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37 lines
1.1 KiB
Python
37 lines
1.1 KiB
Python
# prototype to translate a system to text into dictionary
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# as a type of structured text
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import numpy as np
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import json
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# what is the proper way to store radicals with dictionary?
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# use json
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data = json.load(open('dict.json', 'r'))
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# the essence of the program is to introduce noise to disrupt
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# the mapping relation of the dictionary.
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# learning rules is also essential to machine learning, which
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noise = np.random.randint(1,3)
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for i in data:
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i["numeral"] = int(i["numeral"])
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i["numeral"] += noise
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# write to a new json file
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with open('new.json','w') as w_file:
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json.dump(data,w_file, indent=4)
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# test with an existing corpus
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# try a chinese dictionary and a latin dictionary
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# and any other types of dictionary structures, remix!
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# current rule
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# 1 <= key <= 3, silk; 4 <= key <= 6, earth; 7 <= key <= 9, water
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# then when i query the dictionary again,
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# the rule is disrupted, the message is disrupted
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# the rule is disrupted by adding a simple number
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# are there more disruptive and complex rules?
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# next step is to investigate json files themselves |