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重构提取plot函数

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xinzhu.yin
2026-04-20 10:00:44 +08:00
parent 22c46632ac
commit 77c92ffc05
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app/plots/plot_cct.py Normal file
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"""CCT / 色度一致性绘制。
Step 2 重构：从 pqAutomationApp.PQAutomationApp.plot_cct 原样搬迁。
"""
import numpy as np
def plot_cct(app, test_type):
"""绘制 x 和 y 坐标分离图 - 每个点标注纵坐标值"""
self = app
self.cct_fig.clear()
gray_data = self.results.get_intermediate_data("shared", "gray")
if not gray_data:
gray_data = self.results.get_intermediate_data("cct", "gray")
if not gray_data or len(gray_data) < 2:
self.log_gui.log("⚠️ 无 xy 数据可用")
ax = self.cct_fig.add_subplot(111)
ax.text(
0.5,
0.5,
"无可用数据",
ha="center",
va="center",
fontsize=14,
color="red",
)
ax.axis("off")
self.cct_canvas.draw()
return
x_measured = [data[0] for data in gray_data]
y_measured = [data[1] for data in gray_data]
# 反转数据顺序（从暗到亮）
x_measured = x_measured[::-1]
y_measured = y_measured[::-1]
# 去掉第一个点
x_measured = x_measured[1:]
y_measured = y_measured[1:]
# 重新生成灰阶坐标
total_points = len(gray_data)
grayscale = np.linspace(100 / total_points, 100, len(x_measured))
self.log_gui.log(f"✓ 已移除第一个数据点，当前数据点数: {len(x_measured)}")
self.log_gui.log(f" x范围: {min(x_measured):.6f} - {max(x_measured):.6f}")
self.log_gui.log(f" y范围: {min(y_measured):.6f} - {max(y_measured):.6f}")
# ========== 根据测试类型读取对应参数 ==========
if test_type == "sdr_movie":
try:
x_ideal = float(self.sdr_cct_x_ideal_var.get())
x_tolerance = float(self.sdr_cct_x_tolerance_var.get())
y_ideal = float(self.sdr_cct_y_ideal_var.get())
y_tolerance = float(self.sdr_cct_y_tolerance_var.get())
self.log_gui.log("✓ 使用 SDR 色度参数")
except:
x_ideal = 0.3127
x_tolerance = 0.003
y_ideal = 0.3290
y_tolerance = 0.003
self.log_gui.log("⚠️ SDR 参数读取失败，使用默认值")
elif test_type == "hdr_movie":
try:
x_ideal = float(self.hdr_cct_x_ideal_var.get())
x_tolerance = float(self.hdr_cct_x_tolerance_var.get())
y_ideal = float(self.hdr_cct_y_ideal_var.get())
y_tolerance = float(self.hdr_cct_y_tolerance_var.get())
self.log_gui.log("✓ 使用 HDR 色度参数")
except:
x_ideal = 0.3127
x_tolerance = 0.003
y_ideal = 0.3290
y_tolerance = 0.003
self.log_gui.log("⚠️ HDR 参数读取失败，使用默认值")
else: # screen_module
try:
x_ideal = float(self.cct_x_ideal_var.get())
x_tolerance = float(self.cct_x_tolerance_var.get())
y_ideal = float(self.cct_y_ideal_var.get())
y_tolerance = float(self.cct_y_tolerance_var.get())
self.log_gui.log("✓ 使用屏模组色度参数")
except:
x_ideal = 0.306
x_tolerance = 0.003
y_ideal = 0.318
y_tolerance = 0.003
self.log_gui.log("⚠️ 屏模组参数读取失败，使用默认值")
x_low = x_ideal - x_tolerance
x_high = x_ideal + x_tolerance
y_low = y_ideal - y_tolerance
y_high = y_ideal + y_tolerance
self.log_gui.log(f"✓ 用户设置参数:")
self.log_gui.log(f" x-ideal={x_ideal:.4f}, tolerance={x_tolerance:.4f}")
self.log_gui.log(f" x范围: [{x_low:.4f}, {x_high:.4f}]")
self.log_gui.log(f" y-ideal={y_ideal:.4f}, tolerance={y_tolerance:.4f}")
self.log_gui.log(f" y范围: [{y_low:.4f}, {y_high:.4f}]")
# 为所有测试类型创建子图
ax1 = self.cct_fig.add_subplot(211)
ax2 = self.cct_fig.add_subplot(212)
# ========== 上图：x coordinates ==========
ax1.plot(
grayscale,
x_measured,
"b-o",
label="屏本体",
linewidth=2,
markersize=4,
zorder=5,
)
# 为每个点添加数值标注（x 坐标）
for i, (gs, x_val) in enumerate(zip(grayscale, x_measured)):
ax1.annotate(
f"{x_val:.5f}",
xy=(gs, x_val),
xytext=(0, 8),
textcoords="offset points",
ha="center",
va="bottom",
fontsize=7,
color="blue",
bbox=dict(
boxstyle="round,pad=0.2",
facecolor="white",
edgecolor="blue",
alpha=0.8,
linewidth=0.5,
),
)
# 绘制完整的参考线
full_grayscale = np.linspace(0, 100, 100)
