utils.fixed_point module

This is module implementing fixed point numbers for python. For a motivation, description and some examples, we refer to the docstring of the FixedPoint class.

class utils.fixed_point.FixedPoint(value, precision)

Bases: object

Outline:

1. Motivation

2. Description

3. Examples

1. Motivation

Encryption schemes generally work with (scaled) fixed-point numbers (or integers), while such numbers are represented by floating points in python. This causes a discrepancy between the number that is encrypted and the respective decryption. This results in difficulties, e.g., when you want a random additive plaintext mask. This module addresses that discrepancy and provides arbitrary-precision fixed-point numbers including simple arithmetic such as addition, subtraction, multiplication and comparison operators.

2. Description

A fixed-point number is defined by 2 integers:

• value: an arbitrary-precision integer

• precision: an integer indicating the position of the radix which separates the integer part from the fractional part (counting from the right)

Fixed-point numbers can be instantiated from strings, integers, floats and other fixed-points. using the class method FixedPoint.fxp.

3. Examples:

• fxp(“10.001234”) -> value = 10001234 precision = 6 (this represents 10.001234)

• fxp(“1234e-2”) -> value = 1234 precision = 2 (this represents 12.34)

• fxp(42) -> value = 42 precision = 0 (this represents 42)

• fxp(-123, 2) -> value = -12300 precision = 2 (this represents -123.00)

• fxp(123.) -> value = 123 precision = 0 (This represents 123)

• fxp(-1.23) -> value = -123 precision = 2 (this represents -1.23)

• fxp(-0.123, 5) -> value = -12300 precision = 5 (this represents -0.12300)

• fxp(1234e-2) -> value = 1234 precision = 2 (this represents 12.34)

DEFAULT_FLOAT_PRECISION = 16

__abs__()

Function that returns a fixed point number that represents the absolute value of the fixed point number.

Return type:

FixedPoint

Returns:

absolute value of the fixed point number

__add__(other)

Add another fixed point number (or type convertible to a fixed point number) to self.

Parameters:

other (object) – a fixed pont number, integer, string or float

Return type:

FixedPoint

Returns:

The addition of self to other

Raises:

NotImplementedError – If the other object does not have a compatible type.

__bool__()

Function that casts a fixed point object to a boolean.

Return type:

bool

Returns:

A bool representing whether the fixed point object is unequal to zero.

__eq__(other)

Function that determines whether the fixed point object is equal to another object. The other object does not have to be a fixed point object. Additionally, this is a ‘weak’ equality in the sense that we first cast the other object to a fixed point number if it is not already and then check for equality. The precision value does not need to be equal, as long as the calibrated fixed point objects are equal. For strong equality, use strong_eq.

For example:

• fxp(“100.0”) == fxp(“100.0000”) -> True

• fxp(“12.34”) == 12.34 -> True

• fxp(“0.012”) == fxp(“0.01”) -> False

Parameters:

other (object) – Fixed point object, integer, string or float

Return type:

bool

Returns:

whether self and the other object are (weakly) equal

Raises:

NotImplementedError – If the other object does not have a compatible type.

__float__()

Function that cases a fixed point object to a float. If the fixed point number is too large, the float might return an error.

Return type:

float

Returns:

A floating point number representing the fixed point object

__ge__(other)

Function that returns whether this fixed pont number is greater than or equal to another compatible data type instance.

Parameters:

other (object) – fixed point number, integer, string or float

Return type:

bool

Returns:

whether self is greater than or equal to the fixed point version of other

Raises:

NotImplementedError – If the other object does not have a compatible type.

__gt__(other)

Function that returns whether this fixed pont number is greater than another compatible data type instance.

Parameters:

other (object) – fixed point number, integer, string or float

Return type:

bool

Returns:

whether self is greater than the fixed point version of other

Raises:

NotImplementedError – If the other object does not have a compatible type.

__init__(value, precision)

Initialise the fixed point number.

Parameters:

• value (int) – The arbitrary-precision integer value representing the fixed point number

• precision (int) – The location of the radix, counting from the right

__int__()

Function that casts a fixed point object to an integer. The function uses rounding instead of downward truncation.

Return type:

int

Returns:

An integer representing the rounded fixed point object

__le__(other)

Function that returns whether this fixed pont number is less than or equal to another compatible data type instance.

Parameters:

other (object) – fixed point number, integer, string or float

Return type:

bool

Returns:

whether self is less than or equal to the fixed point version of other

Raises:

NotImplementedError – If the other object does not have a compatible type.

__lshift__(other)

Left bit shift operation without moving the radix. Shifts the underlying integer value, but does not modify the radix position

Parameters:

other (int) – number of bits to shift

Return type:

FixedPoint

Returns:

shifted fixed point

__lt__(other)

Function that returns whether this fixed pont number is less than another compatible data type instance.

