NumPy manual contents¶
- NumPy用户指南
- NumPy参考
- 数组对象
- N维数组（
ndarray）- 构造数组
- numpy.ndarray
- numpy.ndarray.T
- numpy.ndarray.data
- numpy.ndarray.dtype
- numpy.ndarray.flags
- numpy.ndarray.flat
- numpy.ndarray.imag
- numpy.ndarray.real
- numpy.ndarray.size
- numpy.ndarray.itemsize
- numpy.ndarray.nbytes
- numpy.ndarray.ndim
- numpy.ndarray.shape
- numpy.ndarray.strides
- numpy.ndarray.ctypes
- numpy.ndarray.base
- numpy.ndarray.all
- numpy.ndarray.any
- numpy.ndarray.argmax
- numpy.ndarray.argmin
- numpy.ndarray.argpartition
- numpy.ndarray.argsort
- numpy.ndarray.astype
- numpy.ndarray.byteswap
- numpy.ndarray.choose
- numpy.ndarray.clip
- numpy.ndarray.compress
- numpy.ndarray.conj
- numpy.ndarray.conjugate
- numpy.ndarray.copy
- numpy.ndarray.cumprod
- numpy.ndarray.cumsum
- numpy.ndarray.diagonal
- numpy.ndarray.dot
- numpy.ndarray.dump
- numpy.ndarray.dumps
- numpy.ndarray.fill
- numpy.ndarray.flatten
- numpy.ndarray.getfield
- numpy.ndarray.item
- numpy.ndarray.itemset
- numpy.ndarray.max
- numpy.ndarray.mean
- numpy.ndarray.min
- numpy.ndarray.newbyteorder
- numpy.ndarray.nonzero
- numpy.ndarray.partition
- numpy.ndarray.prod
- numpy.ndarray.ptp
- numpy.ndarray.put
- numpy.ndarray.ravel
- numpy.ndarray.repeat
- numpy.ndarray.reshape
- numpy.ndarray.resize
- numpy.ndarray.round
- numpy.ndarray.searchsorted
- numpy.ndarray.setfield
- numpy.ndarray.setflags
- numpy.ndarray.sort
- numpy.ndarray.squeeze
- numpy.ndarray.std
- numpy.ndarray.sum
- numpy.ndarray.swapaxes
- numpy.ndarray.take
- numpy.ndarray.tobytes
- numpy.ndarray.tofile
- numpy.ndarray.tolist
- numpy.ndarray.tostring
- numpy.ndarray.trace
- numpy.ndarray.transpose
- numpy.ndarray.var
- numpy.ndarray.view
- numpy.ndarray
- 索引数组
- ndarray的内部存储器布局
- 数组属性
- 数组方法
- 数组转换
- numpy.ndarray.item
- numpy.ndarray.tolist
- numpy.ndarray.itemset
- numpy.ndarray.tostring
- numpy.ndarray.tobytes
- numpy.ndarray.tofile
- numpy.ndarray.dump
- numpy.ndarray.dumps
- numpy.ndarray.astype
- numpy.ndarray.byteswap
- numpy.ndarray.copy
- numpy.ndarray.view
- numpy.ndarray.getfield
- numpy.ndarray.setflags
- numpy.ndarray.fill
- 形状操作
- 项目选择和处理
- 计算
- numpy.ndarray.argmax
- numpy.ndarray.min
- numpy.ndarray.argmin
- numpy.ndarray.ptp
- numpy.ndarray.clip
- numpy.ndarray.conj
- numpy.ndarray.round
- numpy.ndarray.trace
- numpy.ndarray.sum
- numpy.ndarray.cumsum
- numpy.ndarray.mean
- numpy.ndarray.var
- numpy.ndarray.std
- numpy.ndarray.prod
- numpy.ndarray.cumprod
- numpy.ndarray.all
- numpy.ndarray.any
- 数组转换
- 算术，矩阵乘法和比较运算
- numpy.ndarray .__ lt __
- numpy.ndarray .__ le __
- numpy.ndarray .__ gt __
- numpy.ndarray .__ ge __
- numpy.ndarray .__ eq __
- numpy.ndarray .__ ne __
- numpy.ndarray .__ nonzero __
- numpy.ndarray .__ neg __
- numpy.ndarray .__ pos __
- numpy.ndarray .__ abs __
- numpy.ndarray .__ invert __
- numpy.ndarray .__ add __
- numpy.ndarray .__ sub __
- numpy.ndarray .__ mul __
- numpy.ndarray .__ div __
- numpy.ndarray .__ truediv __
- numpy.ndarray .__ floordiv __
- numpy.ndarray .__ mod __
- numpy.ndarray .__ divmod __
- numpy.ndarray .__ pow __
- numpy.ndarray .__ lshift __
- numpy.ndarray .__ rshift __
- numpy.ndarray .__and__
- numpy.ndarray .__or__
- numpy.ndarray .__ xor __
- numpy.ndarray .__ iadd __
- numpy.ndarray .__ isub __
- numpy.ndarray .__ imul __
- numpy.ndarray .__ idiv __
- numpy.ndarray .__ itruediv __
- numpy.ndarray .__ ifloordiv __
- numpy.ndarray .__ imod __
- numpy.ndarray .__ ipow __
- numpy.ndarray .__ ilshift __
- numpy.ndarray .__ irshift __
- numpy.ndarray .__ iand __
- numpy.ndarray .__ ior __
- numpy.ndarray .__ ixor __
- 特殊方法
- numpy.ndarray .__ copy __
- numpy.ndarray .__ deepcopy __
- numpy.ndarray .__ reduce __
- numpy.ndarray .__ setstate __
- numpy.ndarray .__ new __
- numpy.ndarray .__ array __
- numpy.ndarray .__ array_wrap __
- numpy.ndarray .__ len __
- numpy.ndarray .__ getitem __
- numpy.ndarray .__ setitem __
- numpy.ndarray .__含有__
- numpy.ndarray .__ int __
- numpy.ndarray .__ long __
- numpy.ndarray .__ float __
- numpy.ndarray .__ oct __
- numpy.ndarray .__ hex __
- numpy.ndarray .__ str __
- numpy.ndarray .__ repr __
- 构造数组
- Scalars
- 内置标量类型
- 属性
- numpy.generic.flags
- numpy.generic.shape
- numpy.generic.strides
- numpy.generic.ndim
- numpy.generic.data
- numpy.generic.size
- numpy.generic.itemsize
- numpy.generic.base
- numpy.generic.dtype
- numpy.generic.real
- numpy.generic.imag
- numpy.generic.flat
- numpy.generic.T
- numpy.generic .__ array_interface __
- numpy.generic .__ array_struct __
- numpy.generic .__ array_priority __
- numpy.generic .__ array_wrap __
- 索引
- 方法
- numpy.generic
- numpy.generic.T
- numpy.generic.base
- numpy.generic.data
- numpy.generic.dtype
- numpy.generic.flags
- numpy.generic.flat
- numpy.generic.imag
- numpy.generic.itemsize
- numpy.generic.nbytes
- numpy.generic.ndim
- numpy.generic.real
- numpy.generic.shape
- numpy.generic.size
- numpy.generic.strides
- numpy.generic.all
- numpy.generic.any
- numpy.generic.argmax
- numpy.generic.argmin
- numpy.generic.argsort
- numpy.generic.astype
- numpy.generic.byteswap
- numpy.generic.choose
- numpy.generic.clip
- numpy.generic.compress
- numpy.generic.conj
- numpy.generic.conjugate
- numpy.generic.copy
