diff --git a/code/external/deepmatching_1.2.2_c++_linux/Makefile b/code/external/deepmatching_1.2.2_c++_linux/Makefile
index 3f31795..d16e330 100755
--- a/code/external/deepmatching_1.2.2_c++_linux/Makefile
+++ b/code/external/deepmatching_1.2.2_c++_linux/Makefile
@@ -1,46 +1,47 @@
 CC=g++
 
 OS_NAME=$(shell uname -s)
 ifeq ($(OS_NAME),Linux) 
 #old#  LAPACKLDFLAGS=/usr/lib64/atlas/libsatlas.so   # single-threaded blas
   #LAPACKLDFLAGS=/usr/lib/atlas-base/libatlas.so /usr/lib/libblas/libblas.so
-  LAPACKLDFLAGS=/usr/lib64/atlas/libtatlas.so.3.10  # multi-threaded blas
+  #LAPACKLDFLAGS=/usr/lib64/atlas/libtatlas.so.3.10  # multi-threaded blas for deneb1
+  LAPACKLDFLAGS=/ssoft/spack/cornalin/v1/opt/spack/linux-rhel7-x86_E5v4_Mellanox/gcc-7.1.0/openblas-0.2.19-ylrirtidrpbdgxmcwipnhx4rhla4j4fm/lib/libopenblas_haswellp-r0.2.19.so  #multithreaded blas for fidis
   BLAS_THREADING=-D MULTITHREADED_BLAS # remove this if wrong
 endif
 ifeq ($(OS_NAME),Darwin)  # Mac OS X
   LAPACKLDFLAGS=-framework Accelerate # for OS X
 endif
 LAPACKCFLAGS=-Dinteger=int $(BLAS_THREADING)
 #old#
 #STATICLAPACKLDFLAGS=-fPIC -Wall -g -fopenmp -static -static-libstdc++ /home/lear/douze/tmp/jpeg-6b/libjpeg.a /usr/lib64/libpng.a /usr/lib64/libz.a /usr/lib64/libblas.a /usr/lib/gcc/x86_64-redhat-linux/4.9.2/libgfortran.a /usr/lib/gcc/x86_64-redhat-linux/4.9.2/libquadmath.a # statically linked version
 
 STATICLAPACKLDFLAGS=-fPIC -Wall -g -fopenmp -static -static-libstdc++ /home/lear/douze/tmp/jpeg-6b/libjpeg.a /usr/lib/x86_64-linux-gnu/libpng.a /usr/lib/x86_64-linux-gnu/libz.a /usr/lib/libblas/libblas.a /usr/lib/gcc/x86_64-linux-gnu/4.8/libgfortran.a /usr/lib/gcc/x86_64-linux-gnu/4.8/libquadmath.a # statically linked version
 
-CFLAGS= -fPIC -Wall -g -std=c++11 $(LAPACKCFLAGS) -fopenmp -DUSE_OPENMP -O3
+CFLAGS= -fPIC -Wall -g -std=c++11 $(LAPACKCFLAGS) -fopenmp -DUSE_OPENMP -O3 -march=native
 LDFLAGS=-fPIC -Wall -g -ljpeg -lpng -fopenmp 
 CPYTHONFLAGS=-I/usr/include/python2.7
 
 SOURCES := $(shell find . -name '*.cpp' ! -name 'deepmatching_matlab.cpp')
 OBJ := $(SOURCES:%.cpp=%.o)
 HEADERS := $(shell find . -name '*.h')
 
 
 all: deepmatching 
 
 .cpp.o:  %.cpp %.h
 	$(CC) -o $@ $(CFLAGS) -c $+
 
 deepmatching: $(HEADERS) $(OBJ)
 	$(CC) -o $@ $^ $(LDFLAGS) $(LAPACKLDFLAGS)
 
 deepmatching-static: $(HEADERS) $(OBJ)
 	$(CC) -o $@ $^ $(STATICLAPACKLDFLAGS)
 
