From 7d57faf12a6748026f95bbb2fe55c700c40287f9 Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?Mikkel=20Elle=20Lepper=C3=B8d?= Date: Mon, 16 Dec 2019 16:16:33 +0100 Subject: [PATCH] statistics update --- .../data/20_comparisons_gridcells.html | 1404 ++--------------- .../data/20_comparisons_gridcells.ipynb | 1274 ++------------- .../data/figures/average_rate.svg | 2 +- .../data/figures/average_rate_11.svg | 2 +- .../data/figures/average_rate_30.svg | 2 +- .../data/figures/burst_event_ratio.svg | 2 +- .../data/figures/burst_event_ratio_11.svg | 2 +- .../data/figures/burst_event_ratio_30.svg | 2 +- .../data/figures/bursty_spike_ratio.svg | 2 +- .../data/figures/bursty_spike_ratio_11.svg | 2 +- .../data/figures/bursty_spike_ratio_30.svg | 2 +- .../data/figures/gridness.svg | 2 +- .../data/figures/gridness_11.svg | 2 +- .../data/figures/gridness_30.svg | 2 +- .../data/figures/in_field_mean_rate.svg | 2 +- .../data/figures/in_field_mean_rate_11.svg | 2 +- .../data/figures/in_field_mean_rate_30.svg | 2 +- .../data/figures/information_specificity.svg | 2 +- .../figures/information_specificity_11.svg | 2 +- .../figures/information_specificity_30.svg | 2 +- .../data/figures/isi_cv.svg | 2 +- .../data/figures/isi_cv_11.svg | 2 +- .../data/figures/isi_cv_30.svg | 2 +- .../data/figures/max_field_mean_rate.svg | 2 +- .../data/figures/max_field_mean_rate_11.svg | 2 +- .../data/figures/max_field_mean_rate_30.svg | 2 +- .../data/figures/max_rate.svg | 2 +- .../data/figures/max_rate_11.svg | 2 +- .../data/figures/max_rate_30.svg | 2 +- .../data/figures/out_field_mean_rate.svg | 2 +- .../data/figures/out_field_mean_rate_11.svg | 2 +- .../data/figures/out_field_mean_rate_30.svg | 2 +- .../data/figures/spatial_information.svg | 2 +- .../data/figures/spatial_information_11.svg | 2 +- .../data/figures/spatial_information_30.svg | 2 +- .../data/figures/specificity.svg | 2 +- .../data/figures/specificity_11.svg | 2 +- .../data/figures/specificity_30.svg | 2 +- .../data/figures/speed_score.svg | 2 +- .../data/figures/speed_score_11.svg | 2 +- .../data/figures/speed_score_30.svg | 2 +- .../data/figures/speed_score_ns_inhibited.svg | 2 +- .../data/statistics/statistics.csv | 33 +- .../data/statistics/statistics.tex | 22 +- .../data/statistics/statistics_11.csv | 33 +- .../data/statistics/statistics_11.tex | 24 +- .../data/statistics/statistics_11_vs_30.csv | 33 +- .../data/statistics/statistics_11_vs_30.tex | 22 +- .../data/statistics/statistics_30.csv | 33 +- .../data/statistics/statistics_30.tex | 24 +- .../data/statistics/statistics_b_i_30.csv | 33 +- .../data/statistics/statistics_b_i_30.tex | 24 +- .../statistics_base_i_vs_base_ii.csv | 33 +- .../statistics_base_i_vs_base_ii.tex | 20 +- ...20_longitudinal_comparisons_gridcells.html | 331 +++- ...0_longitudinal_comparisons_gridcells.ipynb | 325 +++- .../data/figures/violins_swarm.png | Bin 115245 -> 116008 bytes .../data/figures/violins_swarm.svg | 4 +- .../data/statistics/MWU.csv | 5 + .../data/statistics/MWU.tex | 10 + .../data/statistics/PRS.csv | 5 + .../data/statistics/PRS.tex | 10 + .../data/statistics/summary.csv | 5 + .../data/statistics/summary.tex | 10 + .../data/20_spikes_in_field.html | 328 +++- .../data/20_spikes_in_field.ipynb | 278 +++- .../data/figures/stim_field_spikes_11.svg | 2 +- .../data/figures/stim_field_spikes_30.svg | 2 +- .../figures/stim_field_spikes_combined.svg | 2 +- .../figures/stim_field_spikes_example.svg | 2 +- .../data/statistics/statistics.csv | 4 + .../data/statistics/statistics.tex | 9 + .../data/20_stimulus-lfp-response.html | 109 +- .../data/20_stimulus-lfp-response.ipynb | 107 +- .../figures/lfp-psd-histogram-stim_energy.svg | 2 +- .../lfp-psd-histogram-stim_half_width.svg | 2 +- .../figures/lfp-psd-histogram-stim_p_max.svg | 2 +- .../lfp-psd-histogram-stim_strength.svg | 2 +- .../lfp-psd-histogram-theta_energy.svg | 2 +- .../figures/lfp-psd-histogram-theta_freq.svg | 2 +- .../lfp-psd-histogram-theta_half_width.svg | 2 +- .../figures/lfp-psd-histogram-theta_peak.svg | 2 +- .../data/figures/lfp-psd.png | Bin 48277 -> 48146 bytes .../data/figures/lfp-psd.svg | 4 +- .../data/statistics/statistics.csv | 39 +- .../data/statistics/statistics.tex | 10 +- .../data/20_stimulus-spike-lfp-response.html | 171 +- .../data/20_stimulus-spike-lfp-response.ipynb | 151 +- .../figures/spike-lfp-coherence-gridcell.png | Bin 62602 -> 62591 bytes .../figures/spike-lfp-coherence-gridcell.svg | 4 +- ...herence-histogram-stim_energy-gridcell.svg | 2 +- ...nce-histogram-stim_energy-ns_inhibited.svg | 2 +- ...histogram-stim_energy-ns_not_inhibited.svg | 2 +- ...nce-histogram-stim_half_width-gridcell.svg | 2 +- ...histogram-stim_half_width-ns_inhibited.svg | 2 +- ...ogram-stim_half_width-ns_not_inhibited.svg | 2 +- ...oherence-histogram-stim_p_max-gridcell.svg | 2 +- ...ence-histogram-stim_p_max-ns_inhibited.svg | 2 +- ...-histogram-stim_p_max-ns_not_inhibited.svg | 2 +- ...rence-histogram-stim_strength-gridcell.svg | 2 +- ...e-histogram-stim_strength-ns_inhibited.svg | 2 +- ...stogram-stim_strength-ns_not_inhibited.svg | 2 +- ...erence-histogram-theta_energy-gridcell.svg | 2 +- ...ce-histogram-theta_energy-ns_inhibited.svg | 2 +- ...istogram-theta_energy-ns_not_inhibited.svg | 2 +- ...oherence-histogram-theta_freq-gridcell.svg | 2 +- ...ence-histogram-theta_freq-ns_inhibited.svg | 2 +- ...-histogram-theta_freq-ns_not_inhibited.svg | 2 +- ...ce-histogram-theta_half_width-gridcell.svg | 2 +- ...istogram-theta_half_width-ns_inhibited.svg | 2 +- ...gram-theta_half_width-ns_not_inhibited.svg | 2 +- ...oherence-histogram-theta_peak-gridcell.svg | 2 +- ...ence-histogram-theta_peak-ns_inhibited.svg | 2 +- ...-histogram-theta_peak-ns_not_inhibited.svg | 2 +- .../spike-lfp-coherence-ns_inhibited.png | Bin 76613 -> 76558 bytes .../spike-lfp-coherence-ns_inhibited.svg | 4 +- .../spike-lfp-coherence-ns_not_inhibited.png | Bin 67404 -> 67432 bytes .../spike-lfp-coherence-ns_not_inhibited.svg | 4 +- .../data/statistics/statistics_gridcell.csv | 39 +- .../data/statistics/statistics_gridcell.tex | 10 +- .../statistics/statistics_ns_inhibited.csv | 39 +- .../statistics/statistics_ns_inhibited.tex | 8 +- .../statistics_ns_not_inhibited.csv | 39 +- .../statistics_ns_not_inhibited.tex | 8 +- 124 files changed, 1828 insertions(+), 3406 deletions(-) create mode 100644 actions/longitudinal-comparisons-gridcells/data/statistics/MWU.csv create mode 100644 actions/longitudinal-comparisons-gridcells/data/statistics/MWU.tex create mode 100644 actions/longitudinal-comparisons-gridcells/data/statistics/PRS.csv create mode 100644 actions/longitudinal-comparisons-gridcells/data/statistics/PRS.tex create mode 100644 actions/longitudinal-comparisons-gridcells/data/statistics/summary.csv create mode 100644 actions/longitudinal-comparisons-gridcells/data/statistics/summary.tex create mode 100644 actions/spikes-in-field/data/statistics/statistics.csv create mode 100644 actions/spikes-in-field/data/statistics/statistics.tex diff --git a/actions/comparisons-gridcells/data/20_comparisons_gridcells.html b/actions/comparisons-gridcells/data/20_comparisons_gridcells.html index 5c43c938e..ade8ee0f1 100644 --- a/actions/comparisons-gridcells/data/20_comparisons_gridcells.html +++ b/actions/comparisons-gridcells/data/20_comparisons_gridcells.html @@ -13115,7 +13115,7 @@ div#notebook {
-
In [2]:
+
In [1]:
%load_ext autoreload
@@ -13129,7 +13129,7 @@ div#notebook {
-
In [3]:
+
In [2]:
import os
@@ -13168,7 +13168,7 @@ div#notebook {
 
 
 

-
13:03:48 [I] klustakwik KlustaKwik2 version 0.2.6
+
12:51:51 [I] klustakwik KlustaKwik2 version 0.2.6
 /home/mikkel/.virtualenvs/expipe/lib/python3.6/importlib/_bootstrap.py:219: RuntimeWarning: numpy.ufunc size changed, may indicate binary incompatibility. Expected 192 from C header, got 216 from PyObject
   return f(*args, **kwds)
 /home/mikkel/.virtualenvs/expipe/lib/python3.6/importlib/_bootstrap.py:219: RuntimeWarning: numpy.ufunc size changed, may indicate binary incompatibility. Expected 192 from C header, got 216 from PyObject
@@ -13183,7 +13183,7 @@ div#notebook {
 

 

 

-
In [4]:

+
In [3]:

 

     

 
project_path = dp.project_path()
@@ -13209,7 +13209,7 @@ div#notebook {
 

 

 

-
In [5]:

+
In [4]:

 

     

 
statistics_action = actions['calculate-statistics']
@@ -13232,7 +13232,7 @@ div#notebook {
 
 

 
-    
Out[5]:

+    
Out[4]:

 
 
 
@@ -13413,7 +13413,7 @@ div#notebook {
 

 

 

-
In [6]:

+
In [5]:

 

     

 
shuffling = actions['shuffling']
@@ -13431,7 +13431,7 @@ div#notebook {
 
 

 
-    
Out[6]:

+    
Out[5]:

 
 
 
@@ -13539,7 +13539,7 @@ div#notebook {
 

 

 

-
In [7]:

+
In [6]:

 

     

 
action_columns = ['action', 'channel_group', 'unit_name']
@@ -13560,7 +13560,7 @@ div#notebook {
 
 

 
-    
Out[7]:

+    
Out[6]:

 
 
 
@@ -13748,7 +13748,7 @@ div#notebook {
 

 

 

-
In [8]:

+
In [7]:

 

     

 
data.groupby('stimulated').count()['action']
@@ -13764,7 +13764,7 @@ div#notebook {
 
 

 
-    
Out[8]:

+    
Out[7]:

 
 
 
@@ -13784,7 +13784,7 @@ Name: action, dtype: int64

 

 

 

-
In [9]:

+
In [8]:

 

     

 
data['unit_day'] = data.apply(lambda x: str(x.unit_idnum) + '_' + x.action.split('-')[1], axis=1)
@@ -13804,7 +13804,7 @@ Name: action, dtype: int64

 

 

 

-
In [10]:

+
In [9]:

 

     

 
query = (
@@ -13844,7 +13844,7 @@ Number of animals 4
 

 

 

-
In [11]:

+
In [10]:

 

     

 
gridcell_sessions = data[data.unit_day.isin(sessions_above_threshold.unit_day.values)]
@@ -13857,7 +13857,7 @@ Number of animals 4
 

 

 

-
In [12]:

+
In [11]:

 

     

 
print("Number of gridcells", gridcell_sessions.unit_idnum.nunique())
@@ -13892,7 +13892,7 @@ Number of animals 4
 

 

 

-
In [13]:

+
In [12]:

 

     

 
baseline_i = gridcell_sessions.query('baseline and Hz11')
@@ -13943,7 +13943,7 @@ Number of gridcells in stimulated 30Hz ms sessions 40
 

 

 

-
In [14]:

+
In [13]:

 

     

 
baseline_i = baseline_i.drop_duplicates('unit_id')
@@ -13959,7 +13959,7 @@ Number of gridcells in stimulated 30Hz ms sessions 40
 

 

 

-
In [15]:

+
In [14]:

 

     

 
print("Number of gridcells in baseline i sessions", len(baseline_i))
@@ -14004,7 +14004,7 @@ Number of gridcells in stimulated 30Hz ms sessions 38
 

 

 

-
In [16]:

+
In [15]:

 

     

 
columns = [
@@ -14022,7 +14022,7 @@ Number of gridcells in stimulated 30Hz ms sessions 38
 

 

 

-
In [17]:

+
In [16]:

 

     

 
gridcell_sessions.groupby('stimulated')[columns].mean()
@@ -14038,7 +14038,7 @@ Number of gridcells in stimulated 30Hz ms sessions 38
 
 

 
-    
Out[17]:

+    
Out[16]:

 
 
 
@@ -14138,7 +14138,7 @@ Number of gridcells in stimulated 30Hz ms sessions 38
 

 

 

-
In [18]:

+
In [17]:

 

     

 
gridcell_sessions.query('baseline')[columns].describe()
@@ -14154,7 +14154,7 @@ Number of gridcells in stimulated 30Hz ms sessions 38
 
 

 
-    
Out[18]:

+    
Out[17]:

 
 
 
@@ -14334,7 +14334,7 @@ Number of gridcells in stimulated 30Hz ms sessions 38
 

 

 

-
In [19]:

+
In [18]:

 

     

 
gridcell_sessions.query("stimulated")[columns].describe()
@@ -14350,7 +14350,7 @@ Number of gridcells in stimulated 30Hz ms sessions 38
 
 

 
-    
Out[19]:

+    
Out[18]:

 
 
 
@@ -14596,7 +14596,7 @@ Number of gridcells in stimulated 30Hz ms sessions 38
 result['PRS'] = list(map(lambda x: PRS(x, _stim_data, _base_data), columns))
 
 result.to_latex(output_path / "statistics" / "statistics.tex")
-result.to_latex(output_path / "statistics" / "statistics.csv")
+result.to_csv(output_path / "statistics" / "statistics.csv")
 result
 

 
@@ -14645,14 +14645,14 @@ Number of gridcells in stimulated 30Hz ms sessions 38
       8.61 ± 0.75 (71)
       8.39 ± 0.60 (102)
       3599.00, 0.947
-      0.55, 0.764
+      0.55, 0.757
     
     
       Gridness
       0.51 ± 0.04 (71)
       0.44 ± 0.04 (102)
       3208.00, 0.203
-      0.13, 0.141
+      0.13, 0.145
     
     
       Sparsity
@@ -14666,63 +14666,63 @@ Number of gridcells in stimulated 30Hz ms sessions 38
       5.91 ± 0.37 (71)
       5.98 ± 0.37 (102)
       3460.00, 0.620
-      0.10, 0.869
+      0.10, 0.874
     
     
       Information specificity
       0.25 ± 0.03 (71)
       0.22 ± 0.02 (102)
       2944.00, 0.037
-      0.05, 0.033
+      0.05, 0.034
     
     
       Max rate
       36.55 ± 1.78 (71)
       33.72 ± 1.31 (102)
       3291.00, 0.309
-      3.19, 0.195
+      3.19, 0.194
     
     
       Information rate
       1.30 ± 0.07 (71)
       0.96 ± 0.06 (102)
       2385.00, 0.000
-      0.32, 0.000
+      0.32, 0.001
     
     
       Interspike interval cv
       2.42 ± 0.10 (71)
       2.22 ± 0.08 (102)
       3034.00, 0.070
-      0.12, 0.392
+      0.12, 0.398
     
     
       In-field mean rate
       14.43 ± 1.00 (71)
       12.94 ± 0.71 (102)
       3368.00, 0.436
-      0.39, 0.812
+      0.39, 0.817
     
     
       Out-field mean rate
       6.05 ± 0.62 (71)
       6.12 ± 0.53 (102)
       3600.00, 0.950
-      0.08, 0.946
+      0.08, 0.944
     
     
       Burst event ratio
       0.22 ± 0.01 (71)
       0.20 ± 0.01 (102)
       3090.00, 0.102
-      0.02, 0.124
+      0.02, 0.129
     
     
       Specificity
       0.48 ± 0.03 (71)
       0.46 ± 0.02 (102)
       3268.00, 0.277
-      0.06, 0.356
+      0.06, 0.360
     
     
       Speed score
@@ -14763,7 +14763,7 @@ Number of gridcells in stimulated 30Hz ms sessions 38
 
 
 result.to_latex(output_path / "statistics" / "statistics_11.tex")
-result.to_latex(output_path / "statistics" / "statistics_11.csv")
+result.to_csv(output_path / "statistics" / "statistics_11.csv")
 result
 

 
@@ -14812,70 +14812,70 @@ Number of gridcells in stimulated 30Hz ms sessions 38
       8.96 ± 0.80 (63)
       8.80 ± 0.85 (58)
       1781.00, 0.813
-      0.04, 0.972
+      0.04, 0.968
     
     
       Gridness
       0.53 ± 0.05 (63)
       0.41 ± 0.05 (58)
       1459.00, 0.057
-      0.21, 0.043
+      0.21, 0.041
     
     
       Sparsity
       0.63 ± 0.02 (63)
       0.67 ± 0.03 (58)
       2138.00, 0.107
-      0.07, 0.119
+      0.07, 0.128
     
     
       Selectivity
       5.76 ± 0.40 (63)
       5.69 ± 0.50 (58)
       1687.00, 0.469
-      0.00, 0.982
+      0.00, 0.983
     
     
       Information specificity
       0.24 ± 0.03 (63)
       0.21 ± 0.03 (58)
       1452.00, 0.052
-      0.06, 0.032
+      0.06, 0.030
     
     
       Max rate
       37.39 ± 1.91 (63)
       33.11 ± 1.85 (58)
       1538.00, 0.134
-      4.06, 0.122
+      4.06, 0.125
     
     
       Information rate
       1.31 ± 0.08 (63)
       0.94 ± 0.08 (58)
       1143.00, 0.000
-      0.32, 0.003
+      0.32, 0.004
     
     
       Interspike interval cv
       2.39 ± 0.10 (63)
       2.19 ± 0.12 (58)
       1462.00, 0.059
-      0.18, 0.135
+      0.18, 0.139
     
     
       In-field mean rate
       14.88 ± 1.05 (63)
       13.27 ± 1.04 (58)
       1633.00, 0.315
-      0.77, 0.688
+      0.77, 0.690
     
     
       Out-field mean rate
       6.37 ± 0.67 (63)
       6.57 ± 0.77 (58)
       1795.00, 0.870
-      0.47, 0.724
+      0.47, 0.719
     
     
       Burst event ratio
@@ -14889,14 +14889,14 @@ Number of gridcells in stimulated 30Hz ms sessions 38
       0.47 ± 0.03 (63)
       0.44 ± 0.03 (58)
       1605.00, 0.250
-      0.06, 0.398
+      0.06, 0.414
     
     
       Speed score
       0.14 ± 0.01 (63)
       0.11 ± 0.01 (58)
       1378.00, 0.020
-      0.04, 0.023
+      0.04, 0.022
     
   
 
@@ -14929,7 +14929,7 @@ Number of gridcells in stimulated 30Hz ms sessions 38
 
 
 result.to_latex(output_path / "statistics" / "statistics_30.tex")
-result.to_latex(output_path / "statistics" / "statistics_30.csv")
+result.to_csv(output_path / "statistics" / "statistics_30.csv")
 result
 

 
@@ -14978,63 +14978,63 @@ Number of gridcells in stimulated 30Hz ms sessions 38
       8.29 ± 0.87 (52)
       7.61 ± 0.87 (38)
       958.00, 0.810
-      0.27, 0.800
+      0.27, 0.808
     
     
       Gridness
       0.54 ± 0.04 (52)
       0.48 ± 0.06 (38)
       914.00, 0.548
-      0.04, 0.601
+      0.04, 0.598
     
     
       Sparsity
       0.63 ± 0.03 (52)
       0.64 ± 0.03 (38)
       1040.00, 0.674
-      0.06, 0.393
+      0.06, 0.398
     
     
       Selectivity
       5.96 ± 0.46 (52)
       6.42 ± 0.60 (38)
       1019.00, 0.803
-      0.20, 0.847
+      0.20, 0.845
     
     
       Information specificity
       0.21 ± 0.02 (52)
       0.22 ± 0.03 (38)
       950.00, 0.759
-      0.04, 0.502
+      0.04, 0.506
     
     
       Max rate
       36.27 ± 2.34 (52)
       33.49 ± 1.89 (38)
       943.00, 0.716
-      2.90, 0.555
+      2.90, 0.565
     
     
       Information rate
       1.13 ± 0.08 (52)
       0.98 ± 0.09 (38)
       827.00, 0.190
-      0.07, 0.334
+      0.07, 0.335
     
     
       Interspike interval cv
       2.37 ± 0.09 (52)
       2.23 ± 0.11 (38)
       869.00, 0.333
-      0.17, 0.476
+      0.17, 0.482
     
     
       In-field mean rate
       13.79 ± 1.12 (52)
       12.21 ± 0.98 (38)
       912.00, 0.537
-      1.06, 0.455
+      1.06, 0.444
     
     
       Out-field mean rate
@@ -15048,21 +15048,21 @@ Number of gridcells in stimulated 30Hz ms sessions 38
       0.20 ± 0.01 (52)
       0.16 ± 0.01 (38)
       676.00, 0.011
-      0.05, 0.006
+      0.05, 0.009
     
     
       Specificity
       0.47 ± 0.03 (52)
       0.48 ± 0.04 (38)
       976.00, 0.925
-      0.00, 0.987
+      0.00, 0.988
     
     
       Speed score
       0.12 ± 0.01 (52)
       0.11 ± 0.01 (38)
       784.00, 0.096
-      0.01, 0.230
+      0.01, 0.242
     
   
 
@@ -15095,7 +15095,7 @@ Number of gridcells in stimulated 30Hz ms sessions 38
 
 
 result.to_latex(output_path / "statistics" / "statistics_b_i_30.tex")
-result.to_latex(output_path / "statistics" / "statistics_b_i_30.csv")
+result.to_csv(output_path / "statistics" / "statistics_b_i_30.csv")
 result
 

 
@@ -15144,84 +15144,84 @@ Number of gridcells in stimulated 30Hz ms sessions 38
       8.96 ± 0.80 (63)
       7.61 ± 0.87 (38)
       1081.00, 0.418
-      0.27, 0.806
+      0.27, 0.804
     
     
       Gridness
       0.53 ± 0.05 (63)
       0.48 ± 0.06 (38)
       1094.00, 0.472
-      0.08, 0.361
+      0.08, 0.354
     
     
       Sparsity
       0.63 ± 0.02 (63)
       0.64 ± 0.03 (38)
       1261.00, 0.656
-      0.03, 0.638
+      0.03, 0.648
     
     
       Selectivity
       5.76 ± 0.40 (63)
       6.42 ± 0.60 (38)
       1276.00, 0.582
-      0.86, 0.293
+      0.86, 0.292
     
     
       Information specificity
       0.24 ± 0.03 (63)
       0.22 ± 0.03 (38)
       1076.00, 0.398
-      0.05, 0.165
+      0.05, 0.159
     
     
       Max rate
       37.39 ± 1.91 (63)
       33.49 ± 1.89 (38)
       1027.00, 0.235
-      3.99, 0.188
+      3.99, 0.191
     
     
       Information rate
       1.31 ± 0.08 (63)
       0.98 ± 0.09 (38)
       797.00, 0.005
-      0.32, 0.047
+      0.32, 0.049
     
     
       Interspike interval cv
       2.39 ± 0.10 (63)
       2.23 ± 0.11 (38)
       1100.00, 0.499
-      0.01, 0.993
+      0.01, 0.991
     
     
       In-field mean rate
       14.88 ± 1.05 (63)
       12.21 ± 0.98 (38)
       1018.00, 0.211
-      1.74, 0.276
+      1.74, 0.273
     
     
       Out-field mean rate
       6.37 ± 0.67 (63)
       5.36 ± 0.73 (38)
       1079.00, 0.410
-      0.51, 0.631
+      0.51, 0.641
     
     
       Burst event ratio
       0.22 ± 0.01 (63)
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       Speed score
@@ -15243,7 +15243,7 @@ Number of gridcells in stimulated 30Hz ms sessions 38
 

 

 

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@@ -15262,7 +15262,7 @@ Number of gridcells in stimulated 30Hz ms sessions 38
 
 
 result.to_latex(output_path / "statistics" / "statistics_11_vs_30.tex")
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@@ -15270,147 +15270,10 @@ Number of gridcells in stimulated 30Hz ms sessions 38
 

 

 
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11 Hz30 HzMWUPRS
Average rate8.80 ± 0.85 (58)7.61 ± 0.87 (38)1010.00, 0.4930.23, 0.893
Gridness0.41 ± 0.05 (58)0.48 ± 0.06 (38)1259.00, 0.2410.13, 0.094
Sparsity0.67 ± 0.03 (58)0.64 ± 0.03 (38)1002.00, 0.4560.04, 0.561
Selectivity5.69 ± 0.50 (58)6.42 ± 0.60 (38)1260.00, 0.2380.85, 0.335
Information specificity0.21 ± 0.03 (58)0.22 ± 0.03 (38)1231.00, 0.3360.01, 0.732
Max rate33.11 ± 1.85 (58)33.49 ± 1.89 (38)1136.00, 0.8020.07, 0.993
Information rate0.94 ± 0.08 (58)0.98 ± 0.09 (38)1171.00, 0.6080.01, 0.789
Interspike interval cv2.19 ± 0.12 (58)2.23 ± 0.11 (38)1228.00, 0.3470.17, 0.328
In-field mean rate13.27 ± 1.04 (58)12.21 ± 0.98 (38)1058.00, 0.7440.97, 0.637
Out-field mean rate6.57 ± 0.77 (58)5.36 ± 0.73 (38)1019.00, 0.5370.04, 0.958
Burst event ratio0.22 ± 0.01 (58)0.16 ± 0.01 (38)552.00, 0.0000.06, 0.000
Specificity0.44 ± 0.03 (58)0.48 ± 0.04 (38)1233.00, 0.3280.07, 0.380
Speed score0.11 ± 0.01 (58)0.11 ± 0.01 (38)1022.00, 0.5510.02, 0.144

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 result.to_latex(output_path / "statistics" / "statistics_base_i_vs_base_ii.tex")
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Baseline IBaseline IIMWUPRS
Average rate8.96 ± 0.80 (63)8.29 ± 0.87 (52)1756.00, 0.5090.55, 0.674
Gridness0.53 ± 0.05 (63)0.54 ± 0.04 (52)1664.00, 0.8860.04, 0.550
Sparsity0.63 ± 0.02 (63)0.63 ± 0.03 (52)1652.00, 0.9400.03, 0.648
Selectivity5.76 ± 0.40 (63)5.96 ± 0.46 (52)1542.00, 0.5920.66, 0.360
Information specificity0.24 ± 0.03 (63)0.21 ± 0.02 (52)1718.00, 0.6550.01, 0.812
Max rate37.39 ± 1.91 (63)36.27 ± 2.34 (52)1757.00, 0.5051.09, 0.610
Information rate1.31 ± 0.08 (63)1.13 ± 0.08 (52)1929.00, 0.1030.25, 0.140
Interspike interval cv2.39 ± 0.10 (63)2.37 ± 0.09 (52)1572.00, 0.7130.16, 0.479
In-field mean rate14.88 ± 1.05 (63)13.79 ± 1.12 (52)1763.00, 0.4840.68, 0.690
Out-field mean rate6.37 ± 0.67 (63)5.80 ± 0.72 (52)1737.00, 0.5800.38, 0.586
Burst event ratio0.22 ± 0.01 (63)0.20 ± 0.01 (52)1834.00, 0.2720.01, 0.681
Specificity0.47 ± 0.03 (63)0.47 ± 0.03 (52)1588.00, 0.7810.01, 0.765
Speed score0.14 ± 0.01 (63)0.12 ± 0.01 (52)1943.00, 0.0870.04, 0.017

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-U-test: U value 4298.0 p value 0.036830785214103115
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-U-test: U value 2202.0 p value 0.05201320820170774
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U-test: U value 3974.0 p value 0.2766869426478231
-U-test: U value 2049.0 p value 0.25046855806374924
-U-test: U value 1000.0 p value 0.9251527394243083
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U-test: U value 3643.0 p value 0.9471010896899097
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-U-test: U value 1018.0 p value 0.8095631030980726
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U-test: U value 3951.0 p value 0.30924120740340955
-U-test: U value 2116.0 p value 0.13443770008325492
-U-test: U value 1033.0 p value 0.7162113753904321
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U-test: U value 4208.0 p value 0.0703111829950676
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-U-test: U value 1107.0 p value 0.3330227188913163
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U-test: U value 3874.0 p value 0.4358627795642821
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U-test: U value 3642.0 p value 0.9495581436162017
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U-test: U value 4152.0 p value 0.10161200342185885
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-U-test: U value 1300.0 p value 0.010937547927479946
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U-test: U value 4196.0 p value 0.07625033158277
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U-test: U value 4034.0 p value 0.20303646513670592
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-U-test: U value 1062.0 p value 0.5482183981489739
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for key, dd in stuff.items(): #TODO narrow broad spiking
@@ -16745,71 +15673,6 @@ U-test: U value 1062.0 p value 0.5482183981489739
 

 

 
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U-test: U value 4696.0 p value 0.0009136914115846572
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-U-test: U value 1192.0 p value 0.09642850317783999
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stim_action = actions['stimulus-response']
@@ -16837,10 +15700,10 @@ U-test: U value 1192.0 p value 0.09642850317783999
 
 data.bs = data.bs.astype(bool)
 
-data.loc[data.eval('not t_i_peak.isnull() and not bs'), 'ns_inhibited'] = True
+data.loc[data.eval('t_i_peak == t_i_peak and not bs'), 'ns_inhibited'] = True
 data.ns_inhibited.fillna(False, inplace=True)
 
-data.loc[data.eval('t_i_peak.isnull() and not bs'), 'ns_not_inhibited'] = True
+data.loc[data.eval('t_i_peak != t_i_peak and not bs'), 'ns_not_inhibited'] = True
 data.ns_not_inhibited.fillna(False, inplace=True)
 
 # make baseline for inhibited vs not inhibited
@@ -16852,75 +15715,6 @@ U-test: U value 1192.0 p value 0.09642850317783999
 

 

 
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-TypeError                                 Traceback (most recent call last)
-<ipython-input-35-d562b46ecc21> in <module>
-     13 data.bs = data.bs.astype(bool)
-     14 
----> 15 data.loc[data.eval('not t_i_peak.isnull() and not bs'), 'ns_inhibited'] = True
-     16 data.ns_inhibited.fillna(False, inplace=True)
-     17 
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-~/.virtualenvs/expipe/lib/python3.6/site-packages/pandas/core/frame.py in eval(self, expr, inplace, **kwargs)
-   3313             kwargs["target"] = self
-   3314         kwargs["resolvers"] = kwargs.get("resolvers", ()) + tuple(resolvers)
--> 3315         return _eval(expr, inplace=inplace, **kwargs)
-   3316 
-   3317     def select_dtypes(self, include=None, exclude=None):
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-~/.virtualenvs/expipe/lib/python3.6/site-packages/pandas/core/computation/eval.py in eval(expr, parser, engine, truediv, local_dict, global_dict, resolvers, level, target, inplace)
-    325         eng = _engines[engine]
-    326         eng_inst = eng(parsed_expr)
---> 327         ret = eng_inst.evaluate()
-    328 
-    329         if parsed_expr.assigner is None:
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-~/.virtualenvs/expipe/lib/python3.6/site-packages/pandas/core/computation/engines.py in evaluate(self)
-     68 
-     69         # make sure no names in resolvers and locals/globals clash
----> 70         res = self._evaluate()
-     71         return _reconstruct_object(
-     72             self.result_type, res, self.aligned_axes, self.expr.terms.return_type
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-    116             scope = env.full_scope
-    117             truediv = scope["truediv"]
---> 118             _check_ne_builtin_clash(self.expr)
-    119             return ne.evaluate(s, local_dict=scope, truediv=truediv)
-    120         except KeyError as e:
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-~/.virtualenvs/expipe/lib/python3.6/site-packages/pandas/core/computation/engines.py in _check_ne_builtin_clash(expr)
-     25         Terms can contain
-     26     """
----> 27     names = expr.names
-     28     overlap = names & _ne_builtins
-     29 
-
-~/.virtualenvs/expipe/lib/python3.6/site-packages/pandas/core/computation/expr.py in names(self)
-    852         if is_term(self.terms):
-    853             return frozenset([self.terms.name])
---> 854         return frozenset(term.name for term in com.flatten(self.terms))
-    855 
-    856 
-
-TypeError: unhashable type: 'numpy.ndarray'

-

-

-
-

-

-
 

 

 

