#!/usr/bin/env ccp4-python
# encoding: utf-8
import logging
import os
import pandas as pd
LATTICE_ID = 'latt'
CONTAMINANT_ID = 'cont'
MORDA_ID = 'morda'
ID2STR = { LATTICE_ID : 'lattice',
CONTAMINANT_ID : 'contaminant',
MORDA_ID : 'MORDA',
}
logger = logging.getLogger(__name__)
[docs]class FileCollection(object):
"""Class for holding results files and annotations"""
def __init__(self):
self.mr_log = None
self.ref_pdb = None
self.ref_pdb_annotation = None
self.ref_mtz_annotation = None
self.ref_log = None
self.ref_map = None
self.diff_map = None
[docs]class SimbadResults(object):
"""Class to handle the results from a SIMBAD search
Attributes
----------
work_dir : str
The SIMBAD work directory where SIMBAD was run
lattice_results : :Pandas dataframe:
Dataframe containing the results of the lattice search
lattice_mr_results : :Pandas dataframe:
Dataframe containing the results of the MR
"""
def __init__(self, work_dir):
assert os.path.isdir(work_dir),"Cannot find work_dir: %s" % work_dir
self.work_dir = os.path.abspath(work_dir)
# Create dataframes from results
lattice_results = os.path.join(self.work_dir, LATTICE_ID, 'lattice_search.csv')
self.lattice_results = pd.read_csv(lattice_results) if os.path.isfile(lattice_results) else None
lattice_mr_results = os.path.join(self.work_dir, LATTICE_ID, 'lattice_mr.csv')
self.lattice_mr_results = pd.read_csv(lattice_mr_results) if os.path.isfile(lattice_mr_results) else None
contaminant_results = os.path.join(self.work_dir, CONTAMINANT_ID, 'rot_search.csv')
self.contaminant_results = pd.read_csv(contaminant_results) if os.path.isfile(contaminant_results) else None
contaminant_mr_results = os.path.join(self.work_dir, CONTAMINANT_ID, 'cont_mr.csv')
self.contaminant_mr_results = pd.read_csv(contaminant_mr_results) if os.path.isfile(contaminant_mr_results) else None
morda_db_results = os.path.join(self.work_dir, MORDA_ID, 'rot_search.csv')
self.morda_db_results = pd.read_csv(morda_db_results) if os.path.isfile(morda_db_results) else None
morda_db_mr_results = os.path.join(self.work_dir, MORDA_ID, 'morda_mr.csv')
self.morda_db_mr_results = pd.read_csv(morda_db_mr_results) if os.path.isfile(morda_db_mr_results) else None
[docs] def top_files(self, num_results=3):
"""Return a list of num_results FileCollection objects with the results of the best MR steps"""
if self.morda_db_mr_results is not None:
return self.get_files(MORDA_ID, num_results=num_results)
elif self.contaminant_mr_results is not None:
return self.get_files(CONTAMINANT_ID, num_results=num_results)
elif self.lattice_mr_results is not None:
return self.get_files(LATTICE_ID, num_results=num_results)
else: None
[docs] def get_files(self, search_type, num_results=10):
"""Return the best num_results results files from search_type
Parameters
----------
search_type : str
The type of search undertaken
Returns
-------
"""
if search_type == LATTICE_ID:
df = self.lattice_mr_results
elif search_type == CONTAMINANT_ID:
df = self.contaminant_mr_results
elif search_type == MORDA_ID:
df = self.morda_db_mr_results
else: raise RuntimeError("Unrecognised search type: %s" % search_type)
results = []
for i in range(0, num_results):
try:
fc = FileCollection()
pdb_code = df.loc[i][0]
mr_program = list(df)[1][0:6]
mr_workdir = os.path.join(
self.work_dir, search_type, 'mr_search', pdb_code, 'mr', mr_program)
fc.mr_log = os.path.join(
mr_workdir, '{0}_mr.log'.format(pdb_code))
fc.ref_pdb = os.path.join(
mr_workdir, 'refine', '{0}_refinement_output.pdb'.format(pdb_code))
fc.ref_pdb_annotation = 'PDB #{0} from REFMAC-refined result of the {1} search'.format(i+1, ID2STR[search_type])
fc.ref_mtz = os.path.join(
mr_workdir, 'refine', '{0}_refinement_output.mtz'.format(pdb_code))
fc.ref_mtz_annotation = 'MTZ #{0} from REFMAC-refined result of the {1} search'.format(i+1, ID2STR[search_type])
fc.ref_log = os.path.join(
mr_workdir, 'refine', '{0}_ref.log'.format(pdb_code))
fc.ref_map = os.path.join(
mr_workdir, 'refine', '{0}_refmac_2fofcwt.map'.format(pdb_code))
fc.diff_map = os.path.join(
mr_workdir, 'refine', '{0}_refmac_fofcwt.map'.format(pdb_code))
results.append(fc)
except KeyError:
logger.debug("No result found at position %s", (i + 1))
return results
if __name__ == "__main__":
# Setup argument parser
from argparse import ArgumentParser
parser = ArgumentParser()
parser.add_argument(dest="work_dir")
# Process arguments
args = parser.parse_args()
SR = SimbadResults(args.work_dir)
for fc in SR.top_files():
print "FC ",fc, fc.ref_log, fc.ref_pdb_annotation
