from ms2lda_molnet_integration import write_output_files
write_output_files(vd,
pairs_file,
output_prefix,
metadata,
overlap_thresh=args.input_network_overlap,
p_thresh=args.input_network_pvalue,
X=args.input_network_topx,
motif_metadata=motifdb_metadata)
# Writing the report - ntoe that you might need to set the 'backend' argument
# for this method to work (see the method in lda.py) as it depends what on
# your system will render the pdf...
from lda import write_topic_report
try:
write_topic_report(vd, output_prefix + '_topic_report.pdf')
except:
print("PDF Generation Failed")
### Writing additional output, creates a list of all motifs found in data, one motif per row and MS/MS Scan
all_motifs_in_scans = get_motifs_in_scans(
vd,
metadata,
overlap_thresh=args.input_network_overlap,
p_thresh=args.input_network_pvalue,
X=args.input_network_topx,
motif_metadata=motifdb_metadata)
# Outputting motif list, one by line
fieldnames = [
'scan', 'precursor.mass', 'retention.time', "motif", "probability",
print "Writing combined edges"
with open(input_prefix+'_edges_ms2lda.csv','w') as f:
writer = csv.writer(f)
for line in all_edges:
writer.writerow(line)
print "Creating summary file"
summary_file = input_prefix + '_lda_summary.csv'
write_summary_file(vd,summary_file)
print "Creating pdf topic report"
report_file = input_prefix + '_lda_report.pdf'
write_topic_report(vd,report_file,backend = 'Agg')
def check_edge(edge,edges):
if check_uni_edge(edge[0],edge[1],edges):
return True
if check_uni_edge(edge[1],edge[0],edges):
return True
return False
def check_uni_edge(node1,node2,edges):
node1edges = filter(lambda x: x[0] == node1)
if len(node1edges) > 0:
node12edges = filter(lambda x: x[1] == node2)
if len(node12edges) > 0:
return True
return False
vlda.run_vb(initialise=True, n_its=input_iterations)
vd = vlda.make_dictionary(
features=features, metadata=metadata, filename=output_prefix + '.dict')
from ms2lda_molnet_integration import write_output_files
write_output_files(vd, pairs_file, output_prefix, metadata,
overlap_thresh=args.input_network_overlap, p_thresh=args.input_network_pvalue,
X=args.input_network_topx, motif_metadata = motifdb_metadata)
# Writing the report - ntoe that you might need to set the 'backend' argument
# for this method to work (see the method in lda.py) as it depends what on
# your system will render the pdf...
from lda import write_topic_report
try:
write_topic_report(vd,output_prefix+'_topic_report.pdf')
except:
print("PDF Generation Failed")
### Writing additional output, creates a list of all motifs found in data, one motif per row and MS/MS Scan
all_motifs_in_scans = get_motifs_in_scans(vd, metadata,
overlap_thresh=args.input_network_overlap, p_thresh=args.input_network_pvalue,
X=args.input_network_topx, motif_metadata = motifdb_metadata)
with open(output_prefix + "_motifs_in_scans.tsv", 'w') as tsvfile:
fieldnames = ['scan', 'precursor.mass',
'retention.time',
"motif",
"probability",
"overlap",