Parameters:

other (object) – fixed point number, integer, string or float

Return type:

bool

Returns:

whether self is less than the fixed point version of other

Raises:

NotImplementedError – If the other object does not have a compatible type.

__mul__(other)

Multiply another fixed point number (or type convertible to a fixed point number) with self. Note that the result is calculated first with arbitrary precision and then rounded to obtain the maximum precision of the two inputs.

For example:

• fxp(“0.1”) * fxp(“0.5”) = fxp(“0.1”)

• fxp(“0.1”) * fxp(“0.4”) = fxp(“0.0”)

Parameters:

other (object) – a fixed point number or other type convertible to a fixed point number.

Return type:

FixedPoint

Returns:

a * b

Raises:

NotImplementedError – If the other object does not have a compatible type.

__neg__()

Function that returns a fixed point number that represents the negation of the fixed point number.

Return type:

FixedPoint

Returns:

negation of the fixed point number

__radd__(other)

Add another fixed point number (or type convertible to a fixed point number) to self.

Parameters:

other (object) – a fixed pont number, integer, string or float

Return type:

FixedPoint

Returns:

The addition of self to other

Raises:

NotImplementedError – If the other object does not have a compatible type.

__repr__()

Function that determines the representation of a fixed point object

Return type:

str

Returns:

string containing a representation of the fixed point object

__rmul__(other)

Multiply another fixed point number (or type convertible to a fixed point number) with self. Note that the result is calculated first with arbitrary precision and then rounded to obtain the maximum precision of the two inputs.

For example:

• fxp(“0.1”) * fxp(“0.5”) = fxp(“0.1”)

• fxp(“0.1”) * fxp(“0.4”) = fxp(“0.0”)

Parameters:

other (object) – a fixed point number or other type convertible to a fixed point number.

Return type:

FixedPoint

Returns:

a * b

Raises:

NotImplementedError – If the other object does not have a compatible type.

__rshift__(other)

Right bit shift operation without moving the radix. Shifts the underlying integer value, but does not modify the radix position.

Parameters:

other (int) – number of bits to shift

Return type:

FixedPoint

Returns:

shifted fixed point

__rsub__(other)

Subtract self from an object of a type convertible to a fixed point number

Parameters:

other (object) – a fixed point number, integer, string or float

Return type:

FixedPoint

Returns:

the result of subtracting self from the other value

Raises:

NotImplementedError – If the other object does not have a compatible type.

__rtruediv__(other)

Divide self with another fixed point number (or type convertible to a fixed point number). Note that the result is calculated first with arbitrary precision and then rounded to obtain the maximum precision of the two inputs.

For example:

• fxp(“0.2”) / fxp(“3.0”) = fxp(“0.7”)

• fxp(“0.1”) / fxp(“2.1”) = fxp(“0.0”)

Parameters:

other (object) – a fixed point number or other type convertible to a fixed point number.

Return type:

FixedPoint

Returns:

a / b

Raises:

NotImplementedError – If the other object does not have a compatible type.

__str__()

Function that casts a fixed point object to a string. First a representation without a radix is found and then the radix is inserted in the right place if the fixed point is not integer.

Return type:

str

Returns:

A string representing the fixed point object

__sub__(other)

Subtract another fixed point number (or type convertible to a fixed point number) from self.

Parameters:

other (object) – a fixed point number, integer, string or float

Return type:

FixedPoint

Returns:

the result of subtracting the other value from self

Raises:

NotImplementedError – If the other object does not have a compatible type.

__truediv__(other)

Divide self with another fixed point number (or type convertible to a fixed point number). Note that the result is calculated first with arbitrary precision and then rounded to obtain the maximum precision of the two inputs.

For example:

• fxp(“0.2”) / fxp(“3.0”) = fxp(“0.7”)

• fxp(“0.1”) / fxp(“2.1”) = fxp(“0.0”)

Parameters:

other (object) – a fixed point number or other type convertible to a fixed point number.

Return type:

FixedPoint

Returns:

a / b

Raises:

NotImplementedError – If the other object does not have a compatible type.

static calibrate(*fixed_points)

Function that determines that maximum precision among all the fixed points and scales the fixed points according to the maximum precision.

Parameters:

*fixed_points (FixedPoint) – fixed point numbers

Return type:

tuple[int, tuple[FixedPoint, ...]]

Returns:

A tuple where the first entry is the maximum precision and the subsequent entries are the given fixed points scaled to this maximum precision.

static deserialize(obj, **_kwargs)

Deserialization function for FixedPoint.

Parameters:

• obj (dict[str, Any]) – Object to deserialize.

