Miscellaneous

This page documents the miscellaneous members of the blosc2 module that do not fit into other categories.

blosc2.DEFAULT_COMPLEX

Default complex floating dtype.

Attributes:

T

Scalar attribute identical to the corresponding array attribute.

base

Scalar attribute identical to the corresponding array attribute.

data

Pointer to start of data.

device

dtype

Get array data-descriptor.

flags

The integer value of flags.

flat

A 1-D view of the scalar.

imag

The imaginary part of the scalar.

itemset

itemsize

The length of one element in bytes.

nbytes

ndim

The number of array dimensions.

newbyteorder

ptp

real

The real part of the scalar.

shape

Tuple of array dimensions.

size

The number of elements in the gentype.

strides

Tuple of bytes steps in each dimension.

Methods

all(ndarr[, axis, keepdims])	Test whether all array elements along a given axis evaluate to True.
any(ndarr[, axis, keepdims])	Test whether any array element along a given axis evaluates to True.
argmax(ndarr[, axis, keepdims])	Returns the indices of the maximum values along a specified axis.
argmin(ndarr[, axis, keepdims])	Returns the indices of the minimum values along a specified axis.
astype(array, dtype[, casting, copy])	Copy of the array, cast to a specified type.
clip(x[, min, max])	Clamps each element x_i of the input array x to the range [min, max].
compress(src[, typesize, clevel, filter, codec])	Compress the given source data with specified parameters.
copy(array[, dtype])	This is equivalent to NDArray.copy()
diagonal(x[, offset])	Returns the specified diagonals of a matrix (or a stack of matrices) x.
max(ndarr[, axis, keepdims])	Return the maximum along a given axis.
mean(ndarr[, axis, dtype, keepdims])	Return the arithmetic mean along the specified axis.
min(ndarr[, axis, keepdims])	Return the minimum along a given axis.
prod(ndarr[, axis, dtype, keepdims])	Return the product of array elements over a given axis.
reshape(src, shape[, c_order])	Returns an array containing the same data with a new shape.
round(x)	Rounds each element x_i of the input array x to the nearest integer-valued number.
sort(array[, order])	Return a sorted array following the specified order.
squeeze(x, axis)	Remove single-dimensional entries from the shape of the array.
std(ndarr[, axis, dtype, ddof, keepdims])	Return the standard deviation along the specified axis.
sum(ndarr[, axis, dtype, keepdims])	Return the sum of array elements over a given axis.
take(x, indices[, axis])	Returns elements of an array along an axis.
trace	program/module to trace Python program or function execution
transpose(x, **kwargs)	Returns a Blosc2 blosc2.NDArray with axes transposed.
var(ndarr[, axis, dtype, ddof, keepdims])	Return the variance along the specified axis.

conj
to_device
tobytes

blosc2.DEFAULT_FLOAT

Default real floating dtype.

Attributes:

T

Scalar attribute identical to the corresponding array attribute.

base

Scalar attribute identical to the corresponding array attribute.

data

Pointer to start of data.

device

dtype

Get array data-descriptor.

flags

The integer value of flags.

flat

A 1-D view of the scalar.

imag

The imaginary part of the scalar.

itemset

itemsize

The length of one element in bytes.

nbytes

ndim

The number of array dimensions.

newbyteorder

ptp

real

The real part of the scalar.

shape

Tuple of array dimensions.

size

The number of elements in the gentype.

strides

Tuple of bytes steps in each dimension.

