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[MNN:Sync] Sync Internal 2.1.0
2022-08-31 20:11:16 +08:00
# Python 各模块用法
## 概览
MNN在C++的基础上，增加了Python扩展。扩展单元包括两个部分：
- MNN：负责推理，训练，图像处理和数值计算
- MNNTools：对MNN的部分工具进行封装，包括：mnn，mnnconvert和mnnquant
## MNN模块
MNN中的模块信息如下：
- [MNN](../pymnn/MNN.md)
- [expr](../pymnn/expr.md)
- [nn](../pymnn/nn.md)
- [loss](../pymnn/loss.md)
- [compress](../pymnn/compress.md)
- [data](../pymnn/data.md)
- [optim](../pymnn/optim.md)
- [cv](../pymnn/cv.md)
- [numpy](../pymnn/numpy.md)
- [linalg](../pymnn/linalg.md)
- [random](../pymnn/random.md)
### MNN
MNN模块是对[Session API](session.md)的Python封装。
同时对图像处理进行了封装，封装了ImageProcess和Matri相关的所有数据结构与函数。
### expr
expr模块是对[Expr API](expr.md)的Python封装。
### nn
nn模块是对[Module API](module.md)的Python封装。
### data
data模块是对[Dataset]的Python封装。
### optim
optim模块是对[Optimizer]的Python封装。
### cv
cv模块提供了与OpenCV相似的接口函数，具备基础的图像处理能力，目前支持的cv函数60个。
#### 图像编解码
| 函数名 | 功能 |
| --- | --- |
| [haveImageReader](../pymnn/cv.html#haveimagereader-filename) | 是否可读（解码） |
| [haveImageWriter](../pymnn/cv.html#haveimagewriter-filename) | 是否可写（编码） |
| [imdecode](../pymnn/cv.html#imdecode-buf-flag) | 从内存解码为Mat |
| [imencode](../pymnn/cv.html#imencode-ext-img-params) | 编码Mat到内存中 |
| [imread](../pymnn/cv.html#imread-filename-flag) | 读图片 |
| [imwrite](../pymnn/cv.html#imwrite-filename-img-params) | 写图片 |
#### 图像滤波
| 函数名 | 功能 |
| --- | --- |
| [blur](../pymnn/cv.html#blur-src-ksize-bordertype) | 均值滤波，平滑模糊 |
| [boxFilter](../pymnn/cv.html#boxfilter-src-ddepth-ksize-normalize-bordertype) | 盒子滤波， |
| [dilate](../pymnn/cv.html#dilate-src-kernel-iterations-bordertype) | 膨胀 |
| [filter2D](../pymnn/cv.html#filter2d-src-ddepth-kernel-delta-bordertype) | 2d卷积 |
| [GaussianBlur](../pymnn/cv.html#gaussianblur-src-ksize-sigmax-sigmay-bordertype) | 高斯模糊 |
| [getDerivKernels](../pymnn/cv.html#getderivkernels-dx-dy-ksize-normalize) | 求导数，实际为Sobel/Scharr |
| [getGaborKernel](../pymnn/cv.html#getgaborkernel-ksize-sigma-theta-lambd-gamma-psi) | 获取Gabor核 |
| [getGaussianKernel](../pymnn/cv.html#getgaussiankernel-ksize-sigma) | 获得高斯核 |
| [getStructuringElement](../pymnn/cv.html#getstructuringelement-shape-ksize) | 获取结构化元素用于形态学操作 |
| [Laplacian](../pymnn/cv.html#laplacian-src-ddepth-ksize-scale-delta-bordertype) | 边缘检测滤波 |
| [pyrDown](../pymnn/cv.html#pyrdown-src-dstsize-bordertype) | 高斯平滑+下采样 |
| [pyrUp](../pymnn/cv.html#pyrup-src-dstsize-bordertype) | 上采样+高斯平滑 |
| [Scharr](../pymnn/cv.html#scharr-src-ddepth-dx-dy-scale-delta-bordertype) | 边缘检测滤波 |
| [sepFilter2D](../pymnn/cv.html#sepfilter2d-src-ddepth-kx-ky-delta-bordertype) | 2个一维kernel做滤波 |
| [Sobel](../pymnn/cv.html#sobel-src-ddepth-dx-dy-ksize-scale-delta-bordertype) | 边缘检测滤波 |
| [spatialGradient](../pymnn/cv.html#spatialgradient-src-ksize-bordertype) | 梯度，实际为Sobel |
| [sqrBoxFilter](../pymnn/cv.html#sqrboxfilter-src-ddepth-ksize-normalize-bordertype) | 平方后滤波 |
#### 图像形变
| 函数名 | 功能 |
| --- | --- |
| [getAffineTransform](../pymnn/cv.html#getaffinetransform-src-dst) | 仿射变换 |
