def _formula_parse_iso(self):
'Parse chemical formula of the salt and get list of all isotopes'
tot_moles: float = 0.0 # Total molar fraction, should add to 1
for meltpart in self.formula.split('+'): # Separate melt components
mfract, comp = meltpart.split(
'%') # Separate component pct. fractions
mfract = float(mfract) / 100.0 # Molar % -> fraction
tot_moles += mfract # Add molar fractions of compositions
comp_f = molmass.Formula(
comp) # Turn component into a molmass formula
for symbol in comp_f._elements: # Elements in a component
ele = self.ELEMENTS[symbol] # Get the element object
for m, n_atoms in comp_f._elements[symbol].items(
): # Number of atoms in a component
if (m != 0): # This should be zero per molmass
raise Exception("Error in parsing")
for A in ele.isotopes.keys(): # Get data for each isotope
Z = ele.protons
amass = ele.isotopes[A].mass
wfrac = ele.isotopes[A].abundance
if wfrac > 0.0:
isotuple = self.SaltIso(Z, A, n_atoms, amass,
wfrac, mfract)
self.isolist.append(isotuple)
self.isolist.sort() # Looks nicer sorted
if abs(tot_moles - 1.0) > 1e-5: # Sanity check
raise ValueError("User Error: Formula " + self.formula +
" molar fractions do not add to 1.0!")
def formula(self):
"""
>>> a = InChI('InChI=1S/C4H6O4.2Na/c5-3(6)1-2-4(7)8;;/h1-2H2,(H,5,6)(H,7,8);;/q;2*+1/p-2')
>>> print a.formula
C4H4Na2O4
>>> a = InChI('InChI=1S/C4H6O4.2Na/c5-3(6)1-2-4(7)8;;/h1-2H2,(H,5,6)(H,7,8);;/q;2*+1/p-2', 'H2O')
>>> print a.formula
H2O
"""
if self.__formula is None:
self.__formula = convert_inchi_to_formula(self.__inchi)
return molmass.Formula(self.__formula)
def ppm_to_ugm3(da, da_T2, da_PSFC):
name = da.name
new_attrs = da.attrs
# get variables needed
chem = da.name.upper()
M = molmass.Formula(chem).mass
R = 8.3145
# convert unit ppmv -> µg/m³
da = (M * da_PSFC * da) / (R * da_T2)
# update attributes with new units
new_attrs['units'] = 'ug m^-3'
new_attrs['description'] = chem + \
' mixing ratio converted to mass concentration'
da.attrs = new_attrs
da.name = name
return (da)
def analyze(formula, maxatoms=250):
"""Return analysis of formula as HTML string."""
def html(formula):
"""Return formula as HTML string."""
formula = re.sub(r'\[(\d+)([A-Za-z]{1,2})\]', r'<sup>\1</sup>\2',
formula)
formula = re.sub(r'([A-Za-z]{1,2})(\d+)', r'\1<sub>\2</sub>', formula)
return formula
result = []
try:
f = molmass.Formula(formula)
result.append(
f'<p><strong>Hill notation</strong>: {html(f.formula)}</p>')
if f.formula != f.empirical:
result.append(f'<p><strong>Empirical formula</strong>:'
f' {html(f.empirical)}</p>')
prec = molmass.precision_digits(f.mass, 8)
if f.mass != f.isotope.mass:
result.append(
f'<p><strong>Average mass</strong>: {f.mass:.{prec}f}</p>')
result.extend((
f'<p><strong>Monoisotopic mass</strong>:'
f' {f.isotope.mass:.{prec}f}</p>',
f'<p><strong>Nominal mass</strong>:'
f' {f.isotope.massnumber}</p>',
))
c = f.composition()
if len(c) > 1:
result.extend((
'<h3>Elemental Composition</h3>'
'<table border="0" cellpadding="2">',
'<tr>',
'<th scope="col" align="left">Element</th>',
'<th scope="col" align="right">Number</th>',
'<th scope="col" align="right">Relative mass</th>',
'<th scope="col" align="right">Fraction %</th>',
'</tr>',
))
for symbol, count, mass, fraction in c:
symbol = re.sub(r'^(\d+)(.+)', r'<sup>\1</sup>\2', symbol)
result.extend((
f'<tr><td>{symbol}</td>',
f'<td align="center">{count}</td>',
f'<td align="right">{mass:.{prec}f}</td>',
f'<td align="right">{fraction * 100:.4f}</td></tr>',
))
count, mass, fraction = c.total
result.extend((
'<tr><td><em>Total</em></td>',
f'<td align="center"><em>{count}</em></td>',
f'<td align="right"><em>{mass:.{prec}f}</em></td>',
f'<td align="right"><em>{fraction * 100:.4f}</em></td>',
'</tr>',
'</table>',
))
if f.atoms < maxatoms:
s = f.spectrum()
if len(s) > 1:
norm = 100.0 / s.peak[1]
result.extend((
'<h3>Mass Distribution</h3>',
'<p><strong>Most abundant mass</strong>: ',
f'{s.peak[0]:.{prec}f} ({s.peak[1] * 100:.3f}%)</p>',
f'<p><strong>Mean mass</strong>: {s.mean:.{prec}}</p>',
'<table border="0" cellpadding="2">',
'<tr>',
'<th scope="col" align="left">Relative mass</th>',
'<th scope="col" align="right">Fraction %</th>',
'<th scope="col" align="right">Intensity</th>',
'</tr>',
))
for mass, fraction in s.values():
result.extend((
f'<tr><td>{mass:.{prec}f}</td>',
f'<td align="right">{fraction*100.:.6}</td>',
f'<td align="right">{fraction*norm:.6}</td></tr>',
))
result.append('</table>')
except Exception as exc:
exc = str(exc).splitlines()
text = exc[0][0].upper() + exc[0][1:]
details = '\n'.join(exc[1:])
result.append('<h2>Error</h2><p>{}</p><pre>{}</pre>'.format(
escape(text, True), escape(details, True)))
return '\n'.join(result)
def formula(self):
return molmass.Formula(self.__formula)
def _weight(x):
return molmass.Formula(x).mass * si.gram / si.mole
def unit_conversion_ratio(df,
unit_conversion_factor={},
feature_units={},
**kwargs):
"""Compute conversion factor between original units and new units (used by hgc)."""
