Comparison Table#

Here is a list of NumPy / SciPy APIs and its corresponding CuPy implementations.

- in CuPy column denotes that CuPy implementation is not provided yet. We welcome contributions for these functions.

NumPy / CuPy APIs#

Module-Level#

NumPy	CuPy
`numpy.DataSource`	`cupy.DataSource` (alias of `numpy.DataSource`)
`numpy.ScalarType`	-
`numpy.abs`	`cupy.abs`
`numpy.absolute`	`cupy.absolute`
`numpy.add`	`cupy.add`
`numpy.all`	`cupy.all`
`numpy.allclose`	`cupy.allclose`
`numpy.alltrue`	`cupy.alltrue`
`numpy.amax`	`cupy.amax`
`numpy.amin`	`cupy.amin`
`numpy.angle`	`cupy.angle`
`numpy.any`	`cupy.any`
`numpy.append`	`cupy.append`
`numpy.apply_along_axis`	`cupy.apply_along_axis`
`numpy.apply_over_axes`	-
`numpy.arange`	`cupy.arange`
`numpy.arccos`	`cupy.arccos`
`numpy.arccosh`	`cupy.arccosh`
`numpy.arcsin`	`cupy.arcsin`
`numpy.arcsinh`	`cupy.arcsinh`
`numpy.arctan`	`cupy.arctan`
`numpy.arctan2`	`cupy.arctan2`
`numpy.arctanh`	`cupy.arctanh`
`numpy.argmax`	`cupy.argmax`
`numpy.argmin`	`cupy.argmin`
`numpy.argpartition`	`cupy.argpartition`
`numpy.argsort`	`cupy.argsort`
`numpy.argwhere`	`cupy.argwhere`
`numpy.around`	`cupy.around`
`numpy.array`	`cupy.array`
`numpy.array2string`	`cupy.array2string`
`numpy.array_equal`	`cupy.array_equal`
`numpy.array_equiv`	`cupy.array_equiv`
`numpy.array_repr`	`cupy.array_repr`
`numpy.array_split`	`cupy.array_split`
`numpy.array_str`	`cupy.array_str`
`numpy.asanyarray`	`cupy.asanyarray`
`numpy.asarray`	`cupy.asarray`
`numpy.asarray_chkfinite`	`cupy.asarray_chkfinite`
`numpy.ascontiguousarray`	`cupy.ascontiguousarray`
`numpy.asfarray`	`cupy.asfarray`
`numpy.asfortranarray`	`cupy.asfortranarray`
`numpy.asmatrix`	- [1]
`numpy.atleast_1d`	`cupy.atleast_1d`
`numpy.atleast_2d`	`cupy.atleast_2d`
`numpy.atleast_3d`	`cupy.atleast_3d`
`numpy.average`	`cupy.average`
`numpy.bartlett`	`cupy.bartlett`
`numpy.base_repr`	`cupy.base_repr`
`numpy.binary_repr`	`cupy.binary_repr`
`numpy.bincount`	`cupy.bincount`
`numpy.bitwise_and`	`cupy.bitwise_and`
`numpy.bitwise_not`	`cupy.bitwise_not`
`numpy.bitwise_or`	`cupy.bitwise_or`
`numpy.bitwise_xor`	`cupy.bitwise_xor`
`numpy.blackman`	`cupy.blackman`
`numpy.block`	-
`numpy.bmat`	- [1]
`numpy.bool_`	`cupy.bool_` (alias of `numpy.bool_`)
`numpy.broadcast`	`cupy.broadcast`
`numpy.broadcast_arrays`	`cupy.broadcast_arrays`
`numpy.broadcast_shapes`	`cupy.broadcast_shapes` (alias of `numpy.broadcast_shapes`)
`numpy.broadcast_to`	`cupy.broadcast_to`
`numpy.busday_count`	- [2]
`numpy.busday_offset`	- [2]
`numpy.busdaycalendar`	- [2]
`numpy.byte`	`cupy.byte` (alias of `numpy.byte`)
`numpy.byte_bounds`	`cupy.byte_bounds`
`numpy.bytes_`	- [3]
`numpy.c_`	`cupy.c_`
`numpy.can_cast`	`cupy.can_cast`
`numpy.cast`	-
`numpy.cbrt`	`cupy.cbrt`
`numpy.cdouble`	`cupy.cdouble` (alias of `numpy.cdouble`)
`numpy.ceil`	`cupy.ceil`
`numpy.cfloat`	`cupy.cfloat` (alias of `numpy.cfloat`)
`numpy.character`	- [3]
`numpy.chararray`	- [3]
`numpy.choose`	`cupy.choose`
`numpy.clip`	`cupy.clip`
`numpy.clongdouble`	-
`numpy.clongfloat`	-
`numpy.column_stack`	`cupy.column_stack`
`numpy.common_type`	`cupy.common_type`
`numpy.compare_chararrays`	- [3]
`numpy.complex128`	`cupy.complex128` (alias of `numpy.complex128`)
`numpy.complex256`	-
`numpy.complex64`	`cupy.complex64` (alias of `numpy.complex64`)
`numpy.complex_`	`cupy.complex_` (alias of `numpy.complex_`)
`numpy.complexfloating`	`cupy.complexfloating` (alias of `numpy.complexfloating`)
`numpy.compress`	`cupy.compress`
`numpy.concatenate`	`cupy.concatenate`
`numpy.conj`	`cupy.conj`
`numpy.conjugate`	`cupy.conjugate`
`numpy.convolve`	`cupy.convolve`
`numpy.copy`	`cupy.copy`
`numpy.copysign`	`cupy.copysign`
`numpy.copyto`	`cupy.copyto`
`numpy.corrcoef`	`cupy.corrcoef`
`numpy.correlate`	`cupy.correlate`
`numpy.cos`	`cupy.cos`
`numpy.cosh`	`cupy.cosh`
`numpy.count_nonzero`	`cupy.count_nonzero`
`numpy.cov`	`cupy.cov`
`numpy.cross`	`cupy.cross`
`numpy.csingle`	`cupy.csingle` (alias of `numpy.csingle`)
`numpy.cumprod`	`cupy.cumprod`
`numpy.cumproduct`	`cupy.cumproduct`
`numpy.cumsum`	`cupy.cumsum`
`numpy.datetime64`	- [2]
`numpy.datetime_as_string`	- [2]
`numpy.datetime_data`	- [2]
`numpy.deg2rad`	`cupy.deg2rad`
`numpy.degrees`	`cupy.degrees`
`numpy.delete`	`cupy.delete`
`numpy.deprecate`	-
`numpy.deprecate_with_doc`	-
`numpy.diag`	`cupy.diag`
`numpy.diag_indices`	`cupy.diag_indices`
`numpy.diag_indices_from`	`cupy.diag_indices_from`
`numpy.diagflat`	`cupy.diagflat`
`numpy.diagonal`	`cupy.diagonal`
`numpy.diff`	`cupy.diff`
`numpy.digitize`	`cupy.digitize`
`numpy.disp`	`cupy.disp` (alias of `numpy.disp`)
`numpy.divide`	`cupy.divide`
`numpy.divmod`	`cupy.divmod`
`numpy.dot`	`cupy.dot`
`numpy.double`	`cupy.double` (alias of `numpy.double`)
`numpy.dsplit`	`cupy.dsplit`
`numpy.dstack`	`cupy.dstack`
`numpy.dtype`	`cupy.dtype` (alias of `numpy.dtype`)
`numpy.ediff1d`	`cupy.ediff1d`
`numpy.einsum`	`cupy.einsum`
`numpy.einsum_path`	-
`numpy.empty`	`cupy.empty`
`numpy.empty_like`	`cupy.empty_like`
`numpy.equal`	`cupy.equal`
`numpy.errstate`	- [4]
`numpy.exp`	`cupy.exp`
`numpy.exp2`	`cupy.exp2`
`numpy.expand_dims`	`cupy.expand_dims`
`numpy.expm1`	`cupy.expm1`
`numpy.extract`	`cupy.extract`
`numpy.eye`	`cupy.eye`
`numpy.fabs`	`cupy.fabs`
`numpy.fill_diagonal`	`cupy.fill_diagonal`
`numpy.find_common_type`	`cupy.find_common_type` (alias of `numpy.find_common_type`)
`numpy.finfo`	`cupy.finfo` (alias of `numpy.finfo`)
`numpy.fix`	`cupy.fix`
`numpy.flatiter`	`cupy.flatiter`
`numpy.flatnonzero`	`cupy.flatnonzero`
`numpy.flexible`	- [3]
`numpy.flip`	`cupy.flip`
`numpy.fliplr`	`cupy.fliplr`
`numpy.flipud`	`cupy.flipud`
`numpy.float128`	-
`numpy.float16`	`cupy.float16` (alias of `numpy.float16`)
`numpy.float32`	`cupy.float32` (alias of `numpy.float32`)
`numpy.float64`	`cupy.float64` (alias of `numpy.float64`)
`numpy.float_`	`cupy.float_` (alias of `numpy.float_`)
`numpy.float_power`	`cupy.float_power`
`numpy.floating`	`cupy.floating` (alias of `numpy.floating`)
`numpy.floor`	`cupy.floor`
`numpy.floor_divide`	`cupy.floor_divide`
`numpy.fmax`	`cupy.fmax`
`numpy.fmin`	`cupy.fmin`
`numpy.fmod`	`cupy.fmod`
`numpy.format_float_positional`	`cupy.format_float_positional`
`numpy.format_float_scientific`	`cupy.format_float_scientific`
`numpy.format_parser`	`cupy.format_parser` (alias of `numpy.format_parser`)
`numpy.frexp`	`cupy.frexp`
`numpy.from_dlpack`	`cupy.from_dlpack`
`numpy.frombuffer`	`cupy.frombuffer`
`numpy.fromfile`	`cupy.fromfile`
`numpy.fromfunction`	`cupy.fromfunction`
`numpy.fromiter`	`cupy.fromiter`
`numpy.frompyfunc`	-
`numpy.fromregex`	- [5]
`numpy.fromstring`	`cupy.fromstring`
`numpy.full`	`cupy.full`
`numpy.full_like`	`cupy.full_like`
`numpy.gcd`	`cupy.gcd`
`numpy.generic`	`cupy.generic` (alias of `numpy.generic`)
`numpy.genfromtxt`	`cupy.genfromtxt`
`numpy.geomspace`	-
`numpy.get_array_wrap`	`cupy.get_array_wrap` (alias of `numpy.get_array_wrap`)
`numpy.get_include`	-
`numpy.get_printoptions`	`cupy.get_printoptions` (alias of `numpy.get_printoptions`)
`numpy.getbufsize`	-
`numpy.geterr`	- [4]
`numpy.geterrcall`	- [4]
`numpy.geterrobj`	- [4]
`numpy.gradient`	`cupy.gradient`
`numpy.greater`	`cupy.greater`
`numpy.greater_equal`	`cupy.greater_equal`
`numpy.half`	`cupy.half` (alias of `numpy.half`)
`numpy.hamming`	`cupy.hamming`
`numpy.hanning`	`cupy.hanning`
`numpy.heaviside`	`cupy.heaviside`
`numpy.histogram`	`cupy.histogram`
`numpy.histogram2d`	`cupy.histogram2d`
`numpy.histogram_bin_edges`	-
`numpy.histogramdd`	`cupy.histogramdd`
`numpy.hsplit`	`cupy.hsplit`
`numpy.hstack`	`cupy.hstack`
`numpy.hypot`	`cupy.hypot`
`numpy.i0`	`cupy.i0`
`numpy.identity`	`cupy.identity`
`numpy.iinfo`	`cupy.iinfo` (alias of `numpy.iinfo`)
`numpy.imag`	`cupy.imag`
`numpy.in1d`	`cupy.in1d`
`numpy.index_exp`	`cupy.index_exp` (alias of `numpy.index_exp`)
`numpy.indices`	`cupy.indices`
`numpy.inexact`	`cupy.inexact` (alias of `numpy.inexact`)
`numpy.info`	-
`numpy.inner`	`cupy.inner`
`numpy.insert`	-
`numpy.int16`	`cupy.int16` (alias of `numpy.int16`)
`numpy.int32`	`cupy.int32` (alias of `numpy.int32`)
`numpy.int64`	`cupy.int64` (alias of `numpy.int64`)
`numpy.int8`	`cupy.int8` (alias of `numpy.int8`)
`numpy.int_`	`cupy.int_` (alias of `numpy.int_`)
`numpy.intc`	`cupy.intc` (alias of `numpy.intc`)
`numpy.integer`	`cupy.integer` (alias of `numpy.integer`)
`numpy.interp`	`cupy.interp`
`numpy.intersect1d`	`cupy.intersect1d`
`numpy.intp`	`cupy.intp` (alias of `numpy.intp`)
`numpy.invert`	`cupy.invert`
`numpy.is_busday`	- [2]
`numpy.isclose`	`cupy.isclose`
`numpy.iscomplex`	`cupy.iscomplex`
`numpy.iscomplexobj`	`cupy.iscomplexobj`
`numpy.isfinite`	`cupy.isfinite`
`numpy.isfortran`	`cupy.isfortran`
`numpy.isin`	`cupy.isin`
`numpy.isinf`	`cupy.isinf`
`numpy.isnan`	`cupy.isnan`
`numpy.isnat`	- [2]
`numpy.isneginf`	`cupy.isneginf`
`numpy.isposinf`	`cupy.isposinf`
`numpy.isreal`	`cupy.isreal`
`numpy.isrealobj`	`cupy.isrealobj`
`numpy.isscalar`	`cupy.isscalar`
`numpy.issctype`	`cupy.issctype`
`numpy.issubclass_`	`cupy.issubclass_`
`numpy.issubdtype`	`cupy.issubdtype` (alias of `numpy.issubdtype`)
`numpy.issubsctype`	`cupy.issubsctype`
`numpy.iterable`	`cupy.iterable` (alias of `numpy.iterable`)
`numpy.ix_`	`cupy.ix_`
`numpy.kaiser`	`cupy.kaiser`
`numpy.kron`	`cupy.kron`
`numpy.lcm`	`cupy.lcm`
`numpy.ldexp`	`cupy.ldexp`
`numpy.left_shift`	`cupy.left_shift`
`numpy.less`	`cupy.less`
`numpy.less_equal`	`cupy.less_equal`
`numpy.lexsort`	`cupy.lexsort`
`numpy.linspace`	`cupy.linspace`
`numpy.load`	`cupy.load`
`numpy.loadtxt`	`cupy.loadtxt`
`numpy.log`	`cupy.log`
`numpy.log10`	`cupy.log10`
`numpy.log1p`	`cupy.log1p`
`numpy.log2`	`cupy.log2`
`numpy.logaddexp`	`cupy.logaddexp`
`numpy.logaddexp2`	`cupy.logaddexp2`
`numpy.logical_and`	`cupy.logical_and`
`numpy.logical_not`	`cupy.logical_not`
`numpy.logical_or`	`cupy.logical_or`
`numpy.logical_xor`	`cupy.logical_xor`
`numpy.logspace`	`cupy.logspace`
`numpy.longcomplex`	-
`numpy.longdouble`	-
`numpy.longfloat`	-
`numpy.longlong`	`cupy.longlong` (alias of `numpy.longlong`)
`numpy.lookfor`	-
`numpy.mask_indices`	`cupy.mask_indices`
`numpy.mat`	- [1]
`numpy.matmul`	`cupy.matmul`
`numpy.matrix`	- [1]
`numpy.max`	`cupy.max`
`numpy.maximum`	`cupy.maximum`
`numpy.maximum_sctype`	-
`numpy.may_share_memory`	`cupy.may_share_memory`
`numpy.mean`	`cupy.mean`
`numpy.median`	`cupy.median`
`numpy.memmap`	-
`numpy.meshgrid`	`cupy.meshgrid`
`numpy.mgrid`	`cupy.mgrid`
`numpy.min`	`cupy.min`
`numpy.min_scalar_type`	`cupy.min_scalar_type`
`numpy.minimum`	`cupy.minimum`
`numpy.mintypecode`	`cupy.mintypecode` (alias of `numpy.mintypecode`)
`numpy.mod`	`cupy.mod`
`numpy.modf`	`cupy.modf`
`numpy.moveaxis`	`cupy.moveaxis`
`numpy.msort`	`cupy.msort`
`numpy.multiply`	`cupy.multiply`
`numpy.nan_to_num`	`cupy.nan_to_num`
`numpy.nanargmax`	`cupy.nanargmax`
`numpy.nanargmin`	`cupy.nanargmin`
`numpy.nancumprod`	`cupy.nancumprod`
`numpy.nancumsum`	`cupy.nancumsum`
`numpy.nanmax`	`cupy.nanmax`
`numpy.nanmean`	`cupy.nanmean`
`numpy.nanmedian`	`cupy.nanmedian`
`numpy.nanmin`	`cupy.nanmin`
`numpy.nanpercentile`	-
`numpy.nanprod`	`cupy.nanprod`
`numpy.nanquantile`	-
`numpy.nanstd`	`cupy.nanstd`
`numpy.nansum`	`cupy.nansum`
`numpy.nanvar`	`cupy.nanvar`
`numpy.nbytes`	-
`numpy.ndarray`	`cupy.ndarray`
`numpy.ndenumerate`	-
`numpy.ndim`	`cupy.ndim`
`numpy.ndindex`	`cupy.ndindex` (alias of `numpy.ndindex`)
`numpy.nditer`	-
`numpy.negative`	`cupy.negative`
`numpy.nested_iters`	-
`numpy.newaxis`	`cupy.newaxis` (alias of `numpy.newaxis`)
`numpy.nextafter`	`cupy.nextafter`
`numpy.nonzero`	`cupy.nonzero`
`numpy.not_equal`	`cupy.not_equal`
`numpy.number`	`cupy.number` (alias of `numpy.number`)
`numpy.obj2sctype`	`cupy.obj2sctype`
`numpy.object_`	- [3]
`numpy.ogrid`	`cupy.ogrid`
`numpy.ones`	`cupy.ones`
`numpy.ones_like`	`cupy.ones_like`
`numpy.outer`	`cupy.outer`
`numpy.packbits`	`cupy.packbits`
`numpy.pad`	`cupy.pad`
`numpy.partition`	`cupy.partition`
`numpy.percentile`	`cupy.percentile`
`numpy.piecewise`	`cupy.piecewise`
`numpy.place`	`cupy.place`
`numpy.poly`	`cupy.poly` [6]
`numpy.poly1d`	`cupy.poly1d`
`numpy.polyadd`	`cupy.polyadd`
`numpy.polyder`	- [6]
`numpy.polydiv`	- [6]
`numpy.polyfit`	`cupy.polyfit`
`numpy.polyint`	- [6]
`numpy.polymul`	`cupy.polymul`
`numpy.polysub`	`cupy.polysub`
`numpy.polyval`	`cupy.polyval`
`numpy.positive`	`cupy.positive`
`numpy.power`	`cupy.power`
`numpy.printoptions`	`cupy.printoptions` (alias of `numpy.printoptions`)
`numpy.prod`	`cupy.prod`
`numpy.product`	`cupy.product`
`numpy.promote_types`	`cupy.promote_types` (alias of `numpy.promote_types`)
`numpy.ptp`	`cupy.ptp`
`numpy.put`	`cupy.put`
`numpy.put_along_axis`	`cupy.put_along_axis`
`numpy.putmask`	`cupy.putmask`
`numpy.quantile`	`cupy.quantile`
`numpy.r_`	`cupy.r_`
`numpy.rad2deg`	`cupy.rad2deg`
`numpy.radians`	`cupy.radians`
`numpy.ravel`	`cupy.ravel`
`numpy.ravel_multi_index`	`cupy.ravel_multi_index`
`numpy.real`	`cupy.real`
`numpy.real_if_close`	`cupy.real_if_close`
`numpy.recarray`	- [5]
`numpy.recfromcsv`	- [5]
`numpy.recfromtxt`	- [5]
`numpy.reciprocal`	`cupy.reciprocal`
`numpy.record`	- [5]
`numpy.remainder`	`cupy.remainder`
`numpy.repeat`	`cupy.repeat`
`numpy.require`	`cupy.require`
`numpy.reshape`	`cupy.reshape`
`numpy.resize`	`cupy.resize`
`numpy.result_type`	`cupy.result_type`
`numpy.right_shift`	`cupy.right_shift`
`numpy.rint`	`cupy.rint`
`numpy.roll`	`cupy.roll`
`numpy.rollaxis`	`cupy.rollaxis`
`numpy.roots`	`cupy.roots`
`numpy.rot90`	`cupy.rot90`
`numpy.round`	`cupy.round`
`numpy.round_`	`cupy.round_`
`numpy.row_stack`	`cupy.row_stack`
`numpy.s_`	`cupy.s_` (alias of `numpy.s_`)
`numpy.safe_eval`	`cupy.safe_eval` (alias of `numpy.safe_eval`)
`numpy.save`	`cupy.save`
`numpy.savetxt`	`cupy.savetxt`
`numpy.savez`	`cupy.savez`
`numpy.savez_compressed`	`cupy.savez_compressed`
`numpy.sctype2char`	`cupy.sctype2char`
`numpy.sctypeDict`	-
`numpy.sctypes`	-
`numpy.searchsorted`	`cupy.searchsorted`
`numpy.select`	`cupy.select`
`numpy.set_numeric_ops`	- [7]
`numpy.set_printoptions`	`cupy.set_printoptions` (alias of `numpy.set_printoptions`)
`numpy.set_string_function`	`cupy.set_string_function` (alias of `numpy.set_string_function`)
`numpy.setbufsize`	-
`numpy.setdiff1d`	`cupy.setdiff1d`
`numpy.seterr`	- [4]
`numpy.seterrcall`	- [4]
`numpy.seterrobj`	- [4]
`numpy.setxor1d`	`cupy.setxor1d`
`numpy.shape`	`cupy.shape`
`numpy.shares_memory`	`cupy.shares_memory`
`numpy.short`	`cupy.short` (alias of `numpy.short`)
`numpy.show_config`	`cupy.show_config`
`numpy.show_runtime`	-
`numpy.sign`	`cupy.sign`
`numpy.signbit`	`cupy.signbit`
`numpy.signedinteger`	`cupy.signedinteger` (alias of `numpy.signedinteger`)
`numpy.sin`	`cupy.sin`
`numpy.sinc`	`cupy.sinc`
`numpy.single`	`cupy.single` (alias of `numpy.single`)
`numpy.singlecomplex`	`cupy.singlecomplex` (alias of `numpy.singlecomplex`)
`numpy.sinh`	`cupy.sinh`
`numpy.size`	`cupy.size`
`numpy.sometrue`	`cupy.sometrue`
`numpy.sort`	`cupy.sort`
`numpy.sort_complex`	`cupy.sort_complex`
`numpy.source`	-
`numpy.spacing`	-
`numpy.split`	`cupy.split`
`numpy.sqrt`	`cupy.sqrt`
`numpy.square`	`cupy.square`
`numpy.squeeze`	`cupy.squeeze`
`numpy.stack`	`cupy.stack`
`numpy.std`	`cupy.std`
`numpy.str_`	- [3]
`numpy.string_`	- [3]
`numpy.subtract`	`cupy.subtract`
`numpy.sum`	`cupy.sum`
`numpy.swapaxes`	`cupy.swapaxes`
`numpy.take`	`cupy.take`
`numpy.take_along_axis`	`cupy.take_along_axis`
`numpy.tan`	`cupy.tan`
`numpy.tanh`	`cupy.tanh`
`numpy.tensordot`	`cupy.tensordot`
`numpy.tile`	`cupy.tile`
`numpy.timedelta64`	- [2]
`numpy.trace`	`cupy.trace`
`numpy.transpose`	`cupy.transpose`
`numpy.trapz`	`cupy.trapz`
`numpy.tri`	`cupy.tri`
`numpy.tril`	`cupy.tril`
`numpy.tril_indices`	`cupy.tril_indices`
`numpy.tril_indices_from`	`cupy.tril_indices_from`
`numpy.trim_zeros`	`cupy.trim_zeros`
`numpy.triu`	`cupy.triu`
`numpy.triu_indices`	`cupy.triu_indices`
`numpy.triu_indices_from`	`cupy.triu_indices_from`
`numpy.true_divide`	`cupy.true_divide`
`numpy.trunc`	`cupy.trunc`
`numpy.typecodes`	-
`numpy.typename`	`cupy.typename` (alias of `numpy.typename`)
`numpy.ubyte`	`cupy.ubyte` (alias of `numpy.ubyte`)
`numpy.ufunc`	`cupy.ufunc`
`numpy.uint`	`cupy.uint` (alias of `numpy.uint`)
`numpy.uint16`	`cupy.uint16` (alias of `numpy.uint16`)
`numpy.uint32`	`cupy.uint32` (alias of `numpy.uint32`)
`numpy.uint64`	`cupy.uint64` (alias of `numpy.uint64`)
`numpy.uint8`	`cupy.uint8` (alias of `numpy.uint8`)
`numpy.uintc`	`cupy.uintc` (alias of `numpy.uintc`)
`numpy.uintp`	`cupy.uintp` (alias of `numpy.uintp`)
`numpy.ulonglong`	`cupy.ulonglong` (alias of `numpy.ulonglong`)
`numpy.unicode_`	- [3]
`numpy.union1d`	`cupy.union1d`
`numpy.unique`	`cupy.unique`
`numpy.unpackbits`	`cupy.unpackbits`
`numpy.unravel_index`	`cupy.unravel_index`
`numpy.unsignedinteger`	`cupy.unsignedinteger` (alias of `numpy.unsignedinteger`)
`numpy.unwrap`	`cupy.unwrap`
`numpy.ushort`	`cupy.ushort` (alias of `numpy.ushort`)
`numpy.vander`	`cupy.vander`
`numpy.var`	`cupy.var`
`numpy.vdot`	`cupy.vdot`
`numpy.vectorize`	`cupy.vectorize`
`numpy.void`	- [3]
`numpy.vsplit`	`cupy.vsplit`
`numpy.vstack`	`cupy.vstack`
`numpy.where`	`cupy.where`
`numpy.who`	`cupy.who`
`numpy.zeros`	`cupy.zeros`
`numpy.zeros_like`	`cupy.zeros_like`

