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936 lines
9.0 KiB
Markdown
936 lines
9.0 KiB
Markdown
# 数组属性方法总结
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| | 作用 |
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| --- | --- |
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| 1 | **基本属性** |
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| `a.dtype` | 数组元素类型 `float32,uint8,...` |
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| `a.shape` | 数组形状 `(m,n,o,...)` |
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| `a.size` | 数组元素数 |
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| `a.itemsize` | 每个元素占字节数 |
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| `a.nbytes` | 所有元素占的字节 |
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| `a.ndim` | 数组维度 |
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| 2 | **形状相关** |
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| `a.flat` | 所有元素的迭代器 |
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| `a.flatten()` | 返回一个1维数组的复制 |
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| `a.ravel()` | 返回一个1维数组，高效 |
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| `a.resize(new_size)` | 改变形状 |
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| `a.swapaxes(axis1, axis2)` | 交换两个维度的位置 |
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| `a.transpose(*axex)` | 交换所有维度的位置 |
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| `a.T` | 转置，`a.transpose()` |
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| `a.squeeze()` | 去除所有长度为1的维度 |
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| 3 | **填充复制** |
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| `a.copy()` | 返回数组的一个复制 |
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| `a.fill(value)` | 将数组的元组设置为特定值 |
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| 4 | **转化** |
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| `a.tolist()` | 将数组转化为列表 |
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| `a.tostring()` | 转换为字符串 |
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| `a.astype(dtype)` | 转化为指定类型 |
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| `a.byteswap(False)` | 转换大小字节序 |
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| `a.view(type_or_dtype)` | 生成一个使用相同内存，但使用不同的表示方法的数组 |
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| 5 | **复数** |
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| `a.imag` | 虚部 |
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| `a.real` | 实部 |
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| `a.conjugate()` | 复共轭 |
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| `a.conj()` | 复共轭（缩写） |
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| 6 | **保存** |
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| `a.dump(file)` | 将二进制数据存在file中 |
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| `a.dump()` | 将二进制数据表示成字符串 |
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| `a.tofile(fid, sep="",format="%s")` | 格式化ASCⅡ码写入文件 |
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| 7 | **查找排序** |
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| `a.nonzero()` | 返回所有非零元素的索引 |
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| `a.sort(axis=-1)` | 沿某个轴排序 |
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| `a.argsort(axis=-1)` | 沿某个轴，返回按排序的索引 |
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| `a.searchsorted(b)` | 返回将b中元素插入a后能保持有序的索引值 |
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| 8 | **元素数学操作** |
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| `a.clip(low, high)` | 将数值限制在一定范围内 |
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| `a.round(decimals=0)` | 近似到指定精度 |
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| `a.cumsum(axis=None)` | 累加和 |
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| `a.cumprod(axis=None)` | 累乘积 |
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| 9 | **约简操作** |
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| `a.sum(axis=None)` | 求和 |
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| `a.prod(axis=None)` | 求积 |
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| `a.min(axis=None)` | 最小值 |
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| `a.max(axis=None)` | 最大值 |
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| `a.argmin(axis=None)` | 最小值索引 |
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| `a.argmax(axis=None)` | 最大值索引 |
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| `a.ptp(axis=None)` | 最大值减最小值 |
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| `a.mean(axis=None)` | 平均值 |
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| `a.std(axis=None)` | 标准差 |
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| `a.var(axis=None)` | 方差 |
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| `a.any(axis=None)` | 只要有一个不为0，返回真，逻辑或 |
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| `a.all(axis=None)` | 所有都不为0，返回真，逻辑与 |
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In [1]:
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```py
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from numpy import *
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```
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## 基本属性
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In [2]:
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```py
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a = array([[0, 1, 2, 3], [4, 5, 6, 7]])
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a
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```
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Out[2]:
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```py
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array([[0, 1, 2, 3],
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[4, 5, 6, 7]])
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```
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数组元素属性：
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In [3]:
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```py
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a.dtype
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```
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Out[3]:
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```py
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dtype('int32')
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```
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形状：
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In [4]:
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```py
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a.shape
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```
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Out[4]:
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```py
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(2L, 4L)
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```
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元素数目：
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In [5]:
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```py
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a.size
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```
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Out[5]:
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```py
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8
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```
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元素占字节大小：
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In [6]:
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```py
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a.itemsize
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```
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Out[6]:
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```py
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4
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```
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所有元素所占字节：
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In [7]:
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```py
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a.nbytes
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```
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Out[7]:
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```py
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32
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```
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数据维度：
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In [8]:
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```py
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a.ndim
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```
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Out[8]:
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```py
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2
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```
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## 形状相关
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In [9]:
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```py
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for row in a:
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print row
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```
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```py
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[0 1 2 3]
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[4 5 6 7]
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```
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所有元素的迭代器：
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In [10]:
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```py
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for elt in a.flat:
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print elt
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```
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```py
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0
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1
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2
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3
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4
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5
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6
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7
