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  2. Double-precision floating-point format - Wikipedia

    en.wikipedia.org/wiki/Double-precision_floating...

    Double-precision floating-point format (sometimes called FP64 or float64) is a floating-point number format, usually occupying 64 bits in computer memory; it represents a wide range of numeric values by using a floating radix point. Double precision may be chosen when the range or precision of single precision would be insufficient.

  3. Type signature - Wikipedia

    en.wikipedia.org/wiki/Type_signature

    commission (sale:: Int, rate:: Float64):: Float64 The types in the arguments are used for the multiple dispatch . The return type is validated when the function returns a value, and a runtime exception is raised if the type of the value does not agree with the specified type.

  4. decimal64 floating-point format - Wikipedia

    en.wikipedia.org/wiki/Decimal64_floating-point...

    Decimal64 supports 'normal' values that can have 16 digit precision from ±1.000 000 000 000 000 × 10 ^ −383 to ±9.999 999 999 999 999 × 10 ^ 384, plus 'denormal' values with ramp-down relative precision down to ±1.×10 −398, signed zeros, signed infinities and NaN (Not a Number). This format supports two different encodings.

  5. NumPy - Wikipedia

    en.wikipedia.org/wiki/NumPy

    NumPy (pronounced / ˈ n ʌ m p aɪ / NUM-py) is a library for the Python programming language, adding support for large, multi-dimensional arrays and matrices, along with a large collection of high-level mathematical functions to operate on these arrays. [3]

  6. Single-precision floating-point format - Wikipedia

    en.wikipedia.org/wiki/Single-precision_floating...

    Single-precision floating-point format (sometimes called FP32 or float32) is a computer number format, usually occupying 32 bits in computer memory; it represents a wide dynamic range of numeric values by using a floating radix point.

  7. Half-precision floating-point format - Wikipedia

    en.wikipedia.org/wiki/Half-precision_floating...

    It is intended for storage of floating-point values in applications where higher precision is not essential, in particular image processing and neural networks. Almost all modern uses follow the IEEE 754-2008 standard, where the 16-bit base-2 format is referred to as binary16, and the exponent uses 5 bits. This can express values in the range ...

  8. Associative array - Wikipedia

    en.wikipedia.org/wiki/Associative_array

    In computer science, an associative array, map, symbol table, or dictionary is an abstract data type that stores a collection of (key, value) pairs, such that each possible key appears at most once in the collection. In mathematical terms, an associative array is a function with finite domain. [1] It supports 'lookup', 'remove', and 'insert ...

  9. float64 - Wikipedia

    en.wikipedia.org/?title=Float64&redirect=no

    From Wikipedia, the free encyclopedia. Redirect page