66 lines
2.2 KiB
Python
66 lines
2.2 KiB
Python
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#!/usr/bin/python3
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import parser
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from series_util import discretize_series, extract_series
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from multiprocessing import Pool, Manager
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import pandas as pd
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class Gesture:
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# mantain data relative to gesture
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# files, parser, normalization
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def __init__(self, gestureId, parser, files):
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manager = Manager()
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self.pool = Pool()
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self.id = gestureId
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self.parser = parser
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self.files = files
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# to allow concurrent update
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self.norm = manager.dict()
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self.discretized = manager.dict()
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self.wordSet = manager.dict()
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# parallelization using map
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def normalize_files(self):
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results = []
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for i in range(0, 4):
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results.append(self.pool.map(self.parser.normalize, self.files[i]))
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self.norm= {"w":results[0], "x":results[1], "y":results[2], "z":results[3]}
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def print_normalized(self):
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if not self.norm:
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self.normalize_files()
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print(self.norm)
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# TODO improve complexity
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def discretize(self, gaussianInterval):
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for coord in self.norm.keys():
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# for each x,y,w,z
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frameList = []
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for frame in self.norm.get(coord):
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# for each dataframe in x,y,w,z
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discFrame = []
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for i in range(0, frame.shape[0]):
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# for each row (series) of the dataframe
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series = extract_series(frame.as_matrix(), i)
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discFrame.append(discretize_series(series, gaussianInterval))
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frameList.append(pd.DataFrame(discFrame))
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self.discretized[coord] = frameList
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# TODO improve complexity
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def get_words(self, window, step):
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for coord in self.norm.keys():
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# for each x,y,w,z
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wordFrameList = []
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for frame in self.discretized.get(coord):
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# for each dataframe in x,y,w,z
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wordFrame = []
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for i in range(0, frame.shape[0]):
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# for each series of the dataframe
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words = get_gesture_words(extract_series(frame.as_matrix(), i))
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wordFrame.append(words)
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wordFrameList.append(pd.DataFrame(wordList))
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self.wordSet[coord] = wordFrameList
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