Parsing the Seidel Coefficient text results to display the Seidel aberration coefficients in wave

ZOS-API: Display Seidel Aberration Coefficients in Wave

# Imports
import numpy as np
import matplotlib.pyplot as plt 

# Initializations
legend = []

spha = []
coma = []
asti = []
fcur = []
dist = []
cla = []
ctr = []

ii = 0

# Open Seidel Coefficient text file
with open("E:\\SeidelCoeffs.txt") as seidel_file:
    # Read lines until "wave" block
    for line in seidel_file:
        if "in Waves" in line:
            break
            
    # Skip header
    seidel_file.readline()
    seidel_file.readline()
    
    # Remove unnecessary space characters
    line = seidel_file.readline().replace(" ", "")
    
    # Loop over the "wave" block
    while line != "\n":
        split_line = line.split("\t")
        
        legend.append(split_line[0])
        
        spha.append(float(split_line[1]))
        coma.append(float(split_line[2]))
        asti.append(float(split_line[3]))
        fcur.append(float(split_line[4]))
        dist.append(float(split_line[5]))
        cla.append(float(split_line[6]))
        ctr.append(float(split_line[7]))
        
        line = seidel_file.readline().replace(" ", "")
        ii += 1
        
# Display
width = 0.4

x_axis = 7*width*np.arange(len(legend))

plt.figure(figsize=(12,8), dpi= 100, facecolor='w', edgecolor='k')

plt.bar(x_axis, spha, width, label = 'SPHA')
plt.bar(x_axis+width, coma, width, label = 'COMA')
plt.bar(x_axis+width*2, asti, width, label = 'ASTI')
plt.bar(x_axis+width*3, fcur, width, label = 'FCUR')
plt.bar(x_axis+width*4, dist, width, label = 'DIST')
plt.bar(x_axis+width*5, cla, width, label = 'CLA')
plt.bar(x_axis+width*6, ctr, width, label = 'CTR')

for point in x_axis:
    plt.axvline(point-width/2, color='lightgray')
plt.axvline(x_axis[-1]+7*width-width/2, color='lightgray')
plt.axhline(0, color='k')

plt.title("Seidel Aberration Coefficients in Waves")
plt.xticks(x_axis+3*width, legend)
plt.legend(loc='upper center', bbox_to_anchor=(0.5, -0.1), 
           fancybox=True, shadow=True, ncol=7)
plt.show()