numpy.matrix
-
class numpy.matrix(data, dtype=None, copy=True)[source] -
Note
It is no longer recommended to use this class, even for linear algebra. Instead use regular arrays. The class may be removed in the future.
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
-
-
dataarray_like or string -
If
datais a string, it is interpreted as a matrix with commas or spaces separating columns, and semicolons separating rows. -
dtypedata-type -
Data-type of the output matrix.
-
copybool -
If
datais already anndarray, then this flag determines whether the data is copied (the default), or whether a view is constructed.
-
See also
Examples
>>> a = np.matrix('1 2; 3 4') >>> a matrix([[1, 2], [3, 4]])>>> np.matrix([[1, 2], [3, 4]]) matrix([[1, 2], [3, 4]])- Attributes
-
-
A -
Return
selfas anndarrayobject. -
A1 -
Return
selfas a flattenedndarray. -
H -
Returns the (complex) conjugate transpose of
self. -
I -
Returns the (multiplicative) inverse of invertible
self. -
T -
Returns the transpose of the matrix.
-
base -
Base object if memory is from some other object.
-
ctypes -
An object to simplify the interaction of the array with the ctypes module.
-
data -
Python buffer object pointing to the start of the array’s data.
-
dtype -
Data-type of the array’s elements.
-
flags -
Information about the memory layout of the array.
-
flat -
A 1-D iterator over the array.
-
imag -
The imaginary part of the array.
-
itemsize -
Length of one array element in bytes.
-
nbytes -
Total bytes consumed by the elements of the array.
-
ndim -
Number of array dimensions.
-
real -
The real part of the array.
-
shape -
Tuple of array dimensions.
-
size -
Number of elements in the array.
-
strides -
Tuple of bytes to step in each dimension when traversing an array.
-
Methods
all(self[, axis, out])Test whether all matrix elements along a given axis evaluate to True.
any(self[, axis, out])Test whether any array element along a given axis evaluates to True.
argmax(self[, axis, out])Indexes of the maximum values along an axis.
argmin(self[, axis, out])Indexes 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.
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(self[, order])Return a flattened copy of the matrix.
getA(self)Return
selfas anndarrayobject.getA1(self)Return
selfas a flattenedndarray.getH(self)Returns the (complex) conjugate transpose of
self.getI(self)Returns the (multiplicative) inverse of invertible
self.getT(self)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(self[, axis, out])Return the maximum value along an axis.
mean(self[, axis, dtype, out])Returns the average of the matrix elements along the given axis.
min(self[, 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 the value of the element in kth position is in the position it would be in a sorted array.
prod(self[, axis, dtype, out])Return the product of the array elements over the given axis.
ptp(self[, axis, out])Peak-to-peak (maximum - minimum) value along the given axis.
put(indices, values[, mode])Set
a.flat[n] = values[n]for allnin indices.ravel(self[, 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
awith 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, (WRITEBACKIFCOPY and UPDATEIFCOPY), respectively.
sort([axis, kind, order])Sort an array in-place.
squeeze(self[, axis])Return a possibly reshaped matrix.
std(self[, axis, dtype, out, ddof])Return the standard deviation of the array elements along the given axis.
sum(self[, axis, dtype, out])Returns the sum of the matrix elements, along the given axis.
swapaxes(axis1, axis2)Return a view of the array with
axis1andaxis2interchanged.take(indices[, axis, out, mode])Return an array formed from the elements of
aat 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(self)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(self[, 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.
© 2005–2020 NumPy Developers
Licensed under the 3-clause BSD License.
https://numpy.org/doc/1.18/reference/generated/numpy.matrix.html