NumPy Operator Coverage Status

Universal Functions (ufunc)

Math operations

opdescriptionstatusnote
numpy.subtractSubtracts arguments elementwise.Done
numpy.multiplyMultiplies two arrays elementwise.Done
numpy.divideElementwise true division (i.e.Done
numpy.logaddexpComputes `log(exp(x1)` `+` `exp(x2))` elementwise.DonePR15495
numpy.logaddexp2Computes `log2(exp2(x1)` `+` `exp2(x2))` elementwise.DonePR15494
numpy.true_divideElementwise true division (i.e.DoneNeed a frontend interface called np.true_divide
numpy.floor_divideElementwise floor division (i.e.Code Reviewhttps://github.com/apache/incubator-mxnet/pull/16124
numpy.negativeTakes numerical negative elementwise.Code Reviewhttps://github.com/apache/incubator-mxnet/pull/16151
numpy.powerComputes `x1` `**` `x2` elementwise.Done
numpy.remainderComputes the remainder of Python division elementwise.DonePR16080
numpy.modComputes the remainder of Python division elementwise.Done
numpy.fmodComputes the remainder of C division elementwise.
numpy.absoluteElementwise absolute value function.Doneabs
numpy.rintRounds each element of an array to the nearest integer.Done
numpy.signElementwise sign function.Done
numpy.expElementwise exponential function.Done
numpy.exp2Elementwise exponentiation with base 2.DonePR15973
numpy.logElementwise natural logarithm function.Done
numpy.log2Elementwise binary logarithm function.Done
numpy.log10Elementwise common logarithm function.Done
numpy.expm1Computes `exp(x)` `-` `1` elementwise.Done
numpy.log1pComputes `log(1` `+` `x)` elementwise.Done
numpy.sqrtElementwise square root function.Done
numpy.squareElementwise square function.Done
numpy.reciprocalComputes `1` `/` `x` elementwise.Done

Trigonometric functions

opdescriptionstatusnote
numpy.sinElementwise sine function.Done
numpy.cosElementwise cosine function.Done
numpy.tanElementwise tangent function.Done
numpy.arcsinElementwise inverse-sine function (a.k.a.Done
numpy.arccosElementwise inverse-cosine function (a.k.a.Done
numpy.arctanElementwise inverse-tangent function (a.k.a.Done
numpy.arctan2Elementwise inverse-tangent of the ratio of two arrays.DonePR15519
numpy.hypotComputes the hypoteneous of orthogonal vectors of given length.Code ReviewPR15901
numpy.sinhElementwise hyperbolic sine function.Done
numpy.coshElementwise hyperbolic cosine function.Done
numpy.tanhElementwise hyperbolic tangent function.Done
numpy.arcsinhElementwise inverse of hyperbolic sine function.Done
numpy.arccoshElementwise inverse of hyperbolic cosine function.Done
numpy.arctanhElementwise inverse of hyperbolic tangent function.Done

Bit-twiddling functions

opdescriptionstatusnote
numpy.bitwise_andComputes the bitwise AND of two arrays elementwise.
numpy.bitwise_orComputes the bitwise OR of two arrays elementwise.Code ReviewPR15293
numpy.bitwise_xorComputes the bitwise XOR of two arrays elementwise.Code ReviewPR15312
numpy.invertComputes the bitwise NOT of an array elementwise.
numpy.left_shiftShifts the bits of each integer element to the left.
numpy.right_shiftShifts the bits of each integer element to the right.

Comparison functions

opdescriptionstatusnote
numpy.greaterTests elementwise if `x1` `>` `x2`.Donehttps://github.com/apache/incubator-mxnet/pull/15940
numpy.greater_equalTests elementwise if `x1` `>=` `x2`.Done
numpy.lessTests elementwise if `x1` `<` `x2`.Done
numpy.less_equalTests elementwise if `x1` `<=` `x2`.Done
numpy.not_equalTests elementwise if `x1` `!=` `x2`.Done
numpy.equalTests elementwise if `x1` `==` `x2`.Done
numpy.logical_andComputes the logical AND of two arrays.
numpy.logical_orComputes the logical OR of two arrays.
numpy.logical_xorComputes the logical XOR of two arrays.
numpy.logical_notComputes the logical NOT of an array.Done
numpy.maximumTakes the maximum of two arrays elementwise.Done
numpy.minimumTakes the minimum of two arrays elementwise.Done
numpy.fmaxTakes the maximum of two arrays elementwise.
numpy.fminTakes the minimum of two arrays elementwise.

