I found 2 scripts in tradingview and added them to my script, however, it didn't work. I lost a lot of time. Can someone help me convert them to version 4? Thank you. Have a nice day!!!
//#version=2
////////////////////////////////////////////////////////////
// Copyright by HPotter v1.0 09/03/2018
// Linear Regression Intercept is one of the indicators calculated by using the
// Linear Regression technique. Linear regression indicates the value of the Y
// (generally the price) when the value of X (the time series) is 0. Linear
// Regression Intercept is used along with the Linear Regression Slope to create
// the Linear Regression Line. The Linear Regression Intercept along with the Slope
// creates the Regression line.
////////////////////////////////////////////////////////////
study(title="Line Regression Intercept", overlay = true)
Length = input(14, minval=1)
xSeria = input(title="Source", type=source, defval=close)
xX = Length * (Length - 1) * 0.5
xDivisor = xX * xX - Length * Length * (Length - 1) * (2 * Length - 1) / 6
xXY = 0
for i = 0 to Length-1
xXY := xXY + (i * xSeria[i])
xSlope = (Length * xXY - xX * sum(xSeria, Length)) / xDivisor
xLRI = (sum(xSeria, Length) - xSlope * xX) / Length
plot(xLRI, color=blue, title="LRI")
//Author - Rajandran R
//www.marketcalls.in
study("Supertrend V1.0 - Buy or Sell Signal", overlay = true)
Factor=input(3, minval=1,maxval = 100)
Pd=input(7, minval=1,maxval = 100)
Up=hl2-(Factor*atr(Pd))
Dn=hl2+(Factor*atr(Pd))
TrendUp=close[1]>TrendUp[1]? max(Up,TrendUp[1]) : Up
TrendDown=close[1]<TrendDown[1]? min(Dn,TrendDown[1]) : Dn
Trend = close > TrendDown[1] ? 1: close< TrendUp[1]? -1: nz(Trend[1],1)
Tsl = Trend==1? TrendUp: TrendDown
linecolor = Trend == 1 ? green : red
plot(Tsl, color = linecolor , style = line , linewidth = 2,title = "SuperTrend")
plotshape(cross(close,Tsl) and close>Tsl , "Up Arrow", shape.triangleup,location.belowbar,green,0,0)
plotshape(cross(Tsl,close) and close<Tsl , "Down Arrow", shape.triangledown , location.abovebar, red,0,0)
//plot(Trend==1 and Trend[1]==-1,color = linecolor, style = circles, linewidth = 3,title="Trend")
plotarrow(Trend == 1 and Trend[1] == -1 ? Trend : na, title="Up Entry Arrow", colorup=lime, maxheight=60, minheight=50, transp=0)
plotarrow(Trend == -1 and Trend[1] == 1 ? Trend : na, title="Down Entry Arrow", colordown=red, maxheight=60, minheight=50, transp=0)
//#version=4
////////////////////////////////////////////////////////////
// Copyright by HPotter v1.0 09/03/2018
// Linear Regression Intercept is one of the indicators calculated by using the
// Linear Regression technique. Linear regression indicates the value of the Y
// (generally the price) when the value of X (the time series) is 0. Linear
// Regression Intercept is used along with the Linear Regression Slope to create
// the Linear Regression Line. The Linear Regression Intercept along with the Slope
// creates the Regression line.
////////////////////////////////////////////////////////////
study(title="Line Regression Intercept", overlay=true)
Length = input(14, minval=1)
xSeria = input(title="Source", type=input.source, defval=close)
xX = Length * (Length - 1) * 0.5
xDivisor = xX * xX - Length * Length * (Length - 1) * (2 * Length - 1) / 6
xXY = 0.
