#encoding=utf-8
import?numpy?as?np
#本節(jié)主要講解對?numpy.array()?數(shù)據(jù)類型的操作，?numpy?中的array?指的的數(shù)學中的?矩陣（行列式）?matrix
def?main():
????lst=[[1,3,5],[2,4,6]]
????print(type(lst))?#<class?'list'>
????np_lst=np.array(lst)
????print(type(np_lst))?#<class?'numpy.ndarray'>
????np_lst=np.array(lst,dtype=np.float)
????#bool,int,int8,int16,int32,int64,int128,uint8,uint16,uint32,uint64,uint128,folat,float16/32/64,complex64/128
????print(np_lst.shape)?#(2,?3)??表示數(shù)據(jù)結(jié)構(gòu)是2行3列
????print(np_lst.ndim)??#2??表示數(shù)據(jù)結(jié)構(gòu)維度是2
????print(np_lst.dtype)?#float64?表示數(shù)據(jù)類型
????print(np_lst.itemsize)?#8?代表每個元素占用的字節(jié)是8字節(jié)?因為上面的數(shù)據(jù)類型是float64
????print(np_lst.size)?#6?代表總共有的元素個數(shù)??此時總共有6*8?=?48個?字節(jié)占用

????#2?常用數(shù)據(jù)?Some?Arrays
????print(np.zeros([2,4]))#?[[0.?0.?0.?0.]?[0.?0.?0.?0.]]?數(shù)組初始化??2行4列,元素值都是0
????print(np.ones([3,5]))#[[1.?1.?1.?1.?1.]?[1.?1.?1.?1.?1.]?[1.?1.?1.?1.?1.]]?數(shù)組初始化??3行5列,元素值都是1
????print("Rand:")
????print(np.random.rand(2,4))#[[0.80108456?0.85873572?0.19077216?0.57489116]?[0.98368305?0.54631833?0.5836906??0.5840696?]]?數(shù)組初始化??2行4列,元素值都是0-1之間的隨機數(shù)
????print(np.random.rand())?#?0.5184057738632414?得到一個0-1之間的隨機數(shù)
????print("RandInt:")
????print(np.random.randint(1,10,3))?#[9?2?1]??得到3個?1-10?之間的隨機整數(shù)
????print("Randn:")
????print(np.random.randn(2,4))?#[[-0.03133145?-2.40511588??0.41716157?-0.40951324]?[-0.16604123?-0.87621271??0.07418091??0.56484108]]?數(shù)組初始化，?2行4列,元素值都是?標準正態(tài)分布?之間的隨機數(shù)
????print("Choice:")
????print(np.random.choice([10,20,30]))#30?得到?[10,20,30]?中隨機一個元素
????print("Distribute:")
????print(np.random.beta(1,10,5))#?[0.27342954?0.06327893?0.05248474?0.37551789?0.18812033]?得到一個貝塔分布，元素個數(shù)5
????#3?Array?Opes
????print(np.arange(1,11))?#?[?1??2??3??4??5??6??7??8??9?10]?得到一個?1-10?的數(shù)組
????print(np.arange(1,?11).reshape([2,5]))??#?[[?1??2??3??4??5]?[?6??7??8??9?10]]?上面的數(shù)組重塑?得到一個2行5列的數(shù)組
????#np.arange(1,11).reshape([2,-1])??的-1?表示不指定列數(shù)量，則會根據(jù)?第一個數(shù)組arange?的元素總數(shù)?除以?行數(shù)?得到列數(shù)?10/2?=5
????lst?=?np.arange(1,5).reshape([2,-1])
????print(np.array(lst))#[[1?2]?[3?4]]
????print("exp?指數(shù)函數(shù)操作?底數(shù)是自然數(shù)e，指數(shù)是?lst:")
????print(np.exp(lst))?#?[[?2.71828183??7.3890561?]?[20.08553692?54.59815003]]?指數(shù)函數(shù)操作?底數(shù)是自然數(shù)e，指數(shù)是?lst
????print("exp2?指數(shù)函數(shù)操作?底數(shù)是2，指數(shù)是?lst:")
????print(np.exp2(lst))?#[[?2.??4.]?[?8.?16.]]指數(shù)函數(shù)操作?底數(shù)是2，指數(shù)是?lst
????print("sqrt?開方:")
????print(np.sqrt(lst))?#[[1.?????????1.41421356]?[1.73205081?2.????????]]?開方
????print("sin?三角函數(shù):")
????print(np.sin(lst))?#[[?0.84147098??0.90929743]?[?0.14112001?-0.7568025?]]三角函數(shù)
????print("log?對數(shù)函數(shù)操作，底數(shù)為自然數(shù)e，對數(shù)是?lst:")
????print(np.log(lst))?#[[0.?????????0.69314718]?[1.09861229?1.38629436]]對數(shù)函數(shù)操作，底數(shù)為自然數(shù)e，對數(shù)是?lst

????lst?=?np.array([
????????????????????[[1,2,3,4],[4,5,6,7]],
????????????????????[[7,8,9,10],[10,11,12,13]],
????????????????????[[14,15,16,17],[18,19,20,21]]
????????????????????])
????#axis?與數(shù)組維數(shù)?有關(guān)?,axis的最大值是數(shù)組-1，axis取值越大，則數(shù)組的深入程度越大
????print(lst.sum(axis=0))#[[22?25?28?31]?[32?35?38?41]]
????print(lst.sum(axis=1))#[[?5??7??9?11]?[17?19?21?23]?[32?34?36?38]]
????print("Sum(axis=2)")
????print(lst.sum(axis=2))#[[10?22]?[34?46]?[62?78]]
????print("Max(axis=1)")
????print(lst.max(axis=1))#[[?4??5??6??7]?[10?11?12?13]?[18?19?20?21]]
????print("Min(axis=0)")
????print(lst.min(axis=0))#[[1?2?3?4]?[4?5?6?7]]
????print(lst.sum())?#?252
????print(lst.max())??#?21
????print(lst.min())??#?1

????lst1?=?np.array([10,20,30,40])
????lst2?=?np.array([4,3,2,1])
????print("Add?加法")
????print(lst1+lst2)?#[14?23?32?41]
????print("Sub?減法")
????print(lst1-lst2)?#[?6?17?28?39]
????print("Mul?乘法")
????print(lst1*lst2)?#[40?60?60?40]
????print("Div?除法")
????print(lst1/lst2)?#[?2.5?????????6.66666667?15.?????????40.????????]
????print("Square?乘方")
????print(lst1**lst2)?#[10000??8000???900????40]
????print("Dot?矩陣乘法")?#
????print(np.dot(lst1.reshape([2,2]),lst2.reshape([2,2])))?#[[?80??50]?[200?130]]
????print("Concatenate?追加")
????print(np.concatenate((lst1,lst2),axis=0))?#?[10?20?30?40??4??3??2??1]
????print("vstack?垂直追加")
????print(np.vstack((lst1,lst2)))#[[10?20?30?40]?[?4??3??2??1]]
????print("vstack?水平追加")
????print(np.hstack((lst1,lst2)))#[10?20?30?40??4??3??2??1]
????print("split?分成等份")
????print(np.split(lst1,2))?#[array([10,?20]),?array([30,?40])]
????print("copy?拷貝")
????print(np.copy(lst1))??#[10?20?30?40]


if?__name__=="__main__":
????main()