runnable
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@ -43,9 +43,9 @@ class Evaluator(ABC):
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@timeit
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def generate_mask(self, img: FFT, merge=False):
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hash = str(img.intens.shape)
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self.mask = self.gen_mask_helper(img, hash=hash)
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self.mask = self.gen_mask_helper(img)
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if merge:
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self.mask = self.merge_mask_helper(hash=hash)
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self.mask = self.merge_mask_helper()
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self.eval_points = [[a] for a in np.arange(len(self.eval_points))]
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@abstractmethod
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@ -1,4 +1,5 @@
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from lattices import SCC_Lattice, VO2_Lattice
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import sys
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from spin_image import SpinImage
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import numpy as np
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import matplotlib.pyplot as plt
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@ -121,7 +122,7 @@ def random(seed):
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for i in tqdm.tqdm(ind):
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maske[np.unravel_index(i, (LEN, LEN))] = True
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counter += 1
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if np.mod(counter, 100) != 0:
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if np.mod(counter, 100) != 0 and not i == ind[-1]:
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continue
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si.apply_mask(lat.parse_mask(maske))
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@ -204,21 +205,34 @@ def ising(seed, temp=0.5):
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out_2=out_rect[1], out_3=out_rect[2], out_4=out_rect[3])
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def runner():
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np.random.seed(1234)
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seeds = np.random.randint(0, 10000, 200)
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idx = int(sys.argv[1])
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if idx < 0:
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return
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if idx >= seeds.size:
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return
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seed = seeds[idx]
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random(seed)
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if __name__ == "__main__":
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np.random.seed(1234)
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runner()
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# test_me()
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# test_square()
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# test_mixed()
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# plt.show()
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# random(1234)
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# ising(1234)
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test_pdf()
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plt.show()
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exit()
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for i in np.random.randint(0, 10000, 5):
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random(i)
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ising(i, 0.5)
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ising(i, 1.0)
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ising(i, 1.5)
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# test_pdf()
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# plt.show()
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# exit()
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# for i in np.random.randint(0, 10000, 5):
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# random(i)
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# ising(i, 0.5)
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# ising(i, 1.0)
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# ising(i, 1.5)
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# plt.show()
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