"""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()