Floating functions

opdescriptionstatusnote
numpy.isfiniteTests finiteness elementwise.
numpy.isinfTests if each element is the positive or negative infinity.
numpy.isnanTests if each element is a NaN.
numpy.signbitTests elementwise if the sign bit is set (i.e.
numpy.copysignReturns the first argument with the sign bit of the second elementwise.Done
numpy.nextafterComputes the nearest neighbor float values towards the second argument.
numpy.modfExtracts the fractional and integral parts of an array elementwise.
numpy.ldexpComputes `x1` `*` `2` `**` `x2` elementwise.Code Reviewhttps://github.com/apache/incubator-mxnet/pull/15845
numpy.frexpDecomposes each element to mantissa and two’s exponent.
numpy.fmodComputes the remainder of C division elementwise.
numpy.floorRounds each element of an array to its floor integer.Done
numpy.ceilRounds each element of an array to its ceiling integer.Done
numpy.truncRounds each element of an array towards zero.Done

Array Creation Routines

Basic creation routines

opdescriptionstatusnote
numpy.emptyReturns an array without initializing the elements.Done
numpy.empty_likeReturns a new array with same shape and dtype of a given array.
numpy.eyeReturns a 2-D array with ones on the diagonals and zeros elsewhere.Done
numpy.identityReturns a 2-D identity array.DonePR15698
numpy.onesReturns a new array of given shape and dtype, filled with ones.Done
numpy.ones_likeReturns an array of ones with same shape and dtype as a given array.Done
numpy.zerosReturns a new array of given shape and dtype, filled with zeros.Done
numpy.zeros_likeReturns an array of zeros with same shape and dtype as a given array.Done
numpy.fullReturns a new array of given shape and dtype, filled with a given value.DonePR15763
numpy.full_likeReturns a full array with same shape and dtype as a given array.

Creation from other data

opdescriptionstatusnote
numpy.arrayCreates an array on the current device.Done
numpy.asarrayConverts an object to array.
numpy.asanyarrayConverts an object to array.
numpy.ascontiguousarrayReturns a C-contiguous array.
numpy.copyCreates a copy of a given array on the current device.Done

Numerical ranges

opdescriptionstatusnote
numpy.arangeReturns an array with evenly spaced values within a given interval.Done
numpy.linspaceReturns an array with evenly-spaced values within a given interval.Done
numpy.logspaceReturns an array with evenly-spaced values on a log-scale.DonePR15825
numpy.meshgridReturn coordinate matrices from coordinate vectors.Done
numpy.mgridConstruct a multi-dimensional “meshgrid”.Cod Reviewhttps://github.com/apache/incubator-mxnet/pull/16171
numpy.ogridConstruct a multi-dimensional “meshgrid”.Code Reviewhttps://github.com/apache/incubator-mxnet/pull/16171

Matrix creation

opdescriptionstatusnote
numpy.diagReturns a diagonal or a diagonal array.
numpy.diagflatCreates a diagonal array from the flattened input.
numpy.triCreates an array with ones at and below the given diagonal.
numpy.trilReturns a lower triangle of an array.DonePR15696
numpy.triuReturns an upper triangle of an array.

Array Manipulation Routines

Basic operations

opdescriptionstatusnote
numpy.copytoCopies values from one array to another with broadcasting.Doneonly convenient mode

Changing array shape

opdescriptionstatusnote
numpy.reshapeReturns an array with new shape and same elements.Done
numpy.ravelReturns a flattened array.