Methods

all(ndarr[, axis, keepdims])	Test whether all array elements along a given axis evaluate to True.
any(ndarr[, axis, keepdims])	Test whether any array element along a given axis evaluates to True.
argmax(ndarr[, axis, keepdims])	Returns the indices of the maximum values along a specified axis.
argmin(ndarr[, axis, keepdims])	Returns the indices of the minimum values along a specified axis.
astype(array, dtype[, casting, copy])	Copy of the array, cast to a specified type.
clip(x[, min, max])	Clamps each element x_i of the input array x to the range [min, max].
compress(src[, typesize, clevel, filter, codec])	Compress the given source data with specified parameters.
copy(array[, dtype])	This is equivalent to NDArray.copy()
diagonal(x[, offset])	Returns the specified diagonals of a matrix (or a stack of matrices) x.
max(ndarr[, axis, keepdims])	Return the maximum along a given axis.
mean(ndarr[, axis, dtype, keepdims])	Return the arithmetic mean along the specified axis.
min(ndarr[, axis, keepdims])	Return the minimum along a given axis.
prod(ndarr[, axis, dtype, keepdims])	Return the product of array elements over a given axis.
reshape(src, shape[, c_order])	Returns an array containing the same data with a new shape.
round(x)	Rounds each element x_i of the input array x to the nearest integer-valued number.
sort(array[, order])	Return a sorted array following the specified order.
squeeze(x, axis)	Remove single-dimensional entries from the shape of the array.
std(ndarr[, axis, dtype, ddof, keepdims])	Return the standard deviation along the specified axis.
sum(ndarr[, axis, dtype, keepdims])	Return the sum of array elements over a given axis.
take(x, indices[, axis])	Returns elements of an array along an axis.
trace	program/module to trace Python program or function execution
transpose(x, **kwargs)	Returns a Blosc2 blosc2.NDArray with axes transposed.
var(ndarr[, axis, dtype, ddof, keepdims])	Return the variance along the specified axis.

conj
to_device
tobytes

blosc2.DEFAULT_INDEX

Default indexing dtype.

Attributes:

T

Scalar attribute identical to the corresponding array attribute.

base

Scalar attribute identical to the corresponding array attribute.

data

Pointer to start of data.

denominator

denominator of value (1)

device

dtype

Get array data-descriptor.

flags

The integer value of flags.

flat

A 1-D view of the scalar.

imag

The imaginary part of the scalar.

itemset

itemsize

The length of one element in bytes.

nbytes

ndim

The number of array dimensions.

newbyteorder

numerator

numerator of value (the value itself)

ptp

real

The real part of the scalar.

shape

Tuple of array dimensions.

size

The number of elements in the gentype.

strides

Tuple of bytes steps in each dimension.

Methods

all(ndarr[, axis, keepdims])	Test whether all array elements along a given axis evaluate to True.
any(ndarr[, axis, keepdims])	Test whether any array element along a given axis evaluates to True.
argmax(ndarr[, axis, keepdims])	Returns the indices of the maximum values along a specified axis.
argmin(ndarr[, axis, keepdims])	Returns the indices of the minimum values along a specified axis.
astype(array, dtype[, casting, copy])	Copy of the array, cast to a specified type.
clip(x[, min, max])	Clamps each element x_i of the input array x to the range [min, max].
compress(src[, typesize, clevel, filter, codec])	Compress the given source data with specified parameters.
copy(array[, dtype])	This is equivalent to NDArray.copy()
diagonal(x[, offset])	Returns the specified diagonals of a matrix (or a stack of matrices) x.
max(ndarr[, axis, keepdims])	Return the maximum along a given axis.
mean(ndarr[, axis, dtype, keepdims])	Return the arithmetic mean along the specified axis.
min(ndarr[, axis, keepdims])	Return the minimum along a given axis.
prod(ndarr[, axis, dtype, keepdims])	Return the product of array elements over a given axis.
reshape(src, shape[, c_order])	Returns an array containing the same data with a new shape.
round(x)	Rounds each element x_i of the input array x to the nearest integer-valued number.
sort(array[, order])	Return a sorted array following the specified order.
squeeze(x, axis)	Remove single-dimensional entries from the shape of the array.
std(ndarr[, axis, dtype, ddof, keepdims])	Return the standard deviation along the specified axis.
sum(ndarr[, axis, dtype, keepdims])	Return the sum of array elements over a given axis.
take(x, indices[, axis])	Returns elements of an array along an axis.
trace	program/module to trace Python program or function execution
transpose(x, **kwargs)	Returns a Blosc2 blosc2.NDArray with axes transposed.
var(ndarr[, axis, dtype, ddof, keepdims])	Return the variance along the specified axis.

conj
to_device
tobytes

blosc2.DEFAULT_INT

Default integer dtype.

Attributes:

T

Scalar attribute identical to the corresponding array attribute.

base

Scalar attribute identical to the corresponding array attribute.

data

Pointer to start of data.

denominator

denominator of value (1)

device

dtype

Get array data-descriptor.

flags

The integer value of flags.

flat

A 1-D view of the scalar.

imag

The imaginary part of the scalar.

itemset

itemsize

The length of one element in bytes.

nbytes

ndim

The number of array dimensions.

newbyteorder

numerator

numerator of value (the value itself)

ptp

real

The real part of the scalar.

shape

Tuple of array dimensions.

size

The number of elements in the gentype.

strides

Tuple of bytes steps in each dimension.

Methods

all(ndarr[, axis, keepdims])	Test whether all array elements along a given axis evaluate to True.
any(ndarr[, axis, keepdims])	Test whether any array element along a given axis evaluates to True.
argmax(ndarr[, axis, keepdims])	Returns the indices of the maximum values along a specified axis.
argmin(ndarr[, axis, keepdims])	Returns the indices of the minimum values along a specified axis.
astype(array, dtype[, casting, copy])	Copy of the array, cast to a specified type.
clip(x[, min, max])	Clamps each element x_i of the input array x to the range [min, max].
compress(src[, typesize, clevel, filter, codec])	Compress the given source data with specified parameters.
copy(array[, dtype])	This is equivalent to NDArray.copy()
diagonal(x[, offset])	Returns the specified diagonals of a matrix (or a stack of matrices) x.
max(ndarr[, axis, keepdims])	Return the maximum along a given axis.
mean(ndarr[, axis, dtype, keepdims])	Return the arithmetic mean along the specified axis.
min(ndarr[, axis, keepdims])	Return the minimum along a given axis.
prod(ndarr[, axis, dtype, keepdims])	Return the product of array elements over a given axis.
reshape(src, shape[, c_order])	Returns an array containing the same data with a new shape.
round(x)	Rounds each element x_i of the input array x to the nearest integer-valued number.
sort(array[, order])	Return a sorted array following the specified order.
squeeze(x, axis)	Remove single-dimensional entries from the shape of the array.
std(ndarr[, axis, dtype, ddof, keepdims])	Return the standard deviation along the specified axis.
sum(ndarr[, axis, dtype, keepdims])	Return the sum of array elements over a given axis.
take(x, indices[, axis])	Returns elements of an array along an axis.
trace	program/module to trace Python program or function execution
transpose(x, **kwargs)	Returns a Blosc2 blosc2.NDArray with axes transposed.
var(ndarr[, axis, dtype, ddof, keepdims])	Return the variance along the specified axis.

conj
to_device
tobytes

class blosc2.LazyUDF(func, inputs, dtype, shape=None, chunked_eval=True, **kwargs)

Attributes:

blocks

Return LazyArray blocks.

chunks

Return LazyArray chunks.

device

Hardware device the array data resides on.

dtype

Get the data type of the Operand.

info

Get information about the Operand.

info_items

ndim

Get the number of dimensions of the Operand.

shape

Get the shape of the Operand.

Methods

all([axis, keepdims])	Test whether all array elements along a given axis evaluate to True.
any([axis, keepdims])	Test whether any array element along a given axis evaluates to True.
argmax([axis, keepdims])	Returns the indices of the maximum values along a specified axis.
argmin([axis, keepdims])	Returns the indices of the minimum values along a specified axis.
compute([item, fp_accuracy])	Return a NDArray containing the evaluation of the LazyArray.
get_chunk(nchunk)	Get the nchunk of the expression, evaluating only that one.
indices([order])	Return an LazyArray containing the indices where self is True.
item()	Copy an element of an array to a standard Python scalar and return it.
max([axis, keepdims])	Return the maximum along a given axis.
mean([axis, dtype, keepdims])	Return the arithmetic mean along the specified axis.
min([axis, keepdims])	Return the minimum along a given axis.
prod([axis, dtype, keepdims])	Return the product of array elements over a given axis.
save([urlpath])	Save the LazyArray on disk.
sort([order])	Return a sorted LazyArray.
std([axis, dtype, ddof, keepdims])	Return the standard deviation along the specified axis.
sum([axis, dtype, keepdims])	Return the sum of array elements over a given axis.
to_cframe()	Compute LazyArray and convert to cframe.
to_device(device)	Copy the array from the device on which it currently resides to the specified device.
var([axis, dtype, ddof, keepdims])	Return the variance along the specified axis.
where([value1, value2])	Select value1 or value2 values based on True/False for self.

property blocks

Return LazyArray blocks.

property chunks

Return LazyArray chunks.

compute(item=(), fp_accuracy: FPAccuracy = FPAccuracy.MEDIUM, **kwargs)

Return a NDArray containing the evaluation of the LazyArray.