| [getPerspectiveTransform](../pymnn/cv.html#getperspectivetransform-src-dst) | 透视变换 |
| [getRectSubPix](../pymnn/cv.html#getrectsubpix-image-patchsize-center) | 截取矩形区域 |
| [getRotationMatrix2D](../pymnn/cv.html#getrotationmatrix2d-center-angle-scale) | 旋转矩阵 |
| [invertAffineTransform](../pymnn/cv.html#invertaffinetransform-m) | 仿射变换矩阵求逆 |
| [resize](../pymnn/cv.html#resize-src-dsize-fx-fy-interpolation-code-mean-norm) | 图片放缩 |
| [warpAffine](../pymnn/cv.html#warpaffine-src-m-dsize-flag-bordermode-bordervalue-code-mean-norm) | 仿射变换 |
| [warpPerspective](../pymnn/cv.html#warpperspective-src-m-dsize-flag-bordermode-bordervalue) | 透视变换 |
#### 图像转换
| 函数名 | 功能 |
| --- | --- |
| [blendLinear](../pymnn/cv.html#blendlinear-src1-src2-weight1-weight2) | 线性混合2个图像 |
| [threshold](../pymnn/cv.html#threshold-src-thresh-maxval-type) | 逐像素阈值化 |
#### 绘画函数
| 函数名 | 功能 |
| --- | --- |
| [arrowedLine](../pymnn/cv.html#arrowedline-img-pt1-pt2-color-thickness-linetype-shift-tiplength) | 画箭头 |
| [circle](../pymnn/cv.html#circle-img-center-radius-color-thickness-linetype-shift) | 画圆 |
| [drawContours](../pymnn/cv.html#drawcontours-img-contours-contouridx-color-thickness-linetype) | 画轮廓 |
| [fillPoly](../pymnn/cv.html#fillpoly-img-contours-color-linetype-shift-offset) | 填充多边形 |
| [line](../pymnn/cv.html#line-img-pt1-pt2-color-thickness-linetype-shift) | 画线段 |
| [rectangle](../pymnn/cv.html#rectangle-src-pt1-pt2-color-thickness-linetype-shift) | 画正方向 |
#### 色彩空间转换
| 函数名 | 功能 |
| --- | --- |
| [cvtColor](../pymnn/cv.html#cvtcolor-src-code-dstcn) | 颜色空间转换 |
| [cvtColorTwoPlane](../pymnn/cv.html#cvtcolortwoplane-src1-src2-code) | YUV420到RGB的转换 |
#### 结构函数
| 函数名 | 功能 |
| --- | --- |
| [findContours](../pymnn/cv.html#findcontours-image-mode-method-offset) | 轮廓检测 |
| [contourArea](../pymnn/cv.html#contourarea-points-oriented) | 计算轮廓的面积 |
| [convexHull](../pymnn/cv.html#convexhull-points-clockwise-returnpoints) | 计算点集的凸包 |
| [minAreaRect](../pymnn/cv.html#minarearect-points) | 最小外接矩形 |
| [boundingRect](../pymnn/cv.html#boundingrect-points) | 计算点集的最小外接矩形 |
| [connectedComponentsWithStats](../pymnn/cv.html#connectedcomponentswithstats-image-connectivity) | 计算图像的连通域 |
| [boxPoints](../pymnn/cv.html#boxpoints-box) | 计算矩形的四个顶点坐标 |
#### 直方图
| 函数名 | 功能 |
| --- | --- |
| [calcHist](../pymnn/cv.html#calchist-imgs-channels-mask-histsize-ranges-accumulate) | 计算直方图 |
#### 3D
| 函数名 | 功能 |
| --- | --- |
| [Rodrigues](../pymnn/cv.html#rodrigues-src) | 旋转矩阵转换为旋转向量 |
| [solvePnP](../pymnn/cv.html#solvepnp-objectpoints-imagepoints-cameramatrix-distcoeffs-flags) | 计算2d到3d的映射 |
#### 数组操作函数
| 函数名 | 功能 |
| --- | --- |
| [copyTo](../pymnn/cv.html#copyto-src-mask-dst) | 带mask的拷贝 |
| [bitwise_and](../pymnn/cv.html#bitwise-and-src1-src2-dst-mask) | 带mask按位与 |
| [bitwise_or](../pymnn/cv.html#bitwise-or-src1-src2-dst-mask) | 带mask按位或 |
| [bitwise_xor](../pymnn/cv.html#bitwise-xor-src1-src2-dst-mask) | 带mask按位异或 |
| [hconcat](../pymnn/cv.html#hconcat-src) | 水平方向拼接 |
| [vconcat](../pymnn/cv.html#vconcat-src) | 垂直方向拼接 |
| [mean](../pymnn/cv.html#mean-src-mask) | 求均值 |
| [flip](../pymnn/cv.html#flip-src-flipcode) | 翻转 |
| [rotate](../pymnn/cv.html#rotate-src-rotatemode) | 旋转 |
### numpy
numpy函数170个，函数列表如下:
#### 数组创建
| 函数名 | 功能 |
| --- | --- |
| [empty](../numpy.html#empty-shape-dtype-float32-order-c) | 空数组 |
| [empty_like](https://numpy.org/doc/stable/reference/generated/numpy.empty_like.html#numpy.empty_like) | 空数组like |
| [eye](https://numpy.org/doc/stable/reference/generated/numpy.eye.html#numpy.eye) | 对角线2d数组 |
| [identity](https://numpy.org/doc/stable/reference/generated/numpy.identity.html#numpy.identity) | 对角线2d数组 |
| [ones](https://numpy.org/doc/stable/reference/generated/numpy.ones.html#numpy.ones) | 全1数组 |
| [ones_like](https://numpy.org/doc/stable/reference/generated/numpy.ones_like.html#numpy.ones_like) | 全1数组like |
| [zeros](https://numpy.org/doc/stable/reference/generated/numpy.zeros.html#numpy.zeros) | 全0数组 |
| [zeros_like](https://numpy.org/doc/stable/reference/generated/numpy.zeros_like.html#numpy.zeros_like) | 全0数组like |
| [full](https://numpy.org/doc/stable/reference/generated/numpy.full.html#numpy.full) | 填充 |
| [full_like](https://numpy.org/doc/stable/reference/generated/numpy.full_like.html#numpy.full_like) | 填充like |
| [array](https://numpy.org/doc/stable/reference/generated/numpy.array.html#numpy.array) | 创建数组 |
| [asarray](https://numpy.org/doc/stable/reference/generated/numpy.asarray.html#numpy.asarray) | 创建数组 |
| [asanyarray](https://numpy.org/doc/stable/reference/generated/numpy.asanyarray.html#numpy.asanyarray) | 创建数组 |
| [ascontiguousarray](https://numpy.org/doc/stable/reference/generated/numpy.ascontiguousarray.html#numpy.ascontiguousarray) | 创建数组 |
| [asmatrix](https://numpy.org/doc/stable/reference/generated/numpy.asmatrix.html#numpy.asmatrix) | 创建2d数组 |
| [copy](https://numpy.org/doc/stable/reference/generated/numpy.copy.html#numpy.copy) | 拷贝数组 |
| [arange](https://numpy.org/doc/stable/reference/generated/numpy.arange.html#numpy.arange) | 范围创建 |
| [linspace](https://numpy.org/doc/stable/reference/generated/numpy.linspace.html#numpy.linspace) | 区间创建 |
| [logspace](https://numpy.org/doc/stable/reference/generated/numpy.logspace.html#numpy.logspace) | log区间创建 |
| [geomspace](https://numpy.org/doc/stable/reference/generated/numpy.geomspace.html#numpy.geomspace) | log区间创建 |
| [meshgrid](https://numpy.org/doc/stable/reference/generated/numpy.meshgrid.html#numpy.meshgrid) | 坐标矩阵 |
| [mat](https://numpy.org/doc/stable/reference/generated/numpy.mat.html#numpy.mat) | 矩阵 |
#### 数组操作
| 函数名 | 功能 |
| --- | --- |
| [copyto](https://numpy.org/doc/stable/reference/generated/numpy.copyto.html#numpy.copyto) | 拷贝至 |
| [shape](https://numpy.org/doc/stable/reference/generated/numpy.shape.html#numpy.shape) | 获取形状 |
| [reshape](https://numpy.org/doc/stable/reference/generated/numpy.reshape.html#numpy.reshape) | 改变形状 |