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```
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所有元素组成的一维数组，按照行排列：
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In [11]:
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```py
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a.flatten()
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```
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Out[11]:
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```py
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array([0, 1, 2, 3, 4, 5, 6, 7])
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```
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In [12]:
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```py
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a.ravel()
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```
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Out[12]:
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```py
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array([0, 1, 2, 3, 4, 5, 6, 7])
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```
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重新改变形状：
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In [13]:
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```py
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a.resize((4,2))
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a
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```
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Out[13]:
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```py
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array([[0, 1],
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[2, 3],
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[4, 5],
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[6, 7]])
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```
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交换这两个轴的顺序：
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In [14]:
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```py
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a.swapaxes(0,1)
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```
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Out[14]:
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```py
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array([[0, 2, 4, 6],
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[1, 3, 5, 7]])
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```
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转置：
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In [15]:
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```py
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a.transpose()
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```
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Out[15]:
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```py
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array([[0, 2, 4, 6],
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[1, 3, 5, 7]])
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```
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转置：
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In [16]:
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```py
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a.T
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```
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Out[16]:
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```py
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array([[0, 2, 4, 6],
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[1, 3, 5, 7]])
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```
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In [17]:
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```py
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a2 = array([1,2,3])
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a2.shape
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```
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Out[17]:
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```py
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(3L,)
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```
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In [18]:
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```py
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a2.resize((1,3,1))
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a2.shape
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```
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Out[18]:
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```py
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(1L, 3L, 1L)
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```
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去除长度为1的维度：
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In [19]:
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```py
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a2 = a2.squeeze()
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a2.shape
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```
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Out[19]:
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```py
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(3L,)
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```
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## 填充复制
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复制：
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In [20]:
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```py
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b = a.copy()
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b
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```
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Out[20]:
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```py
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array([[0, 1],
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[2, 3],
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[4, 5],
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[6, 7]])
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```
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复制不影响原来的数组：
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In [21]:
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```py
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b[0][0] = -1
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b # First value changed
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```
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Out[21]:
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```py
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array([[-1, 1],
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[ 2, 3],
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[ 4, 5],
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[ 6, 7]])
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```
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In [22]:
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```py
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a # original not changed because b is a copy
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```
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Out[22]:
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```py
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array([[0, 1],
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[2, 3],
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[4, 5],
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[6, 7]])
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```
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填充：
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In [23]:
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```py
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b.fill(4)
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b
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```
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Out[23]:
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```py
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array([[4, 4],
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[4, 4],
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[4, 4],
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[4, 4]])
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```
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## 转化
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转化为列表：
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In [24]:
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```py
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a.tolist()
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```
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Out[24]:
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```py
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[[0, 1], [2, 3], [4, 5], [6, 7]]
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```
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转化为字符串：
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In [25]:
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```py
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a.tostring()
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```
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Out[25]:
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```py
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'\x00\x00\x00\x00\x01\x00\x00\x00\x02\x00\x00\x00\x03\x00\x00\x00\x04\x00\x00\x00\x05\x00\x00\x00\x06\x00\x00\x00\x07\x00\x00\x00'
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```
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改变数组元素类型：
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In [26]:
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```py
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a.astype(float)
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```
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Out[26]:
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```py
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array([[ 0., 1.],
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[ 2., 3.],
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[ 4., 5.],
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[ 6., 7.]])
