Variable-precision arithmetic (arbitrary-precision arithmetic)

collapse all in page

Syntax

xVpa = vpa(x)

xVpa = vpa(x,d)

Description

example

xVpa = vpa(x) uses variable-precision arithmetic (arbitrary-precision floating-point numbers) to evaluate each element of the symbolic input x to at least d significant digits, where d is the value of the digits function. The default value of digits is 32.

example

xVpa = vpa(x,d) uses at least d significant digits instead of the value of digits.

Examples

collapse all

Evaluate Symbolic Inputs with Variable-Precision Arithmetic

Open Live Script

Evaluate symbolic inputs with variable-precision floating-point arithmetic. By default, vpa calculates values to 32 significant digits.

p = sym(pi);pVpa = vpa(p)

pVpa = $3.1415926535897932384626433832795$

syms xa = sym(1/3);f = a*sin(2*p*x);fVpa = vpa(f)

fVpa = $0.33333333333333333333333333333333 \sin (6.283185307179586476925286766559 x)$

Evaluate elements of vectors or matrices with variable-precision arithmetic.

V = [x/p a^3];VVpa = vpa(V)

VVpa = $(\begin{array}{c} 0.31830988618379067153776752674503 x & 0.037037037037037037037037037037037 \end{array})$

M = [sin(p) cos(p/5); exp(p*x) x/log(p)];MVpa = vpa(M)

MVpa = $(\begin{array}{c} 0 & 0.80901699437494742410229341718282 \\ e^{3.1415926535897932384626433832795 x} & 0.87356852683023186835397746476334 x \end{array})$

Change Precision Used by `vpa`

Open Live Script

By default, vpa evaluates inputs to 32 significant digits. You can change the number of significant digits by using the digits function.

Approximate the expression 100001/10001 with seven significant digits using digits. Save the old value of digits returned by digits(7). The vpa function returns only five significant digits, which can mean the remaining digits are zeros.

digitsOld = digits(7);y = sym(100001)/10001;yVpa = vpa(y)

yVpa = $9.9991$

Check if the remaining digits are zeros by using a higher precision value of 25. The result shows that the remaining digits are in fact zeros that are part of a repeating decimal.

digits(25)yVpa = vpa(y)

yVpa = $9.999100089991000899910009$

Alternatively, to override digits for a single vpa call, change the precision by specifying the second argument.

Find π to 100 significant digits by specifying the second argument.

pVpa = vpa(pi,100)

Numerically Approximate Symbolic Results

Open Live Script

While symbolic results are exact, they might not be in a convenient form. You can use vpa to numerically approximate exact symbolic results.

Solve a high-degree polynomial for its roots using solve. The solve function cannot symbolically solve the high-degree polynomial and represents the roots using root.

syms xy = solve(x^4 - x + 1, x)

y = $(\begin{array}{c} root (z^{4} - z + 1, z, 1) \\ root (z^{4} - z + 1, z, 2) \\ root (z^{4} - z + 1, z, 3) \\ root (z^{4} - z + 1, z, 4) \end{array})$

Use vpa to numerically approximate the roots.

yVpa = vpa(y)

yVpa = $(\begin{array}{c} 0.72713608449119683997667565867496 - 0.43001428832971577641651985839602 i \\ 0.72713608449119683997667565867496 + 0.43001428832971577641651985839602 i \\ - 0.72713608449119683997667565867496 - 0.93409928946052943963903028710582 i \\ - 0.72713608449119683997667565867496 + 0.93409928946052943963903028710582 i \end{array})$

`vpa` Uses Guard Digits to Maintain Precision

Open Live Script

The value of the digits function specifies the minimum number of significant digits used. Internally, vpa can use more digits than digits specifies. These additional digits are called guard digits because they guard against round-off errors in subsequent calculations.

Numerically approximate 1/3 using four significant digits.

a = vpa(1/3,4)

a = $0.3333$

Approximate the result a using 20 digits. The result shows that the toolbox internally used more than four digits when computing a. The last digits in the result are incorrect because of the round-off error.

aVpa = vpa(a,20)

aVpa = $0.33333333333303016843$

Avoid Hidden Round-Off Errors

Open Live Script

Hidden round-off errors can cause unexpected results.

Evaluate 1/10 with the default 32-digit precision and then with the 10-digit precision.

a = vpa(1/10,32)

a = $0.1$

b = vpa(1/10,10)

b = $0.1$

Superficially, a and b look equal. Check their equality by finding a - b.

roundoff = a - b

roundoff = $0.000000000000000000086736173798840354720600815844403$

The difference is not equal to zero because b was calculated with only 10 digits of precision and contains a larger round-off error than a. When you find a - b, vpa approximates b with 32 digits. Demonstrate this behavior.