diff --git a/actions/comparisons-gridcells/data/20_comparisons_gridcells.ipynb b/actions/comparisons-gridcells/data/20_comparisons_gridcells.ipynb
index 2fafb085f..44fe3d7c5 100644
--- a/actions/comparisons-gridcells/data/20_comparisons_gridcells.ipynb
+++ b/actions/comparisons-gridcells/data/20_comparisons_gridcells.ipynb
@@ -2,7 +2,7 @@
  "cells": [
   {
    "cell_type": "code",
-   "execution_count": 2,
+   "execution_count": 1,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -12,14 +12,14 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 3,
+   "execution_count": 2,
    "metadata": {},
    "outputs": [
     {
      "name": "stderr",
      "output_type": "stream",
      "text": [
-      "13:03:48 [I] klustakwik KlustaKwik2 version 0.2.6\n",
+      "12:51:51 [I] klustakwik KlustaKwik2 version 0.2.6\n",
       "/home/mikkel/.virtualenvs/expipe/lib/python3.6/importlib/_bootstrap.py:219: RuntimeWarning: numpy.ufunc size changed, may indicate binary incompatibility. Expected 192 from C header, got 216 from PyObject\n",
       "  return f(*args, **kwds)\n",
       "/home/mikkel/.virtualenvs/expipe/lib/python3.6/importlib/_bootstrap.py:219: RuntimeWarning: numpy.ufunc size changed, may indicate binary incompatibility. Expected 192 from C header, got 216 from PyObject\n",
@@ -52,7 +52,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 4,
+   "execution_count": 3,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -74,7 +74,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 5,
+   "execution_count": 4,
    "metadata": {},
    "outputs": [
     {
@@ -286,7 +286,7 @@
        "[5 rows x 39 columns]"
       ]
      },
-     "execution_count": 5,
+     "execution_count": 4,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -304,7 +304,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 6,
+   "execution_count": 5,
    "metadata": {},
    "outputs": [
     {
@@ -420,7 +420,7 @@
        "4     0.094041  1833-010719-1            0.0      225.0  "
       ]
      },
-     "execution_count": 6,
+     "execution_count": 5,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -433,7 +433,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 7,
+   "execution_count": 6,
    "metadata": {},
    "outputs": [
     {
@@ -645,7 +645,7 @@
        "[5 rows x 46 columns]"
       ]
      },
-     "execution_count": 7,
+     "execution_count": 6,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -668,7 +668,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 8,
+   "execution_count": 7,
    "metadata": {},
    "outputs": [
     {
@@ -680,7 +680,7 @@
        "Name: action, dtype: int64"
       ]
      },
-     "execution_count": 8,
+     "execution_count": 7,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -691,7 +691,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 9,
+   "execution_count": 8,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -707,7 +707,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 10,
+   "execution_count": 9,
    "metadata": {},
    "outputs": [
     {
@@ -733,7 +733,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 11,
+   "execution_count": 10,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -742,7 +742,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 12,
+   "execution_count": 11,
    "metadata": {},
    "outputs": [
     {
@@ -763,7 +763,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 13,
+   "execution_count": 12,
    "metadata": {},
    "outputs": [
     {
@@ -800,7 +800,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 14,
+   "execution_count": 13,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -812,7 +812,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 15,
+   "execution_count": 14,
    "metadata": {},
    "outputs": [
     {
@@ -843,7 +843,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 16,
+   "execution_count": 15,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -857,7 +857,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 17,
+   "execution_count": 16,
    "metadata": {},
    "outputs": [
     {
@@ -971,7 +971,7 @@
        "True                 0.197264     0.455878     0.104697  "
       ]
      },
-     "execution_count": 17,
+     "execution_count": 16,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -982,7 +982,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 18,
+   "execution_count": 17,
    "metadata": {},
    "outputs": [
     {
@@ -1196,7 +1196,7 @@
        "max             0.393306     1.066391     0.297548  "
       ]
      },
-     "execution_count": 18,
+     "execution_count": 17,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -1207,7 +1207,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 19,
+   "execution_count": 18,
    "metadata": {},
    "outputs": [
     {
@@ -1421,7 +1421,7 @@
        "max             0.393037     1.091064     0.390079  "
       ]
      },
-     "execution_count": 19,
+     "execution_count": 18,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -1512,14 +1512,14 @@
        "      8.61 ± 0.75 (71)\n",
        "      8.39 ± 0.60 (102)\n",
        "      3599.00, 0.947\n",
-       "      0.55, 0.764\n",
+       "      0.55, 0.757\n",
        "    \n",
        "    \n",
        "      Gridness\n",
        "      0.51 ± 0.04 (71)\n",
        "      0.44 ± 0.04 (102)\n",
        "      3208.00, 0.203\n",
-       "      0.13, 0.141\n",
+       "      0.13, 0.145\n",
        "    \n",
        "    \n",
        "      Sparsity\n",
@@ -1533,63 +1533,63 @@
        "      5.91 ± 0.37 (71)\n",
        "      5.98 ± 0.37 (102)\n",
        "      3460.00, 0.620\n",
-       "      0.10, 0.869\n",
+       "      0.10, 0.874\n",
        "    \n",
        "    \n",
        "      Information specificity\n",
        "      0.25 ± 0.03 (71)\n",
        "      0.22 ± 0.02 (102)\n",
        "      2944.00, 0.037\n",
-       "      0.05, 0.033\n",
+       "      0.05, 0.034\n",
        "    \n",
        "    \n",
        "      Max rate\n",
        "      36.55 ± 1.78 (71)\n",
        "      33.72 ± 1.31 (102)\n",
        "      3291.00, 0.309\n",
-       "      3.19, 0.195\n",
+       "      3.19, 0.194\n",
        "    \n",
        "    \n",
        "      Information rate\n",
        "      1.30 ± 0.07 (71)\n",
        "      0.96 ± 0.06 (102)\n",
        "      2385.00, 0.000\n",
-       "      0.32, 0.000\n",
+       "      0.32, 0.001\n",
        "    \n",
        "    \n",
        "      Interspike interval cv\n",
        "      2.42 ± 0.10 (71)\n",
        "      2.22 ± 0.08 (102)\n",
        "      3034.00, 0.070\n",
-       "      0.12, 0.392\n",
+       "      0.12, 0.398\n",
        "    \n",
        "    \n",
        "      In-field mean rate\n",
        "      14.43 ± 1.00 (71)\n",
        "      12.94 ± 0.71 (102)\n",
        "      3368.00, 0.436\n",
-       "      0.39, 0.812\n",
+       "      0.39, 0.817\n",
        "    \n",
        "    \n",
        "      Out-field mean rate\n",
        "      6.05 ± 0.62 (71)\n",
        "      6.12 ± 0.53 (102)\n",
        "      3600.00, 0.950\n",
-       "      0.08, 0.946\n",
+       "      0.08, 0.944\n",
        "    \n",
        "    \n",
        "      Burst event ratio\n",
        "      0.22 ± 0.01 (71)\n",
        "      0.20 ± 0.01 (102)\n",
        "      3090.00, 0.102\n",
-       "      0.02, 0.124\n",
+       "      0.02, 0.129\n",
        "    \n",
        "    \n",
        "      Specificity\n",
        "      0.48 ± 0.03 (71)\n",
        "      0.46 ± 0.02 (102)\n",
        "      3268.00, 0.277\n",
-       "      0.06, 0.356\n",
+       "      0.06, 0.360\n",
        "    \n",
        "    \n",
        "      Speed score\n",
@@ -1619,18 +1619,18 @@
        "Speed score               0.14 ± 0.01 (71)   0.10 ± 0.01 (102)   \n",
        "\n",
        "                                    MWU          PRS  \n",
-       "Average rate             3599.00, 0.947  0.55, 0.764  \n",
-       "Gridness                 3208.00, 0.203  0.13, 0.141  \n",
+       "Average rate             3599.00, 0.947  0.55, 0.757  \n",
+       "Gridness                 3208.00, 0.203  0.13, 0.145  \n",
        "Sparsity                 4170.00, 0.091  0.06, 0.179  \n",
-       "Selectivity              3460.00, 0.620  0.10, 0.869  \n",
-       "Information specificity  2944.00, 0.037  0.05, 0.033  \n",
-       "Max rate                 3291.00, 0.309  3.19, 0.195  \n",
-       "Information rate         2385.00, 0.000  0.32, 0.000  \n",
-       "Interspike interval cv   3034.00, 0.070  0.12, 0.392  \n",
-       "In-field mean rate       3368.00, 0.436  0.39, 0.812  \n",
-       "Out-field mean rate      3600.00, 0.950  0.08, 0.946  \n",
-       "Burst event ratio        3090.00, 0.102  0.02, 0.124  \n",
-       "Specificity              3268.00, 0.277  0.06, 0.356  \n",
+       "Selectivity              3460.00, 0.620  0.10, 0.874  \n",
+       "Information specificity  2944.00, 0.037  0.05, 0.034  \n",
+       "Max rate                 3291.00, 0.309  3.19, 0.194  \n",
+       "Information rate         2385.00, 0.000  0.32, 0.001  \n",
+       "Interspike interval cv   3034.00, 0.070  0.12, 0.398  \n",
+       "In-field mean rate       3368.00, 0.436  0.39, 0.817  \n",
+       "Out-field mean rate      3600.00, 0.950  0.08, 0.944  \n",
+       "Burst event ratio        3090.00, 0.102  0.02, 0.129  \n",
+       "Specificity              3268.00, 0.277  0.06, 0.360  \n",
        "Speed score              2546.00, 0.001  0.05, 0.000  "
       ]
      },
@@ -1655,7 +1655,7 @@
     "result['PRS'] = list(map(lambda x: PRS(x, _stim_data, _base_data), columns))\n",
     "\n",
     "result.to_latex(output_path / \"statistics\" / \"statistics.tex\")\n",
-    "result.to_latex(output_path / \"statistics\" / \"statistics.csv\")\n",
+    "result.to_csv(output_path / \"statistics\" / \"statistics.csv\")\n",
     "result"
    ]
   },
@@ -1697,70 +1697,70 @@
        "      8.96 ± 0.80 (63)\n",
        "      8.80 ± 0.85 (58)\n",
        "      1781.00, 0.813\n",
-       "      0.04, 0.972\n",
+       "      0.04, 0.968\n",
        "    \n",
        "    \n",
        "      Gridness\n",
        "      0.53 ± 0.05 (63)\n",
        "      0.41 ± 0.05 (58)\n",
        "      1459.00, 0.057\n",
-       "      0.21, 0.043\n",
+       "      0.21, 0.041\n",
        "    \n",
        "    \n",
        "      Sparsity\n",
        "      0.63 ± 0.02 (63)\n",
        "      0.67 ± 0.03 (58)\n",
        "      2138.00, 0.107\n",
-       "      0.07, 0.119\n",
+       "      0.07, 0.128\n",
        "    \n",
        "    \n",
        "      Selectivity\n",
        "      5.76 ± 0.40 (63)\n",
        "      5.69 ± 0.50 (58)\n",
        "      1687.00, 0.469\n",
-       "      0.00, 0.982\n",
+       "      0.00, 0.983\n",
        "    \n",
        "    \n",
        "      Information specificity\n",
        "      0.24 ± 0.03 (63)\n",
        "      0.21 ± 0.03 (58)\n",
        "      1452.00, 0.052\n",
-       "      0.06, 0.032\n",
+       "      0.06, 0.030\n",
        "    \n",
        "    \n",
        "      Max rate\n",
        "      37.39 ± 1.91 (63)\n",
        "      33.11 ± 1.85 (58)\n",
        "      1538.00, 0.134\n",
-       "      4.06, 0.122\n",
+       "      4.06, 0.125\n",
        "    \n",
        "    \n",
        "      Information rate\n",
        "      1.31 ± 0.08 (63)\n",
        "      0.94 ± 0.08 (58)\n",
        "      1143.00, 0.000\n",
-       "      0.32, 0.003\n",
+       "      0.32, 0.004\n",
        "    \n",
        "    \n",
        "      Interspike interval cv\n",
        "      2.39 ± 0.10 (63)\n",
        "      2.19 ± 0.12 (58)\n",
        "      1462.00, 0.059\n",
-       "      0.18, 0.135\n",
+       "      0.18, 0.139\n",
        "    \n",
        "    \n",
        "      In-field mean rate\n",
        "      14.88 ± 1.05 (63)\n",
        "      13.27 ± 1.04 (58)\n",
        "      1633.00, 0.315\n",
-       "      0.77, 0.688\n",
+       "      0.77, 0.690\n",
        "    \n",
        "    \n",
        "      Out-field mean rate\n",
        "      6.37 ± 0.67 (63)\n",
        "      6.57 ± 0.77 (58)\n",
        "      1795.00, 0.870\n",
-       "      0.47, 0.724\n",
+       "      0.47, 0.719\n",
        "    \n",
        "    \n",
        "      Burst event ratio\n",
@@ -1774,14 +1774,14 @@
        "      0.47 ± 0.03 (63)\n",
        "      0.44 ± 0.03 (58)\n",
        "      1605.00, 0.250\n",
-       "      0.06, 0.398\n",
+       "      0.06, 0.414\n",
        "    \n",
        "    \n",
        "      Speed score\n",
        "      0.14 ± 0.01 (63)\n",
        "      0.11 ± 0.01 (58)\n",
        "      1378.00, 0.020\n",
-       "      0.04, 0.023\n",
+       "      0.04, 0.022\n",
        "    \n",
        "  \n",
        "\n",
@@ -1804,19 +1804,19 @@
        "Speed score               0.14 ± 0.01 (63)   0.11 ± 0.01 (58)  1378.00, 0.020   \n",
        "\n",
        "                                 PRS  \n",
-       "Average rate             0.04, 0.972  \n",
-       "Gridness                 0.21, 0.043  \n",
-       "Sparsity                 0.07, 0.119  \n",
-       "Selectivity              0.00, 0.982  \n",
-       "Information specificity  0.06, 0.032  \n",
-       "Max rate                 4.06, 0.122  \n",
-       "Information rate         0.32, 0.003  \n",
-       "Interspike interval cv   0.18, 0.135  \n",
-       "In-field mean rate       0.77, 0.688  \n",
-       "Out-field mean rate      0.47, 0.724  \n",
+       "Average rate             0.04, 0.968  \n",
+       "Gridness                 0.21, 0.041  \n",
+       "Sparsity                 0.07, 0.128  \n",
+       "Selectivity              0.00, 0.983  \n",
+       "Information specificity  0.06, 0.030  \n",
+       "Max rate                 4.06, 0.125  \n",
+       "Information rate         0.32, 0.004  \n",
+       "Interspike interval cv   0.18, 0.139  \n",
+       "In-field mean rate       0.77, 0.690  \n",
+       "Out-field mean rate      0.47, 0.719  \n",
        "Burst event ratio        0.00, 0.824  \n",
-       "Specificity              0.06, 0.398  \n",
-       "Speed score              0.04, 0.023  "
+       "Specificity              0.06, 0.414  \n",
+       "Speed score              0.04, 0.022  "
       ]
      },
      "execution_count": 21,
@@ -1841,7 +1841,7 @@
     "\n",
     "\n",
     "result.to_latex(output_path / \"statistics\" / \"statistics_11.tex\")\n",
-    "result.to_latex(output_path / \"statistics\" / \"statistics_11.csv\")\n",
+    "result.to_csv(output_path / \"statistics\" / \"statistics_11.csv\")\n",
     "result"
    ]
   },
@@ -1883,63 +1883,63 @@
        "      8.29 ± 0.87 (52)\n",
        "      7.61 ± 0.87 (38)\n",
        "      958.00, 0.810\n",
-       "      0.27, 0.800\n",
+       "      0.27, 0.808\n",
        "    \n",
        "    \n",
        "      Gridness\n",
        "      0.54 ± 0.04 (52)\n",
        "      0.48 ± 0.06 (38)\n",
        "      914.00, 0.548\n",
-       "      0.04, 0.601\n",
+       "      0.04, 0.598\n",
        "    \n",
        "    \n",
        "      Sparsity\n",
        "      0.63 ± 0.03 (52)\n",
        "      0.64 ± 0.03 (38)\n",
        "      1040.00, 0.674\n",
-       "      0.06, 0.393\n",
+       "      0.06, 0.398\n",
        "    \n",
        "    \n",
        "      Selectivity\n",
        "      5.96 ± 0.46 (52)\n",
        "      6.42 ± 0.60 (38)\n",
        "      1019.00, 0.803\n",
-       "      0.20, 0.847\n",
+       "      0.20, 0.845\n",
        "    \n",
        "    \n",
        "      Information specificity\n",
        "      0.21 ± 0.02 (52)\n",
        "      0.22 ± 0.03 (38)\n",
        "      950.00, 0.759\n",
-       "      0.04, 0.502\n",
+       "      0.04, 0.506\n",
        "    \n",
        "    \n",
        "      Max rate\n",
        "      36.27 ± 2.34 (52)\n",
        "      33.49 ± 1.89 (38)\n",
        "      943.00, 0.716\n",
-       "      2.90, 0.555\n",
+       "      2.90, 0.565\n",
        "    \n",
        "    \n",
        "      Information rate\n",
        "      1.13 ± 0.08 (52)\n",
        "      0.98 ± 0.09 (38)\n",
        "      827.00, 0.190\n",
-       "      0.07, 0.334\n",
+       "      0.07, 0.335\n",
        "    \n",
        "    \n",
        "      Interspike interval cv\n",
        "      2.37 ± 0.09 (52)\n",
        "      2.23 ± 0.11 (38)\n",
        "      869.00, 0.333\n",
-       "      0.17, 0.476\n",
+       "      0.17, 0.482\n",
        "    \n",
        "    \n",
        "      In-field mean rate\n",
        "      13.79 ± 1.12 (52)\n",
        "      12.21 ± 0.98 (38)\n",
        "      912.00, 0.537\n",
-       "      1.06, 0.455\n",
+       "      1.06, 0.444\n",
        "    \n",
        "    \n",
        "      Out-field mean rate\n",
@@ -1953,21 +1953,21 @@
        "      0.20 ± 0.01 (52)\n",
        "      0.16 ± 0.01 (38)\n",
        "      676.00, 0.011\n",
-       "      0.05, 0.006\n",
+       "      0.05, 0.009\n",
        "    \n",
        "    \n",
        "      Specificity\n",
        "      0.47 ± 0.03 (52)\n",
        "      0.48 ± 0.04 (38)\n",
        "      976.00, 0.925\n",
-       "      0.00, 0.987\n",
+       "      0.00, 0.988\n",
        "    \n",
        "    \n",
        "      Speed score\n",
        "      0.12 ± 0.01 (52)\n",
        "      0.11 ± 0.01 (38)\n",
        "      784.00, 0.096\n",
-       "      0.01, 0.230\n",
+       "      0.01, 0.242\n",
        "    \n",
        "  \n",
        "\n",
@@ -1990,19 +1990,19 @@
        "Speed score               0.12 ± 0.01 (52)   0.11 ± 0.01 (38)   784.00, 0.096   \n",
        "\n",
        "                                 PRS  \n",
-       "Average rate             0.27, 0.800  \n",
-       "Gridness                 0.04, 0.601  \n",
-       "Sparsity                 0.06, 0.393  \n",
-       "Selectivity              0.20, 0.847  \n",
-       "Information specificity  0.04, 0.502  \n",
-       "Max rate                 2.90, 0.555  \n",
-       "Information rate         0.07, 0.334  \n",
-       "Interspike interval cv   0.17, 0.476  \n",
-       "In-field mean rate       1.06, 0.455  \n",
+       "Average rate             0.27, 0.808  \n",
+       "Gridness                 0.04, 0.598  \n",
+       "Sparsity                 0.06, 0.398  \n",
+       "Selectivity              0.20, 0.845  \n",
+       "Information specificity  0.04, 0.506  \n",
+       "Max rate                 2.90, 0.565  \n",
+       "Information rate         0.07, 0.335  \n",
+       "Interspike interval cv   0.17, 0.482  \n",
+       "In-field mean rate       1.06, 0.444  \n",
        "Out-field mean rate      0.13, 0.912  \n",
-       "Burst event ratio        0.05, 0.006  \n",
-       "Specificity              0.00, 0.987  \n",
-       "Speed score              0.01, 0.230  "
+       "Burst event ratio        0.05, 0.009  \n",
+       "Specificity              0.00, 0.988  \n",
+       "Speed score              0.01, 0.242  "
       ]
      },
      "execution_count": 22,
@@ -2026,7 +2026,7 @@
     "\n",
     "\n",
     "result.to_latex(output_path / \"statistics\" / \"statistics_30.tex\")\n",
-    "result.to_latex(output_path / \"statistics\" / \"statistics_30.csv\")\n",
+    "result.to_csv(output_path / \"statistics\" / \"statistics_30.csv\")\n",
     "result"
    ]
   },
@@ -2068,84 +2068,84 @@
        "      8.96 ± 0.80 (63)\n",
        "      7.61 ± 0.87 (38)\n",
        "      1081.00, 0.418\n",
-       "      0.27, 0.806\n",
+       "      0.27, 0.804\n",
        "    \n",
        "    \n",
        "      Gridness\n",
        "      0.53 ± 0.05 (63)\n",
        "      0.48 ± 0.06 (38)\n",
        "      1094.00, 0.472\n",
-       "      0.08, 0.361\n",
+       "      0.08, 0.354\n",
        "    \n",
        "    \n",
        "      Sparsity\n",
        "      0.63 ± 0.02 (63)\n",
        "      0.64 ± 0.03 (38)\n",
        "      1261.00, 0.656\n",
-       "      0.03, 0.638\n",
+       "      0.03, 0.648\n",
        "    \n",
        "    \n",
        "      Selectivity\n",
        "      5.76 ± 0.40 (63)\n",
        "      6.42 ± 0.60 (38)\n",
        "      1276.00, 0.582\n",
-       "      0.86, 0.293\n",
+       "      0.86, 0.292\n",
        "    \n",
        "    \n",
        "      Information specificity\n",
        "      0.24 ± 0.03 (63)\n",
        "      0.22 ± 0.03 (38)\n",
        "      1076.00, 0.398\n",
-       "      0.05, 0.165\n",
+       "      0.05, 0.159\n",
        "    \n",
        "    \n",
        "      Max rate\n",
        "      37.39 ± 1.91 (63)\n",
        "      33.49 ± 1.89 (38)\n",
        "      1027.00, 0.235\n",
-       "      3.99, 0.188\n",
+       "      3.99, 0.191\n",
        "    \n",
        "    \n",
        "      Information rate\n",
        "      1.31 ± 0.08 (63)\n",
        "      0.98 ± 0.09 (38)\n",
        "      797.00, 0.005\n",
-       "      0.32, 0.047\n",
+       "      0.32, 0.049\n",
        "    \n",
        "    \n",
        "      Interspike interval cv\n",
        "      2.39 ± 0.10 (63)\n",
        "      2.23 ± 0.11 (38)\n",
        "      1100.00, 0.499\n",
-       "      0.01, 0.993\n",
+       "      0.01, 0.991\n",
        "    \n",
        "    \n",
        "      In-field mean rate\n",
        "      14.88 ± 1.05 (63)\n",
        "      12.21 ± 0.98 (38)\n",
        "      1018.00, 0.211\n",
-       "      1.74, 0.276\n",
+       "      1.74, 0.273\n",
        "    \n",
        "    \n",
        "      Out-field mean rate\n",
        "      6.37 ± 0.67 (63)\n",
        "      5.36 ± 0.73 (38)\n",
        "      1079.00, 0.410\n",
-       "      0.51, 0.631\n",
+       "      0.51, 0.641\n",
        "    \n",
        "    \n",
        "      Burst event ratio\n",
        "      0.22 ± 0.01 (63)\n",
        "      0.16 ± 0.01 (38)\n",
        "      675.00, 0.000\n",
-       "      0.05, 0.003\n",
+       "      0.05, 0.004\n",
        "    \n",
        "    \n",
        "      Specificity\n",
        "      0.47 ± 0.03 (63)\n",
        "      0.48 ± 0.04 (38)\n",
        "      1206.00, 0.952\n",
-       "      0.01, 0.873\n",
+       "      0.01, 0.875\n",
        "    \n",
        "    \n",
        "      Speed score\n",
@@ -2175,18 +2175,18 @@
        "Speed score               0.14 ± 0.01 (63)   0.11 ± 0.01 (38)   835.00, 0.011   \n",
        "\n",
        "                                 PRS  \n",
-       "Average rate             0.27, 0.806  \n",
-       "Gridness                 0.08, 0.361  \n",
-       "Sparsity                 0.03, 0.638  \n",
-       "Selectivity              0.86, 0.293  \n",
-       "Information specificity  0.05, 0.165  \n",
-       "Max rate                 3.99, 0.188  \n",
-       "Information rate         0.32, 0.047  \n",
-       "Interspike interval cv   0.01, 0.993  \n",
-       "In-field mean rate       1.74, 0.276  \n",
-       "Out-field mean rate      0.51, 0.631  \n",
-       "Burst event ratio        0.05, 0.003  \n",
-       "Specificity              0.01, 0.873  \n",
+       "Average rate             0.27, 0.804  \n",
+       "Gridness                 0.08, 0.354  \n",
+       "Sparsity                 0.03, 0.648  \n",
+       "Selectivity              0.86, 0.292  \n",
+       "Information specificity  0.05, 0.159  \n",
+       "Max rate                 3.99, 0.191  \n",
+       "Information rate         0.32, 0.049  \n",
+       "Interspike interval cv   0.01, 0.991  \n",
+       "In-field mean rate       1.74, 0.273  \n",
+       "Out-field mean rate      0.51, 0.641  \n",
+       "Burst event ratio        0.05, 0.004  \n",
+       "Specificity              0.01, 0.875  \n",
        "Speed score              0.06, 0.004  "
       ]
      },
@@ -2211,175 +2211,15 @@
     "\n",
     "\n",
     "result.to_latex(output_path / \"statistics\" / \"statistics_b_i_30.tex\")\n",
-    "result.to_latex(output_path / \"statistics\" / \"statistics_b_i_30.csv\")\n",
+    "result.to_csv(output_path / \"statistics\" / \"statistics_b_i_30.csv\")\n",
     "result"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 24,
+   "execution_count": null,
    "metadata": {},
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11 Hz30 HzMWUPRS
Average rate8.80 ± 0.85 (58)7.61 ± 0.87 (38)1010.00, 0.4930.23, 0.893
Gridness0.41 ± 0.05 (58)0.48 ± 0.06 (38)1259.00, 0.2410.13, 0.094
Sparsity0.67 ± 0.03 (58)0.64 ± 0.03 (38)1002.00, 0.4560.04, 0.561
Selectivity5.69 ± 0.50 (58)6.42 ± 0.60 (38)1260.00, 0.2380.85, 0.335
Information specificity0.21 ± 0.03 (58)0.22 ± 0.03 (38)1231.00, 0.3360.01, 0.732
Max rate33.11 ± 1.85 (58)33.49 ± 1.89 (38)1136.00, 0.8020.07, 0.993
Information rate0.94 ± 0.08 (58)0.98 ± 0.09 (38)1171.00, 0.6080.01, 0.789
Interspike interval cv2.19 ± 0.12 (58)2.23 ± 0.11 (38)1228.00, 0.3470.17, 0.328
In-field mean rate13.27 ± 1.04 (58)12.21 ± 0.98 (38)1058.00, 0.7440.97, 0.637
Out-field mean rate6.57 ± 0.77 (58)5.36 ± 0.73 (38)1019.00, 0.5370.04, 0.958
Burst event ratio0.22 ± 0.01 (58)0.16 ± 0.01 (38)552.00, 0.0000.06, 0.000
Specificity0.44 ± 0.03 (58)0.48 ± 0.04 (38)1233.00, 0.3280.07, 0.380
Speed score0.11 ± 0.01 (58)0.11 ± 0.01 (38)1022.00, 0.5510.02, 0.144
\n",
-       "
"
-      ],
-      "text/plain": [
-       "                                     11 Hz              30 Hz             MWU  \\\n",
-       "Average rate              8.80 ± 0.85 (58)   7.61 ± 0.87 (38)  1010.00, 0.493   \n",
-       "Gridness                  0.41 ± 0.05 (58)   0.48 ± 0.06 (38)  1259.00, 0.241   \n",
-       "Sparsity                  0.67 ± 0.03 (58)   0.64 ± 0.03 (38)  1002.00, 0.456   \n",
-       "Selectivity               5.69 ± 0.50 (58)   6.42 ± 0.60 (38)  1260.00, 0.238   \n",
-       "Information specificity   0.21 ± 0.03 (58)   0.22 ± 0.03 (38)  1231.00, 0.336   \n",
-       "Max rate                 33.11 ± 1.85 (58)  33.49 ± 1.89 (38)  1136.00, 0.802   \n",
-       "Information rate          0.94 ± 0.08 (58)   0.98 ± 0.09 (38)  1171.00, 0.608   \n",
-       "Interspike interval cv    2.19 ± 0.12 (58)   2.23 ± 0.11 (38)  1228.00, 0.347   \n",
-       "In-field mean rate       13.27 ± 1.04 (58)  12.21 ± 0.98 (38)  1058.00, 0.744   \n",
-       "Out-field mean rate       6.57 ± 0.77 (58)   5.36 ± 0.73 (38)  1019.00, 0.537   \n",
-       "Burst event ratio         0.22 ± 0.01 (58)   0.16 ± 0.01 (38)   552.00, 0.000   \n",
-       "Specificity               0.44 ± 0.03 (58)   0.48 ± 0.04 (38)  1233.00, 0.328   \n",
-       "Speed score               0.11 ± 0.01 (58)   0.11 ± 0.01 (38)  1022.00, 0.551   \n",
-       "\n",
-       "                                 PRS  \n",
-       "Average rate             0.23, 0.893  \n",
-       "Gridness                 0.13, 0.094  \n",
-       "Sparsity                 0.04, 0.561  \n",
-       "Selectivity              0.85, 0.335  \n",
-       "Information specificity  0.01, 0.732  \n",
-       "Max rate                 0.07, 0.993  \n",
-       "Information rate         0.01, 0.789  \n",
-       "Interspike interval cv   0.17, 0.328  \n",
-       "In-field mean rate       0.97, 0.637  \n",
-       "Out-field mean rate      0.04, 0.958  \n",
-       "Burst event ratio        0.06, 0.000  \n",
-       "Specificity              0.07, 0.380  \n",
-       "Speed score              0.02, 0.144  "
-      ]
-     },
-     "execution_count": 24,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
+   "outputs": [],
    "source": [
     "_stim_data = stimulated_30\n",
     "_base_data = stimulated_11\n",
@@ -2397,175 +2237,15 @@
     "\n",
     "\n",
     "result.to_latex(output_path / \"statistics\" / \"statistics_11_vs_30.tex\")\n",
-    "result.to_latex(output_path / \"statistics\" / \"statistics_11_vs_30.csv\")\n",
+    "result.to_csv(output_path / \"statistics\" / \"statistics_11_vs_30.csv\")\n",
     "result"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 25,
+   "execution_count": null,
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Baseline IBaseline IIMWUPRS
Average rate8.96 ± 0.80 (63)8.29 ± 0.87 (52)1756.00, 0.5090.55, 0.674
Gridness0.53 ± 0.05 (63)0.54 ± 0.04 (52)1664.00, 0.8860.04, 0.550
Sparsity0.63 ± 0.02 (63)0.63 ± 0.03 (52)1652.00, 0.9400.03, 0.648
Selectivity5.76 ± 0.40 (63)5.96 ± 0.46 (52)1542.00, 0.5920.66, 0.360
Information specificity0.24 ± 0.03 (63)0.21 ± 0.02 (52)1718.00, 0.6550.01, 0.812
Max rate37.39 ± 1.91 (63)36.27 ± 2.34 (52)1757.00, 0.5051.09, 0.610
Information rate1.31 ± 0.08 (63)1.13 ± 0.08 (52)1929.00, 0.1030.25, 0.140
Interspike interval cv2.39 ± 0.10 (63)2.37 ± 0.09 (52)1572.00, 0.7130.16, 0.479
In-field mean rate14.88 ± 1.05 (63)13.79 ± 1.12 (52)1763.00, 0.4840.68, 0.690
Out-field mean rate6.37 ± 0.67 (63)5.80 ± 0.72 (52)1737.00, 0.5800.38, 0.586
Burst event ratio0.22 ± 0.01 (63)0.20 ± 0.01 (52)1834.00, 0.2720.01, 0.681
Specificity0.47 ± 0.03 (63)0.47 ± 0.03 (52)1588.00, 0.7810.01, 0.765
Speed score0.14 ± 0.01 (63)0.12 ± 0.01 (52)1943.00, 0.0870.04, 0.017
\n",
-       "
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-      ],
-      "text/plain": [
-       "                                Baseline I        Baseline II             MWU  \\\n",
-       "Average rate              8.96 ± 0.80 (63)   8.29 ± 0.87 (52)  1756.00, 0.509   \n",
-       "Gridness                  0.53 ± 0.05 (63)   0.54 ± 0.04 (52)  1664.00, 0.886   \n",
-       "Sparsity                  0.63 ± 0.02 (63)   0.63 ± 0.03 (52)  1652.00, 0.940   \n",
-       "Selectivity               5.76 ± 0.40 (63)   5.96 ± 0.46 (52)  1542.00, 0.592   \n",
-       "Information specificity   0.24 ± 0.03 (63)   0.21 ± 0.02 (52)  1718.00, 0.655   \n",
-       "Max rate                 37.39 ± 1.91 (63)  36.27 ± 2.34 (52)  1757.00, 0.505   \n",
-       "Information rate          1.31 ± 0.08 (63)   1.13 ± 0.08 (52)  1929.00, 0.103   \n",
-       "Interspike interval cv    2.39 ± 0.10 (63)   2.37 ± 0.09 (52)  1572.00, 0.713   \n",
-       "In-field mean rate       14.88 ± 1.05 (63)  13.79 ± 1.12 (52)  1763.00, 0.484   \n",
-       "Out-field mean rate       6.37 ± 0.67 (63)   5.80 ± 0.72 (52)  1737.00, 0.580   \n",
-       "Burst event ratio         0.22 ± 0.01 (63)   0.20 ± 0.01 (52)  1834.00, 0.272   \n",
-       "Specificity               0.47 ± 0.03 (63)   0.47 ± 0.03 (52)  1588.00, 0.781   \n",
-       "Speed score               0.14 ± 0.01 (63)   0.12 ± 0.01 (52)  1943.00, 0.087   \n",
-       "\n",
-       "                                 PRS  \n",
-       "Average rate             0.55, 0.674  \n",
-       "Gridness                 0.04, 0.550  \n",
-       "Sparsity                 0.03, 0.648  \n",
-       "Selectivity              0.66, 0.360  \n",
-       "Information specificity  0.01, 0.812  \n",
-       "Max rate                 1.09, 0.610  \n",
-       "Information rate         0.25, 0.140  \n",
-       "Interspike interval cv   0.16, 0.479  \n",
-       "In-field mean rate       0.68, 0.690  \n",
-       "Out-field mean rate      0.38, 0.586  \n",
-       "Burst event ratio        0.01, 0.681  \n",
-       "Specificity              0.01, 0.765  \n",
-       "Speed score              0.04, 0.017  "
-      ]
-     },
-     "execution_count": 25,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
+   "outputs": [],
    "source": [
     "_stim_data = baseline_i\n",
     "_base_data = baseline_ii\n",
@@ -2582,7 +2262,7 @@
     "\n",
     "\n",
     "result.to_latex(output_path / \"statistics\" / \"statistics_base_i_vs_base_ii.tex\")\n",
-    "result.to_latex(output_path / \"statistics\" / \"statistics_base_i_vs_base_ii.csv\")\n",
+    "result.to_csv(output_path / \"statistics\" / \"statistics_base_i_vs_base_ii.csv\")\n",
     "result"
    ]
   },
@@ -2595,7 +2275,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 20,
+   "execution_count": null,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -2610,7 +2290,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 21,
+   "execution_count": null,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -2654,58 +2334,9 @@
   },
   {
    "cell_type": "code",
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+   "execution_count": null,
    "metadata": {},
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-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "\n",
-      "U-test: U value 4298.0 p value 0.036830785214103115\n",
-      "_11\n",
-      "U-test: U value 2202.0 p value 0.05201320820170774\n",
-      "_30\n",
-      "U-test: U value 1026.0 p value 0.7593436297175663\n"
-     ]
-    },
-    {
-     "data": {
-      "image/png": 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\n",
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-     "metadata": {
-      "needs_background": "light"
-     },
-     "output_type": "display_data"
-    },
-    {
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\n",
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-     "metadata": {
-      "needs_background": "light"
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-     "output_type": "display_data"
-    },
-    {
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\n",
-      "text/plain": [
-       "
"
-      ]
-     },
-     "metadata": {
-      "needs_background": "light"
-     },
-     "output_type": "display_data"
-    }
-   ],
+   "outputs": [],
    "source": [
     "for key, dd in stuff.items():\n",
     "    baseline = dd['base']['information_specificity'].to_numpy()\n",
@@ -2723,58 +2354,9 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 23,
+   "execution_count": null,
    "metadata": {},
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "\n",
-      "U-test: U value 4857.0 p value 0.00013747228542563089\n",
-      "_11\n",
-      "U-test: U value 2511.0 p value 0.0003908085167909787\n",
-      "_30\n",
-      "U-test: U value 1149.0 p value 0.18980799435841422\n"
-     ]
-    },
-    {
-     "data": {
-      "image/png": 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\n",
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-     "output_type": "display_data"
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\n",
-      "text/plain": [
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-     "metadata": {
-      "needs_background": "light"
-     },
-     "output_type": "display_data"
-    },
-    {
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\n",
-      "text/plain": [
-       "
"
-      ]
-     },
-     "metadata": {
-      "needs_background": "light"
-     },
-     "output_type": "display_data"
-    }
-   ],
+   "outputs": [],
    "source": [
     "\n",
     "for key, dd in stuff.items():\n",
@@ -2793,55 +2375,9 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 24,
+   "execution_count": null,
    "metadata": {},
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "U-test: U value 3974.0 p value 0.2766869426478231\n",
-      "U-test: U value 2049.0 p value 0.25046855806374924\n",
-      "U-test: U value 1000.0 p value 0.9251527394243083\n"
-     ]
-    },
-    {
-     "data": {
-      "image/png": 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\n",
-      "text/plain": [
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-     "metadata": {
-      "needs_background": "light"
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-     "output_type": "display_data"
-    },
-    {
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jBFuB31VK7a247rno0aMCtaskTiul3lDjmMFgaDFN8YiiEYzrqXMejpTyyRwVoR8CH40T+KQuU/oT9NDxz5gxHB0RT4G424iNwdAZNHTULMocvhKdQFd3hT706hZZtGdTWXRqDXreiw+8REpZOZkzFqL1i2jfYDC0kIYJUVSwaStHq8d9jqNZmwslriv8s2rDhUovyxJPN7iw4nAsRPOdSW0wGBKmkR7RmegJmQ8CL5qtFMY8+Bg6xf+Xs5wTT1WonPRoPCKDocNoZIxoL/CHSqmbFnsjpdRdVCw2NxMp5TPRKf8wowpeVMf5FHS3bVpK+Vn0DOgBdOGu66N0foPB0EY0TIiieUtV14xqJFIvIRMnVu1DFwWLib2hEO0R9VVc/h4p5Y3olSGq1auZrw3/D0DVWPPJYDAsjI6a4hHNHL8GXToU4G9nzqTmqBCl0PV6LkDPdP8d9AzpaXSm6DErQ9TBueedd96b0IJn/pl/5t/Rf3XRMZnVkSf0Hxwt/fBvSqlKQVmHLrtwQCn1xRm/L6HXeVoH3A28QUr5BtNNMxjag44Qoqgw1k84Wp/4+xxbLQ+AKD5VM0allLpXSnk7unzCxRytsmcwGBKk7btmUQD6Ho6K0NXAX9ZYS2o+xNnWT5r1LIPB0DLa2iOK6qDchE4NCNArmX5jjmtsdNH1WvVoYvF1axw3tAHXX389n/nMZ/iDP/gDvvSlL/Gf//mf3HzzzQwPDzMwMMD555/Pe97zHi644IJjrtuxYwff/e53eeihhxgZGSGbzXLWWWfxqle9issuu4yTT56tAKUhKdrWI5JSPgM9InYmeh3xP56HCA2hBeajs5z2/Gi7afFWGprN1NQUf/Znf8a3v/1tCoUC5513HoVCgTvvvJPLLruMu+6668i5q1ev5m1vexvXX38909PTPOUpT+H0009n69atXHPNNVx88cXs39+QFZINDaYthUhKeSI6fnMKumj57ymlZktujNmETnR8p5TyOG9P6tVJ46ztn1YeN7Qf9957L+Pj41x77bXcc8893HDDDdxxxx1IKfF9n6uvvvrIuVdddRWFQoFLL72U++67jxtuuIGbbrqJW265hRUrVnDw4EG+/e2Gl5A2NIBEhUhKebaU8mlSyrMrDv0zepZ9APxZtXrBNfgqegjxfPRKGstmtHURR+v7/jhancDQAXz+85/n5S8/OqXwtNNO48Mf/jAAW7ZsIZ/PH/kZ4K1vfSuZTObI+WeddRaf+tSnePWrX80ZZ5yBof1IOkb0Q3Sh85XoQunxwnTx+lMF4O+lXqa5Ft+LVjVAKbVSSvnX6MLp7wL+VEqp0AXN4+D0TTRwNVJDc7Ftm1e+8pXH/f7cc8898nMul2NwcJBzzjmHrVu3csUVV/Dxj3+cCy64gHRal6V6zWtew2te85qW2W1YGEkLUTVeylG7lqBXs5iN22fuKKW+IaV8APg4OvHxmehExt+ih/2va9bKCobGs3z5cvr6KhPkIZvNHvnZ8/S4xCc+8Qk+8IEPsHbtWi6//HIGBga48MILeelLX8pFF13EihUrWmW2YYE0VYiUUivmOH5Rld/9L/NfebTWfR9BrzFm6HBij2Y24uJ+r3zlK/nFL37Bd77zHe666y7y+TwrV65k5cqVXHXVVbzgBS/gi1/8IuedV23FHEOStKNHZDDUzdOf/nT+9V//Fdd1Wbt2LQ899BD3338/jz32GKtWreLyyy/n1ltvZWBgMQvRGhpNW46aGQwLxfd9du3axSOPPAJoT+qCCy7gQx/6ENdddx3XXXcdQghGR0e5//75jn0YWoXxiAxdwbZt23jLW96CbdusXLmSU0899Zjj559/PoODg+RyOYKg3qR8Q7MwHpGhK3ja057GU5/6VHzf52/+5m84cODAkWOO43D11VeTy+UYGBg4LhvbkDzGIzJ0DVdffTWXXHIJDz/8ML/3e7/HmWeeSX9/P3v37mVqagrbtvniF7/ISSedlLSphgqMEBm6hvPOO48bbriBa6+9lgceeIDh4WHCMOS0007jta99Le9+97t5ylOekrSZhio0bV2zbkZKufG88857xo033pi0KQZDu1FX6o2JERkMhsQxQmQwGBLHCJHBYEgcI0QGgyFxjBAZDIbEMUJkMBgSxwiRwWBIHCNEBoMhcUxmdY9TKBRwHCdpM3qeTCbT06VJjBD1MB/84Ae55pprMNn1ySOE4P3vfz/f+ta3kjYlEcwUjzrohikehUKBJUuWGBFqI4QQRyoEdDBmiodh/jiOY0SozQjDsGe7yaZrZgBgaGiI5cuXJ21GzzE5OWmK+mOEyBCxfPlyTjjhhKTNMPQopmtmMBgSxwiRwWBIHCNEPUomk8Gy9Ntv2/YxSzQbWod5HzRGiHqUgYEBPvKRj2DbNh/+8Ic7fci4YzHvg8bkEdVBN+QRGQxNwuQRGQyGzsQIkcFgSBwjRAaDIXGMEBkMhsQxmdUGQwKEQUBpx4MExcnjD1op+s99MVb/0tYblhBGiAyGBChsup3Rn36S0Csfd0xYKZZc+FZOufjK1huWEEaIDIYE8Mb2EpRzBLnDkMoePRB4CCuFN74vOeMSwAiRwZAAgVOEwEf0LSO1/PSjvy/l8HOHCJ1Cgta1HhOsNhgSICznIQwRouIraFkQBASlXDKGJYQRIoMhAYJynjDwtfDMQAgbwoDQKSZkWTIYITIYEkB7RAFUekTCIgwDgh7rmpkYUQ8yUpjm2xtWknOPjtjYwuKt557PhaevSM6wHiJwChAGNbpmPqHnEHouIpVOxsAWY4SoB1m5byt37NnC5Az3P2un8MPACFGLCMp5CILjumZHPKQwJHAK2KneKN9rumY9yJRboux7CGBZpo8+O03Rc5l2Skmb1jOEToGwStdMCAFCQOjr7luPYISoBym4DkEYkrXTLE33MZjK4IcBebc3V5BIgrhrdlyMCHScKAgI3N4JWBsh6kGm3RJBGGALXTrGEhZBGJJzjUfUKsJyFCOy7OOOCWHpkTPjERm6mZxbxg9DrOhpbAuBHwaUfA838BO2rvsJw5DAKRIGge6GVWJpIQrKvTNyZoSoB5l2Kj0iAaH+guRMnKjphG5Zd8vCAMTxHlHcNeul7GojRD3ItFs6xiMSQmBFXtGU6Z41ndAp6BEzqOoRxV2zwHTNDN3MlFPCn+ERAdiWhR+GTJWNEDWbYEYyo6jWNYtjRMYjMnQrJc+l6LlaiGbksNjCwg+CY3KLDM2h1tD9Eawou7qHPKKmJjRKKd8HXAP8lVLqu3VcfzLwOeAtwJnAOHAf8I9KqQdnue5s4PPA64HTgFHgDuAqpdTmhdrRTUw6RYIwQADWjAUXbGHhhwETRoiajk5m9BGVyYwxwtYTX02wevFIKS8E/mkR158OPAT8NXA6sA4IgYuBe6WUf1HjOgk8BvwlsARYC/QBlwKPSSl/v16buoGJchEvDLArugWpWIh66MOfFEGteWYRwjJds4YgpbwIuAVYTK3L/wHOBW4DzlRKXQA8Efg0YAPXSCmfXtFuCvg1cDLwI+AJSqkLgScA/44WpJ9GnlZPMl7O4wdaiGZiWxZeEDBe6p0Pf1KE5ZzumlXJIQKiUTO/p0qBNFSIpJR9UsorgduBExdxn4uAVwE54M+VUuMASqlAKfVV4MdAGvhsxaXvBM4DdgPvUUoVo+sc4KPAPcAJwMfrta3TOVzK4wUBqYpuQewRHe6hD39SxPPMjpvwGnNk1Kx33ouGCZGU8jxgK3BF9KvPAbvqvN3l0faXSqlDVY5fE23/SErZX+W6H0XicwSlVAj8R7T79jrt6ngOl/L4YUCq4mmcsiy8wOdQqXcCpEkRlHIQHl+LKEZYtp6B30PB6kZ6RGcCZwEPAi9SSn1pEfd6SbS9t8bxhwEPGAQuAJBSWsAL57juvmj7ZCnlWYuwr2M5XMrhBT6piqdxKuqajRkhajpBKaeLolVLZoSjNYlK0601LEEaKUR7gT9USr1EKbWq3ptEgvLkaHdHtXOUUi4QVxd/arQ9A4i9o6rXAXuAeA7DU2uc09WMFnO4QRWPSNh4YcB4uYDjewlZ1xsEpelonlmt4XvtERkhqgOl1Hal1E0NuNWJHE0rGJ3lvMPR9pRoe9qMY1WvU0r5QLyQ1CnVzul2DhamcAP/uBiRFY2g+WHAaLF3YhNJEJSmZ/WI4q5ZUDRClCQDM36eLc03TngZqNgu9LqeIQgDRorTeIFPusIjEkKQtmxc3+dAocqif4aGERQnIfBnHzWLysWGPeKdtqMQLXT6d7jI63qG0WIOx/cICY+LEQGkLQs38NmfN0LUTILCJGHgVy0BAmiBCkM9clacaq1xCdGOQjSzX9A3y3lxPChOfKn3up5hf34y6pbZVec4pS0bN/AZNkLUVObyiIQQYNmEgY9fmGixdcnQrkIUV3WfLfEwjvGMRNuZw/xVr4sSHuMiwCPVzulm9uYncHyfTI0vQNpK4QY++/K98eFPCr8wGU3xqOEREceJPAIjRMmglAoAFe2uqHaOlDKNzrIGnbuEUmqYo4Hoqteh0wvid3/rIk3tOPblxnEDn7RVfYphxrZxfI+9ufEWW9Y7BOUCoVOM1jSbZaqnZRP6Pn5+rHXGJUjbCVHEQ9H2JTWOvxA9slYCVs/4/cNzXPfSaLsrEq6eYvf0GI7v1fSIMpaNE/gcKEyZIfwm4efHdLdMiNrD94CwUtojMkKUKD+Ltm+TUp5U5fgHou3/xNM4Kq57t5QyU+W690fbHyzexM5j1/QYTuCTsas/iW2h5+Mbr6h5BLnDhIGnhWY2rBRh4OFPH579vC4hUSGSUp4tpXxaVLZjJnegs6CXA/83momPlNKSUn4SeAfgAl+tuO7H6GTGJwM/kVIuja7LSCm/Abwc3X37t2b9Te3KtFPiUCmHE3hk7NpB0qydoux77JzqjS9Aq/GmR/WQfI2HQYywU+B7+LlqM5y6j6Q9oh8Cm6PtEaJ5YZehs7VfAeySUj6Kzqb+Knro/d2VtYWUUiX0PLJJ4K3AsJTyEWA/8BHAAS5WSvXct2zn1CFc3ycl7ONm3s8kY6dwfI+dU73xBWg1/vQoBB7CnmMFVztF6Ht4U70xppK0ENVEKfU4cD7wNbQAPRs9LP8b4HeVUtfVuO4R4LnAtcBE9HMA/C96Dtydzbe+/dgxeYiS75Gd40mctbRH9LgRoqbgTx4k9N3ZA9WAsNOEvoc/ebBFliVLUys0KqVWzHH8ojmOH0KX7FhQ2Q6l1C7gPQu5ptvZPjlC2XfnFiI7xVi5wPaJEcIwrF5T2VA33uQBQt9FpGZLddNChO/gTx3sifehbT0iQ2PZNjFC2ffom0OIMnYKP/SZdIrsL/RGVm8r8Sb2g+fOr2sW+ATlAkEPTLkxQtQD5Nwye3JjlH2P7BxfAEsIMlaKku+xbaI3ugWtxBvfp7tmqdnfByGsKE7k4E3sm/XcbsAIUQ+wdeIgZd/HFtZxs+6r0ZdKU/Jc1LgRokbiF6f0PDPfRdjVskuORdgZQs/BG9vbAuuSxQhRD7B57AAlz6UvNb+QYJ+dpuS7bB7f32TLegtvbA+h74CVmjWZMUak0oSei3u43kKnnYMRoh5g09h+ir5D/1xxiYj+yCPaPjFKyXObbF3v4I7uJPQcRGpubwhApLKEXhnvkBEiQ4cThAFbxvdT8lz654hLxKSEhSUEBc9hq4kTNQx3dIjQLSPS2XmdL1IZQq+MO7qzyZYljxGiLmfH5CGmnBJBGJKZa1pBhBCCvlSaouey/nDPTclrGu7IdkKvvECPyME9NNT1BdKMEHU56w/voxh5QwvJRem3MxR9hw2Hu3/EplU4B7dpj2iOHKIj2GkIQwKn2PVxIiNEXY4WIof+eT6FY/ojj2jT2H4zE78B+IVJ/MkR7RHNt2smBCKdJXRLOPvV3Bd0MEaIuhg/CFh3aB8Fz513oDomLhWS88pmGL8BOMObCN0SIpWZtSBaJSLdp4VoeEsTrUseI0RdzPbJUSadIkEYzDm1oxIhBAOpNEXXZc2hPU2ysHdw9m0idIuI9Dy7ZREi3U/olHCGNzbJsvbACFEXs3p095FuWT1zlfpTGQqeY4SoAZT3bSRwSoh0/9wnz8DK9BG6Rdm2+ZsAACAASURBVJzhLYRdnEphhKiLeWx0DwXXYWCB8aGYgVSGouewZewAebc89wWGqoRBQHnPOkKngMgsTIiwM4RAUM7jHOjeOJERoi6l6DlsHttPwXMYmGf+UCVpy8a2LAqeyzozelY37qEhgtyYrsy40K6ZEFiZfkKnQHn3miZZmDxGiLqU9YeHyXtlLGEdt5jiQhiIumePjexuoHW9RXloFUHkDdXTRRaZAQKnQGnX6rlP7lCMEHUpj43sJu86DNYZH4o5IkSjRojqpTS0iqCcx8oM1nW9yAwQlvOUh1bp1T+6ECNEXcqq0V26W5auLz4UM5BKU/Zd9ubGzcKLdRAGAaWdq3R8KFvfKuci3UcYBvj5CZzhzXNf0IEYIepCRgrT7J4ep+TPf35ZLSxh0WenKXguj410d3ZvM3D2b8aPCuYvdMQsRseJBgnLeYrbH2iwhe2BEaIuZNXoLoqeQ5+dnrVQ/nwZSGUouGXTPauD4rb7Cct5rOzgorrIIruEoJyjtOPBBlrXPhgh6kJWjeyORssW1y2LGTiST7QXr0tjFM2itO0+gnIOka0vPhRj9Q0SlAuU96zHz3ffmnNGiLoMPwhYM7rnSKC6EWTtFCEw6RTZPHagIffsBfzpQ5T3btCB6r6li7qXsNOIVJqglKO47b4GWdg+GCHqMtTEQSbqnNZRi3i6R8F1WG2yrOdNYes9BOU8IpXVCyYuEqtvKWE5R3HL3Q2wrr0wQtRlPDa6+0g2dSOXoDH5RAunuPkugtL0or2hGNG3lKA4TXH7/QROce4LOggjRF3GmtE9DY0PxejpHi5bJw4y7ZQaeu9uxC9OUdzxkBai/mUNuadIZUEIgsIEpe33N+Se7YIRoi6i6DlsGT9AsQH5Q5WkLJu0ZVH0XNYd6v5VJRZLcctKgtIUwkrPuyLjXAghEP3LCIrT5Dfe0ZB7tgtGiLqIDYeHKXjOoqd11KJ/xuiZYXYKG24jKE41zBuKsfqWEpSmKKq7CcqFht47SYwQdRFrD+2l4Ll1T3KdizhOZCbAzo6fH6e440GCYuO6ZTEi3QfCIshPUFTdE7Q2QtRFrD20V3fLGhwfium39XSPXVOHGSvlm9JGN1DYeBtBaVpXY2zweyGEwOpbhl+cJL/+Nw29d5IYIeoS8m6ZxydHjxTKbwa2ZUXLUbtsMKt71CS/9maCwiRW//Km3N8aWEZQmqa47X783FhT2mg1Roi6hM1jByj6LilhkWpCfCgmXmZow5gRomq4h3dT3rOOoJxreLcsRuclpQmKU+Q33NqUNlqNEaIuYePYMEXPpa9J3lCMXt3DYaMRoqrk19yog9SZgYYkMdbCGlhOUJwkv/bGprXRSowQdQmbx/X69gtdrWOh9NtpSr7H0ORhip7T1LY6jTAIyK+9Eb84iTVwQlPbsvqW6fKx+zbijOxoalutwAhRFxCEAWr8IEW/+R5RyrKxhUXRd9lilhk6htLQo7hje/XaZX1LmtqWsFNY2SX4xSnyq3/d1LZagRGiLmDX9Bg5t0QYhkfWI2smfbYOWG+bMEI0k/zqXxMUJrD6liEaUH5lLqyB5QSFCfLrbur4JamNEHUB2yZGKPseWTvV0PlltehLpSl7LlsnRpreVqcQlHIUNt1B0IJuWYzILiH0PbyJ/RQ7fMqHEaIuYPvkKCXfJdvk+FBM1k5R8j12TI62pL1OIL/hVl0nSNgLXqmjXoQQWP2RV7T6Vy1ps1kYIeoCHp8cxYk8olaQtVI4gceBwqRZ7ywivybqlg0sb4lXGmMPnIBfnKKg7u7onCIjRB1OGIYMTR8+0jVrBbZlkRIWju8zNHW4JW22M+7oTsq710a5Q81JYqyFSEc5RYVJ8utubmnbjcQIUYdzuJQn55TxgqApE11rkbG1V7RrunOfwo0it+ZGHRvKDjY1d6gW1sAJWojW/JowDFvefiMwQtTh7M6N4QQeadvGamGXIGOlcHyfPR3cHWgEYRCQX3cTfmESq781QepKrP5lBE4eZ7/CPbA1ERsWixGiDmc4N4Hj+y0Ztp9JxrJxAo99uYmWtttulHY8iDe2j9B3m547VAth2Vh9S/GLk+TWdGZOkRGiDmc4P4kb+KSt1nYJ0raNG/g9v+hift3NulvWv6ylQepK9OjZJIUNt3RkTpERog7nQCEWotZ6RGnLxvV9RorTBGHQ0rbbhaBcoLD5zkiIWhukrkRkBwkDD2/iQEeufWaEqMMZKebwAp+01dq3MiUsgjDE8T0my91VyH2+FLbcFeUOWS3LHaqFzilapifCduDomRGiDudQMYcbBE0t/VENIQQpy8ILfUaKuZa23S4UNtx6pBxskt2yGKt/OUFxisKWuztulQ8jRB2MF/hMOkX8MCDVgrlNldjCwgsCxsu9V63RL0xS3P4gQWkKq685dYcWivbKBEFhnOLWe5I2Z0EYIepgJspFgjAkDMOWDt3HpCwLPwgYK3VPEff5UlQrCYpTegXWdDZpc4CZ3bMpCpt+m7Q5C8IIUQczFXlDtmUl0jWwhYUfhkx1WDegERQ23Rktntge3lCM6Fuqy8huvY+gg6bfNGzMV0o5AHwSuAR4EjANrAK+ppSad/RMSrkC2LmApr+glLpyxvUXAXfOcc0vlVJ/tIA22pJpt0wQBtgJdMsgFqKAXAd94BtBUC5QevwhwtI09snnJG3OMRztnk1Q2vEgA097VdImzYuGCJGUchC4A3gR4AIbgJOB1wGvk1JeqZT6wjxvVwLum+OcM4AV0c/bKo49N9ruBx6vcf2medrS1uScEn5C3TIASwi8MGDa7a2VX0s7HiQoToFlQ5NWTKkXIQSib8kRr6inhAj4JlqE1gBvVkrtAZBSXgp8D7hSSnmfUur2uW6klDoAvLzWcSnlUmB1tPttpdR1FafEQvR1pdRXF/ZndBYl30ssPgRaiMIgpOR1XgLdYihuu4+glENkl7TFaFklVnYJ/vQIxe33EYZhW9pYyaJ9einlucA7gQB4RyxCAEqpHwFfiXavXGxbEdcA56JF7+NVjsdCtL5B7bUtRc8hCEMskvmgCSEIwpBCD9WuDsOQ4vYH9Ez77GDS5lRFZAcIPQdvfBj34PakzZkXjQguXArYwANKqWpdnmui7cuklGcvpiEp5RuBPwc84N1KqXLF8RTwzGh3w2La6gTKgU9Ack88C0FIiBv4ibSfBN7h3fgTBwg9B5EdSNqcqghhYWUGCMsFSjsfSdqcedEIIXpJtL232kGl1D5gV7Rbd4dVSpkG/iXa/YZSak2104AsMKmU2l1vW52CG3XNknK8hRCEgBv0TtestPMRAqeASPe3pC51vYjsIIGTpzS0KmlT5kUjYkTnRdvZ1jQZAs4BnrqIdj4UXT8GfLHGOXG3bKOU8vnoLuOzAB/YCPyXUqprumxeNMcrKY9IoLsqXtA7c83Ku9YQOgWsNvWGYkRmgCA/ru0NAkSLpwAtlEZYd1q0na2AcVzG75R6Goi8oU9Eu19TStWa8h0L0XPQqQMfB14LvB74W2CNlPIf6rGhHQnDkHYogxV0aDGueijvXU/gFBGZNheidB9h4BHkx/EOt3/noBFCFL8js43hxhlv9b57lwBPBKaAf5vlvFiI+oAvAU9Gd9WeAnwN/RD/rJTyk3Xa0VYkLwC6axa0hRw2Hz83hje+j9AtJT7JdS6EEIh0P4FbpLy3/TsBjeia+cxf0Or9xH4s2n5LKTVbJa5fA8PAjUqp/53x++3Ax6WUh4B/AK6QUn5PKXWoTnsMQP1vZ2fiHFBahFIZRIsnGdeDSPcRuiWcA5Wpdu1HI4QoB5yI9kJq0R9tFzwpKUoPeEG0+4PZzlVK/fsct/tn4NPAEnSy5U8Wak87kVT+UCUisXB5a3EPbiN0y23vDcWIdJawlMM92P5C1IiuWexVnDzLOXFsqJ4V+S6Oto8ppVQd1x8hGu6PUwyetJh7tQNCJC8BArDbRBCbjXNwh15OOtUek1znQqSyhG4Jd2S2caT2oBFCtDnarpjlnPhYPZW93xJt5+W9SCnnelzFf7Nbhy1tRVz6I6lQUcjRukS9gDe+V+cPtdm0jlqIVJbQd/Hz4wSl9q4Z1YhP0EPR9iXVDkopzwTiRMYFrYsrpcwAL4x2Z50eIqV8jpRyEihGQ/fVzukDnhHtdvx8M1tYUbcoGSWKl66x2jifppF4Y1qIsDtEiCwLLJvQd/HG9iZtzqw04hP082h7kZRSVjn+/mi7Uik1tMB7PwfIoEfdNs5xrkJPMwG4vMY5H0aP3B1CT9LtaFKWjRDJhYxDdHyo1fWykyBwy/i5Mb1aR6o1S3s3ApHKEPoO3sRw0qbMyqKFSCm1Dd1tsoHrpZRxgiNSyncCn4p2j8vfkVKeK6V8mpTyCTVuH3s2W5RSs6bvRvGff412Pyyl/KiU0orasaSUHwSuio5/WinV8UV00pb2iJJaVC8kjGJE3e8R+blDEPggBHTQ3yusFPg+fq69V+Rt1Oz7jwLPjv5tkVKuR4+kxcVaPltj5v0d0Tn/RXUv5oxoO99V/L6M7npdAnwdPUz/ODpGdQr6IX6lUuraed6vrTnqESUXJBJCkElgddNWE+QOEwYewkp1xGz2I1gpwsDTQtrGNETalVKH0TGiL6AD0k9Hj6KtBN6qlPpynbc+NdrOaxU/pZSvlHo78KfArdGvn4sOTP8MePkC6iK1PWnLjjyiZNoPIo+o1SuIJIFfmNAeUYd1Q4VlQ+ATFKeTNmVWGvYoU0rl0aU+rlzANSvmOP5B4IN12PJzjsauupYjQpRgYqEQvREjCssFwjDoOCHCssB3CNp8gYPuf5R1MWk72a5ZEIYIBJkWrzKbBIFTgCBo6xn3VREWYRAQGiEyNIu0SLZrFhIiBL2RR+S7REGxpC1ZGEJAGBL67Z021wOfoO7lqEeUEGHvDN+HgZ9c5uii0MIZtvmy4EaIOpiUMMP3LaPNv8i1iGSo7e3vgU9Q92JHXaIkExoR4ogdXY1ld163jDh+KHQ+URvTA5+g7sUSInrkJThqRvtUAWgmwo6yqTute6YnBEKb53oZIepgjs41S4joO9kTQpTK6IzqNu/iHE8AQiDafH6cEaIOJqnYUCXJFyNpPlZ2UA+Fd5oQRSkH7V5j2whRBxPO+D9J2qNydnMRmQE9m73ThCgMQFiITHuuwRZjhKiD8cMgClkk5JFEzQZB9wuR1b8MhJ4u0UmE0bQUq39J0qbMihGiDsaPlvFJbF0zouWEOs1LqANr4ASEZesvdicR+AjLxh44IWlLZsUIUQfjBr6eZpHYumZ6FQ/H7/4FFu2BE/QQfhgSdtA6bkc8IiNEhmZR8l1CQqykemZCEIQh5R4QIpEZQKSz0Wz2Dvp7Aw9hp7CXzFZSPnmMEHUwJd87MvE0CSyhZ/6X2nweUyMQQugvc1Tfp1MIfQ+sFPagESJDk8i5ZYIwTKxmtCUEfhiQc8uJtN9q7KWnIOwUdIgHGAYBhAHCSmEvrWuR5ZZhhKiDyTkl/DBIbDkfW1gEYci0M9siv92DvfRUsFPay+gEAg9h2VjZAUTWDN8bmsREuRgJUTJvoy0EXhAw6XR8+e95YS89DdFBXbPQd8FOa0+uzbPfjRB1MGPlPH4QJDbp1BYWfhgwVsq3TZZ3M0ktO1XPOeuQmFjoR4HqZacnbcqcGCHqYA6X8nhhcGShxVaTsmz8MKDku+Q9JxEbWom9/HSw053TNfNdhJ02QmRoLgcLU7iBn1hhMksIbGHhBgEjhalEbGglqWWnR8HqDvGIAg/sFKllpyVtypwYIepQHN/THlEQkEqwQmJKWHiBz/4eECJ7qe6ahYHXGV1R30VYaexlp859bsIYIepQ9uUn8AI/qpCYXCAyY6dwfJ99ufHEbGgV9tJTj67i0QFTPY7GiIxHZGgSe6bHcXyfjJ3sgn8Zy8YJPHb3gBCJVBp78ISOGTkL/ahrttQIkaFJDE0fxgk8MgkXrtcekcfQVHsvadwo4lyidk9qDMMwyiNKt30yIxgh6lh2TI5S9j2yCZcAzdopyr7HrqnDuB3QXVks9pJTOsMjCnxdUdJOYQ2elLQ1c2KEqAMJw5DtEyOREKUTtSVOHSj5bk94RdbgSR0xzSOMsqrtgeW6oFub0/4WGo7jYHGaQ6U8TpC8RySEoC+VpuS7bBk/kKgtrcBechJ0Ql2iwAcrhTV4YtKWzAsjRB3I5rH9lDyXPjvVFoXr++w0Rc9l89j+pE1pOtrDSLX/qNkRj6i96xDFGCHqQDYcHqboO/Ql3C2L6Y+EaP3h4c7Ir1kEVt8ysCwI21uIwiCISsQuT9qUeWGEqANZc2gPRc9lINUeS8T0pdK4gcdIcYrh/GTS5jQV0bcEhN3+VRoDH2FZWH3tXas6xghRh3GwMMXe3AQl36Uv1R4ekSUEfXaagueyenR30uY0FSs7GK3m0d4eUaes3hFjhKjDeHRkF0VPd8vaac35gVSGglvm0ZFdSZvSVEQqq1dObfMuaBiGICysdF/SpsyL9vkkG+bFIweHyLtlBtukWxYzmM6Q9xzWHNrb1TWsRboP6ID1zcJohdd0e31OamGEqIMoei6rR/eQ9xwG09mkzTmGjJVCAFNOsau7Z8JOgRDt7hABofbcrPZe8z7GCFEH8djILqacEhYi8akdlQghGExnybllHjjweNLmNJE4XaLtlQgBHZHMCEaIOop79+8g55YZTGfbsvTnkliI9j+O1+55Nt1O++vkMRgh6hBKnsuDBx4n55ZY2mbdsph+O00Qhhwu5Vkzujdpc5pC6LtAcotazpuo+xh6nVHEzQhRh/DIyBAT5SIgEp/WUQshBEvSWabdEiuHtyZtTnPw3WjErP2FCAJCvzNK+Boh6hDu3KuYjryhdn4aL01nmXbK3Ld/B6UOeRovhMArH8nRaWuEpZfH7pA159r81TQATDklHj64i2m3zNJMe+eFxNNOxksFHjq4M2FrGk9Ymj4yfaKdEcKCwCco5ZI2ZV4YIeoAVu7bypRTJC2stu2WxQghWJrJMuWWuH3PlqTNaThBcRpCv/1Hoyw9DSUoTSdtybxo81fTAHD7ns1MOaW294ZilqX7yDklVo3s4nCHPJHni58f0yVA2t0jsmwIPPz8WNKmzAsjRG3OzqlDbB4/QMFzWNoh6foZO0XGTjHldJ9X5OcOg+/pUiDtTFRF0p8+lLQl88IIUZtzy65NTDslBlMZUu3eHZjBskwfU06JW3dv6qrSIP7U6JGi9O1MXEXSnx7tiNe/cz7ZPYjje/x27xYmnSLLOqRbFrM0naXsu+yaHmP94X1Jm9MwvIl9hL6DsNt8DpedJgx8QqdEkGv/Er5GiNqYe/fvYLSYIwzDtqk9NF8sYbE03ceUU+TmXRuTNqchhGGIN7YPPL2UczsjhNCLQfoO7lj7J5caIWpjfrNrY+QN9bd17lAt4u7Zvfu3M1kuJm3OoglyhwlKOb2CR5vUgpqVVIbQc/AOt39pFiNEbcru6THWHtpDzi2zvMO6ZTF9qTQpYTFZLnL73s4PWjsjOwi9MiKV0Xk6bY5IZQm9Mu5I+09CbljETUo5AHwSuAR4EjANrAK+ppS6uY77rQDmyohbq5R6XpVrnwV8Dng1cAKwH7gJ+JJSqiMCFjfv2sCUU2IglUl0bfvFsjzTz6RT5OahDfzxk5/XkZ5djHtweyRE7TnXrxKRzhKWcjgj25M2ZU4aIutSykHgt8AVwJOBjUAeeB1wk5Tyijpu+9xoOwbcV+Pf6iq2vAJ4BPgz9N+3HjgZ+ACwXkp5nHC1G2Xf4/Y9Okjdqd5QzNJMlpLnMjR9mDWH2j9WMRvOfkXolqLiaO2PSGUJ3ZK2u81HzhrlEX0TeBGwBnizUmoPgJTyUuB7wJVSyvuUUrcv4J6xEP1MKfWB+VwgpTwJ+CXQB3wV+JxSypNSLgW+D7wV+F8p5dOVUm07G/DufVsZLU4ThnRckLoSS1gszfQxWS5y09AGzj/1rKRNqhtneCOBU9TLTncAIp0lDDyC/DjexDDpE89I2qSaLNojklKeC7wTCIB3xCIEoJT6EfCVaPfKBd46FqL1C7jmo8CJwINKqU8rpbzIjmngz4HH0R7bZQu0paXctGvDEW+ok7syMcsz/Uy5Je4/sIOxUj5pc+rCL07hHtqtu2ad4hEJC5HKEjhFnL0bkjZnVhrRNbsUsIEHlFKbqhy/Jtq+TEp59gLuGwvRQl7By6PttZUHIg/oe9Hu2xdwz5ayY3KUjWP7ybsOyzL9SZvTELJ2ioxlM1kucuvuah+R9qe8ey2hW0TYaZ0s2CGIzAChW6C8e23SpsxKI4ToJdH23moHo+BwPH74qvncUEq5BO25wDw9IinlE4BzZrMFHVcCLYptOf5605AOUg+mOyuTei6OBK13bSRo98LzVSjvXkPgFBCZgaRNWRBWpp+wXKS867hwalvRCGk/L9rumOWcIbRIPHWe93wOuvLUMHCqlPLvgPPR9m4F/lspdV/FNbEdIbVH24aibRY4ew6bW07BdXQmdbnI6QNLkzanoSxJZxktTrM3N86jI7t54ekrkjZpQZR2PkpYLiA6ZOXUGJEZIJgYxjm4HT8/jj14YtImVaURj9zTou3oLOfEOeanzPOecbfsRGAT8P8BbwBeC3wIuFdKeW2FVxPbMaWUqlUNamau+3xtaRl37lOMlQoIocuudhOWECzL9EVeUXvHKyrxC5M4w5sInAJWtrM8ImGnEKkMgVOgtPORpM2pSSOEKH5nSrOcE6fVzvddjIWoD/gO8Ey0F3MOOj/IBf4C+HqddizElpYQhuGMIHVnZlLPxfJMP9NOiYcO7GSk0Bl1cgBKOx/R3pCdafupHdUQmUHCcp7SjoeSNqUmjeia+cxf0OabzHBPdM/VSqlvz/j9buBLUsoh4MfA+6WU31RKbYzsWAhtlVixbXKEbRMjFDyH0/u7q1sWk7FTZKPyILfu2cQ75YuSNmlelLbdT1DOI7KdsXxzJVbfEvzJgxS33U8YBG1Z1K0RFsWVr2Yb04yHfwrzuaFS6jql1HsrROiY48A2dBzpLXXYMW9bWsXNQxuYKhdZks5it+EHpVHEQetbdm3CD9o/aB0GAcVt9xKUclh9S5I2py5Epp/Qd/EmD+Dsb8+pNo34xMeVl06e5Zw4HjPSgPZi4mGAJ1XYsXSWEbGZcaFG2rIoip7DXfu2MumUOq7cx0IZTGdxfZ/h/ASrOmBFWGffBrzJEULf7bgRsxghLKzsIGEpR1HdnbQ5VWmEEG2OtitmOSc+Nu81ZqSUaSnlbJOsYtvjpSI2z/h9rXyl2I4SsKfGOS1n5b5tjJW7M0hdiRXXtHaK3NIB5UEKW1YSlKax+pZ0dNxO9C0lKE1T3LIyaVOq0gghiiNgL6l2UEp5JkeF4f65bialPFFKOQY4HO12VeP8aLsJQCk1ju6u1bQFeGlss1KqbZYivWX3Rqa6OEhdybJMP1NOiQcOPM54G2dah2FIYdNvIyHq7Lid1beEwCngHNiKe7j9PNFGCNHPo+1FUkpZ5fj7o+1KpdTQXDeLBOVAtHt5tXOklG8DzkWL1fUzDv0s2r63yjUZ9EgbwA/msqNV7Jo+zKYok7pTalIvlmxU03raLXFHG5cHcQ9sxT00pCe6ZjszPhQjLFvnFJWmKWy6I2lzjmPRQqSU2gb8BD3N43opZZxYiJTyncCnot1/qLxWSnmulPJpUVb0TK6Ktm+SUl4lpczOuOZt6AmsAP+olBqecd03gAngFVLKb0TiQzTp9Tp0tvbj0c9twa27NzHtlKNyH90bpK7kaE3rzW07Mzy/4TbtDWWXtOVI00Kx+pcRFKcobFzI3PPW0KhX96PoqRjPALZIKVdHQ+w/QqcIfLbGzPs70LGdq2b+Mpos+8/R7qeBUSnlKinlXrQHtgT4LrrsyMzrRtBz3xzgI8B+KeUjwD7gbWiRerNSqi2WIPUCnzv3bu3ImtSLZWk6S9Fz2Tl1CDVxMGlzjiMMQwobbyMoTmH1L0vanIZg9S3V3bPhzbijQ0mbcwwNESKl1GF0XOYL6ID009GjaCuBtyqlvlzHPT+BzqT+JToR8TlAGvg18Eal1F8ppY4b/1VK/Rq4APgfdCD7eeih/f8CXhDlHLUFj47s4mBhCj8MGOzwch8LxRIWS9JZpp0St+/ZPPcFLcbZux730C5Ct9zx3bIYYdlYmUGC4jT59b9J2pxjaNg0YqVUHl3q48oFXLNijuO3Awv2I5VS69GVItua2/dsYcoptv169s1iWaaPkeI0d+3dynuf+QoybTSrPb/uN9ob6lvaFd2yGGtgGX5+nPz637D81e9rm89d97zCHca0U+KhgzuZdss91y2L6bfThGHI4VKehw8OJW3OEULPJb/h1q7qlsWI7FJCt4w7OoSzdyGlvpqLEaKEuGd4O1PlErawyHZ57lAthBAsTfe13ehZcfv9+FMHCQO/Y6d11EJYlo4VFafIrbkxaXOOYIQoIX67dwtTbu8FqStZmulj2inx8MGhtllyKL/mRoLCJNbAsrbpujQSa2A5QXGSwsbbCL32qJhshCgBDham2HB4OMod6owVIZpF1k6RtmymnRL37E9+tQk/P0Fx6z0ExSnsDqs9NF9EZgDCAH9qhEKbZFobIUqAu/dtI+eW6bNTHb1UUKNYmtHds7v2qqRNobDhFvzCBNjpjqlNvVCEEFj9y/ELk+TX/DppcwAjRIlw1/BWpt1Sz2RSz8WSdJa867Dh8DCHirm5L2giudW/IihMYA10pzcUYw2cQFCcorj9Abyp5Od/GyFqMXtz42yfGKHouSzp8W5ZTNqyydop8l6ZlcPb5r6gSTgHtuLs20RQzmN1abcsRqQyiHSWoDhJfu1NSZvTuDwiw/y4e1h3y/pT6brqDpUn27+yYXb5wieILk1nmXbK3Du8jbeee/7cFzSB3Opf4RcnoykdkbepBgAAIABJREFU3d9ltgZOIChMkl/zK5a9/F2JBuaNELWYe4e3k3PLdXtDv73ssw22qPG84ZffWPA1S9JZDpXybB47wEhhmtNavHhA6Dnk191MUJjEXnba3Bd0AVbfMtzJgzgHd1DevZa+c5JbBNl0zVrIvtwEOyZHdbesQ9ZPbxUpy6Yv6p7df6D1i6sUt96DP3kQwu7LHaqFsCys/qW6e7bmV4naYoSohTxwYAd516Hfrq9b1u0MprPk3DL373+85W3nVv8KvzCB1b+8K3OHamH1R92zjbcTlJOrnmy+DS3kvv07yLllBk2Quirx6Nn6w/sYb+GXwpsapbjtfj2lY+CElrXbDohMPwhBMH0o0TpFJkbUIsaj+EfBczitv/7Z3K/54ZcaaFV7kbZsMpZNwXV49OAQrz37GS1pN7/uJoLiJCKdRfRYFYTKnKIl578pETuMELWIhw4OUfAcsra9qCTGekakOonBdJa8V+bBAztbIkRhGJJf/atoSkdveUMx1sBy3JEdlHY+iju2l/RJZ7behpa32KM8EgnRgAlSz8pgOkPeLfPY6B4c32t6e87eDTgjO/Qqrh1el7pehJ0+UkY2vzaZibBGiFqA43usPrSHvFtmMN1brv9CyVopQmDKKbJxbH/T28uvvUl7Q33LeiJ3qBZ23D1bexNhAuvNGSFqAZvG9jNZLhKiv2iG2gghGExlyHsOj44MNbWt0HOiukOTXT+lYy5E31JCt4R7aBfl3Wta3r4RohawenRP1C3L9NTQcL0MpDIUXIc1o3ub2k5x2334UyMQBh27eGKjOCanaF3ry8gaIWoBqw8dFSLD3PSnMpR8lx2To00dxtflYCcRPZY7VAurf3m0ykfr6xQZIWoyebfMjmiS60CqNysxLpSUZZGxbEq+y/pD+5rSRlCcPlJ3qNvKwdbLkTpF04cobr23pW0bIWoyG8f2U/BcUsIytYcWQH8qTdFzWX+4OUJU2HKnrjtkpbBMORZAx+dEtPZZvsVrnxkhajKbxvZT8l36jTe0IPpTGYqew8ax4blProP8hu5as6xRWH1aiIrq7pZO+TBDOE1my/gBip5rhu0XSJ+douR77Joao+g59DcwvubnJyjteIigOE361CfVdY/D+bZYo3NWTh5c+MNPpPvAsgjy4xS33cvgs17XBMuOxwhREwnCgG0TByn5Lif39caM7kaRsmxsISj5LlsnRnjuKY3L9i2qlQSlHCKVrntKxwv+ufVD3Atl6IoLF3yNEEKv8lGaprDpty0TItM1ayL781NMu2WCMCRj4kMLJmunKfkej08eauh9C5t+S1Cawuoz3bJqiL5lUTD/XgKn1JI2jRA1ke2TI5R9j6ydMsPDdZC1U5R9l+2TjaupHJTzlB5/mKCU69kpHXMh0lk9I78wSenxh1rSphGiJrJ7egzH94w3VCdZO4Xje+yeHmvYPYvbHyAoTuvpHCavqypCCETfEoLSNEV1d0vaNDGiJrIvP4ET+G21pnsnkbFsnMBnOD9BGIYN8SqL6h6C8jSib8mi7rfq75Irq9oKrL6l+JMHKW69hzAIEE0u5Ge+IU1kX24C1/cYNE/eukhbNn4QkHcdJsoFTlxkwD8MAko7HiAo5bCXP2FR96pnRKqTEJkBQt/FmxrF2b+F7BnNLcliumZN5HApjxcEpE1Z2LoQQpCyLLwwYLS0+PXOnP1b8CZHCH1PVyY01EQIgZUdJCzlKG2/v+ntmW9Ik3B8j/FyAS8MsIWJEdVLyrLwAr8hCy+WHn+IsJzHyg6awYN5ILKDBOU8xR3ND1gbIWoSObdMGIaEYYhtPvR1YwsLPwyYbsAwcmnnowROAZHt7Zn288XKDhI4BZy9GwicYnPbaurde5icW8YPAywhzNN3EVjCwg9DcoucDR56DuVda7RHlDHJpfPCTiOEICjnKe9e29SmjBA1iZLvEhBiGRFaFJYQhGFIcZFC5OzfQlDOEYIZtp8nQghEZpCgXGh6sTQjRE3CD0L0p94I0WIJ0UXuF0N5zzpCp4iV6Tce6gIQmX5Cp0B57/qmtmOEqEmEWoWMDDWCMCRYtBCtJ3CKPV+JcaGITD+hW8TZu7GptayNEDWJeFpHLEiG+ogTGbOLTAp19m8hdIt6drlh3ohUljDwCYpTeGN7mtaOEaIm0WensYRY9JO814njbH2LqOfkF6fwxocJ3bIRogUihECk+gjcEs4B1bR2jBA1iSXp7BEhMmJUP0EQYguLpYsQEPfgdkKvrNfvMvP+FoxIZwm9Es6BbU1rwwhRk1iW6SNrpbAsnQdjqA8v9ElZ1qLqObmHhrQQmdGyuhDpLKHr4B0aalobRoiahBCCU/qXkBYWbuAnbU5HEoYhbhCQsmxO/f/bO/M4ycrq7n9r66V6X6ZnelaYhTMb6wwwyCAMMDDsAooCwxIZUCPBoCioRFBDCL5vJGJQjMTgCypBQkQWEw0qUUBiEA0MeADZYYbZe3rvrqr7/vHcGoqml6qu5VZ3n+/nU59bt+7znHuqu+pXz3Ke81SPP2VHYtsrblcK22V3XISilXiJfga3vlS0e5gQFZG5dc1U+KksjNxJeClCuLSx0+PjF6LBna/jJQasRTROQpGYWwC7a1PRZs5MiIrIvLoWX4isRTQe+pMJKiJR5tQ257UDSrJjM15ykFBkcq+YLxqRGKSSeIP9pHp2FuUWJkRFZFHDNKoiUXqT5Z9ovRzpSwxSFYmxsHFaXnYSHW9BcpCQ5YUaF6FQiFAk6lpFHZuLcg8ToiKytGUmVZEYg6kEySIGg01Wev1tmJY3zxy3jXQMjJdKQtiEaNyEo5BKkOq2FtGEo6kyzrz6FqoiMXpKvIXvRCfppehPC1HLrHHbSfV0gJcCzwObuh8/4QheKkmyp6M45oti1djDwW3zqIlV0m1ClBM9gwNURWLsVd9Ke03DuO2k+jpdaygUtjVmeRAKR8BLkurbXRT7JkRF5rAZ850Q+dsKGdnRNdhPTaySVdPHtwFiGi/R71pDIfuo50UoBJ7nwiCKQME6zSISBz4DfAjYG+gEngD+XlV/Mk6bhwCfAI4AZgC9wDPAD4BbVPVdfxUR2QsYK+DhD6pakuznS5pn0B5v4K2e3XQn+vOKEJ4qJFMpuhMDTIvXccTMhXnZ8hIDUKDE+1ObsEv0l+gvkvUCICI1wM+Ba4D5wEagGzgOeFBErhmHzU8AjwHnAK3As0AXsAr4GvBfIjLcDnn7+8cdwCMjPJ7M1Z/xEg6FOWbOYuoqqthdos3qJjqdg/3EozEWNbSxoCG/GTO8FNjC4/wJAXhQpODcQrWIbgYOBX4PnKqqrwGIyHnAd4BrReQRVf3PbIyJyOHAjbi3/xXgC6ra719bA9zh3+9bwNlDqqeF6C5V/Vhe76pArJ2zhB8891u293a5fc5sGnlEPM+jY6CXlqoajp2zJP+WTDiKJWMpAJ4HhIo285h3i0hEFgDrgRRwblqEAFT1duBv/dNrczD7adyn5z5VvTItQr7NXwAX+KcfEpE5Q+qmhai4mZxyYFZtI4dM34u6iip2FTn370SnJzGAh0drdS3HzV2St71QJAp+lkcjHzwIhYq2aLgQXbPzgAjwmKo+M8z1W/zj4SIyN0uba/zjD0a4/hBuDApg5ZBraSF6Ost7lYTTFxxAY2Wc3QN9JCymaER29vfQWBHn+LlLqYnlvzYsVBEnFAr7XTRj3KRShEJhwlW1RTFfCCE6zD/+eriLqvoG8Ip/euRYxkQkDHwQuAT41QjFMtvaeyRaRGpxY1RQRi0igANb57CsuZ3aWCW7+nuCdqcs6UkMMJhK0lwV5/T5BxbEZri63sUPeSlrFeWB56UgHCFcNf41f6NRiA5felrjT6OUeRmYB+wzljFVTQH/PkaxdUD6L7Ix4/X9cCL1JjBNRK4ADsS9z+eAH6jqI2P5UAxCoRDnyqFs3LGJVzt30FhZndf6qcmG53ns6OumqbKGdfOW05bHItdMwpW1TohCYUgl3LopI3dSCULhCOHq8cd0jUYhhKjNP24dpcx2/9ia7838Vs9X/dP/UdVnMy6nu2VNuGn+zG/6WuDjIvId4KOqWvIFYAe3zWO/llns6u9he19PXivKJxvdiQESXorW6ho+uGhFweyGwmGida0MRmJuh1cTonHhJQchEiPSMKMo9gvRNUtnIx9tbjo9QptX5nIRqQDuAgRIAn85pEhaiKqAbwPLgEpca+xqYBD4MG76v+SEQiE2LFtNc1UNXYN99Ft6EMC1hrb1dtFaVcuZCw7KK/fQcEQa292gtS0+HhdeKunGiMJRokUSokK0iJJkL2jj7qSLSDVwN3CC/9Jnhulm/cr35UlV/WbG668C14nIy7ip/4+KyM2qupESs7S5naNm7cN9A//L1t5OZtU0Tvlgu539PUTDYWbVNnJWAVtDaaJNswhFK4oWFTzZ8RIDhCIxIrVNhIu0S24hWkTpTclHCxmu9o/jGqUVkTZcwOSJ/ktfUtWvDi2nqt9T1UuGiNA7rgPP48aRThuPL4Vgw9LVTI/Xk/Q8OgendpDjYCrJzv4epsXr2LB0NdVFSF5W0TbfZRmc4n/r8eIl3KYDsbb8otxHoxBCtM0/toxSJj02tCVX4yKyBHgcF1HtAZ9U1ZwjtTNIR1Xnt4gpD9ridayXQ2irrmNbb/eUnc73PI8tvZ00VFazcto8jp4tRblPrG0hoVhV0ZYnTHbc7ieVZS9E6cHivUYpk772XC6GReQo4FG/fh9wlqreOEadmIiMNh2Vfs+BDhi8b/4BLG1up7aikq29nWNXmIR0DvYxmEoyPV7PpfsdVbQuasXMJf5OFINuvMPICbcfXDUVMxcX7R6FEKLH/eNhw10UkdlAOpDx0WyNisiRwINAI27W7WhVvXuU8k0isgMYYPRuVzpAZbjgy5IRDUe4/IBjaKuuoy+ZoGtwav1aJ1JJtvZ1M726nvPkUObUNRftXpGaJmKt81yryCLbc8LzUngDfYQrqqmcu//YFcZJIYToh/7xKBEZrm39Uf/4sKq+nI1BEdkbuBc3tvQ6cLiqPjZaHVXdCaTzWF44gt33AwtwYnVPNr4Uk4WNbXxw0Uqmx+vY0tNJYor8Wnuex1s9ndTHqti3dRZnLjio6PesnHsA4cpqUgMWTJoL3kAvoWgFkfppRBvHnylzLPIWIlV9Hvg+LmbnHhHZ05EUkfXAlf7pXw+tKyILRGSxiLQPuXQr0ICb9j9JVbPdYvJ6/3iKiFwvInvWCPgi9M/+6VdU9c0sbRaVc+QQlrXMpK6ikrd6O6dE9G/HQC8JL0V7TT1XHLiWSLj4uYKq5h9CqLIWr69r7MLGHlL93YSraqiaf2hRZ3cLtZT2MmBf//FHEXkKF1Q4z7/++RFW3j/kl/kufitGRFYCR/vXe4BvDN/Q2sN16XxHqnq7iOwHXAFchQtgfB6YDqTzjd6KS1dSFsTCET5z0HFc+vCdvNixjY6BXhqLNEVaDvQnE2zv62Z2bRMblq5mbhG7ZJlULVhFuLKGRHLQdvTIAa+vi3DDdKr3Obyo9ynIT5GqbseNEX0RNyC9BDeL9jBwpqr+TQ7mMtejtQCHj/GYPsSXT+OiqO/Ftaj2A2LA/cDJqnqxv4ykbJhX18KGpauZEa9ne183/ZM08C7leWzu2U1zVQ2Htc/n5L33Ldm9I/EGKufsS7iyhlTf1JwcyBUvMYCXHCRcWUPVglVFvVdoKnQFCo2IbFy4cOHSBx54oGA2Pc/j2v++n5+99iwd/T3MqW0iPMnSm27pdeNgS5rb+cZR59BU4pbf7se+z/YffYlk9w5irXuV9N4TkWTnNrzkAHUrzqDtvJuyrTau/tvk+qRPYEKhEJcfcAx717VQEY6ypXdyjWV0DvTRPdjP9Hg9Vxx4XMlFCCC+7FjCVXV4g/14icnZ6iwUnueR6t1NuKqe+PJji34/E6IyorEyzlUr1jGjpoHexCAdk2SqeSCZYEtvJzPiDZyzzyGsaMs2LVVhida3UTX/YMLVdaR6dwXiw0TBG+wDL0mkpon44jVjV8gTE6IyY9/WWVyweBXtNfVs6+2a8Atj0+NCTVU1rJw+j/VyaKD+1B50GpF4I6meXVNihnK8pHp2EY43uFZkgRchD4cJURly1qIVvKd9AS1VtWzq6SA1gbMLbuvtIhIOM6+umSsPOr4kU/WjEV+yhkj9dAhF8PonV/e3UKR3xw1XN1K74n0luacJURkSDoW54sC1LGhopTISZcsEjS/aPdBHd6Kf9ngDV644ntbq4qQZzYVQtILaFacTqW0m2bUjaHfKklTPLsKVNVTOWkrl3JLsumVCVK40Vsb57MoTaI830JdM0DHBtiLqTybY2ttJe00D6+VQDpoWzLjQcNQdehbhmiZI9JOaJONwhcLzPJLdO4jUNlN32LklS1FjQlTGLG1uZ8Oy1bTHG9je10XfBJnpSXkpNvd00FJVy6oZ8zlHDg7apXcQrW+jZvnxhGuaSHVtH7vCFCLV00EoEiPaPIea5ceV7L4mRGXO6fMP4KjZwrTqOjb17CZZ5ilDXGqPLirCUeY3tPLpg44ry3io+iMuJFLbQqq/G2+KLTgeCc/zSHVtI1LbSv3h5xGKli763Hb6K3PS8UUvdmyld9vrbO7ZTU2s8MnDCsVgKklfcpB5dS18dsW6QOKFsqGibT7xZWtJdm0n2bmVaPPsoF0KnFRvB4QjxFrmULvijJLe24RoAlAbq+RzK0/g8l/9kM09HWU/pd8eb+Cipe9hWUvxVmsXgoYjL6Jn488YeOsFUgO9hCuqx640SfG8FKnOrUQa26l/z3rCFaMlXC08JkQThEWNbXx51an89NVnSJX5DNriphmcNn+/oN0Yk4rpC6nZ/ySSj95BsnMr4ZbyGVAvNanunYSiFcRa96b2kLNKfn8TognEgdPmcOC0oTtsG/nQuOYjdD/1H6S6d5Dq6yraTqbljJdKkuzaTqx5Do1rLiFcgB12c6X8RhENo4REm2ZSv+pDROrbSO5+a0LGa+VLsnMr4cpaKmYvo+aAkwPxwYTImPI0vPcioi1zIRwh1b0zaHdKijfYT6qng0j9NJrWfZJQQLsPmxAZU55wdR2NR3+MaP10kl1b8cp8MqBQeJ5HomMzkdoWapYeQ/X8QwLzxYTIMIDag95H5bwDiVTXk9yd865XExKvbzekEkQbZ9C07pOB+mJCZBhAKBym+eQridRPx+vvItU/uZPse6kkiY4tRBpm0PDeDxNtCjbUwoTIMHwqZy2jduWZROqnk+zYhDeBsx6MhRugjlM5czH1h58ftDsmRIaRSdOxlxKbtjehSGzSrkNLDfSQ6t1NtH46zSd/llARtvnOFRMiw8ggXF1H0wmfItIwg2TXjkm3Ds3zUiR3bSZa30btytOp2ntl0C4BJkSG8S7iy44lvvRoInWtJHZtmlSxRamu7YQiEWLT9qZx7WVBu7MHEyLDGEIoFKL55KuINc8BvEkTW5Qa7CPZtYNIQztNJ36aSLwhaJf2YEJkGMMQrW+j8bjLiDa2k+zcipcYCNqlvPA8j+SuTUTqplGzfC3xpccE7dI7MCEyjBGoXXE61fusJlLbPOG7aKmu7RAKEWudR/NJV5Ys82K2mBAZxgiEQiFaTr2aaPMc8JKkeiZmF80b7CfZtZ1o40w3EF/XGrRL78KEyDBGIdo0k6a1lxJtnEly98TronmeR2LXm0TqWokvWUPNficE7dKwmBAZxhjUrnw/1YveMyG7aO/okp3yubLrkqUxITKMMQiFwzSf9lcunewE6qK93SVrp2ndp4jWTwvapRExITKMLIg1zaJp7V9MmC7aO7tkR1Oz/4lBuzQqlqHRMLKkduX76dn4EKm+ThI7XidU4rzOueAlExOiS5bGhMgwsiTdRet/YyPJ8Oag3RmdGIQqa2k6/vKy7pKlMSEyjByINc9m+oW30PfyE0G7MibRhhnES7hJYj6YEBlGjlTOXk7l7OVBuzGpsMFqwzACx4TIMIzAMSEyDCNwTIgMwwgcEyLDMALHhMgwjMAxITIMI3BMiAzDCBwTIsMwAseEyDCMwDEhMgwjcEyIDMMIHBMiwzACx4TIMIzAMSEyDCNwCpaPSETiwGeADwF7A53AE8Dfq+pPxmlzLvAFYB3QBmwFHgKuV9VnR6m3HLgaWAM0ApuAB4HrVPWN8fhiGEbxKEiLSERqgJ8D1wDzgY1AN3Ac8KCIXDMOmwL8DrgIqAX+AFQB5wG/E5HjR6h3BPBb4IO49/cU0AJ8DHhKRA7I1RfDMIpLobpmNwOHAr8HFqjqQao6DzgfSADXisix2RoTkShwP05AbgfaVfVgoB34B5wg3SkiLUPqNQP3+tdv8OutBGYC/wo0Af8qIhX5vFnDMApL3kIkIguA9UAKOFdVX0tfU9Xbgb/1T6/Nwex6YCHwKrBBVXt9ewPAZcCvcF2uy4fUuwwnNr9R1atUNeHX6wTOAV7EtdjOz8EXwzCKTCFaROcBEeAxVX1mmOu3+MfD/TGfbLjQP97ui88eVNUDvuWfnj1CvX8aatC3850R6hmGESCFEKLD/OOvh7voDw6/4p8eOZYxEQkDh4xmE3jEP84XkTl+vXZgXpb1DheR2Fi+GIZRGgohRAv9459GKfOyf9wnC3uzgOoxbL4GJIfYTPvhAS+N4UclkG3rzDCMIlMIIWrzj1tHKbPdP7bmYG9Em6qaBDqG2EzX262q/WP4ka0vhmGUgEIIUdw/9o1SpndI2Wzs5WozFz+y9cUwjBJQCCFKjl1kD16B7WXaHG89wzACphBC1OUfq0Ypkx7z6cnBXq42c/EjW18MwygBhRCibf6xZZQy6fGYLTnYG9GmH/DYMMRmul7dKDNimeNC2fhiGEYJKMRas2eBRcBeo5RJX3tuLGOq+qaIdOCEZi+Gnzmbg4tdyrSZXnsWxs2IDVcv7UcfbuZtvMx59dVXOemkk/IwYRiTjxdeeOHHqnpqrvUKIUSPA6fydjzROxCR2bw9Vf5oljb/G1jr23xomOvv8Y+vqOqbAKq6U0Sex4niYQwvROl6j/szb+OlZ2BggBdeeCEfMTMMw6cQQvRD4DrgKBERVdUh1z/qHx9W1ZeztHkXToj+TES+MjS6OsPmbcPU+zxwCXBH5gV/fdmHR6iXE6o6I5/6hmG8k7zHiFT1eeD7uK7SPSKSDixERNYDV/qnfz20rogsEJHFflR0JnfgWjTzge+LSJ1fvkJEbgJW4+KIvj6k3k3ALuAIEbkpvbjVr/89396L/nPDMMqEkOflP4vtr4L/BbAvbhr9Kdzi0/SSi8+r6t8MU+9lv8x3VfXCIdcOBn6GGyvqAv6IE5JmYABYp6q/GMbmybiV9hXADpzwCFCHE6nVqroxn/drGEZhKUgaEFXdjhuX+SJu8HgJbsbrYeDM4UQoC5u/BfbHLWDd5T9P4UTm0OFEyK93P7AS+BdgEDgAJ2TfBVaYCBlG+VGQFpFhGEY+WM5qwzACx4TIMIzAMSEyDCNwTIgMwwgcEyLDMALHhMgwjMAxITIMI3BMiAzDCBwTIsMwAseEyDCMwClEGpBJi4jsxchbE3nATtxutD8BblTV0XYyKUtE5ELgn4E3VHV2xuu/xO1Dd52qXh2Md6MjIrcBF+BSzBwVwP0/gttA9GJVvTWHeh/HbZ3+Z6p6W473jOLWUAKcp6p3jFF+A/BtIKmqZft9L1vHypCneXsLI3B/uyZgOW5h7cUicrSqPhWEc0Zp8bND/J9x1DsUuKHwHk1sTIiy5y9U9ZdDX/RToHwXOAm4W0SWqGqq1M4VgfNxWy5tG6vgVENEjgLuwaWWyaXeMbjsETVFcGtCY0KUJ6q6XUQuAN7A7Tp7HPDvwXqVP6r6atA+lBsiUgVcBVzN2znTs6lXDXzOf9i47DDYH6UA+PmYnvZPlwfpi1Ec/MyjzwHX+C9dDbySRT3x612Ny6f1WdyPlpGBtYgKR3oLo86hF/wBxrOBs4CDcEnjEsCbwM+Br6rqu3Y4EZHjgY8Dq3DjUR04wbsLuHWYXN6ISD3wCeAMYCHux+ZFXFfiRlXdlc2bGW6wOmPw/i2gHZcD/BJgqV/taeAfgdtU9V2JrgrlW0DMxu0e8xvgUlV9QkQuzqLeHL/uo369J0Xk0iL6OSZDBrzH4p9UdUMx/QETooIgIgtwLaEUQ7plfrP8AWCN/9LLuFS603E7jiwC1ovIEar6ZEa9y4Cv+advAr/H7ct2pP/4gIgcm7kbiYgsxs3g7YVL2fsn3Dbby4AvABeIyDpV/WOebzmEGxc7D5c98zlcGt9V/kNwXZjMv0OpfCsWrwMnqeqDOdZ7FThBVcupu+4Bj4xyvRX3P4QsWn2FwIRonIhIBGjEbVH0f3G/7tep6tB/3JU4EdoGnOinwE3bOBi4F9e6+BzwAf/1Rt6eWTlbVe/MqHMc8CPgKL/8nf7rNcB9uC/6vcCfp7daEpEZwK24AfUfi8j+qtqbx9tvA87BtW5uVtWkP37ybWA98CkR+bt0OEOJfSsKqvoC8MI46j1HFvv5lRL/x2v1cNf8jSZ+7Z/+FMg5zfN4MCHKnl+47v6I3AD81TCvH4trKX0xU4TA5eUWkW8CX8JtPJBGcFtn78Tl3s6s81MRuR7YD7eJQJoNuO7O73B5wpMZdTaLyAd4ezPMC4FvjvZmsuAbqnpTxj36ROQvgXNxn6tDcC3BIHybKtwuIrcXypjfZfsh7rP1LHBWnvv/ZY0NVmfP07jmbPrxG2Aj0O9f/yRwk99S2oOqrsaJyi0j2O3xj/GM117CjSE1AbeJyP5DbH5ZVT+gqvdkvHy6f7xzuA+P38q42z89ZaQ3mQP3DXOP7UA6qLMxQN+mCs/xzs/kcI9cWnE3A8cD24GTVbVjjPIFw1pE2TNSHFEF7lf8H4BLcdO6f55ZRlUHRaRJRFbhpvjn+8cDcWMfaVqqAAADfklEQVRFkPGjoKpbROQG3GaR5wPni8hm3K63PwUeVNWh8T3p2bqLReS0Ed5DemPIxWO+27EZaeYn3a3K/GyV2repwpdziKweFRG5EjfxMACcoaovFsbF7DAhyhN/5uof/U0irwUuEZHrVfU12NPn/hpu7CSWUXUA11V5Elg3jN2rReQJnLi9F/dFPdd/JETkTtwsTPpXq8E/pgfAR6NxjOvZ8K4ZuyGEMp6X2jcjB/yu8fX+6UdU9b9K7YMJUeG4FydEEVxL57WM19fgWgpf5+0u3fN+S+lihhEiAFX9N+Df/GnvI3ED1CfiWg3rcV/wU/3i3f75Kf7ebuVEOfs2pRGRw4D/h/vhuCHXtW+FwoSocGQu6wgB+F2x9LT9SSNsCjl76Av+lP8iIKSqf1DV3bgxmftwM1JX4X7BThGRBr9VpLgB4mXAsF92EVmEE4RXSrxAt5x9m7L4YSc/xo1h/ggXbBkINlhdOE7yjx7whP9874zrTzAEEYnjAh3hnT8KlwB/AO4QkdDQerituNOkB8fTg8cbfCEbeq8ornX2W1y4QSkpZ9+mJCLSDDyIixn6PbB+uCDUUmFClCciEhKRM3ADywB3q+rr/vPM4LwviEgso95SXIBfeswkc9bsLtwYzHLgRj8OJ12vFbjOP31cVXf4z28GNuGmyX8sInMz6kzzbS7x7Zb6y17Ovk05RKQS1wLaBxdge6Kqdgfpk3XNsufrIjJ0OjOGC9Jr88+fAD6WvuiH89+FW9rxKeBCEXkJt8Qj3Vr6GbAWqBORelXdraqbROTDwB24oMGLRORPuP/XAlxTehtwUca9dorIqbjWx7HASyLyDK7LKEAlLiTg7FKnKiln36YonwCO8J9vA77t/9jFhimbKEWuJxOi7BluMWsfLm7mflx6hztUNTGkzDnAfwIX41oE+/t17gO+paoPiMgrwFxcDM33AFT1eyLyOm7WbBVuPVc/8Lx/v68OncJX1f8RkeXAZbhB7IW4L/km4JfA36nq/+bxNxg35ezbFKQ+4/nKMcqWJKAx5HmBdQsNwzAAGyMyDKMMMCEyDCNwTIgMwwgcEyLDMALHhMgwjMAxITIMI3BMiAzDCBwTIsMwAseEyDCMwDEhMgwjcEyIDMMIHBMiwzACx4TIMIzAMSEyDCNwTIgMwwgcEyLDMALHhMgwjMAxITIMI3D+P57AU7lrxUF4AAAAAElFTkSuQmCC\n",
-      "text/plain": [
-       "
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-      ]
-     },
-     "metadata": {
-      "needs_background": "light"
-     },
-     "output_type": "display_data"
-    },
-    {
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\n",
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-      "needs_background": "light"
-     },
-     "output_type": "display_data"
-    }
-   ],
+   "outputs": [],
    "source": [
     "for key, dd in stuff.items():\n",
     "    baseline = dd['base']['specificity'].to_numpy()\n",
@@ -2857,57 +2393,11 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 25,
+   "execution_count": null,
    "metadata": {
     "scrolled": false
    },
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "U-test: U value 3643.0 p value 0.9471010896899097\n",
-      "U-test: U value 1873.0 p value 0.8133796041365939\n",
-      "U-test: U value 1018.0 p value 0.8095631030980726\n"
-     ]
-    },
-    {
-     "data": {
-      "image/png": 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\n",
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\n",
-      "text/plain": [
-       "
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-      ]
-     },
-     "metadata": {
-      "needs_background": "light"
-     },
-     "output_type": "display_data"
-    },
-    {
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\n",
-      "text/plain": [
-       "
"
-      ]
-     },
-     "metadata": {
-      "needs_background": "light"
-     },
-     "output_type": "display_data"
-    }
-   ],
+   "outputs": [],
    "source": [
     "\n",
     "for key, dd in stuff.items():\n",
@@ -2925,57 +2415,11 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 26,
+   "execution_count": null,
    "metadata": {
     "scrolled": false
    },
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "U-test: U value 3951.0 p value 0.30924120740340955\n",
-      "U-test: U value 2116.0 p value 0.13443770008325492\n",
-      "U-test: U value 1033.0 p value 0.7162113753904321\n"
-     ]
-    },
-    {
-     "data": {
-      "image/png": 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\n",
-      "text/plain": [
-       "
"
-      ]
-     },
-     "metadata": {
-      "needs_background": "light"
-     },
-     "output_type": "display_data"
-    },
-    {
-     "data": {
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\n",
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-     "metadata": {
-      "needs_background": "light"
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-     "output_type": "display_data"
-    },
-    {
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zxn3vBXygB7h8ztZ1MNrTOn7eYRU7arlcLhvRMjSfjhYtKeU+4LZo99+FEGdVjwkhrgPeE+1+atzrNjphDzppP9l9PWBftHtOI23uFMrlqT2t0HhahhYxH0oeXgncCrwY2CKE2ApkgTOAIeBtUsrPjTt/Mcfed/8U9x1Al08sa7jFHUC57Ou2NJN6Wjo8LJe8Sa40GOKloz2tCIXOZw2ixeh8tGCBFq3ihPNz4/5dnuK+pUnO7xrKJY9QTeFpmfDQ0CI6WrSEEAuAXwEfRuetrkN7WcuANwCLgM8LIcZ7WrMd8urKVgblclTyMNnooa0r4o2nZWgFnR4e/i1wBbAfeLqUcih6vQz8pxDiIeAe4C+FEN+QUv4GXeZQJTPFvaujhhM9ta6gVPJQocKuER6GoaJUMp6Wofl0tKeFzmMB/Os4wRpDSrkO+GG0+/Jomwcq0b+XTnHvai7rcL1GdiKl0jSJ+Kinlu+bWi1Dc+l00VoTbbdMcc4j0fYM0AWkgIxeO32yC6JpP6ui3a31mdiZlIpeFB5OIlrRS0opSkUTIhqaS6eL1ki0PXmKc1ZMOBf0nEM4Vq81kSvQoXMZeGDO1nUoYaiOlTxMKloWdlT2UDR5LUOT6XTR+lW0fb0Qwpl4UAixBPiTaPf2cYe+EW1fFJ0zkb+Mtl+XUpYmOT6vqVR0El4pJhUtGJfXMp6Wocl0umh9BN2G5gnAV4QQYzVVQogzgB+h81Y7gC+Ou+52dAuahcD3oo4PCCFsIcS7gFcAHvDxZryJdqNYcMdGDiebMA0c87SMaBmaTEeLlpRyAzrBXgJeBuwTQjwohNgAPApchS6FeM54j0lKqYA/A/YCTwZ2CSHuQ1fBfxxd5vBaKeXmZr6fdqFYrB0aVqmKlvG0DM2mo0ULQEr5bfQcw1uAPcC56KT7w8AHgIsnEx8p5Xb0fMVPo8XqQnQJxE/R5RNfbcobaENKRY8wmIlohRQKbhMtMxg6v04LACnloxzLQ83muiPA26MfQ0QhCg/tiX2Wx2E7FoEfUjSiZWgyHe9pGRpPseASzDA8NJ6WodkY0TKcwDFPa3rRMp6WodkY0TKcQKHgEgYhzpSiZRMYT8vQAoxoGU6gkJ+5p1WpmKk8huZiRMtwAmPhoVNbtCwLLHT1fD5vvC1D8zCiZTgO3w8ol/0oEV/743FsKk9IwYiWoYkY0TIcRzU0tDg2MboWtmMRBsqIlqGpGNEyHEc+7xKGIbZt1ZzCU6WajM8XKlOeZzA0EiNahuMo5F1dDT9FPquKEyXj86PG0zI0DyNahuPI5yvT5rOq6PDQTOUxNBcjWobjyEc5ralqtKqMhYejJjw0NA8jWobjyI9WCIJw5uFhYEoeDM3FiJbhOPL56SdLV7GdaslDhTDsykWLDC3AiJbhOAr5CmEw0/DQIgzB90OznJihaRjRMoxRrW4PwpmFh+N7xZsQ0dAsjGgZxiiVPIIgRIW1e8NPpFpgms+bZLyhORjRMoyRH62MTZSerrC0imNbBGFoRhANTcOIlmGMfH7mI4dVbMc24aGhqRjRMoyRH515jVYV27YIAlOrZWgeRrQMY+SjkUPbmfnHQtdqmap4Q/MwomUYQ48cTt38byK6Vst4WobmYUTLMEZ+tDJtm+WJ2Latw0OT0zI0CSNahjEKVU9rNuFh5Gm5ro9b8WO0zmDQGNEyAKCUOpbTmoWnZVkWlq0LU0dNiGhoAka0DABUKgGeF+jRw1mUPAA4UYhokvGGZmBEywAwNunZsplxYWkV2zQDNDQRI1oGIBo5DBTODLo7TORYM0ATHhrix4iWAZjZWoe1sG0ragZoPC1D/BjRMgBQKOhyh9lM4ani2LaeNG1yWoYmYETLAMytsLRKtcC0YDo9GJqAES0DEHUsnWtOK+r0YNY/NDQDI1oG4Njo4VzCQzvqFV8suqbtsiF2jGgZACgUoo6lc0zEKwVBoCgVTdtlQ7wY0TIQhopiwZ11NXyV49sum7yWIV6MaBmiNssKpWbeZnki1bbLpireEDdGtAwUCu6s2yxPZCwZb0TLEDNGtAx1FZZWccxUHkOTMKJliNY6nFthaRU7KjAtGk/LEDNGtAzRyOHsesNPZKzA1IiWIWaMaBl0eDjHkcMq1ZyWGT00xI0RLcOxRPwsOpZOpFryUCyYOi1DvBjRMhxrs1xPIt4xVfGG5pBotQGG1qM9rblVw1exLF0VXy1U7e1LN9DC7qb8c4l7755JjzmnLSL3qsvmXKrSiRjR6nKqyfN6c1qWZR2XjDei1RiUUhS+dB/BvmGYxIO1l/WQftpaEqcuaoF1rcGEh11ONZyrpxq+il5tOjTLiTWSso9yA8LRCuSS0JMa+1EVH4IQ1WULihhPq8sZX1hab4hRLTA1fbUaR1hwtYdlWVh96eN+R8FIGRUoLWhdhPG0upxCwSWos7C0im3b0aRp42k1CpWvQBhiTfalYlsQKlSX1cYZ0epy8qO6j1Y9haVVbMfSS4kZ0WoYKh95WpN9qTh2FB6Wm29YCzGi1eXkx8LD+j8KulbLFJg2kjBfQQVKe1UTsGwLFSodQnYRRrS6nEK0dFgjwsNqrZbxtBqHylcgUDDZl0o1POyySerzJhEvhLgOeDNwNbAUOAL8CviwlHJzjWtywLuAG4EzgFFgPfBpKeVPmmF3q8nnK4RhSDJR/0fBtm29lJjxtBpGOOpCGNYODyu+FrYuYl54WkKIjwG3Ay8AFLAZWAK8ArhfCHHDJNf0oEXtA8CZwCagADwD+LEQ4gPNsb61VBe0aEwiXo8eVioBrhs0wDqDisJDa7KcY+RpmdHDDkMI8Trg3YAHvBZYLaW8CFgF/AjIAP8TidR4PgtcCTwInCWlvFRKuQb4M8AHbhJCXN+kt9ESlFLkRys6PGxQTssCndfqsj+kuFAj5cjTOvH3YzkWqgvrtDpatIQQGeAT0e5fSym/JKVUAFLKQbSnNQqsAJ4/7rqzgFcCIfAKKeXYHAkp5VeAj0W7N8X9HlqJ9oh8PXrYAE8LwHFsgsCEiI0iHIlyWjVHDxXhiBk97CSehw4DtwGfn3hQSjkMvAV4B7Bl3KFXAQ5wj5TykUnue0u0vUYIcVpDLW4jql6WZdOwuWvVqTyjI0a0GkE4XEIFIdZkHTiqJQ8jZVQXTVLv9ER8NVd1m5Ry0iSKlPK/J3n56mh7Z41r9gkhdgFrgKcAX6nX0HZkdKxGq3HfXU40lWe0y0KWuFDDZQgmDw9xdMmDChQqX8FakGm+gS2g00Xr8dF2kxDCQifinw+cAgwCPwO+LKWc2ORpbbR9bIp770SL1jkNs7bNGB0pEwRhw0JDADsKD41o1Y9SinCoVDM8tCxLe2B+SHi0hN0lotXp4eGaaOsBdwDfBl4NPB14MfCfwHohxKkTrlsRbfunuPdAtF3WGFPbj9GRSjRy2FhPKwxCRoa7K88SByrvorwQVcvTAu1tBaEWty6h00WrL9reDDwBeBtakHrQ+a6dwIXAD4UQqXHX5aLtVH9Z1U9BbopzOpqRGD2tEZPTqptwoAC+zmdNWvIAkIg8rYFic41rIZ0eHmaj7XLgBVLK74079kMhxDZgAzqMfDXwhehYwMwFe95mOEeGdSI+lWqgp+VEveKjfFm97W66mfBIAeUHWphqYCUc8APCI4UmWtZamuppCSGyQojnCSH+RAixpAG3rH69PDRBsACQUkrgf6PdPx53KB9tp0oCVAVx3n6FVT2tRhSWVrFt3cHUJOPrJ+jXntZUokXCRvkhweF87XPmGbGIlhBitRDic0KId4977Tx0acL30LmnnUKIl9b5qKFo++AU52yMtmeOe+1ItF06xXXVXNbhOdjV9rhuQLHo6aXDGpjTsixrbATR5LXqIzw0ivICrOQUv5+kDV5IaERr7gghlgO/B/4CeOK4Q/+BrlIHXfDZC3wlErO5Up1TOFVvXz/ajv/ar153+hTXVY9tnbVVHcDwcEl7WVb9HUsn4iSivJYRrboIDo6CF0LCqXmOlXBQXkBwcKSJlrWWODytvwZWA48SFXwKIdYCT0Lnkq6RUi5CV50ngLfX8azfR9srpjjn3Gg7vrzhD9H2aiZBCHEKUC0qvXvO1rUxw0PV0LDxHwHHsQn8kKGj3TOiFQfB/hHtaaVqixbJKBE/WOqaFjVxiNaz0d7NM6WUP4pee060vUtKWRWaD6DDu+vqeNbXou2ZQogXTDwohFgBvCza/da4Q9+Mtk8VQohJ7vvGaHuHlHJnHfa1LUNHSwSBIhGLaFn4QchQFw3DNxrlBpGnFUByCk/LsfXEaS8g2D/cRAtbRxyidSawdcIf+w3oUbhfVF+ICj53cCxknDVSyi3oWiyALwohnlc9JoQ4Cfg6uiziYeA7467bhhY8B/hO5AlWr3slegI2wIfmalu7MzRUIvDDhuazquj5hyFDQyY8nCvBvmFwA7CYfN7heFKOFrldQ1OfN0+Io+Qhy7j6JyFEArg22v3NhHNz1F9S8FbgZLQ3930hxB500ejjgBSwC3iplHKi7/xWdA3XhcAWIcQGYDHHClbfJ6X8ZZ22tS1HB0v4QUgm0/iPgA4PFUNHS6bsYY74OwdRrg+pxLTzQq20g3J9/F2DTbKutcThae0HzhBCJKP9a9FJ91GO5aAQQqxGe2W763mYlLKELiR9JfBrtGd1HrAd+DBwWeSRTbxuAJ3T+iA62X4eejTxDuCFUsqP1GNXu3N0sBijp2URKoXnBabsYY742wdQFX/qfFaVVAIqAcH27hCtODytX6MLOT8uhPgSWjgU8KPqpOYo1/SV6Pm31/vAqB3NV6Of2VxXQLefualeGzqJUsmjVPJ0TmuqGqA5YlkWCcfG90OODhRZuLA75sQ1Ev/RAaj4MINFb610gnCgiL9jMCqRmIHQdTBxeFofRxdk/jXwALrRnh+9jhDiycBedPeEYeBfYrDBMAUDR4r4vp6+E9dy6k5Ci9bg4LytzY0NVfG1p1X2sdIz8CuSNqBQRRd/5/z3thouWlEV+jOAdejaqA3A86WUD0en7Ed7WBvR5Q87G22DYWoGBwpatGLwsqokorKHgSNGtGaLv+0IlHw9KjiD35FlWZBJoko+/uZ5WQt9HLHMPZRS3gNcVePwDuDicSJmaDJVTyuO0LBKImFTKnkMdNGcuEbhbTyIKnuQmT4JX8XKJFBlD2/jQbLPvyBmC1tLXaIlhPg2ug/7T6SUB2ZyjZQyRJcgGFrEkSPa08rMJPSYI9Xw8MhAwYwgzhLv4QOokoeVS05/coSVTRIOl/EeOTTv81r1fmpfAPwJgBDiYbSA/RS4OxInQ5sRhooj/Vq0Er3xfbAdx0IphecGHB0ssnTZxHVFDJMRjlbwtvWjSh720ll0RUo5oECNVvA2Hyb1+JPjM7LF1BsfrAReh642XwO8F10y0C+E+F8hxKuikUJDmzA8XKZc9lENXMxiMizLIlH1tvpNiDhTvPv3oYoeJOxZeUuWZWHlkoQFF2/93hgtbD11iZaUsl9K+d9SypeiuyI8GT1KuBt4KfAlYL8QYp0Q4iYhxJX1Gmyoj/5DeXw/wEnYsY0cVkkkHTwv5NCh7ulAUC/uut2ooovVk5r+5In0pFBFF/e+PSg1b9vANS4RH4WDd0U/7xVCnIyeh/hsdPvjfwD+XggxgO7d/mPgZ9FSX4YmcejQKL4Xkpyic0CjSCRs3IrPYSNaM0KVPNz796EKLvZJfdNfMAErmyQ8nCfYP0Lw2ACJtfOzU3hsw0dSygNSylullC9Ee2HXAZ8CDqHXI/wf4JAQ4q64bDCcyKGDeTwvIDFVj6YGkYw8rcOHRgm7aImrueKu36vXObQsnaOaJZatQ0SVd6nctbPxBrYJTWm3LKX00fMOfwP8bbTQxHPQXtjTmmGDQXcTPXxoFM8L6YkxCV+lmoyvVHwGBgosX94b+zM7mcod2/VSYL2pOYfudm+a8GiJyu+2k3vlpZOvl9jhtOQdSSn3SClvkVI+n6m7hxoayJEjBZ2EJ94kfBXLsrS35YYc3D8a+/M6mWCggPvgvki0pp+6U5NcUvfX6i/gPbi/cQa2EbF5WkKIVcBiKeWmca+9jWOrO/8I+Eg0/8/QBA7sH8XzApJJJ/YkfOgbn0oAACAASURBVJVk0sbzAvbvH+HCi+bvMHy9VH79GGq0AilnZpOka2BZFlZvinCkTPmX20hddkoDrWwP4uoR/0H08l3vHPfae4FPApegV8f5O+AXQoj5WwXXZuzfO4znatFqFsmkg+sF7N/bHQ3q5oIKQiq3byMcKTdklWhrQQY1WsG9bw/BwPzzCeLoEf8c4O/RXlw2ei0NvCs65QdoMduLnkz9hkbbYDgRpRT79g6PeVrNIpF08P2Q4eGy6RlfA3fdHoJ9I+CFcyt1mICVciCdQI1UqPx8/i1xEIen9Xp0K5r3SClvjF57OrAAPXL4p1LKT6GT8AA3nngLQ6M5Olgin3cJAkWyCSOHVWxbF5l6bsBe421NSvknWwiHS1gL0rUXZZ0l1oIM4XCZ8s+36maC84g4Pr1XojuH/vO41/4o2v642lMrynU9hu4waoiZ3buHxkLDZuWzqqRSDq4bsGd3d7QDng3etn68DQdQBbchoWEVqycJKiToz1P59WPTX9BBxCFay4BdUWO+Ktejva9fTzh3mGNL2xtiZM+uo1Rcn2QdSd65Ml605nOl9lwofW8T4VAZelJYDey6YVkW1sIsaqhE6fubUMH8mQoch2iVgEXVnWg5ruoyXhNF6zS0cBliJAhC9u7RSfhUC0QrmXT0itMjFdNfaxz+niHc3+9CjZSxFzW+u6vVl0ZVAoI9Q7jzqNg0DtHaCKwVQpwf7b8y2m6QUo4VjkSr3izHtKmJnf37RigVPZQi1h5atbAsi2TKwXV9du4ws7aqlL69gXC4DNkkVqrx1UeWbWEtzBAeLVH8zgbUPJmVEMcn+KvohY9+JYT4DnrhCIWePI0Q4hQhxL8Bt0avfzkGGwzj2LljkIrrk0o1P59VJZVyqFSMaFXx9wxRuXM7ariMvTgb23OshRlU2SPYPoh7547YntNM4hCt/0CvMbgC3WsriW5X83+j46uBN0evf0FKaUQrZnZsH6RSCUilW1cSl04ncCsB+/eNUC57LbOjXSh94yGdy8okZtYHfo5obytLeLRI8ZsPzYvcVhw94kMp5YuAZ6ELSF8I3BDNPwSQwPfQy3S9scZtDA1icKCo2yt7AakYQpCZ4jg2jmNTqfjseKy7vS1/+wCVu3aihkrYS+Lzsqpob8vH33l0XowkxvYpllL+DN2CZuLrQ8CfxvVcw/E89ugR3GjUsNUtj9Nph0rZ59FHBzjvgpUttaWVFL/2AOFQCXKpWHJZE7FsC2tRhnBQe1vpa89oynPjIvasrBBimRDiSUKI50b7thDCTPdvEo9uG6BS9knHGILMlFQ6QaUSsGvHIK4btNqcluA+fAB3/V49YtgEL6uKtSADXkCwd5jyT05Yu7ijiE20hBBPF0Lcg66CvwMdEoJuy7xXCPEhIYRZ7SBGjh4tcejgKK4btIVoJRI2lgXlss+O7QOtNqfpqFBR/Mp6wsEiVl+6qYtPWLaFtSRHOFCk+O0NhB288ndcE6b/Ch0aXokeSaz+AJyKntLzHuB/43i+QbNN9lOp+CSTrQ8NQZc+pDMJymWfrVv6W21O03F/twNf9hMWXKwYRwxrYfWmwILwcJ7Stzq30iiOCdOXAJ8GQvRUnguBe8adsg49oToAXiyEeEWjbTDoCdJySz/lkk8603ovq0omk6RS9ti542hXjSKqik/ha/cTDBSwF2Vb0pzPsizsJTnCwSKln2wh2D/SdBsaQRz/c++M7vt2KeXfRXMMx8ZZpZQlKeWHgTehva/XxmBD13P4UJ4j/bq1cjuEhlUSCRvbtimXvK7ytko/3Eywdxi8AGth46vfZ4qVS0LKIRwsUvjq/S2zox7iEK2nAIPA56Y571b0xOqLY7Ch69n8yGHKZZ9UOtEWoeF4MtkEpbLP5kfm/xLuAOFQidJ3NxAOFLCW5BrWyWGu2EtzqKES7j078R451FJb5kIcorUc2D5hwvQJRMd3YiZMNxzfD5FbDlMu+WTaKDSskskkcCs+B/aPMHBk/jWpm0jx6w8R9uch6iraaqxUAqs3TThYovDl+zpuek8cojWEngg9E1ZH5xsayPZHBxgdqRAq1ZIJ0tNh2zbJlEO55LFpY+d9088Gf88Q5V9sJRwsYS/NtWwa1USsxVlUvoK/+XDHTe+JQ7TuA1YIIa6f6qSobmtVdL6hgWzccJBSySObSbTNH8lEstkkpZLP5kcO4fudP7WkFsUvryc8WtTTdbLJVpszhpWwsRZlCQcKFL/2QEc1CoxDtD6PTrD/pxDioslOEEI8HfgiesL0F2OwoWs5erTE7l1HqZR9Mm30RzKRVMohVIrRkQqPbTvSanNiwX34gF7tebiMvTTXanNOwFqYQbmB9gZ/3DkFp3HMPbwN+Bo6RLxfCLGBqDupEOIbQohNwM/RS4f9UEr5rUbb0M1seOgA5bKetuO08Zp3lmWRzSQplTwefuhAq81pOK0sJJ0pxxWcfmcD4Uhn9PCP61P9auDjgAtcACxEe18vAs5Dl0DcArwkpud3JZ4X8MjGg5SKLtk29rKqZLIJKmWfvXuG6T+cb7U5DcW9s7WFpDPluILT72xotTkzIpahpagP/HuEEDejuz08Di1cBXSXhx9LKXfH8exuZsvmw4yOVlCKtkzAT8RxbFLpBOWSx4MP7OeGZ57TapMagvICil9/kHCw2LJC0pmiC06zhP0Fyj+VZJ5zHk6brwQe63i4lPIw8N9TnSOEWCOl3BWnHd2AUooH799PqeiRzSXbNgE/kVw2yfBIGbn5MNc8+XRyudaXBNRL5fZH8XcNoSo+9sr2FgAAsklIOoQDRUrffJjeNz2x1RZNSRzTeGbcI0sI8SagM3zSNmf3riH6D+dx3YBMpv1DwyqJpI1tWxQLLhsePthqc+pGuT7F7zxMeLSItTjb8kLSmTA2vWeoRPnXj7b99J44/Nb/K4R4zVQnCCHWCCF+CXwG6InBhq7jgfV7KRY9Mtlk21XAT4VlWeRySYpFj4cf2N/x5Q/ln2+NFl4NsPrSrTZnxliZBKQTup/8t9t7MnUcomUDX6g1ETryxDYATyMqjYjBhq6i/3BeT0AueeRyneNlVUmnEwShYni4zJbNnTu1R7kBpds2dZSXNR57SRY1XKby2+1t7W3FIVpvju77RSHE2OjgOO/qs0AvsB24Tkr5FzHY0FXcf98+ikWPVDrR1mUOtRjztgou99+3l7DDppVUqfzqUYIDI+CHHeVlVbHSCUg7eq3E721stTk1iaNO63PAXwIO8BUhxAsmeFch8AngQinlbxr9/G5jeLjMli2HKRU708uqkskkcd2AI4cLbH+s8xoEqiCk9INNhEdLWIuyHTMQMhF7cZZwqEzljscIBtpzXmgsX8tSys8Db0AL17c45l09DFwppXy3lLIzKtnanAfu20up6JFI2CTbsIBxpti2RTaXpFB0WX/v3o5bidr9/S6CPUPgdlYuayJWJmpdM1Rq2yr52GIJKeV/Aa9DT9UBvazY5VLKzmzi04YUCy4bNxykWHDJ9XSul1Ull0tSKfvs3zfM3j2dtfB46UebCYfKWAvSHZfLmoi9MEM4VKb8i62oUvs1aow1ARKtafgqdEj4HODpcT6v23jwgf0UCi6WbXW0l1XFtm0y2SSFosd99+5ptTkzxtvWj7/5MKrg6gUkOp0ozRAOFKncsb3FxpxIXcWlQoiZVrX7QAr4vhBi4vCQklKuqceObqRc1lXkxYJLT0+6Y3MoE8nlkgwOFNm54ygHD4xw0skLWm3StJR/KvW8vd4UVqLzBkImYlmWnkw9XKb8M0n6mee01eer3or4U2Z5fmqSazoredEmPPTgAfKjFcBq6crRjcZxbNKZBMWiy7o/7OF5f3JBq02akjBfwb17J2q00hnV7zPE6k0RDBbxdw7iy36S565otUlj1Ctapr97C3DdgAfX76MQ5bLa6VuwEeRyKY4OFnns0QH6D+dZvqJ9xaDyux2Ew2WwLWijXvz1Yjk2dk+KcKRM5fZt80e0pJRTzis0xMOGhw4wMlJGhaqtFq1oFImEnkhdjHJbz3ruea02qSaVOx5DjVZ0An6efXlYfWnCwwUqv99Nz+uv0COLbUDnB+Bdhu8H3H/fXgp5l1xPat79oVTp6UlSLLpslf0MDhZbbc6k+PuG8bceQRU9rN7OLXOoSSah29YcLeL+oX0GRupNxF8X/fPuat3VuNdmjJTyV/XYMRlCiARwN/AE4LVSyi9Nck4OeBdwI3AGMAqsBz4tpfxJo21qBJs2HGJoqEQQqrZctKJRJBIOqaRDseBx3x/28IxniVabdALuXTtRhQpkE23dfmauWNFCHCrvUrlnJ+mnnNlqk4D6c1q/RJcznA9sHffabJLrqgF2TMZ70II1KUKIHuB29CrYHrAR3U31GcAzhBA3SSk/GINdcyYIQtav20ux4NGTm79eVpVcT4rhoTKbHznMlVefxsJF7dVMr3L3TsK829HFpNNh9aYI94/iPbCfMF/BbgOPshFfD5Pdw5rFTxztcS5Gr2I9FZ9FC9aDwFlSykuj0os/Q5do3DTd4hzNZssjhxkcLOL7IZns/PWyqiSTDomETanosn7d3labcxz+3iGC3UNQ9rF6Or8HWC2sVAIci7BQwVu/r9XmAPUn4k8QnMleayZCiBTwZfQUogpwwleDEOIs4JVoL/EVUsqxgF1K+RUhxDnA+4Gb0J5jywlDxfp1e/WIYQc1+auXXE+KkZEymzYe4oqrT6O3Db7pAdw/7EEVXB0adngF/HRYPVGIeO/utggR518gDh8ELgT+DajVVe5VaFG7R0r5yCTHb4m21wghZrqGY6w8uu0I/dEy9+28yk6jSaUcnKhJ4ANt8k0P4K3fiyq689rLqmL1pFBFF++h/Sg3aLU58YuWEOJsIcRzhBCvEELcIIRYHeOzrgL+Fp1fe+8Up14dbe+c7KCUch9QbQH9lIYZOEeUUtx37x6KBY9cNtVRTf4aQa4nRaHgRisNtX4uXDhcxtvajyp5WPOgPfS0ROsNqJEK3ubWL64bm2gJIV4qhHgE2AJ8Hx2y/RTYLYS4UwhxbYOfl0X3o7fQo4WlKU5fG20fm+KcndG25ast7N41xMEDo1Rcn2wHt5+ZK6mUg2VZ5EddHn6w9cuNeQ/t1xOJk868mLYzHZZlYWWThEUX74HWe7ux/I8LIT6NXvvwXLSIjAD7gXy0/0Tg10KItzTwsR9DC8zNUsq7pzm3Wt7bP8U51aZOy+o1rF7uvy9qpZzprFbKjcKyLHJR3dZDD+zH91sborgP7dehYReF6eSSqJKH1wZrVMYxcvfHwFuBAPgosEZKuVhKeaqUciHay/kUutThU0KImmUJs3jmU4G3oL2698/gkupyv1P19Kp6ai1dGvjwoc5updwo0ukEYajGSiBahVIK7+EDUWjYPb8PK5uEso+/+2jLmwPG4Wm9FS1IfymlfN/4kTkAKeV2KeU7gbehk+F/U8/DhBB9wBfRI4GvmWFzwdl8Vbd0QvcD9++jVPJId2gr5UZhWceaBD64fl/LWjIHe4cJjxRQXjiv5hpOh+XYkHJQZR9vY2tXTYrjr+DxwD4p5a3TnPdZ9Ojek+p83qeA04FPSin/MMNrqssZT9X8qFrJ2LI5JPl8ha1b+sfWMux2MpkknhvQ319g966jLbFhzMvKzP9Sh4lY2aQeRXy4tSFiHKKVpnapwRhSSgXsARbP9UFCiGcB/wfYDPzDLC49Em2XTnFONZfVslhkw0MHKBZdHGd+NPmrF9u2yGT1cmMP3r+/JTZ4G7svNKxiZZOokva0WtkOOw7R2gA8TggxlSBUR/vORU+fmSsvjbbnAWUhhBr/A1SbC34xeu030f7maHv6FPeuHts6xTmxEQQhGx8+SLHoke2GYfUZksslKZc8du4YZOjoVAPEjUcFId4jh1Flv206HjSVTALlBYT9BcIWLjEWh2h9BB12fTWakFyLf0MvdvHJOp61Fbhrip9KdN62aL+6mnU1jLyaSRBCnAJUi0qnG4mMhcceHWBkuEwYKNLzqMlfvTiOTTLlUC77bGxymBLsGEQNl1FBCF34O7FsCyuT0KOIm1qX14ojk7gHvXL0W4BNQojPA/cCg+jVpB+Hbh54OdrL6hVCvG7iTaKFMaZESvkRtEhOihBiJ9rb+siELg/fBD4MPFUIIaSUcsKlb4y2d0gpd05nRxxseOgAxZJHNpvomik7MyWbTVLIu2zaeIirrjmdRJNqpbyNB3VomO2eaVQTGROtjQfJPKM1nTfiEK0H0SNu1fDsQzXOs9AC9oUax6cVrbkipdwmhPga8HLgO0KIP5ZSPgoghHgl8O7o1Fq2x8rwcJk9u4eolH2WLG1pxUVbkko5jCrF6GiFHY8NcLZY3pTnjonWPG4JNB1WNknYX8DbdAgVqpYMRsTxv7+bzuj7/lb0HMULgS1CiA3oQYFqHux9UsqWTJbevOkQlbJPMul0dZlDLSzLIpNJUC55PLLpUFNES3kB3ubDqJKHvWgerLgzVzIJVBASDhYJdg+ROH3O42hzpuGiJaU8vdH3jAMp5YAQ4mr0XMWXoJP5HnAH8G9Syu+0wi6lFJsfOUyp7JHtxmTvDMlkkhw9WmTXzqMU8i49vfEOVvjbjqDyUYo01X35rCqWNS6vtfHA/BCtqYgmS/8puqj0J5PkkhrKdAIqpSyg28/cFKcds+HQwTxDg0V8LyS9qHvDkOlIJGwSjk257PPotiNcdMmqWJ9Xrc+ii/NZVXTpg4f38AGyzz2/6c+Pa+7hRUKIHwshPjHutWvQ02w+jR4x3CiEeGccz+9ktm3tp1zxSaVNAn460pkElbLPtq1Hpj+5TsaKSrug+eJ0jInWpkMtaVUTx9zDNegQ65noNsxVPocePRwFNqG9rY9H7WQM6NDw0a1HqJR9Ml00RWSupNMJKhWffXuHKeTd2J4T5it42/q7tqj0BFIOKFD5Cv7WqXoOxEMcntbbgQXAPURV6kKIx6MT3i5wuZTy8cCb0SOIb47Bho5k4EiRoaEyvh/OqwVY48JxbJyEjVvx2blzMLbnaC/Lh4SNlTC/F8uydNeHoovbglY1cYjWDejuCS+QUq6PXnt2tP1VtbQA+Hf0dJonx2BDR7JzxyCu65OM+kcZpiedSlBxA3Zuj1G0HuzCVjTToPtreXgPNX86VRyidSqwVUo53m+8AV0GcXv1hWju4S5gZQw2dCQ7dxylUglIdfHo1GxJpR3cis/uXUMEQdjw+6tQ4T6wT69taKZTjWHlolY1OwYJjjS3VU0conXcb1YIkUE3/QP4zYRzF6HLDLoe3w85eGAEz/VJpUw+a6YkEjahUpRKHkf6G//HE2wf0K1o/EAvXmoAolY1aUcn5JscIsYhWruAM8fNO3wGuvPDwLhwESGEQC+Quj0GGzqOQwdHcSsBYOE4JjScKZalO2B4XsC+fcMNv797/z5UQYeG3daKZjqsXApVcHHva+7ybnF8dfwMnVz/r2iqzMfRoeF3qycIIS5FN+6zgLZcybnZ7N83jOsFDctn5fNDDbAqXnp7FzXkPqmkg+sG7Ns7wqWXNeSWY7jr9kTL3pvQcCJWLkl4oKwHKspe0zpfxCFaH0O3jHlx9GOhyxw+CiCEeDrw8+j1XcC/xGBDx3H4kF4eLNmgyb/vv+n5DblPnHz6X37bkPskkrrrQ/+h/PQnz4KgP4+/fUBP3VnR09B7zwtSDti6JMR9+ADpK5qz2l7Dw0Mp5X50y5dvAhL4AXDtuG4Jj6JbI38fuFpKGX9lYAdwpL+A74ckkmau4WxJJGz8IGR0tNzQJcbc+/aiih6kHZ3DMRyHZVljIaK3bs/0FzSIWDKLUsrtwI01ju0SQqyUUsY3Rt1huG7A0FCJwA9JmDqgWWPbFo5t4fsh/YcLnHpaY8JOHRp2x4Ksc8XqSRH2F7TAB2FTxL0lXx9GsI5neKhEECgsi65cIqwROAmbwFcMDTWmm2mYr+hWNAUjWlOSSUCouz74sjnV8WYMtw0YHi4TBCF2A7+lPnTT9xt2r07AcWyCIGRkaCaLMU2Pd/8+VNHVVfCmP39NdHV8irDg4t67m+T58ZddGtFqA0aGywSBamjvrEaNzHUKjmMR+CEjI40RLfe+PcbLmiFWTwo1VMJdt4fcqy+PfTaHyS62AcWiRxgqExrWgW1bhKGiUKg/Ea/cAPeB/Vq0TBX8tFjZJKoSEBwYIdgTf6mNEa02oFQyolUvVdFqxOiht/kQarisqwvNxPVpsWxLC1fBw10ff3W8Ea02oFz2UUa06sKyLEKlKJf8uu/lrd9LWHSxcqbh30yxoq4P3vr4q+NNTqsNCPwApRTmz2PuWJaFUuA3YNK0++B+XQW/sP5e8EcqrVsfcKYsSy+o+x5WLkk4WMTb2k9YcLFjzAUa0WoDgiBaB8So1pyxLEBBGNS3pkrQnyfYNwwVvyFdSs/7wVvqvkfc9L/ov+u+h5V0wLHHlhdLXxlfdbwJD9uAMFQowDKqVRcKRRjW52lVlwkzVfCzZyxE3BjvIrrmt9IG2LaWK9URK6+1KUqLvm3X95H2N3fxsvf1kkmgyj7+lniLTI1otQGJhA1RTsYwNxQ6RKx3tWlPHo46FpjMyWyxMlFjwJ2DhMX4evab30wbkEjYWJZe2MIwN5RSYIGTmHuIrUoewf4RqATQoIVFNj/vMw25TydgJWxwLKgEBDuPYsdUHW9Eqw3IZJPYloVqfLfgrqFa55ato4+7v+souAE4lv4DbACNGJnrKNIJVMXH3z4Q25QeEx62AdlsEtvRdUaGuVEVrVwdS3wF+0f0On6mR/+csVIOygsIDozG9gwjWm1ArielK7pjWJihW9CiZZOtY9pNcHAE5QVmmbB6SNjg6Sk9cWFEqw1YsCAddSkwntZcCYMQx7FYsGDuBaHhYAmCUP/hGeaElXBQfog62pgWQZNhfjttwMKFGd2lIAhNMn6OVLtkLFw0d9FSI2UtWmZhkbnjWBAqwtHGdNuYDCNabcDCRdmxtjRhaERrLviRp7WoHtEq+7oRuJkDOndsLVqqXP8c0JqPiO3OhhmTSNgsWpQlkbAJfJPXmi1hqFChIpGwWbK0jgUogpCo4qtRpnUvMX75GtFqE5Yt79ELNBjRmjW+H+IkbBYszJKppyg0YUM0N8FQJzF6q0a02oTlK3pIJB08I1qzxvcDEgmbZcvrW+bLyiXHwhvDHAkV2FasHV+NaLUJJ528gGTSxvOCVpvScXhuQDLpcPLJfXXdx+7L6ESy+eKYO0EIjo1dxyjudBjRahNOOqmPZNJBhYrA1GvNGKUUnheSSjqcvKq+6nN7ZR9WUg/ZG+aG8kKspI2zsje2ZxjRahOSKYcVK3tJphw813hbM0XXtilSaYeVJ9X3h+KsXqCr4c3//9xxA0g62CfHN33JiFYbceppi0ilHFzzRzNjXNcnlUqwavXCuhe6TZy9DCudADdAmbzWnNAdMpIkz1ke2zOMaLURp61ZTCqVwHUDU2Q6Q1w3IJV2OG1N/UumOUt7cFb2aW+rAQtkdBvKD8ELsTIOCSNa3cHJqxaQzSbAwpQ+zAClFJ4bkEo5nHb64obcM3nRKqxcCtWApci6DRUtBpJYuwy7Af31a2FEq41IJGxOO30x6XQCtxJfRfF8wXV1qcOChRmW11nuUCV11WnYPSlUwTXe7ixReb1OZOqK+PrDgxGttuOss5aSTjtUKiavNR2Vik86neCss5Y2bKmv5AUnYa/ohYSNKsTXfXO+obxALwbSlyZ9zemxPsuIVptxxllLSKcTBGFoQsQpUErhRqJ15tqlDbuvlbDJPH0t9oI0aqTSsPvOd9RIBas3TeqS1TovGCNGtNqMTCbJmihErMQ46bTTcd0A27bpW5DmlFPrT8KPJ3392VgLs3oU0STkp0UFIeFIGXthhswzRezPM6LVhpxz7nIymQTlimfyKjWolH0ymQRnn7Os4StzO8t7yTztLOxFGcIY+0LNF9RwGTuXInHOcpKXrY79eUa02pCz1i4jm03qFZNNiHgCYah0PiuTQJy3IpZnZP/0QqzFOe1txbiyTKejvECL1uIs2Rc/vmG5xakwotWGpFIOZ58TeVslE55MpFLxSSYdli3r4aQ65xvWwlnZR/bZ52IvyREOFI3HW4NwsITVlyZ58SpSTzi1Kc80otWmnHfBCrLZJOWyb/5gJlAueWSyCc5/3MpYv9mzL74IZ9UCvdz7UHydODsVVXSh5GEvydHzmic0xcsCI1ptyymnLmLxkhyJpE3ZJOTH8P0QPwjJZJOcG1NoWMXuSdHz6ifgLOtBDZX0Sj0GAFSoCPsL2Mt7yD7vfBJnLGnas41otSm2bfG4C1eSyyZNiDiOUskjm0ly1llL6e1Lx/681LVnkLriNOzFWcLDeeP1RqgjBaxMksQZS8jdeHFTn21Eq4254HEnkc2lCAJl+myha7PKJY9sLsmFF53clGdalkXPG6/CXr0QbAs1aEYTw3wFVfKwl/fQ+1fXYGXmvtbkXDCi1cbkelKsPWcZ2WyCkvG2KJd0An7p0hynntbY2qypcJb20PvGq3FW9KJGK109mqi8AHWkgL2il9yLHh/bKtJTYUSrzbn4klVkc0kqZZ8w7N7yB6UUxZJLrifJRZesanht1nSkr1pD5tnnYa/oJTxc0NNWugwVKsJDeayFWVIXrSL74otaYkcdqwC0F0KIU4C/Af4IWBO9vAP4IfBJKeXhSa7JAe8CbgTOAEaB9cCnpZQ/aYbd03HyqgWsWrWQ/KhLqejT0xtf7+12ptpjrLc3zfmPO6klNvS8+nL8x47grttLeCiPvWoBVpcsN6aUIjxSwErYJE5bTO87rsVq0aK288LTEkI8GdgAvA04G9gN7AMEWpQeEkI8fsI1PcCvgA8AZwKbgALwDODHQogPNO0NTMPFl60i15OkVOreCvlSds6DaQAAHSdJREFU0SOXS3HBhSeRSrVm2Xor5dD3N08hsWYRVsIm7O+exLwaLkPFx17ZR987rsWpZ6m2Oul40RJCLAK+DSwCfgqcKqU8V0p5NnAOcBdwEvA9IcT4Jj+fBa4EHgTOklJeKqVcA/wZ4AM3CSGub+JbqcnZ5yxnyZIciYRNudR95Q+eF+D7IblckksuXdVSW5zlvfS986nYJ/XpavkumOajCi5qqIRzUh89r7+CZIs83SodL1rAa4DlwH7gJVLKA9UDUsrtwAuAo+jw70UAQoizgFei1xN+hZRyz7hrvgJ8LNq9KX7zp8e2LS65/BRyPUmKxe7r81QseuRyScR5K+iLcZWXmZI8fyW9f3E1zkkLUCMVwtH52w1CVXzCw3nslX1knnUemT+Kf0L0dMwH0XpatP2hlHJ04kEpZT9wd7T7hGj7KsAB7pFSPjLJPW+JttcIIeLtaDZDLrhgJQsWZrBsi0oXNQj0/RDX9cnmklx6efyTcWdK5vqzyb7wQuyT+lBHCqh5OLqrvIDw4Cj2sh7SV55Gz+uvaFrV+1TMB9H6EDqk+68pzqn+T1eTIVdH2zsnO1lKuQ/YFe0+pV4DG0Ey5XDxpavp6UlRLHRPbqtYdMlmk5y1dinLl8e3LNVcyL3iUjJPOVOPKB7Ko9z582WigpDw4ChWX4bkeSvpfcdTWpZ4n0jHjx5KKdcB62odF0IsA54a7W6Ktmuj7WNT3HonehTynPosbBwXXXwy69ftpZCv4FYC0vUsAd8BBEFIpeyzdFkPT7iyOZNxZ4NlW/S+9UmER0u46/YQHhjFXr2wbf6458pYaUMmQWLtUvre93TsGFeMni2d/b87M/4VyAFFdMIeoDpprX+K6wai7bKY7Jo1mUySiy9ZRa4nRaELepgXCy6ZbJLTz1jMSTGuo1cPVipB399dR+K8FVh9acIDI6gOXmxXKUV4OI9lWTinLmbBe5+Os6x1I4WTMa9FSwjxfuDl0e4/jqvVykXbqabuV4eFclOc03QuuWw1fQsyKNS8Xh8xCELKZZ+eniRXXNUWacWa2H1pFrz/ehJnLsVKJwgP5jty3USlFOpIEYIQZ/UCFvzd00isacwqR41k3opWVGf1T9HubcA/jzs8m7/2tvr0ZbPa2+rpSVHIz19v65iXtYTVpyxstTnT4izvZcH7rsc5bTGWY3Xk5Gp1tIQqezgnL6D3bdeSvKC1pQ21mHeiJYRICCH+g2PlCj8DbpRSjv8E5aPtVOPn2WhbbKyF9XOctzUPV+3pJC9rPInTF7PgPdfhrF4IQahHFTtEuMKRMmq0ogXrDVeRvnrN9Be1iHklWkKIBcCPgT+PXvo68Hwp5cQw8Ei0nWoZl2ou64TpP62m6m319qTnZW6rUNAjhp3iZY0nef5Ket/2ZJxVC1FlvyOKT8OCixos4Zy8gNyNF7dFLdZUzBvRiuYe3gXcEL30CeBlUsrJpuRvjranT3HL6rGtjbCv0Vx6+Wr6Fup+UvOpbsv39YhhrifF1de077f9VKSvWkPvX1yFc/IC1GiFcKR9u56qkoc6nMc+qY/Ms84l+5LWTIKeDfNCtIQQq4DfAI9D56v+Ukr5rgkh4Xj+EG2vnuxgJIDVuOTuyc5pNZlMkksvW01P7/zKbRUKLrmcrstq1xHDmZC54RxyL7tEC9dgqS0XflWuryd+r+gl/aQz6HnDlW1RPDodHS9aQogU8H3gLMAFXiylvGXqq/hmtH2qEGIyX/iN0fYOKeXOhhgaA5dcdgqLFmWwbWtetGT2vADX7WwvazzZFz+ezLPOxV7ZpxPzbbSGovJDXVe2OEvqktX0vf3JWE5nyEFnWDk17wYui/79V1LK7053gZRyG/A1dIX8d4QQ1WJThBCvjO4Jutq+bUmlHC6/8lTtbc2D3Fah4NKTSyHOW8HyFe1V/T4XLMui5w1Xkn7iGuzlvboUog36cKlQ6Wr33jSJc1fQ9+6nYaU6p1C5cyydhMjLenu06wOvEUK8ZopLfiyl/Ej077cCF0Y/W4QQG4DFHOvF9T4p5S8bb3VjefxFJ/PAffsoFjxKJd2+pRPx3ADfC1m0KMtVT+x8L6uK5dj0vf1awqH/3965R0lSV3f8U9Xd1c957czuzOzMzuz7x7K7LAu7yy7LSyXEI68oYiIQREWCBqKJRjASRaMhqFGjQTnGREyMAQ4HRYwoHvERTVDkoSJ6FUVABJRdhN15dU935Y9f9U7vbE/PzE4/p+7nnD413VW/6tvT1d+6v/u7v/sbI3vfE0HWfHvDvJoDyaMxl+jKJbS//UW4TTAJfT60uqe1GSs0YAV49yyPA1NyRGQPNqb1LmywfQN2NPGbwDkl4tbURKMRjjt+mHTGY3QkS6FFkxr3j0yQznhsOqqPrq7k7I1aCCcZo/3KFxJd042TjNp5ig3yiv09QfLo8g7arjiFSG9t1o2sJS3taYnIvUxNhj6c9iPYfK6rq2RSQzhyYy/33fNrRkeyjI3mWq66aTabp5D3yWQ8jmuhvKz54C5J0f62F/HcVXcw+che/D2jOHWeHlPYN4E/kiUy2EHm8t3ETG2XYKsVre5pKdh6W7t2D5PJxBkbay1vy/d9RvZnSWc8tmxdXpdlwRpFdGUXbW88kUhvG/5Irq6pEP74JP4zI0T62kj98dHEd6+q23tXGxWtRcKadT0sH2jHi0cZacLh9Zko5pi1tyfYtqP5KjlUG2/7ClLnbSXS14a/ZxS/Djl2fr5A4WlbF8s7YVXDFqSoFipaiwTXddh1wkoyaY/xsRz5Fqg0UPSyMhmPbTsGSSbru35eo0i+bDPe7mHc7jSFp/fVtCrEgcB72iO6fimZy3a3/GIcKlqLiKHhToZWdpFMxlrC2xofm8R1HTq7kmzZ2jxVSWuN4zpkLjuB6NoenESMwu9qN0fRf24c8j6R/nba3nIybouOLpeiorWIcByH3SeuJJX2mJiYZHKyeb0t3/cZGcmSaYuzY+dQw1bYaRRu2qPtL0/EXZaxC2TUoM58ce5jpDdD+rU7iA41X5mZw0FFa5HR19/OuvU9pFIeI/ubd8GF0dEc0ZhLd0+aTUc1ZwmUWhNd20P6gmOI9GZsfKuKiad+wafwu/243WniJ60h/sK1szdqEVS0FiG7dg+TTsfI5fLkmiADezqFgs/oqI1l7dw1RKRFpo/UgsSZG4kdPYDTkahqN9F/dgwnGiGyopP0Ja0xp3CuhPdqWcR096Q54sheW5Z5f/PFtsZGs3helN7eNsyG1swVqhaO65B5/S4iy9psDa4qfF/+xCT+8+O4S9NkLt2Jm1lcaSQqWouUnbuGSKe9YAmu5vG2CgWfsbGc9bJ2D+O2+EhWNbB1rLbg9gTdxAWMJhaXr3e7UsRPXIW3bfGlkahoLVI6OpNsOqo/mEw90TSTqUdHsnjxKP3L21mztlINxnCReMkGomu7cVKxBRUO9PdnoeDjLsuQetW2KlrYPKhoLWJ2HLeCdNojn/ebIraVzxcYG8uRTnvsOn54UcVZFooTi5B+9XbcJSn8fROHFZT3Cz7+3lHc7jTJczYT6W6uVXSqhYrWIibTFmfzlv6mWQRjdDRHIhFlYLCD4VWLY/i9mnhblhPbOoDTnqBwGN6Wv28CYhEiA+0kT99QAwubAxWtRc72HSvIZDwKhcZ6W/l8gfGxHKm0x071smYkfd5W3M4EjGTn5W35vo//+zHcrhSplx+FE2/pWggVUdFa5KQzHpu39B8YSWyUtzU6miOeiDK4ooOh4c6G2NAKRNf24G0dwGmL22z2OeLvm4CoS6S/jfgpiycnqxwqWiHg2O2DZDIe+QZ5W4WC9bLSaY/jdqmXNRuJszfhdiRtKZk5VOzwfR//+QncjiTJMzbgLPLZBSpaISCTibNxcx/ptMfoSP3rlBe9rOUD7eplzYHY5j4iK7twE9G5Te+ZyEO+gNuZIP7CdbU3sMGoaIWEY7cNkkrFmJws1NXbKhR8W5gw5bH9uBXqZc0Bx3FInLoOpy2BP4epWP7+CZxMHG/XStxFXI+siIpWSGjvSHDEkctIpWKM1rECxNhYDs+LsKw3w6rVmpc1V+InrMLJeHYydYWbjO/7+PuzuJk48RNbt7DffFDRChHbtq8gmYqRzeXrUgHC962XlUp7HLt9ULPf54HbmSS2qQ8n5VVeM3F8ElwHtztFbHN//QxsICpaIWJJd4rVa7pJJmKMjdbe2xofnyQSdehakmT9EUtr/n6LDe/YQStaozPHIf3RHE7aI3bMAE40HD/ncHxK5QDHbBsklY4xPj5Z01ryB7yslMfRWwdCXcnhcPGOGbTTesYnZxxF9MdyOMkY3tHhKaKoV1LIGBhsp6/f1pIfG6vdSGIul8f37Qo7GzeHs17WQnH723B7UjgxF8rUkvcLPmTzOIkosY29DbCwMahohQzHcdiydTmpVIyxsVzNkk3HRnMkUzE2bOwlkVi82dm1xHEcYmYZTsJ6W4cwPglehEhfG+6SVP0NbBAqWiFkvVlKe0cC13XITlQ//SGft+VwkskYW7Yur/r5w0R0TTdOPIKfLeNpZSdx4lGia8I1KquiFUKiUZeNm3pJJmM16SKOjdlk0qHhLpaEyAOoBZHhLvCiUKYmmp/N43gRe0yIUNEKKZs295FIRMnl8lVdbsz3fcbHJkklY2wOae33ahIZ7MCJRfBzhUO78tl8UNWhozHGNQgVrZDS0Zlk5aouEonqBuSz2TxuxKG9I8FqLfK3YNzuNE48YtcqnJ5bN1nAidmYVphQ0QoxR27qI5G06Q/VCsiPj+VIJqJsOHKZpjlUAcd1cLvTEHUPEi2/4NuyzFEXd2mmgRbWH72qQszqNd1kMh6OQ1XmIxYKPtlsnkTSjhoq1cFdksKJuAfXjs8XcCIuTiKKkwrHytxFVLRCTDTqYo5YRjIRY3yszJD6PBkft/MM+/ra6O5ZnKV+G4HbkYCIA/kSbzhfgIiD25EI3SR0Fa2QYzYsI56IMjGx8C7ixPgkiWQs9MuCVRsnEwfXsUJVJO9DxLX7QoaKVsjp62+jszNJNOouKGcrny8wOVkgHo+yzvRU0ULFScUg4kLJVB6/4OO4Tui6hqCiFXpc12H9EUtJJKKMl5kqMlcmJiaJx+2iFZkQ3v1riZOM4ThAqSPs++A4OCGcbaCipbB2XTdePEp2AV3EifFJ4okoa9erl1VtHC8CjnPwpGnfBxccT0VLCSHLetvo6EgQibqHtRp1oWC7hp4X0QVYa0HMitZBrpaPfS22uOvBl0NFS8F1HVav7SYeeFvzZWIiT8yL0NffRlsIyv3WGyfqwiHdw5J9ISN8n1gpy6pVS4jHI0xk8/PuImaDeNbKVUtqZF3IcR3rVZWJaRHCarAqWgoAAys6iMej4DOvuYi+bxNKPS/CqtUqWjXhQB5WmZuJipYSVmKxCCuGOvHikXnFtXK5Am7EIZOJs3RZuKaT1I1KwhQ+zVLRUqZYMdSJ581TtLJ5PC/KiqEOXbiiATghVC0VLeUARdHKzSOulc1O4nkRBod0EdaaET5dqoiKlnKA7p406bSH6zpzWmLM931yQarDihUqWkp9UNFSDuC6Dv0DHcQCb2s2crkC0YhLpi1OR2eiDhYq0/HLBecXOSpaykEsX96OF4uQnUOpmlwuTyzmsnx5e+gqDSiNQ0VLOYjlA+3EvAiT5cr7TiOXs0ml/QPtdbJOUVS0lGksXZYmFovg41dczNX3fSZzBWIxWz9LaQxh9HDDN9tSqUg0GqFnaZq9e0bZu3e04pC6j08sFtH8rBrj4JSfxuNQkngaHlS0lENYtXoJTz25b9buoePA0HAn0RDOf6srxfy3XJ7CMyMA+OOTtpZWCHPjVLSUQzhu1xBmwzLys6Q9OA50diXrZFV4cTIejhfBaZ8aoXXSHk4ihpPxGmhZY1DRUg7BcRy6VIyahtjmfjKXHk/h2dGDXneSMeKnrmuQVY0j1KJljEkBbwX+BFgF7APuBT4sInc00jZFKeJEXRIvNo02o2kIbTDCGJMG7gLeCawGfgyMAKcBXzLGvLOB5imKMgOhFS3gOuA44AFgjYgcIyLDwIXAJHC1MebURhqoKMqhhFK0jDFrgAuAAnC+iDxe3Cci/wH8Q/D06vpbpyhKJUIpWsCfAhHg/0TkoTL7rw+2u40xQ/UzS1GU2QiraO0Ktt8ut1NEngAeDZ6eXBeLFEWZE2EVrbXB9hcVjvlVsF1fW1MURZkPYRWt4rrtv6twzJ5gqwv5KUoTEVbRSgXb8QrHjE07VlGUJiCsojWfFUnDV2VNUZqYsIrW/mBbqdxmcR7LaIVjFEWpM2EVrWeCbaU13IuxrN/W2BZFUeZBWOce/gRYB6yscExx388W+F4rHnvsMU4//fQFnkZRFg8PP/zwF0TkrMNpG1bR+i5wFlP5WgdhjBkEikml/7vA9xrNZrM8/PDDj89+qKIos+HMdX27xYQxZh3Wg8oDG0VEpu1/D/B24Jsickr9LVQUZSZCGdMSkZ8Dn8VO5bnVGFNMNsUYcwFwRfD0PQ0wT1GUCoTS0wIwxnQDXwc2Yz2uHwFdwHBwyNtF5O8bZJ6iKDMQWtGCAzW1/hp4BbamVg5bBPAjInJrI21TFKU8oRYtRVFaj1DGtBRFaV1UtBRFaSlUtBRFaSlUtBRFaSlUtBRFaSlUtBRFaSlUtBRFaSlUtBRFaSlUtBRFaSlUtBRFaSnCWk9rwRhjVgKPzLDbB54FHgPuAD4kIpVW/mlKjDEXAZ8CnhCRwZLXv4FdD/K9InJVY6yrjDHmBuBVlCkvVGlfFd9/HXAl8AdAH7AXuBu4TkS+WqFdN3AVcDYwiL2OvgO8T0TunqcNp2CLAgCsEpFfzXL8DdT4/1IN1NOqDg9iL6zi43vYks6bgLcBDxljNjfOPKWeGGP+EPgB8BpsSe+HsJVEzgbuNMa8f4Z2vdgClW8CeoEfYm+ALwW+bYx5Te2tb35UtKrD5SJyQsljp4gY7B32v7H15m8xxiyW//eFwAbgw402pNkwxvQA/4VdGOVGYLmIHC0iA8D5WPF6izHmnDLNbwLWAF8FBkVkG7Ac67FFgOuNMRvq8DGamsXyI2pKRGQP1t2ewK5UfVpjLaoOIvKYiPxURJ6Z/ejQcTG2LtuvgItE5LniDhH5LPAvwdNLSxsFXbmTsStFnScizwZtCiJyLfAZIIatqBtqVLRqTCBcDwZPNzXSFqUuPIL1tD4mIhNl9v8w2A5Pe/2iYHvbDDeD64PtHxljkmX2hwYNxNeHWLDdN32HMSYKvBJbiPAYbAxkEvgNcBfwQRE5ZEWgIG7y58BO7J39Oaw43gx8UkSyZdq0A28EXgasxd60fgncih0s+P1cPky5QHzJwMTTQD82nnMJcGTQ7EHgE8ANInJIEbdq2dZoROQmbDdvJrYF259Pe724yMq3Z2j3Pex1kQ7O8T+Ha+N8mBbMn41Xi8gNtbPGop5WjTHGrMF6WAXgy9P2JYE7gX8HzgCy2LLPe7FLnP0ZcJ8xZuu0dn8RnOtMbLXVB7CCeDJwHfAVY0xkWpsjsMHhd2NLTP8G+8M5AngH8EBwzEJxgE8Dn8R2iX+G/bHtBP4NuGZ6gzra1jCMMZ3GmHcCr8b+P64t2ediK+cC/KJcexHJAU8ET9fX0NTpPMfBg0zTH0+WHPtYPQxST6sGBILRCRwPfAB7c3iviDw67dArgBdgRxpfIiL3lJxjO3Ab1mv5G+Dc4PVOpi74V4rIjSVtTgM+D5wSHH9j8HoauB27luNtwBtE5DfBvj6swJwOfMEYs0VExhbw8ZcB52G9putEJG+MSWBjORcAbzbG/GMxBaTOttWdIOD+Lqz3GAceB14vIt8qOayLqd9ipdSYPdhuZU+FY6qKiNwPnFBunzHmSKaW2Hu3iNxVD5tUtKrD140xlfZfC/xtmddPxXpg7yoVLAARuccY83GmvI8iBkhg83dumtbmTmPMNcBRWK+tyMXYH819wDkiki9p85Qx5lymFrC9CPh4pQ8zBz4mIh8peY9xY8ybsKNnUWAHdlS1EbbVmx3AxpLnXcAZxphviUgxXJAq2T9e4VxFwU5VOGYmHpnlGp0XQXrGl4AObEji6qqdfBa0e1gdpudp3Q38GDtqCPBXwEemd9lE5ASsAF1PeUaDbelF+gi2e9EF3GCM2TLtnH8nIudOW5jjpcH2xlJRKGkzBtwSPD1zpg85D24v8x57mPIiOhtoW735KJDBpi5chBWeS4G7gngm2DSI+XA4Czt8n8rdvO8Av53LiYwxKex3PIyNtb2qXJyyVqinVR0uF5FvTH/RGONhL9R/Bi7D5tq8ofQYEckZY7qMMTuxsYrVwXYrNsEQSm4uIvJbY8y12KHvC4ELjTFPAV/Dxse+VGb0qThq+TpjzNkzfIa+YFuN2NETM7xe9BRKr7t621ZXROTXwZ8jwKeNMXdjY5DbsN3lG7BpDkUSFU5XHDUcrXDMTJw7j4z4Sse42DVDt2O7umeLSCXvsOqoaNWQYATvE8aYfqz7fIkx5hoReRzAGNMG/BP24o2VNM1iu0v3Ay8uc96rjDH3YoXwJOyP+vzgMWmMuRG4rCRHqCPYrgseleicZf9cOGTkchpOyd/1tq2hiIgYY27Fxv1OYUq0JrAxr+4KzYuxrDl5RDXig9jM/hHgLBF5qt4GqGjVh9uwohXBelCPl7z+AqwH8lGmupU/Dzyw11FGtABE5HPA54JUgZOxP4CXYL2RC7BicFZw+Ejw/EwR+WKVP9tCaWbb5o0xZgmwCni0QvJtcUCmD2wCqTFGsLHIlTOcN4btYoIdka07xpjLsQMsBeB8EXmgEXaoaNWHQsnfDkDQHXxB8NrpIlIuF2Zw+gtBmsQ6wBGRH4jI89j4wu3YkbkrsWkFZxpjOgJvS5gKCJcVhmCCbwf2x1bPyd3NbNvhcA+2i38F8L4ZjikmlpZ2o7+LFa1dwL+WabMD+3sdx3rgdcUYcyZT07auFJHb6m1DEQ3E14fTg62PXcEa7N24yL1MIwh2vjJ4WnpzuQSb0/QZY4wzvR123lqRYuC/GBi/uFw2dRAQvg37g/vAzB+jJjSzbYfDncH24sA7OoggCbc4+FA6YHFzsH154K1N5/XB9qZ6p30YY47FZvm7wKdEpOyE73qholVDjDGOMeZlTM0Xu6UkMPvTkkPfUXqBB/kvdzAV4ykdPbwZGzPaBHwoyHMqtusB3hs8/a6I7A3+vg6bBLgWm+80VNJmaXDODcF56y0MzWzb4fB+bHd/HfDZ4DsBIEgS/go2oP4trBgX+Rp2BK8D+HyQUoAxxjXGvBUbr8xRkpRaD4Lv43ZsJv5XsAnPDUW7h9Xho8aY56a9FsPGJ5YFz+9l6m6JiNxvjLkZO33nzcBFxphHsIHYohf2VWw9pjZjTLuIPC8iTwYlSj6DjS+81hjzC+x3uQY7+vQM8NqS93rWGHMW9uI7FZuz8xC222qwAeBJbLLqj6rxD5krzWzb4SAivzTGvAKbQ/dybDddsN9LMZP9bmxOml/SzjfGXAh8EzgReNQY8yAwgI19+dhpMj+p36cB7Mh3f/C3g72xpJjy4ku5X0Qur7VB6mlVh03A7mmPo7AjQl/ETt3YGeQqlXIetrt3D/a72IL9kd4OnCEipzE1NeJAjpKI/Cc28H4L8Hvs/L5h7NSXa4ANIvLj0jcSke8Hdr4bO2l3JdaDeRo7jejYablddaOZbTscggGFLdi5lk9iP0svdl7hpcBJ5YL0IvJL7EDNh7Hxrs1Ysfsy8KLge6837SV/n4YdGDqJQ6/33RycBF0zHN+vW06YoijKglFPS1GUlkJFS1GUlkJFS1GUlkJFS1GUlkJFS1GUlkJFS1GUlkJFS1GUlkJFS1GUlkJFS1GUlkJFS1GUlkJFS1GUlkJFS1GUlkJFS1GUlkJFS1GUlkJFS1GUlkJFS1GUlkJFS1GUlkJFS1GUluL/AXz75QX0BnqnAAAAAElFTkSuQmCC\n",
-      "text/plain": [
-       "
"
-      ]
-     },
-     "metadata": {
-      "needs_background": "light"
-     },
-     "output_type": "display_data"
-    }
-   ],
+   "outputs": [],
    "source": [
     "for key, dd in stuff.items():\n",
     "    baseline = dd['base']['max_rate'].to_numpy()\n",
@@ -2992,55 +2436,9 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 27,
+   "execution_count": null,
    "metadata": {},
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "U-test: U value 4208.0 p value 0.0703111829950676\n",
-      "U-test: U value 2192.0 p value 0.05860549066385172\n",
-      "U-test: U value 1107.0 p value 0.3330227188913163\n"
-     ]
-    },
-    {
-     "data": {
-      "image/png": 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\n",
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OZTAEghVP+g5nS1tBESVo8XGBmdqRiUbHV0ptRqd0AFwtIhfWnvP9ST9Bb8evRfuiDIbQGRUfP8gwqgTt89kKnCUiJyuldtU7SURWAmegt8Eb5a+Bp6GXfDeKyB6gD51flkSX+XiXUqpefpnB0FpqjQONzydQbkCXUb1ORBZPdoJ//Iforfejtsdni1KqgA4o/HPgTrSl82xgO7qQ/bm+hWQwtAVacCwdaBhh8Qna8vkOenv9pcAmEbkWWAMMo9vonIsO9jsB2O+f3zB+GY0f+jeDoa050udjxCcQlFJDfuuc36KXQl+Y5DQL2AdcqJQamuR5g2FBY9nxsd2ueHTFJ/AIZ6XUWkCALwIPAoOAgw4IXO0ff45SaqrAQINh4RKLj5XTsKPbtq4p/3KlVBb4ln8zGAzj0IJj+a2Soys+0SwkYjCEyajlE+2emXOWXb9wO8DPlFKZCcdmjFLqqrnOwWCYj1h2zP/BiM9cuQJdBvU+dJH28cdmgxEfQ7SwYsbyoTHx2Y0Wmsokxwxtxv7sEP/02G1kykUALMvigmecwZ+edl7IM4setbKplrF85oZSauVMjhnag4cO7eSxvj0MFHMAxG2bolM14hMGtR2uiItPaA5nv7zq2WGNHzXKbhXHdUnYNstSnZSdKhWnOv0LDcETcdGpEXQxMUdE7p7h6b9Dl1Q1tICK6+DhEbdjpOMJvV52J+02ZGgyo8utiItQ0JbPjLxofuviE9EVDw0toOq6eJ43+gZ5nkfZiE/IRFt8GtlqPwOdRjHxN/gCEdk9xUtrtZzTwJa5jm+YHVXXwQMs/z8PLUCu52JbJtzL0HoacThvFJH7ObJLKeiSpitmcAkX+NpcxzfMjtqyqxZY6/mbklXXJRkz4mNoPY3Gdn8W3RUUtEVzFdqa+eYUr3GBLLA2oPY5hhmgl11g1+JLPB0T4Xhu2FOLLhH3+TQkPkqpg8Bol1IRuQroNf3R2w8tMp6/6NJ4eFRdIz6GcAi6pIax39sUx3O1z2f8t61nLJ/wia71E6pYiMhLwhw/SrjeWOB5TYDMsssQJoHn84vIicCn0T3SOzla4OL+8RPRu17RrSnQQhxvbKsdau4G7whRMrQYzyPK2UiB/uGLyNPQZVNrbZIBf4d3jNpv2wKKQY5vqI/reRM+5pZv+UT3w28Il6CXXZ8DjgcK6J2vf0eLzL3AN4AfoCsbAvweWB7w+IY6jFk41rj/YywfQ2gEveS5AG3ZvEMp9XsAEflzoKqU+rL/+HjgduC1wPMY6zpqaCKeLzJHuDe9seOG1jH6O/c8f+kVTYK2fJ4BHKwJj8/jwAtFxAJQSh1Ct0u2gU8FPL6hDi4eExdewKTHDE1m1MnvRTrWJ2jxSQN7JxzbjHYwP7N2QCm1Gt3Bwux2tZojdto9Y/mEQS2nLuK/+6DFZ5Cjk0V3+PfPnnD8ALp/l6EF1PPtRPvjHw6eH9gZdeEPWnzWAs8UkVPHHduC/r49d8K5JwGlgMc3zBArwsFtoeM5vtUT7RirZrRLtoHf+M0DAR5C/5Y/URMlEan1V98e8PiGWWJ8Pq3HG112EemlV9DicyWwHjgduFFEkkqpXuAm9Lb6JhE5DFyG/tX/OODxDTPFGD7h4VTHAgyN+ASDUqoIvAYdz7NbKVX2n/oo2vGcQEc1W8ADwHeDHN8wC6L7mQ8dr1qmJjyeG91StoGnNiilDgMfFJH4uGOH/HrNbwdOQQvRjUqpaC962wDj+2k9nlMZtXy0EEWTpuVVKaWqEx6XgJ80azyDYb7gORU8z9UCFGHLx5TAiCjG0Rwi/rLL8zy8SnQ3fBup4VxrEHi+UmrHuGOzwVNKnTzXORhmTr3FlVl0tR7PKY+mVphl19xYgRafxIRjs8F8/baI0SJiXp3jhpbhVoo6xcJz8arG8pkLF/n3ByY5ZmgzdOVma8IxyzicQ8CrlMYsn0p0q8o00r1isjrNDwJblVLGomkzJhUZozuh4FWKvsPZ1VZQRAna4fwLYLuImDo97Uad5ZXRn9bjVQra6vHcSFs+QYvPqUBRKdUf8HUNDTK+rOT4+yiXdAgLb9TnE+1lV9DikwFiAV/T0ERsIz4txy3lxxzO5ULY0wmNoMXnP4FVIvK5gK9rMCwYvHIBz3XxPBe3nA97OqERdITzI8D9wD+LyCfQ+VsH0DWdJ0Up9ZWA52CYBOuohZchLNyyb/m4Ll61jOc6WHb0FgxBi89vGOtWsRKYKoDQ8s814tMCLMs4l9sFryY+fnKpW8oR61gU9rRaTtDicw/mq9VgmBK3mB2tZojn4BWzYMSnMZRS5wd5PYNhIeKWsrqaIbqkqlvKhjyjcDCJpRHB84xJ2i64xSyMs3zcohGfliIi3SLynrDGjxpjWezG8xM2XimL51s+RNjyaUav9ucBX2T6Xu09mFKqoWE6loaHW8hoyycWx3Md/TiCBN2r/TTgPrS4zOQrdk+Q4xvqM2nHUv1Ey+cSZTzPwy1m9PZ6IqXzu4ojYU8rFIK2fD4LdKFje76Pju/5F+C3wK/QJTfeA5wG/E4p9caAxzfUwZ3M42P8QC3HKxfwnCp4LlYsqS2fYjQtn6B9Pq9Bf57fqpT6mlLq28AhYIlS6gql1CXA84F7gdeLiBGfFuF6frvkCR1LHc+U0W4lbmFEx/hYFlYsDhFedgUtPicCe5RSa8Ydexw4R0RiAEqpAvAx9J/BXwU8vqEOrr/dVdOeWhEx4/NpLW5xRPftsmywY77PJ5rLrqDFJ462dMazBUiil1oAKKU2otsonxfw+IY6uF5t4TVm+nj+cUPrcPPDUEunsGPa51MYDntaoRC0+PQDx0w4VutKeuYk5x4b8PiGOlRdHc4/avkA4FE14tNSRi0fO4Zlxfxll7F8guBxYKWInDPuWK1X+4tqB/yeXqcA0QxwCAHHt3xqyy0LC8+riZKhVTj5YfDGLB+97DKWTxD8FC00vxWRj4mIDawGKsDHReSVItINfBPdPvmpgMc31KHqukfuqlt62eUY8WkpbkEvu7BjWoDcKk7eWD5B8CPgLvRy6ruApZQaAn6Ijv25ExhGb8l7wP8EPL6hDlXPxTti2WXheWbZ1WrcQsZ3ONcsH9eP+4ne+xB0r3YHeBPwVWC1/xjgr9GiZI27/RS4KsjxDfWpuo4Wn9Fll95qr7jO1C80BErN8hnvcMZ1Ipli0Yxe7UXgEv9WO5YFXiMiL8Lv1a6UeiLosQ31qbgOnjdWVMyyLDyg4kS3XW8YuPlhHd0cT+kvAsvW4pMfjlxNn6DTK16tlLqz3vNKqYeAh4Ic0zAzyo4z6bKrYpZdLcUpjIxZPoBVczpHMMUiaMvnDhHZAfwAuFYptTPg6xvmSNXzLZ/asst3OBvLp7W4heHRrXYAbFuX1chHb8erGd0rTkGXRn1KRO4QkfeJSEfA4xhmSdmpHmH52L7lUzI+n5Yyml5REx8rFtn8rqDF53h04uitgAu8GrgGOCgiV4jIywMezzBDSo6D53mjrXK0z8ej4hjxaSWjGe3W2LKLiMb6BF1GtQj8BPiJiBwLvBd4H3A28CHgIhHZhhakHyil9gY5vmFyXM8dTa8YdTijq2mUnEqoc4sSXrWMVy37cT7+935tuz2CyaVNq2SolOpTSv2bUupcdGrFP6Hr96wC/hHYISK3NWt8wxglp4qHriVjjbN8XDwT4dxC3MLIWPlUqyY+dmRLqbakjKpSapNS6h/Q/qC/RqdVxIDXtWL8qFNyqkcVE7NGfT7G4dwq3GJGl0+1Y+O+BPxlVwR9PoHH+UyGiJyHXoL9MXAS+m+giu7zZWgyldEAw4m7XR4ls9vVMnTheAfLGvedb9t4VdeIT5CIyKlowXkvupxG7Ut3A3A1cJ1SqrdZ4xvGKDtHBhiC3u1yPJeq2e1qGbpljjvm7wGdZuG5uKVceBMLiaCDDJcD70YLTi2L3QKGgOuBq5VSjwQ5pmF6ym4Vd1xqBfi7XR7G8mkhbimnc7issdbIlm3jeQ6eEZ+G2e9f00Jvtf8Bnb/1K6VUKeCxDDNkdNk17piFrmJocrtaR61N8hHLLsv2Gwca8WmUBLp42DXoCGfTnaINKDvVI6KbYSzOp2wsn5bhlvKTLLts8Fy8SiG8iYVE0OJzvlLqnoCvaWiQiuvqbfZxtk+tmFjFbLW3DK+cx/PcsW120FaQ5+KWoyc+QZfUMMLThlTrLLtMSY3W4lVKOs5nnAWKZeN5Hp4RH8NCRPt8jl52ATieEZ9W4VWKk/h8LL3sciqRKyhmxCcCOJ57RNscqKVXmAjnVuJWiug34kjLB88Dz9PiFCGM+EQAp9YwcEKzZA9MGdUW4lVLWmgmWj76WZ33FSGM+ESAWpH4Iy0fv3mOaRrYOpyKdjhz9PIXz8OLWJKvEZ8I4NU6sk9Yd+l2yUZ8WoVXrfiWz5EWqPb7eGDEZ2aIyFoR+cWEY88QkeMan5YhSHSf9skxlk/rGLVsJhEfD2P5zIaVwIoJx3YCP2vgmoam4U3w+ADeOKvI0HxcR1s4R70T2vLxIhb20Oiy6xQRSU44dtRn3NAeHCUz1pHJpobm4rlV8KsLHIl/IGLlTRqJcF6PTh7dKCIPAbXcrdNEZKb9uDyl1F80MAfDjJlcZKyj/xIMzaKO5aPfAg8vYqkujYjP14AbgVP9W43jgQ9O89raO+ABRnyajG3Vt2+M9LQOr25Yg99KJGJL4DmLj1LqNyLyYuBPgGPQlQk/ABxCF5A3tAmj0jP+s+3X94lZZsOzZYyKz2SS72nLKEI0lFiqlHoUeLT2WEQ+AGxVSl3U6MQMwRHzs6iP1B6/rKpZdrUO1+WoUHMY2/2K2M5j0FntlwK7A76moUHilu1bP2Mf7tq6N24sn5bh+WkudZ6dYlm2MAm6dc6l4x+LyBmAAD3ohoJblVLrgxzTMD0x2x7tUDoey7KI2cbyaT2T/M51e5GWzyRMmlLDWUTejm6Vs2qS5/YAn1dKmXigFlGzfMYHFNZ+jo8r6WloMn7vtClOaNFE2oPAbW4R+RvgF4wVjc+gy6vm/cfPAK4Xkb8NemzD5MT91rwT/M1YWKPPGVqA5zG5wETT5xOo+IjI2cC/on+b/wWcrpRaopR6ulKqBzgDuMJ//hsi8rwgxzdMTtyyR8um1qi10onbxufTOqYSF+PzaZTPoAXtq0qpSyY+qZTaDHxERA4A/xf4OPBXAc8BABGJAw8ALwAuUkpd04xx5gNxO4YfxzaGv9WeMJZP6xjtVjoxt8u/N5ZPQ7wKGAa+Ps15XwdGgNcEPP54/gEtPJEnYR9t+bh+rpexfFqH3u2aatkVLcsn6E/e8cAWpdSU6blKqTKg0N1LA0dEno+2rAyMWT6T7XYZn08LmUpcvGmeX4AELT55dLTzTDgWCLxqtp/o+gN0xLXpFQYk7Niku10mzqe16Kz1ybPaPUxWe6M8CawUkVdMdZKIvApdkmNtwOODDnQ8C/gucLAJ1593xGx7LH3Ix49vNpZPK3EdX3sm8/l4ELHE0qDF5zr0r/J6EXnRZCf4+WA/Rr8N1wU5uH/tzwNbgC8Gee35jI7zYfLdLmP5tIxaSY2jqdXziZb4BL3bdTXwIeAlwAMi8jCwBu2EXgycC7wQLVD3ozubBoKIdADX+te+SClVEJGgLj+viVmWTq+YuNtlIpxbi19G1Zoo+H4ZVa8arUqGQadXuCLyRuBHwJvR9X5eOO6U2if9N8D7lFJBLnK/BZwOfFsp9UCA1533jE8e9TzP3/nSb4ZtLJ+W4VXL2qk8Ydml3x9Pd7eIEIGnVyilMsCF/rLrQuBZwCJ0pPNm4Cal1OogxxSR84FP+df/cpDXXgjYll23cI+xe1qHVy1pp/9RPh/bt3yM+ASCUuoh4KFmXb+GiPSgl3su8EGlVLQ6r80AIzDh41XLejdrQq92wG+Z7EauZfJCsLn/H3rn7Nu+4BkmMHVQv6EVuOXCWBzPJOKD6+pzIsS8Fh8R+SPgL4FNwFdCnk7b4kxSR2Ysot/ITyvwSjmdXmFZRxVwsyxbZ7yXciHNLhyatuxqEe/y758NFKfY3bpaRK4G7lZKnd+KibUT7rhSDkc4n/G0MBmajlMYxvMcmCyuyo7hVUu4hZHWTyxE5rv4bCN3NKEAACAASURBVEFv2dfjPCAFbAV6gXWtmFS7UXFdP67nyDa9rudRcY34tAI3PwyugzVZ/STbBtfBKQy3fmIhMq/FRyn1DeAb9Z4XkZ3AycA3opzVXnaqo+kUNWpBh5WIBbaFhZsf0g7nSSwfy47huQ5ufiiEmYXHvPb5GGZG0ang4WGPs3xs3/IpRCywLSyc7GFwqlixSb7v7TieW8XJHG79xEIkVPExfd1bQ75SxvW8IwIKbUsnmuar5RBnFh2cTL9On7CPFh8rlsBzqji5QbwILYODrmS4XUSun+G59wOPBTm+YXJylRKON9HysXE8j1wlWoFtYeFkevHqWj4xvQ3vVLSFFBGC9vmsBPZOd5KI2MDTmHn5jTmhlFrZzOvPF4bLRVzXJTZOfGKWheO5jJRNTGYrqA7uA6eCleo+6jnLsnzrp0J1cD/xRdFYEMxZfPy2OJdP8tRZInLPFC+10EXETgZ2zXV8w8wZKReoeu4R3Uljlo3ruQxHLLAtLKqD+3VuVzwx+QnxpC8+++Dk57d2ciHRSLvkjSKSB94w7rCHzl5/+Qwv8x9zHd8wcwZKeRzPHe1cCrrGT9VzyVXKFKsV0vX+KAwN4xYy2p/jVLBik/+erVgCr1qmOhCdnpuNLrs+BfzZuMcXozuWXj3Fa1wgCzyulLqrwfENM6C/kKXquqTHffB1Jy+99Oov5jipe0mIM1zYVA7vwKuWsWJxrDrF26x4Cq9apNK3s7WTC5FGe7VvRVcOBEBELgZ2T+xcagiXg4URqq5DIpEaPWZZFgnbpuI4HCqMGPFpIpXe7TpjPZ6qe44VT+IWhqn0bW/hzMIlaIfzKYDxYLYRnudxMDdCxXWOapOTsGNUXYeDuRFdUdvQFMqHnsKrFrGmEp9ECq9aptK/G7dcxE6mWzjDcAi6mJhxILcZQ+UCuUqJquseVa85Yccouw57s4MhzS4alA9swisXsToW1z/JjuvSGpUilUNbSD39ua2bYEg0q1f7W4GXAUv8MeqVlPGUUn/RjDkYNLszA5R9q8eekE2dtOPknTJ7jPg0Dc91KB9QeJUiscXH1z3PsizsRBqvXKS8f5MRn9kiIl3ArcBLxx2eTHhqVTw9wIhPE9k10k/ZqZKMHe3oTMZiDJUddo70hzCzaFA5uBW3mNWlS2LJKc+1kmm8SoHS3vX0vOhdU567EAja8vk82uIBnUG+iSb05jLMnKeG+yg5VVKTbPGmYnHKbpW+QoahUp4lqc4QZriwKe5+HK9cwE52HFXHZyJWshNn5BClXY+3aHbhErT4/CnamvmEUmqyAERDi9k23EfJqUwqLLZlk7BjlJwqTw31cd7xJ4cww4VNadcTuOU8VnJ6YbcSHTrWZ+iAjnReemILZhgeQSeWngLsNcLTHuQrZXaOHKboVElPllMEpGMJik6FzUOmv2LQeK5LcecavHIOawZWpWXbWIk0bjlPcccjLZhhuAQtPjlgIOBrGubI5qGDFJwqMcuu25m0Jj4bBw60eHYLn/KBTTiZw3iOg5XomNFr7FQXXilHYdvCL0cetPg8BJzud5QwhMy6w/soVMt0TJE60RFPUKhW2DRwgErEeoU3m+JTq/FKOexU17T+nhpWqgu3lKW4/eEFX14jaPH5ZyCN7ihhCJknDu8hXy3TOYX4JH2LaKRSRA2apVeQFLbci1vKYqW6ZvwaK9GB57o4mT5Ke55s4uzCJ2iH8wHgMuAzInIucAuwD6hbsUopdVXAczAAmXIRNXiIYrXCcR31DVHLsuiIJ8hXyqzp3c1zlp/UwlkuXKojvZT2rMct5UgsftqMX2dZFnaqG7eYpbD5btInn93EWYZL0OKzmbEYnuf5t+kw4tMEHu3dRb5aJm7HjkqrmEhXPEWmUuTh3p184NkvadEMFzaFzXdrqyeRnryA2BTY6W6c3AD5TXey5A2fnvGSbb4RtPjsxvShawseOrSDXKVMV3zqwDaAzniS3kKGbUN99BUyHDuFpWSYGfkNt+MWM9jp2f8urVQ33tB+Kv27dbTzSWc0YYbhE3Ru18ogr2eYG2WnysOHdpKtlHha56Jpz4/bNulYnFy1xP0HtvH2U6NRzKpZVEd6Ke58DLeYITGHqoSWbWOne3ALI+TX/27Bio/pXrEAWdO3m6FSHvBIzdDk706kyJZL3Lt/a3MnFwHy63+HW8xgJTrqFg+bDrtjEW5hhNz63y3YXa+m9e3y6zSfAzwLWKKU+g8RSQArlFI7mjWuAe7cq8iUS3QnUjP2F3QnUhwu5tjQf4CD+RFOmIHFZDgaz/PIPnEzbn4Iu2Puv0Mr1YU3dIDqwD6K2x+mY9WLA5xle9AUy0dELgJ2ouN+rgW+4z91MrBFRK4TkYVfsCQEcpUSqw/uIFMp0jOLmjBxO0ZHLEG2UuLOvaqJM1zYlPdvonxA4ZbzjYmPZfvWzxC5J24KcIbtQ+DiIyLfAK4AVqCdz+NbYq4AYsB7gFtFZF53TG1H7tq3heFSgZhlk5qkR9RU9CRTjJQL3L5nE67p4T4nco/fhFsYxk731C2ZOlPsjsW4+WHym+7CyS+8VspB9+16NfD3QB74GLAUeLj2vF+z+X3oNIxXAB8JcnwD3LprA8PlAouS6Vlv0XYn0pScKrsyA6w9vK9JM1y4uKU82bW/wc0NYXc2XpbWSqQhFsfJ9pN74uYAZtheBG35/DXa2vmQUuq/lFKZiScopX6IFiALeG/A40caNXgINXSIfLXMosTsV7W2ZdGTTDNSLnDLzvVNmOHCJrfuVpxMH1jWjLLYp8OyLOzOpbj5IbJrfqlrAi0gghaflwAHlVI/m+okpdQNwH7gzIDHjzQ37niS4VKB7kTqiDY5s2FxsoPhUoH7DzxFX+Go7w5DHTzPI/voL3Bzg9idSwILDLQ7FuOWC5QPbVtwme5Bi89SdDrFTNgHzCzV1zAtA8Uc9+zfynC5wJLk3H+tqVicVCzOcLnAzTvWBTjDhU1p1+OU9m7ALeUDWXLVsGwbu3Mxbm6QzEM/Cey67UDQ4tMPnDrdSSJioWv/RKcxdZO5acdaBot5Enas4QaAS1KdDJUK/GbXegrVuml5hnFkVl+Pmx/E7ljUsKN5IrGupTj5IQqb76YyMG038nlD0OLzALBURN49zXkfQPdpfzDg8SNJoVrmlp3rGCzlWRpAKdSueBIPj958hlt3bQxghgub6uB+8pvvwskPEetaFvj1rXgKO9mBkx9aUNZP0OLzXbQj+T/9DhZHICK2iPwF8J9ox7SpeBgAt+xcx8H8CB7ejHK5psOyLJYmOxko5fjFtscoO9XpXxRhRlb/GDc3oCOaE/V7czWC3b0cNztA9rEbcAojTRmj1QQqPkqpe9A1fZYCvxKRIeBcABF5GF3l8L/Rvp7/UUrdHuT4UaTkVPnFtscZLOVZluoMzNHZk0xTdR32ZYe4fc/mQK65EHEKI1oQsgPEupc3bRwr2Qm2jTPSS/bRXzZtnFYSeJChUurv0TE+fcAidHExCzjPfzwC/L1S6qNBjx1Fbtm5jv25YaquS88cttfrYVsWS1Od9Bdz/GTro8b6qUP2kZ/jjPSCbQeyvV4Py7Kwu5bjZPvJrL4ebwH44pqSXqGU+i/g6cCrgU8BXwY+A7wJOEkp9c/NGDdqFKplfrZ1DQPFHMvSwVk9NRYlO6i4VXZnBrhtt/H9TMStlBhZfT1Oth+7a3nT6+7YHYvArVId2Ev2yVuaOlYraFp6g1KqAtzt3wxN4IbtT7I/N4TjunMKKpyOmvVzuJjl+i2P8PqnP7vhnbSFRO7xG6kO7gPXaSiPa6aMWT+HGbn/f+k++21Yc4znagfm78wjzki5yM+eWsPhYo5l6ZkXKJ8ti5IdVF2XvdkhbtixsGsKzwbPdRh54DrcbD9297KWVRu0O5fgVopUDj1FfuMdLRmzWczZ8hGRWtXC82slMvxjs8FTSplOdXPg+i2PcCifwQJ6mrTDAtr6WZ7u4nAxy0+3Psobn3Emi1MmNjS37jYqvdtxK0USS1e0bFzLtnXcT7afkfuuofPM183bMquNWD4r/FtikmOzuRlmyf7sEDfueJL+YpblTbR6avQkUljAwXyGH215eNrzFzqe6zJy37U42X5iXctavvSxu5bhFrOU9m6g+NT8DZVrxOdzkX9/YJJjhiZy1aYHOFzMkYzF6Wqi1VPDsiyOSXdzsDDCTTvWceEpz2VF99Kmj9uuFNTdlPdv1p0plsy8M0VQWHYMu3MJTvYww/dcSXrVS+al9TNn8VFKXTuTY4ZgWXd4H/fs38pgMddSAehMJEmX4/QXs1yx4T4uedGFLRu7nfA8j+F7r8HJHibWtTTwVIqZEuteTqX3KYo7H6O063HSK88JZR6N0KxKhotF5MOTHP+siHxFRI5vxrgLHddzuXzDPfQXsvQk0zOuzxwUx6S7GSrluf/ANtb07mrp2O1CcdtDlHY/iVvMYjchlWKmWLG4znjP9jN879WhzaMRmlHJ8AJ0C53LRWRiB7o/Ai4GNorIG4Iee6Fz666NbBo4QLZSYtksumAGRTIWZ1EyzeFilv9af28k2yuP3Hu1juvpXDLrflxBE+tejpMforjlfkr75l8cVtCVDM8BbgJ6gC3AxESjnwOPodMvfikiq4IcfyGTKRe5ZvMD9BWyLEt3EQ8pvmNZuotCtcLWoV5u3LE2lDmERWn3kxS2P4xbGCHWHZ7VU8OKJ7HTi3ByA4zcN/88HkF/gr+A9iN9DzhjYpcKP/L5hejE0k50yVXDDPjB5tXszw7jel5D9XoaJWbZLE930VvI8MPNDzFQzIU2l1YzfO/VuLkBXTZjji1xgkZbP4PkN9xOuXd72NOZFUGLzyuAQeCzSqlJaz76xz8PZACz9JoB24b7uHnnOg4Xsxzb0R36zsaiRBrbgoP5Ea7ceH+oc2kV5YNbKKh7cXJDTU0gnS1WIoWd7MLJDc476ydo8TkG2KaUmjLrTSlVBLYCxvE8Da7n8r11d3G4kKEjnqAzgJIZjWJZFseme+gvZvn9nk2si0Cx+ZH7foCTG8BOd2O1wXswHrt7OW5ugNy6W6kOHZj+BW1C0OLTC0x0MtfjWHSGu2EKbt+zmSf69jJSLnJsujvs6YySjifoSaQ5XMjyvXV3U13AzufK4D5y63+HkxvEbiOrp4ad7IBEGjc7wMiDPwp7OjMmaPF5DDhBRN451Uki8hZ01vuagMdfUGTKRa7ceD+9hYzvZA4npqQey9Nd5CtlNg8eXNDO58yDP8LJDWAl0thNSOANgli3LreRXfPredPjK2jxuQJdu+cqEfmIiBwRfisiSRH5IPC/6LywKwIef0FxzaYH2ZcdCt3JXI+YbbO8Qzufr9v8EIcL2bCnFDhOfpjsYzfgNrlYWKOMFhvL9JF99BdhT2dGBF3J8CbgOqAL+D4wKCJPisj9IrIWGAKuBBYDP1VK/TzI8RcSW4YOcUsbOZnroZ3PFgfyw1yx8b6wpxM42Ud+hpM5DHasqcXCGsWyLGK1YmMP/WReFBtrRrDIB4Evov05aeAsdD+v5/iPc8A/An/ehLEXBK7n8p9r7+JwMUtnPNkWTuZ6WJbFsR3dDBRz/GGv4vG+PWFPKTC8apnMwz/TCaQtLJsxV6zRYmP7yK27NezpTEvgIZpKKRf4loh8G3glsApYjhadLcC9SqmFZ58HyK27NrKufz+ZcpGTe8IPZpuOdCxBT1I7n7+/7m7+8/z3kGgz/9RcyK3/nV8srIqVbn6xsEbRxcaW4eQGyDz4Y7qef2FbC2azKxne4d8MM2SkXOSaTQ/QV8iwvA2dzPVYnu5iV2aALUOHuGH7E/zJqnPDnlJDeJ5HZvX1ONkB7M6lbf1HPB67cwmVzGFK+zdR2vEo6VNfEPaU6mIqGbYZ1256kH05Hcm8uA2dzPWIWTbHpLvoK2T5kXpk3jufS7ufpLRvA24pi901f8qH6HIbfofTh38a9nSmpJFKhvegd6zeq5TaO+7YbPCUUq+a6xwWGluHerll5zr6i1me1rlo3nzb1uhJpBkuFzmQH+bKjffzd+deEPaU5kz2kZ/rvutN6EDabGKdS6n07yS/+W6qw4eIL27PWN5Gll0vR4tP54Rjs2HSFIwo4nkel6+/m37fydzRxk7metScz/uyQ9yxdzNvWXkWZy4/MexpzRonO0B+4+24+SFiy54R9nRmjZVIYcXTuPkhso/+kiWv/VjYU5qURsTnUv9+fL/1r2IEZU7cuW/LaCTzfHAy1yMdS9CdSNNfyPL99ffw3Vf+KbY1v1b32cdvxMkNQSyJnWzPoMLpqNV5zj5+A4vP/3Do5T8mo5EZecBOpdRA7YBS6pKGZxRBCtUKV2+8n8PFLEtTnfPGyVwP7XzuZ+PAAX6/exMXnHxm2FOaMZ7r6qDC3CB215KwpzNnrHQP3vBBqoP7KWy5j85nnx/2lI6ika+kTwCfHn9ARP4gIv/W2JSixy+eeoxdmQHKjsOSVPsGss2UuG2zLN1FXyHDNZsfJF9p/4C3GqWda6j07cCtFLHnwfZ6PSzL0m128kNkH/t12NOZlEbEZzG65/p4zgfmXzHZEDlcyPr9t3Qksz3PnMz1WJLswPF0v6+fbH007OnMmOwTN+Pmh3xH8/xaLk4k1rkEJz9MYesDVEf6wp7OUTSy7NoPiIh8Dd2VtOQfXywir5zpRZRSs90hW1Bcu/lBegsZYpZN1zx0Mtej1vGir5DlV9sf580rz+K4zp6wpzUlbilHfuMduIVhYi3sxdUsrHgSK5HCLQyTX/dbFr3s/WFP6QgaEZ8fodMo/sG/gfYDPQe4c4bX8Bqcw7xm+3Afv9+9iYFijpO6lsy7rfXp6IonGbJt+gpZrt38IJ8/p71rx+U33oGTGwTLxmrT7PXZYncsxs0Pk33iFnpe+r62+ow1Yldegi6H2ocWkdq/yprFbX7btQ1y1aYHGCjldFuaBdgD3bIsjvHzvm7fs4ntw+1n+o8nt/ZW3PwwdsfitvojbQS7YxFuOU/l4FYqh7aGPZ0jaKRvVxX4lH8DQERc4D6l1IyXXVHlib49PHRwB8OlAs9og2LkzSIdS9CVSDJYynPVpgf42ovfFvaUJqU60kdx+yO4xQyJY08JezqBYdkx7FQ3TnGE3LrbSJ5wethTGmXOlofff2viInIXR3YwNUyC53lcs+lBBoo5epJpErH5vbU+HctS3QyVCjx8cGfbllzNb/g9bjHjB+gtHN8b+NZPfpj8utvwXDfs6YwS6FY7sBM42MA1I8HqQztYP7CfTEj9t1pNMhZjUTLNQCnHNZsfxPPaLw41v+F23MIIdsf83V6vh5XuxquWqQzspbxvfdjTGSXorfZXAWc3cM0Fj+u5XLf5IfqLWZakOkLrv9VqlqU6GSkXWXt4L2t6d4c9nSOoDh2ktHutTiKdx7E99bAsGzvdg1scIb+hfYpMmK32FvPAge1sHjpIvlJmZU/7luUMmrgdY3Gyg4FijuvUQ5x73DPaxqmb3/QH3FIWK9HRlmkIQWB39OBkDpPbeDtL3vDptohhMlvtLcT1XH605WEGijmWpDqJtcEHoJUsTXWyM9PP+oH9rOndzXnHnxz2lADIb/yDXnKl2zsOqRGsVBfe4H6qA/so799IasVzwp6S2WpvJasP7kANHSJfKbdlQfhmE7dtFic7GCzm+PHWh9vC9+NkByjtflIvuToWsPhYNna6G7eYJb/prrCnA5it9pbheR4/2foog8U8i1MdkbN6aixNdbAzM8Daw/tY27+P5x0TbiRxfvNdeskVT7VNC+RmYad7cHKDFDbfyZLXfSL0ZW/QfwG7MVvtk/LE4b1sHDhAtlJiSRt3QWg2cVvvfA2W8vx0a/ht2wqb78YtZhb0kquGlerGqxSo9O2genhn2NMJvHXOSqXUu4K85kLhZ0+tYbCUZ1EyHZkdrnos9Xe+HundybYQo57dUp7ijkfwitloiI9tYyc79dJr891hT6d5PhcRuUBE/kNEbheRR/xjS0TkYhE5plnjtiPbh/t4tHcXI+UiSxdAyYxGSdgxuhMphksFfrnt8dDmUdy2GrcwApYNCyywsB5Wuge3mKHQBpvMgYuPiBwnIncBvwE+BryGsTIbJwMXA0pEXhT02O3KL7c/wXCpQFciuSBaygTBklQHw+UCd+3bElqx+by6B7eYxUr3hO7/aBV2uhu3lKO0Zx1OdmD6FzRzLkFezG+PfBu6X1cG+CUwPp7eAQaApcDvRaQ99lqbyGAxx117FcPlAksj7OuZSDqWIGnHGCrluSmEPu+e61Lc+oDv7+lu+fhhYcUSWPEUbilHYWu4HWaDtnw+ATwPWA2cppR6JzrlAgCl1HrgVOABdEvlzwU8ftvx290bGCoVSNixBZm53ghLUp0MlQrcunsDZafa0rHLe9dRHenFc522boPcDPSWe4aCujfceQR8vXcDLrqdzqSeRKXUCPBetBU0f3urzADHdfnNzvUMlwuRjOuZjq54Etdz6c1nuGd/a8s95NW92upJdUVmyVXDSvXglbIUtq0Otad70OLzLGCTUmrHVCcppXahWyfPv74ks+Dh3p0cyA1TcR26Eqmwp9N2WJbF4qT2/fx2V2sTHgtb7o3MLtdErEQKD3DzwxR3hFfiNmjxiTHz1jlltPWzYPmtb/UsSqQXTG3moFmUTJOtlFjfv59dmf6WjFkZ3Efl0FO4lQJWBKoKTMSyLOyUv/TaEp7fJ2jx2QmcLiJTpgaLyHLgTMb5gxYaA8Ucj/buIlMusmie9n5qBXE7Rmc8yUi5yO17NrdkzIK6B7eU04mkEd191FnuWQrqntDSXIIWn1uAJPBP05z3XXRqx60Bj9823LlvC5lKkWQsTnKBZkoHxaJkmky5yB/2Klyv+cWuCjV/T4R2uSZipTrxqiXfCgynvGrQfxX/CnwI+IiIHA/8EF33BxF5Njrj/ZPotsoZ4LKAx28b7tyrtNWzQAqRN5OueJJeN8PB/DBPHt7H2cc+vWljuYUMxZ2P4ZayJHqObdo47Y5l2dipLjw/2jmM8qpBp1f0Am8DBoG3Az9FL68A1gPXA68AcsC7lVLtWVOzQfZnh9g6dIh8tUK3cTRPi2VZdCdSZMsl7tv/VFPHKmx7EK+YwbLjC65c6myxakuvkPw+gUc4K6XuB54LfAedaDq+hEYvcCVwtlJqwS657j+wjVylTEcsEdns9dnSnUiRrZS4/8C2pi699JIrmrtcE7FT3bjlHOV9G6iO9LZ8/KY4I5RS+4HPAJ8RkS700iunlBpuxnjtxupDO8hWSmZ7fRZ0xBNUXYfDxSybBw9xxrKnBT6G51QpbL0ft5ghtvTEwK8/37BicaxEWkc7q3vpecEft3T8VnwtJ9EiFwkTYKRcZNPAAQrVMl2JaJv1s8GyLDoTSfKVMo8c2tmUMYq7HsPJ9ON5LlbCBH2Cb/0Uwkk0bYrl4+dsfQl4K3DsuOOD6ITTS5VS25oxdtisO7yXQrVC3I4FkkRaGs4EMKvmkloczBKmK54kUynxxOE9fICXBHLN8RQ23zO6yxW1qOZ62OkeKv27KO54BLeUx25h1YXAxUdEXgX8Cr3UmvgOL0OnVrxVRP5YKdU+pfQDYm3/PvLVMh0B5XH94f1fCuQ6zeSPbvhuINfpiCfpK2TZMtRLoVqmI0CHsOd5Or6nmCHWE6mKLlMTT2LZMdz8CIWnHqDrzNe1bOigs9pPQGeyL0Hvbn0EOBc4DXgh8HFgA7AI+LF//oJi0+BBik6FjgVekrMZJOwYtmVRrFbYMhSsA7RyaCuVgT141RJWMnpRzfWwLAsr3Y1bylDY3NqlV9CWz+fQ5TJuBN6plKpMeP5REbkS+DnwFnS9n4sDnkNoVF2HnSOHKVYrHGd2U+ZEOpag6FTYNtwXaH3n/Oa7dC5Xqqst2sa0E3aqB2doP4Wt9+E51Za1Dwp6lDcDFeDDkwgPAEqpioh8GNiDjgUKRHxEZAVa/N6ILloGsAO4Gfi2H4PUVPZkBylU9T876qVS50oqFqfkVAMvr1qr1WwtwI6kjWIlO/A8FyfTT2nX46RPfUFLxg1afE4G1tcrp1FDKdUrIuuBVUEMKiKvQFtbS9DJqk+hk1wFOAN4v4hcoJRqatWqWgZ7wo4F5tB8zQ++Hsh15gsJO0ahUuFgPriojOrQAcr7FW45T2KJ2WKfiGVZozV+8uqeeSs+LjBTZ0eCAHxOIrIE+AVaeG4FPqSUOuA/dyrwA+BlwK9F5AylVLHRMetxMD+ixScWXLJiUDtJ84VELEal5HAgNxLYNQtb7vU7kqYXbEfSRrHTPTiZfp1o+sbPtmQ3MOi1wVbg2dOVRxWRlWiLJIhY+g+it/P3A39aEx4ApdR24B3odI9TgD8JYLy6DJbyVF2XuGWWXHMlbtk4rstwuRBYpHN+dIs9WkI+G6xkF161SLV/D5VDzU1xqRH0X8kN6OXOdSKyeLIT/OM/RG/D/zqAMV/t39+slDoqKMZfAj7gP2yqPZmvlHE9D9uIz5yxLRvX83A9d9R/1ghuKU9p5xrcUi7SWezTYdk60dQtZSlsaU151aBt0O+gt9dfCmwSkWuBNcAwOu7nXOADwAloS+U7AYz5NfTu2ZYpzqnZkE0t3lJ0KngY8WmEWtE119O/z0ZTVIrbVmtHsx2DmIk4nwqrVmBs6/0sfuWHmj5eoOKjlBoSkT8Cfgs8DfjCJKdZ6I4WFyqlhgIY8xHgkXrP+z3Czvcfbmh0vKkwUbPBYUEgIq5zubJYqcaimvtzjVthzWZ5V2OxZXa6m8rIIUp71uLkhoh1LQloZpMTuPdNKbVWRARdt+ct6LrOi9D1ezYDNwHfb2GS6XeATiCPdkw3jZj/4Q6rMtxCYPR3Z0GsQfHxPI/CUw/ilrLEFh3f0LXO/dcnGnp9K9h5cWNeBSuWwIoldSfX7Q/RdVZz+zs0K6s9lxNhtgAAFY9JREFUC3zLv4WGiHwZ+DP/4VebHeuzKNlBzLJxWlCNb6HieC62ZRGzbLobTMyt9G6jOnQAr1rGMt1DZoSV7tadLZ56sOni0zLnhIi0dI9TRC4G/tF/eAPwz80ec2mqk7htUzXiM2eqnkvMtlmc7Gh42VXcthqvlMNOdmEZP9yMsFNduMUcxW0PNd2CD+QdEZGzReR/RWSqr5f1IvJLETk7iDGnmEtcRP4LuMQ/dBu6amLT10Indi0mYceoOAu6KUdTqTg6SPNpXZNuls6K4o41uKU8Vgsztec7VrIDzynjjByi2r+7qWM1bI2IyKXAF9FCdjXwh0nOORk4HZ1geqGIXKKUCjx01++a8XPg9f6hnwDvV0q1pDPaykXHkIrFKbtVPM8zDug5UHKqpGJxTlnUWOa55zoUdz2GV85hdy1reF5r/vb5DV9jPmBZNlaiQ/t9djxK4pjmdTRvSHxE5B+AL6M3J/ZMcWoWXd/nL9HBfl8VkaJS6tuNjD9hLivQu2zP8Q/9C/B3rbB4ahzX0c3iZAdxO0bRqQZWViNKFJwKS1OdrFrcWHH3ysGtuPlhPNfFCqCiZKM7SfMJO9WJV85T2v1EU6sbznnZJSKnMba0+SqwSil1lNUDoJTqV0p9E73z9R20WH1NRE6Z6/gT5nIicBdaeBzgY0qpL7RSeEBvDT/vmKfTGU+SD7EN7XzF9VxdjiSe5PkNdrAo7VuPVylgJTuMBTpLrEQHbrlAaW9zu8g24vP5KDo/63tKqUvqZbGPRylVUUp9BvgRurzqXzUwPgAikkQnlT4T3QX1nUqpyxu97lw55zgtPrlKKawpzFtylTLpWIIV3Us4obOx7PPS3vV45SK2KZc6a6xkB16lSHVgD05usGnjNCI+rwWq6Ajj2fIltPXz+ulOnAF/h46cBviEUupXAVxzzrz0hGfSk0xTcR3KTjXMqcw7MpUiPck0rzzxtIavVTmgdDtk0y121lh2DCuexKuUKB9QTRunEZ/PqcBepdSh2b5QKbVLRJ5CWytzxrd6PuM/rAIfFJEPTvGS3yilvtHImNOxONXBC447mUP5EUbKRY7pMPlEM6HqOuSrFY7vXMSrV0hD1/Jch0r/Ll21MG46iMwFK57SHU37ttOx6sVNGaMR8UkDAw28fhBY2cDrAc5CV04E/W952TTntyRd940nn8l9B55iT2aQZelOk+s1A4ZKBXoSKZ57zAqe0dPY7lR1YC9euQgeYMrZzokx8dnRtDEaEZ9+xioGzoWno1Mu5oxSag1HF6kPnRcev5JTFh1DXyHLcLnIUhNnMiWOp0torOheyv95ZuNhYNWBPTqqOZ4wzua5Ek/iFUeoDky1id0YjXwlrwWWicizZvtCETkDndkeTof6JmNbNu9cdS7L010MFHMm3WIaBkt5OhNJVi05jhcdv7Lh61UzfXhuBctYPXPGisXxnCpOJthytuNpRHxuQlsdX5nDa7+ENorvamD8tua1K57FqsXH0ZlIMljMhz2dtqXqOgyXCixPd/PBZ78kkCWqk+nDc6pgm6qFc8WKJcCp4GT6mzZGI+/0teil17tEZMYCJCJfBN6Djsf5nwbGb2tits1FZ7yU5eluhssFs/NVh75ClkXJDp53zApefHwgYV+4+WFwHV3DxzA37Bie6+CW83gBFHWbdIi5vtCvGngR2vq5WETuE5ELReSo7R0R6RGRt4nIfehkTw/4wkLtWlrjxcefwsue9kyWpjrpLWRMqY0J5Colik6FYzu6+cRZ5wfmn/GqFfA8MI7+uVN7LzwPz2mO+DRklyqlbhaRz6NLZ7wEXRbVEZGdQB86CPEYYAW6iqCFFp5vKKX+rZGx5wOWZfGxs17Fk4f3snWol+FygSXG+QyA47r0FjIc29HDH686h1MXB9dF1KuWABcss+yaO7UvAk//PpvwuW34q8HPz3o1oNAzjqNb4rwEOA+9nR73n3sIeKlS6v82Ou584f+3d+fRcVbnHce/78xoHW1jSZYs2cJ4e0B4AbMJwmrA2NhAgJKymCWAScvaknMKIUBJXMrhQOCQhGaBntKGnEMoTQIktCW0oTm0Jy2lkEJLH2J2G9nCtixZ+2z9474iE0WyFmvmHWmezzk6mu3Oe0ea+b33vfe+dxrLq7i69TM0llexe6CXQTv8Ip1O09G/j/JIMYfEGrl02THTuwHPIw8HQc0I07JrUNWXgVYROQE4HXcO1xygF2jHBdMzqvr+dGxvptm4cAX/sfN9XvzoLXb0dbOgIvbpWsWFqHtogMFUgoWVtfzJ6rWUTvMJuKGSqDvkStko45QNj9B6bmH5bJjuNZxfBl6ezuecDTzP448PP42tXR28tWcHHf37aCirLMg5KAOJOLsGephfEeOq1uNZUjN32rcRKqmAUMiNeJmpSaXAP83Ci2Rn4X3rkcuROaVRbj9yPfOi1Qwk43QN9QddpZxLpFK093VRX1bJKc3LuGDx6qxsJxSN4YUiYOEzZelUHC8UIVyevUXkLXxyaEVdM1e3foZ50Wp2D/TSFy+cZTdS6TTtfV1Ei0qQWAO3HHF61lp+RbUt7sRIW9ZkytwM8WIiWVxMzMInxy5YfATrWg6jsbya9r6ugpj/M9zBHPI8FlbWcvcxGw/4+7j2JzIcPskhm94wVX74FM1pydomLHxyzPM8bl61hqMaWqgtrWB7bxeJ1Oxe83nPYB+DyQRN0RpuP3o9Cw7wxNHxRGqa8Eor8UJhf9jdTFZqqB+vqJSihgNaeGK/LHwCUByOcOfRGzh0TiMVRSV83Ns1bd9Lnm+6hvrpHuqnKVrNTatOZXV99vakw7xQiNKWw/GKy0kP2qktk5VOp0jH+wkVl1O68MjxC0yRhU9AakrK2dJ2Lour6ykKh2nv7SY1yw4ReuKD7OrvoSlaw+WHtLH+oOXjF5omJQtXEyqJkh7qzdk2Z4v00ABeuIhwVT2RuoVZ246FT4CaotV8te1sDqqsBQ929nXPmj6KvsQQO/u6aYrWsPHgFWySY3O6/bIlxxEqqSA12Et6lh/WTrfUQDeh0kpKFx2b1ekgFj4BW1bTwF3HbGB+RYxEOsUn/T0zPoAGknHae7v8VQmXcdPKNTmf01TUsJSihsWEistIDfTkdNszWTqdJtXfTaisiujKWfKNpWZsq+tbuHX1mTRHa+hPxtk90DtjA2gomeDjXjeXp61xEbceuY5wKPdvM8/zKF++llBZNan+rpxvf6ZKD/bihcKEq+ZSuii7rVU78y5PnNS8lL7EEA++/iLbejrp2Tc4I09PSqZS1JZWcOTcFu4+ZiMl4eDeYhWrNtD10qMkuneSjg9Oy/d3zXbJ3j2EozGiK9fjZfl/Z+GTR9YddBh9iSG+8+YvSMzQ85I8D5ZWN7Cl7VzKi7IzLX+iIrEmylvXkOzuINm7m0hNU6D1yXfp+KAb5aptoart4qxvz8Inz5y/+AiOa1xE5+DMHKXxCLG0pp5InizkVXXcpfS+8Y/EO94lXRHHs2+RHVOyZxfh8hjlrWuIxLIf1BY+eWhetJp50eqgqzErlCxYQdniNlI9e0ju+yQnH6qZKBUfIDXYS/HcxVSdcEVOtmkdzmbWqznjRsKVdaQGe0jFB4KuTl5KdncQrqglunI9JU2H5mSbFj5m1itpbiW6ch3hijkku3bO2JHEbEkN7IPEIOHKempOuy5n27XwMQWh5rTriVTPg1TSht4zpFMpkl07CFc3UnX8pTk9LLXwMQUhEmuiZs0fEKlpJNndYQuN+ZL7OvCKyiieJ1SfvDmn27bwMQWj8rhLKDnoCMJlVSS72gv+8Cs12Eeqv5tIdSNzNn6JUHFpTrdv4WMKhhcKU3vunYRrmkgnhkj17Q26SoFJp5Ik924nUt1IxVHnU7Y4t+fegYWPKTDFjcuInXEDkVizO/yKF956P+l0muTedrySKMXNrcTW3RJIPSx8TMGpbLuEMjmRcGUdic7tpGfobPKpSvXtJZ0YIFLTTN0Ff0YooO+Ss/AxBccLhag77ysUNyzBixST7NpRMP0/qaF+kt0dRGLziZ1xPSXNrYHVxcLHFKRwZR11F95LJNZMOt5XEP0/6WSCZOc2ItWNRFeso/L4ywKtj4WPKVilC1cTW3sTkdh8kvs6SM3iJVfT6TSJzu2ESispWbCc2s/eFfj3xln4mIJWefwmoodvJFI9j0TnNtKJeNBVyopk1073XeZ1B1P3+/cTKq0IukoWPqaweZ5H7bl3UbroaMLRGInOj2ZdB3Syt5P0YA+ROfOp+70tFM9dFHSVAAsfYwgVl1J/0QMUNy7Di5SQ3Lt91nRApwZ7XQfznAXUnHEj5XJS0FX6lIWPMUCkuoH6ix6gqO4g0skkye6OoKt0wNLxQRKd24nEmqk48rM5Wypjomw9H2N8JQtWUHve3ez6wW3Ed71PIpWAPFkUbSrSAz1EKuspW3YCted8OfAO5pEsfIzJEF2+lsSebXS+8LBbamIGC1XWUTx/OfUX3Y8XCXZJ29FY+BgzQtWJnycyZz7xne8EXZUD4hWVED38bMLl+bkqpoWPMSN4nkd0+VrI3ResFiTrcDbGBMLCxxgTCAsfY0wgLHyMMYGw8DHGBMLCxxgTCAsfY0wgLHyMMYGw8DHGBMLCxxgTCAsfY0wgvNmyaFK2iUh3cXFxZUtLS9BVMSavbN269TlVPWey5ezE0onrGxoaYuvWrR8FXRFjZgNr+RhjAmF9PsaYQFj4GGMCYeFjjAmEhY8xJhAWPsaYQFj4GGMCYeFjjAmEhY8xJhAWPsaYQFj4GGMCYeFjjAmEhY8xJhAWPsaYQFj4GGMCYev5ZBCRhcB7Y9ydBjqBD4G/Bx5S1U9yVLVpIyJXAn8FbFfV+Rm3vwScDNyjqncEU7v9E5HHgSuAf1HVUwKqwxeAbwObVfWxSZS7Hvgm8HlVfXyS24wAcf/qZar6xDiPvwZ4FEiqat5+xvO2YnngTaAr43oEiAHLgcOBzSKyRlXfCKJyJvdE5Gjg/imUOxa4b/prNLNZ+IztRlV9aeSNIlIL/DWwAXhaRA5V1VSuK5cFlwPlwK6gK5KPROQU4IdA5STLnQb8HRDNQrVmNAufSVLV3SJyBbAdWAasBf4h2FodOFX9MOg65CMRKQVuA+4AwpMoVwbc7v9Y3+oo7I8yBaq6G3dYBu4wzMxCIrIEeBv4U/+mO4APJlBO/HJ3ACngS7idlclgLZ+pK/J/7xt5h99BeDHwOWA1UAskgI+BfwYeVNW3Ryl3JnA90IbrX+rChdxTwGOqOjRKmSrgZuB8YAluh/Iu7hDhIVXdO5EXM1qHc0YH/E5gHnAVcC3Q6hd7E/gu8Liq/s5i4NNVtwDNBxYAvwRuUNVXRWTzBMot8Mv+m1/uNRG5IYv1HNeITuvx/KWqXpPN+oCFz5SIyGJciyfFiEMuv7n9U+BU/6b3gTeABmCp/7NJRE5U1dcyyt0EPOxf/Rh4HajDBcLJwIUicrqqJjPKHIIbeVsIJIF3gH7gMOAu4AoRWaeq/3eAL9nD9XNdBuzF7dUX4UKyDRDcoUnm3yFXdcumbcAGVX1+kuU+BNaraj4djqeBf93P/XW4/yNMoHU3HSx8JkhEwkANcDzwAG4vfo+qjvxH3YoLnl3AWar6SsZzHA08g2tF3A5c6N9ew29GQy5W1SczyqwFfgyc4j/+Sf/2KPAc7sP9DHCdqn7s39cIPIbrFH9WRFapav8BvPy5wCW4Vswjqpr0+0IeBTYBXxSRrw1PPchx3bJGVbcCW6dQ7m1cQOcNf6d1wmj3iUgl8LJ/9QXgz3NRJwufsf3cHbqP6T7gzlFuPx3XIvpKZvAAqOorIvIt4KvAioy7BCjFzSP6wYgyL4jIvcBKIPOw6xrcocx/ARdktohUdYeIXAi8hWtpXQl8a38vZgL+QlW/nrGNARH5I+BS3PvoGFyLL4i6FZLvicj3puvJ/MOxv8W9v94CPpf5/8om63Ae25u4Zurwzy+B/wEG/ftvAb7ut4g+paon4ILk22M8b5//uzzjtvdwfUIx4HERWTXiObeo6oWq+sOMm8/zfz852pvFb0087V89e6wXOQnPjbKN3cDwRMuaAOtWSN7mt9+Xo/1MprX2CHAmsBvYqKpd4zx+2ljLZ2xjzfMpxu2tvwncgBt+vS7zMaoaF5GYiLThhuMX+b+PwPX9QEbwq2qHiNwHfBk33+ZyEdkB/BOuGfy8qo6cfzM8yrZZRM4d4zU0+r8PGffVjm+s0ZrhQ6bM91Ku61ZItkxihvN+icituAGEIeB8VX13eqo4MRY+k+SPOH1XROYBdwPXisi9qvoRfHr8/DCuL6Qoo+gQ7jDkNWDdKM97h4i8igu0k3Afzkv9n4SIPIkbORneM1X7v4c7sfenZpz7J+J3RtpG8DIu57puZpL8Q997/atfUNVf5LoOFj5T9wwufMK4Fs1HGbefimsRfIPfHK792m8RbWaU8AFQ1R8BP/KHqE/GdTKfhWsdbMJ9qM/xH97rXz9bVX8yza/tQOVz3QqeiBwH/A1uh3HfZM81my4WPlOXeUqFB+AfZg0PsW9Q1Z+PUm7+yBv84fmlgKeqv1LVblwfy3O4kaTbcHups0Wk2m/9KK6T9zBg1A+4iCzFhcAHOT4JNp/rVtD8aSLP4volf4ybABkI63Ceug3+7zTwqn/54Iz7X2UEESnHTT6E3w7+a4FfAU+IiDeyHPCzjMvDHdzDHcDX+OE1clsRXCvsFdzUgFzK57oVLBGZAzyPm9PzOrBptMmhuWLhM0ki4onI+bjOYYCnVXWbfzlzwtxdIlKUUa4VN+luuA8kc7TrKVyfynLgIX+ezHC5OuAe/+q/q+oe//IjQDtuSPtZEWnJKFPvP+eh/vPm+gOez3UrSCJSgmvpLMNNfD1LVXuDrJMddo3tGyIyctixCDdxbq5//VXgD4fv9KfRP4U7reKLwJUi8h7u9IrhVtHPgDOAShGpUtVuVW0XkauAJ3AT+a4WkXdw/5/FuCbyLuDqjG11isg5uFbG6cB7IvK/uMNBAUpww/cX53rZj3yuWwG7GTjRv7wLeNTfyRWN8thELtZLsvAZ22gnjA7g5rX8BLdMwhOqmhjxmEuAF4HNuD3/Kr/Mc8B3VPWnIvIB0IKb4/J9AFX9vohsw412teHOnxoEfu1v78GRw+2q+p8ishy4CdcRvQT3wW4HXgK+pqr/fQB/gynL57oVqKqMy0eN89icTDL00unADvmMMQXM+nyMMYGw8DHGBMLCxxgTCAsfY0wgLHyMMYGw8DHGBMLCxxgTCAsfY0wgLHyMMYGw8DHGBMLCxxgTCAsfY0wgLHyMMYGw8DHGBMLCxxgTCAsfY0wgLHyMMYGw8DHGBOL/AXmv4BhtWrTVAAAAAElFTkSuQmCC\n",
