import numpy
np = numpy.array([[1, 2, 3],[4, 5, 6],[7, 8, 9]])
print(np[:, 1]) # ":"表示所有的行，"1"表示第二列
print(np[:, 0:2])
print("------------------------------------------------")
np1 = numpy.array([1, 2, 3, 4, 5, 6])
equal = (np1 == 6) # 挨著挨著匹配np1數(shù)組，dtype為bool類型
print(equal)
print(np1[equal])
print("------------------------------------------------")
np2 = numpy.array(["1", "2", "3"])
print(np2.dtype)
f2 = np2.astype(float) # numpy中的數(shù)據(jù)類型轉(zhuǎn)換，不能直接改原數(shù)據(jù)的dtype!? 只能用函數(shù)astype()
print(f2.dtype)
print(f2)
print("------------------------------------------------")
np3 = numpy.array([[1, 2, 3],[4, 5, 6],[7, 8, 9]])
sum1 = np3.sum(axis=1) # 按行求和
sum2 = np3.sum(axis=0) # 按列求和
print(sum1)
print(sum2)
print("------------------------------------------------")
np4 = numpy.arange(15) # 構(gòu)造15個從0開始的數(shù)
print(np4)
np4_1 = numpy.arange(5, 30, 5) # 構(gòu)造5到30之間，以5為步長的數(shù)組
print(np4_1)
np5 = numpy.arange(15).reshape(5, 3) # 把15個數(shù)分成5行3列
print(np5.shape) # 打印行數(shù)，列數(shù)
print(np5.ndim) # 打印數(shù)組維度
print(np5.size) #打印數(shù)組大小
print(np5.sum(axis=1))
print("------------------------------------------------")
np6 = numpy.zeros((4, 3)) # 構(gòu)造 0
print(np6)
np7 = numpy.ones((2, 3, 4), dtype = numpy.int32) # 構(gòu)造一個三維數(shù)組，值全為1
print(np7)
print("------------------------------------------------")
A = numpy.array([[1, 2], [0, 3]])
B = numpy.array([[2, 4],[5, 0]])
print(A * B) # 算數(shù)的乘法，每個位置都相乘
print(A.dot(B)) # 矩陣的乘法 (行和列相乘)
print(numpy.dot(A, B)) # 矩陣的乘法另一種寫法
print(A.T) # 打印A的轉(zhuǎn)置，實際就是A的行變成了列
print("-------------------矩陣常用操作-----------------------------")
a = numpy.floor(10 * numpy.random.random((2, 2))) # floor向下取整
b = numpy.floor(10 * numpy.random.random((2, 2)))
print(a)
print(b)
print(numpy.hstack((a, b))) # 數(shù)組橫拼接
print(numpy.vstack((a, b))) # 數(shù)組豎拼接
print("------------------矩陣常用操作------------------------------")
np8 = numpy.floor(10 * numpy.random.random((2, 12)))
print(np8)
np8_h = numpy.hsplit(np8, 3) # 將數(shù)組分成三份
print(np8_h)
print(numpy.hsplit(np8, (3, 4))) # 在第三行，第四行各切一刀，分成了三份
print(numpy.hsplit(np8, (3, 4, 5))) # 在第三行，第四行,第五行各切一刀，分成了四份
print("-----------------不同復(fù)制操作對比-------------------------------")
m = numpy.arange(12)
n = m
print(n is m)
n.shape = (3, 4)
print(m.shape)
print(id(m))
print(id(n))
print("------------------------------------------------")
np9 = numpy.arange(0, 20, 5)
print(numpy.tile(np9, (3, 3))) # 對數(shù)組進行擴展
print("------------------------------------------------")
np10 = numpy.array([[2, 3, 1],[4, 2, 5]])
p = numpy.sort(np10, axis=1) # 按行進行升序排序
print(p)
np10.sort(axis=0) # 按列進行升序排序
print(np10)
print("-------------------求升序排序的索引值-----------------------------")
h = numpy.array([2, 3, 1, 4])
print(h.argsort(axis=0))
j = h.argsort(axis=0)
print(h[j]) # 把索引當(dāng)做參數(shù)求原來的值
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