Forecast api update

[Oufattole]

This resolves issue #104 . Will Merge after #103 . This implements generation analysis capabilities and sampling features for the model evaluation pipeline.

Changes

• Added generation analysis script using trainer.predict
• Implemented support for both greedy and non-greedy sampling (via the temperature parameter) with configurable sample count via num_samples
• Added default window attribute that flattens a window to top-level batch dictionary, for the multiwindow dataset class
• Added trajectory data generation with proper schema
• Fixed multiwindow dataset class bug where the global_end was incorrect

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Codecov Report

Attention: Patch coverage is 72.80164% with 133 lines in your changes missing coverage. Please review.

Project coverage is 74.12%. Comparing base (de8082e) to head (2e3f0fd). Report is 101 commits behind head on dev.

Files with missing lines	Patch %	Lines
src/meds_torch/generate_trajectories.py	33.33%	46 Missing :warning:
tests/test_generate_trajectories.py	30.61%	34 Missing :warning:
src/meds_torch/models/eic_forecasting.py	84.61%	22 Missing :warning:
src/meds_torch/utils/custom_tokenization.py	66.66%	15 Missing :warning:
src/meds_torch/data/components/pytorch_dataset.py	93.10%	6 Missing :warning:
src/meds_torch/data/datamodule.py	14.28%	6 Missing :warning:
...rch/data/components/multiwindow_pytorch_dataset.py	92.59%	4 Missing :warning:

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Additional details and impacted files

```diff @@ Coverage Diff @@ ## dev #108 +/- ## ========================================== + Coverage 64.80% 74.12% +9.31% ========================================== Files 10 55 +45 Lines 736 3192 +2456 ========================================== + Hits 477 2366 +1889 - Misses 259 826 +567 ```

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[Oufattole]

When we flatten to 2d tensors, the sequence length goes over the max_seq_len. We need to more elegantly handle this in load_subject. We need to modify this subsection of the function to correctly flatten and subsample to the max_seq_len. I'll add a doctested public function for handling it.

This doctest is flakey and I'm relatively confident it is due to nested-ragged-tensors: subsample_subject_data

@mmcdermott could you take a look?