We read every piece of feedback, and take your input very seriously.
To see all available qualifiers, see our documentation.
Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.
By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.
Already on GitHub? Sign in to your account
At the moment we cannot really make probability distributions in scipy.stats to self-identify.
>>> from scipy.stats import norm >>> type(norm) scipy.stats._continuous_distns.norm_gen >>> type(norm(1, 3)) scipy.stats._distn_infrastructure.rv_frozen
Vanilla introspection on these objects fails to separate id keys from object state, so manual code is in order.
The text was updated successfully, but these errors were encountered:
Probably the best place for this is a plugin + a function to decorate all of the required objects (e.g. random variables).
Also the sklearn wrapper would probably benefit from its own plugin + an optional function to monkey-patch required objects.
Sorry, something went wrong.
sdvillal
No branches or pull requests
At the moment we cannot really make probability distributions in scipy.stats to self-identify.
Vanilla introspection on these objects fails to separate id keys from object state, so manual code is in order.
The text was updated successfully, but these errors were encountered: