Not sure if I'm using the right terms here, but for whatever reason, QBasic doesn't understand something along the lines of "x = y = z". It's limited to two.
To fix that, I did this:
IF sum(1) = sum(2) THEN
IF sum(2) = sum(3) THEN
IF sum(3) = sum2(1) THEN
IF sum2(1) = sum2(2) THEN
IF sum2(2) = sum2(3) THEN
IF sum2(3) = sum3 THEN
IF sum3 = sum4 THEN
PRINT "This is a Lo Shu Square, with all sums equaling"; sum(1)
ELSE
PRINT "This is not a Lo Shu Square."
END IF
END IF
END IF
END IF
END IF
END IF
END IF
END
Definitely works, but something tells me there's a simpler way to have it check if all of the sums equal the same. Any suggestions?
It would work if all comparisons where put on one line separated by AND like this:
REM code to shrink IFTHEN ladder:
IF sum(1) = sum(2) AND sum(2) = sum(3) AND sum(3) = sum2(1) AND sum2(1) = sum2(2) AND sum2(2) = sum2(3) AND sum2(3) = sum3 AND sum3 = sum4 THEN
PRINT "This is a Lo Shu Square, with all sums equaling"; sum(1)
ELSE
PRINT "This is not a Lo Shu Square."
END IF
END
You could also code the logic into a loop:
DIM testvals(8)
testvals(0) = sum(1)
testvals(1) = sum(2)
testvals(2) = sum(3)
testvals(3) = sum2(1)
testvals(4) = sum2(2)
testvals(5) = sum2(3)
testvals(6) = sum3
testvals(7) = sum4
DO
FOR i = 1+LBOUND(testvals) TO UBOUND(testvals)
IF testvals(i-1) <> testvals(i) THEN
PRINT "This is not a Lo Shu square."
EXIT DO
END IF
NEXT
PRINT "This is a Lo Shu square, with all sums equaling"; sum(1)
LOOP WHILE 1 = 0
This has a couple of benefits:
It's easier to spot a typo if you change the code.
You can always add and remove test values in similar cases. In this case, there's no need to do such a thing, but in some other cases, it may be beneficial to simply type testvals(8) = value and change the 8 to a 9 in the DIM line.
It short-circuits the comparison, meaning if the first condition is false, it stops checking and says it's not a Lo Shu Square, similar to a tower of IF-THEN-ELSE statements (where every ELSE is PRINT "This is not a Lo Shu square.") QB64's AND operator evaluates both operands, even if the first operand is 0 or another "false" value. This can be much faster, though you likely won't notice a difference in this case.
On the other hand, it does have some drawbacks:
It's an unusual pattern in QB64 to not use AND in a case like this. In fact, this is one very good reason why AND exists.
You can just as easily remove test values that are combined using AND with no need to renumber the items in the testvals array or change its dimensions.
Even if you have many test values, it's often better to write a small program that generates the IF a AND b AND c AND ... THEN ... END IF block yourself (or something similar to your IF-THEN tower to retain short-circuit behavior) and paste the output into your program's code where it's needed.
A simpler way to check arrays:
testvals(1) = sum(1)
testvals(2) = sum(2)
testvals(3) = sum(3)
testvals(4) = sum2(1)
testvals(5) = sum2(2)
testvals(6) = sum2(3)
testvals(7) = sum3
testvals(8) = sum4
FOR i = 1 TO 7
IF testvals(i) <> testvals(i + 1) THEN
f = -1
EXIT FOR
END IF
NEXT
IF f THEN
PRINT "This is not a Lo Shu square."
ELSE
PRINT "This is a Lo Shu square, with all sums equaling"; sum(1)
END IF
A simpler way to check a loop:
testvals(1) = sum(1)
testvals(2) = sum(2)
testvals(3) = sum(3)
testvals(4) = sum2(1)
testvals(5) = sum2(2)
testvals(6) = sum2(3)
testvals(7) = sum3
testvals(8) = sum4
FOR i = 1 TO 7
IF testvals(i) <> testvals(i + 1) THEN
PRINT "This is not a Lo Shu square."
