simbad.lattice.latticesearch module¶

Module to skim the PDB for similar unit cells

class LatticeSearch(lattice_db_fname, model_dir)[source]¶

Bases: object

A class to do a search for PDB entries with similar unit cell dimensions

Attributes:	lattice_db_fname The path to the lattice database model_dir The path to the model directory

Methods

calculate_niggli_cell(unit_cell, space_group)	Calculate the parameters of the Niggli cell
calculate_penalty(query, reference)	Calculate the linear cell variation between unit cells
calculate_probability(penalty_score)	Calculate the probability that a penalty score will give a solution
calculate_volume_difference(query, reference)	Calculate the difference in volume between the query unit cell and the reference unit cell
cell_within_tolerance(query, reference, …)	Compare two cells and determine if query is within reference cell parameter tolerance
check_sg(sg)	Check the space group for known anomalies
copy_results(source, destination)	Copy the results from a local copy of the PDB
download_results(destination)	Download the results directly from the PDB
pdb_in_results(pdb_code, results)	Check to see if a pdb_code has already been appended to the results
search(space_group, unit_cell[, tolerance, …])	Search for similar Niggli cells
summarize(csvfile)	Summarize the search results

static calculate_niggli_cell(unit_cell, space_group)[source]¶

Calculate the parameters of the Niggli cell

Parameters:	unit_cell : list, tuple The parameters of the unit cell space_group : str The space group
Returns:	list The Niggli cell parameters

classmethod calculate_penalty(query, reference)[source]¶

Calculate the linear cell variation between unit cells

Parameters:	query : list, tuple The query cell parameters reference : list, tuple The reference cell parameters
Returns:	float Total penalty float Length penalty float Angle penalty

classmethod calculate_probability(penalty_score)[source]¶

Calculate the probability that a penalty score will give a solution

Parameters:	penalty_score : float The total penalty score calculate for a search result
Returns:	float Probability score

classmethod calculate_volume_difference(query, reference)[source]¶

Calculate the difference in volume between the query unit cell and the reference unit cell

Parameters:	query : list, tuple The query cell parameters reference : list, tuple The reference cell parameters
Returns:	float The absolute difference in cell volumes

classmethod cell_within_tolerance(query, reference, tolerance)[source]¶

Compare two cells and determine if query is within reference cell parameter tolerance

Parameters:	query : list, tuple The query cell parameters reference : list, tuple The reference cell parameters tolerance : list, tuple The tolerance cell parameter values
Returns:	bool

static check_sg(sg)[source]¶

Check the space group for known anomalies

copy_results(source, destination)[source]¶

Copy the results from a local copy of the PDB

Parameters:	source : str The path to copy results from destination : str The path to save results to
Raises:	ValueError No search results found/available ValueError Output directory does not exist IOError Search result not found in installed PDB

download_results(destination)[source]¶

Download the results directly from the PDB

Parameters:	destination : str The path to save results to
Raises:	ValueError No search results found/available ValueError Output directory does not exist RuntimeError Unable to download PDB

lattice_db_fname¶

The path to the lattice database

model_dir¶

The path to the model directory

static pdb_in_results(pdb_code, results)[source]¶

Check to see if a pdb_code has already been appended to the results

search(space_group, unit_cell, tolerance=0.05, max_to_keep=50, max_penalty=12)[source]¶

Search for similar Niggli cells

Parameters:	unit_cell : list, tuple The parameters of the unit cell space_group : str The space group tolerance : int, float, optional The tolerance applied for Niggli cell comparison [default: 0.05] max_to_keep : int, optional The top-N number of results to return [default: 50] max_penalty : int, optional The total penalty score over which results are ignored [default: 12]

summarize(csvfile)[source]¶

Summarize the search results

Parameters:	csvfile : str The path to an output CSV file