 python: $(HEADERS) $(OBJ)
 #	swig -python $(CPYTHONFLAGS) deepmatching.i # not necessary, only do if you have swig compiler
 	g++ $(CFLAGS) -c deepmatching_wrap.c $(CPYTHONFLAGS)
 	g++ -shared $(LDFLAGS) $(LAPACKLDFLAGS) deepmatching_wrap.o $(OBJ) -o _deepmatching.so $(LIBFLAGS) 
 
 clean:
 	rm -f $(OBJ) deepmatching *~ *.pyc .gdb_history deepmatching_wrap.o _deepmatching.so deepmatching.mex???
 
diff --git a/code/external/deepmatching_1.2.2_c++_linux/deepmatching b/code/external/deepmatching_1.2.2_c++_linux/deepmatching
index 41f0134..cf90a25 100755
Binary files a/code/external/deepmatching_1.2.2_c++_linux/deepmatching and b/code/external/deepmatching_1.2.2_c++_linux/deepmatching differ
diff --git a/fiji_script_vertical_combination.py b/fiji_script_vertical_combination.py
index 4b715da..a05ed9d 100644
--- a/fiji_script_vertical_combination.py
+++ b/fiji_script_vertical_combination.py
@@ -1,77 +1,89 @@
 #@String parameter_file
 
 from ij import IJ, ImagePlus
 from ij.io import Opener, FileSaver
 from ij.plugin import RGBStackMerge, StackCombiner, Resizer
 from ij.process import ImageConverter
-from ij.plugin import Resizer
+from ij.plugin import Resizer, ZProjector, ImageCalculator
 
 import json
 
 #import file paths
 json_file = open(parameter_file,'r')
 text = json_file.read()
 files = json.loads(text)
 json_file.close()
 
 #Instanciate necessary classes
 opener = Opener()
 RGB_stack_merge = RGBStackMerge()
 stack_combiner = StackCombiner()
 resizer = Resizer()
+ic = ImageCalculator()
+z_proj = ZProjector()
 
 
 #Open images
-unregistered_GC6s_info = opener.getTiffFileInfo(files['GC6s_input'])
+unregistered_GC6s_info = opener.getTiffFileInfo(files['output_dir']+'/GC6s_preprocessed.tif')
 unregistered_GC6s_imp = opener.openTiffStack(unregistered_GC6s_info)
 
-unregistered_tdTom_info = opener.getTiffFileInfo(files['tdTom_input'])
+unregistered_tdTom_info = opener.getTiffFileInfo(files['output_dir']+'/GC6s_preprocessed.tif')
 unregistered_tdTom_imp = opener.openTiffStack(unregistered_tdTom_info)
 
 registered_GC6s_info = opener.getTiffFileInfo(files['GC6s_registered'])
 registered_GC6s_imp = opener.openTiffStack(registered_GC6s_info)
 
 registered_tdTom_info = opener.getTiffFileInfo(files['tdTom_registered'])
 registered_tdTom_imp = opener.openTiffStack(registered_tdTom_info)
 
 vector_info = opener.getTiffFileInfo(files['vectors_out'])
 vector_imp = opener.openTiffStack(vector_info)
 
 #Convert fluorescence images to 32-bit and adjust brightness
 IJ.run(unregistered_GC6s_imp,"32-bit","slices")
 IJ.run(registered_GC6s_imp,"32-bit","slices")
 IJ.run(unregistered_tdTom_imp,"32-bit","slices")
 IJ.run(registered_tdTom_imp,"32-bit","slices")
 IJ.run(unregistered_GC6s_imp, "Enhance Contrast", "saturated=0.35");
 IJ.run(registered_GC6s_imp, "Enhance Contrast", "saturated=0.35");
 IJ.run(unregistered_tdTom_imp, "Enhance Contrast", "saturated=0.35");
 IJ.run(registered_tdTom_imp, "Enhance Contrast", "saturated=0.35");
 IJ.run(vector_imp, "Enhance Contrast", "saturated=0.35");
 
