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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.
Convert unsigned to an unsigned int64 (on the stack as int64) and throw an exception on overflow. Base instruction 0x76 conv.r.un: Convert unsigned integer to floating-point, pushing F on stack. Base instruction 0x6B conv.r4: Convert to float32, pushing F on stack. Base instruction 0x6C conv.r8: Convert to float64, pushing F on stack. Base ...
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.
The IEEE 754-2008 standard defines 32-, 64- and 128-bit decimal floating-point representations. Like the binary floating-point formats, the number is divided into a sign, an exponent, and a significand.
Pandas (styled as pandas) is a software library written for the Python programming language for data manipulation and analysis. In particular, it offers data structures and operations for manipulating numerical tables and time series .
Data conversion is the conversion of computer data from one format to another. Throughout a computer environment, data is encoded in a variety of ways. For example, computer hardware is built on the basis of certain standards, which requires that data contains, for example, parity bit checks.
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Regarding the data type, there are two variants depending on the source of the ply file. The type can be specified with one of char uchar short ushort int uint float double, or one of int8 uint8 int16 uint16 int32 uint32 float32 float64. For an object with ten polygonal faces, one might see: element face 10 property list uchar int vertex_index