`vpa` Restores Precision of Common Double-Precision Inputs

Open Live Script

Unlike exact symbolic values, double-precision values inherently contain round-off errors. When you call vpa on a double-precision input, vpa cannot restore the lost precision, even though it returns more digits than the double-precision value. However, vpa can recognize and restore the precision of expressions of the form $\frac{p}{q}$ , $\frac{p π}{q}$ , ${(\frac{p}{q})}^{\frac{1}{2}}$ , $2^{q}$ , and $10^{q}$ , where $p$ and $q$ are modest-sized integers.

First, demonstrate that vpa cannot restore precision for a double-precision input. Call vpa on a double-precision result and the same symbolic result.

dp = log(3);s = log(sym(3));dpVpa = vpa(dp)

dpVpa = $1.0986122886681095600636126619065$

sVpa = vpa(s)

sVpa = $1.0986122886681096913952452369225$

d = sVpa - dpVpa

d = $0.00000000000000013133163257501600766255995767652$

As expected, the double-precision result differs from the exact result at the 16th decimal place.

Demonstrate that vpa restores precision for expressions of the form $\frac{p}{q}$ , $\frac{p π}{q}$ , ${(\frac{p}{q})}^{\frac{1}{2}}$ , $2^{q}$ , and $10^{q}$ , where $p$ and $q$ are modest-sized integers, by finding the difference between the vpa call on the double-precision result and on the exact symbolic result. The differences are $0.0$ showing that vpa restores lost precision for the double-precision input.

d = vpa(1/3) - vpa(1/sym(3))

d = $0.0$

d = vpa(pi) - vpa(sym(pi))

d = $0.0$

d = vpa(1/sqrt(2)) - vpa(1/sqrt(sym(2)))

d = $0.0$

d = vpa(2^66) - vpa(2^sym(66))

d = $0.0$

d = vpa(10^25) - vpa(10^sym(25))

d = $0.0$

Evaluate Symbolic Matrix Variable with Variable-Precision Arithmetic

Since R2022b

Open Live Script

Create a symbolic expression S that represents $\sin ([\begin{array}{c} π & \frac{π}{2} \\ \frac{π}{2} & \frac{π}{3} \end{array}] X)$ , where $X$ is a 2-by-1 symbolic matrix variable.

syms X [2 1] matrixS = sin(hilb(2)*pi*X)

S = $\begin{array}{l} \sin (Σ_{1} X) \\ where \\ Σ_{1} = (\begin{array}{c} π & \frac{π}{2} \\ \frac{π}{2} & \frac{π}{3} \end{array}) \end{array}$

Evaluate the expression with variable-precision arithmetic.

SVpa = vpa(S)

SVpa = $(\begin{array}{c} \sin (3.1415926535897932384626433832795 X_{1} + 1.5707963267948966192313216916398 X_{2}) \\ \sin (1.5707963267948966192313216916398 X_{1} + 1.0471975511965977461542144610932 X_{2}) \end{array})$

Input Arguments

collapse all

`x` — Input to evaluate
number | vector | matrix | multidimensional array | symbolic number | symbolic vector | symbolic matrix | symbolic multidimensional array | symbolic expression | symbolic function | symbolic character vector | symbolic matrix variable

Input to evaluate, specified as a number, vector, matrix, multidimensional array, or a symbolic number, vector, matrix, multidimensional array, expression, function, character vector, or matrix variable.

`d` — Number of significant digits
positive integer scalar

Number of significant digits, specified as a positive integer scalar. d must be greater than 1 and less than $2^{29} + 1$ .

Output Arguments

collapse all

`xVpa` — Variable-precision output
symbolic number | symbolic vector | symbolic matrix | symbolic multidimensional array | symbolic expression | symbolic function

Variable-precision output, returned as a symbolic number, vector, matrix, multidimensional array, expression, or function.

For almost all input data types (such as sym, symmatrix, double, single, int64, and so on), vpa returns the output as data type sym.
If the input is a symbolic function of type symfun, then vpa returns the output as data type symfun. For example, syms f(x); f(x) = pi*x; g = vpa(f) returns the output g as type symfun.
If the input is an evaluated symbolic function of type sym, such as g = vpa(f(x)), then vpa returns the output as data type sym.