Parameters:

• item (slice, list of slices, optional) – If provided, item is used to slice the operands prior to computation; not to retrieve specified slices of the evaluated result. This difference between slicing operands and slicing the final expression is important when reductions or a where clause are used in the expression.

• fp_accuracy (blosc2.FPAccuracy, optional) – Specifies the floating-point accuracy to be used during computation. By default, blosc2.FPAccuracy.DEFAULT is used.

• kwargs (Any, optional) – Keyword arguments that are supported by the empty() constructor. These arguments will be set in the resulting NDArray. Additionally, the following special kwargs are supported:

Returns:

out – A NDArray containing the result of evaluating the LazyUDF or LazyExpr.

Return type:

NDArray

Notes

• If self is a LazyArray from an udf, the kwargs used to store the resulting array will be the ones passed to the constructor in lazyudf() (except the urlpath) updated with the kwargs passed when calling this method.

Examples

>>> import blosc2
>>> import numpy as np
>>> dtype = np.float64
>>> shape = [3, 3]
>>> size = shape[0] * shape[1]
>>> a = np.linspace(0, 5, num=size, dtype=dtype).reshape(shape)
>>> b = np.linspace(0, 5, num=size, dtype=dtype).reshape(shape)
>>> #  Convert numpy arrays to Blosc2 arrays
>>> a1 = blosc2.asarray(a)
>>> b1 = blosc2.asarray(b)
>>> # Perform the mathematical operation
>>> expr = a1 + b1
>>> output = expr.compute()
>>> f"Result of a + b (lazy evaluation): {output[:]}"
Result of a + b (lazy evaluation):
            [[ 0.    1.25  2.5 ]
            [ 3.75  5.    6.25]
            [ 7.5   8.75 10.  ]]

property dtype

Get the data type of the Operand.

Returns:

out – The data type of the Operand.

Return type:

np.dtype

property info

Get information about the Operand.

Returns:

out – A printable class with information about the Operand.

Return type:

InfoReporter

property ndim: int

Get the number of dimensions of the Operand.

Returns:

out – The number of dimensions of the Operand.

Return type:

int

property shape

Get the shape of the Operand.

Returns:

out – The shape of the Operand.

Return type:

tuple

class blosc2.Operand

Base class for all operands in expressions.

Attributes:

device

Hardware device the array data resides on.

dtype

Get the data type of the Operand.

info

Get information about the Operand.

ndim

Get the number of dimensions of the Operand.

shape

Get the shape of the Operand.

Methods

all([axis, keepdims])	Test whether all array elements along a given axis evaluate to True.
any([axis, keepdims])	Test whether any array element along a given axis evaluates to True.
argmax([axis, keepdims])	Returns the indices of the maximum values along a specified axis.
argmin([axis, keepdims])	Returns the indices of the minimum values along a specified axis.
item()	Copy an element of an array to a standard Python scalar and return it.
max([axis, keepdims])	Return the maximum along a given axis.
mean([axis, dtype, keepdims])	Return the arithmetic mean along the specified axis.
min([axis, keepdims])	Return the minimum along a given axis.
prod([axis, dtype, keepdims])	Return the product of array elements over a given axis.
std([axis, dtype, ddof, keepdims])	Return the standard deviation along the specified axis.
sum([axis, dtype, keepdims])	Return the sum of array elements over a given axis.
to_device(device)	Copy the array from the device on which it currently resides to the specified device.
var([axis, dtype, ddof, keepdims])	Return the variance along the specified axis.
where([value1, value2])	Select value1 or value2 values based on True/False for self.

property device

Hardware device the array data resides on. Always equal to ‘cpu’.

abstract property dtype: dtype

Get the data type of the Operand.

