# Fractional factorial DOE in pythonDOE problem

I need to do a fractional factorial DOE analysis for my data that will come at the end of the post as image, I am using this code in python . It would need to pip install diversipy if you haven't installed it.

my problem is that the code documentaion for fractional factorial is not clear for me. it asks :

"Please enter the generator string for the fractional factorial build: "

and in the explanation it is :

    """
Builds a fractional factorial design dataframe from a dictionary of factor/level ranges.
Only min and max values of the range are required.
Example of the dictionary:
{'Pressure':[50,70],'Temperature':[290, 350],'Flow rate':[0.9,1.0]}

This function requires a little more knowledge of how the confounding will be allowed.
This means that some factor effects get muddled with other interaction effects, so it’s harder to distinguish between them).

Let’s assume that we just can’t afford (for whatever reason) the number of runs in a full-factorial design. We can systematically decide on a fraction of the full-factorial by allowing some of the factor main effects to be confounded with other factor interaction effects.
This is done by defining an alias structure that defines, symbolically, these interactions. These alias structures are written like “C = AB” or “I = ABC”, or “AB = CD”, etc.
These define how one column is related to the others.

EXAMPLE
------------
For example, the alias “C = AB” or “I = ABC” indicate that there are three factors (A, B, and C) and that the main effect of factor C is confounded with the interaction effect of the product AB, and by extension, A is confounded with BC and B is confounded with AC.
A full- factorial design with these three factors results in a design matrix with 8 runs, but we will assume that we can only afford 4 of those runs.
To create this fractional design, we need a matrix with three columns, one for A, B, and C, only now where the levels in the C column is created by the product of the A and B columns.
"""


so here the following is my input data, where obviously the code takes only the first row and the last row. but I put all of the values I have used in the experiment, because what I need to find out eventually is that if these chosen values are good comparing to the values offered by DOE analysis

so for the mentioned input data, I did a b ab since I have 2 inputs and one output. and I got the following for the fractional factorial, but I am not sure if I have done it right :

• Fractional factorial in pyDOE is available only for 2-level factors. However, your case got more than 2 levels. Hence, consider GSD of pyDOE2. Dec 12, 2019 at 14:08