for i = 0 to Length - 1 by 1
xXY := xXY + i * xSeria[i]
xXY
xSlope = (Length * xXY - xX * sum(xSeria, Length)) / xDivisor
xLRI = (sum(xSeria, Length) - xSlope * xX) / Length
plot(xLRI, color=color.blue, title="LRI")
//#version=4
//Author - Rajandran R
//www.marketcalls.in
study("Supertrend V1.0 - Buy or Sell Signal", overlay=true)
Factor = input(3, minval=1, maxval=100)
Pd = input(7, minval=1, maxval=100)
Up = hl2 - Factor * atr(Pd)
Dn = hl2 + Factor * atr(Pd)
TrendUp = Up
TrendUp := close[1] > TrendUp[1] ? max(Up, TrendUp[1]) : Up
TrendDown = Dn
TrendDown := close[1] < TrendDown[1] ? min(Dn, TrendDown[1]) : Dn
Trend = int(na)
Trend := close > TrendDown[1] ? 1 : close < TrendUp[1] ? -1 : nz(Trend[1], 1)
Tsl = Trend == 1 ? TrendUp : TrendDown
linecolor = Trend == 1 ? color.green : color.red
plot(Tsl, color=linecolor, style=plot.style_line, linewidth=2, title="SuperTrend")
plotshape(cross(close, Tsl) and close > Tsl, "Up Arrow", shape.triangleup, location.belowbar, color.green, 0, 0)
plotshape(cross(Tsl, close) and close < Tsl, "Down Arrow", shape.triangledown, location.abovebar, color.red, 0, 0)
//plot(Trend==1 and Trend[1]==-1,color = linecolor, style = circles, linewidth = 3,title="Trend")
plotarrow(Trend == 1 and Trend[1] == -1 ? Trend : na, title="Up Entry Arrow", colorup=color.lime, maxheight=60, minheight=50, transp=0)
plotarrow(Trend == -1 and Trend[1] == 1 ? Trend : na, title="Down Entry Arrow", colordown=color.red, maxheight=60, minheight=50, transp=0)
Related
I'm trying to make a strategy of an indicator, but I get the error: Line 73: Cannot call 'operator >' with argument 'expr0'='call 'alertcondition' (void)'. An argument of 'void' type was used but a 'const float' is expected. How can I change the code to get a correct boolean if statement for the trade entry? I'm very new to pine, hopefully someone can help me.
// This work is licensed under a Attribution-NonCommercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0) https://creativecommons.org/licenses/by-nc-sa/4.0/
// © LuxAlgo
//#version=5
// Umgeschrieben von JSt
strategy("Watson Strategie Nadaraya-Watson Envelope [JSt]",overlay=true,max_bars_back=1000,max_lines_count=500,max_labels_count=500)
length = input.float(500,'Window Size',maxval=500,minval=0)
h = input.float(8.,'Bandwidth')
mult = input.float(3.)
src = input.source(close,'Source')
up_col = input.color(#39ff14,'Colors',inline='col')
dn_col = input.color(#ff1100,'',inline='col')
//----
n = bar_index
var k = 2
var upper = array.new_line(0)
var lower = array.new_line(0)
lset(l,x1,y1,x2,y2,col)=>
line.set_xy1(l,x1,y1)
line.set_xy2(l,x2,y2)
line.set_color(l,col)
line.set_width(l,2)
if barstate.isfirst
for i = 0 to length/k-1
array.push(upper,line.new(na,na,na,na))
array.push(lower,line.new(na,na,na,na))
//----
line up = na
line dn = na
//----
cross_up = 0.
cross_dn = 0.
if barstate.islast
y = array.new_float(0)
sum_e = 0.
for i = 0 to length-1
sum = 0.
sumw = 0.
for j = 0 to length-1
w = math.exp(-(math.pow(i-j,2)/(h*h*2)))
sum += src[j]*w
sumw += w
y2 = sum/sumw
sum_e += math.abs(src[i] - y2)
array.push(y,y2)
mae = sum_e/length*mult
for i = 1 to length-1
y2 = array.get(y,i)
y1 = array.get(y,i-1)
up := array.get(upper,i/k)
dn := array.get(lower,i/k)
lset(up,n-i+1,y1 + mae,n-i,y2 + mae,up_col)
lset(dn,n-i+1,y1 - mae,n-i,y2 - mae,dn_col)
if src[i] > y1 + mae and src[i+1] < y1 + mae
label.new(n-i,src[i],'▼',color=#00000000,style=label.style_label_down,textcolor=dn_col,textalign=text.align_center)
if src[i] < y1 - mae and src[i+1] > y1 - mae
label.new(n-i,src[i],'▲',color=#00000000,style=label.style_label_up,textcolor=up_col,textalign=text.align_center)
cross_up := array.get(y,0) + mae
cross_dn := array.get(y,0) - mae
// TestUP = ta.crossover(src,cross_up) > 0
alertcondition(ta.crossover(src,cross_up),'Down','Down')
alertcondition(ta.crossunder(src,cross_dn),'Up','Up')
//---- Alarm für Webhook -----
plot(cross_up, color=#000000, transp=100) //Für den Alert, jedoch Darstellungsfehler → Transparent
plot(cross_dn, color=#000000, transp=100)
plotchar(cross_up, title="cross_up%", char="", location=location.top, color = color.green) // Damit der Wert in der Statusleiste dargestellt wird
plotchar(cross_dn, title="cross_dn%", char="", location=location.top, color = color.red)
//-------------------
// Start Date
// STEP 1. Create inputs that configure the backtest's date range
useDateFilter = input.bool(true, title="Begin Backtest at Start Date",
group="Backtest Time Period")
backtestStartDate = input.time(timestamp("1 Jan 2021"),
title="Start Date", group="Backtest Time Period",
tooltip="This start date is in the time zone of the exchange " +
"where the chart's instrument trades. It doesn't use the time " +
"zone of the chart or of your computer.")