Multi-Dimensional Array#

NumPy	CuPy
`numpy.ndarray.T`	`cupy.ndarray.T`
`numpy.ndarray.all`	`cupy.ndarray.all`
`numpy.ndarray.any`	`cupy.ndarray.any`
`numpy.ndarray.argmax`	`cupy.ndarray.argmax`
`numpy.ndarray.argmin`	`cupy.ndarray.argmin`
`numpy.ndarray.argpartition`	`cupy.ndarray.argpartition`
`numpy.ndarray.argsort`	`cupy.ndarray.argsort`
`numpy.ndarray.astype`	`cupy.ndarray.astype`
`numpy.ndarray.base`	`cupy.ndarray.base`
`numpy.ndarray.byteswap`	- [8]
`numpy.ndarray.choose`	`cupy.ndarray.choose`
`numpy.ndarray.clip`	`cupy.ndarray.clip`
`numpy.ndarray.compress`	`cupy.ndarray.compress`
`numpy.ndarray.conj`	`cupy.ndarray.conj`
`numpy.ndarray.conjugate`	`cupy.ndarray.conjugate`
`numpy.ndarray.copy`	`cupy.ndarray.copy`
`numpy.ndarray.ctypes`	-
`numpy.ndarray.cumprod`	`cupy.ndarray.cumprod`
`numpy.ndarray.cumsum`	`cupy.ndarray.cumsum`
`numpy.ndarray.data`	`cupy.ndarray.data`
`numpy.ndarray.diagonal`	`cupy.ndarray.diagonal`
`numpy.ndarray.dot`	`cupy.ndarray.dot`
`numpy.ndarray.dtype`	`cupy.ndarray.dtype`
`numpy.ndarray.dump`	`cupy.ndarray.dump`
`numpy.ndarray.dumps`	`cupy.ndarray.dumps`
`numpy.ndarray.fill`	`cupy.ndarray.fill`
`numpy.ndarray.flags`	`cupy.ndarray.flags`
`numpy.ndarray.flat`	`cupy.ndarray.flat`
`numpy.ndarray.flatten`	`cupy.ndarray.flatten`
`numpy.ndarray.getfield`	-
`numpy.ndarray.imag`	`cupy.ndarray.imag`
`numpy.ndarray.item`	`cupy.ndarray.item`
`numpy.ndarray.itemset`	-
`numpy.ndarray.itemsize`	`cupy.ndarray.itemsize`
`numpy.ndarray.max`	`cupy.ndarray.max`
`numpy.ndarray.mean`	`cupy.ndarray.mean`
`numpy.ndarray.min`	`cupy.ndarray.min`
`numpy.ndarray.nbytes`	`cupy.ndarray.nbytes`
`numpy.ndarray.ndim`	`cupy.ndarray.ndim`
`numpy.ndarray.newbyteorder`	- [8]
`numpy.ndarray.nonzero`	`cupy.ndarray.nonzero`
`numpy.ndarray.partition`	`cupy.ndarray.partition`
`numpy.ndarray.prod`	`cupy.ndarray.prod`
`numpy.ndarray.ptp`	`cupy.ndarray.ptp`
`numpy.ndarray.put`	`cupy.ndarray.put`
`numpy.ndarray.ravel`	`cupy.ndarray.ravel`
`numpy.ndarray.real`	`cupy.ndarray.real`
`numpy.ndarray.repeat`	`cupy.ndarray.repeat`
`numpy.ndarray.reshape`	`cupy.ndarray.reshape`
`numpy.ndarray.resize`	-
`numpy.ndarray.round`	`cupy.ndarray.round`
`numpy.ndarray.searchsorted`	`cupy.ndarray.searchsorted`
`numpy.ndarray.setfield`	-
`numpy.ndarray.setflags`	-
`numpy.ndarray.shape`	`cupy.ndarray.shape`
`numpy.ndarray.size`	`cupy.ndarray.size`
`numpy.ndarray.sort`	`cupy.ndarray.sort`
`numpy.ndarray.squeeze`	`cupy.ndarray.squeeze`
`numpy.ndarray.std`	`cupy.ndarray.std`
`numpy.ndarray.strides`	`cupy.ndarray.strides`
`numpy.ndarray.sum`	`cupy.ndarray.sum`
`numpy.ndarray.swapaxes`	`cupy.ndarray.swapaxes`
`numpy.ndarray.take`	`cupy.ndarray.take`
`numpy.ndarray.tobytes`	`cupy.ndarray.tobytes`
`numpy.ndarray.tofile`	`cupy.ndarray.tofile`
`numpy.ndarray.tolist`	`cupy.ndarray.tolist`
`numpy.ndarray.tostring`	- [7]
`numpy.ndarray.trace`	`cupy.ndarray.trace`
`numpy.ndarray.transpose`	`cupy.ndarray.transpose`
`numpy.ndarray.var`	`cupy.ndarray.var`
`numpy.ndarray.view`	`cupy.ndarray.view`

