I'm trying to make a simple corona sdk game but I can't get it working.
I wanne make a score text field but I have a lot of problems.
The functions:
function points(num)
addPoints()
score = score + num
scoreTxt.text = "hoi"
scoreTxt:setReferencePoint(display.TopLeftReferencePoint)
end
function addPoints()
num = math.random(100, 350)
end
Some other information:
score = 50;
num = 50;
scoreTxt = display.newText ("Score:", 0, 0, "Helvetica", 20)
scoreTxt:setReferencePoint(display.TopLeftReferencePoint)
scoreTxt.x = display.screenOriginX + 10
scoreTxt.y = display.screenOriginX + 5
Thanks in advance :)
function points()
num=addPoints()
score = score + num
scoreTxt.text = "hoi"
scoreTxt:setReferencePoint(display.TopLeftReferencePoint)
end
function addPoints()
num = math.random(100, 350)
return num
end
How can you get value from that function.Try like this.
Related
I am getting this as an orange error - not sure what I have done wrong or whether this error is the reason that the code doesn't plot. I am brand new to Pine-script and any assistance would be invaluable. Many thanks in advance Alastair
//#version=5
indicator("PCY TEST4")
//Get User Inputs
fast_length = input(title="Fast Length", defval=12)
slow_length = input(title="Slow Length", defval=26)
src = input(title="Source", defval=close)
signal_length = input.int(title="Signal Smoothing", minval = 1, maxval = 50, defval = 9)
sma_source = input.string(title="Oscillator MA Type", defval="EMA", options=["SMA", "EMA"])
sma_signal = input.string(title="Signal Line MA Type", defval="EMA", options=["SMA", "EMA"])
//Variables
a = 0.33
PCY = 0.0
PCYi = 0.0
// Calculating
fast_ma = sma_source == "SMA" ? ta.sma(src, fast_length) : ta.ema(src, fast_length)
slow_ma = sma_source == "SMA" ? ta.sma(src, slow_length) : ta.ema(src, slow_length)
macd = fast_ma - slow_ma
minMacd=0.0
for i = 0 to (signal_length[1])
minMacd := ta.min(macd)
maxMacd=0.0
for i = 0 to (signal_length[1])
maxMacd := ta.max(macd)
//maxMacd = ta.min(macd)
//minMacd = ta.max(macd)
//signal = sma_signal == "SMA" ? ta.sma(macd, signal_length) : ta.ema(macd, signal_length)
//hist = macd - signal
delta = maxMacd-(fast_ma - slow_ma)/(maxMacd -minMacd)
for i = 0 to (signal_length)
PCYi := a*((delta - PCYi[1])+PCYi[1])
PCYi
//Plotting
plot(PCYi)
I think it's because you're calculating the min/max in a for loop
Those functions should (not mandatory but strongly recommended) be calculated at every candle instead
for i = 0 to (signal_length[1])
minMacd := ta.min(macd)
maxMacd=0.0
for i = 0 to (signal_length[1])
maxMacd := ta.max(macd)
If you want to calculate the min/max over a X period of time, maybe use the ta.highest/ta.lowest functions instead :)
And of course, those 2 should be called at every candle (i.e. not in a if, for,... statement)
I have a problem with my code, I want to evaluate a Report with Charts.
What my Macro currently does is, Create for every single column a Row for a nominal, upper, lower tolerance. Then It creates with this values a chart.
After this it starts with the Sorting and then it removes the Marker Points, but here my Problems already start.
I would like to create the charts later for example on pos A100 or A50 or something.