// STEP 2. See if current bar happens on, or later than, the start date
inTradeWindow = not useDateFilter or time >= backtestStartDate
// ---------------
// Enter a long position when the entry rule is triggered
if inTradeWindow and ta.crossover(src,cross_up) > 0
strategy.entry('Long', strategy.long)
// Exit the Long position when the exit rule is triggered
if close > strategy.position_avg_price + 50
strategy.close("Long", comment = "TP")
else if close < strategy.position_avg_price - 50
strategy.close("Long", comment = "SL")
I tried the ta.crossover(src,cross_up) to compare it to zero, but it doesn't work.
ta.crossover() returns a bool value.
ta.crossover(source1, source2) → series bool
So, comparing its return value with some number does not make any sense and the compiler will complain: ta.crossover(src,cross_up) > 0.
You should just do:
if inTradeWindow and ta.crossover(src,cross_up)
strategy.entry('Long', strategy.long)
I have this script:
strategy("My strategy")
var float start_price = na
var float end_price = na
var float[] start_prices = array.new_float(0)
var float[] end_prices = array.new_float(0)
var float p = na
f(x) => math.round(x / 500) * 500
lo = (high + close) / 2
var i = 0
if bar_index == 1
start_price := f(lo)
end_price := f(start_price * 1.015)
else
if close <= start_price
strategy.entry(str.format("Long {0}",i), strategy.long)
array.push(end_prices, end_price)
array.push(start_prices, end_price)
i := i + 1
start_price := start_price - 500
end_price := f(start_price * 1.015)
for j = 0 to (array.size(end_prices) == 0 ? na : array.size(end_prices) - 1)
p := array.get(end_prices, j)
if close >= p
strategy.exit(str.format("Long {0}",j), limit=end_price)
I want to console/debug/display the values in start_prices array
But I can't figure out for the life of me how to do that, there's no console.log or anything like that. I'm a somewhat competent python programmer, but I always use the print()... Anyway, how do people debug in this language?
You can use the tostring() function (str.tostring() in v5) to generate a string of your array. You can then output it into a label or table.
eg.
start_prices_string = str.tostring(start_prices)
debug = label.new(x = bar_index, y = close, style = label.style_label_left, text = start_prices_string)
label.delete(debug[1])
I've been trying my first codes in pine script. The question is this. I have created few array.new_float to use as buffers in the 'for' statement. The thing is that I need to do some math over the data. Now, once the 'for' is done, an error pops: 'Cannot call 'operator -' with argument 'expr0' = 'High'.An argument of 'float[]' type was used but a 'const int' is expected'.
Please, if anyone knows what am I doing wrong, I will thank you.
