INF, NAN, and NULL - Exception values
INF
("infinity"), NAN
("not a number"), and Null
are special-valued system constants that Analytica returns in particular conditions, such as exceptions. These constants can also be used as values in expressions.
Constant | Meaning |
---|---|
INF
|
Infinity or a real number larger than can be represented, e.g., 1/0
|
NAN
|
Not a Number: Actually, the result is known to be “number” but not well
defined, e.g., |
Null
|
The result of an operation where the desired data is not there, such as
|
INF (infinity)
INF
is the result of a numerical calculation that is mathematically infinite, such as:
1/0 → INF
INF
is also the result of a calculation that would produce a number larger than 1.797 x10+308, which is the largest floating point number that Analytica can represent:
10^1000 → INF
INF
can be positive or negative:
-1 * 10^1000 → -INF
-1/0 → -Inf
So -Inf
means negative infinity (or a number below -1.796E308).
You can perform useful, mathematically correct arithmetic with INF, such as:
INF + 10 → INF
INF/0 → INF
10 - INF → -INF
100/0 = INF → True
NAN (Not a Number)
NAN
is the result of an indeterminate numerical calculation, including numerical functions whose parameter is outside their domain, such as"
INF - INF → NAN
0/0 → NAN
INF/INF → NAN
Sqrt(-1) → NAN
ArcSin(2) → NAN
(If you enable Complex Numbers, Sqrt(-1) returns the valid imaginary number, 1j.)
It usually gives a warning if you apply a function to a parameter value outside its range, such as the two examples above — unless you have checked “Ignore warnings”.
Any arithmetic operation, comparison, or function applied to NAN
returns NAN
:
0/0 <> NAN → NAN
Analytica’s representation and treatment of INF
and NAN
is consistent with ANSI (Association of National Standards Institutes) standards and IEEE Floating point standards. NAN
stands for “Not A Number,” which is a bit misleading, since NAN
really is a kind of number. You can detect NAN
in an expression using the IsNaN() function.
Calculations performed with INF and NAN follow the laws of mathematics:
1/Inf → 0
1/(-Inf) → 0
Inf + Inf → Inf
Inf - Inf → NAN
Expressions taking NAN as an operand or parameter give NAN as their result unless the expression has a well-defined logical or numerical value for any value of NAN:
True OR NAN → True
NaN AND False → False
IF True THEN 5 ELSE NAN → 5
NULL
Null: Null
is a result that is ill-defined, usually indicating that there is nothing at the location requested, for example a subscript using a value that does not match a value of the index:
Index I := 1..5
X[I=6] → Null
Other operations and functions that can return Null
include Slice(), Subscript(), Subindex(), and MDTable(), e.g.
- Index Year := [2015, 2016, 2017]
- Slice(Year, 4) → NULL
- Variable X := Array(Year, [20, 23, 28])
- X[Year = 2018] → NULL
You can test for Null
using the standard = or <> operators, such as:
X[I=6] = Null → True
or you can use IsUndef(X[I=6])
.
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
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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