Z group_noteZi_hklrrr.Z indices_fmtr%r%r&rs4      zsystematic_absences_info.show)N)rrrrr*r~rrr%r%r%r&rOs  'r)r>F)N)NNN)NN)NFF)NNFFNN)r>F)S __future__rrrZ cctbx.sgtbxrboost_adaptbx.boost.pythonboostpythonbp six.movesrr import_extr)rrr r r r r rcctbx.array_familyrrhrrrlibtbx.math_utilsrrrZscitbx.python_utils.miscrrlibtbx.str_utilsr libtbx.utilsrrrrrZlibtbx.table_utils itertoolsrrrrytimer~ collectionsrr!floating_point_epsilon_double_getr.Zgenerate_r_free_params_strr'r(robjectrrrrr;r:rHrrr r#rFr|r2rr$rCrNr&rrr%r%r%r&s                      z,  / !^7g.