Transpose-like operations

opdescriptionstatusnote
numpy.moveaxisMoves axes of an array to new positions.DonePR15826
numpy.rollaxisMoves the specified axis backwards to the given place.
numpy.swapaxesSwaps the two axes.Done
numpy.transposePermutes the dimensions of an array.Done

Changing number of dimensions

opdescriptionstatusnote
numpy.atleast_1dConverts arrays to arrays with dimensions >= 1.
numpy.atleast_2dConverts arrays to arrays with dimensions >= 2.
numpy.atleast_3dConverts arrays to arrays with dimensions >= 3.
numpy.expand_dimsExpands given arrays.Done
numpy.squeezeRemoves size-one axes from the shape of an array.Done

Changing kind of array

opdescriptionstatusnote
numpy.asarrayConverts an object to array.
numpy.asanyarrayConverts an object to array.
numpy.asfortranarrayReturn an array laid out in Fortran order in memory.
numpy.ascontiguousarrayReturns a C-contiguous array.

Joining arrays

opdescriptionstatusnote
numpy.concatenateJoins arrays along an axis.Done
numpy.stackStacks arrays along a new axis.Done
numpy.column_stackStacks 1-D and 2-D arrays as columns into a 2-D array.
numpy.dstackStacks arrays along the third axis.DonePR15314
numpy.hstackStacks arrays horizontally.PR15302. Need to port to master branch.
numpy.vstackStacks arrays vertically.Donehttps://github.com/apache/incubator-mxnet/pull/15850

Splitting arrays

opdescriptionstatusnote
numpy.splitSplits an array into multiple sub arrays along a given axis.Done
numpy.array_splitSplits an array into multiple sub arrays along a given axis.
numpy.dsplitSplits an array into multiple sub arrays along the third axis.DonePR15371
numpy.hsplitSplits an array into multiple sub arrays horizontally.DonePR15358
numpy.vsplitSplits an array into multiple sub arrays along the first axis.DonePR15346

Tiling arrays

opdescriptionstatusnote
numpy.tileConstruct an array by repeating A the number of times given by reps.Done
numpy.repeatRepeat arrays along an axis.Partially done.Need to support `repeats` as a list of integers.

opdescriptionstatusnote
numpy.uniqueFind the unique elements of an array.Code Reviewhttps://github.com/apache/incubator-mxnet/pull/15821

Rearranging elements

opdescriptionstatusnote
numpy.flipReverse the order of elements in an array along the given axis.DonePR15586
numpy.fliplrFlip array in the left/right direction.
numpy.flipudFlip array in the up/down direction.
numpy.reshapeReturns an array with new shape and same elements.Done
numpy.rollRoll array elements along a given axis.DonePR15902
numpy.rot90Rotate an array by 90 degrees in the plane specified by axes.DonePR15987

Binary OperationsElementwise bit operations

opdescriptionstatusnote
numpy.bitwise_andComputes the bitwise AND of two arrays elementwise.
numpy.bitwise_orComputes the bitwise OR of two arrays elementwise.
numpy.bitwise_xorComputes the bitwise XOR of two arrays elementwise.
numpy.invertComputes the bitwise NOT of an array elementwise.
numpy.left_shiftShifts the bits of each integer element to the left.
numpy.right_shiftShifts the bits of each integer element to the right.

Bit packing

opdescriptionstatusnote
numpy.packbitsPacks the elements of a binary-valued array into bits in a uint8 array.
numpy.unpackbitsUnpacks elements of a uint8 array into a binary-valued output array.

Output formatting

opdescriptionstatusnote
numpy.binary_reprReturn the binary representation of the input number as a string.

FFT Functions

Standard FFTs

opdescriptionstatusnote
numpy.fft.fftCompute the one-dimensional FFT.WIP
numpy.fft.ifftCompute the one-dimensional inverse FFT.WIP
numpy.fft.fft2Compute the two-dimensional FFT.
numpy.fft.ifft2Compute the two-dimensional inverse FFT.
numpy.fft.fftnCompute the N-dimensional FFT.
numpy.fft.ifftnCompute the N-dimensional inverse FFT.

Real FFTs

opdescriptionstatusnote
numpy.fft.rfftCompute the one-dimensional FFT for real input.
numpy.fft.irfftCompute the one-dimensional inverse FFT for real input.
numpy.fft.rfft2Compute the two-dimensional FFT for real input.
numpy.fft.irfft2Compute the two-dimensional inverse FFT for real input.
numpy.fft.rfftnCompute the N-dimensional FFT for real input.
numpy.fft.irfftnCompute the N-dimensional inverse FFT for real input.

