def get_axes(self):
range_ = self.get_range()
resolution = self.get_resolution()
num = [
step_size_to_num(range_[0], resolution[0]),
step_size_to_num(range_[1], resolution[1])
]
axes = [
axis_from_range(range_[0], num[0]),
axis_from_range(range_[1], num[1])
]
return axes
def test_set_axis(self):
step_size = 0.24
range_ = [-3, 3]
axis = np.linspace(*range_,
num=step_size_to_num(range_, step_size),
endpoint=True)
self.lmfit.set_axis_by_step_size(range_, step_size)
npt.assert_almost_equal(self.lmfit.get_sliced_kmap(0).x_axis, axis)
def set_axis_by_step_size(self, range_, step_size):
"""A convenience setter method to set an axis by defining the
range and the step size.
Args:
range_ (list): A list of min and max value.
step_size (float): A number denoting the step size.
"""
num = step_size_to_num(range_, step_size)
self.set_axis(axis_from_range(range_, num))
import matplotlib.pyplot as plt
import numpy as np
from lmfit import Minimizer, Parameters, report_fit
# kMap.py Imports
from kmap.library.orbital import Orbital
from kmap.library.sliceddata import SlicedData
from kmap.library.misc import step_size_to_num
# Path to data folder; replace with your own; use '/' instead of '+'
# when concatenating with strings
data_path = Path(__file__).parent / Path('../data/')
# define common (kx,ky)-grid for deconvolution
k_range, dk = [-3.0, 3.0], 0.04
num = step_size_to_num(k_range, dk)
kx = np.linspace(k_range[0], k_range[1], num)
ky = kx
# read PTCDA orbitals from file and compute kmaps
names = ['PTCDA_C', 'PTCDA_D', 'PTCDA_E', 'PTCDA_F', 'background']
styles = ['.r-', 'k-', 'r--', '^g-', 'k:']
params = Parameters() # parameters object for minimization
sim_kmaps = []
for name in names[:-1]:
# read cube-file from file
cuberead = open(data_path / (name + '.cube')).read()
orbital = Orbital(cuberead, dk3D=0.12) # 3D-FT
sim_kmap = orbital.get_kmap(
E_kin=27.2,
