diff --git a/eos-toys/make_toys.py b/eos-toys/make_toys.py
new file mode 100644
index 0000000..1df02ed
--- /dev/null
+++ b/eos-toys/make_toys.py
@@ -0,0 +1,41 @@
+# -*- coding: utf-8 -*-
+# @Author: Elena Graverini
+# @Date:   2017-03-16 15:22:00
+# @Last Modified by:   Elena Graverini
+# @Last Modified time: 2017-03-17 16:42:38
+import os
+# import subprocess
+
+chunk_size = 100000
+chunks = 100
+leptons = ['mu', 'tau']
+commands = []
+seed = 12345
+form_factors = "BBGIOvD2017"
+signal_pdf = "Lambda_b->Lambda_c(2625)lnu::dGamma"
+model = "SM"
+prerun_min = 500000
+prerun_update = 2000
+kin_limits = {
+    'mu': (0.011163612964000001, 8.947815864099999),
+    'tau': (3.1570893124, 8.947815864099999),
+}
+
+commands = []
+for l in leptons:
+    commands.append(['eos-sample-events-mcmc',
+                     # '  --kinematics \"s\" %s %s' % kin_limits[l],
+                     '  --global-option \"form-factors\" \"%s\"' % form_factors,
+                     '  --signal-pdf \"%s,l=%s,model=%s\"' % (signal_pdf, l, model),
+                     '  --seed %s' % seed,
+                     '  --output mcmc_samples-%s.hdf5' % l,
+                     '  --prerun-min %s' % prerun_min,
+                     '  --prerun-update %s' % prerun_update,
+                     '  --chunk-size %s' % chunk_size,
+                     '  --chunks %s' % chunks,
+                     ])
+
+for c in commands:
+    print(' '.join(c))
+    # subprocess.call(c)
+    os.system(' '.join(c))
diff --git a/eos-toys/plot-sample.py b/eos-toys/plot-sample.py
new file mode 100644
index 0000000..bf979bc
--- /dev/null
+++ b/eos-toys/plot-sample.py
@@ -0,0 +1,82 @@
+# -*- coding: utf-8 -*-
+# @Author: Elena Graverini
+# @Date:   2017-03-16 11:20:45
+# @Last Modified by:   Elena Graverini
+# @Last Modified time: 2017-03-21 11:38:40
+# import matplotlib
+from __future__ import division
+import sys, os, gc
+import matplotlib.pyplot as plt
+from eosdata import MCMCDataFile  # , Plotter1D
+import pickle
+
+
+def main():
+    input_file = "constantFF/samples-mu-2.hdf5"
+    save_name = 'test-output.pdf'
+    if len(sys.argv) > 1:
+        input_file = str(sys.argv[1])
+    else:
+        print('Warning: no input / output file names specified.\nUsing %s and %s.' % (input_file, save_name))
+    if len(sys.argv) > 2:
+        save_name = str(sys.argv[2])
+    pklfilename = save_name.replace('.pdf', '.pkl')
+    suffix = 'prescaled_10'
+    if not os.path.isfile(pklfilename):
+        datafile = MCMCDataFile(input_file)
+        # print(datafile.parameters[0])
+        gc.collect()
+        data = datafile.data()[:, 0]
+        d = {}
+        reduced_data = data[::10]
+        d['reduced_data'] = reduced_data
+        n, bins, patches = plt.hist(reduced_data, bins=100, normed=True, alpha=0.3)
+        bin_centers = (bins[:-1] + bins[1:]) / 2
+        d['bin_contents'] = n
+        d['bin_centers'] = bin_centers
+        pickle.dump(d, open(pklfilename, 'wb'))
+    else:
