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Method argpartition
NumPy Random Generator4 topics
Method choiceMethod dotMethod finfoMethod histogramMethod iinfoMethod maxMethod meanMethod placeMethod rootsMethod seedMethod uniformMethod viewMethod zerosMethod sumObject busdaycalendarMethod is_busdayProperty dtypeMethod uniqueMethod loadtxtMethod vsplitMethod fliplrMethod setdiff1dMethod msortMethod argsortMethod lexsortMethod aroundMethod nanmaxMethod nanminMethod nanargmaxMethod nanargminMethod argmaxMethod argminProperty itemsizeMethod spacingMethod fixMethod ceilMethod diffProperty flatProperty realProperty baseMethod flipMethod deleteMethod amaxMethod aminMethod logical_xorMethod logical_orMethod logical_notMethod logical_andMethod logaddexpMethod logaddexp2Method logspaceMethod not_equalMethod equalMethod greater_equalMethod lessMethod less_equalMethod remainderMethod modMethod emptyMethod greaterMethod isfiniteMethod busday_countMethod repeatMethod varMethod random_sampleMethod randomMethod signMethod stdMethod absoluteMethod absMethod sortMethod randintMethod isrealMethod linspaceMethod gradientMethod allMethod sampleProperty TProperty imagMethod covMethod insertMethod logMethod log1pMethod exp2Method expm1Method expMethod arccosMethod cosMethod arcsinMethod sinMethod tanMethod fromiterMethod trim_zerosMethod diagflatMethod savetxtMethod count_nonzeroProperty sizeProperty shapeMethod reshapeMethod resizeMethod triuMethod trilMethod eyeMethod arangeMethod fill_diagonalMethod tileMethod saveMethod transposeMethod swapaxesMethod meshgridProperty mgridMethod rot90Method log2Method radiansMethod deg2radMethod rad2degMethod degreesMethod log10Method appendMethod cumprodProperty nbytesMethod tostringProperty dataMethod modfMethod fmodMethod tolistMethod datetime_as_stringMethod datetime_dataMethod array_splitMethod itemsetMethod floorMethod put_along_axisMethod cumsumMethod bincountMethod putMethod putmaskMethod takeMethod hypotMethod sqrtMethod squareMethod floor_divideMethod triMethod signbitMethod flattenMethod ravelMethod rollMethod isrealobjMethod diagMethod diagonalMethod quantileMethod onesMethod iscomplexobjMethod iscomplexMethod isscalarMethod divmodMethod isnatMethod percentileMethod isnanMethod divideMethod addMethod reciprocalMethod positiveMethod subtractMethod medianMethod isneginfMethod isposinfMethod float_powerMethod powerMethod negativeMethod maximumMethod averageMethod isinfMethod multiplyMethod busday_offsetMethod identityMethod interpMethod squeezeMethod get_printoptionsMethod savez_compressedMethod savezMethod loadMethod asfarrayMethod clipMethod arrayMethod array_equivMethod array_equalMethod frombufferMethod set_string_functionMethod matmulMethod genfromtxtMethod fromfunctionMethod asscalarMethod searchsortedMethod full_likeMethod fullMethod shares_memoryMethod ptpMethod digitizeMethod argwhereMethod geomspaceMethod zeros_likeMethod fabsMethod flatnonzeroMethod vstackMethod dstackMethod fromstringMethod tobytesMethod expand_dimsMethod ranfMethod arctanMethod itemMethod extractMethod compressMethod chooseMethod asarrayMethod asmatrixMethod allcloseMethod iscloseMethod anyMethod corrcoefMethod truncMethod prodMethod crossMethod true_divideMethod hsplitMethod splitMethod rintMethod ediff1dMethod lcmMethod gcdMethod cbrtMethod flipudProperty ndimMethod array2stringMethod set_printoptionsMethod whereMethod hstack
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chevron_left Documentation
Method argpartition
NumPy Random Generator4 topics
Method choiceMethod dotMethod finfoMethod histogramMethod iinfoMethod maxMethod meanMethod placeMethod rootsMethod seedMethod uniformMethod viewMethod zerosMethod sumObject busdaycalendarMethod is_busdayProperty dtypeMethod uniqueMethod loadtxtMethod vsplitMethod fliplrMethod setdiff1dMethod msortMethod argsortMethod lexsortMethod aroundMethod nanmaxMethod nanminMethod nanargmaxMethod nanargminMethod argmaxMethod argminProperty itemsizeMethod spacingMethod fixMethod ceilMethod diffProperty flatProperty realProperty baseMethod flipMethod deleteMethod amaxMethod aminMethod logical_xorMethod logical_orMethod logical_notMethod logical_andMethod logaddexpMethod logaddexp2Method logspaceMethod not_equalMethod equalMethod greater_equalMethod lessMethod less_equalMethod remainderMethod modMethod emptyMethod greaterMethod isfiniteMethod busday_countMethod repeatMethod varMethod random_sampleMethod randomMethod signMethod stdMethod absoluteMethod absMethod sortMethod randintMethod isrealMethod linspaceMethod gradientMethod allMethod sampleProperty TProperty imagMethod covMethod insertMethod logMethod log1pMethod exp2Method expm1Method expMethod arccosMethod cosMethod arcsinMethod sinMethod tanMethod fromiterMethod trim_zerosMethod diagflatMethod savetxtMethod count_nonzeroProperty sizeProperty shapeMethod reshapeMethod resizeMethod triuMethod trilMethod eyeMethod arangeMethod fill_diagonalMethod tileMethod saveMethod transposeMethod swapaxesMethod meshgridProperty mgridMethod rot90Method log2Method radiansMethod deg2radMethod rad2degMethod degreesMethod log10Method appendMethod cumprodProperty nbytesMethod tostringProperty dataMethod modfMethod fmodMethod tolistMethod datetime_as_stringMethod datetime_dataMethod array_splitMethod itemsetMethod floorMethod put_along_axisMethod cumsumMethod bincountMethod putMethod putmaskMethod takeMethod hypotMethod sqrtMethod squareMethod floor_divideMethod triMethod signbitMethod flattenMethod ravelMethod rollMethod isrealobjMethod diagMethod diagonalMethod quantileMethod onesMethod iscomplexobjMethod iscomplexMethod isscalarMethod divmodMethod isnatMethod percentileMethod isnanMethod divideMethod addMethod reciprocalMethod positiveMethod subtractMethod medianMethod isneginfMethod isposinfMethod float_powerMethod powerMethod negativeMethod maximumMethod averageMethod isinfMethod multiplyMethod busday_offsetMethod identityMethod interpMethod squeezeMethod get_printoptionsMethod savez_compressedMethod savezMethod loadMethod asfarrayMethod clipMethod arrayMethod array_equivMethod array_equalMethod frombufferMethod set_string_functionMethod matmulMethod genfromtxtMethod fromfunctionMethod asscalarMethod searchsortedMethod full_likeMethod fullMethod shares_memoryMethod ptpMethod digitizeMethod argwhereMethod geomspaceMethod zeros_likeMethod fabsMethod flatnonzeroMethod vstackMethod dstackMethod fromstringMethod tobytesMethod expand_dimsMethod ranfMethod arctanMethod itemMethod extractMethod compressMethod chooseMethod asarrayMethod asmatrixMethod allcloseMethod iscloseMethod anyMethod corrcoefMethod truncMethod prodMethod crossMethod true_divideMethod hsplitMethod splitMethod rintMethod ediff1dMethod lcmMethod gcdMethod cbrtMethod flipudProperty ndimMethod array2stringMethod set_printoptionsMethod whereMethod hstack
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NumPy | matmul Method

