API

Top level functions

abs(x, /[, out, where, casting, order, ...])

This docstring was copied from numpy.absolute.

absolute(x, /[, out, where, casting, order, ...])

This docstring was copied from numpy.absolute.

add(x1, x2, /[, out, where, casting, order, ...])

This docstring was copied from numpy.add.

all(a[, axis, keepdims, split_every, out])

Test whether all array elements along a given axis evaluate to True.

allclose(arr1, arr2[, rtol, atol, equal_nan])

Returns True if two arrays are element-wise equal within a tolerance.

angle(x[, deg])

Return the angle of the complex argument.

any(a[, axis, keepdims, split_every, out])

Test whether any array element along a given axis evaluates to True.

append(arr, values[, axis])

Append values to the end of an array.

apply_along_axis(func1d, axis, arr, *args[, ...])

Apply a function to 1-D slices along the given axis.

apply_over_axes(func, a, axes)

Apply a function repeatedly over multiple axes.

arange(*args[, chunks, like, dtype])

Return evenly spaced values from start to stop with step size step.

arccos(x, /[, out, where, casting, order, ...])

This docstring was copied from numpy.arccos.

arccosh(x, /[, out, where, casting, order, ...])

This docstring was copied from numpy.arccosh.

arcsin(x, /[, out, where, casting, order, ...])

This docstring was copied from numpy.arcsin.

arcsinh(x, /[, out, where, casting, order, ...])

This docstring was copied from numpy.arcsinh.

arctan(x, /[, out, where, casting, order, ...])

This docstring was copied from numpy.arctan.

arctan2(x1, x2, /[, out, where, casting, ...])

This docstring was copied from numpy.arctan2.

arctanh(x, /[, out, where, casting, order, ...])

This docstring was copied from numpy.arctanh.

argmax(a[, axis, keepdims, split_every, out])

Returns the indices of the maximum values along an axis.

argmin(a[, axis, keepdims, split_every, out])

Returns the indices of the minimum values along an axis.

argtopk(a, k[, axis, split_every])

Extract the indices of the k largest elements from a on the given axis, and return them sorted from largest to smallest.

argwhere(a)

Find the indices of array elements that are non-zero, grouped by element.

around(x[, decimals])

Round an array to the given number of decimals.

array(object[, dtype, copy, order, subok, ...])

This docstring was copied from numpy.array.

asanyarray(a[, dtype, order, like, inline_array])

Convert the input to a dask array.

asarray(a[, allow_unknown_chunksizes, ...])

Convert the input to a dask array.

atleast_1d(*arys)

Convert inputs to arrays with at least one dimension.

atleast_2d(*arys)

View inputs as arrays with at least two dimensions.

atleast_3d(*arys)

View inputs as arrays with at least three dimensions.

average(a[, axis, weights, returned, keepdims])

Compute the weighted average along the specified axis.

bincount(x, /[, weights, minlength])

This docstring was copied from numpy.bincount.

bitwise_and(x1, x2, /[, out, where, ...])

This docstring was copied from numpy.bitwise_and.

bitwise_not(x, /[, out, where, casting, ...])

This docstring was copied from numpy.invert.

bitwise_or(x1, x2, /[, out, where, casting, ...])

This docstring was copied from numpy.bitwise_or.

bitwise_xor(x1, x2, /[, out, where, ...])

This docstring was copied from numpy.bitwise_xor.

block(arrays[, allow_unknown_chunksizes])

Assemble an nd-array from nested lists of blocks.

blockwise(func, out_ind, *args[, name, ...])

Tensor operation: Generalized inner and outer products

broadcast_arrays(*args[, subok])

Broadcast any number of arrays against each other.

broadcast_to(x, shape[, chunks, meta])

Broadcast an array to a new shape.

cbrt(x, /[, out, where, casting, order, ...])

This docstring was copied from numpy.cbrt.

coarsen(reduction, x, axes[, trim_excess])

Coarsen array by applying reduction to fixed size neighborhoods

ceil(x, /[, out, where, casting, order, ...])

This docstring was copied from numpy.ceil.

choose(a, choices)

Construct an array from an index array and a list of arrays to choose from.

clip(*args, **kwargs)

Clip (limit) the values in an array.

compress(condition, a[, axis])

Return selected slices of an array along given axis.

concatenate(seq[, axis, ...])

Concatenate arrays along an existing axis

conj(x, /[, out, where, casting, order, ...])

This docstring was copied from numpy.conjugate.

copysign(x1, x2, /[, out, where, casting, ...])

This docstring was copied from numpy.copysign.

corrcoef(x[, y, rowvar])

Return Pearson product-moment correlation coefficients.

cos(x, /[, out, where, casting, order, ...])

This docstring was copied from numpy.cos.

cosh(x, /[, out, where, casting, order, ...])