+        d = pickle.load(open(pklfilename, 'rb'))
+        plt.scatter(d['bin_centers'], d['bin_contents'])
+        suffix += '_scatter'
+    plt.savefig(save_name.replace('.pdf', '_%s.pdf' % suffix))
+    # # plt.figure()
+    # p1d = Plotter1D(datafile, save_name)
+    # p1d.histogram(0, xmin=None, xmax=None, kde=None)
+
+
+def superimpose(files, labels, outname):
+    colors = ['#0078FF', '#FF6600', '#0AAFB6', '#FF3333', '#0000FF', '#00CC00', '#BF8040', '#FF33CC', '#FF7733']
+    ds = []
+    for f in files:
+        ds.append(pickle.load(open(f, 'rb')))
+    for i in range(len(files)):
+        plt.plot(ds[i]['bin_centers'], ds[i]['bin_contents'], label=labels[i], color=colors[i], linewidth=2.0)
+    plt.legend(loc='best')
+    plt.savefig(outname)
+    plt.close("all")
+
+
+def makeFileFromMarzia(x, y, fname):
+    ds = {
+        'bin_centers': x,
+        'bin_contents': y,
+    }
+    if not os.path.isfile(fname):
+        os.system('mkdir -p %s' % os.path.dirname(fname))
+        pickle.dump(ds, open(fname, 'wb'))
+
+
+if __name__ == '__main__':
+    # main()
+    marzia_f = 'Marzia/Marzia_constantFF.pkl'
+    mx = [0.2, 0.4, 0.80, 1, 1.5, 2, 2.5, 3, 3.5, 4, 4.5, 5, 5.5, 6, 6.5, 7, 7.5, 8, 8.5]
+    my = [0.0102553, 0.0110076, 0.0123026, 0.0128953, 0.0142323, 0.015366, 0.0162975, 0.0170258, 0.0175493, 0.0178644, 0.0179659, 0.0178455, 0.017491, 0.016884, 0.0159959, 0.0147803, 0.0131556, 0.0109562, 0.00773188]
+    makeFileFromMarzia(mx, my, marzia_f)
+    files_mu = ['constantFF/mcmc_gamma_muons.pkl', '1pole/mcmc_gamma_muons_1pole.pkl', '1pole_x_sqrtlambda/mcmc_gamma_muonss_1pole_x_sqrtlambda.pkl', marzia_f]
+    out_mu = 'comparison_mu.pdf'
+    files_tau = ['constantFF/mcmc_gamma_taus.pkl', '1pole/mcmc_gamma_taus_1pole.pkl', '1pole_x_sqrtlambda/mcmc_gamma_taus_1pole_x_sqrtlambda.pkl']
+    out_tau = 'comparison_tau.pdf'
+    labels = ['Constant FF', 'One pole', r'One pole $\times\; \sqrt{\lambda}$', 'MB: constant FF']
+    superimpose(files_mu, labels, out_mu)
+    superimpose(files_tau, labels, out_tau)
diff --git a/eos-toys/run.sh b/eos-toys/run.sh
new file mode 100644
index 0000000..cf0b843
--- /dev/null
+++ b/eos-toys/run.sh
@@ -0,0 +1,11 @@
+# @Author: Elena Graverini
+# @Date:   2017-03-21 14:08:36
+# @Last Modified by:   Elena Graverini
+# @Last Modified time: 2017-03-21 14:10:49
+#!/bin/bash
+python make_toys.py
+# TODO:
+# ...Move outputs to appropriate folder according to
+# their parametrization and then go on...
+python plot-sample.py
+bash send_to_zurich.sh
diff --git a/eos-toys/send_to_zurich.sh b/eos-toys/send_to_zurich.sh
new file mode 100755
index 0000000..9aebbc7
--- /dev/null
+++ b/eos-toys/send_to_zurich.sh
@@ -0,0 +1,11 @@
+# @Author: Elena Graverini
+# @Date:   2017-03-21 13:55:51
+# @Last Modified by:   Elena Graverini
+# @Last Modified time: 2017-03-21 16:22:06
+#!/bin/bash
+mkdir -p /home/elena/Desktop/PhD_Work/zurich-cluster
+sshfs egraveri@grid-ui.physik.uzh.ch: /home/elena/Desktop/PhD_Work/zurich-cluster
+cd ..