 #Remove first frame from registered and unregistered stacks
 IJ.run(unregistered_GC6s_imp, "Delete Slice", "")
 IJ.run(registered_GC6s_imp, "Delete Slice", "")
 IJ.run(unregistered_tdTom_imp, "Delete Slice", "")
 IJ.run(registered_tdTom_imp, "Delete Slice", "")
 
 #Upsample to resolution of vector image
 IJ.run(unregistered_GC6s_imp, "Size...", "width=%d height=%d depth=%d interpolation=None" % (vector_imp.getWidth(),vector_imp.getHeight(),vector_imp.getStackSize()))
 IJ.run(registered_GC6s_imp, "Size...", "width=%d height=%d depth=%d interpolation=None" % (vector_imp.getWidth(),vector_imp.getHeight(),vector_imp.getStackSize()))
 IJ.run(unregistered_tdTom_imp, "Size...", "width=%d height=%d depth=%d interpolation=None" % (vector_imp.getWidth(),vector_imp.getHeight(),vector_imp.getStackSize()))
 IJ.run(registered_tdTom_imp, "Size...", "width=%d height=%d depth=%d interpolation=None" % (vector_imp.getWidth(),vector_imp.getHeight(),vector_imp.getStackSize()))
 
 
 #Convert all images to RGB
 unregistered_merged_channels_imp = RGBStackMerge.mergeChannels([unregistered_tdTom_imp, unregistered_GC6s_imp, None],False)
 registered_merged_channels_imp = RGBStackMerge.mergeChannels([registered_tdTom_imp, registered_GC6s_imp, None],False)
 IJ.run(unregistered_merged_channels_imp, "RGB Color", "slices")
 IJ.run(registered_merged_channels_imp, "RGB Color", "slices")
 IJ.run(vector_imp, "RGB Color", "slices")
 
 #Combine image into one (stacked on top of each other)
 two_combined_stack = stack_combiner.combineVertically(unregistered_merged_channels_imp.getStack(), vector_imp.getStack())
 three_combined_stack = stack_combiner.combineVertically(two_combined_stack, registered_merged_channels_imp.getStack())
 
 #Save result
 file_saver_combined_image = FileSaver(ImagePlus('combined',three_combined_stack))
 file_saver_combined_image.saveAsTiffStack(files['column_out'])
+
+##Calculate baseline average intensity
+#n = unregistered_GC6s_imp.getStackSize()
+#unregistered_GC6s_avg_imp = z_proj.run(unregistered_GC6s_imp,"avg")
+#registered_GC6s_avg_imp = z_proj.run(registered_GC6s_imp,"avg")
+#unregistered_tdTom_avg_imp = z_proj.run(unregistered_tdTom_imp,"avg")
+#registered_tdTom_avg_imp = z_proj.run(registered_tdTom_imp,"avg")
+#
+#dF_imp = ic.run("Subtract create 32-bit stack", unregistered_GC6s_imp, unregistered_GC6s_avg_imp)
+#dF_over_F_imp = ic.run("Divide create 32-bit stack", dF_imp,unregistered_GC6s_avg_imp)
diff --git a/files.json b/files.json
index 286e762..1847b01 100644
--- a/files.json
+++ b/files.json
@@ -1,16 +1,16 @@
 {
     "output_dir": "/home/aymanns/Data_R57C10s/2_170608_fly1_007/results",
 
     "GC6s_input": "/home/aymanns/Data_R57C10s/2_170608_fly1_007/GC6s.tif",
     "tdTom_input": "/home/aymanns/Data_R57C10s/2_170608_fly1_007/tdTom.tif",
 
-    "slices_removed": "first=11 increment=1",
+    "slices_removed": "first=251 increment=1",
     
     "GC6s_registered": "/home/aymanns/Data_R57C10s/2_170608_fly1_007/results/warped1.tif",
     "tdTom_registered": "/home/aymanns/Data_R57C10s/2_170608_fly1_007/results/warped2.tif",
     