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```
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In [27]:
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```py
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b = a.copy()
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b.byteswap(False)
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```
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Out[27]:
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```py
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array([[ 0, 16777216],
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[ 33554432, 50331648],
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[ 67108864, 83886080],
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[100663296, 117440512]])
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```
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将它看成16位整数：
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In [28]:
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```py
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a.view(dtype=int16)
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```
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Out[28]:
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```py
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array([[0, 0, 1, 0],
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[2, 0, 3, 0],
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[4, 0, 5, 0],
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[6, 0, 7, 0]], dtype=int16)
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```
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## 复数
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实部：
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In [29]:
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```py
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b = array([1+2j, 3+4j, 5+6j])
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b.real
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```
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Out[29]:
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```py
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array([ 1., 3., 5.])
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```
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虚部：
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In [30]:
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```py
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b.imag
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```
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Out[30]:
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```py
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array([ 2., 4., 6.])
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```
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共轭：
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In [31]:
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```py
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b.conj()
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```
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Out[31]:
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```py
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array([ 1.-2.j, 3.-4.j, 5.-6.j])
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```
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In [32]:
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```py
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b.conjugate()
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```
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Out[32]:
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```py
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array([ 1.-2.j, 3.-4.j, 5.-6.j])
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```
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## 保存
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保存成文本：
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In [33]:
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```py
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a.dump("file.txt")
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```
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字符串：
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In [34]:
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```py
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a.dumps()
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```
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Out[34]:
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```py
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'\x80\x02cnumpy.core.multiarray\n_reconstruct\nq\x01cnumpy\nndarray\nq\x02K\x00\x85U\x01b\x87Rq\x03(K\x01\x8a\x01\x04\x8a\x01\x02\x86cnumpy\ndtype\nq\x04U\x02i4K\x00K\x01\x87Rq\x05(K\x03U\x01<NNNJ\xff\xff\xff\xffJ\xff\xff\xff\xffK\x00tb\x89U \x00\x00\x00\x00\x01\x00\x00\x00\x02\x00\x00\x00\x03\x00\x00\x00\x04\x00\x00\x00\x05\x00\x00\x00\x06\x00\x00\x00\x07\x00\x00\x00tb.'
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```
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写入文件：
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In [35]:
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```py
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a.tofile('foo.csv', sep=',', format="%s")
