dict_dl/analysis.py

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# import matplotlib.pyplot as plt
# from PIL import Image
# from wordcloud import STOPWORDS, WordCloud
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d = FullDictionary("en_merriam_webster/", "_mw.json")
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# d = Dictionary("en_MW_thesaurus/", "_mwt.json")
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# d = Dictionary("de_duden/", "_duden.json")
print(f"{d.readtime:.06f}")
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# print([k for k in d if not all([c in string.ascii_letters for c in k])])
print([k for k in d if "?" in k])
exit()
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again = set()
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for k, v in d.items():
for ke, di in v.items():
if ke != "type":
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if "related" in di:
again.add(k)
print(again, len(again))
with open(f"{d.dir_prefix}redo", "at") as f:
f.write("\n".join(list(again)))
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exit()
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def grey_color_func(
word, font_size, position, orientation, random_state=None, **kwargs
):
return "hsl(0, 0%%, %d%%)" % random.randint(60, 100)
# mask = np.array(Image.open(os.path.join(d, "stormtrooper_mask.png")))
word = "abhorrent"
text = " ".join(mw[word]["synonyms"] + [word])
wc = WordCloud(
max_words=200,
width=1920,
height=1080,
margin=10,
min_font_size=40,
max_font_size=100,
random_state=1,
).generate(text)
default_colors = wc.to_array()
# plt.title("Custom colors")
# plt.imshow(wc.recolor(color_func=grey_color_func, random_state=3),
# interpolation="bilinear")
plt.figure()
plt.title(word)
plt.imshow(default_colors, interpolation="bilinear")
plt.axis("off")
plt.show()
exit()
# letters = {k[0] for k in mw}
# start = time.time()
# for c in letters:
# c_db = {k:v for k,v in mw.items() if k[0] == c}
# with open(f"{c}_mw.json", "w") as f: # save DB
# json.dump(c_db, f, separators=(",", ":"), indent=2)
# print(time.time() - start)
# exit()
# types = {w["word"] for w in mw if not w["history_and_etymology"]}
types = [w["type"] for w in mw]
print(len(types))
new_mw = {w["word"]: {k: v for k, v in w.items() if k != "word"} for w in mw}
print(new_mw)
print(len(new_mw))
with open("new_mw.json", "w") as f:
json.dump(new_mw, f, separators=(",", ":"), indent=2)