     "color_flow_out": "/home/aymanns/Data_R57C10s/2_170608_fly1_007/results/color_flow.tif",
     "vectors_out": "/home/aymanns/Data_R57C10s/2_170608_fly1_007/results/vectors.tif",
     
     "column_out": "/home/aymanns/Data_R57C10s/2_170608_fly1_007/results/column.tif"
 }
diff --git a/files_1_170414_fly1_000.json b/files_1_170414_fly1_000.json
new file mode 100644
index 0000000..b2d971e
--- /dev/null
+++ b/files_1_170414_fly1_000.json
@@ -0,0 +1,16 @@
+{
+    "output_dir": "/home/aymanns/Data_R57C10s/1_170414_fly1_000/results",
+
+    "GC6s_input": "/home/aymanns/Data_R57C10s/1_170414_fly1_000/GC6s.tif",
+    "tdTom_input": "/home/aymanns/Data_R57C10s/1_170414_fly1_000/tdTom.tif",
+
+    "slices_removed": "first=201 increment=1",
+    
+    "GC6s_registered": "/home/aymanns/Data_R57C10s/1_170414_fly1_000/results/warped1.tif",
+    "tdTom_registered": "/home/aymanns/Data_R57C10s/1_170414_fly1_000/results/warped2.tif",
+    
+    "color_flow_out": "/home/aymanns/Data_R57C10s/1_170414_fly1_000/results/color_flow.tif",
+    "vectors_out": "/home/aymanns/Data_R57C10s/1_170414_fly1_000/results/vectors.tif",
+    
+    "column_out": "/home/aymanns/Data_R57C10s/1_170414_fly1_000/results/column.tif"
+}
diff --git a/files.json b/files_2_170608_fly1_007.json
similarity index 93%
copy from files.json
copy to files_2_170608_fly1_007.json
index 286e762..8f47af3 100644
--- a/files.json
+++ b/files_2_170608_fly1_007.json
@@ -1,16 +1,16 @@
 {
     "output_dir": "/home/aymanns/Data_R57C10s/2_170608_fly1_007/results",
 
     "GC6s_input": "/home/aymanns/Data_R57C10s/2_170608_fly1_007/GC6s.tif",
     "tdTom_input": "/home/aymanns/Data_R57C10s/2_170608_fly1_007/tdTom.tif",
 
-    "slices_removed": "first=11 increment=1",
+    "slices_removed": "first=201 increment=1",
     
     "GC6s_registered": "/home/aymanns/Data_R57C10s/2_170608_fly1_007/results/warped1.tif",
     "tdTom_registered": "/home/aymanns/Data_R57C10s/2_170608_fly1_007/results/warped2.tif",
     
     "color_flow_out": "/home/aymanns/Data_R57C10s/2_170608_fly1_007/results/color_flow.tif",
     "vectors_out": "/home/aymanns/Data_R57C10s/2_170608_fly1_007/results/vectors.tif",
     
