def it_warns_on_no_seq_from_uniprot():
csv_string = """
UniprotAC
P1
"""
with zest.mock(helpers._protein_csv_warning) as m_warn:
with zest.mock(helpers._uniprot_lookup) as m_lookup:
m_lookup.returns([])
helpers.protein_csv_df(csv_string)
assert m_warn.called_once()
def it_uses_inputs_args_if_specified():
with zest.mock(PipelineTask._config_dirty, returns=None) as m_config_dirty:
with zest.mock(
PipelineTask._out_of_date, returns=(True, "because, reasons")
) as m_out_of_date:
pt = _pt(Munch(inputs=Munch(a="../a")))
inputs = [src_dir / "a", src_dir / "b"]
pt.is_dirty(inputs)
assert m_out_of_date.n_calls == 1
calls = m_out_of_date.normalized_calls()[0]
assert calls["parents"] == inputs
assert calls["children"] == dst_dir
def it_copies():
with zest.mock(sim_v1_worker._rand3,
returns=np.full((n_samples, 2, 3), 1.0)):
sim_v1_worker._step_2_initialize_samples_including_dark_sampling(
flu, p_bright, n_samples=n_samples)
assert flu[0][
0] == 1 # Check that the original flu was not modified.
def it_allows_zeros_as_first_value_in_unnormalized_abundance_data():
with zest.mock(log.info) as m_log:
unnormalized_abundance_data_with_zeros = PrepParams(proteins=[
_fake_protein(0),
_fake_protein(5),
_fake_protein(10)
])
def it_uses_batch_size():
with zest.mock(zap._cpu_count) as m:
sl = zap._make_batch_slices(_batch_size=2,
n_rows=6,
_limit_slice=None)
assert sl == [(0, 2), (2, 4), (4, 6)]
assert not m.called()
def it_exceptions_serially():
with zest.mock(pretend_unit_under_test.foo) as m_foo:
m_foo.exceptions_serially([ValueError, TypeError])
with zest.raises(ValueError):
pretend_unit_under_test.foo()
with zest.raises(TypeError):
pretend_unit_under_test.foo()
def it_raises_on_duplicate_sequences():
with zest.mock(_error) as m_error:
with zest.raises(ValueError):
pro_spec_df = pd.DataFrame(
dict(name=["name1", "name2"], sequence=["ABC", "ABC"]))
_step_1_check_for_uniqueness(pro_spec_df)
assert m_error.called()
def scope_mocks():
with zest.mock(pretend_unit_under_test.foo) as m_foo:
pretend_unit_under_test.foo()
# Had the real foo been called it would have
# raised NotImplementedError
assert m_foo.called_once()
def it_warns_and_normalized_unnormalized_abundance_data():
with zest.mock(log.info) as m_log:
unnormalized_abundance_data = PrepParams(
proteins=[_fake_protein(10),
_fake_protein(5)])
assert m_log.called_once()
assert unnormalized_abundance_data.proteins[0].abundance == 2
def it_converts_to_power_of_2():
with zest.mock(worker._convert_message):
nd2 = _make_nd2(63)
m_nd2.returns(nd2)
result = worker.ims_import(src_path, ims_import_params)
assert result.field_chcy_ims(0).shape == (n_channels, n_cycles,
64, 64)
def it_reruns_on_a_previous_failure():
with zest.mock(Task1.get_output_state,
returns=PipelineState.error) as m_get_output_state:
_set_dirty(True, False, False)
_p()
assert m_task1_start.called_once()
assert not m_task2_start.called()
assert not m_task3_start.called()
def it_warns_on_more_than_one_seq_from_uniprot():
csv_string = """
UniprotAC
P1
"""
with zest.mock(helpers._protein_csv_warning) as m_warn:
with zest.mock(helpers._uniprot_lookup) as m_lookup:
m_lookup.returns([{
"id": "foo",
"seqstr": "123"
}, {
"id": "bar",
"seqstr": "123456"
}])
df = helpers.protein_csv_df(csv_string)
assert len(df) == 1 and df.loc[0, "seqstr"] == "123456"
assert m_warn.called_once()
def it_traps_exceptions_in_tasks():
with zest.mock(Task1.error) as m_error:
_set_dirty(True, False, False)
e = Exception("problem")
m_task1_start.exceptions(e)
_p()
assert m_error.called_once_with_kws(e=e)
m_task1_start.exceptions(None)
def it_does_run_on_upstream_change_even_if_previous_success():
with zest.mock(Task1.get_output_state,
returns=PipelineState.success) as m_get_output_state:
_set_dirty(True, True, True)
Pipeline(src_dir, dst_dir, tasks)
assert m_task1_start.called_once()
assert m_task2_start.called_once()
assert m_task3_start.called_once()
def it_does_not_darken():
# Similarly a low number will keep everything lit
with zest.mock(sim_v1_worker._rand3,
returns=np.full((n_samples, 2, 3), 0.1)):
flu_samples = sim_v1_worker._step_2_initialize_samples_including_dark_sampling(
flu, p_bright, n_samples=n_samples)
assert flu_samples.shape == (n_samples, 2, 3)
assert np.all(flu_samples[:, 1, 1] == 1.0)
assert np.all(flu_samples[:, 0, 0] == 1.0)
def it_normalizes_calls_into_kwargs():