Then the Marker Points, I would like to keep the Points on the result line but not on the 3 created, but I found no way
Remove the Markers, but it removes all, i would really like to remove them only for
FullSeriesCollection(2).format.Line
FullSeriesCollection(3).format.Line
FullSeriesCollection(4).format.Line
Would be nice if someone would have an idea.. :)
Thanks in advance,
' Unload UFormTools
UFormTools.Hide
Application.ScreenUpdating = False
Sheets("Original Values").Select
Dim lngC As Long, lngR As Long
Dim i As Long
Dim c As Byte
Application.ScreenUpdating = False
With ActiveSheet
lngC = (.Cells(17, 4).End(xlToRight).Column - 4) * 4
For i = 4 To lngC Step 4
lngR = .Cells(.Rows.Count, i).End(xlUp).Row
For c = 1 To 3
.Columns(i + c).EntireColumn.Insert
Next c
.Cells(17, i).AutoFill Destination:=.Range(.Cells(17, i), .Cells(17, i + 3)), Type:=xlFillCopy
.Range(.Cells(28, i + 1), .Cells(lngR, i + 1)).Value = .Cells(18, i).Value
.Range(.Cells(28, i + 2), .Cells(lngR, i + 2)).Value = .Cells(18, i).Value + .Cells(19, i).Value
.Range(.Cells(28, i + 3), .Cells(lngR, i + 3)).Value = .Cells(18, i).Value + .Cells(20, i).Value
.Shapes.AddChart2(332, xlLineMarkers).Select
With ActiveChart
.SetSourceData Source:=Union(ActiveSheet.Range(ActiveSheet.Cells(17, i), ActiveSheet.Cells(17, i + 3)), _
ActiveSheet.Range(ActiveSheet.Cells(28, i), ActiveSheet.Cells(lngR, i + 3)))
' .Legend.Delete
.ChartTitle.Text = ActiveSheet.Cells(17, i).Value
.ChartTitle.format.TextFrame2.TextRange.Characters.Text = ActiveSheet.Cells(17, i).Value
With .ChartTitle.format.TextFrame2.TextRange.Characters(1, Len(ActiveSheet.Cells(17, i).Value)).ParagraphFormat
.TextDirection = msoTextDirectionLeftToRight
.Alignment = msoAlignCenter
End With
With .FullSeriesCollection(3).format.Line
.Visible = msoTrue
.ForeColor.RGB = RGB(255, 0, 0)
.Transparency = 0
End With
With .FullSeriesCollection(4).format.Line
.Visible = msoTrue
.ForeColor.RGB = RGB(255, 0, 0)
.Transparency = 0
End With
With .FullSeriesCollection(2).format.Line
.Visible = msoTrue
.ForeColor.ObjectThemeColor = msoThemeColorText1
.ForeColor.TintAndShade = 0
.ForeColor.Brightness = 0
.Transparency = 0
.Visible = msoTrue
.DashStyle = msoLineDash
.Weight = 1.5
End With
With .FullSeriesCollection(1).format.Line
.Visible = msoTrue
.Weight = 3
End With
.FullSeriesCollection(1).Smooth = True
.Axes(xlValue).MinimumScaleIsAuto = True
.Axes(xlValue).MinimumScaleIsAuto = True
End With
Next i
End With
' Sort and Arrange Charts, but another Position to Start would be nice.. (for example A100)
Dim MyWidth As Single, MyHeight As Single
Dim NumWide As Long
Dim iChtIx As Long, iChtCt As Long
MyWidth = 300
MyHeight = 200
NumWide = 4
iChtCt = ActiveSheet.ChartObjects.Count
For iChtIx = 1 To iChtCt
With ActiveSheet.ChartObjects(iChtIx)
.Width = MyWidth
.Height = MyHeight
.Left = ((iChtIx - 1) Mod NumWide) * MyWidth
.Top = Int((iChtIx - 1) / NumWide) * MyHeight
End With
Next
' Remove the Markers, but it removes all, i would really like to remove them only for
' FullSeriesCollection(2).format.Line
' FullSeriesCollection(3).format.Line
' FullSeriesCollection(4).format.Line
Dim cht As ChartObject
Dim srs As Series
Dim MarkerCount As Long
For Each cht In ActiveSheet.ChartObjects
cht.Activate
For Each srs In ActiveChart.SeriesCollection
If srs.MarkerStyle <> xlMarkerStyleNone Then
srs.MarkerStyle = xlMarkerStyleNone
MarkerCount = MarkerCount + 1
End If
Next srs
Next cht
Range("A1").Select
Application.ScreenUpdating = True
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.
