def _custom_traits(self):
'''
Create creates for the atomic size (using the covalent radius) and atom
colors (using the common `Jmol`_ color scheme). Note that that data is
present in the static data (see :mod:`~exa.relational.isotope`).
.. _Jmol: http://jmol.sourceforge.net/jscolors/
'''
self._set_categories()
grps = self.groupby('frame')
symbols = grps.apply(lambda g: g['symbol'].cat.codes.values) # Pass integers rather than string symbols
symbols = Unicode(symbols.to_json(orient='values')).tag(sync=True)
symmap = {i: v for i, v in enumerate(self['symbol'].cat.categories)}
sym2rad = symbol_to_radius()
radii = sym2rad[self['symbol'].unique()]
radii = Dict({i: radii[v] for i, v in symmap.items()}).tag(sync=True) # (Int) symbol radii
sym2col = symbol_to_color()
colors = sym2col[self['symbol'].unique()] # Same thing for colors
colors = Dict({i: colors[v] for i, v in symmap.items()}).tag(sync=True)
try:
atom_set = grps.apply(lambda g: g['set'].values).to_json(orient='values')
atom_set = Unicode(atom_set).tag(sync=True)
except KeyError:
atom_set = Unicode().tag(sync=True)
# Note that position traits (atom_x, atom_y, atom_z) are created automatically
# since we have defined _traits = ['x', 'y', 'z'] above.
return {'atom_symbols': symbols, 'atom_radii': radii, 'atom_colors': colors,
'atom_set': atom_set}
def _update_custom_traits(self):
sgto = self.groupby('frame').apply(lambda x: x.groupby('l').apply( lambda y: y['ml'].values))
sgto = Unicode(sgto.to_json(orient='values')).tag(sync=True)
return {'sphericalgtforder_ml': sgto}
def _update_custom_traits(self):
coefs = self.groupby('frame').apply(lambda x: x.pivot('basis_function', 'orbital', 'coefficient').fillna(value=0).values)
coefs = Unicode(coefs.to_json(orient='values')).tag(sync=True)
#coefs = Unicode('[' + sq.groupby(by=sq.columns, axis=1).apply(
# lambda x: x[x.columns[0]].values).to_json(orient='values') + ']').tag(sync=True)
return {'momatrix_coefficient': coefs}