END
END IF
NEXT
PRINT "This is a Lo Shu square, with all sums equaling"; sum(1)
Consolidate the logic into a function:
FUNCTION isLoShuSquare (sums() AS DOUBLE)
isLoShuSquare = 1
DIM i AS INTEGER
FOR i = 0 TO UBOUND(sums) - 1
IF sums(i) <> sums(i + 1) THEN
isLoShuSquare = 0
EXIT FOR
END IF
NEXT i
END FUNCTION
Then load the array and pass it to the function:
DIM sums(7) AS DOUBLE
DIM i AS INTEGER
i = 0
sums(i) = sum(1): i = i + 1
sums(i) = sum(2): i = i + 1
sums(i) = sum(3): i = i + 1
sums(i) = sum2(1): i = i + 1
sums(i) = sum2(2): i = i + 1
sums(i) = sum2(3): i = i + 1
sums(i) = sum3: i = i + 1
sums(i) = sum4
PRINT isLoShuSquare(sums())
Another way to check an array in a loop in a function:
DIM sums(8) AS DOUBLE
sums(1) = sum(1)
sums(2) = sum(2)
sums(3) = sum(3)
sums(4) = sum2(1)
sums(5) = sum2(2)
sums(6) = sum2(3)
sums(7) = sum3
sums(8) = sum4
IF isLoShuSquare(sums()) = 0 THEN
PRINT "This is not a Lo Shu square."
ELSE
PRINT "This is a Lo Shu square, with all sums equaling"; sum(1)
END IF
END
FUNCTION isLoShuSquare (sums() AS DOUBLE)
isLoShuSquare = -1
FOR i = 1 TO UBOUND(sums) - 1
IF sums(i) <> sums(i + 1) THEN
isLoShuSquare = 0
EXIT FUNCTION
END IF
NEXT
END FUNCTION
Related
Below is my implementation of a2c using PyTorch. Upon learning about backpropagation in PyTorch, I have known to zero_grad() the optimizer after each update iteration. However, there is still a RunTime error on second-time backpropagation.
def torchworker(number, model):
worker_env = gym.make("Taxi-v3").env
max_steps_per_episode = 2000
worker_opt = optim.Adam(lr=5e-4, params=model.parameters())
p_history = []
val_history = []
r_history = []
running_reward = 0
episode_count = 0
under = 0
start = time.time()
for i in range(2):
state = worker_env.reset()
episode_reward = 0
penalties = 0
drop = 0
print("Episode {} begins ({})".format(episode_count, number))
worker_env.render()
criterion = nn.SmoothL1Loss()
time_solve = 0
for _ in range(1, max_steps_per_episode):
#worker_env.render()
state = torch.tensor(state, dtype=torch.long)
action_probs = model.forward(state)[0]
critic_value = model.forward(state)[1]
val_history.append((state, critic_value[0]))
# Choose action
action = np.random.choice(6, p=action_probs.detach().numpy())
p_history.append(torch.log(action_probs[action]))
# Apply chosen action
state, reward, done, _ = worker_env.step(action)
r_history.append(reward)
episode_reward += reward
time_solve += 1
if reward == -10:
penalties += 1
elif reward == 20:
drop += 1
if done:
break
# Update running reward to check condition for solving
running_reward = (running_reward * (episode_count) + episode_reward) / (episode_count + 1)
# Calculate discounted returns
returns = deque(maxlen=3500)
discounted_sum = 0
for r in r_history[::-1]:
discounted_sum = r + gamma * discounted_sum
returns.appendleft(discounted_sum)
# Calculate actor losses and critic losses
loss_actor_value = 0
loss_critic_value = 0
history = zip(p_history, val_history, returns)
for log_prob, value, ret in history:
diff = ret - value[1]
loss_actor_value += -log_prob * diff
ret_tensor = torch.tensor(ret, dtype=torch.float32)
loss_critic_value += criterion(value[1], ret_tensor)
loss = loss_actor_value + 0.1 * loss_critic_value
print(loss)
# Update params
loss.backward()
worker_opt.step()
worker_opt.zero_grad()
# Log details
end = time.time()
episode_count += 1
if episode_count % 1 == 0:
worker_env.render()
if running_reward > -50: # Condition to consider the task solved
under += 1
if under > 5:
print("Solved at episode {} !".format(episode_count))
break
I believe there may be something to do with the architecture of my AC model, so I also include it here for reference.