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```
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## 查找排序
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非零元素的索引：
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In [36]:
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|
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```py
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a.nonzero()
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```
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Out[36]:
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```py
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(array([0, 1, 1, 2, 2, 3, 3], dtype=int64),
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array([1, 0, 1, 0, 1, 0, 1], dtype=int64))
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```
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排序：
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In [37]:
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```py
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b = array([3,2,7,4,1])
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b.sort()
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b
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```
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Out[37]:
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```py
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array([1, 2, 3, 4, 7])
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```
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排序的索引位置：
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In [38]:
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|
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```py
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b = array([2,3,1])
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b.argsort(axis=-1)
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```
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Out[38]:
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```py
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array([2, 0, 1], dtype=int64)
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```
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将 `b` 插入 `a` 中的索引，使得 `a` 保持有序：
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|
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In [39]:
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|
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```py
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a = array([1,3,4,6])
|
||
b = array([0,2,5])
|
||
a.searchsorted(b)
|
||
|
||
```
|
||
|
||
Out[39]:
|
||
|
||
```py
|
||
array([0, 1, 3], dtype=int64)
|
||
```
|
||
|
||
## 元素数学操作
|
||
|
||
限制在一定范围：
|
||
|
||
In [40]:
|
||
|
||
```py
|
||
a = array([[4,1,3],[2,1,5]])
|
||
a.clip(0,2)
|
||
|
||
```
|
||
|
||
Out[40]:
|
||
|
||
```py
|
||
array([[2, 1, 2],
|
||
[2, 1, 2]])
|
||
```
|
||
|
||
近似：
|
||
|
||
In [41]:
|
||
|
||
```py
|
||
a = array([1.344, 2.449, 2.558])
|
||
a.round(decimals=2)
|
||
|
||
```
|
||
|
||
Out[41]:
|
||
|
||
```py
|
||
array([ 1.34, 2.45, 2.56])
|
||
```
|
||
|
||
累加和：
|
||
|
||
In [42]:
|
||
|
||
```py
|
||
a = array([[4,1,3],[2,1,5]])
|
||
a.cumsum(axis=None)
|
||
|
||
```
|
||
|
||
Out[42]:
|
||
|
||
```py
|
||
array([ 4, 5, 8, 10, 11, 16])
|
||
```
|
||
|
||
累乘积：
|
||
|
||
In [43]:
|
||
|
||
```py
|
||
a.cumprod(axis=None)
|
||
|
||
```
|
||
|
||
Out[43]:
|
||
|
||
```py
|
||
array([ 4, 4, 12, 24, 24, 120])
|
||
```
|
||
|
||
## 约简操作
|
||
|
||
求和：
|
||
|
||
In [44]:
|
||
|
||
```py
|
||
a = array([[4,1,3],[2,1,5]])
|
||
a.sum(axis=None)
|
||
|
||
```
|
||
|
||
Out[44]:
|
||
|
||
```py
|
||
16
|
||
```
|
||
|
||
求积：
|
||
|
||
In [45]:
|
||
|
||
```py
|
||
a.prod(axis=None)
|
||
|
||
```
|
||
|
||
Out[45]:
|
||
|
||
```py
|
||
120
|
||
```
|
||
|
||
最小值：
|
||
|
||
In [46]:
|
||
|
||
```py
|
||
a.min(axis=None)
|
||
|
||
```
|
||
|
||
Out[46]:
|
||
|
||
```py
|
||
1
|
||
```
|
||
|
||
最大值：
|
||
|
||
In [47]:
|
||
|
||
```py
|
||
a.max(axis=None)
|
||
|
||
```
|
||
|
||
Out[47]:
|
||
|
||
```py
|
||
5
|
||
```
|
||
|
||
最小值索引：
|
||
|
||
In [48]:
|
||
|
||
```py
|
||
a.argmin(axis=None)
|
||
|
||
```
|
||
|
||
Out[48]:
|
||
|
||
```py
|
||
1
|
||
```
|
||
|
||
最大值索引：
|
||
|
||
In [49]:
|
||
|
||
```py
|
||
a.argmax(axis=None)
|
||
|
||
```
|
||
|
||
Out[49]:
|
||
|
||
```py
|
||
5
|
||
```
|
||
|
||
最大间隔：
|
||
|
||
In [50]:
|
||
|
||
```py
|
||
a.ptp(axis=None)
|
||
|
||
```
|
||
|
||
Out[50]:
|
||
|
||
```py
|
||
4
|
||
```
|
||
|
||
均值：
|
||
|
||
In [51]:
|
||
|
||
```py
|
||
a.mean(axis=None)
|
||
|
||
```
|
||
|
||
Out[51]:
|
||
|
||
```py
|
||
2.6666666666666665
|
||
```
|
||
|
||
标准差：
|
||
|
||
In [52]:
|
||
|
||
```py
|
||
a.std(axis=None)
|
||
|
||
```
|
||
|
||
Out[52]:
|
||
|
||
```py
|
||
1.49071198499986
|
||
```
|
||
|
||
方差：
|
||
|
||
In [53]:
|
||
|
||
```py
|
||
a.var(axis=None)
|
||
|
||
```
|
||
|
||
Out[53]:
|
||
|
||
```py
|
||
2.2222222222222228
|
||
```
|
||
|
||
是否有非零元素：
|
||
|
||
In [54]:
|
||
|
||
```py
|
||
a.any(axis=None)
|
||
|
||
```
|
||
|
||
Out[54]:
|
||
|
||
```py
|
||
True
|
||
```
|
||
|
||
是否全部非零：
|
||
|
||
In [55]:
|
||
|
||
```py
|
||
a.all()
|
||
|
||
```
|
||
|
||
Out[55]:
|
||
|
||
```py
|
||
True
|
||
```
|
||
|
||
删除生成的文件：
|
||
|
||
In [56]:
|
||
|
||
```py
|
||
import os
|
||
os.remove('foo.csv')
|
||
os.remove('file.txt')
|
||
|
||
``` |