- numpy.generic.cumprod
- numpy.generic.cumsum
- numpy.generic.diagonal
- numpy.generic.dump
- numpy.generic.dumps
- numpy.generic.fill
- numpy.generic.flatten
- numpy.generic.getfield
- numpy.generic.item
- numpy.generic.itemset
- numpy.generic.max
- numpy.generic.mean
- numpy.generic.min
- numpy.generic.newbyteorder
- numpy.generic.nonzero
- numpy.generic.prod
- numpy.generic.ptp
- numpy.generic.put
- numpy.generic.ravel
- numpy.generic.repeat
- numpy.generic.reshape
- numpy.generic.resize
- numpy.generic.round
- numpy.generic.searchsorted
- numpy.generic.setfield
- numpy.generic.setflags
- numpy.generic.sort
- numpy.generic.squeeze
- numpy.generic.std
- numpy.generic.sum
- numpy.generic.swapaxes
- numpy.generic.take
- numpy.generic.tobytes
- numpy.generic.tofile
- numpy.generic.tolist
- numpy.generic.tostring
- numpy.generic.trace
- numpy.generic.transpose
- numpy.generic.var
- numpy.generic.view
- numpy.generic .__ array __
- numpy.generic .__ array_wrap __
- numpy.generic.squeeze
- numpy.generic.byteswap
- numpy.generic .__ reduce __
- numpy.generic .__ setstate __
- numpy.generic.setflags
- numpy.generic
- 定义新类型
- 数据类型对象（
dtype）- 指定和构造数据类型
dtype- 属性
- numpy.dtype.type
- numpy.dtype.kind
- numpy.dtype.char
- numpy.dtype.num
- numpy.dtype.str
- numpy.dtype.name
- numpy.dtype.itemsize
- numpy.dtype.byteorder
- numpy.dtype.fields
- numpy.dtype.names
- numpy.dtype.subdtype
- numpy.dtype.shape
- numpy.dtype.hasobject
- numpy.dtype.flags
- numpy.dtype.isbuiltin
- numpy.dtype.isnative
- numpy.dtype.descr
- numpy.dtype.alignment
- 方法
- 属性
- 索引
- 迭代数组
- 标准数组子类
- 特殊属性和方法
- 矩阵对象
- numpy.matrix.T
- numpy.matrix.H
- numpy.matrix.I
- numpy.matrix.A
- numpy.matrix
- numpy.matrix.A
- numpy.matrix.A1
- numpy.matrix.H
- numpy.matrix.I
- numpy.matrix.T
- numpy.matrix.base
- numpy.matrix.ctypes
- numpy.matrix.data
- numpy.matrix.dtype
- numpy.matrix.flags
- numpy.matrix.flat
- numpy.matrix.imag
- numpy.matrix.itemsize
- numpy.matrix.nbytes
- numpy.matrix.ndim
- numpy.matrix.real
- numpy.matrix.shape
- numpy.matrix.size
- numpy.matrix.strides
- numpy.matrix.all
- numpy.matrix.any
- numpy.matrix.argmax
- numpy.matrix.argmin
- numpy.matrix.argpartition
- numpy.matrix.argsort
- numpy.matrix.astype
- numpy.matrix.byteswap
- numpy.matrix.choose
- numpy.matrix.clip
- numpy.matrix.compress
- numpy.matrix.conj
- numpy.matrix.conjugate
- numpy.matrix.copy
- numpy.matrix.cumprod
- numpy.matrix.cumsum
- numpy.matrix.diagonal
- numpy.matrix.dot
- numpy.matrix.dump
- numpy.matrix.dumps
- numpy.matrix.fill
- numpy.matrix.flatten
- numpy.matrix.getA
- numpy.matrix.getA1
- numpy.matrix.getH
- numpy.matrix.getI
- numpy.matrix.getT
- numpy.matrix.getfield
- numpy.matrix.item
- numpy.matrix.itemset
- numpy.matrix.max
- numpy.matrix.mean
- numpy.matrix.min
- numpy.matrix.newbyteorder
- numpy.matrix.nonzero
- numpy.matrix.partition
- numpy.matrix.prod
- numpy.matrix.ptp
- numpy.matrix.put
- numpy.matrix.ravel
- numpy.matrix.repeat
- numpy.matrix.reshape
- numpy.matrix.resize
- numpy.matrix.round
- numpy.matrix.searchsorted
- numpy.matrix.setfield
- numpy.matrix.setflags
- numpy.matrix.sort
- numpy.matrix.squeeze
- numpy.matrix.std 0>
- numpy.matrix.sum
- numpy.matrix.swapaxes
- numpy.matrix.take
- numpy.matrix.tobytes
- numpy.matrix.tofile
- numpy.matrix.tolist
- numpy.matrix.tostring
- numpy.matrix.trace
- numpy.matrix.transpose
- numpy.matrix.var
- numpy.matrix.view
- numpy.asmatrix
- numpy.bmat 0>
- 内存映射文件数组
- 字符数组（
numpy.char）- numpy.chararray
- numpy.chararray.T
- numpy.chararray.base
- numpy.chararray.ctypes
- numpy.chararray.data
- numpy.chararray.dtype
- numpy.chararray.flags
- numpy.chararray.flat
- numpy.chararray.imag
- numpy.chararray.itemsize
- numpy.chararray.nbytes
- numpy.chararray.ndim
- numpy.chararray.real
- numpy.chararray.shape
- numpy.chararray.size 0>
- numpy.chararray.strides
- numpy.chararray.astype
- numpy.chararray.copy
- numpy.chararray.count
- numpy.chararray.decode
- numpy.chararray.dump
- numpy.chararray.dumps
- numpy.chararray.encode
- numpy.chararray.endswith
- numpy.chararray.expandtabs
- numpy.chararray.fill
- numpy.chararray.find
- numpy.chararray.flatten
- numpy.chararray.getfield
- numpy.chararray.index
- numpy.chararray.isalnum
- numpy.chararray.isalpha
- numpy.chararray.isdecimal
- numpy.chararray.isdigit
- numpy.chararray.islower
- numpy.chararray.isnumeric
- numpy.chararray.isspace
- numpy.chararray.istitle
- numpy.chararray.isupper
- numpy.chararray.item
- numpy.chararray.join
- numpy.chararray.ljust
- numpy.chararray.lower
- numpy.chararray.lstrip
- numpy.chararray.nonzero
- numpy.chararray.put
- numpy.chararray.ravel
- numpy.chararray.repeat
- numpy.chararray.replace
- numpy.chararray.reshape
- numpy.chararray.resize
- numpy.chararray.rfind
- numpy.chararray.rindex
- numpy.chararray.rjust
- numpy.chararray.rsplit
- numpy.chararray.rstrip
- numpy.chararray.searchsorted
- numpy.chararray.setfield
- numpy.chararray.setflags
- numpy.chararray.sort
- numpy.chararray.split
- numpy.chararray.splitlines
- numpy.chararray.squeeze
- numpy.chararray.startswith
- numpy.chararray.strip
- numpy.chararray.swapaxes
- numpy.chararray.swapcase
- numpy.chararray.take
- numpy.chararray.title
- numpy.chararray.tofile
