def test_with_fields(tmp_path):
one_list = [[{"x": 1}, {"x": 2}, {"x": 3}], [], [{"x": 4}, {"x": 5}]]
two_list = [[{"x": 6}], [{"x": 7}, {"x": 8}, {"x": 9}, {"x": 10}]]
one = ak.Array(one_list)
two = ak.Array(two_list)
ak.to_parquet(one, tmp_path / "file1.parquet")
ak.to_parquet(two, tmp_path / "file2.parquet")
assert not os.path.exists(tmp_path / "_common_metadata")
assert not os.path.exists(tmp_path / "_metadata")
no_metadata = ak.from_parquet(tmp_path)
assert no_metadata.tolist() == one_list + two_list
no_metadata_lazy = ak.from_parquet(tmp_path, lazy=True)
assert no_metadata_lazy.tolist() == one_list + two_list
ak.to_parquet.dataset(tmp_path)
assert os.path.exists(tmp_path / "_common_metadata")
assert os.path.exists(tmp_path / "_metadata")
with_metadata = ak.from_parquet(tmp_path)
assert with_metadata.tolist() == one_list + two_list
with_metadata_lazy = ak.from_parquet(tmp_path, lazy=True)
assert with_metadata_lazy.tolist() == one_list + two_list
def test_no_fields(tmp_path):
one = ak.Array([[1, 2, 3], [], [4, 5]])
two = ak.Array([[6], [7, 8, 9, 10]])
ak.to_parquet(one, tmp_path / "file1.parquet")
ak.to_parquet(two, tmp_path / "file2.parquet")
assert not os.path.exists(tmp_path / "_common_metadata")
assert not os.path.exists(tmp_path / "_metadata")
no_metadata = ak.from_parquet(tmp_path)
assert no_metadata.tolist() == [[1, 2, 3], [], [4, 5], [6], [7, 8, 9, 10]]
no_metadata_lazy = ak.from_parquet(tmp_path, lazy=True)
assert no_metadata_lazy.tolist() == [[1, 2, 3], [], [4, 5], [6],
[7, 8, 9, 10]]
ak.to_parquet.dataset(tmp_path)
assert os.path.exists(tmp_path / "_common_metadata")
assert os.path.exists(tmp_path / "_metadata")
with_metadata = ak.from_parquet(tmp_path)
assert with_metadata.tolist() == [[1, 2, 3], [], [4, 5], [6],
[7, 8, 9, 10]]
with_metadata_lazy = ak.from_parquet(tmp_path, lazy=True)
assert with_metadata_lazy.tolist() == [[1, 2, 3], [], [4, 5], [6],
[7, 8, 9, 10]]
def test_6(one, two, three, tmp_path):
filename = os.path.join(str(tmp_path), "test6.parquet")
data = [
{"x": {"y": [], "z": 1.1}},
{"x": {"y": [one], "z": 2.2}},
{"x": {"y": [one, two, three], "z": 3.3}},
]
ak.to_parquet(ak.Array(data), filename)
array = ak.from_parquet(filename, lazy=True, lazy_cache_key="tmp")
assert set(array.caches[0].keys()) == set()
array.layout.field("x").array
assert set(array.caches[0].keys()) == set()
array.layout.field("x").array.field("z").array
assert set(array.caches[0].keys()) == {"tmp:col:x.z[0]"}
array.layout.field("x").array.field("y").array
assert set(array.caches[0].keys()) == {"tmp:col:x.z[0]", "tmp:lst:x.y[0]"}
assert array.tolist() == data
array = ak.from_parquet(filename, lazy=True, lazy_cache_key="tmp")
assert set(array.caches[0].keys()) == set()
array.layout.field("x").array
assert set(array.caches[0].keys()) == set()
array.layout.field("x").array.field("y").array
assert set(array.caches[0].keys()) == {"tmp:lst:x.y[0]"}
array.layout.field("x").array.field("z").array
assert set(array.caches[0].keys()) == {"tmp:lst:x.y[0]", "tmp:col:x.z[0]"}
assert array.tolist() == data
def test_8(one, two, three, tmp_path):
filename = os.path.join(str(tmp_path), "test8.parquet")
data = [
{
"x": []
},
{
"x": [{
"y": one,
"z": 1.1
}]
},
{
"x": [{
"y": one,
