Python Matrix.transpose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 transpose [as 别名]
class TestMatrix(TestCase):

    def setUp(self):	
        self.m1 = Matrix([[1, 2], 
		          [3, 4]])

	self.m2 = Matrix([[-1, 5], 
		          [0, 9]])

	self.m3 = Matrix([[-1, 5, 4],
			  [0, 9, 1],
			  [4, 5, 2]]) 

	self.m4 = Matrix([[-1, 5], 
		          [0, 9],
			  [3, 2]])

    def test_bad_matrix(self):
        """Make sure the input matrix is valid"""

        # should raise an exception for an empty matrix
        self.assertRaises(TypeError, Matrix, [])
	
        # should raise an exception for an invalid matrix
        self.assertRaises(TypeError, Matrix, ['a'])

        # should raise an exception for an incorrect matrix
	# must be 2-dimensional
        self.assertRaises(TypeError, Matrix, [1, 2])

    def test_row_col_getters(self):
	# get row with index 1
	self.assertEqual(self.m1.row(1), [3, 4])

	# get col with index 1
	self.assertEqual(self.m1.col(1), [2, 4])

    def test_transposal(self):
	self.m1.transpose()
	self.assertEqual(self.m1.matrix, [[1, 3], [2, 4]])

    def test_addition(self):
	# should raise an exception for addition of matrices with 
	# different lengths
	self.assertRaises(IndexError, self.m1.__add__, self.m3)

	# test simple addition
	self.assertEqual((self.m1 + self.m2).matrix, [[0, 7], [3, 13]])

    def test_multiplication(self):
	# test whether number of columns in multiplicand
	# is equal to number of rows in multiplier
        self.assertRaises(IndexError, self.m1.__mul__, self.m3)
	
	# test multiplication
	self.assertEqual((self.m3 * self.m4).matrix, [[13, 48], 
                                                      [3, 83], 
	                                              [2, 69]])

# 需要导入模块: from matrix import Matrix [as 别名]
# 或者: from matrix.Matrix import transpose [as 别名]
 def testTranspose(self):
     matrix = Matrix([1, 2], [3, 4])
     self.assertEquals(
         Matrix([1, 3], [2, 4]),
         matrix.transpose())
     matrix2 = Matrix([1, 2, 3], [4, 5, 6], [7, 8, 9])
     self.assertEquals(
         Matrix([1, 4, 7], [2, 5, 8], [3, 6, 9]),
         matrix2.transpose())

# 需要导入模块: from matrix import Matrix [as 别名]
# 或者: from matrix.Matrix import transpose [as 别名]
    def test_should_contain_1337_in_last_row_after_transpose(self):
        cols = 100
        rows = 1
        matrix = Matrix(cols, rows, 1)
        val = 1337
        matrix.set_item(cols - 1, 0, val)

        matrix.transpose()

        self.assertEquals(val, matrix.get_item(0, cols - 1))

# 需要导入模块: from matrix import Matrix [as 别名]
# 或者: from matrix.Matrix import transpose [as 别名]
def rotationMethod(m,A,a,epsilon,p):
    #print("Start Rotation.")
    VECTOR = 1
    X = Matrix(m,VECTOR)
    oldA = Matrix(m,m)
    r = Matrix(m,VECTOR)
    iterationNumber = 0
    condition = True
    #print("Entering while.")
    while condition:
        #print("OldA copy.")
        oldA = copy.deepcopy(A)
        #print("0")
        r = copy.deepcopy(a.substractMatrix(A.matrixMultiplication(X,a)))
        #print("1")
        (xpq,p,q) = getMax(A.lowerTriangularMatrix())
        #print("2")
        theta = 0
        if A.lowerTriangularMatrix().at(p,p) == A.lowerTriangularMatrix().at(q,q):
            #print("3")
            theta = math.pi/4
        else:
            #print("4")
            theta = ( 2 * xpq )/(A.upperTriangularMatrix().at(p,p) - A.upperTriangularMatrix().at(q,q) + (10**(-5)))
        #print("Determined theta.")
        c = math.cos(theta)
        s = math.sin(theta)
        #print("5")
        T = Matrix(m,m)
        for i in range(0,T.numberOfColumns):
            T.insert(i,i,1)
        T.insert(p,p,c)
        T.insert(p,q,s)
        T.insert(q,p,-s)
        T.insert(q,q,c)
        #print("Determined T.")
        A = copy.deepcopy((T.transpose()).multiplyMatrix(oldA.multiplyMatrix(T)))
        #condition = not r.isAlmostZero()
        if iterationNumber%100 == 0:
            print("-----")
            print("Situation at iteration:",iterationNumber)
            print("Condition:",condition)
            print("A matrix:")
            A.display()
            print("X matrix:")
            X.display()
            print("-----")
        X = copy.deepcopy(oldA)
        iterationNumber += 1
        condition = iterationNumber > 10**(15)
        #condition = checkX(X)

    print("===== Rotation Method =====")
    print("X:")
    X.display()
    print("A:")
    A.display()
    #print("Test:")
    #r.display()
    print("====================")

