How to resolve the algorithm Text processing/1 step by step in the Forth programming language

Published on 12 May 2024 09:40 PM

How to resolve the algorithm Text processing/1 step by step in the Forth programming language

Table of Contents

Problem Statement

Often data is produced by one program, in the wrong format for later use by another program or person. In these situations another program can be written to parse and transform the original data into a format useful to the other. The term "Data Munging" is often used in programming circles for this task. A request on the comp.lang.awk newsgroup led to a typical data munging task: The data is free to download and use and is of this format: Data is no longer available at that link. Zipped mirror available here (offsite mirror). Only a sample of the data showing its format is given above. The full example file may be downloaded here. Structure your program to show statistics for each line of the file, (similar to the original Python, Perl, and AWK examples below), followed by summary statistics for the file. When showing example output just show a few line statistics and the full end summary.

Let's start with the solution:

Step by Step solution about How to resolve the algorithm Text processing/1 step by step in the Forth programming language

Source code in the forth programming language

\ data munging

\ 1991-03-30[\t10.000\t[-]1]*24

\ 1. mean of valid (flag > 0) values per day and overall
\ 2. length of longest run of invalid values, and when it happened

fvariable day-sum
variable day-n

fvariable total-sum
variable total-n

10 constant date-size    \ yyyy-mm-dd
create cur-date date-size allot

create bad-date date-size allot
variable bad-n

create worst-date date-size allot
variable worst-n

: split ( buf len char -- buf' l2  buf l1 )  \ where buf'[0] = char, l1 = len-l2
  >r 2dup r> scan
  2swap 2 pick - ;

: next-sample ( buf len -- buf' len' fvalue flag )
  #tab split >float   drop    1 /string
  #tab split snumber? drop >r 1 /string r> ;

: ok?  0> ;

: add-sample ( value -- )
  day-sum f@ f+ day-sum f!
  1 day-n +! ;
  
: add-day
  day-sum f@ total-sum f@ f+ total-sum f!
  day-n @ total-n +! ;

: add-bad-run
  bad-n @ 0= if
    cur-date bad-date date-size move
  then
  1 bad-n +! ;

: check-worst-run
  bad-n @ worst-n @ > if
    bad-n @ worst-n !
    bad-date worst-date date-size move
  then
  0 bad-n ! ;

: hour ( buf len -- buf' len' )
  next-sample ok? if
    add-sample
    check-worst-run
  else
    fdrop
    add-bad-run
  then ;

: .mean ( sum count -- ) 0 d>f f/ f. ;

: day ( line len -- )
  2dup + #tab swap c! 1+			\ append tab for parsing
  #tab split cur-date swap move 1 /string	\ skip date
  0e day-sum f!
  0  day-n !
  24 0 do hour loop 2drop
  cur-date date-size type ."  mean = "
  day-sum f@ day-n @ .mean cr
  add-day ;

stdin value input

: main
  s" input.txt" r/o open-file throw to input
  0e total-sum f!
  0 total-n !
  0 worst-n !
  begin  pad 512 input read-line throw
  while  pad swap day
  repeat
  input close-file throw
  worst-n @ if
    ."  Longest interruption: " worst-n @ .
    ." hours starting " worst-date date-size type cr
  then
  ."  Total mean = "
  total-sum f@ total-n @ .mean cr ;

main bye


  

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