C++实现R语言向量化运算（向量类：c 矩阵类：matrix）2015.9.11
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类源代码：
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- #include
- using std::cout;
- using std::endl;
- using std::cin;
- using std::istream;
- using std::ios_base;
- #include
- using std::vector;
- #include
- using std::initializer_list;
- #include
- using std::for_each;
- using std::sort;
- using std::copy;
- using std::find;
- #include
- using std::runtime_error;
- #include
- using std::srand;
- using std::rand;
- using std::system;
- #include
- using std::time;
- #include
- using std::sqrt;
- #include
- using std::pair;
- using std::make_pair;
- #include
- using std::setw;
- #include
- using std::multiset;
- using std::set;
- #include
- using std::unordered_map;
- using std::unordered_multimap;
- #include
- using std::multimap;
- using std::map;
- class matrix;
- class c
- {
- private:
- vector c_val;
- size_t dim;
- public:
- c():c_val(vector()),dim(0){}
- c(initializer_listlst);
- c(const vector&c_v):c_val(c_v),dim(c_v.size()){}
- c(const matrix&m);
- void out(size_t n=1)const{cout<<“The vector is:\n”;for(size_t i=0;i<<setw(n)<<c_val[i]<<“ ”;cout<<endl<<endl;}
- double operator[](size_t i)const{return c_val[i];}
- double& operator[](size_t i){return c_val[i];}
- size_t re_dim()const{return dim;}
- friend c operator+(const c&a,const c&b);
- friend c operator-(const c&a);
- friend c operator-(const c&a,const c&b);
- friend c rep(const double&d,size_t n);
- friend c operator+(const c&a,const double&d);
- friend c operator-(const c&a,const double&d);
- friend c operator+(const double&d,const c&a);
- friend c operator-(const double&d,const c&a);
- friend c operator*(const double&d,const c&a);
- friend c operator*(const c&a,const double&d);
- friend c operator/(const double&d,const c&a);
- friend c operator/(const c&a,const double&d);
- friend c operator*(const c&a,const c&b);
- friend bool operator==(const c&a,const c&b){return a.c_val==b.c_val;}
- friend bool operator!=(const c&a,const c&b){return a.c_val!=b.c_val;}
- vector const_re_c_val()const{return c_val;}
- };
- class matrix
- {
- private:
- vector m_val;
- size_t rdim;
- size_t cdim;
- public:
- matrix():m_val(vector()),rdim(0),cdim(0){}
- matrix(const vector&m):m_val(m),rdim(m_val.size()),cdim(m_val[0].re_dim()){}
- matrix(size_t m,size_t n,const double&d):m_val(vector(m,vector(n,d))),rdim(m),cdim(n){}
- matrix(const c&v,size_t r,size_t c);
- matrix(const c&v);
- c operator[](size_t i)const{return m_val[i];}
- c& operator[](size_t i){return m_val[i];}
- void out(size_t n=3)const;
- c col(size_t i)const;
- void col_change(size_t i,const c&a);
- friend matrix operator+(const matrix&a,const matrix&b);
- friend matrix operator-(const matrix&a);
- friend matrix operator-(const matrix&a,const matrix&b);
- friend matrix operator+(const matrix&a,const double&d);
