Update README.md
Signed-off-by: David Rotermund <54365609+davrot@users.noreply.github.com>
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# dtype
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# Available dtype
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{:.no_toc}
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{:.no_toc}
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<nav markdown="1" class="toc-class">
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<nav markdown="1" class="toc-class">
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@ -12,61 +12,114 @@ A numpy matrix can have differnt dtype or -- in other words -- differnt types of
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Questions to [David Rotermund](mailto:davrot@uni-bremen.de)
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Questions to [David Rotermund](mailto:davrot@uni-bremen.de)
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## Signed integer types
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## [Signed integer types](https://numpy.org/doc/stable/reference/arrays.scalars.html#sized-aliases)
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**Please use numpy.int8, numpy.int16, numpy.int32, and numpy.int64 !!!**
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**Please use numpy.int8, numpy.int16, numpy.int32, and numpy.int64 !!!**
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* *numpy.int8*:
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* *numpy.int8*: 8-bit signed integer (-128 to 127). Compatible with C char.
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* 8-bit signed integer (-128 to 127). Compatible with C char.
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* *numpy.byte*
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* *numpy.byte*
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* Character code 'b'
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* Character code 'b'
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* *numpy.int16*: 16-bit signed integer (-32 768 to 32 767). Compatible with C short
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* *numpy.int16*:
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* 16-bit signed integer (-32 768 to 32 767). Compatible with C short
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* *numpy.short*
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* *numpy.short*
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* Character code 'h'
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* Character code 'h'
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* *numpy.int32*: 32-bit signed integer (-2 147 483 648 to 2 147 483 647). Compatible with C int
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* *numpy.int32*:
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* 32-bit signed integer (-2 147 483 648 to 2 147 483 647). Compatible with C int
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* *numpy.intc*
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* *numpy.intc*
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* Character code 'i'
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* Character code 'i'
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* *numpy.int64*: 64-bit signed integer (-9 223 372 036 854 775 808 to 9 223 372 036 854 775 807). Compatible with Python int and C long
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* *numpy.int64*:
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* 64-bit signed integer (-9 223 372 036 854 775 808 to 9 223 372 036 854 775 807). Compatible with Python int and C long
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* *numpy.intp*
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* *numpy.intp*
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* *numpy.int_*
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* *numpy.int_*
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* Character code 'l'
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* Character code 'l'
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* *numpy.longlong*: Compatible with C long long
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*numpy.longlong*: Compatible with C long long
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* Character code 'q'
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* Character code 'q'
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## Unsigned integer types
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## [Unsigned integer types](https://numpy.org/doc/stable/reference/arrays.scalars.html#sized-aliases)
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**Please use numpy.uint8, numpy.uint16, numpy.uint32, and numpy.uint64 !!!**
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**Please use numpy.uint8, numpy.uint16, numpy.uint32, and numpy.uint64 !!!**
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* *numpy.uint8*: 8-bit unsigned integer (0 to 255). Compatible with C unsigned char.
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* *numpy.uint8*:
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* 8-bit unsigned integer (0 to 255). Compatible with C unsigned char.
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* *numpy.ubyte*
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* *numpy.ubyte*
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* Character code 'B'
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* Character code 'B'
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* *numpy.uint16*: 16-bit unsigned integer (0 to 65 535). Compatible with C unsigned short.
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* *numpy.uint16*:
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* 16-bit unsigned integer (0 to 65 535). Compatible with C unsigned short.
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* *numpy.ushort*
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* *numpy.ushort*
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* Character code 'H'
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* Character code 'H'
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* *numpy.uint32*: 32-bit unsigned integer (0 to 4 294 967 295). Compatible with C unsigned int.
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* *numpy.uint32*:
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* 32-bit unsigned integer (0 to 4 294 967 295). Compatible with C unsigned int.
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* *numpy.uintc*
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* *numpy.uintc*
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* Character code 'I'
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* Character code 'I'
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* *numpy.uint64*: 64-bit unsigned integer (0 to 18 446 744 073 709 551 615). Compatible with C unsigned long
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* *numpy.uint64*:
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* 64-bit unsigned integer (0 to 18 446 744 073 709 551 615). Compatible with C unsigned long
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* numpy.uint
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* numpy.uint
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* numpy.uintp
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* numpy.uintp
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* Character code 'L'
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* Character code 'L'
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* numpy.ulonglong: Compatible with C unsigned long long
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* *numpy.ulonglong*: Compatible with C unsigned long long
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* Character code 'Q'
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* Character code 'Q'
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## [Floating-point types](https://numpy.org/doc/stable/reference/arrays.scalars.html#sized-aliases)
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**Please use numpy.float32 and numpy.float64 !!! (And in very special cases numpy.float128)**
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* *numpy.float16*:
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* 16-bit-precision.
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* *numpy.half*
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* floating-point number type: sign bit, 5 bits exponent, 10 bits mantissa.
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* Character code 'e'
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* *numpy.float32*:
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* 32-bit-precision. Compatible with C float
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* *numpy.single*
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* floating-point number type: sign bit, 8 bits exponent, 23 bits mantissa.
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* Character code 'f'
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* *numpy.float64*:
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* 64-bit precision. Compatible with Python float and C double.
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* *numpy.double*
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* *numpy.float_*
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* floating-point number type: sign bit, 11 bits exponent, 52 bits mantissa.
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* Character code 'd'
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* *numpy.float128*:
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* 128-bit extended-precision floating-point number type.
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* *numpy.longdouble*
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* *numpy.longfloat*
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* Compatible with C long double but not necessarily with IEEE 754 quadruple-precision.
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* Character code 'g'
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## [Complex floating-point types](https://numpy.org/doc/stable/reference/arrays.scalars.html#sized-aliases)
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**Please use numpy.complex64 and numpy.complex128 !!! (And in very special cases numpy.complex256)**
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* *numpy.complex64*:
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* Composed of 2 32-bit-precision floating-point numbers.
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* *numpy.singlecomplex*
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* *numpy.csingle*
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* Character code 'F'
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* *numpy.complex128*:
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* Composed of 2 64-bit-precision floating-point numbers. Compatible with Python complex.
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* *numpy.cdouble*
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* *numpy.cfloat*
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* *numpy.complex_*
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* Character code 'D'
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* *numpy.complex256*:
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* Composed of 2 128-bit extended-precision floating-point numbers.
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* *numpy.clongdouble*
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* *numpy.clongfloat*
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* *numpy.longcomplex*
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* Character code 'G'
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