+rsync -rd eos-toys /home/elena/Desktop/PhD_Work/zurich-cluster/Public/eos-toys
+cd eos-toys
+fusermount -u /home/elena/Desktop/PhD_Work/zurich-cluster || sudo umount -l /home/elena/Documents/University/PhD/UZH/zurich-cluster
diff --git a/make_toys.py b/make_toys.py
deleted file mode 100644
index 1df02ed..0000000
--- a/make_toys.py
+++ /dev/null
@@ -1,41 +0,0 @@
-# -*- coding: utf-8 -*-
-# @Author: Elena Graverini
-# @Date:   2017-03-16 15:22:00
-# @Last Modified by:   Elena Graverini
-# @Last Modified time: 2017-03-17 16:42:38
-import os
-# import subprocess
-
-chunk_size = 100000
-chunks = 100
-leptons = ['mu', 'tau']
-commands = []
-seed = 12345
-form_factors = "BBGIOvD2017"
-signal_pdf = "Lambda_b->Lambda_c(2625)lnu::dGamma"
-model = "SM"
-prerun_min = 500000
-prerun_update = 2000
-kin_limits = {
-    'mu': (0.011163612964000001, 8.947815864099999),
-    'tau': (3.1570893124, 8.947815864099999),
-}
-
-commands = []
-for l in leptons:
-    commands.append(['eos-sample-events-mcmc',
-                     # '  --kinematics \"s\" %s %s' % kin_limits[l],
-                     '  --global-option \"form-factors\" \"%s\"' % form_factors,
-                     '  --signal-pdf \"%s,l=%s,model=%s\"' % (signal_pdf, l, model),
-                     '  --seed %s' % seed,
-                     '  --output mcmc_samples-%s.hdf5' % l,
-                     '  --prerun-min %s' % prerun_min,
-                     '  --prerun-update %s' % prerun_update,
-                     '  --chunk-size %s' % chunk_size,
-                     '  --chunks %s' % chunks,
-                     ])
-
-for c in commands:
-    print(' '.join(c))
-    # subprocess.call(c)
-    os.system(' '.join(c))
diff --git a/plot-sample.py b/plot-sample.py
deleted file mode 100644
index bf979bc..0000000
--- a/plot-sample.py
+++ /dev/null
@@ -1,82 +0,0 @@
-# -*- coding: utf-8 -*-
-# @Author: Elena Graverini
-# @Date:   2017-03-16 11:20:45
-# @Last Modified by:   Elena Graverini
-# @Last Modified time: 2017-03-21 11:38:40
-# import matplotlib
-from __future__ import division
-import sys, os, gc
-import matplotlib.pyplot as plt
-from eosdata import MCMCDataFile  # , Plotter1D
-import pickle
-
-
-def main():
-    input_file = "constantFF/samples-mu-2.hdf5"
-    save_name = 'test-output.pdf'
-    if len(sys.argv) > 1:
-        input_file = str(sys.argv[1])
-    else:
-        print('Warning: no input / output file names specified.\nUsing %s and %s.' % (input_file, save_name))
-    if len(sys.argv) > 2:
-        save_name = str(sys.argv[2])
-    pklfilename = save_name.replace('.pdf', '.pkl')
-    suffix = 'prescaled_10'
-    if not os.path.isfile(pklfilename):
-        datafile = MCMCDataFile(input_file)
-        # print(datafile.parameters[0])
-        gc.collect()
-        data = datafile.data()[:, 0]
-        d = {}
-        reduced_data = data[::10]
-        d['reduced_data'] = reduced_data
-        n, bins, patches = plt.hist(reduced_data, bins=100, normed=True, alpha=0.3)
-        bin_centers = (bins[:-1] + bins[1:]) / 2
-        d['bin_contents'] = n
-        d['bin_centers'] = bin_centers
-        pickle.dump(d, open(pklfilename, 'wb'))
-    else:
