''' Class to hold the options for ample ''' # python imports import copy import os # Our imports import printTable class AmpleOptions(object): def __init__(self): # The dictionary with all the options self.d = {} # dictionary with the default arguments - if any are paths add to paths in populate self.defaults = { 'alignment_file' : None, 'all_atom' : True, 'arpwarp_cycles' : 10, 'ASU' : 0, 'benchmark_mode' : False, 'blast_dir' : None, 'buccaneer_cycles' : 5, 'ccp4_jobid' : None, 'debug' : False, 'domain_all_chains_pdb' : None, 'domain_termini_distance' : 0, 'early_terminate' : True, 'ensemble_mode' : 'percent', 'ensembler' : False, 'ensembles_dir' : None, 'F' : None, 'fasta' : None, 'frags_3mers' : None, 'frags_9mers' : None, 'FREE' : None, 'import_cluster' : False, 'import_models' : False, 'import_ensembles' : False, 'improve_template' : None, 'LGA' : None, 'make_frags' : False, 'make_models' : True, 'maxcluster_exe' : None, 'max_ensemble_models' : 30, 'missing_domain' : False, 'models_dir' : None, 'molrep_only' : False, 'mr_keys' : None, 'mr_sequence' : None, 'mtz' : None, 'name' : 'ampl', 'native_pdb' : None, 'nmodels' : 1000, 'NMR_model_in' : None, 'NMR_process' : None, 'NMR_protocol' : False, 'NMR_remodel_fasta' : None, 'NMR_Truncate_only' : None, 'nproc' : 1, 'nr' : None, 'num_clusters' : 1, 'old_shelx' : False, 'output_pdb' : 'ample_output.pdb', 'percent' : 5, 'phaser_only' : False, 'phenix_exe' : None, 'psipred_ss2' : None, 'quark_models' : None, 'rg_reweight' : None, 'ROSETTA_cluster' : None, 'rosetta_db' : None, 'rosetta_dir' : None, 'rosetta_fragments_exe' : None, 'rosetta_AbinitioRelax' : None, 'rosetta_version' : None, 'rcdir' : os.path.join( os.path.expanduser("~"), ".ample" ), 'run_dir' : os.getcwd(), 'scwrl_exe' : None, 'sf_cif' : None, 'shelx_cycles' : 15, 'shelxe_exe' : None, 'shelxe_rebuild' : False, 'SIGF' : None, 'spicker_exe' : None, 'split_mr' : False, 'submit_array' : False, 'submit_cluster' : False, 'submit_qtype' : None, 'theseus_exe' : None, 'top_model_only' : False, 'transmembrane' : False, 'transmembrane_octopusfile' : None, 'transmembrane_lipofile' : None, 'transmembrane_spanfile' : None, 'use_arpwarp' : True, 'use_buccaneer' : True, 'use_homs' : True, 'use_scwrl' : False, 'use_shelxe' : True, } self.quick_mode = { 'max_ensemble_models' : 10, 'nmodels' : 200, 'percent' : 20, 'molrep_only' : False, 'phaser_only' : True, 'shelx_cycles' : 5, 'use_arpwarp' : False, 'use_buccaneer' : False, # This kills phaser after 15 minutes # Needs to be a list of lists as there can be multiple mr_keys 'mr_keys' : [ [ 'PKEY', 'KILL','TIME','15' ] ], } # Test use scrwl self.devel_mode = { 'early_terminate': False, 'benchmark_mode': True, 'use_shelxe' : True, 'shelxe_rebuild' : True, 'use_scwrl' : False, 'use_arpwarp' : False, 'use_buccaneer' : False, # This kills phaser after 6 hours # Needs to be a list of lists as there can be multiple mr_keys 'mr_keys' : [ [ 'PKEY', 'KILL','TIME','360' ] ], } # We have a debug mode as the logger isn't activated when we run self.debug = False return def final_summary(self, cluster=None): """Return a string summarising the results of the run. Args: cluster -- the number of the cluster to summarise (COUNTING FROM 0) otherwise all clusters are summarised """ # List of all the possible column titles and their result object attributes # see python/mrbump_results.py title2attr = { 'Ensemble_Name' :'ensembleName', 'Model_Name' :'name', 'MR_Program': 'program', 'Solution_Type': 'solution', 'final_Rfact' : 'rfact', 