Merge pull request #212 from Clinical-Genomics/fix_return_type

Fix get_intervals_completeness return type

CHANGELOG.md

@@ -4,6 +4,8 @@
 - Upgraded Pydantic and Fastapi libraries and their dependencies
 - Use app lifespan instead of deprecated startup `on_event'.
 - Modified code to support upgraded libraries
+- Rename a test file from `test_d4.py` to `test_handle_d4.py` and add 2 new tests to it
+- Fix return type of `get_intervals_completeness` function
 
 ## [1.2]
 ### Added

src/chanjo2/meta/handle_d4.py

@@ -1,5 +1,4 @@
 import logging
-from decimal import Decimal
 from statistics import mean
 from typing import List, Optional, Tuple, Union, Dict
 
@@ -76,7 +75,7 @@ def get_intervals_completeness(
     d4_file: D4File,
     intervals: List[Tuple[str, int, int]],
     completeness_thresholds: Optional[List[int]],
-) -> Optional[List[Tuple[int, Decimal]]]:
+) -> Optional[Dict[int, float]]:
     """Compute coverage completeness over threshold values for a list of intervals."""
 
     if not completeness_thresholds:

tests/src/chanjo2/meta/test_handle_d4.py

@@ -0,0 +1,62 @@
+from chanjo2.constants import DEFAULT_COMPLETENESS_LEVELS
+from chanjo2.meta.handle_d4 import predict_sex
+from chanjo2.models.pydantic_models import Sex
+from chanjo2.meta.handle_d4 import get_intervals_completeness, get_d4_file
+from pyd4 import D4File
+
+
+def test_predict_sex_male():
+    """Test the function that computes sex from coverage data from coverage file of a male sample."""
+    # GIVEN a coverage of chromosome Y which is roughly half of chromosome X
+    # THEN the predicted sex should be Male
+    assert predict_sex(x_cov=12.568, y_cov=6.605) == Sex.MALE
+
+
+def test_predict_sex_female():
+    """Test the function that computes sex from coverage data from coverage file of a female sample."""
+    # GIVEN a coverage of chromosome Y almost null
+    # THEN the predicted sex should be female
+    assert predict_sex(x_cov=22.81, y_cov=0.007) == Sex.FEMALE
+
+
+def test_predict_sex_unknown():
+    """Test the function that computes sex from coverage when it is not possible to establish the sex."""
+    # GIVEN a coverage of chromosome X equal to 0
+    # THEN the predicted sex should be unknown
+    assert predict_sex(x_cov=0, y_cov=6.605) == Sex.UNKNOWN
+
+
+def test_get_intervals_completeness_no_thresholds(real_coverage_path, bed_interval):
+    """Test the get_intervals_completeness function when no coverage thresholds are specified."""
+    # GIVEN a real d4 file
+    d4_file: D4File = get_d4_file(real_coverage_path)
+
+    # WHEN the get_intervals_completeness is invoked without completeness_thresholds values
+    completeness_stats: Optional[dict] = get_intervals_completeness(
+        d4_file=d4_file, intervals=[bed_interval], completeness_thresholds=None
+    )
+
+    # THEN it should return None
+    assert completeness_stats is None
+
+
+def test_get_intervals_completeness(real_coverage_path, bed_interval):
+    """Test the function that returns coverage completeness over a d4 file for a list of intervals and a list of coverage thresholds."""
+
+    # GIVEN a real d4 file
+    d4_file: D4File = get_d4_file(real_coverage_path)
+
+    # WHEN the get_intervals_completeness is invoked with all expected parameters
+    completeness_stats: Dict[int, Decimal] = get_intervals_completeness(
+        d4_file=d4_file,
+        intervals=[bed_interval],
+        completeness_thresholds=DEFAULT_COMPLETENESS_LEVELS,
+    )
+    # THEN it should return a dictionary
+    assert isinstance(completeness_stats, dict)
+
+    # CONTAINING stats for all the provided coverage thresholds
+    for level in DEFAULT_COMPLETENESS_LEVELS:
+        assert completeness_stats[level] == 0 or isinstance(
+            completeness_stats[level], float
+        )