`math` — Mathematical functions¶

This module provides access to the mathematical functions 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.

Number-theoretic and representation functions
`ceil(x)`	Ceiling of x, the smallest integer greater than or equal to x
`comb(n, k)`	Number of ways to choose k items from n items without repetition and without order
`copysign(x, y)`	Magnitude (absolute value) of x with the sign of y
`fabs(x)`	Absolute value of x
`factorial(n)`	n factorial
`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`
`fmod(x, y)`	Remainder of division `x / y`
`frexp(x)`	Mantissa and exponent of x
`fsum(iterable)`	Sum of values in the input iterable
`gcd(*integers)`	Greatest common divisor of the integer arguments
`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
`isinf(x)`	Check if x is a positive or negative infinity
`isnan(x)`	Check if x is a NaN (not a number)
`isqrt(n)`	Integer square root of a nonnegative integer n
`lcm(*integers)`	Least common multiple of the integer arguments
`ldexp(x, i)`	`x * (2**i)`, inverse of function `frexp()`
`modf(x)`	Fractional and integer parts of x
`nextafter(x, y, steps)`	Floating-point value steps steps after x towards y
`perm(n, k)`	Number of ways to choose k items from n items without repetition and with order
`prod(iterable, start)`	Product of elements in the input iterable with a start value
`remainder(x, y)`	Remainder of x with respect to y
`sumprod(p, q)`	Sum of products from two iterables p and q
`trunc(x)`	Integer part of x
`ulp(x)`	Value of the least significant bit of x
Power 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
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
`dist(p, q)`	Euclidean distance between two points p and q given as an iterable of coordinates
`hypot(*coordinates)`	Euclidean norm of an iterable of coordinates
`sin(x)`	Sine of x
`tan(x)`	Tangent of x
Angular conversion
`degrees(x)`	Convert angle x from radians to degrees
`radians(x)`	Convert angle x from degrees to radians
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)

Number-theoretic and representation functions¶

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.comb(n, k)¶

Return the number of ways to choose k items from n items without repetition and without order.

Evaluates to n! / (k! * (n - k)!) when k <= n and evaluates to zero when k > n.

Also called the binomial coefficient because it is equivalent to the coefficient of k-th term in polynomial expansion of (1 + x)ⁿ.

Raises TypeError if either of the arguments are not integers. Raises ValueError if either of the arguments are negative.

Added in version 3.8.

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.fabs(x)¶: Return the absolute value of x.

math.factorial(n)¶: Return n factorial as an integer. Raises ValueError if n is not integral or is negative.

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

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.fmod(x, y)¶: Return fmod(x, y), as defined by the platform C library. 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.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.

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.gcd(*integers)¶: Return the greatest common divisor of the specified integer arguments. If any of the arguments is nonzero, then the returned value is the largest positive integer that is a divisor of all arguments. If all arguments are zero, then the returned value is 0. gcd() without arguments returns 0.

Added in version 3.5.

Changed in version 3.9: Added support for an arbitrary number of arguments. Formerly, only two arguments were supported.

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 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.

Power 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.

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.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.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.sin(x)¶: Return the sine of x radians.

math.tan(x)¶: Return the tangent of x radians.

Angular conversion¶

math.degrees(x)¶: Convert angle x from radians to degrees.

math.radians(x)¶: Convert angle x from degrees to 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.

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.

`math` — Mathematical functions¶

Number-theoretic and representation functions¶

Power and logarithmic functions¶

Trigonometric functions¶

Angular conversion¶

Hyperbolic functions¶

Special functions¶

Constants¶

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math — Mathematical functions¶

Number-theoretic and representation functions¶

Power and logarithmic functions¶

Trigonometric functions¶

Angular conversion¶

Hyperbolic functions¶

Special functions¶

Constants¶

`math` — Mathematical functions¶