Upload 7 files

dividing_into_different_subsets/8/EI/CC_EI.csv

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+Model,CC_subset_1,CC_subset_2,CC_subset_3,CC_subset_4,CC_subset_5,CC_subset_6,CC_subset_7,CC_subset_8
+CodeFuse-DeepSeek-33b,80.39,80.0,70.37,40.0,0.0,100.0,50.0,100.0
+Nxcode-CQ-7B,87.25,86.87,91.67,83.0,90.0,20.0,75.0,100.0
+codegemma-2b,38.63,26.33,17.22,6.0,0.0,0.0,5.0,0.0
+codegemma-7b,51.08,42.07,22.22,18.0,0.0,0.0,30.0,7.5
+codegemma-7b-it,58.14,55.87,46.11,33.0,65.0,0.0,5.0,37.5
+deepseek-coder-1.3b-base,47.06,30.73,20.0,11.0,0.0,0.0,0.0,0.0
+deepseek-coder-6.7b-base,56.96,48.6,30.0,22.0,0.0,0.0,7.5,2.5
+deepseek_coder-6.7b-instruct,73.24,74.0,77.22,38.0,35.0,0.0,22.5,50.0
+deepseek_coder_33b-base,58.33,56.13,42.78,38.0,30.0,0.0,40.0,5.0
+deepseek_coder_33b-instruct,68.04,69.6,61.11,55.0,65.0,0.0,32.5,50.0
+codeqwen1.5-7b,59.02,52.0,43.89,20.0,0.0,0.0,90.0,25.0

dividing_into_different_subsets/8/EI/calculate_humaneval_result.py

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+import json
+import os
+import csv
+# 定义文件所在的目录
+input_dir = 'E:/python-testn/pythonProject3/hh_1/evaluate_result'
+
+# 获取目录中的所有文件
+files = os.listdir(input_dir)
+
+# with open("token_counts_EI.csv","w", newline='') as csvfile:
+#     writer = csv.writer(csvfile)
+#     writer.writerow(["Model", "token_subset_1", "token_subset_2","token_subset_3","token_subset_4","token_subset_5","token_subset_6","token_subset_7","token_subset_8"])
+
+
+# with open("line_counts_EI.csv","w", newline='') as csvfile:
+#     writer = csv.writer(csvfile)
+#     writer.writerow(["Model", "line_subset_1", "line_subset_2","line_subset_3","line_subset_4","line_subset_5","line_subset_6","line_subset_7","line_subset_8"])
+
+with open("CC_EI.csv", "w", newline='') as csvfile:
+    writer = csv.writer(csvfile)
+    writer.writerow(["Model", "CC_subset_1", "CC_subset_2","CC_subset_3","CC_subset_4","CC_subset_5","CC_subset_6","CC_subset_7","CC_subset_8"])
+
+
+
+for file_name in files:
+    # 构建完整的文件路径
+    input_file_path = os.path.join(input_dir, file_name)
+    first_underscore_index = file_name.find('_')
+
+    # 找到最后一个 - 的位置
+    last_dash_index = file_name.rfind('-')
+    model_name = file_name[first_underscore_index + 1:last_dash_index]
+    print(model_name)
+    with open(input_file_path,"r",encoding="utf-8") as file:
+        data1=json.load(file)
+
+    with open("EI.json", "r", encoding="utf-8") as file:
+        data2=json.load(file)
+    sum0=0
+    count0=0
+    sum1=0
+    count1=0
+    sum2=0
+    count2=0
+    sum3 = 0
+    count3 = 0
+    sum4=0
+    count4=0
+    sum5 = 0
+    count5 = 0
+    sum6=0
+    count6=0
+    sum7=0
+    count7=0
+
+
+
+    for (item1,item2) in zip(data1["humaneval"]["pass@1"],data2):
+    #     #按照token个数划分后的评估结果
+    #     if item2["token_diff"] == 0:
+    #         index, value = item1
+    #         print(item2["token_diff"],index,value)
+    #         sum0=sum0+value
+    #         count0=count0+1
+    #     if item2["token_diff"] == 1:
+    #         index, value = item1
+    #         print(item2["token_diff"], index, value)
+    #         sum1=sum1+value
+    #         count1=count1+1
+    #     if item2["token_diff"] == 2:
+    #         index, value = item1
+    #         print(item2["token_diff"], index, value)
+    #         sum2=sum2+value
+    #         count2=count2+1
+    #     if item2["token_diff"] == 3:
+    #         index, value = item1
+    #         print(item2["token_diff"], index, value)
+    #         sum3=sum3+value
+    #         count3=count3+1
+    #     if item2["token_diff"] == 4:
+    #         index, value = item1
+    #         print(item2["token_diff"], index, value)
+    #         sum4 = sum4 + value
+    #         count4 = count4 + 1
+    #     if item2["token_diff"] ==5:
+    #         index, value = item1
+    #         print(item2["token_diff"], index, value)
+    #         sum5 = sum5 + value
+    #         count5 = count5 + 1
+    #     if item2["token_diff"] ==6:
+    #         index, value = item1
+    #         print(item2["token_diff"], index, value)
+    #         sum6 = sum6 + value
+    #         count6 = count6 + 1
+    #     if item2["token_diff"] ==7:
+    #         index, value = item1
+    #         print(item2["token_diff"], index, value)
+    #         sum7 = sum7 + value
+    #         count7 = count7 + 1
+
+
+        #按照行数划分后的评估结果
+        # if item2["line_diff"] == 0:
+        #     index, value = item1
+        #     print(item2["line_diff"],index,value)
+        #     sum0=sum0+value
+        #     count0=count0+1
+        # if item2["line_diff"] == 1:
+        #     index, value = item1
+        #     print(item2["line_diff"], index, value)
+        #     sum1=sum1+value
+        #     count1=count1+1
+        # if item2["line_diff"] == 2:
+        #     index, value = item1
+        #     print(item2["line_diff"], index, value)
+        #     sum2=sum2+value
+        #     count2=count2+1
+        # if item2["line_diff"] == 3:
+        #     index, value = item1
+        #     print(item2["line_diff"], index, value)
+        #     sum3=sum3+value
+        #     count3=count3+1
+        # if item2["line_diff"] == 4:
+        #     index, value = item1
+        #     print(item2["line_diff"], index, value)
+        #     sum4=sum4+value
+        #     count4=count4+1
+        # if item2["line_diff"] == 5:
+        #     index, value = item1
+        #     print(item2["line_diff"], index, value)
+        #     sum5 = sum5 + value
+        #     count5 = count5 + 1
+        # if item2["line_diff"] == 6:
+        #     index, value = item1
+        #     print(item2["line_diff"], index, value)
+        #     sum6 = sum6 + value
+        #     count6 = count6 + 1
+        # if item2["line_diff"] == 7:
+        #     index, value = item1
+        #     print(item2["line_diff"], index, value)
+        #     sum7 = sum7 + value
+        #     count7 = count7 + 1
+
+
+        #按照圈复杂度划分后的评估结果
+        if item2["CC_diff"] == 0:
+            index, value = item1
+            print(item2["CC_diff"],index,value)
+            sum0=sum0+value
+            count0=count0+1
+        if item2["CC_diff"] == 1:
+            index, value = item1
+            print(item2["CC_diff"], index, value)
+            sum1=sum1+value
+            count1=count1+1
+        if item2["CC_diff"] == 2:
+            index, value = item1
+            print(item2["CC_diff"], index, value)
+            sum2=sum2+value
+            count2=count2+1
+        if item2["CC_diff"] == 3 :
+            index, value = item1
+            print(item2["CC_diff"], index, value)
+            sum3=sum3+value
+            count3=count3+1
+        if item2["CC_diff"] == 4 :
+            index, value = item1
+            print(item2["CC_diff"], index, value)
+            sum4=sum4+value
+            count4=count4+1
+        if item2["CC_diff"] == 5 :
+            index, value = item1
+            print(item2["CC_diff"], index, value)
+            sum5=sum5+value
+            count5=count5+1
+        if item2["CC_diff"] == 6 :
+            index, value = item1
+            print(item2["CC_diff"], index, value)
+            sum6=sum6+value
+            count6=count6+1
+        if item2["CC_diff"] == 7:
+            index, value = item1
+            print(item2["CC_diff"], index, value)
+            sum7 = sum7 + value
+            count7 = count7+ 1
+
+    mean0=round(sum0/count0*100,2)
+
+    mean1=round(sum1/count1*100,2)
+    mean2=round(sum2/count2*100,2)
+    mean3=round(sum3/count3*100,2)
+    mean4=round(sum4/count4*100,2)
+    mean5 = round(sum5 / count5 * 100, 2)
+    if count6==0:
+        mean6=0
+    else:
+        mean6=round(sum6/count6*100,2)
+    mean7 = round(sum7 / count7 * 100, 2)
+    print("count_result!!")
+    print(count0,count1,count2,count3,count4,count5,count6,count7)
+    print(mean0,mean1,mean2,mean3,count4,mean5,mean6,mean7)
+    # with open("token_counts_EI.csv", mode='a', newline='', encoding='utf-8') as file:
+    #     writer = csv.writer(file)
+    #     writer.writerow([model_name,mean0,mean1,mean2,mean3,mean4,mean5,mean6,mean7])
+
+    # with open("line_counts_EI.csv", mode='a', newline='', encoding='utf-8') as file:
+    #     writer = csv.writer(file)
+    #     writer.writerow([model_name,mean0,mean1,mean2,mean3,mean4,mean5,mean6,mean7])
+
+    with open("CC_EI.csv", mode='a', newline='', encoding='utf-8') as file:
+        writer = csv.writer(file)
+        writer.writerow([model_name,mean0,mean1,mean2,mean3,mean4,mean5,mean6,mean7])
+
+

dividing_into_different_subsets/8/EI/even.py

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+import json
+
+# 读取数据
+with open("humaneval_new.json", "r", encoding="utf-8") as f:
+    data = json.load(f)
+
+# 定义划分区间数
+num_intervals = 8
+
+# 计算每个特征的值范围
+line_min = min(item['line'] for item in data)
+line_max = max(item['line'] for item in data)
+line_interval_size = (line_max - line_min) / num_intervals
+
+token_min = min(item['token'] for item in data)
+token_max = max(item['token'] for item in data)
+token_interval_size = (token_max - token_min) / num_intervals
+
+cyclomatic_complexity_min = min(item['cyclomatic_complexity'] for item in data)
+cyclomatic_complexity_max = max(item['cyclomatic_complexity'] for item in data)
+cyclomatic_complexity_interval_size = (cyclomatic_complexity_max - cyclomatic_complexity_min) / num_intervals
+count1=0
+count2=0
+count3=0
+count4=0
+count5=0
+count6=0
+count7=0
+count8=0
+
+# 根据等距划分数据
+for item in data:
+    # 计算 line 特征的区间
+    line_diff = int((item['line'] - line_min) // line_interval_size)
+    item['line_diff'] = min(line_diff,num_intervals-1) # 确保区间索引在范围内
+
+
+    # 计算 token 特征的区间
+    token_diff = int((item['token'] - token_min) // token_interval_size)
+    item['token_diff'] = min(token_diff,num_intervals-1)
+    if item['token_diff'] == 0:
+        count1 = count1 + 1
+    if item['token_diff'] == 1:
+        count2 = count2 + 1
+    if item['token_diff'] == 2:
+        count3 = count3 + 1
+    if item['token_diff'] == 3:
+        count4 = count4 + 1
+    if item['token_diff'] == 4:
+        count5 = count5 + 1
+    if item['token_diff'] == 5:
+        count6 = count6 + 1
+    if item['token_diff'] == 6:
+        count7 = count7 + 1
+    if item['token_diff'] == 7:
+        count8 = count8 + 1
+    # 计算 cyclomatic_complexity 特征的区间
+    CC_diff = int((item['cyclomatic_complexity'] - cyclomatic_complexity_min) // cyclomatic_complexity_interval_size)
+    item['CC_diff'] = min(CC_diff,num_intervals-1) # 确保区间索引在范围内
+
+# 恢复原始顺序
+data.sort(key=lambda x: x['id'])
+print(count1,count2,count3,count4,count5,count6,count7,count8)
+
+# 将更新后的数据写回JSON文件
+with open('EI.json', 'w', encoding='utf-8') as file:
+    json.dump(data, file, ensure_ascii=False, indent=4)