class ActorCriticNetwork(nn.Module):
def __init__(self, num_inputs, num_hidden, num_actions):
super(ActorCriticNetwork, self).__init__()
self.embed = nn.Embedding(500, 10)
self.fc1 = nn.Linear(10, num_hidden * 2)
self.fc2 = nn.Linear(num_hidden * 2, num_hidden)
self.c = nn.Linear(num_hidden, 1)
self.fc3 = nn.Linear(num_hidden, num_hidden)
self.a = nn.Linear(num_hidden, num_actions)
def forward(self, x):
out = F.relu(self.embed(x))
out = F.relu(self.fc1(out))
out = F.relu(self.fc2(out))
critic = self.c(out)
out = F.relu(self.fc3(out.detach()))
actor = F.softmax(self.a(out), dim=-1)
return actor, critic
Would you please tell me what the mistake here is? Thank you in advance.
SOLVED: I forgot to clear the history of probabilities, action-values and rewards after iterations. It is clear why that would cause the issue, as the older elements would cause propagating through old dcgs.
I'm writing a program that calculates the Factorial of 5 numbers and output the results in a Tabular form but I keep getting Zeros.
Factorial Formula:. n! = nĂ—(n-1)!
I tried:
CLS
DIM arr(5) AS INTEGER
FOR x = 1 TO 5
INPUT "Enter Factors: ", n
NEXT x
f = 1
FOR i = 1 TO arr(n)
f = f * i
NEXT i
PRINT
PRINT "The factorial of input numbers are:";
PRINT
FOR x = 1 TO n
PRINT f(x)
NEXT x
END
and I'm expecting:
Numbers Factorrials
5 120
3 6
6 720
8 40320
4 24
You did some mistakes
FOR i = 1 TO arr(n)
where is n defined
you also never stored actual values into arr
PRINT f(x)
here you take from array f that is also not defined in your code
Possible solution to calculate arrays of factorials:
CLS
DIM arr(5) AS INTEGER
DIM ans(5) AS LONG
FOR x = 1 TO 5
INPUT "Enter Factors: ", arr(x)
f& = 1
FOR i = 1 TO arr(x)
f& = f& * i
NEXT i
ans(x) = f&
NEXT x
PRINT
PRINT "The factorial of input numbers are:";
PRINT
PRINT "Numbers", "Factorials"
FOR x = 1 TO 5
PRINT arr(x), ans(x)
NEXT x
END
I don't have a BASIC interpreter right in front of me, but I think this is what you're looking for:
CLS
DIM arr(5) AS INTEGER
DIM ans(5) AS LONG 'You need a separate array to store results in.
FOR x = 1 TO 5
INPUT "Enter Factors: ", arr(x)
NEXT x
FOR x = 1 to 5
f& = 1
FOR i = 1 TO arr(x)
f& = f& * i
NEXT i
ans(x) = f&
NEXT x
PRINT
PRINT "The factorial of input numbers are:";
PRINT
PRINT "Numbers", "Factorials"
FOR x = 1 TO 5
PRINT STR$(arr(x)), ans(x)
NEXT x
END
Just a comment though: In programming, you should avoid reusing variables unless you are short on memory. It can be done right, but it creates many opportunities for hard to find bugs in larger programs.
Possible solution to calculate arrays of factorials and square roots:
CLS
PRINT "Number of values";: INPUT n
DIM arr(n) AS INTEGER
DIM ans(n) AS LONG
FOR x = 1 TO n
PRINT "Enter value"; x;: INPUT arr(x)
f& = 1
FOR i = 1 TO arr(x)
f& = f& * i
NEXT i
ans(x) = f&
NEXT x
PRINT
PRINT "The factorial/square root of input numbers are:";
PRINT
PRINT "Number", "Factorial", "Squareroot"
FOR x = 1 TO n
PRINT arr(x), ans(x), SQR(arr(x))
NEXT x
END
I am trying to make a Flappy Bird AI where the agent tries to learn to pass through the pipes via genetic algorithms and neural network.
