> ## Documentation Index > Fetch the complete documentation index at: https://demo.agenticlabs.com/llms.txt > Use this file to discover all available pages before exploring further. # small_parsimony_test.py ## High-level description This file contains unit tests for the `small_parsimony.py` module in Cassiopeia. The tests cover functions related to small parsimony inference on phylogenetic trees, including Fitch-Hartigan reconstruction, parsimony scoring, and the FitchCount algorithm. ## Code Structure The code defines a single test class `TestSmallParsimony` that inherits from `unittest.TestCase`. This class contains multiple test methods, each testing a specific function or aspect of the `small_parsimony` module. The test methods use various assertions provided by the `unittest` framework to check for expected outcomes. ## References This test file references the following symbols from the `cassiopeia.tools.small_parsimony` module: * `fitch_hartigan_bottom_up` * `fitch_hartigan_top_down` * `fitch_hartigan` * `score_small_parsimony` * `fitch_count` ## Symbols ### `TestSmallParsimony` #### Description This class contains unit tests for functions in the `cassiopeia.tools.small_parsimony` module. It sets up two test trees, a binary tree and a general tree, with associated character data, to be used in the test cases. #### Inputs None #### Outputs None #### Internal Logic The class defines several test methods, each testing a specific function or aspect of the `small_parsimony` module. Each test method sets up the necessary input data and calls the function being tested. Assertions are then used to verify that the function behaves as expected. ### `test_fitch_hartigan_bottom_up` #### Description Tests the `fitch_hartigan_bottom_up` function, which performs the bottom-up phase of the Fitch-Hartigan algorithm. #### Inputs Uses the `self.binary_tree` object as input. #### Outputs None #### Internal Logic * Checks for expected errors when invalid input is provided. * Runs the `fitch_hartigan_bottom_up` function on the binary tree. * Verifies that the correct ancestral state sets are assigned to each node. * Tests the function with different `add_key` parameters. ### `test_fitch_hartigan_top_down` #### Description Tests the `fitch_hartigan_top_down` function, which performs the top-down refinement step of the Fitch-Hartigan algorithm. #### Inputs Uses the `self.binary_tree` object as input. #### Outputs None #### Internal Logic * Runs the `fitch_hartigan_bottom_up` function to initialize ancestral state sets. * Runs the `fitch_hartigan_top_down` function on the binary tree. * Verifies that the correct character states are assigned to each node. * Tests the function with different `label_key` parameters. ### `test_fitch_hartigan` #### Description Tests the `fitch_hartigan` function, which combines the bottom-up and top-down steps of the Fitch-Hartigan algorithm. #### Inputs Uses the `self.binary_tree` object as input. #### Outputs None #### Internal Logic * Runs the `fitch_hartigan` function on the binary tree. * Verifies that the correct character states are assigned to each node. ### `test_score_parsimony` #### Description Tests the `score_small_parsimony` function, which calculates the parsimony score of a tree. #### Inputs Uses the `self.binary_tree` object as input. #### Outputs None #### Internal Logic * Checks for expected errors when invalid input is provided. * Runs the `score_small_parsimony` function with and without ancestral state inference. * Verifies that the calculated parsimony score is correct in both cases. ### `test_general_tree_fitch_bottom_up` #### Description Tests the `fitch_hartigan_bottom_up` function on a general (non-binary) tree. #### Inputs Uses the `self.general_tree` object as input. #### Outputs None #### Internal Logic * Runs the `fitch_hartigan_bottom_up` function on the general tree. * Verifies that the correct ancestral state sets are assigned to each node. ### `test_general_tree_fitch_hartigan` #### Description Tests the `fitch_hartigan` function on a general (non-binary) tree. #### Inputs Uses the `self.general_tree` object as input. #### Outputs None #### Internal Logic * Runs the `fitch_hartigan` function on the general tree. * Verifies that the correct character states are assigned to each node. ### `test_general_tree_parsimony` #### Description Tests the `score_small_parsimony` function on a general (non-binary) tree. #### Inputs Uses the `self.general_tree` object as input. #### Outputs None #### Internal Logic * Runs the `score_small_parsimony` function on the general tree. * Verifies that the calculated parsimony score is correct. ### `test_fitch_count_basic_binary` #### Description Tests the `fitch_count` function on a basic binary tree. #### Inputs Uses the `self.binary_tree` object as input. #### Outputs None #### Internal Logic * Runs the `fitch_count` function on the binary tree. * Verifies that the resulting count matrix has the correct dimensions and values. * Tests the function with and without pre-computed ancestral states. ### `test_fitch_count_basic_binary_custom_state_space` #### Description Tests the `fitch_count` function with a custom state space. #### Inputs Uses the `self.binary_tree` object as input. #### Outputs None #### Internal Logic * Runs the `fitch_count` function with a specified state space. * Verifies that the resulting count matrix has the correct dimensions and values. * Checks for expected errors when an invalid state space is provided. ### `test_fitch_count_basic_binary_internal_node` #### Description Tests the `fitch_count` function with a specified root node. #### Inputs Uses the `self.binary_tree` object as input. #### Outputs None #### Internal Logic * Runs the `fitch_count` function with a specified root node. * Verifies that the resulting count matrix has the correct dimensions and values. ### `test_fitch_count_general_tree` #### Description Tests the `fitch_count` function on a general (non-binary) tree. #### Inputs Uses the `self.general_tree` object as input. #### Outputs None #### Internal Logic * Runs the `fitch_count` function on the general tree. * Verifies that the resulting count matrix has the correct dimensions and values. ## Dependencies * `unittest` * `networkx` * `numpy` * `pandas` * `cassiopeia` ## Error Handling The test methods use assertions provided by the `unittest` framework to check for expected errors. For example, the `assertRaises` method is used to verify that a specific exception is raised when invalid input is provided to a function.