-      "text/plain": [
-       "
"
-      ]
-     },
-     "metadata": {
-      "needs_background": "light"
-     },
-     "output_type": "display_data"
-    },
-    {
-     "data": {
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\n",
-      "text/plain": [
-       "
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-      ]
-     },
-     "metadata": {
-      "needs_background": "light"
-     },
-     "output_type": "display_data"
-    }
-   ],
+   "outputs": [],
    "source": [
     "\n",
     "for key, dd in stuff.items():\n",
@@ -3058,55 +2456,9 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 28,
+   "execution_count": null,
    "metadata": {},
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "U-test: U value 3874.0 p value 0.4358627795642821\n",
-      "U-test: U value 2021.0 p value 0.31540792775479376\n",
-      "U-test: U value 1064.0 p value 0.5373862857775564\n"
-     ]
-    },
-    {
-     "data": {
-      "image/png": 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\n",
-      "text/plain": [
-       "
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-     },
-     "metadata": {
-      "needs_background": "light"
-     },
-     "output_type": "display_data"
-    },
-    {
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\n",
-      "text/plain": [
-       "
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-     "metadata": {
-      "needs_background": "light"
-     },
-     "output_type": "display_data"
-    },
-    {
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\n",
-      "text/plain": [
-       "
"
-      ]
-     },
-     "metadata": {
-      "needs_background": "light"
-     },
-     "output_type": "display_data"
-    }
-   ],
+   "outputs": [],
    "source": [
     "\n",
     "for key, dd in stuff.items():\n",
@@ -3124,55 +2476,9 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 29,
+   "execution_count": null,
    "metadata": {},
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "U-test: U value 3642.0 p value 0.9495581436162017\n",
-      "U-test: U value 1859.0 p value 0.8701783404716995\n",
-      "U-test: U value 1017.0 p value 0.8159007523250839\n"
-     ]
-    },
-    {
-     "data": {
-      "image/png": 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\n",
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-     "metadata": {
-      "needs_background": "light"
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-     "output_type": "display_data"
-    },
-    {
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\n",
-      "text/plain": [
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-     "metadata": {
-      "needs_background": "light"
-     },
-     "output_type": "display_data"
-    },
-    {
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\n",
-      "text/plain": [
-       "
"
-      ]
-     },
-     "metadata": {
-      "needs_background": "light"
-     },
-     "output_type": "display_data"
-    }
-   ],
+   "outputs": [],
    "source": [
     "\n",
     "for key, dd in stuff.items():\n",
@@ -3190,55 +2496,9 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 30,
+   "execution_count": null,
    "metadata": {},
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "U-test: U value 4152.0 p value 0.10161200342185885\n",
-      "U-test: U value 1757.0 p value 0.718407479245363\n",
-      "U-test: U value 1300.0 p value 0.010937547927479946\n"
-     ]
-    },
-    {
-     "data": {
-      "image/png": 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\n",
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-     "metadata": {
-      "needs_background": "light"
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-     "output_type": "display_data"
-    },
-    {
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Tn0jblCWN/jskIyhNKW4scE/zQOx2ZPvDwCuAv5BS/lMnhmk0mv6ShKAEbdzbUkmnEOJalKAcBj7QiVEajab/JCEolfiaX+CeQnxddNlXCJFDrerYwHuklOe6M0+j0fSLJATlVHxducA9zdzJiRbG+xhwJfCZpEr2NRpNf0ii9P454BJgywL3NB/b2cJ4Pxpff0oI8VML3LdXCAHwUSnl3S2Mq9EkQjebMQ2jo028Q0MSgvIw8IO8UI/yIoQQFwLNgrYHWxjvu8CheR7LAc0Tsh8BHOBAy5ZqNF1SfeZeTn/hbiK/s93EY9f9MCu+/9cStmpwSEJQPgf8NnCbEEJIKeWsx98bX+9vZXewlPKt8z0mhNgC7I2/fKvebazpN9XH/xHv5D7CxlTbzzUMi8rj/8DyN34QIzOahW9dC4qUcpcQ4rPAjwN/J4T4ISnl8wBCiLuAD8W3fnz2c+M9OjYwKaU82q0tGk0vicIQ5+BTRG6NzIqNGJlcW8/3Tu4hdKq4R54jt+maHlmZLkn1Q3k/cFX8b4cQ4ilgObA5fvzDUsp753jeffE9fwG8KyFbNJqe4J3YTVA7SxQGGNli2/kQM1skcms0DjwxsoKSSPsCKeVpVA7lo6jE63bUqs/9wFuklL+TxDwaTZo4Bx4ncusY2UJHyVUjWyB06jgHnuyBdYNBYh3bpJRVVIuCu9t4zpY259hHh70uNZpucQ48SeTWMLOd7dMxskXC6lk1ThhimKPXgXX0fiKNpgdEUURj/+OETg2jU0Gx80RhQFA9g3fi+YQtHAy0oGg0LeCfOUQweZwocDGyCxWFz49hGBjZApFbw9n/eMIWDgZaUDSaFnAOPE7o1jDsPIbR+dvGzBYJnRqNERUUfdDXEHDWqfG/djxM1Xc6HsMyTN68+UquWHlBgpYtHRr7HiNyOs+fNDGyRcLJozj7HyeKopGrnNWCMgR8YffjfO75R6l6nQtKxrTYM3mK/3b7jydo2dLB2fcYoVvDGlvd1ThGNk8UeARTJ/FP7cNefVFCFg4GWlCGgIeP7+OcUyNrZciaVtvPj4DTjSp7pk5xrDbFuqI+iaQd/LNH8M8eJvKcjhOyTQzDxLALhG6Nxr7HtKBo+suR6iT7pk7RCDzWlyawOozfq55DzXf4zrG9/ODW0Syq6hWN/Y+9kD9JYKnXzBXjxOxjjF3/lgQsHBx0UnbAeejYHqqeS96yOxYTgJKdo+q5PHRsT4LWLQ2c/Y8TuTWMXDJ9Yo1sSSVm9z02csfIakEZcB48upuq51C229s3MptyJkfVc3jy1CGm3IW6dWpm09j7CGECCdkmKo/iEkwdxz9zcPEnDBFaUAaYs40qz545StV3KXUpKLZlkTEtqp7Lw9pLaRl/8jj+mWb+pLD4E1rgfB7FqdHY+0giYw4KWlAGmG/F3knOsrA7SMbOpmznqHgNHji60Iknmpk09j0a509yGAn8DZqcz6PseyyxMQcBLSgDzDePPE/FcyjbnVVmzmbMzlHxHB49cYBKF0vQSwln32Nx/qSU6LjG+QK30cqjaEEZUM42qjx1+nAi+ZMmWStDxrSY9ho8pL2UlmjsfyzR/EkTI1tQeZTJYyOVR9GCMqA0vZOslUkk3GlStnNU3AbfODKam9OSxJ86gX/qAJHXSCx/0kTlUfKEbn2kwh4tKAPK/Ud2Mu02EvNOmrwQ9uznnLPoqSZLGmffY4Re8vmTJma2SDRi+3q0oAwgx2pTPHNare6MJSwoTY+n4jk8oL2UBWnsf5yoi3YFi2HkSoRuFWffoz0ZPw20oAwgXz8kqXgOBcsm04NPxrFsnmm3wb8ent1PXDMTZ7/aYWwmVNA2G8MuEPku/rmj+OdGo6WyFpQBI4oivnZIMu01GMsm6500GbNzVH2Xp08f5Uh1sidzDDtB5QzeyT1EbqN3Hor5Qh5lVMIeLSgDxq7JE+ybOk3d9xLPnzTJmBYFy6biNfjaoR09mWPYcQ48ofrHZrI9yZ80MbKjVY+iBWXAuPfgDqY8lYw1u9i7sxjNsOe+gzsIo7Bn8wwrjf1PqIK2HoU7Tcys2nnsHNAeiiZh3MDn64ck024j8WTsbMp2DifwOVg5yzOnRyN+T5Jmh/uk609mY2SLRF4D79R+gsqZns7VD7SgDBAPH9/LqUaFMAop9vhkOdMwKNs5pt0GXz34bE/nGjZCp4p7bCdhfGRGLzFMC8PKErl1nANP9HSufqAFZYD46oHnmHIbjGXzfWkNOJ4tMOU2+OaR56l3eFbvKOIcfEotF5sWhmX3fD4jW4zDnuE/r0cLyoBwql7h0RP7mXYbjCe0d2cx8lYGw4BzTo1vHN7VlzmHAefAE4RevWerO7MxswUit05DeyiapLj3oPJOclaGrNWfRnqGYTCRLTDp1nXYMwPn4PfigrbehjtNlIdSxz26g9Ct92XOXqEFZQAIo5B/OfAsU26d8T69iJuMxZ3cnj59hP3Tp/s69yAShQHOoae7OiGwXYyMjWGaRG4d9/AzfZmzV2hBGQCePHWYg5WzOIHfs9qT+ciYFsVMlim3wb/s116Kd2wXYX2KiAh6nBifiapHqeMc/F7f5uwFWlAGgH858AxTbp2xbB4zhXNaJrJ5ptwG9x3agRv4fZ9/kHAOPknk1THtzg5E75RmJ/xhT8xqQUmZSafOt47uZsptMNHhEZfdUsxkCaOQE7VpHlzi7SGdg0+pCtk+hTtNjDgx6xx+higc3kJDLSgpc++hHUw6dTKGSa4PS5RzYRhGvIRc5yv7hzuG7xbn4Pf6Un8yG3WQuk9YOYN/en9f504SLSgpEkURX973NJNunYk+v4BnM57NM+05PH7yIIcr51K1JS2C6VP4Z4+ohkp9WrpvYhiGCnu8Os6hp/o6d5JoQUmRp04fZt/0aRq+17Odxa1imxbFjM202+DL+59O1Za0cA49ReTVMTK9aai0GOfDnkPD6yVqQUmRL+1/WiVj7XxPNwK2ynhck3LvweeWZHLWOfR0XNCWjrdo2kpQXO2haNrlrFPjgSMqGTueSycZO5tSnJw9vkSTs+6hp+OEbDqCYmRVyOOe2E04pO05taCkxH0Hn2PSVcnYfErJ2Nk0k7OTbp0v7VtaYU8UBjhHnlU7jO2UBMXKYJiW8lKODGdNkBaUFAijkC/vf4ZJp85ELt1k7GwmsnkqnsOTpw5yYHr4t9O3indiN2Gjos7I6WNB22wMu5lHGU5B14KSAk+eOsz+6TM4gcdYn1cTFiMTJ2en3MaSWkJ2ZoQ7/Sxom835sGdIS/C1oKTAl/c/zaSTXmXsYkzEbQ2WUnLWPfxsXCGbrsArD6WBowVF0wpnnRrfOrqbaa+Reu3JfDQrZ0/WK3xziRy14Rx+mtBN/kCvdjHsPJHvEEyewJ86kaotnaAFpc/ce+A5ptw6tmmR61ObgnaZmZxdCjUpoVPDO7lX1aCklJBtojrh54i8Ou4Q5lG0oPSRMAr5ygGVjB1Pad9OqzSTs0+dPjzyyVn36A6VPzEtjAEQ+fMVs4eHb6VHC0ofeSEZ6w9cMnY2M9sajHpy1j389EB4J01UxWxjKBOzWlD6yFf2p9umoF2abQ1GPTnrHH52IPInTUw7r0KeI88N3c5jLSh9YhDaFLTLzOTsQyNcOeseGiwPhUyOKAwJ6pN4p/albU1baEHpE187JJly021T0C5Loa1BMH0Kf/IYkef2fYfxfKidx3kib/jCHi0ofSCKIv7lwDMD0aagXWa2NThWm0rbnMRxDj+jzi/OZDHMwXk7NHcea0HRvISd506we/KkOq845TYF7WLH5yBPew3uPfBc2uYkjnv42XiH8WB4J02aeZRhK3DTgtIHvnrgWaZddV6xNQBtCtplPE7OfvXgsyN3DrJzOC65H5T8SYyRLRC6Ddxjuwg9J21zWmb4Xt1DhhP43H94J1NeY+BrT+ajZOdwA58j1UmePHU4bXMSIwrD8yX3g7LCcx4zA4Y6WsM7uiNta1pGC0qPeejYHk43qkQRFIYkGTsb0zAYy+aZipsvjQreqX0EtXNEYYCRGaxQ1DAMdaKgN1w7j7Wg9Bh1IqCqjE1zF2u3jNt5pt0GDxwdnXOQVUFbA6PPR2a0imHnCYeslYEWlB5yplHlsRMHqHgOY30+wCtpclYGwzCYdOo8MCIbBp1Dz6TaoW0xzq/0DFFLSC0oPeTrh3cy7TXI9vG84l5hGAbjtkrOfu2QTNucRHAPfi/VDm2LYdgFIt/FP3dsaHYea0HpIf96SDLtOgO/b6dVxrJ5qp7DE6cOcbpRSducrgidmurdOogJ2Ri18zg7VDuPtaD0iEOVs+w8d5ya7w59uNPENi2yVoaK1+Abh4c77HGa+RMzMxA7jOdDHVFaxzk4HGGPFpQe8fXDO6l4DoWMjTVAFZjdMmbnmHYdvn54uMMeFe7UBtY7aXL+EPVDw3GI+ui80geIKIr4xuFdIxXuNCnbeWq+y46zxzlanUzbnI5xDj6VypGj7WI2e8weeY5oCFbXtKD0gH3Tp9WJgIFH2U6vg3ovyJgmBcum6jlDu9oTheELh6IPaEL2PHHtUuhUcY8Mfg2QFpQe8MCR56l4DsWMPRAnAiZN2c6pPMqRXWmb0hHeyT0EtbOqoG3APUhV4BaHPQefTNucRUksGyWEKAK/CrwduAiYBh4FPiGl/HKHY74O+ABwIzAGHAG+CvxXKeXABvHfOrqbqjd64U6Tkp3jZKPCrnMnOFabYl1xPG2T2sI58MRAHJnRKka2QOjUaBx4kvGb07ZmYRL5+BRClICvAR8BtgLPAFXgDcCXhBAf6WDM3wTuBb4//tYzwHLgZ4AnhBBvScD0xDlUOcveqVPUfZfSiIU7TTKmSd7KUPUdHjy6O21z2sY58CSRW8Mc8PxJE5WYrSm7B7yDW1L++CeBG4AngG1SymullJuBdwI+cLcQ4o5WB4s9k4/GX/4KsFZKeS2wFvgEkAf+lxDiwoTsT4yHju6h6rkUrOxQ7ixulbKdo+I6Q9fJLYoiGvsfI3RrGNli2ua0hGHniUKfsHJm4Du4df2KF0JsA+4CQuAdUsqDzceklH8F/F785d1tDPsr8fVvpJR/IKUM4vEc4IPAcyhR+cnurE+ebx/fQ8VzKI1I7cl8lOwcNd/lmdNHmHTqaZvTMsG5owTnjhH57uAnZGMMw8DIFgndGs7+x9I2Z0GS+Aj9CcACHpJSztX3/9Px9WYhxKYWx/wW8A/AZ2Y/IKWMgGaVz+Y2be0pZ50az545Rs13R251Zza2aWGbFlXP5bsn9qVtTsuc907s/EB1aFsMM1tQYc/+x9M2ZUGS+I3eGF8fmOtBKeVhYH/85a2tDCil/C0p5Q9JKe+d/ZgQwgJeHn85UMsMjxzfR81zyZoWGdNK25yeU7JzVH2H7xzfl7YpLePsfzzOnwxHuNPEyJZUYnbfo+pA9wElCUG5OL4ulJ3bF18v7WaiOLz638AlwDHm8GDS5Lsn9lP1Rz/caVLKZKl6Lo+dOIAfBmmb0xKNfY8SOsOTP2liZPNEgUswdQL/9IG0zZmXJARlTXw9ucA9p+Prqk4mEEL8jhBiN7AT+BHgIeB2KeXphZ/ZP4Iw5LETB6h6LsXMaIc7TXJWhoiIs26N584cS9ucRfHPHcM/fZDIc4ZPUAxT7euJvZRBJQlBaf5lGgvc08zadfpXfB1qObpp70ZeWE4eCOS5Y5xz64RRSH6AN5sliWEYFDNZap7LYycH91OzSWPfI0OZP2li5uLl4xEXlHZ83U6Dv7ejVnUuAX4LtXz8n4UQ93Q4XuI8duIgtdg7GYZiqaQoZrLUfJdHh0FQ9j5C5NQwc8PlnTRReZSq+jkGNI+ShKA0G2MsVBbaXJ+rdTKBlHKvlNKRUj4vpfxN4Kfjh34xzqukzuOnDlDzXYojvrozm2LGpu577Dp3gml3ISc1XaIoorH3u4RuFSNXStucjlB5FA9/6gTeycGs/0lCUE7F15UL3NPMnSTSdkpK+ZeoMnwLeHUSY3ZDzXPZceY4dX/p5E+aZOLl47rv8r1Th9I2Z1780wcIzh5V9SdDUiE7G8MwVdWsU6Ox++G0zZmTJASluQVyywL3NB/budhgQghDCHGBEOJmIcRC9l1Ua50AACAASURBVDWXotctamGPefrMEeqBi2WY2EtguXg2hdhLeXyABaWx5+E4f1LAGOIKZjNXInSrNPZ8N21T5iSJ32xTKm+c68G4PL5Z0PZgC+NdCBxG1bVct8B9zaK21A+K+d6pQ9R8j0JmOI/J6JZmHuWp06n/Kealsee7hE4Vc0jDnSZGrkTkVGnsf4wo8NM25yUkISifi6+3CSHEHI+/N77eL6Xct9hgcel+82Sjn5vrHiHE24ALABe1+zhVnjp9mLrvUlhi4U6TgmXjBD77p09z1ukoTdZTosCnsfe7RE5laPMnTYxMjiiKCGvncAawG37XgiKl3AV8FpXP+DshRLPQDSHEXcCH4i8/Pvu5QohtQojLhBDrZz30sfj6LiHEh4UQ9oznvA34s/jL35dSHu/2Z+iGuu/y/LmTNJawh2KZKtRr+B7PnD6StjkvwT38DEH1HFEUDXz/k8UwDEOFPU6Vxu5vp23OS0gqmHw/an/N5cAOIcTjQoh9wF+heq58eK4yeuA+VA7md2d+U0r5N6jlYVBCdFII8YgQ4gjwt0AZ+B+0t+GwJ+w4e5x64GEu0fxJk2Ye5dkzR9M25SXUn3+IyKlgZosjsaRv5EpEjSr150dUUOKK1RtRLQd2AttRqz73A2+RUv5OB2P+JnA78EVUaHMNygv6IvBGKeXPSilTbw7xzJkjS9o7aVKwbBqBxzNnBs9Daez+NmGjipEvp21KIjQTs+6RZwmq59I250UkVtIppayiPIa723jOlkUe/zrw9c6t6j3PnTlKPVD9T5Yy+YzNifo0uydV+JcfEIENapM4h58hdKvYy1JfEEwEw7IxrKwqw9/zMKWr7kzbpPMM7/rZABBGITvOHqfh++QzS6Pcfj4yholhGNQDj+cnB+eUu8bub6vNgFYWY0gPq58LI18mcirUn38obVNehBaULjhYOcu01yCIQnLm0hYUwzBU2ON77Dg7OBsF67seVKs7IxLuNDFzJcJGhcbzDw5UW0gtKF2w8+xx5d7HB4kvdfIZJSjy7GB4KFEYxvmTytDXn8zGyBaJAh9/8gTu0R2LP6FPaEHpAnnuBI3AIz9CrnQ35KwMjcBn57lUV/LP4x59Dn/yOFHgD127gsVoLh9HTpX6rm+lbc55tKB0wa5zx3ECn9wSaVewGHkrgxv6HK9NDUSBW33nA2q5OFcaSQ/SyJdV2KMFZfjxwoC9U6fikEd7KMD5Whwn8Hn+XPphT33ntwgbo5c/aWLmyoRuFefQMwSVM2mbA2hB6ZgD02eo+x6gzqnRKPJxGf7zkws18Os9/tRJ3CPPEro1zNxoCophZTAyOcIBCnv0O6FDdp07gRP45C17JN3pTslZGZzAS91Daez6FqFTxcjkMEY4JDWby8c75+wR33e0oHTInqlTNAJP509m0UzM7pk6tfjNPaS285tqdSc/lqodvcbIlQkb09R3f5vId9M2RwtKp+yePKETsnOQM1Vi9lhtMrUObqHn0Nj9MNEI50+aGHaeKIKwepbGvvQPAdOC0gFhFLJ36jRO4JPVgvIiLNMkY1i4QcC+qXQOJWjs+Q5hbRIMtd1/lDEMAzMfeyk7v5m2OVpQOuFYbZqq5xBGEdklvMN4PnKWWunZm1LYU9/5AKFTwciPLYn8lhkvH9flN1JvXq0FpQP2Tp5U3olpLYkXbLuoxGw6eZQoDKnL+wkb0yO7ujMbI1ci8h28M4fwjqd7mKYWlA7YO63DnYXIxnmUNEIe9+hz+OeOEfkexpAel9EuhmGqqtlGhdqOr6dqixaUDtg/dQZXJ2TnpemhHKicIYz6u3GtvuMbhE4FM18e6mbU7WLkx1QeZcc3UrVj6fzGE2Tf9CncMND5k3mwTYswiqh6Dsdq032du7bj60T1aYwlEu40UVWzNdwjO/DPpbfbWwtKm7iBz5HqpF4yXgDDMMiaaqXnwHT/wh7v9EG8488TenXMEV8uno1hZTDsPKFTob4zPS9FC0qbHKqcww18DMBaQi51u2TjsGf/dP/2mKhkbAUjW8RYgt6jGYc9tR33p2dDajMPKQcqZ3CDgKzugbIgWdPCDX0O9FFQaju+oVZ3lph30sTMjxE6FRp7HyWoT6VjQyqzDjEHp8/ghj7ZJd6hbTGyViYOefojKEH1LM6BJ+LDvEa73H4+jEwWw7QJG9OptTTQgtIm+6fVCk/WWnoudTs0PZRDlbN9Wempx3t3jEwWY0AaZKeBmS8TpRj2aEFpk0OVs3qFpwXUSk9IzXc5Wa/0fL7ajvuXdLjT5Pzy8fMPpbJZUAtKGwRhyJHqudhD0SHPQhiGgW2qsOdQ5WxP5wrdRrwZcBpjxHcXL8aLNgvufaTv82tBaYPjtSkagU+EOjZCszAq7Ak4MN1bQWnseTjeDGiO/GbAxZi5WTCNsEe/K9rgUPUcXhBg6z08LWFbFl7oc7jHp9vVpVrdMfJl/XfhheXj+s5v9v2IDS0obaDyJ77On7RIs7jtSA8FJQrD8wnZUW+m1CpGrkjke/jnjvb9iA0tKG1wuHIONwiw9QpPS9hmBi8MONjDkMc9/DT+5AmiwBu5ozI65YXNgtPU+xz2aEFpgyPVc3h6hadlsqaFFwacalRwAr8nc9Rk0zvR4c5M1GpPhfqu/vaa1YLSBkeqk3hhgK2L2lrCNAwMwA8DjlYnezJHXX6DyFk6vU9axcyV4s2Csq+bBbWgtIgb+JysT8eCoj2UVlBLx8pL6UUexT97RG0GdOsj3zu2XV60WbCPXooWlBY5XpvCD8N4U6B2rVtFrfQEHKslv7ek3jwqwy4syc2Ai2HmyrGgPNi/Ofs205BztDZ13jvRsXrrND2UXoQ8SlAqS746dj6MfJmoUaGx5zt9q5rVgtIix2NByehPwrZoCkrSHkrkuzT2PkLUUGcXa16KkcmBYRDWp2jse7Qvc2pBaZHj5z0U/StrB9tQgnI8YUFp7H+csD4FhgFLvDp2PgzDwMiVVEuD3Q/3ZU797miRY7UpfJ2QbZuMaeGHIcdrU4ke8dDY/bA6KiNX0iHoApi5MlGjSv35h/ozX19mGQHUCk+oQ542yZgmQRjihD6Tbj2xcRu7v03kVPVy8SIYuRKhV8c7vht/qvfnTWtBaZGT9Qp+FJDRIU9bmIaBZZr4YZhYG4Ogehb32E61XKyrYxfEMC2MTI7QrfVl97F+d7SAG/icdWr4YYhtaA+lXWzTxA8DTtaT6YDf2PcokVvHsLIYuo3Eohi5EpFbw+lDYlYLSguccWrnu46ZOl5vG8tQeZTTjWoi4zl7HyV0q0vmIK9uMbNFQqeqPZRB4XS9gh+GZAxTJwA7IBN7KKcSCnmcA08QOXVMHe60hJEtEnkO/pnDPc+jaEFpgWa4Y+n8SUdkDBM/Cjnr1LoeK6hP4Z5QZ+/o/ElrGKaJYecIvTrOgSd6Opd+h7TAWaeGH4W6S1uHWPFKTxKC4h56Os6f2Dp/0gZGtqDyKAee7Ok8+h3SAmcaVYJIeyid0vRQzjjd51Ccw08Teg0Mu5CAZUsH0y4QuXXcw8/2dp6ejj4iTLkNgjDUJwV2iGWYBFHIlNPoeiz38HPKQ7HzCVi2dDCyBUKvgXtsJ5Hv9Wwe/Q5pgXNuXXkoWlA6ohnyTLr1rqtl3aPPEXkNjKwWlLawbCAidKp4p/b2bBr9DmmBabcRC4pe4ekEyzAJowgvDGgEnX86BtVzBNOniHwXI6MFpR0Mw8DI5Il8B/f48z2bRwtKC1S8BmEUaQ+lQwzUHr4wCql4TsfjeCd3KzGxbAydz2obw84ReQ7eid09m0P/VVpg2nUIolAXtXWIYRiYhkkQRUy7XQjKiT1EnoNh693FnWBkckS+g3diT8/m0ILSAjXfIYwiLShdYBoGYRRR8zsXFP/MIaLABSuboGVLByOTJfJd/LOHejaHFpRFCKOQRuDHgqJ/XZ1iYhBFEfUuVhi8s4fi/IkWlE4wLJsoUOf19OoAMP0OWQQnFpNIeyhdoTwUdXh6pwRnj6jzdyw7QcuWEJYNYUDk1gkqp3oyhRaURWgE/vmlTi0nnWMYBiF0dT5PUD0Nga8rZDvEMAywMkShT1A53ZM59F9mEZzAJyRSy27aQ+mYZsjTqaBEgU9QnSQKfUjwXKTT1d4VeSXFylJyHplhZiAICLWgpIMXeyhaSrpDeSidC0pYn4QwgCiCBLvmveIPertZLgn2feT6xMYyTEt5KNUziY05Ex3yLIIXhkSgvZMuMQAiCKLOkoGhUyWKAtAtJLrDtCAKiRJsxzkT7aEsgnoDJO+hOJPJdC/rJbmJscTGMjCIiPA7XF2I3HrsnejPwK4wTKIoJExgo+ZcaEFZhCAKUTnZZCXla+/8cKLj9YI3ffGPkhvMgAjOd75rl8hrQBRi6OCzOwxDeShdVCwvhBaURQgTPPpBo0SlKxIOdx795ZclOt7Q0CNd1oLSIvpzsTtUDiVK9GyeJEhyBUWjk7KaPqGixi6W3ptVygMmSENHM3zv0flSiXkoQogi8KvA24GLgGngUeATUsovdzjmK4FfAl4NrAPqwLPA3wCfllL2/ATo5g7jpF/Gr/3L3054xMHHQNWjdPTcXAlMi6jDHIwmJgoxDLNnDb4TERQhRAm4D7gB8ICngZXAG4A3CCHullJ+tM0xfwn4rygvqg48B6wCXhX/+3EhxBuklMkemjsLw+CFNc8ESXIFZajo0EEx82UMw4QwVHVBeum4M6IATFMJdA9IKuT5JEpMngC2SSmvlVJuBt4J+MDdQog7Wh1MCHEzcE9s338Clkspr5FSbgBeCxyJ5/vvCdk/LxnDipc8Nd2gigONjs+GNnPlOOyJdNjTBVEYgGFh5nvzgda1oAghtgF3ASHwDinlweZjUsq/An4v/vLuNob9FdRn2T9KKT8kpTy/xiWl/FfgJ+Mv3y6E2NiF+Ytim8pJH7Rk4rDRDN07PRvazBWVl2JloIuub0ueeC9UZnxNT4ZPwkP5CcACHpJSztVS+9Px9WYhxKYWx7w9vv7NPI/fh8rRAFzX4pgdYVsZDEN7KN1y3kPpogWENbYaTLW5TdM+URQRhT6GZWONDa6g3BhfH5jrQSnlYWB//OWtiw0mhDCBHwV+BvjmPLfNDKB7ethwzrTOb2zTXkrnRESYBuQznS/TZibWqZ4eXbRAWNKEPqB2HFtjq3oyRRJJ2Yvj60KNKvcBm4FLFxtMShkCX1nktjcCzSDwmcXG7IacZZ9PAEboepROCSNVfp/tovWAvfoi1RdVC0pHNJtT2Ss39awFRBIeStN3OrnAPc290l3LohCijFr9AXhESvlct2MuRM7KxE2WDe2hdEGE6smb7+KFnFm1+XxfVE37RJ6Dkclhr7qoZ3MkISjNBe2FTnFqbm3savFbCJEF/g8ggAD4QDfjtYJlmmStjOo4pjMpHdPsyVvson1jdu3Fcef2hhb3Doj8Boadw16ztWdzJCEoQRv3dvwqEEIUgC8Ab4q/9atSym91Ol47FDNZTIyON7ZpXhCUbnIo9jqhjiCNIuii89tSJXLrmNkC2Q1X9GyOJASlEl8XOnmpeRBtR6dlCyHWAF8D3hx/62NSyv+6wFMSpZjJYhoGgf5U7JggbvJd7uIIUdPOkV13KWa2QOT1pp/HqBKFgcqh2HlyF17Zs3mSEJRmt9uVC9zTzJ2caHdwIcR24GFUdWwEfFBK+ZF2x+mGsWwOMz79TtM+0Ywm32NdnqmT23i1OqfX6eizackSuTUMu0Bm5Sas0vKezZOEoDSTolsWuKf52M52BhZC3AY8GD+/AbxNSnlPW9YlQNnOYxlGx93GljpBXCpvYlCyuzsCI7/1esxcicjtTYOgUSV0qpj5IoWtr+zpPEkIysPx9ca5HhRCXAg0C9oebHVQIcStwJeAZahVotdKKT/fhZ0dM57NY5naQ+mU5kHzZTvX9dlG+S2vwMiViAJfLx+3QeRUMbNl8kMgKJ+Lr7cJIcQcj783vt4vpdzXyoBCiIuAL6JyL4eAm6WUD3VraKdMZAtYhknQo8ORRp3mQfMTucLiNy+CmS+T23g1Zq5E6FQWf4KGyHeJAh8jVyJ3UU8Ly7sXFCnlLuCzqIrVvxNCNAvdEELcBXwo/vLjs58rhNgmhLhMCLF+1kN/Ckyglpu/T0opu7WzGyZySlB8HfJ0RBCGWKbJeLZ7QQEoXnYrZmGMsDH4fXkHgbAxjZkfI7/1OqzCeE/nSqpc7v3AVfG/HUKIp4DlqOpYgA9LKe+d43n3xff8BfAuACHEdagdxaBWhT41t+Nznt/utN9KqyzPFbFMk8DXgtIJzZBnRUJb5gvbb8f8yj3qSE198NeihI1prNIKipfd1vO5EvlLSClPCyFuRO0SfhuwHdUX5X7gj6SUf9fGcDP3+6wEbl7k/rXt2NoJK3IlMjrk6Rg/CsmYJsvzyTT1sZdvIHvBdvyzR+I3S+9WLYadyHeJPAczP0ZhWAQFQEpZRbUouLuN52yZ43v/BfgvSdmVBCvyJTKmDnk6JQhDcpbNynxyTX1KV7+Jxt5HCKpntKAsQFifwiyMkd/2SjLjq3s+n+4p2wKrC2UV8oShXunpAD9UHsqqfDmxMUtX3YlZGCfyHL3aMw9RFBHWJ7EKE5SufvPiT0gALSgtULZz5C0byzTxw3Z2GmgAvCggY5qJeijW2CoKl9yEVRwnqJ1LbNxRInJrEEWYY6sobr998SckgBaUFjAMgzWFMRX26DxKW0RRFHsoFmuLya4wlF/xbzGLywlr53Tz6jkIa+cwS8soX/0mzFxvmlLPRgtKi6wpjmGbFl6kPZR2aO5/sk2LVYXkQh6AwqW3kFm5EcPKEtX1EvJMosBXCevCMsrX/XDf5tWC0iLriuNKUHTI0xZeGGCbFivzpY4bVM+HYVqUr/0hrNJyguoZ3dJgBmHtLGZ+jNzml5Fdt2hfs8TQgtIi60vLlKAEWlDaoSkoG0rLejL+2HU/glVeCYGvdyDHRFFIUD2LVVrB2Kve3te5taC0yIbShPZQOsALfWzT4oIeCYpVXkHpmjdhlpYTVs70ZI5hI6xPqVaPqzZTvPx1fZ1bC0qLbCgtI2tlcMNAu9Zt4AYBWctiQ7k3ggIwduOPY5WWEzrVJb+EHEURYeU0VnklYzf8KEaPjhydDy0oLbK+NEHWtDBAF7i1gRsGZM0Mm8orejZHds02CpfdilVaRlA5vfgTRpioMQ0YZJatp3zdW/o+vxaUFsmYFheWlysvRbcfbIkoivBCn6xlceFYb6tZJ179LszSCsL6FNESPQgsiiKCpnfyyrf2bal4JlpQ2mDL+EpycdijWRw3DM73QVmT8JLxbHIbr6aw9ZWq0G2JeimRU4UwwBpfw9gN/U3GNtGC0gZbxlaSNTM42kNpCTfwyVoZtoyv6rqxUitM3PrTmOVVhLXJJeelRFFEMH0Sa2wVY698a2r7m7SgtMHWidXkrAzOEnuxdooT+OSsDFvHe3NK3WxyF11H/qLrMAtLz0uZ6Z2M33RXanZoQWmDS2JBccNAH6nRAo3AI2/ZXLKsN+fozsYwDCZuew/W2NLyUl7knVz/VqweJsAXQwtKGyzPl1hdGCNrZmjosGdBoig676FcPNEfQQHIX3R9nEuZIJg+tfgTRoCoUYEoxJpYx/gt70zVFi0obXLp8rXkLZ1HWQw3DDAMg7KdY/NY/z4xDcNg4rXvxSyvVCs+I16XMtM7GX/Vj6XeG0YLSptsX76WfMam7i8Nd7pTmuHOpcvWYpn9fZnlN7+c4qWvVnUpI+6lRPUpADLLLmDspnekbI0WlLa5fMV68hmbRuDpitkFaPgehYzN9hWz+4/3h4nX/RxWeRVhY5rIG83D1c97J+OrGb/5J3regLoVtKC0ycUTayhn1Ol3el/P/NRjQblyxQWpzJ+7YDvFK1+PVV5BMN32gZVDQVg7B1YGe+Wm1OpOZqMFpU2yVobLlq+jYOmwZz68MCCIQgpWlstT8lAAlt3+Xqyx1URundAdrZ3IURgSTJ8iM7aG8Ve/O5Wq2LnQgtIBV63aQCGTpTbiCb9Oqfse+YzNxctWU+zy6NFusFdvofzyH8QcW0UwdWKkQtSwdhbTzmGv3cZYHxsoLYYWlA64dvVGirYSlFF6kSZFzXcpZrK8fPWmxW/uMRO3vYfM+BoIPFX8NQJEYUBQOYU1voaJ238WI5OeaM9GC0oHXLpsLRPZAqZh6OXjWURRdF5Qrl29MW1zyEysZeyVb8MaW0UwfXIkPgDCymnMXJnsBdspXfXGtM15EVpQOiBjWrxs9UaKdo6qDntehBP6GMB4tsBly9elbQ4A47e8C2vZeoiieHv/8BIFvurGNraaZXf8PEafl+QXY7CsGSKuX7OZUiZLzR/NJclOqXouJTvHtas3kh2QI0Kt0jLGb7oLa3z10HspQeUUZmGc/EWvoHDpq9M25yVoQemQ69duppjJ4gSBPlpjBlXPoZjJcv3aLWmb8iLGb3wHmRUXgmES1ifTNqcjIt8lrE1ija1i2eveh2EYaZv0ErSgdMjKfBmxfC3FjE11RAun2sUPA9wwoGTnuGHABMXMFZl49buxxtcQTp8cynN8gulTWKVlFC69hfyWV6RtzpxoQemCG9dtpWTnqOiwB4BK7J1cvmIdyxM8JTApxq7/EexVWzCsLGF1uE4bjDxHnbNTXsmy1/5c2ubMixaULrhp/TZKdo667xEM4Sde0lQ8l7Kd48Z129I2ZU6MTJaJW/+dyqVUThENUagaTJ/EKi+nePkd5DZcnrY586IFpQs2ja1g6/gqChmbqre0V3v8MKQReJTsHLdccHHa5sxL+eU/iL1mG6adJ6ydTduclgi9BqFTxSqtZOL2n0nbnAXRgtIlr77gEsp2jmmvkbYpqdIMd7YvX8e6hM8wThLDyjBx609jja0mqJweCi8lnD6FVV5B8ao7ya4dXLEGLShd85oLLqbcDHuG4MXZKypeg7EB906alK55M/a6SzDtwsB7KaHXIHSrWOWVTNz602mbsyhaULpk49gKLlmmVnsqS3S1xwsDGoFPOZvntg39O0e3UwzTYuI1P6WqZwfcSwmnT2GVVlC66k6ya7ambc6iaEFJgNs2XMpYNs/UEg17pt0GZTvH1Ss3sKrHx2UkRenqN2GvHexcSuQ5ce5kBeOv+am0zWkJLSgJcNuGSynbedzAX3KHqUdRxLTXYCyb57UXirTNaRnDtJi45V3KS6meGci6lKByGqu0nOIVd5BdM5grZ7PRgpIAqwplrl29kbKdW3JeihP4BFHEsmyBV19wSdrmtEXpmjeTWbkJw7IJa1Npm/MiIt8lbEwp7+SWn0zbnJbRgpIQr9u4nfFsgSm3MdR7Rdplymswns1z0/ptqfY+6QQjk2X8xneoVpHV0wP1dwuqZ7CKy8hfcuNA153MRgtKQty0bivL80UMoL5EzoMJo4hpVwnK6zdtT9ucjii/4t+SmVgLQORUUrZGEYUBYW0Ss7SC8ZvTPRajXbSgJEQ+Y3PbhksZz+aZcpdG2FP1HLJWhgtKy3jZqgvTNqcjzFyR8nU/jFVeSVA5k7Y5AITVs5i5ErkNl5Pf+sq0zWkLLSgJ8vqNlzOWzVPxnCVRij8Veyd3bNzel7OLe8XYDT+KWVoOvkOY8odBFEUEtbNY5RWM3fiOgdxRvBDD+yoYQC5bvpZtE6spZGym3dGuSfHCgHrgMZ7N84ZNwxPjz0VmfA2lK16PWVxGWEvXS4ka0xhmhszyDZSufH2qtnSCFpQEMQyDOzddwUS2wNSIdVmfzZRbZ8zOce3qTQNdat8qYze8DbO0XJ02mOLxKEH1LFZpOeVX/JuB6hXbKlpQEuZ1Gy9jIlfAj0IaI3rMRhRFTLkNJnIF7tx0RdrmJEL2wqvIbbgCM1dW592kQOQ5RL6DWVxG+bq3pGJDt2hBSZjxbJ5b1l880snZqu9iGiZrC+PcuH7wy8FbwTAMytf9cBz2TKayhBzUzmEVximK16hO/UOIFpQe8MbNVzCeLTDtNQhHMDk75daZyBZ43cbLsE0rbXMSo3TVnVjllRAFRF5/Q9YoCgnrk5jFZZSu/aG+zp0kWlB6wNUrN7BlbCX5jM30iG0Y9MKAmu8xls3zxs2jEe40MXMlSle+/ryX0k+iRgXDssmsuJDCJTf1de4k0YLSAwzDOO+lTDqjlZydijcCvmzVhVxYXp62OYlTetn3YRYmVHK2j95lWJ/CLE5QuvpNGEPs9WlB6RF3bLyMiWycnB2RylmVjFXhzqh5J01ym15OZsUGjEyWqNGfytkoDAidClZ+nNLVb+rLnL1CC0qPWJYrcssF20YqOVuLk7FrimPcvH44dr+2i2GalK56I2ZReSn9IGxMY2aLZNeLge/IthhaUHrImzZfqZKz7mgkZydj7+T1G7cPzCFevaB4xR2Y+TFCp9KX5ktRfRqzME7xijt6Plev0YLSQ65euYHNYytGIjnrn0/G5rhzyCtjFyO7/jLsFRsxMvmeH7AehQGhW8XMlyle/tqeztUPtKD0EMMweNPmK0Yi7JmMk7HXrNrIxrEVaZvTUwzDoLj9dszCGGGPz0KOnCqmXcBesw179UU9nasfaEHpMc0+KV4Y4AR+2uZ0xMxk7Kh7J00K4tWqatap9LTILWxUMPJlCuI1PZujn2hB6THLc0VuWreNMTs/tPt7ar6LYRisKpSHoqt9EuQ2XoNZWoZhGEQ96sIXRRGhU8HMlYe69mQmWlD6wBs3X85EToU94QB1BWuVKbfBRLbAay8U5EY4GTsTI2NT2HoDRq7cszxK5DkYhoFZWkZu4zU9maPfaEHpAy9fvZENpeVkrczQHazuhyFV32Usm18y4U6T/NbrMHMlQrdHguJWMbIl8ltegTEiQq0FpQ+YhsnrN73Qc3aYmPYalOITAbdOrE7bnL6Sv+h6zGyRyK33pGo2cmqYuSL5ioZOgAAAGNRJREFUi65LfOy00ILSJ+7YuJ0xO0c98PBS7LfRDs02BePZAq9fYt4JQGbVFqzx1RiWTZTwB0EURYRuDSNbJL/lFYmOnSZaUPrEuuI4167ZxJidGxovRR2RETKRKwzFiYBJYxgGuY1XY2QLye8+9l0Mw8QsjGMPeXXsTBIL3IQQReBXgbcDFwHTwKPAJ6SUX05ojr+Jx79ESvl8EmP2kzs2bueho3s4VptiRa448P1Cm0dk3LJ+G2U7l7Y5qZDbeBXmY39P2Eg2jxK6dYxsgdyGy4d6M+BsEvFQhBAl4GvAR4CtwDNAFXgD8CUhxEcSmOO9KDEZWm5at5UV+RKGMfhHbcw8IuOOIT0iIwmyG67EsJP3UCKvjpHNk91wZaLjpk1SIc8ngRuAJ4BtUsprpZSbgXcCPnC3EKLjjQpCiA8An0rE0hTJZ2xec8HFjNl5pgc87Kn5Llkrw/ri8B6RkQTZdZdiZHJEYZBor9nIa2DYebLrh+f41lboWlCEENuAu4AQeIeU8mDzMSnlXwG/F395dwdjrxdCfB64Bxjs+KBF7ti4nfH4qI1BrklRTajVecXDfERGt5j5ctzOIJdYgVsURap3bEYLylz8BGABD0kpn53j8U/H15uFEJtaHVQI8W+BXcBbgLPAz3dr6CBw+Yr1bCwPdk1KEIbnNwK+duNoveA7Ibv2klhQEvp7BR6GYWLkSmSWj5b3l4Sg3BhfH5jrQSnlYWB//OWtbYx7DVAE/hq4HPhSpwYOEoZh8NoLL1MbBgf0YPVpz6GYySKWr2Pz2Mq0zUkde9VFGHaWyHcTGS/yHYxMDnvVJgxztLy/JH6a5prX7gXu2Rdf21l7/AZwjZTyLinlsU4MG1Ruv1BQtnPUfQ+/D/022mXaazCWzXP7Bu2dAGRWbVYeip+MhxL5LmSy2Ku2JDLeIJHEsnGz3//JBe45HV9XtTqolPJrHVs04GwoL+Oy5es4Xpum4jVYliumbdJ5vCDADXzG7By3brgkbXMGAnvlJgwrC0FSHoqLkcmSWdlyBmBoSMJDab4bFvLfm2tug/POSZnbNgjGsrmBa7w07TUo2TletnojK/KltM0ZCDLLN2BkbKLAT6SVQRR4qsP9sgsSsG6wSEJQ2llLG9xljT7zmg0XU7bzOIE/UKX4057DmJ1fkpWx82GWlmPYeVWAlkT9UOBhZGwyy7WgzEWzNXh+gXsK8bWWwHwjwcp8matXbqBs56gMiJfiBD5+FDKWzXPTiDah7gTDMMhMrAPLJupSUKIoUh6KaWNNrEvIwsEhCUE5FV8XWg5o5k5OJDDfyPCaDZdQtnMDU+RW8RzG7BzXr928ZEvt58MaW6VaDHTbdS8KIYrAtMiMjd7u7SQE5bn4umWBe5qP7UxgvpHh5niPjBeqRGiaRFHEtKf6xr76Ap2MnY1VXgVmhijs8u8U+BhWBrMwjpHJJmPcAJGEoDwcX2+c60EhxIVAM539YALzjQzLckVevnojpQEIe9wwIIwiJrIFXrV2+JslJ41VXolhWV2X30ehD2YGqzyajb6TEJTPxdfbhBBzFS68N77eL6Xcl8B8I8XN6y8eiDxKxXMo2zmuXbOJoj16n5zdYhYnwMhAtx5KGGCYFmZhIhnDBoyuBUVKuQv4LKr8/u+EEOebOwgh7gI+FH/58dnPFUJsE0JcJoRY360dw8pN67eeD3u8IL3Vnkoc7tyyfnR6cySJWZhQqzxdeygBmJYSqBEkqX4o7weuiv/tEEI8BSwHNsePf1hKee8cz7svvucvgHclZMtQsSxX5OpVF3KsNkXFd1hu9b9Uxw18/DBkzM5zwzod7syFWRgD0+z+JMEoVB5KfjwZwwaMRDYSSClPo3IoH0UlXrejVn3uB94ipfydJOYZVZrJ2bTCnma487LVG/XqzjyYuTKGYalVmm4IAzBMzNxoFg0m1rFNSllFtSi4u43nbGnj3n2MSAuD2dy0fivFTJZjtSn8MCDT5w5eFc9hZb40sgegJ4GRLYJpdi0oURSqVZ4RFZTR2uo4pKzMl9m+Yh3FTJaql8x+kVbxwgAvDCjZOR3uLICZK4KRTMiDYWJkF6oDHV60oAwIN61LJ+ypeg5FO8sVKy9g+QBtUhw0jEwODKP7kCeKVC+UzGiGllpQBoQb12+lZGepBx5BD86AmY+K51LO5Lhx3da+zTmMGJkchmHS9Xa0KATDwLC1h6LpIReWl7NpbAV5K0OtT2FPEIY0Ao+ineVVWlAWRFW1GhBF3e04jiLAGMkqWdCCMlC8at1WSnaOakKdwRaj5rvkLZuLxldxQWk06yKSwrBsFfJ0SUSkPBTLTsCqwUMLygDxqrUXKUHxnET6bixGxXcoae+kNazMC4LSlYcCYIzMWcaz0YIyQGxfsY6V+RKWafb83J4oiqh5LiU7xyvXbunpXKPAiw/j6kbslYeCMTqHe81EC8oAYRom163ZTCmT63kepR54WKbJqnyZy5av7elcI8F5Qeky7IkiNcKINaduMpo/1RBzw9qLKNlZqgk1RJ6PqudSyuS4bu3mJX3uTss0f0cG3YU88SCjdPzoTPQracC4ds0mSpksfhj2dLNgLc6f3KDDnZZ44RzqpIq1R7LoWwvKoFG2c1yxcoOqmu2Rl+IFAX4YUspkefnq0eu8/v+3d+ZRklX1Hf+896qqN3qd7p4ZmBkGhpnfzDBhXwUCKkHCBHNCDpwgw6IwmCiBJJ4TjBLEKCGcRAkgccMTDOghSFAW0aMxYBajMQMScfnBIDBsBocgAtNDdy35496aKZrq7lpuVVdX/T7nVL969d699auuet937+/e+/s1jCDJ7QtOS9q0Vdien2qBc8Tivelt4PDxq1mXyGt/H9PWqJSioAQYgQsiTq2HCUoLctj4SjdrNjvVkPzHO7KT9Ka7OGzcWifVEIUQgeLXaYJiNIu9+0dY3DNAOk6YyIYdPs4XCuzITtGXznDY+MqgdRuGCUoLEkURh46voC+dYUdgP8rO7BTpOGGsp599BixvcXWYQ3YuTFBalEPHV9CbyrAjsB9lR3aS3lSGQ8dWhGnCdxJRFEwLojYVFROUFuWg0eX0pjJM5fNkA2YW3JGdpC+d4RDznxgNwASlRenPdCPDi+lNpYON9mTzeSbzObpTaQ4aXRakzo4iinArjuuppFBSV/thgtLCHDy2gp5UJphjdiI7SU8qzX6D4wxZMKX5xQTFaDYHjy6nN+38KCFWHxf9JwePLQ9gXQcSxd7zUed3Ee3603aYoLQwa0eWMOAje03Wmw+mUGBHdpKeVIaDRk1QaiEKNrs1shaK0XzSccL+i/YMMtoz5VON9qUy7D/SsXnV6qPoQ6kH39K0xYHGvHDQ6DJ6Umkm6hSUiewUPakM60aW0p1qz2hhDSdOgq02xgTFmA8OGF1Gr3fM1uNHmcg5/8kBo3sFtK6ziOKY+n0ftjjQmEdWDYzRn+kmjiJeqzFRd8FPt+9JpTlgkQlKzcQuDGShDqdsoRikOrYQkMY8kMQxG0b2rGv4eCqfo4ALjbB2eElYAzsIF1g6qr/LY0GqjfnkgNG9vB+lNkGZyE7Rk6RZM7yYTJsGR24GUTFQdZ1pNCIiF/S6DTFBWQCs9y2Unbna/CgTOdfd2TCyZwOs6xyiJONHeuoRFJ/oy/LyGPPF6qHxXYGQpmqYjzLh/ScbFpmg1EUq41oXNWZ23HUziGLLHGjMH+k4QYYW052kq06vkc3nyBXy9CRp1g3b/JN6iNPd9XV5CrvX8USJtVCMeWT9yFJ6Uml2VulHmchO0Z2kWTk4Sm+6PX/EzSJKd0MUU6g193Qh74aLo4ioTUNvmqAsENaPLK2phbIzN0V3KsV6a53UTZTpcYJQh6BEUUSc7mnbWDQmKAsEGV5CVypFNp8nl6/8B70zl6UnydhwcQDiTK+b3FZjl6fgWyjt2joBE5QFw0Cmm2V9w3QlKXZW2ErJFwq8lsvSnUqxzgSlbqKuPtdCqXWhZj4PcUzcvUdYw1oIE5QFxNqRJV5QKpsxO5nLkopjhrp6Wdo32GDr2p+4qw/ienwoOaIoIepqX0Fpz9k1bUpxpOflyZ0VdXsmcs4hu2Zocdv22ZtJ3NVHFCUU8rUFDi8UWyhdfYEtax1MUBYQq4fG6U6leX7iZR5/+YWKyizq7mPN0HiDLesM4t5Bt0q4Ch/W6yjkIEqIewbCGtZCmKAsIFYNjrF+ZCmZKpa+96W7OGbpqgZa1TnE3QMQJxQKtfpQckRJQtzTvt1PE5QFRDpOuPa4M6pe7Rq36VL5ZhP3DrrASDU6ZQv5HFGcIjFBMVqFKIraNqdLq5P0DrsWSo1hJMjniNJdxH1DYQ1rIezWZRgVEvcNuzgm+XxNizQL+RzEKZK+4QZY1xqYoBhGhcTd/T4MZAy1tFJyWaI4Ie41QTGMjieKY5I9RoiSFIUK5wKVUshnXQulf7QB1rUGJiiGUQXJHqO+21OdoBQKBT/KkyLZwwTFMAwgGRiDWloo+axbx5Ok23oeigmKYVRBqn/MhYKstoWSyxIlaZL+MR89vz1p309mGA0gGRiHJE2hyjAS5KZcd2egvWctm6AYRhUkA+NEcfVdnkIuC0naBMUwjN2kBpe4FBhVtlAKvoWSGmrvQFcmKIZRBYkXlEK1GQhyU0RJmtTg4sYZ1wKYoBhGFaQGxnfn1KliTU/BC0oy2N6BrkxQDKMKolSGZGBsVyulUgq5KUhlSA21dyoTWxxoGFWSGtqTKEmTf2U7+UpTivqVxiYohmG8jvToPsR9IxSyOysukxpcTDI4TtzV20DL5h8TFMOoksETNpMaXEwhO1lVuZ41xzTIotbBBMUwqiQ1MMbg8efPtxktiTllDcMIhgmKYRjBMEExDCMYJiiGYQQjmFNWRHqBPwV+D9gHeBnYAvytqn6txjpXAJcDJwPjwC+AbwFXqepPQthtGEY4grRQRKQP+BfgQ8C+wI+AV4GTgHtF5EM11CnAA8D5wB7AQ0A3cDbwgIi8LYTthmGEI1SX5wbgSOAHwCpVPURV9wbOAbLAFSJyYqWViUgKuAdYBNwMLFXVw4GlwCdwwnKriCwKZL9hGAGoW1BEZBWwCcgDZ6nqU8Vjqnoz8Fd+94oqqt0E7AdsAy5Q1Qlf3yRwMfBvwBDwx/XabxhGOEK0UM4GEuA/VfXHZY5/ym+P8T6RSjjPb2/2IrILVS0An/a7Z1Zpq2EYDSSEoBztt/9e7qCqPgM86XePn6syEYmBI2arE/gPv91XRJZXaKdhGA0mhKDs57ePzXLOE367poL69gJ65qjzKaAYjKKSOg3DaAIhho2LQTJ/Mcs5L/htJQlJSoNulq1TVXMi8hIwUmGdM7F827ZtbNy4sY4qDKP92Lp1612q+vZqy4UQlOJ67NnWck9MO7eS+kLWORM7Jicn2bp161Nzn2oYxlyEEJQclXedKgnCWXlcvcrrLIuqtnc8PsNoMiF8KK/4bfcs5xR9IjuqqC9knYZhNIEQgrLdb2ebZFb0czxfRX0z1uknvg1WUadhGE0ghKAU19SsnOWc4rFH5qpMVZ8FXpqjzuW4uS8V1WkYRnMIISjf89ujyx0UkWVAcULbdyqs879mqxN4k98+6QXIMIwWIISgfMlvT/AL+qbz+377bVV9osI6b/Pbd4pIZpY6b6qwPsMwmkDdgqKqjwJfxHVB7hCR4kQ3RGQTcKnf/ej0siKySkTWisj0/Iy34Ca17Qt8UUT6/fkZEbkOOBbXLbq+XvsNwwhHVFU6xRnwq37vA34NN+z7Q2AY2Nuf8kFV/csy5Z7w53xeVc+bduxw4Js45+srwE9xAjMCTAInq+p9dRtvGEYwgoQvUNUXcP6OD+OcpOtwIzTfBn63nJhUUOf3gQOBzwG/9M/zwD8BR5qYGEbrEaSFYhiGARZT1jCMgJigGIYRDBMUwzCCYYJiGEYwTFAMwwhGRyRLF5GVwOMzHC4AL+ICYn8NuEZVZwsW1ZKIyHnA3wPPqOqyktfvx4XevFJVL5sf62ZHRG4CzsXNpj5hHt7/3bjYx5tV9cYqyr0Xl4Xhnap6U5XvmQKm/O7ZqnrLHOdfAHwWyKlqy163LWtYA3mY3YsPwf0PhoENwEHAZhF5i6r+cD6MM5qLn0D51zWUOxK4OrxFC5tOFJQ/VNX7p7/oZ/t+HtgI3C4i61Q132zjGsA5uKh22+c6sdMQkROAO4D+Ksu9FTfBsq8BZi1oOlFQyqKqL4jIucAzuMDXJwFfn1+r6kdVt823Da2GiHQD7wcuY3cYjErK9QAf8A/zP5bB/ikl+CUED/vdDfNpi9EY/OLVR3Bpc8GJypMzl9hVTny5y3BLQP4Md/MxSrAWyhtJ++3L0w94R9qZwBnAIbj1SlngWVxu54+r6hsCPvk8zO8FjsL5a17CCddtwI3Tk5n5MgPAJcBpuFQlMfAzXBP9GlX9ZSUfppxTtsRJ/b+49K7vAi4E1vtiDwOfAW7yidUaYts8sQwXoOu7wEWqukVENldQbrkv+x1f7kERuaiBds7JNMfuXHxOVS9opD1ggvI6fFrVDbg70NenHesBvgq82b/0BG5V9WJgtX9sEpHjVPXBknIXA9f63Wdx+Z9HcRf58cDpInKiquZKyqzFjTitxK3efgwX5X9/4HLgXBE5WVV/WudHjnB+o7NxCzAfwa3oPso/BNc1KP0/NMu2RvE0sFFV762y3DbgN1W1lbrBBXYnvSvHKO47hApaYSHoeEERkQSXJ/lNwN/g7rZXqur0L+BSnJhsB07xq6GLdRwO3Im7238AON2/PsTukYAzVfXWkjInAV8BTvDn3+pf7wPuxl2wdwLvKUalE5ElwI04x/FdInJgMe9zjYwD78C1Nm7w+Y66ccOTm4D3icjHisPoTbatIajqVmBrDeUeocXCjfqb0LHljvkYQsXMm98Aql7xXwudKCj3lQ8st4urgT8v8/qJuJbLh0vFBFyoBRH5JPAXuJgwRQQXuf9F4B+nlfmGiFwFHICL71LkAlw34gFc6IdcSZmfi8jpuDi+q3E5oD8524epgL9T1etK3mOniPwRcBbu93EErmU2H7Z1CjeLyM2hKvNdoS/hfls/Ac4o/a4aSSc6ZR/GNROLj+8CPwJe88f/BLjOt1x2oarH4sThU5SnmM6jNPHY4zgfyzBwk4gcOK3Oj6jq6ap6R8nLv+O3t5b7Efi7/u1+99SZPmQV3F3mPV5gd9bGoXm0rVN4hNf/Jss9qmlV3QC8DZex87dU9aU5zg9GJ7ZQZpqHksHdVT8BXIQbTnxP6TmqOiUiwyJyFG5oeV+/PRjnS4ESkVbV50XkauCDuPkg54jIz4Fv4Zqh96rq9PkhxdGlzSLy2zN8hmKCsrVzftq5mWmkothdKf2NNNu2TuEjVcyUnRURuRTnYJ8ETlPVn4UxsTI6UVDK4kdaPuPj214BXCgiV6nqU7CrT3otzreQLik6iesCPAicXKbey0RkC06kfh13wZ3lH1kRuRU3alC8ixTzDRUdvbMxNMfxSnjDCNM0opLnzbbNqALf5bzK775bVf+12TaYoLyRO3GCkuBaHk+VvP5m3J37enZ3lR71LZfNlBEUAFX9MvBlP9x6PM4RewruLr4Jd6EWE1O/6vdPVdV7An+2emll2zoaETka+AfcDeDqatcWhcIE5Y2UTrePAHwXpzhcvHGGeLbLpr/gh5pXA5GqPqSqv8L5LO7GjaC8H3dHOVVEBn0rRXGO0P2BshetiKzGXdhPNnkhYyvb1rH46Q534Xx8X8FNupsXOtEpOxcb/bYAbPHP9yk5voVpiEgvbsIbvF6kLwQeAm4RkWh6OVxU/yJFJ3DRSXqBF6Tp75XCtZa+jxvmbiatbFtHIiIjwL24OSc/ADaVm4zYLExQPCISichpOAcqwO2q+rR/XjpJ63IRSZeUW4+b6FX0KZSO8tyG81FsAK7x8ziK5UaBK/3u91T1//zzG4DncMOzd4nIipIyY77Odb7eZl+0rWxbxyEiXbgWyRrcRMtTVPXV+bSpE7s814vI9GG0NG6y1rjf3wL8QfGgn2Z9G27K/fuA80TkcdzU+2Lr5ZvAbwD9IjKgqr9S1edE5F24xGWXAOeLyGO4//sqXBN1O3B+yXu9KCJvx7UGTgQeF5Ef47piAnThhqLPbHaIhVa2rUO5BDjOP98OfNbftNJlzs02I9ZMJwpKuUV/O3HzLu7BLUu/RVWz0855B/DPwGbcHfpAX+Zu4NOq+lUReRKXx/lU4AsAqvoFEXkaN8pzFG69zGvAo/79Pj596FhV/1tENgAX45y1++Eu1ueA+4GPqer/1PE/qJlWtq0DGSh5ftgc5zZlYpvl5TEMIxjmQzEMIxgmKIZhBMMExTCMYJigGIYRDBMUwzCCYYJiGEYwTFAMwwiGCYphGMEwQTEMIxgmKIZhBMMExTCMYJigGIYRDBMUwzCCYYJiGEYwTFAMwwiGCYphGMEwQTEMIxgmKIZhBOP/AS+VC0jYZ7BHAAAAAElFTkSuQmCC\n",
-      "text/plain": [
-       "
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-      ]
-     },
-     "metadata": {
-      "needs_background": "light"
-     },
-     "output_type": "display_data"
-    },
-    {
-     "data": {
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\n",
-      "text/plain": [
-       "
"
-      ]
-     },
-     "metadata": {
-      "needs_background": "light"
-     },
-     "output_type": "display_data"
-    }
-   ],
+   "outputs": [],
    "source": [
     "for key, dd in stuff.items():\n",
     "    baseline = dd['base']['burst_event_ratio'].to_numpy()\n",
@@ -3255,63 +2515,9 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 31,
+   "execution_count": null,
    "metadata": {},
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "U-test: U value 3934.0 p value 0.3348681711667292\n",
-      "U-test: U value 2022.0 p value 0.3129134904118731\n",
-      "U-test: U value 1069.0 p value 0.5107849438878747\n"
-     ]
-    },
-    {
-     "name": "stderr",
-     "output_type": "stream",
-     "text": [
-      "/home/mikkel/.virtualenvs/expipe/lib/python3.6/site-packages/numpy/linalg/linalg.py:2125: RuntimeWarning: invalid value encountered in det\n",
-      "  r = _umath_linalg.det(a, signature=signature)\n"
-     ]
-    },
-    {
-     "data": {
-      "image/png": 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\n",
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-     "output_type": "display_data"
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\n",
-      "text/plain": [
-       "
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-      ]
-     },
-     "metadata": {
-      "needs_background": "light"
-     },
-     "output_type": "display_data"
-    },
-    {
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\n",
-      "text/plain": [
-       "
"
-      ]
-     },
-     "metadata": {
-      "needs_background": "light"
-     },
-     "output_type": "display_data"
-    }
-   ],
+   "outputs": [],
    "source": [
     "for key, dd in stuff.items():\n",
     "    baseline = dd['base']['max_field_mean_rate'].to_numpy()\n",
@@ -3328,55 +2534,9 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 32,
+   "execution_count": null,
    "metadata": {},
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "U-test: U value 4196.0 p value 0.07625033158277\n",
-      "U-test: U value 1789.0 p value 0.8457359656438074\n",
-      "U-test: U value 1312.0 p value 0.008224362184318894\n"
-     ]
-    },
-    {
-     "data": {
-      "image/png": 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\n",
-      "text/plain": [
-       "
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-      ]
-     },
-     "metadata": {
-      "needs_background": "light"
-     },
-     "output_type": "display_data"
-    },
-    {
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\n",
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-     "output_type": "display_data"
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\n",
-      "text/plain": [
-       "
"
-      ]
-     },
-     "metadata": {
-      "needs_background": "light"
-     },
-     "output_type": "display_data"
-    }
-   ],
+   "outputs": [],
    "source": [
     "for key, dd in stuff.items():\n",
     "    baseline = dd['base']['bursty_spike_ratio'].to_numpy()\n",
@@ -3393,55 +2553,9 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 33,
+   "execution_count": null,
    "metadata": {},
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "U-test: U value 4034.0 p value 0.20303646513670592\n",
-      "U-test: U value 2195.0 p value 0.05655864319615998\n",
-      "U-test: U value 1062.0 p value 0.5482183981489739\n"
-     ]
-    },
-    {
-     "data": {
-      "image/png": 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\n",
-      "text/plain": [
-       "
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-      ]
-     },
-     "metadata": {
-      "needs_background": "light"
-     },
-     "output_type": "display_data"
-    },
-    {
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otKXTg2kh1ATGn/3Zn3HLLbegdzcFj2EYfOYzn+GHP/xh0KYEgt5i14A0wxa7bDZLKpXSIlhHGIZxJEtOA6O32GkaB8uytAjWGa7rtuwyhZ4aa+qCnTt30tnZGbQZLcfg4CBLly4N2ozA0UKoqQs6Ozvp6uoK2gxNi6KnxhqNpuXRQqjRaFoeLYQajabl0UKo0WhaHu0s0VSVbNGi4JQmv84tYZomjuMQCoXIuCXcQnbS++KhMIlwtBqmtgyu64Jjj3kuEjJf83uIhExce5zfnxnCMGYUplf3aCHUVI0H90r++cX7cKYYH7j4bRex5+7HWHTlhXz80f8zpXtMw+Crq67kgmOXV2Jqy2Bn+jn4bx+mNHho3Gs+cs48fvHsIT68ai4937183OvCsxez8FO/wIyn/DA1ULQQaqqC67r81+bn2JcZIFucWlBu9H0Xsex9FwGwbbB7SvekIjF+teV5zl+4rGlHJ9Uks+FerINbKPXvH/eavz4D/vqMdiCLtf+Vca9z8mmymx4kdeY7fbA0WLQQaqrCmp49bB/qIV8qsqxzLqZR/eVn23HYMdyL7D/Ipv6DnDJ7YdX7aDayL92Pkxsi1DEPMznzOE0n04eTGyKz8f6mFELtLNFUhTt3rGewkKU9GvdFBAFCpkl7JMagleOOHet86aOZKPXvp7BrHU4hjZnoxDBDM36YiU6c/DD5bc9gp/uCfmtVRwuhpmL2ZwZ5+uB2hqw8XdGEr311xhIMWXke27+Vnlza174ancyGP+LkhzCiCYxQZZM/IxzFCEe9UeF9VbKwftBCqKmYP+xYz2AhTzwcIVrhB24y4qEIUTPEQCHHXTs3+NpXI+O6Lpl1d+PkhjAT1dnDbSY7cXKDZNbfU5X26gkthJqKyJUs7t39EgNW1vfRYJmuWJKBQpZ7dm2kMF6oR4tj7d+EdXgbjpXFjLdXpU0z3oFTyGDt3Uixe0dV2qwXtBBqKuK+3ZvoyWUASNYovq8tHMVxXQ5mh3h4r6xJn41GZu0fcHKDmPF2DDNUlTaNUBgz1oaTGyS9tnFzYY6FFkLNjHFch9u3r2XAyjIrmqxZOIthGHTFEgwUcty2fa3OazgKt2SR2XAvTnawatPiMmaiEzs7SGb93biOU9W2g0QLoWbGPH1wB7uG+8iXirRH4zXtuyMaJ1ey2DrYzZqePTXtu97JvvII9tBhcB2MWFtV2zbiKVy7SKlvH/ltT1e17SDRQqiZMb/fvo6BQpbOaAKzxsHNIcOkPRpnoJDltm1ra9p3vZNZcyd2dkCFzFT592IYJmaiAyc7QHrNHVVtO0i0EGpmxNaBw6zt2cNwsUBXrDZOktF0RZMMW3mePbST3cPNF9s2E0qDh8htfUp5iysIoJ4IM9mFkxsk98oj2Jl+X/qoNVoINTPitu1rGSzkSEVihKu0GD9doqEQiXCUISvH7dt1gDVAes0dOLlBjEgcwyfnlRmJQyiCnekns+5uX/qoNVoINdOmL5/hkX2bGbRyNQuZGQ/lNMnywJ5NDFn5QG0JGtdxyKy5Azs7QMin0WAZM9mlpscv3t4UziothJppc+eO9fQXckTMEPFwJFBbEqEIIcOkr5Dl7hYPsM5vf4Zi727ckoWRqE7s4HiYiQ4cK4d1aAvWnvW+9lULtBBqpkXBLnH3ro0MFLLMigVf/1aF0qgA6zt3bqA4Tt69ViD9wu9xMgOYiQ4Mn/Z7l1H7j9txsgMMv/B7X/uqBVoIx0AI8WkhhCuE+MQM758jhLhZCLFdCGEJIQ4JIX4nhHhDtW2tNQ/ufYVD2SEc16WtThKktkdiFB2b/ekBHt+/NWhzAsFO95J95WHs3CCh5Kya9FmeHmc33oeTG65Jn36hhXAUQohzgO9UcP8xwDPAfwOOAdYDLvAu4HEhxMeqYWcQuK7L7dvXMVDI0RVL1E0+QMMw6IomGLCy/L5FA6zTa+7EyQ6o5AiRWE36NCIJMELYmT4yGxp7/7EWwhEIIS4B7gUqWWD5NbAMuB9YLKVcBRwL/BUQAm4RQqys0NRAWNuzl62D3eRKFh01DqCejI5ogkzRYlOfylXYSriOQ/rF29W02GcnyUgMw8Bs85wmL/y+ob+AtBACQoi4EOIbwAPAjOcVnpC+EUgD10kp+wGklI6U8tvAfwIR4KuV2hwEd+xYdyTnYMjnNajpEvZyFQ5Y2ZbLVZjf+TzF7h04xTxmvKOmfZuJTpxChsL+TVj7Xqpp39Wkvv6aA0AIsRzYDHzde+lvgF0zbO5G73i7lLJnjPO3eMdrhBDBxp1Mk1rmHJwpXbEEg1aeR/dtaalchZkXb8cp7yQxa/uRNsyQykrjhdI0Ki0vhMBi4DjgaWC1lPJbFbR1nnd8fJzzzwIloA1YVUE/NaeWOQdnSiwUIWaGGLTyLZOr0M4MkH35ISWEbbWbFo9EOU0GVaKHKVQirEe0EMJe4Cop5XlSyhdm2ogQwgRO9J5uG+saKWUR2Oc9PWmmfdWaXKnIfbtfrmnOwZlSDqX54+6XsFogV2Fm/d3YmT4IRdSOjwAwogkwDOx0D5mN9wZiQ6W0vBBKKbdKKauxT2gWrxbDmqgkW693nFuFPmvCQ3slPfk0uLXLOThTVK5Ch4OZIR4/MOb3UdPguq5ykmRr6yQZjWEYalSYGSDzYmMmYmh5IawiI6OLJ9rrlRvj+rrFdV3+sHM9A4UcnXUUMjMehmHQ6YXS3NnkThNr30tYBzfjWDnMRG2dJKNRTpM0hT3rsA5vD9SWmaCFsHpMd0tDQ8QavNx3gC0Dh8mWLDoCmnpNl3IozUt9B6ZcL7kRUbGD1c1CPVNU9uoUdnaITAOm59JCWD1GuiknUozyIltDrCrftXMDg1aO9kiMUI09kjMlbJq0RaIMNXGBJ6dYILvxXm9aXN0s1DNFFXcaILP+HtwGW59tjL/sxiANFLz/z5nguvLa4GF/zamcgUKWxw5sZcjK01nnTpLRdEZVKM2DeyWZYmHyGxqM3CsPYw+rCC0jWh+rLEYshWuXKA0cILf1yaDNmRZaCKuElNIBypWElo51jRAigtplAip2sa55YM8rDBZyhA0z8Cwz0yURimAaBv35LA/tq/sf9bTJrLsbOzuImax+FuqZYhiGWivMDjZcnkIthNXlGe943jjnz0V5lvPAmppYNENc1+WPu15i0Mo13GgQ1IeyIxpn0Mpxz66NDb39azR2uu/VLNRVLs5UKeXaxzn5WEMlYtBCWF1+4x3fK4SYPcb5z3rHX0spc2Ocrxs29O5j13CvV5ipNpv4q01HJE62ZLGl/zBbBut+JWLKZDbei5MbwojEfMtCPVOMcAzMMHamn+zLfwranCmjhXAGCCGOF0KcLIQ4ftSpPwFPAJ3A771MNAghTCHEl4EPAUXg2zU1eAbcu/tlBq0cqUgcs872FU+VkGmSisQYsnLcu+vloM2pGtkN93mjwWBDZsZCTY87cHJDZF66P2hzpkxj/oUHzy+ATd7xCFJKF/gwarfKRcAuIcTzqN0k30aFzHxUSrmptuZOj3SxwGP7y06SxgiZGY+OaJwhK8/D+yT5UjFocyqm1L+fwp71OIV0zRMsTBUz0YGTHya//TnsdGMU1dJCWGWklNuBM4HvowTwdFQ4zR+BN0kpbw3QvCnxyL7NDBZyhAyTWJ3uK54qiVAEF+jNZ3iiCXaaZF66HyefxogmMer0d2OEoxjhKE5uiOzLDwRtzpSoz59kwEgpl05y/pJJzvcAn/ceDYcqhJSjIxqvG4/kTFE7TdSo8IE9m3jTcScHbVJFZF9+ECc/hBn3tyZJpZRHhdlND9N+7vuDNmdS9IhQ8xp2D/fxct8BMiWL9gbZSTIZ7dE46WKBNd17OJQdCtqcGVMaOIi19yWcQqb+hTDejpNPk9/xPHZmIGhzJkULoeY1PLBnE8NWgWQ4QrhBdpJMRsQMkQhFGC4WeGDPK0GbM2Nymx/FKaRVzeI6nRaXUdPjCE4+TW7zY0GbMynN8ZeuqQqO6/DQ3s0MFXN0NGDs4ES0R+MMWzke3PtKw8YU5uTjOPl03Y8Gy5jxdtxCmtzm8dJz1g9aCDVHWN+zjwPZQYq2XffptqZLKhIlb5fYPdyHHDgUtDnTxilkye98XnmLY6mgzZkSRiyFkx8mt+1p3JIVtDkTooVQc4SH9kmGrbwXO9jYTpLRmIaKKRwuFnhwr5z8hjojv/N5FURtmNAgX1JGJI7rujiZAQp1XgReC6EGAMsu8fj+bQxb+YbdSTIZ7ZEYw1aex/ZvwXacoM2ZFvltz+IUMhixtobx5BuGgRlL4RQy5Lc9G7Q5E6KFUAPAc4d20l/I4OKSCDVWgoWpkgxHsV2Hw9lh1vbsCdqcaZHf/ozyFjfItLiMEWtT64Tbng7alAnRQqgB4OF9W9RoMNL4sYPjYRiGNz3ON1RGGjvdS7F7B24xjxGrj5RbU8WMJXGsHNZBiVPIBG3OuGgh1JArWTx7eAfDxQKpJp0Wl1HT4wJPHdjeMMWd8rvW4Fg5FZIScCbq6WKEIhhmCLeQpbC7fksnaCHU8MyhnQwWcpgYxMz6jk+rlHgoArj0FzK80L07aHOmRGHXWlwrWzcJWKeLEUviWFkKu9YGbcq4aCHU8Ni+LaS90WCzTovLHJkeWwUe3bclaHOmRGHvBlwrh9mgsZ1GJIFr5Sjs2xi0KeOihbDFyZUsnj+8i3SxQHukuafFZVIRteXumUM76n567JYsigc34xRzGJEGFcJoAreYw9r3Mm6deuu1ELY4zx7ayZCVxzQMok0+LS4TD4UBl4FClhfrfHpsHdqKY+UAAxrUm2+EY7iOjZMbotRbnz9vLYQtzmP7tzJczJOKNP+0uEx5elzOu1jPFA9uVt7iBvbmG4aBEY7jFPNYh+rTW6+FsIUp2KUj0+JUuDWmxWXKQvjsoZ2UnOmWpK4d1qEtnhA29u/HiMRwS3msg/W5LquFsIV5sXs3Q1YOAxo+Aet0iYciOK5LXz7D+t59QZszLsXD23FLBVULpIExIjHcYoFi9/agTRkTLYQtzJMHtqnRYAtNi8sYhkFbWI0KnzxQnx9OgGLPTtyS1fhCGI7hlixKPTuDNmVMtBC2KLbj8OyhnaSLBdoafNo1U1KRKJligWcO7qjL1FxOIYM93OMJYWMkWhgPIxxVHvC+vbh1WDtGC2GL8nLfAXrzGWzHadq9xZORCEexHJuD2UG2DnYHbc5RlPr34dpFMEMNt6PkKEzlqadUpDRUf2nQtBC2KE8f2k7GGw222rS4jGkYtIWjZIoWTx+sv+lxqX8/rl3EaIIvKsMwMEIRXLtIaWB/0OYchRbCFuWZg960uMGnXJXSFomRKRV45tDOoE05itLAfmgSIQSOCKE9cCBoU45CC2ELsi89wJ50HwW7SFuktYUwGY6SKxXZOnCYnlw6aHNeg53uVVPjJhFCQhFcu0Rp6HDQlhyFFsIW5NlDO8kWLRKhKKbR2n8CYVPVbs6WLJ6ts1GhPdSNa5fqvlDTVDFCYXCK2MM9QZtyFK39KWhRnj+8k0zJItnio8EybeEomZLFC4d3BW3Ka7AzveCUPEdDE2CGce0SdloLoSZgcqUiG3r3kSlZLb8+WCYZjpItFljTs4diHe0ycTL9uI7d+B5jD8MMgWPjZOuvzrEWwhZjQ+8+0sUCJgaRJvmAVUosFMYFBgs5Xu6rn4V8OzsAjg3N8nsywyr5ghZCTdC8eHg3maIaDbZq2MxoDMNQo8KSxYuH6yc7ipMbhqYaEZpqRJgfDtqUo9BC2GK82L2brF4fPIojQlgnabnckoVbKqj8fU0ihBghXNfByWfqbiePFsIWojs3zO7hPgp2iUS4SUIyqkQyHFFhNIPdDBZyQZuDk0+D6wAuNItn3xsRunax7gq+N8lPWDMV1vXsJVeyiIVChJrlw1UlwmaIiBkiV7LYUAfZaJxiDhwHDKN5ljDKf3Oug2tlg7VlFPrT0EKs7dlLtlQkob3FY1IeFa7t2Ru0KbhWDtd1mmc0iFqLxTA8IQx+1D2S5vkpaybEdV3Wde9V64MhLYRjkfDWCdd2B1/83bVy4DoYTSSEABgmruOoEW8d0WQ/Zc14HMoNczg3RNEpEdfrg2OSCEXI20X2ptJh5owAACAASURBVPvpzwdbjNwt5sFtovVBD8MwwHVxi4WgTXkNNf8pCyFOF0K8XgjRJOHyjcHG3n3kSkVioQhms6w5VZmQaRIzw+TtIhv7gs2Q4pYKylnSbL8rwwQcJfR1hC9CKIRICSG+LIT4+IjXFgkhXgTWAi8AW4QQF/vRv+ZoNnhC2Kq5B6dK3Fsn3NgbtBBaKsSk6YTQGxGWmnxEKIRIAU8BNwFvG3HqFuD1gOE9lgB3CSEWV9sGzdFs6jtI3i7qafEklKfHm/oPBmqHEormmxpjmLiuq7Lq1BF+/JQ/B5wK9AB3gxoNokTRBa4F5gK/ANqAv/TBBs0Ihq08u9Ne/KAeEU5IPBwhXyqybbCbXIAp5d1iAVy3eUJnjuB5jVtganwN4ABXSCl/6r12FWoU+IKU8jdSyj7gz4EMcIUPNmhG8Er/QQqlEmHTJGQ22QijykTMEKZhkPdyFAaFa1teQHVzCWErOUsEsFVKuXbEa29BjQbvLb8gpUwD24DjfLBBMwI5cEhNi/VocErEvemxHAiutkazeo0xTG+NsPl3lqSAofITIYQBXOo9fWTUtSFAe499ZsvAYQp2iXiTJPj0m1goTMEusSXIEWHJ8gKqm2tEeCSgugWmxoeBJZ4AAqwGZgF54LHyRUKIWcAyIPj9TE3OloHD5G0VOqOZnHhIrRNuCXBE6Fh5L3ym+UaEruu2hBA+gXKGfF4I0QH8DWpafL+UsgAghIgAPwRiwOM+2KDx6M9n6MtnKDo2MT0inBKxUBjLsTmQHSRbDGYK5xZzzeksMUxwHZwWEMLvAjbwHaAfuNJ7/XsAQohzgf3A+wGr/LrGH7YP9WA5pSNOAM3khEyTkGFg2TY7hoJJK+8Usk05IjSO7DVu8qQLUspnUSEyh1AurwHg01LKR71LhoA5QC/wVinl+mrboHmVHUM9FOwSsWape1EjyuuE2wMSQreQaa5chGXMkBoRFoLdwjgaX75upJS/AxYBC4B5UsqfjDi9DRVis0hKOdp5oqkyu7z8g1E9LZ4WUTOM5ZTYNdwXSP9OIQ2u3aRJF2zcfH2VTvXt0yGldFGOk9GvF4E7/OpX81r2DPdTdGwSUe0omQ7RUIh00WJPUEKYG8RtpnolHoYZwnVs7NzQ5BfXEN+EUAgRBeZIKQ+MeO0a4AZU2MxdwE+llI5fNrQ6ruuyJ92PZZeI6qnxtFAjwix70v2B9N90hZvKeEJYbwWc/Eq68DHgIPDNEa99Avh/qGnxO1F7j3/rR/8axYCVI1MsUHIcXbFumkRCIYqOTX8hS67Gwb+u6+JkB5uqlGeZei3p6UfShfOBfwe6gMXeayHgH7xLXgD+FeU0uVoIcW21bdAoDmQGKTo2YdPUHuNpEjJMQpiUHJsDmcGa9u3kh9UWNMeGZlvbNcO4Tgk7O1BXu0v8SrpgoMTuau+1i4H5KA/yJVLKvwDe4V33YR9s0PCqEOrR4MwojwprLYT20GGVncUMNZ+zpPy36JSwh4PxyI+FHz/lC1Dxg1+UUpYl/63e8R4pZRZASvk4sAs4ywcbNKiqdVoIZ07YNCk6NodztfVw2kOHwClhNNtoEBVHaJhhXLtEaTDYVGcj8UMIjwG2jRBBgMtRu0seGnVtN2r7ncYHunNpSo5DWAvhjAgbIUqOQ0+NC5KX+vbiliyMZq0tE47ilixK/fWzu9YPISyh8gwCIISYi0rICkcL4bFAfQUUNRHduWFKrk242aZXNSJsqjXC7hqPCIt9e1UariatNmiEIri2Rakv+GqBZfz4hLwCrPCSsQK8F7UWuFVKub18kRDiCpQQvuyDDRqgr5DFdhzCOgfhjAgbJiXXoa/GhZyKPTtxixZGkybJMMIx3JJFsWdn0KYcwY9FiN8CZwP3CyH+CHwcNS3+PwBCiDnAR4Cve6//xgcbNMBAIUvJdXQx9xkSMk1sx2GgUNvSk8XD23BLBczU7Jr2WyuMSAwnN0jx8LagTTmCH0L4Lyhv8RtQSVoN4CXgn73zK0f8/27gRz7Y0PK4rstAIYftODor9Qwpjwj7C7VLEGDnhrCHutUaYThWs35riRoRFij27cEpFjAjwb9PP5Iu5IFLgM8CP0bVJDlfSlmeX0hUJbu/BN4ppSxV2wYN5EpFbNfBcV09IpwhIcPEcV1yJQvbqc0GKGvfy7jFPEYo0nTB1EcwQ2CEcIt5igdl0NYAPm2x8zzGPx7nXDc6ZMZ3hot5HNfBMJqt6kXtMA1D7fLAJV0s0BlL+N6nte8l3GIOI+p/X0FhGAZmNI5r5Sjs3UjsuDOCNsn/NPlepupFQJeUcqPf/WkUmWIB23UxDbOqyT0Lg7UNJZkusc72qrVlGAamYeC4tRPCwt6NOFYeI9K8QghgRBK4RSWE9YCfSRdOAf4WlZi1HeUYCQshjkOF0fzjqPRcmiqS9QqEm1UeDz744a9Wtb1qc+Xt/7Oq7ZWFsBb7jV3HprB7Da6VaVpHSRkjmsQePEhh5wu4dZCJ26+kC+8CnkNloe7g1aLuoKrWnQj8WAjxHT/610DBLuG4rt5jXCGGNz0u2P4vZVsHJHZmANd1mtZRUsaIxnFtC3uom1LPrqDN8SXpwnLgP4EE8H9Re4pfHHHJK8BPUcL4BSHEVdW2QQP5UhGH4L9pGx0TNSLM2/4Xe89vexrXymJGk03/ezMMEyOawLGy5Lc/E7Q5vkyNv4QSwW9JKf8WQAjxV+WTXnH3TwohdqHSdH0alZswEIQQSeDLqPICJwDDqAw535dS3jOD9pYCOya5bJ2U8vWTXFMRRddRUw4/O2kBDMPAxaXo2L73ldv6FE4+jRFL+d5XPWDGUjj5NLktT9K++gOB2uKHEL4ZlWLr7ye57p+ALwDn+mDDlBBCtAF/QpUcLQIbUfVU3gK8RQjxDSnl302z2dd5xz5g0zjXbJmBudOiHO5R7ZHFZb/4VlXbawRcF0o+h8/YuSEKu9fjFDJEOo7xta96wYylKKV7ye94HsfKY0bjgdnihxAeC6wflXThKKSUlhBiGxCk7/wHKBFci4pp3AMghLgB+BnwDSHEE1LKB6bRZlkIfyOl/GxVrZ0GJcfGpfojwmp6ZRsBA3BxKbn+CmFOPoZTGFbxg+Hm3Fp3FOEoGCZObpD8tqdIrrw0MFP8cJZkUEWbpsJs1FS05gghlgHXAw7wobIIAkgpfwn8o/f0G9NsuiyEGyq1sRLcI/9oKsHwvkpc198fZnbTgzi5YcxE63zRGIaBEW/HyQ+TfXl0Ppba4ocQrgMWCSHOnugiIcR5qDW5oMp5lmunPCWlHCvxwy3e8QIhxPHTaLcshPURIKWpe5xChvzWp3Hzwxjx1hFCADPRjpMbJrf50UAzVvshhP+BmlH8TAgx5shQCCGAWxmRjCEAzvOOj491Ukq5D5U4FuCNU2lQCJFChQZBwCNCTeOQ3fSwKtZkhpo+bGY0KnDcxR7uJbflicDs8GON8JeoKeebgC1CiIeBFQBCiH8CTkUlao0ATwP/2wcbpsJy7zhRCoydwBLgpCm2eQbqS2A/ME8I8UXgTNTPeTPwKyllTX7bpmGAYejZcYWodVbD1/3a2Q334uQGMROdTR82MxrDMDASnTi5QTIb7g1sndCPpAsOqlLdr1EJWq9C1SsxUIkWrkSJ4L3A26WU/scljM1879g9wTW93nHuFNssT4tnofIs/nfU+30zqpbL40KInwohfF8ND5shtbqllbAiXMAw8C2noz3cQ27b0976YIcvfdQ7ZqIDJzdETj4WWL1jv5IuZIAPCiFuAt4FnAZ0ohwpErizViOjCUh6x/wE15QT0SUnuGYkZSGMo5JO/C9gK8p5dAMqB+PHgALwZ9MxdrpETBMDFQOnmTllJ4lf5Q4y6+/GyQ1hRGIYTZqRejKMcAzMMHamn+zG+2k/5z01t8HXpAtSyvUE5wyZDJupj4inqiaPeW2ukVKOzLO4G/iWEGInatfNZ4QQP5BSvjTFdqdN1AxjGOD47O1sdlzUMkPUByF0XZf02rtwsgOYic6qt98oGIaBmezEyQ6QWXtnIELYyonqyoUoJoriLKcAmVJmTinlrVLKT40SwdecRwVTG7xa6tQX4uGISiOlR4QV4bhqjTDuQ2yftXcj1sHNOFauZafFZcxEJ04hTWHPeqwAMlf7mX3mnajSnl1eP+OtArtSyo/7ZccE9KDW8uZMcE15bfBwFftdg3IenVDFNo8iHopgeJlTNDPHRSWuiPtQPyS95g41Goy3N28S1ilihMKYsRR2dojMi3cQfevna9p/1YXQ27b2R+D8ES+PJYIu5cB9Vdek1mxCCdLSCa4pn9s81UY9R4gzgROoPAr3dRd/MhwhhKmFsAJc18VxHUzDoC1S3fU7p5Als/E+nOwgoa5jq9p2o2Imu7CHDpNedxddl3+upmumfiVduMD7/waU4NS2+s3UeAZ4J6/GE74GIcRioBxI/eRkjQkhZqFCcWYB7wF+N86lZ3pHX6v3paLxI7n06iHfWyPiovYZm4ZJqsp1NbIv3Y893AOG0dTZqKeDEWsD18YePET2lYdpO+0tNevbDyF8P+pv6HNSylsmuzhA/i/wLeASIYSQUo4unvAZ7/iIlHLnZI1JKfuFEAdRQngjYwihEOK9wDLAGut8NUlFYkr8PIdJSAvhtCmPBkOGWfWpcfqF3+Nk+jGTXfpLysMwDMxEF3a2n/SLt9dUCP1wlpwA7K1zEURKuQW1qyUE/M7LowiAEOJ64Cve038Yfa8QYpkQ4mQhxMJRp27yju8QQtwkhIiNuOe9vBo8/k9Syv1VeitjEjFDanpsmNg+JwxoVkquqgDYGY1XVaysw9so7FmHU0i3tLd4LMxkF05umPzWZyj276tdvz60mUGloGoE/gI1fT8FeEUIscYLcfklarT81XEyz/wJNeW/aeSLXrKGcqnSvwK6hRAvCCH2okagKeAnqHhC3+mKJQl5JSk108d2VE3orvhUw0inRubFO7Czg5ixFEbI97JBDYURjqiErflBMmvurFm/fgjhM8BJQoi63z0upexFrRH+HcohshLlRX4EeI+U8n/MoM0voXaS3I5aGz0DtZPmD6idNJ/0dt/4TlcsSdgrUq6ZPrbrCWEV1/DcUpH0urtwsoOYya6qtdtMhJJd2NlB0mvvxK3R364fX0f/BLwV+B7wSR/aryreLphvMI10W1LKpZOcfwCYTg5DX5gbTx0pUq6ZPiXHIWyazIlXL2N0bsvj2IOHcF1bOQc0R2HEU7iDByn17iW/4zkSy1b73qcfQngAuBn4vJeK6y5gH8pBMCZSyp/5YEfLMy+RImyGKNUgzXwzUnIcIqEQ8xLVE8LMurtbNsHCVDEMEzPeoRIxrLu7YYXwFV6NEXwdr+6/nQgthD4wN5EibJpki/5XYGtGiq5Nwowwt0pCaGcHyW1+HDs3RGTOkqq02ayYyU7s/r1kX34Q56qvYMaqu047Gj+EcDc650ldsCDZQcQM1aTwUDNSdGwiZogFyep4dnObHsLODmKEwhhVjktsNoxIXKXxz/ST2/K476E0VRfCydbPNLXj2LYuomaYomProOpp4rouJU8Ij22rjhBmXnoAJzeEGW/tfcVTwTAMzHg7Tn6I7MYHfBfCVk660PQsSHYQNk1cwNZb7aZFyXFUsoVQpCprhHZ2kPz2Z3HyrZt3cLoY5TyFW57AsfzdnKaFsImJhsIsbOskaoawHL1OOB0KToloKMyiVBdmFbJT57c+iVPIeFXqWjPv4HQxwjGvyt0Q+R3P+dpXRVNjIcQvqmCDK6X8SBXa0YzBkvbZrOneg2WXSOoP4JSx7BKxUJil7RMlJ5o6uc1P4ObTmFUMxWl2VJW7FE5hmNzmJ0iKi33rq9I1wut51UM8mpFzsdHn3RGvu4AWQp9Y2jGXWChMwdYjwulgOSXioShLOyoXQtd1yW17BqeQJtQ5elemZiLMWAp7uJv81qd87adSIfwFY3uITwPORqWauh9VQL0flej0VODtqPT3d6EKOGl8YpknhMPWRBUJNKPJ2yW6YklO7JhXcVvF7h046V5cu6gzzUwTI5rELRYo9e+nNHCQcNdUS6ZPj4qEUEp54+jXvOQFL6Dq+l4jpdw+xjULUFvQ3gR8rRIbNBNz0qxjiIUiFJwSjquSjGomxnYcio5NNBTmpFnHVNxeYfdaHCuLEUloz/00MUwTIxLDsbIUdq8h3HWlL/344Sz5e9Ro791jiSCAlPIg8D6UEP+9DzZoPObGU8yNtxE1wxRsX3PBNg0Fu0TMDHNsspOO6ESVHKaGte9l3GIOU48GZ4QaFeYo7NvkWx9+BFRfDrwkpdw60UVSyt1CiA28NpO1psoYhsHK2Qt5pf8guVKRhHaYTErOtkiEI6ycXZ31vOLhrbjFQlWTLPRm6vtLbU5b9fI3GpEYbj5N8fCEklIRfghhDJXjbyqkGL+WiaZKnD5nEX/c9RLDRb1OOBVypSJdsSSnz1lUcVuu41Ds3oFbzKtwkCpx9j+vrVpbfrDz6+dUrS0jHMMp9fgqhH5MjbcCpwghzpjoIiHEZaiaIb6VtNQoTp9zLIlwhHypeKROr2ZsHNclbxdJhCOcUQUhdLIDOIUMrmODHo3PCCMcxS0VsdP9OD45/fwQwv9AjfLuEEJcONYFQoh3AL9GeZz/zQcbNCNY2jHHS8AQIqfXCSckV7KIhsIsSHaysApb6+yhw7h2CcywdpTMFMNUD8fGHq5mQclX8WNqfAuqbsl5wCNexueNqDrCHahsNItQYvn/pJTVCMrWTIBpmJw173i2DnSTLVo6sHoCMiWLtnCMc45ZUhXhKg13g13UmagrwDAMjFAY1y5iD/cQmXP85DdNEz+SLhSEEG9Dpaz/KKqGyegavkXv/N9Vu3/N2Jx7zFLu2rmB7lz6SLFmzWtxXZdM0WJBsoNV86uTJsst5nBdR41oqsgLX3x9VdurewwTXBe36M+eY1++pqSUg8AnhRB/A7wNEKjqbr2ABO6QUvb70bdmbM6adzypSJwDmUEsW+2j1byWglPCxaUjFud1c4+rSptuyQIfMv9U0yvbEBgGLg5useBL875+GqSUh3i1cpsmQNqjcc6cdxwHMgMMFwvM0UJ4FGmrQCoS49z5J5AIV0lo7BLggl4frBBDjQh9Sh6is8+0EBcdu5xUJE66WNDe41G4rku6WKA9EueiY5dPfsMUKScYdXXdmMpwHQzDVD9PH6g0+8yjKM/vh6SUe0e8Nh1cKeUbK7FDMzXOW3AinbEEh3JDFJxS1YuWNzJ5u4gLzIonOeeYpVVr14glPY+nFsKK8NZZzag/KfsrnR9diBLC5KjXpoMemtSI9mic8xeeyIHMIMNWnnhCC2GZIStPR1SNBqs2LQbMeAeGGQJdLqEiXMcGM+RbUttKhfCbKCHrGfGa9gTXMZcvXsn9uzexLz3AnHhKJ2EAHNchXSxwXPtsLl+8sqpth7sWYoQiuHZRl0uYIa7jgGNjhCKEfUpjVmn2mW+M8fK/SCkHKmlX4x9nzT+ORakuDueGSRcLVUkq0OgMWwXi4QhL2+dw6pzqftBC7fNURmrDVI6TKo42WwYvDtOMpzAT7b504Yez5H4hxGNCiNk+tK2pENMweduS0+iKJRi0skGbEziu6zJg5eiMJnj7CadXJS3/SAzTJDzneJU4oORP6Eez45YKGOEYkXmjw5Grhx9CeDKwSErZ50PbmipwxZJT6YolKToO+VJrb7nL2UUc12V2vI3Lj6vutLhMdOHJmJG4b8HAzY5TzGFE4kQXnuxbH34IYRHI+NCupkrMiiW5ZNFJdEUT9Bdae1TYX8jSFUtw+XErSflUazh67MkYkQSuzhI+I1wr7wmh8K0PP4Twl6jsM+/1oW1NlXjv8rPojCXIliysFq1nUrBL5EtFZsWSvHvZmb71E196NkYsiWNldfzmNHEdRyW1jbURW3KWb/34sb3gJ8BZwK+FEI8BjwMHgHHnBVLKn/lgh2YClrTP4bwFJ9KXz9JfyHJMsvVq7fYXMnTGElx07IqqFXEfi8j85YTb51Hq3Y1r5VRsoWZKuFYWIxwjPGsR4dmLfevHDyEsZ4w0gIu8x2RoIQyA969YxZMHt7NzqJfZjk3EnGo+3cbHsktkihZLO+bw/hVn+9qXYZrETzwH64DELaRBC+GUcQppzFgb8WWrfQ098kMI96CDpBuCU2Yv5Jz5S+jPZ+jLZ1pqVNhXyNIZS3DBwmUs66y8Ut1kJE6+hPSLt1MaOIDZPk/HE04B13VxcsNE5hxHcuWlvvblRxqupdVuU+MfHxKree7wLnYO9TKrRbLSFOwSmWKBpR1z+JBYXZM+EysuwEx0Qt9eFQ7i057ZZsK1chiGQSg1h/gJ1Uv9PxY66UKLc8rshaw+5gS6Ygl6C63h7O/Np+mKJbno2BU1GQ0CmLEkiZMuxEx04mQHa9Jno+PkBjGTHSRXXorhcyB61b7+hRAdqBKdD0gpd414ffc4t2yQUl5Vrf41M+ejK8/juUM72THUQ75UJN7Eux9yJYu8XeLYti5uXHleTftOnfkOMuvvodi7G7djvp4eT4DrODi5ISLzTqDt9W/3vb+qjAiFEDcA21H1R94z6vTicR5vFUJ8pBr9ayrjxM55vOm4k5kdb6Mnn2naEA/XdenJZ5gda+PKJaexODWrpv3Hl59HeNYitfc4P1zTvhsNJz+EGYkTmXcCsSX+hTaVqVgIhRAfB34OzEaFyQyNcdlmVNr+8uM2lFf5byvtX1Mdbjj5DcyNpyg6NpmSFbQ5vpAuFrBdh/nJdq4T/q45jYVhhkid+U5CbbOwMzpB+3i4rouT6cdsm0XqrKtrMnKuSAiFEHOA73lPvwMsk1L+ZIxLD0sp/6P8AG4ADgInCCHeWokNmuqwINnBu5edydxEip58uulGhY7r0pNPMy/ezvtXnM2ceCoQO1Kr3o2Z7MItFXxLO9/ouMU82CVCqTmkzrqmJn1WOiL8BNAO/KeU8itSyin9ZqWUWeC7qFGhXiesEz6wYhWLU12EDJMBq7n2xQ4UskRDYY5vn8W7T/R/qjUe4c5jSK68lFCyCzujt+OPhZPpw2zrInnaWwi1ddWkz0qF8ApUzOA3Z3Dvr7x7L6jQBk2VSEai3HjyecxPtNOXz1BqkmSiRcemv5BlXiLFx0+9MHBnUMd512G2zcLJDaqax5ojuCULJz9MqG0WHed9sGb9ViqEAtgtpdw23RullPuB3SjHiaZOePPxKzltzrG0R+P05JsjnKYnl6YjmuCseUt447ErgjaH6HFnEF9yJma8A0ePCl+DneknlOwivvw8ogtOqlm/lQrhXODQJNf8FPjDOOcOA7UZ+2qmhGmYfPb0NzIn3kamWCDX4Gm6skWLnF1kbiLFZ067uC5CVgzDoOP86wmlZmNn+1UGZg2uXcLJDmC2zabj/Otr2nelQmih1gjHRUr5SSnlP41zei7Q2nmg6pCTZy3grUtOZW4ixeHccMM6ThzX5XB+mHnxFO884QxO7Kyf0vaJky8humAFZiSJk9UeZAAn248ZTxFbfBrxZW+oad+VCuFeYKkQYtqJ3IQQncBxwI4KbdD4wEdXns+iti5Mw2hYx8lAIUvYCLG4fRYfPrm2H6zJMEyTjgs/Qqh9Dna6r+XLfbqOo6bFqTl0XPiRmo/cKxXC54A4M/P8vhe1s+WJCm3Q+EBXLMmNK89nXoM6To44SJIpPnHKhbT5lHS1EtpOv5Lw3CWY4WjLb7tzsv2YkQTRBStInvKmmvdfqRD+FhUC8w9CiLap3uTVM/kGymv8mwpt0PjEW5ecwume46Q7nw7anGnRnRumM5bg7HlLuGyxf5mNK8EIR+g4/wbM9jk46d6GXYKoFNd1sNN9hNq90aBZ+xQIlfZ4J7AJ5T2+Uwgx6SKMEGI+8P+ARcBTUsrpFoTX1AjTMPn/zriUeYl2cqUi2WJj7DhJFwsUbJu58XY+d8Yb68JBMh6ps64hPGsxmCGc3FibspofJzuIGY6qfcVnvC0QGyoSQimli9oyVwDeCGwWQnxLCLFaCHGkbSGEKYQ4VQjxdWA9cDFqK94nK+lf4z/Lu+Zz9QmvY14ixeH8ME6dj1oc16U7N8y8RIr3rzibJe1zgjZpQsxonI7zriPUPhcn3dNyo0LXdXHSvZjtc+m44AaMgNLAVTwGlVI+C7wTGECFwvwV8CRgCSEOCSEOobzL64GvAfOBQeCdUspNlfav8Z8Pn/wGjk/NJmKG6r7YU18+QywU4cTOuVy7YlXQ5kyJ9nPeS7hzAWC0XDIGJzcIZojI7MW0nXl1YHZUZTIupXwAWAn8GFWbxPDanuc9TO+1EvAL4DQ9JW4ckpEonzrtIuYl2hkoZLHs+nScFOwSg1aOeV7MYNA7SKaKGU/Rvvr9hFJzsFtorbA8Ggy1z6X9vOswA3RoVW0cKqU8DHxWCPFF4DJUAacFKBHsQY0I79f1jhuTi49dwbnHLGXYytOdH+bYZGddrb253pR4VryNi45dzhsWnBi0SdOiffW1DD15K/ZwtypYFJuy77FhcT0HXLhzAe3nBFv00o9U/RmUE+XOaretCQ7DMPjc6ZewoWcfWwe7yZQs3+oAz4R0sUDJdTgm0c6nT7s4aHOmTchLOTU4eBA73YvZ5ELoui52updQag7t57wv8PerU/VrpsyiVBfvXX4W8xIpunPpunGcOK5Ddz7N/EQ7HzzpnIYtQtVx3ocw22bjFvM4xeYuBu9aOXCKhNrn0f6Ga4M2RwuhZnq8f8UqTuiYQyxUP46T3nyWRDjC8s75vhZq95vwrGNpO+3NhNq6cNLNvYKkUm3Nou11byOUmh20OVoINdMjEY7wqVMvYq7nOCkGvOPEsksMWTnmxpWDpNGr8LWf9yFCydk4+SFcu7ETXoyHW7JwChlCyVl0nHdd0OYAWgg1M+D8hctYNX8JKy2PlAAAIABJREFUnbEEPblgd5x0exXpLli4jFXHLAnUlmoQW3QKsaVnqRRd2YGgzfEFlWqrk8RJFxKZd0LQ5gBaCDUzwDAMPn3aRcyNp8jZRbIB1TjJFAtYdom5iRSfPPWiQGzwg/bVHzhS16TZQmlcx/FSbc2iffX7gzbnCFoINTPihI65XLX0dObE2+jJ1b7GSbki3dx4ined+HoWpZonrWVy5aWE5x7vVbtrrm13Tm4QM5ogMu9E4stqW051IrQQambMdeJcjkl24ALDNS5ENGTlMQxY2NbJBxpkB8lUMUJhUmdd7Y0Km2t67GQHMJNdtK96dyDJFcajfizRNByzYkk+sGIVc+MpevO1C6dxXJfeQoZ58XY+JFbTHo3XpN9aknr9O1W1u2Iet0nKqzrFPNhFQm2zalK0fTpoIdRUxDUnvp7j2mcRMUMM1SiB60AhSywUZmnHHN629LSa9Flrwl0LSKw4HzPRPE4TNRrsJHHyJYTaZgVtzmvQQqipiFgozAdPOoc58RR9hazvo0LbdegvZJkTT3G9WE3EDPnaX5C0vf7thJKdqtpdgztNXNfFyQ1hJjpJnfmOoM05Ci2Emop5y/GneEHWYQZ9HhUOFHIkw1FO6prPpYtrV+UsCJLiYkLt88AwcK36CF6fKW4hjREKE+5aSHzZ6qDNOYrGjj6tAkKIJPBl4FrgBGAYeAH4vpTynhm2eTwq5dhbUWnHuoE/ATc1Y+qxiBnigyedw46hXg5kB+mMJjB9SMjguA4DhSyLU7O47qRzMY3m/h43wlGSp15OsWenGk018P7j8mgwedoVGHU4im/uv6RJ8MoLPAh8HTgReAnIAG8B7vYSyU63TQG8CHwcSAHrUHVdbgBeFEJcUR3r64tLFwuWdMwmFgr7tlY4UMiRCEc5sXMuFx67zJc+6o3kaW9WwdX5xq0m6LoOTj6Nmeig7bQ3B23OmLS0EAI/AFYDa4FlUsqzpJRLgA+jcid+Qwhx+VQbE0KEUTWc5wC/BBZKKc8BFgL/ihLE/xJC1Hfa5BkQNkO8d/nZzIol6S9kq/6hdVyXASvH7LjyVDf7aLBMfOnZhLuOwTDDDTs9dvMZjHCMyOzFRBfXp3OrNf6axkAIsQy4HnCAD0kp95TPSSl/Cfyj9/Qb02j2emA5sBv4hJQy57VnAX8BPIbK4v35Su2vR95y3EoWJjsJGSbpKscVDhfzRMwQi9pmccmi5l4bHIlhhkiIN2ImUjgNmr3ayQ9jJlIkV15WVzksR9KyQoiaqoZQBaReHuP8Ld7xAm/Nbyrc6B1/6YnfEbz6Lj/2nn5wmrY2BNFQmKuWnk5XLFnVWsiu6zJQyDErluTqE88gXIdrTH6SPPmNmLF23AacHruui1NIY8bbSZz8xqDNGZf/v70zD5bkqu70dzOzMrPqLb13q9Xdr1u9nZbUUmtthCQksYzFICPCMBAGC5AxAi+AZ+yYgTEaGxvLhGJssIUZ2yxjzVg4sFhsEMYOjA1MgANZyGALBi4IkBAgDNKApO5+79WSOX/crFbpqape1euqrCXPF/Eia8m8dUqd+tU595x7bpGFsLm+5zPt3rTWfhe4P3u66r9gtlnV0W5j8vgezntFZFePdk4U1+w5zIaoQi1psFQfTPeUxUaNJE3ZGM9w9cLZAxlzkoj3HsXL6u7Ser4reE6VtLqI8Xz8ua1EC0dGbU5HiiyE+7PjN7qcc1927CUW2wGUVxnzAaDZt2oq47sN8QxX7DjAfBjzaHUwzUUfrS6xLox5xk6ZylUkq2GCkHjvxZho9mR7+0khXT6GF81S3n/JWGaLmxRZCLdmxx92Oefh7Ljqfs0t43Uc01rbwO3g1+uYE8nVC2cxH5Z5rLZEkianNFYjSThWW2Y+LPPs3cXzBpuU91+KF82QLE+WECbLxzDxDPH+8Wmw0I4iC2ElO3ZzW5oTXZUu56wcb5BjTiTnbNrB7rmNRH7plJMmj9WWqQQlDqzfyoF1W1e/YEop738qXjRDWl0iHXEz3F5JG3XSehUvrFDed8mozelKkYWwn7uplxnqfu/OyZr17gNjDM/adSZzYcxj1VMVwiXmwphn7jo0thnHPAg2nE6waQFTiiemjCatHscLK4TbZSza8XejyELYjDG6TTo15/x6ufNaY5ZBjTmxXHn6AWZLEYuNGvVkbeFxLWmw3KgzW4q54vQDA7Zw8oj3HsWLKiRjslfMaiTLJzBRhXjv+C2pW0mRhfCh7NituLk5j/eDPsbrOGZWcL2ujzEnltNn13NowzYqQcjxNYbHx2rLzJRCztm0g83l2QFbOHnEZ1yEiWZIq8dHbUpPpMvH8cIZ4jMuHLUpq1JkIWyu+d3T5Zzme19bbTBr7fd4PBHSacxduNrFnsacdC7bvo+ZUsTxNZZ8HK8tM1uKuHT7ZG3WPiziPRfihWXSenXs5wnTRo00aWCiCtHCeaM2Z1WKLIR3Zse26SwR2Qk0C6n/sccx/6nbmMCl2fH+TDinmou37WGmFHKiXuu7PVcjTVhq1KgEIUe3jccGP6PGn91IacveiZgnTJZP4IVlwu2HJqJZRJGF8P3Z8aqsUcJKfj47ftpae1+PY96eHX9WRMIuY97a43gTzZ65TWyvrCP0fRb77LJ8olYl9kvsmd/M6TPrVr+gIES7z8cLx3+eMK2ewIQV4t2Tsc90YYXQWvt14M9xoeqHRKRZYI2IXAe8Pnv62yuvFZF9InJIRLaveOs2XDH1XuDPRWQuOz8UkVuAy3Hh89sH/X3GEWMMF2zZRSUIWexzlclio0Y5CDl/81QuwFkz0cIRTFgZe48wrZ7ACycjLIYCC2HG64B7gLOAr4rIF0TkPlznmAB4o7X2E22u+3vcHONbWl+01i7h1hE/ArwA+J6I3AU8CLwWqAI/Za19mIJwzuadlP2w7y0/F+tVKkHIuZt3DMmyySTefX42T7hMusZs/LBJkwZpo4YJy2O9rK6VQgthJkhPBX4Tl7w4E5fx/TTwAmvt76xhzLuAI8B7gB9njxPgg8BTrLWfHIz1k8G5m3ZQDkosJ/WeV5nUk4RakhAFAYc3qRC24q87DX/9aRg/JK3ls0dMv6TVE5hSTGnLnrHbm6QThe9Qba09jmu19aY+rtmzyvv3A688Fbumhc3lWbZV5nng2I9YatSpBO2mTp/IcqNG5AcszG5kvoBri7thjCHadYTqA/9KWl2EMUxEJNVFFxbvmgxvEAruESr5cGD9VmI/YLlR7+n8pUadyA84sL64S+q6ES8cwZTGd57QJUrKRAvnjtqUnlEhVIbOwfVbiYISS43eEibLjRqxX1Ih7EC06wgmLJNUF8euP2GaJqS1JbywPDGJElAhVHLgjPnNRF5AtdFbEfByo0HkB+yb3zJkyyaT0mkH8CrrMJ43dv0J09oSxi/hz20m2Dg5GX8VQmXo7JrbSOj71JL6qh5MkqbU0wYlz2fX3GRMtOeN8XyinedkZTTjlTBJq4uYsEK067yJapKhQqgMna3lWSpBiGc8aqssDasldQLjsy4qsz6a2k5lp0y0cMSV0YzZPKGrH5ycspkmKoTK0PGMx/aZdZQ8vwchTAh9nx0z63OybjKJF847WVg9LvOEaZqSND3C3ZMzPwgqhEpObKvMZ0LYvZawljQIPJ+tlbmcLJtMwmZonCTQYxJq6NSXMRi88jzhae1WrY4vKoRKLmwrzxN4HvVVPcIGJeOxrTyfk2WTiRfGRDvPduuOxyQ8Tqqu/2C061yMP1klyiqESi5sLs8QGJ/6KqtLGklC4Pnaf7AHooXzMdH41BOmy2598aQ0WmhFhVDJhQ3RDIHn0VglNK6nCb7nsVETJasS77kAL6yQjkEnGjc/mHWkPuOiUZvTNyqESi6sjyr4xuvNIzSeZox7IFo4z3mESYO0z6YWA6dexYCbHzz9rNHasgZUCJVcmA9jfM+s2nihkSZ4xuga4x7wogrRzsNuH5MRh8fJ8nFMNOPEOSiN1Ja1oEKo5MJsKcIzHo0upR5pmpKkKb7xmFUh7ImT+5gsj3Yfk7R6HC+aobz34pHasVZUCJVcmC1F+MaQpmnHureEFIzrsDLTQ5caBeK9T8ELZ0iWj4+snjBNU7djXVghOkOFUFE6UglCDAZjTMf9S5I0xcNQ8nzCCSu/GBXRzsNu3bExI1t3nFYXMX6AP7dl4uoHm6gQKrngex6B52PIPL82pGmKZwyximDPmCAk3nPhSMPjdDkLi/cdxXiTKSmTabUykcR+gJeFx+1I0tQ1HvUnb7J9lJT3X4IXzZIsHRvJ5yfLxzDRDPG+8d/IvRMqhEpulPzAhXCdPELAYAh9v+37Snvi/ZfiRTOktcXc9ztOG3XS+rLzCPdfuvoFY4oKoZIboedjMHSa009JMQZKngphP5Q27SLYvNvtd5xzcXWyfBwvrBBuP4Q/tznXzx4kKoRKbvjGW3WO0GDwJ3SeaZSUD1zmwuPlfMPjdPkYJp6lfOCyXD930Ogdp+RG4HmwSq9OAwRGb8t+KR+8HC9284R5ldGkaUqydAwvmqV88PJcPnNY6B2n5IbzCA0dHEI3R2gMvgph38S7L8Cb2YAxrl1+HqTVExg/IFi3lXDH2bl85rDQO07JjWbr9k7JkpXnKb1jghLlfZfgxXOkOWWPk6VjePEc8f7LJrZspslkW69MFJ4xXSPjZkjnqRCuibJcgYlnSZYfG/pnpWlKuvQYXjxL5dAVQ/+8YaNCqORGr/LWXS6VTjQTJmm9NvxuNPUqpAleeR3x3smtH2yiQqjkzmpT+SqDa8OfWU+8+3y8aGboxdXJ0mOYeJZ478V4U9AyTYVQyQ3n6XWXORXBU6MsV+CV50iWhhseJ0uP4cVzlA9dOdTPyQsVQkWZIspnXuXC4yGuMkkbtWw1ySwVmfz5QVAhVJSporRhB+FpB92mTkMKj5u1g9HCufizm4byGXmjQqjkjoa/w6V86Eq8eJZ0SOFxcjJbPB1hMagQKsrUUT50JSaey5q1dt8aoV/SpEFaPZHND1410LFHiQqhMlaMpsfydBFuP0Sw4XRMEA68R2G6fByvVKa0dR+lTQsDHXuUqBAqY4VBV5acKsYYKoeuOrn2eJC4spnpyRY3USFUcke9vuFTlivwYldGM6gmDCebLMTTky1uokKoKFPI400YvIE1YXBNFkoE67ZNfJOFlagQKrnR2xpiXWA3CExQckvuBpg9bmaLywcvn/gmCyuZrm+jjDXGuL9OpCfPUykcBOWDl2dNGE59ntA1WTiWCeHTBmDdeKFCqORIbwKnMjgYys29TOo10kbt1AarV0nTBK88T7z36GAMHCNUCJXc8FbtR5hiAE8bsw4Ef2Y90a5z8aJTX2WSLGerSfZcOBVNFlaid5ySG15z/q9Lh2qM9iMcJM4rnD3lesJk+ThePEP5wOTuVNcNFUIlN9ymTKZz+Uz2hgrh4IgPXJrNEx5fcxlNmiRuNUk0M/GbNHVChVDJjeYudp1cwua+xrpnyeAITxOC+S0YPyCtLq5pjLR6AhNEBBt3EWzcNWALxwO945TcaO5i13mG0M0RBlNWmjFKjOcRn3HUJU3WGB4ny8fxohnifZdMbUZf7zglN5q72HWL0HQXu8ET7zuKiWZI1iiEaSaE5X3Tly1uoneckhuB50LjTlljt8G7eoSDJj7jYrywQlpbIk3660aTNuqkjSomrBDtuWhIFo4eveOU3Ch5ftfQqrmvcckL8jOqAATrtxNs2oUpRaTVE31dm1ZP4IVlwu0H8SvrhmTh6FEhVHIj9AIMhqRDbOw8QkPo+TlbNv3Eey5ymzr1KYTJ8gnnDe6+cEiWjQcqhEpuOI+wS2icJUtCXz3CQRPtPg8TltfoEVaId583JMvGAxVCJTdKvp8lSzp5hM3QWD3CQRMtnOfmCatLPXetTpNGNj9YJlpQIVSUgRD5AZ7pXFCd4ELjyFchHDTBhh3481swQanntlxpddHVD25awJ/dOGQLR4sKoZIbsb/6HKFnDJFfytmy6ccYQ7TjcBYe91ZYndYW8cIy0c5zhmzd6FEhVHIj8kvOI+wghAmp+x9W5wiHQrjzMF6pDyGsLrqweOd0NWFthwqhkhuxH2CMIelSR+ihQjgswh1nYcK4p9A4TVOS2hKmVJ66btTtUCFUciMOSnhdkiVJFhqXgzBny4pBuP0QJohdkXTS6H5yUoc0xZQiwm0H8jFwhKgQKrlR9kM802WOkBRjoKxzhEPBL88TbNzhCqtX8QrT2hKmFBNu2YspwA+TCqGSG3HQPTRueoRxoEI4LMJtBzMhXO56XlpbxitFlE47mJNlo0WFUMmNctDdI0zSFA+PSgE8kFFROm2/C4/rPXqE2/bnZNloUSFUciPukjVO05QkdVnjONBkybAIt+7vzSOsL2OCkJIKoaIMlkqWLEnS9Eli2HzmGaMe4RAJNu/BBCFpvdplhU9KWq9igojSlr05WzgaVAiV3CgHoes+02a9cdMbNKDlM0OktNF1oQFcZrgd9SrGC/DiOfz5rfkZN0JUCJXcaC6x89qsLknSJCudKekudkPEBCVKG3ac9ArbkTaqmCAk2LQwtR2pV6J3nJIbJgt72yVMEpoZYw2Lh02wcaG7ENarEISUNk3n/iTtKHwMIiKHgRuBpwPrgQeBjwE3WWu/u4bx3gT8xiqn/Sdr7e/3O/Y0UMnC4yd7hE4IZ1QIh05p0+pCaIKQYOPOnC0bHYUWQhF5GvBxIAYeAu4BBPgF4KdF5BnW2i/2OeyR7PhV4OEO5/QtsNNCOSjhG+9JtYTN0pmy1hAOnWDD6Ri/RFprv+l72qjhRTMEG3bkbNnoKKwQishG4MM4EbwZuNFaWxeROeBPgRcAHxSRM6217X8629MUwuuttXcO1OgpYKbUITTOPELNGA8ff30mhI1a+xMaNUxQKpQQFnmO8HXABuBz1to3WGvrANbax4CXAN8E9gIv63VAEZkH9uCqQb48aIOngdgP27biarbgqjQzmsrQCDbsgCAkbTz59z1NU9JGDeOHBOu2j8C60VBkIbw+O75n5RuZB/g/s6cv7mPMcwED3GetbR93FJzHkyVP7JLcTJZoaDx8gnXbMF4ASfLkXe2azRj8oDClM1BQIRSR7cDu7OlnOpz22ex4mYj0+n9nMyy+Z622TTuVUqlDaJxoaJwTXjSDF89h/ABWhMfOGyzhz2127xeE4nzTJ9JcN5QC3+pwzn3ZMQIWgG/0MG5TCL8sItcCz8OFyseAO4F3W2t/sAZ7p4aTHWjaJEt8o+uM88JftxX8EmlSx9AyHdGoY/wSwVxxvEEoqEcINP+VH7XWdlp02Zrx3dzjuE0hfA0uEfMK4BnAtcBNwL0i8rw+bZ0qmgXT7ZMlHnGBvJBR4s9twXjBkxImaVIDr1hhMUyBRygitwIv7+OS84FK9rhbC47WfuaVjmc9bocHHG4Z91dwYvgocB7wJuDZwPtF5OnW2s+2G2faqQRh2+aszSV26hHmQzC3JQuNVyyza9QxfoA/1+tv/3Qw8UK4RlZpz/skOm281koZ+H1cKPxma+1XW967U0SuwRVqXw28FXhKnzZMBc4j7LyyRJMl+eDNbgIvIF2x3jhN6phSjD+7aUSWjYZpEMJX40LRXjmBm/MDV0PYifKKa7pirT0OvLHL+4mI/BZOCI+KyI61rFyZdE72JGxbUK1t+vPCn92I8QOSxUeoP/L9k6+nyyfwoln1CCeNbI6ve3O1FYjIQ9nDOREpWWvbVZa23gmDSnB8oeXxHgq4wuTkBk4d6ghjbdOfC8GGHZiwjFdZ94TXzcx6TCkmWH/6iCwbDRMvhGvkK9nRo3NGeE92XAIe6HVgEYmttZ3mHluTUx3K+qebThs4Nbfy1NA4H8oHLmPTtW+k8diTV4H681uJdl8wAqtGRyGF0Fr7IxH5OnAAeCrthfDS7HintXbVOUUR+Xnc3N+SiGzpcE3z7moAtn/LJ59ml+qVoXGq+5XkivF85o6+aNRmjA1FLZ8BuD07vmrlGyIS4kpfAG7tcbx/xs0rbsDVD7bjv2THv7XWPtLjuFNFOShh2rTrb84RalNWZRQUWQhvAX4MPE1EbsnEj6zpwntx64y/mT0+iYhURORQ9neyrMZa+0/AP2RP/0REntlyzZyIvBP4SVyo/fohfq+xJvJLbRuzpllorHOEyigorBBmKzxeClSB1wIPishduATGf8CJ5LVtEilHcXOMX8ket/IS4Eu4RMsnROTbIvJ54PvADbjs8/OttYVtyBD5AWZFq/40TUlT8Iy26VdGQ2GFEMBa+1HgIuAvcMmL83DL4f4XcGG/gmWt/TecOP5n4PO4MPkwrtnrO4AzrbV/M7AvMIFEWdY4TTkZHqekrlUFhlCFUBkBhb/rrLX3AD/dx/mfIvvftsP7i8DvZn/KCkI/wPD4Bk7NllwGg2cMoeeP2kSlgBTaI1TyJ/R8DGQC6F5L4aQIFmWzIGW8UCFUcsUYQykTvOY8ofMI0bBYGRkqhEruRH6AxxPnCI0xhJ4KoTIaVAiV3Ck1EyaZR5imLlQOfZ0fVEaDWVnYqow/IvJoGIZzCwsLq588hnz32I9ZbNQIjHeyuLqRJpSDkNNn1q0+gKJ04N57773DWnttv9dpLDKZnKhWq9x77709r4EeJ5L58k4Cf6aa1utZ6tjDGP/Y0rFj9z74w8I1olBGj3qEiqIUHp0jVBSl8KgQKopSeFQIFUUpPCqEiqIUHhVCRVEKjwqhoiiFR4VQUZTCo0KoKErhUSFUFKXwqBAqilJ4VAgVRSk8KoSKohQeFUJFUQqPCqGiKIVH+xGOKSKyB/hWh7dT4EfAt4G/Ad5mrf1hTqYNDBG5HvhT4LvW2p0tr38KuBK4yVp742is646I3Aq8HPi0tfaqEdnwauCPgRuste/u47pfAv4Q+Flr7a19fmaA2/oW4KXW2ttWOf+VwLuAhrV2bPVmbA1TnsCXgEdangc8vmfyecANIvKMbGtSpQCIyMXAf1/DdU8Bbh68RZONCuFk8NpsP+UnICKbcJvRXwN8QETOtNYmeRs3BF4GVICHRm3IOCIiVwEfAub6vO6ZwAeBmSGYNdGoEE4w1tqHReTlwHeBg8BPAH87WqtOHWvtt0dtwzgiIjHwBuBGoOedrkSkDPxa9qd5gTbof5QJx1r7MC50BhcqK1OIiOwHvgb8RvbSjcD9PVwn2XU3AgnwX3E/nEoL6hFOB6Xs+NjKN7LJ7RcDLwIuADYBdeB7wD8Ab7XWfq3NdVcDvwRcgpuPfAQnuLcD77bWVttcMw/8MvB8YD/uh/abuDDubdbaH/fyZdolS1qSR/8GbAdeAbwKOCu77EvAO4FbrbVP2ohnULaNkJ3ALuBzwGustXeLyA09XLcru/Yfs+u+ICKvGaKdq7Ii4bIa77HWvnKY9oAK4cQjIvtwnmDCirA4C4n+Gnh69tJ9wD3ANuBA9nediDzNWvuFluteB/xB9vR7wBeBzThxuhJ4oYg8y1rbaLnmEC6DvQdoAN8AFoGzgV8HXi4iz7bWfvUUv7LBzYu+FPgxztvZixPsSwDBhY+t/x3ysm2YfAe4xlr7sT6v+zbw76214zRlkgKf7fL+Zty/I/Tg9Q4CFcIJRER8YD1wKfC7OO/mJmvtypvm9TgRfAh4jrX2rpYxLgY+jPOufg14Yfb6eh7PKr7YWvu+lmt+Avgr4Krs/Pdlr88Ad+CE5sPAL1prv5e9dxrwblxC5yMicsRau3gKX38r8BKcd/cOa20jmzt7F3Ad8Ksi8nvNcqKcbRsa1tp7gXvXcN3XcD8WY0P2A3p5u/dEZA74TPb048Dv5GGTCuFk8Ek31dORm4H/1ub1Z+E8xd9sFUEAa+1dIvJHwG8B57S8JUCMq1P8ixXXfFxE3gKcC7SGxq/EhZv/DLyg1VO01n5fRF4IfAXngV4P/FG3L9MD/8Nae0vLZyyJyH8EfgZ3Tx/FecKjsK1I/JmI/NmgBstC5vfj7q+vAC9q/fcaJposmQy+hAslmn+fA74MLGfv/wpwS+YpnsRaezlO1P64w7gnsmOl5bVv4eYQNwC3isiRFWO+2Vr7Qmvth1pe/qns+L52N27mZX0ge/rcTl+yD+5o8xkPA82i8vUjtK1IfI0n3pft/vrxYt8BXA08DPyktfaRVc4fGOoRTgad6ghDnBfzh8BrcCUVv9h6jrW2JiIbROQSXInN3ux4Pm6uEFp+EK21PxCRm4E34ur5XiYi3wf+HheqfMxau7K+r5mtvkFEntfhO5yWHQ+t+m1Xp1PWsxnWtt7XedtWJN7cx8qSrojI63HJryrwfGvtNwdjYm+oEE4wWeb2nSKyHXgT8CoReYu19gE4Od/yB7i5s1LLpVVcqPgF4Nltxr1RRO7GiesVOKH4meyvLiLvw2Ugm7/Y67JjMwHTjfWrvN8LT8pYr8C0PM7bNqVPsumJt2RPX22t/T9526BCOB18GCeEPs7Te6Dl9afjPKW383hI/fXMU7yBNkIIYK39S+Avs7KTK3EJkufgvKbrcAJzbXb68ez5c621Hx3wdztVxtm2wiMiTwX+N+7H6+Z+1z4PChXC6aB1WZ0ByELhZtnMNdbaT7a5bufKF7KSmwOAsdb+i7X2Udyc3B24jOwbcL/ezxWRdZlXaHEJirOBtmIjIgdwgnR/zg0ixtm2QpOVfn0EN4/9V7hi75GgyZLp4JrsmAJ3Z4/PaHn/blYgIhVcoTU88QfxVcC/ALeJiFl5HfB3LY+byZlm8uKVmZCu/KwA553ehSv3yZNxtq2wiMhG4GO4msEvAte1K4TPCxXCCUZEjIg8H5fYAPiAtfY72ePW4uBfF5FSy3Vn4QqMm3NmrVnj23FzcIeBt2V1eM3rNgM3ZU/vtNb+v+zxO4AHcWUqHxGRhZZrtmRjnpmNm7fYjLNthUREIpwHeBBX5P8ca+3xUdqkofHtkjBhAAABbUlEQVRk8HYRWVlKUMIVCW/Nnt8N/ELzzWwp1e24pXW/ClwvIt/CLbFreot/B/w7YE5E5q21j1prHxSRVwC34YqWf05EvoG7V/bhwpiHgJ9r+awfici1OO/rWcC3ROT/4kJ2ASJcSc6L824VNs62FZhfBp6WPX4IeFf2g1tqc249j36PKoSTQbtmCku4urmP4lor3Watra845yXAJ4AbcB7RkeyaO4A/sdb+tYjcDyzgaujeC2Ctfa+IfAeXNb4Et553Gfh69nlvXVlCY639vIgcBl6HS6Lsx4nMg8CngN+z1v7rKfw3WDPjbFtBmW95fNEq5+ZSUG3SdGRhuaIoyligc4SKohQeFUJFUQqPCqGiKIVHhVBRlMKjQqgoSuFRIVQUpfCoECqKUnhUCBVFKTwqhIqiFB4VQkVRCo8KoaIohUeFUFGUwqNCqChK4VEhVBSl8KgQKopSeFQIFUUpPCqEiqIUHhVCRVEKz/8HfNGo7vFOeo8AAAAASUVORK5CYII=\n",
-      "text/plain": [
-       "
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-      ]
-     },
-     "metadata": {
-      "needs_background": "light"
-     },
-     "output_type": "display_data"
-    },
-    {
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\n",
-      "text/plain": [
-       "
"
-      ]
-     },
-     "metadata": {
-      "needs_background": "light"
-     },
-     "output_type": "display_data"
-    }
-   ],
+   "outputs": [],
    "source": [
     "\n",
     "for key, dd in stuff.items():\n",
@@ -3459,55 +2573,9 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 34,
+   "execution_count": null,
    "metadata": {},
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "U-test: U value 4696.0 p value 0.0009136914115846572\n",
-      "U-test: U value 2276.0 p value 0.019967404084342423\n",
-      "U-test: U value 1192.0 p value 0.09642850317783999\n"
-     ]
-    },
-    {
-     "data": {
-      "image/png": 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\n",
-      "text/plain": [
-       "
"
-      ]
-     },
-     "metadata": {
-      "needs_background": "light"
-     },
-     "output_type": "display_data"
-    },
-    {
-     "data": {
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\n",
-      "text/plain": [
-       "
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-      ]
-     },
-     "metadata": {
-      "needs_background": "light"
-     },
-     "output_type": "display_data"
-    },
-    {
-     "data": {
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\n",
-      "text/plain": [
-       "
"
-      ]
-     },
-     "metadata": {
-      "needs_background": "light"
-     },
-     "output_type": "display_data"
-    }
-   ],
+   "outputs": [],
    "source": [
     "for key, dd in stuff.items(): #TODO narrow broad spiking\n",
     "    baseline = dd['base']['speed_score'].to_numpy()\n",
@@ -3531,27 +2599,9 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 35,
+   "execution_count": null,
    "metadata": {},
-   "outputs": [
-    {
-     "ename": "TypeError",
-     "evalue": "unhashable type: 'numpy.ndarray'",
-     "output_type": "error",
-     "traceback": [
-      "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
-      "\u001b[0;31mTypeError\u001b[0m                                 Traceback (most recent call last)",
-      "\u001b[0;32m\u001b[0m in \u001b[0;36m\u001b[0;34m\u001b[0m\n\u001b[1;32m     13\u001b[0m \u001b[0mdata\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mbs\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mdata\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mbs\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mastype\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mbool\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m     14\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m---> 15\u001b[0;31m \u001b[0mdata\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mloc\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0mdata\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0meval\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m'not t_i_peak.isnull() and not bs'\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m'ns_inhibited'\u001b[0m\u001b[0;34m]\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0;32mTrue\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m     16\u001b[0m \u001b[0mdata\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mns_inhibited\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mfillna\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;32mFalse\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0minplace\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;32mTrue\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m     17\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n",
-      "\u001b[0;32m~/.virtualenvs/expipe/lib/python3.6/site-packages/pandas/core/frame.py\u001b[0m in \u001b[0;36meval\u001b[0;34m(self, expr, inplace, **kwargs)\u001b[0m\n\u001b[1;32m   3313\u001b[0m             \u001b[0mkwargs\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m\"target\"\u001b[0m\u001b[0;34m]\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   3314\u001b[0m         \u001b[0mkwargs\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m\"resolvers\"\u001b[0m\u001b[0;34m]\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mkwargs\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mget\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m\"resolvers\"\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m)\u001b[0m \u001b[0;34m+\u001b[0m \u001b[0mtuple\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mresolvers\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 3315\u001b[0;31m         \u001b[0;32mreturn\u001b[0m \u001b[0m_eval\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mexpr\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0minplace\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0minplace\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m**\u001b[0m\u001b[0mkwargs\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m   3316\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   3317\u001b[0m     \u001b[0;32mdef\u001b[0m \u001b[0mselect_dtypes\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0minclude\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;32mNone\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mexclude\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;32mNone\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
-      "\u001b[0;32m~/.virtualenvs/expipe/lib/python3.6/site-packages/pandas/core/computation/eval.py\u001b[0m in \u001b[0;36meval\u001b[0;34m(expr, parser, engine, truediv, local_dict, global_dict, resolvers, level, target, inplace)\u001b[0m\n\u001b[1;32m    325\u001b[0m         \u001b[0meng\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0m_engines\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0mengine\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    326\u001b[0m         \u001b[0meng_inst\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0meng\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mparsed_expr\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 327\u001b[0;31m         \u001b[0mret\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0meng_inst\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mevaluate\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    328\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    329\u001b[0m         \u001b[0;32mif\u001b[0m \u001b[0mparsed_expr\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0massigner\u001b[0m \u001b[0;32mis\u001b[0m \u001b[0;32mNone\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
-      "\u001b[0;32m~/.virtualenvs/expipe/lib/python3.6/site-packages/pandas/core/computation/engines.py\u001b[0m in \u001b[0;36mevaluate\u001b[0;34m(self)\u001b[0m\n\u001b[1;32m     68\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m     69\u001b[0m         \u001b[0;31m# make sure no names in resolvers and locals/globals clash\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m---> 70\u001b[0;31m         \u001b[0mres\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_evaluate\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m     71\u001b[0m         return _reconstruct_object(\n\u001b[1;32m     72\u001b[0m             \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mresult_type\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mres\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0maligned_axes\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mexpr\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mterms\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mreturn_type\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
-      "\u001b[0;32m~/.virtualenvs/expipe/lib/python3.6/site-packages/pandas/core/computation/engines.py\u001b[0m in \u001b[0;36m_evaluate\u001b[0;34m(self)\u001b[0m\n\u001b[1;32m    116\u001b[0m             \u001b[0mscope\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0menv\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mfull_scope\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    117\u001b[0m             \u001b[0mtruediv\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mscope\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m\"truediv\"\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 118\u001b[0;31m             \u001b[0m_check_ne_builtin_clash\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mexpr\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    119\u001b[0m             \u001b[0;32mreturn\u001b[0m \u001b[0mne\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mevaluate\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0ms\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mlocal_dict\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mscope\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mtruediv\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mtruediv\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    120\u001b[0m         \u001b[0;32mexcept\u001b[0m \u001b[0mKeyError\u001b[0m \u001b[0;32mas\u001b[0m \u001b[0me\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
-      "\u001b[0;32m~/.virtualenvs/expipe/lib/python3.6/site-packages/pandas/core/computation/engines.py\u001b[0m in \u001b[0;36m_check_ne_builtin_clash\u001b[0;34m(expr)\u001b[0m\n\u001b[1;32m     25\u001b[0m         \u001b[0mTerms\u001b[0m \u001b[0mcan\u001b[0m \u001b[0mcontain\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m     26\u001b[0m     \"\"\"\n\u001b[0;32m---> 27\u001b[0;31m     \u001b[0mnames\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mexpr\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mnames\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m     28\u001b[0m     \u001b[0moverlap\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mnames\u001b[0m \u001b[0;34m&\u001b[0m \u001b[0m_ne_builtins\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m     29\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n",
-      "\u001b[0;32m~/.virtualenvs/expipe/lib/python3.6/site-packages/pandas/core/computation/expr.py\u001b[0m in \u001b[0;36mnames\u001b[0;34m(self)\u001b[0m\n\u001b[1;32m    852\u001b[0m         \u001b[0;32mif\u001b[0m \u001b[0mis_term\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mterms\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    853\u001b[0m             \u001b[0;32mreturn\u001b[0m \u001b[0mfrozenset\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mterms\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mname\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 854\u001b[0;31m         \u001b[0;32mreturn\u001b[0m \u001b[0mfrozenset\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mterm\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mname\u001b[0m \u001b[0;32mfor\u001b[0m \u001b[0mterm\u001b[0m \u001b[0;32min\u001b[0m \u001b[0mcom\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mflatten\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mterms\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    855\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    856\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n",
-      "\u001b[0;31mTypeError\u001b[0m: unhashable type: 'numpy.ndarray'"
-     ]
-    }
-   ],
+   "outputs": [],
    "source": [
     "stim_action = actions['stimulus-response']\n",
     "stim_results = pd.read_csv(stim_action.data_path('results'))\n",
@@ -3567,10 +2617,10 @@
     "\n",
     "data.bs = data.bs.astype(bool)\n",
     "\n",
-    "data.loc[data.eval('not t_i_peak.isnull() and not bs'), 'ns_inhibited'] = True\n",
+    "data.loc[data.eval('t_i_peak == t_i_peak and not bs'), 'ns_inhibited'] = True\n",
     "data.ns_inhibited.fillna(False, inplace=True)\n",
     "\n",
-    "data.loc[data.eval('t_i_peak.isnull() and not bs'), 'ns_not_inhibited'] = True\n",
+    "data.loc[data.eval('t_i_peak != t_i_peak and not bs'), 'ns_not_inhibited'] = True\n",
     "data.ns_not_inhibited.fillna(False, inplace=True)\n",
     "\n",
     "# make baseline for inhibited vs not inhibited\n",
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+++ b/actions/comparisons-gridcells/data/figures/average_rate_11.svg
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--- a/actions/comparisons-gridcells/data/figures/burst_event_ratio.svg
+++ b/actions/comparisons-gridcells/data/figures/burst_event_ratio.svg
@@ -1,3 +1,3 @@
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--- a/actions/comparisons-gridcells/data/figures/burst_event_ratio_11.svg
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diff --git a/actions/comparisons-gridcells/data/figures/speed_score_ns_inhibited.svg b/actions/comparisons-gridcells/data/figures/speed_score_ns_inhibited.svg
index 059b2901a..211cb8eca 100644
--- a/actions/comparisons-gridcells/data/figures/speed_score_ns_inhibited.svg
+++ b/actions/comparisons-gridcells/data/figures/speed_score_ns_inhibited.svg
@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:6457f2a66ef8e25d8dd68a4717b72f146a4b470b1f0967319bee0efe556e4e8f
+oid sha256:a7610de13da72ed4f24cf2f354e44bf6789f9e662bf04a3edd8b570c2f85c4ee
 size 31931
diff --git a/actions/comparisons-gridcells/data/statistics/statistics.csv b/actions/comparisons-gridcells/data/statistics/statistics.csv
index b97173750..881235946 100644
--- a/actions/comparisons-gridcells/data/statistics/statistics.csv
+++ b/actions/comparisons-gridcells/data/statistics/statistics.csv
@@ -1,19 +1,14 @@
-\begin{tabular}{lllll}
-\toprule
-{} &         Baseline I &          Stimulated &             MWU &          PRS \\
-\midrule
-Average rate            &   8.61 ± 0.75 (71) &   8.39 ± 0.60 (102) &  3599.00, 0.947 &  0.55, 0.764 \\
-Gridness                &   0.51 ± 0.04 (71) &   0.44 ± 0.04 (102) &  3208.00, 0.203 &  0.13, 0.141 \\
-Sparsity                &   0.61 ± 0.02 (71) &   0.66 ± 0.02 (102) &  4170.00, 0.091 &  0.06, 0.179 \\
-Selectivity             &   5.91 ± 0.37 (71) &   5.98 ± 0.37 (102) &  3460.00, 0.620 &  0.10, 0.869 \\
-Information specificity &   0.25 ± 0.03 (71) &   0.22 ± 0.02 (102) &  2944.00, 0.037 &  0.05, 0.033 \\
-Max rate                &  36.55 ± 1.78 (71) &  33.72 ± 1.31 (102) &  3291.00, 0.309 &  3.19, 0.195 \\
-Information rate        &   1.30 ± 0.07 (71) &   0.96 ± 0.06 (102) &  2385.00, 0.000 &  0.32, 0.000 \\
-Interspike interval cv  &   2.42 ± 0.10 (71) &   2.22 ± 0.08 (102) &  3034.00, 0.070 &  0.12, 0.392 \\
-In-field mean rate      &  14.43 ± 1.00 (71) &  12.94 ± 0.71 (102) &  3368.00, 0.436 &  0.39, 0.812 \\
-Out-field mean rate     &   6.05 ± 0.62 (71) &   6.12 ± 0.53 (102) &  3600.00, 0.950 &  0.08, 0.946 \\
-Burst event ratio       &   0.22 ± 0.01 (71) &   0.20 ± 0.01 (102) &  3090.00, 0.102 &  0.02, 0.124 \\
-Specificity             &   0.48 ± 0.03 (71) &   0.46 ± 0.02 (102) &  3268.00, 0.277 &  0.06, 0.356 \\
-Speed score             &   0.14 ± 0.01 (71) &   0.10 ± 0.01 (102) &  2546.00, 0.001 &  0.05, 0.000 \\
-\bottomrule
-\end{tabular}
+,Baseline I,Stimulated,MWU,PRS
+Average rate,8.61 ± 0.75 (71),8.39 ± 0.60 (102),"3599.00, 0.947","0.55, 0.757"
+Gridness,0.51 ± 0.04 (71),0.44 ± 0.04 (102),"3208.00, 0.203","0.13, 0.145"
+Sparsity,0.61 ± 0.02 (71),0.66 ± 0.02 (102),"4170.00, 0.091","0.06, 0.179"
+Selectivity,5.91 ± 0.37 (71),5.98 ± 0.37 (102),"3460.00, 0.620","0.10, 0.874"
+Information specificity,0.25 ± 0.03 (71),0.22 ± 0.02 (102),"2944.00, 0.037","0.05, 0.034"
+Max rate,36.55 ± 1.78 (71),33.72 ± 1.31 (102),"3291.00, 0.309","3.19, 0.194"
+Information rate,1.30 ± 0.07 (71),0.96 ± 0.06 (102),"2385.00, 0.000","0.32, 0.001"
+Interspike interval cv,2.42 ± 0.10 (71),2.22 ± 0.08 (102),"3034.00, 0.070","0.12, 0.398"
+In-field mean rate,14.43 ± 1.00 (71),12.94 ± 0.71 (102),"3368.00, 0.436","0.39, 0.817"
+Out-field mean rate,6.05 ± 0.62 (71),6.12 ± 0.53 (102),"3600.00, 0.950","0.08, 0.944"
+Burst event ratio,0.22 ± 0.01 (71),0.20 ± 0.01 (102),"3090.00, 0.102","0.02, 0.129"
+Specificity,0.48 ± 0.03 (71),0.46 ± 0.02 (102),"3268.00, 0.277","0.06, 0.360"
+Speed score,0.14 ± 0.01 (71),0.10 ± 0.01 (102),"2546.00, 0.001","0.05, 0.000"
diff --git a/actions/comparisons-gridcells/data/statistics/statistics.tex b/actions/comparisons-gridcells/data/statistics/statistics.tex
index b97173750..95e2dc5a5 100644
--- a/actions/comparisons-gridcells/data/statistics/statistics.tex
+++ b/actions/comparisons-gridcells/data/statistics/statistics.tex
@@ -2,18 +2,18 @@
 \toprule
 {} &         Baseline I &          Stimulated &             MWU &          PRS \\
 \midrule
-Average rate            &   8.61 ± 0.75 (71) &   8.39 ± 0.60 (102) &  3599.00, 0.947 &  0.55, 0.764 \\
-Gridness                &   0.51 ± 0.04 (71) &   0.44 ± 0.04 (102) &  3208.00, 0.203 &  0.13, 0.141 \\
+Average rate            &   8.61 ± 0.75 (71) &   8.39 ± 0.60 (102) &  3599.00, 0.947 &  0.55, 0.757 \\
+Gridness                &   0.51 ± 0.04 (71) &   0.44 ± 0.04 (102) &  3208.00, 0.203 &  0.13, 0.145 \\
 Sparsity                &   0.61 ± 0.02 (71) &   0.66 ± 0.02 (102) &  4170.00, 0.091 &  0.06, 0.179 \\
-Selectivity             &   5.91 ± 0.37 (71) &   5.98 ± 0.37 (102) &  3460.00, 0.620 &  0.10, 0.869 \\
-Information specificity &   0.25 ± 0.03 (71) &   0.22 ± 0.02 (102) &  2944.00, 0.037 &  0.05, 0.033 \\
-Max rate                &  36.55 ± 1.78 (71) &  33.72 ± 1.31 (102) &  3291.00, 0.309 &  3.19, 0.195 \\
-Information rate        &   1.30 ± 0.07 (71) &   0.96 ± 0.06 (102) &  2385.00, 0.000 &  0.32, 0.000 \\
-Interspike interval cv  &   2.42 ± 0.10 (71) &   2.22 ± 0.08 (102) &  3034.00, 0.070 &  0.12, 0.392 \\
-In-field mean rate      &  14.43 ± 1.00 (71) &  12.94 ± 0.71 (102) &  3368.00, 0.436 &  0.39, 0.812 \\
-Out-field mean rate     &   6.05 ± 0.62 (71) &   6.12 ± 0.53 (102) &  3600.00, 0.950 &  0.08, 0.946 \\
-Burst event ratio       &   0.22 ± 0.01 (71) &   0.20 ± 0.01 (102) &  3090.00, 0.102 &  0.02, 0.124 \\
-Specificity             &   0.48 ± 0.03 (71) &   0.46 ± 0.02 (102) &  3268.00, 0.277 &  0.06, 0.356 \\
+Selectivity             &   5.91 ± 0.37 (71) &   5.98 ± 0.37 (102) &  3460.00, 0.620 &  0.10, 0.874 \\
+Information specificity &   0.25 ± 0.03 (71) &   0.22 ± 0.02 (102) &  2944.00, 0.037 &  0.05, 0.034 \\
+Max rate                &  36.55 ± 1.78 (71) &  33.72 ± 1.31 (102) &  3291.00, 0.309 &  3.19, 0.194 \\
+Information rate        &   1.30 ± 0.07 (71) &   0.96 ± 0.06 (102) &  2385.00, 0.000 &  0.32, 0.001 \\
+Interspike interval cv  &   2.42 ± 0.10 (71) &   2.22 ± 0.08 (102) &  3034.00, 0.070 &  0.12, 0.398 \\
+In-field mean rate      &  14.43 ± 1.00 (71) &  12.94 ± 0.71 (102) &  3368.00, 0.436 &  0.39, 0.817 \\
+Out-field mean rate     &   6.05 ± 0.62 (71) &   6.12 ± 0.53 (102) &  3600.00, 0.950 &  0.08, 0.944 \\
+Burst event ratio       &   0.22 ± 0.01 (71) &   0.20 ± 0.01 (102) &  3090.00, 0.102 &  0.02, 0.129 \\
+Specificity             &   0.48 ± 0.03 (71) &   0.46 ± 0.02 (102) &  3268.00, 0.277 &  0.06, 0.360 \\
 Speed score             &   0.14 ± 0.01 (71) &   0.10 ± 0.01 (102) &  2546.00, 0.001 &  0.05, 0.000 \\
 \bottomrule
 \end{tabular}
diff --git a/actions/comparisons-gridcells/data/statistics/statistics_11.csv b/actions/comparisons-gridcells/data/statistics/statistics_11.csv
index 54706d28c..a32f8158e 100644
--- a/actions/comparisons-gridcells/data/statistics/statistics_11.csv
+++ b/actions/comparisons-gridcells/data/statistics/statistics_11.csv
@@ -1,19 +1,14 @@
-\begin{tabular}{lllll}
-\toprule
-{} &         Baseline I &              11 Hz &             MWU &          PRS \\
-\midrule
-Average rate            &   8.96 ± 0.80 (63) &   8.80 ± 0.85 (58) &  1781.00, 0.813 &  0.04, 0.972 \\
-Gridness                &   0.53 ± 0.05 (63) &   0.41 ± 0.05 (58) &  1459.00, 0.057 &  0.21, 0.043 \\
-Sparsity                &   0.63 ± 0.02 (63) &   0.67 ± 0.03 (58) &  2138.00, 0.107 &  0.07, 0.119 \\
-Selectivity             &   5.76 ± 0.40 (63) &   5.69 ± 0.50 (58) &  1687.00, 0.469 &  0.00, 0.982 \\
-Information specificity &   0.24 ± 0.03 (63) &   0.21 ± 0.03 (58) &  1452.00, 0.052 &  0.06, 0.032 \\
-Max rate                &  37.39 ± 1.91 (63) &  33.11 ± 1.85 (58) &  1538.00, 0.134 &  4.06, 0.122 \\
-Information rate        &   1.31 ± 0.08 (63) &   0.94 ± 0.08 (58) &  1143.00, 0.000 &  0.32, 0.003 \\
-Interspike interval cv  &   2.39 ± 0.10 (63) &   2.19 ± 0.12 (58) &  1462.00, 0.059 &  0.18, 0.135 \\
-In-field mean rate      &  14.88 ± 1.05 (63) &  13.27 ± 1.04 (58) &  1633.00, 0.315 &  0.77, 0.688 \\
-Out-field mean rate     &   6.37 ± 0.67 (63) &   6.57 ± 0.77 (58) &  1795.00, 0.870 &  0.47, 0.724 \\
-Burst event ratio       &   0.22 ± 0.01 (63) &   0.22 ± 0.01 (58) &  1897.00, 0.718 &  0.00, 0.824 \\
-Specificity             &   0.47 ± 0.03 (63) &   0.44 ± 0.03 (58) &  1605.00, 0.250 &  0.06, 0.398 \\
-Speed score             &   0.14 ± 0.01 (63) &   0.11 ± 0.01 (58) &  1378.00, 0.020 &  0.04, 0.023 \\
-\bottomrule
-\end{tabular}
+,Baseline I,11 Hz,MWU,PRS
+Average rate,8.96 ± 0.80 (63),8.80 ± 0.85 (58),"1781.00, 0.813","0.04, 0.968"
+Gridness,0.53 ± 0.05 (63),0.41 ± 0.05 (58),"1459.00, 0.057","0.21, 0.041"
+Sparsity,0.63 ± 0.02 (63),0.67 ± 0.03 (58),"2138.00, 0.107","0.07, 0.128"
+Selectivity,5.76 ± 0.40 (63),5.69 ± 0.50 (58),"1687.00, 0.469","0.00, 0.983"
+Information specificity,0.24 ± 0.03 (63),0.21 ± 0.03 (58),"1452.00, 0.052","0.06, 0.030"
+Max rate,37.39 ± 1.91 (63),33.11 ± 1.85 (58),"1538.00, 0.134","4.06, 0.125"
+Information rate,1.31 ± 0.08 (63),0.94 ± 0.08 (58),"1143.00, 0.000","0.32, 0.004"
+Interspike interval cv,2.39 ± 0.10 (63),2.19 ± 0.12 (58),"1462.00, 0.059","0.18, 0.139"
+In-field mean rate,14.88 ± 1.05 (63),13.27 ± 1.04 (58),"1633.00, 0.315","0.77, 0.690"
+Out-field mean rate,6.37 ± 0.67 (63),6.57 ± 0.77 (58),"1795.00, 0.870","0.47, 0.719"
+Burst event ratio,0.22 ± 0.01 (63),0.22 ± 0.01 (58),"1897.00, 0.718","0.00, 0.824"
+Specificity,0.47 ± 0.03 (63),0.44 ± 0.03 (58),"1605.00, 0.250","0.06, 0.414"
+Speed score,0.14 ± 0.01 (63),0.11 ± 0.01 (58),"1378.00, 0.020","0.04, 0.022"
diff --git a/actions/comparisons-gridcells/data/statistics/statistics_11.tex b/actions/comparisons-gridcells/data/statistics/statistics_11.tex
index 54706d28c..5b031f352 100644
--- a/actions/comparisons-gridcells/data/statistics/statistics_11.tex
+++ b/actions/comparisons-gridcells/data/statistics/statistics_11.tex
@@ -2,18 +2,18 @@
 \toprule
 {} &         Baseline I &              11 Hz &             MWU &          PRS \\
 \midrule
-Average rate            &   8.96 ± 0.80 (63) &   8.80 ± 0.85 (58) &  1781.00, 0.813 &  0.04, 0.972 \\
-Gridness                &   0.53 ± 0.05 (63) &   0.41 ± 0.05 (58) &  1459.00, 0.057 &  0.21, 0.043 \\
-Sparsity                &   0.63 ± 0.02 (63) &   0.67 ± 0.03 (58) &  2138.00, 0.107 &  0.07, 0.119 \\
-Selectivity             &   5.76 ± 0.40 (63) &   5.69 ± 0.50 (58) &  1687.00, 0.469 &  0.00, 0.982 \\
-Information specificity &   0.24 ± 0.03 (63) &   0.21 ± 0.03 (58) &  1452.00, 0.052 &  0.06, 0.032 \\
-Max rate                &  37.39 ± 1.91 (63) &  33.11 ± 1.85 (58) &  1538.00, 0.134 &  4.06, 0.122 \\
-Information rate        &   1.31 ± 0.08 (63) &   0.94 ± 0.08 (58) &  1143.00, 0.000 &  0.32, 0.003 \\
-Interspike interval cv  &   2.39 ± 0.10 (63) &   2.19 ± 0.12 (58) &  1462.00, 0.059 &  0.18, 0.135 \\
-In-field mean rate      &  14.88 ± 1.05 (63) &  13.27 ± 1.04 (58) &  1633.00, 0.315 &  0.77, 0.688 \\
-Out-field mean rate     &   6.37 ± 0.67 (63) &   6.57 ± 0.77 (58) &  1795.00, 0.870 &  0.47, 0.724 \\
+Average rate            &   8.96 ± 0.80 (63) &   8.80 ± 0.85 (58) &  1781.00, 0.813 &  0.04, 0.968 \\
+Gridness                &   0.53 ± 0.05 (63) &   0.41 ± 0.05 (58) &  1459.00, 0.057 &  0.21, 0.041 \\
+Sparsity                &   0.63 ± 0.02 (63) &   0.67 ± 0.03 (58) &  2138.00, 0.107 &  0.07, 0.128 \\
+Selectivity             &   5.76 ± 0.40 (63) &   5.69 ± 0.50 (58) &  1687.00, 0.469 &  0.00, 0.983 \\
+Information specificity &   0.24 ± 0.03 (63) &   0.21 ± 0.03 (58) &  1452.00, 0.052 &  0.06, 0.030 \\
+Max rate                &  37.39 ± 1.91 (63) &  33.11 ± 1.85 (58) &  1538.00, 0.134 &  4.06, 0.125 \\
+Information rate        &   1.31 ± 0.08 (63) &   0.94 ± 0.08 (58) &  1143.00, 0.000 &  0.32, 0.004 \\
+Interspike interval cv  &   2.39 ± 0.10 (63) &   2.19 ± 0.12 (58) &  1462.00, 0.059 &  0.18, 0.139 \\
+In-field mean rate      &  14.88 ± 1.05 (63) &  13.27 ± 1.04 (58) &  1633.00, 0.315 &  0.77, 0.690 \\
+Out-field mean rate     &   6.37 ± 0.67 (63) &   6.57 ± 0.77 (58) &  1795.00, 0.870 &  0.47, 0.719 \\
 Burst event ratio       &   0.22 ± 0.01 (63) &   0.22 ± 0.01 (58) &  1897.00, 0.718 &  0.00, 0.824 \\
-Specificity             &   0.47 ± 0.03 (63) &   0.44 ± 0.03 (58) &  1605.00, 0.250 &  0.06, 0.398 \\
-Speed score             &   0.14 ± 0.01 (63) &   0.11 ± 0.01 (58) &  1378.00, 0.020 &  0.04, 0.023 \\
+Specificity             &   0.47 ± 0.03 (63) &   0.44 ± 0.03 (58) &  1605.00, 0.250 &  0.06, 0.414 \\
+Speed score             &   0.14 ± 0.01 (63) &   0.11 ± 0.01 (58) &  1378.00, 0.020 &  0.04, 0.022 \\
 \bottomrule
 \end{tabular}
diff --git a/actions/comparisons-gridcells/data/statistics/statistics_11_vs_30.csv b/actions/comparisons-gridcells/data/statistics/statistics_11_vs_30.csv
index 436bc6ce2..b294eaf16 100644
--- a/actions/comparisons-gridcells/data/statistics/statistics_11_vs_30.csv
+++ b/actions/comparisons-gridcells/data/statistics/statistics_11_vs_30.csv
@@ -1,19 +1,14 @@
-\begin{tabular}{lllll}
-\toprule
-{} &              11 Hz &              30 Hz &             MWU &          PRS \\
-\midrule
-Average rate            &   8.80 ± 0.85 (58) &   7.61 ± 0.87 (38) &  1010.00, 0.493 &  0.23, 0.893 \\
-Gridness                &   0.41 ± 0.05 (58) &   0.48 ± 0.06 (38) &  1259.00, 0.241 &  0.13, 0.094 \\
-Sparsity                &   0.67 ± 0.03 (58) &   0.64 ± 0.03 (38) &  1002.00, 0.456 &  0.04, 0.561 \\
-Selectivity             &   5.69 ± 0.50 (58) &   6.42 ± 0.60 (38) &  1260.00, 0.238 &  0.85, 0.335 \\
-Information specificity &   0.21 ± 0.03 (58) &   0.22 ± 0.03 (38) &  1231.00, 0.336 &  0.01, 0.732 \\
-Max rate                &  33.11 ± 1.85 (58) &  33.49 ± 1.89 (38) &  1136.00, 0.802 &  0.07, 0.993 \\
-Information rate        &   0.94 ± 0.08 (58) &   0.98 ± 0.09 (38) &  1171.00, 0.608 &  0.01, 0.789 \\
-Interspike interval cv  &   2.19 ± 0.12 (58) &   2.23 ± 0.11 (38) &  1228.00, 0.347 &  0.17, 0.328 \\
-In-field mean rate      &  13.27 ± 1.04 (58) &  12.21 ± 0.98 (38) &  1058.00, 0.744 &  0.97, 0.637 \\
-Out-field mean rate     &   6.57 ± 0.77 (58) &   5.36 ± 0.73 (38) &  1019.00, 0.537 &  0.04, 0.958 \\
-Burst event ratio       &   0.22 ± 0.01 (58) &   0.16 ± 0.01 (38) &   552.00, 0.000 &  0.06, 0.000 \\
-Specificity             &   0.44 ± 0.03 (58) &   0.48 ± 0.04 (38) &  1233.00, 0.328 &  0.07, 0.380 \\
-Speed score             &   0.11 ± 0.01 (58) &   0.11 ± 0.01 (38) &  1022.00, 0.551 &  0.02, 0.144 \\
-\bottomrule
-\end{tabular}
+,11 Hz,30 Hz,MWU,PRS
+Average rate,8.80 ± 0.85 (58),7.61 ± 0.87 (38),"1010.00, 0.493","0.23, 0.892"
+Gridness,0.41 ± 0.05 (58),0.48 ± 0.06 (38),"1259.00, 0.241","0.13, 0.099"
+Sparsity,0.67 ± 0.03 (58),0.64 ± 0.03 (38),"1002.00, 0.456","0.04, 0.557"
+Selectivity,5.69 ± 0.50 (58),6.42 ± 0.60 (38),"1260.00, 0.238","0.85, 0.340"
+Information specificity,0.21 ± 0.03 (58),0.22 ± 0.03 (38),"1231.00, 0.336","0.01, 0.727"
+Max rate,33.11 ± 1.85 (58),33.49 ± 1.89 (38),"1136.00, 0.802","0.07, 0.994"
+Information rate,0.94 ± 0.08 (58),0.98 ± 0.09 (38),"1171.00, 0.608","0.01, 0.784"
+Interspike interval cv,2.19 ± 0.12 (58),2.23 ± 0.11 (38),"1228.00, 0.347","0.17, 0.338"
+In-field mean rate,13.27 ± 1.04 (58),12.21 ± 0.98 (38),"1058.00, 0.744","0.97, 0.634"
+Out-field mean rate,6.57 ± 0.77 (58),5.36 ± 0.73 (38),"1019.00, 0.537","0.04, 0.959"
+Burst event ratio,0.22 ± 0.01 (58),0.16 ± 0.01 (38),"552.00, 0.000","0.06, 0.000"
+Specificity,0.44 ± 0.03 (58),0.48 ± 0.04 (38),"1233.00, 0.328","0.07, 0.371"
+Speed score,0.11 ± 0.01 (58),0.11 ± 0.01 (38),"1022.00, 0.551","0.02, 0.144"
diff --git a/actions/comparisons-gridcells/data/statistics/statistics_11_vs_30.tex b/actions/comparisons-gridcells/data/statistics/statistics_11_vs_30.tex
index 436bc6ce2..8c8b5ae65 100644
--- a/actions/comparisons-gridcells/data/statistics/statistics_11_vs_30.tex
+++ b/actions/comparisons-gridcells/data/statistics/statistics_11_vs_30.tex
@@ -2,18 +2,18 @@
 \toprule
 {} &              11 Hz &              30 Hz &             MWU &          PRS \\
 \midrule
-Average rate            &   8.80 ± 0.85 (58) &   7.61 ± 0.87 (38) &  1010.00, 0.493 &  0.23, 0.893 \\
-Gridness                &   0.41 ± 0.05 (58) &   0.48 ± 0.06 (38) &  1259.00, 0.241 &  0.13, 0.094 \\
-Sparsity                &   0.67 ± 0.03 (58) &   0.64 ± 0.03 (38) &  1002.00, 0.456 &  0.04, 0.561 \\
-Selectivity             &   5.69 ± 0.50 (58) &   6.42 ± 0.60 (38) &  1260.00, 0.238 &  0.85, 0.335 \\
-Information specificity &   0.21 ± 0.03 (58) &   0.22 ± 0.03 (38) &  1231.00, 0.336 &  0.01, 0.732 \\
-Max rate                &  33.11 ± 1.85 (58) &  33.49 ± 1.89 (38) &  1136.00, 0.802 &  0.07, 0.993 \\
-Information rate        &   0.94 ± 0.08 (58) &   0.98 ± 0.09 (38) &  1171.00, 0.608 &  0.01, 0.789 \\
-Interspike interval cv  &   2.19 ± 0.12 (58) &   2.23 ± 0.11 (38) &  1228.00, 0.347 &  0.17, 0.328 \\
-In-field mean rate      &  13.27 ± 1.04 (58) &  12.21 ± 0.98 (38) &  1058.00, 0.744 &  0.97, 0.637 \\
-Out-field mean rate     &   6.57 ± 0.77 (58) &   5.36 ± 0.73 (38) &  1019.00, 0.537 &  0.04, 0.958 \\
+Average rate            &   8.80 ± 0.85 (58) &   7.61 ± 0.87 (38) &  1010.00, 0.493 &  0.23, 0.892 \\
+Gridness                &   0.41 ± 0.05 (58) &   0.48 ± 0.06 (38) &  1259.00, 0.241 &  0.13, 0.099 \\
+Sparsity                &   0.67 ± 0.03 (58) &   0.64 ± 0.03 (38) &  1002.00, 0.456 &  0.04, 0.557 \\
+Selectivity             &   5.69 ± 0.50 (58) &   6.42 ± 0.60 (38) &  1260.00, 0.238 &  0.85, 0.340 \\
+Information specificity &   0.21 ± 0.03 (58) &   0.22 ± 0.03 (38) &  1231.00, 0.336 &  0.01, 0.727 \\
+Max rate                &  33.11 ± 1.85 (58) &  33.49 ± 1.89 (38) &  1136.00, 0.802 &  0.07, 0.994 \\
+Information rate        &   0.94 ± 0.08 (58) &   0.98 ± 0.09 (38) &  1171.00, 0.608 &  0.01, 0.784 \\
+Interspike interval cv  &   2.19 ± 0.12 (58) &   2.23 ± 0.11 (38) &  1228.00, 0.347 &  0.17, 0.338 \\
+In-field mean rate      &  13.27 ± 1.04 (58) &  12.21 ± 0.98 (38) &  1058.00, 0.744 &  0.97, 0.634 \\
+Out-field mean rate     &   6.57 ± 0.77 (58) &   5.36 ± 0.73 (38) &  1019.00, 0.537 &  0.04, 0.959 \\
 Burst event ratio       &   0.22 ± 0.01 (58) &   0.16 ± 0.01 (38) &   552.00, 0.000 &  0.06, 0.000 \\
-Specificity             &   0.44 ± 0.03 (58) &   0.48 ± 0.04 (38) &  1233.00, 0.328 &  0.07, 0.380 \\
+Specificity             &   0.44 ± 0.03 (58) &   0.48 ± 0.04 (38) &  1233.00, 0.328 &  0.07, 0.371 \\
 Speed score             &   0.11 ± 0.01 (58) &   0.11 ± 0.01 (38) &  1022.00, 0.551 &  0.02, 0.144 \\
 \bottomrule
 \end{tabular}
diff --git a/actions/comparisons-gridcells/data/statistics/statistics_30.csv b/actions/comparisons-gridcells/data/statistics/statistics_30.csv
index 8390f38fe..78f9db7f4 100644
--- a/actions/comparisons-gridcells/data/statistics/statistics_30.csv
+++ b/actions/comparisons-gridcells/data/statistics/statistics_30.csv
@@ -1,19 +1,14 @@
-\begin{tabular}{lllll}
-\toprule
-{} &        Baseline II &              30 Hz &             MWU &          PRS \\
-\midrule
-Average rate            &   8.29 ± 0.87 (52) &   7.61 ± 0.87 (38) &   958.00, 0.810 &  0.27, 0.800 \\
-Gridness                &   0.54 ± 0.04 (52) &   0.48 ± 0.06 (38) &   914.00, 0.548 &  0.04, 0.601 \\
-Sparsity                &   0.63 ± 0.03 (52) &   0.64 ± 0.03 (38) &  1040.00, 0.674 &  0.06, 0.393 \\
-Selectivity             &   5.96 ± 0.46 (52) &   6.42 ± 0.60 (38) &  1019.00, 0.803 &  0.20, 0.847 \\
-Information specificity &   0.21 ± 0.02 (52) &   0.22 ± 0.03 (38) &   950.00, 0.759 &  0.04, 0.502 \\
-Max rate                &  36.27 ± 2.34 (52) &  33.49 ± 1.89 (38) &   943.00, 0.716 &  2.90, 0.555 \\
-Information rate        &   1.13 ± 0.08 (52) &   0.98 ± 0.09 (38) &   827.00, 0.190 &  0.07, 0.334 \\
-Interspike interval cv  &   2.37 ± 0.09 (52) &   2.23 ± 0.11 (38) &   869.00, 0.333 &  0.17, 0.476 \\
-In-field mean rate      &  13.79 ± 1.12 (52) &  12.21 ± 0.98 (38) &   912.00, 0.537 &  1.06, 0.455 \\
-Out-field mean rate     &   5.80 ± 0.72 (52) &   5.36 ± 0.73 (38) &   959.00, 0.816 &  0.13, 0.912 \\
-Burst event ratio       &   0.20 ± 0.01 (52) &   0.16 ± 0.01 (38) &   676.00, 0.011 &  0.05, 0.006 \\
-Specificity             &   0.47 ± 0.03 (52) &   0.48 ± 0.04 (38) &   976.00, 0.925 &  0.00, 0.987 \\
-Speed score             &   0.12 ± 0.01 (52) &   0.11 ± 0.01 (38) &   784.00, 0.096 &  0.01, 0.230 \\
-\bottomrule
-\end{tabular}
+,Baseline II,30 Hz,MWU,PRS
+Average rate,8.29 ± 0.87 (52),7.61 ± 0.87 (38),"958.00, 0.810","0.27, 0.808"
+Gridness,0.54 ± 0.04 (52),0.48 ± 0.06 (38),"914.00, 0.548","0.04, 0.598"
+Sparsity,0.63 ± 0.03 (52),0.64 ± 0.03 (38),"1040.00, 0.674","0.06, 0.398"
+Selectivity,5.96 ± 0.46 (52),6.42 ± 0.60 (38),"1019.00, 0.803","0.20, 0.845"
+Information specificity,0.21 ± 0.02 (52),0.22 ± 0.03 (38),"950.00, 0.759","0.04, 0.506"
+Max rate,36.27 ± 2.34 (52),33.49 ± 1.89 (38),"943.00, 0.716","2.90, 0.565"
+Information rate,1.13 ± 0.08 (52),0.98 ± 0.09 (38),"827.00, 0.190","0.07, 0.335"
+Interspike interval cv,2.37 ± 0.09 (52),2.23 ± 0.11 (38),"869.00, 0.333","0.17, 0.482"
+In-field mean rate,13.79 ± 1.12 (52),12.21 ± 0.98 (38),"912.00, 0.537","1.06, 0.444"
+Out-field mean rate,5.80 ± 0.72 (52),5.36 ± 0.73 (38),"959.00, 0.816","0.13, 0.912"
+Burst event ratio,0.20 ± 0.01 (52),0.16 ± 0.01 (38),"676.00, 0.011","0.05, 0.009"
+Specificity,0.47 ± 0.03 (52),0.48 ± 0.04 (38),"976.00, 0.925","0.00, 0.988"
+Speed score,0.12 ± 0.01 (52),0.11 ± 0.01 (38),"784.00, 0.096","0.01, 0.242"
diff --git a/actions/comparisons-gridcells/data/statistics/statistics_30.tex b/actions/comparisons-gridcells/data/statistics/statistics_30.tex
index 8390f38fe..6e1643f72 100644
--- a/actions/comparisons-gridcells/data/statistics/statistics_30.tex
+++ b/actions/comparisons-gridcells/data/statistics/statistics_30.tex
@@ -2,18 +2,18 @@
 \toprule
 {} &        Baseline II &              30 Hz &             MWU &          PRS \\
 \midrule
-Average rate            &   8.29 ± 0.87 (52) &   7.61 ± 0.87 (38) &   958.00, 0.810 &  0.27, 0.800 \\
-Gridness                &   0.54 ± 0.04 (52) &   0.48 ± 0.06 (38) &   914.00, 0.548 &  0.04, 0.601 \\
-Sparsity                &   0.63 ± 0.03 (52) &   0.64 ± 0.03 (38) &  1040.00, 0.674 &  0.06, 0.393 \\
-Selectivity             &   5.96 ± 0.46 (52) &   6.42 ± 0.60 (38) &  1019.00, 0.803 &  0.20, 0.847 \\
-Information specificity &   0.21 ± 0.02 (52) &   0.22 ± 0.03 (38) &   950.00, 0.759 &  0.04, 0.502 \\
-Max rate                &  36.27 ± 2.34 (52) &  33.49 ± 1.89 (38) &   943.00, 0.716 &  2.90, 0.555 \\
-Information rate        &   1.13 ± 0.08 (52) &   0.98 ± 0.09 (38) &   827.00, 0.190 &  0.07, 0.334 \\
-Interspike interval cv  &   2.37 ± 0.09 (52) &   2.23 ± 0.11 (38) &   869.00, 0.333 &  0.17, 0.476 \\
-In-field mean rate      &  13.79 ± 1.12 (52) &  12.21 ± 0.98 (38) &   912.00, 0.537 &  1.06, 0.455 \\
+Average rate            &   8.29 ± 0.87 (52) &   7.61 ± 0.87 (38) &   958.00, 0.810 &  0.27, 0.808 \\
+Gridness                &   0.54 ± 0.04 (52) &   0.48 ± 0.06 (38) &   914.00, 0.548 &  0.04, 0.598 \\
+Sparsity                &   0.63 ± 0.03 (52) &   0.64 ± 0.03 (38) &  1040.00, 0.674 &  0.06, 0.398 \\
+Selectivity             &   5.96 ± 0.46 (52) &   6.42 ± 0.60 (38) &  1019.00, 0.803 &  0.20, 0.845 \\
+Information specificity &   0.21 ± 0.02 (52) &   0.22 ± 0.03 (38) &   950.00, 0.759 &  0.04, 0.506 \\
+Max rate                &  36.27 ± 2.34 (52) &  33.49 ± 1.89 (38) &   943.00, 0.716 &  2.90, 0.565 \\
+Information rate        &   1.13 ± 0.08 (52) &   0.98 ± 0.09 (38) &   827.00, 0.190 &  0.07, 0.335 \\
+Interspike interval cv  &   2.37 ± 0.09 (52) &   2.23 ± 0.11 (38) &   869.00, 0.333 &  0.17, 0.482 \\
+In-field mean rate      &  13.79 ± 1.12 (52) &  12.21 ± 0.98 (38) &   912.00, 0.537 &  1.06, 0.444 \\
 Out-field mean rate     &   5.80 ± 0.72 (52) &   5.36 ± 0.73 (38) &   959.00, 0.816 &  0.13, 0.912 \\
-Burst event ratio       &   0.20 ± 0.01 (52) &   0.16 ± 0.01 (38) &   676.00, 0.011 &  0.05, 0.006 \\
-Specificity             &   0.47 ± 0.03 (52) &   0.48 ± 0.04 (38) &   976.00, 0.925 &  0.00, 0.987 \\
-Speed score             &   0.12 ± 0.01 (52) &   0.11 ± 0.01 (38) &   784.00, 0.096 &  0.01, 0.230 \\
+Burst event ratio       &   0.20 ± 0.01 (52) &   0.16 ± 0.01 (38) &   676.00, 0.011 &  0.05, 0.009 \\
+Specificity             &   0.47 ± 0.03 (52) &   0.48 ± 0.04 (38) &   976.00, 0.925 &  0.00, 0.988 \\
+Speed score             &   0.12 ± 0.01 (52) &   0.11 ± 0.01 (38) &   784.00, 0.096 &  0.01, 0.242 \\
 \bottomrule
 \end{tabular}
diff --git a/actions/comparisons-gridcells/data/statistics/statistics_b_i_30.csv b/actions/comparisons-gridcells/data/statistics/statistics_b_i_30.csv
index 1128878d3..c5790bb5d 100644
--- a/actions/comparisons-gridcells/data/statistics/statistics_b_i_30.csv
+++ b/actions/comparisons-gridcells/data/statistics/statistics_b_i_30.csv
@@ -1,19 +1,14 @@
-\begin{tabular}{lllll}
-\toprule
-{} &         Baseline I &              30 Hz &             MWU &          PRS \\
-\midrule
-Average rate            &   8.96 ± 0.80 (63) &   7.61 ± 0.87 (38) &  1081.00, 0.418 &  0.27, 0.806 \\
-Gridness                &   0.53 ± 0.05 (63) &   0.48 ± 0.06 (38) &  1094.00, 0.472 &  0.08, 0.361 \\
-Sparsity                &   0.63 ± 0.02 (63) &   0.64 ± 0.03 (38) &  1261.00, 0.656 &  0.03, 0.638 \\
-Selectivity             &   5.76 ± 0.40 (63) &   6.42 ± 0.60 (38) &  1276.00, 0.582 &  0.86, 0.293 \\
-Information specificity &   0.24 ± 0.03 (63) &   0.22 ± 0.03 (38) &  1076.00, 0.398 &  0.05, 0.165 \\
-Max rate                &  37.39 ± 1.91 (63) &  33.49 ± 1.89 (38) &  1027.00, 0.235 &  3.99, 0.188 \\
-Information rate        &   1.31 ± 0.08 (63) &   0.98 ± 0.09 (38) &   797.00, 0.005 &  0.32, 0.047 \\
-Interspike interval cv  &   2.39 ± 0.10 (63) &   2.23 ± 0.11 (38) &  1100.00, 0.499 &  0.01, 0.993 \\
-In-field mean rate      &  14.88 ± 1.05 (63) &  12.21 ± 0.98 (38) &  1018.00, 0.211 &  1.74, 0.276 \\
-Out-field mean rate     &   6.37 ± 0.67 (63) &   5.36 ± 0.73 (38) &  1079.00, 0.410 &  0.51, 0.631 \\
-Burst event ratio       &   0.22 ± 0.01 (63) &   0.16 ± 0.01 (38) &   675.00, 0.000 &  0.05, 0.003 \\
-Specificity             &   0.47 ± 0.03 (63) &   0.48 ± 0.04 (38) &  1206.00, 0.952 &  0.01, 0.873 \\
-Speed score             &   0.14 ± 0.01 (63) &   0.11 ± 0.01 (38) &   835.00, 0.011 &  0.06, 0.004 \\
-\bottomrule
-\end{tabular}
+,Baseline I,30 Hz,MWU,PRS
+Average rate,8.96 ± 0.80 (63),7.61 ± 0.87 (38),"1081.00, 0.418","0.27, 0.804"
+Gridness,0.53 ± 0.05 (63),0.48 ± 0.06 (38),"1094.00, 0.472","0.08, 0.354"
+Sparsity,0.63 ± 0.02 (63),0.64 ± 0.03 (38),"1261.00, 0.656","0.03, 0.648"
+Selectivity,5.76 ± 0.40 (63),6.42 ± 0.60 (38),"1276.00, 0.582","0.86, 0.292"
+Information specificity,0.24 ± 0.03 (63),0.22 ± 0.03 (38),"1076.00, 0.398","0.05, 0.159"
+Max rate,37.39 ± 1.91 (63),33.49 ± 1.89 (38),"1027.00, 0.235","3.99, 0.191"
+Information rate,1.31 ± 0.08 (63),0.98 ± 0.09 (38),"797.00, 0.005","0.32, 0.049"
+Interspike interval cv,2.39 ± 0.10 (63),2.23 ± 0.11 (38),"1100.00, 0.499","0.01, 0.991"
+In-field mean rate,14.88 ± 1.05 (63),12.21 ± 0.98 (38),"1018.00, 0.211","1.74, 0.273"
+Out-field mean rate,6.37 ± 0.67 (63),5.36 ± 0.73 (38),"1079.00, 0.410","0.51, 0.641"
+Burst event ratio,0.22 ± 0.01 (63),0.16 ± 0.01 (38),"675.00, 0.000","0.05, 0.004"
+Specificity,0.47 ± 0.03 (63),0.48 ± 0.04 (38),"1206.00, 0.952","0.01, 0.875"
+Speed score,0.14 ± 0.01 (63),0.11 ± 0.01 (38),"835.00, 0.011","0.06, 0.004"
diff --git a/actions/comparisons-gridcells/data/statistics/statistics_b_i_30.tex b/actions/comparisons-gridcells/data/statistics/statistics_b_i_30.tex
index 1128878d3..f39eabf97 100644
--- a/actions/comparisons-gridcells/data/statistics/statistics_b_i_30.tex
+++ b/actions/comparisons-gridcells/data/statistics/statistics_b_i_30.tex
@@ -2,18 +2,18 @@
 \toprule
 {} &         Baseline I &              30 Hz &             MWU &          PRS \\
 \midrule
-Average rate            &   8.96 ± 0.80 (63) &   7.61 ± 0.87 (38) &  1081.00, 0.418 &  0.27, 0.806 \\
-Gridness                &   0.53 ± 0.05 (63) &   0.48 ± 0.06 (38) &  1094.00, 0.472 &  0.08, 0.361 \\
-Sparsity                &   0.63 ± 0.02 (63) &   0.64 ± 0.03 (38) &  1261.00, 0.656 &  0.03, 0.638 \\
-Selectivity             &   5.76 ± 0.40 (63) &   6.42 ± 0.60 (38) &  1276.00, 0.582 &  0.86, 0.293 \\
-Information specificity &   0.24 ± 0.03 (63) &   0.22 ± 0.03 (38) &  1076.00, 0.398 &  0.05, 0.165 \\
-Max rate                &  37.39 ± 1.91 (63) &  33.49 ± 1.89 (38) &  1027.00, 0.235 &  3.99, 0.188 \\
-Information rate        &   1.31 ± 0.08 (63) &   0.98 ± 0.09 (38) &   797.00, 0.005 &  0.32, 0.047 \\
-Interspike interval cv  &   2.39 ± 0.10 (63) &   2.23 ± 0.11 (38) &  1100.00, 0.499 &  0.01, 0.993 \\
-In-field mean rate      &  14.88 ± 1.05 (63) &  12.21 ± 0.98 (38) &  1018.00, 0.211 &  1.74, 0.276 \\
-Out-field mean rate     &   6.37 ± 0.67 (63) &   5.36 ± 0.73 (38) &  1079.00, 0.410 &  0.51, 0.631 \\
-Burst event ratio       &   0.22 ± 0.01 (63) &   0.16 ± 0.01 (38) &   675.00, 0.000 &  0.05, 0.003 \\
-Specificity             &   0.47 ± 0.03 (63) &   0.48 ± 0.04 (38) &  1206.00, 0.952 &  0.01, 0.873 \\
+Average rate            &   8.96 ± 0.80 (63) &   7.61 ± 0.87 (38) &  1081.00, 0.418 &  0.27, 0.804 \\
+Gridness                &   0.53 ± 0.05 (63) &   0.48 ± 0.06 (38) &  1094.00, 0.472 &  0.08, 0.354 \\
+Sparsity                &   0.63 ± 0.02 (63) &   0.64 ± 0.03 (38) &  1261.00, 0.656 &  0.03, 0.648 \\
+Selectivity             &   5.76 ± 0.40 (63) &   6.42 ± 0.60 (38) &  1276.00, 0.582 &  0.86, 0.292 \\
+Information specificity &   0.24 ± 0.03 (63) &   0.22 ± 0.03 (38) &  1076.00, 0.398 &  0.05, 0.159 \\
+Max rate                &  37.39 ± 1.91 (63) &  33.49 ± 1.89 (38) &  1027.00, 0.235 &  3.99, 0.191 \\
+Information rate        &   1.31 ± 0.08 (63) &   0.98 ± 0.09 (38) &   797.00, 0.005 &  0.32, 0.049 \\
+Interspike interval cv  &   2.39 ± 0.10 (63) &   2.23 ± 0.11 (38) &  1100.00, 0.499 &  0.01, 0.991 \\
+In-field mean rate      &  14.88 ± 1.05 (63) &  12.21 ± 0.98 (38) &  1018.00, 0.211 &  1.74, 0.273 \\
+Out-field mean rate     &   6.37 ± 0.67 (63) &   5.36 ± 0.73 (38) &  1079.00, 0.410 &  0.51, 0.641 \\
+Burst event ratio       &   0.22 ± 0.01 (63) &   0.16 ± 0.01 (38) &   675.00, 0.000 &  0.05, 0.004 \\
+Specificity             &   0.47 ± 0.03 (63) &   0.48 ± 0.04 (38) &  1206.00, 0.952 &  0.01, 0.875 \\
 Speed score             &   0.14 ± 0.01 (63) &   0.11 ± 0.01 (38) &   835.00, 0.011 &  0.06, 0.004 \\
 \bottomrule
 \end{tabular}
diff --git a/actions/comparisons-gridcells/data/statistics/statistics_base_i_vs_base_ii.csv b/actions/comparisons-gridcells/data/statistics/statistics_base_i_vs_base_ii.csv
index d94cd6e51..7f99b36c1 100644
--- a/actions/comparisons-gridcells/data/statistics/statistics_base_i_vs_base_ii.csv
+++ b/actions/comparisons-gridcells/data/statistics/statistics_base_i_vs_base_ii.csv
@@ -1,19 +1,14 @@
-\begin{tabular}{lllll}
-\toprule
-{} &         Baseline I &        Baseline II &             MWU &          PRS \\
-\midrule
-Average rate            &   8.96 ± 0.80 (63) &   8.29 ± 0.87 (52) &  1756.00, 0.509 &  0.55, 0.674 \\
-Gridness                &   0.53 ± 0.05 (63) &   0.54 ± 0.04 (52) &  1664.00, 0.886 &  0.04, 0.550 \\
-Sparsity                &   0.63 ± 0.02 (63) &   0.63 ± 0.03 (52) &  1652.00, 0.940 &  0.03, 0.648 \\
-Selectivity             &   5.76 ± 0.40 (63) &   5.96 ± 0.46 (52) &  1542.00, 0.592 &  0.66, 0.360 \\
-Information specificity &   0.24 ± 0.03 (63) &   0.21 ± 0.02 (52) &  1718.00, 0.655 &  0.01, 0.812 \\
-Max rate                &  37.39 ± 1.91 (63) &  36.27 ± 2.34 (52) &  1757.00, 0.505 &  1.09, 0.610 \\
-Information rate        &   1.31 ± 0.08 (63) &   1.13 ± 0.08 (52) &  1929.00, 0.103 &  0.25, 0.140 \\
-Interspike interval cv  &   2.39 ± 0.10 (63) &   2.37 ± 0.09 (52) &  1572.00, 0.713 &  0.16, 0.479 \\
-In-field mean rate      &  14.88 ± 1.05 (63) &  13.79 ± 1.12 (52) &  1763.00, 0.484 &  0.68, 0.690 \\
-Out-field mean rate     &   6.37 ± 0.67 (63) &   5.80 ± 0.72 (52) &  1737.00, 0.580 &  0.38, 0.586 \\
-Burst event ratio       &   0.22 ± 0.01 (63) &   0.20 ± 0.01 (52) &  1834.00, 0.272 &  0.01, 0.681 \\
-Specificity             &   0.47 ± 0.03 (63) &   0.47 ± 0.03 (52) &  1588.00, 0.781 &  0.01, 0.765 \\
-Speed score             &   0.14 ± 0.01 (63) &   0.12 ± 0.01 (52) &  1943.00, 0.087 &  0.04, 0.017 \\
-\bottomrule
-\end{tabular}
+,Baseline I,Baseline II,MWU,PRS
+Average rate,8.96 ± 0.80 (63),8.29 ± 0.87 (52),"1756.00, 0.509","0.55, 0.678"
+Gridness,0.53 ± 0.05 (63),0.54 ± 0.04 (52),"1664.00, 0.886","0.04, 0.545"
+Sparsity,0.63 ± 0.02 (63),0.63 ± 0.03 (52),"1652.00, 0.940","0.03, 0.648"
+Selectivity,5.76 ± 0.40 (63),5.96 ± 0.46 (52),"1542.00, 0.592","0.66, 0.360"
+Information specificity,0.24 ± 0.03 (63),0.21 ± 0.02 (52),"1718.00, 0.655","0.01, 0.814"
+Max rate,37.39 ± 1.91 (63),36.27 ± 2.34 (52),"1757.00, 0.505","1.09, 0.612"
+Information rate,1.31 ± 0.08 (63),1.13 ± 0.08 (52),"1929.00, 0.103","0.25, 0.142"
+Interspike interval cv,2.39 ± 0.10 (63),2.37 ± 0.09 (52),"1572.00, 0.713","0.16, 0.479"
+In-field mean rate,14.88 ± 1.05 (63),13.79 ± 1.12 (52),"1763.00, 0.484","0.68, 0.685"
+Out-field mean rate,6.37 ± 0.67 (63),5.80 ± 0.72 (52),"1737.00, 0.580","0.38, 0.577"
+Burst event ratio,0.22 ± 0.01 (63),0.20 ± 0.01 (52),"1834.00, 0.272","0.01, 0.670"
+Specificity,0.47 ± 0.03 (63),0.47 ± 0.03 (52),"1588.00, 0.781","0.01, 0.766"
+Speed score,0.14 ± 0.01 (63),0.12 ± 0.01 (52),"1943.00, 0.087","0.04, 0.015"
diff --git a/actions/comparisons-gridcells/data/statistics/statistics_base_i_vs_base_ii.tex b/actions/comparisons-gridcells/data/statistics/statistics_base_i_vs_base_ii.tex
index d94cd6e51..dd211ea1e 100644
--- a/actions/comparisons-gridcells/data/statistics/statistics_base_i_vs_base_ii.tex
+++ b/actions/comparisons-gridcells/data/statistics/statistics_base_i_vs_base_ii.tex
@@ -2,18 +2,18 @@
 \toprule
 {} &         Baseline I &        Baseline II &             MWU &          PRS \\
 \midrule
-Average rate            &   8.96 ± 0.80 (63) &   8.29 ± 0.87 (52) &  1756.00, 0.509 &  0.55, 0.674 \\
-Gridness                &   0.53 ± 0.05 (63) &   0.54 ± 0.04 (52) &  1664.00, 0.886 &  0.04, 0.550 \\
+Average rate            &   8.96 ± 0.80 (63) &   8.29 ± 0.87 (52) &  1756.00, 0.509 &  0.55, 0.678 \\
+Gridness                &   0.53 ± 0.05 (63) &   0.54 ± 0.04 (52) &  1664.00, 0.886 &  0.04, 0.545 \\
 Sparsity                &   0.63 ± 0.02 (63) &   0.63 ± 0.03 (52) &  1652.00, 0.940 &  0.03, 0.648 \\
 Selectivity             &   5.76 ± 0.40 (63) &   5.96 ± 0.46 (52) &  1542.00, 0.592 &  0.66, 0.360 \\
-Information specificity &   0.24 ± 0.03 (63) &   0.21 ± 0.02 (52) &  1718.00, 0.655 &  0.01, 0.812 \\
-Max rate                &  37.39 ± 1.91 (63) &  36.27 ± 2.34 (52) &  1757.00, 0.505 &  1.09, 0.610 \\
-Information rate        &   1.31 ± 0.08 (63) &   1.13 ± 0.08 (52) &  1929.00, 0.103 &  0.25, 0.140 \\
+Information specificity &   0.24 ± 0.03 (63) &   0.21 ± 0.02 (52) &  1718.00, 0.655 &  0.01, 0.814 \\
+Max rate                &  37.39 ± 1.91 (63) &  36.27 ± 2.34 (52) &  1757.00, 0.505 &  1.09, 0.612 \\
+Information rate        &   1.31 ± 0.08 (63) &   1.13 ± 0.08 (52) &  1929.00, 0.103 &  0.25, 0.142 \\
 Interspike interval cv  &   2.39 ± 0.10 (63) &   2.37 ± 0.09 (52) &  1572.00, 0.713 &  0.16, 0.479 \\
-In-field mean rate      &  14.88 ± 1.05 (63) &  13.79 ± 1.12 (52) &  1763.00, 0.484 &  0.68, 0.690 \\
-Out-field mean rate     &   6.37 ± 0.67 (63) &   5.80 ± 0.72 (52) &  1737.00, 0.580 &  0.38, 0.586 \\
-Burst event ratio       &   0.22 ± 0.01 (63) &   0.20 ± 0.01 (52) &  1834.00, 0.272 &  0.01, 0.681 \\
-Specificity             &   0.47 ± 0.03 (63) &   0.47 ± 0.03 (52) &  1588.00, 0.781 &  0.01, 0.765 \\
-Speed score             &   0.14 ± 0.01 (63) &   0.12 ± 0.01 (52) &  1943.00, 0.087 &  0.04, 0.017 \\
+In-field mean rate      &  14.88 ± 1.05 (63) &  13.79 ± 1.12 (52) &  1763.00, 0.484 &  0.68, 0.685 \\
+Out-field mean rate     &   6.37 ± 0.67 (63) &   5.80 ± 0.72 (52) &  1737.00, 0.580 &  0.38, 0.577 \\
+Burst event ratio       &   0.22 ± 0.01 (63) &   0.20 ± 0.01 (52) &  1834.00, 0.272 &  0.01, 0.670 \\
+Specificity             &   0.47 ± 0.03 (63) &   0.47 ± 0.03 (52) &  1588.00, 0.781 &  0.01, 0.766 \\
+Speed score             &   0.14 ± 0.01 (63) &   0.12 ± 0.01 (52) &  1943.00, 0.087 &  0.04, 0.015 \\
 \bottomrule
 \end{tabular}
diff --git a/actions/longitudinal-comparisons-gridcells/data/20_longitudinal_comparisons_gridcells.html b/actions/longitudinal-comparisons-gridcells/data/20_longitudinal_comparisons_gridcells.html
index 2d0de378e..160cf7966 100644
--- a/actions/longitudinal-comparisons-gridcells/data/20_longitudinal_comparisons_gridcells.html
+++ b/actions/longitudinal-comparisons-gridcells/data/20_longitudinal_comparisons_gridcells.html
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/home/mikkel/.virtualenvs/expipe/lib/python3.6/site-packages/ipykernel_launcher.py:25: TqdmDeprecationWarning: This function will be removed in tqdm==5.0.0
+
13:55:01 [I] klustakwik KlustaKwik2 version 0.2.6
+/home/mikkel/.virtualenvs/expipe/lib/python3.6/importlib/_bootstrap.py:219: RuntimeWarning: numpy.ufunc size changed, may indicate binary incompatibility. Expected 192 from C header, got 216 from PyObject
+  return f(*args, **kwds)
+/home/mikkel/.virtualenvs/expipe/lib/python3.6/importlib/_bootstrap.py:219: RuntimeWarning: numpy.ufunc size changed, may indicate binary incompatibility. Expected 192 from C header, got 216 from PyObject
+  return f(*args, **kwds)
+/home/mikkel/.virtualenvs/expipe/lib/python3.6/site-packages/ipykernel_launcher.py:25: TqdmDeprecationWarning: This function will be removed in tqdm==5.0.0
 Please use `tqdm.notebook.*` instead of `tqdm._tqdm_notebook.*`
 

