Hi everyone,
Recently I've been doing a lot of work using both GRASS databases
(x,y,z,etc vector data) and Numpy. To simplify things I've written a
python function to extract data from a database using db.select into a
numpy array, making an educated guess at the data type using
db.describe. I'm wondering if this would be any use to anyone else? Any
feedback would be appreciated.
#!/usr/bin/env python
import numpy
import grass.script as grass
import tempfile as pytempfile
def db_select_numpy(tables,sql):
"""
Read data from a grass database into a dictionary of numpy arrays,
making
an educated guess at the dtype from table descriptions.
example:
>>> data = db_select('gpspoints','SELECT x,y,z FROM gpspoints')
>>> print len(data['x']), data['x'].dtype
23 float64
"""
# fetch dtypes from table descriptions
if type(tables) == str:
tables = [tables]
cols = {}
for table in tables:
ret = grass.db.db_describe(table)
for n in range(0,len(ret['cols'])):
if ret['cols'][n][0] in cols:
warnings.warn(ret['cols'][n][0] + ' overwriting
previous instance')
cols[ret['cols'][n][0]] = {'type': ret['cols'][n][1],
'len': ret['cols'][n][2]}
# dtypes translations
dtypes = {'DOUBLE PRECISION':numpy.float64, 'INTEGER':numpy.int,
'CHARACTER':'S'}
# query database
ofile = pytempfile.NamedTemporaryFile(mode = 'w+b')
ofile.close
ret = grass.core.run_command('db.select', overwrite = True, quiet =
True, sql = sql, output = ofile.name)
database = ofile.readlines()
# allocate empty numpy arrays
data = {}
columns = database[0].rstrip().split('|')
for m in range(0,len(columns)):
if columns[m] not in cols:
raise NameError('column "'+columns[m]+'" not in specified
tables')
else:
d = dtypes[cols[columns[m]]['type']]
if d == 'S':
d = 'S' + cols[columns[m]]['len'] # e.g., 'S5'
data[columns[m]] = numpy.empty([len(database)-1],dtype=d)
# copy data into numpy arrays
for n in range(1,len(database)):
elements = database[n].rstrip().split('|')
for m in range(0,len(columns)):
if type(data[columns[m]][n-1]) == numpy.string_ or
len(elements[m]) > 0:
data[columns[m]][n-1] = elements[m]
else:
warnings.warn('numeric cells cannot be empty')
return data
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