In [1]:

    

%matplotlib inline
import sys
import pandas as pd
import os
import tables
import pickle

# os.environ['R_LIBS_USER'] = '/project/projectdirs/metatlas/r_pkgs/'
curr_ld_lib_path = ''

# os.environ['LD_LIBRARY_PATH'] = curr_ld_lib_path + ':/project/projectdirs/openmsi/jupyterhub_libs/boost_1_55_0/lib' + ':/project/projectdirs/openmsi/jupyterhub_libs/lib'

#sys.path.insert(0, '/project/projectdirs/metatlas/python_pkgs/')
#sys.path.insert(0,'/global/project/projectdirs/metatlas/anaconda/lib/python2.7/site-packages' )
#sys.path.append('/global/project/projectdirs/openmsi/jupyterhub_libs/anaconda/lib/python2.7/site-packages')

from metatlas import metatlas_objects as metob
from metatlas import h5_query as h5q

import qgrid

from matplotlib import pyplot as plt

import dill

import numpy as np

from rdkit import Chem
from rdkit.Chem import AllChem
from rdkit.Chem import Draw
# from rdkit.Chem.rdMolDescriptors import ExactMolWt
from rdkit.Chem import Descriptors
from rdkit.Chem import rdMolDescriptors
from rdkit.Chem import AllChem
from rdkit.Chem import Draw
from rdkit.Chem import rdDepictor
from rdkit.Chem.Draw import rdMolDraw2D
from rdkit.Chem.Draw import IPythonConsole
from IPython.display import SVG,display


    

    




/home/jimmy/anaconda2/lib/python2.7/site-packages/IPython/html.py:14: ShimWarning: The `IPython.html` package has been deprecated. You should import from `notebook` instead. `IPython.html.widgets` has moved to `ipywidgets`.
  "`IPython.html.widgets` has moved to `ipywidgets`.", ShimWarning)

In [16]:

    

# my_file = 'save_data_pos_exudates_only.pkl'
# my_file = 'save_data_neg_exudates_only.pkl'
# my_file = 'save_data_pos_cassettes.pkl'
my_file = '20160106_save_data_pos_r2a_replicates_hilic.pkl'
# my_file = 'save_data_neg_archetypes_hilic.pkl'
# my_file = 'save_data_pos_archetypes_hilic_istds.pkl'
# project_label = 'kate_exudates_metatlas_exudates_neg_only'
project_label = '20160106_save_data_pos_r2a_replicates_hilic'

with open(my_file,'r') as f:
    data = dill.load(f)


    

In [3]:

    

print data[1][1].keys()
print data[1][1]['data'].keys()


    

    




['group', 'identification', 'lcmsrun', 'data']
['eic', 'ms1_summary', 'msms']

In [4]:

    

data[1][15]['data']


    

    
Out[4]:





{'eic': {'intensity': array([  3.34468408e+03,   7.56296045e+03,   2.46600781e+03,
           3.43390039e+03,   3.15061523e+03,   6.42145508e+03,
           2.98844141e+03,   6.15165039e+03,   3.76552734e+03,
           3.17461328e+03,   3.46189844e+03,   3.54673828e+03,
           1.97250781e+03,   3.09075000e+03,   3.45294531e+03,
           2.83103125e+03,   2.82762109e+03,   3.12122266e+03,
           3.63455469e+03,   2.83837500e+03,   3.49504688e+03,
           2.00257812e+03,   8.09164062e+03,   6.32307812e+03,
           2.46091406e+03,   3.11416406e+03,   6.10220312e+03,
           5.87065625e+03,   3.41347656e+03,   2.29717969e+03,
           3.40531250e+03,   2.88708594e+03,   6.22285938e+03,
           3.48564844e+03,   7.09829688e+03,   6.16707812e+03,
           8.06615625e+03,   3.61534375e+03,   7.63370312e+03,
           8.44620312e+03,   8.82268750e+03,   7.13665625e+03,
           7.67465625e+03,   8.79921875e+03,   1.09832188e+04,
           5.92689062e+03,   8.37332812e+03,   8.08581250e+03,
           9.63750000e+03,   8.71675000e+03,   8.83012500e+03,
           1.31080938e+04,   1.72070000e+04,   1.84554375e+04,
           3.20790625e+04,   4.47371250e+04,   7.74475000e+04,
           9.89211875e+04,   1.51796438e+05,   2.52811875e+05,
           3.81010438e+05,   4.68976875e+05,   6.82685000e+05,
           9.83400000e+05,   1.32700800e+06,   1.50298500e+06,
           2.08075100e+06,   2.23052600e+06,   2.94264600e+06,
           3.37761500e+06,   3.66194800e+06,   4.66007000e+06,
           4.34240400e+06,   4.96443600e+06,   5.67096000e+06,
           6.01307200e+06,   7.01794400e+06,   8.14269200e+06,
           7.89372400e+06,   7.25768800e+06,   7.79206400e+06,
           8.17224800e+06,   7.26413600e+06,   7.33439200e+06,
           6.57461600e+06,   5.79449600e+06,   5.51360000e+06,
           5.06692000e+06,   4.32510400e+06,   3.93380800e+06,
           3.26392000e+06,   2.67577600e+06,   2.24931200e+06,
           1.89424000e+06,   1.61406400e+06,   1.43830400e+06,
           1.08288000e+06,   1.03064000e+06,   9.62848000e+05,
           7.89616000e+05,   7.72032000e+05,   7.09968000e+05,
           5.81840000e+05,   6.19264000e+05,   5.25760000e+05,
           4.53392000e+05,   4.26608000e+05,   3.50352000e+05,
           3.28080000e+05,   2.74592000e+05,   2.77936000e+05,
           1.90176000e+05,   2.09600000e+05,   1.61056000e+05,
           1.49696000e+05,   1.02480000e+05,   1.02112000e+05,
           8.53600000e+04,   7.76800000e+04,   6.88480000e+04,
           7.65280000e+04,   4.56320000e+04,   4.63840000e+04,
           4.60480000e+04,   4.20000000e+04,   3.32320000e+04,
           3.60960000e+04,   2.50880000e+04,   3.22560000e+04,
           3.60320000e+04,   3.14400000e+04,   2.56640000e+04,
           2.84320000e+04,   3.15040000e+04,   2.86560000e+04,
           3.61120000e+04,   3.53600000e+04,   3.79040000e+04,
           5.03360000e+04,   4.84960000e+04,   5.74560000e+04,
           5.31200000e+04,   7.49280000e+04,   7.39200000e+04,
           9.65600000e+04,   1.23904000e+05,   1.25120000e+05,
           1.13040000e+05,   1.21696000e+05,   1.22240000e+05,
           1.25712000e+05,   1.14864000e+05,   1.25888000e+05,
           8.37920000e+04,   8.29920000e+04,   9.55360000e+04,
           1.02144000e+05,   8.15200000e+04,   7.89280000e+04,
           8.88480000e+04,   8.64800000e+04,   9.36160000e+04,
           8.47200000e+04,   8.42400000e+04], dtype=float32),
  'polarity': 1,
  'rt': array([  8.92443085,   8.94357681,   8.95317078,   8.96275806,
           8.98207092,   8.99186611,   9.00158119,   9.01137257,
           9.0210104 ,   9.03081417,   9.04061604,   9.05038261,
           9.06018543,   9.06998348,   9.07974148,   9.08955002,
           9.09936237,   9.10916424,   9.11897278,   9.12877274,
           9.13856888,   9.14837456,   9.15778732,   9.16758919,
           9.17738914,   9.18719101,   9.19699574,   9.20679951,
           9.21658993,   9.22639179,   9.23618507,   9.24597454,
           9.25578308,   9.26558113,   9.2753849 ,   9.28520393,
           9.29499817,   9.30480194,   9.31459999,   9.32441235,
           9.33422089,   9.34402084,   9.35383511,   9.36364174,
           9.3734436 ,   9.38324547,   9.39305401,   9.40283775,
           9.41264153,   9.42244339,   9.43225002,   9.44204617,
           9.45184326,   9.46164989,   9.47145176,   9.4812727 ,
           9.49108124,   9.50087643,   9.51066875,   9.5204668 ,
           9.53025818,   9.54008102,   9.54981422,   9.55964756,
           9.56945419,   9.57924366,   9.58905029,   9.59885216,
           9.60864162,   9.61844158,   9.62824345,   9.63804626,
           9.64783764,   9.6576519 ,   9.66745853,   9.67726898,
           9.68706417,   9.6968565 ,   9.70665455,   9.71646023,
           9.72629833,   9.73609543,   9.74592113,   9.75575161,
           9.76555634,   9.77536011,   9.78514576,   9.79493141,
           9.80473518,   9.81448555,   9.82427692,   9.83400631,
           9.84374809,   9.85336685,   9.86284637,   9.87231064,
           9.8817358 ,   9.89090157,   9.90018368,   9.90941048,
           9.91864586,   9.92780876,   9.93700218,   9.94602489,
           9.95481873,   9.96410179,   9.9729147 ,   9.98228359,