My implementation is that I am using a neural network with two inputs (horizontal distance from pipe and vertical distance from pipe opening), one hidden layer of 5 neurons, and one output layer.
The genetic algorithm evolves the agent by constantly changing one of the weights of the neural network per generation. (based on this GA implementation)
However I noticed that the flappy bird agent is failing to learn, to the point where it never even attempts to flap once (the entire time, it keeps falling at the beginning of every generation) all the way until the 485th generation (where an "maximum recursion depth exceeded" error occurs)
Genetic Algorithm + Neural Network functions:
def flap(playery, playerFlapAcc):
playerVelY = playerFlapAcc
playerFlapped = True
if sound:
SOUNDS['wing'].play()
return playerVelY, playerFlapped
def mutate(n):
global in_to_hidden
global hidden_to_hidden2
global hidden_to_out
layer_select = random.uniform(0,2)
print 'Changed:'
if layer_select == 0:
selector = int(random.uniform(0,5))
print in_to_hidden.params[selector]
in_to_hidden.params[selector] = in_to_hidden.params[selector] + random.uniform(-5,5)
print in_to_hidden.params[selector]
elif layer_select == 1:
selector = int(random.uniform(0,5))
print hidden_to_hidden.params[selector]
hidden_to_hidden2.params[selector] = hidden_to_hidden2.params[selector] + random.uniform(-5,5)
print hidden_to_hidden.params[selector]
else:
selector = int(random.uniform(0,3))
print hidden_to_out.params[selector]
hidden_to_out.params[selector] = hidden_to_out.params[selector] + random.uniform(-5,5)
print hidden_to_out.params[selector]
return n
def predict_action(rangex, error, playery, playerFlapAcc, playerVelY, playerFlapped, i):
global jumped
if i % 10 == 0:
pred = n.activate([rangex, error]).argmax()
if pred == 1:
jumped = True
playerVelY, playerFlapped = flap(playery, playerFlapAcc)
return playerVelY, playerFlapped
def initalize_nn():
global in_to_hidden
global hidden_to_hidden2
global hidden_to_out
# Old code (regression)
n = FeedForwardNetwork()
# n = buildNetwork( 2, 3, data.outdim, outclass=SoftmaxLayer )
inLayer = LinearLayer(2)
hiddenLayer = SigmoidLayer(5)
hiddenLayer2 = SigmoidLayer(5)
outLayer = LinearLayer(1)
n.addInputModule(inLayer)
n.addModule(hiddenLayer)
n.addModule(hiddenLayer2)
n.addOutputModule(outLayer)
in_to_hidden = FullConnection(inLayer, hiddenLayer)
hidden_to_hidden2 = FullConnection(hiddenLayer, hiddenLayer2)
hidden_to_out = FullConnection(hiddenLayer2, outLayer)
n.addConnection(in_to_hidden)
n.addConnection(hidden_to_hidden2)
n.addConnection(hidden_to_out)
n.sortModules()
return n
def fitness_fun(score, x_distance, error):