"z": 1.1
}, {
"y": two,
"z": 2.2
}, {
"y": three,
"z": 3.3
}]
},
]
ak.to_parquet(ak.Array(data), filename)
array = ak.from_parquet(filename, lazy=True, lazy_cache_key="tmp")
assert set(array.caches[0].keys()) == set()
array.layout.field("x").array
assert set(array.caches[0].keys()) == set(["tmp:off:x.list.item.y:x[0]"])
assert np.asarray(
array.layout.field("x").array.offsets).tolist() == [0, 0, 1, 4]
assert set(array.caches[0].keys()) == set(["tmp:off:x.list.item.y:x[0]"])
array.layout.field("x").array.content.field("y").array
assert set(array.caches[0].keys()) == set(
["tmp:off:x.list.item.y:x[0]", "tmp:col:x.list.item.y[0]"])
array.layout.field("x").array.content.field("z").array
assert set(array.caches[0].keys()) == set([
"tmp:off:x.list.item.y:x[0]",
"tmp:col:x.list.item.y[0]",
"tmp:col:x.list.item.z[0]",
])
assert array.tolist() == data
array = ak.from_parquet(filename, lazy=True, lazy_cache_key="tmp")
assert set(array.caches[0].keys()) == set()
array.layout.field("x").array
assert set(array.caches[0].keys()) == set(["tmp:off:x.list.item.y:x[0]"])
assert np.asarray(
array.layout.field("x").array.offsets).tolist() == [0, 0, 1, 4]
assert set(array.caches[0].keys()) == set(["tmp:off:x.list.item.y:x[0]"])
array.layout.field("x").array.content.field("z").array
assert set(array.caches[0].keys()) == set(
["tmp:off:x.list.item.y:x[0]", "tmp:col:x.list.item.z[0]"])
array.layout.field("x").array.content.field("y").array
assert set(array.caches[0].keys()) == set([
"tmp:off:x.list.item.y:x[0]",
"tmp:col:x.list.item.z[0]",
"tmp:col:x.list.item.y[0]",
])
assert array.tolist() == data
def test_issue2(tmp_path):
filename = os.path.join(tmp_path, "whatever.parquet")
null_table = pyarrow.Table.from_pydict({"null_col": pyarrow.array([None])})
pyarrow_parquet.write_table(null_table, filename)
assert ak.from_parquet(filename).type == ak.from_parquet(filename, lazy=True).type
def test_to_parquet_2(tmp_path):
array = ak.Array([
[{
"x": 0.0,
"y": []
}, {
"x": 1.1,
"y": [1]
}, {
"x": 2.2,
"y": None
}],
[],
[{
"x": 3.3,
"y": [1, 2, 3]
}, None, {
"x": 4.4,
"y": [1, 2, 3, 4]
}],
])
assert str(
array.type) == '3 * var * ?{"x": float64, "y": option[var * int64]}'
ak.to_parquet(array, os.path.join(tmp_path, "complicated-example.parquet"))
array2 = ak.from_parquet(
os.path.join(tmp_path, "complicated-example.parquet"))
assert str(array2.type) == str(array.type)
assert array2.tolist() == array.tolist()
def test_parquet2b(tmp_path):
filename = os.path.join(tmp_path, "whatever.parquet")
array = ak.Array(
[
{"x": [{"y": 0.0, "z": 0}]},
{"x": [{"y": 1.1, "z": 1}]},
{"x": [{"y": 2.2, "z": 2}]},
]
)
ak.to_parquet(array, filename)
lazy = ak.from_parquet(filename, lazy=True, lazy_cache=None)
@numba.njit
def f1(lazy):
out = np.ones(3, np.float64)
i = 0
for obj in lazy:
for subobj in obj.x:
out[i] = subobj.y
i += 1
return out
@numba.njit
def f2(lazy):
out = np.ones(3, np.float64)
i = 0
for obj in lazy:
for subobj in obj.x:
out[i] = subobj.z
i += 1
return out
assert f1(lazy).tolist() == [0.0, 1.1, 2.2]
assert f2(lazy).tolist() == [0, 1, 2]
def test(tmp_path):
filename = os.path.join(tmp_path, "what-ever.parquet")
fish = ak.Array([True, True])[np.newaxis]
clob = ak.Array([2, 3, 7])[np.newaxis]
