76 lines
2.4 KiB
Python
76 lines
2.4 KiB
Python
import logging
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import scipy.fftpack as sfft
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from .plotter import Plotter
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from scipy import signal
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from .cache import timeit
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from .extractors import Rect_Evaluator
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import tqdm
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from .lattices import SCC_Lattice, VO2_Lattice, VO2_New
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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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plt.style.use(["style", "colors", "two_column"])
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logger = logging.getLogger('fft')
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# logger.setLevel(logging.DEBUG)
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ch = logging.StreamHandler()
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ch.setLevel(logging.DEBUG)
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formatter = logging.Formatter(
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'%(asctime)s - %(name)s - %(levelname)s - %(message)s')
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ch.setFormatter(formatter)
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logger.addHandler(ch)
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def ising(file, num, LEN=40,iterations=500):
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#lat = VO2_New(LEN, LEN)
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lat = VO2_New(LEN, LEN)
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rect = Rect_Evaluator(lat.get_spots())
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out_rect = [[] for x in range(4)]
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percentage = []
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weighted_percentage = []
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si = SpinImage(lat.get_phases())
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already_inited = False
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spins = np.load(file)["s1"]
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spins[spins==-1] = 0
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ising_percentage=np.mean(spins)
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for i in tqdm.tqdm(range(iterations)):
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(ix,iy) = np.random.randint(2000-LEN-LEN,size=2)
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maske = spins[ix:ix+2*LEN, iy:iy+2*LEN]
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si.apply_mask(lat.parse_mask(maske))
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si.gaussian(LEN/2.)
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intens = si.fft()
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if not already_inited:
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rect.generate_mask(intens, merge=True)
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already_inited = True
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ir, vr = rect.extract(intens)
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for lis, val in zip(out_rect, vr):
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lis.append(val)
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percentage.append(np.sum(maske))
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[p1, p2] = si.get_intens(lat.parse_mask(maske))
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weighted_percentage.append(p1/(p1+p2))
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np.savez(f"ising_rect_{num}_temp.npz",i_percentage=ising_percentage,
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w_percentage=weighted_percentage, percentage=percentage, out_1=out_rect[0],
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out_2=out_rect[1], out_3=out_rect[2], out_4=out_rect[3])
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percentage = np.array(percentage)
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weighted_percentage = np.array(weighted_percentage)
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percentage /= np.max(percentage)
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np.savez(f"ising_rect_{num}.npz",i_percentage=ising_percentage,
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w_percentage=weighted_percentage, percentage=percentage, out_1=out_rect[0],
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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(file, idx, LEN=40, iterations=500):
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np.random.seed(1234)
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print(f"runnig: {file}")
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ising(file=file,num=idx,LEN=LEN,iterations=iterations)
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