PYTHON/ Computational stoichiometry Make an organized output of the species and stoichiometric data for the reaction series : r0 :  C(s) -> C(g)r1 :  2 C(g) + O2 -> 2 COr2 :  CO + 0.5 O2 -> CO2r3 :  C(g) + H2O -> CO + H2r4 :  CH4 <=> C(g) + 2 H2 A sample code has been provided to guide your results, please follow as closely as you can to obtain the right answer. '''Create the species list''' species_tmp = list()  # temporary list for species for r in reactions:        left  = r.split('<=>')[0].strip() # reactants side    right = r.split('<=>')[1].strip() # products side        left_terms  = left.split('+')   # reactant species w/ stoichiometric coeff.    right_terms = right.split('+')  # product  species w/ stoichiometric coeff.        terms = [t.strip() for t in left_terms] + [t.strip() for t in right_terms] # concatenate list comprehensions        for i in terms:                tmp = i.split(' ') # split stoichiometric coefficient from species name                assert len(tmp)==1 or len(tmp)==2,' terms = %r, i = %r, tmp = %r '%(terms, i, tmp)                if len(tmp) == 2:            species_tmp.append(tmp[1].strip()) # species name if there is a stoichiometric coeff.        else:            species_tmp.append(i.strip()) # species name if there is no stoichiometric coeff. species_filtered = set(species_tmp) # filter species as a set species = list(species_filtered)  # convert species set to list print('\nspecies =\n',species)print('# of species =',len(species)) '''Create the stoichiometric matrix''' import numpy as np # Initialize the stoichiometric matrix as zeros_mtrx = np.zeros((len(reactions), len(species))) for (i_row, r) in enumerate(reactions):        left  = r.split('<=>')[0].strip()    right = r.split('<=>')[1].strip()        left_terms = left.split('+')    left_terms = [t.strip() for t in left_terms] # in-place clean up        right_terms = right.split('+')    right_terms = [t.strip() for t in right_terms] # in-place clean up        for t in left_terms: # reactants                tmp = t.split(' ') # split stoichiometric coeff and species name                if len(tmp) == 2: # stoich coeff and species name            coeff = float(tmp[0].strip())            species_member = tmp[1].strip()            j_col = species.index(species_member) # find id of species in the species list             assert s_mtrx[i_row,j_col] == 0.0, \                   'duplicates not allowed r%r: %r %r r'%\                   (i_row,r,species_member,s_mtrx[i_row,j_col])                        s_mtrx[i_row,j_col] = -1.0 * coeff      else: # only species name            species_member = tmp[0].strip()            j_col = species.index(species_member)                        assert s_mtrx[i_row,j_col] == 0.0, \                   'duplicates not allowed r%r: %r %r r'%\                   (i_row,r,species_member,s_mtrx[i_row,j_col])                        s_mtrx[i_row,j_col] = -1.0   for t in right_terms: # products                tmp = t.split(' ')                if len(tmp) == 2:            coeff = float(tmp[0].strip())            species_member = tmp[1].strip()            j_col = species.index(species_member)                        assert s_mtrx[i_row,j_col] == 0.0, \                   'duplicates not allowed r%r: %r %r r'%\                   (i_row,r,species_member,s_mtrx[i_row,j_col])                        s_mtrx[i_row,j_col] = 1.0 * coeff        else:            species_member = tmp[0].strip()            j_col = species.index(species_member)                        assert s_mtrx[i_row,j_col] == 0.0, \                   'duplicates not allowed r%r: %r %r r'%\                   (i_row,r,species_member,s_mtrx[i_row,j_col])            s_mtrx[i_row,j_col] = 1.0 print('m x n =',s_mtrx.shape)print('s_mtrx =\n',s_mtrx)print('')print('mole balance vector =\n', s_mtrx@np.ones(len(species)))print('mole balance vector =\n', s_mtrx.sum(1))