frog = ak.zip({"c": clob, "f": fish}, depth_limit=1)
ak.to_parquet(frog, filename)
assert ak.from_parquet(filename).tolist() == frog.tolist()
def test_12(one, two, three, tmp_path):
filename = os.path.join(str(tmp_path), "test12.parquet")
data = [
{
"x": {
"y": []
}
},
{
"x": {
"y": [[one]]
}
},
{
"x": {
"y": [[one, two], [], [three]]
}
},
]
ak.to_parquet(ak.Array(data), filename)
array = ak.from_parquet(filename, lazy=True, lazy_cache_key="tmp")
assert set(array.caches[0].keys()) == set()
array.layout.field("x").array
assert set(array.caches[0].keys()) == set()
array.layout.field("x").array.field("y").array
assert set(array.caches[0].keys()) == set(["tmp:lst:x.y[0]"])
assert array.tolist() == data
def test_parsing(header_version: int, events_per_chunk: int) -> None:
here = Path(__file__).parent
input_filename = here / "parsing" / f"final_state_hadrons_header_v{header_version}.dat"
for i, arrays in enumerate(
parse_ascii.read(filename=input_filename,
events_per_chunk=events_per_chunk,
parser="pandas")):
# Get the reference array
# Create the reference arrays by checking out the parser v1 (e477e0277fa560f9aba82310c02da8177e61c9e4), setting
# the chunk size in skim_ascii, and then calling:
# $ python jetscape_analysis/analysis/reader/skim_ascii.py -i tests/parsing/final_state_hadrons_header_v1.dat -o tests/parsing/events_per_chunk_50/parser_v1_header_v1/test.parquet
# NOTE: The final state hadron files won't exist when you check out that branch, so
# it's best to copy them for your existing branch.
reference_arrays = ak.from_parquet(
Path(
f"{here}/parsing/events_per_chunk_{events_per_chunk}/parser_v1_header_v1/test_{i:02}.parquet"
))
# There are more fields in v2 than in the reference arrays (v1), so only take those
# that are present in reference for comparison.
# NOTE: We have to compare the fields one-by-one because the shapes of the fields
# are different, and apparently don't broadcast nicely with `__eq__`
for field in ak.fields(reference_arrays):
new_field = _rename_columns.get(field, field)
assert ak.all(reference_arrays[field] == arrays[new_field])
# Check for cross section if header v2
if header_version == 2:
assert "cross_section" in ak.fields(arrays)
assert "cross_section_error" in ak.fields(arrays)
def test():
array = ak.Array([1, 2, 3])
file_ = io.BytesIO()
ak.to_parquet(array, file_)
file_.seek(0)
array_from_file = ak.from_parquet(file_)
assert ak.to_list(array) == ak.to_list(array_from_file)
def test_16(one, two, three, tmp_path):
filename = os.path.join(str(tmp_path), "test15.parquet")
data = [[one, two], [], [three]]
ak.to_parquet(ak.Array(data), filename)
array = ak.from_parquet(filename, lazy=True, lazy_cache_key="tmp")
assert set(array.caches[0].keys()) == set()
assert np.asarray(array.layout.array.offsets).tolist() == [0, 2, 2, 3]
assert set(array.caches[0].keys()) == set(["tmp:lst:[0]"])
assert array.tolist() == data
def load(cls, path, *args, **kwargs):
path = get_path(path)
if path.endswith(".parquet"):
import awkward as ak
return ak.from_parquet(path, *args, **kwargs)
# .pickle, .pkl
return PickleFormatter.load(path, *args, **kwargs)
def test_1(one, two, three, tmp_path):
filename = os.path.join(str(tmp_path), "test1.parquet")
