from multiprocessing import Pool, Process, Manager
from simplfunction import simplefunction
from calltomapper import calltomapper
if __name__ == '__main__':
"""Map reduce test is a simple testing module to check functionality
of map-reduce implementation"""
haystacks = []
haystacks.append(haystack("0",[0, 1, 2, 3, 4, 5, 6, 7, 8, 9]))
haystacks.append(haystack("1",[3, 2, 2, 3, 4, 3, 6, 7, 8, 9]))
haystacks.append(haystack("2",[1, 6, -1, 0, 4, 0, 6, 7, 8, 9]))
haystacks.append(haystack("3",[3, 3, 3]))
haystackmap = haystackmapper(haystacks)
emissions= []
print("USING MAP POOL")
pool = Pool(2) # if it is a quad-core machine it can be set to 4
emissions = pool.map(haystackmap.mapper, [[2],[3]])
print(emissions)
print(haystackreducer(sum(emissions,[])))
emissions= []
print("USING MAP PROCESS")
p = Process(target=simplefunction, args=(1,2))
p.start()
p = Process(target=simplefunction, args=(1,3))
p.start()
def run():
""" run runs the database search taking three user inputs, the query wav file,
number of partitions, and number of partition samples"""
good_file = 0
while (good_file == 0):
query = raw_input(
"Submit .wav file to search against database (Example: button.wav): "
)
if (os.path.isfile(query)):
good_file = 1
#Instantiate Wavsound objects from the wav files
t_wavsounds = {}
query_wavsound = wavsound(query)
print(
"\n**Higher number of partitions increases false positive rates, \nwhile lower number of partitions increases false negative rates\n"
)
partition = raw_input("Set number of partitions of the query from 1 to " +
str(int(len(query_wavsound.get_data()) / 3)) + ": ")
samples = raw_input("Set number of samples of partitions from 1 to " +
partition + " (Recommend < 50): ")
# Database Structure
haystacks = []
# Database look up directory
rootdir = 'db'
for subdir, __, files in os.walk(rootdir):
for file in files:
# for debug print (subdir+"/"+file)
t_wavsounds[subdir + "/" + file] = wavsound(subdir + "/" + file)
# for debug print(t_wavsounds[subdir+"/"+file])
haystacks.append(
haystack(subdir + "/" + file,
t_wavsounds[subdir + "/" + file].get_data()))
query_needle_factory = needlestorage(query_wavsound, int(partition),
int(samples))
haystackmap = haystackmapper(haystacks)
needles = query_needle_factory.get_needles()
len_needles = len(needles)
len_needle = len(needles[0]) # size is the same for all needles
manager = Manager()
# Map processes emit key-value pairs to emissions
return_emissions = manager.dict()
# Job is a list of processes
jobs = []
# Process number
pnum = 0
print "Number of Needles: ", len(needles)
# Database query time
start_time = time.time()
#Distribute processes using multiprocessor
for needle in needles:
p = Process(target=calltomapper,
args=(haystackmap, needle, pnum, len_needles,
return_emissions))
jobs.append(p)
p.start()
pnum += 1
for proc in jobs:
proc.join()
# flatten return_emissions into a list
emissions_list = sum(return_emissions.values(), [])
print "Search Result:"
result_dict = haystackreducer(emissions_list)
# Tabulate % match (wav files with 0% match are excluded from the result)
for key in result_dict:
print str(key), ": ", (25 - len(str(key))) * " ", str("{0:.2f}".format(
int(result_dict[key]) / len(needles) * 100)), "% match"
# Show search time
timelapse_parallel = time.time() - start_time
print timelapse_parallel, "seconds"
def run():
""" run runs the database search taking three user inputs, the query wav file,
number of partitions, and number of partition samples"""
good_file = 0
while (good_file == 0):
query = raw_input("Submit .wav file to search against database (Example: button.wav): ")
if (os.path.isfile(query)):
good_file = 1
#Instantiate Wavsound objects from the wav files
t_wavsounds = {}
query_wavsound = wavsound(query)
print("\n**Higher number of partitions increases false positive rates, \nwhile lower number of partitions increases false negative rates\n")
partition = raw_input("Set number of partitions of the query from 1 to " + str(int(len(query_wavsound.get_data())/3))+": ")
samples = raw_input("Set number of samples of partitions from 1 to " + partition + " (Recommend < 50): ")
# Database Structure
haystacks = []
# Database look up directory
rootdir = 'db'
for subdir, __, files in os.walk(rootdir):
for file in files:
# for debug print (subdir+"/"+file)
t_wavsounds[subdir+"/"+file] = wavsound(subdir+"/"+file)
# for debug print(t_wavsounds[subdir+"/"+file])
haystacks.append(haystack(subdir+"/"+file,t_wavsounds[subdir+"/"+file].get_data()))
query_needle_factory = needlestorage(query_wavsound,int(partition),int(samples))
haystackmap = haystackmapper(haystacks)
needles = query_needle_factory.get_needles()
len_needles = len(needles)
len_needle = len(needles[0]) # size is the same for all needles
manager = Manager()
# Map processes emit key-value pairs to emissions
return_emissions = manager.dict()
# Job is a list of processes
jobs = []
# Process number
pnum = 0
print "Number of Needles: ", len(needles)
# Database query time
start_time = time.time()
#Distribute processes using multiprocessor
for needle in needles:
p = Process(target=calltomapper, args=(haystackmap,needle,pnum,len_needles,return_emissions))
jobs.append(p)
p.start()
pnum += 1
for proc in jobs:
proc.join()
# flatten return_emissions into a list
emissions_list = sum(return_emissions.values(),[])
print "Search Result:"
result_dict = haystackreducer(emissions_list)
# Tabulate % match (wav files with 0% match are excluded from the result)
for key in result_dict:
print str(key),": ",(25-len(str(key)))*" ",str("{0:.2f}".format(int(result_dict[key])/len(needles)*100)),"% match"
# Show search time
timelapse_parallel = time.time() - start_time
print timelapse_parallel, "seconds"
