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

Variable-precision arithmetic (arbitrary-precision arithmetic)

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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

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Evaluate Symbolic Inputs with Variable-Precision Arithmetic

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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 =0.33333333333333333333333333333333sin(6.283185307179586476925286766559x)

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

V = [x/p a^3];VVpa = vpa(V)
VVpa =(0.31830988618379067153776752674503x0.037037037037037037037037037037037)
M = [sin(p) cos(p/5); exp(p*x) x/log(p)];MVpa = vpa(M)
MVpa =

(00.80901699437494742410229341718282e3.1415926535897932384626433832795x0.87356852683023186835397746476334x)

Change Precision Used by vpa

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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 =3.141592653589793238462643383279502884197169399375105820974944592307816406286208998628034825342117068

Restore the original precision value in digitsOld for further calculations.

digits(digitsOld)

Numerically Approximate Symbolic Results

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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 =

(root(z4-z+1,z,1)root(z4-z+1,z,2)root(z4-z+1,z,3)root(z4-z+1,z,4))

Use vpa to numerically approximate the roots.

yVpa = vpa(y)
yVpa =

(0.72713608449119683997667565867496-0.43001428832971577641651985839602i0.72713608449119683997667565867496+0.43001428832971577641651985839602i-0.72713608449119683997667565867496-0.93409928946052943963903028710582i-0.72713608449119683997667565867496+0.93409928946052943963903028710582i)

vpa Uses Guard Digits to Maintain Precision

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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

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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.

roundoff = a - vpa(b,32)
roundoff =0.000000000000000000086736173798840354720600815844403

vpa Restores Precision of Common Double-Precision Inputs

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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 pq, pπq, (pq)12, 2q, and 10q, 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 pq, pπq, (pq)12, 2q, and 10q, 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

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Create a symbolic expression S that represents sin([ππ2π2π3]X), where X is a 2-by-1 symbolic matrix variable.

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

sin(Σ1X)whereΣ1=(ππ2π2π3)

Evaluate the expression with variable-precision arithmetic.

SVpa = vpa(S)
SVpa =

(sin(3.1415926535897932384626433832795X1+1.5707963267948966192313216916398X2)sin(1.5707963267948966192313216916398X1+1.0471975511965977461542144610932X2))

Input Arguments

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xInput 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.

dNumber 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 229+1.

Output Arguments

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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, 2q,and 10q,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

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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.

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').

See Also

digits | double | root | vpaintegral

Topics

  • Increase Precision of Numeric Calculations
  • Recognize and Avoid Round-Off Errors
  • Increase Speed by Reducing Precision
  • Choose Numeric or Symbolic Arithmetic
  • Change Output Format of Symbolic and Variable-Precision Arithmetic

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Variable-precision arithmetic (arbitrary-precision arithmetic) - MATLAB vpa (1)

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

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.

What is the precision of VPA in MATLAB? ›

By default, MATLAB® uses 16 digits of precision. For higher precision, use vpa . The default precision for vpa is 32 digits. Increase precision beyond 32 digits by using digits .

What does vpa stand for in MATLAB? ›

The following article provides an outline for Matlab vpa. Matlab variable precision arithmetic is used in calculations where large numbers are involved (as input or output), and the primary focus is on precision and not the speed of computation.

What are the types of precision in MATLAB? ›

MATLAB represents floating-point numbers in either double-precision or single-precision format. The default is double precision. This example shows how to perform arithmetic and linear algebra with single precision data. MATLAB supports 1-, 2-, 4-, and 8-byte storage for integer data.

How many decimals are in MATLAB VPA? ›

By default, MATLAB® uses 16 digits of precision. For higher precision, use the vpa function in Symbolic Math Toolbox™. vpa provides variable precision which can be increased without limit. When you choose variable-precision arithmetic, by default, vpa uses 32 significant decimal digits of precision.

What is an example of a VPA? ›

So instead of sharing your bank account details, you can simply share your VPA or UPI ID with others to initiate transactions. For example, your VPA could be something like “yourname@bankname (rohit123@paytm)” or the most common one “yourphonenumber@bankname (9989889898@paytm)”.

What is the precision of Vpasolve in MATLAB? ›

By default, vpasolve returns solutions to a precision of 32 significant figures. Use digits to increase the precision to 64 significant figures.

What is vpa solve in MATLAB? ›

vpasolve uses variable-precision arithmetic. You can control precision arbitrarily using digits . For examples, see Increase Precision of Numeric Calculations.

What does the VPA stand for? ›

The full form of VPA is Virtual Payment Address (VPA). VPA is a digital ID that lets you receive and send funds conveniently through UPI-enabled apps. VPA eliminates the need to enter details like bank account number, branch name, IFSC code separately while conducting a transaction.

What is VPA function? ›

vpa(A) uses variable-precision arithmetic (VPA) to compute each element of A to d decimal digits of accuracy, where d is the current setting of digits . Each element of the result is a symbolic expression. vpa(A,d) uses d digits, instead of the current setting of digits .

What are the three types of precision? ›

Precision can assert itself in three different ways:
  • Arithmetic precision - number of significant digits for a value.
  • Stochastic precision - probability distribution of possible values.
  • Granularity - grouping or level of aggregation of values.
Mar 5, 2020

What are the three levels of precision? ›

Precision may be considered at three levels: repeatability, intermediate precision, and reproducibility.

What are variable types in MATLAB? ›

Supported Variable Types
TypeDescription
doubleDouble-precision floating point
int8 , int16 , int32 , int64Signed integer
logicalBoolean true or false
singleSingle-precision floating point
5 more rows

What is vpa in MATLAB? ›

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.

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.

Variable-precision arithmetic (arbitrary-precision ...MathWorkshttps://la.mathworks.com ›

This MATLAB function uses variable-precision arithmetic (arbitrary-precision floating-point numbers) to evaluate each element of the symbolic input x to at leas...

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.

What is the precision of floating-point in MATLAB? ›

Floating-Point Numbers in MATLAB

By default, MATLAB represents floating-point numbers in double precision. Double precision allows you to represent numbers to greater precision but requires more memory than single precision. To conserve memory, you can convert a number to single precision by using the single function.

What is the precision of floating-point binary? ›

All modern computers use binary floating-point arithmetic. That means we have a binary mantissa, which has typically 24 bits for single precision, 53 bits for double precision and 64 bits for extended precision.

What is the accuracy of floating-point precision? ›

Accuracy problems

The fact that floating-point numbers cannot accurately represent all real numbers, and that floating-point operations cannot accurately represent true arithmetic operations, leads to many surprising situations. This is related to the finite precision with which computers generally represent numbers.

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