This docstring was copied from numpy.cosh.

count_nonzero(a[, axis])

Counts the number of non-zero values in the array a.

cov(m[, y, rowvar, bias, ddof])

Estimate a covariance matrix, given data and weights.

cumprod(x[, axis, dtype, out, method])

Return the cumulative product of elements along a given axis.

cumsum(x[, axis, dtype, out, method])

Return the cumulative sum of the elements along a given axis.

deg2rad(x, /[, out, where, casting, order, ...])

This docstring was copied from numpy.deg2rad.

degrees(x, /[, out, where, casting, order, ...])

This docstring was copied from numpy.degrees.

delete(arr, obj, axis)

Return a new array with sub-arrays along an axis deleted.

diag(v[, k])

Extract a diagonal or construct a diagonal array.

diagonal(a[, offset, axis1, axis2])

Return specified diagonals.

diff(a[, n, axis, prepend, append])

Calculate the n-th discrete difference along the given axis.

divide(x1, x2, /[, out, where, casting, ...])

This docstring was copied from numpy.divide.

divmod(x1, x2[, out1, out2], / [[, out, ...])

This docstring was copied from numpy.divmod.

digitize(a, bins[, right])

Return the indices of the bins to which each value in input array belongs.

dot(a, b[, out])

This docstring was copied from numpy.dot.

dstack(tup[, allow_unknown_chunksizes])

Stack arrays in sequence depth wise (along third axis).

ediff1d(ary[, to_end, to_begin])

The differences between consecutive elements of an array.

einsum(subscripts, *operands[, out, dtype, ...])

This docstring was copied from numpy.einsum.

empty(*args, **kwargs)

Blocked variant of empty_like

empty_like(a[, dtype, order, chunks, name, ...])

Return a new array with the same shape and type as a given array.

equal(x1, x2, /[, out, where, casting, ...])

This docstring was copied from numpy.equal.

exp(x, /[, out, where, casting, order, ...])

This docstring was copied from numpy.exp.

exp2(x, /[, out, where, casting, order, ...])

This docstring was copied from numpy.exp2.

expand_dims(a, axis)

Expand the shape of an array.

expm1(x, /[, out, where, casting, order, ...])

This docstring was copied from numpy.expm1.

extract(condition, arr)

Return the elements of an array that satisfy some condition.

eye(N[, chunks, M, k, dtype])

Return a 2-D Array with ones on the diagonal and zeros elsewhere.

fabs(x, /[, out, where, casting, order, ...])

This docstring was copied from numpy.fabs.

fix(*args, **kwargs)

Round to nearest integer towards zero.

flatnonzero(a)

Return indices that are non-zero in the flattened version of a.

flip(m[, axis])

Reverse element order along axis.

flipud(m)

Reverse the order of elements along axis 0 (up/down).

fliplr(m)

Reverse the order of elements along axis 1 (left/right).

float_power(x1, x2, /[, out, where, ...])

This docstring was copied from numpy.float_power.

floor(x, /[, out, where, casting, order, ...])

This docstring was copied from numpy.floor.

floor_divide(x1, x2, /[, out, where, ...])

This docstring was copied from numpy.floor_divide.

fmax(x1, x2, /[, out, where, casting, ...])

This docstring was copied from numpy.fmax.

fmin(x1, x2, /[, out, where, casting, ...])

This docstring was copied from numpy.fmin.

fmod(x1, x2, /[, out, where, casting, ...])

This docstring was copied from numpy.fmod.

frexp(x[, out1, out2], / [[, out, where, ...])

This docstring was copied from numpy.frexp.

fromfunction(func[, chunks, shape, dtype])

Construct an array by executing a function over each coordinate.

frompyfunc(func, /, nin, nout, *[, identity])

This docstring was copied from numpy.frompyfunc.

full(shape, fill_value, *args, **kwargs)

Blocked variant of full_like

full_like(a, fill_value[, order, dtype, ...])

Return a full array with the same shape and type as a given array.

gradient(f, *varargs[, axis])

Return the gradient of an N-dimensional array.

greater(x1, x2, /[, out, where, casting, ...])

This docstring was copied from numpy.greater.

greater_equal(x1, x2, /[, out, where, ...])

This docstring was copied from numpy.greater_equal.

histogram(a[, bins, range, normed, weights, ...])

Blocked variant of numpy.histogram().

histogram2d(x, y[, bins, range, normed, ...])

Blocked variant of numpy.histogram2d().

histogramdd(sample, bins[, range, normed, ...])

Blocked variant of numpy.histogramdd().

hstack(tup[, allow_unknown_chunksizes])

Stack arrays in sequence horizontally (column wise).

hypot(x1, x2, /[, out, where, casting, ...])

This docstring was copied from numpy.hypot.

i0(*args, **kwargs)

Modified Bessel function of the first kind, order 0.

imag(*args, **kwargs)

Return the imaginary part of the complex argument.

indices(dimensions[, dtype, chunks])

Implements NumPy's indices for Dask Arrays.

insert(arr, obj, values, axis)

Insert values along the given axis before the given indices.

invert(x, /[, out, where, casting, order, ...])

