如何使用plt.subplots()绘制Lombscargle功率谱5行4列子图矩阵

我正在使用Lombscargle函数输出输入信号的功率谱，目前可以逐个生成绘图，当前需求是将这些图以5行4列的子图形式绘制为矩阵格式。

现有代码与信号示例 #

import numpy as np
import matplotlib.pyplot as plt
from scipy.signal import lombscargle 

signal = [ '254.24', '254.32', '254.4', '254.84', '254.24', '254.28', '254.84', '253.56', '253.76', '253.32', '253.88', '253.72', '253.92', '251.56', '253.04', '244.72', '243.84', '246.08', '245.84', '249.0', '250.08', '248.2', '253.12', '253.2', '253.48', '253.88', '253.12', '253.4', '253.4']

def LSP_scipy(signal):
    start_ang_freq = 2 * np.pi * (60/60)
    end_ang_freq = 2 * np.pi * (240/60)
    SAMPLES = 5000
    SAMPLE_SPACING = 1/15 

    t = np.linspace(0,len(signal)*SAMPLE_SPACING,len(signal))
    period_freq = np.linspace(start_ang_freq,end_ang_freq,SAMPLES)
    
    modified_signal_axis = []
    modified_time_axis = []
    for count,value in enumerate(signal):
        if value != 'None':
            modified_signal_axis.append(float(value))
            modified_time_axis.append(t[count])
        prog = lombscargle(modified_time_axis, modified_signal_axis, period_freq, normalize=False, precenter = True)
    fig, axes = plt.subplots()
    axes.plot(period_freq,prog)

现有输出效果 #

你需要提前创建5行4列的子图矩阵，修改绘图函数支持传入指定子图对象，再循环将每个功率谱绘制到对应位置即可，修改后完整代码如下：

import numpy as np
import matplotlib.pyplot as plt
from scipy.signal import lombscargle 

# 配置通用常量
START_ANG_FREQ = 2 * np.pi * (60/60)
END_ANG_FREQ = 2 * np.pi * (240/60)
SAMPLES = 5000
SAMPLE_SPACING = 1/15 
period_freq = np.linspace(START_ANG_FREQ, END_ANG_FREQ, SAMPLES)

def LSP_scipy(signal, ax):
    t = np.linspace(0, len(signal)*SAMPLE_SPACING, len(signal))
    
    modified_signal_axis = []
    modified_time_axis = []
    for count,value in enumerate(signal):
        if value != 'None':
            modified_signal_axis.append(float(value))
            modified_time_axis.append(t[count])
    # 过滤完无效值后再计算功率谱，避免重复计算
    prog = lombscargle(modified_time_axis, modified_signal_axis, period_freq, normalize=False, precenter = True)
    # 直接在传入的子图对象上绘图
    ax.plot(period_freq, prog)
    # 可自行添加标题、坐标轴标签等美化逻辑
    ax.tick_params(axis='both', labelsize=8)

# 提前创建5行4列的子图矩阵，可调整figsize控制整体画布大小
fig, axes = plt.subplots(nrows=5, ncols=4, figsize=(16, 18))
# 将你所有待绘制的信号存入signal_list，示例用重复的测试信号，替换为你的实际数据即可
signal_list = [signal for _ in range(20)]

for idx, sig in enumerate(signal_list):
    # 计算当前功率谱对应子图的行、列索引
    row, col = divmod(idx, 4)
    current_ax = axes[row][col]
    LSP_scipy(sig, current_ax)

# 调整子图间距避免重叠
plt.tight_layout()
plt.show()

如果待绘制的信号数量不足20，可在循环结束后隐藏多余的空白子图：

# 示例：只有17个信号时，隐藏后3个空白子图
for idx in range(17, 20):
    row, col = divmod(idx, 4)
    axes[row][col].axis('off')

内容的提问来源于stack exchange，提问作者AMANDEEP KAUR