ihm_validation package

Submodules

ihm_validation.cx module

Crosslinking-MS validation for PDB-IHM

class ihm_validation.cx.CxValidation(mmcif_file, cache)[source]

Bases: GetInputInformation

ID = None

assign_ertypes()[source]

assign_rtdtypes()[source]

check_conditional_flag(data: DataFrame) → None[source]: Check consistency of conditional flags in a restraint group

driver = None

static format_pct_count(pct, count)[source]

get_best_distance_per_restraint(data)[source]

get_best_distances_per_model_group()[source]

get_cx_data() -> (<class 'pandas.core.frame.DataFrame'>, <class 'pandas.core.frame.DataFrame'>)[source]: Extract crosslinking-MS data from mmcif file

get_ertype(row)[source]

get_ertypes()[source]

get_ertypes_df()[source]

get_ertypes_df_html()[source]

get_measured_restraints()[source]

get_models()[source]

get_number_of_restraint_groups() → int[source]

get_number_of_restraints() → int[source]

get_per_model_satifaction_rates() → list[source]

get_pride_data(code)[source]: get data from PRIDE

get_pride_ids() → list[source]: get a list of all PRIDE ids from entry

static get_pyhmmer_version()[source]: return pyhmmer version

get_raw_restraints()[source]: Get all restraints

get_residue_pairs_pride(pid: str, page_size: int = 99) → dict[source]: get sequences from PRIDE entry

get_restraint_group_chain_type(data)[source]

get_restraint_group_entity_type(data)[source]

get_rtdtype(row)[source]

get_rtdtypes()[source]

get_sequences_pride(pid: str) → dict[source]: get sequences from PRIDE entry

get_stats_per_model_group()[source]

is_restraint_group_satisfied(data)[source]

measure_restraint(model, row)[source]

plot_distograms_per_model_group(imgDirname='.')[source]: plot all restraints in the dataset

plot_satisfaction_per_ensemble(imgDirname='.')[source]

process_restraint_groups(data, mode='entity')[source]

static pyhmmer_alignment_to_map(hit) -> (<class 'dict'>, <class 'list'>)[source]: Convert HMMER alignment into residue map

quality_check(data: DataFrame) → None[source]: Check consistency of crosslink restraints

static request_pride(url: str) → dict[source]: pull data from PRIDE using crosslinking PDB-IHM API

save_plots(plot, title, imgDirname='.')[source]

select_atom_by_asym_id_seq_id_atom_id(asym_id, seq_id, atom_id)[source]

validate_all_pride_data() → list[source]: perform data quality validation for all crosslinking-MS datasets

validate_pride_data(data: dict) → tuple[source]: Match sequences, residues pairs and return stats

ihm_validation.em module

3DEM validation for PDB-IHM

class ihm_validation.em.EMValidation(mmcif_file, cache)[source]

Bases: GetInputInformation

ID = None

VA_TIMEOUT = 900

driver = None

static get_chimera_version() → str[source]: return chimera version

static get_chimerax_version() → str[source]: return chimera version

static get_em_reconstruction_method(map_metadata)[source]: Get EM reconsruction method from the conrolled vocabulary

get_emdb_data(code)[source]: get data from EMDB

get_emdb_ids() → list[source]: get a list of all EMDB ids from entry

get_emdb_map(code, fname) → str[source]: download validation data from EMDB

get_emdb_map_images(code, map_validation) → dict[source]

get_emdb_map_metadata(code) → dict[source]: download validation data from EMDB

get_emdb_map_validation(code) → dict[source]: download validation data from EMDB

static get_emdb_numerical_code(code) → str[source]: Extract only numerical part of the EMDB ID

static get_level_from_primary_contour(data: dict) → float[source]: Get recommended level for the map

get_map_image(code, name, rawmap=False, extension='jpeg')[source]

static get_mapq_version() → str[source]: return mapq version

static get_resolution_estimates(map_data, val_data)[source]

static get_va_version() → str[source]: return va version

static request_emdb(url: str) → dict[source]: pull data from EMDB

run_va(data, mid, outpath)[source]: Run EMDB va validation pipeline for map and model

save_plots(plot, title, imageDirName='.')[source]: Save bokeh plots as svg images and json blobs

validate_all_emdb_data(imageDirName='.') → list[source]: perform data quality validation for all crosslinking-MS datasets

validate_emdb_data(data: dict, imageDirName='.') → tuple[source]: Match sequences, residues pairs and return stats

ihm_validation.excludedvolume module

Excluded volume assessment for PDB-IHM

class ihm_validation.excludedvolume.GetExcludedVolume(mmcif_file: str, cache: str = '.', nocache: bool = False)[source]

