gistfile1.txt

#Python3

import csv
import math
import glob
import numpy as np

def getExeNames(titles):
    ti = []
    for title in titles[1:]:
        ti.append(title)
    return ti

def getRow(row):
    r = [row[0]]

    points = []
    for i,p in enumerate( row[1:] ):
        #Convert the numbers separated by space into a array of integers
        #Fetch the max value of and return those.
        #print( p )
        #print( [(i) for i in p.strip().split(' ')] )
        values = [int('0'+i) for i in p.strip().split(' ')]
        #print( values );
        r.append( max( values ))

    return r

def removeFieldName(a, name):
    #https://stackoverflow.com/questions/15575878/how-do-you-remove-a-column-from-a-structured-numpy-array
    names = list(a.dtype.names)
    if name in names:
        names.remove(name)
    b = a[names]
    return b

def leaveFields(a, ns):
    names = list(a.dtype.names)

    #Find the corresponding names of fields that stay
    fields = []
    for n in ns:
        res = [i for i in names if n in i]
        fields.append( res[0] )

    #Find the difference and drop those---except the one named "Name"
    #https://www.w3resource.com/python-exercises/list/python-data-type-list-exercise-19.php
    diff1 = list( set(names) - set(fields) )
    diff2 = list( set(fields) - set(names) )
    diff = diff1 + diff2
    diff.remove("Name")
    for n in diff:
        a = removeFieldName(a, n)

    return a

#
#
#
#
#

fil = []
tul = []
kpl = []

if (0):

    kpl.append( '1: Elävä solu ' )
    fil.append( 'bg7_1.csv'  )
    tul.append( ['P1', 'P2', 'P3', 'S1', 'T1','YT1'] )

    kpl.append( '4: Levät ja planktoneläimet ovat vesien runsaimpia eliöitä' )
    fil.append( 'bg7_4.csv'  )
    tul.append( ['P1'] )

    name = "name1"
    name = "name2"

if (0):

    kpl.append( '3: Metsätyypiy ja puulajit' )
    fil.append( 'bg8_3.csv'  )
    tul.append( ['P1', 'P2'] )

    name = "name3"
    name = "name4"

#
#
#
ka = 0
lkm = 0 
print("\n\n")
print('Hei')
print('Maantiedon tehtäväsi tähän mennessä. Lopussa arvosana seisoo.')
print('Tarkista ainakin, että olet teet ne tehtävä mitkä olen merkinnyt arvosanalla neljä (4). Jos olet tehnyt, mutta arvosanasi on 4, kerro minulle. ')
print('Saat parannella ja lisäillä tehtäviä, jos haluat paremman numeron. Aikaa on.')
print('- - - - - - - - - - - - - - - - - - - - -')
ave = 0 
for i, tcsv in enumerate( fil ):
    lkm = lkm + 1
    names = []
    with open( tcsv ) as csvfile:
        print( kpl[i] )
        print( "-"*len( kpl[i] ) )
        readCSV = csv.reader(csvfile, delimiter=',')
        #Read the column names
        eNames = getExeNames(next(readCSV)) 
        eNames.insert(0,'Name')
        formats = ['u4']*( len( eNames ) - 1)
        formats.insert(0, 'U30')
        #print( eNames )

        # Create the array
        rr = [];
        for row in readCSV:
            r = getRow( row )
            rr.append( tuple(r) )
        points = np.array( (rr),  dtype={'names': eNames, 'formats':formats})
        #print( points )

        #Create the grading table.
        formatsGrade = ['f4']*( len( eNames ) - 1)
        formatsGrade.insert(0, 'U30')
        grades = np.array( (rr),  dtype={'names': eNames, 'formats':formatsGrade})
        #print( grades ) 
        #print( eNames )
        #print( len( eNames ) )
        for n in eNames[1:]:
            #print( grades[n] )
            grades[n] = grades[n]/ max( max( grades[n] ), 1 )
            grades[n] = np.maximum( np.round( ( 4*( 6/(1-0.1)*(grades[n]-1)+10 ))/4, 2), 4)
        #print( grades )
        

        #Get the needed columns (exercises) only
        grades = leaveFields(grades, tul[i])
        #print( grades.dtype.names[1:] ) 
        #print( grades ) 


        if 1:
            names = grades['Name'] 
            nameInd = [j for j,i in enumerate(names) if name.lower() in i.lower()]
            average = 4
            if nameInd:
                nameInd = nameInd[0]
                pp = list( grades[nameInd] )
                print( pp[0] )
                for ni, n in enumerate( grades.dtype.names[1:] ):
                    print( "Arvosana: " + str(pp[ni+1]) , end="\t" )
                    print(n)
                average = np.round( np.average( pp[1:] ), 1) 
            else:
                print("Et ole tehnyt yhtään tehtävää tästä luvusta! Tee vielä:")
                for ni, n in enumerate( grades.dtype.names[1:] ):
                    print(n)

            print( "-> Keskiarvo: " + str( average ) )
            ave = ave + average

        print("\n")
print('---------------')
print( 'Kaikkien tehtävien keskiarvo: ', np.round( ave/lkm, 1) )
print("\n\n")