From 69230e4edd8cb7217fc91cd98ca8e000731761a7 Mon Sep 17 00:00:00 2001
From: Michael Krayer <michael.krayer@posteo.de>
Date: Tue, 25 May 2021 10:32:26 +0200
Subject: [PATCH] added ravel/unravel but untested (it can be loaded from mat
 file)

---
 particle.py | 45 ++++++++++++++++++---------------------------
 1 file changed, 18 insertions(+), 27 deletions(-)

diff --git a/particle.py b/particle.py
index 432816e..a878201 100644
--- a/particle.py
+++ b/particle.py
@@ -91,11 +91,6 @@ class Trajectories:
         for key in self.part[0].attr:
             self.attr[key] = [self.part[0].attr[key].view()]
         self.period = self.part[0].period
-        if any([period is not None for period in self.period]):
-            self._crossings = numpy.zeros((6,self.numpart,1),dtype=numpy.bool)
-        else:
-            self._crossings = None
-        return
         self.unraveled = False
     def __str__(self):
         str = 'Trajectory with\n'
@@ -124,7 +119,7 @@ class Trajectories:
                 raise TypeError("Trajectories can only be sliced by slice objects or integers.")
         return self.get_trajectory(slice_part=sl[0],slice_time=sl[1])
     @classmethod
-    def from_mat(cls,file):
+    def from_mat(cls,file,unraveled=False):
         from .helper import load_mat
         pp,col,time,ccinfo = load_mat(file,['pp','colpy','time','ccinfo'])
         period = [None,None,None]
@@ -137,6 +132,7 @@ class Trajectories:
         traj = cls(Particles(pp[:,:,0],col,time[0],period))
         for ii in range(1,ntime):
             traj += Particles(pp[:,:,ii],col,time[ii],period)
+        traj.unraveled = unraveled
         return traj
     def add_particles(self,part):
         import numpy
@@ -206,36 +202,31 @@ class Trajectories:
                 self.attr['y'][id,slice_time],
                 self.attr['z'][id,slice_time]],axis=0)
     def get_segments(self,id=None):
+        #self.unravel()
+        #if id is None: # npart X ndim X ntime
         return
     def unravel(self):
+        import numpy
         if self.unraveled: return
-        if self._crossings is None: return
-        self._compute_crossings()
-        # do sth
+        raise NotImplementedError('Implemented but untested!')
+        for axis in range(0,3):
+            if self.period[axis] is not None:
+                key = ('x','y','z')[axis]
+                posdiff = (self.part[ii].attr[key]-self.part[ii-1].attr[key]).squeeze()
+                coeff = -(numpy.abs(posdiff)>0.5*self.period[axis]).*numpy.sign(posdiff)
+                coeff = numpy.cumsum(coeff)
+                self.part[ii].attr[key][1:] += coeff*self.period[axis]
         self.unraveled = True
         return
     def ravel(self):
         if not self.unraveled: return
+        raise NotImplementedError('Implemented but untested!')
+        for axis in range(0,3):
+            if self.period[axis] is not None:
+                key = ('x','y','z')[axis]
+                self.part[ii].attr[key] %= self.period[axis]
         self.unraveled = False
         return
-    def _compute_crossings(self):
-        import numpy
-        if self._crossings is not None: # None means no periodicity
-            num_computed = self._crossings.shape[1]
-            if num_computed==self.numtime:
-                return
-            crossings = numpy.zeros((6,self.numpart,self.numtime),dtype=numpy.bool)
-            crossings[:,:,0:num_computed] = self._crossings
-            for ii in range(num_computed,self.numtime):
-                for axis in range(0,3):
-                    if self.period[axis] is not None:
-                        key = ('x','y','z')[axis]
-                        posdiff = (self.part[ii].attr[key]-self.part[ii-1].attr[key]).squeeze()
-                        doesCross = abs(posdiff)>0.5*self.period[axis]
-                        upCross   = numpy.logical_and(posdiff<0,doesCross)
-                        crossings[2*axis,:,ii] = doesCross
-                        crossings[2*axis+1,:,ii] = upCross
-            self._crossings = crossings
     def _make_data_array(self):
         import numpy
         #print('DEBUG: _make_data_array')