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https://github.com/mpusz/mp-units.git
synced 2025-08-03 12:24:26 +02:00
fix: symbol shadowing error on clang-16 fixed
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@@ -61,11 +61,11 @@ int main()
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print_header(initial_guess);
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state next = initial_guess;
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for (int index = 1; const auto& m : measurements) {
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for (int index = 1; const auto& measurement : measurements) {
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const state& previous = next;
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const quantity gain = 1. / index * one;
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const state current = state_update(previous, m, gain);
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const state current = state_update(previous, measurement, gain);
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next = current;
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print(index++, gain, m, current, next);
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print(index++, gain, measurement, current, next);
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}
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}
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@@ -67,10 +67,10 @@ int main()
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print_header(initial);
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state next = state_extrapolation(initial, interval);
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for (int index = 1; const auto& m : measurements) {
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for (int index = 1; const auto& measurement : measurements) {
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const state& previous = next;
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const state current = state_update(previous, m, gain, interval);
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const state current = state_update(previous, measurement, gain, interval);
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next = state_extrapolation(current, interval);
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print(index++, m, current, next);
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print(index++, measurement, current, next);
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}
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}
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@@ -67,10 +67,10 @@ int main()
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print_header(initial);
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state next = state_extrapolation(initial, interval);
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for (int index = 1; const auto& m : measurements) {
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for (int index = 1; const auto& measurement : measurements) {
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const state& previous = next;
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const state current = state_update(previous, m, gain, interval);
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const state current = state_update(previous, measurement, gain, interval);
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next = state_extrapolation(current, interval);
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print(index++, m, current, next);
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print(index++, measurement, current, next);
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}
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}
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@@ -69,10 +69,10 @@ int main()
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print_header(initial);
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state next = state_extrapolation(initial, interval);
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for (int index = 1; const auto& m : measurements) {
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for (int index = 1; const auto& measurement : measurements) {
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const state& previous = next;
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const state current = state_update(previous, m, gain, interval);
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const state current = state_update(previous, measurement, gain, interval);
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next = state_extrapolation(current, interval);
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print(index++, m, current, next);
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print(index++, measurement, current, next);
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}
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}
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@@ -70,11 +70,11 @@ int main()
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print_header(initial);
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estimate next = predict(initial);
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for (int index = 1; const auto& m : measurements) {
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for (int index = 1; const auto& measurement : measurements) {
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const estimate& previous = next;
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const quantity gain = kalman::kalman_gain(previous.variance(), measurement_variance);
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const estimate current = state_estimate_update(previous, m, gain);
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const estimate current = state_estimate_update(previous, measurement, gain);
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next = predict(current);
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print(index++, m, gain, current, next);
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print(index++, measurement, gain, current, next);
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}
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}
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@@ -75,11 +75,11 @@ int main()
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print_header(initial);
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estimate next = predict(initial);
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for (int index = 1; const auto& m : measurements) {
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for (int index = 1; const auto& measurement : measurements) {
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const estimate& previous = next;
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const quantity gain = kalman::kalman_gain(previous.variance(), measurement_variance);
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const estimate current = state_estimate_update(previous, m, gain);
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const estimate current = state_estimate_update(previous, measurement, gain);
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next = predict(current);
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print(index++, m, gain, current, next);
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print(index++, measurement, gain, current, next);
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}
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}
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@@ -75,11 +75,11 @@ int main()
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print_header(initial);
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estimate next = predict(initial);
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for (int index = 1; const auto& m : measurements) {
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for (int index = 1; const auto& measurement : measurements) {
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const estimate& previous = next;
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const quantity gain = kalman::kalman_gain(previous.variance(), measurement_variance);
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const estimate current = state_estimate_update(previous, m, gain);
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const estimate current = state_estimate_update(previous, measurement, gain);
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next = predict(current);
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print(index++, m, gain, current, next);
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print(index++, measurement, gain, current, next);
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}
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}
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@@ -75,11 +75,11 @@ int main()
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print_header(initial);
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estimate next = predict(initial);
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for (int index = 1; const auto& m : measurements) {
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for (int index = 1; const auto& measurement : measurements) {
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const estimate& previous = next;
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const quantity gain = kalman::kalman_gain(previous.variance(), measurement_variance);
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const estimate current = state_estimate_update(previous, m, gain);
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const estimate current = state_estimate_update(previous, measurement, gain);
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next = predict(current);
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print(index++, m, gain, current, next);
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print(index++, measurement, gain, current, next);
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}
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}
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