Linear Algebra#

NumPy	CuPy
`numpy.linalg.cholesky`	`cupy.linalg.cholesky`
`numpy.linalg.cond`	-
`numpy.linalg.det`	`cupy.linalg.det`
`numpy.linalg.eig`	-
`numpy.linalg.eigh`	`cupy.linalg.eigh`
`numpy.linalg.eigvals`	-
`numpy.linalg.eigvalsh`	`cupy.linalg.eigvalsh`
`numpy.linalg.inv`	`cupy.linalg.inv`
`numpy.linalg.lstsq`	`cupy.linalg.lstsq`
`numpy.linalg.matrix_power`	`cupy.linalg.matrix_power`
`numpy.linalg.matrix_rank`	`cupy.linalg.matrix_rank`
`numpy.linalg.multi_dot`	-
`numpy.linalg.norm`	`cupy.linalg.norm`
`numpy.linalg.pinv`	`cupy.linalg.pinv`
`numpy.linalg.qr`	`cupy.linalg.qr`
`numpy.linalg.slogdet`	`cupy.linalg.slogdet`
`numpy.linalg.solve`	`cupy.linalg.solve`
`numpy.linalg.svd`	`cupy.linalg.svd`
`numpy.linalg.tensorinv`	`cupy.linalg.tensorinv`
`numpy.linalg.tensorsolve`	`cupy.linalg.tensorsolve`

Discrete Fourier Transform#

NumPy	CuPy
`numpy.fft.fft`	`cupy.fft.fft`
`numpy.fft.fft2`	`cupy.fft.fft2`
`numpy.fft.fftfreq`	`cupy.fft.fftfreq`
`numpy.fft.fftn`	`cupy.fft.fftn`
`numpy.fft.fftshift`	`cupy.fft.fftshift`
`numpy.fft.hfft`	`cupy.fft.hfft`
`numpy.fft.ifft`	`cupy.fft.ifft`
`numpy.fft.ifft2`	`cupy.fft.ifft2`
`numpy.fft.ifftn`	`cupy.fft.ifftn`
`numpy.fft.ifftshift`	`cupy.fft.ifftshift`
`numpy.fft.ihfft`	`cupy.fft.ihfft`
`numpy.fft.irfft`	`cupy.fft.irfft`
`numpy.fft.irfft2`	`cupy.fft.irfft2`
`numpy.fft.irfftn`	`cupy.fft.irfftn`
`numpy.fft.rfft`	`cupy.fft.rfft`
`numpy.fft.rfft2`	`cupy.fft.rfft2`
`numpy.fft.rfftfreq`	`cupy.fft.rfftfreq`
`numpy.fft.rfftn`	`cupy.fft.rfftn`

Random Sampling#

NumPy	CuPy
`numpy.random.BitGenerator`	`cupy.random.BitGenerator`
`numpy.random.Generator`	-
`numpy.random.MT19937`	-
`numpy.random.PCG64`	-
`numpy.random.PCG64DXSM`	-
`numpy.random.Philox`	-
`numpy.random.RandomState`	`cupy.random.RandomState`
`numpy.random.SFC64`	-
`numpy.random.SeedSequence`	-
`numpy.random.beta`	`cupy.random.beta`
`numpy.random.binomial`	`cupy.random.binomial`
`numpy.random.bytes`	`cupy.random.bytes`
`numpy.random.chisquare`	`cupy.random.chisquare`
`numpy.random.choice`	`cupy.random.choice`
`numpy.random.default_rng`	`cupy.random.default_rng`
`numpy.random.dirichlet`	`cupy.random.dirichlet`
`numpy.random.exponential`	`cupy.random.exponential`
`numpy.random.f`	`cupy.random.f`
`numpy.random.gamma`	`cupy.random.gamma`
`numpy.random.geometric`	`cupy.random.geometric`
`numpy.random.get_bit_generator`	-
`numpy.random.get_state`	-
`numpy.random.gumbel`	`cupy.random.gumbel`
`numpy.random.hypergeometric`	`cupy.random.hypergeometric`
`numpy.random.laplace`	`cupy.random.laplace`
`numpy.random.logistic`	`cupy.random.logistic`
`numpy.random.lognormal`	`cupy.random.lognormal`
`numpy.random.logseries`	`cupy.random.logseries`
`numpy.random.multinomial`	`cupy.random.multinomial`
`numpy.random.multivariate_normal`	`cupy.random.multivariate_normal`
`numpy.random.negative_binomial`	`cupy.random.negative_binomial`
`numpy.random.noncentral_chisquare`	`cupy.random.noncentral_chisquare`
`numpy.random.noncentral_f`	`cupy.random.noncentral_f`
`numpy.random.normal`	`cupy.random.normal`
`numpy.random.pareto`	`cupy.random.pareto`
`numpy.random.permutation`	`cupy.random.permutation`
`numpy.random.poisson`	`cupy.random.poisson`
`numpy.random.power`	`cupy.random.power`
`numpy.random.rand`	`cupy.random.rand`
`numpy.random.randint`	`cupy.random.randint`
`numpy.random.randn`	`cupy.random.randn`
`numpy.random.random`	`cupy.random.random`
`numpy.random.random_integers`	`cupy.random.random_integers`
`numpy.random.random_sample`	`cupy.random.random_sample`
`numpy.random.ranf`	`cupy.random.ranf`
`numpy.random.rayleigh`	`cupy.random.rayleigh`
`numpy.random.sample`	`cupy.random.sample`
`numpy.random.seed`	`cupy.random.seed`
`numpy.random.set_bit_generator`	-
`numpy.random.set_state`	-
`numpy.random.shuffle`	`cupy.random.shuffle`
`numpy.random.standard_cauchy`	`cupy.random.standard_cauchy`
`numpy.random.standard_exponential`	`cupy.random.standard_exponential`
`numpy.random.standard_gamma`	`cupy.random.standard_gamma`
`numpy.random.standard_normal`	`cupy.random.standard_normal`
`numpy.random.standard_t`	`cupy.random.standard_t`
`numpy.random.triangular`	`cupy.random.triangular`
`numpy.random.uniform`	`cupy.random.uniform`
`numpy.random.vonmises`	`cupy.random.vonmises`
`numpy.random.wald`	`cupy.random.wald`
`numpy.random.weibull`	`cupy.random.weibull`
`numpy.random.zipf`	`cupy.random.zipf`

Polynomials#

NumPy	CuPy
`numpy.polynomial.Chebyshev`	-
`numpy.polynomial.Hermite`	-
`numpy.polynomial.HermiteE`	-
`numpy.polynomial.Laguerre`	-
`numpy.polynomial.Legendre`	-
`numpy.polynomial.Polynomial`	-
`numpy.polynomial.set_default_printstyle`	-

Power Series#

NumPy	CuPy
`numpy.polynomial.polynomial.ABCPolyBase`	-
`numpy.polynomial.polynomial.Polynomial`	-
`numpy.polynomial.polynomial.normalize_axis_index`	-
`numpy.polynomial.polynomial.polyadd`	-
`numpy.polynomial.polynomial.polycompanion`	`cupy.polynomial.polynomial.polycompanion`
`numpy.polynomial.polynomial.polyder`	-
`numpy.polynomial.polynomial.polydiv`	-
`numpy.polynomial.polynomial.polydomain`	-
`numpy.polynomial.polynomial.polyfit`	-
`numpy.polynomial.polynomial.polyfromroots`	-
`numpy.polynomial.polynomial.polygrid2d`	-
`numpy.polynomial.polynomial.polygrid3d`	-
`numpy.polynomial.polynomial.polyint`	-
`numpy.polynomial.polynomial.polyline`	-
`numpy.polynomial.polynomial.polymul`	-
`numpy.polynomial.polynomial.polymulx`	-
`numpy.polynomial.polynomial.polyone`	-
`numpy.polynomial.polynomial.polypow`	-
`numpy.polynomial.polynomial.polyroots`	-
`numpy.polynomial.polynomial.polysub`	-
`numpy.polynomial.polynomial.polytrim`	-
`numpy.polynomial.polynomial.polyval`	`cupy.polynomial.polynomial.polyval`
`numpy.polynomial.polynomial.polyval2d`	-
`numpy.polynomial.polynomial.polyval3d`	-
`numpy.polynomial.polynomial.polyvalfromroots`	`cupy.polynomial.polynomial.polyvalfromroots`
`numpy.polynomial.polynomial.polyvander`	`cupy.polynomial.polynomial.polyvander`
`numpy.polynomial.polynomial.polyvander2d`	-
`numpy.polynomial.polynomial.polyvander3d`	-
`numpy.polynomial.polynomial.polyx`	-
`numpy.polynomial.polynomial.polyzero`	-

Polyutils#

NumPy	CuPy
`numpy.polynomial.polyutils.absolute`	-
`numpy.polynomial.polyutils.as_series`	`cupy.polynomial.polyutils.as_series`
`numpy.polynomial.polyutils.dragon4_positional`	-
`numpy.polynomial.polyutils.dragon4_scientific`	-
`numpy.polynomial.polyutils.format_float`	-
`numpy.polynomial.polyutils.getdomain`	-
`numpy.polynomial.polyutils.mapdomain`	-
`numpy.polynomial.polyutils.mapparms`	-
`numpy.polynomial.polyutils.trimcoef`	`cupy.polynomial.polyutils.trimcoef`
`numpy.polynomial.polyutils.trimseq`	`cupy.polynomial.polyutils.trimseq`

SciPy / CuPy APIs#

Discrete Fourier Transform#

SciPy	CuPy
`scipy.fft.dct`	`cupyx.scipy.fft.dct`
`scipy.fft.dctn`	`cupyx.scipy.fft.dctn`
`scipy.fft.dst`	`cupyx.scipy.fft.dst`
`scipy.fft.dstn`	`cupyx.scipy.fft.dstn`
`scipy.fft.fft`	`cupyx.scipy.fft.fft`
`scipy.fft.fft2`	`cupyx.scipy.fft.fft2`
`scipy.fft.fftfreq`	`cupyx.scipy.fft.fftfreq`
`scipy.fft.fftn`	`cupyx.scipy.fft.fftn`
`scipy.fft.fftshift`	`cupyx.scipy.fft.fftshift`
`scipy.fft.fht`	`cupyx.scipy.fft.fht`
`scipy.fft.fhtoffset`	-
`scipy.fft.get_workers`	-
`scipy.fft.hfft`	`cupyx.scipy.fft.hfft`
`scipy.fft.hfft2`	`cupyx.scipy.fft.hfft2`
`scipy.fft.hfftn`	`cupyx.scipy.fft.hfftn`
`scipy.fft.idct`	`cupyx.scipy.fft.idct`
`scipy.fft.idctn`	`cupyx.scipy.fft.idctn`
`scipy.fft.idst`	`cupyx.scipy.fft.idst`
`scipy.fft.idstn`	`cupyx.scipy.fft.idstn`
`scipy.fft.ifft`	`cupyx.scipy.fft.ifft`
`scipy.fft.ifft2`	`cupyx.scipy.fft.ifft2`
`scipy.fft.ifftn`	`cupyx.scipy.fft.ifftn`
`scipy.fft.ifftshift`	`cupyx.scipy.fft.ifftshift`
`scipy.fft.ifht`	`cupyx.scipy.fft.ifht`
`scipy.fft.ihfft`	`cupyx.scipy.fft.ihfft`
`scipy.fft.ihfft2`	`cupyx.scipy.fft.ihfft2`
`scipy.fft.ihfftn`	`cupyx.scipy.fft.ihfftn`
`scipy.fft.irfft`	`cupyx.scipy.fft.irfft`
`scipy.fft.irfft2`	`cupyx.scipy.fft.irfft2`
`scipy.fft.irfftn`	`cupyx.scipy.fft.irfftn`
`scipy.fft.next_fast_len`	`cupyx.scipy.fft.next_fast_len`
`scipy.fft.prev_fast_len`	-
`scipy.fft.register_backend`	-
`scipy.fft.rfft`	`cupyx.scipy.fft.rfft`
`scipy.fft.rfft2`	`cupyx.scipy.fft.rfft2`
`scipy.fft.rfftfreq`	`cupyx.scipy.fft.rfftfreq`
`scipy.fft.rfftn`	`cupyx.scipy.fft.rfftn`
`scipy.fft.set_backend`	-
`scipy.fft.set_global_backend`	-
`scipy.fft.set_workers`	-
`scipy.fft.skip_backend`	-

