import matplotlib.pyplot as plt

import numpy as np

# Data points based on the visual interpretation

t_values = np.array([0, 1, 2, 3])

# Assuming r_peak = 1 and r_trough = -0.5

r_peak_value = 1.0

r_trough_value = -0.5

r_values = np.array([0, r_peak_value, 0, r_trough_value])

# Colors from the image (approximated)

line_color = 'deeppink'

axis_color = 'deeppink'

dashed_line_color = 'lightskyblue' # or 'cyan'

tick_label_color = 'lightskyblue'

plt.figure(figsize=(6, 5))

# Plot the main graph line

plt.plot(t_values, r_values, color=line_color, linewidth=2)

# Add vertical dashed lines

# From t=1, r=0 to t=1, r=r_peak_value

plt.plot([1, 1], [0, r_peak_value], color=dashed_line_color, linestyle='--', dashes=(4, 4), linewidth=1)

# From t=3, r=0 to t=3, r=r_trough_value

plt.plot([3, 3], [0, r_trough_value], color=dashed_line_color, linestyle='--', dashes=(4, 4), linewidth=1)

# Style the axes to look like the image

ax = plt.gca()

# Remove top and right spines

ax.spines['top'].set_visible(False)

ax.spines['right'].set_visible(False)

# Color and position bottom and left spines to act as axes

ax.spines['bottom'].set_position('zero')

ax.spines['bottom'].set_color(axis_color)

ax.spines['bottom'].set_linewidth(1.5)

ax.spines['left'].set_position('zero')

ax.spines['left'].set_color(axis_color)

ax.spines['left'].set_linewidth(1.5)

# Set ticks and labels for the x-axis (t-axis)

plt.xticks([0, 1, 2, 3], labels=['O', '1', '2', '3'], color=tick_label_color)

# Remove y-axis ticks and labels (as they are not prominent in the image)

plt.yticks([])

# Add axis labels 't' and 'r' at the end of the axes

# For 't' label at the right end of the x-axis

plt.text(max(t_values) + 0.1, -0.05, 't', color=axis_color, ha='left', va='top', fontsize=12)

# For 'r' label at the top end of the y-axis

max_r_for_label = max(r_peak_value, abs(r_trough_value)) + 0.2 # Determine a good y-pos for 'r'

plt.text(-0.05, max_r_for_label, 'r', color=axis_color, ha='right', va='top', fontsize=12, rotation=0)

# Set axis limits to give some padding and make arrows visible

plt.xlim(-0.2, max(t_values) + 0.3)

plt.ylim(min(r_trough_value, 0) - 0.3, max(r_peak_value, 0) + 0.3)

# Add arrowheads to the axes (simplified version)

# For x-axis (t)

ax.plot(1, 0, ">", transform=ax.get_yaxis_transform(), clip_on=False, color=axis_color, markersize=8)

# For y-axis (r)

ax.plot(0, 1, "^", transform=ax.get_xaxis_transform(), clip_on=False, color=axis_color, markersize=8)

plt.grid(False) # No grid in the original image

plt.title("r vs t Graph", color=line_color) # Optional title

plt.show()