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from Dataset import Dataset
import csv
def readPerformanceData(index, filename, datasets):
""" Reads performance data from file <filename>, stores information
into the non-empty <datasets> tuple.
The <index> will be used as the x-value in the plots.
Example Usage: see scripts/plotNormalizedEvolution.py
"""
ok = True
try:
file = open(filename, "rt")
except:
print "probs reading file? file=<%s>" % filename
ok=False
pass
if ok:
try:
reader = csv.reader(file, delimiter=' ')
for dirtyRow in reader :
row = filter(len, dirtyRow) # remove null elements from list
#print 'read: <%s>' % row
if row[0]=="#": continue # skip comment lines
if row[1]=="-.------": continue # skip non-existent algorithms
#print "row[0]=",row[0]
#print "row[1]=",row[1]
#print "row[2]=",row[2]
#print "row[3]=",row[3]
#print "row[4] = <%s>" % row[4]
#.. parse input elements
datatype = row[0]
perf = float(row[1])
error = float(row[2])
#.. parse shape / algorithm / implementation
istart = 0
iend = istart + datatype[istart:].find("-")
shape = datatype[istart:iend]
istart = iend+1
iend = istart + datatype[istart:].find("-")
algo = datatype[istart:iend]
istart = iend+1
impl = datatype[istart:]
key = shape+algo+impl
try:
datasets[key].addPoint(index,perf,error)
except KeyError:
#print "Creating key=<%s>, index=%i, perf=%f, error=%f" % (key, index, perf, error)
datasets[key] = Dataset( shape, algo, impl )
datasets[key].addPoint(index,perf,error)
finally:
file.close()
print "Commit=<%s> - %i datasets read." % (filename[0:7], len(datasets))
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