Difference between revisions of "INF, NAN, and Null"

m (More on NULL)
m (More on INF and NAN)
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:Inf + Inf → Inf
 
:Inf + Inf → Inf
 
:Inf - Inf → NAN
 
:Inf - Inf → NAN
 +
 +
NAN in operand does not always generate NAN as the result if the expression has a well-defined logical or numerical value no matter what the value of NAN:
 +
 +
:True OR NAN → True
 +
:NaN AND False → False
 +
:IF True THEN 5 ELSE NAN → 5
  
 
=== More on NULL ===
 
=== More on NULL ===

Revision as of 18:53, 28 January 2015


These are special values that Analytica returns in particular conditions. You can also use them in expressions:

Inf means infinity -- e.g.,

1/0 → Inf

or a number larger than 1.796E308 (due to computer limitations) -- e.g.

1E307 * 100 → Inf

-Inf means negative infinity -- e.g.,

-1/0 → -Inf

or a number less than 1.796E308

NAN means "Not A Number", where the result is numeric, but not a real number or infinity -- e.g.

0/0 → NAN
Sqrt(-1) → NAN

except if you enable Complex Numbers, in which case this will return a valid imaginary number, 1j.

Null means that there is no such value. For example, Slice and Subscript return Null if you try to get the nth slice over an Index with less than n values.

More on INF and NAN

Analytica follows ANSI (Association of National Standards Institutes) standards for computing with these special values, where applicable.

1/Inf → 0
1/(-Inf) → 0
Inf + Inf → Inf
Inf - Inf → NAN

NAN in operand does not always generate NAN as the result if the expression has a well-defined logical or numerical value no matter what the value of NAN:

True OR NAN → True
NaN AND False → False
IF True THEN 5 ELSE NAN → 5

More on NULL

When NULL appears in scalar operations, it generally produces a warning and evaluates to NULL, for example:

10 + NULL → NULL
NULL - 10 → NULL
1 AND NULL → NULL

Array-reducing functions ignore NULL. These examples demonstrate (assume A is indexed by I as indicated).

I: 1 2 3 4 5
A: 8 NULL 4 NULL 0
Sum(A, I) → 12
Average(A, I) → 4
JoinText(A, I, ', ') → "8, 4, 0"

Graphs will simply ignore (not show) any point whose value is NULL.

Array-reducing functions include Sum, Min, Max, ArgMin, ArgMax, Product, Average, JoinText, Irr, Npv. Array functions Sum, Min and Max also accept an optional parameter IgnoreNaN to ignore NaN values (which otherwise propagate, i.e. return NaN).

Regression also ignores any data points which have Y=Null, which is useful for missing data.

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