Bases: GetInputInformation

get_all_spheres(fname: str | None = None) → dict[source]: Get spheres and atoms for each model

get_excluded_volume()[source]

get_nCr(n: int, r: int) → int[source]: get all combinations

static get_radii(atoms: list) → dict[source]: Get VdW radii for all atom types

get_violation_dict(model_spheres_df: DataFrame) → dict[source]: get violation from model_sphere df

get_violation_percentage(viols: dict, n: int) → float[source]: get information on all spheres for each model

get_xyzr(spheres: list) → DataFrame[source]: get X,Y, Z coords from sphere objects

ihm_validation.format_checker module

Check residue and atom names in IHMCIF file

ihm_validation.format_checker.check_all_exception(system: System)[source]: Perform all checks. Throw an exception if a check fails.

ihm_validation.format_checker.check_all_log(system: System) → int[source]: Perform all checks. Throw a message in the log if a check fails and return a non-zero exit code

ihm_validation.format_checker.check_entities_histidines(system: System, histidines=frozenset({'HID', 'HIE', 'HIP'}))[source]: Find any non-standard histidine chemical components

ihm_validation.format_checker.check_file_exception(fname: str)[source]: Parse a file, do all checks, throw an exception if a check fails.

ihm_validation.format_checker.check_file_log(fname: str) → int[source]: Parse a file, do all checks, throw a log message if a check fails and return a non-zero exit code

ihm_validation.format_checker.check_models(system: System)[source]: Find any non-standard histidine chemical components

ihm_validation.format_checker.parse_ihm_cif(fname, encoding='utf8') → tuple[source]

ihm_validation.futures module

This is a beta-version of a new validation framework

class ihm_validation.futures.CXMSValidator[source]

Bases: Validator

property ertypes: Get all extendend restraint types

property ertypes_df

load_restraint(restraint: CrossLinkRestraint) → None[source]: Extract crosslinking-MS data from mmcif file

property number_of_restraint_groups: int

property number_of_restraints: int

property rtdtypes: Get all crosslink types

validate_ensemble(models: list) → dict[source]: Validate the ensemble against the data

validate_model(model: Model) → dict[source]: Validate the model against the data

class ihm_validation.futures.StereoChemistryValidator[source]

Bases: Validator

validate_model(model: Model) → dict[source]: Validate the model against the data

class ihm_validation.futures.Validator[source]

Bases: object

Base validator class

dataset = None

load_restraint(restraint: Restraint)[source]: Parse the restraint data

restraint = None

validate_ensemble(ensemble) → dict[source]: Validate the ensemble against the data

validate_model(model: Model) → dict[source]: Validate the model against the data

ihm_validation.futures.get_hierarchy_from_atoms(atoms)[source]

ihm_validation.futures.get_hierarchy_from_model(model)[source]

ihm_validation.futures.is_model_atomic(model: Model) → bool[source]: Check if model is atomic

ihm_validation.futures.is_model_cg(model: Model) → bool[source]: Check if model is atomic

ihm_validation.futures.is_model_mixed(model: Model) → bool[source]: Check if model is atomic

ihm_validation.generate_static_html_pages module

A script for generation of validation_help.html and about_validation.html

ihm_validation.generate_static_html_pages.createdirs(dirNames: dict)[source]

ihm_validation.generate_static_html_pages.write_html(template_dict: dict, template_list: list, dirName: str, overwrite=False)[source]: Generate HTML pages from templates

ihm_validation.get_plots module

Generate overview plots

class ihm_validation.get_plots.Plots(mmcif, imageDirName, driver)[source]

