Careless

This release adds new functions to calculate and filter by CCpred for each image.
- `careless.image_ccpred` is a new function with similar syntax to the other stats scripts. It calculates the correlation coefficient between the predictions and data for each image.
- `careless.filter_image` is a tool that can be used to reject images in unmerged data on the basis of CCpred from a previous `careless` run.

In this release there are two major changes
- All correlation coefficient based stats functions now use a weighted Pearson correlation by default
- If training encounters numerical issues, optimization will now terminate early rather than crashing

This release fixes a bug which could lead to numerical instability of the truncated normal surrogate posterior.

This version adds a new feature to the CLI, the `--kl-weight` parameter. When `--kl-weight` is specified, the log likelihood and kl divergence terms in the loss function are reduced by taking the mean rather than the sum. The ELBO is then computed as


ELBO = mean(log_likelihood) + kl_weight * mean(kl_div)

This feature will be useful in making comparisons across isomorphous data sets of different sizes.

This release does two things
- Fix a bug whereby the miller indices for Laue predictions files were incorrect
- Add file_id, asu_id, and image_id columns to the predictions files

In v0.3.1, saving the mean and uncertainty of scale factors for each reflection was implemented incorrectly. This release fixes the bug.