There is a horizontal row of n cubes. The length of each cube is given. You need to create a new vertical pile of cubes. The new pile should follow these directions: if cubei is on top of cubej then sideLengthj >= sideLengthi.When stacking the cubes, you can only pick up either the leftmost or …
The NumPy module also comes with a number of built-in routines for linear algebra calculations. These can be found in the sub-module linalg. linalg.det The linalg.det tool computes the determinant of an array. print numpy.linalg.det([[1 , 2], [2, 1]]) #Output : -3.0 linalg.eigThe linalg.eig computes the eigenvalues and right eigenvectors of a square array. vals, vecs = …
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PolyThe poly tool returns the coefficients of a polynomial with the given sequence of roots. print numpy.poly([-1, 1, 1, 10]) #Output : [ 1 -11 9 11 -10] rootsThe roots tool returns the roots of a polynomial with the given coefficients. print numpy.roots([1, 0, -1]) #Output : [-1. 1.] PolyintThe polyint tool returns an antiderivative …
innerThe inner tool returns the inner product of two arrays. import numpy A = numpy.array([0, 1]) B = numpy.array([3, 4]) print numpy.inner(A, B) #Output : 4 outer The outer tool returns the outer product of two arrays. import numpy A = numpy.array([0, 1]) B = numpy.array([3, 4]) print numpy.outer(A, B) #Output : [[0 0] # [3 4]] Task : You …
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dotThe dot tool returns the dot product of two arrays. import numpy A = numpy.array([ 1, 2 ]) B = numpy.array([ 3, 4 ]) print numpy.dot(A, B) #Output : 11 CrossThe cross tool returns the cross product of two arrays. import numpy A = numpy.array([ 1, 2 ]) B = numpy.array([ 3, 4 ]) print …
meanThe mean tool computes the arithmetic mean along the specified axis. import numpy my_array = numpy.array([ [1, 2], [3, 4] ]) print numpy.mean(my_array, axis = 0) #Output : [ 2. 3.] print numpy.mean(my_array, axis = 1) #Output : [ 1.5 3.5] print numpy.mean(my_array, axis = None) #Output : 2.5 print numpy.mean(my_array) #Output : 2.5 By …
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