This docstring was copied from numpy.invert.

isclose(arr1, arr2[, rtol, atol, equal_nan])

Returns a boolean array where two arrays are element-wise equal within a tolerance.

iscomplex(*args, **kwargs)

Returns a bool array, where True if input element is complex.

isfinite(x, /[, out, where, casting, order, ...])

This docstring was copied from numpy.isfinite.

isin(element, test_elements[, ...])

Calculates element in test_elements, broadcasting over element only.

isinf(x, /[, out, where, casting, order, ...])

This docstring was copied from numpy.isinf.

isneginf

This docstring was copied from numpy.equal.

isnan(x, /[, out, where, casting, order, ...])

This docstring was copied from numpy.isnan.

isnull(values)

pandas.isnull for dask arrays

isposinf

This docstring was copied from numpy.equal.

isreal(*args, **kwargs)

Returns a bool array, where True if input element is real.

ldexp(x1, x2, /[, out, where, casting, ...])

This docstring was copied from numpy.ldexp.

left_shift(x1, x2, /[, out, where, casting, ...])

This docstring was copied from numpy.left_shift.

less(x1, x2, /[, out, where, casting, ...])

This docstring was copied from numpy.less.

less_equal(x1, x2, /[, out, where, casting, ...])

This docstring was copied from numpy.less_equal.

linspace(start, stop[, num, endpoint, ...])

Return num evenly spaced values over the closed interval [start, stop].

log(x, /[, out, where, casting, order, ...])

This docstring was copied from numpy.log.

log10(x, /[, out, where, casting, order, ...])

This docstring was copied from numpy.log10.

log1p(x, /[, out, where, casting, order, ...])

This docstring was copied from numpy.log1p.

log2(x, /[, out, where, casting, order, ...])

This docstring was copied from numpy.log2.

logaddexp(x1, x2, /[, out, where, casting, ...])

This docstring was copied from numpy.logaddexp.

logaddexp2(x1, x2, /[, out, where, casting, ...])

This docstring was copied from numpy.logaddexp2.

logical_and(x1, x2, /[, out, where, ...])

This docstring was copied from numpy.logical_and.

logical_not(x, /[, out, where, casting, ...])

This docstring was copied from numpy.logical_not.

logical_or(x1, x2, /[, out, where, casting, ...])

This docstring was copied from numpy.logical_or.

logical_xor(x1, x2, /[, out, where, ...])

This docstring was copied from numpy.logical_xor.

map_overlap(func, *args[, depth, boundary, ...])

Map a function over blocks of arrays with some overlap

map_blocks(func, *args[, name, token, ...])

Map a function across all blocks of a dask array.

matmul(x1, x2, /[, out, casting, order, ...])

This docstring was copied from numpy.matmul.

max(a[, axis, keepdims, split_every, out])

Return the maximum of an array or maximum along an axis.

maximum(x1, x2, /[, out, where, casting, ...])

This docstring was copied from numpy.maximum.

mean(a[, axis, dtype, keepdims, ...])

Compute the arithmetic mean along the specified axis.

median(a[, axis, keepdims, out])

Compute the median along the specified axis.

meshgrid(*xi[, sparse, indexing])

Return a list of coordinate matrices from coordinate vectors.

min(a[, axis, keepdims, split_every, out])

Return the minimum of an array or minimum along an axis.

minimum(x1, x2, /[, out, where, casting, ...])

This docstring was copied from numpy.minimum.

mod(x1, x2, /[, out, where, casting, order, ...])

This docstring was copied from numpy.remainder.

modf(x[, out1, out2], / [[, out, where, ...])

This docstring was copied from numpy.modf.

moment(a, order[, axis, dtype, keepdims, ...])

Calculate the nth centralized moment.

moveaxis(a, source, destination)

Move axes of an array to new positions.

multiply(x1, x2, /[, out, where, casting, ...])

This docstring was copied from numpy.multiply.

nanargmax(a[, axis, keepdims, split_every, out])

Return the indices of the maximum values in the specified axis ignoring NaNs.

nanargmin(a[, axis, keepdims, split_every, out])

Return the indices of the minimum values in the specified axis ignoring NaNs.

nancumprod(x, axis[, dtype, out, method])

Return the cumulative product of array elements over a given axis treating Not a Numbers (NaNs) as one.

nancumsum(x, axis[, dtype, out, method])

Return the cumulative sum of array elements over a given axis treating Not a Numbers (NaNs) as zero.

nanmax(a[, axis, keepdims, split_every, out])

Return the maximum of an array or maximum along an axis, ignoring any NaNs.

nanmean(a[, axis, dtype, keepdims, ...])

