• 官方Document: https://www.numpy.org/devdocs/reference/routines.array-manipulation.html
• 開發(fā)測試環(huán)境
  
  • Win10
  • Python 3.6.4
  • NumPy 1.14.2

Basic operations

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函數(shù)原型作用

[copyto](dst, src[, casting, where])	Copies values from one array to another, broadcasting as necessary.

Changing array shape

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函數(shù)原型作用

[reshape](a, newshape[, order])	Gives a new shape to an array without changing its data.
[ravel](a[, order])	Return a contiguous flattened array.
[ndarray.flat]	A 1-D iterator over the array.
ndarray.flatten	Return a copy of the array collapsed into one dimension.

Transpose-like operations

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函數(shù)原型作用

[moveaxis](a, source, destination)	Move axes of an array to new positions.
[rollaxis](a, axis[, start])	Roll the specified axis backwards, until it lies in a given position.
[swapaxes](a, axis1, axis2)	Interchange two axes of an array.
[ndarray.T]	Same as self.transpose(), except that self is returned if self.ndim < 2.
[transpose](a[, axes])	Permute the dimensions of an array.

Changing number of dimensions

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函數(shù)原型作用

atleast_1d(*arys)	Convert inputs to arrays with at least one dimension.
atleast_2d(*arys)	View inputs as arrays with at least two dimensions.
atleast_3d(*arys)	View inputs as arrays with at least three dimensions.
broadcast	Produce an object that mimics broadcasting.
broadcast_to(array, shape[, subok])	Broadcast an array to a new shape.
broadcast_arrays(*args, **kwargs)	Broadcast any number of arrays against each other.
expand_dims(a, axis)	Expand the shape of an array.
squeeze(a[, axis])	Remove single-dimensional entries from the shape of an array.

expand_dims

擴展array的shape， 插入一個新的軸，該軸將出現(xiàn)在擴展陣列形狀的軸位置

>>> x = np.array([1,2]) >>> x.shape (2,)

以下操作相當于 x[np.newaxis,:] or x[np.newaxis]:

>>> y = np.expand_dims(x, axis=0) >>> y array([[1, 2]]) >>> y.shape (1, 2) >>> y = np.expand_dims(x, axis=1) # Equivalent to x[:,np.newaxis] >>> y array([[1],[2]]) >>> y.shape (2, 1)

注意在一些列子中使用None替換np.newaxis

>>> np.newaxis is None True

squeeze

從數(shù)組的形狀中移除一維條目
- a : array
- axis: None或者整數(shù)或者整數(shù)元組，默認是None
選擇shape單維度的條目，若選取的axis的shape條目不為1，則會拋出異常

>>> x = np.array([[[0], [1], [2]]]) >>> x.shape (1, 3, 1) >>> np.squeeze(x).shape (3,) >>> np.squeeze(x, axis=0).shape (3, 1) >>> np.squeeze(x, axis=1).shape Traceback (most recent call last): ... ValueError: cannot select an axis to squeeze out which has size not equal to one >>> np.squeeze(x, axis=2).shape (1, 3)

axis參數(shù)輸入為整數(shù)列表時，起作用相當于axis=None時的作用

Changing kind of array

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函數(shù)原型作用

[asarray](a[, dtype, order])	Convert the input to an array.
[asanyarray](a[, dtype, order])	Convert the input to an ndarray, but pass ndarray subclasses through.
[asmatrix](data[, dtype])	Interpret the input as a matrix.
[asfarray](a[, dtype])	Return an array converted to a float type.
[asfortranarray](a[, dtype])	Return an array laid out in Fortran order in memory.
[ascontiguousarray](a[, dtype])	Return a contiguous array in memory (C order).
[asarray_chkfinite](a[, dtype, order])	Convert the input to an array, checking for NaNs or Infs.
asscalar	Convert an array of size 1 to its scalar equivalent.
[require](a[, dtype, requirements])	Return an ndarray of the provided type that satisfies requirements.

Joining arrays

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函數(shù)原型作用

concatenate((a1, a2, …)[, axis, out])	Join a sequence of arrays along an existing axis.
stack(arrays[, axis, out])	Join a sequence of arrays along a new axis.
column_stack(tup)	Stack 1-D arrays as columns into a 2-D array.
dstack(tup)	Stack arrays in sequence depth wise (along third axis).
hstack(tup)	Stack arrays in sequence horizontally (column wise).
vstack(tup)	Stack arrays in sequence vertically (row wise).
block(arrays)	Assemble an nd-array from nested lists of blocks.

concatenate

沿著指定的維度進行合并，結果是該維度上shape增加

• a1, a2, … : array序列，除了axis對應的維度外，其他shape相同
• axis : 沿著axis維進行結合，結合后這個維的shape是序列這個維的shape之和

>>> a = np.array([[1, 2], [3, 4]]) >>> b = np.array([[5, 6]]) >>> a.shape, b.shape ((2, 2), (1, 2)) >>> c = np.concatenate((a, b), axis=0) # (2,2) (1,2) =>(3,2) >>> c.shape (3, 2) >>> c array([[1, 2],[3, 4],[5, 6]]) >>> d = np.concatenate((a, b.T), axis=1) >>> d array([[1, 2, 5],[3, 4, 6]]) >>> d.shape (2, 3)

Splitting arrays

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函數(shù)原型作用

[split](ary, indices_or_sections[, axis])	Split an array into multiple sub-arrays.
[array_split](ary, indices_or_sections[, axis])	Split an array into multiple sub-arrays.
[dsplit](ary, indices_or_sections)	Split array into multiple sub-arrays along the 3rd axis (depth).
[hsplit](ary, indices_or_sections)	Split an array into multiple sub-arrays horizontally (column-wise).
[vsplit](ary, indices_or_sections)	Split an array into multiple sub-arrays vertically (row-wise).

Tiling arrays

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函數(shù)原型作用

[tile](A, reps)	Construct an array by repeating A the number of times given by reps.
[repeat](a, repeats[, axis])	Repeat elements of an array.

Adding and removing elements

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函數(shù)原型作用

[delete](arr, obj[, axis])	Return a new array with sub-arrays along an axis deleted.
[insert](arr, obj, values[, axis])	Insert values along the given axis before the given indices.
[append](arr, values[, axis])	Append values to the end of an array.
[resize](a, new_shape)	Return a new array with the specified shape.
[trim_zeros](filt[, trim])	Trim the leading and/or trailing zeros from a 1-D array or sequence.
[unique](ar[, return_index, return_inverse, …])	Find the unique elements of an array.

Rearranging elements

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函數(shù)原型作用

[flip](m[, axis])	Reverse the order of elements in an array along the given axis.
fliplr	Flip array in the left/right direction.
flipud	Flip array in the up/down direction.
[reshape](a, newshape[, order])	Gives a new shape to an array without changing its data.
[roll](a, shift[, axis])	Roll array elements along a given axis.
[rot90](m[, k, axes])	Rotate an array by 90 degrees in the plane specified by axes.

總結

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