numpy_quaternion 2个四元数之间的角度 numpy_quaternion是一个计算两个四元数之间角度的库函数,具体实现过程如下: 1. 首先,导入 numpy 库。 2. 定义 quaternion_to_rotation_matrix 函数,将四元数转换为旋转矩阵,用于计算旋转轴和角度。 3. 定义 quaternion_to_axis_angle 函数,将四元数转换为旋转轴和角度。
R = q.rotation_matrix() # 将四元数转换为旋转矩阵 要将旋转矩阵转换为四元数,我们可以使用以下代码: R = np.array([[0.70710678, -0.70710678, 0.0], [0.70710678, 0.70710678, 0.0], [0.0, 0.0, 1.0]]) # 创建一个旋转矩阵 q = rotation_matrix_to_quaternion(R) # 将旋转矩阵转换为四元数 四元...
# 将四元数转换为旋转矩阵rotation_matrix=q.to_matrix() 异常处理 在使用numpy-quaternion库时,可能会遇到一些异常。例如,如果尝试创建一个四元数的虚部分量超出了[-1, 1]的范围,就会引发InvalidQuaternion异常。处理这些异常的方法是使用try-except语句: try:# 尝试创建一个四元数invalid_q=quaternion(1,2,3,...
该题最终的代码为 importnumpyasnpimportmathfromscipy.spatial.transformimportRotationasRdefquaternion2rot(quaternion):r=R.from_quat(quaternion)rot=r.as_matrix()returnrotdefquaternion_to_rotation_matrix(q):w,x,y,z=qreturn2*np.array([[0.5-y**2-z**2,x*y-z*w,x*z+y*w],[x*y+z*w,0.5-...
to obtain the matrixmfroma quaternionic arrayq1. (Here,mis actually a series of 100 3x3 matrices corresponding to the 100 quaternions inq1.) On the other hand, to obtain a quaternionic array from some matrixm, we would write q2=quaternionic.array.from_rotation_matrix(m) ...
It is also possible to convert a quaternion to or from a 3x3 array of floats representing a rotation matrix, or an array of N quaternions to or from an Nx3x3 array of floats representing N rotation matrices, usingas_rotation_matrixandfrom_rotation_matrix. Similar conversions are possible for...
raise ValueError('Norm of (x, y, z) part of quaternion too close to zero') value[1:4] = value[1:4] / norm * needed_norm # assert abs(np.linalg.norm(value) - 1.0) < _epsilon elif key == 'scaling': value = np.array(value, dtype=np.float32).reshape(3) ...
浏览完整代码 来源:Quaternion.py 项目:pchokanson/atlas-sim示例4def test_mult_simple(self): tempa = [[1,0,0],[0,1,0],[0,0,1]] self.a = matlib.matrix(tempa) self.b = matlib.matrix(tempa) self.c = matlib.matrix(tempa) self.d = multiplierMatrice(self.a, self.b) self.assert...
def random_quat(rand=None): """Return uniform random unit quaternion. rand: array like or None Three independent random variables that are uniformly distributed between 0 and 1. >>> q = random_quat() >>> np.allclose(1.0, vector_norm(q)) True >>> q = random_quat(np.random.random(...
()defquaternion2rot(quaternion):r=Rotation.from_quat(quaternion)rot=r.as_matrix()returnrotposes=[]withopen("pose.txt","r")asf:lines=f.readlines()forlineinlines:data=list(map(lambdax:float(x),line.split(' ')))t=data[0:3]x,y,z,w=data[3:]q=np.array([x,y,z,w])R=quaternion2...