141 lines
2.9 KiB
Python
141 lines
2.9 KiB
Python
import collections
|
|
import sys
|
|
|
|
import ssgetpy
|
|
|
|
import lists
|
|
|
|
Dataset = collections.namedtuple("Dataset", ["name", "mats"])
|
|
|
|
def safe_dir_name(s):
|
|
t = s.strip()
|
|
t = t.replace(" ", "_")
|
|
t = t.replace("/", "_")
|
|
t = t.replace("-", "_")
|
|
t = t.lower()
|
|
return t
|
|
|
|
def filter_reject_blacklist(mats):
|
|
filtered = []
|
|
for mat in mats:
|
|
if mat.name in lists.INTEGER_MATS:
|
|
print(f"BLACKLIST {mat.name}")
|
|
continue
|
|
filtered += [mat]
|
|
return filtered
|
|
|
|
def filter_reject_large(mats):
|
|
filtered = []
|
|
for mat in mats:
|
|
if mat.rows > 1_000_000 or mat.cols > 1_000_000 or mat.nnz > 20_000_000:
|
|
continue
|
|
filtered += [mat]
|
|
return filtered
|
|
|
|
def filter_reject_small(mats):
|
|
filtered = []
|
|
for mat in mats:
|
|
if mat.rows < 1_000 or mat.cols < 1_000 or mat.nnz < 20_000:
|
|
continue
|
|
filtered += [mat]
|
|
return filtered
|
|
|
|
## all real-valued matrices
|
|
REAL_MATS = Dataset(
|
|
name = "reals",
|
|
mats = filter_reject_blacklist(ssgetpy.search(
|
|
dtype='real',
|
|
limit=1_000_000
|
|
))
|
|
)
|
|
|
|
## certain matrices with regular structure
|
|
kinds = [
|
|
"2D/3D",
|
|
"Acoustics Problem",
|
|
"Materials Problem",
|
|
"Structural Problem",
|
|
"Computational Fluid Dynamics Problem",
|
|
"Model Reduction Problem",
|
|
"Semiconductor Device Problem",
|
|
"Theoretical/Quantum Chemistry Problem",
|
|
"Thermal Problem",
|
|
]
|
|
REGULAR_REAL_MATS = Dataset(
|
|
name = "regular_reals",
|
|
mats = []
|
|
)
|
|
mats = []
|
|
for kind in kinds:
|
|
mats += ssgetpy.search(
|
|
kind=kind,
|
|
dtype='real',
|
|
limit=1_000_000
|
|
)
|
|
REGULAR_REAL_MATS = Dataset(
|
|
name="regular_reals",
|
|
mats = filter_reject_blacklist(mats)
|
|
)
|
|
|
|
## keep "small" matrices
|
|
REGULAR_REAL_SMALL_MATS = Dataset (
|
|
name = "regular_reals_small",
|
|
mats = filter_reject_large(REGULAR_REAL_MATS.mats)
|
|
)
|
|
REAL_SMALL_MATS = Dataset (
|
|
name = "reals_small",
|
|
mats = filter_reject_large(REAL_MATS.mats)
|
|
)
|
|
|
|
## keep "medium" matrices
|
|
REGULAR_REAL_MED_MATS = Dataset (
|
|
name = "regular_reals_med",
|
|
mats = filter_reject_large(filter_reject_small(REGULAR_REAL_MATS.mats))
|
|
)
|
|
REAL_MED_MATS = Dataset (
|
|
name = "reals_med",
|
|
mats = filter_reject_large(filter_reject_small(REAL_MATS.mats))
|
|
)
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
## export all datasets
|
|
DATASETS = [
|
|
REAL_MATS,
|
|
REAL_SMALL_MATS,
|
|
REAL_MED_MATS,
|
|
REGULAR_REAL_MATS,
|
|
REGULAR_REAL_SMALL_MATS,
|
|
REGULAR_REAL_MED_MATS
|
|
]
|
|
|
|
def get_kinds():
|
|
"""return set of unique kind fields"""
|
|
|
|
mats = ssgetpy.search(
|
|
limit=1_000_000
|
|
)
|
|
|
|
kinds = set()
|
|
for mat in mats:
|
|
kinds.add(mat.kind)
|
|
print(f"kinds: {kinds}")
|
|
|
|
return kinds
|
|
|
|
for kind in get_kinds():
|
|
d = Dataset(
|
|
name = "kind_"+safe_dir_name(kind),
|
|
mats = filter_reject_blacklist(ssgetpy.search(
|
|
kind=kind,
|
|
dtype='real',
|
|
limit=1_000_000
|
|
))
|
|
)
|
|
if len(d.mats) > 0:
|
|
DATASETS += [d]
|