# Fitness function was designed so that the largest distance is
# the most fit. Before going through the first pipe, total distance traveled is the fitness.
# Once agent passed through the first pipe and earned a point,
# the amount of points it gained is the main determinant of the fitness score
if error != 0:
fitval = abs((100*score) + (x_distance/(2*abs(error))))
else:
fitval = abs(100*score) + x_distance*2
return fitval
Sample implementation in the game:
def mainGame(movementInfo):
global fitness
global old_fitness
global num_nn_parameters
global score
global disx
global first_time
global n
global old_n
global in_to_hidden
global hidden_to_hidden2
global hidden_to_out
global generation
global jumped
print 'generation: ', generation
generation = generation + 1
if first_time:
### Initalizing the neural network
n = initalize_nn()
ds = ClassificationDataSet(2, nb_classes=2)
z = 0
for val in in_to_hidden.params:
in_to_hidden.params[z] = random.uniform(-2,2)
z = z + 1
num_nn_parameters = z
old_nn = n
else:
# create new nn (but with old_nn saved)
n = mutate(old_n)
disx = 0
score = 0
first_time = False
# Print weights
print_all_weights()
####
'''
NOTES:
playerx = player's x position (57)
playery = player's height
upper_gap
lower_gap
center_cord
'''
pipeHeight = IMAGES['pipe'][0].get_height()
upper_gap = newPipe1[0]['y'] + pipeHeight
lower_gap = upper_gap + PIPEGAPSIZE
center_cord = upper_gap + ((lower_gap - upper_gap)/2)
########### The main loop ###########
#playerx = 140
while True:
i = i + 1
disx = disx + 1
# Error is determined by comparing the agent's y distance from the pipe opening
error = playery - center_cord
for event in pygame.event.get():
if event.type == QUIT or (event.type == KEYDOWN and event.key == K_ESCAPE):
pygame.quit()
sys.exit()
if event.type == KEYDOWN and (event.key == K_SPACE or event.key == K_UP):
if playery > -2 * IMAGES['player'][0].get_height():
playerVelY = playerFlapAcc
playerFlapped = True
if sound:
SOUNDS['wing'].play()
# check for crash here
crashTest = checkCrash({'x': playerx, 'y': playery, 'index': playerIndex},
upperPipes, lowerPipes)
if crashTest[0]:
fitness = fitness_fun(score, disx, error)
print '------------------- Game Over ---------------------'
print 'fitness: [', fitness, ']'
print 'old fit: [', old_fitness, ']'
print ''
print ''
print 'error: ', error
#print 'score: ', score
print 'range_x', rangex
print 'player_x: ', disx
print '----------------------------------------------------'
print ''
print ''
print ''
print ''
print ''
# If it turns out the old nn was better
if old_fitness > fitness:
# prevents the old but good nn from being overwritten
n = old_n
fitness = old_fitness
else:
print 'Better fitness discovered'
# store the good nn as the old_nn
old_n = n
old_fitness = fitness
return {
'y': playery,
'groundCrash': crashTest[1],
'basex': basex,
'upperPipes': upperPipes,
'lowerPipes': lowerPipes,
'score': score,
'playerVelY': playerVelY,
}
rangex = upperPipes[0]['x'] - 92
# Make prediction
playerVelY, playerFlapped = predict_action(rangex, error, playery, playerFlapAcc, playerVelY, playerFlapped, i)
Does anyone know the cause of this and how I can fix this?
I don't know why but I am getting this error:
Error in mr_lsbpex (line 3)
dlen = uint32(0) ;
Output argument "a" (and maybe others) not assigned during call to "E:\path\mr_lsbpex.m>mr_lsbpex"
I have tested "dlen = uint32(0) ;" in matlab enviorment (outside of this function) and everything was OK. Here is my code:
function a = mr_lsbpex ( r, p )
% extract from an array
dlen = uint32(0) ;
s = size (r) ;
rnd = rand (s(1),s(2)) ;
rd = 32 ;
rl = s(2) ;
for i=1:s(2)
if rnd(1,i)<rd/rl
d = bitget (round(r(1,i)/p),1);
dlen = bitset (dlen,rd,d);
rd = rd -1 ;
end
rl = rl -1 ;
end
if (dlen > 10000000 )
clear a ;
return ;
end
a = uint8(zeros(dlen,1)) ;
rd = double(dlen * 8) ;
rl = double(s(1)*s(2)-s(2)) ;
for i=2:s(1)
for j=1:s(2)
if rnd(i,j)<rd/rl
d = bitget (round(r(i,j)/p) ,1) ;
a = z_set_bit (a,rd,d) ;
rd = rd - 1 ;
end
rl = rl - 1 ;
end
end
Remember: a needs to be returned ALLWAYS!
The error is not in that specific line, but in the "whole" function itself.
Your problem is that Matlab thinks that a its not going to be created. And actually in some case it may not be created.
The following line in the beginning of your function should do the trick
a=0; % well, or a=NaN; or whatever you want to return
Additionally, don't clear a in if (dlen > 10000000 ).
Here is my code. The intent is I have a Wireshark capture saved to a particularly formatted text file. The MATLAB code is supposed to go through the Packets, dissect them for different protocols, and then make tables based on those protocols. I currently have this programmed for ETHERNET/IP/UDP/MODBUS. In this case, it creates a column in MBTable each time it encounters a new register value, and each time it comes across a change to that register value, it updates the value in that line of the table. The first column of MBTable is time, the registers start with the second column.