Legacy Discrete Fourier Transform#

SciPy	CuPy
`scipy.fftpack.cc_diff`	-
`scipy.fftpack.cs_diff`	-
`scipy.fftpack.dct`	-
`scipy.fftpack.dctn`	-
`scipy.fftpack.diff`	-
`scipy.fftpack.dst`	-
`scipy.fftpack.dstn`	-
`scipy.fftpack.fft`	`cupyx.scipy.fftpack.fft`
`scipy.fftpack.fft2`	`cupyx.scipy.fftpack.fft2`
`scipy.fftpack.fftfreq`	-
`scipy.fftpack.fftn`	`cupyx.scipy.fftpack.fftn`
`scipy.fftpack.fftshift`	-
`scipy.fftpack.hilbert`	-
`scipy.fftpack.idct`	-
`scipy.fftpack.idctn`	-
`scipy.fftpack.idst`	-
`scipy.fftpack.idstn`	-
`scipy.fftpack.ifft`	`cupyx.scipy.fftpack.ifft`
`scipy.fftpack.ifft2`	`cupyx.scipy.fftpack.ifft2`
`scipy.fftpack.ifftn`	`cupyx.scipy.fftpack.ifftn`
`scipy.fftpack.ifftshift`	-
`scipy.fftpack.ihilbert`	-
`scipy.fftpack.irfft`	`cupyx.scipy.fftpack.irfft`
`scipy.fftpack.itilbert`	-
`scipy.fftpack.next_fast_len`	-
`scipy.fftpack.rfft`	`cupyx.scipy.fftpack.rfft`
`scipy.fftpack.rfftfreq`	-
`scipy.fftpack.sc_diff`	-
`scipy.fftpack.shift`	-
`scipy.fftpack.ss_diff`	-
`scipy.fftpack.tilbert`	-

Interpolation#

SciPy	CuPy
`scipy.interpolate.Akima1DInterpolator`	`cupyx.scipy.interpolate.Akima1DInterpolator`
`scipy.interpolate.BPoly`	`cupyx.scipy.interpolate.BPoly`
`scipy.interpolate.BSpline`	`cupyx.scipy.interpolate.BSpline`
`scipy.interpolate.BarycentricInterpolator`	`cupyx.scipy.interpolate.BarycentricInterpolator`
`scipy.interpolate.BivariateSpline`	-
`scipy.interpolate.CloughTocher2DInterpolator`	`cupyx.scipy.interpolate.CloughTocher2DInterpolator`
`scipy.interpolate.CubicHermiteSpline`	`cupyx.scipy.interpolate.CubicHermiteSpline`
`scipy.interpolate.CubicSpline`	`cupyx.scipy.interpolate.CubicSpline`
`scipy.interpolate.InterpolatedUnivariateSpline`	`cupyx.scipy.interpolate.InterpolatedUnivariateSpline`
`scipy.interpolate.KroghInterpolator`	`cupyx.scipy.interpolate.KroghInterpolator`
`scipy.interpolate.LSQBivariateSpline`	-
`scipy.interpolate.LSQSphereBivariateSpline`	-
`scipy.interpolate.LSQUnivariateSpline`	`cupyx.scipy.interpolate.LSQUnivariateSpline`
`scipy.interpolate.LinearNDInterpolator`	`cupyx.scipy.interpolate.LinearNDInterpolator`
`scipy.interpolate.NdBSpline`	`cupyx.scipy.interpolate.NdBSpline`
`scipy.interpolate.NdPPoly`	`cupyx.scipy.interpolate.NdPPoly`
`scipy.interpolate.NearestNDInterpolator`	`cupyx.scipy.interpolate.NearestNDInterpolator`
`scipy.interpolate.PPoly`	`cupyx.scipy.interpolate.PPoly`
`scipy.interpolate.PchipInterpolator`	`cupyx.scipy.interpolate.PchipInterpolator`
`scipy.interpolate.RBFInterpolator`	`cupyx.scipy.interpolate.RBFInterpolator`
`scipy.interpolate.Rbf`	-
`scipy.interpolate.RectBivariateSpline`	-
`scipy.interpolate.RectSphereBivariateSpline`	-
`scipy.interpolate.RegularGridInterpolator`	`cupyx.scipy.interpolate.RegularGridInterpolator`
`scipy.interpolate.SmoothBivariateSpline`	-
`scipy.interpolate.SmoothSphereBivariateSpline`	-
`scipy.interpolate.UnivariateSpline`	`cupyx.scipy.interpolate.UnivariateSpline`
`scipy.interpolate.approximate_taylor_polynomial`	-
`scipy.interpolate.barycentric_interpolate`	`cupyx.scipy.interpolate.barycentric_interpolate`
`scipy.interpolate.bisplev`	-
`scipy.interpolate.bisplrep`	-
`scipy.interpolate.griddata`	-
`scipy.interpolate.insert`	-
`scipy.interpolate.interp1d`	`cupyx.scipy.interpolate.interp1d`
`scipy.interpolate.interp2d`	-
`scipy.interpolate.interpn`	`cupyx.scipy.interpolate.interpn`
`scipy.interpolate.krogh_interpolate`	`cupyx.scipy.interpolate.krogh_interpolate`
`scipy.interpolate.lagrange`	-
`scipy.interpolate.make_interp_spline`	`cupyx.scipy.interpolate.make_interp_spline`
`scipy.interpolate.make_lsq_spline`	`cupyx.scipy.interpolate.make_lsq_spline`
`scipy.interpolate.make_smoothing_spline`	-
`scipy.interpolate.pade`	-
`scipy.interpolate.pchip`	`cupyx.scipy.interpolate.pchip`
`scipy.interpolate.pchip_interpolate`	`cupyx.scipy.interpolate.pchip_interpolate`
`scipy.interpolate.spalde`	-
`scipy.interpolate.splantider`	`cupyx.scipy.interpolate.splantider`
`scipy.interpolate.splder`	`cupyx.scipy.interpolate.splder`
`scipy.interpolate.splev`	-
`scipy.interpolate.splint`	-
`scipy.interpolate.splprep`	-
`scipy.interpolate.splrep`	-
`scipy.interpolate.sproot`	-

Advanced Linear Algebra#

SciPy	CuPy
`scipy.linalg.bandwidth`	`cupyx.scipy.linalg.bandwidth`
`scipy.linalg.block_diag`	`cupyx.scipy.linalg.block_diag`
`scipy.linalg.cdf2rdf`	-
`scipy.linalg.cho_factor`	-
`scipy.linalg.cho_solve`	-
`scipy.linalg.cho_solve_banded`	-
`scipy.linalg.cholesky_banded`	-
`scipy.linalg.circulant`	`cupyx.scipy.linalg.circulant`
`scipy.linalg.clarkson_woodruff_transform`	-
`scipy.linalg.companion`	`cupyx.scipy.linalg.companion`
`scipy.linalg.convolution_matrix`	`cupyx.scipy.linalg.convolution_matrix`
`scipy.linalg.coshm`	-
`scipy.linalg.cosm`	-
`scipy.linalg.cossin`	-
`scipy.linalg.dft`	`cupyx.scipy.linalg.dft`
`scipy.linalg.diagsvd`	-
`scipy.linalg.eig_banded`	-
`scipy.linalg.eigh_tridiagonal`	-
`scipy.linalg.eigvals_banded`	-
`scipy.linalg.eigvalsh_tridiagonal`	-
`scipy.linalg.expm`	`cupyx.scipy.linalg.expm`
`scipy.linalg.expm_cond`	-
`scipy.linalg.expm_frechet`	-
`scipy.linalg.fiedler`	`cupyx.scipy.linalg.fiedler`
`scipy.linalg.fiedler_companion`	`cupyx.scipy.linalg.fiedler_companion`
`scipy.linalg.find_best_blas_type`	-
`scipy.linalg.fractional_matrix_power`	-
`scipy.linalg.funm`	-
`scipy.linalg.get_blas_funcs`	-
`scipy.linalg.get_lapack_funcs`	-
`scipy.linalg.hadamard`	`cupyx.scipy.linalg.hadamard`
`scipy.linalg.hankel`	`cupyx.scipy.linalg.hankel`
`scipy.linalg.helmert`	`cupyx.scipy.linalg.helmert`
`scipy.linalg.hessenberg`	-
`scipy.linalg.hilbert`	`cupyx.scipy.linalg.hilbert`
`scipy.linalg.invhilbert`	-
`scipy.linalg.invpascal`	-
`scipy.linalg.ishermitian`	-
`scipy.linalg.issymmetric`	-
`scipy.linalg.khatri_rao`	`cupyx.scipy.linalg.khatri_rao`
`scipy.linalg.kron`	`cupyx.scipy.linalg.kron`
`scipy.linalg.ldl`	-
`scipy.linalg.leslie`	`cupyx.scipy.linalg.leslie`
`scipy.linalg.logm`	-
`scipy.linalg.lu`	`cupyx.scipy.linalg.lu`
`scipy.linalg.lu_factor`	`cupyx.scipy.linalg.lu_factor`
`scipy.linalg.lu_solve`	`cupyx.scipy.linalg.lu_solve`
`scipy.linalg.matmul_toeplitz`	-
`scipy.linalg.matrix_balance`	-
`scipy.linalg.null_space`	-
`scipy.linalg.ordqz`	-
`scipy.linalg.orth`	-
`scipy.linalg.orthogonal_procrustes`	-
`scipy.linalg.pascal`	-
`scipy.linalg.pinvh`	-
`scipy.linalg.polar`	-
`scipy.linalg.qr_delete`	-
`scipy.linalg.qr_insert`	-
`scipy.linalg.qr_multiply`	-
`scipy.linalg.qr_update`	-
`scipy.linalg.qz`	-
`scipy.linalg.rq`	-
`scipy.linalg.rsf2csf`	-
`scipy.linalg.schur`	-
`scipy.linalg.signm`	-
`scipy.linalg.sinhm`	-
`scipy.linalg.sinm`	-
`scipy.linalg.solve_banded`	-
`scipy.linalg.solve_circulant`	-
`scipy.linalg.solve_continuous_are`	-
`scipy.linalg.solve_continuous_lyapunov`	-
`scipy.linalg.solve_discrete_are`	-
`scipy.linalg.solve_discrete_lyapunov`	-
`scipy.linalg.solve_lyapunov`	-
`scipy.linalg.solve_sylvester`	-
`scipy.linalg.solve_toeplitz`	-
`scipy.linalg.solve_triangular`	`cupyx.scipy.linalg.solve_triangular`
`scipy.linalg.solveh_banded`	-
`scipy.linalg.sqrtm`	-
`scipy.linalg.subspace_angles`	-
`scipy.linalg.svdvals`	-
`scipy.linalg.tanhm`	-
`scipy.linalg.tanm`	-
`scipy.linalg.toeplitz`	`cupyx.scipy.linalg.toeplitz`

Multidimensional Image Processing#

SciPy	CuPy
`scipy.ndimage.affine_transform`	`cupyx.scipy.ndimage.affine_transform`
`scipy.ndimage.binary_closing`	`cupyx.scipy.ndimage.binary_closing`
`scipy.ndimage.binary_dilation`	`cupyx.scipy.ndimage.binary_dilation`
`scipy.ndimage.binary_erosion`	`cupyx.scipy.ndimage.binary_erosion`
`scipy.ndimage.binary_fill_holes`	`cupyx.scipy.ndimage.binary_fill_holes`
`scipy.ndimage.binary_hit_or_miss`	`cupyx.scipy.ndimage.binary_hit_or_miss`
`scipy.ndimage.binary_opening`	`cupyx.scipy.ndimage.binary_opening`
`scipy.ndimage.binary_propagation`	`cupyx.scipy.ndimage.binary_propagation`
`scipy.ndimage.black_tophat`	`cupyx.scipy.ndimage.black_tophat`
`scipy.ndimage.center_of_mass`	`cupyx.scipy.ndimage.center_of_mass`
`scipy.ndimage.convolve`	`cupyx.scipy.ndimage.convolve`
`scipy.ndimage.convolve1d`	`cupyx.scipy.ndimage.convolve1d`
`scipy.ndimage.correlate`	`cupyx.scipy.ndimage.correlate`
`scipy.ndimage.correlate1d`	`cupyx.scipy.ndimage.correlate1d`
`scipy.ndimage.distance_transform_bf`	-
`scipy.ndimage.distance_transform_cdt`	-
`scipy.ndimage.distance_transform_edt`	`cupyx.scipy.ndimage.distance_transform_edt`
`scipy.ndimage.extrema`	`cupyx.scipy.ndimage.extrema`
`scipy.ndimage.find_objects`	-
`scipy.ndimage.fourier_ellipsoid`	`cupyx.scipy.ndimage.fourier_ellipsoid`
`scipy.ndimage.fourier_gaussian`	`cupyx.scipy.ndimage.fourier_gaussian`
`scipy.ndimage.fourier_shift`	`cupyx.scipy.ndimage.fourier_shift`
`scipy.ndimage.fourier_uniform`	`cupyx.scipy.ndimage.fourier_uniform`
`scipy.ndimage.gaussian_filter`	`cupyx.scipy.ndimage.gaussian_filter`
`scipy.ndimage.gaussian_filter1d`	`cupyx.scipy.ndimage.gaussian_filter1d`
`scipy.ndimage.gaussian_gradient_magnitude`	`cupyx.scipy.ndimage.gaussian_gradient_magnitude`
`scipy.ndimage.gaussian_laplace`	`cupyx.scipy.ndimage.gaussian_laplace`
`scipy.ndimage.generate_binary_structure`	`cupyx.scipy.ndimage.generate_binary_structure`
`scipy.ndimage.generic_filter`	`cupyx.scipy.ndimage.generic_filter`
`scipy.ndimage.generic_filter1d`	`cupyx.scipy.ndimage.generic_filter1d`
`scipy.ndimage.generic_gradient_magnitude`	`cupyx.scipy.ndimage.generic_gradient_magnitude`
`scipy.ndimage.generic_laplace`	`cupyx.scipy.ndimage.generic_laplace`
`scipy.ndimage.geometric_transform`	-
`scipy.ndimage.grey_closing`	`cupyx.scipy.ndimage.grey_closing`
`scipy.ndimage.grey_dilation`	`cupyx.scipy.ndimage.grey_dilation`
`scipy.ndimage.grey_erosion`	`cupyx.scipy.ndimage.grey_erosion`
`scipy.ndimage.grey_opening`	`cupyx.scipy.ndimage.grey_opening`
`scipy.ndimage.histogram`	`cupyx.scipy.ndimage.histogram`
`scipy.ndimage.iterate_structure`	`cupyx.scipy.ndimage.iterate_structure`
`scipy.ndimage.label`	`cupyx.scipy.ndimage.label`
`scipy.ndimage.labeled_comprehension`	`cupyx.scipy.ndimage.labeled_comprehension`
`scipy.ndimage.laplace`	`cupyx.scipy.ndimage.laplace`
`scipy.ndimage.map_coordinates`	`cupyx.scipy.ndimage.map_coordinates`
`scipy.ndimage.maximum`	`cupyx.scipy.ndimage.maximum`
`scipy.ndimage.maximum_filter`	`cupyx.scipy.ndimage.maximum_filter`
`scipy.ndimage.maximum_filter1d`	`cupyx.scipy.ndimage.maximum_filter1d`
`scipy.ndimage.maximum_position`	`cupyx.scipy.ndimage.maximum_position`
`scipy.ndimage.mean`	`cupyx.scipy.ndimage.mean`
`scipy.ndimage.median`	`cupyx.scipy.ndimage.median`
`scipy.ndimage.median_filter`	`cupyx.scipy.ndimage.median_filter`
`scipy.ndimage.minimum`	`cupyx.scipy.ndimage.minimum`
`scipy.ndimage.minimum_filter`	`cupyx.scipy.ndimage.minimum_filter`
`scipy.ndimage.minimum_filter1d`	`cupyx.scipy.ndimage.minimum_filter1d`
`scipy.ndimage.minimum_position`	`cupyx.scipy.ndimage.minimum_position`
`scipy.ndimage.morphological_gradient`	`cupyx.scipy.ndimage.morphological_gradient`
`scipy.ndimage.morphological_laplace`	`cupyx.scipy.ndimage.morphological_laplace`
`scipy.ndimage.percentile_filter`	`cupyx.scipy.ndimage.percentile_filter`
`scipy.ndimage.prewitt`	`cupyx.scipy.ndimage.prewitt`
`scipy.ndimage.rank_filter`	`cupyx.scipy.ndimage.rank_filter`
`scipy.ndimage.rotate`	`cupyx.scipy.ndimage.rotate`
`scipy.ndimage.shift`	`cupyx.scipy.ndimage.shift`
`scipy.ndimage.sobel`	`cupyx.scipy.ndimage.sobel`
`scipy.ndimage.spline_filter`	`cupyx.scipy.ndimage.spline_filter`
`scipy.ndimage.spline_filter1d`	`cupyx.scipy.ndimage.spline_filter1d`
`scipy.ndimage.standard_deviation`	`cupyx.scipy.ndimage.standard_deviation`
`scipy.ndimage.sum`	`cupyx.scipy.ndimage.sum`
`scipy.ndimage.sum_labels`	`cupyx.scipy.ndimage.sum_labels`
`scipy.ndimage.uniform_filter`	`cupyx.scipy.ndimage.uniform_filter`
`scipy.ndimage.uniform_filter1d`	`cupyx.scipy.ndimage.uniform_filter1d`
`scipy.ndimage.value_indices`	`cupyx.scipy.ndimage.value_indices`
`scipy.ndimage.variance`	`cupyx.scipy.ndimage.variance`
`scipy.ndimage.watershed_ift`	-
`scipy.ndimage.white_tophat`	`cupyx.scipy.ndimage.white_tophat`
`scipy.ndimage.zoom`	`cupyx.scipy.ndimage.zoom`

