numpy.matrix

class numpy.matrix

Returns a matrix from an array-like object, or from a string of data. A matrix is a specialized 2-D array that retains its 2-D nature through operations. It has certain special operators, such as * (matrix multiplication) and ** (matrix power).

Parameters :

data : array_like or string

If data is a string, it is interpreted as a matrix with commas or spaces separating columns, and semicolons separating rows.

dtype : data-type

Data-type of the output matrix.

copy : bool

If data is already an ndarray, then this flag determines whether the data is copied (the default), or whether a view is constructed.

See also

array

Examples

>>> a = np.matrix('1 2; 3 4')
>>> print a
[[1 2]
 [3 4]]

>>> np.matrix([[1, 2], [3, 4]])
matrix([[1, 2],
        [3, 4]])

Methods

all(a[, axis, out])	Test whether all array elements along a given axis evaluate to True.
any(a[, axis, out])	Test whether any array element along a given axis evaluates to True.
argmax(a[, axis])	Indices of the maximum values along an axis.
argmin(a[, axis])	Return the indices of the minimum values along an axis.
argsort(a[, axis, kind, order])	Returns the indices that would sort an array.
astype
byteswap
choose(a, choices[, out, mode])	Construct an array from an index array and a set of arrays to choose from.
clip(a, a_min, a_max[, out])	Clip (limit) the values in an array.
compress(condition, a[, axis, out])	Return selected slices of an array along given axis.
conj()	Return the complex conjugate, element-wise.
conjugate()	Return the complex conjugate, element-wise.
copy(a)	Return an array copy of the given object.
cumprod(a[, axis, dtype, out])	Return the cumulative product of elements along a given axis.
cumsum(a[, axis, dtype, out])	Return the cumulative sum of the elements along a given axis.
diagonal(a[, offset, axis1, axis2])	Return specified diagonals.
dot(a, b)	Dot product of two arrays.
dump
dumps
fill
flatten
getA
getA1
getH
getI
getT
getfield
item
itemset
max(a[, axis, out])	Return the maximum of an array or maximum along an axis.
mean(a[, axis, dtype, out])	Compute the arithmetic mean along the specified axis.
min(a[, axis, out])	Return the minimum of an array or minimum along an axis.
newbyteorder
nonzero(a)	Return the indices of the elements that are non-zero.
prod(a[, axis, dtype, out])	Return the product of array elements over a given axis.
ptp(a[, axis, out])	Range of values (maximum - minimum) along an axis.
put(a, ind, v[, mode])	Replaces specified elements of an array with given values.
ravel(a[, order])	Return a flattened array.
repeat(a, repeats[, axis])	Repeat elements of an array.
reshape(a, newshape[, order])	Gives a new shape to an array without changing its data.
resize(a, new_shape)	Return a new array with the specified shape.
round(a[, decimals, out])	Round an array to the given number of decimals.
searchsorted(a, v[, side])	Find indices where elements should be inserted to maintain order.
setfield
setflags
sort(a[, axis, kind, order])	Return a sorted copy of an array.
squeeze(a)	Remove single-dimensional entries from the shape of an array.
std(a[, axis, dtype, out, ddof])	Compute the standard deviation along the specified axis.
sum(a[, axis, dtype, out])	Sum of array elements over a given axis.
swapaxes(a, axis1, axis2)	Interchange two axes of an array.
take(a, indices[, axis, out, mode])	Take elements from an array along an axis.
tofile
tolist
tostring
trace(a[, offset, axis1, axis2, dtype, out])	Return the sum along diagonals of the array.
transpose(a[, axes])	Permute the dimensions of an array.
var(a[, axis, dtype, out, ddof])	Compute the variance along the specified axis.
view