 

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results_xcorr_displacement = [[], [], [], [], []]
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/home/mikkel/apps/expipe-project/septum-mec/septum_mec/analysis/data_processing.py:590: RuntimeWarning: divide by zero encountered in true_divide
+  rate_map_1 = smooth_spike_map_1 / smooth_occupancy_map_1
+/home/mikkel/apps/expipe-project/septum-mec/septum_mec/analysis/data_processing.py:590: RuntimeWarning: invalid value encountered in true_divide
+  rate_map_1 = smooth_spike_map_1 / smooth_occupancy_map_1
+/home/mikkel/apps/expipe-project/septum-mec/septum_mec/analysis/data_processing.py:591: RuntimeWarning: divide by zero encountered in true_divide
+  rate_map_2 = smooth_spike_map_2 / smooth_occupancy_map_2
+/home/mikkel/apps/expipe-project/septum-mec/septum_mec/analysis/data_processing.py:591: RuntimeWarning: invalid value encountered in true_divide
+  rate_map_2 = smooth_spike_map_2 / smooth_occupancy_map_2
+/home/mikkel/.virtualenvs/expipe/lib/python3.6/site-packages/numpy/core/fromnumeric.py:90: RuntimeWarning: invalid value encountered in reduce
+  return ufunc.reduce(obj, axis, dtype, out, **passkwargs)
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row_id = ['action', 'channel_group', 'unit_name']
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cmap = ['#252525', '#1b9e77','#d95f02','#7570b3', '#e7298a']
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+    return "{:.2f} ± {:.2f} ({})".format(data.mean(), data.sem(), len(data))
+
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+def MWU(a, b):
+    '''
+    Mann Whitney U
+    '''
+    Uvalue, pvalue = scipy.stats.mannwhitneyu(
+        a, b, alternative='two-sided')
+
+    return "{:.2f}, {:.3f}".format(Uvalue, pvalue)
+
+
+def PRS(df, keys):
+    '''
+    Permutation ReSampling
+    '''
+    pvalue, observed_diff, diffs = permutation_resampling(
+        a, b, statistic=np.median)
+
+    return "{:.2f}, {:.3f}".format(observed_diff, pvalue)
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+for label, data in zip(labels, pairwise_xcorr_cntr_mass):
+    summary.loc['Spatial shift', label] = summarize(pd.Series(data))
+    
+for label, data in zip(labels, pairwise_gridness):
+    data = [d for a in data for d in a]
+    summary.loc['Difference in gridness', label] = summarize(pd.Series(data))
+
+for label, data in zip(labels, pairwise_maxrate):
+    data = [d for a in data for d in a]
+    summary.loc['Relative change in max rate', label] = summarize(pd.Series(data))
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+for label, data in zip(labels, pairwise_avgrate):
+    data = [d for a in data for d in a]
+    summary.loc['Relative change in mean rate', label] = summarize(pd.Series(data))
+
+# for val in data[1:]:
+#     Uvalue, pvalue = scipy.stats.mannwhitneyu(data[0], val, alternative='two-sided')
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Baseline I vs baseline IBaseline I vs baseline IIBaseline I vs stim IBaseline II vs stim IIBaseline I vs stim II
Spatial shift0.03 ± 0.01 (66)0.03 ± 0.00 (21)0.02 ± 0.00 (22)0.02 ± 0.00 (22)0.03 ± 0.00 (12)
Difference in gridness-0.02 ± 0.03 (66)-0.05 ± 0.08 (21)-0.09 ± 0.11 (22)-0.03 ± 0.09 (22)-0.20 ± 0.14 (12)
Relative change in max rate0.05 ± 0.03 (65)0.00 ± 0.07 (21)-0.04 ± 0.07 (22)0.03 ± 0.07 (22)-0.12 ± 0.09 (12)
Relative change in mean rate0.02 ± 0.03 (65)0.09 ± 0.11 (21)-0.03 ± 0.08 (22)0.10 ± 0.08 (22)0.20 ± 0.16 (12)