# 需要导入模块: from matrix import Matrix [as 别名]
# 或者: from matrix.Matrix import transpose [as 别名]
 def train(self, vector):
     matrix_2 = Matrix(vector)
     matrix_1 = Matrix(matrix_2.transpose())
     matrix_3 = matrix_2 * matrix_1
     identity = Matrix.identity(len(vector))
     matrix_4 = matrix_3 - identity
     self.weight = self.weight + matrix_4

# 需要导入模块: from matrix import Matrix [as 别名]
# 或者: from matrix.Matrix import transpose [as 别名]
 def test_transpose_2_by_2_matrix(self):
     m = Matrix(2, 2)
     m[0][0] = 1
     m[0][1] = 2
     m[1][0] = 3
     m[1][1] = 4
     mt = m.transpose()
     self.assertEqual(mt[0][0], 1)
     self.assertEqual(mt[0][1], 3)
     self.assertEqual(mt[1][0], 2)
     self.assertEqual(mt[1][1], 4)

# 需要导入模块: from matrix import Matrix [as 别名]
# 或者: from matrix.Matrix import transpose [as 别名]
class Newton():
    def __init__(self, bases, lmd=0, err=1):
        self.bases = bases
        self.lmd = lmd
        self.err = err

    def fit(self, x, y):
        A = []
        for i in range(self.bases):
            A.append([float(xi)**i for xi in x])
        A.reverse()
        self.A = Matrix(A).transpose()
        self.b = Matrix([y]).transpose()

        w0 = Matrix([[0 for i in range(self.bases)]]).transpose()
        while True:
            w1 = w0 - self.hession(w0).inverse() * self.gradient(w0)
            if abs(self.error(w1).data[0][0] - self.error(w0).data[0][0]) < self.err:
                break
            w0 = w1
        self.w = w1
        return self.w.transpose().data[0]

    def show(self):
        w = self.w.transpose().data[0]
        for i in range(self.bases-1):
            print("(%.3f x^%d) + " % (w[i], self.bases-i-1), end='')
        print("(%.3f) = y" % w[-1])

    def score(self):
        return round(self.error(self.w).data[0][0], 3)

    def error(self, x):
        return (self.A * x - self.b).transpose() * (self.A * x - self.b)

    def gradient(self, x):
        return self.A.transpose() * self.A * 2 * x - self.A.transpose() * self.b * 2

    def hession(self, x):
        return self.A.transpose() * self.A * 2

# 需要导入模块: from matrix import Matrix [as 别名]
# 或者: from matrix.Matrix import transpose [as 别名]
 def filter(x, P):
     for n in range(len(self.measurements)):
         # prediction
         x = (self.F * x) + self.u
         P = self.F * P * self.F.transpose()
         
         # measurement update
         Z = Matrix([self.measurements[n]])
         y = Z.transpose() - (self.H * x)
         S = self.H * P * self.H.transpose() + self.R
         K = P * self.H.transpose() * S.inverse()
         x = x + (K * y)
         P = (self.I - (K * self.H)) * P
     return x,P    

# 需要导入模块: from matrix import Matrix [as 别名]
# 或者: from matrix.Matrix import transpose [as 别名]
 def get_householder_transform(mtrx, col):
     sum_pow_2 = 0
     for i in range(col, mtrx.size[0]):
         sum_pow_2 += mtrx[i][col] ** 2
     v = Matrix((mtrx.size[0], 1))
     v[col][0] = mtrx[col][col] + math.copysign(math.sqrt(sum_pow_2), mtrx[col][col])
     for i in range(col + 1, mtrx.size[0]):
         v[i][0] = mtrx[i][col]
     h_mtrx = Matrix.identity(mtrx.size)
     transpose_v = v.transpose()
     tmp_mtrx = v * transpose_v
     tmp_mtrx *= 2 / (transpose_v * v)[0][0]
     h_mtrx -= tmp_mtrx
     return h_mtrx

# 需要导入模块: from matrix import Matrix [as 别名]
# 或者: from matrix.Matrix import transpose [as 别名]
def rotationMethod(m,A,a,epsilon,p):
    VECTOR = 1
    X = Matrix(m,VECTOR)
    oldA = Matrix(m,m)
    r = Matrix(m,VECTOR)
    iterationNumber = 0
    condition = True
    while condition:
        oldA = copy.deepcopy(A)
        r = copy.deepcopy(a.substractMatrix(A.matrixMultiplication(X,a)))
        (xpq,p,q) = getMax(A.lowerTriangularMatrix())
        theta = 0
        if A.lowerTriangularMatrix().at(p,p) == A.lowerTriangularMatrix().at(q,q):
            theta = math.pi/4
        else:
            theta = (1/2)*math.arct(( 2 * xpq )/(A.upperTriangularMatrix().at(p,p) - A.upperTriangularMatrix().at(q,q)))
        c = math.cos(theta)
        s = math.sin(theta)
        T = Matrix(m,m)
        for i in range(0,T.numberOfColumns):
            T.insert(i,i,1)
        T.insert(p,p,c)
        T.insert(p,q,s)
        T.insert(q,p,-s)
        T.insert(q,q,c)
        A = copy.deepcopy((T.transpose()).multiplyMatrix(oldA.multiplyMatrix(T)))
        '''
        if iterationNumber%100 == 0:
            print("-----")
            print("Situation at iteration:",iterationNumber)
            print("Condition:",condition)
            print("A matrix:")
            A.display()
            print("X matrix:")
            X.display()
            print("-----")
        '''
        X = copy.deepcopy(oldA)
        iterationNumber += 1
        condition = (iterationNumber < ITERATIONS)

