Python numpy Trigonometric Functions

Python numpy module has various trigonometric functions such as sin, cos, tan, sinh, cosh, tanh, arcsin, arccos, arctan, arctan2, arcsinh, arccosh, arctanh, radians, degrees, hypot, deg2rad, rad2deg, and unwrap. Use these numpy Trigonometric Functions on both one dimensional and multi-dimensional arrays.

We use the below arrays to demonstrate the Python numpy Trigonometric Function.

arr1 = np.array([0, 30, 45, 60, 90, 180])
arr1
 
arr2 = np.random.randint(0, 10, size = (10))
arr2
 
arr3 = np.random.randint(10, size = (5, 5))
arr3
 
arr4 = np.random.random((10))
arr4
 
arr5 = np.random.random((5, 5))
arr5
 
arr6 = np.linspace(-1, 1, 10)
arr6
Python NumPy Trigonometric Functions

Python numpy Trigonometric Functions Examples

The list of available Python numpy Trigonometric Functions with an example of each.

Python numpy sin function returns the sine value of a given array.

np.sin(arr1)
np.sin(arr2)
np.sin(arr3)
np.sin(arr6)
NumPy sin

The Python numpy cos function returns the cosine value of a given array.

np.cos(arr1)
np.cos(arr2)
np.cos(arr3)
np.cos(arr6)
NumPy cos

The Python numpy tan function returns the tangent value of a given array.

np.tan(arr1)
np.tan(arr2)
np.tan(arr3)
np.tan(arr6)
NumPy tan

Python numpy sinh function returns the hyperbolic sine value of a given array.

np.sinh(arr1)
np.sinh(arr2)
np.sinh(arr3)
NumPy sinh

The Python numpy cosh function prints the hyperbolic cosine value of all the elements in a given Python array.

np.cosh(arr1)
np.cosh(arr2)
np.cosh(arr3)
NumPy cosh

The Python numpy tanh trigonometric function display the hyperbolic tangent values of a given array.

np.tanh(arr1)
np.tanh(arr2)
np.tanh(arr3)
NumPy tanh

Python numpy arcsinh function returns the hyperbolic arc sine value of a given array.

np.arcsinh(arr1)
np.arcsinh(arr2)
np.arcsinh(arr3)
NumPy arcsinh

Python numpy arccosh function returns the hyperbolic arc cosine value of all the elements in a given array.

np.arccosh(arr1)
np.arccosh(arr2)
np.arccosh(arr3)
NumPy arccosh

The numpy arctanh function returns the hyperbolic arc tangent values of a given array.

np.arctanh(arr4)
np.arctanh(arr5)
np.arctanh(arr6)
NumPy arctanh

The numpy arcsin function returns the arc sine values of a given array.

np.arcsin(arr4)
np.arcsin(arr5)
np.arcsin(arr6)
NumPy arcsin

Python numpy arccos function returns the given array arc cosine values.

np.arccos(arr4)
np.arccos(arr5)
np.arccos(arr6)
NumPy arccos

This Python numpy arctan function returns the arc tangent values of an array.

np.arctan(arr1)
np.arctan(arr2)
np.arctan(arr3)
NumPy arctan

The Python numpy arctan2 function returns the element-wise arc tangent values of an array. It accepts two arrays as arguments x1 and x2 and returns x1/x2.

np.arctan2(arr2, arr6)
np.arctan2(arr6, arr2)
np.arctan2(arr3, arr5)
np.arctan2(arr5, arr3)
NumPy arctan2

Python numpy hypot function returns the hypotenuse of the arguments x1 and x2.

np.hypot(arr2, arr6)
np.hypot(arr3, arr5)
NumPy hypot

The Python numpy radians function converts angles from degrees to radians in an array.

np.radians(arr1)
np.radians(arr1 * 30)
np.radians(arr1 * 180)
 
np.radians(arr2 * 90)
np.radians(arr3 * 180)
np.radians(arr4)
np.radians(arr5 * 180)
NumPy radians

The Python numpy degrees function converts angles from radians to degrees in an array.

np.degrees(arr1)
np.degrees(arr1/30)
np.degrees(arr1/60)

np.degrees(arr2)
np.degrees(arr3/30)
np.degrees(arr4)
np.degrees(arr5)
NumPy degrees

Python numpy deg2rad function converts from degrees to radians. deg2rad(n) is similar or equal to n * pi / 180 (pi or np.pi holds value 3.14)

np.deg2rad(180)
 
np.deg2rad(arr1)

x = np.array([0, 30, 60, 90, 120, 180, 360])
np.deg2rad(x)
NumPy deg2rad

The Python numpy rad2deg function converts from radians to degrees. rad2deg(n) is similar or equal to 180 * n / pi (pi = 3.14)

np.rad2deg(5)
 
np.rad2deg(arr2)
np.rad2deg(arr5)
np.rad2deg(arr6)
NumPy rad2deg

Python numpy unwrap function unwraps the values by changing deltas between values.

np.unwrap(arr2)
np.unwrap(arr3)
np.unwrap(arr4)
np.unwrap(arr5)
np.unwrap(arr6)
NumPy unwrap