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Fixed warnings in MLPPStat.

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Relintai 2023-02-12 15:54:30 +01:00
parent 235ba86eae
commit 10b4b383fb
1 changed files with 14 additions and 14 deletions
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28
mlpp/stat/stat.cpp
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@ -31,7 +31,7 @@ real_t MLPPStat::b1_estimation(const Ref<MLPPVector> &x, const Ref<MLPPVector> &
real_t MLPPStat::mean(const std::vector<real_t> &x) {
real_t sum = 0;
for (int i = 0; i < x.size(); i++) {
for (uint32_t i = 0; i < x.size(); i++) {
sum += x[i];
}
return sum / x.size();
@ -51,15 +51,15 @@ std::vector<real_t> MLPPStat::mode(const std::vector<real_t> &x) {
MLPPData data;
std::vector<real_t> x_set = data.vecToSet(x);
std::map<real_t, int> element_num;
for (int i = 0; i < x_set.size(); i++) {
for (uint32_t i = 0; i < x_set.size(); i++) {
element_num[x[i]] = 0;
}
for (int i = 0; i < x.size(); i++) {
for (uint32_t i = 0; i < x.size(); i++) {
element_num[x[i]]++;
}
std::vector<real_t> modes;
real_t max_num = element_num[x_set[0]];
for (int i = 0; i < x_set.size(); i++) {
for (uint32_t i = 0; i < x_set.size(); i++) {
if (element_num[x_set[i]] > max_num) {
max_num = element_num[x_set[i]];
modes.clear();
@ -82,7 +82,7 @@ real_t MLPPStat::midrange(const std::vector<real_t> &x) {
real_t MLPPStat::absAvgDeviation(const std::vector<real_t> &x) {
real_t sum = 0;
for (int i = 0; i < x.size(); i++) {
for (uint32_t i = 0; i < x.size(); i++) {
sum += std::abs(x[i] - mean(x));
}
return sum / x.size();
@ -94,7 +94,7 @@ real_t MLPPStat::standardDeviation(const std::vector<real_t> &x) {
real_t MLPPStat::variance(const std::vector<real_t> &x) {
real_t sum = 0;
for (int i = 0; i < x.size(); i++) {
for (uint32_t i = 0; i < x.size(); i++) {
sum += (x[i] - mean(x)) * (x[i] - mean(x));
}
return sum / (x.size() - 1);
@ -102,7 +102,7 @@ real_t MLPPStat::variance(const std::vector<real_t> &x) {
real_t MLPPStat::covariance(const std::vector<real_t> &x, const std::vector<real_t> &y) {
real_t sum = 0;
for (int i = 0; i < x.size(); i++) {
for (uint32_t i = 0; i < x.size(); i++) {
sum += (x[i] - mean(x)) * (y[i] - mean(y));
}
return sum / (x.size() - 1);
@ -174,7 +174,7 @@ real_t MLPPStat::covariancev(const Ref<MLPPVector> &x, const Ref<MLPPVector> &y)
real_t MLPPStat::weightedMean(const std::vector<real_t> &x, const std::vector<real_t> &weights) {
real_t sum = 0;
real_t weights_sum = 0;
for (int i = 0; i < x.size(); i++) {
for (uint32_t i = 0; i < x.size(); i++) {
sum += x[i] * weights[i];
weights_sum += weights[i];
}
@ -183,7 +183,7 @@ real_t MLPPStat::weightedMean(const std::vector<real_t> &x, const std::vector<re
real_t MLPPStat::geometricMean(const std::vector<real_t> &x) {
real_t product = 1;
for (int i = 0; i < x.size(); i++) {
for (uint32_t i = 0; i < x.size(); i++) {
product *= x[i];
}
return std::pow(product, 1.0 / x.size());
@ -191,7 +191,7 @@ real_t MLPPStat::geometricMean(const std::vector<real_t> &x) {
real_t MLPPStat::harmonicMean(const std::vector<real_t> &x) {
real_t sum = 0;
for (int i = 0; i < x.size(); i++) {
for (uint32_t i = 0; i < x.size(); i++) {
sum += 1 / x[i];
}
return x.size() / sum;
@ -199,7 +199,7 @@ real_t MLPPStat::harmonicMean(const std::vector<real_t> &x) {
real_t MLPPStat::RMS(const std::vector<real_t> &x) {
real_t sum = 0;
for (int i = 0; i < x.size(); i++) {
for (uint32_t i = 0; i < x.size(); i++) {
sum += x[i] * x[i];
}
return sqrt(sum / x.size());
@ -207,7 +207,7 @@ real_t MLPPStat::RMS(const std::vector<real_t> &x) {
real_t MLPPStat::powerMean(const std::vector<real_t> &x, const real_t p) {
real_t sum = 0;
for (int i = 0; i < x.size(); i++) {
for (uint32_t i = 0; i < x.size(); i++) {
sum += std::pow(x[i], p);
}
return std::pow(sum / x.size(), 1 / p);
@ -216,7 +216,7 @@ real_t MLPPStat::powerMean(const std::vector<real_t> &x, const real_t p) {
real_t MLPPStat::lehmerMean(const std::vector<real_t> &x, const real_t p) {
real_t num = 0;
real_t den = 0;
for (int i = 0; i < x.size(); i++) {
for (uint32_t i = 0; i < x.size(); i++) {
num += std::pow(x[i], p);
den += std::pow(x[i], p - 1);
}
@ -226,7 +226,7 @@ real_t MLPPStat::lehmerMean(const std::vector<real_t> &x, const real_t p) {
real_t MLPPStat::weightedLehmerMean(const std::vector<real_t> &x, const std::vector<real_t> &weights, const real_t p) {
real_t num = 0;
real_t den = 0;
for (int i = 0; i < x.size(); i++) {
for (uint32_t i = 0; i < x.size(); i++) {
num += weights[i] * std::pow(x[i], p);
den += weights[i] * std::pow(x[i], p - 1);
}