# generate a temporary dataframe to compute ratios
df2 = pd.DataFrame()
# split units into inidivual symbols (incl. prefix) and fill NaN
df2[['orig1', 'orig2', 'orig3']] = df['Unit_orig0'].fillna('').str.split(
r"/| ", expand=True, n=2).reindex(columns=range(3)).copy()
df2[['new1', 'new2', 'new3']] = df['Unit'].fillna('').str.split(
r"/| ", expand=True, n=2).reindex(columns=range(3)).copy()
df2.loc[:, 'unit_conversion_correct'] = True
for orig, new in {'orig1': 'new1', 'orig2': 'new2'}.items():
# force column to string (for example 1/m --> '1', 'm')
df2[orig] = df2[orig].fillna('').astype(str)
df2[new] = df2[new].fillna('').astype(str)
# replace non-dimensional units by "1"
df2[orig] = df2[orig].replace(['n', '-', '', ' '], '1').astype(str)
df2[new] = df2[new].replace(['n', '-', '', ' '], '1').astype(str)
# find where to correct for "mol"
maska = df2[orig].str.contains("mol")
maskb = df2[new].str.contains("mol")
mask = maska | maskb
# compute ratio mol --> gram
features = df['Feature'][mask].unique()
map_molwt = {}
for feature in features:
try:
map_molwt[feature] = molmass.Formula(feature).mass
except: # in case feature is not a chemical formula
map_molwt[feature] = np.nan
df2[orig + 'ratio'] = np.where(maska, df['Feature'].map(map_molwt), 1.)
df2[new + 'ratio'] = np.where(maskb, df['Feature'].map(map_molwt), 1.)
# log errors
df2.loc[df2[orig + 'ratio'].isnull(),
'unit_conversion_correct'] = False
df2.loc[df2[new + 'ratio'].isnull(), 'unit_conversion_correct'] = False
# replace mol by gram (to prevent error in next step) and remove N, P, S
df2[orig] = df2[orig].str.replace('mol', 'g')
df2[new] = df2[new].str.replace('mol', 'g')
df2.loc[maska, 'orig3'] = ''
df2.loc[maskb, 'new3'] = ''
# compute unit conversion ratio
df2[orig +
'ratio'] = df2[orig +
'ratio'] * df2[orig].map(unit_conversion_factor)
df2[new +
'ratio'] = df2[new +
'ratio'] * df2[new].map(unit_conversion_factor)
# log errors. If orig and new both np.nan --> replace ratio's by 1
df2.loc[df2[orig + 'ratio'].isnull() | df2[new + 'ratio'].isnull(),
'unit_conversion_correct'] = False
df2.loc[(df2[orig] == '') & (df2[new] == ''),
[orig + 'ratio', new + 'ratio']] = 1.
# there is no error if the units are on purpose empty (eg ph)
df2.loc[(df['Unit'] == '1') & (df['Unit_orig0'] == '1'),
'unit_conversion_correct'] = True
# force column to string
df2['orig3'] = df2['orig3'].fillna('').astype(str)
df2['new3'] = df2['new3'].fillna('').astype(str)
# find where to compute N, P, S, correction factor (for example mg/L N --> mg/L)
mask3a = df2['orig3'] != ''
mask3b = df2['new3'] != ''
mask3 = mask3a | mask3b
df2.loc[mask3 & ~mask3a, 'orig3'] = df['Feature']
df2.loc[mask3 & ~mask3b, 'new3'] = df['Feature']
# compute weight of atoms/ features
atoms = pd.unique(df2[['orig3', 'new3']][mask3].values.ravel())
map_molwt3 = {}
for atom in atoms:
if atom == 'PO4_ortho':
atom = 'PO4'
try:
map_molwt3[atom] = molmass.Formula(atom).mass
except: # in case atom is not a chemical formula
map_molwt3[atom] = np.nan
df2['orig3ratio'] = np.where(mask3, df2['orig3'].map(map_molwt3), 1.)
df2['new3ratio'] = np.where(mask3, df2['new3'].map(map_molwt3), 1.)
# log errors
df2.loc[df2['orig3ratio'].isnull(), 'unit_conversion_correct'] = False
df2.loc[df2['new3ratio'].isnull(), 'unit_conversion_correct'] = False
# Compute ratio, set ratio to 1 if original and desired unit are equal
df['Ratio'] = ((df2['orig1ratio'] / df2['new1ratio']) *
(df2['new2ratio'] / df2['orig2ratio']) *
(df2['new3ratio'] / df2['orig3ratio']))
df['Ratio'] = np.where(
(df['Unit_orig'] == df['Unit']) | (df['Unit_orig0'] == df['Unit']), 1.,
df['Ratio'])
return df