Returns:

out – The data type of the Operand.

Return type:

np.dtype

abstract property info: InfoReporter

Get information about the Operand.

Returns:

out – A printable class with information about the Operand.

Return type:

InfoReporter

item() → float | bool | complex | int

Copy an element of an array to a standard Python scalar and return it.

abstract property ndim: int

Get the number of dimensions of the Operand.

Returns:

out – The number of dimensions of the Operand.

Return type:

int

abstract property shape: tuple[int]

Get the shape of the Operand.

Returns:

out – The shape of the Operand.

Return type:

tuple

to_device(device: str)

Copy the array from the device on which it currently resides to the specified device.

Parameters:

• self (NDArray) – Array instance.

• device (str) – Device to move array object to. Returns error except when device==’cpu’.

Returns:

out – If device=’cpu’, the same array; else raises an Error.

Return type:

NDArray

class blosc2.ProxyNDField(proxy: Proxy, field: str)

Attributes:

device

Hardware device the array data resides on.

dtype

Get the data type of the ProxyNDField.

info

Get information about the Operand.

ndim

Get the number of dimensions of the Operand.

shape

Get the shape of the ProxyNDField.

Methods

all([axis, keepdims])	Test whether all array elements along a given axis evaluate to True.
any([axis, keepdims])	Test whether any array element along a given axis evaluates to True.
argmax([axis, keepdims])	Returns the indices of the maximum values along a specified axis.
argmin([axis, keepdims])	Returns the indices of the minimum values along a specified axis.
item()	Copy an element of an array to a standard Python scalar and return it.
max([axis, keepdims])	Return the maximum along a given axis.
mean([axis, dtype, keepdims])	Return the arithmetic mean along the specified axis.
min([axis, keepdims])	Return the minimum along a given axis.
prod([axis, dtype, keepdims])	Return the product of array elements over a given axis.
std([axis, dtype, ddof, keepdims])	Return the standard deviation along the specified axis.
sum([axis, dtype, keepdims])	Return the sum of array elements over a given axis.
to_device(device)	Copy the array from the device on which it currently resides to the specified device.
var([axis, dtype, ddof, keepdims])	Return the variance along the specified axis.
where([value1, value2])	Select value1 or value2 values based on True/False for self.

property dtype: dtype

Get the data type of the ProxyNDField.

Returns:

out – The data type of the ProxyNDField.

Return type:

np.dtype

property shape: tuple[int]

Get the shape of the ProxyNDField.

Returns:

out – The shape of the ProxyNDField.

Return type:

tuple

blosc2.array_from_ffi_ptr(array_ptr) → NDArray

Create an NDArray from a raw FFI pointer.

This function is useful for passing arrays across FFI boundaries. This function move the ownership of the underlying b2nd_array_t* object to the new NDArray, and it will be freed when the object is destroyed.

blosc2.as_simpleproxy(*arrs: Sequence[Array]) → tuple[SimpleProxy | Operand]

Convert an Array object which fulfills Array protocol into SimpleProxy. If x is already a blosc2.Operand simply returns object.

Parameters:

arrs (Sequence[blosc2.Array]) – Objects fulfilling Array protocol.

Returns:

out – Objects with minimal interface for blosc2 LazyExpr computations.

Return type:

tuple[blosc2.SimpleProxy | blosc2.Operand]

class blosc2.finfo(dtype)

Machine limits for floating point types.

bits

The number of bits occupied by the type.

Type:

int

dtype

Returns the dtype for which finfo returns information. For complex input, the returned dtype is the associated float* dtype for its real and complex components.

Type:

dtype

eps

The difference between 1.0 and the next smallest representable float larger than 1.0. For example, for 64-bit binary floats in the IEEE-754 standard, eps = 2**-52, approximately 2.22e-16.

Type:

float

epsneg

The difference between 1.0 and the next smallest representable float less than 1.0. For example, for 64-bit binary floats in the IEEE-754 standard, epsneg = 2**-53, approximately 1.11e-16.

Type:

float

iexp

The number of bits in the exponent portion of the floating point representation.

Type:

int

machep

The exponent that yields eps.

Type:

int

max

The largest representable number.