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+for label, val in zip(labels[1:], pairwise_xcorr_cntr_mass[1:]):
+    stats.loc['Spatial shift', label] = MWU(pairwise_xcorr_cntr_mass[0], val)
+    
+for label, val in zip(labels[1:], pairwise_gridness[1:]):
+    data = [d for a in val for d in a]
+    stats.loc['Difference in gridness', label] = MWU(pairwise_gridness[0], val)
+
+for label, val in zip(labels[1:], pairwise_maxrate[1:]):
+    data = [d for a in val for d in a]
+    stats.loc['Relative change in max rate', label] = MWU(pairwise_maxrate[0], val)
+
+for label, val in zip(labels[1:], pairwise_avgrate[1:]):
+    data = [d for a in val for d in a]
+    stats.loc['Relative change in mean rate', label] = MWU(pairwise_avgrate[0], val)
+
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Baseline I vs baseline IIBaseline I vs stim IBaseline II vs stim IIBaseline I vs stim II
Spatial shift526.00, 0.099688.00, 0.718689.00, 0.725276.00, 0.098
Difference in gridness819.00, 0.213841.00, 0.270757.00, 0.769495.00, 0.173
Relative change in max rate777.00, 0.345833.00, 0.251786.00, 0.491543.00, 0.032
Relative change in mean rate691.00, 0.936887.00, 0.094649.00, 0.522347.00, 0.551