Compute the arithmetic mean along the specified axis, ignoring NaNs.

nanmedian(a[, axis, keepdims, out])

Compute the median along the specified axis, while ignoring NaNs.

nanmin(a[, axis, keepdims, split_every, out])

Return minimum of an array or minimum along an axis, ignoring any NaNs.

nanprod(a[, axis, dtype, keepdims, ...])

Return the product of array elements over a given axis treating Not a Numbers (NaNs) as ones.

nanstd(a[, axis, dtype, keepdims, ddof, ...])

Compute the standard deviation along the specified axis, while ignoring NaNs.

nansum(a[, axis, dtype, keepdims, ...])

Return the sum of array elements over a given axis treating Not a Numbers (NaNs) as zero.

nanvar(a[, axis, dtype, keepdims, ddof, ...])

Compute the variance along the specified axis, while ignoring NaNs.

nan_to_num(*args, **kwargs)

Replace NaN with zero and infinity with large finite numbers (default behaviour) or with the numbers defined by the user using the nan, posinf and/or neginf keywords.

negative(x, /[, out, where, casting, order, ...])

This docstring was copied from numpy.negative.

nextafter(x1, x2, /[, out, where, casting, ...])

This docstring was copied from numpy.nextafter.

nonzero(a)

Return the indices of the elements that are non-zero.

not_equal(x1, x2, /[, out, where, casting, ...])

This docstring was copied from numpy.not_equal.

notnull(values)

pandas.notnull for dask arrays

ones(*args, **kwargs)

Blocked variant of ones_like

ones_like(a[, dtype, order, chunks, name, shape])

Return an array of ones with the same shape and type as a given array.

outer(a, b)

Compute the outer product of two vectors.

pad(array, pad_width[, mode])

Pad an array.

percentile(a, q[, method, internal_method])

Approximate percentile of 1-D array

PerformanceWarning

A warning given when bad chunking may cause poor performance

piecewise(x, condlist, funclist, *args, **kw)

Evaluate a piecewise-defined function.

positive(x, /[, out, where, casting, order, ...])

This docstring was copied from numpy.positive.

power(x1, x2, /[, out, where, casting, ...])

This docstring was copied from numpy.power.

prod(a[, axis, dtype, keepdims, ...])

Return the product of array elements over a given axis.

ptp(a[, axis])

Range of values (maximum - minimum) along an axis.

rad2deg(x, /[, out, where, casting, order, ...])

This docstring was copied from numpy.rad2deg.

radians(x, /[, out, where, casting, order, ...])

This docstring was copied from numpy.radians.

ravel(array_like)

Return a contiguous flattened array.

ravel_multi_index(multi_index, dims[, mode, ...])

Converts a tuple of index arrays into an array of flat indices, applying boundary modes to the multi-index.

real(*args, **kwargs)

Return the real part of the complex argument.

reciprocal(x, /[, out, where, casting, ...])

This docstring was copied from numpy.reciprocal.

rechunk(x[, chunks, threshold, ...])

Convert blocks in dask array x for new chunks.

reduction(x, chunk, aggregate[, axis, ...])

General version of reductions

register_chunk_type(type)

Register the given type as a valid chunk and downcast array type

remainder(x1, x2, /[, out, where, casting, ...])

This docstring was copied from numpy.remainder.

repeat(a, repeats[, axis])

Repeat each element of an array after themselves

reshape(x, shape[, merge_chunks, limit])

Reshape array to new shape

result_type(*arrays_and_dtypes)

This docstring was copied from numpy.result_type.

right_shift(x1, x2, /[, out, where, ...])

This docstring was copied from numpy.right_shift.

rint(x, /[, out, where, casting, order, ...])

This docstring was copied from numpy.rint.

roll(array, shift[, axis])

Roll array elements along a given axis.

rollaxis(a, axis[, start])

rot90(m[, k, axes])

Rotate an array by 90 degrees in the plane specified by axes.

round(a[, decimals])

Evenly round to the given number of decimals.

searchsorted(a, v[, side, sorter])

Find indices where elements should be inserted to maintain order.

select(condlist, choicelist[, default])

Return an array drawn from elements in choicelist, depending on conditions.

shape(array)

Return the shape of an array.

sign(x, /[, out, where, casting, order, ...])

This docstring was copied from numpy.sign.

signbit(x, /[, out, where, casting, order, ...])

This docstring was copied from numpy.signbit.

sin(x, /[, out, where, casting, order, ...])

This docstring was copied from numpy.sin.

sinc(*args, **kwargs)

Return the normalized sinc function.

sinh(x, /[, out, where, casting, order, ...])

This docstring was copied from numpy.sinh.

spacing(x, /[, out, where, casting, order, ...])

This docstring was copied from numpy.spacing.

sqrt(x, /[, out, where, casting, order, ...])

This docstring was copied from numpy.sqrt.

square(x, /[, out, where, casting, order, ...])

