The following task concerns data that came from a pollution monitoring station with twenty-four instruments monitoring twenty-four aspects of pollution in the air. Periodically a record is added to the file, each record being a line of 49 fields separated by white-space, which can be one or more space or tab characters.

The fields (from the left) are:

 DATESTAMP [ VALUEn FLAGn ] * 24

i.e. a datestamp followed by twenty-four repetitions of a floating-point instrument value and that instrument's associated integer flag. Flag values are >= 1 if the instrument is working and < 1 if there is some problem with it, in which case that instrument's value should be ignored.

A sample from the full data file readings.txt, which is also used in the Text processing/1 task, follows:

Data is no longer available at that link. Zipped mirror available here

1991-03-30	10.000	1	10.000	1	10.000	1	10.000	1	10.000	1	10.000	1	10.000	1	10.000	1	10.000	1	10.000	1	10.000	1	10.000	1	10.000	1	10.000	1	10.000	1	10.000	1	10.000	1	10.000	1	10.000	1	10.000	1	10.000	1	10.000	1	10.000	1	10.000	1
1991-03-31	10.000	1	10.000	1	10.000	1	10.000	1	10.000	1	10.000	1	10.000	1	20.000	1	20.000	1	20.000	1	35.000	1	50.000	1	60.000	1	40.000	1	30.000	1	30.000	1	30.000	1	25.000	1	20.000	1	20.000	1	20.000	1	20.000	1	20.000	1	35.000	1
1991-03-31	40.000	1	0.000	-2	0.000	-2	0.000	-2	0.000	-2	0.000	-2	0.000	-2	0.000	-2	0.000	-2	0.000	-2	0.000	-2	0.000	-2	0.000	-2	0.000	-2	0.000	-2	0.000	-2	0.000	-2	0.000	-2	0.000	-2	0.000	-2	0.000	-2	0.000	-2	0.000	-2	0.000	-2
1991-04-01	0.000	-2	13.000	1	16.000	1	21.000	1	24.000	1	22.000	1	20.000	1	18.000	1	29.000	1	44.000	1	50.000	1	43.000	1	38.000	1	27.000	1	27.000	1	24.000	1	23.000	1	18.000	1	12.000	1	13.000	1	14.000	1	15.000	1	13.000	1	10.000	1
1991-04-02	8.000	1	9.000	1	11.000	1	12.000	1	12.000	1	12.000	1	27.000	1	26.000	1	27.000	1	33.000	1	32.000	1	31.000	1	29.000	1	31.000	1	25.000	1	25.000	1	24.000	1	21.000	1	17.000	1	14.000	1	15.000	1	12.000	1	12.000	1	10.000	1
1991-04-03	10.000	1	9.000	1	10.000	1	10.000	1	9.000	1	10.000	1	15.000	1	24.000	1	28.000	1	24.000	1	18.000	1	14.000	1	12.000	1	13.000	1	14.000	1	15.000	1	14.000	1	15.000	1	13.000	1	13.000	1	13.000	1	12.000	1	10.000	1	10.000	1

Task

 Confirm the general field format of the file.
 Identify any DATESTAMPs that are duplicated.
 Report the number of records that have good readings for all instruments.


package main
 
import (
	"bufio"
	"fmt"
	"log"
	"os"
	"strconv"
	"strings"
	"time"
)
 
const (
	filename   = "readings.txt"
	readings   = 24             // per line
	fields     = readings*2 + 1 // per line
	dateFormat = "2006-01-02"
)
 
func main() {
	file, err := os.Open(filename)
	if err != nil {
		log.Fatal(err)
	}
	defer file.Close()
	var allGood, uniqueGood int
	// map records not only dates seen, but also if an all-good record was
	// seen for the key date.
	m := make(map[time.Time]bool)
	s := bufio.NewScanner(file)
	for s.Scan() {
		f := strings.Fields(s.Text())
		if len(f) != fields {
			log.Fatal("unexpected format,", len(f), "fields.")
		}
		ts, err := time.Parse(dateFormat, f[0])
		if err != nil {
			log.Fatal(err)
		}
		good := true
		for i := 1; i < fields; i += 2 {
			flag, err := strconv.Atoi(f[i+1])
			if err != nil {
				log.Fatal(err)
			}
			if flag > 0 { // value is good
				_, err := strconv.ParseFloat(f[i], 64)
				if err != nil {
					log.Fatal(err)
				}
			} else { // value is bad
				good = false
			}
		}
		if good {
			allGood++
		}
		previouslyGood, seen := m[ts]
		if seen {
			fmt.Println("Duplicate datestamp:", f[0])
		}
		m[ts] = previouslyGood || good
		if !previouslyGood && good {
			uniqueGood++
		}
	}
	if err := s.Err(); err != nil {
		log.Fatal(err)
	}
 
	fmt.Println("\nData format valid.")
	fmt.Println(allGood, "records with good readings for all instruments.")
	fmt.Println(uniqueGood,
		"unique dates with good readings for all instruments.")
}