Signal processing#

SciPy	CuPy
`scipy.signal.CZT`	`cupyx.scipy.signal.CZT`
`scipy.signal.ShortTimeFFT`	-
`scipy.signal.StateSpace`	`cupyx.scipy.signal.StateSpace`
`scipy.signal.TransferFunction`	`cupyx.scipy.signal.TransferFunction`
`scipy.signal.ZerosPolesGain`	`cupyx.scipy.signal.ZerosPolesGain`
`scipy.signal.ZoomFFT`	`cupyx.scipy.signal.ZoomFFT`
`scipy.signal.abcd_normalize`	`cupyx.scipy.signal.abcd_normalize`
`scipy.signal.argrelextrema`	`cupyx.scipy.signal.argrelextrema`
`scipy.signal.argrelmax`	`cupyx.scipy.signal.argrelmax`
`scipy.signal.argrelmin`	`cupyx.scipy.signal.argrelmin`
`scipy.signal.band_stop_obj`	`cupyx.scipy.signal.band_stop_obj`
`scipy.signal.bessel`	-
`scipy.signal.besselap`	-
`scipy.signal.bilinear`	`cupyx.scipy.signal.bilinear`
`scipy.signal.bilinear_zpk`	`cupyx.scipy.signal.bilinear_zpk`
`scipy.signal.bode`	`cupyx.scipy.signal.bode`
`scipy.signal.buttap`	`cupyx.scipy.signal.buttap`
`scipy.signal.butter`	`cupyx.scipy.signal.butter`
`scipy.signal.buttord`	`cupyx.scipy.signal.buttord`
`scipy.signal.cascade`	-
`scipy.signal.cheb1ap`	`cupyx.scipy.signal.cheb1ap`
`scipy.signal.cheb1ord`	`cupyx.scipy.signal.cheb1ord`
`scipy.signal.cheb2ap`	`cupyx.scipy.signal.cheb2ap`
`scipy.signal.cheb2ord`	`cupyx.scipy.signal.cheb2ord`
`scipy.signal.cheby1`	`cupyx.scipy.signal.cheby1`
`scipy.signal.cheby2`	`cupyx.scipy.signal.cheby2`
`scipy.signal.check_COLA`	`cupyx.scipy.signal.check_COLA`
`scipy.signal.check_NOLA`	`cupyx.scipy.signal.check_NOLA`
`scipy.signal.chirp`	`cupyx.scipy.signal.chirp`
`scipy.signal.choose_conv_method`	`cupyx.scipy.signal.choose_conv_method`
`scipy.signal.cmplx_sort`	-
`scipy.signal.coherence`	`cupyx.scipy.signal.coherence`
`scipy.signal.cont2discrete`	`cupyx.scipy.signal.cont2discrete`
`scipy.signal.convolve`	`cupyx.scipy.signal.convolve`
`scipy.signal.convolve2d`	`cupyx.scipy.signal.convolve2d`
`scipy.signal.correlate`	`cupyx.scipy.signal.correlate`
`scipy.signal.correlate2d`	`cupyx.scipy.signal.correlate2d`
`scipy.signal.correlation_lags`	`cupyx.scipy.signal.correlation_lags`
`scipy.signal.csd`	`cupyx.scipy.signal.csd`
`scipy.signal.cspline1d`	`cupyx.scipy.signal.cspline1d`
`scipy.signal.cspline1d_eval`	`cupyx.scipy.signal.cspline1d_eval`
`scipy.signal.cspline2d`	`cupyx.scipy.signal.cspline2d`
`scipy.signal.cwt`	`cupyx.scipy.signal.cwt`
`scipy.signal.czt`	`cupyx.scipy.signal.czt`
`scipy.signal.czt_points`	`cupyx.scipy.signal.czt_points`
`scipy.signal.daub`	-
`scipy.signal.dbode`	`cupyx.scipy.signal.dbode`
`scipy.signal.decimate`	`cupyx.scipy.signal.decimate`
`scipy.signal.deconvolve`	`cupyx.scipy.signal.deconvolve`
`scipy.signal.detrend`	`cupyx.scipy.signal.detrend`
`scipy.signal.dfreqresp`	`cupyx.scipy.signal.dfreqresp`
`scipy.signal.dimpulse`	`cupyx.scipy.signal.dimpulse`
`scipy.signal.dlsim`	`cupyx.scipy.signal.dlsim`
`scipy.signal.dlti`	`cupyx.scipy.signal.dlti`
`scipy.signal.dstep`	`cupyx.scipy.signal.dstep`
`scipy.signal.ellip`	`cupyx.scipy.signal.ellip`
`scipy.signal.ellipap`	`cupyx.scipy.signal.ellipap`
`scipy.signal.ellipord`	`cupyx.scipy.signal.ellipord`
`scipy.signal.fftconvolve`	`cupyx.scipy.signal.fftconvolve`
`scipy.signal.filtfilt`	`cupyx.scipy.signal.filtfilt`
`scipy.signal.find_peaks`	`cupyx.scipy.signal.find_peaks`
`scipy.signal.find_peaks_cwt`	-
`scipy.signal.findfreqs`	`cupyx.scipy.signal.findfreqs`
`scipy.signal.firls`	`cupyx.scipy.signal.firls`
`scipy.signal.firwin`	`cupyx.scipy.signal.firwin`
`scipy.signal.firwin2`	`cupyx.scipy.signal.firwin2`
`scipy.signal.freqresp`	`cupyx.scipy.signal.freqresp`
`scipy.signal.freqs`	`cupyx.scipy.signal.freqs`
`scipy.signal.freqs_zpk`	`cupyx.scipy.signal.freqs_zpk`
`scipy.signal.freqz`	`cupyx.scipy.signal.freqz`
`scipy.signal.freqz_zpk`	`cupyx.scipy.signal.freqz_zpk`
`scipy.signal.gammatone`	`cupyx.scipy.signal.gammatone`
`scipy.signal.gauss_spline`	`cupyx.scipy.signal.gauss_spline`
`scipy.signal.gausspulse`	`cupyx.scipy.signal.gausspulse`
`scipy.signal.get_window`	`cupyx.scipy.signal.get_window`
`scipy.signal.group_delay`	`cupyx.scipy.signal.group_delay`
`scipy.signal.hilbert`	`cupyx.scipy.signal.hilbert`
`scipy.signal.hilbert2`	`cupyx.scipy.signal.hilbert2`
`scipy.signal.iircomb`	`cupyx.scipy.signal.iircomb`
`scipy.signal.iirdesign`	`cupyx.scipy.signal.iirdesign`
`scipy.signal.iirfilter`	`cupyx.scipy.signal.iirfilter`
`scipy.signal.iirnotch`	`cupyx.scipy.signal.iirnotch`
`scipy.signal.iirpeak`	`cupyx.scipy.signal.iirpeak`
`scipy.signal.impulse`	`cupyx.scipy.signal.impulse`
`scipy.signal.invres`	`cupyx.scipy.signal.invres`
`scipy.signal.invresz`	`cupyx.scipy.signal.invresz`
`scipy.signal.istft`	`cupyx.scipy.signal.istft`
`scipy.signal.kaiser_atten`	`cupyx.scipy.signal.kaiser_atten`
`scipy.signal.kaiser_beta`	`cupyx.scipy.signal.kaiser_beta`
`scipy.signal.kaiserord`	`cupyx.scipy.signal.kaiserord`
`scipy.signal.lfilter`	`cupyx.scipy.signal.lfilter`
`scipy.signal.lfilter_zi`	`cupyx.scipy.signal.lfilter_zi`
`scipy.signal.lfiltic`	`cupyx.scipy.signal.lfiltic`
`scipy.signal.lombscargle`	`cupyx.scipy.signal.lombscargle`
`scipy.signal.lp2bp`	`cupyx.scipy.signal.lp2bp`
`scipy.signal.lp2bp_zpk`	`cupyx.scipy.signal.lp2bp_zpk`
`scipy.signal.lp2bs`	`cupyx.scipy.signal.lp2bs`
`scipy.signal.lp2bs_zpk`	`cupyx.scipy.signal.lp2bs_zpk`
`scipy.signal.lp2hp`	`cupyx.scipy.signal.lp2hp`
`scipy.signal.lp2hp_zpk`	`cupyx.scipy.signal.lp2hp_zpk`
`scipy.signal.lp2lp`	`cupyx.scipy.signal.lp2lp`
`scipy.signal.lp2lp_zpk`	`cupyx.scipy.signal.lp2lp_zpk`
`scipy.signal.lsim`	`cupyx.scipy.signal.lsim`
`scipy.signal.lti`	`cupyx.scipy.signal.lti`
`scipy.signal.max_len_seq`	`cupyx.scipy.signal.max_len_seq`
`scipy.signal.medfilt`	`cupyx.scipy.signal.medfilt`
`scipy.signal.medfilt2d`	`cupyx.scipy.signal.medfilt2d`
`scipy.signal.minimum_phase`	`cupyx.scipy.signal.minimum_phase`
`scipy.signal.morlet`	`cupyx.scipy.signal.morlet`
`scipy.signal.morlet2`	`cupyx.scipy.signal.morlet2`
`scipy.signal.normalize`	`cupyx.scipy.signal.normalize`
`scipy.signal.oaconvolve`	`cupyx.scipy.signal.oaconvolve`
`scipy.signal.order_filter`	`cupyx.scipy.signal.order_filter`
`scipy.signal.peak_prominences`	`cupyx.scipy.signal.peak_prominences`
`scipy.signal.peak_widths`	`cupyx.scipy.signal.peak_widths`
`scipy.signal.periodogram`	`cupyx.scipy.signal.periodogram`
`scipy.signal.place_poles`	`cupyx.scipy.signal.place_poles`
`scipy.signal.qmf`	`cupyx.scipy.signal.qmf`
`scipy.signal.qspline1d`	`cupyx.scipy.signal.qspline1d`
`scipy.signal.qspline1d_eval`	`cupyx.scipy.signal.qspline1d_eval`
`scipy.signal.qspline2d`	`cupyx.scipy.signal.qspline2d`
`scipy.signal.remez`	-
`scipy.signal.resample`	`cupyx.scipy.signal.resample`
`scipy.signal.resample_poly`	`cupyx.scipy.signal.resample_poly`
`scipy.signal.residue`	`cupyx.scipy.signal.residue`
`scipy.signal.residuez`	`cupyx.scipy.signal.residuez`
`scipy.signal.ricker`	`cupyx.scipy.signal.ricker`
`scipy.signal.savgol_coeffs`	`cupyx.scipy.signal.savgol_coeffs`
`scipy.signal.savgol_filter`	`cupyx.scipy.signal.savgol_filter`
`scipy.signal.sawtooth`	`cupyx.scipy.signal.sawtooth`
`scipy.signal.sepfir2d`	`cupyx.scipy.signal.sepfir2d`
`scipy.signal.sos2tf`	`cupyx.scipy.signal.sos2tf`
`scipy.signal.sos2zpk`	`cupyx.scipy.signal.sos2zpk`
`scipy.signal.sosfilt`	`cupyx.scipy.signal.sosfilt`
`scipy.signal.sosfilt_zi`	`cupyx.scipy.signal.sosfilt_zi`
`scipy.signal.sosfiltfilt`	`cupyx.scipy.signal.sosfiltfilt`
`scipy.signal.sosfreqz`	`cupyx.scipy.signal.sosfreqz`
`scipy.signal.spectrogram`	`cupyx.scipy.signal.spectrogram`
`scipy.signal.spline_filter`	`cupyx.scipy.signal.spline_filter`
`scipy.signal.square`	`cupyx.scipy.signal.square`
`scipy.signal.ss2tf`	`cupyx.scipy.signal.ss2tf`
`scipy.signal.ss2zpk`	`cupyx.scipy.signal.ss2zpk`
`scipy.signal.step`	`cupyx.scipy.signal.step`
`scipy.signal.stft`	`cupyx.scipy.signal.stft`
`scipy.signal.sweep_poly`	`cupyx.scipy.signal.sweep_poly`
`scipy.signal.symiirorder1`	`cupyx.scipy.signal.symiirorder1`
`scipy.signal.symiirorder2`	`cupyx.scipy.signal.symiirorder2`
`scipy.signal.tf2sos`	`cupyx.scipy.signal.tf2sos`
`scipy.signal.tf2ss`	`cupyx.scipy.signal.tf2ss`
`scipy.signal.tf2zpk`	`cupyx.scipy.signal.tf2zpk`
`scipy.signal.unique_roots`	`cupyx.scipy.signal.unique_roots`
`scipy.signal.unit_impulse`	`cupyx.scipy.signal.unit_impulse`
`scipy.signal.upfirdn`	`cupyx.scipy.signal.upfirdn`
`scipy.signal.vectorstrength`	`cupyx.scipy.signal.vectorstrength`
`scipy.signal.welch`	`cupyx.scipy.signal.welch`
`scipy.signal.wiener`	`cupyx.scipy.signal.wiener`
`scipy.signal.zoom_fft`	`cupyx.scipy.signal.zoom_fft`
`scipy.signal.zpk2sos`	`cupyx.scipy.signal.zpk2sos`
`scipy.signal.zpk2ss`	`cupyx.scipy.signal.zpk2ss`
`scipy.signal.zpk2tf`	`cupyx.scipy.signal.zpk2tf`