This docstring was copied from numpy.square.

squeeze(a[, axis])

Remove axes of length one from a.

stack(seq[, axis, allow_unknown_chunksizes])

Stack arrays along a new axis

std(a[, axis, dtype, keepdims, ddof, ...])

Compute the standard deviation along the specified axis.

subtract(x1, x2, /[, out, where, casting, ...])

This docstring was copied from numpy.subtract.

sum(a[, axis, dtype, keepdims, split_every, out])

Sum of array elements over a given axis.

swapaxes(a, axis1, axis2)

Interchange two axes of an array.

take(a, indices[, axis])

Take elements from an array along an axis.

tan(x, /[, out, where, casting, order, ...])

This docstring was copied from numpy.tan.

tanh(x, /[, out, where, casting, order, ...])

This docstring was copied from numpy.tanh.

tensordot(lhs, rhs[, axes])

Compute tensor dot product along specified axes.

tile(A, reps)

Construct an array by repeating A the number of times given by reps.

topk(a, k[, axis, split_every])

Extract the k largest elements from a on the given axis, and return them sorted from largest to smallest.

trace(a[, offset, axis1, axis2, dtype])

Return the sum along diagonals of the array.

transpose(a[, axes])

Returns an array with axes transposed.

tri(N[, M, k, dtype, chunks, like])

An array with ones at and below the given diagonal and zeros elsewhere.

tril(m[, k])

Lower triangle of an array.

tril_indices(n[, k, m, chunks])

Return the indices for the lower-triangle of an (n, m) array.

tril_indices_from(arr[, k])

Return the indices for the lower-triangle of arr.

triu(m[, k])

Upper triangle of an array.

triu_indices(n[, k, m, chunks])

Return the indices for the upper-triangle of an (n, m) array.

triu_indices_from(arr[, k])

Return the indices for the upper-triangle of arr.

true_divide(x1, x2, /[, out, where, ...])

This docstring was copied from numpy.divide.

trunc(x, /[, out, where, casting, order, ...])

This docstring was copied from numpy.trunc.

union1d(ar1, ar2)

Find the union of two arrays.

unique(ar[, return_index, return_inverse, ...])

Find the unique elements of an array.

unravel_index(indices, shape[, order])

This docstring was copied from numpy.unravel_index.

var(a[, axis, dtype, keepdims, ddof, ...])

Compute the variance along the specified axis.

vdot(a, b, /)

This docstring was copied from numpy.vdot.

vstack(tup[, allow_unknown_chunksizes])

Stack arrays in sequence vertically (row wise).

where(condition, [x, y], /)

This docstring was copied from numpy.where.

zeros(*args, **kwargs)

Blocked variant of zeros_like

zeros_like(a[, dtype, order, chunks, name, ...])

Return an array of zeros with the same shape and type as a given array.

Array

Array(dask, name, chunks[, dtype, meta, shape])

Parallel Dask Array

Array.all([axis, keepdims, split_every, out])

Returns True if all elements evaluate to True.

Array.any([axis, keepdims, split_every, out])

Returns True if any of the elements evaluate to True.

Array.argmax([axis, keepdims, split_every, out])

Return indices of the maximum values along the given axis.

Array.argmin([axis, keepdims, split_every, out])

Return indices of the minimum values along the given axis.

Array.argtopk(k[, axis, split_every])

The indices of the top k elements of an array.

Array.astype(dtype, **kwargs)

Copy of the array, cast to a specified type.

Array.blocks

An array-like interface to the blocks of an array.

Array.choose(choices)

Use an index array to construct a new array from a set of choices.

Array.chunks

Chunks property.

Array.chunksize

Array.clip([min, max])

Return an array whose values are limited to [min, max].

Array.compute(**kwargs)

Compute this dask collection

Array.compute_chunk_sizes()

Compute the chunk sizes for a Dask array.

Array.conj()

Complex-conjugate all elements.

Array.copy()

Copy array.

Array.cumprod(axis[, dtype, out, method])

Return the cumulative product of the elements along the given axis.

Array.cumsum(axis[, dtype, out, method])

Return the cumulative sum of the elements along the given axis.

Array.dask

Array.dot(other)

Dot product of self and other.

Array.dtype

Array.flatten()

Return a flattened array.

Array.imag

Array.itemsize

Length of one array element in bytes

Array.map_blocks(*args[, name, token, ...])

Map a function across all blocks of a dask array.

Array.map_overlap(func, depth[, boundary, trim])

Map a function over blocks of the array with some overlap

Array.max([axis, keepdims, split_every, out])

Return the maximum along a given axis.

Array.mean([axis, dtype, keepdims, ...])

Returns the average of the array elements along given axis.

Array.min([axis, keepdims, split_every, out])

Return the minimum along a given axis.

Array.moment(order[, axis, dtype, keepdims, ...])

Calculate the nth centralized moment.