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action = project.require_action("longitudinal-comparisons-gridcells")
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  '/media/storage/expipe/septum-mec/actions/longitudinal-comparisons-gridcells/data/figures/neuron_47_rate_map.png',
  '/media/storage/expipe/septum-mec/actions/longitudinal-comparisons-gridcells/data/figures/neuron_656_speed_map.svg',
  '/media/storage/expipe/septum-mec/actions/longitudinal-comparisons-gridcells/data/figures/neuron_243_spike_map.svg',
- '/media/storage/expipe/septum-mec/actions/longitudinal-comparisons-gridcells/data/figures/violins_spatial_shift.png',
  '/media/storage/expipe/septum-mec/actions/longitudinal-comparisons-gridcells/data/figures/neuron_121_spike_map.png',
  '/media/storage/expipe/septum-mec/actions/longitudinal-comparisons-gridcells/data/figures/neuron_106_rate_map.png',
  '/media/storage/expipe/septum-mec/actions/longitudinal-comparisons-gridcells/data/figures/neuron_234_speed_map.png',
  '/media/storage/expipe/septum-mec/actions/longitudinal-comparisons-gridcells/data/figures/neuron_243_spike_map.png',
  '/media/storage/expipe/septum-mec/actions/longitudinal-comparisons-gridcells/data/figures/neuron_32_speed_map.png',
  '/media/storage/expipe/septum-mec/actions/longitudinal-comparisons-gridcells/data/figures/neuron_250_rate_map.svg',
- '/media/storage/expipe/septum-mec/actions/longitudinal-comparisons-gridcells/data/figures/violins_gridness_difference.png',
+ '/media/storage/expipe/septum-mec/actions/longitudinal-comparisons-gridcells/data/figures/running_speed.svg',
  '/media/storage/expipe/septum-mec/actions/longitudinal-comparisons-gridcells/data/figures/neuron_35_spike_map.svg',
  '/media/storage/expipe/septum-mec/actions/longitudinal-comparisons-gridcells/data/figures/neuron_32_rate_map.svg',
  '/media/storage/expipe/septum-mec/actions/longitudinal-comparisons-gridcells/data/figures/neuron_47_rate_map.svg',
@@ -17194,6 +17476,7 @@ See the caveats in the documentation: http://pandas.pydata.org/pandas-docs/stabl
  '/media/storage/expipe/septum-mec/actions/longitudinal-comparisons-gridcells/data/figures/neuron_30_spike_map.svg',
  '/media/storage/expipe/septum-mec/actions/longitudinal-comparisons-gridcells/data/figures/neuron_150_rate_map.png',
  '/media/storage/expipe/septum-mec/actions/longitudinal-comparisons-gridcells/data/figures/neuron_253_rate_map.svg',
+ '/media/storage/expipe/septum-mec/actions/longitudinal-comparisons-gridcells/data/figures/violins.png',
  '/media/storage/expipe/septum-mec/actions/longitudinal-comparisons-gridcells/data/figures/neuron_361_rate_map.svg',
  '/media/storage/expipe/septum-mec/actions/longitudinal-comparisons-gridcells/data/figures/neuron_30_spike_map.png',
  '/media/storage/expipe/septum-mec/actions/longitudinal-comparisons-gridcells/data/figures/neuron_195_speed_map.svg',
@@ -17230,6 +17513,7 @@ See the caveats in the documentation: http://pandas.pydata.org/pandas-docs/stabl
  '/media/storage/expipe/septum-mec/actions/longitudinal-comparisons-gridcells/data/figures/neuron_715_rate_map.svg',
  '/media/storage/expipe/septum-mec/actions/longitudinal-comparisons-gridcells/data/figures/neuron_26_spike_map.svg',
  '/media/storage/expipe/septum-mec/actions/longitudinal-comparisons-gridcells/data/figures/neuron_26_rate_map.svg',
+ '/media/storage/expipe/septum-mec/actions/longitudinal-comparisons-gridcells/data/figures/violins_swarm.svg',
  '/media/storage/expipe/septum-mec/actions/longitudinal-comparisons-gridcells/data/figures/neuron_253_rate_map.png',
  '/media/storage/expipe/septum-mec/actions/longitudinal-comparisons-gridcells/data/figures/neuron_57_spike_map.png',
  '/media/storage/expipe/septum-mec/actions/longitudinal-comparisons-gridcells/data/figures/baseline_gridness_vs_other.svg',
@@ -17239,11 +17523,11 @@ See the caveats in the documentation: http://pandas.pydata.org/pandas-docs/stabl
  '/media/storage/expipe/septum-mec/actions/longitudinal-comparisons-gridcells/data/figures/neuron_263_rate_map.svg',
  '/media/storage/expipe/septum-mec/actions/longitudinal-comparisons-gridcells/data/figures/baseline_average_rate_vs_other.png',
  '/media/storage/expipe/septum-mec/actions/longitudinal-comparisons-gridcells/data/figures/neuron_79_spike_map.png',
+ '/media/storage/expipe/septum-mec/actions/longitudinal-comparisons-gridcells/data/figures/violins_swarm.png',
  '/media/storage/expipe/septum-mec/actions/longitudinal-comparisons-gridcells/data/figures/neuron_250_speed_map.png',
  '/media/storage/expipe/septum-mec/actions/longitudinal-comparisons-gridcells/data/figures/neuron_130_speed_map.png',
  '/media/storage/expipe/septum-mec/actions/longitudinal-comparisons-gridcells/data/figures/neuron_381_spike_map.png',
  '/media/storage/expipe/septum-mec/actions/longitudinal-comparisons-gridcells/data/figures/neuron_79_rate_map.png',
- '/media/storage/expipe/septum-mec/actions/longitudinal-comparisons-gridcells/data/figures/violins_mean_rate_difference.svg',
  '/media/storage/expipe/septum-mec/actions/longitudinal-comparisons-gridcells/data/figures/neuron_150_spike_map.png',
  '/media/storage/expipe/septum-mec/actions/longitudinal-comparisons-gridcells/data/figures/neuron_357_rate_map.svg',
  '/media/storage/expipe/septum-mec/actions/longitudinal-comparisons-gridcells/data/figures/neuron_149_rate_map.png',
@@ -17266,7 +17550,6 @@ See the caveats in the documentation: http://pandas.pydata.org/pandas-docs/stabl
  '/media/storage/expipe/septum-mec/actions/longitudinal-comparisons-gridcells/data/figures/neuron_121_speed_map.svg',
  '/media/storage/expipe/septum-mec/actions/longitudinal-comparisons-gridcells/data/figures/neuron_655_spike_map.svg',
  '/media/storage/expipe/septum-mec/actions/longitudinal-comparisons-gridcells/data/figures/neuron_357_speed_map.png',
- '/media/storage/expipe/septum-mec/actions/longitudinal-comparisons-gridcells/data/figures/violins_max_rate_difference.png',
  '/media/storage/expipe/septum-mec/actions/longitudinal-comparisons-gridcells/data/figures/neuron_304_speed_map.png',
  '/media/storage/expipe/septum-mec/actions/longitudinal-comparisons-gridcells/data/figures/neuron_30_rate_map.svg',
  '/media/storage/expipe/septum-mec/actions/longitudinal-comparisons-gridcells/data/figures/neuron_106_rate_map.svg',
@@ -17277,13 +17560,11 @@ See the caveats in the documentation: http://pandas.pydata.org/pandas-docs/stabl
  '/media/storage/expipe/septum-mec/actions/longitudinal-comparisons-gridcells/data/figures/neuron_195_rate_map.png',
  '/media/storage/expipe/septum-mec/actions/longitudinal-comparisons-gridcells/data/figures/neuron_13_spike_map.png',
  '/media/storage/expipe/septum-mec/actions/longitudinal-comparisons-gridcells/data/figures/neuron_35_rate_map.png',
- '/media/storage/expipe/septum-mec/actions/longitudinal-comparisons-gridcells/data/figures/violins_gridness_difference.svg',
  '/media/storage/expipe/septum-mec/actions/longitudinal-comparisons-gridcells/data/figures/neuron_317_speed_map.png',
  '/media/storage/expipe/septum-mec/actions/longitudinal-comparisons-gridcells/data/figures/neuron_381_rate_map.svg',
  '/media/storage/expipe/septum-mec/actions/longitudinal-comparisons-gridcells/data/figures/neuron_332_spike_map.svg',
  '/media/storage/expipe/septum-mec/actions/longitudinal-comparisons-gridcells/data/figures/neuron_659_rate_map.png',
  '/media/storage/expipe/septum-mec/actions/longitudinal-comparisons-gridcells/data/figures/baseline_max_rate_vs_other.svg',
- '/media/storage/expipe/septum-mec/actions/longitudinal-comparisons-gridcells/data/figures/violins_spatial_shift.svg',
  '/media/storage/expipe/septum-mec/actions/longitudinal-comparisons-gridcells/data/figures/neuron_31_rate_map.png',
  '/media/storage/expipe/septum-mec/actions/longitudinal-comparisons-gridcells/data/figures/neuron_240_rate_map.png',
  '/media/storage/expipe/septum-mec/actions/longitudinal-comparisons-gridcells/data/figures/neuron_655_speed_map.png',
@@ -17322,6 +17603,7 @@ See the caveats in the documentation: http://pandas.pydata.org/pandas-docs/stabl
  '/media/storage/expipe/septum-mec/actions/longitudinal-comparisons-gridcells/data/figures/neuron_79_speed_map.png',
  '/media/storage/expipe/septum-mec/actions/longitudinal-comparisons-gridcells/data/figures/neuron_232_speed_map.png',
  '/media/storage/expipe/septum-mec/actions/longitudinal-comparisons-gridcells/data/figures/neuron_332_rate_map.svg',
+ '/media/storage/expipe/septum-mec/actions/longitudinal-comparisons-gridcells/data/figures/running_speed.png',
  '/media/storage/expipe/septum-mec/actions/longitudinal-comparisons-gridcells/data/figures/baseline_gridness_vs_other.png',
  '/media/storage/expipe/septum-mec/actions/longitudinal-comparisons-gridcells/data/figures/neuron_656_spike_map.png',
  '/media/storage/expipe/septum-mec/actions/longitudinal-comparisons-gridcells/data/figures/stickplot_gridness.svg',
@@ -17360,13 +17642,12 @@ See the caveats in the documentation: http://pandas.pydata.org/pandas-docs/stabl
  '/media/storage/expipe/septum-mec/actions/longitudinal-comparisons-gridcells/data/figures/neuron_168_spike_map.png',
  '/media/storage/expipe/septum-mec/actions/longitudinal-comparisons-gridcells/data/figures/neuron_655_spike_map.png',
  '/media/storage/expipe/septum-mec/actions/longitudinal-comparisons-gridcells/data/figures/neuron_317_spike_map.png',
- '/media/storage/expipe/septum-mec/actions/longitudinal-comparisons-gridcells/data/figures/violins_max_rate_difference.svg',
  '/media/storage/expipe/septum-mec/actions/longitudinal-comparisons-gridcells/data/figures/neuron_655_speed_map.svg',
  '/media/storage/expipe/septum-mec/actions/longitudinal-comparisons-gridcells/data/figures/neuron_96_rate_map.png',
  '/media/storage/expipe/septum-mec/actions/longitudinal-comparisons-gridcells/data/figures/neuron_250_speed_map.svg',
  '/media/storage/expipe/septum-mec/actions/longitudinal-comparisons-gridcells/data/figures/neuron_715_speed_map.svg',
  '/media/storage/expipe/septum-mec/actions/longitudinal-comparisons-gridcells/data/figures/neuron_381_speed_map.png',
- '/media/storage/expipe/septum-mec/actions/longitudinal-comparisons-gridcells/data/figures/violins_mean_rate_difference.png',
+ '/media/storage/expipe/septum-mec/actions/longitudinal-comparisons-gridcells/data/figures/violins.svg',
  '/media/storage/expipe/septum-mec/actions/longitudinal-comparisons-gridcells/data/figures/neuron_150_speed_map.svg',
  '/media/storage/expipe/septum-mec/actions/longitudinal-comparisons-gridcells/data/figures/neuron_656_rate_map.png',
  '/media/storage/expipe/septum-mec/actions/longitudinal-comparisons-gridcells/data/figures/neuron_149_spike_map.svg',
@@ -17403,7 +17684,7 @@ See the caveats in the documentation: http://pandas.pydata.org/pandas-docs/stabl
 

