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([axis, out])	Test whether all matrix elements along a given axis evaluate to True.
any([axis, out])	Test whether any array element along a given axis evaluates to True.
argmax([axis, out])	Indices of the maximum values along an axis.
argmin([axis, out])	Return the indices of the minimum values along an axis.
argpartition(kth[, axis, kind, order])	Returns the indices that would partition this array.
argsort([axis, kind, order])	Returns the indices that would sort this array.
astype(dtype[, order, casting, subok, copy])	Copy of the array, cast to a specified type.
byteswap(inplace)	Swap the bytes of the array elements
choose(choices[, out, mode])	Use an index array to construct a new array from a set of choices.
clip(a_min, a_max[, out])	Return an array whose values are limited to [a_min, a_max].
compress(condition[, axis, out])	Return selected slices of this array along given axis.
conj()	Complex-conjugate all elements.
conjugate()	Return the complex conjugate, element-wise.
copy([order])	Return a copy of the array.
cumprod([axis, dtype, out])	Return the cumulative product of the elements along the given axis.
cumsum([axis, dtype, out])	Return the cumulative sum of the elements along the given axis.
diagonal([offset, axis1, axis2])	Return specified diagonals.
dot(b[, out])	Dot product of two arrays.
dump(file)	Dump a pickle of the array to the specified file.
dumps()	Returns the pickle of the array as a string.
fill(value)	Fill the array with a scalar value.
flatten([order])	Return a copy of the array collapsed into one dimension.
getA()	Return self as an ndarray object.
getA1()	Return self as a flattened ndarray.
getH()	Returns the (complex) conjugate transpose of self.
getI()	Returns the (multiplicative) inverse of invertible self.
getT()	Returns the transpose of the matrix.
getfield(dtype[, offset])	Returns a field of the given array as a certain type.
item(*args)	Copy an element of an array to a standard Python scalar and return it.
itemset(*args)	Insert scalar into an array (scalar is cast to array’s dtype, if possible)
max([axis, out])	Return the maximum value along an axis.
mean([axis, dtype, out])	Returns the average of the matrix elements along the given axis.
min([axis, out])	Return the minimum value along an axis.
newbyteorder([new_order])	Return the array with the same data viewed with a different byte order.
nonzero()	Return the indices of the elements that are non-zero.
partition(kth[, axis, kind, order])	Rearranges the elements in the array in such a way that value of the element in kth position is in the position it would be in a sorted array.
prod([axis, dtype, out])	Return the product of the array elements over the given axis.
ptp([axis, out])	Peak-to-peak (maximum - minimum) value along the given axis.
put(indices, values[, mode])	Set a.flat[n] = values[n] for all n in indices.
ravel([order])	Return a flattened array.
repeat(repeats[, axis])	Repeat elements of an array.
reshape(shape[, order])	Returns an array containing the same data with a new shape.
resize(new_shape[, refcheck])	Change shape and size of array in-place.
round([decimals, out])	Return a with each element rounded to the given number of decimals.
searchsorted(v[, side, sorter])	Find indices where elements of v should be inserted in a to maintain order.
setfield(val, dtype[, offset])	Put a value into a specified place in a field defined by a data-type.
setflags([write, align, uic])	Set array flags WRITEABLE, ALIGNED, and UPDATEIFCOPY, respectively.
sort([axis, kind, order])	Sort an array, in-place.
squeeze([axis])	Remove single-dimensional entries from the shape of a.
std([axis, dtype, out, ddof])	Return the standard deviation of the array elements along the given axis.
sum([axis, dtype, out])	Returns the sum of the matrix elements, along the given axis.
swapaxes(axis1, axis2)	Return a view of the array with axis1 and axis2 interchanged.
take(indices[, axis, out, mode])	Return an array formed from the elements of a at the given indices.
tobytes([order])	Construct Python bytes containing the raw data bytes in the array.
tofile(fid[, sep, format])	Write array to a file as text or binary (default).
tolist()	Return the matrix as a (possibly nested) list.
tostring([order])	Construct Python bytes containing the raw data bytes in the array.
trace([offset, axis1, axis2, dtype, out])	Return the sum along diagonals of the array.
transpose(*axes)	Returns a view of the array with axes transposed.
var([axis, dtype, out, ddof])	Returns the variance of the matrix elements, along the given axis.
view([dtype, type])	New view of array with the same data.