Bases: GetInputInformation

plot_quality_at_glance(molprobity_data: dict | None = None, exv_data: dict | None = None, sas_data_quality: dict | None = None, sas_fit: dict | None = None, cx_data_quality: dict | None = None, cx_fit: dict | None = None, em_data_quality: dict | None = None, em_fit: dict | None = None) → dict[source]

save_plots(p, plot_name: str) → dict[source]: Save html and svg plots

ihm_validation.ihm_validator module

Main running script

ihm_validation.ihm_validator.createdirs(dirNames: dict)[source]

ihm_validation.ihm_validator.load_json_plot(fname)[source]

ihm_validation.ihm_validator.write_html(prefix: str, template_dict: dict, template_list: list, dirName: str)[source]

ihm_validation.ihm_validator.write_json(mmcif_file: str, template_dict: dict, dirName: str, dirName_Outputs: str)[source]

ihm_validation.ihm_validator.write_pdf(prefix: str, template_dict: dict, template_file: str, dirName: str, dirName_Output: str)[source]

ihm_validation.ihm_validator.write_supplementary_table(prefix: str, template_dict: dict, template_file: str, dirName: str, dirName_supp: str)[source]

ihm_validation.images module

BASE64 encoded images for the report

ihm_validation.mmcif_io module

Read/write IHMCIF file

class ihm_validation.mmcif_io.GetInputInformation(mmcif_file, cache='.', nocache=False)[source]

Bases: object

property atomic

property cg

check_ensembles() → int[source]: check if ensembles exist

check_for_em(dataset: dict) → bool[source]: check if em is in the dataset

check_sphere() → int[source]: check resolution of structure, returns 0 if its atomic and 1 if the model is multires

dataset_id_type_dic() → dict[source]: dataset id and data items

delete_extra_loops(some_text=[]) → list[source]: function to help re-write mmcif file for molprobity this cleans up extra loops in the cif file

property deposition_date: Return initial deposition date

get_RB_flex_dict() -> (<class 'dict'>, <class 'dict'>, <class 'int'>, <class 'int'>)[source]: get RB and flexible segments from model information

get_all_asym() → list[source]: get all asym units

get_assembly_ID_of_models() → list[source]: Assembly info i.e. model assemblies in the file

get_atomic_coverage() → str[source]: Measure amount of atomic residues

get_authors() → str[source]: get authors of the structure; fallback to authors of primary citation

get_chain_subunit_dict() → dict[source]: Get chains of subunits

get_composition() → dict[source]: Get composition dictionary

get_databases()[source]: get all datasets from the mmcif file

get_dataset_comp() → dict[source]: detailed dataset composition

get_dataset_details() → dict[source]: get information on dataset and databases

get_dataset_dict()[source]: get dataset dictionary

get_dataset_length() → int[source]

get_dataset_xl_info(id: int) → str[source]: Get dataset XL info given dataset ID

get_empty_chain_dict() → dict[source]

get_ensembles()[source]: details on ensembles, if it exists

get_file_id()[source]: Return _entry.id; Requires compliant CIF file

get_id()[source]: Return _entry.id; Requires compliant CIF file

get_model_assem_dict() → dict[source]: Map models to assemblies

get_model_id_column(atom_site: {}) → int[source]

get_model_names() → list[source]: Names of models

get_model_rep_dict() → dict[source]: Map models to representations useful especially for multi-state systems

get_number_of_assemblies() → int[source]

get_number_of_chains() → int[source]: get number of chains per protein per assembly

get_number_of_entities() → int[source]

get_number_of_models() → int[source]: Get total number of models

get_pdb_dev_id() → str[source]: Check database2 table for PDB ID

get_pdb_id() → str[source]: Check database2 table for PDB ID

get_primary_citation_info() → tuple[source]: get title and authors for the primary citation

get_protocol_number() → int[source]: number of protocols/methods used to create model

get_ranked_id_list() → list[source]: Get sorted list of multiple ids

get_representation()[source]: get details on number of model composition based on types of representation listed

