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This commit is contained in:
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GPG Key ID:
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@ -1,17 +1,87 @@
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from ditact_pic import plot
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from spin_image import SpinImage, FFT
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import sys
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import numpy as np
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import matplotlib.pyplot as plt
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import glob
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import scipy.interpolate as ip
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plt.style.use(["style", "colors", "one_column"])
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from spin_image import SpinImage, FFT
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from ditact_pic import plot
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from lattices import VO2_Lattice
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plt.style.use(["style", "colors", "one_column"])
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def check_percentage(p1, p2):
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plt.figure()
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plt.plot(p1, p2)
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def average_mean(arr, window_size=20):
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arr_sum = np.cumsum(arr)
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arr = (arr_sum[window_size:] - arr_sum[:-window_size]) / window_size
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return arr
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def new_merge(files):
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wp = []
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op = []
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spot_1 = []
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spot_2 = []
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spot_3 = []
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plt.figure()
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for file in files:
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print(file)
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data = np.load(file, allow_pickle=True)
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old_percentage = data["percentage"]
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w_percentage = data["w_percentage"]
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wp.append(w_percentage)
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op.append(old_percentage)
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# check_percentage(old_percentage, w_percentage)
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out = []
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for o in ["out_1", "out_2", "out_3", "out_4"]:
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out.append(np.array(data[o]))
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print(out)
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out = np.array(out)[:, :, 0]
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spot_1.append(out[0, :])
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spot_2.append(out[3, :])
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spot_3.append(out[2, :])
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wp = np.concatenate(wp, axis=0)
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op = np.concatenate(op, axis=0)
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spot_1 = np.concatenate(spot_1, axis=0)
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spot_2 = np.concatenate(spot_2, axis=0)
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spot_3 = np.concatenate(spot_3, axis=0)
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arg_sort = np.argsort(op)
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wp = wp[arg_sort]
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op = op[arg_sort]
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spot_1 = spot_1[arg_sort]
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spot_2 = spot_2[arg_sort]
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spot_3 = spot_3[arg_sort]
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win = 100
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wp = average_mean(wp, win)
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op = average_mean(op, win)
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spot_1 = average_mean(spot_1, win)
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spot_2 = average_mean(spot_2, win)
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spot_3 = average_mean(spot_3, win)
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x = op
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plt.plot(x, spot_1, "r.")
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plt.plot(x, spot_2, "g.")
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plt.plot(x, spot_3, "b.")
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ma = np.max(spot_1+spot_2+spot_3)
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spot_1 /= ma
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spot_2 /= ma
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spot_3 /= ma
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print("debug....")
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print(wp.shape)
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plt.savefig("debug.png")
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return op, np.stack([spot_2, spot_1, spot_3])
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def merge(files):
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merge = []
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plt.figure()
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@ -32,17 +102,18 @@ def merge(files):
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out = out / summe
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merge.append(out)
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plt.plot(out[0, :], "r")
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plt.plot(out[3, :], "b")
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plt.plot(out[2, :], "g")
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plt.plot(w_percentage, out[0, :], "r.")
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plt.plot(w_percentage, out[3, :], "b.")
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plt.plot(w_percentage, out[2, :], "g.")
