Added tests for api and load_audio

tests/test_api.py

@@ -10,11 +10,13 @@ import torch
 from torch import nn
 
 from batdetect2 import api
+import io 
 
 PKG_DIR = os.path.dirname(os.path.dirname(os.path.abspath(__file__)))
 TEST_DATA_DIR = os.path.join(PKG_DIR, "example_data", "audio")
 TEST_DATA = glob(os.path.join(TEST_DATA_DIR, "*.wav"))
 
+DATA_DIR = os.path.join(os.path.dirname(__file__), "data")
 
 def test_load_model_with_default_params():
     """Test loading model with default parameters."""
@@ -280,3 +282,28 @@ def test_process_file_with_empty_predictions_does_not_fail(
 
     assert results is not None
     assert len(results["pred_dict"]["annotation"]) == 0
+
+def test_process_file_file_id_defaults_to_basename():
+    """Test that no detections are made above the nyquist frequency."""
+    # Recording donated by @@kdarras
+    basename = "20230322_172000_selec2.wav"
+    path = os.path.join(DATA_DIR, basename)
+
+    output = api.process_file(path)
+    predictions = output["pred_dict"]
+    id = predictions["id"]
+    assert id == basename
+
+def test_bytesio_file_id_defaults_to_md5():
+    """Test that no detections are made above the nyquist frequency."""
+    # Recording donated by @@kdarras
+    basename = "20230322_172000_selec2.wav"
+    path = os.path.join(DATA_DIR, basename)
+
+    with open(path, "rb") as f:
+        data = io.BytesIO(f.read())
+
+    output = api.process_file(data)
+    predictions = output["pred_dict"]
+    id = predictions["id"]
+    assert id == "7ade9ebf1a9fe5477ff3a2dc57001929"

tests/test_audio_utils.py

@@ -7,7 +7,9 @@ from hypothesis import strategies as st
 from batdetect2.detector import parameters
 from batdetect2.utils import audio_utils, detector_utils
 import io
-import requests
+import os
+
+DATA_DIR = os.path.join(os.path.dirname(__file__), "data")
 
 @given(duration=st.floats(min_value=0.1, max_value=2))
 def test_can_compute_correct_spectrogram_width(duration: float):
@@ -144,3 +146,48 @@ def test_get_samplerate_using_bytesio():
 
     expected_sample_rate = 500000
     assert expected_sample_rate == sample_rate
+
+    
+
+def test_load_audio_using_bytes():
+    filename = "example_data/audio/20170701_213954-MYOMYS-LR_0_0.5.wav"
+    
+    with open(filename, "rb") as f:
+        audio_bytes = io.BytesIO(f.read())
+    
+    sample_rate, audio_data = audio_utils.load_audio(audio_bytes, time_exp_fact=1, target_samp_rate=parameters.TARGET_SAMPLERATE_HZ)
+
+    expected_sample_rate, expected_audio_data = audio_utils.load_audio(filename, time_exp_fact=1, target_samp_rate=parameters.TARGET_SAMPLERATE_HZ)
+
+    assert expected_sample_rate == sample_rate
+
+    assert np.array_equal(audio_data, expected_audio_data)
+
+
+
+def test_get_samplerate_using_bytesio_2():
+    basename = "20230322_172000_selec2.wav"
+    path = os.path.join(DATA_DIR, basename)
+
+    with open(path, "rb") as f:
+        audio_bytes = io.BytesIO(f.read())
+    
+    sample_rate = audio_utils.get_samplerate(audio_bytes)
+
+    expected_sample_rate = 192_000
+    assert expected_sample_rate == sample_rate
+
+def test_load_audio_using_bytes_2():
+    basename = "20230322_172000_selec2.wav"
+    path = os.path.join(DATA_DIR, basename)
+
+    with open(path, "rb") as f:
+        data = io.BytesIO(f.read())
+    
+    sample_rate, audio_data = audio_utils.load_audio(data, time_exp_fact=1, target_samp_rate=parameters.TARGET_SAMPLERATE_HZ)
+
+    expected_sample_rate, expected_audio_data = audio_utils.load_audio(path, time_exp_fact=1, target_samp_rate=parameters.TARGET_SAMPLERATE_HZ)
+
+    assert expected_sample_rate == sample_rate
+
+    assert np.array_equal(audio_data, expected_audio_data)