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import pandas as pd
from plotnine import (
labs,
theme,
theme_bw,
guides,
position_nudge,
aes,
geom_violin,
geom_line,
geom_jitter,
scale_x_discrete,
ggplot,
)
from pathlib import Path
import math
class GrewTSEVisualiser:
"""
A basic visualisation class that creates a violin plot based on a syntactic evaluation.
"""
def __init__(self) -> None:
self.data = None
def visualise_syntactic_performance(
self,
results: pd.DataFrame,
title: str,
target_x_label: str,
alt_x_label: str,
x_axis_label: str,
y_axis_label: str,
filename: str,
) -> None:
"""
Visualise a syntactic performance evaluation result.
:param results: pass the results DataFrame created by the GrewTSEEvaluator.
:param title: Give the diagram a main title.
:param target_x_label: Give the original target word and hence first word in the minimal pair a label e.g. 'Accusative'.
:param alt_x_label: Give the second element in the minimal pair a label e.g. 'Dative'.
:param x_axis_label: Give the X Axis a title.
:param y_axis_label: Give the Y Axis a title.
:param filename: A filename to save the visualisation.
:return:
"""
visualise_slope(
filename,
results,
target_x_label,
alt_x_label,
x_axis_label,
y_axis_label,
title,
)
def visualise_slope(
path: Path,
results: pd.DataFrame,
target_x_label: str,
alt_x_label: str,
x_axis_label: str,
y_axis_label: str,
title: str,
):
lsize = 0.65
fill_alpha = 0.7
# X-axis: Acc, Gen
# Y-axis: surprisal
filtered_df = results[
results["form_ungrammatical"].notna()
& (results["form_ungrammatical"].str.strip() != "")
]
filtered_df["subject_id"] = filtered_df.index
# Melt the dataframe
df_long = pd.melt(
filtered_df,
id_vars=["subject_id"],
value_vars=["p_grammatical", "p_ungrammatical"],
var_name="source",
value_name="log_prob",
)
# Map source to fixed x-axis labels
df_long["x_label"] = df_long["source"].map(
{"p_grammatical": target_x_label, "p_ungrammatical": alt_x_label}
)
def surprisal(p: float) -> float:
return -math.log2(p)
def confidence(p: float) -> float:
return math.log2(p)
df_long["surprisal"] = df_long["log_prob"].apply(surprisal)
p = (
ggplot(df_long, aes(x="x_label", y="surprisal", fill="x_label"))
+ scale_x_discrete(limits=[target_x_label, alt_x_label])
+ geom_jitter(aes(color="x_label"), width=0.01, alpha=0.7)
+
# geom_text(aes(label='label'), nudge_y=0.1) +
geom_line(aes(group="subject_id"), color="gray", alpha=0.7, size=0.2)
+ geom_violin(
df_long[df_long["x_label"] == target_x_label],
aes(x="x_label", y="surprisal", group="x_label"),
position=position_nudge(x=-0.2),
style="left-right",
alpha=fill_alpha,
size=lsize,
)
+ geom_violin(
df_long[df_long["x_label"] == alt_x_label],
aes(x="x_label", y="surprisal", group="x_label"),
position=position_nudge(x=0.2),
style="right-left",
alpha=fill_alpha,
size=lsize,
)
+ guides(fill=False)
+ theme_bw()
+ theme(figure_size=(8, 4), legend_position="none")
+ labs(x=x_axis_label, y=y_axis_label, title=title)
)
p.save(path, width=14, height=8, dpi=300)
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