1. Import Python Packages

In [1]:

    

%matplotlib notebook
import sys
sys.path.insert(1,'/global/project/projectdirs/metatlas/anaconda/lib/python2.7/site-packages' )

from metatlas.helpers import metatlas_get_data_helper_fun as ma_data
import metatlas.metatlas_objects as metob

import os
import numpy as np
import pandas as pd

import matplotlib.pyplot as plt


    

    




('Metatlas live in ', '/global/project/projectdirs/metatlas/anaconda/lib/python2.7/site-packages/metatlas')
you're running on mndlhm0203 at 10.36.162.159 

In [2]:

    

my_file = metob.retrieve('Lcmsrun',name='20150910%_WT_%Run61%',username='*')[-1]


    

In [3]:

    

df_container = ma_data.df_container_from_metatlas_file(my_file)


    

In [4]:

    

print df_container.keys()
df = df_container['ms2_neg']
df = df[abs(df.rt-7.495)<0.001]
df.sort_values('i',axis=0,ascending=False,inplace=True)
df.head()


    

    




['ms1_pos', 'ms2_neg', 'ms2_pos', 'ms1_neg']






    




/global/project/projectdirs/metatlas/anaconda/lib/python2.7/site-packages/IPython/kernel/__main__.py:4: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame

See the caveats in the documentation: http://pandas.pydata.org/pandas-docs/stable/indexing.html#indexing-view-versus-copy






    
Out[4]:






  

    

      

      
mz
      
i
      
rt
      
precursor_MZ
      
precursor_intensity
      
collision_energy
    
  
  

    

      
45956
      
392.272003
      
3.666669e+06
      
7.49546
      
392.272034
      
5079225.5
      
20.0
    
    

      
45955
      
377.248199
      
1.919126e+06
      
7.49546
      
392.272034
      
5079225.5
      
20.0
    
    

      
45943
      
236.083069
      
2.674115e+05
      
7.49546
      
392.272034
      
5079225.5
      
20.0
    
    

      
45944
      
237.090897
      
6.987196e+04
      
7.49546
      
392.272034
      
5079225.5
      
20.0
    
    

      
45945
      
250.099396
      
6.263963e+04
      
7.49546
      
392.272034
      
5079225.5
      
20.0
    
  

In [5]:

    

fig = plt.figure(figsize=(10,6))
ax = fig.add_subplot(111)

ax.set_xlabel('m/z',fontsize=12,weight='bold')
ax.set_ylabel('intensity',fontsize=12,weight='bold')

ax.vlines(df['mz'],np.zeros(len(df['mz'])),df['i'],colors='r',linewidth = 2)
labels = [1.001e9]
for i,row in df.iterrows():
     if np.min(np.abs(row.mz - labels)) > 0.1 and row.i > 0.01 * df.i.max():
        ax.annotate('%.4f'%row.mz, xy=(row.mz, 1.01*row.i),rotation = 90, horizontalalignment = 'center', verticalalignment = 'left')
        labels.append(row.mz)

# plt.axhline()
# plt.tight_layout()
# L = plt.ylim()
ax.set_yscale('log')
plt.ylim(1e4,1e7)


    

    















    












    
Out[5]:





(10000.0, 10000000.0)

In [ ]: