# if summary is not yet set: prepare it
if len(summary) == 0:
for m in methodkeys:
summary[m] = defaultdict(list)
# fill results into summary dictionary
for m in methodkeys:
for i, k in enumerate(fpkeys):
j = i * 2
summary[m][k].append(
[target, results[m][j], results[m][j + 1]])
# write out
outdir = outpath + '/method_summary/'
if not os.path.exists(outdir): os.makedirs(outdir)
# loop over methods
for m in methodkeys:
outfile = open(outdir + 'summary_' + m + '.txt', 'w')
ana_func.writeHeader(outfile, fpkeys)
# loop over targets
for t in range(len(summary[m][fpkeys[0]])):
curr_id = summary[m][fpkeys[0]][t][0]
outfile.write("%s " % curr_id)
# loop over fingerprints
for k in fpkeys:
element = summary[m][k][t]
outfile.write("%.3f %.3f " % (element[1], element[2]))
outfile.write("\r\n") # for Windows
outfile.close()
if len(ranks) == 0:
for m in methodkeys:
ranks[m] = defaultdict(list)
# prepare writing out
# if header is not yet written to csv file
if not header:
for m in methodkeys:
outfile_csv = open(outdir_csv+'/fp_ranking_'+m+'.csv', 'w')
outfile_csv.write("\"fp\",\"target\",\"rank\",\"repeat\"\n")
outfile_csv.close()
header = True
# header of average score per target
outfile = open(outdir+'/target_'+str(target)+'.txt', 'w')
ana_func.writeHeader(outfile, fpkeys)
# calculate average score
# loop over methods
for m in methodkeys:
outfile.write("%s\t" % m) # average score file
outfile_csv = open(outdir_csv+'/fp_ranking_'+m+'.csv', 'a') # csv file: append!
# loop over fingerprints
for k in fpkeys:
# csv rank file
for i,v in enumerate(validation[m][k]):
outfile_csv.write("\"%s\",\"%s\",\"%i\",\"%i\"\n" % (k, str(target), v[1], i+1))
# average score file
tmp = []
for i in validation[m][k]:
ranks[m][k].append(i[1]) # store ranks
methodkeys = results.keys()
# if summary is not yet set: prepare it
if len(summary) == 0:
for m in methodkeys:
summary[m] = defaultdict(list)
# fill results into summary dictionary
for m in methodkeys:
for i,k in enumerate(fpkeys):
j = i*2
summary[m][k].append([target, results[m][j], results[m][j+1]])
# write out
outdir = outpath+'/fp_summary/'
if not os.path.exists(outdir): os.makedirs(outdir)
# loop over fingerprints
for k in fpkeys:
outfile = open(outdir+'summary_'+k+'.txt', 'w')
ana_func.writeHeader(outfile, methodkeys)
# loop over targets
for t in range(len(summary[methodkeys[0]][k])):
curr_id = summary[methodkeys[0]][k][t][0]
outfile.write("%s " % curr_id)
# loop over methods
for m in methodkeys:
element = summary[m][k][t]
outfile.write("%.3f %.3f " % (element[1], element[2]))
outfile.write("\r\n") # for Windows
outfile.close()
# if summary is not yet set: prepare it
if len(summary) == 0:
for m in methodkeys:
summary[m] = defaultdict(list)
# fill results into summary dictionary
for m in methodkeys:
for i, k in enumerate(fpkeys):
j = i * 2
summary[m][k].append(
[target, results[m][j], results[m][j + 1]])
# write out
outdir = outpath + '/fp_summary/'
if not os.path.exists(outdir): os.makedirs(outdir)
# loop over fingerprints
for k in fpkeys:
outfile = open(outdir + 'summary_' + k + '.txt', 'w')
ana_func.writeHeader(outfile, methodkeys)
# loop over targets
for t in range(len(summary[methodkeys[0]][k])):
curr_id = summary[methodkeys[0]][k][t][0]
outfile.write("%s " % curr_id)
# loop over methods
for m in methodkeys:
element = summary[m][k][t]
outfile.write("%.3f %.3f " % (element[1], element[2]))
outfile.write("\r\n") # for Windows
outfile.close()