Revert "Run tests in parallel"

CHANGELOG-unreleased.md

@@ -11,7 +11,6 @@ the released changes.
 ### Changed
 - Moved the events -> TOAs and photon weights code into the function `load_events_weights` within `event_optimize`.
 - Updated the `maxMJD` argument in `event_optimize` to default to the current mjd
-- Run CI tests in parallel, re-run failed tests (for intermittent failures due to random chance)
 - `maskParameter.__repr__()` output now includes the frozen attribute.
 - Changed default value of `FDJUMPLOG` to `Y`
 - Bumped `black` version to 24.x

requirements_dev.txt

@@ -12,8 +12,6 @@ wheel>=0.29.0
 pytest>=4.3
 pytest-cov>=2.7.1
 pytest-runner>=5.1
-pytest-xdist
-pytest-rerunfailures
 flake8>=3.7
 pep8-naming>=0.8.2
 flake8-docstrings>=1.4

tests/test_noisefit.py

@@ -6,38 +6,27 @@
 
 from io import StringIO
 import numpy as np
-import pytest
 
+par = """
+    ELAT    1.3     1
+    ELONG   2.5     1
+    F0      100     1
+    F1      1e-13   1
+    PEPOCH  55000
+    EPHEM   DE440
+    EFAC mjd 50000 53000 2      1
+    EQUAD mjd 53000 55000 0.8    1
+"""
 
-@pytest.fixture
-def model_and_toas_1():
-    par = """
-        ELAT    1.3     1
-        ELONG   2.5     1
-        F0      100     1
-        F1      1e-13   1
-        PEPOCH  55000
-        EPHEM   DE440
-        EFAC mjd 50000 53000 2      1
-        EQUAD mjd 53000 55000 0.8    1
-    """
+m = get_model(StringIO(par))
+t = make_fake_toas_uniform(50000, 55000, 200, m, add_noise=True)
 
-    m = get_model(StringIO(par))
-    t = make_fake_toas_uniform(50000, 55000, 200, m, add_noise=True)
+m2, t2 = get_model_and_toas(
+    datadir / "ecorr_fit_test.par", datadir / "ecorr_fit_test.tim"
+)
 
-    return m, t
-
-
-@pytest.fixture
-def model_and_toas_2():
-    return get_model_and_toas(
-        datadir / "ecorr_fit_test.par", datadir / "ecorr_fit_test.tim"
-    )
-
-
-def test_white_noise_fit(model_and_toas_1):
-    m, t = model_and_toas_1
 
+def test_white_noise_fit():
     assert m.EFAC1.uncertainty_value == 0 and m.EQUAD1.uncertainty_value == 0
 
     ftr = DownhillWLSFitter(t, m)
@@ -58,9 +47,7 @@ def test_white_noise_fit(model_and_toas_1):
     )
 
 
-def test_white_noise_refit(model_and_toas_1):
-    m, t = model_and_toas_1
-
+def test_white_noise_refit():
     ftr = DownhillWLSFitter(t, m)
 
     ftr.model.EFAC1.value = 1.5
@@ -80,9 +67,7 @@ def test_white_noise_refit(model_and_toas_1):
     )
 
 
-def test_ecorr_fit(model_and_toas_2):
-    m2, t2 = model_and_toas_2
-
+def test_ecorr_fit():
     ftr = DownhillGLSFitter(t2, m2)
     ftr.fit_toas()
 
@@ -94,9 +79,7 @@ def test_ecorr_fit(model_and_toas_2):
     )
 
 
-def test_ecorr_refit(model_and_toas_2):
-    m2, t2 = model_and_toas_2
-
+def test_ecorr_refit():
     ftr = DownhillGLSFitter(t2, m2)
 
     ftr.model.ECORR1.value = 0.75

tests/test_publish.py

@@ -5,37 +5,24 @@
 from pint.scripts import pintpublish
 import os
 
+data_NGC6440E = get_model_and_toas(datadir / "NGC6440E.par", datadir / "NGC6440E.tim")
 
-@pytest.fixture
-def data_NGC6440E():
-    return get_model_and_toas(datadir / "NGC6440E.par", datadir / "NGC6440E.tim")
 
-
-@pytest.fixture
-def data_J0613m0200_NANOGrav_9yv1():
-    return get_model_and_toas(
-        datadir / "J0613-0200_NANOGrav_9yv1.gls.par",
-        datadir / "J0613-0200_NANOGrav_9yv1.tim",
-    )
-
-
-@pytest.fixture
-def data_J1614m2230_NANOGrav_12yv3_wb():
-    return get_model_and_toas(
-        datadir / "J1614-2230_NANOGrav_12yv3.wb.gls.par",
-        datadir / "J1614-2230_NANOGrav_12yv3.wb.tim",
-    )
-
-
-def test_NGC6440E(data_NGC6440E):
+def test_NGC6440E():
     m, t = data_NGC6440E
     output = publish(m, t)
     assert "1748-2021E" in output
     assert "DE421" in output
 