- numpy.chararray.tolist
- numpy.chararray.tostring
- numpy.chararray.translate
- numpy.chararray.transpose
- numpy.chararray.upper
- numpy.chararray.view
- numpy.chararray.zfill
- numpy.core.defchararray.array
- numpy.chararray
- 记录数组（
numpy.rec）- numpy.recarray
- numpy.recarray.T
- numpy.recarray.base
- numpy.recarray.ctypes
- numpy.recarray.data
- numpy.recarray.dtype
- numpy.recarray.flags
- numpy.recarray.flat
- numpy.recarray.imag
- numpy.recarray.itemsize
- numpy.recarray.nbytes
- numpy.recarray.ndim
- numpy.recarray.real
- numpy.recarray.shape
- numpy.recarray.size
- numpy.recarray.strides
- numpy.recarray.all
- numpy.recarray.any
- numpy.recarray.argmax
- numpy.recarray.argmin
- numpy.recarray.argpartition
- numpy.recarray.argsort
- numpy.recarray.astype
- numpy.recarray.byteswap
- numpy.recarray.choose
- numpy.recarray.clip
- numpy.recarray.compress
- numpy.recarray.conj
- numpy.recarray.conjugate
- numpy.recarray.copy
- numpy.recarray.cumprod
- numpy.recarray.cumsum
- numpy.recarray.diagonal
- numpy.recarray.dot
- numpy.recarray.dump
- numpy.recarray.dumps
- numpy.recarray.field
- numpy.recarray.fill
- numpy.recarray.flatten
- numpy.recarray.getfield
- numpy.recarray.item
- numpy.recarray.itemset
- numpy.recarray.max
- numpy.recarray.mean
- numpy.recarray.min
- numpy.recarray.newbyteorder
- numpy.recarray.nonzero
- numpy.recarray.partition
- numpy.recarray.prod
- numpy.recarray.ptp
- numpy.recarray.put
- numpy.recarray.ravel
- numpy.recarray.repeat
- numpy.recarray.reshape
- numpy.recarray.resize
- numpy.recarray.round
- numpy.recarray.searchsorted
- numpy.recarray.setfield
- numpy.recarray.setflags
- numpy.recarray.sort
- numpy.recarray.squeeze
- numpy.recarray.std
- numpy.recarray.sum
- numpy.recarray.swapaxes
- numpy.recarray.take
- numpy.recarray.tobytes
- numpy.recarray.tofile
- numpy.recarray.tolist
- numpy.recarray.tostring
- numpy.recarray.trace
- numpy.recarray.transpose
- numpy.recarray.var
- numpy.recarray.view
- numpy.record
- numpy.record.T
- numpy.record.base
- numpy.record.data
- numpy.record.dtype
- numpy.record.flags
- numpy.record.flat
- numpy.record.imag
- numpy.record.itemsize
- numpy.record.nbytes
- numpy.record.ndim
- numpy.record.real
- numpy.record.shape
- numpy.record.size
- numpy.record.strides
- numpy.record.all
- numpy.record.any
- numpy.record.argmax
- numpy.record.argmin
- numpy.record.argsort
- numpy.record.astype
- numpy.record.byteswap
- numpy.record.choose
- numpy.record.clip
- numpy.record.compress
- numpy.record.conj
- numpy.record.conjugate
- numpy.record.copy
- numpy.record.cumprod
- numpy.record.cumsum
- numpy.record.diagonal
- numpy.record.dump
- numpy.record.dumps
- numpy.record.fill
- numpy.record.flatten
- numpy.record.getfield
- numpy.record.item
- numpy.record.itemset
- numpy.record.max
- numpy.record.mean
- numpy.record.min
- numpy.record.newbyteorder
- numpy.record.nonzero
- numpy.record.pprint
- numpy.record.prod
- numpy.record.ptp
- numpy.record.put
- numpy.record.ravel
- numpy.record.repeat
- numpy.record.reshape
- numpy.record.resize
- numpy.record.round
- numpy.record.searchsorted
- numpy.record.setfield
- numpy.record.setflags
- numpy.record.sort
- numpy.record.squeeze
- numpy.record.std
- numpy.record.sum
- numpy.record.swapaxes
- numpy.record.take
- numpy.record.tobytes
- numpy.record.tofile
- numpy.record.tolist
- numpy.record.tostring
- numpy.record.trace
- numpy.record.transpose
- numpy.record.var
- numpy.record.view
- numpy.recarray
- 掩码数组（
numpy.ma） - 标准容器类
- 数组迭代器
- 掩码数组
numpy.ma模块- 使用numpy.ma
- 构造屏蔽数组
- numpy.ma.array
- numpy.ma.masked_array
- numpy.ma.asarray
- numpy.ma.asanyarray
- numpy.ma.fix_invalid
- numpy.ma.masked_equal
- numpy.ma.masked_greater
- numpy.ma.masked_greater_equal
- numpy.ma.masked_inside
- numpy.ma.masked_invalid
- numpy.ma.masked_less
- numpy.ma.masked_less_equal
- numpy.ma.masked_not_equal
- numpy.ma.masked_object
- numpy.ma.masked_outside
- numpy.ma.masked_values
- numpy.ma.masked_where
- 访问数据
- 访问掩码
- 只能存取有效的项目
- 修改遮罩
- 索引和切片
- 对掩码数组的操作
- 构造屏蔽数组
- 示例
- Constants of the
numpy.mamodule MaskedArray类- 掩码数组的属性和属性
- numpy.ma.MaskedArray.base
- numpy.ma.MaskedArray.ctypes
- numpy.ma.MaskedArray.dtype
- numpy.ma.MaskedArray.flags
- numpy.ma.MaskedArray.itemsize
- numpy.ma.MaskedArray.nbytes
- numpy.ma.MaskedArray.ndim
- numpy.ma.MaskedArray.shape
- numpy.ma.MaskedArray.size
- numpy.ma.MaskedArray.strides
- numpy.ma.MaskedArray.imag
- numpy.ma.MaskedArray.real
- numpy.ma.MaskedArray.flat
- numpy.ma.MaskedArray .__ array_priority __
- 掩码数组的属性和属性
MaskedArray方法- 转换
- numpy.ma.MaskedArray .__ float __
- numpy.ma.MaskedArray .__ hex __
- numpy.ma.MaskedArray .__ int __
- numpy.ma.MaskedArray .__ long __
- numpy.ma.MaskedArray .__ oct __
- numpy.ma.MaskedArray.view
- numpy.ma.MaskedArray.astype
- numpy.ma.MaskedArray.byteswap
- numpy.ma.MaskedArray.compressed
- numpy.ma.MaskedArray.filled
- numpy.ma.MaskedArray.tofile
- numpy.ma.MaskedArray.toflex
- numpy.ma.MaskedArray.tolist
- numpy.ma.MaskedArray.torecords
- numpy.ma.MaskedArray.tostring
- numpy.ma.MaskedArray.tobytes
- 形状操作
- 项目选择和处理
- numpy.ma.MaskedArray.argmax
- numpy.ma.MaskedArray.argmin
- numpy.ma.MaskedArray.argsort
- numpy.ma.MaskedArray.choose
