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# unifom_leaf_subsampler_test.py

Here's a detailed documentation of the target file:

## High-level description

This file contains unit tests for the UniformLeafSubsampler class, which is responsible for uniformly subsampling leaves from a CassiopeiaTree. The tests cover various scenarios including parameter validation, error handling, and the correctness of the subsampling process.

## Symbols

### `UniformLeafSubsamplerTest`

#### Description

A test class that inherits from `unittest.TestCase`, containing multiple test methods to verify the functionality of the UniformLeafSubsampler class.

#### Internal Logic

The class contains three main test methods:

1. `test_bad_parameters`: Tests error handling for invalid initialization parameters.
2. `test_bad_number_of_samples`: Tests error handling for invalid sample sizes.
3. `test_subsample_balanced_tree`: Tests the subsampling process on a balanced tree.
4. `test_subsample_custom_tree`: Tests the subsampling process on a custom tree.

### `test_bad_parameters`

#### Description

Tests that the UniformLeafSubsampler raises appropriate errors when initialized with invalid parameters.

#### Internal Logic

1. Attempts to create a UniformLeafSubsampler with both ratio and number\_of\_leaves specified, expecting a LeafSubsamplerError.
2. Attempts to create a UniformLeafSubsampler with neither ratio nor number\_of\_leaves specified, expecting a LeafSubsamplerError.

### `test_bad_number_of_samples`

#### Description

Tests that the UniformLeafSubsampler raises appropriate errors when attempting to subsample with invalid sample sizes.

#### Internal Logic

1. Creates a balanced tree using networkx.
2. Attempts to subsample with 0 leaves, expecting a LeafSubsamplerError.
3. Attempts to subsample with a very small ratio (0.0001), expecting a LeafSubsamplerError.

### `test_subsample_balanced_tree`

#### Description

Tests the subsampling process on a balanced tree, verifying the correctness of the resulting subsampled tree.

#### Internal Logic

1. Creates a balanced tree using networkx.
2. Performs subsampling with a fixed number of leaves (3) and verifies the resulting tree structure.
3. Performs subsampling with a ratio (0.65) and verifies the resulting tree structure.

### `test_subsample_custom_tree`

#### Description

Tests the subsampling process on a custom tree, verifying the correctness of the resulting subsampled tree, including branch lengths and node times.

#### Internal Logic

1. Creates a custom tree using networkx.
2. Performs subsampling with a ratio (0.5) and verifies the resulting tree structure, branch lengths, and node times.
3. Performs subsampling with a fixed number of leaves (6) and verifies the resulting tree structure.

## Dependencies

| Dependency                                 | Purpose                                                    |
| :----------------------------------------- | :--------------------------------------------------------- |
| unittest                                   | Provides the testing framework                             |
| networkx                                   | Used to create and manipulate graph structures for testing |
| numpy                                      | Used for random number generation in the tests             |
| cassiopeia.data.CassiopeiaTree             | The main tree structure being tested                       |
| cassiopeia.simulator.LeafSubsampler        | Provides the LeafSubsamplerError                           |
| cassiopeia.simulator.UniformLeafSubsampler | The class being tested                                     |

## Error Handling

The tests specifically check for proper error handling in the following cases:

1. Invalid initialization parameters for UniformLeafSubsampler.
2. Attempting to subsample with invalid sample sizes (0 or very small ratio).

## Notes

* The tests use fixed random seeds (np.random.seed(10) and np.random.seed(11)) to ensure reproducibility of the random subsampling process.
* The tests cover both the case of subsampling with a fixed number of leaves and with a ratio of the total leaves.
* The tests verify not only the structure of the resulting subsampled tree but also the correctness of branch lengths and node times in the custom tree test case.