def plot_ES_e_dependence(Bz=20.): e_range=np.linspace(0,10,100) #gauss spectrum=np.zeros((6,)) for Ex in e_range: spectrum=np.vstack((spectrum,np.sort(nvlevels.get_ES( E_field=[Ex,0.,0.], B_field=[0.,0.,Bz], Ee0=-1.94, transitions=False, )[0]))) spectrum=spectrum[1:] for i in range(6): plot(e_range,spectrum[:,i])
def plot_ES_b_dependence(strain_splitting=2.): b_range=np.linspace(0,1000,100) #gauss Ex=strain_splitting/2. #Ex is approx strain_splitting divided by 2 spectrum=np.zeros((6,)) for Bz in b_range: spectrum=np.vstack((spectrum,np.sort(nvlevels.get_ES( E_field=[Ex,0.,0.], B_field=[0.,0.,Bz], Ee0=-1.94, transitions=False, )[0]))) spectrum=spectrum[1:] for i in range(6): plot(b_range,spectrum[:,i])
def plot_transitions_b_dependence(strain_splitting=2.5): b_range=np.linspace(0,1000,100) #gauss Ex=strain_splitting/2. #Ex is approx strain_splitting divided by 2 no_transitions=8 spectrum=np.zeros((no_transitions,)) for Bz in b_range: spectrum=np.vstack((spectrum,nvlevels.get_optical_transitions( E_field=[Ex,0.,0.], B_field=[0,0.,Bz], Ee0=-1.94, show_FB_E_transitions=False ))) spectrum=spectrum[1:] for i in range(no_transitions): plot(b_range,spectrum[:,i])
ax.set_yticks(yticks)
ax.set_xticks(xticks)
ax.set_yticklabels(yticks,fontsize=fs)
ax.set_xticklabels(xticklabels,fontsize=fs)
min=d['datamin1'].min()
max=d['datazero'].max()
zero=0.5
ax2.set_yticks([0,min,zero,max,1.1])
ax2.set_yticklabels(['','-1','0','1',''],fontsize=fs)
ax2.set_ylabel ('<Sz>N', fontsize = fs)
theta=[90,180,270,360]
t=[]
t.append(0)
for k in theta:
t.append(int((k*229./90.)-12))
print t
t.append(2000)
ax3.set_xticks(t)
ax3.set_xticklabels(['5','90','180','270','360',''],fontsize=fs)
ax3.set_xlabel (r'$\theta$ (degrees)', fontsize = fs)
ax.legend(loc=4,prop={'size':fs})
fig.savefig(os.path.join(basepath,name+'.pdf'),format='pdf')
#analysis()
plot()
esr_data['datamin1'],
yerr=esr_data['udatamin1'],
mfc=plots.colors['N_one'],
mec=plots.colors['N_one'],
color=plots.colors['N_one'],
marker='o',
linestyle='None',
label=' mI=-1')
ax.plot(esr_data['xfit'],
esr_data['min1fit'],
color=plots.colors['N_one'],
ls='-',
linewidth=1)
ax.set_xlabel('MW freq (GHz)', fontsize=fs)
ax.set_ylabel('P(ms=0)', fontsize=fs)
ax.set_ylim([0.4, 1.15])
ax.set_xlim([2.826, 2.832])
ax.set_yticks([0.5, 0.75, 1])
ax.set_xticks([2.826, 2.829, 2.832])
ax.set_yticklabels([0.5, 0.75, 1], fontsize=fs)
ax.set_xticklabels([2.826, 2.829, 2.832], fontsize=fs)
ax.xaxis.set_major_formatter(FormatStrFormatter('%0.3f'))
#ax.set_title('Dark ESR')
ax.legend(loc=4, prop={'size': fs})
fig.savefig(os.path.join(basepath, name + '.pdf'), format='pdf')
#analysis()
plot()