[英]Python zip on two numpy arrays
下面是一個工作示例,您可以復制所有變量並運行for
循環進行檢查
我有兩個列表,其中一個的長度= 13,另一個的長度= 7。
varying_DA = [70,78,86,90,94,98,100,102,106,110,114,122,130]
test_array = [1,2,3,4,5,6,7,8,9,10,11,12,13] #DUMMY array
varying_Hinv = [60,76,92,100,108,124,140]
我想遍歷以上兩個列表,即使用兩個for
循環:
for vary_DA,test in zip(varying_DA,test_array):
for vary_Hinv,min_a,max_a in zip(varying_Hinv,min_aH,max_aH):
所以在上面for
循環,它開始70
對vary_DA
和遍歷的7個值vary_Hinv
,即60,76,...,124140。 然后,對vary_DA
轉到78
, vary_DA
,直到對vary_DA
用130
vary_DA
。
我有一個特定的值min_aH
和max_aH
每個的vary_DA
和vary_Hinv
值。
min_aH = np.array([[24,30,30,30,30,30,30],[36,42,42,47,47,47,47],
[36,42,42,42,42,42,42],[36,42,42,42,42,42,42],
[42,47,47,47,53,47,53],[42,53,47,47,53,53,53],
[47,47,47,47,47,53,47],[47,47,47,47,47,59,59],
[53,53,59,59,59,59,64],[47,65,59,59,47,47,64],
[53,47,41,47,53,47,47],[36,41,41,41,53,47,47],
[36,36,41,41,53,47,47]])
# As you can see it is a 13x7 matrix, 7 for the 7 different vary_Hinv
# values and 13 for the 13 different vary_DA values
max_aH = np.array([[54,60,60,60,60,60,60],[60,66,66,66,66,66,66],
[66,66,72,72,72,72,72],[66,72,72,72,78,78,78],
[72,78,78,78,84,84,84],[78,84,84,89,89,84,84],
[78,84,78,89,84,84,78],[84,84,78,84,84,89,89],
[84,84,84,89,89,89,89],[84,89,84,89,101,101,101],
[89,89,95,101,95,101,101],[96,96,95,107,95,101,101],
[96,101,95,107,107,101,101]])
即,當vary_DA = 70
且vary_Hinv = 60
, min_aH = 24
且max_aH = 54
。 當vary_DA = 70
且vary_Hinv = 76
, min_aH = 30
且max_aH = 60
,依此類推。
現在,我想在for
循環中使用min_aH
和max_aH
這些特定值,但是從下面的工作示例可以看出,它失敗了。
ii = 0
for vary_DA,test in zip(varying_DA,test_array):
jj = 0
for vary_Hinv,min_a,max_a in zip(varying_Hinv,min_aH,max_aH):
print vary_DA,vary_Hinv,ii,jj,min_aH[ii][jj],max_aH[ii][jj]
jj = jj + 1
ii = ii + 1
IndexError:標量變量的索引無效。
底線:我可以清楚地做到以下幾點:
In [12]: min_aH[0]
Out[12]: array([24, 30, 30, 30, 30, 30, 30])
In [13]: min_aH[0][0]
Out[13]: 24
為什么它在for
循環中失敗? 我如何使其工作?
編輯 :
我在上面的工作示例中犯了一個錯誤。 在第二個for
循環中, print
應為:
print vary_DA,vary_Hinv,ii,jj,min_a[ii][jj],max_a[ii][jj]
我以前有min_aH
和max_aH
而不是min_a
和max_a
。 有人可以讓我知道以上是否有效嗎?
一些評論,首先使用python 3,您的示例為我運行而沒有錯誤,並輸出:
70 60 0 0 24 54
70 76 0 1 30 60
70 92 0 2 30 60
...
78 60 0 0 24 54
78 76 0 1 30 60
78 92 0 2 30 60
78 100 0 3 30 60
...