           9.99170399,  10.00119781,  10.01077938,  10.01976871,
          10.02938747,  10.03892899,  10.0485754 ,  10.05830574,
          10.06792736,  10.07760429,  10.08721733,  10.09687328,
          10.10646725,  10.11590576,  10.12532139,  10.13468838,
          10.14416504,  10.15376282,  10.16333771,  10.17272663,
          10.18225193,  10.19174957,  10.20117664,  10.21091747,
          10.22072697,  10.230546  ,  10.24034214,  10.25013065,
          10.25994968,  10.26974583,  10.27955246,  10.28936481,
          10.29917717,  10.30893803,  10.31855774,  10.32812691,
          10.33734798,  10.34615612,  10.35495186,  10.36381721,
          10.37265205,  10.38154793,  10.39042282,  10.39886475,
          10.40773582,  10.41673183,  10.42567062,  10.43464184,
          10.44362926,  10.45267105,  10.46157742,  10.4706316 ,
          10.47957993,  10.48856735,  10.49759197,  10.50685024], dtype=float32)},
 'ms1_summary': {'mz_centroid': 139.05061,
  'mz_peak': 139.05064,
  'peak_area': 5020174.0,
  'peak_height': 2255562.8,
  'polarity': 1,
  'rt_centroid': 9.7323236,
  'rt_peak': 9.7308064},
 'msms': {'data': array([ (53.07600021362305, 1569.101318359375, 9.546207427978516, 139.0500030517578, 3527810.5, 20.0),
         (54.986900329589844, 1945.19140625, 9.546207427978516, 139.0500030517578, 3527810.5, 20.0),
         (56.96588897705078, 101820.8359375, 9.546207427978516, 139.0500030517578, 3527810.5, 20.0),
         (57.97361755371094, 2493.440185546875, 9.546207427978516, 139.0500030517578, 3527810.5, 20.0),
         (60.28266143798828, 1828.879150390625, 9.546207427978516, 139.0500030517578, 3527810.5, 20.0),
         (62.3231086730957, 1898.606689453125, 9.546207427978516, 139.0500030517578, 3527810.5, 20.0),
         (70.066162109375, 4750.68701171875, 9.546207427978516, 139.0500030517578, 3527810.5, 20.0),
         (71.78445434570312, 1956.5794677734375, 9.546207427978516, 139.0500030517578, 3527810.5, 20.0),
         (71.95288848876953, 54462.87109375, 9.546207427978516, 139.0500030517578, 3527810.5, 20.0),
         (72.08160400390625, 1833.3079833984375, 9.546207427978516, 139.0500030517578, 3527810.5, 20.0),
         (74.09734344482422, 9941.6845703125, 9.546207427978516, 139.0500030517578, 3527810.5, 20.0),
         (84.8247299194336, 2034.026123046875, 9.546207427978516, 139.0500030517578, 3527810.5, 20.0),
         (85.07688903808594, 10795.244140625, 9.546207427978516, 139.0500030517578, 3527810.5, 20.0),
         (87.50013732910156, 3329.26123046875, 9.546207427978516, 139.0500030517578, 3527810.5, 20.0),
         (93.04557037353516, 9281.2216796875, 9.546207427978516, 139.0500030517578, 3527810.5, 20.0),
         (95.06105041503906, 26525.69921875, 9.546207427978516, 139.0500030517578, 3527810.5, 20.0),
         (97.07674407958984, 4294.51806640625, 9.546207427978516, 139.0500030517578, 3527810.5, 20.0),
         (98.07242584228516, 3793.576171875, 9.546207427978516, 139.0500030517578, 3527810.5, 20.0),
         (98.09693145751953, 3476.314697265625, 9.546207427978516, 139.0500030517578, 3527810.5, 20.0),
         (98.97612762451172, 908494.4375, 9.546207427978516, 139.0500030517578, 3527810.5, 20.0),
         (99.97937774658203, 13984.7109375, 9.546207427978516, 139.0500030517578, 3527810.5, 20.0),
         (107.38224029541016, 2012.16455078125, 9.546207427978516, 139.0500030517578, 3527810.5, 20.0),
         (111.0927505493164, 2817.5888671875, 9.546207427978516, 139.0500030517578, 3527810.5, 20.0),
         (112.08767700195312, 17997.30859375, 9.546207427978516, 139.0500030517578, 3527810.5, 20.0),
         (112.56375885009766, 1886.869140625, 9.546207427978516, 139.0500030517578, 3527810.5, 20.0),
         (112.86474609375, 3458.617919921875, 9.546207427978516, 139.0500030517578, 3527810.5, 20.0),
         (113.04622650146484, 2290.297607421875, 9.546207427978516, 139.0500030517578, 3527810.5, 20.0),
         (114.79478454589844, 1888.5517578125, 9.546207427978516, 139.0500030517578, 3527810.5, 20.0),
         (115.45660400390625, 1849.5672607421875, 9.546207427978516, 139.0500030517578, 3527810.5, 20.0),
         (116.98653411865234, 963535.125, 9.546207427978516, 139.0500030517578, 3527810.5, 20.0),
         (117.98988342285156, 16885.59765625, 9.546207427978516, 139.0500030517578, 3527810.5, 20.0),
         (121.0402603149414, 116365.8984375, 9.546207427978516, 139.0500030517578, 3527810.5, 20.0),
         (122.04377746582031, 6975.17333984375, 9.546207427978516, 139.0500030517578, 3527810.5, 20.0),
         (122.09701538085938, 2046.290283203125, 9.546207427978516, 139.0500030517578, 3527810.5, 20.0),
         (123.05561065673828, 21062.423828125, 9.546207427978516, 139.0500030517578, 3527810.5, 20.0),
         (128.9866180419922, 3549.794677734375, 9.546207427978516, 139.0500030517578, 3527810.5, 20.0),
         (134.9969482421875, 681782.75, 9.546207427978516, 139.0500030517578, 3527810.5, 20.0),
         (136.00038146972656, 11462.462890625, 9.546207427978516, 139.0500030517578, 3527810.5, 20.0),
         (138.0554656982422, 3403.21533203125, 9.546207427978516, 139.0500030517578, 3527810.5, 20.0),
         (138.0915069580078, 3228.791748046875, 9.546207427978516, 139.0500030517578, 3527810.5, 20.0),
