From ecf337f55a1c800e6c981d113674ac64b35948ad Mon Sep 17 00:00:00 2001
From: gubaidulinvadim <gubaidulinvadim@gmail.com>
Date: Mon, 15 Jul 2024 15:47:16 +0200
Subject: [PATCH] -applying formatters
---
mbtrack2/tracking/particles.py | 36 ++++++++++++++++++++--------------
1 file changed, 21 insertions(+), 15 deletions(-)
diff --git a/mbtrack2/tracking/particles.py b/mbtrack2/tracking/particles.py
index db333b3..74ef09c 100644
--- a/mbtrack2/tracking/particles.py
+++ b/mbtrack2/tracking/particles.py
@@ -283,26 +283,32 @@ class Bunch:
Return the bunch emittance for each plane.
"""
cor = np.squeeze([[self[name] - self[name].mean()] for name in self])
-
+
cov_x = np.cov(self['x'], self['xp'])
- cov_y = np.cov(self['y'], self['yp'])
+ cov_y = np.cov(self['y'], self['yp'])
cov_z = np.cov(self['tau'], self['delta'])
-
+
if (self.ring.optics.local_dispersion != [0, 0, 0, 0]):
cov_xdelta = np.cov(self['x'], self['delta'])
cov_xpdelta = np.cov(self['xp'], self['delta'])
- cov_ydelta = np.cov(self['y'], self['delta'])
- cov_ypdelta = np.cov(self['yp'], self['delta'])
-
- sig11 = cov_x[0, 0] - cov_xdelta[0, 1] * cov_xdelta[0, 1] / cov_z[1,1]
- sig12 = cov_x[0, 1] - cov_xdelta[0, 1] * cov_xpdelta[0, 1] / cov_z[1, 1]
- sig22 = cov_x[1, 1] - cov_xpdelta[0, 1] * cov_xpdelta[0, 1] / cov_z[1, 1]
- emitX = np.sqrt(sig11*sig22-sig12*sig12)
-
- sig11 = cov_y[0, 0] - cov_ydelta[0, 1] * cov_ydelta[0, 1] / cov_z[1,1]
- sig12 = cov_y[0, 1] - cov_ydelta[0, 1] * cov_ypdelta[0, 1] / cov_z[1, 1]
- sig22 = cov_y[1, 1] - cov_ypdelta[0, 1] * cov_ypdelta[0, 1] / cov_z[1, 1]
- emitY = np.sqrt(sig11*sig22-sig12*sig12)
+ cov_ydelta = np.cov(self['y'], self['delta'])
+ cov_ypdelta = np.cov(self['yp'], self['delta'])
+
+ sig11 = cov_x[
+ 0, 0] - cov_xdelta[0, 1] * cov_xdelta[0, 1] / cov_z[1, 1]
+ sig12 = cov_x[
+ 0, 1] - cov_xdelta[0, 1] * cov_xpdelta[0, 1] / cov_z[1, 1]
+ sig22 = cov_x[
+ 1, 1] - cov_xpdelta[0, 1] * cov_xpdelta[0, 1] / cov_z[1, 1]
+ emitX = np.sqrt(sig11*sig22 - sig12*sig12)
+
+ sig11 = cov_y[
+ 0, 0] - cov_ydelta[0, 1] * cov_ydelta[0, 1] / cov_z[1, 1]
+ sig12 = cov_y[
+ 0, 1] - cov_ydelta[0, 1] * cov_ypdelta[0, 1] / cov_z[1, 1]
+ sig22 = cov_y[
+ 1, 1] - cov_ypdelta[0, 1] * cov_ypdelta[0, 1] / cov_z[1, 1]
+ emitY = np.sqrt(sig11*sig22 - sig12*sig12)
else:
emitX = np.sqrt(np.linalg.det(cov_x))
emitY = np.sqrt(np.linalg.det(cov_y))
--
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