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IMP Reference Guide
2.6.1
The Integrative Modeling Platform
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A macro for running all the basic operations of analysis. More...
Inherits object.
A macro for running all the basic operations of analysis.
Includes clustering, precision analysis, and making ensemble density maps. A number of plots are also supported.
Public Member Functions | |
| def | __init__ |
| Constructor. More... | |
| def | clustering |
| Get the best scoring models, compute a distance matrix, cluster them, and create density maps. More... | |
| def | get_modeling_trajectory |
| Get a trajectory of the modeling run, for generating demonstrative movies. More... | |
| def IMP.pmi.macros.AnalysisReplicaExchange0.__init__ | ( | self, | |
| model, | |||
merge_directories = ['./'], |
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stat_file_name_suffix = 'stat', |
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best_pdb_name_suffix = 'model', |
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do_clean_first = True, |
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do_create_directories = True, |
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global_output_directory = 'output/', |
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replica_stat_file_suffix = 'stat_replica', |
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global_analysis_result_directory = './analysis/' |
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| ) |
Constructor.
| model | The IMP model |
| stat_file_name_suffix | |
| merge_directories | The directories containing output files |
| best_pdb_name_suffix | |
| do_clean_first | |
| do_create_directories | |
| global_output_directory | Where everything is |
| replica_stat_file_suffix | |
| global_analysis_result_directory |
| def IMP.pmi.macros.AnalysisReplicaExchange0.clustering | ( | self, | |
score_key = 'SimplifiedModel_Total_Score_None', |
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rmf_file_key = 'rmf_file', |
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rmf_file_frame_key = 'rmf_frame_index', |
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state_number = 0, |
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prefiltervalue = None, |
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feature_keys = [], |
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outputdir = './', |
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alignment_components = None, |
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number_of_best_scoring_models = 10, |
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rmsd_calculation_components = None, |
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distance_matrix_file = 'distances.mat', |
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load_distance_matrix_file = False, |
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skip_clustering = False, |
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number_of_clusters = 1, |
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display_plot = False, |
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exit_after_display = True, |
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get_every = 1, |
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first_and_last_frames = None, |
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density_custom_ranges = None, |
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write_pdb_with_centered_coordinates = False, |
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voxel_size = 5.0 |
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| ) |
Get the best scoring models, compute a distance matrix, cluster them, and create density maps.
| score_key | The score for ranking models |
| rmf_file_key | Key pointing to RMF filename |
| rmf_file_frame_key | Key pointing to RMF frame number |
| state_number | State number to analyze |
| prefiltervalue | Only include frames where the score key is below this value |
| feature_keys | Keywords for which you want to calculate average, medians, etc, |
| outputdir | The local output directory used in the run |
| alignment_components | List of tuples for aligning the structures e.g. ["Rpb1", (20,100,"Rpb2"), .....] |
| number_of_best_scoring_models | Num models to keep per run |
| rmsd_calculation_components | List of tuples for calculating RMSD e.g. ["Rpb1", (20,100,"Rpb2"), .....] |
| distance_matrix_file | Where to store/read the distance matrix |
| load_distance_matrix_file | Try to load the distance matrix file |
| skip_clustering | Just extract the best scoring models and save the pdbs |
| number_of_clusters | Number of k-means clusters |
| display_plot | Display the distance matrix |
| exit_after_display | Exit after displaying distance matrix |
| get_every | Extract every nth frame |
| first_and_last_frames | A tuple with the first and last frames to be analyzed. Values are percentages! Default: get all frames |
| density_custom_ranges | List of tuples or strings for density calculation e.g. ["Rpb1", (20,100,"Rpb2"), .....] |
| write_pdb_with_centered_coordinates | |
| voxel_size | Used for the density output |
| def IMP.pmi.macros.AnalysisReplicaExchange0.get_modeling_trajectory | ( | self, | |
score_key = 'SimplifiedModel_Total_Score_None', |
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rmf_file_key = 'rmf_file', |
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rmf_file_frame_key = 'rmf_frame_index', |
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outputdir = './', |
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get_every = 1, |
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nframes_trajectory = 10000 |
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| ) |
Get a trajectory of the modeling run, for generating demonstrative movies.
