1
2 import numpy as np
3 def sub_sort(array,low,high):
4 data_value = array[low]
5 origLow = low
6 origHigh = high
7 while low < high:
8 while low < high and array[high] >= data_value:
9 high -= 1
10 while low < high and array[high] < data_value:
11 array[low] = array[high]
12 low += 1
13 array[high] = array[low]
14 array[low] = data_value
15 return low
16
17
18 def quick_sort(array,low,high):
19 if low < high:
20 key_index = sub_sort(array,low,high)
21 quick_sort(array,low,key_index)
22 quick_sort(array,key_index+1,high)
23
24
25 if __name__ == '__main__':
26 array = np.arange(30)
27 np.random.shuffle(array)
28 print(array)
29 quick_sort(array,0,len(array)-1)
30 print("quick sort:", array)
31
2 import numpy as np
3 def sub_sort(array,low,high):
4 data_value = array[low]
5 origLow = low
6 origHigh = high
7 while low < high:
8 while low < high and array[high] >= data_value:
9 high -= 1
10 while low < high and array[high] < data_value:
11 array[low] = array[high]
12 low += 1
13 array[high] = array[low]
14 array[low] = data_value
15 return low
16
17
18 def quick_sort(array,low,high):
19 if low < high:
20 key_index = sub_sort(array,low,high)
21 quick_sort(array,low,key_index)
22 quick_sort(array,key_index+1,high)
23
24
25 if __name__ == '__main__':
26 array = np.arange(30)
27 np.random.shuffle(array)
28 print(array)
29 quick_sort(array,0,len(array)-1)
30 print("quick sort:", array)
31
榪愯緇撴灉錛?br />
================= RESTART: D:\work\test\python\quick_sort.py =================
[ 2 19 7 15 4 11 12 17 20 1 3 18 27 8 14 0 16 22 21 13 10 6 28 29 26
23 24 5 25 9]
quick sort: [ 0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24
25 26 27 28 29]
]]>
鎴戣涓哄叾鏄湁婕忔礊鐨勶紝濡傛灉鏌愪釜鏁板湪鎵鏈夊垎緇勪腑騫朵笉鍗犱紭錛岃岄兘鏈夊嚭鐜幫紝鍏跺氨鏈夊彲鑳借婕忛夋帀銆?br />
榪欎釜棰樻槸鎴戦潰璇曟椂紕板埌鐨勶紝褰撴椂鎯沖緱榪囦簬澶嶆潅錛岃繕鑷繁緇欒嚜宸辨寲鍧戯紝闂暟鎹噺浼氫笉浼氬緢澶э紝鑰冨畼璇翠簡浼氬緢澶э紝鍑犵櫨涓囷紝鍏跺疄鍗充嬌鍑犵櫨涓囧鍐呭瓨鏉ヨ涔熶笉鏄粈涔堥棶棰橈紝鍙堜笉鏄嚑鍗冧嚎
錛屽綋鏃跺媺寮虹粰浜嗕釜瑙ｆ硶榪樻湁寰堝綰版紡錛岃嚜宸辮櫧鐒剁紪紼嬪騫達紝榪欐柟闈㈢殑璁粌榪樻槸涓嶅銆傚啓涓嬫潵鍙嶆濄?/span>
1 import pandas as pd
2 import copy
3
4 class BenchMark:
5 def __init__(self):
6 self.MIN = 10000
7 self.data = 0
8 def Reset(self):
9 self.MIN = 10000
10 self.data = 0
11
12 dictCounts = {}
13 dictTop10_D2C = {}
14 BENCH_MARK = BenchMark()
15 LAST_BENCH_MARK = BenchMark()
16 run_count1 = 0
17 run_count2 = 0
18
19 def FindTop10(data):
20 global BENCH_MARK, LAST_BENCH_MARK,run_count1,run_count2
21 if(data in dictCounts):
22 dictCounts[data] += 1
23 else:
24 dictCounts[data] = 1
25
26 temp = dictCounts[data]
27
28 #just record run times
29 run_count1 += 1
30
31 if LAST_BENCH_MARK.MIN != 10000 and temp< LAST_BENCH_MARK.MIN:
32 return
33
34 dictTop10_D2C[data] = temp
35
36 if len(dictTop10_D2C)>10:
37 BENCH_MARK.Reset()
38 for item in dictTop10_D2C:
39
40 #just record run times
41 run_count2+=1
42
43 if dictTop10_D2C[item] < BENCH_MARK.MIN:
