Diagnostics and plots for Pushforward of prior

## Issue
When leaving settings of perfect model-data pairings it is common to have prior or model misspecification. Catching these early, (i.e. before the algorithm iterates) would save users some time.

## Suggestions
The user creates the EKP setting, generates and runs the initial ensemble.
- [ ] We could add recipes that plot the following lines: (1) `y,G(\theta_i)` with ribbon`diag(\Gamma)` (2) `\Gamma^{-1/2}y, \Gamma^{-1/2}G(\theta)_i)` with ribbon `I`. This could be extended to any iteration, for example, `plot_pushforward(ekp,i)` for plotting the pushforward of iteration `i`.
- [ ] Some quick diagnostic to evaluate the consistency of the truth and prior.
- [ ] ...

No files or tests are named. Start by locating the EKP setting and initial-ensemble workflow, then review existing plotting entry points before deciding how a proposed plot_pushforward(ekp,i) API would fit. Done should include pushforward plots for the suggested raw and normalized views plus a defined quick diagnostic for prior-truth consistency.

Written by the indexing model from the issue text.