我不相信這是您想要的,因為后四行對於后兩個數字應具有與前四行不同的值。 我認為您希望顯示的最后四行是:
78 60 1 0 36 60
78 76 1 1 42 66
78 92 1 2 42 66
78 100 1 3 47 66
根據您的描述。 這是因為ii = ii + 1在您的初始循環之外,因此ii始終不會改變值。 一個有效的版本(在python 3.6中再次出現)將是:
ii = 0
for vary_DA,test in zip(varying_DA,test_array):
jj = 0
for vary_Hinv,min_a,max_a in zip(varying_Hinv,min_aH,max_aH):
print (vary_DA,vary_Hinv,ii,jj,min_aH[ii][jj],max_aH[ii][jj])
jj = jj + 1
ii = ii + 1
盡管這根本沒有利用壓縮值,但如果嘗試達到期望的輸出,則將無法實現。 您可以在這里看到是否打印出壓縮值,您只是獲得了min_aH和max_aH的每個列表,但我相信您需要各個值。
ii = 0
for vary_DA,test in zip(varying_DA,test_array):
jj = 0
for vary_Hinv,min_a,max_a in zip(varying_Hinv,min_aH,max_aH):
print (vary_DA,vary_Hinv,ii,jj,min_aH[ii][jj],max_aH[ii][jj],min_a,max_a)
jj = jj + 1
ii = ii + 1
結果是:
70 60 0 0 24 54 [24 30 30 30 30 30 30] [54 60 60 60 60 60 60]
70 76 0 1 30 60 [36 42 42 47 47 47 47] [60 66 66 66 66 66 66]
70 92 0 2 30 60 [36 42 42 42 42 42 42] [66 66 72 72 72 72 72]
...
78 60 1 0 36 60 [24 30 30 30 30 30 30] [54 60 60 60 60 60 60]
78 76 1 1 42 66 [36 42 42 47 47 47 47] [60 66 66 66 66 66 66]
78 92 1 2 42 66 [36 42 42 42 42 42 42] [66 66 72 72 72 72 72]
...
最后,正確使用zip來獲取所需的值,從而使迭代器ii和jj變得不必要:
ii = 0
for vary_DA,test,min_a,max_a in zip(varying_DA,test_array,min_aH,max_aH):
jj = 0
for vary_Hinv,mn,mx in zip(varying_Hinv,min_a,max_a):
print (vary_DA,vary_Hinv,ii,jj,min_aH[ii][jj],max_aH[ii][jj],mn,mx)
jj = jj + 1
ii = ii + 1
贈送:
70 60 0 0 24 54 24 54
70 76 0 1 30 60 30 60
70 92 0 2 30 60 30 60
...
78 60 1 0 36 60 36 60
78 76 1 1 42 66 42 66
78 92 1 2 42 66 42 66
...
根據需要,最后刪除看起來像這樣的迭代器:
for vary_DA,test,min_a,max_a in zip(varying_DA,test_array,min_aH,max_aH):
for vary_Hinv,mn,mx in zip(varying_Hinv,min_a,max_a):
print (vary_DA,vary_Hinv,mn,mx)
這應該可以按需工作。
我還能夠使用python 2.7成功運行您的示例代碼和響應,所以我不確定為什么會根據這里的內容得到該錯誤。
這對我適用於Python 3.6:
varying_DA = [70,78,86,90,94,98,100,102,106,110,114,122,130]
test_array = [1,2,3,4,5,6,7,8,9,10,11,12,13] #DUMMY array
varying_Hinv = [60,76,92,100,108,124,140]
min_aH = np.array([[24,30,30,30,30,30,30],[36,42,42,47,47,47,47],
[36,42,42,42,42,42,42],[36,42,42,42,42,42,42],
[42,47,47,47,53,47,53],[42,53,47,47,53,53,53],
[47,47,47,47,47,53,47],[47,47,47,47,47,59,59],
[53,53,59,59,59,59,64],[47,65,59,59,47,47,64],
[53,47,41,47,53,47,47],[36,41,41,41,53,47,47],
[36,36,41,41,53,47,47]])
max_aH = np.array([[54,60,60,60,60,60,60],[60,66,66,66,66,66,66],
[66,66,72,72,72,72,72],[66,72,72,72,78,78,78],
[72,78,78,78,84,84,84],[78,84,84,89,89,84,84],
[78,84,78,89,84,84,78],[84,84,78,84,84,89,89],
[84,84,84,89,89,89,89],[84,89,84,89,101,101,101],
[89,89,95,101,95,101,101],[96,96,95,107,95,101,101],
[96,101,95,107,107,101,101]])
ii = 0
for vary_DA,test in zip(varying_DA,test_array):
jj = 0
for vary_Hinv,min_a,max_a in zip(varying_Hinv,min_aH,max_aH):
print(vary_DA,vary_Hinv,ii,jj,min_aH[ii][jj],max_aH[ii][jj])
jj = jj + 1
ii = ii + 1
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