ax1.axhline(
y=x_ideal,
color="green",
linestyle="--",
linewidth=1.5,
label=f"x-ideal ({x_ideal:.4f})",
zorder=3,
)
ax1.axhline(
y=x_low,
color="red",
linestyle=":",
linewidth=1,
alpha=0.7,
label=f"x-low ({x_low:.4f})",
zorder=2,
)
ax1.axhline(
y=x_high,
color="red",
linestyle=":",
linewidth=1,
alpha=0.7,
label=f"x-high ({x_high:.4f})",
zorder=2,
)
ax1.fill_between(
full_grayscale, x_low, x_high, alpha=0.15, color="blue", zorder=1
)
ax1.set_xlabel("灰阶 (%)", fontsize=9)
ax1.set_ylabel("CIE x", fontsize=9)
ax1.grid(True, linestyle="--", alpha=0.3)
ax1.tick_params(labelsize=8)
ax1.set_xlim(0, 105)
# 纵坐标范围由用户参数控制
x_min_data = min(x_measured)
x_max_data = max(x_measured)
data_range_x = x_max_data - x_min_data
self.log_gui.log(f" x数据波动: {data_range_x:.6f}")
range_span = x_tolerance * 2
margin_ratio = 0.20
extra_margin = range_span * margin_ratio
final_y_min = min(x_min_data, x_low) - extra_margin
final_y_max = max(x_max_data, x_high) + extra_margin
if x_min_data >= x_low and x_max_data <= x_high:
self.log_gui.log(f" x数据在tolerance范围内，使用tolerance范围显示")
final_y_min = x_low - extra_margin
final_y_max = x_high + extra_margin
else:
self.log_gui.log(f" x数据超出tolerance范围，扩展显示范围")
ax1.set_ylim(final_y_min, final_y_max)
self.log_gui.log(
f" x轴显示范围: {final_y_min:.6f} - {final_y_max:.6f} (跨度: {final_y_max - final_y_min:.6f})"
)
# ========== 下图：y coordinates ==========
ax2.plot(
grayscale,
y_measured,
"r-o",
label="屏本体",
linewidth=2,
markersize=4,
zorder=5,
)
# 为每个点添加数值标注（y 坐标）
for i, (gs, y_val) in enumerate(zip(grayscale, y_measured)):
ax2.annotate(
f"{y_val:.5f}",
xy=(gs, y_val),
xytext=(0, 8),
textcoords="offset points",
ha="center",
va="bottom",
fontsize=7,
color="red",
bbox=dict(
boxstyle="round,pad=0.2",
facecolor="white",
edgecolor="red",
alpha=0.8,
linewidth=0.5,
),
)
ax2.axhline(
y=y_ideal,
color="green",
linestyle="--",
linewidth=1.5,
label=f"y-ideal ({y_ideal:.4f})",
zorder=3,
)
ax2.axhline(
y=y_low,
color="orange",
linestyle=":",
linewidth=1,
alpha=0.7,
label=f"y-low ({y_low:.4f})",
zorder=2,
)
ax2.axhline(
y=y_high,
color="orange",
linestyle=":",
linewidth=1,
alpha=0.7,
label=f"y-high ({y_high:.4f})",
zorder=2,
)
ax2.fill_between(
full_grayscale, y_low, y_high, alpha=0.15, color="orange", zorder=1
)
ax2.set_xlabel("灰阶 (%)", fontsize=9)
ax2.set_ylabel("CIE y", fontsize=9)
ax2.grid(True, linestyle="--", alpha=0.3)
ax2.tick_params(labelsize=8)
ax2.set_xlim(0, 105)
# 纵坐标范围由用户参数控制
y_min_data = min(y_measured)
y_max_data = max(y_measured)
data_range_y = y_max_data - y_min_data
self.log_gui.log(f" y数据波动: {data_range_y:.6f}")
range_span = y_tolerance * 2
extra_margin = range_span * margin_ratio
final_y_min = min(y_min_data, y_low) - extra_margin
final_y_max = max(y_max_data, y_high) + extra_margin
if y_min_data >= y_low and y_max_data <= y_high:
self.log_gui.log(f" y数据在tolerance范围内，使用tolerance范围显示")
final_y_min = y_low - extra_margin
final_y_max = y_high + extra_margin
else:
self.log_gui.log(f" y数据超出tolerance范围，扩展显示范围")
ax2.set_ylim(final_y_min, final_y_max)
self.log_gui.log(
f" y轴显示范围: {final_y_min:.6f} - {final_y_max:.6f} (跨度: {final_y_max - final_y_min:.6f})"
)
# ========== 总标题 - 统一格式（去掉统计信息）==========
test_type_name = self.get_test_type_name(test_type)
self.cct_fig.suptitle(
f"{test_type_name} - 色度一致性测试",
fontsize=12,
y=0.98,
fontweight="bold",
)
self.cct_fig.subplots_adjust(
left=0.12,
right=0.82,
top=0.92,
bottom=0.08,
hspace=0.30,
)
ax1.legend(
fontsize=7, loc="center left", bbox_to_anchor=(1.05, 0.5), framealpha=1.0
)
ax2.legend(
fontsize=7, loc="center left", bbox_to_anchor=(1.05, 0.5), framealpha=1.0
)
self.cct_canvas.draw()
self.chart_notebook.select(2)
self.log_gui.log("✓ xy 色度坐标图绘制完成")