Edit: I will leave the script of what I'm trying to do here
//#version=5
// Indicator name
indicator("DAF_Swing_Index", shorttitle= 'DAF_SwInd', overlay=false)
// Input
T = input.int(30000, title = 'Ratio de escala', minval = 1000, maxval = 150000)
Shift = input.int(0, title = 'Desplazamiento horizontal', minval = 0, maxval = 100)
// Array
SWINGINDEX = array.new_float(200)
Open = array.new_float(200)
Open1 = array.new_float(200)
Close = array.new_float(200)
Close1 = array.new_float(200)
High = array.new_float(200)
Low = array.new_float(200)
// Other variable
var float SwingIndex = 0
var int StartBars = 1
Prev_calculated = bar_index
Rates_total = bar_index + 1
var float SH1 = 0
var float SI = 0
var float R = 0
// Initial bar verification
if Rates_total < StartBars
SwingIndex := 0
Primero = 1
if Prev_calculated > Rates_total or Prev_calculated <= 0
Primero := 1
else
Primero := Prev_calculated-1
// Main process
for bar = Primero to Rates_total
array.push(Open, high[bar])
array.push(Open1, open[bar-1])
array.push(Close, close[bar])
array.push(Close1, close[bar-1])
array.push(High, high[bar])
array.push(Low, low[bar])
K = math.max(math.abs(High - Close1), math.abs(Low - Close1))
TR = math.max(math.max(math.abs(High-Close1), math.abs(Low-Close1)), math.abs(High-Low))
ER = 0.0
if Close1 > High
ER := math.abs(High - Close1)
if Close1 < Low
ER := math.abs(Low - Close1)
SH1 := math.abs(Close1 - Open1)
R := TR - 0.5 * ER + 0.25 * SH1
SI := 0.0
if R != 0
SI := 50 * ((Close - Close1) + 0.5 * (Close - Open1)) * (K / T) / R
SwingIndex := SI
// ploting result
plot(SwingIndex, title = 'Swing Index', style = plot.style_line, color = color.rgb(193, 255, 51, 10))
So, what the error message tells you is, your are passing an array, where it expects a const value.
Like here:
K = math.max(math.abs(High - Close1), math.abs(Low - Close1))
All those variables (High, Close1, Low) are arrays. It simply can not subtract one array from another. You can however, subtract one element from another element.
So for that line, I believe you want something like this:
K = math.max(math.abs(array.get(High, bar) - array.get(Close1, bar)), math.abs(array.get(Low, bar) - array.get(Close1, bar)))
With array.get(), you can get value the of the element at the specified index.
You should fix this in all other occurences.
My problem has a single state and an infinite amount of actions on a certain interval (0,1). After quite some time of googling I found a few paper about an algorithm called zooming algorithm which can solve problems with a continous action space. However my implementation is bad at exploiting. Therefore I'm thinking about adding an epsilon-greedy kind of behavior.
Is it reasonable to combine different methods?
Do you know other approaches to my problem?
Code samples:
import portion as P
def choose_action(self, i_ph):
# Activation rule
not_covered = P.closed(lower=0, upper=1)
for arm in self.active_arms:
confidence_radius = calc_confidence_radius(i_ph, arm)
confidence_interval = P.closed(arm.norm_value - confidence_radius, arm.norm_value + confidence_radius)
not_covered = not_covered - confidence_interval
if not_covered != P.empty():
rans = []
height = 0
heights = []
for i in not_covered:
rans.append(np.random.uniform(i.lower, i.upper))
height += i.upper - i.lower
heights.append(i.upper - i.lower)
ran_n = np.random.uniform(0, height)
j = 0
ran = 0
for i in range(len(heights)):
if j < ran_n < j + heights[i]:
ran = rans[i]
j += heights[i]
self.active_arms.append(Arm(len(self.active_arms), ran * (self.sigma_square - lower) + lower, ran))
# Selection rule
max_index = float('-inf')
max_index_arm = None
for arm in self.active_arms:
confidence_radius = calc_confidence_radius(i_ph, arm)
# indexfunction from zooming algorithm
index = arm.avg_learning_reward + 2 * confidence_radius
if index > max_index:
max_index = index
max_index_arm = arm
action = max_index_arm.value
self.current_arm = max_index_arm
return action
def learn(self, action, reward):
arm = self.current_arm
arm.avg_reward = (arm.pulled * arm.avg_reward + reward) / (arm.pulled + 1)
if reward > self.max_profit:
self.max_profit = reward
elif reward < self.min_profit:
self.min_profit = reward
# normalize reward to [0, 1]
high = 100
low = -75
if reward >= high:
reward = 1
self.high_count += 1
elif reward <= low:
reward = 0
self.low_count += 1
else:
reward = (reward - low)/(high - low)
arm.avg_learning_reward = (arm.pulled * arm.avg_learning_reward + reward) / (arm.pulled + 1)
arm.pulled += 1
# zooming algorithm confidence radius
def calc_confidence_radius(i_ph, arm: Arm):
return math.sqrt((8 * i_ph)/(1 + arm.pulled))
You may find this useful, full algorithm description is here. They grid out the probes uniformly, informing this choice (e.g. normal centering on a reputed high energy arm) is also possible (but this might invalidate a few bounds I am not sure).
