feat(script): Optimize normal distribution generator

* feat(script): Finish experiment 1 and 2

Signed-off-by: KunoiSayami <[email protected]>

3 files changed, 25 insertions, 16 deletions

diff --git a/ex_normal_distribution.py b/ex_normal_distribution.py
index f82df93..272b9b6 100755
--- a/ex_normal_distribution.py
+++ b/ex_normal_distribution.py
@@ -1,24 +1,35 @@
 #!/usr/bin/env python3
+import numpy as np
 import matplotlib.pyplot as plt
+from matplotlib.ticker import PercentFormatter
 
 
 def function_pdf(element: list[int]):
-    plt.hist(element, bins=500)
+    plt.hist(element, bins=500, histtype='step')
     plt.show()
 
 
 def function_cdf(element: list[int]):
-    plt.hist(element, bins=500, cumulative=True)
+    plt.hist(element, bins=500, cumulative=True, histtype='step')
     plt.show()
 
 
-def normal_distribution():
+def function_1000_cdf(element: list[int]):
+    plt.hist(element, bins=250, histtype='step', label='x', cumulative=True,
+             weights=np.ones(len(element)) / len(element))
+    plt.hist(element[:1000], bins=100, histtype='step', label='y', cumulative=True, weights=np.ones(1000) / 1000)
+    plt.gca().yaxis.set_major_formatter(PercentFormatter(1))
+    plt.show()
+
+
+def normal_distribution() -> list[int]:
     with open('normal_distribution.txt') as fin:
         context = fin.read()
-    elements = list(map(int, context.splitlines()))
-    function_pdf(elements)
-    function_cdf(elements)
+    return list(map(int, context.splitlines()))
 
 
 if __name__ == '__main__':
-    normal_distribution()
+    elements = normal_distribution()
+    function_pdf(elements)
+    function_cdf(elements)
+    function_1000_cdf(elements)
diff --git a/main.cu b/main.cu
index bc42b11..c34add0 100644
--- a/main.cu
+++ b/main.cu
@@ -92,7 +92,6 @@ typedef unsigned int LL;
 #endif
 
 #ifdef MEASURE_TIME
-#include <cuda/atomic>
 #undef BUILD_SIZE
 #define BUILD_SIZE 1024
 #endif
@@ -578,12 +577,10 @@ __global__ void kernel(LL *items, LL *op, LL *result) {
       result[tid] = l->Search(item);
 #ifdef MEASURE_TIME
       unsigned long long end_time = clock64() - start_time;
-      // SpendTime[tid] = (int)end_time;
       if (l->spend_time[tid]) {
         printf("%d\n", tid);
       }
       l->spend_time[tid] = (int)end_time;
-      // printf("%d %d\n", SpendTime[tid], tid);
 #endif
     }
   }
@@ -833,7 +830,7 @@ int main(int argc, char **argv) {
   cudaEventCreate(&stop);
   cudaEventRecord(start, nullptr);
 #ifdef MEASURE_TIME
-  kernel<<<NUM_THREADS, 1>>>(Citems, Cop2, Cresult);
+  kernel<<<NUM_ITEMS, 1>>>(Citems, Cop2, Cresult);
 #else
   kernel<<<blocks, NUM_THREADS>>>(Citems, Cop2, Cresult);
 #endif
@@ -891,7 +888,7 @@ int main(int argc, char **argv) {
         break;
       fprintf(file, "%d\n", tmp[i]);
     }
-    // printf("%d\n", i);
+    printf("%d\n", i);
     delete[] tmp;
     fclose(file);
   }
diff --git a/normal_distribution.cpp b/normal_distribution.cpp
index fd52ac1..c320ce4 100644
--- a/normal_distribution.cpp
+++ b/normal_distribution.cpp
@@ -1,4 +1,5 @@
 #include <algorithm>
+#include <cassert>
 #include <cstdio>
 #include <random>
 #include <set>
@@ -22,13 +23,13 @@ int main() {
   while (set.size() != length) {
     auto element = (long long)std::round(normalDistribution(randomEngine));
     auto ret = set.insert(element);
-    if (ret.second)
+    if (ret.second) {
       vector.push_back(element);
+      printf("%lld\n", element);
+    }
   }
 
-  for (long long element : vector) {
-    printf("%lld\n", element);
-  }
+  assert(vector.size() == length);
 
   return 0;
 }
\ No newline at end of file