2024_Kalantari_PRR/code/scripts/mouse_to_human_years.py

import numpy as np
import matplotlib.pyplot as plt
from scipy.interpolate import interp1d, splrep, splev
import os

# Define the data points
mouse_days = np.array([0, 3, 14, 21, 28, 48])
human_days = np.array([0, 1, 7, 90, 180, 360])
phases = ['Hyper-acute', 'Acute', 'Early Subacute', 'Late Subacute', 'Chronic']
phase_colors = [
    (0.8, 0.2, 0.2),  # Hyper-acute
    (0.2, 0.8, 0.2),  # Acute
    (0.2, 0.2, 0.8),  # Early Subacute
    (0.8, 0.8, 0.2),  # Late Subacute
    (0.5, 0.2, 0.5)   # Chronic
]

# Create linear interpolation for the first segment
linear_fit = interp1d(mouse_days[:3], human_days[:3], kind='linear', fill_value='extrapolate')

# Create a spline fit for the second segment
spline_fit = splrep(mouse_days[2:], human_days[2:])

# Generate finer x values for smooth curve plotting
fine_mouse_days_linear = np.linspace(mouse_days[0], mouse_days[2], 100)
fine_human_days_linear = linear_fit(fine_mouse_days_linear)

fine_mouse_days_spline = np.linspace(mouse_days[2], mouse_days[-1], 100)
fine_human_days_spline = splev(fine_mouse_days_spline, spline_fit)

# Plot the data points and the fits
plt.figure()
plt.plot(mouse_days, human_days, 'o', markerfacecolor='b', label='Data Points')
plt.plot(fine_mouse_days_linear, fine_human_days_linear, '-r', label='Linear Fit (0-14 days)')
plt.plot(fine_mouse_days_spline, fine_human_days_spline, '-g', label='Spline Fit (14-48 days)')

# Fill areas under the curve according to phases
for i in range(len(mouse_days) - 1):
    if mouse_days[i+1] <= 14:
        fill_x = np.linspace(mouse_days[i], mouse_days[i+1], 100)
        fill_y = linear_fit(fill_x)
    else:
        fill_x = np.linspace(mouse_days[i], mouse_days[i+1], 100)
        fill_y = splev(fill_x, spline_fit)
    
    plt.fill_between(fill_x, 0, fill_y, color=phase_colors[i], alpha=0.5, label=phases[i])

# Add dashed grey lines from data points to x and y ticks
for i in range(len(mouse_days)):
    x = mouse_days[i]
    y = human_days[i]
    plt.plot([x, x], [0, y], '--', color='grey')
    plt.plot([0, x], [y, y], '--', color='grey')

# Set the ticks for the dashed lines
plt.xticks(mouse_days)
plt.yticks(human_days)

# Add labels and title with font size 10
plt.xlabel('Mouse Days', fontsize=10)
plt.ylabel('Human Days', fontsize=10)
plt.title('Mouse Days to Human Days Conversion', fontsize=10)

# Set the font size for the ticks
plt.xticks(fontsize=10)
plt.yticks(fontsize=10)

# Add a legend for the phases, outside of the plot
handles, labels = plt.gca().get_legend_handles_labels()
by_label = dict(zip(labels, handles))
plt.legend(by_label.values(), by_label.keys(), fontsize=10, bbox_to_anchor=(1.05, 1), loc='upper left')

# Show grid for better visualization
plt.grid(True)

# Get the directory where the code file is located
code_dir = os.path.dirname(os.path.abspath(__file__))

# Get the parent directory of the code directory
parent_dir = os.path.dirname(code_dir)

# Define the output directory for saving the figure
output_dir = os.path.join(parent_dir, 'output', 'figures')
os.makedirs(output_dir, exist_ok=True)

# Save the plot as SVG and PNG with specified size
plt.gcf().set_size_inches(9/2.54, 18/2.54)  # Convert cm to inches
plt.savefig(os.path.join(output_dir, 'mouse_to_human_days.svg'), format='svg', bbox_inches='tight')
plt.savefig(os.path.join(output_dir, 'mouse_to_human_days.png'), format='png', bbox_inches='tight',dpi = 300)

# Show the plot
plt.show()