What I'm trying to do is take numerous(up to 48) 1024x768 images that are color coded images(weather maps, the precip overlay) and add up the precip to fall over the course of time. When I run into non-precip I want to take a box 5x5 around the pixel in question and average the value and use that value as the value of the pixel in question.
I can do this but it takes a long time to accomplish it. I have heard numpy could improve the speed but I still haven't been able to wrap my mind around how it going to improve the speed given the sequence of events that have to take place. It seems like I would still have to do it pixel by pixel. I've included an idea of the code I'm using to accomplish this SLOWLY.
I have this actually as two separate program, one to download the images and the other does the image processing(working up toward merging the two programs in the near future, just trying to get all the bugs worked out before the merger.) Hence some of the download coding may look a little strange. I figure I could probably write the file straight to a variable but I haven't been doing it that way so I stuck with a bit longer approach.
Is there anyway of increasing the speed? I don't see anyway of avoiding pixel by pixel due to the color coding scheme in place(look at the color bar in the lower left it shows the full color scheme...I only included part of it for demo purposes in the coding below.) Some of the coding may be a bit rough since I chopped from the two programs and put the important parts in here...it shows what I'm currently doing and gives the full idea of how I'm going about doing it.
Also, if you happen to see this three to four or more days after it was posted you would need to change the date in the download link to the current date. The files are only kept on the server for 3-4 days before they are removed.
from PIL import Image
import time
import urllib
import os
pathstr = '/'
url = 'http://mag.ncep.noaa.gov/GemPakTier/MagGemPakImages/gfs/20140216/00/gfs_namer_006_1000_500_thick.gif'
urllib.urlretrieve(url,str(pathstr + '20140216006.gif'))
url = 'http://mag.ncep.noaa.gov/GemPakTier/MagGemPakImages/gfs/20140216/00/gfs_namer_012_1000_500_thick.gif'
urllib.urlretrieve(url,str(pathstr + '20140216012.gif'))
url = 'http://mag.ncep.noaa.gov/GemPakTier/MagGemPakImages/gfs/20140216/00/gfs_namer_018_1000_500_thick.gif'
urllib.urlretrieve(url,str(pathstr + '20140216018.gif'))
url = 'http://mag.ncep.noaa.gov/GemPakTier/MagGemPakImages/gfs/20140216/00/gfs_namer_024_1000_500_thick.gif'
urllib.urlretrieve(url,str(pathstr + '20140216024.gif'))
class Convert():
def __init__(self):
self.colorscale2 = [(255,255,255),(127,255,0),(0,205,0),(145,44,238),(16,78,139),
(30,144,255),(0,178,238),(0,238,238),(137,104,205),(0,139,0),
(139,0,139),(139,0,0),(205,0,0),(238,64,0),(255,127,0),(205,133,0),
(255,215,0),(238,238,0),(255,255,0),(139,71,38),(255,0,0),(0,0,255),(0,0,0)]
self.x = 0
self.y = 0
self.grid = 0
self.moist = 0
self.scan = 0
self.turn = 0
self.precip = {}
start = time.time()
for i in range(6, 30, 6):
if i < 10:
filename = '/2014021600' + str(i) + '.gif'
else:
filename = '/201402160' + str(i) + '.gif'
self.im1 = Image.open(filename).convert('RGB')
self.image = self.im1.getdata()
self.size = width, height = self.im1.size
self.coordinates = self.x,self.y = width, height
self.getprecip()
self.turn = 1
print (time.time()-start)
def getprecip(self):
for self.x in range(81, 950):
for self.y in range(29, 749):
if self.turn == 0:
self.moist = 0
else:
self.moist = self.precip[self.x,self.y]
self.coordinates = self.x,self.y
self.scan = 0
self.imagescan()
if self.turn == 0:
self.precip[self.x,self.y] = self.moist
else:
self.precip[self.x,self.y] += self.moist
def imagescan(self):
if self.image[(self.y * 1024) + self.x] == self.colorscale2[0]:
self.moist =0
self.grid -=1
elif self.image[(self.y * 1024) + self.x] == self.colorscale2[1]:
self.moist =.01
elif self.image[(self.y * 1024) + self.x] == self.colorscale2[2]:
self.moist =.1
elif self.image[(self.y * 1024) + self.x] == self.colorscale2[3]:
self.moist =.25
elif self.image[(self.y * 1024) + self.x] == self.colorscale2[4]:
self.moist =.5
#on and on through self.colorscale2[18]
if self.scan == 1:
self.grid += 1
if self.scan == 0:
x = self.x
y = self.y
self.deliso540()
self.x = x
self.y = y
def deliso540(self):
self.grid = 1
self.scan = 1
for p in range(self.x-2,self.x+2):
for q in range(self.y-2,self.y+2):
self.x = p
self.y = q
self.imagescan()
self.moist = self.moist / self.grid
I am developing a financial app and require IRR (in-built functionality of Excel) calculation and found such great tutorials in C here and such answer in C# here.
I implemented code of the C language above, but it gives a perfect result when IRR is in positive. It is not returning a negative value when it should be. Whereas in Excel =IRR(values,guessrate) returns negative IRR as well for some values.
I have referred to code in above C# link too, and it seems that it follows good procedures and returns errors and also hope that it returns negative IRR too, the same as Excel. But I am not familiar with C#, so I am not able to implement the same code in Objective-C or C.
I am writing C code from the above link which I have implemented for helping you guys.
#define LOW_RATE 0.01
#define HIGH_RATE 0.5
#define MAX_ITERATION 1000
#define PRECISION_REQ 0.00000001
double computeIRR(double cf[], int numOfFlows)
{
int i = 0, j = 0;
double m = 0.0;
double old = 0.00;
double new = 0.00;
double oldguessRate = LOW_RATE;
double newguessRate = LOW_RATE;
double guessRate = LOW_RATE;
double lowGuessRate = LOW_RATE;
double highGuessRate = HIGH_RATE;
double npv = 0.0;
double denom = 0.0;
for (i=0; i<MAX_ITERATION; i++)
{
npv = 0.00;
for (j=0; j<numOfFlows; j++)
{
denom = pow((1 + guessRate),j);
npv = npv + (cf[j]/denom);
}
/* Stop checking once the required precision is achieved */
if ((npv > 0) && (npv < PRECISION_REQ))
break;
if (old == 0)
old = npv;
else
old = new;
new = npv;
if (i > 0)
{
if (old < new)
{
if (old < 0 && new < 0)
highGuessRate = newguessRate;
else
lowGuessRate = newguessRate;
}
else
{
if (old > 0 && new > 0)
lowGuessRate = newguessRate;
else
highGuessRate = newguessRate;
}
}
oldguessRate = guessRate;
guessRate = (lowGuessRate + highGuessRate) / 2;
newguessRate = guessRate;
}
return guessRate;
}
I have attached the result for some value which are different in Excel and the above C language code.
Values: Output of Excel: -33.5%
1 = -18.5, Output of C code: 0.010 or say (1.0%)
2 = -18.5,
3 = -18.5,
4 = -18.5,
5 = -18.5,
6 = 32.0
Guess rate: 0.1
Since low_rate and high_rate are both positive, you're not able to get a negative score. You have to change:
#define LOW_RATE 0.01
to, for example,
#define LOW_RATE -0.5