Hermitian FFTs

opdescriptionstatusnote
numpy.fft.hfftCompute the FFT of a signal that has Hermitian symmetry.
numpy.fft.ihfftCompute the FFT of a signal that has Hermitian symmetry.

Helper routines

opdescriptionstatusnote
numpy.fft.fftfreqReturn the FFT sample frequencies.
numpy.fft.rfftfreqReturn the FFT sample frequencies for real input.
numpy.fft.fftshiftShift the zero-frequency component to the center of the spectrum.
numpy.fft.ifftshiftThe inverse of [``fftshift()

Indexing Routines

opdescriptionstatusnote
numpy.c_
numpy.r_
numpy.nonzeroReturn the indices of the elements that are non-zero.
numpy.whereReturn elements, either from x or y, depending on condition.
numpy.indicesReturns an array representing the indices of a grid.
numpy.ix_i
numpy.unravel_indexConverts array of flat indices into a tuple of coordinate arrays.
numpy.takeTakes elements of an array at specified indices along an axis.Done
numpy.choose
numpy.diagReturns a diagonal or a diagonal array.
numpy.diagonalReturns specified diagonals.
numpy.lib.stride_tricks.as_stridedCreate a view into the array with the given shape and strides.
numpy.placeChange elements of an array based on conditional and input values.
numpy.putReplaces specified elements of an array with given values.
numpy.fill_diagonalFills the main diagonal of the given array of any dimensionality.

Input and Output

NumPy binary files (NPY, NPZ)

opdescriptionstatusnote
numpy.loadLoads arrays or pickled objects from `.npy`, `.npz` or pickled file.DoneKnown as npx.load
numpy.saveSaves an array to a binary file in `.npy` format.DoneKnown as npx.save
numpy.savezSaves one or more arrays into a file in uncompressed `.npz` format.
numpy.savez_compressedSaves one or more arrays into a file in compressed `.npz` format.

String formatting

opdescriptionstatusnote
numpy.array_reprReturns the string representation of an array.Built-in repr ready.
numpy.array_strReturns the string representation of the content of an array.Built-in str ready.

Base-n representations

opdescriptionstatusnote
numpy.binary_reprReturn the binary representation of the input number as a string.
numpy.base_reprReturn a string representation of a number in the given base system.

Linear Algebra

Matrix and vector products

opdescriptionstatusnote
numpy.dotReturns a dot product of two arrays.Done
numpy.vdotReturns the dot product of two vectors.Donehttps://github.com/apache/incubator-mxnet/pull/15846
numpy.innerReturns the inner product of two arrays.Donehttps://github.com/apache/incubator-mxnet/pull/15846
numpy.outerReturns the outer product of two vectors.Donehttps://github.com/apache/incubator-mxnet/pull/15846
numpy.matmulReturns the matrix product of two arrays and is the implementation of the @ operator introduced in Python 3.5 following PEP465.dep: einsum
numpy.tensordotReturns the tensor dot product of two arrays along specified axes.DonePR15349
numpy.einsumEvaluates the Einstein summation convention on the operands.DonePR15493. Depends on fixing the legacy bug of using multiple temp spaces on GPUs. See issue 15732.
numpy.linalg.matrix_powerRaise a square matrix to the (integer) power n.dep: matmul
numpy.kronReturns the kronecker product of two arrays.DonePR15893

Decompositions

opdescriptionstatusnote
numpy.linalg.choleskyCholesky decomposition.
numpy.linalg.qrQR decomposition.
numpy.linalg.svdSingular Value Decomposition.wip

Matrix eigenvalues

opdescriptionstatusnote
numpy.linalg.eighEigenvalues and eigenvectors of a symmetric matrix.
numpy.linalg.eigvalshCalculates eigenvalues of a symmetric matrix.