data = [{"x": one}, {"x": two}, {"x": three}]
ak.to_parquet(ak.Array(data), filename)
array = ak.from_parquet(filename, lazy=True, lazy_cache_key="tmp")
assert set(array.caches[0].keys()) == set()
array.layout.field("x").array
assert set(array.caches[0].keys()) == set(["tmp:col:x[0]"])
assert array.tolist() == data
def test_4(one, two, three, tmp_path):
filename = os.path.join(str(tmp_path), "test4.parquet")
data = [{"x": []}, {"x": [one]}, {"x": [one, two, three]}]
ak.to_parquet(ak.Array(data), filename)
array = ak.from_parquet(filename, lazy=True, lazy_cache_key="tmp")
assert set(array.caches[0].keys()) == set()
array.layout.field("x").array
assert set(array.caches[0].keys()) == {"tmp:lst:x[0]"}
assert array.tolist() == data
def test_15(one, two, three, tmp_path):
filename = os.path.join(str(tmp_path), "test15.parquet")
data = [one, two, three]
ak.to_parquet(ak.Array(data), filename)
array = ak.from_parquet(filename, lazy=True, lazy_cache_key="tmp")
assert set(array.caches[0].keys()) == set()
array.layout.array
assert set(array.caches[0].keys()) == set(["tmp:col:[0]"])
assert array.tolist() == data
def test(tmp_path):
filename = os.path.join(tmp_path, "test.parquet")
dog = ak.from_iter([1, 2, 5])
cat = ak.from_iter([4])
pets = ak.zip({
"dog": dog[np.newaxis],
"cat": cat[np.newaxis]
},
depth_limit=1)
ak.to_parquet(pets, filename)
assert ak.from_parquet(filename).tolist() == pets.tolist()
def test_17(one, two, three, tmp_path):
filename = os.path.join(str(tmp_path), "test15.parquet")
data = [[{"x": one}, {"x": two}], [], [{"x": three}]]
ak.to_parquet(ak.Array(data), filename)
array = ak.from_parquet(filename, lazy=True, lazy_cache_key="tmp")
assert set(array.caches[0].keys()) == set()
assert np.asarray(array.layout.array.offsets).tolist() == [0, 2, 2, 3]
assert set(array.caches[0].keys()) == set(["tmp:off:.list.item.x:[0]"])
array.layout.array.content.field("x").array
assert set(array.caches[0].keys()) == set(
["tmp:off:.list.item.x:[0]", "tmp:col:.list.item.x[0]"])
assert array.tolist() == data
def test_pandas(tmp_path):
df = pandas.DataFrame(
{"x": np.arange(10), "y": np.arange(10) % 5, "z": ["low"] * 5 + ["high"] * 5}
)
df.to_parquet(tmp_path, partition_cols=["z", "y"])
a = ak.from_parquet(tmp_path)
assert a.z.tolist() == ["high"] * 5 + ["low"] * 5 # alphabetical
assert a.y.tolist() == ["0", "1", "2", "3", "4", "0", "1", "2", "3", "4"]
assert a.x.tolist() == [5, 6, 7, 8, 9, 0, 1, 2, 3, 4]
b = ak.from_parquet(tmp_path, lazy=True)
assert b.z.tolist() == ["high"] * 5 + ["low"] * 5
assert b.y.tolist() == ["0", "1", "2", "3", "4", "0", "1", "2", "3", "4"]
assert b.x.tolist() == [5, 6, 7, 8, 9, 0, 1, 2, 3, 4]
c = ak.from_parquet(tmp_path, include_partition_columns=False)
assert ak.fields(c) == ["x"]
d = ak.from_parquet(tmp_path, lazy=True, include_partition_columns=False)
assert ak.fields(d) == ["x"]
def test_11(one, two, three, tmp_path):
filename = os.path.join(str(tmp_path), "test11.parquet")
data = [
{"x": []},
{"x": [{"z": 1.1, "y": {"q": one}}]},
{
"x": [
{"z": 1.1, "y": {"q": one}},
{"z": 2.2, "y": {"q": two}},
{"z": 3.3, "y": {"q": three}},
]
},
]
ak.to_parquet(ak.Array(data), filename)
array = ak.from_parquet(filename, lazy=True, lazy_cache_key="tmp")
