From 3b94f54ac07bed274d9b452de78996e97a6cd846 Mon Sep 17 00:00:00 2001
From: Danilo Ferreira de Lima <danilo.enoque.ferreira.de.lima@xfel.de>
Date: Fri, 3 Mar 2023 13:57:28 +0100
Subject: [PATCH] Consistently using the uncertainty as the noise model.
---
pes_to_spec/model.py | 10 +++++-----
1 file changed, 5 insertions(+), 5 deletions(-)
diff --git a/pes_to_spec/model.py b/pes_to_spec/model.py
index 8b47e61..7bb760a 100644
--- a/pes_to_spec/model.py
+++ b/pes_to_spec/model.py
@@ -937,13 +937,13 @@ class Model(TransformerMixin, BaseEstimator):
E = np.fft.fftfreq(len(e), de)
e_axis = np.linspace(-0.5*(e[-1] - e[0]), 0.5*(e[-1] - e[0]), len(e))
# generate a gaussian
- gaussian = np.exp(-0.5*(e_axis)**2/self.high_res_sigma**2)
- gaussian /= np.sum(gaussian, axis=0, keepdims=True)
- gaussian = np.clip(gaussian, a_min=1e-6, a_max=None)
- gaussian_ft = np.fft.fft(gaussian)
+ #gaussian = np.exp(-0.5*(e_axis)**2/self.high_res_sigma**2)
+ #gaussian /= np.sum(gaussian, axis=0, keepdims=True)
+ #gaussian = np.clip(gaussian, a_min=1e-6, a_max=None)
+ #gaussian_ft = np.fft.fft(gaussian)
H = np.mean(Z/D, axis=0)
- N = np.absolute(gaussian_ft*V)**2
+ N = np.absolute(V)**2
S = np.mean(np.absolute(D)**2, axis=0)
H2 = np.absolute(H)**2
nonzero = np.absolute(H) > 0.2
--
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