| [ravel](https://numpy.org/doc/stable/reference/generated/numpy.ravel.html#numpy.ravel) | 拉平 |
| [flat](https://numpy.org/doc/stable/reference/generated/numpy.ndarray.flat.html#numpy.ndarray.flat) | 拉平 |
| [flatten](https://numpy.org/doc/stable/reference/generated/numpy.ndarray.flatten.html#numpy.ndarray.flatten) | 拉平 |
| [moveaxis](https://numpy.org/doc/stable/reference/generated/numpy.moveaxis.html#numpy.moveaxis) | 移动维度 |
| [rollaxis](https://numpy.org/doc/stable/reference/generated/numpy.rollaxis.html#numpy.rollaxis) | 轮转维度 |
| [swapaxes](https://numpy.org/doc/stable/reference/generated/numpy.swapaxes.html#numpy.swapaxes) | 交换维度 |
| [T](https://numpy.org/doc/stable/reference/generated/numpy.ndarray.T.html#numpy.ndarray.T) | 转置 |
| [transpose](https://numpy.org/doc/stable/reference/generated/numpy.transpose.html#numpy.transpose) | 转置 |
| [atleast_1d](https://numpy.org/doc/stable/reference/generated/numpy.atleast_1d.html#numpy.atleast_1d) | 至少1维 |
| [atleast_2d](https://numpy.org/doc/stable/reference/generated/numpy.atleast_2d.html#numpy.atleast_2d) | 至少2维 |
| [atleast_3d](https://numpy.org/doc/stable/reference/generated/numpy.atleast_3d.html#numpy.atleast_3d) | 至少3维 |
| [broadcast_to](https://numpy.org/doc/stable/reference/generated/numpy.broadcast_to.html#numpy.broadcast_to) | 广播 |
| [broadcast_arrays](https://numpy.org/doc/stable/reference/generated/numpy.broadcast_arrays.html#numpy.broadcast_arrays) | 数组广播 |
| [expand_dims](https://numpy.org/doc/stable/reference/generated/numpy.expand_dims.html#numpy.expand_dims) | 增加维度 |
| [squeeze](https://numpy.org/doc/stable/reference/generated/numpy.squeeze.html#numpy.squeeze) | 压缩1维度 |
| [asfarray](https://numpy.org/doc/stable/reference/generated/numpy.asfarray.html#numpy.asfarray) | 转浮点 |
| [asscalar](https://numpy.org/doc/stable/reference/generated/numpy.asscalar.html#numpy.asscalar) | 转标量 |
| [concatenate](https://numpy.org/doc/stable/reference/generated/numpy.concatenate.html#numpy.concatenate) | 连接 |
| [stack](https://numpy.org/doc/stable/reference/generated/numpy.stack.html#numpy.stack) | 连接 |
| [vstack](https://numpy.org/doc/stable/reference/generated/numpy.vstack.html#numpy.vstack) | 垂直连接 |
| [hstack](https://numpy.org/doc/stable/reference/generated/numpy.hstack.html#numpy.hstack) | 水平连接 |
| [dstack](https://numpy.org/doc/stable/reference/generated/numpy.dstack.html#numpy.dstack) | 深度连接 |
| [column_stack](https://numpy.org/doc/stable/reference/generated/numpy.column_stack.html#numpy.column_stack) | 列连接 |
| [row_stack](https://numpy.org/doc/stable/reference/generated/numpy.row_stack.html#numpy.row_stack) | 行连接 |
| [split](https://numpy.org/doc/stable/reference/generated/numpy.split.html#numpy.split) | 切分 |
| [array_split](https://numpy.org/doc/stable/reference/generated/numpy.array_split.html#numpy.array_split) | 数组切分 |
| [dsplit](https://numpy.org/doc/stable/reference/generated/numpy.dsplit.html#numpy.dsplit) | 深度切分 |
