def main(args):
from cifpdfsearch.cifpdf import HDFStorage
from cifpdfsearch import config, normcodid
from cifpdfsearch._utils import getargswithstdin
if args.config:
config.initialize(args.config)
npyfiles = list(getargswithstdin(args.args))
filename = args.output if args.output is not None else config.PDFSTORAGE
hdb = HDFStorage(filename)
# TODO - add check for existing config in HDFStorage
hdb.writeConfig(config.PDFCALCULATOR)
r = hdb.rgrid
progress_step = len(npyfiles) / (80.0 + 1)
progress_next = 0
for i, f in enumerate(npyfiles):
if os.path.getsize(f) == 0:
continue
g = numpy.load(f)
codid = normcodid(os.path.basename(f))
hdb.writePDF(codid, r, g)
if i >= progress_next:
print('.', end='', flush=True)
progress_next += progress_step
print()
return
def codsearch_composition(composition, tolerance):
from diffpy.pdfgetx.functs import composition_analysis
from elasticsearch import Elasticsearch
from elasticsearch.helpers import scan
es = Elasticsearch(ELASTICHOST)
smbls, counts = composition_analysis(composition)
if tolerance == 0:
mustterms = [{
'term': {
("composition." + s): c
}
} for s, c in zip(smbls, counts)]
q = {"bool": {"must": mustterms}}
else:
rangeterms = [{
'range': {
("composition." + s): {
"gte": c - tolerance,
"lte": c + tolerance,
}
}
} for s, c in zip(smbls, counts)]
q = {"bool": {"must": rangeterms}}
gscan = scan(es,
query={'query': q},
index='cod',
doc_type='cif',
_source=False)
for e in gscan:
codid = normcodid(e['_id'])
yield codid
pass
def readPDF(self, codid):
scid = normcodid(codid)
dsname = self._dspdfpath.format(scid)
with self._openhdf('r') as hfile:
g = hfile[dsname][()]
rv = (self.rgrid, g)
return rv
def main(args):
from cifpdfsearch import config, cifpdf, normcodid
from cifpdfsearch._utils import getargswithstdin
from numpy.random import randint
if args.config:
config.initialize(args.config)
if not os.path.isdir(args.output):
emsg = "{} must be a directory".format(args.output)
raise ValueError(emsg)
ciflist = list(getargswithstdin(args.cifs))
pdfc = cifpdf.calculator.fromConfig(config.PDFCALCULATOR)
while ciflist:
cf = ciflist.pop(randint(len(ciflist)))
codid = normcodid(cf)
out = os.path.join(args.output, 'cod{}.npy'.format(codid))
if not args.force and os.path.isfile(out):
continue
# create the file
open(out, 'w').close()
try:
r, g = calculate(pdfc, cf)
except Exception as e:
print('{}: {} {}'.format(cf, type(e).__name__, e))
continue
numpy.save(out, g.astype(numpy.float32))
return
def readPDF(self, codid):
cid = codid
if isinstance(cid, str):
cid = int(normcodid(cid))
row = self.index[cid]
g = self.gdata[row]
rv = (self.rgrid, g)
return rv
def writePDF(self, codid, r, g):
from numpy import allclose
if r.shape != self.rgrid.shape or not allclose(r, self.rgrid):
emsg = "r must equal the {} dataset".format(self._dsrgridpath)
raise ValueError(emsg)
scid = normcodid(codid)
nm = self._dspdfpath.format(scid)
with self._openhdf('a') as hfile:
ds = hfile.require_dataset(nm, shape=g.shape, dtype=self.dtype)
ds[:] = g
return
def genidpdf_all_hdf(hfile):
grp = hfile['pdfc']
for n, v in grp.items():
yield normcodid(n), v[()]
pass