import matplotlib.pyplot as plt
import matplotlib.patches as patches
import os
# Dictionary with parameters for the Endocrine Disruption (Tox21) profile
endocrine_data = {
# Nuclear Receptors
"AR": {"bounds": [0, 0.4, 0.7, 1.0], "colors": ["#63C28D", "#FFDF33", "#C14E4E"]},
"ER": {"bounds": [0, 0.4, 0.7, 1.0], "colors": ["#63C28D", "#FFDF33", "#C14E4E"]},
"AR_LBD": {"bounds": [0, 0.4, 0.7, 1.0], "colors": ["#63C28D", "#FFDF33", "#C14E4E"]},
"ER_LBD": {"bounds": [0, 0.4, 0.7, 1.0], "colors": ["#63C28D", "#FFDF33", "#C14E4E"]},
"Aromatase": {"bounds": [0, 0.4, 0.7, 1.0], "colors": ["#63C28D", "#FFDF33", "#C14E4E"]},
"AhR": {"bounds": [0, 0.4, 0.7, 1.0], "colors": ["#63C28D", "#FFDF33", "#C14E4E"]},
"PPAR": {"bounds": [0, 0.4, 0.7, 1.0], "colors": ["#63C28D", "#FFDF33", "#C14E4E"]},
"TR": {"bounds": [0, 0.4, 0.7, 1.0], "colors": ["#63C28D", "#FFDF33", "#C14E4E"]},
"GR": {"bounds": [0, 0.4, 0.7, 1.0], "colors": ["#63C28D", "#FFDF33", "#C14E4E"]},
# Stress Response Pathways
"ARE": {"bounds": [0, 0.4, 0.7, 1.0], "colors": ["#63C28D", "#FFDF33", "#C14E4E"]},
"ATAD5": {"bounds": [0, 0.4, 0.7, 1.0], "colors": ["#63C28D", "#FFDF33", "#C14E4E"]},
# EXCEPTION IDENTIFIED IN HTML: HSE cuts at 0.3, not 0.4
"HSE": {"bounds": [0, 0.3, 0.7, 1.0], "colors": ["#63C28D", "#FFDF33", "#C14E4E"]},
"p53": {"bounds": [0, 0.4, 0.7, 1.0], "colors": ["#63C28D", "#FFDF33", "#C14E4E"]},
"MMP": {"bounds": [0, 0.4, 0.7, 1.0], "colors": ["#63C28D", "#FFDF33", "#C14E4E"]},
}
def create_endocrine_bars():
"""
Generates and saves the proportional bar charts for the Endocrine Disruption parameters.
"""
# Dimensions: 8 cm x 1.3 cm (converted to inches)
fig_width = 8 / 2.54
fig_height = 1.3 / 2.54
# Output directory for Figure 7
output_dir = "ADMET_Endocrine_Bars"
os.makedirs(output_dir, exist_ok=True)
# Background color matching the established paper style
bg_color = '#FFFFFF'
for param, info in endocrine_data.items():
bounds = info["bounds"]
colors = info["colors"]
labels = [str(b) for b in bounds]
# Initialize figure
fig, ax = plt.subplots(figsize=(fig_width, fig_height))
fig.patch.set_facecolor(bg_color)
ax.set_facecolor(bg_color)
min_val = bounds[0]
max_val = bounds[-1]
# Draw each colored segment proportionally
for i in range(len(colors)):
start = bounds[i]
width = bounds[i+1] - bounds[i]
rect = patches.Rectangle(
(start, 0), width, 1,
facecolor=colors[i], edgecolor='none'
)
ax.add_patch(rect)
# Axes scaling
ax.set_xlim(min_val, max_val)
ax.set_ylim(0, 1)
# X-axis setup (ticks and labels)
ax.set_xticks(bounds)
ax.set_xticklabels(labels, rotation=45, ha='right', rotation_mode='anchor', fontsize=9)
# Hide top, left and right spines
ax.spines['top'].set_visible(False)
ax.spines['right'].set_visible(False)
ax.spines['left'].set_visible(False)
# Offset the bottom spine slightly downwards
ax.spines['bottom'].set_position(('outward', 5))
ax.spines['bottom'].set_linewidth(1)
# Tick styling
ax.tick_params(axis='x', direction='out', length=4, width=1, colors='black')
# Completely hide the Y axis
ax.get_yaxis().set_visible(False)
# Format parameter label
display_param = param.replace("_", " ") + " (Prob)"
ax.set_xlabel(display_param, fontsize=11, labelpad=5, weight='bold')
# Adjust layout manually
plt.subplots_adjust(bottom=0.45)
# Save the figure
filename = os.path.join(output_dir, f"{param}_bar.png")
plt.savefig(filename, dpi=300, bbox_inches='tight', facecolor=fig.get_facecolor())
plt.close()
if __name__ == "__main__":
print("Starting generation of Endocrine Disruption profile bars with exact HTML bounds...")
create_endocrine_bars()
print("Process completed successfully! Check the 'ADMET_Endocrine_Bars' folder.")