| [hsplit](https://numpy.org/doc/stable/reference/generated/numpy.hsplit.html#numpy.hsplit) | 水平切分 |
| [vsplit](https://numpy.org/doc/stable/reference/generated/numpy.vsplit.html#numpy.vsplit) | 垂直切分 |
| [tile](https://numpy.org/doc/stable/reference/generated/numpy.tile.html#numpy.tile) | 重复堆叠 |
| [repeat](https://numpy.org/doc/stable/reference/generated/numpy.repeat.html#numpy.repeat) | 重复 |
| [reshape](https://numpy.org/doc/stable/reference/generated/numpy.reshape.html#numpy.reshape) | 变形 |
#### 坐标操作
| 函数名 | 功能 |
| --- | --- |
| [nonzero](https://numpy.org/doc/stable/reference/generated/numpy.nonzero.html#numpy.nonzero) | 非0元素坐标 |
| [where](https://numpy.org/doc/stable/reference/generated/numpy.where.html#numpy.where) | 条件选取 |
| [unravel_index](https://numpy.org/doc/stable/reference/generated/numpy.unravel_index.html#numpy.unravel_index) | 反拉平坐标 |
#### 线性代数
| 函数名 | 功能 |
| --- | --- |
| [dot](https://numpy.org/doc/stable/reference/generated/numpy.dot.html#numpy.dot) | 点乘 |
| [vdot](https://numpy.org/doc/stable/reference/generated/numpy.vdot.html#numpy.vdot) | 点乘 |
| [inner](https://numpy.org/doc/stable/reference/generated/numpy.inner.html#numpy.inner) | 内积 |
| [matmul](https://numpy.org/doc/stable/reference/generated/numpy.matmul.html#numpy.matmul) | 矩阵乘 |
#### 逻辑函数
| 函数名 | 功能 |
| --- | --- |
| [all](https://numpy.org/doc/stable/reference/generated/numpy.all.html#numpy.all) | 全部非0 |
| [any](https://numpy.org/doc/stable/reference/generated/numpy.any.html#numpy.any) | 任意非0 |
| [logical_and](https://numpy.org/doc/stable/reference/generated/numpy.logical_and.html#numpy.logical_and) | 与 |
| [logical_or](https://numpy.org/doc/stable/reference/generated/numpy.logical_or.html#numpy.logical_or) | 或 |
| [logical_not](https://numpy.org/doc/stable/reference/generated/numpy.logical_not.html#numpy.logical_not) | 否 |
| [logical_xor](https://numpy.org/doc/stable/reference/generated/numpy.logical_xor.html#numpy.logical_xor) | 异或 |
| [array_equal](https://numpy.org/doc/stable/reference/generated/numpy.array_equal.html#numpy.array_equal) | 相等 |
| [array_equiv](https://numpy.org/doc/stable/reference/generated/numpy.array_equiv.html#numpy.array_equiv) | 相等 |
| [greater](https://numpy.org/doc/stable/reference/generated/numpy.greater.html#numpy.greater) | 大于 |
| [greater_equal](https://numpy.org/doc/stable/reference/generated/numpy.greater_equal.html#numpy.greater_equal) | 大于等于 |
| [less](https://numpy.org/doc/stable/reference/generated/numpy.less.html#numpy.less) | 小于 |
| [less_equal](https://numpy.org/doc/stable/reference/generated/numpy.less_equal.html#numpy.less_equal) | 小于等于 |
| [equal](https://numpy.org/doc/stable/reference/generated/numpy.equal.html#numpy.equal) | 等于 |
| [not_equal](https://numpy.org/doc/stable/reference/generated/numpy.not_equal.html#numpy.not_equal) | 不等 |
#### 数学函数
| API | 功能 |
| --- | --- |
| [sin](https://numpy.org/doc/stable/reference/generated/numpy.sin.html#numpy.sin) | 正弦 |