     "column_out": "/home/aymanns/Data_R57C10s/2_170608_fly1_007/results/column.tif"
 }
diff --git a/files_4_170609_fly1_000.json b/files_4_170609_fly1_000.json
new file mode 100644
index 0000000..ab5690d
--- /dev/null
+++ b/files_4_170609_fly1_000.json
@@ -0,0 +1,16 @@
+{
+    "output_dir": "/home/aymanns/Data_R57C10s/4_170609_fly1_000/results",
+
+    "GC6s_input": "/home/aymanns/Data_R57C10s/4_170609_fly1_000/GC6s.tif",
+    "tdTom_input": "/home/aymanns/Data_R57C10s/4_170609_fly1_000/tdTom.tif",
+
+    "slices_removed": "first=201 increment=1",
+    
+    "GC6s_registered": "/home/aymanns/Data_R57C10s/4_170609_fly1_000/results/warped1.tif",
+    "tdTom_registered": "/home/aymanns/Data_R57C10s/4_170609_fly1_000/results/warped2.tif",
+    
+    "color_flow_out": "/home/aymanns/Data_R57C10s/4_170609_fly1_000/results/color_flow.tif",
+    "vectors_out": "/home/aymanns/Data_R57C10s/4_170609_fly1_000/results/vectors.tif",
+    
+    "column_out": "/home/aymanns/Data_R57C10s/4_170609_fly1_000/results/column.tif"
+}
diff --git a/histograms.py b/histograms.py
new file mode 100644
index 0000000..bd32392
--- /dev/null
+++ b/histograms.py
@@ -0,0 +1,63 @@
+from matplotlib import pyplot as plt
+from mpl_toolkits.mplot3d import Axes3D
+import numpy as np
+import glob
+
+path = '.'
+
+n_frames = int(len(glob.glob1(path,"*.dat"))/2)
+
+wx = np.genfromtxt('tmp201804201803wx_frame1.dat', delimiter=',')
+wy = np.genfromtxt('tmp201804201803wy_frame1.dat', delimiter=',')
+
+wx2 = np.square(wx)
+wy2 = np.square(wy)
+l2 = wx2 + wy2
+l = np.sqrt(l2)
+
+lengths = np.empty([n_frames,wx.size])
+lengths[0,:] = l.flatten()
+
+for i in range(1,n_frames):
+
+    wx = np.genfromtxt('tmp201804201803wx_frame{}.dat'.format(i+1), delimiter=',')
+    wy = np.genfromtxt('tmp201804201803wy_frame{}.dat'.format(i+1), delimiter=',')
+    
+    wx2 = np.square(wx)
+    wy2 = np.square(wy)
+    l2 = wx2 + wy2
+    l = np.sqrt(l2)
+    lengths[i,:] = l.flatten()
+
+plt.figure()
+plt.hist(lengths.flatten())
+plt.xlabel('Displacement [pixels]')
+plt.ylabel('Frequency')
+plt.show()
+
+plt.figure()
+plt.hist2d(lengths.flatten(),np.repeat(range(1,n_frames+1),wx.size),bins=9)
+plt.show()
+
+fig = plt.figure()
+ax = fig.add_subplot(111, projection='3d')
+hist, xedges, yedges = np.histogram2d(lengths.flatten(), np.repeat(range(1,n_frames+1),wx.size), bins=9, range=[[0, 50], [1, n_frames]])
+xpos, ypos = np.meshgrid(xedges[:-1], yedges[:-1])
+xpos = xpos.flatten('F')
+ypos = ypos.flatten('F')
+zpos = np.zeros_like(xpos)
+dx = 2.5 * np.ones_like(zpos)
+dy = (n_frames-1)/20*np.ones_like(zpos)
+dz = hist.flatten()
+ax.bar3d(xpos, ypos, zpos, dx, dy, dz, color='b', zsort='average')
+plt.show()
+
+plt.figure()
+max_lengths = np.amax(lengths, axis=1)
+plt.hist(max_lengths)
+plt.show()
+
+plt.figure()
+mean_lengths = np.mean(lengths, axis=1)
+plt.hist(mean_lengths)
+plt.show()
diff --git a/motion_compensate.m b/motion_compensate.m
index ce6818b..f7a7468 100755
--- a/motion_compensate.m
+++ b/motion_compensate.m
@@ -1,77 +1,77 @@
 function motion_compensate(fnInput1,fnInput2,fnMatch,fnDeepMatching,fnOut1,fnOut2,fnColor,fnVector,N,param)
 %% Description
 % Motion is estimated with a brigthness constancy data term defined on fnInput1 
 % and a feature matching similarity term defined on fnMatch. The sequences fnIput1 and
 % fnInput2 are warped according to the estimated motion field.
 % For more details see the paper: "Imaging neural activity in the ventral
 % nerve cord of behaving adult Drosophila", bioRxiv
 %
 %% Input
 % fnInput1: filename of the  sequence used for the brightness constancy term, in TIF format
 % fnInput2: filename of the sequence warped with the motion field estimated from fnInput1 and fnMatch, in TIF format
 % fnMatch: filename of the sequence used for feature matching, in TIF format
 % fnDeepMatching: filename of the deepmatching code
 % fnOut1: filename used to save the warped version of fnInput1, in TIF format
 % fnOut2: filename used to save the warped version of fnInput2, in TIF format
 % fnOut2: filename used to save the color visualization of the estimated motion, in TIF format
 % N: number of frames to process
 % param: parameters of the algorithm (see 'default_parameters.m')
 %
 %     Copyright (C) 2017 D. Fortun, denis.fortun@epfl.ch
 %
 %     This program is free software: you can redistribute it and/or modify
 %     it under the terms of the GNU General Public License as published by
 %     the Free Software Foundation, either version 3 of the License, or
 %     (at your option) any later version.
 %
 %     This program is distributed in the hope that it will be useful,
 %     but WITHOUT ANY WARRANTY; without even the implied warranty of
 %     MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the
 %     GNU General Public License for more details.
 
