# `math` — Mathematical functions

This module provides access to common mathematical functions and constants, including those defined by the C standard.

These functions cannot be used with complex numbers; use the functions of the same name from the `cmath` module if you require support for complex numbers. The distinction between functions which support complex numbers and those which don’t is made since most users do not want to learn quite as much mathematics as required to understand complex numbers. Receiving an exception instead of a complex result allows earlier detection of the unexpected complex number used as a parameter, so that the programmer can determine how and why it was generated in the first place.

The following functions are provided by this module. Except when explicitly noted otherwise, all return values are floats.

Floating point arithmetic
`ceil(x)` | Ceiling of x, the smallest integer greater than or equal to x
`fabs(x)` | Absolute value of x
`floor(x)` | Floor of x, the largest integer less than or equal to x
`fma(x, y, z)` | Fused multiply-add operation: `(x * y) + z`
`fmax(x, y)` | Maximum of two floating-point values
`fmin(x, y)` | Minimum of two floating-point values
`fmod(x, y)` | Remainder of division `x / y`
`modf(x)` | Fractional and integer parts of x
`remainder(x, y)` | Remainder of x with respect to y
`trunc(x)` | Integer part of x
Floating point manipulation functions
`copysign(x, y)` | Magnitude (absolute value) of x with the sign of y
`frexp(x)` | Mantissa and exponent of x
`isclose(a, b, rel_tol, abs_tol)` | Check if the values a and b are close to each other
`isfinite(x)` | Check if x is neither an infinity nor a NaN
`isnormal(x)` | Check if x is a normal number
`issubnormal(x)` | Check if x is a subnormal number
`isinf(x)` | Check if x is a positive or negative infinity
`isnan(x)` | Check if x is a NaN (not a number)
`ldexp(x, i)` | `x * (2**i)`, inverse of function `frexp()`
`nextafter(x, y, steps)` | Floating-point value steps steps after x towards y
`signbit(x)` | Check if x is a negative number
`ulp(x)` | Value of the least significant bit of x
Power, exponential and logarithmic functions
`cbrt(x)` | Cube root of x
`exp(x)` | e raised to the power x
`exp2(x)` | 2 raised to the power x
`expm1(x)` | e raised to the power x, minus 1
`log(x, base)` | Logarithm of x to the given base (e by default)
`log1p(x)` | Natural logarithm of 1+x (base e)
`log2(x)` | Base-2 logarithm of x
`log10(x)` | Base-10 logarithm of x
`pow(x, y)` | x raised to the power y
`sqrt(x)` | Square root of x
Summation and product functions
`dist(p, q)` | Euclidean distance between two points p and q given as an iterable of coordinates
`fsum(iterable)` | Sum of values in the input iterable
`hypot(*coordinates)` | Euclidean norm of an iterable of coordinates
`prod(iterable, start)` | Product of elements in the input iterable with a start value
`sumprod(p, q)` | Sum of products from two iterables p and q
Angular conversion
`degrees(x)` | Convert angle x from radians to degrees
`radians(x)` | Convert angle x from degrees to radians
Trigonometric functions
`acos(x)` | Arc cosine of x
`asin(x)` | Arc sine of x
`atan(x)` | Arc tangent of x
`atan2(y, x)` | `atan(y / x)`
`cos(x)` | Cosine of x
`sin(x)` | Sine of x
`tan(x)` | Tangent of x
Hyperbolic functions
`acosh(x)` | Inverse hyperbolic cosine of x
`asinh(x)` | Inverse hyperbolic sine of x
`atanh(x)` | Inverse hyperbolic tangent of x
`cosh(x)` | Hyperbolic cosine of x
`sinh(x)` | Hyperbolic sine of x
`tanh(x)` | Hyperbolic tangent of x
Special functions
`erf(x)` | Error function at x
`erfc(x)` | Complementary error function at x
`gamma(x)` | Gamma function at x
`lgamma(x)` | Natural logarithm of the absolute value of the Gamma function at x
Constants
`pi` | π = 3.141592…
`e` | e = 2.718281…
`tau` | τ = 2π = 6.283185…
`inf` | Positive infinity
`nan` | “Not a number” (NaN)

## Floating point arithmetic

math.ceil(x)

  Return the ceiling of x, the smallest integer greater than or equal to x. If x is not a float, delegates to `x.__ceil__`, which should return an `Integral` value.

math.fabs(x)

  Return the absolute value of x.

math.floor(x)

  Return the floor of x, the largest integer less than or equal to x. If x is not a float, delegates to `x.__floor__`, which should return an `Integral` value.

math.fma(x, y, z)

  Fused multiply-add operation. Return `(x * y) + z`, computed as though with infinite precision and range followed by a single round to the `float` format. This operation often provides better accuracy than the direct expression `(x * y) + z`.