I'm using faceting heatmap on a spatial field which then returns a 2d array like this
"counts_ints2D",
[
null,
null,
null,
null,
[
0,
8,
4,
0,
0,
0,
0,
0,
0,
...
I want to locate those cluster on the map but the problem is that I don't know how to convert that 2d array in geo coordinates.
There's absolutely no documentation out there showing what to do with those integer.
Can somebody give some guidance ?
Going with the data you gave for Glasgow, and using the formula given in the comments, lets explore the coordinates in a python repl:
# setup
>>> minX = -180
>>> maxX = 180
>>> minY = -53.4375
>>> maxY = 74.53125
>>> columns = 256
>>> rows = 91
# calculate widths
>>> bucket_width = (maxX - minX) / columns
>>> bucket_width
1.40625
>>> bucket_height = (maxY - minY) / rows
>>> bucket_height
1.40625
# calculate area for bucket in heatmap facet for x = 124, y = 13
# point in lower left coordinate
>>> lower_left = {
... 'lat': maxY - (13 + 1) * bucket_height,
... 'lon': minX + 124 * bucket_width,
... }
>>> lower_left
{'lat': 54.84375, 'lon': -5.625}
# point in upper right
>>> upper_right = {
... 'lat': maxY - (13 + 1) * bucket_height + bucket_height,
... 'lon': minX + 124 * bucket_width + bucket_width,
... }
>>> upper_right
{'lat': 56.25, 'lon': -4.21875}
Let's graph these points on a map, courtesy of open street map. We generate a small CSV snippet we can import on umap (select the up arrow, choose 'csv' as the type and enter content into the text box). To our coordinates to show:
>>> bbox = [
... "lat,lon,description",
... str(lower_left['lat']) + "," + str(lower_left['lon']) + ",ll",
... str(upper_right['lat']) + "," + str(lower_left['lon']) + ",ul",
... str(upper_right['lat']) + "," + str(upper_right['lon']) + ",uu",
... str(lower_left['lat']) + "," + str(upper_right['lon']) + ",lu",
... ]
>>> print("\n".join(bbox))
lat,lon,description
54.84375,-5.625,ll
56.25,-5.625,ul
56.25,-4.21875,uu
54.84375,-4.21875,lu
After pasting these points into the import box creating the layer, we get this map:
Map based on Open Street Map data through uMap. This area encloses Glasgow as you expected.
Here's some code that takes 180th meridian (date line) wrapping into account:
$columns = $heatmap['columns'];
$rows = $heatmap['rows'];
$minX = $heatmap['minX'];
$maxX = $heatmap['maxX'];
$minY = $heatmap['minY'];
$maxY = $heatmap['maxY'];
$counts = $heatmap['counts_ints2D'];
// If our min longitude is greater than max longitude, we're crossing
// the 180th meridian (date line).
$crosses_meridian = $minX > $maxX;
// Bucket width needs to be calculated differently when crossing the
// meridian since it wraps.
$bucket_width = $crosses_meridian
? $bucket_width = (360 - abs($maxX - $minX)) / $columns
: $bucket_width = ($maxX - $minX) / $columns;
$bucket_height = ($maxY - $minY) / $rows;
$points = [];
foreach ($counts as $rowIndex => $row) {
if (!$row) continue;
foreach ($row as $columnIndex => $column) {
if (!$column) continue;
$point = []
$point['count'] = $column;
// Put the count in the middle of the bucket (adding a half height and width).
$point['lat'] = $maxY - (($rowIndex + 1) * $bucket_height) + ($bucket_height / 2);
$point['lng'] = $minX + ($columnIndex * $bucket_width) + ($bucket_width / 2);
// We crossed the meridian, so wrap back around to negative.
if ($point['lng'] > 180) {
$point['lng'] = -1 * (180 - ($point['lng'] % 180));
}
$points[] = $point;
}
}