assert set(array.caches[0].keys()) == set()
array.layout.field("x").array
assert len(set(array.caches[0].keys())) == 1
assert np.asarray(array.layout.field("x").array.offsets).tolist() == [0, 0, 1, 4]
assert len(set(array.caches[0].keys())) == 1
array.layout.field("x").array.content.field("y").array
assert len(set(array.caches[0].keys())) == 1
array.layout.field("x").array.content.field("y").array.field("q").array
assert len(set(array.caches[0].keys())) == 2
array.layout.field("x").array.content.field("z").array
assert len(set(array.caches[0].keys())) == 3
assert array.tolist() == data
array = ak.from_parquet(filename, lazy=True, lazy_cache_key="tmp")
assert set(array.caches[0].keys()) == set()
array.layout.field("x").array
assert len(set(array.caches[0].keys())) == 1
assert np.asarray(array.layout.field("x").array.offsets).tolist() == [0, 0, 1, 4]
assert len(set(array.caches[0].keys())) == 1
array.layout.field("x").array.content.field("y").array
assert len(set(array.caches[0].keys())) == 1
array.layout.field("x").array.content.field("z").array
assert len(set(array.caches[0].keys())) == 2
array.layout.field("x").array.content.field("y").array.field("q").array
assert len(set(array.caches[0].keys())) == 3
assert array.tolist() == data
def test(tmp_path):
filename = os.path.join(tmp_path, "test.parquet")
ak.to_parquet(ak.repartition(range(8), 2), filename)
assert ak.from_parquet(filename, row_groups=[1,
3]).tolist() == [2, 3, 6, 7]
assert ak.from_parquet(filename, row_groups=[1, 3],
lazy=True).tolist() == [
2,
3,
6,
7,
]
assert ak.from_parquet(tmp_path, row_groups=[1,
3]).tolist() == [2, 3, 6, 7]
assert ak.from_parquet(tmp_path, row_groups=[1, 3],
lazy=True).tolist() == [
2,
3,
6,
7,
]
ak.to_parquet.dataset(tmp_path)
assert ak.from_parquet(tmp_path, row_groups=[1,
3]).tolist() == [2, 3, 6, 7]
assert ak.from_parquet(tmp_path, row_groups=[1, 3],
lazy=True).tolist() == [
2,
3,
6,
7,
]
def test_parsing_with_parquet(header_version: int, events_per_chunk: int,
tmp_path: Path) -> None:
"""Parse to parquet, read back, and compare."""
here = Path(__file__).parent
input_filename = here / "parsing" / f"final_state_hadrons_header_v{header_version}.dat"
# Convert to chunks in a temp directory.
base_output_filename = tmp_path / "test.parquet"
parse_ascii.parse_to_parquet(base_output_filename=base_output_filename,
store_only_necessary_columns=True,
input_filename=input_filename,
events_per_chunk=events_per_chunk)
output_filenames = tmp_path.glob("*.parquet")
for i, output_filename in enumerate(sorted(output_filenames)):
arrays = ak.from_parquet(output_filename)
# Create the reference arrays by checking out the parser v1 (e477e0277fa560f9aba82310c02da8177e61c9e4), setting
# the chunk size in skim_ascii, and then calling:
# $ python jetscape_analysis/analysis/reader/skim_ascii.py -i tests/parsing/final_state_hadrons_header_v1.dat -o tests/parsing/events_per_chunk_50/parser_v1_header_v1/test.parquet
# NOTE: The final state hadron files won't exist when you check out that branch, so
# it's best to copy them for your existing branch.
reference_arrays = ak.from_parquet(
Path(
f"{here}/parsing/events_per_chunk_{events_per_chunk}/parser_v1_header_v1/test_{i:02}.parquet"
))