 %% Input data
 seq=mijread_stack(fnInput1);
 seqW=mijread_stack(fnInput2);
 seqMatch=mijread_stack(fnMatch);
 
 if N==-1
     N=size(seq,3);
 end
 
 seq=double(seq(:,:,1:N));
 seqRescale=(seq-min(seq(:)))/(max(seq(:))-min(seq(:)))*255;
 seqW=double(seqW(:,:,1:N));
 seqMatch=double(seqMatch(:,:,1:N));
 seqMatch=(seqMatch-min(seqMatch(:)))/(max(seqMatch(:))-min(seqMatch(:)))*255;
 
 % Motion estimation
 w=zeros(size(seqRescale,1),size(seqRescale,2),2,size(seqRescale,3)-1);
 colorFlow=zeros(size(seqRescale,1),size(seqRescale,2),3,size(seqRescale,3)-1);
 vectorFlow=zeros(512,512,size(seqRescale,3)-1);
 i1=seqRescale(:,:,1);
 i1Match=seqMatch(:,:,1);
-parfor t=1:N-1 % Replace parfor by for if you don't want to parallelize
+for t=1:N-1 % Replace parfor by for if you don't want to parallelize
     fprintf('Frame %i\n',t);
     i2=seqRescale(:,:,t+1);
     i2Match=seqMatch(:,:,t+1);
 
     [i10,i2]=midway(i1,i2);
 
     w(:,:,:,t) = compute_motion(i10,i2,i1Match,i2Match,fnDeepMatching,param,t);
     colorFlow(:,:,:,t)=flowToColor(w(:,:,:,t));
     vectorFlow(:,:,t)=flowToVectorImage(w(:,:,:,t),15,[512,512],t);
 end
                 
 %% Registration
 seqWarped=seq;
 seqwWarped=seqW;
 parfor t=1:N-1
     seqWarped(:,:,t+1)=warpImg(seq(:,:,t+1),w(:,:,1,t),w(:,:,2,t));
     seqwWarped(:,:,t+1)=warpImg(seqW(:,:,t+1),w(:,:,1,t),w(:,:,2,t));
 end
 