- numpy.ma.MaskedArray.compress
- numpy.ma.MaskedArray.diagonal
- numpy.ma.MaskedArray.fill
- numpy.ma.MaskedArray.item
- numpy.ma.MaskedArray.nonzero
- numpy.ma.MaskedArray.put
- numpy.ma.MaskedArray.repeat
- numpy.ma.MaskedArray.searchsorted
- numpy.ma.MaskedArray.sort
- numpy.ma.MaskedArray.take
- 腌制和复制
- 计算
- numpy.ma.MaskedArray.all
- numpy.ma.MaskedArray.anom
- numpy.ma.MaskedArray.any
- numpy.ma.MaskedArray.clip
- numpy.ma.MaskedArray.conj
- numpy.ma.MaskedArray.conjugate
- numpy.ma.MaskedArray.cumprod
- numpy.ma.MaskedArray.cumsum
- numpy.ma.MaskedArray.max
- numpy.ma.MaskedArray.mean
- numpy.ma.MaskedArray.min
- numpy.ma.MaskedArray.prod
- numpy.ma.MaskedArray.product
- numpy.ma.MaskedArray.ptp
- numpy.ma.MaskedArray.round
- numpy.ma.MaskedArray.std
- numpy.ma.MaskedArray.sum
- numpy.ma.MaskedArray.trace
- numpy.ma.MaskedArray.var
- 算术和比较操作
- 比较运算符：
- 数组的真值（
bool）： - 算术：
- numpy.ma.MaskedArray .__ abs __
- numpy.ma.MaskedArray .__ add __
- numpy.ma.MaskedArray .__ radd __
- numpy.ma.MaskedArray .__ sub __
- numpy.ma.MaskedArray .__ rsub __
- numpy.ma.MaskedArray .__ mul __
- numpy.ma.MaskedArray .__ rmul __
- numpy.ma.MaskedArray .__ div __
- numpy.ma.MaskedArray .__ rdiv __
- numpy.ma.MaskedArray .__ truediv __
- numpy.ma.MaskedArray .__ rtruediv __
- numpy.ma.MaskedArray .__ floordiv __
- numpy.ma.MaskedArray .__ rfloordiv __
- numpy.ma.MaskedArray .__ mod __
- numpy.ma.MaskedArray .__ rmod __
- numpy.ma.MaskedArray .__ divmod __
- numpy.ma.MaskedArray .__ rdivmod __
- numpy.ma.MaskedArray .__ pow __
- numpy.ma.MaskedArray .__ rpow __
- numpy.ma.MaskedArray .__ lshift __
- numpy.ma.MaskedArray .__ rlshift __
- numpy.ma.MaskedArray .__ rshift __
- numpy.ma.MaskedArray .__ rrshift __
- numpy.ma.MaskedArray .__和__
- numpy.ma.MaskedArray .__ rand __
- numpy.ma.MaskedArray .__或__
- numpy.ma.MaskedArray .__ ror __
- numpy.ma.MaskedArray .__ xor __
- numpy.ma.MaskedArray .__ rxor __
- 算术，原地：
- numpy.ma.MaskedArray .__ iadd __
- numpy.ma.MaskedArray .__ isub __
- numpy.ma.MaskedArray .__ imul __
- numpy.ma.MaskedArray .__ idiv __
- numpy.ma.MaskedArray .__ itruediv __
- numpy.ma.MaskedArray .__ ifloordiv __
- numpy.ma.MaskedArray .__ imod __
- numpy.ma.MaskedArray .__ ipow __
- numpy.ma.MaskedArray .__ ilshift __
- numpy.ma.MaskedArray .__ irshift __
- numpy.ma.MaskedArray .__ iand __
- numpy.ma.MaskedArray .__ ior __
- numpy.ma.MaskedArray .__ ixor __
- 表示
- 特殊方法
- numpy.ma.MaskedArray .__ copy __
- numpy.ma.MaskedArray .__ deepcopy __
- numpy.ma.MaskedArray .__ getstate __
- numpy.ma.MaskedArray .__ reduce __
- numpy.ma.MaskedArray .__ setstate __
- numpy.ma.MaskedArray .__ new __
- numpy.ma.MaskedArray .__ array __
- numpy.ma.MaskedArray .__ array_wrap __
- numpy.ma.MaskedArray .__ len __
- numpy.ma.MaskedArray .__ getitem __
- numpy.ma.MaskedArray .__ setitem __
- numpy.ma.MaskedArray .__ delitem __
- numpy.ma.MaskedArray .__包含__
- 具体方法
- 转换
- 屏蔽数组操作
- 常量
- 创建
- 检查数组
- numpy.ma.all
- numpy.ma.any
- numpy.ma.count
- numpy.ma.count_masked
- numpy.ma.getmask
- numpy.ma.getmaskarray
- numpy.ma.getdata
- numpy.ma.nonzero
- numpy.ma.shape
- numpy.ma.size
- numpy.ma.is_masked
- numpy.ma.is_mask
- numpy.ma.MaskedArray.data
- numpy.ma.MaskedArray.mask
- numpy.ma.MaskedArray.recordmask
- numpy.ma.MaskedArray.all
- numpy.ma.MaskedArray.any
- numpy.ma.MaskedArray.count
- numpy.ma.MaskedArray.nonzero
- numpy.ma.shape
- numpy.ma.size
- 操作MaskedArray
- 面罩操作
- 转换操作
- ＆gt；到掩码数组
- numpy.ma.asarray
- numpy.ma.asanyarray
- numpy.ma.fix_invalid
- numpy.ma.masked_equal
- numpy.ma.masked_greater
- numpy.ma.masked_greater_equal
- numpy.ma.masked_inside
- numpy.ma.masked_invalid
- numpy.ma.masked_less
- numpy.ma.masked_less_equal
- numpy.ma.masked_not_equal
- numpy.ma.masked_object
- numpy.ma.masked_outside
- numpy.ma.masked_values
- numpy.ma.masked_where
- ＆gt；到ndarray
- ＆gt；到另一个对象
- 腌制和取消腌制
- 填充屏蔽数组
- ＆gt；到掩码数组
- 掩蔽数组算术
- 算术
- numpy.ma.anom
- numpy.ma.anomalies
- numpy.ma.average
- numpy.ma.conjugate
- numpy.ma.corrcoef
- numpy.ma.cov
- numpy.ma.cumsum
- numpy.ma.cumprod
- numpy.ma.mean
- numpy.ma.median
- numpy.ma.power
- numpy.ma.prod
- numpy.ma.std
- numpy.ma.sum
- numpy.ma.var
- numpy.ma.MaskedArray.anom
- numpy.ma.MaskedArray.cumprod
- numpy.ma.MaskedArray.cumsum
- numpy.ma.MaskedArray.mean
- numpy.ma.MaskedArray.prod
- numpy.ma.MaskedArray.std
- numpy.ma.MaskedArray.sum
- numpy.ma.MaskedArray.var
- 最小值/最大值
- 排序
- 代数
- 多项式拟合
- 剪辑和舍入
- Miscellanea
- 算术
- 数组接口
- Datetimes和Timedeltas
- N维数组（
- 通用函数（
ufunc） - 例程
- 数组创建例程
- 数组操作例程
- 二进制操作
- 字符串操作
- 字符串操作
- numpy.core.defchararray.add
- numpy.core.defchararray.multiply
- numpy.core.defchararray.mod
- numpy.core.defchararray.capitalize
- numpy.core.defchararray.center
- numpy.core.defchararray.decode
- numpy.core.defchararray.encode
- numpy.core.defchararray.join
- numpy.core.defchararray.ljust
- numpy.core.defchararray.lower
- numpy.core.defchararray.lstrip
- numpy.core.defchararray.partition
- numpy.core.defchararray.replace
- numpy.core.defchararray.rjust
- numpy.core.defchararray.rpartition
- numpy.core.defchararray.rsplit
- numpy.core.defchararray.rstrip 0>
- numpy.core.defchararray.split
- numpy.core.defchararray.splitlines
- numpy.core.defchararray.strip