# There are more fields in v2 than in the reference arrays (v1), so only take those
# that are present in reference for comparison.
# NOTE: We have to compare the fields one-by-one because the shapes of the fields
# are different, and apparently don't broadcast nicely with `__eq__`
for field in ak.fields(reference_arrays):
new_field = _rename_columns.get(field, field)
assert ak.all(reference_arrays[field] == arrays[new_field])
# Check for cross section if header v2
if header_version == 2:
assert "cross_section" in ak.fields(arrays)
assert "cross_section_error" in ak.fields(arrays)
def test(tmp_path):
one = ak.Array([[], [{"x": [{"y": 1}]}]])
two = ak.Array([[{"x": []}, {"x": [{"y": 1}]}]])
three = ak.Array([[{"x": [{"y": 1}]}], [], [{"x": [{"y": 2}]}]])
ak.to_parquet(one, tmp_path / "one.parquet")
ak.to_parquet(two, tmp_path / "two.parquet")
ak.to_parquet(three, tmp_path / "three.parquet")
lazy_one = ak.from_parquet(tmp_path / "one.parquet", lazy=True)
lazy_two = ak.from_parquet(tmp_path / "two.parquet", lazy=True)
lazy_three = ak.from_parquet(tmp_path / "three.parquet", lazy=True)
assert lazy_one.tolist() == [[], [{"x": [{"y": 1}]}]]
assert lazy_two.tolist() == [[{"x": []}, {"x": [{"y": 1}]}]]
assert lazy_three.tolist() == [[{
"x": [{
"y": 1
}]
}], [], [{
"x": [{
"y": 2
}]
}]]
def test_parquet1(tmp_path):
filename = os.path.join(tmp_path, "whatever.parquet")
array = ak.Array([{"x": {"y": 0.0}}, {"x": {"y": 1.1}}, {"x": {"y": 2.2}}])
ak.to_parquet(array, filename)
lazy = ak.from_parquet(filename, lazy=True, lazy_cache=None)
@numba.njit
def f1(lazy):
out = np.ones(3, np.float64)
i = 0
for obj in lazy:
out[i] = obj.x.y
i += 1
return out
assert f1(lazy).tolist() == [0.0, 1.1, 2.2]
def test_9(one, two, three, tmp_path):
filename = os.path.join(str(tmp_path), "test9.parquet")
data = [
{"x": []},
{"x": [{"y": {"q": one}}]},
{"x": [{"y": {"q": one}}, {"y": {"q": two}}, {"y": {"q": three}}]},
]
ak.to_parquet(ak.Array(data), filename)
array = ak.from_parquet(filename, lazy=True, lazy_cache_key="tmp")
assert set(array.caches[0].keys()) == set()
array.layout.field("x").array
assert set(array.caches[0].keys()) == {"tmp:off:x.list.item.y.q:x[0]"}
assert np.asarray(array.layout.field("x").array.offsets).tolist() == [0, 0, 1, 4]
assert set(array.caches[0].keys()) == {"tmp:off:x.list.item.y.q:x[0]"}
array.layout.field("x").array.content.field("y").array
assert set(array.caches[0].keys()) == {"tmp:off:x.list.item.y.q:x[0]"}
array.layout.field("x").array.content.field("y").array.field("q").array
assert set(array.caches[0].keys()) == {
"tmp:off:x.list.item.y.q:x[0]",
"tmp:col:x.list.item.y.q[0]",
}
assert array.tolist() == data
def test_to_parquet(tmp_path):
original = ak.Array([
[{
"x": 1,
"y": 1.1
}, {
"x": 2,
"y": 2.2
}, {
"x": 3,
"y": 3.3
}],
[],
[{
"x": 4,
"y": 4.4
}, {
"x": 5,
"y": 5.5
}],
[],
[],
[
{
"x": 6,
"y": 6.6
},
{
"x": 7,
"y": 7.7
