symmetric

问题 I have searched all this morning but I've found websites where it is said that data is sent through an asymmetric encryption using the TLS protocol. Then I found the contrary. Please can you tell me which is true? Thanks. And does anyone know a guide where it is explained step by step the handshake of TLS protocol over http? 回答1: HTTP uses no encryption at all, as defined in https://tools.ietf.org/html/rfc2616 HTTPS on other hand, uses TLS which may choose from bunch of algorithms to achieve

问题 There are many cases in which JavaScript's type-coercing equality operator is not transitive. For example, see "JavaScript equality transitivity is weird." However, are there any cases in which == isn't symmetric ? That is, where a == b is true and b == a is false ? 回答1: In Javascript, == is always symmetric. The spec says: NOTE 2 The equality operators maintain the following invariants: A != B is equivalent to !(A == B) . A == B is equivalent to B == A , except in the order of evaluation of

问题 There are many cases in which JavaScript's type-coercing equality operator is not transitive. For example, see "JavaScript equality transitivity is weird." However, are there any cases in which == isn't symmetric ? That is, where a == b is true and b == a is false ? 回答1: In Javascript, == is always symmetric. The spec says: NOTE 2 The equality operators maintain the following invariants: A != B is equivalent to !(A == B) . A == B is equivalent to B == A , except in the order of evaluation of

问题 Anyone able to help me speed up some code: n = seq_len(ncol(mat)) # seq 1 to ncol(mat) sym.pr<-outer(n,n,Vectorize(function(a,b) { return(adf.test(LinReg(mat[,c(a,b)]),k=0,alternative="stationary")$p.value) })) Where mat is an NxM matrix of N observation and M objects, e.g: Obj1 Obj2 Obj3 1 . . . 2 . . . 3 . . . LinReg is defined as: # Performs linear regression via OLS LinReg=function(vals) { # regression analysis # force intercept c at y=0 regline<-lm(vals[,1]~as.matrix(vals[,2:ncol(vals)])

问题 Anyone able to help me speed up some code: n = seq_len(ncol(mat)) # seq 1 to ncol(mat) sym.pr<-outer(n,n,Vectorize(function(a,b) { return(adf.test(LinReg(mat[,c(a,b)]),k=0,alternative="stationary")$p.value) })) Where mat is an NxM matrix of N observation and M objects, e.g: Obj1 Obj2 Obj3 1 . . . 2 . . . 3 . . . LinReg is defined as: # Performs linear regression via OLS LinReg=function(vals) { # regression analysis # force intercept c at y=0 regline<-lm(vals[,1]~as.matrix(vals[,2:ncol(vals)])

问题 I am learning C++ and I was wondering if I could gain some insight into the preferred way of creating binary operators that work on instances of two different types. Here is an example that I've made to illustrate my concerns: class A; class B; class A { private: int x; public: A(int x); int getX() const; int operator + (const B& b); }; class B { private: int x; public: B(int x); int getX() const; int operator + (const A& A); }; A::A(int x) : x(x) {} int A::getX() const { return x; } //

问题 I tried to make a random symmetric matrix to test my program. I don't care about the data at all as long as it is symmetric (sufficient randomness is no concern at all). My first attempt was this: x=np.random.random((100,100)) x+=x.T However, np.all(x==x.T) returns False. print x==x.T yields array([[ True, True, True, ..., False, False, False], [ True, True, True, ..., False, False, False], [ True, True, True, ..., False, False, False], ..., [False, False, False, ..., True, True, True],

问题 I want to make my matrix symmetric with regard to the row names and columns names, for example, I have a matrix > ma a b c d a 1 5 9 13 c 9 10 11 15 b 5 6 10 14 d 13 14 15 16 I want to make it like > ma a b c d a 1 5 9 13 b 5 6 10 14 c 9 10 11 15 d 13 14 15 16 Which means the matrix is symmetric in terms of row.names and column names are equal, so as the matrix is symmetric as well (actually I am working on adjacency matrix, thus it is rather important for adjacency matrix to be symmetric.

问题 I am trying to create a symmetric matrix n x n matrix and fill it using a n*(n+1)/2 dimension array using the boost library in c++ . So far, I am able to create the matrix, and fill it with random values using the following code #include <iostream> #include <fstream> #include </usr/include/boost/numeric/ublas/matrix.hpp> #include </usr/include/boost/numeric/ublas/matrix_sparse.hpp> #include </usr/include/boost/numeric/ublas/symmetric.hpp> #include </usr/include/boost/numeric/ublas/io.hpp>

问题 Given this data.frame: 'sample', which represents pairwise wins and losses among species: sp1<-c(0,1,0) sp3<-c(1,2,2) sp5<-c(3,1,0) sample<-as.data.frame(cbind(sp1,sp3,sp5)) rownames(sample)<-c("sp1","sp6","sp8") which should look like this: sp1 sp3 sp5 sp1 0 1 3 sp6 1 2 1 sp8 0 2 0 How do I modify 'sample' so that it has the same column names as rownames, and viceversa, and fill in the added columns or rows with zeros for the dataframe to be symmetric and look like shown below? (I prefer