def geneticOptimizer(ws, create, numGenerations, numSeeds, numChildrenPerSeed,
maxNumRandNodes, maxNumRandTubes, weightMultiplier,
maxDispOfAnyTargetNode, maxAvgDisp, maxWeight):
global webPrintOut
global timeLeft
# Plotting parameters
# ----------------------------
finalDisplacementScaling = 15
# ----------------------------
end = "false"
currentDateTime = datetime.datetime.now()
workingDir = os.getcwd()
simFolderPath = "%s\\sim\\static\\results\\%i" % (workingDir,
int(ws.room_name))
if os.path.isdir(simFolderPath) is False:
os.mkdir(simFolderPath)
consOutPath = "%s\\consoleOutput.txt" % simFolderPath
consoleOutput = open(consOutPath, "w")
def timeRemaining(left):
global timeLeft
timeLeft = '%.1f' % left
def printOut(line):
consoleOutput.write(line)
consoleOutput.write("\n")
global webPrintOut
webPrintOut += (line + "\n")
def printFile(line):
consoleOutput.write(line)
consoleOutput.write("\n")
printFile("--PARAMETERS--")
printFile("\nNumber of Generations: %i" % numGenerations)
printFile("Number of Surviving Seeds Per Generation: %i" % numSeeds)
printFile("Number of Children Per Seed Per Generation: %i" %
numChildrenPerSeed)
numFramesAnalyzed = numGenerations * numSeeds * numChildrenPerSeed
printOut("\nYou have elected to analyze %i frames" % numFramesAnalyzed)
printOut("across %i generations (i.e. %i per generation)" %
(numGenerations, int(numFramesAnalyzed / numGenerations)))
printFile("\nMaximum number of mutated tubes per individual: %i" %
maxNumRandTubes)
printFile("Maximum number of mutated nodes per individual: %i" %
maxNumRandNodes)
printFile(
"\nMaximum displacement allowed for any target node: %.5f inches" %
maxDispOfAnyTargetNode)
printFile(
"Maximum average displacement allowed for all target nodes: %.5f inches"
% maxAvgDisp)
printFile("Maximum weight allowed: %.3f pounds" % maxWeight)
printFile("\nFrame mass is weighted at %f in the objective function" %
weightMultiplier)
def sortingKey(elem):
return elem[0]
# Time the simulation
start = time.time()
# Set up graphs (change size of figure's window using the first line below)
plt.tight_layout()
fig = plt.figure(figsize=(18, 3), dpi=100)
grid = plt.GridSpec(1, 6, wspace=1)
ax1 = fig.add_subplot(grid[:, 0:2], title="Score/Weight vs Generations")
ax1.set_ylabel('Objective Function Score')
ax2 = fig.add_subplot(grid[:, 2:4],
title="Avg Displacement vs Generations")
ax2.set_ylabel('Inches')
ax3 = fig.add_subplot(grid[:, 4:6], title="Weight vs Generations")
ax3.set_ylabel('Pounds')
fig3D = plt.figure(figsize=(9, 7), dpi=100)
ax4 = fig3D.add_subplot(1, 1, 1, projection='3d')
ax4.view_init(azim=-135, elev=35)
ax1.grid()
ax2.grid()
ax3.grid()
ax4.xaxis.set_pane_color((1.0, 1.0, 1.0, 0.0))
ax4.yaxis.set_pane_color((1.0, 1.0, 1.0, 0.0))
ax4.zaxis.set_pane_color((1.0, 1.0, 1.0, 0.0))
ax4.xaxis._axinfo["grid"]['color'] = (1, 1, 1, 0)
ax4.yaxis._axinfo["grid"]['color'] = (1, 1, 1, 0)
ax4.zaxis._axinfo["grid"]['color'] = (1, 1, 1, 0)
# Initialize variables
maxScorePerWeight = 0
averageDisp = 0
maxScoresPerWeight = []
weights = []
averageDisps = []
iterations = []
baseFrame = createFrame(create)
baseFrameScorePerWeight, dispList, baseFrameAvgDisp = baseFrame.solveAllLoadCases(
weightMultiplier)
printOut("\nBase Frame Weight: %.3f" % baseFrame.weight)
printOut("Base Frame Score: %.3f" % baseFrameScorePerWeight)
printOut("Base Frame Avg. Disp.: %.5f" % baseFrameAvgDisp)
printOut("Base Frame Max Disp of A Target Node: %.5f" % max(dispList))
maxScoresPerWeight.append(baseFrameScorePerWeight)
weights.append(baseFrame.weight)
averageDisps.append(baseFrameAvgDisp)
iterations.append(0)
