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import importlib
import os
import pytest
from pint import UnitRegistry
# Conditionally import NumPy, Dask, and Distributed
np = pytest.importorskip("numpy", reason="NumPy is not available")
dask = pytest.importorskip("dask", reason="Dask is not available")
distributed = pytest.importorskip("distributed", reason="Distributed is not available")
from dask.distributed import Client
from distributed.client import futures_of
from distributed.utils_test import ( # noqa: F401
cleanup,
cluster,
gen_cluster,
loop,
loop_in_thread,
)
loop = loop # flake8
units_ = "kilogram"
@pytest.fixture(scope="module")
def local_registry():
# Set up unit registry and sample
return UnitRegistry(force_ndarray_like=True)
def add_five(local_registry, q):
return q + 5 * local_registry(units_)
@pytest.fixture
def dask_array():
return dask.array.arange(0, 25, chunks=5, dtype=float).reshape((5, 5))
@pytest.fixture
def numpy_array():
return np.arange(0, 25, dtype=float).reshape((5, 5)) + 5
def test_is_dask_collection(local_registry, dask_array):
"""Test that a pint.Quantity wrapped Dask array is a Dask collection."""
q = local_registry.Quantity(dask_array, units_)
assert dask.is_dask_collection(q)
def test_is_not_dask_collection(local_registry, numpy_array):
"""Test that other pint.Quantity wrapped objects are not Dask collections."""
q = local_registry.Quantity(numpy_array, units_)
assert not dask.is_dask_collection(q)
def test_dask_scheduler(local_registry, dask_array):
"""Test that a pint.Quantity wrapped Dask array has the correct default scheduler."""
q = local_registry.Quantity(dask_array, units_)
scheduler = q.__dask_scheduler__
scheduler_name = f"{scheduler.__module__}.{scheduler.__name__}"
true_name = "dask.threaded.get"
assert scheduler == dask.array.Array.__dask_scheduler__
assert scheduler_name == true_name
@pytest.mark.parametrize(
"item",
(
pytest.param(1, id="int"),
pytest.param(1.3, id="float"),
pytest.param(np.array([1, 2]), id="numpy"),
pytest.param(
dask.array.arange(0, 25, chunks=5, dtype=float).reshape((5, 5)), id="dask"
),
),
)
def test_dask_tokenize(local_registry, item):
"""Test that a pint.Quantity wrapping something has a unique token."""
dask_token = dask.base.tokenize(item)
q = local_registry.Quantity(item, units_)
assert dask.base.tokenize(item) != dask.base.tokenize(q)
assert dask.base.tokenize(item) == dask_token
def test_dask_optimize(local_registry, dask_array):
"""Test that a pint.Quantity wrapped Dask array can be optimized."""
q = local_registry.Quantity(dask_array, units_)
assert q.__dask_optimize__ == dask.array.Array.__dask_optimize__
def test_compute(local_registry, dask_array, numpy_array):
"""Test the compute() method on a pint.Quantity wrapped Dask array."""
q = local_registry.Quantity(dask_array, units_)
comps = add_five(local_registry, q)
res = comps.compute()
assert np.all(res.m == numpy_array)
assert not dask.is_dask_collection(res)
assert res.units == units_
assert q.magnitude is dask_array
def test_persist(local_registry, dask_array, numpy_array):
"""Test the persist() method on a pint.Quantity wrapped Dask array."""
q = local_registry.Quantity(dask_array, units_)
comps = add_five(local_registry, q)
res = comps.persist()
assert np.all(res.m == numpy_array)
assert dask.is_dask_collection(res)
assert res.units == units_
assert q.magnitude is dask_array
@pytest.mark.skipif(
importlib.util.find_spec("graphviz") is None, reason="GraphViz is not available"
)
def test_visualize(local_registry, dask_array):
"""Test the visualize() method on a pint.Quantity wrapped Dask array."""
q = local_registry.Quantity(dask_array, units_)
comps = add_five(local_registry, q)
res = comps.visualize()
assert res is None
# These commands only work on Unix and Windows
assert os.path.exists("mydask.png")
os.remove("mydask.png")
def test_compute_persist_equivalent(local_registry, dask_array, numpy_array):
"""Test that compute() and persist() return the same numeric results."""
q = local_registry.Quantity(dask_array, units_)
comps = add_five(local_registry, q)
res_compute = comps.compute()
res_persist = comps.persist()
assert np.all(res_compute == res_persist)
assert res_compute.units == res_persist.units == units_
assert type(res_compute) == local_registry.Quantity
assert type(res_persist) == local_registry.Quantity
@pytest.mark.parametrize("method", ["compute", "persist", "visualize"])
def test_exception_method_not_implemented(local_registry, numpy_array, method):
"""Test exception handling for convenience methods on a pint.Quantity wrapped
object that is not a dask.array.Array object.
"""
q = local_registry.Quantity(numpy_array, units_)
exctruth = (
f"Method {method} only implemented for objects of"
" <class 'dask.array.core.Array'>, not"
" <class 'numpy.ndarray'>"
)
with pytest.raises(AttributeError, match=exctruth):
obj_method = getattr(q, method)
obj_method()
def test_distributed_compute(local_registry, loop, dask_array, numpy_array):
"""Test compute() for distributed machines."""
q = local_registry.Quantity(dask_array, units_)
with cluster() as (s, [a, b]):
with Client(s["address"], loop=loop):
comps = add_five(local_registry, q)
res = comps.compute()
assert np.all(res.m == numpy_array)
assert not dask.is_dask_collection(res)
assert res.units == units_
assert q.magnitude is dask_array
def test_distributed_persist(local_registry, loop, dask_array):
"""Test persist() for distributed machines."""
q = local_registry.Quantity(dask_array, units_)
with cluster() as (s, [a, b]):
with Client(s["address"], loop=loop):
comps = add_five(local_registry, q)
persisted_q = comps.persist()
comps_truth = dask_array + 5
persisted_truth = comps_truth.persist()
assert np.all(persisted_q.m == persisted_truth)
assert dask.is_dask_collection(persisted_q)
assert persisted_q.units == units_
assert q.magnitude is dask_array
@gen_cluster(client=True)
async def test_async(c, s, a, b):
"""Test asynchronous operations."""
# TODO: use a fixture for this.
local_registry = UnitRegistry(force_ndarray_like=True)
da = dask.array.arange(0, 25, chunks=5, dtype=float).reshape((5, 5))
q = local_registry.Quantity(da, units_)
x = q + local_registry.Quantity(5, units_)
y = x.persist()
assert str(y)
assert dask.is_dask_collection(y)
assert len(x.__dask_graph__()) > len(y.__dask_graph__())
assert not futures_of(x)
assert futures_of(y)
future = c.compute(y)
w = await future
assert not dask.is_dask_collection(w)
truth = np.arange(0, 25, dtype=float).reshape((5, 5)) + 5
assert np.all(truth == w.m)
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