         (139.05059814453125, 201652.203125, 9.546207427978516, 139.0500030517578, 3527810.5, 20.0),
         (139.1234130859375, 74322.8671875, 9.546207427978516, 139.0500030517578, 3527810.5, 20.0),
         (140.0022735595703, 11542.572265625, 9.546207427978516, 139.0500030517578, 3527810.5, 20.0),
         (140.0557403564453, 13331.4716796875, 9.546207427978516, 139.0500030517578, 3527810.5, 20.0),
         (140.06814575195312, 21061.14453125, 9.546207427978516, 139.0500030517578, 3527810.5, 20.0),
         (140.12657165527344, 7585.0927734375, 9.546207427978516, 139.0500030517578, 3527810.5, 20.0),
         (55.54423904418945, 4075.352294921875, 9.730806350708008, 139.05027770996094, 7792066.5, 20.0),
         (56.96589279174805, 86247.1484375, 9.730806350708008, 139.05027770996094, 7792066.5, 20.0),
         (60.249637603759766, 4831.6171875, 9.730806350708008, 139.05027770996094, 7792066.5, 20.0),
         (64.23908233642578, 4776.29736328125, 9.730806350708008, 139.05027770996094, 7792066.5, 20.0),
         (68.05044555664062, 6191.82421875, 9.730806350708008, 139.05027770996094, 7792066.5, 20.0),
         (69.97936248779297, 6504.6455078125, 9.730806350708008, 139.05027770996094, 7792066.5, 20.0),
         (71.95296478271484, 45160.11328125, 9.730806350708008, 139.05027770996094, 7792066.5, 20.0),
         (74.09727478027344, 6564.14404296875, 9.730806350708008, 139.05027770996094, 7792066.5, 20.0),
         (85.0769271850586, 6255.99658203125, 9.730806350708008, 139.05027770996094, 7792066.5, 20.0),
         (85.4671630859375, 6533.830078125, 9.730806350708008, 139.05027770996094, 7792066.5, 20.0),
         (87.98941802978516, 6185.1962890625, 9.730806350708008, 139.05027770996094, 7792066.5, 20.0),
         (93.04550170898438, 121093.671875, 9.730806350708008, 139.05027770996094, 7792066.5, 20.0),
         (95.06118774414062, 262138.171875, 9.730806350708008, 139.05027770996094, 7792066.5, 20.0),
         (96.06460571289062, 10511.916015625, 9.730806350708008, 139.05027770996094, 7792066.5, 20.0),
         (97.04043579101562, 37434.4609375, 9.730806350708008, 139.05027770996094, 7792066.5, 20.0),
         (98.09724426269531, 5386.2958984375, 9.730806350708008, 139.05027770996094, 7792066.5, 20.0),
         (98.97612762451172, 1112600.625, 9.730806350708008, 139.05027770996094, 7792066.5, 20.0),
         (99.97932434082031, 6864.67529296875, 9.730806350708008, 139.05027770996094, 7792066.5, 20.0),
         (103.43488311767578, 5395.6591796875, 9.730806350708008, 139.05027770996094, 7792066.5, 20.0),
         (112.08744049072266, 10416.47265625, 9.730806350708008, 139.05027770996094, 7792066.5, 20.0),
         (112.15483093261719, 7094.388671875, 9.730806350708008, 139.05027770996094, 7792066.5, 20.0),
         (116.98655700683594, 856504.1875, 9.730806350708008, 139.05027770996094, 7792066.5, 20.0),
         (121.04024505615234, 1286621.0, 9.730806350708008, 139.05027770996094, 7792066.5, 20.0),
         (122.03623962402344, 8376.50390625, 9.730806350708008, 139.05027770996094, 7792066.5, 20.0),
         (122.04364776611328, 102142.90625, 9.730806350708008, 139.05027770996094, 7792066.5, 20.0),
         (134.5682373046875, 5590.9892578125, 9.730806350708008, 139.05027770996094, 7792066.5, 20.0),
         (134.9863739013672, 11520.1396484375, 9.730806350708008, 139.05027770996094, 7792066.5, 20.0),
         (134.99693298339844, 377696.625, 9.730806350708008, 139.05027770996094, 7792066.5, 20.0),
         (139.05064392089844, 2255562.75, 9.730806350708008, 139.05027770996094, 7792066.5, 20.0),
         (139.12342834472656, 59489.4609375, 9.730806350708008, 139.05027770996094, 7792066.5, 20.0),
         (140.00267028808594, 7459.6484375, 9.730806350708008, 139.05027770996094, 7792066.5, 20.0),
         (140.05459594726562, 129185.1640625, 9.730806350708008, 139.05027770996094, 7792066.5, 20.0),
         (140.06874084472656, 10280.2138671875, 9.730806350708008, 139.05027770996094, 7792066.5, 20.0),
         (54.12312698364258, 1690.549560546875, 9.904694557189941, 139.0500030517578, 2999932.5, 20.0),
         (54.98678970336914, 4068.5712890625, 9.904694557189941, 139.0500030517578, 2999932.5, 20.0),
         (56.96589279174805, 76652.296875, 9.904694557189941, 139.0500030517578, 2999932.5, 20.0),
         (57.9736213684082, 2116.113037109375, 9.904694557189941, 139.0500030517578, 2999932.5, 20.0),
         (69.22649383544922, 1908.9400634765625, 9.904694557189941, 139.0500030517578, 2999932.5, 20.0),
         (70.0661392211914, 2960.924560546875, 9.904694557189941, 139.0500030517578, 2999932.5, 20.0),
         (71.95286560058594, 33010.5234375, 9.904694557189941, 139.0500030517578, 2999932.5, 20.0),
         (72.08165740966797, 2413.52392578125, 9.904694557189941, 139.0500030517578, 2999932.5, 20.0),
         (74.0973892211914, 15657.841796875, 9.904694557189941, 139.0500030517578, 2999932.5, 20.0),
         (75.66036224365234, 1823.9996337890625, 9.904694557189941, 139.0500030517578, 2999932.5, 20.0),
         (77.76134490966797, 1878.9400634765625, 9.904694557189941, 139.0500030517578, 2999932.5, 20.0),
         (82.06584167480469, 2904.520263671875, 9.904694557189941, 139.0500030517578, 2999932.5, 20.0),
         (85.07689666748047, 9228.94921875, 9.904694557189941, 139.0500030517578, 2999932.5, 20.0),
