def GetReactionString(self, r, show_cids=False):
rid = self.rids[r]
sparse = dict([(self.cids[c], self.S[c, r])
for c in self.S[:, r].nonzero()[0].flat])
if self.fluxes[0, r] >= 0:
direction = '=>'
else:
direction = '<='
reaction = Reaction(self.kegg.rid2string(rid), sparse, rid=rid,
direction=direction)
return reaction.to_hypertext(show_cids=show_cids)
def GetReactionString(self, r, show_cids=False):
rid = self.rids[r]
sparse = dict([(self.cids[c], self.S[c, r])
for c in self.S[:, r].nonzero()[0].flat])
if self.fluxes[0, r] >= 0:
direction = '=>'
else:
direction = '<='
reaction = Reaction(self.kegg.rid2string(rid), sparse, rid=rid,
direction=direction)
return reaction.to_hypertext(show_cids=show_cids)
def stoichiometric_matrix2html(html_writer, A, cids, eps=1e-10):
"""
Print a table in HTML format.
A is a stoichiometric matrix where each row is a reaction and
each column is a compound, corresponding in position to the list "cids".
"""
dict_list = []
for i in xrange(A.shape[0]):
sparse_reaction = dict([(cids[j], A[i, j]) for j in xrange(A.shape[1]) if abs(A[i, j]) > eps])
r = Reaction("reaction%d" % i, sparse_reaction=sparse_reaction)
dict_list.append({"reaction": r.to_hypertext()})
html_writer.write_ul(
["%d rows" % A.shape[0], "%d columns" % A.shape[1], "%d rank" % LinearRegression.MatrixRank(A)]
)
html_writer.write_table(dict_list, headers=["#", "reaction"])
def stoichiometric_matrix2html(html_writer, A, cids, eps=1e-10):
"""
Print a table in HTML format.
A is a stoichiometric matrix where each row is a reaction and
each column is a compound, corresponding in position to the list "cids".
"""
dict_list = []
for i in xrange(A.shape[0]):
sparse_reaction = dict([(cids[j], A[i, j]) for j in xrange(A.shape[1])
if abs(A[i, j]) > eps])
r = Reaction("reaction%d" % i, sparse_reaction=sparse_reaction)
dict_list.append({'reaction': r.to_hypertext()})
html_writer.write_ul([
'%d rows' % A.shape[0],
'%d columns' % A.shape[1],
'%d rank' % LinearRegression.MatrixRank(A)
])
html_writer.write_table(dict_list, headers=['#', 'reaction'])
def GetTotalReactionString(self, show_cids=False):
total_S = self.S * self.fluxes.T
sparse = dict([(self.cids[c], total_S[c, 0])
for c in total_S.nonzero()[0].flat])
reaction = Reaction("Total", sparse, direction="=>")
return reaction.to_hypertext(show_cids=show_cids)
def GetTotalReactionString(self, show_cids=False):
total_S = self.S * self.fluxes.T
sparse = dict([(self.cids[c], total_S[c, 0])
for c in total_S.nonzero()[0].flat])
reaction = Reaction("Total", sparse, direction="=>")
return reaction.to_hypertext(show_cids=show_cids)
def write_current_solution(self, exp_html, lp, experiment_name,
output_kegg_file=None):
solution = lp.get_active_reaction_data()
solution_id = '%03d' % lp.solution_index
exp_html.write('%d reactions, flux = %g, \n' %
(len(solution.reactions),
float(solution.fluxes.sum(1))))
# draw network as a graph and link to it
Gdot = self.kegg_pathologic.draw_pathway(solution.reactions,
list(solution.fluxes.flat))
svg_fname = '%s/%s_graph' % (experiment_name, solution_id)
exp_html.embed_dot_inline(Gdot, width=240, height=320, name=svg_fname)
# write the solution for the concentrations in a table
if solution.concentrations is not None:
exp_html.insert_toggle(start_here=True)
rowdicts = []
for c, compound in enumerate(solution.compounds):
rowdict = {}
rowdict['KEGG ID'] = '<a href="%s">C%05d</a>' % (compound.get_link(), compound.cid)
rowdict['Compound'] = compound.name
rowdict[symbol_df_G0_prime + "[kJ/mol]"] = solution.dG0_f[0, c]
rowdict[symbol_df_G_prime + "[kJ/mol]"] = solution.dG_f[0, c]
if np.isfinite(solution.concentrations[0, c]):
rowdict['Conc. [M]'] = '%.1e' % solution.concentrations[0, c]
else:
rowdict['Conc. [M]'] = 'N/A'
rowdicts.append(rowdict)
headers=['KEGG ID', 'Compound', symbol_df_G0_prime + "[kJ/mol]",
symbol_df_G_prime + "[kJ/mol]", 'Conc. [M]']
exp_html.write('Compound Concentrations<br>\n')
exp_html.write_table(rowdicts, headers, decimal=1)
total_reaction = Reaction('total', {})
rowdicts = []
for r, reaction in enumerate(solution.reactions):
rowdict = {}
flux = solution.fluxes[0, r]
rowdict['KEGG ID'] = '<a href="%s">R%05d</a>' % (reaction.get_link(), reaction.rid)
rowdict['Reaction'] = reaction.to_hypertext(show_cids=False)
rowdict['Flux'] = flux
rowdict[symbol_dr_Gc_prime + "[kJ/mol]"] = solution.dGc_r[0, r]
rowdict[symbol_dr_G_prime + "[kJ/mol]"] = solution.dG_r[0, r]
rowdicts.append(rowdict)
total_reaction += (flux * reaction)
rowdict = {}
rowdict['KEGG ID'] = 'total'
rowdict['Reaction'] = total_reaction.to_hypertext(show_cids=False)
rowdict[symbol_dr_Gc_prime + "[kJ/mol]"] = float(solution.dGc_r.sum(1))
rowdict[symbol_dr_G_prime + "[kJ/mol]"] = float(solution.dG_r.sum(1))
rowdicts.append(rowdict)
headers=['KEGG ID', 'Reaction', symbol_dr_Gc_prime + "[kJ/mol]",
symbol_dr_G_prime + "[kJ/mol]", "Flux"]
exp_html.write('Reaction Gibbs energies<br>\n')
exp_html.write_table(rowdicts, headers, decimal=1)
exp_html.div_end()
# write the pathway in KEGG format
if output_kegg_file is not None:
write_kegg_pathway(output_kegg_file,
entry=experiment_name + ' ' + solution_id,
reactions=solution.reactions,
fluxes=list(solution.fluxes.flat))
exp_html.write('<br>\n')