get_representation_ID_of_models() → list[source]: Number of representations in model

get_representation_details() → dict[source]: Extract details about representation (atomic/coarse-grained)

get_representation_info()[source]

get_representation_scale(rep, chid=None) → dict[source]: Extract details about representation (atomic/coarse-grained)

get_residues(asym)[source]: Get residues per chain

get_residues_subunit_dict() → dict[source]: Get residues of chains in subunits

get_restraints() → dict[source]: get restraints table from cif file

get_sampling() → dict[source]: sampling composition/details

get_software_comp() → dict[source]: get software composition to write out as a table

get_software_length() → int[source]

get_struc_title() → str[source]: get name of molecule

property has_crosslinking_ms_dataset

property has_em_dataset

property has_sas_dataset

mmcif_get_lists(filetemp=None) -> (<class 'list'>, <class 'dict'>, <class 'dict'>, <class 'list'>)[source]: function to help re-write mmcif file for molprobity this function reads the atom_site dictionary terms and returns a list

nocache = False

property num_models

pretty_print_scale(reprs_: dict) → list[source]: Pretty print information about representation scales

read_all_references() → None[source]

remove_flr(some_text=[]) → list[source]: function to help re-write mmcif file for molprobity this deletes all flr related text/key-value pairs

property sequences: dict: Return dictionary with sequences of polymeric entities from mmcif entry

class ihm_validation.mmcif_io.IHMVAvailableModes(value)[source]

Bases: Enum

An enumeration.

DEVELOPMENT = 1

PRODUCTION = 0

ihm_validation.mmcif_io.get_operational_mode() → IHMVAvailableModes[source]: Check environment variables and set the operational mode

ihm_validation.molprobity module

Perform MolProbit assessment

class ihm_validation.molprobity.AtomSiteVariant(model_id: int | None = None)[source]

Bases: Variant

Used to select typical PDBx/IHM file output. See write().

get_dumpers()[source]

Get the Dumper objects to use to write output.

Returns:: a list of Dumper objects.

class ihm_validation.molprobity.GetMolprobityInformation(mmcif_file, cache='.', nocache=False)[source]

Bases: GetInputInformation

convert = PosixPath('/home/docs/checkouts/readthedocs.org/user_builds/ihmvalidation/checkouts/v3.0/ihm_validation/molprobity_convert.py')

data = {}

get_internal_version(tool: str = 'molprobity.clashscore') → str[source]: Get internal molprobity version. We assume that all tools belong to the same release.

get_mp_data()[source]

get_mq_plot_data()[source]

get_summary_table_stats()[source]

property models: list

property molprobity_version: str: Get MolProbity version. We assume that all tools belong to the same release.

run_molprobity(fname) → dict | None[source]: Run MolProbity

summarize_angles()[source]

summarize_bonds()[source]

summarize_clashes()[source]

summarize_clashscores()[source]

summarize_mp_data()[source]

summarize_rama_rota(mode: Literal['rama', 'rota'])[source]

summarize_rama_rota_stats(mode: Literal['rama', 'rota'])[source]

verify_molprobity_installation()[source]: Stub for a validation function

class ihm_validation.molprobity.MyModelDumper(model_id: int | None = None)[source]

Bases: _ModelDumper

dump(system, writer)[source]

Use writer to write information about system to mmCIF or BinaryCIF.

Parameters:

system (ihm.System) – The ihm.System object containing all information about the system.
writer (ihm.format.CifWriter or ihm.format_bcif.BinaryCifWriter.) – Utility class to write data to the output file.

dump_atoms(system, writer, add_ihm=True)[source]

model_id = None

ihm_validation.molprobity_convert module

Convert MolProbity output from json to a pickled object

ihm_validation.molprobity_convert.get_atom_tuple(atom)[source]

ihm_validation.molprobity_convert.rota_rama_result_to_tuple(r)[source]

ihm_validation.precision module

Run local precision assessment (PrISM)

class ihm_validation.precision.PRISM(mmcif_file, cache='.', nocache=False, timeout=120)[source]