-        d = pickle.load(open(pklfilename, 'rb'))
-        plt.scatter(d['bin_centers'], d['bin_contents'])
-        suffix += '_scatter'
-    plt.savefig(save_name.replace('.pdf', '_%s.pdf' % suffix))
-    # # plt.figure()
-    # p1d = Plotter1D(datafile, save_name)
-    # p1d.histogram(0, xmin=None, xmax=None, kde=None)
-
-
-def superimpose(files, labels, outname):
-    colors = ['#0078FF', '#FF6600', '#0AAFB6', '#FF3333', '#0000FF', '#00CC00', '#BF8040', '#FF33CC', '#FF7733']
-    ds = []
-    for f in files:
-        ds.append(pickle.load(open(f, 'rb')))
-    for i in range(len(files)):
-        plt.plot(ds[i]['bin_centers'], ds[i]['bin_contents'], label=labels[i], color=colors[i], linewidth=2.0)
-    plt.legend(loc='best')
-    plt.savefig(outname)
-    plt.close("all")
-
-
-def makeFileFromMarzia(x, y, fname):
-    ds = {
-        'bin_centers': x,
-        'bin_contents': y,
-    }
-    if not os.path.isfile(fname):
-        os.system('mkdir -p %s' % os.path.dirname(fname))
-        pickle.dump(ds, open(fname, 'wb'))
-
-
-if __name__ == '__main__':
-    # main()
-    marzia_f = 'Marzia/Marzia_constantFF.pkl'
-    mx = [0.2, 0.4, 0.80, 1, 1.5, 2, 2.5, 3, 3.5, 4, 4.5, 5, 5.5, 6, 6.5, 7, 7.5, 8, 8.5]
-    my = [0.0102553, 0.0110076, 0.0123026, 0.0128953, 0.0142323, 0.015366, 0.0162975, 0.0170258, 0.0175493, 0.0178644, 0.0179659, 0.0178455, 0.017491, 0.016884, 0.0159959, 0.0147803, 0.0131556, 0.0109562, 0.00773188]
-    makeFileFromMarzia(mx, my, marzia_f)
-    files_mu = ['constantFF/mcmc_gamma_muons.pkl', '1pole/mcmc_gamma_muons_1pole.pkl', '1pole_x_sqrtlambda/mcmc_gamma_muonss_1pole_x_sqrtlambda.pkl', marzia_f]
-    out_mu = 'comparison_mu.pdf'
-    files_tau = ['constantFF/mcmc_gamma_taus.pkl', '1pole/mcmc_gamma_taus_1pole.pkl', '1pole_x_sqrtlambda/mcmc_gamma_taus_1pole_x_sqrtlambda.pkl']
-    out_tau = 'comparison_tau.pdf'
-    labels = ['Constant FF', 'One pole', r'One pole $\times\; \sqrt{\lambda}$', 'MB: constant FF']
-    superimpose(files_mu, labels, out_mu)
-    superimpose(files_tau, labels, out_tau)
diff --git a/run.sh b/run.sh
deleted file mode 100644
index cf0b843..0000000
--- a/run.sh
+++ /dev/null
@@ -1,11 +0,0 @@
-# @Author: Elena Graverini
-# @Date:   2017-03-21 14:08:36
-# @Last Modified by:   Elena Graverini
-# @Last Modified time: 2017-03-21 14:10:49
-#!/bin/bash
-python make_toys.py
-# TODO:
-# ...Move outputs to appropriate folder according to
-# their parametrization and then go on...
-python plot-sample.py
-bash send_to_zurich.sh
diff --git a/send_to_zurich.sh b/send_to_zurich.sh
deleted file mode 100755
index ef4522a..0000000
--- a/send_to_zurich.sh
+++ /dev/null
@@ -1,11 +0,0 @@
-# @Author: Elena Graverini
-# @Date:   2017-03-21 13:55:51
-# @Last Modified by:   Elena Graverini
-# @Last Modified time: 2017-03-21 14:01:52
-#!/bin/bash
-mkdir -p /home/elena/Desktop/PhD_Work/zurich-cluster
-sshfs egraveri@grid-ui.physik.uzh.ch: /home/elena/Desktop/PhD_Work/zurich-cluster
-cd ..
-rsync -rd LbLcsFFAnalysis /home/elena/Desktop/PhD_Work/zurich-cluster/Public/LbLcsFFAnalysis
-cd LbLcsFFAnalysis
-fusermount -u /home/elena/Desktop/PhD_Work/zurich-cluster || sudo umount -l /home/elena/Documents/University/PhD/UZH/zurich-cluster