Tips

vpa does not convert fractionsin the exponent to floating point. For example, vpa(a^sym(2/5)) returns a^(2/5).
vpa uses more digits than thenumber of digits specified by digits. These extradigits guard against round-off errors in subsequent calculations andare called guard digits.
When you call vpa on a numericinput, such as 1/3, 2^(-5),or sin(pi/4), the numeric expression is evaluatedto a double-precision number that contains round-off errors. Then, vpa iscalled on that double-precision number. For accurate results, convertnumeric expressions to symbolic expressions with sym.For example, to approximate exp(1), use vpa(exp(sym(1))).
If the second argument d is notan integer, vpa rounds it to the nearest integerwith round.
vpa restores precision for numericinputs that match the forms p/q, pπ/q, (p/q)^1/2, 2^q,and 10^q,where p and q are modest-sizedintegers.
Variable-precision arithmetic is different from IEEE^® Floating-Point Standard 754 in these ways:
- Inside computations, division by zero throws an error.
- The exponent range is larger than in any predefined IEEE mode. vpa underflows below approximately 10^(-323228496).
- Denormalized numbers are not implemented.
- Zeros are not signed.
- The number of binary digits in the mantissa of a result may differ between variable-precision arithmetic and IEEE predefined types.
- There is only one NaN representation. No distinction is made between quiet and signaling NaN.
- No floating-point number exceptions are available.

Version History

Introduced before R2006a

expand all

R2022b: Evaluate symbolic matrix variables with variable-precision arithmetic

You can evaluate a symbolic matrix variable of type symmatrix with variable-precision arithmetic. The result is a symbolic expression with variable-precision numbers and scalar variables of type sym. For an example, see Evaluate Symbolic Matrix Variable with Variable-Precision Arithmetic.

R2018a: Support for character vectors has been removed

Support for character vectors that do not define a number has been removed. Instead, first create symbolic numbers and variables using sym and syms, and then use operations on them. For example, use vpa((1 + sqrt(sym(5)))/2) instead of vpa('(1 + sqrt(5))/2').

MATLAB Command

You clicked a link that corresponds to this MATLAB command:

Run the command by entering it in the MATLAB Command Window. Web browsers do not support MATLAB commands.

Select a Web Site

Choose a web site to get translated content where available and see local events and offers. Based on your location, we recommend that you select: .

You can also select a web site from the following list:

Americas

América Latina (Español)
Canada (English)
United States (English)

Europe

Belgium (English)
Denmark (English)
Deutschland (Deutsch)
España (Español)
Finland (English)
France (Français)
Ireland (English)
Italia (Italiano)
Luxembourg (English)

Netherlands (English)
Norway (English)
Österreich (Deutsch)
Portugal (English)
Sweden (English)
Switzerland
- Deutsch
- English
- Français
United Kingdom (English)

Asia Pacific

Australia (English)
India (English)
New Zealand (English)
中国
- 简体中文
- English
日本 (日本語)
한국 (한국어)

Contact your local office

FAQs

Variable-precision arithmetic (arbitrary-precision arithmetic) - MATLAB vpa? ›

Description. xVpa = vpa( x ) uses variable-precision arithmetic (arbitrary-precision floating-point numbers) to evaluate each element of the symbolic input x to at least d significant digits, where d is the value of the digits function. The default value of digits is 32.

Show Me More ›

What is the precision of VPA in MATLAB? ›

The default precision for vpa is 32 digits. Increase precision beyond 32 digits by using digits . Find pi using vpa , which uses the default 32 digits of precision. Confirm that the current precision is 32 by using digits .

How do you define decimals in MATLAB? ›

Select MATLAB > Command Window, and then choose a Numeric format option. The following table summarizes the numeric output format options. Short, fixed-decimal format with 4 digits after the decimal point.

Find Out More ›

How to use double-precision in MATLAB? ›

d = double( s ) converts the symbolic values s to double precision. Converting symbolic values to double precision is useful when a MATLAB^® function does not accept symbolic values. For differences between symbolic and double-precision numbers, see Choose Numeric or Symbolic Arithmetic.

See Details ›

How do you limit decimals in MATLAB? ›

For display purposes, use sprintf to control the exact display of a number as a string. For example, to display exactly 2 decimal digits of pi (and no trailing zeros), use sprintf("%. 2f",pi) .

Get More Info ›

How does vpa work in MATLAB? ›

vpa Uses Guard Digits to Maintain Precision

The value of the digits function specifies the minimum number of significant digits used. Internally, vpa can use more digits than digits specifies. These additional digits are called guard digits because they guard against round-off errors in subsequent calculations.

Read The Full Story ›

What is the VPA code? ›

It is a unique address that you can use to make payments instantly. You can use it to send money via UPI apps or real-time modes of transactions. In fact, VPA numbers are used to create a digital bank account or a virtual bank account.

Tell Me More ›

What is VPA in machine learning? ›

Virtual personal assistants (VPAs) are computer programme created to organically interact with humans to respond to questions, carry on discussions, and carry out different tasks. The two sorts of inputs that a VPA normally accepts are voice input (like Apple Siri) and text input (Google Assistant).

Get More Info Here ›

What is the precision of octave floating point? ›

All built-in floating point numeric data is currently stored as double precision numbers. On systems that use the IEEE floating point format, values in the range of approximately 2.2251e-308 to 1.7977e+308 can be stored, and the relative precision is approximately 2.2204e-16.

Find Out More ›

What is the precision of floating point scale? ›

The value that can be represented by a single precision floating point number is approximately 6 or 7 decimal digits of precision. A double precision, floating-point number is a 64-bit approximation of a real number.

Learn More ›

What is the accuracy of floating point precision? ›

This is a binary format that occupies 32 bits (4 bytes) and its significand has a precision of 24 bits (about 7 decimal digits).

Read The Full Story ›

What is the precision of float type variable? ›

A variable of type float only has 7 digits of precision whereas a variable of type double has 15 digits of precision. If you need better accuracy, use double instead of float.

Get More Info Here ›

Variable-precision arithmetic (arbitrary-precision arithmetic) - MATLAB vpa (2024)

Syntax

Description

Examples

Evaluate Symbolic Inputs with Variable-Precision Arithmetic

Change Precision Used by `vpa`

Numerically Approximate Symbolic Results

`vpa` Uses Guard Digits to Maintain Precision

Avoid Hidden Round-Off Errors

`vpa` Restores Precision of Common Double-Precision Inputs

Evaluate Symbolic Matrix Variable with Variable-Precision Arithmetic

Input Arguments

`x` — Input to evaluate
number | vector | matrix | multidimensional array | symbolic number | symbolic vector | symbolic matrix | symbolic multidimensional array | symbolic expression | symbolic function | symbolic character vector | symbolic matrix variable

`d` — Number of significant digits
positive integer scalar

Output Arguments

`xVpa` — Variable-precision output
symbolic number | symbolic vector | symbolic matrix | symbolic multidimensional array | symbolic expression | symbolic function

Tips

Version History

R2022b: Evaluate symbolic matrix variables with variable-precision arithmetic

R2018a: Support for character vectors has been removed

See Also

Topics

MATLAB Command

Americas

Europe

Asia Pacific

FAQs

Variable-precision arithmetic (arbitrary-precision arithmetic) - MATLAB vpa? ›

How do you define decimals in MATLAB? ›

Variable-precision arithmetic (arbitrary-precision arithmetic) - MATLAB vpa (2024)

Syntax

Description

Examples

Evaluate Symbolic Inputs with Variable-Precision Arithmetic

Change Precision Used by vpa

Numerically Approximate Symbolic Results

vpa Uses Guard Digits to Maintain Precision

Avoid Hidden Round-Off Errors

vpa Restores Precision of Common Double-Precision Inputs

Evaluate Symbolic Matrix Variable with Variable-Precision Arithmetic

Input Arguments

x — Input to evaluate number | vector | matrix | multidimensional array | symbolic number | symbolic vector | symbolic matrix | symbolic multidimensional array | symbolic expression | symbolic function | symbolic character vector | symbolic matrix variable

d — Number of significant digits positive integer scalar

Output Arguments

xVpa — Variable-precision output symbolic number | symbolic vector | symbolic matrix | symbolic multidimensional array | symbolic expression | symbolic function

Tips

Version History

R2022b: Evaluate symbolic matrix variables with variable-precision arithmetic

R2018a: Support for character vectors has been removed

See Also

Topics

MATLAB Command

Americas

Europe

Asia Pacific

FAQs

Variable-precision arithmetic (arbitrary-precision arithmetic) - MATLAB vpa? ›

How do you define decimals in MATLAB? ›

Change Precision Used by `vpa`

`vpa` Uses Guard Digits to Maintain Precision

`vpa` Restores Precision of Common Double-Precision Inputs

`x` — Input to evaluate
number | vector | matrix | multidimensional array | symbolic number | symbolic vector | symbolic matrix | symbolic multidimensional array | symbolic expression | symbolic function | symbolic character vector | symbolic matrix variable

`d` — Number of significant digits
positive integer scalar

`xVpa` — Variable-precision output
symbolic number | symbolic vector | symbolic matrix | symbolic multidimensional array | symbolic expression | symbolic function