Sparse Matrices#

SciPy	CuPy
`scipy.sparse.block_array`	-
`scipy.sparse.block_diag`	-
`scipy.sparse.bmat`	`cupyx.scipy.sparse.bmat`
`scipy.sparse.bsr_array`	-
`scipy.sparse.bsr_matrix`	-
`scipy.sparse.coo_array`	-
`scipy.sparse.coo_matrix`	`cupyx.scipy.sparse.coo_matrix`
`scipy.sparse.csc_array`	-
`scipy.sparse.csc_matrix`	`cupyx.scipy.sparse.csc_matrix`
`scipy.sparse.csr_array`	-
`scipy.sparse.csr_matrix`	`cupyx.scipy.sparse.csr_matrix`
`scipy.sparse.dia_array`	-
`scipy.sparse.dia_matrix`	`cupyx.scipy.sparse.dia_matrix`
`scipy.sparse.diags`	`cupyx.scipy.sparse.diags`
`scipy.sparse.diags_array`	-
`scipy.sparse.dok_array`	-
`scipy.sparse.dok_matrix`	-
`scipy.sparse.eye`	`cupyx.scipy.sparse.eye`
`scipy.sparse.eye_array`	-
`scipy.sparse.find`	`cupyx.scipy.sparse.find`
`scipy.sparse.hstack`	`cupyx.scipy.sparse.hstack`
`scipy.sparse.identity`	`cupyx.scipy.sparse.identity`
`scipy.sparse.issparse`	`cupyx.scipy.sparse.issparse`
`scipy.sparse.isspmatrix`	`cupyx.scipy.sparse.isspmatrix`
`scipy.sparse.isspmatrix_bsr`	-
`scipy.sparse.isspmatrix_coo`	`cupyx.scipy.sparse.isspmatrix_coo`
`scipy.sparse.isspmatrix_csc`	`cupyx.scipy.sparse.isspmatrix_csc`
`scipy.sparse.isspmatrix_csr`	`cupyx.scipy.sparse.isspmatrix_csr`
`scipy.sparse.isspmatrix_dia`	`cupyx.scipy.sparse.isspmatrix_dia`
`scipy.sparse.isspmatrix_dok`	-
`scipy.sparse.isspmatrix_lil`	-
`scipy.sparse.kron`	`cupyx.scipy.sparse.kron`
`scipy.sparse.kronsum`	`cupyx.scipy.sparse.kronsum`
`scipy.sparse.lil_array`	-
`scipy.sparse.lil_matrix`	-
`scipy.sparse.load_npz`	-
`scipy.sparse.rand`	`cupyx.scipy.sparse.rand`
`scipy.sparse.random`	`cupyx.scipy.sparse.random`
`scipy.sparse.random_array`	-
`scipy.sparse.save_npz`	-
`scipy.sparse.sparray`	-
`scipy.sparse.spdiags`	`cupyx.scipy.sparse.spdiags`
`scipy.sparse.spmatrix`	`cupyx.scipy.sparse.spmatrix`
`scipy.sparse.tril`	`cupyx.scipy.sparse.tril`
`scipy.sparse.triu`	`cupyx.scipy.sparse.triu`
`scipy.sparse.vstack`	`cupyx.scipy.sparse.vstack`

Sparse Matrices: COOrdinate Format#

SciPy	CuPy
`scipy.sparse.coo_matrix.T`	`cupyx.scipy.sparse.coo_matrix.T`
`scipy.sparse.coo_matrix.arcsin`	`cupyx.scipy.sparse.coo_matrix.arcsin`
`scipy.sparse.coo_matrix.arcsinh`	`cupyx.scipy.sparse.coo_matrix.arcsinh`
`scipy.sparse.coo_matrix.arctan`	`cupyx.scipy.sparse.coo_matrix.arctan`
`scipy.sparse.coo_matrix.arctanh`	`cupyx.scipy.sparse.coo_matrix.arctanh`
`scipy.sparse.coo_matrix.argmax`	-
`scipy.sparse.coo_matrix.argmin`	-
`scipy.sparse.coo_matrix.asformat`	`cupyx.scipy.sparse.coo_matrix.asformat`
`scipy.sparse.coo_matrix.asfptype`	`cupyx.scipy.sparse.coo_matrix.asfptype`
`scipy.sparse.coo_matrix.astype`	`cupyx.scipy.sparse.coo_matrix.astype`
`scipy.sparse.coo_matrix.ceil`	`cupyx.scipy.sparse.coo_matrix.ceil`
`scipy.sparse.coo_matrix.col`	-
`scipy.sparse.coo_matrix.conj`	`cupyx.scipy.sparse.coo_matrix.conj`
`scipy.sparse.coo_matrix.conjugate`	`cupyx.scipy.sparse.coo_matrix.conjugate`
`scipy.sparse.coo_matrix.copy`	`cupyx.scipy.sparse.coo_matrix.copy`
`scipy.sparse.coo_matrix.count_nonzero`	`cupyx.scipy.sparse.coo_matrix.count_nonzero`
`scipy.sparse.coo_matrix.deg2rad`	`cupyx.scipy.sparse.coo_matrix.deg2rad`
`scipy.sparse.coo_matrix.diagonal`	`cupyx.scipy.sparse.coo_matrix.diagonal`
`scipy.sparse.coo_matrix.dot`	`cupyx.scipy.sparse.coo_matrix.dot`
`scipy.sparse.coo_matrix.dtype`	`cupyx.scipy.sparse.coo_matrix.dtype`
`scipy.sparse.coo_matrix.eliminate_zeros`	`cupyx.scipy.sparse.coo_matrix.eliminate_zeros`
`scipy.sparse.coo_matrix.expm1`	`cupyx.scipy.sparse.coo_matrix.expm1`
`scipy.sparse.coo_matrix.floor`	`cupyx.scipy.sparse.coo_matrix.floor`
`scipy.sparse.coo_matrix.format`	-
`scipy.sparse.coo_matrix.getH`	`cupyx.scipy.sparse.coo_matrix.getH`
`scipy.sparse.coo_matrix.get_shape`	`cupyx.scipy.sparse.coo_matrix.get_shape`
`scipy.sparse.coo_matrix.getcol`	-
`scipy.sparse.coo_matrix.getformat`	`cupyx.scipy.sparse.coo_matrix.getformat`
`scipy.sparse.coo_matrix.getmaxprint`	`cupyx.scipy.sparse.coo_matrix.getmaxprint`
`scipy.sparse.coo_matrix.getnnz`	`cupyx.scipy.sparse.coo_matrix.getnnz`
`scipy.sparse.coo_matrix.getrow`	-
`scipy.sparse.coo_matrix.imag`	-
`scipy.sparse.coo_matrix.log1p`	`cupyx.scipy.sparse.coo_matrix.log1p`
`scipy.sparse.coo_matrix.max`	-
`scipy.sparse.coo_matrix.maximum`	`cupyx.scipy.sparse.coo_matrix.maximum`
`scipy.sparse.coo_matrix.mean`	`cupyx.scipy.sparse.coo_matrix.mean`
`scipy.sparse.coo_matrix.min`	-
`scipy.sparse.coo_matrix.minimum`	`cupyx.scipy.sparse.coo_matrix.minimum`
`scipy.sparse.coo_matrix.multiply`	`cupyx.scipy.sparse.coo_matrix.multiply`
`scipy.sparse.coo_matrix.nanmax`	-
`scipy.sparse.coo_matrix.nanmin`	-
`scipy.sparse.coo_matrix.ndim`	`cupyx.scipy.sparse.coo_matrix.ndim`
`scipy.sparse.coo_matrix.nnz`	`cupyx.scipy.sparse.coo_matrix.nnz`
`scipy.sparse.coo_matrix.nonzero`	-
`scipy.sparse.coo_matrix.power`	`cupyx.scipy.sparse.coo_matrix.power`
`scipy.sparse.coo_matrix.rad2deg`	`cupyx.scipy.sparse.coo_matrix.rad2deg`
`scipy.sparse.coo_matrix.real`	-
`scipy.sparse.coo_matrix.reshape`	`cupyx.scipy.sparse.coo_matrix.reshape`
`scipy.sparse.coo_matrix.resize`	-
`scipy.sparse.coo_matrix.rint`	`cupyx.scipy.sparse.coo_matrix.rint`
`scipy.sparse.coo_matrix.row`	-
`scipy.sparse.coo_matrix.set_shape`	`cupyx.scipy.sparse.coo_matrix.set_shape`
`scipy.sparse.coo_matrix.setdiag`	`cupyx.scipy.sparse.coo_matrix.setdiag`
`scipy.sparse.coo_matrix.shape`	`cupyx.scipy.sparse.coo_matrix.shape`
`scipy.sparse.coo_matrix.sign`	`cupyx.scipy.sparse.coo_matrix.sign`
`scipy.sparse.coo_matrix.sin`	`cupyx.scipy.sparse.coo_matrix.sin`
`scipy.sparse.coo_matrix.sinh`	`cupyx.scipy.sparse.coo_matrix.sinh`
`scipy.sparse.coo_matrix.size`	`cupyx.scipy.sparse.coo_matrix.size`
`scipy.sparse.coo_matrix.sqrt`	`cupyx.scipy.sparse.coo_matrix.sqrt`
`scipy.sparse.coo_matrix.sum`	`cupyx.scipy.sparse.coo_matrix.sum`
`scipy.sparse.coo_matrix.sum_duplicates`	`cupyx.scipy.sparse.coo_matrix.sum_duplicates`
`scipy.sparse.coo_matrix.tan`	`cupyx.scipy.sparse.coo_matrix.tan`
`scipy.sparse.coo_matrix.tanh`	`cupyx.scipy.sparse.coo_matrix.tanh`
`scipy.sparse.coo_matrix.toarray`	`cupyx.scipy.sparse.coo_matrix.toarray`
`scipy.sparse.coo_matrix.tobsr`	`cupyx.scipy.sparse.coo_matrix.tobsr`
`scipy.sparse.coo_matrix.tocoo`	`cupyx.scipy.sparse.coo_matrix.tocoo`
`scipy.sparse.coo_matrix.tocsc`	`cupyx.scipy.sparse.coo_matrix.tocsc`
`scipy.sparse.coo_matrix.tocsr`	`cupyx.scipy.sparse.coo_matrix.tocsr`
`scipy.sparse.coo_matrix.todense`	`cupyx.scipy.sparse.coo_matrix.todense`
`scipy.sparse.coo_matrix.todia`	`cupyx.scipy.sparse.coo_matrix.todia`
`scipy.sparse.coo_matrix.todok`	`cupyx.scipy.sparse.coo_matrix.todok`
`scipy.sparse.coo_matrix.tolil`	`cupyx.scipy.sparse.coo_matrix.tolil`
`scipy.sparse.coo_matrix.trace`	-
`scipy.sparse.coo_matrix.transpose`	`cupyx.scipy.sparse.coo_matrix.transpose`
`scipy.sparse.coo_matrix.trunc`	`cupyx.scipy.sparse.coo_matrix.trunc`