- friend matrix operator+(const double&d,const matrix&a);
- friend matrix operator-(const matrix&a,const double&d);
- friend matrix operator-(const double&b,const matrix&a);
- friend matrix operator*(const matrix&a,const double&d);
- friend matrix operator*(const double&d,const matrix&a);
- friend matrix operator/(const matrix&a,const double&d);
- friend matrix operator/(const double&d,const matrix&a);
- void Swap(size_t i,size_t j)
- {c temp=this->operator[](i);this->operator[](i)=this->operator[](j);this->operator[](j)=temp;}
- void col_Swap(size_t i,size_t j)
- {
- auto temp=this->col(i);
- this->col_change(i,this->col(j));
- this->col_change(j,temp);
- }
- friend bool operator==(const matrix&a,const matrix&b){return a.m_val==b.m_val;}
- friend bool operator!=(const matrix&a,const matrix&b){return a.m_val!=b.m_val;}
- pair re_dim()const{return make_pair(rdim,cdim);}
- friend c operator%(const matrix&m,const c&v);
- friend matrix operator%(const matrix&a,const matrix&b);
- friend matrix operator%(const c&v,const matrix&m);
- };
- //类c的有关定义
- c::c(initializer_listlst)
- {
- vectorout;
- for_each(lst.begin(),lst.end(),[&](const double&d){out.push_back(d);});
- c_val=out;
- dim=out.size();
- }
- c operator+(const c&a,const c&b)
- {
- size_t MAX=b.re_dim();
- if(a.re_dim()>b.re_dim())
- MAX=a.re_dim();
- vectortemp0(MAX,0);
- vectortemp1(MAX,0);
- vectortemp2(MAX,0);
- copy(a.c_val.begin(),a.c_val.end(),temp0.begin());
- copy(b.c_val.begin(),b.c_val.end(),temp1.begin());
- for(size_t i=0;i
- temp2[i]=temp0[i]+temp1[i];
- return c(temp2);
- }
- c operator-(const c&a)
- {
- c out(a);
- for(size_t i=0;i
- out[i]=-out[i];
- return out;
- }
- c operator-(const c&a,const c&b)
- {
- return (a+(-b));
- }
- c rep(const double&d,size_t n)
- {
- return c(vector(n,d));
- }
- c operator+(const c&a,const double&d)
- {
- return a+rep(d,a.re_dim());
- }
- c operator-(const c&a,const double&d)
- {
- return (a+(-d));
- }
- c operator+(const double&d,const c&a)
- {
- return a+d;
- }
- c operator-(const double&d,const c&a)
- {
- return (-a)+d;
- }
- c operator*(const double&d,const c&a)
- {
- c out(a);
- for(size_t i=0;i
- out[i]*=d;
- return out;
- }
- c operator*(const c&a,const double&d)
- {
- return d*a;
- }
- c operator/(const double&d,const c&a)
- {
- c out(a);
- for(size_t i=0;i
- out[i]=d/a[i];
- return out;
- }
- c operator/(const c&a,const double&d)
- {
- c out(a);
- for(size_t i=0;i
- out[i]=a[i]/d;
- return out;
- }
- c::c(const matrix&m)
- {
- vectortemp;
- for(size_t j=0;j
- for(size_t i=0;i
- temp.push_back(m[i][j]);
- c_val=temp;
- dim=temp.size();
- }
- c operator*(const c&a,const c&b)
- {
- if(a.re_dim()!=b.re_dim())
- throw runtime_error(“dim error!\n”);
- c out(a);
- for(size_t i=0;i
- out[i]*=b[i];
- return out;
- }
- //类matrix的有关定义
- void matrix::out(size_t n)const
- {
- cout<<”The matrix is:\n”;
- for(size_t i=0;i
- {
