mhjensen
32 lines
729 B
Python
32 lines
729 B
Python
import numpy as np
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import pickle
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from matplotlib import pyplot as plt
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from sklearn.linear_model import LogisticRegression
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"""
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Download https://physics.bu.edu/~pankajm/ML-Review-Datasets/isingMC/IsingData.zip
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Unzip files in the same folder as this script.
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Run script
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"""
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def read_t(t=0.25,root="./"):
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if t > 0.:
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data = pickle.load(open(root+'Ising2DFM_reSample_L40_T=%.2f.pkl'%t,'rb'))
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return np.unpackbits(data).astype(int).reshape(-1,1600)
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stack = []
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for i,t in enumerate(np.arange(0.25,4.01,0.25)):
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y = np.ones(10000,dtype=int)
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if t > 2.25:
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y*=0
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stack.extend(list(y))
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y = np.array(stack)
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stack = []
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for t in np.arange(0.25,4.01,0.25):
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stack.append(read_t(t))
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X = np.vstack(stack)
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