         (85.19752502441406, 2533.94921875, 9.904694557189941, 139.0500030517578, 2999932.5, 20.0),
         (87.49995422363281, 4491.8837890625, 9.904694557189941, 139.0500030517578, 2999932.5, 20.0),
         (91.05525970458984, 3352.796875, 9.904694557189941, 139.0500030517578, 2999932.5, 20.0),
         (92.05846405029297, 18698.3125, 9.904694557189941, 139.0500030517578, 2999932.5, 20.0),
         (93.04546356201172, 12209.08984375, 9.904694557189941, 139.0500030517578, 2999932.5, 20.0),
         (95.06118774414062, 30029.177734375, 9.904694557189941, 139.0500030517578, 2999932.5, 20.0),
         (97.07665252685547, 3057.402587890625, 9.904694557189941, 139.0500030517578, 2999932.5, 20.0),
         (98.07225036621094, 3161.834716796875, 9.904694557189941, 139.0500030517578, 2999932.5, 20.0),
         (98.09709930419922, 3561.584228515625, 9.904694557189941, 139.0500030517578, 2999932.5, 20.0),
         (98.97611999511719, 708632.4375, 9.904694557189941, 139.0500030517578, 2999932.5, 20.0),
         (99.09242248535156, 22168.634765625, 9.904694557189941, 139.0500030517578, 2999932.5, 20.0),
         (99.97970581054688, 10202.7451171875, 9.904694557189941, 139.0500030517578, 2999932.5, 20.0),
         (102.35235595703125, 2313.960693359375, 9.904694557189941, 139.0500030517578, 2999932.5, 20.0),
         (111.09237670898438, 1979.6954345703125, 9.904694557189941, 139.0500030517578, 2999932.5, 20.0),
         (112.08765411376953, 17920.11328125, 9.904694557189941, 139.0500030517578, 2999932.5, 20.0),
         (112.8648910522461, 4760.0244140625, 9.904694557189941, 139.0500030517578, 2999932.5, 20.0),
         (116.98652648925781, 723291.1875, 9.904694557189941, 139.0500030517578, 2999932.5, 20.0),
         (117.9895248413086, 14486.455078125, 9.904694557189941, 139.0500030517578, 2999932.5, 20.0),
         (120.05359649658203, 15267.6767578125, 9.904694557189941, 139.0500030517578, 2999932.5, 20.0),
         (121.04019927978516, 152462.734375, 9.904694557189941, 139.0500030517578, 2999932.5, 20.0),
         (122.04354095458984, 8483.8310546875, 9.904694557189941, 139.0500030517578, 2999932.5, 20.0),
         (134.9969482421875, 510657.8125, 9.904694557189941, 139.0500030517578, 2999932.5, 20.0),
         (136.00042724609375, 7965.68896484375, 9.904694557189941, 139.0500030517578, 2999932.5, 20.0),
         (137.06150817871094, 2074.626220703125, 9.904694557189941, 139.0500030517578, 2999932.5, 20.0),
         (137.08018493652344, 16043.986328125, 9.904694557189941, 139.0500030517578, 2999932.5, 20.0),
         (138.0919952392578, 2160.206787109375, 9.904694557189941, 139.0500030517578, 2999932.5, 20.0),
         (139.05062866210938, 266821.625, 9.904694557189941, 139.0500030517578, 2999932.5, 20.0),
         (139.1233367919922, 58733.6171875, 9.904694557189941, 139.0500030517578, 2999932.5, 20.0),
         (140.00213623046875, 11295.4267578125, 9.904694557189941, 139.0500030517578, 2999932.5, 20.0),
         (140.05465698242188, 21907.9921875, 9.904694557189941, 139.0500030517578, 2999932.5, 20.0),
         (140.06871032714844, 37729.2421875, 9.904694557189941, 139.0500030517578, 2999932.5, 20.0),
         (140.12693786621094, 2640.744873046875, 9.904694557189941, 139.0500030517578, 2999932.5, 20.0)], 
        dtype=[('mz', '<f4'), ('i', '<f4'), ('rt', '<f4'), ('precursor_MZ', '<f4'), ('precursor_intensity', '<f4'), ('collision_energy', '<f4')]),
  'most_intense_precursor': {'precursor_intensity': array([ 7792066.5,  3527810.5,  2999932.5], dtype=float32),
   'precursor_mz': array([ 139.05027771,  139.05000305,  139.05000305], dtype=float32),
   'spectra': array([[  5.55442390e+01,   4.07535229e+03],
          [  5.69658928e+01,   8.62471484e+04],
          [  6.02496376e+01,   4.83161719e+03],
          [  6.42390823e+01,   4.77629736e+03],
          [  6.80504456e+01,   6.19182422e+03],
          [  6.99793625e+01,   6.50464551e+03],
          [  7.19529648e+01,   4.51601133e+04],
          [  7.40972748e+01,   6.56414404e+03],
          [  8.50769272e+01,   6.25599658e+03],
          [  8.54671631e+01,   6.53383008e+03],
          [  8.79894180e+01,   6.18519629e+03],
          [  9.30455017e+01,   1.21093672e+05],
          [  9.50611877e+01,   2.62138172e+05],
          [  9.60646057e+01,   1.05119160e+04],
          [  9.70404358e+01,   3.74344609e+04],
          [  9.80972443e+01,   5.38629590e+03],
          [  9.89761276e+01,   1.11260062e+06],
          [  9.99793243e+01,   6.86467529e+03],
          [  1.03434883e+02,   5.39565918e+03],
          [  1.12087440e+02,   1.04164727e+04],
          [  1.12154831e+02,   7.09438867e+03],
          [  1.16986557e+02,   8.56504188e+05],
          [  1.21040245e+02,   1.28662100e+06],
          [  1.22036240e+02,   8.37650391e+03],
          [  1.22043648e+02,   1.02142906e+05],
          [  1.34568237e+02,   5.59098926e+03],
          [  1.34986374e+02,   1.15201396e+04],
          [  1.34996933e+02,   3.77696625e+05],
          [  1.39050644e+02,   2.25556275e+06],
          [  1.39123428e+02,   5.94894609e+04],
          [  1.40002670e+02,   7.45964844e+03],
          [  1.40054596e+02,   1.29185164e+05],
          [  1.40068741e+02,   1.02802139e+04]], dtype=float32)},
  'polarity': 1}}