| [cos](https://numpy.org/doc/stable/reference/generated/numpy.cos.html#numpy.cos) | 余弦 |
| [tan](https://numpy.org/doc/stable/reference/generated/numpy.tan.html#numpy.tan) | 正切 |
| [arcsin](https://numpy.org/doc/stable/reference/generated/numpy.arcsin.html#numpy.arcsin) | 反正弦 |
| [arccos](https://numpy.org/doc/stable/reference/generated/numpy.arccos.html#numpy.arccos) | 反余弦 |
| [arctan](https://numpy.org/doc/stable/reference/generated/numpy.arctan.html#numpy.arctan) | 反正切 |
| [hypot](https://numpy.org/doc/stable/reference/generated/numpy.hypot.html#numpy.hypot) |
|
| [arctan2](https://numpy.org/doc/stable/reference/generated/numpy.arctan2.html#numpy.arctan2) |
|
| [sinh](https://numpy.org/doc/stable/reference/generated/numpy.sinh.html#numpy.sinh) |
|
| [cosh](https://numpy.org/doc/stable/reference/generated/numpy.cosh.html#numpy.cosh) |
|
| [tanh](https://numpy.org/doc/stable/reference/generated/numpy.tanh.html#numpy.tanh) |
|
| [arcsinh](https://numpy.org/doc/stable/reference/generated/numpy.arcsinh.html#numpy.arcsinh) |
|
| [arccosh](https://numpy.org/doc/stable/reference/generated/numpy.arccosh.html#numpy.arccosh) |
|
| [arctanh](https://numpy.org/doc/stable/reference/generated/numpy.arctanh.html#numpy.arctanh) |
|
| [around](https://numpy.org/doc/stable/reference/generated/numpy.around.html#numpy.around) |
|
| [round_](https://numpy.org/doc/stable/reference/generated/numpy.round_.html#numpy.round_) |
|
| [rint](https://numpy.org/doc/stable/reference/generated/numpy.rint.html#numpy.rint) |
|
| [floor](https://numpy.org/doc/stable/reference/generated/numpy.floor.html#numpy.floor) |
|
| [ceil](https://numpy.org/doc/stable/reference/generated/numpy.ceil.html#numpy.ceil) |
|
| [trunc](https://numpy.org/doc/stable/reference/generated/numpy.trunc.html#numpy.trunc) |
|
| [prod](https://numpy.org/doc/stable/reference/generated/numpy.prod.html#numpy.prod) | 积 |
| [sum](https://numpy.org/doc/stable/reference/generated/numpy.sum.html#numpy.sum) | 和 |
| [nanprod](https://numpy.org/doc/stable/reference/generated/numpy.nanprod.html#numpy.nanprod) | 积 |
| [nansum](https://numpy.org/doc/stable/reference/generated/numpy.nansum.html#numpy.nansum) | 和 |
| [exp](https://numpy.org/doc/stable/reference/generated/numpy.exp.html#numpy.exp) | e指数 |
| [expm1](https://numpy.org/doc/stable/reference/generated/numpy.expm1.html#numpy.expm1) | e指数-1 |
| [exp2](https://numpy.org/doc/stable/reference/generated/numpy.exp2.html#numpy.exp2) | 2指数 |
| [log](https://numpy.org/doc/stable/reference/generated/numpy.log.html#numpy.log) | 对数 |
| [log10](https://numpy.org/doc/stable/reference/generated/numpy.log10.html#numpy.log10) | 10对数 |
| [log2](https://numpy.org/doc/stable/reference/generated/numpy.log2.html#numpy.log2) | 2对数 |
| [log1p](https://numpy.org/doc/stable/reference/generated/numpy.log1p.html#numpy.log1p) | x+1对数 |
| [logaddexp](https://numpy.org/doc/stable/reference/generated/numpy.logaddexp.html#numpy.logaddexp) | exp对数 |
