def plotfluxcurrents(flux, g_sol, dx, dy, voltage, jlim=jmax, flim=fluxmax):
cmap = 'RdBu_r'
fig, axes = plt.subplots(1, 3, figsize=(12, 5))
jx, jy = curl(g_sol, dx, dy)
axes[0].matshow(flux, aspect=dy / dx, vmin=-flim, vmax=flim, cmap=cmap)
axes[0].set_title("Measured Flux", fontsize=30)
axes[1].matshow(crop(jx, 10, 40),
aspect=dy / dx,
vmin=-jlim,
vmax=jlim,
cmap=cmap)
axes[1].set_title("$j_x$", fontsize=30)
axes[2].matshow(crop(jy, 10, 40),
aspect=dy / dx,
vmin=-jlim,
vmax=jlim,
cmap=cmap)
axes[2].set_title("$j_y$", fontsize=30)
plt.suptitle("Gate voltage = {}".format(voltage), fontsize=30)
for ax in axes:
ax.axis('off')
plt.tight_layout()
def crop(im, px, py):
Ly, Lx = im.shape
return im[py:py + Ly - 2 * py, px:px + Lx - 2 * px]
loc = os.path.dirname(os.path.realpath(__file__))
data = np.load(
os.path.join(loc,
"../../../data/2016-03-09-HgTe-reconstruction.npz"))['data']
dy, dx = 0.16, 0.73 #Pixel distance in micrometers
fluxmax = max([np.abs(d[1]['scan']).max() for d in data])
maxcurrent = lambda jxjy: max(np.abs(jxjy[0]).max(), np.abs(jxjy[1]).max())
jmax = max([maxcurrent(curl(d[1]['g_sol'])) for d in data])
def plotfluxcurrents(flux, g_sol, dx, dy, voltage, jlim=jmax, flim=fluxmax):
cmap = 'RdBu_r'
fig, axes = plt.subplots(1, 3, figsize=(12, 5))
jx, jy = curl(g_sol, dx, dy)
axes[0].matshow(flux, aspect=dy / dx, vmin=-flim, vmax=flim, cmap=cmap)
axes[0].set_title("Measured Flux", fontsize=30)
axes[1].matshow(crop(jx, 10, 40),
aspect=dy / dx,
vmin=-jlim,
vmax=jlim,
cmap=cmap)
def currents(self):
return curl(self.gfield)