-
Notifications
You must be signed in to change notification settings - Fork 0
/
Copy pathgenerate_eval.py
107 lines (101 loc) · 3.79 KB
/
generate_eval.py
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
from micron.prepare_evaluation import set_up_environment
import os
""" COSEM BLOCK 1
"""
solve_dir = "/nrs/funke/ecksteinn/micron_experiments/cosem_hela_2_block_1/04_solve"
base_dir = "/nrs/funke/ecksteinn/micron_experiments"
experiment = "cosem_hela_2_block_1"
train_number = 0
predict_number = 10
graph_number = 0
tracing_file = "/nrs/funke/ecksteinn/micron_experiments/cosem/00_data/tracings/block_1.nml"
tracing_offset = [9996, 396, 21996]
tracing_size = [2000, 2000, 2000]
""" COSEM BLOCK 2
"""
solve_dir = "/nrs/funke/ecksteinn/micron_experiments/cosem_hela_2_block_2/04_solve"
base_dir = "/nrs/funke/ecksteinn/micron_experiments"
experiment = "cosem_hela_2_block_2"
train_number = 0
predict_number = 10
graph_number = 0
tracing_file = "/nrs/funke/ecksteinn/micron_experiments/cosem/00_data/tracings/block_2.nml"
tracing_offset = [2196, 1196, 27996]
tracing_size = [2000, 2000, 2000]
""" COSEM BLOCK 3
"""
solve_dir = "/nrs/funke/ecksteinn/micron_experiments/cosem_hela_2_block_3/04_solve"
base_dir = "/nrs/funke/ecksteinn/micron_experiments"
experiment = "cosem_hela_2_block_3"
train_number = 0
predict_number = 10
graph_number = 0
tracing_file = "/nrs/funke/ecksteinn/micron_experiments/cosem/00_data/tracings/block_3.nml"
tracing_offset = [15596, 596, 22796]
tracing_size = [2000, 2000, 2000]
""" COSEM BLOCK 4
"""
solve_dir = "/nrs/funke/ecksteinn/micron_experiments/cosem_hela_2_block_4/04_solve"
base_dir = "/nrs/funke/ecksteinn/micron_experiments"
experiment = "cosem_hela_2_block_4"
train_number = 0
predict_number = 10
graph_number = 0
tracing_file = "/nrs/funke/ecksteinn/micron_experiments/cosem/00_data/tracings/block_4.nml"
tracing_offset = [10796, 496, 36996]
tracing_size = [2000, 2000, 2000]
min_solve_number = 5000
"""COSEM BLOCK 5
"""
solve_dir = "/nrs/funke/ecksteinn/micron_experiments/cosem_hela_2_block_5/04_solve"
base_dir = "/nrs/funke/ecksteinn/micron_experiments"
experiment = "cosem_hela_2_block_5"
train_number = 0
predict_number = 10
graph_number = 0
tracing_file = "/nrs/funke/ecksteinn/micron_experiments/cosem/00_data/tracings/block_5.nml"
tracing_offset = [11196, 2196, 18796]
tracing_size = [2000, 2000, 2000]
min_solve_number = 0
subsample_factor = 10
max_edges = 5
distance_threshold = 120
optimality_gap = 0.0
time_limit = 300
voxel_size = [4, 4, 4]
mount_dirs = "/nrs, /scratch, /groups, /misc"
singularity = "None"
num_cpus = 1
num_block_workers = 1
num_cache_workers = 1
queue = "normal"
solve_dir = os.path.join(os.path.join(base_dir, experiment), "04_solve")
solve_setups = [os.path.join(solve_dir, f) for f in os.listdir(solve_dir) if "setup_t{}_p{}_g{}_s".format(train_number,
predict_number,
graph_number) in f]
solve_numbers = [int(f.split("_")[-1][1:]) for f in solve_setups]
solve_numbers = [n for n in solve_numbers if n >= min_solve_number]
eval_number = 0
for solve_number in solve_numbers:
set_up_environment(base_dir,
experiment,
train_number,
predict_number,
graph_number,
solve_number,
eval_number,
tracing_file,
tracing_offset,
tracing_size,
subsample_factor,
max_edges,
distance_threshold,
optimality_gap,
time_limit,
voxel_size,
mount_dirs,
singularity,
queue,
num_cpus,
num_block_workers,
num_cache_workers)