code
stringlengths
3
6.57k
TestThriftProfile(ImpalaTestSuite)
get_workload(self)
self.client.close()
suite (IMPALA-6498)
test_query_profile_thrift_timestamps(self)
sleep(5)
self.client.execute_async(query)
handle.get_handle()
self.client.fetch(query, handle)
self.client.close()
time.time()
time.time()
time.sleep(1)
self.impalad_test_service.get_thrift_profile(query_id)
start_time.split('.')
end_time.split('.')
len(end_time_sub_sec_str)
time.time()
logging.info("end_time_sub_sec_str hasn't shown up yet, elapsed=%d", elapsed)
len(end_time_sub_sec_str)
len(start_time_sub_sec_str)
strB2Q(ustring)
ord(uchar)
elif (inside_code >= 33 and inside_code <= 126)
chr(inside_code)
Align_CHstr(str, format_spec)
format_spec.format(strB2Q(str)
chr(12288)
compare_xnxq(xnxq1, xnxq2)
xnxq1.split('-')
xnxq2.split('-')
split(';')
replace(';', ' ')
split(';')
Copyright (c)
Microsoft (R)
AzureFirewallNetworkRule(Model)
__init__(self, *, name: str=None, description: str=None, protocols=None, source_addresses=None, destination_addresses=None, destination_ports=None, **kwargs)
super(AzureFirewallNetworkRule, self)
__init__(**kwargs)
argparse.ArgumentParser(description='Merge demuxlet result with gene-count matrix.')
parser.add_argument('demux_res', metavar = 'demux_result.best', help = 'Demuxlet demultiplexing results.')
parser.add_argument('raw_mat', metavar = 'raw_feature_bc_matrix.h5', help = 'Raw gene count matrix in 10x format.')
parser.add_argument('out_file', metavar = 'output_result.zarr', help = 'Output zarr file.')
parser.parse_args()
write_output(assignment_file: str, input_mat_file: str, output_zarr_file: str)
pd.read_csv(assignment_file, sep = '\t', header = 0, index_col = 'BARCODE')
pd.Index([x[:-2] for x in df.index])
apply(lambda s: demux_type_dict[s])
apply(lambda s: ','.join(s.split(',')
pio.read_input(input_mat_file)
data.obs_names.isin(df.index)
pio.write_output(data, output_zarr_file, zarr_zipstore = True)
write_output(args.demux_res, args.raw_mat, args.out_file)
testmod.build_model( ['BoxCox'] , ['MovingAverage'] , ['BestCycle'] , ['AR'] )
np.stack([poss[:,0], poss[:,2]], axis=1)
len(outline.shape)
np.insert(outline, 1, 0, axis=1)
min()
max()
min()
max()
vectors (p1 - p0)
np.concatenate([self.outline[1:], np.expand_dims(self.outline[0], axis=0)
np.linalg.norm(self.edge_dirs, axis=1)
np.cross(self.edge_dirs, Y_VEC)
np.linalg.norm(self.edge_norms, axis=1)
range(self.num_walls)
np.linalg.norm(e_p1 - e_p0)
sort(key=lambda e: e['start_pos'])
point_inside(self, p)
np.sum(self.edge_norms * ap, axis=1)
np.all(np.greater(dotNAP, 0)
_gen_static_data(self, params, rng)
Texture.get(self.wall_tex_name, rng)
Texture.get(self.floor_tex_name, rng)
Texture.get(self.ceil_tex_name, rng)
np.flip(self.outline, axis=0)
self.wall_segs.append(np.array([s_p1, s_p0])
self.wall_verts.append(s_p0 + min_y * Y_VEC)
self.wall_verts.append(s_p0 + max_y * Y_VEC)
self.wall_verts.append(s_p1 + max_y * Y_VEC)
self.wall_verts.append(s_p1 + min_y * Y_VEC)
np.cross(s_p1 - s_p0, Y_VEC)
np.linalg.norm(normal)
range(4)
self.wall_norms.append(normal)
self.wall_texcs.append(texcs)
range(self.num_walls)
np.linalg.norm(edge_p1 - edge_p0)
len(self.portals[wall_idx])
polygon (going up to the first portal)
enumerate(self.portals[wall_idx])
len(self.portals[wall_idx])
np.array(self.wall_verts)
np.array(self.wall_norms)
len(self.wall_segs)
np.array(self.wall_segs)
np.array([])
reshape(0, 2, 3)