  This function follows the specification of the fusedMultiplyAdd operation described in the IEEE 754 standard. The standard leaves one case implementation-defined, namely the result of `fma(0, inf, nan)` and `fma(inf, 0, nan)`. In these cases, `math.fma` returns a NaN, and does not raise any exception.

  Added in version 3.13.

math.fmax(x, y)

  Get the larger of two floating-point values, treating NaNs as missing data.

  When both operands are (signed) NaNs or zeroes, return `nan` and `0` respectively and the sign of the result is implementation-defined, that is, `fmax()` is not required to be sensitive to the sign of such operands (see Annex F of the C11 standard, §F.10.0.3 and §F.10.9.2).

  Added in version 3.15.

math.fmin(x, y)

  Get the smaller of two floating-point values, treating NaNs as missing data.

  When both operands are (signed) NaNs or zeroes, return `nan` and `0` respectively and the sign of the result is implementation-defined, that is, `fmin()` is not required to be sensitive to the sign of such operands (see Annex F of the C11 standard, §F.10.0.3 and §F.10.9.3).

  Added in version 3.15.

math.fmod(x, y)

  Return the floating-point remainder of `x / y`, as defined by the platform C library function `fmod(x, y)`. Note that the Python expression `x % y` may not return the same result. The intent of the C standard is that `fmod(x, y)` be exactly (mathematically; to infinite precision) equal to `x - n*y` for some integer n such that the result has the same sign as x and magnitude less than `abs(y)`. Python’s `x % y` returns a result with the sign of y instead, and may not be exactly computable for float arguments. For example, `fmod(-1e-100, 1e100)` is `-1e-100`, but the result of Python’s `-1e-100 % 1e100` is `1e100-1e-100`, which cannot be represented exactly as a float, and rounds to the surprising `1e100`. For this reason, function `fmod()` is generally preferred when working with floats, while Python’s `x % y` is preferred when working with integers.

math.modf(x)

  Return the fractional and integer parts of x. Both results carry the sign of x and are floats.

  Note that `modf()` has a different call/return pattern than its C equivalents: it takes a single argument and return a pair of values, rather than returning its second return value through an ‘output parameter’ (there is no such thing in Python).

math.remainder(x, y)

  Return the IEEE 754-style remainder of x with respect to y. For finite x and finite nonzero y, this is the difference `x - n*y`, where `n` is the closest integer to the exact value of the quotient `x / y`. If `x / y` is exactly halfway between two consecutive integers, the nearest even integer is used for `n`. The remainder `r = remainder(x, y)` thus always satisfies `abs(r) <= 0.5 * abs(y)`.

  Special cases follow IEEE 754: in particular, `remainder(x, math.inf)` is x for any finite x, and `remainder(x, 0)` and `remainder(math.inf, x)` raise `ValueError` for any non-NaN x. If the result of the remainder operation is zero, that zero will have the same sign as x.

  On platforms using IEEE 754 binary floating point, the result of this operation is always exactly representable: no rounding error is introduced.

  Added in version 3.7.

math.trunc(x)

  Return x with the fractional part removed, leaving the integer part. This rounds toward 0: `trunc()` is equivalent to `floor()` for positive x, and equivalent to `ceil()` for negative x. If x is not a float, delegates to `x.__trunc__`, which should return an `Integral` value.

For the `ceil()`, `floor()`, and `modf()` functions, note that all floating-point numbers of sufficiently large magnitude are exact integers. Python floats typically carry no more than 53 bits of precision (the same as the platform C double type), in which case any float x with `abs(x) >= 2**52` necessarily has no fractional bits.

## Floating point manipulation functions

math.copysign(x, y)

  Return a float with the magnitude (absolute value) of x but the sign of y. On platforms that support signed zeros, `copysign(1.0, -0.0)` returns -1.0.

math.frexp(x)

  Return the mantissa and exponent of x as the pair `(m, e)`. m is a float and e is an integer such that `x == m * 2**e` exactly. If x is zero, returns `(0.0, 0)`, otherwise `0.5 <= abs(m) < 1`. This is used to “pick apart” the internal representation of a float in a portable way.

  Note that `frexp()` has a different call/return pattern than its C equivalents: it takes a single argument and return a pair of values, rather than returning its second return value through an ‘output parameter’ (there is no such thing in Python).

math.isclose(a, b, *, rel_tol=1e-09, abs_tol=0.0)

  Return `True` if the values a and b are close to each other and `False` otherwise.