Type:

floating point number of the appropriate type

maxexp

The smallest positive power of the base (2) that causes overflow.

Type:

int

min

The smallest representable number, typically -max.

Type:

floating point number of the appropriate type

minexp

The most negative power of the base (2) consistent with there being no leading 0’s in the mantissa.

Type:

int

negep

The exponent that yields epsneg.

Type:

int

nexp

The number of bits in the exponent including its sign and bias.

Type:

int

nmant

The number of bits in the mantissa.

Type:

int

precision

The approximate number of decimal digits to which this kind of float is precise.

Type:

int

resolution

The approximate decimal resolution of this type, i.e., 10**-precision.

Type:

floating point number of the appropriate type

tiny

An alias for smallest_normal, kept for backwards compatibility.

Type:

float

smallest_normal

The smallest positive floating point number with 1 as leading bit in the mantissa following IEEE-754 (see Notes).

Type:

float

smallest_subnormal

The smallest positive floating point number with 0 as leading bit in the mantissa following IEEE-754.

Type:

float

Parameters:

dtype (float, dtype, or instance) – Kind of floating point or complex floating point data-type about which to get information.

See also

iinfo

The equivalent for integer data types.

spacing

The distance between a value and the nearest adjacent number

nextafter

The next floating point value after x1 towards x2

Notes

For developers of NumPy: do not instantiate this at the module level. The initial calculation of these parameters is expensive and negatively impacts import times. These objects are cached, so calling finfo() repeatedly inside your functions is not a problem.

Note that smallest_normal is not actually the smallest positive representable value in a NumPy floating point type. As in the IEEE-754 standard [1], NumPy floating point types make use of subnormal numbers to fill the gap between 0 and smallest_normal. However, subnormal numbers may have significantly reduced precision [2].

This function can also be used for complex data types as well. If used, the output will be the same as the corresponding real float type (e.g. numpy.finfo(numpy.csingle) is the same as numpy.finfo(numpy.single)). However, the output is true for the real and imaginary components.

References

[1]

IEEE Standard for Floating-Point Arithmetic, IEEE Std 754-2008, pp.1-70, 2008, https://doi.org/10.1109/IEEESTD.2008.4610935

[2]

Wikipedia, “Denormal Numbers”, https://en.wikipedia.org/wiki/Denormal_number

Examples

>>> import numpy as np
>>> np.finfo(np.float64).dtype
dtype('float64')
>>> np.finfo(np.complex64).dtype
dtype('float32')

Attributes:

smallest_normal

Return the value for the smallest normal.

tiny

Return the value for tiny, alias of smallest_normal.

property smallest_normal

Return the value for the smallest normal.

Returns:

smallest_normal – Value for the smallest normal.

Return type:

float

Warns:

UserWarning – If the calculated value for the smallest normal is requested for double-double.

property tiny

Return the value for tiny, alias of smallest_normal.

Returns:

tiny – Value for the smallest normal, alias of smallest_normal.

Return type:

float

Warns:

UserWarning – If the calculated value for the smallest normal is requested for double-double.

blosc2.get_cpu_info()

Construct the result of cpuinfo.get_cpu_info(), without actually using cpuinfo.get_cpu_info() since that function takes 1s to run and this method is ran at import time.

class blosc2.iinfo(type)

Machine limits for integer types.

bits

The number of bits occupied by the type.

Type:

int

dtype

Returns the dtype for which iinfo returns information.

Type:

dtype

min

The smallest integer expressible by the type.

Type:

int

max

The largest integer expressible by the type.

Type:

int

Parameters:

int_type (integer type, dtype, or instance) – The kind of integer data type to get information about.

See also

finfo

The equivalent for floating point data types.

Examples

With types:

>>> import numpy as np
>>> ii16 = np.iinfo(np.int16)
>>> ii16.min
-32768
>>> ii16.max
32767
>>> ii32 = np.iinfo(np.int32)
>>> ii32.min
-2147483648
>>> ii32.max
2147483647

With instances:

>>> ii32 = np.iinfo(np.int32(10))
>>> ii32.min
-2147483648
>>> ii32.max
2147483647

Attributes:

max

Maximum value of given dtype.

min

Minimum value of given dtype.