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116 lines
3.1 KiB
Python
116 lines
3.1 KiB
Python
'''
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Development Notes
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JSON is a common format used to represent structured text.
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The essence of the program is to introduce noise to disrupt the
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mapping relation present in the dictionary.
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Rules are also present in machine learning.
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The mapping rule is disrupted, when I query the dictionary again,
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the message is disrupted.
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The rule is disrupted by linear arithemetic operation,
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are there more non-linear and nuanced rules?
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Prototype to translate a system to text into dictionary
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as a type of structured text.
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str int conversion is important to debug the program
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I am still hostile to the concept and etymology of noise, rename
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the concept into something else.
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'''
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import numpy as np
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import json
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# 1 <= key <= 3, silk; 4 <= key <= 6, earth; 7 <= key <= 9, water
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# perform message decryption process via this mini corpus
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# "no" field is similar to ascii/morse code/unicode coding protocols
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# original message identified by "no" field, no 2 & 3
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# first wrd
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# disrupted message idenfified by "no" field
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def parse_json(filename):
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data = json.load(open(filename,'r'))
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return data
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def intify(data):
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for i in data:
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i["no"] = int(i["no"])
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return data
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def in_msg(data):
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message_i = []
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message_full_i = []
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for i in data:
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if i["no"] == 2:
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message_i.append(i["glyph"])
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message_full_i.append(i)
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if i["no"] == 3:
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message_i.append(i["glyph"])
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message_full_i.append(i)
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print("message prior to disruption contains: ")
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for s in message_i:
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print(s)
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def disrupt(data):
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noise = np.random.randint(1,3)
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for i in data:
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i["no"] += noise
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return data
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def save_json(data):
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with open('corpus_cn.json','w', encoding='utf-8') as w_file:
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json.dump(data,w_file, indent=4, ensure_ascii = False)
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def out_msg(noise_data):
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message_o = []
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message_full_o = []
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for i in noise_data:
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#comparing integers, the noise_data no fields are previously
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#dumped as integers
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if i["no"] == 2:
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message_o.append(i["glyph"])
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message_full_o.append(i)
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if i["no"] == 3:
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message_o.append(i["glyph"])
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message_full_o.append(i)
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print("message after disruption contains: ")
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for s in message_o:
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print(s)
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# at this point the interferences are somewhat apparent
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# how can i present the interference to be more apparent?
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# do i need to work with a really large corpus to make it apparent?
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# todo
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# input chinese blocks in here
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if __name__ == "__main__":
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parsed_json = parse_json(filename = "seed.json")
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intified_data = intify(data = parsed_json)
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in_msg(data = intified_data)
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disrupted_data = disrupt(data = intified_data)
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save_json(data = disrupted_data)
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parsed_noise_json = parse_json(filename = "noised.json")
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out_msg(noise_data = parsed_noise_json)
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# test with a large corpus in separate program
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# try with corpuses of different language
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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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# main section looks really ugly |