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other:python:misc_by_jyp [2023/05/04 12:33]
jypeter [Base notions] Improved
other:python:misc_by_jyp [2023/05/04 15:25]
jypeter [Numerical values] Lots of changes
Line 504: Line 504:
 ==== Numerical values ==== ==== Numerical values ====
  
-  * Binary data representation of some numbers (not everythin is listed here):+  * Binary data representation of some numbers (only some common types are listed here): 
 +    * Languages and packages **references** used below: 
 +      * Python: [[https://​numpy.org/​doc/​stable/​reference/​arrays.scalars.html#​sized-aliases|NumPy Sized aliases]] 
 +      * NetCDF: [[https://​docs.unidata.ucar.edu/​nug/​current/​md_types.html|Data Types]], [[https://​docs.unidata.ucar.edu/​netcdf-fortran/​current/​f90-variables.html#​f90-language-types-corresponding-to-netcdf-external-data-types|Fortran related Data Types]], [[https://​docs.unidata.ucar.edu/​nug/​current/​_c_d_l.html#​cdl_data_types|CDL Data Types]] 
 +      * Fortran: Intel Fortran Compiler [[https://​www.intel.com/​content/​www/​us/​en/​docs/​fortran-compiler/​developer-guide-reference/​2023-1/​intrinsic-data-types.html|Intrinsic Data Types]]
     * [[https://​en.wikipedia.org/​wiki/​Integer_(computer_science)|Integers]]     * [[https://​en.wikipedia.org/​wiki/​Integer_(computer_science)|Integers]]
       * Range:       * Range:
-        * 4-byte integers: −2,​147,​483,​648 to 2,​147,​483,​647+        * 4-byte ​//​signed// ​integers: ​''​−2,​147,​483,​648'' ​to ''​2,​147,​483,​647''​
           * Python: ''​numpy.int32''​           * Python: ''​numpy.int32''​
-          * [[https://​docs.unidata.ucar.edu/​nug/​current/​md_types.html|NetCDF]], [[https://​docs.unidata.ucar.edu/​netcdf-fortran/​current/​f90-variables.html#​f90-language-types-corresponding-to-netcdf-external-data-types|NetCDF-Fortran]]: ''​int'',​ ''​NC_INT64'',​ ''​NF90_INT''​ +          * NetCDF: ''​int'',​ ''​NC_INT''​ or ''​NC_LONG'',​ ''​NF90_INT''​ 
-          * Fortran: +          * Fortran: ​''​INTEGER*4''​ 
-        * 8-byte integers: −9,​223,​372,​036,​854,​775,​808 to 9,​223,​372,​036,​854,​775,​807+        * 8-byte ​//​signed// ​integers: ​''​−9,​223,​372,​036,​854,​775,​808'' ​to ''​9,​223,​372,​036,​854,​775,​807''​
           * Python: ''​numpy.int64''​           * Python: ''​numpy.int64''​
-          * [[https://​docs.unidata.ucar.edu/​nug/​current/​md_types.html|NetCDF]]: ''​int64'',​ ''​NC_INT64''​ +          * NetCDF: ''​int64'',​ ''​NC_INT64''​ 
-          * Fortran:+          * Fortran: ​''​INTEGER*8''​
       * Tech note: signed integers use [[https://​en.wikipedia.org/​wiki/​Two%27s_complement|two'​s complement]] for coding negative integers       * Tech note: signed integers use [[https://​en.wikipedia.org/​wiki/​Two%27s_complement|two'​s complement]] for coding negative integers
     * [[https://​en.wikipedia.org/​wiki/​IEEE_754|Floating point numbers]] (//IEEE 754// standard aka //IEEE Standard for Binary Floating-Point for Arithmetic//​)     * [[https://​en.wikipedia.org/​wiki/​IEEE_754|Floating point numbers]] (//IEEE 754// standard aka //IEEE Standard for Binary Floating-Point for Arithmetic//​)
       * Range:       * Range:
-        * 4-byte float: ~8 significant digits * 10E±38+        * 4-byte float: ​''​~8 significant digits * 10E±38''​
           * Python: ''​numpy.float32''​           * Python: ''​numpy.float32''​
-          * [[https://​docs.unidata.ucar.edu/​nug/​current/​md_types.html|NetCDF]][[https://​docs.unidata.ucar.edu/​netcdf-fortran/​current/​f90-variables.html#​f90-language-types-corresponding-to-netcdf-external-data-types|NetCDF-Fortran]]: ​ +          * NetCDF''​float''​''​NC-FLOAT'',​ ''​NF90_FLOAT''​ 
-          * Fortran:+          * Fortran:''​REAL*4''​
           * See also [[https://​en.wikipedia.org/​wiki/​Single-precision_floating-point_format|Single-precision floating-point format]]           * See also [[https://​en.wikipedia.org/​wiki/​Single-precision_floating-point_format|Single-precision floating-point format]]
-        * 8-byte float: ~15 significant digits * 10E±308+        * 8-byte float: ​''​~15 significant digits * 10E±308''​
           * Python: ''​numpy.float64''​           * Python: ''​numpy.float64''​
-          * [[https://​docs.unidata.ucar.edu/​nug/​current/​md_types.html|NetCDF]][[https://​docs.unidata.ucar.edu/​netcdf-fortran/​current/​f90-variables.html#​f90-language-types-corresponding-to-netcdf-external-data-types|NetCDF-Fortran]]: ​ +          * NetCDF''​double''​''​NC_DOUBLE'',​ ''​NF90_DOUBLE''​ 
-          * Fortran: +          * Fortran: ​''​REAL*8''​ 
-      * Special values: +      ​* **Special values**
-        * [[https://​en.wikipedia.org/​wiki/​NaN|NaN]] ​(''​numpy.nan''​): //Not a Number// +        * [[https://​en.wikipedia.org/​wiki/​NaN|NaN]]:​ //Not a Number// 
-        * Infinity ​(''​-numpy.inf''​ and ''​numpy.inf''​)+          * Python: ''​numpy.nan''​ 
 +        * Infinity 
 +          * Python: ​''​-numpy.inf''​ and ''​numpy.inf''​
         * Note: it is cleaner to use masks (and [[https://​numpy.org/​doc/​stable/​reference/​maskedarray.generic.html|Numpy masked arrays]]) than NaNs, when you have to deal with missing values !         * Note: it is cleaner to use masks (and [[https://​numpy.org/​doc/​stable/​reference/​maskedarray.generic.html|Numpy masked arrays]]) than NaNs, when you have to deal with missing values !
-    ​* [[https://​en.wikipedia.org/​wiki/​Bit_numbering|Bit numbering]] +      * <wrap hi>The RISKS of working with (the wrong) floats</​wrap>:​ 
-    * [[https://​en.wikipedia.org/​wiki/​Endianness|Endianness]]+        ​* [[https://​en.wikipedia.org/​wiki/​Round-off_error|Round-off error]] 
 +        * [[https://​en.wikipedia.org/​wiki/​Catastrophic_cancellation|Catastrophic cancellation]] 
 +          * [[https://​docs.oracle.com/​cd/​E19957-01/​806-3568/​ncg_goldberg.html|What Every Computer Scientist Should Know About Floating-Point Arithmetic]]
     * A rather technical example: we //play// with a numpy 4-byte integer scalar     * A rather technical example: we //play// with a numpy 4-byte integer scalar
       * <​code>>>>​ one_int32 = np.int32(1)       * <​code>>>>​ one_int32 = np.int32(1)
other/python/misc_by_jyp.txt · Last modified: 2024/04/19 12:02 by jypeter