In [17]:

    

import re
export_group_names = []
for i,d in enumerate(data):
    newstr = d[0]['group'].name
    export_group_names.append(newstr)
# print export_group_names


    

In [18]:

    

import re
export_file_names = []
for i,d in enumerate(data):
    newstr = os.path.basename(d[0]['lcmsrun'].hdf5_file)
    export_file_names.append(newstr)
# print export_file_names


    

In [19]:

    

import re
from collections import defaultdict

export_compound_names = []
export_compound_objects = []
for i,d in enumerate(data[0]):
    export_compound_objects.append(d['identification'])
    if len(d['identification'].compound) > 0:
        str = d['identification'].compound[0].name
    else:
        str = d.name
    newstr = '%s_%s_%s'%(str,d['identification'].mz_references[0].detected_polarity,d['identification'].mz_references[0].adduct)
    newstr = re.sub('[\[\]]','',newstr)
    newstr = re.sub('[^A-Za-z0-9+-]+', '_', newstr)
    newstr = re.sub('i_[A-Za-z]+_i_', '', newstr)
    if newstr[0] == '_':
        newstr = newstr[1:]
    if newstr[0] == '-':
        newstr = newstr[1:]
    if newstr[-1] == '_':
        newstr = newstr[:-1]

    newstr = re.sub('[^A-Za-z0-9]{2,}', '', newstr) #2 or more in regexp
    export_compound_names.append(newstr)

#If duplicate compound names exist, then append them with a number
D = defaultdict(list)
for i,item in enumerate(export_compound_names):
    D[item].append(i)
D = {k:v for k,v in D.items() if len(v)>1}
for k in D.keys():
    for i,f in enumerate(D[k]):
        export_compound_names[f] = '%s%d'%(export_compound_names[f],i)

# for i, e in enumerate (export_compound_names):
#     print i,e


    

In [20]:

    

def plot_chromatogram(d,file_name, ax=None):
    import numpy as np
    from textwrap import wrap
    if ax is None:
        ax = plt.gca()

    plt.rcParams['pdf.fonttype']=42
    plt.rcParams['pdf.use14corefonts'] = True
    plt.rcParams['text.usetex'] = False
    plt.rcParams.update({'font.size': 12})
    plt.rcParams.update({'font.weight': 'bold'})
    plt.rcParams['axes.linewidth'] = 2 # set the value globally

    rt_min = d['identification'].rt_references[0].rt_min
    rt_max = d['identification'].rt_references[0].rt_max
    rt_peak = d['identification'].rt_references[0].rt_peak
        
    if len(d['data']['eic']['rt']) > 0:
        x = d['data']['eic']['rt']
        y = d['data']['eic']['intensity']
        ax.plot(x,y,'k-',linewidth=2.0,alpha=1.0)  
        myWhere = np.logical_and(x>=rt_min, x<=rt_max )
        ax.fill_between(x,0,y,myWhere, facecolor='c', alpha=0.3)

    ax.axvline(rt_min, color='k',linewidth=2.0)
    ax.axvline(rt_max, color='k',linewidth=2.0)
    ax.axvline(rt_peak, color='r',linewidth=2.0)
#     ax.set_xlabel('Time (min)',weight='bold')
#     ax.set_ylabel('Intensity (au)',weight='bold')

    ax.set_title("\n".join(wrap(file_name,54)),fontsize=12,weight='bold')

def plot_all_chromatograms_all_files(data,nCols,export_file_names,export_compound_names,share_y,project_label):
    import time
    d = 'data/%s/chromatograms/'%project_label
    if not os.path.exists(d):
        os.makedirs(d)
    nRows = int(np.ceil(len(export_file_names)/float(nCols)))
    for compound_idx,compound in enumerate(export_compound_names):
        starttime = time.time()
        f, ax = plt.subplots(nRows, nCols, sharey=share_y,figsize=(8*nCols,nRows * 6)) #original 8 x 6
#         plt.tight_layout()
        print "figure created in ", time.time() - starttime, " seconds"
        ax = ax.flatten()
        parttime = time.time()
        for i,fname in enumerate(export_file_names):
            p = plot_chromatogram(data[i][compound_idx], fname, ax=ax[i])
        print i, "subplots created in ", time.time() - parttime, " seconds"
#         parttime = time.time()
#         print "tight layout is ", time.time() - parttime, " seconds"
        parttime = time.time()
        f.savefig('%s%s.pdf'%(d,export_compound_names[compound_idx]))
        print "time to save figure is ", time.time() - parttime, " seconds"
        parttime = time.time()
#         f.clear()
        plt.close('all')#f.clear()
        print "time to clear and close figure is ", time.time() - parttime, " seconds"
        print " "


    

In [21]:

    

""" contribution from Hans de Winter """
def _InitialiseNeutralisationReactions():
    patts= (
        # Imidazoles
        ('[n+;H]','n'),
        # Amines
        ('[N+;!H0]','N'),
        # Carboxylic acids and alcohols
        ('[$([O-]);!$([O-][#7])]','O'),
        # Thiols
        ('[S-;X1]','S'),
        # Sulfonamides
        ('[$([N-;X2]S(=O)=O)]','N'),
        # Enamines
        ('[$([N-;X2][C,N]=C)]','N'),
        # Tetrazoles
        ('[n-]','[nH]'),
        # Sulfoxides
        ('[$([S-]=O)]','S'),
        # Amides
        ('[$([N-]C=O)]','N'),
        )
    return [(Chem.MolFromSmarts(x),Chem.MolFromSmiles(y,False)) for x,y in patts]

