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ATLASxAnalyses/MetaCycPWanalysis/plot_edges_coverage.py
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plot_edges_coverage.py
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__author__ = 'anastasia'
__author__ = 'anastasia'
import pandas as pd
import matplotlib.pyplot as plt
import os
import numpy as np
coverage_file = 'output/networkEdgesCoverage.csv'
green = '#5a9957'
blue = '#1c74ac'
violet = '#efa6b4'
# creating the directory for plots
if not os.path.exists('plots'):
os.mkdir('plots')
def MetaCycVsATLASxAll():
df = pd.read_csv(
coverage_file)
df = df.drop_duplicates()
fig, ax = plt.subplots()
bar1 = ax.barh([0.02, 0.2],len(df), 0.1, color = violet)
bar2, _ = plotNumberOfReconstructedPerNTDT(df, ['MetaCyc_hp_coveredByNetwork', 'chemATLAS_hp_coveredByNetwork'], ax, [green, green])
labels = ['MetaCyc reactions', 'All ATLASx']
ax.set_xlabel('Number of pathways', fontsize=14)
ax.axes.yaxis.set_visible(False)
ax.text(-50, 0.2, labels[1], va='center', ha='center', fontsize=14, rotation = 90)
ax.text(-50, 0.02, labels[0], va='center', ha='center', fontsize=14, rotation = 90)
ax.text(len(df)+10, 0.1, 'Total: ' + str(len(df))+ ' pathways', ha='left', va='center', fontsize=14, rotation = 90)
ax.tick_params(axis='both', which='major', labelsize=14)
ax.set_xlim(0, 1250)
ax.set_ylim(-0.05, 0.27)
fig.legend((bar1, bar2), ('Pathway not\nexactly reconstructed', 'Pathway exactly\nreconstructed'), loc=[0.10, 0.47], fontsize=14)
plt.vlines(len(df), -0.03, 0.25, linestyles='solid')
fig.tight_layout()
fig.set_size_inches(4, 6)
plt.gca().invert_yaxis()
plt.savefig('plots/MetaCycVsATLASx.png', bbox = [6, 9])
def MetaCycVsATLASxBNICE():
df = pd.read_csv(
coverage_file)
df = df.drop_duplicates()
fig, ax = plt.subplots()
bar1 = ax.barh([0.02, 0.2],len(df), 0.1, color = violet)
bar2, _ = plotNumberOfReconstructedPerNTDT(df, ['MetaCyc_coveredByNetwork', 'chemATLAS_coveredByNetwork'], ax, [green, green])
labels = ['BNICE.ch-curated\nMetaCyc', 'BNICE.ch-curated\nATLASx']
ax.set_xlabel('Number of pathways', fontsize=14)
ax.axes.yaxis.set_visible(False)
ax.text(-50, 0.2, labels[1], va='center', ha='center', fontsize=14, rotation = 90)
ax.text(-50, 0.02, labels[0], va='center', ha='center', fontsize=14, rotation = 90)
ax.text(len(df)+10, 0.1, 'Total: ' + str(len(df))+ ' pathways', ha='left', va='center', fontsize=14, rotation = 90)
ax.tick_params(axis='both', which='major', labelsize=14)
ax.set_xlim(0, 1250)
ax.set_ylim(-0.05, 0.27)
fig.legend((bar1, bar2), ('Pathway not\nexactly reconstructed', 'Pathway exactly\nreconstructed'), loc=[0.10, 0.45], fontsize=14)
plt.vlines(len(df), -0.03, 0.25, linestyles='solid')
fig.tight_layout()
fig.set_size_inches(4, 6)
plt.gca().invert_yaxis()
plt.savefig('plots/MetaCycVsATLASxBNICE.png', bbox = [6, 9])
def plotNumberOfReconstructedPerNTDT(df, values, ax, color):
counts = [df[i].to_list().count(1) for i in values]
width = 0.1 # the width of the bars
rects1 = ax.barh([0.02, 0.2],counts, width, color = color)
# Add some text for labels, title and custom x-axis tick labels, etc.
ax.set_xlabel('Number of pathways')
autolabel(rects1, ax)
return rects1
def autolabel(rects, ax):
#Attach a text label above each bar in *rects*, displaying its height.
