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Add Formulas and Calculations to Data Inputs

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Written by Harmony Palmer
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This is Optional - not required.

Formulas are a feature of Data Inputs that allow users to interpret and calculate the values that will be represented on dashboards and reports. This guide will show a few examples of common formulas and includes a table of acceptable operators and a list of other formulas available.

 

Requirements:

  • Data Inputs referencing Gateway Channel or Mapped Registers (PLC) or Data Input sources*
  • Full-Admin or equivalent access on cloud.samsara.com

Note: Formulas are currently only accessible on the following Sources: Third Party Pin (PLC Mapped Registers), Gateway Channel and Data Inputs. You can reference another Data Input as a Source which will allow you to add formulas to Samsara Sensor data or even multiple Data Inputs.

 

 

Operators and Modifiers:

 

Symbol

Modification

Example // x = 2

+ -

Addition

x+1 // Returns 3

* / ** %

Multiplication

x**3 // Returns 8

>> << | &

Bitwise shifts, masks

See Bit Masking example below

 

 

Setting up Variables:

Create the variable you would like to your device to refer to. A common starting variable is “x”.

 

One of the easiest ways to read a raw value from your Data Inputs is to use your variable “x” as the formula. This will represent the original value that the Data Input is receiving. This will allow you to view the last raw datapoint on the Data Inputs page and view raw datapoints from any reports or dashboards referencing this Data Input.

Some advanced Data Inputs can have multiple variables. An example of multivariable data points is included below. 

 

Predefined Formulas:

Some predefined formulas are available to quickly set up formulas. Presets include but are not limited to Min, Max, Average, Totalize and more.

 You also can select a Time Window with which you would like this preset formula to reference.

 

 

Aggregate Formulas Across Data Groups

Using data groups, you can create aggregate calculations across many assets or sites within your nav structure. This allows you to: 

  1. Calculate averages across child assets
  2. Setup in seconds, no need for a custom formula
  3. Duplicate across customers or sites at scale with data groups
  • To do this, select Aggregate from the Formula Type dropdown list
  • Choose the parent asset that contains all of the child assets you want to create an aggregate calculation for
  • Choose the calculation you want to create, e.g. average, sum, min, max and choose the data group, e.g. pump efficiency
  • Finally, select the units and create the data input

6.png

 

Moving Window Functions:

Moving window functions let you create a rolling average that will smooth out data by plotting continuous averages, in one minute increments.  For example, you may want to calculate an average for the last 15 minutes, every minute. You can set this up by selecting the moving window function within a data input, selecting average, and setting the window size you’d like to use.

1111.png

 

Custom Formulas: 

 

Multivariable

Multivariable Data Inputs if you want to calculate multiple data inputs at one time. Each variable must be an existing data input to select them from the dropdown.

 

 

Ternary Conditionals 

Custom formulas also support ternary conditionals to apply basic logic to your data inputs. The basic structure is the following:

 

x < 1 ? x : 0


This reads as "if the data input value is less than 1, report x. Otherwise report 0".

 

For example, if a user would like to ignore erroneous spikes in data from their third-party device, they can set this ternary operation to report large spikes as "0". The original data input values from the third party device may look like this:

 

mceclip0.png

 

After the condition is applied to the formula the graph will look like the following without the erroneous spikes:

mceclip3.png

 

 

You can also combine the multiple data inputs with your ternary conditional. The following is an example is utilizing the median value with the multivariable feature mentioned earlier. This may be used to set alerts or dashboard indicators if several conditions of different Data Inputs were being met at once. 

 

(median(a,b,c,d,e,f,g,h,i,j,k) > 11 && l < 5000) ? 1 : 0

 

mceclip4.png

 

In this scenario, if the median of the listed data inputs is greater than 11 and the final data input is greater than 5000, set this data input to 1. Otherwise set the input to 0. This may be useful in alerting based off of multiple data inputs and their specific conditions in relation to each other.

 

Note: Creating complex or several layers of conditionals may impact alerting and other calculation processes.

 

Bitmasking values

Some Data Inputs will be reporting bit data from a Third Party Device. Bitmasking is a useful tool to extract the specific bit you would like your Data Input to refer to in order to accurately represent data being communicated from your Third Party Device.

The bitmasking formula is relatively simple and follows the following pattern (x&2^[bit#])/(2^[bit#]):  

Formula

Bit reference

(x&1)

Zero Bit (x&2^0)/(2^0)

(x&2)/2

First Bit (x&2^1)/(2^1)

(x&4)/4

Second Bit (x&2^2)/(2^2)

(x&8)/8

Third Bit (x&2^3)/(2^3)

(x&4096)/4096

Twelfth Bit (x&2^12)/(2^12)

 

 

 

Other Available Formulas 

Min with 4 values  
Example Formula: min(x,1,2,3)
Example Inputs: {-3, -2, 0, 1, 2, 3},
Expected Outputs: {-3, -2, 0, 1, 1, 1}
   
Max with 4 values  
Example Formula: max(x,1,2,3)
Example Inputs: {0, 1, 2, 3, 4, 5}
Expected Outputs: {3, 3, 3, 3, 4, 5}
   
Avg with 4 values  
Example Formula: avg(x,1,2,3)
Example Inputs: {0, 1, 2, 3, 4, 5}
Expected Outputs: {1.5, 1.75, 2, 2.25, 2.5, 2.75}
   
Median (even)  
Example Formula: median(x, 1, 2, 3)
Example Inputs: {0, 1, 2, 3, 4, 5}
Expected Outputs: {1.5, 1.5, 2, 2.5, 2.5, 2.5}
   
Median (odd)  
Example Formula: median(x, 1, 2, 3, 4)
Example Inputs: {0, 1, 2, 3, 4, 5}
Expected Outputs: {2, 2, 2, 3, 3, 3}
   
Mode  
Example Formula: mode(x, 1, 2, 2, 4)
Example Inputs: {0, 1, 2, 3, 4, 5}
Expected Outputs: {2, 1, 2, 2, 2, 2}
   
Mode (multiple)  
Example Formula: mode(x, 1, 2, 2, 1)
Example Inputs: {0, 1, 2, 3, 4, 5}
Expected Outputs: {1, 1, 2, 1, 1, 1}
   
Standard Deviation  
Example Formula: stddev(x, 1, 2, 3)
Example Inputs: {2, 4, 9, 16, 25, 30}
Expected Outputs:
{0.7071067811865476, 1.118033988749895, 3.112474899497183, 6.103277807866851, 9.98436277385793, 12.144957801491119}
   
Square Root  
Example Formula: sqrt(x)
Example Inputs: {2, 4, 9, 16, 25, 30}
Expected Outputs:
{1.4142135623730951, 2, 3, 4, 5, 5.477225575051661}
   
Floor  
Example Formula: floor(x)
Example Inputs: {6, 4.1, 4.99, 4.999, 4.9999, 4.99999}
Expected Outputs: {6, 4, 4, 4, 4, 4}
   
Ceiling  
Example Formula: ceil(x)
Example Inputs: {6, 4.1, 4.99, 3.999, 3.0000000001, 4.4}
Expected Outputs: {6, 5, 5, 4, 4, 5}
   
Absolute  
Example Formula: abs(x)
Example Inputs: {-3, -2, 0, 1, 2, 3}
Expected Outputs: {3, 2, 0, 1, 2, 3}
   
Round  
Example Formula: round(5.854123,x)
Example Inputs: {0, 1, 2, 3, 4, 5}
Expected Outputs: {6, 5.9, 5.85, 5.854, 5.8541, 5.85412}

 

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