MBTable is preallocated to over 100,000 Rows (nol is very large), 10 columns before this code is executed. The actual data from a file I'm pulling into the table gets to about 10,000 rows and 4 columns and the code execution is so slow I have to stop it. The tic/toc value is calculated every 1000 rows and continues to increase exponentially with every iteration. It is a large loop, but I can't see where anything is growing in such a way that it would cause it to run slower with each iteration.
All variables get initialized up top (left out to lessen amount of code.
The variables eth, eth.ip, eth.ip.udp, and eth.ip.udp.modbus are all of type struct as is eth.header and eth.ip.header. WSID is a file ID from a .txt file opened earlier.
MBTable = zeros(nol,10);
tval = tic;
while not(feof(WSID))
packline = packline + 1;
fl = fl + 1;
%Get the next line from the file
MBLine = fgetl(WSID);
%Make sure line is not blank or short
if length(MBLine) >= 3
%Split the line into 1. Line no, 2. Data, 3. ASCII
%MBAll = strsplit(MBLine,' ');
%First line of new packet, if headers included
if strcmp(MBLine(1:3),'No.')
newpack = true;
newtime = false;
newdata = false;
stoppack = false;
packline = 1;
end
%If packet has headers, 2nd line contains timestamp
if newpack
Ordered = false;
if packline == 2;
newtime = true;
%MBstrs = strsplit(MBAll{2},' ');
packno = int32(str2double(MBLine(1:8)));
t = str2double(MBLine(9:20));
et = t - lastt;
if lastt > 0 && et > 0
L = L + 1;
MBTable(L,1) = t;
end
%newpack = false;
end
if packline > 3
dataline = int16(str2double(MBLine(1:4)));
packdata = strcat(packdata,MBLine(7:53));
end
end
else
%if t >= st
if packline > 3
stoppack = true;
newpack = false;
end
if stoppack
invalid = false;
%eth = struct;
eth.pack = packdata(~isspace(packdata));
eth.length = length(eth.pack);
%Dissect the packet data
eth.stbyte = 1;
eth.ebyte = eth.length;
eth.header.stbyte = 1;
eth.header.ebyte = 28;
%Ethernet Packet Data
eth.header.pack = eth.pack(eth.stbyte:eth.stbyte+27);
eth.header.dest = eth.header.pack(eth.header.stbyte:eth.header.stbyte + 11);
eth.header.src = eth.header.pack(eth.header.stbyte + 12:eth.header.stbyte + 23);
eth.typecode = eth.header.pack(eth.header.stbyte + 24:eth.header.ebyte);
if strcmp(eth.typecode,'0800')
eth.type = 'IP';
%eth.ip = struct;
%IP Packet Data
eth.ip.stbyte = eth.header.ebyte + 1;
eth.ip.ver = eth.pack(eth.ip.stbyte);
%IP Header length
eth.ip.header.length = 4*int8(str2double(eth.pack(eth.ip.stbyte+1)));
eth.ip.header.ebyte = eth.ip.stbyte + eth.ip.header.length - 1;
%Differentiated Services Field
eth.ip.DSF = eth.pack(eth.ip.stbyte + 2:eth.ip.stbyte + 3);
%Total IP Packet Length
eth.ip.length = hex2dec(eth.pack(eth.ip.stbyte+4:eth.ip.stbyte+7));
eth.ip.ebyte = eth.ip.stbyte + max(eth.ip.length,46) - 1;
eth.ip.pack = eth.pack(eth.ip.stbyte:eth.ip.ebyte);
eth.ip.ID = eth.pack(eth.ip.stbyte+8:eth.ip.stbyte+11);
eth.ip.flags = eth.pack(eth.ip.stbyte+12:eth.ip.stbyte+13);
eth.ip.fragoff = eth.pack(eth.ip.stbyte+14:eth.ip.stbyte+15);
%Time to Live
eth.ip.ttl = hex2dec(eth.pack(eth.ip.stbyte+16:eth.ip.stbyte+17));
eth.ip.typecode = eth.pack(eth.ip.stbyte+18:eth.ip.stbyte+19);
eth.ip.checksum = eth.pack(eth.ip.stbyte+20:eth.ip.stbyte+23);
%eth.ip.src = eth.pack(eth.ip.stbyte+24:eth.ip.stbyte+31);
eth.ip.src = ...