Array.name

Array.nbytes

Number of bytes in array

Array.ndim

Array.nonzero()

Return the indices of the elements that are non-zero.

Array.npartitions

Array.numblocks

Array.partitions

Slice an array by partitions.

Array.persist(**kwargs)

Persist this dask collection into memory

Array.prod([axis, dtype, keepdims, ...])

Return the product of the array elements over the given axis

Array.ravel()

Return a flattened array.

Array.real

Array.rechunk([chunks, threshold, ...])

Convert blocks in dask array x for new chunks.

Array.repeat(repeats[, axis])

Repeat elements of an array.

Array.reshape(*shape[, merge_chunks, limit])

Reshape array to new shape

Array.round([decimals])

Return array with each element rounded to the given number of decimals.

Array.shape

Array.size

Number of elements in array

Array.squeeze([axis])

Remove axes of length one from array.

Array.std([axis, dtype, keepdims, ddof, ...])

Returns the standard deviation of the array elements along given axis.

Array.store(targets[, lock, regions, ...])

Store dask arrays in array-like objects, overwrite data in target

Array.sum([axis, dtype, keepdims, ...])

Return the sum of the array elements over the given axis.

Array.swapaxes(axis1, axis2)

Return a view of the array with axis1 and axis2 interchanged.

Array.to_backend([backend])

Move to a new Array backend

Array.to_dask_dataframe([columns, index, meta])

Convert dask Array to dask Dataframe

Array.to_delayed([optimize_graph])

Convert into an array of dask.delayed.Delayed objects, one per chunk.

Array.to_hdf5(filename, datapath, **kwargs)

Store array in HDF5 file

Array.to_svg([size])

Convert chunks from Dask Array into an SVG Image

Array.to_tiledb(uri, *args, **kwargs)

Save array to the TileDB storage manager

Array.to_zarr(*args, **kwargs)

Save array to the zarr storage format

Array.topk(k[, axis, split_every])

The top k elements of an array.

Array.trace([offset, axis1, axis2, dtype])

Return the sum along diagonals of the array.

Array.transpose(*axes)

Reverse or permute the axes of an array.

Array.var([axis, dtype, keepdims, ddof, ...])

Returns the variance of the array elements, along given axis.

Array.view([dtype, order])

Get a view of the array as a new data type

Array.vindex

Vectorized indexing with broadcasting.

Array.visualize([filename, format, ...])

Render the computation of this object's task graph using graphviz.

Fast Fourier Transforms

fft.fft_wrap(fft_func[, kind, dtype])

Wrap 1D, 2D, and ND real and complex FFT functions

fft.fft(a[, n, axis])

Wrapping of numpy.fft.fft

fft.fft2(a[, s, axes])

Wrapping of numpy.fft.fft2

fft.fftn(a[, s, axes])

Wrapping of numpy.fft.fftn

fft.ifft(a[, n, axis])

Wrapping of numpy.fft.ifft

fft.ifft2(a[, s, axes])

Wrapping of numpy.fft.ifft2

fft.ifftn(a[, s, axes])

Wrapping of numpy.fft.ifftn

fft.rfft(a[, n, axis])

Wrapping of numpy.fft.rfft

fft.rfft2(a[, s, axes])

Wrapping of numpy.fft.rfft2

fft.rfftn(a[, s, axes])

Wrapping of numpy.fft.rfftn

fft.irfft(a[, n, axis])

Wrapping of numpy.fft.irfft

fft.irfft2(a[, s, axes])

Wrapping of numpy.fft.irfft2

fft.irfftn(a[, s, axes])

Wrapping of numpy.fft.irfftn

fft.hfft(a[, n, axis])

Wrapping of numpy.fft.hfft

fft.ihfft(a[, n, axis])

Wrapping of numpy.fft.ihfft

fft.fftfreq(n[, d, chunks])

Return the Discrete Fourier Transform sample frequencies.

fft.rfftfreq(n[, d, chunks])

Return the Discrete Fourier Transform sample frequencies (for usage with rfft, irfft).

fft.fftshift(x[, axes])

Shift the zero-frequency component to the center of the spectrum.

fft.ifftshift(x[, axes])

The inverse of fftshift.

Linear Algebra

linalg.cholesky(a[, lower])

Returns the Cholesky decomposition, \(A = L L^*\) or \(A = U^* U\) of a Hermitian positive-definite matrix A.

linalg.inv(a)

Compute the inverse of a matrix with LU decomposition and forward / backward substitutions.

linalg.lstsq(a, b)

Return the least-squares solution to a linear matrix equation using QR decomposition.

linalg.lu(a)

Compute the lu decomposition of a matrix.

linalg.norm(x[, ord, axis, keepdims])

Matrix or vector norm.

linalg.qr(a)

Compute the qr factorization of a matrix.

linalg.solve(a, b[, sym_pos, assume_a])

Solve the equation a x = b for x.

linalg.solve_triangular(a, b[, lower])

Solve the equation a x = b for x, assuming a is a triangular matrix.

linalg.svd(a[, coerce_signs])

Compute the singular value decomposition of a matrix.

linalg.svd_compressed(a, k[, iterator, ...])