'final_Rfree' :'rfree', 'Bucc_final_Rfact' :'buccRfact', 'Bucc_final_Rfree' :'buccRfree', 'ARP_final_Rfact' : 'arpWarpRfact', 'ARP_final_Rfree' :'arpWarpRfree', 'SHELXE_CC' : 'shelxeCC', 'SHELXE_ACL' : 'shelxeACL', 'SHELXE_Avg_Chain' : 'shelxeAvgChainLength', } if not cluster: # Get number of clusters from the length of the mrbump results lists clusters = [ i for i in range( len( self.d['mrbump_results'] ) ) ] else: if cluster >= len( self.d['mrbump_results'] ): raise RuntimeError, "Cluster number is not in results list" clusters = [ cluster ] # String to hold the results summary summary = "" for cluster in clusters: summary+="\n\nResults for cluster: {0}\n\n".format( cluster+1 ) # Table for results with header results_table = [] ensemble_results = None if self.d.has_key('ensemble_results'): ensemble_results = self.d['ensemble_results'][ cluster ] # Get map of ensemble name -> ensemble result name2result = {} for i, e in enumerate( ensemble_results ): if name2result.has_key( e.name ): raise RuntimeError, "Duplicate key: {0}".format( e.name ) name2result[ e.name ] = ensemble_results[ i ] # Assume mrbump_results are already sorted mrbump_results = self.d['mrbump_results'][ cluster ] if not len(mrbump_results): print "!!! No results found for cluster {0} !!!".format( cluster+1 ) continue # Get header from first object - need to copy or the assignment just creates a reference header = copy.copy( mrbump_results[0].header ) if ensemble_results: header += [ "#Decoys", "#Residues" ] results_table.append( header ) best=mrbump_results[0] # remember best (first) result for result in mrbump_results: result_summary = [] for h in result.header: result_summary.append( getattr( result, title2attr[ h ] ) ) if ensemble_results: # MRBUMP Results have loc0_ALL_ prepended and _UNMOD appended name = result.name[9:-6] result_summary += [ name2result[ name ].num_models, name2result[ name ].num_residues ] results_table.append( result_summary ) # Get nicely formatted string summarising the results table = printTable.Table() summary += table.pprint_table( results_table ) # Show where it happened summary += '\nBest Molecular Replacement results so far are in:\n\n' summary += best.mrDir if best.pdb and os.path.isfile(best.pdb): summary += '\n\nFinal PDB is:\n\n' summary += best.pdb summary += '\n\n' return summary def populate( self, parser_args ): """ Fill ourselves with the options from the parser """ tmpv = None for k, v in vars(parser_args).iteritems(): #print "{} | {}".format( k, v ) if isinstance(v,list): # All values are in a list tmpv = v[0] else: tmpv = v # Bit of a hack for true/false if isinstance( tmpv, str ): if tmpv.lower() == "true": tmpv = True elif tmpv.lower() == "false": tmpv = False self.d[k] = tmpv # end of loop # print "After populate" # for k, v in self.d.iteritems(): # print "{} | {}".format( k, v ) # Handle any defaults and any preset options self.process_options() return def process_options(self): """Check the options and process any preset defaults""" # First set anything that hasn't been set to its default option for k, v in self.defaults.iteritems(): if k not in self.d: self.d[k] = v elif self.d[k] == None: #if self.debug: # print "Setting default value: {0} : {1}".format(k,v) self.d[k] = v else: if self.debug and self.d[k] != v: print "Changed default value: {0} : {1}".format(k, self.d[k]) # Any changes here if self.d['submit_qtype']: self.d['submit_qtype'] = self.d['submit_qtype'].upper() # Convert all paths to absolute paths paths = [ 'alignment_file', 'blast_dir', 