updates
madrocketsci
4 weeks ago
parent
0866d42781
commit
b722664be4
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@ -0,0 +1,28 @@
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#ifndef __AMSCPPNARRAY_MATH_HPP__
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#define __AMSCPPNARRAY_MATH_HPP__
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namespace ams
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{
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namespace narray
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{
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template<typename T> T narray_max(const narray<T> &q);
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template<typename T> T narray_min(const narray<T> &q);
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template<typename T> double narray_mean(const narray<T> &q);
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template<typename T> double narray_var(const narray<T> &q);
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template<typename T> double narray_stdev(const narray<T> &q);
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template<typename T> double narray_L2norm(const narray<T> &q);
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template<typename T> T narray_sum(const narray<T> &q);
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template<typename T> narray<T> narray_abs(narray<T> &q);
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void narray_testmath1();
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void narray_testmath2();
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}; //end namespaces
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};
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#include <amscppnarray/amscppnarray_mathimpl.hpp>
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#endif
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@ -0,0 +1,381 @@
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#ifndef __AMSCPPNARRAY_MATHIMPL_HPP__
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#define __AMSCPPNARRAY_MATHIMPL_HPP__
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namespace ams
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{
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namespace narray
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{
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template<typename T> T narray_max(const narray<T> &q)
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{
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return q.max();
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}
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template<typename T> T narray_min(const narray<T> &q)
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{
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return q.min();
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}
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template<typename T> void narray_sum_tf(
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const narray<T> *in,
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narray<T> *sums,
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int threadnum,
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int nthreads
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)
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{
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int I0,I1,Is,I;
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Is = in->length/nthreads;
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I0 = Is*threadnum;
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I1 = (threadnum>=(nthreads-1))? in->length: Is*(threadnum+1);
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for(I=I0;I<I1;I++)
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{
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sums->data[threadnum] = sums->data[threadnum] + in->data[I];
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}
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}
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template<typename T> T narray_sum(const narray<T> &q)
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{
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T ret = T();
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narray<T> sums;
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narray_size_t I;
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int J;
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int nthreads;
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std::vector<std::thread*> threads;
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if(q.length<=0)
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{
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return ret;
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}
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if(q.length<narray_thread_sz)
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{
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ret = T();
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for(I=0;I<q.length;I++)
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{
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ret = ret + q.data[I];
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}
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}
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else
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{
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//threaded operation
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nthreads = std::thread::hardware_concurrency();
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nthreads = (nthreads<1) ? 1 : nthreads;
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nthreads = (nthreads>narray_max_threads) ? narray_max_threads : nthreads;
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threads.resize(nthreads);
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sums.resize(nthreads);
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sums.setall(T());
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for(J=0;J<nthreads;J++)
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{
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threads[J] = new(std::nothrow) std::thread(
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&narray_sum_tf<T>,
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&q,
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&sums,
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J,nthreads
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);
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if(threads[J]==NULL)
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{
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printf("narray_sum: warning: thread %d failed to initialize.\n",J);
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//handle errors
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}
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}
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for(J=0;J<nthreads;J++)
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{
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if(threads[J]!=NULL)
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{
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threads[J]->join();
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delete threads[J];
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threads[J]= NULL;
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}
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}
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ret = T();
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for(J=0;J<nthreads;J++)
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{
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ret = ret + sums.data[J];
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}
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}
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return ret;
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}
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template<typename T> double narray_mean(const narray<T> &q)
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{
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double ret = 0.0;
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T sum = narray_sum(q);
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ret = (double)sum/((double)q.length);
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return ret;
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}
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template<typename T> void narray_variance_tf(
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const narray<T> *in,
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narray<double> *sums,
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double mean,
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int threadnum,
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int nthreads
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)
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{
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int I0,I1,Is,I;
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double q2;
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Is = in->length/nthreads;
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I0 = Is*threadnum;
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I1 = (threadnum>=(nthreads-1))? in->length: Is*(threadnum+1);
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for(I=I0;I<I1;I++)
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{
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q2 = in->data[I]-mean;
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sums->data[threadnum] = sums->data[threadnum] + q2*q2/((double)in->length);
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}
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}
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template<typename T> double narray_var(const narray<T> &q)
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{
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double ret = 0.0;