},
{
"x": 8,
"y": 8.8
},
{
"x": 9,
"y": 9.9
},
],
])
ak.to_parquet(original, os.path.join(tmp_path, "data.parquet"))
reconstituted = ak.from_parquet(os.path.join(tmp_path, "data.parquet"))
assert reconstituted.tolist() == [
[{
"x": 1,
"y": 1.1
}, {
"x": 2,
"y": 2.2
}, {
"x": 3,
"y": 3.3
}],
[],
[{
"x": 4,
"y": 4.4
}, {
"x": 5,
"y": 5.5
}],
[],
[],
[
{
"x": 6,
"y": 6.6
},
{
"x": 7,
"y": 7.7
},
{
"x": 8,
"y": 8.8
},
{
"x": 9,
"y": 9.9
},
],
]
assert str(reconstituted.type) == '6 * var * {"x": int64, "y": float64}'
def test_parquet():
empty = ak.from_parquet("tests/samples/zero-record-batches.parquet")
assert isinstance(empty, ak.Array)
assert len(empty) == 0
assert str(empty.type) == "0 * {}"
import time
import subprocess
import awkward as ak
compress = sys.argv[1]
N = int(sys.argv[2])
is_split = sys.argv[3] == "split"
s = "-split" if is_split else ""
filename = f"/home/jpivarski/storage/data/chep-2021-jagged-jagged-jagged/{compress}{s}-jagged{N}.parquet"
subprocess.call(f"vmtouch -t {filename} > /dev/null", shell=True)
subprocess.call(f"vmtouch {filename} | fgrep Pages", shell=True)
array = ak.from_parquet(filename, lazy=True)
begintime = time.time()
for partition in array.layout.partitions:
tmp = partition.array
endtime = time.time()
print(f"pyarrow {compress}{s}-jagged{N}", endtime - begintime, "seconds")
array = ak.from_parquet(filename, lazy=True)
begintime = time.time()
for partition in array.layout.partitions:
tmp = partition.array
def load_df():
return ak.from_parquet(good_uproot_file_path) # type: ignore
ew = Components.EventWise.from_file("../megaIgnore/IRCchecks_noPTcut1/iridis_pp_to_jjj_lo1_fragment/iridis_pp_to_jjj_lo1_fragment0.parquet")
spectral_jets = list({name.split('_')[0] for name in ew.columns if name.startswith("Spect") and "IRC" not in name})
# files that contian kinematic info
file_name = "../megaIgnore/IRCchecks_noPTcut{}/iridis_pp_to_jjj_{}{}_fragment/kinematics.parquet"
end_time = time.time() + 60*60*36
ew_shapes = Components.EventWise.from_file("../megaIgnore/IRC_shapes2.parquet")
for n in range(1, 5):
spectral_shapes = [[[[] for _ in spectral_jets] for _ in ew_shapes.shape_names] for _ in ew_shapes.orders]
for order in ["nlo", "lo"]:
o_idx = list(ew_shapes.orders).index(order)
name = file_name.format(n, order)
kinematics = ak.from_parquet(name)
print(name)
print("Getting jet shapes")
for j_idx, jname in enumerate(spectral_jets):
print('.', end='', flush=True)
ew.selected_event = None
for event_n in range(len(kinematics[o_idx, 0, 0])):
ew.selected_event = event_n
event_kinematics = ak.to_numpy(kinematics[o_idx, 1:, j_idx, event_n, :])
if np.any(np.isnan(event_kinematics)) or len(event_kinematics) != 4:
shapes = [np.nan for _ in ew_shapes.shape_names]
else:
shape_dict = ShapeVariables.shape(*event_kinematics)[1]
shapes = [shape_dict[name] for name in ew_shapes.shape_names]
for i, val in enumerate(shapes):
