numpy.arccos() in Python

Python | Numpy np.coords() method

Last Updated : 03 Nov, 2019

With the help of np.coords() method, we can get the coordinates of a next value in iteration using np.coords() method.

Syntax : np.coords() Return : Return the coordinates of next iterator.

Example #1 : In this example we can see that by using np.coords() method, we are able to get the coordinates of a next iterator using this method.

Python3 1=1

# import numpy
import numpy as np

a = np.array([1, 2, 3])
# using np.coords() method
gfg = a.flat
next(gfg)
print(gfg.coords)

Output :

(1, )

Example #2 :

Python3 1=1

# import numpy
import numpy as np

a = np.array([[1, 2, 3], [4, 5, 6]])
# using np.coords() method
gfg = a.flat
next(gfg)
next(gfg)
next(gfg)
next(gfg)
print(gfg.coords)

Output :

(1, 1)

numpy.arccos() in Python

J

Jitender_1998

Improve

Article Tags :

Practice Tags :

python

Similar Reads

numpy.cosh() in Python

The numpy.cosh() is a mathematical function that helps user to calculate hyperbolic cosine for all x(being the array elements). Equivalent to 1/2 * (np.exp(x) - np.exp(-x)) and np.cos(1j*x). Syntax : numpy.cosh(x[, out]) = ufunc 'cos') Parameters : array : [array_like] elements are in radians. 2pi R

numpy.cos() in Python

numpy.cos(x[, out]) = ufunc 'cos') : This mathematical function helps user to calculate trigonometric cosine for all x(being the array elements). Parameters : array : [array_like]elements are in radians. 2pi Radians = 360 degrees Return : An array with trigonometric cosine of x for all x i.e. array

numpy.arccosh() in Python

numpy.arccosh() : This mathematical function helps user to calculate inverse hyperbolic cosine, element-wise for all arr. Syntax : numpy.arccosh(arr, /, out=None, *, where=True, casting='same_kind', order='K', dtype=None, ufunc 'arccosh') Parameters : arr : array_like Input array. out : [ndarray, op

numpy.arccos() in Python

numpy.arccos(x[, out]) = ufunc 'arccos') : This mathematical function helps user to calculate inverse cos for all x(being the array elements). Parameters : array : [array_like]elements are in radians. out : [array_like]array of same shape as x. Note : 2pi Radians = 360 degrees The convention is to r

numpy.median() in Python

numpy.median(arr, axis = None) : Compute the median of the given data (array elements) along the specified axis. How to calculate median? Given data points. Arrange them in ascending order Median = middle term if total no. of terms are odd. Median = Average of the terms in the middle (if total no. o

Python | numpy.cov() function

Covariance provides the measure of strength of correlation between two variable or more set of variables. The covariance matrix element Cij is the covariance of xi and xj. The element Cii is the variance of xi. If COV(xi, xj) = 0 then variables are uncorrelatedIf COV(xi, xj) > 0 then variables po

numpy.argsort() in Python

numpy.argsort() is a function in NumPy that returns the indices that would sort an array. In other words, it gives you the indices that you would use to reorder the elements in an array to be in sorted order.Example: Pythonimport numpy as geek a = geek.array([2, 0, 1, 5, 4, 1, 9]) print("Input unsor

numpy.ndarray.ndim() method | Python

numpy.ndarray.ndim() function return the number of dimensions of an array. Syntax : numpy.ndarray.ndim(arr) Parameters : arr : [array_like] Input array. If it is not already an ndarray, a conversion is attempted. Return : [int] Return the number of dimensions in arr. Code #1 : Python3 # Python progr

numpy.hypot() in Python

This mathematical function helps user to calculate hypotenuse for the right angled triangle, given its side and perpendicular. Result is equivalent to Equivalent to sqrt(x1**2 + x2**2), element-wise. Syntax : numpy.exp2(arr1, arr2[, out]) = ufunc 'hypot') : Parameters : arr1, arr2 : [array_like] Leg

Python | Numpy numpy.ndarray.__mod__()

With the help of Numpy numpy.ndarray.__mod__(), every element in an array is operated on binary operator i.e mod(%). Remember we can use any type of values in an array and value for mod is applied as the parameter in ndarray.__mod__(). Syntax: ndarray.__mod__($self, value, /) Return: self%value Exam