def test_plot_filter_dataframe_for_plotting_gpu_and_cpu_fail(
capsys, cli_runner, tmpdir, data
):
""" Tests the error when gpu and cpu are set to false.
"""
with tmpdir.as_cwd():
input_df = pd.read_csv(data["testcsv.csv"])
expected_output = "ERROR CPU and GPU not set. Nothing to plot. Exiting.\n"
with pytest.raises(SystemExit) as error:
plot.filter_dataframe_for_plotting(
df=input_df, host_name=(), module_name=(), gpu=False, cpu=False
)
out, _ = capsys.readouterr()
assert out == expected_output
assert error.type == SystemExit
assert error.value.code == 1
def test_plot_filter_empty_dataframe_error(cli_runner, capsys, tmpdir, data):
"""Assert that we exit when given an empty DataFrame through a specific filter combination.
"""
with tmpdir.as_cwd():
df = pd.read_csv(data["testcsv.csv"])
df = df[(~df["gpu"]) & (df["host"] == "draco")]
with pytest.raises(SystemExit) as error:
plot.filter_dataframe_for_plotting(
df=df, host_name=("draco",), module_name=(), gpu=True, cpu=False
)
expected_output = (
"Plotting GPU data only.\n"
"ERROR Your filtering led to an empty dataset. Exiting.\n"
)
out, _ = capsys.readouterr()
assert out == expected_output
assert error.type == SystemExit
assert error.value.code == 1
def test_plot_filter_dataframe_for_plotting_host_name(
cli_runner, tmpdir, data, host_name
):
""" Checks whether the host names are filtered correctly in the filtering function.
"""
with tmpdir.as_cwd():
expected_df = pd.read_csv(data["testcsv.csv"])
expected_df = expected_df[expected_df["host"].str.contains(host_name)]
input_df = pd.read_csv(data["testcsv.csv"])
real_df = plot.filter_dataframe_for_plotting(
df=input_df, host_name=(host_name,), module_name=(), gpu=True, cpu=True
)
assert_frame_equal(expected_df, real_df)
def test_plot_filter_dataframe_for_plotting_gpu_and_cpu(
cli_runner, tmpdir, data, gpu, cpu
):
""" Checks whether the cpu and gpu filtering works properly.
"""
with tmpdir.as_cwd():
input_df = pd.read_csv(data["testcsv.csv"])
if gpu and not cpu:
input_df = input_df[input_df.gpu]
elif not gpu and cpu:
input_df = input_df[~input_df.gpu]
elif not gpu and not cpu:
input_df = pd.read_csv(data["empty_df.csv"])
real_df = plot.filter_dataframe_for_plotting(
df=input_df, host_name=(), module_name=(), gpu=gpu, cpu=cpu
)
# here we compare the dataframes for any differences
assert_frame_equal(input_df, real_df)