Norms etc.

opdescriptionstatusnote
numpy.linalg.detRetruns the deteminant of an array.Done
numpy.linalg.normReturns one of matrix norms specified by `ord` parameter.Done
numpy.linalg.matrix_rankReturn matrix rank of array using SVD method
numpy.linalg.slogdetReturns sign and logarithm of the determinant of an array.Done
numpy.traceReturns the sum along the diagonals of an array.DonePR15258

Solving linear equations

opdescriptionstatusnote
numpy.linalg.solveSolves a linear matrix equation.
numpy.linalg.tensorsolveSolves tensor equations denoted by `ax` `=` `b`.
numpy.linalg.invComputes the inverse of a matrix.
numpy.linalg.pinvCompute the Moore-Penrose pseudoinverse of a matrix.
numpy.linalg.tensorinvComputes the inverse of a tensor.

Logic Functions

Truth value testing

opdescriptionstatusnote
numpy.allTests whether all array elements along a given axis evaluate to True.
numpy.anyTests whether any array elements along a given axis evaluate to True.

Infinities and NaNs

opdescriptionstatusnote
numpy.isfiniteTests finiteness elementwise.
numpy.isinfTests if each element is the positive or negative infinity.
numpy.isnanTests if each element is a NaN.

Array type testing

opdescriptionstatusnote
numpy.iscomplexReturns a bool array, where True if input element is complex.
numpy.iscomplexobjCheck for a complex type or an array of complex numbers.
numpy.isfortranReturns True if the array is Fortran contiguous but not C contiguous.
numpy.isrealReturns a bool array, where True if input element is real.
numpy.isrealobjReturn True if x is a not complex type or an array of complex numbers.
numpy.isscalarReturns True if the type of num is a scalar type.

Logic operations

opdescriptionstatusnote
numpy.logical_andComputes the logical AND of two arrays.
numpy.logical_orComputes the logical OR of two arrays.
numpy.logical_notComputes the logical NOT of an array.Done
numpy.logical_xorComputes the logical XOR of two arrays.

Comparison

opdescriptionstatusnote
numpy.allcloseReturns True if two arrays are element-wise equal within a tolerance.
numpy.iscloseReturns a boolean array where two arrays are equal within a tolerance.
numpy.greaterTests elementwise if `x1` `>` `x2`.DoneRe-implement to return boolean ndarray
numpy.greater_equalTests elementwise if `x1` `>=` `x2`.Done
numpy.lessTests elementwise if `x1` `<` `x2`.Done
numpy.less_equalTests elementwise if `x1` `<=` `x2`.Done
numpy.equalTests elementwise if `x1` `==` `x2`.Done
numpy.not_equalTests elementwise if `x1` `!=` `x2`.Done

Mathematical Functions

Trigonometric functions

opdescriptionstatusnote
numpy.sinElementwise sine function.Done
numpy.cosElementwise cosine function.Done
numpy.tanElementwise tangent function.Done
numpy.arcsinElementwise inverse-sine function (a.k.a.Done
numpy.arccosElementwise inverse-cosine function (a.k.a.Done
numpy.arctanElementwise inverse-tangent function (a.k.a.Done
numpy.hypotComputes the hypoteneous of orthogonal vectors of given length.PR15901
numpy.arctan2Elementwise inverse-tangent of the ratio of two arrays.DonePR15890
numpy.degreesConverts angles from radians to degrees elementwise.Done
numpy.unwrapUnwrap by changing deltas between values to 2*pi complement.

Hyperbolic functions

opdescriptionstatusnote
numpy.sinhElementwise hyperbolic sine function.Done
numpy.coshElementwise hyperbolic cosine function.Done
numpy.tanhElementwise hyperbolic tangent function.Done
numpy.arcsinhElementwise inverse of hyperbolic sine function.Done
numpy.arccoshElementwise inverse of hyperbolic cosine function.Done
numpy.arctanhElementwise inverse of hyperbolic tangent function.Done

Rounding

opdescriptionstatusnote
numpy.aroundRounds to the given number of decimals.
numpy.round_
numpy.rintRounds each element of an array to the nearest integer.Done
numpy.fixIf given value x is positive, it return floor(x).Done
numpy.floorRounds each element of an array to its floor integer.Done
numpy.ceilRounds each element of an array to its ceiling integer.Done
numpy.truncRounds each element of an array towards zero.Done

