I wrote this code and quite unexpectedly ran into this
for i in range(9):
x = np.arange(i+0.8, i+1.3, 0.1)
print(i, x)
this is output
0 [0.8 0.9 1. 1.1 1.2]
1 [1.8 1.9 2. 2.1 2.2]
2 [2.8 2.9 3. 3.1 3.2]
3 [3.8 3.9 4. 4.1 4.2]
4 [4.8 4.9 5. 5.1 5.2]
5 [5.8 5.9 6. 6.1 6.2]
6 [6.8 6.9 7. 7.1 7.2]
7 [7.8 7.9 8. 8.1 8.2 8.3]
8 [8.8 8.9 9. 9.1 9.2]
Why is the 7th row like this?
Why exactly in the 7th row?
In general, decimal fractions do not fit nicely into binary floating point formats.
for i in range(9):
x = np.arange(10*i+8, 10*i+13, 1) / 10
print(i, x)
Result
0 [0.8 0.9 1. 1.1 1.2]
1 [1.8 1.9 2. 2.1 2.2]
2 [2.8 2.9 3. 3.1 3.2]
3 [3.8 3.9 4. 4.1 4.2]
4 [4.8 4.9 5. 5.1 5.2]
5 [5.8 5.9 6. 6.1 6.2]
6 [6.8 6.9 7. 7.1 7.2]
7 [7.8 7.9 8. 8.1 8.2]
8 [8.8 8.9 9. 9.1 9.2]
Always try to use integers for loop control etc.
You can fudge things for decimals by adding "a little extra" but in general it only leads to hard-to-discover bugs later.
print(0.1+0.2 == 0.3)
You might think this should be True, but it is False.
This is because there is a tiny difference, due to the rounding errors in trying to represent round decimals in binary.
print(0.1+0.2 -0.3)
5.551115123125783e-17