44 BENCH_MARK.MIN = dictTop10_D2C[item]
45 BENCH_MARK.data = item
46 LAST_BENCH_MARK = copy.deepcopy(BENCH_MARK)
47 dictTop10_D2C.pop(BENCH_MARK.data)
48
49 def PrintData2Count(aDict):
50 for key in aDict:
51 print('%.1f:%d' % (key, aDict[key]))
52
53 if __name__ == '__main__':
54 df = pd.read_csv('D:/data/ctp_data/rb/201709/rb1801_20170905.csv')
55 for data in df['LastPx']:
56 FindTop10(data)
57
58 PrintData2Count(dictCounts)
59 print("==============dictCounts length:", len(dictCounts))
60 PrintData2Count(dictTop10_D2C)
61
62 print("run_count1:%d,run_count2:%d" %(run_count1,run_count2))
63
2 import copy
3
4 class BenchMark:
5 def __init__(self):
6 self.MIN = 10000
7 self.data = 0
8 def Reset(self):
9 self.MIN = 10000
10 self.data = 0
11
12 dictCounts = {}
13 dictTop10_D2C = {}
14 BENCH_MARK = BenchMark()
15 LAST_BENCH_MARK = BenchMark()
16 run_count1 = 0
17 run_count2 = 0
18
19 def FindTop10(data):
20 global BENCH_MARK, LAST_BENCH_MARK,run_count1,run_count2
21 if(data in dictCounts):
22 dictCounts[data] += 1
23 else:
24 dictCounts[data] = 1
25
26 temp = dictCounts[data]
27
28 #just record run times
29 run_count1 += 1
30
31 if LAST_BENCH_MARK.MIN != 10000 and temp< LAST_BENCH_MARK.MIN:
32 return
33
34 dictTop10_D2C[data] = temp
35
36 if len(dictTop10_D2C)>10:
37 BENCH_MARK.Reset()
38 for item in dictTop10_D2C:
39
40 #just record run times
41 run_count2+=1
42
43 if dictTop10_D2C[item] < BENCH_MARK.MIN:
44 BENCH_MARK.MIN = dictTop10_D2C[item]
45 BENCH_MARK.data = item
46 LAST_BENCH_MARK = copy.deepcopy(BENCH_MARK)
47 dictTop10_D2C.pop(BENCH_MARK.data)
48
49 def PrintData2Count(aDict):
50 for key in aDict:
51 print('%.1f:%d' % (key, aDict[key]))
52
53 if __name__ == '__main__':
54 df = pd.read_csv('D:/data/ctp_data/rb/201709/rb1801_20170905.csv')
55 for data in df['LastPx']:
56 FindTop10(data)
57
58 PrintData2Count(dictCounts)
59 print("==============dictCounts length:", len(dictCounts))
60 PrintData2Count(dictTop10_D2C)
61
62 print("run_count1:%d,run_count2:%d" %(run_count1,run_count2))
63
榪愯緇撴灉濡備笅錛?/p>
銆傘傘傘傘傘?/span>
4121.0:206
4123.0:278
4124.0:180
4122.0:244
4125.0:118
4126.0:34
4127.0:4
4081.0:1366
4080.0:1073
4077.0:1072
4078.0:1091
4079.0:800
4076.0:874
4075.0:886
4074.0:1108
4071.0:719
4073.0:1281
4072.0:1049
4070.0:567
4069.0:442
4068.0:290
4067.0:199
4066.0:204
4065.0:109
4064.0:60
4063.0:80
4062.0:57
4061.0:70
4060.0:70
4059.0:32
4057.0:6
4058.0:22
4129.0:6
4137.0:2
4135.0:2
4133.0:2
==============dictCounts length: 75
4109.0:2080
4108.0:2047
4095.0:3009
4096.0:2785
4094.0:2265
4099.0:2573
4098.0:2702
4097.0:2491
4100.0:2147
4107.0:1809
run_count1:70684,run_count2:19679
]]>
]]>
榪欐槸鎴戦槄璇匯婃繁鍏ヤ簡瑙ｈ綆楁満緋葷粺銆嬬浜岀瘒璇諱功絎旇銆?nbsp; 闃呰鍏ㄦ枃
]]>
]]>
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