- for(size_t j=0;j
- cout<<setw(n)<<(*this)[i][j]<<“ ”;
- cout<<endl;
- }
- cout<<endl;
- }
- c matrix::col(size_t i)const
- {
- c out(rep(0,rdim));
- for(size_t j=0;j
- out[j]=(*this)[j][i];
- return out;
- }
- void matrix::col_change(size_t i,const c&a)
- {
- for(size_t j=0;j
- (*this)[j][i]=a[j];
- }
- matrix::matrix(const c&v,size_t r,size_t c):rdim(r),cdim(c)
- {
- matrix out(r,c,0);
- for(size_t i=0;i
- out[i%r][i/r]=v[i];
- (this->m_val)=out.m_val;
- }
- matrix::matrix(const c&v):rdim(v.re_dim()),cdim(1)
- {
- matrix out(v.re_dim(),1,0);
- for(size_t i=0;i
- out[i][0]=v[i];
- this->m_val=out.m_val;
- }
- matrix operator+(const matrix&a,const matrix&b)
- {
- size_t r_MAX=a.rdim,c_MAX=a.cdim;
- if(a.rdim
- r_MAX=b.rdim;
- if(a.cdim
- c_MAX=b.cdim;
- matrix tempa(r_MAX,c_MAX,0);
- for(size_t i=0;i
- for(size_t j=0;j
- tempa[i][j]=a[i][j];
- matrix tempb(r_MAX,c_MAX,0);
- for(size_t i=0;i
- for(size_t j=0;j
- tempb[i][j]=b[i][j];
- matrix tempout(r_MAX,c_MAX,0);
- for(size_t i=0;i
- for(size_t j=0;j
- tempout[i][j]=tempa[i][j]+tempb[i][j];
- return tempout;
- }
- matrix operator-(const matrix&a)
- {
- matrix out(a);
- for(size_t i=0;i
- for(size_t j=0;j
- out[i][j]=-out[i][j];
- return out;
- }
- matrix operator-(const matrix&a,const matrix&b)
- {
- return ((-b)+a);
- }
- matrix operator+(const matrix&a,const double&d)
- {
- return a+matrix(a.rdim,a.cdim,d);
- }
- matrix operator+(const double&d,const matrix&a)
- {
- return a+d;
- }
- matrix operator-(const matrix&a,const double&d)
- {
- return a+(-d);
- }
- matrix operator-(const double&b,const matrix&a)
- {
- return (-a)+b;
- }
- matrix operator*(const matrix&a,const double&d)
- {
- matrix out(a);
- for(size_t i=0;i
- for(size_t j=0;j
- out[i][j]*=d;
- return out;
- }
- matrix operator*(const double&d,const matrix&a)
- {
- return a*d;
- }
- matrix operator/(const matrix&a,const double&d)
- {
- return a*(1/d);
- }
- matrix operator/(const double&d,const matrix&a)
- {
- matrix out(a.rdim,a.cdim,0);
- for(size_t i=0;i
- for(size_t j=0;j
- out[i][j]=d/a[i][j];
- return out;
- }
- //基本运算函数
- matrix diag(const c&v)
- {
- matrix out(v.re_dim(),v.re_dim(),0);
- for(size_t i=0;i
- out[i][i]=v[i];
- return out;
- }
- matrix diag(const matrix&m)
- {
- if(m.re_dim().first!=m.re_dim().second)
- throw runtime_error(“dim error!\n”);
- matrix out(m.re_dim().first,m.re_dim().second,0);
- for(size_t i=0;i
- out[i][i]=m[i][i];
- return out;
- }
- double inter_product(const c&a,const c&b)
- {
- if(a.re_dim()!=b.re_dim())
- throw runtime_error(“dim error!\n”);
- double out=0;
- for(size_t i=0;i
- out+=(a[i]*b[i]);
- return out;
- }
- c operator%(const matrix&m,const c&v)
- {
- if(m.re_dim().second!=v.re_dim())
- throw runtime_error(“dim error!\n”);
- c out(rep(0,m.re_dim().first));
- for(size_t i=0;i
- out[i]=inter_product(m[i],v);
- return out;
- }
- //同下
- double prod(const c&v)
- {
