Python Matrix.find_max方法代码示例

# 需要导入模块: from Matrix import Matrix [as 别名]
# 或者: from Matrix.Matrix import find_max [as 别名]
    def power(self, iterations, mat, estimate):
        r = 1
        k = 0
        m = iterations
        y = estimate
        x = mat.multiply(y)
        while r > .001 and k < m:
            max_x = x.find_max()
            x.scaler(1 / max_x)
            y = Matrix(x.get_data())
            x = mat.multiply(y)
            temp = Matrix(y.get_data())
            temp.transpose()
            a = temp.multiply(x).get_data()[0][0]
            b = temp.multiply(y).get_data()[0][0]
            mu = a / b
            r = Matrix(y.get_data())
            r.scaler(mu)
            r = r.subtract(x)
            r = r.find_max()
            k += 1

        y.scaler(1 / mu)

        return mu, mat.trace() - mu, y

# 需要导入模块: from Matrix import Matrix [as 别名]
# 或者: from Matrix.Matrix import find_max [as 别名]
class Points:
    def __init__(self):
        self.data = []
        self.points = {}
        self.set_points()
        self.temp_dist = []
        self.distance = Matrix([[0]])
        self.set_distances()
        self.random_bins = [0] * 100
        self.random_total = 0
        self.random_squares = 0
        self.random_count = 0
        self.random_best_dist = self.distance.find_max() * len(self.distance.get_data())
        self.random_best_trip = []
        self.genetic_best_dist = self.distance.find_max() * len(self.distance.get_data())
        self.genetic_best_trip = []
        self.genetic_bins = [0] * 100

    # Return Matrix that is composed of the distances between points being tested
    def get_distances(self):
        return self.distance

    # Return random search bins
    def get_random_bins(self):
        return self.random_bins

    # Return the summation of all trips tested in the random search
    def get_random_total(self):
        return self.random_total

    # Return the summation of all trips squared
    def get_random_squares(self):
        return self.random_squares

    # Return the number of trips tested
    def get_random_count(self):
        return self.random_count

    # Print the bins for the random search
    def print_random_bins(self):
        print('Random bins')
        for i in range(len(self.random_bins)):
            print(self.random_bins[i])

    # Print the bins for the genetic search
    def print_genetic_bins(self):
        print('Genetic bins')
        for i in range(len(self.genetic_bins)):
            print(self.genetic_bins[i])

    # Get points from a file
    def set_points(self):
        count = 1
        temp = []
        filename = open('points.txt', 'r')
        for line in filename:
            row = line.strip()
            temp.append(row)
        for i in range(0, len(temp)):
            self.data.append(temp[i].split())
        for i in self.data:
            mat = Matrix([[float(i[0]), float(i[1])]])
            self.points[count] = mat
            count += 1

    # Create a matrix of each points distance from the other points
    def set_distances(self):
        for i in range(1, 15):
            temp = []
            for j in range(1, 15):
                x1 = self.points[i].get_data()[0][0]
                y1 = self.points[i].get_data()[0][1]
                x2 = self.points[j].get_data()[0][0]
                y2 = self.points[j].get_data()[0][1]
                temp.append(math.hypot(x2 - x1, y2 - y1))
            self.temp_dist.append(temp)
        self.distance = Matrix(self.temp_dist)

    # Create a random trip, including all cities in TSP problem
    def random_trip(self):
        dist = random.sample(range(14), 14)
        for i in range(len(dist)):
            dist[i] += 1
        return dist

    # Performs the random search of finding a possible solution
    # Takes in the number of random trips to evaluate
    # Also returns the best trip and the cost of the best trip
    def random_search(self, iterations):
        self.random_count = iterations
        for i in range(iterations):
            trip = self.random_trip()
            dist = test.calculate_distance(trip)

            if dist < self.random_best_dist:
                self.random_best_dist = dist
                self.random_best_trip = trip
            self.random_total += dist
            self.random_squares += dist * dist
            index = int((dist - 20) / -0.2)
#.........这里部分代码省略.........