# 需要导入模块: from Vector import Vector [as 别名]# 或者: from Vector.Vector importmultiply[as 别名]defcollisionActor(self, actor):ifnotactor.bbox.overlaps(self.bbox):returnFalse, Vector(0,0)# Line segment 1: p + t*r# Line segment 2: q + u*sp = Vector(actor.location.x, actor....
importnumpyasnpclassCalculator:vector=[]def__init__(self,vector):self.vector=vectordefmultiply(self,scalar,vector):returnnp.add(np.multiply(scalar,self.vector),vector).tolist() Then to instance the class directly in Node constnodecallspython=require("node-calls-python");constpy=nodecallspython...
(in other words: we multiply each component of the first vector with each component of the second vector) Here is how it's done in Python: defscale(u,v): return[a * bfora,binzip(u,v)] defscale_by_scalar(u,scalar): return[a * scalarforainu] Usage: u=[1,2] v=[3,4] print...
以下内容大致对应课程(MIT 18.06 Linear Algebra课程,以下简称课程)第一、二讲的内容。 在线性代数中,主要涉及3种数据类型,常量、标量(Scalar)、向量(Vector)、矩阵(Matrix)。 无论NumPy还是SymPy,都直接使用了基本Python类型作为标量,比如: 代码语言:javascript 复制 c1=5 而对于向量和矩阵,处理方法则有很大区别,下...
Now, as it turns out, the SciPy matrix multiplication function is smart enough to infer what you intend if you multiply a matrix and an array so the call to reshape isn’t really necessary here. Next, the demo program displays the values in matrices A and b: XML C...
Scalar(255), 2, 8); //绘制最小外接矩形每条边 cv::line(img_copy_roi, rect[j], rect[(j + 1) % 4], cv::Scalar(255, 0, 0), 2, 8); //绘制最小外接矩形每条边 } } } outImg = img_copy_roi.clone(); } void read_video() { vector<double> sigema; vector<double> weight;...
Z -- a scalar value, result of convolving the sliding window (W, b) on a slice x of the input data """ s = np.multiply(a_slice_prev,W) Z = np.sum(s) Z = Z + float(b) #将b转化为浮点数,将Z转成标量. return Z
[1:]=vector# 将三维向量拓展到四元数,首位为0v_rot=quaternion_multiply(quaternion_multiply(q,v),np.array([q[0],-q[1],-q[2],-q[3]]))rotated_vector=v_rot[1:]# 提取旋转后的三维部分returnrotated_vector@njitdefquaternion_shift_numba(V_outer_I,thetax,thetay,thetaz):q_x=create_...
协议:CC BY-NC-SA 4.0 第五章:用 Python 进行更多数学 概述 在本章结束时,你将能够掌握序列和级数的基本概念,并编写实现这些概念的 Python 函数。你将了解基本三角函数及其应用之间的关系,比如著名的毕达哥拉斯定理。你将练习向量微积分,并通过在 Python 中进行向量代数来了解它的适用性。最后,你会感到高兴,因...
# Multiply by external factorg *= dx*np.exp(-complex(0,1)*w*x0) if sort_results:zipped_lists = zip(w, g)sorted_pairs = sorted(zipped_lists)sorted_list1, sorted_list2 = zip(*sorted_pairs)w = np.array(list(sorted_list1))g = np.ar...