Что такое код is_finite


Содержание

is_infinite — Проверяет, является ли значение бесконечным

(PHP 4 >= 4.2.0, PHP 5, PHP 7)

is_infinite — Проверяет, является ли значение бесконечным

Описание

Возвращает TRUE , если val является бесконечностью (положительной или отрицательной), например, как результат вычисления log(0) или любые другие значения, слишком большие, чтобы уместиться в float на данной платформе.

Список параметров

Возвращаемые значения

TRUE если val является бесконечным, и FALSE в противном случае.

Смотрите также

  • is_finite() — Проверяет, является ли значение допустимым конечным числом
  • is_nan() — Проверяет, является ли значение «не числом»

FINITE GEOMETRY CODE

Англо-русский перевод FINITE GEOMETRY CODE

English-Russian scientific and technological dictionary . Англо-Русский научно-технический словарь. 2005

Еще значения слова и перевод FINITE GEOMETRY CODE с английского на русский язык в англо-русских словарях и с русского на английский язык в русско-английских словарях.

More meanings of this word and English-Russian, Russian-English translations for the word «FINITE GEOMETRY CODE» in dictionaries.

is_finite

(PHP 4 >= 4.2.0, PHP 5, PHP 7)

is_finite — Проверяет, является ли значение допустимым конечным числом

Описание

Проверяет, является ли val допустимым конечным числом на данной платформе.

Список параметров

Возвращаемые значения

TRUE , если val является допустимым конечным числом в разрешенном для типа PHP float диапазоне на данной платформе, FALSE в противном случае.

Смотрите также


  • is_infinite() — Проверяет, является ли значение бесконечным
  • is_nan() — Проверяет, является ли значение «не числом»

User Contributed Notes 1 note

(is_finite($float)) is equivalent to (!is_infinite($float) && !is_nan($float)), i.e. a number can only be one of finite, infinite and NaN. You don’t need to check both is_infinite() and is_nan() to see if a number is invalid or out of range.

= 42 ;
$infinite = log ( 0 );
$nan = acos ( 2 );

var_dump ( is_finite ( $finite ), is_infinite ( $finite ), is_nan ( $finite )); // true, false, false
var_dump ( is_finite ( $infinite ), is_infinite ( $infinite ), is_nan ( $infinite )); // false, true, false
var_dump ( is_finite ( $nan ), is_infinite ( $nan ), is_nan ( $nan )); // false, false, true
?>

Что такое код is_finite

is.finite and is.infinite return a vector of the same length as x , indicating which elements are finite (not infinite and not missing) or infinite.

Inf and -Inf are positive and negative infinity whereas NaN means ‘Not a Number’. (These apply to numeric values and real and imaginary parts of complex values but not to values of integer vectors.) Inf and NaN are reserved words in the R language.

Usage

Arguments

R object to be tested: the default methods handle atomic vectors.

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Details

is.finite returns a vector of the same length as x the jth element of which is TRUE if x[j] is finite (i.e., it is not one of the values NA , NaN , Inf or -Inf ) and FALSE otherwise. Complex numbers are finite if both the real and imaginary parts are.

is.infinite returns a vector of the same length as x the jth element of which is TRUE if x[j] is infinite (i.e., equal to one of Inf or -Inf ) and FALSE otherwise. This will be false unless x is numeric or complex. Complex numbers are infinite if either the real or the imaginary part is.

is.nan tests if a numeric value is NaN . Do not test equality to NaN , or even use identical , since systems typically have many different NaN values. One of these is used for the numeric missing value NA , and is.nan is false for that value. A complex number is regarded as NaN if either the real or imaginary part is NaN but not NA . All elements of logical, integer and raw vectors are considered not to be NaN.

All three functions accept NULL as input and return a length zero result. The default methods accept character and raw vectors, and return FALSE for all entries. Prior to R version 2.14.0 they accepted all input, returning FALSE for most non-numeric values; cases which are not atomic vectors are now signalled as errors.

All three functions are generic: you can write methods to handle specific classes of objects, see InternalMethods.

Value

A logical vector of the same length as x : dim , dimnames and names attributes are preserved.

In R , basically all mathematical functions (including basic Arithmetic ), are supposed to work properly with +/- Inf and NaN as input or output.

The basic rule should be that calls and relations with Inf s really are statements with a proper mathematical limit.

Computations involving NaN will return NaN or perhaps NA : which of those two is not guaranteed and may depend on the R platform (since compilers may re-order computations).

References

The IEC 60559 standard, also known as the ANSI/IEEE 754 Floating-Point Standard.


D. Goldberg (1991) What Every Computer Scientist Should Know about Floating-Point Arithmetic ACM Computing Surveys, 23(1).
Postscript version available at http://www.validlab.com/goldberg/paper.ps Extended PDF version at http://www.validlab.com/goldberg/paper.pdf

The C99 function isfinite is used for is.finite .

See Also

NA , ‘Not Available’ which is not a number as well, however usually used for missing values and applies to many modes, not just numeric and complex.