maxFrame = baseFrame
errorFlag = False
seeds = []
for i in range(numSeeds):
seeds.append(maxFrame)
ax1.plot(iterations, maxScoresPerWeight)
ax2.plot(iterations, averageDisps)
ax3.plot(iterations, weights)
maxFrame.plotAni(ax4)
# Sends live sim data to webpage
figHTML = fig_to_html(fig, figid="plot2D")
sp = figHTML.split('<script>')
div = sp[0].split('</style>')
figDiv = div[1]
script = sp[1].split('</script>')
figScript = script[0]
path = "%s\\sim\\static\\results\\%i" % (workingDir, int(ws.room_name))
if os.path.isdir(path) is False:
os.mkdir(path)
imgPath = path + "\\images"
if os.path.isdir(imgPath) is False:
os.mkdir(imgPath)
fig3DPath = path + "\\images\\fig3D-%i.png" % 0
fig3D.savefig(fig3DPath, pad_inches=0)
webPrintOut = textile.textile(webPrintOut, html_type="xhtml")
ws.send(text_data=json.dumps({
'end': end,
'iter': '0',
'figDiv': figDiv,
'figScript': figScript,
'webPrintOut': webPrintOut,
'timeLeft': timeLeft
}))
webPrintOut = ""
printFile("\n--START--")
for gen in range(1, numGenerations + 1):
# Generate generation individuals
if gen is 1:
startOneGen = time.time()
individuals = []
for seed in seeds:
theSameInd = copy.deepcopy(seed)
individuals.append(theSameInd)
for i in range(1, numChildrenPerSeed):
individual = copy.deepcopy(seed)
randomizeThicknessNotGeometry = random.choice((True, False))
if randomizeThicknessNotGeometry:
numRandTubes = random.randint(1, maxNumRandTubes)
for j in range(numRandTubes):
individual.randomizeThicknessOfRandomTube()
else:
numRandNodes = random.randint(1, maxNumRandNodes)
for j in range(numRandNodes):
individual.randomizeLocationOfRandomNode()
individuals.append(individual)
# Solve generation individuals
sortingList = []
for i in range(len(individuals)):
individual = individuals.__getitem__(i)
scorePerWeight, dispList, avgDisp = individual.solveAllLoadCases(
weightMultiplier)
if (individual.weight < maxWeight
and maxDispOfAnyTargetNode > max(dispList)
and maxAvgDisp > avgDisp):
tuple = (scorePerWeight, avgDisp, individual)
sortingList.append(tuple)
if len(sortingList) is 0:
printOut("--ERROR--")
printOut(
"Check that your maxWeight, maxDispOfAnyTargetNode and maxAvgDisp are not set too low"
)
errorFlag = True
break
sortingList.sort(key=sortingKey, reverse=True)
seeds.clear()
for i in range(numSeeds):
seeds.append(sortingList.__getitem__(i)[2])
bestInd = sortingList.__getitem__(0)
bestIndScore = bestInd[0]
bestIndAvgDisp = bestInd[1]
bestIndFrame = bestInd[2]
if maxScorePerWeight < sortingList.__getitem__(0)[0]:
maxScorePerWeight = bestIndScore
averageDisp = bestIndAvgDisp
maxFrame = bestIndFrame
maxScoresPerWeight.append(maxScorePerWeight)
averageDisps.append(averageDisp)
iterations.append(gen)
weights.append(maxFrame.weight)
ax1.plot(iterations, maxScoresPerWeight)
ax2.plot(iterations, averageDisps)
ax3.plot(iterations, weights)
maxFrame.plotAni(ax4)
if gen is 1:
endOneGen = time.time()
minutesPerGen = (endOneGen - startOneGen) / 60
print(
"\nSimulation will take an estimated %.1f minutes to complete"
% (minutesPerGen * (numGenerations + 1)))
printOut("\n")
printOut("Generation No. %i" % gen)
printOut("Max Score Per Weight:\t\t%.3f" % maxScorePerWeight)
printOut("Avg Disp. of Target Nodes:\t%.5f" % averageDisp)
printOut("Total Weight:\t\t\t%.3f" % maxFrame.weight)
timeToGo = (minutesPerGen * numGenerations) - (minutesPerGen *
(gen - 1))
timeRemaining(timeToGo)
print("\n~%.1f minutes remaining..." % timeToGo)
# Sends live sim data to webpage
figHTML = fig_to_html(fig, figid="plot2D")
sp = figHTML.split('<script>')
div = sp[0].split('</style>')
figDiv = div[1]
