- 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).
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
>>> a = np.matrix('1 2; 3 4') >>> print a [[1 2] [3 4]]
>>> np.matrix([[1, 2], [3, 4]]) matrix([[1, 2], [3, 4]])
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([min, max, out]) Return an array whose values are limited to [min, 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 flattened copy of the matrix. 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 matrix. 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]) Return a possibly reshaped matrix. 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.