DLKcat/DeeplearningApproach/Code/analysis/SuppleFig1b_ECdistribution.py

#!/usr/bin/python
# coding: utf-8

# Author: LE YUAN

import json
import pandas as pd
import seaborn as sns
import matplotlib.pyplot as plt
from matplotlib import rc
# https://zhuanlan.zhihu.com/p/72534851
# https://pythontic.com/visualization/charts/piechart


with open('../../Data/database/Kcat_combination_0918.json', 'r') as infile :
    entries = json.load(infile)

# print(len(entries))  # 17010

ECNumbers = [entry['ECNumber'] for entry in entries]
# print(len(ECNumbers))
# print(ECNumbers[:3])

cluster_1 = [ECNumber for ECNumber in ECNumbers if ECNumber[0] == '1']
cluster_2 = [ECNumber for ECNumber in ECNumbers if ECNumber[0] == '2']
cluster_3 = [ECNumber for ECNumber in ECNumbers if ECNumber[0] == '3']
cluster_4 = [ECNumber for ECNumber in ECNumbers if ECNumber[0] == '4']
cluster_5 = [ECNumber for ECNumber in ECNumbers if ECNumber[0] == '5']
cluster_6 = [ECNumber for ECNumber in ECNumbers if ECNumber[0] == '6']
cluster_7 = [ECNumber for ECNumber in ECNumbers if ECNumber[0] == '7']

print(len(cluster_1))
print(cluster_1[:3])
total_amount = len(cluster_1) + len(cluster_2) + len(cluster_3) + len(cluster_4) + len(cluster_5) + len(cluster_6) + len(cluster_7)
print('The total amount of senven clusters is:', total_amount)

EC_Percentage= dict()
EC_Percentage['EC=1.*'] = len(cluster_1)/total_amount
EC_Percentage['EC=2.*'] = len(cluster_2)/total_amount
EC_Percentage['EC=3.*'] = len(cluster_3)/total_amount
EC_Percentage['EC=4.*'] = len(cluster_4)/total_amount
EC_Percentage['EC=5.*'] = len(cluster_5)/total_amount
EC_Percentage['EC=6.*'] = len(cluster_6)/total_amount
EC_Percentage['EC=7.*'] = len(cluster_7)/total_amount

# print(EC_Percentage)

data = pd.Series(EC_Percentage)

# myfont=FontProperties(size=14)
# sns.set(font=myfont.get_name())

plt.rcParams['figure.figsize'] = (2.4, 3.0)

# To solve the 'Helvetica' font cannot be used in PDF file
# https://stackoverflow.com/questions/59845568/the-pdf-backend-does-not-currently-support-the-selected-font
rc('font',**{'family':'serif','serif':['Helvetica']})
plt.rcParams['pdf.fonttype'] = 42

# plt.axes([0.12,0.12,0.83,0.83])

lbs= data.index
# explodes=[0.1 if i=='EC=1.*' else 0 for i in lbs]
explodes=[0.1, 0.0, 0.0, 0.0, 0.2, 0.4, 0.8]
# plt.pie(data, explode=explodes,labels=lbs, autopct="%1.1f%%",
#                                 colors=sns.color_palette("muted"),startangle = 90,pctdistance = 0.6,
#           textprops={'fontsize':14,'color':'black'})

plt.pie(data, explode=explodes,labels=lbs, autopct="%1.2f%%",
                                colors=sns.color_palette("muted"),startangle = 90,pctdistance = 0.6,
          textprops={'fontsize':6,'color':'black'})


plt.axis('equal')

plt.savefig("../../Results/figures/SuppleFig1b.pdf", dpi=400)