for rect in rects:
width = rect.get_width()
print(width)
ax.annotate('{}'.format(width),
xy=(width-110, rect.get_y() + rect.get_height() - 0.02),
xytext=(0, 3), # 3 points vertical offset
textcoords="offset points",
ha='center', va='bottom', fontsize=14)
MetaCycVsATLASxAll()
MetaCycVsATLASxBNICE()
######## Supplementary material plots #########
def plotLengthDistributionAll():
df = pd.read_csv(coverage_file)
df = df.drop_duplicates()
df['Length'] = df.apply(calculate_length, axis=1)
fig, ax = plt.subplots(figsize=(16,9))
bar1 = plotLengthTotal(df, ax, violet)
bar4 = plotLengthOfReconstructedPerNTDT(df, ['chemATLAS_coveredByNetwork','chemATLAS_hp_coveredByNetwork'], ax, green) #['chemATLAS_edges','chemATLAS_hp_edges']
ax.set_ylabel('Number of pathways', fontsize=20)
ax.set_xlabel('Pathway length', fontsize=20)
fig.legend((bar1, bar4), ('Pathway not\nexactly reconstructed', 'Pathway exactly\nreconstructed'), loc=[0.75, 0.75], fontsize=18)
plt.xticks(np.arange(0, 30, 5), fontsize = 18)
plt.yticks(np.arange(0, 450, 25), fontsize = 18)
plt.xlim(0, 27)
plt.ylim(0, 400)
fig.tight_layout()
plt.savefig('plots/plotMetacycPathwayLengthDistributionAll_all.png', bbox = [9, 9])
def plotLengthDistributionAllCrop():
df = pd.read_csv(coverage_file)
df = df.drop_duplicates()
df['Length'] = df.apply(calculate_length, axis=1)
fig, ax = plt.subplots(figsize=(9,3))
_ = plotLengthTotal(df, ax, violet)
_ = plotLengthOfReconstructedPerNTDT(df, ['chemATLAS_coveredByNetwork','chemATLAS_hp_coveredByNetwork'], ax, green) #['chemATLAS_edges','chemATLAS_hp_edges']
fig.tight_layout()
plt.xticks(np.arange(10, 30, 5), fontsize = 21)
plt.yticks(np.arange(5, 11, 5), fontsize = 21)
plt.xlim(9.5, 27)
plt.ylim(0, 12)
plt.savefig('plots/plotMetacycPathwayLengthDistributionAll_crop.png', bbox = [3, 9])
def plotLengthOfReconstructedPerNTDT(df, search_setups, ax, color):
setup1 = search_setups[0]
setup2 = search_setups[1]
values1 = list(set(df['Length'].to_list()))
width = 0.4 # the width of the bars
counts1 = [df[df[setup1]==1]['Length'].to_list().count(i) for i in values1]
values1 = [i+ width / 2 for i in values1]
rects1 = ax.bar(values1, counts1, width, label=setup1, color=color)
values2 = list(set(df['Length'].to_list()))
counts2 = [df[df[setup2]==1]['Length'].to_list().count(i) for i in values2]
values2 = [i - width / 2 for i in values2]
rects2 = ax.bar(values2, counts2, width, label=setup2, color=color)
return rects1, rects2
def plotLengthTotal(df, ax, color):
values1 = list(set(df['Length'].to_list()))
width = 0.4 # the width of the bars
counts1 = [df['Length'].to_list().count(i) for i in values1]
values1 = [i+ width / 2 for i in values1]
rects1 = ax.bar(values1, counts1, width, color=color)
values2 = list(set(df['Length'].to_list()))
counts2 = [df['Length'].to_list().count(i) for i in values2]
values2 = [i - width / 2 for i in values2]
rects2 = ax.bar(values2, counts2, width, color=color)
return rects1, rects2
def calculate_length(row):
return len(row['Pathway_original_in_refV'].split('|'))-1
plotLengthDistributionAll()
plotLengthDistributionAllCrop()
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