143 lines
4.0 KiB
Python
143 lines
4.0 KiB
Python
"""Gamma 曲线绘制。
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Step 2 重构：从 pqAutomationApp.PQAutomationApp.plot_gamma 原样搬迁。
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"""
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import numpy as np
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def plot_gamma(self, L_bar, results_with_gamma_list, target_gamma, test_type):
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"""绘制Gamma曲线 + 数据表格（包含实测亮度）"""
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# ========== 1. 清空并重置左侧曲线 ==========
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self.gamma_ax.clear()
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self.gamma_ax.set_xlim(0, 105)
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self.gamma_ax.set_ylim(0, 1.1)
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self.gamma_ax.set_xlabel("灰阶 (%)", fontsize=10)
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self.gamma_ax.set_ylabel("L_bar", fontsize=10)
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self.gamma_ax.grid(True, linestyle="--", alpha=0.3)
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self.gamma_ax.tick_params(labelsize=9)
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# 生成横坐标（灰阶百分比）
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x_values = np.linspace(0, 100, len(L_bar))
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# 反转 L_bar（确保从左到右是 0% → 100%）
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if len(L_bar) > 1 and L_bar[0] > L_bar[-1]:
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L_bar = L_bar[::-1]
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results_with_gamma_list = results_with_gamma_list[::-1]
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# 计算平均Gamma
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gamma_values = []
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for item in results_with_gamma_list:
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if isinstance(item, (list, tuple)) and len(item) >= 4:
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gamma = item[3]
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if 0.5 < gamma < 5.0:
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gamma_values.append(gamma)
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avg_gamma = np.mean(gamma_values) if gamma_values else target_gamma
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# 绘制实测曲线
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self.gamma_ax.plot(
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x_values,
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L_bar,
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"b-o",
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label=f"实测 (平均γ={avg_gamma:.2f})",
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linewidth=2,
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markersize=4,
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zorder=5,
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)
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# 绘制理想曲线（使用 target_gamma）
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ideal_L_bar = [(x / 100) ** target_gamma for x in x_values]
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self.gamma_ax.plot(
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x_values,
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ideal_L_bar,
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"r--",
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label=f"理想 (γ={target_gamma})",
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linewidth=2,
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alpha=0.7,
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zorder=3,
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)
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# 图例
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self.gamma_ax.legend(fontsize=9, loc="upper left", framealpha=0.95)
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# ========== 2. 清空并绘制右侧表格 ==========
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self.gamma_table_ax.clear()
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self.gamma_table_ax.axis("off")
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# 构建表格数据（4列）
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table_data = [["灰阶", "实测亮度\n(cd/m²)", "L_bar", "Gamma"]]
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for i, (x_val, L_val, result) in enumerate(
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zip(x_values, L_bar, results_with_gamma_list)
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):
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# 提取实测亮度
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if isinstance(result, (list, tuple)) and len(result) >= 3:
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measured_lv = result[2]
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measured_lv_str = f"{measured_lv:.2f}"
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else:
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measured_lv_str = "--"
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# 提取 Gamma
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if isinstance(result, (list, tuple)) and len(result) >= 4:
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gamma = result[3]
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if gamma < 0.5 or gamma > 5.0:
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gamma_str = "--"
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else:
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gamma_str = f"{gamma:.2f}"
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else:
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gamma_str = "--"
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table_data.append(
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[
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f"{x_val:.0f}%",
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measured_lv_str,
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f"{L_val:.3f}",
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gamma_str,
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]
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)
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# 绘制表格（4列）
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table = self.gamma_table_ax.table(
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cellText=table_data,
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cellLoc="center",
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loc="center",
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colWidths=[0.18, 0.28, 0.27, 0.27],
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)
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# 美化表格
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table.auto_set_font_size(False)
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table.set_fontsize(7.5)
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table.scale(1, 1.5)
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# 表头样式
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for i in range(4):
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cell = table[(0, i)]
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cell.set_facecolor("#4472C4")
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cell.set_text_props(weight="bold", color="white")
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# 数据行交替颜色
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for i in range(1, len(table_data)):
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for j in range(4):
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cell = table[(i, j)]
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if i % 2 == 0:
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cell.set_facecolor("#E7E6E6")
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else:
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cell.set_facecolor("#FFFFFF")
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# ========== 3. 总标题 ==========
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test_type_name = self.get_test_type_name(test_type)
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self.gamma_fig.suptitle(
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f"{test_type_name} - Gamma曲线",
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fontsize=12,
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y=0.98,
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fontweight="bold",
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)
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# ========== 4. 绘制到画布 ==========
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self.gamma_canvas.draw()
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self.chart_notebook.select(self.gamma_chart_frame)
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self.log_gui.log("Gamma曲线 + 数据表格绘制完成", level="success")
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