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all = sum(merge)
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summe = np.max(np.sum(all, axis=0))
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all = all / summe
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plt.plot(all[0, :], "k")
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plt.plot(all[3, :], "k")
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plt.plot(all[2, :], "k")
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# plt.plot(all[0, :], "k")
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# plt.plot(all[3, :], "k")
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# plt.plot(all[2, :], "k")
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plt.savefig("debug.png")
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percentage = 1-percentage
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return percentage, all
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@ -58,18 +129,23 @@ def debug(percentage, out):
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def stacked_plot(ax, percentage, out, title=""):
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stacks = ax.stackplot(percentage, out[[0, 3, 1, 2]], colors=[
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"w"], ls="solid", ec="k")
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hatches = ["/", "", "\\", "\\"]
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for stack, hatch in zip(stacks, hatches):
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stacks = ax.stackplot(percentage, out[[0, 1, 2]], colors=[
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"w"], ls=(0, (0, 1)), ec="w")
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hatches = ["//", "|", "\\\\"]
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for stack, hatch, color in zip(stacks, hatches, ["C1", "C0", "C2"]):
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stack.set_hatch(hatch)
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stack.set_edgecolor(color)
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ax.set_xlabel("Metallic Phase (%)")
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ax.set_ylabel("normalized Intensity ")
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ax.set_ylim([0.4, 1])
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ax.set_xlim([0., 1])
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ax.text(0.1, 0.9, "monoclinic", backgroundcolor="w")
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ax.text(0.6, 0.5, "rutile", backgroundcolor="w")
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ax.text(0.35, 0.75, "diffusive", backgroundcolor="w")
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ax.text(0.1, 0.9, "monoclinic", backgroundcolor="w",
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bbox=dict(boxstyle='square,pad=0.0', ec="None", fc="w"))
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ax.text(0.6, 0.5, "rutile", backgroundcolor="w",
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bbox=dict(boxstyle='square,pad=0.0', ec="None", fc="w"))
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ax.text(0.35, 0.73, "diffusive", backgroundcolor="w",
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bbox=dict(boxstyle='square,pad=0.0', ec="None", fc="w"))
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ax.stackplot(percentage, out[[0, 1, 2]], colors=["None"], ec="k")
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def time_scale(ax, p, o):
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@ -86,21 +162,23 @@ def time_scale(ax, p, o):
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cs_rut = ip.interp1d(p[::-1], rut_perc[::-1])
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cs_mono = ip.interp1d(p[::-1], mono_perc[::-1])
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#plt.figure()
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#ph = np.linspace(0.01, 0.99, 100)
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#plt.plot(ph, cs_rut(ph))
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#plt.plot(ph, cs_mono(ph))
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# plt.figure()
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# ph = np.linspace(0.01, 0.99, 100)
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# plt.plot(ph, cs_rut(ph))
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# plt.plot(ph, cs_mono(ph))
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time = np.linspace(0.01, 3, 1000)
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phy_phase = np.exp(-time)
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phy_phase = 1-np.exp(-time)
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rut_phase = cs_rut(phy_phase)
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mono_phase = cs_mono(phy_phase)
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ax.plot(time, phy_phase, "k:", label="physical")
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ax.plot(time, rut_phase, label="rutile")
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ax.plot(time, mono_phase, label="monoclinic")
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ax.plot(time, rut_phase, label="rutile", color="C1")
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ax.plot(time, mono_phase, label="monoclinic", color="C2")
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ax.set_xlabel("time (a.u.)")
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ax.set_ylabel("Metallic Phase (%)")
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ax.set_xlim([0, 3])
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ax.set_ylim([0, 1])
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ax.legend()
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@ -114,25 +192,61 @@ def intens(ax, file, p, o):
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intens = FFT()
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intens.load(file)
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plot(intens, ax)
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ax.set_xlim([-.8,0.8])
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ax.set_ylim([-.8,1.6])
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axins = ax.inset_axes([0.0, 0.5, 0.47, 0.5])
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axins.plot(p, o[0], label="rut")
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axins.plot(p, o[3], label="diff")
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axins.plot(p, o[2], label="mono")
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axins.legend(loc='lower left', bbox_to_anchor=(1, 0.5))
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#axins.get_yaxis().set_visible(False)
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axins.yaxis.tick_right()
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axins.set_yticks([0,0.5]
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if __name__ == "__main__":
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p, o = merge(sys.argv[2:])
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np.savez("merged.npz", p=p, o=o)
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# eval_data_print(f)
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ax.set_xlim([-1, 1])
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ax.set_ylim([-.9, .9])
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ax.axis("off")
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fig, axs = plt.subplots(1,3)
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fig.set_figheight(3)
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stacked_plot(axs[1],p, o)
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time_scale(axs[2],p, o)