Sums, products, differences

opdescriptionstatusnote
numpy.prodReturns the product of an array along given axes.Done
numpy.sumReturns the sum of an array along given axes.Done
numpy.cumprodReturns the cumulative product of an array along a given axis.DonePR15855
numpy.cumsumReturns the cumulative sum of an array along a given axis.DonePR15309
numpy.diffCalculate the n-th discrete difference along the given axis.DonePR15906

Exponents and logarithms

opdescriptionstatusnote
`numpy.exp`Elementwise exponential function.Done
`numpy.expm1`Computes `exp(x)` `-` `1` elementwise.Done
numpy.exp2Elementwise exponentiation with base 2.WIP sguangyo@
numpy.logElementwise natural logarithm function.Done
numpy.log10Elementwise common logarithm function.Done
numpy.log2Elementwise binary logarithm function.Done
numpy.log1pComputes `log(1` `+` `x)` elementwise.Done
numpy.logaddexpComputes `log(exp(x1)` `+` `exp(x2))` elementwise.Done
numpy.logaddexp2Computes `log2(exp2(x1)` `+` `exp2(x2))` elementwise.Done

Other special functions

opdescriptionstatusnote
numpy.i0Modified Bessel function of the first kind, order 0.
numpy.sincElementwise sinc function.

Floating point routines

opdescriptionstatusnote
numpy.signbitTests elementwise if the sign bit is set (i.e.
numpy.copysignReturns the first argument with the sign bit of the second elementwise.
numpy.frexpDecomposes each element to mantissa and two’s exponent.
numpy.ldexpComputes `x1` `*` `2` `**` `x2` elementwise.
numpy.nextafterComputes the nearest neighbor float values towards the second argument.

Arithmetic operations

opdescriptionstatusnote
numpy.reciprocalComputes `1` `/` `x` elementwise.Done
numpy.negativeTakes numerical negative elementwise.Done
numpy.multiplyMultiplies two arrays elementwise.Done
numpy.divideElementwise true division (i.e.Done
numpy.powerComputes `x1` `**` `x2` elementwise.Done@wangleyu
numpy.subtractSubtracts arguments elementwise.Done
numpy.true_divideElementwise true division (i.e.Done
numpy.floor_divideElementwise floor division (i.e.Done
numpy.fmodComputes the remainder of C division elementwise.
numpy.modComputes the remainder of Python division elementwise.Done
numpy.modfExtracts the fractional and integral parts of an array elementwise.
numpy.remainderComputes the remainder of Python division elementwise.Done
numpy.divmod

Handling complex numbers

opdescriptionstatusnote
numpy.angleReturns the angle of the complex argument.
numpy.realReturns the real part of the elements of the array.
numpy.imagReturns the imaginary part of the elements of the array.
numpy.conjReturns the complex conjugate, element-wise.

Miscellaneous

opdescriptionfinishnote
numpy.clipClips the values of an array to a given interval.Partially doneDoes not support a_min and a_max as arrays.
numpy.sqrtElementwise square root function.Done
numpy.cbrtElementwise cube root function.Done
numpy.squareElementwise square function.Done
numpy.absoluteElementwise absolute value function.Done
numpy.signElementwise sign function.Done
numpy.maximumTakes the maximum of two arrays elementwise.Done
numpy.minimumTakes the minimum of two arrays elementwise.Done
numpy.fmaxTakes the maximum of two arrays elementwise.WIP(tvm) guangtai@ #15800
numpy.fminTakes the minimum of two arrays elementwise.
numpy.nan_to_numElementwise nan_to_num function.
numpy.blackmanReturns the Blackman window.DonePR15815
numpy.hammingReturns the Hamming window.Done
numpy.hanningReturns the Hanning window.Done

opdescriptionstatusnote

Random Sampling (`**`numpy.random`**`)

Sample random data

opdescriptionstatusnote
numpy.random.randReturns an array of uniform random values over the interval `[0,` `1)`.
numpy.random.randnReturns an array of standard normal random values.
numpy.random.randintReturns a scalar or an array of integer values over `[low,` `high)`.Done
numpy.random.random_integersReturn a scalar or an array of integer values over `[low,` `high]`
numpy.random.random_sampleReturns an array of random values over the interval `[0,` `1)`.
numpy.random.randomReturns an array of random values over the interval `[0,` `1)`.
numpy.random.ranfReturns an array of random values over the interval `[0,` `1)`.
numpy.random.sampleReturns an array of random values over the interval `[0,` `1)`.
numpy.random.choiceReturns an array of random values from a given 1-D array.Done
numpy.random.bytesReturns random bytes.