 %% Save
 mijwrite_stack(single(seqWarped),fnOut1);
 mijwrite_stack(single(seqwWarped),fnOut2);
 mijwrite_stack(single(colorFlow),fnColor,1);
 mijwrite_stack(single(vectorFlow),fnVector);
diff --git a/pipeline.run b/pipeline.run
index 1803fad..8841b1d 100644
--- a/pipeline.run
+++ b/pipeline.run
@@ -1,16 +1,19 @@
 #!/bin/bash
+#SBATCH -p debug
 #SBATCH --workdir /home/aymanns/motion-correction-paper
 #SBATCH --nodes 1
 #SBATCH --ntasks 1
 #SBATCH --cpus-per-task 1
-#SBATCH --mem 64000
-#SBATCH --time 02:0:00
+#SBATCH --mem 128000
+#SBATCH --time 01:00:00
 module load matlab
 module load jdk
+module load gcc
+module load openblas/0.2.19-openmp
 echo STARTING at `date`
 /home/aymanns/Fiji.app/ImageJ-linux64 --ij2 --headless --console --run /home/aymanns/motion-correction-paper/preprocessing.py 'parameter_file="files_4_170609_fly1_000.json"'
 echo FINISHED preprocessing at `date`
 matlab -nodesktop -nodisplay -r "test('files_4_170609_fly1_000.json')"
 echo FINISHED Matlab at `date`
 /home/aymanns/Fiji.app/ImageJ-linux64 --ij2 --headless --console --run /home/aymanns/motion-correction-paper/fiji_script_vertical_combination.py 'parameter_file="files_4_170609_fly1_000.json"'
 echo FINISHED Fiji at `date`
diff --git a/pipeline.run b/pipeline2.run
similarity index 65%
copy from pipeline.run
copy to pipeline2.run
index 1803fad..abb7f4a 100644
--- a/pipeline.run
+++ b/pipeline2.run
@@ -1,16 +1,19 @@
 #!/bin/bash
+#SBATCH -p debug
 #SBATCH --workdir /home/aymanns/motion-correction-paper
 #SBATCH --nodes 1
 #SBATCH --ntasks 1
 #SBATCH --cpus-per-task 1
-#SBATCH --mem 64000
-#SBATCH --time 02:0:00
+#SBATCH --mem 128000
+#SBATCH --time 01:00:00
 module load matlab
 module load jdk
+module load gcc
+module load openblas/0.2.19-openmp
 echo STARTING at `date`
-/home/aymanns/Fiji.app/ImageJ-linux64 --ij2 --headless --console --run /home/aymanns/motion-correction-paper/preprocessing.py 'parameter_file="files_4_170609_fly1_000.json"'
+/home/aymanns/Fiji.app/ImageJ-linux64 --ij2 --headless --console --run /home/aymanns/motion-correction-paper/preprocessing.py 'parameter_file="files_2_170608_fly1_007.json"'
 echo FINISHED preprocessing at `date`
-matlab -nodesktop -nodisplay -r "test('files_4_170609_fly1_000.json')"
+matlab -nodesktop -nodisplay -r "test('files_2_170608_fly1_007.json')"
 echo FINISHED Matlab at `date`
-/home/aymanns/Fiji.app/ImageJ-linux64 --ij2 --headless --console --run /home/aymanns/motion-correction-paper/fiji_script_vertical_combination.py 'parameter_file="files_4_170609_fly1_000.json"'
+/home/aymanns/Fiji.app/ImageJ-linux64 --ij2 --headless --console --run /home/aymanns/motion-correction-paper/fiji_script_vertical_combination.py 'parameter_file="files_2_170608_fly1_007.json"'
 echo FINISHED Fiji at `date`
diff --git a/pipeline.run b/pipeline3.run
similarity index 65%
copy from pipeline.run
copy to pipeline3.run
index 1803fad..4c3fb10 100644
--- a/pipeline.run
+++ b/pipeline3.run
@@ -1,16 +1,19 @@
 #!/bin/bash
+#SBATCH -p debug
 #SBATCH --workdir /home/aymanns/motion-correction-paper
 #SBATCH --nodes 1
 #SBATCH --ntasks 1
 #SBATCH --cpus-per-task 1
-#SBATCH --mem 64000
-#SBATCH --time 02:0:00
+#SBATCH --mem 128000
+#SBATCH --time 01:00:00
 module load matlab
 module load jdk
+module load gcc
+module load openblas/0.2.19-openmp
 echo STARTING at `date`
-/home/aymanns/Fiji.app/ImageJ-linux64 --ij2 --headless --console --run /home/aymanns/motion-correction-paper/preprocessing.py 'parameter_file="files_4_170609_fly1_000.json"'
+/home/aymanns/Fiji.app/ImageJ-linux64 --ij2 --headless --console --run /home/aymanns/motion-correction-paper/preprocessing.py 'parameter_file="files_1_170414_fly1_000.json"'
 echo FINISHED preprocessing at `date`
-matlab -nodesktop -nodisplay -r "test('files_4_170609_fly1_000.json')"
+matlab -nodesktop -nodisplay -r "test('files_1_170414_fly1_000.json')"
 echo FINISHED Matlab at `date`
-/home/aymanns/Fiji.app/ImageJ-linux64 --ij2 --headless --console --run /home/aymanns/motion-correction-paper/fiji_script_vertical_combination.py 'parameter_file="files_4_170609_fly1_000.json"'
+/home/aymanns/Fiji.app/ImageJ-linux64 --ij2 --headless --console --run /home/aymanns/motion-correction-paper/fiji_script_vertical_combination.py 'parameter_file="files_1_170414_fly1_000.json"'
 echo FINISHED Fiji at `date`
diff --git a/test.m b/test.m
index 8f74068..3973d45 100755
--- a/test.m
+++ b/test.m
@@ -1,54 +1,58 @@
 function test(fname)
 