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intens(axs[0], sys.argv[1], p ,o)
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# rect = plt.Rectangle((-1, -.8), 2, 1.6, facecolor="None", hatch="//")
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# ax.add_patch(rect)
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lat = VO2_Lattice(20, 20)
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reci = lat.get_spots()
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print(reci)
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size = (intens.freqx[1] - intens.freqx[0]) * 20
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size2 = size/2
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# big_rect = plt.Rectangle((-10, -10), 20, 20, fc="None", ec="k", hatch="//")
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# ax.add_patch(big_rect)
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for x, y in zip(reci[0][0], reci[0][1]):
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if x < 1 and x > -1:
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if y < 1 and y > -1:
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print(x, y)
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rect = plt.Rectangle((-y-size2, x-size2),
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size, size, fc="C1", ec="k", alpha=0.5)
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# big_rect.set_clip_path(rect)
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ax.add_patch(rect)
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for x, y in zip(reci[1][0], reci[1][1]):
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if x < 1 and x > -1:
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if y < 1 and y > -1:
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print(x, y)
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rect = plt.Rectangle((-y-size2, x-size2),
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size, size, fc="C2", ec="k", alpha=0.5)
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ax.add_patch(rect)
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axins = ax.inset_axes([0.0, 0.0, 0.5, 0.5])
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axins.plot(p, o[0], label="rut.", color="C1")
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axins.plot(p, o[2], label="mono.", color="C2")
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axins.plot(p, o[1], label="diff.", color="C0")
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axins.legend(loc='center left', bbox_to_anchor=(1, 0.5))
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axins.set_xlim([0, 1])
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axins.set_ylim([0, 1])
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axins.set_xlabel("phase (%)")
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axins.set_ylabel("signal", labelpad=-5)
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# axins.get_yaxis().set_visible(False)
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# axins.yaxis.tick_right()
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axins.set_yticks([0, 1])
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if __name__ == "__main__":
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p, o = new_merge(sys.argv[2:])
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np.savez("merged.npz", p=p, o=o)
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fig, axs = plt.subplots(1, 3)
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fig.set_figheight(2)
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stacked_plot(axs[1], p, o)
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time_scale(axs[2], p, o)
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if "intens" in sys.argv[1]:
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intens(axs[0], sys.argv[1], p, o)
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plt.tight_layout()
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plt.savefig("analysis.pdf")
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plt.savefig("analysis.png")
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plt.show()
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@ -6,7 +6,7 @@ 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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plt.style.use(["style", "colors", "two_column"])
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def simulate():
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@ -47,18 +47,28 @@ def plot(fft, ax):
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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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# 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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max = np.maximum(max, m)
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return max
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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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@ -75,19 +85,22 @@ def plot_all(intens_rutile, intens_mono, intens_mixed):
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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((-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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# 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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@ -98,11 +111,11 @@ def plot_all(intens_rutile, intens_mono, intens_mixed):
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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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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, orientation="horizontal", ticks=[1e-10, 1e-5, 1e0])
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#cbar.ax.set_xticklabels(['Low', 'Medium', 'High'])
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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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@ -122,10 +135,10 @@ def load():
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if __name__ == "__main__":
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np.random.seed(1234)
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#simulate()
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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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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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81
clean_python/ising.py
Normal file
81
clean_python/ising.py
Normal file
@ -0,0 +1,81 @@
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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):
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LEN = 60
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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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for i in tqdm.tqdm(range(1000)):
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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(20)
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|
||||
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"ising_rect_{num}.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(file, idx):
|
||||
np.random.seed(1234)
|
||||
print(f"runnig: {file}")
|
||||
ising(file,idx)
|
||||
|
||||
|
||||
if __name__ == "__main__":
|
||||
files = sys.argv[2:]
|
||||
idx = int(sys.argv[1])
|
||||
print(f"{idx}/{len(files)}")
|
||||
if idx > len(files):
|
||||
exit()
|
||||
if idx < 1:
|
||||
exit()
|
||||
runner(files[idx-1], idx)
|
||||
Loading…
Reference in New Issue
Block a user