[num2str(hex2dec(eth.pack(eth.ip.stbyte+24:eth.ip.stbyte+25))),'.', ...
num2str(hex2dec(eth.pack(eth.ip.stbyte+26:eth.ip.stbyte+27))),'.', ...
num2str(hex2dec(eth.pack(eth.ip.stbyte+28:eth.ip.stbyte+29))),'.', ...
num2str(hex2dec(eth.pack(eth.ip.stbyte+30:eth.ip.stbyte+31)))];
eth.ip.dest = ...
[num2str(hex2dec(eth.pack(eth.ip.stbyte+32:eth.ip.stbyte+33))),'.', ...
num2str(hex2dec(eth.pack(eth.ip.stbyte+34:eth.ip.stbyte+35))),'.', ...
num2str(hex2dec(eth.pack(eth.ip.stbyte+36:eth.ip.stbyte+37))),'.', ...
num2str(hex2dec(eth.pack(eth.ip.stbyte+38:eth.ip.stbyte+39)))];
if strcmp(eth.ip.typecode,'11')
eth.ip.type = 'UDP';
eth.ip.udp.stbyte = eth.ip.stbyte + 40;
eth.ip.udp.src = hex2dec(eth.pack(eth.ip.udp.stbyte:eth.ip.udp.stbyte + 3));
eth.ip.udp.dest = hex2dec(eth.pack(eth.ip.udp.stbyte+4:eth.ip.udp.stbyte+7));
eth.ip.udp.length = hex2dec(eth.pack(eth.ip.udp.stbyte+8:eth.ip.udp.stbyte+11));
eth.ip.udp.checksum = eth.pack(eth.ip.udp.stbyte+12:eth.ip.udp.stbyte+15);
eth.ip.udp.protoID = eth.pack(eth.ip.udp.stbyte+20:eth.ip.udp.stbyte+23);
if strcmp(eth.ip.udp.protoID,'0000')
eth.ip.udp.proto = 'MODBUS';
%eth.ip.udp.modbus = struct;
eth.ip.udp.modbus.stbyte = eth.ip.udp.stbyte+16;
eth.ip.udp.modbus.transID = eth.pack(eth.ip.udp.modbus.stbyte:eth.ip.udp.modbus.stbyte+3);
eth.ip.udp.modbus.protoID = eth.ip.udp.protoID;
eth.ip.udp.modbus.length = int16(str2double(eth.pack(eth.ip.udp.modbus.stbyte + 8:eth.ip.udp.modbus.stbyte + 11)));
eth.ip.udp.modbus.UID = eth.pack(eth.ip.udp.modbus.stbyte + 12:eth.ip.udp.modbus.stbyte + 13);
eth.ip.udp.modbus.func = hex2dec(eth.pack(eth.ip.udp.modbus.stbyte + 14:eth.ip.udp.modbus.stbyte+15));
eth.ip.udp.modbus.register = eth.pack(eth.ip.udp.modbus.stbyte + 16: eth.ip.udp.modbus.stbyte+19);
%Number of words to a register, or the number of registers
eth.ip.udp.modbus.words = hex2dec(eth.pack(eth.ip.udp.modbus.stbyte+20:eth.ip.udp.modbus.stbyte+23));
eth.ip.udp.modbus.bytes = hex2dec(eth.pack(eth.ip.udp.modbus.stbyte+24:eth.ip.udp.modbus.stbyte+25));
eth.ip.udp.modbus.data = eth.pack(eth.ip.udp.modbus.stbyte + 26:eth.ip.udp.modbus.stbyte + 26 + 2*eth.ip.udp.modbus.bytes - 1);
%If func 16 or 23, loop through data/registers and add to table
if eth.ip.udp.modbus.func == 16 || eth.ip.udp.modbus.func == 23
stp = eth.ip.udp.modbus.bytes*2/eth.ip.udp.modbus.words;
for n = 1:stp:eth.ip.udp.modbus.bytes*2;
%Check for existence of register as a key?