Sparse Matrices: Compressed Sparse Column#

SciPy	CuPy
`scipy.sparse.csc_matrix.T`	`cupyx.scipy.sparse.csc_matrix.T`
`scipy.sparse.csc_matrix.arcsin`	`cupyx.scipy.sparse.csc_matrix.arcsin`
`scipy.sparse.csc_matrix.arcsinh`	`cupyx.scipy.sparse.csc_matrix.arcsinh`
`scipy.sparse.csc_matrix.arctan`	`cupyx.scipy.sparse.csc_matrix.arctan`
`scipy.sparse.csc_matrix.arctanh`	`cupyx.scipy.sparse.csc_matrix.arctanh`
`scipy.sparse.csc_matrix.argmax`	`cupyx.scipy.sparse.csc_matrix.argmax`
`scipy.sparse.csc_matrix.argmin`	`cupyx.scipy.sparse.csc_matrix.argmin`
`scipy.sparse.csc_matrix.asformat`	`cupyx.scipy.sparse.csc_matrix.asformat`
`scipy.sparse.csc_matrix.asfptype`	`cupyx.scipy.sparse.csc_matrix.asfptype`
`scipy.sparse.csc_matrix.astype`	`cupyx.scipy.sparse.csc_matrix.astype`
`scipy.sparse.csc_matrix.ceil`	`cupyx.scipy.sparse.csc_matrix.ceil`
`scipy.sparse.csc_matrix.check_format`	-
`scipy.sparse.csc_matrix.conj`	`cupyx.scipy.sparse.csc_matrix.conj`
`scipy.sparse.csc_matrix.conjugate`	`cupyx.scipy.sparse.csc_matrix.conjugate`
`scipy.sparse.csc_matrix.copy`	`cupyx.scipy.sparse.csc_matrix.copy`
`scipy.sparse.csc_matrix.count_nonzero`	`cupyx.scipy.sparse.csc_matrix.count_nonzero`
`scipy.sparse.csc_matrix.deg2rad`	`cupyx.scipy.sparse.csc_matrix.deg2rad`
`scipy.sparse.csc_matrix.diagonal`	`cupyx.scipy.sparse.csc_matrix.diagonal`
`scipy.sparse.csc_matrix.dot`	`cupyx.scipy.sparse.csc_matrix.dot`
`scipy.sparse.csc_matrix.dtype`	`cupyx.scipy.sparse.csc_matrix.dtype`
`scipy.sparse.csc_matrix.eliminate_zeros`	`cupyx.scipy.sparse.csc_matrix.eliminate_zeros`
`scipy.sparse.csc_matrix.expm1`	`cupyx.scipy.sparse.csc_matrix.expm1`
`scipy.sparse.csc_matrix.floor`	`cupyx.scipy.sparse.csc_matrix.floor`
`scipy.sparse.csc_matrix.format`	-
`scipy.sparse.csc_matrix.getH`	`cupyx.scipy.sparse.csc_matrix.getH`
`scipy.sparse.csc_matrix.get_shape`	`cupyx.scipy.sparse.csc_matrix.get_shape`
`scipy.sparse.csc_matrix.getcol`	`cupyx.scipy.sparse.csc_matrix.getcol`
`scipy.sparse.csc_matrix.getformat`	`cupyx.scipy.sparse.csc_matrix.getformat`
`scipy.sparse.csc_matrix.getmaxprint`	`cupyx.scipy.sparse.csc_matrix.getmaxprint`
`scipy.sparse.csc_matrix.getnnz`	`cupyx.scipy.sparse.csc_matrix.getnnz`
`scipy.sparse.csc_matrix.getrow`	`cupyx.scipy.sparse.csc_matrix.getrow`
`scipy.sparse.csc_matrix.has_canonical_format`	`cupyx.scipy.sparse.csc_matrix.has_canonical_format`
`scipy.sparse.csc_matrix.has_sorted_indices`	`cupyx.scipy.sparse.csc_matrix.has_sorted_indices`
`scipy.sparse.csc_matrix.imag`	-
`scipy.sparse.csc_matrix.log1p`	`cupyx.scipy.sparse.csc_matrix.log1p`
`scipy.sparse.csc_matrix.max`	`cupyx.scipy.sparse.csc_matrix.max`
`scipy.sparse.csc_matrix.maximum`	`cupyx.scipy.sparse.csc_matrix.maximum`
`scipy.sparse.csc_matrix.mean`	`cupyx.scipy.sparse.csc_matrix.mean`
`scipy.sparse.csc_matrix.min`	`cupyx.scipy.sparse.csc_matrix.min`
`scipy.sparse.csc_matrix.minimum`	`cupyx.scipy.sparse.csc_matrix.minimum`
`scipy.sparse.csc_matrix.multiply`	`cupyx.scipy.sparse.csc_matrix.multiply`
`scipy.sparse.csc_matrix.nanmax`	-
`scipy.sparse.csc_matrix.nanmin`	-
`scipy.sparse.csc_matrix.ndim`	`cupyx.scipy.sparse.csc_matrix.ndim`
`scipy.sparse.csc_matrix.nnz`	`cupyx.scipy.sparse.csc_matrix.nnz`
`scipy.sparse.csc_matrix.nonzero`	-
`scipy.sparse.csc_matrix.power`	`cupyx.scipy.sparse.csc_matrix.power`
`scipy.sparse.csc_matrix.prune`	-
`scipy.sparse.csc_matrix.rad2deg`	`cupyx.scipy.sparse.csc_matrix.rad2deg`
`scipy.sparse.csc_matrix.real`	-
`scipy.sparse.csc_matrix.reshape`	`cupyx.scipy.sparse.csc_matrix.reshape`
`scipy.sparse.csc_matrix.resize`	-
`scipy.sparse.csc_matrix.rint`	`cupyx.scipy.sparse.csc_matrix.rint`
`scipy.sparse.csc_matrix.set_shape`	`cupyx.scipy.sparse.csc_matrix.set_shape`
`scipy.sparse.csc_matrix.setdiag`	`cupyx.scipy.sparse.csc_matrix.setdiag`
`scipy.sparse.csc_matrix.shape`	`cupyx.scipy.sparse.csc_matrix.shape`
`scipy.sparse.csc_matrix.sign`	`cupyx.scipy.sparse.csc_matrix.sign`
`scipy.sparse.csc_matrix.sin`	`cupyx.scipy.sparse.csc_matrix.sin`
`scipy.sparse.csc_matrix.sinh`	`cupyx.scipy.sparse.csc_matrix.sinh`
`scipy.sparse.csc_matrix.size`	`cupyx.scipy.sparse.csc_matrix.size`
`scipy.sparse.csc_matrix.sort_indices`	`cupyx.scipy.sparse.csc_matrix.sort_indices`
`scipy.sparse.csc_matrix.sorted_indices`	`cupyx.scipy.sparse.csc_matrix.sorted_indices`
`scipy.sparse.csc_matrix.sqrt`	`cupyx.scipy.sparse.csc_matrix.sqrt`
`scipy.sparse.csc_matrix.sum`	`cupyx.scipy.sparse.csc_matrix.sum`
`scipy.sparse.csc_matrix.sum_duplicates`	`cupyx.scipy.sparse.csc_matrix.sum_duplicates`
`scipy.sparse.csc_matrix.tan`	`cupyx.scipy.sparse.csc_matrix.tan`
`scipy.sparse.csc_matrix.tanh`	`cupyx.scipy.sparse.csc_matrix.tanh`
`scipy.sparse.csc_matrix.toarray`	`cupyx.scipy.sparse.csc_matrix.toarray`
`scipy.sparse.csc_matrix.tobsr`	`cupyx.scipy.sparse.csc_matrix.tobsr`
`scipy.sparse.csc_matrix.tocoo`	`cupyx.scipy.sparse.csc_matrix.tocoo`
`scipy.sparse.csc_matrix.tocsc`	`cupyx.scipy.sparse.csc_matrix.tocsc`
`scipy.sparse.csc_matrix.tocsr`	`cupyx.scipy.sparse.csc_matrix.tocsr`
`scipy.sparse.csc_matrix.todense`	`cupyx.scipy.sparse.csc_matrix.todense`
`scipy.sparse.csc_matrix.todia`	`cupyx.scipy.sparse.csc_matrix.todia`
`scipy.sparse.csc_matrix.todok`	`cupyx.scipy.sparse.csc_matrix.todok`
`scipy.sparse.csc_matrix.tolil`	`cupyx.scipy.sparse.csc_matrix.tolil`
`scipy.sparse.csc_matrix.trace`	-
`scipy.sparse.csc_matrix.transpose`	`cupyx.scipy.sparse.csc_matrix.transpose`
`scipy.sparse.csc_matrix.trunc`	`cupyx.scipy.sparse.csc_matrix.trunc`

Sparse Matrices: Compressed Sparse Row#

SciPy	CuPy
`scipy.sparse.csr_matrix.T`	`cupyx.scipy.sparse.csr_matrix.T`
`scipy.sparse.csr_matrix.arcsin`	`cupyx.scipy.sparse.csr_matrix.arcsin`
`scipy.sparse.csr_matrix.arcsinh`	`cupyx.scipy.sparse.csr_matrix.arcsinh`
`scipy.sparse.csr_matrix.arctan`	`cupyx.scipy.sparse.csr_matrix.arctan`
`scipy.sparse.csr_matrix.arctanh`	`cupyx.scipy.sparse.csr_matrix.arctanh`
`scipy.sparse.csr_matrix.argmax`	`cupyx.scipy.sparse.csr_matrix.argmax`
`scipy.sparse.csr_matrix.argmin`	`cupyx.scipy.sparse.csr_matrix.argmin`
`scipy.sparse.csr_matrix.asformat`	`cupyx.scipy.sparse.csr_matrix.asformat`
`scipy.sparse.csr_matrix.asfptype`	`cupyx.scipy.sparse.csr_matrix.asfptype`
`scipy.sparse.csr_matrix.astype`	`cupyx.scipy.sparse.csr_matrix.astype`
`scipy.sparse.csr_matrix.ceil`	`cupyx.scipy.sparse.csr_matrix.ceil`
`scipy.sparse.csr_matrix.check_format`	-
`scipy.sparse.csr_matrix.conj`	`cupyx.scipy.sparse.csr_matrix.conj`
`scipy.sparse.csr_matrix.conjugate`	`cupyx.scipy.sparse.csr_matrix.conjugate`
`scipy.sparse.csr_matrix.copy`	`cupyx.scipy.sparse.csr_matrix.copy`
`scipy.sparse.csr_matrix.count_nonzero`	`cupyx.scipy.sparse.csr_matrix.count_nonzero`
`scipy.sparse.csr_matrix.deg2rad`	`cupyx.scipy.sparse.csr_matrix.deg2rad`
`scipy.sparse.csr_matrix.diagonal`	`cupyx.scipy.sparse.csr_matrix.diagonal`
`scipy.sparse.csr_matrix.dot`	`cupyx.scipy.sparse.csr_matrix.dot`
`scipy.sparse.csr_matrix.dtype`	`cupyx.scipy.sparse.csr_matrix.dtype`
`scipy.sparse.csr_matrix.eliminate_zeros`	`cupyx.scipy.sparse.csr_matrix.eliminate_zeros`
`scipy.sparse.csr_matrix.expm1`	`cupyx.scipy.sparse.csr_matrix.expm1`
`scipy.sparse.csr_matrix.floor`	`cupyx.scipy.sparse.csr_matrix.floor`
`scipy.sparse.csr_matrix.format`	-
`scipy.sparse.csr_matrix.getH`	`cupyx.scipy.sparse.csr_matrix.getH`
`scipy.sparse.csr_matrix.get_shape`	`cupyx.scipy.sparse.csr_matrix.get_shape`
`scipy.sparse.csr_matrix.getcol`	`cupyx.scipy.sparse.csr_matrix.getcol`
`scipy.sparse.csr_matrix.getformat`	`cupyx.scipy.sparse.csr_matrix.getformat`
`scipy.sparse.csr_matrix.getmaxprint`	`cupyx.scipy.sparse.csr_matrix.getmaxprint`
`scipy.sparse.csr_matrix.getnnz`	`cupyx.scipy.sparse.csr_matrix.getnnz`
`scipy.sparse.csr_matrix.getrow`	`cupyx.scipy.sparse.csr_matrix.getrow`
`scipy.sparse.csr_matrix.has_canonical_format`	`cupyx.scipy.sparse.csr_matrix.has_canonical_format`
`scipy.sparse.csr_matrix.has_sorted_indices`	`cupyx.scipy.sparse.csr_matrix.has_sorted_indices`
`scipy.sparse.csr_matrix.imag`	-
`scipy.sparse.csr_matrix.log1p`	`cupyx.scipy.sparse.csr_matrix.log1p`
`scipy.sparse.csr_matrix.max`	`cupyx.scipy.sparse.csr_matrix.max`
`scipy.sparse.csr_matrix.maximum`	`cupyx.scipy.sparse.csr_matrix.maximum`
`scipy.sparse.csr_matrix.mean`	`cupyx.scipy.sparse.csr_matrix.mean`
`scipy.sparse.csr_matrix.min`	`cupyx.scipy.sparse.csr_matrix.min`
`scipy.sparse.csr_matrix.minimum`	`cupyx.scipy.sparse.csr_matrix.minimum`
`scipy.sparse.csr_matrix.multiply`	`cupyx.scipy.sparse.csr_matrix.multiply`
`scipy.sparse.csr_matrix.nanmax`	-
`scipy.sparse.csr_matrix.nanmin`	-
`scipy.sparse.csr_matrix.ndim`	`cupyx.scipy.sparse.csr_matrix.ndim`
`scipy.sparse.csr_matrix.nnz`	`cupyx.scipy.sparse.csr_matrix.nnz`
`scipy.sparse.csr_matrix.nonzero`	-
`scipy.sparse.csr_matrix.power`	`cupyx.scipy.sparse.csr_matrix.power`
`scipy.sparse.csr_matrix.prune`	-
`scipy.sparse.csr_matrix.rad2deg`	`cupyx.scipy.sparse.csr_matrix.rad2deg`
`scipy.sparse.csr_matrix.real`	-
`scipy.sparse.csr_matrix.reshape`	`cupyx.scipy.sparse.csr_matrix.reshape`
`scipy.sparse.csr_matrix.resize`	-
`scipy.sparse.csr_matrix.rint`	`cupyx.scipy.sparse.csr_matrix.rint`
`scipy.sparse.csr_matrix.set_shape`	`cupyx.scipy.sparse.csr_matrix.set_shape`
`scipy.sparse.csr_matrix.setdiag`	`cupyx.scipy.sparse.csr_matrix.setdiag`
`scipy.sparse.csr_matrix.shape`	`cupyx.scipy.sparse.csr_matrix.shape`
`scipy.sparse.csr_matrix.sign`	`cupyx.scipy.sparse.csr_matrix.sign`
`scipy.sparse.csr_matrix.sin`	`cupyx.scipy.sparse.csr_matrix.sin`
`scipy.sparse.csr_matrix.sinh`	`cupyx.scipy.sparse.csr_matrix.sinh`
`scipy.sparse.csr_matrix.size`	`cupyx.scipy.sparse.csr_matrix.size`
`scipy.sparse.csr_matrix.sort_indices`	`cupyx.scipy.sparse.csr_matrix.sort_indices`
`scipy.sparse.csr_matrix.sorted_indices`	`cupyx.scipy.sparse.csr_matrix.sorted_indices`
`scipy.sparse.csr_matrix.sqrt`	`cupyx.scipy.sparse.csr_matrix.sqrt`
`scipy.sparse.csr_matrix.sum`	`cupyx.scipy.sparse.csr_matrix.sum`
`scipy.sparse.csr_matrix.sum_duplicates`	`cupyx.scipy.sparse.csr_matrix.sum_duplicates`
`scipy.sparse.csr_matrix.tan`	`cupyx.scipy.sparse.csr_matrix.tan`
`scipy.sparse.csr_matrix.tanh`	`cupyx.scipy.sparse.csr_matrix.tanh`
`scipy.sparse.csr_matrix.toarray`	`cupyx.scipy.sparse.csr_matrix.toarray`
`scipy.sparse.csr_matrix.tobsr`	`cupyx.scipy.sparse.csr_matrix.tobsr`
`scipy.sparse.csr_matrix.tocoo`	`cupyx.scipy.sparse.csr_matrix.tocoo`
`scipy.sparse.csr_matrix.tocsc`	`cupyx.scipy.sparse.csr_matrix.tocsc`
`scipy.sparse.csr_matrix.tocsr`	`cupyx.scipy.sparse.csr_matrix.tocsr`
`scipy.sparse.csr_matrix.todense`	`cupyx.scipy.sparse.csr_matrix.todense`
`scipy.sparse.csr_matrix.todia`	`cupyx.scipy.sparse.csr_matrix.todia`
`scipy.sparse.csr_matrix.todok`	`cupyx.scipy.sparse.csr_matrix.todok`
`scipy.sparse.csr_matrix.tolil`	`cupyx.scipy.sparse.csr_matrix.tolil`
`scipy.sparse.csr_matrix.trace`	-
`scipy.sparse.csr_matrix.transpose`	`cupyx.scipy.sparse.csr_matrix.transpose`
`scipy.sparse.csr_matrix.trunc`	`cupyx.scipy.sparse.csr_matrix.trunc`