| [logaddexp2](https://numpy.org/doc/stable/reference/generated/numpy.logaddexp2.html#numpy.logaddexp2) | 2指数对数 |
| [sinc](https://numpy.org/doc/stable/reference/generated/numpy.sinc.html#numpy.sinc) | |
| [signbit](https://numpy.org/doc/stable/reference/generated/numpy.signbit.html#numpy.signbit) | |
| [copysign](https://numpy.org/doc/stable/reference/generated/numpy.copysign.html#numpy.copysign) | |
| [frexp](https://numpy.org/doc/stable/reference/generated/numpy.frexp.html#numpy.frexp) | |
| [ldexp](https://numpy.org/doc/stable/reference/generated/numpy.ldexp.html#numpy.ldexp) | |
| [add](https://numpy.org/doc/stable/reference/generated/numpy.add.html#numpy.add) | 加 |
| [reciprocal](https://numpy.org/doc/stable/reference/generated/numpy.reciprocal.html#numpy.reciprocal) | 倒数 |
| [positive](https://numpy.org/doc/stable/reference/generated/numpy.positive.html#numpy.positive) | 取正 |
| [negative](https://numpy.org/doc/stable/reference/generated/numpy.negative.html#numpy.negative) | 取负 |
| [multiply](https://numpy.org/doc/stable/reference/generated/numpy.multiply.html#numpy.multiply) | 乘 |
| [divide](https://numpy.org/doc/stable/reference/generated/numpy.divide.html#numpy.divide) | 除 |
| [power](https://numpy.org/doc/stable/reference/generated/numpy.power.html#numpy.power) | 指数 |
| [subtract](https://numpy.org/doc/stable/reference/generated/numpy.subtract.html#numpy.subtract) | 减 |
| [true_divide](https://numpy.org/doc/stable/reference/generated/numpy.true_divide.html#numpy.true_divide) | 除 |
| [floor_divide](https://numpy.org/doc/stable/reference/generated/numpy.floor_divide.html#numpy.floor_divide) | 除 |
| [float_power](https://numpy.org/doc/stable/reference/generated/numpy.float_power.html#numpy.float_power) | 指数 |
| [fmod](https://numpy.org/doc/stable/reference/generated/numpy.fmod.html#numpy.fmod) | 模 |
| [mod](https://numpy.org/doc/stable/reference/generated/numpy.mod.html#numpy.mod) | 模 |
| [modf](https://numpy.org/doc/stable/reference/generated/numpy.modf.html#numpy.modf) | 模 |
| [remainder](https://numpy.org/doc/stable/reference/generated/numpy.remainder.html#numpy.remainder) | 余 |
| [divmod](https://numpy.org/doc/stable/reference/generated/numpy.divmod.html#numpy.divmod) | 除，余 |
| [convolve](https://numpy.org/doc/stable/reference/generated/numpy.convolve.html#numpy.convolve) | 卷积 |
| [clip](https://numpy.org/doc/stable/reference/generated/numpy.clip.html#numpy.clip) | 缩小范围 |
| [sqrt](https://numpy.org/doc/stable/reference/generated/numpy.sqrt.html#numpy.sqrt) | 平方根 |
| [cbrt](https://numpy.org/doc/stable/reference/generated/numpy.cbrt.html#numpy.cbrt) | 立方根 |
| [square](https://numpy.org/doc/stable/reference/generated/numpy.square.html#numpy.square) | 平方 |
| [absolute](https://numpy.org/doc/stable/reference/generated/numpy.absolute.html#numpy.absolute) | 绝对值 |
| [fabs](https://numpy.org/doc/stable/reference/generated/numpy.fabs.html#numpy.fabs) | 绝对值 |
| [sign](https://numpy.org/doc/stable/reference/generated/numpy.sign.html#numpy.sign) | 符号 |