dividing_into_different_subsets/8/EI/line_counts_EI.csv

@@ -0,0 +1,12 @@
+Model,line_subset_1,line_subset_2,line_subset_3,line_subset_4,line_subset_5,line_subset_6,line_subset_7,line_subset_8
+CodeFuse-DeepSeek-33b,75.86,80.88,69.23,84.62,57.14,100.0,50.0,100.0
+Nxcode-CQ-7B,92.93,88.82,86.92,84.62,82.86,48.75,60.0,97.5
+codegemma-2b,51.03,25.37,20.13,30.77,6.43,0.0,5.0,2.5
+codegemma-7b,60.17,40.37,31.41,44.23,20.0,3.75,5.0,35.0
+codegemma-7b-it,72.24,53.68,46.79,56.92,27.14,10.0,45.0,42.5
+deepseek-coder-1.3b-base,53.1,31.84,24.87,34.23,6.43,0.0,22.5,45.0
+deepseek-coder-6.7b-base,73.28,45.66,37.44,49.23,13.57,0.0,15.0,17.5
+deepseek_coder-6.7b-instruct,79.31,75.74,72.05,69.23,52.86,10.0,50.0,35.0
+deepseek_coder_33b-base,75.0,54.63,43.08,56.15,32.86,3.75,0.0,52.5
+deepseek_coder_33b-instruct,83.28,69.78,57.05,71.92,53.57,20.0,2.5,32.5
+codeqwen1.5-7b,63.97,53.53,45.51,61.92,28.57,0.0,30.0,45.0

dividing_into_different_subsets/8/EI/token_counts_EI.csv

@@ -0,0 +1,12 @@
+Model,token_subset_1,token_subset_2,token_subset_3,token_subset_4,token_subset_5,token_subset_6,token_subset_7,token_subset_8
+CodeFuse-DeepSeek-33b,75.0,83.87,78.12,61.11,66.67,66.67,0,100.0
+Nxcode-CQ-7B,93.47,87.34,87.03,83.89,80.56,82.5,0,20.0
+codegemma-2b,45.97,32.1,19.84,8.61,0.0,2.5,0,0.0
+codegemma-7b,59.31,43.63,26.87,29.17,18.89,21.67,0,0.0
+codegemma-7b-it,73.33,56.45,37.19,42.5,40.0,43.33,0,0.0
+deepseek-coder-1.3b-base,54.58,38.31,19.06,11.94,0.0,22.5,0,0.0
+deepseek-coder-6.7b-base,72.22,48.31,37.81,25.56,14.44,15.83,0,0.0
+deepseek_coder-6.7b-instruct,85.28,70.89,80.16,56.39,43.33,50.83,0,0.0
+deepseek_coder_33b-base,73.06,57.66,45.78,30.56,28.33,29.17,0,0.0
+deepseek_coder_33b-instruct,87.78,67.74,66.25,38.89,28.33,68.33,0,0.0
+codeqwen1.5-7b,68.19,53.71,43.75,44.17,24.44,37.5,0,0.0