- numpy.core.defchararray.swapcase
- numpy.core.defchararray.title
- numpy.core.defchararray.translate
- numpy.core.defchararray.upper
- numpy.core.defchararray.zfill
- 比较
- 字符串信息
- numpy.core.defchararray.count
- numpy.core.defchararray.find
- numpy.core.defchararray.index
- numpy.core.defchararray.isalpha
- numpy.core.defchararray.isdecimal
- numpy.core.defchararray.isdigit
- numpy.core.defchararray.islower
- numpy.core.defchararray.isnumeric
- numpy.core.defchararray.isspace
- numpy.core.defchararray.istitle
- numpy.core.defchararray.isupper
- numpy.core.defchararray.rfind
- numpy.core.defchararray.rindex
- numpy.core.defchararray.startswith
- 便利类
- numpy.core.defchararray.chararray
- numpy.core.defchararray.chararray.T
- numpy.core.defchararray.chararray.base
- numpy.core.defchararray.chararray.ctypes
- numpy.core.defchararray.chararray.data
- numpy.core.defchararray.chararray.dtype
- numpy.core.defchararray.chararray.flags
- numpy.core.defchararray.chararray.flat
- numpy.core.defchararray.chararray.imag
- numpy.core.defchararray.chararray.itemsize
- numpy.core.defchararray.chararray.nbytes
- numpy.core.defchararray.chararray.ndim
- numpy.core.defchararray.chararray.real
- numpy.core.defchararray.chararray.shape
- numpy.core.defchararray.chararray.size
- numpy.core.defchararray.chararray.strides
- numpy.core.defchararray.chararray.astype
- numpy.core.defchararray.chararray.copy
- numpy.core.defchararray.chararray.count
- numpy.core.defchararray.chararray.decode
- numpy.core.defchararray.chararray.dump
- numpy.core.defchararray.chararray.dumps
- numpy.core.defchararray.chararray.encode
- numpy.core.defchararray.chararray.endswith
- numpy.core.defchararray.chararray.expandtabs
- numpy.core.defchararray.chararray.fill
- numpy.core.defchararray.chararray.find
- numpy.core.defchararray.chararray.flatten
- numpy.core.defchararray.chararray.getfield
- numpy.core.defchararray.chararray.index
- numpy.core.defchararray.chararray.isalnum
- numpy.core.defchararray.chararray.isalpha
- numpy.core.defchararray.chararray.isdecimal
- numpy.core.defchararray.chararray.isdigit
- numpy.core.defchararray.chararray.islower
- numpy.core.defchararray.chararray.isnumeric
- numpy.core.defchararray.chararray.isspace
- numpy.core.defchararray.chararray.istitle
- numpy.core.defchararray.chararray.isupper
- numpy.core.defchararray.chararray.item
- numpy.core.defchararray.chararray.join
- numpy.core.defchararray.chararray.ljust
- numpy.core.defchararray.chararray.lower
- numpy.core.defchararray.chararray.lstrip
- numpy.core.defchararray.chararray.nonzero
- numpy.core.defchararray.chararray.put
- numpy.core.defchararray.chararray.ravel
- numpy.core.defchararray.chararray.repeat
- numpy.core.defchararray.chararray.replace
- numpy.core.defchararray.chararray.reshape
- numpy.core.defchararray.chararray.resize
- numpy.core.defchararray.chararray.rfind
- numpy.core.defchararray.chararray.rindex
- numpy.core.defchararray.chararray.rjust
- numpy.core.defchararray.chararray.rsplit
- numpy.core.defchararray.chararray.rstrip
- numpy.core.defchararray.chararray.searchsorted
- numpy.core.defchararray.chararray.setfield
- numpy.core.defchararray.chararray.setflags
- numpy.core.defchararray.chararray.sort
- numpy.core.defchararray.chararray.split
- numpy.core.defchararray.chararray.splitlines
- numpy.core.defchararray.chararray.squeeze
- numpy.core.defchararray.chararray.startswith
- numpy.core.defchararray.chararray.strip
- numpy.core.defchararray.chararray.swapaxes
- numpy.core.defchararray.chararray.swapcase
- numpy.core.defchararray.chararray.take
- numpy.core.defchararray.chararray.title
- numpy.core.defchararray.chararray.tofile
- numpy.core.defchararray.chararray.tolist
- numpy.core.defchararray.chararray.tostring
- numpy.core.defchararray.chararray.translate
- numpy.core.defchararray.chararray.transpose
- numpy.core.defchararray.chararray.upper
- numpy.core.defchararray.chararray.view
- numpy.core.defchararray.chararray.zfill
- numpy.core.defchararray.chararray
- 字符串操作
- C类型外部函数接口（
numpy.ctypeslib） - 日期时间支持函数
- 数据类型例程
- 可选Scipy加速例程（
numpy.dual） - 具有自动域的数学函数（
numpy.emath） - 浮点错误处理
- 离散傅里叶变换（
numpy.fft） - 财务功能
- 功能编程
- NumPy特定的帮助功能
- 索引例程
- 输入和输出
- 线性代数（
numpy.linalg） - 逻辑功能
- 屏蔽数组操作
- 常量
- 创建
- 检查数组
- numpy.ma.all
- numpy.ma.any
- numpy.ma.count
- numpy.ma.count_masked
- numpy.ma.getmask
- numpy.ma.getmaskarray
- numpy.ma.getdata
- numpy.ma.nonzero
- numpy.ma.shape
- numpy.ma.size
- numpy.ma.is_masked
- numpy.ma.is_mask
- numpy.ma.MaskedArray.data
- numpy.ma.MaskedArray.mask
- numpy.ma.MaskedArray.recordmask
- numpy.ma.MaskedArray.all
- numpy.ma.MaskedArray.any
- numpy.ma.MaskedArray.count
- numpy.ma.MaskedArray.nonzero
- numpy.ma.shape
- numpy.ma.size
- 操作MaskedArray
- 面罩操作
- 转换操作
- ＆gt；到掩码数组
- numpy.ma.asarray
- numpy.ma.asanyarray
- numpy.ma.fix_invalid
- numpy.ma.masked_equal
- numpy.ma.masked_greater
- numpy.ma.masked_greater_equal
- numpy.ma.masked_inside
- numpy.ma.masked_invalid
- numpy.ma.masked_less
- numpy.ma.masked_less_equal
- numpy.ma.masked_not_equal
- numpy.ma.masked_object
- numpy.ma.masked_outside
- numpy.ma.masked_values
- numpy.ma.masked_where
- ＆gt；到ndarray
- ＆gt；到另一个对象
- 腌制和取消腌制
- 填充屏蔽数组
- ＆gt；到掩码数组
- 掩蔽数组算术
