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feat: support gpu

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bernard-ng
2025-09-29 21:07:23 +02:00
parent 9e35f95107
commit a1d500830b
15 changed files with 661 additions and 85 deletions
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research/statistics/plots.py
+5 -9
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@@ -8,11 +8,7 @@ from research.statistics.utils import LETTERS, build_letter_frequencies
def plot_transition_matrix(ax, df_probs, title=""):
hm = sns.heatmap(
df_probs.loc[list(LETTERS), list(LETTERS)],
cmap="Reds",
annot=False,
cbar=False,
ax=ax
df_probs.loc[list(LETTERS), list(LETTERS)], cmap="Reds", annot=False, cbar=False, ax=ax
)
ax.set_title(title, fontsize=12)
return hm
@@ -20,8 +16,8 @@ def plot_transition_matrix(ax, df_probs, title=""):
def plot_letter_frequencies(males, females, sort_values=False, title=None):
# Compute frequencies
L_m = build_letter_frequencies(males['name']).set_index("letter")["freq"]
L_f = build_letter_frequencies(females['name']).set_index("letter")["freq"]
L_m = build_letter_frequencies(males["name"]).set_index("letter")["freq"]
L_f = build_letter_frequencies(females["name"]).set_index("letter")["freq"]
# Combine into one DataFrame
df_plot = pd.DataFrame({"Male": L_m, "Female": L_f}).fillna(0).reset_index()
@@ -35,8 +31,8 @@ def plot_letter_frequencies(males, females, sort_values=False, title=None):
x = np.arange(len(df_plot))
w = 0.4
fig, ax = plt.subplots(figsize=(16, 6))
ax.bar(x - w/2, df_plot["Male"], width=w, label="Male", color="steelblue", alpha=0.8)
ax.bar(x + w/2, df_plot["Female"], width=w, label="Female", color="salmon", alpha=0.8)
ax.bar(x - w / 2, df_plot["Male"], width=w, label="Male", color="steelblue", alpha=0.8)
ax.bar(x + w / 2, df_plot["Female"], width=w, label="Female", color="salmon", alpha=0.8)
ax.set_xticks(x)
ax.set_xticklabels(df_plot["letter"])