NumPy
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schedule Jul 1, 2022
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Numpy's matmul(~) method is used to perform compute the product of two arrays. These arrays can be vectors, matrices and even higher dimensions.

NOTE

matmul(~) is strikingly similar to Numpy's dot(~) method. The difference is as follows:

  • matmul(~) does not support scalar multiplications, while dot(~) does.

  • matmul(~) method is preferred over Numpy's dot(~) method when you need to perform matrix multiplication.

Parameters

1. a | array_like

✜ The first argument.

2. b | array_like

✜ The second argument.

Return value

The following table succinctly summaries what operation is performed as well as the return type:

a

b

operation

Return type

1D array

1D array

Vector dot product

number

2D array

1D array

Matrix-vector product

1D Numpy array

2D array

2D array

Matrix-matrix multiplication

2D Numpy array

n-D array

n-D array

Batch products

n-D Numpy array

Examples

Matrix-vector product

x = [[1,0], [0,1]]
y = [5,5]
np.matmul(x,y)
array([5, 5])

Mathematically, we're doing the following:

$$\begin{pmatrix} 1&0\\ 0&1\\ \end{pmatrix} \begin{pmatrix} 5\\ 5\\ \end{pmatrix}= \begin{pmatrix}5\\ 5\\ \end{pmatrix}$$

Matrix-matrix product

x = [[1,0], [0,1]]
y = [[2,2], [2,2]]
np.matmul(x,y)
array([[2, 2],
[2, 2]])

Mathematically, we're doing the following:

$$\begin{pmatrix} 1&0\\ 0&1\\ \end{pmatrix} \begin{pmatrix} 2&2\\ 2&2\\ \end{pmatrix}= \begin{pmatrix} 2&2\\ 2&2\\ \end{pmatrix}$$

Always remember that parameters just need to be array-like; we can use Numpy arrays as well:

x = np.array([[1,0], [0,1]])
y = np.array([[2,2], [2,2]])
np.matmul(x, y)
array([[2, 2],
[2, 2]])

Batch products

The matmul(~) method can be used to compute multiple products at once, like follows:

x = [ [[1,0], [0,1]], [[1,1], [1,1]] ]
y = [3,4]
np.matmul(x,y)
array([[3, 4],
[7, 7]])

In this example, the variable x holds the following two matrices:

$$\begin{pmatrix} 1&0\\ 0&1\\ \end{pmatrix} \;\;\;\; \begin{pmatrix} 1&1\\ 1&1\\ \end{pmatrix}$$

The final line, np.matmul(x,y), is performing the following mathematical operations:

$$\begin{pmatrix} 1&0\\ 0&1\\ \end{pmatrix} \begin{pmatrix} 3\\ 4\\ \end{pmatrix}= \begin{pmatrix} 3\\ 4\\ \end{pmatrix}$$
$$\begin{pmatrix} 1&1\\ 1&1\\ \end{pmatrix} \begin{pmatrix} 3\\ 4\\ \end{pmatrix}= \begin{pmatrix} 7\\ 7\\ \end{pmatrix}$$

Note that batch products also for vector-vector product and matrix-matrix product as wel

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Published by Isshin Inada
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