# CS 423 lab 5 starter code for experiment
# This code should generate two randomly composed DNA sequences of various
# lengths and run the globalAlignment and localAlignment algorithms
# Authors:
####################################################################
import globalAlignment
#import localAlignment ## comment out once you have this module working
# this is how you call code defined in other files: modulename.functionname
# note that importing globalAlignment above will run the script in its
# entirety, so you may want to comment out any testing code at the bottom
# of that script, so it is not executed prior to the code below
s = "AGAAAAAAAACTA"
t = "TGCATCAAAG"
optimalScore = globalAlignment.globalAlignmentScore(s, t)
print ("Global alignment score: " + str(optimalScore))
# update this code so that it does the following:
# generates randomly composed DNA sequences (25%A, 25%C, 25%T, 25%G)
# of length N and returns it as a string
def randomSeq(N):
return ""
# runs the following experiment:
# From size Start to Stop going by Step:
# Generate 2 random DNA strings of length size
# Calculate the global alignment score between the two strings
# Calculate the local alignment score between the two strings
# Write results to file per line
elif ran < 0.50:
seq += "T"
elif ran < 0.75:
seq += "C"
else:
seq += "G"
return seq
########
# Timing experiment
# creates two random sequences of same length
# calculates time to find the optimal score
# writes the results to a file
# repeats for sequences of length 50 to 5000 stepping by 50
########
with open("longTimingExperiment.txt", 'w') as out:
for N in range(50, 5001, 50):
# generate two random sequences
ranSeq1 = randomSeq(N)
ranSeq2 = randomSeq(N)
# start clock and find global score
t0 = time.clock()
optimalScore = globalAlignment.globalAlignmentScore(ranSeq1, ranSeq2)
t1 = time.clock()
# print the time results to the file
totalTime = str(t1-t0)
print("Seq Len: %d\tTotal time: %s" % (N, totalTime))
out.write("%d\t%s\n" % (N, totalTime))