Distributions

opdescriptionstatusnote
numpy.random.betaBeta distribution.
numpy.random.binomialBinomial distribution.
numpy.random.chisquareChi-square distribution.
numpy.random.dirichletDirichlet distribution.
numpy.random.exponentialExponential distribution.
numpy.random.fF distribution.
numpy.random.gammaGamma distribution.WIP
numpy.random.geometricGeometric distribution.
numpy.random.gumbelReturns an array of samples drawn from a Gumbel distribution.
numpy.random.hypergeometrichypergeometric distribution.
numpy.random.laplaceLaplace distribution.
numpy.random.logisticLogistic distribution.
numpy.random.lognormalReturns an array of samples drawn from a log normal distribution.
numpy.random.logseriesLog series distribution.
numpy.random.multinomialReturns an array from multinomial distribution.Done
numpy.random.multivariate_normal(experimental) Multivariate normal distribution.
numpy.random.negative_binomialNegative binomial distribution.
numpy.random.noncentral_chisquareNoncentral chisquare distribution.
numpy.random.noncentral_fNoncentral F distribution.
numpy.random.normalReturns an array of normally distributed samples.Done
numpy.random.paretoPareto II or Lomax distribution.
numpy.random.poissonPoisson distribution.
numpy.random.powerPower distribution.
numpy.random.rayleighRayleigh distribution.
numpy.random.standard_cauchyStandard cauchy distribution.
numpy.random.standard_exponentialStandard exponential distribution.
numpy.random.standard_gammaStandard gamma distribution.
numpy.random.standard_normalReturns an array of samples drawn from the standard normal distribution.
numpy.random.standard_tStandard Student’s t distribution.
numpy.random.triangularTriangular distribution.
numpy.random.uniformReturns an array of uniformly-distributed samples over an interval.Done
numpy.random.vonmisesvon Mises distribution.
numpy.random.waldWald distribution.
numpy.random.weibullweibull distribution.
numpy.random.zipfZipf distribution.

Random generator

opdescriptionstatusnote
numpy.random.RandomStatePortable container of a pseudo-random number generator.
numpy.random.seedResets the state of the random number generator with a seed.Known as npx.seed
numpy.random.get_random_stateGets the state of the random number generator for the current device.
numpy.random.set_random_stateSets the state of the random number generator for the current device.

Permutations

opdescriptionstatusnote
numpy.random.shuffleShuffles an array.Done
numpy.random.permutationReturns a permuted range or a permutation of an array.

Sorting, Searching, and Counting

Sorting

opdescriptionstatusnote
numpy.sortReturns a sorted copy of an array with a stable sorting algorithm.
numpy.lexsortPerform an indirect sort using an array of keys.
numpy.argsortReturns the indices that would sort an array with a stable sorting.Done
numpy.msortReturns a copy of an array sorted along the first axis.
numpy.partitionReturns a partitioned copy of an array.
numpy.argpartitionReturns the indices that would partially sort an array.

Searching

opdescriptionstatusnote
numpy.argmaxReturns the indices of the maximum along an axis.Done
numpy.argminReturns the indices of the minimum along an axis.
numpy.nonzeroReturn the indices of the elements that are non-zero.Code Reviewhttps://github.com/apache/incubator-mxnet/pull/15838
numpy.flatnonzeroReturn indices that are non-zero in the flattened version of a.
numpy.whereReturn elements, either from x or y, depending on condition.

Counting

opdescriptionstatusnote
numpy.count_nonzeroCounts the number of non-zero values in the array.
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