import seaborn as sns

import matplotlib.pyplot as plt

# Data for the heatmap $($using your probability scale $1-4)$

data $=\{$

'Explore': $[1,2,3],$

'Establish': $[2,3,4],$

'Exploit': $[3,4,4]$

$\}$

index $=[\text{'}$General Prompts', 'Adversarial Prompts', 'Targeted Prompts'$]$

df $=$ pd$.$DataFrame$($data$,$ index$=$index$)$

# Create a custom colormap to better reflect the probability levels

colors $=[(255/255,255/255,204/255),$ # Light Yellow $($Low$)$

$(255/255,237/255,160/255),$ # Light Orange $($Medium$)$

$(254/255,178/255,76/255),$ # Orange $($High$)$

$(227/255,26/255,28/255)]$ # Red $($Very High$)$

cmap $=$ sns$.$color$\_$palette$($colors$)$

# Create the heatmap with seaborn

plt$.$figure$($figsize$=(10,6))$ # Adjust figure size for better readability

sns$.$heatmap$($df$,$ annot$=$True, cmap$=$cmap, fmt$="\mathrm{.}0$f$",$ cbar$\_$kws$=\{\text{'}$label$\text{'}$: 'Probability'$\})$

# Add labels and title

plt$.$title$(\text{'}$Probability of Identifying Harmful LLM Outputs', fontsize$=14)$ # Increase title font size

plt$.$ylabel$(\text{'}$Prompt Type', fontsize$=12)$ # Increase y$-$axis label font size

plt$.$xlabel$(\text{'}$Phase$\text{'},$ fontsize$=12)$ # Increase x$-$axis label font size

plt$.$xticks$($fontsize$=10)$ # Increase x$-$axis tick labels font size

plt$.$yticks$($fontsize$=10)$ # Increase y$-$axis tick labels font size

# Show the plot

plt$.$show$()$ do the heatmap visualize this