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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: -
data : array_like or string -
If
datais 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
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. 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(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. -
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https://docs.scipy.org/doc/numpy-1.17.0/reference/generated/numpy.matrix.html