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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
import pytest
import awkward as ak
import awkward._connect.cling
import awkward._lookup
ROOT = pytest.importorskip("ROOT")
ROOT.ROOT.EnableImplicitMT(1)
compiler = ROOT.gInterpreter.Declare
def test_to_from_data_frame_large():
# Note, with n = 30 (14348907) this test takes ~40 sec to run on my laptop
n = 6
assert 2 * (n // 2) == n
rows = 3 ** (n // 2)
cols = n
arr = np.zeros((rows, cols), dtype=np.int64)
shape = (rows,)
source = np.array([-1, 0, 1], dtype=np.int64)[:, None]
for col in range(n // 2):
shape = (
-1,
3,
shape[-1] // 3,
)
col_view = arr[:, col]
col_view.shape = shape
col_view[:] = source
ak_array_in = ak.from_numpy(arr, regulararray=True)
data_frame = ak.to_rdataframe({"x": ak_array_in})
ak_array_out = ak.from_rdataframe(
data_frame,
columns=("x",),
)
assert len(ak_array_in) == len(ak_array_out)
def test_data_frame_boolean():
ak_array_in = ak.Array([True, False, True, True, True])
data_frame = ak.to_rdataframe({"x": ak_array_in})
assert data_frame.GetColumnType("x") == "bool"
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_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_real():
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_complex():
ak_array_in = ak.Array([1.0 + 0.1j, 2.0 + 0.2j, 3.0 + 0.3j, 4.0 + 0.4j, 5.0 + 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_strings():
ak_array_in = ak.Array(["one", "two", "three"])
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_vec_of_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_vec_of_real():
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") == "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_complex():
ak_array_in = ak.Array(
[[1.0 + 0.1j, 2.0 + 0.2j], [3.0 + 0.3j], [4.0 + 0.4j, 5.0 + 0.5j]]
)
data_frame = ak.to_rdataframe({"x": ak_array_in})
assert data_frame.GetColumnType("x") == "ROOT::VecOps::RVec<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_vec_of_strings():
ak_array_in = ak.Array([["one"], ["two", "three"]])
data_frame = ak.to_rdataframe({"x": ak_array_in})
assert data_frame.GetColumnType("x").startswith("awkward::ListArray_")
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_of_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").startswith("awkward::ListArray_")
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_of_real():
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").startswith("awkward::ListArray_")
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_of_complex():
ak_array_in = ak.Array(
[[[1.0 + 0.1j], [2.0 + 0.2j]], [[3.0 + 0.3j], [4.0 + 0.4j, 5.0 + 0.5j]]]
)
data_frame = ak.to_rdataframe({"x": ak_array_in})
assert data_frame.GetColumnType("x").startswith("awkward::ListArray_")
ak_array_out = ak.from_rdataframe(
data_frame,
columns=("x",),
)
assert ak_array_in.to_list() == ak_array_out["x"].to_list()
def test_rdata_frame_vecs_as_records():
data_frame = ROOT.RDataFrame(10).Define("x", "gRandom->Rndm()")
data_frame_xy = data_frame.Define("y", "x*2")
ak_array_x = ak.from_rdataframe(
data_frame_xy,
columns=("x",),
)
assert ak_array_x["x"].layout.form == ak.forms.NumpyForm("float64")
ak_record_array_x = ak.from_rdataframe(
data_frame_xy,
columns=("x",),
)
assert ak_record_array_x.layout.form == ak.forms.RecordForm(
[ak.forms.NumpyForm("float64")], "x"
)
ak_record_array_y = ak.from_rdataframe(
data_frame_xy,
columns=("y",),
)
ak_array = ak.zip([ak_record_array_x, ak_record_array_y])
assert ak_array.layout.form == ak.forms.RecordForm(
contents=[
ak.forms.RecordForm([ak.forms.NumpyForm("float64")], "x"),
ak.forms.RecordForm([ak.forms.NumpyForm("float64")], "y"),
],
fields=None,
)
def test_rdata_frame_vecs_of_complex():
data_frame = ROOT.RDataFrame(10).Define("x", "gRandom->Rndm()")
data_frame_xy = data_frame.Define("y", "x*2 +1i")
ak_array_y = ak.from_rdataframe(
data_frame_xy,
columns=("y",),
)
assert ak_array_y["y"].layout.form == ak.forms.NumpyForm("complex128")
def test_rdata_frame_rvecs_as_records():
data_frame = ROOT.RDataFrame(1024)
coordDefineCode = """ROOT::VecOps::RVec<double> {0}(len);
std::transform({0}.begin(), {0}.end(), {0}.begin(), [](double){{return gRandom->Uniform(-1.0, 1.0);}});
return {0};"""
data_frame_x_y = (
data_frame.Define("len", "gRandom->Uniform(0, 16)")
.Define("x", coordDefineCode.format("x"))
.Define("y", coordDefineCode.format("y"))
)
# Now we have in hands d, a RDataFrame with two columns, x and y, which
# hold collections of coordinates. The size of these collections vary.
# Let's now define radii out of x and y. We'll do it treating the collections
# stored in the columns without looping on the individual elements.
data_frame_x_y_r = data_frame_x_y.Define("r", "sqrt(x*x + y*y)")
assert data_frame_x_y_r.GetColumnType("r") == "ROOT::VecOps::RVec<double>"
array = ak.from_rdataframe(
data_frame_x_y_r,
columns=("r",),
offsets_type="int32",
)
assert array.layout.form == ak.forms.RecordForm(
[ak.forms.ListOffsetForm("i32", ak.forms.NumpyForm("float64"))], ["r"]
)
def test_to_from_data_frame():
ak_array_in = ak.Array([[1.1], [2.2, 3.3, 4.4], [5.5, 6.6]])
assert ak_array_in.layout.content.is_contiguous is True
data_frame = ak.to_rdataframe({"x": ak_array_in})
assert data_frame.GetColumnType("x") == "ROOT::VecOps::RVec<double>"
ak_array_out = ak.from_rdataframe(
data_frame,
columns=("x",),
)
assert ak_array_out["x"].layout.content.is_contiguous is True
assert ak_array_in.to_list() == ak_array_out["x"].to_list()
def test_to_from_data_frame_rvec_of_rvec():
ak_array_in = ak.Array([[[1.1]], [[2.2, 3.3], [4.4]], [[5.5, 6.6], []]])
data_frame = ak.to_rdataframe({"x": ak_array_in})
assert data_frame.GetColumnType("x").startswith("awkward::ListArray_")
ak_array_out = ak.from_rdataframe(
data_frame,
columns=("x",),
)
assert ak_array_in.to_list() == ak_array_out["x"].to_list()
def test_to_from_data_frame_rvec_of_rvec_of_rvec():
ak_array_in = ak.Array(
[[[[1.1]]], [[[2.2], [3.3], [], [4.4]]], [[[], [5.5, 6.6], []]]]
)
data_frame = ak.to_rdataframe({"x": ak_array_in})
ak_array_out = ak.from_rdataframe(
data_frame,
columns=("x",),
)
assert ak_array_in.to_list() == ak_array_out["x"].to_list()
def test_to_from_data_frame_columns_as_string():
ak_array_in = ak.Array(
[[[[1.1]]], [[[2.2], [3.3], [], [4.4]]], [[[], [5.5, 6.6], []]]]
)
data_frame = ak.to_rdataframe({"x": ak_array_in})
ak_array_out = ak.from_rdataframe(
data_frame,
columns="x",
)
assert ak_array_in.to_list() == ak_array_out.to_list()
|