• **_kwargs (Any) – Optional extra keyword arguments.

Return type:

FixedPoint

Returns:

Deserialized FixedPoint instance.

classmethod fxp(input_value, target_precision=None)

Create a fixed-point number from a string, int, float or fixed-point number with a specified precision. If no precision is provided, it is deduced from the input_value. If precision is provided but it contradicts the precision of the input_value value (too large or too small), the input_value value is either truncated or trailing zeroes are added.

Legitimate input values:

• str: a string containing numbers in the range [0-9].

  This can be point-separated to represent an integer part (before the full stop) and a fractional part (after the full stop).

• int: an arbitrarily large integer.

  By default,it will be converted to a fixed-point with a precision of 0, but if a precision is provided, then the fixed point represents the input_value value times 10**-precision.

• float: a floating-point number.

  The default precision is 16 bits. The floating point is scaled and the value is extracted according to the floating point number and the precision.

• FixedPoint: another fixed-point number.

  If no precision is provided, all values are copied. If a precision is provided, the fixed-point number is either truncated or trailing zeroes are added to attain the new precision.

Parameters:

• input_value (Union[FixedPoint, Integral, str, float]) – the number to be converted to a fixed-point.

• target_precision (int | None) – The desired precision of the resulting fixed-point number.

Return type:

FixedPoint

Returns:

A fixed point version of the provided input

Raises:

TypeError – Raised if the input value is not an integer, float, fixed point or string

static initiate_from_float(input_value, target_precision=None)

if the input value is a float, we multiply it by a power of 10 to create a scaled floating point number and then extract an integer to represent the fixed point number. If no precision is provided, the precision is extracted from the string representation.

Parameters:

• input_value (float) – the input_value integer

• target_precision (int | None) – desired precision

Return type:

FixedPoint

Returns:

the resulting fixed-point number

static initiate_from_fxp(input_value, target_precision=None)

If the input value is another fixed point, correct the value with respect to the target precision.

Parameters:

• input_value (FixedPoint) – the input_value fixed-point number

• target_precision (int | None) – desired precision

Return type:

FixedPoint

Returns:

the resulting fixed-point number

static initiate_from_int(input_value, precision=None)

If the input_value is an integer, we set the integer value to the input_value and decimal to zero.

Parameters:

• input_value (Integral) – the input_value integer

• precision (int | None) – position of the radix, counting from the right

Return type:

FixedPoint

Returns:

the resulting fixed-point number

static initiate_from_string(input_value, precision=None)

This is the most reliable way to instantiate a fixed point, as the string accurately represents how the fixed point will be represented. The input is parsed as <integer>.<fractional> or <integer> or <integer>e<integer>. the precision is extracted automatically. If a target precision is provided then zeroes are added if the target precision is higher and the number is rounded towards the right precision if the target precision is lower.

Parameters:

• input_value (str) – string of decimals, possibly separated by a full stop

• precision (int | None) – desired precision. This has precedence over the implicit string precision.

Return type:

FixedPoint

Returns:

the resulting fixed-point number

Raises:

ValueError – Raised if the provided string does not fit the parsing format.

precision: int

static random_range(lower_bound, upper_bound, signed=False)

Return a uniformly random fixed-point in the interval [lower_bound, upper_bound). If signed is True, the interval becomes [lower_bound, upper_bound) $cup$ (-upper_bound, lower_bound].

Parameters:

• lower_bound (FixedPoint) – integer lower bound (inclusive)

• upper_bound (FixedPoint) – integer upper bound (exclusive)

• signed (bool) – whether the random fixed-point number should have a random sign or just be positive

Return type:

FixedPoint

Returns:

a uniformly random fixed-point in the specified interval

static round_to_precision(value, current_precision, target_precision)

Function that takes a fixed point representation (value, precision) and changes the value to obtain the right precision for the fixed point representation. It uses rounding when the target precision is lower than the current precision.

Parameters:

• value (int) – An integer representing the value

• current_precision (int) – An integer representing the precision of the given value

• target_precision (int) – The desired precision

Return type:

int

Returns:

A new value that represents a (rounded) fixed point number with the target precision

Raises:

TypeError – If value, current_precision or target_precision is not an int

serialize(**_kwargs)

Serialization function for FixedPoint.

Parameters:

**_kwargs (Any) – Optional extra keyword arguments.

Return type:

dict[str, Any]

Returns:

Serialized representation of the current object.

static strong_eq(fxp_1, fxp_2)

Function that determines whether two fixed points are exactly equal

Parameters:

• fxp_1 (FixedPoint) – Fixed point number

• fxp_2 (FixedPoint) – Fixed point number

Return type:

bool

Returns:

Whether the values and precision of the fixed point objects are equal

value: int