  Whether or not two values are considered close is determined according to given absolute and relative tolerances. If no errors occur, the result will be: `abs(a-b) <= max(rel_tol * max(abs(a), abs(b)), abs_tol)`.

  rel_tol is the relative tolerance – it is the maximum allowed difference between a and b, relative to the larger absolute value of a or b. For example, to set a tolerance of 5%, pass `rel_tol=0.05`. The default tolerance is `1e-09`, which assures that the two values are the same within about 9 decimal digits. rel_tol must be nonnegative and less than `1.0`.

  abs_tol is the absolute tolerance; it defaults to `0.0` and it must be nonnegative. When comparing `x` to `0.0`, `isclose(x, 0)` is computed as `abs(x) <= rel_tol * abs(x)`, which is `False` for any nonzero `x` and rel_tol less than `1.0`. So add an appropriate positive abs_tol argument to the call.

  The IEEE 754 special values of `NaN`, `inf`, and `-inf` will be handled according to IEEE rules. Specifically, `NaN` is not considered close to any other value, including `NaN`. `inf` and `-inf` are only considered close to themselves.

  Added in version 3.5.

  See also

  PEP 485 – A function for testing approximate equality

math.isfinite(x)

  Return `True` if x is neither an infinity nor a NaN, and `False` otherwise. (Note that `0.0` is considered finite.)

  Added in version 3.2.

math.isnormal(x)

  Return `True` if x is a normal number, that is a finite nonzero number that is not a subnormal (see `issubnormal()`). Return `False` otherwise.

  Added in version 3.15.

math.issubnormal(x)

  Return `True` if x is a subnormal number, that is a finite nonzero number with a magnitude smaller than `sys.float_info.min`. Return `False` otherwise.

  Added in version 3.15.

math.isinf(x)

  Return `True` if x is a positive or negative infinity, and `False` otherwise.

math.isnan(x)

  Return `True` if x is a NaN (not a number), and `False` otherwise.

math.ldexp(x, i)

  Return `x * (2**i)`. This is essentially the inverse of function `frexp()`.

math.nextafter(x, y, steps=1)

  Return the floating-point value steps steps after x towards y.

  If x is equal to y, return y, unless steps is zero.

  Examples:

  - `math.nextafter(x, math.inf)` goes up: towards positive infinity.

  - `math.nextafter(x, -math.inf)` goes down: towards minus infinity.

  - `math.nextafter(x, 0.0)` goes towards zero.

  - `math.nextafter(x, math.copysign(math.inf, x))` goes away from zero.

  See also `math.ulp()`.

  Added in version 3.9.

  Changed in version 3.12: Added the steps argument.

math.signbit(x)

  Return `True` if the sign of x is negative and `False` otherwise.

  This is useful to detect the sign bit of zeroes, infinities and NaNs.

  Added in version 3.15.

math.ulp(x)

  Return the value of the least significant bit of the float x:

  - If x is a NaN (not a number), return x.

  - If x is negative, return `ulp(-x)`.

  - If x is a positive infinity, return x.

  - If x is equal to zero, return the smallest positive denormalized representable float (smaller than the minimum positive normalized float, `sys.float_info.min`).

  - If x is equal to the largest positive representable float, return the value of the least significant bit of x, such that the first float smaller than x is `x - ulp(x)`.

  - Otherwise (x is a positive finite number), return the value of the least significant bit of x, such that the first float bigger than x is `x + ulp(x)`.

  ULP stands for “Unit in the Last Place”.

  See also `math.nextafter()` and `sys.float_info.epsilon`.

  Added in version 3.9.

## Power, exponential and logarithmic functions

math.cbrt(x)

  Return the cube root of x.

  Added in version 3.11.

math.exp(x)

  Return e raised to the power x, where e = 2.718281… is the base of natural logarithms. This is usually more accurate than `math.e ** x` or `pow(math.e, x)`.

math.exp2(x)

  Return 2 raised to the power x.

  Added in version 3.11.

math.expm1(x)

  Return e raised to the power x, minus 1. Here e is the base of natural logarithms. For small floats x, the subtraction in `exp(x) - 1` can result in a significant loss of precision; the `expm1()` function provides a way to compute this quantity to full precision:

      >>> from math import exp, expm1
      >>> exp(1e-5) - 1  # gives result accurate to 11 places
      1.0000050000069649e-05
      >>> expm1(1e-5)    # result accurate to full precision
      1.0000050000166668e-05

  Added in version 3.2.

math.log(x[, base])

  With one argument, return the natural logarithm of x (to base e).