Randomly compressed rank-k thin Singular Value Decomposition.

linalg.sfqr(data[, name])

Direct Short-and-Fat QR

linalg.tsqr(data[, compute_svd, ...])

Direct Tall-and-Skinny QR algorithm

Masked Arrays

ma.average(a[, axis, weights, returned, ...])

Return the weighted average of array over the given axis.

ma.empty_like(prototype[, dtype, order, ...])

This docstring was copied from numpy.ma.core.empty_like.

ma.filled(a[, fill_value])

Return input as an array with masked data replaced by a fill value.

ma.fix_invalid(a[, fill_value])

Return input with invalid data masked and replaced by a fill value.

ma.getdata(a)

Return the data of a masked array as an ndarray.

ma.getmaskarray(a)

Return the mask of a masked array, or full boolean array of False.

ma.masked_array(data[, mask, fill_value])

An array class with possibly masked values.

ma.masked_equal(a, value)

Mask an array where equal to a given value.

ma.masked_greater(x, value[, copy])

Mask an array where greater than a given value.

ma.masked_greater_equal(x, value[, copy])

Mask an array where greater than or equal to a given value.

ma.masked_inside(x, v1, v2)

Mask an array inside a given interval.

ma.masked_invalid(a)

Mask an array where invalid values occur (NaNs or infs).

ma.masked_less(x, value[, copy])

Mask an array where less than a given value.

ma.masked_less_equal(x, value[, copy])

Mask an array where less than or equal to a given value.

ma.masked_not_equal(x, value[, copy])

Mask an array where not equal to a given value.

ma.masked_outside(x, v1, v2)

Mask an array outside a given interval.

ma.masked_values(x, value[, rtol, atol, shrink])

Mask using floating point equality.

ma.masked_where(condition, a)

Mask an array where a condition is met.

ma.nonzero(self)

This docstring was copied from numpy.ma.core.nonzero.

ma.ones_like(a, **kwargs)

Return an array of ones with the same shape and type as a given array.

ma.set_fill_value(a, fill_value)

Set the filling value of a, if a is a masked array.

ma.where(condition[, x, y])

Return a masked array with elements from x or y, depending on condition.

ma.zeros_like(a, **kwargs)

Return an array of zeros with the same shape and type as a given array.

Random

random.beta(*args, **kwargs)

Draw samples from a Beta distribution.

random.binomial(*args, **kwargs)

Draw samples from a binomial distribution.

random.chisquare(*args, **kwargs)

Draw samples from a chi-square distribution.

random.choice(*args, **kwargs)

Generates a random sample from a given 1-D array

random.default_rng([seed])

Construct a new Generator with the default BitGenerator (PCG64).

random.exponential(*args, **kwargs)

Draw samples from an exponential distribution.

random.f(*args, **kwargs)

Draw samples from an F distribution.

random.gamma(*args, **kwargs)

Draw samples from a Gamma distribution.

random.geometric(*args, **kwargs)

Draw samples from the geometric distribution.

random.gumbel(*args, **kwargs)

Draw samples from a Gumbel distribution.

random.hypergeometric(*args, **kwargs)

Draw samples from a Hypergeometric distribution.

random.laplace(*args, **kwargs)

Draw samples from the Laplace or double exponential distribution with specified location (or mean) and scale (decay).

random.logistic(*args, **kwargs)

Draw samples from a logistic distribution.

random.lognormal(*args, **kwargs)

Draw samples from a log-normal distribution.

random.logseries(*args, **kwargs)

Draw samples from a logarithmic series distribution.

random.multinomial(*args, **kwargs)

Draw samples from a multinomial distribution.

random.negative_binomial(*args, **kwargs)

Draw samples from a negative binomial distribution.

random.noncentral_chisquare(*args, **kwargs)

Draw samples from a noncentral chi-square distribution.

random.noncentral_f(*args, **kwargs)

Draw samples from the noncentral F distribution.

random.normal(*args, **kwargs)

Draw random samples from a normal (Gaussian) distribution.

random.pareto(*args, **kwargs)

Draw samples from a Pareto II or Lomax distribution with specified shape.

random.permutation(*args, **kwargs)

Randomly permute a sequence, or return a permuted range.

random.poisson(*args, **kwargs)

Draw samples from a Poisson distribution.

random.power(*args, **kwargs)

Draws samples in [0, 1] from a power distribution with positive exponent a - 1.

random.randint(*args, **kwargs)

Return random integers from low (inclusive) to high (exclusive).

random.random(*args, **kwargs)

Return random floats in the half-open interval [0.0, 1.0).