Sparse Matrices: DIAgonal Storage#

SciPy	CuPy
`scipy.sparse.dia_matrix.T`	`cupyx.scipy.sparse.dia_matrix.T`
`scipy.sparse.dia_matrix.arcsin`	`cupyx.scipy.sparse.dia_matrix.arcsin`
`scipy.sparse.dia_matrix.arcsinh`	`cupyx.scipy.sparse.dia_matrix.arcsinh`
`scipy.sparse.dia_matrix.arctan`	`cupyx.scipy.sparse.dia_matrix.arctan`
`scipy.sparse.dia_matrix.arctanh`	`cupyx.scipy.sparse.dia_matrix.arctanh`
`scipy.sparse.dia_matrix.asformat`	`cupyx.scipy.sparse.dia_matrix.asformat`
`scipy.sparse.dia_matrix.asfptype`	`cupyx.scipy.sparse.dia_matrix.asfptype`
`scipy.sparse.dia_matrix.astype`	`cupyx.scipy.sparse.dia_matrix.astype`
`scipy.sparse.dia_matrix.ceil`	`cupyx.scipy.sparse.dia_matrix.ceil`
`scipy.sparse.dia_matrix.conj`	`cupyx.scipy.sparse.dia_matrix.conj`
`scipy.sparse.dia_matrix.conjugate`	`cupyx.scipy.sparse.dia_matrix.conjugate`
`scipy.sparse.dia_matrix.copy`	`cupyx.scipy.sparse.dia_matrix.copy`
`scipy.sparse.dia_matrix.count_nonzero`	`cupyx.scipy.sparse.dia_matrix.count_nonzero`
`scipy.sparse.dia_matrix.deg2rad`	`cupyx.scipy.sparse.dia_matrix.deg2rad`
`scipy.sparse.dia_matrix.diagonal`	`cupyx.scipy.sparse.dia_matrix.diagonal`
`scipy.sparse.dia_matrix.dot`	`cupyx.scipy.sparse.dia_matrix.dot`
`scipy.sparse.dia_matrix.dtype`	`cupyx.scipy.sparse.dia_matrix.dtype`
`scipy.sparse.dia_matrix.expm1`	`cupyx.scipy.sparse.dia_matrix.expm1`
`scipy.sparse.dia_matrix.floor`	`cupyx.scipy.sparse.dia_matrix.floor`
`scipy.sparse.dia_matrix.format`	-
`scipy.sparse.dia_matrix.getH`	`cupyx.scipy.sparse.dia_matrix.getH`
`scipy.sparse.dia_matrix.get_shape`	`cupyx.scipy.sparse.dia_matrix.get_shape`
`scipy.sparse.dia_matrix.getcol`	-
`scipy.sparse.dia_matrix.getformat`	`cupyx.scipy.sparse.dia_matrix.getformat`
`scipy.sparse.dia_matrix.getmaxprint`	`cupyx.scipy.sparse.dia_matrix.getmaxprint`
`scipy.sparse.dia_matrix.getnnz`	`cupyx.scipy.sparse.dia_matrix.getnnz`
`scipy.sparse.dia_matrix.getrow`	-
`scipy.sparse.dia_matrix.imag`	-
`scipy.sparse.dia_matrix.log1p`	`cupyx.scipy.sparse.dia_matrix.log1p`
`scipy.sparse.dia_matrix.maximum`	`cupyx.scipy.sparse.dia_matrix.maximum`
`scipy.sparse.dia_matrix.mean`	`cupyx.scipy.sparse.dia_matrix.mean`
`scipy.sparse.dia_matrix.minimum`	`cupyx.scipy.sparse.dia_matrix.minimum`
`scipy.sparse.dia_matrix.multiply`	`cupyx.scipy.sparse.dia_matrix.multiply`
`scipy.sparse.dia_matrix.ndim`	`cupyx.scipy.sparse.dia_matrix.ndim`
`scipy.sparse.dia_matrix.nnz`	`cupyx.scipy.sparse.dia_matrix.nnz`
`scipy.sparse.dia_matrix.nonzero`	-
`scipy.sparse.dia_matrix.power`	`cupyx.scipy.sparse.dia_matrix.power`
`scipy.sparse.dia_matrix.rad2deg`	`cupyx.scipy.sparse.dia_matrix.rad2deg`
`scipy.sparse.dia_matrix.real`	-
`scipy.sparse.dia_matrix.reshape`	`cupyx.scipy.sparse.dia_matrix.reshape`
`scipy.sparse.dia_matrix.resize`	-
`scipy.sparse.dia_matrix.rint`	`cupyx.scipy.sparse.dia_matrix.rint`
`scipy.sparse.dia_matrix.set_shape`	`cupyx.scipy.sparse.dia_matrix.set_shape`
`scipy.sparse.dia_matrix.setdiag`	`cupyx.scipy.sparse.dia_matrix.setdiag`
`scipy.sparse.dia_matrix.shape`	`cupyx.scipy.sparse.dia_matrix.shape`
`scipy.sparse.dia_matrix.sign`	`cupyx.scipy.sparse.dia_matrix.sign`
`scipy.sparse.dia_matrix.sin`	`cupyx.scipy.sparse.dia_matrix.sin`
`scipy.sparse.dia_matrix.sinh`	`cupyx.scipy.sparse.dia_matrix.sinh`
`scipy.sparse.dia_matrix.size`	`cupyx.scipy.sparse.dia_matrix.size`
`scipy.sparse.dia_matrix.sqrt`	`cupyx.scipy.sparse.dia_matrix.sqrt`
`scipy.sparse.dia_matrix.sum`	`cupyx.scipy.sparse.dia_matrix.sum`
`scipy.sparse.dia_matrix.tan`	`cupyx.scipy.sparse.dia_matrix.tan`
`scipy.sparse.dia_matrix.tanh`	`cupyx.scipy.sparse.dia_matrix.tanh`
`scipy.sparse.dia_matrix.toarray`	`cupyx.scipy.sparse.dia_matrix.toarray`
`scipy.sparse.dia_matrix.tobsr`	`cupyx.scipy.sparse.dia_matrix.tobsr`
`scipy.sparse.dia_matrix.tocoo`	`cupyx.scipy.sparse.dia_matrix.tocoo`
`scipy.sparse.dia_matrix.tocsc`	`cupyx.scipy.sparse.dia_matrix.tocsc`
`scipy.sparse.dia_matrix.tocsr`	`cupyx.scipy.sparse.dia_matrix.tocsr`
`scipy.sparse.dia_matrix.todense`	`cupyx.scipy.sparse.dia_matrix.todense`
`scipy.sparse.dia_matrix.todia`	`cupyx.scipy.sparse.dia_matrix.todia`
`scipy.sparse.dia_matrix.todok`	`cupyx.scipy.sparse.dia_matrix.todok`
`scipy.sparse.dia_matrix.tolil`	`cupyx.scipy.sparse.dia_matrix.tolil`
`scipy.sparse.dia_matrix.trace`	-
`scipy.sparse.dia_matrix.transpose`	`cupyx.scipy.sparse.dia_matrix.transpose`
`scipy.sparse.dia_matrix.trunc`	`cupyx.scipy.sparse.dia_matrix.trunc`

Sparse Linear Algebra#

SciPy	CuPy
`scipy.sparse.linalg.LaplacianNd`	-
`scipy.sparse.linalg.LinearOperator`	`cupyx.scipy.sparse.linalg.LinearOperator`
`scipy.sparse.linalg.SuperLU`	`cupyx.scipy.sparse.linalg.SuperLU`
`scipy.sparse.linalg.aslinearoperator`	`cupyx.scipy.sparse.linalg.aslinearoperator`
`scipy.sparse.linalg.bicg`	-
`scipy.sparse.linalg.bicgstab`	-
`scipy.sparse.linalg.cg`	`cupyx.scipy.sparse.linalg.cg`
`scipy.sparse.linalg.cgs`	`cupyx.scipy.sparse.linalg.cgs`
`scipy.sparse.linalg.eigs`	-
`scipy.sparse.linalg.eigsh`	`cupyx.scipy.sparse.linalg.eigsh`
`scipy.sparse.linalg.expm`	-
`scipy.sparse.linalg.expm_multiply`	-
`scipy.sparse.linalg.factorized`	`cupyx.scipy.sparse.linalg.factorized`
`scipy.sparse.linalg.gcrotmk`	-
`scipy.sparse.linalg.gmres`	`cupyx.scipy.sparse.linalg.gmres`
`scipy.sparse.linalg.inv`	-
`scipy.sparse.linalg.lgmres`	-
`scipy.sparse.linalg.lobpcg`	`cupyx.scipy.sparse.linalg.lobpcg`
`scipy.sparse.linalg.lsmr`	`cupyx.scipy.sparse.linalg.lsmr`
`scipy.sparse.linalg.lsqr`	`cupyx.scipy.sparse.linalg.lsqr`
`scipy.sparse.linalg.matrix_power`	-
`scipy.sparse.linalg.minres`	`cupyx.scipy.sparse.linalg.minres`
`scipy.sparse.linalg.norm`	`cupyx.scipy.sparse.linalg.norm`
`scipy.sparse.linalg.onenormest`	-
`scipy.sparse.linalg.qmr`	-
`scipy.sparse.linalg.spilu`	`cupyx.scipy.sparse.linalg.spilu`
`scipy.sparse.linalg.splu`	`cupyx.scipy.sparse.linalg.splu`
`scipy.sparse.linalg.spsolve`	`cupyx.scipy.sparse.linalg.spsolve`
`scipy.sparse.linalg.spsolve_triangular`	`cupyx.scipy.sparse.linalg.spsolve_triangular`
`scipy.sparse.linalg.svds`	`cupyx.scipy.sparse.linalg.svds`
`scipy.sparse.linalg.tfqmr`	-
`scipy.sparse.linalg.use_solver`	-

Compressed sparse graph routines#

SciPy	CuPy
`scipy.sparse.csgraph.bellman_ford`	-
`scipy.sparse.csgraph.breadth_first_order`	-
`scipy.sparse.csgraph.breadth_first_tree`	-
`scipy.sparse.csgraph.connected_components`	`cupyx.scipy.sparse.csgraph.connected_components`
`scipy.sparse.csgraph.construct_dist_matrix`	-
`scipy.sparse.csgraph.csgraph_from_dense`	-
`scipy.sparse.csgraph.csgraph_from_masked`	-
`scipy.sparse.csgraph.csgraph_masked_from_dense`	-
`scipy.sparse.csgraph.csgraph_to_dense`	-
`scipy.sparse.csgraph.csgraph_to_masked`	-
`scipy.sparse.csgraph.depth_first_order`	-
`scipy.sparse.csgraph.depth_first_tree`	-
`scipy.sparse.csgraph.dijkstra`	-
`scipy.sparse.csgraph.floyd_warshall`	-
`scipy.sparse.csgraph.johnson`	-
`scipy.sparse.csgraph.laplacian`	-
`scipy.sparse.csgraph.maximum_bipartite_matching`	-
`scipy.sparse.csgraph.maximum_flow`	-
`scipy.sparse.csgraph.min_weight_full_bipartite_matching`	-
`scipy.sparse.csgraph.minimum_spanning_tree`	-
`scipy.sparse.csgraph.reconstruct_path`	-
`scipy.sparse.csgraph.reverse_cuthill_mckee`	-
`scipy.sparse.csgraph.shortest_path`	-
`scipy.sparse.csgraph.structural_rank`	-
`scipy.sparse.csgraph.yen`	-

Special Functions#

SciPy	CuPy
`scipy.special.agm`	-
`scipy.special.ai_zeros`	-
`scipy.special.airy`	-
`scipy.special.airye`	-
`scipy.special.assoc_laguerre`	-
`scipy.special.bdtr`	`cupyx.scipy.special.bdtr`
`scipy.special.bdtrc`	`cupyx.scipy.special.bdtrc`
`scipy.special.bdtri`	`cupyx.scipy.special.bdtri`
`scipy.special.bdtrik`	-
`scipy.special.bdtrin`	-
`scipy.special.bei`	-
`scipy.special.bei_zeros`	-
`scipy.special.beip`	-
`scipy.special.beip_zeros`	-
`scipy.special.ber`	-
`scipy.special.ber_zeros`	-
`scipy.special.bernoulli`	-
`scipy.special.berp`	-
`scipy.special.berp_zeros`	-
`scipy.special.besselpoly`	-
`scipy.special.beta`	`cupyx.scipy.special.beta`
`scipy.special.betainc`	`cupyx.scipy.special.betainc`
`scipy.special.betaincc`	-
`scipy.special.betainccinv`	-
`scipy.special.betaincinv`	`cupyx.scipy.special.betaincinv`
`scipy.special.betaln`	`cupyx.scipy.special.betaln`
`scipy.special.bi_zeros`	-
`scipy.special.binom`	`cupyx.scipy.special.binom`
`scipy.special.boxcox`	`cupyx.scipy.special.boxcox`
`scipy.special.boxcox1p`	`cupyx.scipy.special.boxcox1p`
`scipy.special.btdtr`	`cupyx.scipy.special.btdtr`
`scipy.special.btdtri`	`cupyx.scipy.special.btdtri`
`scipy.special.btdtria`	-
`scipy.special.btdtrib`	-
`scipy.special.c_roots`	-
`scipy.special.cbrt`	`cupyx.scipy.special.cbrt`
`scipy.special.cg_roots`	-
`scipy.special.chdtr`	`cupyx.scipy.special.chdtr`
`scipy.special.chdtrc`	`cupyx.scipy.special.chdtrc`
`scipy.special.chdtri`	`cupyx.scipy.special.chdtri`
`scipy.special.chdtriv`	-
`scipy.special.chebyc`	-
`scipy.special.chebys`	-
`scipy.special.chebyt`	-