- 算术
- numpy.ma.anom
- numpy.ma.anomalies
- numpy.ma.average
- numpy.ma.conjugate
- numpy.ma.corrcoef
- numpy.ma.cov
- numpy.ma.cumsum
- numpy.ma.cumprod
- numpy.ma.mean
- numpy.ma.median
- numpy.ma.power
- numpy.ma.prod
- numpy.ma.std
- numpy.ma.sum
- numpy.ma.var
- numpy.ma.MaskedArray.anom
- numpy.ma.MaskedArray.cumprod
- numpy.ma.MaskedArray.cumsum
- numpy.ma.MaskedArray.mean
- numpy.ma.MaskedArray.prod
- numpy.ma.MaskedArray.std
- numpy.ma.MaskedArray.sum
- numpy.ma.MaskedArray.var
- 最小值/最大值
- 排序
- 代数
- 多项式拟合
- 剪辑和舍入
- Miscellanea
- 算术
- 数学函数
- 矩阵库（
numpy.matlib） - 其他例程
- 填充数组
- 多项式
- 转换通知
- 多项式封装
- 使用便利类
- 多项式模块（
numpy.polynomial.polynomial）- 多项式类
- numpy.polynomial.polynomial.Polynomial
- numpy.polynomial.polynomial.Polynomial.__call__
- numpy.polynomial.polynomial.Polynomial.basis
- numpy.polynomial.polynomial.Polynomial.cast
- numpy.polynomial.polynomial.Polynomial.convert
- numpy.polynomial.polynomial.Polynomial.copy
- numpy.polynomial.polynomial.Polynomial.cutdeg
- numpy.polynomial.polynomial.Polynomial.degree
- numpy.polynomial.polynomial.Polynomial.deriv
- numpy.polynomial.polynomial.Polynomial.fit
- numpy.polynomial.polynomial.Polynomial.fromroots
- numpy.polynomial.polynomial.Polynomial.has_samecoef
- numpy.polynomial.polynomial.Polynomial.has_samedomain
- numpy.polynomial.polynomial.Polynomial.has_sametype
- numpy.polynomial.polynomial.Polynomial.has_samewindow
- numpy.polynomial.polynomial.Polynomial.identity
- numpy.polynomial.polynomial.Polynomial.integ
- numpy.polynomial.polynomial.Polynomial.linspace
- numpy.polynomial.polynomial.Polynomial.mapparms
- numpy.polynomial.polynomial.Polynomial.roots
- numpy.polynomial.polynomial.Polynomial.trim
- numpy.polynomial.polynomial.Polynomial.truncate
- numpy.polynomial.polynomial.Polynomial
- 基础
- 配件
- 微积分
- 代数
- 其他
- 多项式类
- Chebyshev模块（
numpy.polynomial.chebyshev）- 切比雪夫课
- numpy.polynomial.chebyshev.Chebyshev
- numpy.polynomial.chebyshev.Chebyshev .__ call __
- numpy.polynomial.chebyshev.Chebyshev.basis
- numpy.polynomial.chebyshev.Chebyshev.cast
- numpy.polynomial.chebyshev.Chebyshev.convert
- numpy.polynomial.chebyshev.Chebyshev.copy
- numpy.polynomial.chebyshev.Chebyshev.cutdeg
- numpy.polynomial.chebyshev.Chebyshev.degree
- numpy.polynomial.chebyshev.Chebyshev.deriv
- numpy.polynomial.chebyshev.Chebyshev.fit
- numpy.polynomial.chebyshev.Chebyshev.fromroots
- numpy.polynomial.chebyshev.Chebyshev.has_samecoef
- numpy.polynomial.chebyshev.Chebyshev.has_samedomain
- numpy.polynomial.chebyshev.Chebyshev.has_sametype
- numpy.polynomial.chebyshev.Chebyshev.has_samewindow
- numpy.polynomial.chebyshev.Chebyshev.identity
- numpy.polynomial.chebyshev.Chebyshev.integ
- numpy.polynomial.chebyshev.Chebyshev.linspace
- numpy.polynomial.chebyshev.Chebyshev.mapparms
- numpy.polynomial.chebyshev.Chebyshev.roots
- numpy.polynomial.chebyshev.Chebyshev.trim
- numpy.polynomial.chebyshev.Chebyshev.truncate
- numpy.polynomial.chebyshev.Chebyshev
- 基础
- 配件
- 微积分
- 代数
- 正交
- 其他
- numpy.polynomial.chebyshev.chebcompanion
- numpy.polynomial.chebyshev.chebdomain
- numpy.polynomial.chebyshev.chebzero
- numpy.polynomial.chebyshev.chebone
- numpy.polynomial.chebyshev.chebx
- numpy.polynomial.chebyshev.chebtrim
- numpy.polynomial.chebyshev.chebline
- numpy.polynomial.chebyshev.cheb2poly
- numpy.polynomial.chebyshev.poly2cheb
- 切比雪夫课
- Legendre模块（
numpy.polynomial.legendre）- Legendre Class
- numpy.polynomial.legendre.Legendre
- numpy.polynomial.legendre.Legendre .__ call __
- numpy.polynomial.legendre.Legendre.basis
- numpy.polynomial.legendre.Legendre.cast
- numpy.polynomial.legendre.Legendre.convert
- numpy.polynomial.legendre.Legendre.copy
- numpy.polynomial.legendre.Legendre.cutdeg
- numpy.polynomial.legendre.Legendre.degree
- numpy.polynomial.legendre.Legendre.deriv
- numpy.polynomial.legendre.Legendre.fit
- numpy.polynomial.legendre.Legendre.fromroots
- numpy.polynomial.legendre.Legendre.has_samecoef
- numpy.polynomial.legendre.Legendre.has_samedomain
- numpy.polynomial.legendre.Legendre.has_sametype
- numpy.polynomial.legendre.Legendre.has_samewindow
- numpy.polynomial.legendre.Legendre.identity
- numpy.polynomial.legendre.Legendre.integ
- numpy.polynomial.legendre.Legendre.linspace
- numpy.polynomial.legendre.Legendre.mapparms
- numpy.polynomial.legendre.Legendre.roots
- numpy.polynomial.legendre.Legendre.trim
- numpy.polynomial.legendre.Legendre.truncate
- numpy.polynomial.legendre.Legendre
- 基础
- 配件
- 微积分
- 代数
- 正交
- 其他
- numpy.polynomial.legendre.legcompanion
- numpy.polynomial.legendre.legdomain
- numpy.polynomial.legendre.legzero
- numpy.polynomial.legendre.legone
- numpy.polynomial.legendre.legx
- numpy.polynomial.legendre.legtrim
- numpy.polynomial.legendre.legline
- numpy.polynomial.legendre.leg2poly
- numpy.polynomial.legendre.poly2leg
- Legendre Class
- Laguerre模块（
numpy.polynomial.laguerre）- Laguerre Class
- numpy.polynomial.laguerre.Laguerre
- numpy.polynomial.laguerre.Laguerre .__ call __
- numpy.polynomial.laguerre.Laguerre.basis
- numpy.polynomial.laguerre.Laguerre.cast
- numpy.polynomial.laguerre.Laguerre.convert
- numpy.polynomial.laguerre.Laguerre.copy
- numpy.polynomial.laguerre.Laguerre.cutdeg
- numpy.polynomial.laguerre.Laguerre.degree