  With two arguments, return the logarithm of x to the given base, calculated as `log(x)/log(base)`.

math.log1p(x)

  Return the natural logarithm of 1+x (base e). The result is calculated in a way which is accurate for x near zero.

math.log2(x)

  Return the base-2 logarithm of x. This is usually more accurate than `log(x, 2)`.

  Added in version 3.3.

  See also

  `int.bit_length()` returns the number of bits necessary to represent an integer in binary, excluding the sign and leading zeros.

math.log10(x)

  Return the base-10 logarithm of x. This is usually more accurate than `log(x, 10)`.

math.pow(x, y)

  Return x raised to the power y. Exceptional cases follow the IEEE 754 standard as far as possible. In particular, `pow(1.0, x)` and `pow(x, 0.0)` always return `1.0`, even when x is a zero or a NaN. If both x and y are finite, x is negative, and y is not an integer then `pow(x, y)` is undefined, and raises `ValueError`.

  Unlike the built-in `**` operator, `math.pow()` converts both its arguments to type `float`. Use `**` or the built-in `pow()` function for computing exact integer powers.

  Changed in version 3.11: The special cases `pow(0.0, -inf)` and `pow(-0.0, -inf)` were changed to return `inf` instead of raising `ValueError`, for consistency with IEEE 754.

math.sqrt(x)

  Return the square root of x.

## Summation and product functions

math.dist(p, q)

  Return the Euclidean distance between two points p and q, each given as a sequence (or iterable) of coordinates. The two points must have the same dimension.

  Roughly equivalent to:

      sqrt(sum((px - qx) ** 2.0 for px, qx in zip(p, q)))

  Added in version 3.8.

math.fsum(iterable)

  Return an accurate floating-point sum of values in the iterable. Avoids loss of precision by tracking multiple intermediate partial sums.

  The algorithm’s accuracy depends on IEEE-754 arithmetic guarantees and the typical case where the rounding mode is half-even. On some non-Windows builds, the underlying C library uses extended precision addition and may occasionally double-round an intermediate sum causing it to be off in its least significant bit.

  For further discussion and two alternative approaches, see the ASPN cookbook recipes for accurate floating-point summation.

math.hypot(*coordinates)

  Return the Euclidean norm, `sqrt(sum(x**2 for x in coordinates))`. This is the length of the vector from the origin to the point given by the coordinates.

  For a two dimensional point `(x, y)`, this is equivalent to computing the hypotenuse of a right triangle using the Pythagorean theorem, `sqrt(x*x + y*y)`.

  Changed in version 3.8: Added support for n-dimensional points. Formerly, only the two dimensional case was supported.

  Changed in version 3.10: Improved the algorithm’s accuracy so that the maximum error is under 1 ulp (unit in the last place). More typically, the result is almost always correctly rounded to within 1/2 ulp.

math.prod(iterable, *, start=1)

  Calculate the product of all the elements in the input iterable. The default start value for the product is `1`.

  When the iterable is empty, return the start value. This function is intended specifically for use with numeric values and may reject non-numeric types.

  Added in version 3.8.

math.sumprod(p, q)

  Return the sum of products of values from two iterables p and q.

  Raises `ValueError` if the inputs do not have the same length.

  Roughly equivalent to:

      sum(map(operator.mul, p, q, strict=True))

  For float and mixed int/float inputs, the intermediate products and sums are computed with extended precision.

  Added in version 3.12.

## Angular conversion

math.degrees(x)

  Convert angle x from radians to degrees.

math.radians(x)

  Convert angle x from degrees to radians.

## Trigonometric functions

math.acos(x)

  Return the arc cosine of x, in radians. The result is between `0` and `pi`.

math.asin(x)

  Return the arc sine of x, in radians. The result is between `-pi/2` and `pi/2`.

math.atan(x)

  Return the arc tangent of x, in radians. The result is between `-pi/2` and `pi/2`.

math.atan2(y, x)

  Return `atan(y / x)`, in radians. The result is between `-pi` and `pi`. The vector in the plane from the origin to point `(x, y)` makes this angle with the positive X axis. The point of `atan2()` is that the signs of both inputs are known to it, so it can compute the correct quadrant for the angle. For example, `atan(1)` and `atan2(1, 1)` are both `pi/4`, but `atan2(-1, -1)` is `-3*pi/4`.

math.cos(x)

  Return the cosine of x radians.

math.sin(x)

  Return the sine of x radians.

math.tan(x)

  Return the tangent of x radians.