if ~isKey(MBMap,eth.ip.udp.modbus.register)
MBCol = MBCol + 1;
MBMap(eth.ip.udp.modbus.register) = MBCol;
end
MBTable(L,MBCol) = hex2dec(eth.ip.udp.modbus.data(n:n+stp-1));
eth.ip.udp.modbus.register = dec2hex(hex2dec(eth.ip.udp.modbus.register)+1);
end
lastt = t;
end
%If func 4, make sure it is the response, then put
%data into table for register column
elseif false
%need code to handle serial to UDP conversion box
else
invalid = true;
end
else
invalid = true;
end
else
invalid = true;
end
if ~invalid
end
end
%end
end
%Display Progress
if int64(fl/1000)*1000 == fl
for x = 1:length(mess);
fprintf('\b');
end
%fprintf('Lines parsed: %i',fl);
mess = sprintf('Lines parsed: %i / %i',fl,nol);
fprintf('%s',mess);
%Check execution time - getting slower:
%%{
ext = toc(tval);
mess = sprintf('\nExecution Time: %f\n',ext);
fprintf('%s',mess);
%%}
end
end
ext = toc - exst;
Update: I updated my code above to remove the overloaded operators (disp and lt were replaced with mess and lastt)
Was asked to use the profiler, so I limited to 2000 lines in the table (added && L >=2000 to the while loop) to limit the execution time, and here are the top results from the profiler:
SGAS_Wireshark_Parser_v0p7_fulleth 1 57.110 s 9.714 s
Strcat 9187 29.271 s 13.598 s
Blanks 9187 15.673 s 15.673 s
Uigetfile 1 12.226 s 0.009 s
uitools\private\uigetputfile_helper 1 12.212 s 0.031 s
FileChooser.FileChooser>FileChooser.show 1 12.085 s 0.006s
...er>FileChooser.showPeerAndBlockMATLAB 1 12.056 s 0.001s
...nChooser>FileOpenChooser.doShowDialog 1 12.049 s 12.049 s
hex2dec 44924 2.944 s 2.702 s
num2str 16336 1.139 s 0.550 s
str2double 17356 1.025 s 1.025 s
int2str 16336 0.589 s 0.589 s
fgetl 17356 0.488 s 0.488 s
dec2hex 6126 0.304 s 0.304 s
fliplr 44924 0.242 s 0.242 s
It appears to be strcat calls that are doing it. I only explicitly call strcat on one line. Are some of the other string manipulations I'm doing calling strcat indirectly?
Each loop should be calling strcat the same number of times though, so I still don't understand why it takes longer and longer the more it runs...
also, hex2dec is called a lot, but is not really affecting the time.
But anyway, are there any other methods I can use the combine the strings?
Here is the issue:
The string (an char array in MATLAB) packdata was being resized and reallocated over and over again. That's what was slowing down this code. I did the following steps:
I eliminated the redundant variable packdata and now only use eth.pack.
I preallocated eth.pack and a couple "helper variables" of known lengths by running blanks ONCE for each before the loop ever starts
eth.pack = blanks(604);
thisline = blanks(47);
smline = blanks(32);
(Note: 604 is the maximum possible size of packdata based on headers + MODBUS protocol)
Then I created a pointer variable to point to the location of the last char written to packdata.
pptr = 1;
...
dataline = int16(str2double(MBLine(1:4)));
thisline = MBLine(7:53); %Always 47 characters
smline = [thisline(~isspace(thisline)),blanks(32-sum(~isspace(thisline)))]; %Always 32 Characters
eth.pack(pptr:pptr+31) = smline;
pptr = pptr + 32;
The above was inside the 'if packline > 3' block in place of the 'packdata =' statement, then at the end of the 'if stoppack' block was the reset statement:
pptr = 1; %Reset Pointer
FYI, not surprisingly this brought out other flaws in my code which I've mostly fixed but still need to finish. Not a big issue now as this loop executes lightning fast with these changes. Thanks to Yvon for helping point me in the right direction.
I kept thinking my huge table, MBTable was the issue... but it had nothing to do with it.