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# BSD 3-Clause License; see https://github.com/scikit-hep/awkward/blob/main/LICENSE
from __future__ import annotations
import numpy as np # noqa: F401
import pytest
import awkward as ak
ROOT = pytest.importorskip("ROOT")
ROOT.ROOT.EnableImplicitMT(1)
compiler = ROOT.gInterpreter.Declare
def test_data_frame_integers():
ak_array_in = ak.Array([1, 2, 3, 4, 5])
data_frame = ak.to_rdataframe({"x": ak_array_in})
assert data_frame.GetColumnType("x") == "int64_t"
ak_array_out = ak.from_rdataframe(
data_frame,
columns=("x",),
)
assert ak_array_in.to_list() == ak_array_out["x"].to_list()
def test_data_frame_double():
ak_array_in = ak.Array([1.1, 2.2, 3.3, 4.4, 5.5])
data_frame = ak.to_rdataframe({"x": ak_array_in})
assert data_frame.GetColumnType("x") == "double"
ak_array_out = ak.from_rdataframe(
data_frame,
columns=("x",),
)
assert ak_array_in.to_list() == ak_array_out["x"].to_list()
def test_data_frame_char():
ak_array_in = ak.Array(["a", "b", "c", "d", "e"])
data_frame = ak.to_rdataframe({"x": ak_array_in})
assert data_frame.GetColumnType("x") == "std::string"
ak_array_out = ak.from_rdataframe(
data_frame,
columns=("x",),
)
assert ak_array_in.to_list() == ak_array_out["x"].to_list()
def test_data_frame_complex():
ak_array_in = ak.Array([1.1 + 0.1j, 2.2 + 0.2j, 3.3 + 0.3j, 4.4 + 0.4j, 5.5 + 0.5j])
data_frame = ak.to_rdataframe({"x": ak_array_in})
assert data_frame.GetColumnType("x") == "std::complex<double>"
ak_array_out = ak.from_rdataframe(
data_frame,
columns=("x",),
)
assert ak_array_in.to_list() == ak_array_out["x"].to_list()
def test_data_frame_listoffset_integers():
ak_array_in = ak.Array([[1], [2, 3, 4], [5]])
data_frame = ak.to_rdataframe({"x": ak_array_in})
assert data_frame.GetColumnType("x") == "ROOT::VecOps::RVec<int64_t>"
ak_array_out = ak.from_rdataframe(
data_frame,
columns=("x",),
)
assert ak_array_in.to_list() == ak_array_out["x"].to_list()
def test_data_frame_listoffset_listoffset_double():
ak_array_in = ak.Array(
[
[[1.1, 2.2, 3.3]],
[[4.4, 5.5]],
[[6.6], [7.7, 8.8, 9.9]],
]
)
data_frame = ak.to_rdataframe({"x": ak_array_in})
# awkward::ListArray_ type
# assert data_frame.GetColumnType("x") == "ROOT::VecOps::RVec<double>"
ak_array_out = ak.from_rdataframe(
data_frame,
columns=("x",),
)
assert ak_array_in.to_list() == ak_array_out["x"].to_list()
def test_data_frame_vec_of_vec():
array = ak.Array(
[
[
{"x": 1.1, "y": [1]},
{"x": None, "y": [1, 2]},
{"x": 3.3, "y": [1, 2, 3]},
],
[],
[{"x": None, "y": [1, 2, 3, 4]}, {"x": 5.5, "y": [1, 2, 3, 4, 5]}],
]
)
# ] * 10000)
rdf2 = ak.to_rdataframe({"array": array})
# We create a matrix RxC here
# Note when dimensions R and C are large, the following code suffers
# from potential performance penalties caused by frequent reallocation
# of memory by the push_back() function. This should be used only when
# vector dimensions are not known in advance.
rdf3 = rdf2.Define(
"output",
"""
std::vector<std::vector<double>> tmp1;
for (auto record : array) {
std::vector<double> tmp2;
for (auto number : record.y()) {
tmp2.push_back(number * number);
}
tmp1.push_back(tmp2);
}
return tmp1;
""",
)
assert rdf3.GetColumnType("output") == "vector<vector<double> >"
out = ak.from_rdataframe(
rdf3,
columns=("output",),
)
assert out["output"].to_list() == (array["y"] * array["y"] * 1.0).to_list()
rdf3 = rdf2.Define(
"output2",
"""
std::vector<std::vector<std::vector<double>>> tmp1;
for (auto record : array) {
std::vector<std::vector<double>> tmp2;
// we can check if it's None:
// if (record.x().has_value())
// or set it to 1 so that we do not scale:
double x_number = record.x().value_or(1);
for (auto number : record.y()) {
std::vector<double> tmp3;
for (int64_t i = 0; i < std::rint(x_number); i++) {
double value = x_number * number;
tmp3.push_back(value);
}
tmp2.push_back(tmp3);
}
tmp1.push_back(tmp2);
}
return tmp1;
""",
)
assert rdf3.GetColumnType("output2") == "vector<vector<vector<double> > >"
out = ak.from_rdataframe(
rdf3,
columns=("output2",),
)
result = ak.Array(
[
[
[[1.1]], # "x" is 1 - "y" values are unchanged, and each is nesed
[
[1.0],
[2.0],
], # "x" is None - "y" values are unchanged, and each is nesed
[
[3.3, 3.3, 3.3],
[6.6, 6.6, 6.6],
[9.899999999999999, 9.899999999999999, 9.899999999999999],
], # "x" is 3.3 - "y" values are scaled by 3.3 and each is nesed 3 times
],
[],
[
[
[1.0],
[2.0],
[3.0],
[4.0],
], # "x" is None - "y" values are unchanged, and each is nesed
[
[5.5, 5.5, 5.5, 5.5, 5.5, 5.5],
[11.0, 11.0, 11.0, 11.0, 11.0, 11.0],
[16.5, 16.5, 16.5, 16.5, 16.5, 16.5],
[22.0, 22.0, 22.0, 22.0, 22.0, 22.0],
[27.5, 27.5, 27.5, 27.5, 27.5, 27.5],
], # "x" is 5.5 - "y" values are scaled by 5.5 and each is nesed 5 times
],
]
)
assert out["output2"].to_list() == result.to_list()
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