Heatmap-like as a an option to plot on chart?

sniktau

New member
Hello,

I am new to using thinkorswim to plot information about trading, and so far thinkscript seems promising for my purposes.

I have been interested in taking a measure for which I would like to evaluate multiple values all at once and display the array of results, which are all numbers between 0 and 1, as a stack of colored squares as wide as every time tick. The aggregate should be a sort of "heatmap" where one scale is time along with the chart, and the other is a series of rows along which I will sweep another parameter.

I've been looking through the available plotting resources but I seem to find either line charts, or plotting arrows or other things along a chart. I expected a heatmap, or contour plots, or maybe 3D data representations in the "Advanced" tab but it's only goes to far as to concatenate strings. Ooh. Advanced. So very.

A few twists I know are ahead for me: the ordinate (y-dimension) is calculated once for a series of time scales, back a minute, back a few minutes, back an hour, back a day, etc. I think I have a lead on how to handle calculations on multi-time-frame functions, but there's a chance that someone has worked through both essential issues in one go.

EDIT: Solved. Thermo mode is a whole method for handling input and I don't have to code up anything new.
 
Last edited:
That looks like where I started, but I'm disappointed by the lack of references to other display items. It took me a while but I found a few things.

This is what made me jump into thinkscript in the first place. Not the video and the rambling feller but the heatmap

I thought about being devilish with Add Cloud, but this isn't what I'm trying to plot. Something to try later, perhaps. Then I posted here...

However, this is actually what I wanted, and it came to me just after your post. It was not in an obvious area in the rubbish documentation snarl over there, but whatever. I can give it inputs and so my thinkscript's "scale" should be able to be adjusted by this dialog box. Thanks for the very quick response, though.
 
The study in the video is pretty neat. Having read through this teaching post about combining studies:

https://usethinkscript.com/threads/combine-studies-indicators-in-thinkorswim.8766/

I think I have that down, at least for CCI and RSI anyway, because there is only one plot. I'm confused on what to do with MACD, BB, Ichimoku because they have more than one plot. Thermo appears to use one plot. So I just averaged them for now. In his video he says he has custom points for MACD, ICH, BB and weights them against the RSI and CCI. I don't know what that really means - did he use AverageType.Weighted or is he assigning a weight (40%) to MACD, ICH, BB and averaging them together? Something like (((MACD + ICH + BB)/3) * .04) + (CCI + RSI))/2?

Anyway sure my calc/code is jibberish, but at least I got the syntax down - not bad for noob browsing through the forum trying to learn to trade and code :D:

Code:
Declare lower;

# RSI
input length = 14;
input price = close;
input averageType = AverageType.Wilders;
def NetChgAvg = MovingAverage(averageType, price - price[1], length);
def TotChgAvg = MovingAverage(averageType, AbsValue(price - price[1]), length);
def ChgRatio = if TotChgAvg != 0 then NetChgAvg / TotChgAvg else 0;
def RSI = 50 * (ChgRatio + 1);

# CCI
input length_CCI = 14;
def price_CCI = close + low + high;
def linDev = lindev(price_CCI, length_CCI);
def CCI = if linDev == 0 then 0 else (price_CCI - Average(price_CCI, length_CCI)) / linDev / 0.015;

# MACD
input fastLength = 12;
input slowLength = 26;
input MACDLength = 9;
input averageType_MACD = AverageType.Exponential;
input showBreakoutSignals = no;
def MACD_Value = MovingAverage(averageType, close, fastLength) - MovingAverage(averageType, close, slowLength);
def MACD_Avg = MovingAverage(averageType, MACD_Value, MACDLength);
def MACD_Diff = MACD_Value - MACD_Avg;
def AVG_MACD = (MACD_Value + MACD_Avg + MACD_Diff)/3;

# BB
input price_BB = close;
input displace = 0;
input length_BB = 20;
input Num_Dev_Dn = -2.0;
input Num_Dev_up = 2.0;
input averageType_BB = AverageType.Simple;
def BB_sDev = stdev(data = price_BB[-displace], length = length_BB);
def BB_MidLine = MovingAverage(averageType_BB, data = price_BB[-displace], length = length_BB);
def BB_LowerBand = BB_MidLine + num_Dev_Dn * BB_sDev;
def BB_UpperBand = BB_MidLine + num_Dev_Up * BB_sDev;
DEF AVG_BB = (BB_sDev + BB_MidLine + BB_LowerBand + BB_UpperBand)/5;

# Ichimoku
input tenkan_period = 9;
input kijun_period = 26;
def Tenkan = (Highest(high, tenkan_period) + Lowest(low, tenkan_period)) / 2;
def Kijun = (Highest(high, kijun_period) + Lowest(low, kijun_period)) / 2;
def "Span A" = (Tenkan[kijun_period] + Kijun[kijun_period]) / 2;
def "Span B" = (Highest(high[kijun_period], 2 * kijun_period) + Lowest(low[kijun_period], 2 * kijun_period)) / 2;
def Chikou = close[-kijun_period];
def AVG_ICHO = (Tenkan + Kijun + "Span A" + "Span B" + Chikou)/5;

# All Combined
# MACD, BB, ICH weighted (lets say 40% )against RSI, CCI
def MACD_BB_ICH = ((AVG_MACD + AVG_BB + AVG_ICHO)/3) * .40;
def RSI_CCI = (RSI + CCI)/2;
Plot Combined = MACD_BB_ICH + RSI_CCI;

h2knGPY.jpg
 

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