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@Mehdi-Amine
Last active June 16, 2020 23:36
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concatenating the columns of the happiness dataset
def assemble(col1, col2, col3, col4):
return np.concatenate((col1, col2, col3, col4), axis=1)
csd = assemble(cold[:s], slow[:s], dislike[:s], unhappy)
csl = assemble(cold[s:s*2], slow[s:s*2], like[:s], unhappy)
cfd = assemble(cold[s*2:s*3], fast[:s], dislike[s:s*2], unhappy)
cfl = assemble(cold[s*3:s*4], fast[s:s*2], like[s:s*2], happy)
hsd = assemble(hot[:s], slow[s*2:s*3], dislike[s*2:s*3], unhappy)
hsl = assemble(hot[s:s*2], slow[s*3:s*4], like[s*2:s*3], happy)
hfd = assemble(hot[s*2:s*3], fast[s*2:s*3], dislike[s*3:s*4], happy)
hfl = assemble(hot[s*3:s*4], fast[s*3:s*4], like[s*3:s*4], happy)
bsd = assemble(burning[:s], slow[s*4:s*5], dislike[s*4:s*5], unhappy)
bsl = assemble(burning[s:s*2], slow[s*5:s*6], like[s*4:s*5], unhappy)
bfd = assemble(burning[s*2:s*3], fast[s*4:s*5], dislike[s*5:s*6], unhappy)
bfl = assemble(burning[s*3:s*4], fast[s*5:s*6], like[s*5:s*6], happy)
# tea internet book
tib = np.concatenate((csd, csl, cfd, cfl, hsd, hsl, hfd, hfl, bsd, bsl, bfd, bfl), axis=0)
# printing results
tib[:5], tib.shape
'''
Out:
(array([[11.236, 12.965, 0. , 0. ],
[28.521, 3.448, 0. , 0. ],
[21.96 , 17.448, 0. , 0. ],
[17.96 , 12.262, 0. , 0. ],
[ 4.681, 3.144, 0. , 0. ]]), (6000, 4))
'''
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