+start_time = datestr(now,'yyyymmddHHMM');
+tmpdir = ['/scratch/aymanns/tmp',start_time];
+mkdir(tmpdir);
+
 warn = warning ('off','all');
 poolobj = gcp('nocreate');
 if isempty(poolobj)
     parpool;
 end
 pctRunOnAll warning('off','all')
 
 %% set path
 fnIJ='/home/aymanns/registration/ij.jar';     % Path to "ij.jar"
 fnMIJ='/home/aymanns/registration/mij.jar';   % Path to "mij.jar"
 javaaddpath(fnIJ);
 javaaddpath(fnMIJ);
 addpath('code');
 addpath('code/external/utils');
 addpath(genpath('code/external/InvPbLib'));
 
 %% load file names
 %fname = 'files.json'; 
 fid = fopen(fname); 
 raw = fread(fid,inf); 
 str = char(raw'); 
 fclose(fid); 
 files = parse_json(str);
 
 %% Parameters
 param = default_parameters();
 param.lambda = 1000;    % Regularization parameter
 param.gamma = 100;      % Sets the strength of the feature matching constraint
 
 %% Input - Output
 type=1;                                     % 0 for Mac users, 1 for Linux users
 fnMatch=files.tdTom_input;%'/home/aymanns/data/1_Horizontal_VNC/tdTom.tif';  % Sequence used for the feature matching similarity term
 fnIn1=[files.output_dir,'/GC6s_preprocessed.tif'];     % Sequence used for the brightness constancy term 
 fnIn2=[files.output_dir,'/tdTom_preprocessed.tif'];    % Sequence warped with the motion field estimated from fnIn1 and fnMatch
 N=-1;                                        % Motion is estimated on frames 1 to N. If N=-1, motion is estimated on
                                             % the whole sequence
 
 fnOut1=files.GC6s_registered;              % Sequence fnIn1 warped
 fnOut2=files.tdTom_registered;              % Sequence fnIn2 warped
 fnColor=files.color_flow_out;           % Color visualization of the motion field
 fnVector=files.vectors_out;
 
 if type==0
     fnDeepMatching='code/external/deepmatching_1.2.2_c++_mac';      
 elseif type==1
     fnDeepMatching='code/external/deepmatching_1.2.2_c++_linux';      
 end
 addpath(fnDeepMatching);
 
 %% Perform motion compensation
-motion_compensate(fnIn1,fnIn2,fnMatch,fnDeepMatching,fnOut1,fnOut2,fnColor,fnVector,N,param);
+modified_motion_compensate(fnIn1,fnIn2,fnMatch,fnDeepMatching,fnOut1,fnOut2,fnColor,fnVector,N,param,tmpdir,files.output_dir);
 end