Algorithm算法代写代考

Design Report I create the RoadMap class for the road map system and the Vertex class, Edge class, Road class to model the vertex, edge, and road respectively. The vertex type and event type are represented as enum. All the API function is defined in class RoadMap. The RoadMap class contains fields: vertexes, edges and

1. The reduction Step 1 let the variable in 3SAT is x1, x2, ….. xn, we add corresponding variables Y1, Y2, ….. Yn, and add following inequality: Yi ≥ 0, Yi = 1 . Obviously, this reduction can be done in polynomial-time. Now we prove that 3SAT is satisfiable if and only if the resulting

Part I 1) Use greedy strategy with shortest job first. Sort the jobs with non-decreasing order in time. This can be done by merge sort algorithm in O(nlog(n)). Proof. Suppose ord is the ordering array. Average = (t(ord(1)) + (t(ord(1)+t(ord(2)) + (t(ord(1))+t(ord(2))+t(ord(3)) + … + (t(ord(1)+t(ord(2))+…+t(ord(n)))/n. Note that The t(ord(1)) appears in the most times,

MyRansacLineFit_student In [1]: import numpy as np import numpy.linalg as la import matplotlib import matplotlib.pyplot as plt from skimage.measure import ransac %matplotlib notebook In [2]: class LeastSquareLine: def __init__(self): self.a = 0.0 self.b = 0.0 def estimate(self, points2D): B = points2D[:,1] A = np.copy(points2D) A[:,1] = 1.0 # SVD (singular value decomposition) for (Nx2) matrix A =