 

 

-
In [40]:

+
In [215]:

 

     

 
septum_mec.analysis.registration.store_notebook(action, "20_longitudinal_comparisons_gridcells.ipynb")
diff --git a/actions/longitudinal-comparisons-gridcells/data/20_longitudinal_comparisons_gridcells.ipynb b/actions/longitudinal-comparisons-gridcells/data/20_longitudinal_comparisons_gridcells.ipynb
index 0ed7be585..6708a57d6 100644
--- a/actions/longitudinal-comparisons-gridcells/data/20_longitudinal_comparisons_gridcells.ipynb
+++ b/actions/longitudinal-comparisons-gridcells/data/20_longitudinal_comparisons_gridcells.ipynb
@@ -19,6 +19,11 @@
      "name": "stderr",
      "output_type": "stream",
      "text": [
+      "13:55:01 [I] klustakwik KlustaKwik2 version 0.2.6\n",
+      "/home/mikkel/.virtualenvs/expipe/lib/python3.6/importlib/_bootstrap.py:219: RuntimeWarning: numpy.ufunc size changed, may indicate binary incompatibility. Expected 192 from C header, got 216 from PyObject\n",
+      "  return f(*args, **kwds)\n",
+      "/home/mikkel/.virtualenvs/expipe/lib/python3.6/importlib/_bootstrap.py:219: RuntimeWarning: numpy.ufunc size changed, may indicate binary incompatibility. Expected 192 from C header, got 216 from PyObject\n",
+      "  return f(*args, **kwds)\n",
       "/home/mikkel/.virtualenvs/expipe/lib/python3.6/site-packages/ipykernel_launcher.py:25: TqdmDeprecationWarning: This function will be removed in tqdm==5.0.0\n",
       "Please use `tqdm.notebook.*` instead of `tqdm._tqdm_notebook.*`\n"
      ]
@@ -936,9 +941,26 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 38,
+   "execution_count": 19,
    "metadata": {},
-   "outputs": [],
+   "outputs": [
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "/home/mikkel/apps/expipe-project/septum-mec/septum_mec/analysis/data_processing.py:590: RuntimeWarning: divide by zero encountered in true_divide\n",
+      "  rate_map_1 = smooth_spike_map_1 / smooth_occupancy_map_1\n",
+      "/home/mikkel/apps/expipe-project/septum-mec/septum_mec/analysis/data_processing.py:590: RuntimeWarning: invalid value encountered in true_divide\n",
+      "  rate_map_1 = smooth_spike_map_1 / smooth_occupancy_map_1\n",
+      "/home/mikkel/apps/expipe-project/septum-mec/septum_mec/analysis/data_processing.py:591: RuntimeWarning: divide by zero encountered in true_divide\n",
+      "  rate_map_2 = smooth_spike_map_2 / smooth_occupancy_map_2\n",
+      "/home/mikkel/apps/expipe-project/septum-mec/septum_mec/analysis/data_processing.py:591: RuntimeWarning: invalid value encountered in true_divide\n",
+      "  rate_map_2 = smooth_spike_map_2 / smooth_occupancy_map_2\n",
+      "/home/mikkel/.virtualenvs/expipe/lib/python3.6/site-packages/numpy/core/fromnumeric.py:90: RuntimeWarning: invalid value encountered in reduce\n",
+      "  return ufunc.reduce(obj, axis, dtype, out, **passkwargs)\n"
+     ]
+    }
+   ],
    "source": [
     "results_xcorr_displacement = [[], [], [], [], []]\n",
     "results_xcorr_cntr_mass = [[], [], [], [], []]\n",
@@ -998,7 +1020,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 35,
+   "execution_count": 20,
    "metadata": {},
    "outputs": [
     {
@@ -1010,7 +1032,7 @@
        "Name: 1030, dtype: bool"
       ]
      },
-     "execution_count": 35,
+     "execution_count": 20,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -1022,7 +1044,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 23,
+   "execution_count": 21,
    "metadata": {},
    "outputs": [
     {
@@ -1057,7 +1079,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 24,
+   "execution_count": 22,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -2666,7 +2688,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 81,
+   "execution_count": 28,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -2901,7 +2923,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 87,
+   "execution_count": 23,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -2936,7 +2958,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 119,
+   "execution_count": 24,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -2960,7 +2982,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 207,
+   "execution_count": 25,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -3022,7 +3044,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 208,
+   "execution_count": 26,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -3036,12 +3058,12 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 209,
+   "execution_count": 29,
    "metadata": {},
    "outputs": [
     {
      "data": {
-      "image/png": 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\n",
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\n",
       "text/plain": [
        "
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       ]
@@ -3073,6 +3095,261 @@
     "fig.savefig(output_path / 'figures' / 'violins_swarm.svg', bbox_inches='tight')"
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": 40,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "def summarize(data):\n",
+    "    return \"{:.2f} ± {:.2f} ({})\".format(data.mean(), data.sem(), len(data))\n",
+    "\n",
+    "\n",
+    "def MWU(a, b):\n",
+    "    '''\n",
+    "    Mann Whitney U\n",
+    "    '''\n",
+    "    Uvalue, pvalue = scipy.stats.mannwhitneyu(\n",
+    "        a, b, alternative='two-sided')\n",
+    "\n",
+    "    return \"{:.2f}, {:.3f}\".format(Uvalue, pvalue)\n",
+    "\n",
+    "\n",
+    "def PRS(df, keys):\n",
+    "    '''\n",
+    "    Permutation ReSampling\n",
+    "    '''\n",
+    "    pvalue, observed_diff, diffs = permutation_resampling(\n",
+    "        a, b, statistic=np.median)\n",
+    "\n",
+    "    return \"{:.2f}, {:.3f}\".format(observed_diff, pvalue)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 39,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "
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+       "\n",
+       "\n",
+       "  \n",
+       "    \n",
+       "      \n",
+       "      \n",
+       "      \n",
+       "      \n",
+       "      \n",
+       "      \n",
+       "    \n",
+       "  \n",
+       "  \n",
+       "    \n",
+       "      \n",
+       "      \n",
+       "      \n",
+       "      \n",
+       "      \n",
+       "      \n",
+       "    \n",
+       "    \n",
+       "      \n",
+       "      \n",
+       "      \n",
+       "      \n",
+       "      \n",
+       "      \n",
+       "    \n",
+       "    \n",
+       "      \n",
+       "      \n",
+       "      \n",
+       "      \n",
+       "      \n",
+       "      \n",
+       "    \n",
+       "    \n",
+       "      \n",
+       "      \n",
+       "      \n",
+       "      \n",
+       "      \n",
+       "      \n",
+       "    \n",
+       "  \n",
+       "
Baseline I vs baseline IBaseline I vs baseline IIBaseline I vs stim IBaseline II vs stim IIBaseline I vs stim II
Spatial shift0.03 ± 0.01 (66)0.03 ± 0.00 (21)0.02 ± 0.00 (22)0.02 ± 0.00 (22)0.03 ± 0.00 (12)
Difference in gridness-0.02 ± 0.03 (66)-0.05 ± 0.08 (21)-0.09 ± 0.11 (22)-0.03 ± 0.09 (22)-0.20 ± 0.14 (12)
Relative change in max rate0.05 ± 0.03 (65)0.00 ± 0.07 (21)-0.04 ± 0.07 (22)0.03 ± 0.07 (22)-0.12 ± 0.09 (12)
Relative change in mean rate0.02 ± 0.03 (65)0.09 ± 0.11 (21)-0.03 ± 0.08 (22)0.10 ± 0.08 (22)0.20 ± 0.16 (12)
\n",
+       "
"
+      ],
+      "text/plain": [
+       "                             Baseline I vs baseline I  \\\n",
+       "Spatial shift                        0.03 ± 0.01 (66)   \n",
+       "Difference in gridness              -0.02 ± 0.03 (66)   \n",
+       "Relative change in max rate          0.05 ± 0.03 (65)   \n",
+       "Relative change in mean rate         0.02 ± 0.03 (65)   \n",
+       "\n",
+       "                             Baseline I vs baseline II Baseline I vs stim I  \\\n",
+       "Spatial shift                         0.03 ± 0.00 (21)     0.02 ± 0.00 (22)   \n",
+       "Difference in gridness               -0.05 ± 0.08 (21)    -0.09 ± 0.11 (22)   \n",
+       "Relative change in max rate           0.00 ± 0.07 (21)    -0.04 ± 0.07 (22)   \n",
+       "Relative change in mean rate          0.09 ± 0.11 (21)    -0.03 ± 0.08 (22)   \n",
+       "\n",
+       "                             Baseline II vs stim II Baseline I vs stim II  \n",
+       "Spatial shift                      0.02 ± 0.00 (22)      0.03 ± 0.00 (12)  \n",
+       "Difference in gridness            -0.03 ± 0.09 (22)     -0.20 ± 0.14 (12)  \n",
+       "Relative change in max rate        0.03 ± 0.07 (22)     -0.12 ± 0.09 (12)  \n",
+       "Relative change in mean rate       0.10 ± 0.08 (22)      0.20 ± 0.16 (12)  "
+      ]
+     },
+     "execution_count": 39,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "summary = pd.DataFrame()\n",
+    "\n",
+    "for label, data in zip(labels, pairwise_xcorr_cntr_mass):\n",
+    "    summary.loc['Spatial shift', label] = summarize(pd.Series(data))\n",
+    "    \n",
+    "for label, data in zip(labels, pairwise_gridness):\n",
+    "    data = [d for a in data for d in a]\n",
+    "    summary.loc['Difference in gridness', label] = summarize(pd.Series(data))\n",
+    "\n",
+    "for label, data in zip(labels, pairwise_maxrate):\n",
+    "    data = [d for a in data for d in a]\n",
+    "    summary.loc['Relative change in max rate', label] = summarize(pd.Series(data))\n",
+    "\n",
+    "for label, data in zip(labels, pairwise_avgrate):\n",
+    "    data = [d for a in data for d in a]\n",
+    "    summary.loc['Relative change in mean rate', label] = summarize(pd.Series(data))\n",
+    "\n",
+    "# for val in data[1:]:\n",
+    "#     Uvalue, pvalue = scipy.stats.mannwhitneyu(data[0], val, alternative='two-sided')\n",
+    "\n",
+    "#     labels[1:]\n",
+    "summary"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 43,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "
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+       "      \n",
+       "    \n",
+       "  \n",
+       "
Baseline I vs baseline IIBaseline I vs stim IBaseline II vs stim IIBaseline I vs stim II
Spatial shift526.00, 0.099688.00, 0.718689.00, 0.725276.00, 0.098
Difference in gridness819.00, 0.213841.00, 0.270757.00, 0.769495.00, 0.173
Relative change in max rate777.00, 0.345833.00, 0.251786.00, 0.491543.00, 0.032
Relative change in mean rate691.00, 0.936887.00, 0.094649.00, 0.522347.00, 0.551
\n",
+       "
"
+      ],
+      "text/plain": [
+       "                             Baseline I vs baseline II Baseline I vs stim I  \\\n",
+       "Spatial shift                            526.00, 0.099        688.00, 0.718   \n",
+       "Difference in gridness                   819.00, 0.213        841.00, 0.270   \n",
+       "Relative change in max rate              777.00, 0.345        833.00, 0.251   \n",
+       "Relative change in mean rate             691.00, 0.936        887.00, 0.094   \n",
+       "\n",
+       "                             Baseline II vs stim II Baseline I vs stim II  \n",
+       "Spatial shift                         689.00, 0.725         276.00, 0.098  \n",
+       "Difference in gridness                757.00, 0.769         495.00, 0.173  \n",
+       "Relative change in max rate           786.00, 0.491         543.00, 0.032  \n",
+       "Relative change in mean rate          649.00, 0.522         347.00, 0.551  "
+      ]
+     },
+     "execution_count": 43,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "stats = pd.DataFrame()\n",
+    "\n",
+    "for label, val in zip(labels[1:], pairwise_xcorr_cntr_mass[1:]):\n",
+    "    stats.loc['Spatial shift', label] = MWU(pairwise_xcorr_cntr_mass[0], val)\n",
+    "    \n",
+    "for label, val in zip(labels[1:], pairwise_gridness[1:]):\n",
+    "    data = [d for a in val for d in a]\n",
+    "    stats.loc['Difference in gridness', label] = MWU(pairwise_gridness[0], val)\n",
+    "\n",
+    "for label, val in zip(labels[1:], pairwise_maxrate[1:]):\n",
+    "    data = [d for a in val for d in a]\n",
+    "    stats.loc['Relative change in max rate', label] = MWU(pairwise_maxrate[0], val)\n",
+    "\n",
+    "for label, val in zip(labels[1:], pairwise_avgrate[1:]):\n",
+    "    data = [d for a in val for d in a]\n",
+    "    stats.loc['Relative change in mean rate', label] = MWU(pairwise_avgrate[0], val)\n",
+    "\n",
+    "stats"
+   ]
+  },
   {
    "cell_type": "code",
    "execution_count": 212,
@@ -3253,7 +3530,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 38,
+   "execution_count": 213,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -3262,7 +3539,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 39,
+   "execution_count": 214,
    "metadata": {},
    "outputs": [
     {
@@ -3307,14 +3584,13 @@
        " '/media/storage/expipe/septum-mec/actions/longitudinal-comparisons-gridcells/data/figures/neuron_47_rate_map.png',\n",
        " '/media/storage/expipe/septum-mec/actions/longitudinal-comparisons-gridcells/data/figures/neuron_656_speed_map.svg',\n",
        " '/media/storage/expipe/septum-mec/actions/longitudinal-comparisons-gridcells/data/figures/neuron_243_spike_map.svg',\n",
-       " '/media/storage/expipe/septum-mec/actions/longitudinal-comparisons-gridcells/data/figures/violins_spatial_shift.png',\n",
        " '/media/storage/expipe/septum-mec/actions/longitudinal-comparisons-gridcells/data/figures/neuron_121_spike_map.png',\n",
        " '/media/storage/expipe/septum-mec/actions/longitudinal-comparisons-gridcells/data/figures/neuron_106_rate_map.png',\n",
        " '/media/storage/expipe/septum-mec/actions/longitudinal-comparisons-gridcells/data/figures/neuron_234_speed_map.png',\n",
        " '/media/storage/expipe/septum-mec/actions/longitudinal-comparisons-gridcells/data/figures/neuron_243_spike_map.png',\n",
        " '/media/storage/expipe/septum-mec/actions/longitudinal-comparisons-gridcells/data/figures/neuron_32_speed_map.png',\n",
        " '/media/storage/expipe/septum-mec/actions/longitudinal-comparisons-gridcells/data/figures/neuron_250_rate_map.svg',\n",
-       " '/media/storage/expipe/septum-mec/actions/longitudinal-comparisons-gridcells/data/figures/violins_gridness_difference.png',\n",
+       " '/media/storage/expipe/septum-mec/actions/longitudinal-comparisons-gridcells/data/figures/running_speed.svg',\n",
        " '/media/storage/expipe/septum-mec/actions/longitudinal-comparisons-gridcells/data/figures/neuron_35_spike_map.svg',\n",
        " '/media/storage/expipe/septum-mec/actions/longitudinal-comparisons-gridcells/data/figures/neuron_32_rate_map.svg',\n",
        " '/media/storage/expipe/septum-mec/actions/longitudinal-comparisons-gridcells/data/figures/neuron_47_rate_map.svg',\n",
@@ -3329,6 +3605,7 @@
        " '/media/storage/expipe/septum-mec/actions/longitudinal-comparisons-gridcells/data/figures/neuron_30_spike_map.svg',\n",
        " '/media/storage/expipe/septum-mec/actions/longitudinal-comparisons-gridcells/data/figures/neuron_150_rate_map.png',\n",
        " '/media/storage/expipe/septum-mec/actions/longitudinal-comparisons-gridcells/data/figures/neuron_253_rate_map.svg',\n",
+       " '/media/storage/expipe/septum-mec/actions/longitudinal-comparisons-gridcells/data/figures/violins.png',\n",
        " '/media/storage/expipe/septum-mec/actions/longitudinal-comparisons-gridcells/data/figures/neuron_361_rate_map.svg',\n",
        " '/media/storage/expipe/septum-mec/actions/longitudinal-comparisons-gridcells/data/figures/neuron_30_spike_map.png',\n",
        " '/media/storage/expipe/septum-mec/actions/longitudinal-comparisons-gridcells/data/figures/neuron_195_speed_map.svg',\n",
@@ -3365,6 +3642,7 @@
        " '/media/storage/expipe/septum-mec/actions/longitudinal-comparisons-gridcells/data/figures/neuron_715_rate_map.svg',\n",
        " '/media/storage/expipe/septum-mec/actions/longitudinal-comparisons-gridcells/data/figures/neuron_26_spike_map.svg',\n",
        " '/media/storage/expipe/septum-mec/actions/longitudinal-comparisons-gridcells/data/figures/neuron_26_rate_map.svg',\n",
+       " '/media/storage/expipe/septum-mec/actions/longitudinal-comparisons-gridcells/data/figures/violins_swarm.svg',\n",
        " '/media/storage/expipe/septum-mec/actions/longitudinal-comparisons-gridcells/data/figures/neuron_253_rate_map.png',\n",
        " '/media/storage/expipe/septum-mec/actions/longitudinal-comparisons-gridcells/data/figures/neuron_57_spike_map.png',\n",
        " '/media/storage/expipe/septum-mec/actions/longitudinal-comparisons-gridcells/data/figures/baseline_gridness_vs_other.svg',\n",
@@ -3374,11 +3652,11 @@
        " '/media/storage/expipe/septum-mec/actions/longitudinal-comparisons-gridcells/data/figures/neuron_263_rate_map.svg',\n",
        " '/media/storage/expipe/septum-mec/actions/longitudinal-comparisons-gridcells/data/figures/baseline_average_rate_vs_other.png',\n",
        " '/media/storage/expipe/septum-mec/actions/longitudinal-comparisons-gridcells/data/figures/neuron_79_spike_map.png',\n",
+       " '/media/storage/expipe/septum-mec/actions/longitudinal-comparisons-gridcells/data/figures/violins_swarm.png',\n",
        " '/media/storage/expipe/septum-mec/actions/longitudinal-comparisons-gridcells/data/figures/neuron_250_speed_map.png',\n",
        " '/media/storage/expipe/septum-mec/actions/longitudinal-comparisons-gridcells/data/figures/neuron_130_speed_map.png',\n",
        " '/media/storage/expipe/septum-mec/actions/longitudinal-comparisons-gridcells/data/figures/neuron_381_spike_map.png',\n",
        " '/media/storage/expipe/septum-mec/actions/longitudinal-comparisons-gridcells/data/figures/neuron_79_rate_map.png',\n",
-       " '/media/storage/expipe/septum-mec/actions/longitudinal-comparisons-gridcells/data/figures/violins_mean_rate_difference.svg',\n",
        " '/media/storage/expipe/septum-mec/actions/longitudinal-comparisons-gridcells/data/figures/neuron_150_spike_map.png',\n",
        " '/media/storage/expipe/septum-mec/actions/longitudinal-comparisons-gridcells/data/figures/neuron_357_rate_map.svg',\n",
        " '/media/storage/expipe/septum-mec/actions/longitudinal-comparisons-gridcells/data/figures/neuron_149_rate_map.png',\n",
@@ -3401,7 +3679,6 @@
        " '/media/storage/expipe/septum-mec/actions/longitudinal-comparisons-gridcells/data/figures/neuron_121_speed_map.svg',\n",
        " '/media/storage/expipe/septum-mec/actions/longitudinal-comparisons-gridcells/data/figures/neuron_655_spike_map.svg',\n",
        " '/media/storage/expipe/septum-mec/actions/longitudinal-comparisons-gridcells/data/figures/neuron_357_speed_map.png',\n",
-       " '/media/storage/expipe/septum-mec/actions/longitudinal-comparisons-gridcells/data/figures/violins_max_rate_difference.png',\n",
        " '/media/storage/expipe/septum-mec/actions/longitudinal-comparisons-gridcells/data/figures/neuron_304_speed_map.png',\n",
        " '/media/storage/expipe/septum-mec/actions/longitudinal-comparisons-gridcells/data/figures/neuron_30_rate_map.svg',\n",
        " '/media/storage/expipe/septum-mec/actions/longitudinal-comparisons-gridcells/data/figures/neuron_106_rate_map.svg',\n",
@@ -3412,13 +3689,11 @@
        " '/media/storage/expipe/septum-mec/actions/longitudinal-comparisons-gridcells/data/figures/neuron_195_rate_map.png',\n",
        " '/media/storage/expipe/septum-mec/actions/longitudinal-comparisons-gridcells/data/figures/neuron_13_spike_map.png',\n",
        " '/media/storage/expipe/septum-mec/actions/longitudinal-comparisons-gridcells/data/figures/neuron_35_rate_map.png',\n",
-       " '/media/storage/expipe/septum-mec/actions/longitudinal-comparisons-gridcells/data/figures/violins_gridness_difference.svg',\n",
        " '/media/storage/expipe/septum-mec/actions/longitudinal-comparisons-gridcells/data/figures/neuron_317_speed_map.png',\n",
        " '/media/storage/expipe/septum-mec/actions/longitudinal-comparisons-gridcells/data/figures/neuron_381_rate_map.svg',\n",
        " '/media/storage/expipe/septum-mec/actions/longitudinal-comparisons-gridcells/data/figures/neuron_332_spike_map.svg',\n",
        " '/media/storage/expipe/septum-mec/actions/longitudinal-comparisons-gridcells/data/figures/neuron_659_rate_map.png',\n",
        " '/media/storage/expipe/septum-mec/actions/longitudinal-comparisons-gridcells/data/figures/baseline_max_rate_vs_other.svg',\n",
-       " '/media/storage/expipe/septum-mec/actions/longitudinal-comparisons-gridcells/data/figures/violins_spatial_shift.svg',\n",
        " '/media/storage/expipe/septum-mec/actions/longitudinal-comparisons-gridcells/data/figures/neuron_31_rate_map.png',\n",
        " '/media/storage/expipe/septum-mec/actions/longitudinal-comparisons-gridcells/data/figures/neuron_240_rate_map.png',\n",
        " '/media/storage/expipe/septum-mec/actions/longitudinal-comparisons-gridcells/data/figures/neuron_655_speed_map.png',\n",
@@ -3457,6 +3732,7 @@
        " '/media/storage/expipe/septum-mec/actions/longitudinal-comparisons-gridcells/data/figures/neuron_79_speed_map.png',\n",
        " '/media/storage/expipe/septum-mec/actions/longitudinal-comparisons-gridcells/data/figures/neuron_232_speed_map.png',\n",
        " '/media/storage/expipe/septum-mec/actions/longitudinal-comparisons-gridcells/data/figures/neuron_332_rate_map.svg',\n",
+       " '/media/storage/expipe/septum-mec/actions/longitudinal-comparisons-gridcells/data/figures/running_speed.png',\n",
        " '/media/storage/expipe/septum-mec/actions/longitudinal-comparisons-gridcells/data/figures/baseline_gridness_vs_other.png',\n",
        " '/media/storage/expipe/septum-mec/actions/longitudinal-comparisons-gridcells/data/figures/neuron_656_spike_map.png',\n",
        " '/media/storage/expipe/septum-mec/actions/longitudinal-comparisons-gridcells/data/figures/stickplot_gridness.svg',\n",
@@ -3495,13 +3771,12 @@
        " '/media/storage/expipe/septum-mec/actions/longitudinal-comparisons-gridcells/data/figures/neuron_168_spike_map.png',\n",
        " '/media/storage/expipe/septum-mec/actions/longitudinal-comparisons-gridcells/data/figures/neuron_655_spike_map.png',\n",
        " '/media/storage/expipe/septum-mec/actions/longitudinal-comparisons-gridcells/data/figures/neuron_317_spike_map.png',\n",
-       " '/media/storage/expipe/septum-mec/actions/longitudinal-comparisons-gridcells/data/figures/violins_max_rate_difference.svg',\n",
        " '/media/storage/expipe/septum-mec/actions/longitudinal-comparisons-gridcells/data/figures/neuron_655_speed_map.svg',\n",
        " '/media/storage/expipe/septum-mec/actions/longitudinal-comparisons-gridcells/data/figures/neuron_96_rate_map.png',\n",
        " '/media/storage/expipe/septum-mec/actions/longitudinal-comparisons-gridcells/data/figures/neuron_250_speed_map.svg',\n",
        " '/media/storage/expipe/septum-mec/actions/longitudinal-comparisons-gridcells/data/figures/neuron_715_speed_map.svg',\n",
        " '/media/storage/expipe/septum-mec/actions/longitudinal-comparisons-gridcells/data/figures/neuron_381_speed_map.png',\n",
-       " '/media/storage/expipe/septum-mec/actions/longitudinal-comparisons-gridcells/data/figures/violins_mean_rate_difference.png',\n",
+       " '/media/storage/expipe/septum-mec/actions/longitudinal-comparisons-gridcells/data/figures/violins.svg',\n",
        " '/media/storage/expipe/septum-mec/actions/longitudinal-comparisons-gridcells/data/figures/neuron_150_speed_map.svg',\n",
        " '/media/storage/expipe/septum-mec/actions/longitudinal-comparisons-gridcells/data/figures/neuron_656_rate_map.png',\n",
        " '/media/storage/expipe/septum-mec/actions/longitudinal-comparisons-gridcells/data/figures/neuron_149_spike_map.svg',\n",
@@ -3530,7 +3805,7 @@
        " '/media/storage/expipe/septum-mec/actions/longitudinal-comparisons-gridcells/data/figures/neuron_304_rate_map.png']"
       ]
      },
-     "execution_count": 39,
+     "execution_count": 214,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -3541,7 +3816,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 40,
+   "execution_count": 215,
    "metadata": {},
    "outputs": [],
    "source": [
diff --git a/actions/longitudinal-comparisons-gridcells/data/figures/violins_swarm.png b/actions/longitudinal-comparisons-gridcells/data/figures/violins_swarm.png
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R+VRB-Q
 

-
In [1]:

+
In [2]:

 

     

 
%load_ext autoreload
@@ -13129,7 +13129,7 @@ div#notebook {
 

 

 

-
In [167]:

+
In [3]:

 

     

 
import os
@@ -13173,6 +13173,30 @@ div#notebook {
 

 

 
+

+

+
+
+

+
+    

+
+
+

+
13:18:46 [I] klustakwik KlustaKwik2 version 0.2.6
+/home/mikkel/.virtualenvs/expipe/lib/python3.6/importlib/_bootstrap.py:219: RuntimeWarning: numpy.ufunc size changed, may indicate binary incompatibility. Expected 192 from C header, got 216 from PyObject
+  return f(*args, **kwds)
+/home/mikkel/.virtualenvs/expipe/lib/python3.6/importlib/_bootstrap.py:219: RuntimeWarning: numpy.ufunc size changed, may indicate binary incompatibility. Expected 192 from C header, got 216 from PyObject
+  return f(*args, **kwds)
+/home/mikkel/.virtualenvs/expipe/lib/python3.6/importlib/_bootstrap.py:219: RuntimeWarning: numpy.ufunc size changed, may indicate binary incompatibility. Expected 192 from C header, got 216 from PyObject
+  return f(*args, **kwds)
+

+

+

+
+

+

+
 

 

 

@@ -13189,7 +13213,7 @@ div#notebook {
 

 

 

-
In [3]:

+
In [4]:

 

     

 
# %matplotlib notebook
@@ -13203,7 +13227,7 @@ div#notebook {
 

 

 

-
In [4]:

+
In [5]:

 

     

 
project_path = dp.project_path()
@@ -13229,7 +13253,7 @@ div#notebook {
 

 

 

-
In [5]:

+
In [6]:

 

     

 
statistics_action = actions['calculate-statistics']
@@ -13252,7 +13276,7 @@ div#notebook {
 
 

 
-    
Out[5]:

+    
Out[6]:

 
 
 
@@ -13433,7 +13457,7 @@ div#notebook {
 

 

 

-
In [6]:

+
In [7]:

 

     

 
statistics['unit_day'] = statistics.apply(lambda x: str(x.unit_idnum) + '_' + x.action.split('-')[1], axis=1)
@@ -13446,7 +13470,7 @@ div#notebook {
 

 

 

-
In [7]:

+
In [8]:

 

     

 
stim_response_action = actions['stimulus-response']
@@ -13460,7 +13484,7 @@ div#notebook {
 

 

 

-
In [8]:

+
In [9]:

 

     

 
statistics = pd.merge(statistics, stim_response_results, how='left')
@@ -13473,7 +13497,7 @@ div#notebook {
 

 

 

-
In [9]:

+
In [10]:

 

     

 
print('N cells:',statistics.shape[0])
@@ -13504,7 +13528,7 @@ div#notebook {
 

 

 

-
In [10]:

+
In [11]:

 

     

 
shuffling = actions['shuffling']
@@ -13522,7 +13546,7 @@ div#notebook {
 
 

 
-    
Out[10]:

+    
Out[11]:

 
 
 
@@ -13630,7 +13654,7 @@ div#notebook {
 

 

 

-
In [11]:

+
In [12]:

 

     

 
action_columns = ['action', 'channel_group', 'unit_name']
@@ -13651,7 +13675,7 @@ div#notebook {
 
 

 
-    
Out[11]:

+    
Out[12]:

 
 
 
@@ -13839,7 +13863,7 @@ div#notebook {
 

 

 

-
In [12]:

+
In [13]:

 

     

 
data.groupby('stimulated').count()['action']
@@ -13855,7 +13879,7 @@ div#notebook {
 
 

 
-    
Out[12]:

+    
Out[13]:

 
 
 
@@ -13882,7 +13906,7 @@ Name: action, dtype: int64

 

 

 

-
In [13]:

+
In [14]:

 

     

 
query = (
@@ -13929,7 +13953,7 @@ Number of animals 4
 

 

 

-
In [193]:

+
In [17]:

 

     

 
once_a_gridcell = statistics[statistics.unit_day.isin(sessions_above_threshold.unit_day.values)]
@@ -13942,21 +13966,7 @@ Number of animals 4
 

 

 

-
In [172]:

-

-    

-
once_a_gridcell = statistics[statistics.unit_day.isin(
-    sessions_above_threshold.query('baseline and Hz11').unit_day.values)]
-

-
-    

-

-

-
-

-

-

-
In [194]:

+
In [18]:

 

     

 
print("Number of gridcells", once_a_gridcell.unit_idnum.nunique())
@@ -13998,7 +14008,7 @@ Number of animals 4
 

 

 

-
In [195]:

+
In [19]:

 

     

 
baseline_i = once_a_gridcell.query('baseline and Hz11')
@@ -14042,7 +14052,7 @@ Number of gridcells in stimulated 30Hz ms sessions 40
 

 

 

-
In [196]:

+
In [20]:

 

     

 
baseline_ids = baseline_i.unit_day.unique()
@@ -14055,7 +14065,7 @@ Number of gridcells in stimulated 30Hz ms sessions 40
 

 

 

-
In [197]:

+
In [21]:

 

     

 
baseline_ids
@@ -14071,7 +14081,7 @@ Number of gridcells in stimulated 30Hz ms sessions 40
 
 

 
-    
Out[197]:

+    
Out[21]:

 
 
 
@@ -14103,7 +14113,7 @@ Number of gridcells in stimulated 30Hz ms sessions 40
 

 

 

-
In [198]:

+
In [22]:

 

     

 
stimulated_11_sub = stimulated_11[stimulated_11.unit_day.isin(baseline_ids)]
@@ -14116,7 +14126,7 @@ Number of gridcells in stimulated 30Hz ms sessions 40
 

 

 

-
In [199]:

+
In [23]:

 

     

 
baseline_ids_11 = stimulated_11_sub.unit_day.unique()
@@ -14129,7 +14139,7 @@ Number of gridcells in stimulated 30Hz ms sessions 40
 

 

 

-
In [200]:

+
In [24]:

 

     

 
baseline_i_sub = baseline_i[baseline_i.unit_day.isin(baseline_ids_11)]
@@ -14149,7 +14159,7 @@ Number of gridcells in stimulated 30Hz ms sessions 40
 

 

 

-
In [201]:

+
In [25]:

 

     

 
max_speed = .5 # m/s only used for speed score
@@ -14175,7 +14185,7 @@ Number of gridcells in stimulated 30Hz ms sessions 40
 

 

 

-
In [202]:

+
In [26]:

 

     

 
data_loader = dp.Data(
@@ -14193,7 +14203,7 @@ Number of gridcells in stimulated 30Hz ms sessions 40
 

 

 

-
In [203]:

+
In [27]:

 

     

 
def find_grid_fields(rate_map, sigma=3, seed=2.5):
@@ -14229,7 +14239,7 @@ Number of gridcells in stimulated 30Hz ms sessions 40
 

 

 

-
In [204]:

+
In [28]:

 

     

 
def get_data(row):
@@ -14262,7 +14272,7 @@ Number of gridcells in stimulated 30Hz ms sessions 40
 

 

 

-
In [205]:

+
In [29]:

 

     

 
def compute_field_spikes(row, plot=False, z1=5e-3, z2=11e-3, surrogate_fields=None):
@@ -14348,7 +14358,7 @@ Number of gridcells in stimulated 30Hz ms sessions 40
 

 

 

-
In [342]:

+
In [30]:

 

     

 
def plot_stim_field_spikes(row, t1=0, t2=30, z1_base=0, z2_base=5, z1_stim=5, z2_stim=11, colors=['k','r']):
@@ -15661,7 +15671,7 @@ Number of gridcells in stimulated 30Hz ms sessions 40
 

 

 

-
In [343]:

+
In [31]:

 

     

 
plt.rc('axes', titlesize=12)
@@ -15714,7 +15724,7 @@ Number of gridcells in stimulated 30Hz ms sessions 40
 

 

 

-
In [254]:

+
In [32]:

 

     

 
results_stim_stim_11 = []
@@ -15742,7 +15752,7 @@ Number of gridcells in stimulated 30Hz ms sessions 40
 

 

 

-
In [257]:

+
In [33]:

 

     

 
results_stim_stim_11 = pd.DataFrame(results_stim_stim_11)
@@ -15759,7 +15769,7 @@ Number of gridcells in stimulated 30Hz ms sessions 40
 
 

 
-    
Out[257]:

+    
Out[33]:

 
 
 
@@ -15856,7 +15866,7 @@ Number of gridcells in stimulated 30Hz ms sessions 40
 

 

 

-
In [255]:

+
In [34]:

 

     

 
results_stim_stim_30 = []
@@ -15884,7 +15894,7 @@ Number of gridcells in stimulated 30Hz ms sessions 40
 

 

 

-
In [258]:

+
In [35]:

 

     

 
results_stim_stim_30 = pd.DataFrame(results_stim_stim_30)
@@ -15901,7 +15911,7 @@ Number of gridcells in stimulated 30Hz ms sessions 40
 
 

 
-    
Out[258]:

+    
Out[35]:

 
 
 
@@ -16142,7 +16152,7 @@ Number of gridcells in stimulated 30Hz ms sessions 40
 

 

 

-
In [336]:

+
In [36]:

 

     

 
results_stim_stim_all = pd.concat([results_stim_stim_11, results_stim_stim_30])
@@ -16155,7 +16165,7 @@ Number of gridcells in stimulated 30Hz ms sessions 40
 

 

 

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In [339]:

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In [37]:

 

     

 
plt.rc('axes', titlesize=12)
@@ -16273,16 +16283,147 @@ Number of gridcells in stimulated 30Hz ms sessions 40
 

 

 

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In [115]:

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In [38]:

 

     

-
 
+
def summarize(data):
+    return "{:.2f} ± {:.2f} ({})".format(data.mean(), data.sem(), sum(~np.isnan(data)))
+
+
+def Wilcoxon(df, keys):
+    '''
+    Wilcoxon
+    '''
+    Uvalue, pvalue = scipy.stats.wilcoxon(
+        df[keys[0]].dropna(), 
+        df[keys[1]].dropna(),
+        alternative='two-sided')
+
+    return "{:.2f}, {:.3f}".format(Uvalue, pvalue)
 

 
     

 

 

 
+

+

+

+
In [40]:

+

+    

+
results_stim_stim_all.base_in_field.agg(summarize)
+

+
+    

+

+

+
+

+

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+
+

+
+    
Out[40]:

+
+
+
+
+

+
'0.48 ± 0.02 (101)'

+

+
+

+
+

+

+
+

+

+

+
In [49]:

+

+    

+
stat = pd.DataFrame()
+
+stat['Combined'] = results_stim_stim_all.agg(summarize)
+stat['11 Hz'] = results_stim_stim_11.agg(summarize)
+stat['30 Hz'] = results_stim_stim_30.agg(summarize)
+
+stat.loc['W', 'Combined'] = Wilcoxon(results_stim_stim_all, ['base_in_field', 'stim_in_field'])
+
+stat
+    
+

+
+    

+

+

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+

+
+
+

+
+    
Out[49]:

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+
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+

+

+
+
+  
+    
+      
+      
+      
+      
+    
+  
+  
+    
+      
+      
+      
+      
+    
+    
+      
+      
+      
+      
+    
+    
+      
+      
+      
+      
+    
+  
+
Combined11 Hz30 Hz
base_in_field0.48 ± 0.02 (101)0.47 ± 0.02 (61)0.48 ± 0.02 (40)
stim_in_field0.54 ± 0.01 (101)0.54 ± 0.02 (61)0.52 ± 0.02 (40)
MWU380.00, 0.000NaNNaN

+

+

+
+

+
+

+

+
 

 

 

@@ -17820,6 +17961,79 @@ Number of gridcells in stimulated 30Hz ms sessions 40
 

 

 
+

+

+

+

+
save to expipe

+

+

+

+

+

+
In [344]:

+

+    

+
action = project.require_action("spikes-in-field")
+

+
+    

+

+

+
+

+

+

+
In [345]:

+

+    

+
copy_tree(output_path, str(action.data_path()))
+

+
+    

+

+

+
+

+

+
+
+

+
+    
Out[345]:

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+
+
+
+

+
['/media/storage/expipe/septum-mec/actions/spikes-in-field/data/figures/stim_field_spikes_30.svg',
+ '/media/storage/expipe/septum-mec/actions/spikes-in-field/data/figures/stim_field_spikes_example.svg',
+ '/media/storage/expipe/septum-mec/actions/spikes-in-field/data/figures/stim_field_spikes_11.svg',
+ '/media/storage/expipe/septum-mec/actions/spikes-in-field/data/figures/stim_field_spikes_example.png',
+ '/media/storage/expipe/septum-mec/actions/spikes-in-field/data/figures/stim_field_spikes_combined.svg',
+ '/media/storage/expipe/septum-mec/actions/spikes-in-field/data/figures/stim_field_spikes_combined.png',
+ '/media/storage/expipe/septum-mec/actions/spikes-in-field/data/figures/stim_field_spikes_30.png',
+ '/media/storage/expipe/septum-mec/actions/spikes-in-field/data/figures/stim_field_spikes_11.png']

+

+
+

+
+

+

+
+

+

+

+
In [346]:

+

+    

+
septum_mec.analysis.registration.store_notebook(action, "20_spikes_in_field.ipynb")
+

+
+    

+

+

+
 

 

 

diff --git a/actions/spikes-in-field/data/20_spikes_in_field.ipynb b/actions/spikes-in-field/data/20_spikes_in_field.ipynb
index 00cfa4a60..2513b6506 100644
--- a/actions/spikes-in-field/data/20_spikes_in_field.ipynb
+++ b/actions/spikes-in-field/data/20_spikes_in_field.ipynb
@@ -2,7 +2,7 @@
  "cells": [
   {
    "cell_type": "code",
-   "execution_count": 1,
+   "execution_count": 2,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -12,9 +12,23 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 167,
+   "execution_count": 3,
    "metadata": {},
-   "outputs": [],
+   "outputs": [
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "13:18:46 [I] klustakwik KlustaKwik2 version 0.2.6\n",
+      "/home/mikkel/.virtualenvs/expipe/lib/python3.6/importlib/_bootstrap.py:219: RuntimeWarning: numpy.ufunc size changed, may indicate binary incompatibility. Expected 192 from C header, got 216 from PyObject\n",
+      "  return f(*args, **kwds)\n",
+      "/home/mikkel/.virtualenvs/expipe/lib/python3.6/importlib/_bootstrap.py:219: RuntimeWarning: numpy.ufunc size changed, may indicate binary incompatibility. Expected 192 from C header, got 216 from PyObject\n",
+      "  return f(*args, **kwds)\n",
+      "/home/mikkel/.virtualenvs/expipe/lib/python3.6/importlib/_bootstrap.py:219: RuntimeWarning: numpy.ufunc size changed, may indicate binary incompatibility. Expected 192 from C header, got 216 from PyObject\n",
+      "  return f(*args, **kwds)\n"
+     ]
+    }
+   ],
    "source": [
     "import os\n",
     "import pathlib\n",
@@ -62,7 +76,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 3,
+   "execution_count": 4,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -72,7 +86,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 4,
+   "execution_count": 5,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -94,7 +108,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 5,
+   "execution_count": 6,
    "metadata": {},
    "outputs": [
     {
@@ -306,7 +320,7 @@
        "[5 rows x 39 columns]"
       ]
      },
-     "execution_count": 5,
+     "execution_count": 6,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -324,7 +338,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 6,
+   "execution_count": 7,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -333,7 +347,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 7,
+   "execution_count": 8,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -343,7 +357,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 8,
+   "execution_count": 9,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -352,7 +366,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 9,
+   "execution_count": 10,
    "metadata": {},
    "outputs": [
     {
@@ -369,7 +383,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 10,
+   "execution_count": 11,
    "metadata": {},
    "outputs": [
     {
@@ -485,7 +499,7 @@
        "4     0.094041  1833-010719-1            0.0      225.0  "
       ]
      },
-     "execution_count": 10,
+     "execution_count": 11,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -498,7 +512,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 11,
+   "execution_count": 12,
    "metadata": {},
    "outputs": [
     {
@@ -710,7 +724,7 @@
        "[5 rows x 51 columns]"
       ]
      },
-     "execution_count": 11,
+     "execution_count": 12,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -733,7 +747,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 12,
+   "execution_count": 13,
    "metadata": {},
    "outputs": [
     {
@@ -745,7 +759,7 @@
        "Name: action, dtype: int64"
       ]
      },
-     "execution_count": 12,
+     "execution_count": 13,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -763,7 +777,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 13,
+   "execution_count": 14,
    "metadata": {},
    "outputs": [
     {
@@ -796,7 +810,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 193,
+   "execution_count": 17,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -805,17 +819,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 172,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "once_a_gridcell = statistics[statistics.unit_day.isin(\n",
-    "    sessions_above_threshold.query('baseline and Hz11').unit_day.values)]"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 194,
+   "execution_count": 18,
    "metadata": {},
    "outputs": [
     {
@@ -843,7 +847,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 195,
+   "execution_count": 19,
    "metadata": {},
    "outputs": [
     {
@@ -873,7 +877,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 196,
+   "execution_count": 20,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -882,7 +886,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 197,
+   "execution_count": 21,
    "metadata": {},
    "outputs": [
     {
@@ -906,7 +910,7 @@
        "       '253_200619', '304_200619', '932_280219'], dtype=object)"
       ]
      },
-     "execution_count": 197,
+     "execution_count": 21,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -917,7 +921,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 198,
+   "execution_count": 22,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -926,7 +930,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 199,
+   "execution_count": 23,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -935,7 +939,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 200,
+   "execution_count": 24,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -951,7 +955,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 201,
+   "execution_count": 25,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -973,7 +977,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 202,
+   "execution_count": 26,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -987,7 +991,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 203,
+   "execution_count": 27,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -1019,7 +1023,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 204,
+   "execution_count": 28,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -1048,7 +1052,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 205,
+   "execution_count": 29,
    "metadata": {
     "scrolled": false
    },
@@ -1132,7 +1136,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 342,
+   "execution_count": 30,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -2041,7 +2045,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 343,
+   "execution_count": 31,
    "metadata": {},
    "outputs": [
     {
@@ -2081,7 +2085,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 254,
+   "execution_count": 32,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -2105,7 +2109,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 257,
+   "execution_count": 33,
    "metadata": {},
    "outputs": [
     {
@@ -2211,7 +2215,7 @@
        "[61 rows x 2 columns]"
       ]
      },
-     "execution_count": 257,
+     "execution_count": 33,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -2223,7 +2227,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 255,
+   "execution_count": 34,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -2247,7 +2251,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 258,
+   "execution_count": 35,
    "metadata": {
     "scrolled": true
    },
@@ -2526,7 +2530,7 @@
        "39       0.526316       0.660650"
       ]
      },
-     "execution_count": 258,
+     "execution_count": 35,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -2538,7 +2542,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 336,
+   "execution_count": 36,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -2547,7 +2551,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 339,
+   "execution_count": 37,
    "metadata": {},
    "outputs": [
     {
@@ -2646,10 +2650,124 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 115,
+   "execution_count": 38,
    "metadata": {},
    "outputs": [],
-   "source": []
+   "source": [
+    "def summarize(data):\n",
+    "    return \"{:.2f} ± {:.2f} ({})\".format(data.mean(), data.sem(), sum(~np.isnan(data)))\n",
+    "\n",
+    "\n",
+    "def Wilcoxon(df, keys):\n",
+    "    '''\n",
+    "    Wilcoxon\n",
+    "    '''\n",
+    "    Uvalue, pvalue = scipy.stats.wilcoxon(\n",
+    "        df[keys[0]].dropna(), \n",
+    "        df[keys[1]].dropna(),\n",
+    "        alternative='two-sided')\n",
+    "\n",
+    "    return \"{:.2f}, {:.3f}\".format(Uvalue, pvalue)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 40,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "'0.48 ± 0.02 (101)'"
+      ]
+     },
+     "execution_count": 40,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "results_stim_stim_all.base_in_field.agg(summarize)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 49,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "
\n",
+       "\n",
+       "\n",
+       "  \n",
+       "    \n",
+       "      \n",
+       "      \n",
+       "      \n",
+       "      \n",
+       "    \n",
+       "  \n",
+       "  \n",
+       "    \n",
+       "      \n",
+       "      \n",
+       "      \n",
+       "      \n",
+       "    \n",
+       "    \n",
+       "      \n",
+       "      \n",
+       "      \n",
+       "      \n",
+       "    \n",
+       "    \n",
+       "      \n",
+       "      \n",
+       "      \n",
+       "      \n",
+       "    \n",
+       "  \n",
+       "
Combined11 Hz30 Hz
base_in_field0.48 ± 0.02 (101)0.47 ± 0.02 (61)0.48 ± 0.02 (40)
stim_in_field0.54 ± 0.01 (101)0.54 ± 0.02 (61)0.52 ± 0.02 (40)
MWU380.00, 0.000NaNNaN
\n",
+       "
"
+      ],
+      "text/plain": [
+       "                        Combined             11 Hz             30 Hz\n",
+       "base_in_field  0.48 ± 0.02 (101)  0.47 ± 0.02 (61)  0.48 ± 0.02 (40)\n",
+       "stim_in_field  0.54 ± 0.01 (101)  0.54 ± 0.02 (61)  0.52 ± 0.02 (40)\n",
+       "MWU                380.00, 0.000               NaN               NaN"
+      ]
+     },
+     "execution_count": 49,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "stat = pd.DataFrame()\n",
+    "\n",
+    "stat['Combined'] = results_stim_stim_all.agg(summarize)\n",
+    "stat['11 Hz'] = results_stim_stim_11.agg(summarize)\n",
+    "stat['30 Hz'] = results_stim_stim_30.agg(summarize)\n",
+    "\n",
+    "stat.loc['W', 'Combined'] = Wilcoxon(results_stim_stim_all, ['base_in_field', 'stim_in_field'])\n",
+    "\n",
+    "stat\n",
+    "    \n"
+   ]
   },
   {
    "cell_type": "markdown",
@@ -4101,6 +4219,58 @@
     "baseline_i.merge(stimulated_11, on='unit_day', suffixes=['_base', '_stim'])"
    ]
   },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "# save to expipe"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 344,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "action = project.require_action(\"spikes-in-field\")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 345,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "['/media/storage/expipe/septum-mec/actions/spikes-in-field/data/figures/stim_field_spikes_30.svg',\n",
+       " '/media/storage/expipe/septum-mec/actions/spikes-in-field/data/figures/stim_field_spikes_example.svg',\n",
+       " '/media/storage/expipe/septum-mec/actions/spikes-in-field/data/figures/stim_field_spikes_11.svg',\n",
+       " '/media/storage/expipe/septum-mec/actions/spikes-in-field/data/figures/stim_field_spikes_example.png',\n",
+       " '/media/storage/expipe/septum-mec/actions/spikes-in-field/data/figures/stim_field_spikes_combined.svg',\n",
+       " '/media/storage/expipe/septum-mec/actions/spikes-in-field/data/figures/stim_field_spikes_combined.png',\n",
+       " '/media/storage/expipe/septum-mec/actions/spikes-in-field/data/figures/stim_field_spikes_30.png',\n",
+       " '/media/storage/expipe/septum-mec/actions/spikes-in-field/data/figures/stim_field_spikes_11.png']"
+      ]
+     },
+     "execution_count": 345,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "copy_tree(output_path, str(action.data_path()))"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 346,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "septum_mec.analysis.registration.store_notebook(action, \"20_spikes_in_field.ipynb\")"
+   ]
+  },
   {
    "cell_type": "code",
    "execution_count": null,
diff --git a/actions/spikes-in-field/data/figures/stim_field_spikes_11.svg b/actions/spikes-in-field/data/figures/stim_field_spikes_11.svg
index da66d678d..5f2a620ff 100644
--- a/actions/spikes-in-field/data/figures/stim_field_spikes_11.svg
+++ b/actions/spikes-in-field/data/figures/stim_field_spikes_11.svg
@@ -1,3 +1,3 @@
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-oid sha256:fe803d9f930cb5dab8029f01e75c7cbf9ca4e3f6bba6a344daa430c5e48aa05c
+oid sha256:de928682b6bd18099a63c943086673f98f577b9665100cecc3e2555171098799
 size 31137
diff --git a/actions/spikes-in-field/data/figures/stim_field_spikes_30.svg b/actions/spikes-in-field/data/figures/stim_field_spikes_30.svg
index 33314d68f..070ba2fd9 100644
--- a/actions/spikes-in-field/data/figures/stim_field_spikes_30.svg
+++ b/actions/spikes-in-field/data/figures/stim_field_spikes_30.svg
@@ -1,3 +1,3 @@
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 size 30727
diff --git a/actions/spikes-in-field/data/figures/stim_field_spikes_combined.svg b/actions/spikes-in-field/data/figures/stim_field_spikes_combined.svg
index d3fe18a96..4e8e44a24 100644
--- a/actions/spikes-in-field/data/figures/stim_field_spikes_combined.svg
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diff --git a/actions/spikes-in-field/data/figures/stim_field_spikes_example.svg b/actions/spikes-in-field/data/figures/stim_field_spikes_example.svg
index 7ae87137d..5095b3796 100644
--- a/actions/spikes-in-field/data/figures/stim_field_spikes_example.svg
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diff --git a/actions/spikes-in-field/data/statistics/statistics.csv b/actions/spikes-in-field/data/statistics/statistics.csv
new file mode 100644
index 000000000..72355fe02
--- /dev/null
+++ b/actions/spikes-in-field/data/statistics/statistics.csv
@@ -0,0 +1,4 @@
+,Combined,11 Hz,30 Hz
+base_in_field,0.48 ± 0.02 (101),0.47 ± 0.02 (61),0.48 ± 0.02 (40)
+stim_in_field,0.54 ± 0.01 (101),0.54 ± 0.02 (61),0.52 ± 0.02 (40)
+Wilcoxon,"380.00, 0.000","35.00, 0.000","143.00, 0.000"
diff --git a/actions/spikes-in-field/data/statistics/statistics.tex b/actions/spikes-in-field/data/statistics/statistics.tex
new file mode 100644
index 000000000..e505248de
--- /dev/null
+++ b/actions/spikes-in-field/data/statistics/statistics.tex
@@ -0,0 +1,9 @@
+\begin{tabular}{llll}
+\toprule
+{} &           Combined &             11 Hz &             30 Hz \\
+\midrule
+base\_in\_field &  0.48 ± 0.02 (101) &  0.47 ± 0.02 (61) &  0.48 ± 0.02 (40) \\
+stim\_in\_field &  0.54 ± 0.01 (101) &  0.54 ± 0.02 (61) &  0.52 ± 0.02 (40) \\
+Wilcoxon      &      380.00, 0.000 &      35.00, 0.000 &     143.00, 0.000 \\
+\bottomrule
+\end{tabular}
diff --git a/actions/stimulus-lfp-response/data/20_stimulus-lfp-response.html b/actions/stimulus-lfp-response/data/20_stimulus-lfp-response.html
index 55274b67e..991bff42f 100644
--- a/actions/stimulus-lfp-response/data/20_stimulus-lfp-response.html
+++ b/actions/stimulus-lfp-response/data/20_stimulus-lfp-response.html
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13:24:34 [I] klustakwik KlustaKwik2 version 0.2.6
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12:50:36 [I] klustakwik KlustaKwik2 version 0.2.6
 

 

 

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density = True
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density = True
@@ -13675,7 +13675,7 @@ div#notebook {
 

 

 

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def summarize(data):
@@ -13716,7 +13716,7 @@ div#notebook {
 

 

 

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stat = pd.DataFrame()
@@ -13744,7 +13744,7 @@ div#notebook {
 
 

 
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stat.to_latex(output_path / "statistics" / "statistics.tex")
-stat.to_latex(output_path / "statistics" / "statistics.csv")
+stat.to_csv(output_path / "statistics" / "statistics.csv")
 

 
     

@@ -13988,7 +13988,7 @@ div#notebook {
 

 

 

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psd = pd.read_feather(output_path / 'data' / 'psd.feather')
@@ -14002,7 +14002,7 @@ div#notebook {
 

 

 

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from septum_mec.analysis.plotting import plot_bootstrap_timeseries
@@ -14015,7 +14015,7 @@ div#notebook {
 

 

 

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freq = freqs.T.iloc[0].values
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fig, axs = plt.subplots(1, 2, sharex=True, sharey=True, figsize=(5,2))
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@@ -14094,7 +14072,7 @@ div#notebook {
 

 

 

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action = project.require_action("stimulus-lfp-response")
@@ -14107,7 +14085,7 @@ div#notebook {
 