'domain_all_chains_pdb', 'ensembles_dir', 'fasta', 'frags_3mers', 'frags_9mers', 'import_cluster', 'maxcluster_exe', 'models_dir', 'mr_sequence', 'mtz', 'native_pdb', 'NMR_model_in', 'NMR_remodel_fasta', 'psipred_ss2', 'quark_models', 'rosetta_db', 'rosetta_dir', 'rosetta_fragments_exe', 'rosetta_AbinitioRelax', 'scwrl_exe', 'sf_cif', 'shelxe_exe', 'spicker_exe', 'theseus_exe', 'transmembrane_octopusfile', 'transmembrane_lipofile', 'transmembrane_spanfile' ] for k, v in self.d.iteritems(): if k in paths and isinstance( v, str ): self.d[ k ] = os.path.abspath( v ) # Check if using any preset options if self.d['devel_mode']: for k, v in self.devel_mode.iteritems(): # Set any that haven't been set if self.d[k] == None: self.d[k] = v else: # Already set - only overwrite if it's set to a default value, otherwise we # let the user go with what they've chosen but warn if self.d[k] != self.defaults[k] and self.d[k] != v : print "WARNING! Overriding devel_mode setting: {0} : {1} with user setting {2}".format( k, v, self.d[k] ) else: # We overwrite the default with our value if self.debug: print "Overriding default setting: {0} : {1} with devel_mode setting {2}".format( k, self.defaults[k], v ) self.d[k] = v if self.d['quick_mode']: for k, v in self.quick_mode.iteritems(): # Set any that haven't been set if self.d[k] == None: self.d[k] = v else: # Already set - only overwrite if it's set to a default value, otherwise we # let the user go with what they've chosen but warn if self.d[k] != self.defaults[k] and self.d[k] != v : print "WARNING! Overriding quick_mode setting: {0} : {1} with user setting {2}".format( k, v, self.d[k] ) else: # We overwrite the default with our value if self.debug: print "Overriding default setting: {0} : {1} with quick_mode setting {2}".format( k, self.defaults[k], v ) self.d[k] = v return def prettify_parameters(self): """ Return the parameters nicely formated as a list of strings suitable for writing out to a file """ pstr = "" pstr +='Params Used in this Run\n\n' keys1 = ['fasta','work_dir','mtz','name'] pstr += '---input---\n' for k in keys1: pstr += "{0}: {1}\n".format(k, self.d[k]) keys2 = ['make_frags','rosetta_fragments_exe','frags_3mers','frags_9mers'] pstr+= '\n---fragments---\n' for k in keys2: pstr += "{0}: {1}\n".format(k, self.d[k]) keys3 = ['make_models','rosetta_AbinitioRelax','rosetta_db'] pstr+= '\n---modelling---\n' for k in keys3: pstr += "{0}: {1}\n".format(k, self.d[k]) if self.d['use_scwrl']: pstr+= '\n---3rd party---\nSCWRL {0}\n'.format( self.d['scwrl_exe'] ) keys4 = ['missing_domain','domain_all_chains_pdb'] if keys4[0]: pstr+= '\n---Missing Domain---\n' for k in keys4: pstr += "{0}: {1}\n".format(k, self.d[k]) # This only used for printing INSERT_DOMAIN = False if self.d['domain_termini_distance'] > 0: INSERT_DOMAIN = True pstr += '\nIs an Insert Domain {0} termini distance {1}\n'.format( INSERT_DOMAIN, self.d['domain_termini_distance'] ) # Now print out everything else pstr += "\n---Other parameters---\n" done_keys = keys1 + keys2 + keys3 + keys4 + [ 'use_scwrl', 'domain_termini_distance' ] for k, v in sorted(self.d.items()): if k not in done_keys: pstr += "{0} : {1}\n".format( k, v ) return pstr if __name__ == "__main__": import sys import cPickle if len(sys.argv) == 2: pfile = sys.argv[1] else: pfile = "/opt/ample-dev1/examples/toxd-example/ROSETTA_MR_10/resultsd.pkl" f = open(pfile) d = cPickle.load(f) AD = AmpleOptions() AD.d = d print AD.final_summary() # for k,v in d.iteritems(): # AD.d[k] = v # print AD.final_summary()