draw_bar.py

# import libraries
import matplotlib
matplotlib.use('Agg')
import pandas as pd
import matplotlib.pyplot as plt
import argparse
from collections import defaultdict
#%matplotlib inline

# set font
plt.rcParams['font.family'] = 'sans-serif'
plt.rcParams['font.sans-serif'] = 'Helvetica'

# set the style of the axes and the text color
plt.rcParams['axes.edgecolor']='#333F4B'
plt.rcParams['axes.linewidth']=0.8
plt.rcParams['xtick.color']='#333F4B'
plt.rcParams['ytick.color']='#333F4B'
plt.rcParams['text.color']='#333F4B'




parser = argparse.ArgumentParser(description='Draw Bar')
parser.add_argument('--tsv', default='input.tsv', help='input file separted by \'\\t\' ')
parser.add_argument('--fig', default='out.png', help='the output figure')
parser.add_argument('--title', default='Concept Count in All Papers', help='the title of the graph')
parser.add_argument('--colored_concepts', default=None, nargs='+',
										help='An interleaved list of filenames containing concept tags (e.g. first.txt red second.txt purple)')

args = parser.parse_args()

concept_colors = defaultdict(lambda: '#007ACC')
if args.colored_concepts:
	for i in range(0, len(args.colored_concepts), 2):
		print(f"opening {args.colored_concepts[i]} as {args.colored_concepts[i+1]}")
		with open(args.colored_concepts[i], 'r') as f:
			for line in f:
				line = line.strip()
				concept_colors[line] = args.colored_concepts[i+1]
				print(f'concept_colors[{line}] = {args.colored_concepts[i+1]}')


tsv_file = args.tsv
fig_file = args.fig

fin = open(tsv_file,"r")
cpt_list = []
val_list = []
for line in fin:
	line = line.strip()
	cpt, val = line.split("\t")
	val_list.append(int(val))
	cpt_list.append(cpt)  
fin.close()

percentages = pd.Series(val_list, 
                        index=cpt_list)

df = pd.DataFrame({'percentage' : percentages})
df = df.sort_values(by='percentage')

color_list = [concept_colors[x] for x in df.index]

# we first need a numeric placeholder for the y axis
my_range=list(range(1,len(df.index)+1))

fig, ax = plt.subplots(figsize=(10,25))

# create lines and dots for each bar
plt.hlines(y=my_range, xmin=0, xmax=df['percentage'], colors=color_list, alpha=0.5, linewidth=5)
# plt.plot(df['percentage'], my_range, "o", markersize=5, colors=color_list, alpha=0.6)

# set labels
ax.set_xlabel(args.title, fontsize=15, fontweight='black', color = '#333F4B')
ax.xaxis.set_label_position('top')
ax.xaxis.tick_top() 
#ax.set_ylabel('')

# set axis
ax.tick_params(axis='both', which='major', labelsize=12)
plt.yticks(my_range, df.index)

# add an horizonal label for the y axis 
#fig.text(-0.23, 0.86, 'Concept Coverage (Fulltext)', fontsize=15, fontweight='black', color = '#333F4B')

# change the style of the axis spines
ax.spines['bottom'].set_color('none')
ax.spines['right'].set_color('none')
ax.spines['left'].set_smart_bounds(True)
ax.spines['top'].set_smart_bounds(True)

'''
# set the spines position
ax.spines['bottom'].set_position(('axes', -0.04))
ax.spines['left'].set_position(('axes', 0.015))
'''
plt.savefig(fig_file, dpi=300, bbox_inches='tight')