def simulate(filename=None, do_analysis=False):
print("Runpy Simulate")
results = []
asc_file_path = config.LTSpice_asc_filename
print("filename is : " + asc_file_path)
if filename is not None:
# Parse the file containing the parameters
command_list = simulation_tools.parse_parameter_file(filename)
# Run the list of commands
number_of_finished_simulations = 0
all_filenames = []
if command_list is None:
print('Syntax error in parameter file.')
return
for command in command_list:
if command[0] == 's':
parameter = command[1]
value = command[2]
# Set parameter as specified
print('Setting parameter: ' + str(parameter) + '=' +
str(value))
simulation_tools.set_parameters(asc_file_path, parameter,
value, True)
if command[0] == 'r':
parameter = command[1]
parameter_values = command[2]
# Run tests with the given parameter and corresponding list of parameter values
# The filenames of the output data is returned
results = simulation_tools.run_simulations(
[parameter, parameter_values],
number_of_finished_simulations)
filenames = results[0]
print(filenames)
print("Done Running Simulation")
all_filenames.extend(filenames)
number_of_finished_simulations += len(parameter_values)
if do_analysis:
analyze(filenames)
# If analysis made, make a report with all the analysied data
if do_analysis:
analysis_tools.make_report(all_filenames)
else:
# No parameter file is specified, run simulations with defaults values
results = simulation_tools.run_simulations()
def sim_iterate():
f = open('results.txt', 'w+') # open/create file results.txt for writing
# write headers to results.txt
f.write(
"Gen# BestVB BestVDB MaxDiff Gain #GenBeenBest\n")
i = 0
gen = 0 # counts number of overall generations
max_in = [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0] # used for according input diffs for maxDiffs
results = [] # used for return of simulation_tools.run_simulations
g = [0, 0, 0, 0, 0, 0, 0,
0] # Will be used for returns from genetic funtions
vb = [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0] # Children Vb values
sort = [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0] # sorting of maxDiff in sortMaxDiff()
temp = [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0]
vdb = [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0] # Children Vdb values
maxDiff = [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0] # Children grade values
vb_best = vb[0] # Keep track of Vb of best child pair
vdb_best = vdb[0] # Keep track of Vdb of best child pair
beenBest = 0 # Keep track of num generations pair has been best child
bestGrade = 0 # Keep track of grade of best child pair
asc_file_path = config.LTSpice_asc_filename
i = 0
while i < numChildren:
# Creates inital children randomly and tests them
# children in range 0-5 volts
parameter = 'VDB'
value = float(random.randint(0, 500)) / 500
vdb[i] = value
simulation_tools.set_parameters(asc_file_path, parameter, value, True)
parameter = 'VB'
value = float(random.randint(0, 500)) / 500
vb[i] = value
simulation_tools.set_parameters(asc_file_path, parameter, value, True)
results = simulation_tools.run_simulations()
print(i)
maxDiff[i] = results[1]
max_in[i] = results[0]
print(maxDiff[i])
#print(type(maxDiff[i]))
i += 1
while beenBest < numGenerations:
beenBest += 1 # increment # generations maxDiff[0] has been best for
gen += 1 # increment # generations total
# Get sorted order of indexes for maxDiff
sort = sortMaxDiff(maxDiff)
# Sort VB via sorted order
i = 0
while (i < 20):
temp[i] = vb[i]
i += 1
i = 0
while (i < 20):
vb[i] = temp[sort[i]]
i += 1
# Sort max_in via sorted order
i = 0
while (i < 20):
temp[i] = max_in[i]
i += 1
i = 0
while (i < 20):
max_in[i] = temp[sort[i]]
i += 1
# Sort VDB via sorted order
i = 0
while (i < 20):
temp[i] = vdb[i]
i += 1
i = 0
while (i < 20):
vdb[i] = temp[sort[i]]
i += 1
# Sort maxDiff via sorted order
i = 0
while (i < 20):
temp[i] = maxDiff[i]
i += 1
i = 0
while (i < 20):
maxDiff[i] = temp[sort[i]]
i += 1
# prints top 4 maxDiff values
print("Top 4:")
i = 0
while (i < 4):
print(maxDiff[i])
i += 1
# If maxDiff[0] is a new best, print to terminal & update values
if (maxDiff[0] > bestGrade):
print("New Best Child")
bestGrade = maxDiff[0]
vb_best = vb[0]
vdb_best = vdb[0]
beenBest = 1
# Print updates on beenBest and the best (VB, VDB, maxDiff)
print("Been Best for " + str(beenBest) + " generations")
print("Best VB = " + str(vb[0]) + " and Best VDB = " + str(vdb[0]))
gain = maxDiff[0] / max_in[0] # calculate the gain of the best child
# write data info of best child to file results.txt
f.write(
str(gen) + " " + str(vb[0]) + " " + str(vdb[0]) + " " +
str(maxDiff[0]) + " " + str(gain) + " " + str(beenBest) + "\n")
# Less significant bit mutations
i = 0
g = smallMutation(vb[2], vdb[2], vb[3], vdb[3], vb[4], vdb[4], vb[5],
vdb[5], vb[6], vdb[6], vb[7], vdb[7])
while i < 6:
print(str(vb[i + 2]) + ' ' + str(g[2 * i]))
vb[i + 2] = g[2 * i]
print(str(vdb[i + 2]) + ' ' + str(g[2 * i + 1]))
vdb[i + 2] = g[2 * i + 1]
i += 1
# More significant bit mutations
i = 0
g = recombination(vb[8], vdb[8], vb[9], vdb[9], vb[10], vdb[10],
vb[11], vdb[11])
while i < 4:
print(str(vb[i + 8]) + ' ' + str(g[2 * i]))
vb[i + 8] = g[2 * i]
print(str(vdb[i + 8]) + ' ' + str(g[2 * i + 1]))
vdb[i + 8] = g[2 * i + 1]
i += 1
# Recombinations (crossing one bit)
i = 0
g = largeMutation(vb[12], vdb[12], vb[13], vdb[13], vb[14], vdb[14],
vb[15], vdb[15])
while i < 4:
print(str(vb[i + 12]) + ' ' + str(g[2 * i]))
vb[i + 12] = g[2 * i]
print(str(vdb[i + 12]) + ' ' + str(g[2 * i + 1]))
vdb[i + 12] = g[2 * i + 1]
i += 1
# Throw out and generate new numbers
i = 0
g = throwOut(vb[16], vdb[16], vb[17], vdb[17], vb[18], vdb[18], vb[19],
vdb[19])
while i < 4:
print(str(vb[i + 16]) + ' ' + str(g[2 * i]))
vb[i + 16] = g[2 * i]
print(str(vdb[i + 16]) + ' ' + str(g[2 * i + 1]))
vdb[i + 16] = g[2 * i + 1]
i += 1
# Because of arrangement of while loop, only do this if beenBest for < numGenerations
if (beenBest < numGenerations):
i = 2
while i < numChildren:
# run simulation on children 2-19 (0 and 1 are saved, don't need to re-run)
parameter = 'VDB'
value = vdb[i]
simulation_tools.set_parameters(asc_file_path, parameter,
value, True)
parameter = 'VB'
value = vb[i]
simulation_tools.set_parameters(asc_file_path, parameter,
value, True)
results = simulation_tools.run_simulations()
print(i)
maxDiff[i] = results[1]
max_in[i] = results[0]
print(maxDiff[i])
i += 1
f.close()