## Hyperbolic functions

Hyperbolic functions are analogs of trigonometric functions that are based on hyperbolas instead of circles.

math.acosh(x)

  Return the inverse hyperbolic cosine of x.

math.asinh(x)

  Return the inverse hyperbolic sine of x.

math.atanh(x)

  Return the inverse hyperbolic tangent of x.

math.cosh(x)

  Return the hyperbolic cosine of x.

math.sinh(x)

  Return the hyperbolic sine of x.

math.tanh(x)

  Return the hyperbolic tangent of x.

## Special functions

math.erf(x)

  Return the error function at x.

  The `erf()` function can be used to compute traditional statistical functions such as the cumulative standard normal distribution:

      def phi(x):
          'Cumulative distribution function for the standard normal distribution'
          return (1.0 + erf(x / sqrt(2.0))) / 2.0

  Added in version 3.2.

math.erfc(x)

  Return the complementary error function at x. The complementary error function is defined as `1.0 - erf(x)`. It is used for large values of x where a subtraction from one would cause a loss of significance.

  Added in version 3.2.

math.gamma(x)

  Return the Gamma function at x.

  Added in version 3.2.

math.lgamma(x)

  Return the natural logarithm of the absolute value of the Gamma function at x.

  Added in version 3.2.

## Number-theoretic functions

For backward compatibility, the `math` module provides also aliases of the following functions from the `math.integer` module:

`comb(n, k)` | Number of ways to choose k items from n items without repetition and without order
`factorial(n)` | n factorial
`gcd(*integers)` | Greatest common divisor of the integer arguments
`isqrt(n)` | Integer square root of a nonnegative integer n
`lcm(*integers)` | Least common multiple of the integer arguments
`perm(n, k)` | Number of ways to choose k items from n items without repetition and with order

Added in version 3.5: The `gcd()` function.

Added in version 3.8: The `comb()`, `perm()` and `isqrt()` functions.

Added in version 3.9: The `lcm()` function.

Changed in version 3.9: Added support for an arbitrary number of arguments in the `gcd()` function. Formerly, only two arguments were supported.

Changed in version 3.10: Floats with integral values (like `5.0`) are no longer accepted in the `factorial()` function.

Deprecated since version 3.15: These aliases are soft deprecated in favor of the `math.integer` functions.

## Constants

math.pi

  The mathematical constant π = 3.141592…, to available precision.

math.e

  The mathematical constant e = 2.718281…, to available precision.

math.tau

  The mathematical constant τ = 6.283185…, to available precision. Tau is a circle constant equal to 2π, the ratio of a circle’s circumference to its radius. To learn more about Tau, check out Vi Hart’s video Pi is (still) Wrong, and start celebrating Tau day by eating twice as much pie!

  Added in version 3.6.

math.inf

  A floating-point positive infinity. (For negative infinity, use `-math.inf`.) Equivalent to the output of `float('inf')`.

  Added in version 3.5.

math.nan

  A floating-point “not a number” (NaN) value. Equivalent to the output of `float('nan')`. Due to the requirements of the IEEE-754 standard, `math.nan` and `float('nan')` are not considered to equal to any other numeric value, including themselves. To check whether a number is a NaN, use the `isnan()` function to test for NaNs instead of `is` or `==`. Example:

      >>> import math
      >>> math.nan == math.nan
      False
      >>> float('nan') == float('nan')
      False
      >>> math.isnan(math.nan)
      True
      >>> math.isnan(float('nan'))
      True

  Added in version 3.5.

  Changed in version 3.11: It is now always available.

CPython implementation detail: The `math` module consists mostly of thin wrappers around the platform C math library functions. Behavior in exceptional cases follows Annex F of the C99 standard where appropriate. The current implementation will raise `ValueError` for invalid operations like `sqrt(-1.0)` or `log(0.0)` (where C99 Annex F recommends signaling invalid operation or divide-by-zero), and `OverflowError` for results that overflow (for example, `exp(1000.0)`). A NaN will not be returned from any of the functions above unless one or more of the input arguments was a NaN; in that case, most functions will return a NaN, but (again following C99 Annex F) there are some exceptions to this rule, for example `pow(float('nan'), 0.0)` or `hypot(float('nan'), float('inf'))`.

Note that Python makes no effort to distinguish signaling NaNs from quiet NaNs, and behavior for signaling NaNs remains unspecified. Typical behavior is to treat all NaNs as though they were quiet.

See also

Module `cmath`

  Complex number versions of many of these functions.

Module `math.integer`

  Integer-specific mathematics functions.