    print("===== Rotation Method =====")
    print("X:")
    X.display()
    print("A:")
    A.display()
    print("Test:")
    r.display()
    print("====================")

# 需要导入模块: from matrix import Matrix [as 别名]
# 或者: from matrix.Matrix import transpose [as 别名]
 def test_transpose_non_quadratic_matrix(self):
     m = Matrix(2, 3)
     m[0][0] = 1
     m[0][1] = 2
     m[0][2] = 3
     m[1][0] = 4
     m[1][1] = 5
     m[1][2] = 6
     mt = m.transpose()
     self.assertEqual(mt[0][0], 1)
     self.assertEqual(mt[1][0], 2)
     self.assertEqual(mt[2][0], 3)
     self.assertEqual(mt[0][1], 4)
     self.assertEqual(mt[1][1], 5)
     self.assertEqual(mt[2][1], 6)

# 需要导入模块: from matrix import Matrix [as 别名]
# 或者: from matrix.Matrix import transpose [as 别名]
def matrix_trans_mult(m, v):
    '''Takes an openGL matrix and a 2 Vector and return
    the transpose of teh matrix applied to the vector'''
    if _use_numpy:
        mat = numpy.matrix(m)
        vec = numpy.matrix(v)
        result = vec*mat.T
        return Vector(result[0,0],result[0,1])
    else:
        mat = Matrix([
            RowVector(list(m[0])),
            RowVector(list(m[1])),
            RowVector(list(m[2])),
            RowVector(list(m[3]))] )
        vec = RowVector(v)
        result = vec*mat.transpose()
        return Vector(result[1], result[2])

# 需要导入模块: from matrix import Matrix [as 别名]
# 或者: from matrix.Matrix import transpose [as 别名]
 def mlr(self, order=2):
     sname = self.listSamples()
     X = self.sample[sname[0]]
     Y = self.sample[sname[1]]
     if X.rowcount == Y.rowcount: slen = X.rowcount
     elif X.rowcount > Y.rowcount: slen = Y.rowcount
     else: slen = X.rowcount
     X_data = X.data[:slen]
     Y_data = Y.data[:slen]
     data_array = [[1]*slen]
     for x in range(1, order+1):
         data_array.append([element**x for element in X_data])
     beta_matrix = Matrix(data_array)
     b1 = beta_matrix * beta_matrix.transpose()
     b1 = b1.inverse()
     b2 = Matrix(data_array) * Matrix([Y_data]).transpose()
     result = b1 * b2
     return [x[0] for x in result.m]

# 需要导入模块: from matrix import Matrix [as 别名]
# 或者: from matrix.Matrix import transpose [as 别名]
    def testTranspose(self):
        """Траспонирование матрицы"""

        # выполняем транспонирование матрицы и проверяем результат
        a = Matrix(3, 2)
        a.set(0, 0, 1)
        a.set(0, 1, 2)
        a.set(1, 0, 3)
        a.set(1, 1, 4)
        a.set(2, 0, 5)
        a.set(2, 1, 6)

        b = Matrix(2, 3)
        b.set(0, 0, 1)
        b.set(1, 0, 2)
        b.set(0, 1, 3)
        b.set(1, 1, 4)
        b.set(0, 2, 5)
        b.set(1, 2, 6)
        self.assertEqual(a.transpose(), b)

# 需要导入模块: from matrix import Matrix [as 别名]
# 或者: from matrix.Matrix import transpose [as 别名]
class LSE():
    def __init__(self, bases, lmd=0):
        self.bases = bases
        self.lmd = lmd

    def fit(self, x, y):
        A = []
        for i in range(self.bases):
            A.append([float(xi)**i for xi in x])
        A.reverse()
        self.A = Matrix(A).transpose()
        self.b = Matrix([y]).transpose()
        self.w = (self.A.transpose() * self.A + Matrix(self.bases) * self.lmd).inverse() * (self.A.transpose() * self.b)
        return self.w.transpose().data[0]

    def show(self):
        w = self.w.transpose().data[0]
        for i in range(self.bases-1):
            print("(%.3f x^%d) + " % (w[i], self.bases-i-1), end='')
        print("(%.3f) = y" % w[-1])

    def score(self):
        return round(((self.A * self.w - self.b).transpose() * (self.A * self.w - self.b)).data[0][0], 3)