after ex_open
         I/O word size 8
after ex_get_init_ext(exoid, &par), error = 0
database parameters:
title =  'This is a test'
num_dim = 3
num_assembly = 0
num_blobs = 3
num_nodes = 0
num_edge = 0
num_face = 0
num_elem = 0
num_elem_blk = 0
num_node_sets = 0
num_side_sets = 0
after ex_get_blob(exoid, &blobs[i]), error = 0
Blob named 'Tempus' has id 100. It contains 10 entries.
	
after ex_get_blob(exoid, &blobs[i]), error = 0
Blob named 'IOSS' has id 200. It contains 20 entries.
	
after ex_get_blob(exoid, &blobs[i]), error = 0
Blob named 'Solver' has id 300. It contains 15 entries.
	
after ex_get_blobs(exoid, blb), error = 0
Blob named 'Tempus' has id 100. It contains 10 entries.
Blob named 'IOSS' has id 200. It contains 20 entries.
Blob named 'Solver' has id 300. It contains 15 entries.
Blob named 'Tempus' with id 100. It contains 2 attributes:
	Name: 'Scale', Type = 6, Value Count = 1
		1.5
	Name: 'Units', Type = 4, Value Count = 4
		1	0	0	-1

Blob named 'IOSS' with id 200. It contains 1 attributes:
	Name: 'Offset', Type = 6, Value Count = 3
		1.1	2.2	3.3

Blob named 'Solver' with id 300. It contains 2 attributes:
	Name: 'Dimension', Type = 2, Value Count = 7
		l	e	n	g	t	h
	Name: 'Offset', Type = 6, Value Count = 3
		1.1	2.2	3.3

GLOBAL contains 1 attributes:
	Name: 'SOLID_MODEL', Type = 2, Value Count = 24
after ex_get_reduction_variable_param(exoid, EX_BLOB, &num_red_vars), error = 0
after ex_get_variable_param(exoid, EX_BLOB, &num_vars), error = 0
after ex_get_reduction_variable_names(exoid, EX_BLOB, num_red_vars, var_names), error = 0
There are  4 blob reduction variables; their names are :
 'Momentum_X'
 'Momentum_Y'
 'Momentum_Z'
 'Kinetic_Energy'
after ex_get_variable_names(exoid, EX_BLOB, num_vars, var_names), error = 0
There are  3 blob variables; their names are :
 'X'
 'XDOT'
 'XDDOT'
There are  4 time steps in the database.
after ex_get_time(exoid, i + 1, &time_value), error = 0
Time at step 1 is 0.010000.
after ex_get_reduction_vars(exoid, i + 1, EX_BLOB, blb[k].id, num_red_vars, var_values), error = 0
Values for Blob 100 at step 1: 0.020000	0.030000	0.040000	0.050000
after ex_get_var(exoid, i + 1, EX_BLOB, var_idx+1, blobs[k].id, blobs[k].num_entry, vals), error = 0
0.020
1.020
2.020
3.020
4.020
5.020
6.020
7.020
8.020
9.020
after ex_get_var(exoid, i + 1, EX_BLOB, var_idx+1, blobs[k].id, blobs[k].num_entry, vals), error = 0
0.030
1.030
2.030
3.030
4.030
5.030
6.030
7.030
8.030
9.030
after ex_get_var(exoid, i + 1, EX_BLOB, var_idx+1, blobs[k].id, blobs[k].num_entry, vals), error = 0
0.040
1.040
2.040
3.040
4.040
5.040
6.040
7.040
8.040
9.040
after ex_get_reduction_vars(exoid, i + 1, EX_BLOB, blb[k].id, num_red_vars, var_values), error = 0
Values for Blob 200 at step 1: 1.020000	1.030000	1.040000	1.050000
after ex_get_var(exoid, i + 1, EX_BLOB, var_idx+1, blobs[k].id, blobs[k].num_entry, vals), error = 0
0.030
1.030
2.030
3.030
4.030
5.030
6.030
7.030
8.030
9.030
10.030
11.030
12.030
13.030
14.030
15.030
16.030
17.030
18.030
19.030
after ex_get_var(exoid, i + 1, EX_BLOB, var_idx+1, blobs[k].id, blobs[k].num_entry, vals), error = 0
0.040
1.040
2.040
3.040
4.040
5.040
6.040
7.040
8.040
9.040
10.040
11.040
12.040
13.040
14.040
15.040
16.040
17.040
18.040
19.040
after ex_get_var(exoid, i + 1, EX_BLOB, var_idx+1, blobs[k].id, blobs[k].num_entry, vals), error = 0
0.050
1.050
2.050
3.050
4.050
5.050
6.050
7.050
8.050
9.050
10.050
11.050
12.050
13.050
14.050
15.050
16.050
17.050
18.050
19.050
after ex_get_reduction_vars(exoid, i + 1, EX_BLOB, blb[k].id, num_red_vars, var_values), error = 0
Values for Blob 300 at step 1: 2.020000	2.030000	2.040000	2.050000
after ex_get_var(exoid, i + 1, EX_BLOB, var_idx+1, blobs[k].id, blobs[k].num_entry, vals), error = 0
0.040
1.040
2.040
3.040
4.040
5.040
6.040
7.040
8.040
9.040
10.040
11.040
12.040
13.040
14.040
after ex_get_var(exoid, i + 1, EX_BLOB, var_idx+1, blobs[k].id, blobs[k].num_entry, vals), error = 0
0.050
1.050
2.050
3.050
4.050
5.050
6.050
7.050
8.050
9.050
10.050
11.050
12.050
13.050
14.050
after ex_get_var(exoid, i + 1, EX_BLOB, var_idx+1, blobs[k].id, blobs[k].num_entry, vals), error = 0
0.060
1.060
2.060
3.060
4.060
5.060
6.060
7.060
8.060
9.060
10.060
11.060
12.060
13.060
14.060
after ex_get_time(exoid, i + 1, &time_value), error = 0
Time at step 2 is 0.020000.
after ex_get_reduction_vars(exoid, i + 1, EX_BLOB, blb[k].id, num_red_vars, var_values), error = 0
Values for Blob 100 at step 2: 0.040000	0.060000	0.080000	0.100000
after ex_get_var(exoid, i + 1, EX_BLOB, var_idx+1, blobs[k].id, blobs[k].num_entry, vals), error = 0
0.040
1.040
2.040
3.040
4.040
5.040
6.040
7.040
8.040
9.040
after ex_get_var(exoid, i + 1, EX_BLOB, var_idx+1, blobs[k].id, blobs[k].num_entry, vals), error = 0
0.060
1.060
2.060
3.060
4.060
5.060
6.060
7.060
8.060
9.060
after ex_get_var(exoid, i + 1, EX_BLOB, var_idx+1, blobs[k].id, blobs[k].num_entry, vals), error = 0
0.080
1.080
2.080
3.080
4.080
5.080
6.080
7.080
8.080
9.080
after ex_get_reduction_vars(exoid, i + 1, EX_BLOB, blb[k].id, num_red_vars, var_values), error = 0
Values for Blob 200 at step 2: 1.040000	1.060000	1.080000	1.100000
after ex_get_var(exoid, i + 1, EX_BLOB, var_idx+1, blobs[k].id, blobs[k].num_entry, vals), error = 0
0.050
1.050
2.050
3.050
4.050
5.050
6.050
7.050
8.050
9.050
10.050
11.050
12.050
13.050
14.050
15.050
16.050
17.050
18.050
19.050
after ex_get_var(exoid, i + 1, EX_BLOB, var_idx+1, blobs[k].id, blobs[k].num_entry, vals), error = 0
0.070
1.070
2.070
3.070
4.070
5.070
6.070
7.070
8.070
9.070
10.070
11.070
12.070
13.070
14.070
15.070
16.070
17.070
18.070
19.070
after ex_get_var(exoid, i + 1, EX_BLOB, var_idx+1, blobs[k].id, blobs[k].num_entry, vals), error = 0
0.090
1.090
2.090
3.090
4.090
5.090
6.090
7.090
8.090
9.090
10.090
11.090
12.090
13.090
14.090
15.090
16.090
17.090
18.090
19.090
after ex_get_reduction_vars(exoid, i + 1, EX_BLOB, blb[k].id, num_red_vars, var_values), error = 0
Values for Blob 300 at step 2: 2.040000	2.060000	2.080000	2.100000
