In [1]:

    

import pandas as pd
import numpy as np
import matplotlib.pyplot as plt
import glob
import jedi
%matplotlib inline


    

In [34]:

    

location = "/Users/weilu/Research/server/oct_2017/23oct/memb_3_rg_0.1_lipid_1_topology/simulation/test/0/0/"
fileName = "angles.csv"
data = pd.read_csv(location + fileName)
data.columns = data.columns.str.strip()
data2 = data.pivot_table(values='Angle', index='Frame', columns='Helix')
data2.columns = ["Helix" + str(i) for i in list(data2.columns)]


    

In [35]:

    

data2.query('abs(Helix1) > 0.2 & abs(Helix6) < 0.2')


    

    
Out[35]:







  

    

      

      
Helix1
      
Helix2
      
Helix3
      
Helix4
      
Helix5
      
Helix6
    
    

      
Frame
      

      

      

      

      

      

    
  
  

    

      
2
      
0.958807
      
-0.843155
      
0.784203
      
-0.922474
      
0.316717
      
0.112457
    
    

      
3
      
0.983988
      
-0.884886
      
0.973504
      
-0.875190
      
-0.301486
      
0.138367
    
    

      
4
      
0.988920
      
-0.991375
      
0.819003
      
-0.893863
      
-0.121061
      
0.184560
    
    

      
7
      
0.965696
      
-0.937274
      
0.929194
      
-0.961609
      
-0.277609
      
0.197083
    
    

      
8
      
0.870417
      
-0.975476
      
0.883158
      
-0.783042
      
-0.173975
      
0.154555
    
    

      
9
      
0.984983
      
-0.939534
      
0.913308
      
-0.881203
      
-0.496792
      
0.165638
    
    

      
10
      
0.953259
      
-0.988167
      
0.940443
      
-0.898698
      
-0.253104
      
0.068214
    
    

      
11
      
0.988898
      
-0.869757
      
0.902109
      
-0.756724
      
0.753479
      
-0.038889
    
    

      
2983
      
0.849606
      
-0.876580
      
0.926273
      
-0.838251
      
0.875517
      
0.088100
    
    

      
2984
      
0.956263
      
-0.822980
      
0.982380
      
-0.963726
      
0.976369
      
0.123281
    
    

      
2985
      
0.879235
      
-0.733759
      
0.886220
      
-0.970354
      
0.636246
      
0.167980
    
    

      
2986
      
0.948674
      
-0.861237
      
0.997800
      
-0.949333
      
0.947599
      
-0.117024
    
    

      
2988
      
0.934450
      
-0.776396
      
0.910108
      
-0.843526
      
0.277435
      
0.063588
    
    

      
2989
      
0.928283
      
-0.903119
      
0.987344
      
-0.768861
      
0.485970
      
-0.132733
    
    

      
2993
      
0.975392
      
-0.896838
      
0.987115
      
-0.993382
      
0.557705
      
-0.002005
    
    

      
2994
      
0.996225
      
-0.922031
      
0.950887
      
-0.913136
      
0.755891
      
-0.144787
    
    

      
2996
      
0.990582
      
-0.711645
      
0.945308
      
-0.976782
      
0.773397
      
0.099843
    
    

      
2997
      
0.999059
      
-0.915638
      
0.929169
      
-0.990210
      
0.635490
      
0.016146
    
    

      
2998
      
0.990973
      
-0.705024
      
0.987189
      
-0.827492
      
0.680304
      
-0.122239
    
  

In [1]:

    

location = "/Users/weilu/Research/server/oct_2017/23oct/memb_3_rg_0.1_lipid_1_extended/1d_dis/t_all/force_0.0/evpb-500.dat"
name_list = ["Lipid", "Go", "Mem", "Rg"]
names = ["bin", "x"] + name_list
data = pd.read_table(location, skiprows=1, sep='\s+', names=names)


    

    




---------------------------------------------------------------------------
NameError                                 Traceback (most recent call last)
<ipython-input-1-28befba385d1> in <module>()
      2 name_list = ["Lipid", "Go", "Mem", "Rg"]
      3 names = ["bin", "x"] + name_list
----> 4 data = pd.read_table(location, skiprows=1, sep='\s+', names=names)

NameError: name 'pd' is not defined

In [69]:

    

fig, ax = plt.subplots()

processed_data = data - data.mean()
for name in name_list:
    processed_data.query('x < 120').plot('x', name, ax=ax, ylim=(-50,50))


    

In [64]:

    

data.mean()


    

    
Out[64]:





bin     24.50000
x       71.54094
e1     -38.71914
e2    -487.81078
e3    -122.26358
e4       5.73332
dtype: float64

In [74]:

    

location = "/Users/weilu/Research/server/oct_2017/23oct/memb_3_rg_0.1_lipid_1_topology/sub_sample_1d_dis_t_all/"
file = "pmf-420.dat"
name_list = ["e1", "e2", "e3", "e4"]
names = ["bin", "x"] + name_list
data1 = pd.read_table(location+file, skiprows=2, sep='\s+', names=names)

location = "/Users/weilu/Research/server/oct_2017/23oct/memb_3_rg_0.1_lipid_1_topology/sub_sample_1d_dis_t_all/compare/"
file = "pmf-420.dat"
name_list = ["e1", "e2", "e3", "e4"]
names = ["bin", "x"] + name_list
data2 = pd.read_table(location+file, skiprows=2, sep='\s+', names=names)


    

In [79]:

    

fig, ax = plt.subplots()
data1.plot('x', 'e1', ax=ax)
data2.plot('x', 'e1', ax=ax, c="red")


    

    
Out[79]:





<matplotlib.axes._subplots.AxesSubplot at 0x120ec8e48>






    

In [ ]: