import rpmClassDev_Alex as rpm importlib.reload(rpm) Hc = 0.062 bar_length = 220e-9 vertex_gap = 1e-7 bar_thickness = 25e-9 bar_width = 80e-9 magnetisation = 800e3 angle = 45 squareLattice = rpm.ASI_RPM(25, 25, bar_length = bar_length,\ vertex_gap = vertex_gap, bar_thickness = bar_thickness,\ bar_width = bar_width, magnetisation = magnetisation) Hc_std = 0.05 squareLattice.load('RandomLattice1.npz') Hamp = 1.15 * Hc folder = r'C:\Users\av2813\Box\GitHub\RPM\RPMv2\AlexData\MinorLoopHamp_' directory = folder + str(np.around(Hamp * 1000, 4)).replace('.', 'p') + 'mT' fieldloops, q, mag, monopole = squareLattice.fieldsweep( Hamp / np.cos(np.pi * angle / 180), 20, angle, n=5, loops=8, folder=directory) np.savez(
import numpy as np import matplotlib import matplotlib.pyplot as plt import matplotlib.cm as cm import matplotlib.colors as cl from matplotlib.ticker import MaxNLocator #from matplotlib.colors import Normalize import copy import pickle import importlib import rpmClassDev_Alex as rpm kagomeLattice1 = rpm.ASI_RPM(10, 10) #kagomeLattice1.square(Hc = Hc, Hc_std=Hc_std) folder = r'C:\Users\av2813\Box\Simulations\Mumax3\mumax3.9final_windows\HPCResults\GroundSemiCircle\pkl' mag = [] monopole = [] q = [] field_steps = np.linspace(0, Hmax, steps + 1) field_steps = np.append(field_steps, np.linspace(Hmax, -Hmax, 2 * steps + 1)) field_steps = np.append(field_steps, np.linspace(-Hmax, 0, steps + 1)) fieldloops = field_steps * np.array([np.cos(Htheta), np.sin(Htheta), 0.]) for root, dirs, files in os.walk(folder): for file in files: if '.npz' in file and 'AppliedFieldState' in file: squareLattice.load(os.path.join(root, file)) mag.append(rpm.netMagnetisation()) monopole.append(rpm.monopoleDensity()) q.append(rpm.correlation(self.previous, self)) #vertex.append(rpm.vertexTypePercentage())
importlib.reload(rpm) fieldApplied = [58.9, 59.52,60.14, 60.76, 61.38, 62.0, 62.62, 63.24, 63.86] folder = r'C:\Users\av2813\Box\GitHub\RPM\RPMv2\AlexData' subfolder = r'\MinorLoopHamp_' lattice_list = [] for f in fieldApplied: sub = subfolder+str(f).replace('.', 'p')+'mT\\' name = 'Lattice_Loop7_FieldStrength0p0mT_Angle0p79.npz' directory = r'C:\Users\av2813\Box\GitHub\RPM\RPMv2\AlexData\MinorLoopSquareLattice25x25\\' file = directory + sub+name lattice = rpm.ASI_RPM(25,25) lattice.load(file) lattice_list.append(lattice) #plt.suptitle(str(np.around(f/0.62,0))+'% of Hc') #plt.show() corr = np.zeros((len(lattice_list), len(lattice_list))) i = 0 for l1 in lattice_list: j = 0 for l2 in lattice_list: corr[i, j] = l1.correlation(l1, l2) j+=1 i+=1 plt.figure() plt.plot(np.around(np.array(fieldApplied)/0.62,0), corr[:,0]) plt.ylabel('Correlation')
import numpy as np import matplotlib.pyplot as plt import rpmClassDev_Alex as rpm n = 5 lattice = rpm.ASI_RPM(n,n) #fieldApplied = [58.9, 59.52,60.14, 60.76, 61.38, 62.0, 62.62, 63.24, 63.86] #fieldApplied = [68.3, 71.3,74.4, 77.5] corrEnd = [] monoEnd = [] magEnd = [] loops = np.arange(0,9,1) #for f in fieldApplied: data = np.load('MinorloopQuenchedDisorder'+str(n)+'x'+str(n)+'.npz') field = data['arr_0'] correlation = data['arr_1'] mag = data['arr_2'] monopole = data['arr_3'] vertex = data['arr_4'] cor_split = np.split(correlation, 8) c = [] c.append(correlation[0]) for t in cor_split: c.append(t[-1])