#############
# Catalysis #
#############
job = Entity(name='job',
desc='DFT job',
attrs=[
Attr('stordir',
Varchar,
desc='Directory containing log file',
id=True),
Attr('job_name', Varchar, desc='Name of job - arbitrary'),
Attr('user', Varchar, desc='Owner of job'),
Attr('energy', Double, desc='Energy result of job')
],
fks=[FK('struct'), FK('calc')])
elem = Entity(name='element',
desc='chemical element',
attrs=[
Attr('atomic_number', desc='# of protons', id=True),
Attr('symbol', Varchar, desc='E.g. He, K, Li'),
Attr('name', Varchar)
])
species = Entity(
name='species',
desc="""Abstraction of a struct which throws away position info.
Composition is a python dictionary mapping atomic number
to NORMALIZED stoich""",
attrs=[
# Compute the L² Norm of three 3D vectors
] + [SQLAttr(structs,abc,Double,
Sum([structs['%s%d'%(xyz,i)] ** Literal(2)
for i in range(1,4)]) ** Literal(0.5))
for abc,xyz in zip('abc','xyz')
] + [SQLAttr(calcs,attr,Varchar,Literal(constval))
for attr,constval in calc_constants.items()],
# 1.4: Attrs computed in CQL (can use Java functions + info from multiple tables)
#---------------------------------------------------------------------------
new_attr1 = [NewAttr(structs,'composition', String, mcd(structs['comp'])),
NewAttr(structs,'raw', Text, msj(*msj_args)),
NewAttr(atoms,'ind',Int,bigint_to_int(atoms['bigind']))],
# 1.5: New Entities computed in CQL
#----------------------------------
new_ent1 = [NewEntity(name = 'struct_composition',
gens = [s0, l0],
where = [EQ(gt(elemcount, zero) , JLit('true',Boolean))],
attrs = {Attr('num',Int) : elemcount},
fks = {FK('struct','structures') : s0,
FK('element','elements') : l0}),
NewEntity(name = 'bulk',
gens = [s0],
fks = {FK('struct','structures') : s0})]
)
rots = Entity(name='rotations',
id='id',
attrs=[
Attr('a%d%d' % (i, j), Double, id=True) for i in range(3)
for j in range(3)
])
trans = Entity(name='translations',
id='id',
attrs=[Attr(x, Double, id=True) for x in 'xyz'])
operations = Entity(name='operations',
id='id',
fks=[
FK('rotation_id', 'rotations', id=True),
FK('translation_id', 'translations', id=True)
])
elems = Entity(name='elements',
id='z',
attrs=[
Attr('z', Int, desc='atomic number', id=True),
Attr('name', Varchar, desc='full atomic name'),
Attr('symbol', Varchar, desc='atomic symbol'),
Attr('group', ),
Attr('period', ),
Attr('mass', Double),
Attr('specific_heat', Double),
Attr('s_elec', ),
Attr('p_elec', ),
# External
from typing import Callable as C
# Internal
from cdi import Schema, Entity, Attr, Varchar, FK, Instance, Gen, JLit, Integer
################################################################################
Chap = Entity(name='Chap',
desc="A chapter within a book",
id='id',
attrs=[
Attr('num', id=True, desc='Chapter #'),
Attr('text', Varchar, desc='Full text of a chapter')
],
fks=[FK('novel_id', 'Nov', id=True)])
Nov = Entity(name='Nov',
desc='A book',
id='id',
attrs=[
Attr('aname', Varchar, desc='Author name'),
Attr('title', Varchar, id=True, desc='Book title '),
Attr('year', desc='Book publish date')
])
Readr = Entity(
name='Readr',
desc='A reader',
id='id',
attrs=[
Attr('rname', Varchar, desc='Reader name'),
Attr('borrowed',
Varchar,
overlap = Overlap(
s1=src,
s2=tar,
paths=[
PathEQ(Path(Nov['title']), Path(Novel['title'])),
PathEQ(Path(Nov['aname']), Path(Novel['wrote'], Author['authorname'])),
PathEQ(Path(Chap['num']), Path(Chapter['num'])),
PathEQ(Path(Chap['novel_id']), Path(Chapter['novel'])),
PathEQ(Path(Readr['rname']), Path(Reader['readername'])),
PathEQ(Path(Readr['fav']), Path(Reader['favorite']))
],
new_attr1=[
NewAttr(Chap, 'n_words', Integer, count_words(chap['text'])),
],
new_fk1=[NewFK(Nov, FK('wrote', 'Author'), nov)],
new_ent1=[
NewEntity(name='Author', gens=[nov]),
NewEntity(name='Borrow',
gens=[nov, readr],
where=[
EQ(
matches(readr['borrowed'],
concat(wild, nov['title'], wild)),
Lit('true', Boolean))
],
attrs={
Attr('total_len', Integer):
plus(Len(readr['rname']), Len(nov['title']))
},
fks={