68 lines
1.9 KiB
Python
68 lines
1.9 KiB
Python
import os
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import sys
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import re
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import random
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import numpy as np
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def resample(X, draw):
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Xtuples = [tuple(x) for x in X]
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r = random.random()
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while(True):
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x = draw()
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if tuple(x) not in Xtuples:
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break
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return x.astype(int)
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def generate_dataset(TemplateType, execution_handler, nTuning, nDataPoints, draw):
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# print "Getting some good profiles..."
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# nDim = draw().size
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# X = np.empty((nTuning, nDim))
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# t = np.empty(nTuning)
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# profiles = []
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# for i in range(nTuning):
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# x = resample(X, draw)
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# y = execution_handler(x)
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# if y not in profiles:
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# profiles.append(y)
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# idx = profiles.index(y)
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# X[i,:] = x
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# t[i] = idx
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#
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# print "Generating the dataset..."
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# Y = np.empty((nDataPoints, len(profiles)))
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# X = np.empty((nDataPoints, nDim))
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# t = []
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#
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# for i in range(nDataPoints):
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# x = resample(X, draw)
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# for j,y in enumerate(profiles):
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# T = execution_handler(x, os.devnull, y)
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# Y[i,j] = T
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# idx = np.argmax(Y[i,:])
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# X[i,:] = x
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# t = np.argmax(Y[:i+1,], axis=1)
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# if i%10==0:
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# sys.stdout.write('%d data points generated\r'%i)
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# sys.stdout.flush()
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template_name = TemplateType.__name__
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dir = os.path.join("data", template_name)
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if not os.path.exists(dir):
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os.makedirs(dir)
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# np.savetxt(os.path.join(dir,"profiles.csv"), profiles)
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# np.savetxt(os.path.join(dir,"X.csv"), X)
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# np.savetxt(os.path.join(dir,"Y.csv"), Y)
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profiles = np.loadtxt(os.path.join(dir, "profiles.csv"))
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X = np.loadtxt(os.path.join(dir, "X.csv"),ndmin=2)
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Y = np.loadtxt(os.path.join(dir, "Y.csv"),ndmin=2)
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#idx = np.argsort(np.bincount(np.argmin(Y, axis=1)))
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idx = np.argsort(Y[np.argmax(X),:])
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Y = Y[:, idx]
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profiles = profiles[idx]
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return X, Y, profiles
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