def process_general_file(score, namefile):
res = list(sorted(score, key=score.__getitem__, reverse=True))
l = 0
values = []
for s in res:
if s not in args.skip:
values.append(s)
l += 1
if l >= limit:
break
with open("{}.csv".format(namefile), 'w') as f:
f.write("id,value\n")
for v in values:
val = bubble_annotation(field, field_string, v, potiron_path, None)
f.write("{}{},\n".format(v, val))
f.write("{}{},{}\n".format(v, val, int(score[v])))
return values
def process_general_file(score, namefile, field, field_string, skip, limit):
res = list(sorted(score, key=score.__getitem__, reverse=True))
l = 0
values = []
for s in res:
if s not in skip:
values.append(s)
l+=1
if l >= limit:
break
with open("{}.csv".format(namefile), 'w') as f:
f.write("id,value\n")
for v in values :
val = bubble_annotation(field,field_string,v,potiron_path,None)
f.write("{}{},\n".format(v,val))
f.write("{}{},{}\n".format(v,val,int(score[v])))
return values
def process_file(score, name, prot, skip, limit):
# Sort the complete list of values for the month by score
res = list(sorted(score, key=score.__getitem__, reverse=True))
l = 0
values = []
for s in res:
# If the current value is not one that should be skipped, increment the number of values to include in the chart
if s not in skip:
values.append(s)
l += 1
# When the limit value is reached, we don't need to increment anymore, we break the loop
if l >= limit:
break
# Write all the values and their scores into the csv datafile
with open("{}.csv".format(name),'w') as f:
f.write("id,value\n")
for v in values :
val = bubble_annotation(field,field_string,v,potiron_path,prot)
f.write("{}{},\n".format(v,val))
f.write("{}{},{}\n".format(v,val,int(score[v])))
return values
def process_file(red, redisKey, name, field, protocol, field_string, skip, limit):
l = 0
values = []
# For each value ranged in decreasing order
for v in red.zrevrangebyscore(redisKey,MAXVAL,0):
val = v.decode()
# If the current value is not one that should be skipped, increment the number of values to include in the chart
if val not in skip :
values.append(val)
l += 1
# When the limit value is reached, we don't need to increment anymore, we break the loop
if l >= limit:
break
# Write all the values and their scores into the csv datafile
with open("{}.csv".format(name),'w') as f:
f.write("id,value\n")
for v in values:
val = bubble_annotation(field,field_string,v,potiron_path,protocol)
f.write("{}{},\n".format(v,val))
f.write("{}{},{}\n".format(v,val,red.zscore(redisKey,v)))
return values
def process_file(self, redisKey, name, protocol, field_string):
l = 0
values = []
# For each value ranged in decreasing order
for v in self.red.zrevrangebyscore(redisKey,self.MAXVAL,0):
val = v.decode()
# If the current value is not one that should be skipped, increment the number of values to include in the chart
if val not in self.skip :
values.append(val)
l += 1
# When the limit value is reached, we don't need to increment anymore, we break the loop
if l >= self.limit:
break
# Write all the values and their scores into the csv datafile
with open("{}.csv".format(name),'w') as f:
f.write("id,value\n")
for v in values:
val = bubble_annotation(self.field,field_string,v,potiron.potiron_path,protocol)
f.write("{}{},\n".format(v,val))
f.write("{}{},{}\n".format(v,val,self.red.zscore(redisKey,v)))
return values