_reactions=None
def NeutraliseCharges(mol, reactions=None):
    global _reactions
    if reactions is None:
        if _reactions is None:
            _reactions=_InitialiseNeutralisationReactions()
        reactions=_reactions
#     mol = Chem.MolFromSmiles(smiles)
    replaced = False
    for i,(reactant, product) in enumerate(reactions):
        while mol.HasSubstructMatch(reactant):
            replaced = True
            rms = AllChem.ReplaceSubstructs(mol, reactant, product)
            rms_smiles = Chem.MolToSmiles(rms[0])
            mol = Chem.MolFromSmiles(rms_smiles)
    if replaced:
        return (mol, True) #Chem.MolToSmiles(mol,True)
    else:
        return (mol, False)
def drawStructure_ShowingFragment(pactolus_tree,fragment_idx,myMol,myMol_w_Hs):

    drawer = rdMolDraw2D.MolDraw2DSVG(600,300)

    fragment_atoms = np.where(pactolus_tree[fragment_idx]['atom_bool_arr'])[0]
    mark_atoms_no_H = []
    for a_index in fragment_atoms:
        if myMol_w_Hs.GetAtomWithIdx(a_index).GetSymbol() != 'H':
            mark_atoms_no_H.append(a_index)

    rdDepictor.Compute2DCoords(myMol)

    drawer.DrawMolecule(myMol,highlightAtoms=mark_atoms_no_H)
    drawer.FinishDrawing()
    svg = drawer.GetDrawingText().replace('svg:','')
    return svg

def drawStructure_Fragment(pactolus_tree,fragment_idx,myMol,myMol_w_Hs):
    fragment_atoms = np.where(pactolus_tree[fragment_idx]['atom_bool_arr'])[0]
    depth_of_hit = np.sum(pactolus_tree[fragment_idx]['bond_bool_arr'])
    mol2 = deepcopy(myMol_w_Hs)
    # Now set the atoms you'd like to remove to dummy atoms with atomic number 0
    fragment_atoms = np.where(pactolus_tree[fragment_idx]['atom_bool_arr']==False)[0]
    for f in fragment_atoms:
        mol2.GetAtomWithIdx(f).SetAtomicNum(0)

    # Now remove dummy atoms using a query
    mol3 = Chem.DeleteSubstructs(mol2, Chem.MolFromSmarts('[#0]'))
    mol3 = Chem.RemoveHs(mol3)
    # You get what you are looking for
    return moltosvg(mol3),depth_of_hit


def moltosvg(mol,molSize=(450,150),kekulize=True):
    mc = Chem.Mol(mol.ToBinary())
    if kekulize:
        try:
            Chem.Kekulize(mc)
        except:
            mc = Chem.Mol(mol.ToBinary())
    if not mc.GetNumConformers():
        rdDepictor.Compute2DCoords(mc)
    drawer = rdMolDraw2D.MolDraw2DSVG(molSize[0],molSize[1])
    drawer.DrawMolecule(mc)
    drawer.FinishDrawing()
    svg = drawer.GetDrawingText()
    # It seems that the svg renderer used doesn't quite hit the spec.
    # Here are some fixes to make it work in the notebook, although I think
    # the underlying issue needs to be resolved at the generation step
    return svg.replace('svg:','')

def get_ion_from_fragment(frag_info,spectrum):
    hit_indices = np.where(np.sum(frag_info,axis=1))
    hit = spectrum[hit_indices,:][0]
    return hit,hit_indices


    

In [22]:

    

#plot msms and annotate
#compound name
#formula
#adduct
#theoretical m/z
#histogram of retention times
#scatter plot of retention time with peak area
#retention time
#print all chromatograms
#structure

def file_with_max_precursor_intensity(data,compound_idx):
    idx = []
    my_max = 0
    for i,d in enumerate(data):
        temp = d[compound_idx]['data']['msms']['data']
        if d[compound_idx]['data']['msms']['polarity'] or d[compound_idx]['data']['msms']['polarity'] ==0 :
            m = np.max(temp['precursor_intensity'])
            if m > my_max:
                my_max = m
                idx = i
    return idx,my_max


def make_identification_figure(data,file_idx,compound_idx,export_name,project_label):
    d = 'data/%s/identification/'%project_label
    if not os.path.exists(d):
        os.makedirs(d)
    fig = plt.figure(figsize=(20,20))
#     fig = plt.figure()
    ax = fig.add_subplot(211)
    ax.set_title(data[file_idx][compound_idx]['identification'].compound[0].name,fontsize=12,weight='bold')
    ax.set_xlabel('m/z',fontsize=12,weight='bold')
    ax.set_ylabel('intensity',fontsize=12,weight='bold')

    mz = data[file_idx][compound_idx]['data']['msms']['data']['mz']
    zeros = np.zeros(data[file_idx][compound_idx]['data']['msms']['data']['mz'].shape)
    intensity = data[idx][compound_idx]['data']['msms']['data']['i']
    ax.vlines(mz,zeros,intensity,colors='r',linewidth = 2)
    sx = np.argsort(intensity)[::-1]
    labels = [1.001e9]
    for i in sx:
        if np.min(np.abs(mz[i] - labels)) > 0.1 and intensity[i] > 0.02 * np.max(intensity):
            ax.annotate('%5.4f'%mz[i], xy=(mz[i], 1.01*intensity[i]),rotation = 90, horizontalalignment = 'center', verticalalignment = 'left')
            labels.append(mz[i])

    plt.tight_layout()
    L = plt.ylim()
    plt.ylim(L[0],L[1]*1.12)
   
    inchi =  data[file_idx][compound_idx]['identification'].compound[0].inchi
    myMol = Chem.MolFromInchi(inchi.encode('utf-8'))
    myMol,neutralised = NeutraliseCharges(myMol)
    image = Draw.MolToImage(myMol, size = (300,300) )
    ax2 = fig.add_subplot(223)
    ax2.imshow(image)
    ax2.axis('off')
    #     SVG(moltosvg(myMol))

