def test_row_type_filter_2():
filtered = results.read_result_files(RESULT_FILES, "run =~ *General-0* AND module =~ Test.node1 AND name =~ foo1*")
df = results.get_results(filtered, row_types=["scalar", "attr"])
_assert_sequential_index(df)
# 2 times 3 rows for scalars (incl. value), and 3 times 2 rows for the vector, stats, and histogram (only attr)
# since we only filtered for row types, not result types, we get the attrs for the other kinds of results too, just not the results themselves
return df.shape == (12, 7)
def test_vectors_start_end_time_at_load():
trimmed = results.read_result_files(RESULT_FILES,
vector_start_time=40,
vector_end_time=60)
df = results.get_vectors(trimmed)
_assert_sequential_index(df)
_assert(sanitize_and_compare_csv(df, "vectors_start_end_time.csv"),
"content mismatch")
def test_vector_time_limit_at_load_2():
filtered = results.read_result_files(
RESULT_FILES,
"type =~ vector AND run =~ General-0*",
vector_end_time=50.0)
df = results.get_results(filtered, row_types=["vector"])
_assert_sequential_index(df)
return df["vectime"].map(lambda a: (a < 50.0).all()).all()
def test_vectors_end_time():
trimmed = results.read_result_files(RESULT_FILES)
df = results.get_vectors(trimmed, end_time=80)
_assert_sequential_index(df)
_assert(sanitize_and_compare_csv(df, "vectors_end_time.csv"),
"content mismatch")
def test_vector_data():
filtered = results.read_result_files(
RESULT_FILES, "type =~ vector AND run =~ General-0*")
df = results.get_results(filtered, row_types=["vector"])
_assert_sequential_index(df)
return df["vectime"].map(lambda a: a.shape == (100, )).all()
def test_row_type_filter_3():
filtered = results.read_result_files(RESULT_FILES, "type =~ param")
df = results.get_results(filtered, row_types=["attr"])
_assert_sequential_index(df)
# params don't have attrs
return df.empty
def test_result_filter():
filtered = results.read_result_files(RESULT_FILES, "type =~ scalar")
df = results.get_results(filtered)
_assert_sequential_index(df)
# in all 6 runs: 20 lines of metadata, and 4 lines (1 scalar and 3 attrs) for all 8 scalars
return df.shape == (312, 7)
"""
This is all the tests extracted from results_api_test, adapted to the
standalone result loading/processing API.
"""
from omnetpp.scave import results
import pandas as pd
import tester
tester.print = print
from tester import _assert, _assert_sequential_index, run_tests, sanitize_and_compare_csv
RESULT_FILES = ["results/General-*.vec", "results/General-*.sca"]
r = results.read_result_files(RESULT_FILES)
def test_runs():
df = results.get_runs(r)
_assert_sequential_index(df)
_assert(sanitize_and_compare_csv(df, "runs.csv"), "content mismatch")
def test_runs_with_itervars():
df = results.get_runs(r, include_itervars=True)
_assert_sequential_index(df)
_assert(sanitize_and_compare_csv(df, "runs_with_itervars.csv"),
"content mismatch")
def test_runs_with_runattrs():
df = results.get_runs(r, include_runattrs=True)