random.random_integers(*args, **kwargs)

Random integers of type np.int_ between low and high, inclusive.

random.random_sample(*args, **kwargs)

Return random floats in the half-open interval [0.0, 1.0).

random.rayleigh(*args, **kwargs)

Draw samples from a Rayleigh distribution.

random.standard_cauchy(*args, **kwargs)

Draw samples from a standard Cauchy distribution with mode = 0.

random.standard_exponential(*args, **kwargs)

Draw samples from the standard exponential distribution.

random.standard_gamma(*args, **kwargs)

Draw samples from a standard Gamma distribution.

random.standard_normal(*args, **kwargs)

Draw samples from a standard Normal distribution (mean=0, stdev=1).

random.standard_t(*args, **kwargs)

Draw samples from a standard Student's t distribution with df degrees of freedom.

random.triangular(*args, **kwargs)

Draw samples from the triangular distribution over the interval [left, right].

random.uniform(*args, **kwargs)

Draw samples from a uniform distribution.

random.vonmises(*args, **kwargs)

Draw samples from a von Mises distribution.

random.wald(*args, **kwargs)

Draw samples from a Wald, or inverse Gaussian, distribution.

random.weibull(*args, **kwargs)

Draw samples from a Weibull distribution.

random.zipf(*args, **kwargs)

Draw samples from a Zipf distribution.

Stats

stats.ttest_ind(a, b[, axis, equal_var])

This docstring was copied from scipy.stats.ttest_ind.

stats.ttest_1samp(a, popmean[, axis, nan_policy])

This docstring was copied from scipy.stats.ttest_1samp.

stats.ttest_rel(a, b[, axis, nan_policy])

This docstring was copied from scipy.stats.ttest_rel.

stats.chisquare(f_obs[, f_exp, ddof, axis])

Calculate a one-way chi-square test.

stats.power_divergence(f_obs[, f_exp, ddof, ...])

Cressie-Read power divergence statistic and goodness of fit test.

stats.skew(a[, axis, bias, nan_policy])

This docstring was copied from scipy.stats.skew.

stats.skewtest(a[, axis, nan_policy])

Test whether the skew is different from the normal distribution.

stats.kurtosis(a[, axis, fisher, bias, ...])

This docstring was copied from scipy.stats.kurtosis.

stats.kurtosistest(a[, axis, nan_policy])

Test whether a dataset has normal kurtosis.

stats.normaltest(a[, axis, nan_policy])

Test whether a sample differs from a normal distribution.

stats.f_oneway(*args)

Perform one-way ANOVA.

stats.moment(a[, moment, axis, nan_policy])

This docstring was copied from scipy.stats.moment.

Image Support

image.imread(filename[, imread, preprocess])

Read a stack of images into a dask array

Slightly Overlapping Computations

overlap.overlap(x, depth, boundary, *[, ...])

Share boundaries between neighboring blocks

overlap.map_overlap(func, *args[, depth, ...])

Map a function over blocks of arrays with some overlap

lib.stride_tricks.sliding_window_view(x, ...)

Create a sliding window view into the array with the given window shape.

overlap.trim_internal(x, axes[, boundary])

Trim sides from each block

overlap.trim_overlap(x, depth[, boundary])

Trim sides from each block.

Create and Store Arrays

from_array(x[, chunks, name, lock, asarray, ...])

Create dask array from something that looks like an array.

from_delayed(value, shape[, dtype, meta, name])

Create a dask array from a dask delayed value

from_npy_stack(dirname[, mmap_mode])

Load dask array from stack of npy files

from_zarr(url[, component, storage_options, ...])

Load array from the zarr storage format

from_tiledb(uri[, attribute, chunks, ...])

Load array from the TileDB storage format

store(sources, targets[, lock, regions, ...])

Store dask arrays in array-like objects, overwrite data in target

to_hdf5(filename, *args[, chunks])

Store arrays in HDF5 file

to_zarr(arr, url[, component, ...])

Save array to the zarr storage format

to_npy_stack(dirname, x[, axis])

Write dask array to a stack of .npy files

to_tiledb(darray, uri[, compute, ...])

Save array to the TileDB storage format

Generalized Ufuncs

apply_gufunc(func, signature, *args[, axes, ...])

Apply a generalized ufunc or similar python function to arrays.

as_gufunc([signature])

Decorator for dask.array.gufunc.

gufunc(pyfunc, *[, signature, vectorize, ...])

Binds pyfunc into dask.array.apply_gufunc when called.

Internal functions

blockwise(func, out_ind, *args[, name, ...])

Tensor operation: Generalized inner and outer products

normalize_chunks(chunks[, shape, limit, ...])

Normalize chunks to tuple of tuples

unify_chunks(*args, **kwargs)

Unify chunks across a sequence of arrays

Dask Metadata

meta_from_array(x[, ndim, dtype])

Normalize an array to appropriate meta object