Примеры готовых предложений с finite element code из вдохновляющих источников на английском языке

A finite element code was used to perform numerical investigations.

The general purpose finite element code ABAQUS was selected.

All simulations were performed using the ABAQUS finite element code .

Theoretical analyses are carried out using ABAQUS finite element code .

These simulations were achieved using ABAQUS explicit finite element code .

Finite element code FIDAP (commercially available from Fluent Inc).

Stress analysis is done using finite element code ABAQUS.

The model is implemented into commercial finite element code ABAQUS.

For both analyses, a finite element code has been implemented.

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is_infinite — Проверяет, является ли значение бесконечным

(PHP 4 >= 4.2.0, PHP 5, PHP 7)


is_infinite — Проверяет, является ли значение бесконечным

Описание

Возвращает TRUE , если val является бесконечностью (положительной или отрицательной), например, как результат вычисления log(0) или любые другие значения, слишком большие, чтобы уместиться в float на данной платформе.

Список параметров

Возвращаемые значения

TRUE если val является бесконечным, и FALSE в противном случае.

Смотрите также

  • is_finite() — Проверяет, является ли значение допустимым конечным числом
  • is_nan() — Проверяет, является ли значение «не числом»

Is pi a finite or an infinite number?

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Answer Wiki

It is none of those things.

It can’t be infinite, it has a value between 3 and 4. That means it isn’t ‘big’ either.

It is very easily understood. It is the ratio of diameter to circumference in a circle. That goes back to the very earliest days of mathematics. If you can define it drawing in sand with a stick, it’s easy.

The only infinite thing about pi it is its decimal expansion. But that is trivial. It s just another way of saying it is irrational. It can’t be expressed as a ratio of two intege.

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Is pi a finite or an infinite number?

a gKWk d Vg GdeO b nq y CKD dL E hRF l AKZ a BKT s XWt t rlC i BX c BCR

Answer Wiki

It is none of those things.

It can’t be infinite, it has a value between 3 and 4. That means it isn’t ‘big’ either.

It is very easily understood. It is the ratio of diameter to circumference in a circle. That goes back to the very earliest days of mathematics. If you can define it drawing in sand with a stick, it’s easy.

The only infinite thing about pi it is its decimal expansion. But that is trivial. It s just another way of saying it is irrational. It can’t be expressed as a ratio of two intege.

How to force an error if non-finite values (NA, NaN, or Inf) are encountered

There’s a conditional debugging flag I miss from Matlab: dbstop if infnan described here. If set, this condition will stop code execution when an Inf or NaN is encountered (IIRC, Matlab doesn’t have NAs).

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How might I achieve this in R in a more efficient manner than testing all objects after every assignment operation?

At the moment, the only ways I see to do this are via hacks like the following:

  1. Manually insert a test after all places where these values might be encountered (e.g. a division, where division by 0 may occur). The testing would be to use is.finite() , described in this Q & A, on every element.
  2. Use body() to modify the code to call a separate function, after each operation or possibly just each assignment, which tests all of the objects (and possibly all objects in all environments).
  3. Modify R’s source code (. )
  4. Attempt to use tracemem to identify those variables that have changed, and check only these for bad values.
  5. (New — see note 2) Use some kind of call handlers / callbacks to invoke a test function.

The 1st option is what I am doing at present. This is tedious, because I can’t guarantee I’ve checked everything. The 2nd option will test everything, even if an object hasn’t been updated. That is a massive waste of time. The 3rd option would involve modifying assignments of NA, NaN, and infinite values (+/- Inf), so that an error is produced. That seems like it’s better left to R Core. The 4th option is like the 2nd — I’d need a call to a separate function listing all of the memory locations, just to ID those that have changed, and then check the values; I’m not even sure this will work for all objects, as a program may do an in-place modification, which seems like it would not invoke the duplicate function.

Is there a better approach that I’m missing? Maybe some clever tool by Mark Bravington, Luke Tierney, or something relatively basic — something akin to an options() parameter or a flag when compiling R?

Example code Here is some very simple example code to test with, incorporating the addTaskCallback function proposed by Josh O’Brien. The code isn’t interrupted, but an error does occur in the first scenario, while no error occurs in the second case (i.e. badDiv(0,0,FALSE) doesn’t abort). I’m still investigating callbacks, as this looks promising.

Note 1. I’d be satisfied with a solution for standard R operations, though a lot of my calculations involve objects used via data.table or bigmemory (i.e. disk-based memory mapped matrices). These appear to have somewhat different memory behaviors than standard matrix and data.frame operations.

Note 2. The callbacks idea seems a bit more promising, as this doesn’t require me to write functions that mutate R code, e.g. via the body() idea.

Note 3. I don’t know whether or not there is some simple way to test the presence of non-finite values, e.g. meta information about objects that indexes where NAs, Infs, etc. are stored in the object, or if these are stored in place. So far, I’ve tried Simon Urbanek’s inspect package, and have not found a way to divine the presence of non-numeric values.

Follow-up: Simon Urbanek has pointed out in a comment that such information is not available as meta information for objects.

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