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# markup module that provides marked up text and a plot for the explanations
# external imports
import numpy as np
from numpy import ndarray
# internal imports
from utils import formatting as fmt
def markup_text(input_text: list, text_values: ndarray, variant: str):
buckets = 10
# Flatten the explanations values
if variant == "shap":
text_values = np.transpose(text_values)
text_values = fmt.flatten_values(text_values)
# Determine the minimum and maximum values
min_val, max_val = np.min(text_values), np.max(text_values)
# Separate the threshold calculation for negative and positive values
if variant == "visualizer":
thresholds = np.linspace(min_val, max_val, num=buckets, endpoint=False)[1:]
else:
neg_thresholds = np.linspace(min_val, 0, num=buckets // 2 + 1, endpoint=False)[
1:
]
pos_thresholds = np.linspace(0, max_val, num=buckets // 2 + 1)[1:]
thresholds = np.concatenate([neg_thresholds, pos_thresholds])
marked_text = []
# Function to determine the bucket for a given value
for text, value in zip(input_text, text_values):
bucket = 0
for i, threshold in enumerate(thresholds, start=1):
if value > threshold:
bucket = i
marked_text.append((text, str(bucket)))
return marked_text
def color_codes():
return {
# 1-5: Strong Light Red to Lighter Red
"1": "#FF6666", # Strong Light Red
"2": "#FF8080", # Slightly Lighter Red
"3": "#FF9999", # Intermediate Light Red
"4": "#FFB3B3", # Light Red
"5": "#FFCCCC", # Very Light Red
# 6-10: Light Green to Strong Light Green
"6": "#B3FFB3", # Light Green
"7": "#99FF99", # Slightly Stronger Green
"8": "#80FF80", # Intermediate Green
"9": "#66FF66", # Strong Green
"10": "#4DFF4D", # Very Strong Green
}
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