 
+data_J0613m0200_NANOGrav_9yv1 = get_model_and_toas(
+    datadir / "J0613-0200_NANOGrav_9yv1.gls.par",
+    datadir / "J0613-0200_NANOGrav_9yv1.tim",
+)
+
+
 @pytest.mark.parametrize("full", [True, False])
-def test_J0613m0200_NANOGrav_9yv1(data_J0613m0200_NANOGrav_9yv1, full):
+def test_J0613m0200_NANOGrav_9yv1(full):
     m, t = data_J0613m0200_NANOGrav_9yv1
     output = publish(
         m, t, include_dmx=full, include_fd=full, include_noise=full, include_jumps=full
@@ -52,8 +39,14 @@ def test_J0613m0200_NANOGrav_9yv1(data_J0613m0200_NANOGrav_9yv1, full):
     assert not full or "RNAMP" in output
 
 
+data_J1614m2230_NANOGrav_12yv3_wb = get_model_and_toas(
+    datadir / "J1614-2230_NANOGrav_12yv3.wb.gls.par",
+    datadir / "J1614-2230_NANOGrav_12yv3.wb.tim",
+)
+
+
 @pytest.mark.parametrize("full", [True, False])
-def test_J1614m2230_NANOGrav_12yv3_wb(data_J1614m2230_NANOGrav_12yv3_wb, full):
+def test_J1614m2230_NANOGrav_12yv3_wb(full):
     m, t = data_J1614m2230_NANOGrav_12yv3_wb
     output = publish(
         m, t, include_dmx=full, include_fd=full, include_noise=full, include_jumps=full

tests/test_timing_model.py

@@ -42,6 +42,9 @@ def timfile_nojumps():
     return get_TOAs(os.path.join(datadir, "NGC6440E.tim"))
 
 
+len_timfile_nojumps = len(get_TOAs(os.path.join(datadir, "NGC6440E.tim")))
+
+
 class TestModelBuilding:
     def setup_method(self):
         self.parfile = os.path.join(datadir, "J0437-4715.par")

tests/test_toa_shuffle.py

@@ -18,22 +18,33 @@
 import pint.residuals
 from pint.models import get_model
 
+shuffletoas = """FORMAT 1
+test 1234.0 54321 0 pks
+test2 888 59055 0 meerkat
+test3 350 59000 0 gbt
+"""
+
 
 class TOAOrderSetup:
     parfile = os.path.join(datadir, "NGC6440E.par")
     model = get_model(parfile)
     # fake a multi-telescope, multi-frequency data-set and make sure the results don't depend on TOA order
-    t = (
+    fakes = [
         simulation.make_fake_toas_uniform(
             55000, 55500, 30, model=model, freq=1400 * u.MHz, obs="ao"
-        )
-        + simulation.make_fake_toas_uniform(
+        ),
+        simulation.make_fake_toas_uniform(
             55010, 55500, 40, model=model, freq=800 * u.MHz, obs="gbt"
-        )
-        + simulation.make_fake_toas_uniform(
+        ),
+        simulation.make_fake_toas_uniform(
             55020, 55500, 50, model=model, freq=2000 * u.MHz, obs="@"
-        )
-    )
+        ),
+    ]
+    f = io.StringIO()
+    for t in fakes:
+        t.write_TOA_file(f)
+    f.seek(0)
+    t = toa.get_TOAs(f)
     r = pint.residuals.Residuals(t, model, subtract_mean=False)
 
     @classmethod
@@ -84,11 +95,6 @@ def test_resorting_toas_chi2_match(sortkey):
 
 
 class TOALineOrderSetup:
-    shuffletoas = """FORMAT 1
-        test 1234.0 54321 0 pks
-        test2 888 59055 0 meerkat
-        test3 350 59000 0 gbt
-    """
     timfile = io.StringIO(shuffletoas)
     t = toa.get_TOAs(timfile)
     timfile.seek(0)

tox.ini

@@ -18,8 +18,7 @@ envlist =
 skip_missing_interpreters = True
 
 [tool:pytest]
-# pytest docs seem to say that this section should be called just pytest, 
-# not tool:pytest; is it working?
+# pytest docs seem to say that this section should be called just pytest, not tool:pytest; is it working?
 testpaths = tests
 addopts =
     --cov-report=term-missing
@@ -34,8 +33,6 @@ passenv =
 
 deps =
     pytest
-    pytest-xdist
-    pytest-rerunfailures
     cov: coverage
     cov: pytest-cov
     cov: pytest-remotedata
@@ -45,9 +42,8 @@ deps =
     setuptools
 commands =
     pip freeze
-    !cov: pytest --reruns 5 --verbose tests/test_toa_selection.py
-    !cov: pytest -n 6 --reruns 5 --verbose --ignore=tests/test_toa_selection.py
-    cov: pytest -n 6 --reruns 5 --verbose --pyargs tests --cov=pint --cov-config={toxinidir}/.coveragerc {posargs}
+    !cov: pytest 
+    cov: pytest -v --pyargs tests --cov=pint --cov-config={toxinidir}/.coveragerc {posargs}
     cov: coverage xml -o {toxinidir}/coverage.xml
 
 depends =
@@ -74,13 +70,9 @@ deps =
     matplotlib==3.2.0
     scipy==1.4.1
     pytest
-    pytest-xdist
-    pytest-rerunfailures
     coverage
     hypothesis<=6.72.0
-commands = 
-    pytest -n 6 --reruns 5 --verbose
-
+commands = {posargs:pytest}
 
 [testenv:report]
 skip_install = true