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51 lines
1.3 KiB
Python
51 lines
1.3 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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for i in data:
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print(i["letter"])
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# modify numeral for letter and update json file
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i["numeral"] = "updated value nul"
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print(i["numeral"])
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for i in data:
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print(i)
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# how to save to json file
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# the problem is, dictionary keys are saved as strings
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# using numerical update can apply?
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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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# add noise to rule
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# there is some noise
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noise = np.random.randint(1,3)
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# loop through keys, add noise to key value
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# say noise is 2, every key adds 2
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# dict = { '3':'silk-1', '4':'silk-2', '5':'silk-3',
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# '6':'earth-1', '7':'earth-2', '8':'earth-3',
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# '9':'water-1', '10':'water-2', '11':'water-3',
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# }
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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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