def load_data_from_URLs(self, URLs): # -> create data[BE,kx,ky]
# Last element in URLs are the parameters. All other elements
# are individual orbitals to load. Each is a list of length 2
# with first entry being the URL, the second the meta_data
# dictionary
*orbitals, options = URLs
name, *parameters = options
self.data = SlicedData.init_from_orbitals(name, orbitals, parameters)
self.change_slice(0, 0)
def load_data_from_URLs(self, URLs, ID=None): # -> create data[BE,kx,ky]
# Last element in URLs are the parameters. All other elements
# are individual orbitals to load. Each is a list of length 2
# with first entry being the URL, the second the meta_data
# dictionary
*orbitals, options = URLs
name, *parameters = options
s_share = float(config.get_key('orbital', 's_share_sliced'))
self.data = SlicedData.init_from_orbitals(name, orbitals,
parameters, s_share=s_share,
ID=ID)
self.load_data = ['load_from_URLs', URLs]
self.change_slice(0, 0)
0.0, # fermi_energy (float): Fermi energy in eV
0.4, # energy_broadening (float): FWHM of Gaussian energy broadenening in eV
0.03, # dk (float): Desired k-resolution in kmap in Angstroem^-1.
0, # phi (float): Euler orientation angle phi in degree.
0, # theta (float): Euler orientation angle phi in degree.
0, # psi (float): Euler orientation angle phi in degree.
'no', # Ak_type (string): Treatment of |A.k|^2: either 'no', 'toroid' or 'NanoESCA'.
'p', # polarization (string): Either 'p', 's', 'C+', 'C-' or 'CDAD'.
0, # alpha (float): Angle of incidence plane in degree.
0, # beta (float): Azimuth of incidence plane in degree.
'auto', # gamma (float/str): Damping factor for final state in Angstroem^-1. str = 'auto' sets gamma automatically
'no'
] # symmetrization (str): either 'no', '2-fold', '2-fold+mirror',
# '3-fold', '3-fold+mirror','4-fold', '4-fold+mirror'
# initialize SlicedData object
kmap_stack = SlicedData.init_from_orbitals(name, orbitals, parameters)
# Plot some slices
fig, _ax = plt.subplots(3, 3)
ax = _ax.flatten()
nplots = len(ax)
nslice = kmap_stack.data.shape[0]
count = 0
for i in range(0, nslice, 1 + nslice // nplots):
plot_data = kmap_stack.slice_from_index(i)
ax[count].imshow(plot_data.data)
count += 1
plt.show()