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Suppose, we have n integers in an array nums. We have to find out if the numbers in the array are pairwise coprime, setwise coprime, or not coprime.Two numbers nums[i] and nums[j] are said to be pairwise coprime if gcd(nums[i], nums[j]) = 1. This should hold for every number pair in the array and i < j.The numbers are said to be setwise coprime if gcd(nums[i]) = 1.If they are neither, we say that they are not coprime.So, if the input is like n = 4, nums = {7, 11, 13, 17}, then the output will be the numbers are ... Read More
To get the Inner product of two arrays, use the numpy.inner() method in Python. Ordinary inner product of vectors for 1-D arrays, in higher dimensions a sum product over the last axes. The parameters are 1 and b, two vectors. If a and b are nonscalar, their last dimensions must match.StepsAt first, import the required libraries −import numpy as npCreating two numpy One-Dimensional array using the array() method −arr1 = np.arange(2).reshape((1, 1, 2)) arr2 = np.arange(6).reshape((3, 2))Display the arrays −print("Array1...", arr1) print("Array2...", arr2)Check the Dimensions of both the arrays −print("Dimensions of Array1...", arr1.ndim) print("Dimensions of Array2...", arr2.ndim)Check the Shape of ... Read More
To get the Outer product of an array and a scalar, use the numpy.outer() method in Python. The 1st parameter a is the first input vector. Input is flattened if not already 1-dimensional. The 2nd parameter b is the second input vector. Input is flattened if not already 1-dimensional. The 3rd parameter out is a location where the result is stored.Given two vectors, a = [a0, a1, ..., aM] and b = [b0, b1, ..., bN], the outer product is −[[a0*b0 a0*b1 ... a0*bN ] [a1*b0 . [ ... . [aM*b0 aM*bN ]]StepsAt first, import the required ... Read More
Suppose, there are 2n number of letters and each of them has an integer number between 1 to n written on them. There are exactly two letters that have the same number written on them. These letters are arranged into m stacks and stack i has letters stack[i] on it. Our task is to empty all the stacks in the following mannerWe have to choose any two stacks and remove the top letter from both of them.The letters that we have removed must have the same number on both of them.If we can empty the m stacks in this manner, ... Read More
Given two vectors, a = [a0, a1, ..., aM] and b = [b0, b1, ..., bN], the outer product is −[[a0*b0 a0*b1 ... a0*bN ] [a1*b0 . [ ... . [aM*b0 aM*bN ]]To get the Outer product of an array with vector of letters, use the numpy.outer() method in Python. The 1st parameter a is the first input vector. Input is flattened if not already 1-dimensional. The 2nd parameter b is the second input vector. Input is flattened if not already 1-dimensional. The 3rd parameter out is a location where the result is storedStepsAt first, import ... Read More
Given two vectors, a = [a0, a1, ..., aM] and b = [b0, b1, ..., bN], the outer product [1] is −[[a0*b0 a0*b1 ... a0*bN ] [a1*b0 . [ ... . [aM*b0 aM*bN ]]To get the Outer product of two arrays, use the numpy.outer() method in Python. The numpy.ones() return a new array of given shape and type, filled with ones. The numpy.linspace() returns evenly spaced numbers over a specified interval.StepsAt first, import the required libraries −import numpy as np The real part −rl = np.outer(np.ones((5, )), np.linspace(-2, 2, 5)) print("The real part of the complex number...", ... Read More
To get the Outer product of two One-Dimensional arrays, use the numpy.outer() method in Python. The 1st parameter a is the first input vector. Input is flattened if not already 1-dimensional. The 2nd parameter b is the second input vector. Input is flattened if not already 1-dimensional. The 3rd parameter out is a location where the result is stored.Given two vectors, a = [a0, a1, ..., aM] and b = [b0, b1, ..., bN], the outer product [1] is −[[a0*b0 a0*b1 ... a0*bN ] [a1*b0 . [ ... . [aM*b0 aM*bN ]]StepsAt first, import the required libraries ... Read More
To get the Outer product of two multi-dimensional arrays, use the numpy.outer() method in Python. The 1st parameter a is the first input vector. Input is flattened if not already 1-dimensional. The 2nd parameter b is the second input vector. Input is flattened if not already 1-dimensional. The 3rd parameter out is a location where the result is stored.Given two vectors, a = [a0, a1, ..., aM] and b = [b0, b1, ..., bN], the outer product [1] is −[[a0*b0 a0*b1 ... a0*bN ] [a1*b0 . [ ... . [aM*b0 aM*bN ]]StepsAt first, import the required libraries ... Read More
To Compute the sign and natural logarithm of the determinant of an array, use the numpy.linalg.slogdet() method in Python. The 1st parameter, s is an input array, has to be a square 2-D array.The method, with sign returns a number representing the sign of the determinant. For a real matrix, this is 1, 0, or -1. For a complex matrix, this is a complex number with absolute value 1, or else 0. The method, with logdet returns the natural log of the absolute value of the determinant. If the determinant is zero, then sign will be 0 and logdet will ... Read More
To return the cumulative product of array elements over a given axis treating NaNs as one, use the nancumprod() method. The cumulative product does not change when NaNs are encountered and leading NaNs are replaced by ones. Ones are returned for slices that are all-NaN or empty.The method returns a new array holding the result is returned unless out is specified, in which case it is returned. Cumulative works like, 5, 5*10, 5*10*15, 5*10*15*20. The 1st parameter is the input array. The 2nd parameter is the Axis along which the cumulative product is computed. By default the input is flattened.The ... Read More