    ax3 = fig.add_subplot(224)
    ax3.set_xlim(0,1)
    mz_theoretical = data[file_idx][compound_idx]['identification'].mz_references[0].mz
    mz_measured = data[file_idx][compound_idx]['data']['ms1_summary']['mz_centroid']
    if not mz_measured:
        mz_measured = 0

    delta_mz = abs(mz_theoretical - mz_measured)
    delta_ppm = delta_mz / mz_theoretical * 1e6
    
    rt_theoretical = data[file_idx][compound_idx]['identification'].rt_references[0].rt_peak
    rt_measured = data[file_idx][compound_idx]['data']['ms1_summary']['rt_centroid']
    if not rt_measured:
        rt_measured = 0
    ax3.text(0,1,'%s'%os.path.basename(data[file_idx][compound_idx]['lcmsrun'].hdf5_file),fontsize=12)
    ax3.text(0,0.95,'%s %s'%(data[file_idx][compound_idx]['identification'].compound[0].name, data[file_idx][compound_idx]['identification'].mz_references[0].adduct),fontsize=12)
    ax3.text(0,0.9,'m/z theoretical = %5.4f, measured = %5.4f, %5.4f ppm difference'%(mz_theoretical, mz_measured, delta_ppm),fontsize=12)
    ax3.text(0,0.85,'Expected Elution of %5.2f minutes, %5.2f min actual'%(rt_theoretical,rt_measured),fontsize=12)
    ax3.set_ylim(0.2,1.01)
    ax3.axis('off')
#     plt.show()
    fig.savefig('%sIdentifications_%s.pdf'%(d,export_name))
    fig.clear()
    plt.close('all')#f.clear()


    

In [23]:

    

inchi =  '%s'%data[idx][9]['identification'].compound[0].InChI
myMol = Chem.MolFromInchi(inchi.encode('utf-8'))
SVG(moltosvg(myMol))


    

    




---------------------------------------------------------------------------
AttributeError                            Traceback (most recent call last)
<ipython-input-23-b2296acbf8e2> in <module>()
----> 1 inchi =  '%s'%data[idx][9]['identification'].compound[0].InChI
      2 myMol = Chem.MolFromInchi(inchi.encode('utf-8'))
      3 SVG(moltosvg(myMol))

/global/project/projectdirs/metatlas/anaconda/lib/python2.7/site-packages/metatlas/metatlas_objects.pyc in __getattribute__(self, name)
    233         """Automatically resolve stubs on demand.
    234         """
--> 235         value = super(MetatlasObject, self).__getattribute__(name)
    236         if isinstance(value, Stub) and FETCH_STUBS:
    237             value = value.retrieve()

AttributeError: 'Compound' object has no attribute 'InChI'

In [24]:

    

# column name list
# row name list
import pandas as pd
import os
peak_height = pd.DataFrame( index=export_compound_names, columns=export_file_names, dtype=float)
peak_area = pd.DataFrame( index=export_compound_names, columns=export_file_names, dtype=float)

# peak_height['compound'] = compound_list
# peak_height.set_index('compound',drop=True)
for i,dd in enumerate(data):
    for j,d in enumerate(dd):
        if not d['data']['ms1_summary']['peak_height']:
            peak_height.ix[export_compound_names[j],export_file_names[i]] = 0
            peak_area.ix[export_compound_names[j],export_file_names[i]] = 0
        else:
            peak_height.ix[export_compound_names[j],export_file_names[i]] = d['data']['ms1_summary']['peak_height']  
            peak_area.ix[export_compound_names[j],export_file_names[i]] = d['data']['ms1_summary']['peak_area']
columns = []
for i,f in enumerate(export_file_names):
    columns.append((export_group_names[i],f))
peak_height.columns = pd.MultiIndex.from_tuples(columns,names=['group', 'file'])
peak_area.columns = pd.MultiIndex.from_tuples(columns,names=['group', 'file'])


    

In [25]:

    

d = 'data/%s/sheets/'%project_label
if not os.path.exists(d):
    os.makedirs(d)
peak_height.to_csv('data/%s/sheets/compounds peak height.tab'%project_label,sep='\t')
peak_area.to_csv('data/%s/sheets/compounds peak area.tab'%project_label,sep='\t')


    

In [26]:

    

from matplotlib import pyplot as plt

def plot_errorbar_plots(df,compound_list,project_label):
    d = 'data/%s/error_bar/'%project_label
    if not os.path.exists(d):
        os.makedirs(d)
    for compound in compound_list:
        m = df.ix[compound].groupby(level='group').mean()
        e = df.ix[compound].groupby(level='group').std()
        c = df.ix[compound].groupby(level='group').count()

        for i in range(len(e)):
            if c[i]>0:
                e[i] = e[i] / c[i]**0.5

        f, ax = plt.subplots(1, 1,figsize=(20,12))
        m.plot(yerr=e, kind='bar',ax=ax)
        ax.set_title(compound,fontsize=12,weight='bold')
        plt.tight_layout()
        f.savefig('%sErrorBar_%s.pdf'%(d,compound))
        f.clear()
        plt.close('all')#f.clear()


    

In [28]:

    

for compound_idx in range(len(export_compound_names)):
    idx, m = file_with_max_precursor_intensity(data,compound_idx)
    if idx:
        make_identification_figure(data,idx,compound_idx,export_compound_names[compound_idx],project_label)

plot_errorbar_plots(peak_height,export_compound_names,project_label)

nCols = 2
compound_idx = 9
share_y=True
t = plot_all_chromatograms_all_files(data,nCols,export_file_names,export_compound_names,share_y,project_label)


    

    




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