def make_computed_fields(self, json_cmd):
print('Adding computed fields')
cmd = json.loads(json_cmd)
array_url = cmd.get('input', self.base_url + self.array_name)
if not array_url.startswith(self.base_url):
raise RuntimeError('Input array must start with the base url')
array_name = array_url[len(self.base_url):]
fields = cmd['fields']
replace_undim = cmd.get('replace_undim', 0)
fnname = cmd.get('fnname', None)
arr = self.get_session_array(array_name).ddesc.dynd_arr()
res = nd.make_computed_fields(arr, replace_undim, fields, fnname)
defarr = self.array_provider.create_deferred_array_filename(
self.session_name, 'computed_fields_', array(res))
dshape = nd.dshape_of(res)
defarr[0].write(json.dumps({
'dshape': dshape,
'command': 'make_computed_fields',
'params': {
'fields': fields,
'replace_undim': replace_undim,
'fnname': fnname
}
}))
defarr[0].close()
content_type = 'application/json; charset=utf-8'
body = json.dumps({
'session': self.base_url + self.session_name,
'output': self.base_url + defarr[1],
'dshape': dshape
})
return (content_type, body)
def make_computed_fields(self, json_cmd):
print('Adding computed fields')
cmd = json.loads(json_cmd)
array_url = cmd.get('input', self.base_url + self.array_name)
if not array_url.startswith(self.base_url):
raise RuntimeError('Input array must start with the base url')
array_name = array_url[len(self.base_url):]
fields = cmd['fields']
replace_undim = cmd.get('replace_undim', 0)
fnname = cmd.get('fnname', None)
arr = self.get_session_array(array_name).ddesc.dynd_arr()
res = nd.make_computed_fields(arr, replace_undim, fields, fnname)
defarr = self.array_provider.create_deferred_array_filename(
self.session_name, 'computed_fields_', array(res))
dshape = nd.dshape_of(res)
defarr[0].write(
json.dumps({
'dshape': dshape,
'command': 'make_computed_fields',
'params': {
'fields': fields,
'replace_undim': replace_undim,
'fnname': fnname
}
}))
defarr[0].close()
content_type = 'application/json; charset=utf-8'
body = json.dumps({
'session': self.base_url + self.session_name,
'output': self.base_url + defarr[1],
'dshape': dshape
})
return (content_type, body)
def test_aggregate(self):
a = nd.array([
('A', 1, 2),
('A', 3, 4),
('B', 1.5, 2.5),
('A', 0.5, 9),
('C', 1, 5),
('B', 2, 2)],
dtype='c{cat: string, x: float32, y: float32}')
gb = nd.groupby(a, nd.fields(a, 'cat')).eval()
b = nd.make_computed_fields(gb, 1,
fields=[('sum_x', ndt.float32, 'sum(x)'),
('mean_y', ndt.float32, 'mean(y)'),
('max_x', ndt.float32, 'max(x)'),
('max_y', ndt.float32, 'max(y)')])
self.assertEqual(nd.as_py(b.sum_x), [4.5, 3.5, 1])
self.assertEqual(nd.as_py(b.mean_y), [5, 2.25, 5])
self.assertEqual(nd.as_py(b.max_x), [3, 2, 1])
self.assertEqual(nd.as_py(b.max_y), [9, 2.5, 5])
