How physics based loss function applied to synthetic data generation?

[kilickursat]

Problem description

I have soil parameters and they are small in size. I applied CopulaGAN and also GaussianCopula to increase the size of data. I have obtained large size soil parameters. By the way, the dataset is only a continuous variable.
My purpose is to obtain physics consistency while data generation because I would like to show the synthetic data will be generated based on rock mechanics law. Therefore, I would like to add rock mechanics law as a loss function to the Copulas.
But I didn't see loss inside the Copulas class.
Do I need to add rock mechanics law into the constraints?
Or how can I implement this physics law to the data generation?

What I already tried

I have applied GaussianCopula and CopulaGAN so far. The dataset has 7 columns 18 rows (real data). After application, I have obtained 7 columns 700 rows (synthetic data). The dataset is only consisting of continuous variables.

[npatki]

Unfortunately, the SDV does not support modifying the loss function right now, and it's not currently in our roadmap.

Constraints are meant to help ensure that strict rules found in the dataset are followed. Use these for cases when all rows must follow some explicit logic.

[kilickursat]

Thanks for the reply. So, could you elaborate on the constraints?
I have 7 features and they are related to each other because the real data was obtained from laboratory tests. How can I apply constraints to sustain logic in data generation?
For example,
I have triaxial test results like effective stress, pressure, axial stress, so the effective stress was obtained by axial stress and pressure in the empirical formula. When I try to increase the number of these parameters, how can I use constraints?
How do these rows follow explicit logic?
Thank you.

[npatki]

No problem! If your columns follow a deterministic formula then you can use the ColumnFormula constraint -- for example ColumnC = ColumnA - ColumnB. The SDV will then synthesize ColumnA & ColumnB, and then use the logic to compute ColumnC based on that.

You can apply the ColumnFormula constraint multiple times for different columns, as long as the logic to compute columns is not circular.

[kilickursat]

Many Thanks, Neha, I will apply and inform the GitHub issue about the outcome.

[kilickursat]

I have taken the following error after ColumnFormula for UniqueConstraints. I have also attached some part of data.

[npatki]

Hello, thanks for the feedback!

Issue #595 has more details about the ConstraintsNotMetError. Could you check there and add your details to that discussion?

[kilickursat]

Thanks for the reply. I have already checked #595 issue but I could not understand how can I solve this error. I will add my detail in the 595 issues. Thanks for your help.

[npatki]

Hello, I'm closing off this issue since he had further discussion in #595.