# Creates a csv of the cost function to plot in Excel
import simpleOptimization as simple_opt
with open('costPlot.csv', 'w') as cost_file:
for s in range(500 + 1):
cost_file.write('{0},{1}\n'.format(s, simple_opt.cost(s)))
total_bests[3] += gs_solutions[sol][i][4]
iteration = rw_solutions[0][i][0]
# Calculating averages in place
best_file.write("%d, %f, %f, %f, %f\n" % (iteration,
total_bests[0] / trials,
total_bests[1] / trials,
total_bests[2] / trials,
total_bests[3] / trials))
# Fourth part: calculations
iteration = 100
# Compute global minimum
min_cost = simple_opt.cost(0)
for i in range(501):
cur_cost = simple_opt.cost(i)
if (cur_cost < min_cost):
min_cost = cur_cost
rw_at_iteration = numpy.zeros([trials, 1])
rs_at_iteration = numpy.zeros([trials, 1])
gd_at_iteration = numpy.zeros([trials, 1])
gs_at_iteration = numpy.zeros([trials, 1])
rw_num_correct = 0
rs_num_correct = 0
gd_num_correct = 0
gs_num_correct = 0
