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62 lines
1.7 KiB
62 lines
1.7 KiB
import logging
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import sys
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import traceback
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import operator
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import numpy as np
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import random
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from sklearn import decomposition
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import matplotlib.pyplot as plt
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from fastText import load_model
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from .cache import load_cache
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logger = logging.getLogger("crytic-pred")
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def plot(args):
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try:
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model = args.model
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model = load_model(model)
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filename = args.filename
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contract = args.contract
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fname = args.fname
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solc = args.solc
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infile = args.input
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ext = args.filter
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if contract is None or fname is None or infile is None:
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logger.error('The plot mode requieres contract, fname and input parameters.')
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sys.exit(-1)
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cache = load_cache(infile, model, ext=ext, solc=solc)
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#save_cache("cache.npz", cache)
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data = list()
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fs = list()
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for (f,c,n),y in cache.items():
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if c == contract and n == fname:
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fs.append(f)
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data.append(y)
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#r[x] = similarity(fvector, y)
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data = np.array(data)
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pca = decomposition.PCA(n_components=2)
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tdata = pca.fit_transform(data)
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plt.figure()
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assert(len(tdata) == len(fs))
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for ([x,y],l) in zip(tdata, fs):
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x = random.gauss(0, 0.01) + x
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y = random.gauss(0, 0.01) + y
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plt.scatter(x, y, c='blue')
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plt.text(x-0.001,y+0.001, l.split("_")[1].replace(".sol.ast.compact.json",""))
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plt.show()
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#r = sorted(r.items(), key=operator.itemgetter(1), reverse=True)
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#for x,score in r[:10]:
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except Exception:
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logger.error('Error in %s' % args.filename)
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logger.error(traceback.format_exc())
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sys.exit(-1)
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