Bases: GetInputInformation

data = {}

get_data()[source]

get_plots(imgDirname='.')[source]: Render PrISM images with PyMOL

property prism_version: This is a stub. Using hardoced commit id for now.

property pymol_version

timeout = 120

ihm_validation.report module

Generation of PDF and HTML reports

class ihm_validation.report.WriteReport(mmcif_file, db, cache, nocache=False, enable_sas=False, enable_cx=False, enable_em=False, enable_prism=False)[source]

Bases: object

clean() → None[source]: cleanup

create_webdriver() → WebDriver[source]: instantiate webdriver for rendering plots

run_cx_validation(Template_Dict: dict) → dict[source]: get cx validation information from mmcif files NOTE: this function is incomplete it currently evaluates satisfaction from mmcif files and not the enetire ensemble

run_cx_validation_plots(Template_Dict: dict, imageDirName: str) → None[source]: create validation plots for cx datasets NOTE: this function is incomplete, the plots are also ugly and need to be refined

run_em_validation(Template_Dict: dict, imageDirName: str) → dict[source]: 3DEM validation

run_entry_composition(Template_Dict: dict) → dict[source]: get entry composition, relies on IHM library

run_model_quality(Template_Dict: dict, csvDirName: str, htmlDirName: str) -> (<class 'dict'>, <class 'dict'>, <class 'dict'>, <class 'dict'>, <class 'dict'>)[source]: get excluded volume for multiscale models get MolProbity info for atomic models exception: models with DNA–we need a way to assess models with DNA

run_prism(Template_Dict: dict, imageDirName: str) → dict[source]

run_quality_glance(molprobity_dict: dict, exv_data: dict, sas_data_quality: dict, sas_fit: dict, cx_data_quality: dict, cx_fit: dict, em_data_quality: dict, em_fit: dict, imageDirName: str) → dict[source]: get quality at glance image; will be updated as validation report is updated

run_sas_validation(Template_Dict: dict) -> (<class 'dict'>, <class 'dict'>, <class 'dict'>)[source]: get sas validation information from SASCIF or JSON files

run_sas_validation_plots(Template_Dict: dict, imageDirName: str)[source]: get sas validation information from SASCIF or JSON files

run_supplementary_table(Template_Dict, location='N/A', physics=['Information about physical principles was not provided'], method_details='N/A', sampling_validation=None, validation_input=['-'], cross_validation='N/A', Data_quality=['-'], clustering=None, resolution='N/A')[source]: get supplementary table, will be updated as validation report is updated

ihm_validation.sas module

SAS assessment for PDB-IHM

class ihm_validation.sas.SasValidation(mmcif_file, db='.')[source]

Bases: GetInputInformation

check_sascif_dicts()[source]

findMinDiff(listn: list, num: int) → int[source]: quick min diff operation for calculating errors

get_Guinier_data() -> (<class 'dict'>, <class 'dict'>)[source]: get Guinier plot data from JSON files

get_atsas_version(tool: str = 'datcmp') → str[source]: Get ATSAS version

get_fit_data() → dict[source]: get fit information to make plots

get_fit_r2(df: DataFrame) → int[source]

get_fits_for_plot() → dict[source]: get chi-squared values from SASCIF files

get_intensities() → dict[source]: get intensity data from SASCIF file

get_number_of_fits() → dict[source]: get number of fits

get_parameters_mw_many() → dict[source]: get MW details from SASCIF files

get_parameters_vol_many() → dict[source]: get volume details from SASCIF files

get_pddf() → dict[source]: get p(r) data from JSON

get_pddf_info() → dict[source]: get p(r) related info from JSON

get_pofr() → dict[source]: get pair-dist distribution from SASCIF files

get_pofr_errors() → dict[source]: get pair-distance details and errors from JSON files

get_pofr_ext() → dict[source]: get pair-distance details from SASCIF files

get_pvals() → dict[source]: get p-values from ATSAS

get_rg_and_io() → dict[source]: get rg information from SASCIF file

get_rg_for_plot() → dict[source]: get Rg values from SASCIF file, if unavailabel, get it from JSON

get_rg_table_many() → dict[source]: get rg information from multiple SASCIF files