 

 

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copy_tree(output_path, str(action.data_path()))
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Out[26]:

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['/media/storage/expipe/septum-mec/actions/stimulus-lfp-response/data/data/psd.feather',
- '/media/storage/expipe/septum-mec/actions/stimulus-lfp-response/data/data/freqs.feather',
- '/media/storage/expipe/septum-mec/actions/stimulus-lfp-response/data/figures/lfp-psd-histogram-stim_energy.png',
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- '/media/storage/expipe/septum-mec/actions/stimulus-lfp-response/data/figures/lfp-psd.png',
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septum_mec.analysis.registration.store_notebook(action, "20_stimulus-lfp-response.ipynb")
diff --git a/actions/stimulus-lfp-response/data/20_stimulus-lfp-response.ipynb b/actions/stimulus-lfp-response/data/20_stimulus-lfp-response.ipynb
index 2d27b2e14..d4447580a 100644
--- a/actions/stimulus-lfp-response/data/20_stimulus-lfp-response.ipynb
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-      "text/plain": [
-       "
"
-      ]
-     },
-     "metadata": {
-      "needs_background": "light"
-     },
-     "output_type": "display_data"
-    }
-   ],
+   "outputs": [],
    "source": [
     "\n",
     "fig, axs = plt.subplots(1, 2, sharex=True, sharey=True, figsize=(5,2))\n",
@@ -916,7 +903,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 25,
+   "execution_count": null,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -925,46 +912,16 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 26,
+   "execution_count": null,
    "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "['/media/storage/expipe/septum-mec/actions/stimulus-lfp-response/data/data/psd.feather',\n",
-       " '/media/storage/expipe/septum-mec/actions/stimulus-lfp-response/data/data/freqs.feather',\n",
-       " '/media/storage/expipe/septum-mec/actions/stimulus-lfp-response/data/figures/lfp-psd-histogram-stim_energy.png',\n",
-       " '/media/storage/expipe/septum-mec/actions/stimulus-lfp-response/data/figures/lfp-psd-histogram-stim_strength.png',\n",
-       " '/media/storage/expipe/septum-mec/actions/stimulus-lfp-response/data/figures/lfp-psd.png',\n",
-       " '/media/storage/expipe/septum-mec/actions/stimulus-lfp-response/data/figures/lfp-psd-histogram-theta_peak.svg',\n",
-       " '/media/storage/expipe/septum-mec/actions/stimulus-lfp-response/data/figures/lfp-psd-histogram-stim_p_max.png',\n",
-       " '/media/storage/expipe/septum-mec/actions/stimulus-lfp-response/data/figures/lfp-psd-histogram-theta_freq.png',\n",
-       " '/media/storage/expipe/septum-mec/actions/stimulus-lfp-response/data/figures/lfp-psd-histogram-theta_energy.svg',\n",
-       " '/media/storage/expipe/septum-mec/actions/stimulus-lfp-response/data/figures/lfp-psd-histogram-theta_freq.svg',\n",
-       " '/media/storage/expipe/septum-mec/actions/stimulus-lfp-response/data/figures/lfp-psd-histogram-stim_half_width.png',\n",
-       " '/media/storage/expipe/septum-mec/actions/stimulus-lfp-response/data/figures/lfp-psd-histogram-stim_half_width.svg',\n",
-       " '/media/storage/expipe/septum-mec/actions/stimulus-lfp-response/data/figures/lfp-psd-histogram-theta_half_width.svg',\n",
-       " '/media/storage/expipe/septum-mec/actions/stimulus-lfp-response/data/figures/lfp-psd-histogram-theta_energy.png',\n",
-       " '/media/storage/expipe/septum-mec/actions/stimulus-lfp-response/data/figures/lfp-psd-histogram-theta_peak.png',\n",
-       " '/media/storage/expipe/septum-mec/actions/stimulus-lfp-response/data/figures/lfp-psd-histogram-stim_p_max.svg',\n",
-       " '/media/storage/expipe/septum-mec/actions/stimulus-lfp-response/data/figures/lfp-psd-histogram-theta_half_width.png',\n",
-       " '/media/storage/expipe/septum-mec/actions/stimulus-lfp-response/data/figures/lfp-psd.svg',\n",
-       " '/media/storage/expipe/septum-mec/actions/stimulus-lfp-response/data/figures/lfp-psd-histogram-stim_energy.svg',\n",
-       " '/media/storage/expipe/septum-mec/actions/stimulus-lfp-response/data/figures/lfp-psd-histogram-stim_strength.svg']"
-      ]
-     },
-     "execution_count": 26,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
+   "outputs": [],
    "source": [
     "copy_tree(output_path, str(action.data_path()))"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 27,
+   "execution_count": null,
    "metadata": {},
    "outputs": [],
    "source": [
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index 8fa9e5bd7..ea43b5fd3 100644
--- a/actions/stimulus-lfp-response/data/figures/lfp-psd-histogram-stim_energy.svg
+++ b/actions/stimulus-lfp-response/data/figures/lfp-psd-histogram-stim_energy.svg
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index 8873c804b..36f8dea6d 100644
--- a/actions/stimulus-lfp-response/data/figures/lfp-psd-histogram-stim_half_width.svg
+++ b/actions/stimulus-lfp-response/data/figures/lfp-psd-histogram-stim_half_width.svg
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index 611caeb97..d5bcd7da5 100644
--- a/actions/stimulus-lfp-response/data/figures/lfp-psd-histogram-stim_p_max.svg
+++ b/actions/stimulus-lfp-response/data/figures/lfp-psd-histogram-stim_p_max.svg
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index 631ecf9ac..6271b07eb 100644
--- a/actions/stimulus-lfp-response/data/figures/lfp-psd-histogram-stim_strength.svg
+++ b/actions/stimulus-lfp-response/data/figures/lfp-psd-histogram-stim_strength.svg
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index a091075f7..756924b10 100644
--- a/actions/stimulus-lfp-response/data/figures/lfp-psd-histogram-theta_energy.svg
+++ b/actions/stimulus-lfp-response/data/figures/lfp-psd-histogram-theta_energy.svg
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diff --git a/actions/stimulus-lfp-response/data/figures/lfp-psd.svg b/actions/stimulus-lfp-response/data/figures/lfp-psd.svg
index d6b9ee65e..cccb2813b 100644
--- a/actions/stimulus-lfp-response/data/figures/lfp-psd.svg
+++ b/actions/stimulus-lfp-response/data/figures/lfp-psd.svg
@@ -1,3 +1,3 @@
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+size 163875
diff --git a/actions/stimulus-lfp-response/data/statistics/statistics.csv b/actions/stimulus-lfp-response/data/statistics/statistics.csv
index da5065291..b3a945cd9 100644
--- a/actions/stimulus-lfp-response/data/statistics/statistics.csv
+++ b/actions/stimulus-lfp-response/data/statistics/statistics.csv
@@ -1,22 +1,17 @@
-\begin{tabular}{lllllllll}
-\toprule
-{} &      Theta energy &        Theta peak &        Theta freq &  Theta half width &       Stim energy &   Stim half width &        Stim p max &      Stim strength \\
-\midrule
-Baseline I                 &  0.25 ± 0.02 (48) &  0.18 ± 0.02 (48) &  7.78 ± 0.09 (48) &  1.79 ± 0.33 (46) &               NaN &               NaN &               NaN &                NaN \\
-11 Hz                      &  0.08 ± 0.00 (44) &  0.03 ± 0.00 (44) &  7.55 ± 0.12 (44) &  5.80 ± 0.50 (43) &  0.05 ± 0.00 (44) &  0.16 ± 0.00 (44) &  0.51 ± 0.04 (44) &   7.14 ± 0.81 (44) \\
-Baseline II                &  0.24 ± 0.02 (34) &  0.17 ± 0.02 (34) &  7.96 ± 0.09 (34) &  1.23 ± 0.22 (33) &               NaN &               NaN &               NaN &                NaN \\
-30 Hz                      &  0.04 ± 0.00 (34) &  0.02 ± 0.00 (34) &  7.74 ± 0.19 (34) &  5.88 ± 0.64 (31) &  0.16 ± 0.02 (34) &  0.14 ± 0.00 (34) &  1.54 ± 0.16 (34) &  45.30 ± 6.54 (34) \\
-MWU Baseline I 11 Hz       &    2075.00, 0.000 &    2102.00, 0.000 &    1201.50, 0.256 &     253.00, 0.000 &               NaN &               NaN &               NaN &                NaN \\
-PRS Baseline I 11 Hz       &       0.15, 0.000 &       0.12, 0.000 &       0.05, 0.679 &       4.74, 0.000 &               NaN &               NaN &               NaN &                NaN \\
-MWU Baseline I Baseline II &     860.00, 0.682 &     850.00, 0.753 &     645.50, 0.108 &     805.00, 0.651 &               NaN &               NaN &               NaN &                NaN \\
-PRS Baseline I Baseline II &       0.00, 0.954 &       0.01, 0.612 &       0.30, 0.008 &       0.05, 0.582 &               NaN &               NaN &               NaN &                NaN \\
-MWU Baseline I 30 Hz       &    1629.00, 0.000 &    1629.00, 0.000 &     781.50, 0.749 &     225.00, 0.000 &               NaN &               NaN &               NaN &                NaN \\
-PRS Baseline I 30 Hz       &       0.19, 0.000 &       0.13, 0.000 &       0.20, 0.416 &       4.84, 0.000 &               NaN &               NaN &               NaN &                NaN \\
-MWU 11 Hz Baseline II      &      22.00, 0.000 &      10.00, 0.000 &     524.50, 0.024 &    1328.00, 0.000 &               NaN &               NaN &               NaN &                NaN \\
-PRS 11 Hz Baseline II      &       0.15, 0.000 &       0.12, 0.000 &       0.35, 0.019 &       4.79, 0.000 &               NaN &               NaN &               NaN &                NaN \\
-MWU 11 Hz 30 Hz            &    1299.00, 0.000 &    1275.00, 0.000 &     657.00, 0.361 &     664.00, 0.983 &     248.00, 0.000 &    1408.00, 0.000 &     236.00, 0.000 &      202.00, 0.000 \\
-PRS 11 Hz 30 Hz            &       0.04, 0.000 &       0.01, 0.000 &       0.25, 0.523 &       0.10, 0.912 &       0.11, 0.000 &       0.02, 0.000 &       1.09, 0.000 &       31.00, 0.000 \\
-MWU Baseline II 30 Hz      &    1154.00, 0.000 &    1154.00, 0.000 &     604.00, 0.754 &     108.00, 0.000 &               NaN &               NaN &               NaN &                NaN \\
-PRS Baseline II 30 Hz      &       0.19, 0.000 &       0.13, 0.000 &       0.10, 0.582 &       4.89, 0.000 &               NaN &               NaN &               NaN &                NaN \\
-\bottomrule
-\end{tabular}
+,Theta energy,Theta peak,Theta freq,Theta half width,Stim energy,Stim half width,Stim p max,Stim strength
+Baseline I,0.25 ± 0.02 (48),0.18 ± 0.02 (48),7.78 ± 0.09 (48),1.79 ± 0.33 (46),,,,
+11 Hz,0.08 ± 0.00 (44),0.03 ± 0.00 (44),7.55 ± 0.12 (44),5.80 ± 0.50 (43),0.05 ± 0.00 (44),0.16 ± 0.00 (44),0.51 ± 0.04 (44),7.14 ± 0.81 (44)
+Baseline II,0.24 ± 0.02 (34),0.17 ± 0.02 (34),7.96 ± 0.09 (34),1.23 ± 0.22 (33),,,,
+30 Hz,0.04 ± 0.00 (34),0.02 ± 0.00 (34),7.74 ± 0.19 (34),5.88 ± 0.64 (31),0.16 ± 0.02 (34),0.14 ± 0.00 (34),1.54 ± 0.16 (34),45.30 ± 6.54 (34)
+MWU Baseline I 11 Hz,"2075.00, 0.000","2102.00, 0.000","1201.50, 0.256","253.00, 0.000",,,,
+PRS Baseline I 11 Hz,"0.15, 0.000","0.12, 0.000","0.05, 0.686","4.74, 0.000",,,,
+MWU Baseline I Baseline II,"860.00, 0.682","850.00, 0.753","645.50, 0.108","805.00, 0.651",,,,
+PRS Baseline I Baseline II,"0.00, 0.955","0.01, 0.597","0.30, 0.009","0.05, 0.584",,,,
+MWU Baseline I 30 Hz,"1629.00, 0.000","1629.00, 0.000","781.50, 0.749","225.00, 0.000",,,,
+PRS Baseline I 30 Hz,"0.19, 0.000","0.13, 0.000","0.20, 0.416","4.84, 0.000",,,,
+MWU 11 Hz Baseline II,"22.00, 0.000","10.00, 0.000","524.50, 0.024","1328.00, 0.000",,,,
+PRS 11 Hz Baseline II,"0.15, 0.000","0.12, 0.000","0.35, 0.020","4.79, 0.000",,,,
+MWU 11 Hz 30 Hz,"1299.00, 0.000","1275.00, 0.000","657.00, 0.361","664.00, 0.983","248.00, 0.000","1408.00, 0.000","236.00, 0.000","202.00, 0.000"
+PRS 11 Hz 30 Hz,"0.04, 0.000","0.01, 0.000","0.25, 0.510","0.10, 0.909","0.11, 0.000","0.02, 0.000","1.09, 0.000","31.00, 0.000"
+MWU Baseline II 30 Hz,"1154.00, 0.000","1154.00, 0.000","604.00, 0.754","108.00, 0.000",,,,
+PRS Baseline II 30 Hz,"0.19, 0.000","0.13, 0.000","0.10, 0.577","4.89, 0.000",,,,
diff --git a/actions/stimulus-lfp-response/data/statistics/statistics.tex b/actions/stimulus-lfp-response/data/statistics/statistics.tex
index da5065291..c7c8b6eb8 100644
--- a/actions/stimulus-lfp-response/data/statistics/statistics.tex
+++ b/actions/stimulus-lfp-response/data/statistics/statistics.tex
@@ -7,16 +7,16 @@ Baseline I                 &  0.25 ± 0.02 (48) &  0.18 ± 0.02 (48) &  7.78 ±
 Baseline II                &  0.24 ± 0.02 (34) &  0.17 ± 0.02 (34) &  7.96 ± 0.09 (34) &  1.23 ± 0.22 (33) &               NaN &               NaN &               NaN &                NaN \\
 30 Hz                      &  0.04 ± 0.00 (34) &  0.02 ± 0.00 (34) &  7.74 ± 0.19 (34) &  5.88 ± 0.64 (31) &  0.16 ± 0.02 (34) &  0.14 ± 0.00 (34) &  1.54 ± 0.16 (34) &  45.30 ± 6.54 (34) \\
 MWU Baseline I 11 Hz       &    2075.00, 0.000 &    2102.00, 0.000 &    1201.50, 0.256 &     253.00, 0.000 &               NaN &               NaN &               NaN &                NaN \\
-PRS Baseline I 11 Hz       &       0.15, 0.000 &       0.12, 0.000 &       0.05, 0.679 &       4.74, 0.000 &               NaN &               NaN &               NaN &                NaN \\
+PRS Baseline I 11 Hz       &       0.15, 0.000 &       0.12, 0.000 &       0.05, 0.686 &       4.74, 0.000 &               NaN &               NaN &               NaN &                NaN \\
 MWU Baseline I Baseline II &     860.00, 0.682 &     850.00, 0.753 &     645.50, 0.108 &     805.00, 0.651 &               NaN &               NaN &               NaN &                NaN \\
-PRS Baseline I Baseline II &       0.00, 0.954 &       0.01, 0.612 &       0.30, 0.008 &       0.05, 0.582 &               NaN &               NaN &               NaN &                NaN \\
+PRS Baseline I Baseline II &       0.00, 0.955 &       0.01, 0.597 &       0.30, 0.009 &       0.05, 0.584 &               NaN &               NaN &               NaN &                NaN \\
 MWU Baseline I 30 Hz       &    1629.00, 0.000 &    1629.00, 0.000 &     781.50, 0.749 &     225.00, 0.000 &               NaN &               NaN &               NaN &                NaN \\
 PRS Baseline I 30 Hz       &       0.19, 0.000 &       0.13, 0.000 &       0.20, 0.416 &       4.84, 0.000 &               NaN &               NaN &               NaN &                NaN \\
 MWU 11 Hz Baseline II      &      22.00, 0.000 &      10.00, 0.000 &     524.50, 0.024 &    1328.00, 0.000 &               NaN &               NaN &               NaN &                NaN \\
-PRS 11 Hz Baseline II      &       0.15, 0.000 &       0.12, 0.000 &       0.35, 0.019 &       4.79, 0.000 &               NaN &               NaN &               NaN &                NaN \\
+PRS 11 Hz Baseline II      &       0.15, 0.000 &       0.12, 0.000 &       0.35, 0.020 &       4.79, 0.000 &               NaN &               NaN &               NaN &                NaN \\
 MWU 11 Hz 30 Hz            &    1299.00, 0.000 &    1275.00, 0.000 &     657.00, 0.361 &     664.00, 0.983 &     248.00, 0.000 &    1408.00, 0.000 &     236.00, 0.000 &      202.00, 0.000 \\
-PRS 11 Hz 30 Hz            &       0.04, 0.000 &       0.01, 0.000 &       0.25, 0.523 &       0.10, 0.912 &       0.11, 0.000 &       0.02, 0.000 &       1.09, 0.000 &       31.00, 0.000 \\
+PRS 11 Hz 30 Hz            &       0.04, 0.000 &       0.01, 0.000 &       0.25, 0.510 &       0.10, 0.909 &       0.11, 0.000 &       0.02, 0.000 &       1.09, 0.000 &       31.00, 0.000 \\
 MWU Baseline II 30 Hz      &    1154.00, 0.000 &    1154.00, 0.000 &     604.00, 0.754 &     108.00, 0.000 &               NaN &               NaN &               NaN &                NaN \\
-PRS Baseline II 30 Hz      &       0.19, 0.000 &       0.13, 0.000 &       0.10, 0.582 &       4.89, 0.000 &               NaN &               NaN &               NaN &                NaN \\
+PRS Baseline II 30 Hz      &       0.19, 0.000 &       0.13, 0.000 &       0.10, 0.577 &       4.89, 0.000 &               NaN &               NaN &               NaN &                NaN \\
 \bottomrule
 \end{tabular}
diff --git a/actions/stimulus-spike-lfp-response/data/20_stimulus-spike-lfp-response.html b/actions/stimulus-spike-lfp-response/data/20_stimulus-spike-lfp-response.html
index 222e67dbc..745860af2 100644
--- a/actions/stimulus-spike-lfp-response/data/20_stimulus-spike-lfp-response.html
+++ b/actions/stimulus-spike-lfp-response/data/20_stimulus-spike-lfp-response.html
@@ -13181,7 +13181,7 @@ div#notebook {
 
 
 

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def summarize(data):
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for cell_type, stat in stats.items():
-    stat.to_latex(output_path / f"statistics_{cell_type}" / "statistics.tex")
-    stat.to_latex(output_path / f"statistics_{cell_type}" / "statistics.csv")
+    stat.to_latex(output_path / "statistics" / f"statistics_{cell_type}.tex")
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freq = freqs.T.iloc[0].values
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action = project.require_action("stimulus-spike-lfp-response")
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- '/media/storage/expipe/septum-mec/actions/stimulus-spike-lfp-response/data/figures/spike-lfp-coherence-histogram-stim_p_max-ns_not_inhibited.png',
- '/media/storage/expipe/septum-mec/actions/stimulus-spike-lfp-response/data/figures/spike-lfp-coherence-histogram-theta_energy-not-bs.svg',
- '/media/storage/expipe/septum-mec/actions/stimulus-spike-lfp-response/data/figures/spike-lfp-coherence-histogram-stim_p_max-ns_inhibited.png',
- '/media/storage/expipe/septum-mec/actions/stimulus-spike-lfp-response/data/figures/spike-lfp-coherence-histogram-stim_energy-ns_inhibited.svg',
- '/media/storage/expipe/septum-mec/actions/stimulus-spike-lfp-response/data/figures/spike-lfp-coherence-ns_inhibited.svg',
- '/media/storage/expipe/septum-mec/actions/stimulus-spike-lfp-response/data/figures/spike-lfp-coherence-histogram-stim_p_max-gridcell.svg',
- '/media/storage/expipe/septum-mec/actions/stimulus-spike-lfp-response/data/figures/spike-lfp-coherence-histogram-stim_energy-gridcell.png',
- '/media/storage/expipe/septum-mec/actions/stimulus-spike-lfp-response/data/figures/spike-lfp-coherence-histogram-stim_half_width-gridcell.png',
- '/media/storage/expipe/septum-mec/actions/stimulus-spike-lfp-response/data/figures/spike-lfp-coherence-histogram-theta_energy-not-bs.png',
- '/media/storage/expipe/septum-mec/actions/stimulus-spike-lfp-response/data/figures/spike-lfp-coherence-histogram-stim_p_max-gridcell.png',
- '/media/storage/expipe/septum-mec/actions/stimulus-spike-lfp-response/data/figures/spike-lfp-coherence-histogram-theta_half_width-gridcell.svg',
- '/media/storage/expipe/septum-mec/actions/stimulus-spike-lfp-response/data/figures/spike-lfp-coherence-gridcell.png',
- '/media/storage/expipe/septum-mec/actions/stimulus-spike-lfp-response/data/figures/spike-lfp-coherence-histogram-stim_strength-ns_not_inhibited.svg',
- '/media/storage/expipe/septum-mec/actions/stimulus-spike-lfp-response/data/figures/spike-lfp-coherence-histogram-theta_freq-ns_not_inhibited.png',
- '/media/storage/expipe/septum-mec/actions/stimulus-spike-lfp-response/data/figures/spike-lfp-coherence-ns_not_inhibited.svg',
- '/media/storage/expipe/septum-mec/actions/stimulus-spike-lfp-response/data/figures/spike-lfp-coherence-histogram-theta_half_width-ns_not_inhibited.png',
- '/media/storage/expipe/septum-mec/actions/stimulus-spike-lfp-response/data/figures/spike-lfp-coherence-histogram-theta_half_width-gridcell.png',
- '/media/storage/expipe/septum-mec/actions/stimulus-spike-lfp-response/data/figures/spike-lfp-coherence-histogram-stim_energy-not-bs.svg']

-

-
-

-
-

-

-
 

 

 

-
In [34]:

+
In [ ]:

 

     

 
septum_mec.analysis.registration.store_notebook(action, "20_stimulus-spike-lfp-response.ipynb")
diff --git a/actions/stimulus-spike-lfp-response/data/20_stimulus-spike-lfp-response.ipynb b/actions/stimulus-spike-lfp-response/data/20_stimulus-spike-lfp-response.ipynb
index 0dae796e8..10169c347 100644
--- a/actions/stimulus-spike-lfp-response/data/20_stimulus-spike-lfp-response.ipynb
+++ b/actions/stimulus-spike-lfp-response/data/20_stimulus-spike-lfp-response.ipynb
@@ -19,7 +19,7 @@
      "name": "stderr",
      "output_type": "stream",
      "text": [
-      "11:00:42 [I] klustakwik KlustaKwik2 version 0.2.6\n"
+      "13:08:55 [I] klustakwik KlustaKwik2 version 0.2.6\n"
      ]
     }
    ],
@@ -911,7 +911,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 33,
+   "execution_count": 25,
    "metadata": {
     "scrolled": false
    },
@@ -1124,7 +1124,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 34,
+   "execution_count": 27,
    "metadata": {
     "scrolled": false
    },
@@ -1335,7 +1335,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 30,
+   "execution_count": 28,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -1409,8 +1409,8 @@
    "outputs": [],
    "source": [
     "for cell_type, stat in stats.items():\n",
-    "    stat.to_latex(output_path / f\"statistics_{cell_type}\" / \"statistics.tex\")\n",
-    "    stat.to_latex(output_path / f\"statistics_{cell_type}\" / \"statistics.csv\")"
+    "    stat.to_latex(output_path / \"statistics\" / f\"statistics_{cell_type}.tex\")\n",
+    "    stat.to_csv(output_path / \"statistics\" / f\"statistics_{cell_type}.csv\")"
    ]
   },
   {
@@ -1422,7 +1422,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 28,
+   "execution_count": null,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -1431,7 +1431,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 29,
+   "execution_count": null,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -1441,7 +1441,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 30,
+   "execution_count": null,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -1452,46 +1452,9 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 31,
+   "execution_count": null,
    "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "image/png": 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\n",
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-     "output_type": "display_data"
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\n",
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-     "output_type": "display_data"
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\n",
-      "text/plain": [
-       "
"
-      ]
-     },
-     "metadata": {
-      "needs_background": "light"
-     },
-     "output_type": "display_data"
-    }
-   ],
+   "outputs": [],
    "source": [
     "for cell_type in ['gridcell', 'ns_inhibited', 'ns_not_inhibited']:\n",
     "    fig, axs = plt.subplots(1, 2, sharex=True, sharey=True, figsize=(5,2))\n",
@@ -1527,7 +1490,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 32,
+   "execution_count": null,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -1536,100 +1499,16 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 33,
+   "execution_count": null,
    "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "['/media/storage/expipe/septum-mec/actions/stimulus-spike-lfp-response/data/data/freqs.feather',\n",
-       " '/media/storage/expipe/septum-mec/actions/stimulus-spike-lfp-response/data/data/coherence.feather',\n",
-       " '/media/storage/expipe/septum-mec/actions/stimulus-spike-lfp-response/data/figures/spike-lfp-coherence-histogram-theta_freq-ns_not_inhibited.svg',\n",
-       " '/media/storage/expipe/septum-mec/actions/stimulus-spike-lfp-response/data/figures/spike-lfp-coherence-histogram-stim_strength-not-bs.svg',\n",
-       " '/media/storage/expipe/septum-mec/actions/stimulus-spike-lfp-response/data/figures/spike-lfp-coherence-histogram-stim_energy-not-bs.png',\n",
-       " '/media/storage/expipe/septum-mec/actions/stimulus-spike-lfp-response/data/figures/spike-lfp-coherence-histogram-theta_peak-gridcell.png',\n",
-       " '/media/storage/expipe/septum-mec/actions/stimulus-spike-lfp-response/data/figures/spike-lfp-coherence-histogram-theta_energy-ns_inhibited.svg',\n",
-       " '/media/storage/expipe/septum-mec/actions/stimulus-spike-lfp-response/data/figures/spike-lfp-coherence-histogram-theta_energy-gridcell.svg',\n",
-       " '/media/storage/expipe/septum-mec/actions/stimulus-spike-lfp-response/data/figures/spike-lfp-coherence-histogram-stim_half_width-ns_not_inhibited.svg',\n",
-       " '/media/storage/expipe/septum-mec/actions/stimulus-spike-lfp-response/data/figures/spike-lfp-coherence-histogram-theta_half_width-ns_not_inhibited.svg',\n",
-       " '/media/storage/expipe/septum-mec/actions/stimulus-spike-lfp-response/data/figures/spike-lfp-coherence-not-bs.svg',\n",
-       " '/media/storage/expipe/septum-mec/actions/stimulus-spike-lfp-response/data/figures/spike-lfp-coherence-histogram-stim_energy-gridcell.svg',\n",
-       " '/media/storage/expipe/septum-mec/actions/stimulus-spike-lfp-response/data/figures/spike-lfp-coherence-histogram-theta_peak-not-bs.png',\n",
-       " '/media/storage/expipe/septum-mec/actions/stimulus-spike-lfp-response/data/figures/spike-lfp-coherence-histogram-stim_strength-not-bs.png',\n",
-       " '/media/storage/expipe/septum-mec/actions/stimulus-spike-lfp-response/data/figures/spike-lfp-coherence-histogram-stim_p_max-not-bs.svg',\n",
-       " '/media/storage/expipe/septum-mec/actions/stimulus-spike-lfp-response/data/figures/spike-lfp-coherence-histogram-theta_peak-gridcell.svg',\n",
-       " '/media/storage/expipe/septum-mec/actions/stimulus-spike-lfp-response/data/figures/spike-lfp-coherence-gridcell.svg',\n",
-       " '/media/storage/expipe/septum-mec/actions/stimulus-spike-lfp-response/data/figures/spike-lfp-coherence-histogram-stim_p_max-ns_not_inhibited.svg',\n",
-       " '/media/storage/expipe/septum-mec/actions/stimulus-spike-lfp-response/data/figures/spike-lfp-coherence-histogram-stim_strength-ns_not_inhibited.png',\n",
-       " '/media/storage/expipe/septum-mec/actions/stimulus-spike-lfp-response/data/figures/spike-lfp-coherence-histogram-stim_strength-ns_inhibited.svg',\n",
-       " '/media/storage/expipe/septum-mec/actions/stimulus-spike-lfp-response/data/figures/spike-lfp-coherence-histogram-stim_half_width-not-bs.svg',\n",
-       " '/media/storage/expipe/septum-mec/actions/stimulus-spike-lfp-response/data/figures/spike-lfp-coherence-histogram-theta_half_width-not-bs.svg',\n",
-       " '/media/storage/expipe/septum-mec/actions/stimulus-spike-lfp-response/data/figures/spike-lfp-coherence-histogram-stim_half_width-ns_not_inhibited.png',\n",
-       " '/media/storage/expipe/septum-mec/actions/stimulus-spike-lfp-response/data/figures/spike-lfp-coherence-histogram-theta_energy-ns_not_inhibited.png',\n",
-       " '/media/storage/expipe/septum-mec/actions/stimulus-spike-lfp-response/data/figures/spike-lfp-coherence-histogram-stim_energy-ns_not_inhibited.svg',\n",
-       " '/media/storage/expipe/septum-mec/actions/stimulus-spike-lfp-response/data/figures/spike-lfp-coherence-histogram-theta_half_width-ns_inhibited.svg',\n",
-       " '/media/storage/expipe/septum-mec/actions/stimulus-spike-lfp-response/data/figures/spike-lfp-coherence-ns_inhibited.png',\n",
-       " '/media/storage/expipe/septum-mec/actions/stimulus-spike-lfp-response/data/figures/spike-lfp-coherence-histogram-stim_half_width-ns_inhibited.png',\n",
-       " '/media/storage/expipe/septum-mec/actions/stimulus-spike-lfp-response/data/figures/spike-lfp-coherence-histogram-theta_half_width-not-bs.png',\n",
-       " '/media/storage/expipe/septum-mec/actions/stimulus-spike-lfp-response/data/figures/spike-lfp-coherence-histogram-stim_energy-ns_not_inhibited.png',\n",
-       " '/media/storage/expipe/septum-mec/actions/stimulus-spike-lfp-response/data/figures/spike-lfp-coherence-histogram-theta_energy-gridcell.png',\n",
-       " '/media/storage/expipe/septum-mec/actions/stimulus-spike-lfp-response/data/figures/spike-lfp-coherence-histogram-theta_energy-ns_not_inhibited.svg',\n",
-       " '/media/storage/expipe/septum-mec/actions/stimulus-spike-lfp-response/data/figures/spike-lfp-coherence-histogram-theta_half_width-ns_inhibited.png',\n",
-       " '/media/storage/expipe/septum-mec/actions/stimulus-spike-lfp-response/data/figures/spike-lfp-coherence-histogram-stim_p_max-ns_inhibited.svg',\n",
-       " '/media/storage/expipe/septum-mec/actions/stimulus-spike-lfp-response/data/figures/spike-lfp-coherence-histogram-theta_freq-not-bs.png',\n",
-       " '/media/storage/expipe/septum-mec/actions/stimulus-spike-lfp-response/data/figures/spike-lfp-coherence-histogram-theta_peak-ns_not_inhibited.png',\n",
-       " '/media/storage/expipe/septum-mec/actions/stimulus-spike-lfp-response/data/figures/spike-lfp-coherence-histogram-stim_half_width-ns_inhibited.svg',\n",
-       " '/media/storage/expipe/septum-mec/actions/stimulus-spike-lfp-response/data/figures/spike-lfp-coherence-histogram-stim_strength-gridcell.svg',\n",
-       " '/media/storage/expipe/septum-mec/actions/stimulus-spike-lfp-response/data/figures/spike-lfp-coherence-histogram-theta_freq-gridcell.svg',\n",
-       " '/media/storage/expipe/septum-mec/actions/stimulus-spike-lfp-response/data/figures/spike-lfp-coherence-not-bs.png',\n",
-       " '/media/storage/expipe/septum-mec/actions/stimulus-spike-lfp-response/data/figures/spike-lfp-coherence-histogram-theta_peak-not-bs.svg',\n",
-       " '/media/storage/expipe/septum-mec/actions/stimulus-spike-lfp-response/data/figures/spike-lfp-coherence-histogram-stim_half_width-gridcell.svg',\n",
-       " '/media/storage/expipe/septum-mec/actions/stimulus-spike-lfp-response/data/figures/spike-lfp-coherence-histogram-theta_peak-ns_inhibited.png',\n",
-       " '/media/storage/expipe/septum-mec/actions/stimulus-spike-lfp-response/data/figures/spike-lfp-coherence-ns_not_inhibited.png',\n",
-       " '/media/storage/expipe/septum-mec/actions/stimulus-spike-lfp-response/data/figures/spike-lfp-coherence-histogram-theta_freq-ns_inhibited.png',\n",
-       " '/media/storage/expipe/septum-mec/actions/stimulus-spike-lfp-response/data/figures/spike-lfp-coherence-histogram-theta_peak-ns_not_inhibited.svg',\n",
-       " '/media/storage/expipe/septum-mec/actions/stimulus-spike-lfp-response/data/figures/spike-lfp-coherence-histogram-stim_p_max-not-bs.png',\n",
-       " '/media/storage/expipe/septum-mec/actions/stimulus-spike-lfp-response/data/figures/spike-lfp-coherence-histogram-theta_peak-ns_inhibited.svg',\n",
-       " '/media/storage/expipe/septum-mec/actions/stimulus-spike-lfp-response/data/figures/spike-lfp-coherence-histogram-theta_freq-not-bs.svg',\n",
-       " '/media/storage/expipe/septum-mec/actions/stimulus-spike-lfp-response/data/figures/spike-lfp-coherence-histogram-theta_energy-ns_inhibited.png',\n",
-       " '/media/storage/expipe/septum-mec/actions/stimulus-spike-lfp-response/data/figures/spike-lfp-coherence-histogram-stim_half_width-not-bs.png',\n",
-       " '/media/storage/expipe/septum-mec/actions/stimulus-spike-lfp-response/data/figures/spike-lfp-coherence-histogram-theta_freq-gridcell.png',\n",
-       " '/media/storage/expipe/septum-mec/actions/stimulus-spike-lfp-response/data/figures/spike-lfp-coherence-histogram-theta_freq-ns_inhibited.svg',\n",
-       " '/media/storage/expipe/septum-mec/actions/stimulus-spike-lfp-response/data/figures/spike-lfp-coherence-histogram-stim_strength-ns_inhibited.png',\n",
-       " '/media/storage/expipe/septum-mec/actions/stimulus-spike-lfp-response/data/figures/spike-lfp-coherence-histogram-stim_energy-ns_inhibited.png',\n",
-       " '/media/storage/expipe/septum-mec/actions/stimulus-spike-lfp-response/data/figures/spike-lfp-coherence-histogram-stim_strength-gridcell.png',\n",
-       " '/media/storage/expipe/septum-mec/actions/stimulus-spike-lfp-response/data/figures/spike-lfp-coherence-histogram-stim_p_max-ns_not_inhibited.png',\n",
-       " '/media/storage/expipe/septum-mec/actions/stimulus-spike-lfp-response/data/figures/spike-lfp-coherence-histogram-theta_energy-not-bs.svg',\n",
-       " '/media/storage/expipe/septum-mec/actions/stimulus-spike-lfp-response/data/figures/spike-lfp-coherence-histogram-stim_p_max-ns_inhibited.png',\n",
-       " '/media/storage/expipe/septum-mec/actions/stimulus-spike-lfp-response/data/figures/spike-lfp-coherence-histogram-stim_energy-ns_inhibited.svg',\n",
-       " '/media/storage/expipe/septum-mec/actions/stimulus-spike-lfp-response/data/figures/spike-lfp-coherence-ns_inhibited.svg',\n",
-       " '/media/storage/expipe/septum-mec/actions/stimulus-spike-lfp-response/data/figures/spike-lfp-coherence-histogram-stim_p_max-gridcell.svg',\n",
-       " '/media/storage/expipe/septum-mec/actions/stimulus-spike-lfp-response/data/figures/spike-lfp-coherence-histogram-stim_energy-gridcell.png',\n",
-       " '/media/storage/expipe/septum-mec/actions/stimulus-spike-lfp-response/data/figures/spike-lfp-coherence-histogram-stim_half_width-gridcell.png',\n",
-       " '/media/storage/expipe/septum-mec/actions/stimulus-spike-lfp-response/data/figures/spike-lfp-coherence-histogram-theta_energy-not-bs.png',\n",
-       " '/media/storage/expipe/septum-mec/actions/stimulus-spike-lfp-response/data/figures/spike-lfp-coherence-histogram-stim_p_max-gridcell.png',\n",
-       " '/media/storage/expipe/septum-mec/actions/stimulus-spike-lfp-response/data/figures/spike-lfp-coherence-histogram-theta_half_width-gridcell.svg',\n",
-       " '/media/storage/expipe/septum-mec/actions/stimulus-spike-lfp-response/data/figures/spike-lfp-coherence-gridcell.png',\n",
-       " '/media/storage/expipe/septum-mec/actions/stimulus-spike-lfp-response/data/figures/spike-lfp-coherence-histogram-stim_strength-ns_not_inhibited.svg',\n",
-       " '/media/storage/expipe/septum-mec/actions/stimulus-spike-lfp-response/data/figures/spike-lfp-coherence-histogram-theta_freq-ns_not_inhibited.png',\n",
-       " '/media/storage/expipe/septum-mec/actions/stimulus-spike-lfp-response/data/figures/spike-lfp-coherence-ns_not_inhibited.svg',\n",
-       " '/media/storage/expipe/septum-mec/actions/stimulus-spike-lfp-response/data/figures/spike-lfp-coherence-histogram-theta_half_width-ns_not_inhibited.png',\n",
-       " '/media/storage/expipe/septum-mec/actions/stimulus-spike-lfp-response/data/figures/spike-lfp-coherence-histogram-theta_half_width-gridcell.png',\n",
-       " '/media/storage/expipe/septum-mec/actions/stimulus-spike-lfp-response/data/figures/spike-lfp-coherence-histogram-stim_energy-not-bs.svg']"
-      ]
-     },
-     "execution_count": 33,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
+   "outputs": [],
    "source": [
     "copy_tree(output_path, str(action.data_path()))"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 34,
+   "execution_count": null,
    "metadata": {},
    "outputs": [],
    "source": [
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diff --git a/actions/stimulus-spike-lfp-response/data/figures/spike-lfp-coherence-ns_not_inhibited.svg b/actions/stimulus-spike-lfp-response/data/figures/spike-lfp-coherence-ns_not_inhibited.svg
index dd3f5157d..8c75eb074 100644
--- a/actions/stimulus-spike-lfp-response/data/figures/spike-lfp-coherence-ns_not_inhibited.svg
+++ b/actions/stimulus-spike-lfp-response/data/figures/spike-lfp-coherence-ns_not_inhibited.svg
@@ -1,3 +1,3 @@
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diff --git a/actions/stimulus-spike-lfp-response/data/statistics/statistics_gridcell.csv b/actions/stimulus-spike-lfp-response/data/statistics/statistics_gridcell.csv
index 4d7939a20..65e143778 100644
--- a/actions/stimulus-spike-lfp-response/data/statistics/statistics_gridcell.csv
+++ b/actions/stimulus-spike-lfp-response/data/statistics/statistics_gridcell.csv
@@ -1,22 +1,17 @@
-\begin{tabular}{lllllllll}
-\toprule
-{} &      Theta energy &        Theta peak &        Theta freq &  Theta half width &       Stim energy &   Stim half width &        Stim p max &      Stim strength \\
-\midrule
-Baseline I                 &  0.22 ± 0.03 (66) &  0.21 ± 0.02 (66) &  7.77 ± 0.07 (66) &  0.65 ± 0.03 (66) &               NaN &               NaN &               NaN &                NaN \\
-11 Hz                      &  0.07 ± 0.01 (62) &  0.06 ± 0.01 (62) &  7.91 ± 0.12 (62) &  0.29 ± 0.02 (62) &  0.07 ± 0.01 (62) &  0.21 ± 0.01 (62) &  0.41 ± 0.03 (62) &  10.15 ± 0.85 (62) \\
-Baseline II                &  0.19 ± 0.03 (56) &  0.16 ± 0.02 (56) &  7.94 ± 0.07 (56) &  0.64 ± 0.04 (56) &               NaN &               NaN &               NaN &                NaN \\
-30 Hz                      &  0.05 ± 0.01 (40) &  0.05 ± 0.01 (40) &  8.22 ± 0.15 (40) &  0.25 ± 0.02 (40) &  0.10 ± 0.01 (40) &  0.25 ± 0.00 (40) &  0.43 ± 0.03 (40) &  11.34 ± 1.15 (40) \\
-MWU Baseline I 11 Hz       &    3146.00, 0.000 &    3317.00, 0.000 &    1886.00, 0.446 &    3557.00, 0.000 &               NaN &               NaN &               NaN &                NaN \\
-PRS Baseline I 11 Hz       &       0.11, 0.000 &       0.14, 0.000 &       0.31, 0.034 &       0.47, 0.000 &               NaN &               NaN &               NaN &                NaN \\
-MWU Baseline I Baseline II &    2040.00, 0.325 &    2106.00, 0.186 &    1368.50, 0.013 &    1992.00, 0.461 &               NaN &               NaN &               NaN &                NaN \\
-PRS Baseline I Baseline II &       0.06, 0.101 &       0.06, 0.112 &       0.24, 0.000 &       0.13, 0.151 &               NaN &               NaN &               NaN &                NaN \\
-MWU Baseline I 30 Hz       &    2156.00, 0.000 &    2189.00, 0.000 &     834.50, 0.002 &    2389.00, 0.000 &               NaN &               NaN &               NaN &                NaN \\
-PRS Baseline I 30 Hz       &       0.11, 0.000 &       0.14, 0.000 &       0.85, 0.000 &       0.47, 0.000 &               NaN &               NaN &               NaN &                NaN \\
-MWU 11 Hz Baseline II      &     878.00, 0.000 &     753.00, 0.000 &    1668.50, 0.717 &     518.00, 0.000 &               NaN &               NaN &               NaN &                NaN \\
-PRS 11 Hz Baseline II      &       0.06, 0.000 &       0.07, 0.000 &       0.06, 0.269 &       0.33, 0.000 &               NaN &               NaN &               NaN &                NaN \\
-MWU 11 Hz 30 Hz            &    1372.00, 0.367 &    1306.00, 0.653 &    1003.00, 0.105 &    1355.00, 0.433 &     771.00, 0.001 &     433.00, 0.000 &    1164.00, 0.605 &     1085.00, 0.290 \\
-PRS 11 Hz 30 Hz            &       0.00, 0.900 &       0.00, 0.602 &       0.55, 0.026 &       0.01, 0.699 &       0.04, 0.000 &       0.05, 0.000 &       0.01, 0.917 &        1.49, 0.404 \\
-MWU Baseline II 30 Hz      &    1829.00, 0.000 &    1845.00, 0.000 &     757.00, 0.007 &    2023.00, 0.000 &               NaN &               NaN &               NaN &                NaN \\
-PRS Baseline II 30 Hz      &       0.06, 0.000 &       0.08, 0.000 &       0.61, 0.000 &       0.34, 0.000 &               NaN &               NaN &               NaN &                NaN \\
-\bottomrule
-\end{tabular}
+,Theta energy,Theta peak,Theta freq,Theta half width,Stim energy,Stim half width,Stim p max,Stim strength
+Baseline I,0.22 ± 0.03 (66),0.21 ± 0.02 (66),7.77 ± 0.07 (66),0.65 ± 0.03 (66),,,,
+11 Hz,0.07 ± 0.01 (62),0.06 ± 0.01 (62),7.91 ± 0.12 (62),0.29 ± 0.02 (62),0.07 ± 0.01 (62),0.21 ± 0.01 (62),0.41 ± 0.03 (62),10.15 ± 0.85 (62)
+Baseline II,0.19 ± 0.03 (56),0.16 ± 0.02 (56),7.94 ± 0.07 (56),0.64 ± 0.04 (56),,,,
+30 Hz,0.05 ± 0.01 (40),0.05 ± 0.01 (40),8.22 ± 0.15 (40),0.25 ± 0.02 (40),0.10 ± 0.01 (40),0.25 ± 0.00 (40),0.43 ± 0.03 (40),11.34 ± 1.15 (40)
+MWU Baseline I 11 Hz,"3146.00, 0.000","3317.00, 0.000","1886.00, 0.446","3557.00, 0.000",,,,
+PRS Baseline I 11 Hz,"0.11, 0.000","0.14, 0.000","0.31, 0.031","0.47, 0.000",,,,
+MWU Baseline I Baseline II,"2040.00, 0.325","2106.00, 0.186","1368.50, 0.013","1992.00, 0.461",,,,
+PRS Baseline I Baseline II,"0.06, 0.107","0.06, 0.114","0.24, 0.000","0.13, 0.158",,,,
+MWU Baseline I 30 Hz,"2156.00, 0.000","2189.00, 0.000","834.50, 0.002","2389.00, 0.000",,,,
+PRS Baseline I 30 Hz,"0.11, 0.001","0.14, 0.000","0.85, 0.000","0.47, 0.000",,,,
+MWU 11 Hz Baseline II,"878.00, 0.000","753.00, 0.000","1668.50, 0.717","518.00, 0.000",,,,
+PRS 11 Hz Baseline II,"0.06, 0.000","0.07, 0.000","0.06, 0.270","0.33, 0.000",,,,
+MWU 11 Hz 30 Hz,"1372.00, 0.367","1306.00, 0.653","1003.00, 0.105","1355.00, 0.433","771.00, 0.001","433.00, 0.000","1164.00, 0.605","1085.00, 0.290"
+PRS 11 Hz 30 Hz,"0.00, 0.897","0.00, 0.596","0.55, 0.027","0.01, 0.706","0.04, 0.001","0.05, 0.000","0.01, 0.916","1.49, 0.409"
+MWU Baseline II 30 Hz,"1829.00, 0.000","1845.00, 0.000","757.00, 0.007","2023.00, 0.000",,,,
+PRS Baseline II 30 Hz,"0.06, 0.000","0.08, 0.000","0.61, 0.000","0.34, 0.000",,,,
diff --git a/actions/stimulus-spike-lfp-response/data/statistics/statistics_gridcell.tex b/actions/stimulus-spike-lfp-response/data/statistics/statistics_gridcell.tex
index 4d7939a20..bdda1e133 100644
--- a/actions/stimulus-spike-lfp-response/data/statistics/statistics_gridcell.tex
+++ b/actions/stimulus-spike-lfp-response/data/statistics/statistics_gridcell.tex
@@ -7,15 +7,15 @@ Baseline I                 &  0.22 ± 0.03 (66) &  0.21 ± 0.02 (66) &  7.77 ±
 Baseline II                &  0.19 ± 0.03 (56) &  0.16 ± 0.02 (56) &  7.94 ± 0.07 (56) &  0.64 ± 0.04 (56) &               NaN &               NaN &               NaN &                NaN \\
 30 Hz                      &  0.05 ± 0.01 (40) &  0.05 ± 0.01 (40) &  8.22 ± 0.15 (40) &  0.25 ± 0.02 (40) &  0.10 ± 0.01 (40) &  0.25 ± 0.00 (40) &  0.43 ± 0.03 (40) &  11.34 ± 1.15 (40) \\
 MWU Baseline I 11 Hz       &    3146.00, 0.000 &    3317.00, 0.000 &    1886.00, 0.446 &    3557.00, 0.000 &               NaN &               NaN &               NaN &                NaN \\
-PRS Baseline I 11 Hz       &       0.11, 0.000 &       0.14, 0.000 &       0.31, 0.034 &       0.47, 0.000 &               NaN &               NaN &               NaN &                NaN \\
+PRS Baseline I 11 Hz       &       0.11, 0.000 &       0.14, 0.000 &       0.31, 0.031 &       0.47, 0.000 &               NaN &               NaN &               NaN &                NaN \\
 MWU Baseline I Baseline II &    2040.00, 0.325 &    2106.00, 0.186 &    1368.50, 0.013 &    1992.00, 0.461 &               NaN &               NaN &               NaN &                NaN \\
-PRS Baseline I Baseline II &       0.06, 0.101 &       0.06, 0.112 &       0.24, 0.000 &       0.13, 0.151 &               NaN &               NaN &               NaN &                NaN \\
+PRS Baseline I Baseline II &       0.06, 0.107 &       0.06, 0.114 &       0.24, 0.000 &       0.13, 0.158 &               NaN &               NaN &               NaN &                NaN \\
 MWU Baseline I 30 Hz       &    2156.00, 0.000 &    2189.00, 0.000 &     834.50, 0.002 &    2389.00, 0.000 &               NaN &               NaN &               NaN &                NaN \\
-PRS Baseline I 30 Hz       &       0.11, 0.000 &       0.14, 0.000 &       0.85, 0.000 &       0.47, 0.000 &               NaN &               NaN &               NaN &                NaN \\
+PRS Baseline I 30 Hz       &       0.11, 0.001 &       0.14, 0.000 &       0.85, 0.000 &       0.47, 0.000 &               NaN &               NaN &               NaN &                NaN \\
 MWU 11 Hz Baseline II      &     878.00, 0.000 &     753.00, 0.000 &    1668.50, 0.717 &     518.00, 0.000 &               NaN &               NaN &               NaN &                NaN \\
-PRS 11 Hz Baseline II      &       0.06, 0.000 &       0.07, 0.000 &       0.06, 0.269 &       0.33, 0.000 &               NaN &               NaN &               NaN &                NaN \\
+PRS 11 Hz Baseline II      &       0.06, 0.000 &       0.07, 0.000 &       0.06, 0.270 &       0.33, 0.000 &               NaN &               NaN &               NaN &                NaN \\
 MWU 11 Hz 30 Hz            &    1372.00, 0.367 &    1306.00, 0.653 &    1003.00, 0.105 &    1355.00, 0.433 &     771.00, 0.001 &     433.00, 0.000 &    1164.00, 0.605 &     1085.00, 0.290 \\
-PRS 11 Hz 30 Hz            &       0.00, 0.900 &       0.00, 0.602 &       0.55, 0.026 &       0.01, 0.699 &       0.04, 0.000 &       0.05, 0.000 &       0.01, 0.917 &        1.49, 0.404 \\
+PRS 11 Hz 30 Hz            &       0.00, 0.897 &       0.00, 0.596 &       0.55, 0.027 &       0.01, 0.706 &       0.04, 0.001 &       0.05, 0.000 &       0.01, 0.916 &        1.49, 0.409 \\
 MWU Baseline II 30 Hz      &    1829.00, 0.000 &    1845.00, 0.000 &     757.00, 0.007 &    2023.00, 0.000 &               NaN &               NaN &               NaN &                NaN \\
 PRS Baseline II 30 Hz      &       0.06, 0.000 &       0.08, 0.000 &       0.61, 0.000 &       0.34, 0.000 &               NaN &               NaN &               NaN &                NaN \\
 \bottomrule
diff --git a/actions/stimulus-spike-lfp-response/data/statistics/statistics_ns_inhibited.csv b/actions/stimulus-spike-lfp-response/data/statistics/statistics_ns_inhibited.csv
index 6444e27b8..ec99e8b68 100644
--- a/actions/stimulus-spike-lfp-response/data/statistics/statistics_ns_inhibited.csv
+++ b/actions/stimulus-spike-lfp-response/data/statistics/statistics_ns_inhibited.csv
@@ -1,22 +1,17 @@
-\begin{tabular}{lllllllll}
-\toprule
-{} &      Theta energy &        Theta peak &        Theta freq &  Theta half width &       Stim energy &   Stim half width &        Stim p max &      Stim strength \\
-\midrule
-Baseline I                 &  1.10 ± 0.10 (17) &  0.66 ± 0.04 (17) &  7.66 ± 0.06 (17) &  1.36 ± 0.08 (17) &               NaN &               NaN &               NaN &                NaN \\
-11 Hz                      &  0.23 ± 0.04 (34) &  0.13 ± 0.02 (34) &  7.83 ± 0.11 (34) &  0.70 ± 0.11 (34) &  0.16 ± 0.03 (34) &  0.56 ± 0.31 (34) &  0.56 ± 0.04 (34) &   8.12 ± 1.12 (34) \\
-Baseline II                &  0.94 ± 0.12 (21) &  0.56 ± 0.05 (21) &  7.81 ± 0.08 (21) &  1.34 ± 0.12 (21) &               NaN &               NaN &               NaN &                NaN \\
-30 Hz                      &  0.11 ± 0.02 (36) &  0.09 ± 0.01 (36) &  8.36 ± 0.13 (36) &  0.45 ± 0.05 (36) &  0.15 ± 0.01 (36) &  0.31 ± 0.02 (36) &  0.55 ± 0.04 (36) &  10.39 ± 1.70 (36) \\
-MWU Baseline I 11 Hz       &     550.00, 0.000 &     568.00, 0.000 &     223.50, 0.193 &     477.00, 0.000 &               NaN &               NaN &               NaN &                NaN \\
-PRS Baseline I 11 Hz       &       1.02, 0.000 &       0.63, 0.000 &       0.24, 0.086 &       0.87, 0.002 &               NaN &               NaN &               NaN &                NaN \\
-MWU Baseline I Baseline II &     215.00, 0.291 &     235.00, 0.100 &     123.00, 0.102 &     192.00, 0.703 &               NaN &               NaN &               NaN &                NaN \\
-PRS Baseline I Baseline II &       0.30, 0.255 &       0.12, 0.297 &       0.12, 0.009 &       0.05, 0.587 &               NaN &               NaN &               NaN &                NaN \\
-MWU Baseline I 30 Hz       &     606.00, 0.000 &     607.00, 0.000 &      89.00, 0.000 &     594.00, 0.000 &               NaN &               NaN &               NaN &                NaN \\
-PRS Baseline I 30 Hz       &       1.07, 0.000 &       0.64, 0.000 &       0.61, 0.001 &       0.92, 0.000 &               NaN &               NaN &               NaN &                NaN \\
-MWU 11 Hz Baseline II      &      84.00, 0.000 &      57.00, 0.000 &     391.50, 0.554 &     143.00, 0.000 &               NaN &               NaN &               NaN &                NaN \\
-PRS 11 Hz Baseline II      &       0.72, 0.000 &       0.51, 0.000 &       0.12, 0.156 &       0.82, 0.002 &               NaN &               NaN &               NaN &                NaN \\
-MWU 11 Hz 30 Hz            &     756.00, 0.092 &     715.00, 0.228 &     362.50, 0.003 &     701.00, 0.298 &     576.00, 0.677 &     376.00, 0.006 &     597.00, 0.865 &      562.00, 0.561 \\
-PRS 11 Hz 30 Hz            &       0.05, 0.230 &       0.02, 0.408 &       0.37, 0.018 &       0.05, 0.442 &       0.01, 0.586 &       0.02, 0.071 &       0.00, 0.921 &        1.25, 0.687 \\
-MWU Baseline II 30 Hz      &     701.00, 0.000 &     704.00, 0.000 &     154.50, 0.000 &     709.00, 0.000 &               NaN &               NaN &               NaN &                NaN \\
-PRS Baseline II 30 Hz      &       0.78, 0.000 &       0.52, 0.000 &       0.49, 0.003 &       0.87, 0.000 &               NaN &               NaN &               NaN &                NaN \\
-\bottomrule
-\end{tabular}
+,Theta energy,Theta peak,Theta freq,Theta half width,Stim energy,Stim half width,Stim p max,Stim strength
+Baseline I,1.10 ± 0.10 (17),0.66 ± 0.04 (17),7.66 ± 0.06 (17),1.36 ± 0.08 (17),,,,
+11 Hz,0.23 ± 0.04 (34),0.13 ± 0.02 (34),7.83 ± 0.11 (34),0.70 ± 0.11 (34),0.16 ± 0.03 (34),0.56 ± 0.31 (34),0.56 ± 0.04 (34),8.12 ± 1.12 (34)
+Baseline II,0.94 ± 0.12 (21),0.56 ± 0.05 (21),7.81 ± 0.08 (21),1.34 ± 0.12 (21),,,,
+30 Hz,0.11 ± 0.02 (36),0.09 ± 0.01 (36),8.36 ± 0.13 (36),0.45 ± 0.05 (36),0.15 ± 0.01 (36),0.31 ± 0.02 (36),0.55 ± 0.04 (36),10.39 ± 1.70 (36)
+MWU Baseline I 11 Hz,"550.00, 0.000","568.00, 0.000","223.50, 0.193","477.00, 0.000",,,,
+PRS Baseline I 11 Hz,"1.02, 0.000","0.63, 0.000","0.24, 0.085","0.87, 0.002",,,,
+MWU Baseline I Baseline II,"215.00, 0.291","235.00, 0.100","123.00, 0.102","192.00, 0.703",,,,
+PRS Baseline I Baseline II,"0.30, 0.263","0.12, 0.295","0.12, 0.009","0.05, 0.594",,,,
+MWU Baseline I 30 Hz,"606.00, 0.000","607.00, 0.000","89.00, 0.000","594.00, 0.000",,,,
+PRS Baseline I 30 Hz,"1.07, 0.000","0.64, 0.000","0.61, 0.001","0.92, 0.000",,,,
+MWU 11 Hz Baseline II,"84.00, 0.000","57.00, 0.000","391.50, 0.554","143.00, 0.000",,,,
+PRS 11 Hz Baseline II,"0.72, 0.000","0.51, 0.000","0.12, 0.152","0.82, 0.003",,,,
+MWU 11 Hz 30 Hz,"756.00, 0.092","715.00, 0.228","362.50, 0.003","701.00, 0.298","576.00, 0.677","376.00, 0.006","597.00, 0.865","562.00, 0.561"
+PRS 11 Hz 30 Hz,"0.05, 0.226","0.02, 0.406","0.37, 0.017","0.05, 0.451","0.01, 0.585","0.02, 0.073","0.00, 0.923","1.25, 0.684"
+MWU Baseline II 30 Hz,"701.00, 0.000","704.00, 0.000","154.50, 0.000","709.00, 0.000",,,,
+PRS Baseline II 30 Hz,"0.78, 0.000","0.52, 0.000","0.49, 0.003","0.87, 0.000",,,,
diff --git a/actions/stimulus-spike-lfp-response/data/statistics/statistics_ns_inhibited.tex b/actions/stimulus-spike-lfp-response/data/statistics/statistics_ns_inhibited.tex
index 6444e27b8..86b3f2a91 100644
--- a/actions/stimulus-spike-lfp-response/data/statistics/statistics_ns_inhibited.tex
+++ b/actions/stimulus-spike-lfp-response/data/statistics/statistics_ns_inhibited.tex
@@ -7,15 +7,15 @@ Baseline I                 &  1.10 ± 0.10 (17) &  0.66 ± 0.04 (17) &  7.66 ±
 Baseline II                &  0.94 ± 0.12 (21) &  0.56 ± 0.05 (21) &  7.81 ± 0.08 (21) &  1.34 ± 0.12 (21) &               NaN &               NaN &               NaN &                NaN \\
 30 Hz                      &  0.11 ± 0.02 (36) &  0.09 ± 0.01 (36) &  8.36 ± 0.13 (36) &  0.45 ± 0.05 (36) &  0.15 ± 0.01 (36) &  0.31 ± 0.02 (36) &  0.55 ± 0.04 (36) &  10.39 ± 1.70 (36) \\
 MWU Baseline I 11 Hz       &     550.00, 0.000 &     568.00, 0.000 &     223.50, 0.193 &     477.00, 0.000 &               NaN &               NaN &               NaN &                NaN \\
-PRS Baseline I 11 Hz       &       1.02, 0.000 &       0.63, 0.000 &       0.24, 0.086 &       0.87, 0.002 &               NaN &               NaN &               NaN &                NaN \\
+PRS Baseline I 11 Hz       &       1.02, 0.000 &       0.63, 0.000 &       0.24, 0.085 &       0.87, 0.002 &               NaN &               NaN &               NaN &                NaN \\
 MWU Baseline I Baseline II &     215.00, 0.291 &     235.00, 0.100 &     123.00, 0.102 &     192.00, 0.703 &               NaN &               NaN &               NaN &                NaN \\
-PRS Baseline I Baseline II &       0.30, 0.255 &       0.12, 0.297 &       0.12, 0.009 &       0.05, 0.587 &               NaN &               NaN &               NaN &                NaN \\
+PRS Baseline I Baseline II &       0.30, 0.263 &       0.12, 0.295 &       0.12, 0.009 &       0.05, 0.594 &               NaN &               NaN &               NaN &                NaN \\
 MWU Baseline I 30 Hz       &     606.00, 0.000 &     607.00, 0.000 &      89.00, 0.000 &     594.00, 0.000 &               NaN &               NaN &               NaN &                NaN \\
 PRS Baseline I 30 Hz       &       1.07, 0.000 &       0.64, 0.000 &       0.61, 0.001 &       0.92, 0.000 &               NaN &               NaN &               NaN &                NaN \\
 MWU 11 Hz Baseline II      &      84.00, 0.000 &      57.00, 0.000 &     391.50, 0.554 &     143.00, 0.000 &               NaN &               NaN &               NaN &                NaN \\
-PRS 11 Hz Baseline II      &       0.72, 0.000 &       0.51, 0.000 &       0.12, 0.156 &       0.82, 0.002 &               NaN &               NaN &               NaN &                NaN \\
+PRS 11 Hz Baseline II      &       0.72, 0.000 &       0.51, 0.000 &       0.12, 0.152 &       0.82, 0.003 &               NaN &               NaN &               NaN &                NaN \\
 MWU 11 Hz 30 Hz            &     756.00, 0.092 &     715.00, 0.228 &     362.50, 0.003 &     701.00, 0.298 &     576.00, 0.677 &     376.00, 0.006 &     597.00, 0.865 &      562.00, 0.561 \\
-PRS 11 Hz 30 Hz            &       0.05, 0.230 &       0.02, 0.408 &       0.37, 0.018 &       0.05, 0.442 &       0.01, 0.586 &       0.02, 0.071 &       0.00, 0.921 &        1.25, 0.687 \\
+PRS 11 Hz 30 Hz            &       0.05, 0.226 &       0.02, 0.406 &       0.37, 0.017 &       0.05, 0.451 &       0.01, 0.585 &       0.02, 0.073 &       0.00, 0.923 &        1.25, 0.684 \\
 MWU Baseline II 30 Hz      &     701.00, 0.000 &     704.00, 0.000 &     154.50, 0.000 &     709.00, 0.000 &               NaN &               NaN &               NaN &                NaN \\
 PRS Baseline II 30 Hz      &       0.78, 0.000 &       0.52, 0.000 &       0.49, 0.003 &       0.87, 0.000 &               NaN &               NaN &               NaN &                NaN \\
 \bottomrule
diff --git a/actions/stimulus-spike-lfp-response/data/statistics/statistics_ns_not_inhibited.csv b/actions/stimulus-spike-lfp-response/data/statistics/statistics_ns_not_inhibited.csv
index a70b33cf6..fced2071a 100644
--- a/actions/stimulus-spike-lfp-response/data/statistics/statistics_ns_not_inhibited.csv
+++ b/actions/stimulus-spike-lfp-response/data/statistics/statistics_ns_not_inhibited.csv
@@ -1,22 +1,17 @@
-\begin{tabular}{lllllllll}
-\toprule
-{} &      Theta energy &        Theta peak &        Theta freq &  Theta half width &       Stim energy &   Stim half width &        Stim p max &     Stim strength \\
-\midrule
-Baseline I                 &  0.83 ± 0.08 (49) &  0.52 ± 0.04 (49) &  7.50 ± 0.06 (49) &  1.13 ± 0.08 (49) &               NaN &               NaN &               NaN &               NaN \\
-11 Hz                      &  0.29 ± 0.04 (55) &  0.17 ± 0.02 (55) &  8.04 ± 0.08 (55) &  0.79 ± 0.09 (55) &  0.15 ± 0.02 (55) &  0.36 ± 0.10 (55) &  0.55 ± 0.04 (55) &  5.48 ± 0.62 (55) \\
-Baseline II                &  0.84 ± 0.09 (47) &  0.49 ± 0.04 (47) &  7.83 ± 0.05 (47) &  1.24 ± 0.08 (47) &               NaN &               NaN &               NaN &               NaN \\
-30 Hz                      &  0.14 ± 0.02 (34) &  0.11 ± 0.02 (34) &  8.18 ± 0.12 (34) &  0.49 ± 0.06 (34) &  0.12 ± 0.01 (34) &  0.36 ± 0.06 (34) &  0.47 ± 0.05 (34) &  7.97 ± 1.51 (34) \\
-MWU Baseline I 11 Hz       &    2006.00, 0.000 &    2148.00, 0.000 &     595.00, 0.000 &    1871.00, 0.001 &               NaN &               NaN &               NaN &               NaN \\
-PRS Baseline I 11 Hz       &       0.66, 0.000 &       0.48, 0.000 &       0.37, 0.000 &       0.63, 0.001 &               NaN &               NaN &               NaN &               NaN \\
-MWU Baseline I Baseline II &    1127.00, 0.860 &    1211.00, 0.665 &     600.50, 0.000 &    1032.00, 0.383 &               NaN &               NaN &               NaN &               NaN \\
-PRS Baseline I Baseline II &       0.01, 0.918 &       0.03, 0.567 &       0.24, 0.000 &       0.07, 0.536 &               NaN &               NaN &               NaN &               NaN \\
-MWU Baseline I 30 Hz       &    1372.00, 0.000 &    1415.00, 0.000 &     287.00, 0.000 &    1420.00, 0.000 &               NaN &               NaN &               NaN &               NaN \\
-PRS Baseline I 30 Hz       &       0.73, 0.000 &       0.52, 0.000 &       0.73, 0.000 &       0.72, 0.000 &               NaN &               NaN &               NaN &               NaN \\
-MWU 11 Hz Baseline II      &     584.00, 0.000 &     445.00, 0.000 &    1638.00, 0.020 &     696.00, 0.000 &               NaN &               NaN &               NaN &               NaN \\
-PRS 11 Hz Baseline II      &       0.66, 0.000 &       0.45, 0.000 &       0.12, 0.007 &       0.71, 0.000 &               NaN &               NaN &               NaN &               NaN \\
-MWU 11 Hz 30 Hz            &    1243.00, 0.009 &    1191.00, 0.031 &     760.00, 0.139 &    1182.00, 0.037 &    1041.00, 0.373 &     658.00, 0.020 &    1111.00, 0.138 &     930.00, 0.970 \\
-PRS 11 Hz 30 Hz            &       0.08, 0.046 &       0.03, 0.175 &       0.37, 0.001 &       0.09, 0.240 &       0.00, 0.658 &       0.02, 0.086 &       0.11, 0.128 &       0.27, 0.809 \\
-MWU Baseline II 30 Hz      &    1385.00, 0.000 &    1410.00, 0.000 &     442.50, 0.001 &    1397.00, 0.000 &               NaN &               NaN &               NaN &               NaN \\
-PRS Baseline II 30 Hz      &       0.74, 0.000 &       0.49, 0.000 &       0.49, 0.000 &       0.79, 0.000 &               NaN &               NaN &               NaN &               NaN \\
-\bottomrule
-\end{tabular}
+,Theta energy,Theta peak,Theta freq,Theta half width,Stim energy,Stim half width,Stim p max,Stim strength
+Baseline I,0.83 ± 0.08 (49),0.52 ± 0.04 (49),7.50 ± 0.06 (49),1.13 ± 0.08 (49),,,,
+11 Hz,0.29 ± 0.04 (55),0.17 ± 0.02 (55),8.04 ± 0.08 (55),0.79 ± 0.09 (55),0.15 ± 0.02 (55),0.36 ± 0.10 (55),0.55 ± 0.04 (55),5.48 ± 0.62 (55)
+Baseline II,0.84 ± 0.09 (47),0.49 ± 0.04 (47),7.83 ± 0.05 (47),1.24 ± 0.08 (47),,,,
+30 Hz,0.14 ± 0.02 (34),0.11 ± 0.02 (34),8.18 ± 0.12 (34),0.49 ± 0.06 (34),0.12 ± 0.01 (34),0.36 ± 0.06 (34),0.47 ± 0.05 (34),7.97 ± 1.51 (34)
+MWU Baseline I 11 Hz,"2006.00, 0.000","2148.00, 0.000","595.00, 0.000","1871.00, 0.001",,,,
+PRS Baseline I 11 Hz,"0.66, 0.000","0.48, 0.000","0.37, 0.000","0.63, 0.000",,,,
+MWU Baseline I Baseline II,"1127.00, 0.860","1211.00, 0.665","600.50, 0.000","1032.00, 0.383",,,,
+PRS Baseline I Baseline II,"0.01, 0.914","0.03, 0.572","0.24, 0.000","0.07, 0.542",,,,
+MWU Baseline I 30 Hz,"1372.00, 0.000","1415.00, 0.000","287.00, 0.000","1420.00, 0.000",,,,
+PRS Baseline I 30 Hz,"0.73, 0.000","0.52, 0.000","0.73, 0.000","0.72, 0.000",,,,
+MWU 11 Hz Baseline II,"584.00, 0.000","445.00, 0.000","1638.00, 0.020","696.00, 0.000",,,,
+PRS 11 Hz Baseline II,"0.66, 0.000","0.45, 0.000","0.12, 0.006","0.71, 0.000",,,,
+MWU 11 Hz 30 Hz,"1243.00, 0.009","1191.00, 0.031","760.00, 0.139","1182.00, 0.037","1041.00, 0.373","658.00, 0.020","1111.00, 0.138","930.00, 0.970"
+PRS 11 Hz 30 Hz,"0.08, 0.049","0.03, 0.174","0.37, 0.001","0.09, 0.251","0.00, 0.651","0.02, 0.092","0.11, 0.137","0.27, 0.811"
+MWU Baseline II 30 Hz,"1385.00, 0.000","1410.00, 0.000","442.50, 0.001","1397.00, 0.000",,,,
+PRS Baseline II 30 Hz,"0.74, 0.000","0.49, 0.000","0.49, 0.000","0.79, 0.000",,,,
diff --git a/actions/stimulus-spike-lfp-response/data/statistics/statistics_ns_not_inhibited.tex b/actions/stimulus-spike-lfp-response/data/statistics/statistics_ns_not_inhibited.tex
index a70b33cf6..d3518135f 100644
--- a/actions/stimulus-spike-lfp-response/data/statistics/statistics_ns_not_inhibited.tex
+++ b/actions/stimulus-spike-lfp-response/data/statistics/statistics_ns_not_inhibited.tex
@@ -7,15 +7,15 @@ Baseline I                 &  0.83 ± 0.08 (49) &  0.52 ± 0.04 (49) &  7.50 ±
 Baseline II                &  0.84 ± 0.09 (47) &  0.49 ± 0.04 (47) &  7.83 ± 0.05 (47) &  1.24 ± 0.08 (47) &               NaN &               NaN &               NaN &               NaN \\
 30 Hz                      &  0.14 ± 0.02 (34) &  0.11 ± 0.02 (34) &  8.18 ± 0.12 (34) &  0.49 ± 0.06 (34) &  0.12 ± 0.01 (34) &  0.36 ± 0.06 (34) &  0.47 ± 0.05 (34) &  7.97 ± 1.51 (34) \\
 MWU Baseline I 11 Hz       &    2006.00, 0.000 &    2148.00, 0.000 &     595.00, 0.000 &    1871.00, 0.001 &               NaN &               NaN &               NaN &               NaN \\
-PRS Baseline I 11 Hz       &       0.66, 0.000 &       0.48, 0.000 &       0.37, 0.000 &       0.63, 0.001 &               NaN &               NaN &               NaN &               NaN \\
+PRS Baseline I 11 Hz       &       0.66, 0.000 &       0.48, 0.000 &       0.37, 0.000 &       0.63, 0.000 &               NaN &               NaN &               NaN &               NaN \\
 MWU Baseline I Baseline II &    1127.00, 0.860 &    1211.00, 0.665 &     600.50, 0.000 &    1032.00, 0.383 &               NaN &               NaN &               NaN &               NaN \\
-PRS Baseline I Baseline II &       0.01, 0.918 &       0.03, 0.567 &       0.24, 0.000 &       0.07, 0.536 &               NaN &               NaN &               NaN &               NaN \\
+PRS Baseline I Baseline II &       0.01, 0.914 &       0.03, 0.572 &       0.24, 0.000 &       0.07, 0.542 &               NaN &               NaN &               NaN &               NaN \\
 MWU Baseline I 30 Hz       &    1372.00, 0.000 &    1415.00, 0.000 &     287.00, 0.000 &    1420.00, 0.000 &               NaN &               NaN &               NaN &               NaN \\
 PRS Baseline I 30 Hz       &       0.73, 0.000 &       0.52, 0.000 &       0.73, 0.000 &       0.72, 0.000 &               NaN &               NaN &               NaN &               NaN \\
 MWU 11 Hz Baseline II      &     584.00, 0.000 &     445.00, 0.000 &    1638.00, 0.020 &     696.00, 0.000 &               NaN &               NaN &               NaN &               NaN \\
-PRS 11 Hz Baseline II      &       0.66, 0.000 &       0.45, 0.000 &       0.12, 0.007 &       0.71, 0.000 &               NaN &               NaN &               NaN &               NaN \\
+PRS 11 Hz Baseline II      &       0.66, 0.000 &       0.45, 0.000 &       0.12, 0.006 &       0.71, 0.000 &               NaN &               NaN &               NaN &               NaN \\
 MWU 11 Hz 30 Hz            &    1243.00, 0.009 &    1191.00, 0.031 &     760.00, 0.139 &    1182.00, 0.037 &    1041.00, 0.373 &     658.00, 0.020 &    1111.00, 0.138 &     930.00, 0.970 \\
-PRS 11 Hz 30 Hz            &       0.08, 0.046 &       0.03, 0.175 &       0.37, 0.001 &       0.09, 0.240 &       0.00, 0.658 &       0.02, 0.086 &       0.11, 0.128 &       0.27, 0.809 \\
+PRS 11 Hz 30 Hz            &       0.08, 0.049 &       0.03, 0.174 &       0.37, 0.001 &       0.09, 0.251 &       0.00, 0.651 &       0.02, 0.092 &       0.11, 0.137 &       0.27, 0.811 \\
 MWU Baseline II 30 Hz      &    1385.00, 0.000 &    1410.00, 0.000 &     442.50, 0.001 &    1397.00, 0.000 &               NaN &               NaN &               NaN &               NaN \\
 PRS Baseline II 30 Hz      &       0.74, 0.000 &       0.49, 0.000 &       0.49, 0.000 &       0.79, 0.000 &               NaN &               NaN &               NaN &               NaN \\
 \bottomrule

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