script = sp[1].split('</script>')
figScript = script[0]
path = "%s\\sim\\static\\results\\%i" % (workingDir, int(ws.room_name))
if os.path.isdir(path) is False:
os.mkdir(path)
fig3DPath = path + "\\images\\fig3D-%i.png" % gen
fig3D.savefig(fig3DPath, pad_inches=0)
webPrintOut = textile.textile(webPrintOut, html_type="xhtml")
ws.send(text_data=json.dumps({
'end': end,
'iter': str(gen),
'figDiv': figDiv,
'figScript': figScript,
'webPrintOut': webPrintOut,
'timeLeft': timeLeft
}))
webPrintOut = ""
ax1.plot(iterations, maxScoresPerWeight)
ax2.plot(iterations, averageDisps)
ax3.plot(iterations, weights)
maxFrame.plotAni(ax4)
maxFrame.toTextFile(simFolderPath + "\createFrame.txt")
if not errorFlag:
printOut("\n--FINISHED--")
printOut("\n--STATS--")
end = time.time()
minutesTaken = (end - start) / 60
printOut("\nMinutes taken for simulation to complete: %.1f" %
minutesTaken)
printOut("That's %.2f frames per second!" % (numFramesAnalyzed /
(minutesTaken * 60)))
printOut("\nTotal Number of Frames Analyzed: %i" % numFramesAnalyzed)
printOut("\nThe best frame's score was %.3f" %
(maxScorePerWeight - baseFrameScorePerWeight))
printOut("better than the original seed frame")
printOut("\nThe weight of the best frame was")
printOut("%.2f pounds less than the original seed frame" %
(baseFrame.weight - maxFrame.weight))
printOut(
"\nThe avg. displacement of all target nodes for the best frame was"
)
printOut("%.5f inches less than the original seed frame" %
(baseFrameAvgDisp - averageDisp))
# Plot graphs and frame/displacements
figPath = '%s\\graph.png' % simFolderPath
fig.savefig(figPath, pad_inches=0)
for loadCase in LoadCases.listLoadCases:
maxFrame.setLoadCase(loadCase)
figPath = '%s\\%s.png' % (simFolderPath, loadCase.name)
maxFrame.solve(weightMultiplier)
maxFrame.plot(finalDisplacementScaling, figPath)
plt.close(fig)
end = "true"
timeLeft = 0
ws.send(text_data=json.dumps({'end': end, 'timeLeft': timeLeft}))
consoleOutput.close()
import smtplib, ssl
smtp_server = "smtp.gmail.com"
port = 587 # For starttls
sender_email = "*****@*****.**"
password = '******'
# Create a secure SSL context
context = ssl.create_default_context()
# Try to log in to server and send email
try:
server = smtplib.SMTP(smtp_server, port)
server.ehlo() # Can be omitted
server.starttls(context=context) # Secure the connection
server.ehlo() # Can be omitted
server.login(sender_email, password)
sender_email = "*****@*****.**"
receiver_email = "*****@*****.**"
message = "Frame Simulation Complete!"
server.sendmail(sender_email, receiver_email, message)
except Exception as e:
# Print any error messages to stdout
print(e)
finally:
server.quit()
ax1.grid()
ax2.grid()
ax3.grid()
# Initialize variables
maxScorePerWeight = 0
averageDisp = 0
maxScoresPerWeight = []
weights = []
averageDisps = []
iterations = []
if useOriginalBaseFrame:
baseFrame = createBaseFrame()
else:
baseFrame = createFrame()
baseFrameScorePerWeight, dispList, baseFrameAvgDisp = baseFrame.solveAllLoadCases(weightMultiplier)
printOut("\nBase Frame Weight: %.3f" % baseFrame.weight)
printOut("Base Frame Score: %.3f" % baseFrameScorePerWeight)
printOut("Base Frame Avg. Disp.: %.5f" % baseFrameAvgDisp)
printOut("Base Frame Max Disp of A Target Node: %.5f" % max(dispList))
maxScoresPerWeight.append(baseFrameScorePerWeight)
weights.append(baseFrame.weight)
averageDisps.append(baseFrameAvgDisp)
iterations.append(0)
maxFrame = baseFrame
errorFlag = False
seeds = []
for i in range(numSeeds):
def frameToNodeString(create):
frame = createFrame(create)
return textile.textile(frame.toString('nodes'), html_type="xhtml")