- numpy.polynomial.laguerre.Laguerre.deriv
- numpy.polynomial.laguerre.Laguerre.fit
- numpy.polynomial.laguerre.Laguerre.fromroots
- numpy.polynomial.laguerre.Laguerre.has_samecoef
- numpy.polynomial.laguerre.Laguerre.has_samedomain
- numpy.polynomial.laguerre.Laguerre.has_sametype
- numpy.polynomial.laguerre.Laguerre.has_samewindow
- numpy.polynomial.laguerre.Laguerre.identity
- numpy.polynomial.laguerre.Laguerre.integ
- numpy.polynomial.laguerre.Laguerre.linspace
- numpy.polynomial.laguerre.Laguerre.mapparms
- numpy.polynomial.laguerre.Laguerre.roots 0>
- numpy.polynomial.laguerre.Laguerre.trim
- numpy.polynomial.laguerre.Laguerre.truncate
- numpy.polynomial.laguerre.Laguerre
- 基础
- 配件
- 微积分
- 代数
- 正交
- 其他
- numpy.polynomial.laguerre.lagcompanion
- numpy.polynomial.laguerre.lagdomain
- numpy.polynomial.laguerre.lagzero
- numpy.polynomial.laguerre.lagone
- numpy.polynomial.laguerre.lagx
- numpy.polynomial.laguerre.lagtrim
- numpy.polynomial.laguerre.lagline
- numpy.polynomial.laguerre.lag2poly
- numpy.polynomial.laguerre.poly2lag
- Laguerre Class
- Hermite模块，“物理学家”（
numpy.polynomial.hermite）- Hermite类
- numpy.polynomial.hermite.Hermite
- numpy.polynomial.hermite.Hermite .__ call __
- numpy.polynomial.hermite.Hermite.basis
- numpy.polynomial.hermite.Hermite.cast
- numpy.polynomial.hermite.Hermite.convert
- numpy.polynomial.hermite.Hermite.copy
- numpy.polynomial.hermite.Hermite.cutdeg 0>
- numpy.polynomial.hermite.Hermite.degree
- numpy.polynomial.hermite.Hermite.deriv
- numpy.polynomial.hermite.Hermite.fit
- numpy.polynomial.hermite.Hermite.fromroots
- numpy.polynomial.hermite.Hermite.has_samecoef
- numpy.polynomial.hermite.Hermite.has_samedomain
- numpy.polynomial.hermite.Hermite.has_sametype
- numpy.polynomial.hermite.Hermite.has_samewindow
- numpy.polynomial.hermite.Hermite.identity
- numpy.polynomial.hermite.Hermite.integ
- numpy.polynomial.hermite.Hermite.linspace
- numpy.polynomial.hermite.Hermite.mapparms
- numpy.polynomial.hermite.Hermite.roots
- numpy.polynomial.hermite.Hermite.trim
- numpy.polynomial.hermite.Hermite.truncate
- numpy.polynomial.hermite.Hermite
- 基础
- 配件
- 微积分
- 代数
- 正交
- 其他
- numpy.polynomial.hermite.hermcompanion
- numpy.polynomial.hermite.hermdomain
- numpy.polynomial.hermite.hermzero
- numpy.polynomial.hermite.hermone
- numpy.polynomial.hermite.hermx
- numpy.polynomial.hermite.hermtrim
- numpy.polynomial.hermite.hermline
- numpy.polynomial.hermite.herm2poly
- numpy.polynomial.hermite.poly2herm
- Hermite类
- HermiteE模块，“Probabilists”（
numpy.polynomial.hermite_e）- HermiteE类
- numpy.polynomial.hermite_e.HermiteE
- numpy.polynomial.hermite_e.HermiteE .__ call __
- numpy.polynomial.hermite_e.HermiteE.basis
- numpy.polynomial.hermite_e.HermiteE.cast
- numpy.polynomial.hermite_e.HermiteE.convert
- numpy.polynomial.hermite_e.HermiteE.copy
- numpy.polynomial.hermite_e.HermiteE.cutdeg
- numpy.polynomial.hermite_e.HermiteE.degree
- numpy.polynomial.hermite_e.HermiteE.deriv
- numpy.polynomial.hermite_e.HermiteE.fit
- numpy.polynomial.hermite_e.HermiteE.fromroots
- numpy.polynomial.hermite_e.HermiteE.has_samecoef
- numpy.polynomial.hermite_e.HermiteE.has_Samedomain
- numpy.polynomial.hermite_e.HermiteE.has_sametype
- numpy.polynomial.hermite_e.HermiteE.has_samewindow
- numpy.polynomial.hermite_e.HermiteE.identity
- numpy.polynomial.hermite_e.HermiteE.integ
- numpy.polynomial.hermite_e.HermiteE.linspace
- numpy.polynomial.hermite_e.HermiteE.mapparms
- numpy.polynomial.hermite_e.HermiteE.roots
- numpy.polynomial.hermite_e.HermiteE.trim
- numpy.polynomial.hermite_e.HermiteE.truncate
- numpy.polynomial.hermite_e.HermiteE
- 基础
- 配件
- 微积分
- 代数
- 正交
- 其他
- numpy.polynomial.hermite_e.hermecompanion
- numpy.polynomial.hermite_e.hermedomain
- numpy.polynomial.hermite_e.hermezero
- numpy.polynomial.hermite_e.hermeone
- numpy.polynomial.hermite_e.hermex
- numpy.polynomial.hermite_e.hermetrim
- numpy.polynomial.hermite_e.hermeline
- numpy.polynomial.hermite_e.herme2poly
- numpy.polynomial.hermite_e.poly2herme
- HermiteE类
- Poly1d
- 多项式封装
- 转换通知
- 随机抽样（
numpy.random）- 简单随机数据
- 排列
- 分发
- numpy.random.beta
- numpy.random.binomial
- numpy.random.chisquare
- numpy.random.dirichlet
- numpy.random.exponential
- numpy.random.f
- numpy.random.gamma
- numpy.random.geometric
- numpy.random.gumbel
- numpy.random.hypergeometric
- numpy.random.laplace
- numpy.random.logistic
- numpy.random.lognormal
- numpy.random.logseries
- numpy.random.multinomial
- numpy.random.multivariate_normal
- numpy.random.negative_binomial
- numpy.random.noncentral_chisquare
- numpy.random.noncentral_f
- numpy.random.normal
- numpy.random.pareto
- numpy.random.poisson
- numpy.random.power
- numpy.random.rayleigh
- numpy.random.standard_cauchy
- numpy.random.standard_exponential
- numpy.random.standard_gamma
- numpy.random.standard_normal
- numpy.random.standard_t
- numpy.random.triangular
- numpy.random.uniform
- numpy.random.vonmises
- numpy.random.wald
- numpy.random.weibull
- numpy.random.zipf
- 随机生成器
- numpy.random.RandomState
- numpy.random.RandomState.beta
- numpy.random.RandomState.binomial
- numpy.random.RandomState.bytes
- numpy.random.RandomState.chisquare
- numpy.random.RandomState.choice
- numpy.random.RandomState.dirichlet
