FFT/clean_python/main.py
2023-04-25 16:25:05 +02:00

86 lines
2.3 KiB
Python

import logging
import scipy.fftpack as sfft
from plotter import Plotter
from scipy import signal
from cache import timeit
from extractors import Rect_Evaluator
import tqdm
from lattices import SCC_Lattice, VO2_Lattice, VO2_New
import sys
from spin_image import SpinImage
import numpy as np
import matplotlib.pyplot as plt
plt.style.use(["style", "colors", "two_column"])
logger = logging.getLogger('fft')
# logger.setLevel(logging.DEBUG)
ch = logging.StreamHandler()
ch.setLevel(logging.DEBUG)
formatter = logging.Formatter(
'%(asctime)s - %(name)s - %(levelname)s - %(message)s')
ch.setFormatter(formatter)
logger.addHandler(ch)
def random(seed):
np.random.seed(seed)
LEN = 40
#lat = VO2_New(LEN, LEN)
lat = VO2_Lattice(LEN, LEN)
maske = np.zeros((LEN, LEN))
ind = np.arange(maske.size)
np.random.shuffle(ind)
rect = Rect_Evaluator(lat.get_spots())
out_rect = [[] for x in range(4)]
percentage = []
weighted_percentage = []
counter = 0
si = SpinImage(lat.get_phases())
already_inited = False
for i in tqdm.tqdm(ind):
maske[np.unravel_index(i, maske.shape)] = True
counter += 1
if np.mod(counter, 100) != 0 and i != ind[-1] and i != ind[0]:
continue
print(counter, i)
si.apply_mask(lat.parse_mask(maske))
si.gaussian(20)
intens = si.fft()
if not already_inited:
rect.generate_mask(intens, merge=True)
already_inited = True
ir, vr = rect.extract(intens)
for lis, val in zip(out_rect, vr):
lis.append(val)
percentage.append(np.sum(maske))
[p1, p2] = si.get_intens(lat.parse_mask(maske))
weighted_percentage.append(p1/(p1+p2))
percentage = np.array(percentage)
weighted_percentage = np.array(weighted_percentage)
percentage /= np.max(percentage)
np.savez(f"random_rect_{seed}.npz",
w_percentage=weighted_percentage, percentage=percentage, out_1=out_rect[0],
out_2=out_rect[1], out_3=out_rect[2], out_4=out_rect[3])
def runner():
np.random.seed(1234)
seeds = np.random.randint(0, 10000, 200)
idx = int(sys.argv[1])
if idx < 0:
return
if idx >= seeds.size:
return
seed = seeds[idx]
random(seed)
if __name__ == "__main__":
np.random.seed(1234)
runner()