From 9da93ac8fc6c32ece8fe1ed15aa77341a69549be Mon Sep 17 00:00:00 2001
From: Danilo Ferreira de Lima <danilo.enoque.ferreira.de.lima@xfel.de>
Date: Wed, 22 May 2024 18:47:33 +0200
Subject: [PATCH] Fixed roll.
---
pes_to_spec/model.py | 27 ++++++++++++++-------------
1 file changed, 14 insertions(+), 13 deletions(-)
diff --git a/pes_to_spec/model.py b/pes_to_spec/model.py
index b696dba..bf61877 100644
--- a/pes_to_spec/model.py
+++ b/pes_to_spec/model.py
@@ -520,19 +520,20 @@ class SelectRelevantLowResolution(TransformerMixin, BaseEstimator):
y[channel] = np.stack(y[channel], axis=1)
# roll data in the first pulse to check best shift
- shifts = np.arange(-3, 3+1)
- chi2 = {ch: np.zeros_like(shifts, dtype=np.float32)
- for ch in y.keys()}
- for i, s in enumerate(shifts):
- meanX = {ch: np.mean(np.roll(y[ch][:,0,:], s, axis=-1), axis=0, keepdims=True)
- for ch in y.keys()}
- for ch in y.keys():
- chi2[ch] = np.sum(((meanX[ch] - self.mean[ch][:,0,:])/self.std[ch][:,0,:])**2)
- shift = {ch: shifts[np.argmin(chi2[ch])]
- for ch in y.keys()}
- print("Shifts", shift)
- y = {ch: np.roll(y[ch], shift[ch], axis=-1)
- for ch in y.keys()}
+ if len(self.mean) > 0:
+ shifts = np.arange(-3, 3+1)
+ chi2 = {ch: np.zeros_like(shifts, dtype=np.float32)
+ for ch in y.keys()}
+ for i, s in enumerate(shifts):
+ meanX = {ch: np.mean(np.roll(y[ch][:,:1,:], s, axis=-1), axis=(0, 1), keepdims=True)
+ for ch in y.keys()}
+ for ch in y.keys():
+ chi2[ch][i] = np.sum(((meanX[ch] - self.mean[ch])/self.std[ch])**2)
+ shift = {ch: shifts[np.argmin(chi2[ch])]
+ for ch in y.keys()}
+ print("Shifts", shift)
+ y = {ch: np.roll(y[ch], shift[ch], axis=-1)
+ for ch in y.keys()}
if not keep_dictionary_structure:
selected = list(y.values())
--
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