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narray<double> sums;
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narray_size_t I;
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int J;
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int nthreads;
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std::vector<std::thread*> threads;
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double mn = ams::narray::narray_mean(q);
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double q2;
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if(q.length<=0)
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{
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return ret;
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}
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if(q.length<narray_thread_sz)
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{
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ret = 0.0;
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for(I=0;I<q.length;I++)
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{
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q2 = (double)q.data[I]-mn;
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ret = ret + q2*q2/((double)q.length);
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}
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}
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else
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{
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//threaded operation
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nthreads = std::thread::hardware_concurrency();
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nthreads = (nthreads<1) ? 1 : nthreads;
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nthreads = (nthreads>narray_max_threads) ? narray_max_threads : nthreads;
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threads.resize(nthreads);
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sums.resize(nthreads);
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sums.setall(T());
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for(J=0;J<nthreads;J++)
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{
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threads[J] = new(std::nothrow) std::thread(
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&narray_variance_tf<T>,
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&q,
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&sums,
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mn,
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J,nthreads
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);
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if(threads[J]==NULL)
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{
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printf("narray_var: warning: thread %d failed to initialize.\n",J);
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//handle errors
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}
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}
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for(J=0;J<nthreads;J++)
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{
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if(threads[J]!=NULL)
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{
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threads[J]->join();
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delete threads[J];
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threads[J]= NULL;
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}
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}
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ret = T();
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for(J=0;J<nthreads;J++)
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{
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ret = ret + sums.data[J];
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}
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}
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return ret;
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}
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template<typename T> double narray_stdev(const narray<T> &q)
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{
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double ret = narray_var(q);
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ret = ::sqrt(ret);
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return ret;
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}
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template<typename T> void narray_L2norm_tf(
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const narray<T> *in,
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narray<double> *sums,
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int threadnum,
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int nthreads
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)
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{
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int I0,I1,Is,I;
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double q2;
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Is = in->length/nthreads;
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I0 = Is*threadnum;
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I1 = (threadnum>=(nthreads-1))? in->length: Is*(threadnum+1);
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for(I=I0;I<I1;I++)
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{
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q2 = in->data[I];
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sums->data[threadnum] = sums->data[threadnum] + q2*q2;
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}
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}
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template<typename T> double narray_L2norm(const narray<T> &q)
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{
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double ret = 0.0;
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narray<double> sums;
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narray_size_t I;
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int J;
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int nthreads;
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std::vector<std::thread*> threads;
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double q2;
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if(q.length<=0)
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{
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return ret;
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}
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if(q.length<narray_thread_sz)
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{
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ret = 0.0;
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for(I=0;I<q.length;I++)
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{
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q2 = (double)q.data[I];
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ret = ret + q2*q2;
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}
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}
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else
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{
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//threaded operation
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nthreads = std::thread::hardware_concurrency();
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nthreads = (nthreads<1) ? 1 : nthreads;
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nthreads = (nthreads>narray_max_threads) ? narray_max_threads : nthreads;
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threads.resize(nthreads);
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sums.resize(nthreads);
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sums.setall(T());
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for(J=0;J<nthreads;J++)
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{
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threads[J] = new(std::nothrow) std::thread(
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&narray_L2norm_tf<T>,
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&q,
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&sums,
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J,nthreads
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);
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if(threads[J]==NULL)
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{
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printf("narray_L2norm: warning: thread %d failed to initialize.\n",J);
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//handle errors
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}
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}
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for(J=0;J<nthreads;J++)
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{
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if(threads[J]!=NULL)
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{
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threads[J]->join();
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delete threads[J];
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threads[J]= NULL;
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}
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}
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ret = T();
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for(J=0;J<nthreads;J++)
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{
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ret = ret + sums.data[J];
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}
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}
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ret = ::sqrt(ret);
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return ret;
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}
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template<typename T> void narray_abs_tf(
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const narray<T> *in,
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narray<T> *out,
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int threadnum,
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int nthreads
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)
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{
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int I0,I1,Is,I;
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double q2;
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Is = in->length/nthreads;
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I0 = Is*threadnum;
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I1 = (threadnum>=(nthreads-1))? in->length: Is*(threadnum+1);
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for(I=I0;I<I1;I++)
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{
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out->data[I] = (in->data[I]<T(0)) ? -in->data[I] : in->data[I];
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}
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}
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template<typename T> narray<T> narray_abs(narray<T> &q)
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{
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narray<T> ret;
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narray_size_t I;
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int J;
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int nthreads;
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std::vector<std::thread*> threads;
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if(q.length<=0)
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{
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ret.resize(0);
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return ret;
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}
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ret.resize(q.length);
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if(ret.length!=q.length)
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{
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printf("narray_abs: error - could not allocate return array.\n");
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ret.resize(0);
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return ret;
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}
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if(q.length<narray_thread_sz)
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{
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for(I=0;I<q.length;I++)
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{
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ret.data[I] = (q.data[I]<T(0)) ? -q.data[I] : q.data[I];
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}
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}
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else
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{
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//threaded operation
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nthreads = std::thread::hardware_concurrency();
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nthreads = (nthreads<1) ? 1 : nthreads;
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nthreads = (nthreads>narray_max_threads) ? narray_max_threads : nthreads;
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threads.resize(nthreads);
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for(J=0;J<nthreads;J++)
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{
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threads[J] = new(std::nothrow) std::thread(
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&narray_abs_tf<T>,
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&q,
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&ret,
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J,nthreads
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);
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if(threads[J]==NULL)
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{
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printf("narray_abs: warning: thread %d failed to initialize.\n",J);
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//handle errors
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}
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}
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for(J=0;J<nthreads;J++)
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{
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if(threads[J]!=NULL)
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{
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threads[J]->join();
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delete threads[J];
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threads[J]= NULL;
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}
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}
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}
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return ret;
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}
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}; //end namespaces
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};
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#endif
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@ -0,0 +1,85 @@
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#include <amscppnarray/amscppnarray.hpp>
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namespace ams
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{
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namespace narray
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{
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static void _intl_printarr(narray<int> &q)
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{
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int I;
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if(q.length>0)
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{
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printf("{");
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for(I=0;I<q.length-1;I++) printf("%d,",q[I]);
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printf("%d}",q[q.length-1]);
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}
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else
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{
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printf("{}");
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}
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}
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static void _intl_printarr(narray<double> &q)
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{
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int I;
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if(q.length>0)
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{
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printf("{");
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for(I=0;I<q.length-1;I++) printf("%1.3f,",q[I]);
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printf("%1.3f}",q[q.length-1]);
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}
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else
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{
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printf("{}");
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}
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}
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void narray_testmath1()
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{
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narray<int> a = {-4,-3,-2,-1,0,1,2,3,4,5};
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narray<int> b;
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int asum = narray_sum(a);
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double amean = narray_mean(a);
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printf("sum(a)=%d\n",asum);
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printf("mean(a)=%1.3f\n",amean);
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printf("stdev(a)=%1.3f\n",narray_stdev(a));
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printf("L2norm(a)=%1.3f\n",narray_L2norm(a));
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printf("min(a)=%d\n",narray_min(a));
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printf("max(a)=%d\n",narray_max(a));
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b = narray_abs(a);
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_intl_printarr(b); printf("\n");
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return;
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}
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void narray_testmath2()
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{
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rand::set_rseed_withtimer();
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narray<double> unif = ams::narray::rand::narray_rand(10000);
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double mn1 = narray_mean(unif);
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double std1 = narray_stdev(unif);
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double mn2,std2;
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//_intl_printarr(unif); printf("\n");
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unif = unif*2.0-1.0;
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//_intl_printarr(unif); printf("\n");
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mn2 = narray_mean(unif);
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std2 = narray_stdev(unif);
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printf("mn1=%1.3f std1=%1.3f\n",mn1,std1);
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printf("mn2=%1.3f std2=%1.3f\n",mn2,std2);
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return;
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}
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};
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};
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