fix: symbol shadowing error on clang-16 fixed

mpusz · May 29, 2024 · 1d1057a · 1d1057a
1 parent 9c4a87e
commit 1d1057a
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Showing 8 changed files with 24 additions and 24 deletions.
diff --git a/example/kalman_filter/kalman_filter-example_1.cpp b/example/kalman_filter/kalman_filter-example_1.cpp
@@ -61,11 +61,11 @@ int main()
 
   print_header(initial_guess);
   state next = initial_guess;
-  for (int index = 1; const auto& m : measurements) {
+  for (int index = 1; const auto& measurement : measurements) {
     const state& previous = next;
     const quantity gain = 1. / index * one;
-    const state current = state_update(previous, m, gain);
+    const state current = state_update(previous, measurement, gain);
     next = current;
-    print(index++, gain, m, current, next);
+    print(index++, gain, measurement, current, next);
   }
 }
diff --git a/example/kalman_filter/kalman_filter-example_2.cpp b/example/kalman_filter/kalman_filter-example_2.cpp
@@ -67,10 +67,10 @@ int main()
 
   print_header(initial);
   state next = state_extrapolation(initial, interval);
-  for (int index = 1; const auto& m : measurements) {
+  for (int index = 1; const auto& measurement : measurements) {
     const state& previous = next;
-    const state current = state_update(previous, m, gain, interval);
+    const state current = state_update(previous, measurement, gain, interval);
     next = state_extrapolation(current, interval);
-    print(index++, m, current, next);
+    print(index++, measurement, current, next);
   }
 }
diff --git a/example/kalman_filter/kalman_filter-example_3.cpp b/example/kalman_filter/kalman_filter-example_3.cpp
@@ -67,10 +67,10 @@ int main()
 
   print_header(initial);
   state next = state_extrapolation(initial, interval);
-  for (int index = 1; const auto& m : measurements) {
+  for (int index = 1; const auto& measurement : measurements) {
     const state& previous = next;
-    const state current = state_update(previous, m, gain, interval);
+    const state current = state_update(previous, measurement, gain, interval);
     next = state_extrapolation(current, interval);
-    print(index++, m, current, next);
+    print(index++, measurement, current, next);
   }
 }
diff --git a/example/kalman_filter/kalman_filter-example_4.cpp b/example/kalman_filter/kalman_filter-example_4.cpp
@@ -69,10 +69,10 @@ int main()
 
   print_header(initial);
   state next = state_extrapolation(initial, interval);
-  for (int index = 1; const auto& m : measurements) {
+  for (int index = 1; const auto& measurement : measurements) {
     const state& previous = next;
-    const state current = state_update(previous, m, gain, interval);
+    const state current = state_update(previous, measurement, gain, interval);
     next = state_extrapolation(current, interval);
-    print(index++, m, current, next);
+    print(index++, measurement, current, next);
   }
 }
diff --git a/example/kalman_filter/kalman_filter-example_5.cpp b/example/kalman_filter/kalman_filter-example_5.cpp
@@ -70,11 +70,11 @@ int main()
 
   print_header(initial);
   estimate next = predict(initial);
-  for (int index = 1; const auto& m : measurements) {
+  for (int index = 1; const auto& measurement : measurements) {
     const estimate& previous = next;
     const quantity gain = kalman::kalman_gain(previous.variance(), measurement_variance);
-    const estimate current = state_estimate_update(previous, m, gain);
+    const estimate current = state_estimate_update(previous, measurement, gain);
     next = predict(current);
-    print(index++, m, gain, current, next);
+    print(index++, measurement, gain, current, next);
   }
 }
diff --git a/example/kalman_filter/kalman_filter-example_6.cpp b/example/kalman_filter/kalman_filter-example_6.cpp
@@ -75,11 +75,11 @@ int main()
 
   print_header(initial);
   estimate next = predict(initial);
-  for (int index = 1; const auto& m : measurements) {
+  for (int index = 1; const auto& measurement : measurements) {
     const estimate& previous = next;
     const quantity gain = kalman::kalman_gain(previous.variance(), measurement_variance);
-    const estimate current = state_estimate_update(previous, m, gain);
+    const estimate current = state_estimate_update(previous, measurement, gain);
     next = predict(current);
-    print(index++, m, gain, current, next);
+    print(index++, measurement, gain, current, next);
   }
 }
diff --git a/example/kalman_filter/kalman_filter-example_7.cpp b/example/kalman_filter/kalman_filter-example_7.cpp
@@ -75,11 +75,11 @@ int main()
 
   print_header(initial);
   estimate next = predict(initial);
-  for (int index = 1; const auto& m : measurements) {
+  for (int index = 1; const auto& measurement : measurements) {
     const estimate& previous = next;
     const quantity gain = kalman::kalman_gain(previous.variance(), measurement_variance);
-    const estimate current = state_estimate_update(previous, m, gain);
+    const estimate current = state_estimate_update(previous, measurement, gain);
     next = predict(current);
-    print(index++, m, gain, current, next);
+    print(index++, measurement, gain, current, next);
   }
 }
diff --git a/example/kalman_filter/kalman_filter-example_8.cpp b/example/kalman_filter/kalman_filter-example_8.cpp
@@ -75,11 +75,11 @@ int main()
 
   print_header(initial);
   estimate next = predict(initial);
-  for (int index = 1; const auto& m : measurements) {
+  for (int index = 1; const auto& measurement : measurements) {
     const estimate& previous = next;
     const quantity gain = kalman::kalman_gain(previous.variance(), measurement_variance);
-    const estimate current = state_estimate_update(previous, m, gain);
+    const estimate current = state_estimate_update(previous, measurement, gain);
     next = predict(current);
-    print(index++, m, gain, current, next);
+    print(index++, measurement, gain, current, next);
   }
 }