- numpy.random.RandomState.exponential
- numpy.random.RandomState.f
- numpy.random.RandomState.gamma
- numpy.random.RandomState.geometric
- numpy.random.RandomState.get_state
- numpy.random.RandomState.gumbel
- numpy.random.RandomState.hypergeometric
- numpy.random.RandomState.laplace
- numpy.random.RandomState.logistic
- numpy.random.RandomState.lognormal
- numpy.random.RandomState.logseries
- numpy.random.RandomState.multinomial
- numpy.random.RandomState.multivariate_normal
- numpy.random.RandomState.negative_binomial
- numpy.random.RandomState.noncentral_chisquare
- numpy.random.RandomState.noncentral_f
- numpy.random.RandomState.normal
- numpy.random.RandomState.pareto
- numpy.random.RandomState.permutation
- numpy.random.RandomState.poisson
- numpy.random.RandomState.power
- numpy.random.RandomState.rand
- numpy.random.RandomState.randint
- numpy.random.RandomState.randn
- numpy.random.RandomState.random_integers
- numpy.random.RandomState.random_sample
- numpy.random.RandomState.rayleigh
- numpy.random.RandomState.seed
- numpy.random.RandomState.set_state
- numpy.random.RandomState.shuffle
- numpy.random.RandomState.standard_cauchy
- numpy.random.RandomState.standard_exponential
- numpy.random.RandomState.standard_gamma
- numpy.random.RandomState.standard_normal
- numpy.random.RandomState.standard_t
- numpy.random.RandomState.tomaxint
- numpy.random.RandomState.triangular
- numpy.random.RandomState.uniform
- numpy.random.RandomState.vonmises
- numpy.random.RandomState.wald
- numpy.random.RandomState.weibull
- numpy.random.RandomState.zipf
- numpy.random.seed
- numpy.random.get_state
- numpy.random.set_state
- numpy.random.RandomState
- 设置例程
- 排序，搜索和计数
- 统计
- 测试支持（
numpy.testing）- 断言
- numpy.testing.assert_almost_equal
- numpy.testing.assert_approx_equal
- numpy.testing.assert_array_almost_equal
- numpy.testing.assert_allclose
- numpy.testing.assert_array_almost_equal_nulp
- numpy.testing.assert_array_max_ulp
- numpy.testing.assert_array_equal
- numpy.testing.assert_array_less
- numpy.testing.assert_equal
- numpy.testing.assert_raises
- numpy.testing.assert_raises_regex
- numpy.testing.assert_warns
- numpy.testing.assert_string_equal
- 装饰
- 测试运行
- 断言
- 窗口函数
- 包装（
numpy.distutils）- 在
numpy.distutils中的模块- misc_util
- numpy.distutils.misc_util.get_numpy_include_dirs
- numpy.distutils.misc_util.dict_append
- numpy.distutils.misc_util.appendpath
- numpy.distutils.misc_util.allpath
- numpy.distutils.misc_util.dot_join
- numpy.distutils.misc_util.generate_config_py
- numpy.distutils.misc_util.get_cmd
- numpy.distutils.misc_util.terminal_has_colors
- numpy.distutils.misc_util.red_text
- numpy.distutils.misc_util.green_text
- numpy.distutils.misc_util.yellow_text
- numpy.distutils.misc_util.blue_text
- numpy.distutils.misc_util.cyan_text
- numpy.distutils.misc_util.cyg2win32
- numpy.distutils.misc_util.all_strings
- numpy.distutils.misc_util.has_f_sources
- numpy.distutils.misc_util.has_cxx_sources
- numpy.distutils.misc_util.filter_sources
- numpy.distutils.misc_util.get_dependencies
- numpy.distutils.misc_util.is_local_src_dir
- numpy.distutils.misc_util.get_ext_source_files
- numpy.distutils.misc_util.get_script_files
- 其他模块
- misc_util
- 构建可安装的C库
- 转换
.src文件
- 在
- NumPy C-API
- NumPy内部
- NumPy和SWIG
- 致谢
- 数组对象
- F2PY用户指南和参考手册
- 参与NumPy
- NumPy增强提议
- 已实施NEP
- 覆盖Ufunc的机制
- 通用通用功能
- 优化迭代器/ UFunc性能
- NumPy数组的简单文件格式
- 其他NEP
- NumPy中缺少数据功能
- 清除numpy.core的数学配置
- 向NumPy添加groupby功能的提议
- 建议在没有警告的情况下使用大量警告标志创建numpy
- 将Trac替换为其他错误跟踪器
- 延迟UFunc评估
- 结构化数组扩展
- 在NumPy中实现某些日期/时间类型的提议
- 在NumPy中实现某些日期/时间类型的（第三个）提案
- 已实施NEP
- 发行说明
- NumPy 1.13.0发行说明
- NumPy 1.12.0发行说明
- NumPy 1.11.3发行说明
- 维护人员/ 1.11.3
- 合并提取请求
- 合并提取请求
- 修正合并
- 亮点
- 构建系统更改
- 未来变化
- 兼容性说明
- 新功能
- 改进
- 更改 T0>
- 弃用
- FutureWarnings
- 兼容性说明
- 已修复问题
- 合并的PR
- 兼容性说明
- 轻松步幅检查不再是默认值
- 修复
numpy.i中的swig错误 - 弃用按fortran顺序更改尺寸的视图
- 已修复问题
- 合并的PR
- 备注
- 亮点
- 删除支持
- 未来变化
- 兼容性说明
- 新功能
- 改进
- 更改
- dotblas功能已移至multiarray
- 更严格检查gufunc签名合规性
- 从np.einsum返回的视图是可写的
- np.argmin跳过NaT值
- 弃用
- 已修复问题
- 已修复问题
- 亮点
- 删除支持
- 未来变化
- 兼容性说明
- 对角线和diag函数返回只读视图。
- 特殊标量浮点值不会导致上传重载
- 输出变化百分比
- ndarray.tofile例外类型
- 无效的填充值异常
- 多项式类不再派生自PolyBase
- 使用numpy.random.binomial可以改变RNG状态对numpy
- 随机种子强制为32位无符号整数
- Argmin和argmax输出参数
- Einsum
- 索引
- 非整数缩减轴索引已弃用
promote_types和string dtypecan_cast和string dtype- astype和string dtype
- npyio.recfromcsv关键字参数更改
- 移动了
doc/swig目录 npy_3kcompat.h标头已变更- C-Api中的负指数
sq_item和sq_ass_item序列方法 - NDIter
zeros_like对于字符串dtypes现在返回空字符串
- 新功能
- 改进
- 弃用
- 已修复问题
- 已修复问题
- 更改 T0>
- NDIter
- np.distutils的可选简化冗余
- 弃用
- 亮点
- 删除支持
- 未来变化
- 兼容性说明
- 新功能
- 支持堆叠数组上的线性代数
- 为ufuncs定位花型索引
- 新功能分区和argpartition
- 新功能nanmean，nanvar和nanstd
- 新功能满和full_like
- IO与大型文件的兼容性
- 构建对OpenBLAS
- 新常数
- qr的新模式
- 新反转参数为in1d
- 使用np.newaxis进行高级索引
- C-API
- runtests.py
- 改进
- IO性能改进
- pad的性能提升
- isnan，isinf，isfinite和byteswap
- 通过SSE2向量化实现的性能提升
- 中位数的性能提升
- ufunc C-API中的可重写操作数标志
- 更改 T0>
- 弃用
- 作者
- 已修复问题
- 已修复问题
- 亮点
- 兼容性说明
- 新功能
- 更改 T0>
- 弃用
- 已修复问题
- 更改
- 已修复问题
- 亮点
- 新功能
- 更改 T0>
- 已弃用的功能
- 已删除的功能
- 亮点
- 新功能
- 更改 T0>
- 亮点
- 新功能
- 改进
- 弃用
- 内部更改
- 亮点
- 新功能
- 已弃用的功能
- 文档更改
- 新建C API
- 内部更改
- 关于NumPy
- 关于本文档
- 报告错误
- NumPy License
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