for typedesc in dtype.descr:
name = typedesc[0]
type = typedesc[1]
if (type[0] == '<') or (type[0] == '>'):
type = type[1:]
if len(typedesc) > 2:
type = '{}'.format(typedesc[2][0]) + type
#tdescr += (typedesc[2],)
# bit of a hack, but doesn't work with the more complicated format
# specification and FITS binary tables don't support multidimensional
# arrays as columns.
tdescr = (name, type)
columns.append(tdescr)
pool = pool2.Pool()
db = DB(db)
with db.transaction():
if not db.table_exists(table):
table = db.create_table(table, table_def)
else:
table = db.table(table)
for fn, num in pool.imap_unordered(filenames, import_file,
(table, ra, dec, is_radians)):
print 'Imported file {:s} containing {:d} entries.'.format(fn, num)
def main():
parser = argparse.ArgumentParser(description='Import FITS files to LSD')
parser.add_argument('--db', '-d', default=os.environ['LSD_DB'])
parser.add_argument('--ra', default='ra', help='Column in FITS file to rename "ra"')
parser.add_argument('--dec', default='dec', help='Column in FITS file to rename "dec"')
#!/usr/bin/env python
from lsd import DB
def row_counter_kernel(qresult):
for rows in qresult:
yield len(rows)
db = DB('db')
query = db.query("SELECT obj_id FROM ps1_obj, sdss")
total = 0
for subtotal in query.execute([row_counter_kernel]):
total += subtotal
print "The total number of rows returned by the query '%s' is %d" % (query,
total)
import os
def mapper(qresult, bins):
for rows in qresult:
counts, _ = np.histogram(rows['dec'], bins)
for (bin, count) in zip(bins, counts):
if count != 0:
yield (bin, count)
def reducer(kv):
bin, counts = kv
yield (bin, sum(counts))
db = DB(os.environ['LSD_DB'])
query = db.query("SELECT dec FROM sdss")
ddec = 10.
bins = np.arange(-90, 90.0001, ddec)
hist = {}
for (bin, count) in query.execute([(mapper, bins), reducer]):
hist[bin + ddec / 2] = count
for binctr in sorted(hist.keys()):
print "%+05.1f %10d" % (binctr, hist[binctr])
print "Total number of objects:", sum(hist.values())