Not able to use plt.subplots() for my data

Question

I am using the Lombscargle function to output the power spectrum for a signal I pass as input, I am able to get the plots one after another but the task at hand is to plot these graphs using subplots in a way that there are 5 rows, 4 cols.

An example for signal would be:

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']

from scipy.signal import lombscargle 

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()
    ax.plot(period_freq,prog)

How do I plot these graphs in a matrix format?

Trying loop approach,

Answer 1

• See inline comments to add and flatten the subplots.
• This is an implementation of flattening the axes array from this answer of the duplicate.

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

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 = []
    
    # create the figure and subplots
    fig, axes = plt.subplots(5, 6, figsize=(20, 9), sharex=False, sharey=False)
    
    # flatten the array
    axes = axes.ravel()
    
    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)
        
        # plot
        axes[count].plot(period_freq, prog)
        
        # format the axes
        axes[count].set(title=value)
        # some plot have an exponential offset on the yaxis, this turns it off
        axes[count].ticklabel_format(useOffset=False)
        # some yaxis values are long floats, this formats them to 3 decimal places
        axes[count].yaxis.set_major_formatter(FormatStrFormatter('%.3f'))
        
    # format the figure
    fig.tight_layout()


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']
LSP_scipy(signal[:20])  # as per comment, only first 20