140 lines
3.2 KiB
Python
140 lines
3.2 KiB
Python
import collections
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import sys
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import ssgetpy
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from lib import dtypes
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Dataset = collections.namedtuple("Dataset", ["name", "mats"])
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def safe_dir_name(s):
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t = s.strip()
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t = t.replace(" ", "_")
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t = t.replace("/", "_")
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t = t.replace("-", "_")
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t = t.lower()
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return t
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def mat_is_real(mat):
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val = dtypes.DTYPES[(mat.group, mat.name)] == "real"
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return val
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def filter_keep_real(mats):
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return [mat for mat in mats if mat_is_real(mat)]
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def mat_is_small(mat):
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return (mat.rows < 1_000 and mat.cols < 1_000) \
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or mat.nnz < 20_000
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def mat_is_large(mat):
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return (mat.rows > 1_000_000 and mat.cols > 1_000_000) \
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or mat.nnz > 20_000_000
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def filter_reject_large(mats):
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return [mat for mat in mats if not mat_is_large(mat)]
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def filter_reject_small(mats):
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return [mat for mat in mats if not mat_is_small(mat)]
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def filter_keep_square(mats):
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return [mat for mat in mats if mat.rows == mat.cols]
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## all real-valued matrices
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REAL_MATS = Dataset(
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name = "reals",
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mats = filter_keep_real(ssgetpy.search(
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dtype='real',
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limit=1_000_000
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))
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)
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## certain matrices with regular structure
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kinds = [
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"2D/3D",
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"Acoustics Problem",
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"Materials Problem",
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"Structural Problem",
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"Computational Fluid Dynamics Problem",
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"Model Reduction Problem",
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"Semiconductor Device Problem",
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"Theoretical/Quantum Chemistry Problem",
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"Thermal Problem",
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]
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mats = []
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for kind in kinds:
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mats += ssgetpy.search(
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kind=kind,
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dtype='real',
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limit=1_000_000
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)
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REGULAR_REAL_MATS = Dataset(
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name="regular_reals",
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mats = filter_keep_real(mats)
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)
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## keep "small" matrices
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REGULAR_REAL_SMALL_MATS = Dataset (
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name = "regular_reals_small",
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mats = filter_reject_large(REGULAR_REAL_MATS.mats)
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)
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REAL_SMALL_MATS = Dataset (
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name = "reals_small",
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mats = filter_reject_large(REAL_MATS.mats)
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)
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REGULAR_SQUARE_REAL_SMALL_MATS = Dataset (
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name = "regular_square_reals_small",
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mats = filter_keep_square(REGULAR_REAL_SMALL_MATS.mats)
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)
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SQUARE_REAL_SMALL_MATS = Dataset (
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name = "square_reals_small",
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mats = filter_keep_square(REAL_SMALL_MATS.mats)
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)
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## keep "medium" matrices
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REGULAR_REAL_MED_MATS = Dataset (
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name = "regular_reals_med",
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mats = filter_reject_large(filter_reject_small(REGULAR_REAL_MATS.mats))
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)
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REAL_MED_MATS = Dataset (
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name = "reals_med",
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mats = filter_reject_large(filter_reject_small(REAL_MATS.mats))
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)
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## export all datasets
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DATASETS = [
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# REAL_MATS,
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REAL_SMALL_MATS,
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REAL_MED_MATS,
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# REGULAR_REAL_MATS,
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REGULAR_REAL_SMALL_MATS,
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REGULAR_REAL_MED_MATS,
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REGULAR_SQUARE_REAL_SMALL_MATS,
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SQUARE_REAL_SMALL_MATS,
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]
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def get_kinds():
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"""return set of unique kind fields"""
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mats = ssgetpy.search(
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limit=1_000_000
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)
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kinds = set()
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for mat in mats:
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kinds.add(mat.kind)
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return kinds
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for kind in get_kinds():
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d = Dataset(
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name = "kind_"+safe_dir_name(kind),
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mats = filter_reject_large( \
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filter_reject_small( \
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filter_keep_real(ssgetpy.search(
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kind=kind,
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dtype='real',
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limit=1_000_000
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))))
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)
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if len(d.mats) > 0:
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DATASETS += [d]
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