get_sas_ids() → list[source]: function to get all SASBDB codes used in the model, returns a list of SASBDB codes

get_sasbdb_ids() → list[source]: function to get all SASBDB codes used in the model, returns a list of SASBDB codes

get_sascif_dicts()[source]

get_sascif_file(code, output_dir='.')[source]: get data from SASCIF files

get_sasdb_code_fits() → list[source]: get asumber of fits per SASBDB ID

static get_scan_unit_mult(unit) → int[source]

get_total_number_of_fits() → int[source]

modify_intensity() → dict[source]: modify intensity data to calcualte errors and log values

ihm_validation.sas_plots module

Generate plots for SAS assessment

class ihm_validation.sas_plots.SasValidationPlots(mmcif_file, imageDirName, driver, db='.')[source]

Bases: SasValidation

Guinier_plot_fit_rwt(sasbdb: str, df: DataFrame, score: float)[source]: Gunier plot with fit

plot_Guinier()[source]

plot_fit_rwt(sasbdb: str, fit: int, score: float, df: DataFrame)[source]: plot chi-squared fit

plot_fits()[source]

plot_intensities(sasbdb: str, df: DataFrame)[source]: plot intensities with errors

plot_intensities_log(sasbdb: str, df: DataFrame)[source]: plot intensities on a log scale with errors

plot_kratky(sasbdb: str, df: DataFrame)[source]: plot dimensionless kratky

plot_multiple()[source]

plot_pddf(sasbdb: str, df: DataFrame, Rg=None, Dmax=None)[source]: p(r) plot, deprecated function

plot_pddf_int_rwt(sasbdb: str, df_int: DataFrame, df_pofr: DataFrame, df_error: DataFrame)[source]: p(r) with fit

plot_pf()[source]

plot_porod_debye(sasbdb: str, df: DataFrame)[source]: Porod-Debye plot for flexibility

save_plots(p, plot_name: str) → dict[source]: Save html and svg plots

static set_plot_style(p)[source]

ihm_validation.utility module

Various helper functions

ihm_validation.utility.all_same(items: list)[source]: minor func

ihm_validation.utility.calc_optimal_range(counts: list) → tuple[source]

heuristics to find optimal range for plots

>>> calc_optimal_range((10, 1567))
(9.0, 1568.5669999999998)

ihm_validation.utility.cat_list_string(listn: list) → str[source]: minor func

ihm_validation.utility.check_for_dataset_type(dataset_list: list | None = None, dataset_type=None) → bool[source]: check if the specific dataset type is present in the dataset list

ihm_validation.utility.clean_all(report=None)[source]: delete all generated files

ihm_validation.utility.compress_cx_stats(cx_stats: dict) → list[source]: Extract per-model satisfactions stats as a flat list

ihm_validation.utility.dict_to_JSlist(d: dict) → list[source]: convert dictionary to list of lists

ihm_validation.utility.dict_to_JSlist_rows(dict1: dict, dict2: dict) → list[source]: format rigid and flexible segments

ihm_validation.utility.encode_img(buffer)[source]

ihm_validation.utility.format_RB_text(tex: list) → str[source]: convert RB information to text for supp table

ihm_validation.utility.format_flex_text(tex: list) → str[source]: convert flex information to text for supp table

ihm_validation.utility.format_list_text(sublist: list) → str[source]: minor func

ihm_validation.utility.format_range(data, format='.2f')[source]

ihm_validation.utility.format_tuple(tex: list) → str[source]

ihm_validation.utility.format_wwpdb_id(pdbid: str) → str[source]: Format all pdb ids to extended format

ihm_validation.utility.format_wwpdb_url(pdbid: str) → str[source]: Generate a url to the wwPDB entry page

ihm_validation.utility.get_RB(data_list: list) → list[source]: format RB for supplementary/summary table

ihm_validation.utility.get_all_files(path_dir)[source]: minor func

ihm_validation.utility.get_alphafolddb_link(acc: str) → str | None[source]: Format link for AlphaFold DB

ihm_validation.utility.get_bead_size(sphere: Sphere) → int[source]: Number of residues per bead

