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--- other:python:misc_by_jyp [2023/04/28 16:59] – [Data representation] Added link to old tutorial jypeter
+++ other:python:misc_by_jyp [2023/05/04 13:19] – [Base notions] jypeter
@@ Line 467: / Line 467: @@
 FIXME Add parts (pages 28 to 37) of this [[https://wiki.lsce.ipsl.fr/pmip3/doku.php/other:python:jyp_steps#part_2|old tutorial]] to this section
+==== Base notions ====
+  * **Never forget** that all the bits and pieces of information we use are coded in [[https://en.wikipedia.org/wiki/Binary_number#Counting_in_binary|base 2]] (''0''s and ''1''s), grouped in bytes!
+    * Some things can be stored exactly (integers, characters, ...)
+    * In other cases (**//real// numbers** that we work with all the time, compressed images/videos/music) we only store **//good enough approximation//**
+  * 1 byte <=> 8 bits
+    * ''REAL*4'' <=> 4 bytes <=> 32 bits
+    * For easier written/displayed representation, 1 byte is usually split into 2 groups of 4 bits, and displayed using base 16 and [[https://en.wikipedia.org/wiki/Hexadecimal|hexadecimal representation]] (characters ''0'', ''1'', ..., ''A'', ''B'', ..., ''F'')
+      * ''0000'' <=> ''0'',\\ ''0010'' <=> ''1'', ...,\\ ''1111'' <=> ''F''
+      * ''1101'' <=> ''D'' in hexadecimal <=> ''13'' in decimal (''**1** * 8 + **1** * 4 + **0** * 2 + **1** * 1'')
+      * ''11111101'' <=> ''1111 1101'' <=> ''FD'' in hexadecimal <=> ''253'' in decimal (''15 * 16 + 13'')
+  * Conversion with Python
+    * <code>>>> hex(13) # Decimal to Hexadecimal conversion
+'0xd'
+>>> hex(253)
+'0xfd'
+>>> hex(256)
+'0x100'
+>>> int('0x100', 16) # Hexadecimal to Decimal conversion
+>>> int('11', 2)
+>>> int('1111', 2) # Binary to Decimal conversion
+>>> int('11111101', 2)
+>>> 15 * 16 + 13
+>>> 013 # DANGER! Python considers an integer to be in OCTAL base if it starts with a 0
+>>> int('13', 8) # 1*8 + 3
+</code>
 ==== Numerical values ====
-  * Binary data representation of some numbers:
+  * Binary data representation of some numbers (not everythin is listed here):
     * [[https://en.wikipedia.org/wiki/Integer_(computer_science)|Integers]]
       * Range:
-        * 4-byte integers (''numpy.int32''): −2,147,483,648 to 2,147,483,647
+        * 4-byte integers: −2,147,483,648 to 2,147,483,647
-        * 8-byte integers (''numpy.int64''): −9,223,372,036,854,775,808 to 9,223,372,036,854,775,807
+          * 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''
+          * Fortran:
+        * 8-byte integers: −9,223,372,036,854,775,808 to 9,223,372,036,854,775,807
+          * Python: ''numpy.int64''
+          * [[https://docs.unidata.ucar.edu/nug/current/md_types.html|NetCDF]]: ''int64'', ''NC_INT64''
+          * Fortran:
       * 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//)
       * Range:
-        * 4-byte float (''numpy.float32''): ~8 significant digits * 10E±38
+        * 4-byte float: ~8 significant digits * 10E±38
+          * 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]]:
+          * Fortran:
           * See also [[https://en.wikipedia.org/wiki/Single-precision_floating-point_format|Single-precision floating-point format]]
-        * 8-byte float (''numpy.float64''): ~15 significant digits * 10E±308
+        * 8-byte float: ~15 significant digits * 10E±308
+          * 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]]:
+          * Fortran:
       * Special values:
         * [[https://en.wikipedia.org/wiki/NaN|NaN]] (''numpy.nan''): //Not a Number//