| [maximum](https://numpy.org/doc/stable/reference/generated/numpy.maximum.html#numpy.maximum) | 取大 |
| [minimum](https://numpy.org/doc/stable/reference/generated/numpy.minimum.html#numpy.minimum) | 取小 |
| [fmax](https://numpy.org/doc/stable/reference/generated/numpy.fmax.html#numpy.fmax) | 取大 |
| [fmin](https://numpy.org/doc/stable/reference/generated/numpy.fmin.html#numpy.fmin) | 取小 |
#### 数组扩充
| 函数名 | 功能 |
| --- | --- |
| [pad](https://numpy.org/doc/stable/reference/generated/numpy.pad.html#numpy.pad) | 扩充 |
#### 随机采样
| 函数名 | 功能 |
| --- | --- |
| random | 随机数 |
| rand | 随机数 |
| randn | 随机数 |
| randint | 随机定点数 |
#### 排序，搜索，计数
| 函数名 | 功能 |
| --- | --- |
| [sort](https://numpy.org/doc/stable/reference/generated/numpy.sort.html#numpy.sort)，[lexsort](https://numpy.org/doc/stable/reference/generated/numpy.lexsort.html#numpy.lexsort)，[argsort](https://numpy.org/doc/stable/reference/generated/numpy.argsort.html#numpy.argsort) | 排序 |
| [argmax](https://numpy.org/doc/stable/reference/generated/numpy.argmax.html#numpy.argmax) | 最大值坐标 |
| [nanargmax](https://numpy.org/doc/stable/reference/generated/numpy.nanargmax.html#numpy.nanargmax) | 最大值坐标 |
| [argmin](https://numpy.org/doc/stable/reference/generated/numpy.argmin.html#numpy.argmin) | 最小值坐标 |
| [nanargmin](https://numpy.org/doc/stable/reference/generated/numpy.nanargmin.html#numpy.nanargmin) | 最小值坐标 |
| [argwhere](https://numpy.org/doc/stable/reference/generated/numpy.argwhere.html#numpy.argwhere) | 非0坐标 |
| [flatnonzero](https://numpy.org/doc/stable/reference/generated/numpy.flatnonzero.html#numpy.flatnonzero) | 非0元素 |
| [count_nonzero](https://numpy.org/doc/stable/reference/generated/numpy.count_nonzero.html#numpy.count_nonzero) | 非0总数 |
#### 统计
| 函数名 | 功能 |
| --- | --- |
| [amin](https://numpy.org/doc/stable/reference/generated/numpy.amin.html#numpy.amin) | 最小值 |
| [amax](https://numpy.org/doc/stable/reference/generated/numpy.amax.html#numpy.amax) | 最大值 |
| [nanmin](https://numpy.org/doc/stable/reference/generated/numpy.nanmin.html#numpy.nanmin) | 最小值 |
| [nanmax](https://numpy.org/doc/stable/reference/generated/numpy.nanmax.html#numpy.nanmax) | 最大值 |
| [ptp](https://numpy.org/doc/stable/reference/generated/numpy.ptp.html#numpy.ptp) | 范围 |
| [average](https://numpy.org/doc/stable/reference/generated/numpy.average.html#numpy.average) | 均值 |
| [mean](https://numpy.org/doc/stable/reference/generated/numpy.mean.html#numpy.mean) | 均值 |
| [std](https://numpy.org/doc/stable/reference/generated/numpy.std.html#numpy.std) | 标准差 |
| [var](https://numpy.org/doc/stable/reference/generated/numpy.var.html#numpy.var) | 方差 |
| [nanmean](https://numpy.org/doc/stable/reference/generated/numpy.nanmean.html#numpy.nanmean) | 均值 |
| [nanstd](https://numpy.org/doc/stable/reference/generated/numpy.nanstd.html#numpy.nanstd) | 标准差 |
| [nanvar](https://numpy.org/doc/stable/reference/generated/numpy.nanvar.html#numpy.nanvar) | 方差 |