- double out=1;
- for(size_t i=0;i
- out*=v[i];
- return out;
- }
- //对于matrix的求和由c复制构造函数的重载函数定义：c(const matrix&m)
- double sum(const c&v)
- {
- double out=v[0];
- for(size_t i=1;i
- out+=v[i];
- return out;
- }
- matrix operator%(const c&v,const matrix&m)
- {
- if(v.re_dim()!=m.re_dim().first)
- throw runtime_error(“dim error!\n”);
- matrix out(1,m.re_dim().second,0);
- for(size_t i=0;i
- out[0][i]=inter_product(v,m.col(i));
- return out;
- }
- matrix outer_product(const c&a,const c&b)
- {
- matrix out(a.re_dim(),b.re_dim(),0);
- for(size_t i=0;i
- for(size_t j=0;j
- out[i][j]=a[i]*b[j];
- return out;
- }
- size_t length(const c&v)
- {
- return v.re_dim();
- }
- c sort(const c&v)
- {
- vectorout;
- for(size_t i=0;i
- out.push_back(v[i]);
- sort(out.begin(),out.end());
- return c(out);
- }
- double mean(const c&v)
- {
- return sum(v)/length(v);
- }
- //其转换版本返回矩阵转为向量的方差
- double var(const c&v)
- {
- return mean((v-mean(v))*(v-mean(v)));
- }
- c connect(initializer_list lst)
- {
- vectortemp;
- for_each(lst.begin(),lst.end(),[&](const c&v){for(auto a:v.const_re_c_val())temp.push_back(a);});
- return c(temp);
- }
- //标准差
- template
- double STD(const any&a)
- {
- return sqrt(var(a)*(length(a))/(length(a)-1));
- }
- matrix rbind(initializer_listlst)
- {
- size_t r=0;
- auto a=lst.begin();
- while(a!=lst.end())
- {
- a++;
- r++;
- }
- size_t co=0;
- for_each(lst.begin(),lst.end(),[&](const c&v){if(v.re_dim()>co)co=v.re_dim();});
- matrix out(r,co,0);
- size_t i=0;
- a=lst.begin();
- while(a!=lst.end())
- {
- vectortemp(co,0);
- for(size_t i=0;iconst_re_c_val().size();i++)
- temp[i]=a->operator[](i);
- out[i]=c(temp);
- i++;
- a++;
- }
- return out;
- }
- size_t dim(const c&v)
- {
- return v.re_dim();
- }
- pair dim(const matrix&m)
- {
- return m.re_dim();
- }
- double min(const c&v)
- {
- double temp=v[0];
- for(size_t i=1;i
- if(v[i]
- temp=v[i];
- return temp;
- }
- double max(const c&v)
- {
- double temp=v[0];
- for(size_t i=1;i
- if(v[i]>temp)
- temp=v[i];
- return temp;
- }
- c pmin(initializer_listlst)
- {
- c temp=rep(0,lst.size());
- auto a=lst.begin();
- for(size_t i=0;i
- {
- temp[i]=min(*a);
- a++;
- }
- return temp;
- }
- c pmax(initializer_listlst)
- {
- c temp=rep(0,lst.size());
- auto a=lst.begin();
- for(size_t i=0;i
- {
- temp[i]=max(*a);
- a++;
- }
- return temp;
- }
- template
- pair range(const any&v)
- {
- cout<<”MIN: ”<<min(v)<<“ MAX: ”<<max(v)<<endl;
- return make_pair(min(v),max(v));
- }
- double median(const c&v)
- {
- return sort(v)[length(v)/2];
- }
- double var(const c&a,const c&b)
- {
- if(length(a)!=length(b))
- throw runtime_error(“dim error!\n”);
- c t1(a-mean(a)),t2(b-mean(b));
- return inter_product(t1,t2)/(length(a)-1);
- }
- double cov(const c&a,const c&b)
- {
- return var(a,b);
- }
- double cor(const c&a,const c&b)
- {
- return var(a,b)/STD(a)/STD(b);
- }
- matrix var(const matrix&a,const matrix&b)
