Add data_visualization/tests/test_core.py

data_visualization/tests/test_core.py

@@ -0,0 +1,51 @@
+import pytest
+import numpy as np
+import matplotlib.figure as mpl_figure
+
+from src.data_visualization import core
+
+
+def test_plot_spectrum_returns_figure():
+    # Nominal case with a small set of frequencies
+    frequency_data = [20.0, 100.0, 1000.0, 5000.0, 15000.0]
+    fig = core.plot_spectrum(frequency_data)
+    assert isinstance(fig, mpl_figure.Figure)
+
+
+def test_plot_spectrum_handles_empty_data():
+    # Should not crash on empty input, should still return a Figure
+    fig = core.plot_spectrum([])
+    assert isinstance(fig, mpl_figure.Figure)
+
+
+def test_plot_spectrum_with_large_data():
+    # Large dataset of synthetic frequency amplitudes
+    frequency_data = np.linspace(0, 22050, num=2048).tolist()
+    fig = core.plot_spectrum(frequency_data)
+    assert isinstance(fig, mpl_figure.Figure)
+
+
+def test_plot_spectrum_invalid_input_type():
+    # Edge case: wrong input type should raise a TypeError or ValueError
+    with pytest.raises((TypeError, ValueError)):
+        core.plot_spectrum('not_a_list')
+
+
+def test_plot_spectrum_visual_properties(monkeypatch):
+    # Patch pyplot to check function calls without actually rendering
+    call_log = {}
+
+    def fake_plot(x, y, **kwargs):
+        call_log['called'] = True
+        call_log['x_len'] = len(x)
+        call_log['y_len'] = len(y)
+
+    monkeypatch.setattr(core.plt, 'plot', fake_plot)
+
+    freq_data = [10.0, 50.0, 100.0]
+    fig = core.plot_spectrum(freq_data)
+
+    assert isinstance(fig, mpl_figure.Figure)
+    assert call_log.get('called', False)
+    assert call_log['x_len'] == len(freq_data)
+    assert call_log['y_len'] == len(freq_data)