plot_bintree_level_count.py

#!/usr/local/bin/python3

import sys
import numpy as np
import pandas as pd
import matplotlib as mpl
import matplotlib.pyplot as plt
import seaborn as sns
import warnings; warnings.filterwarnings(action='once')

csv_file_name = sys.argv[1]
print(csv_file_name)

large = 22; med = 16; small = 12
params = {'axes.titlesize': large,
          'legend.fontsize': med,
          'figure.figsize': (16, 10),
          'axes.labelsize': med,
          'axes.titlesize': med,
          'xtick.labelsize': med,
          'ytick.labelsize': med,
          'figure.titlesize': large}
plt.rcParams.update(params)
plt.style.use('seaborn-whitegrid')
sns.set_style("white")

# Import Data
df = pd.read_csv(csv_file_name)
print(df.to_string())

# Draw Plot
plt.figure(figsize=(16,10), dpi= 80)
plt.plot('level', 'count', data=df, color='tab:red')

# Decoration
plt.xlim(0, 32)
plt.ylim(0, 900)
xtick_location = [x for x in df.level.tolist()]
xtick_labels = [x for x in df.level.tolist()]
plt.xticks(ticks=xtick_location, labels=xtick_labels, rotation=0, fontsize=12, horizontalalignment='center', alpha=.7)
plt.yticks(fontsize=12, alpha=.7)
plt.title("Element count in a randomized binary search tree, by level", fontsize=22)
plt.xlabel('Levels')
plt.ylabel('Count')
plt.grid(axis='both', alpha=.3)

# Remove borders
plt.gca().spines["top"].set_alpha(0.0)    
plt.gca().spines["bottom"].set_alpha(0.3)
plt.gca().spines["right"].set_alpha(0.0)    
plt.gca().spines["left"].set_alpha(0.3)   
plt.show()