- {
- if(a.re_dim().first!=b.re_dim().first)
- throw runtime_error(“dim error!\n”);
- matrix temp(a.re_dim().second,b.re_dim().second,0);
- for(size_t i=0;i
- for(size_t j=0;j
- temp[i][j]=var(a.col(i),b.col(j));
- return temp;
- }
- matrix cov(const matrix&a,const matrix&b)
- {
- return var(a,b);
- }
- matrix cor(const matrix&a,const matrix&b)
- {
- matrix temp=var(a,b);
- for(size_t i=0;i
- for(size_t j=0;j
- temp[i][j]/=((STD(a.col(i))*STD(b.col(j))));
- return temp;
- }
- matrix cov(const matrix&a)
- {
- return var(a,a);
- }
- matrix cor(const matrix&a)
- {
- return cor(a,a);
- }
- //由于关联容器的删除方法利用误差排序的方法
- //利用顺序容器迭代器的删除方法有困难
- c rank(const c&v)
- {
- vectortemp00(v.const_re_c_val());
- for(size_t i=0;i
- temp00[i]+=(0.00000001*i);
- vectortemp0(temp00);
- multisettemp2(temp0.begin(),temp0.end());
- vectortemp1(v.re_dim());
- size_t i=0,j=0;
- double pre_val=min(c(vector(temp2.begin(),temp2.end())));
- vector::iterator s0;
- while(i
- {
- double val=min(c(vector(temp2.begin(),temp2.end())));
- s0=find(temp0.begin(),temp0.end(),val);
- if(sqrt((pre_val-val)*(pre_val-val))>0.000001)
- j++;
- temp1[s0-temp0.begin()]=j;
- temp2.erase(val);
- i++;
- pre_val=val;
- }
- return c(temp1);
- }
- c rev(const c&v)
- {
- vector temp;
- auto a=v.const_re_c_val().rbegin();
- while(a!=v.const_re_c_val().rend())
- {
- temp.push_back(*a);
- a++;
- }
- return c(temp);
- }
- //向量先排序再输出排序前的下标值
- c order(const c&v)
- {
- unordered_multimapm0;
- for(size_t i=0;i
- m0.insert(make_pair(v[i],i));
- multimapm1(m0.begin(),m0.end());
- c temp(rep(0,length(v)));
- auto a=m1.begin();
- size_t i=0;
- while(a!=m1.end())
- {
- temp[i]=a->second;
- i++;
- a++;
- }
- return temp;
- }
- c cumsum(const c&v)
- {
- c temp(v);
- for(size_t i=1;i
- temp[i]+=temp[i-1];
- return temp;
- }
- c cumprod(const c&v)
- {
- c temp(v);
- for(size_t i=1;i
- temp[i]*=temp[i-1];
- return temp;
- }
- matrix cumsum(const matrix&m)
- {
- c temp(m);
- for(size_t i=1;i
- temp[i]+=temp[i-1];
- return matrix(temp,m.re_dim().first,m.re_dim().second);
- }
- matrix cumprod(const matrix&m)
- {
- c temp(m);
- for(size_t i=1;i
- temp[i]*=temp[i-1];
- return matrix(temp,m.re_dim().first,m.re_dim().second);
- }
- //矩阵运算函数
- //初等行变换化上三角求解行列式
- double det(const matrix&m)
- {
- auto f=[](const matrix&mm)->pair
- {
- if(mm.re_dim().first!=mm.re_dim().second)
- throw runtime_error(“dim error!\n”);
- size_t MIN=mm.re_dim().first;
- double mult=1;
- size_t col=0;
- size_t bar=0;
- size_t b_c=0;
- matrix t(mm);
- while(b_c
- {
- for(size_t i=bar+1;i
- {
- if(t[i][col]==0)
- i++;
- else
- {
- t.Swap(i,bar);
- mult*=(-1);
- break;
- }
- }
- if(bar!=MIN+1)
- {
- if(t[bar][col]!=0)
- {
- for(size_t i=bar+1;i
- {
- t[bar][i]=t[bar][i]/t[bar][col];
- if(i==bar+1)
- mult*=t[bar][col];
- }
- if(col!=MIN-1)
- t[bar][col]=1;
- }
- for(size_t i=bar+1;i
- {
- t[i]=t[i]-t[i][col]*t[bar];
- }
- }