# normalized_call() is a handy when you want to just know
# what was passed to the mock but you don't care if
# it was passed as args or kwargs.
with zest.mock(pretend_unit_under_test.foo) as m_foo:
pretend_unit_under_test.foo("arg1", arg2="arg2")
kwargs = m_foo.normalized_call()
assert kwargs == dict(arg1="arg1", arg2="arg2")
def it_bubbles_exceptions():
with zest.mock(zap._show_work_order_exception) as m_ex:
with zest.raises(ValueError):
work_orders[0].fn = test2
zap.work_orders(
work_orders,
_process_mode=True,
_trap_exceptions=False,
)
assert m_ex.called_once()
def it_nans_missing_abundances():
csv_string = """
UniprotAC
P1
"""
with zest.mock(helpers._uniprot_lookup) as m:
m.returns([{"id:": "foo", "seqstr": "ABC"}])
df = helpers.protein_csv_df(csv_string)
assert (df.loc[0, "id"] == "P1" and df.loc[0, "seqstr"] == "ABC"
and np.isnan(df.loc[0, "abundance"]))
def it_darkens():
# Large random numbers mean it will go dark so a 0.9 will
# darken the 0.5 but not the 1.0
with zest.mock(sim_v1_worker._rand3,
returns=np.full((n_samples, 2, 3), 0.9)):
flu_samples = sim_v1_worker._step_2_initialize_samples_including_dark_sampling(
flu, p_bright, n_samples=n_samples)
assert flu_samples.shape == (n_samples, 2, 3)
assert np.all(flu_samples[:, 1, 1] == 1.0)
assert np.all(flu_samples[:, 0, 0] == 0.0)
def it_hooks():
with zest.mock(pretend_unit_under_test.foo) as m_foo:
got_callback = False
def _callback():
nonlocal got_callback
got_callback = True
m_foo.hook(_callback)
pretend_unit_under_test.foo()
assert got_callback is True
def it_converts_to_power_of_2():
with zest.mock(worker._convert_message):
m_nd2.hook_to_call = lambda _: _make_nd2(
63, "cycle", n_fields)
result = worker.ims_import(src_path, ims_import_params)
assert result.field_chcy_ims(0).shape == (
n_channels,
n_fields,
64,
64,
)
def it_retries():
progress = MockFunction()
with zest.mock(zap._mock_BrokenProcessPool_exception) as m:
m.exceptions(BrokenProcessPool)
results = zap.work_orders(work_orders,
_process_mode=True,
_progress=progress)
assert progress.calls == [
((1, 2, True), {}),
((2, 2, True), {}),
]
def it_can_degrade_one_sample_and_not_another():
samples = npf([
[[n, 1, 0], [n, 1, 0]],
[[0, 1, 1], [0, 0, 1]],
])
n_samples = 2
with zest.mock(sim_v1_worker._rand1,
returns=np.full((n_samples, ), [0.0, 1.0])):
result = sim_v1_worker._step_3a_cycle_edman(samples,
is_mock=False,
p_edman_failure=0.5)
expected = npf([
[[n, 1, 0], [n, 1, 0]],
[[n, 1, 1], [n, 0, 1]],
])
assert np_array_same(expected, result)
def it_lookups_uniprot():
csv_string = """
UniprotAC, Abundance
P1, 10
"""
with zest.mock(helpers._uniprot_lookup) as m:
m.returns([{"id:": "foo", "seqstr": "ABC"}])
df = helpers.protein_csv_df(csv_string)
assert df.loc[0, "seqstr"] == "ABC"
def it_uses_uniprot_ac_as_name():
assert df.loc[0, "id"] == "P1"
def it_imports_abundance():
assert df.loc[0, "abundance"] == 10.0
zest()
def it_solves_for_batch_size_by_scaling_the_cpu_count():
with zest.mock(zap._cpu_count, returns=2):
sl = zap._make_batch_slices(_batch_size=None,
n_rows=32,
_limit_slice=None)
assert sl == [
(0, 3),
(3, 6),
(6, 9),
(9, 12),
(12, 15),
(15, 18),
(18, 21),
(21, 24),
(24, 27),
(27, 30),
(30, 32),
]
def it_returns_dirty_check_config():
with zest.mock(PipelineTask._config_dirty, returns="config dirty"):
pt = _pt(Munch(inputs=Munch(a="../a")))
assert pt.is_dirty() is True
assert pt.dirty_reason == "config dirty"
def it_prints_array_shape_if_not_specified():
with zest.mock(check._print) as p:
check.array_t(arr)
assert "(3,)" in p.normalized_call()["msg"]
def it_checks_against_normalized_call():
with zest.mock(pretend_unit_under_test.foo) as m_foo:
pretend_unit_under_test.foo("arg1", arg2="arg2")
assert m_foo.called_once_with_kws(arg1="arg1", arg2="arg2")
def it_calls_the_task_success():
with zest.mock(Task1.success) as m_success:
_set_dirty(True, False, False)
_p()
assert m_success.called_once()
def it_exceptions():
with zest.mock(pretend_unit_under_test.foo) as m_foo:
m_foo.exceptions(ValueError)
with zest.raises(ValueError):
pretend_unit_under_test.foo()