after ex_get_var(exoid, i + 1, EX_BLOB, var_idx+1, blobs[k].id, blobs[k].num_entry, vals), error = 0
0.060
1.060
2.060
3.060
4.060
5.060
6.060
7.060
8.060
9.060
10.060
11.060
12.060
13.060
14.060
after ex_get_var(exoid, i + 1, EX_BLOB, var_idx+1, blobs[k].id, blobs[k].num_entry, vals), error = 0
0.080
1.080
2.080
3.080
4.080
5.080
6.080
7.080
8.080
9.080
10.080
11.080
12.080
13.080
14.080
after ex_get_var(exoid, i + 1, EX_BLOB, var_idx+1, blobs[k].id, blobs[k].num_entry, vals), error = 0
0.100
1.100
2.100
3.100
4.100
5.100
6.100
7.100
8.100
9.100
10.100
11.100
12.100
13.100
14.100
after ex_get_time(exoid, i + 1, &time_value), error = 0
Time at step 3 is 0.030000.
after ex_get_reduction_vars(exoid, i + 1, EX_BLOB, blb[k].id, num_red_vars, var_values), error = 0
Values for Blob 100 at step 3: 0.060000	0.090000	0.120000	0.150000
after ex_get_var(exoid, i + 1, EX_BLOB, var_idx+1, blobs[k].id, blobs[k].num_entry, vals), error = 0
0.060
1.060
2.060
3.060
4.060
5.060
6.060
7.060
8.060
9.060
after ex_get_var(exoid, i + 1, EX_BLOB, var_idx+1, blobs[k].id, blobs[k].num_entry, vals), error = 0
0.090
1.090
2.090
3.090
4.090
5.090
6.090
7.090
8.090
9.090
after ex_get_var(exoid, i + 1, EX_BLOB, var_idx+1, blobs[k].id, blobs[k].num_entry, vals), error = 0
0.120
1.120
2.120
3.120
4.120
5.120
6.120
7.120
8.120
9.120
after ex_get_reduction_vars(exoid, i + 1, EX_BLOB, blb[k].id, num_red_vars, var_values), error = 0
Values for Blob 200 at step 3: 1.060000	1.090000	1.120000	1.150000
after ex_get_var(exoid, i + 1, EX_BLOB, var_idx+1, blobs[k].id, blobs[k].num_entry, vals), error = 0
0.070
1.070
2.070
3.070
4.070
5.070
6.070
7.070
8.070
9.070
10.070
11.070
12.070
13.070
14.070
15.070
16.070
17.070
18.070
19.070
after ex_get_var(exoid, i + 1, EX_BLOB, var_idx+1, blobs[k].id, blobs[k].num_entry, vals), error = 0
0.100
1.100
2.100
3.100
4.100
5.100
6.100
7.100
8.100
9.100
10.100
11.100
12.100
13.100
14.100
15.100
16.100
17.100
18.100
19.100
after ex_get_var(exoid, i + 1, EX_BLOB, var_idx+1, blobs[k].id, blobs[k].num_entry, vals), error = 0
0.130
1.130
2.130
3.130
4.130
5.130
6.130
7.130
8.130
9.130
10.130
11.130
12.130
13.130
14.130
15.130
16.130
17.130
18.130
19.130
after ex_get_reduction_vars(exoid, i + 1, EX_BLOB, blb[k].id, num_red_vars, var_values), error = 0
Values for Blob 300 at step 3: 2.060000	2.090000	2.120000	2.150000
after ex_get_var(exoid, i + 1, EX_BLOB, var_idx+1, blobs[k].id, blobs[k].num_entry, vals), error = 0
0.080
1.080
2.080
3.080
4.080
5.080
6.080
7.080
8.080
9.080
10.080
11.080
12.080
13.080
14.080
after ex_get_var(exoid, i + 1, EX_BLOB, var_idx+1, blobs[k].id, blobs[k].num_entry, vals), error = 0
0.110
1.110
2.110
3.110
4.110
5.110
6.110
7.110
8.110
9.110
10.110
11.110
12.110
13.110
14.110
after ex_get_var(exoid, i + 1, EX_BLOB, var_idx+1, blobs[k].id, blobs[k].num_entry, vals), error = 0
0.140
1.140
2.140
3.140
4.140
5.140
6.140
7.140
8.140
9.140
10.140
11.140
12.140
13.140
14.140
after ex_get_time(exoid, i + 1, &time_value), error = 0
Time at step 4 is 0.040000.
