140 lines
3.6 KiB
Python
140 lines
3.6 KiB
Python
from .plotter import Plotter
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import matplotlib
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from .lattices import VO2_New
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from .spin_image import SpinImage, FFT
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import numpy as np
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import matplotlib.pyplot as plt
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if __name__ == "__main__":
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plt.style.use(["style", "colors", "two_column"])
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def simulate():
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LEN = 50
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lat = VO2_New(LEN, LEN)
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plot = Plotter(lat)
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si = SpinImage(lat.get_phases())
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mask_misk = np.ones((2*LEN, 2*LEN))
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ind = np.arange(mask_misk.size)
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np.random.shuffle(ind)
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mask_misk[np.unravel_index(
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ind[:int(mask_misk.size/2)], mask_misk.shape)] = 0
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print(mask_misk.shape)
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si.apply_mask(lat.parse_mask(np.ones((2*LEN, 2*LEN))))
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si.gaussian(20)
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intens_mono = si.fft()
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intens_mono.clean()
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si.apply_mask(lat.parse_mask(np.zeros((2*LEN, 2*LEN))))
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si.gaussian(20)
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intens_rutile = si.fft()
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intens_rutile.clean()
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si.apply_mask(lat.parse_mask(mask_misk))
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# si.apply_mask(mask_misk)
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si.gaussian(20)
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intens_mixed = si.fft()
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intens_mixed.clean()
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intens_rutile.save("intens_rut.npz")
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intens_mono.save("intens_mono.npz")
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intens_mixed.save("intens_mixed.npz")
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def plot(fft, ax):
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return ax.imshow(
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fft.intens,
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extent=fft.extents(),
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norm=matplotlib.colors.LogNorm(vmin=1e-10, vmax=1),
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# norm=matplotlib.colors.Normalize(vmax=1, vmin=1e-10),
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cmap="magma",
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origin="lower"
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)
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def norm(*intenss):
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max = 1e-10
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for intens in intenss:
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m = np.max(intens.intens)
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max = np.maximum(max, m)
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return max
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def plot_all(intens_rutile, intens_mono, intens_mixed):
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fig, axs = plt.subplots(3, 2)
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fig.set_figheight(5.2)
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for ax in axs.flatten():
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ax.axis("off")
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axs = axs[:, 1]
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ax = axs[0]
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plot(intens_rutile, ax)
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ax = axs[1]
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plot(intens_mono, ax)
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y_shift = 0.175
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h_shift = 2*y_shift
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l_shift = 0.108
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big_shift = l_shift + h_shift
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# c = plt.Circle((-l_shift, y_shift), radius=0.07,
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# label='patch', fill=False, ec="w", ls=":")
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# ax.add_patch(c)
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# c = plt.Circle((l_shift, -y_shift), radius=0.07,
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# label='patch', fill=False, ec="w", ls=":")
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# ax.add_patch(c)
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# c = plt.Circle((-h_shift, -y_shift), radius=0.07,
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# label='patch', fill=False, ec="w", ls=":")
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# ax.add_patch(c)
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# c = plt.Circle((h_shift, y_shift), radius=0.07,
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# label='patch', fill=False, ec="w", ls=":")
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# ax.add_patch(c)
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ax.annotate("", (-l_shift, y_shift), (0, 0),
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arrowprops=dict(ec='w', facecolor='white', width=.8, headwidth=3, headlength=5))
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ax = axs[2]
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cmap = plot(intens_mixed, ax)
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cut_off = 0.8
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for ax in axs:
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ax.axis("off")
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ax.set_xlim(-cut_off, cut_off)
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ax.set_ylim(-cut_off, cut_off)
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plt.tight_layout()
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fig.subplots_adjust(bottom=0.1, right=0.95, left=0.15, wspace=0.)
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cbar_ax = fig.add_axes([0.55, 0.07, 0.4, 0.015])
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cbar = fig.colorbar(cmap, cax=cbar_ax,
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orientation="horizontal", ticks=[1e-10, 1e-5, 1e0])
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#cbar.ax.set_xticklabels(['Low', 'Medium', 'High'])
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fig.savefig("erklaerbaer.pdf")
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fig.savefig("erklaerbaer.png")
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# Plotting cuts
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def load():
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r = FFT()
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r.load("intens_rut.npz")
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mo = FFT()
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mo.load("intens_mono.npz")
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mi = FFT()
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mi.load("intens_mixed.npz")
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return r, mo, mi
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if __name__ == "__main__":
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np.random.seed(1234)
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simulate()
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np.savez("intens.npz", r=r, mo=mo, mi=mi)
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r, mo, mi = load()
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max = norm(r, mo, mi)
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r.intens = r.intens/max
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mo.intens = mo.intens/max
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mi.intens = mi.intens/max
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plot_all(r, mo, mi)
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plt.show()
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