ai-content-maker/.venv/Lib/site-packages/pandas/tests/io/pytables/test_complex.py

204 lines
6.1 KiB
Python

from warnings import catch_warnings
import numpy as np
import pytest
import pandas as pd
from pandas import (
DataFrame,
Series,
)
import pandas._testing as tm
from pandas.tests.io.pytables.common import (
ensure_clean_path,
ensure_clean_store,
)
from pandas.io.pytables import read_hdf
def test_complex_fixed(setup_path):
df = DataFrame(
np.random.rand(4, 5).astype(np.complex64),
index=list("abcd"),
columns=list("ABCDE"),
)
with ensure_clean_path(setup_path) as path:
df.to_hdf(path, "df")
reread = read_hdf(path, "df")
tm.assert_frame_equal(df, reread)
df = DataFrame(
np.random.rand(4, 5).astype(np.complex128),
index=list("abcd"),
columns=list("ABCDE"),
)
with ensure_clean_path(setup_path) as path:
df.to_hdf(path, "df")
reread = read_hdf(path, "df")
tm.assert_frame_equal(df, reread)
def test_complex_table(setup_path):
df = DataFrame(
np.random.rand(4, 5).astype(np.complex64),
index=list("abcd"),
columns=list("ABCDE"),
)
with ensure_clean_path(setup_path) as path:
df.to_hdf(path, "df", format="table")
reread = read_hdf(path, "df")
tm.assert_frame_equal(df, reread)
df = DataFrame(
np.random.rand(4, 5).astype(np.complex128),
index=list("abcd"),
columns=list("ABCDE"),
)
with ensure_clean_path(setup_path) as path:
df.to_hdf(path, "df", format="table", mode="w")
reread = read_hdf(path, "df")
tm.assert_frame_equal(df, reread)
def test_complex_mixed_fixed(setup_path):
complex64 = np.array(
[1.0 + 1.0j, 1.0 + 1.0j, 1.0 + 1.0j, 1.0 + 1.0j], dtype=np.complex64
)
complex128 = np.array(
[1.0 + 1.0j, 1.0 + 1.0j, 1.0 + 1.0j, 1.0 + 1.0j], dtype=np.complex128
)
df = DataFrame(
{
"A": [1, 2, 3, 4],
"B": ["a", "b", "c", "d"],
"C": complex64,
"D": complex128,
"E": [1.0, 2.0, 3.0, 4.0],
},
index=list("abcd"),
)
with ensure_clean_path(setup_path) as path:
df.to_hdf(path, "df")
reread = read_hdf(path, "df")
tm.assert_frame_equal(df, reread)
def test_complex_mixed_table(setup_path):
complex64 = np.array(
[1.0 + 1.0j, 1.0 + 1.0j, 1.0 + 1.0j, 1.0 + 1.0j], dtype=np.complex64
)
complex128 = np.array(
[1.0 + 1.0j, 1.0 + 1.0j, 1.0 + 1.0j, 1.0 + 1.0j], dtype=np.complex128
)
df = DataFrame(
{
"A": [1, 2, 3, 4],
"B": ["a", "b", "c", "d"],
"C": complex64,
"D": complex128,
"E": [1.0, 2.0, 3.0, 4.0],
},
index=list("abcd"),
)
with ensure_clean_store(setup_path) as store:
store.append("df", df, data_columns=["A", "B"])
result = store.select("df", where="A>2")
tm.assert_frame_equal(df.loc[df.A > 2], result)
with ensure_clean_path(setup_path) as path:
df.to_hdf(path, "df", format="table")
reread = read_hdf(path, "df")
tm.assert_frame_equal(df, reread)
def test_complex_across_dimensions_fixed(setup_path):
with catch_warnings(record=True):
complex128 = np.array([1.0 + 1.0j, 1.0 + 1.0j, 1.0 + 1.0j, 1.0 + 1.0j])
s = Series(complex128, index=list("abcd"))
df = DataFrame({"A": s, "B": s})
objs = [s, df]
comps = [tm.assert_series_equal, tm.assert_frame_equal]
for obj, comp in zip(objs, comps):
with ensure_clean_path(setup_path) as path:
obj.to_hdf(path, "obj", format="fixed")
reread = read_hdf(path, "obj")
comp(obj, reread)
def test_complex_across_dimensions(setup_path):
complex128 = np.array([1.0 + 1.0j, 1.0 + 1.0j, 1.0 + 1.0j, 1.0 + 1.0j])
s = Series(complex128, index=list("abcd"))
df = DataFrame({"A": s, "B": s})
with catch_warnings(record=True):
objs = [df]
comps = [tm.assert_frame_equal]
for obj, comp in zip(objs, comps):
with ensure_clean_path(setup_path) as path:
obj.to_hdf(path, "obj", format="table")
reread = read_hdf(path, "obj")
comp(obj, reread)
def test_complex_indexing_error(setup_path):
complex128 = np.array(
[1.0 + 1.0j, 1.0 + 1.0j, 1.0 + 1.0j, 1.0 + 1.0j], dtype=np.complex128
)
df = DataFrame(
{"A": [1, 2, 3, 4], "B": ["a", "b", "c", "d"], "C": complex128},
index=list("abcd"),
)
msg = (
"Columns containing complex values can be stored "
"but cannot be indexed when using table format. "
"Either use fixed format, set index=False, "
"or do not include the columns containing complex "
"values to data_columns when initializing the table."
)
with ensure_clean_store(setup_path) as store:
with pytest.raises(TypeError, match=msg):
store.append("df", df, data_columns=["C"])
def test_complex_series_error(setup_path):
complex128 = np.array([1.0 + 1.0j, 1.0 + 1.0j, 1.0 + 1.0j, 1.0 + 1.0j])
s = Series(complex128, index=list("abcd"))
msg = (
"Columns containing complex values can be stored "
"but cannot be indexed when using table format. "
"Either use fixed format, set index=False, "
"or do not include the columns containing complex "
"values to data_columns when initializing the table."
)
with ensure_clean_path(setup_path) as path:
with pytest.raises(TypeError, match=msg):
s.to_hdf(path, "obj", format="t")
with ensure_clean_path(setup_path) as path:
s.to_hdf(path, "obj", format="t", index=False)
reread = read_hdf(path, "obj")
tm.assert_series_equal(s, reread)
def test_complex_append(setup_path):
df = DataFrame(
{"a": np.random.randn(100).astype(np.complex128), "b": np.random.randn(100)}
)
with ensure_clean_store(setup_path) as store:
store.append("df", df, data_columns=["b"])
store.append("df", df)
result = store.select("df")
tm.assert_frame_equal(pd.concat([df, df], axis=0), result)