ihm_validation.utility.get_copy(name)[source]: minor func

ihm_validation.utility.get_cx_data_fits(cx_dict: dict) → list[source]: format crosslinking-MS data for supplementary/summary table

ihm_validation.utility.get_datasets(data_dict: dict) → list[source]: format datasets for supplementary/summary table

ihm_validation.utility.get_datasets_summary(system: System) → list[source]: Get counts for all data types used for modeling

ihm_validation.utility.get_flex(data_list: list) → list[source]: format flexible regions for supplementary/summary table

ihm_validation.utility.get_hierarchy_from_atoms(atoms) → dict[source]: Construct polymer hierarchy from a list of atoms

ihm_validation.utility.get_hierarchy_from_model(model) → dict[source]: Construct polymer hierarchy from atoms and beads in the model

ihm_validation.utility.get_key_from_val(dict1: dict, val1: str) → list[source]: minor func

ihm_validation.utility.get_larget_assembly_model(system: System) → tuple[source]: Find model ID corresponding to the largest assembly

ihm_validation.utility.get_method_name(sample_dict: dict) → str[source]: format method name for supplementary/summary table

ihm_validation.utility.get_method_type(sample_dict: dict) → str[source]: format method type for supplementary/summary table

ihm_validation.utility.get_name(name) → str[source]: minor func

ihm_validation.utility.get_output_file_html(prefix: str) → str[source]: minor func

ihm_validation.utility.get_output_file_json(prefix: str) → str[source]: minor func

ihm_validation.utility.get_output_file_pdf(prefix: str) → str[source]: minor func

ihm_validation.utility.get_output_file_temp_html(prefix: str) → str[source]: minor func

ihm_validation.utility.get_python_ihm_version() → str[source]: returns Python-IHM version

ihm_validation.utility.get_restraints_info(restraints: dict) → list[source]: format restraints info for supplementary/summary table

ihm_validation.utility.get_rg_data(rg_dict: dict) → list[source]: format rg data for supplementary/summary table

ihm_validation.utility.get_rg_data_fits(rg_dict: dict) → list[source]: format sas model fits for supplementary/summary table

ihm_validation.utility.get_software(data_dict: dict) → list[source]: format software for supplementary/summary table

ihm_validation.utility.get_subunits(sub_dict: dict) → list[source]: format chains for supplementary/summary table

ihm_validation.utility.get_supp_file_html(prefix: str) → str[source]: minor func

ihm_validation.utility.get_supp_file_pdf(prefix: str) → str[source]: minor func

ihm_validation.utility.get_unique_datasets(name: dict) → list[source]: get all datatypes that are yet to be validated the ones that can’t or the ones that have already been validated are in the sub_data set

ihm_validation.utility.get_val_from_key(dict1: dict, key1: str) → list[source]: minor func

ihm_validation.utility.is_atomic(data: System | Model)[source]

ihm_validation.utility.is_cg(data: System | Model)[source]

ihm_validation.utility.islistempty(inlist: list) → bool[source]: minor func

ihm_validation.utility.load_img(path)[source]

ihm_validation.utility.mp_readable_format(mp: dict) → list[source]: Format MolProbity results for supplementary/summary table

ihm_validation.utility.order_of_magnitude(value: float) → float[source]

calculate the order of magnitude for a given number

>>> order_of_magnitude(135)
2.0

ihm_validation.utility.parse_ihm_cif(fname, encoding='utf8') → tuple[source]

ihm_validation.utility.pretty_print_representations(reprs: dict) → list[source]: Pretty print information about representation scales

ihm_validation.utility.ranges(i)[source]

ihm_validation.utility.runInParallel(*fns)[source]: minor func

ihm_validation.utility.runInParallel_noargs(*fns)[source]: minor func

ihm_validation.utility.summarize_entities(rep_info: dict) → list[source]

ihm_validation.utility.summarize_segments(rep_info: dict) → list[source]

class ihm_validation.utility.timeout(seconds=1, error_message='Timeout')[source]

Bases: object

handle_timeout(signum, frame)[source]

Module contents

__init__.py - Init file for the package