- col++;
- bar++;
- b_c=bar;
- if(col>bar);
- b_c=col;
- }
- return make_pair(t,mult);
- };
- pair tt=f(m);
- return tt.second*prod(diag(tt.first)%rep(1,m.re_dim().first));
- }
- //Cramer法则解线性方程组：要求自变量矩阵为方阵且相应行列式不为0
- c solve(const matrix&m,const c&v)
- {
- c temp(rep(0,v.re_dim()));
- double low=det(m);
- if(m.re_dim().first!=m.re_dim().second)
- throw runtime_error(“dim error!\n”);
- if(low==0)
- throw runtime_error(“singular!\n”);
- for(size_t i=0;i
- {
- matrix temp0(m);
- temp0.col_change(i,v);
- temp[i]=det(temp0)/low;
- }
- return temp;
- }
- double tr(const matrix&m)
- {
- if(m.re_dim().first!=m.re_dim().second)
- throw runtime_error(“dim error!\n”);
- return inter_product(diag(m)%rep(1,m.re_dim().first),rep(1,m.re_dim().first));
- }
- matrix T(const matrix&m)
- {
- matrix out(m.re_dim().second,m.re_dim().first,0);
- for(size_t i=0;i
- for(size_t j=0;j
- out[i][j]=m[j][i];
- return out;
- }
- matrix cbind(initializer_listlst)
- {
- return T(rbind(lst));
- }
- matrix operator%(const matrix&a,const matrix&b)
- {
- matrix out(a.re_dim().first,a.re_dim().second,0);
- for(size_t i=0;i
- for(size_t j=0;j
- out[i][j]=inter_product(a[i],b.col(j));
- return out;
- }
- double F_norm(const matrix&m)
- {
- return sqrt(tr(T(m)%m));
- }
- //a,b为区间 d为步长 e为精度 默认为求整数精度：以1为精度特征值 如所求特征值太少可通过减少d改善
- //只能求实值
- //可以用F_norm作为a、b的界（-F_norm(m),F_norm(m)）可确保值在范围中
- //可用于求解但效率低
- c eigen(const matrix&m,const double&a,const double& b,const double &d=0.0001,const double &e=1)
- {
- if(m.re_dim().first!=m.re_dim().second)
- throw runtime_error(“dim error!\n”);
- vectortemp;
- double pre_beg=100000000;
- for(double beg=a;beg
- {
- matrix mm0(diag(rep(beg,m.re_dim().first))-m);
- double s0=det(mm0);
- if(sqrt(s0*s0)
- {
- if(sqrt((pre_beg-beg)*(pre_beg-beg))>1)
- {
- temp.push_back(beg);
- pre_beg=beg;
- cout<<”Done!\n”;
- cout<<beg<<endl;//eigenvalue
- }
- }
- }
- return c(temp);
- }
- //重载求eign的函数 d:步长 可保证绝对求出所有特征值（利用循环增大精度）
- c eigen(const matrix&m,const double&d=0.1)
- {
- double dd=d;
- double ra=F_norm(m);
- double trr=tr(m);
- c temp;
- double r=0;
- do
- {
- dd*=0.1;
- temp=eigen(m,-ra,ra,dd);
- if(temp.re_dim()==m.re_dim().first)
- break;
- r=sum(temp)-trr;
- }
- while(sqrt((r*r)>1));
- //与迹的差距（精度）设定为1 绝对值小于此值的特征值被忽略
- //此种方法的一个缺陷为异号特征值的抵消 对于同号特征值有把握
- //只适用于所有特征值为实值的情况
- //如有复特征值，只输出实数的并循环不能结束
- return temp;
- }
- matrix M(const matrix&m,size_t k,size_t l)
- {
- matrix temp(m);
- set s1;
- for(size_t i=0;i
- s1.insert(i);
- set s2;
- for(size_t i=0;i
- s2.insert(i);
- s1.erase(k);
- s2.erase(l);
- vectortemp00;
- for(auto j:s2)
- for(auto i:s1)
- temp00.push_back(temp[i][j]);
- return matrix (c(temp00),m.re_dim().first-1,m.re_dim().second-1);
- }
- matrix A_accompany(const matrix&m)
- {
- matrix out(m.re_dim().first,m.re_dim().second,0);
- for(size_t i=0;i
- for(size_t j=0;j
- out[i][j]=det(M(m,i,j))*(((i+j)%2)?-1:1);
- //代数余子式