after ex_get_reduction_vars(exoid, i + 1, EX_BLOB, blb[k].id, num_red_vars, var_values), error = 0
Values for Blob 100 at step 4: 0.080000	0.120000	0.160000	0.200000
after ex_get_var(exoid, i + 1, EX_BLOB, var_idx+1, blobs[k].id, blobs[k].num_entry, vals), error = 0
0.080
1.080
2.080
3.080
4.080
5.080
6.080
7.080
8.080
9.080
after ex_get_var(exoid, i + 1, EX_BLOB, var_idx+1, blobs[k].id, blobs[k].num_entry, vals), error = 0
0.120
1.120
2.120
3.120
4.120
5.120
6.120
7.120
8.120
9.120
after ex_get_var(exoid, i + 1, EX_BLOB, var_idx+1, blobs[k].id, blobs[k].num_entry, vals), error = 0
0.160
1.160
2.160
3.160
4.160
5.160
6.160
7.160
8.160
9.160
after ex_get_reduction_vars(exoid, i + 1, EX_BLOB, blb[k].id, num_red_vars, var_values), error = 0
Values for Blob 200 at step 4: 1.080000	1.120000	1.160000	1.200000
after ex_get_var(exoid, i + 1, EX_BLOB, var_idx+1, blobs[k].id, blobs[k].num_entry, vals), error = 0
0.090
1.090
2.090
3.090
4.090
5.090
6.090
7.090
8.090
9.090
10.090
11.090
12.090
13.090
14.090
15.090
16.090
17.090
18.090
19.090
after ex_get_var(exoid, i + 1, EX_BLOB, var_idx+1, blobs[k].id, blobs[k].num_entry, vals), error = 0
0.130
1.130
2.130
3.130
4.130
5.130
6.130
7.130
8.130
9.130
10.130
11.130
12.130
13.130
14.130
15.130
16.130
17.130
18.130
19.130
after ex_get_var(exoid, i + 1, EX_BLOB, var_idx+1, blobs[k].id, blobs[k].num_entry, vals), error = 0
0.170
1.170
2.170
3.170
4.170
5.170
6.170
7.170
8.170
9.170
10.170
11.170
12.170
13.170
14.170
15.170
16.170
17.170
18.170
19.170
after ex_get_reduction_vars(exoid, i + 1, EX_BLOB, blb[k].id, num_red_vars, var_values), error = 0
Values for Blob 300 at step 4: 2.080000	2.120000	2.160000	2.200000
after ex_get_var(exoid, i + 1, EX_BLOB, var_idx+1, blobs[k].id, blobs[k].num_entry, vals), error = 0
0.100
1.100
2.100
3.100
4.100
5.100
6.100
7.100
8.100
9.100
10.100
11.100
12.100
13.100
14.100
after ex_get_var(exoid, i + 1, EX_BLOB, var_idx+1, blobs[k].id, blobs[k].num_entry, vals), error = 0
0.140
1.140
2.140
3.140
4.140
5.140
6.140
7.140
8.140
9.140
10.140
11.140
12.140
13.140
14.140
after ex_get_var(exoid, i + 1, EX_BLOB, var_idx+1, blobs[k].id, blobs[k].num_entry, vals), error = 0
0.180
1.180
2.180
3.180
4.180
5.180
6.180
7.180
8.180
9.180
10.180
11.180
12.180
13.180
14.180
after ex_close(exoid), error = 0