def Initialize(self, db):
from pygibbs.unified_group_contribution import UnifiedGroupContribution
ugc = UnifiedGroupContribution(db)
ugc.LoadGroups(FromDatabase=True)
ugc.LoadObservations(FromDatabase=True)
ugc.LoadGroupVectors(FromDatabase=True)
ugc.LoadData(FromDatabase=True)
ugc.init()
self.groups_data = ugc.groups_data
self.group_decomposer = ugc.group_decomposer
result_dict = ugc._GetContributionData(ugc.S.copy(), ugc.cids,
ugc.b.copy(), ugc.anchored)
self.g_pgc = result_dict['group_contributions']
self.P_L_pgc = result_dict['pgc_conservations']
def Initialize(self, db):
from pygibbs.unified_group_contribution import UnifiedGroupContribution
ugc = UnifiedGroupContribution(db)
ugc.LoadGroups(FromDatabase=True)
ugc.LoadObservations(FromDatabase=True)
ugc.LoadGroupVectors(FromDatabase=True)
ugc.LoadData(FromDatabase=True)
ugc.init()
self.groups_data = ugc.groups_data
self.group_decomposer = ugc.group_decomposer
result_dict = ugc._GetContributionData(ugc.S.copy(), ugc.cids,
ugc.b.copy(), ugc.anchored)
self.g_pgc = result_dict['group_contributions']
self.P_L_pgc = result_dict['pgc_conservations']
plt.figure(figsize=(6, 6), dpi=90)
bins = np.arange(-30, 30, 2)
plt.hist([err_feist_nist, err_ugcm_nist], bins=bins, histtype='bar', cumulative=False, normed=False)
plt.xlabel('Error in kJ/mol')
plt.ylabel('# of reactions')
plt.legend(['value in iAF1260', 'UGCM estimation'])
plt.savefig(FIG_FNAME + "_fig3.svg", fmt='.svg')
db = SqliteDatabase('../res/gibbs.sqlite', 'w')
ugc = UnifiedGroupContribution(db)
ugc.LoadGroups(True)
ugc.LoadObservations(True)
ugc.LoadGroupVectors(True)
ugc.LoadData(True)
ugc.init()
r_list = []
#r_list += [Reaction.FromFormula("C00036 + C00044 = C00011 + C00035 + C00074")]
#r_list += [Reaction.FromFormula("C00003 + C00037 + C00101 = C00004 + C00011 + C00014 + C00080 + C00143")] # glycine synthase
r_list += [Reaction.FromFormula("C00001 + C00002 + C00064 + C04376 => C00008 + C00009 + C00025 + C04640")]
#r_list += [Reaction.FromFormula("C00001 + 2 C00002 + C00064 + C00288 <=> 2 C00008 + C00009 + C00025 + C00169")]
kegg = Kegg.getInstance()
S, cids = kegg.reaction_list_to_S(r_list)
logging.getLogger('').setLevel(logging.DEBUG)
dG0_prime = ugc.GetTransfromedReactionEnergies(S, cids, pH=pH, I=I, pMg=pMg, T=T)
RT = R * T
for i in xrange(len(r_list)):
bins=bins,
histtype='bar',
cumulative=False,
normed=False)
plt.xlabel('Error in kJ/mol')
plt.ylabel('# of reactions')
plt.legend(['value in iAF1260', 'UGCM estimation'])
plt.savefig(FIG_FNAME + "_fig3.svg", fmt='.svg')
db = SqliteDatabase('../res/gibbs.sqlite', 'w')
ugc = UnifiedGroupContribution(db)
ugc.LoadGroups(True)
ugc.LoadObservations(True)
ugc.LoadGroupVectors(True)
ugc.LoadData(True)
ugc.init()
r_list = []
#r_list += [Reaction.FromFormula("C00036 + C00044 = C00011 + C00035 + C00074")]
#r_list += [Reaction.FromFormula("C00003 + C00037 + C00101 = C00004 + C00011 + C00014 + C00080 + C00143")] # glycine synthase
r_list += [
Reaction.FromFormula(
"C00001 + C00002 + C00064 + C04376 => C00008 + C00009 + C00025 + C04640"
)
]
#r_list += [Reaction.FromFormula("C00001 + 2 C00002 + C00064 + C00288 <=> 2 C00008 + C00009 + C00025 + C00169")]
kegg = Kegg.getInstance()
S, cids = kegg.reaction_list_to_S(r_list)
logging.getLogger('').setLevel(logging.DEBUG)