- return T(out);
- }
- //求方阵的逆矩阵（利用伴随矩阵方法）
- matrix solve(const matrix&m)
- {
- double de=det(m);
- if(sqrt(de*de)<0.000001)
- throw runtime_error(“singular!\n”);
- return A_accompany(m)/de;
- }
- //利用逆矩阵法求解方程组 要求自变量阵为方阵 且可逆
- c solve_eq(const matrix&m,const c&v)
- {
- c out;
- double de=det(m);
- if(sqrt(de*de)<0.000001)
- throw runtime_error(“singular!\n”);
- return solve(m)%v;
- }
- 测试程序：
- int main()
- {
- //测试程序：
- c c0({35.1,12});
- vectorv0;
- for(size_t i=0;i<10;i++)
- v0.push_back(i);
- c c1(v0);
- c0.out();
- c1.out();
- cout<<c0[1]<<endl;
- c0[1]=10;
- cout<<c0[1]<<endl;
- (c0+c1).out();
- (-c0).out();
- (c0-c1).out();
- rep(1,10).out();
- (c0+rep(1,10)).out();
- (c0-rep(1,10)).out();
- (rep(1,10)+1).out();
- (rep(1,10)-1).out();
- (10/rep(1,10)).out();
- (rep(1,10)/10).out();
- cout<<((10/rep(1,10))==(rep(1,10)/10))<<endl;
- matrix m0=matrix(3,4,10);
- m0[1]=rep(4,4);
- m0.out();
- m0.col(2).out();
- m0.col_change(0,c({1,2,3}));
- m0.out();
- matrix m1=(matrix(c({1,5,7,8,9,0,3,4,5}),3,3)+matrix(c({3,5,7,9}),2,2));
- m1.out();
- (-m1).out();
- (m1-matrix(rep(1,10),5,2)).out();
- (m1+1).out();
- (m1*0.6).out();
- (m1-1).out();
- (1-m1).out();
- (0.6*m1).out();
- (1/m1).out();
- (m1/10).out();
- m1.out();
- m1.Swap(1,2);
- m1.out();
- m1.col_Swap(1,2);
- m1.out();
- matrix m2=m1;
- m1.Swap(0,1);
- cout<<(m1==m2)<<endl;
- cout<<m1.re_dim().first<<” ”<<m1.re_dim().second<<endl;
- matrix A(c({1,2,1,4,7,1,5,2,1}),3,3);
- cout<<det((A+diag(rep(10,A.re_dim().first))))<<endl;
- solve(matrix(c({30,7.3,4.2,0,0,6,8,7,0}),3,3),c({11,12,13})).out();
- m1.out();
- cout<<F_norm(m1)<<endl;
- eigen(matrix(c({50,1,1,9,7,1,4,1,13}),3,3)).out();
- solve(matrix(c({50,1,1,9,7,1,4,1,13}),3,3),c({1,1,1})).out();
- solve(matrix(c({50,1,1,9,7,1,4,1,13}),3,3)).out();
- solve_eq(matrix(c({50,1,1,9,7,1,4,1,13}),3,3),c({1,1,1})).out();
- m2.out();
- M(m2,0,0).out();
- cout<<sum(m2)<<endl;
- cout<<prod(m2)<<endl;
- (c({1,1})%matrix(c({5,6,7,8,9,10}),2,3)).out();
- outer_product(c({1,1}),c({5,6,7})).out();
- diag(m2).out();
- diag(c(diag(m2))).out();
- cout<<length(m2)<<endl;
- cout<<length(m2[0])<<endl;
- sort(c({3,2,1})).out();
- cout<<mean(m2)<<endl;
- cout<<mean(m2.col(0))<<endl;
- cout<<var(matrix(c({1,2,3,4,5,6,7,8,9}),3,3))<<endl;
- connect({c({1,1,1}),c({-1,1,-1})}).out();
- cout<<STD(matrix(c({1,2,3,4,5,6,7,8,9}),3,3))<<endl;
- matrix m3=rbind({c({1,2}),c({3,4,5})});
- cbind({c({1,2}),c({3,4,5})}).out();
- cout<<dim(m3).first<<” ”<<dim(m3).second<<endl;
- m3.out();
- cout<<dim(m3[0])<<endl;
- cout<<min(m3)<<endl;
- cout<<min(m3[0])<<endl;
- cout<<max(m3)<<endl;
- cout<<max(m3[0])<<endl;
- c(m3).out();
- pmin({m3[0],m3[1]}).out();
- pmax({m3[0],m3[1]}).out();
- range(m3);
- cout<<median(m3)<<endl;
- var(m3,m3).out();
- cov(m3).out();
- cor(m3).out();
- rank(c({0,3,4,4,5,6,7,6,6,3})).out();
- rev(c({1,5,7,6,9})).out();
- order(c({0,3,4,4,5,6,7,6,3})).out();
- m3.out();
- cumsum(m3[0]).out();
- cumsum(m3).out();
- cumprod(m3[0]).out();
- cumprod(m3).out();
- cout<<det(matrix(c({50,7,8,9,10,4,3,2,9,4,8,7,1,1,1,10}),4,4))<<endl;
- return 0;
- }
#includeusing std::cout;using std::endl;using std::cin;using std::istream;using std::ios_base;
运行结果：
The vector is:
35.1 12
The vector is:
0 1 2 3 4 5 6 7 8 9
12
10
The vector is:
35.1 11 2 3 4 5 6 7 8 9
The vector is:
-35.1 -10
The vector is:
35.1 9 -2 -3 -4 -5 -6 -7 -8 -9
The vector is:
1 1 1 1 1 1 1 1 1 1
The vector is:
36.1 11 1 1 1 1 1 1 1 1
The vector is:
34.1 9 -1 -1 -1 -1 -1 -1 -1 -1
The vector is:
2 2 2 2 2 2 2 2 2 2
The vector is:
0 0 0 0 0 0 0 0 0 0
The vector is:
10 10 10 10 10 10 10 10 10 10
The vector is:
0.1 0.1 0.1 0.1 0.1 0.1 0.1 0.1 0.1 0.1
0
The matrix is:
10 10 10 10
4 4 4 4
10 10 10 10
The vector is:
10 4 10
The matrix is:
1 10 10 10
2 4 4 4
3 10 10 10
The matrix is:
4 15 3
10 18 4
7 0 5
The matrix is:
-4 -15 -3
-10 -18 -4
-7 -0 -5
The matrix is:
3 14 3
9 17 4
6 -1 5
-1 -1 0
-1 -1 0
The matrix is:
5 16 4
11 19 5
8 1 6
The matrix is:
2.4 9 1.8
6 10.8 2.4
4.2 0 3
The matrix is:
3 14 2
9 17 3
6 -1 4
The matrix is:
-3 -14 -2
-9 -17 -3
-6 1 -4
The matrix is:
2.4 9 1.8
6 10.8 2.4
4.2 0 3
The matrix is:
0.25 0.0666667 0.333333
0.1 0.0555556 0.25
0.142857 inf 0.2
The matrix is:
0.4 1.5 0.3
1 1.8 0.4
0.7 0 0.5
The matrix is:
4 15 3
10 18 4
7 0 5
The matrix is:
4 15 3
7 0 5
10 18 4
The matrix is:
4 3 15
7 5 0
10 4 18
0
3 3
1880
The vector is:
-0.12533 2.2544 1.84499
The matrix is:
7 5 0
4 3 15
10 4 18
27.6405
Done!
6.67574
Done!
6.67374
Done!
12.9967
Done!
50.3227
The vector is:
6.67374 12.9967 50.3227
The vector is:
-0.00961538 0.134615 0.0673077
The matrix is:
0.0206044 -0.02587 -0.00434982
-0.00274725 0.147894 -0.0105311
-0.00137363 -0.00938645 0.0780678
The vector is:
-0.00961538 0.134615 0.0673077
The matrix is:
4 3 15
7 5 0
10 4 18
The matrix is:
5 0
4 18
66
0
The matrix is:
11 15 19
The matrix is:
5 6 7
5 6 7
The matrix is:
4 0 0
0 5 0
0 0 18
The matrix is:
4 0 0 0 0 0 0 0 0
0 0 0 0 0 0 0 0 0
0 0 0 0 0 0 0 0 0
0 0 0 0 0 0 0 0 0
0 0 0 0 5 0 0 0 0
0 0 0 0 0 0 0 0 0
0 0 0 0 0 0 0 0 0
0 0 0 0 0 0 0 0 0
0 0 0 0 0 0 0 0 18
9
3
The vector is:
1 2 3
7.33333
7
6.66667
The vector is:
1 1 1 -1 1 -1
2.73861
The matrix is:
1 3
2 4
0 5
2 3
The matrix is:
1 2 0
3 4 5
3
0
0
5
2
The vector is:
1 3 2 4 0 5
The vector is:
0 3
The vector is:
2 5
MIN: 0 MAX: 5
3
The matrix is:
2 2 5
2 2 5
5 5 12.5
The matrix is:
2 2 5
2 2 5
5 5 12.5
The matrix is:
1 1 1
1 1 1
1 1 1
The vector is:
0 1 2 2 3 4 5 4 4 1
The vector is:
9 6 7 5 1
The vector is:
0 8 1 3 2 4 7 5 6
The matrix is:
1 2 0
3 4 5
The vector is:
1 3 3
The matrix is:
1 6 10
4 10 15
The vector is:
1 2 0
The matrix is:
1 6 0
3 24 0
6194
Process returned 0 (0x0) execution time : 4.891 s
Press any key to continue.
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