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fix scaling of params

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This commit is contained in:
Valentin Boettcher 2023-03-20 21:16:57 -04:00
parent 7908745b63
commit 3148c054a5
1 changed files with 28 additions and 13 deletions
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41
bandfit/bandfit.py
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@ -7,6 +7,7 @@ from skimage.transform import resize
from skimage.filters import hessian
from skimage.morphology import skeletonize
from itertools import chain
from scipy.interpolate import splrep, BSpline
def load_data(data_file: str) -> np.ndarray:
@ -236,14 +237,15 @@ def plot_data_with_bands(data, bands):
# return sc.optimize.curve_fit(double_lorentzian, e_axis, col, (0, 10, 0, 3))
def candidate(k, a, b, c, d, s, k_scale):
k = np.asarray(k) * k_scale
energies = energy(k, a, b, c, d)
def candidate(k, b, c, d, k_scale, k_shift):
k = np.asarray(k[: k.size // 2]) * k_scale + k_shift
energies = energy(k, 1 - b - c - d, b, c, d)
energies /= energies.max()
return energies * s
return np.hstack([energies, energies])
def fit_to_bands(bands, a=1, b=1, c=1, d=1):
def fit_to_bands(bands, b=1, c=1, d=1):
bands_normalized = bands.copy()
bands_normalized[:, :2] -= np.sum(bands_normalized[:, :2], axis=1).mean() / 2
@ -254,15 +256,28 @@ def fit_to_bands(bands, a=1, b=1, c=1, d=1):
plt.plot(ks, bands_normalized[:, 0])
plt.plot(ks, bands_normalized[:, 1])
p, _ = sc.optimize.curve_fit(
p, cov = sc.optimize.curve_fit(
candidate,
ks,
bands_normalized[:, 0],
(a, b, c, d, 1, 1),
sigma=bands_normalized[:, 2],
bounds=[(0.5, 0.5, -5, -5, 0.5, 0.5), (1.5, 1.5, 5, 5, 1.5, 1.5)],
np.hstack([ks, ks]),
np.hstack([bands_normalized[:, 0], bands_normalized[:, 1]]),
(b, c, d, 1, 0),
sigma=np.hstack([bands_normalized[:, 2], bands_normalized[:, 3]]),
bounds=[(-10, -10, -10, 0.9, -0.5), (10, 10, 10, 1.1, 0.5)],
)
plt.plot(ks, candidate(ks, *p))
plt.plot(ks, candidate(np.hstack([ks, ks]), *p)[: bands.shape[0]])
(b, c, d, k_scale, k_shift) = p
a = 1 - b - c - d
return p, _
scale = 1 / a
a *= scale
b *= scale
c *= scale
σ = np.sqrt(np.diag(cov))
σ = np.array([np.sqrt(sum(σ[:3] ** 2)), *σ])
σ[:4] *= scale
return ((a, b, c, d, k_scale, k_shift), σ)