feat(plotting): extract plotting module with histogram and CDF

tests/test_plots.py

@@ -0,0 +1,134 @@
+"""Tests for the plotting module."""
+
+import pytest
+from pathlib import Path
+from unittest.mock import MagicMock, patch
+import matplotlib
+matplotlib.use("Agg")
+import matplotlib.pyplot as plt
+
+from disk_checker.plotting.plots import draw_histogram, draw_cdf, generate_plot
+import pandas as pd
+
+
+class TestDrawHistogram:
+    """Tests for draw_histogram function."""
+
+    @pytest.fixture
+    def sample_df(self):
+        """Create a sample DataFrame for testing."""
+        return pd.DataFrame({
+            "metric": ["read_clat", "read_clat", "write_clat"],
+            "latency_ns": [1000, 2000, 1500],
+            "count": [1, 2, 1],
+        })
+
+    def test_draws_histogram(self, sample_df, tmp_path):
+        """Test that histogram is drawn without errors."""
+        fig, ax = plt.subplots()
+        draw_histogram(ax, sample_df, ["read_clat"])
+        assert ax.get_title() == "Completion latency distribution"
+        plt.close(fig)
+
+    def test_multiple_metrics(self, sample_df, tmp_path):
+        """Test drawing multiple metrics."""
+        fig, ax = plt.subplots()
+        draw_histogram(ax, sample_df, ["read_clat", "write_clat"])
+        assert len(ax.collections) > 0
+        plt.close(fig)
+
+    def test_log_scale(self, sample_df, tmp_path):
+        """Test logarithmic scale."""
+        fig, ax = plt.subplots()
+        draw_histogram(ax, sample_df, ["read_clat"], log_x=True, log_y=True)
+        assert ax.get_xscale() == "log"
+        assert ax.get_yscale() == "log"
+        plt.close(fig)
+
+
+class TestDrawCdf:
+    """Tests for draw_cdf function."""
+
+    @pytest.fixture
+    def sample_df(self):
+        """Create a sample DataFrame for testing."""
+        return pd.DataFrame({
+            "metric": ["read_clat", "read_clat"],
+            "latency_ns": [1000, 2000],
+            "count": [1, 3],
+        })
+
+    def test_draws_cdf(self, sample_df, tmp_path):
+        """Test that CDF is drawn without errors."""
+        fig, ax = plt.subplots()
+        draw_cdf(ax, sample_df, ["read_clat"])
+        assert ax.get_title() == "Cumulative latency distribution"
+        assert ax.get_ylim() == (0, 100)
+        plt.close(fig)
+
+    def test_log_scale(self, sample_df, tmp_path):
+        """Test logarithmic X scale."""
+        fig, ax = plt.subplots()
+        draw_cdf(ax, sample_df, ["read_clat"], log_x=True)
+        assert ax.get_xscale() == "log"
+        plt.close(fig)
+
+
+class TestGeneratePlot:
+    """Tests for generate_plot function."""
+
+    @pytest.fixture
+    def sample_df(self):
+        """Create a sample DataFrame for testing."""
+        return pd.DataFrame({
+            "metric": ["read_clat", "read_clat"],
+            "latency_ns": [1000, 2000],
+            "count": [1, 3],
+        })
+
+    def test_generates_histogram(self, sample_df, tmp_path):
+        """Test generating histogram plot."""
+        output = tmp_path / "test.png"
+        result = generate_plot(
+            df=sample_df,
+            metrics=["read_clat"],
+            output_path=output,
+        )
+        assert result == output
+        assert output.exists()
+
+    def test_generates_cdf_only(self, sample_df, tmp_path):
+        """Test generating CDF-only plot."""
+        output = tmp_path / "test_cdf.png"
+        result = generate_plot(
+            df=sample_df,
+            metrics=["read_clat"],
+            output_path=output,
+            cdf_only=True,
+        )
+        assert result == output
+        assert output.exists()
+
+    def test_generates_histogram_with_cdf(self, sample_df, tmp_path):
+        """Test generating histogram with CDF below."""
+        output = tmp_path / "test_both.png"
+        result = generate_plot(
+            df=sample_df,
+            metrics=["read_clat"],
+            output_path=output,
+            show_cdf=True,
+        )
+        assert result == output
+        assert output.exists()
+
+    def test_custom_dpi(self, sample_df, tmp_path):
+        """Test custom DPI setting."""
+        output = tmp_path / "test_dpi.png"
+        result = generate_plot(
+            df=sample_df,
+            metrics=["read_clat"],
+            output_path=output,
+            dpi=300,
+        )
+        assert result == output
+        assert output.exists()